  I present the results of multi-component decomposition of V and R broadband
images of a sample of 17 nearby galaxies, most of them hosting bars and active
galactic nuclei. I use BUDDA v2.1 to produce the fits, allowing to include bars
and AGN in the models. A comparison with previous results from the literature
shows a fairly good agreement. It is found that the axial ratio of bars, as
measured from ellipse fits, can be severely underestimated if the galaxy
axisymmetric component is relatively luminous. Thus, reliable bar axial ratios
can only be determined by taking into account the contributions of bulge and
disc to the light distribution in the galaxy image. Through a number of tests,
I show that neglecting bars when modelling barred galaxies can result in a
overestimation of the bulge-to-total luminosity ratio of a factor of two.
Similar effects result when bright, type 1 AGN are not considered in the
models. By artificially redshifting the images, I show that the structural
parameters of more distant galaxies can in general be reliably retrieved
through image fitting, at least up to the point where the physical spatial
resolution is ~ 1.5 Kpc. This exercise shows that disc parameters are
particularly robust, but bulge parameters are prone to errors if its effective
radius is small compared to the seeing radius, and might suffer from systematic
effects. In this low resolution regime, the effects of ignoring bars are still
present, but AGN light is smeared out. I briefly discuss the consequences of
these results to studies of the structural properties of galaxies, in
particular on the stellar mass budget in the local universe. With reasonable
assumptions, it is possible to show that the stellar content in bars can be
similar to that in classical bulges and elliptical galaxies. (Abridged)


  The intragrain pinning in high-$T_c$ superconductor compounds
Y$_{1-x}$RE$_{x}$Ba$_{2}$Cu$_{3}$O$_{7-\delta}$ with low concentration of RE
(La, Ce, Pr) was investigated. Magnetic and transport measurements reveal that
the pinning is maximal for the concentration of heterovalent RE such that the
average distance between the impurity ions in the plane of rare-earth elements
close to the diameter of Abrikosov vortices in YBCO.


  Consider a multi-class labelling problem, where the labels can take values in
$[k]$, and a predictor predicts a distribution over the labels. In this work,
we study the following foundational question: Are there notions of multi-class
calibration that give strong guarantees of meaningful predictions and can be
achieved in time and sample complexities polynomial in $k$? Prior notions of
calibration exhibit a tradeoff between computational efficiency and
expressivity: they either suffer from having sample complexity exponential in
$k$, or needing to solve computationally intractable problems, or give rather
weak guarantees.
  Our main contribution is a notion of calibration that achieves all these
desiderata: we formulate a robust notion of projected smooth calibration for
multi-class predictions, and give new recalibration algorithms for efficiently
calibrating predictors under this definition with complexity polynomial in $k$.
Projected smooth calibration gives strong guarantees for all downstream
decision makers who want to use the predictor for binary classification
problems of the form: does the label belong to a subset $T \subseteq [k]$: e.g.
is this an image of an animal? It ensures that the probabilities predicted by
summing the probabilities assigned to labels in $T$ are close to some perfectly
calibrated binary predictor for that task. We also show that natural
strengthenings of our definition are computationally hard to achieve: they run
into information theoretic barriers or computational intractability. Underlying
both our upper and lower bounds is a tight connection that we prove between
multi-class calibration and the well-studied problem of agnostic learning in
the (standard) binary prediction setting.


  The coupled mechanics of fluid-filled granular media controls the behavior of
many natural systems such as saturated soils, fault gouge, and landslides. The
grain motion and the fluid pressure influence each other: It is well
established that when the fluid pressure rises, the shear resistance of
fluid-filled granular systems decreases, and as a result catastrophic events
such as soil liquefaction, earthquakes, and accelerating landslides may be
triggered. Alternatively, when the pore pressure drops, the shear resistance of
these systems increases. Despite the great importance of the coupled mechanics
of grains-fluid systems, the basic physics that controls this coupling is far
from understood. We developed a new multi-scaled model based on the discrete
element method, coupled with a continuum model of fluid pressure, to explore
this dynamical system. The model was shown recently to capture essential
feedbacks between porosity changes arising from rearrangement of grains, and
local pressure variations due to changing pore configurations. We report here
new results from numerical experiments of a continuously shearing layer of
circular two-dimensional grains, trapped between two parallel rough boundaries.
The experiments use a fixed confining stress on the boundary walls, and a
constant velocity applied to one of the boundaries, as if this system was the
interior of a sliding geological fault filled with 'fault gouge'. In addition,
we control the layer permeability and the drainage boundary conditions. This
paper presents modeling results showing that the localization of shear (into a
narrow shear band within the shearing layer) is strongly affected by the
presence of fluids. While in dry granular layers there is no preferred position
for the onset of localization, drained systems tend to localize shear on their
boundary. We propose a scaling argument to describe the pressure deviations in
a shear band, and use that to predict the allowable positions of shear
localizations as a function of the fault and gouge properties.


  The Hall-Petch effect has been described for the past sixty years as a
dependence of the strength of polycrystalline metals on the inverse square-root
of grain size d. The value of the coefficient of the dependence has been the
subject of discussion throughout. Here, we find what factors in the experiments
determine its values. A meta-analysis using maximum-likelihood methods is
reported of the literature values of the coefficient in sixty-one datasets.
Weak dependence is found on composition and bulk strength. Clear dependence is
found on the elastic anisotropy of the different metals and on their stacking
fault energies. Surprisingly, no dependence is found on plastic strain, and the
strongest dependence is found on the average grain size of each study.
Combining these effects accounts for the reported values of about 80% of the
sixty-one coefficients. The grain-size dependence and the bulk strength
dependence indicate that the Hall-Petch coefficient is an artefact arising from
incorrect fitting of the data. Moreover, the grain-size dependence implies a
minimum strength described by a simple inverse 1/d or a lnd/d function, which
arises theoretically from considerations of dislocation curvature.


  This paper concerns the 3-dimensional Lagrangian Navier-Stokes $\alpha$ model
and the limiting Navier-Stokes system on smooth bounded domains with a class of
vorticity-slip boundary conditions and the Navier-slip boundary conditions. It
establishes the spectrum properties and regularity estimates of the associated
Stokes operators, the local well-posedness of the strong solution and global
existence of weak solutions for initial boundary value problems for such
systems. Furthermore, the vanishing $\alpha$ limit to a weak solution of the
corresponding initial-boundary value problem of the Navier-Stokes system is
proved and a rate of convergence is shown for the strong solution.


  The Total Matching Polytope generalizes the Stable Set Polytope and the
Matching Polytope. In this paper, we give the perfect formulation for Trees and
we derive two new families of valid inequalities, the balanced biclique
inequalities which are always facet-defining and the non-balanced lifted
biclique inequalities obtained by a lifting procedure, which are facet-defining
for bipartite graphs. Finally, we give a complete description for Complete
Bipartite Graphs.


  This paper expands further on a category theoretical formulation of
Hochschild cohomology for monoid objects in monoidal categories enriched over
abelian groups, which has been studied in arXiv:1605.00842. This topic was also
presented at ISCRA, Isfahan, Iran, April 2019. The present paper aims to
provide a more intuitive formulation of the Hochschild cochain complex and
extend the definition to Hochschild cohomology with values in a bimodule
object. In addition, an equivalent formulation of the Hochschild cochain
complex in terms of a cosimplicial object in the category of abelian groups is
provided.


  We consider extensions of the next-to-minimal supersymmetric model (NMSSM) in
which the observed neutrino masses are generated through a TeV scale inverse
seesaw mechanism. The new particles associated with this mechanism can have
sizable couplings to the Higgs field which can yield a large contribution to
the mass of the lightest CP-even Higgs boson. With this new contribution, a 126
GeV Higgs is possible along with order of 200 GeV masses for the stop quarks
for a broad range of \tan\beta. The Higgs production and decay in the diphoton
channel can be enhanced due to this new contribution. It is also possible to
solve the little hierarchy problem in this model without invoking a maximal
value for the NMSSM trilinear coupling and without severe restrictions on the
value of \tan\beta.


  An out-of-plane Oersted field produced from a current-carrying Au wire is
used to induce local domain formation in wires made from [Co/Pd]15 multilayers
with perpendicular anisotropy. A 100 ns pulsed current of 56-110 mA injected
into the Au wire created a reverse domain size of 120-290 nm in a Co/Pd
nanowire on one side of the Au wire. A Biot-Savart model was used to estimate
the position dependence of the Oersted field around the Au wire. The shape,
size and location of the reversed region of Co/Pd was consistent with the
magnitude of the Oersted field and the switching field distribution of the
unpatterned film. A current density of 6.2 x 10^11 A m-2 in the Co/Pd nanowire
did not translate the domain walls due to low spin transfer efficiency, but the
Joule heating promoted domain growth in a field below the coercive field.


  Given a classifier ensemble and a set of examples to be classified, many
examples may be confidently and accurately classified after only a subset of
the base models in the ensemble are evaluated. This can reduce both mean
latency and CPU while maintaining the high accuracy of the original ensemble.
To achieve such gains, we propose jointly optimizing a fixed evaluation order
of the base models and early-stopping thresholds. Our proposed objective is a
combinatorial optimization problem, but we provide a greedy algorithm that
achieves a 4-approximation of the optimal solution for certain cases. For those
cases, this is also the best achievable polynomial time approximation bound
unless $P = NP$. Experiments on benchmark and real-world problems show that the
proposed Quit When You Can (QWYC) algorithm can speed-up average evaluation
time by $2$x--$4$x, and is around $1.5$x faster than prior work. QWYC's joint
optimization of ordering and thresholds also performed better in experiments
than various fixed orderings, including gradient boosted trees' ordering.


