  A large class of symmetry-protected topological phases (SPT) in boson / spin
systems have been recently predicted by the group cohomology theory. In this
work, we consider SPT states at least with charge symmetry (U(1) or Z$_N$) or
spin $S^z$ rotation symmetry (U(1) or Z$_N$) in 2D, 3D, and the surface of 3D.
If both are U(1), we apply external electromagnetic field / `spin gauge field'
to study the charge / spin response. For the SPT examples we consider (i.e.
U$_c$(1)$\rtimes$Z$^T_2$, U$_s$(1)$\times$Z$^T_2$,
U$_c$(1)$\times$[U$_s$(1)$\rtimes$Z$_2$]; subscripts $c$ and $s$ are short for
charge and spin; Z$^T_2$ and Z$_2$ are time-reversal symmetry and
$\pi$-rotation about $S^y$, respectively), many variants of Witten effect in
the 3D SPT bulk and various versions of anomalous surface quantum Hall effect
are defined and systematically investigated. If charge or spin symmetry reduces
to Z$_N$ by considering charge-$N$ or spin-$N$ condensate, instead of the
linear response approach, we gauge the charge/spin symmetry, leading to a
dynamical gauge theory with some remaining global symmetry. The 3D dynamical
gauge theory describes a symmetry-enriched topological phase (SET), i.e. a
topologically ordered state with global symmetry which admits nontrivial ground
state degeneracy depending on spatial manifold topology. For the SPT examples
we consider, the corresponding SET states are described by dynamical
topological gauge theory with topological BF term and axionic $\Theta$-term in
3D bulk. And the surface of SET is described by the chiral boson theory with
quantum anomaly.


  We begin an investigation of the action of pseudo-Anosov elements of
$\mathrm{Out}(\mathbf{F}_{2})$ on the Markoff-type varieties \[
\mathbb{X}_{\kappa}:\:x^{2}+y^{2}+z^{2}=xyz+2+\kappa \] over finite fields
$\mathbb{F}_{p}$ with $p$ prime. We first make a precise conjecture about the
permutation group generated by $\mathrm{Out}(\mathbf{F}_{2})$ on
$\mathbb{X}_{-2}(\mathbb{F}_{p})$ that shows there is no obstruction at the
level of the permutation group to a pseudo-Anosov acting `generically'. We
prove that this conjecture is sharp. We show that for a fixed pseudo-Anosov
$g\in\mathrm{Out}(\mathbf{F}_{2})$, there is always an orbit of $g$ of length
$\geq C\log p+O(1)$ on $\mathbb{X}_{\kappa}(\mathbb{F}_{p})$ where $C>0$ is
given in terms of the eigenvalues of $g$ viewed as an element of
$\mathrm{GL}_{2}(\mathbf{Z})$. This improves on a result of Silverman (2007)
that applies to general morphisms of quasi-projective varieties. We have
discovered that the asymptotic $(p\to\infty)$ behavior of the longest orbit of
a fixed pseudo-Anosov $g$ acting on $\mathbb{X}_{-2}(\mathbb{F}_{p})$ is
dictated by a dichotomy that we describe both in combinatorial terms and in
algebraic terms related to Gauss's ambiguous binary quadratic forms, following
Sarnak. This dichotomy is illustrated with numerics, based on which we
formulate a precise conjecture.


  Statistical classification of the Helios solar wind observations into several
populations sorted by bulk speed has revealed an outward acceleration of the
wind. The faster the wind is, the smaller is this acceleration in the 0.3 - 1
au radial range (Maksimovic et al. 2020). In this article we show that recent
measurements from the Parker Solar Probe (PSP) are compatible with an extension
closer to the Sun of the latter Helios classification. For instance the well
established bulk speed/proton temperature (u,Tp) correlation and bulk
speed/electron temperature (u,Te) anti-correlation, together with the
acceleration of the slowest winds, are verified in PSP data. We also model the
combined PSP and Helios data, using empirical Parker-like models for which the
solar wind undergoes an "iso-poly" expansion: isothermal in the corona, then
polytropic at distances larger than the sonic point radius. The polytropic
indices are derived from the observed temperature and density gradients. Our
modelling reveals that the electron thermal pressure has a major contribution
in the acceleration process of slow and intermediate winds (in the range of
300-500 km/s at 1 au), over a broad range of distances and that the global
(electron and protons) thermal energy, alone, is able to explain the
acceleration profiles. Moreover, we show that the very slow solar wind requires
in addition to the observed pressure gradients, another source of acceleration.


  We study momentum-resolved tunneling into a system of spinless chiral
one-dimensional fermions, such as electrons at the edge of an integer quantum
Hall system. Interactions between particles give rise to broadening of the
spectral function of the system. We develop an approach that enables one to
obtain the shape of the peak in the spectral function in the regime of strong
interaction. We apply our technique to the special cases of short-range and
Coulomb interactions.


  We consider a superfluid of trapped fermionic atoms and study the single
vortex solution in the Ginzburg-Landau regime. We define simple analytical
estimates for the main characteristics of the system, such as the vortex core
size, temperature regimes for the existence of a vortex, and the effects of
rotation and interactions with normal fermions. The parameter dependence of the
vortex core size (healing length) is found to be essentially different from
that of the healing length in metallic superconductors or in trapped atomic BEC
in the Thomas-Fermi limit. This is an indication of the importance of the
confining geometry for the properties of fermionic superfluids.


  We construct an explicit K3 surface over the field of rational numbers that
has geometric Picard rank one, and for which there is a transcendental
Brauer-Manin obstruction to weak approximation. To do so, we exploit the
relationship between polarized K3 surfaces endowed with particular kinds of
Brauer classes and cubic fourfolds.


  The fermionic gyromagnetic ratio g= 2 of the Kerr-Newman spacetime cannot be
a computational "coincidence". This naturally immerges in a four dimensional
generally covariant modified Yang-Mills action, which depends on the lorentzian
complex structure of spacetime and not its metric. This metric independence
makes the model renormalizable. It is a counter example to the general belief
that "string theory is the only selfconsistent quantum model which includes
gravity". The other properties of the model are phenomenologically very
interesting too. The modified Yang-Mills action generates a linear potential,
instead of the Coulomb-like (1/r) potential of the ordinary action. Therefore
the Yang-Mills excitations must be perturbatively confined. This separates the
solutions of the model into the vacuum bosonic sector of the periodic
configurations, the "leptonic" sector with fermionic solitons and their gauge
field excitations, the "hadronic" sector. Simple integrability conditions of
the pure geometric equations imply a limited number of "leptonic" and
"hadronic" families. The geometric surfaces are generally inside the SU(2,2)
classical domain. Soliton spin and gravity measure how much the surface
penetrates inside the classical domain. The i0 point of infinity breaks the
SU(2,2) symmetry down to the Poincare and dilation groups. A scaling breaking
mechanism is presented. Hence the pure geometric modes and asymptotically flat
solitons of the model must belong to representations of the Poincare group. The
metrics compatible to the lorentzian complex structure are induced by a Kaehler
metric and the spacetime is a totally real lagrangian submanifold of a Kaehler
manifold. This opens up the possibility to use the geometric quantization
directly to the solitonic surfaces of the model, considering their
corresponding Kaehler symplectic manifold as their phase space.


  We perform a global parton fit to DIS and related data, including
next-to-leading logarithmic (NLL) BFKL resummations in both the massless and
massive sectors. The resummed fit improves over a standard next-to-leading
order (NLO) DGLAP fit, with a positive definite gluon at the input scale as
opposed to the negative gluon seen at NLO. Furthermore, the predicted
longitudinal structure function is free of perturbative instability at small x,
and the reduced cross-section shows a turnover at high y (absent in the NLO
fit) consistent with the HERA data.


  This paper deals with new proposals for the design of passive solutions
adapted to the climate of the highlands of Madagascar. While the strongest
population density is located in the central highlands, the problem of thermal
comfort in buildings occurs mainly during winter time. Currently, people use
raw wood to warm the poorly designed houses. This leads to a large scale
deforestation of the areas and causes erosion and environmental problems. The
methodology used consisted of the identification of a typical building and of a
typical meteorological year. Simulations were carried out using a thermal and
airflow software (CODYRUN) to improve each building component (roof, walls,
windows, and soil) in such a way as to estimate the influence of some technical
solutions on each component in terms of thermal comfort. The proposed solutions
also took into account the use of local materials and the standard of living of
the country.


  Debugging, finding and fixing bugs in code, is a heterogeneous process that
shapes novice learners' self-beliefs and motivation in computing. Our Debugging
by Design intervention (DbD) provocatively puts students in control over bugs
by having them collaborate on designing creative buggy projects during an
electronic textiles unit in an introductory computing course. We implemented
DbD virtually in eight classrooms with two teachers in public schools with
historically marginalized populations, using a quasi-experimental design. Data
from this study included post-activity results from a validated survey
instrument (N=144). For all students, project completion correlated with
increased computer science creative expression and e-textiles coding
self-efficacy. In the comparison classes, project completion correlated with
reduced programming anxiety, problem-solving competency beliefs, and
programming self-concept. In DbD classes, project completion is uniquely
correlated with increased fascination with design and programming growth
mindset. In the discussion, we consider the relative benefits of DbD versus
other open-ended projects.


  We systematically measured and compared the mechanical losses of various
kinds of bulk fused silica. Their quality factors ranged widely from 7x10^5 to
4x10^7, the latter being one of the highest reported among bulk fused silica.
We observed frequency-dependent losses and a decrease in the losses upon
annealing.


  We have examined polycrystalline MgB2 by electron energy loss spectroscopy
(EELS) and density of state calculations. In particular, we have studied two
different crystal orientations, [110] and [001] with respect to the incident
electron beam direction, and found significant changes in the near-edge
fine-structure of the B K-edge. Density functional theory suggests that the
pre-peak of the B K-edge core loss is composed of a mixture of pxy and pz hole
states and we will show that these contributions can be distinguished only with
an experimental energy resolution better than 0.5 eV. For conventional TEM/STEM
instruments with an energy resolution of ~1.0 eV the pre-peak still contains
valuable information about the local charge carrier concentration that can be
probed by core-loss EELS. By considering the scattering momentum transfer for
different crystal orientations, it is possible to analytically separate pxy and
pz components from of the experimental spectra With careful experiments and
analysis, EELS can be a unique tool measuring the superconducting properties of
MgB2, doped with various elements for improved transport properties on a
sub-nanometer scale.


