  First order phase transitions in the very early universe are a prediction of
many extensions of the Standard Model of particle physics and could provide the
departure from equilibrium needed for a dynamical explanation of the baryon
asymmetry of the Universe. They could also produce gravitational waves of a
frequency observable by future space-based detectors such as the Laser
Interferometer Space Antenna (LISA). All calculations of the gravitational wave
power spectrum rely on a relativistic version of the classical nucleation
theory of Cahn-Hilliard and Langer, due to Coleman and Linde. The high purity
and precise control of pressure and temperature achievable in the laboratory
made the first-order A to B transition of superfluid $^3$He an ideal for test
of classical nucleation theory. As Leggett and others have noted the theory
fails dramatically. The lifetime of the metastable A phase is measurable,
typically of order minutes to hours, far faster than classical nucleation
theory predicts. If the nucleation of B phase from the supercooled A phase is
due to a new, rapid intrinsic mechanism that would have implications for
first-order cosmological phase transitions as well as predictions for
gravitational wave (GW) production in the early universe. Here we discuss
studies of the AB phase transition dynamics in $^3$He, both experimental and
theoretical, and show how the computational technology for cosmological phase
transition can be used to simulate the dynamics of the A-B transition, support
the experimental investigations of the A-B transition in the QUEST-DMC
collaboration with the goal of identifying and quantifying the mechanism(s)
responsible for nucleation of stable phases in ultra-pure metastable quantum
phases.


  It is well-known that GPS is vulnerable to signal spoofing attacks. Although
several spoofing detection techniques exist, they are incapable of mitigation
and recovery from stealthy attackers. In this work, we present SemperFi, a
single antenna GPS receiver capable of tracking legitimate GPS satellite
signals and estimating the true location even during a spoofing attack. The
main challenge in building SemperFi is, unlike most wireless systems where
\emph{the data} contained in the wireless signals is important, GPS relies on
the time of arrival (ToA) of satellite signals. SemperFi is capable of
distinguishing spoofing signals and recovering legitimate GPS signals that are
even completely overshadowed by a strong adversary. We exploit the short-term
stability of inertial sensors to identify the spoofing signal and extend the
successive interference cancellation algorithm to preserve the legitimate
signal's ToA. We implement SemperFi in GNSS-SDR, an open-source
software-defined GNSS receiver, and evaluate its performance using UAV
simulators, real drones, a variety of real-world GPS datasets, and various
embedded platforms. Our evaluation results indicate that in many scenarios,
SemperFi can identify adversarial peaks by executing flight patterns that are
less than 50 m long and recover the true location within 10 seconds (Jetson
Xavier). We show that our receiver is secure against stealthy attackers who
exploit inertial sensor errors and execute seamless takeover attacks. We design
SemperFi as a pluggable module capable of generating a spoofer-free GPS signal
for processing on any commercial-off-the-shelf GPS receiver available today.
Finally, we release our implementation to the community for usage and further
research.


  We consider a smooth Euclidean solid cone endowed with a smooth homogeneous
density function used to weight Euclidean volume and hypersurface area. By
assuming convexity of the cone and a curvature-dimension condition we prove
that the unique compact, orientable, second order minima of the weighted area
under variations preserving the weighted volume and with free boundary in the
boundary of the cone are intersections with the cone of round spheres centered
at the vertex.


  The historical detection of gravitational waves from the binary neutron star
merger GW170817 is providing fundamental new insights into the astrophysical
site for the creation of the heaviest elements in the cosmos and on the
equation of state of neutron-rich matter. Shortly after this historical
detection, electromagnetic observations of neutron stars together with
measurements of the properties of neutron-rich nuclei at terrestrial facilities
have placed additional constraints on the dynamics of neutron-rich matter. It
is this unique synergy between heaven and earth that is the focus of this
article.


  Given two sets S and T, a limited-capacity many-to-many matching (LCMM)
between S and T matches each element p in S (resp. T) to at least 1 and at most
Cap(p) elements in T (resp. S), where the function Cap:S\cup T-> Z>0 denotes
the capacity of p. In this paper, we present the first linear time algorithm
for finding a minimum-cost one-dimensional LCMM (OLCMM) between S and T, where
S and T are points lying on a line, and the cost of matching p in S to q in T
equals the l_2 distance between p,q. Our algorithm improves the previous
best-known quadratic time algorithm.


  We prove limit theorems for cylindrical martingale problems associated to
L\'evy generators. Furthermore, we give sufficient and necessary conditions for
the Feller property of well-posed problems with continuous coefficients. We
discuss two applications. First, we derive continuity and linear growth
conditions for the existence of weak solutions to infinite-dimensional
stochastic differential equations driven by L\'evy noise. Second, we derive
continuity, local boundedness and linear growth conditions for limit theorems
and the Feller property of weak solutions to stochastic partial differential
equations driven by Wiener noise.


  Recently, numerous approaches have emerged in the social sciences to exploit
the opportunities made possible by the vast amounts of data generated by online
social networks (OSNs). Having access to information about users on such a
scale opens up a range of possibilities, all without the limitations associated
with often slow and expensive paper-based polls. A question that remains to be
satisfactorily addressed, however, is how demography is represented in the OSN
content? Here, we study language use in the US using a corpus of text compiled
from over half a billion geo-tagged messages from the online microblogging
platform Twitter. Our intention is to reveal the most important spatial
patterns in language use in an unsupervised manner and relate them to
demographics. Our approach is based on Latent Semantic Analysis (LSA) augmented
with the Robust Principal Component Analysis (RPCA) methodology. We find
spatially correlated patterns that can be interpreted based on the words
associated with them. The main language features can be related to slang use,
urbanization, travel, religion and ethnicity, the patterns of which are shown
to correlate plausibly with traditional census data. Our findings thus validate
the concept of demography being represented in OSN language use and show that
the traits observed are inherently present in the word frequencies without any
previous assumptions about the dataset. Thus, they could form the basis of
further research focusing on the evaluation of demographic data estimation from
other big data sources, or on the dynamical processes that result in the
patterns found here.


  Federated learning typically considers collaboratively training a global
model using local data at edge clients. Clients may have their own individual
requirements, such as having a minimal training loss threshold, which they
expect to be met by the global model. However, due to client heterogeneity, the
global model may not meet each client's requirements, and only a small subset
may find the global model appealing. In this work, we explore the problem of
the global model lacking appeal to the clients due to not being able to satisfy
local requirements. We propose MaxFL, which aims to maximize the number of
clients that find the global model appealing. We show that having a high global
model appeal is important to maintain an adequate pool of clients for training,
and can directly improve the test accuracy on both seen and unseen clients. We
provide convergence guarantees for MaxFL and show that MaxFL achieves a
$22$-$40\%$ and $18$-$50\%$ test accuracy improvement for the training clients
and unseen clients respectively, compared to a wide range of FL modeling
approaches, including those that tackle data heterogeneity, aim to incentivize
clients, and learn personalized or fair models.


  Phase Shift Keying on the Hypersphere (PSKH), a generalization of
conventional Phase Shift Keying (PSK) for Multiple-Input Multiple-Output (MIMO)
systems, is introduced. In PSKH, constellation points are distributed on a
multidimensional hypersphere. The use of such constellations with a
Peak-To-Average-Sum-Power-Ratio (PASPR) of 1 allows to use load-modulated
transmitters which can cope with a small backoff, which in turn results in a
high power efficiency. In this paper, we discuss several methods how to
generate PSKH constellations and compare their performance. After applying
conventional Pulse-Amplitude Modulation (PAM), the PASPR of the continuous time
PSKH signal depends on the choice of the pulse shaping method. This choice also
influences bandwidth and power efficiency of a PSKH system. In order to reduce
the PASPR of the continuous transmission signal, we use spherical interpolation
to generate a smooth signal over the hypersphere and present corresponding
receiver techniques. Additionally, complexity reduction techniques are proposed
and compared. Finally, we discuss the methods presented in this paper regarding
their trade-offs with respect to PASPR, bandwidth, power efficiency and
receiver complexity.


  The LMTO method based on the density-functional theory and the semi-empirical
INDO method based on the Hartree--Fock formalism are used for the supercell
study of the F centers in cubic and orthorhombic ferroelectric KNbO3 crystals.
Two electrons are found to be considerably delocalized even in the ground state
of the defect. The absorption energies were calculated by means of the INDO
method using the Delta-SCF scheme after a relaxation of atoms surrounding the F
center.
  As an example of another type of point defect in perovskite, an isolated Li
impurity in KTaO3 as well as interacting Li pairs are considered in the
supercell approach, using the supercells of up to 270 atoms. The off-center Li
displacement, reorientational energy barriers and the lattice relaxation around
impurities are calculated. The results are compared with those obtained earlier
within the shell model, revealing the relaxation pattern somehow different from
the shell model estimations.


  The main focus of this work is to understand the dynamics of non regulated
markets. The present model can describe the dynamics of any market where the
pricing is based on supply and demand. It will be applied here, as an example,
for the German stock market presented by the Deutscher Aktienindex (DAX), which
is a measure for the market status. The duality of the present model consists
of the superposition of the two components - the long and the short term
behaviour of the market. The long term behaviour is characterised by a stable
development which is following a trend for time periods of years or even
decades. This long term growth (or decline) is based on the development of
fundamental market figures. The short term behaviour is described as a
dynamical evaluation (trading) of the market by the participants. The trading
process is described as an exchange between supply and demand. In the framework
of this model there the trading is modelled by a system of nonlinear
differential equations. The model also allows to explain the chaotic behaviour
of the market as well as periods of growth or crashes.


  We show that there is a query expressible in first-order logic over the reals
that returns, on any given semi-algebraic set A, for every point a radius
around which A is conical. We obtain this result by combining famous results
from calculus and real algebraic geometry, notably Sard's theorem and Thom's
first isotopy lemma, with recent algorithmic results by Rannou.