  The study of the sobriety of Scott spaces has got an relative long history in
domain theory. Lawson and Hoffmann independently proved that the Scott space of
every continuous directed complete poset (usually called domain) is sober.
Johnstone constructed the first directed complete poset whose Scott space is
non-sober. Not long after, Isbell gave a complete lattice with non-sober Scott
space. Based on Isbell's example, Xu, Xi and Zhao showed that there is even a
complete Heyting algebra whose Scott space is non-sober. Achim Jung then asked
whether every countable complete lattice has a sober Scott space.
  Let $\Sigma P$ be the Scott space of poset $P$. In this paper, we first prove
that the topology of the product space $\Sigma P\times \Sigma Q$ coincides with
the Scott topology on the product poset $P\times Q$ if the set $Id(P)$ and
$Id(Q)$ of all non-trivial ideals of posets $P$ and $Q$ are both countable.
Based on this result, we deduce that a directed complete poset $P$ has a sober
Scott space, if $Id(P)$ is countable and the space $\Sigma P$ is coherent and
well-filtered. Thus a complete lattice $L$ with $Id(L)$ countable has a sober
Scott space. Making use the obtained results, we then construct a countable
complete lattice whose Scott space is non-sober and thus give a negative answer
to Jung's problem.


  We present a wide-field study of the globular cluster system (GCS) of the
field lenticular galaxy NGC 1172, based on observations from GMOS/Gemini
(optical), FourStar/Magellan (NIR), and archival data from ACS/HST (optical).
This analysis covers the full extension of the GCS, and results in a value of
specific frequency (S_N=8.6 +/- 1.5) peculiarly high for an intermediate-mass
galaxy in a low-density environment such as this one. We find that the GCS
appears to be bimodal, although the colour distribution is narrow and does not
allow for an accurate separation of the subpopulations. However, the
combination of optical and NIR filters allows us to obtain an estimation of the
metallicity distribution based on the photometry, which supports bimodality. We
conclude that the presence of a large fraction of metal-poor globular clusters
(GCs) and the high specific frequency point to NGC 1172 having accreted a
significant amount of GCs from low-mass satellites in the past.


  Engineering change orders (ECOs) in late stages make minimal design fixes to
recover from timing shifts due to excessive IR drops. This paper integrates
IR-drop-aware timing analysis and ECO timing optimization using reinforcement
learning (RL). The method operates after physical design and power grid
synthesis, and rectifies IR-drop-induced timing degradation through gate
sizing. It incorporates the Lagrangian relaxation (LR) technique into a novel
RL framework, which trains a relational graph convolutional network (R-GCN)
agent to sequentially size gates to fix timing violations. The R-GCN agent
outperforms a classical LR-only algorithm: in an open 45nm technology, it (a)
moves the Pareto front of the delay-area tradeoff curve to the left and (b)
saves runtime over the classical method by running fast inference using trained
models at iso-quality. The RL model is transferable across timing
specifications, and transferable to unseen designs with zero-shot learning or
fine tuning.


  We construct geometric realizations for the infimax family of substitutions
by generalizing the Rauzy-Canterini-Siegel method for a single substitution to
the S-adic case. The composition of each countably infinite subcollection of
substitutions from the family has an asymptotic fixed sequence whose shift
orbit closure is an infimax minimal set $\Delta^+$. The subcollection of
substitutions also generates an infinite Bratteli-Vershik diagram with
prefix-suffix labeled edges. Paths in the diagram give the Dumont-Thomas
expansion of sequences in $\Delta^+$ which in turn gives a projection onto the
asymptotic stable direction of the infinite product of the Abelianization
matrices. The projections of all sequences from $\Delta^+$ is the generalized
Rauzy fractal which has subpieces corresponding to the images of symbolic
cylinder sets. The intervals containing these subpieces are shown to be
disjoint except at endpoints, and thus the induced map derived from the
symbolic shift translates them. Therefore the process yields an Interval
Translation Map, and the Rauzy fractal is proved to be its attractor.


  We present a formalism and numerical results for the energy loss of a charged
particle scattered at an arbitrary angle from epitaxially grown multilayer
graphene (MLG). It is compared with that of free-standing graphene layers.
Specifically, we investigated the effect of the substrate induced energy gap on
one of the layers. The gap yields collective plasma oscillations whose
characteristics are qualitatively and quantitatively different from those
produced by Dirac fermions in gapless graphene. The range of wave numbers for
undamped self-sustaining plasmons is increased as the gap is increased, thereby
increasing and red-shifting the MLG stopping power for some range of charged
particle velocity. We also applied our formalism to interpret several distinct
features of experimentally obtained electron energy loss spectroscopy (EELS)
data.


  In this paper, we study the indirect stabilization problem for a system of
two coupled semilinear wave equations with internal damping in a bounded domain
in $\mathbb{R}^3$. The nonlinearity is assumed to be subcritical, defocusing
and analytic. Under geometric control condition on both coupling and damping
regions, we establish the exponential energy decay rate.


  Detailed alias frequency formula and the effect of alias sampling on the
calculation of MHD mode number are derived. It is discovered that the absolute
MHD mode number/structure does not change under alias sampling. This discovery
can help us to determine the structure of the high frequency MHD mode with low
frequency sampled diagnostics even when the Nyquist-Shannon sampling theorem is
no longer valid.


  Renewable energy conversion and storage, and greenhouse gas emission-free
technologies are within the primary tasks and challenges for the society.
Hydrogen fuel, produced by alkaline water electrolysis is fulfilling all these
demands, however the technology is economically feeble, limited by the slow
rate of oxygen evolution reaction. Complex metal oxides were suggested to
overcome this problem being low-cost efficient catalysts. However, the
insufficient long-term stability, degradation of structure and electrocatalytic
activity are restricting their utilization. Here we report on a new
perovskite-based self-assembling material BaCo0.98Ti0.02O3-$\delta$:Co3O4 with
superior performance, showing outstanding properties compared to current
state-of-the-art materials without degeneration of its properties even at 353
K. By chemical and structural analysis the degradation mechanism was identified
and modified by selective doping. Short-range order and chemical composition
rather than long-range order are factors determining the outstanding
performance. The derived general design rules can be used for further
development of oxide-based electrocatalytic materials.


  Supernova remnants (SNRs) are believed to accelerate particles up to high
energies through the mechanism of diffusive shock acceleration (DSA). Except
for direct plasma simulations, all modeling efforts must rely on a given form
of the diffusion coefficient, a key parameter that embodies the interactions of
energetic charged particles with the magnetic turbulence. The so-called Bohm
limit is commonly employed. In this paper we revisit the question of
acceleration at perpendicular shocks, by employing a realistic model of
perpendicular diffusion. Our coefficient reduces to a power-law in momentum for
low momenta (of index $\alpha$), but becomes independent of the particle
momentum at high momenta (reaching a constant value $\kappa_{\infty}$ above
some characteristic momentum $p_{\rm c}$). We first provide simple analytical
expressions of the maximum momentum that can be reached at a given time with
this coefficient. Then we perform time-dependent numerical simulations to
investigate the shape of the particle distribution that can be obtained when
the particle pressure back-reacts on the flow. We observe that, for a given
index $\alpha$ and injection level, the shock modifications are similar for
different possible values of $p_{\rm c}$, whereas the particle spectra differ
markedly. Of particular interest, low values of $p_{\rm c}$ tend to remove the
concavity once thought to be typical of non-linear DSA, and result in steep
spectra, as required by recent high-energy observations of Galactic SNRs.


  We consider the electron-positron annihilation process into hadrons
$R_{e^+e^-}$ up to $\mathcal{O}(\alpha_{s}^{3})$ and we adopt the smearing
method suggest by Poggio, Quinn and Weinberg to confront the experimental data
with theory. As a theoretical model we use a QCD coupling constant frozen in
the low energy regime, where this coupling can be parameterised in terms of an
effective dynamical gluon mass ($m_g$) which is determined through
Schwinger-Dyson equations. In order to find the best fit between experimental
data and theory we perform a $\chi^2$ study, that, within the uncertainties of
the approach, has a minimum value when $m_g/\Lambda_{QCD}$ is in the range $1.2
\, - \, 1.4$. These values are in agreement with other phenomenological
determinations of this ratio and lead to an infrared effective charge
$\alpha_s(0) \approx 0.7$. We comment how this effective charge may affect the
global duality mass scale that indicates the frontier between perturbative and
non-perturbative physics.


  Results on Deeply Virtual Compton Scattering at HERA measured by the H1 and
ZEUS Collaborations are presented. The cross section, measured for the first
time, is reported for by H1 and ZEUS for $Q^2$ above a few GeV$^2$ in the low
$x$ region. The measured cross section is discussed and compared to different
predictions.


  In this paper, we study the network pinning control problem in the presence
of two different types of coupling: (i) node-to-node coupling among the network
nodes and (ii) input-to-node coupling from the source node to the `pinned
nodes'. Previous work has mainly focused on the case that (i) and (ii) are of
the same type. We decouple the stability analysis of the target synchronous
solution into subproblems of the lowest dimension by using the techniques of
simultaneous block diagonalization (SBD) of matrices. Interestingly, we obtain
two different types of blocks, driven and undriven. The overall dimension of
the driven blocks is equal to the dimension of an appropriately defined
controllable subspace, while all the remaining undriven blocks are scalar. Our
main result is a decomposition of the stability problem into four independent
sets of equations, which we call quotient controllable, quotient
uncontrollable, redundant controllable, and redundant uncontrollable. Our
analysis shows that the number and location of the pinned nodes affect the
number and the dimension of each set of equations. We also observe that in a
large variety of complex networks, stability of the target synchronous solution
is de facto only determined by a single quotient controllable block.


