  Training a generative adversarial network (GAN) with limited data has been a
challenging task. A feasible solution is to start with a GAN well-trained on a
large scale source domain and adapt it to the target domain with a few samples,
termed as few shot generative model adaption. However, existing methods are
prone to model overfitting and collapse in extremely few shot setting (less
than 10). To solve this problem, we propose a relaxed spatial structural
alignment method to calibrate the target generative models during the adaption.
We design a cross-domain spatial structural consistency loss comprising the
self-correlation and disturbance correlation consistency loss. It helps align
the spatial structural information between the synthesis image pairs of the
source and target domains. To relax the cross-domain alignment, we compress the
original latent space of generative models to a subspace. Image pairs generated
from the subspace are pulled closer. Qualitative and quantitative experiments
show that our method consistently surpasses the state-of-the-art methods in few
shot setting.


  When a surface acoustic wave (SAW) is coupled piezoelectrically to a two
dimensional electron gas (2DEG), a velocity shift and attenuation of the SAW
are induced that reflect the conductivity of the 2DEG. This paper considers the
case of a AlGaAs heterostructure with a 2DEG a distance $d$ from a (100)
surface of the crystal where the SAWs are propagated in the [011] direction at
wavevector $q$. It is found that the velocity shift $\Delta v_s$ and the
attenuation coefficient $\kappa$ satisfy the well known equation $(\Delta
v_s/v_s) - (i \kappa/q) = (\alpha^2/2)/\left(1 + \frac{i \sigma_{xx}(q,\omega)}
{\sigma_m}\right)$ where $\sigma_{xx}(q,\omega)$ is the complex conductivity at
wavevector $q$ and frequency $\omega = v_s q$ with $v_s$ the velocity of the
SAW. The coefficients $\alpha$ and $\sigma_m$ are calculated and it is found
that $\alpha$ has a nontrivial dependence on the product $qd$.


  This paper provides upper and lower bounds on the kissing number of congruent
radius $r > 0$ spheres in hyperbolic $\mathbb{H}^n$ and spherical
$\mathbb{S}^n$ spaces, for $n\geq 2$. For that purpose, the kissing number is
replaced by the kissing function $\kappa_H(n, r)$, resp. $\kappa_S(n, r)$,
which depends on the dimension $n$ and the radius $r$. After we obtain some
theoretical upper and lower bounds for $\kappa_H(n, r)$, we study their
asymptotic behaviour and show, in particular, that $\kappa_H(n,r) \sim (n-1)
\cdot d_{n-1} \cdot B(\frac{n-1}{2}, \frac{1}{2}) \cdot e^{(n-1) r}$, where
$d_n$ is the sphere packing density in $\mathbb{R}^n$, and $B$ is the
beta-function. Then we produce numeric upper bounds by solving a suitable
semidefinite program, as well as lower bounds coming from concrete spherical
codes. A similar approach allows us to locate the values of $\kappa_S(n, r)$,
for $n= 3,\, 4$, over subintervals in $[0, \pi]$ with relatively high accuracy.


  Handwritten signatures are biometric traits at the center of debate in the
scientific community. Over the last 40 years, the interest in signature studies
has grown steadily, having as its main reference the application of automatic
signature verification, as previously published reviews in 1989, 2000, and 2008
bear witness. Ever since, and over the last 10 years, the application of
handwritten signature technology has strongly evolved, and much research has
focused on the possibility of applying systems based on handwritten signature
analysis and processing to a multitude of new fields. After several years of
haphazard growth of this research area, it is time to assess its current
developments for their applicability in order to draw a structured way forward.
This perspective reports a systematic review of the last 10 years of the
literature on handwritten signatures with respect to the new scenario, focusing
on the most promising domains of research and trying to elicit possible future
research directions in this subject.


  In this work we study the effects of the electromagnetic coupling in natural
inflation in a systematic manner using the Schwinger-Keldysh formalism. The
corresponding influence functional is evaluated to one-loop level. It can be
interpreted as due to a single stochastic force. The equation of motion of the
inflaton field is therefore given in the form of a Langevin equation. Lastly,
the two-point and the three-point correlation functions of the inflaton field
are worked out. They are related to the power spectrum and the nongaussianity
of the inflaton field, respectively.


  Consider a data set collected by (individuals-features) pairs in different
times. It can be represented as a tensor of three dimensions (Individuals,
features and times). The tensor biclustering problem computes a subset of
individuals and a subset of features whose signal trajectories over time lie in
a low-dimensional subspace, modeling similarity among the signal trajectories
while allowing different scalings across different individuals or different
features. This approach are based on spectral decomposition in order to build
the desired biclusters. We evaluate the quality of the results from each
algorithms with both synthetic and real data set.


  Motivated by the problem of deformation quantization we introduce and study
directed graph complexes with oriented loops and wheels. We develop some
technique for computing cohomology of such graph complexes and apply it to
several concrete examples such as wheeled completion of the operad of strongly
homotopy Lie algebras and the wheeled completion of the dg prop of Poisson
structures. We prove also a deformation quantization theorem of wheeled Poisson
structures on arbitrary formal graded manifolds.


  Real filaments are not perfectly homogeneous. Most of them have various
materials composition and shapes making their stiffnesses not constant along
the arclength. We investigate the existence of circular and helical equilibrium
solutions of an intrinsically straight rod with varying bending and twisting
stiffnesses, within the framework of the Kirchhoff model. The planar ring
equilibrium solution only exists for a rod with a given form of variation of
the bending stiffness. We show that the well known circular helix is not an
equilibrium solution of the static Kirchhoff equations for a rod with non
constant bending stiffness. Our results may provide an explanation for the
variation of the curvature seen in small closed DNAs immersed in a solution
containing Zn^{2+}, and in the DNA wrapped around a nucleosome.


  We performed a numerical study of the efficiency of mixing by alternating
horizontal and vertical shear ``wedge'' flows on the two-dimensional torus. Our
results suggest that except in cases where each individual flow is applied for
only a short time, these flows produce exponentially fast mixing. The observed
mixing rates are higher when the individual flow times are shorter (but not too
short), and randomizing either the flow times or phase shifts of the flows does
not appear to enhance mixing (again when the flow times are not too short). In
fact, the latter surprisingly seems to inhibit it slightly.


  We develop a convergence analysis of a multi-level algorithm combining higher
order quasi-Monte Carlo (QMC) quadratures with general Petrov-Galerkin
discretizations of countably affine parametric operator equations of elliptic
and parabolic type, extending both the multi-level first order analysis in
[\emph{F.Y.~Kuo, Ch.~Schwab, and I.H.~Sloan, Multi-level quasi-Monte Carlo
finite element methods for a class of elliptic partial differential equations
with random coefficient} (in review)] and the single level higher order
analysis in [\emph{J.~Dick, F.Y.~Kuo, Q.T.~Le~Gia, D.~Nuyens, and Ch.~Schwab,
Higher order QMC Galerkin discretization for parametric operator equations} (in
review)]. We cover, in particular, both definite as well as indefinite,
strongly elliptic systems of partial differential equations (PDEs) in
non-smooth domains, and discuss in detail the impact of higher order
derivatives of {\KL} eigenfunctions in the parametrization of random PDE inputs
on the convergence results. Based on our \emph{a-priori} error bounds, concrete
choices of algorithm parameters are proposed in order to achieve a prescribed
accuracy under minimal computational work. Problem classes and sufficient
conditions on data are identified where multi-level higher order QMC
Petrov-Galerkin algorithms outperform the corresponding single level versions
of these algorithms. Numerical experiments confirm the theoretical results.


  Deep reinforcement learning (DRL) techniques have become increasingly used in
various fields for decision-making processes. However, a challenge that often
arises is the trade-off between both the computational efficiency of the
decision-making process and the ability of the learned agent to solve a
particular task. This is particularly critical in real-time settings such as
video games where the agent needs to take relevant decisions at a very high
frequency, with a very limited inference time.
  In this work, we propose a generic offline learning approach where the
computation cost of the input features is taken into account. We derive the
Budgeted Decision Transformer as an extension of the Decision Transformer that
incorporates cost constraints to limit its cost at inference. As a result, the
model can dynamically choose the best input features at each timestep. We
demonstrate the effectiveness of our method on several tasks, including D4RL
benchmarks and complex 3D environments similar to those found in video games,
and show that it can achieve similar performance while using significantly
fewer computational resources compared to classical approaches.


  We present a detailed derivation of a multi-site mean-field theory (MSMFT)
used to describe the Mott-insulator to superfluid transition of bosonic atoms
in optical lattices. The approach is based on partitioning the lattice into
small clusters which are decoupled by means of a mean field approximation. This
approximation invokes local superfluid order parameters defined for each of the
boundary sites of the cluster. The resulting MSMFT grand potential has a
non-trivial topology as a function of the various order parameters. An
understanding of this topology provides two different criteria for the
determination of the Mott insulator superfluid phase boundaries. We apply this
formalism to $d$-dimensional hypercubic lattices in one, two and three
dimensions, and demonstrate the improvement in the estimation of the phase
boundaries when MSMFT is utilized for increasingly larger clusters, with the
best quantitative agreement found for $d=3$. The MSMFT is then used to examine
a linear dimer chain in which the on-site energies within the dimer have an
energy separation of $\Delta$. This system has a complicated phase diagram
within the parameter space of the model, with many distinct Mott phases
separated by superfluid regions.


  We analyze the relationship between tripartite entanglement and genuine
tripartite nonlocality for 3-qubit pure states in the GHZ class. We consider a
family of states known as the generalized GHZ states and derive an analytical
expression relating the 3-tangle, which quantifies tripartite entanglement, to
the Svetlichny inequality, which is a Bell-type inequality that is violated
only when all three qubits are nonlocally correlated. We show that states with
3-tangle less than 1/2 do not violate the Svetlichny inequality. On the other
hand, a set of states known as the maximal slice states do violate the
Svetlichny inequality, and exactly analogous to the two-qubit case, the amount
of violation is directly related to the degree of tripartite entanglement. We
discuss further interesting properties of the generalized GHZ and maximal slice
states.


