  The social presence theory in social psychology suggests that
computer-mediated online interactions are inferior to face-to-face, in-person
interactions. In this paper, we consider the scenarios of organizing in person
friend-making social activities via online social networks (OSNs) and formulate
a new research problem, namely, Hop-bounded Maximum Group Friending (HMGF), by
modeling both existing friendships and the likelihood of new friend making. To
find a set of attendees for socialization activities, HMGF is unique and
challenging due to the interplay of the group size, the constraint on existing
friendships and the objective function on the likelihood of friend making. We
prove that HMGF is NP-Hard, and no approximation algorithm exists unless P =
NP. We then propose an error-bounded approximation algorithm to efficiently
obtain the solutions very close to the optimal solutions. We conduct a user
study to validate our problem formulation and per- form extensive experiments
on real datasets to demonstrate the efficiency and effectiveness of our
proposed algorithm.


  In relativistic heavy-ion collisions, properties of the initial state and
effects arising during evolution of the medium, such as a transition between
the hadronic and partonic phases, should reflect themselves in event-by-event
fluctuations of the number of produced particles. In this paper, recent
measurements of several event-by-event observables, namely, dynamical
fluctuations of relative particle yields and forward-backward correlations of
different types, are discussed. Also, new observables for forward-backward
correlation studies are proposed: correlations between ratios of identified
particle yields in two separated acceptance intervals and the correlation
between the ratio in one interval and average transverse momentum in another.


  We describe a general (primitively) polarized K3 surface $(S,h)$ with
$(h^2)=24$ as a complete intersection variety with respect to vector bundles on
the $6$-dimensional moduli space $\mathcal{N}^-$ of the stable vector bundles
of rank two with fixed odd determinant on a curve $C$ of genus $3$. If the
curve $C$ is hyperelliptic, then $\mathcal{N}^-$ is a subvariety of the
$12$-dimensional Grassmann variety $\operatorname{Gr}(\mathbf{C}^8,2)$ defined
by a pencil of quadric forms. In this case, our description implies that a
general $(S,h)$ is the intersection of two (7-dimensional) contact homogeneous
varieties of $\operatorname{Spin}(7)$ in the Grassmann variety
$\operatorname{Gr}(\mathbf{C}^8,2)$.


  We study the limiting behavior of Maass forms on Benjamini-Schramm convergent
sequences of compact quotients of ${\rm SL}_d(\mathbb{R})/{\rm SO}(d)$, $d\ge
3$, whose spectral parameter stays in a fixed window. We prove a form of
Quantum Ergodicity in this level aspect which extends results of Le Masson and
Sahlsten to the higher rank case.


  We study the finite size effects on the thermal deconfinement phase
transition from the hadronic gas phase to the QGP phase, using a simple
thermodynamic model based on the coexistence of confined and deconfined phases
in a finite volume. We first consider the bag model partition function for the
QGP, then we include the necessary color singletness condition. By probing the
behavior of some physical quantities on the hole range of temperature, it turns
out that in a finite size system, all singularities occuring in these
quantities in the thermodynamic limit are smoothed out, and the phase
transition is then rounded over a broadened critical region, with an additional
shifting effect of the critical point induced by the exact color singletness
requirement. An analysis of the finite size scaling behavior at criticality of
some characteristic quantities allows us to determine the scaling critical
exponents characterizing the thermal deconfinement phase transition. The
obtained results are in good agreement with those predicted by other studies
for a first-order phase transition


  In Federated Learning (FL), multiple clients collaboratively train a global
model without sharing private data. In semantic segmentation, the Federated
source Free Domain Adaptation (FFreeDA) setting is of particular interest,
where clients undergo unsupervised training after supervised pretraining at the
server side. While few recent works address FL for autonomous vehicles,
intrinsic real-world challenges such as the presence of adverse weather
conditions and the existence of different autonomous agents are still
unexplored. To bridge this gap, we address both problems and introduce a new
federated semantic segmentation setting where both car and drone clients
co-exist and collaborate. Specifically, we propose a novel approach for this
setting which exploits a batch-norm weather-aware strategy to dynamically adapt
the model to the different weather conditions, while hyperbolic space
prototypes are used to align the heterogeneous client representations. Finally,
we introduce FLYAWARE, the first semantic segmentation dataset with adverse
weather data for aerial vehicles.


  Structured pruning methods are developed to bridge the gap between the
massive scale of neural networks and the limited hardware resources. Most
current structured pruning methods rely on training datasets to fine-tune the
compressed model, resulting in high computational burdens and being
inapplicable for scenarios with stringent requirements on privacy and security.
As an alternative, some data-free methods have been proposed, however, these
methods often require handcraft parameter tuning and can only achieve
inflexible reconstruction. In this paper, we propose the Automatic Data-Free
Pruning (AutoDFP) method that achieves automatic pruning and reconstruction
without fine-tuning. Our approach is based on the assumption that the loss of
information can be partially compensated by retaining focused information from
similar channels. Specifically, We formulate data-free pruning as an
optimization problem, which can be effectively addressed through reinforcement
learning. AutoDFP assesses the similarity of channels for each layer and
provides this information to the reinforcement learning agent, guiding the
pruning and reconstruction process of the network. We evaluate AutoDFP with
multiple networks on multiple datasets, achieving impressive compression
results. For instance, on the CIFAR-10 dataset, AutoDFP demonstrates a 2.87\%
reduction in accuracy loss compared to the recently proposed data-free pruning
method DFPC with fewer FLOPs on VGG-16. Furthermore, on the ImageNet dataset,
AutoDFP achieves 43.17\% higher accuracy than the SOTA method with the same
80\% preserved ratio on MobileNet-V1.


  We model the light-curves from radiation-driven clouds near an accreting
black hole. Taking into account the multiple images due to strong gravitational
lensing, we find that sharp spikes can significantly enhance the observed flux.
Following our previous work (Horak & Karas 2006a,b) we assume that scattering
of ambient light takes place in a cloud that is in radial motion under a
combined influence of black hole gravity and the radiation field. The
retro-lensed photons give rise to peaks in the observed signal that follow with
a characteristic time lag after the direct-image photons. Duration of these
features is very short and the predicted polarization varies abruptly on the
time-scale comparable with the light-crossing time of the system -- a signature
of the photon orbit. We also consider the polarization properties of scattered
light.


  Tight-binding molecular dynamics simulated annealing technique is employed to
search for the ground state geometries of silicon clusters containing 11-17
atoms. These studies revealed that layer formation is the dominant growth
pattern in all these clusters. Fullerene-like precursor structures consisting
of fused pentagon rings are also observed. The atoms in all these clusters
exhibit pronounced preference for residing on the surface.


  We evaluate differential distributions for the four-body $p p \to n n \pi^+
\pi^+$ reaction. The amplitude for the process is calculated in the Regge
approach including many diagrams. We make predictions for possible future
experiments at RHIC and LHC energies. Very large cross sections are found which
is partially due to interference of a few mechanisms. Presence of several
interfering mechanisms precludes extraction of the elastic $\pi^+ \pi^+$
scattering cross section. Absorption effects are estimated. Differential
distributions in pseudorapidity, rapidity, invariant two-pion mass,
transverse-momentum and energy distributions of neutrons are presented for
proton-proton collisions at $\sqrt{s}$ = 500 GeV (RHIC) and $\sqrt{s}$ = 0.9,
2.36 and 7 TeV (LHC). Cross sections with experimental cuts are presented.


  We carry on the investigation started in [2] about the regularity of weak
solutions to the strongly degenerate parabolic equation \[
u_{t}-\mathrm{div}\left[(\vert Du\vert-1)_{+}^{p-1}\frac{Du}{\vert
Du\vert}\right]=f\,\,\,\,\,\,\,\,\,\mathrm{in}\,\,\Omega_{T}=\Omega\times(0,T),
\] where $\Omega$ is a bounded domain in $\mathbb{R}^{n}$ for $n\geq2$,
$p\geq2$ and $\left(\,\cdot\,\right)_{+}$ stands for the positive part. Here,
we weaken the assumption on the right-hand side, by assuming that $f\in
L_{loc}^{p'}\left(0,T;B_{p',\infty,loc}^{\alpha}\left(\Omega\right)\right)$,
with $\alpha\in(0,1)$ and $p'=p/(p-1)$. This leads us to obtain higher
fractional differentiability results for a function of the spatial gradient
$Du$ of the solutions. Moreover, we establish the higher summability of $Du$
with respect to the spatial variable. The main novelty of the above equation is
that the structure function satisfies standard ellipticity and growth
conditions only outside the unit ball centered at the origin. We would like to
point out that the main result of this paper can be considered, on the one
hand, as the parabolic counterpart of an elliptic result contained in [1], and
on the other hand as the fractional version of some results established in [2].


  WR 148 (HD 197406) is an extreme runaway system considered to be a potential
candidate for a short-period (4.3173 d) rare WR + compact object binary.
Provided with new high resolution, high signal-to-noise spectra from the Keck
observatory, we determine the orbital parameters for both the primary WR and
the secondary, yielding respective projected orbital velocity amplitudes of
$88.1\pm3.8$ km s$^{-1}$ and $79.2\pm3.1$ km s$^{-1}$ and implying a mass ratio
of $1.1\pm0.1$. We then apply the shift-and-add technique to disentangle the
spectra and obtain spectra compatible with a WN7ha and an O4-6 star.
Considering an orbital inclination of $\sim67^\circ$, derived from previous
polarimetry observations, the system's total mass would be a mere 2-3
M$_{\odot}$ , an unprecedented result for a putative massive binary system.
However, a system comprising a 37 M$_{\odot}$ secondary (typical mass of an O5V
star) and a 33 M$_{\odot}$ primary (given the mass ratio) would infer an
inclination of $\sim18^\circ$. We therefore reconsider the previous methods of
deriving the orbital inclination based on time-dependent polarimetry and
photometry. While the polarimetric results are inconclusive requiring better
data, the photometric results favour low inclinations. Finally, we compute WR
148's space velocity and retrace the runaway's trajectory back to the Galactic
plane (GP). With an ejection velocity of $198\pm27$ km s$^{-1}$ and a travel
time of $4.7\pm0.8$ Myr to reach its current location, WR 148 was most likely
ejected via dynamical interactions in a young cluster.


  We study the homology of the dual de Rham complex as functors on the category
of abelian groups. We give a description of homology of the dual de Rham
complex up to degree 7 for free abelian groups and present a corrected version
of the proof of Jean's computations of the zeroth homology group.


