  As the importance of comprehensive evaluation in workshop courses increases,
there is a growing demand for efficient and fair assessment methods that reduce
the workload for faculty members. This paper presents an evaluation conducted
with Large Language Models (LLMs) using actual student essays in three
scenarios: 1) without providing guidance such as rubrics, 2) with pre-specified
rubrics, and 3) through pairwise comparison of essays. Quantitative analysis of
the results revealed a strong correlation between LLM and faculty member
assessments in the pairwise comparison scenario with pre-specified rubrics,
although concerns about the quality and stability of evaluations remained.
Therefore, we conducted a qualitative analysis of LLM assessment comments,
showing that: 1) LLMs can match the assessment capabilities of faculty members,
2) variations in LLM assessments should be interpreted as diversity rather than
confusion, and 3) assessments by humans and LLMs can differ and complement each
other. In conclusion, this paper suggests that LLMs should not be seen merely
as assistants to faculty members but as partners in evaluation committees and
outlines directions for further research.


  We present a deep learning method for the interactive video object
segmentation. Our method is built upon two core operations, interaction and
propagation, and each operation is conducted by Convolutional Neural Networks.
The two networks are connected both internally and externally so that the
networks are trained jointly and interact with each other to solve the complex
video object segmentation problem. We propose a new multi-round training scheme
for the interactive video object segmentation so that the networks can learn
how to understand the user's intention and update incorrect estimations during
the training. At the testing time, our method produces high-quality results and
also runs fast enough to work with users interactively. We evaluated the
proposed method quantitatively on the interactive track benchmark at the DAVIS
Challenge 2018. We outperformed other competing methods by a significant margin
in both the speed and the accuracy. We also demonstrated that our method works
well with real user interactions.


  In this paper, we are concerned with the fractional and higher order
H\'{e}non-Hardy type equations \begin{equation*}
  (-\Delta)^{\frac{\alpha}{2}}u(x)=f(x,u(x)) \,\,\,\,\,\,\,\,\,\,\,\, \text{in}
\,\,\, \mathbb{R}^{n}, \,\,\, \mathbb{R}^{n}_{+} \,\,\, \text{or} \,\,\, \Omega
\end{equation*} with $n>\alpha$, $0<\alpha<2$ or $\alpha=2m$ with $1\leq
m<\frac{n}{2}$. We first consider the typical case $f(x,u)=|x|^{a}u^{p}$ with
$a\in(-\alpha,\infty)$ and $0<p<p_{c}(a):=\frac{n+\alpha+2a}{n-\alpha}$. By
using the method of scaling spheres, we prove Liouville theorems for the above
H\'{e}non-Hardy equations and equivalent integral equations in $\mathbb{R}^{n}$
and $\mathbb{R}^{n}_{+}$. Our results improve the known Liouville theorems for
some especially admissible subranges of $a$ and
$1<p<\min\left\{\frac{n+\alpha+a}{n-\alpha},p_{c}(a)\right\}$ to the full range
$a\in(-\alpha,\infty)$ and $p\in(0,p_{c}(a))$. When $a>0$, we covered the gap
$p\in\big[\frac{n+\alpha+a}{n-\alpha},p_{c}(a)\big)$. In particular, when
$\alpha=2$, our results give an affirmative answer to the conjecture posed by
Phan and Souplet \cite{PS}. As a consequence, we derive a priori estimates and
existence of positive solutions to higher order Lane-Emden equations in bounded
domains for all $1<p<\frac{n+2m}{n-2m}$. Our theorems improve the results in
\cite{CFL,DPQ} remarkably to the maximal range of $p$. For bounded domains
$\Omega$, we also apply the method of scaling spheres to derive Liouville
theorems for super-critical problems. Extensions to PDEs and IEs with general
nonlinearities $f(x,u)$ are also included. We believe the method of scaling
spheres developed here can be applied conveniently to various fractional or
higher order problems with singularities or without translation invariance or
in the cases the method of moving planes in conjunction with Kelvin transforms
do not work.


  In this paper, we propose a new methodology based on the Negative Selection
Algorithm that belongs to the field of Computational Intelligence,
specifically, Artificial Immune Systems to identify takeover targets. Although
considerable research based on customary statistical techniques and some
contemporary Computational Intelligence techniques have been devoted to
identify takeover targets, most of the existing studies are based upon multiple
previous mergers and acquisitions. Contrary to previous research, the novelty
of this proposal lies in its ability to suggest takeover targets for novice
firms that are at the beginning of their merger and acquisition spree. We first
discuss the theoretical perspective and then provide a case study with details
for practical implementation, both capitalizing from unique generalization
capabilities of artificial immune systems algorithms.


  We present spectroscopic observations of the massive multiple system
HD\,167971, located in the open cluster NGC\,6604. The brighter component of
the triple system is the overcontact eclipsing binary MY\,Ser with an orbital
period of 3.32\,days. The radial velocities and the previously published UBV
data obtained by \citet{may10} and the UBVRI light curves by \citet{dav88} are
analysed for the physical properties of the components. We determine the
following absolute parameters: for the primary star M$_p$=32.23$\pm$0.54
M$_{\odot}$, R$_p$=14.23$\pm$0.75 R$_{\odot}$; and for the secondary star
M$_s$=30.59$\pm$0.53 M$_{\odot}$, R$_s$=13.89$\pm$0.75 R$_{\odot}$.
Photoelectric times of minimum light are analyzed under the consideration of
the light-time orbit. The center-of-mass of the eclipsing binary is orbiting
around the common center-of-gravity of the triple system with a period of
21.2$\pm$0.7\,yr and with a projected semi-major axis of 5.5$\pm$0.7\,AU. The
mass function for the third star was calculated as 0.370$\pm$0.036 M$_{\odot}$.
The light contributions of the third star to the triple system in the UBV
pass-bands were derived and the intrinsic magnitudes and colors were calculated
individually for the three stars. The components of the eclipsing pair were
classified as O7.5 {\sc iii} and O9.5 {\sc iii}. The intrinsic color indices
for the third star yield a spectral type of (O9.5-B0) {\sc iii-i}. {\bf This
classification leads to constrain the inclination of the third-body orbit,
which should be about 30$^{o}$, and therefore its mass should be about 29
M$_{\odot}$. MY\,Ser is one of the rare massive O-type triple system at a
distance of 1.65$\pm$0.13\,kpc, the same as for the NGC\,6604 embedded in the
Ser\,OB2 association.}


  We present deep L-Band observations of the equatorial field centered on the
z=6.3 SDSS QSO, reaching a 1 sigma sensitivity of ~2.5 uJy at the center of the
field. We extracted a catalog of 1489 radio sources down to a flux density of
~12.5 uJy (5 sigma) over a field of view of ~ 30' diameter. We derived the
source counts accounting for catalog reliability and completeness, and compared
them with others available in the literature. Our source counts are among the
deepest available so far, and, overall, are consistent with recent counts'
determinations and models. We detected for the first time in the radio band the
SDSS J1030+0524 QSO (26 +/- 5 uJy). We derived its optical radio loudness R_O =
0.62 +/- 0.12, which makes it the most radio quiet AGN at z >~ 6 discovered so
far and detected at radio wavelengths. We unveiled extended diffuse radio
emission associated with the lobes of a bright FRII radio galaxy located close
to the center of the J1030 field, which is likely to become the future BCG of a
protocluster at z=1.7. The lobes' complex morphology, coupled with the presence
of X-ray diffuse emission detected around the FRII galaxy lobes, may point
toward an interaction between the radio jets and the external medium. We also
investigated the relation between radio and X-ray luminosity for a sample of
243 X-ray-selected objects obtained from 500 ks Chandra observations of the
same field, and spanning a wide redshift range (0 ~< z ~< 3). Focused on
sources with a spectroscopic redshift and classification, we found that sources
hosted by ETG and AGN follow Log(L_R)/Log(L_X) linear correlations with slopes
of ~0.6 and ~0.8, respectively. This is interpreted as a likely signature of
different efficiency in the accretion process. Finally, we found that most of
these sources (>~87%) show a radio-to-X-ray radio loudness R_X < -3.5,
classifying these objects as radio quiet.


  In this paper, we investigate the recovery of a sparse weight vector
(parameters vector) from a set of noisy linear combinations. However, only
partial information about the matrix representing the linear combinations is
available. Assuming a low-rank structure for the matrix, one natural solution
would be to first apply a matrix completion on the data, and then to solve the
resulting compressed sensing problem. In big data applications such as massive
MIMO and medical data, the matrix completion step imposes a huge computational
burden. Here, we propose to reduce the computational cost of the completion
task by ignoring the columns corresponding to zero elements in the sparse
vector. To this end, we employ a technique to initially approximate the support
of the sparse vector. We further propose to unify the partial matrix completion
and sparse vector recovery into an augmented four-step problem. Simulation
results reveal that the augmented approach achieves the best performance, while
both proposed methods outperform the natural two-step technique with
substantially less computational requirements.


  For a given morphism of schemes f:X->S, a sheaf F on X, a geometric point x
on X, and s=f(x), the morphism f\_x : X(x) -> S(s) between the strict
henselizations doesn't necessarily behave (with respect to F) like a proper
morphism. However, we know it is so (assuming constructibility of F etc.) if S
is the spectrum of a dvr (P. Deligne, SGA 4 1/2, [Th. finitude]). In this
article, we prove it becomes so after an appropriate modification of the base
S. The main ingredient is a theorem by A.J. de Jong on plurinodal fibrations.
An application of this formalism to Lefschetz pencils is given.


  Public-Private Partnership (PPP) is a contract between a public entity and a
consortium, in which the public outsources the construction and the maintenance
of an equipment (hospital, university, prison...). One drawback of this
contract is that the public may not be able to observe the effort of the
consortium but only its impact on the social welfare of the project. We aim to
characterize the optimal contract for a PPP in this setting of asymmetric
information between the two parties. This leads to a stochastic control under
partial information and it is also related to principal-agent problems with
moral hazard. Considering a wider set of information for the public and using
martingale arguments in the spirit of Sannikov, the optimization problem can be
reduced to a standard stochastic control problem, that is solved numerically.
We then prove that for the optimal contract, the effort of the consortium is
explicitly characterized. In particular, it is shown that the optimal rent is
not a linear function of the effort, contrary to some models of the economic
literature on PPP contracts.