  We consider the spatially inhomogeneous Landau equation with soft potentials,
including the case of Coulomb interactions. First, we establish the existence
of solutions for a short time, assuming the initial data is in a fourth-order
Sobolev space and has Gaussian decay in the velocity variable (no decay
assumptions are made in the spatial variable). Next, we show that the evolution
instantaneously spreads mass to every point in its domain. The resulting
pointwise lower bounds have a sub-Gaussian rate of decay, which we show is
optimal. The proof of mass-spreading is based on a stochastic process
associated to the equation, and makes essential use of nonlocality. By
combining this theorem with prior regularity results, we derive two important
applications: $C^\infty$ smoothing in all three variables, even for initial
data with vacuum regions, and a continuation criterion that states the solution
can be extended for as long as the mass and energy densities stay bounded from
above. This is the weakest condition known to prevent blow-up. In particular,
it does not require a lower bound on the mass density or an upper bound on the
entropy density.


  CDF has obtained new results on quarkonium production in p\bar{p} collisions
at \sqrt{s} = 1.8 TeV. We report on measurements of Upsilon meson production,
Upsilon(1S) production from Chi_b feeddown, and the production polarization of
Upsilon(1S), J/Psi and Psi(2S) mesons.


  We calculate characteristic correlation functions for the Anderson model with
additional phonon-assisted coupling to the odd conduction channel. This model
describes, for example, the behavior of a molecule embedded between two
electrodes in linear transport experiments where the position of the molecule
with respect to the leads affects the tunneling amplitudes. We use variational
projection-operator method and numerical renormalization group (NRG) method.
The spin is Kondo screened either by even or odd conduction channel depending
on the gate voltage and electron-phonon coupling. However, in all regimes the
gate-voltage dependence of the zero temperature conductance is found to be
qualitatively the same as in the model with no coupling to the vibrational
mode.


  Motivated by orbifold string theory, we introduce orbifold cohomology group
for any almost complex orbifold and orbifold Dolbeault cohomology for any
complex orbifold. Then, we show that our new cohomology group satisfies
Poincare duality and has a natural ring structure. Some examples of orbifold
cohomology ring are computed.


  Continual Test-Time Adaptation (CTTA) aims to adapt the source model to
continually changing unlabeled target domains without access to the source
data. Existing methods mainly focus on model-based adaptation in a
self-training manner, such as predicting pseudo labels for new domain datasets.
Since pseudo labels are noisy and unreliable, these methods suffer from
catastrophic forgetting and error accumulation when dealing with dynamic data
distributions. Motivated by the prompt learning in NLP, in this paper, we
propose to learn an image-level visual domain prompt for target domains while
having the source model parameters frozen. During testing, the changing target
datasets can be adapted to the source model by reformulating the input data
with the learned visual prompts. Specifically, we devise two types of prompts,
i.e., domains-specific prompts and domains-agnostic prompts, to extract current
domain knowledge and maintain the domain-shared knowledge in the continual
adaptation. Furthermore, we design a homeostasis-based prompt adaptation
strategy to suppress domain-sensitive parameters in domain-invariant prompts to
learn domain-shared knowledge more effectively. This transition from the
model-dependent paradigm to the model-free one enables us to bypass the
catastrophic forgetting and error accumulation problems. Experiments show that
our proposed method achieves significant performance gains over
state-of-the-art methods on four widely-used benchmarks, including CIFAR-10C,
CIFAR-100C, ImageNet-C, and VLCS datasets.


  Present work deals with the dynamics of vehicles which intentionally operate
in the ground proximity. The dynamics in ground effect is influenced by the
vehicle orientation with respect to the ground, since the aerodynamic force and
moment coefficients, which in turn depend on height and angle of attack, also
vary with the Euler angles. This feature, usually neglected in the
applications, can be responsible for sizable variations of the aircraft
performance and stability. A further effect, caused by the sink rate,
determines unsteadiness that modifies the aerodynamic coefficients. In this
work, an analytical formulation is proposed for the force and moment
calculation in the presence of the ground and taking the aircraft attitude and
sink rate into account. The aerodynamic coefficients are firstly calculated for
a representative vehicle and its characteristics in ground effect are
investigated. Performance and stability characteristics are then discussed with
reference to significant equilibrium conditions, while the non-linear dynamics
is studied through the numerical integration of the equations of motion.


  We consider corrections to the Lamb shift of p-wave atomic states due to the
finite nuclear size (FNS). In other words, these are radiative corrections to
the atomic isotop shift related to FNS. It is shown that the structure of the
corrections is qualitatively different from that for s-wave states. The
perturbation theory expansion for the relative correction for a $p_{1/2}$-state
starts from $\alpha\ln(1/Z\alpha)$-term, while for $s_{1/2}$-states it starts
from $Z\alpha^2$ term. Here $\alpha$ is the fine structure constant and $Z$ is
the nuclear charge. In the present work we calculate the $\alpha$-terms for
$2p$-states, the result for $2p_{1/2}$-state reads
$(8\alpha/9\pi)[\ln(1/(Z\alpha)^2)+0.710]$. Even more interesting are
$p_{3/2}$-states. In this case the ``correction'' is by several orders of
magnitude larger than the ``leading'' FNS shift.


  A model for diffusion-controlled spherical particle growth is presented and
solved numerically, showing how, on cooling at sufficient rate from a given
fraction solid, growth velocity first increases, and then decreases rapidly
when solute fields of adjacent particles overlap. An approximate analytical
solution for the spherical particle growth velocity is then developed and shown
to be valid until the solute fields begin to overlap. A particle stability
model is next presented, building on the above analytic solution. This model
permits prediction of the maximum cooling rate at which a semi-solid slurry or
reheated semi-solid billet can be cooled while still retaining the spherical
growth morphology. The model shows that particle stability is favored by high
particle density, high fraction solid and low cooling rate. The predictions of
the stability model are found to be in good quantitative agreement with
experimental data collected for Al-4.5wt%Cu alloy. Engineering applications of
the results obtained are discussed.


  Entanglement in bipartite systems has been applied for the generation of
secure random numbers, which are playing an important role in cryptography or
scientific numerical simulations. Here, we propose to use multipartite
entanglement distributed between trusted and untrusted parties for generating
randomness of arbitrary dimensional systems. We show that the distributed
structure of several parties leads to additional protection against possible
attacks by an eavesdropper, resulting in more secure randomness generated than
in the corresponding bipartite scenario. Especially, randomness can be
certified in the group of untrusted parties, even there is no randomness exists
in either of them individually. We prove that the necessary and sufficient
resource for quantum randomness in this scenario is multipartite quantum
steering when two measurement settings are performed on the untrusted parties.
However, the sufficiency no longer holds with more measurement settings.
Finally, we apply our analysis to some experimentally realized states and show
that more randomness can be extracted in comparison to the existing analysis.


  The system allowing a user to operate with simulated curves of spectral
energy distribution (SED) and to estimate ages and redshifts by photometric
data at server {\bf sed.sao.ru} is described.


  We describe defense mechanisms designed to detect sophisticated grid attacks
involving both physical actions (including load modification) and sensor output
alteration, with the latter performed in a sparse manner and also so as to take
into account grid response mechanisms (secondary response). The attacks aim to
be both undetectable even under a full AC power flow model, and to hide
equipment overload. We demonstrate that such attacks, while perhaps difficult
to implement, nevertheless are easily computed even on systems with a large
number of installed sensors, and can, in a static setting, successfuly hide
large line overloads. Furthermore an attacker that understands the ongoing
stochastic nature of sensor signals can extend the attack so as to remain
effective for a nontrivial time period. To counteract such "ideal" or "perfect"
attacks, we demonstrate a set of data-driven stochastic techniques to thwart
the attacker and detect that an attack has taken place.


  An exact solution of $(2+1)$-dimensional Einstein gravity with cosmological
constant is studied. The corresponding spacetime is interpreted as an
accelerating BTZ spacetime. The proper acceleration, horizon structure,
temperature and entropy are presented in detail. The metric being studied is
very similar to the one studied by Astorino in arXiv:1101.2616, but the range
of parameters is different which results in significant changes in the causal
structures.


  We present a model describing the use of ultra-short strong pulses to control
the population of the excited level of a two-level quantum system. In
particular, we study an off-resonance excitation with a few cycles pulse which
presents a smooth phase jump i.e. a change of the pulse's phase which is not
step-like, but happens over a finite time interval. A numerical solution is
given for the time-dependent probability amplitude of the excited level. The
control of the excited level's population is obtained acting on the shape of
the phase transient, and other parameters of the excitation pulse.


  We describe an access control model that has been implemented in the web
content management framework "Deme" (which rhymes with "team"). Access control
in Deme is an example of what we call "bivalent relation object access
control"(BROAC). This model builds on recent work by Giunchiglia et al. on
relation-based access control (RelBAC), as well as other work on relational,
flexible, fine-grained, and XML access control models. We describe Deme's
architecture and review access control models, motivating our approach. BROAC
allows for both positive and negative permissions, which may conflict with each
other. We argue for the usefulness of defining access control rules as objects
in the target database, and for the necessity of resolving permission conflicts
in a social Web/collaboration architecture. After describing how Deme access
control works, including the precedence relations between different permission
types in Deme, we provide several examples of realistic scenarios in which
permission conflicts arise, and show how Deme resolves them. Initial
performance tests indicate that permission checking scales linearly in time on
a practical Deme website.


  The increasing significance of sustainability considerations within both
public spheres (such as policies and regulations) and private sectors
(including voluntary commitments by major multinational corporations)
underscores the imperative to harness cutting-edge technological advancements.
This is essential to ensure that the momentum of this trend translates into
tangible outcomes, thwarting phenomena like greenwashing and upholding high
standards of integrity, all while expediting progress through automation. This
paper focuses specifically on carbon markets, which, after enduring years of
confusion and controversy, may finally be on the brink of converging toward
internationally recognized minimum standards. Beginning with an introduction to
fundamental concepts pertaining to carbon markets and Distributed Ledger
Technologies (DLTs), the paper proceeds to dissect the challenges and
opportunities within this burgeoning field. Its primary contribution lies in
offering a comprehensive overview of recent developments across various
initiatives (such as ICVCM, IETA/WorldBank/CAD Trust, IEEE/ISO) and providing a
layered analysis of the entire ecosystem. This framework aids in understanding
and prioritising future endeavours. Ultimately, the paper furnishes a set of
recommendations aimed at bolstering scalability and fostering widespread
adoption of best practices within international markets.


