  A small number of anomalously bright boulders on the near-Earth, rubble-pile
asteroid (101955) Bennu were recently identified as eucritic material
originating from asteroid (4) Vesta. Building on this discovery, we explored
the global presence of exogenic boulders on Bennu. Our analysis focused on
boulders larger than 1 m that show the characteristic 1-micron pyroxene
absorption band in the four-color MapCam data from the OSIRIS-REx mission. We
confirm the presence of exogenic boulders similar to eucrites and find that
mixtures of eucrites with carbonaceous material is also a possible composition
for some boulders. Some of the exogenic boulders have spectral properties
similar to those of ordinary chondrite (OC) meteorites, although the laboratory
spectra of these meteorites have a higher albedo than those measured on Bennu,
which could be explained by either a grain size effect, the presence of impact
melt, or optical mixing with carbonaceous material owing to dust coating. Our
Monte Carlo simulations predict that the median amount of OC mass added to the
parent body of Bennu is 0.055% and 0.037% of the volume of a 100- and
200-km-diameter parent body, respectively. If Bennu was a uniformly mixed
byproduct of parent body and S-type projectiles, the equivalent mass of OC
material would be a sphere with a diameter of 36 to 40 m (or a volume of 24,200
to 33,600 m3). The total amount of OC material in the interior of Bennu
estimated from the MapCam data is slightly higher (91,000-150,000 m3).


  Young's experiment is the quintessential quantum experiment. It is argued
here that quantum interference is a consequence of the finiteness of
information. The observer has the choice whether that information manifests
itself as path information or in the interference pattern or in both partially
to the extent defined by the finiteness of information.


  We consider machine learning techniques associated with the application of a
Boosted Decision Tree (BDT) to searches at the Large Hadron Collider (LHC) for
pair-produced lepton partners which decay to leptons and invisible particles.
This scenario can arise in the Minimal Supersymmetric Standard Model (MSSM),
but can be realized in many other extensions of the Standard Model (SM). We
focus on the case of intermediate mass splitting ($\sim 30~{\rm GeV}$) between
the dark matter (DM) and the scalar. For these mass splittings, the LHC has
made little improvement over LEP due to large electroweak backgrounds. We find
that the use of machine learning techniques can push the LHC well past
discovery sensitivity for a benchmark model with a lepton partner mass of $\sim
110~{\rm GeV}$, for an integrated luminosity of $300~{\rm fb}^{-1}$, with a
signal-to-background ratio of $\sim 0.3$. The LHC could exclude models with a
lepton partner mass as large as $\sim 160~{\rm GeV}$ with the same luminosity.
The use of machine learning techniques in searches for scalar lepton partners
at the LHC could thus definitively probe the parameter space of the MSSM in
which scalar muon mediated interactions between SM muons and Majorana singlet
DM can both deplete the relic density through dark matter annihilation and
satisfy the recently measured anomalous magnetic moment of the muon. We
identify several machine learning techniques which can be useful in other LHC
searches involving large and complex backgrounds.


  This note is an extension of a recent work on the analytical bootstrapping of
$O(N)$ models. An additonal feature of the $O(N)$ model is that the OPE
contains trace and antisymmetric operators apart from the symmetric-traceless
objects appearing in the OPE of the singlet sector. This in addition to the
stress tensor $(T_{\mu\nu})$ and the $\phi_i\phi^i$ scalar, we also have other
minimal twist operators as the spin-1 current $J_\mu$ and the
symmetric-traceless scalar in the case of $O(N)$. We determine the effect of
these additional objects on the anomalous dimensions of the corresponding
trace, symmetric-traceless and antisymmetric operators in the large spin sector
of the $O(N)$ model, in the limit when the spin is much larger than the twist.
As an observation, we also verified that the leading order results for the
large spin sector from the $\epsilon-$expansion are an exact match with our
$n=0$ case. A plausible holographic setup for the special case when $N=2$ is
also mentioned which mimics the calculation in the CFT.


  In this communication we briefly report an unexpected theoretical discovery
which emerge from the mapping of Elko mass-dimension-one spinors into single
helicity spinors. Such procedure unveils a class of spinor which is classified
as type-4 spinor field within Lounesto classification. In this paper we explore
the underlying physical and mathematical contents of the type-4 spinor.


  This paper evaluates data stream classifiers from the perspective of
connected devices, focusing on the use case of HAR. We measure both
classification performance and resource consumption (runtime, memory, and
power) of five usual stream classification algorithms, implemented in a
consistent library, and applied to two real human activity datasets and to
three synthetic datasets. Regarding classification performance, results show an
overall superiority of the HT, the MF, and the NB classifiers over the FNN and
the Micro Cluster Nearest Neighbor (MCNN) classifiers on 4 datasets out of 6,
including the real ones. In addition, the HT, and to some extent MCNN, are the
only classifiers that can recover from a concept drift. Overall, the three
leading classifiers still perform substantially lower than an offline
classifier on the real datasets. Regarding resource consumption, the HT and the
MF are the most memory intensive and have the longest runtime, however, no
difference in power consumption is found between classifiers. We conclude that
stream learning for HAR on connected objects is challenged by two factors which
could lead to interesting future work: a high memory consumption and low F1
scores overall.


  Neutron transmission experiments can offer a new type of highly sensitive
search for time-reversal invariance violating (TRIV) effects in nucleon-nucleon
interactions via the same enhancement mechanism observed for large parity
violating (PV) effects in neutron-induced compound nuclear processes. In these
compound processes, the TRIV cross-section is given as the product of the PV
cross-section, a spin-factor $\kappa$, and a ratio of TRIV and PV matrix
elements. We determined $\kappa$ to be $0.59\pm0.05$ for $^{139}$La+$n$ using
both $(n, \gamma)$ spectroscopy and ($\vec{n}+^{139}\vec{\rm La}$)
transmission. This result quantifies for the first time the high sensitivity of
the $^{139}$La 0.75~eV $p$-wave resonance in a future search for P-odd/T-odd
interactions in ($\vec{n}+^{139}\vec{\rm La}$) forward transmission.


  We study ground-state properties of the two-dimensional random-bond Ising
model with couplings having a concentration $p\in[0,1]$ of antiferromagnetic
and $(1-p)$ of ferromagnetic bonds. We apply an exact matching algorithm which
enables us the study of systems with linear dimension $L$ up to 700. We study
the behavior of the domain-wall energies and of the magnetization. We find that
the paramagnet-ferromagnet transition occurs at $p_c \sim 0.103$ compared to
the concentration $p_n\sim 0.109$ at the Nishimory point, which means that the
phase diagram of the model exhibits a reentrance. Furthermore, we find no
indications for an (intermediate) spin-glass ordering at finite temperature.


  We consider an inelastic dark matter model, where a fermion is charged under
a broken U(1) gauge symmetry, and introduce a tiny Majorana mass term to split
the fermion into two states with the light one being a dark matter candidate.
If the gauge boson is light, it can mediate both elastic and inelastic dark
matter self-interactions in dark halos, leading to observational consequences.
Using a numerical technique based on partial wave analysis, we accurately
calculate the elastic and inelastic self-scattering cross sections. We assume a
thermal freeze-out scenario and fix the gauge coupling constant using the relic
density constraint. Then, we focus on six benchmark masses of dark matter,
covering a wide range from $10~{\rm MeV}$ to $160~{\rm GeV}$ and map parameter
regions where the elastic scattering cross section per unit mass is within
$1~{\rm cm^2/g} - 5~{\rm cm^2/g}$, favored to solve small-scale issues of cold
dark matter. If the heavy state can decay to the light state and a massless
species, the inelastic up-scattering process can cool the halo and lead to core
collapse. Taking galaxies with evidence of dark matter density cores, we
further derive constraints on the parameter space. For dark matter masses below
$10~{\rm GeV}$, the mass splitting must be large enough to forbid up scattering
in the dwarf halo for evading the core-collapse constraint; while for higher
masses, the up-scattering process can still be allowed. Our results show
astrophysical observations can provide powerful tests for dark matter models
with large elastic and inelastic self-interactions.


  Effects of four-Fermi-type new interactions are studied in top-quark pair
production and their subsequent decays at future e^+e^- colliders.
Secondary-lepton-energy distributions are calculated for arbitrary longitudinal
beam polarizations. An optimal-observables procedure is applied for the
determination of new parameters.


  Diestel and M\"uller showed that the connected tree-width of a graph $G$,
i.e., the minimum width of any tree-decomposition with connected parts, can be
bounded in terms of the tree-width of $G$ and the largest length of a geodesic
cycle in $G$. We improve their bound to one that is of correct order of
magnitude. Finally, we construct a graph whose connected tree-width exceeds the
connected order of any of its brambles. This disproves a conjecture by Diestel
and M\"uller asserting an analogue of tree-width duality.


  We use James Webb Space Telescope Near-Infrared Camera Wide Field Slitless
Spectroscopy (NIRCam WFSS) and Near-Infrared spectrograph (NIRSpec) in the
Cosmic Evolution Early Release survey (CEERS) to measure rest-frame optical
emission-line of 155 galaxies at z>2. The blind NIRCam grism observations
include a sample of galaxies with bright emission lines that were not observed
on the NIRSpec masks. We study the changes of the Ha, [OIII]/Hb, and
[NeIII]/[OII] emission lines in terms of redshift by comparing to lower
redshift SDSS and CLEAR samples. We find a significant (>3$\sigma$) correlation
between [OIII]/Hb with redshift, while [NeIII]/[OII] has a marginal (2$\sigma$)
correlation with redshift. We compare [OIII]/Hb and [NeIII]/[OII] to stellar
mass and Hb SFR. We find that both emission-line ratios have a correlation with
Hb SFR and an anti-correlation with stellar mass across the redshifts 0<z<9.
Comparison with MAPPINGS~V models indicates that these trends are consistent
with lower metallicity and higher ionization in low-mass and high-SFR galaxies.
We additionally compare to IllustriousTNG predictions and find that they
effectively describe the highest [OIII]/Hb ratios observed in our sample,
without the need to invoke MAPPINGS models with significant shock ionizionation
components.


