  Blockchain technology ensures secure and trustworthy data flow between
multiple participants on the chain, but interoperability of on-chain and
off-chain data has always been a difficult problem that needs to be solved. To
solve the problem that blockchain systems cannot access off-chain data, oracle
is introduced. however, existing research mainly focuses on the consistency and
integrity of data, but ignores the problem that oracle nodes may be externally
attacked or provide false data for selfish motives, resulting in the unresolved
problem of data accuracy. In this paper, we introduce a new decentralized
testing architecture (DesTest) that aims to improve data accuracy. A blockchain
oracle random secret testing mechanism is first proposed to enhance the
monitoring and verification of nodes by introducing a dynamic anonymized
question-verification committee. Based on this, a comprehensive evaluation
incentive mechanism is designed to incentivize honest work performance by
evaluating nodes based on their reputation scores. The simulation results show
that we successfully reduced the discrete entropy value of the acquired data
and the real value of the data by 61.4%.


  We study the dynamics of Random Threshold Network (RTN) on scale free
networks, with asymmetric links, some interaction rules where propagation of
local perturbations depends on in-degree $k$ of the nodes. We find that there
is no phase transition with respect to average connectivty independently of
network topology for the case temperature T=0, threshold $h=0$ and the
probability distribution of indegree $P(k)$ satisfies $P(0)=D=0$. We have
investigated the emergence of phase transition involving three parameters, i.e.
$T,h$ and $D$. RTN can be continuously connected to Random Boolean Network
(RBN) in $T\to \infty$, and we find moderate thermal noise extends the regime
of ordered dynamics, compared to RTN in T=0 regime and RBN. Furthermore, we
discuss the dynamic properties from another point of view, dynamical mean field
reaction rate equation.


  The optical properties of quasi-one-dimensional metallic LaTiO$_{3.41}$ are
studied for the polarization along the $a$ and $b$ axes. With decreasing
temperature modes appear along both directions suggestive for a phase
transition. The broadness of these modes along the conducting axis might be due
to the coupling of the phonons to low-energy electronic excitations across an
energy gap. We observe a pronounced midinfrared band with a temperature
dependence consistent with (interacting) polaron models. The polaronic picture
is corroborated by the presence of strong electron-phonon coupling and the
temperature dependence of the dc conductivity.


  Conventional federated learning primarily aims to secure the privacy of data
distributed across multiple edge devices, with the global model dispatched to
edge devices for parameter updates during the learning process. However, the
development of large language models (LLMs) requires substantial data and
computational resources, rendering them valuable intellectual properties for
their developers and owners. To establish a mechanism that protects both data
and model privacy in a federated learning context, we introduce a method that
just needs to distribute a quantized version of the model's parameters during
training. This method enables accurate gradient estimations for parameter
updates while preventing clients from accessing a model whose performance is
comparable to the centrally hosted one. Moreover, we combine this quantization
strategy with LoRA, a popular and parameter-efficient fine-tuning method, to
significantly reduce communication costs in federated learning. The proposed
framework, named \textsc{FedLPP}, successfully ensures both data and model
privacy in the federated learning context. Additionally, the learned central
model exhibits good generalization and can be trained in a resource-efficient
manner.


  Dantzig Selector (DS) is widely used in compressed sensing and sparse
learning for feature selection and sparse signal recovery. Since the DS
formulation is essentially a linear programming optimization, many existing
linear programming solvers can be simply applied for scaling up. The DS
formulation can be explained as a basis pursuit denoising problem, wherein the
data matrix (or measurement matrix) is employed as the denoising matrix to
eliminate the observation noise. However, we notice that the data matrix may
not be the optimal denoising matrix, as shown by a simple counter-example. This
motivates us to pursue a better denoising matrix for defining a general DS
formulation. We first define the optimal denoising matrix through a minimax
optimization, which turns out to be an NPhard problem. To make the problem
computationally tractable, we propose a novel algorithm, termed as Optimal
Denoising Dantzig Selector (ODDS), to approximately estimate the optimal
denoising matrix. Empirical experiments validate the proposed method. Finally,
a novel sparse reinforcement learning algorithm is formulated by extending the
proposed ODDS algorithm to temporal difference learning, and empirical
experimental results demonstrate to outperform the conventional vanilla DS-TD
algorithm.


  We study generalized global symmetries and their 't Hooft anomalies in 3d N=4
superconformal field theories (SCFTs). Following some general considerations,
we focus on good quiver gauge theories, comprised of balanced unitary nodes and
unbalanced unitary and special unitary nodes. While the global form of the
Higgs branch symmetry group may be determined from the UV Lagrangian, the
global form of Coulomb branch symmetry groups and associated mixed 't Hooft
anomalies are more subtle due to potential symmetry enhancement in the IR. We
describe how Coulomb branch symmetry groups and their mixed 't Hooft anomalies
can be deduced from the UV Lagrangian by studying center charges of various
types of monopole operators, providing a concrete and unambiguous way to
implement 't Hooft anomaly matching. The final expression for the symmetry
group and 't Hooft anomalies has a concise form that can be easily read off
from the quiver data, specifically from the positions of the unbalanced and
flavor nodes with respect to the positions of the balanced nodes. We provide
consistency checks by applying our method to compute symmetry groups of 3d N=4
theories corresponding to magnetic quivers of 4d Class S theories and 5d SCFTs.
We are able to match these results against the flavor symmetry groups of the 4d
and 5d theories computed using independent methods. Another strong consistency
check is provided by comparing symmetry groups and anomalies of two theories
related by 3d mirror symmetry.


  A systematic field theoretic formalism for treating Fermionic resonances with
non zero width is given. The implication of unitarity to coupling constants of
non local interactions is shown. The extension of the formalism to Bosonic
resonance field operators is straight forward.


  It is well known that an arbitrary closed orientable $3$-manifold can be
realized as the unique boundary of a compact orientable $4$-manifold, that is,
any closed orientable $3$-manifold is cobordant to zero. In this paper, we
consider the geometric cobordism problem: a hyperbolic $3$-manifold is
geometrically bounding if it is the only boundary of a totally geodesic
hyperbolic 4-manifold. However, there are very rare geometrically bounding
closed hyperbolic 3-manifolds according to the previous research [11,13]. Let
$v \approx 4.3062\ldots$ be the volume of the regular right-angled hyperbolic
dodecahedron in $\mathbb{H}^{3}$, for each $n \in \mathbb{Z}_{+}$ and each odd
integer $k$ in $[1,5n+3]$, we construct a closed hyperbolic 3-manifold $M$ with
$\beta^1(M)=k$ and $vol(M)=16nv$ that bounds a totally geodesic hyperbolic
4-manifold. The proof uses small cover theory over a sequence of linearly-glued
dodecahedra and some results of Kolpakov-Martelli-Tschantz [9].


  Answering questions is a primary goal of many conversational systems or
search products. While most current systems have focused on answering questions
against structured databases or curated knowledge graphs, on-line community
forums or frequently asked questions (FAQ) lists offer an alternative source of
information for question answering systems. Automatic duplicate question
detection (DQD) is the key technology need for question answering systems to
utilize existing online forums like StackExchange. Existing annotations of
duplicate questions in such forums are community-driven, making them sparse or
even completely missing for many domains. Therefore, it is important to
transfer knowledge from related domains and tasks. Recently, contextual
embedding models such as BERT have been outperforming many baselines by
transferring self-supervised information to downstream tasks. In this paper, we
apply BERT to DQD and advance it by unsupervised adaptation to StackExchange
domains using self-supervised learning. We show the effectiveness of this
adaptation for low-resource settings, where little or no training data is
available from the target domain. Our analysis reveals that unsupervised BERT
domain adaptation on even small amounts of data boosts the performance of BERT.


  Damage to the white matter underlying the left posterior temporal lobe leads
to deficits in multiple language functions. The posterior temporal white matter
may correspond to a bottleneck where both dorsal and ventral language pathways
are vulnerable to simultaneous damage. Damage to a second putative white matter
bottleneck in the left deep prefrontal white matter involving projections
associated with ventral language pathways and thalamo-cortical projections has
recently been proposed as a source of semantic deficits after stroke. However,
the effects of damage to a priori identified white matter bottlenecks on
language function have not been directly investigated. Here, we first used
white matter atlases to identify the previously described white matter
bottlenecks in the posterior temporal and deep prefrontal white matter. We then
assessed the effects of damage to each region on measures of category fluency,
picture naming, and auditory semantic decision-making in 43 patients with
chronic aphasia. Damage to the posterior temporal bottleneck predicted deficits
on all language measures, while damage to the anterior bottleneck only
predicted deficits in category fluency. Importantly, the effects of damage to
the bottleneck regions were not attributable to lesion volume, lesion loads on
the tracts traversing the bottlenecks, or damage to nearby cortical language
areas. Multivariate lesion-symptom mapping and fiber tracking analyses
corroborated these findings. Together, our results provide strong support for
the proposal that spatially specific white matter damage affecting white matter
bottlenecks, particularly in the posterior temporal lobe, contribute to chronic
language deficits after left hemispheric stroke. Our results suggest that
damage to this area is likely to simultaneously disrupt signaling via the
simultaneous disruption of dorsal and ventral language processing streams.


  In this paper, we consider the adiabatic limit of Fu-Yau equations on a
product of two Calabi-Yau manifolds. We prove that the adiabatic limit of
Fu-Yau equations are quasilinear equations.


  In this paper, we show that the $\theta$-graph with three cones is connected.
We also provide an alternative proof of the connectivity of the Yao graph with
three cones.


  We develop a first-principles theory of resonant impurities in graphene and
show that a broad range of typical realistic impurities leads to the
characteristic sublinear dependence of the conductivity on the carrier
concentration. By means of density functional calculations various organic
groups as well as ad-atoms like H absorbed to graphene are shown to create
midgap states within +-0.03eV around the neutrality point. A low energy
tight-binding description is mapped out. Boltzmann transport theory as well as
a numerically exact Kubo formula approach yield the conductivity of graphene
contaminated with these realistic impurities in accordance with recent
experiments.


  The effect of quantum dot shape on the hole energy spectrum and optical
properties caused by the interlevel charge transition based on the 4x4
Hamiltonian has been studied for the GaAs quantum dot in the AlAs semiconductor
matrix. Calculations have been carried out in perturbation theory taking into
account the hybridization of states for cubic, ellipsoidal, cylindrical and
tetrahedral shapes by changing the volume of a quantum dot. Based on the energy
calculations and on the determined wave functions of the hole states we have
defined the selection rules and the dependence of the interlevel hole
absorption coefficient on QD shapes and volumes.


