  Parity-Time (PT)-symmetry is being actively investigated as a fundamental
property of observables in quantum physics. We show that the governing
equations of the classical two-fluid interaction and the incompressible fluid
system are PT-symmetric, and the well-known Kelvin-Helmholtz instability is the
result of spontaneous PT-symmetry breaking. It is expected that all classical
conservative systems governed by Newton's law admit PT-symmetry, and the
spontaneous breaking thereof is a generic mechanism for classical
instabilities. Discovering the PT-symmetry of systems in fluid dynamics and
plasma physics and identifying the PT-symmetry breaking responsible for
instabilities enable new techniques to classical physics and enrich the physics
of PT-symmetry.


  We introduce two new tools that can be useful in nonlinear observer and
output feedback design. The first one is a simple extension of the notion of
homogeneous approximation to make it valid both at the origin and at infinity
(homogeneity in the bi-limit). Exploiting this extension, we give several
results concerning stability and robustness for a homogeneous in the bi-limit
vector field. The second tool is a new recursive observer design procedure for
a chain of integrator. Combining these two tools, we propose a new global
asymptotic stabilization result by output feedback for feedback and feedforward
systems.


  In this work, we use 8 years of deep near-infrared imaging to select and
study a new set of 601 active galaxies identified through long-term
near-infrared (NIR) variability in the UKIDSS Ultra Deep Survey (UDS). These
objects are compared to 710 X-ray bright AGN detected by the Chandra X-ray
observatory. We show that infrared variability and X-ray emission select
distinct sets of active galaxies, finding only a 37 per cent overlap of
galaxies detected by both techniques and confirming NIR-variable AGN to be
typically X-ray quiet. Examining the mass functions of the active galaxies
shows that NIR variability detects AGN activity in galaxies over a
significantly wider range of host stellar mass compared to X-ray detection. For
example, at z $\sim$ 1, variable AGN are identified among approximately 1 per
cent of galaxies in a roughly flat distribution above the stellar mass
completeness limit (> 10$^{9}$M$_{\odot}$), while X-ray detection primarily
identifies AGN in galaxies of higher mass (> 10$^{10}$M$_{\odot}$). We conclude
that long-term near-infrared variability provides an important new tool for
obtaining more complete samples of AGN in deep survey fields.


  The theoretical understanding of density waves in disk galaxies starts from
the classical WKB perturbative analysis of tight-winding perturbations, the key
assumption being that the potential due to the density wave is approximately
radial. The above has served as a valuable guide in aiding the understanding of
both simulated and observed galaxies, in spite of a number of caveats being
present. The observed spiral or bar patterns in real galaxies are frequently
only marginally consistent with the tight-winding assumption, often in fact,
outright inconsistent. Here we derive a complementary formulation to the
problem, by treating quasi-radial density waves under simplified assumptions in
the linear regime. We assume that the potential due to the density wave is
approximately tangential, and derive the corresponding dispersion relation of
the problem. We obtain an instability criterion for the onset of quasi-radial
density waves, which allows a clear understanding of the increased stability of
the higher order modes, which appear at progressively larger radii, as often
seen in real galaxies. The theory naturally yields a range of pattern speeds
for these arms which appears constrained by the condition
$\Omega_{p}<\Omega_{0} \pm \kappa /m$. For the central regions of galaxies
where solid body rotation curves might apply, we find weak bars in the
oscillatory regime with various pattern speeds, including counter rotating
ones, and a prediction for $\Omega_{p}$ to increase towards the centre, as seen
in the rapidly rotating bars within bars of some numerical simulations. We
complement this study with detailed numerical simulations of galactic disks and
careful Fourier analysis of the emergent perturbations, which support the
theory presented.


  In this review, we discuss inflation models based on supergravity. After
explaining the difficulties in realizing inflation in the context of
supergravity, we show how to evade such difficulties. Depending on types of
inflation, we give concrete examples, particularly paying attention to chaotic
inflation because the ongoing experiments like Planck might detect the tensor
perturbations in near future. We also discuss inflation models in Jordan frame
supergravity, motivated by Higgs inflation.


  We summarize studies of growing lengths in different aging systems. The
article is structured as follows. We recall the definition of a number of
observables, typically correlations and susceptibilities, that give access to
dynamic and static correlation lengths. We use a growing length perspective to
review three out of equilibrium cases: domain growth phenomena; the evolution
of Edwards-Wilkinson and Kardar-Parisi-Zhang manifolds and other directed
elastic manifolds in random media; spin and structural glasses in relaxation
and under an external drive. Finally, we briefly report on a mechanism for
dynamic fluctuations in aging systems that is based on a time-reparametrization
invariance scenario and may be at the origin of the dynamic growing length in
glassy materials.


  We give a short introduction to operator quantum error correction. This is a
new protocol for error correction in quantum computing that has brought the
fundamental methods under a single umbrella, and has opened up new
possibilities for protecting quantum information against undesirable noise. We
describe the various conditions that characterize correction in this scheme.


  Most existing recommendation approaches implicitly treat user tastes as
unimodal, resulting in an average-of-tastes representations when multiple
distinct interests are present. We show that appropriately modelling the
multi-faceted nature of user tastes through a mixture-of-tastes model leads to
large increases in recommendation quality. Our result holds both for deep
sequence-based and traditional factorization models, and is robust to careful
selection and tuning of baseline models. In sequence-based models, this
improvement is achieved at a very modest cost in model complexity, making
mixture-of-tastes models a straightforward improvement on existing baselines.


  We investigate the problem of joint statistical estimation of several
parameters for a stochastic differential equation driven by an additive
fractional Brownian motion. Based on discrete-time observations of the model,
we construct an estimator of the Hurst parameter, the diffusion parameter and
the drift, which lies in a parametrised family of coercive drift coefficients.
Our procedure is based on the assumption that the stationary distribution of
the SDE and of its increments permits to identify the parameters of the model.
Under this assumption, we prove consistency results and derive a rate of
convergence for the estimator. Finally, we show that the identifiability
assumption is satisfied in the case of a family of fractional
Ornstein-Uhlenbeck processes and illustrate our results with some numerical
experiments.


  In many wireless systems, the channel state information at the transmitter
(CSIT) can not be learned until after a transmission has taken place and is
thereby outdated. In this paper, we study the benefits of delayed CSIT on a
block-fading channel at finite blocklength. First, the achievable rates of a
family of codes that allows the number of codewords to expand during
transmission, based on delayed CSIT, are characterized. A fixed-length and a
variable-length characterization of the rates are provided using the dependency
testing bound and the variable-length setting introduced by Polyanskiy et al.
Next, a communication protocol based on codes with expandable message space is
put forth, and numerically, it is shown that higher rates are achievable
compared to coding strategies that do not benefit from delayed CSIT.


  We consider the Arveson-Douglas conjecture on the essential normality of
homogeneous submodules corresponding to algebraic subvarieties of the unit
ball. We prove that the property of essential normality is preserved by
isomorphisms between varieties, and we establish a similar result for maps
between varieties that are not necessarily invertible. We also relate the
decomposability of an algebraic variety to the problem of establishing the
essential normality of the corresponding submodule. These results are applied
to prove that the Arveson-Douglas conjecture holds for submodules corresponding
to varieties that decompose into linear subspaces, and varieties that decompose
into components with mutually disjoint linear spans.


  Turbulence may have been produced in the early universe during several kind
of non-equilibrium processes. Periods of cosmic turbulence may have left a
detectable relic in the form of stochastic backgrounds of gravitational waves.
In this paper we derive general expressions for the power spectrum of the
expected signal. Extending previous works on the subject, we take into account
the effects of a continuous energy injection power and of magnetic fields. Both
effects lead to considerable deviations from the Kolmogorov turbulence
spectrum. We applied our results to determine the spectrum of gravity waves
which may have been produced by neutrino inhomogeneous diffusion and by a first
order phase transition. We show that in both cases the expected signal may be
in the sensitivity range of LISA.


  The major loss mechanism of photogenerated polarons was investigated in
P3HT:PCBM solar cells by the photo-CELIV technique. For pristine and annealed
devices, we find that the experimental data can be explained by a bimolecular
recombination rate reduced by a factor of about ten (pristine) and 25
(annealed) as compared to Langevin theory. Aided by a macroscopic device model,
we discuss the implications of the lowered loss rate on the characteristics of
polymer:fullerene solar cells.


  Fracture surfaces provide various types of information about fracture. The
fracture toughness $K_{{\rm I}c}$, which represents the resistance to fracture,
can be estimated using the three-dimensional (3D) information of a fracture
surface, i.e., its roughness. However, this is time-consuming and expensive to
obtain the 3D information of a fracture surface; thus, it is desirable to
estimate $K_{{\rm I}c}$ from a two-dimensional (2D) image, which can be easily
obtained. In recent years, methods of estimating a 3D structure from its 2D
image using deep learning have been rapidly developed. In this study, we
propose a framework for fractography that directly estimates $K_{{\rm I}c}$
from a 2D fracture surface image using deep neural networks (DNNs). Typically,
image recognition using a DNN requires a tremendous amount of image data, which
is difficult to acquire for fractography owing to the high experimental cost.
To compensate for the limited data, in this study, we used the transfer
learning (TL) method, and constructed high-performance prediction models even
with a small dataset by transferring machine learning models trained using
other large datasets. We found that the regression model obtained using our
proposed framework can predict $K_{{\rm I}c}$ in the range of approximately 1-5
[MPa$\sqrt{m}$] with a standard deviation of the estimation error of
approximately $\pm$0.37 [MPa$\sqrt{m}$]. The present results demonstrate that
the DNN trained with TL opens a new route for quantitative fractography by
which parameters of fracture process can be estimated from a fracture surface
even with a small dataset. The proposed framework also enables the building of
regression models in a few hours. Therefore, our framework enables us to screen
a large number of image datasets available in the field of materials science
and find candidates that are worth expensive machine learning analysis.


  Terahertz radiation has broad application prospect due to its ability to
penetrate deep into many organic materials without damage caused by ionizing
radiations. A FEL-based THz source is the best choice to produce high-power
radiation. In this paper, a 14 MeV injector is introduced for generating
high-quality beam for FEL, which is composed of an EC-ITC RF gun, compensating
coils and a travelling-wave structure. Start-to-end simulation has been done
with ASTRA code to verify the design and to optimize parameters. Simulation of
operating mode at 6 MeV is also executed.