  A method for photoacoustic tomography is presented that uses circular
integrals of the acoustic wave for the reconstruction of a three-dimensional
image. Image reconstruction is a two-step process: In the first step data from
a stack of circular integrating are used to reconstruct the circular projection
of the source distribution. In the second step the inverse circular Radon
transform is applied. In this article we establish inversion formulas for the
first step, which involves an inverse problem for the axially symmetric wave
equation. Numerical results are presented that show the validity and robustness
of the resulting algorithm.


  We present a novel RG approach to 2D random XY models using direct and
replicated Coulomb gas methods. By including fusion of environments (charge
fusion in the replicated CG) it follows the distribution of local disorder,
found to obey a Kolmogorov non linear equation (KPP) with traveling wave
solutions. At low T and weak disorder it yields a glassy XY phase with broad
distributions and precise connections to Derrida's GREM. Finding marginal
operators at the disorder-induced transition is related to the front velocity
selection problem in KPP equations yielding new critical behaviour. The method
is applied to critical random Dirac problems.


  A crucial yet challenging issue in quantum metrology is to ascertain the
ultimate precision achievable in estimation strategies. While there are two
paradigms of estimations, local and global, current research is largely
confined to local estimations, which are useful once the parameter of interest
is approximately known. In this Letter we target a paradigm shift towards
global estimations, which can operate reliably even with a few measurement data
and no substantial prior knowledge about the parameter. The key innovation here
is to develop a technique, dubbed virtual imaginary time evolution, capable of
mapping global estimations into local ones. This offers an intriguing pathway
to surmount challenges in the realm of global estimations by leveraging
powerful tools tailored for local estimations. We explore our technique to
unveil a strict hierarchy of achievable precision for different global
estimation strategies, including parallel, sequential, and
indefinite-causal-order strategies.


  For a microscopic model of a Josephson junction the normal coordinates of the
two junction Goldstone bosons are constructed and their dynamical spectrum is
computed. The explicit dependence on the phase difference of the two
superconductors is calculated.


  The class of minimal difference partitions MDP($q$) (with gap $q$) is defined
by the condition that successive parts in an integer partition differ from one
another by at least $q\ge 0$. In a recent series of papers by A. Comtet and
collaborators, the MDP($q$) ensemble with uniform measure was interpreted as a
combinatorial model for quantum systems with fractional statistics, that is,
interpolating between the classic Bose-Einstein ($q=0$) and Fermi-Dirac ($q=1$)
cases. This was done by formally allowing values $q \in (0,1)$ using an
analytic continuation of the limit shape of the corresponding Young diagrams
calculated for integer $q$. To justify this "replica-trick", we introduce a
more general model based on a variable MDP-type condition encoded by an integer
sequence $(q_i)$, whereby the (limiting) gap $q$ is naturally interpreted as
the Ces\`aro mean of $(q_i)$. In this model, we find the family of limit shapes
parameterized by $q \in [0,\infty)$ confirming the earlier answer, and also
obtain the asymptotics of the number of parts.


  Pion exchange is the central ingredient to nucleon-nucleon interactions used
in nuclear structure calculations, and one pion exchange (OPE) enters at
leading order in chiral effective field theory. In the $^{2S+1}L_J={^1S_0}$
partial wave, however, OPE and a contact term needed for proper renormalization
fail to produce the qualitative, and quantitative, features of the scattering
phase shifts. Cutoff variation also revealed a surprisingly low breakdown
momentum of about 330 MeV in this partial wave. Here we show that potentials
consisting of OPE, two pion exchange (TPE), and a single contact address these
problems and yield accurate and renormalization group (RG) invariant phase
shifts in the $^1S_0$ partial wave. We demonstrate that a leading-order
potential with TPE can be systematically improved by adding a contact quadratic
in momenta. For momentum cutoffs below about 500 MeV, the removal of relevant
physics from TPE loops needs to be compensated by additional contacts to keep
RG invariance. Inclusion of the $\Delta$ isobar degree of freedom in the
potential does not change the strong contributions of TPE.


  We consider the real time dynamics of an initially localized distinguishable
impurity injected into the ground state of the Lieb-Liniger model. Focusing on
the case where integrability is preserved, we numerically compute the time
evolution of the impurity density operator in regimes far from analytically
tractable limits. We find that the injected impurity undergoes a stuttering
motion as it moves and expands. For an initially stationary impurity, the
interaction-driven formation of a quasibound state with a hole in the
background gas leads to arrested expansion -- a period of quasistationary
behavior. When the impurity is injected with a finite center of mass momentum,
the impurity moves through the background gas in a snaking manner, arising from
a quantum Newton's cradle-like scenario where momentum is exchanged
back-and-forth between the impurity and the background gas.


  We discuss Bayesian methods for learning Bayesian networks when data sets are
incomplete. In particular, we examine asymptotic approximations for the
marginal likelihood of incomplete data given a Bayesian network. We consider
the Laplace approximation and the less accurate but more efficient BIC/MDL
approximation. We also consider approximations proposed by Draper (1993) and
Cheeseman and Stutz (1995). These approximations are as efficient as BIC/MDL,
but their accuracy has not been studied in any depth. We compare the accuracy
of these approximations under the assumption that the Laplace approximation is
the most accurate. In experiments using synthetic data generated from discrete
naive-Bayes models having a hidden root node, we find that the CS measure is
the most accurate.


  Ranked set sampling is a sampling design which has a wide range of
applications in industrial statistics, and environmental and ecological
studies, etc.. It is well known that ranked set samples provide more Fisher
information than simple random samples of the same size about the unknown
parameters of the underlying distribution in parametric inferences. In this
paper, we consider the uncertainty and information content of ranked set
samples in both perfect and imperfect ranking scenarios in terms of Shannon
entropy, R\'enyi and Kullback-Leibler (KL) information measures. It is proved
that under these information measures, ranked set sampling design performs
better than its simple random sampling counterpart of the same size. The
information content is also a monotone function of the set size in ranked set
sampling. Moreover, the effect of ranking error on the information content of
the data is investigated.


  Recent approaches in Incomplete Utterance Rewriting (IUR) fail to capture the
source of important words, which is crucial to edit the incomplete utterance,
and introduce words from irrelevant utterances. We propose a novel and
effective multi-task information interaction framework including context
selection, edit matrix construction, and relevance merging to capture the
multi-granularity of semantic information. Benefiting from fetching the
relevant utterance and figuring out the important words, our approach
outperforms existing state-of-the-art models on two benchmark datasets
Restoration-200K and CANAND in this field. Code will be provided on
\url{https://github.com/yanmenxue/QR}.


  We extend the variational cluster approach to deal with strongly correlated
lattice bosons in the superfluid phase. To this end, we reformulate the
approach within a pseudoparticle formalism, whereby cluster excitations are
described by particlelike excitations. The approximation amounts to solving a
multicomponent noninteracting bosonic system by means of a multimode Bogoliubov
approximation. A source-and-drain term is introduced in order to break U(1)
symmetry at the cluster level. We provide an expression for the grand
potential, the single-particle normal and anomalous Green's functions, the
condensate density, and other static quantities. As a first nontrivial
application of the method we choose the two-dimensional Bose-Hubbard model and
evaluate results in both the Mott and the superfluid phases. Our results show
an excellent agreement with quantum Monte Carlo calculations.


  Notions of convergence and continuity specifically adapted to Riesz ideals I
of the space of continuous real-valued functions on a Lindel\"of locally
compact Hausdorff space are given, and used to prove Stone-Weierstra{\ss}-type
theorems for I. As applications, sufficient conditions are discussed that
guarantee that various types of positive linear maps on I are uniquely
determined by their restriction to various point-separating subsets of I. A
very special case of this is the characterization of the strong determinacy of
moment problems, which is rederived here in a rather general setting and
without making use of spectral theory.


  In photonic crystals the propagation of light is governed by their photonic
band structure, an ensemble of propagating states grouped into bands, separated
by photonic band gaps. Due to discrete symmetries in spatially strictly
periodic dielectric structures their photonic band structure is intrinsically
anisotropic. However, for many applications, such as manufacturing artificial
structural color materials or developing photonic computing devices, but also
for the fundamental understanding of light-matter interactions, it is of major
interest to seek materials with long range non-periodic dielectric structures
which allow the formation of {\it isotropic} photonic band gaps. Here, we
report the first ever 3D isotropic photonic band gap for an optimized
disordered stealthy hyperuniform structure for microwaves. The transmission
spectra are directly compared to a diamond pattern and an amorphous structure
with similar node density. The band structure is measured experimentally for
all three microwave structures, manufactured by 3D-Laser-printing for
meta-materials with refractive index up to $n=2.1$. Results agree well with
finite-difference-time-domain numerical investigations and a priori
calculations of the band-gap for the hyperuniform structure: the diamond
structure shows gaps but being anisotropic as expected, the stealthy
hyperuniform pattern shows an isotropic gap of very similar magnitude, while
the amorphous structure does not show a gap at all. The centimeter scaled
microwave structures may serve as prototypes for micrometer scaled structures
with bandgaps in the technologically very interesting region of infrared (IR).


  JEM-EUSO, on board of the Japanese Exploration Module of the International
Space Station, is being proposed as the first space observatory devoted to
UHECR. Its privileged position at 430 km above the Earth surface, combined with
a large field of view, innovative optics and a high efficiency focal surface,
results in an unprecedented exposure which significantly surpasses that of the
largest ground observatories. The large number of events expected above the GZK
threshold for photo-pion production by protons will allow the directional
identification of individual sources and the determination of their spectra,
i.e., doing astronomy and astrophysics through the particle channel. Similar
goals can be achieved in the case of light UHECR nuclei. Furthermore, the
atmospheric target volume ($\sim 10^{12}$ ton) makes the possibility of
neutrino observation a highlight of the mission. Other exploratory objectives
include the detection of extreme energy gammas and the study of Galactic
magnetic fields as well as global observations of the earth's atmosphere,
including clouds, night-glows, plasma discharges, and meteors. In this
contribution we will describe the scientific objectives of JEM-EUSO.


