  The equivalence principle (EP), as well as Schiff's conjecture, are discussed
(en passant), and the connection between the EP and quantum mechanics is then
briefly analyzed. Two semiclassical violations of the classical equivalence
principle (CEP) but not of the weak one (WEP), i.e. Greenberger gravitational
Bohr atom and the tree-level scattering of different quantum particles by an
external weak higher-order gravitational field, are thoroughly investigated
afterwards. Next, two quantum examples of systems that agree with the WEP but
not with the CEP, namely COW experiment and free fall in a constant
gravitational field of a massive object described by its wave-function $\Psi$,
are discussed in detail. Keeping in mind that among the four examples focused
on this work only COW experiment is based on an experimental test, some
important details related to it, are presented as well.


  We develop and experimentally verify a theory of Type-II spontaneous
parametric down-conversion (SPDC) in media with inhomogeneous distributions of
second-order nonlinearity. As a special case, we explore interference effects
from SPDC generated in a cascade of two bulk crystals separated by an air gap.
The polarization quantum-interference pattern is found to vary strongly with
the spacing between the two crystals. This is found to be a cooperative effect
due to two mechanisms: the chromatic dispersion of the medium separating the
crystals and spatiotemporal effects which arise from the inclusion of
transverse wave vectors. These effects provide two concomitant avenues for
controlling the quantum state generated in SPDC. We expect these results to be
of interest for the development of quantum technologies and the generation of
SPDC in periodically varying nonlinear materials.


  All supersymmetric gauge theories based on simple groups which have an affine
quantum moduli space, i.e. one generated by gauge invariants with no relations,
W=0, and anomaly matching at the origin, are classified. It is shown that the
only theories with no gauge invariants (and moduli space equal to a single
point) are the two known examples, SU(5) with 5-bar + 10 and SO(10) with a
spinor. The index of the matter representation must be at least as big as the
index of the adjoint in theories which have a non-trivial relation among the
gauge invariants.


  One of the basic principles of Approximation Theory is that the quality of
approximations increase with the smoothness of the function to be approximated.
Functions that are smooth in certain subdomains will have good approximations
in those subdomains, and these {\em sub-approximations} can possibly be
calculated efficiently in parallel, as long as the subdomains do not overlap.
This paper proposes a class of algorithms that first calculate
sub-approximations on non-overlapping subdomains, then extend the subdomains as
much as possible and finally produce a global solution on the given domain by
letting the subdomains fill the whole domain. Consequently, there will be no
Gibbs phenomenon along the boundaries of the subdomains. Throughout, the
algorithm works for fixed scattered input data of the function itself, not on
spectral data, and it does not resample.


  We study the problem of optimal oculomotor control during the execution of
visual search tasks. We introduce a computational model of human eye movements,
which takes into account various constraints of the human visual and oculomotor
systems. In the model, the choice of the subsequent fixation location is posed
as a problem of stochastic optimal control, which relies on reinforcement
learning methods. We show that if biological constraints are taken into
account, the trajectories simulated under learned policy share both basic
statistical properties and scaling behaviour with human eye movements. We
validated our model simulations with human psychophysical eye-tracking
experiments


  Let $\mathbb K$ be a field of characteristic 0. Given $n$ linear forms in
$R=\mathbb K[x_1,\ldots,x_k]$, with no two proportional, in one of our main
results we show that the ideal $I\subset R$ generated by all $(n-2)$-fold
products of these linear forms has linear graded free resolution. This result
helps determining a complete set of generators of the symmetric ideal of $I$.
Via Sylvester forms we can analyze from a different perspective the generators
of the presentation ideal of the Orlik-Terao algebra of the second order; this
is the algebra generated by the reciprocals of the products of any two
(distinct) of the linear forms considered. We also show that when $k=2$, and
when the collection of $n$ linear forms may contain proportional linear forms,
for any $1\leq a\leq n$, the ideal generated by $a$-fold products of these
linear forms has linear graded free resolution.


  In this review we discuss the population of stellar-mass black holes in our
galaxy and beyond, which are the extreme endpoints of massive star evolution.
In particular we focus on how we can attempt to balance the available accretion
energy with feedback to the environment via radiation, jets and winds,
considering also possible contributions to the energy balance from black hole
spin and advection. We review quantitatively the methods which are used to
estimate these quantities, regardless of the details of the astrophysics close
to the black hole. Once these methods have been outlined, we work through an
outburst of a black hole X-ray binary system, estimating the flow of mass and
energy through the different accretion rates and states. While we focus on
feedback from stellar mass black holes in X-ray binary systems, we also
consider the applicability of what we have learned to supermassive black holes
in active galactic nuclei. As an important control sample we also review the
coupling between accretion and feedback in neutron stars, and show that it is
very similar to that observed in black holes, which strongly constrains how
much of the astrophysics of feedback can be unique to black holes.


  The reduction number r(A) of a standard graded algebra A is the least integer
k such that there exists a minimal reduction J of the homogeneous maximal ideal
m of A such that Jm^k=m^{k+1}. Vasconcelos conjectured that the reduction
number of A=R/I can only increase by passing to the initial ideal, i.e
r(R/I)\leq r(R/in(I)). The goal of this note is to prove the conjecture.


  Event cameras are vision sensors that record asynchronous streams of
per-pixel brightness changes, referred to as "events". They have appealing
advantages over frame-based cameras for computer vision, including high
temporal resolution, high dynamic range, and no motion blur. Due to the sparse,
non-uniform spatiotemporal layout of the event signal, pattern recognition
algorithms typically aggregate events into a grid-based representation and
subsequently process it by a standard vision pipeline, e.g., Convolutional
Neural Network (CNN). In this work, we introduce a general framework to convert
event streams into grid-based representations through a sequence of
differentiable operations. Our framework comes with two main advantages: (i)
allows learning the input event representation together with the task dedicated
network in an end to end manner, and (ii) lays out a taxonomy that unifies the
majority of extant event representations in the literature and identifies novel
ones. Empirically, we show that our approach to learning the event
representation end-to-end yields an improvement of approximately 12% on optical
flow estimation and object recognition over state-of-the-art methods.


  We compute the spatial population statistics for one-dimensional fermi-gases
and for bose-gases with hard core repulsions in periodic potentials. We show
how the statistics depend on the atomic density in the ground state of the
system, and we present calculations for the dynamical turn-on of the potential.


  We consider an entangled but non-interacting qubit pair a_{1} and b_{1} that
are independently coupled to a set of local qubit systems, a_{I} and b_{J}, of
0-bit value, respectively. We derive rules for the transfer of entanglement
from the pair a_{1}-b_{1} to an arbitrary pair a_{I}-b_{J}, for the case of
qubit-number conserving local interactions. It is shown that the transfer rule
depends strongly on the initial entangled state. If the initial entanglement is
in the form of the Bell state corresponding to anti-correlated qubits, the sum
of the square of the non-local pairwise concurrences is conserved. If the
initial state is the Bell state with correlated qubits, this sum can be
reduced, even to zero in some cases, to reveal a complete and abrupt loss of
all non-local pairwise entanglement. We also identify that for the nonlocal
bipartitions A-b_{J} involving all qubits at one location, with one qubit b_{J}
at the other location, the concurrences satisfies a simple addition rule for
both cases of the Bell states, that the sum of the square of the nonlocal
concurrences is conserved.


  Large spectroscopic surveys have enabled in the recent years the computation
of three-dimensional interstellar extinction maps thanks to accurate stellar
atmospheric parameters and line-of-sight distances. Such maps are complementary
to 3D maps extracted from photometry, allowing a more thorough study of the
dust properties. Our goal is to use the high-resolution spectroscopic survey
Gaia-ESO in order to obtain with a good distance resolution the interstellar
extinction and its dependency as a function of the environment and the
Galactocentric position. We use the stellar atmospheric parameters of more than
5000 stars, obtained from the Gaia-ESO survey second internal data release, and
combine them with optical (SDSS) and near-infrared (VISTA) photometry as well
as different sets of theoretical stellar isochrones, in order to calculate
line-of-sight extinction and distances. The extinction coefficients are then
compared with the literature to discuss their dependancy on the stellar
parameters and position in the Galaxy. Within the errors of our method, our
work does not show that there is any dependence of the interstellar extinction
coefficient on the atmospheric parameters of the stars. We do not find any
evidence of the variation of E(J-H)/E(J-K) with the angle from the Galactic
centre nor with Galactocentric distance. This suggests that we are dealing with
a uniform extinction law in the SDSS ugriz bands and the near-IR JHKs bands.
Therefore, extinction maps using mean colour-excesses and assuming a constant
extinction coefficient can be used without introducing any systematic errors.


  Based on SU(3) flavor symmetry, we decompose the decay amplitudes of bottom
baryon decays to a pseudoscalar meson and an octet (a decuplet) pentaquark in
terms of three (two) invariant amplitudes $T_1$ and $T_{2,3}$ ($\tilde T_1$ and
$\tilde T_2$) corresponding to external $W$-emission and internal $W$-emission
diagrams, respectively. For antitriplet bottom baryons $\Lambda_b^0,\Xi_b^0$
and $\Xi_b^-$, their decays to a decuplet pentaquark proceed only through the
internal $W$-emission diagram. Assuming the dominance from the external
$W$-emission amplitudes, we present an estimate of the decay rates relative to
$\Lambda_b^0\to P_p^+K^-$, where $P_p^+$ is the hidden-charm pentaquark with
the same light quark content as the proton. Hence, our numerical results will
provide a very useful guideline to the experimental search for pentaquarks in
bottom baryon decays. For example, $\Xi_b^0\to P_{\Sigma^+}K^-$, $\Xi_b^-\to
P_{\Sigma^-}\bar K^0$, $\Omega_b^-\to P_{\Xi^-}\bar K^0$ and $\Omega_b^-\to
P_{\Xi^0}K^-$ may have rates comparable to that of $\Lambda_b^0\to P_p^+K^-$
and these modes should be given the higher priority in the experimental
searches for pentaquarks.


  We characterize the symmetric measures which satisfy the one dimensional
convex infimum convolution inequality of Maurey. For these measures the
tensorization argument yields the two level Talagrand's concentration
inequalities for their products and convex sets in $\mathbb{R}^n$.