  We show that the combined dimming of Type Ia supernovae induced by both a
cosmological constant and the conversion of photons into axions in
extra-galactic magnetic fields can impersonate dark energy with an equation of
state w < -1. An observer unaware of the presence of photon-axion conversion
would interpret the additional dimming as cosmic acceleration faster than that
induced by a cosmological constant alone. We find that this mechanism can mimic
equations of state as negative as w \simeq - 1.5. Our model does not have any
ghosts, phantoms and the like. It is fully consistent with the conventional
effective field theory in curved space, and all existing observational
constraints on the axions are obeyed.


  Cognitive radio networks (CRNs) have emerged as a promising solution to
enhance spectrum utilization by using unused or less used spectrum in radio
environments. The basic idea of CRNs is to allow secondary users (SUs) access
to licensed spectrum, under the condition that the interference perceived by
the primary users (PUs) is minimal. In CRNs, the channel availability is
uncertainty due to the existence of PUs, resulting in intermittent
communication. Transmission control protocol (TCP) performance may
significantly degrade in such conditions. To address the challenges, some
transport protocols have been proposed for reliable transmission in CRNs. In
this paper we survey the state-of-the-art transport protocols for CRNs. We
firstly highlight the unique aspects of CRNs, and describe the challenges of
transport protocols in terms of PU behavior, spectrum sensing, spectrum
changing and TCP mechanism itself over CRNs. Then, we provide a summary and
comparison of existing transport protocols for CRNs. Finally, we discuss
several open issues and research challenges. To the best of our knowledge, our
work is the first survey on transport protocols for CRNs.


  There is a major opportunity for the KDUST 2.5m telescope to carry out the
next generation IR survey. A resolution of 0.2 arcsec is obtainable from Dome A
over a wide field. This opens a unique discovery space during the 2015-2025
decade. A next generation 2 micron survey will feed JWST with serendipitous
targets for spectroscopy, including spectra and images of the first galaxies.


  We prove `twisted' versions of Kirchhoff's network theorem and Kirchhoff's
matrix-tree theorem on connected finite graphs. Twisting here refers to chains
with coefficients in a flat unitary line bundle.


  In this paper, we investigate inhomogeneous and simultaneous Diophantine
approximation in beta dynamical systems. For $\beta>1$ let $T_{\beta}$ be the
$\beta$-transformation on $[0,1]$. We determine the Lebesgue measure and
Hausdorff dimension of the set \[\left\{(x,y)\in [0,1]^2:
|T_{\beta}^nx-f(x,y)|<\varphi(n)\text{ for infinitely many
}n\in\mathbb{N}\right\},\] where $f:[0,1]^2\to [0,1]$ is a Lipschitz function
and $\varphi$ is a positive function on $\mathbb{N}$. Let $\beta_2\geq
\beta_1>1$, $f_1,f_2:[0,1]\to [0,1]$ be two Lipschitz functions,
$\tau_1,\tau_2$ be two positive continuous functions on $[0,1]$. We also
determine the Hausdorff dimension of the set \[\left\{(x,y)\in [0,1]^2:
\begin{aligned}&|T_{\beta_1}^nx-f_1(x)|<\beta_1^{-n\tau_1(x)}\\
&|T_{\beta_2}^ny-f_2(y)|<\beta_2^{-n\tau_2(y)}\end{aligned}\text{ for
infinitely many }n\in\mathbb{N}\right\}.\] Under certain additional
assumptions, the Hausdorff dimension of the set \[\left\{(x,y)\in [0,1]^2:
\begin{aligned}&|T_{\beta_1}^nx-g_1(x,y)|<\beta_1^{-n\tau_1(x)}\\
&|T_{\beta_2}^ny-g_2(x,y)|<\beta_2^{-n\tau_2(y)}\end{aligned}\text{ for
infinitely many }n\in\mathbb{N}\right\}\] is also determined, where
$g_1,g_2:[0,1]^2\to [0,1]$ are two Lipschitz functions.


  In the absence of a theory of everything, modern physicists need to rely on
other predictive tools and turned to Effective Field Theories (EFTs) in a
number of fields, including but not limited to statistical mechanics, condensed
matter, particle physics, cosmology and gravity. The coefficients of an EFT can
be constrained with high precision by experiments, which can involve
high-energy particle colliders for instance but are generally left free from
the theoretical point of view. The focus of this thesis is to use various
consistency criteria to get theoretical constraints on the low-energy
coefficients of EFTs. In particular, we construct a new model of massive spin-1
field by requiring that the theory is free of any ghostly degree of freedom. We
then study its cosmological perturbations and ask that all propagating modes
are stable and subluminal, reducing the space of viable cosmological solutions.
Finally, we implement a method to get 'causality bounds', which are obtained by
requiring infrared causality. This is imposed by forbidding any resolvable time
advance in the EFT. We derive such 'causality bounds' for shift-symmetric and
Galileon scalar EFTs, before turning to gauge-symmetric vector fields. We prove
that our causality bounds can be competitive with positivity bounds and can
even be used in scenarios that are out of reach of the positivity approach. The
result of this thesis, by exploring several consistency criteria, is to provide
compact causality bounds for low-energy EFT coefficients, in addition to
constraints coming from the absence of ghosts, stability and cosmological
viability.


  The electronic excitations of manganese phthalocyanine (MnPc) films were
studied as a function of potassium doping using electron energy-loss
spectroscopy in transmission. Our data reveal doping induced changes in the
excitation spectrum, and they provide evidence for the existence of three doped
phases: K$_1$MnPc, K$_2$MnPc, and K$_4$MnPc. Furthermore, the addition of
electrons first leads to a filling of orbitals with strong Mn 3d character, a
situation which also affects the magnetic moment of the molecule.


  We investigate the estimation of orbital parameters by least-$\chi^2$
Keplerian fits to radial velocity (RV) data using synthetic data sets. We find
that while the fitted period is fairly accurate, the best-fit eccentricity and
$M_p\sin i$ are systematically biased upward from the true values for low
signal-to-noise ratio $K/\sigma\lesssim 3$ and moderate number of observations
$N_{\rm obs}\lesssim 60$, leading to a suppression of the number of nearly
circular orbits. Assuming intrinsic distributions of orbital parameters, we
generate a large number of mock RV data sets and study the selection effect on
the eccentricity distribution. We find the overall detection efficiency only
mildly decreases with eccentricity. This is because although high eccentricity
orbits are more difficult to sample, they also have larger RV amplitudes for
fixed planet mass and orbital semi-major axis. Thus the primary source of
uncertainties in the eccentricity distribution comes from biases in Keplerian
fits to detections with low-amplitude and/or small $N_{\rm obs}$, rather than
from selection effects. Our results suggest that the abundance of
low-eccentricity exoplanets may be underestimated in the current sample and we
urge caution in interpreting the eccentricity distributions of low-amplitude
detections in future RV samples.


  Here we report a TiHfNbTa bulk medium-entropy alloy (MEA) superconductor
crystallized in the body-centered cubic structure, which is synthesized by an
arc melting method. Superconducting properties of the TiHfNbTa are studied by
employing magnetic susceptibility, resistivity, and specific heat measurements.
Experimental results show a bulk superconducting transition temperature (Tc) of
around 6.75 K. The lower and upper crit-ical fields for TiHfNbTa are 45.8 mT
and 10.46 T, respectively. First-principles calculations show that the d
electron of Ti, Hf, Nb, and Ta is the main contribution near the Fermi level.
Our results indicate that the superconductivity is a conven-tional s-wave type
with extremely strong coupling. The extremely strong coupling behavior in the
s-wave type TiHfNbTa MEA superconductor is unusual because it generally happens
in cuprates, pnictides, and other unconventional superconductors.


  The AUGER Collaboration has recently published the precise energy spectrum of
cosmic rays above 1 EeV, which exhibits rich and interesting features. These
features provide an opportunity to investigate the galactic propagation and
interaction of ultra-high-energy cosmic rays (UHECRs). While the classic dip
model, which describes the UHECR propagation and interaction with CMB in
extragalactic space by theoretical calculation, well explains the cutoff
behaviour of the highest high energy spectrum of AUGER, it fails to describe
the low energy features. It indicates that the galactic propagation and
interaction of UHECR might play an important role in modulating the low energy
side of AUGER spectrum. With the disk-halo diffusion model, this work
demonstrates excellent agreement with the energy spectrum measured by AUGER and
supports that the diffusion coefficient follows a power-law with an index of
$1.81^{+0.05}_{-0.04}$ in the galaxy at least above $5\times10^{18}$eV. The
inferred diffusion coefficient is one to two order of magnitude smaller than
these extrapolated from low energy studies when conventional model parameters
are adopted. Study of the modulation effect at cluster of galaxy level might be
needed.


  We describe possible kaon physics goals to achieve with a high luminosity
phi-factory. We motivate the relevance to improve the present bounds on CPT
kaon physics quantities. Also, the interferometer machine phi-factory is useful
to study CP violating/conserving effects in kaon decays. Thus we investigate K
--> 3 pi amplitudes: charge asymmetries are interesting in charged kaon decays.
In the case of neutral kaon decays one can study directely K_S --> 3 pi or
interferences effects. Interference may also be used to study the CP even K_S
-->pi+ pi- pi0 and final state interactions.


  Mining attacks aim to gain an unfair share of extra rewards in the blockchain
mining. Selfish mining can preserve discovered blocks and strategically release
them, wasting honest miners' computing resources and getting higher profits.
Previous mining attacks either conceal the mined whole blocks (hiding or
discarding), or release them completely in a particular time slot (e.g.,
causing a fork). In this paper, we extend the mining attack's strategy space to
partial block sharing, and propose a new and feasible Partial Selfish Mining
(PSM) attack. We show that by releasing partial block data publicly and
attracting rational miners to work on attacker's private branch, attackers and
these attracted miners can gain an unfair share of mining rewards. We then
propose Advanced PSM (A-PSM) attack that can further improve attackers' profits
to be no less than the selfish mining. Both theoretical and experimental
results show that PSM attackers can be more profitable than selfish miners
under a certain range of mining power and network conditions. A-PSM attackers
can gain even higher profits than both selfish mining and honest mining with
attracted rational miners.