  Fix $c\in (0,1)$ and let $\Gamma$ be a $\lfloor c n\rfloor$-regular digraph
on $n$ vertices drawn uniformly at random. We prove that when $n$ is large, the
(non-symmetric) adjacency matrix $M$ of $\Gamma$ is invertible with high
probability. The proof uses a couplings approach based on the switchings method
of McKay and Wormald. We also rely on discrepancy properties for the
distribution of edges in $\Gamma$, recently proved by the author, to overcome
certain difficulties stemming from the dependencies between the entries of $M$.


  The inner disk of the Galaxy has a number of young star clusters dominated by
red supergiants that are heavily obscured by dust extinction and observable
only at infrared wavelengths. These clusters are important tracers of the
recent star formation and chemical enrichment history in the inner Galaxy.
During the technical commissioning and as a first science verification of the
GIANO spectrograph at the Telescopio Nazionale Galileo, we secured
high-resolution (R~50,000) near-infrared spectra of three red supergiants in
the young Scutum cluster RSGC2. Taking advantage of the full YJHK spectral
coverage of GIANO in a single exposure, we were able to identify several tens
of atomic and molecular lines suitable for chemical abundance determinations.
By means of spectral synthesis and line equivalent width measurements, we
obtained abundances of Fe and other iron-peak elements such as V, Cr, Ni, of
alpha (O, Mg, Si, Ca and Ti) and other light elements (C, N, Na, Al, K, Sc),
and of some s-process elements (Y, Sr). We found iron abundances between half
and one third solar and solar-scaled [X/Fe] abundance patterns of iron-peak,
alpha and most of the light elements, consistent with a thin-disk chemistry. We
found a depletion of [C/Fe] and enhancement of [N/Fe], consistent with CN
burning, and low 12C/13C abundance ratios (between 9 and 11), requiring
extra-mixing processes in the stellar interiors during the post-main sequence
evolution. Finally, we found a slight [Sr/Fe] enhancement and a slight [Y/Fe]
depletion (by a factor of <=2), with respect to solar.


  The Cosmology Large Angular Scale Surveyor consists of four instruments
performing a CMB polarization survey. Currently, the 40 GHz and first 90 GHz
instruments are deployed and observing, with the second 90 GHz and a
multichroic 150/220 GHz instrument to follow. The receiver is a central
component of each instrument's design and functionality. This paper describes
the CLASS receiver design, using the first 90 GHz receiver as a primary
reference. Cryogenic cooling and filters maintain a cold, low-noise environment
for the detectors. We have achieved receiver detector temperatures below 50 mK
in the 40 GHz instrument for 85% of the initial 1.5 years of operation, and
observed in-band efficiency that is consistent with pre-deployment estimates.
At 90 GHz, less than 26% of in-band power is lost to the filters and lenses in
the receiver, allowing for high optical efficiency. We discuss the mounting
scheme for the filters and lenses, the alignment of the cold optics and
detectors, stray light control, and magnetic shielding.


  The linear stability of a shocked isothermal accretion flow onto a black hole
is investigated in the inviscid limit. The outer shock solution, which was
previously found to be stable with respect to axisymmetric perturbations, is,
however, generally unstable to non-axisymmetric ones. Eigenmodes and growth
rates are obtained by numerical integration of the linearized equations. The
mechanism of this instability is based on the cycle of acoustic waves between
their corotation radius and the shock. It is a form of the Papaloizou-Pringle
instability, modified by advection and the presence of the shock. As such it
can be generalized to non isothermal shocked accretion flows. Blobs and
vortices are generated by the shock as a by-product of the instability.


  A notion of cyclic descents on standard Young tableaux (SYT) of rectangular
shape was introduced by Rhoades, and extended to certain skew shapes by Adin,
Elizalde and Roichman. The cyclic descent set restricts to the usual descent
set when the largest value is ignored, and has the property that the number of
SYT of a given shape with a given cyclic descent set D is invariant under
cyclic shifts of the entries of D. Adin, Reiner and Roichman proved that a skew
shape has a cyclic descent map if and only if it is not a connected ribbon.
Unfortunately, their proof is nonconstructive. Recently Huang constructed an
explicit cyclic descent map for all shapes where this is possible.
  In the earlier version of Adin, Elizalde and Roichman's paper, they asked to
find statistics on combinatorial objects which are equidistributed with cyclic
descents on SYT of given shapes. In this paper, we explicitly describe cyclic
descent sets for Motzkin paths, which are equidistributed with cyclic descent
sets of SYT for three-row shapes. Moreover, in light of Stanley's shuffling
theorem, we give a bijective proof of the shuffling property of descent
statistics for Motzkin paths.


  We used the quantitative theory of solubility of karst rocks of Shopov et.
al, (1989, 1991a) in dependence of the temperature and other thermodynamic
parameters to make reconstructions of past carbonate denudation rates. This
theory produced equations assessing the carbonate denudation rates in
dependence on the temperature or on the precipitation. We estimated the
averaged denudation rate in the region to 14 mm/kyr or 38 t/km2 per year. We
used this estimate as starting point and substituted our proxy records of the
annual temperature and the annual precipitation in the equations of dependence
of karst denudation rate on precipitation and temperature. This way we
reconstructed variations of the annual karst denudation rate for the last 280
years in dependence on the annual precipitation and for the last 1250 years in
dependence on the temperature. Both reconstructions produce quite reasonable
estimate of the variations of carbonate denudation, which is within observed
variation of 8- 20 mm/kyr (86% variation). Precipitation dependence of
carbonate denudation produces 79 % variation in the denudation rate in result
of the reconstructed variation of 300 mm/yr from the driest to the wettest year
during the last 280 years. Temperature dependence of carbonate denudation due
to temperature dependence of solubility of the carbonate dioxide produce only
9.3% variation in the denudation rate in result of the reconstructed variation
of 4.7 deg. C during the last 1250 years, so it is negligible in respect of the
precipitation dependence.


  Let $k$ be a field and let $\Lambda$ be a finite dimensional $k$-algebra. We
prove that every bounded complex $V^\bullet$ of finitely generated
$\Lambda$-modules has a well-defined versal deformation ring
$R(\Lambda,V^\bullet)$ which is a complete local commutative Noetherian
$k$-algebra with residue field $k$. We also prove that nice two-sided tilting
complexes between $\Lambda$ and another finite dimensional $k$-algebra $\Gamma$
preserve these versal deformation rings. Additionally, we investigate stable
equivalences of Morita type between self-injective algebras in this context. We
apply these results to the derived equivalence classes of the members of a
particular family of algebras of dihedral type that were introduced by Erdmann
and shown by Holm to be not derived equivalent to any block of a group algebra.


  This paper reports on the extreme ultraviolet (EUV) spectrum of three low
redshift ($z \sim 0.6$) radio loud quasars, 3C 95, 3C 57 and PKS 0405-123. The
spectra were obtained with the Cosmic Origins Spectrograph (COS) of the Hubble
Space Telescope. The bolometric thermal emission, $L_{bol}$, associated with
the accretion flow is a large fraction of the Eddington limit for all of these
sources. We estimate the long term time averaged jet power, $\overline{Q}$, for
the three sources. $\overline{Q}/L_{bol}$, is shown to lie along the
correlation of $\overline{Q}/L_{bol}$ and $\alpha_{EUV}$ found in previous
studies of the EUV continuum of intermediate and high redshift quasars, where
the EUV continuum flux density between 1100 \AA\, and 700 \AA\, is defined by
$F_{\nu} \sim \nu^{-\alpha_{EUV}}$. The high Eddington ratios of the three
quasars extends the analysis into a wider parameter space. Selecting quasars
with high Eddington ratios has accentuated the statistical significance of the
partial correlation analysis of the data. Namely. the correlation of
$\overline{Q}/L_{\mathrm{bol}}$ and $\alpha_{EUV}$ is fundamental and the
correlation of $\overline{Q}$ and $\alpha_{EUV}$ is spurious at a very high
statistical significance level (99.8\%). This supports the regulating role of
ram pressure of the accretion flow in magnetically arrested accretion models of
jet production. In the process of this study, we use multi-frequency and
multi-resolution Very Large Array radio observations to determine that one of
the bipolar jets in 3C 57 is likely frustrated by galactic gas that keeps the
jet from propagating outside the host galaxy.


  A recent paper [DDL] claims that the increase of the proton electric charge e
leads to a (forbidden) decrease of black hole entropy, therefore, possible
evidence for variation of $\alpha=e^2/\hbar c$ [alpha] must be interpreted as a
decrease of the speed of light. We argue that purely theoretical consideration
of black holes possibly cannot give any model-independent limitations on
variation of fundamental constants.


  We describe a method to construct irreducible baryon operators using
all-to-all quark propagators. It was demonstrated earlier that a large basis of
extended baryon operators on anisotropic, quenched lattices can be used to
reliably extract the masses of 5 or more excited states in the nucleon channel.
All-to-all quark propagators are expected to be needed when studying these
excited states on light, dynamical configurations because contributions from
multi-particle states are expected to be significant. The dilution method is
used to approximate the all-to-all quark propagators. Low-lying eigenmodes can
also be used if necessary. For efficient computation of matrix elements of the
interpolating operators, the algorithms should exploit the fact that many
extended baryon operators can be obtained from the different linear
combinations of three-quark colour-singlet operators. The sparseness of the
diluted noise vectors also afford several computation simplifications. Some
preliminary results are presented for nucleon effective masses.


  A variation of fundamental constants of physics is proposed in a frame of
static universe. It is shown when the velocity of light increases (decreases)
the Planck's constant increases (decreases) and mass of bodies decreases
(increases). This variation of constants leads to the variation of dimensions
of bodies and the energy levels of atoms, but a fine structure constant remains
unaltered.