  We give a connection formula for the Jackson integral of Riemann-Papperitz
type. This includes a solution of the connection problem for the variant of
$q$-hypergeometric equation of degree three introduced by
Hatano-Matsunawa-Sato-Takemura. Using this formula we show a linear relation
for the Kajihara's $q$-hypergeometric series $W^{M,2}$, whose $q$-difference
equation is recently obtained by one of the author.


  Recently, Mike and Farmer have constructed a very powerful and realistic
behavioral model to mimick the dynamic process of stock price formation based
on the empirical regularities of order placement and cancelation in a purely
order-driven market, which can successfully reproduce the whole distribution of
returns, not only the well-known power-law tails, together with several other
important stylized facts. There are three key ingredients in the Mike-Farmer
(MF) model: the long memory of order signs characterized by the Hurst index
$H_s$, the distribution of relative order prices $x$ in reference to the same
best price described by a Student distribution (or Tsallis' $q$-Gaussian), and
the dynamics of order cancelation. They showed that different values of the
Hurst index $H_s$ and the freedom degree $\alpha_x$ of the Student distribution
can always produce power-law tails in the return distribution $f(r)$ with
different tail exponent $\alpha_r$. In this paper, we study the origin of the
power-law tails of the return distribution $f(r)$ in the MF model, based on
extensive simulations with different combinations of the left part $f_L(x)$ for
$x<0$ and the right part $f_R(x)$ for $x>0$ of $f(x)$. We find that power-law
tails appear only when $f_L(x)$ has a power-law tail, no matter $f_R(x)$ has a
power-law tail or not. In addition, we find that the distributions of returns
in the MF model at different timescales can be well modeled by the Student
distributions, whose tail exponents are close to the well-known cubic law and
increase with the timescale.


  The isoscalar-isovector ($\rho-\omega$) interferences in the exclusive
reactions $\pi^- p \to n e^+ e^-$ and $\pi^+ n \to p e^+ e^-$ near the $\omega$
threshold leads to a distinct difference of the dielectron invariant mass
distributions depending on beam energy. The strength of this effect is
determined by the coupling of resonances to the nucleon vector-meson channels
and other resonance properties. Therefore, a combined analysis of these
reactions can be used as a tool for determining the baryon resonance dynamics.


  The inclusion of electromagnetism in a low energy effective theory is worth
further study in view of the present high precision experiments (muon g-2,
pi_0->2 gamma, tau decays, etc.). In particular in many applications of chiral
perturbation theory, one has to purify physical matrix elements from
electromagnetic effects. The theoretical problems that I want to point out here
are following: the splitting of a pure QCD and a pure electromagnetic part in a
hadronic process is model dependent: is it possible to parametrise in a clear
way this splitting? What kind of information (scale dependence, gauge
dependence,..) is actually included in the parameters of the low energy
effective theory? I will attempt to answer these questions introducing a
possible convention to perform the splitting between strong and electromagnetic
parts in some examples.


  Kotlarski (1978) proved a result on identification of the distributions of
independent random variables $X,Y$ and $Z$ from the joint distribution of the
bivariate random vector $(U,V)$ where $(U,V)= (\max(X,Z),\max(Y,Z)).$ We extend
this result to the case $(U,V)=(\max(X,aZ_1,bZ_2),\max(Y,cZ_1,dZ_2))$ where
$X,Y,Z_1,Z_2$ are independent or max-independent random variables, $Z_1$ and
$Z_2$ are identically distributed and $a,b,c,d$ are known positive constants.


  Semi-supervised learning (SSL) is an effective means to leverage unlabeled
data to improve a model's performance. Typical SSL methods like FixMatch assume
that labeled and unlabeled data share the same label space. However, in
practice, unlabeled data can contain categories unseen in the labeled set,
i.e., outliers, which can significantly harm the performance of SSL algorithms.
To address this problem, we propose a novel Open-set Semi-Supervised Learning
(OSSL) approach called OpenMatch. Learning representations of inliers while
rejecting outliers is essential for the success of OSSL. To this end, OpenMatch
unifies FixMatch with novelty detection based on one-vs-all (OVA) classifiers.
The OVA-classifier outputs the confidence score of a sample being an inlier,
providing a threshold to detect outliers. Another key contribution is an
open-set soft-consistency regularization loss, which enhances the smoothness of
the OVA-classifier with respect to input transformations and greatly improves
outlier detection. OpenMatch achieves state-of-the-art performance on three
datasets, and even outperforms a fully supervised model in detecting outliers
unseen in unlabeled data on CIFAR10.


  Free energy calculations based on atomistic Hamiltonians and sampling are key
to a first principles understanding of biomolecular processes, material
properties, and macromolecular chemistry. Here, we generalize the Free Energy
Perturbation method and derive non-linear Hamiltonian transformation sequences
for optimal sampling accuracy that differ markedly from established linear
transformations. We show that our sequences are also optimal for the Bennett
Acceptance Ratio (BAR) method, and our unifying framework generalizes BAR to
small sampling sizes and non-Gaussian error distributions. Simulations on a
Lennard-Jones gas show that an order of magnitude less sampling is required
compared to established methods.


  The shape of buildings plays a critical role in the energy efficiency,
lifestyles, land use and infrastructure systems of cities. Thus, as most of the
world's cities continue to grow and develop, understanding the interplay
between the characteristics of urban environments and the built form of cities
is essential to achieve local and global sustainability goals. Here, we compile
and analyze the most extensive data set of building shapes to date, covering
more than 4.8 million individual buildings across several major cities in North
America. We show that average building height increases systematically with
city size and follows theoretical predictions derived from urban scaling
theory. We also study the allometric relationship between surface area and
volume of buildings in terms of characteristic shape parameters. This allows us
to demonstrate that the reported trend towards higher (and more voluminous)
buildings effectively decreases the average surface-to-volume ratio, suggesting
potentially significant energy savings with growing city size. At the same
time, however, the surface-to-volume ratio increases in the downtown cores of
large cities, due to shape effects and specifically to the proliferation of
tall, needlelike buildings. Thus, the issue of changes in building shapes with
city size and associated energy management problem is highly heterogeneous. It
requires a systematic approach that includes the factors that drive the form of
built environments, entangling physical, infrastructural and socioeconomic
aspects of cities.


  From the analysis of a ~100 ks Chandra observation of the dwarf starburst
galaxy NGC 1569, we have found that the X-ray point sources, CXOU
043048.1+645050 and CXOU 043048.6+645058, showed significant time variability.
During this observation, the X-ray flux of CXOU 043048.1+645050 increased by 10
times in only 2 x 10^4 s. Since the spectrum in its bright phase was fitted
with a disk blackbody model with kT_in ~0.43 keV and the bolometric luminosity
is L_bol ~10^38 ergs s^-1, this source is an X-ray binary with a stellar mass
black-hole. Since the spectrum in its faint phase was also fitted with a disk
blackbody model, the time variability can be explained by a change of the
accretion rate onto the black hole. The other variable source, CXOU
043048.6+645058, had a flat spectrum with a photon index of ~1.6. This source
may be an X-ray binary with an X-ray luminosity of several x 10^37 ergs s^-1.
In addition, three other weak sources showed possible time variability. Taking
all of the variability into account may suggest an abundant population of
compact X-ray sources in NGC 1569.


  This article presents an implementation of a graphical software with various
algorithms in Operations research, like minimum path, minimum tree, chinese
postman problem and travelling salesman.


  Recently, Deutsch and Elizalde studied the largest and the smallest fixed
points of permutations. Motivated by their work, we consider the analogous
problems in weighted set partitions. Let $A_{n,k}(\mathbf{t})$ denote the total
weight of partitions on $[n+1]$ with the largest singleton $\{k+1\}$. In this
paper, explicit formulas for $A_{n,k}(\mathbf{t})$ and many combinatorial
identities involving $A_{n,k}(\mathbf{t})$ are obtained by umbral operators and
combinatorial methods. As applications, we investigate three special cases such
as permutations, involutions and labeled forests. Particularly in the
permutation case, we derive a surprising identity analogous to the Riordan
identity related to tree enumerations, namely, \begin{eqnarray*}
\sum_{k=0}^{n}\binom{n}{k}D_{k+1}(n+1)^{n-k} &=& n^{n+1}, \end{eqnarray*} where
$D_{k}$ is the $k$-th derangement number or the number of permutations of
$\{1,2,\dots, k\}$ with no fixed points.


  Depressions (or pits) are low areas within a digital elevation model that are
surrounded by higher terrain, with no outlet to lower areas. Filling them so
they are level, as fluid would fill them if the terrain were impermeable, is
often necessary in preprocessing DEMs. The depression-filling algorithm
presented here---called Priority-Flood---unifies and improves on the work of a
number of previous authors who have published similar algorithms. The algorithm
operates by flooding DEMs inwards from their edges using a priority queue to
determine the next cell to be flooded. The resultant DEM has no depressions or
digital dams: every cell is guaranteed to drain. The algorithm is optimal for
both integer and floating-point data, working in O(n) and O(n lg n) time,
respectively. It is shown that by using a plain queue to fill depressions once
they have been found, an O(m lg m) time-complexity can be achieved, where m
does not exceed the number of cells n. This is the lowest time complexity of
any known floating-point depression-filling algorithm. In testing, this
improved variation of the algorithm performed up to 37% faster than the
original. Additionally, a parallel version of an older, but widely-used
depression-filling algorithm required six parallel processors to achieve a
run-time on par with what the newer algorithm's improved variation took on a
single processor. The Priority-Flood Algorithm is simple to understand and
implement: the included pseudocode is only 20 lines and the included C++
reference implementation is under a hundred lines. The algorithm can work on
irregular meshes as well as 4-, 6-, 8-, and n-connected grids. It can also be
adapted to label watersheds and determine flow directions through either
incremental elevation changes or depression carving. In the case of incremental
elevation changes, the algorithm includes safety checks not present in prior
works.


  Prompt learning represents a promising method for adapting pre-trained
vision-language models (VLMs) to various downstream tasks by learning a set of
text embeddings. One challenge inherent to these methods is the poor
generalization performance due to the invalidity of the learned text embeddings
for unseen tasks. A straightforward approach to bridge this gap is to freeze
the text embeddings in prompts, which results in a lack of capacity to adapt
VLMs for downstream tasks. To address this dilemma, we propose a paradigm
called EnPrompt with a novel External Layer (EnLa). Specifically, we propose a
textual external layer and learnable visual embeddings for adapting VLMs to
downstream tasks. The learnable external layer is built upon valid embeddings
of pre-trained CLIP. This design considers the balance of learning capabilities
between the two branches. To align the textual and visual features, we propose
a novel two-pronged approach: i) we introduce the optimal transport as the
discrepancy metric to align the vision and text modalities, and ii) we
introduce a novel strengthening feature to enhance the interaction between
these two modalities. Four representative experiments (i.e., base-to-novel
generalization, few-shot learning, cross-dataset generalization, domain shifts
generalization) across 15 datasets demonstrate that our method outperforms the
existing prompt learning method.


