  In this study, we present a criterion based on the analysis of EEG signals
through the mean of the conventional power spectral density (PSD) in the aim to
localize and detect the epileptic area of the brain. Firstly, as the EEG
signals are commonly non stationary in practice, we processed the data with
technique of differentiation in order to have the stationary which is
convenient to model with autoregressive model (AR). For this, we have used many
techniques for to determine the order which model better the data in this work.
Therefore, we can characterize normal and abnormal activity which correspond to
epileptic discharge for the patient. Our contribution in this work is the
automatic detection of epilepsy seizure with the PSD novel approach by a better
resolution in the frequency domain as the examination of EEG signals is often
done with visual inspection of the rhythm (delta, theta, alpha, beta, gamma) by
neurologists practitioners. The accuracy of the detection is estimated to 70%
with the sensitivity of 80.55% compared with the interpretation of neurologist.


  This article introduces the analytical approach of practice mapping, using
vector embeddings of network actions and interactions to map commonalities and
disjunctures in the practices of social media users, as a framework for
methodological advancement beyond the limitations of conventional network
analysis and visualisation. In particular, the methodological framework we
outline here has the potential to incorporate multiple distinct modes of
interaction into a single practice map, can be further enriched with
account-level attributes such as information gleaned from textual analysis,
profile information, available demographic details, and other features, and can
be applied even to a cross-platform analysis of communicative patterns and
practices.
  The article presents practice mapping as an analytical framework and outlines
its key methodological considerations. Given its prominence in past social
media research, we draw on examples and data from the platform formerly known
as Twitter in order to enable experienced scholars to translate their
approaches to a practice mapping paradigm more easily, but point out how data
from other platforms may be used in equivalent ways in practice mapping
studies. We illustrate the utility of the approach by applying it to a dataset
where the application of conventional network analysis and visualisation
approaches has produced few meaningful insights.


  We report a method to promote photoluminescence emission in graphene
materials by enhancing carrier scattering instead of directly modifying band
structure in multilayer reduced graphene oxide (rGO) nanospheres. We
intentionally curl graphene layers to form nanospheres by reducing graphene
oxide with spherical polymer templates to manipulate the carrier scattering.
These nanospheres produce hot-carrier luminescence with more than ten-fold
improvement of emission efficiency as compared to planar nanosheets. With
increasing excitation power, hot-carrier luminescence from nanospheres exhibits
abnormal spectral redshift with dynamic feature associated to the strengthened
electron-phonon coupling. These experimental results can be well understood by
considering the screened Coulomb interactions. With increasing carrier density,
the reduced screening effect promotes carrier scattering which enhances
hot-carrier emission from such multilayer rGO nanospheres. This
carrier-scattering scenario is further confirmed by pump-probe measurements.


  We give an integrability criterion on a real-valued non-increasing function
$\psi$ guaranteeing that for almost all (or almost no) pairs $(A, \textbf{b})$,
where $A$ is a real $m\times n$ matrix and $\textbf{b} \in \mathbb{R}^m$, the
system $\|A \textbf{q}+\textbf{b}-\textbf{p}\|^m< \psi({T})$,
$\|\textbf{q}\|^n<{T}$ is solvable in $\textbf{p} \in \mathbb{Z}^m$,
$\textbf{q} \in \mathbb{Z}^n$ for all sufficiently large $T$. The proof
consists of a reduction to a shrinking target problem on the space of grids in
$\mathbb{R}^{m+n}$. We also comment on the homogeneous counterpart to this
problem, whose $m=n=1$ case was recently solved, but whose general case remains
open.


  We present a detailed analysis of the two-channel atom-molecule effective
Hamiltonian for an ultracold two-component homogeneous Fermi gas interacting
near a Feshbach resonance. We particularly focus on the two-body and many-body
properties of the dressed molecules in such a gas. An exact result for the
many-body T-matrix of the two-channel theory is derived by both considering
coupled vertex equations and the functional integral methods. The field theory
incorporates exactly the two-body physics of the Feshbach scattering by means
of simple analytical formulas without any fitting parameters. New interesting
many-body effects are discussed in the case of narrow resonances. We give also
a description of the BEC-BCS crossover above and below T_C. The effects of
different approximations for the selfenergy of the dressed molecules are
discussed. The single-channel results are derived as a special limit for broad
resonances. Moreover, through an analytic analysis of the BEC limit, the
relation between the composite boson of the single-channel model and the
dressed-molecule of the two-channel model is established.


  A specification theory combines notions of specifications and implementations
with a satisfaction relation, a refinement relation and a set of operators
supporting stepwise design. We develop a complete specification framework for
real-time systems using Timed I/O Automata as the specification formalism, with
the semantics expressed in terms of Timed I/O Transition Systems. We provide
constructs for refinement, consistency checking, logical and structural
composition, and quotient of specifications -- all indispensable ingredients of
a compositional design methodology. The theory is backed by rigorous proofs and
is being implemented in the open-source tool ECDAR.


  Famous people, such as celebrities and influencers, are harassed online on a
daily basis. Online harassment mentally disturbs them and negatively affects
society. However, limited studies have been conducted on the online harassment
victimization of famous people, and its effects remain unclear. We surveyed
Japanese famous people ($N=213$), who were influential people who appeared on
television and other traditional media and on social media, regarding online
harassment victimization, emotional injury, and action against offenders and
revealed that various forms of online harassment are prevalent. Some victims
used the anti-harassment functions provided by weblogs and social media systems
(e.g., blocking/muting/reporting offender accounts and closing comment forms),
talked about their victimization to close people, and contacted relevant
authorities to take legal action (talent agencies, legal consultants, and
police). By contrast, some victims felt compelled to accept harassment and did
not initiate action for offenses. We propose several approaches to support
victims, inhibit online harassment, and educate people. Our findings help that
platforms establish support systems against online harassment.


  Self-supervised methods have recently proved to be nearly as effective as
supervised methods in various imaging inverse problems, paving the way for
learning-based methods in scientific and medical imaging applications where
ground truth data is hard or expensive to obtain. This is the case in magnetic
resonance imaging and computed tomography. These methods critically rely on
invariance to translations and/or rotations of the image distribution to learn
from incomplete measurement data alone. However, existing approaches fail to
obtain competitive performances in the problems of image super-resolution and
deblurring, which play a key role in most imaging systems. In this work, we
show that invariance to translations and rotations is insufficient to learn
from measurements that only contain low-frequency information. Instead, we
propose a new self-supervised approach that leverages the fact that many image
distributions are approximately scale-invariant, and that enables recovering
high-frequency information lost in the measurement process. We demonstrate
throughout a series of experiments on real datasets that the proposed method
outperforms other self-supervised approaches, and obtains performances on par
with fully supervised learning.


  The amplitudes of the quadrupole and octopole measured from the Wilkinson
Microwave Anisotropy Probe (WMAP) appear to be lower than expected according to
the concordance Lambda CDM cosmology. However, the pseudo-Cl estimator used by
the WMAP team is non-optimal. In this paper, we discuss the effects of Galactic
cuts on pseudo-Cl and quadratic maximum likelihood estimators. An application
of a quadratic maximum likelihood estimator to Galaxy subtracted maps produced
by the WMAP team and Tegmark, de Oliveira-Costa and Hamilton (2003) shows that
the amplitudes of the low multipoles are stable to different Galactic cuts. In
particular, the quadrupole and octopole amplitudes are found to lie in the
ranges 176 - 250 (micro K)**2 794 - 1183 (micro K)**2 (and more likely to be at
the upper ends of these ranges) rather than the values of 123 (micro K)**2 and
611 (micro K)**2 found by the WMAP team. These results indicate that the
discrepancy with the concordance Lambda CDM model at low multipoles is not
particularly significant and is in the region of a few percent. This conclusion
is consistent with an analysis of the low amplitude of the angular correlation
function computed from quadratic maximum likelihood power spectrum estimates.


  In this work, we study the following Kirchhoff equation
$$\begin{cases}-\left(\varepsilon^2 a+\varepsilon b\int_{\mathbb R^3}|\nabla
u|^2\right)\Delta u +u =Q(x)u^{q-1},\quad u>0,\quad x\in
{\mathbb{R}^{3}},\\u\to 0,\quad \text{as}\ |x|\to +\infty,\end{cases}$$ where
$a,b>0$ are constants, $2<q<6$, and $\varepsilon>0$ is a parameter. Under some
suitable assumptions on the function $Q(x)$, we obtain that the equation above
has positive multi-peak solutions concentrating at a critical point of $Q(x)$
for $\varepsilon>0$ sufficiently small, by using the Lyapunov-Schmidt reduction
method. We extend the result in (Discrete Contin. Dynam. Systems 6(2000),
39--50) to the nonlinear Kirchhoff equation.


  We show how to use numerical methods within the framework of successive
scaling to analyse the microstructure of turbulence, in particular to find
inertial range exponents and structure functions. The methods are first
calibrated on the Burgers problem and are then applied to the 3D Euler
equations. Known properties of low order structure functions appear with a
relatively small computational outlay; however, more sensitive properties
cannot yet be resolved with this approach well enough to settle ongoing
controversies.


  Disease diagnosis from medical images via supervised learning is usually
dependent on tedious, error-prone, and costly image labeling by medical
experts. Alternatively, semi-supervised learning and self-supervised learning
offer effectiveness through the acquisition of valuable insights from readily
available unlabeled images. We present Semi-Supervised Relational Contrastive
Learning (SRCL), a novel semi-supervised learning model that leverages
self-supervised contrastive loss and sample relation consistency for the more
meaningful and effective exploitation of unlabeled data. Our experimentation
with the SRCL model explores both pre-train/fine-tune and joint learning of the
pretext (contrastive learning) and downstream (diagnostic classification)
tasks. We validate against the ISIC 2018 Challenge benchmark skin lesion
classification dataset and demonstrate the effectiveness of our semi-supervised
method on varying amounts of labeled data.


  We consider a holographic description of a system of strongly-coupled
fermions in 2+1 dimensions based on a D7-brane probe in the background of
D3-branes. The black hole embedding represents a Fermi-like liquid. We study
the excitations of the Fermi liquid system. Above a critical density which
depends on the temperature, the system becomes unstable towards an
inhomogeneous modulated phase which is similar to a charge density and spin
wave state. The essence of this instability can be effectively described by a
Maxwell-axion theory with a background electric field. We also consider the
fate of zero sound at non-zero temperature.