  A central problem in parameterized algorithms is to obtain algorithms
  with running time $f(k)\cdot n^{O(1)}$ such that $f$ is as slow growing
function of the parameter $k$ as possible. In particular, a large number of
basic parameterized problems admit parameterized algorithms where $f(k)$ is
single-exponential, that is, $c^k$ for some constant $c$, which makes aiming
for such a running time a natural goal for other problems as well. However
there are still plenty of problems where the $f(k)$ appearing in the best known
running time is worse than single-exponential and it remained ``slightly
superexponential'' even after serious attempts to bring it down. A natural
question to ask is whether the $f(k)$ appearing in the running time of the
best-known algorithms is optimal for any of these problems.
  In this paper, we examine parameterized problems where $f(k)$ is
$k^{O(k)}=2^{O(k\log k)}$ in the best known running time and for a number of
such problems, we show that the dependence on $k$ in the running time cannot be
improved to single exponential. (See paper for the longer abstract.)


  Quantum nonlocality and quantum steering are fundamental correlations of
quantum systems which can not be created using classical resources only.
Nonlocality describes the ability to influence the possible results of
measurements carried out in distant systems, in quantum steering Alice remotely
steers Bob's state. Research in nonlocality and steering possess a fundamental
interest for the development of quantum information and in many applications
requiring nonlocal resources like quantum key distribution. On the other hand,
the Stern-Gerlach experiment holds an important place in the history,
development and teaching of quantum mechanics and quantum information. In
particular, the thought experiment of consecutive Stern-Gerlach Experiments is
commonly used to exemplify the concept of non-commutativity between quantum
operators. However, to the best of our knowledge, the consecutive Stern-Gerlach
Experiments have not been treated in a fully quantum manner yet, and it is a
widely accepted idea that atoms crossing consecutive Stern-Gerlach Experiments
follow classical paths. Here we demonstrate that two consecutive Stern-Gerach
Experiment generate nonlocality and steering, these nonlocal effects strongly
modify our usual understanding of this experiment. Also, we discuss the
implications of this result and its relation with the entanglement. This
suggests the use of quantum correlations, of particles possessing mass, to
generate nonlocal taks using this venerable experiment.


  In this text we introduce the torsion of spinor connections. In terms of the
torsion we give conditions on a spinor connection to produce Killing vector
fields. We relate the Bianchi type identities for the torsion of spinor
connections with Jacobi identities for vector fields on supermanifolds.
Furthermore, we discuss applications of this notion of torsion.


  Magnetite (Fe3O4) is one of the most actively studied materials with a famous
metal-insulator transition (MIT), so-called the Verwey transition at around 123
K. Despite the recent progress in synthesis and characterization of Fe3O4
nanocrystals (NCs), it is still an open question how the Verwey transition
changes on a nanometer scale. We herein report the systematic studies on size
dependence of the Verwey transition of stoichiometric Fe3O4 NCs. We have
successfully synthesized stoichiometric and uniform-sized Fe3O4 NCs with sizes
ranging from 5 to 100 nm. These stoichiometric Fe3O4 NCs show the Verwey
transition when they are characterized by conductance, magnetization, cryo-XRD,
and heat capacity measurements. The Verwey transition is weakly size-dependent
and becomes suppressed in NCs smaller than 20 nm before disappearing completely
for less than 6 nm, which is a clear, yet highly interesting indication of a
size effect of this well-known phenomena. Our current work will shed new light
on this ages-old problem of Verwey transition.


  We establish an effective theory for heavy fermion compounds close to a zero
temperature Anti-Ferromagnetic (AF) transition. Coming from the heavy Fermi
liquid phase across to the AF phase, the heavy electron fractionalizes into a
light electron, a bosonic spinon and a {\it new} excitation: a spinless
fermionic field. Assuming this field acquires dynamics and dispersion when one
integrates out the high energy degrees of freedom, we give a scenario for the
volume of its Fermi surface through the phase diagram. We apply our theory to
the special case of YbRh$_2$(Si$_{1-x}$ Ge$_x$)$_2$ where we recover, within
experimental resolution, several low temperature exponents for transport and
thermodynamics.


  We present a new solution for the dispersive element in astronomical
spectrographs, which in many cases can provide an upgrade path to enhance the
spectral resolution of existing moderate-resolution reflection-grating
spectrographs. We demonstrate that in the case of LRIS-R at the Keck 1
Telescope a spectral resolution of 18,000 can be achieved with reasonable
throughput under good seeing conditions.


  With the growth of fake news and disinformation, the NLP community has been
working to assist humans in fact-checking. However, most academic research has
focused on model accuracy without paying attention to resource efficiency,
which is crucial in real-life scenarios. In this work, we review the
State-of-the-Art datasets and solutions for Automatic Fact-checking and test
their applicability in production environments. We discover overfitting issues
in those models, and we propose a data filtering method that improves the
model's performance and generalization. Then, we design an unsupervised
fine-tuning of the Masked Language models to improve its accuracy working with
Wikipedia. We also propose a novel query enhancing method to improve evidence
discovery using the Wikipedia Search API. Finally, we present a new
fact-checking system, the \textit{WikiCheck} API that automatically performs a
facts validation process based on the Wikipedia knowledge base. It is
comparable to SOTA solutions in terms of accuracy and can be used on low-memory
CPU instances.


  Plasma wakefield acceleration (PWFA) is a promising method for reducing the
scale and cost of future electron-positron collider experiments by using
shorter plasma sections to enhance beam energy. While electron acceleration has
already achieved breakthroughs in theory and experimentation, generating
high-quality positron beams in plasma presents greater challenges, such as
controlling emittance and energy spread, improving energy conversion
efficiency, and generating positron sources. In this paper, we have summarized
the research progress on advanced positron acceleration schemes, including
particle beam-driven wakefield acceleration, laser-driven wakefield
acceleration, radiation-based acceleration, hollow plasma channels, among
others. The strengths and weaknesses of these approaches are analyzed, and the
future outlook is discussed to drive experimental advancements.


  Let $\mathbb{A}_n^m$ be an arbitrary $n$-dimensional commutative associative
algebra over the field of complex numbers with $m$ idempotents. Let
$e_1=1,e_2,\ldots,e_k$ with $2\leq k\leq 2n$ be elements of $\mathbb{A}_n^m$
which are linearly independent over the field of real numbers. We consider
monogenic (i.~e. continuous and differentiable in the sense of Gateaux)
functions of the variable $\sum_{j=1}^k x_j\,e_j$, where $x_1,x_2,\ldots,x_k$
are real, and obtain a constructive description of all mentioned functions by
means of holomorphic functions of complex variables. It follows from this
description that monogenic functions have Gateaux derivatives of all orders.
The present article is generalized of the author's paper [1], where mentioned
results are obtained for $k=3$.


  Wave packet scattering off an attractive well is investigated in two spatial
dimensions numerically. The results confirm what was found previously for the
one dimensional case. The wave scattered at large angles is a polychotomous
(multiple peak) coherent train. Large angle scattering is extremely important
for low impinging velocities and at all impact parameters. The effect
disappears for packets more extended than the well. Experiments to detect the
polychotomous behavior are suggested.


  We study the logit evolutionary dynamics in population games. For general
population games, we prove that, on the one hand strict Nash equilibria are
locally asymptotically stable under the logit dynamics in the low noise regime,
on the other hand a globally exponentially stable fixed point exists in the
high noise regime. This suggests the emergence of bifurcations in population
games admitting multiple strict Nash equilibria, as verified numerically in
previous publications. We then prove sufficient conditions on the game
structure for global asymptotic stability of the logit dynamics in every noise
regime. Our results find application in particular to heterogeneous routing
games, a class of non-potential population games modelling strategic
decision-making of users having heterogeneous preferences in transportation
networks. In this setting, preference heterogeneities are due, e.g., to access
to different sources of information or to different trade-offs between time and
money. We show that if the transportation network has parallel routes, then the
unique equilibrium of the game is globally asymptotically stable.


  We present a sufficient condition for a non-injective function of a Markov
chain to be a second-order Markov chain with the same entropy rate as the
original chain. This permits an information-preserving state space reduction by
merging states or, equivalently, lossless compression of a Markov source on a
sample-by-sample basis. The cardinality of the reduced state space is bounded
from below by the node degrees of the transition graph associated with the
original Markov chain.
  We also present an algorithm listing all possible information-preserving
state space reductions, for a given transition graph. We illustrate our results
by applying the algorithm to a bi-gram letter model of an English text.


  Calculations of the nuclear modification factor, R_dAu, for pi^0 production
in dAu collisions at s_NN^1/2 = 200 GeV are presented. The applied
pQCD-improved parton model incorporates intrinsic k_T. Nuclear multiscattering
and nuclear shadowing are considered in the Au nucleus. Theoretical results are
displayed for midrapidity and high pseudorapidity (eta), and compared to
preliminary PHENIX and BRAHMS data.


  In this paper, the hybrid metric-Palatini gravity is an approach to modified
gravity in which is added to the usual Einstein-Hilbert action a supplementary
term containing a Palatini-type correction of the form $f({\cal R},T)$. Here,
${\cal R}$ is the Palatini curvature scalar, which is constructed from an
independent connection and $T$ is the trace of the energy-momentum tensor. This
theory describes a non-minimal coupling between matter and geometry. The
modified Einstein field equations in this hybrid metric-Palatini approach are
obtained. Then, it is investigated whether this modified theory of gravity and
its field equations allow G\"{o}del-type solutions, which essentially lead to
violation of causality. Considering physically well-motivated matter sources,
causal and non-causal solutions are explored.


  Critical surfaces can be regarded as topological index 2 minimal surfaces
which was introduced by David Bachman. In this paper we give a sufficient
condition and a necessary condition for self-amalgamated Heegaard surfaces to
be critical.


  We have applied the image subtraction method to images of the peculiar,
bimodal-horizontal branch globular cluster NGC 2808, taken over a total of six
nights over a range of five months. As a result, we have found, for the first
time, a sizeable population of variable stars in the crowded inner regions of
the cluster, thus raising the known RR Lyrae population in the cluster to a
total of 18 stars. In addition, an eclipsing binary and two other variables
with periods longer than 1 day were also found. Periods, positions and
(differential) light curves are provided for all the detected variables. The
Oosterhoff classification of NGC 2808, which has recently been associated with
a previously unknown dwarf galaxy in Canis Major, is briefly discussed.