  GRBAlpha is a 1U CubeSat mission with an expected launch date in the first
half of 2021. It carries a 75 x 75 x 5 mm CsI(Tl) scintillator, read out by a
dual-channel multi-pixel photon counter (MPPC) setup, to detect gamma-ray
bursts (GRBs). The GRB detector is an in-orbit demonstration for the detector
system on the Cubesats Applied for MEasuring and LOcalising Transients
(CAMELOT) mission. While GRBAlpha provides 1/8th of the expected effective area
of CAMELOT, the comparison of the observed light curves with other existing GRB
monitoring satellites will allow us to validate the core idea of CAMELOT, i.e.
the feasibility of timing-based localization.


  The authors report on the design and measurement of a reflective single-pole
single-throw microwave switch with no internal power dissipation, based on a
superconducting circuit containing a single Josephson junction. The data
demonstrate the switch operation with 2 GHz instantaneous bandwidth centered at
10 GHz, low insertion loss, and better than 20 dB on/off ratio. The switch's
measured performance agrees well with simulations for input powers up to -100
dBm. An extension of the demonstrated circuit to implement a single-pole
double-throw switch is shown in simulation.


  We argue for network slicing as an efficient solution that addresses the
diverse requirements of 5G mobile networks, thus providing the necessary
flexibility and scalability associated with future network implementations. We
elaborate on the challenges that emerge when we design 5G networks based on
network slicing. We focus on the architectural aspects associated with the
coexistence of dedicated as well as shared slices in the network. In
particular, we analyze the realization options of a flexible radio access
network with focus on network slicing and their impact on the design of 5G
mobile networks. In addition to the technical study, this paper provides an
investigation of the revenue potential of network slicing, where the
applications that originate from such concept and the profit capabilities from
the network operator's perspective are put forward.


  The ANTARES telescope is well-suited for detecting astrophysical transient
neutrino sources as it can observe a full hemisphere of the sky at all times
with a high duty cycle. The background due to atmospheric particles can be
drastically reduced, and the point-source sensitivity improved, by selecting a
narrow time window around possible neutrino production periods. Blazars, being
radio-loud active galactic nuclei with their jets pointing almost directly
towards the observer, are particularly attractive potential neutrino point
sources, since they are among the most likely sources of the very high-energy
cosmic rays. Neutrinos and gamma rays may be produced in hadronic interactions
with the surrounding medium. Moreover, blazars generally show high time
variability in their light curves at different wavelengths and on various time
scales. This paper presents a time-dependent analysis applied to a selection of
flaring gamma-ray blazars observed by the FERMI/LAT experiment and by TeV
Cherenkov telescopes using five years of ANTARES data taken from 2008 to 2012.
The results are compatible with fluctuations of the background. Upper limits on
the neutrino fluence have been produced and compared to the measured gamma-ray
spectral energy distribution.


  We propose a lattice model, in both one- and multidimensional versions, which
may give rise to matching conditions necessary for the generation of solitons
through the second-harmonic generation. The model describes an array of
linearly coupled two-component dipoles in an anisotropic nonlinear host medium.
Unlike this discrete system, its continuum counterpart gives rise to the
matching conditions only in a trivial degenerate situation. A system of
nonlinear evolution equations for slowly varying envelope functions of the
resonantly coupled fundamental- and second-harmonic waves is derived. In the
one-dimensional case, it coincides with the standard system known in nonlinear
optics, which gives rise to stable solitons. In the multidimensional case, the
system prove to be more general than its counterpart in optics, because of the
anisotropy of the underlying lattice model.


  Despite the success of convolutional neural networks (CNNs) in many academic
benchmarks for computer vision tasks, their application in the real-world is
still facing fundamental challenges. One of these open problems is the inherent
lack of robustness, unveiled by the striking effectiveness of adversarial
attacks. Current attack methods are able to manipulate the network's prediction
by adding specific but small amounts of noise to the input. In turn,
adversarial training (AT) aims to achieve robustness against such attacks and
ideally a better model generalization ability by including adversarial samples
in the trainingset. However, an in-depth analysis of the resulting robust
models beyond adversarial robustness is still pending. In this paper, we
empirically analyze a variety of adversarially trained models that achieve high
robust accuracies when facing state-of-the-art attacks and we show that AT has
an interesting side-effect: it leads to models that are significantly less
overconfident with their decisions, even on clean data than non-robust models.
Further, our analysis of robust models shows that not only AT but also the
model's building blocks (like activation functions and pooling) have a strong
influence on the models' prediction confidences. Data & Project website:
https://github.com/GeJulia/robustness_confidences_evaluation


  When assisting human users in reinforcement learning (RL), we can represent
users as RL agents and study key parameters, called \emph{user traits}, to
inform intervention design. We study the relationship between user behaviors
(policy classes) and user traits. Given an environment, we introduce an
intuitive tool for studying the breakdown of "user types": broad sets of traits
that result in the same behavior. We show that seemingly different real-world
environments admit the same set of user types and formalize this observation as
an equivalence relation defined on environments. By transferring intervention
design between environments within the same equivalence class, we can help
rapidly personalize interventions.


  The most successful Gogny interactions of the D1 family, namely D1S, D1N and
D1M, suffer the common problem of a too soft neutron matter equation of state
at high density, which prevents them from predicting a maximal mass of neutron
stars of two solar masses, as required by recent astronomical observations. To
cure this deficiency, we have proposed recently a reparametrization of the D1M
force by fine tuning the slope of the symmetry energy in such a way that it
preserves the ground-state properties of D1M in finite nuclei and also
describes successfully the global properties of neutron stars, in particular
its maximal mass, in consonance with the observational data. In this
contribution we revisit this reparametrization by discussing two modified Gogny
forces, dubbed D1M$^*$ and D1M$^{**}$.


  As the usage of large language models (LLMs) grows, performing efficient
inference with these models becomes increasingly important. While speculative
decoding has recently emerged as a promising direction for speeding up
inference, existing methods are limited in their ability to scale to larger
speculation budgets, and adapt to different hyperparameters and hardware. This
paper introduces Sequoia, a scalable, robust, and hardware-aware algorithm for
speculative decoding. To attain better scalability, Sequoia introduces a
dynamic programming algorithm to find the optimal tree structure for the
speculated tokens. To achieve robust speculative performance, Sequoia uses a
novel sampling and verification method that outperforms prior work across
different decoding temperatures. Finally, Sequoia introduces a hardware-aware
tree optimizer that maximizes speculative performance by automatically
selecting the token tree size and depth for a given hardware platform.
Evaluation shows that Sequoia improves the decoding speed of Llama2-7B,
Llama2-13B, and Vicuna-33B on an A100 by up to $4.04\times$, $3.73\times$, and
$2.27\times$. For offloading setting on L40, Sequoia achieves as low as 0.56
s/token for exact Llama2-70B inference latency, which is $9.96\times$ on our
optimized offloading system (5.6 s/token), $9.7\times$ than
DeepSpeed-Zero-Inference, $19.5\times$ than Huggingface Accelerate.


  A new algorithm for determining the eigenstates of n-dimensional billiards is
presented. It is based on the application of the Cauchy theorem for the
determination of the null space of the boundary overlap matrix. The method is
free from the limitations associated with the shape of the billiard and could
be applied even for nonconvex geometries where other algorithms face
difficulties. Moreover it does not suffer from the existence of eigenvalue
degeneracies which is another serious shortcoming of many methods. In the paper
we apply the algorithm to a few simple cases where the analytical solutions
exist. Numerical solutions have been investigated for the case of annular
billiard.


  This paper proposes a novel approach for extending monocular visual odometry
to a stereo camera system. The proposed method uses an additional camera to
accurately estimate and optimize the scale of the monocular visual odometry,
rather than triangulating 3D points from stereo matching. Specifically, the 3D
points generated by the monocular visual odometry are projected onto the other
camera of the stereo pair, and the scale is recovered and optimized by directly
minimizing the photometric error. It is computationally efficient, adding
minimal overhead to the stereo vision system compared to straightforward stereo
matching, and is robust to repetitive texture. Additionally, direct scale
optimization enables stereo visual odometry to be purely based on the direct
method. Extensive evaluation on public datasets (e.g., KITTI), and outdoor
environments (both terrestrial and underwater) demonstrates the accuracy and
efficiency of a stereo visual odometry approach extended by scale optimization,
and its robustness in environments with challenging textures.


  We consider generalized Nash equilibrium problems (GNEPs) with non-convex
strategy spaces and non-convex cost functions. This general class of games
includes the important case of games with mixed-integer variables for which
only a few results are known in the literature. We present a new approach to
characterize equilibria via a convexification technique using the Nikaido-Isoda
function. To any given instance of the GNEP, we construct a set of convexified
instances and show that a feasible strategy profile is an equilibrium for the
original instance if and only if it is an equilibrium for any convexified
instance and the convexified cost functions coincide with the initial ones. We
develop this convexification approach along three dimensions: We first show
that for quasi-linear models, where a convexified instance exists in which for
fixed strategies of the opponent players, the cost function of every player is
linear and the respective strategy space is polyhedral, the convexification
reduces the GNEP to a standard (non-linear) optimization problem. Secondly, we
derive two complete characterizations of those GNEPs for which the
convexification leads to a jointly constrained or a jointly convex GNEP,
respectively. These characterizations require new concepts related to the
interplay of the convex hull operator applied to restricted subsets of feasible
strategies and may be interesting on their own. Note that this characterization
is also computationally relevant as jointly convex GNEPs have been extensively
studied in the literature. Finally, we demonstrate the applicability of our
results by presenting a numerical study regarding the computation of equilibria
for three classes of GNEPs related to integral network flows and discrete
market equilibria.


  Starting with the partition functions for quantum group invariant systems we
calculate the metric in the two-dimensional space defined by the parameters
$\beta$ and $\gamma=-\beta\mu$ and the corresponding scalar curvature for these
systems in two and three spatial dimensions. Our results exhibit the details of
the anyonic behavior of quantum group boson and fermion systems as a function
of the fugacity $z$ and the quantum group parameter $q$. For the case of the
quantum group $SU_q(2)$, we compare the stability of these systems with the
stability of SU(2) invariant boson and fermion systems.