  The objective of this work is to train a chatbot capable of solving evolving
problems through conversing with a user about a problem the chatbot cannot
directly observe. The system consists of a virtual problem (in this case a
simple game), a simulated user capable of answering natural language questions
that can observe and perform actions on the problem, and a Deep Q-Network
(DQN)-based chatbot architecture. The chatbot is trained with the goal of
solving the problem through dialogue with the simulated user using
reinforcement learning. The contributions of this paper are as follows: a
proposed architecture to apply a conversational DQN-based agent to evolving
problems, an exploration of training methods such as curriculum learning on
model performance and the effect of modified reward functions in the case of
increasing environment complexity.


  We present a simple quantum mechanical model to describe Coulomb explosion of
H$_2^+$ by short, intense, infrared laser pulses. The model is based on the
length gauge version of the molecular strong-field approximation and is valid
for pulses shorter than 50 fs where the process of dissociation prior to
ionization is negligible. The results are compared with recent experimental
results for the proton energy spectrum [I. Ben-Itzhak et al., Phys. Rev. Lett.
95, 073002 (2005), B. D. Esry et al., Phys. Rev. Lett. 97, 013003 (2006)]. The
predictions of the model reproduce the profile of the spectrum although the
peak energy is slightly lower than the observations. For comparison, we also
present results obtained by two different tunneling models for this process.


  Some models of leptogenesis involve a nearly-degenerate pair of heavy
Majorana neutrinos $N_{1,2}$ whose masses can be small, $O({\rm GeV})$. There
can be heavy-light neutrino mixing parametrized by $|B_{\ell N}|^2 = 10^{-5}$,
which leads to the rare lepton-number-violating decay $W^\pm \to \ell_1^\pm
\ell_2^\pm (q'{\bar q})^\mp$. With contributions to this decay from both $N_1$
and $N_2$, a CP-violating rate difference between the decay and its
CP-conjugate can be generated. In this talk, I describe the prospects for
measuring such a CP asymmetry $A_{\rm CP}$ at the LHC. I consider three
versions of the LHC -- HL-LHC, HE-LHC, FCC-hh -- and show that, for $5~{\rm
GeV} \le M_N \le 80~{\rm GeV}$, small values of the CP asymmetry can be
measured at $3\sigma$, in the range $1\%\le A_{\rm CP} \le 15\%$.


  In this paper, we prove the stability of metric measure spaces satisfying the
curvature-dimension condition for negative dimensions under a concentration
topology. This result is an analogue of the result by Funano-Shioya with
respect to the dimension parameter.


  In the past few years, more and more AI applications have been applied to
edge devices. However, models trained by data scientists with machine learning
frameworks, such as PyTorch or TensorFlow, can not be seamlessly executed on
edge. In this paper, we develop an end-to-end code generator parsing a
pre-trained model to C source libraries for the backend using MicroTVM, a
machine learning compiler framework extension addressing inference on bare
metal devices. An analysis shows that specific compute-intensive operators can
be easily offloaded to the dedicated accelerator with a Universal Modular
Accelerator (UMA) interface, while others are processed in the CPU cores. By
using the automatically generated ahead-of-time C runtime, we conduct a hand
gesture recognition experiment on an ARM Cortex M4F core.


  A graph $G$ is a prime distance graph (respectively, a 2-odd graph) if its
vertices can be labeled with distinct integers such that for any two adjacent
vertices, the difference of their labels is prime (either 2 or odd). We prove
that trees, cycles, and bipartite graphs are prime distance graphs, and that
Dutch windmill graphs and paper mill graphs are prime distance graphs if and
only if the Twin Prime Conjecture and dePolignac's Conjecture are true,
respectively. We give a characterization of 2-odd graphs in terms of edge
colorings, and we use this characterization to determine which circulant graphs
of the form $Circ(n, \{1,k\})$ are 2-odd and to prove results on circulant
prime distance graphs.


  Temporal grounding aims to predict a time interval of a video clip
corresponding to a natural language query input. In this work, we present
EVOQUER, a temporal grounding framework incorporating an existing text-to-video
grounding model and a video-assisted query generation network. Given a query
and an untrimmed video, the temporal grounding model predicts the target
interval, and the predicted video clip is fed into a video translation task by
generating a simplified version of the input query. EVOQUER forms closed-loop
learning by incorporating loss functions from both temporal grounding and query
generation serving as feedback. Our experiments on two widely used datasets,
Charades-STA and ActivityNet, show that EVOQUER achieves promising improvements
by 1.05 and 1.31 at<EMAIL_ADDRESS>We also discuss how the query generation task could
facilitate error analysis by explaining temporal grounding model behavior.


  Detection of X-ray emission from classical novae in their post-outburst
stages provides crucial information about the nova phenomenon. The soft X-ray
emission gives a direct insight into the remaining hot nuclear burning shell. A
numerical model for steady H-burning white dwarf envelopes has been developed
to study the post-outburst phases of classical novae. Properties of the X-ray
emission of the post-nova white dwarf are obtained, and the results are
compared to ROSAT observations of V1974 Cyg.


  Euler noted the relation $6^3=3^3+4^3+5^3$ and asked for other instances of
cubes that are sums of consecutive cubes. Similar problems have been studied by
Cunningham, Catalan, Gennochi, Lucas, Pagliani, Cassels, Uchiyama, Stroeker and
Zhongfeng Zhang. In particular Stroeker determined all squares that can be
written as a sum of at most $50$ consecutive cubes. We generalize Stroeker's
work by determining all perfect powers that are sums of at most $50$
consecutive cubes. Our methods include descent, linear forms in two logarithms,
and Frey-Hellegouarch curves.


  The formation of current sheets in ideal incompressible magnetohydrodynamic
flows in two dimensions is studied numerically using the technique of adaptive
mesh refinement. The growth of current density is in agreement with simple
scaling assumptions. As expected, adaptive mesh refinement shows to be very
efficient for studying singular structures compared to non-adaptive treatments.


  Parental control apps, which are mobile apps that allow parents to monitor
and restrict their children's activities online, are becoming increasingly
adopted by parents as a means of safeguarding their children's online safety.
However, it is not clear whether these apps are always beneficial or effective
in what they aim to do; for instance, the overuse of restriction and
surveillance has been found to undermine parent-child relationship and
children's sense of autonomy. In this work, we investigate this gap, asking
specifically: how might children's and parents' perceptions be related to how
parental control features were designed? To investigate this question, we
conducted an analysis of 58 top Android parental control apps designed for the
purpose of promoting children's online safety, finding three major axes of
variation in how key restriction and monitoring features were realised:
granularity, feedback/transparency, and parent-child communications support. To
relate these axes to perceived benefits and problems, we then analysed 3264 app
reviews to identify references to aspects of the each of the axes above, to
understand children's and parents' views of how such dimensions related to
their experiences with these apps. Our findings led towards 1) an understanding
of how parental control apps realise their functionalities differently along
three axes of variation, 2) an analysis of exactly the ways that such variation
influences children's and parents' perceptions, respectively of the usefulness
or effectiveness of these apps, and finally 3) an identification of design
recommendations and opportunities for future apps by contextualising our
findings within existing digital parenting theories.


  The Centre de Donnees astronomiques de Strasbourg (CDS) provides homogeneous
access to heterogeneous information of various origins: information about
astronomical objects in Simbad; catalogs and observation logs in VizieR and in
the catalogue service; reference images and overlays in Aladin; nomenclature in
the Dictionary of Nomenclature; Yellow Page services; the AstroGLU resource
discovery tool; mirror copies of other reference services; and documentation.
With the implementation of links between the CDS services, and with other
on--line reference information, CDS has become a major hub in the rapidly
evolving world of information retrieval in astronomy, developing efficient
tools to help astronomers to navigate in the world-wide `Virtual Observatory'
under construction, from data in the observatory archives to results published
in journals. The WWW interface to the CDS services is available at:
http://cdsweb.u-strasbg.fr/


  In streaming applications, doping improves the performance of
spatially-coupled low-density parity-check (SC-LDPC) codes by creating
reduced-degree check nodes in the coupled chain. We formulate a scaling law to
predict the bit and block error rate of periodically-doped semi-infinite
SC-LDPC code ensembles streamed over the binary erasure channel under sliding
window decoding for a given finite component block length. The scaling law
assumes that with some probability doping is equivalent to full termination and
triggers two decoding waves; otherwise, decoding performs as if the coupled
chain had not been doped at all. We approximate that probability and use the
derived scaling laws to predict the error rates of SC-LDPC code ensembles in
the presence of doping. The proposed scaling law provides accurate error rate
predictions. We further use it to show that in streaming applications periodic
doping can yield higher rates than periodic full termination for the same
error-correcting performance.


  We examine the prospects of the high redshift Long Gamma Ray Bursts (LGRB)
Hubble Diagram as a test of the basic cosmological principles. Analysis of the
Hubble Diagram allows us to test several fundamental cosmological principles
using the directly observed flux-distance-redshift relation. Modern LGRB data,
together with the correlation between the spectral peak energy and the
isotropic-equivalent radiated energy (the so-called Amati relation) can be used
for construction of the Hubble Diagram at the model-independent level. We
emphasise observational selection effects, which inevitably exist and distort
the theoretically predicted relations. An example is the weak and strong
gravitational lensing bias effect for high redshift LGRB in the presence of
limited observational sensitivity (Malmquist bias). After bias correction,
there is a tendency to vacuum dominated models with $\Omega_\Lambda \rightarrow
0.9$, $\Omega_\text{m} \rightarrow 0.1$. Forthcoming gamma-ray observations by
the space THESEUS mission together with ground and space based multimessenger
facilities will allow us to improve essentially the restrictions on alternative
basic principles of cosmological models.


  Most of the existing characterizations of the integral input-to-state
stability (iISS) property are not valid for time-varying or switched systems in
cases where converse Lyapunov theorems for stability are not available. This
note provides a characterization that is valid for switched and time-varying
systems, and shows that natural extensions of some of the existing
characterizations result in only sufficient but not necessary conditions. The
results provided also pinpoint suitable iISS gains and relate these to supply
functions and bounds on the function defining the system dynamics.


  Is "Gravity" a deformation of "Electromagnetism"? Deformation theory suggests
quantizing Special Relativity: formulate Quantum Information Dynamics
$SL(2,C)_h$-gauge theory of dynamical lattices, with unifying gauge ``group''
the quantum bundle obtained from the Hopf monopole bundle underlying the
quaternionic algebra and Dirac-Weyl spinors. The deformation parameter is the
inverse of light speed 1/c, in duality with Planck's constant h. Then mass and
electric charge form a complex coupling constant (m,q), for which the quantum
determinant of the quantum group $SL(2,C)_h$ expresses the interaction strength
as a linking number 2-form. There is room for both Coulomb constant $k_C$ and
Newton's gravitational constant $G_N$, exponentially weaker then the reciprocal
of the fine structure constant $\alpha$. Thus "Gravity" emerges already
"quantum", in the discrete framework of QID, based on the quantized complex
harmonic oscillator: the quantized qubit. All looks promising, but will the
details backup this "grand design scheme"?