  Let ${[n] \choose k}$ and ${[n] \choose l}$ $( k > l ) $ where $[n] =
\{1,2,3,...,n\}$ denote the family of all $k$-element subsets and $l$-element
subsets of $[n]$ respectively. Define a bipartite graph $G_{k,l} = ({[n]
\choose k},{[n] \choose l},E)$ such that two vertices $S\, \epsilon \,{[n]
\choose k} $ and $T\, \epsilon \,{[n] \choose l} $ are adjacent if and only if
$T \subset S$. In this paper, we give an upper bound for the domination number
of graph $G_{k,2}$ for $k > \lceil \frac{n}{2} \rceil$ and exact value for
$k=n-1$.


  We study the interplay between higher curvature terms and the backreaction of
quantum fluctuations in 3-dimensional massive gravity in asymptotically
(Anti-)de Sitter space. We focus on the theory at the special point of the
parameter space where the two maximally symmetric vacua coincide. In the case
of positive cosmological constant, this corresponds to the partially massless
point, at which the classical theory admits de Sitter black holes and exhibits
an extra conformal symmetry at linear level. We explicitly find the quantum
corrected black hole geometry in the semiclassical approximation and show that
it induces a relaxation of the standard asymptotic conditions. Nonetheless, the
new asymptotic behavior is still preserved by an infinite-dimensional algebra,
which, in addition to Virasoro, contains logarithmic supertranslations.
Finally, we show that all the results we obtain for the quadratic massive
gravity theory can be extended to theories including cubic and quartic terms in
the curvature.


  The concept of a propagator is useful and is a well-known object in diffusion
NMR experiments. Here, we investigate the related concept; the propagator for
the magnetisation or the Green's function of the Torrey-Bloch equations. The
magnetisation propagator is constructed by defining functions such as the
Hamiltonian and Lagrangian and using these to define a path integral. It is
shown that the equations of motion derived from the Lagrangian produce
complex-valued trajectories (classical paths) and it is conjectured that the
end-points of these trajectories are real-valued. The complex nature of the
trajectories also suggests that the spin degrees of freedom are also encoded
into the trajectories and this idea is explored by explicitly modeling the spin
or precessing magnetisation by anticommuting Grassmann variables. A
pseudoclassical Lagrangian is constructed by combining the diffusive (bosonic)
Lagrangian with the Grassmann (fermionic) Lagrangian, and performing the path
integral over the Grassmann variables recovers the original Lagrangian that was
used in the construction of the propagator for the magnetisation. The
trajectories of the pseudoclassical model also provide some insight into the
nature of the end-points.


  We present a $U(4)_R \times U(4)_L$ chirally symmetric model, which in
addition to scalar and pseudoscalar mesons also includes vector and
axial-vector mesons. A part from the three new parameters pertaining to the
charm degree of freedom, the parameters of the model are fixed from the $N_f=3$
flavor sector. We calculate open charmed meson masses and the weak decay
constants of nonstrange open charm $D$ and strange open charm $D_S$. We also
evaluate the (OZI-dominant) strong decays of open charmed mesons. The results
are turn out to be in quantitative agreement with experimental data.


  This article deals with the problem of vessel edge and centerline detection
using classical image processing techniques due to their simpleness and
easiness to be implemented. The method is divided into four steps: the vessel
enhancement which implies a non-linear filtering proposed by Frangi, the
thresholding using Otsu method and the contour detection using the Canny edge
detector due to its good performances for the small vessels and the
morphological skeletonisation. The algorithms are tested on real data collected
from a cardiac catheterism laboratory and it is accurate for images with good
spatial resolution (512*512). The output image can be used for further
processing in order to find the vessel length or its radius.


  The rainfall associated with Topical Cyclone(TC) contributes a major amount
to the annual rainfall in India. Due to the limited research on the
quantitative precipitation associated with Tropical Cyclones (TC), the
prediction of the amount of precipitation and area that it may cover remains a
challenge. This paper proposes an approach to estimate the accumulated
precipitation and impact on affected area using Remote Sensing data. For this
study, an instance of Extremely Severe Cyclonic Storm, Biparjoy that formed
over the Arabian Sea and hit India in 2023 is considered in which we have used
the satellite images of IMERG-Late Run of Global Precipitation Measurement
(GPM). Image processing techniques were employed to identify and extract
precipitation clusters linked to the cyclone. The results indicate that
Biparjoy contributed a daily average rainfall of 53.14 mm/day across India and
the Arabian Sea, with the Indian boundary receiving 11.59 mm/day, covering an
extensive 411.76 thousand square kilometers. The localized intensity and
variability observed in states like Gujarat, Rajasthan, Madhya Pradesh, and
Uttar Pradesh highlight the need for tailored response measures, emphasizing
the importance of further research to enhance predictive models and disaster
readiness, crucial for building resilience against the diverse impacts of
tropical cyclones.


  Intrinsic emission and absorption lines of QSOs provide several independent
probes of the metal abundances in QSO environments. They indicate that the
metallicities are typically solar or higher out to redshifts z > 4. These
results support models of galaxy evolution where galactic nuclei, or dense
condensations that later become galactic nuclei, form stars and evolve quickly
at redshifts higher than the QSOs themselves.


  We examine statistical fluctuation of eigenvalues from the near-edge bulk of
QCD Dirac spectra above the critical temperature. For completeness we start by
reviewing on the spectral property of Anderson tight-binding Hamiltonians as
described by nonlinear sigma models and random matrices, and on the
scale-invariant intermediate spectral statistics at the mobility edge. By
fitting the level spacing distributions, deformed random matrix ensembles which
model multifractality of the wave functions typical of the Anderson
localization transition, are shown to provide an excellent effective
description for such a critical statistics. Next we carry over the above
strategy for the Anderson Hamiltonians to the Dirac spectra. For the staggered
Dirac operators of QCD with 2+1 flavors of dynamical quarks at the physical
point and of SU(2) quenched gauge theory, we identify the precise location of
the mobility edge as the scale-invariant fixed point of the level spacing
distribution. The eigenvalues around the mobility edge are shown to obey
critical statistics described by the aforementioned deformed random matrix
ensembles of unitary and symplectic classes. The best-fitting deformation
parameter for QCD at the physical point turns out to be consistent with the
Anderson Hamiltonian in the unitary class. Finally, we propose a method of
locating the mobility edge at the origin of QCD Dirac spectrum around the
critical temperature, by the use of individual eigenvalue distributions of
deformed chiral random matrices.


  We compute properties of the interface of the 3-dimensional Ising model for a
wide range of temperatures, covering the whole region from the low temperature
domain through the roughening transition to the bulk critical point. The
interface tension sigma is obtained by integrating the surface energy density
over the inverse temperature beta. We use lattices of size L x L x T, with L up
to 64, and T up to 27. The simulations with antiperiodic boundary conditions in
T-direction are done with the Hasenbusch-Meyer interface cluster algorithm that
turns out to be very efficient. We demonstrate that in the rough phase the
large distance behavior of the interface is well described by a massless
Gaussian dynamics. The surface stiffness coefficient kappa is determined. We
also attempt to determine the correlation length xi and study universal
quantities like xi^2 * sigma and xi^2 * kappa. Results for the interfacial
width on lattices up to 512 x 512 x 27 are also presented.


  Traffic speed prediction is significant for intelligent navigation and
congestion alleviation. However, making accurate predictions is challenging due
to three factors: 1) traffic diffusion, i.e., the spatial and temporal
causality existing between the traffic conditions of multiple neighboring
roads, 2) the poor interpretability of traffic data with complicated
spatio-temporal correlations, and 3) the latent pattern of traffic speed
fluctuations over time, such as morning and evening rush. Jointly considering
these factors, in this paper, we present a novel architecture for traffic speed
prediction, called Interpretable Causal Spatio-Temporal Diffusion Network
(ICST-DNET). Specifically, ICST-DENT consists of three parts, namely the
Spatio-Temporal Causality Learning (STCL), Causal Graph Generation (CGG), and
Speed Fluctuation Pattern Recognition (SFPR) modules. First, to model the
traffic diffusion within road networks, an STCL module is proposed to capture
both the temporal causality on each individual road and the spatial causality
in each road pair. The CGG module is then developed based on STCL to enhance
the interpretability of the traffic diffusion procedure from the temporal and
spatial perspectives. Specifically, a time causality matrix is generated to
explain the temporal causality between each road's historical and future
traffic conditions. For spatial causality, we utilize causal graphs to
visualize the diffusion process in road pairs. Finally, to adapt to traffic
speed fluctuations in different scenarios, we design a personalized SFPR module
to select the historical timesteps with strong influences for learning the
pattern of traffic speed fluctuations. Extensive experimental results prove
that ICST-DNET can outperform all existing baselines, as evidenced by the
higher prediction accuracy, ability to explain causality, and adaptability to
different scenarios.


  Modern mathematics is known for its rigorous proofs and tight analysis. Math
is the paradigm of objectivity for most. We identify the source of that
objectivity as our knowledge of the physical world given through our senses. We
show in detail, for the core of modern mathematics, how modern mathematical
formalism encapsulates deep realities about extension into a system of symbols
and axiomatic rules. In particular, we proceed from the foundations in our
senses to the natural numbers through integers, rational numbers, and real
numbers, including introducing the concept of a field. An appendix shows how
the formalism of complex numbers arises.


  This paper assumes that neutrino flavor conversion is induced by right-handed
neutrino mixture via seesaw mechanism, which leads to apparent fake neutrino
mixture with neutrino mass eigenstate consistent with flavor state of
left-handed neutrino rather than mixture of flavor state. The transition
probability between right-handed neutrinos due to mixture can be explained well
by boson intermediating flavor flip interaction between right-handed neutrinos
and neutrino oscillation can be considered macro phenomenon before all flavor
flip interactions arrive at balance.


  The anti-D meson self-energy is evaluated self-consistently, using unitarized
coupled-channel theory, by computing the in-medium meson-baryon T-matrix in the
C=-1,S=0 sector. The heavy pseudo-scalar and heavy vector mesons, anti-D and
anti-D^*, are treated on equal footing as required by heavy quark spin
symmetry. Results for energy levels and widths of D^- mesic atoms in 12C, 40Ca,
118Sn and 208Pb are presented. The spectrum contains states of atomic and of
nuclear types for all nuclei. anti-D^0--nucleus bound states are also obtained.
We find that, after electromagnetic and nuclear cascade, these systems end up
with the anti-D bound in the nucleus, either as a meson or as part of a exotic
anti-D N (pentaquark) loosely bound state.