  Time series modeling for predictive purpose has been an active research area
of machine learning for many years. However, no sufficiently comprehensive and
meanwhile substantive survey was offered so far. This survey strives to meet
this need. A unified presentation has been adopted for entire parts of this
compilation.
  A red thread guides the reader from time series preprocessing to forecasting.
Time series decomposition is a major preprocessing task, to separate
nonstationary effects (the deterministic components) from the remaining
stochastic constituent, assumed to be stationary. The deterministic components
are predictable and contribute to the prediction through estimations or
extrapolation. Fitting the most appropriate model to the remaining stochastic
component aims at capturing the relationship between past and future values, to
allow prediction.
  We cover a sufficiently broad spectrum of models while nonetheless offering
substantial methodological developments. We describe three major linear
parametric models, together with two nonlinear extensions, and present five
categories of nonlinear parametric models. Beyond conventional statistical
models, we highlight six categories of deep neural networks appropriate for
time series forecasting in nonlinear framework.
  Finally, we enlighten new avenues of research for time series modeling and
forecasting. We also report software made publicly available for the models
presented.


  Galactic dynamo models take as input certain parameters of the interstellar
turbulence, most essentially the correlation time $\tau$, root-mean-square
turbulent speed $u$, and correlation scale $l$. However, these quantities are
difficult, or, in the case of $\tau$, impossible, to directly observe, and
theorists have mostly relied on order of magnitude estimates. Here we present
an analytic model to derive these quantities in terms of a small set of more
accessible parameters. In our model, turbulence is assumed to be driven
concurrently by isolated supernovae (SNe) and superbubbles (SBs), but
clustering of SNe to form SBs can be turned off if desired, which reduces the
number of model parameters by about half. In general, we find that isolated SNe
and SBs can inject comparable amounts of turbulent energy into the interstellar
medium, but SBs do so less efficiently. This results in rather low overall
conversion rates of SN energy into turbulent energy of $\sim1$-$3\%$. The
results obtained for $l$, $u$ and $\tau$ for model parameter values
representative of the Solar neighbourhood are consistent with those determined
from direct numerical simulations. Our analytic model can be combined with
existing dynamo models to predict more directly the magnetic field properties
for nearby galaxies or for statistical populations of galaxies in cosmological
models.


  In this study, we examine the ways in which user attitudes towards privacy
and security relating to mobile devices and the data stored thereon may impact
the strength of unlock authentication, focusing on Android's graphical unlock
patterns. We conducted an online study with Amazon Mechanical Turk ($N=750$)
using self-reported unlock authentication choices, as well as Likert scale
agreement/disagreement responses to a set of seven privacy/security prompts. We
then analyzed the responses in multiple dimensions, including a straight
average of the Likert responses as well as using Principle Component Analysis
to expose latent factors. We found that responses to two of the seven questions
proved relevant and significant. These two questions considered attitudes
towards general concern for data stored on mobile devices, and attitudes
towards concerns for unauthorized access by known actors. Unfortunately, larger
conclusions cannot be drawn on the efficacy of the broader set of questions for
exposing connections between unlock authentication strength (Pearson Rank
$r=-0.08$, $p<0.1$). However, both of our factor solutions exposed differences
in responses for demographics groups, including age, gender, and residence
type. The findings of this study suggests that there is likely a link between
perceptions of privacy/security on mobile devices and the perceived threats
therein, but more research is needed, particularly on developing better survey
and measurement techniques of privacy/security attitudes that relate to mobile
devices specifically.


  The recent discovery of superconductivity in La$_3$Ni$_2$O$_7$ with
$T_\mathrm{c} \simeq 80~\mathrm{K}$ under high pressure opens up a new route to
high-$T_\mathrm{c}$ superconductivity. This material realizes a bilayer square
lattice model featuring a strong interlayer hybridization unlike many
unconventional superconductors. A key question in this regard concerns how
electronic correlations driven by the interlayer hybridization affect the
low-energy electronic structure and the concomitant superconductivity. Here, we
demonstrate using a cluster dynamical mean-field theory that the interlayer
electronic correlations (IECs) induce a Lifshitz transition resulting in a
change of Fermi surface topology. By solving an appropriate gap equation, we
further show that the leading pairing instability, $s \pm$-wave, is enhanced by
the IECs. The underlying mechanism is the quenching of a strong ferromagnetic
channel, resulting from the Lifshitz transition driven by the IECs. Based on
this picture, we provide a possible reason of why superconductivity emerges
only under high pressure.


  In this paper, we study a model of network adaptation mechanism to control
spreading processes over switching contact networks, called adaptive
susceptible-infected-susceptible model. The edges in the network model are
randomly removed or added depending on the risk of spread through them. By
analyzing the joint evolution of the spreading dynamics "in the network" and
the structural dynamics "of the network", we derive conditions on the
adaptation law to control the dynamics of the spread in the resulting switching
network. In contrast with the results in the literature, we allow the initial
topology of the network to be an arbitrary graph. Furthermore, assuming there
is a cost associated to switching edges in the network, we propose an
optimization framework to find the cost-optimal network adaptation law, i.e.,
the cost-optimal edge switching probabilities. Under certain conditions on the
switching costs, we show that the optimal adaptation law can be found using
convex optimization. We illustrate our results with numerical simulations.


  High energy single- to few-cycle terahertz pulses enable the exploration of
the frontier of science, such as electron acceleration, strong-field physics,
and spectroscopy. One important method of generating such terahertz pulses is
to use the tilted-pulse-front (TPF) technique. However, due to the
non-collinear phase-matching, the large angular dispersion leads to a spatial
and temporal break-up of the optical pump, limiting the terahertz generation
efficiency and reducing the few-cycle character of the generated terahertz
fields. To reduce the effects caused by angular dispersion, multiple schemes
with discrete pulse-front-tilt have been suggested. We propose a terahertz
generation scheme, where a spatio-temporally chirped (STC) pump pulse is
utilized. With our 2D+1 numerical model, we perform a systematic comparative
study of the conventional TPF scheme, three discrete TPF schemes, and the STC
scheme. This model predicts smaller optimal interaction length and
significantly smaller conversion efficiency compared to simple 1D models. We
conclude that the STC scheme delivers spatially homogeneous few-cycle terahertz
pulses with the highest conversion efficiency. Additionally, given a short
interaction length, the discrete TPF schemes cannot outperform the continuous
ones. In general, this work gives guidance to choose the most appropriate setup
for a given terahertz experiment


  With the great success of graph embedding model on both academic and industry
area, the robustness of graph embedding against adversarial attack inevitably
becomes a central problem in graph learning domain. Regardless of the fruitful
progress, most of the current works perform the attack in a white-box fashion:
they need to access the model predictions and labels to construct their
adversarial loss. However, the inaccessibility of model predictions in real
systems makes the white-box attack impractical to real graph learning system.
This paper promotes current frameworks in a more general and flexible sense --
we demand to attack various kinds of graph embedding model with black-box
driven. To this end, we begin by investigating the theoretical connections
between graph signal processing and graph embedding models in a principled way
and formulate the graph embedding model as a general graph signal process with
corresponding graph filter. As such, a generalized adversarial attacker:
GF-Attack is constructed by the graph filter and feature matrix. Instead of
accessing any knowledge of the target classifiers used in graph embedding,
GF-Attack performs the attack only on the graph filter in a black-box attack
fashion. To validate the generalization of GF-Attack, we construct the attacker
on four popular graph embedding models. Extensive experimental results validate
the effectiveness of our attacker on several benchmark datasets. Particularly
by using our attack, even small graph perturbations like one-edge flip is able
to consistently make a strong attack in performance to different graph
embedding models.


  We consider a Urysohn integral operator $\mathcal{K}$ with kernel of the type
of Green's function. For $r \geq 1$, a space of piecewise polynomials of degree
$\leq r-1 $ with respect to a uniform partition is chosen to be the
approximating space and the projection is chosen to be the orthogonal
projection. Iterated Galerkin method is applied to the integral equation $x -
\mathcal{K}(x) = f$. It is known that the order of convergence of the iterated
Galerkin solution is $r+2$ and, at the above partition points it is $2r$. We
obtain an asymptotic expansion of the iterated Galerkin solution at the
partition points of the above Urysohn integral equation. Richardson
extrapolation is used to improve the order of convergence. A numerical example
is considered to illustrate our theoretical results.


  3D lung segmentation is essential since it processes the volumetric
information of the lungs, removes the unnecessary areas of the scan, and
segments the actual area of the lungs in a 3D volume. Recently, the deep
learning model, such as U-Net outperforms other network architectures for
biomedical image segmentation. In this paper, we propose a novel model, namely,
Recurrent Residual 3D U-Net (R2U3D), for the 3D lung segmentation task. In
particular, the proposed model integrates 3D convolution into the Recurrent
Residual Neural Network based on U-Net. It helps learn spatial dependencies in
3D and increases the propagation of 3D volumetric information. The proposed
R2U3D network is trained on the publicly available dataset LUNA16 and it
achieves state-of-the-art performance on both LUNA16 (testing set) and VESSEL12
dataset. In addition, we show that training the R2U3D model with a smaller
number of CT scans, i.e., 100 scans, without applying data augmentation
achieves an outstanding result in terms of Soft Dice Similarity Coefficient
(Soft-DSC) of 0.9920.


  We introduce a notion of shadowing property for actions of finitely generated
groups and study its basic properties. We formulate and prove a shadowing lemma
for actions of nilpotent groups. We construct an example of a faithful linear
action of a solvable Baumslag-Solitar group and show that the shadowing
property depends on quantitative characteristics of hyperbolicity. Finally we
show that any linear action of a non-abelian free group does not have the
shadowing property.


