  We present a detailed analysis of the Horizontal Branch of the Carina Dwarf
Spheroidal Galaxy by means of synthetic modelling techniques, taking
consistently into account the star formation history and metallicity evolution
as determined from main sequence and red giant branch spectroscopic
observations. We found that a range of integrated red giant branch mass loss
values of 0.1-0.14 M, increasing with metallicity, is able to reproduce the
colour extension of the old Horizontal Branch. However, leaving the mass loss
as the only free parameter is not enough to match the detailed morphology of
Carina Horizontal Branch. We explored the role played by the star formation
history on the discrepancies between synthetic and observed Horizontal
Branches. We derived a toy bursty star formation history that reproduces the
horizontal branch star counts, and also matches qualitatively the red giant and
the turn off regions. This star formation history is made of a subset of age
and [M/H] components of the star formation history based on turn off and red
giants only, and entails four separate bursts of star formation of different
strenghts, centred at 2, 5, 8.6 and 11.5 Gyr, with mean [M/H] decreasing from
\sim -1.7 to \sim -2.2 for increasing ages, and a Gaussian spread of 0.1 dex.
The comparison between the metallicity distribution function of our star
formation history and the one measured from the infrared CaT feature using a
CaT-[Fe/H] calibration shows a qualitative agreement, once taken into account
the range of [Ca/Fe] abundances measured in a sample of Carina stars, that
biases the derived [Fe/H] distribution toward too low values. In conclusion, we
have shown how the information contained within the horizontal branch of Carina
(and dwarf galaxies in general) can be extracted and interpreted to refine the
star formation history derived from red giants and turn off stars only.
Abridged


  Schmidt and Spie{\ss} described the abelian tame fundamental group of a
smooth variety over a finite field by using Suslin homology. In this paper we
show that their result generalizes to singular varieties if one uses
Weil-Suslin homology instead.


  Privacy policies have become the most critical approach to safeguarding
individuals' privacy and digital security. To enhance their presentation and
readability, researchers propose the concept of contextual privacy policies
(CPPs), aiming to fragment policies into shorter snippets and display them only
in corresponding contexts. In this paper, we propose a novel multi-modal
framework, namely SeePrivacy, designed to automatically generate contextual
privacy policies for mobile apps. Our method synergistically combines mobile
GUI understanding and privacy policy document analysis, yielding an impressive
overall 83.6% coverage rate for privacy-related context detection and an
accuracy of 0.92 in extracting corresponding policy segments. Remarkably, 96%
of the retrieved policy segments can be correctly matched with their contexts.
The user study shows SeePrivacy demonstrates excellent functionality and
usability (4.5/5). Specifically, participants exhibit a greater willingness to
read CPPs (4.1/5) compared to original privacy policies (2/5). Our solution
effectively assists users in comprehending privacy notices, and this research
establishes a solid foundation for further advancements and exploration.


  In the framework of recently introduced frustrated lattice gas models, we
study the out of equilibrium dynamical processes during the compaction process
in granular media. We find irreversible-reversible cycles in agreement with
recent experimental observations. Moreover in analogy with the phenomenology of
the glass transition we find aging effects during the compaction process In
particular we find that the two time density correlation function $C(t,t')$
asymptotically scales as a function of the single variable $\ln(t')/\ln(t)$.
This result is interpreted in terms of multiscaling properties of the system.


  Let S be a smooth real surface in C^2 and let p\in S be a point at which the
tangent plane is a complex line. How does one determine whether or not S is
locally polynomially convex at such a p --- i.e. at a CR singularity ? Even
when the order of contact of T_p(S) with S at p equals 2, no clean
characterisation exists; difficulties are posed by parabolic points. Hence, we
study non-parabolic CR singularities. We show that the presence or absence of
Bishop discs around certain non-parabolic CR singularities is completely
determined by a Maslov-type index. This result subsumes all known facts about
Bishop discs around order-two, non-parabolic CR singularities. Sufficient
conditions for Bishop discs have earlier been investigated at CR singularities
having high order of contact with T_p(S). These results relied upon a
subharmonicity condition, which fails in many simple cases. Hence, we look
beyond potential theory and refine certain ideas going back to Bishop.


  Detailed balance of a chemical reaction network can be defined in several
different ways. Here we investigate the relationship among four types of
detailed balance conditions: deterministic, stochastic, local, and zero-order
local detailed balance. We show that the four types of detailed balance are
equivalent when different reactions lead to different species changes and are
not equivalent when some different reactions lead to the same species change.
Under the condition of local detailed balance, we further show that the system
has a global potential defined over the whole space, which plays the central
role in the large deviation theory and the Freidlin-Wentzell-type metastability
theory of chemical reaction networks. Finally, we provide a new sufficient
condition for stochastic detailed balance, which is applied to construct a
class of high-dimensional chemical reaction networks that both satisfies
stochastic detailed balance and displays multistability.


  The set of integers which can be written as the sum of four prime cubes has
lower density at least $0.009664$. This improves earlier bounds of
  $0.003125$ by Ren and $0.005776$ by Liu.


  We study spin resonance in the superconducting state of recently discovered
alkali-intercalated iron selenide materials A_xFe_(2-y)Se_2 (A=K,Rb,Cs) in
which the Fermi surface has only electron pockets. Recent angle-resolved
photoemission spectroscopy (ARPES) studies [M. Xu et al., Phys. Rev. B 85,
220504(R) (2012)] were interpreted as strong evidence for s-wave gap in these
materials, while the observation of the resonance peak in neutron scattering
measurements [G. Friemel et al., Phys. Rev. B 85, 140511 (2012)] suggests that
the gap must have different signs at Fermi surface points connected by the
momentum at which the resonance has been observed. We consider recently
proposed unconventional s+- superconducting state of A_xFe_(2-y)Se_2 with
superconducting gap changing sign between the hybridized electron pockets. We
argue that such a state supports a spin resonance. We compute the dynamical
structure factor and show that it is consistent with the results of inelastic
neutron scattering.


  We examine our previous conjecture that the eta' intermediate resonance has
the dominant role in the long distance contributions to B decay into two
photons and a strange final state hadron. We calculate the branching ratio of
the exclusive B-> K eta'-> K photon photon decay using the nonspectator
mechanism for eta' production in charmless hadronic B decays. It is shown that
the obtained branching ratio B^eta'(B-> K\gamma\gamma)~ 8.7 X 10^{-7} is more
than twice as large as the eta_c contribution to this decay mode.


  In this paper we consider the existence of global weak entropy solutions for
a particualr nonsymmetric Keyfitz-Kranzer type system, by using the compensated
compactness method we get bounde entropy weak solutions


  In this work we introduce the concept of a sub-space decomposition, subject
to a partition of the coordinates. Considering metrics determined by partial
orders in the set of coordinates, the so called poset metrics, we show the
existence of maximal decompositions according to the metric. These
decompositions turns to be an important tool to obtain the canonical form for
codes over any poset metrics and to obtain bounds for important invariants such
as the packing radius of a linear subspace. Furthermore, using maximal
decompositions, we are able to reduce and optimize the full lookup table
algorithm for the syndrome decoding process.


  We examine the correlation of projected rotational velocities in binary
systems. It is an extension of previous work (Steinitz and Pyper, 1970; Levato,
1974). An enlarged data basis and new tests enable us to conclude that there is
indeed correlation between the projected rotational velocities of components of
binaries. In fact we suggest that spins are already correlated.


  We experimentally squeeze the thermal motional state of an optically
levitated nanosphere, by fast switching between two trapping frequencies. The
measured phase space distribution of our particle shows the typical shape of a
squeezed thermal state, from which we infer up to 2.7dB of squeezing along one
motional direction. The experiment features a large number of thermal
excitations, therefore remaining in the classical regime. Nevertheless, we
argue that the manipulation scheme described here could be used to achieve
squeezing below the zero-point level, if preceded by ground state cooling of
the levitated mechanical oscillator. Additionally, a higher degree of squeezing
could in principle be achieved by repeating the frequency-switching protocol
multiple times.


  We present general conditions on Dirac and Majorana mass terms under which a
type-I seesaw mechanism can lead to three exactly massless neutrinos at the
tree level. We depict several examples where the conditions are satisfied and
relate some of them to an underlying U(1) symmetry. We show that higher order
corrections may generate the small observed masses and this may be achieved
even when the heavy Majorana neutrinos are at the electroweak scale or a little
higher.


  We report the numerical realization and demonstration of robustness of
certain 2-component structures in Bose-Einstein Condensates in 2 and 3 spatial
dimensions with non-trivial topological charge in one of the components. In
particular, we identify a stable symbiotic state in which a higher-dimensional
bright soliton exists even in a homogeneous setting with defocusing
interactions, as a result of the effective potential created by a stable vortex
in the other component. The resulting vortex-bright solitary waves, which
naturally generalize the recently experimentally observed dark-bright solitons,
are examined both in the homogeneous medium and in the presence of parabolic
and periodic external confinement and are found to be very robust.


  Depth estimation is a core task in 3D computer vision. Recent methods
investigate the task of monocular depth trained with various depth sensor
modalities. Every sensor has its advantages and drawbacks caused by the nature
of estimates. In the literature, mostly mean average error of the depth is
investigated and sensor capabilities are typically not discussed. Especially
indoor environments, however, pose challenges for some devices. Textureless
regions pose challenges for structure from motion, reflective materials are
problematic for active sensing, and distances for translucent material are
intricate to measure with existing sensors. This paper proposes HAMMER, a
dataset comprising depth estimates from multiple commonly used sensors for
indoor depth estimation, namely ToF, stereo, structured light together with
monocular RGB+P data. We construct highly reliable ground truth depth maps with
the help of 3D scanners and aligned renderings. A popular depth estimators is
trained on this data and typical depth senosors. The estimates are extensively
analyze on different scene structures. We notice generalization issues arising
from various sensor technologies in household environments with challenging but
everyday scene content. HAMMER, which we make publicly available, provides a
reliable base to pave the way to targeted depth improvements and sensor fusion
approaches.


