  We assess whether a confined Wigner molecule constituted by $2N$ fermions
behaves as $N$ bosons or $2N$ fermions. Following the work by C. K. Law [Phys.
Rev. A \textbf{71}, 034306 (2005)] and Chudzicki et al. [Phys. Rev. Lett.
\textbf{104}, 070402 (2010)] we discuss the physical meaning and the reason why
a large amount of entanglement is needed in order to ensure a bosonic composite
behavior. By applying a composite boson ansatz, we found that a Wigner molecule
confined in two dimensional traps presents a bosonic behavior induced by
symmetry. The two-particle Wigner molecule ground state required by the
composite boson ansatz was obtained within the harmonic approximation in the
strong interacting regime. Our approach allows us to address few-particle
states (widely studied within a variety of theoretical and numerical
techniques) as well as a large number of particles (difficult to address due to
computational costs). For a large number of particles, we found strong
fermionic correlations exposed by the suppression of particle fluctuations. For
a small number of particles, we show that the wave function calculated within
the composite boson ansatz captures the Friedel-Wigner transition. The latter
is shown in a regime in which strong correlations due to the Pauli exclusion
principle arise, therefore, we conclude that the coboson ansatz reproduces the
many particle physics of a confined Wigner molecule, even in the presence of
strong deviations of the ideal bosonic behavior due to fermionic correlations.


  In this paper we consider the Recoverable Traveling Salesman Problem (TSP).
Here the task is to find two tours simultaneously, such that the intersection
between the tours is at least a given minimum size, while the sum of travel
distances with respect to two different distance metrics is minimized. Building
upon the classic double-tree method, we derive a 4-approximation algorithm for
the RecoverableTSP. We also show that if the required size of the intersection
between the tours is constant, a 2-approximation guarantee can be achieved,
even if more than two tours need to be constructed. We discuss consequences for
approximability results in the more general area of recoverable robust
optimization.


  The classical Maclaurin inequality asserts that the elementary symmetric
means $$ s_k(y) = \frac{1}{\binom{n}{k}} \sum_{1 \leq i_1 < \dots < i_k \leq n}
y_{i_1} \dots y_{i_k}$$ obey the inequality $s_\ell(y)^{1/\ell} \leq
s_k(y)^{1/k}$ whenever $1 \leq k \leq \ell \leq n$ and $y = (y_1,\dots,y_n)$
consists of non-negative reals. We establish a variant $$
|s_\ell(y)|^{\frac{1}{\ell}} \ll \frac{\ell^{1/2}}{k^{1/2}} \max
(|s_k(y)|^{\frac{1}{k}}, |s_{k+1}(y)|^{\frac{1}{k+1}})$$ of this inequality in
which the $y_i$ are permitted to be negative. In this regime the inequality is
sharp up to constants. Such an inequality was previously known without the
$k^{1/2}$ factor in the denominator.


  Despite super-resolution fluorescence blinking microscopes break the
diffraction limit, the intense phototoxic illumination and long-term image
sequences thus far still pose to major challenges in visualizing
live-organisms. Here, we proposed a super-resolution method based on
auto-correlation two-step deconvolution (SACD) to enhance the temporal
resolution at lower signal intensity levels. Unlike conventional techniques,
such as super-resolution optical fluctuation imaging (SOFI) or stochastic
optical reconstruction microscopy (STORM), our model allows 16 frames to
generate super-resolution images, without noticeable degradation in recording
quality. We demonstrate SACD both in simulated predictions and experimental
validations, with the resulting spatial resolution of 64 nm and 2-10 fold speed
improvements. The use of low signal-to-noise ratio acquisition of image
sequences, our SACD enables fast, background-free, super-resolution imaging
that maybe advance implemented as a suitable tool for rapid live-cells imaging.


  Data from multi-modality provide complementary information in clinical
prediction, but missing data in clinical cohorts limits the number of subjects
in multi-modal learning context. Multi-modal missing imputation is challenging
with existing methods when 1) the missing data span across heterogeneous
modalities (e.g., image vs. non-image); or 2) one modality is largely missing.
In this paper, we address imputation of missing data by modeling the joint
distribution of multi-modal data. Motivated by partial bidirectional generative
adversarial net (PBiGAN), we propose a new Conditional PBiGAN (C-PBiGAN) method
that imputes one modality combining the conditional knowledge from another
modality. Specifically, C-PBiGAN introduces a conditional latent space in a
missing imputation framework that jointly encodes the available multi-modal
data, along with a class regularization loss on imputed data to recover
discriminative information. To our knowledge, it is the first generative
adversarial model that addresses multi-modal missing imputation by modeling the
joint distribution of image and non-image data. We validate our model with both
the national lung screening trial (NLST) dataset and an external clinical
validation cohort. The proposed C-PBiGAN achieves significant improvements in
lung cancer risk estimation compared with representative imputation methods
(e.g., AUC values increase in both NLST (+2.9\%) and in-house dataset (+4.3\%)
compared with PBiGAN, p$<$0.05).


  New Chandra observations of the giant (0.5 Mpc) radio galaxy 4C23.56 at z =
2.5 show X-rays in a linear structure aligned with its radio emission, but
anti-correlated with the detailed radio structure. Consistent with the
powerful, high-z giant radio galaxies we have studied previously, X-rays seem
to be invariably found where the lobe plasma is oldest even where the radio
emission has long since faded. The hotspot complexes seem to show structures
resembling the double shock structure exhibited by the largest radio quasar
4C74.26, with the X-ray shock again being offset closer to the nucleus than the
radio synchrotron shock. In the current paper, the offsets between these shocks
are even larger at 35kpc. Unusually for a classical double (FRII) radio source,
there is smooth low surface-brightness radio emission associated with the
regions beyond the hotspots (further away from the nucleus than the hotspots
themselves), which seems to be symmetric for the ends of both jets. We consider
possible explanations for this phenomenon, and conclude that it arises from
high-energy electrons, recently accelerated in the nearby radio hotspots that
are leaking into a pre-existing weakly-magnetized plasma that are symmetric
relic lobes fed from a previous episode of jet activity. This contrasts with
other manifestations of previous epochs of jet ejection in various examples of
classical double radio sources namely (1) double-double radio galaxies by e.g.
Schoenmakers et al, (2) the double-double X-ray/radio galaxies by Laskar et al
and (3) the presence of a relic X-ray counter-jet in the prototypical classical
double radio galaxy, Cygnus A by Steenbrugge et al. The occurrence of
multi-episodic jet activity in powerful radio galaxies and quasars indicates
that they may have a longer lasting influence on the on-going structure
formation processes in their environs than previously presumed.


  The cluster state, the highly entangled state that is the central resource
for one-way quantum computing, can be efficiently generated in a variety of
physical implementations via global nearest-neighbor interactions. In practice,
a systematic phase error is expected in the entangling process, resulting in
imperfect cluster states. We present a stochastic measurement technique to
generate large perfect cluster states and other graph states with high
probability from imperfect cluster states even when their initial entanglement
is weak.


  Most results regarding Skorokhod embedding problems (SEP) so far rely on the
assumption that the corresponding stopped process is uniformly integrable,
which is equivalent to the convex ordering condition
$\mathrm{U}^{\mu}\leq\mathrm{U}^{\nu}$ when the underlying process is a local
martingale. In this paper, we study the existence, construction of Root's
solutions to SEP, in the absence of this convex ordering condition. We replace
the uniform integrability condition by the minimality condition (Monroe,1972),
as the criterion of "good" solutions. A sufficient and necessary condition (in
terms of local time) for minimality is given. We also discuss the optimality of
such minimal solutions. These results extend the generality of the results
given by Cox and Wang [2013] and Gassiat et al. [2015]. At last, we extend all
the results mentioned above to multi-marginal embedding problems based on the
work of Cox et al. [2018].


  The volume of data that will be produced by new-generation surveys requires
automatic classification methods to select and analyze sources. Indeed, this is
the case for the search for strong gravitational lenses, where the population
of the detectable lensed sources is only a very small fraction of the full
source population. We apply for the first time a morphological classification
method based on a Convolutional Neural Network (CNN) for recognizing strong
gravitational lenses in $255$ square degrees of the Kilo Degree Survey (KiDS),
one of the current-generation optical wide surveys. The CNN is currently
optimized to recognize lenses with Einstein radii $\gtrsim 1.4$ arcsec, about
twice the $r$-band seeing in KiDS. In a sample of $21789$ colour-magnitude
selected Luminous Red Galaxies (LRG), of which three are known lenses, the CNN
retrieves 761 strong-lens candidates and correctly classifies two out of three
of the known lenses. The misclassified lens has an Einstein radius below the
range on which the algorithm is trained. We down-select the most reliable 56
candidates by a joint visual inspection. This final sample is presented and
discussed. A conservative estimate based on our results shows that with our
proposed method it should be possible to find $\sim100$ massive LRG-galaxy
lenses at $z\lsim 0.4$ in KiDS when completed. In the most optimistic scenario
this number can grow considerably (to maximally $\sim$2400 lenses), when
widening the colour-magnitude selection and training the CNN to recognize
smaller image-separation lens systems.


  The Equi-Energy Sampler (EES) introduced by Kou et al [2006] is based on a
population of chains which are updated by local moves and global moves, also
called equi-energy jumps. The state space is partitioned into energy rings, and
the current state of a chain can jump to a past state of an adjacent chain that
has energy level close to its level. This algorithm has been developed to
facilitate global moves between different chains, resulting in a good
exploration of the state space by the target chain. This method seems to be
more efficient than the classical Parallel Tempering (PT) algorithm. However it
is difficult to use in combination with a Gibbs sampler and it necessitates
increased storage. In this paper we propose an adaptation of this EES that
combines PT with the principle of swapping between chains with same levels of
energy. This adaptation, that we shall call Parallel Tempering with Equi-Energy
Moves (PTEEM), keeps the original idea of the EES method while ensuring good
theoretical properties, and practical implementation even if combined with a
Gibbs sampler. Performances of the PTEEM algorithm are compared with those of
the EES and of the standard PT algorithms in the context of mixture models, and
in a problem of identification of gene regulatory binding motifs.