  The surface conditions of terrestrial bodies strongly reflect their
geological evolutionary processes and vary among various terrestrial bodies.
This diversity is attributed to variations in the timescales of boulder
formation through processes such as impact cratering, rockfalls from crater
walls, seismic motion, and boulder fragmentation caused by micrometeoroid
impacts and thermal stress. In this study, we examined boulders on Ceres using
high-resolution images with a resolution of approximately 5 m/px obtained
during the Ceres Extended Mission 2 Orbit 7 of the Dawn mission. Almost all
boulders were present around impact craters, even at a resolution of 5 m/px,
thus indicating that the boulders on Ceres were created by impact cratering
alone. The maximum boulder size on Ceres is approximately 200 m, even around
large craters, which may indicate the upper size limit determined by the
mechanical strength of the boulders, such as the tensile strength, the scale
effect, and/or shattering strength. The slope of the size-frequency
distribution of boulders on Ceres varied significantly across the range of
boulder sizes, thus making it difficult to describe it using a single function
of a power-law relationship; in particular, it changed at approximately 100 m,
thus indicating that destructive or formation mechanisms may be different for
large boulders > 100 m and for small boulders < 100 m. There may also be a
subsurface structure that prevents the formation of small boulders, although
this is difficult to argue conclusively. We estimated that the lifetime of
boulders larger than 50 m was equivalent to or shorter than 100 Myr. This
lifetime is consistent with a theoretical estimation assuming that
micrometeoroid impacts are the primary destructive mechanism.


  A uniqueness theorem for an LU decomposition of a totally nonnegative matrix
is obtained.


  A simple band model such as the effective mass approximation (EMA) can be
used to quickly obtain the lower-energy region for the band structure of
monolayer molybdenum disulfide. But the EMA band model cannot give the correct
description for the band structure in the higher-energy region. To address this
major issue, we propose an analytical band calculation (ABC) model to study
monolayer molybdenum disulfide. Important parameters of the ABC model are
obtained by fitting the three-direction band structure of monolayer molybdenum
disulfide obtained from the first-principles (FP) method. The proposed ABC
model fits well with the FP band structure calculation result for monolayer
molybdenum disulfide. We also use the ABC model to calculate physical
quantities used in carrier transport such as density of states and group
velocity. Our ABC model can be extended and further utilized for calculating
the key physical quantities of ballistic transport of 2D semiconductor
materials.


  Fuzzy logic is a powerful tool to model knowledge uncertainty, measurements
imprecision, and vagueness. However, there is another type of vagueness that
arises when data have multiple forms of expression that fuzzy logic does not
address quite well. This is the case for multiple instance learning problems
(MIL). In MIL, an object is represented by a collection of instances, called a
bag. A bag is labeled negative if all of its instances are negative, and
positive if at least one of its instances is positive. Positive bags encode
ambiguity since the instances themselves are not labeled. In this paper, we
introduce fuzzy inference systems and neural networks designed to handle bags
of instances as input and capable of learning from ambiguously labeled data.
First, we introduce the Multiple Instance Sugeno style fuzzy inference
(MI-Sugeno) that extends the standard Sugeno style inference to handle
reasoning with multiple instances. Second, we use MI-Sugeno to define and
develop Multiple Instance Adaptive Neuro Fuzzy Inference System (MI-ANFIS). We
expand the architecture of the standard ANFIS to allow reasoning with bags and
derive a learning algorithm using backpropagation to identify the premise and
consequent parameters of the network. The proposed inference system is tested
and validated using synthetic and benchmark datasets suitable for MIL problems.
We also apply the proposed MI-ANFIS to fuse the output of multiple
discrimination algorithms for the purpose of landmine detection using Ground
Penetrating Radar.


  Fake websites have emerged as a major source of online fraud, accounting for
billions of dollars of loss by Internet users. We explore the process by which
salient design elements could increase the use of protective tools, thus
reducing the success rate of fake websites. Using the protection motivation
theory, we conceptualize a model to investigate how salient design elements of
detection tools could influence user perceptions of the tools, efficacy in
dealing with threats, and use of such tools. The research method was a
controlled lab experiment with a novel and extensive experimental design and
protocol. We found that trust in the detector is the pivotal coping mechanism
in dealing with security threats and is a major conduit for transforming
salient design elements into increased use. We also found that design elements
have profound and unexpected impacts on self-efficacy. The significant
theoretical and empirical implications of findings are discussed.


  We reconsider the one loop divergence of ${\cal N}=8$ supergravity in four
dimensions. We compute the finite effective potential of ${\cal N}=8$
anti-deSitter supergravity and interpret it as logarithmic running of the
cosmological constant. We find that quantum inequivalence between fields that
are classically dual is due to boundary modes in AdS$_4$. Some subtleties are
traced to the difference between the Euler characteristic of global and thermal
AdS$_4$.


  We have reanalysed the 1996/1997 VLA monitoring data of the gravitational
lens system JVAS B0218+357 to produce improved total flux density and
polarization variability curves at 15, 8.4 and 5 GHz. This has been done using
improved calibration techniques, accurate subtraction of the emission from the
Einstein ring and careful correction of various systematic effects, especially
an offset in polarization position angle that is hour-angle dependent. The
variations in total and polarized flux density give the best constraints and we
determine a combined delay estimate of $11.3 \pm 0.2$ d (1$\sigma$). This is
consistent with the $\gamma$-ray value recently derived using the Fermi
Gamma-ray Space Telescope and thus we find no evidence for a positional shift
between the radio and $\gamma$-ray emitting regions. Combined with the
previously published lens model found using LensClean, the new delay gives a
value for the Hubble constant of $H_0 = 72.9 \pm 2.6$ km s$^{-1}$ Mpc$^{-1}$
(1$\sigma$).


  It is counter-intuitive that multi-modality methods based on point cloud and
images perform only marginally better or sometimes worse than approaches that
solely use point cloud. This paper investigates the reason behind this
phenomenon. Due to the fact that multi-modality data augmentation must maintain
consistency between point cloud and images, recent methods in this field
typically use relatively insufficient data augmentation. This shortage makes
their performance under expectation. Therefore, we contribute a pipeline, named
transformation flow, to bridge the gap between single and multi-modality data
augmentation with transformation reversing and replaying. In addition,
considering occlusions, a point in different modalities may be occupied by
different objects, making augmentations such as cut and paste non-trivial for
multi-modality detection. We further present Multi-mOdality Cut and pAste
(MoCa), which simultaneously considers occlusion and physical plausibility to
maintain the multi-modality consistency. Without using ensemble of detectors,
our multi-modality detector achieves new state-of-the-art performance on
nuScenes dataset and competitive performance on KITTI 3D benchmark. Our method
also wins the best PKL award in the 3rd nuScenes detection challenge. Code and
models will be released at https://github.com/open-mmlab/mmdetection3d.


  The reverse transcription paradigm shift in RNA tumor virus research marked
by the discovery of the reverse transcriptase in 1970 was traced using
co-citation and title word frequency analysis. It is shown that this event is
associated with a break in citation patterns and the occurrence of previously
unknown technical terms.


  Multiferroics, showing simultaneous ordering of electrical and magnetic
degrees of freedom, are remarkable materials as seen from both the academic and
technological points of view. A prominent mechanism of multiferroicity is the
spin-driven ferroelectricity, often found in frustrated antiferromagnets with
helical spin order. There, similar to conventional ferroelectrics, the
electrical dipoles arise from an off-centre displacement of ions. However,
recently a different mechanism, namely purely electronic ferroelectricity,
where charge order breaks inversion symmetry, has attracted considerable
interest. Here we provide evidence for this exotic type of ferroelectricity,
accompanied by antiferromagnetic spin order, in a two-dimensional organic
charge-transfer salt, thus representing a new class of multiferroics. Quite
unexpectedly for electronic ferroelectrics, dipolar and spin order arise nearly
simultaneously. This can be ascribed to the loss of spin frustration induced by
the ferroelectric ordering. Hence, here the spin order is driven by the
ferroelectricity, in marked contrast to the spin-driven ferroelectricity in
helical magnets.


  Let $M = (m_{ij})$ be an $n \times n$ square matrix of integers. For our
purposes, we can assume without loss of generality that $M$ is homogeneous and
that the entries are non-increasing going leftward and downward. Let $d$ be the
sum of the entries on either diagonal. We give a complete characterization of
which such matrices have the property that a general form of degree $d$ in
$\mathbb C[x_0,x_1,x_2]$ can be written as the determinant of a matrix of forms
$(f_{ij})$ with $\deg f_{ij} = m_{ij}$ (of course $f_{ij} = 0$ if $m_{ij} <
0$). As a consequence, we answer the related question of which $(n-1) \times n$
matrices $Q$ of integers have the property that a general plane curve of degree
$d$ contains a zero-dimensional subscheme whose degree Hilbert-Burch matrix is
$Q$. This leads to an algorithmic method to determine properties of linear
series contained in general plane curves.


  We study N=2 super-conformal field theories in four dimensions that
correspond to mass-deformed linear quivers with n gauge groups and
(bi-)fundamental matter. We describe them using Seiberg-Witten curves obtained
from an M-theory construction and via the AGT correspondence. We take
particular care in obtaining the detailed relation between the parameters
appearing in these descriptions and the physical quantities of the quiver gauge
theories. This precise map allows us to efficiently reconstruct the
non-perturbative prepotential that encodes the effective IR properties of these
theories. We give explicit expressions in the cases n=1,2, also in the presence
of an Omega-background in the Nekrasov-Shatashvili limit. All our results are
successfully checked against those of the direct microscopic evaluation of the
prepotential a la Nekrasov using localization methods.