  We present the detailed design of the near infrared camera for the SuMIRe
(Subaru Measurement of Images and Redshifts) Prime Focus Spectrograph (PFS)
being developed for the Subaru Telescope. The PFS spectrograph is designed to
collect spectra from 2394 objects simultaneously, covering wavelengths that
extend from 380 nm - 1.26 um. The spectrograph is comprised of four identical
spectrograph modules, with each module collecting roughly 600 spectra from a
robotic fiber positioner at the telescope prime focus. Each spectrograph module
will have two visible channels covering wavelength ranges 380 nm - 640 nm and
640 nm - 955 nm, and one near infrared (NIR) channel with a wavelength range
955 nm - 1.26 um. Dispersed light in each channel is imaged by a 300 mm focal
length, f/1.07, vacuum Schmidt camera onto a 4k x 4k, 15 um pixel, detector
format. For the NIR channel a HgCdTe substrate-removed Teledyne 1.7 um cutoff
device is used. In the visible channels, CCDs from Hamamatsu are used. These
cameras are large, having a clear aperture of 300 mm at the entrance window,
and a mass of ~ 250 kg.
  Like the two visible channel cameras, the NIR camera contains just four
optical elements: a two-element refractive corrector, a Mangin mirror, and a
field flattening lens. This simple design produces very good imaging
performance considering the wide field and wavelength range, and it does so in
large part due to the use of a Mangin mirror (a lens with a reflecting rear
surface) for the Schmidt primary. In the case of the NIR camera, the rear
reflecting surface is a dichroic, which reflects in-band wavelengths and
transmits wavelengths beyond 1.26 um. This, combined with a thermal rejection
filter coating on the rear surface of the second corrector element, greatly
reduces the out-of-band thermal radiation that reaches the detector.


  The prediction of non-trivial topological electronic states hosted by
half-Heusler compounds makes them prime candidates for discovering new physics
and devices as they harbor a variety of electronic ground states including
superconductivity, magnetism, and heavy fermion behavior. Here we report normal
state electronic properties of a superconducting half-Heusler compound YPtBi
using angle-resolved photoemission spectroscopy (ARPES). Our data reveal the
presence of a Dirac state at the zone center of the Brillouin zone at 500 meV
below the chemical potential. We observe the presence of multiple Fermi surface
pockets including two concentric hexagonal and six half oval shaped pockets at
the gamma and K points of the Brillouin zone, respectively. Furthermore, our
measurements show Rashba-split bands and multiple surface states crossing the
chemical potential which are supported by the first-principles calculations.
Our finding of a Dirac state in YPtBi plays a significant role in establishing
half-Heusler compounds as a new potential platform for novel topological phases
and explore their connection with superconductivity.


  A variety of physical phenomena can lead to viscous effects. Several sources
of shear and bulk viscosity are reviewed with an emphasis on the bulk viscosity
associated with chiral restoration and with chemical non-equilibrium. We show
that in a mean-field treatment of the limiting case of a second order phase
transition, the bulk viscosity peaks in a singularity at the critical point.


  Gauge theory requires physical observables to be gauge-independent. However,
ever since Lamb noticed the problem of gauge selection in calculating atomic
spontaneous radiation spectrum, the problem of gauge dependence was encountered
in many fields of physics research. Therefore, it is important to test the
self-consistency of gauge symmetry for various physical systems. In this paper,
we calculate the transient spontaneous radiation spectrum of a relativistic
hydrogen atom in the non-uniform electrostatic field under the atomic
self-reference frame. The physical system studied in this paper is a
frame-transformed version of our recent work
[\href{https://link.springer.com/paper/10.1140/epjd/s10053-022-00407-5}{Euro.
J. Phys. D \textbf{76}, 84(2022)}] where the radiating object is static while
the charge is moving relativistically. The obtained peak frequency can differ
by about $413$ $\mathrm{KHz}$ or larger for the commonly used Coulomb, Lorentz,
and multipolar gauges. This observation can be significant not only for
studying how the gauge field interacts with the quantum system in theory, but
also for practical experimental applications, such as the timing accuracy of
atomic clocks in the external electromagnetic field.


  The main drawback for the application of the conforming Argyris FEM is the
labourious implementation on the one hand and the low convergence rates on the
other. If no appropriate adaptive meshes are utilised, only the convergence
rate caused by corner singularities [Blum and Rannacher, 1980], far below the
approximation order for smooth functions, can be achieved. The fine
approximation with the Argyris FEM produces high-dimensional linear systems and
for a long time an optimal preconditioned scheme was not available for
unstructured grids. This paper presents numerical benchmarks to confirm that
the adaptive multilevel solver for the hierarchical Argyris FEM from
[Carstensen and Hu, 2021] is in fact highly efficient and of linear time
complexity. Moreover, the very first display of optimal convergence rates in
practically relevant benchmarks with corner singularities and general boundary
conditions leads to the rehabilitation of the Argyris finite element from the
computational perspective.


  We introduce a generalization structure of the su(1,1) algebra which depends
on a function of one generator of the algebra, f(H). Following the same ideas
developed to the generalized Heisenberg algebra (GHA) and to the generalized
su(2), we show that a symmetry is present in the sequence of eigenvalues of one
generator of the algebra. Then, we construct the Barut-Girardello coherent
states associated with the generalized su(1,1) algebra for a particle in a
P\"oschl-Teller potential. Furthermore, we compare the time evolution of the
uncertainty relation of the constructed coherent states with that of GHA
coherent states. The generalized su(1,1) coherent states are very localized.


  Recent population studies have searched for a subpopulation of primordial
black holes (PBHs) in the gravitational-wave (GW) events so far detected by
LIGO/Virgo/KAGRA (LVK), in most cases adopting a phenomenological PBH mass
distribution. When deriving such population from first principles in the
standard scenario, however, the equation of state of the Universe at the time
of PBH formation may strongly affect the PBH abundance and mass distribution,
which ultimately depend on the power spectrum of cosmological perturbations.
Here we improve on previous population studies on several aspects: (i) we adopt
state-of-the-art PBH formation models describing the collapse of cosmological
perturbations across the QCD epoch; (ii) we perform the first Bayesian
multi-population inference on GW data including PBHs and directly using power
spectrum parameters instead of phenomenological distributions; (iii) we
critically confront the PBH scenario with LVK phenomenological models
describing the GWTC-3 catalog both in the neutron-star and in the BH mass
ranges, also considering PBHs as subpopulation of the total events. Our results
confirm that LVK observations prevent the majority of the dark matter to be in
the form of stellar mass PBHs. We find that the best fit PBH model can comprise
a small fraction of the total events, in particular it can naturally explain
events in the mass gaps. If the lower mass-gap event GW190814 is interpreted as
a PBH binary, we predict that LVK should detect up to a few subsolar mergers
and one to $\approx 30$ lower mass gap events during the upcoming O4 and O5
runs. Finally, mapping back the best-fit power spectrum into an ultra slow-roll
inflationary scenario, we show that the latter predicts detectable PBH mergers
in the LVK band, a stochastic GW background detectable by current and future
instruments, and may include the entirety of dark matter in asteroid-mass PBHs.


  A family of original formulae for computing number PI and its proof are
presented. An algorithm is proposed to validate the results of this new
algorithm.


  Homogenization is studied for a nonlinear elliptic boundary-value problem
with a large nonlinear potential. More specifically we are interested in the
asymptotic behavior of a sequence of p-Laplacians of the form $$
-\text{div}(a(\frac{x}{\varepsilon})|Du_\varepsilon|^{p-2}Du_\varepsilon)
+\frac{1}{\varepsilon}V(\frac{x}{\varepsilon})|u_\varepsilon|^{p-2}u_\varepsilon=f.
$$ It is shown that, under a centring condition on the potential $V$, there
exists a two-scale homogenized system with solution $(u, u_1)$ such that the
sequence $u_\varepsilon$ of solutions converges weakly to $u$ in $W^{1,p}$ and
the gradients $D_x u_\varepsilon$ two-scale converges weakly to $D_x u+ D_y
u_1$ in $L^p$, respectively. We characterize the limit system explicitly by
means of two-scale convergence and a new convergence result.


  This paper has been withdrawn by the author, because it final version is
published in: N. Fatkullin, C. Mattea, S. Stapf, Polymer 52 (2011) 3522.


  We study possible correlations between properties of the observable and
hidden sectors in heterotic string theory. Specifically, we analyze the case of
the Z6-II orbifold compactification which produces a significant number of
models with the spectrum of the supersymmetric standard model. We find that
requiring realistic features does affect the hidden sector such that hidden
sector gauge group factors SU(4) and SO(8) are favoured. In the context of
gaugino condensation, this implies low energy supersymmetry breaking.


  Densities of states for simple (sc) and base-centered (bcc) cubic lattices
with account of nearest and next-nearest neighbour hopping integrals $t$ and
$t'$ are investigated in detail. It is shown that at values of $\tau \equiv
t'/t = \tau_\ast$, corresponding to the change of isoenergetic surface
topology, the formation of van Hove $\bf k$ lines takes place. At small
deviation from these special values, the weakly dispersive spectrum in the
vicinity of van Hove lines is replaced by a weak $\bf k$-dependence in the
vicinity of few van Hove points which possess huge masses proportional to
$|\tau - \tau_\ast|^{-1}$. The singular contributions to the density of states
originating from van Hove points and lines are considered, as well as the
change in the topology of isoenergetic surfaces in the $\bf k$-space with the
variation of $\tau$. Closed analytical expressions for density of states as a
function of energy and $\tau$ in terms of elliptic integrals, and power-law
asymptotics at $\tau = \tau_\ast$ are obtained. Besides the case of sc lattice
with small $\tau$ (maximum of density of states corresponds to energy level of
X $\bf k$-point), maximal value of the density of states is always achieved at
energies corresponding to \textit{inner} $\bf k$-points of the Brillouin zone
positioned in high-symmetry directions, and not at zone faces.