  Recently, an ingenious protocol called Algorand has been proposed to overcome
these limitations. Algorand uses an innovative process - called cryptographic
sortition - to securely and unpredictably elect a set of voters from the
network periodically. These voters are responsible for reaching consensus
through a Byzantine Agreement (BA) protocol on one block per time, guaranteeing
an overwhelming probability of linearity of the blockchain.
  In this paper, we present a security analysis of Algorand. To the best of our
knowledge, it is the first security analysis as well as the first formal study
on Algorand. We designed an attack scenario in which a group of malicious users
tries to break the protocol, or at least limiting it to a reduced partition of
network users, by exploiting a possible security flaw in the messages
validation process of the BA. Since the source code or an official simulator
for Algorand was not available at the time of our study, we created a simulator
(which is available on request) to implement the protocol and assess the
feasibility of our attack scenario. Our attack requires the attacker to have a
trivial capability of establishing multiple connections with targeted nodes and
costs practically nothing to the attacker. Our results show that it is possible
to slow down the message validation process on honest nodes, which eventually
forces them to choose default values on the consensus; leaving the targeted
nodes behind in the chain as compared to the non-attacked nodes. Even though
our results are subject to the real implementation assumption, the core concept
of our attack remains valid.


  Let X be an Abelian surface and C a holomorphic curve in X representing a
primitive homology class. The space of genus g curves in the class of C is g
dimensional. We count the number of such curves that pass through g generic
points and we also count the number of curves in the fixed linear system |C|
passing through g-2 generic points. These two numbers, (defined appropriately)
only depend on n and g where 2n=C^2+2-2g and not on the particular X or C (n is
the number of nodes when a curve is nodal and reduced).
  Gottsche conjectured that certain quasi-modular forms are the generating
functions for the number of curves in a fixed linear system. Our theorem proves
his formulas and shows that (a different) modular form also arises in the
problem of counting curves without fixing a linear system. We use techniques
that were developed in our earlier paper for similar questions on K3 surfaces.
The techniques include Gromov-Witten invariants for families and a degeneration
to an elliptic fibration. One new feature of the Abelian surface case is the
presence of non-trivial Pic^0(X). We show that for any surface S the cycle in
the moduli space of stable maps defined by requiring that the image of the map
lies in a fixed linear system is homologous to the cycle defined by requiring
the image of the map meets b_1 generic loops in S representing the generators
of the first integral homology group (mod torsion).


  This "blue sky idea" paper outlines the opportunities and challenges in data
mining and machine learning involving making a computational attorney -- an
intelligent software agent capable of helping human lawyers with a wide range
of complex high-level legal tasks such as drafting legal briefs for the
prosecution or defense in court. In particular, we discuss what a ChatGPT-like
Large Legal Language Model (L$^3$M) can and cannot do today, which will inspire
researchers with promising short-term and long-term research objectives.


  Linear/non-linear (LNL) models, as described by Benton, soundly model a LNL
term calculus and LNL logic closely related to intuitionistic linear logic.
Every such model induces a canonical enrichment that we show soundly models a
LNL lambda calculus for string diagrams, introduced by Rios and Selinger (with
primary application in quantum computing). Our abstract treatment of this
language leads to simpler concrete models compared to those presented so far.
We also extend the language with general recursion and prove soundness.
Finally, we present an adequacy result for the diagram-free fragment of the
language which corresponds to a modified version of Benton and Wadler's adjoint
calculus with recursion.


  The large scale interferometric gravitational wave detectors consist of
Fabry-Perot cavities operating at very high powers ranging from tens of kW to
MW for next generations. The high powers may result in several nonlinear
effects which would affect the performance of the detector. In this paper, we
investigate the effects of radiation pressure, which tend to displace the
mirrors from their resonant position resulting in the detuning of the cavity.
We observe a remarkable effect, namely, that the freely hanging mirrors gain
energy continuously and swing with increasing amplitude. It is found that the
`time delay', that is, the time taken for the field to adjust to its
instantaneous equilibrium value, when the mirrors are in motion, is responsible
for this effect. This effect is likely to be important in the optimal operation
of the full-scale interferometers such as VIRGO and LIGO.


  Doping MoS$_2$ with Re is known to alter the electronic, structural, and
tribological properties. Re-doped MoS$_2$ has been previously mainly studied in
monolayer or few-layer form, but can also be relevant for applications in
many-layer or bulk form. In this work, we use density functional theory to
explore the structure, phase stability, and Raman spectrum of bulk Re-doped
MoS$_2$. We consider the possibility of the Re dopant existing at different
locations and provide experimentally distinguishable characteristics of the
most likely sites: Mo-substitution and tetrahedral (t-) intercalation. We
demonstrate and benchmark a general approach to calculate Raman spectra of
doped materials with metallic densities of states by using atomic Raman tensors
from the pristine material. Applying this method to the metallic Re-doped
structures, we find characteristic shifts in the Raman-active peaks depending
on Re dopant position: redshifts in both A$_{\rm 1g}$ and E$_{\rm 2g}^1$ peaks
in the t-intercalated case versus a redshift for A$_{\rm 1g}$ and blueshift
(sometimes accompanied by a smaller redshifted peak) for E$_{\rm 2g}^1$ peaks
in the Mo-substituted case, which can be used to identify the dopant sites in
experimental samples. We analyze the interactions giving rise to these shifts.


  This work investigates the stability of (discrete) empirical interpolation
for nonlinear model reduction and state field approximation from measurements.
Empirical interpolation derives approximations from a few samples
(measurements) via interpolation in low-dimensional spaces. It has been
observed that empirical interpolation can become unstable if the samples are
perturbed due to, e.g., noise, turbulence, and numerical inaccuracies. The main
contribution of this work is a probabilistic analysis that shows that stable
approximations are obtained if samples are randomized and if more samples than
dimensions of the low-dimensional spaces are used. Oversampling, i.e., taking
more sampling points than dimensions of the low-dimensional spaces, leads to
approximations via regression and is known under the name of gappy proper
orthogonal decomposition. Building on the insights of the probabilistic
analysis, a deterministic sampling strategy is presented that aims to achieve
lower approximation errors with fewer points than randomized sampling by taking
information about the low-dimensional spaces into account. Numerical results of
reconstructing velocity fields from noisy measurements of combustion processes
and model reduction in the presence of noise demonstrate the instability of
empirical interpolation and the stability of gappy proper orthogonal
decomposition with oversampling.


  Two dimensional statistical integrable models, such as the Ising model, the
chiral Potts model and the Belavin model, becomes integrable. Because of the
SU(2) symmetry of these models, these models become integrable. The integral
models are often parameterized by the elliptic function or the elliptic theta
function. In this paper, we study the Ising model, and we show that the
Yang-Baxter equation of the Ising model can be written as the integrability
condition of SU(2), and we gives the natural explanation why the Ising model
can be parameterized by the elliptic function by connecting the spherical
trigonometry relation and the elliptic function. Addition formula of the
elliptic function is the secret of the exact solvability of the Ising model.


  We solve an one-dimensional stochastic model of interacting particles on a
chain. Particles can have branching and coagulation reactions, they can also
appear on an empty site and disappear spontaneously.
  This model which can be viewed as an epidemic model and/or as a
generalization of the {\it voter} model, is treated analytically beyond the
{\it conventional} solvable situations. With help of a suitably chosen {\it
string function}, which is simply related to the density and the
non-instantaneous two-point correlation functions of the particles, exact
expressions of the density and of the non-instantaneous two-point correlation
functions, as well as the relaxation spectrum are obtained on a finite and
periodic lattice.


  We present an analogy between the one dimensional Poisson equation in
inhomogeneous media and the Dirac equation in one space dimension with a
Lorentz scalar potential for zero energy. We illustrate how the zero energy
state in the Jackiw-Rebbi model can be implemented in a simple one dimensional
electrostatic setting by using an inhomogeneous electric permittivity and an
infinite charged sheet. Our approach provides a novel insight into the
Jackiw-Rebbi zero energy state and provides a helpful view in teaching this
important quantum field theory model using basic electrostatics.


  With the rapid growth of data, distributed momentum stochastic gradient
descent~(DMSGD) has been widely used in distributed learning, especially for
training large-scale deep models. Due to the latency and limited bandwidth of
the network, communication has become the bottleneck of distributed learning.
Communication compression with sparsified gradient, abbreviated as \emph{sparse
communication}, has been widely employed to reduce communication cost. All
existing works about sparse communication in DMSGD employ local momentum, in
which the momentum only accumulates stochastic gradients computed by each
worker locally. In this paper, we propose a novel method, called
\emph{\underline{g}}lobal \emph{\underline{m}}omentum
\emph{\underline{c}}ompression~(GMC), for sparse communication. Different from
existing works that utilize local momentum, GMC utilizes global momentum.
Furthermore, to enhance the convergence performance when using more aggressive
sparsification compressors (e.g., RBGS), we extend GMC to GMC+. We
theoretically prove the convergence of GMC and GMC+. To the best of our
knowledge, this is the first work that introduces global momentum for sparse
communication in distributed learning. Empirical results demonstrate that,
compared with the local momentum counterparts, our GMC and GMC+ can achieve
higher test accuracy and exhibit faster convergence, especially under non-IID
data distribution.


  Classical models for the propagation of ultrasound waves are the Westervelt
equation, the Kuznetsov and the Khokhlov-Zabolotskaya-Kuznetsov equations. The
Jordan-Moore-Gibson-Thompson equation is a prominent example of a Partial
Differential Equation (PDE) model which describes the acoustic velocity
potential in ultrasound wave propagation, where the paradox of infinite speed
of propagation of thermal signals is eliminated; the use of the constitutive
Cattaneo law for the heat flux, in place of the Fourier law, accounts for its
being of third order in time. Aiming at the understanding of the fully
quasilinear PDE, a great deal of attention has been recently devoted to its
linearization -- referred to in the literature as the Moore-Gibson-Thompson
equation -- whose mathematical analysis is also of independent interest, posing
already several questions and challenges. In this work we consider and solve a
quadratic control problem associated with the linear equation, formulated
consistently with the goal of keeping the acoustic pressure close to a
reference pressure during ultrasound excitation, as required in medical and
industrial applications. While optimal control problems with smooth controls
have been considered in the recent literature, we aim at relying on controls
which are just $L^2$ in time; this leads to a singular control problem and to
non-standard Riccati equations. In spite of the unfavourable combination of the
semigroup describing the free dynamics that is not analytic, with the
challenging pattern displayed by the dynamics subject to boundary control, a
feedback synthesis of the optimal control as well as well-posedness of operator
Riccati equations are established.


