  We use finite-size scaling to investigate the critical behavior of the
quasiespecies model of molecular evolution in the single-sharp-peak replication
landscape. This model exhibits a sharp threshold phenomenon at Q=Q_c=1/a, where
Q is the probability of exact replication of a molecule of length L and a is
the selective advantage of the master string.
  We investigate the sharpness of the threshold and find that its
characteristic persist across a range of Q of order L^(-1) about Q_c.
Furthermore, using the data collapsing method we show that the normalized mean
Hamming distance between the master string and the entire population, as well
as the properly scaled fluctuations around this mean value, follow universal
forms in the critical region.


  Despite the remarkable performance of Large Language Models (LLMs), they
still struggle with generating logically sound arguments, resulting in
potential risks such as spreading misinformation. An important factor
contributing to LLMs' suboptimal performance in generating coherent arguments
is their oversight of logical fallacies. To address this issue, we introduce
FIPO, a fallacy-informed framework that leverages preference optimization
methods to steer LLMs toward logically sound arguments. FIPO includes a
classification loss, to capture the fine-grained information on fallacy
categories. Our results on argumentation datasets show that our method reduces
the fallacy errors by up to 17.5%. Furthermore, our human evaluation results
indicate that the quality of the generated arguments by our method
significantly outperforms the fine-tuned baselines, as well as prior preference
optimization methods, such as DPO. These findings highlight the importance of
ensuring models are aware of logical fallacies for effective argument
generation.


  If a quantum system is prepared and later post-selected in certain states,
"paradoxical" predictions for intermediate measurements can be obtained. This
is the case both when the intermediate measurement is strong, i.e. a projective
measurement with Luders-von Neumann update rule, or with weak measurements
where they show up in anomalous weak values. Leifer and Spekkens
[quant-ph/0412178] identified a striking class of such paradoxes, known as
logical pre- and post-selection paradoxes, and showed that they are indirectly
connected with contextuality. By analysing the measurement-disturbance required
in models of these phenomena, we find that the strong measurement version of
logical pre- and post-selection paradoxes actually constitute a direct
manifestation of quantum contextuality. The proof hinges on under-appreciated
features of the paradoxes. In particular, we show by example that it is not
possible to prove contextuality without Luders-von Neumann updates for the
intermediate measurements, nonorthogonal pre- and post-selection, and 0/1
probabilities for the intermediate measurements. Since one of us has recently
shown that anomalous weak values are also a direct manifestation of
contextuality [arXiv:1409.1535], we now know that this is true for both
realizations of logical pre- and post-selection paradoxes.


  We present a new technique for calibrating the primary beam of a wide-field,
drift-scanning antenna element. Drift-scan observing is not compatible with
standard beam calibration routines, and the situation is further complicated by
difficult-to-parametrize beam shapes and, at low frequencies, the sparsity of
accurate source spectra to use as calibrators. We overcome these challenges by
building up an interrelated network of source "crossing points" -- locations
where the primary beam is sampled by multiple sources. Using the single
assumption that a beam has 180 degree rotational symmetry, we can achieve
significant beam coverage with only a few tens of sources. The resulting
network of crossing points allows us to solve for both a beam model and source
flux densities referenced to a single calibrator source, circumventing the need
for a large sample of well-characterized calibrators. We illustrate the method
with actual and simulated observations from the Precision Array for Probing the
Epoch of Reionization (PAPER).


  Video grounding aims to localize a spatio-temporal section in a video
corresponding to an input text query. This paper addresses a critical
limitation in current video grounding methodologies by introducing an
Open-Vocabulary Spatio-Temporal Video Grounding task. Unlike prevalent
closed-set approaches that struggle with open-vocabulary scenarios due to
limited training data and predefined vocabularies, our model leverages
pre-trained representations from foundational spatial grounding models. This
empowers it to effectively bridge the semantic gap between natural language and
diverse visual content, achieving strong performance in closed-set and
open-vocabulary settings. Our contributions include a novel spatio-temporal
video grounding model, surpassing state-of-the-art results in closed-set
evaluations on multiple datasets and demonstrating superior performance in
open-vocabulary scenarios. Notably, the proposed model outperforms
state-of-the-art methods in closed-set settings on VidSTG (Declarative and
Interrogative) and HC-STVG (V1 and V2) datasets. Furthermore, in
open-vocabulary evaluations on HC-STVG V1 and YouCook-Interactions, our model
surpasses the recent best-performing models by $4.88$ m_vIoU and $1.83\%$
accuracy, demonstrating its efficacy in handling diverse linguistic and visual
concepts for improved video understanding. Our codes will be publicly released.


  The investigation of interactions between magnetic nanotubes is complex and
often involves substantial simplifications. In this letter an analytical
expression for the magnetostatic interaction, taking into account the geometry
of the tubes, has been obtained. This expression allows for the definition of a
critical vertical separation for relative magnetization between nanotubes and
can be used for tailoring barcode-type nanostructures with prospective
applications such as biological separation and transport.


  In order theory, a rank function measures the vertical "level" of a poset
element. It is an integer-valued function on a poset which increments with the
covering relation, and is only available on a graded poset. Defining a vertical
measure to an arbitrary finite poset can be accomplished by extending a rank
function to be interval-valued. This establishes an order homomorphism from a
base poset to a poset over real intervals, and a standard (canonical) specific
interval rank function is available as an extreme case. Various ordering
relations are available over intervals, and we begin in this paper by
considering conjugate orders which "partition" the space of pairwise
comparisons of order elements. For us, these elements are real intervals, and
we consider the weak and subset interval orders as (near) conjugates. It is
also natural to ask about interval rank functions applied reflexively on
whatever poset of intervals we have chosen, and thereby a general iterative
strategy for interval ranks. We explore the convergence properties of standard
and conjugate interval ranks, and conclude with a discussion of the
experimental mathematics needed to support this work.


  We present here two standalone results from a forthcoming work on the
analysis of Markov chains using the representation theory of $S_n$. First, we
give explicit formulas for the decompositions of tensor powers of the defining
and standard representations of $S_n$. Secondly, we prove that any Markov chain
on $S_n$ starting with one fixed point and whose increment distributions are
class measures will always average exactly one fixed point.


  We study the model of a discrete directed polymer (DP) on the square lattice
with homogeneous inverse gamma distribution of site random Boltzmann weights,
introduced by Seppalainen. The integer moments of the partition sum,
$\overline{Z^n}$, are studied using a transfer matrix formulation, which
appears as a generalization of the Lieb-Liniger quantum mechanics of bosons to
discrete time and space. In the present case of the inverse gamma distribution
the model is integrable in terms of a coordinate Bethe Ansatz, as discovered by
Brunet. Using the Brunet-Bethe eigenstates we obtain an exact expression for
the integer moments of $\overline{Z^n}$ for polymers of arbitrary lengths and
fixed endpoint positions. Although these moments do not exist for all integer
n, we are nevertheless able to construct a generating function which reproduces
all existing integer moments, and which takes the form of a Fredholm
determinant (FD). This suggests an analytic continuation via a Mellin-Barnes
transform and we thereby propose a FD ansatz representation for the probability
distribution function (PDF) of $Z$ and its Laplace transform. In the limit of
very long DP, this ansatz yields that the distribution of the free energy
converges to the GUE Tracy-Widom distribution up to a non-trivial average and
variance that we calculate. Our asymptotic predictions coincide with a result
by Borodin et al. based on a formula obtained by Seppalainen using the gRSK
correspondence. In addition we obtain the dependence on the endpoint position
and the exact elastic coefficient at large time. We argue the equivalence
between our formula and the one of Borodin et al. As we discuss, this open the
way to explore the connections between quantum integrability and tropical
geometry.


  The probabilistic approach to turbulence is applied to investigate density
fluctuations in supersonic turbulence. We derive kinetic equations for the
probability distribution function (PDF) of the logarithm of the density field,
$s$, in compressible turbulence in two forms: a first-order partial
differential equation involving the average divergence conditioned on the flow
density, $\langle \nabla \cdot {\bs u} | s\rangle$, and a Fokker-Planck
equation with the drift and diffusion coefficients equal to $-\langle {\bs u}
\cdot \nabla s | s\rangle$ and $\langle {\bs u} \cdot \nabla s | s\rangle$,
respectively. Assuming statistical homogeneity only, the detailed balance at
steady state leads to two exact results, $\langle \nabla \cdot {\bs u} | s
\rangle =0$, and $\langle {\bs u} \cdot \nabla s | s\rangle=0$. The former
indicates a balance of the flow divergence over all expanding and contracting
regions at each given density. The exact results provide an objective criterion
to judge the accuracy of numerical codes with respect to the density statistics
in supersonic turbulence. We also present a method to estimate the effective
numerical diffusion as a function of the flow density and discuss its effects
on the shape of the density PDF.


  Radio frequency (RF) signals have facilitated the development of non-contact
human monitoring tasks, such as vital signs measurement, activity recognition,
and user identification. In some specific scenarios, an RF signal analysis
framework may prioritize the performance of one task over that of others. In
response to this requirement, we employ a multi-objective optimization approach
inspired by biological principles to select discriminative features that
enhance the accuracy of breathing patterns recognition while simultaneously
impeding the identification of individual users. This approach is validated
using a novel vital signs dataset consisting of 50 subjects engaged in four
distinct breathing patterns. Our findings indicate a remarkable result: a
substantial divergence in accuracy between breathing recognition and user
identification. As a complementary viewpoint, we present a contrariwise result
to maximize user identification accuracy and minimize the system's capacity for
breathing activity recognition.


  The aim of this paper is to estimate the irrationality of moduli spaces of
hyperk\"ahler manifolds of types K3$^{[n]}$, Kum$_{n}$, OG6, and OG10. We prove
that the degrees of irrationality of these moduli spaces are bounded from above
by a universal polynomial in the dimension and degree of the manifolds they
parametrize. We also give a polynomial bound for the degrees of irrationality
of moduli spaces of $(1,d)$-polarized abelian surfaces.