  We study the identification and estimation of structural parameters in
dynamic panel data logit models where decisions are forward-looking and the
joint distribution of unobserved heterogeneity and observable state variables
is nonparametric, i.e., fixed-effects model. We consider models with two
endogenous state variables: the lagged decision variable, and the time duration
in the last choice. This class of models includes as particular cases important
economic applications such as models of market entry-exit, occupational choice,
machine replacement, inventory and investment decisions, or dynamic demand of
differentiated products. The identification of structural parameters requires a
sufficient statistic that controls for unobserved heterogeneity not only in
current utility but also in the continuation value of the forward-looking
decision problem. We obtain the minimal sufficient statistic and prove
identification of some structural parameters using a conditional likelihood
approach. We apply this estimator to a machine replacement model.


  Using $(448.1\pm2.9)\times 10^{6}$ $\psi(3686)$ events collected with the
BESIII detector and a single-baryon tagging technique, we present the first
observation of the decays $\psi(3686)\to\Xi(1530)^{0}\bar{\Xi}(1530)^{0}$ and
$\Xi(1530)^{0}\bar{\Xi}^0$. The branching fractions are measured to be
${\cal{B}}(\psi(3686)\to\Xi(1530)^{0}\bar{\Xi}(1530)^{0}) =
(6.77\pm0.14\pm0.39)\times10^{-5}$ and
${\cal{B}}(\psi(3686)\to\Xi(1530)^{0}\bar{\Xi}^{0}) =
(0.53\pm0.04\pm0.03)\times10^{-5}$. Here, the first and second uncertainties
are statistical and systematic, respectively. In addition, the parameter
associated with the angular distribution for the decay
$\psi(3686)\to\Xi(1530)^{0}\bar{\Xi}(1530)^0$ is determined to be $\alpha =
0.32\pm0.19\pm0.07$, in agreement with theoretical predictions within one
standard deviation.


  In this paper, we propose an inexact multi-block ADMM-type first-order method
for solving a class of high-dimensional convex composite conic optimization
problems to moderate accuracy. The design of this method combines an inexact
2-block majorized semi-proximal ADMM and the recent advances in the inexact
symmetric Gauss-Seidel (sGS) technique for solving a multi-block convex
composite quadratic programming whose objective contains a nonsmooth term
involving only the first block-variable. One distinctive feature of our
proposed method (the sGS-imsPADMM) is that it only needs one cycle of an
inexact sGS method, instead of an unknown number of cycles, to solve each of
the subproblems involved.With some simple and implementable error tolerance
criteria, the cost for solving the subproblems can be greatly reduced, and many
steps in the forward sweep of each sGS cycle can often be skipped, which
further contributes to the efficiency of the proposed method. Global
convergence as well as the iteration complexity in the non-ergodic sense is
established.Preliminary numerical experiments on some high-dimensional linear
and convex quadratic SDP problems with a large number of linear equality and
inequality constraints are also provided. The results show that for the vast
majority of the tested problems, the sGS-imsPADMM is 2 to 3 times faster than
the directly extended multi-block ADMM with the aggressive step-length of
1.618, which is currently the benchmark among first-order methods for solving
multi-block linear and quadratic SDP problems though its convergence is not
guaranteed.


  The puzzling features of recent photoemission data in cuprates have been
object of several analysis in order to identity the nature of the underlying
electron-boson interaction. In this paper we point out that many basilar
assumptions of the conventional analysis as expected to fail in small Fermi
energy systems when, as the cuprates, the Fermi energy $E_{\rm F}$ is
comparable with the boson energy scale. We discuss in details the novel
features appearing in the self-energy of small Fermi energy systems and the
possible implications on the ARPES data in cuprates.


  This paper considers a batch solution to the multi-object tracking problem
based on sets of trajectories. Specifically, we present two offline
implementations of the trajectory Poisson multi-Bernoulli mixture (TPMBM)
filter for batch data based on Markov chain Monte Carlo (MCMC) sampling of the
data association hypotheses. In contrast to online TPMBM implementations, the
proposed offline implementations solve a large-scale, multi-scan data
association problem across the entire time interval of interest, and therefore
they can fully exploit all the measurement information available. Furthermore,
by leveraging the efficient hypothesis structure of TPMBM filters, the proposed
implementations compare favorably with other MCMC-based multi-object tracking
algorithms. Simulation results show that the TPMBM implementation using the
Metropolis-Hastings algorithm presents state-of-the-art multiple trajectory
estimation performance.


  The microscopic dynamics and aging of a soft thermosensitive suspension was
investigated by looking at the thermal fluctuations of tracers in the
suspension. Below and above the glass transition, the dense microgel particles
suspension was found to develop an heterogeneous dynamics, featured by a non
Gaussian Probability Distribution Function (PDF) of the probes' displacements,
with an exponential tail. We show that non Gaussian shapes are a characteristic
of the ensemble-averaged PDF, while local PDF remain Gaussian. This shows that
the scenario behind the non Gaussian van Hove functions is a spatially
heterogeneous dynamics, characterized by a spatial distribution of locally
homogeneous dynamical environments through the sample, on the considered time
scales. We characterize these statistical distributions of dynamical
environments, in the liquid, supercooled, and glass states, and show that it
can explain the observed exponential tail of the van Hove functions observed in
the concentrated states. The intensity of spatial heterogeneities was found to
amplify with increasing volume fraction. In the aging regime, it tends to
increase as the glass gets more arrested.


  The 3rd annual installment of the ActivityNet Large- Scale Activity
Recognition Challenge, held as a full-day workshop in CVPR 2018, focused on the
recognition of daily life, high-level, goal-oriented activities from
user-generated videos as those found in internet video portals. The 2018
challenge hosted six diverse tasks which aimed to push the limits of semantic
visual understanding of videos as well as bridge visual content with human
captions. Three out of the six tasks were based on the ActivityNet dataset,
which was introduced in CVPR 2015 and organized hierarchically in a semantic
taxonomy. These tasks focused on tracing evidence of activities in time in the
form of proposals, class labels, and captions. In this installment of the
challenge, we hosted three guest tasks to enrich the understanding of visual
information in videos. The guest tasks focused on complementary aspects of the
activity recognition problem at large scale and involved three challenging and
recently compiled datasets: the Kinetics-600 dataset from Google DeepMind, the
AVA dataset from Berkeley and Google, and the Moments in Time dataset from MIT
and IBM Research.


  Safety limitations in service robotics across various industries have raised
significant concerns about the need for robust mechanisms ensuring that robots
adhere to safe practices, thereby preventing actions that might harm humans or
cause property damage. Despite advances, including the integration of Knowledge
Graphs (KGs) with Large Language Models (LLMs), challenges in ensuring
consistent safety in autonomous robot actions persist. In this paper, we
propose a novel integration of Large Language Models with Embodied Robotic
Control Prompts (ERCPs) and Embodied Knowledge Graphs (EKGs) to enhance the
safety framework for service robots. ERCPs are designed as predefined
instructions that ensure LLMs generate safe and precise responses. These
responses are subsequently validated by EKGs, which provide a comprehensive
knowledge base ensuring that the actions of the robot are continuously aligned
with safety protocols, thereby promoting safer operational practices in varied
contexts. Our experimental setup involved diverse real-world tasks, where
robots equipped with our framework demonstrated significantly higher compliance
with safety standards compared to traditional methods. This integration fosters
secure human-robot interactions and positions our methodology at the forefront
of AI-driven safety innovations in service robotics.


  We present an encoding and hardware-independent formulation of optimization
problems for quantum computing. Using this generalized approach, we present an
extensive library of optimization problems and their various derived spin
encodings. Common building blocks that serve as a construction kit for building
these spin Hamiltonians are identified. This paves the way towards a fully
automatic construction of Hamiltonians for arbitrary discrete optimization
problems. The presented freedom in the problem formulation is a key step for
tailoring optimal spin Hamiltonians for different hardware platforms.


  Recent advances in quantum technology have led to the development and the
manufacturing of programmable quantum annealers that promise to solve certain
combinatorial optimization problems faster than their classical counterparts.
Semi-supervised learning is a machine learning technique that makes use of both
labeled and unlabeled data for training, which enables a good classifier with
only a small amount of labeled data. In this paper, we propose and
theoretically analyze a graph-based semi-supervised learning method with the
aid of the quantum annealing technique, which efficiently utilize the quantum
resources while maintaining a good accuracy. We illustrate two classification
examples, suggesting the feasibility of this method even with a small portion
(20%) of labeled data is involved.


  We propose a novel method to generate fabrication blueprints from images of
carpentered items. While 3D reconstruction from images is a well-studied
problem, typical approaches produce representations that are ill-suited for
computer-aided design and fabrication applications. Our key insight is that
fabrication processes define and constrain the design space for carpentered
objects, and can be leveraged to develop novel reconstruction methods. Our
method makes use of domain-specific constraints to recover not just valid
geometry, but a semantically valid assembly of parts, using a combination of
image-based and geometric optimization techniques.
  We demonstrate our method on a variety of wooden objects and furniture, and
show that we can automatically obtain designs that are both easy to edit and
accurate recreations of the ground truth. We further illustrate how our method
can be used to fabricate a physical replica of the captured object as well as a
customized version, which can be produced by directly editing the reconstructed
model in CAD software.


  Vacuum expectation values of products of local bilinears $\bar\psi\psi$ are
computed in massless $QED_2$ at finite density. It is shown that chiral
condensates exhibit an oscillatory inhomogeneous behaviour depending on the
chemical potential. The use of a path-integral approach clarifies the
connection of this phenomenon with the topological structure of the theory.


