  In this paper, we define normal soft int-groups and derive their some basic
properties. We also investigate some relations on {\alpha}-inclusion, soft
product and normal soft int-groups. Then we define normalizer, quotient group
and give some theorems concerning these concepts.


  Purcell-enhanced emission from a coupled emitter-cavity system is a
fundamental manifestation of cavity quantum electrodynamics. Starting from a
theoretical description we derive a scheme for photon emission from an emitter
coupled to a birefringent cavity that exceeds hitherto anticipated limitations.
Based on a recent study and experimental investigation of the intra-cavity
coupling of orthogonal polarisation modes in birefringent cavities, we now
decouple the emitter and the photon prior to emission from the cavity mode.
Effectively, this is "hiding" the emitter from the photon in the cavity to
suppress re-excitation, increasing the overall emission through the cavity
mirrors. In doing so we show that tailored cavity birefringence can offer
significant advantages and that these are practically achievable within the
bounds of present-day technology. It is found that birefringence can mitigate
the tradeoff between stronger emitter-cavity coupling and efficient photon
extraction. This allows for longer cavities to be constructed without a loss of
performance -- a significant result for applications where dielectric mirrors
interfere with any trapping fields confining the emitter. We then generalise
our model to consider a variety of equivalent schemes. For instance, detuning a
pair of ground states in a three-level emitter coupled to a cavity in a
Lambda-system is shown to provide the same enhancement, and it can be combined
with a birefringent cavity to further increase performance. Additionally, it is
found that when directly connecting multiple ground states of the emitter to
form a chain of coupled states, the extraction efficiency approaches its
fundamental upper limit. The principles proposed in this work can be applied in
multiple ways to any emitter-cavity system, paving the way to surpassing the
traditional limits of such systems with technologies that exist today.


  We investigate the nonlocal optical conductivity of Fermi surface nesting
materials which support charge density waves or spin density waves. The
nonlocal optical conductivity contains information of correlations in electron
fluids which could not be accessed by standard optical probes. Half metal
emerges from doping a charge density wave and similarly spin-valley half metal
emerges from doping a spin density wave. Based on the parabolic band
approximation, we find the Drude peak is shifted to higher frequency and splits
into two peaks in the nonlocal optical conductivity. We attribute this to the
two Fermi velocities in the half-metal or spin-valley half metal states.


  There is a significant ongoing effort in realizing quantum annealing with
different physical platforms. The challenge is to achieve a fully programmable
quantum device featuring coherent adiabatic quantum dynamics. Here we show that
combining the well-developed quantum simulation toolbox for Rydberg atoms with
the recently proposed Lechner-Hauke-Zoller~(LHZ) architecture allows one to
build a prototype for a coherent adiabatic quantum computer with all-to-all
Ising interactions and, therefore, a novel platform for quantum annealing. In
LHZ a infinite-range spin-glass is mapped onto the low energy subspace of a
spin-1/2 lattice gauge model with quasi-local 4-body parity constraints. This
spin model can be emulated in a natural way with Rubidium and Cesium atoms in a
bipartite optical lattice involving laser-dressed Rydberg-Rydberg interactions,
which are several orders of magnitude larger than the relevant decoherence
rates. This makes the exploration of coherent quantum enhanced optimization
protocols accessible with state-of-the-art atomic physics experiments.


  This study compares publication pattern dynamics in the social sciences and
humanities in five European countries. Three are Central and Eastern European
countries that share a similar cultural and political heritage (the Czech
Republic, Slovakia, and Poland). The other two are Flanders (Belgium) and
Norway, representing Western Europe and the Nordics, respectively. We analysed
449,409 publications from 2013-2016 and found that, despite persisting
differences between the two groups of countries across all disciplines,
publication patterns in the Central and Eastern European countries are becoming
more similar to those in their Western and Nordic counterparts. Articles from
the Central and Eastern European countries are increasingly published in
journals indexed in Web of Science and also in journals with the highest
citation impacts. There are, however, clear differences between social science
and humanities disciplines, which need to be considered in research evaluation
and science policy.


  Given the large variety of existing logical formalisms it is of utmost
importance to select the most adequate one for a specific purpose, e.g. for
representing the knowledge relevant for a particular application or for using
the formalism as a modeling tool for problem solving. Awareness of the nature
of a logical formalism, in other words, of its fundamental intrinsic
properties, is indispensable and provides the basis of an informed choice. In
this treatise we consider the existence characterization logics as well as
properties like existence and uniqueness, expressibility, replaceability and
verifiability in the realm of abstract argumentation


  We propose a novel approach to detect the binding between proteins making use
of the anomalous diffraction of natively present heavy elements inside the
molecule 3D structure. In particular, we suggest considering sulfur atoms
contained in protein structures at lower percentages than the other atomic
species. Here, we run an extensive preliminary investigation to probe both the
feasibility and the range of usage of the proposed protocol. In particular, we
(i) analytically and numerically show that the diffraction patterns produced by
the anomalous scattering of the sulfur atoms in a given direction depend
additively on the relative distances between all couples of sulfur atoms. Thus
the differences in the patterns produced by bound proteins with respect to
their non-bonded states can be exploited to rapidly assess protein complex
formation. Next, we (ii) carried out analyses on the abundances of sulfurs in
the different proteomes and molecular dynamics simulations on a representative
set of protein structures to probe the typical motion of sulfur atoms. Finally,
we (iii) suggest a possible experimental procedure to detect protein-protein
binding. Overall, the completely label-free and rapid method we propose may be
readily extended to probe interactions on a large scale even between other
biological molecules, thus paving the way to the development of a novel field
of research based on a synchrotron light source.


  Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an
unlabeled target domain supervised by a black-box predictor trained on a source
domain. It does not require access to both the source-domain data and the
predictor parameters, thus addressing the data privacy and portability issues
of standard domain adaptation. Existing DABP approaches mostly rely on model
distillation from the black-box predictor, \emph{i.e.}, training the model with
its noisy target-domain predictions, which however inevitably introduces the
confirmation bias accumulated from the prediction noises. To mitigate such
bias, we propose a new method, named BETA, to incorporate knowledge
distillation and noisy label learning into one coherent framework. This is
enabled by a new divide-to-adapt strategy. BETA divides the target domain into
an easy-to-adapt subdomain with less noise and a hard-to-adapt subdomain. Then
it deploys mutually-teaching twin networks to filter the predictor errors for
each other and improve them progressively, from the easy to hard subdomains. As
such, BETA effectively purifies the noisy labels and reduces error
accumulation. We theoretically show that the target error of BETA is minimized
by decreasing the noise ratio of the subdomains. Extensive experiments
demonstrate BETA outperforms existing methods on all DABP benchmarks, and is
even comparable with the standard domain adaptation methods that use the
source-domain data.


  Central clearing counterparty houses (CCPs) play a fundamental role in
mitigating the counterparty risk for exchange traded options. CCPs cover for
possible losses during the liquidation of a defaulting member's portfolio by
collecting initial margins from their members. In this article we analyze the
current state of the art in the industry for computing initial margins for
options, whose core component is generally based on a VaR or Expected Shortfall
risk measure. We derive an approximation formula for the VaR at short horizons
in a model-free setting. This innovating formula has promising features and
behaves in a much more satisfactory way than the classical Filtered Historical
Simulation-based VaR in our numerical experiments. In addition, we consider the
neural-SDE model for normalized call prices proposed by [Cohen et al.,
arXiv:2202.07148, 2022] and obtain a quasi-explicit formula for the VaR and a
closed formula for the short term VaR in this model, due to its conditional
affine structure.


  The unitary equal-mass Fermi gas with zero-range interactions constitutes a
paradigmatic model system that is relevant to atomic, condensed matter,
nuclear, particle, and astro physics. This work determines the fourth-order
virial coefficient $b_4$ of such a strongly-interacting Fermi gas using a
customized \textit{ab initio} path integral Monte Carlo (PIMC) algorithm. In
contrast to earlier theoretical results, which disagreed on the sign and
magnitude of $b_4$, our $b_4$ agrees within error bars with the experimentally
determined value, thereby resolving an ongoing literature debate. Utilizing a
trap regulator, our PIMC approach determines the fourth-order virial
coefficient by directly sampling the partition function. An on-the-fly
anti-symmetrization avoids the Thomas collapse and, combined with the use of
the exact two-body zero-range propagator, establishes an efficient general
means to treat small Fermi systems with zero-range interactions.


  We investigate the effect of cooperative interactions in an ensemble of
microorganisms, modelled as self-propelled disk-like and rod-like particles, in
a three-dimensional turbulent flow to show flocking as an emergent phenomenon.
Building on the work by Choudhary, et al. [Europhys. Lett. 112, 24005 (2015)]
for two-dimensional systems, and combining ideas from active matter and
turbulent transport, we show that non-trivial correlations between the flow and
individual dynamics are essential for the microorganisms to flock in, for
example, a turbulent three-dimensional, marine environment. Our results may
have implications especially in the modelling of artificial microswimmers in a
hostile environment.


  We study the amortized number of combinatorial changes (edge insertions and
removals) needed to update the graph structure of the Voronoi diagram
$\mathcal{V}(S)$ (and several variants thereof) of a set $S$ of $n$ sites in
the plane as sites are added.
  We define a general update operation for planar graphs modeling the
incremental construction of several variants of Voronoi diagrams as well as the
incremental construction of an intersection of halfspaces in $\mathbb{R}^3$. We
show that the amortized number of edge insertions and removals needed to add a
new site is $O(\sqrt{n})$. A matching $\Omega(\sqrt{n})$ combinatorial lower
bound is shown, even in the case where the graph of the diagram is a tree. This
contrasts with the $O(\log{n})$ upper bound of Aronov et al. (2006) for
farthest-point Voronoi diagrams when the points are inserted in order along
their convex hull.
  We present a semi-dynamic data structure that maintains the Voronoi diagram
of a set $S$ of $n$ sites in convex position. This structure supports the
insertion of a new site $p$ and finds the asymptotically minimal number $K$ of
edge insertions and removals needed to obtain the diagram of $S \cup \{p\}$
from the diagram of $S$, in time $O(K\,\mathrm{polylog}\ n)$ worst case, which
is $O(\sqrt{n}\;\mathrm{polylog}\ n)$ amortized by the aforementioned result.
  The most distinctive feature of this data structure is that the graph of the
Voronoi diagram is maintained at all times and can be traversed in the natural
way; this contrasts with other known data structures supporting nearest
neighbor queries. Our data structure supports general search operations on the
current Voronoi diagram, which can, for example, be used to perform point
location queries in the cells of the current Voronoi diagram in $O(\log n)$
time, or to determine whether two given sites are neighbors in the Delaunay
triangulation.