  Retrieval plays a fundamental role in recommendation systems, search, and
natural language processing by efficiently finding relevant items from a large
corpus given a query. Dot products have been widely used as the similarity
function in such retrieval tasks, thanks to Maximum Inner Product Search (MIPS)
that enabled efficient retrieval based on dot products. However,
state-of-the-art retrieval algorithms have migrated to learned similarities.
Such algorithms vary in form; the queries can be represented with multiple
embeddings, complex neural networks can be deployed, the item ids can be
decoded directly from queries using beam search, and multiple approaches can be
combined in hybrid solutions. Unfortunately, we lack efficient solutions for
retrieval in these state-of-the-art setups. Our work investigates techniques
for approximate nearest neighbor search with learned similarity functions. We
first prove that Mixture-of-Logits (MoL) is a universal approximator, and can
express all learned similarity functions. We next propose techniques to
retrieve the approximate top K results using MoL with a tight bound. We finally
compare our techniques with existing approaches, showing that MoL sets new
state-of-the-art results on recommendation retrieval tasks, and our approximate
top-k retrieval with learned similarities outperforms baselines by up to two
orders of magnitude in latency, while achieving > .99 recall rate of exact
algorithms.


  In the Italian education system, secondary students (ages 14-19) face the
foundations of quantum physics during the final term of scientific high school
(pre-university year). The Italian Ministry of Education, University and
Research (MIUR) has remarked its importance in the syllabus to address the high
school exit examination (30% of the 5th year physics course) but, due to
limited learning time and intrinsic difficulty, this branch of physics is
neither assimilated nor appreciated as it should. We wish to illustrate six
didactic suggestions focused on learning motivation, emerged during a 17-year
long teaching experience, which could help to tackle the main problems found.
The key reference is the talk "Why nobody understands quantum mechanics?" given
in 2013 at the 2nd Rome workshop "Science Perception" together with a concise
and evocative poster outlining the history of quanta. Other useful resources
are a 2015 conceptual diagram and four invited lectures held in the years
2010-2017.


  We study Wronskians of Appell polynomials indexed by integer partitions.
These families of polynomials appear in rational solutions of certain
Painlev\'e equations and in the study of exceptional orthogonal polynomials. We
determine their derivatives, their average and variance with respect to
Plancherel measure, and introduce several recurrence relations. In addition, we
prove an integrality conjecture for Wronskian Hermite polynomials previously
made by the first and last authors. Our proofs all exploit strong connections
with the theory of symmetric functions.


  We determine the image of the braid groups inside the Iwahori-Hecke algebras
of type A, when defined over a finite field, in the semisimple case, and for
suitably large (but controlable) order of the defining (quantum) parameter.


  We analyze upper limits on a possible gluon mass, $m_g$. We first discuss
various ways to modify quantum chromodynamics to include $m_g \ne 0$, including
a bare mass, a Higgs mechanism, and dynamical breaking of color SU(3)$_c$. From
an examination of experimental data, we infer an upper limit $m_g < O(1)$ MeV.
We discuss subtleties in interpreting gluon mass limits in view of the fact
that at scales below $\Lambda_{QCD}$, quantum chromodynamics is strongly
coupled, perturbation theory is not reliable, and the physics is not accurately
described in terms of the Lagrangian degrees of freedom, including gluons. We
also point out a fundamental difference in the behavior of quantum
chromodynamics with a nonzero gluon mass and a weakly coupled gauge theory with
a gauge boson mass.


  Quantum dots can be formed in simple GaN/AlGaN field-effect-transistors
(FETs) by disordered potential induced by impurities and defects. Here, we
investigate the channel length dependence of the formation of quantum dots. We
observe decrease of the number of formed quantum dots with decrease of the FET
channel length. A few quantum dots are formed in the case with the gate length
of 0.05~$\mu $m and we evaluate the dot parameters and the disordered
potential. We also investigate the effects of a thermal cycle and illumination
of light, and reveal the change of the disordered potential.


  DADApy is a python software package for analysing and characterising
high-dimensional data manifolds. It provides methods for estimating the
intrinsic dimension and the probability density, for performing density-based
clustering and for comparing different distance metrics. We review the main
functionalities of the package and exemplify its usage in toy cases and in a
real-world application. DADApy is freely available under the open-source Apache
2.0 license.


  We explore the feasibility of learning the connection between SDSS galaxies
and ELUCID subhaloes with random forest (RF). ELUCID is a constrained $N$-body
simulation constructed using the matter density field of SDSS. Based on an
SDSS-ELUCID matched catalogue, we build RF models that predict $M_r$ magnitude,
colour, stellar mass $M_*$, and specific star formation rate (sSFR) with
several subhalo properties. While the RF can predict $M_r$ and $M_*$ with
reasonable accuracy, the prediction accuracy of colour and sSFR is low, which
could be due to the mismatch between galaxies and subhaloes. To test this, we
shuffle the galaxies in subhaloes of narrow mass bins in the local
neighbourhood using galaxies of a semi-analytic model (SAM) and the TNG
hydrodynamic simulation. We find that the shuffling only slightly reduces the
colour prediction accuracy in SAM and TNG, which is still considerably higher
than that of the SDSS. This suggests that the true connection between SDSS
colour and subhalo properties could be weaker than that in the SAM and TNG
without the mismatch effect. We also measure the Pearson correlation
coefficient between galaxy properties and the subhalo properties in SDSS, SAM,
and TNG. Similar to the RF results, we find that the colour-subhalo correlation
in SDSS is lower than both the SAM and TNG. We also show that the
galaxy-subhalo correlations depend on subhalo mass in the galaxy formation
models. Advanced surveys with more fainter galaxies will provide new insights
into the galaxy-subhalo relation in the real Universe.


  We consider an analytical signal control problem on a signalized network
whose traffic flow dynamic is described by the Lighthill-Whitham-Richards (LWR)
model (Lighthill and Whitham, 1955; Richards, 1956). This problem explicitly
addresses traffic-derived emissions as side constraints. We seek to tackle this
problem using a mixed integer mathematical programming approach. Such a class
of problems, which we call LWR-Emission (LWR-E), has been analyzed before to
certain extent. Since mixed integer programs are practically efficient to solve
in many cases (Bertsimas et al., 2011b), the mere fact of having integer
variables is not the most significant challenge to solving LWR-E problems;
rather, it is the presence of the potentially nonlinear and nonconvex
emission-related constraints/objectives that render the program computationally
expensive. To address this computational challenge, we proposed a novel
reformulation of the LWR-E problem as a mixed integer linear program (MILP).
This approach relies on the existence of a statistically valid macroscopic
relationship between the aggregate emission rate and the vehicle occupancy of
the same link. This relationship is approximated with certain functional forms
and the associated uncertainties are handled explicitly using robust
optimization (RO) techniques. The RO allows emissions-related constraints
and/or objectives to be reformulated as linear forms under mild conditions. To
further reduce the computational cost, we employ the link transmission model to
describe traffic dynamics with the benefit of fewer (integer) variables and
less potential traffic holding. The proposed MILP explicitly captures vehicle
spillback, avoids traffic holding, and simultaneously minimizes travel delay
and addresses emission-related concerns.


  Many outdoor autonomous mobile platforms require more human identity
anonymized data to power their data-driven algorithms. The human identity
anonymization should be robust so that less manual intervention is needed,
which remains a challenge for current face detection and anonymization systems.
In this paper, we propose to use the skeleton generated from the
state-of-the-art human pose estimation model to help localize human heads. We
develop criteria to evaluate the performance and compare it with the face
detection approach. We demonstrate that the proposed algorithm can reduce
missed faces and thus better protect the identity information for the
pedestrians. We also develop a confidence-based fusion method to further
improve the performance.


  So far, all relativistically boosted jets with superluminal motion have only
been detected in typical radio galaxies with early type host galaxies. We have
now discovered superluminal motion in the Seyfert I galaxy III Zw 2, classified
as a spiral. The lower limit for the apparent expansion speed is 1.25 c.
Spectral and spatial evolution are closely linked. Before and after this rapid
expansion we have seen a period of virtually no expansion with an expansion
speed less than 0.04 c. However, at 15 GHz the picture is completely different.
III Zw 2 shows slow expansion ($\sim 0.6 c$) during the time of no expansion at
43 GHz and no expansion during the rapid expansion at 43 GHz. The difference
between the two frequencies is qualitatively explained by optical-depth effects
in an 'inflating- balloon model', describing the evolution of radio lobes on an
ultra-compact scale. The stop-and-go behavior could be explained by a jet
interacting with a molecular cloud or the molecular torus. Since III Zw 2 is
also part of a sample of so- called radio-intermediate quasars (RIQ), it
confirms earlier predictions of superluminal motion for this source, based on
the argument that RIQs could be relativistically boosted jets in radio-weak
quasars and Seyfert galaxies.


  This study on public-private research collaboration measures the variation
over time of the propensity of academics to collaborate with colleagues from
private companies. It also investigates the change in weights of the main
drivers underlying the academics' propensity to collaborate, and whether the
type profile of the collaborating academics changes. To do this, the study
applies an inferential model on a dataset of professors working in Italian
universities in consecutive periods, 2010-2013 and 2014-2017. The results,
obtained at overall and field levels, support the formulation of policies aimed
at fostering public-private research collaborations, and should be taken into
account in post-assessment of their effectiveness.


  For a gerbe $\Y$ over a smooth proper Deligne-Mumford stack $\B$ banded by a
finite group $G$, we prove a structure result on the Gromov-Witten theory of
$\Y$, expressing Gromov-Witten invariants of $\Y$ in terms of Gromov-Witten
invariants of $\B$ twisted by various flat $U(1)$-gerbes on $\B$. This is
interpreted as a Leray-Hirsch type of result for Gromov-Witten theory of
gerbes.


  Changes in the level of synchronization and desynchronization in coupled
oscillator systems due to an external stimulus is called event related
synchronization or desynchronization (ERS/ERD). Such changes occur in real life
systems where the collective activity of the entities of a coupled system is
affected by some external influence. In order to understand the role played by
the external influence in the occurrence of ERD and ERS, we study a system of
coupled nonlinear oscillators in the presence of an external stimulus signal.
We find that the phenomena of ERS and ERD are generic and occur in all types of
coupled oscillator systems. We also find that the same external stimulus signal
can cause ERS and ERD depending upon the strength of the signal. We identify
the stability of the ERS and ERD states and also find analytical and numerical
boundaries between the different synchronization regimes involved in the
occurrence of ERD and ERS.