  Often when multiple labels are obtained for a training example it is assumed
that there is an element of noise that must be accounted for. It has been shown
that this disagreement can be considered signal instead of noise. In this work
we investigate using soft labels for training data to improve generalization in
machine learning models. However, using soft labels for training Deep Neural
Networks (DNNs) is not practical due to the costs involved in obtaining
multiple labels for large data sets. We propose soft label
memorization-generalization (SLMG), a fine-tuning approach to using soft labels
for training DNNs. We assume that differences in labels provided by human
annotators represent ambiguity about the true label instead of noise.
Experiments with SLMG demonstrate improved generalization performance on the
Natural Language Inference (NLI) task. Our experiments show that by injecting a
small percentage of soft label training data (0.03% of training set size) we
can improve generalization performance over several baselines.


  NGC 1448 is one of the nearest luminous galaxies ($L_{8-1000\mu m} >$ 10$^{9}
L_{\odot}$) to ours ($z$ $=$ 0.00390), and yet the active galactic nucleus
(AGN) it hosts was only recently discovered, in 2009. In this paper, we present
an analysis of the nuclear source across three wavebands: mid-infrared (MIR)
continuum, optical, and X-rays. We observed the source with the Nuclear
Spectroscopic Telescope Array (NuSTAR), and combined this data with archival
Chandra data to perform broadband X-ray spectral fitting ($\approx$0.5-40 keV)
of the AGN for the first time. Our X-ray spectral analysis reveals that the AGN
is buried under a Compton-thick (CT) column of obscuring gas along our
line-of-sight, with a column density of $N_{\rm H}$(los) $\gtrsim$ 2.5 $\times$
10$^{24}$ cm$^{-2}$. The best-fitting torus models measured an intrinsic 2-10
keV luminosity of $L_{2-10\rm{,int}}$ $=$ (3.5-7.6) $\times$ 10$^{40}$ erg
s$^{-1}$, making NGC 1448 one of the lowest luminosity CTAGNs known. In
addition to the NuSTAR observation, we also performed optical spectroscopy for
the nucleus in this edge-on galaxy using the European Southern Observatory New
Technology Telescope. We re-classify the optical nuclear spectrum as a Seyfert
on the basis of the Baldwin-Philips-Terlevich diagnostic diagrams, thus
identifying the AGN at optical wavelengths for the first time. We also present
high spatial resolution MIR observations of NGC 1448 with Gemini/T-ReCS, in
which a compact nucleus is clearly detected. The absorption-corrected 2-10 keV
luminosity measured from our X-ray spectral analysis agrees with that predicted
from the optical [OIII]$\lambda$5007\AA\ emission line and the MIR 12$\mu$m
continuum, further supporting the CT nature of the AGN.


  The possibility that star-forming galaxies may leak ionizing photons is at
the heart of many present-day studies that investigate the reionization of the
Universe. We test this hypothesis on local blue compact dwarf galaxies of very
high excitation. We assembled a sample of such galaxies by examining the
spectra from Data Releases 7 and 10 of the Sloan Digital Sky Survey. We argue
that reliable conclusions cannot be based on strong lines alone, and adopt a
strategy that includes important weak lines such as [OI] and the
high-excitation HeII and [ArIV] lines. Our analysis is based on purely
observational diagrams and on a comparison of photoionization models with
well-chosen emission-line ratio diagrams. We show that spectral energy
distributions from current stellar population synthesis models cannot account
for all the observational constraints, which led us to mimick several scenarios
that could explain the data. These include the additional presence of hard
X-rays or of shocks. We find that only ionization-bounded models (or models
with an escape fraction of ionizing photons lower than 10%) are able to
simultaneously explain all the observational constraints.


  Simulations of QCD suffer from severe critical slowing down towards the
continuum limit. This problem is known to be prominent in the topological
charge, however, all observables are affected to various degree by these slow
modes in the Monte Carlo evolution. We investigate the slowing down in high
statistics simulations and propose a new error analysis method, which gives a
realistic estimate of the contribution of the slow modes to the errors.


  The aim of this paper is to investigate the links between ${\cal T}_C$-class
algorithms, CQ Algorithm and shrinking projection methods. We show that strong
convergence of these algorithms are related to coherent ${\cal T}_C$-class
sequences of mapping. Some examples dealing with nonexpansive finite set of
mappings and nonexpansive semigroups are given. They extend some existing
theorems.


  The Krein--Tannaka duality for compact groups was a generalization the
Pontryagin--Van Kampen duality for locally compact abelian groups and a remote
predecessor of the theory of tensor categories. It is less known that it found
applications in algebraic combinatorics (``Krein algebras''). Later, this
duality was substantially extended: in \cite{V}, the notion of {\it involutive
algebras in positive vector duality} was introduced. In this paper, we
reformulate the notions of this theory using the language of bialgebras (and
Hopf algebras) and introduce the class of involutive bialgebras and positive
2-algebras. The main goal of the paper is to give a precise statement of a new
problem, which we consider as one of the main problems in this field,
concerning the existence of dilations (embeddings) of positive 2-algebras into
involutive bialgebras, or, in other words, the problem of describing subobjects
in involutive bialgebras. We define two types of subobjects in the category of
bialgebras, strict and nonstrict ones, and consider the corresponding
embeddings (dilations) of positive 2-algebras into bialgebras. The difference
between the two types of dilations is illustrated by the example of
bicommutative positive 2-algebras (commutative hypergroups). The most
interesting instance of our problem concerns dilations of the Hecke algebra
$H_n(q)$. It seems that in this case strict dilations may exist only for
$q=p^k$ (with $p$ a prime); it is not known whether nonstrict dilations exist
for other $q$. We also show that the class of finite-dimensional involutive
semisimple bialgebras coincides with the class of semigroup algebras of finite
inverse semigroups.


  This technical report extends our work presented in [9] with more
experiments. In [9], we tackle long-term video understanding, which requires
reasoning from current and past or future observations and raises several
fundamental questions. How should temporal or sequential relationships be
modelled? What temporal extent of information and context needs to be
processed? At what temporal scale should they be derived? [9] addresses these
questions with a flexible multi-granular temporal aggregation framework. In
this report, we conduct further experiments with this framework on different
tasks and a new dataset, EPIC-KITCHENS-100.


  We study the potential of noisy labels y to pretrain semantic segmentation
models in a multi-modal learning framework for geospatial applications.
Specifically, we propose a novel Cross-modal Sample Selection method (CromSS)
that utilizes the class distributions P^{(d)}(x,c) over pixels x and classes c
modelled by multiple sensors/modalities d of a given geospatial scene.
Consistency of predictions across sensors $d$ is jointly informed by the
entropy of P^{(d)}(x,c). Noisy label sampling we determine by the confidence of
each sensor d in the noisy class label, P^{(d)}(x,c=y(x)). To verify the
performance of our approach, we conduct experiments with Sentinel-1 (radar) and
Sentinel-2 (optical) satellite imagery from the globally-sampled SSL4EO-S12
dataset. We pair those scenes with 9-class noisy labels sourced from the Google
Dynamic World project for pretraining. Transfer learning evaluations
(downstream task) on the DFC2020 dataset confirm the effectiveness of the
proposed method for remote sensing image segmentation.


  We experimentally and computationally study the flow of a
quasi-two-dimensional emulsion through a constricting hopper shape. Our area
fractions are above jamming such that the droplets are always in contact with
one another and are in many cases highly deformed. At the lowest flow rates,
the droplets exit the hopper via intermittent avalanches. At the highest flow
rates, the droplets exit continuously. The transition between these two types
of behaviors is a fairly smooth function of the mean strain rate. The
avalanches are characterized by a power law distribution of the time interval
between droplets exiting the hopper, with long intervals between the
avalanches. Our computational studies reproduce the experimental observations
by adding a flexible compliance to the system. The compliance results in
continuous flow at high flow rates, and allows the system to clog at low flow
rates leading to avalanches. The computational results suggest that the
interplay of the flow rate and compliance controls the presence or absence of
the avalanches.


  An analysis of the slab phase as it is expected in the innermost layer of
neutron-star crusts is performed within the Hartree-Fock-Bogoliubov framework.
We take the periodicity of the slabs into account using Bloch boundary
conditions, in order to well describe the interplay between the band structure
and superfluidity. We introduce a relative flow between the slabs and the
surrounding neutron gas in a time-independent way. This induces a non-trivial
phase of the complex order parameter, leading to a counterflow between neutrons
inside and outside the slabs. With the resulting current, we compute the actual
neutron superfluid fraction. For the latter our results are slightly larger
than previous ones obtained in normal band theory, suggesting that normal band
theory overestimates the entrainment effect.


  Ethereum Improvement Proposal (EIP) 1559 was recently implemented to
transform Ethereum's transaction fee market. EIP-1559 utilizes an algorithmic
update rule with a constant learning rate to estimate a base fee. The base fee
reflects prevailing network conditions and hence provides a more reliable
oracle for current gas prices.
  Using on-chain data from the period after its launch, we evaluate the impact
of EIP-1559 on the user experience and market performance. Our empirical
findings suggest that although EIP-1559 achieves its goals on average,
short-term behavior is marked by intense, chaotic oscillations in block sizes
(as predicted by our recent theoretical dynamical system analysis [1]) and slow
adjustments during periods of demand bursts (e.g., NFT drops). Both phenomena
lead to unwanted inter-block variability in mining rewards. To address this
issue, we propose an alternative base fee adjustment rule in which the learning
rate varies according to an additive increase, multiplicative decrease (AIMD)
update scheme. Our simulations show that the latter robustly outperforms the
EIP-1559 protocol under various demand scenarios. These results provide
evidence that variable learning rate mechanisms may constitute a promising
alternative to the default EIP-1559-based format and contribute to the ongoing
discussion on the design of more efficient transaction fee markets.


  Subset take-away is a two-player game involving a fixed finite set A. Players
alternate choosing a proper, non-empty subset of A, with the condition that one
may not name a set containing a set that was named earlier. A player unable to
move loses. It was conjectured by David Gale that this game is always a second
player win, and this was known to hold if A has no more than 5 elements. In
this paper, we describe a technique called "binary star reduction" that often
allows one to dramatically reduce the complexity of a position. Using this tool
and some computer search we show that Gale's conjecture holds when A has six
elements. We also show how this game can be interpreted geometrically.