  Web pages contain a large variety of information, but are largely designed
for use by graphical web browsers. Mobile access to web-based information often
requires presenting HTML web pages using channels that are limited in their
graphical capabilities such as small-screens or audio-only interfaces. Content
transcoding and annotations have been explored as methods for intelligently
presenting HTML documents. Much of this work has focused on transcoding for
small-screen devices such as are found on PDAs and cell phones. Here, we focus
on the use of annotations and transcoding for presenting HTML content through a
voice user interface instantiated in VoiceXML. This transcoded voice interface
is designed with an assumption that it will not be used for extended web
browsing by voice, but rather to quickly gain directed access to information on
web pages. We have found repeated structures that are common in the
presentation of data on web pages that are well suited for voice presentation
and navigation. In this paper, we describe these structures and their use in an
annotation system we have implemented that produces a VoiceXML interface to
information originally embedded in HTML documents. We describe the transcoding
process used to translate HTML into VoiceXML, including transcoding features we
have designed to lead to highly usable VoiceXML code.


  Carbon nanotubes (CNT) have been recently proposed as stabilizers against
grain growth that can happen even at low temperature inputs in nano-crystalline
and ultrafine-grained materials obtained by severe plastic deformation. In this
study, we analyzed the evolution of the structural defects on the nanotubes in
CNT-reinforced nickel matrix composites with different reinforcement weight
fractions. The composites were processed by high pressure torsion, and we used
Raman spectroscopy as the main characterization technique. The results indicate
that for CNT subjected to highly energetic processing, it is not sufficient to
analyze only the ID/IG ratio (as proposed in the available literature), but it
is also necessary to evaluate the shifting of the G band, which traces the
amorphization trajectory undergone by the CNT. Furthermore, we observed that
the deformation suffered by the CNT is related to the accumulated strain and
varies with the partial CNT fractions of these composites. This is related to
their capacity to withstand the plastic strain that occurs during deformation.
In addition, the defective state reaches a saturation before achieving the
saturation in the microstructural refinement. These results will help to
efficiently optimize the processing of this type of engineering composites.


  We define and study several new interleaving distances for persistent
cohomology which take into account the algebraic structures of the cohomology
of a space, for instance the cup product or the action of the Steenrod algebra.
In particular, we prove that there exists a persistent A-infinity-structure
associated to data sets and and we define the associated distance. We prove the
stability of these new distances for Cech or Vietoris Rips complexes with
respect to the Gromov-Hausdorff distance, and we compare these new distances
with each other and the classical one, building some examples which prove that
they are not equal in general and refine effectively the classical bottleneck
distance.


  The TRAPPIST-1 system is an iconic planetary system in various aspects (e.g.,
habitability, resonant relation, and multiplicity) and hence has attracted
considerable attention. The mass distribution of the TRAPPIST-1 planets is
characterized by two features: the two inner planets are large, and the masses
of the four planets in the outer orbit increase with orbital distance. The
origin of these features cannot be explained by previous formation models. We
investigate whether the mass distribution of the TRAPPIST-1 system can be
reproduced by a planet formation model using N-body simulations. We used a gas
disk evolution model around a low-mass star constructed by considering disk
winds and followed the growth and orbital migration from planetary embryos with
the isolation mass, which increases with orbital distance. As a result, we find
that from the initial phase, planets in inner orbits undergo rapid orbital
migration, and the coalescence growth near the inner disk edge is enhanced.
This allows the inner planets to grow larger. Meanwhile, compared with the
inner planets, planets in outer orbits migrate more slowly and do not
frequently collide with neighboring planets. Therefore, the trend of increasing
mass toward the outer orbit, called reversed mass ranking, is maintained. The
final mass distribution approximately agrees with the two features of the mass
distribution in the TRAPPIST-1 system. We discover that the mass distribution
in the TRAPPIST-1 system can be reproduced when embryos experience rapid
migration and become trapped near the disk inner edge, and then more massive
embryos undergo slower migration. This migration transition can be achieved
naturally in a disk evolution model with disk winds.


  We perform tunable resonant Raman scattering on 17 semiconducting and 7
metallic singly resonant single wall carbon nanotubes. The measured scattering
cross-section as a function laser energy provides information about a tube's
electronic structure, the lifetime of intermediate states involved in the
scattering process and also energies of zone center optical phonons. Recording
the scattered Raman signal as a function of tube location in the microscope
focal plane allows us to construct two-dimensional spatial maps of singly
resonant tubes. We also describe a spectral nanoscale artifact we have coined
the "nano-slit effect".


  With the growth of complexity and extent, large scale interconnected network
systems, e.g. transportation networks or infrastructure networks, become more
vulnerable towards external disruptions. Hence, managing potential disruptive
events during the design, operating, and recovery phase of an engineered system
therefore improving the system's resilience is an important yet challenging
task. In order to ensure system resilience after the occurrence of failure
events, this study proposes a mixed-integer linear programming (MILP) based
restoration framework using heterogeneous dispatchable agents. Scenario-based
stochastic optimization (SO) technique is adopted to deal with the inherent
uncertainties imposed on the recovery process from nature. Moreover, different
from conventional SO using deterministic equivalent formulations, additional
risk measure is implemented for this study because of the temporal sparsity of
the decision making in applications such as the recovery from extreme events.
The resulting restoration framework involves a large-scale MILP problem and
thus an adequate decomposition technique, i.e. modified Lagrangian dual
decomposition, is also employed in order to achieve tractable computational
complexity. Case study results based on the IEEE 37-bus test feeder demonstrate
the benefits of using the proposed framework for resilience improvement as well
as the advantages of adopting SO formulations.


  Tungsten usually exhibits poor weldability and marked brittleness at room
temperature. This cause tungsten welds to be affected by the evolution of
cracks along the weld bead, which can be eliminated by using a pre-heating step
to reduce thermal straining. In this study, based on the tungsten inert gas
welding process, a working envelope, focussed on varying welding speed and five
different shielding gas mixtures of argon and helium, has been defined with the
view of producing crack-free autogenous welds. The bead appearance and the
microstructure of the different welds were correlated to the welding
parameters, whose main effects have been analysed. Welding defects such as
humping occurred when using gas mixtures with relatively low content of helium,
and when using relatively high welding speeds. Crack-free autogenous welds have
been produced without pre-heating when using a high content of helium and
relatively low welding speeds. Thus, this study has demonstrated that a
helium-rich shielding gas is required for welding thick tungsten plates.
Moreover, the low thermal shock induced by the process, coupled with the purity
of the tungsten plates used, strongly contributed to avoid the occurrence of
any crack.


  Automatic repeat request (ARQ) is widely used in modern communication systems
to improve transmission reliability. In conventional ARQ protocols developed
for systems with energy-unconstrained receivers, an
acknowledgement/negative-acknowledgement (ACK/NACK) message is fed back when
decoding succeeds/fails. Such kind of non-adaptive feedback consumes
significant amount of energy, and thus will limit the performance of systems
with energy harvesting (EH) receivers. In order to overcome this limitation and
to utilize the harvested energy more efficiently, we propose a novel ARQ
protocol for EH receivers, where the ACK feedback can be adapted based upon the
receiver's EH state. Two conventional ARQ protocols are also considered. By
adopting the packet drop probability (PDP) as the performance metric, we
formulate the throughput constrained PDP minimization problem for a
communication link with a non-EH transmitter and an EH receiver. Optimal
reception policies including the sampling, decoding and feedback strategies,
are developed for different ARQ protocols. Simulation results will show that
the proposed ARQ protocol not only outperforms the conventional ARQs in terms
of PDP, but can also achieve a higher throughput.


  We study the class of endlessly single-mode all-silica photonic crystal
fibers with a triangular air-hole cladding. We consider the sensibility to
longitudinal nonuniformities and the consequences and limitations for realizing
low-loss large-mode area photonic crystal fibers. We also discuss the
dominating scattering mechanism and experimentally we confirm that both macro
and micro-bending can be the limiting factor.


  We study adapting trained object detectors to unseen domains manifesting
significant variations of object appearance, viewpoints and backgrounds. Most
current methods align domains by either using image or instance-level feature
alignment in an adversarial fashion. This often suffers due to the presence of
unwanted background and as such lacks class-specific alignment. A common remedy
to promote class-level alignment is to use high confidence predictions on the
unlabelled domain as pseudo labels. These high confidence predictions are often
fallacious since the model is poorly calibrated under domain shift. In this
paper, we propose to leverage model predictive uncertainty to strike the right
balance between adversarial feature alignment and class-level alignment.
Specifically, we measure predictive uncertainty on class assignments and the
bounding box predictions. Model predictions with low uncertainty are used to
generate pseudo-labels for self-supervision, whereas the ones with higher
uncertainty are used to generate tiles for an adversarial feature alignment
stage. This synergy between tiling around the uncertain object regions and
generating pseudo-labels from highly certain object regions allows us to
capture both the image and instance level context during the model adaptation
stage. We perform extensive experiments covering various domain shift
scenarios. Our approach improves upon existing state-of-the-art methods with
visible margins.


  We report on studies of untriggered two-particle angular correlations of
identified particles (pions, kaons and protons) measured in proton-proton
collisions at center-of-mass energy sqrt{s}=7 TeV recorded by ALICE at the LHC.
These type of studies are sensitive to a wide range of correlations which arise
from different physics mechanisms, each of them having a unique structure in
DeltaEta-DeltaPhi space. The correlations of particles with different quark
content and flavor are sensitive to various conservation laws. The study of
these correlations is the main goal of this analysis. The results confirm that
these laws strongly influence the shape of the correlation functions for
different particle types and must be taken into account while analysing the
data. Moreover, we verify their implementation using two Monte Carlo event
generators and we found that the analyzed models do not reproduce the measured
correlations for protons.