  For decades, the grand-design SAB spiral galaxy NGC 5248 has been postulated
to host a short bar of semi-major axis 22" (1.6 kpc). From dynamical and
morphological arguments, we argue, however, that its spiral structure is being
driven by a large-scale bar whose corotation radius lies at around 115" (8.6
kpc).Our estimate is based partially on a deep R-band image which reveals that
the feature previously thought to be an inclined disk is in fact an extended
stellar bar. The bar is embedded within a fainter outer disk visible out to a
radius of 230" (17.2 kpc). The bar has a deprojected ellipticity of 0.44 and a
semi-major axis of 95" (7.1 kpc). The classical grand-design spirals of NGC
5248, prominent in B, R, and K light, lie on the leading edge of the
large-scale stellar bar and are accompanied by concave dust lanes out to at
least 70". The offset between the dust and young stars is consistent with our
understanding of gas flows in barred galaxies, where shocks along the leading
edges of a moderately strong bar compress the gas to form massive young stars.
While in many strongly barred galaxies, optical spiral arms are prominent
outside the bar but not within it, NGC 5248 illustrates how intense star
formation along a moderately strong bar can lead to conspicuous open spiral
arms within the bar itself. NGC 5248 also provides a clear example of how a
large-scale stellar bar embedded within a faint outer optical disk can be
misidentified as an inclined disk when imaging studies lack the sensitivity to
detect the actual outer disk. We discuss the implications for the estimated bar
fraction at higher redshifts.


  In the usual optomechanical cooling, even if the system has no thermal
component, it still has a quantum limit-known as the quantum backaction limit
(QBL)-on the minimum phonon number related to shot noise. By studying the
side-band cooling regime in optomechanical system (OMS), we find that the
cooling can be improved significantly when the frequency modulation (FM) that
can suppress the Stokes heating processes is introduced into the system. We
analyze and demonstrate the reasons of the phonon number below the QBL
redefined in the whole stable region of the standard OMSs. The above analyses
are further checked by numerically solving the differential equations of second
order moments derived from the quantum master equation with broad system
parameters, ranging from weak coupling (WC) to ultra-strong coupling (USC) and
resolved side-band (RSB) to unresolved side-band (USB) regimes. Comparing with
the cases of those without FM, the stable ground-state cooling can also be
achieved even in the conventional unstable region.


  We developed and provide AnalyticLC, a novel analytic method and code
implementation for dynamical modeling of planetary systems, including
non-coplanar interactions, based on a disturbing function expansion to fourth
order in eccentricities and inclinations. AnalyticLC calculates the system
dynamics in 3D and the resulting model light curve, radial velocity, and
astrometry signatures, enabling simultaneous fitting of these data. We show
that for a near-resonant chain of three planets, where the two super-periods
are close to each other, the TTVs of the pair-wise interactions cannot be
directly summed to give the full system TTVs because the super-periods
themselves resonate. We derive the simultaneous three-planet correction and
include it in AnalyticLC. We compare the model computed by AnalyticLC to
synthetic data generated by an N-body integrator, and evaluate its accuracy.
Depending on the maximal order of expansion terms kept, AnalyticLC computation
time can be up to an order of magnitude faster than state-of-the-art published
N-body integrator TTVFast, with smaller enhancement seen at higher order. The
advantage increases for long-term observations as our approach's computation
time does not depend on the time-span of the data. Depending on the system
parameters, the photometric accuracy is typically a few ppm, significantly
smaller than typical Kepler's and other observatories' data uncertainty. Our
highly efficient and accurate implementation allows full inversion of a large
number of observed systems for planetary physical and orbital parameters,
presented in a companion paper.


  In the current paper, we present an optimization system solving multi
objective production scheduling problems (MOOPPS). The identification of Pareto
optimal alternatives or at least a close approximation of them is possible by a
set of implemented metaheuristics. Necessary control parameters can easily be
adjusted by the decision maker as the whole software is fully menu driven. This
allows the comparison of different metaheuristic algorithms for the considered
problem instances. Results are visualized by a graphical user interface showing
the distribution of solutions in outcome space as well as their corresponding
Gantt chart representation.
  The identification of a most preferred solution from the set of efficient
solutions is supported by a module based on the aspiration interactive method
(AIM). The decision maker successively defines aspiration levels until a single
solution is chosen.
  After successfully competing in the finals in Ronneby, Sweden, the MOOPPS
software has been awarded the European Academic Software Award 2002
(http://www.bth.se/llab/easa_2002.nsf)


  We give a new proof that every holomorphic one-form on a smooth complex
projective variety of general type must vanish at some point, first proven by
Popa and Schnell using generic vanishing theorems for Hodge modules. Our proof
relies on Simpson's results on the relation between rank one Higgs bundles and
local systems of one-dimensional complex vectors spaces, and the structure of
the cohomology jump loci in their moduli spaces.


  We present the results of a systematic investigation of the magnetic
properties of the three-dimensional Kondo topological insulator SmB6 using
magnetization and muon-spin relaxation/rotation (muSR) measurements. The muSR
measurements exhibit magnetic field fluctuations in SmB6 below 15 K due to
electronic moments present in the system. However, no evidence for magnetic
ordering is found down to 19 mK. The observed magnetism in SmB6 is homogeneous
in nature throughout the full volume of the sample. Bulk magnetization
measurements on the same sample show consistent behavior. The agreement between
muSR, magnetization, and NMR results strongly indicate the appearance of
intrinsic bulk magnetic in-gap states associated with fluctuating magnetic
fields in SmB6 at low temperature.


  It was noted recently that the ADM-diffeomorphism-constraint does not
generate all observed symmetries for several Bianchi-models. We will suggest
not to use the ADM-constraint restricted to homogeneous variables, but some
equivalent which is derived from a restricted action principle. This will
generate all homogeneity preserving diffeomorphisms, which will be shown to be
automorphism generating vector fields, in class A and class B models. Following
Dirac's constraint formalism one will naturally be restricted to the unimodular
part of the automorphism group.


  Recent studies have shown that for suitable initial conditions both super-
and sub-Chandrasekhar mass carbon-oxygen white dwarf mergers produce explosions
similar to observed SNe Ia. The question remains, however, how much fine tuning
is necessary to produce these conditions. We performed a large set of SPH
merger simulations, sweeping the possible parameter space. We find trends for
merger remnant properties, and discuss how our results affect the viability of
our recently proposed sub-Chandrasekhar merger channel for SNe Ia.


  We consider late-time cosmology in a (phantom) scalar-tensor theory with an
exponential potential, as a dark energy model with equation of state parameter
close to -1 (a bit above or below this value). Scalar (and also other kinds of)
matter can be easily taken into account. An exact spatially-flat FRW cosmology
is constructed for such theory, which admits (eternal or transient)
acceleration phases for the current universe, in correspondence with
observational results. Some remarks on the possible origin of the phantom,
starting from a more fundamental theory, are also made. It is shown that
quantum gravity effects may prevent (or, at least, delay or soften) the cosmic
doomsday catastrophe associated with the phantom, i.e. the otherwise
unavoidable finite-time future singularity (Big Rip). A novel dark energy model
(higher-derivative scalar-tensor theory) is introduced and it is shown to admit
an effective phantom/quintessence description with a transient acceleration
phase. In this case, gravity favors that an initially insignificant portion of
dark energy becomes dominant over the standard matter/radiation components in
the evolution process.


  A review is focused on experimental measurements on neutron lifetime. The
latest measurements with a gravitational trap (PNPI NRC KI) and a magnetic trap
(LANL, USA) confirmed PNPI result of 2005. The results of measurements with
storage of ultra cold neutrons are in agreement, yet, there is discrepancy with
a beam experiment by $3.5{\sigma}$ (1% of decay probability), which is
discussed in literature as "neutron anomaly" along with the ideas of explaining
it by decay into dark matter partially. The second part of the paper is devoted
to so called "reactor antineutrino anomaly", which refers to deficiency of the
measured flux of antineutrino from reactor in respect to the calculated flux by
$3{\sigma}$(deviation by 6.6%). Specific feature of the proposal in this paper
lies in the fact that both anomalies can be accounted for by one and the same
phenomenon of oscillation in baryon sector between a neutron and a neutron of
dark matter $n{\rightarrow}n'$ with mass $m_{n'}$, somewhat less than mass
$m_n$ of an ordinary neutron. Calculations of the proposed model require one
free parameter: mass difference $m_n-m_{n'}$ if one normalizes probability of
oscillations for a free neutron on "neutron anomaly" 1%, then, having succeeded
to interpret 6.6% of neutron anomaly in calculations, one can determine mass
difference. According to preliminary estimations, the mass difference is
$m_n-m_{n'}{\approx}$ 3 MeV. However, the analysis of cumulative yields of
isotopes occurs in fission fragments was performed and it does not confirm
possibility of existence of additional decay channel with emission of dark
matter neutron with mass difference $m_n-m_{n'}{\approx}$ 3 MeV. The result of
the analysis is the conclusion that for mirror neutrons the region of the mass
difference $m_n-m_{n'} {\geq}$ 3 MeV is closed. The region of the mass
difference $m_n-m_{n'}{\leq}$ 2 MeV turned out to be not closed.


  On the basis of an analysis of a 3/4-filled two-dimensional (2D) extended
Hubbard model under the fluctuation-exchange approximation, we find Coulomb
frustrated phase separation (PS) in a region of nonzero temperature, where the
quantum critical phenomenon of charge ordering (CO) dominates. In quasi-2D
organic conductors on the verge of CO, this frustrated PS provides a mechanism
for generating spatial inhomogeneity, which is characterized by an extremely
slow relaxation and an intermediate length scale.


  Star formation and chemical enrichment histories of the dwarf spheroidal
galaxies (dSphs) Draco, Sextans, and Ursa Minor are investigated by means of
chemical evolution models and a simulation code for colour-magnitude diagrams
(CMDs). The CMD simulation code is designed to fully consider effects of the
chemical evolution on stellar evolution and photometric properties. Comparisons
between the chemical evolution models and the observed abundance patterns
reveal that the star formation rates were very low (1-5% of that of the solar
neighbourhood disc) and that the initial star formation continued for a long
duration (> 3.9-6.5 Gyr) in these dSphs. This star formation history can
reproduce morphologies of the observed CMDs, such as narrow red giant branches
and red horizontal branches. Hence, both of the abundance patterns and the
morphologies of the CMDs can be explained by the star formation histories
characterised by the low star formation rate and the long duration of the star
formation period. Because of the low star formation rates, plenty of gas
remains at the final epoch of star formation. We suggest that gas stripping by
the Galaxy results in termination of star formation in the dSphs.


