  In this paper, we consider the problem of recovering a compactly supported
multivariate function from a collection of pointwise samples of its Fourier
transform taken nonuniformly. We do this by using the concept of weighted
Fourier frames. A seminal result of Beurling shows that sample points give rise
to a classical Fourier frame provided they are relatively separated and of
sufficient density. However, this result does not allow for arbitrary
clustering of sample points, as is often the case in practice. Whilst keeping
the density condition sharp and dimension independent, our first result removes
the separation condition and shows that density alone suffices. However, this
result does not lead to estimates for the frame bounds. A known result of
Groechenig provides explicit estimates, but only subject to a density condition
that deteriorates linearly with dimension. In our second result we improve
these bounds by reducing the dimension dependence. In particular, we provide
explicit frame bounds which are dimensionless for functions having compact
support contained in a sphere. Next, we demonstrate how our two main results
give new insight into a reconstruction algorithm---based on the existing
generalized sampling framework---that allows for stable and quasi-optimal
reconstruction in any particular basis from a finite collection of samples.
Finally, we construct sufficiently dense sampling schemes that are often used
in practice---jittered, radial and spiral sampling schemes---and provide
several examples illustrating the effectiveness of our approach when tested on
these schemes.


  Background: Psoriasis is a multifactorial chronic inflammatory disorder of
the skin with significant morbidity, characterized by hyper proliferation of
the epidermis. Even though psoriasis etiology is not fully understood, it is
believed to be multifactorial with numerous key components. Methods: In order
to cast light on the complex molecular interactions in psoriasis vulgaris at
both protein-protein interactions and transcriptomics levels, we analyzed a set
of microarray gene expression analysis consisting of 170 paired lesional and
non-lesional samples. Afterwards, a network analysis was conducted on
protein-protein interaction network of differentially expressed genes based on
micro- and macro-level network metrics at a systemic level standpoint. Results:
We found 17 top communicative genes, all of which experimentally proven to be
pivotal in psoriasis were identified in two modules, namely, cell cycle and
immune system. Intra- and inter-gene interaction subnetworks from the top
communicative genes might provide further insight into the corresponding
characteristic mechanisms. Conclusions: Potential gene combinations for
therapeutic/diagnostics purposes were identified. Moreover, our proposed
pipeline could be of interest to a broader range of biological network analysis
studies.


  The iDian (previously named as the Operation Agent System) is a framework
designed to enable computer users to operate software in natural language.
Distinct from current speech-recognition systems, our solution supports
format-free combinations of orders, and is open to both developers and
customers. We used a multi-layer structure to build the entire framework,
approached rule-based natural language processing, and implemented demos
narrowing down to Windows, text-editing and a few other applications. This
essay will firstly give an overview of the entire system, and then scrutinize
the functions and structure of the system, and finally discuss the prospective
de-velopment, esp. on-line interaction functions.


  We present an overview on the development and characterization of multiscale
laser processing optics for versatile material modifications across more than
six orders of magnitude. Starting with solutions for micromachining we present
high-NA microscope objectives creating sub-wavelength material modifications on
macroscopic scales with highest peak intensities. Moving on to the millimeter
range, the adaptability and scalability of scanning optics is examined for
large-area machining. Finally, we explore line beam optics in the meter range,
evaluating their use in uniform material processing using average powers above
100kW. This study provides an insight into the design and performance
characteristics of such optics and demonstrates their potential in advanced
laser processing.


  As the luminosity of an accreting black hole drops to a few percent of
Eddington, the spectrum switches from the familiar soft state to a hard state
that is well-described by a distended and tenuous advection-dominated accretion
flow (ADAF). An ADAF is a poor radiator, and the ion temperature can approach
10^{12} K near the center, although the electrons are cooler, with their
temperature typically capped at ~10^{9-11} K. The foundational papers predicted
that the large thermal energy in an ADAF would drive strong winds and jets, as
later observed and also confirmed in computer simulations. Of chief interest,
however, is the accreting gas that races inward. It carries the bulk of the
accretion energy as stored thermal energy, which vanishes without a trace as
the gas passes through the hole's event horizon. One thus expects black holes
in the ADAF regime to be unusually faint. Indeed, this is confirmed by a
comparison of accreting stellar-mass black holes and neutron stars, which
reside in very similar transient X-ray binary systems. The black holes are on
average observed to be fainter by a factor of ~100-1000. The natural
explanation is that a neutron star must radiate the advected thermal energy
from its surface, whereas a black hole can hide the energy behind its event
horizon. The case for an event horizon in Sagittarius A*, which is immune to
caveats on jet outflows and is furthermore independent of the ADAF model, is
especially compelling. These two lines of evidence for event horizons are
impervious to counterarguments that invoke strong gravity or exotic stars.


  Spatial data infrastructure (SDI) is the infrastructure that facilitates the
discovery, access, management, distribution, reuse, and preservation of digital
geospatial resources. These resources may include maps, data, geospatial
services, and tools. As cyberinfrastructures, SDIs are similar to other
infrastructures, such as water supplies and transportation networks, since they
play fundamental roles in many aspects of the society. These roles have become
even more significant in today's big data age, when a large volume of
geospatial data and Web services are available. From a technological
perspective, SDIs mainly consist of data, hardware, and software. However, a
truly functional SDI also needs the efforts of people, supports from
organizations, government policies, data and software standards, and many
others. In this chapter, we will present the concepts and values of SDIs, as
well as a brief history of SDI development in the U.S. We will also discuss the
components of a typical SDI, and will specifically focus on three key
components: geoportals, metadata, and search functions. Examples of the
existing SDI implementations will also be discussed.


  The theoretical results are presented showing that strain-induced anisotropy
of graphene spectrum gives rise to the valley currents under the illumination
by normally incident light. The currents of the two graphene valleys are
mutually compensated providing zero net electric current. The magnitude and
direction of the valley currents are determined by the parameters of strain and
light polarization. For not too high photon energy strain-induced valley
current exceed that due to intrinsic warping of the graphene spectrum which
suggests feasibility of strain-mediated valleytronics.


  Flow cytometry (FC) is a single-cell profiling platform for measuring the
phenotypes of individual cells from millions of cells in biological samples. FC
employs high-throughput technologies and generates high-dimensional data, and
hence algorithms for analyzing the data represent a bottleneck. This
dissertation addresses several computational challenges arising in modern
cytometry while mining information from high-dimensional and high-content
biological data. A collection of combinatorial and statistical algorithms for
locating, matching, prototyping, and classifying cellular populations from
multi-parametric FC data is developed.
  The algorithmic pipeline, flowMatch, developed in this dissertation consists
of five well-defined algorithmic modules to (1) transform data to stabilize
within-population variance, (2) identify cell populations by robust clustering
algorithms, (3) register cell populations across samples, (4) encapsulate a
class of samples with templates, and (5) classify samples based on their
similarity with the templates. Components of flowMatch can work independently
or collaborate with each other to perform the complete data analysis. flowMatch
is made available as an open-source R package in Bioconductor.
  We have employed flowMatch for classifying leukemia samples, evaluating the
phosphorylation effects on T cells, classifying healthy immune profiles, and
classifying the vaccination status of HIV patients. In these analyses, the
pipeline is able to reach biologically meaningful conclusions quickly and
efficiently with the automated algorithms. The algorithms included in flowMatch
can also be applied to problems outside of flow cytometry such as in microarray
data analysis and image recognition. Therefore, this dissertation contributes
to the solution of fundamental problems in computational cytometry and related
domains.


  Temperature stabilization of oil and gas wells is used to ensure stability
and prevent deformation of a subgrade estuary zone. In this work, we consider
the numerical simulation of thermal stabilization using vertical seasonal
freezing columns.
  A mathematical model of such problems is described by a time-dependent
temperature equation with phase transitions from water to ice. The resulting
equation is a standard nonlinear parabolic equation.
  Numerical implementation is based on the finite element method using the
package Fenics. After standard purely implicit approximation in time and simple
linearization, we obtain a system of linear algebraic equations. Because the
size of freezing columns are substantially less than the size of the modeled
area, we obtain mesh refinement near columns. Due to this, we get a large
system of equations which are solved using high performance computing systems.


  Architectural monitoring and adaptation allows self-management capabilities
of autonomic systems to realize more powerful adaptation steps, which observe
and adjust not only parameters but also the software architecture. However,
monitoring as well as adaptation of the architecture of a running system in
addition to the parameters are considerably more complex and only rather
limited and costly solutions are available today. In this paper we propose a
model-driven approach to ease the development of architectural monitoring and
adaptation for autonomic systems. Using meta models and model transformation
techniques, we were able to realize an incremental synchronization between the
run-time system and models for different self-management activities. The
synchronization might be triggered when needed and therefore the activities can
operate concurrently.


  Shifting to a lexicalized grammar reduces the number of parsing errors and
improves application results. However, such an operation affects a syntactic
parser in all its aspects. One of our research objectives is to design a
realistic model for grammar lexicalization. We carried out experiments for
which we used a grammar with a very simple content and formalism, and a very
informative syntactic lexicon, the lexicon-grammar of French elaborated by the
LADL. Lexicalization was performed by applying the parameterized-graph
approach. Our results tend to show that most information in the lexicon-grammar
can be transferred into a grammar and exploited successfully for the syntactic
parsing of sentences.


  We present a measurement of phonon propagation in a silicon wafer utilizing
an array of frequency-multiplexed superconducting resonators coupled to a
single transmission line. The electronic readout permits fully synchronous
array sampling with a per-resonator bandwidth of 1.2 MHz, allowing sub-$\mu$s
array imaging. This technological achievement is potentially vital in a variety
of low-temperature applications, including single-photon counting,
quantum-computing and dark-matter searches.