  A noise-tolerant data communications fabric has been developed to meet the
real-time data acquisition and control requirements of fast feedback loops,
machine protection systems, pulse-to-pulse sequencing, and machine-experiment
communications at next-generation pulsed accelerators such as the Next Linear
Collider ("NLC"). The fabric is constructed from "platform" or
"system-on-a-chip" field programmable gate arrays ("FPGAs") containing embedded
processors, block memory, and multi-gigabit serial transceivers interconnected
via an array of point-to-point fiber-optic physical links for standard networks
such as gigabit Ethernet. The FPGA-based link hardware segments messages of
varying priorities into a continuous sequence of fixed-length data cells,
interrupting the cell stream of lower priority messages with those comprising
higher priority traffic. A high level of noise-tolerance is provided by
dedicating almost half the contents of each cell to Reed-Solomon forward error
correcting code ("ECC") data. Further reliability is achieved by hardware
implementation of algorithms for cell-by-cell receipt acknowledgment, receipt
timeout and retransmission after a tunable round-trip propagation delay, and
separate backpressure flow control for each priority.


  A relative contribution to irradiation hardening caused by dislocation loops
and solute-rich precipitates is established for RPV steels of WWER-440 and
WWER-1000 reactors, based on TEM measurements and mechanical testing at reactor
operating temperature of 563 K. The pinning strength factors evaluated for
loops and precipitates are shown to be much lower than those obtained for model
alloys based on the room temperature testing as well as those evaluated by
means of atomistic simulations in the temperature range of 300 to 600 K. This
discrepancy is explained in the framework of a model of thermally activated
dislocation motion, which takes into account the difference in temperature and
strain rate employed in atomistic simulations and in mechanical testing.


  Conditional Sums-of-AM/GM-Exponentials (conditional SAGE) is a decomposition
method to prove nonnegativity of a signomial or polynomial over some subset $X$
of real space. In this article, we undertake the first structural analysis of
conditional SAGE signomials for convex sets $X$. We introduce the $X$-circuits
of a finite subset $\mathcal{A} \subset \mathbb{R}^n$, which generalize the
simplicial circuits of the affine-linear matroid induced by $\mathcal{A}$ to a
constrained setting. The $X$-circuits serve as the main tool in our analysis
and exhibit particularly rich combinatorial properties for polyhedral $X$, in
which case the set of $X$-circuits is comprised of one-dimensional cones of
suitable polyhedral fans.
  The framework of $X$-circuits transparently reveals when an $X$-nonnegative
conditional AM/GM-exponential can in fact be further decomposed as a sum of
simpler $X$-nonnegative signomials. We develop a duality theory for
$X$-circuits with connections to geometry of sets that are convex according to
the geometric mean. This theory provides an optimal power cone reconstruction
of conditional SAGE signomials when $X$ is polyhedral. In conjunction with a
notion of reduced $X$-circuits, the duality theory facilitates a
characterization of the extreme rays of conditional SAGE cones.
  Since signomials under logarithmic variable substitutions give polynomials,
our results also have implications for nonnegative polynomials and polynomial
optimization.


  The recent Fermilab muon $g-2$ result and the same for electron due to
fine-structure constant measurement through ${}^{133}{\rm Cs}$ matter-wave
interferometry are probed in relation to MSSM with non-holomorphic (NH)
trilinear soft SUSY breaking terms, referred as NHSSM. Supersymmetric
contributions to charged lepton $(g-2)_l$ can be enhanced via the new trilinear
terms involving a wrong Higgs coupling with left and right-handed scalars.
Unlike many MSSM based analyses, the model does not require a light
electroweakino, or light sleptons, or unequal left and right slepton masses, or
a very large higgsino mass parameter. The first part of the analysis involves
$(g-2)_\mu$ constraint along with limits from Higgs mass, B-physics, collider
data, direct detection of dark matter (DM) while focusing on a higgsino DM
which is underabundant in nature. We then impose the constraint from electron
$g-2$ where a large Yukawa threshold corrections (an outcome of NHSSM) and
opposite signs of trilinear NH coefficients associated with $\mu$ and $e$
fields are used to satisfy the dual limits of $\Delta {a_\mu}$ and $\Delta
{a_e}$ (where the latter comes with negative sign). Varying Yukawa threshold
corrections further provide the necessary flavor-dependent enhancement of
$\Delta {a_e}/m_e^2$ compared to that of $\Delta {a_\mu}/m_\mu^2$. A larger
Yukawa threshold correction through $A^\prime_e$ for $y_e$ also takes away the
direct proportionality of $a_e$ with respect to $\tan\beta$. With a finite
intercept, $a_e$ becomes only an increasing function of $\tan\beta$. We
identified the available parameter space in the two cases while also applying
the ATLAS data on slepton pair production in the plane of slepton mass
parameter and the mass of the lightest neutralino.


  Terahertz (THz) frequencies are important for next generation wireless
systems due to the advantages in terms of large available bandwidths. On the
other hand, the limited range due to high attenuation in these frequencies can
be overcome via densely installed heterogeneous networks also utilizing UAVs in
a three-dimensional hyperspace. Yet, THz communications rely on precise beam
alignment, if not handled properly results in low signal strength at the
receiver which impacts THz signals more than conventional ones. This work
focuses on the importance of precise alignment in THz communication systems and
the significant effect of proper alignment is validated through comprehensive
measurements conducted through a state-of-the-art measurement setup, which
enables accurate data collection between 240 GHz to 300 GHz at varying angles
and distances in an anechoic chamber eliminating reflections. By analyzing the
channel frequency and impulse responses of these extensive and particular
measurements, this study provides the first quantifiable results in terms of
measuring the effects of beam misalignment in THz frequencies.


  Offline reinforcement learning (RL) faces a significant challenge of
distribution shift. Model-free offline RL penalizes the Q value for
out-of-distribution (OOD) data or constrains the policy closed to the behavior
policy to tackle this problem, but this inhibits the exploration of the OOD
region. Model-based offline RL, which uses the trained environment model to
generate more OOD data and performs conservative policy optimization within
that model, has become an effective method for this problem. However, the
current model-based algorithms rarely consider agent robustness when
incorporating conservatism into policy. Therefore, the new model-based offline
algorithm with a conservative Bellman operator (MICRO) is proposed. This method
trades off performance and robustness via introducing the robust Bellman
operator into the algorithm. Compared with previous model-based algorithms with
robust adversarial models, MICRO can significantly reduce the computation cost
by only choosing the minimal Q value in the state uncertainty set. Extensive
experiments demonstrate that MICRO outperforms prior RL algorithms in offline
RL benchmark and is considerably robust to adversarial perturbations.


  I discuss the ontological assumptions and implications of General Relativity.
I maintain that General Relativity is a theory about gravitational fields, not
about space-time. The latter is a more basic ontological category, that emerges
from physical relations among all existents. I also argue that there are no
physical singularities in space-time. Singular space-time models do not belong
to the ontology of the world: they are not things but concepts, i.e. defective
solutions of Einstein's field equations. I briefly discuss the actual
implication of the so-called singularity theorems in General Relativity and
some problems related to ontological assumptions of Quantum Gravity.


  The Pais-Uhlenbeck model is a quantum theory described by a higher-derivative
field equation. It has been believed for many years that this model possesses
ghost states (quantum states of negative norm) and therefore that this model is
a physically unacceptable quantum theory. The existence of such ghost states
was believed to be attributable to the field equation having more than two
derivatives. This paper shows that the Pais-Uhlenbeck model does not possess
any ghost states at all and that it is a perfectly acceptable quantum theory.
The supposed ghost states in this model arise if the Hamiltonian of the model
is (incorrectly) treated as being Dirac Hermitian (invariant under combined
matrix transposition and complex conjugation). However, the Hamiltonian is {\it
not} Dirac Hermitian, but rather it is PT symmetric. When it is quantized
correctly according to the rules of PT quantum mechanics, the energy spectrum
is real and bounded below and all of the quantum states have positive norm.


  In this paper,we study spatial central configurations where N bodies are at
the vertices of a regular N-gon $T$ and the other 4 bodies are symmetrically
located on the straight line that is perpendicular to the plane that contains
$T$ and passes through the center of $T$.We study the necessary conditions
about masses for the bodies which can form a central configuration and show the
existence of central configurations for Newtonian N+4-body problems.


  Using the energy spectrum of graphene with spatially modulated potential, we
study the Goos-H\"anshen shifts near extra Dirac points located at finite
energy $\varepsilon=m\pi$, with $m$ integer. On both sides of such points, we
show that the Goos-H\"anshen shifts can be negative as well as positive under
various conditions. It is found that the shifts are strongly depending on the
effects of the incident energy, potential height, incident angle and width of
central region of unit cell. Such effects tell us that such width can be used
to tune the shifts at the extra Dirac points.


  Noise, corruptions and variations in face images can seriously hurt the
performance of face recognition systems. To make such systems robust,
multiclass neuralnetwork classifiers capable of learning from noisy data have
been suggested. However on large face data sets such systems cannot provide the
robustness at a high level. In this paper we explore a pairwise neural-network
system as an alternative approach to improving the robustness of face
recognition. In our experiments this approach is shown to outperform the
multiclass neural-network system in terms of the predictive accuracy on the
face images corrupted by noise.


  Evaluating environmental variables that vary stochastically is the principal
topic for designing better environmental management and restoration schemes.
Both the upper and lower estimates of these variables, such as water quality
indices and flood and drought water levels, are important and should be
consistently evaluated within a unified mathematical framework. We propose a
novel pair of Orlicz regrets to consistently bound the statistics of random
variables both from below and above. Here, consistency indicates that the upper
and lower bounds are evaluated with common coefficients and parameter values
being different from some of the risk measures proposed thus far. Orlicz
regrets can flexibly evaluate the statistics of random variables based on their
tail behavior. The explicit linkage between Orlicz regrets and divergence risk
measures was exploited to better comprehend them. We obtain sufficient
conditions to pose the Orlicz regrets as well as divergence risk measures, and
further provide gradient descent-type numerical algorithms to compute them.
Finally, we apply the proposed mathematical framework to the statistical
evaluation of 31-year water quality data as key environmental indicators in a
Japanese river environment.


