  Universally valid ground truth is almost impossible to obtain or would come
at a very high cost. For supervised learning without universally valid ground
truth, a recommended approach is applying crowdsourcing: Gathering a large data
set annotated by multiple individuals of varying possibly expertise levels and
inferring the ground truth data to be used as labels to train the classifier.
Nevertheless, due to the sensitivity of the problem at hand (e.g. mitosis
detection in breast cancer histology images), the obtained data needs
verification and proper assessment before being used for classifier training.
Even in the context of organic computing systems, an indisputable ground truth
might not always exist. Therefore, it should be inferred through the
aggregation and verification of the local knowledge of each autonomous agent.


  Possible main formation sites of F in the Universe include AGB stars, the
{\nu}-process in Type II SNe, and/or W-R stars. The importance of the W-R stars
has theoretically been questioned and they are probably not needed in the
modelling of the chemical evolution of F in the solar neighborhood. It has,
however, been suggested that W-R stars are indeed needed to explain the
chemical evolution of F in the Bulge. The molecular spectral data of the often
used HF-molecule has not been presented in a complete and consistent way and
has recently been debated in the literature. In this article we determine the
[F/O] vs. [O/H] trend in the Bulge to investigate the possible contribution
from W-R stars. Additionally, we present here a HF line list for the K- and
L-bands (including the often used 23358.33 {\AA} line) and an accompanying
partition function. The F abundances were determined using spectral fitting
from hi-res NIR spectra of eight K giants recorded by the spectrograph CRIRES.
We have also re-analyzed five previously published Bulge giants using our new
HF molecular data. We find that the F-O abundance in the Bulge probably cannot
be explained with chemical evolution models including only AGB-stars and the
{\nu}-process in SNe Type II, i.e. a significant amount of F production in W-R
stars is likely needed to explain the F abundance in the Bulge. Concerning the
HF line list, we find that a possible reason for the inconsistencies in the
literature, with two different excitation energies being used, is two different
definitions of the zero-point energy for the HF molecule and therefore also two
accompanying different dissociation energies. Both line lists are correct, as
long as the corresponding consistent partition function is used in the spectral
synthesis. However, we suspect this has not been the case in several earlier
works leading to F abundances 0.3 dex too high.


  We present a novel Bayesian inference tool that uses a neural network to
parameterise efficient Markov Chain Monte-Carlo (MCMC) proposals. The target
distribution is first transformed into a diagonal, unit variance Gaussian by a
series of non-linear, invertible, and non-volume preserving flows. Neural
networks are extremely expressive, and can transform complex targets to a
simple latent representation. Efficient proposals can then be made in this
space, and we demonstrate a high degree of mixing on several challenging
distributions. Parameter space can naturally be split into a block diagonal
speed hierarchy, allowing for fast exploration of subspaces where it is
inexpensive to evaluate the likelihood. Using this method, we develop a nested
MCMC sampler to perform Bayesian inference and model comparison, finding
excellent performance on highly curved and multi-modal analytic likelihoods. We
also test it on {\em Planck} 2015 data, showing accurate parameter constraints,
and calculate the evidence for simple one-parameter extensions to LCDM in
$\sim20$ dimensional parameter space. Our method has wide applicability to a
range of problems in astronomy and cosmology.


  ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time
projection chamber that operated in a hadron test beam at the CERN Neutrino
Platform in 2018. We present a measurement of the total inelastic cross section
of charged kaons on argon as a function of kaon energy using 6 and 7 GeV/$c$
beam momentum settings. The flux-weighted average of the extracted inelastic
cross section at each beam momentum setting was measured to be 380$\pm$26
mbarns for the 6 GeV/$c$ setting and 379$\pm$35 mbarns for the 7 GeV/$c$
setting.


  Factor analysis is a statistical technique that explains correlations among
observed random variables with the help of a smaller number of unobserved
factors. In traditional full factor analysis, each observed variable is
influenced by every factor. However, many applications exhibit interesting
sparsity patterns, that is, each observed variable only depends on a subset of
the factors. In this paper, we study such sparse factor analysis models from an
algebro-geometric perspective. Under mild conditions on the sparsity pattern,
we examine the dimension of the set of covariance matrices that corresponds to
a given model. Moreover, we study algebraic relations among the covariances in
sparse two-factor models. In particular, we identify cases in which a Gr\"obner
basis for these relations can be derived via a 2-delightful term order and
joins of toric edge ideals.


  We study a pair of commuting difference operators arising from the elliptic
C_2^{(1)}-face model. The operators, whose coefficients are expressed in terms
of the Jacobi's elliptic theta function, act on the space of meromorphic
functions on the weight space of the C_2 type simple Lie algebra. We show that
the space of functions spanned by the level one characters of the affine Lie
algebra sp(4,C) is invariant under the action of the difference operators.


  While observing OB stars within the most crowded regions of the Large
Magellanic Cloud, we happened upon a new Wolf-Rayet star in Lucke-Hodge 41, the
rich OB association that contains S Doradus and numerous other massive stars.
At first glance the spectrum resembled that of a WC4 star, but closer
examination showed strong OVI 3811, 34 lines, leading us to classify it as a
WO4. This is only the second known WO in the LMC, and the first known WO4 (the
other being a WO3). This rarity is to be expected due to these stars' short
lifespans as they represent the most advanced evolutionary stage in a massive
star's lifetime before exploding as SNe. This discovery shows that while the
majority of WRs within the LMC have been discovered, there may be a few WRs
left to be found.


  We investigate non-relativistic quantum mechanical potentials between
fermions generated by various classes of QFT operators and evaluate their
singularity structure. These potentials can be generated either by four-fermion
operators or by the exchange of a scalar or vector mediator coupled via
renormalizable or non-renormalizable operators. In the non-relativistic regime,
solving the Schr\"odinger equation with these potentials provides an accurate
description of the scattering process. This procedure requires providing a set
of boundary conditions. We first recapitulate the procedure for setting the
boundary conditions by matching the first Born approximation in quantum
mechanics to the tree-level QFT approximation. Using this procedure, we show
that the potentials are nonsingular, despite the presence of terms proportional
to $r^{-3}$ and $\nabla_{i}\nabla_{j}\delta^{3}(\vec{r})$. This surprising
feature leads us to propose the \emph{Quantum Mechanics Swampland}, in which
the Landscape consists of non-relativistic quantum mechanical potentials that
can be UV completed to a QFT, and the Swampland consists of pathological
potentials which cannot. We identify preliminary criteria for distinguishing
potentials which reside in the Landscape from those that reside in the
Swampland. We also consider extensions to potentials in higher dimensions and
find that Coulomb potentials are nonsingular in an arbitrary number of
spacetime dimensions.


  The modular envelope of a cyclic operad is the smallest modular operad
containing it. A modular operad is constructed from moduli spaces of Riemann
surfaces with boundary; this modular operad is shown to be the modular envelope
of the A-infinity cyclic operad. This gives a new proof of the result of
Harer-Mumford-Thurston-Penner-Kontsevich that a cell complex built from ribbon
graphs is homotopy equivalent to the moduli space of curves.


  We introduce here a new axiomatisation of the rational fragment of the
ZX-calculus, a diagrammatic language for quantum mechanics. Compared to the
previous axiomatisation introduced in [8], our axiomatisation does not use any
metarule , but relies instead on a more natural rule, called the cyclotomic
supplementarity rule, that was introduced previously in the literature. Our
axiomatisation is only complete for diagrams using rational angles , and is not
complete in the general case. Using results on diophantine geometry, we
characterize precisely which diagram equality involving arbitrary angles are
provable in our framework without any new axioms, and we show that our
axiomatisation is continuous, in the sense that a diagram equality involving
arbitrary angles is provable iff it is a limit of diagram equalities involving
rational angles. We use this result to give a complete characterization of all
Euler equations that are provable in this axiomatisation.


  We present GPU accelerated simulations to calculate the annihilation energy
of magnetic skyrmions in an atomistic spin model considering dipole-dipole,
exchange, uniaxial-anisotropy and Dzyaloshinskii-Moriya interactions using the
simplified string method. The skyrmion annihilation energy is directly related
to its thermal stability and is a key measure for the applicability of magnetic
skyrmions to storage and logic devices. We investigate annihilations mediated
by Bloch points as well as annihilations via boundaries for various interaction
energies. Both processes show similar behaviour, with boundary annihilations
resulting in slightly smaller energy barriers than Bloch point annihilations.


  A new model for the origin of dark energy is proposed based on the Casimir
effect in a supersymmetry-breaking brane-world. Supersymmetry is assumed to be
preserved in the bulk while broken on a 3-brane. Due to the boundary conditions
imposed on the compactified extra dimensions, there is an effective Casimir
energy induced on the brane. The net Casimir energy contributed from the
graviton and the gravitino modes as a result of supersymmetry-breaking on the
brane is identified as the observed dark energy, which in our construction is a
cosmological constant. We show that the smallness of the cosmological constant,
which results from the huge contrast in the extra-dimensional volumes between
that associated with the 3-brane and that of the bulk, is attainable under very
relaxed conditions.


  A computer code is written that simulates the relaxation back to thermal
equilibrium of an ensemble of particles after a pi/2 pulse. Beginning with
Bloch's equations the exponential relaxation behavior is discussed and the
transition into a step by step process (from the continuous process) is made
such that it is possible for the computer code to simulate the action. An
analysis of Boltzmann's factor is offered and serves as the link between the
temperature of the ensemble and the parameter that is used to determine if a
spin is in the up state or the down state. The specifics of the code are
discussed and the spins are shown to follow the rules of interaction governed
by the physical collisions that can take place. Lastly, graphs of the
simulation are provided and a discussion of its usefulness is given.


  Control over minivalley polarization and interlayer coupling is demonstrated
in double bilayer graphene twisted with an angle of 2.37$^\circ$. This
intermediate angle is small enough for the minibands to form and large enough
such that the charge carrier gases in the layers can be tuned independently.
Using a dual-gated geometry we identify and control all possible combinations
of minivalley polarization via the population of the two bilayers. An applied
displacement field opens a band gap in either of the two bilayers, allowing us
to even obtain full minivalley polarization. In addition, the wavefunctions of
the minivalleys are mixed by tuning through a Lifshitz transition, where the
Fermi surface topology changes. The high degree of control makes twisted double
bilayer graphene a promising platform for valleytronics devices such as valley
valves, filters and logic gates.