  Finding a new mathematical representations for graph, which allows direct
comparison between different graph structures, is an open-ended research
direction. Having such a representation is the first prerequisite for a variety
of machine learning algorithms like classification, clustering, etc., over
graph datasets. In this paper, we propose a symmetric positive semidefinite
matrix with the $(i,j)$-{th} entry equal to the covariance between normalized
vectors $A^ie$ and $A^je$ ($e$ being vector of all ones) as a representation
for graph with adjacency matrix $A$. We show that the proposed matrix
representation encodes the spectrum of the underlying adjacency matrix and it
also contains information about the counts of small sub-structures present in
the graph such as triangles and small paths. In addition, we show that this
matrix is a \emph{"graph invariant"}. All these properties make the proposed
matrix a suitable object for representing graphs.
  The representation, being a covariance matrix in a fixed dimensional metric
space, gives a mathematical embedding for graphs. This naturally leads to a
measure of similarity on graph objects. We define similarity between two given
graphs as a Bhattacharya similarity measure between their corresponding
covariance matrix representations. As shown in our experimental study on the
task of social network classification, such a similarity measure outperforms
other widely used state-of-the-art methodologies. Our proposed method is also
computationally efficient. The computation of both the matrix representation
and the similarity value can be performed in operations linear in the number of
edges. This makes our method scalable in practice.
  We believe our theoretical and empirical results provide evidence for
studying truncated power iterations, of the adjacency matrix, to characterize
social networks.


  We develop a thermodynamic formalism for a strongly dissipative H\'enon-like
map at the first bifurcation parameter at which the uniform hyperbolicity is
destroyed by the formation of tangencies inside the limit set. For any
$t\in\mathbb R$ we prove the existence of an invariant Borel probability
measure which minimizes the free energy associated with a non continuous
geometric potential $-t\log J^u$, where $J^u$ denotes the Jacobian in the
unstable direction. Under a mild condition, we show that any accumulation point
of these measures as $t\to+\infty$ minimizes the unstable Lyapunov exponent. We
also show that the equilibrium measures converge as $t\to-\infty$ to a Dirac
measure which maximizes the unstable Lyapunov exponent.


  The appealing feature of quantum key distribution (QKD), from a cryptographic
viewpoint, is the ability to prove the information-theoretic security (ITS) of
the established keys. As a key establishment primitive, QKD however does not
provide a standalone security service in its own: the secret keys established
by QKD are in general then used by a subsequent cryptographic applications for
which the requirements, the context of use and the security properties can
vary. It is therefore important, in the perspective of integrating QKD in
security infrastructures, to analyze how QKD can be combined with other
cryptographic primitives. The purpose of this survey article, which is mostly
centered on European research results, is to contribute to such an analysis. We
first review and compare the properties of the existing key establishment
techniques, QKD being one of them. We then study more specifically two generic
scenarios related to the practical use of QKD in cryptographic infrastructures:
1) using QKD as a key renewal technique for a symmetric cipher over a
point-to-point link; 2) using QKD in a network containing many users with the
objective of offering any-to-any key establishment service. We discuss the
constraints as well as the potential interest of using QKD in these contexts.
We finally give an overview of challenges relative to the development of QKD
technology that also constitute potential avenues for cryptographic research.


  We define two generalizations of the totally nonnegative Grassmannian and
determine their topology in the case of real projective space. We find the
spaces to be PL manifolds with boundary which are homotopy equivalent to
another real projective space of smaller dimension. One generalization makes
use of sign variation while the other uses boundary measurement. Spaces arising
from boundary measurement are shown to admit Cohen-Macaulay triangulations.


  In the present work, we explore the influence of habitat complexity on the
activities of prey and predator of a spatio-temporal system by incorporating
self diffusion. First we modify the Rosenzweig-MacArthur predator-prey model by
incorporating the effects of habitat complexity on the carrying capacity and
fear effect of prey and predator functional response. We establish conditions
for the existence and stability of all feasible equilibrium points of the
non-spatial model and later we prove the existence of Hopf and transcritical
bifurcations in different parametric phase-planes analytically and numerically.
The stability of the spatial system is studied and we discuss the conditions
for Turing instability. Selecting suitable control parameter from the Turing
space, the existence conditions for stable patterns are derived using the
amplitude equations. Results obtained from theoretical analysis of the
amplitude equations are justified by numerical simulation results near the
critical parameter value. Further, from numerical simulation, we illustrate the
effect of diffusion of the dynamical system in the spatial domain by different
pattern formations. Thus our model clearly shows that the fear effect of prey
and predator's functional response make an anti-predator behaviour including
habitat complexity which helps the prey to survive in the spatio-temporal
domain through diffusive process.


  In a recent Letter, Luo et al. (Phys. Rev. Lett. 92, 256602 (2004)) analyze
the Fano line shapes obtained from scanning tunneling spectroscopy (STS) of
transition metal impurities on a simple metal surface, in particular of the
Ti/Au(111) and Ti/Ag(100) systems. As the key point of their analysis, they
claim that there is not only a Fano interference effect between the impurity
d-orbital and the conduction electron continuum, as derived in Ujsaghy et al.
(Phys. Rev. Lett. 85, 2557 (2000)), but that the Kondo resonance in the
d-electron spectral density has by itself a second Fano line shape, leading to
the experimentally observed spectra. In the present note we point out that this
analysis is conceptually incorrect. Therefore, the quantitative agreement of
the fitted theoretical spectra with the experimental results is meaningless.


  Recently, Large Language Model based Autonomous system(LLMAS) has gained
great popularity for its potential to simulate complicated behaviors of human
societies. One of its main challenges is to present and analyze the dynamic
events evolution of LLMAS. In this work, we present a visualization approach to
explore detailed statuses and agents' behavior within LLMAS. We propose a
general pipeline that establishes a behavior structure from raw LLMAS execution
events, leverages a behavior summarization algorithm to construct a
hierarchical summary of the entire structure in terms of time sequence, and a
cause trace method to mine the causal relationship between agent behaviors. We
then develop AgentLens, a visual analysis system that leverages a hierarchical
temporal visualization for illustrating the evolution of LLMAS, and supports
users to interactively investigate details and causes of agents' behaviors. Two
usage scenarios and a user study demonstrate the effectiveness and usability of
our AgentLens.


  We review current understanding of the underlying, as opposed to the
observed, pulsar population. The observed sample is heavily biased by selection
effects, so that surveys see less than 10% of all potentially observable
pulsars. We compare various techniques used to correct the sample for these
biases. By far the most significant recent development has been the discovery
of over 700 pulsars in the Parkes Multibeam (PM) survey. This new sample is far
less affected by selection effects and we use it to make a preliminary analysis
of the Galactic pulsar distribution, finding further evidence for a deficit of
pulsars in the inner Galaxy.


  Selected theoretical developments in modeling of deposition of submicrometer
size (submicron) particles on solid surfaces, with and without surface
diffusion, of interest in colloid, polymer, and certain biological systems, are
surveyed. We review deposition processes involving extended objects, with
jamming and its interplay with in-surface diffusion yielding interesting
dynamics of approach to the large-time state. Mean-field and low-density
approximation schemes can be used in many instances for short and intermediate
times, in large enough dimensions, and for particle sizes larger than few
lattice units. Random sequential adsorption models are appropriate for higher
particle densities (larger times). Added diffusion allows formation of denser
deposits and leads to power-law large-time behavior which, in one dimension
(linear substrate, such as DNA), was related to diffusion-limited reactions,
while in two dimensions (planar substrate), was associated with evolution of
the domain-wall and defect network, reminiscent of equilibrium ordering
processes.


  A diffusion spider is a strong Markov process with continuous paths taking
values on a graph with one vertex and a finite number of edges (of infinite
length). An example is Walsh's Brownian spider where the process on each edge
behaves as Brownian motion. We calculate the density of the resolvent kernel in
terms of the characteristics of the underlying diffusion. Excessive functions
are studied via the Martin boundary theory. The main result is an explicit
expression for the representing measure of a given excessive function. These
results are used to solve optimal stopping problems for diffusion spiders.


  Projection-based augmented reality (AR) has much potential, but is limited in
that it requires burdensome installations and prone to geometric distortions on
display surface. To overcome these limitations, we propose AIR. It can be
carried and placed anywhere to project AR using pan/tilting motors, while
providing the user with distortion-free projection of a correct 3D view.


  Let $(X_n)_{n\geq 0}$ be a Markov chain with values in a finite state space
$\mathbb X$ starting at $X_0=x \in \mathbb X$ and let $f$ be a real function
defined on $\mathbb X$. Set $S_n=\sum_{k=1}^{n} f(X_k)$, $n\geqslant 1$. For
any $y \in \mathbb R$ denote by $\tau_y$ the first time when $y+S_n$ becomes
non-positive. We study the asymptotic behaviour of the probability $\mathbb P_x
\left( y+S_{n} \in [z,z+a] \,,\, \tau_y > n \right)$ as $n\to+\infty.$ We first
establish for this probability a conditional version of the local limit theorem
of Stone. Then we find for it an asymptotic equivalent of order $n^{3/2}$ and
give a generalization which is useful in applications. We also describe the
asymptotic behaviour of the probability $\mathbb P_x \left( \tau_y = n \right)$
as $n\to+\infty$.


  We derive the closed form solutions for the surface area, the capacitance and
the demagnetizing factors of the ellipsoid immersed in the Euclidean space R^3.
The exact solutions for the above geometrical and physical properties of the
ellipsoid are expressed elegantly in terms of the generalized hypergeometric
functions of Appell of two variables. Various limiting cases of the theorems of
the exact solution for the surface area, the demagnetizing factors and the
capacitance of the ellipsoid are derived, which agree with known solutions for
the prolate and oblate spheroids and the sphere. Possible applications of the
results achieved, in various fields of science, such as in physics, biology and
space science are briefly discussed.


  This paper focuses on a class of continuous-time controlled Markov chains
with time-inconsistent and distribution-dependent cost functional (in some
appropriate sense). A new definition of time-inconsistent
distribution-dependent equilibrium in closed-loop sense is given and its
existence and uniqueness have been established. Because of the
time-inconsistency, it is proved that the equilibrium is locally optimal in an
appropriate sense. Moreover, it has been shown that our problem is essentially
equivalent to an infinite-player mean-field game with time-inconsistent cost.


