  In light of the recent inference of a high optical depth to Thomson
scattering, tau, from the WMAP data we investigate the effects of extended
periods of partial ionization and ask if the value of tau inferred by assuming
a single sharp transition is an unbiased estimate. We construct and consider
several representative ionization models and evaluate their signatures in the
CMB. If tau is estimated with a single sharp transition we show that there can
be a significant bias in the derived value (and therefore a bias in sigma8 as
well). For WMAP noise levels the bias in tau is smaller than the statistical
uncertainty, but for Planck or a cosmic variance limited experiment the tau
bias could be much larger than the statistical uncertainties. This bias can be
reduced in the ionization models we consider by fitting a slightly more
complicated ionization history, such as a two-step ionization process. Assuming
this two-step process we find the Planck satellite can simultaneously determine
the initial redshift of reionization to +-2 and tau to +-0.01 Uncertainty about
the ionization history appears to provide a limit of about 0.005 on how well
tau can be estimated from CMB polarization data, much better than expected from
WMAP but significantly worse than expected from cosmic-variance limits.


  Proposals that quantum gravity gives rise to non-commutative spacetime
geometry and deformations of Poincare symmetry are examined in the context of
(2+1)-dimensional quantum gravity. The results are expressed in five lessons,
which summarise how the gravitational constant, Planck's constant and the
cosmological constant enter the non-commutative and non-cocommutative
structures arising in (2+1)-dimensional quantum gravity. It is emphasised that
the much studied bicrossproduct kappa-Poincare algebra does not arise directly
in (2+1)-dimensional quantum gravity.


  The present work focuses on the large eddy simulation (LES) and the study of
turbulent dilute methanol spray flames in vitiated coflow using the secondary
oxidizer Flamelet Generated Model (FGM). The modified FGM model uses an
additional secondary oxidizer parameter in addition to the three other
parameters previously used for spray flames progress variable, mixture
fraction, and enthalpy. The results for gas phase and droplet properties are
validated against the dilute methanol spray flame database for varying fuel
injection amounts. The droplet statistics and the lift-off flame heights are
accurately captured for all the cases. A proper orthogonal decomposition (POD)
of the scalar fluctuating hydroxyl radical (OH) field and velocity-temperature
field capture the flame structures in the downstream region of ignition
kernels. The detailed POD analysis reveals that the base frequency of the
dominant OH field equals that of the dominant vortical structure of 67.3 Hz.
The flame propagation happens around these dominant vortical structures because
of the less-strained fluid mixing.


  Thin films based on Layer-by-Layer (LbL) self assembled technique are useful
for immobilization of DNA onto solid support. This communication reports the
immobilization of DNA onto a solid support by electrostatic interaction with a
polycation Poly (allylamine hydrochloride) (PAH). UV-Vis absorption and steady
state fluorescence spectroscopic studies exhibit the characteristics of DNA
organized in LbL films. The most significant observation is that single strand
DNA are immobilized on the PAH backbone of LbL films when the films are
fabricated above the melting temperature of DNA. DNA immobilized in this way on
LbL films remains as such when the temperature is restored at room temperature
and the organization remains unaffected even after several days. UV-Vis
absorption spectroscopic studies confirm this finding.


  Three-dimensional gravity is a topological field theory, which can be
quantized as the Ponzano-Regge state-sum model built from the $\{3nj\}$-symbols
of the recoupling of the $\SU(2)$ representations, in which spins are
interpreted as quantized edge lengths in Planck units. It describes the flat
spacetime as gluing of three-dimensional cells with a fixed boundary metric
encoding length scale. In this paper, we revisit the Ponzano-Regge model
formulated in terms of spinors and rewrite the quantum geometry of 3D cells
with holomorphic recoupling symbols. These symbols, known as Schwinger's
generating function for the $\{6j\}$-symbols, are simply the squared inverse of
the partition function of the 2D Ising model living on the boundary of the 3D
cells. They can furthermore be interpreted, in their critical regime, as
scale-invariant basic elements of geometry. We show how to glue them together
into a discrete topological quantum field theory. This reformulation of the
path integral for 3D quantum gravity, with a rich pole structure of the
elementary building blocks, opens a new door toward the study of phase
transitions and continuum limits in 3D quantum gravity, and offers a new twist
on the construction of a duality between 3D quantum gravity and a 2d conformal
theory.


  We present collaborative similarity embedding (CSE), a unified framework that
exploits comprehensive collaborative relations available in a user-item
bipartite graph for representation learning and recommendation. In the proposed
framework, we differentiate two types of proximity relations: direct proximity
and k-th order neighborhood proximity. While learning from the former exploits
direct user-item associations observable from the graph, learning from the
latter makes use of implicit associations such as user-user similarities and
item-item similarities, which can provide valuable information especially when
the graph is sparse. Moreover, for improving scalability and flexibility, we
propose a sampling technique that is specifically designed to capture the two
types of proximity relations. Extensive experiments on eight benchmark datasets
show that CSE yields significantly better performance than state-of-the-art
recommendation methods.


  The relation between thermodynamic phase transitions in classical systems and
topology changes in their state space is discussed for systems in which
equivalence of statistical ensembles does not hold. As an example, the
spherical model with mean field-type interactions is considered. Exact results
for microcanonical and canonical quantities are compared with topological
properties of a certain family of submanifolds of the state space. Due to the
observed ensemble inequivalence, a close relation is expected to exist only
between the topological approach and one of the statistical ensembles. It is
found that the observed topology changes can be interpreted meaningfully when
compared to microcanonical quantities.


  Let $X$ be a smooth projective threefold of Picard number one for which the
generalized Bogomlov-Gieseker inequality holds. We characterize the limit
Bridgeland semistable objects at large volume in the vertical region of the
geometric stability conditions associated to $X$ in complete generality and
provide examples of asymptotically semistable objects. In the case of the
projective space and $ch^\beta(E)=(-R,0,D,0)$, we prove that there are only a
finite number of nested walls in the $(\alpha,s)$-plane. Moreover, when $R=0$
the only semistable objects in the outermost chamber are the 1-dimensional
Gieseker semistable sheaves, and when $\beta=0$ there are no semistable objects
in the innermost chamber. In both cases, the only limit semistable objects of
the form $E$ or $E[1]$ (where $E$ is a sheaf) that do not get destabilized
until the innermost wall are precisely the (shifts of) instanton sheaves.


  Using perturbative techniques, we investigate the existence and properties of
a new static solution for the Einstein equation with a negative cosmological
constant, which we call the deformed black hole. We derive a solution for a
static and axisymmetric perturbation of the Schwarzschild-anti-de Sitter black
hole that is regular in the range from the horizon to spacelike infinity. The
key result is that this perturbation simultaneously deforms the two boundary
surfaces--i.e., both the horizon and spacelike two-surface at infinity. Then we
discuss the Abbott-Deser mass and the Ashtekar-Magnon one for the deformed
black hole, and according to the Ashtekar-Magnon definition, we construct the
thermodynamic first law of the deformed black hole. The first law has a
correction term which can be interpreted as the work term that is necessary for
the deformation of the boundary surfaces. Because the work term is negative,
the horizon area of the deformed black hole becomes larger than that of the
Schwarzschild-anti-de Sitter black hole, if compared under the same mass,
indicating that the quasistatic deformation of the Schwarzschild-anti-de Sitter
black hole may be compatible with the thermodynamic second law (i.e., the area
theorem).


  A method enabling automatic detection and tracking of large amounts of
individual dust particles in plasmas is presented. Individual trajectories can
be found with a good spatiotemporal resolution, even without applying any
external light source to facilitate detection. Main advantages of this method
is a high portability and the possibility of making statistical analyses of the
trajectories of a large amount of non uniformly size distributed particles,
under challenging illumination conditions and with low time and computational
resources. In order to evaluate the efficiency of different detection and
tracking strategies statistically, an experimental benchmark is proposed, and
completed by numerical simulations.


  We consider the task of building compact deep learning pipelines suitable for
deployment on storage and power constrained mobile devices. We propose a
unified framework to learn a broad family of structured parameter matrices that
are characterized by the notion of low displacement rank. Our structured
transforms admit fast function and gradient evaluation, and span a rich range
of parameter sharing configurations whose statistical modeling capacity can be
explicitly tuned along a continuum from structured to unstructured.
Experimental results show that these transforms can significantly accelerate
inference and forward/backward passes during training, and offer superior
accuracy-compactness-speed tradeoffs in comparison to a number of existing
techniques. In keyword spotting applications in mobile speech recognition, our
methods are much more effective than standard linear low-rank bottleneck layers
and nearly retain the performance of state of the art models, while providing
more than 3.5-fold compression.


  Optimistic parallelization is a promising approach for the parallelization of
irregular algorithms: potentially interfering tasks are launched dynamically,
and the runtime system detects conflicts between concurrent activities,
aborting and rolling back conflicting tasks. However, parallelism in irregular
algorithms is very complex. In a regular algorithm like dense matrix
multiplication, the amount of parallelism can usually be expressed as a
function of the problem size, so it is reasonably straightforward to determine
how many processors should be allocated to execute a regular algorithm of a
certain size (this is called the processor allocation problem). In contrast,
parallelism in irregular algorithms can be a function of input parameters, and
the amount of parallelism can vary dramatically during the execution of the
irregular algorithm. Therefore, the processor allocation problem for irregular
algorithms is very difficult.
  In this paper, we describe the first systematic strategy for addressing this
problem. Our approach is based on a construct called the conflict graph, which
(i) provides insight into the amount of parallelism that can be extracted from
an irregular algorithm, and (ii) can be used to address the processor
allocation problem for irregular algorithms. We show that this problem is
related to a generalization of the unfriendly seating problem and, by extending
Tur\'an's theorem, we obtain a worst-case class of problems for optimistic
parallelization, which we use to derive a lower bound on the exploitable
parallelism. Finally, using some theoretically derived properties and some
experimental facts, we design a quick and stable control strategy for solving
the processor allocation problem heuristically.


  We consider the nonrelativistic four-boson system in two dimensions
interacting via a short-range attractive potential. For a weakly attractive
potential with one shallow two-body bound state with binding energy B_2, the
binding energies B_N of shallow N-body bound states are universal and thus do
not depend on the details of the interaction potential. We compute the
four-body binding energies in an effective quantum mechanics approach. There
are exactly two bound states: the ground state with B_4^(0)=197.3(1)B_2 and one
excited state with B_4^(1)=25.5(1)B_2. We compare our results to recent
predictions for N-body bound states with large N>>1.


