  The article is devoted to construction of effective procedures of the
mean-square approximation for iterated Stratonovich stochastic integrals of
multiplicities 1 to 5. We apply the method of generalized multiple Fourier
series for approximation of iterated stochastic integrals. More precisely, we
use multiple Fourier-Legendre series converging in the sense of norm in Hilbert
space $L_2([t,T]^k),$ $k\in\mathbb{N}.$ Considered iterated Stratonovich
stochastic integrals are part of the Taylor-Stratonovich expansion. That is why
the results of the article can be applied to implementation of numerical
methods with the orders 1.0, 1.5, 2.0 and 2.5 of strong convergence for Ito
stochastic differential equations with multidimensional non-commutative noise.


  When free vortices are present in the pseudogap region of underdoped
cuprates, it is shown that conventional Anderson-Higgs mechanism does not work
because the Goldstone field is not an analytic function. However, after
decomposing the Goldstone field into longitudinal and transverse components, we
find that the former can be eliminated by a special gauge transformation and
the gauge field becomes massive, but the latter persists in the theory in any
case. Thus we obtain an extended Anderson-Higgs mechanism which exhibits
completely new physics comparing with the conventional one.


  Hochster and Huneke showed that the property of F-regularity deforms for
Gorenstein rings, i.e., if (R,m) is a Gorenstein local ring such that R/tR is
F-regular for some nonzerodivisor t in m, then R is F-regular. This result was
later extended to the case of Q-Gorenstein rings by Smith (for rings of
characteristic zero) and Aberbach, Katzman, and MacCrimmon (for rings of
positive characteristic). We investigate the deformation of strong F-regularity
using an anti-canonical cover of R, i.e., a symbolic Rees algebra S = R + It +
I^(2)t^2 + ..., where I is an inverse for the canonical module in the divisor
class group of the ring R. We show that strong F-regularity deforms in the case
that the symbolic powers I^(i) satisfy the Serre condition S_3 for all i > 0,
and the ring S is Noetherian. We also construct examples which show that the
property of F-purity does not deform.


  We give several sufficient conditions for uniform exponential growth in the
setting of virtually torsion-free hierarchically hyperbolic groups. For
example, any hierarchically hyperbolic group that is also acylindrically
hyperbolic has uniform exponential growth. In addition, we provide a
quasi-isometric characterization of hierarchically hyperbolic groups without
uniform exponential growth. To achieve this, we gain new insights on the
structure of certain classes of hierarchically hyperbolic groups. Our methods
give a new unified proof of uniform exponential growth for several examples of
groups with notions of non-positive curvature. In particular, we obtain the
first proof of uniform exponential growth for certain groups that act
geometrically on CAT(0) cubical spaces of dimension 3 or more. Under additional
hypotheses, we show that a quantitative Tits alternative holds for
hierarchically hyperbolic groups.


  Anomaly localization is a practical technology for improving industrial
production line efficiency. Due to anomalies are manifold and hard to be
collected, existing unsupervised researches are usually equipped with anomaly
synthesis methods. However, most of them are biased towards structural defects
synthesis while ignoring the underlying logical constraints. To fill the gap
and boost anomaly localization performance, we propose an edge manipulation
based anomaly synthesis framework, named LogicAL, that produces photo-realistic
both logical and structural anomalies. We introduce a logical anomaly
generation strategy that is adept at breaking logical constraints and a
structural anomaly generation strategy that complements to the structural
defects synthesis. We further improve the anomaly localization performance by
introducing edge reconstruction into the network structure. Extensive
experiments on the challenge MVTecLOCO, MVTecAD, VisA and MADsim datasets
verify the advantage of proposed LogicAL on both logical and structural anomaly
localization.


  We construct an Sp(2,R) gauge invariant particle action which possesses
manifest space-time SO(d,2) symmetry, global supersymmetry and kappa
supersymmetry. The global and local supersymmetries are non-abelian
generalizations of Poincare type supersymmetries and are consistent with the
presence of two timelike dimensions. In particular, this action provides a
unified and explicit superparticle representation of the superconformal groups
OSp(N/4), SU(2,2/N) and OSp(8*/N) which underlie various AdS/CFT dualities in
M/string theory. By making diverse Sp(2,R) gauge choices our action reduces to
diverse one-time physics systems, one of which is the ordinary (one-time)
massless superparticle with superconformal symmetry that we discuss explicitly.
We show how to generalize our approach to the case of superalgebras, such as
OSp(1/32), which do not have direct space-time interpretations in terms of only
zero branes, but may be realizable in the presence of p-branes.


  In this note we will adapt Topping's $\mathcal{L}$-optimal transportation
theory for Ricci flow to a more general situation, i.e. to a closed manifold
$(M,g_{ij}(t))$ evolving by $\partial_tg_{ij}=-2S_{ij}$, where $S_{ij}$ is a
symmetric tensor field of (2,0)-type on $M$. We extend some recent results of
Topping, Lott and Brendle, generalize the monotonicity of List's (and hence
also of Perelman's) $\mathcal{W}$-entropy, and recover the monotonicity of
M$\ddot{u}$ller's (and hence also of Perelman's) reduced volume.


  We extend the Generalised Langevin Equation (GLE) method [Phys. Rev. B 89,
134303 (2014)] to model a central classical region connected to two realistic
thermal baths at two different temperatures. In such nonequilibrium conditions
a heat flow is established, via the central system, in between the two baths.
The GLE-2B (GLE two baths) scheme permits us to have a realistic description of
both the dissipative central system and its surrounding baths. Following the
original GLE approach, the extended Langevin dynamics scheme is modified to
take into account two sets of auxiliary degrees of freedom corresponding to the
mapping of the vibrational properties of each bath. These auxiliary variables
are then used to solve the non-Markovian dissipative dynamics of the central
region. The resulting algorithm is used to study a model of a short Al nanowire
connected to two baths. The results of the simulations using the GLE-2B
approach are compared to the results of other simulations that were carried out
using standard thermostatting approaches (based on Markovian Langevin and
Nose-Hoover thermostats). We concentrate on the steady state regime and study
the establishment of a local temperature profile within the system. The
conditions for obtaining a flat profile or a temperature gradient are examined
in detail, in agreement with earlier studies. The results show that the GLE-2B
approach is able to treat, within a single scheme, two widely different thermal
transport regimes, i.e. ballistic systems, with no temperature gradient, and
diffusive systems with a temperature gradient.


  LexNLP is an open source Python package focused on natural language
processing and machine learning for legal and regulatory text. The package
includes functionality to (i) segment documents, (ii) identify key text such as
titles and section headings, (iii) extract over eighteen types of structured
information like distances and dates, (iv) extract named entities such as
companies and geopolitical entities, (v) transform text into features for model
training, and (vi) build unsupervised and supervised models such as word
embedding or tagging models. LexNLP includes pre-trained models based on
thousands of unit tests drawn from real documents available from the SEC EDGAR
database as well as various judicial and regulatory proceedings. LexNLP is
designed for use in both academic research and industrial applications, and is
distributed at https://github.com/LexPredict/lexpredict-lexnlp.


  The bihamiltonian structure of the N=2 Supersymmetric Boussinesq equation is
found. It is not reduced to the corresponding classical structure and hence it
describes the pure supersymmetric effect. For the supersymmetric Boussinesq
equation which contains the classical partner the Lax pair is given explicitly.
Thus we prove the integrability of the equation.


  We show that for $1\leq p, q<\infty$ with $p/q \notin \mathbb{N}$, the doubly
atomless separable $L_pL_q$ Banach lattice $L_p(L_q)$ is approximately
ultrahomogeneous (AUH) over the class of its finitely generated sublattices.
The above is not true when $p/q \in \mathbb{N}$. However, for any $p\neq q$,
$L_p(L_q)$ is AUH over the finitely generated lattices in the class $BL_pL_q$
of bands of $L_pL_q$ lattices.


  The characteristics of the chiral phase transition are analyzed within the
framework of chiral quark models with nonlocal interactions in the mean field
approximation. In the chiral limit, we develop a semi-analytic framework which
allows us to explicitly determine the phase transition curve, the position of
the critical points, some relevant critical exponents, etc. For the case of
finite current quark masses, we show the behavior of various thermodynamical
and chiral response functions across the phase transition.


  The influence of random pinning on the vortex dynamics in a periodic square
potential under an external drive is investigated. Using theoretical approach
and numerical experiments, we found several dynamical phases of vortex motion
that are different from the ones for a regular pinning potential. Vortex
transfer is controlled by kinks and antikinks, which either preexist in the
system or appear spontaneously in pairs and then propagate in groups. When
kinks and antikinks collide, they annihilate.


  Pulsating stars, such as Cepheids and RR Lyrae, offer us a window to measure
and study changes due to stellar evolution. In this work, we study the former
by calculating a set of evolutionary tracks of stars with an initial mass of 4
to 7 $M_\odot$, varying the initial rotation rate and metallicity, using the
stellar evolution code Modules for Experiments in Stellar Astrophysics (MESA).
Using Radial Stellar Pulsations (RSP), a recently added functionality of MESA,
we obtained theoretical instability strip (IS) edges and linear periods for the
radial fundamental mode. Period-age, period-age-temperature, period-luminosity,
and period-luminosity-temperature relationships were derived for three rotation
rates and metallicities, showing a dependence on crossing number, position in
the IS, rotation, and metallicity. We calculated period change rates (PCRs)
based on the linear periods from RSP. We compared our models with literature
results using the Geneva code, and found large differences, as expected due to
the different implementations of rotation between codes. In addition, we
compared our theoretical PCRs with those measured in our recent work for Large
Magellanic Cloud Cepheids. We found good overall agreement, even though our
models do not reach the short-period regime exhibited by the empirical data.
Implementations of physical processes not yet included in our models, such as
pulsation-driven mass loss, an improved treatment of convection that may lead
to a better description of the instability strip edges, as well as
consideration of a wider initial mass range, could all help improve the
agreement with the observed PCRs.


  This note is a discussion of the paper "Confidence distribution" by Min-ge
Xie and Kesar Singh, to appear in the International Statistical Review.