  The production of high-mass, color-singlet particles in hadron colliders is
universally accompanied by initial state QCD radiation that is predominantly
soft with respect to the hard process scale $Q$ and/or collinear with respect
to the beam axis. At TeV-scale colliders, this is in contrast to top quark and
multijet processes, which, by definition, are hard and central. Consequently,
vetoing events with jets possessing transverse momenta above $p_T^{\rm Veto}$
in searches for new color-singlet states can efficiently reduce non-singlet
backgrounds, thereby increasing experimental sensitivity. To quantify this
generic observation, we investigate the production and leptonic decay of a
Sequential Standard Model $W'$ boson at the 13 TeV LHC. We systematically
consider signal and background processes at next-to-leading-order (NLO) in QCD
with parton shower (PS) matching; for color-singlet channels, we resum Sudakov
logarithms of the form $\alpha_s^j(p_T^{\rm Veto})\log^k(Q/p_T^{\rm Veto})$ up
to next-to-next-to-leading logarithmic accuracy (NNLL) with NLO matching. We
obtain our results using the MadGraph5aMC@NLO and MadGraph5aMC@NLO-SCET
frameworks, respectively. Associated FeynRules model files capable of handling
NLO+PS- and NLO+NNLL-accurate computations are publicly available. We find that
within their given uncertainties, both the NLO+PS and NLO+NNLL(veto)
calculations give accurate and consistent predictions. Consequently, jet vetoes
applied to color-singlet processes can be reliably modeled at the NLO+PS level.
With respect to a $b$-jet veto of $p_{T}^{\rm Veto} = 30$ GeV, flavor-agnostic
vetoes of $p_{T}^{\rm Veto} = 30-40$ GeV can further reduce single top and
$t\overline{t}$ rates by a factor of 2-50 at a mild cost of the signal rate.
Jet vetoes can increase signal-to-noise ratios by roughly 10\% for light $W'$
boson masses of 30-50 GeV and 25\%-250\% for masses of 300-800 GeV.


  This paper shows that quantization induces a Lawvere-Tierney topology on
(hence, a sheaf topos in) the quantum topos. We show that a quantization map
from classical observables to self-adjoint operators on a Hilbert space
naturally induces geometric morphisms from presheaf topoi related to the
classical system into a presheaf topos, called the quantum topos, on the
context category consisting of commutative von Neumann algebras of bounded
operators on the Hilbert space. By means of the geometric morphisms, we define
Lawvere-Tierney topologies on the quantum topos (and their equivalent
Grothendieck topologies on the context category). We show that, among them, we
can uniquely select the most informative one, which we call the quantization
topology. We furthermore construct sheaves induced by the quantization
topology. This can be done in an elementary and self-contained way, because the
quantization topology has a quite simple expression.


  This note is motivated by the article by F. Lutscher, E. Pachepsky, and M.
Lewis (2005), The Effect of Dispersal Patterns on Stream Populations SIAM Rev.
Vol. 47 No. 4 pp. 749-772 on the drift paradox. We consider the case of a
regime switching probabilistic model for a population of organisms living in a
one dimensional environment with drift towards an absorbing boundary of the
type introduced by Lutscher et al. (2005). In particular, the two regimes
consist of birth/death style demographics governing the evolution of the
immobile regime, and some form of advection-dispersion governing the evolution
of the mobile regime, together with a regime-switching mechanism linking the
two. In the present note it is shown for the regime-switching model, and in
contrast to the results in the afore cited work, for any finite advection
speed, no matter how large, there is a finite critical length of the domain
above which the population can persist.


  Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost
one fifth of hospitalized patients, as well as more than half of the patients
who are admitted to the intensive care unit (ICU). Stratifying AKI patients
into groups based on severity and duration would facilitate more targeted
efforts for treating AKI. Methods: In a retrospective, multicenter and
longitudinal cohort study of 935,679 patients who were admitted between 2012
and 2020 to health centers included in OneFlorida+ Network, we analyzed the
impact of AKI trajectories which are rapidly reversed AKI, persistent AKI with
renal recovery, and persistent AKI without renal recovery on patients' clinical
outcomes, including hospital, 30-day, 1-year, and 3-year mortality, kidney
replacement therapy, new chronic kidney disease (CKD) within 90 days or 1-year
of discharge, CKD progression within 1-year of discharge, resource utilization,
hospital disposition, and major complications during hospitalization. As
analytical approaches, Kaplan-Meier estimators and survival curves, Cox
proportional-hazards regression model, logistic regression model,
Kruskal-Wallis test, analysis of variance, chi-square, Fisher's exact test were
used. Results: Among 2,187,254 encounters, 14% had AKI, of which 63%, 21%, and
16% had Stage 1, 2, and 3, respectively, as the worst AKI stage. Fraction of
patients with persistent AKI was 31%. Patients with AKI had worse clinical
outcomes and increased resource utilization compared to patients without the
condition. One-year mortality was 5 times greater for patients with persistent
AKI compared to those without AKI. Conclusions: Persistent AKI was associated
with prolonged hospitalization, increased ICU admission and mortality compared
to the other groups. This may emphasize the critical need for devising
strategies targeting effective management of AKI and prevention of persisting
AKI.


  We introduce a computationally efficient method based on the path integral
formalism to describe defect-modified graphene. By taking into account the
entire Brillouin zone, our approach respects the lattice symmetry and can be
used to investigate both short-range and long-range effects. The proposed
method's key advantage is that the computational complexity does not increase
with the system size, scaling, instead, with the number of defects. As a
demonstration of our method, we explore the graphene-mediated RKKY interaction
between multiple magnetic impurities. Our results concur with earlier findings
by showing that the interaction strength and sign depend on various factors
like impurity separation, sublattice arrangement, and system doping. We
demonstrate that frustration can be introduced between the impurity spins by
controlling their relative positions and that this frustration can be switched
on and off by tuning the chemical potential of the system.


  We extend Carleson's interpolation Theorem to sequences of matrices, by
giving necessary and sufficient separation conditions for a sequence of
matrices to be interpolating.


  Charges as small as 1 pC degrade the performance of high precision inertial
reference instruments when accumulated on their test masses (TMs). Non-contact
charge management systems are required for the most sensitive of these
instruments, with the TMs free-floating, and their charges compensated by
photoelectrons in a feedback loop with a TM charge measurement. Three space
missions have successfully demonstrated this technique: GP-B, LPF, and the
UV-LED mission. Charge management techniques that eliminate the charge
measurement and feedback systems, referred henceforth as passive, reduce the
complexities and disturbance effects introduced by these systems, and are thus
the subject of active research and development work. Passive charge management
depends critically on the stability and reproducibility of the photoemission
properties of a given system. In support of this work, we present comprehensive
flight characterization data for a suite of 16 UV-LEDs in various
configurations and 255+/-1 nm center wavelength. Flight data was acquired
between December 2014 and December 2015 with the UV-LED instrument flown on
SaudiSat 4. We back up our results with ground-based measurements performed in
configurations comparable to the flight one between September 4, 2020, and
October 8, 2020. All results confirm the excellent reliability of the UV-LEDs
in the space environment, are fully consistent with the findings of ground
studies, and support the approach of using LEDs for passive charge management.
We find that the equilibrium potential of the TM, under illumination by the 255
nm LEDs, is independent of the UV intensity and reproduceable to about +/- 6
mV, or +/-6 fC/pF, over periods of up to six months. The value of the
equilibrium potential is dependent on the geometry of the electric field
between the TM and its enclosure, and thus on the exact configuration of the
instrument.


  We study operator complexity on various time scales with emphasis on those
much larger than the scrambling period. We use, for systems with a large but
finite number of degrees of freedom, the notion of K-complexity employed in
arXiv:1812.08657 for infinite systems. We present evidence that K-complexity of
ETH operators has indeed the character associated with the bulk time evolution
of extremal volumes and actions. Namely, after a period of exponential growth
during the scrambling period the K-complexity increases only linearly with time
for exponentially long times in terms of the entropy, and it eventually
saturates at a constant value also exponential in terms of the entropy. This
constant value depends on the Hamiltonian and the operator but not on any
extrinsic tolerance parameter. Thus K-complexity deserves to be an entry in the
AdS/CFT dictionary. Invoking a concept of K-entropy and some numerical examples
we also discuss the extent to which the long period of linear complexity growth
entails an efficient randomization of operators.


  In a universal framework that expresses any market system in terms of state
transition rules, we prove that every DeFi market system has an invariant
function and is thus by definition a CFMM; indeed, all automated market makers
(AMMs) are CFMMs.
  Invariants connect directly to arbitrage and to completeness, according to
two fundamental equivalences. First, a DeFi market system is, we prove,
arbitrage-free if and only if it has a strictly increasing invariant, where
arbitrage-free means that no state can be transformed into a dominated state by
any sequence of transactions. Second, the invariant is, we prove, unique if and
only if the market system is complete, meaning that it allows transitions
between all pairs of states in the state space, in at least one direction.
  Thus a necessary and sufficient condition for no-arbitrage (respectively, for
completeness) is the existence of the increasing (respectively, the uniqueness
of the) invariant, which, therefore, fulfills in nonlinear DeFi theory the
foundational role parallel to the existence (respectively, uniqueness) of the
pricing measure in the Fundamental Theorem of Asset Pricing for linear markets.
  Moreover, a market system is recoverable by its invariant if and only if it
is complete; and in all cases, complete or incomplete, every market system has,
and is recoverable by, a multi-invariant. A market system is arbitrage-free if
and only if its multi-invariant is increasing.
  Our examples illustrate (non)existence of various specific types of arbitrage
in the context of various specific types of market systems -- with or without
fees, with or without liquidity operations, and with or without coordination
among multiple pools -- but the fundamental theorems have full generality,
applicable to any DeFi market system and to any notion of arbitrage expressible
as a strict partial order.


  We develop a novel framework for single-scene video anomaly localization that
allows for human-understandable reasons for the decisions the system makes. We
first learn general representations of objects and their motions (using deep
networks) and then use these representations to build a high-level,
location-dependent model of any particular scene. This model can be used to
detect anomalies in new videos of the same scene. Importantly, our approach is
explainable - our high-level appearance and motion features can provide
human-understandable reasons for why any part of a video is classified as
normal or anomalous. We conduct experiments on standard video anomaly detection
datasets (Street Scene, CUHK Avenue, ShanghaiTech and UCSD Ped1, Ped2) and show
significant improvements over the previous state-of-the-art.