  This paper offers a natural stochastic semantics of Networks of Priced Timed
Automata (NPTA) based on races between components. The semantics provides the
basis for satisfaction of probabilistic Weighted CTL properties (PWCTL),
conservatively extending the classical satisfaction of timed automata with
respect to TCTL. In particular the extension allows for hard real-time
properties of timed automata expressible in TCTL to be refined by performance
properties, e.g. in terms of probabilistic guarantees of time- and cost-bounded
properties. A second contribution of the paper is the application of
Statistical Model Checking (SMC) to efficiently estimate the correctness of
non-nested PWCTL model checking problems with a desired level of confidence,
based on a number of independent runs of the NPTA. In addition to applying
classical SMC algorithms, we also offer an extension that allows to efficiently
compare performance properties of NPTAs in a parametric setting. The third
contribution is an efficient tool implementation of our result and applications
to several case studies.


  We present the optical-near infrared spectral energy distributions (SED) and
near infrared variability properties of 30 low-redshift iron low-ionization
Broad Absorption Line quasars (FeLoBALQs) and matched samples of LoBALQs and
unabsorbed quasars. Significant correlations between the SED properties and
accretion rate indicators found among the unabsorbed comparison sample objects
suggest an intrinsic origin for SED differences. A range of reddening likely
mutes these correlations among the FeLoBAL quasars. The restframe optical-band
reddening is correlated with the location of the outflow, suggesting a link
between the outflows and the presence of dust. We analyzed WISE variability and
provide a correction for photometry uncertainties in an appendix. We found an
anticorrelation between the variability amplitude and inferred continuum
emission region size, and suggest that as the origin of the anticorrelation
between variability amplitude and luminosity typically observed in quasars. We
found that the LoBALQ optical emission line and other parameters are more
similar to those of the unabsorbed continuum sample objects than the FeLoBALQs.
Thus, FeLoBAL quasars are a special population of objects. We interpret the
results using an accretion-rate scenario for FeLoBAL quasars. The high
accretion rate FeLoBAL quasars are radiating powerfully enough to drive a
thick, high-velocity outflow. Quasars with intermediate accretion rates may
have an outflow, but it is not sufficiently thick to include FeII absorption.
Low accretion rate FeLoBAL outflows originate in absorption in a failing torus,
no longer optically thick enough to reprocess radiation into the near-IR.


  Even though most of its energy generation comes from renewable sources,
Brazil is one of the largest emitters of greenhouse gases in the world, due to
intense farming and deforestation of biomes such as the Amazon Rainforest,
whose preservation is essential for compliance with the Paris Agreement. Still,
regardless of lobbies or prevailing political orientation, all government legal
actions are published daily in the Brazilian Federal Official Gazette (BFOG, or
"Di\'ario Oficial da Uni\~ao" in Portuguese). However, with hundreds of decrees
issued every day by the authorities, it is absolutely burdensome to manually
analyze all these processes and find out which ones can pose serious
environmental hazards. In this paper, we present a strategy to compose
automated techniques and domain expert knowledge to process all the data from
the BFOG. We also provide the Government Actions Tracker, a highly curated
dataset, in Portuguese, annotated by domain experts, on federal government acts
about the Brazilian environmental policies. Finally, we build and compared four
different NLP models on the classfication task in this dataset. Our best model
achieved a F1-score of $0.714 \pm 0.031$. In the future, this system should
serve to scale up the high-quality tracking of all oficial documents with a
minimum of human supervision and contribute to increasing society's awareness
of government actions.


  We describe two new types of vacua for ten-dimensional string models without
supersymmetry, in which dilaton potentials are compensated by constant electric
or magnetic fields. These arise from $\alpha '$ corrections to the equations of
motion, and we comment on the reliability of this expansion. We identify
explicitly unstable singlet scalar perturbations in the orientifold vacua, and
we argue that in both cases additional instabilities are induced by non-abelian
couplings.


  Recently, several authors have suggested the use of first order methods, such
as fast dual ascent and the alternating direction method of multipliers, for
embedded model predictive control. The main reason is that they can be
implemented using simple arithmetic operations only. However, a known
limitation of gradient-based methods is that they are sensitive to
ill-conditioning of the problem data. In this paper, we present a fast dual
gradient method for which the sensitivity to ill-conditioning is greatly
reduced. This is achieved by approximating the negative dual function with a
quadratic upper bound with different curvature in different directions in the
algorithm, as opposed to having the same curvature in all directions as in
standard fast gradient methods. The main contribution of this paper is a
characterization of the set of matrices that can be used to form such a
quadratic upper bound to the negative dual function. We also describe how to
choose a matrix from this set to get an improved approximation of the dual
function, especially if it is ill-conditioned, compared to the approximation
used in standard fast dual gradient methods. This can give a significantly
improved performance as illustrated by a numerical evaluation on an
ill-conditioned AFTI-16 aircraft model.


  This paper addresses information-based sensing point selection from a set of
possible sensing locations, which determines a set of measurement points
maximizing the mutual information between the sensor measurements and the
variables of interest. A potential game approach has been applied to addressing
distributed implementation of decision making for cooperative sensor planning.
When a sensor network involves a large number of sensing agents, the local
utility function for a sensing agent is hard to compute, because the local
utility function depends on the other agents' decisions while each sensing
agent is inherently faced with limitations in both its communication and
computational capabilities. Accordingly, a local utility function for each
agent should be approximated to accommodate limitations in information
gathering and processing. We propose an approximation method for a local
utility function using only a portion of the decisions of other agents. The
part of the decisions that each agent considers is called the neighboring set
for the agent. The error induced by the approximation is also analyzed, and to
keep the error small we propose a neighbor selection algorithm that chooses the
neighbor set for each agent in a greedy way. The selection algorithm is based
on the correlation information between one agent's measurement selection and
the other agents' selections. Futhermore, we show that a game with an
approximate local utility function has an $\epsilon$-equilibrium and the set of
the equilibria include the Nash equilibrium of the original potential game. We
demonstrate the validity of our approximation method through two numerical
examples on simplified weather forecasting and multi-target tracking.


  We propose a general formulation of the renormalisation group as a family of
quantum channels which connect the microscopic physical world to the observable
world at some scale. By endowing the set of quantum states with an
operationally motivated information geometry, we induce the space of
Hamiltonians with a corresponding metric geometry. The resulting structure
allows one to quantify information loss along RG flows in terms of the
distinguishability of thermal states. In particular, we introduce a family of
functions, expressible in terms of two-point correlation functions, which are
non increasing along the flow. Among those, we study the speed of the flow, and
its generalization to infinite lattices.


  In this study, we develop a latent factor model for analysing
high-dimensional binary data. Specifically, a standard probit model is used to
describe the regression relationship between the observed binary data and the
continuous latent variables. Our method assumes that the dependency structure
of the observed binary data can be fully captured by the continuous latent
factors. To estimate the model, a moment-based estimation method is developed.
The proposed method is able to deal with both discontinuity and high
dimensionality. Most importantly, the asymptotic properties of the resulting
estimators are rigorously established. Extensive simulation studies are
presented to demonstrate the proposed methodology. A real dataset about product
descriptions is analysed for illustration.


  Let X be a compact 4-manifold with boundary. We study the space of
hyperk\"ahler triples on X, modulo diffeomorphisms which are the identity on
the boundary. We prove that this moduli space is a smooth infinite-dimensional
manifold and describe the tangent space in terms of triples of closed
anti-self-dual 2-forms. We also explore the corresponding boundary value
problem: a hyperk\"ahler triple restricts to a closed framing of the bundle of
2-forms on the boundary; we identify the infinitesimal deformations of this
closed framing that can be filled in to hyperk\"ahler deformations of the
original triple. Finally we study explicit examples coming from gravitational
instantons with isometric actions of SU(2).


  I apply the modified spherical infall model to test the dependence of the
shape of density profiles of dark matter halos on redshift. The model predicts
that the density profile of a halo of a given mass steepens with time and its
concentration parameter changes like c~1/(1+z_0)^2.


  We explore dynamical behaviour of dust particles that populate the surface of
inner optically thick protoplanetary discs. This is a disc region with the
hottest dust and of a great importance for planet formation and dust evolution,
but we still struggle to understand all the forces that shape this environment.
In our approach we combine results from two separate numerical studies - one is
the wind velocity and density distributions obtained from magnetohydrodynamical
simulations of accretion discs, and the other is a high-resolution multigrain
dust radiation transfer. In our previous paper in the series, we described the
methodology for utilising these results as an environmental input for the
integration of dust trajectories driven by gravity, gas drag, and radiation
pressure. Now we have two improvements - we incorporate time changes in the
wind density and velocity, and we implement the non-radial radiation pressure
force. We applied our analysis on Herbig Ae and T Tau stars. We confirm that
the radiation pressure force can lead to dust outflow, especially in the case
of more luminous stars. Additionally, it opposes dust accretion at the inner
disc edge and reduces dust settling. These effects are enhanced by the disc
wind, especially in the zone where the stellar and the disc magnetic fields
meet. Our results suggest that dust grains can stay in the hottest disc region
for an extended period and then can end up ejected into the outer disc regions.


  We develop a chiral symmetric relativistic mean field model with logarithmic
sigma potential derived in the strong coupling limit of the lattice QCD. We
find that both of the nuclear matter and finite nuclei are well described in
the present model. The normal vacuum is found to have global stability at zero
and finite baryon densities, and an equation of state with moderate stiffness
(K ~ 280 MeV) is obtained. The binding energies and charge radii of Z closed
even-even nuclei are well reproduced in a wide mass range from C to Pb
isotopes, except for the underestimates of binding energies in several jj
closed nuclei.


