  Large Language Models (LLMs) such as ChatGPT and Llama-2 have become
prevalent in real-world applications, exhibiting impressive text generation
performance. LLMs are fundamentally developed from a scenario where the input
data remains static and lacks a clear structure. To behave interactively over
time, LLM-based chat systems must integrate additional contextual information
(i.e., chat history) into their inputs, following a pre-defined structure. This
paper identifies how such integration can expose LLMs to misleading context
from untrusted sources and fail to differentiate between system and user
inputs, allowing users to inject context. We present a systematic methodology
for conducting context injection attacks aimed at eliciting disallowed
responses by introducing fabricated context. This could lead to illegal
actions, inappropriate content, or technology misuse. Our context fabrication
strategies, acceptance elicitation and word anonymization, effectively create
misleading contexts that can be structured with attacker-customized prompt
templates, achieving injection through malicious user messages. Comprehensive
evaluations on real-world LLMs such as ChatGPT and Llama-2 confirm the efficacy
of the proposed attack with success rates reaching 97%. We also discuss
potential countermeasures that can be adopted for attack detection and
developing more secure models. Our findings provide insights into the
challenges associated with the real-world deployment of LLMs for interactive
and structured data scenarios.


  We consider nonlinear effective actions for a spin-2 field, whose
`decoupling' limit gives Fierz-Pauli action in D dimensional maximally
symmetric spacetime. We find, especially, the effective action for a partially
massless field can take a concise geometrical form. The exact solution for time
evolution of the background metric in the model using the effective action is
also studied.


  The Hydra I cluster offers an excellent opportunity to study and compare the
relic old stellar populations in the core of its two brightest galaxies. In
addition, the differing kinematics of the two galaxies allows a test of the
local validity of general scaling relations. In this work we present a direct
comparison employing full spectral fitting of new high-quality long-slit
optical and NIR spectroscopic data. We retrieve age, metallicity and 19
elemental abundances out to about 12 kpc within each galaxy, as well as the IMF
in their central regions. Our results suggest that the inner 5 kpc region of
both galaxies, despite their different masses, formed at the same time and
evolved with a similar star formation time-scale and chemical enrichment,
confirming their early formation in the cluster build up. Only the overall
metallicity and IMF radial profiles show differences connected with their
different velocity dispersion profiles. The radial trend of the IMF positively
correlates with both [Z/H] and velocity dispersion. While the trends of the IMF
with metallicity agree with a global trend for both galaxies, the trends with
the velocity dispersion exhibit differences. The outer regions show signs of
mixed stellar populations with large differences in chemical content compared
to the centers, but with similar old ages.


  Bismuth, the heaviest of all group V elements with strong spin-orbit
coupling, is famously known to exhibit many interesting transport properties,
and effects such as Shubnikov-de Haas and de Haas-van Alphen were first
revealed in its bulk form. However, the transport properties have not yet been
fully explored experimentally in thin bismuth nor in its 2D limit. In this
work, bismuth flakes with average thicknesses ranging from 29 to 69 nm were
mechanically exfoliated by a micro-trench technique and were used to fabricate
four-point devices. Due to mixing of components, Onsager's relations were used
to extract the longitudinal ($R_{xx}$) and Hall ($R_{xy}$) resistances where
the latter shows a Hall anomaly that is consistent with the Anomalous Hall
Effect (AHE). Our work strongly suggests that that there could be a hidden
mechanism for time-reversal symmetry breaking in pure bismuth thin films.


  A solution that is only reliable under favourable conditions is hardly a safe
solution. Min Max Optimization is an approach that returns optima that are
robust against worst case conditions. We propose algorithms that perform Min
Max Optimization in a setting where the function that should be optimized is
not known a priori and hence has to be learned by experiments. Therefore we
extend the Bayesian Optimization setting, which is tailored to maximization
problems, to Min Max Optimization problems. While related work extends the two
acquisition functions Expected Improvement and Gaussian Process Upper
Confidence Bound; we extend the two acquisition functions Entropy Search and
Knowledge Gradient. These acquisition functions are able to gain knowledge
about the optimum instead of just looking for points that are supposed to be
optimal. In our evaluation we show that these acquisition functions allow for
better solutions - converging faster to the optimum than the benchmark
settings.


  We introduce the notions of de Bruijn polyominoes and prismatic polyominoes,
which generalize the notions of de Bruijn sequences and arrays. Given a small
fixed polyomino $p$ and a set of colors $[n]$, a de Bruijn polyomino for
$(p,n)$ is a colored fixed polyomino $P$ with cells colored from $[n]$ such
that every possible coloring of $p$ from $[n]$ exists as a subset of $P$. We
call de Bruijn polyominoes for $(p,n)$ of minimum size $(p,n)$-prismatic. We
discuss for some values of $p$ and $n$ the shape of a $(p,n)$-prismatic
polyomino $P$, the construction of a coloring of $P$, and the enumeration of
the colorings of $P$. We find evidence that the difficulty of these problems
may depend on the parity of the size of $p$


  We present the longest, by a factor of two, near-infrared lightcurve from Sgr
A* - the supermassive black hole in the Galactic center. Achieved by combining
Keck and VLT data from one common night, which fortuitously had simultaneous
Chandra and SMA data, this lightcurve is used to address two outstanding
problems. First, a putative quasi-periodicity of ~20 min reported by groups
using ESO's VLT is not confirmed by Keck observations. Second, while the
infrared and mm-regimes are thought to be related based on reported time lags
between lightcurves from the two wavelength domains, the reported time lag of
20 min inferred using the Keck data of this common VLT/Keck night only is at
odds with the lag of ~100 min reported earlier. With our long lightcurve, we
find that (i) the simultaneous 1.3 millimeter observations are in fact
consistent with a ~100 min time lag, (ii) the different methods of NIR
photometry used by the VLT and Keck groups lead to consistent results, (iii)
the Lomb-Scargle periodogram of the whole NIR lightcurve is featureless and
follows a power-law with slope -1.6, and (iv) scanning the lightcurve with a
sliding window to look for a transient QPO phenomenon reveals for a certain
part of the lightcurve a 25 min peak in the periodogram. Using Monte Carlo
simulations and taking the number of trials into account, we find it to be
insignificant.


  The first measurement of the cross section ratio sigma(t t-bar b b-bar) /
sigma(t t-bar jj) is presented using a data sample corresponding to an
integrated luminosity of 19.6 inverse femtobarns collected in pp collisions at
sqrt(s) = 8 TeV with the CMS detector at the LHC. Events with two leptons (e or
mu) and four reconstructed jets, including two identified as b quark jets, in
the final state are selected. The ratio is determined for a minimum jet
transverse momentum pt of both 20 and 40 GeV. The measured ratio is 0.022 +/-
0.003 (stat) +/- 0.005 (syst) for pt > 20 GeV. The absolute cross sections
sigma(t t-bar b b-bar) and sigma(t t-bar jj) are also measured. The measured
ratio for pt > 40 GeV is compatible with a theoretical quantum chromodynamics
calculation at next-to-leading order.


  We theoretically investigate effect of a transverse electric field generated
by side gates and a vertical electric field generated by top, back gates on
energy bands and transport properties of zigzag bilayer graphene ribbons
(Bernal stacking). Using atomistic Tight Binding calculations and Green
function formalism we demonstrate that bandgap is opened when either field is
applied and even enlarged under simultaneous influence of the two fields.
Interestingly, although vertical electric fields are widely used to control
bandgap in bilayer graphene, here we show that transverse fields exhibit more
positive effect in terms of modulating a larger range of bandgap and retaining
good electrical conductance. Seebeck effect is also demonstrated to be enhanced
strongly about 13 times for a zigzag bilayer graphene ribbons with 16 chain
lines. These results may motivate new designs of devices made of bilayer
graphene ribbons using electric gates.


  The present dissertation describes design, qualification and operation of
several electronic instrumentations for High Energy Particle Physics
experiments (LHCb) and Neutrino Physics experiments (CUORE and CUPID). Starting
from 2019, the LHCb experiment at the LHC accelerator will be upgraded to
operate at higher luminosity and several of its detectors will be redesigned.
The RICH detector will require a completely new optoelectronic readout system.
The development of such system has already reached an advanced phase, and
several tests at particle beam facilities allowed to qualify the performance of
the entire system. In order to achieve a higher stability and a better power
supply regulation for the frontend chip, a rad-hard low dropout linear
regulator, named ALDO, has been developed. Design strategies, performance tests
and results from the irradiation campaign are presented. In the Neutrino
Physics field, large scale bolometric detectors, like those adopted by CUORE
and its future upgrade CUPID, offer unique opportunities for the study of
neutrinoless double beta decay. Their operation requires particular strategies
in the readout instrumentation, which is described here in its entirety. The
qualification and optimization of the working parameters as well as the
integration of the system in the experimental area are also thoroughly
discussed,together with the latest upgrades of two electronic subsystems for
the future CUPID experiment


  We numerically investigate the decay, via parametric resonance, of the
inflaton with an m^2 phi^2 potential into a scalar matter field with a symmetry
breaking potential. We consider the case where symmetry breaking takes place
during inflation. We show that when expansion is not taken into account
symmetry restoration and non-thermal defect production during reheating is
possible. However in an expanding universe the fields do not spend sufficient
time in the instability bands; thus symmetry restoration and subsequent domain
wall production do not occur.


  In this paper, we determine all irreducible spherical functions \Phi of any K
-type associated to the pair (G,K)=(\SO(4),\SO(3)). This is accomplished by
associating to \Phi a vector valued function H=H(u) of a real variable u, which
is analytic at u=0 and whose components are solutions of two coupled systems of
ordinary differential equations. By an appropriate conjugation involving Hahn
polynomials we uncouple one of the systems. Then this is taken to an uncoupled
system of hypergeometric equations, leading to a vector valued solution P=P(u)
whose entries are Gegenbauer's polynomials. Afterward, we identify those
simultaneous solutions and use the representation theory of \SO(4) to
characterize all irreducible spherical functions. The functions P=P(u)
corresponding to the irreducible spherical functions of a fixed K-type \pi_\ell
are appropriately packaged into a sequence of matrix valued polynomials
(P_w)_{w\ge0} of size (\ell+1)\times(\ell+1). Finally we proved that \widetilde
P_w={P_0}^{-1}P_w is a sequence of matrix orthogonal polynomials with respect
to a weight matrix W. Moreover we showed that W admits a second order symmetric
hypergeometric operator \widetilde D and a first order symmetric differential
operator \widetilde E.