  We demonstrate how probes of CP-violating observables in Higgs di-tau decays
at prospective future lepton colliders could provide a test of weak scale
baryogenesis with significant discovery potential. Measurements at the Circular
Electron Positron Collider, for example, could exclude a CP phase larger than
$2.9^\circ$ ($5.6^\circ$) at 68% (95%) C.L. assuming the Standard Model value
for magnitude of the tau lepton Yukawa coupling. Conversely, this sensitivity
would allow for a $5\,\sigma$ discovery for 82% of the CP phase range
$[0,2\pi)$. The reaches of the Future Circular Collider - ee and International
Linear Collider are comparable. As a consequence, future lepton colliders could
establish the presence of CP violation required by lepton flavored electroweak
baryogenesis with at least $3\,\sigma$ sensitivity. Our results illustrate that
Higgs factories are not just precision machines but can also make $\mathcal
O(1)$ measurement of the new physics beyond the Standard Model.


  We study the geodesics of massive particles around accelerating Schwarzschild
black hole. We show that the radius of the innermost stable circular orbit
increases and the angular momentum of particle at this orbit decreases by
increasing the acceleration. Apart from quantitative influence, the
acceleration qualitatively changes the physics. We show that in accelerating
black hole spacetime there exist an outermost stable circular orbit in flat, de
Sitter, and anti de Sitter background. Investigations of radial geodesics show
that the acceleration acts like a repulsive force in the sense that test
particles around accelerating black holes can move radially outward, unless
there exist a large negative value of cosmological constant in the background
to compensate the repulsive force. We also investigate the precession of
perihelion of orbits around accelerating black holes. The precession would be
larger compared to the non-accelerating case. It is also shown that the
precession in anti de Sitter background could be opposite to the particle
motion.


  A argument is described for how deformed or doubly special relativity may
arise in the semiclassical limit of a quantum theory of gravity. We consider a
generic quantum theory of gravity coupled to matter, from which we use only the
assumption that a Hamiltonian constraint is imposed. We study circumstances in
which Lambda, G and hbar all may be separately neglected, but there may arise
terms in the ratio of particle energies to the Planck mass which are small but
measurable. Such cases include probes of an energy dependent speed of light
such as are possible in experiments such as MAGIC and GLAST. We show that in
such cases the leading order effect of quantum gravity will, if certain scaling
relations are satisfied, be to deform the metric in the effective Hamiltonian
of the matter quantum field theory by terms linear in energies. As the
Hamiltonian constraint has been imposed there can be no preferred time
coordinate or frame of reference, hence this is a modification rather than a
breaking of special relativity.


  Three nonequivalent real forms of the complex twisted N=2 supersymmetric Toda
chain hierarchy (solv-int/9907021) in real N=1 superspace are presented. It is
demonstrated that they possess a global twisted N=2 supersymmetry. We discuss a
new superfield basis in which the supersymmetry transformations are local.
Furthermore, a representation of this hierarchy is given in terms of two
twisted chiral N=2 superfields. The relations to the s-Toda hierarchy by H.
Aratyn, E. Nissimov and S. Pacheva (solv-int/9801021) as well as to the
modified and derivative NLS hierarchies are established.


  We report on the progress in the study of a five-dimensional SU(2)
Gauge-Higgs Unification model. In this non-perturbative study, the Higgs
mechanism is triggered by the spontaneous breaking of a global symmetry. In the
same region of the phase diagram, we observe both dimensional reduction and the
ratio of Higgs and Z boson masses to take the value known from experiment. We
present the first results on the construction of a line of constant physics in
this region, including the prediction for the mass scale of the first excited
states of the Higgs and gauge bosons.


  It has been recently shown that the particle-hole symmetric Anderson impurity
model can be mapped onto a $Z_2$ slave-spin theory without any need of
additional constraints. Here we prove by means of Numerical Renormalization
Group that the slave-spin behaves in this model like a two-level system coupled
to a sub-ohmic dissipative environment. It follows that the $Z_2$ symmetry gets
spontaneously broken at zero temperature, which we find can be identified with
the on-set of Kondo coherence, being the Kondo temperature proportional to the
square of the order parameter. Since the model is numerically solvable, the
results are very enlightening on the role of quantum fluctuations beyond mean
field in the context of slave-boson approaches to correlated electron models,
an issue that has been attracting interest since the 80's. Finally, our results
suggest as a by-product that the paramagnetic metal phase of the Hubbard model
at half-filling, in infinite coordination lattices and at zero temperature, as
described for instance by Dynamical Mean Field Theory, corresponds to a
slave-spin theory with a spontaneous breakdown of a local $Z_2$ gauge symmetry.


  Low-dimensional ferroelectricity and Dirac materials with protected band
crossings are fascinating research subjects. Based on first-principles
calculations, we predict the coexistence of spontaneous in-plane polarization
and novel 2D emergent fermions in dynamically stable quadruple-layer (QL)
XSbO$_2$ (X= Li, Na). Depending on the different polarization configurations,
QL-XSbO$_2$ can exhibit unconventional inner-QL ferroelectricity and
antiferroelectricity. Both ground states harbor robust ferroelectricity with
enhanced spontaneous polarization of 0.56 nC/m and 0.39 nC/m for QL-LiSbO$_2$
and QL-NaSbO$_2$, respectively. Interestingly, the QL-LiSbO$_2$ possesses two
other metastable ferroelectric (FE) phases, demonstrating the first 2D example
with multiple FE orders. The ground FE phase can be flexibly driven into one of
the two metastable FE phases and then into the antiferroelectric (AFE) phase.
During this phase transition, several types of 2D fermions emerge, for
instance, hourglass hybrid and type-II Weyl loops in the ground FE phase,
type-II Weyl fermions in the metastable FE phase, and type-II Dirac fermions in
the AFE phase. These 2D fermions are robust under spin-orbit coupling. Notably,
two of these fermions, e.g., an hourglass hybrid or type-II Weyl loop, have not
been observed before. Our findings identify QL-XSbO$_2$ as a unique platform
for studying 2D ferroelectricity relating to 2D emergent fermions.


  We study bracket words, which are a far-reaching generalisation of Sturmian
words, along Hardy field sequences, which are a far-reaching generalisation of
Piatetski--Shapiro sequences $\lfloor n^c \rfloor$. We show that thus obtained
sequences are deterministic (i.e., they have sub-exponential subword
complexity) and satisfy Sarnak's conjecture.


  Tasks involving localization, memorization and planning in partially
observable 3D environments are an ongoing challenge in Deep Reinforcement
Learning. We present EgoMap, a spatially structured neural memory architecture.
EgoMap augments a deep reinforcement learning agent's performance in 3D
environments on challenging tasks with multi-step objectives. The EgoMap
architecture incorporates several inductive biases including a differentiable
inverse projection of CNN feature vectors onto a top-down spatially structured
map. The map is updated with ego-motion measurements through a differentiable
affine transform. We show this architecture outperforms both standard recurrent
agents and state of the art agents with structured memory. We demonstrate that
incorporating these inductive biases into an agent's architecture allows for
stable training with reward alone, circumventing the expense of acquiring and
labelling expert trajectories. A detailed ablation study demonstrates the
impact of key aspects of the architecture and through extensive qualitative
analysis, we show how the agent exploits its structured internal memory to
achieve higher performance.


  We consider the solution of initial value problems within the context of
hybrid systems and emphasise the use of high precision approximations (in
software for exact real arithmetic). We propose a novel algorithm for the
computation of trajectories up to the area where discontinuous jumps appear,
applicable for holomorphic flow functions. Examples with a prototypical
implementation illustrate that the algorithm might provide results with higher
precision than well-known ODE solvers at a similar computation time.


  Temperature is a crucial parameter in circumstellar disk evolution and planet
formation, because it governs the resistance of the gas to gravitational
instability and sets the chemical composition of the planet-forming material.
We set out to determine the gas temperature of the young disk-like structure
around the Class 0 protostar IRAS 16293$-$2422A. We use Atacama Large
Millimeter/submillimeter Array (ALMA) observations of multiple H$_2$CS $J=7-6$
and $J=10-9$ lines from the Protostellar Interferometric Line Survey (PILS) to
create a temperature map for the inner $\sim$200 AU of the disk-like structure.
This molecule is a particularly useful temperature probe because transitions
between energy levels with different $K_{\rm{a}}$ quantum numbers operate only
through collisions. Based on the H$_2$CS line ratios, the temperature is
between $\sim$100$-$175 K in the inner $\sim$150 AU, and drops to $\sim$75 K at
$\sim$200 AU. At the current resolution (0.5$^{\prime\prime} \sim$70 AU), no
jump is seen in the temperature at the disk-envelope interface. The temperature
structure derived from H$_2$CS is consistent with envelope temperature profiles
that constrain the temperature from 1000 AU scales down to $\sim$100 AU, but
does not follow the temperature rise seen in these profiles at smaller radii.
Higher angular resolution observations of optically thin temperature tracers
are needed to establish whether cooling by gas-phase water, the presence of a
putative disk or the dust optical depth influences the gas temperature at
$\lesssim$100 AU scales. The temperature at 100 AU is higher in IRAS 16293A
than in the embedded Class 0/I disk L1527, consistent with the higher
luminosity of the former.


  The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT)
challenge aims to advance automated segmentation algorithms using the largest
known multi-institutional dataset of radiotherapy planning brain MRIs with
expert-annotated target labels for patients with intact or post-operative
meningioma that underwent either conventional external beam radiotherapy or
stereotactic radiosurgery. Each case includes a defaced 3D post-contrast
T1-weighted radiotherapy planning MRI in its native acquisition space,
accompanied by a single-label "target volume" representing the gross tumor
volume (GTV) and any at-risk post-operative site. Target volume annotations
adhere to established radiotherapy planning protocols, ensuring consistency
across cases and institutions. For pre-operative meningiomas, the target volume
encompasses the entire GTV and associated nodular dural tail, while for
post-operative cases, it includes at-risk resection cavity margins as
determined by the treating institution. Case annotations were reviewed and
approved by expert neuroradiologists and radiation oncologists. Participating
teams will develop, containerize, and evaluate automated segmentation models
using this comprehensive dataset. Model performance will be assessed using the
lesion-wise Dice Similarity Coefficient and the 95% Hausdorff distance. The
top-performing teams will be recognized at the Medical Image Computing and
Computer Assisted Intervention Conference in October 2024. BraTS-MEN-RT is
expected to significantly advance automated radiotherapy planning by enabling
precise tumor segmentation and facilitating tailored treatment, ultimately
improving patient outcomes.