  The Chinese Space Station Telescope (CSST) spectroscopic survey aims to
deliver high-quality low-resolution ($R > 200$) slitless spectra for hundreds
of millions of targets down to a limiting magnitude of about 21 mag,
distributed within a large survey area (17500 deg$^2$) and covering a wide
wavelength range (255-1000 nm by 3 bands GU, GV, and GI). As slitless
spectroscopy precludes the usage of wavelength calibration lamps, wavelength
calibration is one of the most challenging issues in the reduction of slitless
spectra, yet it plays a key role in measuring precise radial velocities of
stars and redshifts of galaxies. In this work, we propose a star-based method
that can monitor and correct for possible errors in the CSST wavelength
calibration using normal scientific observations, taking advantage of the facts
that i) there are about ten million stars with reliable radial velocities now
available thanks to spectroscopic surveys like LAMOST, ii) the large field of
view of CSST enables efficient observations of such stars in a short period of
time, and iii) radial velocities of such stars can be reliably measured using
only a narrow segment of CSST spectra. We demonstrate that it is possible to
achieve a wavelength calibration precision of a few
$\mathrm{km}\,\mathrm{s}^{-1}$ for the GU band, and about 10 to 20
$\mathrm{km}\,\mathrm{s}^{-1}$ for the GV and GI bands, with only a few hundred
velocity standard stars. Implementations of the method to other surveys are
also discussed.


  Recent advances in the cryptographic field of "Zero-Knowledge Proofs" have
sparked a new wave of research, giving birth to many exciting theoretical
approaches in the last few years. Such research has often overlapped with the
need for private and scalable solutions of Blockchain-based communities,
resulting in the first practical implementations of such systems. Many of these
innovative constructions have developed in parallel, using different
terminologies and evolving into a fragmented ecosystem, calling for their
consolidation into the more stable domain of "Verifiable Computation". In this
master thesis I propose a unifying Verifiable Computation model for the
simplification and efficient comparison of all cryptographic proof systems. I
take advantage of this model to analyse innovative technologies (Homomorphic
Authenticators, Verifiable Delay Functions) which developed into their own
specialised domains, and I attempt to make them more accessible for newcomers
to the field. Furthermore, I expand on the future of Verifiable Computation,
Universal proof compilers and "Proofs of All", by approaching the
state-of-the-art zk-STARK construction from a more accessible and informal
design perspective.


  This article provides a formalization of the W3C Draft Core SHACL Semantics
specification using Z notation. This formalization exercise has identified a
number of quality issues in the draft. It has also established that the
recursive definitions in the draft are well-founded. Further formal validation
of the draft will require the use of an executable specification technology.


  We construct a self-consistent model for the wind around W Hya by solving the
coupled equations describing the hydrodynamics and dust radiative transfer
problems. The model matches simultaneously the observed continuum radiation and
wind velocity profile. The water line emission is calculated next using the
water abundance as the only free parameter, fitted from the ISO observations of
Neufeld et al. (1996) and Barlow et al. (1996). The gas temperature is
determined from a thermal balance calculation that includes water as one of its
main components. Our model successfully fits all the observed water lines,
resolving a major discrepancy between the modeling results of the two observing
teams. The mass loss rate is 2.3 x 10^{-6} M_solar yr^{-1}, the water abundance
is 1.0 x 10^{-4} and the ortho:para ratio is 1:1.3.


  Fourth-order tensor-valued functions appear in numerous fields of study. The
formulation of practical models for these complex functions often requires
their representation in terms of tensors of order two. In this paper, we
develop an appropriate representation formula by assuming that the isotropic
fourth--order tensor--valued function is a polynomial function in the
components of two symmetric second-order tensors of degree $\leq$ 2. We
illustrate the utility of the result by applying it to obtain a representation
of the fluctuating velocity, pressure-gradient correlations of turbulence.


  We consider SISI epidemic model with discrete-time. The crucial point of this
model is that an individual can be infected twice. This non-linear evolution
operator depends on seven parameters and we assume that the population size
under consideration is constant, so death rate is the same with birth rate per
unit time. Reducing to quadratic stochastic operator (QSO) we study the
dynamical system of the SISI model.


  We establish the existence of static and spherically symmetric fermion-boson
stars, in a low energy effective model of (beyond) Horndeski theories. These
stars are in equilibrium, and are composed by a mixing of scalar and fermionic
matters that only interact gravitationally one with each other. Properties such
as mass, radius, and compactness are studied, highlighting the existence of two
families of configurations defined by the parameter $c_4$. These families have
distinctive properties, although in certain limits both are reduced to their
counterparts in General Relativity. Finally, by assuming the same conditions
used in General Relativity, we find the maximum compactness of these hybrid
stars and determine that it remains below the so-called Buchdahl's limit.


  Single component pseudo-potential lattice Boltzmann models have been widely
studied due to their simplicity and stability in multiphase simulations. While
numerous model have been proposed, comparative analysis and advantages and
disadvantages of different force schemes is often lacking. A pseudo-potential
model to simulate large density ratios proposed by Kupershtokh et al. is
analyzed in detail in this work. Several common used force schemes are utilized
and results compared. Based on the numerical results, the relatively most
accurate force scheme proposed by Guo et al. is selected and applied to improve
the accuracy of Kupershtokh et al.'s model. Results obtained using the modified
Kupershtokh et al.'s model for different value of are compared with those
obtained using Li et al.'s model. Effect of relaxation time on the accuracy of
the results is reported. Moreover, it is noted that the error in the density
ratio predicted by the model is directly correlated with the magnitude of the
spurious velocities on (curved) interfaces. Simulation results show that, the
accuracy of Kupershtokh et al.'s model can be improved with Guo et al.'s force
scheme. However, the errors and relax time's effects are still noticeable when
density ratios are large. To improve the accuracy of the pseudo-potential model
and to reduce the effects of the relax time, two possible methods were
discussed in the present work . Both, a rescaling of the equation of state and
multi-relaxation time, are applied and are shown to improve the prediction
accuracy of the density ratios.


  We introduce neutrosophic choice functions, the neutrosophic counterpart of
the Axiom of Choice, prove some results, and discuss how it effects the
foundations of mathematics in a neutrosophic setting.


  We theoretically demonstrate soliton steering in $\mathcal{PT}$-symmetric
coupled nonlinear dimers. We show that if the length of the
$\mathcal{PT}$-symmetric system is set to $2\pi$ contrary to the conventional
one which operates satisfactorily well only at the half-beat coupling length,
the $\mathcal{PT}$ dimer remarkably yields an ideal soliton switch exhibiting
almost 99.99% energy efficiency with an ultra-low critical power.


  Quark-hadron duality addresses some of the most fundamental issues in strong
interaction physics, in particular the nature of the transition from the
perturbative to non-perturbative regions of QCD. I summarize recent
developments in quark-hadron duality in lepton-hadron scattering, and outline
how duality can be studied at future high-luminosity facilities such as
Jefferson Lab at 12 GeV, or an electron-hadron collider such as EPIC.


  Deep learning approaches have shown great success in image classification
tasks and can aid greatly towards the fast and reliable classification of
pollen grain aerial imagery. However, often-times deep learning methods in the
setting of natural images can suffer generalization problems and yield poor
performance on unseen test distribution. In this work, we present and a robust
deep learning framework that can generalize well for pollen grain
aerobiological imagery classification. We develop a convolutional neural
network-based pollen grain classification approach and combine some of the best
practices in deep learning for better generalization. In addition to
commonplace approaches like data-augmentation and weight regularization, we
utilize implicit regularization methods like manifold mixup to allow learning
of smoother decision boundaries. We also make use of proven state-of-the-art
architectural choices like EfficientNet convolutional neural networks. Inspired
by the success of generative modeling with variational autoencoders, we train
models with a richer learning objective which can allow the model to focus on
the relevant parts of the image. Finally, we create an ensemble of neural
networks, for the robustness of the test set predictions. Based on our
experiments, we show improved generalization performance as measured with a
weighted F1-score with the aforementioned approaches. The proposed approach
earned a fourth-place in the final rankings in the ICPR-2020 Pollen Grain
Classification Challenge; with a 0.972578 weighted F1 score,0.950828 macro
average F1 scores, and 0.972877 recognition accuracy.


  We present a class of photonic lattices with an underlying symmetry given by
a finite-dimensional representation of the 2+1D Lorentz group. In order to
construct such a finite-dimensional representation of a non-compact group, we
have to design a $\mathcal{PT}$-symmetric optical structure. Thus, the array of
coupled waveguides may keep or break $\mathcal{PT}$-symmetry, leading to a
device that behaves like an oscillator or directional amplifier, respectively.
We show that the so-called linear $\mathcal{PT}$-symmetric dimer belongs to
this class of photonic lattices.


  We theoretically investigate the macroscopic quantum dynamics of a pi
junction with a superconductor (S) and a multiferroic material or a
ferromagnetic insulator (FI). By deriving the effective action from a
microscopic Hamiltonian, a pi-junction qubit (a S-FI-S superconducting quantum
interference device ring) is proposed. In this qubit, a quantum two-level
system is spontaneously generated and the effect of the quasiparticle
dissipation is found to be very weak. These features make it possible to
realize a quiet qubit with high coherency. We also investigate macroscopic
quantum tunneling (MQT) in current-biased S-FI-S pi junctions and show that the
influence of the quasiparticle dissipation on MQT is negligibly small.


  There is a large body of legacy scientific code written in languages like
Fortran that is not optimised to get the best performance out of heterogeneous
acceleration devices like GPUs and FPGAs, and manually porting such code into
parallel languages frameworks like OpenCL requires considerable effort. We are
working towards developing a turn-key, self-optimising compiler for
accelerating scientific applications, that can automatically transform legacy
code into a solution for heterogeneous targets. In this paper we focus on FPGAs
as the acceleration devices, and carry out our discussion in the context of the
OpenCL programming framework. We show a route to automatic creation of kernels
which are optimised for execution in a "streaming" fashion, which gives optimal
performance on FPGAs. We use a 2D shallow-water model as an illustration;
specifically we show how the use of \emph{channels} to communicate directly
between peer kernels and the use of on-chip memory to create stencil buffers
can lead to significant performance improvements. Our results show better FPGA
performance against a baseline CPU implementation, and better energy-efficiency
against both CPU and GPU implementations.


  Astronomers have discovered that both planets and binaries are abundant
throughout the Galaxy. In combination, we know of over 100 planets in binary
and higher-order multi-star systems, in both circumbinary and circumstellar
configurations. In this chapter we review these findings and some of their
implications for the formation of both stars and planets. Most of the planets
found have been circumstellar, where there is seemingly a ruinous influence of
the second star if sufficiently close (<50 AU). Hosts of hot Jupiters have been
a particularly popular target for binary star studies, showing an enhanced rate
of stellar multiplicity for moderately wide binaries (>100 AU). This was
thought to be a sign of Kozai-Lidov migration, however recent studies have
shown this mechanism to be too inefficient to account for the majority of hot
Jupiters. A couple of dozen circumbinary planets have been proposed around both
main sequence and evolved binaries. Around main sequence binaries there are
preliminary indications that the frequency of gas giants is as high as those
around single stars. There is however a conspicuous absence of circumbinary
planets around the tightest main sequence binaries with periods of just a few
days, suggesting a unique, more disruptive formation history of such close
stellar pairs.