  The problem is sequence prediction in the following setting. A sequence
$x_1,...,x_n,...$ of discrete-valued observations is generated according to
some unknown probabilistic law (measure) $\mu$. After observing each outcome,
it is required to give the conditional probabilities of the next observation.
The measure $\mu$ belongs to an arbitrary but known class $C$ of stochastic
process measures. We are interested in predictors $\rho$ whose conditional
probabilities converge (in some sense) to the "true" $\mu$-conditional
probabilities if any $\mu\in C$ is chosen to generate the sequence. The
contribution of this work is in characterizing the families $C$ for which such
predictors exist, and in providing a specific and simple form in which to look
for a solution. We show that if any predictor works, then there exists a
Bayesian predictor, whose prior is discrete, and which works too. We also find
several sufficient and necessary conditions for the existence of a predictor,
in terms of topological characterizations of the family $C$, as well as in
terms of local behaviour of the measures in $C$, which in some cases lead to
procedures for constructing such predictors. It should be emphasized that the
framework is completely general: the stochastic processes considered are not
required to be i.i.d., stationary, or to belong to any parametric or countable
family.


  This paper presents a case study for the application of semiring semantics
for fixed-point formulae to the analysis of strategies in B\"uchi games.
Semiring semantics generalizes the classical Boolean semantics by permitting
multiple truth values from certain semirings. Evaluating the fixed-point
formula that defines the winning region in a given game in an appropriate
semiring of polynomials provides not only the Boolean information on who wins,
but also tells us how they win and which strategies they might use. This is
well-understood for reachability games, where the winning region is definable
as a least fixed point. The case of B\"chi games is of special interest, not
only due to their practical importance, but also because it is the simplest
case where the fixed-point definition involves a genuine alternation of a
greatest and a least fixed point.
  We show that, in a precise sense, semiring semantics provide information
about all absorption-dominant strategies - strategies that win with minimal
effort, and we discuss how these relate to positional and the more general
persistent strategies. This information enables applications such as game
synthesis or determining minimal modifications to the game needed to change its
outcome.


  We present a kinetic model of crystal growth of polymers of finite molecular
weight. Experiments help to classify polymer crystallization broadly into two
kinetic regimes. One is observed in melts or in high molar mass polymer
solutions and is dominated by nucleation control with $G \sim \exp(1/T \Delta
T)$, where $G$ is the growth rate and $\Delta T$ is the super-cooling. The
other is observed in low molar mass solutions (as well as for small molecules)
and is diffusion controlled with $G \sim \Delta T$, for small $\Delta T$. Our
model unifies these two regimes in a single formalism. The model accounts for
the accumulation of polymer chains near the growth front and invokes an
entropic barrier theory to recover both limits of nucleation and diffusion
control. The basic theory applies to both melts and solutions, and we
numerically calculate the growth details of a single crystal in a dilute
solution. The effects of molecular weight and concentration are also determined
considering conventional polymer dynamics. Our theory shows that entropic
considerations, in addition to the traditional energetic arguments, can capture
general trends of a vast range of phenomenology. Unifying ideas on
crystallization from small molecules and from flexible polymer chains emerge
from our theory.


  In this paper we find smooth embeddings of solenoids in smooth foliations. We
show that if a smooth foliation F of a manifold M contains a compact leaf L
with H^1(L;R)= 0 and if the foliation is a product foliation in some saturated
open neighbourhood U of L, then there exists a foliation F' on M which is
C^1-close to F, and F' has an uncountable set of solenoidal minimal sets
contained in U that are pair wise non-homeomorphic. If H^1(L;R) is not 0, then
it is known that any sufficiently small perturbation of F contains a saturated
product neighbourhood. Thus, our result can be thought of as an instability
result complementing the stability results of Reeb, Thurston and Langevin and
Rosenberg.


  Recently measured high precision data of fusion excitation function have
enabled a detailed study on the effects of nuclear collective excitations on
fusion reactions. Using such highly accurate data of the $^{16}$O +
$^{144,148}$Sm reactions, we discuss the anharmonic properties of collective
phonon excitations in $^{144,148}$Sm nuclei. It is shown that subbarrier fusion
reactions are strongly affected by the anharmonic effects and thus offer an
alternative method to extract the static quadrupole moments of phonon states in
a spherical nucleus.


  We resolve Schinzel's Hypothesis (H) for $100\%$ of polynomials of arbitrary
degree.
  We deduce that a positive proportion of diagonal conic bundles over
$\mathbb{Q}$ with any given number of degenerate fibres have a rational point,
and obtain similar results for generalised Ch\^atelet equations.


  We study here the topology of information on the space of probability
measures over Polish spaces that was defined in Hellwig (1996). We show that
under this topology, a convergent sequence of probability measures satisfying a
conditional independence property converges to a measure that also satisfies
the same conditional independence property. This also corrects the proof of a
claim in Hellwig (1996, Lemma 4). Additionally, we determine sufficient
conditions on the Polish spaces and the topology over measures spaces under
which a convergent sequence of probability measures is also convergent in the
topology of information.


  I present a scheme of drawing causal diagrams based on physically motivated
mathematical models expressed in terms of temporal differential equations. They
provide a means of better understanding the processes and causal relationships
contained within such systems.


  In this paper, we prove the existence of the spreading speed of nonlocal KPP
equations in two cases: 1. The media is almost periodic and the kernel of
diffusion is continuous; 2. The media is periodic and the diffusion is not
continuous but weak irreducible. To do this, we develop the theory of
generalized principal eigenvalues, the method homogenization and special
Harnack's inequalities of nonlocal diffusion equations.


  Generative AI (GAI) is impacting teaching and learning directly or indirectly
across a range of subjects and disciplines. As educators, we need to understand
the potential and limitations of AI in HCI education and ensure our graduating
HCI students are aware of the potential and limitations of AI in HCI. In this
paper, we report on the main pedagogical insights gained from the inclusion of
generative AI into a 10 week undergraduate module. We designed the module to
encourage student experimentation with GAI models as part of the design brief
requirement and planned practical sessions and discussions. Our insights are
based on replies to a survey sent out to the students after completing the
module. Our key findings, for HCI educators, report on the use of AI as a
persona for developing project ideas and creating resources for design, and AI
as a mirror for reflecting students' understanding of key concepts and ideas
and highlighting knowledge gaps. We also discuss potential pitfalls that should
be considered and the need to assess students' literacies and assumptions of
GAIs as pedagogical tools. Finally, we put forward the case for educators to
take the opportunities GAI presents as an educational tool and be experimental,
creative, and courageous in their practice. We end with a discussion of our
findings in relation to the TPACK framework in HCI.


  The out of equilibrium dynamics of finite dimensional spin glasses is
considered from a point of view going beyond the standard `mean-field theory'
versus `droplet picture' debate of the last decades. The main predictions of
both theories concerning the spin glass dynamics are discussed. It is shown, in
particular, that predictions originating from mean-field ideas concerning the
violations of the fluctuation-dissipation theorem apply quantitatively,
provided one properly takes into account the role of the spin glass coherence
length which plays a central role in the droplet picture. Dynamics in a uniform
magnetic field is also briefly discussed.


  Gradient compression has surfaced as a key technique to address the challenge
of communication efficiency in distributed learning. In distributed deep
learning, however, it is observed that gradient distributions are heavy-tailed,
with outliers significantly influencing the design of compression strategies.
Existing parameter quantization methods experience performance degradation when
this heavy-tailed feature is ignored. In this paper, we introduce a novel
compression scheme specifically engineered for heavy-tailed gradients, which
effectively combines gradient truncation with quantization. This scheme is
adeptly implemented within a communication-limited distributed Stochastic
Gradient Descent (SGD) framework. We consider a general family of heavy-tail
gradients that follow a power-law distribution, we aim to minimize the error
resulting from quantization, thereby determining optimal values for two
critical parameters: the truncation threshold and the quantization density. We
provide a theoretical analysis on the convergence error bound under both
uniform and non-uniform quantization scenarios. Comparative experiments with
other benchmarks demonstrate the effectiveness of our proposed method in
managing the heavy-tailed gradients in a distributed learning environment.


  In a recent paper, Krawczyk proved that there are continuum many axiomatic
extensions of global consequence associated with the modal system $E$ that do
not admit the local deduction detachment theorem. In algebraic parlance, he
showed that there are continuum many varieties of modal algebras lacking the
congruence extension property. In this paper, we extend Krawczyk's results and
construct a continuum of varieties of modal algebras that do not have the
congruence extension property, but that do admit other, logically relevant
properties, such as monotonicity, extensiveness, idempotency, normality, etc.
This gives a continuum of axiomatic extensions of the corresponding modal
systems not having the local deduction detachment theorem.


  One dominant aspect of cities is transport and massive passenger mobilization
which remains a challenge with the increasing demand on the public as cities
grow. In addition, public transport infrastructure suffers from traffic
congestion and deterioration, reducing its efficiency. In this paper, we study
the capacity of transport in 33 worldwide metro systems under the accumulation
of damage. We explore the gradual reduction of functionality in these systems
associated with damage that occurs stochastically. The global transport of each
network is modeled as the diffusive movement of Markovian random walkers on
networks considering the capacity of transport of each link, where these links
are susceptible to damage. Monte Carlo simulations of this process in metro
networks show the evolution of the functionality of the system under damage
considering all the complexity in the transportation structure. This
information allows us to compare and classify the effect of damage in metro
systems. Our findings provide a general framework for the characterization of
the capacity to maintain the transport under failure in different systems
described by networks.


  Centuries of development in natural sciences and mathematical modeling
provide valuable domain expert knowledge that has yet to be explored for the
development of machine learning models. When modeling complex physical systems,
both domain knowledge and data provide necessary information about the system.
In this paper, we present a data-driven model that takes advantage of partial
domain knowledge in order to improve generalization and interpretability. The
presented approach, which we call EVGP (Explicit Variational GaussianProcess),
has the following advantages: 1) using available domain knowledge to improve
the assumptions(inductive bias) of the model, 2) scalability to large datasets,
3) improved interpretability. We show how the EVGP model can be used to learn
system dynamics using basic Newtonian mechanics as prior knowledge. We
demonstrate how the addition of prior domain-knowledge to data-driven models
outperforms purely data-driven models.