  We give an elementary, case-free, Coxeter-theoretic derivation of the formula
$h^nn!/|W|$ for the number of maximal chains in the noncrossing partition
lattice $NC(W)$ of a real reflection group $W$. Our proof proceeds by comparing
the Deligne-Reading recursion with a parabolic recursion for the characteristic
polynomial of the $W$-Laplacian matrix considered in our previous work. We
further discuss the consequences of this formula for the geometric group theory
of spherical and affine Artin groups.


  In 1990 Erd\H{o}s, Faudree, Rousseau and Schelp proved that for $k\geq 2$,
every graph with $n\geq k+1$ vertices and $(k-1)(n-k+2)+\binom{k-2}{2}+1$ edges
contains a subgraph of minimum degree $k$ on at most $n-\sqrt{n}/\sqrt{6k^3}$
vertices. They conjectured that it is possible to remove at least $\epsilon_k
n$ many vertices and remain with a subgraph of minimum degree $k$, for some
$\epsilon_k>0$. We make progress towards their conjecture by showing that one
can remove at least $\Omega(n/\log n)$ many vertices.


  This is a progress report on a preliminary feasibility study of experimental
setups for preparing and probing a gravitational cat state [1].


  Fractional order proportional-integral-derivative (FOPID) controllers are
designed for load frequency control (LFC) of two interconnected power systems.
Conflicting time domain design objectives are considered in a multi objective
optimization (MOO) based design framework to design the gains and the
fractional differ-integral orders of the FOPID controllers in the two areas.
Here, we explore the effect of augmenting two different chaotic maps along with
the uniform random number generator (RNG) in the popular MOO algorithm - the
Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Different measures of
quality for MOO e.g. hypervolume indicator, moment of inertia based diversity
metric, total Pareto spread, spacing metric are adopted to select the best set
of controller parameters from multiple runs of all the NSGA-II variants (i.e.
nominal and chaotic versions). The chaotic versions of the NSGA-II algorithm
are compared with the standard NSGA-II in terms of solution quality and
computational time. In addition, the Pareto optimal fronts showing the
trade-off between the two conflicting time domain design objectives are
compared to show the advantage of using the FOPID controller over that with
simple PID controller. The nature of fast/slow and high/low noise amplification
effects of the FOPID structure or the four quadrant operation in the two
inter-connected areas of the power system is also explored. A fuzzy logic based
method has been adopted next to select the best compromise solution from the
best Pareto fronts corresponding to each MOO comparison criteria. The time
domain system responses are shown for the fuzzy best compromise solutions under
nominal operating conditions. Comparative analysis on the merits and de-merits
of each controller structure is reported then. A robustness analysis is also
done for the PID and the FOPID controllers.


  We study structure, eigenvalue spectra and diffusion dynamics in a wide class
of networks with subgraphs (modules) at mesoscopic scale. The networks are
grown within the model with three parameters controlling the number of modules,
their internal structure as scale-free and correlated subgraphs, and the
topology of connecting network. Within the exhaustive spectral analysis for
both the adjacency matrix and the normalized Laplacian matrix we identify the
spectral properties which characterize the mesoscopic structure of sparse
cyclic graphs and trees. The minimally connected nodes, clustering, and the
average connectivity affect the central part of the spectrum. The number of
distinct modules leads to an extra peak at the lower part of the Laplacian
spectrum in cyclic graphs. Such a peak does not occur in the case of
topologically distinct tree-subgraphs connected on a tree. Whereas the
associated eigenvectors remain localized on the subgraphs both in trees and
cyclic graphs. We also find a characteristic pattern of periodic localization
along the chains on the tree for the eigenvector components associated with the
largest eigenvalue equal 2 of the Laplacian. We corroborate the results with
simulations of the random walk on several types of networks. Our results for
the distribution of return-time of the walk to the origin (autocorrelator)
agree well with recent analytical solution for trees, and it appear to be
independent on their mesoscopic and global structure. For the cyclic graphs we
find new results with twice larger stretching exponent of the tail of the
distribution, which is virtually independent on the size of cycles. The
modularity and clustering contribute to a power-law decay at short return
times.


  Rate distortion theory is concerned with optimally encoding a given signal
class $\mathcal{S}$ using a budget of $R$ bits, as $R\to\infty$. We say that
$\mathcal{S}$ can be compressed at rate $s$ if we can achieve an error of
$\mathcal{O}(R^{-s})$ for encoding $\mathcal{S}$; the supremal compression rate
is denoted $s^\ast(\mathcal{S})$. Given a fixed coding scheme, there usually
are elements of $\mathcal{S}$ that are compressed at a higher rate than
$s^\ast(\mathcal{S})$ by the given coding scheme; we study the size of this set
of signals. We show that for certain "nice" signal classes $\mathcal{S}$, a
phase transition occurs: We construct a probability measure $\mathbb{P}$ on
$\mathcal{S}$ such that for every coding scheme $\mathcal{C}$ and any $s
>s^\ast(\mathcal{S})$, the set of signals encoded with error
$\mathcal{O}(R^{-s})$ by $\mathcal{C}$ forms a $\mathbb{P}$-null-set. In
particular our results apply to balls in Besov and Sobolev spaces that embed
compactly into $L^2(\Omega)$ for a bounded Lipschitz domain $\Omega$. As an
application, we show that several existing sharpness results concerning
function approximation using deep neural networks are generically sharp.
  We also provide quantitative and non-asymptotic bounds on the probability
that a random $f\in\mathcal{S}$ can be encoded to within accuracy $\varepsilon$
using $R$ bits. This result is applied to the problem of approximately
representing $f\in\mathcal{S}$ to within accuracy $\varepsilon$ by a
(quantized) neural network that is constrained to have at most $W$ nonzero
weights and is generated by an arbitrary "learning" procedure. We show that for
any $s >s^\ast(\mathcal{S})$ there are constants $c,C$ such that, no matter how
we choose the "learning" procedure, the probability of success is bounded from
above by $\min\big\{1,2^{C\cdot W\lceil\log_2(1+W)\rceil^2
-c\cdot\varepsilon^{-1/s}}\big\}$.


  We study the dynamics of nonequilibrium instabilities in anisotropically
expanding systems. The most prominent example of such a system is the 'Glasma'
in the context of relativistic heavy-ion collision experiments, where the
expansion is a consequence of approximately boost-invariant initial conditions.
Here we consider the problem of parametric resonance in scalar $N$-component
quantum field theories with boost-invariant initial conditions, which is
similar in spirit. We find that many aspects of the dynamics can be treated
analytically by introducing a generalized conformal time. Primary
instabilities, which are described by the linearized evolution equations, are
seen to lead to a secondary regime of amplifications with strongly enhanced
growth rates due to nonlinear corrections. For the secondary instabilities we
present a power-counting scheme for weak coupling, and discuss their role for
the question of isotropization and the establishment of an equation of state.


  Building on work of Mondino-Scharrer, we show that among closed, smoothly
embedded surfaces in $\mathbb{R}^3$ of genus $g$ and given isoperimetric ratio
$v$, there exists one with minimum bending energy $\mathcal{W}$. We do this by
gluing $g+1$ small catenoidal bridges to the bigraph of a singular solution for
the linearized Willmore equation $\Delta (\Delta +2)\varphi=0$ on the
$(g+1)$-punctured sphere $\mathbb{S}^2$ to construct a comparison surface of
genus $g$ with arbitrarily small isoperimetric ratio $v\in (0, 1)$ and
$\mathcal{W} < 8\pi$.


  We study fermionic one-matrix, two-matrix and $D$-dimensional gauge invariant
matrix models. In all cases we derive loop equations which unambiguously
determine the large-$N$ solution. For the one-matrix case the solution is
obtained for an arbitrary interaction potential and turns out to be equivalent
to the one for the Hermitean one-matrix model with a logarithmic potential and,
therefore, belongs to the same universality class. The explicit solutions for
the fermionic two-matrix and $D$-dimensional matrix models are obtained at
large $N$ (or in the spherical approximation) for the quadratic potential.


  Bayesian optimization (BO) conventionally relies on handcrafted acquisition
functions (AFs) to sequentially determine the sample points. However, it has
been widely observed in practice that the best-performing AF in terms of regret
can vary significantly under different types of black-box functions. It has
remained a challenge to design one AF that can attain the best performance over
a wide variety of black-box functions. This paper aims to attack this challenge
through the perspective of reinforced few-shot AF learning (FSAF).
Specifically, we first connect the notion of AFs with Q-functions and view a
deep Q-network (DQN) as a surrogate differentiable AF. While it serves as a
natural idea to combine DQN and an existing few-shot learning method, we
identify that such a direct combination does not perform well due to severe
overfitting, which is particularly critical in BO due to the need of a
versatile sampling policy. To address this, we present a Bayesian variant of
DQN with the following three features: (i) It learns a distribution of
Q-networks as AFs based on the Kullback-Leibler regularization framework. This
inherently provides the uncertainty required in sampling for BO and mitigates
overfitting. (ii) For the prior of the Bayesian DQN, we propose to use a demo
policy induced by an off-the-shelf AF for better training stability. (iii) On
the meta-level, we leverage the meta-loss of Bayesian model-agnostic
meta-learning, which serves as a natural companion to the proposed FSAF.
Moreover, with the proper design of the Q-networks, FSAF is general-purpose in
that it is agnostic to the dimension and the cardinality of the input domain.
Through extensive experiments, we demonstrate that the FSAF achieves comparable
or better regrets than the state-of-the-art benchmarks on a wide variety of
synthetic and real-world test functions.


  We propose a simple technique for the generation of arbitrary-sized Dicke
states in a chain of trapped ions. The method uses global addressing of the
entire chain by two pairs of delayed but partially overlapping laser pulses to
engineer a collective adiabatic passage along a multi-ion dark state. Our
technique, which is a many-particle generalization of stimulated Raman
adiabatic passage (STIRAP), is decoherence-free with respect to spontaneous
emission and robust against moderate fluctuations in the experimental
parameters. Furthermore, because the process is very rapid, the effects of
heating are almost negligible under realistic experimental conditions. We
predict that the overall fidelity of synthesis of a Dicke state involving ten
ions sharing two excitations should approach 98% with currently achievable
experimental parameters.