  According to quantum chromodynamics (QCD), matter at ultra-high densities
will take the form of a color-superconducting quark liquid, in which there is a
condensate of Cooper pairs of quarks near the Fermi surface. I present a review
of the physics of color superconductivity. I give particular attention to the
recently proposed gapless CFL (gCFL) phase, which has unusual properties such
as quasiquarks with a near-quadratic dispersion relation, and which may well be
the favored phase of quark matter in the density range relevant to compact
stars. I also discuss the effects of color superconductivity on the mass-radius
relationship of compact stars, showing that one would have to fix the bag
constant by other measurements in order to see the effects of color
superconductivity. An additional parameter in the quark matter equation of
state connected with perturbative corrections allows quark matter to imitate
nuclear matter over the relevant density range, so that hybrid stars can show a
mass-radius relationship very similar to that of nuclear matter, and their
masses can reach 1.9 M_solar.


  This paper aims to determine how the LMS Web portal application reshapes the
learner experience through the developed E-Learning Management System using
Data Mining Algorithm.
  The methodology that the researchers used is descriptive research involving
the interpretation of the meaning or significance of what is described. Gather
data from questionnaires, surveys, observations concerned with the study, and
the chi-square formula for the statistical treatment of data.
  The findings of the study, the extent that LMS Web portal application
reshapes the learner experience in terms of the following variables with the
Average Weighted Mean (AWM): Flexible engagement of Learners in any device is
highly satisfied; Personalize learning tracker is highly satisfied;
Collaborating with the Learning Expert is highly satisfied; Provides
user-friendly Teaching Tools is satisfied; Evident Learner Progress and
Involvement and is satisfied.
  In the final analysis, this E-Learning System can fit any educational needs
as follows: chat, virtual classes, supportive resources for the students,
individual and group monitoring, and assessment using LMS as maximum
efficiency. Moreover, this platform can be used to deliver hybrid learning.


  The chemical and magnetic structures of the series of compounds
Ca$_{2-x}$La$_x$RuO$_4$ [$x = 0$, $0.05(1)$, $0.07(1)$, $0.12(1)$] have been
investigated using neutron diffraction and resonant elastic x-ray scattering.
Upon La doping, the low temperature S-Pbca space group of the parent compound
is retained in all insulating samples [$x\leq0.07(1)$], but with significant
changes to the atomic positions within the unit cell. These changes can be
characterised in terms of the local RuO$_6$ octahedral coordination: with
increasing doping the structure, crudely speaking, evolves from an orthorhombic
unit cell with compressed octahedra to a quasi-tetragonal unit cell with
elongated ones. The magnetic structure on the other hand, is found to be
robust, with the basic $k=(0,0,0)$, $b$-axis antiferromagnetic order of the
parent compound preserved below the critical La doping concentration of
$x\approx0.11$. The only effects of La doping on the magnetic structure are to
suppress the A-centred mode, favouring the B mode instead, and to reduce the
N\'{e}el temperature somewhat. Our results are discussed with reference to
previous experimental reports on the effects of cation substitution on the
$d^4$ Mott insulator Ca$_2$RuO$_4$, as well as with regard to theoretical
studies on the evolution of its electronic and magnetic structure. In
particular, our results rule out the presence of a proposed ferromagnetic
phase, and suggest that the structural effects associated with La substitution
play an important role in the physics of the system.


  We study gradient corrections to the transport equation for energetic light
partons in dense QCD environments. In the diffusion limit, the transport
dynamics is solely controlled by small-angle elastic scatterings, leading to
transverse momentum broadening with respect to the parton's initial direction.
Such a parton propagation is usually considered in the limit of transversely
homogeneous matter. The transport processes admit a classical description and
the transverse spatial dependence of the medium properties emerges only through
the jet quenching parameter. In this work, we show that a gradient expansion of
the all-order evolution equation for the partonic Wigner function leads to an
evolution equation in the Boltzmann-diffusion form only up to the leading order
in transverse gradients. At the second order in gradients, the quantum
corrections associated with non-local interactions give rise to a novel
transport that can be implemented in Monte Carlo simulations. In addition,
using our results, we compute the gradient corrections to the jet quenching
parameter in inhomogeneous matter.


  Supersymmetry plays a fundamental role in the radiative stability of many
inflationary models. Spontaneous breaking of the symmetry inevitably leads to
fields with masses of order the Hubble scale during inflation. When these
fields couple to the inflaton they produce a unique signature in the squeezed
limit of the three-point function of primordial curvature perturbations. In
this paper, we make this connection between naturalness, supersymmetry,
Hubble-mass degrees of freedom and the squeezed limit precise. To study the
physics in a model-insensitive way, we develop a supersymmetric effective
theory of inflation. We use the effective theory to classify all possible
interactions between the inflaton and the additional fields, and determine
which ones naturally allow large non-Gaussianities when protected by
supersymmetry. Finally, we discuss the tantalizing prospect of using
cosmological observations as a probe of supersymmetry.


  We reexamine the existence and stability conditions of Dirac points between
valence and conduction bands of 3/4 filled $\alpha$-(BEDT-TTF)$_2$I$_3$
conducting plane. We consider the usual nearest neigbhor tight binding model
with the seven transfer energies that depend on the applied pressure. Owing to
the four distinct molecules (A, A', B, C) per unit cell of the Bravais lattice,
the corresponding Bloch Hamiltonian is a $4\times4$ matrix ${\cal H}({\bm k})$
for each wave vector $\mathbf{k}$ of the Brillouin zone. In most previous works
the study of Dirac points was achieved through direct numerical diagonalization
of matrix ${\cal H}({\bm k})$. In this work we develop a novel analytical
approach which allows to analyze the existence and stability conditions of
Dirac points from the knowledge of their merging properties at time reversal
points. Within this approach we can discuss thoroughly the role of each
transfer integrals and demonstrate that inversion symmetry is convenient but
not necessary.


  Training machine learning (ML) models is expensive in terms of computational
power, amounts of labeled data and human expertise. Thus, ML models constitute
intellectual property (IP) and business value for their owners. Embedding
digital watermarks during model training allows a model owner to later identify
their models in case of theft or misuse. However, model functionality can also
be stolen via model extraction, where an adversary trains a surrogate model
using results returned from a prediction API of the original model. Recent work
has shown that model extraction is a realistic threat. Existing watermarking
schemes are ineffective against IP theft via model extraction since it is the
adversary who trains the surrogate model. In this paper, we introduce DAWN
(Dynamic Adversarial Watermarking of Neural Networks), the first approach to
use watermarking to deter model extraction IP theft. Unlike prior watermarking
schemes, DAWN does not impose changes to the training process but it operates
at the prediction API of the protected model, by dynamically changing the
responses for a small subset of queries (e.g., <0.5%) from API clients. This
set is a watermark that will be embedded in case a client uses its queries to
train a surrogate model. We show that DAWN is resilient against two
state-of-the-art model extraction attacks, effectively watermarking all
extracted surrogate models, allowing model owners to reliably demonstrate
ownership (with confidence $>1- 2^{-64}$), incurring negligible loss of
prediction accuracy (0.03-0.5%).


  Let $X$ be a minimal cubic surface over a finite field $\mathbb{F}_q$. The
image $\Gamma$ of the Galois group $\operatorname{Gal}(\overline{\mathbb{F}}_q
/ \mathbb{F}_q)$ in the group
$\operatorname{Aut}(\operatorname{Pic}(\overline{X}))$ is a cyclic subgroup of
the Weyl group $W(E_6)$. There are $25$ conjugacy classes of cyclic subgroups
in $W(E_6)$, and $5$ of them correspond to minimal cubic surfaces. It is
natural to ask which conjugacy classes come from minimal cubic surfaces over a
given finite field. In this paper we give a partial answer to this question and
present many explicit examples.


  We study the height of the delta peak at 0 in the spectrum of random tree
incidence matrices. We show that the average fraction of the spectrum occupied
by the eigenvalue 0 in a large random tree is asymptotic to 2x-1 =
0.1342865808195677459999... where x is the unique real root of x = exp(-x). For
finite trees, we give a closed form, a generating function, and an asymptotic
estimate for the sequence 1,0,3,8,135,1164,21035,.... of the total multiplicity
of the eigenvalue 0 in the set of n^{n-2} tree incidence matrices of size n>0.


  Bethe-Salpeter equation is applied to $p$-$p$ elastic scattering. The
observables of spin are calculated in the framework of the M matrix using the
two-body interaction potential. The parameter of the pseudovector coupling
constant is adjusted so as to reproduce the spin singlet part. It is shown that
the spin rotation $R(\theta)$ and $A(\theta)$ are improved by the resonance
effect for ${}^{\rm 1}S_{\rm 0}$.


  The large $N$ limit of symmetric orbifold theories was recently argued to
have an AdS/CFT dual world-sheet description in terms of an
$\mathfrak{sl}(2,\mathbb{R})$ WZW model. In previous work the world-sheet state
corresponding to the symmetric orbifold stress-energy tensor was identified. We
calculate certain 2- and 3-point functions of the corresponding vertex operator
on the world-sheet, and demonstrate that these amplitudes reproduce exactly
what one expects from the dual symmetric orbifold perspective.


  A key aspect of human intelligence is the ability to imagine -- composing
learned concepts in novel ways -- to make sense of new scenarios. Such capacity
is not yet attained for machine learning systems. In this work, in the context
of visual reasoning, we show how modularity can be leveraged to derive a
compositional data augmentation framework inspired by imagination. Our method,
denoted Object-centric Compositional Neural Module Network (OC-NMN), decomposes
visual generative reasoning tasks into a series of primitives applied to
objects without using a domain-specific language. We show that our modular
architectural choices can be used to generate new training tasks that lead to
better out-of-distribution generalization. We compare our model to existing and
new baselines in proposed visual reasoning benchmark that consists of applying
arithmetic operations to MNIST digits.