  The challenges of graph stream algorithms are twofold. First, each edge needs
to be processed only once, and second, it needs to work on highly constrained
memory. Diffusion degree is a measure of node centrality that can be calculated
(for all nodes) trivially for static graphs using a single Breadth-First Search
(BFS). However, keeping track of the Diffusion Degree in a graph stream is
nontrivial. The memory requirement for exact calculation is equivalent to
keeping the whole graph in memory. The present paper proposes an estimator (or
sketch) of diffusion degree for graph streams. We prove the correctness of the
proposed sketch and the upper bound of the estimated error. Given $\epsilon,
\delta \in (0,1)$, we achieve error below $\epsilon(b_u-a_u)d_u\lambda$ in node
$u$ with probability $1-\delta$ by utilizing
$O(n\frac1{\epsilon^2}\log{\frac1{\delta}})$ space, where $b_u$ and $a_u$ are
the maximum and minimum degrees of neighbors of $u$, $\lambda$ is diffusion
probability, and $d_u$ is the degree of node $u$. With the help of this sketch,
we propose an algorithm to extract the top-$k$ influencing nodes in the graph
stream. Comparative experiments show that the spread of top-$k$ nodes by the
proposed graph stream algorithm is equivalent to or better than the spread of
top-$k$ nodes extracted by the exact algorithm.


  The iterated learning model is an agent-based model of language evolution
notable for demonstrating the emergence of compositional language. In its
original form, it modelled language evolution along a single chain of
teacher-pupil interactions; here we modify the model to allow more complex
patterns of communication within a population and use the extended model to
quantify the effect of within-community and between-community communication
frequency on language development. We find that a small amount of
between-community communication can lead to population-wide language
convergence but that this global language amalgamation is more difficult to
achieve when communities are spatially embedded.


  We investigate how generic the onset of chaos in interacting many-body
classical systems is in the context of lattices of classical spins with nearest
neighbor anisotropic couplings. Seven large lattices in different spatial
dimensions were considered. For each lattice, more than 2000 largest Lyapunov
exponents for randomly sampled Hamiltonians were numerically computed. Our
results strongly suggest the absence of integrable nearest-neighbor
Hamiltonians for the infinite lattices except for the trivial Ising case. In
the vicinity of the Ising case, the largest Lyapunov exponents exhibit a
power-law growth, while further away they become rather weakly sensitive to the
Hamiltonian anisotropy. We also provide an analytical derivation of these
results.


  A simple pseudo-Hamiltonian formulation is proposed for the linear
inhomogeneous systems of ODEs. In contrast to the usual Hamiltonian mechanics,
our approach is based on the use of non-stationary Poisson brackets, i.e.
corresponding Poisson tensor is allowed to explicitly depend on time. Starting
from this pseudo-Hamiltonian formulation we develop a consistent deformation
quantization procedure involving a non-stationary star-product $*_t$ and an
``extended'' operator of time derivative $D_t=\partial_t+...$, differentiating
the $\ast_t$-product. As in the usual case, the $\ast_t$-algebra of physical
observables is shown to admit an essentially unique (time dependent) trace
functional $\mathrm{Tr}_t$. Using these ingredients we construct a complete and
fully consistent quantum-mechanical description for any linear dynamical system
with or without dissipation. The general quantization method is exemplified by
the models of damped oscillator and radiating point charge.


  Recent research has developed several Monte Carlo methods for estimating the
normalization constant (partition function) based on the idea of annealing.
This means sampling successively from a path of distributions that interpolate
between a tractable "proposal" distribution and the unnormalized "target"
distribution. Prominent estimators in this family include annealed importance
sampling and annealed noise-contrastive estimation (NCE). Such methods hinge on
a number of design choices: which estimator to use, which path of distributions
to use and whether to use a path at all; so far, there is no definitive theory
on which choices are efficient. Here, we evaluate each design choice by the
asymptotic estimation error it produces. First, we show that using NCE is more
efficient than the importance sampling estimator, but in the limit of
infinitesimal path steps, the difference vanishes. Second, we find that using
the geometric path brings down the estimation error from an exponential to a
polynomial function of the parameter distance between the target and proposal
distributions. Third, we find that the arithmetic path, while rarely used, can
offer optimality properties over the universally-used geometric path. In fact,
in a particular limit, the optimal path is arithmetic. Based on this theory, we
finally propose a two-step estimator to approximate the optimal path in an
efficient way.


  We investigate the coupling between Rydberg states of electrons trapped on a
liquid Helium surface and Landau levels induced by a perpendicular magnetic
field. We show that this realises a prototype quantum system equivalent to an
atom in a cavity, where their coupling strength can be tuned by a parallel
magnetic field. We determine experimentally the renormalisation of the atomic
transition energies induced by the coupling to the cavity, which can be seen as
an analogue of the Lamb shift. When the coupling is sufficiently strong the
transition between the ground and first excited Rydberg states splits into two
resonances corresponding to dressed states with vacuum and one photon in the
cavity. Our results are in quantitative agreement with the energy shifts
predicted by the effective atom in a cavity model where all parameters are
known with high accuracy.


  As the application of deep neural networks proliferates in numerous areas
such as medical imaging, video surveillance, and self driving cars, the need
for explaining the decisions of these models has become a hot research topic,
both at the global and local level. Locally, most explanation methods have
focused on identifying relevance of features, limiting the types of
explanations possible. In this paper, we investigate a new direction by
leveraging latent features to generate contrastive explanations; predictions
are explained not only by highlighting aspects that are in themselves
sufficient to justify the classification, but also by new aspects which if
added will change the classification. The key contribution of this paper lies
in how we add features to rich data in a formal yet humanly interpretable way
that leads to meaningful results. Our new definition of "addition" uses latent
features to move beyond the limitations of previous explanations and resolve an
open question laid out in Dhurandhar, et. al. (2018), which creates local
contrastive explanations but is limited to simple datasets such as grayscale
images. The strength of our approach in creating intuitive explanations that
are also quantitatively superior to other methods is demonstrated on three
diverse image datasets (skin lesions, faces, and fashion apparel). A user study
with 200 participants further exemplifies the benefits of contrastive
information, which can be viewed as complementary to other state-of-the-art
interpretability methods.


  We derive stringent upper bounds on all the $(\lambda''_{ijk} \mu_l)$-type
combinations from the consideration of proton stability, where
$\lambda''_{ijk}$ are baryon-number-violating trilinear couplings and $\mu_l$
are lepton-number-violating bilinear mass parameters in a R-parity-violating
supersymmetric theory.


  Synchronized brain rhythms, associated with diverse cognitive functions, have
been observed in electrical recordings of brain activity. Neural
synchronization may be well described by using the population-averaged global
potential $V_G$ in computational neuroscience. The time-averaged fluctuation of
$V_G$ plays the role of a "thermodynamic" order parameter $\cal {O}$ used for
describing the synchrony-asynchrony transition in neural systems. Population
spike synchronization may be well visualized in the raster plot of neural
spikes. The degree of neural synchronization seen in the raster plot is well
measured in terms of a "statistical-mechanical" spike-based measure $M_s$
introduced by considering the occupation and the pacing patterns of spikes. The
global potential $V_G$ is also used to give a reference global cycle for the
calculation of $M_s$. Hence, $V_G$ becomes an important collective quantity
because it is associated with calculation of both $\cal {O}$ and $M_s$.
However, it is practically difficult to directly get $V_G$ in real experiments.
To overcome this difficulty, instead of $V_G$, we employ the instantaneous
population spike rate (IPSR) which can be obtained in experiments, and develop
realistic thermodynamic and statistical-mechanical measures, based on IPSR, to
make practical characterization of the neural synchronization in both
computational and experimental neuroscience. Particularly, more accurate
characterization of weak sparse spike synchronization can be achieved in terms
of realistic statistical-mechanical IPSR-based measure, in comparison with the
conventional measure based on $V_G$.


  Multimedia security has been the aim point of considerable research activity
because of its wide application area. The major technology to achieve copyright
protection, content authentication, access control and multimedia security is
watermarking which is the process of embedding data into a multimedia element
such as image or audio, this embedded data can later be extracted from, or
detected in the embedded element for different purposes. In this work, a blind
watermarking algorithm based on SVD and circulant matrices has been presented.
Every circulant matrix is associated with a matrix for which the SVD
decomposition coincides with the spectral decomposition. This leads to improve
the Chandra algorithm [1], our presentation will include a discussion on the
data hiding capacity, watermark transparency and robustness against a wide
range of common image processing attacks.


  The recently developed method to investigate mesonic fluctuations off the
chiral soliton in the Nambu--Jona--Lasinio model is applied to kaons in the
S--wave channel. It is shown that for commonly accepted choices of parameters
the presence of the soliton and the lack of confinement in this model provide
an unphysical (valence) quark threshold which is lower than the kaon mass.
Choosing parameters such that this threshold is avoided a bound state is
obtained in the S--wave channel. After semiclassical quantization this state
acquires the quantum numbers of an odd parity $\Lambda$ and is predicted at
about 420MeV above the nucleon mass.


  The World Space Observatory for Ultraviolet (WSO-UV) is an orbital optical
telescope with a 1.7 m-diameter primary mirror currently under development. The
WSO-UV is aimed to operate in the 115-310 nm UV spectral range. Its two major
science instruments are UV spectrographs and a UV imaging field camera with
filter wheels. The WSO-UV project is currently in the implementation phase,
with a tentative launch date in 2023. Recently, two additional instruments
devoted to exoplanets have been proposed for WSO-UV, which are the focus of
this paper. UVSPEX, a UV-Spectrograph for Exoplanets, aims to determine atomic
hydrogen and oxygen abundance in the exospheres of terrestrial exoplanets. The
spectral range is 115-130 nm which enables simultaneous measurement of hydrogen
and oxygen emission intensities during an exoplanet transit. Study of exosphere
transit photometric curves can help differentiate among different types of
rocky planets. The exospheric temperature of an Earth-like planet is much
higher than that of a Venus-like planet, because of the low mixing ratio of the
dominant coolant (CO2) in the upper atmosphere of the former, which causes a
large difference in transit depth at the oxygen emission line. Thus, whether
the terrestrial exoplanet is Earth-like, Venus-like, or other can be
determined. SCEDI, a Stellar Coronagraph for Exoplanet Direct Imaging is aimed
to directly detect the starlight reflected from exoplanets orbiting their
parent stars or from the stellar vicinity including circumstellar discs, dust,
and clumps. SCEDI will create an achromatic (optimized to 420-700 nm wavelength
range), high-contrast stellocentric coronagraphic image of a circumstellar
vicinity. The two instruments: UVSPEX and SCEDI, share common power and control
modules. The present communication outlines the science goals of both proposed
instruments and explains some of their engineering features.


