  The relationship linking a galaxy cluster's total mass with the concentration
of its mass profile and its redshift is a fundamental prediction of the Cold
Dark Matter (CDM) paradigm of cosmic structure formation. However, confronting
those predictions with observations is complicated by the fact that simulated
clusters are not representative of observed samples where detailed mass profile
constraints are possible. In this work, we calculate the
Symmetry-Peakiness-Alignment (SPA) morphology metrics for maps of X-ray
emissivity from THE THREE HUNDRED project hydrodynamical simulations of galaxy
clusters at four redshifts, and thereby select a sample of morphologically
relaxed, simulated clusters, using observational criteria. These clusters have
on average earlier formation times than the full sample, confirming that they
are both morphologically and dynamically more relaxed than typical. We
constrain the concentration-mass-redshift relation of both the relaxed and
complete sample of simulated clusters, assuming power-law dependences on mass
($\kappa_m$) and $1+z$ ($\kappa_\zeta$), finding $\kappa_m = -0.12 \pm 0.07$
and $\kappa_\zeta = -0.27 \pm 0.19$ for the relaxed subsample. From an
equivalently selected sample of massive, relaxed clusters observed with ${\it
Chandra}$, we find $\kappa_m = -0.12 \pm 0.08$ and $\kappa_\zeta = -0.48 \pm
0.19$, in good agreement with the simulation predictions. The simulated and
observed samples also agree well on the average concentration at a pivot mass
and redshift providing further validation of the $\Lambda$CDM paradigm in the
properties of the largest gravitationally collapsed structures observed. This
also represents the first clear detection of decreasing concentration with
redshift, a longstanding prediction of simulations, in data.


  We introduce the notion of a stochastic probabilistic program and present a
reference implementation of a probabilistic programming facility supporting
specification of stochastic probabilistic programs and inference in them.
Stochastic probabilistic programs allow straightforward specification and
efficient inference in models with nuisance parameters, noise, and
nondeterminism. We give several examples of stochastic probabilistic programs,
and compare the programs with corresponding deterministic probabilistic
programs in terms of model specification and inference. We conclude with
discussion of open research topics and related work.


  We study the connection between the polymer deposition patterns to appear
following the evaporation of a solution of poly-methyl-methacrylate (PMMA) in
toluene, the transport of the polymer coils in the solution, and the motion of
the meniscus of the solution. Different deposition patterns are observed when
varying the molecular mass and initial concentration of the solute and
temperature and are systematically presented in the form of morphological phase
diagrams. The modi of deposition and meniscus motion are correlated. They vary
with the ratio between the evaporation-driven convective flux and diffusive
flux of the polymer coils in the solution. In the case of a diffusion-dominated
solute transport, the solution monotonically dewets the solid substrate by
evaporation, supporting continuous contact line motion and continuous polymer
deposition. However, a convection-dominated transport results in an oscillatory
ratcheting dewetting-wetting motion of the contact line with more pronounced
dewetting phases. The deposition process is then periodic and produces a stripe
pattern. The oscillatory motion of the meniscus differs from the well
documented stick-slip motion of the meniscus, observed as well, and is
attributed to the opposing influences of evaporation and Marangoni stresses,
which alternately dominate the deposition process.


  Recent advances in quantum computing have drawn considerable attention to
building realistic application for and using quantum computers. However,
designing a suitable quantum circuit architecture requires expert knowledge.
For example, it is non-trivial to design a quantum gate sequence for generating
a particular quantum state with as fewer gates as possible. We propose a
quantum architecture search framework with the power of deep reinforcement
learning (DRL) to address this challenge. In the proposed framework, the DRL
agent can only access the Pauli-$X$, $Y$, $Z$ expectation values and a
predefined set of quantum operations for learning the target quantum state, and
is optimized by the advantage actor-critic (A2C) and proximal policy
optimization (PPO) algorithms. We demonstrate a successful generation of
quantum gate sequences for multi-qubit GHZ states without encoding any
knowledge of quantum physics in the agent. The design of our framework is
rather general and can be employed with other DRL architectures or optimization
methods to study gate synthesis and compilation for many quantum states.


  We propose a topological inflation model in supergravity. In this model, the
vacuum expectation value (VEV) of a scalar field takes a value much larger than
the gravitational scale $M_{G} \simeq 2.4 \times 10^{18}$ GeV, which is large
enough to cause topological inflation. On the other hand, expansions of the
K\"ahler potential and the superpotential beyond the gravitational scale are
validated by the introduction of a Nambu-Goldstone-like shift symmetry. Thus,
topological inflation inevitably takes place in our model.


  We estimate ages, metallicities, $\alpha$-element abundance ratios and
stellar initial mass functions of elliptical (E) and S0 galaxies from the
MaNGA-DR15 survey. We stack spectra and use a variety of single stellar
population synthesis models to interpret the absorption line strengths in these
spectra. We quantify how these properties vary across the population, as well
as with galactocentric distance. This paper is the first of a series and is
based on a sample of pure elliptical galaxies at z $\le$ 0.08. We show that the
properties of the inner regions of Es with the largest luminosity (L$_r$) and
central velocity dispersion ($\sigma_0$) are consistent with those associated
with the commonly used Salpeter IMF, whereas a Kroupa-like IMF is a better
description at $\sim$ 0.8R/Re (assuming [Ti/Fe] variations are limited). For
these galaxies the stellar mass-to-light ratio decreases at most by a factor of
2 from the central regions to Re. In contrast, for lower L$_r$ and $\sigma_0$
galaxies, the IMF is shallower and M$_{*}$/L$_r$ in the central regions is
similar to the outskirts. Although a factor of 2 is smaller than previous
reports based on a handful of galaxies, it is still large enough to matter for
dynamical mass estimates. Accounting self-consistently for these gradients when
estimating both M$_{*}$ and M$_{dyn}$ brings the two into good agreement:
gradients reduce M$_{dyn}$ by $\sim$ 0.2 dex while only slightly increasing the
M$_{*}$ inferred using a Kroupa IMF. This is a different resolution of the
M$_{*}$-M$_{dyn}$ discrepancy than has been followed in the recent literature
where M$_{*}$ of massive galaxies is increased by adopting a Salpeter IMF while
leaving Mdyn unchanged. A companion paper discusses how stellar population
differences are even more pronounced if one separates slow from fast rotators.


  The coldness of the universe is a thermodynamic resource that has largely
remained untapped for renewable energy generation. Recently, a growing interest
in this area has led to a number of studies with the aim to realize the
potential of tapping this vast resource for energy generation. While the
theoretical calculation based on thermodynamic principles places an upper limit
in the power density at the level of 6000 mW/m$^2$, most experimental
demonstrations so far result in much lower power density at the level of tens
of mW/m$^2$. Here we demonstrate, through design optimization involving the
tailoring of the thermal radiation spectrum, the minimization of parasitic heat
leakage, and the maximum conversion of heat to electricity, an energy
generation system harvesting electricity from the thermal radiation of the
ambient heat to the cold universe that achieves a sustained power density of
350 mW/m$^2$. We further demonstrate a power density at the 1000 mW/m$^2$ level
using an additional heat source or heat storage that provides access to heat at
a temperature above ambient. Our work here shows that the coldness of the
universe can be harvested to generate renewable energy at the power density
level that approaches the established bound.


  In recent years, statistical physics' methodologies have proven extremely
successful in offering insights into the mechanisms that govern social
interactions. However, the question of whether these models are able to capture
trends observed in real-world datasets is hardly addressed in the current
literature. With this work we aim at bridging the gap between theoretical
modeling and validation with data. In particular, we propose a model for
opinion dynamics on a social network in the presence of external triggers,
framing the interpretation of the model in the context of misbehavior
spreading. We divide our population in aware, unaware and zealot/educated
agents. Individuals change their status according to two competing dynamics,
referred to as behavioral dynamics and broadcasting. The former accounts for
information spreading through contact among individuals whereas broadcasting
plays the role of an external agent, modeling the effect of mainstream media
outlets. Through both simulations and analytical computations we find that the
stationary distribution of the fraction of unaware agents in the system
undergoes a phase transition when an all-to-all approximation is considered.
Surprisingly, such a phase transition disappears in the presence of a minimum
fraction of educated agents. Finally, we validate our model using data
collected from the public discussion on Twitter, including millions of posts,
about the potential adverse effects of the AstraZeneca vaccine against
COVID-19. We show that the intervention of external agents, as accounted for in
our model, is able to reproduce some key features that are found in this
real-world dataset.


  As a contribution requested by the editors of a Memorial Volume for Peter
G.O. Freund (1936-2018), we recall the lively particle theory group at the
Enrico Fermi Institute of the University of Chicago in the late sixties, of
which Peter was a memorable member. We also discuss a period some twenty years
later when our and Peter's research overlapped on the topic of p-adic strings.


  Neural audio coding has shown very promising results recently in the
literature to largely outperform traditional codecs but limited attention has
been paid on its error resilience. Neural codecs trained considering only
source coding tend to be extremely sensitive to channel noises, especially in
wireless channels with high error rate. In this paper, we investigate how to
elevate the error resilience of neural audio codecs for packet losses that
often occur during real-time communications. We propose a feature-domain packet
loss concealment algorithm (FD-PLC) for real-time neural speech coding.
Specifically, we introduce a self-attention-based module on the received latent
features to recover lost frames in the feature domain before the decoder. A
hybrid segment-level and frame-level frequency-domain discriminator is employed
to guide the network to focus on both the generative quality of lost frames and
the continuity with neighbouring frames. Experimental results on several error
patterns show that the proposed scheme can achieve better robustness compared
with the corresponding error-free and error-resilient baselines. We also show
that feature-domain concealment is superior to waveform-domain counterpart as
post-processing.


  Supersymmetry (SUSY) is a symmetry transforming bosons to fermions and vice
versa. Indications of its existence have been extensively sought after in
high-energy experiments. However, signatures of SUSY have yet to be detected.
In this manuscript we propose a condensed matter realization of SUSY on the
edge of a Read-Rezayi quantum Hall state, given by filling factors of the form
$\nu =\frac{k}{k+2}$, where $k$ is an integer. As we show, this strongly
interacting state exhibits an $\mathcal{N}=2$ SUSY. This allows us to use a
topological invariant - the Witten index - defined specifically for
supersymmetric theories, to count the difference between the number of bosonic
and fermionic zero-modes in a circular edge. In our system, we argue that the
edge hosts $k+1$ protected zero-modes. We further discuss the stability of SUSY
with respect to generic perturbations, and find that much of the above results
remain unchanged. In particular, these results directly apply to the
well-established $\nu=1/3$ Laughlin state, in which case SUSY is a highly
robust property of the edge theory. These results unveil a hidden topological
structure on the long-studied Read-Rezayi states.