  This paper proposes a hypothesis for the aesthetic appreciation that
aesthetic images make a neural network strengthen salient concepts and discard
inessential concepts. In order to verify this hypothesis, we use multi-variate
interactions to represent salient concepts and inessential concepts contained
in images. Furthermore, we design a set of operations to revise images towards
more beautiful ones. In experiments, we find that the revised images are more
aesthetic than the original ones to some extent.


  Any knot in $S^3$ may be reduced to a slice knot by crossing changes. Indeed,
this slice knot can be taken to be the unknot. In this paper we study the
question of when the same holds for knots in homology spheres. We show that a
knot in a homology sphere is nullhomotopic in a smooth homology ball if and
only if that knot is smoothly concordant to a knot which is homotopic to a
smoothly slice knot. As a consequence, we prove that the equivalence relation
on knots in homology spheres given by cobounding immersed annuli in a homology
cobordism is generated by concordance in homology cobordisms together with
homotopy in a homology sphere.


  Studies have shown that a dominant class of questions asked by visually
impaired users on images of their surroundings involves reading text in the
image. But today's VQA models can not read! Our paper takes a first step
towards addressing this problem. First, we introduce a new "TextVQA" dataset to
facilitate progress on this important problem. Existing datasets either have a
small proportion of questions about text (e.g., the VQA dataset) or are too
small (e.g., the VizWiz dataset). TextVQA contains 45,336 questions on 28,408
images that require reasoning about text to answer. Second, we introduce a
novel model architecture that reads text in the image, reasons about it in the
context of the image and the question, and predicts an answer which might be a
deduction based on the text and the image or composed of the strings found in
the image. Consequently, we call our approach Look, Read, Reason & Answer
(LoRRA). We show that LoRRA outperforms existing state-of-the-art VQA models on
our TextVQA dataset. We find that the gap between human performance and machine
performance is significantly larger on TextVQA than on VQA 2.0, suggesting that
TextVQA is well-suited to benchmark progress along directions complementary to
VQA 2.0.


  A generalization of the Bernstein matrix concentration inequality to random
tensors of general order is proposed. This generalization is based on the use
of Einstein products between tensors, from which a strong link can be
established between matrices and tensors, in turn allowing exploitation of
existing results for the former.


  We report the results of a search for the decay $K^+ \to \pi^+ \nu \bar \nu$
in the kinematic region with $\pi^+$ momentum $140 < P < 195$ MeV/c using the
data collected by the E787 experiment at BNL. No events were observed. When
combined with our previous search in this region, one candidate event with an
expected background of $1.22 \pm 0.24$ events results in a 90% C.L. upper limit
of $2.2 \times 10^{-9}$ on the branching ratio of $K^+ \to \pi^+ \nu \bar \nu$.
We also report improved limits on the rates of $K^+ \to \pi^+ X^0$ and $K^+ \to
\pi^+ X^1 X^2$ where $X^0, X^1, X^2$ are hypothetical, massless, long-lived
neutral particles.


  We investigate how symmetries and conserved quantities relate to the
occurrence of the boundary time crystal (BTC) phase in a generalized spin model
with Lindblad dissipation. BTCs are a non-equilibrium phase of matter in which
the system, coupled to an external environment, breaks the continuous time
translational invariance. We perform a detailed mean-field study aided by a
finite-size analysis of the quantum model of a p,q-spin-interaction system, a
generalized p-spin interaction system, which can be implemented in
fully-connected spin-1/2 ensembles. We find the following conditions for the
observation of the BTC phase: First, the BTC appears when the discrete symmetry
held by the Hamiltonian, $\mathbb{Z}_2$ in the considered models, is explicitly
broken by the Lindblad jump operators. Second, the system must be coupled
uniformly to the same bath in order to preserve the total angular momentum
during the time evolution. If these conditions are not satisfied, any
oscillatory behavior appears only as a transient in the dynamics and a
time-independent stationary state is eventually reached. Our results suggest
that these two elements may be general requirements for the observation of a
stable BTC phase relating symmetries and conserved quantities in arbitrary spin
models.


  In this paper we present The Rosario Dataset, a collection of sensor data for
autonomous mobile robotics in agricultural scenes. The dataset is motivated by
the lack of realistic sensor readings gathered by a mobile robot in such
environments. It consists of 6 sequences recorded in soybean fields showing
real and challenging cases: highly repetitive scenes, reflection and burned
images caused by direct sunlight and rough terrain among others. The dataset
was conceived in order to provide a benchmark and contribute to the
agricultural SLAM/odometry and sensor fusion research. It contains synchronized
readings of several sensors: wheel odometry, IMU, stereo camera and a GPS-RTK
system. The dataset is publicly available in
http://www.cifasis-conicet.gov.ar/robot/.


  Gravitational waves emitted during intermediate-mass-ratio inspirals (IMRIs)
of intermediate-mass black holes (IMBHs) into supermassive black holes could
represent a very interesting source for LISA. Similarly, IMRIs of stellar-mass
compact objects into IMBHs could be detectable by Advanced LIGO. At present,
however, it is not clear what waveforms could be used for IMRI detection, since
the post-Newtonian approximation breaks down as an IMRI approaches the
innermost stable circular orbit, and perturbative solutions are only known to
the lowest order in the mass ratio. We discuss the expected mismatches between
approximate and true waveforms, and the choice of the best available waveform
as a function of the mass ratio and the total mass of the system. We also
comment on the significance of the spin of the smaller body and the need for
its inclusion in the waveforms.


  We show that the resulting manifold by $r$-surgery on the knot $5_2$, which
is the two-bridge knot corresponding to the rational number 3/7, has
left-orderable fundamental group if the slope $r$ satisfies $0\le r\le 4$.


  We investigate the structure and features of an ultralong-range triatomic
Rydberg molecule formed by a Rb Rydberg atom and a KRb diatomic molecule. In
our numerical description, we perform a realistic treatment of the internal
rotational motion of the diatomic molecule, and take into account the Rb($n,
l\ge 3$) Rydberg degenerate manifold and the energetically closest neighboring
levels with principal quantum numbers $n'>n$ and orbital quantum number
$l\le2$. We focus here on the adiabatic electronic potentials evolving from the
Rb($n, l\ge 3$) and Rb($n=26, l=2$) manifolds. The directional properties of
the KRb diatomic molecule within the Rb-KRb triatomic Rydberg molecule are also
analyzed in detail.


  We construct a cohomology theory with compact support H^i_c(X_ar,Z(n))$ for
separated schemes of finite type over a finite field, which should play a role
analog to Lichtenbaum's Weil-etale cohomology groups for smooth and projective
schemes. In particular, if Tate's conjecture holds and rational and numerical
equivalence agree up to torsion, then the groups H^i_c(X_ar,Z(n)) are finitely
generated, form an integral version of l-adic cohomology with compact support,
and admit a formula for the special values of the zeta-function of X.


  3D Shape representation has substantial effects on 3D shape reconstruction.
Primitive-based representations approximate a 3D shape mainly by a set of
simple implicit primitives, but the low geometrical complexity of the
primitives limits the shape resolution. Moreover, setting a sufficient number
of primitives for an arbitrary shape is challenging. To overcome these issues,
we propose a constrained implicit algebraic surface as the primitive with few
learnable coefficients and higher geometrical complexities and a deep neural
network to produce these primitives. Our experiments demonstrate the
superiorities of our method in terms of representation power compared to the
state-of-the-art methods in single RGB image 3D shape reconstruction.
Furthermore, we show that our method can semantically learn segments of 3D
shapes in an unsupervised manner. The code is publicly available from
https://myavartanoo.github.io/3dias/ .


  Fan, Chen, Ma and Wang constructed a moment-angle manifold $Z_K$ whose
cohomology ring is isomorphic to that of a connected sum of sphere products
with one product of three spheres. In this paper, we show that they are
actually diffeomorphic.


  The effects of dc excitation current on the current-voltage curves of
polycrystalline samples of Nd0.5Ca0.5Mn0.96Cr0.04O3 were investigated. The
experimental results show that an abrupt jump of the voltage is concomitant
with a huge increase in the temperature of the sample. A simple model and
estimates for Joule self-heating effects support the experimental data.
Moreover, the data strongly suggest that both the current localization in the
metallic paths and local Joule self-heating effects are essential ingredients
to understand the current-induced phase transition in phase-separated
manganites.


  Quantum simulators, machines that can replicate the dynamics of quantum
systems, are being built as useful devices and are seen as a stepping stone to
universal quantum computers. A key difference between the two is that computers
have the ability to perform the logic gates that make up algorithms. We propose
a method for learning how to construct these gates efficiently by using the
simulator to perform optimal control on itself. This bypasses two major
problems of purely classical approaches to the control problem: the need to
have an accurate model of the system, and a classical computer more powerful
than the quantum one to carry out the required simulations. Strong evidence
that the scheme scales polynomially in the number of qubits, for systems of up
to 9 qubits with Ising interactions, is presented from numerical simulations
carried out in different topologies. This suggests that this in situ approach
is a practical way of upgrading quantum simulators to computers.


  We present submillimeter observations of the Local Group, metal-poor,
irregular dwarf galaxy IC 10, directly relevant to the interaction between
interstellar medium and star formation activity in primeval galaxies. Using the
JCMT, we have observed the fine structure neutral carbon transition at 492 GHz
and the rotational J=3-2 transition of 12CO and 13CO in the most massive giant
molecular cloud complex in this galaxy, IC10-SE. We find that, although the
I([CII])/I(CO) ratio for this object is a factor of 4 larger than the typical
Milky Way value, its [C~I] to CO intensity ratio is I([CI])/I(CO)~18 is similar
(only about 50% larger) to that of the Milky Way. Modelling of the [CII]/CO and
[CI]/CO intensity ratios with metallicity indicates that, if C+ and C are
chiefly produced by UV photodissociation, both ratios should increase sharply
with decreasing metallicity (and consequently diminished UV shielding; Bolatto,
Jackson, and Ingalls 1999). These data then suggest a different origin for an
important fraction of C in these clouds, unrelated to photodissociation. We
have also mapped the 850 um continuum in this region using SCUBA. Employing
these data in conjunction with KAO and IRAM measurements we find an extremely
low emissivity exponent, b~0.5. We conclude that this low exponent is most
likely due to the destruction of small dust grains, brought about by the
increased penetration of UV radiation in the low metallicity ISM. If a low b in
the submillimeter is a general property of metal-poor systems then the
interpretation of millimeter and submillimeter surveys of high-z galaxies
should be revised.