  When modeling real world domains we have to deal with information that is
incomplete or that comes from sources with different trust levels. This
motivates the need for managing uncertainty in the Semantic Web. To this
purpose, we introduced a probabilistic semantics, named DISPONTE, in order to
combine description logics with probability theory. The probability of a query
can be then computed from the set of its explanations by building a Binary
Decision Diagram (BDD). The set of explanations can be found using the tableau
algorithm, which has to handle non-determinism. Prolog, with its efficient
handling of non-determinism, is suitable for implementing the tableau
algorithm. TRILL and TRILLP are systems offering a Prolog implementation of the
tableau algorithm. TRILLP builds a pinpointing formula, that compactly
represents the set of explanations and can be directly translated into a BDD.
Both reasoners were shown to outperform state-of-the-art DL reasoners. In this
paper, we present an improvement of TRILLP, named TORNADO, in which the BDD is
directly built during the construction of the tableau, further speeding up the
overall inference process. An experimental comparison shows the effectiveness
of TORNADO. All systems can be tried online in the TRILL on SWISH web
application at http://trill.ml.unife.it/.


  Task-oriented dialog systems increasingly rely on deep learning-based slot
filling models, usually needing extensive labeled training data for target
domains. Often, however, little to no target domain training data may be
available, or the training and target domain schemas may be misaligned, as is
common for web forms on similar websites. Prior zero-shot slot filling models
use slot descriptions to learn concepts, but are not robust to misaligned
schemas. We propose utilizing both the slot description and a small number of
examples of slot values, which may be easily available, to learn semantic
representations of slots which are transferable across domains and robust to
misaligned schemas. Our approach outperforms state-of-the-art models on two
multi-domain datasets, especially in the low-data setting.


  We show that, besides the usual short distance contribution for CP violation,
final state interactions together with CPT invariance can play an important
role in the recent observation of CP violation in three-body charmless $B^\pm$
decays. A significant part of the observed CP asymmetry distribution in the
Dalitz plot is located in a region where hadronic channels are strongly
coupled. We illustrate our discussion comparing the recent observation of CP
violation in the $B^\pm\to K^\pm K^+ K^-$ and $B^\pm\to K^\pm \pi^+ \pi^-$
phase space, with a calculation based on $\pi\pi\to KK$ scattering.


  Inter-Landau-level transitions in the bilayer graphene at high perpendicular
magnetic field at the filling-factor v<<1 have been studied. The
next-nearest-neighbor transitions, energy difference between dimer and
non-dimer sites and layer asymmetry are included. The influence of Coulomb
interaction is taken into account. The magnetoplasmon excitations in bilayer
graphene at small momenta are considered in the frame of the Hartree-Fock
approximation. It is shown that asymmetry in cyclotron resonance of clean
bilayer graphene depends on magnetic field. At lower magnetic fields the energy
splitting in the spectrum is due to electron-hole one-particle asymmetry, at
higher magnetic fields the energy splitting in the spectrum is due to Coulomb
interaction. For the fullsymmetric case with half-filled zero-energy levels the
energy splitting proportional to the energy of Coulomb interaction is found
both for bilayer and monolayer graphene.


  It is of great interest to understand the equation of state (EOS) of the
neutron star (NS), whose core includes highly dense matter. However, there are
large uncertainties in the theoretical predictions for the EOS of NS. It is
useful to develop a new framework, which is flexible enough to consider the
systematic error in theoretical predictions and to use them as a best guess at
the same time. We employ a deep neural network to perform a non-parametric fit
of the EOS of NS using currently available data. In this framework, the
Gaussian process is applied to represent the EOSs and the training set data
required to close physical solutions. Our model is constructed under the
assumption that the true EOS of NS is a perturbation of the relativistic
mean-field model prediction. We fit the EOSs of NS using two different example
datasets, which can satisfy the latest constraints from the massive neutron
stars, NICER, and the gravitational wave of the binary neutron stars. Given our
assumptions, we find that a maximum neutron star mass is $2.38^{+0.15}_{-0.13}
M_\odot$ or $2.41^{+0.15}_{-0.14}$ at $95\%$ confidence level from two
different example datasets. It implies that the $1.4 M_\odot$ radius is
$12.31^{+0.29}_{-0.31}$ km or $12.30^{+0.35}_{-0.37}$ km. These results are
consistent with results from previous studies using similar priors. It has
demonstrated the recovery of the EOS of NS using a nonparametric model.


  The spin correlation parameters, polarization - $A_{N}$ and double spin
correlation parameters - $A_{NN}$, are calculated in the framework of dynamical
model (GKS) of the hadron-hadron interection in the whole region of small
angles and for energy HERA-N $\sqrt{s}=40 GeV$. It is shown that the
measurements of such spin effects at small trunsfer momenta, in the region of
the dip structure and at $t=-4 GeV^{2}$ have to give significant values of such
spin correlation parameters.


  In this paper we propose and prove that cyclic quorum sets can efficiently
manage all-pairs computations and data replication. The quorums are
O(N/sqrt(P)) in size, up to 50% smaller than the dual N/sqrt(P) array
implementations, and significantly smaller than solutions requiring all data.
Implementation evaluation demonstrated scalability on real datasets with a 7x
speed up on 8 nodes with 1/3rd the memory usage per process. The all-pairs
problem requires all data elements to be paired with all other data elements.
These all-pair problems occur in many science fields, which has led to their
continued interest. Additionally, as datasets grow in size, new methods like
these that can reduce memory footprints and distribute work equally across
compute nodes will be demanded.


  Motivated by the possibility of $H_0t_0 > 1$ where $H_0$ and $t_0$ are the
Hubble parameter and the age of the universe, respectively, we investigate the
cosmology including x-matter. x-matter is expressed by the equation of state
$p_x=w_0\rho_{x0} + c_s^2(\rho_x-\rho_{x0})$, where $p_x$, $\rho_x$ and
$\rho_{x0}$ are the pressure, the density of x-matter and the density at
present, respectively. $w_0$ and $c_s^2$ are functions of $\rho_x$ in general.
x-matter has the most general form of the equation of state which is
characterized by 1)violation of strong energy condition at present for $w_0 <
-1/3$ ; 2) locally stable (i.e. $c_s^2\geq 0$); 3)causality is guaranteed
($c_s\leq 1$). Considering the case that $w_0$ and $c_s^2$ are constants, we
find that there is a large parameter space of $(w_0,c_s^2,\Omega_{x0})$ in
which the model universe is consistent with the age of the universe and the
observations of distant Type I supernovae.


  Pulsars are considered to be the leading explanation for the excess in
cosmic-ray positrons detected by PAMELA and AMS-02. A notable feature of
standard pulsar models is the sharp spectral cutoff produced by the
increasingly efficient cooling of very-high-energy electrons by synchrotron and
inverse-Compton processes. This spectral break has been employed to: (1)
constrain the age of pulsars that contribute to the excess, (2) argue that a
large number of pulsars must significantly contribute to the positron flux, and
(3) argue that spectral cutoffs cannot distinguish between dark matter and
pulsar models. We prove that this spectral feature does not exist -- it appears
due to approximations that treat inverse-Compton scattering as a continuous,
instead of as a discrete and catastrophic, energy-loss process. Astrophysical
sources do not produce sharp spectral features via cooling, reopening the
possibility that such a feature would provide incontrovertible evidence for
dark matter.


  We consider the inverse problem of recovering the magnetic and potential term
of a magnetic Schr\"{o}dinger operator on certain compact Riemannian manifolds
with boundary from partial Dirichlet and Neumann data on suitable subsets of
the boundary. The uniqueness proof relies on proving a suitable Carleman
estimate for functions which vanish only on a part of boundary and constructing
complex geometric optics solutions which vanish on a part of the boundary.


  We follow the dynamics of an ensemble of interacting self-propelled motorized
particles in contact with an equilibrated thermal bath. We find that the
fluctuation-dissipation relation allows for the definition of an effective
temperature that is compatible with the results obtained using a tracer
particle as a thermometer. The effective temperature takes a value which is
higher than the temperature of the bath and it is continuously controlled by
the motor intensity.


  We propose that light-matter coupling can be used to realize synthetic
lattices. In particular, we consider a one-dimensional chain of exciton-photon
sites to create a comb lattice that exhibits a transition from a flat band to a
finite mass dispersion by tuning site-dependent light-matter coupling.
Moreover, in a non-Hermitian system with gain and loss, the flat band phase is
much more robust and the transition is accompanied by the appearance of
exceptional points in the complex energy spectrum. We demonstrate that by
engineering the light-matter coupling in the synthetic lattice, one can explore
various phases in the lasing regime. Our proposal paves the way for studying
non-Hermitian systems in higher dimensions.


  Single image super-resolution (SISR) is of great importance as a low-level
computer vision task. The fast development of Generative Adversarial Network
(GAN) based deep learning architectures realises an efficient and effective
SISR to boost the spatial resolution of natural images captured by digital
cameras. However, the SISR for medical images is still a very challenging
problem. This is due to (1) compared to natural images, in general, medical
images have lower signal to noise ratios, (2) GAN based models pre-trained on
natural images may synthesise unrealistic patterns in medical images which
could affect the clinical interpretation and diagnosis, and (3) the vanilla GAN
architecture may suffer from unstable training and collapse mode that can also
affect the SISR results. In this paper, we propose a novel lesion focused SR
(LFSR) method, which incorporates GAN to achieve perceptually realistic SISR
results for brain tumour MRI images. More importantly, we test and make
comparison using recently developed GAN variations, e.g., Wasserstein GAN
(WGAN) and WGAN with Gradient Penalty (WGAN-GP), and propose a novel
multi-scale GAN (MS-GAN), to achieve a more stabilised and efficient training
and improved perceptual quality of the super-resolved results. Based on both
quantitative evaluations and our designed mean opinion score, the proposed LFSR
coupled with MS-GAN has performed better in terms of both perceptual quality
and efficiency.


  Let K be a field of characteristic zero. We describe an algorithm which
requires a homogeneous polynomial F of degree three in K[x_0,x_1,x_2,x_3] and a
zero A of F in P^3_K and ensures a linear pfaffian representation of V(F) with
entries in K[x_0,x_1,x_2,x_3], under mild assumptions on F and A. We use this
result to give an explicit construction of (and to prove the existence of) a
linear pfaffian representation of V(F), with entries in K'[x_0,x_1,x_2,x_3],
being K' an algebraic extension of K of degree at most six. An explicit example
of such a construction is given.