  The emergence of multi-petawatt laser facilities is expected to push forward
the maximum energy gain that can be achieved in a single stage of a LWFA to
tens of GeV, which begs the question - is it likely to impact particle physics
by providing a truly compact particle collider? Colliders have very stringent
requirements on beam energy, acceleration efficiency and beam quality. In this
article, we propose a LWFA scheme that can for the first time simultaneously
achieve hitherto unrealized acceleration efficiency from the laser to the
electron beam of >20% and a sub-one percent energy spread using a stepwise
plasma structure and a nonlinearly chirped laser pulse. Three-dimensional
high-fidelity simulations show that the nonlinear chirp can effectively
mitigate the laser waveform distortion and lengthen the acceleration distance.
This combined with an inter-stage rephasing process in the stepwise plasma can
triple the beam energy gain compared to that in a uniform plasma for a fixed
laser energy thereby dramatically increasing the efficiency. A dynamic beam
loading effect can almost perfectly cancel the energy chirp that arises during
the acceleration, leading to the sub-percent energy spread. This scheme is
highly scalable and can be applied to peta-watt LWFA scenarios. Scaling laws
are obtained that suggest electron beams with energy gain of >100 GeV, charge
of 2 nC, and with an energy spread <1% can be realized with a high laser pulse
to particle beam energy transfer efficiency in a LWFA driven by a peta-watt
laser, which could be the basis for a proof of concept of one arm of a future
electron-positron collider.


  We demonstrate a new statistical method of determining the global photometric
properties of the Milky Way (MW) to an unprecedented degree of accuracy,
allowing our Galaxy to be compared directly to objects measured in
extragalactic surveys. Capitalizing on the high-quality imaging and
spectroscopy dataset from the Sloan Digital Sky Survey (SDSS), we exploit the
inherent dependence of galaxies' luminosities and colors on their total stellar
mass, $\mathrm{M}_\star$, and star formation rate (SFR),
$\mathrm{\dot{M}}_\star$, by selecting a sample of $Milky$ $Way$ $analog$
$galaxies$ designed to reproduce the best Galactic $\mathrm{M}_\star$ and
$\mathrm{\dot{M}}_\star$ measurements, including all measurement uncertainties.
Making the Copernican assumption that the MW is not extraordinary amongst
galaxies of similar stellar mass and SFR, we then analyze the photometric
properties of this matched sample, constraining the characteristics of our
Galaxy without suffering interference from interstellar dust. We explore a
variety of potential systematic errors that could affect this method, and find
that they are subdominant to random uncertainties. We present both SDSS $ugriz$
absolute magnitudes and colors in both rest-frame $z$=0 and $z$=0.1 passbands
for the MW, which are in agreement with previous estimates but can have up to
$\sim$3$\times$ lower errors. We find the MW to have absolute magnitude
$^0\!M_r-5\log h=-21.00_{-0.37}^{+0.38}$ and integrated color
$^0(g-r)=0.682_{-0.056}^{+0.066}$, indicating that it may belong to the
green-valley region in color-magnitude space and ranking it amongst the
brightest and reddest of spiral galaxies. We also present new estimates of
global stellar mass-to-light ratios for our Galaxy. This work will help relate
our in-depth understanding of the Galaxy to studies of more distant objects.


  Electromagnetically induced transparency and coherent population trapping
were observed in a hot (1000 K) calcium vapor embedded into an electrical gas
discharge. Unexpectedly large transparencies (of up to 70%) were observed under
very unfavorable conditions: probe wavelength shorter than the coupling
wavelength, and coupling Rabi frequency significantly smaller than the residual
Doppler linewidth of the two photon transition. We developed a theoretical
model that shows that the observed results are due to the combined effects of a
strong probe beam and a small open character of the atomic system. Coherent
population trapping also manifests itself as a change in the impedance of the
gas discharge, and the phenomenon can be probed with high sensitivity via the
optogalvanic effect.


  The theory of cellular automata in operational probabilistic theories is
developed. We start introducing the composition of infinitely many elementary
systems, and then use this notion to define update rules for such infinite
composite systems. The notion of causal influence is introduced, and its
relation with the usual property of signalling is discussed. We then introduce
homogeneity, namely the property of an update rule to evolve every system in
the same way, and prove that systems evolving by a homogeneous rule always
correspond to vertices of a Cayley graph. Next, we define the notion of
locality for update rules. Cellular automata are then defined as homogeneous
and local update rules. Finally, we prove a general version of the wrapping
lemma, that connects CA on different Cayley graphs sharing some small-scale
structure of neighbourhoods.


  We study the ideals of the rational cohomology ring of the Hilbert scheme
X^{[n]} of n points on a smooth projective surface X. As an application, for a
large class of smooth quasi-projective surfaces X, we show that every cup
product structure constant of H^*(X^{[n]}) is independent of n; moreover, we
obtain two sets of ring generators for the cohomology ring H^*(X^{[n]}).
  Similar results are established for the Chen-Ruan orbifold cohomology ring of
the symmetric product. In particular, we prove a ring isomorphism between
H^*(X^{[n]}, C) and H^*_{orb}(X^{[n]}/S_n, C) for a large class of smooth
quasi-projective surfaces with numerically trivial canonical class.


  We have developed a method of solving for multi-species chemical reaction
flows in non--equilibrium and self--consistently with the hydrodynamic
equations in an expanding FLRW universe. The method is based on a backward
differencing scheme for the required stability when solving stiff sets of
equations and is designed to be efficient for three-dimensional calculations
without sacrificing accuracy. In all, 28 kinetic reactions are solved including
both collisional and radiative processes for the following nine separate
species: H, H+, He, He+, He++, H-, H2+, H2, and e-. The method identifies those
reactions (involving H- and H2+) ocurring on the shortest time scales,
decoupling them from the rest of the network and imposing equilibrium
concentrations to good accuracy over typical cosmological dynamical times.
Several tests of our code are presented, including radiative shock waves,
cosmological sheets, conservation constraints, and fully three-dimensional
simulations of CDM cosmological evolutions in which we compare our method to
results obtained when the packaged routine LSODAR is substituted for our
algorithms.


  We discuss family unification in grand unified theory (GUT) based on an
$SU(19)$ GUT gauge group broken to its subgroups including a special subgroup.
In the $SU(19)$ GUT on the six-dimensional (6D) orbifold space $M^4\times
T^2/\mathbb{Z}_2$, three generations of the 4D SM Weyl fermions can be embedded
into a 6D bulk Weyl fermions in an $SU(19)$ second-rank anti-symmetric tensor
representation. 6D and 4D gauge anomalies can be canceled out by considering
proper matter content without 4D exotic chiral fermions at low energies.


  The Airy array beams are attractive for optical manipulation of particles
owing to their non-diffraction and auto-focusing properties. An Airy array
beams is composed of $N$ Airy beams which accelerate mutually and symmetrically
in opposite direction, for different ballistics trajectories, that is, with
different initial launch angles. Based on this, we investigate the optical
force distribution acting on Rayleigh particles. Results show that is possible
to obtain greater stability, for optical trapping, increasing the number of
beams in the array. Also, the intensity focal point and gradient and scattering
force of array on Rayleigh particles can be controlled through a launch angle
parameter.


  The harmonic action functional allows a natural generalisation to
semi-Riemannian supergeometry, referred to as superharmonic action, which
resembles the supersymmetric sigma models studied in high energy physics. We
show that Killing vector fields are infinitesimal supersymmetries of the
superharmonic action and prove three different Noether theorems in this
context. En passant, we provide a homogeneous treatment of five
characterisations of Killing vector fields on semi-Riemannian supermanifolds,
thus filling a gap in the literature.


  In the wake of the COVID-19 virus outbreak, a brief phenomenological
(descriptive, comparative) analysis of the dynamics of the disease spread among
different countries is presented. Results indicate that the infection spread
dynamics is currently the most pronounced in the USA (confirmed cases are
currently doubling every 2.16 days, with a decreasing doubling time tendency),
while other countries with the most confirmed cases show different values, and
tendencies. The reported number of deaths is currently doubled every 2.28 days
in Germany, 2.56 days in France, 2.57 days in Switzerland, 2.59 days in France,
and 2.62 days in USA, while only France and USA are currently exhibiting
further acceleration (diminishing doubling time).


  We have conducted an Arecibo 327 MHz search of two dwarf irregular galaxies
in the Local Group, Leo A and T, for radio pulsars and single pulses from fast
radio bursts and other giant pulse emitters. We detected no astrophysical
signals in this search, and we estimate flux density limits on both periodic
and burst emission. Our derived luminosity limits indicate that only the most
luminous radio pulsars known in our Galaxy and in the Magellanic Clouds (MCs)
would have been detectable in our search if they were at the distances of Leo A
and T. Given the much smaller stellar mass content and star formation rates of
Leo A and T compared to the Milky Way and the MCs, there are likely to be few
(if any) extremely luminous pulsars in these galaxies. It is therefore not
surprising that we detected no pulsars in our search.


  The graphical lasso \citep{FHT2007a} is an algorithm for learning the
structure in an undirected Gaussian graphical model, using $\ell_1$
regularization to control the number of zeros in the precision matrix
${\B\Theta}={\B\Sigma}^{-1}$ \citep{BGA2008,yuan_lin_07}. The {\texttt R}
package \GL\ \citep{FHT2007a} is popular, fast, and allows one to efficiently
build a path of models for different values of the tuning parameter.
Convergence of \GL\ can be tricky; the converged precision matrix might not be
the inverse of the estimated covariance, and occasionally it fails to converge
with warm starts. In this paper we explain this behavior, and propose new
algorithms that appear to outperform \GL.
  By studying the "normal equations" we see that, \GL\ is solving the {\em
dual} of the graphical lasso penalized likelihood, by block coordinate ascent;
a result which can also be found in \cite{BGA2008}.
  In this dual, the target of estimation is $\B\Sigma$, the covariance matrix,
rather than the precision matrix $\B\Theta$. We propose similar primal
algorithms \PGL\ and \DPGL, that also operate by block-coordinate descent,
where $\B\Theta$ is the optimization target. We study all of these algorithms,
and in particular different approaches to solving their coordinate
sub-problems. We conclude that \DPGL\ is superior from several points of view.


  The computational complexity of the solutions $h$ to the ordinary
differential equation $h(0)=0$, $h'(t) = g(t, h(t))$ under various assumptions
on the function $g$ has been investigated. Kawamura showed in 2010 that the
solution $h$ can be PSPACE-hard even if $g$ is assumed to be Lipschitz
continuous and polynomial-time computable. We place further requirements on the
smoothness of $g$ and obtain the following results: the solution $h$ can still
be PSPACE-hard if $g$ is assumed to be of class $C^1$; for each $k\ge2$, the
solution $h$ can be hard for the counting hierarchy even if $g$ is of class
$C^k$.