  The article is a slightly extended version of the talk, with the same title,
which I gave at the Kinosaki Symposium on Algebraic Geometry in October 2011,
and dealing with the classification of complex projective surfaces of general
type with vanishing geometric genus, and especially with the moduli spaces of
Burniat surfaces.


  The structure of proteins is essential for its function. The determination of
protein structures is possible by experimental or predicted by computational
methods, but also a combination of both approaches is possible. Here, first an
overview about experimental structure determination methods with their pros and
cons is given. Then we describe how mass spectrometry is useful for
semi-experimental integrative protein structure determination. We review the
methodology and describe software programs supporting such integrated protein
structure prediction approaches, making use of distance constraints got from
mass spectrometry cross-linking experiments


  We present a novel framework for evaluating recommendation algorithms in
terms of the `jumps' that they make to connect people to artifacts. This
approach emphasizes reachability via an algorithm within the implicit graph
structure underlying a recommender dataset, and serves as a complement to
evaluation in terms of predictive accuracy. The framework allows us to consider
questions relating algorithmic parameters to properties of the datasets. For
instance, given a particular algorithm `jump,' what is the average path length
from a person to an artifact? Or, what choices of minimum ratings and jumps
maintain a connected graph? We illustrate the approach with a common jump
called the `hammock' using movie recommender datasets.


  The data acquisition (DAQ) system of the SND detector successfully operated
during four data-taking seasons (2010-2013) at the e+e- collider VEPP-2000.
Currently the collider is shut down for planned reconstruction, which is
expected to increase the VEPP-2000 luminosity and data flow from the SND
detector electronics by up to 10 times. Since current DAQ system implementation
(electronics and computer part) does not have enough reserve for selection of
events in the new environment without compromising quality, there arose the
need for the system upgrade. Here we report on the major SND data acquisition
system upgrade which includes developing new electronics for digitization and
data transfer, complete redesign of the data network, increasing of the DAQ
computer farm processing capacity and making the event building process
concurrent. These measures will allow us to collect data flow from the most
congested detector subsystems in parallel in contrast to the current situation.
We would like to discuss also the possibility to implement full software
trigger solution in the future.


  New class of reference distribution functions for numerical approximation of
the solution of the Fokker-Planck equations associated to the charged particle
dynamics in tokamak are studied. The reference distribution functions are
obtained by maximization of the generalized Renyi entropy under scale-invariant
restrictions. Explicit analytic form, with algebraic decay, that is a
generalization of the previous distribution with exponential tails was derived.


  We use a numerical simulation of cosmological reionization to estimate the
likelihood of detecting Lyman-alpha emitting galaxies during the
pre-reionization era. We show that it is possible to find galaxies even at z~9
that are barely affected by the dumping wing of the Gunn-Peterson absorption
from the neutral IGM outside of their HII regions. The damping wing becomes
rapidly more significant at z>9, but even at z>10 is it not inconceivable
(although quite hard) to see a Lyman-alpha emission line from a star-forming
galaxy.


  Visual domain randomization in simulated environments is a widely used method
to transfer policies trained in simulation to real robots. However, domain
randomization and augmentation hamper the training of a policy. As
reinforcement learning struggles with a noisy training signal, this additional
nuisance can drastically impede training. For difficult tasks it can even
result in complete failure to learn. To overcome this problem we propose to
pre-train a perception encoder that already provides an embedding invariant to
the randomization. We demonstrate that this yields consistently improved
results on a randomized version of DeepMind control suite tasks and a stacking
environment on arbitrary backgrounds with zero-shot transfer to a physical
robot.


  Bethe ansatz formulation is presented for several explicit examples of quasi
exactly solvable difference equations of one degree of freedom which are
introduced recently by one of the present authors. These equations are
deformation of the well-known exactly solvable difference equations of the
Meixner-Pollaczek, continuous Hahn, continuous dual Hahn, Wilson and
Askey-Wilson polynomials. Up to an overall factor of the so-called pseudo
ground state wavefunction, the eigenfunctions within the exactly solvable
subspace are given by polynomials whose roots are solutions of the associated
Bethe ansatz equations. The corresponding eigenvalues are expressed in terms of
these roots.


  We present the last version of the PyrAmid Simulator Software for Adaptive
opTics Arcetri (PASSATA), an IDL and CUDA based object oriented software
developed in the Adaptive Optics group of the Arcetri observatory for
Monte-Carlo end-to-end adaptive optics simulations. The original aim of this
software was to evaluate the performance of a single conjugate adaptive optics
system for ground based telescope with a pyramid wavefront sensor. After some
years of development, the current version of PASSATA is able to simulate
several adaptive optics systems: single conjugate, multi conjugate and ground
layer, with Shack Hartmann and Pyramid wavefront sensors. It can simulate from
8m to 40m class telescopes, with diffraction limited and resolved sources at
finite or infinite distance from the pupil. The main advantages of this
software are the versatility given by the object oriented approach and the
speed given by the CUDA implementation of the most computational demanding
routines. We describe the software with its last developments and present some
examples of application.


  In this article we obtain two-sided estimates for the Greens function of
fractional boundary value problems on $\mathbb R_+ \times \mathbb R_+ \times
\mathbb R^d$ of the form \[(-{}_{t_1}D^\beta_{0+*} -
{}_{t_2}D^\gamma_{0+*})u(t_1, t_2, x) = L_{x}u(t_1, t_2, x),\] with some
prescribed boundary functions on the boundaries $\{0\} \times \mathbb R_+
\times \mathbb R^d$ and $\mathbb R_+ \times\{0\}\times \mathbb R^d$. The
operators ${}_{t_1}D^\beta$ and ${}_{t_1}D^\gamma$ are Caputo fractional
derivatives of order $\beta, \gamma \in (0, 1)$ and $L_{x}$ is the generator of
a diffusion semigroup: $L_x= \nabla \cdot(a(x) \nabla)$ for some nice function
$a(x)$. The Greens function of such boundary value problems are decomposed into
its components along each boundary, giving rise to a natural extension to the
case involving $k \geq 2$ number of fractional derivatives on the left hand
side.


  By developing a suitable version of the circle method, we show that the space
of degree $e$ rational curves on a smooth hypersurface of degree $d$ has only
canonical singularities provided its dimension is sufficiently large with
respect to $e$ and $d$.


  According to the World Health Organization(WHO), malaria is estimated to have
killed 627,000 people and infected over 241 million people in 2020 alone, a 12%
increase from 2019. Microscopic diagnosis of blood cells is the standard
testing procedure to diagnose malaria. However, this style of diagnosis is
expensive, time-consuming, and greatly subjective to human error, especially in
developing nations that lack well-trained personnel to perform high-quality
microscopy examinations. This paper proposes Mass-AI-Scope (MAIScope): a novel,
low-cost, portable device that can take microscopic images and automatically
detect malaria parasites with embedded AI. The device has two subsystems. The
first subsystem is an on-device multi-layered deep learning network, that
detects red blood cells (RBCs) from microscopic images, followed by a malaria
parasite classifier that recognizes malaria parasites in the individual RBCs.
The testing and validation demonstrated a high average accuracy of 89.9% for
classification and average precision of 61.5% for detection models using
TensorFlow Lite while addressing limited storage and computational capacity.
This system also has cloud synchronization, which sends images to the cloud
when connected to the Internet for analysis and model improvement purposes. The
second subsystem is the hardware which consists of components like Raspberry
Pi, a camera, a touch screen display, and an innovative low-cost bead
microscope. Evaluation of the bead microscope demonstrated similar image
quality with that of expensive light microscopes. The device is designed to be
portable and work in remote environments without the Internet or power. The
solution is extensible to other diseases requiring microscopy and can help
standardize automation of disease diagnosis in rural parts of developing
nations.


  We revisit the popular notion of effective or renormalized charge, which is a
concept of central importance in the field of highly charged colloidal or
polyelectrolyte solutions. Working at the level of a linear Debye-H\"uckel like
theory only, we propose a simple, efficient and versatile method to predict the
saturated amount of charge renormalization, which is however a non-linear
effect arising at strong electrostatic coupling. The results are successfully
tested against the numerical solutions of Poisson-Boltzmann theory for polyions
of various shapes (planar, cylindrical and spherical), both in the infinite
dilution limit or in confined geometry, with or without added electrolyte. Our
approach, accurate for monovalent micro-ions in solvents like water, is finally
confronted against experimental results, namely the crystallization of charged
colloidal suspensions and the osmotic coefficient of B-DNA solutions.


  Total hip replacement is the most effective treatment for late stage
osteoarthritis. However, adverse local tissue reactions (ALTRs) associated with
fretting corrosion have been observed in patients with modular total hip
implants. The purpose of this study is to increase the fretting corrosion
resistance of the CoCrMo alloy and the associated metal ion release by applying
hard coatings to the surface. Cathodic arc evaporation technique (arc-PVD) was
used to deposit TiSiN and ZrN hard coatings on to CoCrMo substrates. The
morphology, chemical composition, crystal structures and residual stress of the
coatings were characterized by scanning electron microscopy, energy dispersive
x-ray spectroscopy, and X-ray diffractometry. Hardness, elastic modulus, and
adhesion of the coatings were measured by nano-indentation, nano-scratch test,
and the Rockwell C test. Fretting corrosion resistance tests of coated and
uncoated CoCrMo discs against Ti6Al4V spheres were conducted on a four-station
fretting testing machine in simulated body fluid at 1Hz for 1 million cycles.
Post-fretting samples were analyzed for morphological changes, volume loss and
metal ion release. Our analyses showed better surface finish and lower residual
stress for ZrN coating, but higher hardness and better scratch resistance for
TiSiN coating. Fretting results demonstrated substantial improvement in
fretting corrosion resistance of CoCrMo with both coatings. ZrN and TiSiN
decreased fretting volume loss by more than 10 times and 1000 times,
respectively. Both coatings showed close to 90% decrease of Co ion release
during fretting corrosion tests. Our results suggest that hard coating
deposition on CoCrMo alloy can significantly improve its fretting corrosion
resistance and could thus potentially alleviate ALTRs in metal hip implants.


  We present the exact numerical solutions for the Schwinger-Dyson equations at
finite temperature with general gauge in Abelian gauge theory. We then study
the chiral phase transition on temperature from the obtained solutions. We find
that, within the quenched Schwinger-Dyson equations, there exists substantial
gauge dependence on the solutions and the critical temperature.