  We prove that the control polygon of a Bezier curve B becomes homeomorphic
and ambient isotopic to B via subdivision, and we provide closed-form formulas
to compute the number of iterations to ensure these topological
characteristics. We first show that the exterior angles of control polygons
converge exponentially to zero under subdivision.


  The seminal work of DiPerna and Lions [Invent. Math., 98, 1989] guarantees
the existence and uniqueness of regular Lagrangian flows for Sobolev vector
fields. The latter is a suitable selection of trajectories of the related ODE
satisfying additional compressibility/semigroup properties. A long-standing
open question is whether the uniqueness of the regular Lagrangian flow is a
corollary of the uniqueness of the trajectory of the ODE for a.e. initial
datum. Using Ambrosio's superposition principle we relate the latter to the
uniqueness of positive solutions of the continuity equation and we then provide
a negative answer using tools introduced by Modena and Sz\'ekelyhidi in the
recent groundbreaking work [Ann. PDE, 4, 2018]. On the opposite side, we
introduce a new class of asymmetric Lusin-Lipschitz inequalities and use them
to prove the uniqueness of positive solutions of the continuity equation in an
integrability range which goes beyond the DiPerna-Lions theory.


  Accurate and fast assessment of resection margins is an essential part of a
dermatopathologist's clinical routine. In this work, we successfully develop a
deep learning method to assist the pathologists by marking critical regions
that have a high probability of exhibiting pathological features in Whole Slide
Images (WSI). We focus on detecting Basal Cell Carcinoma (BCC) through semantic
segmentation using several models based on the UNet architecture. The study
includes 650 WSI with 3443 tissue sections in total. Two clinical
dermatopathologists annotated the data, marking tumor tissues' exact location
on 100 WSI. The rest of the data, with ground-truth section-wise labels, is
used to further validate and test the models. We analyze two different encoders
for the first part of the UNet network and two additional training strategies:
a) deep supervision, b) linear combination of decoder outputs, and obtain some
interpretations about what the network's decoder does in each case. The best
model achieves over 96%, accuracy, sensitivity, and specificity on the test
set.


  We present for the first time, discharge-free operation at cryogenic
conditions of a Resistive-Plate WELL (RPWELL) detector. It is a single-sided
Thick Gaseous Electron Multiplier (THGEM) coupled to a readout anode via a
plate of high bulk resistivity. The results of single- and double-stage RPWELL
detectors operated in stable conditions in Ne/5$\%$CH$_{4}$ at 163 K are
summarized. The RPWELL comprised a ferric-based (Fe$^{3+}$) ceramic composite
("Fe-ceramic") as the resistive plate, of volume resistivity $\sim$$10^{11}$
$\Omega$$\cdot$cm at this temperature. Gains of $\sim$$10^{4}$ and
$\sim$$10^{5}$ were reached with the single-stage RPWELL, with 6 keV X-rays and
single UV-photons, respectively. The double-stage detector, a THGEM followed by
the RPWELL, reached gains $\sim$$10^{5}$ and $\sim$$10^{6}$ with X-rays and
single UV-photons, respectively. The results were obtained with and without a
CsI photocathode on the first multiplying element. Potential applications at
these cryogenic conditions are discussed.


  Based on the hadronic model with the gauge prescription suggested by Ohta and
Haberzettl, we investigate the possibility of determining the parity state of
the $\Theta^+$ baryon using photon induced processes, $\gamma n\to K^-
\Theta^+$ and $\gamma p\to \bar{K}^0 \Theta^+$. The total and differential
cross sections are simulated in two versions of pseudovector(PV) and
pseudoscalar(PS) coupling schemes and the results are reported both on the
positive and negative parity states of the $\Theta^+$ baryon. It is found that
in both coupling schemes the total cross sections from the neutron target are
in general larger than those from the proton target, regardless of the
$\Theta^+$ parities. The cross sections of the $\Theta^+$ production however
depend largely on the value of the $\Theta^+$ decay width which is not yet well
established. Moreover, there is a wide theoretical uncertainty associated with
the different assumption on the gauge prescription in model calculations. We
discuss these points by comparing theoretical predictions with the existing
experimental data. Our analysis suggests that the observation of the angular
distribution rather than just the total cross section in the photoproduction
process may be a useful tool to distinguish the parity of the $\Theta^+$
baryon.


  We propose a model to learn visually grounded word embeddings (vis-w2v) to
capture visual notions of semantic relatedness. While word embeddings trained
using text have been extremely successful, they cannot uncover notions of
semantic relatedness implicit in our visual world. For instance, although
"eats" and "stares at" seem unrelated in text, they share semantics visually.
When people are eating something, they also tend to stare at the food.
Grounding diverse relations like "eats" and "stares at" into vision remains
challenging, despite recent progress in vision. We note that the visual
grounding of words depends on semantics, and not the literal pixels. We thus
use abstract scenes created from clipart to provide the visual grounding. We
find that the embeddings we learn capture fine-grained, visually grounded
notions of semantic relatedness. We show improvements over text-only word
embeddings (word2vec) on three tasks: common-sense assertion classification,
visual paraphrasing and text-based image retrieval. Our code and datasets are
available online.


  Pretrained Language Models (PLMs) store extensive knowledge within their
weights, enabling them to recall vast amount of information. However, relying
on this parametric knowledge brings some limitations such as outdated
information or gaps in the training data. This work addresses these problems by
distinguish between two separate solutions: knowledge editing and knowledge
augmentation. We introduce Difference Injection for Efficient Knowledge
Augmentation and Editing (DIEK\AE), a new method that decouples knowledge
processing from the PLM (LLaMA2-7B, in particular) by adopting a series of
encoders. These encoders handle external knowledge and inject it into the PLM
layers, significantly reducing computational costs and improving performance of
the PLM. We propose a novel training technique for these encoders that does not
require back-propagation through the PLM, thus greatly reducing the memory and
time required to train them. Our findings demonstrate how our method is faster
and more efficient compared to multiple baselines in knowledge augmentation and
editing during both training and inference. We have released our code and data
at https://github.com/alessioGalatolo/DIEKAE.


  With hybrid organic-inorganic perovskites increasing its technological reach,
from photovoltaics solar cells to light-emitting devices, to nanoscale
transistors, it is critical to establish the role of microstructures in
dictating how carrier dynamics dictate device efficiency. Here we report on the
ultrafast dynamics of charge carriers in hybrid perovskites at various stages
of nucleation and growth kinetics. A solution-processed fabrication technique,
with spin-coating conditions optimized to control the nucleation density of an
intermediate phase, converts to hybrid perovskites upon a temperature gradient
annealing. This strategy decouples the nucleation and growth steps that lead
eventually to large-grain thin films, allowing us to probe electronic and
carrier dynamic differences. We find, surprisingly, that the nucleating
microcrystals already display the electronic properties of hybrid perovskites
and share similar femtosecond-to-nanosecond dynamics as large-grain hybrid
perovskite thin films.


  Reductions in the cost of PV and batteries encourage households to invest in
PV battery prosumage. We explore the implications for the rest of the power
sector by applying two open-source techno-economic models to scenarios in
Western Australia for the year 2030. Household PV capacity generally
substitutes utility PV, but slightly less so as additional household batteries
are installed. Wind power is less affected, especially in scenarios with higher
shares of renewables. With household batteries operating to maximise
self-consumption, utility battery capacities are hardly substituted. Wholesale
prices to supply households, including those not engaging in prosumage,
slightly decrease, while prices for other consumers slightly increase. We
conclude that the growth of prosumage has implications on the various elements
of the power sector and should be more thoroughly considered by investors,
regulators, and power sector planners.


  We consider the spacetime dynamics of a gas of closed strings in the context
of General Relativity in a background of arbitrary spatial dimensions. Our
motivation is primarily late time String Gas Cosmology, where such a spacetime
picture has to emerge after the dilaton has stabilized. We find that after
accounting for the thermodynamics of a gas of strings, only string modes which
are massless at the self-dual radius are relevant, and that they lead to a
dynamics which is qualitatively different from that induced by the modes
usually considered in the literature. In the context of an ansatz with three
large spatial dimensions and an arbitrary number of small extra dimensions, we
obtain isotropic stabilization of these extra dimensions at the self-dual
radius. This stabilization occurs for fixed dilaton, and is induced by the
special string states we focus on. The three large dimensions undergo a regular
Friedmann-Robertson-Walker expansion. We also show that this framework for
late-time cosmology is consistent with observational bounds.


  Coded caching is used to reduce network congestion during peak hours. A
single server is connected to a set of users through a bottleneck link, which
generally is assumed to be error-free. During non-peak hours, all the users
have full access to the files and they fill their local cache with portions of
the files available. During delivery phase, each user requests a file and the
server delivers coded transmissions to meet the demands taking into
consideration their cache contents. In this paper we assume that the shared
link is error prone. A new delivery scheme is required to meet the demands of
each user even after receiving finite number of transmissions in error. We
characterize the minimum average rate and minimum peak rate for this problem.
We find closed form expressions of these rates for a particular caching scheme
namely \textit{symmetric batch prefetching}. We also propose an optimal error
correcting delivery scheme for coded caching problem with symmetric batch
prefetching.


  In this paper, we describe the properties of the $i$-components of Hamming
codes. We suggest constructions of the admissible families of components of
Hamming codes. It is shown that every $q$-ary code of length $m$ and minimum
distance 5 (for $q = 3$ the minimum distance is 3) can be embedded in a $q$-ary
1-perfect code of length $n = (q^{m}-1)/(q-1)$. It is also shown that every
binary code of length $m + k$ and minimum distance $3k + 3$ can be embedded in
a binary 1-perfect code of length $n = 2^{m}-1$.


  Theoretically calculated power spectra are compares with observed solar
p-mode velocity power spectra over a range of mode degree and frequency. The
depth for the sources responsible for exciting p-modes of frequency 2.0 mHz is
determined from the asymmetry of their power spectra and found to be about 800
km below the photosphere for quadrupole sources and 150 km if sources are
dipole. The source depth for high frequency oscillations of frequency greater
than about 6 mHz is 180 (50) km for quadrupole (dipole) sources.