  We consider the next-to-leading order thermal production rate of heavy
right-handed neutrinos in the non-relativistic regime m_top < pi*T << M, where
m_top refers to the electroweak scale. Rephrasing the problem in an OPE
language and making use of different techniques than a previous analysis by
Salvio et al, we confirm the general structure of their result and many of the
coefficients. We also extend the analysis to the next order in the
non-relativistic expansion, thereby revealing the leading non-trivial momentum
dependence, as well as to NNLO in couplings, revealing the leading sensitivity
to thermal resummations. Our results are expressed as a sum of simple "master"
structures, which renders them a suitable starting point for determining the
next-to-leading order rate also in the relativistic regime pi*T ~ M.


  Social media platforms play an essential role in crisis communication, but
analyzing crisis-related social media texts is challenging due to their
informal nature. Transformer-based pre-trained models like BERT and RoBERTa
have shown success in various NLP tasks, but they are not tailored for
crisis-related texts. Furthermore, general-purpose sentence encoders are used
to generate sentence embeddings, regardless of the textual complexities in
crisis-related texts. Advances in applications like text classification,
semantic search, and clustering contribute to the effective processing of
crisis-related texts, which is essential for emergency responders to gain a
comprehensive view of a crisis event, whether historical or real-time. To
address these gaps in crisis informatics literature, this study introduces
CrisisTransformers, an ensemble of pre-trained language models and sentence
encoders trained on an extensive corpus of over 15 billion word tokens from
tweets associated with more than 30 crisis events, including disease outbreaks,
natural disasters, conflicts, and other critical incidents. We evaluate
existing models and CrisisTransformers on 18 crisis-specific public datasets.
Our pre-trained models outperform strong baselines across all datasets in
classification tasks, and our best-performing sentence encoder improves the
state-of-the-art by 17.43% in sentence encoding tasks. Additionally, we
investigate the impact of model initialization on convergence and evaluate the
significance of domain-specific models in generating semantically meaningful
sentence embeddings. The models are publicly available at:
https://huggingface.co/crisistransformers


  Quantum droplets are ultradilute liquid states which emerge from the
competitive interplay of two Hamiltonian terms, the mean-field energy and
beyond-mean-field correction, in a weakly interacting binary Bose gas. We
relate the formation of droplets in symmetric and asymmetric two-component
one-dimensional boson systems to the modulational instability of a spatially
uniform state driven by the beyond-mean-field term. Asymmetry between the
components may be caused by their unequal populations or unequal
intra-component interaction strengths. Stability of both symmetric and
asymmetric droplets is investigated. Robustness of the symmetric solutions
against symmetry-breaking perturbations is confirmed.


  A new spinning particle with a definite sign of the energy is defined on
spacelike hypersurfaces after a critical discussion of the standard spinning
particles. They are the pseudoclassical basis of the positive energy $({1\over
2},0)$ [or negative energy $(0,{1\over 2})$] parts of the $({1\over 2},{1\over
2})$ solutions of the Dirac equation. The study of the isolated system of N
such spinning charged particles plus the electromagnetic field leads to their
description in the rest-frame Wigner-covariant instant form of dynamics on the
Wigner hyperplanes orthogonal to the total 4-momentum of the isolated system
(when it is timelike). We find that on such hyperplanes these spinning
particles have a nonminimal coupling only of the type "spin-magnetic field"
like the nonrelativistic Pauli particles to which they tend in the
nonrelativistic limit. The Lienard-Wiechert potentials associated with these
charged spinning particles are found. Then, a comment on how to quantize the
spinning particles respecting their fibered structure describing the spin
structure is done.


  We study the electronic transport in a graphene-based
superconductor-normal(graphene)-superconductor (SNS) junction by use of the
Dirac-Bogoliubov-de Gennes equation. We consider the properties of tunneling
conductance through an undoped strip of graphene with heavily doped
superconducting electrodes in the dirty limit. We find that spectrum of Andreev
bound states are modified in the presence of single localized defect in the
bulk. The minimum tunneling conductance remains the same and this result
doesn't depend on the actual location of the imperfection.


  We have investigated electrically-active magnetic excitations
(electromagnons) in perovskite manganites with the $E$-type (up-up-down-down)
spin structure by terahertz spectroscopy. Eu$_{1-x}$Y$_x$MnO$_3$ (0.1$\le
x\le$1) and Y$_{1-y}$Lu$_y$MnO$_3$ (0$\le y\le$1) without magnetic $f$-moments,
which host collinear sinusoidal, $A$-type, cycloidal, and $E$-type spin orders,
are used to examine the systematics of possible electromagnons. Three-peak
structures (23, 35, 45 cm$^{-1}$) of magnetic origin show up in the $E$-type
phase with little composition ($y$) dependence of frequencies, making a
contrast with the electromagnons observed in the cycloidal-spin ($x\le0.8$)
phases. One of these electromagnon is ascribed to the zone-edge magnon mode
based on the calculated magnon dispersions.


  The differences of the ejection-image structures in the chromospheric lines
and the coronal continuum are considered. The outer, more diffusive scattering
envelope of the ejection seems to be produced by the excessive free electrons
due to the Compton effect. The resulting electric field accelerate the
particles while the hard radiation is acting. The directed motion of the
accelerated particles induces the magnetic fields.


  We study the population dynamics of lytic viruses which replicate slowly in
dividing host cells within an organism or cell culture, and find a range of
viral replication rates that allows viruses to persist, avoiding extinction of
host cells or dilution of viruses at too rapid or too slow viral replication.
For the within-host competition between multiple viral strains, a strain with a
"stable" replication rate could outcompete another strain with a higher or
lower replication rate, therefore natural selection of viruses stabilizes the
viral persistence. However, when strains with higher and lower than the
"stable" value replication rates are both present, competition between strains
does not result in dominance of one strain, but in their coexistence.


  Microfluidic mixing is a fundamental functionality in most lab on a chip
(LOC) systems,whereas realization of efficient mixing is challenging in
microfluidic channels due to the small Reynolds numbers. Here, we design and
fabricate a compact three-dimensional (3D) micromixer to enable efficient
mixing at various flow rates. The performance of the fabricated micromixer was
examined using blue and red inks. The extreme flexibility in fabricating
microfluidic structures of arbitrary 3D geometries using femtosecond laser
micromachining allows us to tackle the major disadvantageous effects for
optimizing the mixing efficiency.


  Purpose: Deep Neuroevolution (DNE) holds the promise of providing radiology
artificial intelligence (AI) that performs well with small neural networks and
small training sets. We seek to realize this potential via a proof-of-principle
application to MRI brain sequence classification.
  Methods: We analyzed a training set of 20 patients, each with four
sequences/weightings: T1, T1 post-contrast, T2, and T2-FLAIR. We trained the
parameters of a relatively small convolutional neural network (CNN) as follows:
First, we randomly mutated the CNN weights. We then measured the CNN training
set accuracy, using the latter as the fitness evaluation metric. The fittest
child CNNs were identified. We incorporated their mutations into the parent
CNN. This selectively mutated parent became the next generation's parent CNN.
We repeated this process for approximately 50,000 generations.
  Results: DNE achieved monotonic convergence to 100% training set accuracy.
DNE also converged monotonically to 100% testing set accuracy.
  Conclusions: DNE can achieve perfect accuracy with small training sets and
small CNNs. Particularly when combined with Deep Reinforcement Learning, DNE
may provide a path forward in the quest to make radiology AI more human-like in
its ability to learn. DNE may very well turn out to be a key component of the
much-anticipated meta-learning regime of radiology AI algorithms that can adapt
to new tasks and new image types, similar to human radiologists.


  One exact and two heuristic algorithms for determining the generators, orbits
and order of the graph automorphism group are presented. A basic tool of these
algorithms is the well-known individualization and refinement procedure. A
search tree is used in the algorithms - each node of the tree is a partition.
All nonequivalent discreet partitions derivative of the selected vertices are
stored in a coded form. A new strategy is used in the exact algorithm: if
during its execution some of the searched or intermediate variables obtain a
wrong value then the algorithm continues from a new start point losing some of
the results determined so far. The algorithms has been tested on one of the
known benchmark graphs and shows lower running times for some graph families.
The heuristic versions of the algorithms are based on determining some number
of discreet partitions derivative of each vertex in the selected cell of the
initial partition and comparing them for an automorphism - their search trees
are reduced. The heuristic algorithms are almost exact and are many times
faster than the exact one. The experimental tests exhibit that the worst-cases
running time of the exact algorithm is exponential but it is polynomial for the
heuristic algorithms. Several cell selectors are used. Some of them are new. We
also use a chooser of cell selector for choosing the optimal cell selector for
the manipulated graph. The proposed heuristic algorithms use two main heuristic
procedures that generate two different forests of search trees.


  Online Social Networks (OSNs) allow personalities and companies to
communicate directly with the public, bypassing filters of traditional medias.
As people rely on OSNs to stay up-to-date, the political debate has moved
online too. We witness the sudden explosion of harsh political debates and the
dissemination of rumours in OSNs. Identifying such behaviour requires a deep
understanding on how people interact via OSNs during political debates. We
present a preliminary study of interactions in a popular OSN, namely Instagram.
We take Italy as a case study in the period before the 2019 European Elections.
We observe the activity of top Italian Instagram profiles in different
categories: politics, music, sport and show. We record their posts for more
than two months, tracking "likes" and comments from users. Results suggest that
profiles of politicians attract markedly different interactions than other
categories. People tend to comment more, with longer comments, debating for
longer time, with a large number of replies, most of which are not explicitly
solicited. Moreover, comments tend to come from a small group of very active
users. Finally, we witness substantial differences when comparing profiles of
different parties.


  The new discoveries of circumbinary planetary systems shed light on the
understanding of planetary system formation. Learning the architectural
properties of these systems is essential for constraining the different
formation mechanisms. We first revisit the stability limit of circumbinary
planets. Next, we focus on eclipsing stellar binaries and obtain an analytical
expression for the transit probability in a realistic setting, where finite
observation period and planetary orbital precession are included. Then,
understanding of the architectural properties of the currently observed
transiting systems is refined, based on Bayesian analysis and a series of
hypothesis tests. We find 1) it is not a selection bias that the innermost
planets reside near the stability limit for eight of the nine observed systems,
and this is consistent with a log uniform distribution of the planetary
semi-major axis; 2) it is not a selection bias that the planetary and stellar
orbits are nearly coplanar ($\lesssim 3^\circ$), and this together with
previous studies may imply an occurrence rate of circumbinary planets similar
to that of single star systems; 3) the dominance of observed circumbinary
systems with only one transiting planet may be caused by selection effects; 4)
formation mechanisms involving Lidov-Kozai oscillations, which may produce
misalignment and large separation between planet and stellar binaries, are
consistent with the lack of transiting circumbinary planets around short-period
stellar binaries, in agreement with previous studies. As a consequence of 4),
eclipse timing variations may better suit the detection of planets in such
configurations.