  It turned out that the partial sums $g_n(z) = \sum_{k=0}^n \frac{(a_1)_k ...
(a_p)_k}{(b_1)_k ... (b_q)_k} \frac{z^k}{k!}$, of the generalized
hypergeometric series ${}_p F_q(a_1,...,a_p; b_1,...,b_q;z)$, with parameters
$a_j,b_l\in\mathbb{C}\backslash\{ 0,-1,-2,... \}$, are Sobolev orthogonal
polynomials. The corresponding monic polynomials $G_n(z)$ are polynomials of
$R_I$ type, and therefore they are related to biorthogonal rational functions.
Polynomials $g_n$ possess a differential equation (in $z$), and a recurrence
relation (in $n$). We study integral representations for $g_n$, and some other
their basic properties. Partial sums of arbitrary power series with non-zero
coefficients are shown to be also related to biorthogonal rational functions.
We obtain a relation of polynomials $g_n(z)$ to Jacobi-type pencils and their
associated polynomials.


  Monitoring the administration of drugs and adverse drug reactions are key
parts of pharmacovigilance. In this paper, we explore the extraction of drug
mentions and drug-related information (reason for taking a drug, route,
frequency, dosage, strength, form, duration, and adverse events) from hospital
discharge summaries through deep learning that relies on various
representations for clinical named entity recognition. This work was officially
part of the 2018 n2c2 shared task, and we use the data supplied as part of the
task. We developed two deep learning architecture based on recurrent neural
networks and pre-trained language models. We also explore the effect of
augmenting word representations with semantic features for clinical named
entity recognition. Our feature-augmented BiLSTM-CRF model performed with
F1-score of 92.67% and ranked 4th for entity extraction sub-task among
submitted systems to n2c2 challenge. The recurrent neural networks that use the
pre-trained domain-specific word embeddings and a CRF layer for label
optimization perform drug, adverse event and related entities extraction with
micro-averaged F1-score of over 91%. The augmentation of word vectors with
semantic features extracted using available clinical NLP toolkits can further
improve the performance. Word embeddings that are pre-trained on a large
unannotated corpus of relevant documents and further fine-tuned to the task
perform rather well. However, the augmentation of word embeddings with semantic
features can help improve the performance (primarily by boosting precision) of
drug-related named entity recognition from electronic health records.


  Permutations over $F_{2^{2k}}$ with low differential uniform, high algebraic
degree and high nonlinearity are of great cryptographical importance since they
can be chosen as the substitution boxes (S-boxes) for many block ciphers. A
well known example is that the Advanced Encryption Standard (AES) chooses a
differentially 4-uniform permutation, the multiplicative inverse function, as
its S-box. In this paper, we present a new construction of differentially
4-uniformity permutations over even characteristic finite fields and obtain
many new CCZ-inequivalent functions. All the functions are switching neighbors
in the narrow sense of the multiplicative inverse function and have the optimal
algebraic degree and high nonlinearity.


  The quantum cohomology of Grassmannians exhibits two symmetries related to
the quantum product, namely a \Bbb {Z}/n action and an involution related to
complex conjugation. We construct a new ring by dividing out these symmetries
in an ideal theoretic way and analyze its structure, which is shown to control
the sum of all coefficients appearing in the product of cohomology classes. We
derive a combinatorial formula for the sum of all Littlewood-Richardson
coefficients appearing in the expansion of a product of two Schur polynomials.


  In this work we make use of DR14 APOGEE spectroscopic data to study a sample
of 92 known OB stars. We developed a near-infrared semi-empirical spectral
classification method that was successfully used in case of four new exemplars,
previously classified as later B-type stars. Our results agree well with those
determined independently from ECHELLE optical spectra, being in line with the
spectral types derived from the "canonical" MK blue optical system. This
confirms that the APOGEE spectrograph can also be used as a powerful tool in
surveys aiming to unveil and study large number of moderately and highly
obscured OB stars still hidden in the Galaxy.


  This paper studies the problem for an affine hypersurface system to reach a
polytopic target set starting from inside a polytope in the state space. We
present an exhaustive solution which begins with a characterization of states
which can reach the target by open-loop control and concludes with a systematic
procedure to synthesize a feedback control. Our emphasis is on methods of
subdivision, triangulation, and covers which explicitly account for the
capabilities of the control system. In contrast with previous literature, the
partition methods are guaranteed to yield a correct feedback synthesis,
assuming the problem is solvable by open-loop control.


  Research on the convergence of gaming and gambling has been around since the
1990s. The emergence of loot boxes in video games in the mid 2010s, a game
mechanic with a chance-based outcome that shares structural and psychological
similarities to gambling, caused public controversy and lead to the inception
of a new field of study, loot box research. Since then, various studies have
found a relationship between loot box engagement and problem gambling as well
as problem gaming. Due to the cross-sectional nature of this data, however,
inferences about causality are limited. While loot box research has extensively
investigated the relationship between loot box engagement and problem
behaviour, little research has been done to explain the underlying motivations
of players that drive them to interact with loot boxes. The goal of this thesis
is to provide possible explanations for the relationship between loot box
engagement and problem gamblers or problem gamers. In doing so, it draws upon
two prominent psychological theories. Self-Determination Theory and the
Dualistic Model of Passion. Self-Determination Theory's concept of
psychological needs and their satisfaction or frustration is hereby used to
explain the development of harmonious or obsessive passions, which are
introduced in the Dualistic Model of Passion. These obsessive passions have
been shown to be possible antecedents of behavioural addictions, such as
problem gambling or problem gaming. Thus, the interplay between needs, passions
and loot box opening could elucidate the aforementioned correlations between
loot box engagement and problem behaviour. However, further research,
especially utilising longitudinal data, is needed to better understand these
processes.


  We study transverse spin in a sub-wavelength metal-dielectric-metal (MDM)
sphere when the MDM sphere exhibits avoided crossing due to hybridization of
the surface plasmon with the Mie localized plasmon. We show that the change in
the absorptive and dipersive character near the crossing can have significant
effect on the transverse spin. An enhancement in the transverse spin is shown
to be possible associated with the transparency (suppression of extinction) of
the MDM sphere. The effect is attributed to the highly structured field
emerging as a consequence of competition of the electric and magnetic modes.


  We study a class of dynamical systems given by measure preserving actions of
the group $Z^d$ or $R^d$ and generating a set of spectral measures with an
extremal rate of the Fourier coefficient decay: $\Hat\sigma(n) =
O(|n|^{-1/2+\epsilon})$ for any $\epsilon > 0$. Singular measures with this
property are investigated in works due to Wiener and Wintner, Schaeffer, Salem,
Ivashev-Musatov, Zygmund et al. Thus, the discovered effect provides a new
construction of singular distributions of Schaeffer-Salem type on the torus
$T^d$ and in the space $R^d$.


  Quantum Chromodynamics (QCD) is the fundamental theory describing the strong
nuclear force and the interactions among quarks and gluons. Topological stars,
characterized by extreme density conditions, offer a unique environment where
QCD phenomena play a crucial role due to the confinement of fundamental
particles. Understanding these phenomena is essential for unraveling the
behavior and properties of these celestial bodies.
  In this study, we explore the implications of QCD within extreme density
regimes, focusing on its contribution to the energy-momentum tensor
($T^{\mu\nu}_{\text{QCD}}$) within the framework of Quantum Chromodynamics. Our
analysis sheds light on how these QCD effects influence the fabric of spacetime
in the vicinity of topological stars, providing valuable insights into their
underlying physics.


  Using large language models (LLMs) for educational applications like
dialogue-based teaching is a hot topic. Effective teaching, however, requires
teachers to adapt the difficulty of content and explanations to the education
level of their students. Even the best LLMs today struggle to do this well. If
we want to improve LLMs on this adaptation task, we need to be able to measure
adaptation success reliably. However, current Static metrics for text
difficulty, like the Flesch-Kincaid Reading Ease score, are known to be crude
and brittle. We, therefore, introduce and evaluate a new set of Prompt-based
metrics for text difficulty. Based on a user study, we create Prompt-based
metrics as inputs for LLMs. They leverage LLM's general language understanding
capabilities to capture more abstract and complex features than Static metrics.
Regression experiments show that adding our Prompt-based metrics significantly
improves text difficulty classification over Static metrics alone. Our results
demonstrate the promise of using LLMs to evaluate text adaptation to different
education levels.


  We elaborate on a recent study of a model of supersymmetry breaking we
proposed recently, in the presence of a tunable positive cosmological constant,
based on a gauged shift symmetry of a string modulus, external to the Standard
Model (SM) sector. Here, we identify this symmetry with a global symmetry of
the SM and work out the corresponding phenomenology. A particularly attracting
possibility is to use a combination of Baryon and Lepton number that contains
the known matter parity and guarantees absence of dimension-four and five
operators that violate B and L.


  Hyperfine splitting of positronium is an important parameter for particle
physics. This paper gives experimental techniques and results of R&D studies of
our experiment to observe direct hyperfine transition of ortho-positronium to
para-positronium.


  The energy evolution of a quantum chaotic system under the perturbation that
harmonically depends on time is studied for the case of large perturbation, in
which the rate of transition calculated from the Fermi golden rule (FGR) is
about or exceeds the frequency of perturbation. For this case the models of
Hamiltonian with random non-correlated matrix elements demonstrate that the
energy evolution retains its diffusive character, but the rate of diffusion
increases slower than the square of the magnitude of perturbation, thus
destroying the quantum-classical correspondence for the energy diffusion and
the energy absorption in the classical limit $\hbar \to 0$. The numerical
calculation carried out for a model built from the first principles (the
quantum analog of the Pullen - Edmonds oscillator) demonstrates that the
evolving energy distribution, apart from the diffusive component, contains a
ballistic one with the energy dispersion that is proportional to the square of
time. This component originates from the chains of matrix elements with
correlated signs and vanishes if the signs of matrix elements are randomized.
The presence of the ballistic component formally extends the applicability of
the FGR to the non-perturbative domain and restores the quantum-classical
correspondence.


  The relativistic six-quark equations are constructed in the framework of the
dispersion relation technique. The relativistic six-quark amplitudes of
dibaryons including the light $u$, $d$ and heavy $c$, $b$ quarks are
calculated. The approximate solutions of these equations using the method based
on the extraction of leading singularities of the heavy hexaquark amplitudes
are obtained. The poles of these amplitudes determine the masses of charmed and
bottom dibaryons with the isospins I=0, 1, 2 and the spin-parities $J^P=0^+$,
$1^+$, $2^+$.