  Galaxy groups host the majority of matter and more than half of all the
galaxies in the Universe. Their hot ($10^7$ K), X-ray emitting intra-group
medium (IGrM) reveals emission lines typical of many elements synthesized by
stars and supernovae. Because their gravitational potentials are shallower than
those of rich galaxy clusters, groups are ideal targets for studying, through
X-ray observations, feedback effects, which leave important marks on their gas
and metal contents. Here, we review the history and present status of the
chemical abundances in the IGrM probed by X-ray spectroscopy. We discuss the
limitations of our current knowledge, in particular due to uncertainties in the
modeling of the Fe-L shell by plasma codes, and coverage of the volume beyond
the central region. We further summarize the constraints on the abundance
pattern at the group mass scale and the insight it provides to the history of
chemical enrichment. Parallel to the observational efforts, we review the
progress made by both cosmological hydrodynamical simulations and controlled
high-resolution 3D simulations to reproduce the radial distribution of metals
in the IGrM, the dependence on system mass from group to cluster scales, and
the role of AGN and SN feedback in producing the observed phenomenology.
Finally, we highlight future prospects in this field, where progress will be
driven both by a much richer sample of X-ray emitting groups identified with
eROSITA, and by a revolution in the study of X-ray spectra expected from
micro-calorimeters onboard XRISM and ATHENA.


  The 2017 ASSISTments Data Mining competition aims to use data from a
longitudinal study for predicting a brand-new outcome of students which had
never been studied before by the educational data mining research community.
Specifically, it facilitates research in developing predictive models that
predict whether the first job of a student out of college belongs to a STEM
(the acronym for science, technology, engineering, and mathematics) field. This
is based on the student's learning history on the ASSISTments blended learning
platform in the form of extensive clickstream data gathered during the middle
school years. To tackle this challenge, we first estimate the expected
knowledge state of students with respect to different mathematical skills using
a deep knowledge tracing (DKT) model and an enhanced DKT (DKT+) model. We then
combine the features corresponding to the DKT/DKT+ expected knowledge state
with other features extracted directly from the student profile in the dataset
to train several machine learning models for the STEM/non-STEM job prediction.
Our experiments show that models trained with the combined features generally
perform better than the models trained with the student profile alone. Detailed
analysis of the student's knowledge state reveals that, when compared with
non-STEM students, STEM students generally show a higher mastery level and a
higher learning gain in mathematics.


  We present a formalism for precise description of oscillation phenomena in
matter at high energies or high densities, V > \Delta m^2/2E, where V is the
matter-induced potential of neutrinos. The accuracy of the approximation is
determined by the quantity \sin^2 2\theta_m \Delta V/2\pi V, where \theta_m is
the mixing angle in matter and \Delta V is a typical change of the potential
over the oscillation length (l \sim 2\pi/V). We derive simple and physically
transparent formulas for the oscillation probabilities, which are valid for
arbitrary matter density profiles. They can be applied to oscillations of high
energy (E > 10 GeV) accelerator, atmospheric and cosmic neutrinos in the matter
of the Earth, substantially simplifying numerical calculations and providing an
insight into the physics of neutrino oscillations in matter. The effect of
parametric enhancement of the oscillations of high energy neutrinos is
considered. Future high statistics experiments can provide an unambiguous
evidence for this effect.


  The exploration of quantum phases in moir\'e systems has drawn intense
experimental and theoretical efforts. The realization of honeycomb symmetry has
been a recent focus. The combination of strong interaction and honeycomb
symmetry can lead to exotic electronic states such as fractional Chern
insulator, unconventional superconductor, and quantum spin liquid. Accurate
computations in such systems, with reliable treatment of strong long-ranged
Coulomb interaction and approaching the large system sizes to extract
thermodynamic phases, are mostly missing. We study the two-dimensional electron
gas on a honeycomb moir\'e lattice at quarter filling, using fixed-phase
diffusion Monte Carlo. The ground state phases of this important model are
determined in the parameter regime relevant to current experiments. With
increasing moir\'e potential, the systems transitions from a paramagnetic metal
to an itinerant ferromagnetic semimetal and then a charge-density-wave
insulator.


  We imaged the X-ray error box of GRB 980703, beginning 22.5 hours after the
gamma--ray event, in both the optical R and near-infrared H bands. A fading
optical/IR object was detected within the X-ray error box, coincident with the
variable radio source reported by Frail et al. (1998a), who also detected the
optical transient independently of us. Further imagery revealed the GRB host
galaxy, with R = 22.49 +/- 0.04 and H = 20.5 +/- 0.25, the brightest so far
detected. When excluding its contribution to the total flux, both the R and
H-band light curves are well-fit by a power-law decay with index alpha~1.4. Our
data suggest an intrinsic column density in the host galaxy of ~ 3.5 x 10^21
cm^-2 which indicates the existence of a dense and rich-gas medium in which the
GRB occurred, thus supporting the hypernova model scenarios.


  A deterministic theory describing the melting of an ultrathin lubricant film
between two atomically smooth solid surfaces has been developed. The lubricant
state is described by introducing a parameter of excess volume that arises
owing to the solid structure chaotization at its melting. The thermodynamic and
shear kinds of melting are described consistently. The dependences of the
stationary friction force on the lubricant temperature and the shear velocity
of rubbing surfaces that move with respect to each other with a constant
velocity have been analyzed. In the framework of a simple tribological model,
the stick-slip mode of friction, when the lubricant periodically melts and
solidifies, has been described. The influence of velocity, temperature, and
load on the stick-slip friction has been analyzed. A qualitative comparison
between the results obtained and experimental data has been carried out.


  Joinings of C*-dynamical systems are defined in terms of free products of
C*-algebras, as an analogue of joinings of classical dynamical systems. We then
consider disjointness in this context, in particular for ergodic versus
identity systems. Lastly we show how multi-time correlation functions appearing
in quantum statistical mechanics naturally fit into this joining framework.


  We study a relation between topological quantum field theory and the Kodama
(Chern-Simons) state. It is shown that the Kodama (Chern-Simons) state
describes a topological state with unbroken diffeomorphism invariance in
Yang-Mills theory and Einstein's general relativity in four dimensions. We give
a clear explanation of "why" such a topological state exists.


  Q & A (quantum electrodynamics test and search for axion) experiment was
first proposed in 1994 and a 3.5 m high-finesse Fabry-Perot prototype detector
extendable to 7 m has been built and tested. We now enter into the 2nd phase of
improving the ellipticity detection sensitivity. We present our scheme, compare
with other ongoing experiments, analyze the displacement spectra of our
suspension system, and use them for designing automatic alignment control to
improve the ellipticicy detection sensitivity. To improve ellipsometry
resolution, we use new polarizers of extinction ratio smaller than 10^{-8}.


  The development of materials for optical signal processing represents a major
issue in present technology. In this contribution we present a study on
Er-doped fiber preforms where particular attention is devoted on how the
addition of CaO in the glass modifies the local environment of the rare earth.
The results from photoluminescence and Extended X-ray Absorption Fine Structure
(EXAFS) are compared and a clear link between the width of the emission line at
1.5 $\mu$m and the amorphous/crystalline local structure around the Er3+ ion is
evidenced.


  Starting with a `bare' 4-dimensional differential manifold as a model of
spacetime, we discuss the options one has for defining a volume element which
can be used for physical theories. We show that one has to prescribe a scalar
density \sigma. Whereas conventionally \sqrt{|\det g_{ij}|} is used for that
purpose, with g_{ij} as the components of the metric, we point out other
possibilities, namely \sigma as a `dilaton' field or as a derived quantity from
either a linear connection or a quartet of scalar fields, as suggested by
Guendelman and Kaganovich.


  Mobile software engineering has been a hot research topic for decades. Our
fellow researchers have proposed various approaches (with over 7,000
publications for Android alone) in this field that essentially contributed to
the great success of the current mobile ecosystem. Existing research efforts
mainly focus on popular mobile platforms, namely Android and iOS. OpenHarmony,
a newly open-sourced mobile platform, has rarely been considered, although it
is the one requiring the most attention as OpenHarmony is expected to occupy
one-third of the market in China (if not in the world). To fill the gap, we
present to the mobile software engineering community a research roadmap for
encouraging our fellow researchers to contribute promising approaches to
OpenHarmony. Specifically, we start by presenting a literature review of mobile
software engineering, attempting to understand what problems have been targeted
by the mobile community and how they have been resolved. We then summarize the
existing (limited) achievements of OpenHarmony and subsequently highlight the
research gap between Android/iOS and OpenHarmony. This research gap eventually
helps in forming the roadmap for conducting software engineering research for
OpenHarmony.


  Van Zuylen et al. [35] introduced the notion of a popular ranking in a voting
context, where each voter submits a strict ranking of all candidates. A popular
ranking $\pi$ of the candidates is at least as good as any other ranking
$\sigma$ in the following sense: if we compare $\pi$ to $\sigma$, at least half
of all voters will always weakly prefer $\pi$. Whether a voter prefers one
ranking to another is calculated based on the Kendall distance. A more
traditional definition of popularity -- as applied to popular matchings, a
well-established topic in computational social choice -- is stricter, because
it requires at least half of the voters who are not indifferent between $\pi$
and $\sigma$ to prefer $\pi$. In this paper, we derive structural and
algorithmic results in both settings, also improving upon the results in [35].
We also point out connections to the famous open problem of finding a Kemeny
consensus with three voters.


  We report on a theory of the Skyrmion states which occur in quantum Hall
regime near certain filling factors. It is shown that in the limit of zero
Zeeman splitting in a realistic temperature range the Skyrmion plasma is a
liquid described by the effective model of massive two-dimensional Dirac
fermions.


  In this work we studied, by means of high-resolution neutron diffraction as a
function of temperature, the La1.4Sr0.8Ca0.8Mn2O7 bilayered manganite for two
different annealing treatments. Out data allowed us to shown, for the first
time, the absence of long-range magnetic order in this optimally doped
bilayered manganite where the A-site of the structure is doped with equal
proportions of different isovalent cations (Ca and Sr). The system, however,
presents defined IM transitions which suggest that the transport properties are
not linked to the evolution of long-range order and that two dimensional spin
ordering in the layers of the perovskite blocks may be sufficient to 'assist'
the hole hopping. Possible reason for the suppression of magnetic order induced
by the Ca doping is a size effect coupled to the cation size mismatch between
the Sr and Ca ions.