  Given a single copy of a mixed state of the form
\rho=\lambda\rho_1+(1-\lambda)\rho_2, what is the optimal measurement to
estimate the parameter \lambda, if \rho_1 and \rho_2 are known? We present a
general strategy to obtain the optimal measurements employing a Bayesian
estimator. The measurements are chosen to minimize the deviation between the
estimated- and the true value of \lambda. We explicitly determine the optimal
measurements for a general two-dimensional system and for important higher
dimensional cases.


  We study quadratically divergent radiative corrections to the oblique
parameters at LEP1 induced by non-standard vector boson self-couplings. We work
in the Stueckelberg formalism and regulate the divergences through a
gauge-invariant higher derivative scheme. Using consistency arguments together
with the data we find a limit on the anomalous magnetic moment Delta kappa of
the W-boson, |Delta kappa| <= 0.26.


  We present a detailed powder and single crystal neutron diffraction study of
the spin chain compound Ca3Co2O6. Below 25 K, the system orders magnetically
with a modulated partially disordered antiferromagnetic structure. We give a
description of the magnetic interactions in the system which is consistent with
this magnetic structure. Our study also reveals that the long-range magnetic
order co-exists with a shorter range order with a correlation length scale of
180 A in the ab plane. Remarkably, on cooling, the volume of material
exhibiting short range order increases at the expense of the long-range order.


  Many Natural Language Generation (NLG) tasks aim to generate a single output
text given an input prompt. Other settings require the generation of multiple
texts, e.g., for Synthetic Traffic Generation (STG). This generation task is
crucial for training and evaluating QA systems as well as conversational
agents, where the goal is to generate multiple questions or utterances
resembling the linguistic variability of real users. In this paper, we show
that common NLG metrics, like BLEU, are not suitable for evaluating STG. We
propose and evaluate several metrics designed to compare the generated traffic
to the distribution of real user texts. We validate our metrics with an
automatic procedure to verify whether they capture different types of quality
issues of generated data; we also run human annotations to verify the
correlation with human judgements. Experiments on three tasks, i.e., Shopping
Utterance Generation, Product Question Generation and Query Auto Completion,
demonstrate that our metrics are effective for evaluating STG tasks, and
improve the agreement with human judgement up to 20% with respect to common NLG
metrics. We believe these findings can pave the way towards better solutions
for estimating the representativeness of synthetic text data.


  We provide a straightforward and efficient procedure to combine LDA+U total
energy functional with the full potential linearized augmented plane wave
method. A detailed derivation of the LDA+U Kohn-Sham type equations is
presented for the augmented plane wave basis set, and a simple
``second-variation'' based procedure for self-consistent LDA+U calculations is
given. The method is applied to calculate electronic structure and magnetic
properties of NiO and Gd. The magnetic moments and band eigenvalues obtained
are in very good quantitative agreement with previous full potential LMTO
calculations. We point out that LDA+U reduces the total d charge on Ni by 0.1
in NiO.


  We study uniform interpolation and forgetting in the description logic ALC.
Our main results are model-theoretic characterizations of uniform inter-
polants and their existence in terms of bisimula- tions, tight complexity
bounds for deciding the existence of uniform interpolants, an approach to
computing interpolants when they exist, and tight bounds on their size. We use
a mix of model- theoretic and automata-theoretic methods that, as a by-product,
also provides characterizations of and decision procedures for conservative
extensions.


  There is a widespread perception that pharmaceutical R&D is facing a
productivity crisis characterised by stagnation in the numbers of new drug
approvals in the face of increasing R&D costs. This study explores
pharmaceutical R&D dynamics by examining the publication activities of all R&D
laboratories of the major European and US pharmaceutical firms during the
period 1995-2009. The empirical findings present an industry in
transformation.In the first place, we observe a decline of the total number of
publications by large firms. Second, we show a relative increase of their
external collaborations suggesting a tendency to outsource, and a
diversification of the disciplinary base, in particular towards computation,
health services and more clinical approaches. Also evident is a more pronounced
decline in publications by both R&D laboratories located in Europe and by firms
with European headquarters. Finally, while publications by Big Pharma in
emerging economies sharply increase, they remain extremely low compared with
those in developed countries. In summary, the trend in this transformation is
one of a gradual decrease in internal research efforts and increasing reliance
on external research. These empirical insights support the view that large
pharmaceutical firms are increasingly becoming networks integrators rather than
the prime locus of drug discovery.


  I discuss the basic elements of the process that will lead to the discovery
of possible new phenomena at the LHC. We review the status of the tools
available to model the Standard Model backgrounds, and the role that such tools
can play in the discovery phase, and in the exploration of the features and
parameters of such new phenomena.


  Generalized differential cohomology theories, in particular differential
K-theory (often called "smooth K-theory"), are becoming an important tool in
differential geometry and in mathematical physics. In this survey, we describe
the developments of the recent decades in this area. In particular, we discuss
axiomatic characterizations of differential K-theory (and that these uniquely
characterize differential K-theory). We describe several explicit
constructions, based on vector bundles, on families of differential operators,
or using homotopy theory and classifying spaces. We explain the most important
properties, in particular about the multiplicative structure and push-forward
maps and will state versions of the Riemann-Roch theorem and of Atiyah-Singer
family index theorem for differential K-theory.


  The dynamical response of the solar corona to surface and sub-surface
perturbations depends on the chromospheric stratification, and specifically on
how efficiently these layers reflect or transmit incoming Alfv\'en waves. While
it would be desirable to include the chromospheric layers in the numerical
simulations used to study such phenomena, that is most often not feasible. We
defined and tested a simple approximation allowing the study of coronal
phenomena while taking into account a parametrised chromospheric reflectivity.
We addressed the problems of the transmission of the surface rotation to the
corona and that of the generation of polar plumes by Alfv\'en waves (Pinto et
al., 2010, 2011). We found that a high (yet partial) effective chromospheric
reflectivity is required to properly describe the angular momentum balance in
the corona and the way the surface differential rotation is transmitted
upwards. Alfv\'en wave-driven polar plumes maintain their properties for a wide
range of values for the reflectivity, but they become bursty (and eventually
disrupt) when the limit of total reflection is attained.


  In a classical conformal invariant supersymmetric gauge theory, the chiral
R-symmetry current, the supersymmetry current and the energy-momentum tensor
constitute a supercurrent multiplet. There are two different superconformal
anoamly multiplets in four-dimensional supersymmetric gauge theories, one
originating from the supersymmetric gauge dynamics and the consequent
nonvanishing \beta-function, and the other one coming from the coupling of the
supercurrent multiplet to the external supergravity multiplet with non-trivial
topology. We emphasize that in the gauge/gravity dual correspondence these two
types of superconformal anomaly multiplets have distinct reflections in the
classical supergravity: the anomaly multiplet due to the supersymmetry gauge
dynamics is dual to the spontaneous symmetry breaking and the consequent
super-Higgs effect in AdS_5 bulk supergravity, while the anomaly multiplet
originating from the non-trivial topology of external conformal supergravity
mutiplet is a boundary effects of the AdS_5 space.


  Despite many important applications of a-Fe2O3 and Fe doped SnO2 in
semiconductors, catalysis, sensors, clinical diagnosis and treatments, one
fundamental issue that is crucial to these applications remains theoretically
equivocal- the reversible carrier-type transition between n- and p-type
conductivities during gas-sensing operations. Here, we give unambiguous and
rigorous theoretical analysis in order to explain why and how the oxygen
vacancies affect the n-type semiconductors, a-Fe2O3 and Fe doped SnO2 in which
they are both electronically and chemically transformed into a p-type
semiconductor. Furthermore, this reversible transition also occurs on the oxide
surfaces during gas-sensing operation due to physisorbed gas molecules (without
any chemical reaction). We make use of the ionization energy theory and its
renormalized ionic displacement polarizability functional to reclassify,
generalize and to explain the concept of carrier-type transition in solids, and
during gas-sensing operation. The origin of such a transition is associated to
the change in ionic polarizability and the valence states of cations in the
presence of (a) oxygen vacancies and (b) physisorped gas molecules.


  Massive spin-1/2 fields are studied in the framework of loop quantum gravity
by considering a state approximating, at a length scale $\cal L$ much greater
than Planck length $\ell_P=1.2\times 10^{-33}$cm, a spin-1/2 field in flat
spacetime. The discrete structure of spacetime at $\ell_P$ yields corrections
to the field propagation at scale $\cal L$. Next, Neutrino Bursts (${\bar
p}\approx 10^5$GeV) accompaning Gamma Ray Bursts that have travelled
cosmological distances, $L\approx 10^{10}$l.y., are considered. The dominant
correction is helicity independent and leads to a time delay w.r.t. the speed
of light, $c$, of order $({\bar p} \ell_P) L/c\approx 10^4$s. To next order in
${\bar p} \ell_P$ the correction has the form of the Gambini and Pullin effect
for photons. Its contribution to time delay is comparable to that caused by the
mass term. Finally, a dependence $L_{\rm os}^{-1} \propto {\bar p}^2 \ell_P$ is
found for a two-flavour neutrino oscillation length.


  High energy astrophysics has made good use of combined high energy (X-ray,
gamma-ray) and radio observations to uncover connections between outbursts,
accretion, particle acceleration and kinetic feedback to the local ambient
medium. In the field of microquasars the connections have been particularly
important. However, radio astronomy has been relying on essentially the same
facilities for the past ~25 years, whereas high-energy astrophysics, in
particular space-based research, has had a series of newer and more powerful
missions. In the next fifteen years this imbalance is set to be redressed, with
a whole familiy of new radio facilities under development en route to the
Square Kilometre Array (SKA) in the 2020s. In this brief review I will
summarize these future prospects for radio astronomy, and focus on possibly the
most exciting of the new facilities to be built in the next decade, the Low
Frequency Array LOFAR, and its uses in high energy astrophysics.