  The coherent transduction between microwave and optical frequencies is
critical to interconnect superconducting quantum processors over long
distances. However, it is challenging to establish such a quantum interface
with high efficiency and small added noise based on the standard direct
conversion scheme. Here, we propose a transduction scheme based on
continuous-variable quantum teleportation. Reliable quantum information
transmission can be realized with an arbitrarily small cooperativity, in
contrast to the direct conversion scheme which requires a large minimum
cooperativity. We show that the teleportation-based scheme maintains a
significant rate advantage robustly for all values of cooperativity. We further
investigate the performance in the transduction of complex quantum states such
as cat states and Gottesman-Kitaev-Preskill(GKP) states and show that a higher
fidelity or success probability can be achieved with the teleportation-based
scheme. Our scheme significantly reduces the device requirement, and makes
quantum transduction between microwave and optical frequencies feasible in the
near future.


  The escape process of particles accelerated at supernova remnant (SNR) shocks
is one of the poorly understood aspects of the shock acceleration theory. Here
we adopt a phenomenological approach to study the particle escape and its
impact on the gamma-ray spectrum resulting from hadronic collisions both inside
and outside of a middle-aged SNR. Under the assumption that in the spatial
region immediately outside of the remnant the diffusion coefficient is
suppressed with respect to the average Galactic one, we show that a significant
fraction of particles are still located inside the SNR long time after their
nominal release from the acceleration region. This fact results into a
gamma-ray spectrum that resembles a broken power law, similar to those observed
in several middle-aged SNRs. Above the break, the spectral steepening is
determined by the diffusion coefficient outside of the SNR and by the time
dependence of maximum energy. Consequently, the comparison between the model
prediction and actual data will contribute to determining these two quantities,
the former being particularly relevant within the predictions of the gamma-ray
emission from the halo of escaping particles around SNRs which could be
detected with future Cherenkov telescope facilities. We also calculate the
spectrum of run-away particles injected into the Galaxy by an individual
remnant. Assuming that the acceleration stops before the SNR enters the
snowplow phase, we show that the released spectrum can be a featureless power
law only if the accelerated spectrum has a slope alpha > 4.


  We study pilgrim dark energy model by taking IR cut-offs as particle and
event horizons as well as conformal age of the universe. We derive evolution
equations for fractional energy density and equation of state parameters for
pilgrim dark energy. The phantom cosmic evolution is established in these
scenarios which is well supported by the cosmological parameters such as
deceleration parameter, statefinder parameters and phase space of
$\omega_\vartheta$ and $\omega'_\vartheta$. We conclude that the consistent
value of parameter $\mu$ is $\mu<0$ in accordance with the current Planck and
WMAP$9$ results.


  In previous work on galaxy clusters, several authors reported a discovery of
an unusual population of galaxies, which have spiral morphologies, but do not
show any star formation activity. These galaxies are called ``passive
spirals'', and have been interesting since it has been difficult to understand
the existence of such galaxies. Using a volume limited sample (0.05<z<0.1 and
Mr<-20.5; 25813 galaxies) of the Sloan Digital Sky Survey data, we have found
73 (0.28$\pm$0.03%) passive spiral galaxies and studied their environments. It
is found that passive spiral galaxies live in local galaxy density 1-2
Mpc$^{-2}$ and 1-10 cluster-centric virial radius. Thus the origins of passive
spiral galaxies are likely to be cluster related. These characteristic
environments coincide with the previously reported environment where galaxy
star formation rate suddenly declines and the so-called morphology-density
relation turns. It is likely that the same physical mechanism is responsible
for all of these observational results. The existence of passive spiral
galaxies suggests that a physical mechanism that works calmly is preferred to
dynamical origins such as major merger/interaction since such a mechanism can
destroy spiral arm structures. Compared with observed cluster galaxy evolution
such as the Butcher-Oemler effect and the morphological Butcher-Oemler effect,
passive spiral galaxies are likely to be a galaxy population in transition
between red, elliptical/S0 galaxies in low redshift clusters and blue, spiral
galaxies more numerous in higher redshift clusters.


  Given a smoothly bounded domain $\Omega\Subset\mathbb{R}^n$ with $n\ge 1$
odd, we study the blow-up of bounded sequences $(u_k)\subset
H^\frac{n}{2}_{00}(\Omega)$ of solutions to the non-local equation
$$(-\Delta)^\frac n2 u_k=\lambda_k u_ke^{\frac n2 u_k^2}\quad \text{in
}\Omega,$$ where $\lambda_k\to\lambda_\infty \in [0,\infty)$, and $H^{\frac
n2}_{00}(\Omega)$ denotes the Lions-Magenes spaces of functions $u\in
L^2(\mathbb{R}^n)$ which are supported in $\Omega$ and with
$(-\Delta)^\frac{n}{4}u\in L^2(\mathbb{R}^n)$. Extending previous works of
Druet, Robert-Struwe and the second author, we show that if the sequence
$(u_k)$ is not bounded in $L^\infty(\Omega)$, a suitably rescaled subsequence
$\eta_k$ converges to the function
$\eta_0(x)=\log\left(\frac{2}{1+|x|^2}\right)$, which solves the prescribed
non-local $Q$-curvature equation $$(-\Delta)^\frac n2 \eta
=(n-1)!e^{n\eta}\quad \text{in }\mathbb{R}^n$$ recently studied by Da
Lio-Martinazzi-Rivi\`ere when $n=1$, Jin-Maalaoui-Martinazzi-Xiong when $n=3$,
and Hyder when $n\ge 5$ is odd. We infer that blow-up can occur only if
$\Lambda:=\limsup_{k\to \infty}\|(-\Delta)^\frac n4 u_k\|_{L^2}^2\ge
\Lambda_1:= (n-1)!|S^n|$.


  A means to extract the fine-structure constant $\alpha$ from precision
spectroscopic data on one-electron ions is presented. We show that in an
appropriately weighted difference of the bound-electron $g$ factor and the
ground state energy, nuclear structural effects can be effectively suppressed.
This method is anticipated to deliver an independent value of $\alpha$ via
existing or near-future combined Penning trap and x-ray spectroscopic
technology, and enables decreasing the uncertainty of $\alpha$ by orders of
magnitude.


  We investigate the non-linear dynamics of a two-dimensional film flowing down
a finite heater, for a non-volatile and a volatile liquid. An oscillatory
instability is predicted beyond a critical value of Marangoni number using
linear stability theory. Continuation along the Marangoni number using
non-linear evolution equation is used to trace bifurcation diagram associated
with the oscillatory instability. Hysteresis, a characteristic attribute of a
sub-critical Hopf bifurcation, is observed in a critical parametric region. The
bifurcation is universally observed for both, a non-volatile film and a
volatile film.


  We address a recent conjecture according to which the relaxation time $\tau$
of a viscous liquid obeys density scaling ($\tau=F(\rho^\gamma/T)$ where $\rho$
is density) if the liquid is ``strongly correlating,'' i.e., has almost 100%
correlation between equilibrium virial and potential-energy fluctuations
[Pedersen {\it et al.}, PRL {\bf 100}, 011201 (2008)]. Computer simulations of
two model liquids - an asymmetric dumbbell model and the Lewis-Wahnstr\"om OTP
model - confirm the conjecture and demonstrate that the scaling exponent
$\gamma$ can be accurately predicted from equilibrium fluctuations.


  Generative retrieval stands out as a promising new paradigm in text retrieval
that aims to generate identifier strings of relevant passages as the retrieval
target. This generative paradigm taps into powerful generative language models,
distinct from traditional sparse or dense retrieval methods. However, only
learning to generate is insufficient for generative retrieval. Generative
retrieval learns to generate identifiers of relevant passages as an
intermediate goal and then converts predicted identifiers into the final
passage rank list. The disconnect between the learning objective of
autoregressive models and the desired passage ranking target leads to a
learning gap. To bridge this gap, we propose a learning-to-rank framework for
generative retrieval, dubbed LTRGR. LTRGR enables generative retrieval to learn
to rank passages directly, optimizing the autoregressive model toward the final
passage ranking target via a rank loss. This framework only requires an
additional learning-to-rank training phase to enhance current generative
retrieval systems and does not add any burden to the inference stage. We
conducted experiments on three public benchmarks, and the results demonstrate
that LTRGR achieves state-of-the-art performance among generative retrieval
methods. The code and checkpoints are released at
https://github.com/liyongqi67/LTRGR.


  Modern network virtualization platforms enable users to specify custom
topologies and arbitrary addressing schemes for their virtual networks. These
platforms have, however, been targeting the data center of a single provider,
which is insufficient to support (critical) applications that need to be
deployed across multiple trust domains, while enforcing diverse security
requirements. This paper addresses this limitation by presenting a novel
solution for the central resource allocation problem of network virtualization
-- the virtual network embedding, which aims to find efficient mappings of
virtual network requests onto the substrate network. We improve over the
state-of-the-art by considering security as a first-class citizen of virtual
networks, while enhancing the substrate infrastructure with resources from
multiple cloud providers. Our solution enables the definition of flexible
policies in three core elements: on the virtual links, where alternative
security compromises can be explored (e.g., encryption); on the virtual
switches, supporting various degrees of protection and redundancy if necessary;
and on the substrate infrastructure, extending it across multiple clouds,
including public and private facilities, with their inherently diverse trust
levels associated. We propose an optimal solution to this problem formulated as
a Mixed Integer Linear Program (MILP). The results of our evaluation give
insight into the trade-offs associated with the inclusion of security demands
into network virtualization. In particular, they provide evidence that
enhancing the user's virtual networks with security does not preclude high
acceptance rates and an efficient use of resources, and allows providers to
increase their revenues.


  We have analyzed the polarization properties of pulsars at an observing
frequency of 4.9 GHz. Together with low frequency data, we are able to trace
polarization profiles over more than three octaves into an interesting
frequency regime. At those high frequencies the polarization properties often
undergo important changes such as significant depolarization. A detailed
analysis allowed us to identify parameters, which regulate those changes. A
significant correlation was found between the integrated degree of polarization
and the loss of rotational energy E^dot. The data were also used to review the
widely established pulsar profile classification scheme of core- and cone-type
beams. We have discovered the existence of pulsars which show a strongly
increasing degree of circular polarization towards high frequencies. Previously
unpublished average polarization profiles, recorded at the 100m Effelsberg
radio telescope, are presented for 32 radio pulsars at 4.9 GHz. The data were
used to derive polarimetric parameters and emission heights.