  We have adapted the Planck cluster likelihood in such a way that it can be
applied to the sample of clusters detected by the Atacama Cosmology Telescope
(ACT). Applying it to the 2016 sample from Planck and the 2018 sample from ACT
we find, by fixing the cosmology using CMB observations and the cluster model
adopted by Planck, that the mass bias required by the two are $1-b_{\rm
Planck}=0.61\pm 0.03$ and $1-b_{\rm ACT}=0.75\pm 0.06$. These are broadly in
agreement but hint that the model could be adapted to reach a better agreement.
By normalizing the cluster model using weak lensing observations, we find
evidence for either evolution in the cluster model, quantified by the cluster
modeling parameter describing redshift dependence $\beta=0.86 \pm 0.07$ using
an updated CCCP-based normalization, or evolution in the cosmological model
quantified by the dark energy equation of state parameter $w=-0.82 \pm 0.07$.


  Mammalian cells have about 30,000-fold more protein molecules than mRNA
molecules. This larger number of molecules and the associated larger dynamic
range have major implications in the development of proteomics technologies. We
examine these implications for both liquid chromatography-tandem mass
spectrometry (LC-MS/MS) and single-molecule counting and provide estimates on
how many molecules are routinely measured in proteomics experiments by
LC-MS/MS. We review strategies that have been helpful for counting billions of
protein molecules by LC-MS/MS and suggest that these strategies can benefit
single-molecule methods, especially in mitigating the challenges of the wide
dynamic range of the proteome. We also examine the theoretical possibilities
for scaling up single-molecule and mass spectrometry proteomics approaches to
quantifying the billions of protein molecules that make up the proteomes of our
cells.


  We report an ab initio study on the rovibronic spectroscopy of the
closed-shell diatomic molecule phosphorous mononitride, PN. The study considers
the nine lowest electronic states, $X\,{}^{1}\Sigma^{+}$, $A\,{}^{1}\Pi$,
$C\,{}^{1}\Sigma^{-}$, $D\,{}^{1}\Delta$, $E\,{}^{1}\Sigma^{-}$,
$a\,{}^{3}\Sigma^{+}$, $b\,{}^{3}\Pi$, $d\,{}^{3}\Delta$ and
$e\,{}^{3}\Sigma^{-}$ using high level electronic structure theory and accurate
nuclear motion calculations. The ab initio data cover 9 potential energy, 14
spin-orbit coupling, 7 electronic angular momentum coupling, 9 electric dipole
moment and 8 transition dipole moment curves. The Duo nuclear motion program is
used to solve the coupled nuclear motion Schr\"{o}dinger equations for these
nine electronic states and to simulate rovibronic absorption spectra of
$^{31}$P$^{14}$N for different temperatures, which are compared to available
spectroscopic studies. Lifetimes for all states are calculated and compared to
previous results from the literature. The calculated lifetime of the
$A\,{}^{1}\Pi$ state shows good agreement with an experimental value from the
literature, which is an important quality indicator for the ab initio $A$-$X$
transition dipole moment.


  We show that differently constructed ensembles having the same density matrix
may be physically distinguished by observing fluctuations of some observables.
An explicit expression for fluctuations of an observable in an ensemble is
given. This result challenges Peres's fundamental postulate and seems to be
contrary to the widely-spread belief that ensembles with the same density
matrix are physically identical. This leads us to suggest that the current
liquid NMR quantum computing is truly quantum-mechanical in nature.


  This work presents a comprehensive and extensive study to illustrate how the
geometrical configurations of low angular momentum axially symmetric general
relativistic matter flow in Schwarzschild metric may influence the formation of
energy preserving shocks for adiabatic/polytropic accretion as well as of
temperature preserving dissipative shocks for for the isothermal accretion onto
non-rotating astrophysical black holes. The dynamical and thermodynamic states
of post shock polytropic and isothermal flow have been studied extensively for
three possible matter geometries, and it has been thoroughly discussed about
how such states depend on the flow structure, even when the self gravity and
the back reaction on the metric are not taken into account. Main purpose of
this paper is thus to mathematically demonstrate that for non-self gravitating
accretion, various matter geometry, in addition to the corresponding space-time
geometry, controls the shock induced phenomena as observed within the black
hole accretion discs. This work is expected to reveal how the shock generated
phenomena (emergence of the outflows/flare or the behaviour of QPO of the
associated light curves) observed at the close proximity of the horizon depends
on the physical environment of the source harbouring a supermassive black hole.


  Fix a commutative ring $\mathbf{k}$, two elements $\beta,\alpha\in\mathbf{k}$
and a positive integer $n$. Let $\mathcal{X}$ be the polynomial ring over
$\mathbf{k}$ in the $n(n-1)/2$ indeterminates $x_{i,j}$ for all $1\leq i<j\leq
n$. Consider the ideal $\mathcal{J}$ of $\mathcal{X}$ generated by all
polynomials of the form $x_{i,j}x_{j,k}-x_{i,k}(x_{i,j}+x_{j,k}+\beta)-\alpha$
for $1\leq i<j<k\leq n$. The quotient algebra $\mathcal{X}/\mathcal{J}$ (at
least for a certain choice of $\mathbf{k}$, $\beta$ and $\alpha$) has been
introduced by Karola M\'esz\'aros as a commutative analogue of Anatol
Kirillov's quasi-classical Yang-Baxter algebra. A monomial in $\mathcal{X}$ is
said to be pathless if it has no divisors of the form $x_{i,j}x_{j,k}$ with
$1\leq i<j<k\leq n$. The residue classes of these pathless monomials span the
$\mathbf{k}$-module $\mathcal{X}/\mathcal{J}$, but (in general) are
$\mathbf{k}$-linearly dependent. Recently, the study of Grothendieck
polynomials has led Laura Escobar and Karola M\'esz\'aros to defining a
$\mathbf{k}$-algebra homomorphism $D$ from $\mathcal{X}$ into the polynomial
ring $\mathbf{k}[t_{1},t_{2},\ldots,t_{n-1}]$ that sends each $x_{i,j}$ to
$t_{i}$. We show the following fact (generalizing a conjecture of
M\'esz\'aros): If $p\in\mathcal{X}$, and if $q\in\mathcal{X}$ is a
$\mathbf{k}$-linear combination of pathless monomials satisfying $p\equiv
q\operatorname{mod}\mathcal{J}$, then $D(q)$ does not depend on $q$ (as long as
$\beta$, $\alpha$ and $p$ are fixed). Thus, reducing a $p\in\mathcal{X}$ modulo
$\mathcal{J}$ may lead to different results depending on the choices made in
the reduction process, but all of them become identical once $D$ is applied. We
also find an actual basis of the $\mathbf{k}$-module $\mathcal{X}/\mathcal{J}$,
using what we call forkless monomials.


  We investigate the effect of weak interactions on the full counting
statistics of charge transfer through an arbitrary mesoscopic conductor. We
show that the main effect can be incorporated into an energy dependence of the
transmission eigenvalues and study this dependence in a non-perturbative
approach. An unexpected result is that all mesoscopic conductors behave at low
energies like either a single or a double tunnel junction, which divides them
into two broad classes.


  We provide a new virtual description of the symmetric group action on the
cohomology of ordered configuration space on SU_2 up to translations. We use
this formula to prove the Moseley-Proudfoot-Young conjecture. As a consequence
we obtain the graded Frobenius character of the Orlik-Terao algebra of type
A_n.


  Herschel FIR imaging and spectroscopy were taken at several epochs to probe
the central point source and the extended environment of V838 Mon. PACS and
SPIRE maps were used to obtain photometry of the near and far dust around V838
Mon. Fitting reveals 0.5-0.6 solar masses of ~19K dust in the environs (~2.7pc)
surrounding the star. The surface-integrated infrared flux (signifying the
thermal light echo) and derived dust properties do not vary significantly
between the epochs. We also fit the SED of the point source. As the peak of the
SED lies outside the Herschel spectral range, it is only by incorporating data
from other observatories and epochs that we can perform useful fitting; with
this we explicitly assume no evolution of the point source between the epochs.
We find warm dust with a temperature of ~300K distributed over a radius of
150-200AU. PACS and SPIRE spectra were also used to detect emission lines from
the extended environment around the star. We fit the far-infrared lines of CO
arising from the point source, from an extended environment around V838 Mon.
Assuming a model of a spherical shell for this gas, we find that the CO appears
to arise from two temperature zones: a cold zone (Tkin ~18K) that could be
associated with the ISM or possibly with a cold layer in the outermost part of
the shell, and a warm (Tkin ~400K) zone that is associated with the extended
environment of V838 Mon within a region of radius of ~210AU. The SiO lines
arise from a warm/hot zone. We did not fit the lines of H2O as they are far
more dependent on the model assumed.


  Band engineering is employed thoroughly and targets technologically scalable
photoanodes for solar water splitting applications. Complex and costly recipes
are necessary, often for average performances. Here we report simple photoanode
growth and thermal annealing, with effective band engineering results. By
comparing Ti-doped hematite photoanodes annealed under Nitrogen to photoanodes
annealed in air, we found strongly enhanced photocurrent, of more than 200 % in
the first case. Using electrochemical impedance spectroscopy and synchrotron
X-rays spectromicroscopies we demonstrate that oxidized surface states and
increased density of charge carriers are responsible for the enhanced
photoelectrochemical activity. Surface states are found to be related to the
formation of pseudo-brookite clusters by surface Ti segregation.
Spectro-ptychography is used for the first time at Ti L3 absorption edge to
isolate Ti chemical coordination arising from pseudo-brookite clusters
contribution. Correlated with electron microscopy investigation and Density
Functional Theory (DFT) calculations, the synchrotron spectromicroscopy data
prove unambiguously the origin of the better photoelectrochemical activity of
N2- annealed Ti-doped hematite nanorods. Finally, we present here a handy and
cheap surface engineering method, beyond the known oxygen vacancy doping,
allowing a net gain in the photoelectrochemical activity for the hematite-based
photoanodes.