  For highly sensitive real-world predictive analytic applications such as
healthcare and medicine, having good prediction accuracy alone is often not
enough. These kinds of applications require a decision making process which
uses uncertainty estimation as input whenever possible. Quality of uncertainty
estimation is a subject of over or under confident prediction, which is often
not addressed in many models. In this paper we show several extensions to the
Gaussian Conditional Random Fields model, which aim to provide higher quality
uncertainty estimation. These extensions are applied to the temporal disease
graph built from the State Inpatient Database (SID) of California, acquired
from the HCUP. Our experiments demonstrate benefits of using graph information
in modeling temporal disease properties as well as improvements in uncertainty
estimation provided by given extensions of the Gaussian Conditional Random
Fields method.


  The Zn-paratacamite family, Zn$_{x}$Cu$_{4-x}$(OH)$_{6}$Cl$_{2}$ for $x \,
\geq$ 0.33, is an ideal system for studying spin-1/2 frustrated magnetism in
the form of antiferromagnetic Cu$^{2+}$ kagome planes. Here we report a new
synthesis method by which high quality millimeter-sized single crystals of
Zn-paratacamite have been produced. These crystals have been characterized by
metal analysis, x-ray diffraction, neutron diffraction, and thermodynamic
measurements. The $x$ = 1 member of the series displays a magnetic
susceptibility that is slightly anisotropic at high temperatures with $\chi_{c}
\, > \, \chi_{ab}$. Neutron and synchrotron x-ray diffraction experiments
confirm the quality of these $x$ = 1 single crystals and indicate no obvious
structural transition down to temperatures of T=2 K.


  The All-Pairs Shortest Paths (APSP) problem is one of the fundamental
problems in theoretical computer science. It asks to compute the distance
matrix of a given $n$-vertex graph. We revisit the classical problem of
maintaining the distance matrix under a fully dynamic setting undergoing vertex
insertions and deletions with a fast worst-case running time and efficient
space usage.
  Although an algorithm with amortized update-time $\tilde O(n ^ 2)$ has been
known for nearly two decades [Demetrescu and Italiano, STOC 2003], the current
best algorithm for worst-case running time with efficient space usage runs is
due to [Gutenberg and Wulff-Nilsen, SODA 2020], which improves the space usage
of the previous algorithm due to [Abraham, Chechik, and Krinninger, SODA 2017]
to $\tilde O(n ^ 2)$ but fails to improve their running time of $\tilde O(n ^
{2 + 2 / 3})$. It has been conjectured that no algorithm in $O(n ^ {2.5 -
\epsilon})$ worst-case update time exists. For graphs without negative cycles,
we meet this conjectured lower bound by introducing a Monte Carlo algorithm
running in randomized $\tilde O(n ^ {2.5})$ time while keeping the $\tilde O(n
^ 2)$ space bound from the previous algorithm. Our breakthrough is made
possible by the idea of ``hop-dominant shortest paths,'' which are shortest
paths with a constraint on hops (number of vertices) that remain shortest after
we relax the constraint by a constant factor.


  We prove the following conjecture, due to Tomaszewski (1986): Let $X=
\sum_{i=1}^{n} a_{i} x_{i}$, where $\sum_i a_i^2=1$ and each $x_i$ is a
uniformly random sign. Then $\Pr[|X|\leq 1] \geq 1/2$. Our main novel tools are
local concentration inequalities and an improved Berry-Esseen inequality for
Rademacher sums.


  We consider a random walk on a supercritical Galton-Watson tree with leaves,
where the transition probabilities of the walk are determined by biases that
are randomly assigned to the edges of the tree. The biases are chosen
independently on distinct edges, each one according to a given law that
satisfies a logarithmic non-lattice condition. We determine the condition under
which the walk is sub-ballistic, and, in the sub-ballistic regime, we find a
formula for the exponent gamma (which is positive but less than one) such that
the distance | X_n | moved by the walk in time n is of the order of n^gamma. We
prove a stable limiting law for walker distance at late time, proving that the
rescaled walk n^{-gamma} | X_n | converges in distribution to an explicitly
identified function of the stable law of index gamma. This paper is a
counterpart to [4], in which it is proved that, in the model where the biases
on edges are taken to be a given constant, there is a logarithmic periodicity
effect that prevents the existence of a stable limit law for scaled walker
displacement. It is randomization of edge-biases that is responsible for the
emergence of the stable limit in the present article, while also introducing
further correlations into the model in comparison with the constant bias case.
The derivation requires the development of a detailed understanding of trap
geometry and the interplay between traps and backbone.The paper may be
considered as a sequel to [2], since it makes use of a result on the regular
tail of the total conductance of a randomly biased subcritical Galton-Watson
tree.


  Contacting metallic single-walled carbon nanotubes by palladium (Pd) affords
highly reproducible ohmic contacts and allows for detailed elucidation of
ballistic transport in metallic nanotubes. The Pd ohmic contacts are more
reliable than titanium (Ti) previously used for ballistic nanotube devices. In
contrast, Pt contacts appear to give non-ohmic contacts to metallic nanotubes.
For both ohmic and non-ohmic contacts, the length of the nanotube under the
metal contact area is electrically turned off. Transport occurs from metal to
nanotube at the edges of the contacts. Measurements with large numbers of Pd
contacted nanotube samples reveal that the mean free path for defect scattering
in SWNTs grown by chemical vapor deposition can be up to 4 microns. The mean
free paths for acoustic phonon scattering are on the order of 500 nm at room
temperature and >> 4 microns at low temperatures.


  The Galactic center offers us a unique opportunity to test General Relativity
(GR) with the orbits of stars around a supermassive black hole. Observations of
these stars have been one of the great successes of adaptive optics on 8-10 m
telescopes, driving the need for the highest angular resolution and astrometric
precision. New tests of gravitational physics in the strong gravity regime with
stellar orbits will be made possible through the leap in angular resolution and
sensitivity from the next generation of extremely large ground-based
telescopes. We present new simulations of specific science cases such as the
detection of the GR precession of stars, the measurement of extended dark mass,
and the distance to the Galactic center. We use realistic models of the
adaptive optics system for TMT and the IRIS instrument to simulate these
science cases. In additions, the simulations include observational issues such
as the impact of source confusion on astrometry and radial velocities in the
dense environment of the Galactic center. We qualitatively show how
improvements in sensitivity, astrometric and spectroscopic precision, and
increasing the number of stars affect the science with orbits at the Galactic
center. We developed a tool to determine the constraints on physical models
using a joint fit of over 100 stars that are expected to be observable with
TMT. These science cases require very high astrometric precision and stability,
thus they provide some of the most stringent constraints on the planned
instruments and adaptive optics systems.


  The concept of $Diff^4$ invariant Poincare transformations is a cornerstone
of T(opological) G(eometro)D(ynamics). This concept makes it possible to
understand the concept of subjective time and irreversibelity as well as
nontriviality of S-matrix at quantum level. In this paper the possibility of
identifying $Diff^4$ invariant Poincare transformations as the recently
discovered Lorentz invariant deformation of Poincare algebra with the basic
property that 'new' energy is some function of 'old' energy, is considered.


  Due to their characteristic temperature and density, loop structures in
active regions (ARs) can be seen bright in extreme ultraviolet (EUV) and soft
X-ray images. The semiempirical determination of the three-dimensional (3D)
distribution of basic physical parameters (electronic density and temperature,
and magnetic field) is a key constraint for coronal heating models. In this
work we develop a technique for the study of EUV bright loops based on
differential emission measure (DEM) analysis and we first apply it to AR
structures observed by the {Atmospheric Imaging Assembly} (AIA) on board the
{Solar Dynamics Observatory} (SDO). The 3D structure and intensity of the
magnetic field of the observed EUV loops are modelled using force-free field
extrapolations based on magnetograms taken by the {Helioseismic and Magnetic
Imager} (HMI) on board SDO. In this work we report the results obtained for
several bright loops identified in different ARs. Our analysis indicates that
the mean and width of the temperature distributions are nearly invariant along
the loop lengths. For a particular loop we study its temporal evolution and
find that these characteristics remain approximately constant for most of its
life time. The appearance and disappearance of this loop occurs at time-scales
much shorter than its life time of $\approx 2.5$ hours. The results of this
analysis are compared with numerical simulations using the zero-dimensional
(0D) hydrodynamic model, Enthalpy-Based Thermal Evolution of Loops (EBTEL). We
study two alternative heating scenarios: first, we apply a constant heating
rate assuming loops in quasi-static equilibrium, and second, we heat the loops
using impulsive events or nanoflares. We find that all the observed loops are
overdense with respect to a quasi-static equilibrium solution and that the
nanoflare heating better reproduces the observed densities and temperatures.


  We investigate the computationally hard problem whether a random graph of
finite average vertex degree has an extensively large $q$-regular subgraph,
i.e., a subgraph with all vertices having degree equal to $q$. We reformulate
this problem as a constraint-satisfaction problem, and solve it using the
cavity method of statistical physics at zero temperature. For $q=3$, we find
that the first large $q$-regular subgraphs appear discontinuously at an average
vertex degree $c_\reg{3} \simeq 3.3546$ and contain immediately about 24% of
all vertices in the graph. This transition is extremely close to (but different
from) the well-known 3-core percolation point $c_\cor{3} \simeq 3.3509$. For
$q>3$, the $q$-regular subgraph percolation threshold is found to coincide with
that of the $q$-core.


  Let $U^N$ be a family of $N\times N$ independent Haar unitary random matrices
and their adjoints, $Z^N$ a family of deterministic matrices, $P$ a
self-adjoint noncommutative polynomial, i.e. such that for any $N$,
$P(U^N,Z^N)$ is self-adjoint, $f$ a smooth function. We prove that for any $k$,
if $f$ is smooth enough, there exist deterministic constants
$\alpha_i^P(f,Z^N)$ such that $$ \mathbb{E}\left[\frac{1}{N}\text{Tr}\left(
f(P(U^N,Z^N)) \right)\right]\ =\ \sum_{i=0}^k \frac{\alpha_i^P(f,Z^N)}{N^{2i}}\
+\ \mathcal{O}(N^{-2k-2}) .$$ Besides the constants $\alpha_i^P(f,Z^N)$ are
built explicitly with the help of free probability. As a corollary, we prove
that given $\alpha<1/2$, for $N$ large enough, every eigenvalue of $P(U^N,Z^N)$
is $N^{-\alpha}$-close to the spectrum of $P(u,Z^N)$ where $u$ is a $d$-tuple
of free Haar unitaries. We also prove the convergence of the norm of any
polynomial $P(U^N\otimes I_M, I_N\otimes Y^M)$ as long as the family $Y^M$
converges strongly and that $M\ll N \ln^{-5/2}(N)$.