  We show a method to control magnetic interfacial effects in multilayers with
Dzyaloshinskii-Moriya interaction (DMI) using helium (He$^{+}$) ion
irradiation. We report results from SQUID magnetometry, ferromagnetic resonance
as well as Brillouin light scattering results on multilayers with DMI as a
function of irradiation fluence to study the effect of irradiation on the
magnetic properties of the multilayers. Our results show clear evidence of the
He$^{+}$ irradiation effects on the magnetic properties which is consistent
with interface modification due to the effects of the He$^{+}$ irradiation.
This external degree of freedom offers promising perspectives to further
improve the control of magnetic skyrmions in multilayers, that could push them
towards integration in future technologies.


  A poset $P = (X,\prec)$ has an interval representation if each $x \in X$ can
be assigned a real interval $I_x$ so that $x \prec y$ in $P$ if and only if
$I_x$ lies completely to the left of $I_y$. Such orders are called
\emph{interval orders}. In this paper we give a surprisingly simple forbidden
poset characterization of those posets that have an interval representation in
which each interval length is either 0 or 1. In addition, for posets
$(X,\prec)$ with a weight of 1 or 2 assigned to each point, we characterize
those that have an interval representation in which for each $x \in X$ the
length of the interval assigned to $x$ equals the weight assigned to $x$. For
both these problems we can determine in polynomial time whether the desired
interval representation is possible and in the affirmative case, produce such a
representation.


  Quantum Information Processing relies on coherent quantum dynamics for a
precise control of its basic operations. A swapping gate in a two-spin system
exchanges the degenerate states |+,-> and |-,+>. In NMR, this is achieved
turning on and off the spin-spin interaction b=\Delta E that splits the energy
levels and induces an oscillation with a natural frequency \Delta E/\hbar.
Interaction of strength \hbar/\tau_{SE}, with an environment of neighboring
spins, degrades this oscillation within a decoherence time scale \tau_{\phi}.
While the experimental frequency \omega and decoherence time \tau_{\phi} were
expected to be roughly proportional to b/\hbar and \tau_{SE} respectively, we
present here experiments that show drastic deviations in both \omega and
\tau_{\phi}. By solving the many spin dynamics, we prove that the swapping
regime is restricted to \Delta E \tau_{SE} > \hbar. Beyond a critical
interaction with the environment the swapping freezes and the decoherence rate
drops as 1/\tau_{\phi} \propto (b/\hbar)^2 \tau_{SE}. The transition between
quantum dynamical phases occurs when \omega \propto
\sqrt{(b/\hbar)^{2}-(k/\tau_{SE})^2} becomes imaginary, resembling an
overdamped classical oscillator. Here, 0<k^2<1 depends only on the anisotropy
of the system-environment interaction, being 0 for isotropic and 1 for XY
interactions. This critical onset of a phase dominated by the Quantum Zeno
effect opens up new opportunities for controlling quantum dynamics.


  A phenomenon of weak transient chaos is discussed that is caused by
sub-exponential divergence of trajectories in the basin of a non-chaotic
attractor. Such a regime is not easy to detect, because conventional
characteristics, such as the largest Lyapunov exponent is non-positive. Here we
study, how such a divergence can be exposed and detected. First, we show that
weak transient chaos can be exposed if a small random perturbation is added to
the system, leading to positive values of the largest Lyapunov exponent.
Second, we introduce an alternative definition of the Lyapunov exponent, which
allows us to detect weak transient chaos in the deterministic unperturbed
system. We show that this novel characteristic becomes positive, reflecting
transient chaos. We demonstrate this phenomenon and its detection using a
master-slave system where the master possesses a heteroclinic cycle attractor,
while the slave is the Van-der-Pol-Duffing oscillator possessing a stable limit
cycle.


  A stationary Josephson effect in the ballistic contact of two d-wave
superconductors with different axes orientation and with tangential transport
current in the banks is considered theoretically. We study the influence of the
transport current on the current-phase dependence for the Josephson and
tangential currents at the interface. It is demonstrated that the spontaneous
surface current at the interface depends on the transport current in the banks
due to the interference of the angle-dependent current-carrying condensate wave
functions of the two superconductors.


  We summarize the results of a multiwavelength observing campaign on the
massive eclipsing binary CPD-41deg7742, another remarkable object in the young
open cluster NGC 6231. Our campaign relies on high resolution echelle
spectroscopy, narrow-band optical photometry, and XMM-Newton X-ray
observations. Combined with the spectroscopic analysis, the light curve
analysis provides a direct measurement of the masses and sizes of the system
components. However, the most outstanding results come from the XMM-Newton
observations. Our 180 ks campaign towards NGC 6231, and CPD-41deg7742, provides
an unprecedented phase coverage of such a close early-type binary. The EPIC-MOS
light curves almost fully cover the 2.4 day period of the system and the
brightness of the object is sufficient to yield a time resolution as tight as 1
ks. The X-ray flux presents clear variations along the orbit, that we interpret
as the signature of an unusual wind interaction. We indeed expect that, in this
O+B system, the dominant primary wind crashes into the secondary surface,
leading to a wind-photosphere interaction. As a strong support to our
interpretation, we provide a geometrical model that associates an extra X-ray
emission to the secondary inner surface. Though quite simple, the present model
matches the main features of the X-ray light curve.


  In this article, we introduce the concept of weakly uniquely stationary
representations. This framework enables us to investigate the complementability
of closed subspaces within the context of continuous cohomology with
coeffcients in Banach modules. As an application, we extend and refine several
cohomological results from the literature, particularly in the settings of
nilpotent groups, products of groups, and lattices.


  We develop a model of sneutrino inflation that is charged under $U(1)_{B-L}$
gauge symmetry in no-scale supergravity framework. The model provides an
interesting modification of tribrid inflation. We impose $U(1)_R$ symmetry on
the renormalizable level while allow Planck suppressed non-renormalizable
operators that break R-symmetry. This plays a crucial role in realizing a
Starobinsly-like inflation scenario from one hand. On the other hand it plays
essential role, as well as SUSY breaking effects, in deriving the neutrino
masses from TeV inverse seesaw mechanism. Thus we provide an interpretation for
the extremely small value of the $\mu_S$ mass parameter required for inverse
seesaw mechanism. We discuss the reheating scenario and the possible
constraints on the parameter space in connection to neutrino masses.


  The structure of spherical micelles of the diblock poly(styrene-block-acrylic
acid) [PS-b-PA] copolymer in water was investigated up to concentrations where
the polyelectrolyte coronal layers have to shrink and/or interpenetrate in
order to accommodate the micelles in the increasingly crowded volume. We
obtained the partial structure factors pertaining to the core and corona
density correlations with small angle neutron scattering (SANS) and contrast
matching in the water. The counterion structure factor was obtained with small
angle X-ray scattering (SAXS) with a synchrotron radiation source. Furthermore,
we have measured the flow curves and dynamic visco-elastic moduli. The
functionality of the micelles is fixed with a 9 nm diameter PS core and a
corona formed by around 100 PA arms. As shown by the SAXS intensities, the
counterions are distributed in the coronal layer with the same density profile
as the corona forming segments. Irrespective ionic strength and micelle charge,
the corona shrinks with increasing packing fraction. At high charge and minimal
screening conditions, the polyelectrolyte chains remain almost fully stretched
and they interdigitate once the volume fraction exceeds the critical value
0.53+/-0.02. Interpenetration of the polyelectrolyte brushes also controls the
fluid rheology: the viscosity increases by 3 orders of magnitude and the
parallel frequency scaling behavior of the dynamic moduli suggests the
formation of a physical gel. In excess salt, the coronal layers are less
extended and they do not interpenetrate in the present concentration range.


  We use a reformulation of compositional game theory to reunite game theory
with game semantics, by viewing an open game as the System and its choice of
contexts as the Environment. Specifically, the system is jointly controlled by
$n \geq 0$ noncooperative players, each independently optimising a real-valued
payoff. The goal of the system is to play a Nash equilibrium, and the goal of
the environment is to prevent it. The key to this is the realisation that
lenses (from functional programming) form a dialectica category, which have an
existing game-semantic interpretation.
  In the second half of this paper, we apply these ideas to build a compact
closed category of `computable open games' by replacing the underlying
dialectica category with a wave-style geometry of interaction category,
specifically the Int-construction applied to the cartesian monoidal category of
directed-complete partial orders.


  The Internet of Things (IoT) is expected to generate large amounts of
heterogeneous data from diverse sources including physical sensors, user
devices, and social media platforms. Over the last few years, significant
attention has been focused on personal data, particularly data generated by
smart wearable and smart home devices. Making personal data available for
access and trade is expected to become a part of the data driven digital
economy. In this position paper, we review the research challenges in building
personal Databoxes that hold personal data and enable data access by other
parties, and potentially thus sharing of data with other parties. These
Databoxes are expected to become a core part of future data marketplaces.


  In this paper we develop a framework for discretely compounding interest
rates which is based on the forward price process approach. This approach has a
number of advantages, in particular in the current market environment. Compared
to the classical as well as the L\'evy Libor market model, it allows in a
natural way for negative interest rates and has superb calibration properties
even in the presence of extremely low rates. Moreover, the measure changes
along the tenor structure are simplified significantly. These properties make
it an excellent base for a post-crisis multiple curve setup. Two variants for
multiple curve constructions are discussed. Time-inhomogeneous L\'evy processes
are used as driving processes. An explicit formula for the valuation of caps is
derived using Fourier transform techniques. Based on the valuation formula, we
calibrate the two model variants to market data.


  Recent experimental observations of unexpectedly large thermal Hall
conductivities, $\kappa_H$, in insulating materials, including the parent
compounds of the high temperature superconducting cuprates, likely reflect an
extrinsic contribution from a yet to be identified extrinsic source of skew
scattering of acoustic phonons. We show that resonant scattering of phonons
from a certain class of three-level systems produces strong skew scattering in
the presence of a modest magnetic field. We interpret this as a first step
towards understanding the experiments.