  We have studied the dynamic response of Pb thin films with a square array of
antidots by means of ac susceptibility chi(T,H) measurements. At low enough ac
drive amplitudes h, vortices moving inside the pinning potential give rise to a
frequency- and h-independent response together with a scarce dissipation. For
higher amplitudes, the average distance travelled by vortices surpasses the
pinning range and a critical state develops. We found that the boundary h*(H,T)
between these regimes smoothly decreases as T increases whereas a step-like
behavior is observed as a function of field. We demonstrate that these steps in
h*(H) arise from sharp changes in the pinning strength corresponding to
different vortex configurations. For a wide set of data at several fields and
temperatures in the critical state regime, we show that the scaling laws based
on the simple Bean model are satisfied.


  A well known result of Newman says that upto a limit, multiples of $3$ with
even number of 1's in binary representation always exceed multiples of $3$ with
odd number of 1's. The phenomenon of preponderance of even number of 1's is now
known as Newman's phenomenon. We show that this phenomenon exists for higher
bases. Let $b$ be a positive integer($\geq 2$). Let $A_{b}$ be the set of all
natural numbers which contain only 0's and 1's in b-ary expansion and
$S^{(b)}_{q,i}(n)$ be the difference between the corresponding number of
$k_e<n$, $k_e\equiv i \mod q$, $k_e\in A_{b}$ and $k_e$ has even number of 1's
in b-ary expansion and the number of $k_o$ $k_o<n$, $k_o\equiv i \mod q$,
$k_o\in A_{b}$ and $k_o$ has odd number of 1's in b-ary expansion. Let $q$ be a
multiple or divisor of $b+1$ which is relatively prime to $b$ then we show that
$S^{(b)}_{q,0}(n)>0$ for sufficiently large $n$. We show that there is a
stronger Newman's phenomenon in $A_b$ in the following sense. If $b>2$ and
$n=\sum_{i=0}^{k-1}b_i2^i$ with $b_i\in \{0,1\}$, let
$b(n)=\sum_{i=0}^{k-1}b_ib^i$ then $\lim_{n\rightarrow \infty}
\frac{S^{(2)}_{3,0}(n)}{S^{(b)}_{b+1,0}(b(n))}=0$. That is, for the same number
of terms there is stronger preponderance in $A_b$ than in $A_2=\mathbb{N}$. In
the last section we show that number of primes $p\leq x$ for which
$S_{p,0}^{(b)}(n)>0$ for sufficiently large $n$ is $o\left(\frac{x}{\log
x}\right)$.


  Given a sequence of oriented links L^1,L^2,L^3,... each of which has a
distinguished, unknotted component, there is a decomposition of the 3-sphere
naturally associated to it, which is constructed as the components of the
intersection of an infinite sequence of nested solid tori. The Bing and
Whitehead continua are simple, well known examples. We give a necessary and
sufficient criterion to determine whether such a decomposition is shrinkable,
generalising previous work of F. Ancel and M. Starbird and others. This
criterion can effectively determine, in many cases, whether the quotient map
which identifies the elements of the decomposition to points can be
approximated by homeomorphisms.


  Let $K$ be a local field and $f(x)\in K[x]$ be a non-constant polynomial.
When ${\rm char}K=0$, Igusa showed the local zeta function is a rational
function. However, when ${\rm char}K>0$, the rationality of the local zeta
function is unknown in general. In this paper, we study the local zeta
functions for the so-called hybrid polynomials in three variables with
coefficients in a non-archimedean local field of positive characteristic. These
hybrid polynomials were first introduced by Hauser in 2003 to study the
resolution of singularities in positive characteristic. We establish the
rationality theorem for these local zeta functions and list explicitly all the
candidate poles. Our result generalizes the work of Le$\acute{o}$n-Cardenal,
Ibadula and Segers and that of Yin and Hong.


  Let $M_n$ and $T_n$ denote the $n$th Motzkin number and the $n$th central
trinomial coefficient respectively. We prove that for any prime $p\ge 5$,
\begin{align*} &\sum_{k=0}^{p-1}M_k^2\equiv
\left(\frac{p}{3}\right)\left(2-6p\right)\pmod{p^2},\\
&\sum_{k=0}^{p-1}kM_k^2\equiv
\left(\frac{p}{3}\right)\left(9p-1\right)\pmod{p^2},\\
&\sum_{k=0}^{p-1}T_kM_k\equiv
\frac{4}{3}\left(\frac{p}{3}\right)+\frac{p}{6}\left(1-9\left(\frac{p}{3}\right)\right)\pmod{p^2},
\end{align*} where $\left(-\right)$ is the Legendre symbol. These results
confirm three 12-year-old supercongruence conjectures of Z.-W. Sun.


  Using the economic complexity methodology on data for disease prevalence in
195 countries during the period of 1990-2016, we propose two new metrics for
quantifying the relatedness between diseases, or the `disease space' of
countries. With these metrics, we analyze the geography of diseases and
empirically investigate the effect of economic development on the health
complexity of countries. We show that a higher income per capita increases the
complexity of countries' diseases. Furthermore, we build a disease-level index
that links a disease to the average level of GDP per capita of the countries
that have prevalent cases of the disease. With this index, we highlight the
link between economic development and the complexity of diseases and
illustrate, at the disease-level, how increases in income per capita are
associated with more complex diseases


  The purpose of the article is to provide an unified way to formulate zero-sum
invariants. Let $G$ be a finite additive abelian group. Let $B(G)$ denote the
set consisting of all nonempty zero-sum sequences over G. For
  $\Omega \subset B(G$), let $d_{\Omega}(G)$ be the smallest integer $t$ such
that every sequence $S$ over $G$ of length $|S|\geq t$ has a subsequence in
$\Omega$.We provide some first results and open problems on $d_{\Omega}(G)$.


  We give a new proof of the vanishing noise limit theorem for exit times of
1-dimensional diffusions conditioned on exiting through a point separated from
the starting point by a potential wall. We also prove a scaling limit for exit
location in a model 2-dimensional situation.


  Face recognition is a popular form of biometric authentication and due to its
widespread use, attacks have become more common as well. Recent studies show
that Face Recognition Systems are vulnerable to attacks and can lead to
erroneous identification of faces. Interestingly, most of these attacks are
white-box, or they are manipulating facial images in ways that are not
physically realizable. In this paper, we propose an attack scheme where the
attacker can generate realistic synthesized face images with subtle
perturbations and physically realize that onto his face to attack black-box
face recognition systems. Comprehensive experiments and analyses show that
subtle perturbations realized on attackers face can create successful attacks
on state-of-the-art face recognition systems in black-box settings. Our study
exposes the underlying vulnerability posed by the Face Recognition Systems
against realizable black-box attacks.


  Natural selection favors the more successful individuals. This is the
elementary premise that pervades common models of evolution. Under extreme
conditions, however, the process may no longer be probabilistic. Those that
meet certain conditions survive and may reproduce while others perish. By
introducing the corresponding binary birth-death dynamics to spatial
evolutionary games, we observe solutions that are fundamentally different from
those reported previously based on imitation dynamics. Social dilemmas
transform to collective enterprises, where the availability of free expansion
ranges and limited exploitation possibilities dictates self-organized growth.
Strategies that dominate are those that are collectively most apt in meeting
the survival threshold, rather than those who succeed in exploiting others for
unfair benefits. Revisiting Darwinian principles with the focus on survival
rather than imitation thus reveals the most counterintuitive ways of
reconciling cooperation with competition.


  Post-processing in algorithmic fairness is a versatile approach for
correcting bias in ML systems that are already used in production. The main
appeal of post-processing is that it avoids expensive retraining. In this work,
we propose general post-processing algorithms for individual fairness (IF). We
consider a setting where the learner only has access to the predictions of the
original model and a similarity graph between individuals, guiding the desired
fairness constraints. We cast the IF post-processing problem as a graph
smoothing problem corresponding to graph Laplacian regularization that
preserves the desired "treat similar individuals similarly" interpretation. Our
theoretical results demonstrate the connection of the new objective function to
a local relaxation of the original individual fairness. Empirically, our
post-processing algorithms correct individual biases in large-scale NLP models
such as BERT, while preserving accuracy.


  The role of models in Quantum Chromodynamics is to produce simple physical
pictures that connect the phenomenological regularities with the underlying
structure. The static properties of hadrons have provided experimental input to
define a variety of very succesful Quark Models. We discuss applications of
some of the most widely used of these models to the high energy regime, a
scenario for which they were not proposed. The initial assumption underlying
our presentation will be that gluon and sea bremsstrahlung connect the
constituent quark momentum distributions with the partonic structure functions.
The results obtained are encouraging but lead to the necessity of more complex
structures at the hadronic scale. This initial hypothesis may be relaxed by
introducing some non perturbative model for the constituent quarks. Within this
scheme we will discuss some relevant problems in nucleon structure as seen in
high energy experiments.


  The strength of the submillimeter background light shows directly that much
of the energy radiated by star formation and AGN is moved to far infrared
wavelengths. However, it is only as this background at 850 microns has been
resolved with direct submillimeter imaging that we have seen that it is created
by a population of ultraluminous (or near ultraluminous) infrared galaxies
(ULIGs) which appear to lie at relatively high redshifts (z>1). Mapping the
redshift evolution of this major portion of the universal star formation has
been difficult because of the poor submillimeter spatial resolution, but this
difficulty can be overcome by using extremely deep cm continuum radio
observations to obtain precise astrometric information since the bulk of the
brighter submillimeter sources have detectable radio counterparts. However,
with this precise position information available, we find that most of the
submillimeter sources are extremely faint in the optical and near infrared
(I>>24 and K=21-22) and inaccessible to optical spectroscopy. Rough photometric
redshift estimates can be made from combined radio and submillimeter energy
distributions. We shall refer to this procedure as millimetric redshift
estimation to distinguish it from photometric estimators in the optical and
near IR. These estimators place the bulk of the submillimeter population at
z=1-3, where it corresponds to the high redshift tail of the faint cm radio
population. While still preliminary, the results suggest that the submillimeter
population appears to dominate the star formation in this redshift range by
almost an order of magnitude over the mostly distinct populations selected in
the optical-ultraviolet.


  We focus on credal nets, which are graphical models that generalise Bayesian
nets to imprecise probability. We replace the notion of strong independence
commonly used in credal nets with the weaker notion of epistemic irrelevance,
which is arguably more suited for a behavioural theory of probability. Focusing
on directed trees, we show how to combine the given local uncertainty models in
the nodes of the graph into a global model, and we use this to construct and
justify an exact message-passing algorithm that computes updated beliefs for a
variable in the tree. The algorithm, which is linear in the number of nodes, is
formulated entirely in terms of coherent lower previsions, and is shown to
satisfy a number of rationality requirements. We supply examples of the
algorithm's operation, and report an application to on-line character
recognition that illustrates the advantages of our approach for prediction. We
comment on the perspectives, opened by the availability, for the first time, of
a truly efficient algorithm based on epistemic irrelevance.