  We use a numerical algorithm on the Lie group of rotation matrices to obtain
rotated constellations for Rayleigh fading channels. Our approach minimizes the
union bound for the pairwise error probability to produce rotations optimized
for a given signal-to-noise ratio. This approach circumvents explicit
parametrization of rotation matrices, which has previously prevented robust
numerical methods from being applied to constellation rotation. Our algorithm
is applicable to arbitrary finite constellations in arbitrary dimensions, and
one can thus apply our method to non-uniform constellations, which are of
interest for practical concerns due to their ability to increase BICM capacity.
We show how our rotations can improve the codeword error performance of
non-uniform constellations, and we also apply our method to reproduce and
improve rotations given by ideal lattices in cyclotomic fields.


  Close to a solid surface, the properties of a fluid deviate significantly
from their bulk values. In this context, we study the surface adsorption
profiles of a symmetric binary liquid confined to a slit pore by means of
molecular dynamics simulations; the latter naturally entails that mass and
concentration are locally conserved. Near a bulk consolute point, where the
liquid exhibits a demixing transition with the local concentration as the order
parameter, we determine the order parameter profiles and characterise the
relevant critical scaling behaviour, in the regime of strong surface
attraction, for a range of pore widths and temperatures. The obtained order
parameter profiles decay monotonically near the surfaces, also in the presence
of a pronounced layering in the number density. Overall, our results agree
qualitatively with recent theoretical predictions from a mesoscopic
field-theoretical approach for the canonical ensemble.


  This study reports the results of applying the cross-lingual bug localization
approach proposed by Xia et al. to industrial software projects. To realize
cross-lingual bug localization, we applied machine translation to non-English
descriptions in the source code and bug reports, unifying them into
English-based texts, to which an existing English-based bug localization
technique was applied. In addition, a prototype tool based on BugLocator was
implemented and applied to two Japanese industrial projects, which resulted in
a slightly different performance from that of Xia et al.


  We introduce a parity $R_F$ to introduce naturally small masses for the first
family members and in particular almost massless $u$ quark toward the strong CP
solution. We also discuss the phenomenological implications of this model on
the proton decay and the neutrino mass. Furthermore, it is possible to embed
this $R_F$ parity to local $U(1)_R$ gauge symmetry.


  The classical Painlev\'e theorem tells that sets of zero length are removable
for bounded analytic functions, while (some) sets of positive length are not.
For general $K$-quasiregular mappings in planar domains the corresponding
critical dimension is $\frac{2}{K+1}$. We show that when $K>1$, unexpectedly
one has improved removability. More precisely, we prove that sets $E$ of
$\sigma$-finite Hausdorff $\frac{2}{K+1}$-measure are removable for bounded
$K$-quasiregular mappings. On the other hand, $\dim(E) = \frac{2}{K+1}$ is not
enough to guarantee this property.
  We also study absolute continuity properties of pull-backs of Hausdorff
measures under $K$-quasiconformal mappings, in particular at the relevant
dimensions 1 and $\frac{2}{K+1}$. For general Hausdorff measures ${\cal H}^t$,
$0 < t < 2$, we reduce the absolute continuity properties to an open question
on conformal mappings.


  We explain how to derive an explicit formula for a natural transformation
relating the (left adjoints of) the homotopy coherent nerve and the Dwyer-Kan
simplicial classifying space functor. The formula is derived using a method
introduced by Szczarba when comparing two different chain models of a
fibration. This note may be taken as a companion to section 3 of our previous
article "Categorical models for path spaces".


  Following on from work of Dunfield, we determine the fibred status of all the
unknown hyperbolic 3-manifolds in the cusped census. We then find all the
fibred hyperbolic 3-manifolds in the closed census and use this to find over
100 examples each of closed and cusped virtually fibred non-fibred census
3-manifolds, including the Weeks manifold. We also show that the co-rank of the
fundamental group of every 3-manifold in the cusped and in the closed census is
0 or 1.


  We introduce T2Ku, an open source project that aims at building a semantic
wiki of mathematics featuring automated reasoning(AR) techniques. We want to
utilize AR techniques in a way that truly helps mathematical researchers solve
problems in the real world, instead of building another ambitious yet useless
system. By setting this as our objective, we exploit pragmatic design decisions
that have proven feasible in other projects, while still employs a loosely
coupled architecture to allow better inference programs to be integrated in the
future. In this paper, we state the motivations and examine state-of-the-art
systems, why we are not satisfied with those systems and how we are going to
improve. We then describe our architecture and the way we implemented the
system. We present examples showing how to use its facilities. T2Ku is an
on-going project. We conclude this paper by summarizing the development
progress and encouraging the reader to join the project.


  We state and discuss several interrelated results, conjectures, and questions
regarding contractive inequalities for classical $H^p$ spaces of the unit disc.
We study both coefficient estimates in terms of weighted $\ell^2$ sums and the
Riesz projection viewed as a map from $L^q$ to $H^p$ with $q\ge p$. Some
numerical evidence is given that supports our conjectures.


  Replacement of papers q-bio/0605026 and q-bio/0607043 by a single manuscript
(q-bio/0701029) follows suggestions from a magazine's referee


  We present and discuss a new computationally inexpensive method to study,
within the single active electron approximation, the interaction of a complex
system with an intense ultrashort laser pulse. As a first application, we
consider the one photon single ionisation of the highest occupied molecular
orbital of the water molecule by a laser pulse. The ionisation yield is
calculated for different orientations of the molecule with respect to the field
polarization axis and for different carrier envelope phases of the pulse, and
compared against predictions of another single active electron approach.


  This paper describes the digital library of historical resources, a research
project which involves building a testbed for the purpose of developing and
testing new collaborative digital library functionality and presents an initial
analysis of the digital library's public use on the web. The digital library is
modeled to focus on serving secondary students information needs in conducting
history projects. As such, in the implementation of the digital library, the
use of online resources would be an integral part of history project based
learning activities. Students should be enabled to access digital resources,
create and publish their own documents in the digital library and share them
with others. As a testbed system, the collaborative digital library known as
CoreDev has demonstrated its capabilities in serving an educational community
as has been reflected by the positive feedback on the functional requirements
from 44 users. Over 75% of the respondents in the user survey considered
themselves capable of using the digital library easily. The beta tester
demographics (n = 105) indicate that the digital library is reaching its target
communities.


  We discuss the role of dissipation in the explosive spinodal decomposition
scenario of hadron production during the chiral transition after a high-energy
heavy ion collision. We use a Langevin description inspired by microscopic
nonequilibrium field theory results to perform real-time lattice simulations of
the behavior of the chiral fields. We show that the effect of dissipation can
be dramatic. Analytic results for the short-time dynamics are also presented.


  We have obtained high, 11 and 14 \kms, and medium, 40 and 53 \kms, resolution
spectra of the $z_{em} = 4.11$ quasar Q0000--2619 covering the range 4400 \AA\
to 9265 \AA . We identify nine metal absorption systems, of which four were
previously known. A fifth previously suggested system at $z_{abs} \approx
3.409$ (Turnshek et al~ 1991) is ruled out by our data. Two of the eight
systems for which the \lya~ line is in the observable range have a damped \lya~
line. Six of the nine systems show evidence for complex sub--component
structure. At our resolution and S/N we identify a total of 21 sub--components
in the nine systems. Five of the nine systems (11 of the 21 components) fall
within the $\pm 5000$ \kms~ range of the emission redshift, and are hence
classified as \zae~ absorbers. For the two damped systems we find metal
abundances of $\leq 1$% and $\leq 8$% of solar values at redshifts of 3.0541
and 3.3901 respectively. These upper limits are consistent with what would be
expected from previous determinations at lower redshifts, and our data are
hence compatible with earlier conclusions that no evidence is yet found for
chemical evolution of intervening damped and Lyman limit absorbers. For the
\zae~ systems we found indications of metallicities comparable to, and even in
excess of solar values. These much higher values compared to the damped
systems, are in favour of the intrinsic hypothesis for these systems.


  Cooper pairing in two dimensions is analyzed with a set of renormalized
equations to determine its binding energy for any fermion number density and
all coupling assuming a generic pairwise residual interfermion interaction. \
Also considered are Cooper pairs (CPs) with nonzero center-of-mass momentum
(CMM)--usually neglected in BCS theory--and their binding energy is expanded
analytically in powers of the CMM up to quadratic terms. A Fermi-sea-dependent
{\it linear} term in the CMM dominates the pair excitation energy in weak
coupling (also called the BCS regime) while the more familiar quadratic term
prevails in strong coupling (the Bose regime). The crossover, though strictly
unrelated to BCS theory {\it per se,} is studied numerically as it is expected
to play a central role in a model of superconductivity as a Bose-Einstein
condensation of CPs where the transition temperature vanishes for all
dimensionality $d\leq 2$ for quadratic dispersion, but is {\it nonzero} for all
$d\geq 1$ for linear dispersion.


  We present the complete four-loop four-point amplitude in N=4
super-Yang-Mills theory, for a general gauge group and general D-dimensional
covariant kinematics, and including all non-planar contributions. We use the
method of maximal cuts --- an efficient application of the unitarity method ---
to construct the result in terms of 50 four-loop integrals. We give graphical
rules, valid in D-dimensions, for obtaining various non-planar contributions
from previously-determined terms. We examine the ultraviolet behavior of the
amplitude near D=11/2. The non-planar terms are as well-behaved in the
ultraviolet as the planar terms. However, in the color decomposition of the
three- and four-loop amplitude for an SU(N_c) gauge group, the coefficients of
the double-trace terms are better behaved in the ultraviolet than are the
single-trace terms. The results from this paper were an important step toward
obtaining the corresponding amplitude in N=8 supergravity, which confirmed the
existence of cancellations beyond those needed for ultraviolet finiteness at
four loops in four dimensions. Evaluation of the loop integrals near D=4 would
permit tests of recent conjectures and results concerning the infrared behavior
of four-dimensional massless gauge theory.


  In simulations of some infinite range spin glass systems with finite
connectivity, it is found that for any resonable computational time, the
saturatedenergy per spin that is achieved by a cluster algorithm is lowered in
comparison to that achieved by Metropolis dynamics.The gap between the average
energies obtained from these two dynamics is robust with respect to variations
of the annealing schedule. For some probability distribution of the
interactions the ground state energy is calculated analytically within the
replica symmetry assumptionand is found to be saturated by a cluster algorithm.