  Time-dependent basis reduced order models (TDB ROMs) have successfully been
used for approximating the solution to nonlinear stochastic partial
differential equations (PDEs). For many practical problems of interest,
discretizing these PDEs results in massive matrix differential equations (MDEs)
that are too expensive to solve using conventional methods. While TDB ROMs have
the potential to significantly reduce this computational burden, they still
suffer from the following challenges: (i) inefficient for general
nonlinearities, (ii) intrusive implementation, (iii) ill-conditioned in the
presence of small singular values, and (iv) error accumulation due to fixed
rank. To this end, we present a scalable method based on oblique projections
for solving TDB ROMs that is computationally efficient, minimally intrusive,
robust in the presence of small singular values, rank-adaptive, and highly
parallelizable. These favorable properties are achieved via low-rank
approximation of the time discrete MDE. Using the discrete empirical
interpolation method (DEIM), a low-rank decomposition is computed at each
iteration of the time stepping scheme, enabling a near-optimal approximation at
a fraction of the cost. We coin the new approach TDB-CUR since it is equivalent
to a CUR decomposition based on sparse row and column samples of the MDE. We
also propose a rank-adaptive procedure to control the error on-the-fly.
Numerical results demonstrate the accuracy, efficiency, and robustness of the
new method for a diverse set of problems.


  It is well known that for two qubits the upper bounds of the relative entropy
of entanglement (REE) for a given concurrence as well as the negativity for a
given concurrence are reached by pure states. We show that, by contrast, there
are two-qubit mixed states for which the REE for some range of a fixed
negativity is higher than that for pure states. Moreover, we demonstrate that a
mixture of a pure entangled state and pure separable state orthogonal to it is
likely to give the maximal REE. By noting that the negativity is a measure of
entanglement cost under operations preserving positivity of partial transpose,
our results provide an explicit example of operations such that, even though
the entanglement cost for an exact preparation is the same, the entanglement of
distillation of a mixed state can exceed that of pure states. This means that
the entanglement manipulation via a pure state can result in a larger
entanglement loss than that via a mixed state.


  We define a multi-index filtration on the ring of germs of functions on a
hypersurface singularity associated with its Newton diagram and compute the
multivariable Poincar\'e series of this filtration in some cases.


  Derivative-free optimization (DFO) consists in finding the best value of an
objective function without relying on derivatives. To tackle such problems, one
may build approximate derivatives, using for instance finite-difference
estimates. One may also design algorithmic strategies that perform space
exploration and seek improvement over the current point. The first type of
strategy often provides good performance on smooth problems but at the expense
of more function evaluations. The second type is cheaper and typically handles
non-smoothness or noise in the objective better. Recently, full-low evaluation
methods have been proposed as a hybrid class of DFO algorithms that combine
both strategies, respectively denoted as Full-Eval and Low-Eval. In the
unconstrained case, these methods showed promising numerical performance.
  In this paper, we extend the full-low evaluation framework to bound and
linearly constrained derivative-free optimization. We derive convergence
results for an instance of this framework, that combines finite-difference
quasi-Newton steps with probabilistic direct-search steps. The former are
projected onto the feasible set, while the latter are defined within tangent
cones identified by nearby active constraints. We illustrate the practical
performance of our instance on standard linearly constrained problems, that we
adapt to introduce noisy evaluations as well as non-smoothness. In all cases,
our method performs favorably compared to algorithms that rely solely on
Full-eval or Low-eval iterations.


  We consider the problem of multiparticle production at threshold in a
$\phi^4$-theory with an $O(N_1$$+$$N_2)$ symmetry softly broken down to
$O(N_1)\times O(N_2)$ by nonequal masses. We derive the set of recurrence
relations between the multiparticle amplitudes which sums all relevant diagrams
with arbitrary number of loops in the large-$N$ limit with fixed number of
produced particles. We transform it into a quantum mechanical problem and show
how it can be obtained directly from the operator equations of motion by
applying the factorization at large $N$. We find the exact solutions to the
problem by using the Gelfand--Diki\u{\i} representation of the diagonal
resolvent of the Schr\"{o}dinger operator. The result coincides with the tree
amplitudes while the effect of loops is the renormalization of the coupling
constant and masses. The form of the solution is due to the fact that the exact
amplitude of the process $2$$\ra$$n$ vanishes at $n$$>$$2$ on mass shell when
averaged over the $O(N_{1,2})$-indices of incoming particles. We discuss what
dynamical symmetry is behind this property. We also give an exact solution in
the large-$N$ limit for the model of the $O(N)$$+$$singlet$ scalar particle
with the spontaneous breaking of a reflection symmetry.


  An adaptive Monte Carlo localization algorithm based on coevolution mechanism
of ecological species is proposed. Samples are clustered into species, each of
which represents a hypothesis of the robots pose. Since the coevolution between
the species ensures that the multiple distinct hypotheses can be tracked
stably, the problem of premature convergence when using MCL in highly symmetric
environments can be solved. And the sample size can be adjusted adaptively over
time according to the uncertainty of the robots pose by using the population
growth model. In addition, by using the crossover and mutation operators in
evolutionary computation, intra-species evolution can drive the samples move
towards the regions where the desired posterior density is large. So a small
size of samples can represent the desired density well enough to make precise
localization. The new algorithm is termed coevolution based adaptive Monte
Carlo localization (CEAMCL). Experiments have been carried out to prove the
efficiency of the new localization algorithm.


  Traditionally, fault detection and isolation community has used system
dynamic equations to generate diagnosers and to analyze detectability and
isolability of the dynamic systems. Model-based fault detection and isolation
methods use system model to generate a set of residuals as the bases for fault
detection and isolation. However, in many complex systems it is not feasible to
develop highly accurate models for the systems and to keep the models updated
during the system lifetime. Recently, data-driven solutions have received an
immense attention in the industries systems for several practical reasons.
First, these methods do not require the initial investment and expertise for
developing accurate models. Moreover, it is possible to automatically update
and retrain the diagnosers as the system or the environment change over time.
Finally, unlike the model-based methods it is straight forward to combine time
series measurements such as pressure and voltage with other sources of
information such as system operating hours to achieve a higher accuracy. In
this paper, we extend the traditional model-based fault detection and isolation
concepts such as residuals, and detectable and isolable faults to the
data-driven domain. We then propose an algorithm to automatically generate
residuals from the normal operating data. We present the performance of our
proposed approach through a comparative case study.


  We present a detailed QCD analysis of nucleon structure functions $xF_3 (x,
Q^2)$, based on Laplace transforms and Jacobi polynomials approach. The
analysis corresponds to the next-to-leading order and next-to-next-to-leading
order approximation of perturbative QCD. The Laplace transform technique, as an
exact analytical solution, is used for the solution of nonsinglet
Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations at low- and
large-$x$ values. The extracted results are used as input to obtain the $x$ and
Q$^2$ evolution of $xF_3(x, Q^2)$ structure functions using the Jacobi
polynomials approach. In our work, the values of the typical QCD scale
$\Lambda_{\overline{\rm MS}}^{(n_f)}$ and the strong coupling constant
$\alpha_s(M_Z^2)$ are determined for four quark flavors ($n_f=4$) as well. A
careful estimation of the uncertainties shall be performed using the Hessian
method for the valence-quark distributions, originating from the experimental
errors. We compare our valence-quark parton distribution functions sets with
those of other collaborations; in particular with the {\tt BBG}, {\tt CT14},
{\tt MMHT14} and {\tt NNPDF} sets, which are contemporary with the present
analysis. The obtained results from the analysis are in good agreement with
those from the literature.


  We describe a completely automated large scale visual recommendation system
for fashion. Our focus is to efficiently harness the availability of large
quantities of online fashion images and their rich meta-data. Specifically, we
propose four data driven models in the form of Complementary Nearest Neighbor
Consensus, Gaussian Mixture Models, Texture Agnostic Retrieval and Markov Chain
LDA for solving this problem. We analyze relative merits and pitfalls of these
algorithms through extensive experimentation on a large-scale data set and
baseline them against existing ideas from color science. We also illustrate key
fashion insights learned through these experiments and show how they can be
employed to design better recommendation systems. Finally, we also outline a
large-scale annotated data set of fashion images (Fashion-136K) that can be
exploited for future vision research.


  Real-time 6D object pose estimation is essential for many real-world
applications, such as robotic grasping and augmented reality. To achieve an
accurate object pose estimation from RGB images in real-time, we propose an
effective and lightweight model, namely High-Resolution 6D Pose Estimation
Network (HRPose). We adopt the efficient and small HRNetV2-W18 as a feature
extractor to reduce computational burdens while generating accurate 6D poses.
With only 33\% of the model size and lower computational costs, our HRPose
achieves comparable performance compared with state-of-the-art models.
Moreover, by transferring knowledge from a large model to our proposed HRPose
through output and feature-similarity distillations, the performance of our
HRPose is improved in effectiveness and efficiency. Numerical experiments on
the widely-used benchmark LINEMOD demonstrate the superiority of our proposed
HRPose against state-of-the-art methods.


  Dependence on information, including for some of the world's largest
organisations such as governments and multi-national corporations, has grown
rapidly in recent years. However, reports of information security breaches and
their associated consequences continue to indicate that attacks are still
escalating on organisations when conducting these information-based activities.
Clearly, more research is needed to better understand how organisations should
formulate strategy to secure their information. Through a thematic review of
academic security literature, we (1) analyse the antecedent conditions that
motivate the potential adoption of a comprehensive information security
strategy, (2) the current perspectives of strategy and (3) the yields and
benefits that could be enjoyed post-adoption. Our contributions include a
definition of information security strategy. We argue for a paradigm shift to
extend from internally-focussed protection of organisation-wide information
towards a strategic view that considers the inter-organisational level. Our
findings are then used to suggest future research directions.


  Two-dimensional (2D) metal-organic frameworks (MOFs) hold immense potential
for various applications due to their distinctive intrinsic properties compared
to their 3D analogues. Herein, we designed in silico a highly stable
NiF$_2$(pyrazine)$_2$ 2D MOF with a two-periodic wine-rack architecture.
Extensive first-principles calculations and Molecular Dynamics simulations
based on a newly developed machine learning potential (MLP) revealed that this
2D MOF exhibits huge in-plane Poisson's ratio anisotropy. This results into an
anomalous negative in-plane stretchability, as evidenced by an uncommon
decrease of its in-plane area upon the application of uniaxial tensile strain
that makes this 2D MOF particularly attractive for flexible wearable
electronics and ultra-thin sensor applications. We further demonstrated that
the derived MLP offers a unique opportunity to effectively anticipate the
finite temperature mechanical properties of MOFs at large scale. As a
proof-concept, MLP-based Molecular Dynamics simulations were successfully
achieved on 2D NiF$_2$(pyrazine)$_2$ with a dimension of 28.2$\times$28.2
nm$^2$ relevant to the length scale experimentally attainable for the
fabrication of MOF film.