  Extensive equilibrium Monte Carlo simulations are performed for a
three-dimensional Heisenberg spin glass with the nearest-neighbor Gaussian
coupling to investigate its spin-glass and chiral-glass orderings. The
occurrence of a finite-temperature chiral-glass transition without the
conventional spin-glass order is established. Critical exponents characterizing
the transition are different from those of the standard Ising spin glass. The
calculated overlap distribution suggests the appearance of a peculiar type of
replica-symmetry breaking in the chiral-glass ordered state.


  We consider the four dimensional abelian topological BF theory with a planar
boundary introduced following the Symanzik's method. We find the most general
boundary conditions compatible with the fields equations broken by the
boundary. The residual gauge invariance is described by means of two Ward
identities which generate an algebra of conserved currents. We interpret this
algebra as canonical commutation relations of fields, which we use to construct
a three dimensional Lagrangian. As a remarkable by-product, the (unique)
boundary condition which we found, can be read as a duality relation between 3D
dynamical variables.


  Within the supersymmetric SO(10) GUT we explore the possibility of the light
Higgs doublet being a member of the 16-dimensional spinorial representation.
This fact is ultimately related with the assumption that the light matter (at
least partially) resides in some of the tensor representations as well. Several
interesting features emerge. First, provided that the same 16-plet is
responsible for the breaking $SO(10) \rightarrow SU(5)$, the heaviness of the
top can automatically follow from the field content at $M_{GUT}$, without need
of any flavour symmetries. Secondly, the doublet--triplet splitting problem
receives a new natural solution. In addition, a dimension=5 (Higgsino mediated)
proton decay can be naturally suppressed. We construct explicit SO(10) models
with the above properties, with most general superpotentials under the
symmetries.


  We study QCD axion or cosmological axion-like particles (ALPs) in a model
inspired by the recent interest in 4-dimensional clockwork models, with the
global symmetry being accidentally enforced by a gauge abelian quiver with
scalar bifundamental fields.
  For the QCD axion, we analyze the connection between the degree of protection
of the axion mass against gravitational corrections, the explanation of the
hierarchy $f_a \ll M_P$ and the number of colored fermions needed to generate
anomalous couplings to gluons, all linked together by the underlying gauge
symmetries. Based on that model and on the comparison with earlier models in
the literature, we derive certain general conclusions on QCD axion models that
use accidental global symmetries.
  For the ALPs, assuming that their mass is solely given by gravitational
corrections, we identify the parameter space where the decay constant and the
mass are consistent with the DM abundance, and we show that this
clockwork-inspired model is a particularly economical model for a very light
ALP DM candidate.


  A graph is edge-distance-regular when it is distance-regular around each of
its edges and it has the same intersection numbers for any edge taken as a
root. In this paper we give some (combinatorial and algebraic) proofs of the
fact that every edge-distance-regular graph $\G$ is distance-regular and
homogeneous. More precisely, $\G$ is edge-distance-regular if and only if it is
bipartite distance-regular or a generalized odd graph. Also, we obtain the
relationships between some of their corresponding parameters, mainly, the
distance polynomials and the intersection numbers.


  The possibilities of decentralization and immutability make blockchain
probably one of the most breakthrough and promising technological innovations
in recent years. This paper presents an overview, analysis, and classification
of possible blockchain solutions for practical tasks facing multi-agent robotic
systems. The paper discusses blockchain-based applications that demonstrate how
distributed ledger can be used to extend the existing number of research
platforms and libraries for multi-agent robotic systems.


  The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator
chain. Providing stable intensity, energy, and emittance is key since it
directly affects downstream machines. To operate high current beam,
accelerators must minimize uncontrolled particle loss; this can be accomplished
by minimizing beam longitudinal emittance via RF parameter optimization.
However, RF tuning is required daily since the resonance frequency of the
accelerating cavities is affected by ambient temperature and humidity
variations and thus drifts with time. In addition, the energy and phase space
distribution of particles emerging from the ion source are subject to
fluctuations. Such drift is not unique to Fermilab, but rather affects most
laboratories. We are exploring machine learning (ML) algorithms for automated
RF tuning for 2 objectives: optimization of Linac output energy and phase
oscillation correction, with an emphasis on time-drift aware modeling that can
account for conditions changing over time.


  Traveling waves are commonly observed across the brain. While previous
studies have suggested the role of traveling waves in learning, the mechanism
is still unclear. We adopted a computational approach to investigate the effect
of traveling waves on synaptic plasticity. Our results indicate that traveling
waves facilitate the learning of poly-synaptic network-paths when combined with
a reward-dependent local synaptic plasticity rule. We also demonstrate that
traveling waves expedite finding the shortest paths and learning nonlinear
input/output-mapping, such as exclusive or (XOR) function.


  Using numerical simulations, we show that the asymptotic states of
two-dimensional (2D) Euler turbulence exhibit large-scale flow structures due
to nonzero energy transfers among small wavenumber modes. These asymptotic
states, which depend on the initial conditions, are out of equilibrium, and
they are different from the predictions of Onsager and Kraichnan. We propose
``hydrodynamic entropy'' to quantify order in 2D Euler turbulence; we show that
this entropy decreases with time, even though the system is isolated with no
dissipation and no contact with a heat bath.


  We give an explicit coinduction principle for recursively-defined stochastic
processes. The principle applies to any closed property, not just equality, and
works even when solutions are not unique. The rule encapsulates low-level
analytic arguments, allowing reasoning about such processes at a higher
algebraic level. We illustrate the use of the rule in deriving properties of a
simple coin-flip process.


  The QCD Explorer will give opportunity to enlighten the origin of the 98.5%
portion of the visible universe's mass, clarify the nature of the strong
interactions from parton to nuclear level and provide precission pdf's for the
LHC. Especially the {\gamma}-nucleus option seems to be very promising for QCD
studies.


  In many practical applications the underlying graph must be as equitable
colored as possible. A coloring is called equitable if the number of vertices
colored with each color differs by at most one, and the least number of colors
for which a graph has such a coloring is called its equitable chromatic number.
We introduce a new integer linear programming approach for studying the
equitable coloring number of a graph and show how to use it for improving lower
bounds for this number. The two stage method is based on finding or upper
bounding the maximum cardinality of an equitable color class in a valid
equitable coloring and, then, sequentially improving the lower bound for the
equitable coloring number. The computational experiments were carried out on
DIMACS graphs and other graphs from the literature.


  The sizes of entire systems of globular clusters (GCs) depend on the
formation and destruction histories of the GCs themselves, but also on the
assembly, merger and accretion history of the dark matter (DM) haloes that they
inhabit. Recent work has shown a linear relation between total mass of globular
clusters in the globular cluster system and the mass of its host dark matter
halo, calibrated from weak lensing. Here we extend this to GC system sizes, by
studying the radial density profiles of GCs around galaxies in nearby galaxy
groups. We find that radial density profiles of the GC systems are well fit
with a de Vaucouleurs profile. Combining our results with those from the
literature, we find tight relationship ($\sim 0.2$ dex scatter) between the
effective radius of the GC system and the virial radius (or mass) of its host
DM halo. The steep non-linear dependence of this relationship ($R_{e, GCS}
\propto R_{200}^{2.5 - 3}$) is currently not well understood, but is an
important clue regarding the assembly history of DM haloes and of the GC
systems that they host.


  The OFDM sequences with low correlation sidelobe level (SLCL) is desired in
many 5G wireless systems. In this letter, the OFDM sequences and mismatch
filter are jointly designed to achieve the SLCL under the constraints of
spectra and peak to average power ratio (PAPR). Specifically, we formulate the
optimization problem by maximizing the peak side lobe ratio (PSLR) of the
cross-correlation between the OFDM sequences and mismatch filter, subject to
several practice constraints. To solve the nonconvex problem, an efficient
alternating optimization (AltOpt) algorithm is proposed. Numerical simulations
are provided to demonstrate the effectiveness of the proposed algorithms.


  In the Max-k-diameter problem, we are given a set of points in a metric
space, and the goal is to partition the input points into k parts such that the
maximum pairwise distance between points in the same part of the partition is
minimized.
  The approximability of the Max-k-diameter problem was studied in the
eighties, culminating in the work of Feder and Greene [STOC'88], wherein they
showed it is NP-hard to approximate within a factor better than 2 in the
$\ell_1$ and $\ell_\infty$ metrics, and NP-hard to approximate within a factor
better than 1.969 in the Euclidean metric. This complements the celebrated 2
factor polynomial time approximation algorithm for the problem in general
metrics (Gonzalez [TCS'85]; Hochbaum and Shmoys [JACM'86]).
  Over the last couple of decades, there has been increased interest from the
algorithmic community to study the approximability of various clustering
objectives when the number of clusters is fixed. In this setting, the framework
of coresets has yielded PTAS for most popular clustering objectives, including
k-means, k-median, k-center, k-minsum, and so on.
  In this paper, rather surprisingly, we prove that even when k=3, the
Max-k-diameter problem is NP-hard to approximate within a factor of 1.5 in the
$\ell_1$-metric (and Hamming metric) and NP-hard to approximate within a factor
of 1.304 in the Euclidean metric.
  Our main conceptual contribution is the introduction of a novel framework
called cloud systems which embed hypergraphs into $\ell_p$-metric spaces such
that the chromatic number of the hypergraph is related to the quality of the
Max-k-diameter clustering of the embedded pointset. Our main technical
contributions are the constructions of nontrivial cloud systems in the
Euclidean and $\ell_1$-metrics using extremal geometric structures.


  This paper investigates the impact of different standard environmental sound
representations (spectrograms) on the recognition performance and adversarial
attack robustness of a victim residual convolutional neural network, namely
ResNet-18. Our main motivation for focusing on such a front-end classifier
rather than other complex architectures is balancing recognition accuracy and
the total number of training parameters. Herein, we measure the impact of
different settings required for generating more informative Mel-frequency
cepstral coefficient (MFCC), short-time Fourier transform (STFT), and discrete
wavelet transform (DWT) representations on our front-end model. This
measurement involves comparing the classification performance over the
adversarial robustness. We demonstrate an inverse relationship between
recognition accuracy and model robustness against six benchmarking attack
algorithms on the balance of average budgets allocated by the adversary and the
attack cost. Moreover, our experimental results have shown that while the
ResNet-18 model trained on DWT spectrograms achieves a high recognition
accuracy, attacking this model is relatively more costly for the adversary than
other 2D representations. We also report some results on different
convolutional neural network architectures such as ResNet-34, ResNet-56,
AlexNet, and GoogLeNet, SB-CNN, and LSTM-based.