  Given an isometric immersion $f\colon M^n\to \R^{n+1}$ of a compact
Riemannian manifold of dimension $n\geq 3$ into Euclidean space of dimension
$n+1$, we prove that the identity component $Iso^0(M^n)$ of the isometry group
$Iso(M^n)$ of $M^n$ admits an orthogonal representation $\Phi\colon
Iso^0(M^n)\to SO(n+1)$ such that $f\circ g=\Phi(g)\circ f$ for every $g\in
Iso^0(M^n)$. If $G$ is a closed connected subgroup of $Iso(M^n)$ acting locally
polarly on $M^n$, we prove that $\Phi(G)$ acts polarly on $\R^{n+1}$, and we
obtain that $f(M^n)$ is given as $\Phi(G)(L)$, where $L$ is a hypersurface of a
section which is invariant under the Weyl group of the $\Phi(G)$-action. We
also find several sufficient conditions for such an $f$ to be a rotation
hypersurface. Finally, we show that compact Euclidean rotation hypersurfaces of
dimension $n\geq 3$ are characterized by their underlying warped product
structure.


  We study the $\alpha$-$z$-R\'enyi divergences $D_{\alpha,z}(\psi\|\varphi)$
where $\alpha,z>0$ ($\alpha\ne1$) for normal positive functionals
$\psi,\varphi$ on general von Neumann algebras, introduced in [S.~Kato and
Y.~Ueda, arXiv:2307.01790] and [S.~Kato, arXiv:2311.01748]. We prove the
variational expressions and the data processing inequality (DPI) for the
$\alpha$-$z$-R\'enyi divergences. We establish the sufficiency theorem for
$D_{\alpha,z}(\psi\|\varphi)$, saying that for $(\alpha,z)$ inside the DPI
bounds, the equality
$D_{\alpha,z}(\psi\circ\gamma\|\varphi\circ\gamma)=D_{\alpha,z}(\psi\|\varphi)<\infty$
in the DPI under a quantum channel (or a normal $2$-positive unital map)
$\gamma$ implies the reversibility of $\gamma$ with respect to $\psi,\varphi$.
Moreover, we show the monotonicity properties of $D_{\alpha,z}(\psi\|\varphi)$
in the parameters $\alpha,z$ and their limits to the normalized relative
entropy as $\alpha\nearrow1$ and $\alpha\searrow1$.


  In conventional well-known derivation methods for the adaptive
Thouless-Anderson-Palmer (TAP) free energy, special assumptions that are
difficult to mathematically justify except in some mean-field models, must be
made. Here, we present a new adaptive TAP free energy derivation method. Using
this derivation technique, without any special assumptions, the adaptive TAP
free energy can be simply obtained as a high-temperature expansion of the Gibbs
free energy.


  It is shown that the onset of the color superconducting phase occurs in the
BCS-BE crossover region.


  We consider a generalization of the weighted random ball model. The model is
driven by a random Poisson measure with a product heavy tailed intensity
measure. Such a model typically represents the transmission of a network of
stations with a fading effect. In a previous article, the authors proved the
convergence of the finite-dimensional distributions of related generalized
random fields under various scalings and in the particular case when the fading
function is the indicator function of the unit ball. In this paper, tightness
and functional convergence are investigated. Using suitable moment estimates,
we prove functional convergences for some parametric classes of configurations
under the so-called large ball scaling and intermediate ball scaling.
Convergence in the space of distributions is also discussed.


  We investigate the possibility of hidden non-Abelian Local Phase symmetries
in large-U doped planar Hubbard antiferromagnets, believed to simulate the
physics of two-dimensional (magnetic) superconductors. We present a spin-charge
separation ansatz, appropriate to incorporate holon spin flip, which allows for
such a hidden local gauge symmetry to emerge in the effective action. The group
is of the form $SU(2)\otimes U_S(1) \otimes U_E(1)$, where SU(2) is a local
non-Abelian group associated with the spin degrees of freedom, U_E(1) is that
of ordinary electromagnetism, associated with the electric charge of the holes,
and U_S(1) is a `statistical' Abelian gauge group pertaining to the fractional
statistics of holes on the spatial plane. In a certain regime of the parameters
of the model, namely strong U_S(1) and weak SU(2), there is the possibility of
dynamical formation of a holon condensate. This leads to a dynamical breaking
of $SU(2) \to U(1)$. The resulting Abelian effective theory is closely related
to an earlier model proposed as the continuum limit of large-spin planar doped
antiferromagnets, which lead to an unconventional scenario for two-dimensional
parity-invariant superconductivity.


  We investigate the phenomenological implications of the recent $W$ mass
measurement by the CDF collaboration, which exhibits tension with the standard
model (SM) electroweak fit. Performing the fit to the electroweak observables
within the SM effective field theory, we find that the new physics that
contributes either to the determination of the electroweak vacuum expectation
value, or to the oblique parameters, can improve the agreement with data. The
best description is obtained from a fit where flavor universality is not
required in the new physics operators, with 2 to 3 $\sigma$ indications for
several nonzero Wilson coefficients. We point out that top partners with order
TeV masses could lead to the observed shift in the $W$ mass.


  We present a general quantum circuit design for finding eigenvalues of
non-unitary matrices on quantum computers using the iterative phase estimation
algorithm. In particular, we show how the method can be used for the simulation
of resonance states for quantum systems.


  We prove that the modular symbols appropriately normalized and ordered have
an asymptotical normal distribution for all cocompact subgroups of SL_2(R). We
introduce hyperbolic Eisenstein series in order to calculate the moments of the
modular symbols.


  Testing heteroscedasticity of the errors is a major challenge in
high-dimensional regressions where the number of covariates is large compared
to the sample size. Traditional procedures such as the White and the
Breusch-Pagan tests typically suffer from low sizes and powers. This paper
proposes two new test procedures based on standard OLS residuals. Using the
theory of random Haar orthogonal matrices, the asymptotic normality of both
test statistics is obtained under the null when the degree of freedom tends to
infinity. This encompasses both the classical low-dimensional setting where the
number of variables is fixed while the sample size tends to infinity, and the
proportional high-dimensional setting where these dimensions grow to infinity
proportionally. These procedures thus offer a wide coverage of dimensions in
applications. To our best knowledge, this is the first procedures in the
literature for testing heteroscedasticity which are valid for medium and
high-dimensional regressions. The superiority of our proposed tests over the
existing methods are demonstrated by extensive simulations and by several real
data analyses as well.


  High resolution depth-maps, obtained by upsampling sparse range data from a
3D-LIDAR, find applications in many fields ranging from sensory perception to
semantic segmentation and object detection. Upsampling is often based on
combining data from a monocular camera to compensate the low-resolution of a
LIDAR. This paper, on the other hand, introduces a novel framework to obtain
dense depth-map solely from a single LIDAR point cloud; which is a research
direction that has been barely explored. The formulation behind the proposed
depth-mapping process relies on local spatial interpolation, using
sliding-window (mask) technique, and on the Bilateral Filter (BF) where the
variable of interest, the distance from the sensor, is considered in the
interpolation problem. In particular, the BF is conveniently modified to
perform depth-map upsampling such that the edges (foreground-background
discontinuities) are better preserved by means of a proposed method which
influences the range-based weighting term. Other methods for spatial upsampling
are discussed, evaluated and compared in terms of different error measures.
This paper also researches the role of the mask's size in the performance of
the implemented methods. Quantitative and qualitative results from experiments
on the KITTI Database, using LIDAR point clouds only, show very satisfactory
performance of the approach introduced in this work.


  Generative AI (GenAI) systems offer unprecedented opportunities for
transforming professional and personal work, yet present challenges around
prompting, evaluating and relying on outputs, and optimizing workflows. We
argue that metacognition$\unicode{x2013}$the psychological ability to monitor
and control one's thoughts and behavior$\unicode{x2013}$offers a valuable lens
to understand and design for these usability challenges. Drawing on research in
psychology and cognitive science, and recent GenAI user studies, we illustrate
how GenAI systems impose metacognitive demands on users, requiring a high
degree of metacognitive monitoring and control. We propose these demands could
be addressed by integrating metacognitive support strategies into GenAI
systems, and by designing GenAI systems to reduce their metacognitive demand by
targeting explainability and customizability. Metacognition offers a coherent
framework for understanding the usability challenges posed by GenAI, and
provides novel research and design directions to advance human-AI interaction.


  The ongoing efforts aiming at control and manipulation of novel topological
phases renewed the interest in bound states induced in superconducting
substrates by magnetic impurities. First described by Yu, Shiba and Rusinov,
those bound states are spin-polarized and exhibit a rather large spatial extent
in two dimensional (2D) materials. Here, using the Bogoliubov--de~Gennes
formalism, we study the Yu--Shiba--Rusinov bound states induced by a
ferromagnetic dimer in 2D triangular lattice. We describe various topographies
of the in-gap bound states, depending on the coupling between impurities and
superconducting host.


  Here we present a liquid nitrogen-cooled Ca^+ optical clock with an overall
systematic uncertainty of 3*10^-18. In contrast with the room-temperature Ca^+
optical clock that we have reported previously, the temperature of the
blackbody radiation (BBR) shield in vacuum has been reduced to 82(5) K using
liquid nitrogen. An ion trap with a lower heating rate and improved cooling
lasers were also introduced. This allows cooling the ion temperature to the
Doppler cooling limit during the clock operation, and the systematic
uncertainty due to the ion's secular (thermal) motion is reduced to < 1*10^-18.
The uncertainty due to the probe laser light shift and the servo error are also
reduced to < 1*10^-19 and 4*10^-19 with the hyper-Ramsey method and the
higher-order servo algorithm, respectively. By comparing the output frequency
of the cryogenic clock to that of a room-temperature clock, the differential
BBR shift between the two was measured with a fractional statistical
uncertainty of 7*10^-18. The differential BBR shift was used to calculate the
static differential polarizability, and it was found in excellent agreement
with our previous measurement with a different method. This work suggests that
the BBR shift of optical clocks can be well suppressed in a liquid nitrogen
environment. This is advantageous because conventional liquid-helium cryogenic
systems for optical clocks are more expensive and complicated. Moreover, the
proposed system can be used to suppress the BBR shift significantly in other
types of optical clocks such as Yb^+, Sr^+, Yb, Sr, etc.