  We consider the differential entropy of probability measures absolutely
continuous with respect to a given $\sigma$-finite reference measure on an
arbitrary measurable space. We state the asymptotic equipartition property in
this general case; the result is part of the folklore but our presentation is
to some extent novel. Then we study a general framework under which such
entropies satisfy a chain rule: disintegrations of measures. We give an
asymptotic interpretation for conditional entropies in this case. Finally, we
apply our result to Haar measures in canonical relation.


  We examine the dynamics of circulating modes of a Bose-Einstein condensate
confined in toroidal lattice. Nonlinearity due to interactions leads to
criticality that separates oscillatory and self-trapped phases among
counter-propagating modes which however share the same physical space. In the
mean-field limit, the criticality is found to substantially enhance sensitivity
to rotation of the system. Analysis of the quantum dynamics reveals the
fluctuations near criticality are significant, that we explain using
spin-squeezing formalism visualized on a Bloch sphere. We utilize the squeezing
to propose a Ramsey interferometric scheme that suppresses fluctuation in the
relevant quadrature sensitive to rotation.


  Building phenotype models using electronic health record (EHR) data
conventionally requires manually labeled cases and controls. Assigning labels
is labor intensive and, for some phenotypes, identifying gold-standard controls
is prohibitive. To facilitate comprehensive clinical decision support and
research, we sought to develop an accurate EHR phenotyping approach that
assesses its performance without a validation set. Our framework relies on
specifying a random subset of cases, potentially using an anchor variable that
has excellent positive predictive value and sensitivity that is independent of
predictors. We developed a novel maximum likelihood approach that efficiently
leverages data from anchor-positive and unlabeled patients to develop logistic
regression phenotyping models. Additionally, we described novel statistical
methods for estimating phenotyping prevalence and assessing model calibration
and predictive performance measures. Theoretical and simulation studies
indicated our method generates accurate predicted probabilities, leading to
excellent discrimination and calibration, and consistent estimates of phenotype
prevalence and anchor sensitivity. The method appeared robust to minor
lack-of-fit and the proposed calibration assessment detected major lack-of-fit.
We applied our method to EHR data to develop a preliminary model for
identifying patients with primary aldosteronism, which achieved an AUC of 0.99
and PPV of 0.8. We developed novel statistical methods for accurate model
development and validation with minimal manual labeling, facilitating
development of scalable, transferable, semi-automated case labeling and
practice-specific models. Our EHR phenotyping approach decreases
labor-intensive manual phenotyping and annotation, which should enable broader
model development and dissemination for EHR clinical decision support and
research.


  So far, quantum properties of N=1/2 nonanticommutative (NAC) super
Yang--Mills theories have been investigated in the WZ gauge. The gauge
independence of the results requires assuming that at the quantum level
supergauge invariance is not broken by nonanticommutative geometry. In this
paper we use an alternative approach which allows studying these theories in a
manifestly gauge independent superspace setup. This is accomplished by
generalizing the background field method to the NAC case, by moving to a
momentum superspace where star products are treated as exponential factors and
by developing momentum supergraph techniques. We compute the one--loop gauge
effective action for NAC U(N) gauge theories with matter in the adjoint
representation. Despite the appearance of divergent contributions which break
(super)gauge invariance, we prove that the effective action at this order is
indeed invariant.


  We point out a relation between the dissipative spin-transfer-torque
parameter $\beta$ and the contribution of magnon drag to the thermoelectric
power in conducting ferromagnets. Using this result we estimate $\beta$ in iron
at low temperatures, where magnon drag is believed to be the dominant
contribution to the thermopower. Our results may be used to determine $\beta$
from magnon-drag-thermopower experiments, or, conversely, to infer the strength
of magnon drag via experiments on spin transfer.


  We propose a new pattern-matching algorithm for matching CCD images to a
stellar catalogue based statistical method in this paper. The method of
constructing star pairs can greatly reduce the computational complexity
compared with the triangle method. We use a subsample of the brightest objects
from the image and reference catalogue, and then find a coordinate
transformation between the image and reference catalogue based on the
statistical information of star pairs. Then all the objects are matched based
on the initial plate solution. The matching process can be accomplished in
several milliseconds for the observed images taken by Yunnan observatory 1-m
telescope.


  We study transfer learning for estimation in latent variable network models.
In our setting, the conditional edge probability matrices given the latent
variables are represented by $P$ for the source and $Q$ for the target. We wish
to estimate $Q$ given two kinds of data: (1) edge data from a subgraph induced
by an $o(1)$ fraction of the nodes of $Q$, and (2) edge data from all of $P$.
If the source $P$ has no relation to the target $Q$, the estimation error must
be $\Omega(1)$. However, we show that if the latent variables are shared, then
vanishing error is possible. We give an efficient algorithm that utilizes the
ordering of a suitably defined graph distance. Our algorithm achieves $o(1)$
error and does not assume a parametric form on the source or target networks.
Next, for the specific case of Stochastic Block Models we prove a minimax lower
bound and show that a simple algorithm achieves this rate. Finally, we
empirically demonstrate our algorithm's use on real-world and simulated graph
transfer problems.


  We present results from ongoing science projects conducted by members of the
Faulkes Telescope (FT) team and Las Cumbres Observatory Global Telescope
(LCOGT). Many of these projects incorporate observations carried out and
analysed by FT users, comprising amateur astronomers and schools.
  We also discuss plans for the further development of the LCOGT network.


  This report introduce our work on Egocentric 3D Hand Pose Estimation
workshop. Using AssemblyHands, this challenge focuses on egocentric 3D hand
pose estimation from a single-view image. In the competition, we adopt ViT
based backbones and a simple regressor for 3D keypoints prediction, which
provides strong model baselines. We noticed that Hand-objects occlusions and
self-occlusions lead to performance degradation, thus proposed a non-model
method to merge multi-view results in the post-process stage. Moreover, We
utilized test time augmentation and model ensemble to make further improvement.
We also found that public dataset and rational preprocess are beneficial. Our
method achieved 12.21mm MPJPE on test dataset, achieve the first place in
Egocentric 3D Hand Pose Estimation challenge.


  We study totally geodesic codimension 1 smooth foliations on Lorentzian
manifold. We are in particular interested by the relations between riemannian
flows and geodesic foliations. We prove that, up to a 2-cover, any Seifert
bundle admit such a foliation.


  We analyse mesons at finite temperature in a chiral, confining string dual.
The temperature dependence of low-spin as well as high-spin meson masses is
shown to exhibit a pattern familiar from the lattice. Furthermore, we find the
dissociation temperature of mesons as a function of their spin, showing that at
a fixed quark mass, mesons with larger spins dissociate at lower temperatures.
The Goldstone bosons associated with chiral symmetry breaking are shown to
disappear above the chiral symmetry restoration temperature. Finally, we show
that holographic consideration imply that large-spin mesons do not experience
drag effects when moving through the quark gluon plasma. They do, however, have
a maximum velocity for fixed spin, beyond which they dissociate.


  We discuss evolution of the Fermi surface (FS) topology with doping in
electron doped cuprates within the framework of a one-band Hubbard Hamiltonian,
where antiferromagnetism and superconductivity are assumed to coexist in a
uniform phase. In the lightly doped insulator, the FS consists of electron
pockets around the $(\pi,0)$ points. The first change in the FS topology occurs
in the optimally doped region when an additional hole pocket appears at the
nodal point. The second change in topology takes place in the overdoped regime
($\sim18%$) where antiferromagnetism disappears and a large
$(\pi,\pi)$-centered metallic FS is formed. Evidence for these two topological
transitions is found in recent Hall effect and penetration depth experiments on
Pr$_{2-x}$Ce$_{x}$CuO$_{4-\delta}$ (PCCO) and with a number of spectroscopic
measurements on Nd$_{2-x}$Ce$_{x}$CuO$_{4-\delta}$ (NCCO).


  We propose an optimized algorithm for the numerical simulation of two-time
correlation functions by means of stochastic wave functions. As a first
application, we investigate the two-time correlation function of a nonlinear
optical parametric oscillator.


  Automatic evaluation metrics for generated texts play an important role in
the NLG field, especially with the rapid growth of LLMs. However, existing
metrics are often limited to specific scenarios, making it challenging to meet
the evaluation requirements of expanding LLM applications. Therefore, there is
a demand for new, flexible, and effective metrics. In this study, we introduce
RepEval, the first metric leveraging the projection of LLM representations for
evaluation. RepEval requires minimal sample pairs for training, and through
simple prompt modifications, it can easily transition to various tasks. Results
on ten datasets from three tasks demonstrate the high effectiveness of our
method, which exhibits stronger correlations with human judgments compared to
previous metrics, even outperforming GPT-4. Our work underscores the richness
of information regarding text quality embedded within LLM representations,
offering insights for the development of new metrics.


  We present a theory of the $b$-function (or Bernstein-Sato polynomial) in
positive characteristic. Let $f$ be a non-constant polynomial with coefficients
in a perfect field $k$ of characteristic $p>0.$ Its $b$-function $b_f$ is
defined to be an ideal of the algebra of continuous $k$-valued functions on
$\mathbb{Z}_p.$ The zero-locus of the $b$-function is thus naturally
interpreted as a subset of $\mathbb{Z}_p,$ which we call the set of roots of
$b_f.$ We prove that $b_f$ has finitely many roots and that they are negative
rational numbers. Our construction builds on an earlier work of Musta\c{t}\u{a}
and is in terms of $D$-modules, where $D$ is the ring of Grothendieck
differential operators. We use the Frobenius to obtain finiteness properties of
$b_f$ and relate it to the test ideals of $f.$


  We propose a generalized formulation of the Scalar Weak Gravity Conjecture
(SWGC) based on the analogy with the derivation of the Gauge Weak Gravity
Conjecture (GWGC). We discuss some phenomenological implications of this
Generalized SWGC, including the scale of New Physics (NP) when applied to the
SM Higgs sector, and the bounds on the axion's couplings to fermions and the
photon when applied to the axion. The Generalized SWGC constraints rule out
most of the parameter space of axion-nucleon couplings, leaving only a tiny
parameter space.