  Learning-based techniques, especially advanced Large Language Models (LLMs)
for code, have gained considerable popularity in various software engineering
(SE) tasks. However, most existing works focus on designing better
learning-based models and pay less attention to the properties of datasets.
Learning-based models, including popular LLMs for code, heavily rely on data,
and the data's properties (e.g., data distribution) could significantly affect
their behavior. We conducted an exploratory study on the distribution of SE
data and found that such data usually follows a skewed distribution (i.e.,
long-tailed distribution) where a small number of classes have an extensive
collection of samples, while a large number of classes have very few samples.
We investigate three distinct SE tasks and analyze the impacts of long-tailed
distribution on the performance of LLMs for code. Our experimental results
reveal that the long-tailed distribution has a substantial impact on the
effectiveness of LLMs for code. Specifically, LLMs for code perform between
30.0\% and 254.0\% worse on data samples associated with infrequent labels
compared to data samples of frequent labels. Our study provides a better
understanding of the effects of long-tailed distributions on popular LLMs for
code and insights for the future development of SE automation.


  Here, we introduce a fully local index named "sensitivity" for each neuron to
control chaoticity or gradient globally in a neural network (NN). We also
propose a learning method to adjust it named "sensitivity adjustment learning
(SAL)". The index is the gradient magnitude of its output with respect to its
inputs. By adjusting its time average to 1.0 in each neuron, information
transmission in the neuron changes to be moderate without shrinking or
expanding for both forward and backward computations. That results in moderate
information transmission through a layer of neurons when the weights and inputs
are random. Therefore, SAL can control the chaoticity of the network dynamics
in a recurrent NN (RNN). It can also solve the vanishing gradient problem in
error backpropagation (BP) learning in a deep feedforward NN or an RNN. We
demonstrate that when applying SAL to an RNN with small and random initial
weights, log-sensitivity, which is the logarithm of RMS (root mean square)
sensitivity over all the neurons, is equivalent to the maximum Lyapunov
exponent until it reaches 0.0. We also show that SAL works with BP or BPTT (BP
through time) to avoid the vanishing gradient problem in a 300-layer NN or an
RNN that learns a problem with a lag of 300 steps between the first input and
the output. Compared with manually fine-tuning the spectral radius of the
weight matrix before learning, SAL's continuous nonlinear learning nature
prevents loss of sensitivities during learning, resulting in a significant
improvement in learning performance.


  Quadratic relations of the intertwiners are given explicitly in two cases of
chiral conformal field theory, and monomial bases of the representation spaces
are constructed by using the Fourier components of the intertwiners. The two
cases are the (p,p')-minimal series for the Virasoro algebra where 1<p'/p<2,
and the level k integrable highest weight modules for the affine Lie algebra
\hat{sl}_2.


  We present Hubble Space Telescope NICMOS imaging of W3 IRS 5, a binary
high-mass protostar. In addition to the two protostars, NICMOS images taken in
the F222M and F160W filters show three new 2.22 micron sources with very red
colors; these sources fall within a region 5600 AU in diameter, and are
coincident with a 100 solar mass dense molecular clump. Two additional point
sources are found within 0.4'' (800 AU) of one of the high-mass protostars;
these may be stellar companions or unresolved emission knots from an outflow.
We propose that these sources constitute a nascent Trapezium system in the
center of the W3 IRS 5 cluster containing as many as five proto OB stars. This
would be the first identification of a Trapezium still deeply embedded in its
natal gas.


  Time-series, multi-color photometry and high-resolution spectra of the short
period eclipsing binary V Tri were obtained by observations. The completely
covered light and radial velocity curves of the binary system are presented.
All times of light minima derived from both photoelectric and CCD photometry
were used to calculate the orbital period and new ephemerides of the eclipsing
system. The analysis of $O-C$ diagram reveals that the orbital period is
$0.58520481\ days$, decreasing at a rate of $dP/dt=-7.80\times10^{-8} d\
yr^{-1} $. The mass transfer between the two components and the light
time-travel effect due to a third body could be used to explain the period
decrease. However, a semidetached configuration with the less-mass component
filling and the primary nearly filling each of their Roche lobes was derived
from the synthesis of the light and radial velocity curves by using the 2015
version of the Wilson-Devinney code. We consider the period decrease to be the
nonconservative mass transfer from the secondary component to the primary and
the mass loss of the system, which was thought to be an EB type while it should
be an EA type (semi-detached Algol-type) from our study. The masses, radii and
luminosities of the primary and secondary are $1.60\pm0.07 M_\odot$,
$1.64\pm0.02 R_\odot$, $14.14\pm0.73 L_\odot$ and $0.74\pm0.02 M_\odot$,
$1.23\pm0.02 R_\odot$, $1.65\pm0.05 L_\odot$, respectively.


  In order to understand the origin of stock price jumps, we cross-correlate
high-frequency time series of stock returns with different news feeds. We find
that neither idiosyncratic news nor market wide news can explain the frequency
and amplitude of price jumps. We find that the volatility patterns around jumps
and around news are quite different: jumps are followed by increased
volatility, whereas news tend on average to be followed by lower volatility
levels. The shape of the volatility relaxation is also markedly different in
the two cases. Finally, we provide direct evidence that large transaction
volumes are_not_ responsible for large price jumps. We conjecture that most
price jumps are induced by order flow fluctuations close to the point of
vanishing liquidity.


  Despite the availability of very detailed data on financial market,
agent-based modeling is hindered by the lack of information about real trader
behavior. This makes it impossible to validate agent-based models, which are
thus reverse-engineering attempts. This work is a contribution to the building
of a set of stylized facts about the traders themselves. Using the client
database of Swissquote Bank SA, the largest on-line Swiss broker, we find
empirical relationships between turnover, account values and the number of
assets in which a trader is invested. A theory based on simple mean-variance
portfolio optimization that crucially includes variable transaction costs is
able to reproduce faithfully the observed behaviors. We finally argue that our
results bring into light the collective ability of a population to construct a
mean-variance portfolio that takes into account the structure of transaction
costs


  Finding the mixed Nash equilibria (MNE) of a two-player zero sum continuous
game is an important and challenging problem in machine learning. A canonical
algorithm to finding the MNE is the noisy gradient descent ascent method which
in the infinite particle limit gives rise to the {\em Mean-Field Gradient
Descent Ascent} (GDA) dynamics on the space of probability measures. In this
paper, we first study the convergence of a two-scale Mean-Field GDA dynamics
for finding the MNE of the entropy-regularized objective. More precisely we
show that for each finite temperature (or regularization parameter), the
two-scale Mean-Field GDA with a suitable {\em finite} scale ratio converges
exponentially to the unique MNE without assuming the convexity or concavity of
the interaction potential. The key ingredient of our proof lies in the
construction of new Lyapunov functions that dissipate exponentially along the
Mean-Field GDA. We further study the simulated annealing of the Mean-Field GDA
dynamics. We show that with a temperature schedule that decays logarithmically
in time the annealed Mean-Field GDA converges to the MNE of the original
unregularized objective.


  In this paper we study nonequilibrium dynamics of one dimensional Bose gas
from the general perspective of dynamics of integrable systems. After outlining
and critically reviewing methods based on inverse scattering transform,
intertwining operators, q-deformed objects, and extended dynamical conformal
symmetry, we focus on the form-factor based approach. Motivated by possible
applications in nonlinear quantum optics and experiments with ultracold atoms,
we concentrate on the regime of strong repulsive interactions. We consider
dynamical evolution starting from two initial states: a condensate of particles
in a state with zero momentum and a condensate of particles in a gaussian
wavepacket in real space. Combining the form-factor approach with the method of
intertwining operator we develop a numerical procedure which allows explicit
summation over intermediate states and analysis of the time evolution of
non-local density-density correlation functions. In both cases we observe a
tendency toward formation of crystal-like correlations at intermediate time
scales.


  We prove Griffiths inequalities for spins in n>1 dimensions with no
interaction.


  A work of Sorensen is rewritten here to include nontrivial types at the
infinite places. This extends results of K. Ribet and R. Taylor on
level-raising for algebraic modular forms on D^{\times}, where D is a definite
quaternion algebra over a totally real field F. This is done for any
automorphic representations \pi of an arbitrary reductive group G over F which
is compact at infinity. It is not assumed that \pi_\infty is trivial. If
\lambda is a finite place of \bar{\Q}, and w is a place where \pi_w is
unramified and \pi_w is congruent to the trivial representation mod \lambda,
then under some mild additional assumptions (relaxing requirements on the
relation between w and \ell which appear in previous works) the existence of a
\tilde{\pi} congruent to \pi mod \lambda such that \tilde{\pi}_w has more
parahoric fixed vectors than \pi_w, is proven. In the case where G_w has
semisimple rank one, results of Clozel, Bellaiche and Graftieaux according to
which \tilde{\pi}_w is Steinberg, are sharpened. To provide applications of the
main theorem two examples over F of rank greater than one are considered. In
the first example G is taken to be a unitary group in three variables and a
split place w. In the second G is taken to be an inner form of GSp(2). In both
cases, precise satisfiable conditions on a split prime w guaranteeing the
existence of a \tilde{\pi} congruent to \pi mod \lambda such that the component
\tilde{\pi}_w is generic and Iwahori spherical, are obtained. For symplectic G,
to conclude that \tilde{\pi}_w is generic, computations of R. Schmidt are used.
In particular, if \pi is of Saito-Kurokawa type, it is congruent to a
\tilde{\pi} which is not of Saito-Kurokawa type.


  Neutron diffraction measurements on a high quality single crystal of CeAu2Ge2
reveal two new magnetic structures that coexist with commensurate long range
antiferromagnetic order below the Neel temperature T_N ~ 14 K. The new magnetic
structures, which exhibit distinct temperature and field dependencies, are
described by both commensurate and incommensurate magnetic structures and
introduces new region in the H-T phase diagram. These new experimental
observations provide essential information for developing a universal
understanding of the magnetic properties of this class of Ce-based CeX2M2 (X =
Cu, Ag, Au; M = Ge, Si) compounds, which are prototypes for exploring quantum
phase transitions and their interplay with unconventional superconductivity.