  In this paper, we study the integral curvatures of Finsler manifolds and
prove several Myers type theorems.


  A typical phenomenon for machine models of transfinite computations is the
existence of so-called lost melodies, i.e. real numbers $x$ such that the
characteristic function of the set $\{x\}$ is computable while $x$ itself is
not (a real having the first property is called recognizable). This was first
observed by J. D. Hamkins and A. Lewis for infinite time Turing machine, then
demonstrated by P. Koepke and the author for $ITRM$s. We prove that, for
unresetting infinite time register machines introduced by P. Koepke,
recognizability equals computability, i.e. the lost melody phenomenon does not
occur. Then, we give an overview on our results on the behaviour of
recognizable reals for $ITRM$s. We show that there are no lost melodies for
ordinal Turing machines or ordinal register machines without parameters and
that this is, under the assumption that $0^{\sharp}$ exists, independent of
$ZFC$. Then, we introduce the notions of resetting and unresetting
$\alpha$-register machines and give some information on the question for which
of these machines there are lost melodies.


  We study the tunneling through delta and double delta potentials in
fractional quantum mechanics. After solving the fractional Schr\"odinger
equation for these potentials, we calculate the corresponding reflection and
transmission coefficients. These coefficients have a very interesting
behaviour. In particular, we can have zero energy tunneling when the order of
the Riesz fractional derivative is different from 2. For both potentials, the
zero energy limit of the transmission coefficient is given by $\mathcal{T}_0 =
\cos^2{\pi/\alpha}$, where $\alpha$ is the order of the derivative ($1 < \alpha
\leq 2$).


  We present first results from the ongoing radio monitoring of SN 2008iz in
M82. The VLBI images reveal a shell-like structure with circular symmetry,
which expands in a self-similar way. There is strong evidence of a compact
component with a steep spectrum at the center of the shell. The expansion curve
obtained from our VLBI observations is marginally decelerated (m = 0.89) and
can be modeled simultaneously with the available radio light curves. While the
results of this simultaneous fitting are not conclusive (i.e. different
combinations of values of the magnetic field, CSM density profile, and electron
energy distribution, provide fits to the available data with similar quality),
additional observations should allow a more robust and detailed modeling.


  We report measurements of trigonometric parallaxes for six high-mass
star-forming regions in the Scutum spiral arm of the Milky Way as part of the
BeSSeL Survey. Combining our measurements with 10 previous measurements from
the BeSSeL Survey yields a total sample of 16 sources in the Scutum arm with
trigonometric parallaxes in the Galactic longitude range from 5 deg to 32 deg.
Assuming a logarithmic spiral model, we estimate a pitch angle of 19.8 (+/-3.1)
deg for the Scutum arm, which is larger than pitch angles reported for other
spiral arms. The high pitch angle of the arm may be due to the arm's proximity
to the Galactic bar. The Scutum arm sources show an average peculiar motion of
4 km/s slower than the Galactic rotation and 8 km/s toward the Galactic center.
While the direction of this non-circular motion has the same sign as determined
for sources in other spiral arms, the motion toward the Galactic center is
greater for the Scutum arm sources.


  The nature of glassy states in realistic finite dimensions is still under
fierce debate. Lattice models can offer valuable insights and facilitate deeper
theoretical understanding. Recently, a disordered-interacting lattice model
with distinguishable particles in two dimensions (2D) has been shown to produce
a wide range of dynamical properties of structural glasses, including the slow
and heterogeneous characteristics of the glassy dynamics, various fragility
behaviors of glasses, and so on. These findings support the usefulness of this
model for modeling structural glasses. An important question is whether such
properties still hold in the more realistic three dimensions. In this study, we
aim to extend the distinguishable-particle lattice model (DPLM) to three
dimensions (3D) and explore the corresponding glassy dynamics. Through
extensive kinetic Monte Carlo simulations, we found that the 3D DPLM exhibits
many typical glassy behaviors, such as plateaus in the mean square displacement
of particles and the self-intermediate scattering function, dynamic
heterogeneity, variability of glass fragilities, and so on, validating the
effectiveness of the DPLM in a broader realistic setting. The observed glassy
behaviors of the 3D DPLM appear similar to those of its 2D counterpart, in
accordance with recent findings in molecular models of glasses. We further
investigate the role of void-induced motions in dynamical relaxations and
discuss their relation to dynamic facilitation. As lattice models tend to keep
the minimal but important modeling elements, they are typically much more
amenable to analysis. Therefore, we envisage that the DPLM will benefit future
theoretical developments, such as the configuration tree theory, towards a more
comprehensive understanding of structural glasses.


  This paper reports a cathodoluminescence (CL) spectroscopic study of
nanogranular AlNOErx samples with erbiumcontent, x, in the range 0.5--3.6 at%.
A wide range of erbium concentration was studied with the aim ofunderstanding
the concentration quenching of CL. The composition of thin films, deposited by
radiofrequencyreactive magnetron sputtering, was accurately determined by
Energy Dispersive X-ray Spectroscopy (EDS). CLemission was investigated in the
extended visible spectral range from 350 nm to 850 nm. The critical
concentrationof luminescent activator Er3+ above which CL quenching occurs is
1%; the corresponding criticaldistance between Er3+ ions in AlNOErx is about
1.0 nm. The quenching mechanism is discussed. We discount anexchange-mediated
interaction in favour of a multipole-multipole phonon-assisted interaction.


  Quantum darwinism (QD) is the process responsible for the proliferation of
redundant information in the environment of a quantum system that is being
decohered. This enables independent observers to access separate environmental
fragments and reach consensus about the system's state. In this work, we study
the effect of disorder in the emergence of QD and find that a highly disordered
environment is greatly beneficial for it. By introducing the notion of lack of
redundancy to quantify objectivity, we show that it behaves analogously to the
entanglement entropy (EE) of the environmental eigenstate taken as an initial
state. This allows us to estimate the many-body mobility edge by means of our
darwinistic measure, implicating the existence of a critical degree of disorder
beyond which the degree of objectivity rises the larger the environment is. The
latter hints the key role that disorder may play when the environment is of a
thermodynamic size. At last, we show that a highly disordered evolution may
reduce the spoiling of redundancy in the presence of intra-environment
interactions.


  We report on the temperature dependence of the impurity-induced resonant
state in Zn-doped Bi_2Sr_2CaCu_2O$_{8+\delta}$ by scanning tunneling
spectroscopy at 30 mK < T < 52 K. It is known that a Zn impurity induces a
sharp resonant peak in tunnel spectrum at an energy close to the Fermi level.
We observed that the resonant peak survives up to 52 K. The peak broadens with
increasing temperature, which is explained by the thermal effect. This result
provides information to understand the origin of the resonant peak.


  We derive simple empirical color-redshift relations for $z\la 4$ galaxies in
the Hubble Deep Field (HDF) using a linear function of three photometric colors
($U-B$, $B-V$, $V-I$). The dispersion between the estimated redshifts and the
spectroscopically observed ones is small for relations derived in several
separate color regimes; the dispersions range from $\sigma_z\simeq 0.03$ to 0.1
for $z\la 2$ galaxies, and from $\sigma_z\simeq 0.14$ to 0.25 for $z\ga 2 $
galaxies. We apply the color-redshift relations to the HDF photometric catalog
and obtain estimated redshifts that are consistent with those derived from
spectral template fitting methods. The advantage of these color-redshift
relations is that they are simple and easy to use and do not depend on the
assumption of any particular spectral templates; they provide model independent
redshift estimates for $z\la 4$ galaxies using only multi-band photometry, and
they apply to about 90% of all galaxies. We provide a color-based estimated
redshift catalog of HDF galaxies to $z\la 4$. We use the estimated redshifts to
investigate the redshift distribution of galaxies in the HDF; we find peaks in
the redshift distribution that suggest large-scale clustering of galaxies to at
least $z\sim 1$ and that are consistent with those identified in spectroscopic
probes of the HDF.


  Kernel alignment measures the degree of similarity between two kernels. In
this paper, inspired from kernel alignment, we propose a new Linear
Discriminant Analysis (LDA) formulation, kernel alignment LDA (kaLDA). We first
define two kernels, data kernel and class indicator kernel. The problem is to
find a subspace to maximize the alignment between subspace-transformed data
kernel and class indicator kernel. Surprisingly, the kernel alignment induced
kaLDA objective function is very similar to classical LDA and can be expressed
using between-class and total scatter matrices. This can be extended to
multi-label data. We use a Stiefel-manifold gradient descent algorithm to solve
this problem. We perform experiments on 8 single-label and 6 multi-label data
sets. Results show that kaLDA has very good performance on many single-label
and multi-label problems.


  Training robotic policies in simulation suffers from the sim-to-real gap, as
simulated dynamics can be different from real-world dynamics. Past works
tackled this problem through domain randomization and online
system-identification. The former is sensitive to the manually-specified
training distribution of dynamics parameters and can result in behaviors that
are overly conservative. The latter requires learning policies that
concurrently perform the task and generate useful trajectories for system
identification. In this work, we propose and analyze a framework for learning
exploration policies that explicitly perform task-oriented exploration actions
to identify task-relevant system parameters. These parameters are then used by
model-based trajectory optimization algorithms to perform the task in the real
world. We instantiate the framework in simulation with the Linear Quadratic
Regulator as well as in the real world with pouring and object dragging tasks.
Experiments show that task-oriented exploration helps model-based policies
adapt to systems with initially unknown parameters, and it leads to better task
performance than task-agnostic exploration.


  In this paper we present a unified Lagrangian--Hamiltonian geometric
formalism to describe time-dependent contact mechanical systems, based on the
one first introduced by K. Kamimura and later formalized by R. Skinner and R.
Rusk. This formalism is especially interesting when dealing with systems
described by singular Lagrangians, since the second-order condition is
recovered from the constraint algorithm. In order to illustrate this
formulation, some relevant examples are described in full detail: the Duffing
equation, an ascending particle with time-dependent mass and quadratic drag,
and a charged particle in a stationary electric field with a time-dependent
constraint.