  The decay rate for a particle in a metastable cubic potential is investigated
in the quantum regime by the Euclidean path integral method in semiclassical
approximation. The imaginary time formalism allows one to monitor the system as
a function of temperature. The family of classical paths, saddle points for the
action, is derived in terms of Jacobian elliptic functions whose periodicity
sets the energy-temperature correspondence. The period of the classical
oscillations varies monotonically with the energy up to the sphaleron, pointing
to a smooth crossover from the quantum to the activated regime. The softening
of the quantum fluctuation spectrum is evaluated analytically by the theory of
the functional determinants and computed at low $T$ up to the crossover. In
particular, the negative eigenvalue, causing an imaginary contribution to the
partition function, is studied in detail by solving the Lam\`{e} equation which
governs the fluctuation spectrum. For a heavvy particle mass, the decay rate
shows a remarkable temperature dependence mainly ascribable to a low lying soft
mode and, approaching the crossover, it increases by a factor five over the
predictions of the zero temperature theory. Just beyond the peak value, the
classical Arrhenius behavior takes over. A similar trend is found studying the
quartic metastable potential but the lifetime of the latter is longer by a
factor ten than in a cubic potential with same parameters. Some formal
analogies with noise-induced transitions in classically activated metastable
systems are discussed.


  We propose and analyze a new asymptotic preserving (AP) finite volume scheme
for the multidimensional compressible barotropic Euler equations to simulate
low Mach number flows. The proposed scheme uses a stabilized upwind numerical
flux, with the stabilization term being proportional to the stiff pressure
gradient, and we prove its conditional energy stability and consistency.
Utilizing the concept of dissipative measure-valued (DMV) solutions, we
rigorously illustrate the AP properties of the scheme for well-prepared initial
data. In particular, we prove that the numerical solutions will converge weakly
to a DMV solution of the compressible Euler equations as the mesh parameter
vanishes, while the Mach number is fixed. The DMV solutions then converge to a
classical solution of the incompressible Euler system as the Mach number goes
to zero. Conversely, we show that if the mesh parameter is kept fixed, we
obtain an energy stable and consistent finite-volume scheme approximating the
incompressible Euler equations as the Mach number goes to zero. The numerical
solutions generated by this scheme then converge weakly to a DMV solution of
the incompressible Euler system as the mesh parameter vanishes. Invoking the
weak-strong uniqueness principle, we conclude that the DMV solution and
classical solution of the incompressible Euler system coincide, proving the AP
property of the scheme. We also present an extensive numerical case study in
order to illustrate the theoretical convergences, wherein we utilize the
techniques of K-convergence.


  Pre-trained vision-language (V-L) models such as CLIP have shown excellent
generalization ability to downstream tasks. However, they are sensitive to the
choice of input text prompts and require careful selection of prompt templates
to perform well. Inspired by the Natural Language Processing (NLP) literature,
recent CLIP adaptation approaches learn prompts as the textual inputs to
fine-tune CLIP for downstream tasks. We note that using prompting to adapt
representations in a single branch of CLIP (language or vision) is sub-optimal
since it does not allow the flexibility to dynamically adjust both
representation spaces on a downstream task. In this work, we propose
Multi-modal Prompt Learning (MaPLe) for both vision and language branches to
improve alignment between the vision and language representations. Our design
promotes strong coupling between the vision-language prompts to ensure mutual
synergy and discourages learning independent uni-modal solutions. Further, we
learn separate prompts across different early stages to progressively model the
stage-wise feature relationships to allow rich context learning. We evaluate
the effectiveness of our approach on three representative tasks of
generalization to novel classes, new target datasets and unseen domain shifts.
Compared with the state-of-the-art method Co-CoOp, MaPLe exhibits favorable
performance and achieves an absolute gain of 3.45% on novel classes and 2.72%
on overall harmonic-mean, averaged over 11 diverse image recognition datasets.
Our code and pre-trained models are available at
https://github.com/muzairkhattak/multimodal-prompt-learning.


  The dependence of random telegraph noise (RTN) amplitude on the gate
overdrive in a junctionless field-effect transistor (FinFET) with rectangular
and trapezoidal channel (fin) cross sections manufactured using
silicon-on-insulator technology has been numerically simulated. It is
established that the RTN amplitude in the subthreshold region of gate voltages
for a FinFET with a trapezoidal cross-section of the channel is significantly
lower than that for the transistor with a rectangular cross-section of a
channel. In addition, under the same conditions, the RTN amplitude at the
threshold gate voltage in a junctionless FinFET is significantly lower than
that in planar fully depleted and in usual FinFET.


  We present new quantum codes with good parameters which are constructed from
self-orthogonal algebraic geometry codes. Our method permits a wide class of
curves to be used in the formation of these codes, which greatly extends the
class of a previous paper due to Munuera, Ten\'orio and Torres. These results
demonstrate that there is a lot more scope for constructing self-orthogonal AG
codes than was previously known.


  We present a unified strategy to derive Hardy-Poincar\'e inequalities on
bounded and unbounded domains. The approach allows proving a general
Hardy-Poincar\'e inequality from which the classical Poincar\'e and Hardy
inequalities immediately follow. The idea also applies to the more general
context of variable exponent Sobolev spaces. The argument, concise and
constructive, does not require a priori knowledge of compactness results and
retrieves geometric information on the best constants.


  Compact stars such as neutron stars and black holes are gravitationally bound
many body systems. We investigate the importance of short and long range part
of gravity for such systems. From our analysis, we conclude that the true
essence of gravity lies with the long range nature of the interaction. At the
end we show how these arguments in the manybody theory consistently leads to
Dvali-Gomez picture of a black holes as a collective bound state of long
wavelength gravitons.


  Computing the electric eddy currents in non-linear materials, such as
superconductors, is \E{not straightforward}. The design of superconducting
magnets and power applications needs electromagnetic computer modeling, being
in many cases a three-dimensional (3D) problem. Since 3D problems require high
computing times, novel time-efficient modeling tools are highly desirable. This
article presents a novel computing modeling method based on a variational
principle. The self-programmed implementation uses an original minimization
method, which divides the sample into sectors. This speeds-up the computations
with no loss of accuracy, while enabling efficient parallelization. This method
could also be applied to model transients in linear materials or networks of
non-linear electrical elements. As example, we analyze the magnetization
currents of a cubic superconductor. This 3D situation remains unknown, in spite
of the fact that it is often met in material characterization and bulk
applications. We found that below the penetration field and in part of the
sample, current flux lines are not rectangular and significantly bend in the
direction parallel to the applied field. In conclusion, the presented numerical
method is able to time-efficiently solve fully 3D situations without loss of
accuracy.


  The electrical control of magnons opens up new ways to transport and process
information for logic devices. In magnetoelectrical multiferroics, the
Dzyaloshinskii-Moriya (DM) interaction directly allow for such a control and,
hence, is of major importance. We determine the origin and the strength of the
(converse) spin current DM interaction in the R3c bulk phase of the
multiferroic BiFeO3 based on density functional theory. Our data supports only
the existence of one DM interaction contribution originating from the spin
current model. By exploring then magnon dispersion in the full Brillouin Zone,
we show that the exchange is isotropic, but the DM interaction and anisotropy
prefer any propagation and any magnetization direction within the full (111)
plane. Our work emphasizes the significance of the asymmetric potential induced
by the spin current over the structural asymmetry induced by the anionic
octahedron in multiferroics such as BiFeO3.


  We present the updated photometric calibration of the twelve optical
passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) second
data release (DR2), comprising 1088 pointings of two square degrees, and study
the systematic impact of metallicity in the stellar locus technique. The [Fe/H]
metallicity from LAMOST DR5 for 146184 high-quality calibration stars, defined
with S/N > 10 in J-PLUS passbands and S/N > 3 in Gaia parallax, was used to
compute the metallicity-dependent stellar locus (ZSL). The initial
homogenization of J-PLUS photometry, performed with a unique stellar locus, was
refined by including the metallicity effect in colours via the ZSL. The
variation of the average metallicity along the Milky Way produces a systematic
offset in J-PLUS calibration. This effect is well above 1% for the bluer
passbands and amounts 0.07, 0.07, 0.05, 0.03, and 0.02 mag in u, J0378, J0395,
J0410, and J0430, respectively. We modelled this effect with the Milky Way
location of the J-PLUS pointing, providing also an updated calibration for
those observations without LAMOST information. The estimated accuracy in the
calibration after including the metallicity effect is at 1% level for the bluer
J-PLUS passbands and below for the rest. We conclude that photometric
calibration with the stellar locus technique is prone to significant systematic
bias along the Milky Way location for passbands bluer than lambda = 4500 A. The
updated calibration method for J-PLUS DR2 reaches 1-2% precision and 1%
accuracy for twelve optical filters within an area of 2176 square degrees.


  A well-known result in general relativity is that the tidal Love numbers of
black holes vanish. In contrast, different configurations to a black hole may
have non-vanishing Love numbers. For instance, it has been conjectured recently
that the Love number of generic exotic compact objects (ECOs) shows a
logarithmic behavior. Here we analyze the ultracompact Schwarzschild star which
allows the compactness to cross and go beyond the Buchdahl limit. This
Schwarzschild star has been shown to be a good black hole mimicker, moreover,
it has been found that the Love number of these objects approaches zero as
their compactness approaches the black hole limit. Here we complement those
results, by showing that the Love number for these configurations follows an
exponentially decaying behavior rather than the logarithmic behavior proposed
for generic ECOs.


  Latest gaze estimation methods require large-scale training data but their
collection and exchange pose significant privacy risks. We propose PrivatEyes -
the first privacy-enhancing training approach for appearance-based gaze
estimation based on federated learning (FL) and secure multi-party computation
(MPC). PrivatEyes enables training gaze estimators on multiple local datasets
across different users and server-based secure aggregation of the individual
estimators' updates. PrivatEyes guarantees that individual gaze data remains
private even if a majority of the aggregating servers is malicious. We also
introduce a new data leakage attack DualView that shows that PrivatEyes limits
the leakage of private training data more effectively than previous approaches.
Evaluations on the MPIIGaze, MPIIFaceGaze, GazeCapture, and NVGaze datasets
further show that the improved privacy does not lead to a lower gaze estimation
accuracy or substantially higher computational costs - both of which are on par
with its non-secure counterparts.


  Non-Markovian quantum state diffusion (NMQSD) provides a powerful approach to
the dynamics of an open quantum system in bosonic environments. Here we develop
an NMQSD method to study the open quantum system in fermionic environments.
This problem involves anticommutative noise functions (i.e., Grassmann
variables) that are intrinsically different from the noise functions of bosonic
baths. We obtain the NMQSD equation for quantum states of the system and the
non-Markovian master equation. Moreover, we apply this NMQSD method to single
and double quantum-dot systems.