  By systematically investigating the relaxation behavior of a model metallic
glass based on the extensive molecular dynamics (MD) simulations combined with
the dynamic mechanical spectroscopy method, a pronounced ultra-low temperature
peak on the loss modulus spectrum was discovered for the first time in MD
simulations. It was found that the relation peak occurs at a much lower
temperature than the typical temperature for the conventional beta relation
peak as reported in the literature. According to the atomic displacement
analysis, we unravel that the reversible atomic motions, rather than the
thermal vibrations or local structural rearrangements, mainly contribute to
this relaxation peak. We further identify the atomic level mechanism of this
fast relaxation process by characterizing the local geometrical anisotropy.
Furthermore, by tracing the dynamic behaviors of these "reversible" atoms, we
demonstrate the intrinsic hierarchy of the local relaxation modes, which are
triggered by atomic vibrations and gradually developed to the reversible and
irreversible atomic movements. Our findings shed light on a general picture of
the relaxation processes in metallic glasses.


  We present a phenomenological model for the initial conditions needed in a
one-fluid hydrodynamical description of ultrarelativistic nuclear collisions at
CERN--SPS. The basic ingredient is the parametrization of the baryon stopping,
i.e. the rapidity distribution, as a function of the thickness of the nuclei.
We apply the model to S + S and Pb + Pb collisions and find after
hydrodynamical evolution reasonable agreement with the data.


  Starting with work of Serre, Katz, and Swinnerton-Dyer, theta operators have
played a key role in the study of $p$-adic and $\bmod p$ modular forms and
Galois representations. This paper achieves two main results for theta
operators on automorphic forms on PEL-type Shimura varieties: 1) the analytic
continuation at unramified primes $p$ to the whole Shimura variety of the
$\bmod p$ reduction of $p$-adic Maass--Shimura operators {\it a priori} defined
only over the $\mu$-ordinary locus, and 2) the construction of new $\bmod p$
theta operators that do not arise as the $\bmod p$ reduction of Maass--Shimura
operators. While the main accomplishments of this paper concern the geometry of
Shimura varieties and consequences for differential operators, we conclude with
applications to Galois representations. Our approach involves a careful
analysis of the behavior of Shimura varieties and enables us to obtain more
general results than allowed by prior techniques, including for arbitrary
signature, vector weights, and unramified primes in CM fields of arbitrary
degree.


  This workshop brought together international experts in the research area of
strangeness in nuclei physics, working on theory as well as on experiments, to
discuss the present status, to develop new methods of analysis and to have the
opportunity for brainstorming towards future studies, going towards a deeper
understanding of the hot topics in the low-energy QCD in the strangeness
sector.


  We examine the benefits of visual context in training neural language models
to perform next-word prediction. A multi-modal neural architecture is
introduced that outperform its equivalent trained on language alone with a 2\%
decrease in perplexity, even when no visual context is available at test.
Fine-tuning the embeddings of a pre-trained state-of-the-art bidirectional
language model (BERT) in the language modeling framework yields a 3.5\%
improvement. The advantage for training with visual context when testing
without is robust across different languages (English, German and Spanish) and
different models (GRU, LSTM, $\Delta$-RNN, as well as those that use BERT
embeddings). Thus, language models perform better when they learn like a baby,
i.e, in a multi-modal environment. This finding is compatible with the theory
of situated cognition: language is inseparable from its physical context.


  Let $M$ be a three-dimensional contact manifold and $\psi:D\setminus\{0\}\to
M\times{\Bbb R}$ a finite-energy pseudoholomorphic map from a punctured disc in
${\Bbb C}$, that is asymptotic to a periodic orbit of the Reeb vector field.
This article examines conditions under which smooth coordinates may be defined
in a tubular neighbourhood of the orbit such that $\psi$ resembles a
holomorphic curve, invoking comparison with the theory of topological linking
of plane complex algebroid curves near a singularity. Examples of this
behaviour which are studied in some detail include pseudoholomorphic maps into
${\Bbb E}_{p,q}\times{\Bbb R}$, where ${\Bbb E}_{p,q}$ denotes a rational
ellipsoid with contact structure induced by the complex structure of the
ambient ${\Bbb C}^{2}$. Contact structures arising from non-standard
circle-fibrations of the three-sphere are also examined.


  The problem of characterizing the capacity region for Gaussian broadcast
channels with receiver message side information appears difficult and remains
open for N >= 3 receivers. This paper proposes a joint network and
Gelfand-Pinsker coding method for 3-receiver cases. Using the method, we
establish a unified inner bound on the capacity region of 3-receiver Gaussian
broadcast channels under general message side information configuration. The
achievability proof of the inner bound uses an idea of joint interference
cancelation, where interference is canceled by using both dirty-paper coding at
the encoder and successive decoding at some of the decoders. We show that the
inner bound is larger than that achieved by state of the art coding schemes. An
outer bound is also established and shown to be tight in 46 out of all 64
possible cases.


  It is well known that measurements performed on spatially separated entangled
quantum systems can give rise to correlations that are non-local, in the sense
that a Bell inequality is violated. They cannot, however, be used for
super-luminal signalling. It is also known that it is possible to write down
sets of ``super-quantum'' correlations that are more non-local than is allowed
by quantum mechanics, yet are still non-signalling. Viewed as an information
theoretic resource, super-quantum correlations are very powerful at reducing
the amount of communication needed for distributed computational tasks. An
intriguing question is why quantum mechanics does not allow these more powerful
correlations. We aim to shed light on the range of quantum possibilities by
placing them within a wider context. With this in mind, we investigate the set
of correlations that are constrained only by the no-signalling principle. These
correlations form a polytope, which contains the quantum correlations as a
(proper) subset. We determine the vertices of the no-signalling polytope in the
case that two observers each choose from two possible measurements with d
outcomes. We then consider how interconversions between different sorts of
correlations may be achieved. Finally, we consider some multipartite examples.


  I present a measurement of the W boson mass (M_W) and width (G_W) using 200
and 350 pb-1 of CDF Run II data respectively. The measurements, performed in
both the electron and muon decay channels, rely on a fit to the W transverse
mass distribution. We measure M_W = 80413 +/- 48 MeV and G_W = 2032 +/- 71 MeV
which represent the world's single most precise measurements to date.


  Training vision or language models on large datasets can take days, if not
weeks. We show that averaging the weights of the k latest checkpoints, each
collected at the end of an epoch, can speed up the training progression in
terms of loss and accuracy by dozens of epochs, corresponding to time savings
up to ~68 and ~30 GPU hours when training a ResNet50 on ImageNet and
RoBERTa-Base model on WikiText-103, respectively. We also provide the code and
model checkpoint trajectory to reproduce the results and facilitate research on
reusing historical weights for faster convergence.


  One of the algebraic structures that has emerged recently in the study of the
operator product expansions of chiral fields in conformal field theory is that
of a Lie conformal algebra. A Lie pseudoalgebra is a generalization of the
notion of a Lie conformal algebra for which C[\partial] is replaced by the
universal enveloping algebra H of a finite-dimensional Lie algebra. The finite
(i.e., finitely generated over H) simple Lie pseudoalgebras were classified in
our previous work. The present paper is the second in our series on
representation theory of simple Lie pseudoalgebras. In the first paper we
showed that any finite irreducible module over a simple Lie pseudoalgebra of
type W or S is either an irreducible tensor module or the kernel of the
differential in a member of the pseudo de Rham complex. In the present paper we
establish a similar result for Lie pseudoalgebras of type K, with the pseudo de
Rham complex replaced by a certain reduction called the contact pseudo de Rham
complex. This reduction in the context of contact geometry was discovered by
Rumin.


  We demonstrate how adversaries with unbounded computing resources can break
Quantum Key Distribution (QKD) protocols which employ a particular message
authentication code suggested previously. This authentication code, featuring
low key consumption, is not Information-Theoretically Secure (ITS) since for
each message the eavesdropper has intercepted she is able to send a different
message from a set of messages that she can calculate by finding collisions of
a cryptographic hash function. However, when this authentication code was
introduced it was shown to prevent straightforward Man-In-The-Middle (MITM)
attacks against QKD protocols.
  In this paper, we prove that the set of messages that collide with any given
message under this authentication code contains with high probability a message
that has small Hamming distance to any other given message. Based on this fact
we present extended MITM attacks against different versions of BB84 QKD
protocols using the addressed authentication code; for three protocols we
describe every single action taken by the adversary. For all protocols the
adversary can obtain complete knowledge of the key, and for most protocols her
success probability in doing so approaches unity.
  Since the attacks work against all authentication methods which allow to
calculate colliding messages, the underlying building blocks of the presented
attacks expose the potential pitfalls arising as a consequence of non-ITS
authentication in QKD-postprocessing. We propose countermeasures, increasing
the eavesdroppers demand for computational power, and also prove necessary and
sufficient conditions for upgrading the discussed authentication code to the
ITS level.


  Super hydrophobic surfaces have been the focus of research in the recent
years.One of the reasons for this is the self cleaning property of these
surfaces which emerges from the ability of the droplets to roll freely over
them.However majority of the studies available in literature are on the static
wetting behavior of liquid droplets on such surfaces and the physics of the
motion of droplets has not been studied exhaustively either theoretically or
experimentally.In the present study droplet motion on super hydrophobic
surfaces has been modeled to analyze the sliding/ rolling characteristics of
the droplet motion.A non-dimensional number is proposed to indicate whether a
given droplet would tend to roll or slide more on a given super hydrophobic
surface.We refer to this number as 'Slip Reynolds' number. Simulations of
droplet motion were carried out with different surface and droplet
characteristics leading to a unique value of this number corresponding to
sliding/rolling behavior.The applicability of this number was tested with
available experiments from literature.


  In this conference contribution, we discuss the influence of
gluon-bremsstrahlung damping in hot, absorptive QCD matter on the heavy-quark
radiation spectra. Within our Monte-Carlo implementation for the description of
the heavy-quark in-medium propagation we demonstrate that as a consequence of
gluon damping the quenching of heavy quarks becomes significantly affected at
higher transverse momenta.


  During the process of computed tomography (CT), metallic implants often cause
disruptive artifacts in the reconstructed images, impeding accurate diagnosis.
Several supervised deep learning-based approaches have been proposed for
reducing metal artifacts (MAR). However, these methods heavily rely on training
with simulated data, as obtaining paired metal artifact CT and clean CT data in
clinical settings is challenging. This limitation can lead to decreased
performance when applying these methods in clinical practice. Existing
unsupervised MAR methods, whether based on learning or not, typically operate
within a single domain, either in the image domain or the sinogram domain. In
this paper, we propose an unsupervised MAR method based on the diffusion model,
a generative model with a high capacity to represent data distributions.
Specifically, we first train a diffusion model using CT images without metal
artifacts. Subsequently, we iteratively utilize the priors embedded within the
pre-trained diffusion model in both the sinogram and image domains to restore
the degraded portions caused by metal artifacts. This dual-domain processing
empowers our approach to outperform existing unsupervised MAR methods,
including another MAR method based on the diffusion model, which we have
qualitatively and quantitatively validated using synthetic datasets. Moreover,
our method demonstrates superior visual results compared to both supervised and
unsupervised methods on clinical datasets.