  We analyze the spectral properties of the volume operator of Ashtekar and
Lewandowski in Loop Quantum Gravity, which is the quantum analogue of the
classical volume expression for regions in three dimensional Riemannian space.
Our analysis considers for the first time generic graph vertices of valence
greater than four. Here we find that the geometry of the underlying vertex
characterizes the spectral properties of the volume operator, in particular the
presence of a `volume gap' (a smallest non-zero eigenvalue in the spectrum) is
found to depend on the vertex embedding. We compute the set of all
non-spatially diffeomorphic non-coplanar vertex embeddings for vertices of
valence 5--7, and argue that these sets can be used to label spatial
diffeomorphism invariant states. We observe how gauge invariance connects
vertex geometry and representation properties of the underlying gauge group in
a natural way. Analytical results on the spectrum on 4-valent vertices are
included, for which the presence of a volume gap is proved. This paper presents
our main results; details are provided by a companion paper arXiv:0706.0382v1.


  The group velocity of light has been measured at eight different wavelengths
between 385 nm and 532 nm in the Mediterranean Sea at a depth of about 2.2 km
with the ANTARES optical beacon systems. A parametrisation of the dependence of
the refractive index on wavelength based on the salinity, pressure and
temperature of the sea water at the ANTARES site is in good agreement with
these measurements.


  Nonlinear second-harmonic magnetic response (M2) was used to characterize an
aqueous colloidal solution of dextran-coated magnetite (Fe3O4) nanoparticles.
Data analysis with the formalism based on Gilbert-Landau-Lifshitz equation for
stochastic dynamics of superparamagnetic (SP) particles ensured extensive
quantifying of the system via a set of magnetic and magnetodynamic parameters,
such as the mean magnetic moment, the damping constant, the longitudinal
relaxation time, the magnetic anisotropy field and energy, and others. Combined
with transmission electron microscopy and dynamic light scattering, M2
technique allowed obtaining additional parameters, viz., the dextran-coating
thickness and the interparticle magnetic dipolar energy. Aggregated colloidal
nanoparticles were shown to be magnetically correlated inside the aggregate due
to magnetic dipole-dipole (d-d) coupling within the correlation radius ~50 nm.
With the d-d coupling account, the volume distribution of the aggregates
recovered from M2 measurements is well consistent with electron microscopy
results. From electron magnetic resonance, abrupt change of SP dynamics with
increasing external magnetic field was observed and explained. The presented
study exemplifies a novel M2-based procedure of comprehensive quantitative
characterization applicable for a wide variety of SP systems.


  We state a general purpose algorithm for quickly finding primes in evenly
divided sub-intervals. Legendre's conjecture claims that for every positive
integer $n$, there exists a prime between $n^2$ and $(n+1)^2$. Oppermann's
conjecture subsumes Legendre's conjecture by claiming there are primes between
$n^2$ and $n(n+1)$ and also between $n(n+1)$ and $(n+1)^2$. Using Cram\'er's
conjecture as the basis for a heuristic run-time analysis, we show that our
algorithm can verify Oppermann's conjecture, and hence also Legendre's
conjecture, for all $n\le N$ in time $O( N \log N \log \log N)$ and space
$N^{O(1/\log \log N)}$. We implemented a parallel version of our algorithm and
improved the empirical verification of Oppermann's conjecture from the previous
$N = 2\cdot 10^{9}$ up to $N = 3.33\cdot 10^{13}$, so we were finding $27$
digit primes. The computation ran for about half a year on four Intel Xeon Phi
$7210$ processors using a total of $256$ cores.


  Very unhealthy air quality is consistently connected with numerous diseases.
Appropriate extreme analysis and accurate predictions are in rising demand for
exploring potential linked causes and for providing suggestions for the
environmental agency in public policy strategy. This paper aims to model the
spatial and temporal pattern of both moderate and extremely poor PM10
concentrations (of daily mean) collected from 342 representative monitors
distributed throughout mainland Spain from 2017 to 2021. We firstly propose and
compare a series of Bayesian hierarchical generalized extreme models of annual
maxima PM10 concentrations, including both the fixed effect of altitude,
temperature, precipitation, vapour pressure and population density, as well as
the spatio-temporal random effect with the Stochastic Partial Differential
Equation (SPDE) approach and a lag-one dynamic auto-regressive component
(AR(1)). Under WAIC, DIC and other criteria, the best model is selected with
good predictive ability based on the first four-year data (2017--2020) for
training and the last-year data (2021) for testing. We bring the structure of
the best model to establish the joint Bayesian model of annual mean and annual
maxima PM10 concentrations and provide evidence that certain predictors
(precipitation, vapour pressure and population density) influence comparably
while the other predictors (altitude and temperature) impact reversely in the
different scaled PM10 concentrations. The findings are applied to identify the
hot-spot regions with poor air quality using excursion functions specified at
the grid level. It suggests that the community of Madrid and some sites in
northwestern and southern Spain are likely to be exposed to severe air
pollution, simultaneously exceeding the warning risk threshold.


  Scientific disciplines, such as Behavioural Psychology, Anthropology and
recently Social Signal Processing are concerned with the systematic exploration
of human behaviour. A typical work-flow includes the manual annotation (also
called coding) of social signals in multi-modal corpora of considerable size.
For the involved annotators this defines an exhausting and time-consuming task.
In the article at hand we present a novel method and also provide the tools to
speed up the coding procedure. To this end, we suggest and evaluate the use of
Cooperative Machine Learning (CML) techniques to reduce manual labelling
efforts by combining the power of computational capabilities and human
intelligence. The proposed CML strategy starts with a small number of labelled
instances and concentrates on predicting local parts first. Afterwards, a
session-independent classification model is created to finish the remaining
parts of the database. Confidence values are computed to guide the manual
inspection and correction of the predictions. To bring the proposed approach
into application we introduce NOVA - an open-source tool for collaborative and
machine-aided annotations. In particular, it gives labellers immediate access
to CML strategies and directly provides visual feedback on the results. Our
experiments show that the proposed method has the potential to significantly
reduce human labelling efforts.


  Electroweak baryon number violation may play a crucial role for the creation
of the matter-antimatter asymmetry in the early universe. In this talk, we
review the basic mechanism, which relies on the behavior of chiral fermions in
nontrivial Yang-Mills gauge field backgrounds.


  The theoretical measuring of information was famously initiated by Shannon in
his mathematical theory of communication, in which he proposed a now widely
used quantity, the entropy, measured in bits. Yet, in the same paper, Shannon
also chose to measure the information in continuous systems in nats, which
differ from bits by the use of the natural rather than the binary logarithm.
  We point out that there is nothing natural about the choice of logarithm
basis, rather it is arbitrary. We remedy this problematic state of affairs by
proposing a genuinely natural measure of information, which we dub gnats. We
show that gnats have many advantages in information theory, and propose to
adopt the underlying methodology throughout science, arts and everyday life.


  In this paper, we show a condition for two-parameter Gorenstein cyclic
quotient singularities to have a crepant resolution by using the remainder
polynomial in any dimension.


  Using a quantization of the nonassociative and noncommutative Snyder phi^4
scalar field theory in a Hermitian realization, we present in this article
analytical formulas for the momentum-conserving part of the one-loop two-point
function of this theory in D-, 4-, and 3-dimensional Euclidean spaces, which
are exact with respect to the noncommutative deformation parameter beta. We
prove that these integrals are regularized by the Snyder deformation. These
results indicate that the Snyder deformation does partially regularize the UV
divergences of the undeformed theory, as it was proposed decades ago.
Furthermore, it is observed that different nonassociative phi^4 products can
generate different momentum-conserving integrals. Finally most importantly, a
logarithmic infrared divergence emerges in one of these interaction terms. We
then analyze sample momentum nonconserving integral qualitatively and show that
it could exhibit IR divergence too. Therefore infrared divergences should
exist, in general, in the Snyder phi^4 theory. We consider infrared divergences
at the limit p -> 0 as UV-IR mixings induced by nonassociativity, since they
are associated to the matching UV divergence in the zero-momentum limit and
appear in specific types of nonassociative phi^4 products. We also discuss the
extrapolation of the Snyder deformation parameter beta to negative values as
well as certain general properties of one-loop quantum corrections in Snyder
phi^4 theory at the zero-momentum limit.


  Rapidly growing data sizes of scientific simulations pose significant
challenges for interactive visualization and analysis techniques. In this work,
we propose a compact probabilistic representation to interactively visualize
large scattered datasets. In contrast to previous approaches that represent
blocks of volumetric data using probability distributions, we model clusters of
arbitrarily structured multivariate data. In detail, we discuss how to
efficiently represent and store a high-dimensional distribution for each
cluster. We observe that it suffices to consider low-dimensional marginal
distributions for two or three data dimensions at a time to employ common
visual analysis techniques. Based on this observation, we represent
high-dimensional distributions by combinations of low-dimensional Gaussian
mixture models. We discuss the application of common interactive visual
analysis techniques to this representation. In particular, we investigate
several frequency-based views, such as density plots in 1D and 2D,
density-based parallel coordinates, and a time histogram. We visualize the
uncertainty introduced by the representation, discuss a level-of-detail
mechanism, and explicitly visualize outliers. Furthermore, we propose a spatial
visualization by splatting anisotropic 3D Gaussians for which we derive a
closed-form solution. Lastly, we describe the application of brushing and
linking to this clustered representation. Our evaluation on several large,
real-world datasets demonstrates the scaling of our approach.


  Fat based pasty products are an essential part of food industries, both as
process intermediate or end products. Such materials are made of a continuous
fat phase in which solid particles are dispersed. Phenomena such as yield and
fracture occur in those materials and depend heavily on the composition of the
samples. The crystallization of fat is altered in presence of particle, which
leads to products with different physical properties. However, because of the
very complex aspect of the problem, very few studies have been trying to
characterize the influence of the solid particles on the final product. Small
amplitude oscillatory rheology is often used to characterize the stiffness of
the materials. But processed products might not meet the desired shape
necessary to perform rheology experiment, which require a very specific product
shape that might not be easily achievable when it comes to industrial trials.
Oscillatory rheology is therefore not always the best option to measure the
physical properties of hard fat mixes. In this paper, we formulate binary mixes
consisting of a hard fat matrix in which we added solid inclusions of sodium
chloride. We create various set of samples with different salt and fat volume
fraction and let them crystallize for a few weeks. We then perform various
micro indentation protocols on the resulting samples. We then elaborate a small
rheology model that is in accord with the data, and is able to predict the
small deformation of heterogeneous materials indented by various shapes and
loading protocols. We derive various physical quantities from this model such
as the storage and loss moduli. We conclude by stating that the complex modulus
of the binary mix grows with the solid volume fraction, following the classical
Krieger Dougherty empirical law (similarly to suspensions), to finally diverge
at a given volume fraction.