  The existing methods for Reconfigurable Intelligent Surface (RIS) beamforming
in wireless communication are typically limited to uniform phase quantization.
However, in real world applications, the phase and bit resolution of RIS units
are often non-uniform due to practical requirements and engineering challenges.
To fill this research gap, we formulate an optimization problem for discrete
non-uniform phase configuration in RIS assisted multiple-input single-output
(MISO) communications. Subsequently, a partition-and-traversal (PAT) algorithm
is proposed to solve that, achieving the global optimal solution. The efficacy
and superiority of the PAT algorithm are validated through numerical
simulations, and the impact of non-uniform phase quantization on system
performance is analyzed.


  Many stars exhibit strong magnetic fields, some of which are thought to be of
primordial origin and others a sign of magnetic dynamo processes. We briefly
review the results of observational studies of solar-type stars seeking to
evaluate the linkage between rotation rate and possible magnetic cycles of
activity. Clearly turbulent convection and rotation within spherical shell
geometries provide ingredients essential for dynamo action. However, intensive
efforts over several decades in solar research have demonstrated that it is no
easy matter to achieve cyclic magnetic activity that is in accord with
observations. Helioseismology has revealed that an essential element for the
global solar dynamo is the presence of a tachocline of shear at the base of the
solar convection zone, leading to the likely operation of an interface dynamo.
We review the crucial elements for achieving a cyclic magnetic activity. We
then discuss some of our current 3--D MHD simulations of solar turbulent
convection in spherical shells that yield differential rotation profiles which
make good contact with some of the helioseismic findings. We show that such
turbulent motions can amplify and sustain magnetic field in the bulk of the
convective zone whose strength are sufficient to feed back both upon the
convection and its global circulations.


  We report theoretical investigations of the tomographic procedure suggested
by Itatani {\it et al.} [Nature, {\bf 432} 867 (2004)] for reconstructing
highest occupied molecular orbitals (HOMO) using high-order harmonic generation
(HHG). Using the limited range of harmonics from the plateau region, we found
that under the most favorable assumptions, it is still very difficult to obtain
accurate HOMO wavefunction, but the symmetry of the HOMO and the internuclear
separation between the atoms can be accurately extracted, especially when
lasers of longer wavelengths are used to generate the HHG. We also considered
the possible removal or relaxation of the approximations used in the
tomographic method in actual applications. We suggest that for chemical
imaging, in the future it is better to use an iterative method to locate the
positions of atoms in the molecule such that the resulting HHG best fits the
macroscopic HHG data, rather than by the tomographic method.


  We study ensembles of globally coupled, nonidentical phase oscillators
subject to correlated noise, and we identify several important factors that
cause noise and coupling to synchronize or desychronize a system. By
introducing noise in various ways, we find a novel estimate for the onset of
synchrony of a system in terms of the coupling strength, noise strength, and
width of the frequency distribution of its natural oscillations. We also
demonstrate that noise alone is sufficient to synchronize nonidentical
oscillators. However, this synchrony depends on the first Fourier mode of a
phase-sensitivity function, through which we introduce common noise into the
system. We show that higher Fourier modes can cause desychronization due to
clustering effects, and that this can reinforce clustering caused by different
forms of coupling. Finally, we discuss the effects of noise on an ensemble in
which antiferromagnetic coupling causes oscillators to form two clusters in the
absence of noise.


  Using the publicly available VESPA database of SDSS Data Release 7 spectra,
we calculate the stellar Mass Weighted Age (hereafter MWA) as a function of
local galaxy density and dark matter halo mass. We compare our results with
semi-analytic models from the public Millennium Simulation. We find that the
stellar MWA has a large scatter which is inherent in the data and consistent
with that seen in semi-analytic models. The stellar MWA is consistent with
being independent (to first order) with local galaxy density, which is also
seen in semi-analytic models.
  As a function of increasing dark matter halo mass (using the SDSS New York
Value Added Group catalogues), we find that the average stellar MWA for member
galaxies increases, which is again found in semi-analytic models. Furthermore
we use public dark matter Mass Accretion History (MAH) code calibrated on
simulations, to calculate the dark matter Mass Weighted Age as a function of
dark matter halo mass. In agreement with earlier analyses, we find that the
stellar MWA and the dark matter MWA are anti correlated for large mass halos,
i.e, dark matter accretion does not seem to be the primary factor in
determining when stellar mass was compiled. This effect can be described by
down-sizing.


  The GANs are generative models whose random samples realistically reflect
natural images. It also can generate samples with specific attributes by
concatenating a condition vector into the input, yet research on this field is
not well studied. We propose novel methods of conditioning generative
adversarial networks (GANs) that achieve state-of-the-art results on MNIST and
CIFAR-10. We mainly introduce two models: an information retrieving model that
extracts conditional information from the samples, and a spatial bilinear
pooling model that forms bilinear features derived from the spatial cross
product of an image and a condition vector. These methods significantly enhance
log-likelihood of test data under the conditional distributions compared to the
methods of concatenation.


  Extrusion-based 3D printing is a recent and widely used tissue engineering
tool that provides precise 3D control of bioinks to create organ-size
biomaterial-based objects composed of hierarchically organized cellularized
scaffolds. The internal organization of scaffold constituents should mimic the
structural anisotropy of targeted tissue to stimulate proliferative cellular
behavior during 3D cell culture. Both the choice of polymers constituting the
bioink and the topological properties during the extrusion process greatly
influence the structural anisotropy and cellular response of tissue engineering
constructs. The bioink used in our study was a hydrogel made of three
constituents: fibrinogen, alginate and gelatin. These components provide
biocompatibility, printability and conservation of 3D shape after printing. The
topological properties in flowing polymers are dictated by macromolecule
conformation i.e. their orientation and degree of stretch. In this study, we
used the micro-macro approach to describe the orientation state of hydrogel
macromolecules during the extrusion process, offering a two-scale description
of fluid behavior. The goal of our study was to use the Fokker-Planck equation,
which describes the evolution of probability distribution function over time,
to represent the real state of the constituent population in the representative
elementary volume within a hydrogel during extrusion-based 3D printing. Our
data suggest that for a tubular nozzle syringe, constituent orientation is
driven by a high shear rate, which overcomes the fluid rheological behavior.
Also, the interaction coefficient, which represents the microscopic interaction
between fluid particles overcomes hydrogel behavior for constituent orientation
in the prediction model.


  The 1/2$^-$ resonant states in $^{13}{\rm C}$ are investigated to search for
the Hoyle-analog state. In order to treat the resonance states located around
the 3$\alpha+n$ threshold, the analytic continuation in the coupling constant
(ACCC) has been combined with the real-time evolution method (REM). The
properties of the 1/2$^-$ resonance states such as the radii and monopole
transition probabilities are calculated. We show the 1/2$^-_3$ and 1/2$^-_4$
states are well-developed $\alpha$ cluster states, and the 1/2$^-_4$ state is a
candidate of the Hoyle-analog state.


  Many human-related activities show power-law decaying interevent time
distribution with exponents usually varying between 1 and 2. We study a simple
task-queuing model, which produces bursty time series due to the nontrivial
dynamics of the task list. The model is characterised by a priority
distribution as an input parameter, which describes the choice procedure from
the list. We give exact results on the asymptotic behaviour of the model and we
show that the interevent time distribution is power-law decaying for any kind
of input distributions that remain normalizable in the infinite list limit,
with exponents tunable between 1 and 2. The model satisfies a scaling law
between the exponents of interevent time distribution (alpha) and
autocorrelation function (beta): alpha + beta = 2. This law is general for
renewal processes with power-law decaying interevent time distribution. We
conclude that slowly decaying autocorrelation function indicates long-range
dependency only if the scaling law is violated.


  Background: Thick-target-induced nucleon-adding transfer reactions onto
energetic rare-isotope beams are an emerging spectroscopic tool. Their
sensitivity to single-particle structure complements one-nucleon removal
reaction capabilities in the quest to reveal the evolution of nuclear shell
structure in very exotic nuclei. Purpose: To add intermediate-energy,
carbon-target-induced one-proton pickup reactions to the arsenal of
$\gamma$-ray tagged direct reactions applicable in the regime of low beam
intensities and to apply these for the first time to $fp$-shell nuclei.
Methods: Inclusive and partial cross sections were measured for the
$\nuc{12}{C}(\nuc{48}{Cr},\nuc{49}{Mn}+\gamma)$X and
$\nuc{12}{C}(\nuc{50}{Fe},\nuc{51}{Co}+\gamma)$X proton pickup reactions at
56.7 and 61.2 MeV/nucleon, respectively, using coincident particle-$\gamma$
spectroscopy at the NSCL. The results are compared to reaction theory
calculations using $fp$-shell-model nuclear structure input. For comparison
with our previous work, the same reactions were measured on \nuc{9}{Be}
targets. Results: The measured partial cross sections confirm the specific
population pattern predicted by theory, with pickup into high-$\ell$ orbitals
being strongly favored; driven by linear and angular momentum matching.
Conclusion: Carbon target-induced pickup reactions are well-suited, in the
regime of modest beam intensity, to study the evolution of nuclear structure,
with specific sensitivities that are well described by theory.


  We investigate the rich nonlinear dynamics during the end of hilltop
inflation by numerically solving the coupled Klein-Gordon-Friedmann equations
in a expanding universe. In particular, we search for coherent, nonperturbative
configurations that may emerge due to the combination of nontrivial couplings
between the fields and resonant effects from the cosmological expansion. We
couple a massless field to the inflaton to investigate its effect on the
existence and stability of coherent configurations and the effective equation
of state at reheating. For parameters consistent with data from the Planck and
WMAP satellites, and for a wide range of couplings between the inflaton and the
massless field, we identify a transition from disorder to order characterized
by emergent oscillon-like configurations. We verify that these configurations
can contribute a maximum of roughly 30% of the energy density in the universe.
At late times their contribution to the energy density drops to about 3%, but
they remain long-lived on cosmological time-scales, being stable throughout our
simulations. Cosmological oscillon emergence is described using a new measure
of order in field theory known as relative configurational entropy.