  Prototypical Learning is based on the idea that there is a point (which we
call prototype) around which the embeddings of a class are clustered. It has
shown promising results in scenarios with little labeled data or to design
explainable models. Typically, prototypes are either defined as the average of
the embeddings of a class or are designed to be trainable. In this work, we
propose to predefine prototypes following human-specified criteria, which
simplify the training pipeline and brings different advantages. Specifically,
in this work we explore two of these advantages: increasing the inter-class
separability of embeddings and disentangling embeddings with respect to
different variance factors, which can translate into the possibility of having
explainable predictions. Finally, we propose different experiments that help to
understand our proposal and demonstrate empirically the mentioned advantages.


  In this paper, we characterize when the $\ell^p$ uniform Roe algebra of a
metric space with bounded geometry is (stably) finite and when it is properly
infinite in standard form for $p\in [1,\infty)$. Moreover, we show that the
$\ell^p$ uniform Roe algebra is a (non-sequential) spatial $L^p$ AF algebra in
the sense of Phillips and Viola if and only if the underlying metric space has
asymptotic dimension zero.
  We also consider the ordered $K_0$ groups of $\ell^p$ uniform Roe algebras
for metric spaces with low asymptotic dimension, showing that (1) the ordered
$K_0$ group is trivial when the metric space is non-amenable and has asymptotic
dimension at most one, and (2) when the metric space is a countable locally
finite group, the (ordered) $K_0$ group is a complete invariant for the
(bijective) coarse equivalence class of the underlying locally finite group. It
happens that in both cases the ordered $K_0$ group does not depend on $p\in
[1,\infty)$.


  We model the atmospheres and spectra of Earth-like planets orbiting the
entire grid of M dwarfs for active and inactive stellar models with $T_{eff}$ =
2300K to $T_{eff}$ = 3800K and for six observed MUSCLES M dwarfs with UV
radiation data. We set the Earth-like planets at the 1AU equivalent distance
and show spectra from the VIS to IR (0.4$\mu$m - 20$\mu$m) to compare
detectability of features in different wavelength ranges with JWST and other
future ground- and spaced-based missions to characterize exo-Earths. We focus
on the effect of UV activity levels on detectable atmospheric features that
indicate habitability on Earth, namely: H$_2$O, O$_3$, CH$_4$, N$_2$O and
CH$_3$Cl.
  To observe signatures of life - O$_2$/O$_3$ in combination with reducing
species like CH$_4$, we find that early and active M dwarfs are the best
targets of the M star grid for future telescopes. The O$_2$ spectral feature at
0.76$\mu$m is increasingly difficult to detect in reflected light of later M
dwarfs due to low stellar flux in that wavelength region. N$_2$O, another
biosignature detectable in the IR, builds up to observable concentrations in
our planetary models around M dwarfs with low UV flux. CH$_3$Cl could become
detectable, depending on the depth of the overlapping N$_2$O feature.
  We present a spectral database of Earth-like planets around cool stars for
directly imaged planets as a framework for interpreting future lightcurves,
direct imaging, and secondary eclipse measurements of the atmospheres of
terrestrial planets in the HZ to design and assess future telescope
capabilities.


  Generalized disformal transformations enable us to construct the generalized
disformal Horndeski theories, which form the most general class of ghost-free
scalar-tensor theories to this date. We extend the effective field theory (EFT)
of cosmological perturbations to incorporate these generalized disformal
Horndeski theories. The main difference from the conventional EFT is that our
extended EFT involves operators with higher spatial derivatives of the lapse
function. Our EFT also accommodates the generalized disformal transformation of
U-DHOST theories.


  We develop a unified theory for clocks and gravimeters using the
interferences of multiple atomic waves put in levitation by traveling light
pulses. Inspired by optical methods, we exhibit a propagation invariant, which
enables to derive analytically the wave function of the sample scattering on
the light pulse sequence. A complete characterization of the device sensitivity
with respect to frequency or to acceleration measurements is obtained. These
results agree with previous numerical simulations and confirm the conjecture of
sensitivity improvement through multiple atomic wave interferences. A realistic
experimental implementation for such clock architecture is discussed.


  We compute the Chern-Simons transgressed forms of some modularly invariant
characteristic forms, which are related to the elliptic genera. We study the
modularity properties of these secondary characteristic forms and the relations
among them. We also compute the Chern-Simons forms of some vector bundles over
free loop space.


  The electronic structure of low-density n-type SrTiO3 delta-doped
heterostructures is investigated by angular dependent Shubnikov-de Haas
oscillations. In addition to a controllable crossover from a three- to
two-dimensional Fermi surface, clear beating patterns for decreasing dopant
layer thicknesses are found. These indicate the lifting of the degeneracy of
the conduction band due to subband quantization in the two-dimensional limit.
Analysis of the temperature-dependent oscillations shows that similar effective
masses are found for all components, associated with the splitting of the light
electron pocket. The dimensionality crossover in the superconducting state is
found to be distinct from the normal state, resulting in a rich phase diagram
as a function of dopant layer thickness.


  Fungal automata are a variation of the two-dimensional sandpile automaton of
Bak, Tang, and Wiesenfeld (Phys. Rev. Lett. 1987). In each step toppling cells
emit grains only to some of their neighbors chosen according to a specific
update sequence. We show how to embed any Boolean circuit into the initial
configuration of a fungal automaton with update sequence $HV$. In particular we
give a constructor that, given the description $B$ of a circuit, computes the
states of all cells in the finite support of the embedding configuration in
$O(\log |B|)$ space. As a consequence the prediction problem for fungal
automata with update sequence $HV$ is $\mathsf{P}$-complete. This solves an
open problem of Goles et al. (Phys. Lett. A, 2020).


  We employ a non-compact gauging of four-dimensional maximal supergravity to
construct a two-parameter family of AdS$_4$ J-fold solutions preserving
$\mathcal{N}=2$ supersymmetry. All solutions preserve
$\mathfrak{u}(1)\times\mathfrak{u}(1)$ global symmetry and in special limits we
recover the previously known $\mathfrak{su}(2)\times\mathfrak{u}(1)$ invariant
$\mathcal{N}=2$ and $\mathfrak{su}(2)\times\mathfrak{su}(2)$ invariant
$\mathcal{N}=4$ J-fold solutions. This family of AdS$_4$ backgrounds can be
uplifted to type IIB string theory and is holographically dual to the conformal
manifold of a class of three-dimensional $S$-fold SCFTs obtained from the
$\mathcal{N}=4$ $T[\text{U}(N)]$ theory of Gaiotto-Witten. We find the spectrum
of supergravity excitations of the AdS$_4$ solutions and use it to study how
the operator spectrum of the three-dimensional SCFT depends on the exactly
marginal couplings.


  Domain adaptation (DA) aims to transfer knowledge from a label-rich but
heterogeneous domain to a label-scare domain, which alleviates the labeling
efforts and attracts considerable attention. Different from previous methods
focusing on learning domain-invariant feature representations, some recent
methods present generic semi-supervised learning (SSL) techniques and directly
apply them to DA tasks, even achieving competitive performance. One of the most
popular SSL techniques is pseudo-labeling that assigns pseudo labels for each
unlabeled data via the classifier trained by labeled data. However, it ignores
the distribution shift in DA problems and is inevitably biased to source data.
To address this issue, we propose a new pseudo-labeling framework called
Auxiliary Target Domain-Oriented Classifier (ATDOC). ATDOC alleviates the
classifier bias by introducing an auxiliary classifier for target data only, to
improve the quality of pseudo labels. Specifically, we employ the memory
mechanism and develop two types of non-parametric classifiers, i.e. the nearest
centroid classifier and neighborhood aggregation, without introducing any
additional network parameters. Despite its simplicity in a pseudo
classification objective, ATDOC with neighborhood aggregation significantly
outperforms domain alignment techniques and prior SSL techniques on a large
variety of DA benchmarks and even scare-labeled SSL tasks.


  Hashing is a basic tool for dimensionality reduction employed in several
aspects of machine learning. However, the perfomance analysis is often carried
out under the abstract assumption that a truly random unit cost hash function
is used, without concern for which concrete hash function is employed. The
concrete hash function may work fine on sufficiently random input. The question
is if it can be trusted in the real world when faced with more structured
input.
  In this paper we focus on two prominent applications of hashing, namely
similarity estimation with the one permutation hashing (OPH) scheme of Li et
al. [NIPS'12] and feature hashing (FH) of Weinberger et al. [ICML'09], both of
which have found numerous applications, i.e. in approximate near-neighbour
search with LSH and large-scale classification with SVM.
  We consider mixed tabulation hashing of Dahlgaard et al.[FOCS'15] which was
proved to perform like a truly random hash function in many applications,
including OPH. Here we first show improved concentration bounds for FH with
truly random hashing and then argue that mixed tabulation performs similar for
sparse input. Our main contribution, however, is an experimental comparison of
different hashing schemes when used inside FH, OPH, and LSH.
  We find that mixed tabulation hashing is almost as fast as the
multiply-mod-prime scheme ax+b mod p. Mutiply-mod-prime is guaranteed to work
well on sufficiently random data, but we demonstrate that in the above
applications, it can lead to bias and poor concentration on both real-world and
synthetic data. We also compare with the popular MurmurHash3, which has no
proven guarantees. Mixed tabulation and MurmurHash3 both perform similar to
truly random hashing in our experiments. However, mixed tabulation is 40%
faster than MurmurHash3, and it has the proven guarantee of good performance on
all possible input.


  This article proposes a general approach to the simulation and design of a
multilayer perceptron (MLP) network on the basis of cross-bar arrays of
metal-oxide memristive devices. The proposed approach uses the ANNM theory,
tolerance theory, simulation methodology and experiment design. The tolerances
analysis and synthesis process is performed for the ANNM hardware
implementation on the basis of two arrays of memristive microdevices in the
original 16x16 cross-bar topology being a component of bidirectional adaptive
neural interface for automatic registration and stimulation of bioelectrical
activity of a living neuronal culture used in robotics control system. The ANNM
is trained for solving a nonlinear classification problem of stable information
characteristics registered in the culture grown on a multi-electrode array.
Memristive devices are fabricated on the basis of a newly engineered
Au/Ta/ZrO2(Y)/Ta2O5/TiN/Ti multilayer structure, which contains self-organized
interface oxide layers, nanocrystals and is specially developed to obtain
robust resistive switching with low variation of parameters. An array of
memristive devices is mounted into a standard metal-ceramic package and can be
easily integrated into the neurointerface circuit. Memristive devices
demonstrate bipolar switching of anionic type between the high-resistance state
and low-resistance state and can be programmed to set the intermediate
resistive states with a desired accuracy. The ANNM tuning, testing and control
are implemented by the FPGA-based control subsystem. All developed models and
algorithms are implemented as Python-based software.