  Light propagation in turbulent media is conventionally studied with the help
of the spatio-temporal power spectra of the refractive index fluctuations. In
particular, for natural water turbulence several models for the spatial power
spectra have been developed based on the classic, Kolmogorov postulates.
However, as currently widely accepted, non-Kolmogorov turbulent regime is also
common in the stratified flow fields, as suggested by recent developments in
atmospheric optics. Until now all the models developed for the non-Kolmogorov
optical turbulence were pertinent to atmospheric research and, hence, involved
only one advected scalar, e.g., temperature. We generalize the oceanic spatial
power spectrum, based on two advected scalars, temperature and salinity
concentration, to the non-Kolmogorov turbulence regime, with the help of the
so-called "Upper-Bound Limitation" and by adopting the concept of spectral
correlation of two advected scalars. The proposed power spectrum can handle
general non-Kolmogorov, anisotropic turbulence but reduces to Kolmogorov,
isotropic case if the power law exponents of temperature and salinity are set
to 11/3 and anisotropy coefficient is set to unity. To show the application of
the new spectrum, we derive the expression for the second-order mutual
coherence function of a spherical wave and examine its coherence radius (in
both scalar and vector forms) to characterize the turbulent disturbance. Our
numerical calculations show that the statistics of the spherical wave vary
substantially with temperature and salinity non-Kolmogorov power law exponents
and temperature-salinity spectral correlation coefficient. The introduced
spectrum is envisioned to become of significance for theoretical analysis and
experimental measurements of non-classic natural water double-diffusion
turbulent regimes.


  We show operation of a silicon MEMS based narrow-band optical modulator with
large modulation depth by improving the electro-mechanical transducer. We
demonstrate an application of the narrowband optical modulator as both the
filter and optical modulator in an opto-electronic oscillator loop to obtain a
236.22 MHz Opto-Acoustic Oscillator (OAO) with phase noise of -68 dBc/Hz at 1
kHz offset.


  Quantum nonlocality would naturally fit into a version of relativity with a
preferred reference system. However, acceptance of this idea has traditionally
required experimental evidence. Namely, detecting in laboratory a small angular
dependence of the velocity of light correlated to the cosmic motion of the
Earth. Here, we summarize a new theoretical framework where the tiny, irregular
residuals observed so far, from Michelson-Morley to current experiments of
laser interferometry, can indeed be understood in terms of the Earth motion in
the Cosmic Microwave Background observed directly with satellites in space. Our
results, challenging the usual null interpretation, emphasize the central role
of 'ether-drift' experiments for Relativity, Cosmology and Quantum Physics.


  This short note provides a simple formal proof of a folklore result in
statistical phylogenetics concerning the convergence of bootstrap support for a
tree and its edges.


  Since the development of transport systems, humans have exploited
ground-level, below-ground, and high-altitude spaces for transportation
purposes. However, with the increasing burden of expanding populations and
rapid urbanization in recent decades, public transportation systems and freight
traffic are suffering huge pressure, plaguing local governments and straining
economies. Engineers and researchers have started to re-examine, propose, and
develop the underused near-ground spaces (NGS) for transportation purposes. For
instance, flying cars, which are not a totally novel idea, aim at solving the
traffic congestion problem and releasing the strains on existing city transport
networks by utilizing unoccupied NGS. Flying cars differ from traditional
grounded transportation systems that are entirely limited by their physical
space, such as trains on tracks or automobiles on roads. Flying cars do not
occupy or compete for high-altitude spaces used by air traffic for
long-distance transfer. However, there is a clear lack of specific literature
on flying cars and flying car transportation systems (FCTS), which this paper
aims to address by describing modern advances, techniques, and challenges of
FCTS. We explore the inherent nature of NGS transportation and devise useful
proposals to facilitate the construction and commercialization of FCTS. We
begin with an introduction to the increasing need for NGS transportation and we
address the advantages of using flying cars. Next, we present a brief overview
of the history of the development of flying cars in terms of the historic
timeline and technique development. Then, we discuss and compare the state of
the art in the design of flying cars, including the take-off \& landing (TOL)
modes, pilot modes, operation modes, and power types, ...


  Gun related violence is a complex issue and accounts for a large proportion
of violent incidents. In the research reported in this paper, we set out to
investigate the pro-gun and anti-gun sentiments expressed on a social media
platform, namely Twitter, in response to the 2012 Sandy Hook Elementary School
shooting in Connecticut, USA. Machine learning techniques are applied to
classify a data corpus of over 700,000 tweets. The sentiments are captured
using a public sentiment score that considers the volume of tweets as well as
population. A web-based interactive tool is developed to visualise the
sentiments and is available at http://www.gunsontwitter.com. The key findings
from this research are: (i) There are elevated rates of both pro-gun and
anti-gun sentiments on the day of the shooting. Surprisingly, the pro-gun
sentiment remains high for a number of days following the event but the
anti-gun sentiment quickly falls to pre-event levels. (ii) There is a different
public response from each state, with the highest pro-gun sentiment not coming
from those with highest gun ownership levels but rather from California, Texas
and New York.


  We study the statistics of fluid (gas) density and concentration of passive
tracer particles (dust) in compressible turbulence. We raise the question of
whether the fluid density which is an active field that reacts back on the
transporting flow and the passive concentration of tracers must coincide in the
steady state, which we demonstrate to be crucial both theoretically and
experimentally. The fields' coincidence is provable at small Mach numbers,
however at finite Mach numbers the assumption of mixing is needed, not evident
due to the possibility of self-organization. Irrespective of whether the fields
coincide we obtain a number of rigorous conclusions on both fields. As Ma
increases the fields in the inertial range go through a phase transition from a
finite continuous smooth to a singular multifractal distribution. We propose a
way to calculate fractal dimensions from numerical or experimental data. We
derive a simple expression for the spectrum of fractal dimensions of isothermal
turbulence and describe limitations of lognormality. The expression depends on
a single parameter: the scaling exponent of the density spectrum. We propose a
mechanism for the phase transition of concentration to multifractality. We
demonstrate that the pair-correlation function is invariant under the action of
the probability density function of the inter-pair distance that has the Markov
property implying applicability of the Kraichnan turbulence model. We use the
model to derive an explicit expression for the tracers pair correlation that
demonstrates their smooth transition to multifractality and confirms the
transition's mechanism. Our results are of potentially important implications
on astrophysical problems such as star formation as well as on technological
applications such as supersonic combustion. As an example we demonstrate strong
increase of planetesimals formation rate at the transition.


  We revisit the exact microscopic equations (in differential, and equivalent
integral form) ruling a relativistic cold plasma after the plane-wave Ansatz,
without customary approximations. We show that in the Eulerian description the
motion of a very diluted plasma initially at rest and excited by an arbitrary
transverse plane electromagnetic travelling-wave has a very simple and explicit
dependence on the transverse electromagnetic potential; for a non-zero density
plasma the above motion is a good approximation of the real one as long as the
back-reaction of the charges on the electromagnetic field can be neglected,
i.e. for a time lapse decreasing with the plasma density, and can be used as
initial step in an iterative resolution scheme.
  As one of many possible applications, we use these results to describe how
the ponderomotive force of a very intense and short plane laser pulse hitting
normally the surface of a plasma boosts the surface electrons into the ion
background. Because of this penetration the electrons are then pulled back by
the electric force exerted by the ions and may leave the plasma with high
energy in the direction opposite to that of propagation of the pulse [G. Fiore,
R. Fedele, U. De Angelis, "The slingshot effect: a possible new laser-driven
high energy acceleration mechanism for electrons", arXiv:1309.1400].


  Terrestrial planets grew in a series of similar-sized collisions that swept
up most of the next-largest bodies. Theia was accreted by the Earth to form the
Moon according to the theory. Planetesimals likewise may have finished their
accretion in a sequence of 'junior giant impacts', scaled down in size and
velocity. This chapter considers the complicated physics of pairwise accretion,
as planetesimals grow to planetary scales, and considers how the inefficiency
of that process influences the origin of planetesimals and the diversity of
meteorites and primary asteroids.


  In this paper, we propose an improved Bayesian bidirectional long-short term
memory (BiLSTM) neural networks for multi-step ahead (MSA) solar generation
forecasting. The proposed technique applies alpha-beta divergence for a more
appropriate consideration of outliers in the solar generation data and
resulting variability of the weight parameter distribution in the neural
network. The proposed method is examined on highly granular solar generation
data from Ausgrid using probabilistic evaluation metrics such as Pinball loss
and Winkler score. Moreover, a comparative analysis between MSA and the
single-step ahead (SSA) forecasting is provided to test the effectiveness of
the proposed method on variable forecasting horizons. The numerical results
clearly demonstrate that the proposed Bayesian BiLSTM with alpha-beta
divergence outperforms standard Bayesian BiLSTM and other benchmark methods for
MSA forecasting in terms of error performance.


  For Hill's equations with matrix valued periodic potential, we discuss
relations between the Morse index, counting the number of unstable eigenvalues,
and the Maslov index, counting the number of signed intersections of a path in
the space of Lagrangian planes with a fixed plane. We adapt to the one
dimensional periodic setting the strategy of a recent paper by J. Deng and C.
Jones relating the Morse and Maslov indices for multidimensional elliptic
eigenvalue problems.


  If nature realizes $TeV$ scale gravity, we are entering a very exciting
period in which we could be able to address, experimentally, some questions on
quantum gravity, strings, branes and other exotic aspects of the fundamental
theory of gravity. This article reviews recent development in models with Large
Extra Dimensions and Black hole production at future colliders. Experimental
results from current experiments as well as the expectation for the future
colliders are summarized.


  The program dependence graph (PDG) represents data and control dependence
between statements in a program. This paper presents an operational semantics
of program dependence graphs. Since PDGs exclude artificial order of statements
that resides in sequential programs, executions of PDGs are not unique.
However, we identified a class of PDGs that have unique final states of
executions, called deterministic PDGs. We prove that the operational semantics
of control flow graphs is equivalent to that of deterministic PDGs. The class
of deterministic PDGs properly include PDGs obtained from well-structured
programs. Thus, our operational semantics of PDGs is more general than that of
PDGs for well-structured programs, which are already established in literature.


  We combine different wavelengths from an intense high-order harmonics source
with variable delay at the focus of a split-mirror interferometer to conduct
pump-probe experiments on gas-phase molecules. We report measurements of the
time resolution (<44 fs) and spatial profiles (4 {\mu}m x 12 {\mu}m) at the
focus of the apparatus. We demonstrate the utility of this two-color,
high-order-harmonic technique by time resolving molecular hydrogen elimination
from C2H4 excited into its absorption band at 161 nm.