  We establish results about the second cohomology with coefficients in the
trivial module, symmetric invariant bilinear forms and derivations of a Lie
algebra extended over a commutative associative algebra without unit. These
results provide a simple unified approach to a number of questions treated
earlier in completely separated ways: periodization of semisimple Lie algebras
(Anna Larsson), derivation algebras, with prescribed semisimple part, of
nilpotent Lie algebras (Benoist), and presentations of affine Kac-Moody
algebras.


  The dependence of the surface plasmons resonance (SPR) frequency on the size
of gold nanoparticles (GNPs) is experimentally studied. The measured data for
the SPR frequency by UV-Vis spectroscopy and GNPs diameter by Dynamic Light
Scattering (DLS), Transmission Electron Microscopy (TEM) and Atomic Force
Microscopy (AFM) are collected in the course of classical citrate GNPs
synthesis. The relationship between the GNPs size and the blue shift of the
light absorption is presented. They are fitted by an equation with a single
free parameter, the dielectric permittivity of the surrounding media. Thus, the
refractive index of the surrounding media is determined, which characterizes
the GNPs surface shell.


  Extensive results from the commissioning phase of PUEO, the adaptive optics
instrument adaptor for the Canada-France-Hawaii telescope, are presented and
discussed. Analyses of more than 750 images recorded with a CCD and a near-IR
camera on 16 nights in wavelengths from B to H are used to derive the
properties of the compensated wavefront and images in a variety of conditions.
The performance characteristics of the system are analyzed and presented in
several ways, in terms of delivered Strehl ratios, full-width-half-maxima, and
quantities describing the improvements of both. A qualitative description is
given of how the properties of the corrected images result from the structure
function of the compensated phase. Under median seeing conditions, PUEO
delivers essentially diffraction-limited images at H and K, images with FWHM
~0.1" at J and I, and provides significant gains down to B, with guide stars as
faint as R = 14. During good conditions, substantial gains were realized with
guide stars as faint as R = 17. A simple user-interface and software which
automatically and continuously optimizes the mode gains during observations
makes the operational efficiency extremely high. A few astronomical examples
are briefly discussed.


  We consider a finite ferroelectric superlattice in which the elementary unit
cell is made up of l atomic layers of type A and n atomic layers of type B.
Based on the transverse Ising model we examine the phase transition properties
of the ferroelectric superlattice. Using the transfer matrix method we derive
the equation for the Curie temperature of the superlattice. Numerical results
are given for the dependence of the Curie temperature on the thickness and
exchange constants of the superlattice.


  In this work, we present a new model for the heat conductivity of porous dust
layers in vacuum, based on an existing solution of the heat transfer equation
of single spheres in contact. This model is capable of distinguishing between
two different types of dust layers: dust layers composed of single particles
(simple model) and dust layers consisting of individual aggregates (complex
model). Additionally, we describe laboratory experiments, which were used to
measure the heat conductivity of porous dust layers, in order to test the
model. We found that the model predictions are in an excellent agreement with
the experimental results, if we include radiative heat transport in the model.
This implies that radiation plays an important role for the heat transport in
porous materials. Furthermore, the influence of this new model on the Hertz
factor are demonstrated and the implications of this new model on the modeling
of cometary activity are discussed. Finally, the limitations of this new model
are critically reviewed.


  We consider the totally asymmetric simple exclusion process with open
boundaries, at the edge of the maximal current phase. Using analytic
continuations from the known stationary eigenvalue, we obtain exact expressions
for the spectral gaps in the limit of large system size. The underlying Riemann
surface,generated by modified Lambert functions, interpolates between the one
for periodic TASEP and the one for open TASEP in the maximal current phase.


  We present results for non-perturbative renormalization (NPR) factors for
staggered fermion bilinears of arbitrary spin and taste. We use "covariant"
bilinears which transform irreducibly under the lattice translation and
rotation group, and thus do not mix. We form ~ 30 ratios which have no
anomalous dimensions, and compare the NPR results to those from 1-loop
perturbation theory. We also compare the absolute renormalization factors
(which, in general, do have anomalous dimensions) to 1-loop perturbation
theory. We use asqtad and HYP-smeared staggered valence fermions on the coarse
MILC asqtad lattices.


  We report observations of the z = 3.87 broad absorption line quasar APM
08279+5255 (Irwin et al. 1998) with the Adaptive Optics Bonnette (AOB) of the
Canada-France-Hawaii Telescope. The object is found to be a double source. The
separation of the two images is 0.35" +/- 0.02" and the intensity ratio
I_{north}/I_{south} = 1.21 +/- 0.25 in the H-band. No other image is detected
down to H(5sigma) = 21.3 within 10" from the double image. Strong support for
the lensing hypothesis comes from the uniformity of the quasar spectrum as a
function of spatial position in the image obtained with the integral field
spectrograph OASIS at CFHT. From the 2D-spectroscopy, narrow-band images are
reconstructed over the wavelength range 5600-6200A to search for emission-line
objects in a field of 15"x12" around the quasar. We find no such object to a
limit of 6x10^{-17} erg cm^{-2} s^{-1}. We use the images centered on the
deepest absorption lines of the Ly-alpha forest to dim the quasar and to
increase the sensitivity closer to the line of sight. One of the images,
centered at 5766.4A, exhibits a 3sigma excess 1.5" from the quasar to the
north-east.


  High demand for computation resources severely hinders deployment of
large-scale Deep Neural Networks (DNN) in resource constrained devices. In this
work, we propose a Structured Sparsity Learning (SSL) method to regularize the
structures (i.e., filters, channels, filter shapes, and layer depth) of DNNs.
SSL can: (1) learn a compact structure from a bigger DNN to reduce computation
cost; (2) obtain a hardware-friendly structured sparsity of DNN to efficiently
accelerate the DNNs evaluation. Experimental results show that SSL achieves on
average 5.1x and 3.1x speedups of convolutional layer computation of AlexNet
against CPU and GPU, respectively, with off-the-shelf libraries. These speedups
are about twice speedups of non-structured sparsity; (3) regularize the DNN
structure to improve classification accuracy. The results show that for
CIFAR-10, regularization on layer depth can reduce 20 layers of a Deep Residual
Network (ResNet) to 18 layers while improve the accuracy from 91.25% to 92.60%,
which is still slightly higher than that of original ResNet with 32 layers. For
AlexNet, structure regularization by SSL also reduces the error by around ~1%.
Open source code is in https://github.com/wenwei202/caffe/tree/scnn


  We study the nonlinear perturbation of a high-order exceptional point (EP) of
the order equal to the system site number $L$ in a Hatano-Nelson model with
unidirectional hopping and Kerr nonlinearity. Notably, We find a class of
discrete breathers that aggregate to one boundary, here named as skin discrete
breathers (SDBs). The nonlinear spectrum of these SDBs shows a hierarchical
power-law scaling near the EP. Specifically, the response of nonlinear energy
to the perturbation is given by $E_m\propto \varGamma^{\alpha_{m}}$, where
$\alpha_m=3^{m-1}$ is the power with $m=1,\cdots,L$ labeling the nonlinear
energy bands. This is in sharp contrast to the $L$-th root of a linear
perturbation in general. These SDBs decay in a double-exponential manner,
unlike the edge states or skin modes in linear systems, which decay
exponentially. Furthermore, these SDBs can survive over the full range of
nonlinearity strength and are continuously connected to the self-trapped states
in the limit of large nonlinearity. They are also stable, as confirmed by a
defined nonlinear fidelity of an adiabatic evolution from the stability
analysis. As nonreciprocal nonlinear models may be experimentally realized in
various platforms, such as the classical platform of optical waveguides, where
Kerr nonlinearity is naturally present, and the quantum platform of optical
lattices with Bose-Einstein condensates, our analytical results may inspire
further exploration of the interplay between nonlinearity and non-Hermiticity,
particularly on high-order EPs, and benchmark the relevant simulations.


  Recognizing and comprehending human actions and gestures is a crucial
perception requirement for robots to interact with humans and carry out tasks
in diverse domains, including service robotics, healthcare, and manufacturing.
Event cameras, with their ability to capture fast-moving objects at a high
temporal resolution, offer new opportunities compared to standard action
recognition in RGB videos. However, previous research on event camera action
recognition has primarily focused on sensor-specific network architectures and
image encoding, which may not be suitable for new sensors and limit the use of
recent advancements in transformer-based architectures. In this study, we
employ a computationally efficient model, namely the video transformer network
(VTN), which initially acquires spatial embeddings per event-frame and then
utilizes a temporal self-attention mechanism. In order to better adopt the VTN
for the sparse and fine-grained nature of event data, we design
Event-Contrastive Loss ($\mathcal{L}_{EC}$) and event-specific augmentations.
Proposed $\mathcal{L}_{EC}$ promotes learning fine-grained spatial cues in the
spatial backbone of VTN by contrasting temporally misaligned frames. We
evaluate our method on real-world action recognition of N-EPIC Kitchens
dataset, and achieve state-of-the-art results on both protocols - testing in
seen kitchen (\textbf{74.9\%} accuracy) and testing in unseen kitchens
(\textbf{42.43\% and 46.66\% Accuracy}). Our approach also takes less
computation time compared to competitive prior approaches, which demonstrates
the potential of our framework \textit{EventTransAct} for real-world
applications of event-camera based action recognition. Project Page:
\url{https://tristandb8.github.io/EventTransAct_webpage/}


  We describe a formalism for calculating electroweak Sudakov logarithms in the
Coulomb gauge. This formalism is applicable to arbitrary electroweak processes.
For illustration we focus on the specific reactions e^+e^- -> f \bar{f} and
e^+e^- -> W_T^+W_T^-, W_L^+W_L^-, which contain all the salient details of
dealing with the various types of particles. We discuss an explicit two-loop
calculation and have a critical look at the (non-)exponentiation and
factorisation properties of the Sudakov logarithms in the Standard Model.