  In order to make a case for or against a trend in the evolution of complexity
in biological evolution, complexity needs to be both rigorously defined and
measurable. A recent information-theoretic (but intuitively evident) definition
identifies genomic complexity with the amount of information a sequence stores
about its environment. We investigate the evolution of genomic complexity in
populations of digital organisms and monitor in detail the evolutionary
transitions that increase complexity. We show that because natural selection
forces genomes to behave as a natural ``Maxwell Demon'', within a fixed
environment genomic complexity is forced to increase.


  This paper presents a combined power system with a common dc bus that
contains solar power, wind power, battery storage, and a constant dc load
(CDL). In wind system, an AC-DC uncontrolled rectifier is used at the first
stage and the DC-DC converter is controlled by a maximum power point tracker
(MPPT) at second stage. In the solar system, two cascaded boost converters are
controlled through a sliding mode controller (SMC) to regulate the power flow
to the load. A supervisory control strategy is also introduced to maximize the
simultaneous energy harvesting from both renewable sources and balance the
energy between the sources, battery, and the load. According to the level of
power generation available at each renewable energy source, the state of charge
in the battery, and the load requirement, the controller results in four
contingencies. Simulation results show the accurate operation of the
supervisory controller and functionality of the maximum power point tracking
algorithm for solar and for wind power.


  Starting from the new sources of $LL$- and $LR$- scalar (slepton) mixings due
to R-parity violation, we discuss the structure of lepton-flavor violation
focusing on the radiative decay of muon into electron. Using an optimal
parametrization, we give the general formulae for the one-loop contributions.
from which we discuss all combinations of R-parity violating parameters having
possibly a substantial contribution to the $\mu \to e \gamma$ decay width. An
exact numerical study is performed to obtain explicit bounds on the parameters
under the present experimental limit. The most interesting one involves a
combination of bilinear and trilinear couplings.


  The axion photon system in an external magnetic field, when the direction of
propagation of axions and photons is orthogonal to the direction of the
external magnetic field, displays a continuous axion-photon duality symmetry in
the limit the axion mass is neglected. The conservation law that follow in this
effective 2+1 dimensional theory from this symmetry is obtained. The magnetic
field interaction is seen to be equivalent to first order to the interaction of
a complex charged field with an external electric potential, where this
ficticious "electric potential" is proportional to the external magnetic field.
This allows one to solve for the scattering amplitudes using already known
scalar QED results. From the scalar QED analog the axion and the photon are
symmetric and antisymmetric combinations of particle and antiparticle. If one
considers therefore scattering experiments in which the two spatial dimensions
of the effective theory are involved non trivially, one observes that both
particle and antiparticle components of photons and axions are preferentially
scattered in different directions, thus producing the splitting or
decomposition of the photon and axion into their particle and antiparticle
components in an inhomogeneous magnetic field. This observable in principle
effect is of first order in the axion photon coupling, unlike the "light
shining through a wall phenomena ", which is second order.


  We study the ground state phase diagram of ultracold dipolar gases in highly
anisotropic traps. Starting from a one-dimensional geometry, by ramping down
the transverse confinement along one direction, the gas reaches various planar
distributions of dipoles. At large linear densities, when the dipolar gas
exhibits a crystal-like phase, critical values of the transverse frequency
exist below which the configuration exhibits novel transverse patterns. These
critical values are found by means of a classical theory, and are in full
agreement with classical Monte Carlo simulations. The study of the quantum
system is performed numerically with Monte Carlo techniques and shows that the
quantum fluctuations smoothen the transition and make it completely disappear
in a gas phase. These predictions could be experimentally tested and would
allow one to reveal the effect of zero-point motion on self-organized
mesoscopic structures of matter waves, such as the transverse pattern of the
zigzag chain.


  The determination of chemical abundances constitutes a fundamental
requirement for obtaining a complete picture of a star. Particularly in massive
stars, CNO abundances are of prime interest, due to the nuclear CNO-cycle and
various mixing processes which bring these elements to the surface.
  We aim at enabling a reliable carbon spectroscopy for our unified NLTE
atmosphere code FASTWIND.
  We develop a new carbon model atom including CII/III/IV/V, and discuss
problems related to carbon spectroscopy in O-type stars. We describe different
tests to examine the reliability of our implementation, and investigate which
mechanisms influence the carbon ionization balance. By comparing with
high-resolution spectra from six O-type stars, we check in how far
observational constraints can be reproduced by our new carbon line synthesis.
  Carbon lines are even more sensitive to a variation of temperature, gravity,
and mass-loss rate, than hydrogen/helium lines. We are able to reproduce most
of the observed lines from our stellar sample, and to estimate those specific
carbon abundances which bring the lines from different ions into agreement. For
hot dwarfs and supergiants earlier than O7, X-rays from wind-embedded shocks
can impact the synthesized line strengths, particularly for CIV, potentially
affecting the abundance determination.
  We have demonstrated our capability to derive realistic carbon abundances by
means of FASTWIND, using our recently developed model atom. We found that
complex effects can have a strong influence on the carbon ionization balance in
hot stars. For a further understanding, the UV range needs to be explored as
well. By means of detailed nitrogen and oxygen model atoms available to use, we
will be able to perform a complete CNO abundance analysis for larger samples of
massive stars, and to provide constraints on corresponding evolutionary models
and aspects.


  Leader-based data replication improves consistency in highly available
distributed storage systems via sequential writes to the leader nodes. After a
write has been committed by the leaders, follower nodes are written by a
multicast mechanism and are only guaranteed to be eventually consistent. With
Age of Information (AoI) as the freshness metric, we characterize how the
number of leaders affects the freshness of the data retrieved by an
instantaneous read query. In particular, we derive the average age of a read
query for a deterministic model for the leader writing time and a probabilistic
model for the follower writing time. We obtain a closed-form expression for the
average age for exponentially distributed follower writing time. Our numerical
results show that, depending on the relative speed of the write operation to
the two groups of nodes, there exists an optimal number of leaders which
minimizes the average age of the retrieved data, and that this number increases
as the relative speed of writing on leaders increases.


  We study a generalized notion of a homogeneous skew-product extension of a
probability-preserving system in which the homogeneous space fibres are allowed
to vary over the ergodic decomposition of the base. The construction of such
extensions rests on a simple notion of `direct integral' for a `measurable
family' of homogeneous spaces, which has a number of precedents in older
literature. The main contribution of the present paper is the systematic
development of a formalism for handling such extensions, including non-ergodic
versions of the results of Mackey describing ergodic components of such
extensions, of the Furstenberg-Zimmer Structure Theory and of results of
Mentzen describing the structure of automorphisms of such extensions when they
are relatively ergodic. We then offer applications to two structural results
for actions of several commuting transformations: firstly to describing the
possible joint distributions of three isotropy factors corresponding to three
commuting transformations; and secondly to describing the characteristic
factors for a system of double nonconventional ergodic averages. Although both
applications are modest in themselves, we hope that they point towards a
broader usefulness of this formalism in ergodic theory.


  Zeeman Doppler imaging has successfully mapped the large-scale magnetic
fields of stars over a large range of spectral types, rotation periods and
ages. When observed over multiple epochs, some stars show polarity reversals in
their global magnetic fields. On the Sun, polarity reversals are a feature of
its activity cycle. In this paper, we examine the magnetic properties of stars
with existing chromospherically determined cycle periods. Previous authors have
suggested that cycle periods lie on multiple branches, either in the cycle
period-Rossby number plane or the cycle period-rotation period plane. We find
some evidence that stars along the active branch show significant average
toroidal fields that exhibit large temporal variations while stars exclusively
on the inactive branch remain dominantly poloidal throughout their entire
cycle. This lends credence to the idea that different shear layers are in
operation along each branch. There is also evidence that the short magnetic
polarity switches observed on some stars are characteristic of the inactive
branch while the longer chromospherically determined periods are characteristic
of the active branch. This may explain the discrepancy between the magnetic and
chromospheric cycle periods found on some stars. These results represent a
first attempt at linking global magnetic field properties obtained form ZDI and
activity cycles.


  Dutch book arguments have been applied to beliefs about the outcomes of
measurements of quantum systems, but not to beliefs about quantum objects prior
to measurement. In this paper, we prove a quantum version of the probabilists'
Dutch book theorem that applies to both sorts of beliefs: roughly, if ideal
beliefs are given by vector states, all and only Born-rule probabilities avoid
Dutch books. This theorem and associated results have implications for
operational and realist interpretations of the logic of a Hilbert lattice. In
the latter case, we show that the defenders of the eigenstate-value orthodoxy
face a trilemma. Those who favor vague properties avoid the trilemma, admitting
all and only those beliefs about quantum objects that avoid Dutch books.


  The problem of nonuniqueness of minimal coupling procedure for
Einstein--Cartan (EC) gravity with matter is investigated. It is shown that the
predictions of the theory of gravity with fermionic matter can radically change
if the freedom of addition of a divergence to the flat space matter Lagrangean
density is exploited. The well--known gravity induced four--fermion interaction
is shown to reveal unexpected features. The solution to the problem of
nonuniqueness of minimal coupling of EC gravity is argued to be necessary in
order for the theory to produce definite predictions. In particular, the EC
theory with fermions is shown to be indistinguishable from usual General
Relativity on the effective level, if the flat space fermionic Lagrangean is
appropriately chosen. Hence, the solution to the problem of nonuniqueness of
minimal coupling procedure is argued to be necessary if EC theory is to be
experimentally verifiable. It could also enable experimental tests of theories
based on EC, such as loop approach to quantisation of gravitational field. Some
ideas of how the arbitrariness incorporated in EC theory could be restricted or
even eliminated are presented.