  An original approach, termed Divide-and-Evolve is proposed to hybridize
Evolutionary Algorithms (EAs) with Operational Research (OR) methods in the
domain of Temporal Planning Problems (TPPs). Whereas standard Memetic
Algorithms use local search methods to improve the evolutionary solutions, and
thus fail when the local method stops working on the complete problem, the
Divide-and-Evolve approach splits the problem at hand into several, hopefully
easier, sub-problems, and can thus solve globally problems that are intractable
when directly fed into deterministic OR algorithms. But the most prominent
advantage of the Divide-and-Evolve approach is that it immediately opens up an
avenue for multi-objective optimization, even though the OR method that is used
is single-objective. Proof of concept approach on the standard
(single-objective) Zeno transportation benchmark is given, and a small original
multi-objective benchmark is proposed in the same Zeno framework to assess the
multi-objective capabilities of the proposed methodology, a breakthrough in
Temporal Planning.


  Web3 and AI have been among the most discussed fields over the recent years,
with substantial hype surrounding each field's potential to transform the world
as we know it. However, as the hype settles, it's evident that neither AI nor
Web3 can address all challenges independently. Consequently, the intersection
of AI and Web3 is gaining increased attention, emerging as a new field with the
potential to address the limitations of each. In this article, we will focus on
the integration of web3 and the AI marketplace, where AI services and products
can be provided in a decentralized manner (DeAI). A comprehensive review is
provided by summarizing the opportunities and challenges on this topic.
Additionally, we offer analyses and solutions to address these challenges.
We've developed a framework that lets users pay with any kind of cryptocurrency
to get AI services. Additionally, they can also enjoy AI services for free on
our platform by simply locking up their assets temporarily in the protocol.
This unique approach is a first in the industry. Before this, offering free AI
services in the web3 community wasn't possible. Our solution opens up exciting
opportunities for the AI marketplace in the web3 space to grow and be widely
adopted.


  We provide a method, using essentially elementary arithmetic, to solve the
exponential diophantine equation 7x^2 + 59y^2 = 3^m, which leads to a simple
algorithm, with no use of radicals or complex numbers, that generates all the
(infinitely many) primitive and positive solutions of this equation. The method
can be generalized to solve a class of exponential equations of the form ax^2 +
by^2 = ck^z.


  A careful study of the physical properties of a family of coherent states on
the circle, introduced some years ago by de Bi\`evre and Gonz\'alez in [DG 92],
is carried out. They were obtained from the Weyl-Heisenberg coherent states in
$L^2(\R)$ by means of the Weil-Brezin-Zak transformation, they are labeled by
the points of the cylinder $S^1 \times \R$, and they provide a realization of
$L^2(S^1)$ by entire functions (similar to the well-known Fock-Bargmann
construction). In particular, we compute the expectation values of the position
and momentum operators on the circle and we discuss the Heisenberg uncertainty
relation.


  When $X$ is a $d$-dimensional variety defined over a field $k$ of
characteristic zero, a constructive resolution of singularities can be achieved
by successively lowering the maximum multiplicity via blow ups at smooth
equimultiple centers. This is done by stratifying the maximum multiplicity
locus of $X$ by means of the so called {\em resolution functions}. The most
important of these functions is what we know as {\em Hironaka's order function
in dimension $d$}. Actually, this function can be defined for varieties when
the base field is perfect; however if the characteristic of $k$ is positive,
the function is, in general, too coarse and does not provide enough information
so as to define a resolution. It is very natural to ask what the meaning of
this function is in this case, and to try to find refinements that could lead,
ultimately, to a resolution. In this paper we show that Hironaka's order
function in dimension $d$ can be read in terms of the {\em Nash multiplicity
sequences} introduced by Lejeune-Jalabert. Therefore, the function is intrinsic
to the variety and has a geometrical meaning in terms of its space of arcs.


  We study next-to-leading order contributions to the soft static fermion
dispersion relation in hot QED. We derive an expression for the complete
next-to-leading order contribution to the retarded fermion self-energy. The
real and imaginary parts of this expression give the next-to-leading order
contributions to the mass and damping rate of the fermionic quasi-particle.
Many of the terms that are expected to contribute according to the traditional
power counting argument are actually subleading. We explain why the power
counting method over estimates the contribution from these terms. For the
electron damping rate in QED we obtain: $\gamma_{QED} = \frac{e^2
T}{4\pi}(2.70)$. We check our method by calculating the next-to-leading order
contribution to the damping rate for the case of QCD with two flavours and
three coulours. Our result agrees with the result obtained previously in the
literature. The numerical evaluation of the nlo contribution to the mass is
left to a future publication.


  The increasing adoption of Cloud storage poses a number of privacy issues.
Users wish to preserve full control over their sensitive data and cannot accept
that it to be accessible by the remote storage provider. Previous research was
made on techniques to protect data stored on untrusted servers; however we
argue that the cloud architecture presents a number of open issues. To handle
them, we present an approach where confidential data is stored in a highly
distributed database, partly located on the cloud and partly on the clients.
Data is shared in a secure manner using a simple grant-and-revoke permission of
shared data and we have developed a system test implementation, using an
in-memory RDBMS with row-level data encryption for fine-grained data access
control


  On a 6-dimensional, conformal, oriented, compact manifold $M$ without
boundary, we compute a whole family of differential forms $\Omega_6(f,h)$ of
order 6, with $f,h \in C^\infty(M).$ Each of these forms will be symmetric on
$f,$ and $h,$ conformally invariant, and such that $\int_M f_0
\Omega_6(f_1,f_2)$ defines a Hochschild 2-cocycle over the algebra
$C^\infty(M).$ In the particular 6-dimensional conformally flat case, we
compute the unique one satisfying $\Wres(f_0[F,f][F,h]) = \int_M
f_0\Omega_6(f,h)$ for $(\cH,F)$ the Fredholm module associated by A. Connes
\cite{Con1} to the manifold $M,$ and $\Wres$ the Wodzicki residue.


  Machine-learning excels in many areas with well-defined goals. However, a
clear goal is usually not available in art forms, such as photography. The
success of a photograph is measured by its aesthetic value, a very subjective
concept. This adds to the challenge for a machine learning approach.
  We introduce Creatism, a deep-learning system for artistic content creation.
In our system, we break down aesthetics into multiple aspects, each can be
learned individually from a shared dataset of professional examples. Each
aspect corresponds to an image operation that can be optimized efficiently. A
novel editing tool, dramatic mask, is introduced as one operation that improves
dramatic lighting for a photo. Our training does not require a dataset with
before/after image pairs, or any additional labels to indicate different
aspects in aesthetics.
  Using our system, we mimic the workflow of a landscape photographer, from
framing for the best composition to carrying out various post-processing
operations. The environment for our virtual photographer is simulated by a
collection of panorama images from Google Street View. We design a
"Turing-test"-like experiment to objectively measure quality of its creations,
where professional photographers rate a mixture of photographs from different
sources blindly. Experiments show that a portion of our robot's creation can be
confused with professional work.


  The student generation nowadays is considered as the Net Generation who grow
up in the age of Internet and mobile technology and prefer bringing
technological application into their life. The Learning Resource Center, an
academic information center, takes the initiative in developing a collaborative
network with the participation of students for delivering information of
natural disasters and climate adaptation to the people who live in the
vulnerable areas of Thua Thien Hue province. The network is aimed at helping
local people mitigating vulnerabilities and adapting to the globally climate
change for a better life.


  Vf-safe delta-matroids have the desirable property of behaving well under
certain duality operations. Several important classes of delta-matroids are
known to be vf-safe, including the class of ribbon-graphic delta-matroids,
which is related to the class of ribbon graphs or embedded graphs in the same
way that graphic matroids correspond to graphs. In this paper, we characterize
vf-safe delta-matroids and ribbon-graphic delta-matroids by finding the minimal
obstructions, called excluded 3-minors, to membership in the class. We find the
unique (up to twisted duality) excluded $3$-minor within the class of set
systems for the class of vf-safe delta-matroids. In the literature, binary
delta-matroids appear in many different guises, with appropriate notions of
minor operations equivalent to that of $3$-minors, perhaps most notably as
graphs with vertex minors. We give a direct explanation of this equivalence and
show that some well-known results may be expressed in terms of $3$-minors.


  The universal analytical approach was developed to describe the process of
particle slow extraction from a synchrotron using adiabatic crossing the
betatron resonance of the third order. The obtained formulas make it possible
to calculate the time diagrams for the current of the extracted beam ('spill
profile'), taking into account the chromaticity, particle momentum spread and
synchrotron oscillations. On this basis, a method for monochromatization of
extracted beam is indicated. The theory is compared with some results obtained
in the experiment on crossing the third-order resonance at the VEPP-4M storage
ring.


  A simple upwind discretization of the highly coupled non-linear differential
equations which define the hydrodynamic model for semiconductors is given in
full detail. The hydrodynamic model is able to describe inertia effects which
play an increasing role in different fields of opto- and microelectronics. A
silicon $n^+ - n - n^+$ - structure is simulated, using the energy-balance
model and the full hydrodynamic model. Results for stationary cases are then
compared, and it is pointed out where the energy-balance model, which is
implemented in most of today's commercial semiconductor device simulators,
fails to describe accurately the electron dynamics. Additionally, a GaAs $n^+ -
n - n^+$-structure is simulated in time-domain in order to illustrate the
importance of inertia effects at high frequencies in modern submicron devices.


  We study an ancient problem that in a static or dynamical system, sought an
optimal path, which the context always means within an extremal condition. In
fact, through those discussions about this theme, we established a universal
essential calculated model to serve for these complex systems. Meanwhile we
utilize the sample space to character the system. These contents in this paper
would involve in several major areas including the geometry, probability, graph
algorithms and some prior approaches, which stands the ultimately subtle linear
algorithm to solve this class problem. Along with our progress, our discussion
would demonstrate more general meaning and robust character, which provides
clear ideas or notion to support our concrete applications, who work in a more
popular complex system.