  We analyze and test using Fourier extensions that minimize a Hilbert space
norm for the purpose of solving partial differential equations (PDEs) on
surfaces. In particular, we prove that the approach is arbitrarily high-order
and also show a general result relating boundedness, solvability, and
convergence that can be used to find eigenvalues. The method works by extending
a solution to a surface PDE into a box-shaped domain so that the differential
operators of the extended function agree with the surface differential
operators, as in the Closest Point Method. This differs from approaches that
require a basis for the surface of interest, which may not be available.
Numerical experiments are also provided, demonstrating super-algebraic
convergence. Current high-order methods for surface PDEs are often limited to a
small class of surfaces or use radial basis functions (RBFs). Our approach
offers certain advantages related to conditioning, generality, and ease of
implementation. The method is meshfree and works on arbitrary surfaces (closed
or non-closed) defined by point clouds with minimal conditions.


  Gauge bosons associated to new gauge symmetries under which the standard
model particles are not charged are predicted in many extensions of the
standard model of particles and interactions. We show that under very general
conditions, the average energy-momentum tensor of these rapidly oscillating
vector fields is isotropic for any locally inertial observer. This result has a
fundamental importance in order to consider coherent vector fields as a viable
alternative to support models of dark matter, dark energy or inflation.


  Standard stellar evolution theory poorly predicts the surface abundances of
chemical species in low-mass, red giant branch (RGB) stars. Observations show
an enhancement of p-p chain and CNO cycle products in red giant envelopes,
which suggests the existence of non-canonical mixing that brings interior
burning products to the surface of these stars. The 12C/13C ratio is a highly
sensitive abundance metric used to probe this mixing. We investigate extra RGB
mixing by examining (1) how 12C/13C is altered along the RGB and (2) how
12C/13C changes for stars of varying age and mass. Our sample consists of 43
red giants spread over 15 open clusters from the Sloan Digital Sky Survey's
APOGEE DR17 that have reliable 12C/13C ratios derived from their APOGEE
spectra. We vetted these 12C/13C ratios and compared them as a function of
evolution and age/mass to the standard mixing model of stellar evolution and to
a model that includes prescriptions for RGB thermohaline mixing and stellar
rotation. We find that the observations deviate from standard mixing models,
implying the need for extra mixing. Additionally, some of the abundance
patterns depart from the thermohaline model, and it is unclear whether these
differences are due to incomplete observations, issues inherent to the model,
our assumption of the cause of extra mixing, or any combination of these
factors. Nevertheless, the surface abundances across our age/mass range clearly
deviate from the standard model, agreeing with the notion of a universal
mechanism for RGB extra mixing in low-mass stars.


  Soft robots offer significant advantages in adaptability, safety, and
dexterity compared to conventional rigid-body robots. However, it is
challenging to equip soft robots with accurate proprioception and tactile
sensing due to their high flexibility and elasticity. In this work, we describe
the development of a vision-based proprioceptive and tactile sensor for soft
robots called GelFlex, which is inspired by previous GelSight sensing
techniques. More specifically, we develop a novel exoskeleton-covered soft
finger with embedded cameras and deep learning methods that enable
high-resolution proprioceptive sensing and rich tactile sensing. To do so, we
design features along the axial direction of the finger, which enable
high-resolution proprioceptive sensing, and incorporate a reflective ink
coating on the surface of the finger to enable rich tactile sensing. We design
a highly underactuated exoskeleton with a tendon-driven mechanism to actuate
the finger. Finally, we assemble 2 of the fingers together to form a robotic
gripper and successfully perform a bar stock classification task, which
requires both shape and tactile information. We train neural networks for
proprioception and shape (box versus cylinder) classification using data from
the embedded sensors. The proprioception CNN had over 99\% accuracy on our
testing set (all six joint angles were within 1 degree of error) and had an
average accumulative distance error of 0.77 mm during live testing, which is
better than human finger proprioception. These proposed techniques offer soft
robots the high-level ability to simultaneously perceive their proprioceptive
state and peripheral environment, providing potential solutions for soft robots
to solve everyday manipulation tasks. We believe the methods developed in this
work can be widely applied to different designs and applications.


  Environment-induced localization transitions (LT) occur when a small quantum
system interacts with a bath of harmonic oscillators. At equilibrium, LTs are
accompanied by an entropy change, signaling the loss of coherence. Despite
extensive efforts, equilibrium LTs have yet to be observed. Here, we
demonstrate that ongoing experiments on double quantum dots that measure
entropy using a nearby quantum point contact (QPC) realize the celebrated
spin-boson model and allow to measure the entropy change of its LT. We find a
Kosterlitz-Thouless flow diagram, leading to a universal jump in the spin-bath
interaction, reflected in a discontinuity in the zero temperature QPC
conductance.


  We study in detail the little-Higgs model proposed by Low, Skiba and Smith
with an SU(6)/Sp(6) group structure. The effective theory at the TeV scale is a
two-Higgs doublet model (2HDM) with additional heavy vector-like fermions and
vector-bosons. We identify a set of independent input parameters and develop
expressions for masses and couplings in terms of these. We perform a random
scan of the parameter space and find points that satisfy constraints, including
the recent 8 TeV LHC Higgs measurements, namely, the Higgs mass, Higgs
couplings to the top, bottom, $\tau$, $W^\pm$ and $Z$, top-quark mass, and
collider bounds on colored vector-like fermions ($t'$ and $b'$), and also
precision electroweak constraints. The LHC constraints on the $hWW$ and $hZZ$
couplings are satisfied by being close to the "alignment limit". We find how
fine-tuned the model is after including these constraints. For the points that
satisfy the constraints, we present the 1-loop effective couplings of the
CP-even and CP-odd neutral scalars to two gluons including contributions of
standard model and heavy vector-like quarks. We also present the branching
ratios of the heavy neutral scalars into the $\gamma\gamma,\, \tau\bar\tau,\,
b\bar b,\, t\bar t, WW, ZZ, Zh, hh$ modes, and the heavy charged scalar into
$tb,\, \tau\nu, cs, W h$ modes. These will aid searches of the heavy scalars at
the LHC and other future colliders.


  Most existing deep learning models are trained based on the closed-world
assumption, where the test data is assumed to be drawn i.i.d. from the same
distribution as the training data, known as in-distribution (ID). However, when
models are deployed in an open-world scenario, test samples can be
out-of-distribution (OOD) and therefore should be handled with caution. To
detect such OOD samples drawn from unknown distribution, OOD detection has
received increasing attention lately. However, current endeavors mostly focus
on grid-structured data and its application for graph-structured data remains
under-explored. Considering the fact that data labeling on graphs is commonly
time-expensive and labor-intensive, in this work we study the problem of
unsupervised graph OOD detection, aiming at detecting OOD graphs solely based
on unlabeled ID data. To achieve this goal, we develop a new graph contrastive
learning framework GOOD-D for detecting OOD graphs without using any
ground-truth labels. By performing hierarchical contrastive learning on the
augmented graphs generated by our perturbation-free graph data augmentation
method, GOOD-D is able to capture the latent ID patterns and accurately detect
OOD graphs based on the semantic inconsistency in different granularities
(i.e., node-level, graph-level, and group-level). As a pioneering work in
unsupervised graph-level OOD detection, we build a comprehensive benchmark to
compare our proposed approach with different state-of-the-art methods. The
experiment results demonstrate the superiority of our approach over different
methods on various datasets.


  In this paper we construct path integral representations of the boundary
states in some special backgrounds such as the U(1) gauge field background, the
linear dilaton background and the open string tachyon background. The initial
purpose of this paper is to construct a general solution of the boundary
conformal field theory with the analytical approach, mainly for the constraint
equations$(L_{n}-\tilde{L}_{-n}) |B > =0 $ are difficult to be solved to obtain
the solution represented by string modes from the pure algebraic approach.
However in the path integral representation it is easy transforming those
algebraic equations into the differential equations which can be solved.
Another purpose of this paper is to try to explore an open question. we do not
know how to construct an exact theory of D-branes in the general background
until now. However many recent researches show the boundary state description
indeed seizes some fundamental features of D-branes in the rather special
backgrounds. Since the general background field effects can be easily
introduced in the path integral representation, we argue that path integral
representation of the boundary state should provide an exact description of D
branes in the general backgrounds.


  The simplified Lennard-Jones (LJ) potential minimization problem is
$f(x)=4\sum_{i=1}^N \sum_{j=1,j<i}^N (\frac{1}{\tau_{ij}^6}
-\frac{1}{\tau_{ij}^3}) {subject to} x\in \mathbb{R}^n,$ where
$\tau_{ij}=(x_{3i-2}-x_{3j-2})^2 +(x_{3i-1}-x_{3j-1})^2 +(x_{3i} -x_{3j})^2$,
$(x_{3i-2},x_{3i-1},x_{3i})$ is the coordinates of atom $i$ in $\mathbb{R}^3$,
$i,j=1,2,...,N(\geq 2 \quad \text{integer})$, $n=3N$ and $N$ is the whole
number of atoms. The nonconvexity of the objective function and the huge number
of local minima, which is growing exponentially with $N$, interest many
mathematical optimization experts. In this paper, the canonical dual theory
elegantly tackles this problem illuminated by the amyloid fibril molecular
model building.
  Keywords: Mathematical Canonical Duality Theory $\cdot$ Mathematical
Optimization $\cdot$ Lennard-Jones Potential Minimization Problem $\cdot$
Global Optimization.


  We have constructed a new, fast, robust and reliable pipeline to detect
variable stars from the ROTSE-IIId archival data. Turkish share of ROTSE-III
archive contains approximately one million objects from a large field of view
(1.85\dgr) and it considerably covers a large portion of northern sky
($\delta>-25\dgr$). The unfiltered ROTSE-III magnitude of the objects ranges
from 7.7 to 16.9. The main stages of the new pipeline are as follows: Source
extraction, astrometry of the objects, light curve generation and inhomogeneous
ensemble photometry. A high performance computing (HPC) algorithm has also been
implemented into the pipeline where we had a good performance even on a
personal computer. Running the algorithms of the pipeline on a cluster
decreases analysis time significantly from weeks to hours. The pipeline is
especially tested against long period variable stars with periods of a few
hundred days (e.g Mira and SR) and variables having periods starting from a few
days to a few hundred days were detected.