  We present all the publicly available data, from optical/UV wavelengths
(UVOT) to X-rays (XRT, BAT), obtained from Swift observations of the blazar PKS
2155-304, performed in response to the rapid alert sent out after the strong
TeV activity (up to 17 Crab flux level at E > 200 GeV) at the end of July 2006.
The X-ray flux increased by a factor of 5 in the 0.3-10 keV energy band and by
a factor of 1.5 at optical/UV wavelengths, with roughly one day of delay. The
comparison of the spectral energy distribution built with data
quasi-simultaneous to the TeV detections shows an increase of the overall
normalization with respect to archival data, but only a small shift of the
frequency of the synchrotron peak that remains consistent with the values
reported in past observations when the TeV activity was much weaker.


  In a viscoelastic flow over a microfluidic canopy of polymeric pillars, we
report the spontaneous emergence of waves in the form of propagating regions of
low flow velocity compared to the surrounding flow. The occurrence of the wave
is chaotic and shows characteristics of elastic turbulence. We systematically
study the coupling between the low velocity wave and the microfluidic canopy by
combining flow velocimetry experiments and high speed tracking of the pillars.
The waves form an angle $\beta$ with the primary flow direction that depends on
the geometry of the pillar array. If the canopy is composed of flexible
structures, the passage of a wave deflects the structures locally in a manner
reminiscent of the emergence of the Monami waves observed in inertial
turbulence over canopies of vegetation. Due to the analogies with classical
(inertial) canopy turbulence, we name our newly-observed phenomenon as canopy
elastic turbulence.


  A $k$-cyclic graph is a connected graph of order $n$ and size $n+k-1$. In
this paper, we determine the maximal signless Laplacian spectral radius and the
corresponding extremal graph among all $C_{4}$-free $k$-cyclic graphs of order
$n$. Furthermore, we determine the first three unicyclic, and bicyclic,
$C_{4}$-free graphs whose spectral radius of the signless Laplacian is maximal.
Similar results are obtained for the (combinatorial) Laplacian.


  We study and compute supersymmetric observables for line defects in 3d
$\mathcal{N}\ge4$ theories. Our setup is a novel supersymmetric configuration
involving line operators and local operators living on a linked circle. The
algebra of the local operators is described by a topological quantum mechanics.
For operators belonging to conserved current multiplets, we propose an exact
formula for their correlation functions based on a Ward identity for integrated
correlators. Our formula gives a general recipe to compute the bremsstrahlung
function for any $\frac{1}{3}$-BPS lines in $\mathcal{N}=6$ SCFTs. We apply our
relation to the $\frac{1}{2}$-BPS Wilson loop in the ABJM model, showing the
validity of previous computations. Furthermore, our construction allows us to
explore higher points correlators. As an example, we compute the two-point
function of the stress tensor multiplet correlators in ABJM theory in the
presence of the Wilson line. We also present some perturbative checks of our
formulae.


  We consider a system of two massive, mutually interacting probe real scalar
fields, in zero temperature holographic backgrounds. The system does not have
any continuous symmetry. For a suitable range of the interaction parameters
adhering to the interaction potential between the bulk scalars, we have shown
that as one turns on the source for one scalar field, the system may go through
a second order quantum critical phase transition across which the second scalar
field forms a condensate. We have looked at the resulting phase diagram and
numerically computed the condensate. We have also investigated our system in
two different backgrounds: $AdS_4$ and $AdS$ soliton, and got similar phase
structure.


  We study the space-time evolution of ``flavor'' neutrino wave-packets at
finite temperature and density in the early Universe prior to BBN. We implement
non-equilibrium field theory methods and linear response to study the
space-time evolution directly from the effective Dirac equation in the medium.
There is a rich hierarchy of time scales associated with transverse and
longitudinal dispersion and coherence. A phenomenon of ``freezing of
coherence'' is a result of a competition between longitudinal dispersion and
the separation of wave-packets of propagating modes in the medium. Near a
resonance the coherence and oscillation time scales are enhanced by a factor
$1/\sin2\theta$ compared to the vacuum. Collisional relaxation via charged and
neutral currents occurs on time scales much shorter than the coherence time
scale and for small vacuum mixing angle, shorter than the oscillation scale.
Assuming that the momentum spread of the initial wave packet is determined by
the large angle scattering mean free path of charged leptons, we find that the
transverse dispersion time scale is the shortest and is responsible for a large
suppression in both the survival and transition probabilities on time scales
much shorter than the Hubble time. For small mixing angle the oscillation time
scale is \emph{longer} than the collisional relaxation scale. The method also
yields the evolution of right-handed wave packets. Corrections to the
oscillation frequencies emerge from wave-packet structure as well as from the
energy dependence of mixing angles in the medium.


  The LiHo$_x$Y$_{1-x}$F$_4$ magnetic material in a transverse magnetic field
$B_{x}\hat x$ perpendicular to the Ising spin direction has long been used to
study tunable quantum phase transitions in a random disordered system. We show
that the $B_{x}-$induced magnetization along the $\hat x$ direction, combined
with the local random dilution-induced destruction of crystalline symmetries,
generates, via the predominant dipolar interactions between Ho$^{3+}$ ions,
{\it random fields} along the Ising $\hat z$ direction. This identifies
LiHo$_x$Y$_{1-x}$F$_4$ in $B_x$ as a new random field Ising system. The random
fields explain the rapid decrease of the critical temperature in the diluted
ferromagnetic regime and the smearing of the nonlinear susceptibility at the
spin glass transition with increasing $B_{x}$, and render the $B_{x}-$induced
quantum criticality in LiHo$_x$Y$_{1-x}$F$_4$ likely inaccessible.


  The anomalous strange metal phase found in high-$T_c$ cuprates does not
follow the conventional condensed-matter principles enshrined in the Fermi
liquid and presents a great challenge for theory. Highly precise experimental
determination of the electronic self-energy can provide a test bed for
theoretical models of strange metals, and angle-resolved photoemission can
provide this as a function of frequency, momentum, temperature and doping. Here
we show that constant energy cuts through the nodal spectral function in
(Pb,Bi)$_{2}$Sr$_{2-x}$La$_x$CuO$_{6+\delta}$ have a non-Lorentzian lineshape,
meaning the nodal self-energy is $k$ dependent. We show that the experimental
data are captured remarkably well by a power law with a $k$-dependent scaling
exponent smoothly evolving with doping, a description that emerges naturally
from AdS/CFT-based semi-holography. This puts a spotlight on holographic
methods for the quantitative modelling of strongly interacting quantum
materials like the cuprate strange metals.


  Purpose: To objectively assess new medical imaging technologies via
computer-simulations, it is important to account for the variability in the
ensemble of objects to be imaged. This source of variability can be described
by stochastic object models (SOMs). It is generally desirable to establish SOMs
from experimental imaging measurements acquired by use of a well-characterized
imaging system, but this task has remained challenging. Approach: A generative
adversarial network (GAN)-based method that employs AmbientGANs with modern
progressive or multiresolution training approaches is proposed. AmbientGANs
established using the proposed training procedure are systematically validated
in a controlled way using computer-simulated magnetic resonance imaging (MRI)
data corresponding to a stylized imaging system. Emulated single-coil
experimental MRI data are also employed to demonstrate the methods under less
stylized conditions. Results: The proposed AmbientGAN method can generate clean
images when the imaging measurements are contaminated by measurement noise.
When the imaging measurement data are incomplete, the proposed AmbientGAN can
reliably learn the distribution of the measurement components of the objects.
Conclusions: Both visual examinations and quantitative analyses, including
task-specific validations using the Hotelling observer, demonstrated that the
proposed AmbientGAN method holds promise to establish realistic SOMs from
imaging measurements.


  We identify analytically a multiple-peak structure in the energy-density
spectrum of induced gravitational waves (GWs) generated at second-order from a
primordial scalar perturbations also with multiple($n$) peaks at small scales
$k_{*i}$. The energy-density spectrum of induced GWs exhibits at most
$C_{n+1}^2$ and at least $n$ peaks at wave-vectors
$k_{ij}\equiv(k_{*i}+k_{*j})/\sqrt{3}$ due to resonant amplification, and,
under the narrow-width approximation, it contains an universal factor that can
be interpreted as a result of momentum conservation. We also extend these
discussions to the case of non-Gaussian perturbations.


  As collaborative learning and the outsourcing of data collection become more
common, malicious actors (or agents) which attempt to manipulate the learning
process face an additional obstacle as they compete with each other. In
backdoor attacks, where an adversary attempts to poison a model by introducing
malicious samples into the training data, adversaries have to consider that the
presence of additional backdoor attackers may hamper the success of their own
backdoor. In this paper, we investigate the scenario of a multi-agent backdoor
attack, where multiple non-colluding attackers craft and insert triggered
samples in a shared dataset which is used by a model (a defender) to learn a
task. We discover a clear backfiring phenomenon: increasing the number of
attackers shrinks each attacker's attack success rate (ASR). We then exploit
this phenomenon to minimize the collective ASR of attackers and maximize
defender's robustness accuracy by (i) artificially augmenting the number of
attackers, and (ii) indexing to remove the attacker's sub-dataset from the
model for inference, hence proposing 2 defenses.


  In the first part of this text we give a survey of the properties satisfied
by the C1-generic conservative diffeomorphisms of compact surfaces. The main
result that we will discuss is that a C1-generic conservative diffeomorphism of
a connected compact surface is transitive. It is obtain as a consequence of a
connecting lemma for pseudo-orbits. In the last parts we expose some recent
developments of the C1-perturbation technics and the proof of this connecting
lemma. We are not aimed to deal with technicalities nor to give the finest
available versions of these results. Besides this theory exists also in higher
dimension and in the non-conservative setting, we restricted the scope of this
presentation to the conservative case on surfaces, since it offers some
simplifications which allow to explain in an easier way the main ideas of the
subject.


