  We aim at studying approximate null-controllability properties of a
particular class of piecewise linear Markov processes (Markovian switch
systems). The criteria are given in terms of algebraic invariance and are
easily computable. We propose several necessary conditions and a sufficient
one. The hierarchy between these conditions is studied via suitable
counterexamples. Equivalence criteria are given in abstract form for general
dynamics and algebraic form for systems with constant coefficients or
continuous switching. The problem is motivated by the study of lysis phenomena
in biological organisms and price prediction on spike-driven commodities.


  Specific heat of dipolar glasses does not obey Debye law. It is of interest
to know if the non-Debye specific heat can be accounted for in terms of
Schottky-type specific heat arising from rotational tunneling states of the
dipoles. This paper deals with rotational tunneling spectra of NH$_{4}^{+}$
ions and the non-Debye specific heat of mixed salts (e.g.
(NH$_{4})_{x}$Rb$_{1-x}$Br) of ammonium and alkali halides which are known to
exhibit dipolar glass phase. We have measured specific heat of above mixed
salts at low temperatures (1.5 K $< T <$ 15 K). It is seen that while the
specific heat of pure salts obeys Debye law, the specific heat of mixed salts
does not obey Debye law. We have studied the effect of the NH$_{4}^{+}$ ion
concentration, first neighbor environment of NH$_{4}^{+}$ ion and the lattice
strain field on the non-Debye specific heat by carrying out measurements on
suitably chosen mixed salts. Independent of above, we have measured the
rotational tunneling spectra, $f(\omega $), of the NH$_{4}^{+}$ ions in above
salts using technique of neutron incoherent inelastic scattering. The above
studies show that both the non-Debye specific heat and the tunneling spectra of
the NH$_{4}^{+}$ ions depend on the NH$_{4}^{+}$ ion concentration, first
neighbor environment of NH$_{4}^{+}$ ions and the lattice strain field. We have
further shown that the temperature dependence of the measured specific heat can
be explained for all the samples in terms of a model that takes account of
contributions to the specific heat from the Debye phonons and the rotational
tunneling states of the NH$_{4}^{+}$ ions. To the best of our knowledge, this
is a first study where it is shown that measured specific heat of
(NH$_{4})_{x}$Rb$_{1-x}$Br can be quantitatively explained in terms of an
experimentally measured rotational tunneling spectra $f(\omega $) of the
NH$_{4}^{+}$ ions.


  This essay provides a comprehensive analysis of the optimization and
performance evaluation of various routing algorithms within the context of
computer networks. Routing algorithms are critical for determining the most
efficient path for data transmission between nodes in a network. The
efficiency, reliability, and scalability of a network heavily rely on the
choice and optimization of its routing algorithm. This paper begins with an
overview of fundamental routing strategies, including shortest path, flooding,
distance vector, and link state algorithms, and extends to more sophisticated
techniques.


  We extend our earlier lattice-QCD analysis of heavy-quark correlators to
smaller lattice spacings and larger masses to obtain new values for the c mass
and QCD coupling, and, for the first time, values for the b mass:
m_c(3GeV,n_f=4)=0.986(6)GeV, alpha_msb(M_Z,n_f=5)=0.1183(7), and
m_b(10GeV,n_f=5)=3.617(25)GeV. These are among the most accurate determinations
by any method. We check our results using a nonperturbative determination of
the mass ratio m_b(mu,n_f)/m_c(mu,n_f); the two methods agree to within our 1%
errors and taken together imply m_b/m_c=4.51(4). We also update our previous
analysis of alpha_msb from Wilson loops to account for revised values for r_1
and r_1/a, finding a new value alpha_\msb(M_Z,n_f=5)=0.1184(6); and we update
our recent values for light-quark masses from the ratio m_c/m_s. Finally, in
the Appendix, we derive a procedure for simplifying and accelerating
complicated least-squares fits.


  The coherence of a random matrix, which is defined to be the largest
magnitude of the Pearson correlation coefficients between the columns of the
random matrix, is an important quantity for a wide range of applications
including high-dimensional statistics and signal processing. Inspired by these
applications, this paper studies the limiting laws of the coherence of $n\times
p$ random matrices for a full range of the dimension $p$ with a special focus
on the ultra high-dimensional setting. Assuming the columns of the random
matrix are independent random vectors with a common spherical distribution, we
give a complete characterization of the behavior of the limiting distributions
of the coherence. More specifically, the limiting distributions of the
coherence are derived separately for three regimes: $\frac{1}{n}\log p \to 0$,
$\frac{1}{n}\log p \to \beta\in (0, \infty)$, and $\frac{1}{n}\log p
\to\infty$. The results show that the limiting behavior of the coherence
differs significantly in different regimes and exhibits interesting phase
transition phenomena as the dimension $p$ grows as a function of $n$.
Applications to statistics and compressed sensing in the ultra high-dimensional
setting are also discussed.


  This paper addresses the question of how an arbitrage-free semimartingale
model is affected when stopped at a random horizon. We focus on
No-Unbounded-Profit-with-Bounded-Risk (called NUPBR hereafter) concept, which
is also known in the literature as the first kind of non-arbitrage. For this
non-arbitrage notion, we obtain two principal results. The first result lies in
describing the pairs of market model and random time for which the resulting
stopped model fulfills NUPBR condition. The second main result characterises
the random time models that preserve the NUPBR property after stopping for any
market model. These results are elaborated in a very general market model, and
we also pay attention to some particular and practical models. The analysis
that drives these results is based on new stochastic developments in
semimartingale theory with progressive enlargement. Furthermore, we construct
explicit martingale densities (deflators) for some classes of local martingales
when stopped at random time.


  Front-end polarization modulation enables improved polarization measurement
stability by modulating the targeted signal above the low-frequency $1/f$
drifts associated with atmospheric and instrumental instabilities and
diminishes the impact of instrumental polarization. In this work, we present
the design and characterization of a new 60-cm diameter Reflective Half-Wave
Plate (RHWP) polarization modulator for the 90 GHz band telescope of the
Cosmology Large Angular Scale Surveyor (CLASS) project. The RHWP consists of an
array of parallel wires (diameter $50~\mathrm{\mu m}$, $175~\mathrm{\mu m}$
pitch) positioned $0.88~\mathrm{mm}$ from an aluminum mirror. In lab tests, it
was confirmed that the wire resonance frequency ($f_\mathrm{res}$) profile is
consistent with the target, $139~\mathrm{Hz}<f_\mathrm{res}<154~\mathrm{Hz}$ in
the optically active region (diameter smaller than $150~\mathrm{mm}$),
preventing the wire vibration during operation and reducing the RHWP
deformation under the wire tension. The mirror tilt relative to the rotating
axis was controlled to be $<15''$, corresponding to an increase in beam width
due to beam smearing of $<0.6''$, negligible compared to the beam's full-width
half-maximum of $36'$. The median and 16/84th percentile of the wire--mirror
separation residual was $0.048^{+0.013}_{-0.014}~\mathrm{mm}$ in the optically
active region, achieving a modulation efficiency
$\epsilon=96.2_{+0.5}^{-0.4}\%$ with an estimated bandpass of 34 GHz. The
angular velocity of the RHWP was maintained to an accuracy of within $0.005\%$
at the nominal rotation frequency ($2.5~\mathrm{Hz}$). The RHWP has been
successfully integrated into the CLASS 90 GHz telescope and started taking data
in June 2024, replacing the previous modulator that has been in operation since
June 2018.


  In this paper, I study the location and symmetry of superconducting protons.
Solving the Tolman-Oppenheimer-Volkoff (TOV) equations based on the unified
Barcelona-Catania-Paris-Madrid equation of state (BCPM EoS) and on the pairing
gap calculations by Lim and Holt [1], I find that roughly 500 meters of the
liquid core (with isotropic and continuous symmetry) and roughly 100-150 meters
of the core-crust interface (with anisotropic symmetry) are superconducting,
while the rest of the star is normal. To specify whether the superconducting
symmetry is discreet in the pasta phase, I study the coexistence of the
saturated nuclear and the pure neutron matter using EoS based on the chiral
effective field theory (ChEFT). I find that the maximum pressure at coexistence
is $P_{*}\simeq0.5\;{\rm MeV\,fm^{-3}}$. To verify the precision of the
coexistence calculations I evaluate the surface and the Coulomb corrections
using the compressible liquid drop model. I calculate the proton tunneling rate
in the perfectly ordered slab region of the pasta phase and conclude that for
the chosen EoS, the proton supercurrent tunneling between the adjacent slabs is
negligible and the slab region should be described as a discreet symmetry
system of quasi two-dimensional layers.


  A nice paper by Morrison demonstrates the recent convergence of opinion that
has taken place concerning the graviton propagator on de Sitter background. We
here discuss the few points which remain under dispute. First, the inevitable
decay of tachyonic scalars really does result in their 2-point functions
breaking de Sitter invariance. This is obscured by analytic continuation
techniques which produce formal solutions to the propagator equation that are
not propagators. Second, Morrison's de Sitter invariant solution for the spin
two sector of the graviton propagator involves derivatives of the scalar
propagator at $M^2 = 0$, where it is not meromorphic unless de Sitter breaking
is permitted. Third, de Sitter breaking does not require zero modes. Fourth,
the ambiguity Morrison claims in the equation for the spin two structure
function is fixed by requiring it to derive from a mode sum. Fifth, Morrison's
spin two sector is not "physically equivalent" to ours because their
coincidence limits differ. Finally, it is only the noninvariant propagator that
gets the time independence and scale invariance of the tensor power spectrum
correctly.


  We study the Lagrangian velocity and acceleration statistics of light
particles (micro-bubbles in water) in homogeneous isotropic turbulence.
Micro-bubbles with a diameter of 340 microns and Stokes number from 0.02 to
0.09 are dispersed in a turbulent water tunnel operated at Taylor-Reynolds
numbers (Re) ranging from 160 to 265. We reconstruct the bubble trajectories by
employing three-dimensional particle tracking velocimetry (PTV). It is found
that the probability density functions (PDFs) of the micro-bubble acceleration
show a highly non-Gaussian behavior with flatness values in the range 23-30.
The acceleration flatness values show an increasing trend with Re, consistent
with previous experiments (Voth et al., JFM, 2002) and numerics (Ishihara et
al., JFM, 2007). These acceleration PDFs show a higher intermittency compared
to tracers (Ayyalasomayajula et al., Phys. Fluids, 2008) and heavy particles
(Ayyalasomayajula et al., Phys. Rev. Lett., 2006) in wind tunnel experiments.
In addition, the micro-bubble acceleration autocorrelation function
decorrelates slower with increasing Re. We also compare our results with
experiments in von Karman flows and point-particle direct numerical simulations
with periodic boundary conditions.