  General types of Bose-Einstein condensates are considered. The formation of
black-hole analogues is examined for both short- and long-range interactions
for arbitrary spatial dimensions greater than two. The former case includes
non-linear derivative terms plus an inevitable external potential, while the
latter one consists solely of gravity-like self-interactions for which
intrinsic formation of analogue Schwarzschild-type background space-times is
possible. The corresponding geometries are studied, and it is shown how they
can be made stable. Their Hawking temperature is estimated, and it is found
that in certain set-ups it can be significantly increased, thus providing
better detectability.


  The author was informed that the result in the original version had been
obtained earlier by K. Ueda (arXiv:math/0503355 [math.AG]). The paper is
retracted.


  The fracture process of commercially pure titanium was visualized in model
materials containing artificial holes. These model materials were fabricated
using a femtosecond laser coupled with a diffusion bonding technique to obtain
voids in the interior of titanium samples. Changes in void dimensions during
in-situ straining were recorded in three dimensions using x-ray computed
tomography. Void growth obtained experimentally was compared with the Rice and
Tracey model which predicted well the average void growth. A large scatter in
void growth data was explained by differences in grain orientation which was
confirmed by crystal plasticity simulations. It was also shown that grain
orientation has a stronger effect on void growth than intervoid spacing and
material strength. Intervoid spacing, however, appears to control whether the
intervoid ligament failure is ductile or brittle.


  Protocol for a Systematic Mapping of the Literature, which aims to identify
and classify the estimations techniques used in software development agile
methodologies based on the results found, and to compare their estimation
accuracies against those obtained in traditional software development
methodologies.


  We study an opinion formation model that takes into account that individuals
have diverse preferences when forming their opinion regarding a particular
issue. We show that the system exhibits a phenomenon called "diversity-induced
resonance"[Tessone et al. Phys. Rev. Lett. 97, 194101 (2006)], by which an
external influence (for example advertising, or fashion trends) is better
followed by populations having the right degree of diversity in their
preferences, rather than others where the individuals are identical or have too
different preferences. We support our findings by numerical simulations of the
model and a mean-field type analytical theory.


  Let $B$ be a $\mathbb{Z}$-graded Lie superalgebra equipped with an invariant
$\mathbb{Z}_2$-symmetric homogeneous bilinear form and containing a grading
element. Its local part (in the terminology of Kac) $B_{-1} \oplus B_{0} \oplus
B_{1}$ gives rise to another $\mathbb{Z}$-graded Lie superalgebra, recently
constructed in arXiv:2207.12417, that we here denote $B^W$ and call the
cartanification of $B^W$, since it is of Cartan type in the cases where it
happens to finite-dimensional. In cases where $B$ is given by a generalised
Cartan matrix, we compare $B^W$ to the tensor hierarchy algebra $W$ constructed
from the same generalised Cartan matrix by a modification of the generators and
relations. We generalise this construction and give conditions under which $W$
and $B^W$ are isomorphic, proving a conjecture in arXiv:2207.12417. We expect
that the algebras with restricted associativity underlying the cartanifications
will be useful in applications of tensor hierarchy algebras to the field of
extended geometry in physics.


  We have analyzed 16 years of observations dedicated to the Crab (pulsar +
nebula) with the INTEGRAL SPI instrument to investigate its polarization
properties. We find that the source presents a substantially polarized emission
(PF = 24%) in the hard X-ray domain, with the electric vector aligned with the
pulsar spin axis, in agreement with other results at various wavelengths. The
stability of the polarization characteristics with energy and over the 16 years
covered by the data is remarkable, completing the standard candle status of the
source in the spectral domain. The polarization measurements imply that the
synchrotron emission is the dominant mechanism of photon production from radio
to hard X-rays. The high level of polarized emission points out the steadiness
of the source, in particular of the magnetic field configuration and geometry.


  Ptychography is an imaging technique which involves a sample being
illuminated by a coherent, localized probe of illumination. When the probe
interacts with the sample, the light is diffracted and a diffraction pattern is
detected. Then the sample (or probe) is shifted laterally in space to
illuminate a new area of the sample whilst ensuring sufficient overlap.
Near-field Ptychography (NFP) occurs when the sample is placed at a short
defocus distance having a large Fresnel number. In this paper, we prove that
certain NFP measurements are robustly invertible (up to an unavoidable global
phase ambiguity) by constructing a point spread function and physical mask
which leads to a well-conditioned lifted linear system. We then apply a block
phase retrieval algorithm using weighted angular synchronization and prove that
the proposed approach accurately recovers the measured sample. Finally, we also
propose using a Wirtinger Flow for NFP problems and numerically evaluate that
alternate approach both against our main proposed approach, as well as with NFP
measurements for which our main approach does not apply.


  In many real-world scientific problems, generating ground truth (GT) for
supervised learning is almost impossible. The causes include limitations
imposed by scientific instrument, physical phenomenon itself, or the complexity
of modeling. Performing artificial intelligence (AI) tasks such as
segmentation, tracking, and analytics of small sub-cellular structures such as
mitochondria in microscopy videos of living cells is a prime example. The 3D
blurring function of microscope, digital resolution from pixel size, optical
resolution due to the character of light, noise characteristics, and complex 3D
deformable shapes of mitochondria, all contribute to making this problem GT
hard. Manual segmentation of 100s of mitochondria across 1000s of frames and
then across many such videos is not only herculean but also physically
inaccurate because of the instrument and phenomena imposed limitations.
Unsupervised learning produces less than optimal results and accuracy is
important if inferences relevant to therapy are to be derived. In order to
solve this unsurmountable problem, we bring modeling and deep learning to a
nexus. We show that accurate physics based modeling of microscopy data
including all its limitations can be the solution for generating simulated
training datasets for supervised learning. We show here that our
simulation-supervised segmentation approach is a great enabler for studying
mitochondrial states and behaviour in heart muscle cells, where mitochondria
have a significant role to play in the health of the cells. We report
unprecedented mean IoU score of 91% for binary segmentation (19% better than
the best performing unsupervised approach) of mitochondria in actual microscopy
videos of living cells. We further demonstrate the possibility of performing
multi-class classification, tracking, and morphology associated analytics at
the scale of individual mitochondrion.


  Laboratory automation is an expensive and complicated endeavor with limited
inflexible options for small-scale labs. We develop a prototype system for
tending to a bench-top centrifuge using computer vision methods for color
detection and circular Hough Transforms to detect and localize centrifuge
buckets. Initial results show that the prototype is capable of automating the
usage of regular bench-top lab equipment.


  Several multiscale methods account for sub-grid scale features using coarse
scale basis functions. For example, in the Multiscale Finite Volume method the
coarse scale basis functions are obtained by solving a set of local problems
over dual-grid cells. We introduce a data-driven approach for the estimation of
these coarse scale basis functions. Specifically, we employ a neural network
predictor fitted using a set of solution samples from which it learns to
generate subsequent basis functions at a lower computational cost than solving
the local problems. The computational advantage of this approach is realized
for uncertainty quantification tasks where a large number of realizations has
to be evaluated. We attribute the ability to learn these basis functions to the
modularity of the local problems and the redundancy of the permeability patches
between samples. The proposed method is evaluated on elliptic problems yielding
very promising results.


  We address the issue of the fallacy of the gauge concept in electromagnetism.
The role of groupthink in the perpetuation of this concept in the physics
literature is also discussed. Brief, elementary arguments suffice to
demonstrate the fallacy. The simplicity of the proofs indicates that the norms
of the scientific method have been neglected on this topic.


  We study quantum frequency translation and two-color photon interference
enabled by the Bragg scattering four-wave mixing process in optical fiber.
Using realistic model parameters, we computationally and analytically determine
the Green function and Schmidt modes for cases with various pump-pulse lengths.
These cases can be categorized as either "non-discriminatory" or
"discriminatory" in regards to their propensity to exhibit high-efficiency
translation or high-visibility two-photon interference for many different
shapes of input wave packets or for only a few input wave packets,
respectively. Also, for a particular case, the Schmidt mode set was found to be
nearly equal to a Hermite-Gaussian function set. The methods and results also
apply with little modification to frequency conversion by sum-frequency
conversion in optical crystals.


  Atomic clocks play a vital role in fundamental science and practical
technology. However, their sensitivity is typically limited by the standard
quantum limit, which is determined by parallel measurements with individual
particles or repeated measurements with a single particle. Overcoming this
limitation requires exploiting correlations between particles or interrogation
times. While it has been demonstrated that sensitivity can be improved to the
Heisenberg limit by utilizing quantum entanglement, it remains unclear whether
the scaling of sensitivity with respect to total interrogation time can achieve
the Heisenberg scaling. Here, we develop an adaptive Bayesian frequency
estimation protocol that approaches the Heisenberg scaling and experimentally
demonstrate its validity with a cold-atom coherent-population-trapping clock.
In further, we achieve robust closed-loop locking of the atomic clock by
utilizing our Bayesian frequency estimation protocol. In comparison with the
conventional clock locking, our Bayesian clock locking yields an improvement of
5.1(4) dB in fractional frequency stability. Our findings not only provide an
alternative approach to locking atomic clocks but also hold promising
applications in other quantum sensors, such as quantum magnetometers and atomic
interferometers.


  We present a novel background-independent framework for cosmic inflation,
starting with a matrix model. In this framework, inflation is portrayed as a
dynamic process responsible for the generation of both space and time. This
stands in contrast to conventional inflation, which is characterized as a mere
(exponential) expansion of an already existing spacetime, driven by the vacuum
energy associated with an inflaton field. We observe that the cosmic inflation
is triggered by the condensate of Planck energy into vacuum and responsible for
the dynamical emergence of spacetime. The emergent spacetime picture admits a
background-independent formulation so that the inflation is described by a
conformal Hamiltonian system which requires neither an inflaton field nor an ad
hoc inflation potential. This implies that the emergent spacetime may
incapacitate all the rationales to introduce the multiverse hypothesis.


  SmN is ferromagnetic below 27 K, and its net magnetic moment of 0.03 Bohr
magnetons per formula unit is one of the smallest magnetisations found in any
ferromagnetic material. The near-zero moment is a result of the nearly equal
and opposing spin and orbital moments in the 6H5/2 ground state of the Sm3+
ion, which leads finally to a nearly complete cancellation for an ion in the
SmN ferromagnetic state. Here we explore the spin alignment in this compound
with X-ray magnetic circular dichroism at the Sm L2,3 edges. The spectral
shapes are in qualitative agreement with computed spectra based on an LSDA+U
(local spin density approximation with Hubbard-U corrections) band structure,
though there remain differences in detail which we associate with the anomalous
branching ratio in rare-earth L edges. The sign of the spectra determine that
in a magnetic field the Sm 4f spin moment aligns antiparallel to the field; the
very small residual moment in ferromagnetic SmN aligns with the 4f orbital
moment and antiparallel to the spin moment. Further measurements on very thin
(1.5 nm) SmN layers embedded in GdN show the opposite alignment due to a strong
Gd-Sm exchange, suggesting that the SmN moment might be further reduced by
about 0.5 % Gd substitution.