  We study the DC conductivities of various holographic models using the open
string metric (OSM), which is an effective metric geometrizing density and
electromagnetic field effect. We propose a new way to compute the nonlinear
conductivity using OSM. As far as the final conductivity formula is concerned,
it is equivalent to the Karch-O'Bannon's real-action method. However, it yields
a geometrical insight and technical simplifications. Especially, a real-action
condition is interpreted as a regular geometry condition of OSM. As
applications of the OSM method, we study several holographic models on the
quantum Hall effect and strange metal. By comparing a Lifshitz background and
the Light-Cone AdS, we show how an extra parameter can change the temperature
scaling behavior of conductivity. Finally we discuss how OSM can be used to
study other transport coefficients, such as diffusion constant, and effective
temperature induced by the effective world volume horizon.


  This paper establishes a link between the non-local behaviour of granular
materials and the presence of transient clusters of jammed particles within the
flow. These clusters are first evidenced in simulated dense granular flows
subjected to plane shear, and are found to originate from a mechanism of
multiple orthogonal shear banding. A continuum non-local model, similar in form
to the non-local Cooperative model, is then derived by considering the spatial
redistribution of vorticity induced by these clusters. The non-locality length
scale is thus expressed in terms of the cluster size. The purely kinematic
nature of this derivation indicates that non-local behaviour should be expected
in all glassy materials, regardless of their local constitutive law, as long as
they partially jam during flow.


  The Belleplaine test site, located in the island of Guadeloupe (French Lesser
Antilles) includes a three-accelerometer vertical array, designed for liquefac-
tion studies. The seismic response of the soil column at the test site is
computed using three methods: the spectral ratio method using the vertical
array data, a numerical method using the geotechnical properties of the soil
column, and an operative fre- quency domain decomposition (FDD) modal analysis
method. The Belleplaine test site is characterized by a mangrove layer overlaid
by a stiff sandy deposit. This con- figuration is widely found at the border
coast of the Caribbean region, which is exposed to high seismic hazard. We show
that the buried mangrove layer plays the role of an isolation system equivalent
to those usually employed in earthquake engineering aimed at reducing the
seismic shear forces by reducing the internal stress within the structure. In
our case, the flexibility of the mangrove layer reduces the distortion and the
stress in the sandy upper layer, and consequently reduces the potential of
liquefaction of the site.


  For any finite abelian group $G$ and any subset $S\seq G$, we determine the
connectivity of the addition Cayley graph induced by $S$ on $G$. Moreover, we
show that if this graph is not complete, then it possesses a minimum vertex cut
of a special, explicitly described form.


  In this paper we construct an invariant probability measure concentrated on
$H^2(K)\times H^1(K)$ for a general cubic Klein-Gordon equation (including the
case of the wave equation). Here $K$ represents both the $3$-dimensional torus
or a bounded domain with smooth boundary in $\Bbb R^3.$ That allows to deduce
some corollaries on the long time behaviour of the flow of the equation in a
probabilistic sense. We also establish qualitative properties of the
constructed measure. This work extends the Fluctuation-Dissipation-Limit (FDL)
approach to PDEs having only one (coercive) conservation law.


  In this paper, we present a novel framework for data redundancy measurement
based on probabilistic modeling of datasets, and a new criterion for redundancy
detection that is resilient to noise. We also develop new methods for data
redundancy reduction using both deterministic and stochastic optimization
techniques. Our framework is flexible and can handle different types of
features, and our experiments on benchmark datasets demonstrate the
effectiveness of our methods. We provide a new perspective on feature
selection, and propose effective and robust approaches for both supervised and
unsupervised learning problems.


  This study investigates the impact of three cold plasma treatments on barley
seed germination: direct treatment of dry seeds (DDS), direct treatment of
water-soaked seeds (DWS), and indirect treatment of seeds using
plasma-activated water (IPAW).


  Management of network resources in advanced IoT applications is a challenging
topic due to their distributed nature from the Edge to the Cloud, and the heavy
demand of real-time data from many sources to take action in the deployment.
FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous
multi-modal use cases, which require strict quality in the network
communications, as well as the coordination of the computing capabilities, in
order to operate correctly the final service. In this paper, we present a
Virtual Network Embedding (VNE) framework designed for the allocation of
dataflow applications, composed of nano-services that produce or consume data,
in a wireless infrastructure, such as an airborne network. To address the
problem, an anypath-based heuristic algorithm that considers the quality demand
of the communication between nano-services is proposed, coined as
Quality-Revenue Paired Anypath Dataflow VNE (QRPAD-VNE). We also provide a
simulation environment for the evaluation of its performance according to the
virtual network (VN) request load in the system. Finally, we show the
suitability of a multi-parameter framework in conjunction with anypath routing
in order to have better performance results that guarantee minimum quality in
the wireless communications.


  How impulsive magnetic energy release leads to solar eruptions and how those
eruptions are energized and evolve are vital unsolved problems in Heliophysics.
The standard model for solar eruptions summarizes our current understanding of
these events. Magnetic energy in the corona is released through drastic
restructuring of the magnetic field via reconnection. Electrons and ions are
then accelerated by poorly understood processes. Theories include contracting
loops, merging magnetic islands, stochastic acceleration, and turbulence at
shocks, among others. Although this basic model is well established, the
fundamental physics is poorly understood. HXR observations using
grazing-incidence focusing optics can now probe all of the key regions of the
standard model. These include two above-the-looptop (ALT) sources which bookend
the reconnection region and are likely the sites of particle acceleration and
direct heating. The science achievable by a direct HXR imaging instrument can
be summarized by the following science questions and objectives which are some
of the most outstanding issues in solar physics (1) How are particles
accelerated at the Sun? (1a) Where are electrons accelerated and on what time
scales? (1b) What fraction of electrons is accelerated out of the ambient
medium? (2) How does magnetic energy release on the Sun lead to flares and
eruptions? A Focusing Optics X-ray Solar Imager (FOXSI) instrument, which can
be built now using proven technology and at modest cost, would enable
revolutionary advancements in our understanding of impulsive magnetic energy
release and particle acceleration, a process which is known to occur at the Sun
but also throughout the Universe.


  Integer-valued trawl processes are a class of serially correlated, stationary
and infinitely divisible processes that Ole E. Barndorff-Nielsen has been
working on in recent years. In this Chapter, we provide the first analysis of
likelihood inference for trawl processes by focusing on the so-called
exponential-trawl process, which is also a continuous time hidden Markov
process with countable state space. The core ideas include prediction
decomposition, filtering and smoothing, complete-data analysis and EM
algorithm. These can be easily scaled up to adapt to more general trawl
processes but with increasing computation efforts.


  It is constructively proved that for class $A_{r,\gamma}=\{q\in
L_{1,loc}(0,1): q\leq 0, \int_0^1 rq^\gamma\,dx\leqslant 1\}$, where $r\in
C[0,1]$ is uniformly positive weight and $\gamma>1$, there exists a unique
potential $\hat q\in A_{r,\gamma}$ such that minimal eigenvalue $\lambda_0(\hat
q)$ of boundary problem $$-y"+\hat qy=\lambda y, y(0)=y(1)=0 $$ is equal to
$M_{r,\gamma}=\sup_{q\in A_{r,\gamma}}\lambda_0(q)$. For case $\gamma=1$ we
obtain that there exists a unique potential $\hat q\in\Gamma_{r,\gamma}$ with
analogous property. Here $\Gamma_{r,\gamma}$ is a closure of $A_{r,\gamma}$ in
the space $W_{2,loc}^{-1}(0,1)$ of generalized functions.


  Realtime crowdsourcing research has demonstrated that it is possible to
recruit paid crowds within seconds by managing a small, fast-reacting worker
pool. Realtime crowds enable crowd-powered systems that respond at interactive
speeds: for example, cameras, robots and instant opinion polls. So far, these
techniques have mainly been proof-of-concept prototypes: research has not yet
attempted to understand how they might work at large scale or optimize their
cost/performance trade-offs. In this paper, we use queueing theory to analyze
the retainer model for realtime crowdsourcing, in particular its expected wait
time and cost to requesters. We provide an algorithm that allows requesters to
minimize their cost subject to performance requirements. We then propose and
analyze three techniques to improve performance: push notifications, shared
retainer pools, and precruitment, which involves recalling retainer workers
before a task actually arrives. An experimental validation finds that
precruited workers begin a task 500 milliseconds after it is posted, delivering
results below the one-second cognitive threshold for an end-user to stay in
flow.


  In this survey, we review the literature investigating participatory
budgeting as a social choice problem. Participatory Budgeting (PB) is a
democratic process in which citizens are asked to vote on how to allocate a
given amount of public money to a set of projects. From a social choice
perspective, it corresponds then to the problem of aggregating opinions about
which projects should be funded, into a budget allocation satisfying a budget
constraint. This problem has received substantial attention in recent years and
the literature is growing at a fast pace. In this survey, we present the most
important research directions from the literature, each time presenting a large
set of representative results. We only focus on the indivisible case, that is,
PB problems in which projects can either be fully funded or not at all.
  The aim of the survey is to present a comprehensive overview of the state of
the research on PB. We aim at providing both a general overview of the main
research questions that are being investigated, and formal and unified
definitions of the most important technical concepts from the literature.


  We continue our study of codimension two solutions of warped space-time
varying compactifications of string theory. In this letter we discuss a
non-supersymmetric solution of the classical type IIB string theory with de
Sitter gravity on a codimension two uncompactified part of spacetime. A
non-zero positive value of the cosmological constant is induced by the presence
of non-trivial stringy moduli, such as the axion-dilaton system for the type
IIB string theory. Furthermore, the naked singularity of the codimension two
solution is resolved by the presence of a small but non-zero cosmological
constant.


  The cross section of bremsstrahlung from high-energy electron suppressed due
to the multiple scattering of an emitting electron in a dense media (the LPM
effect) is discussed. Development of the LPM effect theory is outlined. For the
target of finite thickness one has to include boundary photon radiation as well
as the interference effects. The importance of multiphoton effects is
emphasized. Comparison of theory with SLAC data is presented.