  We consider a state-constrained optimal control problem of a system of two
non-local partial-differential equations, which is an extension of the one
introduced in a previous work in mathematical oncology. The aim is to minimize
the tumor size through chemotherapy while avoiding the emergence of resistance
to the drugs. The numerical approach to solve the problem was the combination
of direct methods and continuation on discretization parameters, which happen
to be insufficient for the more complicated model, where diffusion is added to
account for mutations. In the present paper, we propose an approach relying on
changing the problem so that it can theoretically be solved thanks to a
Pontryagin Maximum Principle in infinite dimension. This provides an excellent
starting point for a much more reliable and efficient algorithm combining
direct methods and continuations. The global idea is new and can be thought of
as an alternative to other numerical optimal control techniques.


  We study the scattering of a pseudoscalar meson off one ground state octet
baryon in covariant baryon chiral perturbation theory (BChPT) up to the
next-to-next-to-leading order. The inherent power counting breaking terms are
removed within extended-on-mass-shell scheme. We perform the first combined
study of the pion-nucleon and kaon-nucleon scattering data in covariant BChPT
and show that it can provide a reasonable description of the experimental data.
In addition, we find that it is possible to fit the experimental baryon masses
and the pion-nucleon and kaon-nucleon scattering data simultaneously at this
order, thus providing a consistent check on covariant BChPT. We compare the
scattering lengths of all the pertinent channels with available experimental
data and those of other approaches. In addition, we have studied the leading
order contributions of the virtual decuplet and found that they can improve the
description of the $\pi N$ phase shifts near the $\Delta(1232)$ peak, while
they have negligible effects on the description of the $K N$ phase shifts.


  Philosophical thinking has a side effect: by aiming to find the essence of a
diverse set of phenomena, it often makes it difficult to see the differences
between them. This can be the case with Mathematics, Programming, Writing and
Philosophy itself. Their unified essence is having a shared understanding of
the world helped by off-loading our cognitive efforts to suitable languages.


  This is the second in a series of papers. Here we develop here an
intersection theory for manifolds equipped with an action of a finite group. As
in our previous paper, our approach will be homotopy theoretic, enabling us to
circumvent the specter of equivariant transversality.
  This theory has applications to embedding problems, equivariant fixed point
theory and the problem of enumerating the periodic points of a self map of a
compact smooth manifold.


  We minimize a discrete version of the fourth-order curvature based Landau
free energy by extending Brakke's Surface Evolver. This model predicts
spherical as well as non-spherical shapes with dimples, bumps and ridges to be
the energy minimizers. Our results suggest that the buckling and faceting
transitions, usually associated with crystalline matter, can also be an
intrinsic property of non-crystalline membranes.


  This paper presents BodyPIN, which is a continuous user authentication system
by contactless wireless sensing using commodity Wi-Fi. BodyPIN can track the
current user's legal identity throughout a computer system's execution. In case
the authentication fails, the consequent accesses will be denied to protect the
system. The recent rich wireless-based user identification designs cannot be
applied to BodyPIN directly, because they identify a user's various activities,
rather than the user herself. The enforced to be performed activities can thus
interrupt the user's operations on the system, highly inconvenient and not
user-friendly. In this paper, we leverage the bio-electromagnetics domain human
model for quantifying the impact of human body on the bypassing Wi-Fi signals
and deriving the component that indicates a user's identity. Then we extract
suitable Wi-Fi signal features to fully represent such an identity component,
based on which we fulfill the continuous user authentication design. We
implement a BodyPIN prototype by commodity Wi-Fi NICs without any extra or
dedicated wireless hardware. We show that BodyPIN achieves promising
authentication performances, which is also lightweight and robust under various
practical settings.


  The interplay of social and strategic motivations in human interactions is a
largely unexplored question in collective social phenomena. Whether
individuals' decisions are taken in a pure strategic basis or due to social
pressure without a rational background crucially influences the model outcome.
Here we study a networked Prisoner's Dilemma in which decisions are made either
based on the replication of the most successful neighbor's strategy
(unconditional imitation) or by pure social imitation following an update rule
inspired by the voter model. The main effects of the voter dynamics are an
enhancement of the final consensus, i.e., asymptotic states are generally
uniform, and a promotion of cooperation in certain regions of the parameter
space as compared to the outcome of purely strategic updates. Thus, voter
dynamics acts as an interface noise and has a similar effect to a pure random
noise; furthermore, its influence is mostly independent of the network
heterogeneity. When strategic decisions are made following other update rules
such as the replicator or Moran processes, the dynamic mixed state found under
unconditional imitation for some parameters disappears, but an increase of
cooperation in certain parameter regions is still observed. Comparing our
results with recent experiments on the Prisoner's Dilemma, we conclude that
such a mixed dynamics may explain moody conditional cooperation among the
agents.


  The category of compact Hausdorff locales is a pretopos which is filtral,
meaning that every object is covered by one whose subobject lattice is
isomorphic to the lattice of filters of complemented elements. We show that any
filtral pretopos satisfying some mild additional conditions can be embedded
into the category of compact Hausdorff locales. This result is valid in the
internal logic of any topos. Assuming the principle of weak excluded middle and
the existence of copowers of the terminal object in the pretopos, the image of
the embedding contains all spatial compact Hausdorff locales.
  The notion of filtrality was introduced by V. Marra and L. Reggio (Theory
Appl. Categ., 2020) to characterise the category of compact Hausdorff spaces
within the class of pretoposes. Our results can be regarded as a constructive
extension of the aforementioned characterisation, avoiding reference to points.
If the ambient logic is classical, i.e. it satisfies excluded middle, and the
prime ideal theorem for Boolean algebras holds, we obtain as a corollary the
characterisation of compact Hausdorff spaces in op. cit.


  In multi-hop QA, answering complex questions entails iterative document
retrieval for finding the missing entity of the question. The main steps of
this process are sub-question detection, document retrieval for the
sub-question, and generation of a new query for the final document retrieval.
However, building a dataset that contains complex questions with sub-questions
and their corresponding documents requires costly human annotation. To address
the issue, we propose a new method for weakly supervised multi-hop retriever
pre-training without human efforts. Our method includes 1) a pre-training task
for generating vector representations of complex questions, 2) a scalable data
generation method that produces the nested structure of question and
sub-question as weak supervision for pre-training, and 3) a pre-training model
structure based on dense encoders. We conduct experiments to compare the
performance of our pre-trained retriever with several state-of-the-art models
on end-to-end multi-hop QA as well as document retrieval. The experimental
results show that our pre-trained retriever is effective and also robust on
limited data and computational resources.


  It is demonstrated that the well-known Smale-horseshoe chaos exists in the
time evolution of the one-dimensional Bose-Einstein condensate (BEC) driven by
the time-periodic harmonic or inverted-harmonic potential. A formally exact
solution of the time-dependent Gross-Pitaevskii equation is constructed, which
describes the matter shock waves with chaotic or periodic amplitudes and
phases. When the periodic driving is switched off and the number of condensed
atoms is conserved, we obtained the exact stationary states and non-stationary
states. The former contains the stable non-propagated shock wave, and in the
latter the shock wave alternately collapses and grows for the harmonic trapping
or propagates with exponentially increased shock-front speed for the
antitrapping. It is revealed that existence of chaos play a role for
suppressing the blast of matter wave. The results suggest a method for
preparing the exponentially accelerated BEC shock waves or the stable
stationary states.


  In this work we design and train deep neural networks to predict topological
invariants for one-dimensional four-band insulators in AIII class whose
topological invariant is the winding number, and two-dimensional two-band
insulators in A class whose topological invariant is the Chern number. Given
Hamiltonians in the momentum space as the input, neural networks can predict
topological invariants for both classes with accuracy close to or higher than
90%, even for Hamiltonians whose invariants are beyond the training data set.
Despite the complexity of the neural network, we find that the output of
certain intermediate hidden layers resembles either the winding angle for
models in AIII class or the solid angle (Berry curvature) for models in A
class, indicating that neural networks essentially capture the mathematical
formula of topological invariants. Our work demonstrates the ability of neural
networks to predict topological invariants for complicated models with local
Hamiltonians as the only input, and offers an example that even a deep neural
network is understandable.


  The quest for high-temperature superconductivity at ambient pressure is a
central issue in physics. In this regard, the relationship between
unconventional superconductivity and the quantum critical point (QCP)
associated with the suppression of some form of symmetry-breaking order to zero
temperature has received particular attention. The key question is how the
strength of the electron pairs changes near the QCP, and this can be verified
by high-field experiments. However, such studies are limited mainly to
superconductors with magnetic QCPs, and the possibility of unconventional
mechanisms by which nonmagnetic QCP promotes strong pairing remains a
nontrivial issue. Here, we report systematic measurements of the upper critical
field $H_{{\rm c2}}$ in nonmagnetic FeSe$_{1-x}$Te$_{x}$ superconductors, which
exhibit a QCP of electronic nematicity characterized by spontaneous
rotational-symmetry breaking. As the magnetic field increases, the
superconducting phase of FeSe$_{1-x}$Te$_{x}$ shrinks to a narrower dome
surrounding the nematic QCP. The analysis of $H_{{\rm c2}}$ reveals that the
Pauli-limiting field is enhanced toward the QCP, implying that the pairing
interaction is significantly strengthened via nematic fluctuations emanated
from the QCP. Remarkably, this nonmagnetic nematic QCP is not accompanied by a
divergent effective mass, distinct from the magnetically mediated pairing. Our
observation opens up a nonmagnetic route to high-temperature superconductivity.


  This report demonstrates our solution for the Open Images 2018 Challenge.
Based on our detailed analysis on the Open Images Datasets (OID), it is found
that there are four typical features: large-scale, hierarchical tag system,
severe annotation incompleteness and data imbalance. Considering these
characteristics, an amount of strategies are employed, including SNIPER, soft
sampling, class-aware sampling (CAS), hierarchical non-maximum suppression
(HNMS) and so on. In virtue of these effective strategies, and further using
the powerful SENet154 armed with feature pyramid module and deformable ROIalign
as the backbone, our best single model could achieve a mAP of 56.9%. After a
further ensemble with 9 models, the final mAP is boosted to 62.2% in the public
leaderboard (ranked the 2nd place) and 58.6% in the private leaderboard (ranked
the 3rd place, slightly inferior to the 1st place by only 0.04 point).