  We present prospects for the Belle II experiment to further elucidate the KM
mechanism and beyond. Recent measurements of the CKM parameter, and the
radiative and electroweak penguin decays are also reported.


  We show how to perform a fault-tolerant universal quantum computation in 2D
architectures using only transversal unitary operators and local syndrome
measurements. Our approach is based on a doubled version of the 2D color code.
It enables a transversal implementation of all logical gates in the Clifford+T
basis using the gauge fixing method proposed recently by Paetznick and
Reichardt. The gauge fixing requires six-qubit parity measurements for Pauli
operators supported on faces of the honeycomb lattice with two qubits per site.
Doubled color codes are promising candidates for the experimental demonstration
of logical gates since they do not require state distillation. Secondly, we
propose a Maximum Likelihood algorithm for the error correction and gauge
fixing tasks that enables a numerical simulation of logical circuits in the
Clifford+T basis. The algorithm can be used in the online regime such that a
new error syndrome is revealed at each time step. We estimate the average
number of logical gates that can be implemented reliably for the smallest
doubled color code and a toy noise model that includes depolarizing memory
errors and syndrome measurement errors.


  We study electrical and thermoelectric transport properties of the surface
state of the topological insulator and graphene in the presence of randomly
distributed impurities. For finite impurity strength, the dependence of the
transport coefficients as a function of gate voltage, magnetic field and
impurity potential, are obtained numerically. In the limit of zero impurities
(clean limit), analytic results for the peak values of the magneto-oscillations
in thermopower are derived. Analogous with the conventional two dimensional
electron gas, the peak values are universal in the clean limit. Unlike
graphene, in topological insulators the coupling of the electron spin to its
momentum leads to a dependence of the transport coefficients on the
gyromagnetic ratio ($g$). We compare our results with data on graphene and
identify unique signatures expected in topological insulators due to the
magnetoelectric coupling.


  In this paper we study the clockwise simply connected rotating patches for
Euler equations. By using the moving plane method we prove that Rankine
vortices are the only solutions to this problem in the class of {\it slightly}
convex domains. We discuss in the second part of the paper the case where the
angular velocity $\Omega=\frac12$ and we show without any geometric condition
that the set of the V-states is trivial and reduced to the Rankine vortices.


  We employ Clarkson's inequality to deduce that each extremal of Morrey's
inequality is axially symmetric and is antisymmetric with respect to reflection
about a plane orthogonal to its axis of symmetry. We also use symmetrization
methods to show that each extremal is monotone in the distance from its axis of
symmetry and in the direction of its axis when restricted to spheres centered
at the intersection of its axis and its antisymmetry plane.


  Twin Higgs mechanism has recently been proposed to solve the ``little
Hierarchy'' problem. We studied the implementation of twin Higgs mechanism in
left-right models. We discussed the particle spectrum, and the collider
phenomenology at the Large Hadron Collider.


  In this communication we present a first principle study of
Pr$_{1-x}$Sr$_{x}$MnO$_3$ with $x = 0.25$. While the parent compounds of this
system are antiferromagnetic insulators with different structural and magnetic
ground states, the $x = 0.25$ is in the colossal magnetoresistance regime of
the Pr$_{1-x}$Sr$_{x}$MnO$_3$ phase diagram [C. Martin, A. Maignan, M. Hervieu,
B. Raveau, Phys. Rev. B 60 (1999) 12191]. Our band structure calculations for
the end-point compounds matches well with the existing theoretical and
experimental results [C. Martin, A. Maignan, M. Hervieu, B. Raveau, Phys. Rev.
B 60 (1999) 12191; Rune Sondena, P. Ravindran, Svein Stolen, Tor Grande,
Michael Hanfland, Phys. Rev. B 74 (2006) 144102]. Interestingly, our
calculations show that the Pr$_{0.75}$Sr$_{0.25}$MnO$_3$ has a half-metallic
character with a huge band gap of 2.8 eV in the minority band. We believe this
result would fuel further interest in some of these special compositions of
colossal magnetoresistive manganites as they could be potential candidates for
spintronic devices. We discuss the half-metallicity of the
Pr$_{0.75}$Sr$_{0.25}$MnO$_3$ in the light of changes in the orbital
hybridization as a result of Sr doping in PrMnO$_3$. Further, we highlight the
importance of half-metallicity for a consolidated understanding of colossal
magnetoresistance effect.


  Large Language Models (LLMs) are increasingly relied upon to evaluate text
outputs of other LLMs, thereby influencing leaderboards and development
decisions. However, concerns persist over the accuracy of these assessments and
the potential for misleading conclusions. In this work, we investigate the
effectiveness of LLMs as evaluators for text generation tasks. We propose FBI,
a novel framework designed to examine the proficiency of Evaluator LLMs in
assessing four critical abilities in other LLMs: factual accuracy, instruction
following, coherence in long-form writing, and reasoning proficiency. By
introducing targeted perturbations in answers generated by LLMs, that clearly
impact one of these key capabilities, we test whether an Evaluator LLM can
detect these quality drops. By creating a total of 2400 perturbed answers
covering 22 perturbation categories, we conduct a comprehensive study using
different evaluation strategies on five prominent LLMs commonly used as
evaluators in the literature. Our findings reveal significant shortcomings in
current Evaluator LLMs, which failed to identify quality drops in over 50\% of
cases on average. Single-answer and pairwise evaluations demonstrated notable
limitations, whereas reference-based evaluations showed comparatively better
performance. These results underscore the unreliable nature of current
Evaluator LLMs and advocate for cautious implementation in practical
applications. Code and data are available at https://github.com/AI4Bharat/FBI.


  Attackers demonstrated the use of remote access to the in-vehicle network of
connected vehicles to launch cyber-attacks and remotely take control of these
vehicles. Machine-learning-based Intrusion Detection Systems (IDSs) techniques
have been proposed for the detection of such attacks. The evaluation of some of
these IDS demonstrated their efficacy in terms of accuracy in detecting message
injections but was performed offline, which limits the confidence in their use
for real-time protection scenarios. This paper evaluates four architecture
designs for real-time IDS for connected vehicles using Controller Area Network
(CAN) datasets collected from a moving vehicle under malicious speed reading
message injections. The evaluation shows that a real-time IDS for a connected
vehicle designed as two processes, a process for CAN Bus monitoring and another
one for anomaly detection engine is reliable (no loss of messages) and could be
used for real-time resilience mechanisms as a response to cyber-attacks.


  In the realm of open quantum systems, steady states and high-harmonic
generation (HHG) existing far from equilibrium have become core pillars of
ultrafast science. Most solid-state research explores charge HHG with limited
investigations into spin degrees of freedom. In this study, we theoretically
address spin HHG in the steady state resulting from the terahertz laser-driven
spin-phonon coupling in a dissipative dimerized spin-1/2 chain. Instead of
directly driving spins using time-dependent magnetic fields, we employ the
magnetophononic mechanism, where the laser first drives the lattice, and then
the excited lattice subsequently drives the spins. We investigate the role of
various model parameters for optimizing HHG. Increasing the laser's amplitude
amplifies spin HHG beyond the perturbative regime, enhancing both harmonic
amplitudes and orders. We find that configuring the drive frequency far below
the spin band yields the highest harmonic order. Additionally, we provide a
theory matching the numerical results under weak spin-phonon coupling and
propose an experimental procedure to probe the emission spectrum of spin HHG.


  Zero-point fluctuations are a universal consequence of quantum theory. Vacuum
fluctuations of electromagnetic field have provided crucial evidence and
guidance for QED as a successful quantum field theory with a defining gauge
symmetry through the Lamb shift, Casimir effect, and spontaneous emission. In
an accelerated frame, the thermalisation of the zero-point electromagnetic
field gives rise to the Unruh effect linked to the Hawking effect of a black
hole via the equivalence principle. This principle is the basis of general
covariance, the symmetry of general relativity as the classical theory of
gravity. If quantum gravity exists, the quantum vacuum fluctuations of the
gravitational field should also lead to the quantum decoherence and
dissertation of general forms of energy and matter. Here we present a novel
theoretical effect involving the spontaneous emission of soft gravitons by
photons as they bend around a heavy mass and discuss its observational
prospects. Our analytic and numerical investigations suggest that the
gravitational bending of starlight predicted by classical general relativity
should also be accompanied by the emission of gravitational waves. This in turn
redshifts the light causing a loss of its energy somewhat analogous to the
bremsstrahlung of electrons by a heavier charged particle. It is suggested that
this new effect may be important for a combined astronomical source of intense
gravity and high-frequency radiation such as X-ray binaries and that the
proposed LISA mission may be potentially sensitive to the resulting sub-Hz
stochastic gravitational waves.


  This paper contains first results on the finite-gap integration of the
Sine-Gordon equation. They were published on Russian in 1976. The papers
\cite{Koz}, \cite{KK}, \cite{KK02} have been rewritten in the English language
with small modifications for a convenience. Such a translation was made due to
requests of some interested readers.
  In those papers, the method of constructing of the finite-gap solutions of
the equation $u_{tt}-u_{xx}+\sin u=0$ was proposed. The explicit formulae were
obtained for these solutions. The formulae are constructed in terms of
$\theta$-functions and they are analogous to the formulae obtained by A.R.Its
and V.B.Matveev \cite{IM}, B.A.Dubrovin and S.P.Novikov \cite{DN} for periodic
and almost periodic solutions to the Korteweg de Vries equation.


  The convergence and numerical analysis of a low memory implementation of the
Orthogonal Matching Pursuit greedy strategy, which is termed Self Projected
Matching Pursuit, is presented. This approach renders an iterative way of
solving the least squares problem with much less storage requirement than
direct linear algebra techniques. Hence, it appropriate for solving large
linear systems. The analysis highlights its suitability within the class of
well posed problems.