  Within the framework of the Fock-Feynman-Schwinger (equivalently, worldline)
casting of QCD a four-point process, mediated by a closed quark loop, is
studied in the Sudakov kinematical region, first perturbatively and
subsequently with the inclusion of non-perturbative contributions through the
use of the stochastic vacuum model. Deformations of the, first order,
perturbative results are determined. Finally, the resummation of the leading
logarithmic terms is performed and physical implications of the result are
discussed.


  $\require{mediawiki-texvc}$A stellar chromospheric activity database of
solar-like stars is constructed based on the Large Sky Area Multi-Object Fiber
Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The
database contains spectral bandpass fluxes and indexes of Ca II H&K lines
derived from 1,330,654 high-quality LRS spectra of solar-like stars. We measure
the mean fluxes at line cores of the Ca II H&K lines using a 1 ${\AA}$
rectangular bandpass as well as a 1.09 ${\AA}$ full width at half maximum
(FWHM) triangular bandpass, and the mean fluxes of two 20 ${\AA}$
pseudo-continuum bands on the two sides of the lines. Three activity indexes,
$S_{\rm rec}$ based on the 1 ${\AA}$ rectangular bandpass, and $S_{\rm tri}$
and $S_L$ based on the 1.09 ${\AA}$ FWHM triangular bandpass, are evaluated
from the measured fluxes to quantitatively indicate the chromospheric activity
level. The uncertainties of all the obtained parameters are estimated. We also
produce spectrum diagrams of Ca II H&K lines for all the spectra in the
database. The entity of the database is composed of a catalog of spectral
sample and activity parameters, and a library of spectrum diagrams. Statistics
reveal that the solar-like stars with high level of chromospheric activity
($S_{\rm rec}>0.6$) tend to appear in the parameter range of $T_{\rm eff}\text{
(effective temperature)}<5500\,{\rm K}$, $4.3<\log\,g\text{ (surface
gravity)}<4.6$, and $-0.2<[{\rm Fe/H}]\text{ (metallicity)}<0.3$. This database
with more than one million high-quality LAMOST LRS spectra of Ca II H&K lines
and basal chromospheric activity parameters can be further used for
investigating activity characteristics of solar-like stars and solar-stellar
connection.


  We compute the maximal Thurston-Bennequin number for a Legendrian two-bridge
knot or oriented two-bridge link in standard contact R^3, by showing that the
upper bound given by the Kauffman polynomial is sharp. As an application, we
present a table of maximal Thurston-Bennequin numbers for prime knots with nine
or fewer crossings.


  We present a method for calculating expectation values of operators in terms
of a corresponding c-function formalism which is not the Wigner--Weyl
position-momentum phase-space, but another space. Here, the quantity
representing the quantum system is the expectation value of the displacement
operator, parametrized by the position and momentum displacements, and
expectation values are evaluated as classical integrals over these parameters.
The displacement operator is found to offer a complete orthogonal basis for
operators, and some of its other properties are investigated. Connection to the
Wigner distribution and Weyl procedure are discussed and examples are given.


  We report the first observation of electromagnetically induced transparency
(EIT) in an isotopically purified Nd$^{3+}$:YLiF$_4$ crystal. This crystal
demonstrates inhomogeneous broadening of optical transitions of about 35 MHz.
EIT is observed in a symmetrical $\Lambda$-like system formed by two hyperfine
sublevels of the ground state corresponding to a zero first order Zeeman
(ZEFOZ) transition and a hyperfine sublevel of the excited state, which is not
coupled to other ground-state sublevels. It is found that transmission of the
probe field as a function of the two-photon detuning demonstrates a comb-like
structure that can be attributed to superhyperfine coupling between Nd$^{3+}$
ions and fluorine nuclei. The observed structure can be resolved only in the
vicinity of the ZEFOZ point where the homogeneous linewidth of the spin
transition is sufficiently small. The results pave the way for implementing
solid-state quantum memories based on off-resonant Raman interaction without
spectral tailoring of optical transitions.


  Despite recent success, most contrastive self-supervised learning methods are
domain-specific, relying heavily on data augmentation techniques that require
knowledge about a particular domain, such as image cropping and rotation. To
overcome such limitation, we propose a novel domain-agnostic approach to
contrastive learning, named DACL, that is applicable to domains where
invariances, and thus, data augmentation techniques, are not readily available.
Key to our approach is the use of Mixup noise to create similar and dissimilar
examples by mixing data samples differently either at the input or hidden-state
levels. To demonstrate the effectiveness of DACL, we conduct experiments across
various domains such as tabular data, images, and graphs. Our results show that
DACL not only outperforms other domain-agnostic noising methods, such as
Gaussian-noise, but also combines well with domain-specific methods, such as
SimCLR, to improve self-supervised visual representation learning. Finally, we
theoretically analyze our method and show advantages over the Gaussian-noise
based contrastive learning approach.


  We present the outcome of a highly-sensitive search for magnetic fields on
the cool supergiant Betelgeuse. A time-series of six circularly-polarized
spectra was obtained using the NARVAL spectropolarimeter at T\'elescope Bernard
Lyot (Pic du Midi Observatory), between 2010 March and April. Zeeman signatures
were repeatedly detected in cross-correlation profiles, corresponding to a
longitudinal component of about 1 G. The time-series unveils a smooth increase
of the longitudinal field from 0.5 to 1.5 G, correlated with radial velocity
fluctuations. We observe a strong asymmetry of Stokes V signatures, also
varying in correlation with the radial velocity. The Stokes V line profiles are
red-shifted by about 9 km/s with respect to the Stokes I profiles, suggesting
that the observed magnetic elements may be concentrated in the sinking
components of the convective flows.


  We construct an invariant basis for Compton scattering with two virtual
photons (VVCS). The basis tensors are chosen to be gauge invariant and
orthogonal to each other. The properties of the corresponding 18 invariant
amplitudes are studied in detail. We consider the special case of elastic VVCS
with the virtualities of the initial and final photons equal. The invariant
basis for VVCS in this orthogonal form does not exist in the literatur. We
furthermore use this VVCS tensor for a calculation of the beam normal spin
asymmetry in the forward kinematics. For this, we relate the invariant
amplitudes to the helicity amplitudes of the VVCS reaction. The imaginary parts
of these latter are related to the inclusive cross section by means of the
optical theorem. We use the phenomenological value of the transverse cross
section $\sigma_T\sim0.1$ mbarn and the Callan-Gross relation which relates the
longitudinal cross section $\sigma_L$ to the transverse one. The result of the
calculation agrees with an existing calculation and predicts the negative
values of the asymmetry $B_n$ of the order of 4-6 ppm in the energy range from
6 to 45 ppm and for very forward angles.


  The Murchison Widefield Array (MWA) is a new low-frequency interferometric
radio telescope built in Western Australia at one of the locations of the
future Square Kilometre Array (SKA). We describe the automated radio-frequency
interference (RFI) detection strategy implemented for the MWA, which is based
on the AOFlagger platform, and present 72-231-MHz RFI statistics from 10
observing nights. RFI detection removes 1.1% of the data. RFI from digital TV
(DTV) is observed 3% of the time due to occasional ionospheric or atmospheric
propagation. After RFI detection and excision, almost all data can be
calibrated and imaged without further RFI mitigation efforts, including
observations within the FM and DTV bands. The results are compared to a
previously published Low-Frequency Array (LOFAR) RFI survey. The remote
location of the MWA results in a substantially cleaner RFI environment compared
to LOFAR's radio environment, but adequate detection of RFI is still required
before data can be analysed. We include specific recommendations designed to
make the SKA more robust to RFI, including: the availability of sufficient
computing power for RFI detection; accounting for RFI in the receiver design; a
smooth band-pass response; and the capability of RFI detection at high time and
frequency resolution (second and kHz-scale respectively).


  This is a comment on a reply (gr-qc/9601040) to a comment (gr-qc/9606045) on
a paper of Hellaby & Dray (gr-qc/9404001), repeating the identification of an
important mistake which is still being denied by the authors: their proposed
solutions do not satisfy the Einstein- Klein-Gordon equations at a change of
signature. Substitution of the proposed solutions into the
Einstein-Klein-Gordon equations in unit normal coordinates yields Dirac delta
terms describing source layers at the junction. Hellaby & Dray's criticisms of
this straightforward calculation are absurd: it does not involve "imaginary
time", it does not involve a "modified form" of the field equations, and it is
"purely classical". Moreover, Hellaby & Dray's latest attempt to lose the delta
terms is mathematically invalid, involving division by zero and products of
distributions, hinging on an identity whose incorrectness may be checked by
substitution.


  Learning stable dynamics from observed time-series data is an essential
problem in robotics, physical modeling, and systems biology. Many of these
dynamics are represented as an inputs-output system to communicate with the
external environment. In this study, we focus on input-output stable systems,
exhibiting robustness against unexpected stimuli and noise. We propose a method
to learn nonlinear systems guaranteeing the input-output stability. Our
proposed method utilizes the differentiable projection onto the space
satisfying the Hamilton-Jacobi inequality to realize the input-output
stability. The problem of finding this projection can be formulated as a
quadratic constraint quadratic programming problem, and we derive the
particular solution analytically. Also, we apply our method to a toy bistable
model and the task of training a benchmark generated from a glucose-insulin
simulator. The results show that the nonlinear system with neural networks by
our method achieves the input-output stability, unlike naive neural networks.
Our code is available at https://github.com/clinfo/DeepIOStability.


  The IS-Impact Measurement Model, developed by Gable, Sedera and Chan in 2008,
represents the to-date and expected stream of net profits from a given
information system (IS), as perceived by all major user classes. Although this
model has been stringently validated in previous studies, its generalizability
and verified effectiveness are enhanced through this new application in
e-learning. This paper focuses on the re-validation of the findings of the
IS-Impact Model in two universities in the Kingdom of Saudi Arabia (KSA). Among
the users of 2 universities e-learning systems, 528 students were recruited. A
formative validation measurement with SmartPLS, a graphical structural equation
modeling tool was used to analyse the collected data. On the basis of the
SmartPLS results, as well as with the aid of data-supported IS impact
measurements and dimensions, we confirmed the validity of the IS-Impact Model
for assessing the effect of e-learning systems in KSA universities. The newly
constructed model is more understandable, its use was proved as robust and
applicable to various circumstances.