  We have developed a general method for constructing a set of non-orthogonal
bases with equal separations between all different basis' states in prime
dimensions.It results that the corresponding bi-orthogonal counterparts are
pairwise unbiased with the components of the original bases. Using these bases
we derive an explicit expression for the optimal tomography in non-orthogonal
bases. Special two dimensional case is analyzed separately.


  We study the scattering problem for the nonlinear wave equation with
potential. In the absence of the potential, one has sharp existence results for
the Cauchy problem with small initial data; those require the data to decay at
a rate greater than or equal to a critical decay rate which depends on the
order of the nonlinearity. However, scattering results have appeared only for
the supercritical case. In this paper, we extend the scattering results to the
critical case and we also allow the presence of a short-range potential.


  Advances in the field of vision-language contrastive learning have made it
possible for many downstream applications to be carried out efficiently and
accurately by simply taking the dot product between image and text
representations. One of the most representative approaches proposed recently
known as CLIP has garnered widespread adoption due to its effectiveness. CLIP
is trained with an InfoNCE loss that takes into account both positive and
negative samples to help learn a much more robust representation space. This
paper reveals that the common downstream practice of taking a dot product is
only a zeroth-order approximation of the optimization goal, resulting in a loss
of information during test-time. Intuitively, since the model has been
optimized based on the InfoNCE loss, test-time procedures should also be in
alignment. The question lies in how one can retrieve any semblance of negative
samples information during inference in a computationally efficient way. To
this end, we propose Distribution Normalization (DN), where we approximate the
mean representation of a batch of test samples and use such a mean to represent
what would be analogous to negative samples in the InfoNCE loss. DN requires no
retraining or fine-tuning and can be effortlessly applied during inference.
Extensive experiments on a wide variety of downstream tasks exhibit a clear
advantage of DN over the dot product on top of other existing test-time
augmentation methods.


  The coupling between Angstrom-sized electron probes and spin polarised
electronic transitions shows that the inelastically scattered probe is in a
mixed state containing electron vortices with non-zero orbital angular
momentum. These electrons create an asymmetric intensity distribution in energy
filtered diffraction patterns, giving access to maps of the magnetic moments
with atomic resolution. A feasibility experiment shows evidence of the
predicted effect. Potential applications are column-by-column maps of magnetic
ordering, and the creation of Angstrom-sized free electrons with orbital
angular momentum by inelastic scattering in a thin ferromagnetic foil.


  Metal artifacts present a frequent challenge to cone-beam CT (CBCT) in
image-guided surgery, obscuring visualization of metal instruments and adjacent
anatomy. Recent advances in mobile C-arm systems have enabled 3D imaging
capacity with non-circular orbits. We extend a previously proposed metal
artifacts avoidance (MAA) method to reduce the influence of metal artifacts by
prospectively defining a non-circular orbit that avoids metal-induced biases in
projection domain. Accurate geometric calibration is an important challenge to
accurate 3D image reconstruction for such orbits. We investigate the
performance of interpolation-based calibration from a library of circular
orbits for any non-circular orbit. We apply the method to non-circular scans
acquired for MAA, which involves: (i) coarse 3D localization of metal objects
via only two scout views using an end-to-end trained neural network; (ii)
calculation of the metal-induced x-ray spectral shift for all possible views;
and (iii) identification of the non-circular orbit that minimizes the
variations in spectral shift. Non-circular orbits with interpolation-based
geometric calibration yielded reasonably accurate 3D image reconstruction. The
end-to-end neural network accurately localized metal implants with just two
scout views even in complex anatomical scenes, improving Dice coefficient by
~42% compared to a more conventional cascade of separately trained U-nets. In a
spine phantom with pedicle screw instrumentation, non-circular orbits
identified by the MAA method reduced the magnitude of metal "blomming"
artifacts (apparent width of the screw shaft) in CBCT reconstructions by ~70%.
The proposed imaging and calibration methods present a practical means to
improve image quality in mobile C-arm CBCT by identifying non-circular scan
protocols that improve sampling and reduce metal-induced biases in the
projection data.


  We provide a proof of the first correction to the leading asymptotics of the
minimal energy of pseudo-relativistic molecules in the presence of magnetic
fields, the so-called "relativistic Scott correction", when $\max{Z_k\alpha}
\leq 2/\pi$, where $Z_k$ is the charge of the $k$-th nucleus and $\alpha$ is
the fine structure constant. Our theorem extends a previous result by
Erd\H{o}s, Fournais, and Solovej to the critical constant $2/\pi$ in the
relativistic Hardy inequality $|p| - \frac{2}{\pi |x|} \geq 0$.


  Handover (HO) management has attracted attention of research in the context
of wireless cellular communication networks. One crucial problem of HO
management is to deal with increasing HOs experienced by a mobile user. To
address this problem, HO skipping techniques have been studied in recent years.
In this paper, we propose a novel HO skipping scheme, namely, time-based HO
skipping. In the proposed scheme, HOs of a user are controlled by a certain
fixed period of time, which we call skipping time. The skipping time can be
managed as a system parameter, thereby enabling flexible operation of HO
skipping. We analyze the transmission performance of the proposed scheme on the
basis of a stochastic geometry approach. In the scenario where a user performs
the time-based HO skipping, we derive the analytical expressions for two
performance metrics: the HO rate and the expected data rate. The analysis
results demonstrate that the scenario with the time-based HO skipping
outperforms the scenario without HO skipping particularly when the user moves
fast. Furthermore, we reveal that there is a unique optimal skipping time
maximizing the transmission performance, which we obtain approximately.


  Ruthenium trichloride is the subject of many recent experimental and
theoretical studies. Johnson et al. infer a candidate for the magnetic
structure (Cc2/m) from results gathered in an extensive set of experiments on
an untwined sample of alpha-RuCl3 [R. D. Johnson et al., Phys. Rev. B 92,
235119 (2015)]. The proposed zigzag antiferromagnetic ground state of Ru ions
does not respond to bulk magnetic probes. Properties of the candidate magnetic
structure not previously explored include polar magnetism that supports Ru
Dirac multipoles, e.g., a ruthenium anapole. In a general case, Dirac dipoles
are capable of generating interactions between magnetic ions, as in an
electrical Dzyaloshinskii-Moryia interaction [T. A. Kaplan and S. D. Mahanti,
Phys. Rev. B 83, 174432 (2011) and H. J. Zhao et al., Nat. Mat. 20, 341
(2021)]. Dirac multipoles contribute to the diffraction of both x-rays and
neutrons, and a stringent test of the magnetic structure Cc2/m awaits future
experiments. From symmetry-informed calculations we show that, the magnetic
candidate permits Bragg spots that arise solely from Dirac multipoles.
Stringent tests of Cc2/m can also be accomplished by performing resonant x-ray
diffraction with signal enhancement from the chlorine K-edge. X-ray absorption
spectra published for alpha-RuCl3 possess a significant low-energy feature [K.
W. Plumb et al., Phys. Rev. B 90, 041112(R) (2014)]. Many experimental studies
of other Cl-metal compounds concluded that identical features hallmark the
chemical bond. Using a monoclinic Cc2/m structure, we predict the contribution
to Bragg diffraction at the Cl K-edge absorption. Specifically, the variation
of intensity of Bragg spots with rotation of the sample about the reflection
vector. The two principal topics of our studies, polar magnetism and the
chemical bond in alpha-RuCl3, are brought together in a minimal model of
magnetic Ru ions in Cc2/m.


  We consider a phase-field model of prostate cancer growth with chemotherapy
and antiangiogenic therapy effects which is introduced in [2]. It is comprised
of phase-field equation to describe tumor growth, which is coupled to a
reaction-diffusion type equation for generic nutrient for the tumor. An
additional equation couples the concentration of prostate-specific antigen
(PSA) in the prostatic tissue and it obeys a linear reaction-diffusion
equation. The system completes with homogeneous Dirichlet boundary conditions
for the tumor variable and Neuman boundary condition for the nutrient and the
concentration of PSA. Here we investigate the long time dynamics of the model.
We first prove that the initial-boundary value problem generates a strongly
continuous semigroup on a suitable phase space that admits the global attractor
in a proper phase space. Moreover, we also discuss the convergence of a
solution to a single stationary state and obtain a convergence rate estimate
under some conditions on the coefficients.


  KASCADE-Grande is the extension of the multi-detector setup KASCADE to cover
a primary cosmic ray energy range from 100 TeV to 1 EeV. The enlarged EAS
experiment provides comprehensive observations of cosmic rays in the energy
region around the knee. Grande is an array of 700 x 700 sqm equipped with 37
plastic scintillator stations sensitive to measure energy deposits and arrival
times of air shower particles. LOPES is a small radio antenna array to operate
in conjunction with KASCADE-Grande in order to calibrate the radio emission
from cosmic ray air showers. Status and capabilities of the KASCADE-Grande
experiment and the LOPES project are presented.


  Let m,n be positive integers. Define T(m,n) to be the transportation polytope
consisting of the m x n non-negative real matrices whose rows each sum to 1 and
whose columns each sum to m/n. The special case B(n)=T(n,n) is the much-studied
Birkhoff-von Neumann polytope of doubly-stochastic matrices. Using a recent
asymptotic enumeration of non-negative integer matrices (Canfield and McKay,
2007), we determine the asymptotic volume of T(m,n) as n goes to infinity, with
m=m(n) such that m/n neither decreases nor increases too quickly. In
particular, we give an asymptotic formula for the volume of B(n).


  We propose a model for the simulation of the blowdown of vessels containing
two-phase (gas-liquid) hydrocarbon fluids, considering non equilibrium between
phases. Two phases may be present either already at the beginning of the
blowdown process (for instance in gas-liquid separators) or as the liquid is
formed from flashing of the vapor due to the cooling induced by pressure
decrease. There is experimental evidence that the assumption of thermodynamic
equilibrium is not appropriate, since the two phases show an independent
temperature evolution. Thus, due to the greater heat transfer between the
liquid phase with the wall, the wall in contact with the liquid experiences a
stronger cooling than the wall in contact with the gas, during the blowdown. As
a consequence, the vessel should be designed for a lower temperature than if it
was supposed to contain vapor only. Our model is based on a compositional
approach, and it takes into account internal heat and mass transfer processes,
as well as heat transfer with the vessel wall and the external environment.
Numerical simulations show a generally good agreement with experimental
measurements.