  In this paper, we show that the soft-decision input to the main decoder in an
SST Viterbi decoder is regarded as the innovation as well from the viewpoint of
mutual information and mean-square error. It is assumed that a code sequence is
transmitted symbol by symbol over an AWGN channel using BPSK modulation. Then
we can consider the signal model, where the signal is composed of the
signal-to-noise ratio (SNR) and the equiprobable binary input. By assuming that
the soft-decision input to the main decoder is the innovation, we show that the
minimum mean-square error (MMSE) in estimating the binary input is expressed in
terms of the distribution of the encoded block for the main decoder. It is
shown that the obtained MMSE satisfies indirectly the known relation between
the mutual information and the MMSE in Gaussian channels. Thus the derived MMSE
is justified, which in turn implies that the soft-decision input to the main
decoder can be regarded as the innovation. Moreover, we see that the
input-output mutual information is connected with the distribution of the
encoded block for the main decoder.


  We study the critical properties of a non-equilibrium statistical model, the
majority-vote model, on heptagonal and dual heptagonal lattices. Such lattices
have the special feature that they only can be embedded in negatively curved
surfaces. We find, by using Monte Carlo simulations and finite-size analysis,
that the critical exponents $1/\nu$, $\beta/\nu$ and $\gamma/\nu$ are different
from those of the majority-vote model on regular lattices with periodic
boundary condition, which belongs to the same universality class as the
equilibrium Ising model. The exponents are also from those of the Ising model
on a hyperbolic lattice. We argue that the disagreement is caused by the
effective dimensionality of the hyperbolic lattices. By comparative studies, we
find that the critical exponents of the majority-vote model on hyperbolic
lattices satisfy the hyperscaling relation
$2\beta/\nu+\gamma/\nu=D_{\mathrm{eff}}$, where $D_{\mathrm{eff}}$ is an
effective dimension of the lattice. We also investigate the effect of boundary
nodes on the ordering process of the model.


  We present the kinematics of a sample of bipolar planetary nebulae (PNe)
which cover a wide range of observed morphologies and collimation degrees, from
bipolar PNe with a marked equatorial ring and wide lobes to highly collimated
objects. We use an empirical model in order to derive the expansion velocity,
collimation degree, and inclination angle of the PN with respect to the plane
of the sky. The equatorial expansion velocities measured in the objects in our
sample are always in the low to medium range (3-16km/s),while their polar
expansion velocities range from low to very high (18-100 km/s). None of the
objects in our sample, even those that show an extreme collimation degree, seem
to be (kinematically) younger than ~1000 yr. We compare our results with the
state-of-the-art theoretical models for the formation of bipolar PNe. We find
good agreement between the observed expansion velocities and numerical models
that use magnetic fields with stellar rotation as collimation mechanism.


  We consider momentum transfer using frequency-chirped standing wave fields.
Novel atom-beam splitter and mirror schemes based on Bragg scattering are
presented. It is shown that a predetermined number of photon momenta can be
transferred to the atoms in a single interaction zone.


  Working in the framework of a nonrelativistic quark model we evaluate the
widths for the strong one-pion decays $\Sigma_c\to\Lambda_c \pi$,
$\Sigma_c^*\to\Lambda_c \pi$ and $\Xi_c^{*}\to\Xi_c \pi$. We take advantage of
the constraints imposed by heavy quark symmetry to solve the three-body problem
by means of a simple variational ansatz. We use partial conservation of the
axial current hypothesis to get the strong vertices from weak axial current
matrix elements. Our results are in good agreement with experimental data.


  Using quasiparticle self-consistent $GW$ calculations we examined the
electronic structure of LaNiO$_3$ and the LaNiO$_3$/LaAlO$_3$ superlattice. The
effects of electron correlation in Ni-$d$ bands were reasonably well described
without any {\it ad hoc} parameter and without the ambiguity related to the
double-counting and downfolding issues. The effective mass is about $30\%$
enhanced compared to the GGA result. One band feature, which is believed to be
essential for the cuprate-like superconductivity, is not realized and the
central Fermi surface pocket does not disappear. Our result is consistent with
a recent dynamical mean field calculation based on the $d$--$p$ model and in
contrast to the result from a $d$-band only model.


  We propose two structural models for stochastic losses given default which
allow to model the credit losses of a portfolio of defaultable financial
instruments. The credit losses are integrated into a structural model of
default events accounting for correlations between the default events and the
associated losses. We show how the models can be calibrated and analyze the
impact of correlations between the occurrences of defaults and recoveries by
testing our models for a representative sample portfolio.


  We propose a self-consistent theoretical framework of chorus wave excitation,
which describes the evolution of the whistler fluctuation spectrum as well as
the supra-thermal electron distribution function. The renormalized hot electron
response is cast in the form of a Dyson-like equation, which then leads to
evolution equations for nonlinear fluctuation growth and frequency shift. This
approach allows us to analytically derive for the first time exactly the same
expression for the chorus chirping rate originally proposed by Vomvoridis et
al.,1982. Chorus chirping is shown to correspond to maximization of wave
particle power exchange, where each individual wave belonging to the whistler
wave packet is characterized by small nonlinear frequency shift. We also show
that different interpretations of chorus chirping proposed in published
literature have a consistent reconciliation within the present theoretical
framework, which further illuminates the analogy with similar phenomena in
fusion plasmas and free electron laser physics.


  We revise the treatment of fermionic dark matter interacting with photons via
dimension-5 and -6 effective operators. We show how the application of the
effective operators beyond their validity introduces unphysical, gauge
violating effects that are relevant for current experimental searches.
Restoring gauge invariance by coupling dark matter to the hypercharge gauge
field has implications for the parameter space above and below the electroweak
scale. We review the phenomenology of these hypercharge form factors at the LHC
as well as for direct and indirect detection experiments. We highlight where
the electromagnetic and hypercharge descriptions lead to wildly different
conclusions about the viable parameter space and the relative sensitivity of
various probes. These include a drastic weakening of vector bosons fusion
versus mono-jet searches at the LHC, and the incorrect impression that indirect
searches could lead to better constraints than direct detection for larger dark
matter masses. We find that the dimension-5 operators are strongly constrained
by direct detection bounds, while for dimension-6 operators LHC mono-jet
searches are competitive or performing better than the other probes we
consider.


  Real-time databases deal with time-constrained data and time-constrained
transactions. The design of this kind of databases requires the introduction of
new concepts to support both data structures and the dynamic behaviour of the
database. In this paper, we give an overview about different aspects of
real-time databases and we clarify requirements of their modelling. Then, we
present a framework for real-time database design and describe its fundamental
operations. A case study demonstrates the validity of the structural model and
illustrates SQL queries and Java code generated from the classes of the model


  Convolutional Neural Networks (CNN) have revolutionized perception for color
images, and their application to sonar images has also obtained good results.
But in general CNNs are difficult to train without a large dataset, need manual
tuning of a considerable number of hyperparameters, and require many careful
decisions by a designer. In this work, we evaluate three common decisions that
need to be made by a CNN designer, namely the performance of transfer learning,
the effect of object/image size and the relation between training set size. We
evaluate three CNN models, namely one based on LeNet, and two based on the Fire
module from SqueezeNet. Our findings are: Transfer learning with an SVM works
very well, even when the train and transfer sets have no classes in common, and
high classification performance can be obtained even when the target dataset is
small. The ADAM optimizer combined with Batch Normalization can make a high
accuracy CNN classifier, even with small image sizes (16 pixels). At least 50
samples per class are required to obtain $90\%$ test accuracy, and using
Dropout with a small dataset helps improve performance, but Batch Normalization
is better when a large dataset is available.


  Aims. We present the first theoretical SN Ia light curves calculated with the
time-dependent version of the general purpose model atmosphere code PHOENIX.
Our goal is to produce light curves and spectra of hydro models of all types of
supernovae. Methods. We extend our model atmosphere code PHOENIX to calculate
type Ia supernovae light curves. A simple solver was imple- mented which keeps
track of energy conservation in the atmosphere during the free expansion phase.
Results. The correct operation of the new additions to PHOENIX were verified in
test calculations. Furthermore, we calculated theo- retical light curves and
compared them to the observed SN Ia light curves of SN 1999ee and SN 2002bo. We
obtained LTE as well as NLTE model light curves. Conclusions. We have verified
the correct operation of our extension into the time domain. We have calculated
the first SN Ia model light curves using PHOENIX in both LTE and NLTE. For
future work the infrared model light curves need to be further investigated.


  The LAB4D is a new application-specific integrated circuit (ASIC) of the
Large Analog Bandwidth Recorder and Digitizer with Ordered Readout (LABRADOR)
family, for use in direct wideband radio frequency digitization such as is used
in ultrahigh energy neutrino and cosmic ray astrophysics. The LAB4D is a single
channel switched-capacitor array (SCA) 12-bit sampler with integrated
analog-to-digital converters (ADC), developed in the TSMC 0.25um process. The
LAB4D, operating at 3.2GSa/s, contains 4096 total samples arranged in 32
windows, for a total record length of 1280ns. The 3dB bandwidth is
approximately 1.3GHz, with a directly-coupled 50ohm input. This represents a
factor of 16 increase in the sample depth and an increase in analog bandwidth
and sampling depth in comparison to the previous generation LAB3 digitizer.
Individually addressable windows allow for sampling and digitization to occur
simultaneously, leading to nearly deadtime-free readout for kHz readout rates.
All biases and current references are generated via internal digital-to-analog
converters (DACs), resulting in a stand-alone digitizer with no additional
support circuitry. In addition, the LAB4D contains sample cell timebase
trimming capabilities, reducing the intrinsic sample-to-sample time variance to
less than 5ps; an improvement of about 80%. This allows the LAB4D to be used in
precision timing applications with minimal post-hoc calibration.


  Visual question answering (VQA) is an interesting learning setting for
evaluating the abilities and shortcomings of current systems for image
understanding. Many of the recently proposed VQA systems include attention or
memory mechanisms designed to support "reasoning". For multiple-choice VQA,
nearly all of these systems train a multi-class classifier on image and
question features to predict an answer. This paper questions the value of these
common practices and develops a simple alternative model based on binary
classification. Instead of treating answers as competing choices, our model
receives the answer as input and predicts whether or not an
image-question-answer triplet is correct. We evaluate our model on the Visual7W
Telling and the VQA Real Multiple Choice tasks, and find that even simple
versions of our model perform competitively. Our best model achieves
state-of-the-art performance on the Visual7W Telling task and compares
surprisingly well with the most complex systems proposed for the VQA Real
Multiple Choice task. We explore variants of the model and study its
transferability between both datasets. We also present an error analysis of our
model that suggests a key problem of current VQA systems lies in the lack of
visual grounding of concepts that occur in the questions and answers. Overall,
our results suggest that the performance of current VQA systems is not
significantly better than that of systems designed to exploit dataset biases.