  We investigate fixed energy scattering from conical potentials having an
irregular cross-section. The incident wave can be any arbitrary non-trivial
Herglotz wave. We show that a large number of such local conical scatterers
scatter all incident waves, meaning that the far-field will always be non-zero.
In essence there are no incident waves for which these potentials would seem
transparent at any given energy. We show more specifically that there is a
large collection of star-shaped cones whose local geometries always produce a
scattered wave. In fact, except for a countable set, all cones from a family of
deformations between a circular and a star-shaped cone will always scatter any
non-trivial incident Herglotz wave. Our methods are based on the use of
spherical harmonics and a deformation argument. We also investigate the related
problem for sources. In particular if the support of the source is locally a
thin cone, with an arbitrary cross-section, then it will produce a non-zero
far-field.


  Speaker Verification (SV) is a task to verify the claimed identity of the
claimant using his/her voice sample. Though there exists an ample amount of
research in SV technologies, the development concerning a multilingual
conversation is limited. In a country like India, almost all the speakers are
polyglot in nature. Consequently, the development of a Multilingual SV (MSV)
system on the data collected in the Indian scenario is more challenging. With
this motivation, the Indic- Multilingual Speaker Verification (I-MSV) Challenge
2022 has been designed for understanding and comparing the state-of-the-art SV
techniques. For the challenge, approximately $100$ hours of data spoken by
$100$ speakers has been collected using $5$ different sensors in $13$ Indian
languages. The data is divided into development, training, and testing sets and
has been made publicly available for further research. The goal of this
challenge is to make the SV system robust to language and sensor variations
between enrollment and testing. In the challenge, participants were asked to
develop the SV system in two scenarios, viz. constrained and unconstrained. The
best system in the constrained and unconstrained scenario achieved a
performance of $2.12\%$ and $0.26\%$ in terms of Equal Error Rate (EER),
respectively.


  We implement double electromagnetically-induced transparency (double EIT) in
rubidium vapor, using a tripod-shaped energy level scheme consisting of
hyperfine and magnetic sublevels of the 5S1/2 to 5P1/2 transition. We show
experimentally that through the use of double EIT one can control the contrast
of transparency windows as well as group velocities of the two signal fields.
In particular, the group velocities can be equalized, which holds promise to
greatly enhance nonlinear optical interaction between these fields.


  Proxies are the swiss army knives of object adaptation. They introduce a
level of indirection to intercept select operations on a target object and
divert them as method calls to a handler. Proxies have many uses like
implementing access control, enforcing contracts, virtualizing resources.
  One important question in the design of a proxy API is whether a proxy object
should inherit the identity of its target. Apparently proxies should have their
own identity for security-related applications whereas other applications, in
particular contract systems, require transparent proxies that compare equal to
their target objects.
  We examine the issue with transparency in various use cases for proxies,
discuss different approaches to obtain transparency, and propose two designs
that require modest modifications in the JavaScript engine and cannot be
bypassed by the programmer.
  We implement our designs in the SpiderMonkey JavaScript interpreter and
bytecode compiler. Our evaluation shows that these modifications of have no
statistically significant impact on the benchmark performance of the JavaScript
engine. Furthermore, we demonstrate that contract systems based on wrappers
require transparent proxies to avoid interference with program execution in
realistic settings.


  Silver nanowires have great application potential in fields like flexible
electronic devices, solar cells and transparent electrodes. It is critical and
fundamental to study the thermal and electrical transport properties in a
single silver nanowire. In this work, the thermal and electrical transport in
an individual silver nanowire is characterized down to 35 K with the steady
state electro-thermal technique. The results indicate that, at room
temperature, the electrical resistivity increases by around 4 folds compared
from that of its bulk counterpart. After fitting the temperature dependent
electrical resistivity curves with the Bloch-Gr\"uneisen formula, the Debye
temperature (151 K) of the silver nanowire is found 36% lower than that (235 K)
of bulk silver, confirming strong phonon softening. The thermal conductivity is
reduced by 55% compared with that of its bulk counterpart at room temperature
and this reduction becomes larger as the temperature goes down. To explain the
opposite trends of thermal conductivity (\k{appa}) ~ temperature (T) of silver
nanowire and bulk silver, a unified thermal resistivity is used to elucidate
the electron scattering mechanism. A large residual unified thermal resistivity
for the silver nanowire is observed while that of the bulk silver is almost
zero. The same trend of variation against T indicates that the silver nanowire
and bulk silver share the same phonon-electron scattering mechanism.
Additionally, due to phonon-assisted electron energy transfer across the grain
boundaries, the Lorenz number of the silver nanowire is found much larger than
that of bulk silver and decreases with decreasing temperature.


  We consider the unitarity of D=9,10,11 conformal supersymmetry using the
recently established classification of the UIRs of the superalgebras
osp(1|2n,R).


  Let $R$ be a local ring and let ($x_1\biss x_r$) be part of a system of
parameters of a finitely generated $R$-module $M,$ where $r < \dim_R M$. We
will show that if ($y_1\biss y_r$) is part of a reducing system of parameters
of $M$ with $(y_1\biss y_r)M=(x_1\biss x_r)M$ then $(x_1\biss x_r)$ is already
reducing. Moreover, there is such a part of a reducing system of parameters of
$M$ iff for all primes $P\in \supp M \cap V_R(x_1\biss x_r)$ with $\dim_R R/P =
\dim_R M -r$ the localization $M_P$ of $M$ at $P$ is an $r$-dimensional \cm\
module over $R_P$. Furthermore, we will show that $M$ is a \cm module iff $y_d$
is a non zero divisor on $M/(y_1\biss y_{d-1})M$, where $(y_1\biss y_d)$ is a
reducing system of parameters of $M$ ($d := \dim_R M$).


  Chvatal, Roedl, Szemeredi and Trotter proved that the Ramsey numbers of
graphs of bounded maximum degree are linear in their order. In previous work,
we proved the same result for 3-uniform hypergraphs. Here we extend this result
to k-uniform hypergraphs, for any integer k > 3. As in the 3-uniform case, the
main new tool which we prove and use is an embedding lemma for k-uniform
hypergraphs of bounded maximum degree into suitable k-uniform `quasi-random'
hypergraphs.


  State selective protocols, like entanglement purification, lead to an
essentially non-linear quantum evolution, unusual in naturally occurring
quantum processes. Sensitivity to initial states in quantum systems, stemming
from such non-linear dynamics, is a promising perspective for applications.
Here we demonstrate that chaotic behaviour is a rather generic feature in state
selective protocols: exponential sensitivity can exist for all initial states
in an experimentally realisable optical scheme. Moreover, any complex rational
polynomial map, including the example of the Mandelbrot set, can be directly
realised. In state selective protocols, one needs an ensemble of initial
states, the size of which decreases with each iteration. We prove that
exponential sensitivity to initial states in any quantum system have to be
related to downsizing the initial ensemble also exponentially. Our results show
that magnifying initial differences of quantum states (a Schr\"odinger
microscope) is possible, however, there is a strict bound on the number of
copies needed.


  The performance of user-centric ultra-dense networks (UCUDNs) hinges on the
Service zone (Szone) radius, which is an elastic parameter that balances the
area spectral efficiency (ASE) and energy efficiency (EE) of the network.
Accurately determining the Szone radius requires the precise location of the
user equipment (UE) and data base stations (DBSs). Even a slight error in
reported positions of DBSs or UE will lead to an incorrect determination of
Szone radius and UE-DBS pairing, leading to degradation of the UE-DBS
communication link. To compensate for the positioning error impact and improve
the ASE and EE of the UCUDN, this work proposes a data-driven optimization and
error compensation (DD-OEC) framework. The framework comprises an additional
machine learning model that assesses the impact of residual errors and
regulates the erroneous datadriven optimization to output Szone radius,
transmit power, and DBS density values which improve network ASE and EE. The
performance of the framework is compared to a baseline scheme, which does not
employ the residual, and results demonstrate that the DD-OEC framework
outperforms the baseline, achieving up to a 23% improvement in performance.


  We report the results of 3D spectroscopic observations of Mrk 493 (NLS1
galaxy) with the integral-field spectrograph MPFS of the SAO RAS 6-m telescope.
The difference in the slope of the optical continuum emission intensity across
the nucleus part and an extensive continuum emission region} is detected. The
emission in lines (H$\alpha$, H$\beta$, [OIII], etc.) coincides with a
composite nuclear region: an AGN plus a circum-nuclear star-forming ring
observed in the HST UV/optical images. The [SII] emission region tends to be up
to 1kpc around the center. The H$\alpha$ and H$\beta$ could be decomposed into
three components (broad $\sim$ 2000 km/s. intermediate $\sim$ 700 km/s and
narrow $\sim$ 250 km/s). We found that width ($\sim$ 750 km/s) of the Fe II
lines correspond to the intermediate component, that may indicate a non-BLR
origin of the Fe II lines, or that a large fraction of the Fe II emission arise
in the outher parts of the BLR. The weak broad component detected in the
H$\alpha$, H$\beta$ and He$\lambda$4686 may come from the unresolved central
BLR, but also partly produced by violent starburst in the circum-nuclear ring.
Moreover, diagnostic diagrams clearly show presence of the HII regions (not a
Sy 1 nucleus) in the NLR of Mrk 493.


  Although 3D-aware GANs based on neural radiance fields have achieved
competitive performance, their applicability is still limited to objects or
scenes with the ground-truths or prediction models for clearly defined
canonical camera poses. To extend the scope of applicable datasets, we propose
a novel 3D-aware GAN optimization technique through contrastive learning with
implicit pose embeddings. To this end, we first revise the discriminator design
and remove dependency on ground-truth camera poses. Then, to capture complex
and challenging 3D scene structures more effectively, we make the discriminator
estimate a high-dimensional implicit pose embedding from a given image and
perform contrastive learning on the pose embedding. The proposed approach can
be employed for the dataset, where the canonical camera pose is ill-defined
because it does not look up or estimate camera poses. Experimental results show
that our algorithm outperforms existing methods by large margins on the
datasets with multiple object categories and inconsistent canonical camera
poses.