  The classical moduli space M of a supersymmetric gauge theory with trivial
superpotential can be stratified according to the unbroken gauge subgroup at
different vacua. We apply known results about this stratification to obtain the
W \neq 0 theory classical moduli space M^W \subset M, working entirely with the
composite gauge invariant operators X that span M, assuming we do not known
their elementary matter chiral field content. In this construction, the
patterns of gauge symmetry breaking of the W \neq 0 theory are determined,
Higgs flows in these theories show important differences from the W=0 case. The
methods here introduced provide an alternative way to construct tree level
superpotentials that lift all classical flat directions leaving a candidate
theory for dynamical supersymmetry breaking, and are also useful to identify
heavy composite fields to integrate out from effective superpotentials when the
elementary field content of the composites is unknown. We also show how to
recognize the massless singlets after Higgs mechanism at a vacuum X \in M^W
among the moduli \delta X using the stratification of M, and establish
conditions under which the space of non singlet massless fields after Higgs
mechanism (unseen as moduli \delta X) is null. A small set of theories with so
called "unstable" representations of the complexified gauge group is shown to
exhibit unexpected properties regarding the dimension of their moduli space,
and the presence of non singlet massless fields after Higgs mechanism at all of
their vacua.


  Mesh adaptivity is a technique to provide detail in numerical solutions
without the need to refine the mesh over the whole domain. Mesh adaptivity in
isogeometric analysis can be driven by Truncated Hierarchical B-splines
(THB-splines) which add degrees of freedom locally based on finer B-spline
bases. Labeling of elements for refinement is typically done using
residual-based error estimators. In this paper, an adaptive meshing workflow
for isogeometric Kirchhoff-Love shell analysis is developed. This framework
includes THB-splines, mesh admissibility for combined refinement and coarsening
and the Dual-Weighted Residual (DWR) method for computing element-wise error
contributions. The DWR can be used in several structural analysis problems,
allowing the user to specify a goal quantity of interest which is used to mark
elements and refine the mesh. This goal functional can involve, for example,
displacements, stresses, eigenfrequencies etc. The proposed framework is
evaluated through a set of different benchmark problems, including modal
analysis, buckling analysis and non-linear snap-through and bifurcation
problems, showing high accuracy of the DWR estimator and efficient allocation
of degrees of freedom for advanced shell computations.


  This work extends the results of the recently developed theory of a rather
complete thermodynamic formalism for discrete-state, continuous-time Markov
processes with and without detailed balance. We aim at investigating the
question that whether and how the thermodynamic structure is invariant in a
multiscale stochastic system. That is, whether the relations between
thermodynamic functions of state and process variables remain unchanged when
the system is viewed at different time scales and resolutions. Our results show
that the dynamics on a fast time scale contribute an entropic term to the
"internal energy function", $u_S(x)$, for the slow dynamics. Based on the
conditional free energy $u_S(x)$, one can then treat the slow dynamics as if
the fast dynamics is nonexistent. Furthermore, we show that the free energy,
which characterizes the spontaneous organization in a system without detailed
balance, is invariant with or without the fast dynamics: The fast dynamics is
assumed to reach stationarity instantaneously on the slow time scale; they have
no effect on the system's free energy. The same can not be said for the entropy
and the internal energy, both of which contain the same contribution from the
fast dynamics. We also investigate the consequences of time-scale separation in
connection to the concepts of quasi-stationaryty and steady-adiabaticity
introduced in the phenomenological steady-state thermodynamics.


  For high precision in source reconstruction of magnetoencephalography (MEG)
or electroencephalography data, high accuracy of the coregistration of sources
and sensors is mandatory. Usually, the source space is derived from magnetic
resonance imaging (MRI). In most cases, however, no quality assessment is
reported for sensor-to-MRI coregistrations. If any, typically root mean squares
(RMS) of point residuals are provided. It has been shown, however, that RMS of
residuals do not correlate with coregistration errors. We suggest using target
registration error (TRE) as criterion for the quality of sensor-to-MRI
coregistrations. TRE measures the effect of uncertainty in coregistrations at
all points of interest. In total, 5544 data sets with sensor-to-head and 128
head-to-MRI coregistrations, from a single MEG laboratory, were analyzed. An
adaptive Metropolis algorithm was used to estimate the optimal coregistration
and to sample the coregistration parameters (rotation and translation). We
found an average TRE between 1.3 and 2.3mm at the head surface. Further, we
observed a mean absolute difference in coregistration parameters between the
Metropolis and iterative closest point algorithm of (1.9 $\pm$ 1.5){\deg} and
(1.1 $\pm$ 0.9)mm. A paired sample t-test indicated a significant improvement
in goal function minimization by using the Metropolis algorithm. The sampled
parameters allowed computation of TRE on the entire grid of the MRI volume.
Hence, we recommend the Metropolis algorithm for head-to-MRI coregistrations.


  We consider the problem of Open-world Information Extraction (Open-world IE),
which extracts comprehensive entity profiles from unstructured texts. Different
from the conventional closed-world setting of Information Extraction (IE),
Open-world IE considers a more general situation where entities and relations
could be beyond a predefined ontology. More importantly, we seek to develop a
large language model (LLM) that is able to perform Open-world IE to extract
desirable entity profiles characterized by (possibly fine-grained) natural
language instructions. We achieve this by finetuning LLMs using instruction
tuning. In particular, we construct INSTRUCTOPENWIKI, a substantial instruction
tuning dataset for Open-world IE enriched with a comprehensive corpus,
extensive annotations, and diverse instructions. We finetune the pretrained
BLOOM models on INSTRUCTOPENWIKI and obtain PIVOINE, an LLM for Open-world IE
with strong instruction-following capabilities. Our experiments demonstrate
that PIVOINE significantly outperforms traditional closed-world methods and
other LLM baselines, displaying impressive generalization capabilities on both
unseen instructions and out-of-ontology cases. Consequently, PIVOINE emerges as
a promising solution to tackle the open-world challenge in IE effectively.


  Metaverse as-a-Service (MaaS) enables Metaverse tenants to execute their
APPlications (MetaAPP) by allocating Metaverse resources in the form of
Metaverse service functions (MSF). Usually, each MSF is deployed in a virtual
machine (VM) for better resiliency and security. However, these MSFs along with
VMs and virtual machine monitors (VMM) running them may encounter software
aging after prolonged continuous operation. Then, there is a decrease in
MetaAPP dependability, namely, the dependability of the MSF chain (MSFC),
consisting of MSFs allocated to MetaAPP. This paper aims to investigate the
impact of both software aging and rejuvenation techniques on MetaAPP
dependability in the scenarios, where both active components (MSF, VM and VMM)
and their backup components are subject to software aging. We develop a
hierarchical model to capture behaviors of aging, failure, and recovery by
applying Semi-Markov process and reliability block diagram. Numerical analysis
and simulation experiments are conducted to evaluate the approximation accuracy
of the proposed model and dependability metrics. We then identify the key
parameters for improving the MetaAPP/MSFC dependability through sensitivity
analysis. The investigation is also made about the influence of various
parameters on MetaAPP/MSFC dependability.


  In this work we prove the existence and uniqueness of the strong solution to
the two-dimensional stochastic magneto-hydrodynamic system perturbed by Levy
noise. The local monotonicity arguments have been ex- ploited in the proofs.
The existence of a unique invariant measures has been proved using the
exponential stability of solutions.


  In October 2000, the third PCaPAC (PCs and Particle Accelerator Controls)
workshop took place at DESY. This paper presents a summary of the workshop. The
workshop reviewed existing and new PC-based accelerator control systems, from
small-scale to large-scale installations. It demonstrated convincingly the
advantage of modern, commercial mass-market products used for accelerator
controls. Disadvantages of these technologies were reported as well.
Large-scale PC systems inherently bring administrative concerns into the
picture. In this vein, special emphasis was given to system administration for
distributed systems. A major topic of the workshop was the integration of
different control system approaches as well as the integration of different
platforms within the same control system. In particular, PC-based concepts
offer the simple opportunity to interface to commercial SCADA systems. In
addition, large emphasis was given to the presentation of future developments
including the next network trends to data exchange via SOAP and XML.


  We consider a one-parameter family of non-evolutionary partial differential
equations which includes the integrable Camassa-Holm equation and a new
equation first isolated by Degasperis and Procesi. A Lagrangian and Hamiltonian
formulation is presented for the whole family of equations, and we discuss how
this fits into a bi-Hamiltonian framework in the integrable cases. The
Hamiltonian dynamics of peakons and some other special finite-dimensional
reductions are also described.


  A $k$-plex in a latin square of order $n$ is a selection of $kn$ entries that
includes $k$ representatives from each row and column and $k$ occurrences of
each symbol. A $1$-plex is also known as a transversal.
  It is well known that if $n$ is even then $B_n$, the addition table for the
integers modulo $n$, possesses no transversals. We show that there are a great
many latin squares that are similar to $B_n$ and have no transversal. As a
consequence, the number of species of transversal-free latin squares is shown
to be at least $n^{n^{3/2}(1/2-o(1))}$ for even $n\rightarrow\infty$.
  We also produce various constructions for latin squares that have no
transversal but do have a $k$-plex for some odd $k>1$. We prove a 2002
conjecture of the second author that for all even orders $n>4$ there is a latin
square of order $n$ that contains a $3$-plex but no transversal. We also show
that for odd $k$ and $m\geq 2$, there exists a latin square of order $2km$ with
a $k$-plex but no $k'$-plex for odd $k'<k$.


  The surprise discovery of superconductivity below 5K in sodium cobalt oxides
when hydrated with water has caught the attention of experimentalists and
theorists alike. Most explanations for its occurence have focused heavily on
the properties of some small elliptically shaped pockets predicted to be the
electronically dominant Fermi surface sheet, but direct attempts to look for
them have instead cast serious doubts over their existence. Here we present
evidence that these pockets do indeed exist, based on bulk measurements of the
electron momentum distribution in unhydrated and hydrated sodium cobalt oxides
using the technique of x-ray Compton scattering.


  The binary heap of Williams (1964) is a simple priority queue characterized
by only storing an array containing the elements and the number of elements $n$
- here denoted a strictly implicit priority queue. We introduce two new
strictly implicit priority queues. The first structure supports amortized
$O(1)$ time Insert and $O(\log n)$ time ExtractMin operations, where both
operations require amortized $O(1)$ element moves. No previous implicit heap
with $O(1)$ time Insert supports both operations with $O(1)$ moves. The second
structure supports worst-case $O(1)$ time Insert and $O(\log n)$ time (and
moves) ExtractMin operations. Previous results were either amortized or needed
$O(\log n)$ bits of additional state information between operations.