  Over the past 20 years, bright sources of entangled photons have led to a
renaissance in quantum optical interferometry. Optical interferometry has been
used to test the foundations of quantum mechanics and implement some of the
novel ideas associated with quantum entanglement such as quantum teleportation,
quantum cryptography, quantum lithography, quantum computing logic gates, and
quantum metrology. In this paper, we focus on the new ways that have been
developed to exploit quantum optical entanglement in quantum metrology to beat
the shot-noise limit, which can be used, e.g., in fiber optical gyroscopes and
in sensors for biological or chemical targets. We also discuss how this
entanglement can be used to beat the Rayleigh diffraction limit in imaging
systems such as in LIDAR and optical lithography.


  When immigrating to a new country, it is easy to feel overwhelmed by the need
to obtain information on financial support, housing, schooling, language
courses, and other issues. If relocation is rushed or even forced, the
necessity for high-quality answers to such questions is all the more urgent.
Official immigration counselors are usually overbooked, and online systems
could guide newcomers to the requested information or a suitable counseling
service.
  To this end, we present OMoS-QA, a dataset of German and English questions
paired with relevant trustworthy documents and manually annotated answers,
specifically tailored to this scenario. Questions are automatically generated
with an open-source large language model (LLM) and answer sentences are
selected by crowd workers with high agreement. With our data, we conduct a
comparison of 5 pretrained LLMs on the task of extractive question answering
(QA) in German and English. Across all models and both languages, we find high
precision and low-to-mid recall in selecting answer sentences, which is a
favorable trade-off to avoid misleading users. This performance even holds up
when the question language does not match the document language. When it comes
to identifying unanswerable questions given a context, there are larger
differences between the two languages.


  We implement a computational pipeline based on a recent machine learning
technique, namely the Topological Data Analysis (TDA), that has the capability
of extracting powerful information-carrying topological features. We apply such
a method to the study quantum phase transitions and, to showcase its validity
and potential, we exploit such a method for the investigation of two paramount
important quantum systems: the 2D periodic Anderson model and the Hubbard model
on the honeycomb lattice, both cases on the half-filling. To this end, we have
performed unbiased auxiliary field quantum Monte Carlo simulations, feeding the
TDA with snapshots of the Hubbard-Stratonovich fields through the course of the
simulations The quantum critical points obtained from TDA agree quantitatively
well with the existing literature, therefore suggesting that this technique
could be used to investigate quantum systems where the analysis of the phase
transitions is still a challenge.


  In the paper, the authors establish integral representations of some
functions related to the remainder of Burnside's formula for the gamma function
and find the (logarithmically) complete monotonicity of these and related
functions. These results extend and generalize some known conclusions.


  We propose two experimental setups that allow for the implementation and the
detection of fractional solitons of the Goldstone-Wilczek type. The first setup
is based on two magnetic barriers at the edge of a quantum spin Hall system for
generating the fractional soliton. If then a quantum point contact is created
with the other edge, the linear conductance shows evidence of the fractional
soliton. The second setup consists of a single magnetic barrier covering both
edges and implementing a long quantum point contact. In this case, the
fractional soliton can unambiguously be detected as a dip in the conductance
without the need to control the magnetization of the barrier.


  Equipment shortages in Africa undermine Science, Technology, Engineering and
Mathematics (STEM) Education. We have pioneered the LabHackathon (LabHack): a
novel initiative that adapts the conventional hackathon and draws on insights
from the Open Hardware movement and Responsible Research and Innovation (RRI).
LabHacks are fun, educational events that challenge student participants to
build frugal and reproducible pieces of laboratory equipment. Completed designs
are then made available to others. LabHacks can therefore facilitate the open
and sustainable design of laboratory equipment, in situ, in Africa. In this
case study we describe the LabHackathon model, discuss its application in a
pilot event held in Zimbabwe and outline the opportunities and challenges it
presents.


  We consider item allocation to individual agents who have additive
valuations, in settings in which there are protected groups, and the allocation
needs to give each protected group its "fair" share of the total welfare.
Informally, within each protected group we consider the total welfare that the
allocation gives the members of the group, and compare it to the maximum
possible welfare that an allocation can give to the group members. An
allocation is fair towards the group if the ratio between these two values is
no worse then the relative size of the group. For divisible items, our formal
definition of fairness is based on the proportional share, whereas for
indivisible items, it is based on the anyprice share.
  We present examples in which there are no fair allocations, and even not
allocations that approximate the fairness requirement within a constant
multiplicative factor. We then attempt to identify sufficient conditions for
fair or approximately fair allocations to exist. For example, for indivisible
items, when agents have identical valuations and the family of protected groups
is laminar, we show that if the items are chores, then an allocation that
satisfies every fairness requirement within a multiplicative factor no worse
than two exists and can be found efficiently, whereas if the items are goods,
no constant approximation can be guaranteed.


  Let x(t) be a trajectory of the gradient of a real analytic function and
suppose that x_0 is a limit point of x(t). We prove the gradient conjecture of
R. Thom which states that the secants of x(t) at x_0 have a limit. Actually we
show a stronger statement: the radial projection of x(t) from x_0 onto the unit
sphere has finite length.


  We present a Gauss-Newton-Krylov solver for large deformation diffeomorphic
image registration. We extend the publicly available CLAIRE library to
multi-node multi-graphics processing unit (GPUs) systems and introduce novel
algorithmic modifications that significantly improve performance. Our
contributions comprise ($i$) a new preconditioner for the reduced-space
Gauss-Newton Hessian system, ($ii$) a highly-optimized multi-node multi-GPU
implementation exploiting device direct communication for the main
computational kernels (interpolation, high-order finite difference operators
and Fast-Fourier-Transform), and ($iii$) a comparison with state-of-the-art CPU
and GPU implementations. We solve a $256^3$-resolution image registration
problem in five seconds on a single NVIDIA Tesla V100, with a performance
speedup of 70% compared to the state-of-the-art. In our largest run, we
register $2048^3$ resolution images (25 B unknowns; approximately 152$\times$
larger than the largest problem solved in state-of-the-art GPU implementations)
on 64 nodes with 256 GPUs on TACC's Longhorn system.


  In this work, we model the movement of a figure skater gliding on ice by the
Chaplygin sleigh, a classic pedagogical example of a nonholonomic mechanical
system. The Chaplygin sleigh is controlled by a movable added mass, modeling
the movable center of mass of the figure skater. The position and velocity of
the added mass act as controls that can be used to steer the skater in order to
produce prescribed patterns. For any piecewise smooth prescribed curve, this
model can be used to determine the controls needed to reproduce that curve by
approximating the curve with circular arcs. Tracing of the circular arcs is
exact in our control procedure, so the accuracy of the method depends solely on
the accuracy of approximation of a trajectory by circular arcs. To reproduce
the individual elements of a pattern, we employ an optimization algorithm. We
conclude by reproducing a classical "double flower" figure skating pattern and
compute the resulting controls.


  In this paper, we prove the Gan-Gross-Prasad conjecture and the Ichino-Ikeda
conjecture for unitary groups $U_n\times U_{n+1}$ in all the endoscopic cases.
Our main technical innovation is the computation of the contributions of
certain cuspidal data, called $*$-generic, to the Jacquet-Rallis trace formula
for linear groups. We offer two different computations of these contributions:
one, based on truncation, is expressed in terms of regularized Rankin-Selberg
periods of Eisenstein series and Flicker-Rallis intertwining periods. The
other, built upon Zeta integrals, is expressed in terms of functionals on the
Whittaker model. A direct proof of the equality between the two expressions is
also given. Finally several useful auxiliary results about the spectral
expansion of the Jacquet-Rallis trace formula are provided.


  One important yet exceedingly rare property of the cuprate high-temperature
superconductors is the presence of a single correlated $d$ band in the
low-energy spectrum, leading to the one-band Hubbard model as the minimal
description. In order to search for materials with interesting strong
correlation physics as well as possible benchmark systems for the one-band
Hubbard model, here we present a new approach to find one-band correlated
materials analogous to the cuprates by leveraging the emerging area of
materials informatics. Using the composition, structure, and formation energy
of more than half a million real and hypothetical inorganic crystalline
materials in the Open Quantum Materials Database, we search for synthesizable
materials whose nominal transition metal $d$ electron count and crystal field
are compatible with achieving an isolated half-filled $d$ band. Five Cu
compounds, including bromide, oxide, selenate, and pyrophosphate chemistries,
are shown to successfully achieve the one-band electronic structure based on
density functional theory band structure calculations. Further calculations
including magnetism and explicit on-site Coulomb interaction reveal significant
evidence for strong correlation physics in the five candidates, including Mott
insulating behavior and antiferromagnetism. The success of our data-driven
approach to discovering new correlated materials opens up new avenues to design
and discover materials with rare electronic properties.


  Neutral models for the dynamics of a system of competing species are used,
nowadays, to describe a wide variety of empirical communities. These models are
used in many situations, ranging from population genetics and ecological
biodiversity to macroevolution and cancer tumors. One of the main issues
discussed within this framework is the relationships between the abundance of a
species and its age. Here we provide a comprehensive analysis of the
age-abundance relationships for fixed-size and growing communities. Explicit
formulas for the average and the most likely age of a species with abundance
$n$ are given, together with the full probability distribution function. We
further discuss the universality of these results and their applicability to
the tropical forest community.


  In this paper convex optimization techniques are employed for
  convex optimization problems in infinite dimensional Hilbert spaces. A first
order optimality condition is given. Let $f : \mathbb{R}^{n}\rightarrow
\mathbb{R}$ and let $x\in \mathbb{R}^{n}$ be a local solution to the problem
$\min_{x\in \mathbb{R}^{n}} f(x).$ Then $f'(x,d)\geq 0$ for every direction
$d\in \mathbb{R}^{n}$ for which $f'(x,d)$ exists. Moreover, Let $f :
\mathbb{R}^{n}\rightarrow \mathbb{R}$ be differentiable at $x^{*}\in
\mathbb{R}^{n}.$ If $x^{*}$ is a local minimum of $f$, then $\nabla f(x^{*}) =
0.$ A simple application involving the Dirichlet problem is also given.


  This paper treats absorption problems for the one-dimensional quantum walk
determined by a 2 times 2 unitary matrix U on a state space {0,1,...,N} where N
is finite or infinite by using a new path integral approach based on an
orthonormal basis P, Q, R and S of the vector space of complex 2 times 2
matrices. Our method studied here is a natural extension of the approach in the
classical random walk.