  Following the recent work by Braguta et al., we perform an indirect
calculation of the chiral vortical conductivity with free lattice overlap
fermions by measuring the response of the energy flow to the constant axial
magnetic field. We find that the measurements are contaminated by very large
finite-volume artifacts. However, the continuum result for finite-temperature
contribution to the chiral vortical conductivity (T^2/12) is still reproduced
in the limit of infinite volume at fixed temperature.


  Digital twin serves as a crucial facilitator in the advancement and
implementation of emerging technologies within 5G and beyond networks. However,
the intricate structure and diverse functionalities of the existing 5G core
network, especially the control plane, present challenges in constructing core
network digital twins. In this paper, we propose two novel data-driven
architectures for modeling the 5G control plane and implement corresponding
deep learning models, namely 5GC-Seq2Seq and 5GC-former, based on the Vanilla
Seq2Seq model and Transformer decoder respectively. We also present a solution
enabling the interconversion of signaling messages and length-limited vectors
to construct a dataset. The experiments are based on 5G core network signaling
messages collected by the Spirent C50 network tester, encompassing various
procedures such as registration, handover, and PDU sessions. The results show
that 5GC-Seq2Seq achieves a 99.997\% F1-score (a metric measuring the accuracy
of positive samples) in single UE scenarios with a simple structure, but
exhibits significantly reduced performance in handling concurrency. In
contrast, 5GC-former surpasses 99.999\% F1-score while maintaining robust
performance under concurrent UE scenarios by constructing a more complex and
highly parallel model. These findings validate that our method accurately
replicates the principal functionalities of the 5G core network control plane.


  We prove stability for a formally determined inverse problem for a hyperbolic
PDE where the coefficients depend on space and time variables. The hyperbolic
operator has constant wave speed and we study the recovery of zeroth order and
first order coefficients and the space dimension can be one or higher. We use a
modification of the Bukhgeim-Klibanov method to obtain our results.


  I give a pedagogical introduction to the physics of electroweak symmetry
breaking and the uses of effective field theory in the context of Higgs
physics. Higgs boson production and decay at the LHC and the consistency of the
Higgs measurements with triviality arguments, vacuum stability, and precision
electroweak measurements are discussed. Effective Lagrangian techniques are
used to understand potential deviations from the Standard Model (SM)
predictions. Finally, I end with a brief discussion of the future of Higgs
physics.


  The feasibility of measuring the pion and kaon structure functions has been
investigated. A high luminosity electron-proton collider would make these
measurements feasible. Also, it appears feasible to measure these structure
functions in a nuclear medium. Simulations using the RAPGAP Monte Carlo of a
possible pion structure function measurement are presented.


  With the rapid development of railways, especially high-speed railways, there
is an increasingly urgent demand for new wireless communication system for
railways. Taking the mature 5G technology as an opportunity, 5G-railways (5G-R)
have been widely regarded as a solution to meet the diversified demands of
railway wireless communications. For the design, deployment and improvement of
5G-R networks, radio communication scenario classification plays an important
role, affecting channel modeling and system performance evaluation. In this
paper, a standardized radio communication scenario classification, including 18
scenarios, is proposed for 5G-R. This paper analyzes the differences of 5G-R
scenarios compared with the traditional cellular networks and GSM-railways,
according to 5G-R requirements and the unique physical environment and
propagation characteristics. The proposed standardized scenario classification
helps deepen the research of 5G-R and promote the development and application
of the existing advanced technologies in railways.


  This paper presents an end-to-end framework for safe learning-based control
(LbC) using nonlinear stochastic MPC and distributionally robust optimization
(DRO). This work is motivated by several open challenges in LbC literature. In
particular, many control-theoretic LbC methods require subject matter expertise
in order to translate their own safety guarantees, often manifested as
preexisting data of safe trajectories or structural model knowledge. In this
paper, we focus on LbC where the controller is applied directly to a system of
which it has no or extremely limited direct experience, towards safety during
\textit{tabula-rasa} or ``\textit{blank slate''} model-based learning and
control as a challenging case for validation. This explores the boundary of the
status-quo in control theory relating to requirements for subject matter
expertise. We show under basic and limited assumptions on the underlying
problem, we can translate probabilistic guarantees on feasibility to nonlinear
systems using results in stochastic MPC and DRO literature whose relevance we
formally extend in a mathematical analysis. We also present a coupled and
intuitive formulation for persistence of excitation (PoE), and illustrate the
connection between PoE and applicability of the proposed method. Our case
studies of vehicle obstacle avoidance and safe extreme fast charging of
lithium-ion batteries reveal powerful empirical results supporting the
underlying DRO theory. Our method is widely applicable within the LbC domain
to, for example, airborne wind energy systems, vehicle obstacle avoidance, and
energy storage systems management. It is also applicable to quantifying
uncertainty beyond the LbC case.


  For nearly two decades, CAPTCHAs have been widely used as a means of
protection against bots. Throughout the years, as their use grew, techniques to
defeat or bypass CAPTCHAs have continued to improve. Meanwhile, CAPTCHAs have
also evolved in terms of sophistication and diversity, becoming increasingly
difficult to solve for both bots (machines) and humans. Given this
long-standing and still-ongoing arms race, it is critical to investigate how
long it takes legitimate users to solve modern CAPTCHAs, and how they are
perceived by those users.
  In this work, we explore CAPTCHAs in the wild by evaluating users' solving
performance and perceptions of unmodified currently-deployed CAPTCHAs. We
obtain this data through manual inspection of popular websites and user studies
in which 1,400 participants collectively solved 14,000 CAPTCHAs. Results show
significant differences between the most popular types of CAPTCHAs:
surprisingly, solving time and user perception are not always correlated. We
performed a comparative study to investigate the effect of experimental context
-- specifically the difference between solving CAPTCHAs directly versus solving
them as part of a more natural task, such as account creation. Whilst there
were several potential confounding factors, our results show that experimental
context could have an impact on this task, and must be taken into account in
future CAPTCHA studies. Finally, we investigate CAPTCHA-induced user task
abandonment by analyzing participants who start and do not complete the task.


  The Ultra-luminous Compact X-ray Sources (ULXs) in nearby spiral galaxies and
the Galactic super-luminal jet sources share the common spectral characteristic
that they have extremely high disk temperatures which cannot be explained in
the framework of the standard accretion disk model in the Schwarzschild metric.
We examine several possibilities to solve this ``too-hot'' disk problem. In
particular, we have calculated an extreme Kerr disk model to fit the observed
spectra. We found that the Kerr disk will become significantly harder compared
to the Schwarzschild disk only when the disk is highly inclined. For
super-luminal jet sources, which are known to be inclined systems, the Kerr
disk model may work if we choose proper values for the black hole angular
momentum. For the ULXs, however, the Kerr disk interpretation will be
problematic, as it is highly unlikely that their accretion disks are
preferentially inclined.


  Rigorous statistical numerical analysis of the response of a nonspherical
dust particle ensemble composed of aggregates of astronomical silicate is
presented. It is found that the rotational disruption mechanism is not only
likely to occur but to be a key element in explaining many separate
observations of cometary dust. Namely, radiative torques are shown to spin-up
and align cometary dust within the timescales of cometary activity.
Additionally, the radiative torque alignment and disruption mechanisms within
certain conditions are shown to be consistent with observations of rapid
polarization of dust and spectral bluing of dust. The results indicate that
radiative torques should be taken into account nearly universally when
considering the evolution of cometary dust.


  We explore the response of the He II 304 {\AA} and He I 584 {\AA} line
intensities to electron beam heating in solar flares using radiative
hydrodynamic simulations. Comparing different electron beams parameters, we
found that the intensities of both He lines are very sensitive to the energy
flux deposited in the chromosphere, or more specifically to the heating rate,
with He II 304 {\AA} being more sensitive to the heating than He I 584 {\AA}.
Therefore, the He line ratio increases for larger heating rates in the
chromosphere. A similar trend is found in observations, using SDO/EVE He
irradiance ratios and estimates of the electron beam energy rate obtained from
hard X-ray data. From the simulations, we also found that spectral index of the
electrons can affect the He ratio but a similar effect was not found in the
observations.


  We consider the homogenisation of the Stokes equations in a porous medium
which is evolving in time. At the interface of the pore space and the solid
part, we prescribe an inhomogeneous Dirichlet boundary condition, which enables
to model a no-slip boundary condition at the evolving boundary. We pass
rigorously to the homogenisation limit with the two-scale transformation
method. In order to derive uniform a priori estimates, we show a Korn-type
inequality for the two-scale transformation method and construct a family of
$\varepsilon$-scaled operators $\operatorname{div}_\varepsilon^{-1}$, which are
right-inverse to the corresponding divergences. The homogenisation result is a
new version of Darcy's law. It features a time- and space-dependent
permeability tensor, which accounts for the local pore structure, and a
macroscopic compressibility condition, which induces a new source term for the
pressure. In the case of a no-slip boundary condition at the interface, this
source term relates to the change of the local pore volume.


  We consider an extension of nuMSSM with an extra U(1) that realizes D-term
inflation driven by the right-handed sneutrino. Non-renormalizable terms in the
Kahler potential and the superpotential are considered, the latter controlled
by a suitable discrete R-symmetry. We find that, for subplanckian inflaton
values, the predictions of inflationary parameters are compatible with
observations, establishing the right-handed sneutrino driven inflation as a
viable scenario.


  In this paper we study existence and spectral properties for weak solutions
of Neumann and Dirichlet problems associated to second order linear degenerate
elliptic partial differential operators $X$, with rough coefficients of the
form $$X=-\text{div}(P\nabla )+{\bf HR}+{\bf S^\prime G} +F$$ in a geometric
homogeneous space setting where the $n\times n$ matrix function $P=P(x)$ is
allowed to degenerate. We give a maximum principle for weak solutions of
$Xu\leq 0$ and follow this with a result describing a relationship between
compact projection of the degenerate Sobolev space $QH^{1,p}$ into $L^q$ and a
Poincar\'e inequality with gain adapted to $Q$.