  We analyse very deep X-ray and mid-IR surveys in common areas of the Lockman
Hole and the HDF North to study the sources of the X-ray background (XRB) and
to test the standard obscured accretion paradigm. We detect with ISO a rich
population of X-ray luminous sources with red optical colours, including a
fraction identified with Extremely Red Objects (R-K > 5) and galaxies with SEDs
typical of normal massive ellipticals or spirals at z ~ 1. The high 0.5-10 keV
X-ray luminosities of these objects (1E43-1E45 erg/s) indicate that the
ultimate energy source is gravitational accretion, while the X-ray to IR flux
ratios and the X-ray spectral hardness show evidence of photoelectric
absorption at low X-ray energies. An important hint on the physics comes from
the mid-IR data at 6.7 and 15 um, well reproduced by model spectra of
completely obscured quasars under standard assumptions and l.o.s. optical
depths tau ~ 30-40. Other predictions of the standard XRB picture, like the
distributions of intrinsic bolometric luminosities and the relative fractions
of type-I and -II objects (1:3), are also consistent with our results. Obscured
gravitational accretion is then confirmed as being responsible for the bulk of
the X-ray background, since we detect in the IR the down-graded energy
photoelectrically absorbed in X-rays: 63% of the faint 5-10 keV XMM sources are
detected in the mid-IR by Fadda et al. (2001). However, although as much as 90%
of the X-ray energy production could be converted to IR photons, no more than
20% of the Cosmic IR Background can be attributed to X-ray loud AGNs.


  We introduce a new percolation model to describe and analyze the spread of an
epidemic on a general directed and locally finite graph. We assign a
two-dimensional random weight vector to each vertex of the graph in such a way
that the weights of different vertices are i.i.d., but the two entries of the
vector assigned to a vertex need not be independent. The probability for an
edge to be open depends on the weights of its end vertices, but conditionally
on the weights, the states of the edges are independent of each other. In an
epidemiological setting, the vertices of a graph represent the individuals in a
(social) network and the edges represent the connections in the network. The
weights assigned to an individual denote its (random) infectivity and
susceptibility, respectively. We show that one can bound the percolation
probability and the expected size of the cluster of vertices that can be
reached by an open path starting at a given vertex from above and below by the
corresponding quantities for respectively independent bond and site percolation
with certain densities; this generalizes a result of Kuulasmaa. Many models in
the literature are special cases of our general model.


  Within a semi--infinite thre--dimensional lattice gas model describing the
coexistence of two phases on a substrate, we study, by cluster expansion
techniques, the free energy (line tension) associated with the contact line
between the two phases and the substrate. We show that this line tension, is
given at low temperature by a convergent series whose leading term is negative,
and equals 0 at zero temperature.


  In this work we investigate characteristic modifications of the spectrum of
cosmological perturbations and the spectral index due to chain inflation. We
find two types of effects. First, modifications of the spectral index depending
on interactions between radiation and the vacuum, and on features of the
effective vacuum potential of the underlying fundamental theory. Second, a
modulation of the spectrum signalling new physics due to bubble nucleation.
This effect is similar to those of transplanckian physics. Measurements of such
signatures could provide a wealth of information on the fundamental physics at
the basis of inflation.


  The surface and bulk states in topological materials have shown promise in
many applications. Grey or $\alpha$-Sn, the inversion symmetric analogue to
HgTe, can exhibit a variety of these phases. However there is disagreement in
both calculation and experiment over the exact shape of the bulk bands and the
number and origin of the surface states. Using spin- and angle-resolved
photoemission we investigate the bulk and surface electronic structure of
$\alpha$-Sn thin films on InSb(001) grown by molecular beam epitaxy. We find
that there is no significant warping in the shapes of the bulk bands. We also
observe the presence of only two surface states near the valence band maximum
in both thin (13 bilayer) and thick (400 bilayer) films. In 50 bilayer films,
these two surface states coexist with quantum well states. Surprisingly, both
of these surface states are spin-polarized with orthogonal spin-momentum
locking and opposite helicities. One of these states is the spin-polarized
topological surface state and the other a spin resonance. Finally, the presence
of another orthogonal spin-momentum locked topological surface state from a
secondary band inversion is verified. Our work clarifies the electronic
structure of $\alpha$-Sn(001) such that better control of the electronic
properties can be achieved. In addition, the presence of two spin-polarized
surface states near the valence band maximum has important ramifications for
the use of $\alpha$-Sn in spintronics.


  Terahertz (THz) communications and reconfigurable intelligent surfaces (RISs)
have been recently proposed to enable various powerful indoor applications,
such as wireless virtual reality (VR). For an efficient servicing of VR users,
an efficient THz path allocation solution becomes a necessity. Assuming the RIS
component is the most critical one in enabling the service, we investigate the
impact of RIS hardware failure on path allocation performance. To this end, we
study a THz network that employs THz operated RISs acting as base stations,
serving VR users. We propose a Semi-Markov decision Process (SMDP)-based path
allocation model to ensure the reliability of THz connection, while maximizing
the total long-term expected system reward, considering the system gains, costs
of link utilization, and the penalty of RIS failure. The SMDP-based model of
the RIS system is formulated by defining the state space, action space, reward
model, and transition probability distribution. We propose an optimal iterative
algorithm for path allocation that decides the next action at each system
state. The results show the average reward and VR service blocking probability
under different scenarios and with various VR service arrivals and RIS failure
rates, as first step towards feasible VR services over unreliable THz RIS.


  With the advent of Big Data, nowadays in many applications databases
containing large quantities of similar time series are available. Forecasting
time series in these domains with traditional univariate forecasting procedures
leaves great potentials for producing accurate forecasts untapped. Recurrent
neural networks (RNNs), and in particular Long Short-Term Memory (LSTM)
networks, have proven recently that they are able to outperform
state-of-the-art univariate time series forecasting methods in this context
when trained across all available time series. However, if the time series
database is heterogeneous, accuracy may degenerate, so that on the way towards
fully automatic forecasting methods in this space, a notion of similarity
between the time series needs to be built into the methods. To this end, we
present a prediction model that can be used with different types of RNN models
on subgroups of similar time series, which are identified by time series
clustering techniques. We assess our proposed methodology using LSTM networks,
a widely popular RNN variant. Our method achieves competitive results on
benchmarking datasets under competition evaluation procedures. In particular,
in terms of mean sMAPE accuracy, it consistently outperforms the baseline LSTM
model and outperforms all other methods on the CIF2016 forecasting competition
dataset.


  Accurate CCD observations of three Cepheids in the SMC were made with the
purpose of confirming their nature of second overtone mode Cepheids. The stars
were suspected pulsating in the second overtone mode owing to the unusual light
curve and short period reported by Payne-Gaposchkin & Gaposchkin (1966). The
analysis of the new data shows that for two stars the previous periods are
wrong, and in the three cases the new light curves are normal. According to the
new observations, HV 1353 is a fundamental mode pulsator with small amplitude,
and HV 1777 and HV 1779 are first overtone mode pulsators.
  Also the star HV 1763, whose nature was unknown, was observed in the field of
HV 1777. The new data show that it is a first overtone mode Cepheid with
P=2.117d.


  We prove that any $n$-dimensional Hamiltonian operator with pure point
spectrum is completely integrable via self-adjoint first integrals.
Furthermore, we establish that given any closed set $\Sigma\subset\mathbb R$
there exists an integrable $n$-dimensional Hamiltonian which realizes it as its
spectrum. We develop several applications of these results and discuss their
implications in the general framework of quantum integrability.


  We provide high-order approximations to periodic travelling wave profiles and
to the velocity field and the pressure beneath the waves, in flows with
constant vorticity over a flat bed.


  In this paper we review, and extend to the non-isothermal case, some results
concerning the application of the maximum entropy closure technique to the
derivation of hydrodynamic equations for particles with spin-orbit interaction
and Fermi-Dirac statistics. In the second part of the paper we treat in more
details the case of electrons on a graphene sheet and investigate various
asymptotic regimes.


  Holes drilled in a type-II superconductor trap the magnetic flux. Following
Clem's flux pinning model, we consider surface pinning as a mechanism for
compressing the magnetic flux in the holes. Estimations of the trapped magnetic
flux demonstrate that the holes with the diameter up to 2 mm are advantageous
for bulk single-crystal REBCO samples. The REBCO films and tapes can be
improved by the holes with diameter smaller than 10 $\mu$m.


  The past years have witnessed increasing research interest in achieving
passive human localization with commodity WiFi devices. However, due to the
fundamental limited spatial resolution of WiFi signals, it is still very
difficult to achieve accurate localization with existing commodity WiFi
devices. To tackle this problem, in this paper, we propose to exploit the
degree of freedom provided by the Intelligent Reflecting Surface (IRS), which
is composed of a large number of controllable reflective elements, to modulate
the spatial distribution of WiFi signals and thus break down the spatial
resolution limitation of WiFi signals to achieve accurate localization.
Specifically, in the single-person scenario, we derive the closed-form solution
to optimally control the phase shift of the IRS elements. In the multi-person
scenario, we propose a Side-lobe Cancellation Algorithm to eliminate the
near-far effect to achieve accurate localization of multiple persons in an
iterative manner. Extensive simulation results demonstrate that without any
change to the existing WiFi infrastructure, the proposed framework can locate
multiple moving persons passively with sub-centimeter accuracy under multipath
interference and random noise.


  We present a geometrical interpretation of linear regression based on vectors
in n dimensions (n the number of data points). This is to be used as a didactic
tool for teachers when presenting that topic.


  Langevin dynamics is used to study equilibrium properties of the suspension
of magnetic filaments (chains of nanoparticles permanently crosslinked with
polymers). It is shown that the filament suspension generally has a larger
magnetic susceptibility than the system of unlinked nanoparticles with the same
average particle concentration. However, actual susceptibility gain strongly
depends on length and flexibility of filaments. It is also shown that in a
strong gravitational (centrifugal) field sedimentation profiles of filaments
are less homogeneous than that of unlinked particles. The spatial distribution
of filaments weakly depends on the intensity of interparticle dipole-dipole
interactions.