  A new construction technique of multiple solutions of the Euler equa- tion in
strong spaces is introduced which reveals the relationship to multi- ple Navier
Stokes equation solutions with special force terms while avoid- ing viscosity
limit constructions. This shows that severe restrictions have to be imposed on
time dependent external force terms in order to ob- tain uniqueness for the
Navier Stokes equation Cauchy problem. Such restrictions are imposed in the
statement of the so-called millenium prob- lem. Minimal turbulence models
should arguably incorporate weaker force terms in order to account for boundary
conditions and forces. However, we show that models of this type which have
been proposed recently, do not have a unique solution. This lack of determinism
of mimimal turbu- lence models indicates a dilemma: either models are too
simple to capture turbulence but may have unique smooth solutions, or there is
a modelling gap as the model does not determine a unique solution.


  We give explicit equations of smooth Jacobian Kummer surfaces of degree 8 by
theta functions. As byproducts, we can write down Rosenhain's 80 hyperpanes and
32 lines on these Kummer surfaces explicitly.


  We demonstrate self-supervised pretraining (SSP) is a scalable solution to
deep learning with differential privacy (DP) regardless of the size of
available public datasets in image classification. When facing the lack of
public datasets, we show the features generated by SSP on only one single image
enable a private classifier to obtain much better utility than the non-learned
handcrafted features under the same privacy budget. When a moderate or large
size public dataset is available, the features produced by SSP greatly
outperform the features trained with labels on various complex private datasets
under the same private budget. We also compared multiple DP-enabled training
frameworks to train a private classifier on the features generated by SSP.
Finally, we report a non-trivial utility 25.3\% of a private ImageNet-1K
dataset when $\epsilon=3$. Our source code can be found at
\url{https://github.com/UnchartedRLab/SSP}.


  The presence of metal implants within CT imaging causes severe attenuation of
the X-ray beam. Due to the incomplete information recorded by CT detectors,
artifacts in the form of streaks and dark bands would appear in the resulting
CT images. The metal-induced artifacts would firstly affect the quantitative
accuracy of CT imaging, and consequently, the radiation treatment planning and
dose estimation in radiation therapy. To address this issue, CT scanner vendors
have implemented metal artifact reduction (MAR) algorithms to avoid such
artifacts and enhance the overall quality of CT images. The orthopedic-MAR
(OMAR) and normalized MAR (NMAR) algorithms are the most well-known metal
artifact reduction (MAR) algorithms, used worldwide. These algorithms have been
implemented on Philips and Siemens scanners, respectively. In this study, we
set out to quantitatively and qualitatively evaluate the effectiveness of these
two MAR algorithms and their impact on accurate radiation treatment planning
and CT-based dosimetry. The quantitative metrics measured on the simulated
metal artifact dataset demonstrated superior performance of the OMAR technique
over the NMAR one in metal artifact reduction. The analysis of radiation
treatment planning using the OMAR and NMAR techniques in the corrected CT
images showed that the OMAR technique reduced the toxicity of healthy tissues
by 10% compared to the uncorrected CT images.


  A recent interest in resting state functional magnetic resonance imaging
(rsfMRI) lies in subdividing the human brain into anatomically and functionally
distinct regions of interest. For example, brain parcellation is often used for
defining the network nodes in connectivity studies. While inference has
traditionally been performed on group-level data, there is a growing interest
in parcellating single subject data. However, this is difficult due to the low
signal-to-noise ratio of rsfMRI data, combined with typically short scan
lengths. A large number of brain parcellation approaches employ clustering,
which begins with a measure of similarity or distance between voxels. The goal
of this work is to improve the reproducibility of single-subject parcellation
using shrinkage estimators of such measures, allowing the noisy
subject-specific estimator to "borrow strength" in a principled manner from a
larger population of subjects. We present several empirical Bayes shrinkage
estimators and outline methods for shrinkage when multiple scans are not
available for each subject. We perform shrinkage on raw intervoxel correlation
estimates and use both raw and shrinkage estimates to produce parcellations by
performing clustering on the voxels. Our proposed method is agnostic to the
choice of clustering method and can be used as a pre-processing step for any
clustering algorithm. Using two datasets---a simulated dataset where the true
parcellation is known and is subject-specific and a test-retest dataset
consisting of two 7-minute rsfMRI scans from 20 subjects---we show that
parcellations produced from shrinkage correlation estimates have higher
reliability and validity than those produced from raw estimates. Application to
test-retest data shows that using shrinkage estimators increases the
reproducibility of subject-specific parcellations of the motor cortex by up to
30%.


  The General Spectral Modeling (GSM) code employs the quasi-static
approximation, a standard, low-density methodology that assumes the ionization
balance is separable from a determination of the excited-state populations that
give rise to the spectra. GSM also allows for some states to be treated only as
contributions to effective rates. While these two approximations are known to
be valid at low densities, this work investigates using such methods to model
high-density, non-LTE emission spectra and determines at what point the
approximations break down by comparing to spectra produced by the LANL code
ATOMIC which makes no such approximations. As both approximations are used by
other astrophysical and low-density modeling codes, the results should be of
broad interest. He-like K$\alpha$ emission spectra are presented for Ni, Fe,
and Ca, in order to gauge the effect of both approximations employed in GSM.
This work confirms that at and above the temperature of maximum abundance of
the He-like ionization stage, the range of validity for both approximations is
sufficient for modeling the low- and moderate-density regimes one typically
finds in astrophysical and magnetically confined fusion plasmas. However, a
breakdown does occur for high densities; we obtain quantitative limits that are
significantly higher than previous works. This work demonstrates that, while
the range of validity for both approximations is sufficient to predict the
density-dependent quenching of the z line, the approximations break down at
higher densities. Thus these approximations should be used with greater care
when modeling high-density plasmas such as those found in inertial confinement
fusion and electromagnetic pinch devices.


  The Probe of Inflation and Cosmic Origins (PICO) is an imaging polarimeter
that will scan the sky for 5 years in 21 frequency bands spread between 21 and
799 GHz. It will produce full-sky surveys of intensity and polarization with a
final combined-map noise level of 0.87 $\mu$K arcmin for the required
specifications, equivalent to 3300 Planck missions, and with our current
best-estimate would have a noise level of 0.61 $\mu$K arcmin (6400 Planck
missions). PICO will either determine the energy scale of inflation by
detecting the tensor to scalar ratio at a level $r=5\times 10^{-4}~(5\sigma)$,
or will rule out with more than $5\sigma$ all inflation models for which the
characteristic scale in the potential is the Planck scale. With LSST's data it
could rule out all models of slow-roll inflation. PICO will detect the sum of
neutrino masses at $>4\sigma$, constrain the effective number of light particle
species with $\Delta N_{\rm eff}<0.06~(2\sigma)$, and elucidate processes
affecting the evolution of cosmic structures by measuring the optical depth to
reionization with errors limited by cosmic variance and by constraining the
evolution of the amplitude of linear fluctuations $\sigma_{8}(z)$ with
sub-percent accuracy. Cross-correlating PICO's map of the thermal
Sunyaev-Zeldovich effect with LSST's gold sample of galaxies will precisely
trace the evolution of thermal pressure with $z$. PICO's maps of the Milky Way
will be used to determine the make up of galactic dust and the role of magnetic
fields in star formation efficiency. With 21 full sky legacy maps in intensity
and polarization, which cannot be obtained in any other way, the mission will
enrich many areas of astrophysics. PICO is the only single-platform instrument
with the combination of sensitivity, angular resolution, frequency bands, and
control of systematic effects that can deliver this compelling, timely, and
broad science.


  We show, using an ab initio approach based on Quantum Monte Carlo technique,
that the pseudogap regime emerges in ultracold Fermi gases close to the unitary
point. We locate the onset of this regime at a value of the interaction
strength corresponding to (k_{F}a)^{-1}\approx -0.05 (a - scattering length).
We determine the evolution of the gap as a function of temperature and
interaction strength in the Fermi gas around the unitary limit and show that
our results exhibit a remarkable agreement with the recent wave-vector resolved
radio frequency spectroscopy data. Our results indicate that a finite
temperature structure of the Fermi gas around unitarity is more complicated and
involves the presence of the phase with preformed Cooper pairs, which however
do not contribute to the long range order.


  We identify three properties of the standard oncology phase I trial design or
3 + 3 design. We show that the standard design implicitly uses isotonic
regression to estimate a maximum tolerated dose. We next illustrate the
relationship between the standard design and a Bayesian design proposed by Ji
et al. (2007). A slight modification to this Bayesian design, under a
particular model specification, would assign treatments in a manner identical
to the standard design. We finally present calculations revealing the behavior
of the standard design in a worst case scenario and compare its behavior with
other 3 + 3-like designs.


  Nowadays, technology is rapidly advancing: bots are writing comments,
articles, and reviews. Due to this fact, it is crucial to know if the text was
written by a human or by a bot. This paper focuses on comparing structures of
the coarse-grained partitions of semantic paths for human-written and
bot-generated texts. We compare the clusterizations of datasets of n-grams from
literary texts and texts generated by several bots. The hypothesis is that the
structures and clusterizations are different. Our research supports the
hypothesis. As the semantic structure may be different for different languages,
we investigate Russian, English, German, and Vietnamese languages.


  The dynamics of low-x partons in the transverse plane of a high-energy
nuclear collision is classical, and therefore admits a fully non--perturbative
numerical treatment. We report results of a recent study estimating the initial
energy density in the central region of a collision. Preliminary estimates of
the number of gluons per unit rapidity, and the initial transverse momentum
distribution of gluons, are also provided.


  Point clouds obtained from capture devices or 3D reconstruction techniques
are often noisy and interfere with downstream tasks. The paper aims to recover
the underlying surface of noisy point clouds. We design a novel model,
NoiseTrans, which uses transformer encoder architecture for point cloud
denoising. Specifically, we obtain structural similarity of point-based point
clouds with the assistance of the transformer's core self-attention mechanism.
By expressing the noisy point cloud as a set of unordered vectors, we convert
point clouds into point embeddings and employ Transformer to generate clean
point clouds. To make the Transformer preserve details when sensing the point
cloud, we design the Local Point Attention to prevent the point cloud from
being over-smooth. In addition, we also propose sparse encoding, which enables
the Transformer to better perceive the structural relationships of the point
cloud and improve the denoising performance. Experiments show that our model
outperforms state-of-the-art methods in various datasets and noise
environments.