  A pebbling move on a graph consists of taking two pebbles off of one vertex
and placing one pebble on an adjacent vertex. In the traditional pebbling
problem we try to reach a specified vertex of the graph by a sequence of
pebbling moves. In this paper we investigate the case when every vertex of the
graph must end up with at least one pebble after a series of pebbling moves.
The cover pebbling number of a graph is the minimum number of pebbles such that
however the pebbles are initially placed on the vertices of the graph we can
eventually put a pebble on every vertex simultaneously. We find the cover
pebbling numbers of trees and some other graphs. We also consider the more
general problem where (possibly different) given numbers of pebbles are
required for the vertices.


  We have implemented a systematic LSDA and LSDA+U study of the double
perovskites $A_{2}$FeReO$_{6}$ (A=Ba,Sr,Ca) and Sr$_{2}$$M$MoO$_{6}$
(M=Cr,Mn,Fe,Co) for understanding of their intriguing electronic and magnetic
properties. The results suggest a ferrimagnetic (FiM) and half-metallic (HM)
state of $A_{2}$FeReO$_{6}$ (A=Ba,Sr) due to a pdd-$\pi$ coupling between the
down-spin Re$^{5+}$/Fe$^{3+}$ $t_{2g}$ orbitals via the intermediate O
$2p_{\pi}$ ones, also a very similar FiM and HM state of Sr$_{2}$FeMoO$_{6}$.
In contrast, a decreasing Fe $t_{2g}$ component at Fermi level ($E_{F}$) in the
distorted Ca$_{2}$FeReO$_{6}$ partly accounts for its nonmetallic behavior,
while a finite $pdd$-$\sigma$ coupling between the down-spin
Re$^{5+}$/Fe$^{3+}$ $e_{g}$ orbitals being present at $E_{F}$ serves to
stabilize its FiM state. For Sr$_{2}$CrMoO$_{6}$ compared with
Sr$_{2}$FeMoO$_{6}$, the coupling between the down-spin Mo$^{5+}$/Cr$^{3+}$
$t_{2g}$ orbitals decreases as a noticeable shift up of the Cr$^{3+}$ 3d
levels, which is likely responsible for the decreasing $T_{C}$ value and weak
conductivity. Moreover, the calculated level distributions indicate a
Mn$^{2+}$(Co$^{2+}$)/Mo$^{6+}$ ionic state in Sr$_{2}$MnMoO$_{6}$
(Sr$_{2}$CoMoO$_{6}$), in terms of which their antiferromagnetic insulating
ground state can be interpreted. While orbital population analyses show that
owing to strong intrinsic pd covalence effects, Sr$_{2}M$MoO$_{6}$
(M=Cr,Mn,Fe,Co) have nearly the same valence state combinations, as accounts
for the similar M-independent spectral features observed in them.


  We present preliminary results for the heavy-light leptonic decay constants
in the presence of three light dynamical flavors. We generate dynamical
configurations with improved staggered and gauge actions and analyze them for
heavy-light physics with tadpole improved clover valence quarks. When the scale
is set by $m_\rho$, we find an increase of approximately 23% in $f_B$ with
three dynamical flavors over the quenched case. Discretization errors appear to
be small (of order 3% or less) in the quenched case but have not yet been
measured in the dynamical case.


  Much recent research has been devoted to modeling effects within type theory.
Building on this work, we observe that effectful type theories can provide a
foundation on which to build semantics for more complex programming constructs
and program logics, extending the reasoning principles that apply within the
host effectful type theory itself. Concretely, our main contribution is a
semantics for concurrent separation logic (CSL) within the F* proof assistant
in a manner that enables dependently typed, effectful F* programs to make use
of concurrency and to be specified and verified using a full-featured,
extensible CSL. In contrast to prior approaches, we directly derive the
partial-correctness Hoare rules for CSL from the denotation of computations in
the effectful semantics of non-deterministically interleaved atomic actions.
Demonstrating the flexibility of our semantics, we build generic, verified
libraries that support various concurrency constructs, ranging from dynamically
allocated, storable spin locks, to protocol-indexed channels. We conclude that
our effectful semantics provides a simple yet expressive basis on which to
layer domain-specific languages and logics for verified, concurrent
programming.


  In this paper, we establish an exponential periodic turnpike property for
linear quadratic optimal control problems governed by periodic systems in
infinite dimension. We show that the optimal trajectory converges exponentially
to a periodic orbit when the time horizon tends to infinity. Similar results
are obtained for the optimal control and adjoint state. Our proof is based on
the large time behavior of solutions of operator differential Riccati equations
with periodic coefficients.


  Hydrogen trapping ability of various metal - ethylene complexes has been
studied at the B3LYP and MP2 level of theory using the 6-311+G(d,p) basis set.
Different global and local reactivity descriptors and the associated electronic
structure principles provide important insights into the associated
interactions. There exist two distinct classes of bonding patterns, viz., a
Kubas-type interaction between the metal and the H2 molecule behaving as a
{\eta}2-ligand and an electrostatic interaction between the metal and the
atomic hydrogens.


  This paper is devoted to the estimation of the number of points of bounded
height on fibrations in toric varieties over algebraic varieties, generalizing
previous work by Strauch and the second author. Under reasonable hypotheses on
``Arakelov L-functions'' of the base, we show how to deduce a good estimate for
the open subset of the total space of the unerlying fibration in torus. In
passing, we improve drastically the error term for toric varieties themselves,
generalizing a theorem by de la Breteche over any number field.


  Accretion and ejection of matter in active galactic nuclei (AGN) are tightly
connected phenomena and represent fundamental mechanisms regulating the growth
of the central supermassive black hole and the evolution of the host galaxy.
However, the exact physical processes involved are not yet fully understood. We
present a high-resolution spectral analysis of a simultaneous \xmm\ and
\nustar\ observation of the narrow line Seyfert 1 (NLS1) AGN 1H 1934-063,
during which the X-ray flux dropped by a factor of $\sim6$ and subsequently
recovered within 140 kiloseconds. By means of the time-resolved and
flux-resolved X-ray spectroscopy, we discover a potentially variable warm
absorber and a relatively stable ultra-fast outflow (UFO,
$v_\mathrm{UFO}\sim-0.075\,c$) with a mild ionization state
($\log(\xi/\mathrm{erg\,cm\,s^{-1})}\sim1.6$). The detected emission lines
(especially a strong and broad feature around 1\,keV) are of unknown origin and
cannot be explained with emission from plasmas in photo- or
collisional-ionization equilibrium. Such emission lines could be well described
by a strongly blueshifted ($z\sim-0.3$) secondary reflection off the base of
the equatorial outflows, which may reveal the link between the reprocessing of
the inner accretion flow photons and the ejection. However, this scenario
although being very promising is only tentative and will be tested with future
observations.


  The general and practical inversion of diffraction data-producing a computer
model correctly representing the material explored - is an important unsolved
problem for disordered materials. Such modeling should proceed by using our
full knowledge base, both from experiment and theory. In this paper, we
describe a robust method to jointly exploit the power of ab initio atomistic
simulation along with the information carried by diffraction data. The method
is applied to two very different systems: amorphous silicon and two
compositions of a solid electrolyte memory material silver-doped GeSe3 . The
technique is easy to implement, is faster and yields results much improved over
conventional simulation methods for the materials explored. By direct
calculation, we show that the method works for both poor and excellent glass
forming materials. It offers a means to add a priori information in first
principles modeling of materials, and represents a significant step toward the
computational design of non-crystalline materials using accurate interatomic
interactions and experimental information.


  Solid-state quantum light sources are being intensively investigated for
applications in quantum technology. A key challenge is to extract light from
host materials with high refractive index, where efficiency is limited by
refraction and total internal reflection. Here we show that an index-matched
solid immersion lens can, if placed sufficiently close to the semiconductor,
extract light coupled through the evanescent field at the surface. Using both
numerical simulations and experiments, we investigate how changing the
thickness of the spacer between the semiconductor and lens impacts the
collection efficiency (CE). Using automatic selection and measurement of 100 s
of individually addressable colour centres in several aluminium nitride samples
we demonstrate spacer-thickness dependent photon CE enhancement, with a mean
enhancement factor of 4.2 and a highest measured photon detection rate of 743
kcps.


  A universal formula is shown to predict the dynamics of public opinion
including eventual sudden and unexpected outbreaks of minority opinions within
a generic parameter space of five dimensions. The formula is obtained combining
and extending several components of Galam model of opinion dynamics, otherwise
treated separately, into one single update equation, which then deploys in a
social space of five dimensions. Four dimensions account for a rich diversity
of individual traits within a heterogeneous population, including
differentiated stubbornness, contrarianism, and embedded prejudices. The fifth
dimension is the size for the discussing update groups. Having one single
formula allows exploring the complete geometry of the underlying landscape of
opinion dynamics. Attractors and tipping points, which shape the topology of
the different possible dynamics flows, are unveiled. Driven by repeated
discussions among small groups of people during a social or political public
campaign, the phenomenon of minority spreading and parallel majority collapse
are thus revealed ahead of their occurrence. Accordingly, within the opinion
landscape, unexpected and sudden events like Brexit and Trump victories become
visible within a forecast time horizon making them predictable. Despite the
accidental nature of the landscape, evaluating the parameter values for a
specific case allows to single out which basin of attraction is going to drive
the associate dynamics and thus a prediction of the outcome becomes feasible.
The model may apply to a large spectrum of social situations including voting
outcomes, market shares and societal trends, allowing to envision novel winning
strategies in competing environments.


  A simple matrix is a (0,1)-matrix with no repeated columns. For a
(0,1)-matrix $F$, we say that a (0,1)-matrix $A$ has $F$ as a configuration if
there is a submatrix of $A$ which is a row and column permutation of $F$ (trace
is the set system version of a configuration). Let $\ncols{A}$ denote the
number of columns of $A$. Let ${\cal F}$ be a family of matrices. We define the
extremal function $forb(m,{\cal F})=\max{\ncols{A} : A is m-rowed simple matrix
and has no configuration F\in{\cal F}}$. We consider some families ${\cal
F}=\{F_1,F_2,\ldots, F_t\}$ such that individually each $\forb(m,F_i)$ has
greater asymptotic growth than $\forb(m,{\cal F})$.