  Some electrolytic capacitors show dielectric behaviour that can not be
entirely explained by the well known long lasting relaxation. Extra charges
able to generate a useful conduction current can be detected for an indefinite
time. A squarewave oscillator based on MOSFET CMOS technology and requiring
less than 2 nW was powered for 80 days at 25 {\deg}C by a 58.2 mF capacitor
battery, without voltage decrease during the last 53 days of observation. The
battery consisted of three series of 16 parallel, 15 years aged, capacitors
with DC capacitance of 10.9 mF. Capacitors so old, stored without voltage
application, were affected by degradation and thinning of the alumina layer
that could promote tunnelling of the charge. The main purpose of the present
study is to stimulate further investigations aimed at confirming or disputing
the observed phenomenon and, if necessary, at shedding light on its physical
mechanisms.


  On a M\"obius surface, as defined by D. Calderbank, we study a variant of the
Einstein-Weyl (EW) equation which we call scalar-flat M\"obius EW (sf-MEW).
This is a conformally invariant, finite type, overdetermined system of
semi-linear partial differential equations. We derive local algebraic
constraints for this equation to admit a solution and give local obstructions.
In the generic case when a certain invariant of the M\"obius structure given by
a symmetric tensor $M_{ab}$ is non-zero, the obstructions are given by
resultants of 3 polynomial equations whose coefficients are conformal
invariants of the M\"obius structure. The vanishing of the resultants is a
necessary condition for there to be solutions to sf-MEW.


  Let $A,B \subset \mathbb{R}$ be closed Ahlfors-regular sets with dimensions
$\dim_{\mathrm{H}} A =: \alpha$ and $\dim_{\mathrm{H}} B =: \beta$. I prove
that $$\dim_{\mathrm{H}} [A + \theta B] \geq \alpha + \beta \cdot \tfrac{1 -
\alpha}{2 - \alpha}$$ for all $\theta \in \mathbb{R} \, \setminus \, E$, where
$\dim_{\mathrm{H}} E = 0$.


  The Monte Carlo HYDJET++ model, that combines parametrized hydrodynamics with
jets, is employed to study formation of second v_2 and fourth v_4 components of
the anisotropic flow in ultrarelativistic heavy-ion collisions at energies of
the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC),
sqrt{s}=200 AGeV and sqrt{s}=2.76 ATeV, respectively. It is shown that the
quenched jets contribute to the soft part of the v_2(p_T) and v_4(p_T) spectra.
The jets increase the ratio v_4/v_2^2 thus leading to deviations of the ratio
from the value of 0.5 predicted by the ideal hydrodynamics. Together with the
event-by-event fluctuations, the influence of jets can explain quantitatively
the ratio v_4/v_2^2 at p_T < 2 GeV/c for both energies and qualitatively the
rise of its high-p_T tail at LHC. Jets are also responsible for violation of
the number-of-constituent-quark (NCQ) scaling at LHC despite the fact that the
scaling is fulfilled for the hydro-part of particle spectra.


  We present a catalogue of 107 point-like X-ray sources derived from a
systematic analysis of all the ROSAT PSPC observations of the galactic center
region performed in 1992-1993. Besides SgrA*, the massive black hole at the
galactic center, 41 X-ray sources have been positionally associated with
already classified objects. Twenty are identified with foreground stars and
five with known Low Mass X-ray Binaries. The majority of the sources in our
catalogue still remains unidentified. They are hard and/or severely absorbed
and probably represent a large population of X-ray binaries located in the
galactic center region, accreting at low accretion rates, and still largely
unknown.


  We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake
ecosystem model by augmenting the individual cognitive maps drawn by 8
scientists working in the area of shallow lake ecology. We calculated graph
theoretical indices of the individual cognitive maps and the collective
cognitive map produced by augmentation. The graph theoretical indices revealed
internal cycles showing non-linear dynamics in the shallow lake ecosystem. The
ecological processes were organized democratically without a top-down
hierarchical structure. The steady state condition of the generic model was a
characteristic turbid shallow lake ecosystem since there were no dynamic
environmental changes that could cause shifts between a turbid and a clearwater
state, and the generic model indicated that only a dynamic disturbance regime
could maintain the clearwater state. The model developed herein captured the
empirical behavior of shallow lakes, and contained the basic model of the
Alternative Stable States Theory. In addition, our model expanded the basic
model by quantifying the relative effects of connections and by extending it.
In our expanded model we ran 4 simulations: harvesting submerged plants,
nutrient reduction, fish removal without nutrient reduction, and
biomanipulation. Only biomanipulation, which included fish removal and nutrient
reduction, had the potential to shift the turbid state into clearwater state.
The structure and relationships in the generic model as well as the outcomes of
the management simulations were supported by actual field studies in shallow
lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to
understand the complex structure of shallow lake ecosystems as a whole and
obtain a valid generic model based on tacit knowledge of experts in the field.


  The origin of the resistivity minimum observed in strongly phase separated
manganites has been investigated in single crystalline thin films of LPCMO
(x~0.42, y~0.40). The antiferromagnetic/charge ordered insulator
(AFM/COI)-ferromagnetic metal (FMM) phase transition, coupled with the colossal
hysteresis between the field cool cooled and field cooled warming magnetization
demonstrates strongly phase separated nature, which gives rise to
non-equilibrium magnetic liquid state that freezes into a magnetic glass. The
thermal cycling and magnetic field dependence of the resistivity unambiguously
shows that the pronounced resistivity minimum observed during warming is a
consequence non-equilibrium states resulting from the magnetic frustration
created by the delicate coexistence of the FMM and AFM/COI phases. The
non-equilibrium states and hence the resistivity minimum is extremely sensitive
to the relative fraction of the coexisting phases and can be tuned by intrinsic
and extrinsic perturbations like the defect density, thermal cycling and
magnetic field.


  In recent years, high-frequency trading has emerged as a crucial strategy in
stock trading. This study aims to develop an advanced high-frequency trading
algorithm and compare the performance of three different mathematical models:
the combination of the cross-entropy loss function and the quasi-Newton
algorithm, the FCNN model, and the vector machine. The proposed algorithm
employs neural network predictions to generate trading signals and execute buy
and sell operations based on specific conditions. By harnessing the power of
neural networks, the algorithm enhances the accuracy and reliability of the
trading strategy. To assess the effectiveness of the algorithm, the study
evaluates the performance of the three mathematical models. The combination of
the cross-entropy loss function and the quasi-Newton algorithm is a widely
utilized logistic regression approach. The FCNN model, on the other hand, is a
deep learning algorithm that can extract and classify features from stock data.
Meanwhile, the vector machine is a supervised learning algorithm recognized for
achieving improved classification results by mapping data into high-dimensional
spaces. By comparing the performance of these three models, the study aims to
determine the most effective approach for high-frequency trading. This research
makes a valuable contribution by introducing a novel methodology for
high-frequency trading, thereby providing investors with a more accurate and
reliable stock trading strategy.


  Background: Three-dimensional (3D) cephalometric analysis using computerized
tomography data has been rapidly adopted for dysmorphosis and anthropometry.
Several different approaches to automatic 3D annotation have been proposed to
overcome the limitations of traditional cephalometry. The purpose of this study
was to evaluate the accuracy of our newly-developed system using a deep
learning algorithm for automatic 3D cephalometric annotation. Methods: To
overcome current technical limitations, some measures were developed to
directly annotate 3D human skull data. Our deep learning-based model system
mainly consisted of a 3D convolutional neural network and image data
resampling. Results: The discrepancies between the referenced and predicted
coordinate values in three axes and in 3D distance were calculated to evaluate
system accuracy. Our new model system yielded prediction errors of 3.26, 3.18,
and 4.81 mm (for three axes) and 7.61 mm (for 3D). Moreover, there was no
difference among the landmarks of the three groups, including the midsagittal
plane, horizontal plane, and mandible (p>0.05). Conclusion: A new 3D
convolutional neural network-based automatic annotation system for 3D
cephalometry was developed. The strategies used to implement the system were
detailed and measurement results were evaluated for accuracy. Further
development of this system is planned for full clinical application of
automatic 3D cephalometric annotation.


  Cloud Service Providers, such as Google Cloud Platform, Microsoft Azure, or
Amazon Web Services, offer continuously evolving cloud services. It is a
growing industry. Businesses, such as Netflix and PayPal, rely on the Cloud for
data storage, computing power, and other services. For businesses, the cloud
reduces costs, provides flexibility, and allows for growth. However, there are
security and privacy concerns regarding the Cloud. Because Cloud services are
accessed through the internet, hackers and attackers could possibly access the
servers from anywhere. To protect data in the Cloud, it should be encrypted
before it is uploaded, it should be protected in storage and also in transit.
On the other hand, data owners may need to access their encrypted data. It may
also need to be altered, updated, deleted, read, searched, or shared with
others. If data is decrypted in the Cloud, sensitive data is exposed and could
be exposed and misused. One solution is to leave the data in its encrypted form
and use Searchable Encryption (SE) which operates on encrypted data. The
functionality of SE has improved since its inception and research continues to
explore ways to improve SE. This paper reviews the functionality of Searchable
Encryption, mostly related to Cloud services, in the years 2019 to 2023, and
evaluates one of its schemes, Fully Homomorphic Encryption. Overall, it seems
that research is at the point where SE efficiency is increased as multiple
functionalities are aggregated and tested.


  Recent convolutional neural network (CNN) development continues to advance
the state-of-the-art model accuracy for various applications. However, the
enhanced accuracy comes at the cost of substantial memory bandwidth and storage
requirements and demanding computational resources. Although in the past the
quantization methods have effectively reduced the deployment cost for edge
devices, it suffers from significant information loss when processing the
biased activations of contemporary CNNs. In this paper, we hence introduce an
adaptive high-performance quantization method to resolve the issue of biased
activation by dynamically adjusting the scaling and shifting factors based on
the task loss. Our proposed method has been extensively evaluated on image
classification models (ResNet-18/34/50, MobileNet-V2, EfficientNet-B0) with
ImageNet dataset, object detection model (YOLO-V4) with COCO dataset, and
language models with PTB dataset. The results show that our 4-bit integer
(INT4) quantization models achieve better accuracy than the state-of-the-art
4-bit models, and in some cases, even surpass the golden full-precision models.
The final designs have been successfully deployed onto extremely
resource-constrained edge devices for many practical applications.