  We report measurements of partial branching fractions of inclusive charmless
semileptonic $B$-meson decays at the endpoint of the electron momentum
spectrum. The measurements are made in six overlapping momentum intervals that
have lower bounds ranging from 1.9 GeV/$c$ to 2.4 GeV/$c$ and a common upper
bound of 2.6 GeV/$c$, as measured in the centre of mass frame. The results are
based on a sample of 29 million $B\bar{B}$ pairs, accumulated by the Belle
detector at the KEKB asymmetric $e^+e^-$ collider operating on the
$\Upsilon(4S)$ resonance. In the momentum interval ranging from 1.9 GeV/$c$ to
2.6 GeV/$c$ we measure the partial branching fraction $\Delta \mathcal{B}(B\to
X_u e \nu_e)=(8.47 \pm 0.37 \pm 1.53)\times 10^{-4}$, where the first error is
statistical and the second is systematic. A prediction of the partial rate
$R=(21.69 \pm 3.62^{+ 2.18}_{- 1.98}) |V_{ub}|^2 \mathrm{ps}^{-1}$ in this
momentum interval based on theory is calculated with input HQET parameters that
have been derived from Belle's measurement of the $B\to X_s\gamma$ photon
energy spectrum, where the first error is due to the uncertainty on HQET
parameters and the second error is from theory. Using both $\Delta
\mathcal{B}(B\to X_u e \nu_e)$ and $R$ we find $|V_{ub}|=(5.08 \pm 0.47 \pm
0.42^{+ 0.26}_{- 0.23})\times 10^{-3}$, where the first error is from the
partial branching fraction, and the second and third errors are from
uncertainties in $R$.


  The fermion spin-flip conversion $f_L \to f_R + \gamma$ is considered, caused
by the difference of the additional energies of the electroweak origin,
acquired by left- and right-handed fermions (neutrino, electron) in medium. An
accurate taking account of the fermion and photon dispersion in medium is shown
to be important.


  We report a measurement of a new high spin Jp = 5- state at 22.4(0.2) MeV in
12C which fits very well to the predicted (ground state) rotational band of an
oblate equilateral triangular spinning top with a D_3h symmetry characterized
by the sequence 0+, 2+, 3-, 4+/-, 5- with almost degenerate 4+ and 4- (parity
doublet) states. Such a D_3h symmetry was observed in triatomic molecules and
it is observed here for the first time in nuclear physics. We discuss a
classification of other rotation-vibration bands in 12C such as the (0+) Hoyle
band and the (1-) bending mode band and suggest measurements in search of the
predicted ("missing") states that may shed new light on clustering in 12C and
light nuclei. In particular the observation (or non-observation) of the
predicted ("missing") states in the Hoyle band will allow us to conclude the
geometrical arrangement of the three alpha-particle composing the Hoyle state
at 7.654 MeV in 12C.


  We report the operation of a field-effect transistor based on a single InAs
nanowire gated by an ionic liquid. Liquid gating yields very efficient carrier
modulation with a transconductance value thirty time larger than standard back
gating with the SiO2 /Si++ substrate. Thanks to this wide modulation we show
the controlled evolution from semiconductor to metallic-like behavior in the
nanowire. This work provides the first systematic study of ionic-liquid gating
in electronic devices based on individual III-V semiconductor nanowires: we
argue this architecture opens the way to a wide range of fundamental and
applied studies from the phase-transitions to bioelectronics.


  We propose a modified Josephson corner-junction experiment which can test
whether the order parameter in the iron pnictides changes sign between the
electron and hole pockets of the Fermi surface.


  Risaliti and Lusso have compiled X-ray and UV flux measurements of 1598
quasars (QSOs) in the redshift range $0.036 \leq z \leq 5.1003$, part of which,
$z \sim 2.4 - 5.1$, is largely cosmologically unprobed. In this paper we use
these QSO measurements, alone and in conjunction with baryon acoustic
oscillation (BAO) and Hubble parameter [$H(z)$] measurements, to constrain
cosmological parameters in six different cosmological models, each with two
different Hubble constant priors. In most of these models, given the larger
uncertainties, the QSO cosmological parameter constraints are mostly consistent
with those from the $H(z)$ + BAO data. A somewhat significant exception is the
non-relativistic matter density parameter $\Omega_{m0}$ where the QSO data
favors $\Omega_{m0} \sim 0.5 - 0.6$ in most models. Consequently in joint
analyses of QSO data with $H(z)$ + BAO data the one-dimensional $\Omega_{m0}$
distributions shift slightly toward larger values. A joint analysis of the QSO
+ $H(z)$ + BAO data is consistent with the current standard model,
spatially-flat $\Lambda$CDM, but mildly favors closed spatial hypersurfaces and
dynamical dark energy. Since the higher $\Omega_{m0}$ values favored by the QSO
data appear to be associated with the $z \sim 2 - 5$ part of these data, and
conflict somewhat with strong indications for $\Omega_{m0} \sim 0.3$ from most
$z < 2.5$ data as well as from the cosmic microwave background anisotropy data
at $z \sim 1100$, in most models, the larger QSO data $\Omega_{m0}$ is possibly
more indicative of an issue with the $z \sim 2 - 5$ QSO data than of an
inadequacy of the standard flat $\Lambda$CDM model.


  We present a mechanism to sort out particles of different masses in an
asymmetric channel, where the entropic barriers arise naturally and control the
diffusion of these particles. When particles are subjected to an oscillatory
force, with the scaled amplitude $a$ and frequency $\omega$, the mean particle
velocity exhibits a bell-shaped behavior as a function of the particle mass,
indicating that particles with an optimal mass $m_{op}$ drift faster than other
particles. By tuning $a$ and $\omega$, we get an empirical relation to estimate
$m_{op} \sim (a\,\omega^2)^{-0.4}$. An additional static bias, applied in the
opposite direction of the rectified velocity, would push the particles of
lighter mass to move in its direction while the others drift opposite to it.
This study is useful to design lab-on-a-chip devices for separating particles
of different masses.


  We study the parameter space of cold dark matter axions in two cosmological
scenarios with non-standard thermal histories before Big Bang nucleosynthesis:
the Low Temperature Reheating (LTR) cosmology and the kination cosmology. If
the Peccei-Quinn symmetry breaks during inflation, we find more allowed
parameter space in the LTR cosmology than in the standard cosmology and less in
the kination cosmology. On the contrary, if the Peccei-Quinn symmetry breaks
after inflation, the Peccei-Quinn scale is orders of magnitude higher than
standard in the LTR cosmology and lower in the kination cosmology. We show that
the axion velocity dispersion may be used to distinguish some of these
non-standard cosmologies. Thus, axion cold dark matter may be a good probe of
the history of the Universe before Big Bang nucleosynthesis.


  With the advent of the Post-Moore era, the scientific community is faced with
the challenge of addressing the demands of current data-intensive machine
learning applications, which are the cornerstone of urgent analytics in
distributed computing. Quantum machine learning could be a solution for the
increasing demand of urgent analytics, providing potential theoretical speedups
and increased space efficiency. However, challenges such as (1) the encoding of
data from the classical to the quantum domain, (2) hyperparameter tuning, and
(3) the integration of quantum hardware into a distributed computing continuum
limit the adoption of quantum machine learning for urgent analytics. In this
work, we investigate the use of Edge computing for the integration of quantum
machine learning into a distributed computing continuum, identifying the main
challenges and possible solutions. Furthermore, exploring the data encoding and
hyperparameter tuning challenges, we present preliminary results for quantum
machine learning analytics on an IoT scenario.


  We present new radio continuum observations of two dwarf starburst galaxies,
NGC3125 and NGC5408, with observations at 4.80GHz (6cm) and 8.64GHz (3cm),
taken with the Australia Telescope Compact Array (ATCA). Both galaxies show a
complex radio morphology with several emission regions, mostly coincident with
massive young star clusters. The radio spectral indices of these regions are
negative (with alpha ~ -0.5 - -0.7), indicating that the radio emission is
dominated by synchrotron emission associated with supernova activity from the
starburst. One emission region in NGC5408 has a flatter index (alpha ~ -0.1)
indicative of optically thin free-free emission, which could indicate it is a
younger cluster. Consequently, in these galaxies we do not see regions with the
characteristic positive spectral index indicative of optically obscured
star-formation regions, as seen in other dwarf starbursts such as Hen 2-10.


  We study the phenomenological credibility of a vectorial dark matter, coupled
to a $Z'$ portal through Chern-Simons interaction. We scrutinize two
possibilities of connecting a $Z'$ with the Standard Model: (1) through kinetic
mixing and (2) from a second Chern-Simons interaction. Both scenarios are
characterized by suppressed nuclear recoil scatterings, rendering direct
detection searches not promising. Indirect detection experiments, on the other
hand, furnish complementary limits for TeV scale masses, specially with the
CTA. Searches for mono-jet and dileptons signals at the LHC are important to
partially probe the kinetic mixing setup. Finally we propose an UV completion
of the Chern-Simons Dark Matter framework.


  We report on our calculation of the kaon semileptonic form factors in Nf=2+1
lattice QCD. Chiral symmetry is exactly preserved by using the overlap quark
action for a straightforward comparison with chiral perturbation theory (ChPT).
We simulate three pion masses down to 290 MeV at a single lattice spacing of
0.11 fm and at a strange quark mass very close to its physical value. The form
factors near zero momentum transfer are precisely calculated by using the
all-to-all propagator and twisted boundary conditions. We compare the
normalizations and slopes of the form factors with ChPT and experiments.


  Light cone spreading of correlations and entanglement is a key feature of the
non-equilibrium quench dynamics of many-body quantum systems. First proposed
theoretically, it has been experimentally revealed in cold-atomic gases and it
is expected to be a generic characteristic of any quench in systems with
short-range interactions and no disorder. Conversely, here we propose a
mechanism that, through confinement of the elementary excitations, strongly
suppresses the light-cone spreading. Confinement is a celebrated concept in
particle physics, but it also exists in condensed matter systems, most notably
in one spatial dimension where it has been experimentally observed. Our results
are obtained for the Ising spin chain with transverse and longitudinal magnetic
field, but the proposed mechanism is of general validity since it is based on
the sole concept of confinement and it should be easily observed in cold atom
experiments.