  This paper details the development of high-quality, c-axis oriented AlN thin
films up to 2 {\mu}m thick, using sputtering on platinum-coated SOI substrates
for use in piezoelectric MEMS. Our comprehensive studies illustrate how
important growth parameters such as the base Pt electrode quality, deposition
temperature, power, and pressure, can influence film quality. With careful
adjustment of these parameters, we managed to manipulate residual stresses
(from compressive -1.2 GPa to tensile 230 MPa), and attain a high level of
orientation in the AlN thin films, evidenced by < 5deg FWHM X-Ray diffraction
peak widths. We also report on film surface quality regarding roughness, as
assessed by atomic force microscopy, and grain size, as determined through
scanning electron microscopy. Having attained the desired film quality, we
proceeded to a fabrication process to create piezoelectric micromachined
ultrasound transducers (PMUTs) with the AlN on SOI material stack, using deep
reactive ion etching (DRIE). Initial evaluations of the vibrational behavior of
the created devices, as observed through Laser Doppler Vibrometry, hint at the
potential of these optimized AlN thin films for MEMS transducer development.


  We study the interplay effect of spin-orbit coupling(SOC) and optical lattice
to the single-particle physics and superfluid-insulator transition in ultracold
Fermi gases. We consider the type of SOC that has been realized in cold atoms
experiments via two-photon Raman processes. Our analyses are based on the
knowledge of full single-particle spectrum in lattices, without relying on any
tightbinding approximation.We evaluate existing tight-binding models and point
out their limitations in predicting the correct single-particle physics due to
the missed high-band contributions. Moreover, we show that the Raman field
(creating SOC) can induce band-gap closing in a two-dimensional optical
lattice, leading to the intriguing phenomenon of superfluidity-reentrance for
interacting fermions at integer filling. We present the superfluid-insulator
phase diagram in a wide parameter regime of chemical potentials and Raman
fields. All these results are far beyond any tight-binding model can predict,
and can be directly probed in current cold atoms experiments.


  We show that eigen-energies and energy eigenstates play different roles in
the equilibration process of an isolated quantum system. Their roles are
revealed numerically by exchanging the eigen-energies between an integrable
model and a non-integrable model. We ?find that the structure of eigenenergies
of a non-integrable model characterized by non-degeneracy ensures that quantum
revival occurs rarely whereas the energy eigenstates of a non-integrable model
suppress the fluctuations for the equilibrated quantum state. Our study is
aided with a quantum entropy that describes how randomly a wave function is
distributed in quantum phase space. We also demonstrate with this quantum
entropy the validity of Berry's conjecture for energy eigenstates. This implies
that the energy eigenstates of a non-integrable model appear indeed "random".


  The Fred Young Submillimeter Telescope (FYST), on Cerro Chajnantor in the
Atacama desert of Chile, will conduct wide-field and small deep-field surveys
of the sky with more than 100,000 detectors on the Prime-Cam instrument.
Kinetic inductance detectors (KIDs) were chosen as the primary sensor
technology for their high density focal plane packing. Additionally, they
benefit from low cost, ease of fabrication, and simplified cryogenic readout,
which are all beneficial for successful deployment at scale. The cryogenic
multiplexing complexity is pulled out of the cryostat and is instead pushed
into the digital signal processing of the room temperature electronics. Using
the Xilinx Radio Frequency System on a Chip (RFSoC), a highly multiplexed KID
readout was developed for the first light Prime-Cam and commissioning Mod-Cam
instruments. We report on the performance of the RFSoC-based readout with
multiple detector arrays in various cryogenic setups. Specifically we
demonstrate detector noise limited performance of the RFSoC-based readout under
the expected optical loading conditions.


  Antiferromagnets with vanishingly small (or zero) magnetization are
interesting candidates for spintronics applications. In the present paper we
propose two models for description of the current-induced phenomena in
antiferromagnetic textures. We show that the magnetization that originates from
rotation or oscillations of antiferromagnetic vector can, via $sd$-exchange
coupling, polarize the current and give rise to adiabatic and nonadiabatic spin
torques. Due to the Lorentz-type dynamics of antiferromagnetic moments (unlike
the Galilenian-like dynamics in ferromagnets), the adiabatic spin torque
affects the characteristic lengthscale of the moving texture. Nonadiabatic spin
torque contributes to the energy pumping and can induce the stable motion of
antiferromagnetic texture, but, in contrast to ferromagnets, has pure dynamic
origin. We also consider the current-induced phenomena in artificial
antiferromagnets where the current maps the staggered magnetization of the
structure. In this case the effect of nonadiabatic spin torque is similar to
that in ferromagnetic constituents of the structure. In particular, the current
can remove degeneracy of the translational antiferromagnetic domains
indistinguishable in the external magnetic field and thus can set into motion
the 180$^\circ$ domain wall.


  Deep reinforcement learning (deep RL) is a combination of deep learning with
reinforcement learning principles to create efficient methods that can learn by
interacting with its environment. This has led to breakthroughs in many complex
tasks, such as playing the game "Go", that were previously difficult to solve.
However, deep RL requires significant training time making it difficult to use
in various real-life applications such as Human-Computer Interaction (HCI). In
this paper, we study pre-training in deep RL to reduce the training time and
improve the performance of Speech Recognition, a popular application of HCI. To
evaluate the performance improvement in training we use the publicly available
"Speech Command" dataset, which contains utterances of 30 command keywords
spoken by 2,618 speakers. Results show that pre-training with deep RL offers
faster convergence compared to non-pre-trained RL while achieving improved
speech recognition accuracy.


  In this contribution, the nuclear modification factor and azimuthal
anisotropy of prompt charm mesons and baryons in Pb-Pb collisions at
$\sqrt{s_\mathrm{NN}}=5.02$ TeV by the ALICE Collaboration are presented. Heavy
quarks are a very suitable probe to investigate the quark-gluon plasma (QGP)
produced in heavy-ion collisions, since they are mainly produced in
hard-scattering processes and hence in shorter timescales compared to the QGP.
Measurements of charm-hadron production in nucleus-nucleus collisions are
therefore useful to study the properties of the in-medium charm-quark energy
loss via the comparison with theoretical models. Models describing the
heavy-flavour transport and energy loss in a hydrodynamically expanding QGP
require also a precise modelling of the in-medium hadronisation of heavy
quarks, which is investigated via the measurement of prompt $\mathrm{D_s^+}$
mesons and $\Lambda_\mathrm{c}^{+}$ baryons.


  We present a detailed beyond-mean-field analysis of a weakly interacting Bose
gas in the crossover from three to low dimensions. We find an analytical
solution for the energy and provide a clear qualitative picture of the
crossover in the case of a box potential with periodic boundary conditions. We
show that the leading contribution of the confinement-induced resonance is of
beyond-mean-field order and calculate the leading corrections in the three- and
low-dimensional limits. We also characterize the crossover for harmonic
potentials in a model system with particularly chosen short- and long-range
interactions and show the limitations of the local-density approximation. Our
analysis is applicable to Bose-Bose mixtures and gives a starting point for
developing the beyond-mean-field theory in inhomogeneous systems with
long-range interactions such as dipolar particles or Rydberg-dressed atoms.


  We provide a general procedure to calculate the current-induced spin-transfer
torque which acts on a general steep magnetic texture due to the exchange
interaction with an applied spin-polarized current. As an example, we consider
a one-dimensional ferromagnetic quantum wire and also include a Rashba
spin-orbit interaction. The spin-transfer torque becomes generally spatially
non-local. Likewise, the Rashba spin-orbit interaction induces a spatially
nonlocal field-like nonequilibrium spin-transfer torque. We also find a
spatially varying nonadiabaticity parameter and markedly different domain wall
dynamics for very steep textures as compared to wide domain walls.


  A novel lattice Boltzmann (LB) model with self-tuning equation of state (EOS)
is developed in this work for simulating coupled thermo-hydrodynamic flows. The
velocity field is solved by the recently developed multiple-relaxation-time
(MRT) LB equation for density distribution function (DF), by which a
self-tuning EOS can be recovered. As to the temperature field, a novel MRT LB
equation for total energy DF is directly developed at the discrete level. By
introducing a density-DF-related term into this LB equation and devising the
equilibrium moment function for total energy DF, the viscous dissipation and
compression work are consistently considered, and by modifying the collision
matrix, the targeted energy conservation equation is recovered without
deviation term. The full coupling of thermo-hydrodynamic effects is achieved
via the self-tuning EOS and the viscous dissipation and compression work. The
present LB model is developed on the basis of the standard lattice, and various
EOSs can be adopted in real applications. Moreover, both the Prandtl number and
specific heat ratio can be arbitrarily adjusted. Furthermore, boundary
condition treatment is also proposed on the basis of the judicious
decomposition of DF into its equilibrium, force (source), and nonequilibrium
parts. The local conservation of mass, momentum, and energy can be strictly
satisfied at the boundary node. Numerical simulations of thermal Poiseuille and
Couette flows are carried out with three different EOSs, and the numerical
results are in good agreement with the analytical solutions. Then, natural
convection in a square cavity with a large temperature difference is simulated
for the Rayleigh number from $10^3$ up to $10^8$. Good agreement between the
present and previous numerical results is observed, which further validates the
present LB model for coupled thermo-hydrodynamic flows.


  A recent line of convolutional neural network-based works has succeeded in
capturing rain streaks. However, difficulties in detailed recovery still
remain. In this paper, we present a multi-level connection and wide regional
non-local block network (MCW-Net) to properly restore the original background
textures in rainy images. Unlike existing encoder-decoder-based image deraining
models that improve performance with additional branches, MCW-Net improves
performance by maximizing information utilization without additional branches
through the following two proposed methods. The first method is a multi-level
connection that repeatedly connects multi-level features of the encoder network
to the decoder network. Multi-level connection encourages the decoding process
to use the feature information of all levels. In multi-level connection,
channel-wise attention is considered to learn which level of features is
important in the decoding process of the current level. The second method is a
wide regional non-local block. As rain streaks primarily exhibit a vertical
distribution, we divide the grid of the image into horizontally-wide patches
and apply a non-local operation to each region to explore the rich rain-free
background information. Experimental results on both synthetic and real-world
rainy datasets demonstrate that the proposed model significantly outperforms
existing state-of-the-art models. Furthermore, the results of the joint
deraining and segmentation experiment prove that our model contributes
effectively to other vision tasks.


  We propose two strategies for Presenter in on-line graph coloring games. The
first one constructs bipartite graphs and forces any on-line coloring algorithm
to use $2\log_2 n - 10$ colors, where $n$ is the number of vertices in the
constructed graph. This is best possible up to an additive constant. The second
strategy constructs graphs that contain neither $C_3$ nor $C_5$ as a subgraph
and forces $\Omega(\frac{n}{\log n}^\frac{1}{3})$ colors. The best known
on-line coloring algorithm for these graphs uses $O(n^{\frac{1}{2}})$ colors.