  We study the extent to which \psi-epistemic models for quantum measurement
statistics---models where the quantum state does not have a real, ontic
status---can explain the indistinguishability of nonorthogonal quantum states.
This is done by comparing the overlap of any two quantum states with the
overlap of the corresponding classical probability distributions over ontic
states in a \psi-epistemic model. It is shown that in Hilbert spaces of
dimension $d \geq 4$, the ratio between the classical and quantum overlaps in
any \psi-epistemic model must be arbitrarily small for certain nonorthogonal
states, suggesting that such models are arbitrarily bad at explaining the
indistinguishability of quantum states. For dimensions $d$ = 3 and 4, we
construct explicit states and measurements that can be used experimentally to
put stringent bounds on the ratio of classical-to-quantum overlaps in
\psi-epistemic models, allowing one in particular to rule out maximally
\psi-epistemic models more efficiently than previously proposed.


  Finding ground states of quantum many-body systems is known to be hard for
both classical and quantum computers. As a result, when Nature cools a quantum
system in a low-temperature thermal bath, the ground state cannot always be
found efficiently. Instead, Nature finds a local minimum of the energy. In this
work, we study the problem of finding local minima in quantum systems under
thermal perturbations. While local minima are much easier to find than ground
states, we show that finding a local minimum is computationally hard for
classical computers, even when the task is to output a single-qubit observable
at any local minimum. In contrast, we prove that a quantum computer can always
find a local minimum efficiently using a thermal gradient descent algorithm
that mimics the cooling process in Nature. To establish the classical hardness
of finding local minima, we consider a family of two-dimensional Hamiltonians
such that any problem solvable by polynomial-time quantum algorithms can be
reduced to finding ground states of these Hamiltonians. We prove that for such
Hamiltonians, all local minima are global minima. Therefore, assuming quantum
computation is more powerful than classical computation, finding local minima
is classically hard and quantumly easy.


  The transformer neural network has significantly out-shined all other neural
network architectures as the engine behind large language models. We provide a
theoretical analysis of the expressivity of the transformer architecture
through the lens of topos theory. From this viewpoint, we show that many common
neural network architectures, such as the convolutional, recurrent and graph
convolutional networks, can be embedded in a pretopos of piecewise-linear
functions, but that the transformer necessarily lives in its topos completion.
In particular, this suggests that the two network families instantiate
different fragments of logic: the former are first order, whereas transformers
are higher-order reasoners. Furthermore, we draw parallels with architecture
search and gradient descent, integrating our analysis in the framework of
cybernetic agents.


  We present systematic temperature-quench Monte Carlo simulations on
discrete-strain pseudospin model Hamiltonians to study microstructural
evolutions in 2D ferroelastic transitions with two-component vector order
parameters ($N_{OP}=2$). The zero value pseudospin is the single
high-temperature phase while the low-temperature phase has $N_v$ variants. Thus
the number of nonzero values of pseudospin are triangle-to-centered rectangle
($N_v=3$), square-to-oblique ($N_v=4$) and triangle-to-oblique ($N_v=6$). The
model Hamiltonians contain a transition-specific Landau energy term, a domain
wall cost or Ginzburg term, and power-law anisotropic interaction potential,
induced from a strain compatibility condition. On quenching below a transition
temperature, we find behaviour similar to the previously studied
square-to-rectangle transition ($N_{OP} =1, N_v = 2$), showing that the rich
behaviour found, is generic. Thus we find for two-component order parameters,
that the same Hamiltonian can describe both athermal and isothermal martensite
regimes for different material parameters. The athermal/isothermal/austenite
parameter regimes and temperature-time-transformation diagrams are understood,
as previously, through parametrization of effective-droplet energies. In the
athermal regime, we find rapid conversions below a spinodal like temperature
and austenite-martensite conversion delays above it, as in the experiment. The
delays show early incubation behaviour, and at the transition to austenite the
delay times have Vogel-Fulcher divergences and are insensitive to Hamiltonian
energy scales, suggesting that entropy barriers are dominant.


  In this paper, we consider three typical problems on a locally finite
connected graph. The first one is to study the Bochner formula for the
Laplacian operator on a locally finite connected graph. We use the Bochner
formula to derive the Bernstein type estimate of the heat equation. The second
is to derive the Reilly type formula of the Laplacian operator. The last one is
to obtain global positive solution to porous-media equation via the use of
Aronson-Benilan argument. There is not much work in the direction of the study
of nonlinear heat equations on locally finite connected graphs.


  We work with a class of scalar extended theory of gravity that can drive the
present cosmic acceleration as well as accommodate a mild cosmic variation of
the fine structure constant $\alpha$. The motivation comes from a vintage
theory developed by Bekenstein, Sandvik, Barrow and Magueijo. The $\alpha$
variation is introduced by a real scalar field interacting with charged matter.
We execute a cosmological reconstruction based on a parametrization of the
present matter density of the Universe. Observational consistency is ensured by
comparing the theoretical estimates with JLA + OHD + BAO data sets, using a
Markov chain Monte Carlo simulation. An analysis of molecular absorption lines
from HIRES and UVES spectrographs is considered as a reference for the
variation of $\alpha$ at different redshifts. Two examples are discussed. The
first explores a field-dependent kinetic coupling of the scalar field
interacting with charged matter. The second example is a generalized
Brans-Dicke formalism where the varying $\alpha$ is fitted in as an effective
matter field. This generates a simultaneous variation of the Newtonian constant
$G$ and $\alpha$. The pattern of this variation can have a crucial role in
cosmic expansion history.


  The adaptive immune response relies on T cells that combine phenotypic
specialization with diversity of T cell receptors (TCRs) to recognize a wide
range of pathogens. TCRs are acquired and selected during T cell maturation in
the thymus. Characterizing TCR repertoires across individuals and T cell
maturation stages is important for better understanding adaptive immune
responses and for developing new diagnostics and therapies. Analyzing a dataset
of human TCR repertoires from thymocyte subsets, we find that the variability
between individuals generated during the TCR V(D)J recombination is maintained
through all stages of T cell maturation and differentiation. The
inter-individual variability of repertoires of the same cell type is of
comparable magnitude to the variability across cell types within the same
individual. To zoom in on smaller scales than whole repertoires, we defined a
distance measuring the relative overlap of locally similar sequences in
repertoires. We find that the whole repertoire models correctly predict local
similarity networks, suggesting a lack of forbidden T cell receptor sequences.
The local measure correlates well with distances calculated using whole
repertoire traits and carries information about cell types.


  All the observations performed with the IBIS telescope aboard the INTEGRAL
observatory during the first 2.5 years of its in-orbit operation have been
analyzed to find X-ray bursts. There were 1788 statistically confident events
with a duration from 5 to 500 s revealed in time records of the 15-25 keV count
rate of the IBIS/ISGRI detector, 319 of them were localized and, with one
exception, identified with persistent X-ray sources. The known bursters were
responsible for 215 of the localized events. One burst was detected from
AXJ1754.2-2754, the source previously unknown as a burster, and another burst -
from a new source. There was duality in determining its position - its name
could be either IGR J17364-2711 or IGR J17380-3749. Curiously enough, the 138
bursts were detected from one X-ray burster - GX 354-0.


  We discuss the interplay between lagrangian distributions and connections in
symplectic geometry, beginning with the traditional case of symplectic
manifolds and then passing to the more general context of poly- and
multisymplectic structures on fiber bundles, which is relevant for the
covariant hamiltonian formulation of classical field theory. In particular, we
generalize Weinstein's tubular neighborhood theorem for symplectic manifolds
carrying a (simple) lagrangian foliation to this situation. In all cases, the
Bott connection, or an appropriately extended version thereof, plays a central
role.


  We study a new variant of \emph{connected coloring} of graphs based on the
concept of \emph{strong} edge coloring (every color class forms an
\emph{induced} matching). In particular, an edge-colored path is \emph{strongly
proper} if its color sequence does not contain identical terms within a
distance of at most two. A \emph{strong proper connected} coloring of $G$ is
the one in which every pair of vertices is joined by at least one strongly
proper path. Let spc($G$) denote the least number of colors needed for such
coloring of a graph $G$. We prove that the upper bound spc($G$)$\leq${5} holds
for any $2$-connected graph $G$. On the other hand, we demonstrate that there
are $2$-connected graphs with arbitrarily large girth satisfying
spc($G$)$\geq${4}. Additionally, we prove that graphs whose cycle lengths are
divisible by $3$ satisfy spc($G$)$\leq{3}$. We also consider briefly other
connected colorings defined by various restrictions on color sequences of
connecting paths. For instance, in a \emph{nonrepetitive connected coloring} of
$G$, every pair of vertices should be joined by a path whose color sequence is
\emph{nonrepetitive}, that is, it does not contain two adjacent identical
blocks. We demonstrate that $2$-connected graphs are $15$-colorable while
$4$-connected graphs are $6$-colorable, in the connected nonrepetitive sense. A
similar conclusion with a finite upper bound on the number of colors holds for
a much wider variety of connected colorings corresponding to fairly general
properties of sequences. We end the paper with some open problems of concrete
and general nature.


  Deep operator networks (DeepONets) are trained to predict the linear
amplification of instability waves in high-speed boundary layers and to perform
data assimilation. In contrast to traditional networks that approximate
functions, DeepONets are designed to approximate operators. Using this
framework, we train a DeepONet to take as inputs an upstream disturbance and a
downstream location of interest, and to provide as output the perturbation
field downstream in the boundary layer. DeepONet thus approximates the
linearized and parabolized Navier-Stokes operator for this flow. Once trained,
the network can perform predictions of the downstream flow for a wide variety
of inflow conditions, without the need to calculate the whole trajectory of the
perturbations, and at a very small computational cost compared to
discretization of the original equations. In addition, we show that DeepONets
can solve the inverse problem, where downstream wall measurements are adopted
as input and a trained network can predict the upstream disturbances that led
to these observations. This capability, along with the forward predictions,
allows us to perform a full data assimilation cycle: starting from
wall-pressure data, we predict the upstream disturbance using the inverse
DeepONet and its evolution using the forward DeepONet.