  We confront measurable neutrino degrees of freedom $N_{\rm eff}$ and summed
neutrino mass in the early universe to particle physics at the energy scale
beyond the standard model (BSM), in particular including the issue of neutrino
mass type distinction. The Majorana-type of massive neutrino is perfectly
acceptable by Planck observations, while the Dirac-type neutrino may survive in
a restricted class of models that suppresses extra right-handed contribution to
$\Delta N_{\rm eff} = N_{\rm eff} - 3$ at a nearly indistinguishable level from
the Majorana case. There is a chance that supersymmetry energy scale may be
identified in supersymmetric extension of left-right symmetric model if
improved $N_{\rm eff}$ measurements discover a finite value. Combined analysis
of this quantity with the summed neutrino mass helps to determine the neutrino
mass ordering pattern, if measurement accuracy of order, $60 \sim 80\,$meV, is
achieved, as in CMB-S4.


  Localized high frequency (several GHz) electrodynamic properties of a high
quality epitaxial, single-crystal Iron-Pnicitde Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$
thin film near optimal doping (x=0.08) are measured under a localized and
strong RF magnetic field, created by a near-field microwave microscope. Two
reflection electrodynamic measurements, including linear and the third harmonic
responses, are performed to understand the electromagnetic properties of
Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$. Our measurement results show that
Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$ has have a wide superconducting transition width
and may have a multi-gap nature. In addition, based on the $1/T^2$ dependence
of the third harmonics signal at lower temperature,
Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$ shows the possibility of nodal behavior.


  This article investigates the propagation of chaos property for weakly
interacting mild solutions to semilinear stochastic partial differential
equations whose coefficients might not satisfy Lipschitz conditions.
Furthermore, we derive continuity and linear growth conditions for the
existence and uniqueness of mild solutions to SPDEs with distribution dependent
coefficients, so-called McKean-Vlasov SPDEs.


  The bootstrap condition is generalized to $n$ reggeized gluons. As a result
it is demonstrated that the intercept generated by $n$ reggeized gluons cannot
be lower than the one for $n=2$. Arguments are presented that in the limit
$N_{c}\rightarrow\infty$ the bootstrap condition reduces the $n$ gluon chain
with interacting neighbours to a single BFKL pomeron. In this limit the leading
contribution from $n$ gluons corresponds to $n/2$ non-interacting BFKL pomerons
(the $n/2$ pomeron cut). The sum over $n$ leads to a unitary
$\gamma^{\ast}\gamma$ amplitude of the eikonal form.


  With the advent of new IEEE 802.11ax (WiFi 6) devices, enabling security is a
priority. Since previous versions were found to have security vulnerabilities,
to fix the most common security flaws, the WiFi Protected Access 3 (WPA3) got
introduced. Although WPA3 is an improvement over its predecessor in terms of
security, recently it was found that WPA3 has a few security vulnerabilities as
well. In this paper, we have mentioned the previously known vulnerabilities in
WPA3 and WPA2. In addition to that, we have created our own dataset based on
WPA3 attacks (Section III). We have proposed a two-stage solution for the
detection of an intrusion in the network. The two-stage approach will help ease
computational processing burden of an AP and WLAN Controller. First, AP will
perform a lightweight simple operation for some duration (say 500ms) at certain
time interval. Upon discovering any abnormality in the flow of traffic an
ML-based solution at the controller will detect the type of attack. Our
approach is to utilize resources on AP as well as the back-end controller with
certain level of optimization. We have achieved over 99% accuracy in attack
detection using an ML-based solution. We have also publicly provided our code
and dataset for the open-source research community, so that it can contribute
for future research work.


  Skew stable Grothendieck polynomials are $K$-theoretic analogues of skew
Schur polynomials. We give a free-fermionic presentation of skew stable
Grothendieck polynomials and their dual symmetric functions. By using our
presentation, we derive a family of determinantal formulas, which are
$K$-analogues of the Jacobi-Trudi formula for skew Schur functions. We also
introduce a combinatorial method to calculate certain expansions of skew (dual)
stable Grothendieck polynomials by using the non-commutative supersymmetric
Schur functions.


  This paper presents the design, the fabrication and the characterization of
Schottky graphene/silicon photodetectors, operating at both 2 micron and room
temperature. The graphene/silicon junction has been carefully: characterized
device shows a non ideal behaviour with the increasing temperature and the
interfacial trap density has been measured as 1.1x10^14 eV^-1cm^-2.
Photodetectors are characterized by an internal (external) responsivity of 10.3
mA/W (0.16 mA/W) in an excellent agreement with the theory. Our devices pave
the way for developing hybrid graphene-Si free-space illuminated PDs operating
at 2 micron, for free-space optical communications, optical coherence
tomography and light-radars.


  The high spin states in $^{195}$Bi has been studied by $\gamma$-ray
spectroscopic method using the $^{181}$Ta($^{20}$Ne, 6n) fusion evaporation
reaction at 130 MeV. The $\gamma\gamma$ coincidence data were taken using an
array of 8 clover HPGe detectors. The spin and parity assignments of the
excited states have been made from the measured directional correlation from
oriented states (DCO) ratios and integrated polarization asymmetry (IPDCO)
ratios. The results show, for the first time, the evidence of a rotational like
band based on a 13/2$^+$ band head in this nucleus, indicating the onset of
deformation at neutron number $N = 112$ for the Bismuth isotopes. The results
obtained were found to be consistent with the prediction of the total Routhian
surface calculations using Woods Saxon potential. The same calculations also
predict a change in shape from oblate to triaxial in $^{195}$Bi at high
rotational frequency.


  We present an approach to perform 3D pose estimation of multiple people from
a few calibrated camera views. Our architecture, leveraging the recently
proposed unprojection layer, aggregates feature-maps from a 2D pose estimator
backbone into a comprehensive representation of the 3D scene. Such intermediate
representation is then elaborated by a fully-convolutional volumetric network
and a decoding stage to extract 3D skeletons with sub-voxel accuracy. Our
method achieves state of the art MPJPE on the CMU Panoptic dataset using a few
unseen views and obtains competitive results even with a single input view. We
also assess the transfer learning capabilities of the model by testing it
against the publicly available Shelf dataset obtaining good performance
metrics. The proposed method is inherently efficient: as a pure bottom-up
approach, it is computationally independent of the number of people in the
scene. Furthermore, even though the computational burden of the 2D part scales
linearly with the number of input views, the overall architecture is able to
exploit a very lightweight 2D backbone which is orders of magnitude faster than
the volumetric counterpart, resulting in fast inference time. The system can
run at 6 FPS, processing up to 10 camera views on a single 1080Ti GPU.


  The analytic signal is a useful mathematical tool. It separates qualitative
and quantitative information of a signal in form of the local phase and local
amplitude. The Clifford Fourier transform (CFT) plays a vital role in the
representation of multidimensional signals. By generalizing the CFT to the
Clifford linear canonical transform (CLCT), we present a new type of Clifford
biquaternionic analytic signal. Due to the advantages of more freedom, the
envelop detection problems of 3D images, with the help of this new analytic
signal, can get a better visual appearance. Synthesis examples are presented to
demonstrate these advantages.


  The last 25 years saw a major step forward in the analysis of optical and UV
spectroscopic data of large quasar samples. Multivariate statistical approaches
have led to the definition of systematic trends in observational properties
that are the basis of physical and dynamical modeling of quasar structure. We
discuss the empirical correlates of the so-called "main sequence" associated
with the quasar Eigenvector 1, its governing physical parameters and several
implications on our view of the quasar structure, as well as some luminosity
effects associated with the virialized component of the line emitting regions.
We also briefly discuss quasars in a segment of the main sequence that includes
the strongest FeII emitters. These sources show a small dispersion around a
well-defined Eddington ratio value, a property which makes them potential
Eddington standard candles.


  Measuring yielding in cohesive suspensions is often hampered by slip at
measurement surfaces. This paper presents creep data for strongly-flocculated
suspensions obtained using vane-in-cup tools with differing cup-to-vane
diameter ratios. The three suspensions were titania and alumina aggregated at
their isoelectric points and polymer-flocculated alumina. The aim was to find
the diameter ratio where slip or premature yielding at the cup wall had no
effect on the transient behaviour. The large diameter ratio results showed
readily understandable material behaviour comprising linear viscoelasticity at
low stresses, strain-softening close to yielding, time-dependent yield across a
range of stresses and then viscous flow. Tests in small ratio geometries
however showed more complex responses. Effects attributed to the cup wall
included delayed softening, slip, multiple yielding and stick-slip events, and
unsteady flow. The conclusion was that cups have to be relatively large to
eliminate wall artefacts. A diameter ratio of three was sufficient in practice,
although the minimum ratio must be material dependent.


  We discuss a role of a momentum vector in the description of dynamics of
systems with variable mass, and show some ambiguity in expressing the 2nd
Newtonian law of dynamics in terms of momentum change in time for variable-mass
systems. A simple expression that the time-derivative of the momentum of the
body with variable mass is equal to the net external force is not always true
(only if a special frame of reference is assumed). In basic textbooks and
multiple lecture notes the correct equation of motion for a variable-mass
system (including relative velocities of the masses entering or leaving the
body) is not sufficiently well discussed, leading to some problems with
understanding the dynamics of these systems among students. We also show how
the equation of motion in classical case (in translational motion) can be
easily expanded to the relativistic case and discuss a motion of a relativistic
rocket. For the non-relativistic case also a rotational motion is discussed. It
is of course true, that most of the good literature treats the problem
accurately, but some of the commonly used textbooks do not. The purpose of our
letter is to pay attention to the problem of dynamics of variable-mass systems
and show yet another perspective of the subject.


  We reveal relations between the duality of capacities and the duality between
Sobolev extendability of Jordan domains in the plane, and explain how to read
the curve conditions involvd in the Sobolev extendability of Jordan domains via
the duality of capacities. Finally as an application, we give an alternative
proof of the necessary condition for a Jordan planar domain to be $W^{1,
q}$-extension domain when $2 < q < \infty$.