  We present the first report on inverse chaos synchronization between
bi-directionally non-linearly and linearly coupled variable multiple time delay
Ikeda systems. The results are of certain importance in secure chaos-based
communication systems.


  In this paper we analyze states on C*-algebras and their relationship to
filter-like structures of projections and positive elements in the unit ball.
After developing the basic theory we use this to investigate the Kadison-Singer
conjecture, proving its equivalence to an apparently quite weak paving
conjecture and the existence of unique maximal centred extensions of
projections coming from ultrafilters on the natural numbers. We then prove that
Reid's positive answer to this for q-points in fact also holds for rapid
p-points, and that maximal centred filters are obtained in this case. We then
show that consistently such maximal centred filters do not exist at all meaning
that, for every pure state on the Calkin algebra, there exist projections p and
q on which the state is 1, even though it is bounded strictly below 1 for
projections below both p and q. Lastly we investigate towers, using cardinal
invariant equalities to construct towers on the natural numbers that do and do
not remain towers when canonically embedded into the Calkin algebra. Finally we
show that consistently all towers on the natural numbers remain towers under
this embedding.


  Quantum entanglement stands at the forefront of quantum information science,
heralding new paradigms in quantum communication, computation, and
cryptography. This paper introduces a quantum optimal control approach by
focusing on entanglement measures rather than targeting predefined maximally
entangled states. Leveraging the indirect Pontryagin Minimum Principle, we
formulate an optimal control problem centered on maximizing an enhanced lower
bound of the entanglement measure within a shortest timeframe in the presence
of input constraints. We derive optimality conditions based on Pontryagin's
Minimum Principle tailored for a matrix-valued dynamic control system and
tackle the resulting boundary value problem through a Physics-Informed Neural
Network, which is adept at handling differential matrix equations. The proposed
strategy not only refines the process of generating entangled states but also
introduces a method with increased sensitivity in detecting entangled states,
thereby overcoming the limitations of conventional concurrence estimation.


  Explainable artificial intelligence (XAI) is essential for enabling clinical
users to get informed decision support from AI and comply with evidence-based
medical practice. Applying XAI in clinical settings requires proper evaluation
criteria to ensure the explanation technique is both technically sound and
clinically useful, but specific support is lacking to achieve this goal. To
bridge the research gap, we propose the Clinical XAI Guidelines that consist of
five criteria a clinical XAI needs to be optimized for. The guidelines
recommend choosing an explanation form based on Guideline 1 (G1)
Understandability and G2 Clinical relevance. For the chosen explanation form,
its specific XAI technique should be optimized for G3 Truthfulness, G4
Informative plausibility, and G5 Computational efficiency. Following the
guidelines, we conducted a systematic evaluation on a novel problem of
multi-modal medical image explanation with two clinical tasks, and proposed new
evaluation metrics accordingly. Sixteen commonly-used heatmap XAI techniques
were evaluated and found to be insufficient for clinical use due to their
failure in G3 and G4. Our evaluation demonstrated the use of Clinical XAI
Guidelines to support the design and evaluation of clinically viable XAI.


  We present an analysis of the rare exclusive $B$ decays $B\to K\nu\bar\nu$
and $B\to K^{*}\nu\bar\nu$ within the Standard Model (SM), in a
model-independent manner, and in a number of new physics (NP) models. Combining
new form factor determinations from lattice QCD with light-cone sum rule
results and including complete two-loop electroweak corrections to the SM
Wilson coefficient, we obtain the SM predictions $\text{BR}(B^+\to
K^+\nu\bar\nu) = (4.0 \pm 0.5) \times 10^{-6}$ and $\text{BR}(B^0\to K^{*
0}\nu\bar\nu) = (9.2\pm1.0) \times 10^{-6}$, more precise and more robust than
previous estimates. Beyond the SM, we make use of an effective theory with
dimension-six operators invariant under the SM gauge symmetries to relate NP
effects in $b\to s\nu\bar\nu$ transitions to $b\to s\ell^+\ell^-$ transitions
and use the wealth of experimental data on $B\to K^{(*)}\ell^+\ell^-$ and
related modes to constrain NP effects in $B\to K^{(*)}\nu\bar\nu$. We then
consider several specific NP models, including $Z'$ models, the MSSM, models
with partial compositeness, and leptoquark models, demonstrating that the
correlations between $b\to s\nu\bar\nu$ observables among themselves and with
$B_s\to\mu^+\mu^-$ and $b\to s\ell^+\ell^-$ transitions offer powerful tests of
NP with new right-handed couplings and non-MFV interactions.


  In supersymmetric scenarios with a long-lived stau, the LHC experiments
provide us with a great environment for precise mass measurements of
superparticles. We study a case in which the mass differences between the
lightest stau and other sleptons are about 10 GeV or larger, so that the decay
products of heavier sleptons are hard enough to be detected. We demonstrate
that the masses of neutralinos, sleptons, and squarks can be measured with a
good accuracy.


  The ground state phase diagram is determined for the frustrated classical
Heisenberg chain with added nearest-neighbor biquadratic exchange interactions.
There appear ferromagnetic, incommensurate-spiral, and up-up-down-down phases;
a lock-in transition occurs at the spiral boundary. The model contains an
isotropic version of the ANNNI model; it is also closely related to a model
proposed for some manganites. The Luttinger-Tisza method is not obviously
useful due to the non-linear weak-constraint problem; however the ground state
is obtained analytically by the exact cluster method of Lyons and Kaplan. The
results are compared to the model of Thorpe and Blume, where the Heisenberg
part of the energy is not frustrated.


  We consider reduced Super Yang-Mills Theory in $d+1$ dimensions, where
$d=2,3,5,9$. We present commutators to prove that for $d=3,5$ and 9 a possible
ground state must be a $Spin(d)$ singlet. We also discuss the case $d=2$, where
we give an upper bound on the total angular momentum and show that for odd
dimensional gauge group no $Spin(d)$ invariant state exists in the Hilbert
space.


  We study the instantaneous and local energy injection in a turbulent shear
flow driven by volume forces. The energy injection can be both positive and
negative. Extremal events are related to coherent streaks. The probability
distribution is asymmetric, deviates slightly from a Gaussian shape and depends
on the position in shear direction. The probabilities for positive and negative
injection are exponentially related, but the prefactor in the exponent varies
across the shear layer.


  We investigate dwarf irregular(dIrr) galaxies as a new category of targets
for indirect Dark Matter(DM) searches with gamma-rays. In the framework of
point-like analysis, dwarf spheroidal(dSph) galaxies are usually considered as
one of the best category of targets for indirect DM searches. Nonetheless, as a
result of their uncertain kinematics, the DM content and astrophysical
J-factors of dSphs are usually affected by significant errors. In this paper,
we study a sample of 36 dIrrs as prospective targets of interest. In the
framework of the universal rotation curve, the kinematics of dIrr galaxies
provides a good estimation of their DM halo density distribution and,
consequently, of their astrophysical J-factors. We calculate the J-factors for
these 36 dIrr galaxies. We find a range of values comparable with the J-factors
of dSph galaxies. However, differently from dSphs an extra astrophysical
gamma-ray background component is expected in dIrrs, that is due to their
star-formation activity. In this paper, we show via a theoretical approach that
for galaxies in our sample the extra astrophysical background component is
negligible. Therefore, we conclude that dIrr galaxies can be potentially
considered as additional point-like targets for DM searches with gamma-rays. As
a first application of this study, we show the sensitivity limits of the
Fermi-LAT telescope to these objects and we calculate constraints on the DM
particle mass and annihilation cross-section. We conclude that the results of
the individual study of several dIrr galaxies are not yet competitive with
respect to the analysis of one of the most promising dSph galaxies, ie SEGUE1.
However, taking into account SEGUE1's symmetry-related uncertainties in the
J-factor calculation might alter this conclusion. Additionally, we calculate
constraints for the combined analysis of the 7 most promising dIrr galaxies of
our sample.


  A detailed study of the Hourglass Nebula in the M8 star forming region is
presented. The study is mainly based on recent subarcsec-resolution JHKs images
taken at Las Campanas Observatory and complemented with archival HST images and
longslit spectroscopy retrieved from the ESO Archive Facility. Using the new
numerical code CHORIZOS, we estimate the distance to the earliest stars in the
region to be 1.25 kpc. Infrared photometry of all the sources detected in the
field is given. From analysis of the JHKs colour-colour diagrams, we find that
an important fraction of these sources exhibit significant infrared excess.
These objects are candidates to be low- and intermediate-mass pre-main sequence
stars. Based on HST observations, the spatial distribution of gas, dust and
stars in the region is analyzed. The morphological analysis of these images
also reveals a rich variety of structures related to star formation (proplyds,
jets, bow shocks), similar to those observed in M16 and M42, along with the
detection of the first four Herbig-Haro objects in the region. Furthermore, a
longslit spectrum obtained with NTT confirms the identification of one of them
(HH 870) in the core of the Hourglass nebula, providing the first direct
evidence of active star formation by accretion in M8.


  Non-prehensile multi-object rearrangement is a robotic task of planning
feasible paths and transferring multiple objects to their predefined target
poses without grasping. It needs to consider how each object reaches the target
and the order of object movement, which significantly deepens the complexity of
the problem. To address these challenges, we propose a hierarchical policy to
divide and conquer for non-prehensile multi-object rearrangement. In the
high-level policy, guided by a designed policy network, the Monte Carlo Tree
Search efficiently searches for the optimal rearrangement sequence among
multiple objects, which benefits from imitation and reinforcement. In the
low-level policy, the robot plans the paths according to the order of path
primitives and manipulates the objects to approach the goal poses one by one.
We verify through experiments that the proposed method can achieve a higher
success rate, fewer steps, and shorter path length compared with the
state-of-the-art.