  This paper is an H band interferometric examination of Arcturus, a star
frequently used as a spatial and spectral calibrator. Using the IOTA 3
telescope interferometer, we performed spectro-interferometric observation
(R~35) of Arcturus. Atmospheric models and prescriptions were fitted to the
data to derive the brightness distribution of the photosphere. Image
reconstruction was also obtained using two software algorithms: Wisard and
Mira. An achromatic power law proved to be a good model of the brightness
distribution, with a limb darkening compatible with the one derived from
atmospheric model simulations using our Marcs model. A Rosseland diameter of
21.05+/-0.21 was derived, corresponding to an effective temperature of
T_eff=4295+/-26 K. No companion was detected from the closure phases, with an
upper limit on the brightness ratio of 8e-4 at 1AU. Dynamic range at such
distance from the photosphere was established at 1.5e-4 (1sigma rms). An upper
limit of 1.7e-3 was also derived for the level of brightness asymmetries
present on the photosphere.


  In this paper, we provide variation of constants formulae for linear
(forward) stochastic Volterra integral equations (SVIEs, for short) and linear
Type-II backward stochastic Volterra integral equations (BSVIEs, for short) in
the usual It\^{o}'s framework. For these purposes, we define suitable classes
of stochastic Volterra kernels and introduce new notions of the products of
adapted $L^2$-processes. Observing the algebraic properties of the products, we
obtain the variation of constants formulae by means of the corresponding
resolvent. Our framework includes SVIEs with singular kernels such as
fractional stochastic differential equations. Also, our results can be applied
to general classes of SVIEs and BSVIEs with infinitely many iterated stochastic
integrals. The duality principle between generalized SVIEs and generalized
BSVIEs is also proved.


  In this note we show that the nilpotence conjecture for toric varieties is
true over any regular coefficient ring containing Q.


  Plasma rotation plays a large role in determining the size and shape of
Saturn's disc-like magnetosphere. A magnetosphere more confined to the equator
in the polar regions is expected as a result of the interaction between this
type of obstacle and the solar wind. In addition, at times away from equinox, a
north-south asymmetry is expected where the magnetopause will be further
confined in one hemisphere but less confined in the opposite hemisphere.
Examining the extent of this confinement has been limited by a lack of
high-latitude spacecraft observations. Here, for the first time, direct
evidence for polar confinement of Saturn's magnetopause has been observed using
in-situ data obtained by the Cassini spacecraft during a series of
high-inclination orbits between 2007 and 2009. Following techniques established
by previous authors, we assume an equilibrium between the solar wind dynamic
pressure (which Cassini is generally unable to measure directly), and the
magnetic plus plasma pressure inside the magnetosphere. This assumption thus
allows us to estimate the upstream solar wind dynamic pressure ($D_P$) for a
series of magnetopause crossings, and hence to determine the expected location
and global shape of the magnetopause as a function of $D_P$. A clear divergence
from the familiar axisymmetric models of the magnetosphere is observed which
may be characterised by an 'apparent flattening parameter' of 0.81+0.03/-0.06
(representing a simple dilation of the nominal axisymmetric boundary along the
$Z_{KSM}$ axis such that the extent is reduced by 19% in this direction). This
figure is insensitive to variations in $D_P$.


  We study a modification of the fractional analogue of the Brownian meander,
which is Brownian motion conditioned to be positive on the time interval
${[0,1]}$. More precisely, we determine the weak limit of a fractional Brownian
motion which is penalized -- instead of being killed -- when leaving the
positive half-axis. In the Brownian case, we give a representation of the
limiting process in terms of an explicit SDE and compare it to the SDE
fulfilled by the Brownian meander.


  The observations of the total electronic component and the positron fraction
in cosmic rays by the FERMI, HESS, ATIC, and PAMELA instruments are studied
with analytical propagation models, both for a set of discrete sources and for
a spatially smooth source distribution. The positron fraction over the entire
energy range of ~1-100 GeV is shown to fit with the nested leaky box model. We
derive the spectrum of electrons in cosmic rays arising from direct
acceleration by the sources and discuss the narrow spectral feature in the
spectrum.


  Machine learning can provide deep insights into data, allowing machines to
make high-quality predictions and having been widely used in real-world
applications, such as text mining, visual classification, and recommender
systems. However, most sophisticated machine learning approaches suffer from
huge time costs when operating on large-scale data. This issue calls for the
need of {Large-scale Machine Learning} (LML), which aims to learn patterns from
big data with comparable performance efficiently. In this paper, we offer a
systematic survey on existing LML methods to provide a blueprint for the future
developments of this area. We first divide these LML methods according to the
ways of improving the scalability: 1) model simplification on computational
complexities, 2) optimization approximation on computational efficiency, and 3)
computation parallelism on computational capabilities. Then we categorize the
methods in each perspective according to their targeted scenarios and introduce
representative methods in line with intrinsic strategies. Lastly, we analyze
their limitations and discuss potential directions as well as open issues that
are promising to address in the future.


  We demonstrate that a self-complementary checkerboard-like metasurface works
as a broadband coherent perfect absorber (CPA) when symmetrically illuminated
by two counter-propagating incident waves. A theoretical analysis based on wave
interference and results of numerical simulations of the proposed metasurface
are provided. In addition, we experimentally demonstrate the proposed CPA in
the terahertz regime by using a time-domain spectroscopy technique. We observe
that the metasurface can work as a CPA below its lowest diffraction frequency.
The size of the absorptive areas of the proposed CPA can be much smaller than
the incident wavelength. Unlike conventional CPAs, the presented one
simultaneously achieves the broadband operation and energy concentration of
electromagnetic waves at the deep-subwavelength scale.


  For normalized sums $Z_n$ of i.i.d. random variables, we explore necessary
and sufficient conditions which guarantee the normal approximation with respect
to the R\'enyi divergence of infinite order. In terms of densities $p_n$ of
$Z_n$, this is a strengthened variant of the local limit theorem taking the
form $\sup_x (p_n(x) - \varphi(x))/\varphi(x) \rightarrow 0$ as $n \rightarrow
\infty$.


  Grammar compression represents a string as a context free grammar. Achieving
compression requires encoding such grammar as a binary string; there are a few
commonly used encodings. We bound the size of practically used encodings for
several heuristical compression methods, including \RePair and \Greedy
algorithms: the standard encoding of \RePair, which combines entropy coding and
special encoding of a grammar, achieves $1.5|S|H_k(S)$, where $H_k(S)$ is
$k$-th order entropy of $S$. We also show that by stopping after some iteration
we can achieve $|S|H_k(S)$. This is particularly interesting, as it explains a
phenomenon observed in practice: introducing too many nonterminals causes the
bit-size to grow. We generalize our approach to other compression methods like
\Greedy and a wide class of irreducible grammars as well as to other
practically used bit encodings (including naive, which uses fixed-length
codes). Our approach not only proves the bounds but also partially explains why
\Greedy and \RePair are much better in practice than other grammar based
methods. In some cases we argue that our estimations are optimal. The tools
used in our analysis are of independent interest: we prove the new, optimal,
bounds on the zeroth order entropy of parsing of a string.


  Use case modeling is very popular to represent the functionality of the
system to be developed, and it consists of two parts: use case diagram and use
case description. Use case descriptions are written in structured natural
language (NL), and the usage of NL can lead to poor descriptions such as
ambiguous, inconsistent and/or incomplete descriptions, etc. Poor descriptions
lead to missing requirements and eliciting incorrect requirements as well as
less comprehensiveness of produced use case models. This paper proposes a
technique to automate detecting bad smells of use case descriptions, symptoms
of poor descriptions. At first, to clarify bad smells, we analyzed existing use
case models to discover poor use case descriptions concretely and developed the
list of bad smells, i.e., a catalogue of bad smells. Some of the bad smells can
be refined into measures using the Goal-Question-Metric paradigm to automate
their detection. The main contribution of this paper is the automated detection
of bad smells. We have implemented an automated smell detector for 22 bad
smells at first and assessed its usefulness by an experiment. As a result, the
first version of our tool got a precision ratio of 0.591 and recall ratio of
0.981.


  Semantic role labeling (SRL) is the task of identifying the
predicate-argument structure of a sentence. It is typically regarded as an
important step in the standard NLP pipeline. As the semantic representations
are closely related to syntactic ones, we exploit syntactic information in our
model. We propose a version of graph convolutional networks (GCNs), a recent
class of neural networks operating on graphs, suited to model syntactic
dependency graphs. GCNs over syntactic dependency trees are used as sentence
encoders, producing latent feature representations of words in a sentence. We
observe that GCN layers are complementary to LSTM ones: when we stack both GCN
and LSTM layers, we obtain a substantial improvement over an already
state-of-the-art LSTM SRL model, resulting in the best reported scores on the
standard benchmark (CoNLL-2009) both for Chinese and English.


  The Schatten-p quasi-norm $(0<p<1)$ is usually used to replace the standard
nuclear norm in order to approximate the rank function more accurately.
However, existing Schatten-p quasi-norm minimization algorithms involve
singular value decomposition (SVD) or eigenvalue decomposition (EVD) in each
iteration, and thus may become very slow and impractical for large-scale
problems. In this paper, we first define two tractable Schatten quasi-norms,
i.e., the Frobenius/nuclear hybrid and bi-nuclear quasi-norms, and then prove
that they are in essence the Schatten-2/3 and 1/2 quasi-norms, respectively,
which lead to the design of very efficient algorithms that only need to update
two much smaller factor matrices. We also design two efficient proximal
alternating linearized minimization algorithms for solving representative
matrix completion problems. Finally, we provide the global convergence and
performance guarantees for our algorithms, which have better convergence
properties than existing algorithms. Experimental results on synthetic and
real-world data show that our algorithms are more accurate than the
state-of-the-art methods, and are orders of magnitude faster.


  Distributed quantum computing provides a viable approach towards scalable
quantum computation, which relies on nonlocal quantum gates to connect distant
quantum nodes, to overcome the limitation of a single device. However, such an
approach has only been realized within single nodes or between nodes separated
by a few tens of meters, preventing the target of harnessing computing
resources in large-scale quantum networks. Here, we demonstrate distributed
quantum computing between two nodes spatially separated by 7.0 km, using
stationary qubits based on multiplexed quantum memories, flying qubits at
telecom wavelengths, and active feedforward control based on field-deployed
fiber. Specifically, we illustrate quantum parallelism by implementing
Deutsch-Jozsa algorithm and quantum phase estimation algorithm between the two
remote nodes. These results represent the first demonstration of distributed
quantum computing over metropolitan-scale distances and lay the foundation for
the construction of large-scale quantum computing networks relying on existing
fiber channels.