  The Internet of Things (IoT) is rapidly changing our society to a world where
every "thing" is connected to the Internet, making computing pervasive like
never before. This tsunami of connectivity and data collection relies more and
more on the Cloud, where data analytics and intelligence actually reside. Cloud
computing has indeed revolutionized the way computational resources and
services can be used and accessed, implementing the concept of utility
computing whose advantages are undeniable for every business. However, despite
the benefits in terms of flexibility, economic savings, and support of new
services, its widespread adoption is hindered by the security issues arising
with its usage. From a security perspective, the technological revolution
introduced by IoT and Cloud computing can represent a disaster, as each object
might become inherently remotely hackable and, as a consequence, controllable
by malicious actors. While the literature mostly focuses on security of IoT and
Cloud computing as separate entities, in this article we provide an up-to-date
and well-structured survey of the security issues of Cloud computing in the IoT
era. We give a clear picture of where security issues occur and what their
potential impact is. As a result, we claim that it is not enough to secure IoT
devices, as cyber-storms come from Clouds.


  One-loop counterterms are computed in the first order formalism for the
Einstein-Hilbert action with a minimally coupled scalar field using the
background field method and the heat kernel technique. The {\em off-shell}
divergent piece in the harmonic gauge is {\em exactly} the same as the one
first found by 't Hooft and Veltman.


  The energy loss mechanism of jets plays a central role in nuclear and high
energy physics. We propose direct measurements of the energy loss of leading
jets and perform a calculation at next-to-leading logarithmic (NLL$'$) accuracy
in the vacuum. The formation of leading jets can be described by jet functions
which constitute probability densities and thus allow for a perturbative
calculation of the average the energy loss. We identify the following three
criteria for a direct measurement of jet energy loss at the cross section
level. $i)$ We measure a well defined object, the leading jet, where the
formation process can be expressed in terms of a probability density. $ii)$ In
addition, we need a measurement of a hard reference scale with respect to which
jet energy loss is defined. $iii)$ At leading logarithmic accuracy, we require
that the jet energy loss can be identified with parton energy loss. We discuss
suitable observables and present numerical results including threshold
corrections by making use of a parton shower Monte Carlo approach.


  We prove that for any dimension function $h$ with $h \prec x^d$ and for any
countable set of linear patterns, there exists a compact set $E$ with
$\mathcal{H}^h(E)>0$ avoiding all the given patterns. We also give several
applications and recover results of Keleti, Maga, and M\'{a}th\'{e}.


  We benchmark the 5000+ qubit system Advantage coupled with the Hybrid Solver
Service 2 released by D-Wave Systems Inc. in September 2020 by using a new
class of optimization problems called garden optimization problems known in
companion planting. These problems are scalable to an arbitrarily large number
of variables and intuitively find application in real-world scenarios. We
derive their QUBO formulation and illustrate their relation to the quadratic
assignment problem. We demonstrate that the Advantage system and the new hybrid
solver can solve larger problems in less time than their predecessors. However,
we also show that the solvers based on the 2000+ qubit system DW2000Q sometimes
produce more favourable results if they can solve the problems.


  We present the results of simulation of the chaotic dynamics of quantized
vortices in the bulk of superfluid He II.
  Evolution of vortex lines is calculated on the base of the Biot-Savart law.
The dissipative effects appeared from the interaction with the normal
component, or/and from relaxation of the order parameter are taken into
account. Chaotic dynamics appears in the system via a random forcing, e.i. we
use the Langevin approach to the problem. In the present paper we require the
correlator of the random force to satisfy the fluctuation-disspation relation,
which implies that thermodynamic equilibrium should be reached. In the paper we
describe the numerical methods for integration of stochastic differential
equation (including a new algorithm for reconnection processes), and we present
the results of calculation of some characteristics of a vortex tangle such as
the total length, distribution of loops in the space of their length, and the
energy spectrum.


  We investigate the fundamental optimization question of minimizing a target
function $f$, whose gradients are expensive to compute or have limited
availability, given access to some auxiliary side function $h$ whose gradients
are cheap or more available. This formulation captures many settings of
practical relevance, such as i) re-using batches in SGD, ii) transfer learning,
iii) federated learning, iv) training with compressed models/dropout, Et
cetera. We propose two generic new algorithms that apply in all these settings;
we also prove that we can benefit from this framework under the Hessian
similarity assumption between the target and side information. A benefit is
obtained when this similarity measure is small; we also show a potential
benefit from stochasticity when the auxiliary noise is correlated with that of
the target function.


  Quantum Gravity has been so elusive because we have tried to approach it by
two paths which can never meet: standard quantum field theory and general
relativity. The gateway is covariance under the complexified Clifford algebra
of our space-time manifold M, and its spinor representations, which Sachs
dubbed the Einstein group, E. On the microscopic scale, quantum gravity appears
as the statistical mechanics of the null zig-zag rays of spinor fields in
imaginary time T. Our unified field/particle action L_g also contains new
couplings of gravitomagnetic fields to strong fields and weak potentials. These
predict new physical phenomena: Axial jets of nuclear decay products emitted
with left helicity along the axis of a massive, spinning body.


  We deal with the problem of outsourcing the debt for a big investment,
according two situations: either the firm outsources both the investment (and
the associated debt) and the exploitation to a private consortium, or the firm
supports the debt and the investment but outsources the exploitation. We prove
the existence of Stackelberg and Nash equilibria between the firm and the
private consortium, in both situations. We compare the benefits of these
contracts. We conclude with a study of what happens in case of incomplete
information, in the sense that the risk aversion coefficient of each partner
may be unknown by the other partner.


  In this paper, we propose some Chebyshev polynomials of the 1st-kind which
produce optimal bound for a polynomial dependent constant involved in the AMG
$V$-cycle error bound and do not require information about the spectrum of
matrices. We formulate a variant of a minimax problem already proposed in [J.
Lottes, Optimal polynomial smoothers for multigrid V-cycles, Numer. Lin. Alg.
with Appl., 30 (2023), p. e2518, https://doi.org/10.1002/nla.2518] and define
Chebyshev polynomial of the 1st-kind as acceleration for a weighted-Jacobi
smoother; we also describe efficient GPU kernels for the application of the
polynomial smoother and compare results with accelerators defined in [J.
Lottes, Optimal polynomial smoothers for multigrid V-cycles, Numer. Lin. Alg.
with Appl., 30 (2023), p. e2518, https://doi.org/10.1002/nla.2518] on usual
benchmarks at very large scales.


  $ \newcommand{\cardin}[1]{\left| {#1} \right|}%
\newcommand{\Graph}{\Mh{\mathsf{G}}}% \providecommand{\G}{\Graph}%
\renewcommand{\G}{\Graph}% \providecommand{\GA}{\Mh{H}}%
\renewcommand{\GA}{\Mh{H}}% \newcommand{\VV}{\Mh{\mathsf{V}}}%
\newcommand{\VX}[1]{\VV\pth{#1}}% \providecommand{\EE}{\Mh{\mathsf{E}}}%
\renewcommand{\EE}{\Mh{\mathsf{E}}}% \newcommand{\Re}{\mathbb{R}}
\newcommand{\reals}{\mathbb{R}} \newcommand{\SetX}{\mathsf{X}}
\newcommand{\rad}{r} \newcommand{\Mh}[1]{#1} \newcommand{\query}{q}
\newcommand{\eps}{\varepsilon} \newcommand{\VorX}[1]{\mathcal{V} \pth{#1}}
\newcommand{\Polygon}{\mathsf{P}} \newcommand{\IntRange}[1]{[ #1 ]}
\newcommand{\Space}{\overline{\mathsf{m}}}
\newcommand{\pth}[2][\!]{#1\left({#2}\right)}
\newcommand{\polylog}{\mathrm{polylog}} \newcommand{\N}{\mathbb N}
\newcommand{\Z}{\mathbb Z} \newcommand{\pt}{p} \newcommand{\distY}[2]{\left\|
{#1} - {#2} \right\|} \newcommand{\ptq}{q} \newcommand{\pts}{s}$ For an
undirected graph $\mathsf{G}=(\mathsf{V}, \mathsf{E})$, with $n$ vertices and
$m$ edges, the \emph{densest subgraph} problem, is to compute a subset $S
\subseteq \mathsf{V}$ which maximizes the ratio $|\mathsf{E}_S| / |S|$, where
$\mathsf{E}_S \subseteq \mathsf{E}$ is the set of all edges of $\mathsf{G}$
with endpoints in $S$. The densest subgraph problem is a well studied problem
in computer science. Existing exact and approximation algorithms for computing
the densest subgraph require $\Omega(m)$ time. We present near-linear time (in
$n$) approximation algorithms for the densest subgraph problem on
\emph{implicit} geometric intersection graphs, where the vertices are
explicitly given but not the edges. As a concrete example, we consider $n$
disks in the plane with arbitrary radii and present two different approximation
algorithms.


  Suppose $g=g_0+g_1$ is a finite-dimensional restricted Lie superalgebra over
an algebraically closed field $k$ of characteristic $p>2$. In this article, we
propose a conjecture for maximal dimensions of irreducible modules over the
universal enveloping algebra $U(g)$ of $g$, as a super generalization of the
celebrated first Kac-Weisfeiler conjecture. It is demonstrated that the
conjecture holds for all basic classical Lie superalgebras and all completely
solvable restricted Lie superalgebras. In this process, we investigate
irreducible representations of solvable Lie superalgebras.


  Several Bayesian estimation based heuristics have been developed to perform
quantum state tomography (QST). Their ability to quantify uncertainties using
region estimators and include a priori knowledge of the experimentalists makes
this family of methods an attractive choice for QST. However, specialized
techniques for pure states do not work well for mixed states and vice versa. In
this paper, we present an adaptive particle filter (PF) based QST protocol
which improves the scaling of fidelity compared to nonadaptive Bayesian schemes
for arbitrary multi-qubit states. This is due to the protocol's unabating
perseverance to find the states's diagonal bases and more systematic handling
of enduring problems in popular PF methods relating to the subjectivity of
informative priors and the invalidity of particles produced by resamplers.
Numerical examples and implementation on IBM quantum devices demonstrate
improved performance for arbitrary quantum states and the application readiness
of our proposed scheme.