  Transition states (TSs) are transient structures that are key in
understanding reaction mechanisms and designing catalysts but challenging to be
captured in experiments. Alternatively, many optimization algorithms have been
developed to search for TSs computationally. Yet the cost of these algorithms
driven by quantum chemistry methods (usually density functional theory) is
still high, posing challenges for their applications in building large reaction
networks for reaction exploration. Here we developed React-OT, an optimal
transport approach for generating unique TS structures from reactants and
products. React-OT generates highly accurate TS structures with a median
structural root mean square deviation (RMSD) of 0.053{\AA} and median barrier
height error of 1.06 kcal/mol requiring only 0.4 second per reaction. The RMSD
and barrier height error is further improved by roughly 25% through pretraining
React-OT on a large reaction dataset obtained with a lower level of theory,
GFN2-xTB. We envision the great accuracy and fast inference of React-OT useful
in targeting TSs when exploring chemical reactions with unknown mechanisms.


  It has been recently proposed that the interpretation of gravity as an
emergent, entropic force might have nontrivial implications to cosmology. Here
two approaches are investigated: in one, the Friedman equation receives
entropic contributions from the usually neglected surface terms, and in
another, the extra terms are derived from quantum corrections to the entropy
formula. UV terms may drive inflation, avoiding a recently derived no-go
theorem, though in some cases leading to a graceful exit problem. IR terms can
generate dark energy, alleviating the cosmological constant problem. The
quantum corrections are bounded by their implications to the BBN, and the
surface terms are constrained in addition by their effect upon the behavior of
matter. Likelihood analyses are performed to constrain the modifications by the
SNeIa, BAO and CMB data. It is found that a monomial correction to the
area-entropy formula results in late acceleration in very good agreement with
observations, which then turn out to be compatible with positive curvature. The
evolution of perturbations is deduced by assuming the Jebsen-Birkhoff theorem.
Distinct signatures can then be identified in the large scale structure
formation. Furthermore, it is shown that the visible universe satisfies the
Bekenstein bound.


  Recent advances in reinforcement learning with social agents have allowed us
to achieve human-level performance on some interaction tasks. However, most
interactive scenarios do not have as end-goal performance alone; instead, the
social impact of these agents when interacting with humans is as important and,
in most cases, never explored properly. This preregistration study focuses on
providing a novel learning mechanism based on a rivalry social impact. Our
scenario explored different reinforcement learning-based agents playing a
competitive card game against human players. Based on the concept of
competitive rivalry, our analysis aims to investigate if we can change the
assessment of these agents from a human perspective.


  We extend the linear {\pi}-calculus with composite regular types in such a
way that data containing linear values can be shared among several processes,
if there is no overlapping access to such values. We describe a type
reconstruction algorithm for the extended type system and discuss some
practical aspects of its implementation.


  We report on the redshift measurement and CO line excitation of HERMES
J105751.1+573027 (HLSW-01), a strongly lensed submillimeter galaxy discovered
in Herschel/SPIRE observations as part of the Herschel Multi-tiered
Extragalactic Survey (HerMES). HLSW-01 is an ultra-luminous galaxy with an
intrinsic far-infrared luminosity of 1.4x10^(13) solar luminosities, and is
lensed by a massive group of galaxies into at least four images with a total
magnification of 10.9+/-0.7. With the 100 GHz instantaneous bandwidth of the
Z-Spec instrument on the Caltech Submillimeter Observatory, we robustly
identify a redshift of z=2.958+/-0.007 for this source, using the simultaneous
detection of four CO emission lines (J = 7-6, J = 8-7, J = 9-8, and J = 10-9).
Combining the measured line fluxes for these high-J transitions with the J =
1-0, J = 3-2 and J = 5-4 line fluxes measured with the Green Bank Telescope,
the Combined Array for Research in Millimeter Astronomy, and the Plateau de
Bure Interferometer, respectively, we model the physical properties of the
molecular gas in this galaxy. We find that the full CO spectral line energy
distribution is well described by warm, moderate-density gas with Tkin = 86-235
K and n(H2) = (1.1-3.5)x10^3 cm^(-3). However, it is possible that the
highest-J transitions are tracing a small fraction of very dense gas in
molecular cloud cores, and two-component models that include a warm/dense
molecular gas phase with Tkin ~ 200 K, n(H2) ~ 10^5 cm^(-3) are also consistent
with these data. Higher signal-to-noise measurements of the J(upper) > 7
transitions with high spectral resolution, combined with high spatial
resolution CO maps, are needed to improve our understanding of the gas
excitation, morphology, and dynamics of this interesting high-redshift galaxy.


  MACRO can detect three topologies of neutrino induced events, corresponding
to different parent neutrino energies. The most numerous sample is made of
upward throughgoing muons induced by atmospheric neutrinos of average energy
100 GeV. We have observed less events than expected events and the observed
zenith distribution does not fit the expected one in the no-oscillation
hypothesis, giving a maximum probability of 0.1 percent. Considering the
neutrino (numu-nutau) oscillation hypothesis the best probability (17 percent)
is obtained for maximum mixing and difference of square masses of a few times
10-3 eV2. The other detected samples are due to internally produced events and
upward-going stopping muons, corresponding to an average neutrino energy of
around 4 GeV. The results concerning these lower energy sample show a deficit
and a shape of the angular distributions in agreement with that predicted by
the oscillation model suggested by the higher energy sample. No evidence of a
neutrino signal due to dark matter particles in the direction of the core of
the Earth and of the Sun has been found among the background due to atmospheric
neutrinos and limits have been set. The neutralino hypothesis is investigated
and limits on its mass are given.


  What is the 'level of excellence' of a scientist and the real impact of
his/her work upon the scientific thinking and practising? How can we design a
fair, an unbiased metric -- and most importantly -- a metric robust to
manipulation?


  How to efficiently utilize temporal information to recover videos in a
consistent way is the main issue for video inpainting problems. Conventional 2D
CNNs have achieved good performance on image inpainting but often lead to
temporally inconsistent results where frames will flicker when applied to
videos (see
https://www.youtube.com/watch?v=87Vh1HDBjD0&list=PLPoVtv-xp_dL5uckIzz1PKwNjg1yI0I94&index=1);
3D CNNs can capture temporal information but are computationally intensive and
hard to train. In this paper, we present a novel component termed Learnable
Gated Temporal Shift Module (LGTSM) for video inpainting models that could
effectively tackle arbitrary video masks without additional parameters from 3D
convolutions. LGTSM is designed to let 2D convolutions make use of neighboring
frames more efficiently, which is crucial for video inpainting. Specifically,
in each layer, LGTSM learns to shift some channels to its temporal neighbors so
that 2D convolutions could be enhanced to handle temporal information.
Meanwhile, a gated convolution is applied to the layer to identify the masked
areas that are poisoning for conventional convolutions. On the FaceForensics
and Free-form Video Inpainting (FVI) dataset, our model achieves
state-of-the-art results with simply 33% of parameters and inference time.


  In this introductory article we present the basics of an approach to
implementing computational interpreting of natural language aiming to model the
meanings of words and phrases. Unlike other approaches, we attempt to define
the meanings of text fragments in a composable and computer interpretable way.
We discuss models and ideas for detecting different types of semantic
incomprehension and choosing the interpretation that makes most sense in a
given context. Knowledge representation is designed for handling
context-sensitive and uncertain / imprecise knowledge, and for easy
accommodation of new information. It stores quantitative information capturing
the essence of the concepts, because it is crucial for working with natural
language understanding and reasoning. Still, the representation is general
enough to allow for new knowledge to be learned, and even generated by the
system. The article concludes by discussing some reasoning-related topics:
possible approaches to generation of new abstract concepts, and describing
situations and concepts in words (e.g. for specifying interpretation
difficulties).


  We propose the possibility that compact extra dimensions can obtain large
size by higher dimensional inflation, relating the weakness of the actual
gravitational force to the size of the observable universe. Solution to the
horizon problem implies that the fundamental scale of gravity is smaller than
$10^{13}$ GeV which can be realised in a braneworld framework for any number of
extra dimensions. However, requirement of (approximate) flat power spectrum of
primordial density fluctuations consistent with present observations makes this
simple proposal possible only for one extra dimension at around the micron
scale. After the end of five-dimensional inflation, the radion modulus can be
stabilised at a vacuum with positive energy of the order of the present dark
energy scale. An attractive possibility is based on the contribution to the
Casimir energy of right-handed neutrinos with a mass at a similar scale.


  The paper citation network is a traditional social medium for the exchange of
ideas and knowledge. In this paper we view citation networks from the
perspective of information diffusion. We study the structural features of the
information paths through the citation networks of publications in computer
science, and analyze the impact of various citation choices on the subsequent
impact of the article. We find that citing recent papers and papers within the
same scholarly community garners a slightly larger number of citations on
average. However, this correlation is weaker among well-cited papers implying
that for high impact work citing within one's field is of lesser importance. We
also study differences in information flow for specific subsets of citation
networks: books versus conference and journal articles, different areas of
computer science, and different time periods.


  Improving the representation of contextual information is key to unlocking
the potential of end-to-end (E2E) automatic speech recognition (ASR). In this
work, we present a novel and simple approach for training an ASR context
mechanism with difficult negative examples. The main idea is to focus on proper
nouns (e.g., unique entities such as names of people and places) in the
reference transcript, and use phonetically similar phrases as negative
examples, encouraging the neural model to learn more discriminative
representations. We apply our approach to an end-to-end contextual ASR model
that jointly learns to transcribe and select the correct context items, and
show that our proposed method gives up to $53.1\%$ relative improvement in word
error rate (WER) across several benchmarks.


  Satisfiability Modulo Theories (SMT) has significant application in various
domains. In this paper, we focus on quantifier-free Satisfiablity Modulo Real
Arithmetic, referred to as SMT(RA), including both linear and non-linear real
arithmetic theories. As for non-linear real arithmetic theory, we focus on one
of its important fragments where the atomic constraints are multi-linear. We
propose the first local search algorithm for SMT(RA), called LocalSMT(RA),
based on two novel ideas. First, an interval-based operator is proposed to
cooperate with the traditional local search operator by considering the
interval information. Moreover, we propose a tie-breaking mechanism to further
evaluate the operations when the operations are indistinguishable according to
the score function. Experiments are conducted to evaluate LocalSMT(RA) on
benchmarks from SMT-LIB. The results show that LocalSMT(RA) is competitive with
the state-of-the-art SMT solvers, and performs particularly well on
multi-linear instances.