  Recently much attention has been paid to the discovery of Hubble's law: the
linear relation between the rate of recession of the distant galaxies and
distance to them. Though we now mention several names associated with this law
instead of one, the motivation of each remains somewhat obscure. As it is turns
out, two major contributors arrived at their discoveries from erroneous
reasoning, thus making a case for a Type III error. It appears that G. Lemaitre
(1927) theoretically derived Hubble's Law due to his choice of the wrong
scenario of the Universe's evolution. E. Hubble (1929) tested the linearity law
not based on Lemaitre's non-static model, but rather a cumbersome extension of
de Sitter's static theory proposed by H. Weyl (1923) and L. Silberstein (1924).


  The inherent generative power of denoising diffusion models makes them
well-suited for image restoration tasks where the objective is to find the
optimal high-quality image within the generative space that closely resembles
the input image. We propose a method to adapt a pretrained diffusion model for
image restoration by simply adding noise to the input image to be restored and
then denoise. Our method is based on the observation that the space of a
generative model needs to be constrained. We impose this constraint by
finetuning the generative model with a set of anchor images that capture the
characteristics of the input image. With the constrained space, we can then
leverage the sampling strategy used for generation to do image restoration. We
evaluate against previous methods and show superior performances on multiple
real-world restoration datasets in preserving identity and image quality. We
also demonstrate an important and practical application on personalized
restoration, where we use a personal album as the anchor images to constrain
the generative space. This approach allows us to produce results that
accurately preserve high-frequency details, which previous works are unable to
do. Project webpage: https://gen2res.github.io.


Describes 10 rules that should be followed by scientist.


  Differentiable solvers for the linear assignment problem (LAP) have attracted
much research attention in recent years, which are usually embedded into
learning frameworks as components. However, previous algorithms, with or
without learning strategies, usually suffer from the degradation of the
optimality with the increment of the problem size. In this paper, we propose a
learnable linear assignment solver based on deep graph networks. Specifically,
we first transform the cost matrix to a bipartite graph and convert the
assignment task to the problem of selecting reliable edges from the constructed
graph. Subsequently, a deep graph network is developed to aggregate and update
the features of nodes and edges. Finally, the network predicts a label for each
edge that indicates the assignment relationship. The experimental results on a
synthetic dataset reveal that our method outperforms state-of-the-art baselines
and achieves consistently high accuracy with the increment of the problem size.
Furthermore, we also embed the proposed solver, in comparison with
state-of-the-art baseline solvers, into a popular multi-object tracking (MOT)
framework to train the tracker in an end-to-end manner. The experimental
results on MOT benchmarks illustrate that the proposed LAP solver improves the
tracker by the largest margin.


  We consider a design for a cyclic microrefrigerator using a superconducting
flux qubit. Adiabatic modulation of the flux combined with thermalization can
be used to transfer energy from a lower temperature normal metal thin film
resistor to another one at higher temperature. The frequency selectivity of
photonic heat conduction is achieved by including the hot resistor as part of a
high frequency LC resonator and the cold one as part of a low-frequency
oscillator while keeping both circuits in the underdamped regime. We discuss
the performance of the device in an experimentally realistic setting. This
device illustrates the complementarity of information and thermodynamic entropy
as the erasure of the quantum bit directly relates to the cooling of the
resistor.


  We describe system verification tests and early science results from the
pulsar processor (PTUSE) developed for the newly-commissioned 64-dish SARAO
MeerKAT radio telescope in South Africa. MeerKAT is a high-gain (~2.8 K/Jy)
low-system temperature (~18 K at 20cm) radio array that currently operates from
580-1670 MHz and can produce tied-array beams suitable for pulsar observations.
This paper presents results from the MeerTime Large Survey Project and
commissioning tests with PTUSE. Highlights include observations of the double
pulsar J0737-3039A, pulse profiles from 34 millisecond pulsars from a single
2.5h observation of the Globular cluster Terzan 5, the rotation measure of
Ter5O, a 420-sigma giant pulse from the Large Magellanic Cloud pulsar PSR
J0540-6919, and nulling identified in the slow pulsar PSR J0633-2015. One of
the key design specifications for MeerKAT was absolute timing errors of less
than 5 ns using their novel precise time system. Our timing of two bright
millisecond pulsars confirm that MeerKAT delivers exceptional timing. PSR
J2241-5236 exhibits a jitter limit of <4 ns per hour whilst timing of PSR
J1909-3744 over almost 11 months yields an rms residual of 66 ns with only 4
min integrations. Our results confirm that the MeerKAT is an exceptional pulsar
telescope. The array can be split into four separate sub-arrays to time over
1000 pulsars per day and the future deployment of S-band (1750-3500 MHz)
receivers will further enhance its capabilities.


  An intuitive physical mechanism for single attosecond pulse generation in
multi-cycle pulse regime is proposed. We suggest that the continuum spectra of
HHG can be controlled through the modulation of carrier wave, while keeping the
multi-cycle envelope unchanged approximately. By increasing the time interval
between the adjacent maximum return kinetic energy peaks, the kinetic energy of
the side peaks will be apparently suppressed by the multi-cycle envelope. The
photons with energies near the cutoff burst only at the pulse center with high
coherence, which contribute to the generation of single attosecond pulse. We
verify this mechanism by using a multi-cycle tri-color pulse as driver field.


  Magnetic fields permeate the entire Galaxy and are essential to, for example,
the regulation of several stages of the star formation process and cosmic ray
transportation. Unraveling its properties, such as intensity and topology, is
an observational challenge that requires combining different and complementary
techniques. The polarization of starlight due to the absorption by
field-aligned non-spherical dust grains provides a unique source of information
about the interstellar magnetic field in the optical band. This work introduces
a first analysis of a new catalog of optical observations of linearly polarized
starlight in the diffuse interstellar medium (ISM), the Interstellar
Polarization Survey, General ISM (IPS-GI). We used data from the IPS-GI,
focusing on 38 fields sampling lines of sight in the diffuse medium. The fields
are about 0.3$^{\circ}$ by 0.3$^{\circ}$ in size and each of them contains
$\sim1000$ stars on average. The IPS-GI catalog has polarimetric measurements
of over 40000 stars, over 18000 of which have ${P}/\sigma_{P} > 5$. We added
distances and other parameters from auxiliary catalogs to over 36000 of these
stars. We analyzed parameter distributions and correlations between parameters
of a high-quality subsample of 10516 stars (i.e. $\sim275$ stars per field). As
expected, the degree of polarization tends to increase with the extinction,
producing higher values of polarization at greater distances or at lower
absolute Galactic latitudes. Furthermore, we find evidence for a large-scale
ordered Galactic magnetic field.


  We prove that, in a class of spherically symmetric spacetimes exhibiting
stable trapping of null geodesics, linear waves cannot (uniformly) decay faster
than logarithmically. When these linear waves are treated as a model for
nonlinear perturbations, this slow decay is highly suggestive of nonlinear
instability. We also prove that, in a large class of asymptotically flat,
spherically symmetric spacetimes, logarithmic decay actually holds as a uniform
upper bound. In the presence of stable trapping, this result is therefore the
best one can obtain. In addition, we provide an application of these results to
ultracompact neutron stars, suggesting that all stars with r < 3M might be
unstable.


  We employ a state-of-the-art asteroseismological model of G117-B15A, the
archetype of the H-rich atmosphere (DA) white dwarf pulsators (also known as
DAV or ZZ Ceti variables), and use the most recently measured value of the rate
of period change for the dominant mode of this pulsating star to derive a new
constraint on the mass of axion, the still conjectural non-barionic particle
considered as candidate for dark matter of the Universe. Assuming that
G117-B15A is truly represented by our asteroseismological model, and in
particular, that the period of the dominant mode is associated to a pulsation
g-mode trapped in the H envelope, we find strong indications of the existence
of extra cooling in this star, compatible with emission of axions of mass m_a
\cos^2 \beta = 17.4^{+2.3}_{-2.7} meV.


  In the present paper, the impact of small Fermi energy on the selected
parameters of the superconducting state in Ba$_{1-x}$K$_{x}$BiO$_{3}$ (BKBO) is
studied at $x \in (0.3, 0.4, 0.5)$. This is done by employing the adiabatic and
non-adiabatic Eliashberg equations in context of the available experimental
data. It is found that the retardation, strong-coupling and the non-adiabatic
effects notably influence superconducting phase in BKBO. In particular, the
electron-electron interaction, approximated here by the Coulomb
pseudopotential, is argued to be reduced by the non-adiabatic effects that
supplement retardation and allow for the phonon-mediated superconductivity.
These findings are reinforced by further analysis of the isotope effect showing
reduction of the isotope coefficient with respect to the canonical
Bardeen-Cooper-Schrieffer (BCS) level, as caused by the interplay of all
effects mentioned above. Although physics behind the isotope effect appears to
be complex, its resulting behavior comply with the scenario for the
conventional superconductors. In summary, obtained results confirm recent
theoretical and experimental studies that suggest phonon-mediated mechanism of
superconductivity in BKBO. However, they also point out that this phase cannot
be properly described with the BCS theory due to the existence of somewhat
unusual effects.


  Previous studies have demonstrated that putatively single nitrogen-type
Wolf-Rayet stars (WN stars) without known companions are X-ray sources.
However, almost all WN star X-ray detections so far have been of earlier WN2 -
WN6 spectral subtypes. Later WN7 - WN9 subtypes (also known as WNL stars) have
proved more difficult to detect, an important exception being WR 79a (WN9ha).
We present here new X-ray detections of the WNL stars WR 16 (WN8h) and WR 78
(WN7h). These new results, when combined with previous detections, demonstrate
that X-ray emission is present in WN stars across the full range of spectral
types, including later WNL stars. The two WN8 stars observed to date (WR 16 and
WR 40) show unusually low X-ray luminosities (Lx) compared to other WN stars,
and it is noteworthy that they also have the lowest terminal wind speeds
(v_infty). Existing X-ray detections of about a dozen WN stars reveal a trend
of increasing Lx with wind luminosity Lwind = (1/2) M_dot v_infty^2, suggesting
that wind kinetic energy may play a key role in establishing X-ray luminosity
levels in WN stars.