  Two hydrogen-rich materials, H$_3$S and LaH$_{10}$, synthesized at megabar
pressures, have revolutionized the field of condensed matter physics providing
the first glimpse to the solution of the hundred-year-old problem of room
temperature superconductivity. The mechanism underlying superconductivity in
these exceptional compounds is the conventional electron-phonon coupling. Here
we describe recent advances in experimental techniques, superconductivity
theory and first-principles computational methods which have made possible
these discoveries. This work aims to provide an up-to-date compendium of the
available results on superconducting hydrides and explain how the synergy of
different methodologies led to extraordinary discoveries in the field. Besides,
in an attempt to evidence empirical rules governing superconductivity in binary
hydrides under pressure, we discuss general trends in the electronic structure
and chemical bonding. The last part of the Review introduces possible
strategies to optimize pressure and transition temperatures in conventional
superconducting materials as well as future directions in theoretical,
computational and experimental research.


  This article proposes quantum processing in an optical lattice, using Rydberg
electron's Fermi scattering from ground-state atoms in spin-dependent lattices
as a source of interaction. Instead of relying on Rydberg pair potentials, the
interaction is controlled by engineering the electron cloud of a sole Rydberg
atom. Here we specifically propose the implementation of two prominent
multi-qubit gates i.e. the stabilizer-phase operator and the Toffoli gate. The
new scheme addresses the main bottleneck in Rydberg quantum simulation by
suppressing the population of short-lived Rydberg states over multi-qubit
operations. This scheme mitigates different competing infidelity criteria,
eliminates unwanted cross-talks, and allows operations in dense atomic
lattices. The restoring forces in the molecule type Ryd-Fermi potential
preserve the trapping over a long interaction period. The features in the new
scheme are of special interest for the implementation of quantum optimization
and error correction algorithms.


  Machine learning has enabled the prediction of quantum chemical properties
with high accuracy and efficiency, allowing to bypass computationally costly ab
initio calculations. Instead of training on a fixed set of properties, more
recent approaches attempt to learn the electronic wavefunction (or density) as
a central quantity of atomistic systems, from which all other observables can
be derived. This is complicated by the fact that wavefunctions transform
non-trivially under molecular rotations, which makes them a challenging
prediction target. To solve this issue, we introduce general SE(3)-equivariant
operations and building blocks for constructing deep learning architectures for
geometric point cloud data and apply them to reconstruct wavefunctions of
atomistic systems with unprecedented accuracy. Our model achieves speedups of
over three orders of magnitude compared to ab initio methods and reduces
prediction errors by up to two orders of magnitude compared to the previous
state-of-the-art. This accuracy makes it possible to derive properties such as
energies and forces directly from the wavefunction in an end-to-end manner. We
demonstrate the potential of our approach in a transfer learning application,
where a model trained on low accuracy reference wavefunctions implicitly learns
to correct for electronic many-body interactions from observables computed at a
higher level of theory. Such machine-learned wavefunction surrogates pave the
way towards novel semi-empirical methods, offering resolution at an electronic
level while drastically decreasing computational cost. Additionally, the
predicted wavefunctions can serve as initial guess in conventional ab initio
methods, decreasing the number of iterations required to arrive at a converged
solution, thus leading to significant speedups without any loss of accuracy or
robustness.


  We study anisotropic lattice strips in the presence of a magnetic field in
the quantum Hall effect regime. At specific magnetic fields, causing resonant
Umklapp scattering, the system is gapped in the bulk and supports chiral edge
states in close analogy to topological insulators. These gaps result in
plateaus for the Hall conductivity exactly at the known fillings n/m (both
positive integers and m odd) for the integer and fractional quantum Hall
effect. For double strips we find topological phase transitions with phases
that support midgap edge states with flat dispersion. The topological effects
predicted here could be tested directly in optical lattices.


  We show how to design different couplings between a single ion trapped in a
harmonic potential and an environment. This will provide the basis for the
experimental study of the process of decoherence in a quantum system. The
coupling is due to the absorption of a laser photon and subsequent spontaneous
emission. The variation of the laser frequencies and intensities allows one to
``engineer'' the coupling and select the master equation describing the motion
of the ion.


  We performed path integral simulations of spin evolution controlled by the
Rashba spin-orbit interaction in the semiclassical regime for chaotic and
regular quantum dots. The spin polarization dynamics have been found to be
strikingly different from the D'yakonov-Perel' (DP) spin relaxation in bulk
systems. Also an important distinction have been found between long time spin
evolutions in classically chaotic and regular systems. In the former case the
spin polarization relaxes to zero within relaxation time much larger than the
DP relaxation, while in the latter case it evolves to a time independent
residual value. The quantum mechanical analysis of the spin evolution based on
the exact solution of the Schroedinger equation with Rashba SOI has confirmed
the results of the classical simulations for the circular dot, which is
expected to be valid in general regular systems. In contrast, the spin
relaxation down to zero in chaotic dots contradicts to what have to be expected
from quantum mechanics. This signals on importance at long time of the
mesoscopic echo effect missed in the semiclassical simulations.


  The second H. Weyl curvature invariant of a Riemannian manifold, denoted
$h_4$, is the second curvature invariant which appears in the well known tube
formula of H. Weyl. It coincides with the Gauss-Bonnet integrand in dimension
4.
  A crucial property of $h_4$ is that it is nonnegative for Einstein manifolds,
hence it provides a geometric obstruction to the existence of Einstein metrics
in dimensions $\geq 4$, independently from the sign of the Einstein constant.
This motivates our study of the positivity of this invariant. Here in this
paper, we prove many constructions of metrics with positive second H. Weyl
curvature invariant, generalizing similar well known results for the scalar
curvature.


  A classical theorem of Dirac from 1952 asserts that every graph on $n$
vertices with minimum degree at least $\lceil n/2 \rceil$ is Hamiltonian. In
this paper we extend this result to random graphs. Motivated by the study of
resilience of random graph properties we prove that if $p \gg \log n /n$, then
a.a.s. every subgraph of $G(n,p)$ with minimum degree at least $(1/2+o(1))np$
is Hamiltonian. Our result improves on previously known bounds, and answers an
open problem of Sudakov and Vu. Both, the range of edge probability $p$ and the
value of the constant 1/2 are asymptotically best possible.


  Out-of-distribution (OOD) detection aims to detect "unknown" data whose
labels have not been seen during the in-distribution (ID) training process.
Recent progress in representation learning gives rise to distance-based OOD
detection that recognizes inputs as ID/OOD according to their relative
distances to the training data of ID classes. Previous approaches calculate
pairwise distances relying only on global image representations, which can be
sub-optimal as the inevitable background clutter and intra-class variation may
drive image-level representations from the same ID class far apart in a given
representation space. In this work, we overcome this challenge by proposing
Multi-scale OOD DEtection (MODE), a first framework leveraging both global
visual information and local region details of images to maximally benefit OOD
detection. Specifically, we first find that existing models pretrained by
off-the-shelf cross-entropy or contrastive losses are incompetent to capture
valuable local representations for MODE, due to the scale-discrepancy between
the ID training and OOD detection processes. To mitigate this issue and
encourage locally discriminative representations in ID training, we propose
Attention-based Local PropAgation (ALPA), a trainable objective that exploits a
cross-attention mechanism to align and highlight the local regions of the
target objects for pairwise examples. During test-time OOD detection, a
Cross-Scale Decision (CSD) function is further devised on the most
discriminative multi-scale representations to distinguish ID/OOD data more
faithfully. We demonstrate the effectiveness and flexibility of MODE on several
benchmarks -- on average, MODE outperforms the previous state-of-the-art by up
to 19.24% in FPR, 2.77% in AUROC. Code is available at
https://github.com/JimZAI/MODE-OOD.


  Magnetic particle imaging is an imaging modality of relatively recent origin,
and it exploits the nonlinear magnetization response for reconstructing the
concentration of nanoparticles. Since first invented in 2005, it has received
much interest in the literature. In this work, we study one prototypical
mathematical model in multi-dimension, i.e., the equilibrium model, which
formulates the problem as a linear Fredholm integral equation of the first
kind. We analyze the degree of ill-posedness of the associated linear integral
operator by means of the singular value decay estimate for Sobolev smooth
bivariate functions, and discuss the influence of various experimental
parameters. In particular, applied magnetic fields with a field free point and
a field free line are distinguished. The study is complemented with extensive
numerical experiments.


  We grow epitaxial Sm-Co thin films by sputter deposition from an alloy target
with a nominal SmCo5 composition on Cr(100)-buffered MgO(100) single-crystal
substrates. By varying the Ar gas pressure, we can change the composition of
the film from a SmCo5-like to a Sm2Co7-like phase. The composition, crystal
structure, morphology and magnetic properties of these films have been
determined using Rutherford Backscattering, X-ray diffraction and magnetization
measurements. We find that the various properties are sensitive to the sputter
background pressure in different ways. In particular, the lattice parameter
changes in a continuous way, the coercive fields vary continuously with a
maximum value of 3.3 T, but the saturation magnetization peaks when the lattice
parameter is close to that of Sm2Co7. Moreover, we find that the Sm content of
the films is higher than expected from the expected stoichiometry.


  We give a simple, local process for nodes in an undirected graph to form
non-adjacent clusters that (1) have at most a polylogarithmic diameter and (2)
contain at least half of all vertices. Efficient deterministic distributed
clustering algorithms for computing strong-diameter network decompositions and
other key tools follow immediately. Overall, our process is a direct and
drastically simplified way for computing these fundamental objects.


  We study properties of strongly coupled CFT's with non-zero background
electric charge in 1+1 dimensions by studying the dual gravity theory - which
is a charged BTZ black hole. Correlators of operators dual to scalars, gauge
fields and fermions are studied at both T=0 and $T\neq 0$. In the $T=0$ case we
are also able to compare with analytical results based on $ AdS_2$ and find
reasonable agreement. In particular the correlation between log periodicity and
the presence of finite spectral density of gapless modes is seen. The real part
of the conductivity (given by the current-current correlator) also vanishes as
$\omega \rightarrow 0$ as expected. The fermion Green's function shows
quasiparticle peaks with approximately linear dispersion but the detailed
structure is neither Fermi liquid nor Luttinger liquid and bears some
similarity to a "Fermi-Luttinger" liquid. This is expected since there is a
background charge and the theory is not Lorentz or scale invariant. A boundary
action that produces the observed non-Luttinger-liquid like behavior
($k$-independent non-analyticity at $\omega=0$) in the Greens function is
discussed.