  WiMAX (Worldwide Interoperability for Microwave Access) technology has
emerged in response to the increasing demand for multimedia services in the
internet broadband networks. WiMAX standard has defined five different
scheduling services to meet the QoS (Quality of Service) requirement of
multimedia applications and this paper investigates one specific scheduling
service, i.e. UGS scheduling. In parallel, it was observed that in the
difference of the traditional quality assessment approaches, nowadays, current
researches are centered on the user perception of the quality, the existing
scheduling approaches take into account the QoS, mobility and many other
parameters, but do not consider the Quality of Experience (QoE). In order to
control the packet transmission rate so as to match with the minimum subjective
rate requirements of each user and therefore reduce packet loss and delays, an
efficient scheduling approach has been proposed in this paper. The solution has
been implemented and evaluated in the WiMAX simulation platform developed based
on NS-2. Simulation results show that by applying various levels of MOS (Mean
Opinion Score) the QoE provided to the users is enhanced in term of jitter,
packet loss rate, throughput and delay.


  Gravitational wave detectors (GWDs), which have brought about a new era in
astronomy, have reached such a level of maturity that further improvement
necessitates quantum-noise-evading techniques. Numerous proposals to this end
have been discussed in the literature, e.g., invoking frequency-dependent
squeezing or replacing the current Michelson interferometer topology by that of
the quantum speedmeter. Recently, a proposal based on the linking of a standard
interferometer to a negative-mass spin system via entangled light has offered
an unintrusive and small-scale new approach to quantum noise evasion in GWDs
[Phys. Rev. Lett. $\mathbf{121}$, 031101 (2018)]. The solution proposed therein
does not require modifications to the highly refined core optics of the present
GWD design and, when compared to previous proposals, is less prone to losses
and imperfections of the interferometer. In the present article, we refine this
scheme to an extent that the requirements on the auxiliary spin system are
feasible with state-of-the-art implementations. This is accomplished by
matching the effective (rather than intrinsic) susceptibilities of the
interferometer and spin system using the virtual rigidity concept, which, in
terms of implementation, requires only suitable choices of the various
homodyne, probe, and squeezing phases.


  Experience is what makes our life more effective that is why it is necessary
to share experience among people. The use of information technologies is the
most technological way to work with experience, and the use of the Web is the
best way for sharing it. This paper describes a web resource designed for
storing, sharing and using experience that is obtained from different people in
the Web. The main purpose of this paper is to present this web resource in
order to evaluate the interest in such a web resource.


  Anisotropic flow measurements have demonstrated development of partonic
collectivity in $200\mathrm{GeV}$ Au+Au collisions at RHIC. To understand the
partonic EOS, thermalization must be addressed. Collective motion of
heavy-flavor (c,b) quarks can be used to indicate the degree of thermalization
of the light-flavor quarks (u,d,s). Measurement of heavy-flavor quark
collectivity requires direct reconstruction of heavy-flavor hadrons in the low
$\pt$ region. Measurement of open charm spectra to high $\pt$ can be used to
investigate heavy-quark energy loss and medium properties. The Heavy Flavor
Tracker (HFT), a proposed upgrade to the STAR experiment at midrapidity, will
measure $v_{2}$ of open-charm hadrons to very low $\pt$ by reconstructing their
displaced decay vertices. The innermost part of the HFT is the PIXEL detector
(made of two low mass monolithic active pixel sensor layers), which delivers a
high precision position measurement close to the collision vertex. The
Intermediate Silicon Tracker (IST), a 1-layer strip detector, is essential to
improve hit identification in the PIXEL detector when running at full RHIC-II
luminosity. Using a full GEANT simulation, open charm measurement capabilities
of STAR with the HFT will be shown. Its performance in a broad $\pt$ range will
be demonstrated on $v_{2}$ ($\pt > 0.5\mathrm{GeV}/c$) and $R_\mathrm{CP}$
($\pt < 10\mathrm{GeV}/c$) measurements of $\D$ meson. Results of
reconstruction of $\Lc$ baryon in heavy-ion collisions are presented.


  Collisionless N-body simulations are used in an effort to reproduce the
observed tendency of the surface brightness profile of bulges to change
progressively from a de Vaucouleurs law to an exponential, going from early to
late type spirals. A possible cause for this is the formation of the disc,
later in the history of the galaxy, and this is simulated by applying on the
N-body bulge the force field of a exponential disc whose surface density
increases with time. It is shown that [n], the index of the Sersic law that
best describes the surface brightness profile, does indeed decrease from 4 (de
Vaucouleurs law) to smaller values; this decrease is larger for more massive
and more compact discs. A large part of the observed trend of [n] with B/D
ratio is explained, and many of the actual profiles can be matched exactly by
the simulations. The correlation between the disc scalelength and bulge
effective radius, used recently to support the "secular evolution" origin for
bulges, is also shown to arise naturally in a scenario like this. This
mechanism, however, saturates at around n=2 and exponential bulges cannot be
produced; as [n] gets closer to 1, the profile becomes increasingly robust
against a disc field. These results provide strong support to the old-bulge
hypothesis for the early-type bulges. The exponential bulges, however, remain
essentially unexplained; the results here suggest that they did not begin their
lives as de Vaucouleurs spheroids, and hence were probably formed, at least in
part, by different processes than those of early type spirals.


  This paper presents a solution for recovering full trajectory information,
via the calculation of the posterior of the set of trajectories, from a
sequence of multitarget (unlabelled) filtering densities and the multitarget
dynamic model. Importantly, the proposed solution opens an avenue of trajectory
estimation possibilities for multitarget filters that do not explicitly
estimate trajectories. In this paper, we first derive a general multitrajectory
forward-backward smoothing equation based on sets of trajectories and the
random finite set framework. Then we show how to sample sets of trajectories
using backward simulation when the multitarget filtering densities are
multi-Bernoulli processes. The proposed approach is demonstrated in a
simulation study.


  The smallest number of cliques, covering all edges of a graph $ G $, is
called the (edge) clique cover number of $ G $ and is denoted by $ cc(G) $. It
is an easy observation that for every line graph $ G $ with $ n $ vertices,
$cc(G)\leq n $. G. Chen et al. [Discrete Math. 219 (2000), no. 1--3, 17--26;
MR1761707] extended this observation to all quasi-line graphs and questioned if
the same assertion holds for all claw-free graphs. In this paper, using the
celebrated structure theorem of claw-free graphs due to Chudnovsky and Seymour,
we give an affirmative answer to this question for all claw-free graphs with
independence number at least three. In particular, we prove that if $ G $ is a
connected claw-free graph on $ n $ vertices with $ \alpha(G)\geq 3 $, then $
cc(G)\leq n $ and equality holds if and only if $ G $ is either the graph of
icosahedron, or the complement of a graph on $10$ vertices called twister or
the $p^{th}$ power of the cycle $ C_n $, for $1\leq p \leq \lfloor
(n-1)/3\rfloor $.


  Deep learning models have achieved significant success across various
applications but continue to struggle with tasks requiring complex reasoning
over sequences, such as function composition and compositional tasks. Despite
advancements, models like Structured State Space Models (SSMs) and Transformers
underperform in deep compositionality tasks due to inherent architectural and
training limitations. Maintaining accuracy over multiple reasoning steps
remains a primary challenge, as current models often rely on shortcuts rather
than genuine multi-step reasoning, leading to performance degradation as task
complexity increases. Existing research highlights these shortcomings but lacks
comprehensive theoretical and empirical analysis for SSMs. Our contributions
address this gap by providing a theoretical framework based on complexity
theory to explain SSMs' limitations. Moreover, we present extensive empirical
evidence demonstrating how these limitations impair function composition and
algorithmic task performance. Our experiments reveal significant performance
drops as task complexity increases, even with Chain-of-Thought (CoT) prompting.
Models frequently resort to shortcuts, leading to errors in multi-step
reasoning. This underscores the need for innovative solutions beyond current
deep learning paradigms to achieve reliable multi-step reasoning and
compositional task-solving in practical applications.


  We study geodesic equations for a family of right-invariant Riemannian
metrics on the group of diffeomorphisms of a compact manifold. The metrics
descend to Fisher's information metric on the space of smooth probability
densities. The right reduced geodesic equations are higher-dimensional
generalisations of the $\mu$--Hunter--Saxton equation, used to model liquid
crystals under influence of magnetic fields. Local existence and uniqueness
results are established by proving smoothness of the geodesic spray.
  The descending property of the metrics is used to obtain a novel
factorisation of diffeomorphisms. Analogous to the polar factorisation in
optimal mass transport, this factorisation solves an optimal information
transport problem. It can be seen as an infinite-dimensional version of $QR$
factorisation of matrices.


  We identify 225 filaments from an H$_2$ column density map constructed using
simultaneous $^{12}$CO, $^{13}$CO, and C$^{18}$O (J=1-0) observations carried
out as a part of the MWISP project. We select 46 long filaments with lengths
above 1.2 pc to analyze the filament column density profiles. We divide the
selected filaments into 397 segments and calculate the column density profiles
for each segment. The symmetries of the profiles are investigated. The
proportion of intrinsically asymmetrical segments is 65.3$\%$, and that of
intrinsically symmetrical ones is 21.4$\%$. The typical full width at half
maximum (FWHM) of the intrinsically symmetrical filament segments is $\sim$
0.67 pc with the Plummer-like fitting, and $\sim$ 0.50 pc with the Gaussian
fitting, respectively. The median FWHM widths derived from the second-moment
method for intrinsically symmetrical and asymmetrical profiles are $\sim$ 0.44
and 0.46 pc, respectively. Close association exists between the filamentary
structures and the YSOs in the region.


  For a network of discrete states with a periodically driven Markovian
dynamics, we develop an inference scheme for an external observer who has
access to some transitions. Based on waiting-time distributions between these
transitions, the periodic probabilities of states connected by these observed
transitions and their time-dependent transition rates can be inferred.
Moreover, the smallest number of hidden transitions between accessible ones and
some of their transition rates can be extracted. We prove and conjecture lower
bounds on the total entropy production for such periodic stationary states.
Even though our techniques are based on generalizations of known methods for
steady states, we obtain original results for those as well.


  In the minimum $k$-cut problem, we want to find the minimum number of edges
whose deletion breaks the input graph into at least $k$ connected components.
The classic algorithm of Karger and Stein runs in $\tilde O(n^{2k-2})$ time,
and recent, exciting developments have improved the running time to $O(n^k)$.
For general, weighted graphs, this is tight assuming popular hardness
conjectures.
  In this work, we show that perhaps surprisingly, $O(n^k)$ is not the right
answer for simple, unweighted graphs. We design an algorithm that runs in time
$O(n^{(1-\epsilon)k})$ where $\epsilon>0$ is an absolute constant, breaking the
natural $n^k$ barrier. This establishes a separation of the two problems in the
unweighted and weighted cases.