  We propose and verify experimentally a new concept for achieving strong
nonlinear coupling between the electromagnetic and elastic properties in
metamaterials. This coupling is provided through a novel degree of freedom in
metamaterial design: internal rotation within structural elements. Our
meta-atoms have high sensitivity to electromagnetic wave power, and the elastic
and electromagnetic properties can be independently designed to optimise the
response. We demonstrate a rich range of nonlinear phenomena including
self-tuning and bistability, and provide a comprehensive experimental
demonstration of the predicted effects.


  Bulk nuclear observables such as charge radii and binding energies are well
described by both nonrelativistic and covariant mean-field models. However,
predictions of neutron radii, which are not tightly constrained by reliable
data, vary significantly. The nature of this variation is investigated using
correlations between basic properties of the models and the neutron skin
thickness in lead. The results suggest that conventional covariant models are
too limited. The study is guided by principles and insights of effective field
theory (EFT), such as power counting, and the relation of mean-field models to
a more general EFT approach to nuclei is discussed.


  A conjecture in algorithmic model theory predicts that the model-checking
problem for first-order logic is fixed-parameter tractable on a hereditary
graph class if and only if the class is monadically dependent. Originating in
model theory, this notion is defined in terms of logic, and encompasses nowhere
dense classes, monadically stable classes, and classes of bounded twin-width.
Working towards this conjecture, we provide the first two combinatorial
characterizations of monadically dependent graph classes. This yields the
following dichotomy.
  On the structure side, we characterize monadic dependence by a
Ramsey-theoretic property called flip-breakability. This notion generalizes the
notions of uniform quasi-wideness, flip-flatness, and bounded grid rank, which
characterize nowhere denseness, monadic stability, and bounded twin-width,
respectively, and played a key role in their respective model checking
algorithms. Natural restrictions of flip-breakability additionally characterize
bounded treewidth and cliquewidth and bounded treedepth and shrubdepth.
  On the non-structure side, we characterize monadic dependence by explicitly
listing few families of forbidden induced subgraphs. This result is analogous
to the characterization of nowhere denseness via forbidden subdivided cliques,
and allows us to resolve one half of the motivating conjecture: First-order
model checking is AW[$*$]-hard on every hereditary graph class that is
monadically independent. The result moreover implies that hereditary graph
classes which are small, have almost bounded twin-width, or have almost bounded
flip-width, are monadically dependent.
  Lastly, we lift our result to also obtain a combinatorial dichotomy in the
more general setting of monadically dependent classes of binary structures.


  The electromagnetic effect is studied on the short wavelength branch of the
ion temperature gradient mode in the linear regime for the first time using a
global gyrokinetic model. The short wavelength ion temperature gradient mode
growth rate is found to be reduced in the presence of electromagnetic
perturbations at finite plasma $\beta$. The effect on real frequency is found
to be weak. The threshold value of $\eta_i$ is found to increase for the mode
as the magnitude of $\beta$ is increased. The global mode structure of the
short wavelength branch of the ion temperature gradient mode is compared with
the conventional branch. The magnetic character of the mode, measured as the
ratio of mode average square values of electromagnetic potential to
electrostatic potential, is found to increase with increasing values of the
plasma $\beta$. The mixing length estimate for flux shows that the maximum
contribution still comes from the long wavelengths modes. The magnitude of the
flux decreases with increasing $\beta$.


  The left-invariant sub-Lorentzian problem on the Heisenberg group is
considered. An optimal synthesis is constructed, the sub-Lorentzian distance
and spheres are described.


  We give a characterization of those Alexandrov spaces admitting a
cohomogeneity one action of a compact connected Lie group $G$ for which the
action is Cohen--Macaulay. This generalizes a similar result for manifolds to
the singular setting of Alexandrov spaces where, in contrast to the manifold
case, we find several actions which are not Cohen--Macaulay. In fact, we
present results in a slightly more general context. We extend the methods in
this field by a conceptual approach on equivariant cohomology via rational
homotopy theory using an explicit rational model for a double mapping cylinder.


  We present millimetre-line imaging of the Galactic HII region Sh 104. We show
that it is surrounded by a ring of molecular gas and dust. Four large molecular
condensations are regularly spaced around the ring. These condensations are
themselves fragmented and contain several massive dense cores. A deeply
embedded cluster is observed in the near IR towards the largest condensation.
It contains at least one massive star ionizing an ultra-compact HII region. The
Sh 104 region is a good illustration of the `collect and collapse' model for
star formation triggered by the expansion of an HII region.


  We extend the standard model fermions by a mirror copy to realize a
left-right symmetry. During a strongly first order phase transition of the
spontaneous left-right symmetry breaking, the CP-violating reflections of the
mirror fermions off the mirror Higgs bubbles can generate a mirror lepton
asymmetry and an equal mirror baryon asymmetry. We then can obtain an ordinary
baryon asymmetry through the mirror fermion decays where a dark matter scalar
plays an essential role. Benefitted from a parity symmetry for solving the
strong CP problem, the cosmic baryon asymmetry can be well described by the
ordinary lepton mass matrices up to an overall factor. In this scenario, the
Dirac CP phase in the Majorana neutrino mass matrix can provide a unique source
for the required CP violation. Furthermore, the Higgs triplet for type-II
seesaw as well as the first generation of mirror charged fermions can be
allowed at the TeV scale.


  Pinnipeds like seals and sea lions use their whiskers in hunting their prey
in dark and turbid conditions. There is no theoretical model or a hypothesis to
explain the interaction of whiskers with hydrodynamic fish trails. The present
work provides insight into the mechanism behind the Strouhal frequency
identification from a Von-Karman vortex street behind bluff bodies, similar to
the inverted hydrodynamic fish trail. Flow over 3D printed sea lion head with
integrated whiskers of similar geometrical and material properties was
investigated when being exposed to vortex streets behind cylindrical bluff
bodies. It is found that the whiskers respond to the vortices by a jerky motion
similar to the stick-slip response of rat whiskers on different surface
textures. The Strouhal frequency of the upstream wake is clearly decoded with
the time-derivative of the whisker response rather than the displacement
response, which increases the sensing efficiency in noisy environments. It is
hypothesized from the work that the time derivative of the bending moment of
the whiskers is the best physical variable, which can be used as the input to
the neural system of the pinnipeds.


  We search for weakly interacting fixed points in extensions of the minimally
supersymmetric standard model (MSSM). Necessary conditions lead to three
distinct classes of anomaly-free extensions involving either new quark
singlets, new quark doublets, or a fourth generation. While interacting fixed
points arise prolifically in asymptotically free theories, their existence is
significantly constrained as soon as some of the non-abelian gauge sectors are
infrared free. Performing a scan over $\sim 200$k different MSSM extensions
using matter field multiplicities and the number of superpotential couplings as
free parameters, we find mostly infrared conformal fixed points, and a small
subset with ultraviolet ones. All settings predict low-scale
supersymmetry-breaking and a violation of $R$-parity. Despite of residual
interactions, the running of couplings out of asymptotically safe fixed points
is logarithmic as in asymptotic freedom. Some fixed points can be matched to
the Standard Model though the matching scale comes out too low. Prospects for
higher matching scales and asymptotic safety beyond the MSSM are indicated.


  We present 63 Solar analogues and twins for which high S/N archival data are
available for the HARPS high resolution spectrograph at the ESO 3.6m telescope.
We perform a differential analysis of these stellar spectra relative to the
Solar spectrum, similar to previous work using ESO 2.2m/FEROS data, and expand
our analysis by introducing a new method to test the temperature and
metallicity calibration of Sun-like stars in the Geneva-Copenhagen-Survey
(GCS). The HARPS data are significantly better than the FEROS data, with
improvements in S/N, spectral resolution, and number of lines we can analyse.
We confirm the offsets to the photometric scale found in our FEROS study. We
confirm 3 Solar twins found in the FEROS data as Solar twins in the HARPS data,
as well as identify 6 new twins.


  Effective field theories of the strong interactions based on the approximate
chiral symmetry of QCD provide a model-independent approach to low-energy
hadron physics. We give a brief introduction to mesonic and baryonic chiral
perturbation theory and discuss a number of applications. We also consider the
effective field theory including vector and axial-vector mesons.


  We present a multiwavelength study of the OH megamaser galaxy (OHMG)
IRAS17526+3253, based on new Gemini Multi-Object Spectrograph Integral Field
Unit (GMOS/IFU) observations, Hubble Space Telescope F814W and H$\alpha$+[N{\sc
ii}] images, and archival 2MASS and 1.49GHz VLA data. The HST images clearly
reveal a mid-to-advanced stage major merger whose northwestern and southeastern
nuclei have a projected separation of $\sim$8.5kpc. Our HST/H$\alpha$+[N{\sc
ii}] image shows regions of ongoing star-formation across the envelope on
$\sim$10kpc scales, which are aligned with radio features, supporting the
interpretation that the radio emission originates from star-forming regions.
The measured H$\alpha$ luminosities imply that the unobscured star-formation
rate is $\sim$10-30\,M$_{\odot}$yr$^{-1}$. The GMOS/IFU data reveal two
structures in northwestern separated by 850\,pc and by a discontinuity in the
velocity field of $\sim$~200~km~s$^{-1}$. We associate the blue-shifted and
red-shifted components with, respectively, the distorted disk of northwestern
and tidal debris, possibly a tail originating in southeastern. Star-formation
is the main ionization source in both components, which have SFRs of
$\sim$2.6-7.9\,M$_{\odot}$yr$^{-1}$ and $\sim$1.5-4.5\,M$_{\odot}$yr$^{-1}$,
respectively. Fainter line emission bordering these main components is
consistent with shock ionization at a velocity $\sim$200~km~s$^{-1}$ and may be
the result of an interaction between the tidal tail and the northwestern
galaxy's disk. IRAS17526+3253 is one of only a few systems known to host both
luminous OH and H$_{2}$O masers. The velocities of the OH and H$_{2}$O maser
lines suggest that they are associated with the northwestern and southeastern
galaxies, respectively.