  A measurement of the $\bjet$ production cross section is presented for events
containing a $Z$ boson produced in $p\bar{p}$ collisions at $\sqrt{s}=1.96$
TeV, using data corresponding to an integrated luminosity of 2 fb$^{-1}$
collected by the CDF II detector at the Tevatron. $Z$ bosons are selected in
the electron and muon decay modes. Jets are considered with transverse energy
$E_T>20$ GeV and pseudorapidity $|\eta|<1.5$ and are identified as $\bjets$
using a secondary vertex algorithm. The ratio of the integrated $Z+\bjet$ cross
section to the inclusive $Z$ production cross section is measured to be $3.32
\pm 0.53 {\rm (stat.)} \pm 0.42 {\rm (syst.)}\times 10^{-3}$. This ratio is
also measured differentially in jet $E_T$, jet $\eta$, $Z$-boson transverse
momentum, number of jets, and number of $\bjets$. The predictions from leading
order Monte Carlo generators and next-to-leading-order QCD calculations are
found to be consistent with the measurements within experimental and
theoretical uncertainties.


  Fake news is pervasive on social media, inflicting substantial harm on public
discourse and societal well-being. We investigate the explicit structural
information and textual features of news pieces by constructing a heterogeneous
graph concerning the relations among news topics, entities, and content.
Through our study, we reveal that fake news can be effectively detected in
terms of the atypical heterogeneous subgraphs centered on them, which
encapsulate the essential semantics and intricate relations between news
elements. However, suffering from the heterogeneity, exploring such
heterogeneous subgraphs remains an open problem. To bridge the gap, this work
proposes a heterogeneous subgraph transformer (HeteroSGT) to exploit subgraphs
in our constructed heterogeneous graph. In HeteroSGT, we first employ a
pre-trained language model to derive both word-level and sentence-level
semantics. Then the random walk with restart (RWR) is applied to extract
subgraphs centered on each news, which are further fed to our proposed subgraph
Transformer to quantify the authenticity. Extensive experiments on five
real-world datasets demonstrate the superior performance of HeteroSGT over five
baselines. Further case and ablation studies validate our motivation and
demonstrate that performance improvement stems from our specially designed
components.


  The WHOT-QCD Collaboration is pushing forward a series of lattice studies of
QCD at finite temperatures and densities using improved Wilson quarks. Because
Wilson-type quarks require more computational resources than the more widely
adopted staggered-type quarks, various theoretical and computational techniques
have to be developed and applied. In this paper, we introduce the fixed-scale
approach armed with the T-integration method, the Gaussian method based on the
cumulant expansion, and the histogram method combined with the reweighting
technique. Adopting these methods, we have carried out the first study of
finite-density QCD with Wilson-type quarks and the first calculation of the
equation of state with 2+1 flavors of Wilson-type quarks. We present results of
these studies and discuss perspectives towards a clarification of the
properties of 2+1 flavor QCD at the physical point, at finite temperatures and
densities.


  With the rapid development of pre-training techniques, a number of language
models have been pre-trained on large-scale code corpora and perform well in
code generation. In this paper, we investigate how to equip pre-trained
language models with the ability of code generation for private libraries. In
practice, it is common for programmers to write code using private libraries.
However, this is a challenge for language models since they have never seen
private APIs during training. Motivated by the fact that private libraries
usually come with elaborate API documentation, we propose a novel framework
with two modules: the APIRetriever finds useful APIs, and then the APICoder
generates code using these APIs. For APIRetriever, we present a dense retrieval
system and also design a friendly interaction to involve uses. For APICoder, we
can directly use off-the-shelf language models, or continually pre-train the
base model on a code corpus containing API information. Both modules are
trained with data from public libraries and can be generalized to private ones.
Furthermore, we craft three benchmarks for private libraries, named
TorchDataEval, MonkeyEval, and BeatNumEval. Experimental results demonstrate
the impressive performance of our framework.


  Ram pressure stripping may be the dominant mechanisms driving the evolution
of galaxy colors in groups and clusters. In this paper, an analytic model of
ram pressure stripping is confronted with observations of galaxy colors and
star formation rates in groups using a group catalog drawn from the Sloan
Digital Sky Survey. An observed increase in the fraction of galaxies residing
on the red sequence, the red fraction, with both increasing group mass,
$M_{gr}$, and decreasing satellite luminosity, $L_{sat}$, is predicted by the
model. The size of the differences in the red fraction can be understood in
terms of the effect of the scatter in satellite and cluster morphologies and
satellite orbits on the relationship between $M_{gr}$ and $L_{sat}$ and the
stripped gas fraction. Observations of the group galaxies' H$\delta$ and
4000\AA break spectral measures and a comparison of the distribution of
$SFR/M_{\ast}$ for star forming galaxies in the groups and in isolation both
indicate that the color differences observed in the groups are the result of
slowly declining SFRs, as expected if the color change is driven by stripping
of the outer H \textsc{i} disk.


  A majorized accelerated block coordinate descent (mABCD) method in Hilbert
space is analyzed to solve a sparse PDE-constrained optimization problem via
its dual. The finite element approximation method is investigated. The
attractive $O(1/k^2)$ iteration complexity of {the mABCD} method for the dual
objective function values can be achieved. Based on the convergence result, we
prove the robustness with respect to the mesh size $h$ for the mABCD method by
establishing that asymptotically the infinite dimensional ABCD method and
finite dimensional discretizations have the same convergence property, and the
number of iterations of mABCD method remains almost constant as the
discretization is refined.


  In this paper, we begin with the study of elements in $C^*$-algebras which
are mapped to Schatten class ideals through faithful left regular
representation. We further give some functorial properties of Schatten classes
on the category of representations of a $C^*$-algebra and category of unitary
representations of a group.


  Ambitious scenarios of carbon emission redistribution for mitigating climate
change in line with the Paris Agreement and reaching the sustainable
development goal of eradicating poverty have been proposed recently. They imply
a strong reduction in carbon footprint inequality by 2030 that effectively
halves the Gini coefficient to about 0.25. This paper examines feasibility of
these scenarios by analyzing the historical evolution of both weighted
international inequality in CO2 emissions attributed territorially and global
inequality in carbon footprints attributed to end consumers. For the latter, a
new dataset is constructed that is more comprehensive than existing ones. In
both cases, we find a decreasing trend in global inequality, partially
attributed to the move of China from the lower to the middle part of the
distribution, with footprints more unequal than territorial emissions. These
results show that realization of the redistributive scenarios would require an
unprecedented reduction in global inequality far below historical levels.
Moreover, the territorial emissions data, available for more recent years up to
2017, show a saturation of the decreasing Gini coefficient at a level of 0.5.
This observation confirms an earlier prediction based on maximal entropy
reasoning that the Lorenz curve converges to the exponential distribution. This
saturation further undermines feasibility of the redistributive scenarios,
which are also hindered by structural tendencies that reinforce carbon
footprint inequality under global capitalism. One way out of this conundrum is
a fast decarbonization of the global energy supply in order to decrease global
carbon emissions without relying crucially on carbon inequality reduction.


  Any architecture for practical quantum computing must be scalable. An
attractive approach is to create multiple cores, computing regions of fixed
size that are well-spaced but interlinked with communication channels. This
exploded architecture can relax the demands associated with a single monolithic
device: the complexity of control, cooling and power infrastructure as well as
the difficulties of cross-talk suppression and near-perfect component yield.
Here we explore interlinked multicore architectures through analytic and
numerical modelling. While elements of our analysis are relevant to diverse
platforms, our focus is on semiconductor electron spin systems in which
numerous cores may exist on a single chip. We model shuttling and
microwave-based interlinks and estimate the achievable fidelities, finding
values that are encouraging but markedly inferior to intra-core operations. We
therefore introduce optimsed entanglement purification to enable high-fidelity
communication, finding that $99.5\%$ is a very realistic goal. We then assess
the prospects for quantum advantage using such devices in the NISQ-era and
beyond: we simulate recently proposed exponentially-powerful error mitigation
schemes in the multicore environment and conclude that these techniques
impressively suppress imperfections in both the inter- and intra-core
operations.


  A family of unusually stable boron cages was identified and examined using
first-principles local density functional method. The structure of the
fullerenes is similar to that of the B12 icosahedron and consists of six
crossing double-rings. The energetically most stable fullerene is made up of
180 boron atoms. A connection between the fullerene family and its precursors,
boron sheets, is made. We show that the most stable boron sheets are not
necessarily precursors of very stable boron cages. Our finding is a step
forward in the understanding of the structure of the recently produced boron
nanotubes.


  We consider the problem of sensor selection for designing observer and filter
for continuous linear time invariant systems such that the sensor precisions
are minimized, and the estimation errors are bounded by the prescribed
$\mathcal{H}_2/\mathcal{H}_{\infty}$ performance criteria. The proposed
integrated framework formulates the precision minimization as a convex
optimization problem subject to linear matrix inequalities, and it is solved
using an algorithm based on the alternating direction method of multipliers
(ADMM). We also present a greedy approach for sensor selection and demonstrate
the performance of the proposed algorithms using numerical simulations.


  The effects of CP-odd supersymmetric phases on slepton pair production are
considered. It is shown that CP-even observables in $e^+ e^-$ and $e^- e^-$
collisions, such as the total selectron cross section, can depend on CP-odd
supersymmetric phases through interference between different tree level
amplitudes. Left handed selectron pair production in $e^- e^-$ collisions is
particularly sensitive to the relative phase between the bino and wino masses.
This sensitivity is not limited to any kinematic regime and extends over all of
neutralino parameter space. The relative phase between the bino and wino masses
is a renormalization group invariant at one-loop, and as such provides a clean
probe for operators which violate gaugino universality at the messenger scale.


  This paper characterizes the difficulty of estimating a network's eigenvector
centrality only from data on the nodes, i.e., with no information about the
topology of the network. We model this nodal data as graph signals generated by
passing white noise through generic (not necessarily low-pass) graph filters.
Leveraging the spectral properties of graph filters, we estimate the
eigenvectors of the adjacency matrix of the underlying network. To this end, a
simple selection algorithm is proposed, which chooses the correct eigenvector
of the signal covariance matrix with minimal assumptions on the underlying
graph filter. We then present a theoretical characterization of the asymptotic
and non-asymptotic performance of this algorithm, thus providing a sample
complexity bound for the centrality estimation and revealing key elements
driving this complexity. Finally, we illustrate the developed insights through
a set of numerical experiments on different random graph models.