  We demonstrate the simultaneous magneto-optical trapping (MOT) of Rb and Sr
and examine the characteristic loss of Rb in the MOT due to photoionization by
the cooling laser for Sr. The photoionization cross section of Rb in the
$5P_{3/2}$ state at 461 nm is determined to be $1.4(1)\times10^{-17}$ cm$^2$.
It is important to consider this loss rate to realize a sufficiently large
number of trapped Rb atoms to achieve a quantum degenerate mixture of Rb and
Sr.


  Our societies are heterogeneous in many dimensions such as census, education,
religion, ethnic and cultural composition. The links between individuals - e.g.
by friendship, marriage or collaboration - are not evenly distributed, but
rather tend to be concentrated within the same group. This phenomenon, called
`imbreeding homophily', has been related to either (social) preference for
links with own-type individuals (`choice-based' homophily) or to the prevalence
of individuals of her same type in the choice set of an individual
(`opportunity-based' homophily). Choices determine the network of relations we
observe whereas opportunities pertain to the composition of the (unobservable)
social network individuals are embedded in and out of which their network of
relations is drawn. In this view, we propose a method that, in the presence of
multiple data, allows one to distinguish between opportunity and choice based
homophily. The main intuition is that, with unbiased opportunities, the effect
of choice-based homophily gets weaker and weaker as the size of the minority
shrinks, because individuals of the minority rarely meet and have the chance to
establish links together. The occurrence of homophily in the limit of very
small minorities is therefore an indicator of opportunity bias. We test this
idea across the dimensions of race and education on data on US marriages, and
across race on friendships in US schools.


  This paper evaluates the impact of the power extent on price in the
electricity market. The competitiveness extent of the electricity market during
specific times in a day is considered to achieve this. Then, the effect of
competitiveness extent on the forecasting precision of the daily power price is
assessed. A price forecasting model based on multi-layer perception via back
propagation with the Levenberg-Marquardt mechanism is used. The Residual Supply
Index (RSI) and other variables that affect prices are used as inputs to the
model to evaluate the market competitiveness. The results show that using
market power indices as inputs helps to increase forecasting accuracy. Thus,
the competitiveness extent of the market power in different daily time periods
is a notable variable in price formation. Moreover, market players cannot
ignore the explanatory power of market power in price forecasting. In this
research, the real data of the electricity market from 2013 is used and the
main source of data is the Grid Management Company in Iran.


  Energy disaggregation is the process of estimating the energy consumed by
individual electrical appliances given only a time series of the whole-home
power demand. Energy disaggregation researchers require datasets of the power
demand from individual appliances and the whole-home power demand. Multiple
such datasets have been released over the last few years but provide metadata
in a disparate array of formats including CSV files and plain-text README
files. At best, the lack of a standard metadata schema makes it unnecessarily
time-consuming to write software to process multiple datasets and, at worse,
the lack of a standard means that crucial information is simply absent from
some datasets. We propose a metadata schema for representing appliances,
meters, buildings, datasets, prior knowledge about appliances and appliance
models. The schema is relational and provides a simple but powerful inheritance
mechanism.


  A general method to mitigate the effect of errors in quantum circuits is
outlined. The method is developed in sight of characteristics that an ideal
method should possess and to ameliorate an existing method which only mitigates
state preparation and measurement errors. The method is tested on different IBM
Q quantum devices, using randomly generated circuits with up to four qubits. A
large majority of results show significant error mitigation.


  The properties of neutron stars are determined by the nature of the matter
that they contain. These properties can be constrained by measurements of the
star's size. We obtain stringent constraints on neutron-star radii by combining
multimessenger observations of the binary neutron-star merger GW170817 with
nuclear theory that best accounts for density-dependent uncertainties in the
equation of state. We construct equations of state constrained by chiral
effective field theory and marginalize over these using the gravitational-wave
observations. Combining this with the electromagnetic observations of the
merger remnant that imply the presence of a short-lived hyper-massive neutron
star, we find that the radius of a $1.4\,\rm{M}_\odot$ neutron star is
$R_{1.4\,\mathrm{M}_\odot} = 11.0^{+0.9}_{-0.6}~{\rm km}$ (90% credible
interval). Using this constraint, we show that neutron stars are unlikely to be
disrupted in neutron-star black-hole mergers; subsequently, such events will
not produce observable electromagnetic emission.


  There has been a long recognition that discrete features (n-gram features)
and neural network based features have complementary strengths for language
models (LMs). Improved performance can be obtained by model interpolation,
which is, however, a suboptimal two-step integration of discrete and neural
features. The trans-dimensional random field (TRF) framework has the potential
advantage of being able to flexibly integrate a richer set of features.
However, either discrete or neural features are used alone in previous TRF LMs.
This paper develops a mixed-feature TRF LM and demonstrates its advantage in
integrating discrete and neural features. Various LMs are trained over PTB and
Google one-billion-word datasets, and evaluated in N-best list rescoring
experiments for speech recognition. Among all single LMs (i.e. without model
interpolation), the mixed-feature TRF LMs perform the best, improving over both
discrete TRF LMs and neural TRF LMs alone, and also being significantly better
than LSTM LMs. Compared to interpolating two separately trained models with
discrete and neural features respectively, the performance of mixed-feature TRF
LMs matches the best interpolated model, and with simplified one-step training
process and reduced training time.


  The coupling parameter expansion in thermodynamic perturbation theory of
simple fluids is generalized to include the derivatives of bridge function. We
applied seventh order version of the theory to Square-Well (SW) and
Lennard-Jones (LJ) fluids using Sarkisov Bridge function. In both cases, the
theory reproduced the radial distribution functions obtained from integral
equation theory (IET) and simulations with good accuracy. Also, the method
worked inside the liquid-vapor coexistence region where the IETs are known to
fail. In the case of SW fluids, the use of Carnahan-Starling expression for
free energy density of Hard-Sphere reference system has improved the
liquid-vapor phase diagram (LVPD) over that obtained from IET. We also obtained
the surface tension of SW fluids of various ranges. Results of present theory
and simulations are in good agreement. In the case of LJ fluids, the equation
of state obtained from the present method matched with that obtained from IET
with negligible deviation. We also obtained LVPD of LJ fluid from virial and
energy routes and found that there is slight inconsistency between the two
routes. The applications lead to the following conclusions. In cases where
reference system properties are known accurately, the present method gives
results which are very much improved over those obtained from the IET with the
same bridge function. In cases where reference system data is not available,
the method serves as an alternative way of solving the Ornstein-Zernike
equation with a given closure relation with the advantage that solution can be
obtained throughout the phase diagram with a proper choice of the reference
system.


  Optimal symbol detection for multiple-input multiple-output (MIMO) systems is
known to be an NP-hard problem. Conventional heuristic algorithms are either
too complex to be practical or suffer from poor performance. Recently, several
approaches tried to address those challenges by implementing the detector as a
deep neural network. However, they either still achieve unsatisfying
performance on practical spatially correlated channels, or are computationally
demanding since they require retraining for each channel realization. In this
work, we address both issues by training an additional neural network (NN),
referred to as the hypernetwork, which takes as input the channel matrix and
generates the weights of the neural NN-based detector. Results show that the
proposed approach achieves near state-of-the-art performance without the need
for re-training.


  In its current state, the Internet does not provide end users with
transparency and control regarding on-path forwarding devices. In particular,
the lack of network device information reduces the trustworthiness of the
forwarding path and prevents end-user applications requiring specific router
capabilities from reaching their full potential. Moreover, the inability to
influence the traffic's forwarding path results in applications communicating
over undesired routes, while alternative paths with more desirable properties
remain unusable.
  In this work, we present FABRID, a system that enables applications to
forward traffic flexibly, potentially on multiple paths selected to comply with
user-defined preferences, where information about forwarding devices is exposed
and transparently attested by autonomous systems (ASes). The granularity of
this information is chosen by each AS individually, protecting them from
leaking sensitive network details, while the secrecy and authenticity of
preferences embedded within the users' packets are protected through efficient
cryptographic operations. We show the viability of FABRID by deploying it on a
global SCION network test bed, and we demonstrate high throughput on commodity
hardware.


  We introduce an analytical model to study the evolution towards equilibrium
in spatial games, with `memory-aware' agents, i.e., agents that accumulate
their payoff over time. In particular, we focus our attention on the spatial
Prisoner's Dilemma, as it constitutes an emblematic example of a game whose
Nash equilibrium is defection. Previous investigations showed that, under
opportune conditions, it is possible to reach, in the evolutionary Prisoner's
Dilemma, an equilibrium of cooperation. Notably, it seems that mechanisms like
motion may lead a population to become cooperative. In the proposed model, we
map agents to particles of a gas so that, on varying the system temperature,
they randomly move. In doing so, we are able to identify a relation between the
temperature and the final equilibrium of the population, explaining how it is
possible to break the classical Nash equilibrium in the spatial Prisoner's
Dilemma when considering agents able to increase their payoff over time.
Moreover, we introduce a formalism to study order-disorder phase transitions in
these dynamics. As result, we highlight that the proposed model allows to
explain analytically how a population, whose interactions are based on the
Prisoner's Dilemma, can reach an equilibrium far from the expected one; opening
also the way to define a direct link between evolutionary game theory and
statistical physics.


  Experimental and theoretical studies of nonlinear frequency combs in \chi^(3)
optical microresonators attracted tremendous research interest during the last
decade and resulted in prototypes of solitonbased steadily working devices.
Realization of similar combs owing to \chi^(2) optical nonlinearity promises
new breakthroughs and is a big scientific challenge. We analyze the main
obstacles for realization of the \chi^(2) frequency combs in high-Q
microresonators and propose two families of steadystate nonlinear solutions,
including soliton and periodic solutions, for such combs. Despite generic
periodicity of light fields inside microresonators, the nonlinear solutions can
be topologically different and relevant to periodic and antiperiodic boundary
conditions. The found particular solutions exist owing to a large difference in
the group velocities between the first and second harmonics, typical of
\chi^(2) microresonators, and to the presence of the pump. They have no
zero-pump counterparts relevant to conservative solitons. Stability issue for
the found comb solutions remains open and requires further numerical analysis.