  We prove a higher regularity result for weak solutions to nonlinear nonlocal
equations along the integrability scale of Bessel potential spaces $H^{s,p}$
under a mild continuity assumption on the kernel. By embedding, this also
yields regularity in Sobolev-Slobodeckij spaces $W^{s,p}$. Our approach is
based on a characterization of Bessel potential spaces in terms of a certain
nonlocal gradient-type operator and a perturbation approach commonly used in
the context of local elliptic equations in divergence form.


  Nuclear saturation is a crucial feature in nuclear physics that plays a
fundamental role in understanding various nuclear phenomena, ranging from
properties of finite nuclei to those of neutron stars. However, a proper
description of nuclear saturation is highly nontrivial in modern
nonrelativistic~\textit{ab initio}~studies because of the elusive three-body
forces. In this letter, we calculate the equation of state for nuclear matter
in the relativistic Brueckner-Hartree-Fock (RBHF) framework with the leading
order covariant chiral nuclear force. We show that a simultaneous description
of the nucleon-nucleon scattering data and the saturation of the symmetric
nuclear matter can be achieved. In this regard, the relativistic effects nicely
explain the saturation of nuclear matter. As a result, the present study based
on the covariant chiral nuclear force shows that in the RBHF framework, one can
achieve saturation with a leading order covariant chiral nuclear force with
only two-body forces, in contrast to the vast majorities of studies in the
non-relativistic framework, where the next-to-next-to-leading order two-body
and three-body chiral forces are needed. This study sets the foundation for
studying nuclear saturation with the covariant chiral force in the RBHF
framework, which allows for a systematic understanding of one of the key
features of nuclear physics more microscopically.


  The influence of incommensurate spin density waves (SDW) on superconductivity
in unconventional superconductors is studied by means of the Bogolubov-de
Gennes (BdG) equations. Exploiting translational symmetries of a magnetically
ordered two-dimensional system we propose an approach that allows to solve the
BdG equations on much larger clusters than it is usually possible for
inhomogeneous systems. Applying this approach we demonstrate that the presence
of incommensurate spin density waves induces real-space inhomogeneity of the
superconducting order parameter even in the absence of external magnetic field.
In this case a homogeneous order parameter of the
Bardeen-Cooper-Schrieffer-type superconducting state is slightly modulated, or
equivalently, a small fraction of the charge carriers form Cooper pairs with
non-zero total momentum. However, when a sufficiently strong magnetic field is
applied, the homogeneous component of the order parameter is suppressed and the
system transits to the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state, where the
order parameter oscillates changing sign. We show that for s-wave pairing the
presence of external magnetic field diminishes the destructive influence of the
SDW order on superconductivity. A simple explanation of this effect is also
proposed.


  We investigate theoretically the resonant splitting of ballistic conductance
peaks in magnetic superlattices. It is found that, for magnetic superlattices
with periodically arranged $n$ identical magnetic-barriers, there exists a
general $(n-1)$-fold resonant peak splitting rule for ballistic conductance,
which is the analogy of the $(n-1)$-fold resonant splitting for transmission in
$n$-barrier electric superlattices (R. Tsu and L. Esaki, Appl. Phys. Lett. {\bf
22}, 562 (1973)).


  We demonstrate the direct dry transfer of large area Chemical Vapor
Deposition graphene to several polymers (low density polyethylene, high density
polyethylene, polystyrene, polylactide acid and
poly(vinylidenefluoride-co-trifluoroethylene) by means of only moderate heat
and pressure, and the later mechanical peeling of the original graphene
substrate. Simulations of the graphene-polymer interactions, rheological tests
and graphene transfer at various experimental conditions show that controlling
the graphene-polymer interface is the key to controlling graphene transfer.
Raman spectroscopy and Optical Microscopy were used to identify and quantify
graphene transferred to the polymer substrates. The results showed that the
amount of graphene transferred to the polymer, from no-graphene to full
graphene transfers, can be achieved by fine tuning the transfer conditions. As
a result of the direct dry transfer technique, the graphene-polymer adhesion
being stronger than graphene to Si/SiO2 wafer.


  Sequential recommender systems have achieved state-of-the-art recommendation
performance by modeling the sequential dynamics of user activities. However, in
most recommendation scenarios, the popular items comprise the major part of the
previous user actions. Therefore, the learned models are biased towards the
popular items irrespective of the user's real interests. In this paper, we
propose a structural causal model-based method to address the popularity bias
issue for sequential recommendation model learning. For more generalizable
modeling, we disentangle the popularity and interest representations at both
the item side and user context side. Based on the disentangled representation,
we identify a more effective structural causal graph for general recommendation
applications. Then, we design delicate sequential models to apply the
aforementioned causal graph to the sequential recommendation scenario for
unbiased prediction with counterfactual reasoning. Furthermore, we conduct
extensive offline experiments and online A/B tests to verify the proposed
\textbf{DCR} (Disentangled Counterfactual Reasoning) method's superior overall
performance and understand the effectiveness of the various introduced
components. Based on our knowledge, this is the first structural causal model
specifically designed for the popularity bias correction of sequential
recommendation models, which achieves significant performance gains over the
existing methods.


  Background. The large-scale pattern of distribution of genes on the
chromosomes in the known animal genomes is not well characterized. We
hypothesized that individual genes will be distributed on chromosomes in a
mathematically ordered manner across the animal kingdom. Results. Twenty-one
animal genomes reported in the NCBI database were examined. Numerically, there
was a trend towards increasing overall gene content with increasing size of the
genome as reflected by the chromosomal complement. Gene frequency on individual
chromosomes in each animal genome was analyzed and demonstrated uniformity of
proportions within each animal with respect to both average gene frequency on
individual chromosomes and gene distribution across the unique genomes.
Further, average gene distribution across animal species followed a
relationship whereby it was, approximately, inversely proportional to the
square root of the number of chromosomes in the unique animal genomes,
consistent with the notion that there is an ordered increase in gene dispersion
as the complexity of the genome increased. To further corroborate these
findings a derived measure, termed gene spacing on chromosomes correlated with
gene frequency and gene distribution. Conclusion. As animal species have
evolved, the distribution of their genes on individual chromosomes and within
their genomes, when viewed on a large scale is not random, but follows a
mathematically ordered process, such that as the complexity of the organism
increases, the genes become less densely distributed on the chromosomes and
more dispersed across the genome.


  Generative Pre-trained Transformer 4 (GPT-4) is the fourth-generation
language model in the GPT series, developed by OpenAI, which promises
significant advancements in the field of natural language processing (NLP). In
this research article, we have discussed the features of GPT-4, its potential
applications, and the challenges that it might face. We have also compared
GPT-4 with its predecessor, GPT-3. GPT-4 has a larger model size (more than one
trillion), better multilingual capabilities, improved contextual understanding,
and reasoning capabilities than GPT-3. Some of the potential applications of
GPT-4 include chatbots, personal assistants, language translation, text
summarization, and question-answering. However, GPT-4 poses several challenges
and limitations such as computational requirements, data requirements, and
ethical concerns.


  In this work, we propose Dilated Point Convolutions (DPC). In a thorough
ablation study, we show that the receptive field size is directly related to
the performance of 3D point cloud processing tasks, including semantic
segmentation and object classification. Point convolutions are widely used to
efficiently process 3D data representations such as point clouds or graphs.
However, we observe that the receptive field size of recent point convolutional
networks is inherently limited. Our dilated point convolutions alleviate this
issue, they significantly increase the receptive field size of point
convolutions. Importantly, our dilation mechanism can easily be integrated into
most existing point convolutional networks. To evaluate the resulting network
architectures, we visualize the receptive field and report competitive scores
on popular point cloud benchmarks.


  Digitalization and sector coupling enable companies to turn into flexumers.
By using the flexibility of their multi-energy system (MES), they reduce costs
and carbon emissions while stabilizing the electricity system. However, to
identify the necessary investments in energy conversion and storage
technologies to leverage demand response (DR) potentials, companies need to
assess the value of flexibility. Therefore, this study quantifies the
flexibility value of a production company's MES by optimizing the synthesis,
design, and operation of a decarbonizing MES considering self-consumption
optimization, peak shaving, and integrated DR based on hourly prices and carbon
emission factors (CEFs). The detailed case study of a beverage company in
northern Germany considers vehicle-to-X of powered industrial trucks,
power-to-heat on multiple temperatures, wind turbines, photovoltaic systems,
and energy storage systems (thermal energy, electricity, and hydrogen). We
propose and apply novel data-driven metrics to evaluate the intensity of
price-based and CEF-based DR. The results reveal that flexibility usage reduces
decarbonization costs (by 19-80% depending on electricity and carbon removal
prices), total annual costs, operating carbon emissions, energy-weighted
average prices and CEFs, and fossil energy dependency. The results also suggest
that a net-zero operational carbon emission MES requires flexibility, which, in
an economic case, is provided by a combination of different flexible
technologies and storage systems that complement each other. While the value of
flexibility depends on various market and consumer-specific factors such as
electricity or carbon removal prices, this study highlights the importance of
demand flexibility for the decarbonization of MESs.


  Let $D$ be a nonempty domain in $\mathbb C^n$. We give a scale of necessary
conditions for the distribution of the zero set of holomorphic function $f$ on
domain $D\subset {\mathbb C}^n$ under a restriction on its growth $|f|\leq \exp
M$, where $M\not\equiv -\infty$ is a subharmonic function. If $n=1$, $D\neq
\mathbb C$ is simply connected, and $M$ is continuous, then this conditions are
sufficient.


  A scalar singlet, coupled to the other particles only through its mixing with
the Higgs boson, appears in several motivated extensions of the Standard Model.
The prospects for the discovery of a generic singlet at the various stages of
the LHC, as well as at future high-energy colliders, are studied, and the reach
of direct searches is compared with the precision attainable with Higgs
couplings measurements. The results are then applied to the NMSSM and Twin
Higgs.