  We study inhomogeneous semilinear parabolic equations with source term f
independent of time u_{t}={\Delta}u+u^{p}+f(x) on a metric measure space,
subject to the conditions that f(x)\geq 0 and u(0,x)=\phi(x)\geq 0. By
establishing Harnack-type inequalities in time t and some powerful estimates,
we give sufficient conditions for non-existence, local existence, and global
existence of weak solutions. This paper generalizes previous results on
Euclidean spaces to general metric measure spaces.


  We have performed quantum chemical computational studies to determine carbon
dioxide affinity to carbon compounds and minerals, which could be present in
shales. These studies shed light on the microscopic mechanisms of the possible
carbon oxide sequestration processes. Our studies reveal that the carbon oxide
can be adsorbed to various forms of carbon structures and also minerals such as
periclase or illite. We find out that the strongest affinity of carbon oxide
towards carbon structures occurs when the carbon structures exhibit $sp^3$
bonds.


  Long-lived radioactive by-products of nucleosynthesis provide an opportunity
to trace the flow of ejecta away from its sources for times beyond where ejecta
can be seen otherwise. Gamma rays from such radioactive decay in interstellar
space can be measured with space-borne telescopes. A prominent useful example
is 26Al with a radioactive decay time of one My. Such observations have
revealed that typical surroundings of massive stars are composed of large
cavities, extending to kpc sizes. Implications are that material recycling into
new stars is twofold: rather direct as parental clouds are hosts to new star
formation triggered by feedback, and more indirect as these large cavities
merge with ambient interstellar gas after some delay. Kinematic measurements of
hot interstellar gas carrying such ejecta promises important measurements
complementing stellar and dense gas kinematics.


  We desribe how we extend R with an external C++ code library by using the
Rcpp package. Our working example uses the recent machine learning library and
application 'Corels' providing optimal yet easily interpretable rule lists
<arXiv:1704.01701> which we bring to R in the form of the 'RcppCorels' package.
We discuss each step in the process, and derive a set of simple rules and
recommendations which are illustrated with the concrete example.


  The effective supersymmetric theory (ESUSY) with R parity conservation cannot
give a large anomalous magnetic moment of $\mu$. It is pointed out that the
flavor conservation and a large $(g-2)_\mu$ within the experimental limits are
achievable in the ESUSY with R parity violating couplings involving the third
generation superparticles.


  At National Institute of Metrological Research (INRIM), a selectable-value
Transportable High dcVoltage Standard (THVS) operating in the range from 10 V
to 100 V in steps of 10 V, was developed. This Standard was built to cover the
lack of high level dc Voltage Standards at voltages higher than 10 V to employ
as laboratory (local) or travelling Standards for Inter-Laboratory Comparisons
(ILCs). A ground-mobile electronic technique was used to enhance the accuracy
of the THVS at the higher values. The THVS shows better noise, better
short-mid-term stability than top level dc Voltage and multifunction
calibrators (MFCs) and better suitability and insensibility to be transported
than these instruments. The project is extensible to 1000 V.


  This work extends the variance reduction method for the pricing of possibly
path-dependent derivatives, which was developed in (Genin and Tankov, 2016) for
exponential L\'evy models, to affine stochastic volatility models
(Keller-Ressel, 2011). We begin by proving a pathwise large deviations
principle for affine stochastic volatility models. We then apply a
time-dependent Esscher transform to the affine process and use Varadhan's
lemma, in the fashion of (Guasoni and Robertson, 2008) and (Robertson, 2010),
to approximate the problem of finding the Esscher measure that minimises the
variance of the Monte-Carlo estimator. We test the method on the Heston model
with and without jumps to demonstrate the numerical efficiency of the method.


  PHENIX has measured $\Upsilon$ production in p+p, d+Au and Au+Au collisions
at $\sqrt{s_{NN}}$=200 GeV. A baseline cross-section measurement has been made
in p+p collisions. Preliminary studies of d+Au collisions found no suppression
in the backward direction, but suppression was observed in the forward
direction indicating the presence of cold nuclear matter effects. In Au+Au
collisions preliminary studies of $\Upsilon$ production at mid-rapidity found
hints of suppression.


  Solution processed {\gamma}-Fe2O3 nanoparticles via the solvothermal
colloidal synthesis in conjunction with ligand-exchange method are used for
interface modification of the top electrode in inverted perovskite solar cells.
In comparison to more conventional top electrodes such as PC(70)BM/Al and
PC(70)BM/AZO/Al, we show that incorporation of a {\gamma}-Fe2O3 provides an
alternative solution processed top electrode (PC(70)BM/{\gamma}-Fe2O3/Al) that
not only results in comparable power conversion efficiencies but also improved
thermal stability of inverted perovskite photovoltaics. The origin of improved
stability of inverted perovskite solar cells incorporating PC(70)BM/
{\gamma}-Fe2O3/Al under accelerated heat lifetime conditions is attributed to
the acidic surface nature of {\gamma}-Fe2O3 and reduced charge trapped density
within PC(70)BM/ {\gamma}-Fe2O3/Al top electrode interfaces.


  According to the current galaxy formation paradigm, mergers and interactions
play an important role in shaping present-day galaxies. The remnants of this
merger activity can be used to constrain galaxy formation models. In this work
we use a sample of thirty hydrodynamical simulations of Milky Way-mass halos,
from the AURIGA project, to generate surface brightness maps and search for the
brightest stream in each halo as a function of varying limiting magnitude. We
find that none of the models shows signatures of stellar streams at
$\mu_{r}^{lim} \leq 25$ mag arcsec$^{-2}$. The stream detection increases
significantly between 27 and 28 mag arcsec$^{-2}$. Nevertheless, even at 30 mag
arcsec$^{-2}$, 13 percent of our models show no detectable streams. We study
the properties of the brightest streams progenitors (BSPs). We find that BSPs
are accreted within a broad range of infall times, from 1.6 to 10 Gyr ago, with
only 25 percent accreted within the last 5 Gyrs; thus most BSPs correspond to
relatively early accretion events. We also find that 37 percent of the BSPs
survive to the present day. The median infall times for surviving and disrupted
BSPs are 5.6 and 6.7 Gyr, respectively. We find a clear relation between infall
time and infall mass of the BSPs, such that more massive progenitors tend to be
accreted at later times. However, we find that the BSPs are not, in most cases,
the dominant contributor to the accreted stellar halo of each galaxy.


  Contemporary Deep Neural Network (DNN) contains millions of synaptic
connections with tens to hundreds of layers. The large computation and memory
requirements pose a challenge to the hardware design. In this work, we leverage
the intrinsic activation sparsity of DNN to substantially reduce the execution
cycles and the energy consumption. An end-to-end training algorithm is proposed
to develop a lightweight run-time predictor for the output activation sparsity
on the fly. From our experimental results, the computation overhead of the
prediction phase can be reduced to less than 5% of the original feedforward
phase with negligible accuracy loss. Furthermore, an energy-efficient hardware
architecture, SparseNN, is proposed to exploit both the input and output
sparsity. SparseNN is a scalable architecture with distributed memories and
processing elements connected through a dedicated on-chip network. Compared
with the state-of-the-art accelerators which only exploit the input sparsity,
SparseNN can achieve a 10%-70% improvement in throughput and a power reduction
of around 50%.


  In this paper, we address analytically and numerically the inversion of the
integral transform (\emph{cone} or \emph{Compton} transform) that maps a
function on $\mathbb{R}^3$ to its integrals over conical surfaces. It arises in
a variety of imaging techniques, e.g. in astronomy, optical imaging, and
homeland security imaging, especially when the so called Compton cameras are
involved.
  Several inversion formulas are developed and implemented numerically in $3D$
(the much simpler $2D$ case was considered in a previous publication). An
admissibility condition on detectors geometry is formulated, under which all
these inversion techniques will work.


  We report on results of fully consistent N-body simulations of globular
cluster models with N = 100 000 members containing neutron stars and black
holes. Using the improved `algorithmic regularization' method of Hellstrom and
Mikkola for compact subsystems, the new code NBODY7 enables for the first time
general relativistic coalescence to be achieved for post-Newtonian terms and
realistic parameters. Following an early stage of mass segregation, a few black
holes form a small dense core which usually leads to the formation of one
dominant binary. The subsequent evolution by dynamical shrinkage involves the
competing processes of ejection and mergers by radiation energy loss. Unless
the binary is ejected, long-lived triple systems often exhibit Kozai cycles
with extremely high inner eccentricity (e > 0.999) which may terminate in
coalescence at a few Schwarzschild radii. A characteristic feature is that
ordinary stars as well as black holes and even BH binaries are ejected with
high velocities. On the basis of the models studied so far, the results suggest
a limited growth of a few remaining stellar mass black holes in globular
clusters.


  Radii of charge and neutron distributions are fundamental nuclear properties.
They depend on both nuclear interaction parameters related to the equation of
state of infinite nuclear matter and on quantal shell effects, which are
strongly impacted by the presence of nuclear surface. In this work, by studying
the dependence of charge and neutron radii, and neutron skin, on nuclear matter
parameters, we assess different mechanisms that drive nuclear sizes. We apply
nuclear density functional theory using a family of Skyrme functionals obtained
by means of different optimization protocols targeting specific nuclear
properties. By performing the Monte-Carlo sampling of reasonable functionals
around the optimal parametrization, we study correlations between nuclear
matter paramaters and observables characterizing charge and neutron
distributions. We demonstrate the existence of the strong converse relation
between the nuclear charge radii and the saturation density of symmetric
nuclear matter and also between the neutron skins and the slope of the symmetry
energy. For functionals optimized to experimental binding energies only, proton
and neutron radii are weakly correlated due to canceling trends from different
nuclear matter parameters. We show that by requiring that the nuclear
functional reproduces the empirical saturation point of symmetric nuclear
matter practically fixes the charge (or proton) radii, and vice versa. The
neutron skin uncertainty primarily depends on the slope of the symmetry energy.
Consequently, imposing a constraint on both $\rho_0$ and $L$ practically
determines the nuclear size, modulo small variations due to shell effects.