  The effect of quark anomalous magnetic moment (AMM) to chiral restoration and
deconfinement phase transitions under magnetic fields is investigated in a
Pauli-Villars regularized PNJL model. A linear-in-$B$ term for quark anomalous
magnetic moment is introduced to the Lagrangian density of our model, and it
plays the role of inverse catalysis to the phase transitions. With fixed
magnetic field, the critical temperature decreases with quark AMM. When fixing
quark AMM, the critical temperature increases with magnetic field for a small
quark AMM, but decreases with magnetic field for a large quark AMM. The
critical temperature of chiral restoration and deconfinement phase transitions
is determined by the two competing factors, the catalysis effect of magnetic
field and inverse catalysis of quark anomalous magnetic moment.


  Bordered Floer homology associates to a parametrized oriented surface a
certain differential graded algebra. We study the properties of this algebra
under splittings of the surface. To the circle we associate a differential
graded 2-algebra, the nilCoxeter sequential 2-algebra, and to a surface with
connected boundary an algebra-module over this 2-algebra, such that a natural
gluing property is satisfied. Moreover, with a view toward the structure of a
potential Floer homology theory of 3-manifolds with codimension-two corners, we
present a decomposition theorem for the Floer complex of a planar grid diagram,
with respect to vertical and horizontal slicing.


  Gravitational wave observations of binary black hole mergers probe their
astrophysical origins via the binary spin, namely the spin magnitudes and
directions of each component black hole, together described by six degrees of
freedom. However, the emitted signals primarily depend on two effective spin
parameters that condense the spin degrees of freedom to those parallel and
those perpendicular to the orbital plane. Given this reduction in
dimensionality between the physically relevant problem and what is typically
measurable, we revisit the question of whether information about the component
spin magnitudes and directions can successfully be recovered via
gravitational-wave observations, or if we simply extrapolate information about
the distributions of effective spin parameters. To this end, we simulate three
astrophysical populations with the same underlying effective-spin distribution
but different spin magnitude and tilt distributions, on which we conduct full
individual-event and population-level parameter estimation. We find that
parameterized population models can indeed qualitatively distinguish between
populations with different spin magnitude and tilt distributions at current
sensitivity. However, it remains challenging to either accurately recover the
true distribution or to diagnose biases due to model misspecification. We
attribute the former to practical challenges of dealing with high-dimensional
posterior distributions, and the latter to the fact that each individual event
carries very little information about the full six spin degrees of freedom.


  We prove that for sub-extremal axisymmetric and stationary black holes with
arbitrary surrounding matter the inequality $8\pi|J|<A$ holds, where $J$ is the
angular momentum and $A$ the horizon area of the black hole.


  A new model validation and performance assessment tool is introduced, the
sliding threshold of observation for numeric evaluation (STONE) curve. It is
based on the relative operating characteristic (ROC) curve technique, but
instead of sorting all observations in a categorical classification, the STONE
tool uses the continuous nature of the observations. Rather than defining
events in the observations and then sliding the threshold only in the
classifier (model) data set, the threshold is changed simultaneously for both
the observational and model values, with the same threshold value for both data
and model. This is only possible if the observations are continuous and the
model output is in the same units and scale as the observations, that is, the
model is trying to exactly reproduce the data. The STONE curve has several
similarities with the ROC curve, plotting probability of detection against
probability of false detection, ranging from the (1,1) corner for low
thresholds to the (0,0) corner for high thresholds, and values above the
zero-intercept unity-slope line indicating better than random predictive
ability. The main difference is that the STONE curve can be nonmonotonic,
doubling back in both the x and y directions. These ripples reveal asymmetries
in the data-model value pairs. This new technique is applied to modeling output
of a common geomagnetic activity index as well as energetic electron fluxes in
the Earth's inner magnetosphere. It is not limited to space physics
applications but can be used for any scientific or engineering field where
numerical models are used to reproduce observations.


  This paper proposes a joint analysis of variations of global sea-level
pressure and of Earth's rotation (RP), expressed as the coordinates of the
rotation pole and length of day. Sea-Level-Pressure (SLP) extracted components
are a weak trend, eleven quasi-periodic or periodic components ($\sim$130, 90,
50, 22, 15, 4, 1.8 yr), an annual cycle and its first three harmonics. These
periods are characteristic of the space-time evolution of the Earth's rotation
axis and are present in many characteristic features of solar and terrestrial
physics. We focus mainly on the annual and to a lesser extent semi-annual
components. Maps of the first three components of SLP (that together comprise
more than 85% of the data variance) reveal interesting symmetries. The trend is
very stable and forms a triskel structure that can be modeled as Taylor-Couette
flow of mode 3. The annual component is characterized by a large negative
anomaly extending over Eurasia in the NH Summer (and the opposite in the NH
Winter) and three large positive anomalies over Australia and the southern tips
of South America and South Africa in the SH Spring (and the opposite in the SH
Autumn) forming a triskel. The semi-annual component is characterized by three
positive anomalies (an irregular triskel) in the NH Spring and Autumn (and the
opposite in the NH Summer and Winter), and in the SH Spring and Autumn by a
strong stable pattern consisting of three large negative anomalies forming a
clear triskel within the 40$^{\circ}$-60$^{\circ}$ annulus formed by the
southern oceans. A large positive anomaly centered over Antarctica, with its
maximum displaced toward Australia, and a smaller one centered over Southern
Africa complement the pattern.


  One of the most neglected sources of energy loss is streetlights which
generate too much light in areas where it is not required. Energy waste has
enormous economic and environmental effects. In addition, due to the
conventional manual nature of the operation, streetlights are frequently seen
being turned ON during the day and OFF in the evening, which is regrettable
even in the twenty-first century. These issues require automated streetlight
control in order to be resolved. This study aims to develop a novel streetlight
controlling method by combining a smart transport monitoring system powered by
computer vision technology with a closed circuit television (CCTV) camera that
allows the light-emitting diode (LED) streetlight to automatically light up
with the appropriate brightness by detecting the presence of pedestrians or
vehicles and dimming the streetlight in their absence using semantic image
segmentation from the CCTV video streaming. Consequently, our model
distinguishes daylight and nighttime, which made it feasible to automate the
process of turning the streetlight 'ON' and 'OFF' to save energy consumption
costs. According to the aforementioned approach, geolocation sensor data could
be utilized to make more informed streetlight management decisions. To complete
the tasks, we consider training the U-net model with ResNet-34 as its backbone.
The validity of the models is guaranteed with the use of assessment matrices.
The suggested concept is straightforward, economical, energy-efficient,
long-lasting, and more resilient than conventional alternatives.


  In this paper we make an attempt to combine the two kinds of data from the
Swift-XRT instrument (windowed timing and photon counting modes) and the from
BAT. A thorough desription of the applied procedure will be given. We apply
various binning techniques to the different data: Bayes blocks, exponential
binning and signal-to-noise type of binning. We present a handful of
lightcurves and some possible applications.


  This paper presents a randomization-based framework for estimating causal
effects under interference between units, motivated by challenges that arise in
analyzing experiments on social networks. The framework integrates three
components: (i) an experimental design that defines the probability
distribution of treatment assignments, (ii) a mapping that relates experimental
treatment assignments to exposures received by units in the experiment, and
(iii) estimands that make use of the experiment to answer questions of
substantive interest. We develop the case of estimating average unit-level
causal effects from a randomized experiment with interference of arbitrary but
known form. The resulting estimators are based on inverse probability
weighting. We provide randomization-based variance estimators that account for
the complex clustering that can occur when interference is present. We also
establish consistency and asymptotic normality under local dependence
assumptions. We discuss refinements including covariate-adjusted effect
estimators and ratio estimation. We evaluate empirical performance in realistic
settings with a naturalistic simulation using social network data from American
schools. We then present results from a field experiment on the spread of
anti-conflict norms and behavior among school students.


  The role of tidal shear in the formation of structure in the Universe is
explored. To illustrate the possible and sometimes dramatic impact of tidal
fields we focus on the evolution of voids. We firstly analyze the role of tidal
fields both in the highly symmetric situation of an initially homogeneous
ellipsoidal underdensity embedded in an artificially imposed tidal field. In
addition, we present selfconsistent case studies consisting of N-body
simulations that start from constrained Gaussian initial conditions in which
the matter distribution is appropriately sculpted to yield an a priori
specified tidal field. We conclude that voids may indeed be induced to
collapse. Also, we present evidence for the strong relation between tidal
fields and filaments in the mass distribution.


  Until recently, the only known method of finding the roots of polynomials
over prime power rings, other than fields, was brute force. One reason for this
is the lack of a division algorithm, obstructing the use of greatest common
divisors. Fix a prime $p \in \mathbb{Z}$ and $f \in ( \mathbb{Z}/p^n \mathbb{Z}
) [x]$ any nonzero polynomial of degree $d$ whose coefficients are not all
divisible by $p$. For the case $n=2$, we prove a new efficient algorithm to
count the roots of $f$ in $\mathbb{Z}/p^2\mathbb{Z}$ within time polynomial in
$(d+\operatorname{size}(f)+\log{p})$, and record a concise formula for the
number of roots, formulated by Cheng, Gao, Rojas, and Wan.


  We present experimental results using a passive whole-body control approach
for quadruped robots that achieves dynamic locomotion while compliantly
balancing the robot's trunk. We formulate the motion tracking as a Quadratic
Program (QP) that takes into account the full robot rigid body dynamics, the
actuation limits, the joint limits and the contact interaction. We analyze the
controller's robustness against inaccurate friction coefficient estimates and
unstable footholds, as well as its capability to redistribute the load as a
consequence of enforcing actuation limits. Additionally, we present practical
implementation details gained from the experience with the real platform.
Extensive experimental trials on the 90 kg Hydraulically actuated Quadruped
(HyQ) robot validate the capabilities of this controller under various terrain
conditions and gaits. The proposed approach is superior for accurate execution
of highly dynamic motions with respect to the current state of the art.