  Superintegrable systems are a class of physical systems which possess more
conserved quantities than their degrees of freedom. The study of these systems
has a long history and continues to attract significant international
attention. This thesis investigates finite dimensional quantum superintegrable
systems with scalar potentials as well as vector potentials with monopole type
interactions. We introduce new families of $N$-dimensional superintegrable
Kepler-Coulomb systems with non-central terms and double singular harmonic
oscillators in the Euclidean space, and new families of superintegrable Kepler,
MIC-harmonic oscillator and deformed Kepler systems interacting with
Yang-Coulomb monopoles in the flat and curved Taub-NUT spaces. We show their
multiseparability and obtain their Schr\"{o}dinger wave functions in different
coordinate systems. We show that the wave functions are given by (exceptional)
orthogonal polynomials and Painlev\'{e} transcendents (of hypergeometric type).
We construct higher-order algebraically independent integrals of motion of the
systems via the direct and constructive approaches. These integrals form
(higher-rank) polynomial algebras with structure constants involving Casimir
operators of certain Lie algebras. We obtain finite dimensional unitary
representations of the polynomial algebras and present the algebraic
derivations for degenerate energy spectra of these systems. Finally, we present
a generalized superintegrable Kepler-Coulomb model from exceptional orthogonal
polynomials and obtain its energy spectrum using both the separation of
variable and the algebraic methods.


  Within the framework proposed in this paper, we address the issue of
extending the certain networks to a fuzzy certain networks in order to cope
with a vagueness and limitations of existing models for decision under
imprecise and uncertain knowledge. This paper proposes a framework that
combines two disciplines to exploit their own advantages in uncertain and
imprecise knowledge representation problems. The framework proposed is a
possibilistic logic based one in which Bayesian nodes and their properties are
represented by local necessity-valued knowledge base. Data in properties are
interpreted as set of valuated formulas. In our contribution possibilistic
Bayesian networks have a qualitative part and a quantitative part, represented
by local knowledge bases. The general idea is to study how a fusion of these
two formalisms would permit representing compact way to solve efficiently
problems for knowledge representation. We show how to apply possibility and
necessity measures to the problem of knowledge representation with large scale
data. On the other hand fuzzification of crisp certainty degrees to fuzzy
variables improves the quality of the network and tends to bring smoothness and
robustness in the network performance. The general aim is to provide a new
approach for decision under uncertainty that combines three methodologies:
Bayesian networks certainty distribution and fuzzy logic.


  The Erd\H{o}s-Hajnal Conjecture states that for every $H$ there exists a
constant $\epsilon(H)>0$ such that every graph $G$ that does not contain $H$ as
an induced subgraph contains a clique or a stable set of size at least
$|V(G)|^{\epsilon(H)}$. The Conjecture is still open. Some time ago its
directed version was formulated (see:\cite{alon}). In the directed version
graphs are replaced by tournaments, and cliques and stable sets by transitive
subtournaments. If the Conjecture is not true then the smallest counterexample
is a prime tournament. For a long time the Conjecture was known only for
finitely many prime tournaments. Recently in \cite{bcc} and \cite{choromanski2}
the Conjecture was proven for the families of galaxies and constellations that
contain infinitely many prime tournaments. In \cite{bcc} the Conjecture was
also proven for all $5$-vertex tournaments. We say that a tournament $H$ has
the $EH$-property if it satisfies the Conjecture. In this paper we introduce
the so-called \textit{strong EH-property} which enables us to prove the
Conjecture for new prime tournaments, but what is even more interesting,
provides a mechanism to combine tournaments satisfying the Conjecture to get
bigger tournaments that do so and are not necessarily nonprime. We give several
examples of families of tournaments constructed according to this procedure.
The only procedure known before used to construct bigger tournaments satisfying
the Conjecture from smaller tournaments satisfying the Conjecture was the
so-called \textit{substitution procedure} (see: \cite{alon}). However an
outcome of this procedure is always a nonprime tournament and, from what we
have said before, prime tournaments are those that play crucial role in the
research on the Conjecture. Our method may be potentially used to prove the
Conjecture for several new classes of tournaments.


  Organizational, political, and configuration mistakes in the deployment of a
static source code analysis tool within a software development organization can
result in most of the value of the tool being lost, even while apparently
meeting management goals. A list of pitfalls encountered as a static analysis
consultant is presented, with discussion of techniques for avoiding or
mitigating them. This is part of a work in progress, tentatively entitled
"Handbook of Static Analysis Deployment."


  The topological edge states of two-dimensional topological insulators with
large energy gap furnish ideal conduction channels for dissipationless current
transport. Transition metal tellurides XTe5 (X=Zr, Hf) are theoretically
predicted to be large-gap two-dimensional topological insulators and the
experimental observations of their bulk insulating gap and in-gap edge states
have been reported, but the topological nature of these edge states still
remains to be further elucidated. Here, we report our low temperature scanning
tunneling microscopy/spectroscopy study on single crystals of HfTe5. We
demonstrate a full energy gap of ~80 meV near the Fermi level on the surface
monolayer of HfTe5 and that such insulating energy gap gets filled with finite
energy states when measured at the monolayer step edges. Remarkably, such
states are absent at the edges of a narrow monolayer strip of one-unit-cell in
width but persist at both step edges of a unit-cell wide monolayer groove.
These experimental observations strongly indicate that the edge states of HfTe5
monolayers are not trivially caused by translational symmetry breaking, instead
they are topological in nature protected by the 2D nontrivial bulk properties.


  This paper addresses the problem of cooperative manipulation of a single
object by N robotic agents under local goal specifications given as Metric
Interval Temporal Logic (MITL) formulas. In particular, we propose a
distributed model-free control protocol for the trajectory tracking of the
cooperatively manipulated object without necessitating feedback of the contact
forces/torques or inter-agent communication. This allows us to abstract the
motion of the coupled object-agents system as a finite transition system and,
by employing standard automata-based methodologies, we derive a hybrid control
algorithm for the satisfaction of a given MITL formula. In addition, we use
load sharing coefficients to represent potential differences in power
capabilities among the agents. Finally, simulation studies verify the validity
of the proposed scheme.


  We formulate a class of mean field games on a finite state space with
variational principles resembling those in continuous-state mean field games.
We construct a controlled continuity equation featuring a nonlinear activation
function on graphs induced by finite-state reversible continuous time Markov
chains. In these graphs, each edge is weighted by the transition probability
and invariant measure of the original process. Using these controlled dynamics
on the graph and the dynamic programming principle for the value function, we
derive several key components: the mean field game systems, the functional
Hamilton-Jacobi equations, and the master equations on a finite probability
space for potential mean field games. The existence and uniqueness of solutions
to the potential mean field game system are ensured through a convex
optimization reformulation in terms of the density-flux pair. We also derive
variational principles for the master equations of both non-potential games and
mixed games on a continuous state space. Finally, we offer several concrete
examples of discrete mean field game dynamics on a two-point space, complete
with closed-formula solutions. These examples include discrete Wasserstein
distances, mean field planning, and potential mean field games.


  Scalable kernel methods, including kernel ridge regression, often rely on
low-rank matrix approximations using the Nystrom method, which involves
selecting landmark points from large data sets. The existing approaches to
selecting landmarks are typically computationally demanding as they require
manipulating and performing computations with large matrices in the input or
feature space. In this paper, our contribution is twofold. The first
contribution is to propose a novel landmark selection method that promotes
diversity using an efficient two-step approach. Our landmark selection
technique follows a coarse to fine strategy, where the first step computes
importance scores with a single pass over the whole data. The second step
performs K-means clustering on the constructed coreset to use the obtained
centroids as landmarks. Hence, the introduced method provides tunable
trade-offs between accuracy and efficiency. Our second contribution is to
investigate the performance of several landmark selection techniques using a
novel application of kernel methods for predicting structural responses due to
earthquake load and material uncertainties. Our experiments exhibit the merits
of our proposed landmark selection scheme against baselines.


  The analysis results of the isotopic yields for products obtained in
reactions of protons at energies 0.66, 1, 8.1GeV with separated tin isotopes
are presented. The experimental data are compared in form of reactions of
element cross sections for two targets of different isotope compositions. The
scaling behaviour have been shown in the dependence of this ratios from neutron
and proton composition at the reaction products. The discussion of scaling
parameters allows to explain the mechanism of light and medium mass fragment
production.


  The most essential component of every Distributed Ledger Technology (DLT) is
the Consensus Algorithm (CA), which enables users to reach a consensus in a
decentralized and distributed manner. Numerous CA exist, but their viability
for particular applications varies, making their trade-offs a crucial factor to
consider when implementing DLT in a specific field. This article provided a
comprehensive analysis of the various consensus algorithms used in distributed
ledger technologies (DLT) and blockchain networks. We cover an extensive array
of thirty consensus algorithms. Eleven attributes including hardware
requirements, pre-trust level, tolerance level, and more, were used to generate
a series of comparison tables evaluating these consensus algorithms. In
addition, we discuss DLT classifications, the categories of certain consensus
algorithms, and provide examples of authentication-focused and
data-storage-focused DLTs. In addition, we analyze the pros and cons of
particular consensus algorithms, such as Nominated Proof of Stake (NPoS),
Bonded Proof of Stake (BPoS), and Avalanche. In conclusion, we discuss the
applicability of these consensus algorithms to various Cyber Physical System
(CPS) use cases, including supply chain management, intelligent transportation
systems, and smart healthcare.


  We construct pairs of algebras with mixed independence relations by using
truncations of reduced free products of algebras. For example, we construct
free-Boolean pairs of algebras and free-monotone pairs of algebras. We also
introduce free-Boolean cumulants and show that free-Boolean independence is
equivalent to the vanishing of mixed cumulants.