  When migrating smart contracts from one blockchain platform to another, there
are potential security risks. This is because different blockchain platforms
have different environments and characteristics for executing smart contracts.
The focus of this paper is to study the security risks associated with the
migration of smart contracts from Ethereum to Arbitrum. We collected relevant
data and analyzed smart contract migration cases to explore the differences
between Ethereum and Arbitrum in areas such as Arbitrum cross-chain messaging,
block properties, contract address alias, and gas fees. From the 36 types of
smart contract migration cases we identified, we selected 4 typical types of
cases and summarized their security risks. The research shows that smart
contracts deployed on Ethereum may face certain potential security risks during
migration to Arbitrum, mainly due to issues inherent in public blockchain
characteristics, such as outdated off-chain data obtained by the inactive
sequencer, logic errors based on time, the permission check failed, Denial of
Service(DOS) attacks. To mitigate these security risks, we proposed avoidance
methods and provided considerations for users and developers to ensure a secure
migration process. It's worth noting that this study is the first to conduct an
in-depth analysis of the secure migration of smart contracts from Ethereum to
Arbitrum.


  The need for dietary data management is growing with public awareness of food
intakes. As a result, there are increasing deployments of smart canteens where
dietary data is collected through either Radio Frequency Identification (RFID)
or Computer Vision(CV)-based solutions. As human labor is involved in both
cases, manpower allocation is critical to data quality. Where manpower
requirements are underestimated, data quality is compromised. This paper has
studied the relation between the quality of dietary data and the manpower
invested, using numerical simulations based on real data collected from
multiple smart canteens. We found that in both RFID and CV-based systems, the
long-term cost of dietary data acquisition is dominated by manpower. Our study
provides a comprehensive understanding of the cost composition for dietary data
acquisition and useful insights toward future cost effective systems.


  Top-down information plays a central role in human perception, but plays
relatively little role in many current state-of-the-art deep networks, such as
Convolutional Neural Networks (CNNs). This work seeks to explore a path by
which top-down information can have a direct impact within current deep
networks. We explore this path by learning and using "generators" corresponding
to the network internal effects of three types of transformation (each a
restriction of a general affine transformation): rotation, scaling, and
translation. We demonstrate how these learned generators can be used to
transfer top-down information to novel settings, as mediated by the "feature
flows" that the transformations (and the associated generators) correspond to
inside the network. Specifically, we explore three aspects: 1) using generators
as part of a method for synthesizing transformed images --- given a previously
unseen image, produce versions of that image corresponding to one or more
specified transformations, 2) "zero-shot learning" --- when provided with a
feature flow corresponding to the effect of a transformation of unknown amount,
leverage learned generators as part of a method by which to perform an accurate
categorization of the amount of transformation, even for amounts never observed
during training, and 3) (inside-CNN) "data augmentation" --- improve the
classification performance of an existing network by using the learned
generators to directly provide additional training "inside the CNN".


  Tempering is used to change the quark mass while remaining in equilibrium
between the trajectories of a standard hybrid Monte Carlo simulation of four
flavours of staggered fermions. The algorithm is faster for small enough quark
masses, and particularly so when more than one mass is required.


  We present an analysis of high-resolution N-body simulations of decaying dark
matter cosmologies focusing on the statistical properties of the transmitted
Lyman-alpha forest flux in the high-redshift intergalactic medium. In this type
of model a dark matter particle decays into a slightly less massive stable dark
matter daughter particle and a comparably light particle. The small mass
splitting provides a non-relativistic kick velocity V_k to the daughter
particle resulting in free-streaming and subsequent damping of small-scale
density fluctuations. Current Lyman-alpha forest power spectrum measurements
probe comoving scales up to ~ 2-3 h^-1 Mpc at redshifts z ~ 2-4, providing one
of the most robust ways to probe cosmological density fluctuations on
relatively small scales. The suppression of structure growth due to the
free-streaming of dark matter daughter particles also has a significant impact
on the neutral hydrogen cloud distribution, which traces the underlying dark
matter distribution well at high redshift. We exploit Lyman-alpha forest power
spectrum measurements to constrain the amount of free-streaming of dark matter
in such models and thereby place limits on decaying dark matter based only on
the dynamics of cosmological perturbations without any assumptions about the
interactions of the decay products. We find that SDSS 1D Lyman-alpha forest
power spectrum data place a lifetime-dependent upper limit V_k < 30-70 km/s for
decay lifetimes < 10 Gyr. This is the most stringent model-independent bound on
invisible dark matter decays with small mass splittings. For large mass
splittings (large V_k), Lyman-alpha forest data restrict the dark matter
lifetime to Gamma^-1 > 40 Gyr. Forthcoming BOSS data should be able to provide
more stringent constraints on exotic dark matter, mainly because the larger
BOSS quasar spectrum sample will significantly reduce statistical errors.


  Elegant and general algorithms for handling upwards-closed and
downwards-closed subsets of WQOs can be developed using the filter-based and
ideal-based representation for these sets. These algorithms can be built in a
generic or parameterized way, in parallel with the way complex WQOs are
obtained by combining or modifying simpler WQOs.


  Relationships form the core of connected learning. In this study, we apply
and extend social network analysis methods to uncover the layered network
structure of relationships among Fanfiction.net authors and reviewers.
Fanfiction.net, one of the world's largest fanfiction communities, is a space
where millions of young people engage with written media, connect over shared
interests, and receive support and mentoring from a distributed audience. Does
an affinity space such as Fanfiction.net have the same structure as social
networks Facebook and Twitter? We applied k-means clustering on millions of
relationships to determine that Fanfiction.net has 2 to 3 layers, in contrast
with the 4-layer structure of Facebook and 5-layer structure of Twitter. In
addition, we conducted a large-scale machine classification of Fanfiction.net
reviews to reveal the types of mentoring exchanged in each layer. Our findings
show that the relationships where reviews are exchanged most frequently are
most likely to contain substantive reviews. We discuss implications of these
findings for the theory of distributed mentoring as well as the design of
online affinity networks.


  We raise the possibility that the chiral degeneracy of the magnons in
ultrathin films can be lifted due to the presence of Dzyaloshinskii-Moriya
interactions. By using simple symmetry arguments, we discuss under which
conditions such a chiral asymmetry occurs. We then perform relativistic first
principles calculations for an Fe monolayer on W(110) and explicitly reveal the
asymmetry of the spin-wave spectrum in case of wave-vectors parallel to the
(001) direction. Furthermore, we quantitatively interpret our results in terms
of a simplified spin-model by using calculated Dzyaloshinskii-Moriya vectors.
Our theoretical prediction should inspire experiments to explore the asymmetry
of spin-waves, with a particular emphasis on the possibility to measure the
Dzyaloshinskii-Moriya interactions in ultrathin films.


  It was proved few years ago that classes of Boolean functions definable by
means of functional equations \cite{EFHH}, or equivalently, by means of
relational constraints \cite{Pi2}, coincide with initial segments of the
quasi-ordered set $(\Omega, \leq)$ made of the set $\Omega$ of Boolean
functions, suitably quasi-ordered. The resulting ordered set $(\Omega/\equiv,
\sqsubseteq)$ embeds into $([\omega]^{<\omega}, \subseteq)$, the set -ordered
by inclusion- of finite subsets of the set $\omega$ of integers. We prove that
$(\Omega/\equiv, \sqsubseteq)$ also embeds $([\omega]^{<\omega}, \subseteq)$.
We prove that initial segments of $(\Omega, \leq)$ which are definable by
finitely many obstructions coincide with classes defined by finitely many
equations. This gives, in particular, that the classes of Boolean functions
with a bounded number of essential variables are finitely definable. As an
example, we provide a concrete characterization of the subclasses made of
linear functions.


  This paper aims to give an elementary proof for Toponogov's theorem in
Alexandrov geometry with lower curvature bound. The idea of the proof comes
from the fact that, in Riemannian geometry, sectional curvature can be embodied
in the second variation formula.


  Eye lens dosimetry has been an important field of research in the last
decade. Dose measurements with a prototype of an active personal eye lens
dosemeter based on the Dosepix detector are presented. The personal dose
equivalent at $3\,$mm depth of soft tissue, $H_\text{p}(3)$, was measured in
the center front of a water-filled cylinder phantom with a height and diameter
of $20\,$cm. The energy dependence of the normalized response is investigated
for mean photon energies between $12.4\,$keV and $248\,$keV for continuous
reference radiation fields (N-series) according to ISO 4037. The response
normalized to N-60 ($\overline{E}=47.9\,\text{keV}$) at $0^\circ$ angle of
irradiation stays within the approval limits of IEC 61526 for angles of
incidence between $-75^\circ$ and $+75^\circ$. Performance in pulsed photon
fields was tested for varying dose rates from $0.1\,\frac{\text{Sv}}{\text{h}}$
up to $1000\,\frac{\text{Sv}}{\text{h}}$ and pulse durations from
$1\,\text{ms}$ up to $10\,\text{s}$. The dose measurement works well within the
approval limits (acc. to IEC 61526) up to $1\,\frac{\text{Sv}}{\text{h}}$. No
significant influence of the pulse duration on the measured dose is found.
Reproducibility measurements yield a coefficient of variation which does not
exceed $1\,\%$ for two tested eye lens dosemeter prototypes.


  A relativistic quark model and a new set of wave functions of nucleon and
Delta have been used to study the electromagnetic propertities of (1/2)^+
baryons and photoelectric production of Delta(1236).


  Quantum metrology enhances measurement precision by utilising the properties
of quantum physics. In interferometry, this is typically achieved by evolving
highly-entangled quantum states before performing single-shot measurements to
reveal information about an unknown parameter. While this is often the optimum
approach, implementation with all but the smallest states is still extremely
challenging. An alternative approach is quantum jump metrology [L. A. Clark et
al., Phys. Rev. A 99, 022102 (2019)] which deduces information by continuously
monitoring an open quantum system, while inducing phase-dependent temporal
correlations with the help of quantum feedback. Taking this approach here, we
analyse measurements of a relative phase in an optical network of two cavities
with quantum feedback in the form of laser pulses. It is shown that the
proposed approach can exceed the standard quantum limit without the need for
complex quantum states while being scalable and more practical than previous
related schemes.


  The membrane instanton superpotential for $M$-theory on the $G_2$ holonomy
manifold given by the cone on ${\bf S^3}\x {\bf S^3}$ is given by the
dilogarithm and has Heisenberg monodromy group in the quantum moduli space. We
compare this to a Heisenberg group action on the type IIA hypermultiplet moduli
space for the universal hypermultiplet, to metric corrections from membrane
instantons related to a twisted dilogarithm for the deformed conifold and to a
flat bundle related to a conifold period, the Heisenberg group and the
dilogarithm appearing in five-dimensional Seiberg/Witten theory.