  Although lyrics represent an essential component of music, few music
information processing studies have been conducted on the characteristics of
lyricists. Because these characteristics may be valuable for musical
applications, such as recommendations, they warrant further study. We
considered a potential method that extracts features representing the
characteristics of lyricists from lyrics. Because these features must be
identified prior to extraction, we focused on lyricists with easily
identifiable features. We believe that it is desirable for singers to perform
unique songs that share certain characteristics specific to the singer.
Accordingly, we hypothesized that lyricists account for the unique
characteristics of the singers they write lyrics for. In other words,
lyric-lyricist classification performance or the ease of capturing the features
of a lyricist from the lyrics may depend on the variety of singers. In this
study, we observed a relationship between lyricist-singer entropy or the
variety of singers associated with a single lyricist and lyric-lyricist
classification performance. As an example, the lyricist-singer entropy is
minimal when the lyricist writes lyrics for only one singer. In our
experiments, we grouped lyricists among five groups in terms of lyricist-singer
entropy and assessed the lyric-lyricist classification performance within each
group. Consequently, the best F1 score was obtained for the group with the
lowest lyricist-singer entropy. Our results suggest that further analyses of
the features contributing to lyric-lyricist classification performance on the
lowest lyricist-singer entropy group may improve the feature extraction task
for lyricists.


  Earth-like planets have viscoelastic mantles, whereas giant planets may have
viscoelastic cores. The tidal dissipation of such solid regions,
gravitationally perturbed by a companion body, highly depends on their rheology
and on the tidal frequency. Therefore, modelling tidal interactions presents a
high interest to provide constraints on planets' properties and to understand
their history and their evolution, in our Solar System or in exoplanetary
systems. We examine the equilibrium tide in the anelastic parts of a planet
whatever the rheology, taking into account the presence of a fluid envelope of
constant density. We show how to obtain the different Love numbers that
describe its tidal deformation. Thus, we discuss how the tidal dissipation in
solid parts depends on the planet's internal structure and rheology. Finally,
we show how the results may be implemented to describe the dynamical evolution
of planetary systems. The first manifestation of the tide is to distort the
shape of the planet adiabatically along the line of centers. Then, the response
potential of the body to the tidal potential defines the complex Love numbers
whose real part corresponds to the purely adiabatic elastic deformation, while
its imaginary part accounts for dissipation. This dissipation is responsible
for the imaginary part of the disturbing function, which is implemented in the
dynamical evolution equations, from which we derive the characteristic
evolution times. The rate at which the system evolves depends on the physical
properties of tidal dissipation, and specifically on how the shear modulus
varies with tidal frequency, on the radius and also the rheological properties
of the solid core. The quantification of the tidal dissipation in solid cores
of giant planets reveals a possible high dissipation which may compete with
dissipation in fluid layers.


  We study shear viscosity in weakly coupled hot pure gauge field QCD theory
basing on transport theory and the Kubo formula using the closed time path
formalism (CTP) of real time finite temperature field theory. We show that the
viscosity can be obtained as the integral of a retarded three-point function.
Non-perturbative corrections to the bare one loop result can be obtained by
solving a Schwinger-Dyson type integral equation for this vertex. This integral
equation represents the resummation of an infinite series of ladder diagrams
which all contribute to the leading-log order result. We show that this
integral equation has exactly the same form as the linearized Boltzmann
equation and explain the reason behind this formal equality.


  Camouflaged objects attempt to conceal their texture into the background and
discriminating them from the background is hard even for human beings. The main
objective of this paper is to explore the camouflaged object segmentation
problem, namely, segmenting the camouflaged object(s) for a given image. This
problem has not been well studied in spite of a wide range of potential
applications including the preservation of wild animals and the discovery of
new species, surveillance systems, search-and-rescue missions in the event of
natural disasters such as earthquakes, floods or hurricanes. This paper
addresses a new challenging problem of camouflaged object segmentation. To
address this problem, we provide a new image dataset of camouflaged objects for
benchmarking purposes. In addition, we propose a general end-to-end network,
called the Anabranch Network, that leverages both classification and
segmentation tasks. Different from existing networks for segmentation, our
proposed network possesses the second branch for classification to predict the
probability of containing camouflaged object(s) in an image, which is then
fused into the main branch for segmentation to boost up the segmentation
accuracy. Extensive experiments conducted on the newly built dataset
demonstrate the effectiveness of our network using various fully convolutional
networks. \url{https://sites.google.com/view/ltnghia/research/camo}


  A phenomenon of energy dissipation in Bose-Einstein condensates is studied
based on a microscopic model for the motion of impurity. Critical velocities
for onset of energy dissipation are obtained for periodic motions, such as a
dipole-like oscillation and a circular motion. The first example is similar to
a series of MIT group experiments settings where the critical velocity was
observed much below the Landau critical velocity. The appearance of the smaller
values for the critical velocity is also found in our model, even in the
homogeneous condensate in the thermodynamic limit. This suggests that the
landau criterion be reexamined in the absence of quantized vortices in the bulk
limit.


  In this article, we introduce the notion of Lie triple centralizer as
follows. Let $\mathcal{A}$ be an algebra, and $\phi:\mathcal{A}\to\mathcal{A}$
be a linear mapping. we say $\phi$ is a Lie triple centralizer whenever
$\phi([[a,b],c])=[[\phi(a),b],c]$ for all $a,b,c\in\mathcal{A}$. Then we
characterize the general form of Lie triple centralizers on generalized matrix
algebra $\mathcal{U}$ and under some mild conditions on $\mathcal{U}$, we
present the necessary and sufficient conditions for Lie triple centralizers to
be proper. As an application of our results, we characterize generalized Lie
triple derivations on generalized matrix algebras.


  In this paper we study iterative algorithms for finding a common element of
the set of fixed points of $\kappa$-strict pseudocontractions or finding a
solution of a variational inequality problem for a monotone, Lipschitz
continuous mapping. The last problem being related to finding fixed points of
pseudocontractions. These algorithms were already studied in [G.L. Acedo, H.-K.
Xu] and [N. Nadezhkina, W. Takahashi] but our aim here is to provide the links
between these know algorithms and the general framework of ${\cal T}$-class
algorithms studied in [H.H. Bauschke, P.L. Combettes].


  Motivated by recent experiments showing nonlinear elasticity of in vitro
networks of the biopolymer actin cross-linked with filamin, we present an
effective medium theory of flexibly cross-linked stiff polymer networks. We
model such networks by randomly oriented elastic rods connected by flexible
connectors to a surrounding elastic continuum, which self-consistently
represents the behavior of the rest of the network. This model yields a
crossover from a linear elastic regime to a highly nonlinear elastic regime
that stiffens in a way quantitatively consistent with experiment.


  The problem of unstable particle decay is discussed to show how elementarity
of a subsystem immersed in an infinitely larger environment is lost. The decay
law, when the same kind of particles as decay product make up a thermal medium,
is worked out in detail. The relic abundance of unstable particles does not
suffer from the Boltzmann suppression crucial at very low temperatures, because
the off shell contribution not considered in the Boltzmann approach, becomes
dominant at low temperatures. The short-time behavior of the non-decay
probability is also clarified, which is important to discuss physical relevance
of the non-observation of nucleon decay. Two powerful methods in this respect
are the operator and the path integral approach, both of which are reviewed.


  We study a neural network model of interacting stochastic discrete two--state
cellular automata on a regular lattice. The system is externally tuned to a
critical point which varies with the degree of stochasticity (or the effective
temperature). There are avalanches of neuronal activity, namely spatially and
temporally contiguous sites of activity; a detailed numerical study of these
activity avalanches is presented, and single, joint and marginal probability
distributions are computed. At the critical point, we find that the scaling
exponents for the variables are in good agreement with a mean--field theory.


  In this paper, I revisit the constraints obtained by several authors
(Reichart et al. 1999; Eke et al. 1998; Henry 2000) on the estimated values of
$\Omega_{\rm m}$, $n$ and $\sigma_8$ in the light of recent theoretical
developments: 1) new theoretical mass functions (Sheth & Tormen 1999, Sheth, Mo
& Tormen 2001, Del Popolo 2002b); 2) a more accurate mass-temperature relation,
also determined for arbitrary $\Omega_{\rm m}$ and $\Omega_{\rm \Lambda}$ (Del
Popolo 2002a). Firstly, using the quoted improvements, I re-derive an
expression for the X-ray Luminosity Function (XLF), similarly to Reichart et
al. (1999), and then I get some constraints to $\Omega_{\rm m}$ and $n$, by
using the {\it ROSAT} BCS and {\rm EMSS} samples and maximum-likelihood
analysis. Then I re-derive the X-ray Temperature Function (XTF), similarly to
Henry (2000), re-obtaining the constraints on $\Omega_{\rm m}$, $n$,
$\sigma_8$. Both in the case of the XLF and XTF, the changes in the mass
function and M-T relation produces an increase in $\Omega_{\rm m}$ of $ \simeq
20%$ and similar results in $\sigma_8$ and $n$.


  We used the data of 701 stars covering the colour index interval
0.32<B-V<=1.16, with metallicities -1.76<=[Fe/H]<=+0.40 dex, which were taken
from PASTEL catalogue and estimated metallicity dependent guillotine factors
which provide a more accurate metallicity calibration. We reduced the
metallicities of 11 authors to the metallicities of Valenti & Fischer (2005),
thus obtained a homogeneous set of data which increased the accuracy of the
calibration, i.e. [Fe/H]=-14.316*delta^{2}_{0.6}-3.557*delta_{0.6}+0.105.
Comparison of the metallicity residuals, for two sets of data, based on the
metallicity dependent guillotine factors with the ones obtained via metal free
guillotine factors, shows that metallicities estimated by means of new
guillotine factors are more accurate than the other ones. This advantage can be
used in the metallicity gradient investigation of the Galactic components, i.e.
thin disc, thick disc and halo.


  Recent observations of Jupiter and Saturn provided by spacecraft missions,
such as Juno and Cassini, compel us to revise and improve our models of giant
planet interiors. Even though hydrogen and helium are by far the dominant
species in these planets, heavy elements can play a significant role in the
structure and evolution of the planet. For instance, giant-planet cores may be
eroded by their surrounding fluid, which would result in a significantly
increased concentration of heavy elements in the hydrogen-helium envelope.
Furthermore, the heavy elements could inhibit convection by creating a
stabilizing gradient of composition. In order to explore the effects of core
erosion, we performed ab initio simulations to study structural, diffusion and
viscosity properties of dense multi-component mixtures of hydrogen, helium, and
silicon dioxide at relevant pressure-temperature conditions. We computed radial
distribution functions to identify changes in the chemical behavior of the
mixture and to reveal dissociation trends with pressure and temperature. The
computed diffusion coefficients of the different species as well as the
viscosity provide constraints for the time scale of the dynamics of the core
erosion and the mixing of its constituents into the envelope, which will help
improve planetary models.