  The virial theorem for the translation-invariant theory of a polaron [3] is
discussed. It is shown that, in [3], Tulub made a nonoptimal choice of
variational parameters in the strong-coupling limit, which led to the violation
of the virial relations. The introduction of an additional variational
parameter to the test function reduces the polaron energy and makes it possible
to satisfy the relations of the virial theorem for a strong-coupling polaron
(the Pekar 1 : 2 : 3 : 4 theorem).


  Modelling the integrated H I spectra of galaxies has been a difficult task
due to their diverse shapes, but more dynamical information is waiting to be
explored in Hi line profiles. Based on simple assumptions, we construct a
physically motivated model for the integrated Hi spectra: Parametrized
Asymmetric Neutral hydrogen Disk Integrated Spectrum Characterization
(PANDISC). The model shows great flexibility in reproducing the diverse Hi
profiles. We use Monte-Carlo Markov Chain (MCMC) for fitting the model to
global H I profiles, producing statistically robust quantitative results.
Comparing with several samples of H I data available in the literature , we
find the model-fitted results agree with catalogued velocity widths (e.g., W50)
down to the lowest S/N. The model is also shown to be useful for applications
like the baryonic Tully-Fisher relation (BTFR) and profile-based sample
control. By comparing v_r to v_flat , we uncover how the H I width is affected
by the structure of the rotation curve, following a trend consistent with the
difference in the BTFR slope. We also select a sample of spectra with broad
wing-like features suggestive of a population of galaxies with unusual gas
dynamics. The PANDISC model bears both promise and limitations for potential
use beyond H I lines. Further application on the whole ALFALFA sample will
enable us to perform large scale ensemble studies of the H I properties and
dynamics in nearby galaxies.


  Many engineering and scientific applications require high precision
arithmetic. IEEE~754-2008 compliant (floating-point) arithmetic is the de facto
standard for performing these computations. Recently, posit arithmetic has been
proposed as a drop-in replacement for floating-point arithmetic. The
posit\texttrademark data representation and arithmetic claim several absolute
advantages over the floating-point format and arithmetic, including higher
dynamic range, better accuracy, and superior performance-area trade-offs.
However, there does not exist any accessible, holistic framework that
facilitates the validation of these claims of posit arithmetic, especially when
the claims involve long accumulations (quire).
  In this paper, we present a consolidated general-purpose processor-based
framework to support posit arithmetic empiricism. The end-users of the
framework have the liberty to seamlessly experiment with their applications
using posit and floating-point arithmetic since the framework is designed for
the two number systems to coexist. Melodica is a posit arithmetic core that
implements parametric fused operations that uniquely involve the quire data
type. Clarinet is a Melodica-enabled processor based on the RISC-V ISA. To the
best of our knowledge, this is the first-ever integration of quire with a
RISC-V core. To show the effectiveness of the Clarinet platform, we perform an
extensive application study and benchmark some of the common linear algebra and
computer vision kernels. We emulate Clarinet on a Xilinx FPGA and present
utilization and timing data. Clarinet and Melodica remain actively under
development and is available in open-source for posit arithmetic empiricism.


  This study addresses the challenge of, without training or fine-tuning,
controlling the global color aspect of images generated with a diffusion model.
We rewrite the guidance equations to ensure that the outputs are closer to a
known color map, and this without hindering the quality of the generation. Our
method leads to new guidance equations. We show in the color guidance context
that, the scaling of the guidance should not decrease but remains high
throughout the diffusion process. In a second contribution, our guidance is
applied in a compression framework, we combine both semantic and general color
information on the image to decode the images at low cost. We show that our
method is effective at improving fidelity and realism of compressed images at
extremely low bit rates, when compared to other classical or more semantic
oriented approaches.


  Extending the classical Dirichlet's density theorem on coprime pairs, in this
paper we describe completely the probability distribution of the number of
coprime pairs in random squares of fixed side length in the lattice
$\mathbb{N}^2$. The limit behaviour of this distribution as the side length of
the random square tends to infinity is also considered.


  We report quantum interference effects in the electrical conductance of
chemical vapor deposited graphene nanoconstrictions fabricated using feedback
controlled electroburning. The observed multimode Fabry-Perot interferences can
be attributed to reflections at potential steps inside the channel. Sharp
antiresonance features with a Fano line shape are observed. Theoretical
modeling reveals that these Fano resonances are due to localized states inside
the constriction, which couple to the delocalized states that also give rise to
the Fabry-Perot interference patterns. This study provides new insight into the
interplay between two fundamental forms of quantum interference in graphene
nanoconstrictions.


  We investigate the role of intra-molecular conformational disorder and
inter-molecular electronic interactions on the electronic structure of disorder
clusters of poly-p-phenylene vinylene (PPV) oligomers. Classical molecular
dynamics is used to determine probable molecular geometries, and
first-principle density functional theory (DFT) calculations are used to
determine electronic structure. Intra-molecular and inter-molecular effects are
disentangled by contrasting results for densely packed oligomer clusters with
those for ensembles of isolated oligomers with the same intra-molecular
geometries. We find that electron trap states are induced primarily by
intra-molecular configuration disorder, while the hole trap states are
generated primarily from inter-molecular electronic interactions.


  Recent discoveries of a super-virial hot phase of the Milky Way
circumgalactic medium (CGM) has launched new questions regarding the
multi-phase structure of the CGM around the Galaxy. We use 1.05 Ms of archival
Chandra/HETG observations to characterize highly ionized metal absorption at
z=0 along the line of sight of the quasar NGC 3783. We detect two distinct
temperature phases with T$_1 = 5.83^{+0.15}_{-0.07}$ K, warm-hot virial
temperature, and T$_2=6.61^{+0.12}_{-0.06}$ K, hot super-virial temperature.
The super-virial hot phase coexisting with the warm-hot virial phase has been
detected in absorption along only two other sightlines and in one stacking
analysis. There is scatter in temperature of the hot as well as warm-hot gas.
Similar to previous observations, we detect super-solar abundance ratios of
metals in the hot phase, with a Ne/O ratio 2$\sigma$ above solar mixtures.
These new detections continue the mystery of the mechanism behind the
super-virial hot phase, but provide evidence that this is a true property of
the CGM rather than an isolated observation. The super-virial CGM could hold
the key to understanding the physical and chemical history of the Milky Way.


  In this note we classify the non-Noetherian generalized Heisenberg algebras
H(f) introduced by Rencai L\"u and Kaiming Zhao [Linear Algebra Appl., 2015].
In case the polynomial f has degree greater than 1, we determine all locally
finite and also all locally nilpotent derivations of H(f) and describe the
automorphism group of these algebras.


  We describe a superconducting circuit consisting of a Josephson junction in
parallel with a quantum phase slip wire, which implements a Hamiltonian that is
periodic in both charge and flux. This Hamiltonian is exactly diagonalisable in
a double-Bloch band, and the eigenstates are shown to be code states of the
Gottesman-Kitaev-Preskill quantum error correcting code. The eigenspectrum has
several critical points, where the linear sensitivity to external charge and
flux noise vanishes. The states at these critical points thus hold promise as
qubit states that are insensitive to external noise sources.


  We consider separable $C^*$-dynamical systems $(A,G,\alpha)$ for which the
induced action of the group $G$ on the spectrum $\hat A$ of the $C^*$-algebra
$A$ is free. We study how the representation theory of the associated
crossed-product $C^*$-algebra $A\rtimes_\alpha G$ depends on the representation
theory of $A$ and the properties of the action of $G$ on $\hat A$. Our main
tools involve computations of upper and lower bounds on multiplicity numbers
associated to irreducible representations of $A\rtimes_\alpha G$. We apply our
techniques to give necessary and sufficient conditions, in terms of $A$ and the
action of $G$ on $\hat A$, for $A\rtimes_{\alpha}G$ to be (i) a
continuous-trace $C^*$-algebra, (ii) a Fell $C^*$-algebra and (iii) a
bounded-trace $C^*$-algebra. When $G$ is amenable, we also give necessary and
sufficient conditions for the crossed-product $C^*$-algebra
$A\rtimes_{\alpha}G$ to be (iv) a liminal $C^*$-algebra and (v) a Type I
$C^*$-algebra. The results in (i), (iii)--(v) extend some earlier special cases
in which $A$ was assumed to have the corresponding property.


  The wave-particle duality is the main point of demarcation between quantum
and classical physics, and is the quintessential mystery of quantum mechanics.
Young's two-slit interference experiment is the arch prototype of actual and
gedanken experiments used as a testing ground of this duality. Quantum
mechanics predicts that any detector capable of determining the path taken by a
particle through one or the other of a two-slit plate will destroy the
interference pattern. We will examine both the experimental and theoretical
attempts to test this assertion, including a new kind of experiment, and to
grasp the underlying truth behind this mystery from the earliest days to the
present. Where positions differ, the views of both sides are presented in a
balanced approach.


  The ALFA subdetector is designed to measure elastic proton-proton scattering
from which the total cross section and $\rho$-parameter are determined. In
2016, special runs at a center-of-mass energy of $\sqrt{s} = 13$\,TeV and with
$\beta^\star = 2.5$\,km were recorded.


  The paper deals with the three-dimensional Dirichlet boundary value problem
(BVP) for a second order strongly elliptic self-adjoint system of partial
differential equations in the divergence form with variable coefficients and
develops the integral potential method based on a localized parametrix. Using
Green's representation formula and properties of the localized layer and volume
potentials, we reduce the Dirichlet BVP to a system of localized
boundary-domain integral equations (LBDIEs). The equivalence between the
Dirichlet BVP and the corresponding LBDIE system is studied. We establish that
the obtained localized boundary-domain integral operator belongs to the Boutet
de Monvel algebra. With the help of the Wiener-Hopf factorization method we
investigate corresponding Fredholm properties and prove invertibility of the
localized operator in appropriate Sobolev (Bessel potential) spaces.


  For the radial and one-dimensional Schr\"{o}dinger operator $H$ with growing
potential $q(x)$ we outline a method of obtaining the trace identities - an
asymptotic expansion of the Fredholm determinant $\mathrm{det}_{F}(H-\lambda
I)$ as $\lambda\to-\infty$. As an illustrating example, we consider
Schr\"{o}dinger operator with the potential $q(x)=2\cosh 2x$, associated with
the modified Mathieu equation.


  In this work we study the zero-charge sector of massive two-dimensional
Quantum Chromodynamics in the decoupled formulation. We find that some general
features of the massless theory, concerning the constraints and the right- and
left-moving character of the corresponding BRST currents, survive in the
massive case. The implications for the integrability properties previously
valid in the massless case, and the structure of the Hilbert space are
discussed.