  The weighted k-nearest neighbors algorithm is one of the most fundamental
non-parametric methods in pattern recognition and machine learning. The
question of setting the optimal number of neighbors as well as the optimal
weights has received much attention throughout the years, nevertheless this
problem seems to have remained unsettled. In this paper we offer a simple
approach to locally weighted regression/classification, where we make the
bias-variance tradeoff explicit. Our formulation enables us to phrase a notion
of optimal weights, and to efficiently find these weights as well as the
optimal number of neighbors efficiently and adaptively, for each data point
whose value we wish to estimate. The applicability of our approach is
demonstrated on several datasets, showing superior performance over standard
locally weighted methods.


  We investigate the wind of lambda And, a solar-mass star that has evolved off
the main sequence becoming a sub-giant. We present spectropolarimetric
observations and use them to reconstruct the surface magnetic field of lambda
And. Although much older than our Sun, this star exhibits a stronger (reaching
up to 83 G) large-scale magnetic field, which is dominated by the poloidal
component. To investigate the wind of lambda And, we use the derived magnetic
map to simulate two stellar wind scenarios, namely a polytropic wind
(thermally-driven) and an Alfven-wave driven wind with turbulent dissipation.
From our 3D magnetohydrodynamics simulations, we calculate the wind thermal
emission and compare it to previously published radio observations and more
recent VLA observations, which we present here. These observations show a basal
sub-mJy quiescent flux level at ~5 GHz and, at epochs, a much larger flux
density (>37 mJy), likely due to radio flares. By comparing our model results
with the radio observations of lambda And, we can constrain its mass-loss rate
Mdot. There are two possible conclusions. 1) Assuming the quiescent radio
emission originates from the stellar wind, we conclude that lambda And has Mdot
~ 3e-9 Msun/yr, which agrees with the evolving mass-loss rate trend for evolved
solar-mass stars. 2) Alternatively, if the quiescent emission does not
originate from the wind, our models can only place an upper limit on mass-loss
rates, indicating that Mdot <~ 3e-9 Msun/yr.


  We show that parametric level correlations in random-matrix theories are
closely related to a breaking of the symmetry between the advanced and the
retarded Green's functions. The form of the parametric level correlation
function is the same as for the disordered case considered earlier by Simons
and Altshuler and is given by the graded trace of the commutator of the
saddle--point solution with the particular matrix that describes the symmetry
breaking in the actual case of interest. The strength factor differs from the
case of disorder. It is determined solely by the Goldstone mode. It is
essentially given by the number of levels that are strongly mixed as the
external parameter changes. The factor can easily be estimated in applications.


  Special atom spaces have been around for quite awhile since the introduction
of atoms by R. Coifman in his seminal paper who led to another proof that the
dual of the Hardy space $H^1$ is in fact the space of functions of bounded
means oscillations (BMO). Special atom spaces enjoy quite a few attributes of
their own, among which the fact that they have an analytic extension to the
unit disc. Recently, an extension of special atom spaces to higher dimensions
was proposed, making ripe the possible exploration of the above extension in
higher dimensions. In this paper we propose an analytic characterization of
special atom spaces in higher dimensions.


  We extend a result on renormalized oscillation theory, originally derived for
Sturm-Liouville and Dirac-type operators on arbitrary intervals in the context
of scalar coefficients, to the case of general Hamiltonian systems with block
matrix coefficients. In particular, this contains the cases of general
Sturm-Liouville and Dirac-type operators with block matrix-valued coefficients
as special cases.
  The principal feature of these renormalized oscillation theory results
consists in the fact that by replacing solutions by appropriate Wronskians of
solutions, oscillation theory now applies to intervals in essential spectral
gaps where traditional oscillation theory typically fails.


  This article surveys the development of observational understanding of the
interior rotation of the Sun and its temporal variation over approximately
forty years, starting with the 1960s attempts to determine the solar core
rotation from oblateness and proceeding through the development of
helioseismology to the detailed modern picture of the internal rotation deduced
from continuous helioseismic observations during solar cycle 23. After
introducing some basic helioseismic concepts, it covers, in turn, the rotation
of the core and radiative interior, the "tachocline" shear layer at the base of
the convection zone, the differential rotation in the convection zone, the
near-surface shear, the pattern of migrating zonal flows known as the torsional
oscillation, and the possible temporal variations at the bottom of the
convection zone. For each area, the article also briefly explores the
relationship between observations and models.


  The Mathisson-Papapetrou-Dixon (MPD) equations describe the motion of
spinning test particles. It is well-known that these equations, which couple
the Riemann curvature tensor with the antisymmetric spin tensor S, together
with the normalization condition for the four-velocity, is a system of eleven
equations relating fourteen unknowns. To ``close'' the system, it is necessary
to introduce a constraint of the form V_\mu S^{\mu \nu} = 0, usually known as
the spin supplementary condition (SSC), where V_\mu is a future-oriented
reference vector satisfying the normalization condition V_\alpha V^\alpha = -1.
There are several SSCs in the literature. In particular, the Tulzcyjew-Dixon,
Mathisson-Pirani, and Ohashi-Kyrian-Semer\'ak are the most used by the
community. From the physical point of view, choosing a different SSC (a
different reference vector $V^\mu$) is equivalent to fixing the centroid of the
test particle. In this manuscript, we compare different SSCs for spinning test
particles moving around a Morris-Thorne traversable wormhole. To do so, we
first obtain the orbital frequency and expand it up to third-order in the
particle's spin; as expected, the zero-order coincides with the Keplerian
frequency, the same in all SSCs; nevertheless, we found that differences appear
in the second order of the expansion, similar to the Schwarzschild and Kerr
black holes. We also compare the behavior of the innermost stable circular
orbit (ISCO). Since each SSC is associated with a different centroid of the
test particle, we analyze (separately) the radial and spin corrections for each
SSC. We found that the radial corrections improve the convergence, especially
between Tulzcyjew-Dixon and Mathisson-Pirani SSCs. In the case of
Ohashi-Kyrian-Semer\'ak, we found that the spin corrections remove the
divergence for the ISCO and extend its existence for higher values of the
particle's spin.


  This paper proposes a novel imperfect spherical transmitter (TX) model,
namely the membrane fusion (MF)-based TX, that adopts MF between a vesicle and
the TX membrane to release molecules encapsulated within the vesicle. For the
MF-based TX, the molecule release probability and the fraction of molecules
released from the TX membrane are derived. Incorporating molecular degradation
and a fully-absorbing receiver (RX), the end-to-end molecule hitting
probability at the RX is also derived. A simulation framework for the MF-based
TX is proposed, where the released point on the TX membrane and the released
time of each molecule are determined. Aided by the simulation framework, the
derived analytical expressions are validated. Simulation results verify that a
low MF probability or low vesicle mobility slows the release of molecules from
the TX, extends time required to reach the peak release probability, and
reduces the end-to-end molecule hitting probability at the RX.


  Modern tactical operations have complex communication and computing
requirements, often involving different coalition teams, that cannot be
supported by today's mobile ad hoc networks. To this end, the emerging Software
Defined Networking (SDN) paradigm has the potential to enable the redesign and
successful deployment of these systems. In this paper, we propose a set of
novel architecture designs for SDN-enabled mobile ad hoc networks in the
tactical field. We discuss in detail the challenges raised by the ad hoc and
coalition network environment, and we present specific solutions to address
them. The proposed approaches build on evidence from experimental evaluation of
such architectures and leverage recent theoretical results from SDN deployments
in large backbone networks.


  Following Manin's approach to renormalization in the theory of computation,
we investigate Dyson-Schwinger equations on Hopf algebras, operads and
properads of flow charts, as a way of encoding self-similarity structures in
the theory of algorithms computing primitive and partial recursive functions
and in the halting problem.


  We present diffraction-limited 2-25 micron images obtained with the W. M.
Keck 10-m telescopes that spatially resolve the cool source, IRS 21, one of a
small group of enigmatic objects in the central parsec of our Galaxy that have
eluded classification. Modeled as a Gaussian, the azimuthally-averaged
intensity profile of IRS 21 has a half-width half-maximum (HWHM) size of
650+/-80 AU at 2.2 microns and an average HWHM size of 1600+/-200 AU at
mid-infrared wavelengths. These large apparent sizes imply an extended
distribution of dust. The mid-infrared color map indicates that IRS 21 is a
self-luminous source rather than an externally heated dust clump as originally
suggested. The spectral energy distribution has distinct near- and mid-infrared
components. A simple radiative transfer code, which simultaneously fits the
near- and mid- infrared photometry and intensity profiles, supports a model in
which the near-infrared radiation is scattered and extincted light from an
embedded central source, while the mid-infrared emission is from thermally
re-radiating silicate dust. We argue that IRS 21 (and by analogy the other
luminous sources along the Northern Arm) is a massive star experiencing rapid
mass loss and plowing through the Northern Arm, thereby generating a bow shock,
which is spatially resolved in our observations.


  In the presence of strong electronic interactions, a partially filled Chern
band may stabilize a fractional Chern insulator (FCI) state, the zero-field
analog of the fractional quantum Hall phase. While FCIs have long been
hypothesized, feasible solid-state realizations only recently emerged, largely
due to the rise of moir\'e materials. In these systems, the quantum geometry of
the electronic bands plays a critical role in stabilizing the FCI in the
presence of competing correlated phases. In the limit of ``ideal'' quantum
geometry, where the quantum geometry is identical to that of Landau levels,
this role is well understood. However, in more realistic scenarios only empiric
numerical evidence exists, accentuating the need for a clear understanding of
the mechanism by which the FCI deteriorates moving further away from these
ideal conditions. We introduce and analyze an anisotropic model of a $\left|C
\right|=1$ Chern insulator, whereupon partial filling of its bands, an FCI
phase is stabilized over a certain parameter regime. We incorporate strong
electronic interaction analytically by employing a coupled-wires approach,
studying the FCI stability and its relation to the the quantum metric. We
identify an unusual anti-FCI phase benefiting from non-ideal geometry,
generically subdominant to the FCI. However, its presence hinders the formation
of FCI in favor of other competitive phases at fractional fillings, such as the
charge density wave. Though quite peculiar, this anti-FCI phase may have
already been observed in experiments at high magnetic fields. This establish a
direct link between quantum geometry and FCI stability in a tractable model far
from any ideal band conditions, and illuminates a unique mechanism of FCI
deterioration.


  We analyzed the effects of having a close companion on the star formation
activity of galaxies in 8K galaxy pair catalog selected from the 2dFGRS. We
found that, statistically, galaxies with $r_{\rm p} < 25 {\rm h^{-1}}$ kpc and
$\Delta V < 100 {\rm km/s}$ have enhanced star formation with respect to
isolated galaxies with the same luminosity and redshift distribution. Our
results suggest that the physical processes at work during tidal interactions
can overcome the effects of environment, expect in dense regions.