  All-polymer syntactic foams are studied under large strain cyclic and
monotonic tensile loading in order to reveal their tensile stress-strain
behaviour, recoverability, tensile strength, and elongation at break. The
syntactic foam under study here consists of hollow thermoplastic microspheres
(HTMs) of two distinct grades (551 and 920), with distributions of mean-wall
thicknesses and diameters, embedded inside a polyurethane matrix in various
volume fractions. Cyclic loading-unloading curves are recorded, revealing the
level of viscoelasticity exhibited by the materials (which becomes a stronger
effect with increasing volume fractions of HTMs) and indicating the level of
repeatability of loading under large strain. Samples are also subjected to
monotonic tensile loading in order to study their elongation at break. Higher
volume fractions of HTMs increase the stiffness of the material and whilst it
is observed that the materials are highly elastic over a wide range of tensile
strains, damage arises at lower levels of strain for more highly filled
materials. The HTM syntactic foams thus exhibit lower breaking strains compared
to the neat matrix, which is attributed to matrix-microsphere interfacial
debonding. Furthermore, by employing optimization techniques, linear elastic
properties of the microspheres and an average shell thickness of the 551 grade
are inferred by comparing experimental results to predictions from the
Generalized Self-Consistent Method, incorporating polydispersity data on the
size distribution of the microspheres. These results complement previous work
which involved direct experimental measurements of the 920 grade shell
thickness. Results also indicate that the characterization of microsphere
properties is not critically dependent on access to high resolution microsphere
diameter distribution data, provided that an accurate representative mean
diameter is known.


  Resonant annihilation of ultra-high energy cosmic neutrinos (UHECnu) on the
cosmic neutrino background (CnuB) into Z bosons--the Z-burst mechanism--and its
associated absorption and emission phenomenology provide a unique, albeit
indirect, probe of the CnuB in its present state. In this paper, we examine the
implications of gravitational clustering of the CnuB in nearby galaxy clusters
for the Z-burst phenomenology. In particular, we study the emission features of
the Z-decay products originating from the Virgo cluster, and the potential of
future cosmic ray experiments to observe clustering-enhanced Z-burst rates. We
find that a detector with an exposure equivalent to three years of observations
at the Extreme Universe Space Observatory (EUSO) will very likely measure these
enhanced rates together with the associated UHECnu flux, provided that the
latter saturates current observational limits and the neutrino masses are
quasi-degenerate, m_nu_i < 0.1 eV. In the case of UHECnu fluxes below the
electromagnetic cascade limit, or a hierarchical neutrino mass spectrum, an
experimental sensitivity exceeding that of EUSO by at least two orders of
magnitude is required to detect the clustering enhancements with any certainty.


  We study a nonlinear coupled parabolic system with non-local drift terms
modeling at the continuum level the inter-species interaction within a ternary
mixture that allows the evaporation of one of the species. In the absence of
evaporation, the proposed system coincides with the hydrodynamic limit of a
stochastic interacting particle system of Blume-Capel-type driven by the
Kawasaki dynamics. Similar governing dynamics are found in models used to study
morphology formation in the design of organic solar cells, thin adhesive bands,
and other applications. We investigate the well-posedness of the target system
and present preliminary numerical simulations which incorporate evaporation
into the model. We employ a finite volumes scheme to construct approximations
of the weak solution and illustrate how the evaporation process can affect the
shape and connectivity of the evolving-in-time morphologies.


  (Please refer to arXiv:1810.08050, which has completely different aims but
contains all the main contents of this paper) In this work, we propose to
access the information of criticality and excitations of one-dimensional
quantum systems by a matrix product state (MPS) defined in the (imaginary) time
direction. This state, dubbed as time MPS (tMPS), is a boundary state of tensor
network (TN) that represents the ground-state simulation after Trotter-Suzuki
decomposition. We show that the tMPS exhibits the structure of the continuous
MPS originally proposed for the field theories. The information of excitations,
e.g., dynamic correlation length and energy gap, can be accurately calculated
from the tMPS. The non-universal renormalization of velocity of the excitations
is given by a ratio between the correlations of the ground state and the tMPS.
When the system is at the quantum critical point, the tMPS is found to show the
logarithmic scaling law, where the scaling coefficient gives the central charge
that characterizes the criticality of the theory. Our work also implies that
the spectra of the transfer matrices defined by the ground state and tMPS
provide information of the low-lying masses of the theory in the continuous
limit. This could help to understand the role of the finiteness of the bond
dimension as an infra red regulator. Furthermore, we show from the perspective
of methodology that, the tMPS emerges from a generalized TN ab-initio
optimization principle scheme, which unifies the infinite density matrix
renormalization group and the infinite time-evolving block decimation
algorithms.


  Silicon-MEMS gyroscope is an important part of MEMS (Micro Electrical
Mechanical System). There are some disturb ignored in traditional gyroscope
that must be evaluated newly because of its smaller size (reach the level of
micron). In these disturb, the air pressure largely influences the performance
of MEMS gyroscope. Different air pressure causes different gas damping
coefficient for the MEMS comb linear vibration gyroscope and different gas
damping coefficient influences the quality factor of the gyroscope directive.
The quality factor influences the dynamic working bandwidth of the MEMS comb
linear vibration gyroscope, so it is influences the output characteristic of
the MEMS comb linear vibration gyroscope. The paper shows the relationship
between the air pressure and the output amplified and phase of the detecting
axis through analyzing the air pressure influence on the MEMS comb linear
vibration gyroscope. It discusses the influence on the frequency distribute and
quality factor of the MEMS comb linear vibration gyroscope for different air
pressure.


  Data availability (DA) attack is a well-known problem in certain blockchains
where users accept an invalid block with unavailable portions. Previous works
have used LDPC and 2-D Reed Solomon (2DRS) codes with Merkle trees to mitigate
DA attacks. These codes perform well across various metrics such as DA
detection probability and communication cost. However, these codes are
difficult to apply to blockchains with large blocks due to large decoding
complexity and coding fraud proof size (2D-RS codes), and intractable code
guarantees for large code lengths (LDPC codes). In this paper, we focus on
large block size applications and address the above challenges by proposing the
novel Polar Coded Merkle Tree (PCMT): a Merkle tree encoded using the encoding
graph of polar codes. We provide a specialized polar code design algorithm
called Sampling Efficient Freezing and an algorithm to prune the polar encoding
graph. We demonstrate that the PCMT built using the above techniques results in
a better DA detection probability and communication cost compared to LDPC
codes, has a lower coding fraud proof size compared to LDPC and 2D-RS codes,
provides tractable code guarantees at large code lengths (similar to 2D-RS
codes), and has comparable decoding complexity to 2D-RS and LDPC codes.


  We present and discuss a systematic calculation, based on two-loop chiral
perturbation theory, of the pion-nuclear s-wave optical potential. A proper
treatment of the explicit energy dependence of the off-shell pion self-energy
together with (electromagnetic) gauge invariance of the Klein-Gordon equation
turns out to be crucial. Accurate data for the binding energies and widths of
the 1s and 2p levels in pionic ^{205}Pb and ^{207}Pb are well reproduced, and
the notorious "missing repulsion" in the pion-nuclear s-wave optical potential
is accounted for. The connection with the in-medium change of the pion decay
constant is clarified.


  In the present study an ab initio investigation on the AlN:Er system for
concentrations of Er ranging from 0.78 to 12.5 % is presented. The
crystallographic localisation of the rare earth atoms in the wurtzite lattice
is determined, elucidating previously published experimental deductions, and
the existence of a solid solution in the AlN:Er system in this range is
confirmed. Er incorporation in the tetrahedral and octahedral insertion sites
is shown to be thermodynamically metastable and is found to induce shallow
states in the bandgaps. The effect of Er concentration on the lattice constants
and bandgaps and bandstructures of the ErxAl1-xN ternary compound is presented.
Finally, in accordance with experimental specifications, Er incorporation in
the AlNO system is also examined.


  Interesting magnetic properties and spin-exchange interactions along various
possible pathways in half-integral spin quantum magnetic tetramer system:
A$_{2}$PO$_{4}$OH (A = Co, Cu) are investigated. Interplay of structural
distortion and the magnetic properties with the evolution of localized band
structure explain the gradual transition from a three-dimensional
antiferromagnet to a low-dimensional frustrated magnetic system along the
series. Detailed study of exchange mechanism in this system explores various
possibilities of complex magnetic interaction. Electronic structure of this
series, studied with the help of different appropriate density-functional
approaches like N-th order Muffin-Tin orbital(NMTO) and Planewave
Pseudopotential calculations incorporating onsite Coulomb repulsion(U),
identifies the underlying magnetic exchange mechanism of this series.
Thereafter a generalized minimal model spin-Hamiltonian is constructed for the
low-dimensional system. Solution of this model Hamiltonian within first order
perturbation theory results into the evaluation of spin-gap in the
spin-tetramer system. In addition, the effects of size-confinement and volume
reduction on the relevant exchange integrals and spin-gap of the
low-dimensional system are also discussed.


  The implicit particle filter seeks to mitigate particle degeneracy by
identifying particles in the target distribution's high-probability regions.
This study is motivated by the need to enhance computational tractability in
implementing this approach. We investigate the connection of the particle
update step in the implicit particle filter with that of the Kalman filter and
then formulate a novel realization of the implicit particle filter based on a
bank of nonlinear Kalman filters. This realization is more amenable and
efficient computationally.


  Nonverbal communication, in particular eye contact, is a critical element of
the music classroom, shown to keep students on task, coordinate musical flow,
and communicate improvisational ideas. Unfortunately, this nonverbal aspect to
performance and pedagogy is lost in the virtual classroom. In this paper, we
propose a machine learning system which uses single instance, single camera
image frames as input to estimate the gaze target of a user seated in front of
their computer, augmenting the user's video feed with a display of the
estimated gaze target and thereby restoring nonverbal communication of directed
gaze. The proposed estimation system consists of modular machine learning
blocks, leading to a target-oriented (rather than coordinate-oriented) gaze
prediction. We instantiate one such example of the complete system to run a
pilot study in a virtual music classroom over Zoom software. Inference time and
accuracy meet benchmarks for videoconferencing applications, and quantitative
and qualitative results of pilot experiments include improved success of cue
interpretation and student-reported formation of collaborative, communicative
relationships between conductor and musician.