  We study magnetic behaviour of the Yb$^{3+}$ ions on a frustrated pyrochlore
lattice in the spinel {\CYS}. The crystal-electric field parameters deduced
from high-energy inelastic neutron scattering reveal well-isolated ytterbium
ground state doublet with a weakly Ising character. Magnetic order studied by
powder neutron diffraction evolves from the $XY$-type antiferromagnetic
$\Gamma_5$ state to a splayed ice-like ferromagnet (both with k=0) in applied
magnetic field with $B_c$=3 T. Low-energy inelastic neutron scattering
identifies weakly dispersive magnetic bands around 0.72 meV starting at
$\mid\bf{Q}\mid$ = 1.1 \AA$^{-1}$~ at zero field, which diminish with field and
vanish above 3 T. We explain the observed magnetic behaviour in framework of
the nearest-neighbour anisotropic exchange model for effective $S=1/2$ Kramers
doublets on the pyrochlore lattice. The estimated exchanges position the {\CYS}
spinel close to the phase boundary between the $\Gamma_5$ and splayed
ferromagnet states, similar to the Yb-pyrochlores suggesting an important role
of the competition between these phases.


  Models of epidemics over networks have become popular, as they describe the
impact of individual behavior on infection spread. However, they come with high
computational complexity, which constitutes a problem in case large-scale
scenarios are considered. This paper presents a discrete-time multi-agent SIR
(Susceptible, Infected, Recovered) model that extends known results in
literature. Based on that, using the novel notion of Contagion Graph, it
proposes a graphbased method derived from Dijkstra's algorithm that allows to
decrease the computational complexity of a simulation. The Contagion Graph can
be also employed as an approximation scheme describing the "mean behavior" of
an epidemic over a network and requiring low computational power. Theoretical
findings are confirmed by randomized large-scale simulation.


  We present a mechanism for thermalizing a moving particle by microscopic
deterministic scattering. As an example, we consider the periodic Lorentz gas.
We modify the collision rules by including energy transfer between particle and
scatterer such that the scatterer mimics a thermal reservoir with arbitrarily
many degrees of freedom. The complete system is deterministic, time-reversible,
and provides a microcanonical density in equilibrium. In the limit of the disk
representing infinitely many degrees of freedom and by applying an electric
field the system goes into a nonequilibrium steady state.


  It is argued that the presence of a nonanalytic term in the effective
potential of the Ginzburg-Landau model is immaterial as far as the order of the
superconductor-normal phase transition is concerned. To achieve agreement with
the renormalization group, the effective potential has to be extended to
include derivative terms, which provide the theory with a low momentum scale
which can be varied to probe the (possible) fixed point.


  Single crystals of intermetallic Re$_3$Ge$_7$ were grown and characterized by
measuring magnetization, electrical resistivity, Hall coefficient, and specific
heat. Magnetization measurements show the material is weakly diamagnetic. A
phase transition is indicated by a kink in magnetic susceptibility at $T_{c} =
58.5$K and is confirmed by a $\lambda$-like anomaly in specific heat. In
zero-field, the temperature dependence of electrical resistivity $\rho(T)$
follows a typical metallic behavior above $T_c$ and sharply increases below
$T_c$, showing a metal-to-insulator-like transition. When a magnetic field is
applied, strong effects on the transport properties are observed. The
temperature dependence of magnetoresistivity $\Delta\rho$ = $\rho (T, H)$ -
$\rho (T, H=0)$ develops a maximum around 30 K, deviating from ordinary
metallic behavior. Analysis of the Hall coefficient measurements indicates that
the carrier density is 0.04 per formula unit at 300 K and drops by two orders
of magnitude below $T_c$. The effective mass of charge carriers is inferred
from the analysis of the Shubnikov-de Haas quantum oscillations to be close to
the bare electron mass.


  The World Space Observatory - Ultraviolet (WSO-UV) space telescope is
equipped with high dispersion (55,000) spectrographs working in the 1150-3100
{\AA} spectral range. To evaluate the impact of the design on the scientific
objectives of the mission, a simulation software tool has been developed. This
simulator builds on the development made for the PLATO space mission, and it is
designed to generate synthetic time-series of images by including models of all
important noise sources. In this article, we describe its design and
performance. Moreover, its application to the detectability of important
spectral features for star formation and exoplanetary research is addressed.


  We investigate scenarios in which a charged, long-lived scalar particle
decouples from the primordial plasma in the Early Universe. We compute the
number density at time of freeze-out considering both the cases of abelian and
non-abelian interactions and including the effect of Sommerfeld enhancement at
low initial velocity. We also discuss as extreme case the maximal cross section
that fulfils the unitarity bound. We then compare these number densities to the
exotic nuclei searches for stable relics and to the BBN bounds on unstable
relics and draw conclusions for the cases of a stau or stop NLSP in
supersymmetric models with a gravitino or axino LSP.


  We study the dynamics of up to two Rydberg excitations and the correlation
growth in a chain of atoms coupled to a photonic crystal waveguide. In this
setup, an excitation can hop from one atom to another via exponentially
decaying exchange interactions mediated by the waveguide. An initially
localized excitation undergoes a continuous-time quantum walk for short-range
hopping, and for long-range, it experiences quasi-localization. Besides that,
the inverse participation ratio reveals a super-ballistic diffusion of the
excitation in short times, whereas, at a long time, it becomes ballistic. For
two initially localized excitations, intriguing, and complex dynamical
scenarios emerge for different initial separations due to the competition
between the Rydberg-Rydberg and exchange interactions. In particular, the
two-point correlation reveals a light-cone behavior even for sufficiently
long-range exchange interactions. Additionally, we characterize the growth of
bipartite entanglement entropy, which exhibits a global bound if only one
excitation is present in the dynamics. Finally, we analyze the effect of
imperfections due to spontaneous emission from the Rydberg state into photons
outside the waveguide and show that all physical phenomena we predict are well
within experimental reach.


  Hippocampal dentate granule cells are among the few neuronal cell types
generated throughout adult life in mammals. In the normal brain, new granule
cells are generated from progenitors in the subgranular zone and integrate in a
typical fashion. During the development of epilepsy, granule cell integration
is profoundly altered. The new cells migrate to ectopic locations and develop
misoriented basal dendrites. Although it has been established that these
abnormal cells are newly generated, it is not known whether they arise
ubiquitously throughout the progenitor cell pool or are derived from a smaller
number of bad actor progenitors. To explore this question, we conducted a
clonal analysis study in mice expressing the Brainbow fluorescent protein
reporter construct in dentate granule cell progenitors. Mice were examined 2
months after pilocarpine-induced status epilepticus, a treatment that leads to
the development of epilepsy. Brain sections were rendered translucent so that
entire hippocampi could be reconstructed and all fluorescently labeled cells
identified. Our findings reveal that a small number of progenitors produce the
majority of ectopic cells following status epilepticus, indicating that either
the affected progenitors or their local microenvironments have become
pathological. By contrast, granule cells with basal dendrites were equally
distributed among clonal groups. This indicates that these progenitors can
produce normal cells and suggests that global factors sporadically disrupt the
dendritic development of some new cells. Together, these findings strongly
predict that distinct mechanisms regulate different aspects


  We introduce a class of discrete random walk model driven by global memory
effects. At any time the right-left transitions depend on the whole previous
history of the walker, being defined by an urn-like memory mechanism. The
characteristic function is calculated in an exact way, which allows us to
demonstrate that the ensemble of realizations is ballistic. Asymptotically each
realization is equivalent to that of a biased Markovian diffusion process with
transition rates that strongly differs from one trajectory to another. Using
this "inhomogeneous diffusion" feature the ergodic properties of the dynamics
are analytically studied through the time-averaged moments. In the long time
regime they becomes random objects. While their mean values recover the
corresponding ensemble averages, departure between time and ensemble averages
is explicitly shown through their probability densities. For the density of the
second time-averaged moment an ergodic limit and the limit of infinite lag
times do not commutate. All these effects are induced by the memory effects.


  In this paper we tried to condense the determinant of n square matrix to the
determinant of (n - 1) square matrix with the mathematical proof.


  A set $A$ of integers is called total if there is an algorithm which, given
an enumeration of $A$, enumerates the complement of $A$, and called cototal if
there is an algorithm which, given an enumeration of the complement of $A$,
enumerates $A$. Many variants of totality and cototality have been studied in
computability theory. In this note, by an effective forcing construction with
strongly infinite dimensional Cantor manifolds, which can be viewed as an
effectivization of Zapletal's "half-Cohen" forcing (i.e., the forcing with
Henderson compacta), we construct a set of integers whose enumeration degree is
cototal, almost total, but neither cylinder-cototal nor telograph-cototal.


  Several differential equations usually appearing in mathematical physics are
solved through a power series expansion, which reduces in solving difference
equations. In this paper a probability problem is presented whose solution
follows a completely reversed but systematic approach. Hence, this work is
about illustrating how complex probability problems could be tackled with the
more powerful techniques of a better studied and well understood field, that of
differential equations. The problem is defined as follows: Inside a box
containing r red and w white balls random removals occur. The balls are removed
successively according to the three following rules. Rule I: If a white ball is
chosen it is immediately discarded. If a red ball is chosen, it is placed back
into the box and a new ball is randomly chosen. The second ball is then removed
irrespective of the color. Rule II: Once one ball is removed, the game
continues from Rule I. Rule III: The game ends once all the red balls are
removed. The question posed is the determination of the probability that k
white balls remain where k = 0, 1, 2, ..., w. Ending the game once all the
white balls are removed, a second question is the determination of the
probability that k red balls remain where k = 0, 1, 2, ..., r. While inductive
solutions are possible, the current approach demonstrates a different and
algorithmic route. In particular, the law of total probability yields a
recursion that is transformed into a linear inhomogeneous 2D PDE, with suitable
boundary conditions. The PDE solutions, which are found analytically, provide
the generating functionals of the required probabilities as a function of r, w
and k. Using the functionals, the probability formulas for any r, w and k are
finally obtained in a closed form. Reproducing existing results of the
literature this method is quite generic and adaptable to a large class of
problems.


  Recently, Aizenman and Warzel discovered a mechanism for the appearance of
absolutely continuous spectrum for random Schroedinger operators on the Bethe
lattice through rare resonances (resonant delocalization). We extend their
analysis to operators with matrix-valued random potentials drawn from ensembles
such as the Gaussian Orthogonal Ensemble. These operators can be viewed as
random operators on the Bethe strip, a graph (lattice) with loops.