  Dallenbach layer is composed of an absorbing magnetic-dielectric layer
attached to a perfect electric conductor (PEC) sheet. Under linearity and time
invariance (LTI) assumptions Rozanov has established analytically a sum-rule
trade-off between the absorption efficacy over a predefined bandwidth and the
thickness of the layer, that is the so-called Rozanov bound. In recent years
several proposals have been introduced to bypass this bound by using non-LTI
absorbers. However, in practice, their implementation may be challenging. Here,
we expose additional hidden assumptions in Rozanov's derivation, and thus we
introduce several new sum rules for LTI layer absorbers that are not covered by
the original Rozanov's criterion, and give rise to more relaxed constraints on
the absorption limit. We then, demonstrate practical LTI designs of absorbing
thin layers that provide absorption beyond the Rozanov's bound. These designs
are based on the replacement of the original PEC boundary by various types of
penetrable impedance sheet.


  We derive an expression for the drag rate (i.e., interlayer momentum transfer
rate) for carriers in two coupled two-dimensional gases to lowest nonvanishing
order in the screened interlayer electron--electron interaction, valid for {\sl
arbitrary} intralayer scattering mechanisms, using the Boltzmann transport
equation. We calculate the drag rate for experimentally relevant parameters,
and show that for moderately high temperatures ($T\gtrsim 0.2 T_F$, where $T_F$
is the Fermi temperature) the dynamical screening of the interlayer results in
a large enhancement of the drag rate due to the presence of coupled plasmon
modes. This plasmon enhancement causes the scaled drag rate to have a peak (i)
as a function of temperature at $T \approx 0.5 T_F$, and (ii) as a function of
the ratio of densities of the carriers in the two layers when their Fermi
velocities are equal. We also show that the drag rate can be significantly
affected by the {\sl intralayer} scattering mechanisms; in particular, the drag
rate changes approximately by a factor of 2 when the dopant layer modulation
doped structures are moved in from 400~\AA to 100~\AA.


  We analyze here a nonclassical state produced by an atom-cavity field
interaction. The two-level atom is passed through the single-mode
electromagnetic cavity field. By deforming the field operators and introducing
nonlinearity to the classic Jaynes-Cummings model, we explore the system in
respect of a nonlinear Hamiltonian. Assuming that the atom is in an excited
state and the field is in a coherent state initially, the analytic expression
for the state vector of the entire system state vector is obtained. With the
help of the derived state vector, we calculate the photon number distribution,
Mandel's $Q_M$ parameter, Wigner function, anti-bunching, squeezing properties
and $Q$ function etc.


  We theoretically prose and investigate a photo-Otto engine that is working
with a single-mode radiation field inside an optical cavity and alternatively
driven by a hot and a cold reservoir, where the hot reservoir is realized by
sending one of a pair of correlated two-level atoms to pass through the optical
cavity, and the cold one is made of a collection of noninteracting boson modes.
In terms of the quantum discord of the pair of atoms, we derive the analytical
expressions for the performance parameters (power and efficiency) and stability
measure (coefficient of variation for power). We show that quantum discord
boosts the performance and efficiency of the quantum engine, and even may
change the operation mode. We also demonstrate that quantum discord improves
the stability of machine by decreasing the coefficient of variation for power
which satisfies the generalized thermodynamic uncertainty relation. Finally, we
find that these results can be transferred to another photo-Otto engine model,
where the optical cavity is alternatively coupled to a hot thermal bosonic bath
and to a beam of pairs of the two correlated atoms that play the role of a cold
reservoir.


  In this paper, we propose a game-theoretical framework to investigate
advanced persistent threat problems with two types of insider threats:
malicious and inadvertent. Within this framework, a unified three-player game
is established and Nash equilibria are obtained in response to different
insiders. By analyzing Nash equilibria, we provide quantitative solutions to
the advanced persistent threat problems with insider threats. Furthermore,
optimal defense strategy and defender's cost comparisons between two insider
threats have been performed. The findings suggest that the defender should
employ more active defense strategies against inadvertent insider threats than
against malicious insider threats, despite the fact that malicious insider
threats cost the defender more. Our theoretical analysis is validated by
numerical results, including an additional examination of the conditions of the
risky strategies adopted by different insiders. This may help the defender in
determining monitoring intensities and defensive strategies.


  We study how a gluing construction, which produces compact manifolds with
holonomy G_2 from matching pairs of asymptotically cylindrical G_2-manifolds,
behaves under deformations. We show that the gluing construction defines a
smooth map from a moduli space of gluing data to the moduli space of
torsion-free G_2-structures on the glued manifold, and that this is a local
diffeomorphism. We use this to partially compactify the moduli space of
torsion-free G_2-structures, including it as the interior of a topological
manifold with boundary. The boundary points are equivalence classes of matching
pairs of torsion-free asymptotically cylindrical G_2-structures.


  The recent discovery of spin-current transmission through antiferromagnetic
(AFM) insulating materials opens up unprecedented opportunities for fundamental
physics and spintronics applications. The great mystery currently surrounding
this topic is: how could THz AFM magnons mediate a GHz spin current? This
mis-match of frequencies becomes particularly critical for the case of coherent
ac spin-current, raising the fundamental question of whether a GHz ac
spin-current can ever keep its coherence inside an AFM insulator and so drive
the spin precession of another FM layer coherently? Utilizing element- and
time-resolved x-ray pump-probe measurements on Py/Ag/CoO/Ag/Fe75Co25/MgO(001)
heterostructures, we demonstrate that a coherent GHz ac spin current pumped by
the permalloy (Py) ferromagnetic resonance (FMR) can transmit coherently across
an antiferromagnetic CoO insulating layer to drive a coherent spin precession
of the FM Fe75Co25 layer. Further measurement results favor thermal magnons
rather than evanescent spin waves as the mediator of the coherent ac spin
current in CoO.


  This paper addresses the ''Teenager's Problem'': efficiently removing
scattered garments from a planar surface. As grasping and transporting
individual garments is highly inefficient, we propose analytical policies to
select grasp locations for multiple garments using an overhead camera. Two
classes of methods are considered: depth-based, which use overhead depth data
to find efficient grasps, and segment-based, which use segmentation on the RGB
overhead image (without requiring any depth data); grasp efficiency is measured
by Objects per Transport, which denotes the average number of objects removed
per trip to the laundry basket. Experiments suggest that both depth- and
segment-based methods easily reduce Objects per Transport (OpT) by $20\%$;
furthermore, these approaches complement each other, with combined hybrid
methods yielding improvements of $34\%$. Finally, a method employing
consolidation (with segmentation) is considered, which manipulates the garments
on the work surface to increase OpT; this yields an improvement of $67\%$ over
the baseline, though at a cost of additional physical actions.


  Machine learning for data-driven diagnosis has been actively studied in
medicine to provide better healthcare. Supporting analysis of a patient cohort
similar to a patient under treatment is a key task for clinicians to make
decisions with high confidence. However, such analysis is not straightforward
due to the characteristics of medical records: high dimensionality,
irregularity in time, and sparsity. To address this challenge, we introduce a
method for similarity calculation of medical records. Our method employs event
and sequence embeddings. While we use an autoencoder for the event embedding,
we apply its variant with the self-attention mechanism for the sequence
embedding. Moreover, in order to better handle the irregularity of data, we
enhance the self-attention mechanism with consideration of different time
intervals. We have developed a visual analytics system to support comparative
studies of patient records. To make a comparison of sequences with different
lengths easier, our system incorporates a sequence alignment method. Through
its interactive interface, the user can quickly identify patients of interest
and conveniently review both the temporal and multivariate aspects of the
patient records. We demonstrate the effectiveness of our design and system with
case studies using a real-world dataset from the neonatal intensive care unit
of UC Davis.


  A laser can be understood as thermodynamic engine converting heat to a
coherent single mode field close to Carnot efficiency. From this perspective
spectral shaping of the excitation light generates a higher effective
temperature on the pump than on the gain transition. Here, using a toy model of
a quantum well structure with two suitably designed tunnel-coupled wells kept
at different temperature, we study a laser operated on an actual spatial
temperature gradient between pump and gain region. We predict gain and narrow
band laser emission for a sufficient temperature gradient and resonator
quality. Lasing appears concurrent with amplified heat flow and points to a new
form of stimulated solid state cooling. Such a mechanism could raise the
operating temperature limit of quantum cascade lasers by substituting phonon
emission driven injection, which generates intrinsic heat, by an extended model
with phonon absorption steps.


  We consider the high radio frequency (15 GHz - 353 GHz) properties and
variability of 35 Brightest Cluster Galaxies (BCGs). These are the most
core-dominated sources drawn from a parent sample of more than 700 X-ray
selected clusters, thus allowing us to relate our results to the general
population. We find that >6.0% of our parent sample (>15.1% if only cool-core
clusters are considered) contain a radio-source at 150 GHz of at least 3mJy
(~1x10^23 W/Hz at our median redshift of z~0.13). Furthermore, >3.4% of the
BCGs in our parent sample contain a peaked component (Gigahertz Peaked
Spectrum, GPS) in their spectra that peaks above 2 GHz, increasing to >8.5% if
only cool-core clusters are considered. We see little evidence for strong
variability at 15 GHz on short (week-month) time-scales although we see
variations greater than 20% at 150 GHz over 6-month times-frames for 4 of the
23 sources with multi-epoch observations. Much more prevalent is long-term
(year-decade time-scale) variability, with average annual amplitude variations
greater than 1% at 15 GHz being commonplace. There is a weak trend towards
higher variability as the peak of the GPS-like component occurs at higher
frequency. We demonstrate the complexity that is seen in the radio spectra of
BCGs and discuss the potentially significant implications of these high-peaking
components for Sunyaev-Zel'dovich cluster searches.


  We study pore nucleation in a model membrane system, a freestanding polymer
film. Nucleated pores smaller than a critical size close, while pores larger
than the critical size grow. Holes of varying size were purposefully prepared
in liquid polymer films, and their evolution in time was monitored using
optical and atomic force microscopy to extract a critical radius. The critical
radius scales linearly with film thickness for a homopolymer film. The results
agree with a simple model which takes into account the energy cost due to
surface area at the edge of the pore. The energy cost at the edge of the pore
is experimentally varied by using a lamellar-forming diblock copolymer
membrane. The underlying molecular architecture causes increased frustration at
the pore edge resulting in an enhanced cost of pore formation.


  We present a multi-core reconfigurable quantum processor architecture, called
Requp, which supports a hierarchical approach to mapping a quantum algorithm
while sharing physical and logical ancilla qubits. Each core is capable of
performing any quantum instruction. Moreover, we introduce a scalable quantum
mapper, called Squash 2, which divides a given quantum circuit into a number of
quantum modules---each module is divided into k parts such that each part will
run on one of k available cores. Experimental results demonstrate that Squash~2
can handle large-scale quantum algorithms while providing an effective
mechanism for sharing ancilla qubits.