  We investigate the use of correlated photon pair sources for the improved
quantum-level detection of a target in the presence of a noise background.
Photon pairs are generated by spontaneous four-wave mixing, one photon from
each pair (the herald) is measured locally while the other (the signal) is sent
to illuminate the target. Following diffuse reflection from the target, the
signal photons are detected by a receiver and non-classical timing correlations
between the signal and herald are measured in the presence of a configurable
background noise source. Quantum correlations from the photon pair source can
be used to provide an enhanced signal-to-noise ratio when compared to a
classical light source of the same intensity.


  We show that any $\mathbb{R}^d\setminus\{0\}$-valued self-similar Markov
process $X$, with index $\alpha>0$ can be represented as a path transformation
of some Markov additive process (MAP) $(\theta,\xi)$ in
$S_{d-1}\times\mathbb{R}$. This result extends the well known Lamperti
transformation. Let us denote by $\widehat{X}$ the self-similar Markov process
which is obtained from the MAP $(\theta,-\xi)$ through this extended Lamperti
transformation. Then we prove that $\widehat{X}$ is in weak duality with $X$,
with respect to the measure $\pi(x/\|x\|)\|x\|^{\alpha-d}dx$, if and only if
$(\theta,\xi)$ is reversible with respect to the measure $\pi(ds)dx$, where
$\pi(ds)$ is some $\sigma$-finite measure on $S_{d-1}$ and $dx$ is the Lebesgue
measure on $\mathbb{R}$. Besides, the dual process $\widehat{X}$ has the same
law as the inversion $(X_{\gamma_t}/\|X_{\gamma_t}\|^2,t\ge0)$ of $X$, where
$\gamma_t$ is the inverse of $t\mapsto\int_0^t\|X\|_s^{-2\alpha}\,ds$. These
results allow us to obtain excessive functions for some classes of self-similar
Markov processes such as stable L\'evy processes.


  We show that every co--orientable taut foliation F of an orientable,
atoroidal 3-manifold admits a transverse essential lamination. If this
transverse lamination is a foliation G, the pair F,G are the unstable and
stable foliation respectively of an Anosov flow. Otherwise, F admits a pair of
transverse very full genuine laminations.
  In the second case, M satisfies the weak geometrization conjecture - either
its fundamental group contains Z+Z or it is word-hyperbolic. Moreover, if M is
atoroidal, the mapping class group of M is finite, and any automorphism
homotopic to the identity is isotopic to the identity.


  Discovery of communities in complex networks is a fundamental data analysis
problem with applications in various domains. Most of the existing approaches
have focused on discovering communities of nodes, while recent studies have
shown great advantages and utilities of the knowledge of communities of links
in networks. From this new perspective, we propose a link dynamics based
algorithm, called UELC, for identifying link communities of networks. In UELC,
the stochastic process of a link-node-link random walk is employed to unfold an
embedded bipartition structure of links in a network. The local mixing
properties of the Markov chain underlying the random walk are then utilized to
extract two emerged link communities. Further, the random walk and the
bipartitioning processes are wrapped in an iterative subdivision strategy to
recursively identify link partitions that segregate the network links into
multiple subdivisions. We evaluate the performance of the new method on
synthetic benchmarks and demonstrate its utility on real-world networks. Our
experimental results show that our method is highly effective for discovering
link communities in complex networks. As a comparison, we also extend UELC to
extracting communities of node, and show that it is effective for node
community identification.


  Scintillation produced in liquid xenon by alpha particles and gamma rays has
been studied as a function of applied electric field. For back scattered gamma
rays with energy of about 200 keV, the number of scintillation photons was
found to decrease by 64+/-2% with increasing field strength. Consequently, the
pulse shape discrimination power between alpha particles and gamma rays is
found to reduce with increasing field, but remaining non-zero at higher fields.


  This paper studies defense mechanisms against model inversion (MI) attacks --
a type of privacy attacks aimed at inferring information about the training
data distribution given the access to a target machine learning model. Existing
defense mechanisms rely on model-specific heuristics or noise injection. While
being able to mitigate attacks, existing methods significantly hinder model
performance. There remains a question of how to design a defense mechanism that
is applicable to a variety of models and achieves better utility-privacy
tradeoff. In this paper, we propose the Mutual Information Regularization based
Defense (MID) against MI attacks. The key idea is to limit the information
about the model input contained in the prediction, thereby limiting the ability
of an adversary to infer the private training attributes from the model
prediction. Our defense principle is model-agnostic and we present tractable
approximations to the regularizer for linear regression, decision trees, and
neural networks, which have been successfully attacked by prior work if not
attached with any defenses. We present a formal study of MI attacks by devising
a rigorous game-based definition and quantifying the associated information
leakage. Our theoretical analysis sheds light on the inefficacy of DP in
defending against MI attacks, which has been empirically observed in several
prior works. Our experiments demonstrate that MID leads to state-of-the-art
performance for a variety of MI attacks, target models and datasets.


  This paper presents a novel framework to integrate both semantic and instance
contexts for panoptic segmentation. In existing works, it is common to use a
shared backbone to extract features for both things (countable classes such as
vehicles) and stuff (uncountable classes such as roads). This, however, fails
to capture the rich relations among them, which can be utilized to enhance
visual understanding and segmentation performance. To address this shortcoming,
we propose a novel Panoptic, Instance, and Semantic Relations (PISR) module to
exploit such contexts. First, we generate panoptic encodings to summarize key
features of the semantic classes and predicted instances. A Panoptic Relational
Attention (PRA) module is then applied to the encodings and the global feature
map from the backbone. It produces a feature map that captures 1) the relations
across semantic classes and instances and 2) the relations between these
panoptic categories and spatial features. PISR also automatically learns to
focus on the more important instances, making it robust to the number of
instances used in the relational attention module. Moreover, PISR is a general
module that can be applied to any existing panoptic segmentation architecture.
Through extensive evaluations on panoptic segmentation benchmarks like
Cityscapes, COCO, and ADE20K, we show that PISR attains considerable
improvements over existing approaches.


  In this paper we are interested in the following notions of smallness: a
subset $A$ of an abelian Polish group $X$ is called
Haar-countable/Haar-finite/Haar-$n$ if there are a Borel hull $B\supseteq A$
and a copy $C$ of $2^\omega$ such that $(C+x)\cap B$ is countable/finite/of
cardinality at most $n$, for all $x\in X$.
  Recently, Banakh et al. have unified the notions of Haar-null and Haar-meager
sets by introducing Haar-$\mathcal{I}$ sets, where $\mathcal{I}$ is a
collection of subsets of $2^\omega$. It turns out that if $\mathcal{I}$ is the
$\sigma$-ideal of countable sets, the ideal of finite sets or the collection of
sets of cardinality at most $n$, then we get the above notions. Moreover, those
notions have been studied independently by Zakrzewski (under a different name
-- perfectly $\kappa$-small sets).
  We study basic properties of the corresponding families of small sets, give
suitable examples distinguishing them (in all abelian Polish groups of the form
$\mathbb{R}\times X$) and study $\sigma$-ideals generated by compact members of
the considered families. In particular, we show that Haar-countable sets do not
form an ideal. Moreover, we answer some questions concerning null-finite sets,
asked by Banakh and Jab{\l}o\'nska, and pose several open problems.


  Experiments at the Juelich Cooler Synchrotron (COSY) have now found
compelling evidence for a new resonant state in the two-baryon system with mass
2380 MeV and a width of 70 MeV. The structure, containing six valence quarks,
constitutes a so-called dibaryon, either a hexaquark or a hadronic molecule.
The present knowledge about the dibaryon as well as other implications and
possible future experiments are discussed.


  The actions of 0-Kashiwara operators on the $U'_q(G_2^{(1)})$-crystal $B_l$
in [Yamane S., J. Algebra 210 (1998), 440-486] are made explicit by using a
similarity technique from that of a $U'_q(D_4^{(3)})$-crystal. It is shown that
$\{B_l\}_{l\ge1}$ forms a coherent family of perfect crystals.


  Adopting a good health information system (HIS) is essential for providing
high-quality healthcare. With rapid advances in technology in the healthcare
industry in recent years, healthcare providers seek effective options to deal
with numerous diseases and a growing number of patients, adopting advanced HIS
such as for clinical decision support. While the clinical decision support
systems (CDSS) can help medical personnel make better decisions, they may bring
negative results due to a lack of understanding of the elements that influence
GP's adoption of CDSS. This paper focuses on discovering obstacles that may
contribute to the problems surrounding CDSS adoption. Thirty general
practitioners were interviewed from different primary health centers in Saudi
Arabia in order to determine the challenges and obstacles in the sector. While
the outcome confirms that there are obstacles that affect the aspects, such as
time risk, quality of the system used, slow Internet speed, user interface,
lack of training, high costs, patient satisfaction, multiple systems used,
technical support, computer skills, lack of flexibility, system update,
professional skills and knowledge, computer efficiency and quality and accuracy
of data.


  Infrared spectrum (IR) of Herbig Ae young stars was reproduced and classified
by hydrocarbon pentagon-hexagon combined molecules by the quantum chemical
calculation. Observed IR list by B. Acke et al. was categorized to four
classes. Among 53 Herbig Ae stars, 26 samples show featured IR pattern named
Type-D, which shows common IR peaks at 6.2, 8.3, 9.2, 10.0, 11.3, 12.1, and
14.0 micrometer. Typical star is HD144432. Calculation on di-cation molecule
(C12H8)2+ having hydrocarbon one pentagon and two hexagons shows best
coincidence at 6.1, 8.2, 9.2, 9.9, 11.3, 12.2, and 14.1 micrometer. There are
some variation in Type-D. Spectrum of HD37357 was explained by a mixture with
di-cation (C12H8)2+ and tri-cation (C12H8)3+. Ubiquitously observed spectrum
Type-B was observed in 12 samples of Acke's list. In case of HD85567, observed
16 peaks were precisely reproduced by a single molecule (C23H12)2+. There is a
mixture case with Type-B and Type-D. Typical example was HD142527. In this
study, we could identify hidden carrier molecules for all types of IR in Herbig
Ae stars.