  Let $\mathcal{L}$ be a fixed $d$-dimensional lattice. We study the
localization properties of solutions of the stationary Schr\"odinger equation
with a positive $L^\infty$ potential on tori $\mathbb{R}^d/L\mathcal{L}$ in the
limit, as $L\to\infty$, for dimension $d \leq 3$. We show that the probability
measures associated with $L^2$-normalized solutions, with eigenvalue $E$ near
the bottom of the spectrum, satisfy an algebraic delocalization theorem which
states that these probability measures cannot be localized inside a ball of
radius $r = o(E^{-1/4+\epsilon})$, unless localization occurs with a
sufficiently slow algebraic decay. In particular, we apply our result to
Schr\"odinger operators modeling disordered systems, such as the d-dimensional
continuous Anderson- Bernoulli model, where almost sure exponential
localization of eigenfunctions, in the limit as $E \to 0$, was proved by
Bourgain-Kenig in dimension $d \geq 2$, and show that our theorem implies an
algebraic blow-up of localization length in this limit.


  Nuclei with magic numbers serve as important benchmarks in nuclear theory. In
addition, neutron-rich nuclei play an important role in the astrophysical rapid
neutron-capture process (r-process). 78Ni is the only doubly-magic nucleus that
is also an important waiting point in the r-process, and serves as a major
bottleneck in the synthesis of heavier elements. The half-life of 78Ni has been
experimentally deduced for the first time at the Coupled Cyclotron Facility of
the National Superconducting Cyclotron Laboratory at Michigan State University,
and was found to be 110 (+100 -60) ms. In the same experiment, a first
half-life was deduced for 77Ni of 128 (+27 -33) ms, and more precise half-lives
were deduced for 75Ni and 76Ni of 344 (+20 -24) ms and 238 (+15 -18) ms
respectively.


  A bar-joint framework $(G,p)$ in the Euclidean space $\mathbb{E}^d$ is
globally rigid if it is the unique realisation, up to rigid congruences, of $G$
in $\mathbb{E}^d$ with the edge lengths of $(G,p)$. Building on key results of
Hendrickson and Connelly, Jackson and Jord\'{a}n gave a complete combinatorial
characterisation of when a generic framework is global rigidity in
$\mathbb{E}^2$. We prove an analogous result when the Euclidean norm is
replaced by any norm that is analytic on $\mathbb{R}^2 \setminus \{0\}$. More
precisely, we show that a graph $G=(V,E)$ is globally rigid in a non-Euclidean
analytic normed plane if and only if $G$ is 2-connected and $G-e$ contains 2
edge-disjoint spanning trees for all $e\in E$. The main technical tool is a
recursive construction of 2-connected and redundantly rigid graphs in analytic
normed planes. We also obtain some sufficient conditions for global rigidity as
corollaries of our main result and prove that the analogous necessary
conditions hold in $d$-dimensional analytic normed spaces.


  In this paper, we determine the radii of $\beta -$uniformly convex of order
$\alpha $ for three kinds of normalized Lommel and Struve functions of the
first kind. In the cases considered the normalized Lommel and Struve functions
are $\beta -$uniformly convex functions of order $\alpha $ on the determined
disks. The basic tool of this study is Lommel and Struve functions in series.


  In argumentative discourse, persuasion is often achieved by refuting or
attacking others arguments. Attacking is not always straightforward and often
comprise complex rhetorical moves such that arguers might agree with a logic of
an argument while attacking another logic. Moreover, arguer might neither deny
nor agree with any logics of an argument, instead ignore them and attack the
main stance of the argument by providing new logics and presupposing that the
new logics have more value or importance than the logics present in the
attacked argument. However, no existing studies in the computational
argumentation capture such complex rhetorical moves in attacks or the
presuppositions or value judgements in them. In order to address this gap, we
introduce LPAttack, a novel annotation scheme that captures the common modes
and complex rhetorical moves in attacks along with the implicit presuppositions
and value judgements in them. Our annotation study shows moderate
inter-annotator agreement, indicating that human annotation for the proposed
scheme is feasible. We publicly release our annotated corpus and the annotation
guidelines.


  The main result of this paper is the description of asymptotics along rays in
weight space of traces of equivariant Toeplitz operators composed with
quantomorphisms for torus actions. The main ingredient in the proof is the
microlocal analysis of the equivariant Szego kernels.


  The evolution of a dark matter halo in a dark matter only simulation is
governed purely byNewtonian gravity, making a clean testbed to determine what
halo properties drive its fate.Using machine learning, we predict the survival,
mass loss, final position, and merging time of subhalos within a cosmological
N-body simulation, focusing on what instantaneous initial features of the halo,
interaction, and environment matter most. Survival is well predicted, with our
model achieving 96.5% accuracy using only 3 model inputs from the initial
interaction.However, the mass loss, final location, and merging times are much
more stochastic processes, with significant margins of error between the true
and predicted quantities for much of our sample. The redshift, impact angle,
relative velocity, and the masses of the host and subhalo are the only relevant
initial inputs for determining subhalo evolution. In general, subhalos that
enter their hosts at a mid-range of redshifts (typically z = 0.67-0.43) are the
most challenging to make predictions for, across all of our final outcomes.
Subhalo orbits that come in more perpendicular to the host are also easier to
predict, except for in the case of predicting disruption, where the opposite
appears to be true. We conclude that the detailed evolution of individual
subhalos within N-body simulations is quite difficult to predict, pointing to a
stochasticity in the merging process. We discuss implications for both
simulations and observations


  We study the impact of dimension-six operators on single- and double-Higgs
production rates via gluon fusion at the Large Hadron Collider (LHC). If the
top-Yukawa coupling is modified by some new physics whose scale is of the TeV
scale, its effect changes the cross sections of single-Higgs production $gg\to
H$ and double-Higgs production $gg\to HH$ through the top-loop diagram. In
particular, double-Higgs production can receive significant enhancement from
the effective top-Yukawa coupling and the new dimension-five coupling $t{\bar
t}HH$ which are induced by the dimension-six operator. Comparing these results
to the forthcoming data at the LHC, one can extract information of the
dimension-six operators relevant to the top quark and the Higgs boson.


  This paper explores ``black hole'' solutions of various Einstein-wave matter
systems admitting an isometry of their domain of outer communications taking
every point to its future. In the first two parts, it is shown that such
solutions, assuming in addition that they are spherically symmetric and the
matter has a certain structure, must be Schwarzschild or Reissner-Nordstrom.
Non-trivial examples of matter for which the result applies are a wave map and
a massive charged scalar field interacting with an electromagnetic field. The
results thus generalize work of Bekenstein [1] and Heusler [12] from the static
to the periodic case. In the third part, which is independent of the first two,
it is shown that Dirac fields preserved by an isometry of a spherically
symmetric domain of outer communications of the type described above must
vanish. It can be applied in particular to the Einstein-Dirac-Maxwell equations
or the Einstein-Dirac-Yang/Mills equations, generalizing work of Finster,
Smoller, and Yau [9], [7], [8], and also [6].


  The Facility for Antiproton and Ion Research (FAIR) in Darmstadt will provide
unique research opportunities for the investigation of fundamental open
questions related to nuclear physics and astrophysics, including the
exploration of QCD matter under extreme conditions, which governs the structure
and dynamics of cosmic objects and phenomena like neutron stars, supernova
explosions, and neutron star mergers. The physics program of the Compressed
Baryonic Matter (CBM) experiment is devoted to the production and investigation
of dense nuclear matter, with a focus on the high-density equation-of-state
(EOS), and signatures for new phases of dense QCD matter. According to the
present schedule, the CBM experiment will receive the first beams from the FAIR
accelerators in 2025. This article reviews promising observables, outlines the
CBM detector system, and presents results of physics performance studies.


  We theoretically investigate the formation of $W$ states in a tripartite
system composed of three charge qubits coupled to vibrational modes. The
electromechanical coupling is responsable for second order virtual processes
that result in an effective electron-electron interaction between neighbor
qubits, which yields to the formation of $W$ states. Based on the Lang-Firsov
transformation and perturbation theory, we analytically solve the quantum
dynamics, providing a mathematical expression for the maximally entangled $W$
state. Dephasing is also taken into accout, paying particular attention on the
robustness of bipartite entanglement against local dephasing processes.


  A high-resolution, high signal-to-noise HIRES-Keck spectrum of APM 08279+5255
reveals a feature in the HI Ly alpha profile of the zabs=3.514 absorber at the
expected position of the corresponding DI Lyalpha line. The absorber shows a
relatively simple velocity structure, with a major component detected in
several metallic lines including CII, CIV, SiII, SiIII and Si IV. Modeling of
the hydrogen column density with the minimum number of components yields D/H ~
1.5 x 10E-5. However, a more complex structure for the hydrogen cloud with
somewhat ad hoc components would allow a higher D/H. The system has a very low
metallicity with [Si/H] ~ -3.5 and [C/H] ~ -4.0 and is therefore representative
of essentially unprocessed material, with a deuterium abundance close to the
primordial value. The present analysis favours the low value of D/H
=3.39(+/-0.25) x 10E-5 measured towards QSO 1009+2956 and QSO 1937-1009 (Burles
& Tytler 1998a, 1998b) as the fiducial value of deuterium at high redshift.


  In a topological structure affected by geographical constraints on liking,
the connectivity is weakened by constructing local stubs with small cycles, a
something of randomness to bridge them is crucial for the robust network
design. In this paper, we numerically investigate the effects of adding
shortcuts on the robustness in geographical scale-free network models under a
similar degree distribution to the original one. We show that a small fraction
of shortcuts is highly contribute to improve the tolerance of connectivity
especially for the intentional attacks on hubs. The improvement is equivalent
to the effect by fully rewirings without geographical constraints on linking.
Even in the realistic Internet topologies, these effects are virtually
examined.


  The single-letter characterisation of the entanglement-assisted capacity of a
quantum channel is one of the seminal results of quantum information theory. In
this paper, we consider a modified communication scenario in which the receiver
is allowed an additional, `inconclusive' measurement outcome, and we employ an
error metric given by the error probability in decoding the transmitted message
conditioned on a conclusive measurement result. We call this setting
postselected communication and the ensuing highest achievable rates the
postselected capacities. Here, we provide a precise single-letter
characterisation of postselected capacities in the setting of entanglement
assistance as well as the more general nonsignalling assistance, establishing
that they are both equal to the channel's projective mutual information -- a
variant of mutual information based on the Hilbert projective metric. We do so
by establishing bounds on the one-shot postselected capacities, with a lower
bound that makes use of a postselected teleportation-based protocol and an
upper bound in terms of the postselected hypothesis testing relative entropy.
As such, we obtain fundamental limits on a channel's ability to communicate
even when this strong resource of postselection is allowed, implying
limitations on communication even when the receiver has access to postselected
closed timelike curves.