  We put forward an adaptive alpha (Type I Error) that decreases as the
information grows, for hypothesis tests in which nested linear models are
compared. A less elaborate adaptation was already presented in \citet{PP2014}
for comparing general i.i.d. models. In this article we present refined
versions to compare nested linear models. This calibration may be interpreted
as a Bayes-non-Bayes compromise, of a simple translations of a Bayes Factor on
frequentist terms that leads to statistical consistency, and most importantly,
it is a step towards statistics that promotes replicable scientific findings.


  We introduce a novel machine learning strategy, kernel addition Gaussian
process regression (KA-GPR), in molecular-orbital-based machine learning
(MOB-ML) to learn the total correlation energies of general electronic
structure theories for closed- and open-shell systems by introducing a machine
learning strategy. The learning efficiency of MOB-ML (KA-GPR) is the same as
the original MOB-ML method for the smallest criegee molecule, which is a
closed-shell molecule with multi-reference characters. In addition, the
prediction accuracies of different small free radicals could reach the chemical
accuracy of 1 kcal/mol by training on one example structure. Accurate potential
energy surfaces for the H10 chain (closed-shell) and water OH bond dissociation
(open-shell) could also be generated by MOB-ML (KA-GPR). To explore the breadth
of chemical systems that KA-GPR can describe, we further apply MOB-ML to
accurately predict the large benchmark datasets for closed- (QM9, QM7b-T,
GDB-13-T) and open-shell (QMSpin) molecules.


  Enforcing distributions of latent variables in neural networks is an active
subject. It is vital in all kinds of generative models, where we want to be
able to interpolate between points in the latent space, or sample from it.
Modern generative AutoEncoders (AE) like WAE, SWAE, CWAE add a regularizer to
the standard (deterministic) AE, which allows to enforce Gaussian distribution
in the latent space. Enforcing different distributions, especially
topologically nontrivial, might bring some new interesting possibilities, but
this subject seems unexplored so far.
  This article proposes a new approach to enforce uniform distribution on
d-dimensional torus. We introduce a circular spring loss, which enforces
minibatch points to be equally spaced and satisfy cyclic boundary conditions.
  As example of application we propose multiple-path morphing. Minimal distance
geodesic between two points in uniform distribution on latent space of angles
becomes a line, however, torus topology allows us to choose such lines in
alternative ways, going through different edges of $[-\pi,\pi]^d$.
  Further applications to explore can be for example trying to learn real-life
topologically nontrivial spaces of features, like rotations to automatically
recognize 2D rotation of an object in picture by training on relative angles,
or even 3D rotations by additionally using spherical features - this way
morphing should be close to object rotation.


  By following the spirit of arXiv:1003.5665, we define a new Tolman
temperature of Kodama observer directly related to its acceleration. We give a
generalized integral form of thermodynamics relation on virtual sphere of
constant $r$ in non-static spherical symmetric spacetimes. This relation
contains work term contributed by `redshift work density', `pressure density'
and `gravitational work density'. We illustrate it in RN black hole,
Dilaton-Maxwell-Einstein black hole and Vaidya black hole. We argue that the
co-moving observers are not physically related to Kodama observers in FRW
universe unless in the vacuum case. We also find that a generalized
differential form of first law is difficult to be well defined, and it would
not give more information than the integral form.


  FTTO means Fiber To The Office, in reference to FTTH (Fibre To The Home),
deployed in France for individuals. The principle of FTTO is to cable a
building totally in fibre optic, to remove as much copper cabling as possible
and install microswitches in each office (duct or adjacent), as near the
machines as possible. Users are still connected with standard RJ45 copper
wiring. Through questions and answers, we will highlight the reasons why FFTO
is a controlled and future-oriented technology.Over the last six years, several
building projects within the perimeter of Higher Education and Research have
chosen this technology and have seen or will see the light of day. Depending on
the project, different topologies and technologies are possible. What is the
feedback after these years? Is the result as expected? How is the solution
experienced on a day-to-day basis? What security, how is a large switch
assembly configured and maintained, what high availability is possible? How is
Wi-Fi, IP telephony and all PoE devices integrated? Does FTTO contribute to
eco-consumption? How can a FTTO call for tender be set up for a project, what
are the essential elements to be included and what are the errors to be avoided
at all costs? In the future, what is the life expectancy for its infrastructure
and what speeds can be envisaged? The RESINFO FTTO Group is working to provide
clear answers to all these questions and to share its experience with the
community.


  We present far-ultraviolet (far-UV) images of the rich galaxy cluster
ZwCl1358.1+6245, taken with the Space Telescope Imaging Spectrograph on board
the Hubble Space Telescope (HST). When combined with archival HST observations,
our data provide a measurement of the UV-to-optical flux ratio in 8 early-type
galaxies at z=0.33. Because the UV flux originates in a population of evolved,
hot, horizontal branch (HB) stars, this ratio is potentially one of the most
sensitive tracers of age in old populations -- it is expected to fade rapidly
with lookback time. We find that the UV emission in these galaxies, at a
lookback time of 3.9 Gyr, is significantly weaker than it is in the current
epoch, yet similar to that in galaxies at a lookback time of 5.6 Gyr. Taken at
face value, these measurements imply different formation epochs for the massive
ellipticals in these clusters, but an alternative explanation is a "floor" in
the UV emission due to a dispersion in the parameters that govern HB
morphology.


  Merger-remnant galaxies with kpc-scale separation dual active galactic nuclei
(AGNs) should be widespread as a consequence of galaxy mergers and triggered
gas accretion onto supermassive black holes, yet very few dual AGNs have been
observed. Galaxies with double-peaked narrow AGN emission lines in the Sloan
Digital Sky Survey are plausible dual AGN candidates, but their double-peaked
profiles could also be the result of gas kinematics or AGN-driven outflows and
jets on small or large scales. To help distinguish between these scenarios, we
have obtained spatial profiles of the AGN emission via follow-up long-slit
spectroscopy of 81 double-peaked narrow-line AGNs in SDSS at 0.03 < z < 0.36
using Lick, Palomar, and MMT Observatories. We find that all 81 systems exhibit
double AGN emission components with ~kpc projected spatial separations on the
sky, which suggests that they are produced by kpc-scale dual AGNs or kpc-scale
outflows, jets, or rotating gaseous disks. In addition, we find that the
subsample (58%) of the objects with spatially compact emission components may
be preferentially produced by dual AGNs, while the subsample (42%) with
spatially extended emission components may be preferentially produced by AGN
outflows. We also find that for 32% of the sample the two AGN emission
components are preferentially aligned with the host galaxy major axis, as
expected for dual AGNs orbiting in the host galaxy potential. Our results both
narrow the list of possible physical mechanisms producing the double AGN
components, and suggest several observational criteria for selecting the most
promising dual AGN candidates from the full sample of double-peaked narrow-line
AGNs. Using these criteria, we determine the 17 most compelling dual AGN
candidates in our sample.


  We report on the source Gaia 17bpi and identify it as a new, ongoing FU Ori
type outburst, associated with a young stellar object. The optical lightcurve
from Gaia exhibited a 3.5 mag rise with the source appearing to plateau in
mid/late 2018. Mid-infrared observations from NEOWISE also show a $>$3 mag rise
that occurred in two stages, with the second one coincident with the optical
brightening, and the first one preceding the optical brightening by $\sim$1.5
years. We model the outburst as having started between October and December of
2014. This wavelength-dependent aspect of young star accretion-driven outbursts
has never been documented before. Both the mid-infrared and the optical colors
of the object become bluer as the outburst proceeds. Optical spectroscopic
characteristics in the outburst phase include: a GK-type absorption spectrum,
strong wind/outflow in e.g. Mgb, NaD, H$\alpha$, KI, OI, and CaII profiles, and
detection of LiI 6707 \AA. The infrared spectrum in the outburst phase is
similar to that of an M-type spectrum, notably exhibiting prominent $H_2O$ and
$^{12}$CO (2-0) bandhead absorption in the K-band, and likely HeI wind in the
Y-band. The new FU Ori source Gaia 17bpi is associated with a little-studied
dark cloud in the galactic plane, located at a distance of 1.27 kpc.


  In this paper, uniform versions of index for uniform spaces equipped with
free involutions are introduced. They are mainly based on B-index defined and
studied by C.-T. Yang in 1955, index studied by Conner and Floyd in 1960 and
further development well collected by Matou$\check{s}$ek in his book on using
the Borsuk-Ulam theorem in 2003. Examples of uniform spaces with finite B-index
but infinite uniform version of index are given. It is also seen that for a
uniform space $X$ with a free involution $T$, a dense $T$-invariant subspace is
capable of determining the uniform version of index of $(X,T)$. In the end, the
concept of coloring is carried over to uniform set up and, to a certain extent,
connection between uniform versions of coloring and uniform versions of index
is also established.


  We predict a huge interference effect contributing to the conductance through
large ultra-clean quantum dots of chaotic shape. When a double-dot structure is
made such that the dots are the mirror-image of each other, constructive
interference can make a tunnel barrier located on the symmetry axis effectively
transparent. We show (via theoretical analysis and numerical simulation) that
this effect can be orders of magnitude larger than the well-known universal
conductance fluctuations and weak-localization (both less than a conductance
quantum). A small magnetic field destroys the effect, massively reducing the
double-dot conductance; thus a magnetic field detector is obtained, with a
similar sensitivity to a SQUID, but requiring no superconductors.


  In this paper we present a study about minima among random variables, about
the context of voting theory, and about paradoxes related with such topics. In
the field of reliability theory, the term load-sharing model is commonly used
to designate a special type of multivariate survival models. We demonstrate the
effectiveness that such dependence models can have also in some other fields,
such as those of interest here. Several important, and by now classic, papers
have been devoted to single out and to prove general conclusions in the field
of voting theory. We reformulate and achieve such conclusions by developing a
method of proof, alternative to the existing ones, and completely probabilistic
in nature. As main features of this method, we focus attention on ranking
schemes associated to m-tuples of non-negative random variables and suitably
single out a special subclass of load-sharing models. Then we show that all
possible ranking schemes can be conveniently obtained by only considering such
a special family of survival models. This result leads to some new insight
about the construction of voting situations which give rise to all possible
types of voting paradoxes. Our method and related implications will be also
illustrated by means of some examples and informative remarks.