  A practical autonomous driving system urges the need to reliably and
accurately detect vehicles and persons. In this report, we introduce a
state-of-the-art 2D object detection system for autonomous driving scenarios.
Specifically, we integrate both popular two-stage detector and one-stage
detector with anchor free fashion to yield a robust detection. Furthermore, we
train multiple expert models and design a greedy version of the auto ensemble
scheme that automatically merges detections from different models. Notably, our
overall detection system achieves 70.28 L2 mAP on the Waymo Open Dataset v1.2,
ranking the 2nd place in the 2D detection track of the Waymo Open Dataset
Challenges.


  Context. HD 172555 is a young A7 star belonging to the Beta Pictoris Moving
Group that harbours a debris disc. The Spitzer IRS spectrum of the source
showed mid-IR features such as silicates and glassy silica species, indicating
the presence of a warm dust component with small grains, which places HD 172555
among the small group of debris discs with such properties. The IRS spectrum
also shows a possible emission of SiO gas. Aims. We aim to study the dust
distribution in the circumstellar disc of HD 172555 and to asses the presence
of gas in the debris disc. Methods. As part of the GASPS Open Time Key
Programme, we obtained Herschel-PACS photometric and spectroscopic observations
of the source. We analysed PACS observations of HD 172555 and modelled the
Spectral Energy Distribution (SED) with a modified blackbody and the gas
emission with a two-level population model with no collisional de-excitation.
Results. We report for the first time the detection of OI atomic gas emission
at 63.18 microns in the HD 172555 circumstellar disc. We detect excesses due to
circumstellar dust toward HD 172555 in the three photometric bands of PACS (70,
100, and 160 microns). We derive a large dust particle mass of 4.8e-4 Earth
masses and an atomic oxygen mass of 2.5e-2*R^2 Earth masses, where R in AU is
the separation between the star and the inner disc. Thus, most of the detected
mass of the disc is in the gaseous phase.


  Important developments in fault-tolerant quantum computation using the
braiding of anyons have placed the theory of braid groups at the very
foundation of topological quantum computing. Furthermore, the realization by
Kauffman and Lomonaco that a specific braiding operator from the solution of
the Yang-Baxter equation, namely the Bell matrix, is universal implies that in
principle all quantum gates can be constructed from braiding operators together
with single qubit gates. In this paper we present a new class of braiding
operators from the Temperley-Lieb algebra that generalizes the Bell matrix to
multi-qubit systems, thus unifying the Hadamard and Bell matrices within the
same framework. Unlike previous braiding operators, these new operators
generate {\it directly}, from separable basis states, important entangled
states such as the generalized Greenberger-Horne-Zeilinger states, cluster-like
states, and other states with varying degrees of entanglement.


  One proposed formation channel for stellar mass black holes (BHs) is through
hierarchical mergers of smaller BHs. Repeated mergers between comparable mass
BHs leave an imprint on the spin of the resulting BH, since the final BH spin
is largely determined by the orbital angular momentum of the binary. We find
that for stellar mass BHs forming hierarchically the distribution of spin
magnitudes is universal, with a peak at $a \sim 0.7$ and little support below
$a \sim 0.5$. We show that the spin distribution is robust against changes to
the mass ratio of the merging binaries, the initial spin distribution of the
first generation of BHs, and the number of merger generations. While we assume
an isotropic distribution of initial spin directions, spins that are
preferentially aligned or antialigned do not qualitatively change our results.
We also consider a "cluster catastrophe" model for BH formation in which we
allow for mergers of arbitrary mass ratios and show that this scenario predicts
a unique spin distribution that is similar to the universal distribution
derived for major majors. We explore the ability of spin measurements from
ground-based gravitational-wave (GW) detectors to constrain hierarchical merger
scenarios. We apply a hierarchical Bayesian mixture model to mock GW data and
argue that the fraction of BHs that formed through hierarchical mergers will be
constrained with $\mathcal{O}(100)$ LIGO binary black hole detections, while
with $\mathcal{O}(10)$ detections we could falsify a model in which all
component BHs form hierarchically.


  We describe a resonator based optical gyroscope whose sensitivity for
measuring absolute rotation is enhanced via use of the anomalous dispersion
characteristic of superluminal light propagation. The enhancement is given by
the inverse of the group index, saturating to a bound determined by the group
velocity dispersion. We also show how the offsetting effect of the concomitant
broadening of the resonator linewidth may be circumvented by using an active
cavity. For realistic conditions, the enhancement factor is as high as 106. We
also show how normal dispersion used for slow light can enhance relative
rotation sensing in a specially designed Sagnac interferometer, with the
enhancement given by the slowing factor


  In this paper, we present an ensemble approach for the NL4Opt competition
subtask 1(NER task). For this task, we first fine tune the pretrained language
models based on the competition dataset. Then we adopt differential learning
rates and adversarial training strategies to enhance the model generalization
and robustness. Additionally, we use a model ensemble method for the final
prediction, which achieves a micro-averaged F1 score of 93.3% and attains the
second prize in the NER task.


  The Galaxy Zoo has provided morphological data on many galaxies. Several
biases have been identified in the Galaxy Zoo data. Here we report on a newly
discovered selection effect: astronomers interested in studying spiral galaxies
may select a set of spiral galaxies based upon a threshold in spirality (the
fraction of Galaxy Zoo humans who report seeing spiral structure). SpArcFiRe is
an automated tool that decomposes a spiral galaxy into its constituent spiral
arms, providing objective, quantitative data on their structure. SpArcFiRe
measures the pitch angle of spiral arms. We have observed that when selecting a
set of spiral galaxies based on a threshold on spirality, the pitch angle of
spiral arms appear increase with redshift. We hypothesize that this is a
selection effect: tightly-wound spiral arms become less visible as images
degrade with increasing redshift, leading to fewer such galaxies being included
in the sample at higher redshifts. We corroborate this hypothesis by
artificially degrading images of nearby galaxies, then using a machine learning
algorithm trained on Galaxy Zoo data to provide a spirality for each
artificially degraded image. It correctly predicts that spirality decreases as
image quality degrades. Thus, the mean pitch angle of those galaxies remaining
above the spirality threshold is higher than those eliminated by the selection
effect. This demonstrates that users who select samples of galaxies using a
threshold of Galaxy Zoo votes must carefully consider the possibility of
selection effects on morphological measures, even if the measure itself is
believed to be objective and unbiased. Finally, we also perform an empirical
sensitivity analysis to demonstrate that SpArcFiRe's output changes in a smooth
and predictable fashion to changes in its internal algorithmic parameters.


  Recently, an analytical expression for the system size dependence and
direction-dependence of self-diffusion coefficients for neat liquids due to
hydrodynamic interactions has been derived for molecular dynamics (MD)
simulations using orthorhombic unit cells. Based on this description, we show
that for systems with a "magic" box length ratio of
$L_z/L_x\!=\!L_z/L_y\!=\!2.7933596497$ the computed self-diffusion coefficients
$D_x$ and $D_y$ in $x$- and $y$-direction become system-size independent and
represent the true self-diffusion coefficient $D_0\!=\!(D_x+D_y)/2$. Moreover,
by using this particular box geometry, the viscosity can be determined with a
reasonable degree of accuracy from the difference of components of the
diffusion coefficients in $x$-,$y$- and $z$-direction using the simple
expression $\eta\!=\!k_\mathrm{B}T\cdot 8.1711245653/[3\pi
L_z(D_{x}+D_{y}-2D_z)]$, where $k_\mathrm{B}$ denotes Boltzmann's constant, and
$T$ represents the temperature. MD simulations of TIP4P/2005 water for various
system-sizes using both orthorhombic and cubic box geometries are used to test
the approach.


  Determinantal Point Processes (DPPs) are a widely used probabilistic model
for negatively correlated sets. DPPs have been successfully employed in Machine
Learning applications to select a diverse, yet representative subset of data.
In seminal work on DPPs in Machine Learning, Kulesza conjectured in his PhD
Thesis (2011) that the problem of finding a maximum likelihood DPP model for a
given data set is NP-complete.
  In this work we prove Kulesza's conjecture. In fact, we prove the following
stronger hardness of approximation result: even computing a
$\left(1-O(\frac{1}{\log^9{N}})\right)$-approximation to the maximum
log-likelihood of a DPP on a ground set of $N$ elements is NP-complete. At the
same time, we also obtain the first polynomial-time algorithm that achieves a
nontrivial worst-case approximation to the optimal log-likelihood: the
approximation factor is $\frac{1}{(1+o(1))\log{m}}$ unconditionally (for data
sets that consist of $m$ subsets), and can be improved to $1-\frac{1+o(1)}{\log
N}$ if all $N$ elements appear in a $O(1/N)$-fraction of the subsets.
  In terms of techniques, we reduce approximating the maximum log-likelihood of
DPPs on a data set to solving a gap instance of a "vector coloring" problem on
a hypergraph. Such a hypergraph is built on a bounded-degree graph construction
of Bogdanov, Obata and Trevisan (FOCS 2002), and is further enhanced by the
strong expanders of Alon and Capalbo (FOCS 2007) to serve our purposes.


  Layout generation aims to synthesize realistic graphic scenes consisting of
elements with different attributes including category, size, position, and
between-element relation. It is a crucial task for reducing the burden on
heavy-duty graphic design works for formatted scenes, e.g., publications,
documents, and user interfaces (UIs). Diverse application scenarios impose a
big challenge in unifying various layout generation subtasks, including
conditional and unconditional generation. In this paper, we propose a Layout
Diffusion Generative Model (LDGM) to achieve such unification with a single
decoupled diffusion model. LDGM views a layout of arbitrary missing or coarse
element attributes as an intermediate diffusion status from a completed layout.
Since different attributes have their individual semantics and characteristics,
we propose to decouple the diffusion processes for them to improve the
diversity of training samples and learn the reverse process jointly to exploit
global-scope contexts for facilitating generation. As a result, our LDGM can
generate layouts either from scratch or conditional on arbitrary available
attributes. Extensive qualitative and quantitative experiments demonstrate our
proposed LDGM outperforms existing layout generation models in both
functionality and performance.