  Drug metabolites usually have structures of split-ring resonators (SRRs),
which might lead to negative permittivity and permeability in electromagnetic
field. As a result, in the UV-vis region, the latent fingermarks images of drug
addicts and non drug users are inverse. The optical properties of latent
fingermarks are quite different between drug addicts and non-drug users. This
is a technic superiority for crime scene investigation to distinguish them. In
this paper, we calculate the permittivity and permeability of drug metabolites
using tight-binding model. The latent fingermarks of smokers and non-smokers
are given as an example.


  We consider an ancient solution $g(\cdot,t)$ of the Ricci flow on a compact
surface that exists for $t\in (-\infty,T)$ and becomes spherical at time $t=T$.
We prove that the metric $g(\cdot,t)$ is either a family of contracting
spheres, which is a type I ancient solution, or a Rosenau solution, which is a
type II ancient solution.


  Catalan's conjecture claims that the Diophantine equation $x^p-y^q=1$ admits
the unique solution $3^2-2^3=1$ in integers $x,y,p,q \ge 2$. The conjecture has
been finally proved by P. Mih\u{a}ilescu (2002) using the theory of cyclotomic
fields and Galois modules.
  Here, relying only on elementary techniques, we prove several instances of
this classical result. In particular, we prove the conjecture in the following
cases: $p$ even (due to V.A. Lebesgue), $q$ is even (due to L. Euler and Chao
Ko), $x$ divides $q$, $y$ divides $x-1$, $y$ is a power of a prime, and $y\le
p^{p/2}$.


  We give a tutorial for the study of dynamical systems on networks. We focus
especially on "simple" situations that are tractable analytically, because they
can be very insightful and provide useful springboards for the study of more
complicated scenarios. We briefly motivate why examining dynamical systems on
networks is interesting and important, and we then give several fascinating
examples and discuss some theoretical results. We also briefly discuss
dynamical systems on dynamical (i.e., time-dependent) networks, overview
software implementations, and give an outlook on the field.


  Ion irradiation can cause burrowing of nanoparticles in substrates, strongly
depending on the material properties and irradiation parameters. In this study,
we demonstrate that the sinking process can be accomplished with ion
irradiation of cube-shaped Ag nanoparticles on top of silicon; how ion
channeling affects the sinking rate; and underline the importance of the
amorphous state of the substrate upon ion irradiation. Based on our
experimental findings, the sinking process is described as being driven by
capillary forces enabled by ion-induced plastic flow of the substrate.


  Ultrafast scattering using X-rays or electrons is an emerging method to
obtain structure dynamics at the atomic length and time scales. However,
directly resolving in real-space atomic motions is inherently limited by the
finite detector range and the probe energy. As a result, the time-resolved
signal interpretation is mostly done in reciprocal space and relies on modeling
and simulations of specific structures and processes. Here, we introduce a
model-free approach to directly resolve scattering signals in real space,
surpassing the diffraction limit, using scattering kernels and signal priors
that naturally arise from the measurement constraints. We demonstrate the
approach on simulated and experimental data, recover multiple atomic motions at
sub-$\angstrom$ngstrom resolutions, and discuss the recovery accuracy and
resolution limits vs signal fidelity. The approach offers a robust path to
obtain high-resolution real-space information of atomic-scale structure
dynamics using current time-resolved X-ray or electron scattering sources.


  Peppytides is a coarse-grained, accurate, physical model of the polypeptide
chain. I have shared instructions to make your own polypeptide chain and STL
files of Peppytides in MAKE magazine in Jan 2014 issue. However, Peppytides
involves a lot of steps and assembly of units. People were asking me, 'Is there
any easier way to make these models?'. I have been at several workshops,
hands-on sessions, talks and a science events with Peppytides. From the
feedback that I got everywhere, most of the makers, teachers and students want
something that is 3D-Print-&-Go, or at least easier to make, even at the cost
of some features.
  I have designed a new version of the model, named PeppyChains, in which the
backbone chain of the model can be 3d-printed as a single unit. PeppyChains
design eliminates the assembling of parts to form the backbone chain, but with
the cost of losing the ability to use bias-magnets to favor certain phi/psi
angles in the backbone. I have been demonstrating PeppyChains at various talks
and workshops along with Peppytides, and I have received requests for making
the STL file public. On popular demand, here I am sharing this STL and
providing the step-by-step instructions to make PeppyChains. Just add the
hydrogen-bond magnets, paint and color-code the atoms, and you are ready to go!
No drilling. No time consuming assembly.


  This paper investigates a hypothesis proposed in previous research relating
neutron star (NS) mass and its dark matter (DM) accumulation. As DM
accumulates, NS mass decreases, predicting lower NS masses toward the Galactic
center. Due to limited NSs data near the galactic center, we examine NSs
located within DM clumps. Using the CLUMPY code simulations, we determine the
DM clumps distribution, with masses from 10 to $10^{8}$ $M_{\odot}$ and scales
from $10^{-3}$ to 10 kpc. These clumps' DM exhibit a peak at the center,
tapering toward the outskirts, resembling our Galaxy's DM distribution.
  We analyse these DM clumps' NS mass variations, considering diverse DM
particle masses and galaxy types. We find relatively stable NS mass within 0.01
to 5 kpc from the clump center. This stability supports the initial hypothesis,
particularly for NSs located beyond 0.01 kpc from the clump center, where NS
mass reaches a plateau around 0.1 kpc. Nevertheless, NS mass near the clump's
periphery reveals spatial dependence: NS position within DM clumps influences
its mass in Milky Way-type galaxies. Moreover, this dependence varies with the
DM model considered.
  In summary, our study investigates the proposed link between NS mass and DM
accumulation by examining NSs within DM clumps. While NS mass remains stable at
certain distances from the clump center, spatial dependencies arise near the
clump's outer regions, contingent on the specific DM model.


  Cross-modality image synthesis is an active research topic with multiple
medical clinically relevant applications. Recently, methods allowing training
with paired but misaligned data have started to emerge. However, no robust and
well-performing methods applicable to a wide range of real world data sets
exist. In this work, we propose a generic solution to the problem of
cross-modality image synthesis with paired but non-aligned data by introducing
new deformation equivariance encouraging loss functions. The method consists of
joint training of an image synthesis network together with separate
registration networks and allows adversarial training conditioned on the input
even with misaligned data. The work lowers the bar for new clinical
applications by allowing effortless training of cross-modality image synthesis
networks for more difficult data sets.


  We introduce a new topological effect involving interference of two meson
loops, manifesting a path-independent topological area dependence. The effect
also draws a connection between quark confinement, Wilson-loops and topological
interference effects. Although this is only a gedanken experiment in the
context of particle physics, such an experiment may be realized and used as a
tool to test confinement effects and phase transitions in quantum simulation of
dynamic gauge theories.


  We consider optical spectroscopy of molecular junctions from the quantum
transport perspective when radiation field is quantized and optical response of
the system is simulated as photon flux. Using exact expressions for photon and
electronic fluxes derived within the nonequilibrium Green function (NEGF)
methodology and utilizing fourth order diagrammatic perturbation theory in
molecular coupling to radiation field we perform simulations employing
realistic parameters. Results of the simulations are compared to the bare
perturbation theory (PT) usually employed in studies on nonlinear optical
spectroscopy to classify optical processes. We show that the bare PT violates
conservation laws, while flux conserving NEGF formulation mixes optical
processes.


  One of the fundamental questions in inflation is how to characterize the
structure of different types of models in the field theoretic landscape.
Proposals in this direction include attempts to directly characterize the
formal structure of the theory by considering complexity measures of the
potentials. An alternative intrinsic approach is to focus on the behavior of
the observables that result from different models and to ask whether their
behavior differs among models. This type of analysis can be applied even to
nontrivial multifield theories where a natural measure of the complexity of the
model is not obvious and the analytical evaluation of the observables is often
impossible. In such cases one may still compute these observables numerically
and investigate their behavior. One interesting case is when observables show a
scaling behavior, in which case theories can be characterized in terms of their
scaling amplitudes and exponents. Generically, models have nontrivial parameter
spaces, leading to exponents that are functions of these parameters. In such
cases we consider an iterative procedure to determine whether the exponent
functions in turn lead to a scaling behavior. We show that modular inflation
models can be characterized by families of simple scaling laws and that the
scaling exponents that arise in this way in turn show a scaling law in
dependence of these varying energy scales.


  In this article, we discuss the mechanism for generating the lepton/baryon
number and its subsequent conservation based on extradimensional evolution. The
internal angular momentum of extra space is related to the lepton/baryon
charge. Extra space metric are assumed to be initially asymmetric. Symmetries
appear during inflation due to an increase in entropy. Using the
multidimensional field toy model, we show that internal angular momentum can
accumulate in fermions, which could explain the lepton/baryon asymmetry of the
Universe.


  We investigate contributions of excited states to nucleon matrix elements by
studying the two- and three-point functions using nucleon and pion-nucleon
interpolating fields. This study is carried out using twisted mass fermion
ensembles with pion masses 346 MeV and 131 MeV. We compare the results obtained
using these two ensembles and show preliminary results for nucleon charges.


  We develop a method to search for pair halos around active galactic nuclei
(AGN) through a temporal analysis of gamma-ray data. The basis of our method is
an analysis of the spatial distributions of photons coming from AGN flares and
from AGN quiescent states and a further comparison of these two spatial
distributions. This method can also be used for a reconstruction of a point
spread function (PSF). We found no evidence for a pair halo component through
this method by applying it to the Fermi-LAT data in the energy bands of 4.5-6,
6-10, and >10 GeV and set upper limits on the fraction of photons attributable
to a pair halo component. An illustration of how to reconstruct the PSF of
Fermi-LAT is given. We demonstrate that the PSF reconstructed by using this
method is in good agreement with that which was obtained by using the gamma-ray
data taken by LAT in the direction of the Crab pulsar and nebula.


  We show how to extend the enhanced Gaussian noise (EGN) model to account for
polarization-dependent loss (PDL) of optical devices placed along a fiber-optic
link. We provide a comprehensive theory highlighting the relationships between
the time, frequency, and polarization domains in the presence of fiber
nonlinear Kerr effect and amplified spontaneous emission. We double-check the
new model with split-step Fourier method (SSFM) simulations showing very good
accuracy. The model can be efficiently exploited to estimate low values of
outage probabilities induced by PDL with computational times orders of
magnitude faster than the SSFM, thus opening new opportunities in the design of
optical communication links.