  We recommend configuring the LSST coverage of the inner Galactic plane to
allow the production of the definitive age/metallicity map of the Galactic
bulge from LSST data, matched to external surveys where appropriate. This will
allow the formation history of the Galactic bulge to be reconstructed, as well
as furnishing a huge legacy dataset to support one of the key LSST science
goals (Mapping the Milky Way). We recommend precise multi-color
$grizy$~photometry as deeply as spatial crowding will allow (ideally completing
early in the project), complemented by a single-filter survey spread over the
entire 10-year time baseline. Both strands should cover as broad an area within
the Bulge as possible, with image quality sufficient to reach at least the
bulge main sequence turn-off in seeing-limited observations. We specify metrics
and a figure of merit by which candidate observing strategies could be
evaluated with respect to `static' bulge science (proper motions and
photometry)


  Open-retrieval question answering systems are generally trained and tested on
large datasets in well-established domains. However, low-resource settings such
as new and emerging domains would especially benefit from reliable question
answering systems. Furthermore, multilingual and cross-lingual resources in
emergent domains are scarce, leading to few or no such systems. In this paper,
we demonstrate a cross-lingual open-retrieval question answering system for the
emergent domain of COVID-19. Our system adopts a corpus of scientific articles
to ensure that retrieved documents are reliable. To address the scarcity of
cross-lingual training data in emergent domains, we present a method utilizing
automatic translation, alignment, and filtering to produce English-to-all
datasets. We show that a deep semantic retriever greatly benefits from training
on our English-to-all data and significantly outperforms a BM25 baseline in the
cross-lingual setting. We illustrate the capabilities of our system with
examples and release all code necessary to train and deploy such a system.


  We study a class of systems of stochastic differential equations describing
diffusive phenomena. The Smoluchowski-Kramers approximation is used to describe
their dynamics in the small mass limit. Our systems have arbitrary
state-dependent friction and noise coefficients. We identify the limiting
equation and, in particular, the additional drift term that appears in the
limit is expressed in terms of the solution to a Lyapunov matrix equation. The
proof uses a theory of convergence of stochastic integrals developed by Kurtz
and Protter. The result is sufficiently general to include systems driven by
both white and Ornstein-Uhlenbeck colored noises. We discuss applications of
the main theorem to several physical phenomena, including the experimental
study of Brownian motion in a diffusion gradient.


  We classify all primes appearing in the denominators of the Hauptmodul $J$
and modular forms for non-arithmetic triangle groups with a cusp. These primes
have a congruence condition in terms of the order of the generators of the
group. As a corollary we show that for the Hecke group of type $(2,m,\infty)$,
the prime $p$ does not appear in the denominator of $J$ if and only if $p\equiv
\pm 1\pmod m$.


  Social reputation (e.g., likes, comments, shares, etc.) on YouTube is the
primary tenet to popularize channels/videos. However, the organic way to
improve social reputation is tedious, which often provokes content creators to
seek the services of online blackmarkets for rapidly inflating content
reputation. Such blackmarkets act underneath a thriving collusive ecosystem
comprising core users and compromised accounts (together known as collusive
users). Core users form the backbone of blackmarkets; thus, spotting and
suspending them may help in destabilizing the entire collusive network.
Although a few studies focused on collusive user detection on Twitter,
Facebook, and YouTube, none of them differentiate between core users and
compromised accounts.
  We are the first to present a rigorous analysis of core users in YouTube
blackmarkets. To this end, we collect a new dataset of collusive YouTube users.
We study the core-periphery structure of the underlying collusive commenting
network (CCN). We examine the topology of CCN to explore the behavioral
dynamics of core and compromised users. We then introduce KORSE, a novel
graph-based method to automatically detect core users based only on the
topological structure of CCN. KORSE performs a weighted k-core decomposition
using our proposed metric, called Weighted Internal Core Collusive Index
(WICCI). However, KORSE is infeasible to adopt in practice as it requires
complete interactions among collusive users to construct CCN. We, therefore,
propose NURSE, a deep fusion framework that only leverages user timelines
(without considering the underlying CCN) to detect core blackmarket users.
Experimental results show that NURSE is quite close to KORSE in detecting core
users and outperforms nine baselines.


  During the last few years, significant attention has been paid to the
stochastic training of artificial neural networks, which is known as an
effective regularization approach that helps improve the generalization
capability of trained models. In this work, the method of modified equations is
applied to show that the residual network and its variants with noise injection
can be regarded as weak approximations of stochastic differential equations.
Such observations enable us to bridge the stochastic training processes with
the optimal control of backward Kolmogorov's equations. This not only offers a
novel perspective on the effects of regularization from the loss landscape
viewpoint but also sheds light on the design of more reliable and efficient
stochastic training strategies. As an example, we propose a new way to utilize
Bernoulli dropout within the plain residual network architecture and conduct
experiments on a real-world image classification task to substantiate our
theoretical findings.


  It has been revealed that the first order symmetry operator for the
linearized Einstein equation on a vacuum spacetime can be constructed from a
Killing-Yano 3-form. This might be used to construct all or part of solutions
to the field equation. In this paper, we perform a mode decomposition of a
metric perturbation on the Schwarzschild spacetime and the Myers-Perry
spacetime with equal angular momenta in 5 dimensions, and investigate the
action of the symmetry operator on specific modes concretely. We show that on
such spacetimes, there is no transition between the modes of a metric
perturbation by the action of the symmetry operator, and it ends up being the
linear combination of the infinitesimal transformations of isometry.


  Manipulation of tissue with surgical tools often results in large
deformations that current methods in tracking and reconstructing algorithms
have not effectively addressed. A major source of tracking errors during large
deformations stems from wrong data association between observed sensor
measurements with previously tracked scene. To mitigate this issue, we present
a surgical perception framework, SuPerPM, that leverages learning-based
non-rigid point cloud matching for data association, thus accommodating larger
deformations. The learning models typically require training data with ground
truth point cloud correspondences, which is challenging or even impractical to
collect in surgical environments. Thus, for tuning the learning model, we
gather endoscopic data of soft tissue being manipulated by a surgical robot and
then establish correspondences between point clouds at different time points to
serve as ground truth. This was achieved by employing a position-based dynamics
(PBD) simulation to ensure that the correspondences adhered to physical
constraints. The proposed framework is demonstrated on several challenging
surgical datasets that are characterized by large deformations, achieving
superior performance over state-of-the-art surgical scene tracking algorithms.


  The layered material ZrSiTe is currently extensively investigated as a
nodal-line semimetal with Dirac-like band crossings protected by nonsymmorphic
symmetry close to the Fermi energy. A recent infrared spectroscopy study on
ZrSiTe under external pressure found anomalies in the optical response,
providing hints for pressure-induced phase transitions at $\approx$4.1 and
$\approx$6.5 GPa. By pressure-dependent Raman spectroscopy and x-ray
diffraction measurements combined with electronic band structure calculations
we find indications for two pressure-induced Lifshitz transitions with major
changes in the Fermi surface topology in the absence of lattice symmetry
changes. These electronic phase transitions can be attributed to the enhanced
interlayer interaction induced by external pressure. Our findings demonstrate
the crucial role of the interlayer distance for the electronic properties of
layered van der Waals topological materials.


  Relating two quantities to describe a physical system or process is at the
heart of "doing physics" for novices and experts alike. In this paper, we
explore the ways in which experts use covariational reasoning when solving
introductory physics graphing problems. Here, graduate students are considered
experts for the introductory level material, as they often take the role of
instructor at large research universities. Drawing on work from Research in
Undergraduate Mathematics Education (RUME), we replicated a study of
mathematics experts' covariational reasoning done by Hobson and Moore with
physics experts [N. L. F. Hobson and K. C. Moore, in RUME Conference
Proceedings, pp. 664-672 (2017)]. We conducted think-aloud interviews with 10
physics graduate students using tasks minimally adapted from the mathematics
study. Adaptations were made solely for the purpose of participant
understanding of the question, and validated by preliminary interviews.
Preliminary findings suggest physics experts approach covariational reasoning
problems significantly differently than mathematics experts. In particular, two
behaviors are identified in the reasoning of expert physicists that were not
seen in the mathematics study. We introduce these two behaviors, which we call
Using Compiled Relationships and Neighborhood Analysis, and articulate their
differences from the behaviors articulated by Hobson and Moore. Finally, we
share implications for instruction and questions for further research.


  Since the 1928 seminal work of Dirac, and its subsequent development by
Weinberg, a view is held that there is a unique Fermi field of spin one-half.
It is endowed with mass dimension three-half. Combined, these characteristics
profoundly affect the phenomenology of the high energy physics, astrophysics,
and cosmology. We here present a counter example by providing a local, mass
dimension one, Fermi field of spin one-half. The theory, inter alia, thus
allows dimensionless quartic self interaction for the new fermions, and its
only other dimensionless coupling is quadratic in the new fermions and in the
standard-model scalar field. For these reasons, the immediate application of
the new theory resides in the dark-matter sector of physical reality. The
lowest-mass associated new particle may leave its unique signature at the Large
Hadron Collider. We discuss in detail the theoretical crevice that allows the
existence of the new quantum field.


  Recent studies of the electro-disintegration of the few body systems at JLab
have revived the field. Not only recoil momentum distributions have been
determined in a single shot. But also they confirm that the diagrammatic
approach, which I developed 25 years ago, is relevant to analyze them, provided
that the Nucleon-Nucleon scattering amplitude, determined in the same energy
range, is used. They provide us with a solid starting point to address the
issue of the propagation of exotic components of hadrons in nuclear matter


  We analyze the dynamics of modulation instability in optical fiber (or any
other nonlinear Schr\"{o}dinger equation system) using the machine-learning
technique of data-driven dominant balance. We aim to automate the
identification of which particular physical processes drive propagation in
different regimes, a task usually performed using intuition and comparison with
asymptotic limits. We first apply the method to interpret known analytic
results describing Akhmediev breather, Kuznetsov-Ma, and Peregrine soliton
(rogue wave) structures, and show how we can automatically distinguish regions
of dominant nonlinear propagation from regions where nonlinearity and
dispersion combine to drive the observed spatio-temporal localization. Using
numerical simulations, we then apply the technique to the more complex case of
noise-driven spontaneous modulation instability, and show that we can readily
isolate different regimes of dominant physical interactions, even within the
dynamics of chaotic propagation.