  The conversion of brain activity into text using electroencephalography (EEG)
has gained significant traction in recent years. Many researchers are working
to develop new models to decode EEG signals into text form. Although this area
has shown promising developments, it still faces numerous challenges that
necessitate further improvement. It's important to outline this area's recent
developments and future research directions. In this review article, we
thoroughly summarize the progress in EEG-to-text conversion. Firstly, we talk
about how EEG-to-text technology has grown and what problems we still face.
Secondly, we discuss existing techniques used in this field. This includes
methods for collecting EEG data, the steps to process these signals, and the
development of systems capable of translating these signals into coherent text.
We conclude with potential future research directions, emphasizing the need for
enhanced accuracy, reduced system constraints, and the exploration of novel
applications across varied sectors. By addressing these aspects, this review
aims to contribute to developing more accessible and effective Brain-Computer
Interface (BCI) technology for a broader user base.


  We present an analysis of the formation and chemical evolution of stellar
haloes around (a) Milky Way Analogue (MWA) galaxies and (b) galaxy clusters in
the L-Galaxies 2020 semi-analytic model of galaxy evolution. Observed stellar
halo properties are better reproduced when assuming a gradual stripping model
for the removal of cold gas and stars from satellites, compared to an
instantaneous stripping model. The slope of the stellar mass -- metallicity
relation for MWA stellar haloes is in good agreement with that observed in the
local Universe. This extends the good agreement between L-Galaxies 2020 and
metallicity observations from the gas and stars inside galaxies to those
outside. Halo stars contribute on average only $\sim{}0.1$ per cent of the
total circumgalactic medium (CGM) enrichment by $z=0$ in MWAs, ejecting
predominantly carbon produced by AGB stars. Around a quarter of MWAs have a
single `significant progenitor' with a mean mass of
$\sim{}2.3\times{}10^{9}M_{\odot}$, similar to that measured for Gaia
Enceladus. For galaxy clusters, L-Galaxies 2020 shows good correspondence with
observations of stellar halo mass fractions, but slightly over-predicts stellar
masses. Assuming a Navarro-Frenk-White profile for the stellar halo mass
distribution provides the best agreement. On average, the intracluster stellar
component (ICS) is responsible for 5.4 per cent of the total intracluster
medium (ICM) iron enrichment, exceeding the contribution from the brightest
cluster galaxy (BCG) by $z=0$. We find that considering gradual stripping of
satellites and realistic radial profiles is crucial for accurately modelling
stellar halo formation on all scales in semi-analytic models.


  The Jodcast (www.jodcast.net) is a twice-monthly astronomy podcast from The
University of Manchester's Jodrell Bank Observatory. In this paper I give the
motivation and history of The Jodcast, as well as a description of The
Jodcast's content, operations, personnel, performance and aspirations.


  We introduce discrete-time linear control systems on connected Lie groups and
present an upper bound for the outer invariance entropy of admissible pairs
(K,Q). If the stable subgroup of the uncontrolled system is closed and K has
positive measure for a left invariant Haar measure, the upper bound coincides
with the outer invariance entropy.


  Applying the Clausius relation, $\delta Q=TdS$, to the apparent horizon of
FRW universe in brane world scenarios, we show that an explicit entropy
expression associated with the apparent horizon can be obtained. On the
apparent horizon, the relation, $dE=TdS +WdV$, also holds in the brane world
scenarios. We show these results in the RSII model, warped DGP model and the
more general case with a Gauss-Bonnet term in the bulk and an intrinsic
curvature term on the brane.


  It is shown that any graph with maximum degree $\Delta$ in which the average
degree of the induced subgraph on the set of all neighbors of any vertex
exceeds $\frac{6k^2}{6k^2 + 1}\Delta + k + 6$ is either $(\Delta -
k)$-colorable or contains a clique on more than $\Delta - 2k$ vertices. In the
$k=1$ case we improve the bound on the average degree to $\frac23\Delta + 4$
and the bound on the clique number to $\Delta-1$. As corollaries, we show that
every graph satisfies $\chi \leq \max\set{\omega, \Delta - 1, 4\alpha}$ and
every graph satisfies $\chi \leq \max\set{\omega, \Delta - 1, \ceil{\frac{15 +
\sqrt{48n + 73}}{4}}}$.


  In this paper, we analytically analyzed the impact of an error-prone channel
over all performance measures in a trafficsaturated IEEE 802.11 WLAN. We
calculated station's transmission probability by using the modified Markov
chain model of the backoff window size that considers the frame-error rates and
maximal allowable number of retransmission attempts. The frame error rate has a
significant impact over theoretical throughput, mean frame delay, and discard
probability. The peak throughput of a WLAN is insensitive of the maximal number
of retransmissions. Discard probabilities are insensitive to the station access
method, Basic or RTS/CTS.


  We elaborate on our earlier proposal connecting entanglement renormalization
and holographic duality in which we argued that a tensor network can be
reinterpreted as a kind of skeleton for an emergent holographic space. Here we
address the question of the large $N$ limit where on the holographic side the
gravity theory becomes classical and a non-fluctuating smooth spacetime
description emerges. We show how a number of features of holographic duality in
the large $N$ limit emerge naturally from entanglement renormalization,
including a classical spacetime generated by entanglement, a sparse spectrum of
operator dimensions, and phase transitions in mutual information. We also
address questions related to bulk locality below the AdS radius, holographic
duals of weakly coupled large $N$ theories, Fermi surfaces in holography, and
the holographic interpretation of branching MERA. Some of our considerations
are inspired by the idea of quantum expanders which are generalized quantum
transformations that add a definite amount of entropy to most states. Since we
identify entanglement with geometry, we thus argue that classical spacetime may
be built from quantum expanders (or something like them).


  In this note we study a class of one-dimensional Ising chain having a highly
degenerated set of ground-state configurations. The model consists of spin
chain having infinite-range pair interactions with a given structure. We show
that the set of ground-state configurations of such a model can be fully
characterized by means of symbolic dynamics. Particularly we found that the set
ground- state configurations defines what in symbolic dynamics is called sofic
shift space. Finally we prove that this system has a non-vanishing residual
entropy (the topological entropy of the shift space), which can be exactly
calculated.


  In Time-Sensitive Networking (TSN), it is important to formally prove per
flow latency and backlog bounds. To this end, recent works apply network
calculus and obtain latency bounds from service curves. The latency component
of such service curves is directly derived from upper bounds on the values of
the credit counters used by the Credit-Based Shaper (CBS), an essential
building-block of TSN. In this paper, we derive and formally prove credit upper
bounds for CBS, which improve on existing bounds.


  The exploration of petroleum reservoirs has a close relationship with the
identification of salt domes. To efficiently interpret salt-dome structures, in
this paper, we propose a method that tracks salt-dome boundaries through
seismic volumes using a tensor-based subspace learning algorithm. We build
texture tensors by classifying image patches acquired along the boundary
regions of seismic sections and contrast maps. With features extracted from the
subspaces of texture tensors, we can identify tracked points in neighboring
sections and label salt-dome boundaries by optimally connecting these points.
Experimental results show that the proposed method outperforms the
state-of-the-art salt-dome detection method by employing texture information
and tensor-based analysis.


  The Lasso is biased. Concave penalized least squares estimation (PLSE) takes
advantage of signal strength to reduce this bias, leading to sharper error
bounds in prediction, coefficient estimation and variable selection. For
prediction and estimation, the bias of the Lasso can be also reduced by taking
a smaller penalty level than what selection consistency requires, but such
smaller penalty level depends on the sparsity of the true coefficient vector.
The sorted L1 penalized estimation (Slope) was proposed for adaptation to such
smaller penalty levels. However, the advantages of concave PLSE and Slope do
not subsume each other. We propose sorted concave penalized estimation to
combine the advantages of concave and sorted penalizations. We prove that
sorted concave penalties adaptively choose the smaller penalty level and at the
same time benefits from signal strength, especially when a significant
proportion of signals are stronger than the corresponding adaptively selected
penalty levels. A local convex approximation, which extends the local linear
and quadratic approximations to sorted concave penalties, is developed to
facilitate the computation of sorted concave PLSE and proven to possess desired
prediction and estimation error bounds. We carry out a unified treatment of
penalty functions in a general optimization setting, including the penalty
levels and concavity of the above mentioned sorted penalties and mixed
penalties motivated by Bayesian considerations. Our analysis of prediction and
estimation errors requires the restricted eigenvalue condition on the design,
not beyond, and provides selection consistency under a required minimum signal
strength condition in addition. Thus, our results also sharpens existing
results on concave PLSE by removing the upper sparse eigenvalue component of
the sparse Riesz condition.


  The Kirchhoff-Plateau problem concerns the equilibrium shapes of a system in
which a flexible filament in the form of a closed loop is spanned by a liquid
film, with the filament being modeled as a Kirchhoff rod and the action of the
spanning surface being solely due to surface tension. We establish the
existence of an equilibrium shape that minimizes the total energy of the system
under the physical constraint of non-interpenetration of matter, but allowing
for points on the surface of the bounding loop to come into contact. In our
treatment, the bounding loop retains a finite cross-sectional thickness and a
nonvanishing volume, while the liquid film is represented by a set with finite
two-dimensional Hausdorff measure. Moreover, the region where the liquid film
touches the surface of the bounding loop is not prescribed a priori. Our
mathematical results substantiate the physical relevance of the chosen model.
Indeed, no matter how strong is the competition between surface tension and the
elastic response of the filament, the system is always able to adjust to
achieve a configuration that complies with the physical constraints encountered
in experiments.


  We give sharp upper bounds on the maximal injectivity radius of finite-area
hyperbolic surfaces and use them, for each g at least 2, to identify a constant
r_{g-1,2} with the property that the set of closed genus-g hyperbolic surfaces
with maximal injectivity radius at least r is compact if and only if r >
r_{g-1,2}. The main tool is a version of the "centered dual complex" that we
introduced earlier, a coarsening of the Delaunay complex of a locally finite
set. In particular, we bound the area of a compact centered dual two-cell below
given lower bounds on its side lengths.


  We are concerned with a one dimensional flow of a compressible fluid which
may be seen as a simplification of the flow of fluid in a long thin pipe. We
assume that the pipe is on one side ended by a spring. The other side of the
pipe is let open -- there we assume either inflow or outflow boundary
conditions. Such situation can be understood as a toy model for human lungs. We
tackle the question of uniqueness and existence of a strong solution for a
system modelling the above process, special emphasis is laid upon the estimate
of the maximal time of existence.