  We have investigated the modular binary octahedral group $2O$ as a flavor
symmetry to explain the structure of Standard Model. The vector-valued modular
forms in all irreducible representations of this group are constructed. We have
classified all possible fermion masses models based on the modular binary
octahedral group $2O$. A comprehensive numerical analysis is performed, and we
present some benchmark quark/lepton masses models in well agreement with the
experimental data. Notably we find a minimal modular invariant model for
leptons and quarks, which is able to explain simultaneously the masses and
mixing parameters of both quarks and leptons in terms of 14 real free
parameters including the modulus $\tau$. The fermion mass hierarchies around
the vicinity of the modular fixed points are explored.


  We define and study a new type of quantum oracle, the quantum conditional
oracle, which provides oracle access to the conditional probabilities
associated with an underlying distribution. Amongst other properties, we (a)
obtain speed-ups over the best known quantum algorithms for identity testing,
equivalence testing and uniformity testing of probability distributions; (b)
study the power of these oracles for testing properties of boolean functions,
and obtain an algorithm for checking whether an $n$-input $m$-output boolean
function is balanced or $\epsilon$-far from balanced; and (c) give a sub-linear
algorithm, requiring $\tilde{O}(n^{3/4}/\epsilon)$ queries, for testing whether
an $n$-dimensional quantum state is maximally mixed or not.


  We prove that a first-order cooperative system of interacting agents
converges to consensus if the so-called Persistence Excitation condition holds.
This condition requires that the interaction function between any pair of
agents satisfies an integral lower bound. The interpretation is that the
interaction needs to ensure a minimal amount of service.


  Graph anomaly detection on attributed networks has become a prevalent
research topic due to its broad applications in many influential domains. In
real-world scenarios, nodes and edges in attributed networks usually display
distinct heterogeneity, i.e. attributes of different types of nodes show great
variety, different types of relations represent diverse meanings. Anomalies
usually perform differently from the majority in various perspectives of
heterogeneity in these networks. However, existing graph anomaly detection
approaches do not leverage heterogeneity in attributed networks, which is
highly related to anomaly detection. In light of this problem, we propose
AHEAD: a heterogeneity-aware unsupervised graph anomaly detection approach
based on the encoder-decoder framework. Specifically, for the encoder, we
design three levels of attention, i.e. attribute level, node type level, and
edge level attentions to capture the heterogeneity of network structure, node
properties and information of a single node, respectively. In the decoder, we
exploit structure, attribute, and node type reconstruction terms to obtain an
anomaly score for each node. Extensive experiments show the superiority of
AHEAD on several real-world heterogeneous information networks compared with
the state-of-arts in the unsupervised setting. Further experiments verify the
effectiveness and robustness of our triple attention, model backbone, and
decoder in general.


  Regularization by denoising (RED) is a widely-used framework for solving
inverse problems by leveraging image denoisers as image priors. Recent work has
reported the state-of-the-art performance of RED in a number of imaging
applications using pre-trained deep neural nets as denoisers. Despite the
recent progress, the stable convergence of RED algorithms remains an open
problem. The existing RED theory only guarantees stability for convex
data-fidelity terms and nonexpansive denoisers. This work addresses this issue
by developing a new monotone RED (MRED) algorithm, whose convergence does not
require nonexpansiveness of the deep denoising prior. Simulations on image
deblurring and compressive sensing recovery from random matrices show the
stability of MRED even when the traditional RED algorithm diverges.


  It was shown by computer simulation that coarsened grains with lower content
of defects are formed at uniaxial deformation of a four-grain infinite
nano-wire. The structure similar to crystal filaments was formed in the case of
tension. The case of compression demonstrated formation of two grains (from
four initial one) disoriented at an angle of four degrees.


  The LHC potential for discovering doubly-charged vector bileptons is
investigated considering the measurable process $p p$ $\rightarrow$
$\mu^{\mp}\mu^{\mp}\mu^{\pm}\mu^{\pm} X$. The study is performed assuming
different bilepton and leptoquark masses. The process cross-section is
calculated at leading-order using the \textsc{Calchep} package. Combining the
calculation with the latest ATLAS experiment results at a center-of-mass energy
of 7 TeV, bounds on bilepton masses based on LHC data are derived for the first
time. The results exclude bileptons masses in the range of 200 GeV to 500 GeV
at 95\% C.L., depending on the leptoquark mass. Moreover, minimal LHC
integrated luminosities needed for discovering and for setting limits on
bilepton masses are obtained for 13 TeV center-of-mass energy. Simulated events
are passed through a fast parametric detector simulation using the Delphes
package.


  The momentum transfer $\Delta k$ required for a photon to scatter from a
target and emerge as a $\rho^0$ decreases as the photon energy $k$ rises. For
$k>3\times10^{14}$ eV, $\Delta k$ is small enough that the interaction cannot
be localized to a single nucleus. At still higher energies, photons may
coherently scatter elastically from bulk matter and emerge as a $\rho^0$, in a
manner akin to kaon regeneration. Constructive interference from the different
nuclei coherently raises the cross section and the interaction probability
rises linearly with energy. At energies above $10^{23}$ eV, coherent conversion
is the dominant process; photons interact predominantly as $\rho^0$. We compute
the coherent scattering probabilities in slabs of lead, water and rock, and
discuss the implications of the increased hadronic interaction probabilities
for photons on ultra-high energy shower development.


  The coefficients of the chain polynomial of a finite poset enumerate chains
in the poset by their number of elements. The chain polynomials of the
partition lattices and their standard type $B$ analogues are shown to have only
real roots. The real-rootedness of the chain polynomial is conjectured for all
geometric lattices and is shown to be preserved by the pyramid and the prism
operations on Cohen--Macaulay posets. As a result, new families of convex
polytopes whose face lattices have real-rooted chain polynomials are presented.
An application to the face enumeration of the second barycentric subdivision of
the boundary complex of the simplex is also included.


  Mediation analysis seeks to infer how much of the effect of an exposure on an
outcome can be attributed to specific pathways via intermediate variables or
mediators. This requires identification of so-called path-specific effects.
These express how a change in exposure affects those intermediate variables
(along certain pathways), and how the resulting changes in those variables in
turn affect the outcome (along subsequent pathways). However, unlike
identification of total effects, adjustment for confounding is insufficient for
identification of path-specific effects because their magnitude is also
determined by the extent to which individuals who experience large exposure
effects on the mediator, tend to experience relatively small or large mediator
effects on the outcome. This chapter therefore provides an accessible review of
identification strategies under general nonparametric structural equation
models (with possibly unmeasured variables), which rule out certain such
dependencies. In particular, it is shown which path-specific effects can be
identified under such models, and how this can be done.


  Accreting supermassive black holes (SMBHs) can exhibit variable emission
across the electromagnetic spectrum and over a broad range of timescales. The
variability of active galactic nuclei (AGNs) in the ultraviolet and optical is
usually at the few tens of per cent level over timescales of hours to weeks.
Recently, rare, more dramatic changes to the emission from accreting SMBHs have
been observed, including tidal disruption events, 'changing look' AGNs and
other extreme variability objects. The physics behind the 're-ignition',
enhancement and 'shut-down' of accretion onto SMBHs is not entirely understood.
Here we present a rapid increase in ultraviolet-optical emission in the centre
of a nearby galaxy, marking the onset of sudden increased accretion onto a
SMBH. The optical spectrum of this flare, dubbed AT 2017bgt, exhibits a mix of
emission features. Some are typical of luminous, unobscured AGNs, but others
are likely driven by Bowen fluorescence - robustly linked here with
high-velocity gas in the vicinity of the accreting SMBH. The spectral features
and increased ultraviolet flux show little evolution over a period of at least
14 months. This disfavours the tidal disruption of a star as their origin, and
instead suggests a longer-term event of intensified accretion. Together with
two other recently reported events with similar properties, we define a new
class of SMBH-related flares. This has important implications for the
classification of different types of enhanced accretion onto SMBHs.


  This paper develops upper bounds on the end-to-end transmission capacity of
multi-hop wireless networks. Potential source-destination paths are dynamically
selected from a pool of randomly located relays, from which a closed-form lower
bound on the outage probability is derived in terms of the expected number of
potential paths. This is in turn used to provide an upper bound on the number
of successful transmissions that can occur per unit area, which is known as the
transmission capacity. The upper bound results from assuming independence among
the potential paths, and can be viewed as the maximum diversity case. A useful
aspect of the upper bound is its simple form for an arbitrary-sized network,
which allows insights into how the number of hops and other network parameters
affect spatial throughput in the non-asymptotic regime. The outage probability
analysis is then extended to account for retransmissions with a maximum number
of allowed attempts. In contrast to prevailing wisdom, we show that
predetermined routing (such as nearest-neighbor) is suboptimal, since more hops
are not useful once the network is interference-limited. Our results also make
clear that randomness in the location of relay sets and dynamically varying
channel states is helpful in obtaining higher aggregate throughput, and that
dynamic route selection should be used to exploit path diversity.


  This work is devoted to establishing the local-in-time well-posedness of
strong solutions to the three-dimensional compressible primitive equations of
atmospheric dynamics. It is shown that strong solutions exist, unique, and
depend continuously on the initial data, for a short time in two cases: with
gravity but without vacuum, and with vacuum but without gravity. We also
introduce the free boundary problem for the compressible primitive equations.


  We examine the effect of the Philadelphia LandCare (PLC) vacant lot greening
initiative on crime and the extent to which surrounding land uses and business
types moderate this intervention. We rely on a propensity score matching
analysis to account for substantial differences in demographic, economic, land
use, and business characteristics between greened and ungreened vacant lots. We
estimate larger and more significant crime reductions around vacant lots that
are greened in our matched pairs analysis compared to unmatched analyses. The
effects of vacant lot greening on crime are larger in areas with high
residential and low commercial land use and are moderated by the presence of
different types of nearby businesses.


  I discuss new results concerning the evolution of the bispectrum due to
gravitational instability from gaussian initial conditions using one-loop
perturbation theory (PT). Particular attention is paid to the transition from
weakly non-linear scales to the non-linear regime at small scales. Comparison
with numerical simulations is made to assess the regime of validity of the
perturbative approach.