  Locating and distilling the valuable relevant information continued to be the
major challenges of Information Retrieval (IR) Systems owing to the explosive
growth of online web information. These challenges can be considered the XML
Information Retrieval challenges as XML has become a de facto standard over the
Web. The research on XML IR starts with the classical IR strategies customized
to XML IR. Later novel IR strategies specific to XML IR are evolved. Meanwhile
literatures reveal development of the rapid and intelligent IR systems. Despite
their success in their specified constrained domains, they have additional
limitations in the complex information space. The effectiveness of IR systems
is thus unsolved in satisfying the most. This article attemptsan overview of
earlier efforts and the gaps in XML IR.


  A well known theorem of Voronoi caracterizes extreme quadratic forms and
Euclidean lattices, that is those which are local maxima for the Hermite
function, as perfect and eutactic. This caracterization has been extended in
various cases, such that family of lattices, sections of lattices, Humbert
forms, etc. Moreover, there is a criterion for extreme lattices, discovered by
Venkov, formulated in terms of spherical designs which has been extended in the
case of Grassmannians and sections of lattices. In this article, we define a
general frame, in which there is a ``Voronoi characterization'', and a ``Venkov
criterion'' through an appropriate notion of design. This frame encompasses
many interesting situations in which a ``Voronoi characterization'' has been
proved. We also discuss the question of extremality relatively to the Epstein
zeta function, and we extend to our frame a characterization of final
zeta-extremality formulated by Delone and Ryshkov and a criterion in terms of
designs found by Coulangeon.


  Many scientific and industrial processes produce data that is best analysed
as vectors of relative values, often called compositions or proportions. The
Dirichlet distribution is a natural distribution to use for composition or
proportion data. It has the advantage of a low number of parameters, making it
the parsimonious choice in many cases. In this paper we consider the case where
the outcome of a process is Dirichlet, dependent on one or more explanatory
variables in a regression setting. We explore some existing approaches to this
problem, and then introduce a new simulation approach to fitting such models,
based on the Bayesian framework. We illustrate the advantages of the new
approach through simulated examples and an application in sport science. These
advantages include: increased accuracy of fit, increased power for inference,
and the ability to introduce random effects without additional complexity in
the analysis.


  A switching random walk, commonly known under the misnomer `oscillating
random walk', is a real-valued Markov chain such that the distribution of its
increments depends only on the sign of the current position. In this note we
find invariant measures for such chains. In the particular case where the chain
is an actual random walk, our proof naturally relates its stationarity relative
to the Lebesgue measure to stationarity of the renewal processes of its
ascending and descending ladder heights.


  Recent coronagraphic imaging of the AB Aurigae disk has revealed a region of
low polarized scattered light suggestive of perturbations from a planet at a
radius of ~100 AU. We model this darkened region using our fully
non-plane-parallel radiative-transfer code combined with a simple hydrostatic
equilibirum approximation to self-consistently solve for the structure of the
disk surface as seen in scattered light. By comparing the observations to our
models, we find that the observations are consistent with the absence of a
planet, with an upper limit of 1 Jupiter mass.


  Existing single view, 3D face reconstruction methods can produce beautifully
detailed 3D results, but typically only for near frontal, unobstructed
viewpoints. We describe a system designed to provide detailed 3D
reconstructions of faces viewed under extreme conditions, out of plane
rotations, and occlusions. Motivated by the concept of bump mapping, we propose
a layered approach which decouples estimation of a global shape from its
mid-level details (e.g., wrinkles). We estimate a coarse 3D face shape which
acts as a foundation and then separately layer this foundation with details
represented by a bump map. We show how a deep convolutional encoder-decoder can
be used to estimate such bump maps. We further show how this approach naturally
extends to generate plausible details for occluded facial regions. We test our
approach and its components extensively, quantitatively demonstrating the
invariance of our estimated facial details. We further provide numerous
qualitative examples showing that our method produces detailed 3D face shapes
in viewing conditions where existing state of the art often break down.


  In this paper we present a simple proof of the strong converse for
identification via discrete memoryless quantum channels, based on a novel
covering lemma. The new method is a generalization to quantum communication
channels of Ahlswede's recently discovered appoach to classical channels. It
involves a development of explicit large deviation estimates to the case of
random variables taking values in selfadjoint operators on a Hilbert space.
This theory is presented separately in an appendix, and we illustrate it by
showing its application to quantum generalizations of classical hypergraph
covering problems.


  Can an agent learn efficiently in a noisy and self adapting environment with
sequential, non-stationary and non-homogeneous observations? Through trading
bots, we illustrate how Deep Reinforcement Learning (DRL) can tackle this
challenge. Our contributions are threefold: (i) the use of contextual
information also referred to as augmented state in DRL, (ii) the impact of a
one period lag between observations and actions that is more realistic for an
asset management environment, (iii) the implementation of a new repetitive
train test method called walk forward analysis, similar in spirit to cross
validation for time series. Although our experiment is on trading bots, it can
easily be translated to other bot environments that operate in sequential
environment with regime changes and noisy data. Our experiment for an augmented
asset manager interested in finding the best portfolio for hedging strategies
shows that AAMDRL achieves superior returns and lower risk.


  Given manifolds $M$ and $N$, with $M$ compact, we study the geometrical
structure of the space of embeddings of $M$ into $N$, having less regularity
than $\mathcal C^\infty$, quotiented by the group of diffeomorphisms of $M$.


  We study the effect of coupling between the superconducting current and
magnetization in the superconductor/ferromagnet/superconductor Josephson
junction under an applied circularly polarized magnetic field. Manifestation of
ferromagnetic resonance in the frequency dependence of the amplitude of the
magnetization and the average critical current density is demonstrated
numerically. The IV-characteristics show subharmonic steps that form devil's
staircases, following a continued fraction algorithm. The origin of the found
steps is related to the effect of the magnetization dynamics on the phase
difference in the Josephson junction. The dynamics of our system is described
by a generalized RCSJ model coupled to the Landau-Lifshitz-Gilbert equation. In
the suplement we justify analytically the appearance of the fractional steps in
IV-characteristics of the superconductor/ferromagnet/superconductor Josephson
junction.


  The Raman response of new structures grown after filling SWCNTs with
ferrocene and transformation at moderate high temperatures is demonstrated to
be very strong, even stronger than the response from the tubes. Transmission
electron microscopy demonstrates that the new objects are flat and exhibit a
structure similar to short fragments of nanoribbons. The growth process is
controlled by two different activation energies for low and high transformation
temperatures, respectively. Immediately after filling Raman pattern from a
precursor molecule are detected. Two different types of nanoribbons were
identified by selecting special laser energies for the Raman excitation. These
ribbons have the signature of quaterrylene and terrylene, respectively.


  A systematic digital-discrete method for obtaining continuous functions with
smoothness to a certain order (C^(n)) from sample data is designed. This method
is based on gradually varied functions and the classical finite difference
method. This new method has been applied to real groundwater data and the
results have validated the method. This method is independent from existing
popular methods such as the cubic spline method and the finite element method.
The new digital-discrete method has considerable advantages for a large number
of real data applications. This digital method also differs from other
classical discrete methods that usually use triangulations. This method can
potentially be used to obtain smooth functions such as polynomials through its
derivatives f^(k) and the solution for partial differential equations such as
harmonic and other important equations.


  In this paper, we present a generalized effective completeness theorem for
continuous logic. The primary result is that any continuous theory is satisfied
in a structure which admits a presentation of the same Turing degree. It then
follows that any decidable theory is satisfied by a computably presentable
structure. This modifies and extends previous partial effective completeness
theorems for continuous logic given by Calvert and Didehvar, Ghasemloo, and
Pourmahdian.


  We present LVG and non-local radiative transfer calculations involving the
rotational and hyperfine structure of the spectrum of N$_2$H$^+$ with
collisional rate coefficients recently derived by us. The goal of this study is
to check the validity of the assumptions made to treat the hyperfine structure
and to study the physical mechanisms leading to the observed hyperfine
anomalies.
  We find that the usual hypothesis of identical excitation temperatures for
all hyperfine components of the $J$=1-0 transition is not correct within the
range of densities existing in cold dense cores, i.e., a few 10$^4$ $\textless$
n(H$_2$) $\textless$ a few 10$^6$ cm$^{-3}$. This is due to different radiative
trapping effects in the hyperfine components. Moreover, within this range of
densities and considering the typical abundance of N$_2$H$^+$, the total
opacity of rotational lines has to be derived taking into account the hyperfine
structure. The error made when only considering the rotational energy structure
can be as large as 100%. Using non-local models we find that, due to
saturation, hyperfine anomalies appear as soon as the total opacity of the
$J$=1-0 transition becomes larger than $\simeq$ 20. Radiative scattering in
less dense regions enhance these anomalies, and particularly, induce a
differential increase of the excitation temperatures of the hyperfine
components. This process is more effective for the transitions with the highest
opacities for which emerging intensities are also reduced by self-absorption
effects. These effects are not as critical as in HCO$^+$ or HCN, but should be
taken into account when interpreting the spatial extent of the N$_2$H$^+$
emission in dark clouds.


  The quantum entanglement measure of concurrence is shown to be directly
calculable from a Tomita- Takesaki modular operator framework constructed from
the local von Neumann algebras of observables for two quantum systems.
Specifically, the Tomita-Takesaki modular conjugation operator $J$ that links
two separate systems with respect to their von Neumann algebras is related to
the quantum concurrence $C$ of a pure bi-variate entangled state composed from
these systems. This concurrence relation provides a direct physical meaning to
$J$ as both a symmetry operator and a quantitative measure of entanglement.
This procedure is then demonstrated for a supersymmetric quantum mechanical
system and a real scalar field interacting with two entangled
spin-$\frac{1}{2}$ Unruh-DeWitt qubit detectors. For the latter system, the
concurrence result is shown to be consistent with some known results on the
Bell-CHSH inequality for such a system.