  Niobium superconducting radiofrequency cavities enable applications in modern
accelerators and quantum computers. However, the surface resistance
significantly deteriorates the cavities performance. Nitrogen doping surface
treatment can consistently increase cavity performance by reducing surface
resistance, but the improvement mechanism is not fully understood. Herein, we
employed transmission electron microscopy and spectroscopy to uncover the
structural and chemical differences of the Nb-air interface between the
non-doped and nitrogen-doped cavities. The results indicate that nitrogen
doping passivates the Nb surface by introducing a compressive strain close to
the Nb/air interface, which impedes the oxygen diffusion and hydrogen atoms and
reduces surface oxide thickness.


  We show that the phase space of stratified turbulence mainly consists of two
slow invariant manifolds with rich physics, embedded on a larger basin with
fast evolution. A local invariant manifold in the vicinity of the fluid at
equilibrium corresponds to waves, while a global invariant manifold corresponds
to the onset of local convection. Using a reduced model derived from the
Boussinesq equations, we propose that waves accumulate energy nonlinearly up to
a point such that fluid elements escape from the local manifold and evolve fast
to the global manifold, where kinetic energy can be more efficiently
dissipated. After this, fluid elements return to the first manifold. As the
stratification increases, the volume of the first manifold increases, and the
second manifold becomes harder to access. This explains recent observations of
enhanced intermittency and marginal instability in these flows. The reduced
model also allows us to study structure formation, alignment of field gradients
in the flow, and to identify balance relations that hold for each fluid
element.


  We demonstrate an attack on a clock synchronization protocol that attempts to
detect tampering of the synchronization channel using polarization-entangled
photon pairs. The protocol relies on a symmetrical channel, where propagation
delays do not depend on propagation direction, for correctly deducing the
offset between clocks -- a condition that could be manipulated with optical
circulators, which rely on static magnetic fields to break the reciprocity of
propagating electromagnetic fields. Despite the polarization transformation
induced within a set of circulators, our attack creates an error in time
synchronization while successfully evading detection.


  We show how to use standard transmission line outage historical data to
obtain the network topology in such a way that cascades of line outages can be
easily located on the network. Then we obtain statistics quantifying how
cascading outages typically spread on the network. Processing real outage data
is fundamental for understanding cascading and for evaluating the validity of
the many different models and simulations that have been proposed for cascading
in power networks.


  We propose a model that explains the hierarchical organization of proteins in
fold families. The model, which is based on the evolutionary selection of
proteins by their native state stability, reproduces patterns of amino acids
conserved across protein families. Due to its dynamic nature, the model sheds
light on the evolutionary time scales. By studying the relaxation of the
correlation function between consecutive mutations at a given position in
proteins, we observe separation of the evolutionary time scales: at the short
time intervals families of proteins with similar sequences and structures are
formed, while at long time intervals the families of structurally similar
proteins that have low sequence similarity are formed. We discuss the
evolutionary implications of our model. We provide a ``profile'' solution to
our model and find agreement between predicted patterns of conserved amino
acids and those actually observed in nature.


  We study the following multiagent variant of the knapsack problem. We are
given a set of items, a set of voters, and a value of the budget; each item is
endowed with a cost and each voter assigns to each item a certain value. The
goal is to select a subset of items with the total cost not exceeding the
budget, in a way that is consistent with the voters' preferences. Since the
preferences of the voters over the items can vary significantly, we need a way
of aggregating these preferences, in order to select the socially best valid
knapsack. We study three approaches to aggregating voters' preferences, which
are motivated by the literature on multiwinner elections and fair allocation.
This way we introduce the concepts of individually best, diverse, and fair
knapsack. We study the computational complexity (including parameterized
complexity, and complexity under restricted domains) of the aforementioned
multiagent variants of knapsack.


  Power analysis is a class of side-channel attacks, where power consumption
data is used to infer sensitive information and extract secrets from a system.
Traditionally, such attacks required physical access to the target, as well as
specialized devices to measure the power consumption with enough precision. The
PLATYPUS attack has shown that on-chip power meter capabilities exposed to a
software interface might form a new class of power side-channel attacks. This
paper presents a software-based power side-channel attack on Apple Silicon
M1/M2 platforms, exploiting the System Management Controller (SMC) and its
power-related keys, which provides access to the on-chip power meters through a
software interface to user space software. We observed data-dependent power
consumption reporting from such keys and analyzed the correlations between the
power consumption and the processed data. Our work also demonstrated how an
unprivileged user mode application successfully recovers bytes from an AES
encryption key from a cryptographic service supported by a kernel mode driver
in macOS. Furthermore, we discuss the impact of software-based power
side-channels in the industry, possible countermeasures, and the overall
implications of software interfaces for modern on-chip power management
systems.


  The aim of this note is to give an elementary formulation of Tomio Kubota's
proof of Satz 4 in his paper in Nagoya Math. t. 10 (1956) since this
proposition is a cornerstone for the computation of the order of the Polya
group of the biquadratic number fields.


  Incremental Learning (IL) is an interesting AI problem when the algorithm is
assumed to work on a budget. This is especially true when IL is modeled using a
deep learning approach, where two com- plex challenges arise due to limited
memory, which induces catastrophic forgetting and delays related to the
retraining needed in order to incorpo- rate new classes. Here we introduce
DeeSIL, an adaptation of a known transfer learning scheme that combines a fixed
deep representation used as feature extractor and learning independent shallow
classifiers to in- crease recognition capacity. This scheme tackles the two
aforementioned challenges since it works well with a limited memory budget and
each new concept can be added within a minute. Moreover, since no deep re-
training is needed when the model is incremented, DeeSIL can integrate larger
amounts of initial data that provide more transferable features. Performance is
evaluated on ImageNet LSVRC 2012 against three state of the art algorithms.
Results show that, at scale, DeeSIL performance is 23 and 33 points higher than
the best baseline when using the same and more initial data respectively.


  Structural Health Monitoring (SHM) has been continuously benefiting from the
advancements in the field of data science. Various types of Artificial
Intelligence (AI) methods have been utilized for the assessment and evaluation
of civil structures. In AI, Machine Learning (ML) and Deep Learning (DL)
algorithms require plenty of datasets to train; particularly, the more data DL
models are trained with, the better output it yields. Yet, in SHM applications,
collecting data from civil structures through sensors is expensive and
obtaining useful data (damage associated data) is challenging. In this paper,
1-D Wasserstein loss Deep Convolutional Generative Adversarial Networks using
Gradient Penalty (1-D WDCGAN-GP) is utilized to generate damage associated
vibration datasets that are similar to the input. For the purpose of
vibration-based damage diagnostics, a 1-D Deep Convolutional Neural Network
(1-D DCNN) is built, trained, and tested on both real and generated datasets.
The classification results from the 1-D DCNN on both datasets resulted to be
very similar to each other. The presented work in this paper shows that for the
cases of insufficient data in DL or ML-based damage diagnostics, 1-D WDCGAN-GP
can successfully generate data for the model to be trained on. Keywords: 1-D
Generative Adversarial Networks (GAN), Deep Convolutional Generative
Adversarial Networks (DCGAN), Wasserstein Generative Adversarial Networks with
Gradient Penalty (WGAN-GP), 1-D Convolutional Neural Networks (CNN), Structural
Health Monitoring (SHM), Structural Damage Diagnostics, Structural Damage
Detection


  We present a new approach in modelling the polarized Galactic synchrotron
emission in the microwave range (20-100 GHz), where this radiation is expected
to play the leading role in contaminating the Cosmic Microwave Background (CMB)
data. Our method is based on real surveys and aims at providing the real
spatial distributions of both polarized intensity and polarization angles. Its
main features are the modelling of a polarization horizon to determine the
polarized intensity and the use of starlight optical data to model the
polarization angle pattern. Our results are consistent with several existing
data, and our template is virtually free from Faraday rotation effects as
required at frequencies in the cosmological window.


  We propose that the Antarctic Impulsive Transient Antenna (ANITA) can serve
as a detector for long-lived, charged particles, through its measurement of
extensive air showers from secondary leptons. To test this on an example model,
we simulate the production of staus inside the earth from interactions between
ultra-high energy neutrinos and nuclei. We propose that results of ANITA
searches for upgoing air showers can be interpreted in terms of constraints on
long-lived, charged massive particles (CHAMPs) and consider a supersymmetric
partner of the tau lepton, the stau, as an example of such a particle.
Exploring the parameter space in stau mass and lifetimes, we find that the stau
properties that lead to an observable signal in ANITA are highly energy
dependent. At $10^{18.5}$ eV, we find that the best constraints on the product
of the neutrino flux and the stau production cross section would be placed near
$m_{\tilde{\tau}}=$1 TeV and $\tau_{\tilde{\tau}}=$10 ns. Thus ANITA could be
sensitive to new physics in a region of parameter space that is unconstrained
by experiments at the Large Hadron Collider.


  Nano engineered spin degree of freedom in carbon system may offer desired
exchange coupling with optimum spin orbit interaction which is essential, to
construct solid state qubits, for fault tolerant quantum computation. The
purpose of this communication is to analyze spin dynamics of, basically, four
types of systems, (i) Graphene (system with inversion symmetry), (ii) Graphene
like nanocarbons (GNCs, broken inversion symmetry and heterostructure, sp2 and
sp3, environment), and (iii) their nitrogen doped derivatives. The spin
transport data was obtained using the electron spin resonance spectroscopy
(ESR) technique, carried out over 123 to 473K temperature range. Analysis of
shape, linewidths of dispersion derivatives,, and g factor anisotropy has been
carried out. Spin parameters such as, spin spin relaxation time, spin lattice
relaxation time, spin flip parameter,spin relaxation rate,spin, momentum
relaxation rate,pseudo chemical potential, density of states, effective
magnetic moment, spin concentration, defect concentration, and Pauli
susceptibility, has been estimated, and examined for their temperature as well
as interdependence. Details of the analysis are presented. The quantitative
study underlined the following facts: (i) by and large, spin dynamics in
Graphene and GNCs is significantly different, (ii) transport of spin behaves in
opposite fashion, after doping nitrogen, in both the systems, (iii) reduction
in the magnetization has been observed for both GNCs and Graphene, after doping
nitrogen, (iv) hyperfine interactions have been observed in all classes of
systems except in GNCs, (v) nitrogen doped GNCs seems to be appropriate for
qubit designing.