  We have investigated critical phenomena in spin glasses RxY1-xRu2Si2 (R = Dy,
Tb, Gd). These compounds, where the magnetic moments of rare-earth ions
interact by the long-range Ruderman-Kittel-Kasuya-Yoshida (RKKY) interaction
via conduction electrons, has uniaxial magnetic anisotropy. The separation of
the zero-field-cooled and field-cooled magnetization was found only along the
c-axis in all compounds, and hence, they are classified into the long-range
Ising spin glass. The magnetic anisotropic energies in these compounds are
different from each other in two orders of magnitude, from 330 K to 1.8 K,
however, the critical exponents are similar. It clearly indicates a presence of
the universality of the long-range RKKY Ising spin glasses.


  Lectures at VII Jorge Andre Swieca Summer School in Nuclear Physics; Brasil;
Jan 22 - Feb 4 1995. To be published by Plenum Press (C.A.Amaral Nunes ed.)


  We report the detection of CO emission from the optically luminous,
radio-quiet quasar J140955.5+562827, at a redshift z_CO =2.583. We also present
VLA continuum mapping results and VLBA high spatial resolution observations at
1.4 GHz. Both the CO(3-2) and CO(7-6) emission lines are detected using the
IRAM Plateau de Bure interferometer. The 3-2/7-6 line luminosity ratio is about
1/3 indicating the presence of warm and dense molecular gas with an estimated
mass of 6x10^10 Msun. The infrared-to-CO luminosity ratio is L_FIR/L'_CO(1-0)
\approx 500 Lsun (Kkms^-1 pc^2)^-1,comparable with values found for other
high-z sources where CO line emission is seen.
  J1409+5628 is detected using the VLA with a 1.4 GHz rest-frame luminosity
density of 4.0x10^25 W Hz^-1. The radio to far-infrared ratio, q, has a value
of 2.0 which is consistent with the values found in star forming galaxies. At
the 30 mas resolution of the VLBA, J1409+5628 is not detected with a 4 sigma
upper limit to the surface brightness of 0.29 mJy beam^-1. This implies a limit
to the intrinsic brightness temperature of 2x10^5 K at 8 GHz, typical for
nuclear starbursts and two or more orders of magnitude weaker than typical
radio-loud active galactic nuclei. Both the properties of the CO line emission
and the radio emission from J1409+5628 are therefore consistent with those
expected for a star forming galaxy.
  In J1409+5628 young massive stars are the dominant source of dust heating,
accounting for most of the infrared luminosity, and the massive reservoir of
molecular gas can sustain the star formation rate of a few 1000 \Msun yr^-1
implied by the far-infrared luminosity for about 10 million years.


  For Kummer extensions $y^m=f(x)$, we discuss conditions for an integer be a
Weierstrass gap at a place $P$. In the case of totally ramified places, the
conditions will be necessary and sufficient. As a consequence, we extend
independent results of several authors.


  The development and adoption of Vision Transformers and other deep-learning
architectures for image classification tasks has been rapid. However, the
"black box" nature of neural networks is a barrier to adoption in applications
where explainability is essential. While some techniques for generating
explanations have been proposed, primarily for Convolutional Neural Networks,
adapting such techniques to the new paradigm of Vision Transformers is
non-trivial. This paper presents T-TAME, Transformer-compatible Trainable
Attention Mechanism for Explanations, a general methodology for explaining deep
neural networks used in image classification tasks. The proposed architecture
and training technique can be easily applied to any convolutional or Vision
Transformer-like neural network, using a streamlined training approach. After
training, explanation maps can be computed in a single forward pass; these
explanation maps are comparable to or outperform the outputs of computationally
expensive perturbation-based explainability techniques, achieving SOTA
performance. We apply T-TAME to three popular deep learning classifier
architectures, VGG-16, ResNet-50, and ViT-B-16, trained on the ImageNet
dataset, and we demonstrate improvements over existing state-of-the-art
explainability methods. A detailed analysis of the results and an ablation
study provide insights into how the T-TAME design choices affect the quality of
the generated explanation maps.


  This paper proposes and analyzes a distributed MAC protocol that achieves
zero collision with no control message exchange nor synchronization. ZC
(ZeroCollision) is neither reservation-based nor dynamic TDMA; the protocol
supports variable-length packets and does not lose efficiency when some of the
stations do not transmit. At the same time, ZC is not a CSMA; in its steady
state, it is completely collision-free. The stations transmit repeatedly in a
round-robin order once the convergence state is reached. If some stations skip
their turn, their transmissions are replaced by idle $20 \mu$-second mini-slots
that enable the other stations to keep track of their order. Because of its
short medium access delay and its efficiency, the protocol supports both
real-time and elastic applications. The protocol allows for nodes leaving and
joining the network; it can allocate more throughput to specific nodes (such as
an access point). The protocol is robust against carrier sensing errors or
clock drift. While collision avoidance is guaranteed in a single collision
domain, it is not the case in a multiple collision one. However, experiments
show ZC supports a comparable amount of goodput to CSMA in a multiple collision
domain environment. The paper presents an analysis and extensive simulations of
the protocol, confirming that ZC outperforms both CSMA and TDMA at high and low
load.


  In this paper, we study a class of heterotic Landau-Ginzburg models. We show
that the action can be written as a sum of BRST-exact and non-exact terms. The
non-exact terms involve the pullback of the complexified Kahler form to the
worldsheet and terms arising from the superpotential, which is a Grassmann-odd
holomorphic function of the superfields. We then demonstrate that the action is
invariant on-shell under supersymmetry transformations up to a total
derivative. Finally, we extend the analysis to the case in which the
superpotential is not holomorphic. In this case, we find that supersymmetry
imposes a constraint which relates the nonholomorphic parameters of the
superpotential to the Hermitian curvature. Various special cases of this
constraint have previously been used to establish properties of Mathai-Quillen
form analogues which arise in the corresponding heterotic Landau-Ginzburg
models. There, it was claimed that supersymmetry imposes those constraints. Our
goal in this paper is to support that claim. The analysis for the
nonholomorphic case also reveals a constraint imposed by supersymmetry that we
did not anticipate from studies of Mathai-Quillen form analogues.


  Current remote-sensing interpretation models often focus on a single task
such as detection, segmentation, or caption. However, the task-specific
designed models are unattainable to achieve the comprehensive multi-level
interpretation of images. The field also lacks support for multi-task joint
interpretation datasets. In this paper, we propose Panoptic Perception, a novel
task and a new fine-grained dataset (FineGrip) to achieve a more thorough and
universal interpretation for RSIs. The new task, 1) integrates pixel-level,
instance-level, and image-level information for universal image perception, 2)
captures image information from coarse to fine granularity, achieving deeper
scene understanding and description, and 3) enables various independent tasks
to complement and enhance each other through multi-task learning. By
emphasizing multi-task interactions and the consistency of perception results,
this task enables the simultaneous processing of fine-grained foreground
instance segmentation, background semantic segmentation, and global
fine-grained image captioning. Concretely, the FineGrip dataset includes 2,649
remote sensing images, 12,054 fine-grained instance segmentation masks
belonging to 20 foreground things categories, 7,599 background semantic masks
for 5 stuff classes and 13,245 captioning sentences. Furthermore, we propose a
joint optimization-based panoptic perception model. Experimental results on
FineGrip demonstrate the feasibility of the panoptic perception task and the
beneficial effect of multi-task joint optimization on individual tasks. The
dataset will be publicly available.


  The use of a finite mixture of normal distributions in model-based clustering
allows to capture non-Gaussian data clusters. However, identifying the clusters
from the normal components is challenging and in general either achieved by
imposing constraints on the model or by using post-processing procedures.
Within the Bayesian framework we propose a different approach based on sparse
finite mixtures to achieve identifiability. We specify a hierarchical prior
where the hyperparameters are carefully selected such that they are reflective
of the cluster structure aimed at. In addition this prior allows to estimate
the model using standard MCMC sampling methods. In combination with a
post-processing approach which resolves the label switching issue and results
in an identified model, our approach allows to simultaneously (1) determine the
number of clusters, (2) flexibly approximate the cluster distributions in a
semi-parametric way using finite mixtures of normals and (3) identify
cluster-specific parameters and classify observations. The proposed approach is
illustrated in two simulation studies and on benchmark data sets.


  The single crystal elastic constants, polycrystalline elastic moduli and
related properties of orthorhombic MgSiN$_{2}$, MgGeN$_{2}$ and MgSnN$_{2}$
have been calculated using density functional theory and compared to the
related wurtzite structured AlN, GaN and InN. Since there are no experimental
studies of single crystal elastic properties of neither MgSiN$_{2}$,
MgGeN$_{2}$ or MgSnN$_{2}$, we have established the accuracy of the
calculations by comparison with experimental data for AlN, GaN and InN. The
calculated polycrystalline elastic moduli of MgSiN$_{2}$ are found to be in
good agreement with available experimental elastic moduli. It will be shown
that MgSiN$_{2}$ and MgGeN$_{2}$ have a small $xy$-plane lattice mismatch with
AlN and GaN, respectively, while at the same time being significantly softer
than both AlN and GaN. This shows that MgSiN$_{2}$ and MgGeN$_{2}$ should be
possible to be grown on AlN and GaN without significant lattice mismatch or
strain.


  Heavy-ion collisions will enter a new era with the start of the CERN Large
Hadron Collider (LHC). A first short run with proton-proton collisions at the
injection energy of 0.9 TeV will be followed by a longer one with $pp$
collisions at 10 TeV. First Pb-Pb collisions at $\sqrt{s_{NN}}$=5.5 TeV will
take place in 2009. Three experiments (ALICE, ATLAS, and CMS) will study both
$pp$ and Pb-Pb collisions. A selection of results showing the capabilities of
the three experiments for the study of the LHC medium with electromagnetic
probes is presented.


  We show how the gauge symmetry representations of the massless particle
content of gauged supergravities that arise in the AdS/CFT correspondences can
be derived from symmetric subgroups to be carried by string theory vertex
operators in these compactified models, although an explicit vertex operator
construction of IIB string and M theories on AdSxS remains elusive. Our
symmetry mechanism parallels the construction of representations of the Monster
group and affine algebras in terms of twisted conformal field theories, and may
serve as a guide to the perturbative description of the IIB string on AdSxS.


  Inflation may provide unique insight into the physics at the highest
available energy scales that cannot be replicated in any realistic terrestrial
experiment. Features in the primordial power spectrum are generically predicted
in a wide class of models of inflation and its alternatives, and are
observationally one of the most overlooked channels for finding evidence for
non-minimal inflationary models. Constraints from observations of the cosmic
microwave background cover the widest range of feature frequencies, but the
most sensitive constraints will come from future large-scale structure surveys
that can measure the largest number of linear and quasi-linear modes.