  For coherent electron spins, hyperfine coupling to nuclei in the host
material can either be a dominant source of unwanted spin decoherence or, if
controlled effectively, a resource allowing storage and retrieval of quantum
information. To investigate the effect of a controllable nuclear environment on
the evolution of confined electron spins, we have fabricated and measured
gate-defined double quantum dots with integrated charge sensors made from
single-walled carbon nanotubes with a variable concentration of 13C (nuclear
spin I=1/2) among the majority zero-nuclear-spin 12C atoms. Spin-sensitive
transport in double-dot devices grown using methane with the natural abundance
(~ 1%) of 13C is compared with similar devices grown using an enhanced (~99%)
concentration of 13C. We observe strong isotope effects in spin-blockaded
transport, and from the dependence on external magnetic field, estimate the
hyperfine coupling in 13C nanotubes to be on the order of 100 micro-eV, two
orders of magnitude larger than anticipated theoretically. 13C-enhanced
nanotubes are an interesting new system for spin-based quantum information
processing and memory, with nuclei that are strongly coupled to gate-controlled
electrons, differ from nuclei in the substrate, are naturally confined to one
dimension, lack quadrupolar coupling, and have a readily controllable
concentration from less than one to 10^5 per electron.


  We prove an explicit Chinese Remainder Theorem for one variable polynomials
with complex coefficients, and derive some consequences.


  In this paper, we compare the currently available evolutionary tracks for
Galactic massive stars. Our main goal is to highlight the uncertainties on the
predicted evolutionary paths. We compute stellar evolution models with the
codes MESA and STAREVOL. We compare our results with those of four published
grids of massive stellar evolution models (Geneva, STERN, Padova and FRANEC
codes). We first investigate the effects of overshooting, mass loss,
metallicity, chemical composition. We subsequently focus on rotation. Finally,
we compare the predictions of published evolutionary models with the observed
properties of a large sample of Galactic stars. We find that all models agree
well for the main sequence evolution. Large differences in luminosity and
temperatures appear for the post main sequence evolution, especially in the
cool part of the HR diagram. Depending on the physical ingredients, tracks of
different initial masses can overlap, rendering any mass estimate doubtful. For
masses between 7 and 20 Msun, we find that the main sequence width is slightly
too narrow in the Geneva models including rotation. It is (much) too wide for
the (STERN) FRANEC models. This conclusion is reached from the investigation of
the HR diagram and from the evolution of the surface velocity as a function of
surface gravity. An overshooting parameter alpha between 0.1 and 0.2 in models
with rotation is preferred to reproduce the main sequence width. Determinations
of surface abundances of carbon and nitrogen are partly inconsistent and cannot
be used at present to discriminate between the predictions of published tracks.
For stars with initial masses larger than about 60 Msun, the FRANEC models with
rotation can reproduce the observations of luminous O supergiants and WNh
stars, while the Geneva models remain too hot.


  We investigate the role of nonperturbative, bubble-like inhomogeneities on
the decay rate of false-vacuum states in two and three-dimensional scalar field
theories. The inhomogeneities are induced by setting up large-amplitude
oscillations of the field about the false vacuum as, for example, after a rapid
quench or in certain models of cosmological inflation. We show that, for a wide
range of parameters, the presence of large-amplitude bubble-like
inhomogeneities greatly accelerates the decay rate, changing it from the
well-known exponential suppression of homogeneous nucleation to a power-law
suppression. It is argued that this fast, power-law vacuum decay -- known as
resonant nucleation -- is promoted by the presence of long-lived oscillons
among the nonperturbative fluctuations about the false vacuum. A phase diagram
is obtained distinguishing three possible mechanisms for vacuum decay:
homogeneous nucleation, resonant nucleation, and cross-over. Possible
applications are briefly discussed.


  In arXiv:1106.4305 extended superpolynomials were introduced for the torus
links T[m,mk+r], which are functions on the entire space of time variables and,
at expense of reducing the topological invariance, possess additional algebraic
properties, resembling those of the matrix model partition functions and the
KP/Toda tau-functions. Not surprisingly, being a suitable extension it actually
allows one to calculate the superpolynomials. These functions are defined as
expansions into MacDonald polynomials, and their dependence on k is entirely
captured by the action of the cut-and-join operator, like in the HOMFLY case.
We suggest a simple description of the coefficients in these character
expansions, by expanding the initial (at k=0) conditions for the k-evolution
into the new auxiliary basis, this time provided by the Hall-Littlewood
polynomials, which, hence, play a role in the description of the dual
m-evolution. For illustration we list manifest expressions for a few first
series, mk\pm 1, mk\pm 2, mk\pm 3, mk\pm 4. Actually all formulas were
explicitly tested up to m=17 strands in the braid.


  We perform three dimensional (3D) ideal magnetohydrodynamic (MHD) simulations
to study the parametric decay instability of Alfven waves in turbulent plasmas
and explore its possible applications in the solar wind. We find that, over a
broad range of parameters in background turbulence amplitudes, the parametric
decay instability of an Alfven wave with various amplitudes can still occur,
though its growth rate in turbulent plasmas tends to be lower than both the
theoretical linear theory prediction and that in the non-turbulent situations.
Spatial - temporal FFT analyses of density fluctuations produced by the
parametric decay instability match well with the dispersion relation of the
slow MHD waves. This result may provide an explanation of the generation
mechanism of slow waves in the solar wind observed at 1 AU. It further
highlights the need to explore the effects of density variations in modifying
the turbulence properties as well as in heating the solar wind plasmas.


  This paper presents a Bayesian estimation method for the passive localization
of an acoustic source in shallow water. Our probabilistic focalization approach
estimates the time-varying source location by associating direction of arrival
(DOA) observations to DOAs predicted based on a statistical model. Embedded ray
tracing makes it possible to incorporate environmental parameters and
characterize the nonlinear acoustic waveguide. We demonstrate performance
advantages of our approach compared to matched field processing using data
collected during the SWellEx-96 experiment.


  Quantum mechanics can strongly influence the noise properties of mesoscopic
devices. To probe this effect we have measured the current fluctuations at
high-frequency (5-90G Hz) using a superconductor-insulator-superconductor
tunnel junction as an on-chip spectrum analyzer. By coupling this
frequency-resolved noise detector to a quantum device we can measure the
high-frequency, non-symmetrized noise as demonstrated for a Josephson junction.
The same scheme has been used to detect the current fluctuations arising from
coherent charge oscillations in a two-level system, a superconducting charge
qubit. A narrow band peak was observed in the spectral noise density at the
frequency of the coherent charge oscillations.


  We construct a stochastic model showing the relationship between noise,
gradient flows and rate-independent systems. The model consists of a
one-dimensional birth-death process on a lattice, with rates derived from
Kramers' law as an approximation of a Brownian motion on a wiggly energy
landscape. Taking various limits we show how to obtain a whole family of
generalized gradient flows, ranging from quadratic to rate-independent ones,
connected via '$L \log L$' gradient flows. This is achieved via
Mosco-convergence of the renormalized large-deviations rate functional of the
stochastic process.


  A solution of magnetic Hall equations for plasma filaments in the Coulomb
gauge is obtained in the non-holonomic frame. Some physical features of the
solution include, the non-conservation of the magnetic helicity and the decay
of the magnetic field in the filaments. From the mathematical point of view,the
presence of Frenet torsion in the filament is actually shown to be fundamental
for the breaking of conservation of magnetic helicity in the case of helicoidal
filaments. Since the magnetic helicity is not conserved even in the Coulomb
gauge, and the magnetic field decays, one can say that the dynamo action fails.
Actually the presence of torsion enhances the breaking of magnetic field
helicity conservation. A similar formula of the one obtained here without
considering the Hall effect has been obtained by Moffatt and Ricca (PRSA-1992)
in the case of holonomic filaments. It is shown that unknotted magnetic
filaments may place a lower bound on the magnetic energy. Discussions on the
writhe number are also discussed.


  Spectral Photon-Counting Computed Tomography (SPCCT) is a promising
technology that has shown a number of advantages over conventional X-ray
Computed Tomography (CT) in the form of material separation, artefact removal
and enhanced image quality. However, due to the increased complexity and
non-linearity of the SPCCT governing equations, model-based reconstruction
algorithms typically require handcrafted regularisation terms and meticulous
tuning of hyperparameters making them impractical to calibrate in variable
conditions. Additionally, they typically incur high computational costs and in
cases of limited-angle data, their imaging capability deteriorates
significantly. Recently, Deep Learning has proven to provide state-of-the-art
reconstruction performance in medical imaging applications while circumventing
most of these challenges. Inspired by these advances, we propose a Deep
Learning imaging method for SPCCT that exploits the expressive power of Neural
Networks while also incorporating model knowledge. The method takes the form of
a two-step learned primal-dual algorithm that is trained using case-specific
data. The proposed approach is characterised by fast reconstruction capability
and high imaging performance, even in limited-data cases, while avoiding the
hand-tuning that is required by other optimisation approaches. We demonstrate
the performance of the method in terms of reconstructed images and quality
metrics via numerical examples inspired by the application of cardiovascular
imaging.


  The detection of phosphine in the atmosphere of Venus at an abundance of
$\sim 20$ ppb suggests that this gas is being generated by either indeterminate
abiotic pathways or biological processes. We consider the latter possibility,
and explore whether the amount of biomass required to produce the observed flux
of phosphine may be reasonable. We estimate that the typical biomass densities
predicted by our simple model are potentially orders of magnitude lower than
the biomass density of Earth's aerial biosphere in the lower atmosphere. We
briefly discuss how small spacecraft could sample the Venusian cloud decks and
search for biomarkers.


  A specific combination of $s$-state Lamb shift $\Delta E_L(1s_{1/2}) - n^3
\Delta E_L(ns_{1/2})$ is considered. Its value is calculated both in the
hydrogen and deuterium atoms for $n$ up to 12. The result inludes all
correction which can contribute $1 kHz$ and particulary: one-loop self energy
and vacuum polarization, two-loop contribution. Nuclear finite-size corrections
for the isotopic difference of the combination are also evaluated.