  If the fundamental Planck scale is near a TeV, then parton collisions with
high enough center-of-mass energy should produce black holes. The production
rate for such black holes has been extensively studied for the case of a
proton-proton collision at \sqrt s = 14 TeV and for a lead-lead collision at
\sqrt s = 5.5 TeV at LHC. As the parton energy density is much higher at
lead-lead collisions than in pp collisions at LHC, one natural question is
whether the produced black holes will be able to absorb the partons formed in
the lead-lead collisions and eventually `eat' the quark-gluon plasma formed at
LHC. In this paper, we make a quantitative analysis of this possibility and
find that since the energy density of partons formed in lead-lead collisions at
LHC is about 500 GeV/fm^3, the rate of absorption for one of these black holes
is much smaller than the rate of evaporation. Hence, we argue that black holes
formed in such collisions will decay very quickly, and will not absorb very
many nearby partons. More precisely, we show that for the black hole mass to
increase via parton absorption at the LHC the typical energy density of quarks
and gluons should be of the order of 10^{10} GeV/fm^3. As LHC will not be able
to produce such a high energy density partonic system, the black hole will not
be able to absorb a sufficient number of nearby partons before it decays. The
typical life time of the black hole formed at LHC is found to be a small
fraction of a fm/c.


  Despite the long history of studying instant messaging usage, we know very
little about how today's people participate in group chat channels and interact
with others inside a real-world organization. In this short paper, we aim to
update the existing knowledge on how group chat is used in the context of
today's organizations. The knowledge is particularly important for the new norm
of remote works under the COVID-19 pandemic. We have the privilege of
collecting two valuable datasets: a total of 4,300 group chat channels in Slack
from an R&D department in a multinational IT company; and a total of 117
groups' performance data. Through qualitative coding of 100 randomly sampled
group channels from the 4,300 channels dataset, we identified and reported 9
categories such as Project channels, IT-Support channels, and Event channels.
We further defined a feature metric with 21 meta features (and their derived
features) without looking at the message content to depict the group
communication style for these group chat channels, with which we successfully
trained a machine learning model that can automatically classify a given group
channel into one of the 9 categories. In addition to the descriptive data
analysis, we illustrated how these communication metrics can be used to analyze
team performance. We cross-referenced 117 project teams and their team-based
Slack channels and identified 57 teams that appeared in both datasets, then we
built a regression model to reveal the relationship between these group
communication styles and the project team performance. This work contributes an
updated empirical understanding of human-human communication practices within
the enterprise setting, and suggests design opportunities for the future of
human-AI communication experience.


  Photoionized nebulae comprise basically HII regions and planetary nebulae,
and their abundances give important clues on the nucleosynthesis and chemical
evolution of their host galaxies. There is presently a large amount of data on
these objects, especially for the elements He and N, which are strongly
affected by the evolution of intermediate mass stars, as well as O, Ne, S, and
Ar, which are essentially synthesized in stars with larger masses. The
abundances of these elements in several systems in the Local Group are
discussed on the basis of distance-independent correlations.


  Current state-of-the-art object detectors can have significant performance
drop when deployed in the wild due to domain gaps with training data.
Unsupervised Domain Adaptation (UDA) is a promising approach to adapt models
for new domains/environments without any expensive label cost. However, without
ground truth labels, most prior works on UDA for object detection tasks can
only perform coarse image-level and/or feature-level adaptation by using
adversarial learning methods. In this work, we show that such adversarial-based
methods can only reduce the domain style gap, but cannot address the domain
content distribution gap that is shown to be important for object detectors. To
overcome this limitation, we propose the Cross-Domain Semi-Supervised Learning
(CDSSL) framework by leveraging high-quality pseudo labels to learn better
representations from the target domain directly. To enable SSL for cross-domain
object detection, we propose fine-grained domain transfer,
progressive-confidence-based label sharpening and imbalanced sampling strategy
to address two challenges: (i) non-identical distribution between source and
target domain data, (ii) error amplification/accumulation due to noisy pseudo
labeling on the target domain. Experiment results show that our proposed
approach consistently achieves new state-of-the-art performance (2.2% - 9.5%
better than prior best work on mAP) under various domain gap scenarios. The
code will be released.


  The warped bulk standard model has been studied in the Randall-Sundrum
background on $S^1/\Z\times\Z'$ interval with the bulk gauge symmetry
$SU(3)\times SU(2)_L\times SU(2)_R\times U(1)_{B-L}$. With the assumption of no
large cancellation between the fermion flavor mixing matrices, we present a
simple analytic method to determine the bulk masses of standard model fermions
in the almost universal bulk Yukawa coupling model. We also predict $U_{e3}$
element of MNS matrix to be near the experimental upper bound when the neutrino
masses are of Dirac type.


  Advanced computer vision technology can provide near real-time home
monitoring to support "aging in place" by detecting falls and symptoms related
to seizures and stroke. Affordable webcams, together with cloud computing
services (to run machine learning algorithms), can potentially bring
significant social benefits. However, it has not been deployed in practice
because of privacy concerns. In this paper, we propose a strategy that uses
homomorphic encryption to resolve this dilemma, which guarantees information
confidentiality while retaining action detection. Our protocol for secure
inference can distinguish falls from activities of daily living with 86.21%
sensitivity and 99.14% specificity, with an average inference latency of 1.2
seconds and 2.4 seconds on real-world test datasets using small and large
neural nets, respectively. We show that our method enables a 613x speedup over
the latency-optimized LoLa and achieves an average of 3.1x throughput increase
in secure inference compared to the throughput-optimized nGraph-HE2.


  We investigate the caustic topologies for binary gravitational lenses made up
of two objects whose gravitational potential declines as $1/r^n$. With $n<1$
this corresponds to power-law dust distributions like the singular isothermal
sphere. The $n>1$ regime can be obtained with some violations of the energy
conditions, one famous example being the Ellis wormhole. Gravitational lensing
provides a natural arena to distinguish and identify such exotic objects in our
Universe. We find that there are still three topologies for caustics as in the
standard Schwarzschild binary lens, with the main novelty coming from the
secondary caustics of the close topology, which become huge at higher $n$.
After drawing caustics by numerical methods, we derive a large amount of
analytical formulae in all limits that are useful to provide deeper insight in
the mathematics of the problem. Our study is useful to better understand the
phenomenology of galaxy lensing in clusters as well as the distinct signatures
of exotic matter in complex systems.


  The basic models of helix-coil transitions in biomolecules are introduced.
These include phenomenological, zipper (Bragg-Zimm) models of polypeptides,
loop-entropy (Poland-Scheraga) and Hamiltonian (Peyrard-Bishop) models of
homogeneous DNA denaturation. The transfer integral approach to one-dimensional
thermodynamics is presented in some detail, including the necessary extensions
to deal with the singular integral equations arising in the case of on-site
potentials with a flat top. The (non-)applicability of the theorems which
prohibit phase transitions in one-dimensional systems is discussed.


  We examine the structure of compact metal nanoparticles (NPs) forming
polyhedral sections of face centered (fcc) and body centered (bcc) cubic
lattices, which are confined by facets characterized by highly dense {100},
{110}, and {111} monolayers. Together with the constraint that the NPs exhibit
the same point symmetry as the ideal cubic lattice, i.e. Oh, different types of
generic NPs serve for the definition of general compact polyhedral cubic NPs.
Their structural properties, such as shape, size, and surface facets, can be
described by only three integer valued polyhedral NP parameters N, M, K.
Corresponding analytical details are discussed with visualization of
characteristic examples. While the overall NP shapes are quite similar between
the different cubic lattice types, structural fine details differ. In
particular, monolayer planes of adjacent NP facets can join at corners and
edges which are not occupied by atoms of the ideal lattice. This gives rise to
microfacets and narrow facet strips depending on the lattice type. The
discussion illustrates the complexity of seemingly simple nanoparticles in a
quantitative account. The geometric relationships of the model particles can
also be used to classify shapes and estimate sizes of real compact metal
nanoparticles observed by experiment.


  We discuss the problem of observing spontaneous parity and CP violation in
collision systems. We discuss and propose observables which may be used in
heavy-ion collisions to observe such violations, as well as event-by-event
methods to analyze the data. Finally, we discuss simple monte-carlo models of
these CP violating effects which we have used to develop our techniques and
from which we derive rough estimates of sensitivities to signals which may be
seen at RHIC.


  We consider those simply connected isothermic surfaces for which their Hopf
differential factorizes into a real function and a meromorphic quadratic
differential that has a zero or pole at some point, but is nowhere zero and
holomorphic otherwise. Upon restriction to a simply connected patch that does
not contain the zero or pole, the Darboux and Calapso transformations yield new
isothermic surfaces. We determine the limiting behaviour of these transformed
patches as the zero or pole of the meromorphic quadratic differential is
approached and investigate whether they are continuous around that point.


  We report the 888 MHz radio detection in the Rapid ASKAP Continuum Survey
(RACS) of VIK J2318$-$3113, a $z$=6.44 quasar. Its radio luminosity (1.2
$\times 10^{26}$ W Hz$^{-1}$ at 5 GHz) compared to the optical luminosity (1.8
$\times 10^{24}$ W Hz$^{-1}$ at 4400 A) makes it the most distant radio-loud
quasar observed so far, with a radio loudness R$\sim$70
(R$=L_\mathrm{{5GHz}}/L_\mathrm{{4400A}}$). Moreover, the high bolometric
luminosity of the source (L$_\mathrm{{bol}}$=7.4 $\times 10^{46}$ erg s$^{-1}$)
suggests the presence of a supermassive black hole with a high mass ($\gtrsim$6
$\times$10$^8$ M$_\odot$) at a time when the Universe was younger than a
billion years. Combining the new radio data from RACS with previous ASKAP
observations at the same frequency, we found that the flux density of the
source may have varied by a factor of $\sim$2, which could suggest the presence
of a relativistic jet oriented towards the line of sight, that is, a blazar
nature. However, currently available radio data do not allow us to firmly
characterise the orientation of the source. Further radio and X-ray
observations are needed.


  Exploiting analogies between the precessing quantum spin system and the
charge-monopole system, we construct Bloch hyper-spheres with $\it{exact}$
spherical symmetries in arbitrary dimensions. Such Bloch hyper-spheres are
realized as a collection of the orbits of a precessing quantum spin. The
geometry of Bloch hyper-spheres is exactly equal to the quantum Nambu geometry
of higher dimensional fuzzy spheres. The stabilizer group symmetry of the Bloch
hyper-sphere necessarily introduces degenerate spin-coherent states, giving
rise to the Wilczek-Zee geometric phase of non-Abelian monopoles associated
with the hyper-sphere holonomy. The degenerate spin-coherent states induce
matrix-valued quantum geometric tensors. While the minimal spin Bloch
hyper-spheres exhibit similar properties in even and odd dimensions, their
large spin counterparts differ qualitatively depending on the parity of the
dimensions. Exact correspondences between spin-coherent states and monopole
harmonics in higher dimensions are established. We also investigate density
matrices described by Bloch hyper-balls and elucidate their corresponding
statistical and geometric properties, such as von Neumann entropies and Bures
quantum metrics.