  We propose a novel mechanism enabling us to have a continuum bump as a
signature of gamma-ray excess in indirect detection experiments of dark matter
(DM), postulating a generic dark sector having (at least) two DM candidates.
With the assumption of non-zero mass gap between the two DM candidates, the
heavier one directly communicates to the partner of the lighter one. Such a
partner then decays into a lighter DM particle along with an "axion-like"
particle (ALP) or dark "pion", which subsequently decays into a pair of
photons, via a more-than-one step cascade decay process. Since the cascade is
initiated by the dark partner obtaining a non-trivial fixed boost factor, a
continuum gamma-ray energy spectrum naturally arises even with a particle
directly decaying into two photons. We apply the main idea to the energy
spectrum of the GeV gamma-rays from around the Galactic Center (GC), and find
that the relevant observational data is well-reproduced by the theory
expectation predicted by the proposed mechanism. Remarkably, the relevant
energy spectrum has a robust peak at half the mass of the ALP or dark pion, as
opposed to popular DM models directly annihilating to Standard Model particles
where physical interpretations of the energy peak are not manifest. Our data
analysis reports substantially improved fits, compared to those annihilating DM
models, and ~900 MeV mass of the ALP or dark pion.


  We argue that a small or large CP-violating asymmetry {\cal A}_{\psi K_S} in
B^0_d vs \bar{B}^0_d --> J/\psi K_S decays, which seems to be favored by the
recent BaBar or Belle data, might hint at the existence of new physics in B^0_d
- \bar{B}^0_d mixing. We present a model-independent framework to show how new
physics in B^0_d - \bar{B}^0_d mixing modifies the standard-model CP-violating
asymmetry {\cal A}^{\rm SM}_{\psi K_S}. We particularly emphasize that an
experimental confirmation of {\cal A}_{\psi K_S} \approx {\cal A}^{\rm
SM}_{\psi K_S} must not imply the absence of new physics in B^0_d - \bar{B}^0_d
mixing.


  Edges of an image are considered a crucial type of information. These can be
extracted by applying edge detectors with different methodology. Edge detection
is a vital step in computer vision tasks, because it is an essential issue for
pattern recognition and visual interpretation. In this paper, we propose a new
method for edge detection in images, based on the estimation by kernel of the
probability density function. In our algorithm, pixels in the image with
minimum value of density function are labeled as edges. The boundary between
two homogeneous regions is defined in two domains: the spatial/lattice domain
and the range/color domain. Extensive experimental evaluations proved that our
edge detection method is significantly a competitive algorithm.


  Laser powder bed fusion (LPBF) is an additive manufacturing (AM) technology.
To achieve high product quality, the powder is best spread as a uniform, dense
layer. The challenge for LPBF manufacturers is to develop a spreading process
that can produce a consistent layer quality for the many powders used, which
show considerable differences in spreadability. Therefore, we investigate the
influence of material properties, process parameters and the type of spreading
tool on the layer quality. The discrete particle method is used to simulate the
spreading process and to define metrics to evaluate the powder layer
characteristics. We found that particle shape and surface roughness in terms of
rolling resistance and interparticle sliding friction as well as particle
cohesion all have a major (sometimes surprising) influence on the powder layer
quality: more irregular shaped particles, rougher particle surfaces and/or
higher interfacial cohesion usually, but not always, lead to worse
spreadability. Our findings illustrate that there is a trade-off between
material properties and process parameters. Increasing the spreading speed
decreases layer quality for non- and weakly cohesive powders, but improves it
for strongly cohesive ones. Using a counter-clockwise rotating roller as a
spreading tool improves the powder layer quality compared to spreading with a
blade. Finally, for both geometries, a unique correlation between the quality
criteria uniformity and mass fraction is reported and some of the findings are
related to size-segregation during spreading.


  Classical single-mode fiber interferometers, using one fiber per aperture,
have very limited imaging capabilities and small field of view. Observations of
extended sources (resolved by one aperture) cannot be fully corrected for
wavefront aberrations: accurate measurements of object visibilities are then
made very difficult from ground-based fiber interferometers. These limitations
are very severe for the new generation of interferometers, which make use of
large telescopes equipped with adaptive optics, but can be overcome by using
several fibers per aperture. This technique improves the wide field imaging
capabilities of both ground-based and space interferometers.


  An overview of the searches for the Standard Model Higgs boson at the LHC is
presented. The main Higgs production and decay modes that have been studied are
introduced, and the analysis techniques and the recent developments done by the
ATLAS and CMS experiments are described. Some preliminary results from current
studies are included. The discovery potential within the first few years of
physics running is evaluated.


  We study the maximum number of quads among $\ell$ cards from an EvenQuads
deck of size $2^n$. This corresponds to enumerating quadruples of integers in
the range $[0,\ell-1]$ such that their bitwise XOR is zero. In this paper, we
conjecture a formula that calculates the maximum number of quads among $\ell$
cards.


  Motivated by the increasing interest in the posit numeric format, in this
paper we evaluate the accuracy and efficiency of posit arithmetic in contrast
to the traditional IEEE 754 32-bit floating-point (FP32) arithmetic. We first
design and implement a Posit Arithmetic Unit (PAU), called POSAR, with flexible
bit-sized arithmetic suitable for applications that can trade accuracy for
savings in chip area. Next, we analyze the accuracy and efficiency of POSAR
with a series of benchmarks including mathematical computations, ML kernels,
NAS Parallel Benchmarks (NPB), and Cifar-10 CNN. This analysis is done on our
implementation of POSAR integrated into a RISC-V Rocket Chip core in comparison
with the IEEE 754-based Floting Point Unit (FPU) of Rocket Chip. Our analysis
shows that POSAR can outperform the FPU, but the results are not spectacular.
For NPB, 32-bit posit achieves better accuracy than FP32 and improves the
execution by up to 2%. However, POSAR with 32-bit posit needs 30% more FPGA
resources compared to the FPU. For classic ML algorithms, we find that 8-bit
posits are not suitable to replace FP32 because they exhibit low accuracy
leading to wrong results. Instead, 16-bit posit offers the best option in terms
of accuracy and efficiency. For example, 16-bit posit achieves the same Top-1
accuracy as FP32 on a Cifar-10 CNN with a speedup of 18%.


  We study non-equilibrium analogues of surface phase transitions in a minimal
model of active particles in contact with a purely repulsive potential barrier
that mimics a thin porous membrane. Under conditions of bulk motility-induced
phase separation, the interaction strength $\varepsilon_w$ of the barrier
controls the affinity of the dense phase for the barrier region. We uncover
clear signatures of a wetting phase transition as $\varepsilon_w$ is varied. In
common with its equilibrium counterpart, the character of this transition
depends on the system dimensionality: a continuous transition with large
density fluctuations and gas bubbles is uncovered in 2d while 3d systems
exhibit a sharp transition absent of large correlations.


  Branched polymers can be classified into two categories that obey the
different formulae: \begin{equation} \nu= \begin{cases}
\hspace{1mm}\displaystyle\frac{2(1+\nu_{0})}{d+2} & \hspace{3mm}\mbox{for
polymers
with}\hspace{2mm}\displaystyle\nu_{0}\ge\frac{1}{d+1}\hspace{10mm}\text{(I)}\\[3mm]
\hspace{5mm}2\nu_{0}& \hspace{3mm}\mbox{for polymers
with}\hspace{2mm}\displaystyle\nu_{0}\le\frac{1}{d+1}\hspace{10mm}\text{(II)}
\end{cases}\notag \end{equation} for the dilution limit in good solvents. The
category II covers the exceptional polymers having fully expanded
configurations. On the basis of these equalities, we discuss the size exponents
of the nested architectures and the lattice trees. In particular, we compare
our preceding result, $\nu_{d=2}=1/2$, for the $z$=2 polymer having
$\nu_{0}=1/4$ with the numerical result, $\nu_{d=2}\doteq 0.64115$, for the
lattice trees generated on the 2-dimensional lattice. Our conjecture is that
while both the conclusions in polymer physics and condensed matter physics are
correct, the discrepancy arises from the fact that the lattice trees are
constructed from less branched architectures than the branched polymers having
$\nu_{0} = 1/4$ in polymer physics. The present analysis suggests that the
2-dimensional lattice trees are the mixture of isomers having the mean ideal
size exponent of $\bar{\nu}_{0}\doteq0.32$.


  The Jones polynomial and Khovanov homology of a classical link are invariants
that depend upon an initial choice of orientation for the link. In this paper,
we give a Khovanov homology theory for unoriented virtual links. The graded
Euler characteristic of this homology is proportional to a similarly-defined
unoriented Jones polynomial for virtual links, which is a new invariant in the
category of non-classical virtual links. The unoriented Jones polynomial
continues to satisfy an important property of the usual one: for classical or
even virtual links, the unoriented Jones polynomial evaluated at one is two to
the power of the number of components of the link. As part of extending the
main results of this paper to non-classical virtual links, a new framework for
computing integral Khovanov homology is described that can be efficiently and
effectively implemented on a computer. We define an unoriented Lee homology
theory for virtual links based upon the unoriented version of Khovanov
homology.


  In this paper a novel low-storage method for time-resolved databases is
presented. This approach reduces the storage cost of time-resolved databases by
storing filtered flow fields that target the large and intermediate scales,
while retaining all the information needed to fully reconstruct the flow at the
level of filtered flow fields and complete second-order statistics. This is
done by storing also the filtered turbulent stresses, allowing to recover the
exact effect of the small scales on the large and intermediate scales. A
significant speed-up of the computations is achieved, first, by relaxing the
numerical resolution, which is shown to affect only the dynamics close to the
wall, but not the large scales stored in the database, and, second, by
exploiting the \change{computing power and efficiency} of GPU co-processors
using a new high-resolution hybrid CUDA-MPI code. This speed-up allows running
for physically meaningful times to capture the dynamics of the large scales.
The resulting temporally resolved large-scale database of a turbulent channel
flow up to $Re_\tau=5300$, in large boxes for long times, is briefly
introduced, showing significant indicators of large-scale dynamics with
characteristic times of the order of up to eight eddy turnover times.