  In the past three decades, the development of nuclear physics facilities for
fundamental and applied science purposes has required an increasing current of
multicharged ion beams. Multiple ionization implies the formation of dense and
energetic plasmas, which, in turn, requires specific plasma trapping
configurations. Two types of ion source have been able to produce very high
charge states in a reliable and reproducible way: electron beam ion sources
(EBIS) and electron cyclotron resonance ion sources (ECRIS). Multiple
ionization is also obtained in laser-generated plasmas (laser ion sources
(LIS)), where the high-energy electrons and the extremely high electron density
allow step-by-step ionization, but the reproducibility is poor. This chapter
discusses the atomic physics background at the basis of the production of
highly charged ions and describes the scientific and technological features of
the most advanced ion sources. Particular attention is paid to ECRIS and the
latest developments, since they now represent the most effective and reliable
machines for modern accelerators.


  In this talk, we present a global analysis of available small-x data on
inclusive DIS and exclusive diffractive processes, including the latest data
from the combined HERA analysis on reduced cross sections within the
Impact-Parameter dependent Saturation (IP-Sat) Model. The impact-parameter
dependence of dipole amplitude is crucial in order to have a unified
description of both inclusive and exclusive diffractive processes. With the
parameters of model fixed via a fit to the high-precision reduced
cross-section, we compare model predictions to data for the structure
functions, the longitudinal structure function, the charm structure function,
exclusive vector mesons production and Deeply Virtual Compton Scattering
(DVCS). Excellent agreement is obtained for the processes considered at small x
in a wide range of Q^2.


  The $F$ and $G$ form-factors of $K_{\ell4}$ and the quark condensates are
calculated to ${\cal O}(p^6)$ in Chiral Perturbation Theory (CHPT). Full
formulas are presented as much as possible. A full refit of most of the ${\cal
O}(p^4)$ CHPT parameters is done with a discussion of all inputs and underlying
assumptions. We discuss the consequences for the vacuum expectation values,
decay constants, pseudoscalar masses and $\pi$-$\pi$ scattering.


  We evaluate the induced value of Newton's constant which would arise in QCD.
The ingredients are modern lattice results, perturbation theory and the
operator product expansion. The resulting shift in the Planck mass is positive.
A scaled-up version of such a theory may be part of a quantum field theory
treatment of gravity.


  Semiconductors in all dimensionalities ranging from 0D quantum dots and
molecules to 3D bulk crystals support bound electron-hole pair quasiparticles
termed as excitons. Over the past two decades, the emergence of a variety of
low-dimensional semiconductors that support excitons combined with advances in
nano-optics and photonics has burgeoned a new area of research that focuses on
engineering, imaging, and modulating coupling between excitons and photons,
resulting in the formation of hybrid-quasiparticles termed exciton-polaritons.
This new area has the potential to bring about a paradigm shift in quantum
optics, as well as classical optoelectronic devices. Here, we present a review
on the coupling of light in excitonic semiconductors and investigation of the
unique properties of these hybrid quasiparticles via both far-field and
near-field imaging and spectroscopy techniques. Special emphasis is laid on
recent advances with critical evaluation of the bottlenecks that plague various
materials towards practical device implementations including quantum light
sources. Our review highlights a growing need for excitonic materials
development together with optical engineering and imaging techniques to harness
the utility of excitons and their host materials for a variety of applications.


  Multiquark systems appear less frequently than mesons and baryons despite the
enormous world-wide experimental effort that has been made during the last two
decades. In this work, we will propose a possible explanation for that fact,
restricting ourselves to the case of sets including only $c$ and $\bar{c}$
quarks. We will show that those multiquarks can be thought as different
combinations of smaller units that associate together to produce colorless
assemblies with a definite value of the total spin. For instance, for the
$cccccc$ hexaquark with $S=0$, we have three possibilities: a set of six
undistinguishable $c$ quarks, an association of two $ccc$ baryons, or a set of
three $cc$ diquarks close together. This means we can have three different
values for the mass of an open-charm hexaquark with $S=0$. Using the diffusion
Monte Carlo method, we calculate all possible combinations compatible with
tetraquark $cc \bar{c} \bar{c}$, pentaquark $cccc \bar{c}$, open-charm $cccccc$
and hidden-charm $ccc \bar{c} \bar{c} \bar{c}$ hexaquark structures with the
minimum value of total spin ($S=0$ or $S=1/2$). We consider compact structures
with radial wave functions including interactions between all the quarks in the
cluster. We find that, in all cases, the mass of the multiquark decreases with
the number of small units that conform the set of quarks. For instance, an open
charm hexaquark made up of three diquarks has a smaller mass than a set of six
of $c$ undistinguishable units. When the pieces that conform the multiquark are
themselves colorless with a definite value of the total spin, the cluster
splits into those smaller units that separate infinitely from each other.


  Extrapolation to unseen sequence lengths is a challenge for neural generative
models of language. In this work, we characterize the effect on length
extrapolation of a modeling decision often overlooked: predicting the end of
the generative process through the use of a special end-of-sequence (EOS)
vocabulary item. We study an oracle setting - forcing models to generate to the
correct sequence length at test time - to compare the length-extrapolative
behavior of networks trained to predict EOS (+EOS) with networks not trained to
(-EOS). We find that -EOS substantially outperforms +EOS, for example
extrapolating well to lengths 10 times longer than those seen at training time
in a bracket closing task, as well as achieving a 40% improvement over +EOS in
the difficult SCAN dataset length generalization task. By comparing the hidden
states and dynamics of -EOS and +EOS models, we observe that +EOS models fail
to generalize because they (1) unnecessarily stratify their hidden states by
their linear position is a sequence (structures we call length manifolds) or
(2) get stuck in clusters (which we refer to as length attractors) once the EOS
token is the highest-probability prediction.


  In the context of solving large distributed constraint optimization problems
(DCOP), belief-propagation and approximate inference algorithms are candidates
of choice. However, in general, when the factor graph is very loopy (i.e.
cyclic), these solution methods suffer from bad performance, due to
non-convergence and many exchanged messages. As to improve performances of the
Max-Sum inference algorithm when solving loopy constraint optimization
problems, we propose here to take inspiration from the
belief-propagation-guided dec-imation used to solve sparse random graphs
(k-satisfiability). We propose the novel DeciMaxSum method, which is
parameterized in terms of policies to decide when to trigger decimation, which
variables to decimate, and which values to assign to decimated variables. Based
on an empirical evaluation on a classical BP benchmark (the Ising model), some
of these combinations of policies exhibit better performance than
state-of-the-art competitors.


  We consider families of confocal conics and two pencils of Apollonian circles
having the same foci. We will show that these families of curves generate
trivial 3-webs and find the exact formulas describing them.


  Many self-propelled microorganisms are attracted to surfaces. This makes
their dynamics in restricted geometries very different from that observed in
the bulk. Swimming along walls is beneficial for directing and sorting cells,
but may be detrimental if homogeneous populations are desired, such as in
counting microchambers. In this work, we characterize the motion of human sperm
cells $60 \mu m$ long, strongly confined to $25 \mu m$ shallow chambers. We
investigate the nature of the cell trajectories between the confining surfaces
and their accumulation near the borders. Observed cell trajectories are
composed of a succession of quasi-circular and quasi-linear segments. This
suggests that the cells follow a path of intermittent trappings near the top
and bottom surfaces separated by stretches of quasi-free motion in between the
two surfaces, as confirmed by depth resolved confocal microscopy studies. We
show that the introduction of artificial petal-shaped corrugation in the
lateral boundaries removes the tendency of cells to accumulate near the
borders, an effect which we hypothesize may be valuable for microfluidic
applications in biomedicine.


  We analyze in detail the proposal for a two-qubit gate for travelling
single-photon qubits recently presented by C. Ottaviani \emph{et al}. [Phys.
Rev. A \textbf{73}, 010301(R) (2006)]. The scheme is based on an ensemble of
five-level atoms coupled to two quantum and two classical light fields. The two
quantum fields undergo cross-phase modulation induced by electromagnetically
induced transparency. The performance of this two-qubit quantum phase gate for
travelling single-photon qubits is thoroughly examined in the steady-state and
transient regimes, by means of a full quantum treatment of the system dynamics.
In the steady-state regime, we find a general trade-off between the size of the
conditional phase shift and the fidelity of the gate operation. However, this
trade-off can be bypassed in the transient regime, where a satisfactory gate
operation is found to be possible, significantly reducing the gate operation
time.


  As predictive models are increasingly being deployed in high-stakes decision
making (e.g., loan approvals), there has been growing interest in post hoc
techniques which provide recourse to affected individuals. These techniques
generate recourses under the assumption that the underlying predictive model
does not change. However, in practice, models are often regularly updated for a
variety of reasons (e.g., dataset shifts), thereby rendering previously
prescribed recourses ineffective. To address this problem, we propose a novel
framework, RObust Algorithmic Recourse (ROAR), that leverages adversarial
training for finding recourses that are robust to model shifts. To the best of
our knowledge, this work proposes the first solution to this critical problem.
We also carry out detailed theoretical analysis which underscores the
importance of constructing recourses that are robust to model shifts: 1) we
derive a lower bound on the probability of invalidation of recourses generated
by existing approaches which are not robust to model shifts. 2) we prove that
the additional cost incurred due to the robust recourses output by our
framework is bounded. Experimental evaluation on multiple synthetic and
real-world datasets demonstrates the efficacy of the proposed framework and
supports our theoretical findings.


  Modern remote sensing image change detection has witnessed substantial
advancements by harnessing the potent feature extraction capabilities of CNNs
and Transforms.Yet,prevailing change detection techniques consistently
prioritize extracting semantic features related to significant
alterations,overlooking the viability of directly interacting with bitemporal
image features.In this letter,we propose a bitemporal image graph Interaction
network for remote sensing change detection,namely BGINet-CD. More
specifically,by leveraging the concept of non-local operations and mapping the
features obtained from the backbone network to the graph structure space,we
propose a unified self-focus mechanism for bitemporal images.This approach
enhances the information coupling between the two temporal images while
effectively suppressing task-irrelevant interference,Based on a streamlined
backbone architecture,namely ResNet18,our model demonstrates superior
performance compared to other state-of-the-art methods (SOTA) on the GZ CD
dataset. Moreover,the model exhibits an enhanced trade-off between accuracy and
computational efficiency,further improving its overall effectiveness