  We demonstrate that, in a quasi-two-dimensional electron system confined to
an AlAs quantum well and occupying two conduction-band minima (valleys), a
parallel magnetic field can couple to the electrons' orbital motion and tune
the energies of the two valleys by different amounts. The measured density
imbalance between the two valleys, which is a measure of the valley
susceptibility with respect to parallel magnetic field, is enhanced compared to
the predictions of non-interacting calculations, reflecting the role of
electron-electron interaction.


  In this study, we have investigated the photoionization cross section of an
on-center hydrogenic impurity in a multi-layered spherical quantum dot. The
electronic energy levels and their wave functions have been determined fully
numerically by shooting method. Also, we have calculated the binding energy of
the impurity by using these energy values. The photoionization cross section
has also been computed as a function of the layer thickness and normalized
photon energies. We have discussed in detail the possible physical reasons
behind the changes in the binding energies and photoionization cross section.
It is observed that both the binding energies and the photoionization cross
sections depend strongly on the layer thickness and photon energies.


  We have calculated the Tsallis entropy and Fisher information matrix
(entropy) of spatially-correlated nonextensive systems, by using an analytic
non-Gaussian distribution obtained by the maximum entropy method. Effects of
the correlated variability on the Fisher information matrix are shown to be
different from those on the Tsallis entropy. The Fisher information is
increased (decreased) by a positive (negative) correlation, whereas the Tsallis
entropy is decreased with increasing an absolute magnitude of the correlation
independently of its sign. This fact arises from the difference in their
characteristics. It implies from the Cram\'{e}r-Rao inequality that the
accuracy of unbiased estimate of fluctuation is improved by the negative
correlation. A critical comparison is made between the present study and
previous ones employing the Gaussian approximation for the correlated
variability due to multiplicative noise.


  In this article, we analyse optimal statistical arbitrage strategies from
stochastic control and optimisation problems for multiple co-integrated stocks
with eigenportfolios being factors. Optimal portfolio weights are found by
solving a Hamilton-Jacobi-Bellman (HJB) partial differential equation, which we
solve for both an unconstrained portfolio and a portfolio constrained to be
market neutral. Our analyses demonstrate sufficient conditions on the model
parameters to ensure long-term stability of the HJB solutions and stable growth
rates for the optimal portfolios. To gauge how these optimal portfolios behave
in practice, we perform backtests on historical stock prices of the S&P 500
constituents from year 2000 through year 2021. These backtests suggest three
key conclusions: that the proposed co-integrated model with eigenportfolios
being factors can generate a large number of co-integrated stocks over a long
time horizon, that the optimal portfolios are sensitive to parameter
estimation, and that the statistical arbitrage strategies are more profitable
in periods when overall market volatilities are high.


  Let ${\mathcal O} \subset {\mathbb R}^d$ be a bounded domain with the
boundary of class $C^{1,1}$. In $L_2({\mathcal O};{\mathbb C}^n)$, a matrix
elliptic second order differential operator ${\mathcal A}_{N,\varepsilon}$ with
the Neumann boundary condition is considered. Here $\varepsilon>0$ is a small
parameter, the coefficients of ${\mathcal A}_{N,\varepsilon}$ are periodic and
depend on ${\mathbf x} /\varepsilon$. There are no regularity assumptions on
the coefficients. It is shown that the resolvent $({\mathcal
A}_{N,\varepsilon}+\lambda I)^{-1}$ converges in the $L_2({\mathcal O};{\mathbb
C}^n)$-operator norm to the resolvent of the effective operator ${\mathcal
A}_N^0$ with constant coefficients, as $\varepsilon \to 0$. A sharp order error
estimate $|({\mathcal A}_{N,\varepsilon}+\lambda I)^{-1} - ({\mathcal A}_{N}^0
+\lambda I)^{-1}|_{L_2\to L_2} \le C\varepsilon$ is obtained. Approximation for
the resolvent $({\mathcal A}_{N,\varepsilon}+\lambda I)^{-1}$ in the norm of
operators acting from $L_2({\mathcal O};{\mathbb C}^n)$ to the Sobolev space
$H^1({\mathcal O};{\mathbb C}^n)$ with an error $O(\sqrt{\varepsilon})$ is
found. Approximation is given by the sum of the operator $({\mathcal A}^0_N
+\lambda I)^{-1}$ and the first order corrector. In a strictly interior
subdomain ${\mathcal O}'$ a similar approximation with an error
$O(\varepsilon)$ is obtained.


  The unitary group $\mathrm U(\mathcal H)$ on an infinite dimensional complex
Hilbert space $\mathcal H$ in its strong topology is a topological group and
has some further nice properties, e.g. it is metrizable and contractible if
$\mathcal H$ is separable. As an application Hilbert bundles are classified by
homotopy.


  Optical loss from scattered light could limit the performance of
quantum-noise filter cavities being considered for an upgrade to the Advanced
LIGO gravitational-wave detectors. This paper describes imaging scatterometer
measurements of the large-angle scattered light from two high-quality sample
optics, a high reflector and a beam splitter. These optics are each
superpolished fused silica substrates with silica:tantala dielectric coatings.
They represent the current state-of-the art optical technology for use in
filter cavities. We present angle-resolved scatter values and integrate these
to estimate the total scatter over the measured angles. We find that the total
integrated light scattered into larger angles can be as small as 4 ppm.


  We use analytic conformal bootstrap methods to determine the anomalous
dimensions and OPE coefficients for large spin operators in general conformal
field theories in four dimensions containing a scalar operator of conformal
dimension $\Delta_\phi$. It is known that such theories will contain an
infinite sequence of large spin operators with twists approaching
$2\Delta_\phi+2n$ for each integer $n$. By considering the case where such
operators are separated by a twist gap from other operators at large spin, we
analytically determine the $n$, $\Delta_\phi$ dependence of the anomalous
dimensions. We find that for all $n$, the anomalous dimensions are negative for
$\Delta_\phi$ satisfying the unitarity bound. We further compute the first
subleading correction at large spin and show that it becomes universal for
large twist. In the limit when $n$ is large, we find exact agreement with the
AdS/CFT prediction corresponding to the Eikonal limit of a 2-2 scattering with
dominant graviton exchange.


  Attack vectors for adversaries have increased in organizations because of the
growing use of less secure IoT devices. The risk of attacks on an
organization's network has also increased due to the bring your own device
(BYOD) policy which permits employees to bring IoT devices onto the premises
and attach them to the organization's network. To tackle this threat and
protect their networks, organizations generally implement security policies in
which only white listed IoT devices are allowed on the organization's network.
To monitor compliance with such policies, it has become essential to
distinguish IoT devices permitted within an organization's network from non
white listed (unknown) IoT devices. In this research, deep learning is applied
to network communication for the automated identification of IoT devices
permitted on the network. In contrast to existing methods, the proposed
approach does not require complex feature engineering of the network
communication, because the 'communication behavior' of IoT devices is
represented as small images which are generated from the device's network
communication payload. The proposed approach is applicable for any IoT device,
regardless of the protocol used for communication. As our approach relies on
the network communication payload, it is also applicable for the IoT devices
behind a network address translation (NAT) enabled router. In this study, we
trained various classifiers on a publicly accessible dataset to identify IoT
devices in different scenarios, including the identification of known and
unknown IoT devices, achieving over 99% overall average detection accuracy.


  We parameterize the non-universal couplings of t-t-Z and t-b-W in the
electroweak chiral lagrangian approach, and examine the constraints on these
parameters from the LEP data. We also study how the SLC, Tevatron, LHC and NLC
can improve the measurement of these couplings. Different symmetry breaking
scenarios imply different correlations among these couplings, whose measurement
will then provide a means to probe the electroweak symmetry breaking sector.


  We perform a comprehensive study of the formation of three dimensional
(pyramidal) structures in a large range of conditions, including the possible
evaporation of adatoms from the surface and the presence of surface defects. We
compare our computer simulations to theoretical calculations of the growth and
find good agreement between them. This work clarifies precedent studies of
three dimensional growth and predicts the island size distributions obtained in
the different regimes. Finally, we show how our analysis can be used to
interpret experimental data.


  Let $D$ be a subset of a finite commutative ring $R$ with identity. Let
$f(x)\in R[x]$ be a polynomial of positive degree $d$. For integer $0\leq k
\leq |D|$, we study the number $N_f(D,k,b)$ of $k$-subsets $S\subseteq D$ such
that
  \begin{align*}
  \sum_{x\in S} f(x)=b.
  \end{align*} In this paper, we establish several asymptotic formulas for
$N_f(D,k, b)$, depending on the nature of the ring $R$ and $f$.
  For $R=\mathbb{Z}_n$, let $p=p(n)$ be the smallest prime divisor of $n$,
$|D|=n-c \geq C_dn p^{-\frac 1d }+c$ and $f(x)=a_dx^d +\cdots +a_0\in
\mathbb{Z}[x]$ with $(a_d, \dots, a_1, n)=1$. Then
  $$\left| N_f(D, k, b)-\frac{1}{n}{n-c \choose k}\right|\leq
  {\delta(n)(n-c)+(1-\delta(n))(C_dnp^{-\frac 1d}+c)+k-1\choose k},$$ partially
answering an open question raised by Stanley \cite{St}, where
$\delta(n)=\sum_{i\mid n, \mu(i)=-1}\frac 1 i$ and $C_d=e^{1.85d}$.
Furthermore, if $n$ is a prime power, then $\delta(n) =1/p$ and one can take
$C_d=4.41$.
  For $R=\mathbb{F}_q$ of characteristic $p$, let $f(x)\in \mathbb{F}_q[x]$ be
a polynomial of degree $d$ not divisible by $p$ and
  $D\subseteq \mathbb{F}_q$ with $|D|=q-c\geq (d-1)\sqrt{q}+c$. Then $$\left|
N_f(D, k, b)-\frac{1}{q}{q-c \choose k}\right|\leq {\frac{q-c}{p}+\frac
{p-1}{p}((d-1)q^{\frac 12}+c)+k-1 \choose k}.$$
  If $f(x)=ax+b$, then this problem is precisely the well-known subset sum
problem over a finite abelian group. Let $G$ be a finite abelian group and let
$D\subseteq G$ with $|D|=|G|-c\geq c$. Then $$\left| N_x(D, k,
b)-\frac{1}{|G|}{|G|-c \choose k}\right|\leq {c + (|G|-2c)\delta(e(G))+k-1
\choose k},$$ where $e(G)$ is the exponent of $G$ and $\delta(n)=\sum_{i\mid n,
\mu(i)=-1}\frac 1 i$. In particular, we give a new short proof for the explicit
counting formula for the case $D=G$.