  We explore the possibility of unification of gauge couplings near the Planck
scale in models of extended technicolor. We observe that models of the form G X
SU(3)_c X SU(2)_L X U(1)_Y cannot be realized, due to the presence of massless
neutral Goldstone bosons (axions) and light charged pseudo-Goldstone bosons;
thus, unification of the known forces near the Planck scale cannot be achieved.
The next simplest possibility, G X SU(4)_{PS} X SU(2)_L X U(1)_{T_{3R}}, cannot
lead to unification of the Pati-Salam and weak gauge groups near the Planck
scale. However, superstring theory provides relations between couplings at the
Planck scale without the need for an underlying grand-unified gauge group,
which allows unification of the SU(4)$_{PS}$ and SU(2)$_L$ couplings.


  I propose that the ground state of the 2D $t$-$J$ model near half-filling
with $J/t\sim1/3$ has both ferromagnetic and antiferromagnetic fluctuations
leading to a magnetically frustrated ground state. I further argue that the
frustrated state is spin-charge separated to account for the observed behavior
of the equal time spin and charge correlation functions.


  The volume distance from a point p to a convex hypersurface M of the
(N+1)-dimensional space is defined as the minimum (N+1)-volume of a region
bounded by M and a hyperplane H through the point. This function is
differentiable in a neighborhood of M and if we restrict its hessian to the
minimizing hyperplane H(p) we obtain, after normalization, a symmetric
bi-linear form Q.
  In this paper, we prove that Q converges to the affine Blaschke metric when
we approximate the hypersurface along a curve whose points are centroids of
parallel sections. We also show that the rate of this convergence is given by a
bilinear form associated with the shape operator of M. These convergence
results provide a geometric interpretation of the Blaschke metric and the shape
operator in terms of the volume distance.


  We provide an explicit combinatorial description of the embedding of the
crystal of Kashiwara-Nakashima tableaux in types $B$ and $C$ into that of
$\bi$-Lusztig data associated to a family of reduced expressions $\bi$ of the
longest element $w_0$. The description of the embedding is simple and
elementary using only the Sch\"{u}tzenberger's jeu de taquin and RSK algorithm.
A spinor model for classical crystals plays an important role as an
intermediate object connecting Kashiwara-Nakashima tableaux and Lusztig data.


  Using PCA data from the Rossi X-Ray Timing Explorer (RXTE), we track the
spectral states of the neutron star transient system Aql X-1 through a complete
outburst cycle. We find a hard-to-soft state transition during the very early,
rising phase of the outburst and show that there is a hysteresis effect such
that the transition back to the hard state occurs at a luminosity $\sim $ 5
times {\it lower} than the hard-to-soft transition. This hysteresis effect
rules out the propeller mechanism as the sole cause of state transitions in Aql
X-1. Assuming the propeller mechanism only operates at a luminosity equal to or
below that of the observed soft-to-hard transition requires that the magnetic
field of Aql X-1 be less than $7\times 10^7$ Gauss, the lowest neutron star
field known to date. To compare the state transition behavior of Aql X-1 with
that found in transient black hole systems, we use RXTE ASM data to compute
hardness-intensity diagrams for four black hole candidate transients where the
ASM data should also give us state information throughout much of the outburst
cycles. In all four systems, we find evidence for a hard-to-soft state
transition during the rising outburst phase and for the source staying in a
soft state down to much lower luminosities during the declining phase, i.e., a
hysteresis effect. This similarity suggests a common origin for state
transitions in low magnetic field neutron star and black hole systems, and the
hysteresis effect rules out the ``Strong ADAF Principle'' for determining the
state of an accretion disc. We discuss the general implications of these
observations for current models of state transitions. We note the contrast to
previous observations of the non-transient systems Cygnus X-1 and X-3 which do
not show a hysteresis effect.


  This paper proposes two algorithms, namely "back-tracking" and "history
following", to reach consensus in case of communication loss for a network of
distributed agents with switching topologies. To reach consensus in distributed
control, considered communication topology forms a strongly connected graph.
The graph is no more strongly connected whenever an agent loses
communication.Whenever an agent loses communication, the topology is no more
strongly connected. The proposed back-tracking algorithm makes sure that the
agent backtracks its position unless the communication is reestablished, and
path is changed to reach consensus. In history following, the agents use their
memory and move towards previous consensus point until the communication is
regained. Upon regaining communication, a new consensus point is calculated
depending on the current positions of the agents and they change their
trajectories accordingly. Simulation results, for a network of six agents, show
that when the agents follow the previous history, the average consensus time is
less than that of back-tracking. However, situation may arise in history
following where a false notion of reaching consensus makes one of the agents
stop at a point near to the actual consensus point. An obstacle avoidance
algorithm is integrated with the proposed algorithms to avoid collisions.
Hardware implementation for a three robots system shows the effectiveness of
the algorithms.


  Short TCP flows that are critical for many interactive applications in data
centers are plagued by large flows and head-of-line blocking in switches.
Hash-based load balancing schemes such as ECMP aggravate the matter and result
in long-tailed flow completion times (FCT). Previous work on reducing FCT
usually requires custom switch hardware and/or protocol changes. We propose
RepFlow, a simple yet practically effective approach that replicates each short
flow to reduce the completion times, without any change to switches or host
kernels. With ECMP the original and replicated flows traverse distinct paths
with different congestion levels, thereby reducing the probability of having
long queueing delay. We develop a simple analytical model to demonstrate the
potential improvement of RepFlow. Extensive NS-3 simulations and Mininet
implementation show that RepFlow provides 50%--70% speedup in both mean and
99-th percentile FCT for all loads, and offers near-optimal FCT when used with
DCTCP.


  We construct codimension 1 surfaces of any dimension that minimize a periodic
nonlocal perimeter functional among surfaces that are periodic, cylindrically
symmetric and decreasing.
  These surfaces may be seen as a nonlocal analogue of the classical Delaunay
surfaces (onduloids). For small volume, most of their mass tends to be
concentrated in a periodic array and the surfaces are close to a periodic array
of balls (in fact, we give explicit quantitative bounds on these facts).


  Integrable hierarchy based on the constrained Osp(2$\mid%2) connection is
considered. The connection with 2D supergravity and some analogies with the
W$_3^{(2)}$ case are given. It is shown that super Virasoro transformations are
symmetries of tha hierarchy.


  In photometry of $\gamma$ Cas (B0.5 IVe) from the SMEI and
BRITE-Constellation satellites, indications of low-order non-radial pulsation
have recently been found, which would establish an important commonality with
the class of classical Be stars at large. New photometry with the TESS
satellite has detected three frequency groups near 1.0 ($g1$), 2.4 ($g2$), and
5.1 ($g3$) d$^{-1}$, respectively. Some individual frequencies are nearly
harmonics or combination frequencies but not exactly so. Frequency groups are
known from roughly three quarters of all classical Be stars and also from
pulsations of $\beta$ Cep, SPB, and $\gamma$ Dor stars and, therefore, firmly
establish $\gamma$ Cas as a non-radial pulsator. The total power in each
frequency group is variable. An isolated feature exists at 7.57 d$^{-1}$ and,
together with the strongest peaks in the second and third groups ordered by
increasing frequency ($g2$ and $g3$), is the only one detected in all three
TESS sectors. The former long-term 0.82 d$^{-1}$ variability would fall into
$g1$ and has not returned at a significant level, questioning its attribution
to rotational modulation. Low-frequency stochastic variability is a dominant
feature of the TESS light curve, possibly caused by internal gravity waves
excited at the core-envelope interface. These are known to be efficient at
transporting angular momentum outward, and may also drive the oscillations that
constitute $g1$ and $g2$. The hard X-ray flux of $\gamma$ Cas is the only
remaining major property that distinguishes this star from the class of
classical Be stars.


  Hexagonal boron nitride (h-BN), a prevalent insulating crystal for dielectric
and encapsulation layers in two-dimensional (2D) nanoelectronics and a
structural material in 2D nanoelectromechanical systems (NEMS), has also
rapidly emerged as a promising platform for quantum photonics with the recent
discovery of optically active defect centers and associated spin states.
Combined with measured emission characteristics, here we propose and
numerically investigate the cavity quantum electrodynamics (cavity-QED) scheme
incorporating these defect-enabled single photon emitters (SPEs) in h-BN
microdisk resonators. The whispering-gallery nature of microdisks can support
multiple families of cavity resonances with different radial and azimuthal mode
indices simultaneously, overcoming the challenges in coinciding a single point
defect with the maximum electric field of an optical mode both spatially and
spectrally. The excellent characteristics of h-BN SPEs, including exceptional
emission rate, considerably high Debye-Waller factor, and Fourier transform
limited linewidth at room temperature, render strong coupling with the ratio of
coupling to decay rates g/max({\gamma},\k{appa}) predicated as high as 500.
This study not only provides insight into the emitter-cavity interaction, but
also contributes toward realizing h-BN photonic components, such as
low-threshold microcavity lasers and high-purity single photon sources,
critical for linear optics quantum computing and quantum networking
applications.


  Answering questions within business and finance requires reasoning,
precision, and a wide-breadth of technical knowledge. Together, these
requirements make this domain difficult for large language models (LLMs). We
introduce BizBench, a benchmark for evaluating models' ability to reason about
realistic financial problems. BizBench comprises eight quantitative reasoning
tasks, focusing on question-answering (QA) over financial data via program
synthesis. We include three financially-themed code-generation tasks from newly
collected and augmented QA data. Additionally, we isolate the reasoning
capabilities required for financial QA: reading comprehension of financial text
and tables for extracting intermediate values, and understanding financial
concepts and formulas needed to calculate complex solutions. Collectively,
these tasks evaluate a model's financial background knowledge, ability to parse
financial documents, and capacity to solve problems with code. We conduct an
in-depth evaluation of open-source and commercial LLMs, comparing and
contrasting the behavior of code-focused and language-focused models. We
demonstrate that the current bottleneck in performance is due to LLMs' limited
business and financial understanding, highlighting the value of a challenging
benchmark for quantitative reasoning within this domain.


  In the previous paper hep-th/0312199 we studied the 't Hooft-Polyakov (TP)
monopole configuration in the U(2) gauge theory on the fuzzy 2-sphere and
showed that it has a nonzero topological charge in the formalism based on the
Ginsparg-Wilson relation. In this paper, by showing that the TP monopole
configuration is stabler than the U(2) gauge theory without any condensation in
the Yang-Mills-Chern-Simons matrix model, we will present a mechanism for
dynamical generation of a nontrivial index. We further analyze the instability
and decay processes of the U(2) gauge theory and the TP monopole configuration.