  We construct a sequence of rank 3 distributions on $n$-dimensional manifolds
for any $n\geq 7$ such that the dimension of their symmetry group grows
exponentially in $n$ (more precisely it is equal to
$\operatorname{Fib}_{n-1}+n+2$, where $\operatorname{Fib}_n$ is the $n$-th
Fibonacci number, starting with $\operatorname{Fib}_1=\operatorname{Fib}_2=1$)
and such that the maximal order of weighted jet needed to determine these
symmetries grows quadratically in $n$. These examples are in sharp contrast
with the parabolic geometries where the dimension of a symmetry group grows
polynomially with respect to the dimension of the ambient manifold and the
corresponding maximal order of weighted jet space is equal to the degree of
nonholonomy of the underlying distribution plus $1$. Our models are closely
related to the geometry of certain curves of symplectic flags and of the
rational normal curves.


  We present comprehensive experimental line lists of methane (CH4) at high
temperatures obtained by recording Fourier transform infrared emission spectra.
Calibrated line lists are presented for the temperatures 300 - 1400 degC at
twelve 100 degC intervals spanning the 960 - 5000 cm-1 (2.0 - 10.4 microns)
region of the infrared. This range encompasses the dyad, pentad and octad
regions, i.e., all fundamental vibrational modes along with a number of
combination, overtone and hot bands. Using our CH4 spectra, we have estimated
empirical lower state energies (Elow in cm-1) and our values have been
incorporated into the line lists along with line positions (cm-1) and
calibrated line intensities (S' in cm molecule-1). We expect our hot CH4 line
lists to find direct application in the modeling of planetary atmospheres and
brown dwarfs.


  The Born rule, a foundational axiom used to deduce probabilities of events
from wavefunctions, is indispensable in the everyday practice of quantum
physics. It is also key in the quest to reconcile the ostensibly inconsistent
laws of the quantum and classical realms, as it confers physical significance
to reduced density matrices, the essential tools of decoherence theory.
Following Bohr's Copenhagen interpretation, textbooks postulate the Born rule
outright. However, recent attempts to derive it from other quantum principles
have been successful, holding promise for simplifying and clarifying the
quantum foundational bedrock. A major family of derivations is based on
envariance, a recently discovered symmetry of entangled quantum states. Here,
we identify and experimentally test three premises central to these
envariance-based derivations, thus demonstrating, in the microworld, the
symmetries from which the Born rule is derived. Further, we demonstrate
envariance in a purely local quantum system, showing its independence from
relativistic causality.


  We propose to cast the task of morphological inflection - mapping a lemma to
an indicated inflected form - for resource-poor languages as a meta-learning
problem. Treating each language as a separate task, we use data from
high-resource source languages to learn a set of model parameters that can
serve as a strong initialization point for fine-tuning on a resource-poor
target language. Experiments with two model architectures on 29 target
languages from 3 families show that our suggested approach outperforms all
baselines. In particular, it obtains a 31.7% higher absolute accuracy than a
previously proposed cross-lingual transfer model and outperforms the previous
state of the art by 1.7% absolute accuracy on average over languages.


  Network analysis has become an increasingly prevalent research tool across a
vast range of scientific fields. Here, we focus on the particular issue of
comparing network statistics, i.e. graph-level measures of network structural
features, across multiple networks that differ in size. Although "normalized"
versions of some network statistics exist, we demonstrate via simulation why
direct comparison of raw and normalized statistics is often inappropriate. We
examine a recent suggestion to normalize network statistics relative to
Erdos-Renyi random graphs and demonstrate via simulation how this is an
improvement over direct comparison, but still sometimes problematic. We propose
a new adjustment method based on a reference distribution constructed as a
mixture model of random graphs which reflect the dependence structure exhibited
in the observed networks. We show that using simple Bernoulli models as mixture
components in this reference distribution can provide adjusted network
statistics that are relatively comparable across different network sizes but
still describe interesting features of networks, and that this can be
accomplished at relatively low computational expense. Finally, we apply this
methodology to a collection of co-location networks derived from the Los
Angeles Family and Neighborhood Survey activity location data.


  We examine the decoherence properties of a quantum open system as modeled by
a quantum optical system in the Markov regime. We look for decoherence in both
the Environment Induced Superselection (EIS) and Consistent Histories (CH)
frameworks. We propose a general measure of the coherence of the reduced
density matrix and find that EIS decoherence occurs in a number of bases for
this model. The degree of ``diagonality'' achieved increases with bath
temperature. We evaluate the Decoherence Functional of Consistent Histories for
coarse grained phase space two-time projected histories. Using the measures
proposed by Dowker and Halliwell we find that the consistency of the histories
improves with increasing bath temperature, time and final grain size and
decreases with initial grain size. The peaking increases with increasing grain
size and decreases with increasing bath temperature. Adopting the above
proposed measure of ``coherence'' to the Decoherence Functional gives similar
results. The results agree in general with expectations while the anomalous
dependence of the consistency on the initial grain size is discussed.


  With the proliferation of mobile computing devices, the demand for continuous
network connectivity regardless of physical location has spurred interest in
the use of mobile ad hoc networks. Since Transmission Control Protocol (TCP) is
the standard network protocol for communication in the internet, any wireless
network with Internet service need to be compatible with TCP. TCP is tuned to
perform well in traditional wired networks, where packet losses occur mostly
because of congestion. However, TCP connections in Ad-hoc mobile networks are
plagued by problems such as high bit error rates, frequent route changes,
multipath routing and temporary network partitions. The throughput of TCP over
such connection is not satisfactory, because TCP misinterprets the packet loss
or delay as congestion and invokes congestion control and avoidance algorithm.
In this research, the performance of TCP in Adhoc mobile network with high Bit
Error rate (BER) and mobility is studied and investigated. Simulation model is
implemented and experiments are performed using the Network Simulatior 2 (NS2).


  In this article we study the existence of limit cycles in families of
piecewise smooth differential equations having the unit circle as discontinuity
region. We consider families presenting singularities of center or saddle type,
visible or invisible, as well as the case without singularities. We establish
an upper bound for the number of limit cycles and give examples showing that
the maximum number of limit cycles can be reached. We also discuss the
existence of homoclinic cycles for such differential equations in the
saddle-center case.


  We report on the ion beam fabrication of all-carbon multi electrode arrays
(MEAs) based on 16 graphitic micro-channels embedded in single-crystal diamond
(SCD) substrates. The fabricated SCD-MEAs are systematically employed for the
in vitro simultaneous amperometric detection of the secretory activity from
populations of chromaffin cells, demonstrating a new sensing approach with
respect to standard techniques. The biochemical stability and biocompatibility
of the SCD-based device combined with the parallel recording of
multi-electrodes array allow: i) a significant time saving in data collection
during drug screening and/or pharmacological tests over a large number of
cells, ii) the possibility of comparing altered cell functionality among cell
populations, and iii) the repeatition of acquisition runs over many cycles with
a fully non-toxic and chemically robust bio-sensitive substrate.


  We propose a novel mechanism where Primordial Black Hole (PBH) dark matter is
formed much later in the history of the universe between the epoch of Big Bang
Nucleosynthesis (BBN) and Cosmic Microwave Background (CMB) photon decoupling.
In our setup, one does not need to modify the scale-invariant inflationary
power spectra; instead, a late phase transition in strongly interacting
fermion-scalar fluid (which naturally occurs around red-shift $ 10^6 \leq \,
z_{\scriptscriptstyle T} \, \leq 10^8$ ) creates an instability in the density
perturbation as sound speed turns imaginary. As a result, the dark matter
perturbation grows exponentially in sub-Compton scales. This follows the
immediate formation of early dense dark matter halo, which finally evolves into
PBH due to cooling through scalar radiation. We calculate the variance of the
density perturbations and PBH fractional abundances $f(M)$ by using a
non-monochromatic mass function. We find the peak of our PBH mass function lies
between $10^{-16} - 10^{-14}$ solar mass for $ z_{\scriptscriptstyle T} \simeq
10^6$, and thus it can be the entire dark matter of the universe. In PBH
formation, one would expect a temporary phase where an attractive scalar
balances the Fermi pressure. We numerically confirm that such a state indeed
exists, and we find the radius and density profile of the temporary static
structure of the dark matter halo, which finally evolves to PBH due to cooling
through scalar radiation.


  The generating function of the Betti numbers of the Heisenberg Lie algebra
over a field of characteristic 2 is calculated using discrete Morse theory.


  The Fokker-Planck Equation, applied to transport processes in fusion plasmas,
can model several anomalous features, including uphill transport, scaling of
confinement time with system size, and convective propagation of externally
induced perturbations. It can be justified for generic particle transport
provided that there is enough randomness in the Hamiltonian describing the
dynamics. Then, except for 1 degree-of-freedom, the two transport coefficients
are largely independent. Depending on the statistics of interest, the same
dynamical system may be found diffusive or dominated by its L\'{e}vy flights.


  This paper starts by an investigation of nonlinear transmission in
space-division multiplexed (SDM) systems using multimode fibers exhibiting a
rapidly varying birefringence. A primary objective is to generalize the Manakov
equations, well known in the case of single-mode fibers. We first investigate a
reference case where linear coupling among the spatial modes of the fiber is
weak and after averaging over birefringence fluctuations, we obtain new Manakov
equations for multimode fibers. Such an averaging reduces the number of
intermodal nonlinear terms drastically since all four-wave-mixing terms average
out. Cross-phase modulation terms still affect multimode transmission but their
effectiveness is reduced. We then verify the accuracy of our new Manakov
equations by transmitting multiple PDM-QPSK signals over different modes of a
multimode fiber and comparing the numerical results with those obtained by
solving the full stochastic equation. The agreement is excellent in all cases
studied. A great benefit of the new equations is to reduce the computation time
by a factor of 10 or more. Another important feature observed is that
birefringence fluctuations improve system performance by reducing the impact of
fiber nonlinearities. Finally multimode fibers with strong random coupling
among all spatial modes are considered. Linear coupling is modeled using the
random matrix theory approach. We derive new Manakov equations for multimode
fibers in that regime and show that such fibers can perform better than
single-modes fiber for large number of propagating spatial modes.


  We present a mobile dataset obtained from electroencephalography (EEG) of the
scalp and around the ear as well as from locomotion sensors by 24 participants
moving at four different speeds while performing two brain-computer interface
(BCI) tasks. The data were collected from 32-channel scalp-EEG, 14-channel
ear-EEG, 4-channel electrooculography, and 9-channel inertial measurement units
placed at the forehead, left ankle, and right ankle. The recording conditions
were as follows: standing, slow walking, fast walking, and slight running at
speeds of 0, 0.8, 1.6, and 2.0m/s, respectively. For each speed, two different
BCI paradigms, event-related potential and steady-state visual evoked
potential, were recorded. To evaluate the signal quality, scalp- and ear-EEG
data were qualitatively and quantitatively validated during each speed. We
believe that the dataset will facilitate BCIs in diverse mobile environments to
analyze brain activities and evaluate the performance quantitatively for
expanding the use of practical BCIs.