  Whereas formal category theory is classically considered within a
$2$-category, in this paper a double-dimensional approach is taken. More
precisely we develop such theory within the setting of augmented virtual double
categories, a notion extending that of virtual double category by adding cells
with nullary target.
  [...] After this the notion of `weak' Kan extension within an augmented
virtual double category is considered, together with three strengthenings.
[...] The notion of yoneda embedding is then considered in an augmented virtual
double category, and compared to that of a good yoneda structure on a
$2$-category; the latter in the sense of Street-Walters and Weber. Conditions
are given ensuring that a yoneda embedding $y \colon A \to \hat A$ defines
$\hat A$ as the free small cocompletion of $A$, in a suitable sense.
  In the second half we consider formal category theory in the presence of
algebraic structures. In detail: to a monad $T$ on an augmented virtual double
category $\mathcal K$ several augmented virtual double categories
$T\text-\mathsf{Alg}_{(v, w)}$ of $T$-algebras are associated, [...]. This is
followed by the study of the creation of, amongst others, left Kan extensions
by the forgetful functors $T\text-\mathsf{Alg}_{(v, w)} \to \mathcal K$. The
main motivation of this paper is the description of conditions ensuring that
yoneda embeddings in $\mathcal K$ lift along these forgetful functors, as well
as ensuring that such lifted algebraic yoneda embeddings again define free
small cocompletions, now in $T\text-\mathsf{Alg}_{(v, w)}$. As a first example
we apply the previous to monoidal structures on categories, hence recovering
Day convolution of presheaves and Im-Kelly's result on free monoidal
cocompletion, as well as obtaining a "monoidal Yoneda lemma".


  We show that a linear Young differential equation generates a topological
two-parameter flow, thus the notions of Lyapunov exponents and Lyapunov
spectrum are well-defined. The spectrum can be computed using the discretized
flow and is independent of the driving path for triangular systems which are
regular in the sense of Lyapunov. In the stochastic setting, the system
generates a stochastic two-parameter flow which satisfies the integrability
condition, hence the Lyapunov exponents are random variables of finite moments.
Finally, we prove a Millionshchikov theorem stating that almost all, in a sense
of an invariant measure, linear nonautonomous Young differential equations are
Lyapunov regular.


  The Alcator C-Mod mirror Langmuir probe system has been used to sample data
time series of fluctuating plasma parameters in the outboard mid-plane far
scrape-off layer. We present a statistical analysis of one second long time
series of electron density, temperature, radial electric drift velocity and the
corresponding particle and electron heat fluxes. These are sampled during
stationary plasma conditions in an ohmically heated, lower single null diverted
discharge.
  The electron density and temperature are strongly correlated and feature
fluctuation statistics similar to the ion saturation current. Both electron
density and temperature time series are dominated by intermittent,
large-amplitude burst with an exponential distribution of both burst amplitudes
and waiting times between them.
  The characteristic time scale of the large-amplitude bursts is approximately
15{\mu}s. Large-amplitude velocity fluctuations feature a slightly faster
characteristic time scale and appear at a faster rate than electron density and
temperature fluctuations.
  Describing these time series as a superposition of uncorrelated exponential
pulses, we find that probability distribution functions, power spectral
densities as well as auto-correlation functions of the data time series agree
well with predictions from the stochastic model.
  The electron particle and heat fluxes present large-amplitude fluctuations.
For this low-density plasma, the radial electron heat flux is dominated by
convection, that is, correlations of fluctuations in the electron density and
radial velocity. Hot and dense blobs contribute approximately 6% of the total
fluctuation driven heat flux.


  Spin and orbital freedoms of electrons traveling on spin-resolved quantum
Hall edge states (quantum Hall ferromagnets) are maximally entangled. The
unitary operations on these two freedoms are hence equivalent, which means one
can manipulate the spins with non-magnetic methods through the orbitals. If one
takes the quantization axis of spins along the magnetization axis, the zenith
angle is determined by the partition rate of spin-separated edges while the
azimuth angle is defined as the phase difference between the edges. Utilizing
these properties, we have realized electrically controlled unitary operation on
the electron spins on the quantum Hall ferromagnets. The zenith angle of the
spin was controlled through the radius of gyration at a corner by means of
applying voltage to a thin gate placed at one edge. The subsequent rotation in
the azimuth angle was controlled via the distance between the edge channels
also by a gate voltage. The combination of the two operations constitutes the
first systematic electric operation on spins in the quantum Hall edge channels.


  We show the existence and uniqueness of fundamental solution operators to
Kolmo\-gorov-Fokker-Planck equations with rough (measurable) coefficients and
local or integral diffusion on finite and infinite time strips. In the local
case, that is to say when the diffusion operator is of differential type, we
prove $\L^2$ decay using Davies' method and the conservation property. We also
prove that the existence of a generalized fundamental solution with the
expected pointwise Gaussian upper bound is equivalent to Moser's
$\L^2-\L^\infty$ estimates for local weak solutions to the equation and its
adjoint. When coefficients are real, this gives the existence and uniqueness of
such a generalized fundamental solution and a new and natural way to obtain
pointwise decay.


  We apply two variations of the principle of Minimum Cross Entropy (the
Kullback information measure) to fit parameterized probability density models
to observed data densities. For an array beamforming problem with P incident
narrowband point sources, N > P sensors, and colored noise, both approaches
yield eigenvector fitting methods similar to that of the MUSIC algorithm[1].
Furthermore, the corresponding cross-entropies are related to the MDL model
order selection criterion[2].


  Long gamma-ray bursts (GRBs) offer significant insights into cosmology due to
their high energy emissions and the potential to probe the early universe. The
Amati relation, which links the intrinsic peak energy to the isotropic energy,
is crucial for understanding their cosmological applications. This study
investigates the redshift-driven heterogeneity of the Amati correlation in long
GRBs. Analyzing 221 long GRBs with redshifts from 0.034 to 8.2 we divided the
dataset based on redshift thresholds of 1.5 and 2. Using Bayesian
marginalization and Reichart's likelihood approach, we found significant
differences in the Amati parameters between low and high redshift subgroups.
These variations, differing by approximately $2\sigma$ at $z = 1.5$ and more
than $1\sigma$ at $z = 2$, suggest an evolution in the GRB population with
redshift, possibly reflecting changes in host galaxy properties. However,
selection effects and instrumental biases may also contribute. Our results
challenge the assumption of the Amati relation's universality and underscore
the need for larger datasets and more precise measurements from upcoming
missions like THESEUS and eXTP to refine our understanding of GRB physics.


  Transverse momentum (p_T) spectra of neutral pions and charged hadrons
measured in Au+Au and d+Au collisions at sqrt{s_NN}=200 GeV by the PHENIX
experiment at RHIC are compared to p+p reference spectra at the same
sqrt{s_NN}. In central Au+Au collisions a factor 4-5 suppression for neutral
pions and charged hadrons with p_T > 5 GeV/c is found relative to the p+p
reference scaled by the nuclear overlap function <T_AB>. In contrast, such a
suppression of high p_T particles is absent in d+Au collisions.


  Despite the absence of viscous drag, the neutron superfluid permeating the
inner crust of a neutron star can still be strongly coupled to nuclei due to
non-dissipative entrainment effects. Neutron superfluidity and entrainment have
been systematically studied in all regions of the inner crust of a cold
non-accreting neutron star in the framework of the band theory of solids. It is
shown that in the intermediate layers of the inner crust a large fraction of
"free" neutrons are actually entrained by the crust. The results suggest that a
revision of the interpretation of many observable astrophysical phenomena might
be necessary.


  Virtualization of network functions (as virtual routers, virtual firewalls,
etc.) enables network owners to efficiently respond to the increasing
dynamicity of network services. Virtual Network Functions (VNFs) are easy to
deploy, update, monitor, and manage. The number of VNF instances, similar to
generic computing resources in cloud, can be easily scaled based on load.
Hence, auto-scaling (of resources without human intervention) has been
receiving attention. Prior studies on auto-scaling use measured network traffic
load to dynamically react to traffic changes. In this study, we propose a
proactive Machine Learning (ML) based approach to perform auto-scaling of VNFs
in response to dynamic traffic changes. Our proposed ML classifier learns from
past VNF scaling decisions and seasonal/spatial behavior of network traffic
load to generate scaling decisions ahead of time. Compared to existing
approaches for ML-based auto-scaling, our study explores how the properties
(e.g., start-up time) of underlying virtualization technology impacts Quality
of Service (QoS) and cost savings. We consider four different virtualization
technologies: Xen and KVM, based on hypervisor virtualization, and Docker and
LXC, based on container virtualization. Our results show promising accuracy of
the ML classifier using real data collected from a private ISP. We report
in-depth analysis of the learning process (learning-curve analysis), feature
ranking (feature selection, Principal Component Analysis (PCA), etc.), impact
of different sets of features, training time, and testing time. Our results
show how the proposed methods improve QoS and reduce operational cost for
network owners. We also demonstrate a practical use-case example
(Software-Defined Wide Area Network (SD-WAN) with VNFs and backbone network) to
show that our ML methods save significant cost for network service leasers.


  Ultraviolet spectra of Comet 96/P Machholz were obtained during its 2002
perihelion with the UVCS instrument aboard the SOHO satellite. Emission from H
I, C II, C III, and O I, is detected near the nucleus. The outgassing rate is
in line with the value extrapolated from rates at larger distances from the
Sun, and abundances of C and O are estimated. Reconstructed images show a
nearly spherical cloud in H I Ly$\alpha$ emission and an ion tail seen in C
III. Radiation pressure on the hydrogen atoms produces a modest distortion of
the shape of the Ly$\alpha$ cloud as seen from SOHO, and it produces Doppler
shifts up to 30 km s$^{-1}$ in the outer parts of the cloud. We estimate a
ratio of C to H$_2$O similar to what is observed in other comets, so low carbon
abundance does not account for the anomalously low C$_2$ and C$_3$ ratios to
NH$_2$ observed at optical wavelengths.


  Hot viscous plasmas unavoidably emit a gravitational wave background, similar
to the electromagnetic black body radiation. We study the contribution from
hidden particles to the diffuse background emitted by the primordial plasma in
the early universe. While this contribution can easily dominate over that from
Standard Model particles, we find that both are capped by a generic upper bound
that makes them difficult to detect with interferometers in the foreseeable
future. However, resonant cavity experiments could potentially observe
backgrounds that saturate the upper bound. We illustrate our results for axions
and heavy neutral leptons. Finally, our results suggest that previous works
overestimated the gravitational wave background from particle decays out of
thermal equilibrium.