  We exhibit a bijection between 132-avoiding permutations and Dyck paths.
Using this bijection, it is shown that all the recently discovered results on
generating functions for 132-avoiding permutations with a given number of
occurrences of the pattern $12... k$ follow directly from old results on the
enumeration of Motzkin paths, among which is a continued fraction result due to
Flajolet. As a bonus, we use these observations to derive further results and a
precise asymptotic estimate for the number of 132-avoiding permutations of
$\{1,2,...,n\}$ with exactly $r$ occurrences of the pattern $12... k$. Second,
we exhibit a bijection between 123-avoiding permutations and Dyck paths. When
combined with a result of Roblet and Viennot, this bijection allows us to
express the generating function for 123-avoiding permutations with a given
number of occurrences of the pattern $(k-1)(k-2)... 1k$ in form of a continued
fraction and to derive further results for these permutations.


  We revisit the case of SN2002ic that recently revived the debate about the
progenitors of SNeIa after the claim of the unprecedented presence of hydrogen
lines over a diluted SNIa spectrum. As an alternative to the previous
interpretation, we suggest that SN2002ic actually was a type Ic SN, the core
collapse of a massive star which lost its hydrogen and helium envelope. In this
scenario the observed interaction with a dense circumstellar material (CSM) is
the predictable consequence of the intense mass-loss of the progenitor and/or
of the presence of a gas rich environment. With this view we establish a link
between energetic SNeIc and highly interacting SNeIIn and add some credits to
the proposed association of some SNeIIn to GRBs.


  We examine data obtained by the Lunar Penetrating Radar (LPR) onboard the
Chang'E-4 (CE-4) mission to study the dielectric properties and stratigraphy of
lunar regolith on the far side of the Moon. The data collected from January
2019 to September 2020 were processed to generate a 540 m radargram. The travel
velocity of the radar signal and the permittivity of the regolith were deduced
from hyperbolas in the radargram. As CE-4 LPR detected distinct planar
reflectors, we evaluated the dielectric loss from the maximum penetration depth
based on the radar equation. The derived dielectric properties are compared
with the measurements of Apollo samples and Chang'E-2 microwave radiometer
observations. The results suggest that regolith at the landing site has a
permittivity of 2.64-3.85 and a loss tangent of 0.0032-0.0044, indicating that
the local regolith is composed of a fine-grained, low-loss material that is
much more homogeneous than that found at the Chang'E-3 landing site. The total
thickness of weathered material is 40 m, with several regolith layers and a
buried craternidentified in the reconstructed subsurface structure. These
layers clearly record a series of impact events from the adjacent regions. We
suggest that the top layer is primarily made up of the ejecta from a large
crater 140 km away. In contrast, the material source of other thinner layers
comes from nearby smaller craters.


  Experimental work suggests that biological soil crusts, dominant primary
producers in drylands and tundra, are particularly vulnerable to disturbances
that cause reverse ecological succession. To model successional transitions in
biocrust communities, we propose a resource-firing game that captures
succession dynamics without specifying detailed function forms. The model is
evaluated in idealized terrestrial ecosystems, where disturbances are modeled
as a reduction in available resources that triggers inter-species competition.
The resource-firing game is executed on a finite graph with nodes representing
species in the community and a sink node that becomes active when every species
is depleted of resources. First, we discuss the theoretical basis of the
resource-firing game, evaluate it in the light of existing literature, and
consider the characteristics of a biocrust community that has evolved to
equilibrium. We then examine the dependence of resource-firing and game
stability on species richness, showing that high species richness increases the
probability of very short and long avalanches, but not those of intermediate
length. Indeed, this result suggests that the response of the community to
disturbance is both directional and episodic, proceeding towards reverse
succession in bursts of variable length. Finally, we incorporate the spatial
structure of the biocrust community into a Cayley Tree and derive a formula for
the probability that a disturbance, modeled as a random attack, initiates a
large species-death event.


  SN 2015J was discovered on April 27th 2015 and is classified as a type IIn
supernova. At first, it appeared to be an orphan SN candidate, i.e. without any
clear identification of its host galaxy. Here, we present the analysis of the
observations carried out {by the VLT 8-m class telescope with the FORS2 camera
in the R band and the Magellan telescope (6.5 m) equipped with the IMACS
Short-Camera (V and I filters) and the FourStar camera (Ks filter)}. We show
that SN 2015J resides in what appears to be a very compact galaxy establishing
a relation between the SN event and its natural host. We also present and
discuss archival and new $X$-ray data centred on SN 2015J. At the time of the
supernova explosion, Swift/XRT observations were made and a weak X-ray source
was detected at the location of SN 2015J. Almost one year later, the same
source was unambiguously identified during serendipitous observations by
Swift/XRT and $XMM$-Newton, clearly showing an enhancement of the 0.3-10 keV
band flux by a factor $\simeq 30$ with respect to the initial state. Swift/XRT
observations show that the source is still active in the $X$-rays at a level of
$\simeq 0.05$ counts s$^{-1}$. The unabsorbed X-ray luminosity derived from the
{\it XMM}-Newton slew and SWIFT observations, $L_{x}\simeq 5\times10^{41}$ erg
s$^{-1}$, places SN 2015J among the brightest young supernovae in X-rays.


  The First Perception Test challenge was held as a half-day workshop alongside
the IEEE/CVF International Conference on Computer Vision (ICCV) 2023, with the
goal of benchmarking state-of-the-art video models on the recently proposed
Perception Test benchmark. The challenge had six tracks covering low-level and
high-level tasks, with both a language and non-language interface, across
video, audio, and text modalities, and covering: object tracking, point
tracking, temporal action localisation, temporal sound localisation,
multiple-choice video question-answering, and grounded video
question-answering. We summarise in this report the task descriptions, metrics,
baselines, and results.


  In $d$-Scattered Set we are given an (edge-weighted) graph and are asked to
select at least $k$ vertices, so that the distance between any pair is at least
$d$, thus generalizing Independent Set. We provide upper and lower bounds on
the complexity of this problem with respect to various standard graph
parameters. In particular, we show the following:
  - For any $d\ge2$, an $O^*(d^{\textrm{tw}})$-time algorithm, where
$\textrm{tw}$ is the treewidth of the input graph.
  - A tight SETH-based lower bound matching this algorithm's performance. These
generalize known results for Independent Set.
  - $d$-Scattered Set is W[1]-hard parameterized by vertex cover (for
edge-weighted graphs), or feedback vertex set (for unweighted graphs), even if
$k$ is an additional parameter.
  - A single-exponential algorithm parameterized by vertex cover for unweighted
graphs, complementing the above-mentioned hardness.
  - A $2^{O(\textrm{td}^2)}$-time algorithm parameterized by tree-depth
($\textrm{td}$), as well as a matching ETH-based lower bound, both for
unweighted graphs.
  We complement these mostly negative results by providing an FPT approximation
scheme parameterized by treewidth. In particular, we give an algorithm which,
for any error parameter $\epsilon > 0$, runs in time
$O^*((\textrm{tw}/\epsilon)^{O(\textrm{tw})})$ and returns a
$d/(1+\epsilon)$-scattered set of size $k$, if a $d$-scattered set of the same
size exists.


  The novel MPGD-based photon detectors of COMPASS RICH-1 consist of large-size
hybrid MPGDs with multi-layer architecture including two layers of Thick-GEMs
and a bulk resistive MicroMegas. The top surface of the first THGEM is coated
with a CsI film which also acts as photo-cathode. These detectors have been
successfully in operation at COMPASS since 2016. Concerning bias-voltage
supply, the Thick-GEMs are segmented in order to reduce the energy released in
case of occasional discharges, while the MicroMegas anode is segmented into
pads individually biased with positive voltage while the micromesh is grounded.
In total, there are about ten different electrode types and more than 20000
electrodes supplied by more than 100 HV channels, where appropriate
correlations among the applied voltages are required for the correct operation
of the detectors. Therefore, a robust control system is mandatory, implemented
by a custom designed software package, while commercial power supply units are
used. This sophisticated control system allows to protect the detectors against
errors by the operator, to monitor and log voltages and currents at 1 Hz rate,
and automatically react to detector misbehaviour. In addition, a voltage
compensation system has been developed to automatically adjust the biasing
voltage according to environmental pressure and temperature variations, to
achieve constant gain over time. This development answers to a more general
need. In fact, voltage compensation is always a requirement for the stability
of gaseous detectors and its need is enhanced in multi-layer ones.
  In this paper, the HV system and its performance are described in details, as
well as the stability of the novel MPGD-based photon detectors during the
physics data taking at COMPASS.


  In this work, we present the analytical approach to the evaluation of the
conditional measure Wiener path integral. We consider the time-dependent model
parameters. We find the differential equation for the variable, determining the
behavior of the harmonic as well the an-harmonic parts of the oscillator. We
present the an-harmonic part of the result in the form of the operator
function.


  We introduce a new hierarchy of higher-order nested pushdown trees
generalising Alur et al.'s concept of nested pushdown trees. Nested pushdown
trees are useful representations of control flows in the verification of
programs with recursive calls of first-order functions. Higher-order nested
pushdown trees are expansions of unfoldings of graphs generated by higher-order
pushdown systems. Moreover, the class of nested pushdown trees of level n is
uniformly first-order interpretable in the class of collapsible pushdown graphs
of level n+1. The relationship between the class of higher-order pushdown
graphs and the class of collapsible higher-order pushdown graphs is not very
well understood. We hope that the further study of the nested pushdown tree
hierarchy leads to a better understanding of these two hierarchies. In this
paper, we are concerned with the first-order model checking problem on
higher-order nested pushdown trees. We show that the first-order model checking
on the first two levels of this hierarchy is decidable. Moreover, we obtain an
2-EXPSPACE algorithm for the class of nested pushdown trees of level 1. The
proof technique involves a pseudo-local analysis of strategies in the
Ehrenfeucht-Fraisse games on two identical copies of a nested pushdown tree.
Ordinary locality arguments in the spirit of Gaifman's lemma do not apply here
because nested pushdown trees tend to have small diameters. We introduce the
notion of relevant ancestors which provide a sufficient description of the FO_k
-type of each element in a higher-order nested pushdown tree. The local
analysis of these ancestors allows us to prove the existence of restricted
winning strategies in the Ehrenfeucht-Fraisse game. These strategies are then
used to create a first-order model checking algorithm.