  The emergence and stability of splay states is studied in fully coupled
finite networks of N excitable quadratic integrate-and-fire neurons, connected
via synapses modeled as pulses of finite amplitude and duration. For such
synapses, by introducing two distinct types of synaptic events (pulse emission
and termination), we were able to write down an exact event-driven map for the
system and to evaluate the splay state solutions. For M overlapping post
synaptic potentials the linear stability analysis of the splay state should
take in account, besides the actual values of the membrane potentials, also the
firing times associated to the M previous pulse emissions. As a matter of fact,
it was possible, by introducing M complementary variables, to rephrase the
evolution of the network as an event-driven map and to derive an analytic
expression for the Floquet spectrum. We find that, independently of M, the
splay state is marginally stable with N-2 neutral directions. Furthermore, we
have identified a family of periodic solutions surrounding the splay state and
sharing the same neutral stability directions. In the limit of $\delta$-pulses,
it is still possible to derive an event-driven formulation for the dynamics,
however the number of neutrally stable directions, associated to the splay
state, becomes N. Finally, we prove a link between the results for our system
and a previous theory [Watanabe and Strogatz, Physica D, 74 (1994), pp. 197-
253] developed for networks of phase oscillators with sinusoidal coupling.


  Analyzing available photometry from the Super WASP and other databases, we
performed the very first light curve analysis of eight eclipsing binary systems
V537 And, GS Boo, AM CrB, V1298 Her, EL Lyn, FW Per, RU Tri, and WW Tri. All of
these systems were found to be detached ones of Algol-type, having the orbital
periods of the order of days. 722 new times of minima for these binaries were
derived and presented, trying to identify the period variations caused by the
third bodies in these systems.


  What is a general expression for the sum of the first n integers, each raised
to the mth power, where m is a positive integer? Answering this question will
be the aim of the paper....We will take the unorthodox approach of presenting
the material from the point of view of someone who is trying to solve the
problem himself. Keywords: analogy, Johann Faulhaber, finite sums, heuristics,
inductive reasoning, number theory, George Polya, problem solving, teaching of
mathematics


  Quantum computation using continuous-time evolution under a natural hardware
Hamiltonian is a promising near- and mid-term direction toward powerful quantum
computing hardware. We investigate the performance of continuous-time quantum
walks as a tool for finding spin glass ground states, a problem that serves as
a useful model for realistic optimization problems. By performing detailed
numerics, we uncover significant ways in which solving spin glass problems
differs from applying quantum walks to the search problem. Importantly, unlike
for the search problem, parameters such as the hopping rate of the quantum walk
do not need to be set precisely for the spin glass ground state problem.
Heuristic values of the hopping rate determined from the energy scales in the
problem Hamiltonian are sufficient for obtaining a better than square-root
scaling. This makes it practical to use quantum walks for solving such
problems, and opens the door for a range of applications on suitable quantum
hardware.


  We show that the class of groups with $k$-multiple context-free word problem
is closed under graphs of groups with finite edge groups.


  We derive various novel free boundary problems as limits of a coupled
bulk-surface reaction-diffusion system modelling ligand-receptor dynamics on
evolving domains. These limiting free boundary problems may be formulated as
Stefan-type problems on an evolving hypersurface. Our results are new even in
the setting where there is no domain evolution. The models are of particular
relevance to a number of applications in cell biology. The analysis utilises
$L^\infty$-estimates in the manner of De Giorgi iterations and other technical
tools, all in an evolving setting. We also report on numerical simulations.


  We present a detailed study of the dust energy balance in the Sombrero galaxy
M104. From a full radiative transfer analysis, including scattering, absorption
and thermal re-emission, we construct models that can reproduce images at
optical/near-infrared wavelengths, the observed stellar SED and the minor axis
extinction profiles in the V and R_C band. A standard model, that contains only
an old stellar population to heat the dust, underestimates the observations of
dust emission at infrared wavelengths by a factor of ~ 3. Supplementing this
basic model with a young stellar component of low star formation activity in
both the inner disk (SFR ~ 0.21 Msun/yr) and dust ring (SFR ~ 0.05 Msun/yr), we
are capable of solving the discrepancy in the dust energy budget of the
Sombrero galaxy at wavelengths shortwards of 100 \mum. To account for the
increased FIR/submm emission beyond 100 \mum, we propose a additional dust
component distributed in quiescent clumps. This model with a clumpy dust
structure predicts three-quarters of the total dust content (~ 2.8 x 10^7 Msun)
to reside in compact dust clouds with no associated embedded sources. Although
the assumption of a clumpy dust structure in the Sombrero galaxy is supported
by high-resolution optical data, we cannot rule out the possibility that dust
grains with a higher dust emissivity account for part of the discrepancy in the
energy budget at submm wavelengths.


  Let $G$ be a connected affine algebraic group and $X$ a regular $G$-variety
(in the sense of Bifet-De Concini-Procesi) with open orbit $G/H$ and boundary
divisor $D$. We show the vanishing of the $G$-equivariant Chern classes of the
bundle of differential forms on $X$ with logarithmic poles along $D$, in
degrees larger than $\dim(X) - \rk(G) + \rk(H)$. Our motivation comes from
Gieseker's degeneration method to prove the Newstead-Ramanan conjecture on the
vanishing of the top Chern classes of the moduli space of stable vector bundles
on a curve.


  We have studied tunneling of electrons into multi-wall carbon nanotubes.
Nanotube/electrode interfaces with low transparency as well as
nanotube/nanotube junctions created with atomic force microscope manipulation
have been used. The tunneling conductance goes to zero as the temperature and
bias are reduced, and the functional form is consistent with a power law
suppression of tunneling as a function of energy. The exponent depends upon
sample geometry. The relationship between these results and theories for
tunneling into ballistic and disordered metals is discussed.


  Well-established cognitive models coming from anthropology have shown that,
due to the cognitive constraints that limit our "bandwidth" for social
interactions, humans organize their social relations according to a regular
structure. In this work, we postulate that similar regularities can be found in
other cognitive processes, such as those involving language production. In
order to investigate this claim, we analyse a dataset containing tweets of a
heterogeneous group of Twitter users (regular users and professional writers).
Leveraging a methodology similar to the one used to uncover the
well-established social cognitive constraints, we find regularities at both the
structural and semantic level. At the former, we find that a concentric layered
structure (which we call ego network of words, in analogy to the ego network of
social relationships) very well captures how individuals organise the words
they use. The size of the layers in this structure regularly grows
(approximately 2-3 times with respect to the previous one) when moving
outwards, and the two penultimate external layers consistently account for
approximately 60% and 30% of the used words, irrespective of the number of the
total number of layers of the user. For the semantic analysis, each ring of
each ego network is described by a semantic profile, which captures the topics
associated with the words in the ring. We find that ring #1 has a special role
in the model. It is semantically the most dissimilar and the most diverse among
the rings. We also show that the topics that are important in the innermost
ring also have the characteristic of being predominant in each of the other
rings, as well as in the entire ego network. In this respect, ring #1 can be
seen as the semantic fingerprint of the ego network of words.


  Obtaining high quality particle distribution representing clean geometry in
pre-processing is essential for the simulation accuracy of the particle-based
methods. In this paper, several level-set based techniques for cleaning up
`dirty' geometries automatically and generating homogeneous particle
distributions are presented. First, a non-resolved structure identifying method
based on level-set field is employed to detect the tiny fragments which make
the geometry `dirty' under a given resolutions. Second, a re-distance algorithm
is proposed to remove the tiny fragments and reconstruct clean and smooth
geometries. Third, a `static confinement' boundary condition is developed in
the particle relaxation process. By complementing the kernel support for the
particles near the geometric surface, the boundary condition achieves better
body-fitted particle distribution on the narrow region with high curvature.
Several numerical examples include a 2D airfoil 30P30N, 3D SPHinXsys symbol, a
skyscraper with a flagpole and an inferior vena cava demonstrate that the
present method not only cleans up the `dirty' geometries efficiently, but also
provides better body-fitted homogeneous particle distribution for complex
geometry.


  A comparison of the structural, optical and electronic properties of the
recently discovered transparent conducting oxide (TCO), nanoporous Ca12Al14O33,
with those of the conventional TCO's (such as Sc-doped CdO) indicates that this
material belongs conceptually to a new class of transparent conductors. For
this class of materials, we formulate criteria for the successful combination
of high electrical conductivity with complete transparency in the visible
range. Our analysis suggests that this set of requirements can be met for a
group of novel materials called electrides.


  The slow neutron capture process in massive stars (the weak s-process)
produces most of the s-only isotopes in the mass region 60 < A < 90. The
nuclear reaction rates used in simulations of this process have a profound
effect on the final s-process yields. We generated 1D stellar models of a 25
solar mass star varying the 12C + 12C rate by a factor of 10 and calculated
full nucleosynthesis using the post-processing code PPN. Increasing or
decreasing the rate by a factor of 10 affects the convective history and
nucleosynthesis, and consequently the final yields.


  Video moment retrieval aims to localize the target moment in an video
according to the given sentence. The weak-supervised setting only provides the
video-level sentence annotations during training. Most existing weak-supervised
methods apply a MIL-based framework to develop inter-sample confrontment, but
ignore the intra-sample confrontment between moments with semantically similar
contents. Thus, these methods fail to distinguish the target moment from
plausible negative moments. In this paper, we propose a novel Regularized
Two-Branch Proposal Network to simultaneously consider the inter-sample and
intra-sample confrontments. Concretely, we first devise a language-aware filter
to generate an enhanced video stream and a suppressed video stream. We then
design the sharable two-branch proposal module to generate positive proposals
from the enhanced stream and plausible negative proposals from the suppressed
one for sufficient confrontment. Further, we apply the proposal regularization
to stabilize the training process and improve model performance. The extensive
experiments show the effectiveness of our method. Our code is released at here.


  Extraordinary dispersion features of a circular waveguide filled by a
longitudinally magnetized composite gyroelectromagnetic medium are studied. The
composite medium is considered to be constructed by juxtaposition together of
magnetic and semiconductor layers providing all characteristic dimensions of
the resulting multilayered system are much smaller than the wavelength in the
corresponding part of the composite medium. The waveguide dispersion equation
and its eigenmodes are derived. The mode classification is made in a standard
manner so that the guided modes are sorted into a class of hybrid HE and EH
waves in terms of their unique dispersion characteristics. The numerical
results are obtained in the band near the frequencies of corresponding
resonances in constitutive materials of the composite medium, and they show
that the modes behaviors become to be quite diverse due to manifestation of a
strong combined geometrical and material dispersion related to the waveguide
parameters and gyroelectromagnetic filling, respectively.