  We prove a version of Manin's conjecture for the projective plane blown up in
three collinear points, the base field being a global field of positive
characteristic.


  In this note, two important transport observables in the RHIC experiment,
relaxation time constant and jet quenching parameter, are calculated from an
AdS/QCD model. A quark moving in the viscous medium such as the
Quark-Gluon-Plasma is modelled by an open string whose end point travels on the
boundary of a deformed AdS_5 black hole. The correction introduced via the
deformed AdS_5 is believed to help us better understand the data which is
expected to be measured in the RHIC.


  We report X-ray structural studies of the metal-insulator phase transition in
bismuth ferrite, BiFeO3, both as a function of temperature and of pressure (931
oC at atmospheric pressure and ca. 45 GPa at ambient temperature). Based on the
experimental results, we argue that the metallic gamma-phase is not
rhombohedral but is instead the same cubic Pm3m structure whether obtained via
high temperature or high pressure, that the MI transition is second order or
very nearly so, that this is a band-type transition due to semi-metal band
overlap in the cubic phase and not a Mott transition, and that it is primarily
structural and not an S=5/2 to S=1/2 high-spin/low-spin electronic transition.
Our data are compatible with the orthorhombic Pbnm structure for the beta-phase
determined definitively by the neutron scattering study of Arnold et al .[Phys.
Rev. Lett. 2009]; the details of this beta-phase had also been controversial,
with a remarkable collection of five crystal classes (cubic, tetragonal,
orthorhombic, monoclinic, and rhombohedral!) all claimed in recent
publications.


  In this paper, we study the Edgeworth expansion for a pre-averaging estimator
of quadratic variation in the framework of continuous diffusion models observed
with noise. More specifically, we obtain a second order expansion for the joint
density of the estimators of quadratic variation and its asymptotic variance.
Our approach is based on martingale embedding, Malliavin calculus and stable
central limit theorems for continuous diffusions. Moreover, we derive the
density expansion for the studentized statistic, which might be applied to
construct asymptotic confidence regions.


  We introduce a parametric family of models to characterize the properties of
astrophysical systems in a quasi-stationary evolution under the incidence
evaporation. We start from an one-particle distribution
$f_{\gamma}\left(\mathbf{q},\mathbf{p}|\beta,\varepsilon_{s}\right)$ that
considers an appropriate deformation of Maxwell-Boltzmann form with inverse
temperature $\beta$, in particular, a power-law truncation at the scape energy
$\varepsilon_{s}$ with exponent $\gamma>0$. This deformation is implemented
using a generalized $\gamma$-exponential function obtained from the
\emph{fractional integration} of ordinary exponential. As shown in this work,
this proposal generalizes models of tidal stellar systems that predict
particles distributions with \emph{isothermal cores and polytropic haloes},
e.g.: Michie-King models. We perform the analysis of thermodynamic features of
these models and their associated distribution profiles. A nontrivial
consequence of this study is that profiles with isothermal cores and polytropic
haloes are only obtained for low energies whenever deformation parameter
$\gamma<\gamma_{c}\simeq 2.13$.


  Bacterial biofilms, surface-attached communities of cells, are in some
respects similar to colloidal solids; both are densely packed with non-zero
yield stresses. However, unlike non-living materials, bacteria reproduce and
die, breaking mechanical equilibrium and inducing collective dynamic responses.
We report experiments and theory investigating the motion of immotile Vibrio
cholerae, which can kill each other and reproduce in biofilms. We vary
viscosity by using bacterial variants that secrete different amounts of
extracellular matrix polymers, but are otherwise identical. Unlike
thermally-driven diffusion, in which diffusivity decreases with increased
viscosity, we find that cellular motion mediated by death and reproduction is
independent of viscosity over timescales relevant to bacterial reproduction. To
understand this surprising result, we use two separate modeling approaches.
First we perform explicitly mechanical simulations of one-dimensional chains of
Voigt-Kelvin elements that can die and reproduce. Next, we perform an
independent statistical approach, modeling Brownian motion with the classic
Langevin equation under an effective temperature that depends on cellular
division rate. The diffusion of cells in both approaches agrees quite well,
supporting a kinetic interpretation for the effective temperature used here and
developed in previous work. As the viscoelastic behavior of biofilms is
believed to play a large role in their anomalous biological properties, such as
antibiotic resistance, the independence of cellular diffusive motion ---
important for biofilm growth and remodeling --- on viscoelastic properties
likely holds ecological, medical, and industrial relevance.


  We review some theoretical and experimental issues in unparticle physics,
focusing mainly on collider signatures.


  The statistical study of voids in the matter distribution promises to be an
important tool for precision cosmology, but there are known discrepancies
between theoretical models of voids and the voids actually found in large
simulations or galaxy surveys. The empirical properties of observed voids are
also not well understood. In this paper, we study voids in an N-body
simulation, using the ZOBOV watershed algorithm. As in other studies, we use
sets of subsampled dark matter particles as tracers to identify voids, but we
use the full-resolution simulation output to measure dark matter densities at
the identified locations. Voids span a wide range of sizes and densities, but
there is a clear trend towards larger voids containing deeper density minima, a
trend which is expected for all watershed void finders. We also find that the
tracer density at void locations is usually smaller than the true density, and
that this relationship depends on the sampling density of tracers. We show that
fits given in the literature fail to match the observed density profiles of
voids. The average enclosed density contrast within watershed voids varies
widely with both the size of the void and the minimum density within it, but is
always far from the shell crossing threshold expected from theoretical models.
Voids with deeper density minima also show much broader density profiles. We
discuss the implications of these results for the excursion set approach to
modelling such voids.


  There are errors in the algorithm proposed by Narendra Chaudhari [2]
purporting to solve the 3-sat problem in polynomial time. The present paper
present instances for which the algorithm outputs erroneous results.


  Let $\Sigma$ be a $k$-dimensional complete proper minimal submanifold in the
Poincar\'{e} ball model $B^n$ of hyperbolic geometry. If we consider $\Sigma$
as a subset of the unit ball $B^n$ in Euclidean space, we can measure the
Euclidean volumes of the given minimal submanifold $\Sigma$ and the ideal
boundary $\partial_\infty \Sigma$, say $\rvol(\Sigma)$ and
$\rvol(\partial_\infty \Sigma)$, respectively. Using this concept, we prove an
optimal linear isoperimetric inequality. We also prove that if
$\rvol(\partial_\infty \Sigma) \geq \rvol(\mathbb{S}^{k-1})$, then $\Sigma$
satisfies the classical isoperimetric inequality. By proving the monotonicity
theorem for such $\Sigma$, we further obtain a sharp lower bound for the
Euclidean volume $\rvol(\Sigma)$, which is an extension of Fraser and Schoen's
recent result \cite{FS} to hyperbolic space. Moreover we introduce the
M\"{o}bius volume of $\Sigma$ in $B^n$ to prove an isoperimetric inequality via
the M\"{o}bius volume for $\Sigma$.


  We analyze the response of a nanomechanical resonator to an external drive
when it is also coupled to a single-electron transistor (SET). The interaction
between the SET electrons and the mechanical resonator depends on the amplitude
of the mechanical motion leading to a strongly non-linear response to the drive
which is similar to that of a Duffing oscillator. We show that the average
dynamics of the resonator is well-described by a simple effective model which
incorporates damping and frequency renormalization terms which are amplitude
dependent. We also find that for a certain range of parameters the system
displays interesting bistable dynamics in which noise arising from charge
fluctuations causes the resonator to switch slowly between different dynamical
states.


  With the increasing demand for greener and more energy efficient
transportation solutions, electric vehicles (EVs) have emerged to be the future
of transportation across the globe. However, currently, one of the biggest
bottlenecks of EVs is the battery. Small batteries limit the EVs driving range,
while big batteries are expensive and not environmentally friendly. One
potential solution to this challenge is the deployment of charging roads, i.e.,
dynamic wireless charging systems installed under the roads that enable EVs to
be charged while driving. In this paper, we use tools from stochastic geometry
to establish a framework that enables evaluating the performance of charging
roads deployment in metropolitan cities. We first present the course of actions
that a driver should take when driving from a random source to a random
destination in order to maximize dynamic charging during the trip. Next, we
analyze the distribution of the distance to the nearest charging road. This
distribution is vital for studying multiple performance metrics such as the
trip efficiency, which we define as the fraction of the total trip spent on
charging roads. Next, we derive the probability that a given trip passes
through at least one charging road. The derived probability distributions can
be used to assist urban planners and policy makers in designing the deployment
plans of dynamic wireless charging systems. In addition, they can also be used
by drivers and automobile manufacturers in choosing the best driving routes
given the road conditions and level of energy of EV battery.


  We prove the sharp global well-posedness results for the initial value
problems (IVPs) associated to the modified Korteweg-de Vries (mKdV) equation
and a system modeled by the coupled modified Korteweg-de Vries equations
(mKdV-system). To obtain our results we use the second generation of the
modified energy and almost conserved quantities, more precisely, the refined
I-method introduced by Colliander, Keel, Staffilani, Takaoka and Tao.


  We examine deformed Poincar\'e algebras containing the exact Lorentz algebra.
We impose constraints which are necessary for defining field theories on these
algebras and we present simple field theoretical examples. Of particular
interest is a case that exhibits improved renormalization properties.


  In this work we provide a novel class of degenerate solutions to the Dirac
equation for massive particles, where the rotation of the spin of the particles
is synchronized with the rotation of the magnetic field of the wave-like
electromagnetic fields corresponding to these solutions. We show that the state
of the particles does not depend on the intensity of the electromagnetic fields
but only on their frequency, which is proportional to the mass of the particles
and lies in the region of Gamma/X-rays for typical elementary charged
particles, such as electrons and protons. These novel theoretical results could
play an important role in plasma physics, astrophysics, and other fields of
physics, involving the interaction of charged particles with high energy
photons.


  We show that any sequence $(x_n)_{n \in \mathbb{N}} \subseteq [0,1]$ that has
Poissonian correlations of $k$-th order is uniformly distributed, also
providing a quantitative description of this phenomenon. Additionally, we
extend connections between metric correlations and additive energy, already
known for pair correlations, to higher orders. Furthermore, we examine how the
property of Poissonian $k$-th correlations is reflected in the asymptotic size
of the moments of the function $F(t,s,N) = #\{n\leq N : \|x_n - t\| \leq s/(2N)
\},\, t\in [0,1]. $