  The hypergraph Ramsey number of two $3$-uniform hypergraphs $G$ and $H$,
denoted by $R(G,H)$, is the least integer $N$ such that every red-blue
edge-coloring of the complete $3$-uniform hypergraph on $N$ vertices contains a
red copy of $G$ or a blue copy of $H$.
  The Fano plane $\mathbb{F}$ is the unique 3-uniform hypergraph with seven
edges on seven vertices in which every pair of vertices is contained in a
unique edge. There is a simple construction showing that $R(H,\mathbb{F}) \ge
2(v(H)-1) + 1.$ Hypergraphs $H$ for which the equality holds are called
$\mathbb{F}$-good. Conlon asked to determine all $H$ that are
$\mathbb{F}$-good.
  In this short paper we make progress on this problem and prove that the tight
path of length $n$ is $\mathbb{F}$-good.


  Having a good Human-Computer Interaction (HCI) design is challenging.
Previous works have contributed significantly to fostering HCI, including
design principle with report study from the instructor view. The questions of
how and to what extent students perceive the design principles are still left
open. To answer this question, this paper conducts a study of HCI adoption in
the classroom. The studio-based learning method was adapted to teach 83
graduate and undergraduate students in 16 weeks long with four activities. A
standalone presentation tool for instant online peer feedback during the
presentation session was developed to help students justify and critique
other's work. Our tool provides a sandbox, which supports multiple application
types, including Web-applications, Object Detection, Web-based Virtual Reality
(VR), and Augmented Reality (AR). After presenting one assignment and two
projects, our results showed that students acquired a better understanding of
the Golden Rules principle over time, which was demonstrated by the development
of visual interface design. The Wordcloud reveals the primary focus was on the
user interface and shed some light on students' interest in user experience.
The inter-rater score indicates the agreement among students that they have the
same level of understanding of the principles. The results show a high level of
guideline compliance with HCI principles, in which we witnessed variations in
visual cognitive styles. Regardless of diversity in visual preference, the
students presented high consistency and a similar perspective on adopting HCI
design principles. The results also elicited suggestions into the development
of the HCI curriculum in the future.


  We investigate further the existence of solutions to kinetic models of
chemotaxis. These are nonlinear transport-scattering equations with a quadratic
nonlinearity which have been used to describe the motion of bacteria since the
80's when experimental observations have shown they move by a series of 'run
and tumble'. The existence of solutions has been obtained in several papers
[Chalub et al. Monatsh. Math. 142, 123--141 (2004), Hwang et al. SIAM J. Math.
Anal. 36, 1177--1199 (2005)] using direct and strong dispersive effects.
  Here, we use the weak dispersion estimates of [Castella et al. C. R. Acad.
Sci. Paris 322, 535--540 (1996)] to prove global existence in various
situations depending on the turning kernel. In the most difficult cases, where
both the velocities before and after tumbling appear, with the known methods,
only Strichartz estimates can give a result, with a smallness assumption.


  Digital electronics is a technological cornerstone in our modern society
which has covered the increasing demand in computing power during the last
decades thanks to a periodic doubling of transistor density and power
efficiency in integrated circuits. Currently, such scaling laws are reaching
their fundamental limits, leading to the emergence of a large gamut of
applications that cannot be supported by digital electronics, specifically,
those that involve real time analog multi-data processing, e.g., medical
diagnostic imaging, robotic control and remote sensing, among others. In this
scenario, an analog computing approach implemented in a real-time
reconfigurable non-electronic hardware such as programmable integrated
photonics (PIP) can be more efficient than digital electronics to perform these
emerging applications. However, actual analog computing models such as quantum
and neuromorphic computation were not conceived to extract the benefits of PIP
technology (and integrated photonics in general). Here, we present the
foundations of a new computation theory, termed Analog Programmable-Photonic
Computation (APC), explicitly designed to unleash the full potential of PIP.
Interestingly, APC enables overcoming basic theoretical and technological
limitations of existing computational models, can be implemented in other
technologies (e.g. in electronics, acoustics or using metamaterials) and,
consequently, exhibits the potential to spark a ground-breaking impact on our
information society.


  The NA57 experiment at the CERN SPS has measured the production of strange
and multi-strange particles in Pb-Pb (and p-Be) collisions at mid-rapidity. The
collective dynamics of the collision is studied in the transverse and
longitudinal directions as a function of centrality and beam momentum and
analysed based on hydrodynamical models. Central-to-peripheral nuclear
modification factors at 158 A GeV/c are presented and compared with other
measurements and theory.


  We present the results of processing an additional 44% of the High Time
Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey, the most
sensitive blind pulsar survey of the southern Galactic plane to date. Our
partially-coherent segmented acceleration search pipeline is designed to enable
the discovery of pulsars in short, highly-accelerated orbits, while our 72-min
integration lengths will allow us to discover pulsars at the lower end of the
pulsar luminosity distribution. We report the discovery of 40 pulsars,
including three millisecond pulsar-white dwarf binary systems (PSRs J1537-5312,
J1547-5709 and J1618-4624), a black-widow binary system (PSR J1745-23) and a
candidate black-widow binary system (PSR J1727-2951), a glitching pulsar (PSR
J1706-4434), an eclipsing binary pulsar with a 1.5-yr orbital period (PSR
J1653-45), and a pair of long spin-period binary pulsars which display either
nulling or intermittent behaviour (PSRs J1812-15 and J1831-04). We show that
the total population of 100 pulsars discovered in the HTRU-S LowLat survey to
date represents both an older and lower-luminosity population, and indicates
that we have yet to reach the bottom of the luminosity distribution function.
We present evaluations of the performance of our search technique and of the
overall yield of the survey, considering the 94% of the survey which we have
processed to date. We show that our pulsar yield falls below earlier
predictions by approximately 25% (especially in the case of millisecond
pulsars), and discuss explanations for this discrepancy as well as future
adaptations in RFI mitigation and searching techniques which may address these
shortfalls.


  We evaluate the branching ratios of the radiative decays $B \to K^* \gamma $,
and $B \to K_1 \gamma $ in the framework of three-point function QCD sum rules.
We find: $ \Gamma(B \to K^* \gamma) / \Gamma(b \to s \gamma) = 0.17 \pm 0.05$
and $ \Gamma(B \to K_1 \gamma) / \Gamma(b \to s \gamma) = 0.30 \pm 0.15$. We
also study, in the infinite quark mass limit, the connection between the form
factor of the radiative $B \to K^* \gamma $ transition and the weak hadronic
form factors entering the semileptonic B-meson decays.


  We design a method to optimize the global mean first-passage time (GMFPT) of
multiple random walkers searching in complex networks for a general target,
without specifying the property of the target node. According to the Laplace
transformed formula of the GMFPT, we can equivalently minimize the overlap
between the probability distribution of sites visited by the random walkers. We
employ a mutation only genetic algorithm to solve this optimization problem
using a population of walkers with different starting positions and a
corresponding mutation matrix to modify them. The numerical experiments on two
kinds of random networks (WS and BA) show satisfactory results in selecting the
origins for the walkers to achieve minimum overlap. Our method thus provides
guidance for setting up the search process by multiple random walkers on
complex networks.


  We present an experimental study of single electron emission in ZEPLIN-III, a
two-phase xenon experiment built to search for dark matter WIMPs, and discuss
applications enabled by the excellent signal-to-noise ratio achieved in
detecting this signature. Firstly, we demonstrate a practical method for
precise measurement of the free electron lifetime in liquid xenon during normal
operation of these detectors. Then, using a realistic detector response model
and backgrounds, we assess the feasibility of deploying such an instrument for
measuring coherent neutrino-nucleus elastic scattering using the ionisation
channel in the few-electron regime. We conclude that it should be possible to
measure this elusive neutrino signature above an ionisation threshold of
$\sim$3 electrons both at a stopped pion source and at a nuclear reactor.
Detectable signal rates are larger in the reactor case, but the triggered
measurement and harder recoil energy spectrum afforded by the accelerator
source enable lower overall background and fiducialisation of the active
volume.


  The success of NLP systems often relies on the availability of large,
high-quality datasets. However, not all samples in these datasets are equally
valuable for learning, as some may be redundant or noisy. Several methods for
characterizing datasets based on model-driven meta-information (e.g., model's
confidence) have been developed, but the relationship and complementary effects
of these methods have received less attention. In this paper, we introduce
infoVerse, a universal framework for dataset characterization, which provides a
new feature space that effectively captures multidimensional characteristics of
datasets by incorporating various model-driven meta-information. infoVerse
reveals distinctive regions of the dataset that are not apparent in the
original semantic space, hence guiding users (or models) in identifying which
samples to focus on for exploration, assessment, or annotation. Additionally,
we propose a novel sampling method on infoVerse to select a set of data points
that maximizes informativeness. In three real-world applications (data pruning,
active learning, and data annotation), the samples chosen on infoVerse space
consistently outperform strong baselines in all applications. Our code and demo
are publicly available.


  We explore energy transfer in a generic three-level system, which is coupled
to three non-equilibrium baths. Built on the concept of quantum heat engine,
our three-level model describes non-equilibrium quantum processes including
light-harvesting energy transfer, nano-scale heat transfer, photo-induced
isomerization, and photovoltaics in double quantum-dots. In the context of
light-harvesting, the excitation energy is first pumped up by sunlight, then is
transferred via two excited states which are coupled to a phonon bath, and
finally decays to the ground state. The efficiency of this process is evaluated
by steady state analysis via a polaron-transformed master equation; thus a wide
range of the system-phonon coupling strength can be covered. We show that the
coupling with the phonon bath not only modifies the steady state, resulting in
population inversion, but also introduces a finite steady state coherence which
optimizes the energy transfer flux and efficiency. In the strong coupling
limit, the steady state coherence disappears and the efficiency approaches the
heat engine limit given by Scovil and Schultz-Dubois in Phys. Rew. Lett. 2, 262
(1959).