  In this paper we study existence, dependence and optimal control results
concerning solutions to a class of hemivariational inequalities for stationary
Navier-Stokes equations but without making use of the theory of pseudo-monotone
operators. To do so, we consider a classical assumption, due to J. Rauch, which
constrains us to make a slight change on the definition of a solution. The
Rauch assumption,, although insure the existence of a solution, does not allow
the conclusion that the non-convex functional is locally Lipschitz. Moreover,
two dependence results are proved, one with respect to changes of the boundary
condition and the other with respect to the density of external forces. The
later one will be used to prove the existence of an optimal control to the
distributed parameter optimal control problem where the control is represented
by the external forces.


  Lieb and Carlen have shown that mixed states with minimal Wehrl entropy are
coherent states. We prove that mixed states with almost minimal Wehrl entropy
are almost coherent states. This is proved in a quantitative sense where both
the norm and the exponent are optimal and the constant is explicit. We prove a
similar bound for generalized Wehrl entropies. As an application, a sharp
quantitative form of the log-Sobolev inequality for functions in the Fock space
is provided.


  The locus of $\theta \equiv {k^{\mu}};_{\mu} = 0$ for bundles of light rays
emitted at noncentral points is investigated for Lema\^{\i}tre -- Tolman (L--T)
models. The three loci that coincide for a central emission point: (1) maxima
of $R$ along the rays, (2) $\theta = 0$, (3) $R = 2M$ are all different for a
noncentral emitter. If an extremum of $R$ along a nonradial ray exists, then it
must lie in the region $R > 2M$. In $2M < R \leq 3M$ it can only be a maximum;
in $R > 3M$ both minima and maxima can exist. The intersection of (1) with the
equatorial hypersurface (EHS) $\vartheta = \pi/2$ is numerically determined for
an exemplary toy model (ETM), for two typical emitter locations. The equation
of (2) is derived for a general L--T model, and its intersection with the EHS
in the ETM is numerically determined for the same two emitter locations.
Typically, $\theta$ has no zeros or two zeros along a ray, and becomes $+
\infty$ at the Big Crunch (BC). The only rays on which $\theta \to - \infty$ at
the BC are the radial ones. Along rays on the boundaries between the no-zeros
and the two-zeros regions $\theta$ has one zero, but still tends to $+ \infty$
at the BC. When the emitter is sufficiently close to the center, $\theta$ has 4
or 6 zeros along some rays (resp. 3 or 5 on the boundary rays). For noncentral
emitters in a collapsing L--T model, $R = 2M$ is still the ultimate barrier
behind which events become invisible from outside; loci (1) and (2) are not
such barriers.


  We study the topological gap labeling of general 3D quasicrystals and we find
that every gap in the spectrum is characterized by a set of the third Chern
numbers. We show that a quasi-periodic structure has multiple Brillouin zones
defined by redundant wavevectors, and the number of states below a gap is
quantized as an integer linear combination of volumes of these Brillouin zones.
The associated quantum numbers to characterize energy gaps can be expressed as
third Chern numbers by considering a formal relationship between an adiabatic
charge pumping under cyclic deformation of the quasi-periodic potential and a
topological nonlinear electromagnetic response in 6D insulators.


  Decoding human visual neural representations is a challenging task with great
scientific significance in revealing vision-processing mechanisms and
developing brain-like intelligent machines. Most existing methods are difficult
to generalize to novel categories that have no corresponding neural data for
training. The two main reasons are 1) the under-exploitation of the multimodal
semantic knowledge underlying the neural data and 2) the small number of paired
(stimuli-responses) training data. To overcome these limitations, this paper
presents a generic neural decoding method called BraVL that uses multimodal
learning of brain-visual-linguistic features. We focus on modeling the
relationships between brain, visual and linguistic features via multimodal deep
generative models. Specifically, we leverage the mixture-of-product-of-experts
formulation to infer a latent code that enables a coherent joint generation of
all three modalities. To learn a more consistent joint representation and
improve the data efficiency in the case of limited brain activity data, we
exploit both intra- and inter-modality mutual information maximization
regularization terms. In particular, our BraVL model can be trained under
various semi-supervised scenarios to incorporate the visual and textual
features obtained from the extra categories. Finally, we construct three
trimodal matching datasets, and the extensive experiments lead to some
interesting conclusions and cognitive insights: 1) decoding novel visual
categories from human brain activity is practically possible with good
accuracy; 2) decoding models using the combination of visual and linguistic
features perform much better than those using either of them alone; 3) visual
perception may be accompanied by linguistic influences to represent the
semantics of visual stimuli. Code and data: https://github.com/ChangdeDu/BraVL.


  Symbolic Regression (SR) is a widely studied field of research that aims to
infer symbolic expressions from data. A popular approach for SR is the Sparse
Identification of Nonlinear Dynamical Systems (\sindy) framework, which uses
sparse regression to identify governing equations from data. This study
introduces an enhanced method, Nested SINDy, that aims to increase the
expressivity of the SINDy approach thanks to a nested structure. Indeed,
traditional symbolic regression and system identification methods often fail
with complex systems that cannot be easily described analytically. Nested SINDy
builds on the SINDy framework by introducing additional layers before and after
the core SINDy layer. This allows the method to identify symbolic
representations for a wider range of systems, including those with compositions
and products of functions. We demonstrate the ability of the Nested SINDy
approach to accurately find symbolic expressions for simple systems, such as
basic trigonometric functions, and sparse (false but accurate) analytical
representations for more complex systems. Our results highlight Nested SINDy's
potential as a tool for symbolic regression, surpassing the traditional SINDy
approach in terms of expressivity. However, we also note the challenges in the
optimization process for Nested SINDy and suggest future research directions,
including the designing of a more robust methodology for the optimization
process. This study proves that Nested SINDy can effectively discover symbolic
representations of dynamical systems from data, offering new opportunities for
understanding complex systems through data-driven methods.


  We suggest a new web-based approach for browsing and visualizing data
produced by a network of telescopes, such as those of the ongoing TAOS and the
forthcoming TAOS II projects. We propose a modern client-side technology and we
present two examples based on two software packages developed for different
kinds of server- side database approaches. In spite our examples are specific
for the browsing of TAOS light curves, the software is coded in a way to be
suitable for the use in several types of astronomical projects.


  The third column of the left row in the Basilica of Santa Maria in Aracoeli
in Rome, has a hole carved in it, of probable astronomical use. The tube aims
at a point a 116 degrees of azimut, East-South-East and 17.3 degrees of
altitude, the Sun could be aimed in that direction at 07:00 UTC of 12 october
and 7:25 UT of march 2, but the view is obstructed by the church's building.
Same situation for the 3.9 magnitude alpha Monocerotis, visible 2000 years ago,
taking into account the precession. Other hypotheses on the meridian
astronomical use of this hole are here reviewed. In the case of solar
observations it cannot be for meridian transits in Rome, since the lower
transits occurs now at 24.5 degrees at winter solstice; we investigate the case
of stellar transits, of declination 30.8 degrees South. Many alignments are
possible leaving the azimut as free parameter, being the columun not in its
original collocation, but here we investigate only the meridian transits, and
no bright stars could have been seen through that hole, taking also into
account the precession 2000 years ago. We conclude that this hole was probably
not used for meridian observations.


  We report the results of a survey of 442 planetary nebulae at 30 GHz. The
purpose of the survey is to develop a list of planetary nebulae as calibration
sources which could be used for high frequency calibration in future. For 41
PNe with sufficient data, we test the emission mechanisms in order to evaluate
whether or not spinning dust plays an important role in their spectra at 30
GHz.
  The 30-GHz data were obtained with a twin-beam differencing radiometer,
OCRA-p, which is in operation on the Torun 32-m telescope. Sources were scanned
both in right ascension and declination. We estimated flux densities at 30 GHz
using a free-free emission model and compared it with our data.
  The primary result is a catalogue containing the flux densities of 93
planetary nebulae at 30 GHz. Sources with sufficient data were compared with a
spectral model of free-free emission. The model shows that free-free emission
can generally explain the observed flux densities at 30 GHz thus no other
emission mechanism is needed to account for the high frequency spectra.


  In this study we present detailed calculations of absorption line indices on
the Lick System based on the stellar models by Salasnich et al. (2000)
calculated with enhanced mix of alpha-elements. Using the so-called Response
Functions (RFs) of Tripicco & Bell (1995, TB95), we calculate the indices for
SSPs of different age, metallicity and enhancement. We made use of the triplet
Hb, Mgb and <Fe>, and Minimum-Distance Method proposed by Trager et al. (2000,
TFWG00) to estimate the age, metallicity and enhancement degree for the
galaxies of the Gonzalez (1993) sample, and compare the results with those
TFWG00 and Thomas et al (2003). Since very large differences are found, in
particular as far as the age is concerned, we analyze in a great detail all
possible sources of disagreement, going from the stellar models and SSPs to
many technical details of the procedure to calculate the indices, and finally
the pattern of chemical elements (especially when alpha-enhanced mixtures are
adopted). The key issue of the analysis is that at given metallicity Z and
enhancement factor, the specific abundance ratios [Xel/Fe] adopted for some
elements (e.g. O, Mg, Ti, and likely others) dominate the scene because with
the TB95 RFs they may strongly affect indices like Hb and the age in turn.
Finally we have drawn some remarks on the interpretation of the distribution of
early-type galaxies in popular two-indices planes, like Hb vs. [MgFe]. We argue
that part of the scatter along the Hb axis observed in this plane could be
attributed instead of the age, the current explanation, to a spread both in the
degree of enhancement and some abundance ratios. The main conclusion of this
study is that deriving ages, metallicities and degree of enhancement from line
indices is a cumbersome affair whose results are still uncertain.