  Two solar type II radio bursts, separated by ~24 hours in time, are examined
together. Both events are associated with coronal mass ejections (CMEs)
erupting from the same active region (NOAA 11176) beneath a well-observed
helmet streamer. We find that the type II emissions in both events ended once
the CME/shock fronts passed the white-light streamer tip, which is presumably
the magnetic cusp of the streamer. This leads us to conjecture that the closed
magnetic arcades of the streamer may play a role in electron acceleration and
type II excitation at coronal shocks. To examine such a conjecture, we conduct
a test-particle simulation for electron dynamics within a large-scale
partially-closed streamer magnetic configuration swept by a coronal shock. We
find that the closed field lines play the role of an electron trap, via which
the electrons are sent back to the shock front for multiple times, and
therefore accelerated to high energies by the shock. Electrons with an initial
energy of 300eV can be accelerated to tens of keV concentrating at the loop
apex close to the shock front with a counter-streaming distribution at most
locations. These electrons are energetic enough to excite Langmuir waves and
radio bursts. Considering the fact that most solar eruptions originate from
closed field regions, we suggest that the scenario may be important to the
generation of more metric type IIs. This study also provides an explanation to
the general ending frequencies of metric type IIs at or above 20-30 MHz and the
disconnection issue between metric and interplanetary type IIs.


  We investigate the shear viscosity of leptons in a strongly coupled quark
gluon plasma (QGP). We find that the shear viscosity due to the lepton-quark
scattering is inversely proportional to the ratio of electric conductivity of
the QGP to temperature up to the leading logarithmic order of the
electromagnetic coupling. The finding implies that the thermal leptons form a
more viscous fluid than the quarks by a large ratio. Using the known result for
the electrical conductivity of strongly coupled plasmas obtained from
gauge/gravity duality, we find that the lepton shear viscosity is suppressed
compared with the one from lepton-lepton scattering. Consistently, we find an
enhancement of the energy loss of hard leptons in a strongly coupled scenario
compared with that in a weakly coupled plasma.


  In this paper we propose a new time-varying econometric model, called
Time-Varying Poisson AutoRegressive with eXogenous covariates (TV-PARX), suited
to model and forecast time series of counts. {We show that the score-driven
framework is particularly suitable to recover the evolution of time-varying
parameters and provides the required flexibility to model and forecast time
series of counts characterized by convoluted nonlinear dynamics and structural
breaks.} We study the asymptotic properties of the TV-PARX model and prove
that, under mild conditions, maximum likelihood estimation (MLE) yields
strongly consistent and asymptotically normal parameter estimates.
Finite-sample performance and forecasting accuracy are evaluated through Monte
Carlo simulations. The empirical usefulness of the time-varying specification
of the proposed TV-PARX model is shown by analyzing the number of new daily
COVID-19 infections in Italy and the number of corporate defaults in the US.


  Which ads should we display in sponsored search in order to maximize our
revenue? How should we dynamically rank information sources to maximize value
of information? These applications exhibit strong diminishing returns:
Selection of redundant ads and information sources decreases their marginal
utility. We show that these and other problems can be formalized as repeatedly
selecting an assignment of items to positions to maximize a sequence of
monotone submodular functions that arrive one by one. We present an efficient
algorithm for this general problem and analyze it in the no-regret model. Our
algorithm possesses strong theoretical guarantees, such as a performance ratio
that converges to the optimal constant of 1-1/e. We empirically evaluate our
algorithm on two real-world online optimization problems on the web: ad
allocation with submodular utilities, and dynamically ranking blogs to detect
information cascades.


  Given an inclusion $A\to L$ of Lie algebroids sharing the same base manifold
$M$, i.e. a Lie pair, we prove that the space $\Gamma(\Lambda^\bullet
A^\vee)\otimes_{C^\infty(M)} \frac{U(L)}{U(L)\cdot\Gamma(A)}$ admits a natural
$A_\infty$ algebra structure. This $A_\infty$ algebra structure is inherited,
by homotopy transfer, from the universal enveloping algebra of the differential
graded Lie algebroid arising as the pullback of the Lie algebroid $L\to M$
through the canonical surjective submersion $A[1]\to M$.


  X-ray grating interferometry is an excellent technique for X-ray phase
contrast imaging and X-ray wavefront sensing with applications in materials
science, biology and medical diagnosis. Among other requirements, the method
depends on the availability of highly X-ray absorbing metallic gratings. Here,
we report on the fabrication and characterization of high aspect ratio iridium
gratings with a period of one micrometer and a depth of 30 micrometer combining
deep reactive ion etching of silicon and atomic layer deposition of iridium.
The implementation of such structures can greatly enhance the sensitivity of
grating-based X-ray phase contrast imaging and thus, expand further its broad
range of applications.


  A restrictive constraint for any quasi-elastic process was obtained in the
previously inaccessible energy range dE~10^(-12)-3x10^(-10) eV for reflections
of ultracold neutrons from surfaces in the experiement on neutron quantum
states in the earth's gravitational field. This could be useful for precision
neutron spectrometry experiments and for the verification of extensions of
quantum mechanics.


  Using the model of words, we give bijective proofs of Gould-Mohanty's and
Raney-Mohanty's identities, which are respectively multivariable
generalizations of Gould's identity $$\sum_{k=0}^{n}{x-kz\choose k}{y+kz\choose
n-k}= \sum_{k=0}^{n}{x+\epsilon-kz\choose k}{y-\epsilon+kz\choose n-k} $$ and
Rothe's identity $$ \sum_{k=0}^{n}\frac{x}{x-kz}{x-kz\choose k}{y+kz\choose
n-k}= {x+y\choose n}. $$


  Consider the $n \times n$ reverse circulant $RC_n(t)$ and symmetric circulant
$SC_n(t)$ matrices with independent Brownian motion entries. We discuss the
process convergence of the time dependent fluctuations of linear eigenvalue
statistics of these matrices as $n \tends \infty$, when the test functions of
the statistics are polynomials. The proofs are mainly combinatorial, based on
the trace formula, method of moments and some results on process convergence.


  Straight cylindrical stethoscopes serve as an important alternative to
conventional stethoscopes whose application in the treatment of infectious
diseases might be limited by the use of protective clothing. Yet their
miniaturization is challenging due to the low-frequency of bioacoustics signal.
Here, we design and experimentally implement a meta-stethoscope with
subwavelength size, simple fabrication, easy assembly yet high sensitivity,
which simply comprises multiple round perforated plate units and a cylindrical
shell. We elucidate our proposed mechanism by analytically deriving the
frequency response equation, which proves that the equivalent acoustic
propagation path is substantially increased by the high-index metamaterial,
enabling downscaling of the meta-stethoscope to subwavelength footprint. The
acoustic performance of meta-stethoscope is experimentally characterized by
monitoring the cardiac auscultation on clothed human body. The simulated and
measured results agree well, with both showing the expected enhancement of
sensitivity of our proposed meta-stethoscope (~ 10 dB) within the predicted
working frequency range from 80 to 130 Hz despite its compactness and
simplicity. Our designed portable, detachable yet effective meta-stethoscope
opens a route to metamaterial-enabled stethoscope paradigm, with potential
applications in diverse scenarios such as medical diagnosis and acoustic
sensing.


  We provide sufficient conditions for a mapping between two Banach spaces to
be a diffeomorphism using the approach of an auxiliary functional and also by
the aid of a duality mapping corresponding to a normalization function. We
simplify and generalize our previous results. Applications to algebraic
equations and to integro-differential systems are also given.


  Berry-Esseen-type bounds are developed in the multidimensional local limit
theorem in terms of the Lyapunov coefficients and maxima of involved densities.


  A sequence of exact relations is found which connect one- and many-particle
time-dependent distribution functions of low-density gas with their derivatives
in respect to mean density. It is shown that, at least in the context of
spatially non-uniform gas evolutions, these relations forbid the "molecular
chaos propagation" and imply inapplicability of the Boltzmann kinetic equation
even under the Boltzmann-Grad limit and regardless of degree of the
non-uniformity.


  The Kolmogorov complexity of a physical state is the minimal physical
resources required to reproduce that state. We define a second quantized
quantum Turing machine and use it to define second quantized Kolmogorov
complexity. There are two advantages to our approach - our measure of second
quantized Kolmogorov complexity is closer to physical reality and unlike other
quantum Kolmogorov complexities it is continuous. We give examples where second
quantized and quantum Kolmogorov complexity differ.


  We investigate thermal and isothermal symmetric liquid-vapor separations via
a FFT-Thermal Lattice Boltzmann (FFT-TLB) model. Structure factor, domain size
and Minkowski functionals are employed to characterize the density and velocity
fields as well as to understand the configurations and the kinetic processes.
Compared with the isothermal phase separation, the freedom in temperature
prolongs the Spinodal Decomposition (SD) stage and induces different
rheological and morphological behaviors in the thermal system. After the
transient procedure, both the thermal and isothermal separations show power-law
scalings in domain growth; while the exponent for thermal system is lower than
that for isothermal system. With respect to the density of field, the
isothermal system presents more likely bicontinuous configurations with
narrower interfaces, while the thermal system presents more likely
configurations with scattered bubbles. Heat creation, conduction and lower
interfacial stresses are main reasons for the differences in thermal system.
Different from the case with isothermal phase separation, the release of latent
heat causes the changing of local temperature which results in new local
mechanical balance. When the Prandtl number becomes smaller, the system
approaches thermodynamical equilibrium more quickly. The increasing of mean
temperature makes lower the interfacial stress in the following way:
$\sigma=\sigma_{0}[(T_{c}-T)/(T_{c}-T_{0})]^{3/2}$, where $T_{c}$ is the
critical temperature and $\sigma_{0}$ is the interfacial stress at a reference
temperature $T_{0}$, which is the main reason for lower growth exponent in
thermal case.


  Erasing quantum-mechanical distinguishability is of fundamental interest and
also of practical importance, particularly in subject areas related to quantum
information processing. We demonstrate a method applicable to optical systems
in which single-mode filtering is used with only linear optical instruments to
achieve quantum indistinguishability. Through "heralded" Hong-Ou-Mandel
interference experiments we measure and quantify the improvement of
indistinguishability between single photons generated via spontaneous four-wave
mixing in optical fibers. The experimental results are in excellent agreement
with predictions of a quantum-multimode theory we develop for such systems,
without the need for any fitting parameter.


  We provide an explicit twistorial construction of quaternion-Kahler manifolds
obtained by deformation of c-map spaces and carrying an isometric action of the
modular group SL(2,Z). The deformation is not assumed to preserve any
continuous isometry and therefore this construction presents a general
framework for describing NS5-brane instanton effects in string
compactifications with N=2 supersymmetry. In this context the modular invariant
parametrization of twistor lines found in this work yields the complete
non-perturbative mirror map between type IIA and type IIB physical fields.