  I prove a crystalline characterization of abelian varieties in characteristic
$p>0$ amongst the class of varieties with trivial tangent bundle. I show using
my characterization that a smooth, projective, ordinary variety with trivial
tangent bundle is an abelian variety if and only if its second crystalline
cohomology is torsion free. I also show that a conjecture of Ke-Zheng Li about
characteristic $p>0$ varieties with trivial tangent bundles is true for
surfaces. I give a new proof of a result of Li and prove a refinement of it.
Based on my characterization of abelian varieties I propose modifications of
Li's conjecture which I expect to be true.


  We use a suite of high-resolution $N$-body simulations and state-of-the-art
perturbation theory to improve the code halofit, which predicts the nonlinear
matter power spectrum. We restrict attention to parameters in the vicinity of
the Planck Collaboration's best fit. On large-scales ($k\lesssim 0.07 h/{\rm
Mpc}$), our model evaluates the 2-loop calculation from the Multi-point
Propagator Theory of Bernardeau et al.(2012). On smaller scales ($k \gtrsim 0.7
h/{\rm Mpc}$), we transition to a smoothing-spline-fit model, that
characterises the differences between the Takahashi et al. (2012) recalibration
of halofit2012 and our simulations. We use an additional suite of simulations
to explore the response of the power spectrum to variations in the cosmological
parameters. In particular, we examine: the time evolution of the dark energy
equation of state ($w_0$, $w_a$); the matter density $\Omega_m$; the physical
densities of CDM and baryons $(\omega_c,\omega_b)$; and the primordial power
spectrum amplitude $A_s$, spectral index $n_s$, and its running $\alpha$. We
construct correction functions, which improve halofit's dependence on
cosmological parameters. Our newly calibrated model reproduces all of our data
with $\lesssim1\%$ precision. Including various systematic errors, such as
choice of $N$-body code, resolution, and through inspection of the scaled
second order derivatives, we estimate the accuracy to be $\lesssim3\%$ over the
hyper-cube: $w_0\in\{-1.05,-0.95\}$, $w_a\in\{-0.4,0.4\}$, $\Omega_{\rm
m,0}\in\{0.21,0.4\}$, $\omega_{\rm c}\in\{0.1,0.13\}$, $\omega_{\rm
b}\in\{2.0,2.4\}$, $n_{\rm s}\in\{0.85,1.05\}$, $A_s\in\{1.72\times
10^{-9},2.58\times 10^{-9}\}$, $\alpha\in\{-0.2,0.2\}$ up to $k=9.0 h/{\rm
Mpc}$ and out to $z=3$. Outside of this range the model reverts to halofit2012.


  The impressive multimodal capabilities demonstrated by OpenAI's GPT-4 have
generated significant interest in the development of Multimodal Large Language
Models (MLLMs). Visual instruction tuning of MLLMs with machine-generated
instruction-following data has shown to enhance zero-shot capabilities across
various tasks. However, there has been limited exploration into controlling the
quality of the instruction data.Current methodologies for data selection in
MLLMs often rely on single, unreliable scores or use downstream tasks for
selection, which is time-consuming and can lead to potential overfitting on the
chosen evaluation datasets. To mitigate these limitations, we propose a novel
data selection methodology that utilizes image-text correlation and model
perplexity to evaluate and select data of varying quality. This approach
leverages the distinct distribution of these two attributes, mapping data
quality into a two-dimensional space that allows for the selection of data
based on their location within this distribution. By utilizing this space, we
can analyze the impact of task type settings, used as prompts, on data quality.
Additionally, this space can be used to construct multi-stage subsets of
varying quality to facilitate curriculum learning. Our research includes
comprehensive experiments conducted on various datasets. The results emphasize
substantial enhancements in five commonly assessed capabilities compared to
using the complete dataset. Our codes, data, and models are publicly available
at: \url{https://anonymous.4open.science/r/EHIT-31B4}


  Homological smoothness and twisted Calabi-Yau property of generalized Weyl
algebras over polynomial algebras in two variables is studied. A necessary and
sufficient condition to be homologically smooth is given. The Nakayama
automorphisms of such algebras are also computed in terms of the Jacobian
determinants of defining automorphisms.


  We examine noncommutative Chern-Simons theory on a bounded spatial domain. We
argue that upon `turning on' the noncommutativity, the edge observables, which
characterized the commutative theory, move into the bulk. We show this to
lowest order in the noncommutativity parameter appearing in the Moyal star
product.
  If one includes all orders, the Hamiltonian formulation of the gauge theory
ceases to exist, indicating that the Moyal star product must be modified in the
presence of a boundary. Alternative descriptions are matrix models. We examine
one such model, obtained by a simple truncation of Chern-Simons theory on the
noncommutative plane, and express its observables in terms of Wilson lines.


  The purpose of this study is to test the effectiveness of current straggler
mitigation techniques over different important iterative convergent machine
learning(ML) algorithm including Matrix Factorization (MF), Multinomial
Logistic Regression (MLR), and Latent Dirichlet Allocation (LDA) . The
experiment was conducted to implemented using the FlexPS system, which is the
latest system implementation that employ parameter server architecture. The
experiment employed the Bulk Synchronous Parallel (BSP) computational model to
examine the straggler problem in Parameter Server on Iterative Convergent
Distributed Machine Learning. Moreover, the current research analyzes the
experimental arrangement of the parameter server strategy concerning the
parallel learning problems by injecting universal straggler patterns and
executing latest mitigation techniques. The findings of the study are
significant in that as they will provide the necessary platform for conducting
further research into the problem and allow the researcher to compare different
methods for various applications. The outcome is therefore expected to
facilitate the development of new techniques coupled with new perspectives in
addressing this problem.


  It has been recently shown that, under some general conditions, it is always
possible to find a fourth order gravity theory capable of reproducing the same
dynamics of a given dark energy model. Here, we discuss this approach for a
dark energy model with a scalar field evolving under the action of an
exponential potential. In absence of matter, such a potential can be recovered
from a fourth order theory via a conformal transformation. Including the matter
term, the function f(R) entering the generalized gravity Lagrangian can be
reconstructed according to the dark energy model.


  We propose that spin-fluctuation-mediated spin-triplet superconductivity may
be realized in repulsive Hubbard models with disconnected Fermi surfaces. The
idea is confirmed for Hubbard models on triangular (dilute band filling) and
honeycomb (near half-filling) lattices using fluctuation exchange
approximation, where triplet pairing order parameter with f-wave symmetry is
obtained. Possible relevance to real superconductors is suggested.


  Recent lunar crater studies have revealed an asymmetric distribution of rayed
craters on the lunar surface. The asymmetry is related to the synchronous
rotation of the Moon: there is a higher density of rayed craters on the leading
hemisphere compared with the trailing hemisphere. Rayed craters represent
generally the youngest impacts. The purpose of this paper is to test the
hypotheses that (i) the population of Near-Earth asteroids (NEAs) is the source
of the impactors that have made the rayed craters, and (ii) that impacts by
this projectile population account quantitatively for the observed asymmetry.
We carried out numerical simulations of the orbital evolution of a large number
of test particles representing NEAs in order to determine directly their impact
flux on the Moon. The simulations were done in two stages. In the first stage
we obtained encounter statistics of NEAs on the Earth's activity sphere. In the
second stage we calculated the direct impact flux of the encountering particles
on the surface of the Moon; the latter calculations were confined within the
activity sphere of the Earth. A steady-state synthetic population of NEAs was
generated from a debiased orbital distribution of the known NEAs. We find that
the near-Earth asteroids do have an asymmetry in their impact flux on the Moon:
apex-to-antapex ratio of 1.32 +/- 0.01. However, the observed rayed crater
distribution's asymmetry is significantly more pronounced: apex-to-antapex
ratio of 1.65 +/- 0.16. Our results suggest the existence of an undetected
population of slower (low impact velocity) projectiles, such as a population of
objects nearly coorbiting with Earth; more observational study of young lunar
craters is needed to secure this conclusion.


  We present deep MUSE observations of five quasars within the first Gyr of the
Universe ($z\gtrsim6$), four of which display extended Ly$\alpha$ halos. After
PSF-subtraction, we reveal halos surrounding two quasars for the first time, as
well as confirming the presence of two more halos for which tentative
detections exist in long-slit spectroscopic observations and narrow-band
imaging. The four Ly$\alpha$ halos presented here are diverse in morphology and
size, they each display spatial asymmetry, and none are centred on the position
of the quasar. Spectra of the diffuse halos demonstrate that none are
dramatically offset in velocity from the systemic redshift of the quasars
($\Delta$ v $< 200$ kms$^{-1}$), however each halo shows a broad Ly$\alpha$
line, with a velocity width of order $\sim1000$ kms$^{-1}$. Total Ly$\alpha$
luminosities range between $\sim$ $2 \times 10^{43}$ erg s$^{-1}$ and $\sim$ $2
\times 10^{44}$ erg s$^{-1}$, reaching maximum radial extents of $13 - 30$ pkpc
from the quasar positions. We find larger sizes and higher Ly$\alpha$
luminosities than previous literature results at this redshift, but find no
correlation between the quasar properties and the Ly$\alpha$ halo, suggesting
that the detected emission is most closely related to the physical properties
of the circum-galactic medium


  This paper analyzes stochastic networks consisting of finite capacity nodes
with different classes of requests which move according to some routing policy.
The Markov processes describing these networks do not, in general, have
reversibility properties, so the explicit expression of their invariant
distribution is not known. Kelly's limiting regime is considered: the arrival
rates of calls as well as the capacities of the nodes are proportional to a
factor going to infinity. It is proved that, in limit, the associated rescaled
Markov process converges to a deterministic dynamical system with a unique
equilibrium point characterized by a nonstandard fixed point equation.