  Dedicated model transformation languages are claimed to provide many benefits
over the use of general purpose languages for developing model transformations.
However, the actual advantages associated with the use of MTLs are poorly
understood empirically. There is little knowledge and empirical assessment
about what advantages and disadvantages hold and where they originate from. In
a prior interview study, we elicited expert opinions on what advantages result
from what factors and a number of factors that moderate the influence. We aim
to quantitatively asses the interview results to confirm or reject the effects
posed by different factors. We intend to gain insights into how valuable
different factors are so that future studies can draw on these data for
designing targeted and relevant studies. We gather data on the factors and
quality attributes using an online survey. To analyse the data, we use
universal structure modelling based on a structure model. We use significance
values and path coefficients produced bz USM for each hypothesised
interdependence to confirm or reject correlation and to weigh the strength of
influence present. We analyzed 113 responses. The results show that the Tracing
and Reuse Mechanisms are most important overall. Though the observed effects
were generally 10 times lower than anticipated. Additionally, we found that a
more nuanced view of moderation effects is warranted. Their moderating
influence differed significantly between the different influences, with the
strongest effects being 1000 times higher than the weakest. The empirical
assessment of MTLs is a complex topic that cannot be solved by looking at a
single stand-alone factor. Our results provide clear indication that evaluation
should consider transformations of different sizes and use-cases. Language
development should focus on providing transformation specific reuse mechanisms .


  The rise of quantum mechanics is reviewed with special attention to the
development between June 1925 and October 1927 when the Copenhagen
interpretation was proposed.


  This paper investigates the asymptotics of the maximal throughput of
communication over AWGN channels by $n$ channel uses under a covert constraint
in terms of an upper bound $\delta$ of Kullback-Leibler divergence (KL
divergence). It is shown that the first and second order asymptotics of the
maximal throughput are $\sqrt{n\delta \log e}$ and
$(2)^{1/2}(n\delta)^{1/4}(\log e)^{3/4}\cdot Q^{-1}(\epsilon)$, respectively.
The technique we use in the achievability is quasi-$\varepsilon$-neighborhood
notion from information geometry. For finite blocklength $n$, the generating
distributions are chosen to be a family of truncated Gaussian distributions
with decreasing variances. The law of decreasing is carefully designed so that
it maximizes the throughput at the main channel in the asymptotic sense under
the condition that the output distributions satisfy the covert constraint. For
the converse, the optimality of Gaussian distribution for minimizing KL
divergence under the second order moment constraint is extended from dimension
$1$ to dimension $n$. Based on that, we establish an upper bound on the average
power of the code to satisfy the covert constraint, which further leads to the
direct converse bound in terms of covert metric.


  Within the framework of the hard thermal loop effective theory we derive a
system of Boltzmann-like kinetic equations taking into account the simplest
processes of nonlinear interaction of soft fermionic and bosonic QCD plasma
excitations: elastic scattering of soft-(anti)quark excitations off soft-gluon
and soft-quark excitations, pair production of soft quark-antiquark
excitations, annihilation into two soft-gluon excitations. The matrix elements
of these processes to leading order in the coupling constant $g$ are obtained.
The iterative method of calculation of the matrix elements for the higher
processes of soft-mode interactions is proposed. The most general expression
for the emitted radiant power induced by the effective currents and effective
sources in a quark-gluon plasma (QGP) taking into account an existence of
fermion sector of plasma excitations is defined. The explicit form of the
linearized Boltzmann equation accounting for scattering of color(less)
plasminos off color(less) plasmons is written out.


  Through the use of suitable variable transformations, the commonality of all
extended magnetohydrodynamics (MHD) models is established. Remarkable
correspondences between the Poisson brackets of inertialess Hall MHD and
inertial MHD (which has electron inertia, but not the Hall drift) and extended
MHD (which has both effects), are established. The helicities (two in all) for
each of these models are obtained through these correspondences. The
commonality of all the extended MHD models is traced to the existence of two
Lie-dragged 2-forms, which are closely associated with the canonical momenta of
the two underlying species. The Lie-dragging of these 2-forms by suitable
velocities also leads to the correct equations of motion. The Hall MHD Poisson
bracket is analyzed in detail, and the Jacobi identity is verified through a
detailed proof and this proof ensures the Jacobi identity for the Poisson
brackets of all the models.


  The effective restoration of chiral and axial symmetries is investigated
within the framework of the SU(3) Nambu-Jona-Lasinio model. The topological
susceptibility, modeled from lattice data at finite temperature, is used to
extract the temperature dependence of the coupling strength of the anomaly. The
study of the scalar and pseudoscalar mixing angles is performed in order to
discuss the evolution of the flavor combinations of $q \bar q$ pairs and its
consequences for the degeneracy of chiral partners. A similar study at zero
temperature and finite density is also realized.


  It is well-known that normal extremals in sub-Riemannian geometry are curves
which locally minimize the energy functional. Most proofs of this fact do not
make, however, an explicit use of relations between local optimality and the
geometry of the problem. In this paper, we provide a new proof of that
classical result, which gives insight into direct geometric reasons of local
optimality. Also the relation of the regularity of normal extremals with their
optimality becomes apparent in our approach.


  Inclusive event shape variables have been measured in the Breit Frame for
neutral current deep-inelastic positron-proton scattering using the H1 and ZEUS
detectors at HERA. The variables thrust, jet broadening, C-parameter, jet mass
and two kinds of differential two-jet rate have been studied in the kinematic
range 7 < Q < 100 GeV. The Q dependence of the shape variables have been
compared with QCD applying power corrections proportional to 1/Q^p to account
for hadronisation effects. The concept of power corrections is tested by
fitting the strong coupling constant alpha_s and a non-perturbative parameter
alpha(p-1)_bar.


  We discuss the production of charmonium states in antiproton-nucleus
collisions at the $\psi'$ threshold. It is explained that measurements in $\bar
p A$ collisions will allow to get new information about the strengths of the
inelastic $J/\psi N, \psi'N$ interaction, on the production of $\Lambda_c$ and
$\bar{D}$ in charmonium-nucleon interactions and for the first time about
nondiagonal transitions $\psi' N\to J/\psi N$. The inelastic $J/\psi$-nucleon
cross section is extracted from the comparison of hadron-nucleus collisions
with hadron-nucleon collisions. We extract the total $J/\psi$ nucleon cross
section from photon-nucleon collisions by accounting for the color transparency
phenomenon within the frame of the GVDM (Generalized Vector meson Dominance
Model). We evaluate also within the GVDM the inelastic $\psi'$-nucleon cross
section as well as the cross section for the nondiagonal transitions.
Predictions for the ratio of $J/\psi$ to $\psi'$ yields in antiproton-nucleus
scatterings close to the threshold of $\psi'$ production for different nuclear
targets are presented.


  Protein folding cooperativity is defined by the nature of the finite-size
thermodynamic transition exhibited upon folding: two-state transitions show a
free energy barrier between the folded and unfolded ensembles, while downhill
folding is barrierless. A microcanonical analysis, where the energy is the
natural variable, has shown better suited to unambiguously characterize the
nature of the transition compared to its canonical counterpart. Replica
exchange molecular dynamics simulations of a high resolution coarse-grained
model allow for the accurate evaluation of the density of states, in order to
extract precise thermodynamic information, and measure its impact on structural
features. The method is applied to three helical peptides: a short helix shows
sharp features of a two-state folder, while a longer helix and a three-helix
bundle exhibit downhill and two-state transitions, respectively. Extending the
results of lattice simulations and theoretical models, we find that it is the
interplay between secondary structure and the loss of non-native tertiary
contacts which determines the nature of the transition.


  A 1-truncated compact Lie group is any extension of a finite group by a
torus. In this note we compute the homotopy types of $Map_*(BG,BH)$,
$Map(BG,BH)$, and $Map(EG, B_GH)^G$ for compact Lie groups $G$ and $H$ with $H$
1-truncated, showing that they are computed entirely in terms of spaces of
homomorphisms from $G$ to $H$. These results generalize the well-known case
when $H$ is finite, and the case of $H$ compact abelian due to Lashof, May, and
Segal.


  This paper identifies and addresses the problems with naively combining
(reinforcement) learning-based controllers and state estimators for robotic
in-hand manipulation. Specifically, we tackle the challenging task of purely
tactile, goal-conditioned, dextrous in-hand reorientation with the hand
pointing downwards. Due to the limited sensing available, many control
strategies that are feasible in simulation when having full knowledge of the
object's state do not allow for accurate state estimation. Hence, separately
training the controller and the estimator and combining the two at test time
leads to poor performance. We solve this problem by coupling the control policy
to the state estimator already during training in simulation. This approach
leads to more robust state estimation and overall higher performance on the
task while maintaining an interpretability advantage over end-to-end policy
learning. With our GPU-accelerated implementation, learning from scratch takes
a median training time of only 6.5 hours on a single, low-cost GPU. In
simulation experiments with the DLR-Hand II and for four significantly
different object shapes, we provide an in-depth analysis of the performance of
our approach. We demonstrate the successful sim2real transfer by rotating the
four objects to all 24 orientations in the $\pi/2$ discretization of SO(3),
which has never been achieved for such a diverse set of shapes. Finally, our
method can reorient a cube consecutively to nine goals (median), which was
beyond the reach of previous methods in this challenging setting.


  Few-shot object detection, expecting detectors to detect novel classes with a
few instances, has made conspicuous progress. However, the prototypes extracted
by existing meta-learning based methods still suffer from insufficient
representative information and lack awareness of query images, which cannot be
adaptively tailored to different query images. Firstly, only the support images
are involved for extracting prototypes, resulting in scarce perceptual
information of query images. Secondly, all pixels of all support images are
treated equally when aggregating features into prototype vectors, thus the
salient objects are overwhelmed by the cluttered background. In this paper, we
propose an Information-Coupled Prototype Elaboration (ICPE) method to generate
specific and representative prototypes for each query image. Concretely, a
conditional information coupling module is introduced to couple information
from the query branch to the support branch, strengthening the query-perceptual
information in support features. Besides, we design a prototype dynamic
aggregation module that dynamically adjusts intra-image and inter-image
aggregation weights to highlight the salient information useful for detecting
query images. Experimental results on both Pascal VOC and MS COCO demonstrate
that our method achieves state-of-the-art performance in almost all settings.


  This paper addresses two seemingly unrelated problems, (a) What is the
entropy and energy accounting in the Maxwell Demon problem? and (b) How can the
efficiency of markets be measured? Here we show, in a simple model for the
Maxwell Demon, the entropy of the universe increases by an amount
eta=0.839995520 in going from a random state to an ordered state and by an
amount eta*=2.731382 in going from one sorted state to another sorted state. We
calculate the efficiency of an engine driven by the Maxwell sorting process.
The efficiency depends only on the temperatures of the particles and of the
computer the Demon uses to sort the particles. We also show the approach is
general and create a simple model of a stock market in which the Limit Trader
plays the role of the Maxwell Demon. We use this model to define and measure
market efficiency.