  The origin of the Kerr type nonlinearity of the medium as a result of the
interaction between photons via the Dirac delta-potential is presented in the
formalism adopted from the photon wave function approach. In the view of the
result the optical soliton may be treated as a bound state (cluster) of many
photons.


Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]


  Pre-saddle neutron multiplicity has been calculated for several fission
reactions induced by heavy ions and light particles. Experimentally, it is
impossible to determine the contribution of neutrons being emitted before the
saddle point and those emitted between the saddle and the scission points.
Determination of the pre-saddle neutron multiplicity in our research is based
on the comparison between the experimental anisotropies and those predicted by
the standard saddle-point statistical model. Analysis of the results shows that
the pre-saddle neutron multiplicity depends on the fission barrier height and
stability of the compound nucleus. In heavy ion induced fission, the number of
pre-saddle neutrons decreases with increasing the excitation energy of the
compound nucleus. A main cause of this behavior is due to a reduction in the
ground state-to-saddle point transition time with increasing the excitation
energy of the compound nucleus. Whereas in induced fission by light particles,
the number of pre-saddle neutrons increases with increasing the excitation
energy of the compound nucleus.


  Radio frequency transceivers operating in in-band full-duplex or
frequency-division duplex mode experience strong transmitter leakage. Combined
with receiver nonlinearities, this causes intermodulation products in the
baseband, possibly with higher power than the desired receive signal. In order
to restore the receiver signal-to-noise ratio in such scenarios, we propose two
novel digital self-interference cancellation approaches based on spline
interpolation. Both employ a Wiener structure, thereby matching the baseband
model of the intermodulation effect. Unlike most state-of-the-art spline-based
adaptive learning schemes, the proposed concept allows for complex-valued in-
and out-put signals. The optimization of the model parameters is based on the
stochastic gradient descent concept, where the convergence is supported by an
appropriate step-size normalization. Additionally, we provide a gain control
scheme and enable pipelining in order to facilitate a hardware implementation.
An optional input transform improves the performance consistency for correlated
sequences. In a realistic interference scenario, the proposed algorithms
clearly outperform a state-of-the-art least mean squares variant with
comparable complexity, which is specifically tailored to second-order
intermodulation distortions. The high flexibility of the spline interpolation
allows the spline-based Wiener models to match the performance of the kernel
recursive least squares algorithm at less than 0.6% of the arithmetic
operations.


  Blanking processes belong to the most widely used manufacturing techniques
due to their economic efficiency. Their economic viability depends to a large
extent on the resulting product quality and the associated customer
satisfaction as well as on possible downtimes. In particular, the occurrence of
increased tool wear reduces the product quality and leads to downtimes, which
is why considerable research has been carried out in recent years with regard
to wear detection. While processes have widely been monitored based on force
and acceleration signals, a new approach is pursued in this paper. Blanked
workpieces manufactured by punches with 16 different wear states are
photographed and then used as inputs for Deep Convolutional Neural Networks to
classify wear states. The results show that wear states can be predicted with
surprisingly high accuracy, opening up new possibilities and research
opportunities for tool wear monitoring of blanking processes.


  In this study, we investigate the magnetic and magnetocaloric properties of
nanostructured La0.6Sr0.4CoO3 (LSC) samples synthesized under confinement
conditions within porous templates. Using this method, we obtained
de-agglomerated nanoparticles, which provide us with the feasibility of
applying them in nanoparticle films that can be tailored to intricate
geometries. We specifically explored the impact of pore size of the template on
key parameters including saturation magnetization (MS), Curie temperature (TC),
maximum entropy change ({\Delta}S), and relative cooling power (RCP). Our
findings reveal enhancements in those quantities, that are likely to be related
with the nanostructure of the samples, indicating the potential of
nanostructured LSC as an active material for magnetic refrigeration devices.
Our alternative approach of synthesizing magnetocaloric materials under
confinement conditions presents an exciting prospect for future research and
development in the field.


  Current GNN-oriented NAS methods focus on the search for different layer
aggregate components with shallow and simple architectures, which are limited
by the 'over-smooth' problem. To further explore the benefits from structural
diversity and depth of GNN architectures, we propose a GNN generation pipeline
with a novel two-stage search space, which aims at automatically generating
high-performance while transferable deep GNN models in a block-wise manner.
Meanwhile, to alleviate the 'over-smooth' problem, we incorporate multiple
flexible residual connection in our search space and apply identity mapping in
the basic GNN layers. For the search algorithm, we use deep-q-learning with
epsilon-greedy exploration strategy and reward reshaping. Extensive experiments
on real-world datasets show that our generated GNN models outperforms existing
manually designed and NAS-based ones.


  In a finite undirected graph $G=(V,E)$, a vertex $v \in V$ {\em dominates}
itself and its neighbors in $G$. A vertex set $D \subseteq V$ is an {\em
efficient dominating set} ({\em e.d.} for short) of $G$ if every $v \in V$ is
dominated in $G$ by exactly one vertex of $D$. The {\em Efficient Domination}
(ED) problem, which asks for the existence of an e.d. in $G$, is known to be
NP-complete for $P_7$-free graphs but solvable in polynomial time for
$P_5$-free graphs. The $P_6$-free case was the last open question for the
complexity of ED on $F$-free graphs.
  Recently, Lokshtanov, Pilipczuk and van Leeuwen showed that weighted ED is
solvable in polynomial time for $P_6$-free graphs, based on their
sub-exponential algorithm for the Maximum Weight Independent Set problem for
$P_6$-free graphs. Independently, at the same time, Mosca found a polynomial
time algorithm for weighted ED on $P_6$-free graphs using a direct approach. In
this paper, we describe the details of this approach which is simpler and much
faster, namely its time bound is ${\cal O}(n^6 m)$.


  A recently proposed method of estimating the asymptotic behaviour of QCD
perturbation theory coefficients is critically reviewed and shown to contain
numerous invalid mathematical operations and unsubstantiated assumptions. We
discuss in detail why this procedure, based solely on renormalization group
(RG) considerations and analyticity constraints, cannot lead to such estimates.
We stress the importance of correct renormalization scheme (RS) dependence of
any meaningful asymptotic estimate and argue that the unambiguous summation of
QCD perturbation expansions for physical quantities requires information from
outside of perturbation theory itself.


  Bootstrap particle filter (BPF) is the corner stone of many popular
algorithms used for solving inference problems involving time series that are
observed through noisy measurements in a non-linear and non-Gaussian context.
The long term stability of BPF arises from particle interactions which in the
context of modern parallel computing systems typically means that particle
information needs to be communicated between processing elements, which makes
parallel implementation of BPF nontrivial.
  In this paper we show that it is possible to constrain the interactions in a
way which, under some assumptions, enables the reduction of the cost of
communicating the particle information while still preserving the consistency
and the long term stability of the BPF. Numerical experiments demonstrate that
although the imposed constraints introduce additional error, the proposed
method shows potential to be the method of choice in certain settings.


  We report measured rate coefficients for electron-ion recombination for Si10+
forming Si9+ and for Si9+ forming Si8+, respectively. The measurements were
performed using the electron-ion merged-beams technique at a heavy-ion storage
ring. Electron-ion collision energies ranged from 0 to 50 eV for Si9+ and from
0 to 2000 eV for Si10+, thus, extending previous measurements for Si10+ [Orban
et al. 2010, Astrophys. J. 721, 1603] to much higher energies. Experimentally
derived rate coefficients for the recombination of Si9+ and Si10+ ions in a
plasma are presented along with simple parameterizations. These rate
coefficients are useful for the modeling of the charge balance of silicon in
photoionized plasmas (Si9+ and Si10+) and in collisionally ionized plasmas
(Si10+ only). In the corresponding temperature ranges, the experimentally
derived rate coefficients agree with the latest corresponding theoretical
results within the experimental uncertainties.


  This paper experimentally evaluates the Generalized Sinusoidal Frequency
Modulated (GSFM) waveform, a generalization of the Sinusoidal Frequency
Modulated (SFM) waveform. The Instantaneous Frequency (IF) of the GSFM
resembles the time/voltage characteristic of a Linear FM (LFM) chirp waveform.
Consequently, the GSFM possesses an Ambiguity Function (AF) that resembles a
thumbtack shape. Practical sonar system design must consider two factors beyond
the AF. The spectral efficiency (SE), defined as the ratio of energy in an
operational frequency band to the total waveform energy, is another important
metric for waveform design. The Peak-to-Average-Power Ratio (PAPR) quantifies
how close the waveform is to constant amplitude. These measures predict a
waveform's energy efficiency and ability to be accurately replicated on
practical piezoelectric transducers, which have limits on both their bandwidth
and maximum transmit power. This paper explores these design considerations for
the GSFM waveform and evaluates its performance against a host of other well
established waveforms using simulated and experimental acoustic data. The GSFM
possesses superior SE, PAPR, and overall energy efficiency when compared to
thumbtack waveforms.


  A comparison on some facts concerning the geometric quantization of
symplectic manifolds is presented here. Criticism, facts and improvements on
the sophisticated theory of geometric quantization are presented touching
briefly, all the "salient points of the theory". The unfamiliar reader can
consider this as a "soft" introduction to the topic.


  We present a modification of a model of solar cycle evolution of the solar
Lyman-alpha line profile, along with a sensitivity study of interstellar
neutral H hydrogen to uncertainties in radiation pressure level. The line
profile model, originally developed by Kowalska-Leszczynska et al. 2018a, is
parametrized by the composite solar Lyman-alpha flux, which recently was
revised Machol et al. 2019. We present modified parameters of the
previously-developed model of solar radiation pressure for neutral hydrogen and
deuterium atoms in the heliosphere. The mathematical function used in the
model, as well as the fitting procedure, remain unchanged. We show selected
effects of the model modification on ISN H properties in the heliosphere and we
discuss the sensitivity of these quantities to uncertainties in the calibration
of the composite Lyman-alpha series.


  In this paper we study various forms of (hereditary) structural completeness
for quasivarieties of algebras, using mostly algebraic techniques. More
specifically we study relative weakly projective algebras and the way they
interact with structural completeness in quasivarieties. These ideas are then
applied to the study of $C$-structural completeness and $C$-primitivity,
through an algebraic generalization of Prucnal's substitution. Finally we study
in depth dual i-discriminator quasivarieties in which a particular instance of
Prucnal's substitution is used to prove that if each fundamental operation
commutes with the i-discriminator, then it is primitive.