  Stability and electronic properties of atomic layers of GaN are investigated
in the framework of the van der Waals-density functional theory. We find that
the ground state of the layered GaN is a planar graphene-like configuration
rather than a buckled bulk-like configuration. Application of an external
perpendicular electric field to the layered GaN induces distinct
stacking-dependent features of the tunability of the band gap; the band gap of
the monolayer does not change whereas that of the trilayer GaN is significantly
reduced for the applied field of 0.4 V/ {\AA}. It is suggested that such a
stacking-dependent tunability of the band gap in the presence of an applied
field may lead to novel applications of the devices based on the layered GaN.


  So far, research in the field of metamaterials has been carried out largely
with arrays of flat, 2-dimensional structures. Here, we report a newly
identified magnetic resonance in Split Cylinder Resonators (SCRs), a
3-dimensional version of the Split Ring Resonator (SRR), which were fabricated
with the Proton Beam Writing technique. Experimental and numerical results
indicate a hitherto unobserved 3-dimensional resonance mode under normal
incidence at about 26 THz, when the SCR depth is approximately half the free
space wavelength. This mode is characterized by strong currents along the
cylinder axis which are concentrated at the cylinder gaps. Due to their
orientation, these axial currents give rise to a magnetic response under normal
incidence, which is not possible in shallow SRRs. Our results reveal new
behavior in the SRR structure which arises from a change in its aspect ratio.
Such new resonances can have a significant influence on the quest for
practical, 3-dimensional metamaterials.


  Automatic detection of multimodal misinformation has gained a widespread
attention recently. However, the potential of powerful Large Language Models
(LLMs) for multimodal misinformation detection remains underexplored. Besides,
how to teach LLMs to interpret multimodal misinformation in cost-effective and
accessible way is still an open question. To address that, we propose MMIDR, a
framework designed to teach LLMs in providing fluent and high-quality textual
explanations for their decision-making process of multimodal misinformation. To
convert multimodal misinformation into an appropriate instruction-following
format, we present a data augmentation perspective and pipeline. This pipeline
consists of a visual information processing module and an evidence retrieval
module. Subsequently, we prompt the proprietary LLMs with processed contents to
extract rationales for interpreting the authenticity of multimodal
misinformation. Furthermore, we design an efficient knowledge distillation
approach to distill the capability of proprietary LLMs in explaining multimodal
misinformation into open-source LLMs. To explore several research questions
regarding the performance of LLMs in multimodal misinformation detection tasks,
we construct an instruction-following multimodal misinformation dataset and
conduct comprehensive experiments. The experimental findings reveal that our
MMIDR exhibits sufficient detection performance and possesses the capacity to
provide compelling rationales to support its assessments.


  Magnetoelectric composites are an important class of multiferroic materials
that pave the way towards a new generation of multifunctional devices directly
integrable in data storage technology and spintronics. This study focuses on
strain-mediated electrical manipulation of magnetization in an extrinsic
multiferroic. The composite includes 5 nm or 60 nm Fe$_{81}$Ga$_{19}$ thin
films coupled to a piezoelectric (011)-PMN-PZT. The magnetization reversal
study reveals a converse magnetoelectric coefficient $\alpha_\mathrm{CME,max}
\approx 2.7 \times {10^{-6}}$ s.m$^{-1}$ at room temperature. This reported
value of $\alpha_\mathrm{CME}$ is among the highest so far compared to previous
reports of single-phase multiferroics as well as composites. An angular
dependency of $\alpha_\mathrm{CME}$ is also shown for the first time, arising
from the intrinsic magnetic anisotropy of FeGa. The highly efficient
magnetoelectric composite FeGa/PMN-PZT demonstrates drastic modifications of
the in-plane magnetic anisotropy, with an almost 90$^{\circ}$ rotation of the
preferential anisotropy axis in the thinner films under an electric field E =
10.8 kV.cm$^{-1}$. Also, the influence of thermal strain on the bilayer's
magnetic coercivity is compared to that of a reference bilayer FeGa/Glass at
cryogenic temperatures. A different evolution is observed as a function of
temperature, revealing a substrate thermo-mechanical influence which has not
yet been reported in FeGa thin films coupled to a piezoelectric material.


  In this paper, a distributed and autonomous technique for resource and power
allocation in orthogonal frequency division multiple access (OFDMA)
femto-cellular networks is presented. Here, resource blocks (RBs) and their
corresponding transmit powers are assigned to the user(s) in each cell
individually without explicit coordination between femto base stations (FBSs).
The "allocatability" of each resource is determined utilising only locally
available information of the following quantities: - the required rate of the
user; - the quality (i.e., strength) of the desired signal; - the
frequency-selective fading on each RB; and - the level of interference incident
on each RB. Using a fuzzy logic system, the time-averaged values of each of
these inputs are combined to determine which RBs are most suitable to be
allocated in a particular cell, i.e., which resources can be allocated such
that the user requested rate(s) in that cell are satisfied. Furthermore, link
adaptation (LA) is included, enabling users to adjust to varying channel
conditions. A comprehensive study of this system in a femto-cell environment is
performed, yielding system performance improvements in terms of throughput,
energy efficiency and coverage over state-of-the-art ICIC techniques.


  We use a state-of-the-art semi-analytic model to study the size and the
specific angular momentum of galaxies. Our model includes a specific treatment
for the angular momentum exchange between different galactic components. Disk
scale radii are estimated from the angular momentum of the gaseous/stellar
disk, while bulge sizes are estimated assuming energy conservation. The
predicted size--mass and angular momentum--mass relations are in fair agreement
with observational measurements in the local Universe, provided a treatment for
gas dissipation during major mergers is included. Our treatment for disk
instability leads to unrealistically small radii of bulges formed through this
channel, and predicts an offset between the size--mass relations of central and
satellite early-type galaxies, that is not observed. The model reproduces the
observed dependence of the size--mass relation on morphology, and predicts a
strong correlation between specific angular momentum and cold gas content. This
correlation is a natural consequence of galaxy evolution: gas-rich galaxies
reside in smaller halos, and form stars gradually until present day, while
gas-poor ones reside in massive halos, that formed most of their stars at early
epochs, when the angular momentum of their parent halos is low. The dynamical
and structural properties of galaxies can be strongly affected by a different
treatment for stellar feedback, as this would modify their star formation
history. A higher angular momentum for gas accreted through rapid mode does not
affect significantly the properties of massive galaxies today, but has a more
important effect on low-mass galaxies at higher redshift.


  In previous work, we have developed a simple method to study the behavior of
the Sherrington-Kirkpatrick mean field spin glass model for high temperatures,
or equivalently for high external fields. The basic idea was to couple two
different replicas with a quadratic term, trying to push out the two replica
overlap from its replica symmetric value. In the case of zero external field,
our results reproduced the well known validity of the annealed approximation,
up to the known critical value for the temperature. In the case of nontrivial
external field, our method could prove the validity of the
Sherrington-Kirkpatrick replica symmetric solution up to a line, which fell
short of the Almeida-Thouless line, associated to the onset of the spontaneous
replica symmetry breaking, in the Parisi Ansatz. Here, we make a strategic
improvement of the method, by modifying the flow equations, with respect to the
parameters of the model. We exploit also previous results on the overlap
fluctuations in the replica symmetric region. As a result, we give a simple
proof that replica symmetry holds up to the critical Almeida-Thouless line, as
expected on physical grounds. Our results are compared with the
characterization of the replica symmetry breaking line previously given by
Talagrand. We outline also a possible extension of our methods to the broken
replica symmetry region.


  In this paper, we consider three similar optimization problems: the
fault-tolerant metric dimension problem, the local metric dimension problem and
the strong metric dimension problem. These problems have applications in many
diverse areas, including network discovery and verification, robot navigation
and chemistry, etc. We give integer linear programming formulations of the
fault-tolerant metric dimension problem and the local metric dimension problem.
Also, we study local metric dimension and strong metric dimension of two convex
polytopes $S_n$ and $U_n$.


  Continuous-time projected dynamical systems are an elementary class of
discontinuous dynamical systems with trajectories that remain in a feasible
domain by means of projecting outward-pointing vector fields. They are
essential when modeling physical saturation in control systems, constraints of
motion, as well as studying projection-based numerical optimization algorithms.
Motivated by the emerging application of feedback-based continuous-time
optimization schemes that rely on the physical system to enforce nonlinear hard
constraints, we study the fundamental properties of these dynamics on general
locally-Euclidean sets. Among others, we propose the use of Krasovskii
solutions, show their existence on nonconvex, irregular subsets of
low-regularity Riemannian manifolds, and investigate how they relate to
conventional Carath\'eodory solutions. Furthermore, we establish conditions for
uniqueness, thereby introducing a generalized definition of prox-regularity
which is suitable for non-flat domains. Finally, we use these results to study
the stability and convergence of projected gradient flows as an illustrative
application of our framework. We provide simple counter-examples for our main
results to illustrate the necessity of our already weak assumptions.


  We theoretically investigate the thermoelectric properties of heat engines
based on Mach-Zehnder interferometers. The energy dependence of the
transmission amplitudes in such setups arises from a difference in the
interferometer arm lengths. Any thermoelectric response is thus of purely
quantum mechanical origin. In addition to an experimentally established
three-terminal setup, we also consider a two-terminal geometry as well as a
four-terminal setup consisting of two interferometers. We find that
Mach-Zehnder interferometers can be used as powerful and efficient heat engines
which perform well under realistic conditions.


  A generalization of the Kohn--Sham approach is derived where the
correlation-energy functional depends on the one-particle density matrix of
noninteracting states and on the external potential from the interacting
target-state. The one-particle equations contain the exact exchange potential,
a nonlocal correlation potential, and an additional operator involving the
correlation density. The electronic-energy functional has multiple solutions:
Any one-particle density matrix delivering the target-state density yields a
solution. In order to obtain the Kohn--Sham solution, the nonlocal operators
are converted into local ones using an approach developed by Sala and Gorling.
Since the exact exchange-potential is used, and the N--representability problem
does not arise--in contrast to the Kohn--Sham approach--errors from Coulomb
self-interactions do not occur, nor the need to introduce functionals defined
by a constraint search. Furthermore, the approach does not use the
Hohenberg-Kohn theorem. A density functional formalism is also derived that
assumes that the one-particle density matrices of interest have v-representable
(non-interacting) densities and that these density matrices can be written as
an explicit functional of the electron density. For simplicity, we only
consider noninteracting closed-shell states and target states that are
nondegenerate, singlet ground-states.