  The three flavor version of the Nambu-Jona-Lasinio chiral soliton model for
baryons is employed to calculate the twist-2 contribution to the polarized
nucleon structure function $g_1(x)$. In particular the role of the strange
quark degree of freedom as a collective excitation of the chiral soliton is
investigated in the context of flavor symmetry breaking. The model prediction
for $g_1(x)$ refers to a low momentum scale $Q_0^2$. The leading order
corrections to the scale dependence is computed along the QCD evolution program
allowing to compare with data from SLAC.


  Medical imaging has been employed to support medical diagnosis and treatment.
It may also provide crucial information to surgeons to facilitate optimal
surgical preplanning and perioperative management. Essentially, semi-automatic
organ and tumor segmentation has been studied by many researchers. Recently,
with the development of Deep Learning (DL) algorithms, automatic organ
segmentation has been gathered lots of attention from the researchers. This
paper addresses to propose the most efficient DL architectures for Liver
segmentation by adapting and comparing state-of-the-art DL frameworks, studied
in different disciplines. These frameworks are implemented and adapted into a
Commercial software, 'LiverVision'. It is aimed to reveal the most effective
and accurate DL architecture for fully automatic liver segmentation. Equal
conditions were provided to all architectures in the experiments so as to
measure the effectiveness of algorithms accuracy, and Dice coefficient metrics
were also employed to support comparative analysis. Experimental results prove
that 'U-Net' and 'SegNet' have been superior in line with the experiments
conducted considering the concepts of time, cost, and effectiveness.
Considering both architectures, 'SegNet' was observed to be more successful in
eliminating false-positive values. Besides, it was seen that the accuracy
metric used to measure effectiveness in image segmentation alone was not
enough. Results reveal that DL algorithms are able to automate organ
segmentation from DICOM images with high accuracy. This contribution is
critical for surgical preplanning and motivates author to apply this approach
to the different organs and field of medicine.


  We study BPS solitons in N=6 U(N) \times U(N) Chern-Simons-matter theory
deformed by an F-term mass. The F-term mass generically breaks N=6
supersymmetry down to N=2. At vacua, M2-branes are polarized into a fuzzy S^3
forming a spherical M5-brane with topology \mathbf{R}^{1,2} \times S^3. The
polarization is interpreted as Myers' dielectric effect caused by an
anti-self-dual 4-form flux T_4 in the eleven-dimensional supergravity. Assuming
a polarized M2-brane configuration, the model effectively reduces to the
well-known abelian Chern-Simons-Higgs model studied in detail by
Jackiw-Lee-Weinberg. We find that the potential for the fuzzy S^3 radius agrees
with the one calculated from the M5-brane point of view at large N. This
effective model admits not only BPS topological vortex and domain wall
solutions but also non-topological solitons that keep 1/4 of the manifest N=2
supersymmetry. We also comment on the reduction of our configuration to ten
dimensions.


  The linear programming (LP) bound of Delsarte can be applied to several
problems in various branches of mathematics. We describe a general Fourier
analytic method to get a slight improvement on this bound. We then apply our
method to the problem of mutually unbiased bases (MUBs) to prove that the
Fourier family $F(a,b)$ in dimension 6 cannot be extended to a full system of
MUBs.


  The Normal Means problem plays a fundamental role in many areas of modern
high-dimensional statistics, both in theory and practice. And the Empirical
Bayes (EB) approach to solving this problem has been shown to be highly
effective, again both in theory and practice. However, almost all EB treatments
of the Normal Means problem assume that the observations are independent. In
practice correlations are ubiquitous in real-world applications, and these
correlations can grossly distort EB estimates. Here, exploiting theory from
Schwartzman (2010), we develop new EB methods for solving the Normal Means
problem that take account of unknown correlations among observations. We
provide practical software implementations of these methods, and illustrate
them in the context of large-scale multiple testing problems and False
Discovery Rate (FDR) control. In realistic numerical experiments our methods
compare favorably with other commonly-used multiple testing methods.


  It is proved that fermions can acquire the mass through the additional
non-integrable exponential factor. For this propose the special vector
potential associated with the spinor field was introduced. Such a vector
potential has close relation with the triality property in Dirac spinors and
plays crucial role in the construction of massive term. It is shown that the
change in phase of a wavefunction round any closed curve with the possibility
of there being singularities in our vector potential will lead to the law of
quantization of physical constants including the mass. The triality properties
of Dirac's spinors are studied and it leads to a double covering vector
representation of Dirac spinor field. It is proved that massive Dirac equation
in the bosonic representation is self-dual.


  We propose a new fast randomized algorithm for interpolative decomposition of
matrices which utilizes CountSketch. We then extend this approach to the tensor
interpolative decomposition problem introduced by Biagioni et al. (J. Comput.
Phys. 281, pp. 116-134, 2015). Theoretical performance guarantees are provided
for both the matrix and tensor settings. Numerical experiments on both
synthetic and real data demonstrate that our algorithms maintain the accuracy
of competing methods, while running in less time, achieving at least an order
of magnitude speed-up on large matrices and tensors.


  Statistics New Zealand (Stats NZ) has committed unreservedly to an
administrative data first policy. Thus, all new methods used at Stats NZ are to
be viewed within this context and discussing strategies for using
administrative data is an integral part of every working day. As statistical
methodologists, the three authors were drawn into these discussions. Like most
methodologists, the authors see surveys and the publications of their results
as a process where estimation is the key tool to achieve the final goal of an
accurate statistical output. Randomness and sampling exists to support this
goal, and early on it was clear to us that the incoming it-is-what-it-is data
sources were not randomly selected. These sources were obviously biased and
thus would produce biased estimates. So, we set out to design a strategy to
deal with this issue. This led us to the concept of representativeness which is
closely related to statistical bias but has a wider context invoking both
randomness and judgement. The representativeness issue was the principal
question that we set out to answer. The necessary components that we gathered
for our solution are summarized in the paper.
  Keywords: Representativeness, Timeline Databases, Statistical Registers,
Estimation


  We exhibit an example of a line bundle M on a smooth complex projective
variety Y s.t. M satisfy Property N_p for some p, the p-module of a minimal
resolution of the ideal of the embedding of Y by M is nonzero and M^2 does not
satisfy Property N_p.


  Convolutional Neural Networks (CNN) have been a good solution for
understanding a vast image dataset. As the increased number of battery-equipped
electric vehicles is flourishing globally, there has been much research on
understanding which charge levels electric vehicle drivers would choose to
charge their vehicles to get to their destination without any prevention. We
implemented deep learning approaches to analyze the tabular datasets to
understand their state of charge and which charge levels they would choose. In
addition, we implemented the Image Generator for Tabular Dataset algorithm to
utilize tabular datasets as image datasets to train convolutional neural
networks. Also, we integrated other CNN architecture such as EfficientNet to
prove that CNN is a great learner for reading information from images that were
converted from the tabular dataset, and able to predict charge levels for
battery-equipped electric vehicles. We also evaluated several optimization
methods to enhance the learning rate of the models and examined further
analysis on improving the model architecture.


  For invasive breast cancer, immunohistochemical (IHC) techniques are often
used to detect the expression level of human epidermal growth factor receptor-2
(HER2) in breast tissue to formulate a precise treatment plan. From the
perspective of saving manpower, material and time costs, directly generating
IHC-stained images from Hematoxylin and Eosin (H&E) stained images is a
valuable research direction. Therefore, we held the breast cancer
immunohistochemical image generation challenge, aiming to explore novel ideas
of deep learning technology in pathological image generation and promote
research in this field. The challenge provided registered H&E and IHC-stained
image pairs, and participants were required to use these images to train a
model that can directly generate IHC-stained images from corresponding
H&E-stained images. We selected and reviewed the five highest-ranking methods
based on their PSNR and SSIM metrics, while also providing overviews of the
corresponding pipelines and implementations. In this paper, we further analyze
the current limitations in the field of breast cancer immunohistochemical image
generation and forecast the future development of this field. We hope that the
released dataset and the challenge will inspire more scholars to jointly study
higher-quality IHC-stained image generation.


  We give a characterization of transport-entropy inequalities in metric
spaces. As an application we deduce that such inequalities are stable under
bounded perturbation (Holley-Stroock perturbation Lemma).


  Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveys
including the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands
($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in the
stacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3,
21.4) respectively. The upper bound on the systematic uncertainty in the
photometric calibration across the sky is 7-12 millimag depending on the
bandpass. The systematic uncertainty of the astrometric calibration using the
Gaia frame comes from a comparison of the results with Gaia: the standard
deviation of the mean and median residuals ($ \Delta ra, \Delta dec $) are
(2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRS
system and the design of the PS1 surveys are described and an overview of the
resulting image and catalog data products and their basic characteristics are
described together with a summary of important results. The images, reduced
data products, and derived data products from the Pan-STARRS1 surveys are
available to the community from the Mikulski Archive for Space Telescopes
(MAST) at STScI.


  We discuss the allowed order parameter symmetries in multi-layer cuprates and
their physical consequences using highly non-specific forms of the inter- and
intra-plane interactions. Within this framework, the bi-layer case is discussed
in detail with particular attention paid to the role of small orthorhombic
distortions as would derive from the chains in YBCO or superlattice effects in
BSCCO. In the orthorhombic bi-layer case the (s,-s) state is of special
interest, since for a wide range of parameters this state exhibits pi phase
shifts in corner Josephson junction experiments. In addition, its transition
temperature is found to be insensitive to non-magnetic inter-plane disorder, as
would be present at the rare earth site in YBCO, for example. Of particular
interest, also, are the role of van Hove singularities which are seen to
stabilize states with d_{x^2 - y^2}-like symmetry, (as well as nodeless
s-states) and to elongate the gap functions along the four van Hove points,
thereby leading to a substantial region of gaplessness. We find that d_{x^2 -
y^2}-like states are general solutions for repulsive interactions; they possess
the fewest number of nodes and therefore the highest transition temperatures.
In this way, they should not be specifically associated with a spin fluctuation
driven pairing mechanism.