  The high repair cost of (n,k) Maximum Distance Separable (MDS) erasure codes
has recently motivated a new class of codes, called Regenerating Codes, that
optimally trade off storage cost for repair bandwidth. On one end of this
spectrum of Regenerating Codes are Minimum Storage Regenerating (MSR) codes
that can match the minimum storage cost of MDS codes while also significantly
reducing repair bandwidth. In this paper, we describe Exact-MSR codes which
allow for any failed nodes (whether they are systematic or parity nodes) to be
regenerated exactly rather than only functionally or information-equivalently.
We show that Exact-MSR codes come with no loss of optimality with respect to
random-network-coding based MSR codes (matching the cutset-based lower bound on
repair bandwidth) for the cases of: (a) k/n <= 1/2; and (b) k <= 3. Our
constructive approach is based on interference alignment techniques, and,
unlike the previous class of random-network-coding based approaches, we provide
explicit and deterministic coding schemes that require a finite-field size of
at most 2(n-k).


  This is a survey article for "Handbook of Linear Algebra", 2nd ed., Chapman &
Hall/CRC, 2014. An informal introduction to representations of quivers and
finite dimensional algebras from a linear algebraist's point of view is given.
The notion of quiver representations is extended to representations of mixed
graphs, which permits one to study systems of linear mappings and bilinear or
sesquilinear forms. The problem of classifying such systems is reduced to the
problem of classifying systems of linear mappings.


  This paper describes a method to determine the complex permittivity of a thin
dielectric film from finite element analysis and microstrip line measurements.
Two transmission line equivalent circuit models were used for the cases of an
air-filled line and a lossless line, whose distributed elements can be
calculated from full wave finite element simulations. With these calculated
distributed elements and microstrip line measurements, the complex permittivity
was extracted. The technique utilizes a simple way to separate the dielectric
loss from the measured total loss and the complex permittivity was extracted
using the measured propagation constant. A rational dielectric model was
employed to fit the extracted complex permittivity, which ensures causality of
the final solution. The best fitting results obtained through this procedure
are considered as the final permittivity results, which have shown excellent
match to the data sheet values. Moreover, simulations using the fitted
permittivity exhibit good agreement with the experimental propagation constant
data of microstrip lines up to 60 GHz. The proposed method was demonstrated on
polyimide, and it can be applied to other thin film materials.


  Modulational instability is a phenomenon that reveals itself as the
exponential growth of weak perturbations in the presence of an intense pump
beam propagating in a nonlinear medium. It plays a key role in such nonlinear
optical processes as supercontinuum generation, light filamentation, and rogue
waves. However, practical realization of these phenomena in the majority of
available nonlinear media still relies on high-intensity optical beams. Here,
we analytically and numerically show the possibility of necklace beam
generation originating from low-intensity spatial modulational instability of
vortex beams in engineered soft-matter nonlinear media.


  Superconducting spintronics focuses on the interplay between
superconductivity and magnetism and has sparked significant interest in
nonunitary superconductors as a platform for novel magneto-superconducting
phenomena. However, a direct test for nonunitary superconductors is currently
absent, and their identification is challenging. In this paper, we demonstrate
that spin current driven by the thermal gradient sensitively probes the nature
of the condensate in nonunitary superconductors. We should note that the spin
polarization of the condensate in the momentum space induces the spin-Seebeck
effect, and the spin-dependent chirality (spin-chirality) of the condensate
induces the spin-Nernst effect in nonunitary superconductors. Notably, the
nonvanishing spin-Seebeck effect provides a smoking gun evidence of nonunitary
superconductivity in materials because it reflects the spin polarization of the
Cooper pairs in the momentum space, irrespective of whether the net pair spin
magnetization vanishes. Our results position the spin caloritronics phenomena
as a definitive probe of nonunitary superconductors.


  This note presents a simple, universal closed form for the powers of any
square matrix. A diligent search of the internet gave no indication that the
form is known.


  We use new and extant literature spectroscopy to address abundances and
membership for UMa moving group stars. We first compare the UMa, Coma, and
Hyades H-R diagrams via a homogeneous set of isochrones, and find that these
three aggregates are essentially coeval. Our spectroscopy of cool UMa dwarfs
reveals striking abundance anomalies--trends with Teff, ionization state, and
excitation potential--like those recently seen in young cool M34, Pleaides, and
Hyades dwarfs. In particular, the trend of rising 7774 Ang-based OI abundance
with declining Teff is markedly subdued in UMa compared to the Pleiades,
suggesting a dependence on age or metallicity. Despite disparate sources of Li
data,our homogeneous analysis indicates that UMa members evince remarkably
small scatter in the Li-Teff plane for Teff>5200 K. Significant star-to-star
scatter suggested by previous studies is seen for cooler stars. Comparison with
the consistently determined Hyades Li-Teff trend reveals differences
qualitatively consistent with this cluster's larger [Fe/H] (and perhaps
slightly larger age). However, quantitative comparison with standard stellar
models indicates the differences are smaller than expected, suggesting the
action of a fourth parameter beyond age, mass, and [Fe/H] controlling Li
depletion.


  By analogue of [1,2] we define a cubic stochastic process and study evolution
(dynamics) of a system $E$ which contains at least three elements.


  Benchmarking studies in computational chemistry use reference datasets to
assess the accuracy of a method through error statistics. The commonly used
error statistics, such as the mean signed and mean unsigned errors, do not
inform end-users on the expected amplitude of prediction errors attached to
these methods. We show that, the distributions of model errors being neither
normal nor zero-centered, these error statistics cannot be used to infer
prediction error probabilities. To overcome this limitation, we advocate for
the use of more informative statistics, based on the empirical cumulative
distribution function of unsigned errors, namely (1) the probability for a new
calculation to have an absolute error below a chosen threshold, and (2) the
maximal amplitude of errors one can expect with a chosen high confidence level.
Those statistics are also shown to be well suited for benchmarking and ranking
studies. Moreover, the standard error on all benchmarking statistics depends on
the size of the reference dataset. Systematic publication of these standard
errors would be very helpful to assess the statistical reliability of
benchmarking conclusions.


  Truncating the Fourier transform averaged by means of a generalized Hausdorff
operator, we approximate the adjoint to that Hausdorff operator of the given
function. We find the formulas for the rate of approximation in various metrics
in terms of the parameter of truncation and the components of the Hausdorff
operator. Explicit rates of approximation and comparison with approximate
identities are given in the case of Lipschitz $\alpha$ continuous functions.


  The coincidence problem of late cosmic acceleration is a serious riddle in
connection with our understanding of the evolution of the Universe. In this
paper we show that an interaction between the dark energy component (either
phantom or quintessence) and dark matter can alleviate it. In this scenario the
baryon component is independently conserved. This generalizes a previous study
[S. del Campo, R. Herrera, and D. Pavon, Phys. Rev. D 71, 123529 (2005)] in
which neither baryons nor phantom energy were considered.


  We investigate the Fermi acceleration of charged particles in 2D MHD
anti-parallel plasmoid reconnection, finding a drastic enhancement in
energization rate $\dot{\varepsilon}$ over a standard Fermi model of
$\dot{\varepsilon} \sim \varepsilon$. The shrinking particle orbit width around
a magnetic island due to $\vec{E}\times\vec{B}$ drift produces a
$\dot{\varepsilon}_\parallel \sim \varepsilon_\parallel^{1+1/2\chi}$ power law
with $\chi \sim 0.75$. The increase in the maximum possible energy gain of a
particle within a plasmoid due to the enhanced efficiency increases with the
plasmoid size, and is by multiple factors of 10 in the case of solar flares and
much more for larger plasmas. Including effects of the non-constant
$\vec{E}\times\vec{B}$ drift rates leads to further variation of power law
indices from $\gtrsim 2$ to $\lesssim 1$, decreasing with plasmoid size at the
time of injection.


  An appropriate and safe behavior for exiting a facility is key to reducing
injuries and increasing survival when facing an emergency evacuation in a
building. Knowledge on the best evacuation practice is commonly delivered by
traditional training approaches such as videos, posters, or evacuation drills,
but they may become ineffective in terms of knowledge acquisition and
retention. Serious games (SGs) are an innovative approach devoted to training
and educating people in a gaming environment. Recently, increasing attention
has been paid to immersive virtual reality (IVR)-based SGs for evacuation
knowledge delivery and behavior assessment because they are highly engaging and
promote greater cognitive learning.
  This paper aims to understand the development and implementation of IVR SGs
in the context of building evacuation training and research, applied to various
indoor emergencies such as fire and earthquake. Thus, a conceptual framework
for effective design and implementation through the systematic literature
review method was developed. As a result, this framework integrates critical
aspects and provides connections between them, including pedagogical and
behavioral impacts, gaming environment development, and outcome and
participation experience measures.


  Although quantum field theory allows local negative energy densities and
fluxes, it also places severe restrictions upon the magnitude and extent of the
negative energy. The restrictions take the form of quantum inequalities. These
inequalities imply that a pulse of negative energy must not only be followed by
a compensating pulse of positive energy, but that the temporal separation
between the pulses is inversely proportional to their amplitude. In an earlier
paper we conjectured that there is a further constraint upon a negative and
positive energy delta-function pulse pair. This conjecture (the quantum
interest conjecture) states that a positive energy pulse must overcompensate
the negative energy pulse by an amount which is a monotonically increasing
function of the pulse separation. In the present paper we prove the conjecture
for massless quantized scalar fields in two and four-dimensional flat
spacetime, and show that it is implied by the quantum inequalities.


  We consider the simplified model of strategic allocation of trajectories in
the airspace presented in a previous publication. Two types of companies,
characterized by different cost functions, compete for allocation of
trajectories in the airspace. We study how the equilibrium state of the model
depends on the traffic demand and number of airports. We show that in a mixed
population environment the equilibrium solution is not the optimal at the
global level, but rather than it tends to have a larger fraction of companies
who prefer to delay the departure time rather taking a longer routes. Finally
we study the evolutionary dynamics investigating the fluctuations of airline
types around the equilibrium and the speed of convergence toward it in finite
populations. We find that the equilibrium point is shifted by the presence of
noise and is reached more slowly.


  Gonzalez Cazares and Ivanovs (2021) suggested a new method for "recovering"
the Brownian motion component from the trajectory of a Levy process that
required sampling from an independent Brownian motion process. We show that
such a procedure works equally well without any additional source of randomness
if one uses normal quantiles instead of the ordered increments of the auxiliary
Brownian motion process.