  Complete intersections inside rational homogeneous varieties provide
interesting examples of Fano manifolds. For example, if $X = \cap_{i=1}^r D_i
\subset G/P$ is a general complete intersection of $r$ ample divisors such that
$K_{G/P}^* \otimes \mathcal{O}_{G/P}(-\sum_i D_i)$ is ample, then $X$ is Fano.
We first classify these Fano complete intersections which are locally rigid. It
turns out that most of them are hyperplane sections. We then classify general
hyperplane sections which are quasi-homogeneous.


  Current approaches to identifying driving heterogeneity face challenges in
comprehending fundamental patterns from the perspective of underlying driving
behavior mechanisms. The concept of Action phases was proposed in our previous
work, capturing the diversity of driving characteristics with physical
meanings. This study presents a novel framework to further interpret driving
patterns by classifying Action phases in an unsupervised manner. In this
framework, a Resampling and Downsampling Method (RDM) is first applied to
standardize the length of Action phases. Then the clustering calibration
procedure including ''Feature Selection'', ''Clustering Analysis'',
''Difference/Similarity Evaluation'', and ''Action phases Re-extraction'' is
iteratively applied until all differences among clusters and similarities
within clusters reach the pre-determined criteria. Application of the framework
using real-world datasets revealed six driving patterns in the I80 dataset,
labeled as ''Catch up'', ''Keep away'', and ''Maintain distance'', with both
''Stable'' and ''Unstable'' states. Notably, Unstable patterns are more
numerous than Stable ones. ''Maintain distance'' is the most common among
Stable patterns. These observations align with the dynamic nature of driving.
Two patterns ''Stable keep away'' and ''Unstable catch up'' are missing in the
US101 dataset, which is in line with our expectations as this dataset was
previously shown to have less heterogeneity. This demonstrates the potential of
driving patterns in describing driving heterogeneity. The proposed framework
promises advantages in addressing label scarcity in supervised learning and
enhancing tasks such as driving behavior modeling and driving trajectory
prediction.


  We generalize the Susceptible-Infected-Removed model for epidemics to take
into account generic effects of heterogeneity in the degree of susceptibility
to infection in the population. We introduce a single new parameter
corresponding to a power-law exponent of the susceptibility distribution that
characterizes the population heterogeneity. We show that our generalized model
is as simple as the original model which is contained as a limiting case.
Because of this simplicity, numerical solutions can be generated easily and key
properties of the epidemic wave can still be obtained exactly. In particular,
we present exact expressions for the herd immunity level, the final size of the
epidemic, as well as for the shape of the wave and for observables that can be
quantified during an epidemic. We find that in strongly heterogeneous
populations the epidemic reaches only a small fraction of the population. This
implies that the herd immunity level can be much lower than in commonly used
models with homogeneous populations. Using our model to analyze data for the
SARS-CoV-2 epidemic in Germany shows that the reported time course is
consistent with several scenarios characterized by different levels of
immunity. These scenarios differ in population heterogeneity and in the time
course of the infection rate, for example due to mitigation efforts or
seasonality. Our analysis reveals that quantifying the effects of mitigation
requires knowledge on the degree of heterogeneity in the population. Our work
shows that key effects of population heterogeneity can be captured without
increasing the complexity of the model. We show that information about
population heterogeneity will be key to understand how far an epidemic has
progressed and what can be expected for its future course.


  Although fluorescence is the prevailing labeling technique in biosensing
applications, sensitivity improvement is still a striving challenge. We show
that coating standard microscope slides with nanoroughened silver films
provides a high fluorescence signal enhancement due to plasmonic interactions.
As a proof of concept, we applied these films with tailored plasmonic
properties to DNA microarrays. Using common optical scanning devices, we
achieved signal amplifications by more than 40-fold.


  It has been shown that the thermal photon and the lepton pair spectra can be
used to estimate the radial velocity of different phases of the matter formed
in nuclear collisions at ultra-relativistic energies. We observe a
non-monotonic variation of the flow velocity with invariant mass of the lepton
pair which is indicative of two different sources of thermal dilepton sources
at early and late stage of the dynamically evolving system. We also show that
the study of radial velocity through electromagnetic probes may shed light on
the nature of the phase transition from hadrons to QGP.


  Many of the early-type galaxies observed so far at z>1 turned out to have
smaller radii with respect to that of a typical present-day early-type galaxy
with comparable mass. This has generated the conviction that in the past
early-type galaxies were more compact, hence denser, and that as a consequence,
they should have increased their radius across the time to reconcile with the
present-day ones. However, observations have not yet established whether the
population of early-types in the early Universe was fully represented by
compact galaxies nor if they were so much more numerous than in the present-day
Universe to require an evolution of their sizes. Here we report the results of
a study based on a complete sample of 34 early-type galaxies at
0.9<z_{spec}<1.92. We find a majority (62 per cent) of normal early-type
galaxies similar to typical local ones, co-existing with compact early-types
from ~2 to ~6 times smaller in spite of the same mass and redshift. The
co-existence of normal and compact early-type galaxies at <z>~1.5 suggests that
their build-up taken place in the first 3-4 Gyr, followed distinct paths. Also,
we find that the number density of compact early-types at <z>~1.5 is consistent
with the lower limits of the local number density of compact early-types
derived from local clusters of galaxies. The similar number of compact
early-types found in the early and in the present day Universe frustrates the
hypothesized effective radius evolution while provides evidence that also
compact ETGs were as we see them today 9-10 Gyr ago. Finally, the fact that (at
least) most of the compact ETGs at high-z are accounted for by compact
early-types in local cluster of galaxies implies that the former are the direct
progenitors of the compact early-type cluster galaxies establishing a direct
link between environment and early phases of assembly of ETGs.


  For decades, H_0 and q_0 were the quest of cosmology, as they promised to
characterize our "world model" without reference to a specific cosmological
framework. Using Monte Carlo simulations, we show that q_0 cannot be directly
measured using distance indicators with both accuracy (without offset away from
its true value) and precision (small error bar). While H_0 can be measured with
accuracy and precision, to avoid a small bias in its direct measurement (of
order 5%) we demonstrate that the pair H_0 and Omega_M (assuming flatness and w
= -1) is a better choice of two parameters, even if our world model is not
precisely LambdaCDM. We illustrate with analysis of the Constitution set of
supernovae and indirectly infer q_0 = -0.57+/-0.04. Finally, we show that it
may be possible to directly determine q_0 with both accuracy and precision
using the time dependence of redshifts ("redshift drift").


  Cloud computing is a new paradigm and innovation in the technology service
delivery. It is utilized for IT-enabled value creation. The capex-free nature
of cloud service delivery renders it very attractive to many SMEs. But it is
saddled with multi-tenancy issues; prominent under this study are concerns of
privacy, trust and availability. How do end-users trust providers with their
sensitive data? How secured and confidential are their corporate assets? Amidst
the perennial power outages (a.k.a. Dumsor), what is the acceptable available
uptime? We sampled and interviewed cloud service providers (CSPs) as well as
end-users in Ghana, a developing economy. We also gleaned through some
secondary data to ascertain some operational concerns. The results indicate
that security and service level agreements (SLAs) are key concerns in respect
of privacy and trust issues. Similarly, perennial power outages and security
were key availability concerns. This was expected as end-users use cloud
services for mission critical information assets, and so requires high
availability. The implications are that the cyber-security concerns ought to be
addressed if SMEs in developing economies are to adopt and accept cloud
computing resources for IT-enabled competitive advantage.


  We explore the shape of the galaxy luminosity function (LF) in groups of
different mass by creating composite LFs over large numbers of groups.
Following previous work using total group luminosity as the mass indicator,
here we split our groups by multiplicity and by estimated virial (group halo)
mass, and consider red (passive) and blue (star forming) galaxies separately.
In addition we utilise two different group catalogues (2PIGG and Yang et al.)
in order to ascertain the impact of the specific grouping algorithm and further
investigate the environmental effects via variations in the LF with position in
groups. Our main results are that LFs show a steepening faint end for early
type galaxies as a function of group mass/ multiplicity, with a much suppressed
trend (evident only in high mass groups) for late type galaxies. Variations
between LFs as a function of group mass are robust irrespective of which
grouping catalogue is used, and broadly speaking what method for determining
group `mass' is used. We find in particular that there is a significant deficit
of low-mass passive galaxies in low multiplicity groups, as seen in high
redshift clusters. Further to this, the variation in the LF appears to only
occur in the central regions of systems, and in fact seems to be most strongly
dependent on the position in the group relative to the virial radius. Finally,
distance-rank magnitude relations were considered. Only the Yang groups
demonstrated any evidence of a correlation between a galaxy's position relative
to the brightest group member and its luminosity. 2PIGG possessed no such
gradient, the conclusion being the FOF algorithm suppresses the signal for weak
luminosity--position trends and the Yang grouping algorithm naturally enhances
it.


  We prove the Fargues-Rapoport conjecture for p-adic period domains in the
non-basic case with minuscule cocharacter. More precisely, we give a group
theoretical criterion for the cases when the admissible locus and weakly
admissible locus coincide.


  We consider a quantum dot coupled to both superconducting and spin-polarized
electrodes, and study the triad interplay of the Kondo effect,
superconductivity, and ferromagnetism, any pair of which compete with and
suppress each other. We find that the interplay leads to a mixed-valence
quantum phase transition, which for other typical sysmstems is merely a
crossover rather than a true transition. At the transition, the system changes
from the spin doublet to singlet state. The singlet phase is adiabatically
connected (through crossovers) to the so-called 'charge Kondo state' and to the
superconducting state. We analyze in detail the physical characteristics of
different states and propose that the measurement of the cross-current
correlation and the charge relaxation resistance can clearly distinguish
between them.


  We re-examine the historically important decay of the neutral pion into two
photons. Schwinger's Equivalence Theorem is confirmed. We then consider
radiative corrections to the famous Adler-Bell-Jackiw (ABJ) anomaly. The result
depends crucially on a physically motivated regularization scheme. Our approach
is largely based on Schwinger's source (dispersion) method.