  Let $K$ be an algebraically closed field. Let $(Q,Sp,I)$ be a skewed-gentle
triple, $(Q^{sg},I^{sg})$ and $(Q^g,I^{g})$ be its corresponding skewed-gentle
pair and associated gentle pair respectively. It proves that the skewed-gentle
algebra $KQ^{sg}/< I^{sg}>$ is singularity equivalent to $KQ/< I>$. Moreover,
we use $(Q,Sp,I)$ to describe the singularity category of $KQ^g/< I^g>$. As a
corollary, we get that $\mathrm{gldim} KQ^{sg}/< I^{sg}><\infty$ if and only if
$\mathrm{gldim} KQ/< I><\infty$ if and only if $\mathrm{gldim} KQ^{g}/<
I^{g}><\infty$.


  The sum of the first $n \geq 1$ eigenvalues of the Laplacian is shown to be
maximal among simplexes for the regular simplex (the regular tetrahedron, in
three dimensions), maximal among parallelepipeds for the hypercube, and maximal
among ellipsoids for the ball, provided the volume and moment of inertia of an
"inverse" body are suitably normalized. This result holds for Dirichlet, Robin
and Neumann eigenvalues. Additionally, the cubical torus is shown to be maximal
among flat tori.
  The method of proof involves tight frames for euclidean space generated by
the orbits of the rotation group of the extremal domain.
  The ball is conjectured to maximize sums of Neumann eigenvalues among general
convex domains, provided the volume and moment of inertia of the polar dual of
the domain are suitably normalized.


  First-principles investigations on the edge energies and edge stresses of
single-layer hexagonal boron-nitride (BN) are presented. The armchair edges of
BN nanoribbons (BNNRs) are more stable in energy than zigzag ones. Armchair
BNNRs are under compressive edge stress while zigzag BNNRs are under tensile
edge stress. The intrinsic spin-polarization and edge saturation play important
roles in modulating the edge stability of BNNRs. The edge energy difference
between BN and graphene could be used to guide the design of the specific
hybrid BNC structures: in an armchair BNC nanoribbon (BNCNR), BN domains are
expected to grow outside of C domains, while the opposite occurs in a zigzag
BNCNR. More importantly, armchair BNCNRs can reproduce unique electronic
properties of armchair graphene nanoribbons (GNRs), which are expected to be
robust against edge functionalization or disorder. Within certain C/BN ratio,
zigzag BNCNRs may exhibit intrinsic half-metallicity without any external
constraints. These unexpected electronic properties of BNCNRs may offer unique
opportunities to develop nanoscale electronics and spintronics beyond
individual graphene and BN. Generally, these principles for designing BNC could
be extended to other hybrid nanostructures.


  In physics simulation chains, the PHOTOS Monte Carlo program is often used to
simulate QED effects in decays of intermediate particles and resonances. The
program is based on an exact multiphoton phase space. In general, the matrix
element is obtained from iterations of a universal kernel and approximations
are involved. To evaluate the program precision, it is necessary to formulate
and implement within the generator the exact matrix element, which depends on
the decay channel. Then, all terms necessary for non-leading logarithms are
taken into account.
  In the present letter we focus on the decay K to pi l^pm nu_l and tests of
the PHOTOS Monte Carlo program. We conclude a 0.2% relative precision in the
implementation of the hard photon matrix element into the emission kernel,
including the case where approximations are used.


  We study generically stable types/measures in both classical and continuous
logics, and their connection with randomization and modes of convergence of
types/measures.


  We review the current state and future prospect of ultra high energy cosmic
ray physics and the relationship between cosmic rays and gamma-ray
astrophysics.


  When interested in a time-to-event outcome, competing events that prevent the
occurrence of the event of interest may be present. In the presence of
competing events, various statistical estimands have been suggested for
defining the causal effect of treatment on the event of interest. Depending on
the estimand, the competing events are either accommodated or eliminated,
resulting in causal effects with different interpretation. The former approach
captures the total effect of treatment on the event of interest while the
latter approach captures the direct effect of treatment on the event of
interest that is not mediated by the competing event. Separable effects have
also been defined for settings where the treatment effect can be partitioned
into its effect on the event of interest and its effect on the competing event
through different causal pathways. We outline various causal effects that may
be of interest in the presence of competing events, including total, direct and
separable effects, and describe how to obtain estimates using regression
standardisation with the Stata command standsurv. Regression standardisation is
applied by obtaining the average of individual estimates across all individuals
in a study population after fitting a survival model. With standsurv several
contrasts of interest can be calculated including differences, ratios and other
user-defined functions. Confidence intervals can also be obtained using the
delta method. Throughout we use an example analysing a publicly available
dataset on prostate cancer to allow the reader to replicate the analysis and
further explore the different effects of interest.


  We investigate the dynamics of colloids at a fluid interface driven by
attractive capillary interactions. At submillimeter length scales, the
capillary attraction is formally analogous to two-dimensional gravity. In
particular it is a non-integrable interaction and it can be actually relevant
for collective phenomena in spite of its weakness at the level of the pair
potential. We introduce a mean-field model for the dynamical evolution of the
particle number density at the interface. For generic values of the physical
parameters the homogeneous distribution is found to be unstable against
large-scale clustering driven by the capillary attraction. We also show that
for the instability to be observable, the appropriate values for the relevant
parameters (colloid radius, surface charge, external electric field, etc.) are
experimentally well accessible. Our analysis contributes to current studies of
the structure and dynamics of systems governed by long-ranged interactions and
points towards their experimental realizations via colloidal suspensions.


  Astrophysical S-factors of radiative capture reactions on light nuclei have
been calculated in a two-cluster potential model, taking into account the
separation of orbital states by the use of Young schemes. The local two-body
potentials describing the interaction of the clusters were determined by
fitting scattering data and properties of bound states. The many-body character
of the problem is approximatively accounted for by Pauli forbidden states. An
important feature of the approach is the consideration of the dependence of the
interaction potential between the clusters on the orbital Young schemes, which
determine the permutation symmetry of the nucleon system. Proton capture on 2H,
6Li, 7Li, 12C, and 13C was analyzed in this approach. Experimental data at low
energies were described reasonably well when the phase shifts for
cluster-cluster scattering, extracted from precise data, were used. This shows
that decreasing the experimental error on differential elastic scattering cross
sections of light nuclei at astrophysical energies is very important also to
allow a more accurate phase shift analysis. A future increase in precision will
allow more definite conclusions regarding the reaction mechanisms and
astrophysical conditions of thermonuclear reactions.


  This article emphasizes an extension of the study of metric and par- tition
dimension to hypergraphs. We give a sharp lower bounds for the metric and
partition dimension of hypergraphs in general and give exact values under
specified conditions.eral and give exact values with specified conditions.


  We obtain $C^2$ a priori estimates for solutions of the nonlinear
second-order elliptic equation related to the geometric problem of finding a
strictly locally convex hypersurface with prescribed curvature and boundary in
a space form. Under the assumption of a strictly locally convex subsolution, we
establish existence results by using degree theory arguments.


  We investigate particles whose dynamics is invariant under the Carroll group.
Although a single free such Carroll particle has no non-trivial dynamics (`the
Carroll particle does not move') we show that there exists non-trivial dynamics
for a set of interacting Carroll particles. Furthermore, we gauge the Carroll
algebra and couple the Carroll particle to these gauge fields. It turns out
that for such a coupled system even a single Carroll particle can have
non-trivial dynamics.


  A high intensity laser-solid interaction invariably drives a non-thermal fast
electron current through the target, however characterizing these fast electron
distributions can prove difficult. An understanding of how these electrons
propagate through dense materials is of fundamental interest and has
applications relevant to fast ignition schemes and ion acceleration. Here, we
utilize an upgraded version of the Hybrid code ZEPHYROS to demonstrate how the
resulting k-alpha emission from such an interaction can be used as a diagnostic
to obtain the characteristic temperature, divergence and total energy of the
fast electron population.


  Groups of galaxies are the intermediate density environment in which much of
the evolution of galaxies is thought to take place. In spectroscopic redshift
surveys, one can identify these as close spatial redshift associations.
However, spectroscopic surveys will always be more limited in luminosity and
completeness than imaging ones. Here we combine the Galaxy And Mass Assembly
group catalogue with the extended Satellites Around Galactic Analogues (xSAGA)
catalogue of Machine Learning identified low-redshift satellite galaxies. We
find 1825 xSAGA galaxies within the bounds of the GAMA equatorial fields (m <
21), 1562 of which could have a counterpart in the GAMA spectroscopic catalogue
(m < 19.8). Of these, 1326 do have a GAMA counterpart with 974 below z=0.03
(true positives) and 352 above (false positives). By crosscorrelating the GAMA
group catalogue with the xSAGA catalogue, we can extend and characterize the
satellite content of GAMA galaxy groups. We find that most groups have <5 xSAGA
galaxies associated with them but richer groups may have more. Each additional
xSAGA galaxy contributes only a small fraction of the group's total stellar
mass (<<10%). Selecting GAMA groups that resemble the Milky Way halo, with a
few (<4) bright galaxies, we find xSAGA can add a magnitude fainter sources to
a group and that the Local Group does not stand out in the number of bright
satellites. We explore the quiescent fraction of xSAGA galaxies in GAMA groups
and find a good agreement with the literature.


  In this paper, we show the implementation of deep neural networks applied in
process control. In our approach, we based the training of the neural network
on model predictive control. Model predictive control is popular for its
ability to be tuned by the weighting matrices and by the fact that it respects
the constraints. We present the neural network that can approximate the
behavior of the MPC in the way of mimicking the control input trajectory while
the constraints on states and control input remain unimpaired of the value of
the weighting matrices. This approach is demonstrated in a simulation case
study involving a continuous stirred tank reactor, where multi-component
chemical reaction takes place.


  We analyze the three-body charmless decay B+- -> K+-K+-K-+ using a sample of
226.0 +- 2.5 million BBbar pairs collected by the BABAR detector. We measure
the total branching fraction and CP asymmetry to be B = (35.2 +- 0.9 +-1.6) x
10^{-6} and A_CP = (-1.7 +- 2.6 +- 1.5)%. We fit the Dalitz plot distribution
using an isobar model and measure the magnitudes and phases of the decay
coefficients. We find no evidence of CP violation for the individual components
of the isobar model. The decay dynamics is dominated by the K+K- S-wave, for
which we perform a partial-wave analysis in the region m(K+K-) < 2 GeV/c^2.
Significant production of the f0(980) resonance, and of a spin zero state near
1.55 GeV/c^2 are required in the isobar model description of the data. The
partial-wave analysis supports this observation.