  The outstanding pattern recognition performance of deep learning brings new
vitality to the synthetic aperture radar (SAR) automatic target recognition
(ATR). However, there is a limitation in current deep learning based ATR
solution that each learning process only handle one SAR image, namely learning
the static scattering information, while missing the space-varying information.
It is obvious that multi-aspect joint recognition introduced space-varying
scattering information should improve the classification accuracy and
robustness. In this paper, a novel multi-aspect-aware method is proposed to
achieve this idea through the bidirectional Long Short-Term Memory (LSTM)
recurrent neural networks based space-varying scattering information learning.
Specifically, we first select different aspect images to generate the
multi-aspect space-varying image sequences. Then, the Gabor filter and
three-patch local binary pattern (TPLBP) are progressively implemented to
extract a comprehensive spatial features, followed by dimensionality reduction
with the Multi-layer Perceptron (MLP) network. Finally, we design a
bidirectional LSTM recurrent neural network to learn the multi-aspect features
with further integrating the softmax classifier to achieve target recognition.
Experimental results demonstrate that the proposed method can achieve 99.9%
accuracy for 10-class recognition. Besides, its anti-noise and anti-confusion
performance are also better than the conventional deep learning based methods.


  We study the discreteness for non-elementary subgroup G in PU(1, n;C), under
the assumption that G satisfies Condition A. Mainly, we present that one can
use a test map, which need not to be in G, to examine the discreteness of G,
and also show that G is discrete, if every two-loxodromic-generator subgroup of
G is discrete.


  We revisit and complete the study of curved BPS-domain walls in
matter-coupled 5D, N=2 supergravity and carefully analyse the relation to
gravitational theories known as "fake supergravities". We first show that
\emph{curved} BPS-domain walls require the presence of non-trivial
hypermultiplet scalars, whereas walls that are solely supported by vector
multiplet scalars are necessarily \emph{flat}, due to the constraints from very
special geometry. We then recover fake supergravity as the effective
description of true supergravity where one restricts the attention to the
flowing scalar field of a given BPS-domain wall. In general, however, true
supergravity can be simulated by fake supergravity at most \emph{locally},
based upon two choices: (i) a suitable adapted coordinate system on the scalar
manifold, such that only one scalar field plays a dynamical role, and (ii) a
gauge fixing of the SU(2) connection on the quaternionic-Kahler manifold, as
this connection does not fit the simple formalism of fake supergravity.
Employing these gauge and coordinate choices, the BPS-equations for both vector
and hypermultiplet scalars become identical to the fake supergravity equations,
once the line of flow is determined by the full supergravity equations.


  The proposed Beam Dump Facility (BDF) is foreseen to be located at the North
Area of the SPS. It is designed to be able to serve both beam dump like and
fixed target experiments. The SPS and the new facility would offer unique
possibilities to enter a new era of exploration at the intensity frontier.
Possible options include searches for very weakly interacting particles
predicted by Hidden Sector models, and flavour physics measurements. In the
first instance, exploitation of the facility, in beam dump mode, is envisaged
to be for the Search for Hidden Particle (SHiP) experiment.
  Following the first evaluation of the BDF in 2014-2016, CERN management
launched a Comprehensive Design Study over three years for the facility. The
BDF study team has since executed an in-depth feasibility study of proton
delivery to target, the target complex, and the underground experimental area,
including prototyping of key sub-systems and evaluations of the radiological
aspects and safety. A first iteration of detailed integration and civil
engineering studies have been performed in order to produce a realistic
schedule and cost. This document gives a detailed overview of the proposed
facility together with the results of the studies, and draws up a possible road
map for a three-year Technical Design Report phase, followed by a 5 to 6 year
construction phase.


  We develop a general numerical method aimed at studying particle production
from vacuum states in a variety of settings. As a first example we look at
particle production in a simple cosmological model. We apply the same approach
to the dynamical Casimir effect, with special focus on the case of an
oscillating mirror. We confirm previous estimates and obtain long-time
production rates and particle spectra for both resonant and off-resonant
frequencies. Finally, we simulate a system with space and time-dependent
optical properties, analogous to a one-dimensional expanding dielectric bubble.
  We obtain simple expressions for the dependence of the final particle number
on the expansion velocity and final dielectric constant.


  We give an explicit formula for the Higgs and Coulomb branch Hilbert series
for the class of 3d N=4 superconformal gauge theories T^{\sigma}_{\rho}(G)
corresponding to a set of D3 branes ending on NS5 and D5-branes, with or
without O3 planes. Here G is a classical group, \sigma is a partition of G and
\rho a partition of the dual group G^\vee. In deriving such a formula we make
use of the recently discovered formula for the Hilbert series of the quantum
Coulomb branch of N=4 superconformal theories. The result can be expressed in
terms of a generalization of a class of symmetric functions, the
Hall-Littlewood polynomials, and can be interpreted in mathematical language in
terms of localization. We mainly consider the case G=SU(N) but some interesting
results are also given for orthogonal and symplectic groups.


  We show that the phenomenon of anomalous weak values is not limited to
quantum theory. In particular, we show that the same features occur in a simple
model of a coin subject to a form of classical backaction with pre- and
post-selection. This provides evidence that weak values are not inherently
quantum, but rather a purely statistical feature of pre- and post-selection
with disturbance.


  We present solutions of the Yang-Mills equation on cylinders $\mathbb R\times
G/H$ over coset spaces with Sasakian structure and odd dimension $2m+1$. The
gauge potential is assumed to be $SU(m)$-equivariant, parametrized by two real,
scalar-valued functions. Yang-Mills theory with torsion in this setup reduces
to the Newtonian mechanics of a point particle moving in $\mathbb R^2$ under
the influence of an inverted potential. We analyze the critical points of this
potential and present an analytic as well as several numerical finite-action
solutions. Apart from the Yang-Mills solutions that constitute
$SU(m)$-equivariant instanton configurations, we construct periodic sphaleron
solutions on $S^1\times G/H$ and dyon solutions on $i\mathbb R\times G/H$.


  We study the $L^{p},$ $1\leqslant p\leqslant \infty,$ boundedness for Riesz
transforms of the form $V^{a}(-\frac{1}{2}\Delta+V)^{-a},$ where $a>0$ and $V$
is a non-negative potential. We prove that $V^{a}(-\frac{1}{2}\Delta+V)^{-a}$
is bounded on $L^p(\mathbb{R}^d)$ with $1< p\leqslant 2$ whenever $a\leqslant
1/p.$ We demonstrate that the $L^{\infty}(\mathbb{R}^d)$ boundedness holds if
$V$ satisfies an $a$-dependent integral condition that is resistant to small
perturbations. Similar results with stronger assumptions on $V$ are also
obtained on $L^{1}(\mathbb{R}^d).$ In particular our $L^{\infty}$ and $L^1$
results apply to non-negative potentials $V$ which globally have a power growth
or an exponential growth. We also discuss a counterexample showing that the
$L^{\infty}(\mathbb{R}^d)$ boundedness may fail.


  This paper presents the end-to-end QoS approach to provide performance
guarantees followed in the SELENE platform, a high-performance RISC-V based
heterogeneous SoC for safety-related real-time systems. Our QoS approach
includes smart interconnect solutions for buses and NoCs, along with multicore
interference-aware statistics units to, cooperatively, achieve end-to-end QoS.


  Motivated by recent realizations of Dy$_{2}$Ti$_{2}$O$_{7}$ and
Ho$_{2}$Ti$_{2}$O$_{7}$ spin ice thin films, and more generally by the physics
of confined gauge fields, we study a model of spin ice thin film with surfaces
perpendicular to the $[001]$ cubic axis. The resulting open boundaries make
half of the bonds on the interfaces inequivalent. By tuning the strength of
these inequivalent "orphan" bonds, dipolar interactions induce a surface
ordering equivalent to a two-dimensional crystallization of magnetic surface
charges. This surface ordering can also be expected on the surfaces of bulk
crystals. In analogy with partial wetting in soft matter, spins just below the
surface are more correlated than in the bulk, but \emph{not} ordered. For
ultrathin films made of one cubic unit cell, once the surfaces are ordered, a
square ice phase is stabilized over a finite temperature window, as confirmed
by its entropy and the presence of pinch points in the structure factor.
Ultimately, the square ice degeneracy is lifted at lower temperature and the
system orders in analogy with the well-known $F$-transition of the $6$-vertex
model.


  Controlling and analyzing cyberphysical and robotics systems is increasingly
becoming a Big Data challenge. Pushing this data to, and processing in the
cloud is more efficient than on-board processing. However, current cloud-based
solutions are not suitable for the latency requirements of these applications.
We present a new concept, Discretized Streams or D-Streams, that enables
massively scalable computations on streaming data with latencies as short as a
second.
  We experiment with an implementation of D-Streams on top of the Spark
computing framework. We demonstrate the usefulness of this concept with a novel
algorithm to estimate vehicular traffic in urban networks. Our online EM
algorithm can estimate traffic on a very large city network (the San Francisco
Bay Area) by processing tens of thousands of observations per second, with a
latency of a few seconds.


  Gait control of legged robotic walkers on dynamically moving surfaces (e.g.,
ships and vehicles) is challenging due to the limited balance control actuation
and unknown surface motion. We present a contingent model predictive control
(CMPC) for bipedal walker locomotion on moving surfaces with a linear inverted
pendulum (LIP) model. The CMPC is a robust design that is built on regular
model predictive control (MPC) to incorporate the "worst case" predictive
motion of the moving surface. Integrated with an LIP model and walking
stability constraints, the CMPC framework generates a set of consistent control
inputs considering to anticipated uncertainties of the surface motions.
Simulation results and comparison with the regular MPC for bipedal walking are
conducted and presented. The results confirm the feasibility and superior
performance of the proposed CMPC design over the regular MPC under various
motion profiles of moving surfaces.


  It is now well documented that genetic covariance between functionally
related traits leads to an uneven distribution of genetic variation across
multivariate trait combinations, and possibly a large part of phenotype-space
that is inaccessible to evolution. How the size of this nearly-null genetic
space translates to the broader phenome level is unknown. High dimensional
phenotype data to address these questions are now within reach, however,
incorporating these data into genetic analyses remains a challenge. Multi-trait
genetic analyses, of more than a handful of traits, are slow and often fail to
converge when fit with REML. This makes it challenging to estimate the genetic
covariance ($\mathbf{G}$) underlying thousands of traits, let alone study its
properties. We present a previously proposed REML algorithm that is feasible
for high dimensional genetic studies in the specific setting of a balanced
nested half-sib design, common of quantitative genetics. We show that it
substantially outperforms other common approaches when the number of traits is
large, and we use it to investigate the bias in estimated eigenvalues of
$\mathbf{G}$ and the size of the nearly-null genetic subspace. We show that the
high-dimensional biases observed are qualitatively similar to those
substantiated by asymptotic approximation in a simpler setting of a sample
covariance matrix based on i.i.d. vector observation, and that interpreting the
estimated size of the nearly-null genetic subspace requires considerable
caution in high-dimensional studies of genetic variation. Our results provide
the foundation for future research characterizing the asymptotic approximation
of estimated genetic eigenvalues, and a statistical null distribution for
phenome-wide studies of genetic variation.