  The Proton Improvement Plan-II (PIP-II) is a superconducting linear
accelerator being built at Fermilab that will provide 800 MeV proton beam for
neutrino production. The linac consists of a total of twenty-three (23)
cryomodules of five (5) different types. Cooling is required at 2K, 5K and 40K.
The Cryogenic Distribution System (CDS) consists of a Distribution Valve Box,
~285 m of cryogenic transfer line, modular Bayonet Cans to interface with
cryomodules, and a Turnaround Can. The cryogenic system must provide protection
from over-pressure by sizing pressure relief devices for all volumes and
process line circuits. The cryomodule cavity circuits have dual pressure
ratings, 4.1 bara when cold and 2.05 bara when warm (T>80K). Worst case
relieving cases will be identified. The methods for determining heat flux will
be presented. For the relieving occurring in the linac tunnel, flow must vent
to outside to avoid an oxygen deficiency hazard. Also, we will present vacuum
vessel relief sizing to protect the cryogenic distribution system vacuum shells
from over pressure during an internal line rupture. The project is funded by US
DOE Offices of Science, High Energy Physics.


  The Ultra-Violet Imaging Telescope (UVIT) is one of the payloads in ASTROSAT,
the first Indian Space Observatory. The UVIT instrument has two 375mm
telescopes: one for the far-ultraviolet (FUV) channel (1300--1800\AA), and the
other for the near-ultraviolet (NUV) channel (2000--3000\AA) and the visible
(VIS) channel (3200--5500\AA). UVIT is primarily designed for simultaneous
imaging in the two ultraviolet channels with spatial resolution better than 1.8
arcsec, along with provision for slit-less spectroscopy in the NUV and FUV
channels.The results of in-orbit calibrations of UVIT are presented in this
paper.


  The directed network of telephone subscribers is considered in the article.
It can be described as a dynamic network with vertices that correspond to the
subscribers of the telephone network and emerging directional edges that
correspond to the connections between the respective subscribers. The position
of the edge and its direction is determined by the incoming and outgoing calls
from the corresponding vertices. The subject of the article is the statistical
properties of the connections of a certain subset of telephone network
subscribers. Such connections are dynamic in nature due to their appearance and
disappearance. The number of outgoing (or incoming) connections occurred during
a day at a selected vertex is used as the main characteristic. The distribution
density of the number of outgoing (or incoming) connections (or calls) of such
a network has been analyzed using the experimental data. It has been shown that
such a distribution density over the number of calls obeys the lognormal
distribution density, which depends on the two parameters. The values of two
parameters, namely the mean value and the variance, determining the lognormal
distribution density are established. The reasons for the appearance of a
lognormal distribution density over the number of incoming (or outgoing)
connections have been discussed. The statistical properties of other groups of
subscribers have been considered as well. In particular, the group that makes a
large number of outgoing calls to various subscribers of the telephone network
has been selected for a separate study. The members of this group, who create
and distribute spam can be called spammers. It has been shown that these
groups, spammers for example, also obeys the lognormal distribution density
over the number of calls but they are characterized by the different mean value
and variance.


  Weak values are usually associated with weak measurements of an observable on
a pre- and post-selected ensemble. We show that more generally, weak values are
proportional to the correlation between two pointers in a successive
measurement. We show that this generalized concept of weak measurements
displays a symmetry under reversal of measurement order. We show that the
conditions for order symmetry are the same as in classical mechanics. We also
find that the imaginary part of the weak value has a counterpart in classical
mechanics. This scheme suggests new experimental possibilities.


  After a brief presentation of Feynman diagrams, we criticizise the idea that
Feynman diagrams can be considered to be pictures or depictions of actual
physical processes. We then show that the best interpretation of the role they
play in quantum field theory and quantum electrodynamics is captured by Hughes'
Denotation, Deduction and Interpretation theory of models (DDI), where models
are to be interpreted as inferential, non-representational devices constructed
in given social contexts by the community of physicists.


  This paper is focused on delivering a solution that can scan and reconstruct
the 3D profile of a pipeline in real-time using a crawler robot. A structured
infrared (IR) laser ring projector and a stereo camera system are used to
generate the 3D profile of the pipe as the robot moves inside the pipe. The
proposed stereo system does not require field calibrations and it is not
affected by the lateral movement of the robot, hence capable of producing an
accurate 3D map. The wavelength of the IR light source is chosen to be non
overlapping with the visible spectrum of the color camera. Hence RGB color
values of the depth can be obtained by projecting the 3D map into the color
image frame. The proposed system is implemented in Robotic Operating System
(ROS) producing real-time RGB-D maps with defects. The defect map exploit
differences in ovality enabling real-time identification of structural defects
such as surface corrosion in pipe infrastructure. The lab experiments showed
the proposed laser profiling system can detect ovality changes of the pipe with
millimeter level of accuracy and resolution.


  In the solid-state circuit QED system and based on the homodyne measurement
in dispersive regime, we demonstrate that a homodyne-current-based feedback can
create and stabilize highly entangled two-qubit states in the presence of
moderate noisy environment. Particularly, we present an extended analysis for
the current-based Markovian feedback, which leads to an improved
filtered-current-based feedback scheme. We show that this is essential for us
to achieve the desirable control effect in present system.


  Online learning of Hawkes processes has received increasing attention in the
last couple of years especially for modeling a network of actors. However,
these works typically either model the rich interaction between the events or
the latent cluster of the actors or the network structure between the actors.
We propose to model the latent structure of the network of actors as well as
their rich interaction across events for real-world settings of medical and
financial applications. Experimental results on both synthetic and real-world
data showcase the efficacy of our approach.


  Zero-index materials (ZIMs) have become popular because of their unique
optical behaviors, such as infinite effective wavelengths and spatially uniform
electromagnetic distributions. The all-dielectric ZIMs, Dirac-like cone-based
zero-index materials (DCZIMs) are used in various photonic applications owing
to their superior optical properties, such as finite impedances, zero Ohmic
losses, and high compatibility with photonic circuits. We propose a more
general and simple approach that is independent of the Dirac-like cone mode for
realizing near-zero index (NZI) behavior in all-dielectric waveguides. This
approach can be applied to various dielectric materials up to the necessary NZI
bandwidth. Si3N4 and Ge NZI waveguides are demonstrated for achieving broadband
and narrowband NZI, respectively. The proposed broadband NZI waveguide achieves
a bandwidth of 140 nm for neff < 0.1 (neff = effective refractive index) at
telecommunication wavelengths, which is 2 times larger than that of the
reported NZI waveguides. Further, NZI waveguide-based beam steering was
demonstrated with a wide steering range delta theta 105 degrees across the
radiation angle of theta 0 degree. The proposed NZI-waveguide design principle
and beam steering present a feasible approach for the development of photonic
circuits and zero-index-based photonic applications.


  In this article we study large central charge partition function and
entanglement entropy of $T\bar{T}$ deformed two dimensional conformal field
theory, following the approach to $T\bar{T}$ deformation as integrated
infinitesimal double trace deformation used by Guica et al.. For sphere
partition function and entanglement entropy of half great circle with antipodal
points being the entangling surface, we obtain different results compared to
previous works, with more reasonable CFT limits and qualitatively different
behaviour as the deformation parameter $\mu$ goes to infinity, which
contradicts the simple version of the cutoff AdS holography proposal. For a
modified version of cutoff AdS holography which is supposed to work only in the
sector of classical pure gravity, we show that the flow equation of the metric
and one point function of energy-momentum tensor in $T\bar{T}$ deformation
corresponds to the flow equation of the boundary metric and Brown-York tensor
on a cutoff surface in AdS space as the cutoff surface moves in the direction
of normal geodesics. In addition the flow equation of gravity on-shell action
takes the form of $T\bar{T}$ deformation, with straightforward generalization
to higher dimensions. As an example we give a holographic computation of the
sphere partition function of $T\bar{T}$ CFT.


  Let $A$ be a $d$-dimensional local ring containing a field. We will prove
that the highest Lyubeznik number $\lambda_{d,d}(A)$ (defined in \cite{l1}) is
equal to the number of connected components of the Hochster-Huneke graph
(defined in \cite{hh}) associated to $B$, where $B=\hat{\hat{A}^{sh}}$ is the
completion of the strict Henselization of the completion of $A$. This was
proven by Lyubeznik in characteristic $p>0$. Our statement and proof are
characteristic-free.


  We introduce a logic for reasoning about contextual trust for web addresses,
provide a Kripke semantics for it, and prove its soundness under reasonable
assumptions about principals' policies.
  Self-Authenticating Traditional Addresses (SATAs) are valid DNS addresses or
URLs that are generally meaningful -- to both humans and web infrastructure --
and contain a commitment to a public key in the address itself. Trust in web
addresses is currently established via domain name registration, TLS
certificates, and other hierarchical elements of the internet infrastructure.
SATAs support such structural roots of trust but also complementary contextual
roots associated with descriptive properties. The existing structural roots
leave web connections open to a variety of well-documented and significant
hijack vulnerabilities. Contextual trust roots provide, among other things,
stronger resistance to such vulnerabilities.
  We also consider labeled SATAs, which include descriptive properties such as
that a SATA is an address for a news organization, a site belonging to a
particular government or company, a site with information about a certain
topic, etc. Our logic addresses both trust in the bound together identity of
the address and trust in the binding of labels to it. Our logic allows
reasoning about delegation of trust with respect to specified labels,
relationships between labels that provide more or less specific information,
and the interaction between these two aspects.
  In addition to soundness, we prove that if a principal trusts a particular
identity (possibly with label), then either this trust is initially assumed, or
there is a trust chain of delegations to this from initial trust assumptions.
We also present an algorithm that effectively derives all possible trust
statements from the set of initial trust assumptions and show it to be sound,
complete, and terminating.


  Environmental effects on the muon lifetime are described. A general theorem
on the cancellation of bound state phase space suppression and final state
interaction enhancement is illustrated for muonium and muonic atoms. Lessons
from those bound muon examples are applied to the b decay puzzle and apparent
inconsistencies in K{e3} decay rates.


  We present a new computation of the renormalized graviton self-energy induced
by a loop of massless, minimally coupled scalars on de Sitter background. Our
result takes account of the need to include a finite renormalization of the
cosmological constant, which was not included in the first analysis. We also
avoid preconceptions concerning structure functions and instead express the
result as a linear combination of 21 tensor differential operators. By using
our result to quantum-correct the linearized effective field equation we derive
logarithmic corrections to both the electric components of the Weyl tensor for
gravitational radiation and to the two potentials which quantify the
gravitational response to a static point mass.