  The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the
rendering speed of novel view synthesis. Unlike neural implicit representations
like Neural Radiance Fields (NeRF) that represent a 3D scene with position and
viewpoint-conditioned neural networks, 3D Gaussian Splatting utilizes a set of
Gaussian ellipsoids to model the scene so that efficient rendering can be
accomplished by rasterizing Gaussian ellipsoids into images. Apart from the
fast rendering speed, the explicit representation of 3D Gaussian Splatting
facilitates editing tasks like dynamic reconstruction, geometry editing, and
physical simulation. Considering the rapid change and growing number of works
in this field, we present a literature review of recent 3D Gaussian Splatting
methods, which can be roughly classified into 3D reconstruction, 3D editing,
and other downstream applications by functionality. Traditional point-based
rendering methods and the rendering formulation of 3D Gaussian Splatting are
also illustrated for a better understanding of this technique. This survey aims
to help beginners get into this field quickly and provide experienced
researchers with a comprehensive overview, which can stimulate the future
development of the 3D Gaussian Splatting representation.


  We present a framework to cluster nodes in directed networks according to
their roles by combining Role-Based Similarity (RBS) and Markov Stability, two
techniques based on flows. First we compute the RBS matrix, which contains the
pairwise similarities between nodes according to the scaled number of in- and
out-directed paths of different lengths. The weighted RBS similarity matrix is
then transformed into an undirected similarity network using the Relaxed
Minimum-Spanning Tree (RMST) algorithm, which uses the geometric structure of
the RBS matrix to unblur the network, such that edges between nodes with high,
direct RBS are preserved. Finally, we partition the RMST similarity network
into role-communities of nodes at all scales using Markov Stability to find a
robust set of roles in the network. We showcase our framework through a
biological and a man-made network.


  We present analytic all-order results for the highest three threshold
logarithms of the space-like and time-like off-diagonal splitting functions and
the corresponding coefficient functions for inclusive deep-inelastic scattering
(DIS) and semi-inclusive e^+ e^- annihilation. All these results, obtained
through an order-by-order analysis of the structure of the corresponding
unfactorized quantities in dimensional regularization, can be expressed in
terms of the Bernoulli functions introduced by one of us and
leading-logarithmic soft-gluon exponentials. The resulting numerical
corrections are small for the splitting functions but large for the coefficient
functions. In both cases more terms in the threshold expansion need to be
determined in order to arrive at quantitatively reliable results.


  The strength of the $E_{\rm p} = 1.842$ MeV resonance in the
$^{40}$Ca(p,$\gamma$)$^{41}$Sc reaction is determined with two different
methods: First, by an absolute strength measurement using calcium hydroxide
targets, and second, relative to the well-determined strength of the resonance
triplet at $E_\alpha$ = 4.5 MeV in the $^{40}$Ca($\alpha$,$\gamma$)$^{44}$Ti
reaction. The present new value of $\omega\gamma=(0.192\pm0.017)$ eV is 37%
(equivalent to $3.5\sigma$) higher than the evaluated literature value. In
addition, the ratio of the strengths of the 1.842 MeV
$^{40}$Ca(p,$\gamma$)$^{41}$Sc and 4.5 MeV
$^{40}$Ca($\alpha$,$\gamma$)$^{44}$Ti resonances has been determined to be
$0.0229\pm0.0018$. The newly corrected strength of the 1.842-MeV resonance can
be used in the future as a normalization point for experiments with calcium
targets.


  Inference for statistics of a stationary time series often involve nuisance
parameters and sampling distributions that are difficult to estimate. In this
paper, we propose the method of orthogonal samples, which can be used to
address some of these issues. For a broad class of statistics, an orthogonal
sample is constructed through a slight modification of the original statistic,
such that it shares similar distributional properties as the centralised
statistic of interest. We use the orthogonal sample to estimate nuisance
parameters of weighted average periodogram estimators and $L_{2}$-type spectral
statistics. Further, the orthogonal sample is utilized to estimate the finite
sampling distribution of various test statistics under the null hypothesis. The
proposed method is simple and computationally fast to implement. The viability
of the method is illustrated with various simulations.


  We consider a partially spin-polarized atomic Fermi gas in a
high-aspect-ratio trap, with a flux of predominantly spin-up atoms exiting the
center of the trap. We argue that such a scenario can be produced by
evaporative cooling, and we find that it can result in a substantially
non-equilibrium polarization pattern for typical experimental parameters. We
offer this as a possible explanation for the quantitative discrepancies in
recent experiments on spin-imbalanced unitary Fermi gases.


  The perfect conductivity problem concerns optimal bounds for the magnitude of
an electric field in the presence of almost touching perfect conductors. This
reduces to obtaining gradient estimates for harmonic functions with Dirichlet
boundary conditions in the narrow region between the conductors. In this paper
we extend estimates of Bao-Li-Yin to deal with the case when the boundaries of
the conductors are given by graphs with arbitrary vanishing orders. Our
estimates allow us to deal with globally defined narrow regions with possibly
non-trivial topology.
  We also prove the sharpness of our estimates in terms of the distance between
the perfect conductors. The precise optimality statement we give is new even in
the setting of Bao-Li-Yin.


  Effective emergency and natural disaster management depend on the efficient
mission-critical voice and data communication between first responders and
victims. Land Mobile Radio System (LMRS) is a legacy narrowband technology used
for critical voice communications with limited use for data applications.
Recently Long Term Evolution (LTE) emerged as a broadband communication
technology that has a potential to transform the capabilities of public safety
technologies by providing broadband, ubiquitous, and mission-critical voice and
data support. For example, in the United States, FirstNet is building a
nationwide coast-to-coast public safety network based of LTE broadband
technology. This paper presents a comparative survey of legacy and the
LTE-based public safety networks, and discusses the LMRS-LTE convergence as
well as mission-critical push-to-talk over LTE. A simulation study of LMRS and
LTE band class 14 technologies is provided using the NS-3 open source tool. An
experimental study of APCO-25 and LTE band class 14 is also conducted using
software-defined radio, to enhance the understanding of the public safety
systems. Finally, emerging technologies that may have strong potential for use
in public safety networks are reviewed.


  The $\pi_1(1600)$, a $J^{PC} = 1^{-+}$ exotic meson has been observed by
experiments using pion beams. Theorists predict that photon beams could produce
gluonic hybrid mesons, of which the $\pi_1(1600)$ is a candidate, at enhanced
levels relative to pion beams. The g12 rungroup at Jefferson Lab's CEBAF Large
Acceptance Spectrometer (CLAS) has recently acquired a large photoproduction
dataset, using a liquid hydrogen target and tagged photons from a 5.71 GeV
electron beam. A partial-wave analysis of 502K $\gamma p \to \pi^+\pi^+\pi^-n$
events selected from the g12 dataset has been performed, and preliminary fit
results show strong evidence for well-known states such as the $a_1(1260)$,
$a_2(1320)$, and $\pi_2(1670)$. However, we observe no evidence for the
production of the $\pi_1(1600)$ in either the partial-wave intensities or the
relative complex phase between the $1^{-+}$ and the $2^{-+}$ (corresponding to
the $\pi_2$) partial waves.


  Aim of this paper is to address the problem of learning Boolean functions
from training data with missing values. We present an extension of the BRAIN
algorithm, called U-BRAIN (Uncertainty-managing Batch Relevance-based
Artificial INtelligence), conceived for learning DNF Boolean formulas from
partial truth tables, possibly with uncertain values or missing bits.
  Such an algorithm is obtained from BRAIN by introducing fuzzy sets in order
to manage uncertainty. In the case where no missing bits are present, the
algorithm reduces to the original BRAIN.


  Given a full fingerprint image (rolled or slap), we present CycleGAN models
to generate multiple latent impressions of the same identity as the full print.
Our models can control the degree of distortion, noise, blurriness and
occlusion in the generated latent print images to obtain Good, Bad and Ugly
latent image categories as introduced in the NIST SD27 latent database. The
contributions of our work are twofold: (i) demonstrate the similarity of
synthetically generated latent fingerprint images to crime scene latents in
NIST SD27 and MSP databases as evaluated by the NIST NFIQ 2 quality measure and
ROC curves obtained by a SOTA fingerprint matcher, and (ii) use of synthetic
latents to augment small-size latent training databases in the public domain to
improve the performance of DeepPrint, a SOTA fingerprint matcher designed for
rolled to rolled fingerprint matching on three latent databases (NIST SD27,
NIST SD302, and IIITD-SLF). As an example, with synthetic latent data
augmentation, the Rank-1 retrieval performance of DeepPrint is improved from
15.50% to 29.07% on challenging NIST SD27 latent database. Our approach for
generating synthetic latent fingerprints can be used to improve the recognition
performance of any latent matcher and its individual components (e.g.,
enhancement, segmentation and feature extraction).


  Recent analyses of the Pal 5 and GD-1 tidal streams suggest that the inner
dark matter halo of the Milky Way is close to spherical, in tension with
predictions from collisionless N-body simulations of cosmological structure
formation. We use the Eris simulation to test whether the combination of
dissipative physics and hierarchical structure formation can produce Milky
Way-like galaxies whose dark matter halos match the tidal stream constraints
from the GD-1 and Pal 5 clusters. We use a dynamical model of the simulated
Eris galaxy to generate many realizations of the GD-1 and Pal 5 tidal streams,
marginalize over observational uncertainties in the cluster galactocentric
positions and velocities, and compare with the observational constraints. We
find that the total density and potential of Eris contributed by baryons and
dark matter satisfies constraints from the existing Milky Way stellar stream
data, as the baryons both round and redistribute the dark matter during the
dissipative formation of the galaxy, and provide a centrally-concentrated mass
distribution that rounds the inner potential. The Eris dark matter halo or a
spherical Navarro-Frenk-White dark matter work comparably well in modeling the
stream data. In contrast, the equivalent dark matter-only ErisDark simulation
produces a prolate halo that cannot reproduce the observed stream data. The
on-going Gaia mission will provide decisive tests of the consistency between
$\Lambda$CDM and Milky Way streams, and should distinguish between models like
Eris and more spherical halos.


  This paper introduces the order-theoretic concept of lattices along with the
concept of consistent quantification where lattice elements are mapped to real
numbers in such a way that preserves some aspect of the order-theoretic
structure. Symmetries, such as associativity, constrain consistent
quantification and lead to a constraint equation known as the sum rule.
Distributivity in distributive lattices also constrains consistent
quantification and leads to a product rule. The sum and product rules, which
are familiar from, but not unique to, probability theory, arise from the fact
that logical statements form a distributive (Boolean) lattice, which exhibits
the requisite symmetries.