  We compare a series of time compression methods applied to normal and clear
speech. First we evaluate a linear (uniform) method applied to these styles as
well as to naturally-produced fast speech. We found, in line with the
literature, that unprocessed fast speech was less intelligible than linearly
compressed normal speech. Fast speech was also less intelligible than
compressed clear speech but at the highest rate (three times faster than
normal) the advantage of clear over fast speech was lost. To test whether this
was due to shorter speech duration we evaluate, in our second experiments, a
range of methods that compress speech and silence at different rates. We found
that even when the overall duration of speech and silence is kept the same
across styles, compressed normal speech is still more intelligible than
compressed clear speech. Compressing silence twice as much as speech improved
results further for normal speech with very little additional computational
costs.


  Revisiting charge transport in degenerate hopping systems we present a
modification to the drift diffusion equation where instead of employing the
generalized Einstein relation we add an energy flux term thus solving several
inconsistencies. This leads also to the conclusion that, contrary to common
belief, a constant quasi-Fermi level does not necessarily ensure zero
electrical current. While we revisit the drift diffusion process in the context
of degenerate hopping systems, a considerable part of the argumentation put
forward can be applied generally to degenerate systems.


  We study the tunneling behavior of Dirac fermions in graphene subjected to a
double barrier potential profile created by spatially overlapping laser fields.
By modulating the graphene sheet with an oscillating structure formed from two
laser barriers, we aim to understand how the transmission of Dirac fermions is
influenced by such a light-induced electric potential landscape. Using the
Floquet method, we determine the eigenspinors of the five regions defined by
the barriers applied to the graphene sheet. Applying the continuity of the
eigenspinors at barrier edges and using the transfer matrix method, we
establish the transmission coefficients. These allow us to show that
oscillating laser fields generate multiple transmission modes, including
zero-photon transmission aligned with the central band $\varepsilon$ and
photon-assisted transmission at sidebands $\varepsilon+ l\varpi$, with
$l=0,\pm1, \cdots$ and frequency $\varpi$. For numerical purposes, our
attention is specifically directed towards transmissions related to zero-photon
processes ($l=0$), along with processes involving photon emission ($l=1$) and
absorption ($l=-1$). We find that transmission occurs only when the incident
energy is above the threshold energy $\varepsilon>k_y+2\varpi$, {with
transverse wave vector $k_y$}. We find that the variation in distance {$d_1$
separating two barriers of widths $d_2-d_1$} suppresses one transmission mode.
Additionally, we show that an increase in laser intensity modifies transmission
sharpness and amplitude.


  In this paper we consider extensions of the super Virasoro algebra by one and
two super primary fields. Using a non-explicitly covariant approach we compute
all SW-algebras with one generator of dimension up to 7 in addition to the
super Virasoro field. In complete analogy to W-algebras with two generators
most results can be classified using the representation theory of the super
Virasoro algebra. Furthermore, we find that the SW(3/2, 11/2)-algebra can be
realized as a subalgebra of SW(3/2, 5/2) at c = 10/7. We also construct some
new SW-algebras with three generators, namely SW(3/2, 3/2, 5/2), SW(3/2, 2, 2)
and SW(3/2, 2, 5/2).


  We prove that the dimension of the arity $n$ component of the operad of dual
alternative algebras over a field of characteristic three is equal to $2^n-n$,
and describe the structure of the corresponding $S_n$-module.


  We consider the problem of olfactory searches in a turbulent environment. We
focus on agents that respond solely to odor stimuli, with no access to spatial
perception nor prior information about the odor location. We ask whether
navigation strategies to a target can be learned robustly within a sequential
decision making framework. We develop a reinforcement learning algorithm using
a small set of interpretable olfactory states and train it with realistic
turbulent odor cues. By introducing a temporal memory, we demonstrate that two
salient features of odor traces, discretized in few olfactory states, are
sufficient to learn navigation in a realistic odor plume. Performance is
dictated by the sparse nature of turbulent plumes. An optimal memory exists
which ignores blanks within the plume and activates a recovery strategy outside
the plume. We obtain the best performance by letting agents learn their
recovery strategy and show that it is mostly casting cross wind, similar to
behavior observed in flying insects. The optimal strategy is robust to
substantial changes in the odor plumes, suggesting minor parameter tuning may
be sufficient to adapt to different environments.


  Causal relationships among variables are commonly represented via directed
acyclic graphs. There are many methods in the literature to quantify the
strength of arrows in a causal acyclic graph. These methods, however, have
undesirable properties when the causal system represented by a directed acyclic
graph is degenerate. In this paper, we characterize a degenerate causal system
using multiplicity of Markov boundaries. We show that in this case, it is
impossible to find an identifiable quantitative measure of causal effects that
satisfy a set of natural criteria. To supplement the impossibility result, we
also develop algorithms to identify degenerate causal systems from observed
data. Performance of our algorithms is investigated through synthetic data
analysis.


  This paper presents a novel approach to Multi-Agent Reinforcement Learning
(MARL) that combines cooperative task decomposition with the learning of reward
machines (RMs) encoding the structure of the sub-tasks. The proposed method
helps deal with the non-Markovian nature of the rewards in partially observable
environments and improves the interpretability of the learnt policies required
to complete the cooperative task. The RMs associated with each sub-task are
learnt in a decentralised manner and then used to guide the behaviour of each
agent. By doing so, the complexity of a cooperative multi-agent problem is
reduced, allowing for more effective learning. The results suggest that our
approach is a promising direction for future research in MARL, especially in
complex environments with large state spaces and multiple agents.


  A novel model of intermittency is presented in which the dynamics of the
rates of energy transfer between successive steps in the energy cascade is
described by a hierarchy of stochastic differential equations. The probability
distribution of velocity increments is calculated explicitly and expressed in
terms of generalized hypergeometric functions of the type ${_n}F_0$, which
exhibit power-law tails. The model predictions are found to be in good
agreement with experiments on a low temperature gaseous helium jet. It is
argued that distributions based on the functions ${_n}F_0$ might be relevant
also for other physical systems with multiscale dynamics.


  Global warming is one of the main threats to the future of humanity and
extensive emissions of greenhouse gases are found to be the main cause of
global temperature rise as well as climate change. During the last decades
international attention has focused on this issue, as well as on searching for
viable solutions to mitigate global warming. In this context, the pricing of
greenhouse gas emissions turned out to be the most prominent mechanism: First,
to lower the emissions, and second, to capture their external costs. By now,
various carbon dioxide taxes have been adopted by several countries in Europe
and around the world; moreover, the list of these countries is growing.
However, there is no standardized approach and the price for carbon varies
significantly from one country to another. Regionally diversified carbon prices
in turn lead to carbon leakage, which will offset the climate protection goals.
In this paper, a simplified European power system with flexible carbon prices
regarding the Gross Domestic Product (GDP) is investigated. A distribution
parameter that quantifies carbon leakage is defined and varied together with
the base carbon price, where the combination of both parameters describes the
spatially resolved price distribution, i.e. the effective carbon pricing among
the European regions. It is shown that inhomogeneous carbon prices will indeed
lead to significant carbon leakage across the continent, and that coal-fired
electricity generation will remain a cheap and therefore major source of power
in Eastern and South-Eastern Europe - representing a potential risk for the
long term decarbonization targets within the European Union.


  We prove that the extended Khovanov arc algebras are isomorphic to the basic
algebras of anti-spherical Hecke categories for maximal parabolics of symmetric
groups. We present these algebras by quiver and relations and provide the full
submodule lattices of Verma modules.


  We investigate entanglement mediated by DC current induced nonreciprocal
graphene plasmon polaritons. Nonreciprocal systems are ideal for the
enhancement, control, and preservation of entanglement due to the potential for
unidirectional beam-like wave propagation, i.e., efficiently transporting
photons from one emitter to another. Using a quantum master equation and
three-dimensional Green's function analysis, we investigate a system consisting
of two two-level emitters dominantly interacting via electric current induced
nonreciprocal plasmonic modes of a graphene waveguide. We use concurrence as a
measure of entanglement. We show that nonreciprocal graphene plasmon polaritons
are a promising candidate to generate and mediate concurrence, where it is
shown that there is good enhancement and control of entanglement over vacuum,
which is beneficial for the broad applications of entanglement as a quantum
resource. We believe our findings contribute to the development of quantum
devices, enabling efficient and tunable entanglement between two-level systems,
which is a central goal in quantum technologies.


  We show that perturbing the definition of sl(n) Khovanov-Rozansky link
homology gives a lower bound on the slice genus of a knot. As a corollary this
yields another proof of Milnor's conjecture on the slice genus of torus knots.


  In this note I expand further on the main assumptions leading to the
consistent-amplitude approach to quantum theory and I offer a reply to Jerry
Finkelstein's recent comment (quant-ph/9809017) concerning my argument for the
linearity of quantum mechanics (Phys. Rev. A57, 1572 (1998)).


  We report on a series of experiments with convolutional neural networks (CNN)
trained on top of pre-trained word vectors for sentence-level classification
tasks. We show that a simple CNN with little hyperparameter tuning and static
vectors achieves excellent results on multiple benchmarks. Learning
task-specific vectors through fine-tuning offers further gains in performance.
We additionally propose a simple modification to the architecture to allow for
the use of both task-specific and static vectors. The CNN models discussed
herein improve upon the state of the art on 4 out of 7 tasks, which include
sentiment analysis and question classification.


  A derivation of the optical axis lenght fluctations due by tilts of the
mirrors of the Fabry-Perot cavity of long-baseline interferometers for the
detection of gravitational waves in presence of the gravitational field of the
earth is discussed. By comparing with the typical tilt-induced noises it is
shown that this potential signal, which is considered a weak source of noise,
is negligible for the first generation of gravitational waves interferometers,
but, in principle, this effect could be used for high precision measures of the
gravitational acceleration if advanced projects will achieve an high
sensitivity. In that case the precision of the misure could be higher than the
gravimeter realized by the Istituto di Metrologia ``Gustavo Colonnetti''.