  The super Pioneering High Energy Nuclear Interaction eXperiment (sPHENIX) at
the Relativistic Heavy Ion Collider (RHIC) will perform high precision
measurements of jets and heavy flavor observables for a wide selection of
nuclear collision systems, elucidating the microscopic nature of strongly
interacting matter ranging from nucleons to the strongly coupled quark-gluon
plasma. A prototype of the sPHENIX calorimeter system was tested at the
Fermilab Test Beam Facility as experiment T-1044 in the spring of 2016. The
electromagnetic calorimeter (EMCal) prototype is composed of scintillating
fibers embedded in a mixture of tungsten powder and epoxy. The hadronic
calorimeter (HCal) prototype is composed of tilted steel plates alternating
with plastic scintillator. Results of the test beam reveal the energy
resolution for electrons in the EMCal is $2.8\%\oplus~15.5\%/\sqrt{E}$ and the
energy resolution for hadrons in the combined EMCal plus HCal system is
$13.5\%\oplus 64.9\%/\sqrt{E}$. These results demonstrate that the performance
of the proposed calorimeter system satisfies the sPHENIX specifications.


  Oeljeklaus-Toma manifolds are complex non-K\"ahler manifolds constructed by
Oeljeklaus and Toma from certain number fields, and generalizing the Inoue
surfaces $S_m$. We prove that Oeljeklaus-Toma manifolds contain no compact
complex curves.


  The purpose of this report is to define abstractions for multi-agent systems
under coupled constraints. In the proposed decentralized framework, we specify
a finite or countable transition system for each agent which only takes into
account the discrete positions of its neighbors. The dynamics of the considered
systems consist of two components. An appropriate feedback law which guarantees
that certain performance requirements (eg. connectivity) are preserved and
induces the coupled constraints and additional free inputs which we exploit in
order to accomplish high level tasks. In this work we provide sufficient
conditions on the space and time discretization of the system which ensure that
we can extract a well posed and hence meaningful finite transition system.


  As autonomous systems begin to operate amongst humans, methods for safe
interaction must be investigated. We consider an example of a small autonomous
vehicle in a pedestrian zone that must safely maneuver around people in a
free-form fashion. We investigate two key questions: How can we effectively
integrate pedestrian intent estimation into our autonomous stack. Can we
develop an online monitoring framework to give formal guarantees on the safety
of such human-robot interactions. We present a pedestrian intent estimation
framework that can accurately predict future pedestrian trajectories given
multiple possible goal locations. We integrate this into a reachability-based
online monitoring scheme that formally assesses the safety of these
interactions with nearly real-time performance (approximately 0.3 seconds).
These techniques are integrated on a test vehicle with a complete in-house
autonomous stack, demonstrating effective and safe interaction in real-world
experiments.


  In this paper, we provide the exact expression for the coefficients in the
low-temperature series expansion of the partition function of the
two-dimensional Ising model on the infinite square lattice. This is equivalent
to exact determination of the number of spin configurations at a given energy.
With these coefficients, we show that the ferromagnetic--to--paramagnetic phase
transition in the square lattice Ising model can be explained through
equivalence between the model and the perfect gas of energy clusters model, in
which the passage through the critical point is related to the complete change
in the thermodynamic preferences on the size of clusters. The combinatorial
approach reported in this article is very general and can be easily applied to
other lattice models.


  Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife
monitoring, with several advantages over traditional field-based methods. They
have readily been used to count birds, marine mammals and large herbivores in
different environments, tasks which are routinely performed through manual
counting in large collections of images. In this paper, we propose a
semi-automatic system able to detect large mammals in semi-arid Savanna. It
relies on an animal-detection system based on machine learning, trained with
crowd-sourced annotations provided by volunteers who manually interpreted
sub-decimeter resolution color images. The system achieves a high recall rate
and a human operator can then eliminate false detections with limited effort.
Our system provides good perspectives for the development of data-driven
management practices in wildlife conservation. It shows that the detection of
large mammals in semi-arid Savanna can be approached by processing data
provided by standard RGB cameras mounted on affordable fixed wings UAVs.


  The collision processes of two crescentic dunes called barchans are
systematically studied using a simple computer simulation model. The simulated
processes, coalescence, ejection and reorganization, qualitatively correspond
to those observed in a water tank experiment. Moreover we found the realized
types of collision depend both on the mass ratio and on the lateral distance
between barchans under initial conditions. A simple set of differential
equations to describe the collision of one-dimensional (1D) dunes is
introduced.


  In this work we study demagnetization protocols for an artificial spin ice in
a triangular geometry. Our results show that a simple hysteresis-like process
is very efficient in driving the system to its ground state, even for a
relatively strong disorder in the system, confirming previous expectations. In
addition, transitions between the magnetized state and the ground state were
observed to be mediated by the creation and propagation of vertices that behave
like magnetic monopoles pseudo-particles. This is an important step towards a
more detailed experimental study of monopole-like excitations in artificial
spin ice systems.


  This paper studies the cross-layer challenges and performance of Hybrid
Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in 5G
millimeter wave (mmWave) cellular networks with full-stack TCP/IP traffic and
MAC scheduling. While previous research on HBF and MU-MIMO has focused on
link-level analysis of full-buffer transmissions, this work reveals the
interplay between HBF techniques and the higher layers of the protocol stack.
To this aim, prior work on full stack simulation of mmWave cellular network has
been extended by including the modeling of MU-MIMO and HBF. Our results reveal
novel relations between the networking layers and the HBF MU-MIMO performance
in the physical layer. Particularly, throughput can be increased in 5G networks
by means of Spatial Division Multiple Access (SDMA). However, in order to
achieve such benefits it is necessary to take into account certain trade-offs
and the implementation complexity of a full-stack HBF solution.


  We study the generation of large-scale vortices in rotating turbulent
convection by means of Cartesian direct numerical simulations. We find that for
sufficiently rapid rotation, cyclonic structures on a scale large in comparison
to that of the convective eddies, emerge, provided that the fluid Reynolds
number exceeds a critical value. For slower rotation, cool cyclonic vortices
are preferred, whereas for rapid rotation, warm anti-cyclonic vortices are
favored. In some runs in the intermediate regime both types of cyclones
co-exist for thousands of convective turnover times. The temperature contrast
between the vortices and the surrounding atmosphere is of the order of five per
cent. We relate the simulation results to observations of rapidly rotating
late-type stars that are known to exhibit large high-latitude spots from
Doppler imaging. In many cases, cool spots are accompanied with spotted regions
with temperatures higher than the average. In this paper, we investigate a
scenario according to which the spots observed in the temperature maps could
have a non-magnetic origin due to large-scale vortices in the convection zones
of the stars.


  We analyze two theoretical approaches to ensemble averaging for integrable
systems in quantum chaos - spectral averaging and parametric averaging. For
spectral averaging, we introduce a new procedure - rescaled spectral averaging.
Unlike traditional spectral averaging, it can describe the correlation function
of spectral staircase and produce persistent oscillations of the interval level
number variance. Parametric averaging, while not as accurate as rescaled
spectral averaging for the correlation function of spectral staircase and
interval level number variance, can also produce persistent oscillations of the
global level number variance and better describes saturation level rigidity as
a function of the running energy. Overall, it is the most reliable method for a
wide range of statistics.


  The physics of the state at even denominator fractional fillings of Landau
levels depends on the Coulomb pseudopotentials, and produces, in different GaAs
Landau levels, a composite fermion Fermi sea, a stripe phase, or, possibly, a
paired composite fermion state. We consider here even denominator fractions in
graphene, which has different pseudopotentials as well as a possible four fold
degeneracy of each Landau level. We test various composite fermion Fermi sea
wave functions (fully polarized, SU(2) singlet, SU(4) singlet) as well as the
paired composite fermion states in the n=0 and $n=1$ Landau levels and predict
that (i) the paired states are not favorable, (ii) CF Fermi seas occur in both
Landau levels, and (iii) an SU(4) singlet composite fermion Fermi sea is
stabilized in the appropriate limit. The results from detailed microscopic
calculations are generally consistent with the predictions of the mean field
model of composite fermions.


  We theoretically investigate the quantum uncertainty in the beam width of
transverse optical modes and, for this purpose, define a corresponding quantum
operator. Single mode states are studied as well as multimode states with small
quantum noise. General relations are derived, and specific examples of
different modes and quantum states are examined. For the multimode case, we
show that the quantum uncertainty in the beam width can be completely
attributed to the amplitude quadrature uncertainty of one specific mode, which
is uniquely determined by the field under investigation. This discovery
provides us with a strategy for the reduction of the beam width noise by an
appropriate choice of the quantum state.


  In the general framework of a semimartingale financial model and a utility
function $U$ defined on the positive real line, we compute the first-order
expansion of marginal utility-based prices with respect to a ``small'' number
of random endowments. We show that this linear approximation has some important
qualitative properties if and only if there is a risk-tolerance wealth process.
In particular, they hold true in the following polar cases:
\begin{tabular}@p97mm@ for any utility function $U$, if and only if the set of
state price densities has a greatest element from the point of view of
second-order stochastic dominance;for any financial model, if and only if $U$
is a power utility function ($U$ is an exponential utility function if it is
defined on the whole real line). \end{tabular}


  Conventional entity typing approaches are based on independent classification
paradigms, which make them difficult to recognize inter-dependent, long-tailed
and fine-grained entity types. In this paper, we argue that the implicitly
entailed extrinsic and intrinsic dependencies between labels can provide
critical knowledge to tackle the above challenges. To this end, we propose
\emph{Label Reasoning Network(LRN)}, which sequentially reasons fine-grained
entity labels by discovering and exploiting label dependencies knowledge
entailed in the data. Specifically, LRN utilizes an auto-regressive network to
conduct deductive reasoning and a bipartite attribute graph to conduct
inductive reasoning between labels, which can effectively model, learn and
reason complex label dependencies in a sequence-to-set, end-to-end manner.
Experiments show that LRN achieves the state-of-the-art performance on standard
ultra fine-grained entity typing benchmarks, and can also resolve the long tail
label problem effectively.