  We present experimental evidences for the existence of a semi-hard scale in
light hadrons. This includes the suppression of gluon radiation that is seen in
high mass hadron diffraction; the weak energy dependence of hadronic total
cross sections; the small value of the Pomeron trajectory slope measured in
photoproduction of J/Psi; the weakness of gluon shadowing in nuclei; shortage
of gluons in the proton revealed by an unusual behavior of the proton structure
function in the soft limit, and the enhanced intrinsic transverse momentum of
quarks and gluons, which considerably exceeds the inverse hadronic size. All
these observations suggest that gluons in hadrons are located within spots of a
small size relative to the confinement radius.


  Significant photovoltages are observed in permalloy grating-like structures
in response to pulsed laser light illumination. Electric signals are enhanced
at plasmon resonance conditions and show a clear dependence on the magnetic
field with a characteristic hysteresis. Estimations show that the effect could
not be explained solely by the laser-induced heating. Alternative mechanisms
are discussed.


  IP Pegasi is an eclipsing dwarf nova lying above the period gap with an
orbital period of 3.8h. It is the first cataclysmic variable to show evidence
of spiral arms in its accretion disc. We present new time-resolved echelle
spectroscopic observations of IP Peg, covering the 3900-7700 Angstrom range.
This allows us to produce simultaneous Doppler Maps in 9 emission lines.


  Knowledge flow analysis offers a simple and flexible way to find flaws in
security protocols. A protocol is described by a collection of rules
constraining the propagation of knowledge amongst principals. Because this
characterization corresponds closely to informal descriptions of protocols, it
allows a succinct and natural formalization; because it abstracts away message
ordering, and handles communications between principals and applications of
cryptographic primitives uniformly, it is readily represented in a standard
logic. A generic framework in the Alloy modelling language is presented, and
instantiated for two standard protocols, and a new key management scheme.


  The growing enrollments in computer science courses and increase in class
sizes necessitate scalable, automated tutoring solutions to adequately support
student learning. While Large Language Models (LLMs) like GPT-4 have
demonstrated potential in assisting students through question-answering,
educators express concerns over student overreliance, miscomprehension of
generated code, and the risk of inaccurate answers. Rather than banning these
tools outright, we advocate for a constructive approach that harnesses the
capabilities of AI while mitigating potential risks. This poster introduces
CourseAssist, a novel LLM-based tutoring system tailored for computer science
education. Unlike generic LLM systems, CourseAssist uses retrieval-augmented
generation, user intent classification, and question decomposition to align AI
responses with specific course materials and learning objectives, thereby
ensuring pedagogical appropriateness of LLMs in educational settings. We
evaluated CourseAssist against a baseline of GPT-4 using a dataset of 50
question-answer pairs from a programming languages course, focusing on the
criteria of usefulness, accuracy, and pedagogical appropriateness. Evaluation
results show that CourseAssist significantly outperforms the baseline,
demonstrating its potential to serve as an effective learning assistant. We
have also deployed CourseAssist in 6 computer science courses at a large public
R1 research university reaching over 500 students. Interviews with 20 student
users show that CourseAssist improves computer science instruction by
increasing the accessibility of course-specific tutoring help and shortening
the feedback loop on their programming assignments. Future work will include
extensive pilot testing at more universities and exploring better collaborative
relationships between students, educators, and AI that improve computer science
learning experiences.


  The crystallographic symmetries and spatial distribution of stacking domains
in graphene films on SiC have been studied by low energy electron diffraction
(LEED) and dark field imaging in a low energy electron microscope (LEEM). We
find that the graphene diffraction spots from 2 and 3 atomic layers of graphene
have 3-fold symmetry consistent with AB (Bernal) stacking of the layers. On the
contrary, graphene diffraction spots from the buffer layer and monolayer
graphene have apparent 6-fold symmetry, although the 3-fold nature of the
satellite spots indicates a more complex periodicity in the graphene sheets.


  Biochemical reaction networks are often modelled using discrete-state,
continuous-time Markov chains. System statistics of these Markov chains usually
cannot be calculated analytically and therefore estimates must be generated via
simulation techniques. There is a well documented class of simulation
techniques known as exact stochastic simulation algorithms, an example of which
is Gillespie's direct method. These algorithms often come with high
computational costs, therefore approximate stochastic simulation algorithms
such as the tau-leap method are used. However, in order to minimise the bias in
the estimates generated using them, a relatively small value of tau is needed,
rendering the computational costs comparable to Gillespie's direct method.
  The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model.
Simul. 10:146-179, 2012) provides a reduction in computational costs whilst
minimising or even eliminating the bias in the estimates of system statistics.
This is achieved by first crudely approximating required statistics with many
sample paths of low accuracy. Then correction terms are added until a required
level of accuracy is reached. Recent literature has primarily focussed on
implementing the multi-level method efficiently to estimate a single system
statistic. However, it is clearly also of interest to be able to approximate
entire probability distributions of species counts. We present two novel
methods that combine known techniques for distribution reconstruction with the
multi-level method. We demonstrate the potential of our methods using a number
of examples.


  We present a method for constructing a consistent low energy canonical
formalism for higher order time-derivative theories, extending the Dirac method
to include perturbative Hamiltonian constraints. We apply it to two
paradigmatic examples: the Pais-Uhlenbeck oscillator and the Bernard-Duncan
scalar field. We also compare the results, both at the classical and quantum
level, with the ones corresponding to a direct perturbative construction
applied to the exact higher order theory. This comparison highligths the
soundness of the present formalism.


  The Gaia Data Release 2 provides a parallax of 0.734+/-0.073 mas for SDSS
J102915+172927, currently the most metal-poor known object. This parallax
implies that it is dwarf star, ruling out the scenario that it is a subgiant.
The subgiant scenario had as a corollary that the star had been formed in a
medium highly enriched in C, thus making line cooling efficient during the
collapse, that was also highly enriched in Fe by Type Ia SNe. This scenario can
also now be ruled out for this star, reinforcing the need of dust cooling and
fragmentation to explain its formation.


  The dynamic behaviors of a mixed spin (1/2-1) hexagonal Ising nanowire (HIN)
with core-shell structure in the presence of a time dependent magnetic field
are investigated by using the effective-field theory with correlations based on
the Glauber-type stochastic dynamics (DEFT). According to the values of
interaction parameters, temperature dependence of the dynamic magnetizations,
the hysteresis loop areas and the dynamic correlations are investigated to
characterize the nature (first- or second-order) of the dynamic phase
transitions (DPTs). Dynamic phase diagrams, including compensation points, are
also obtained. Moreover, from the thermal variations of the dynamic total
magnetization, the five compensation types can be found under certain
conditions, namely the Q-, R-, S-, P-, and N-types.


  This survey hinges on the interplay between regularity and approximation for
linear and quasi-linear fractional elliptic problems on Lipschitz domains. For
the linear Dirichlet integral Laplacian, after briefly recalling H\"older
regularity and applications, we discuss novel optimal shift theorems in Besov
spaces and their Sobolev counterparts. These results extend to problems with
finite horizon and are instrumental for the subsequent error analysis.
Moreover, we dwell on extensions of Besov regularity to the fractional
$p$-Laplacian, and review the regularity of fractional minimal graphs and
stickiness. We discretize these problems using continuous piecewise linear
finite elements and derive global and local error estimates for linear
problems, thereby improving some existing error estimates for both
quasi-uniform and graded meshes. We also present a BPX preconditioner which
turns out to be robust with respect to both the fractional order and the number
of levels. We conclude with the discretization of fractional quasi-linear
problems and their error analysis. We illustrate the theory with several
illuminating numerical experiments.


  Using both a continuum Navier-Stokes solver, with the mu(I)-flow-law
implemented to model the viscous behavior, and the discrete Contact Dynamics
algorithm, the discharge of granular silos is simulated in two dimensions from
the early stages of the discharge until complete release of the material. In
both cases, the Beverloo scaling is recovered. We first do not attempt
quantitative comparison, but focus on the qualitative behavior of velocity and
pressure at different locations in the flow. A good agreement is obtained in
the regions of rapid flows, while areas of slow creep are not entirely captured
by the continuum model. The pressure field shows a general good agreement. The
evolution of the free surface implies differences, however, the bulk
deformation is essentially identical in both approaches. The influence of the
parameters of the mu(I)-flow-law is systematically investigated, showing the
importance of the dependence on the inertial number I to achieve quantitative
agreement between continuum and discrete discharge. The general ability of the
continuum model to reproduce qualitatively the granular behavior is found to be
very encouraging.


  Realizing computationally complex quantum circuits in the presence of noise
and imperfections is a challenging task. While fault-tolerant quantum computing
provides a route to reducing noise, it requires a large overhead for generic
algorithms. Here, we develop and analyze a hardware-efficient, fault-tolerant
approach to realizing complex sampling circuits. We co-design the circuits with
the appropriate quantum error correcting codes for efficient implementation in
a reconfigurable neutral atom array architecture, constituting what we call a
fault-tolerant compilation of the sampling algorithm. Specifically, we consider
a family of $[[2^D , D, 2]]$ quantum error detecting codes whose transversal
and permutation gate set can realize arbitrary degree-$D$ instantaneous quantum
polynomial (IQP) circuits. Using native operations of the code and the atom
array hardware, we compile a fault-tolerant and fast-scrambling family of such
IQP circuits in a hypercube geometry, realized recently in the experiments by
Bluvstein et al. [Nature 626, 7997 (2024)]. We develop a theory of
second-moment properties of degree-$D$ IQP circuits for analyzing hardness and
verification of random sampling by mapping to a statistical mechanics model. We
provide evidence that sampling from hypercube IQP circuits is classically hard
to simulate and analyze the linear cross-entropy benchmark (XEB) in comparison
to the average fidelity. To realize a fully scalable approach, we first show
that Bell sampling from degree-$4$ IQP circuits is classically intractable and
can be efficiently validated. We further devise new families of
$[[O(d^D),D,d]]$ color codes of increasing distance $d$, permitting exponential
error suppression for transversal IQP sampling. Our results highlight
fault-tolerant compiling as a powerful tool in co-designing algorithms with
specific error-correcting codes and realistic hardware.