  Brain-computer interfaces (BCIs) and their associated technologies have the
potential to shape future forms of communication, control, and security.
Specifically, the steady-state visual evoked potential (SSVEP) based BCIs have
the advantages of better recognition accuracy, and higher information transfer
rate (ITR) compared to other BCI modalities. To fully exploit the capabilities
of such devices, it is necessary to understand the underlying biological
features of SSVEPs and design the system considering their inherent
characteristics. This paper introduces bio-inspired filter banks (BIFBs) for
improved SSVEP frequency recognition. SSVEPs are frequency selective,
subject-specific, and their power gets weaker as the frequency of the visual
stimuli increases. Therefore, the gain and bandwidth of the filters are
designed and tuned based on these characteristics while also incorporating
harmonic SSVEP responses. The BIFBs are utilized in the feature extraction
stage to increase the separability of classes. This method not only improves
the recognition accuracy but also increases the total number of available
commands in a BCI system by allowing the use of stimuli frequencies that elicit
weak SSVEP responses. The BIFBs are promising particularly in the
high-frequency band, which causes less visual fatigue. Hence, the proposed
approach might enhance user comfort as well. The BIFB method is tested on two
online benchmark datasets and outperforms the compared methods. The results
show the potential of bio-inspired design, and the findings will be extended by
including further SSVEP characteristics for future SSVEP based BCIs.


  We present a new process for fabricating vertical NbN-MgO-NbN Josephson
junctions using self-aligned silicon nitride spacers. It allows for a wide
range of junction areas from 0.02 um^2 to several 100 um^2. At the same time,
it is suited for the implementation of complex microwave circuits with
transmission line impedances ranging from < 1 Ohm to > 1 kOhm. The constituent
thin films and the finished junctions are characterized. The latter are shown
to have high gap voltages (> 4 mV) and low sub-gap leakage currents.


  We show that final state interactions (FSI) within a CPT invariant
two-channel framework can enhance the charge-parity (CP) violation difference
between $D^0\to\pi^-\pi^+$ and $D^0\to K^-K^+$ decays up to the current
experimental value. This result relies upon: (i) the dominant tree level
diagram, (ii) the well-known experimental values for the $D^ 0\to\pi^-\pi^+$
and $D^ 0\to K^-K^+$ branching ratios, and (iii) the $\pi\pi \to \pi\pi$ and
$\pi\pi \to K K $ scattering data to extract the strong phase difference and
inelasticity. Based on well-grounded theoretical properties, we find the sign
and bulk value of the $\Delta A_{CP}$ and $A_{CP}(D^0 \to \pi^-\pi^+)$ recently
observed by the LHCb Collaboration.


  Photometric measurements of the contact binary system CK Aqr are presented.
49 new times of minimum were obtained between 2005 and 2020. Along with already
published observations, this allows the derivation of an improved ephemeris.
The resulting O-C diagram shows oscillations which are interpreted as the light
time travel effect due to a third component, with a period of 8.2 years.


  We investigate the probe holographic fermions by using an anisotropic charged
black brane solution. We derive the equation of motion of probe bulk fermions
with one Fermi momentum along the anisotropic and one along the isotropic
directions. We then numerically solve the equation and analyze the properties
of Green function with these two momentums. We find in this case the shape of
Fermi surface is anisotropic. However, for both Fermi momentums perpendicular
to the anisotropic direction, the Fermi surface is isotropic. We verify that
our system obeys the recently conjectured bound for thermoelectric diffusion
constants for the stable branch of the black brane solutions.


  We have developed an electron-tracking Compton camera (ETCC) for use in
next-generation MeV gamma ray telescopes. An ETCC consists of a gaseous time
projection chamber (TPC) and pixel scintillator arrays (PSAs). Since the TPC
measures the three dimensional tracks of Compton-recoil electrons, the ETCC can
completely reconstruct the incident gamma rays. Moreover, the ETCC demonstrates
efficient background rejection power in Compton-kinematics tests, identifies
particle from the energy deposit rate (dE/dX) registered in the TPC, and
provides high quality imaging by completely reconstructing the Compton
scattering process. We are planning the "Sub-MeV gamma ray Imaging
Loaded-on-balloon Experiment" (SMILE) for our proposed all-sky survey
satellite. Performance tests of a mid-sized 30 cm-cubic ETCC, constructed for
observing the Crab nebula, are ongoing. However, observations at balloon
altitudes or satellite orbits are obstructed by radiation background from the
atmosphere and the detector itself. The background rejection power was checked
using proton accelerator experiments conducted at the Research Center for
Nuclear Physics, Osaka University. To create the intense radiation fields
encountered in space, which comprise gamma rays, neutrons, protons, and other
energetic entities, we irradiated a water target with a 140 MeV proton beam and
placed a SMILE-II ETCC near the target. In this situation, the counting rate
was five times than that expected at the balloon altitude. Nonetheless, the
ETCC stably operated and identified particles sufficiently to obtain a clear
gamma ray image of the checking source. Here, we report the performance of our
detector and demonstrate its effective background rejection based in electron
tracking experiments.


  The ESO Public Survey Southern H-ATLAS Regions Ks-band Survey (SHARKS)
comprises 300 square degrees of deep imaging at 2.2 microns (the Ks band) with
the VISTA InfraRed CAMera (VIRCAM) at the 4-metre Visible and Infrared Survey
Telescope for Astronomy (VISTA). The first data release of the survey,
comprising 5% of the data, was published via the ESO database on 31 January
2022. We describe the strategy and status of the first data release and present
the data products. We discuss briefly different scientific areas being explored
with the SHARKS data and conclude with an outline of planned data releases.


  Several text-to-video diffusion models have demonstrated commendable
capabilities in synthesizing high-quality video content. However, it remains a
formidable challenge pertaining to maintaining temporal consistency and
ensuring action smoothness throughout the generated sequences. In this paper,
we present an innovative video generation AI agent that harnesses the power of
Sora-inspired multimodal learning to build skilled world models framework based
on textual prompts and accompanying images. The framework includes two parts:
prompt enhancer and full video translation. The first part employs the
capabilities of ChatGPT to meticulously distill and proactively construct
precise prompts for each subsequent step, thereby guaranteeing the utmost
accuracy in prompt communication and accurate execution in following model
operations. The second part employ compatible with existing advanced diffusion
techniques to expansively generate and refine the key frame at the conclusion
of a video. Then we can expertly harness the power of leading and trailing key
frames to craft videos with enhanced temporal consistency and action
smoothness. The experimental results confirm that our method has strong
effectiveness and novelty in constructing world models from text and image
inputs over the other methods.


  Kernel methods have been proven to be a powerful tool for the integration and
analysis of highthroughput technologies generated data. Kernels offer a
nonlinear version of any linear algorithm solely based on dot products. The
kernelized version of Principal Component Analysis is a valid nonlinear
alternative to tackle the nonlinearity of biological sample spaces. This paper
proposes a novel methodology to obtain a data-driven feature importance based
on the KPCA representation of the data. The proposed method, kernel PCA
Interpretable Gradient (KPCA-IG), provides a datadriven feature importance that
is computationally fast and based solely on linear algebra calculations. It has
been compared with existing methods on three benchmark datasets. The accuracy
obtained using KPCA-IG selected features is equal to or greater than the other
methods' average. Also, the computational complexity required demonstrates the
high efficiency of the method. An exhaustive literature search has been
conducted on the selected genes from a publicly available Hepatocellular
carcinoma dataset to validate the retained features from a biological point of
view. The results once again remark on the appropriateness of the computed
ranking. The black-box nature of kernel PCA needs new methods to interpret the
original features. Our proposed methodology KPCA-IG proved to be a valid
alternative to select influential variables in high-dimensional high-throughput
datasets, potentially unravelling new biological and medical biomarkers.


  Advanced motor skills are essential for robots to physically coexist with
humans. Much research on robot dynamics and control has achieved success on
hyper robot motor capabilities, but mostly through heavily case-specific
engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous
manner, robot learning from human demonstration (LfD) has achieved great
progress, but still has limitations handling dynamic skills and compound
actions. In this paper, we present a composite learning scheme which goes
beyond LfD and integrates robot learning from human definition, demonstration,
and evaluation. The method tackles advanced motor skills that require dynamic
time-critical maneuver, complex contact control, and handling partly soft
partly rigid objects. We also introduce the "nunchaku flipping challenge", an
extreme test that puts hard requirements to all these three aspects. Continued
from our previous presentations, this paper introduces the latest update of the
composite learning scheme and the physical success of the nunchaku flipping
challenge.


  Recently, the concept of spread complexity, Krylov complexity for states, has
been introduced as a measure of the complexity and chaoticity of quantum
systems. In this paper, we study the spread complexity of the thermofield
double state within \emph{integrable} systems that exhibit saddle-dominated
scrambling. Specifically, we focus on the Lipkin-Meshkov-Glick model and the
inverted harmonic oscillator as representative examples of quantum mechanical
systems featuring saddle-dominated scrambling. Applying the Lanczos algorithm,
our numerical investigation reveals that the spread complexity in these systems
exhibits features reminiscent of \emph{chaotic} systems, displaying a
distinctive ramp-peak-slope-plateau pattern. Our results indicate that,
although spread complexity serves as a valuable probe, accurately diagnosing
true quantum chaos generally necessitates additional physical input. We also
explore the relationship between spread complexity, the spectral form factor,
and the transition probability within the Krylov space. We provide analytical
confirmation of our numerical results, validating the Ehrenfest theorem of
complexity and identifying a distinct quadratic behavior in the early-time
regime of spread complexity.


  Stochastic field equations represent a powerful tool to describe the thermal
state of a trapped Bose gas. Often, such approaches are confronted with the old
problem of an ultraviolet catastrophe, which demands a cutoff at high energies.
In [arXiv:0809.1002, Phys. B 42, 081001 (2009)] we introduce a quantum
stochastic field equation, avoiding the cutoff problem through a fully quantum
approach based on the Glauber-Sudarshan P-function. For a close link to actual
experimental setups the theory is formulated for a fixed particle number and
thus based on the canonical ensemble. In this work the derivation and the
non-trivial numerical implementation of the equation is explained in detail. We
present applications for finite Bose gases trapped in a variety of potentials
and show results for ground state occupation numbers and their equilibrium
fluctuations. Moreover, we investigate spatial coherence properties by studying
correlation functions of various orders.


  The magnetic domain structure and magnetic properties of a ferromagnetic
(Ga,Mn)As epilayer with perpendicular magnetic easy-axis are investigated. We
show that, despite strong hysteresis, domain theory at thermodynamical
equilibrium can be used to determine the micromagnetic parameters. Combining
magneto-optical Kerr microscopy, magnetometry and ferromagnetic resonance
measurements, we obtain the characteristic parameter for magnetic domains
$\lambda_c$, the domain wall width and specific energy, and the spin stiffness
constant as a function of temperature. The nucleation barrier for magnetization
reversal and the Walker breakdown velocity for field-driven domain wall
propagation are also estimated.