  We have analyzed ALMA Cycle 5 data in Band 4 toward three low-mass young
stellar objects (YSOs), IRAS 03235+3004 (hereafter IRAS 03235), IRAS 03245+3002
(IRAS 03245), and IRAS 03271+3013 (IRAS 03271), in the Perseus region. The
HC$_{3}$N ($J=16-15$; $E_{\rm {up}}/k = 59.4$ K) line has been detected in all
of the target sources, while four CH$_{3}$OH lines ($E_{\rm {up}}/k =
15.4-36.3$ K) have been detected only in IRAS 03245. Sizes of the HC$_{3}$N
distributions ($\sim 2930-3230$ au) in IRAS 03235 and IRAS 03245 are similar to
those of the carbon-chain species in the warm carbon chain chemistry (WCCC)
source L1527. The size of the CH$_{3}$OH emission in IRAS 03245 is $\sim 1760$
au, which is slightly smaller than that of HC$_{3}$N in this source. We compare
the CH$_{3}$OH/HC$_{3}$N abundance ratios observed in these sources with
predictions of chemical models. We confirm that the observed ratio in IRAS
03245 agrees with the modeled values at temperatures around 30--35 K, which
supports the HC$_{3}$N formation by the WCCC mechanism. In this temperature
range, CH$_{3}$OH does not thermally desorb from dust grains. Non-thermal
desorption mechanisms or gas-phase formation of CH$_{3}$OH seem to work
efficiently around IRAS 03245. The fact that IRAS 03245 has the highest
bolometric luminosity among the target sources seems to support these
mechanisms, in particular the non-thermal desorption mechanisms.


  We propose Kernel Predictive Control (KPC), a learning-based predictive
control strategy that enjoys deterministic guarantees of safety.
Noise-corrupted samples of the unknown system dynamics are used to learn
several models through the formalism of non-parametric kernel regression. By
treating each prediction step individually, we dispense with the need of
propagating sets through highly non-linear maps, a procedure that often
involves multiple conservative approximation steps. Finite-sample error bounds
are then used to enforce state-feasibility by employing an efficient robust
formulation. We then present a relaxation strategy that exploits on-line data
to weaken the optimization problem constraints while preserving safety. Two
numerical examples are provided to illustrate the applicability of the proposed
control method.


  Problems involving code-mixed language are often plagued by a lack of
resources and an absence of materials to perform sophisticated transfer
learning with. In this paper we describe our submission to the Sentimix
Hindi-English task involving sentiment classification of code-mixed texts, and
with an F1 score of 67.1%, we demonstrate that simple convolution and attention
may well produce reasonable results.


  The phenomenon of Coulombic friction enters the stochastic description of dry
friction between two solids and the statistic characterization of vibrating
granular media. Here we analyze the corresponding Fokker-Planck equation
including both velocity and spatial components, exhibiting a formal connection
to a quantum mechanical harmonic oscillator in the presence of a delta
potential. Numerical solutions for the resulting spatial displacement
statistics show a crossover from exponential to Gaussian displacement
statistics. We identify a transient intermediate regime that exhibits
multiscaling properties arising from the contribution of Coulombic friction.
The possible role of these effects during observations in diffusion experiments
is shortly discussed.


  A transitive compact foliated space is shown to be a Riemannian foliation if
and only if it is locally connected, finite dimensional, strongly
equicontinuous and quasi-analytic, and the closure of its holonomy pseudogroup
is quasi-analytic.


  The idea of the inheritance of biological processes, such as the
developmental process or the life cycle of an organism, has been discussed in
the biology literature, but formal mathematical descriptions and plausible data
analysis frameworks are lacking. We introduce an extension of the nested
Dirichlet Process (nDP) to a multiscale model to aid in understanding the
mechanisms by which biological processes are inherited, remain stable, and are
modified across generations. To address these issues, we introduce Nested
Inheritance Dynamics Algorithm (NIDA). At its primary level, NIDA encompasses
all processes unfolding within an individual organism's lifespan. The secondary
level delineates the dynamics through which these processes evolve or remain
stable over time. This framework allows for the specification of a physical
system model at either scale, thus promoting seamless integration with
established models of development and heredity.


  We revisit, qualify, and objectively resolve the seemingly controversial
question about what is the number of dimensional fundamental constants in
Nature. For this purpose, we only assume that all we can directly measure are
space and time intervals, and that this is enough to evaluate any physical
observable. We conclude that the number of dimensional fundamental constants is
two. We emphasize that this is an objective result rather than a "philosophical
opinion", and we let it clear how it could be refuted in order to prove us
wrong. Our conclusion coincides with Veneziano's string-theoretical one but our
arguments are not based on any particular theory. As a result, this implies
that one of the three usually considered fundamental constants "G", "c" or "h"
can be eliminated and we show explicitly how this can be accomplished.


  The effects of velocity shear on the unstable modes driven by the effective
gravity (Rayleigh-Taylor and interchange) and resistive drift wave
instabilities for inhomogeneous equilibrium fluid/plasma density are analyzed
for the localized eigenmode problems. It is shown that the effect of the
velocity shear drastically depends on the type of instability. Whereas the
velocity shear can significantly suppress both Rayleigh-Taylor and interchange
instabilities, it has only a week impact on the growth rate of the resistive
drift wave. This is directly related to the physical nature of these
instabilities. For the Rayleigh-Taylor and interchange instabilities, the shear
flow tilts the eddies of the stream functions, while for the resistive drift
wave instability the shear flow simply shifts the eddies in the radial
direction with no tilting. However, for large velocity shear, the eigenmode
solutions for resistive drift waves cease to exist.


  We show that there exists a suitable sequence $\{w^{(k)}\}_{k \ge 0}$ of Weyl
group elements for the perfect crystal $B = B^{1,3l}$ such that the path
realizations of the Demazure crystals $B_{w^{(k)}}(l\Lambda_2)$ for the quantum
affine algebra $U_q(D_4^{(3)})$ have tensor product like structure with mixing
index $\kappa =1$.


  Due to their simplicity and versatility of design, straight strip or
rectangular pad anode structures are frequently employed with micro-pattern gas
detectors to reconstruct high precision space points for various tracking
applications. The particle impact point is typically determined by
interpolating the charge collected by several neighboring pads. However, to
effectively extract the inherent positional information, the lateral spacing of
the straight pads must be significantly smaller than the extent of the charge
cloud. In contrast, highly interleaved anode patterns, such as zigzags, can
adequately sample the charge with a pitch comparable to the size of the charge
cloud or even larger. This has the considerable advantage of providing the same
performance while requiring far fewer instrumented channels. Additionally, the
geometric parameters defining such zigzag structures may be tuned to provide a
uniform detector response without the need for so-called pad response
functions, while simultaneously maintaining excellent position resolution. We
have measured the position resolution of a variety of zigzag shaped anode
patterns optimized for various MPGDs, including GEM, Micromegas, and
micro-RWELL and compared this performance to the same detectors equipped with
straight pads of varying pitch. We report on the performance results of each
readout structure, evaluated under identical conditions in a test beam.


  Methods based on hypothesis tests (HTs) in the Haar domain are widely used to
denoise Poisson count data. Facing large datasets or real-time applications,
Haar-based denoisers have to use the decimated transform to meet limited-memory
or computation-time constraints. Unfortunately, for regular underlying
intensities, decimation yields discontinuous estimates and strong "staircase"
artifacts. In this paper, we propose to combine the HT framework with the
decimated biorthogonal Haar (Bi-Haar) transform instead of the classical Haar.
The Bi-Haar filter bank is normalized such that the p-values of Bi-Haar
coefficients (pBH) provide good approximation to those of Haar (pH) for
high-intensity settings or large scales; for low-intensity settings and small
scales, we show that pBH are essentially upper-bounded by pH. Thus, we may
apply the Haar-based HTs to Bi-Haar coefficients to control a prefixed false
positive rate. By doing so, we benefit from the regular Bi-Haar filter bank to
gain a smooth estimate while always maintaining a low computational complexity.
A Fisher-approximation-based threshold imple- menting the HTs is also
established. The efficiency of this method is illustrated on an example of
hyperspectral-source-flux estimation.


  We perform a galaxy-galaxy lensing study by correlating the shapes of
$\sim$2.7 $\times$ 10$^5$ galaxies selected from the VLA FIRST radio survey
with the positions of $\sim$38.5 million SDSS galaxies, $\sim$132000 BCGs and
$\sim$78000 SDSS galaxies that are also detected in the VLA FIRST survey. The
measurements are conducted on angular scales ${\theta}$ $\lesssim$ 1200 arcsec.
On scales ${\theta}$ $\lesssim$ 200 arcsec we find that the measurements are
corrupted by residual systematic effects associated with the instrumental beam
of the VLA data. Using simulations we show that we can successfully apply a
correction for these effects. Using the three lens samples (the SDSS DR10
sample, the BCG sample and the SDSS-FIRST matched object sample) we measure a
tangential shear signal that is inconsistent with zero at the 10${\sigma}$,
3.8${\sigma}$ and 9${\sigma}$ level respectively. Fitting an NFW model to the
detected signals we find that the ensemble mass profile of the BCG sample
agrees with the values in the literature. However, the mass profiles of the
SDSS DR10 and the SDSS-FIRST matched object samples are found to be shallower
and steeper than results in the literature respectively. The best-fitting
Virial masses for the SDSS DR10, BCG and SDSS-FIRST matched samples, derived
using an NFW model and allowing for a varying concentration factor, are
M$^{SDSS-DR10}_{200}$ = (1.2 $\pm$ 0.4) $\times$ 10$^{12}$M$_{\odot}$,
M$^{BCG}_{200}$ = (1.4 $\pm$ 1.3) $\times$ 10$^{13}$M$_{\odot}$ and
M$^{SDSS-FIRST}_{200}$ = 8.0 $\pm$ 4.2 $\times$ 10$^{13}$M$_{\odot}$
respectively. These results are in good agreement (within $\sim$2${\sigma}$)
with values in the literature. Our findings suggest that for galaxies to be
both bright in the radio and in the optical they must be embedded in very dense
environment on scales R $\lesssim$ 1Mpc.


  Information-theoretic work for wiretap channels is mostly based on random
coding schemes. Designing practical coding schemes to achieve
information-theoretic security is an important problem. By applying the two
recently developed techniques for polar codes, we propose a polar coding scheme
to achieve the secrecy capacity of the general wiretap channel.