  The recent advances in representation learning inspire us to take on the
challenging problem of unsupervised image classification tasks in a principled
way. We propose ContraCluster, an unsupervised image classification method that
combines clustering with the power of contrastive self-supervised learning.
ContraCluster consists of three stages: (1) contrastive self-supervised
pre-training (CPT), (2) contrastive prototype sampling (CPS), and (3)
prototype-based semi-supervised fine-tuning (PB-SFT). CPS can select highly
accurate, categorically prototypical images in an embedding space learned by
contrastive learning. We use sampled prototypes as noisy labeled data to
perform semi-supervised fine-tuning (PB-SFT), leveraging small prototypes and
large unlabeled data to further enhance the accuracy. We demonstrate
empirically that ContraCluster achieves new state-of-the-art results for
standard benchmark datasets including CIFAR-10, STL-10, and ImageNet-10. For
example, ContraCluster achieves about 90.8% accuracy for CIFAR-10, which
outperforms DAC (52.2%), IIC (61.7%), and SCAN (87.6%) by a large margin.
Without any labels, ContraCluster can achieve a 90.8% accuracy that is
comparable to 95.8% by the best supervised counterpart.


  A de Sitter black hole or a black hole spacetime endowed with a positive
cosmological constant has two Killing horizons -- a black hole and a
cosmological event horizon surrounding it. It is natural to expect that the
total Bekenstein-Hawking entropy of such spacetimes should be the sum of the
two horizons' areas. In this work we apply the recently developed formalism
using the Gibbons-Hawking-York boundary term and the near horizon symmetries to
derive the total entropy of such two horizon spacetimes. We construct a
suitable general geometric set up for general stationary axisymmetric
spacetimes with two or more than two commuting Killing vector fields in an
arbitrary spacetime dimensions. This framework helps us to deal with both the
horizons in an equal footing. We show that in order to obtain the total entropy
of such spacetimes, the near horizon mode functions for the diffeomorphism
generating vector fields have to be restricted in a certain manner, compared to
the single horizon spacetimes. We next discuss specific known exact solutions
belonging to the Kerr-Newman- or the Plebanski-Demianski-de Sitter families to
show that they fall into the category of our general framework. We end with a
sketch of further possible extensions of this work.


  Magnons in antiferromagnetic insulators couple strongly to conduction
electrons in adjacent metals. We show that this interfacial tie can lead to
superconductivity in a tri-layer consisting of a metal sandwiched between two
antiferromagnetic insulators. The critical temperature is closely related to
the magnon gap, which can be in the THz range. We estimate the critical
temperature in MnF$_2$-Au-MnF$_2$ to be on the order of 1 K. The Umklapp
scattering at metal-antiferromagnet interfaces leads to a d-wave
superconductive pairing, in contrast to the p-wave superconductivity mediated
by magnons in ferromagnets.


  We investigate in detail the white dwarf cooling sequence of the globular
cluster Messier 4. In particular we study the influence of various systematic
uncertainties, both observational and theoretical, on the determination of the
cluster age from the white dwarf cooling sequence. These include uncertainties
in the distance to the cluster and the extinction along the line of sight, as
well as the white dwarf mass, envelope and core compositions and the white
dwarf --main sequence mass relation. We find that fitting to the full
two-dimensional colour-magnitude diagram offers a more robust method for age
determination than the traditional method of fitting the one-dimensional white
dwarf luminosity function.
  After taking into account the various uncertainties, we find a best fit age
of 12.1 Gyr, with a 95% lower limit of 10.3 Gyr. We also perform fits using two
other sets of cooling models from the literature. The models of Chabrier et al
(2000) yield an encouragingly similar result, although the models of Salaris et
al (2000) do not provide as good a fit. Our results support our previous
determination of a delay between the formation of the Galactic halo and the
onset of star formation in the Galactic disk.


  An important family of span programs, st-connectivity span programs, have
been used to design quantum algorithms in various contexts, including a number
of graph problems and formula evaluation problems. The complexity of the
resulting algorithms depends on the largest positive witness size of any
1-input, and the largest negative witness size of any 0-input. Belovs and
Reichardt first showed that the positive witness size is exactly characterized
by the effective resistance of the input graph, but only rough upper bounds
were known previously on the negative witness size. We show that the negative
witness size in an st-connectivity span program is exactly characterized by the
capacitance of the input graph. This gives a tight analysis for algorithms
based on st-connectivity span programs on any set of inputs.
  We use this analysis to give a new quantum algorithm for estimating the
capacitance of a graph. We also describe a new quantum algorithm for deciding
if a graph is connected, which improves the previous best quantum algorithm for
this problem if we're promised that either the graph has at least kappa > 1
components, or the graph is connected and has small average resistance, which
is upper bounded by the diameter. We also give an alternative algorithm for
deciding if a graph is connected that can be better than our first algorithm
when the maximum degree is small. Finally, using ideas from our second
connectivity algorithm, we give an algorithm for estimating the algebraic
connectivity of a graph, the second largest eigenvalue of the Laplacian.


  The future scenarios often associated with Internet of Things (IoT) oscillate
between the peril of IoT for the future of humanity and the promises for an
ever-connected and efficient future. Such a dichotomous positioning creates
problems not only for expanding the field of application of the technology, but
also ensuring ethical and responsible design and production. As part of VirtEU
(Values and Ethics in Innovation for Responsible Technology in Europe) (EU
Horizon 2020 FP7), we have conducted ethnographic research into the main hubs
of IoT in Europe, such as London, Amsterdam, Barcelona and Belgrade, with
developers and designers of IoT to identify the challenges they face in their
day-to-day work. In this paper, we focus on the IoT and the ethical imaginaries
explore the practical challenges IoT developers face when they are designing,
producing and marketing IoT technologies. We argue that top-down ethical
frameworks that overlook the situated capabilities of developers or the
solutionist approaches that treat ethical issues as technical problems are
unlikely to provide an alternative to the dichotomous imaginary for the future.


  We present results from multi-epoch neutral hydrogen (HI) absorption
observations of six bright pulsars with the Arecibo telescope. Moving through
the interstellar medium (ISM) with transverse velocities of 10--150 AU/yr,
these pulsars have swept across 1--200 AU over the course of our experiment,
allowing us to probe the existence and properties of the tiny scale atomic
structure (TSAS) in the cold neutral medium (CNM). While most of the observed
pulsars show no significant change in their HI absorption spectra, we have
identified at least two clear TSAS-induced opacity variations in the direction
of B1929+10. These observations require strong spatial inhomogeneities in
either the TSAS clouds' physical properties themselves or else in the clouds'
galactic distribution. While TSAS is occasionally detected on spatial scales
down to 10 AU, it is too rare to be characterized by a spectrum of turbulent
CNM fluctuations on scales of 10-1000 AU, as previously suggested by some work.
In the direction of B1929+10, an apparent correlation between TSAS and
interstellar clouds inside the warm Local Bubble (LB) indicates that TSAS may
be tracing the fragmentation of the LB wall via hydrodynamic instabilities.
While similar fragmentation events occur frequently throughout the ISM, the
warm medium surrounding these cold cloudlets induces a natural selection effect
wherein small TSAS clouds evaporate quickly and are rare, while large clouds
survive longer and become a general property of the ISM.


  Population-based metaheuristic algorithms are powerful tools in the design of
neutron scattering instruments and the use of these types of algorithms for
this purpose is becoming more and more commonplace. Today there exists a wide
range of algorithms to choose from when designing an instrument and it is not
always initially clear which may provide the best performance. Furthermore, due
to the nature of these types of algorithms, the final solution found for a
specific design scenario cannot always be guaranteed to be the global optimum.
Therefore, to explore the potential benefits and differences between the
varieties of these algorithms available, when applied to such design scenarios,
we have carried out a detailed study of some commonly used algorithms. For this
purpose, we have developed a new general optimization software package which
combines a number of common metaheuristic algorithms within a single user
interface and is designed specifically with neutronic calculations in mind. The
algorithms included in the software are implementations of Particle-Swarm
Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC),
and a Genetic Algorithm (GA). The software has been used to optimize the design
of several problems in neutron optics and shielding, coupled with Monte-Carlo
simulations, in order to evaluate the performance of the various algorithms.
Generally, the performance of the algorithms depended on the specific
scenarios, however it was found that DE provided the best average solutions in
all scenarios investigated in this work.


  Single phase, sol-gel prepared Cu1-xFexO (0<x<0.125) are characterized in
terms of structural, electronic and magnetic properties. Using dielectric and
magnetic studies we investigate the coupling of electron and spin. The
electrical conductivities and activation energies are studied with increasing
Fe content. Modeling of experimental conductivity data emphasizes on a single
hopping mechanism for all samples except x=0.125, which have two activation
energies. Hole doping is confirmed from Hall effect [1] and by confirming a
majority Fe3+ substitution of Cu2+ in CuO from XPS studies. Such a substitution
results in stabilized ferromagnetism. Fe substitution introduces variation in
coercivity as an intrinsic magnetic property in Fe-doped CuO, and not as a
secondary impurity phase.


  In this article we present preliminary results on the upper limits to the
mass of a companion for 8 apparently single subdwarf B stars, derived from
high-precision radial velocity measurements obtained from Harps-N spectra.
These limits, corresponding to a few Jupiter masses, show that these stars do
not have close companions and keep open the unresolved question of the
mechanism that caused the almost complete loss of the envelope for the giant
precursors of these stars. For 4 stars with a larger data coverage, it was also
possible to set upper limits to the mass of a more massive companion in a wider
orbit.


  We present a method for optimal path planning of human walking paths in
mountainous terrain, using a control theoretic formulation and a
Hamilton-Jacobi-Bellman equation. Previous models for human navigation were
entirely deterministic, assuming perfect knowledge of the ambient elevation
data and human walking velocity as a function of local slope of the terrain.
Our model includes a stochastic component which can account for uncertainty in
the problem, and thus includes a Hamilton-Jacobi-Bellman equation with
viscosity. We discuss the model in the presence and absence of stochastic
effects, and suggest numerical methods for simulating the model. We discuss two
different notions of an optimal path when there is uncertainty in the problem.
Finally, we compare the optimal paths suggested by the model at different
levels of uncertainty, and observe that as the size of the uncertainty tends to
zero (and thus the viscosity in the equation tends to zero), the optimal path
tends toward the deterministic optimal path.