  The model atmosphere programs FASTWIND and CMFGEN are both elegantly designed
to perform non-LTE analyses of the spectra of hot massive stars, and include
sphericity and mass-loss. The two codes differ primarily in their approach
towards line blanketing, with CMFGEN treating all of the lines in the co-moving
frame and FASTWIND taking an approximate approach which speeds up execution
times considerably. Although both have been extensively used to model the
spectra of O-type stars, no studies have used the codes to independently model
the same spectra of the same stars and compare the derived physical properties.
We perform this task on ten O-type stars in the Magellanic Clouds. For the
late-type O supergiants, both CMFGEN and FASTWIND have trouble fitting some of
the He I lines, and we discuss causes and cures. We find that there is no
difference in the average effective temperatures found by the two codes for the
stars in our sample, although the dispersion is large, due primarily to the
various difficulties each code has with He I. The surface gravities determined
using FASTWIND are systematically lower by 0.12 dex compared to CMFGEN, a
result we attribute to the better treatment of electron scattering by CMFGEN.
This has implications for the interpretation of the origin of the so-called
mass discrepancy, as the masses derived by FASTWIND are on average lower than
inferred from stellar evolutionary models, while those found by CMFGEN are in
better agreement.


  We propose a novel framework for abnormal event detection in video that
requires no training sequences. Our framework is based on unmasking, a
technique previously used for authorship verification in text documents, which
we adapt to our task. We iteratively train a binary classifier to distinguish
between two consecutive video sequences while removing at each step the most
discriminant features. Higher training accuracy rates of the intermediately
obtained classifiers represent abnormal events. To the best of our knowledge,
this is the first work to apply unmasking for a computer vision task. We
compare our method with several state-of-the-art supervised and unsupervised
methods on four benchmark data sets. The empirical results indicate that our
abnormal event detection framework can achieve state-of-the-art results, while
running in real-time at 20 frames per second.


  Software Engineering courses play an important role for preparing students
with the right knowledge and attitude for software development in practice. The
implication is far reaching, as the quality of the software that we use
ultimately depends on the quality of the people that make them. Educating
Software Engineering, however, is quite challenging, as the subject is not
considered as most exciting by students, while teachers often have to deal with
exploding number of students. The EU project IMPRESS seeks to explore the use
of gamification in educating software engineering at the university level to
improve students' engagement and hence their appreciation for the taught
subjects. This paper presents the project, its objectives, and its current
progress.


  zero-shot learning is an essential part of computer vision. As a classical
downstream task, zero-shot semantic segmentation has been studied because of
its applicant value. One of the popular zero-shot semantic segmentation methods
is based on the generative model Most new proposed works added structures on
the same architecture to enhance this model. However, we found that, from the
view of causal inference, the result of the original model has been influenced
by spurious statistical relationships. Thus the performance of the prediction
shows severe bias. In this work, we consider counterfactual methods to avoid
the confounder in the original model. Based on this method, we proposed a new
framework for zero-shot semantic segmentation. Our model is compared with
baseline models on two real-world datasets, Pascal-VOC and Pascal-Context. The
experiment results show proposed models can surpass previous confounded models
and can still make use of additional structures to improve the performance. We
also design a simple structure based on Graph Convolutional Networks (GCN) in
this work.


  We present cosmological solutions for (1+3+n)-dimensional steady state
universe in dilaton gravity with an arbitrary dilaton coupling constant w and
exponential dilaton self-interaction potentials in the string frame. We focus
particularly on the class in which the 3-space expands with a time varying
deceleration parameter. We discuss the number of the internal dimensions and
the value of the dilaton coupling constant to determine the cases that are
consistent with the observed universe and the primordial nucleosynthesis. The
3-space starts with a decelerated expansion rate and evolves into accelerated
expansion phase subject to the values of w and n, but ends with a Big Rip in
all cases. We discuss the cosmological evolution in further detail for the
cases w=1 and w=1/2 that permit exact solutions. We also comment on how the
universe would be conceived by an observer in four dimensions who is unaware of
the internal dimensions and thinks that the conventional general relativity is
valid at cosmological scales.


  We study the problem of change point localization in dynamic networks models.
We assume that we observe a sequence of independent adjacency matrices of the
same size, each corresponding to a realization of an unknown inhomogeneous
Bernoulli model. The underlying distribution of the adjacency matrices are
piecewise constant, and may change over a subset of the time points, called
change points. We are concerned with recovering the unknown number and
positions of the change points. In our model setting we allow for all the model
parameters to change with the total number of time points, including the
network size, the minimal spacing between consecutive change points, the
magnitude of the smallest change and the degree of sparsity of the networks. We
first identify a region of impossibility in the space of the model parameters
such that no change point estimator is provably consistent if the data are
generated according to parameters falling in that region. We propose a
computationally-simple algorithm for network change point localization, called
Network Binary Segmentation, that relies on weighted averages of the adjacency
matrices. We show that Network Binary Segmentation is consistent over a range
of the model parameters that nearly cover the complement of the impossibility
region, thus demonstrating the existence of a phase transition for the problem
at hand. Next, we devise a more sophisticated algorithm based on singular value
thresholding, called Local Refinement, that delivers more accurate estimates of
the change point locations. Under appropriate conditions, Local Refinement
guarantees a minimax optimal rate for network change point localization while
remaining computationally feasible.


  The research on pattern-avoidance has yielded so far limited knowledge on
Wilf-ordering of permutations. The Stanley-Wilf limits sqrt[n](|S_n(tau)|) and
further works suggest asymptotic ordering of layered versus monotone patterns.
Yet, Bona has provided the only known up to now result of its type on ordering
of permutations: |S_n(1342)|<|S_n(1234)|<|S_n(1324)| for n>6. We give a
different proof of this result by ordering S_3 up to the stronger
shape-Wilf-order: |S_Y(213)|<=|S_Y(123)|<=|S_Y(312)| for any Young diagram Y,
derive as a consequence that |S_Y(k+2,k+1,k+3,tau)|<=|S_Y(k+1,k+2,k+3,tau)|<=
|S_Y(k+3,k+1,k+2,tau)| for any tau in S_k, and find out when equalities are
obtained. (In particular, for specific Y's we find out that
|S_Y(123)|=|S_Y(312)| coincide with every other Fibonacci term.) This
strengthens and generalizes Bona's result to arbitrary length permutations.
While all length-3 permutations have been shown in numerous ways to be
Wilf-equivalent, the current paper distinguishes between and orders these
permutations by employing all Young diagrams. This opens up the question of
whether shape-Wilf-ordering of permutations, or some generalization of it, is
not the ``true'' way of approaching pattern-avoidance ordering.


  We discuss experimental situations that consist of multiple preparation and
measurement stages. This leads us to a new approach to quantum mechanics. In
particular, we introduce the idea of multi-time quantum states which are the
appropriate tools for describing these experimental situations. We also
describe multi-time measurements and discuss their relation to multi-time
states. A consequence of our new formalism is to put states and operators on an
equal footing. Finally we discuss the implications of our new approach to
quantum mechanics for the problem of the flow of time.


  The new minimal supersymmetric standard model (nMSSM), a variant of the
general next to minimal supersymmetric standard model (NMSSM) without $Z_3$
symmetry, features a naturally light singlino with a mass below 75 GeV. In
light of the new constraints from LHC Run-1 on the Higgs couplings, sparticles
searches and flavour observables, we define the parameter space of the model
which is compatible with both collider and dark matter (DM) properties. Among
the regions compatible with these constraints, implemented through NMSSMTools,
SModelS and MadAnalysis 5, only one with a singlino lightest supersymmetric
particle (LSP) with a mass around 5 GeV can explain all the DM abundance of the
universe, while heavier mixed singlinos can only form one of the DM components.
Typical collider signatures for each region of the parameter space are
investigated. In particular, the decay of the 125 GeV Higgs into light scalars
and/or pseudoscalars and the decay of the heavy Higgs into charginos and
neutralinos, provide distinctive signatures of the model. Moreover, the
sfermion decays usually proceed through heavier neutralinos rather than
directly into the LSP, as the couplings to the singlino are suppressed. We also
show that direct detection searches are complementary to collider ones, and
that a future ton-scale detector could completely probe the region of parameter
space with a LSP mass around 65 GeV.


  The current paper is concerned with the existence of spreading speeds and
linear determinacy for two species competition systems with nonlocal dispersal
in time and space periodic habitats. The notion of spreading speed intervals
for such a system is first introduced via the natural features of spreading
speeds. The existence and lower bounds of spreading speed intervals are then
established. When the periodic dependence of the habitat is only on the time
variable, the existence of a single spreading speed is proved. It also shows
that, under certain conditions, the spreading speed interval in any direction
is a singleton, and, moreover, the linear determinacy holds.


  We present the Supernova X-ray Database (SNaX), a compilation of the X-ray
data from young supernovae (SNe). The database includes the X-ray flux and
luminosity of young SNe, days to years after outburst. The original goal and
intent were to present a database of Type IIn SNe. After having accomplished
this we are slowly expanding it to include all SNe for which published data are
available. The interface allows one to search for SNe using various criteria,
plot all or selected data-points, and download both the data and the plot. The
plotting facility allows for significant customization. There is also a
facility for the user to submit data that can be directly incorporated into the
database. We include an option to fit the decay of any given SN lightcurve with
a power-law. The database includes a conversion of most datapoints to a common
0.3-8 keV band so that SN lightcurves may be directly compared with each other.
A mailing list has been set up to disseminate information about the database.
We outline the structure and function of the database, describe its various
features and outline the plans for future expansion.


  Given an n-tuple of positive real numbers, Konno defines an algebraic variety
called a hyperpolygon space, a hyperkahler analogue of the Kahler variety
parametrizing spacial polygons with fixed edge lengths. The ordinary polygon
space can be interpreted as the moduli space of stable representations of a
certain quiver with fixed dimension vector; from this point of view, the
hyperpolygon space is the hyperkahler quiver variety defined by Nakajima. A
quiver variety admits a natural action of the nonzero complex numbers, and the
union of the precompact orbits is called the core. We study the components of
the core of the hyperpolygon space, interpreting each one as a moduli space of
pairs of spatial polygons with certain properties. Konno gives a presentation
of the cohomology ring of the hyperpolygon space; we extend this result by
computing the circle-equivariant cohomology ring, as well as the ordinary and
equivariant cohomology rings of the core components.