  We consider Hardy-Rellich inequalities and discuss their possible
improvement. The procedure is based on decomposition into spherical harmonics,
where in addition various new inequalities are obtained (e.g. Rellich-Sobolev
inequalities). We discuss also the optimality of these inequalities in the
sense that we establish (in most cases) that the constants appearing there are
the best ones. Next, we investigate the polyharmonic operator (Rellich and
Higher Order Rellich inequalities); the difficulties arising in this case come
from the fact that (generally) minimizing sequences are no longer expected to
consist of radial functions. Finally, the successively use of the Rellich
inequalities lead to various new Higher Order Rellich inequalities.


  Low-light image enhancement (LLIE) has achieved promising performance by
employing conditional diffusion models. Despite the success of some conditional
methods, previous methods may neglect the importance of a sufficient
formulation of task-specific condition strategy, resulting in suboptimal visual
outcomes. In this study, we propose JoReS-Diff, a novel approach that
incorporates Retinex- and semantic-based priors as the additional
pre-processing condition to regulate the generating capabilities of the
diffusion model. We first leverage pre-trained decomposition network to
generate the Retinex prior, which is updated with better quality by an
adjustment network and integrated into a refinement network to implement
Retinex-based conditional generation at both feature- and image-levels.
Moreover, the semantic prior is extracted from the input image with an
off-the-shelf semantic segmentation model and incorporated through semantic
attention layers. By treating Retinex- and semantic-based priors as the
condition, JoReS-Diff presents a unique perspective for establishing an
diffusion model for LLIE and similar image enhancement tasks. Extensive
experiments validate the rationality and superiority of our approach.


  Inverse reinforcement learning (IRL) methods assume that the expert data is
generated by an agent optimizing some reward function. However, in many
settings, the agent may optimize a reward function subject to some constraints,
where the constraints induce behaviors that may be otherwise difficult to
express with just a reward function. We consider the setting where the reward
function is given, and the constraints are unknown, and propose a method that
is able to recover these constraints satisfactorily from the expert data. While
previous work has focused on recovering hard constraints, our method can
recover cumulative soft constraints that the agent satisfies on average per
episode. In IRL fashion, our method solves this problem by adjusting the
constraint function iteratively through a constrained optimization procedure,
until the agent behavior matches the expert behavior. We demonstrate our
approach on synthetic environments, robotics environments and real world
highway driving scenarios.


  Scheduling is important in Edge computing. In contrast to the Cloud, Edge
resources are hardware limited and cannot support workload-driven
infrastructure scaling. Hence, resource allocation and scheduling for the Edge
requires a fresh perspective. Existing Edge scheduling research assumes
availability of all needed resources whenever a job request is made. This paper
challenges that assumption, since not all job requests from a Cloud server can
be scheduled on an Edge node. Thus, guaranteeing fairness among the clients
(Cloud servers offloading jobs) while accounting for priorities of the jobs
becomes a critical task. This paper presents four scheduling techniques, the
first is a naive first come first serve strategy and further proposes three
strategies, namely a client fair, priority fair, and hybrid that accounts for
the fairness of both clients and job priorities. An evaluation on a target
platform under three different scenarios, namely equal, random, and Gaussian
job distributions is presented. The experimental studies highlight the low
overheads and the distribution of scheduled jobs on the Edge node when compared
to the naive strategy. The results confirm the superior performance of the
hybrid strategy and showcase the feasibility of fair schedulers for Edge
computing.


  With the advent of generative adversarial networks, synthesizing images from
textual descriptions has recently become an active research area. It is a
flexible and intuitive way for conditional image generation with significant
progress in the last years regarding visual realism, diversity, and semantic
alignment. However, the field still faces several challenges that require
further research efforts such as enabling the generation of high-resolution
images with multiple objects, and developing suitable and reliable evaluation
metrics that correlate with human judgement. In this review, we contextualize
the state of the art of adversarial text-to-image synthesis models, their
development since their inception five years ago, and propose a taxonomy based
on the level of supervision. We critically examine current strategies to
evaluate text-to-image synthesis models, highlight shortcomings, and identify
new areas of research, ranging from the development of better datasets and
evaluation metrics to possible improvements in architectural design and model
training. This review complements previous surveys on generative adversarial
networks with a focus on text-to-image synthesis which we believe will help
researchers to further advance the field.


  Extensive body of work has shown that for the model of a non-interacting
electron in a random potential there is a quantum critical point for dimensions
greater than two---a metal-insulator transition. This model also plays an
important role in the plateau-to-plateu transition in the integer quantum Hall
effect, which is also correctly captured by a scaling theory. Yet, in neither
of these cases the ground state energy shows any non-analyticity as a function
of a suitable tuning parameter, typically considered to be a hallmark of a
quantum phase transition, similar to the non-analyticity of the free energy in
a classical phase transition. Here we show that von Neumann entropy
(entanglement entropy) is non-analytic at these phase transitions and can track
the fundamental changes in the internal correlations of the ground state wave
function. In particular, it summarizes the spatially wildly fluctuating
intensities of the wave function close to the criticality of the Anderson
transition. It is likely that all quantum phase transitions can be similarly
described.


  We investigate clustering properties of quasars using a new version of our
semi-analytic model of galaxy and quasar formation with state-of-the-art
cosmological N-body simulations. In this study, we assume that a major merger
of galaxies triggers cold gas accretion on to a supermassive black hole and
quasar activity. Our model can reproduce the downsizing trend of the evolution
of quasars. We find that the median mass of quasar host dark matter haloes
increases with cosmic time by an order of magnitude from z=4 (a few 1e+11 Msun)
to z=1 (a few 1e+12 Msun), and depends only weakly on the quasar luminosity.
Deriving the quasar bias through the quasar--galaxy cross-correlation function
in the model, we find that the quasar bias does not depend on the quasar
luminosity, similar to observed trends. This result reflects the fact that
quasars with a fixed luminosity have various Eddington ratios and thus have
various host halo masses that primarily determine the quasar bias. We also show
that the quasar bias increases with redshift, which is in qualitative agreement
with observations. Our bias value is lower than the observed values at high
redshifts, implying that we need some mechanisms that make quasars inactive in
low-mass haloes and/or that make them more active in high-mass haloes.


  Using experimental longitudinal and transverse velocities data for very high
Reynolds number turbulence, we study both anisotropy and asymmetry of
turbulence. These both seem to be related to small scale turbulent structures,
and to intermittency. We may assume that the large scale velocity shear gives
an impact into the small scale turbulence, resulting in non-locality, and
related anomalous events.


  Existing works for extracting navigation objects from webpages focus on
navigation menus, so as to reveal the information architecture of the site.
However, web 2.0 sites such as social networks, e-commerce portals etc. are
making the understanding of the content structure in a web site increasingly
difficult. Dynamic and personalized elements such as top stories, recommended
list in a webpage are vital to the understanding of the dynamic nature of web
2.0 sites. To better understand the content structure in web 2.0 sites, in this
paper we propose a new extraction method for navigation objects in a webpage.
Our method will extract not only the static navigation menus, but also the
dynamic and personalized page-specific navigation lists. Since the navigation
objects in a webpage naturally come in blocks, we first cluster hyperlinks into
different blocks by exploiting spatial locations of hyperlinks, the
hierarchical structure of the DOM-tree and the hyperlink density. Then we
identify navigation objects from those blocks using the SVM classifier with
novel features such as anchor text lengths etc. Experiments on real-world data
sets with webpages from various domains and styles verified the effectiveness
of our method.


  In this paper, we prove six conjectures on the evaluations of permanents,
relating them to Genocchi numbers of the first and second kinds as well as
(binomial) Euler numbers. For example, we prove that
$$\mathrm{per}\left[\left\lfloor\frac{2j-k}{n}\right\rfloor\right]_{1\le j,k\le
n}=2(2^{n+1}-1)B_{n+1},$$ where $\lfloor\cdot\rfloor$ is the floor function and
$B_0,B_1,\ldots$ are the Bernoulli numbers. This was previously conjectured by
the third author. Various permutation statistics are at the heart of our
approaches.


  We have determined the structural and lattice dynamical properties of the
orthorhombic, wide band gap semiconductors MgSiN$_{2}$ and MgGeN$_{2}$ using
density functional theory. In addition, we present structural properties and
Raman spectra of a MgSiN$_{2}$ powder. The structural properties and lattice
dynamics of the orthorhombic systems are compared to wurtzite AlN. We find
clear differences in the lattice dynamics between MgSiN$_{2}$, MgGeN$_{2}$ and
AlN, for example we find that the highest phonon frequency in MgSiN$_{2}$ is
about 100~cm$^{-1}$ higher than the highest frequency in AlN and that
MgGeN$_{2}$ is much softer. We also provide the Born effective charge tensors
and dielectric tensors of MgSiN$_{2}$, MgGeN$_{2}$ and AlN. Phonon related
thermodynamic properties, such as the heat capacity and entropy, are in very
good agreement with available experimental results.


  Probabilistic amplification through photon addition, at the output of an
Mach-Zehnder interferometer is discussed for a coherent input state. When a
metric of signal to noise ratio is considered, nondeterministic, noiseless
amplification of a coherent state shows improvement over a standard coherent
state, for the general addition of $m$ photons. The efficiency of realizable
implementation of photon addition is also considered and shows how the
collected statistics of a post selected state, depend on this efficiency. We
also consider the effects of photon loss and inefficient detectors.


  Let $a_1,a_2,\dots,a_k$ be positive integers with
$\gcd(a_1,a_2,\dots,a_k)=1$. Frobenius number is the largest positive integer
that is NOT representable in terms of $a_1,a_2,\dots,a_k$. When $k\ge 3$, there
is no explicit formula in general, but some formulae may exist for special
sequences $a_1,a_2,\dots,a_k$, including, those forming arithmetic progressions
and their modifications. In this paper we give explicit formulae for the sum of
nonrepresentable positive integers (Sylvester sum) as well as Frobenius numbers
and the number of nonrepresentable positive integers (Sylverster number) for
$a_1,a_2,\dots,a_k$ forming arithmetic progressions with initial gaps.