  We study the magnetic-field-induced spin-density-wave (FISDW) phases in TMTSF
organic conductors in the framework of the quantized nesting model. In
agreement with recent suggestions, we find that the SDW wave-vector ${\bf Q}$
deviates from its quantized value near the transition temperature $T_c$ for all
phases with quantum numbers $N>0$. Deviations from quantization are more
pronounced at low pressure and higher $N$ and may lead to a suppression of the
first-order transitions $N+1\to N$ for $N\ge 5$. Below a critical pressure, we
find that the N=0 phase invades the entire phase diagram in accordance with
earlier experiments. We also show that at T=0, the quantization of ${\bf Q}$
and hence the Hall conductance is always exact. Our results suggest a novel
phase transition/crossover at intermediate temperatures between phases with
quantized and non-quantized ${\bf Q}$.


  We use Deep Convolutional Neural Networks (DCNNs) for image segmentation
problems. DCNNs can well extract the features from natural images. However, the
classification functions in the existing network architecture of CNNs are
simple and lack capabilities to handle important spatial information in a way
that have been done for many well-known traditional variational models. Prior
such as spatial regularity, volume prior and object shapes cannot be well
handled by existing DCNNs. We propose a novel Soft Threshold Dynamics (STD)
framework which can easily integrate many spatial priors of the classical
variational models into the DCNNs for image segmentation. The novelty of our
method is to interpret the softmax activation function as a dual variable in a
variational problem, and thus many spatial priors can be imposed in the dual
space. From this viewpoint, we can build a STD based framework which can enable
the outputs of DCNNs to have many special priors such as spatial regularity,
volume constraints and star-shape priori. The proposed method is a general
mathematical framework and it can be applied to any semantic segmentation
DCNNs. To show the efficiency and accuracy of our method, we applied it to the
popular DeepLabV3+ image segmentation network, and the experiments results show
that our method can work efficiently on data-driven image segmentation DCNNs.


  In this paper we obtain a new sufficient condition for the existence of
directed cycles of length 4 in oriented bipartite graphs. As a corollary, a
conjecture of H. Li is confirmed. As an application, a sufficient condition for
the existence of rainbow cycles of length 4 in bipartite edge-colored graphs is
obtained.


  We report specific heat measurements on the Fe-based superconductor
BaFe2(As0.7P0.3)2, a material on which previous penetration depth, NMR, and
thermal conductivity measurements have observed a high density of low-energy
excitations, which have been interpreted in terms of order parameter nodes.
Within the resolution of our measurements, the low temperature limiting C/T is
found to be linear in field, i.e. we find no evidence for a Volovik effect
associated with nodal quasiparticles in either the clean or dirty limit. We
discuss possible reasons for this apparent contradiction.


  The quest for new sources of the simultaneous violation of $C$ and $CP$
symmetry was popular in the 1960s and has since been mostly neglected for more
than half a century. In this work we revisit fundamental quark-level operators
that break $C$ and $CP$ up to and including mass dimension 8 for
flavor-conserving transitions, relying on the complete operator sets of the
so-called Standard Model effective field theory and the low-energy effective
field theory. With the formalism of chiral perturbation theory, we match these
quark operators to light-meson physics, derive $C$- and $CP$-odd Lagrangians
for several processes in the $\eta$, $\eta'$, and pion sectors, and
furthermore, as a proof of principle, give estimates for the respective
observables in explicit dependence of the underlying high-energy scale for new
physics.


  The cutting plane approach to optimal matchings has been discussed by several
authors over the past decades (e.g., Padberg and Rao '82, Grotschel and Holland
'85, Lovasz and Plummer '86, Trick '87, Fischetti and Lodi '07) and its
convergence has been an open question. We give a cutting plane algorithm that
converges in polynomial-time using only Edmonds' blossom inequalities; it
maintains half-integral intermediate LP solutions supported by a disjoint union
of odd cycles and edges. Our main insight is a method to retain only a subset
of the previously added cutting planes based on their dual values. This allows
us to quickly find violated blossom inequalities and argue convergence by
tracking the number of odd cycles in the support of intermediate solutions.


  We construct the general static solution to the supergravity action
containing gravity, the dilaton and a set of antisymmetric forms describing the
intersecting branes delocalized in the relative transverse dimensions. The
solution is obtained by reducing the system to a set of separate Liouville
equations (the intersection rules implying the separability); it contains the
maximal number of free parameters corresponding to the rank of the differential
equations. Imposing the requirement of the absence of naked singularities, we
show that the general configurations are restricted to two and only two
classes: the usual asymptotically flat intersecting branes, and the
intersecting branes some of which are asymptotically flat and some approach the
linear dilaton background at infinity. In both cases the configurations are
black. These are supposed to be relevant for the description of the thermal
phase of the QFT's in the corresponding Domain-Wall/QFT duality.


  The increasing digitization and interconnection of legacy Industrial Control
Systems (ICSs) open new vulnerability surfaces, exposing such systems to
malicious attackers. Furthermore, since ICSs are often employed in critical
infrastructures (e.g., nuclear plants) and manufacturing companies (e.g.,
chemical industries), attacks can lead to devastating physical damages. In
dealing with this security requirement, the research community focuses on
developing new security mechanisms such as Intrusion Detection Systems (IDSs),
facilitated by leveraging modern machine learning techniques. However, these
algorithms require a testing platform and a considerable amount of data to be
trained and tested accurately. To satisfy this prerequisite, Academia,
Industry, and Government are increasingly proposing testbed (i.e., scaled-down
versions of ICSs or simulations) to test the performances of the IDSs.
Furthermore, to enable researchers to cross-validate security systems (e.g.,
security-by-design concepts or anomaly detectors), several datasets have been
collected from testbeds and shared with the community. In this paper, we
provide a deep and comprehensive overview of ICSs, presenting the architecture
design, the employed devices, and the security protocols implemented. We then
collect, compare, and describe testbeds and datasets in the literature,
highlighting key challenges and design guidelines to keep in mind in the design
phases. Furthermore, we enrich our work by reporting the best performing IDS
algorithms tested on every dataset to create a baseline in state of the art for
this field. Finally, driven by knowledge accumulated during this survey's
development, we report advice and good practices on the development, the
choice, and the utilization of testbeds, datasets, and IDSs.


  Motion Sickness (MS) is an issue of most transportation systems. Several
countermeasures for such problem in cars are proposed in the literature, but
most of them are qualitative, behavioural or involving complex chassis systems.
With the growing interest in self-employed vehicles, the issue of MS may be so
important that it undermines their benefits in terms of increased productivity;
not addressing such issue may limit the users' acceptance reducing the safety
and environmental impact of autonomous vehicles. The present study presents a
novel approach to combine minimal travel time with minimal Motion Sickness
Incidence (MSI) by optimising the speed profile for a given path. Through
simulation, a simple vehicle model is used to compare several strategies
evaluating which of them are effective and which not. The optimisation task is
formulated as a Non-linear Model Predictive Control (NMPC) and a series of
optimisation routines are computed along the path; the strategies are
implemented within the cost function of the NMPC problem evaluating their
performance and if using a numerical MS model is mandatory to get a significant
reduction of the MSI. The results show that not all the cost functions are
effective, but it is possible to reduce MS without modelling its dynamics;
however, the strategy taking into account the current MSI using a MS model
outperforms the other cost functions in term of efficacy and efficiency. Such a
quantitative approach can be used during motion planning in autonomous
vehicles, to suggest an optimal speed in human-driven vehicles and to improve
the comfort for bus-line services or even trains.


  We prove that in every bipartite Cayley graph of every non-amenable group,
there is a perfect matching that is obtained as a factor of independent uniform
random variables. We also discuss expansion properties of factors and improve
the Hoffman spectral bound on independence number of finite graphs.


  Synthesising a text-to-image model of high-quality images by guiding the
generative model through the Text description is an innovative and challenging
task. In recent years, AttnGAN based on the Attention mechanism to guide GAN
training has been proposed, SD-GAN, which adopts a self-distillation technique
to improve the performance of the generator and the quality of image
generation, and Stack-GAN++, which gradually improves the details and quality
of the image by stacking multiple generators and discriminators. However, this
series of improvements to GAN all have redundancy to a certain extent, which
affects the generation performance and complexity to a certain extent. We use
the popular simple and effective idea (1) to remove redundancy structure and
improve the backbone network of AttnGAN. (2) to integrate and reconstruct
multiple losses of DAMSM. Our improvements have significantly improved the
model size and training efficiency while ensuring that the model's performance
is unchanged and finally proposed our SEAttnGAN. Code is avalilable at
https://github.com/jmyissb/SEAttnGAN.


  We present recent results on our development of single photon detectors,
including: gated and free-running InGaAs/InP avalanche photodiodes; hybrid
detection systems based on sum-frequency generation and Si APDs; and SSPDs
(superconducting single photon detectors), for telecom wavelengths; as well as
SiPM (Silicon photomultiplier) detectors operating in the visible regime.


  A unified first law of black-hole dynamics and relativistic thermodynamics is
derived in spherically symmetric general relativity. This equation expresses
the gradient of the active gravitational energy E according to the Einstein
equation, divided into energy-supply and work terms. Projecting the equation
along the flow of thermodynamic matter and along the trapping horizon of a
blackhole yield, respectively, first laws of relativistic thermodynamics and
black-hole dynamics. In the black-hole case, this first law has the same form
as the first law of black-hole statics, with static perturbations replaced by
the derivative along the horizon. There is the expected term involving the area
and surface gravity, where the dynamic surface gravity is defined as in the
static case but using the Kodama vector and trapping horizon. This surface
gravity vanishes for degenerate trapping horizons and satisfies certain
expected inequalities involving the area and energy. In the thermodynamic case,
the quasi-local first law has the same form, apart from a relativistic factor,
as the classical first law of thermodynamics, involving heat supply and
hydrodynamic work, but with E replacing the internal energy. Expanding E in the
Newtonian limit shows that it incorporates the Newtonian mass, kinetic energy,
gravitational potential energy and thermal energy. There is also a weak type of
unified zeroth law: a Gibbs-like definition of thermal equilibrium requires
constancy of an effective temperature, generalising the Tolman condition and
the particular case of Hawking radiation, while gravithermal equilibrium
further requires constancy of surface gravity. Finally, it is suggested that
the energy operator of spherically symmetric quantum gravity is determined by
the Kodama vector, which encodes a dynamic time related to E.


  This article is devoted to the investigation of limit theorems for mixed
max-sum processes with renewal type stopping indexes. Limit theorems of weak
convergence type are obtained as well as functional limit theorems.