  Episodic reinforcement learning and contextual bandits are two widely studied
sequential decision-making problems. Episodic reinforcement learning
generalizes contextual bandits and is often perceived to be more difficult due
to long planning horizon and unknown state-dependent transitions. The current
paper shows that the long planning horizon and the unknown state-dependent
transitions (at most) pose little additional difficulty on sample complexity.
  We consider the episodic reinforcement learning with $S$ states, $A$ actions,
planning horizon $H$, total reward bounded by $1$, and the agent plays for $K$
episodes. We propose a new algorithm, \textbf{M}onotonic \textbf{V}alue
\textbf{P}ropagation (MVP), which relies on a new Bernstein-type bonus.
Compared to existing bonus constructions, the new bonus is tighter since it is
based on a well-designed monotonic value function. In particular, the
\emph{constants} in the bonus should be subtly setting to ensure optimism and
monotonicity.
  We show MVP enjoys an $O\left(\left(\sqrt{SAK} + S^2A\right) \poly\log
\left(SAHK\right)\right)$ regret, approaching the
$\Omega\left(\sqrt{SAK}\right)$ lower bound of \emph{contextual bandits} up to
logarithmic terms. Notably, this result 1) \emph{exponentially} improves the
state-of-the-art polynomial-time algorithms by Dann et al. [2019] and Zanette
et al. [2019] in terms of the dependency on $H$, and 2) \emph{exponentially}
improves the running time in [Wang et al. 2020] and significantly improves the
dependency on $S$, $A$ and $K$ in sample complexity.


  We initiate the study of diameter computation in geometric intersection
graphs from the fine-grained complexity perspective. A geometric intersection
graph is a graph whose vertices correspond to some shapes in $d$-dimensional
Euclidean space, such as balls, segments, or hypercubes, and whose edges
correspond to pairs of intersecting shapes. The diameter of a graph is the
largest distance realized by a pair of vertices in the graph.
  Computing the diameter in near-quadratic time is possible in several classes
of intersection graphs [Chan and Skrepetos 2019], but it is not at all clear if
these algorithms are optimal, especially since in the related class of planar
graphs the diameter can be computed in $\widetilde{\mathcal{O}}(n^{5/3})$ time
[Cabello 2019, Gawrychowski et al. 2021].
  In this work we (conditionally) rule out sub-quadratic algorithms in several
classes of intersection graphs, i.e., algorithms of running time
$\mathcal{O}(n^{2-\delta})$ for some $\delta>0$. In particular, there are no
sub-quadratic algorithms already for fat objects in small dimensions: unit
balls in $\mathbb{R}^3$ or congruent equilateral triangles in $\mathbb{R}^2$.
For unit segments and congruent equilateral triangles, we can even rule out
strong sub-quadratic approximations already in $\mathbb{R}^2$. It seems that
the hardness of approximation may also depend on dimensionality: for
axis-parallel unit hypercubes in~$\mathbb{R}^{12}$, distinguishing between
diameter 2 and 3 needs quadratic time (ruling out $(3/2-\varepsilon)$-
approximations), whereas for axis-parallel unit squares, we give an algorithm
that distinguishes between diameter $2$ and $3$ in near-linear time.
  Note that many of our lower bounds match the best known algorithms up to
sub-polynomial factors.


  The quantum field theory describing electric and magnetic charges and
revealing a dual symmetry was developed in the Zwanziger formalism. The
renormalization group (RG) equations for both fine structure constants -
electric $\alpha$ and magnetic $\tilde \alpha$ - were obtained. It was shown
that the Dirac relation is valid for the renormalized $\alpha $ and $\tilde
\alpha$ at the arbitrary scale, but these RG equations can be considered
perturbatively only in the small region: $0.25 \stackrel{<}{\sim} \alpha,
\tilde \alpha \stackrel{<}{\sim} 1$ with $\tilde \alpha$ given by the Dirac
relation: $\alpha {\tilde \alpha}$ = 1/4.


  J.Eells and L. Lemaire introduced k-harmonic maps, and T. Ichiyama, J.
Inoguchi and H.Urakawa showed the first variation formula. In this paper, we
give the second variation formula of k-harmonic maps, and show non-existence
theorem of proper k-harmonic maps into a Riemannian manifold of non-positive
curvature (k >= 2). We also study k-harmonic maps into the product Riemannian
manifold, and describe the ordinary differential equations of 3-harmonic curves
and 4-harmonic curves into a sphere, and show their non-trivial solutions.


  This paper summarizes the recent calculations of the masses and decay
constants of the pseudoscalar mesons at the two-loop level, or NNLO, in
Partially Quenched Chiral Perturbation Theory (PQxPT). Possible applications
include chiral extrapolations of Lattice QCD, as well as the determination of
the low-energy constants (LEC:s) of QCD.


  In high-temperature plasma physics, a strong magnetic field is usually used
to confine charged particles. Therefore, for studying the classical
mathematical models of the physical problems it is needed to consider the
effect of external magnetic fields. One of the important model equations in
plasma is the Vlasov-Poisson equation with an external magnetic field. In this
paper, we study the error analysis of Hamiltonian particle methods for this
kind of system. The convergence of particle method for Vlasov equation and that
of Hamiltonian method for particle equation are provided independently. By
combining them, it can be concluded that the numerical solutions converge to
the exact particle trajectories.


  The embedding theorem arises in several problems from analysis and geometry.
The purpose of this paper is to provide a deeper understanding of analysis and
geometry with a particular focus on embedding theorems on spaces of homogeneous
type in the sense of Coifman and Weiss. We prove that embedding theorems hold
on spaces of homogeneous type if and only if geometric conditions, namely the
measures of all balls have lower bounds, hold. As applications, our results
provide new and sharp previous related embedding theorems for the Sobolev,
Besov and Triebel-Lizorkin spaces.


  We present a multiplexing scheme for the measurement of large numbers of
mesoscopic devices in cryogenic systems. The multiplexer is used to contact an
array of 256 split gates on a GaAs/AlGaAs heterostructure, in which each split
gate can be measured individually. The low-temperature conductance of
split-gate devices is governed by quantum mechanics, leading to the appearance
of conductance plateaux at intervals of 2e^2/h. A fabrication-limited yield of
94% is achieved for the array, and a "quantum yield" is also defined, to
account for disorder affecting the quantum behaviour of the devices. The
quantum yield rose from 55% to 86% after illuminating the sample, explained by
the corresponding increase in carrier density and mobility of the
two-dimensional electron gas. The multiplexer is a scalable architecture, and
can be extended to other forms of mesoscopic devices. It overcomes previous
limits on the number of devices that can be fabricated on a single chip due to
the number of electrical contacts available, without the need to alter existing
experimental set ups.


  We study some aspects of countably additive vector measures with values in
$\ell_\infty$ and the Banach lattices of real-valued functions that are
integrable with respect to such a vector measure. On the one hand, we prove
that if $W \subseteq \ell_\infty^*$ is a total set not containing sets
equivalent to the canonical basis of $\ell_1(\mathfrak{c})$, then there is a
non-countably additive $\ell_\infty$-valued map $\nu$ defined on a
$\sigma$-algebra such that the composition $x^* \circ \nu$ is countably
additive for every $x^*\in W$. On the other hand, we show that a Banach lattice
$E$ is separable whenever it admits a countable positively norming set and both
$E$ and $E^*$ are order continuous. As a consequence, if $\nu$ is a countably
additive vector measure defined on a $\sigma$-algebra and taking values in a
separable Banach space, then the space $L_1(\nu)$ is separable whenever
$L_1(\nu)^*$ is order continuous.


  Let $(L_n^{(k)})_{n\geq 2-k}$ be the sequence of $k$--generalized Lucas
numbers for some fixed integer $k\ge 2$ whose first $k$ terms are
$0,\ldots,0,2,1$ and each term afterwards is the sum of the preceding $k$
terms. For an integer $m$, let $P(m)$ denote the largest prime factor of $m$,
with $P(0)=P(\pm 1)=1$. We show that if $n \ge k + 1$, then $P (L_n^{(k)} ) >
(1/86) \log \log n$. Furthermore, we determine all the $k$--generalized Lucas
numbers $L_n^{(k)}$ whose largest prime factor is at most $ 7$.


  In finite-time quantum heat engines, some work is consumed to drive a working
fluid accompanying coherence, which is called `friction'. To understand the
role of friction in quantum thermodynamics, we present a couple of finite-time
quantum Otto cycles with two different baths: Agarwal versus Lindbladian. We
solve them exactly and compare the performance of the Agarwal engine with that
of the Lindbladian engine. In particular, we find remarkable and
counterintuitive results that the performance of the Agarwal engine due to
friction can be much higher than that in the quasistatic limit with the Otto
efficiency, and the power of the Lindbladian engine can be nonzero in the
short-time limit. Based on additional numerical calculations of these outcomes,
we discuss possible origins of such differences between two engines and reveal
them. Our results imply that even with an equilibrium bath, a nonequilibrium
working fluid brings on the higher performance than what an equilibrium working
fluid does.


  Absence of localization is demonstrated analytically to leading order in weak
disorder in a one-dimensional Anderson model of a ring threaded by an
Aharonov-Bohm (A-B) flux. The result follows from adapting an earlier
perturbation treatment of disorder in a superconducting ring subjected to an
imaginary vector potential proportional to a depinning field for flux lines
bound to random columnar defects parallel to the axis of the ring. The absence
of localization in the ring threaded by an A-B flux for sufficiently weak
disorder is compatible with large free electron type persistent current
obtained in recent studies of the above model.


  Elongated Bose-Einstein condensates (BECs) exhibit strong spatial phase
fluctuations even well below the BEC transition temperature. We demonstrate
that atom interferometers using such condensates are robust against phase
fluctuations, i.e. the relative phase of the split condensate is reproducible
despite axial phase fluctuations. However, larger phase fluctuations limit the
coherence time, especially in the presence of some asymmetries in the two wells
of the interferometer.