  A forest is a generalization of a tree, and here we consider the Aronszajn
and Suslin properties for forests. We focus on those forests satisfying
coherence, a local smallness property. We show that coherent Aronszajn forests
can be constructed within ZFC. We give several ways of obtaining coherent
Suslin forests by forcing, one of which generalizes the well-known argument of
Todor\v{c}evi\'{c} that a Cohen real adds a Suslin tree. Another uses a strong
combinatorial principle that plays a similar role to diamond. We show that,
starting from a large cardinal, this principle can be obtained by a forcing
that is small relative to the forest it constructs.


  Machine learning-based wearable human activity recognition (WHAR) models
enable the development of various smart and connected community applications
such as sleep pattern monitoring, medication reminders, cognitive health
assessment, sports analytics, etc. However, the widespread adoption of these
WHAR models is impeded by their degraded performance in the presence of data
distribution heterogeneities caused by the sensor placement at different body
positions, inherent biases and heterogeneities across devices, and personal and
environmental diversities. Various traditional machine learning algorithms and
transfer learning techniques have been proposed in the literature to address
the underpinning challenges of handling such data heterogeneities. Domain
adaptation is one such transfer learning techniques that has gained significant
popularity in recent literature. In this paper, we survey the recent progress
of domain adaptation techniques in the Inertial Measurement Unit (IMU)-based
human activity recognition area, discuss potential future directions.


  Recognizing sounds is a key aspect of computational audio scene analysis and
machine perception. In this paper, we advocate that sound recognition is
inherently a multi-modal audiovisual task in that it is easier to differentiate
sounds using both the audio and visual modalities as opposed to one or the
other. We present an audiovisual fusion model that learns to recognize sounds
from weakly labeled video recordings. The proposed fusion model utilizes an
attention mechanism to dynamically combine the outputs of the individual audio
and visual models. Experiments on the large scale sound events dataset,
AudioSet, demonstrate the efficacy of the proposed model, which outperforms the
single-modal models, and state-of-the-art fusion and multi-modal models. We
achieve a mean Average Precision (mAP) of 46.16 on Audioset, outperforming
prior state of the art by approximately +4.35 mAP (relative: 10.4%).


  We prove that the image under any dominant meromorphic map of the
Monge-Amp{\`e}re measure of a H{\"o}lder continuous quasi-psh function still
possesses a H{\"o}lder potential. We also discuss the case of lower regularity.


  We discuss the long-wave hydrodynamic model for a thin film of nematic liquid
crystal in the limit of strong anchoring at the free surface and at the
substrate. We rigorously clarify how the elastic energy enters the evolution
equation for the film thickness in order to provide a solid basis for further
investigation: several conflicting models exist in the literature that predict
qualitatively different behaviour. We consolidate the various approaches and
show that the long-wave model derived through an asymptotic expansion of the
full nemato-hydrodynamic equations with consistent boundary conditions agrees
with the model one obtains by employing a thermodynamically motivated gradient
dynamics formulation based on an underlying free energy functional. As a
result, we find that in the case of strong anchoring the elastic distortion
energy is always stabilising. To support the discussion in the main part of the
paper, an appendix gives the full derivation of the evolution equation for the
film thickness via asymptotic expansion.


  Recently multi-channel multi-radio wireless mesh networks are considered a
reliable and cost effective way for internet access in wide area. A major
research challenge in this network is selecting least interference channel from
available channel and then assigning it to radio efficiently. Many algorithms
and methods have been developed for channel assignment to maximize network
throughput using orthogonal channels. Recent research and testbed experiments
proved that POC based channel assignment allows more flexibility in wireless
spectrum sharing. In this paper, we represent the channel assignment as a graph
edge coloring problem using POC. The signal-to-noise interference ratio is
measured to avoid interference from neighbouring transmission, when we assign
channel to link. Simulation result shows that our proposed method improves
network throughput and performance. Keywords:
  Wireless Mesh Networks, Multi-Radio, Multi-Channel, Partially Overlapping
Channels, Signal-to-noise interference


  We examine a graphene quantum dot formed by combining an electric and a
uniform magnetic field. The electric field creates a smooth quantum well
potential while the magnetic field induces an exponential tail to the dot
states. The states peak in the well and the electrostatic barrier region as a
result of the Klein tunneling effect. Coupling between dot states which peak in
different regions can be achieved with the electric and magnetic fields. The
tunability of this dot with moderate external fields could be used for
designing quantum devices in monolayer graphene.


  In arXiv:1606.07885, many different Grothendieck topologies were introduced
on the category of Azumaya algebras. Here we give a classification in terms of
sets of supernatural numbers. Then we discuss the associated categories of
sheaves and their topos-theoretic points, which are related to UHF-algebras.
The sheaf toposes that correspond to a single supernatural number have an
alternative description, involving actions of the associated projective general
linear group.


  These are the extended notes of a mini-course given at the school
WinterBraids X. We discuss algebras simultaneously related to: the braid group,
the Yang-Baxter equation and the representation theory of quantum groups. The
main goal is to explain the idea of the fusion procedure for the Yang-Baxter
equation and to show how it leads to new examples of such algebras: the fused
Hecke algebras.


  In this brief, the spontaneous symmetry breaking (SSB) of the $\varphi^4$
theory in phase space, is studied. This phase space results from the
appropriate system of Poincare maps, produced in both the Minkowski and the
Euclidean time. The importance of discretization in the creation of phase
space, is highlighted. A series of interesting, novel, unknown behaviors are
reported for the first time; among them the most characteristic is the change
in stability. In specific, the stable fixed points of the $\varphi^4$ potential
appear as unstable ones, in phase space. Additionally, in the Euclidean-time
phase space a unique instability in the position of the critical point, can be
created. This instability is further proposed to host tachyonic field in
Euclidean space.


  This paper proposes to use both audio input and subject information to
predict the personalized preference of two audio segments with the same content
in different qualities. A siamese network is used to compare the inputs and
predict the preference. Several different structures for each side of the
siamese network are investigated, and an LDNet with PANNs' CNN6 as the encoder
and a multi-layer perceptron block as the decoder outperforms a baseline model
using only audio input the most, where the overall accuracy grows from 77.56%
to 78.04%. Experimental results also show that using all the subject
information, including age, gender, and the specifications of headphones or
earphones, is more effective than using only a part of them.


  The study of Active Galactic Nuclei (AGNs) is vital in order to understand
their respective nuclei bounded activity primarily triggered by the accretion
disk and the associated corona. The hard X-ray emission characterised by the
spectral index $\Gamma$ emitted by these sources in 2-10 keV band ionizes the
nearby physical features like disk, BLR, NLR and provides a radiative
configuration. However, based on previous studies, there is degeneracy in the
evolution of $\Gamma$ across the redshift, wherein few studies display a
systematic trend in the evolution and others rule out the systematic variation.
In the present work, we study the evolution of $\Gamma$ across the redshift for
a very large sample and perform further studies on the variation of $\Gamma$
with optical parameters using SDSS data viz. H$_{\beta}$ \& Mg II and their
luminosities. Based on analysis we find that there is no change in $\Gamma$
across the redshift and it does not show any correlation with the optical
parameters. This strongly suggests that the $\Gamma$ is influenced by the soft
excess and/or reflection component and is affecting the disk and BLR region at
the same strength across the redshift.


  This paper shows the results of an experiment applied to 170 students from
two Chilean universities who solve a task about reading a graph of an affine
function in an online assessment environment where the parameters (coefficients
of the graphed affine function) are randomly defined from an ad-hoc algorithm,
with automatic correction and automatic feedback. We distinguish two versions:
one of them with integer coefficients and the other one with decimal
coefficients in the affine function. We observed that the nature of the
coefficients impacts the mathematical work used by the students, where we again
focus on two of them: by direct estimation from the graph or by calculating the
equation of the line. On the other hand, a feedback oriented towards the
"estimation" strategy influences the mathematical work used by the students,
even though a non-negligible group persists in the "calculating" strategy,
which is partly explained by the perception of each of the strategies.


  The collateral choice option allows a collateral-posting party the
opportunity to change the type of security in which the collateral is
deposited. Due to non-zero collateral basis spreads, this optionality
significantly impacts asset valuation. Because of the complexity of valuing the
option, many practitioners resort to deterministic assumptions on the
collateral rates. In this article, we focus on a valuation model of the
collateral choice option based on stochastic dynamics. Intrinsic differences in
the resulting collateral choice option valuation and its implications for
collateral management are presented. We obtain sensitivities of the collateral
choice option price under both the deterministic and the stochastic model, and
we show that the stochastic model attributes risks to all involved collateral
currencies. Besides an inability to capture volatility effects, the
deterministic model exhibits a digital structure in which only the
cheapest-to-deliver currency influences the valuation at a given time. We
further consider hedging an asset with the collateral choice option by a
portfolio of domestic and foreign zero-coupon bonds that do not carry the
collateral choice option. We propose static hedging strategies based on the
crossing times of the deterministic model and based on variance-minimization
under the stochastic model. We show how the weights of this model can be
explicitly determined with the semi-analytical common factor approach and we
show in numerical experiments that this strategy offers good hedging
performance under minimized variance.


  This paper addresses an interesting yet challenging problem -- source-free
unsupervised domain adaptation (SFUDA) for pinhole-to-panoramic semantic
segmentation -- given only a pinhole image-trained model (i.e., source) and
unlabeled panoramic images (i.e., target). Tackling this problem is nontrivial
due to the semantic mismatches, style discrepancies, and inevitable distortion
of panoramic images. To this end, we propose a novel method that utilizes
Tangent Projection (TP) as it has less distortion and meanwhile slits the
equirectangular projection (ERP) with a fixed FoV to mimic the pinhole images.
Both projections are shown effective in extracting knowledge from the source
model. However, the distinct projection discrepancies between source and target
domains impede the direct knowledge transfer; thus, we propose a panoramic
prototype adaptation module (PPAM) to integrate panoramic prototypes from the
extracted knowledge for adaptation. We then impose the loss constraints on both
predictions and prototypes and propose a cross-dual attention module (CDAM) at
the feature level to better align the spatial and channel characteristics
across the domains and projections. Both knowledge extraction and transfer
processes are synchronously updated to reach the best performance. Extensive
experiments on the synthetic and real-world benchmarks, including outdoor and
indoor scenarios, demonstrate that our method achieves significantly better
performance than prior SFUDA methods for pinhole-to-panoramic adaptation.