  A recent technology breakthrough in spatial molecular profiling has enabled
the comprehensive molecular characterizations of single cells while preserving
spatial information. It provides new opportunities to delineate how cells from
different origins form tissues with distinctive structures and functions. One
immediate question in spatial molecular profiling data analysis is to identify
genes whose expressions exhibit spatially correlated patterns, called spatially
variable genes. Most current methods to identify spatially variable genes are
built upon the geostatistical model with Gaussian process to capture the
spatial patterns, which rely on ad hoc kernels that could limit the models'
ability to identify complex spatial patterns. In order to overcome this
challenge and capture more types of spatial patterns, we introduce a Bayesian
approach to identify spatially variable genes via a modified Ising model. The
key idea is to use the energy interaction parameter of the Ising model to
characterize spatial expression patterns. We use auxiliary variable Markov
chain Monte Carlo algorithms to sample from the posterior distribution with an
intractable normalizing constant in the model. Simulation studies using both
simulated and synthetic data showed that the energy-based modeling approach led
to higher accuracy in detecting spatially variable genes than those
kernel-based methods. When applied to two real spatial transcriptomics
datasets, the proposed method discovered novel spatial patterns that shed light
on the biological mechanisms. In summary, the proposed method presents a new
perspective for analyzing spatial transcriptomics data.


  GAP functions are useful for solving optimization problems, but the
literature contains a variety of different concepts of GAP functions. It is
interesting to point out that these concepts have many similarities. Here we
introduce G-coupling functions, thus presenting a way to take advantage of
these common properties.


  In Newtonian space-time there exist four, and only four, causal classes of
frames. Natural frames allow to extend this result to coordinate systems, so
that coordinate systems may be also locally classified in four causal classes.
These causal classes admit simple geometric descriptions and physical
interpretations. For example, one can generate representatives of the four
causal classes by means of the {\em linear synchronization group}. Of
particular interest is the {\em local Solar time synchronization}, which
reveals the limits of the frequent use of the concept of `causally oriented
oordinate', such as that of `time-like coordinate'. Classical {\em positioning
systems}, based in sound or light signals, are, by themselves, interesting
examples of location systems, i.e. of physically constructible coordinate
systems. They show that one can locate events in Newtonian space-time {\em
without} any use of the concept of synchronization. In fact, the coordinate
systems associated to positioning systems, belong to all the classes but the
standard one, i.e. the one based in the simultaneity synchronization. The
relativistic analogs of these examples, emphasize the contrast between the four
Newtonian and the one hundred and ninety nine Lorentzian causal classes of
frames of classical and relativistic space-times, respectively.


  Here we present the results of applying the generalized Riemann zeta-function
regularization method to the gravitational radiation reaction problem. We
analyze in detail the headon collision of two nonspinning black holes with
extreme mass ratio. The resulting reaction force on the smaller hole is
repulsive. We discuss the possible extensions of these method to generic orbits
and spinning black holes. The determination of corrected trajectories allows to
add second perturbative corrections with the consequent increase in the
accuracy of computed waveforms.


  Stars twinkle to the eye through atmospheric turbulence, but planets, because
of their larger angular size, do not. Similarly, scintillation due to the local
interstellar medium will modulate the radio flux of gamma-ray-burst afterglows
and may permit indirect measurements of their angular sizes. The amplitude of
refractive scintillation is of order ten percent at ten gigahertz unless the
source size is much larger than the expected size, of order ten
microarcseconds. Diffractive scintillation is marginally possible, depending
sensitively on the source size, observing frequency, and scattering measure of
the interstellar medium.


  The model theory of a first-order logic called N^4 is introduced. N^4 does
not eliminate double negations, as classical logic does, but instead reduces
fourfold negations. N^4 is very close to classical logic: N^4 has two truth
values; implications in N^4 are material, like in classical logic; and negation
distributes over compound formulas in N^4 as it does in classical logic.
Results suggest that the semantics of normal logic programs is conveniently
formalized in N^4: Classical logic Herbrand interpretations generalize
straightforwardly to N^4; the classical minimal Herbrand model of a positive
logic program coincides with its unique minimal N^4 Herbrand model; the stable
models of a normal logic program and its so-called complete minimal N^4
Herbrand models coincide.


  We present ultraviolet spectroscopy covering the Ly$\alpha$ + N V complex of
six candidate low-redshift ($0.9 < z < 1.5$) weak emission-line quasars (WLQs)
based on observations with the Hubble Space Telescope. The original systematic
searches for these puzzling Type 1 quasars with intrinsically weak broad
emission lines revealed an $N \approx 100$ WLQ population from optical
spectroscopy of high-redshift ($z > 3$) quasars, defined by a Ly$\alpha$ + N V
rest-frame equivalent width (EW) threshold $< 15.4$ \r{A}. Identification of
lower-redshift ($z < 3$) WLQ candidates, however, has relied primarily on
optical spectroscopy of weak broad emission lines at longer rest-frame
wavelengths. With these new observations expanding existing optical coverage
into the ultraviolet, we explore unifying the low- and high-$z$ WLQ populations
via EW[Ly$\alpha$+NV]. Two objects in the sample unify with high-$z$ WLQs,
three others appear consistent with the intermediate portion of the population
connecting WLQs and normal quasars, and the final object is consistent with
typical quasars. The expanded wavelength coverage improves the number of
available line diagnostics for our individual targets, allowing a better
understanding of the shapes of their ionizing continua. The ratio of
EW[Ly$\alpha$+NV] to EW[MgII] in our sample is generally small but varied,
favoring a soft ionizing continuum scenario for WLQs, and we find a lack of
correlation between EW[Ly$\alpha$+NV] and the X-ray properties of our targets,
consistent with a "slim-disk" shielding gas model. We also find indications
that weak absorption may be a more significant contaminant in low-$z$ WLQ
populations than previously thought.


  We consider a model for a polymer interacting with an attractive wall through
a random sequence of charges. We focus on the so-called diluted limit, when the
charges are very rare but have strong intensity. In this regime, we determine
the quenched critical point of the model, showing that it is different from the
annealed one. The proof is based on a rigorous renormalization procedure.
Applications of our results to the problem of a copolymer near a selective
interface are discussed.


  We investigated the viscoelastic response of model interphase chromosomes by
tracking the three-dimensional motion of hundreds of dispersed Brownian
particles of sizes ranging from the thickness of the chromatin fiber up to
slightly above the mesh size of the chromatin solution. In agreement with
previous computational studies on polymer solutions and melts, we found that
the large-time behaviour of diffusion coefficient and the experienced viscosity
of moving particles as functions of particle size deviate from the traditional
Stokes-Einstein relation, and agree with a recent scaling theory of diffusion
of non-sticky particles in polymer solutions. Interestingly, we found that at
short times large particles are temporary "caged" by chromatin spatial
constraints, which thus form effective domains whose size match remarkably well
recent experimental results for micro-tracers inside interphase nuclei.
Finally, by employing a known mathematical relation between the time
mean-square displacement of tracked particles and the complex shear modulus of
the surrounding solution, we calculated the elastic and viscous moduli of
interphase chromosomes.


  The sensitivity of the nitrogen-vacancy (NV) color centers in diamond-based
magnetometers strongly depends on the number of NV centers involved in the
measurement. Unfortunately, an increasing concentration of NV centers leads to
decreases of their dephasing and coherence time if the nitrogen content exceeds
a certain threshold level (approximately ${10^{17}}{\rm{ c}}{{\rm{m}}^{ -
3}}$). Here, we demonstrate that this increased dephasing can be efficiently
compensated by postprocessing procedures in the vicinity of the threshold
concertation, thus extending possible useful concentrations on NV centers with
the maximum possible decoherence time in diamonds with a natural carbon
content.


  Predicting the transition temperature, Tc, of a superconductor from Periodic
Table normal state properties is regarded as one of the grand challenges of
superconductivity. By studying the correlations of Periodic Table properties
with known superconductors, it is possible to estimate their transition
temperatures. Starting from the isotope effect and correlations of
superconductivity with electronegativity (\Chi), valence electron count per
atom (Ne), atomic number(Z) and formula weight (Fw), we derive an empirical
formula for estimating Tc that includes an unknown parameter,(Ko). With average
values of \Chi, Ne and Z, we develop a material specific characterization
dataset (MSCD) model of a superconductor that is quantitatively useful for
characterizing and comparing superconductors. We show that for most
superconductors, Ko correlates with Fw/Z, Ne, Z, number of atoms (An) in the
formula, number of elements (En) and with Tc. We study some superconductor
families and use the discovered correlations to predict similar and novel
superconductors and also estimate their Tcs. Thus the material specific
equations derived in this paper, the material specific characterization dataset
(MSCD) system developed here and the discovered correlation between Tc and
Fw/Z, En and An, provide the building blocks for the analysis, design and
search of potential novel high temperature superconductors with specific
estimated Tcs.


  We perform the complete one-loop renormalization of a general
two-Higgs-doublet model. We present all the vertices for this model including
the ones in the scalar sector and calculate all the counterterms of the theory.


  Dynamic Discrete Choice Models (DDCMs) are important in the structural
estimation literature. Since the structural errors are practically always
continuous and unbounded in nature, researchers often use the expected value
function. The idea to solve for the expected value function made solution more
practical and estimation feasible. However, as we show in this paper, the
expected value function is impractical compared to an alternative: the
integrated (ex ante) value function. We provide brief descriptions of the
inefficacy of the former, and benchmarks on actual problems with varying
cardinality of the state space and number of decisions. Though the two
approaches solve the same problem in theory, the benchmarks support the claim
that the integrated value function is preferred in practice.


  In this paper, we review the undercutting attacks in the
transaction-fee-based regime of proof-of-work (PoW) blockchains with the
longest chain fork-choice rule. Next, we focus on the problem of fluctuations
in mining revenue and the mining gap - i.e., a situation, in which the
immediate reward from transaction fees does not cover miners' expenditures.
  To mitigate these issues, we propose a solution that splits transaction fees
from a mined block into two parts - (1) an instant reward for the miner of a
block and (2) a deposit sent to one or more fee-redistribution smart contracts
($\mathcal{FRSC}$s) that are part of the consensus protocol. At the same time,
these redistribution smart contracts reward the miner of a block with a certain
fraction of the accumulated funds of the incoming fees over a predefined time.
This setting enables us to achieve several interesting properties that are
beneficial for the incentive stability and security of the protocol.
  With our solution, the fraction of Default-Compliant miners who strictly do
not execute undercutting attacks is lowered from the state-of-the-art result of
66% to 30%.