  The tau-lepton plays an important role in the physics program at the Large
Hadron Collider (LHC). It offers a probe in searches for New Physics and to
measure parameters of the Standard Model. Spin of tau lepton is an interesting
phenomenological quantity for separation of signal from background or in
measuring properties of particles. A proper treatment of tau spin effects in
the Monte Carlo simulations is important for understanding the detector
acceptance as well as for the measurements/use of tau polarization and tau spin
correlations. The TauSpinner is a tool to modify tau$spin effects in any
sample. Also production matrix elements can be modified with its help. The
general principle of TauSpinner algorithm rely on the kinematic of outgoing
particles (or jets) only, and to average over all possible initial states
accordingly to assumed parton distributions and cross-sections. Incoming on
mass-shell parton four-momenta are reconstructed in approximation, but
energy-momentum conservation is obeyed. Samples of events featuring tau leptons
with their decay products, can be used as an input. The information on the
polarization and spin correlations, and production/decay matrix elements is
reconstructed from the kinematics of the tau lepton(s) (also nu_tau in case of
W-mediated processes) and tau decay products (also jets). No other information
is required. By calculating spin (or production/decay matrix element) weights,
attributed to each event, it enables evaluation of modifications without
regenerating events.
  Elements of program functionalities together with explanation of the use are
given in Appendices. Present publication collect program documentation,
previously scattered over several publiications.


  Let $\{X_i\}$ be a sequence of independent identically distributed random
variables with an intermediate regularly varying (IR) right tail $\bar{F}$. Let
$(N, C_1, ..., C_N)$ be a nonnegative random vector independent of the
$\{X_i\}$ with $N \in \mathbb{N} \cup \{\infty\}$. We study the weighted random
sum $S_N = \sum_{i=1}^N C_i X_i$, and its maximum, $M_N = \sup_{1 \leq k < N+1}
\sum_{i=1}^k C_i X_i$. These type of sums appear in the analysis of stochastic
recursions, including weighted branching processes and autoregressive
processes. In particular, we derive conditions under which $$P(M_N > x) \sim
P(S_N > x) \sim E[\sum_{i=1}^N \bar{F}(x/C_i)],$$ as $x \to \infty$. When
$E[X_1] > 0$ and the distribution of $Z_N = \sum_{i=1}^N C_i$ is also IR, we
obtain the asymptotics $$P(M_N > x) \sim P(S_N > x) \sim E[\sum_{i=1}^N
\bar{F}(x/C_i)] + P(Z_N > x/E[X_1]).$$ For completeness, when the distribution
of $Z_N$ is IR and heavier than $\bar{F}$, we also obtain conditions under
which the asymptotic relations $$P(M_N > x) \sim P(S_N > x) \sim P(Z_N >
x/E[X_1])$$ hold.


  We present a novel spontaneous collapse model where size is no longer the
property of a physical system which determines its rate of collapse. Instead,
we argue that the rate of spontaneous localization should depend on a system's
quantum Integrated Information (QII), a novel physical property which describes
a system's capacity to act like a quantum observer. We introduce quantum
Integrated Information, present our QII collapse model and briefly explain how
it may be experimentally tested against quantum theory.


  For the past decade, the BICEP/Keck collaboration has been operating a series
of telescopes at the Amundsen-Scott South Pole Station measuring degree-scale
$B$-mode polarization imprinted in the Cosmic Microwave Background (CMB) by
primordial gravitational waves (PGWs). These telescopes are compact refracting
polarimeters mapping about 2% of the sky, observing at a broad range of
frequencies to account for the polarized foreground from Galactic synchrotron
and thermal dust emission. Our latest publication "BK18" utilizes the data
collected up to the 2018 observing season, in conjunction with the publicly
available WMAP and Planck data, to constrain the tensor-to-scalar ratio $r$. It
particularly includes (1) the 3-year BICEP3 data which is the current deepest
CMB polarization map at the foreground-minimum 95 GHz; and (2) the Keck 220 GHz
map with a higher signal-to-noise ratio on the dust foreground than the Planck
353 GHz map. We fit the auto- and cross-spectra of these maps to a
multicomponent likelihood model ($\Lambda$CDM+dust+synchrotron+noise+$r$) and
find it to be an adequate description of the data at the current noise level.
The likelihood analysis yields $\sigma(r)=0.009$. The inference of $r$ from our
baseline model is tightened to $r_{0.05}=0.014^{+0.010}_{-0.011}$ and
$r_{0.05}<0.036$ at 95% confidence, meaning that the BICEP/Keck $B$-mode data
is the most powerful existing dataset for the constraint of PGWs. The up-coming
BICEP Array telescope is projected to reach $\sigma(r) \lesssim 0.003$ using
data up to 2027.


  This paper proposes a learning strategy that extracts object-part concepts
from a pre-trained convolutional neural network (CNN), in an attempt to 1)
explore explicit semantics hidden in CNN units and 2) gradually grow a
semantically interpretable graphical model on the pre-trained CNN for
hierarchical object understanding. Given part annotations on very few (e.g.,
3-12) objects, our method mines certain latent patterns from the pre-trained
CNN and associates them with different semantic parts. We use a four-layer
And-Or graph to organize the mined latent patterns, so as to clarify their
internal semantic hierarchy. Our method is guided by a small number of part
annotations, and it achieves superior performance (about 13%-107% improvement)
in part center prediction on the PASCAL VOC and ImageNet datasets.


  A (2+1)-dimensional linear ultra-parabolic Fokker--Planck--Kolmogorov
equation is investigated from the group-theoretical point of view. By using the
Berest--Aksenov approach, an algebra of invariance of fundamental solutions of
the equation is found. A fundamental solution of the equation under study is
computed in an explicit form as a weak invariant solution.


  Based on the analysis of approaches to the definition of professional
competencies of IT students the competence in programming of bachelor of
informatics is proposed. Due to the standard of training in 040302
"Informatics" and Computing Curricula 2001 it was defined the content and
structure of the competence in programming of bachelor of informatics. The
system of content modules providing its formation was designed. The
contribution of regulatory competencies of bachelor of informatics in the
formation of competence in programming is defined. The directions of formation
of competence in programming in the cloudy-oriented learning environment are
proposed.


  The stochastic expansion of the marginal quasi-likelihood function associated
with a class of generalized linear models is shown. Based on the expansion, a
quasi-Bayesian information criterion is proposed that is able to deal with
misspecified models and dependent data, resulting in a theoretical extension of
the classical Schwarz's Bayesian information criterion. It is also proved that
the proposed criterion has model selection consistency with respect to the
optimal model. Some illustrative numerical examples and a real data example are
presented.


  In the digital era, the prevalence of depressive symptoms expressed on social
media has raised serious concerns, necessitating advanced methodologies for
timely detection. This paper addresses the challenge of interpretable
depression detection by proposing a novel methodology that effectively combines
Large Language Models (LLMs) with eXplainable Artificial Intelligence (XAI) and
conversational agents like ChatGPT. In our methodology, explanations are
achieved by integrating BERTweet, a Twitter-specific variant of BERT, into a
novel self-explanatory model, namely BERT-XDD, capable of providing both
classification and explanations via masked attention. The interpretability is
further enhanced using ChatGPT to transform technical explanations into
human-readable commentaries. By introducing an effective and modular approach
for interpretable depression detection, our methodology can contribute to the
development of socially responsible digital platforms, fostering early
intervention and support for mental health challenges under the guidance of
qualified healthcare professionals.


  The real challenge in drone-logistics is to develop an economically-feasible
Unmanned Aerial Mobility Network (UAMN). In this paper, we propose an
integrated airport location (strategic decision) and routes planning
(operational decision) optimization framework to minimize the total cost of the
network, while guaranteeing flow constraints, capacity constraints, and
electricity constraints. To facility expensive long-term infrastructure
planning facing demand uncertainty, we develop a data-driven risk-averse
two-stage stochastic optimization model based on the Wasserstein distance. We
develop a reformulation technique which simplifies the worst-case expectation
term in the original model, and obtain a fractable Min-Max solution procedure
correspondingly. Using Lagrange multipliers, we successfully decompose decision
variables and reduce the complexity of computation. To provide managerial
insights, we design specific numerical examples. For example, we find that the
optimal network configuration is affected by the "pooling effects" in channel
capacities. A nice feature of our DRO framework is that the optimal network
design is relatively robust under demand uncertainty. Interestingly, a
candidate node without historical demand records can be chosen to locate an
airport. We demonstrate the application of our model for a real medical
resources transportation problem with our industry partner, collecting donated
blood to a blood bank in Hangzhou, China.


  The standard model of cosmology is dominated - at the present epoch - by dark
energy. Its voids are rigid and Newtonian within a relativistic background. The
model prevents them from becoming hyperbolic. Observations of rapid velocity
flows out of voids are normally interpreted within the standard model that is
rigid in comoving coordinates, instead of allowing the voids' density parameter
to drop below critical and their curvature to become negative. Isn't it time to
advance beyond nineteenth century physics and relegate dark energy back to the
"no significant evidence" box?


  We study the chiral condensate $<\bar{\psi} \psi>$ for an SU(3) gauge theory
with $N_f$ massless Dirac fermions in the fundamental representation when $N_f$
is increased from 2 to 6. For $N_f=2$, our lattice simulations of $<\bar{\psi}
\psi >/F^3$, where $F$ is the Nambu-Goldstone-boson decay constant, agree with
the measured QCD value. For $N_f = 6$, this ratio shows significant
enhancement, presaging an even larger enhancement anticipated as $N_f$
increases further, toward the critical value for transition from confinement to
infrared conformality.


  In the paper the asymptotic bifurcation of solutions to a parameterized
stationary semilinear Schr\"odinger equation involving a potential of the
Kato-Rellich type is studied. It is shown that the bifurcation from infinity
occurs if the parameter is an eigenvalue of the hamiltonian lying below the
asymptotic bottom of the bounded part of the potential. Thus the bifurcating
solution are related to bound states of the corresponding Schr\"odinger
equation. The argument relies on the use of the (generalized) Conley index due
to Rybakowski and resonance assumptions of the Landesman-Lazer or
sign-condition type.