  As quantum computers progress towards a larger scale, it is imperative that
the "top" of the computing-technology stack is improved. This project
investigates the quantum resources required to compute primitive arithmetic
algorithms, particularly multiplication. By using various quantum resource
estimators, like Microsoft's Azure Quantum Resource Estimator, one can
determine the resources required for numerous quantum algorithms [5]. In this
paper, we will provide a comprehensive resource analysis of numerous quantum
multiplication algorithms such as Karatsuba, schoolbook, and windowed
arithmetic for different qubit platforms (trapped ion, superconducting, and
Majorana) using the new Azure Quantum Resource Estimator.


  Expansions in noninteger positive bases have been intensively investigated
since the pioneering works of R\'enyi (1957) and Parry (1960). The discovery of
surprising unique expansions in certain noninteger bases by Erd\H os, Horv\'ath
and Jo\'o (1991) was followed by many studies aiming to clarify the topological
and combinatorial nature of the sets of these bases. In the present work we
extend some of these studies to more general, negative or complex bases.


  Synthetic electronic health records (EHRs) that are both realistic and
preserve privacy can serve as an alternative to real EHRs for machine learning
(ML) modeling and statistical analysis. However, generating high-fidelity and
granular electronic health record (EHR) data in its original,
highly-dimensional form poses challenges for existing methods due to the
complexities inherent in high-dimensional data. In this paper, we propose
Hierarchical Autoregressive Language mOdel (HALO) for generating longitudinal
high-dimensional EHR, which preserve the statistical properties of real EHR and
can be used to train accurate ML models without privacy concerns. Our HALO
method, designed as a hierarchical autoregressive model, generates a
probability density function of medical codes, clinical visits, and patient
records, allowing for the generation of realistic EHR data in its original,
unaggregated form without the need for variable selection or aggregation.
Additionally, our model also produces high-quality continuous variables in a
longitudinal and probabilistic manner. We conducted extensive experiments and
demonstrate that HALO can generate high-fidelity EHR data with high-dimensional
disease code probabilities (d > 10,000), disease co-occurrence probabilities
within visits (d > 1,000,000), and conditional probabilities across consecutive
visits (d > 5,000,000) and achieve above 0.9 R2 correlation in comparison to
real EHR data. This performance then enables downstream ML models trained on
its synthetic data to achieve comparable accuracy to models trained on real
data (0.938 AUROC with HALO data vs. 0.943 with real data). Finally, using a
combination of real and synthetic data enhances the accuracy of ML models
beyond that achieved by using only real EHR data.


  The evolution of a localized vortex in stably stratified flow, within the
Boussinesq approximation, is analyzed using the fluid impulse concept. The set
of equations describing the temporal development of the fluid impulse has an
integro-differential character where the terms representing the effect of
stratification appear as convolution integral of the component of the fluid
impulse and time-depended 'memory' functions. These functions are calculated
for the case where the external parallel shear flow varies only in the
direction gravitational force and is subjected to localized two- and
three-dimensional disturbances. As follows from the solution of evolution
equations, in both cases there is a range of Richardson numbers where the fluid
impulse associated with the disturbance grows exponentially. The upper limit of
this range for two- and three-dimensional cases are Ri ~ 1.23 and Ri ~ 0.89.
Both cases are also characterized by a critical value of the Richardson number
(around Ri ~ 0.3 for both cases), beyond which the solution exhibits
oscillatory behavior. Indeed, this oscillatory behavior has been observed in
turbulent flows and, as is shown in the present study, it is an inherent
feature of a non-wavy localized vortex embedded in a stably stratified shear
flow. The paper was written in 2001 and published now without changes and new
additions.


  Purpose: To rapidly obtain high isotropic-resolution T2 maps with whole-brain
coverage and high geometric fidelity.
  Methods: A T2 blip-up/down echo planar imaging (EPI) acquisition with
generalized Slice-dithered enhanced resolution (T2-BUDA-gSlider) is proposed. A
radiofrequency (RF)-encoded multi-slab spin-echo EPI acquisition with multiple
echo times (TEs) was developed to obtain high SNR efficiency with reduced
repetition time (TR). This was combined with an interleaved 2-shot EPI
acquisition using blip-up/down phase encoding. An estimated field map was
incorporated into the joint multi-shot EPI reconstruction with a structured low
rank constraint to achieve distortion-free and robust reconstruction for each
slab without navigation. A Bloch simulated subspace model was integrated into
gSlider reconstruction and utilized for T2 quantification.
  Results: In vivo results demonstrated that the T2 values estimated by the
proposed method were consistent with gold standard spin-echo acquisition.
Compared to the reference 3D fast spin echo (FSE) images, distortion caused by
off-resonance and eddy current effects were effectively mitigated.
  Conclusion: BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint
reconstruction enabled distortion-free whole-brain T2 mapping in 2 min at ~1
mm3 isotropic resolution, which could bring significant benefits to related
clinical and neuroscience applications.


  This paper describes how the current lexical similarity and analogy gold
standards are built to conform to certain ideas about what the models they are
designed to evaluate are used for. Topical relevance has always been the most
important target notion for information access tools and related language
technology technologies, and while this has proven a useful starting point for
much of what information technology is used for, it does not always align well
with other uses to which technologies are being put, most notably use cases
from digital scholarship in the humanities or social sciences. This paper
argues for more systematic formulation of requirements from the digital
humanities and social sciences and more explicit description of the assumptions
underlying model design.


  Bolibruch's examples of representations of pi_1(P^1-finitely many points)
which are not realizable by Fuchsian differential systems are adapted to curves
of higher genus.


  We describe the design, manufacture, and performance of bare-fiber integral
field units (IFUs) for the SDSS-IV survey MaNGA (Mapping Nearby Galaxies at
APO) on the the Sloan 2.5 m telescope at Apache Point Observatory (APO). MaNGA
is a luminosity-selected integral-field spectroscopic survey of 10,000 local
galaxies covering 360-1030 nm at R ~ 2200. The IFUs have hexagonal dense
packing of fibers with packing regularity of 3 um (RMS), and throughput of
96+/-0.5% from 350 nm to 1 um in the lab. Their sizes range from 19 to 127
fibers (3-7 hexagonal layers) using Polymicro FBP 120:132:150 um
core:clad:buffer fibers to reach a fill fraction of 56%. High throughput (and
low focal-ratio degradation) is achieved by maintaining the fiber cladding and
buffer intact, ensuring excellent surface polish, and applying a multi-layer AR
coating of the input and output surfaces. In operations on-sky, the IFUs show
only an additional 2.3% FRD-related variability in throughput despite repeated
mechanical stressing during plate plugging (however other losses are present).
The IFUs achieve on-sky throughput 5% above the single-fiber feeds used in
SDSS-III/BOSS, attributable to equivalent performance compared to single fibers
and additional gains from the AR coating. The manufacturing process is geared
toward mass-production of high-multiplex systems. The low-stress process
involves a precision ferrule with hexagonal inner shape designed to lead
inserted fibers to settle in a dense hexagonal pattern. The ferrule inner
diameter is tapered at progressively shallower angles toward its tip and the
final 2 mm are straight and only a few um larger than necessary to hold the
desired number of fibers. This process scales to accommodate other fiber sizes
and to IFUs with substantially larger fiber count. (Abridged)


  We introduce a method for fast estimation of data-adapted, spatio-temporally
dependent regularization parameter-maps for variational image reconstruction,
focusing on total variation (TV)-minimization. Our approach is inspired by
recent developments in algorithm unrolling using deep neural networks (NNs),
and relies on two distinct sub-networks. The first sub-network estimates the
regularization parameter-map from the input data. The second sub-network
unrolls $T$ iterations of an iterative algorithm which approximately solves the
corresponding TV-minimization problem incorporating the previously estimated
regularization parameter-map. The overall network is trained end-to-end in a
supervised learning fashion using pairs of clean-corrupted data but crucially
without the need of having access to labels for the optimal regularization
parameter-maps. We prove consistency of the unrolled scheme by showing that the
unrolled energy functional used for the supervised learning $\Gamma$-converges
as $T$ tends to infinity, to the corresponding functional that incorporates the
exact solution map of the TV-minimization problem. We apply and evaluate our
method on a variety of large scale and dynamic imaging problems in which the
automatic computation of such parameters has been so far challenging: 2D
dynamic cardiac MRI reconstruction, quantitative brain MRI reconstruction,
low-dose CT and dynamic image denoising. The proposed method consistently
improves the TV-reconstructions using scalar parameters and the obtained
parameter-maps adapt well to each imaging problem and data by leading to the
preservation of detailed features. Although the choice of the regularization
parameter-maps is data-driven and based on NNs, the proposed algorithm is
entirely interpretable since it inherits the properties of the respective
iterative reconstruction method from which the network is implicitly defined.


  Quadratic forms with embedded discriminants. Integral binary quadratic forms
have multiple applications, for example in factorization or cryptography. The
Nice family of cryptographic systems makes use of quadratic forms with
different discriminants $\pm p$, and $\pm pq^2$ where $p$, $q$ are large
primes. This paper shows the precise links between forms with $D$ discriminant
and forms with $Df^2$ discriminant, which are crucial in the analysis of the
systems Nice and theirs attacks. We also introduce the notion of
semi-equivalence of binary quadratic forms, and give some characterizations of
semi-equivalent forms, which are useful in the analysis of these attacks.
  -----
  Les formes quadratiques binaires fournissent un moyen explicite pour
manipuler des id\'eaux de corps quadratiques, et leurs applications pratiques
sont multiples. De nombreux algorithmes de factorisation les utilisent. Elle
sont aussi utilis\'ees en cryptographie, en particulier pour les syst\`emes
Nice. Les syst\`emes de chiffrement Nice utilisent des formes quadratiques de
discriminants $\pm p$ et $\pm pq^2$ o\`u $p$ et $q$ sont des nombres premiers.
Cet article pr\'ecise les liens entre les formes de discriminant $D$ et celles
de discriminant $Df^2$, ce qui est essentiel pour l'analyse de Nice et de ses
attaques. Il introduit aussi la notion de formes quadratiques
semi-\'equivalentes et en explicite plusieurs caract\'erisations, utiles pour
l'analyse de ces attaques.