  The unit cell of a chevronic sculptured thin film (ChevSTF) comprises two
identical columnar thin films (CTFs) except that the nanocolumns of the first
are oriented at an angle \chi and nanocolumns of the second are oriented at an
angle \pi-\chi with respect to the interface of the two CTFs. A ChevSTF
containing 10 unit cells was fabricated using resistive-heating physical vapor
deposition of zinc selenide. Planewave reflectance and transmittance spectrums
of this ChevSTF were measured for a wide variety of incidence conditions over
the 500--900-nm range of the free-space wavelength. Despite its structural
periodicity, the ChevSTF did not exhibit the Bragg phenomenon. Theoretical
calculations with the CTFs modeled as biaxial dielectric materials indicated
that the Bragg phenomenon would not be manifested for normal and near-normal
incidence, but vestigial manifestation was possible for suffciently oblique
incidence. Thus, structural periodicity does not always lead to electromagnetic
periodicity that underlies the exhibition of the Bragg phenomenon.


  This second paper of two companion papers on the estimation of power spectra
specializes to the topic of estimating galaxy power spectra at large, linear
scales using maximum likelihood methods. As in the first paper, the aims are
pedagogical, and the emphasis is on concepts rather than technical detail. The
paper covers most of the salient issues, including selection functions,
likelihood functions, Karhunen-Loeve compression, pair-integral bias, Local
Group flow, angular or radial systematics (arising for example from
extinction), redshift distortions, quadratic compression, decorrelation, and
disentanglement. The procedures are illustrated with results from the IRAS PSCz
survey. Most of the PSCz graphics included in this paper have not been
published elsewhere.


  This paper presents LMStream, which ensures bounded latency while maximizing
the throughput on the GPU-enabled micro-batch streaming systems. The main ideas
behind LMStream's design can be summarized as two novel mechanisms: (1) dynamic
batching and (2) dynamic operation-level query planning. By controlling the
micro-batch size, LMStream significantly reduces the latency of individual
dataset because it does not perform unconditional buffering only for improving
GPU utilization. LMStream bounds the latency to an optimal value according to
the characteristics of the window operation used in the streaming application.
Dynamic mapping between a query to an execution device based on the data size
and dynamic device preference improves both the throughput and latency as much
as possible. In addition, LMStream proposes a low-overhead online cost model
parameter optimization method without interrupting the real-time stream
processing. We implemented LMStream on Apache Spark, which supports micro-batch
stream processing. Compared to the previous throughput-oriented method,
LMStream showed an average latency improvement up to a maximum of 70.7%, while
improving average throughput up to 1.74x.


  Low-noise temperature measurements at frequencies in the milli-Hertz range
are needed in the LISA and LISA PathFinder (LPF). The required temperature
stability for LISA is around 10 uK/sqrt(Hz) at frequencies down to 0.1 mHz. In
this paper we focus on the identification and reduction of a source of excess
noise detected when measuring time-varying temperature signals. This is shown
to be due to non-idealities in the ADC transfer curve, and degrades the
measurement by about one order of magnitude in the measurement bandwidth when
the measured temperature exhibits drifts of uK/s. In a suitable measuring
system for the LISA mission, this noise needs to be reduced. Two different
methods based on the same technique have been implemented, both consisting in
the addition of dither signals out of band to mitigate the ADC non-ideality
errors. Excess noise of this nature has been satisfactorily reduced by using
these methods when measuring temperature ramps up to 10 uK/s .


  We introduce the notion of "type" of a tableau, that allows us to define new
families of tableaux including both balanced and standard Young tableaux. We
use these new objects to describe the set of reduced decompositions of any
permutation. We then generalize the work of Fomin \emph{et al.} by giving,
among other things, a new proof of the fact that balanced and standard tableaux
are equinumerous, and by exhibiting many new families of tableaux having
similar combinatorial properties to those of balanced tableaux.


  Based on the complete-lattice approach, a new Lagrangian duality theory for
set-valued optimization problems is presented. In contrast to previous
approaches, set-valued versions for the known scalar formulas involving infimum
and supremum are obtained. In particular, a strong duality theorem, which
includes the existence of the dual solution, is given under very weak
assumptions: The ordering cone may have an empty interior or may not be
pointed. "Saddle sets" replace the usual notion of saddle points for the
Lagrangian, and this concept is proven to be sufficient to show the equivalence
between the existence of primal/dual solutions and strong duality on the one
hand and the existence of a saddle set for the Lagrangian on the other hand.


  The most passive galaxies at high redshift are unlikely to be identified by
either narrow-band emission-line searches, or by Lyman limit searches (both
techniques which have been highlighted at this meeting) simply because such
selection methods rely on the presence of a strong ultraviolet component.
Selection on the basis of extreme radio power has also proved to yield
optically active objects with the majority of high-redshift objects studied to
date displaying complex elongated optical/UV morphologies, relatively blue
optical-ultraviolet continuum colours, and strong emission lines. These
features, coupled with the failure to detect any spectral signatures of old
stars at $z > 1$, has led to the suggestion that these galaxies are being
observed close to or even during a general epoch of formation. However, we have
recently demonstrated that radio selection at significantly fainter (mJy) flux
densities can be used to identify apparently passively evolving elliptical
galaxies at high redshift. Deep Keck spectra have now been obtained for two
such objects yielding absorption line redshifts $z \simeq 1.5$; 53W091 at $z =
1.552$ (Dunlop et al. 1996) and most recently 53W069 at $z = 1.432$. The
ultraviolet SEDs of these galaxies indicate minimum ages $> 3$ Gyr while, as
stressed in this article, the strength of the reddenning-independent
ultraviolet spectral breaks actually indicate a greater minimum age of 5 Gyr
for both objects assuming solar metallicity. Since the spectra comprise the
integrated light of each galaxy to radii greater than $r_e$, I argue that it is
difficult to justify the adoption of significantly super-solar metallicity in
interpreting these data. It thus seems hard to escape the conclusion that
$\Omega_0 < 1$ and that, irrespective of the adopted cosmology, at least some
massive ellipitical galaxies were formed at high redshift ($z> 5$).


  Now a days, the text document is spontaneously increasing over the internet,
e-mail and web pages and they are stored in the electronic database format. To
arrange and browse the document it becomes difficult. To overcome such problem
the document preprocessing, term selection, attribute reduction and maintaining
the relationship between the important terms using background knowledge,
WordNet, becomes an important parameters in data mining. In these paper the
different stages are formed, firstly the document preprocessing is done by
removing stop words, stemming is performed using porter stemmer algorithm, word
net thesaurus is applied for maintaining relationship between the important
terms, global unique words, and frequent word sets get generated, Secondly,
data matrix is formed, and thirdly terms are extracted from the documents by
using term selection approaches tf-idf, tf-df, and tf2 based on their minimum
threshold value. Further each and every document terms gets preprocessed, where
the frequency of each term within the document is counted for representation.
The purpose of this approach is to reduce the attributes and find the effective
term selection method using WordNet for better clustering accuracy. Experiments
are evaluated on Reuters Transcription Subsets, wheat, trade, money grain, and
ship, Reuters 21578, Classic 30, 20 News group (atheism), 20 News group
(Hardware), 20 News group (Computer Graphics) etc.


  We show that the Morita equivalences $\mathrm{Cliff}(4) \simeq {\mathbb H}$,
$\mathrm{Cliff}(7) \simeq \mathrm{Cliff}(-1)$, and $\mathrm{Cliff}(8) \simeq
{\mathbb R}$ arise from quantizing the Hamiltonian reductions ${\mathbb
R}^{0|4} // \mathrm{Spin}(3)$, ${\mathbb R}^{0|7} // G_2$, and ${\mathbb
R}^{0|8} // \mathrm{Spin}(7)$, respectively.


  Linear stability of a plane shock waves in ultrarelativistic anisotropic
hydrodynamics is investigated. The properties of the amplitudes of
perturbations of physical quantities are studied depending on the components of
the wave vector of a small harmonic perturbation. Analytical calculationsfor
the longitudinal and transverse propagation of shock wave normal with respect
to the anisotropy axis (beam-axis) and numerical calculations for an arbitrary
polar angle are carried out.


  We study the parity effect and transport due to quasiparticles in circuits
comprised of many superconducting islands. We develop a general approach and
show that it is equivalent to previous methods for describing the parity effect
in their more limited regimes of validity. As an example we study transport
through linear arrays of Josephson junctions in the limit of negligible
Josephson energy and observe the emergence of the parity effect with decreasing
number of non-equilibrium quasiparticles. Due to the exponential increase in
the number of relevant charge states with increasing length, in multi-junction
arrays the parity effect manifests in qualitatively different ways to the two
junction case. The role of charge disorder is also studied as this hides much
of the parity physics which would otherwise be observed. Nonetheless, we see
that the current through a multi-junction array at low bias is limited by the
formation of meta-stable even-parity states.


  The loop braid group is the motion group of unknotted oriented circles in
$\mathbb{R}^3$. In this paper, we study their representations through the
approach inspired by two dimensional topological phases of matter. In
principle, the motion of loops in $\mathbb{R}^3$ reduces to the motions of
points in a two dimensional sliced plane. We realize this physical picture in
terms of braided tensor categories and their braid group representations.


  Translational invariance induced by pooling operations is an inherent
property of convolutional neural networks, which facilitates numerous computer
vision tasks such as classification. Yet to leverage rotational invariant
tasks, convolutional architectures require specific rotational invariant layers
or extensive data augmentation to learn from diverse rotated versions of a
given spatial configuration. Unwrapping the image into its polar coordinates
provides a more explicit representation to train a convolutional architecture
as the rotational invariance becomes translational, hence the visually distinct
but otherwise equivalent rotated versions of a given scene can be learnt from a
single image. We show with two common vision-based solar irradiance forecasting
challenges (i.e. using ground-taken sky images or satellite images), that this
preprocessing step significantly improves prediction results by standardising
the scene representation, while decreasing training time by a factor of 4
compared to augmenting data with rotations. In addition, this transformation
magnifies the area surrounding the centre of the rotation, leading to more
accurate short-term irradiance predictions.