  The core of information retrieval (IR) is to identify relevant information
from large-scale resources and return it as a ranked list to respond to the
user's information need. In recent years, the resurgence of deep learning has
greatly advanced this field and leads to a hot topic named NeuIR (i.e., neural
information retrieval), especially the paradigm of pre-training methods (PTMs).
Owing to sophisticated pre-training objectives and huge model size, pre-trained
models can learn universal language representations from massive textual data,
which are beneficial to the ranking task of IR. Recently, a large number of
works, which are dedicated to the application of PTMs in IR, have been
introduced to promote the retrieval performance. Considering the rapid progress
of this direction, this survey aims to provide a systematic review of
pre-training methods in IR. To be specific, we present an overview of PTMs
applied in different components of an IR system, including the retrieval
component, the re-ranking component, and other components. In addition, we also
introduce PTMs specifically designed for IR, and summarize available datasets
as well as benchmark leaderboards. Moreover, we discuss some open challenges
and highlight several promising directions, with the hope of inspiring and
facilitating more works on these topics for future research.


  By an additive structure on a hypersurface S in projective space we mean an
effective action of commutative unipotent group on projective space which
leaves S invariant and acts on S with an open orbit. It is known that these
structures correspond to pairs (R,H) of local finite-dimensional algebra R and
a hyperplane H in the maximal ideal of R. We show when a projective
hypersurface of degree 3 has an additive structure and when structure is
unique.


  Microorganisms are rarely found in Nature swimming freely in an unbounded
fluid. Instead, they typically encounter other organisms, hard walls, or
deformable boundaries such as free interfaces or membranes. Hydrodynamic
interactions between the swimmer and nearby objects lead to many interesting
phenomena, such as changes in swimming speed, tendencies to accumulate or turn,
and coordinated flagellar beating. Inspired by this class of problems, we
investigate locomotion of microorganisms near deformable boundaries. We
calculate the speed of an infinitely long swimmer close to a flexible surface
separating two fluids; we also calculate the deformation and swimming speed of
the flexible surface. When the viscosities on either side of the flexible
interface differ, we find that fluid is pumped along or against the swimming
direction, depending on which viscosity is greater.


  In this paper, the interaction between two immiscible fluids with a finite
mobility ratio is investigated numerically within a Hele-Shaw cell. Fingering
instabilities initiated at the interface between a low viscosity fluid and a
high viscosity fluid are analysed at varying capillary numbers and mobility
ratios using a finite mobility ratio model. The present work is motivated by
the possible development of interfacial instabilities that can occur in porous
media during the process of CO$_2$ sequestration, but does not pretend to
analyse this complex problem. Instead, we present a detailed study of the
analogous problem occurring in a Hele-Shaw cell, giving indications of possible
plume patterns that can develop during the CO$_2$ injection. The numerical
scheme utilises a boundary element method in which the normal velocity at the
interface of the two fluids is directly computed through the evaluation of a
hypersingular integral. The boundary integral equation is solved using a
Neumann convergent series with cubic B-Spline boundary discretisation,
exhibiting 6th order spatial convergence. The convergent series allows the long
term non-linear dynamics of growing viscous fingers to be explored accurately
and efficiently. Simulations in low mobility ratio regimes reveal large
differences in fingering patterns compared to those predicted by previous high
mobility ratio models. Most significantly, classical finger shielding between
competing fingers is inhibited. Secondary fingers can possess significant
velocity, allowing greater interaction with primary fingers compared to high
mobility ratio flows. Eventually, this interaction can lead to base thinning
and the breaking of fingers into separate bubbles.


  A theoretical foundation for a generalization of the elliptic difference
Painlev\'e equation to higher dimensions is provided in the framework of
birational Weyl group action on the space of point configurations in general
position in a projective space. By introducing an elliptic parametrization of
point configurations, a realization of the Weyl group is proposed as a group of
Cremona transformations containing elliptic functions in the coefficients. For
this elliptic Cremona system, a theory of $\tau$-functions is developed to
translate it into a system of bilinear equations of Hirota-Miwa type for the
$\tau$-functions on the lattice.


  An analytical work on intrinsic localized modes in a two-dimensional
Heisenberg ferromagnet on the checkerboard lattice is presented. Taking
advantage of an asymptotic method, the governing lattice dynamical equations
are reduced to one (2+1) -dimensional nonlinear Schr\"odinger. In our work, we
obtain two types of nonlinear localized mode solutions, namely, Brillouin zone
center modes and Brillouin zone corner modes. The occurrence conditions for
these intrinsic localized modes are given in detail. Especially, we find that
the competition between the Dzialozinskii-Moriy interaction and the
next-nearest neighbor interaction of the checkerboard ferromagnet has an effect
on the local structure of the Brillouin zone corner acoustic mode.


  We present a new independent pipeline for the CMB bispectrum estimation of
primordial non-Gaussianity and release a public code for constraining
bispectrum shapes of interest based on the Planck 2018 temperature and
polarization data. The estimator combines the strengths of the conventional KSW
and Modal estimators at the cost of increased computational complexity, which
has been made manageable through intensive algorithmic and implementation
optimization. We also detail some methodological advances in numerical
integration over a tetrapyd - domain where the bispectrum is defined on - via
new quadrature rules. The pipeline has been validated both internally and
against Planck. As a proof-of-concept example, we constrain some highly
oscillatory models that were out of reach in conventional analyses using a
targeted basis with a fixed oscillation frequency, and no significant evidence
for primordial non-Gaussianity of these shapes is found. The methodology and
code developed in this work will be directly applicable to future surveys where
we expect a notable boost in sensitivity.


  A digital security breach, by which confidential information is leaked, does
not only affect the agent whose system is infiltrated, but is also detrimental
to other agents socially connected to the infiltrated system. Although it has
been argued that these externalities create incentives to under-invest in
security, this presumption is challenged by the possibility of strategic
adversaries that attack the least protected agents. In this paper we study a
new model of security games in which agents share tokens of sensitive
information in a network of contacts. The agents have the opportunity to invest
in security to protect against an attack that can be either strategically or
randomly targeted. We show that, in the presence of random attack,
under-investments always prevail at the Nash equilibrium in comparison with the
social optimum. Instead, when the attack is strategic, either under-investments
or over-investments are possible, depending on the network topology and on the
characteristics of the process of the spreading of information. Actually,
agents invest more in security than socially optimal when dependencies among
agents are low (which can happen because the information network is sparsely
connected or because the probability that information tokens are shared is
small). These over-investments pass on to under-investments when information
sharing is more likely (and therefore, when the risk brought by the attack is
higher).


  A novel frequency dependence of anomaly in dielectric constant versus
temperature plot, around the Neel temperature T_N (~150 K), has been observed
in a single crystal of bilayer manganite Pr(Sr0.1Ca0.9)2Mn2O7. The anomaly in
the permittivity (epsilon'||c) occurs at a temperature T_f which moves within a
temperature window (delT_f) of ~40 K around T_N for a frequency range 50 kHz-5
MHz. The capacitive component Cp of the dielectric response exhibits a clear
yet broad feature around T_N which establishes the intrinsic capacitive nature
of the anomaly.


  Uncovering the quantitative laws that govern the growth and division of
single cells remains a major challenge. Using a unique combination of
technologies that yields unprecedented statistical precision, we find that the
sizes of individual Caulobacter crescentus cells increase exponentially in
time. We also establish that they divide upon reaching a critical multiple
($\approx$1.8) of their initial sizes, rather than an absolute size. We show
that when the temperature is varied, the growth and division timescales scale
proportionally with each other over the physiological temperature range.
Strikingly, the cell-size and division-time distributions can both be rescaled
by their mean values such that the condition-specific distributions collapse to
universal curves. We account for these observations with a minimal stochastic
model that is based on an autocatalytic cycle. It predicts the scalings, as
well as specific functional forms for the universal curves. Our experimental
and theoretical analysis reveals a simple physical principle governing these
complex biological processes: a single temperature-dependent scale of cellular
time governs the stochastic dynamics of growth and division in balanced growth
conditions.


  Secluded dark matter models, in which WIMPs annihilate first into metastable
mediators, can present novel indirect detection signatures in the form of gamma
rays and fluxes of charged particles arriving from directions correlated with
the centers of large astrophysical bodies within the solar system, such as the
Sun and larger planets. This naturally occurs if the mean free path of the
mediator is in excess of the solar (or planetary) radius. We show that existing
constraints from water Cerenkov detectors already provide a novel probe of the
parameter space of these models, complementary to other sources, with
significant scope for future improvement from high angular resolution gamma-ray
telescopes such as Fermi-LAT. Fluxes of charged particles produced in mediator
decays are also capable of contributing a significant solar system component to
the spectrum of energetic electrons and positrons, a possibility which can be
tested with the directional and timing information of PAMELA and Fermi.


  We study the primordial density perturbations and non-Gaussianities generated
from the combined effects of an inhomogeneous end of inflation and curvaton
decay in hybrid inflation. This dual role is played by a single isocurvature
field which is massless during inflation but acquire a mass at the end of
inflation via the waterfall phase transition. We calculate the resulting
primordial non-Gaussianity characterized by the non-linearity parameter,
$f_{NL}$, recovering the usual end-of-inflation result when the field decays
promptly and the usual curvaton result if the field decays sufficiently late.


  We present the cross sections for both electromagnetic and diffractive
dissociation of protons for semiexclusive production of $J/\psi$ mesons in
proton-proton collisions at the LHC. Differential distributions in missing mass
($M_X$), as well as distributions in rapidity and transverse momentum of the
$J/\psi$ are calculated for $\sqrt{s} = 7$ TeV and 13 TeV proton proton
collisions. We compare the distributions for purely electromagnetic and purely
diffractive proton excitations/dissociation. We predict cross sections for
electromagnetic and diffractive excitations of similar order of magnitude.