  We investigate the random dynamics of rational maps on the Riemann sphere and
the dynamics of semigroups of rational maps on the Riemann sphere. We show that
regarding random complex dynamics of polynomials, in most cases, the chaos of
the averaged system disappears, due to the cooperation of the generators. We
investigate the iteration and spectral properties of transition operators. We
show that under certain conditions, in the limit stage, "singular functions on
the complex plane" appear. In particular, we consider the functions $T$ which
represent the probability of tending to infinity with respect to the random
dynamics of polynomials. Under certain conditions these functions $T$ are
complex analogues of the devil's staircase and Lebesgue's singular functions.
More precisely, we show that these functions $T$ are continuous on the Riemann
sphere and vary only on the Julia sets of associated semigroups. Furthermore,
by using ergodic theory and potential theory, we investigate the
non-differentiability and regularity of these functions. We find many phenomena
which can hold in the random complex dynamics and the dynamics of semigroups of
rational maps, but cannot hold in the usual iteration dynamics of a single
holomorphic map. We carry out a systematic study of these phenomena and their
mechanisms.


  We study regular spacelike warped black holes in the three dimensional
general massive gravity model, which contains both the gravitational
Chern-Simons term and the linear combination of curvature squared terms
characterizing the new massive gravity besides the Einstein-Hilbert term. The
parameters of the metric are found by solving a quartic equation constrained by
an inequality that imposes the absence of closed timelike curves. Explicit
expressions for the central charges are suggested by exploiting the fact that
these black holes are discrete quotients of spacelike warped AdS(3) and a known
formula for the entropy. Previous results obtained separately in topological
massive gravity and in new massive gravity are recovered as special cases.


  We theoretically study the resonant phenomenon in a spin-1 Bose-Einstein
condensate periodically driven by a quadratic Zeeman coupling. This phenomenon
is closely related to the Shapiro steps in superconducting Josephson junctions,
and the previous experimental work [Evrard $et al.,$ Phys. Rev. A 100, 023604
(2019)] for a spin-1 bosonic system observed the resonant dynamics and then
called it Shapiro resonance. In this work, using the spin-1 Gross-Pitaevskii
equation, we study the Shapiro resonance beyond the single-mode approximation
used in the previous work, which assumes that all components of the spinor
wavefunction have the same spatial configuration. Considering resonant dynamics
starting from a polar state, we analytically calculate the Floquet-Lyapunov
exponents featuring an onset of the resonance under a linear analysis and find
that spin waves with finite wavenumbers can be excited. This kind of
non-uniform excitation cannot be described by the single-mode approximation.
Furthermore, to study the long-time resonant dynamics beyond the linear
analysis, we numerically solve the one-dimensional spin-1 Gross-Pitaevskii
equation, finding that the nonresonant hydrodynamic variables also grow at
wavelengths of even multiples of the resonant one due to the nonlinear effect.


  In this paper, we consider a new variant for principal component analysis
(PCA), aiming to capture the grouping and/or sparse structures of factor
loadings simultaneously. To achieve these goals, we employ a non-convex
truncated regularization with naturally adjustable sparsity and grouping
effects, and propose the Feature Grouping and Sparse Principal Component
Analysis (FGSPCA). The proposed FGSPCA method encourages the factor loadings
with similar values to collapse into disjoint homogeneous groups for feature
grouping or into a special zero-valued group for feature selection, which in
turn helps reducing model complexity and increasing model interpretation.
Usually, existing structured PCA methods require prior knowledge to construct
the regularization term. However, the proposed FGSPCA can simultaneously
capture the grouping and/or sparse structures of factor loadings without any
prior information. To solve the resulting non-convex optimization problem, we
propose an alternating algorithm that incorporates the difference-of-convex
programming, augmented Lagrange method and coordinate descent method.
Experimental results demonstrate the promising performance and efficiency of
the new method on both synthetic and real-world datasets. An R implementation
of FGSPCA can be found on github {https://github.com/higeeks/FGSPCA}.


  We construct optimal PPTES witnesses to detect $3\otimes 3$ PPT entangled
edge states of type $(6,8)$ constructed recently \cite{kye_osaka}. To do this,
we consider positive linear maps which are variants of the Choi type map
involving complex numbers, and examine several notions related to optimality
for those entanglement witnesses. Through the discussion, we suggest a method
to check the optimality of entanglement witnesses without the spanning
property.


  We show generalized Galileons -- a particular subclass of Horndeski gravity
-- arise from a consistent Kaluza-Klein reduction of the low-energy effective
action of heterotic string theory to first order in $\alpha'$. This suggests
Horndeski theories of gravity have a string-theoretic origin. The form of the
Galileonic terms is precisely fixed by parameters of the embedding spacetime,
so that only a specific subset of Horndeski theories is permitted by string
theory. A novel limit of the model is considered by performing a dimensionful
rescaling of $\alpha'$.


  We present an example of a highly connected closed network of servers, where
the time correlations do not go to zero in the infinite volume limit. This
phenomenon is similar to the continuous symmetry breaking at low temperatures
in statistical mechanics. The role of the inverse temperature is played by the
average load.


  Among the lines of evidence for a buried ocean on Titan is the possible
detection, in 2005, by the Permittivity, Wave and Altimetry (PWA) analyzer on
board the ESA Huygens probe of Schumann-like Resonances (SR). SR are Extremely
Low Frequency electromagnetic waves resonating between two electrically
conductive layers. On Titan, it has been proposed that they propagate between
the moon's ionosphere and a salty subsurface water ocean. Their
characterization by electric field sensors can provide constraints on Titan's
cavity characteristics and in particular on the depth of Titan's ocean which is
key to better assess Titan's habitability. For this work we have developed a
numerical model of Titan's electromagnetic cavity as well as a surrogate model
to conduct simulations and sensitivity analyses at a low computational cost.
This surrogate model is used both to re-assess PWA/Huygens measurements and to
predict the future performance of the EFIELD experiment on board the NASA
Dragonfly mission. We demonstrate that the PWA/Huygens measurements, in
particular due to their low spectral resolution, do not bring any meaningful
constraint on Titan's ocean depth. On the other hand, the finer resolution of
the EFIELD experiment and its ability to capture several harmonics of SR should
provide more robust constraints on Titan's internal structure, especially if
the electrical properties of the ice crust and the atmosphere can be better
constrained.


  In common relativistic models of gravitational collapse, the interior
experiences a bubble-like local inflation, allowing radii to diverge rather
than converge toward a singularity. This proves a conjecture of Shatskiy. At
the horizon, the solution locally resembles the neck of a wormhole from the
exterior to the interior. The implied limiting curvature is at the horizon not
the Planck level.


  Transfer function design is crucial in volume rendering, as it directly
influences the visual representation and interpretation of volumetric data.
However, creating effective transfer functions that align with users' visual
objectives is often challenging due to the complex parameter space and the
semantic gap between transfer function values and features of interest within
the volume. In this work, we propose a novel approach that leverages recent
advancements in language-vision models to bridge this semantic gap. By
employing a fully differentiable rendering pipeline and an image-based loss
function guided by language descriptions, our method generates transfer
functions that yield volume-rendered images closely matching the user's intent.
We demonstrate the effectiveness of our approach in creating meaningful
transfer functions from simple descriptions, empowering users to intuitively
express their desired visual outcomes with minimal effort. This advancement
streamlines the transfer function design process and makes volume rendering
more accessible to a wider range of users.


  Tensor processing units (TPUs), specialized hardware accelerators for machine
learning tasks, have shown significant performance improvements when executing
convolutional layers in convolutional neural networks (CNNs). However, they
struggle to maintain the same efficiency in fully connected (FC) layers,
leading to suboptimal hardware utilization. In-memory analog computing (IMAC)
architectures, on the other hand, have demonstrated notable speedup in
executing FC layers. This paper introduces a novel, heterogeneous,
mixed-signal, and mixed-precision architecture that integrates an IMAC unit
with an edge TPU to enhance mobile CNN performance. To leverage the strengths
of TPUs for convolutional layers and IMAC circuits for dense layers, we propose
a unified learning algorithm that incorporates mixed-precision training
techniques to mitigate potential accuracy drops when deploying models on the
TPU-IMAC architecture. The simulations demonstrate that the TPU-IMAC
configuration achieves up to $2.59\times$ performance improvements, and $88\%$
memory reductions compared to conventional TPU architectures for various CNN
models while maintaining comparable accuracy. The TPU-IMAC architecture shows
potential for various applications where energy efficiency and high performance
are essential, such as edge computing and real-time processing in mobile
devices. The unified training algorithm and the integration of IMAC and TPU
architectures contribute to the potential impact of this research on the
broader machine learning landscape.


  We study the following coupled Schr\"{o}dinger equations which have appeared
as several models from mathematical physics: {displaymath} {cases}-\Delta u_1
+\la_1 u_1 = \mu_1 u_1^3+\beta u_1 u_2^2, \quad x\in \Omega, -\Delta u_2 +\la_2
u_2 =\mu_2 u_2^3+\beta u_1^2 u_2, \quad x\in \Om, u_1=u_2=0 \,\,\,\hbox{on
\,$\partial\Om$}.{cases}{displaymath} Here $\Om$ is a smooth bounded domain in
$\R^N (N=2, 3)$ or $\Om=\RN$, $\la_1,\, \la_2$, $\mu_1,\,\mu_2$ are all
positive constants and the coupling constant $\bb<0$. We show that this system
has infinitely many sign-changing solutions. We also obtain infinitely many
semi-nodal solutions in the following sense: one component changes sign and the
other one is positive. The crucial idea of our proof, which has never been used
for this system before, is turning to study a new problem with two constraints.
Finally, when $\Om$ is a bounded domain, we show that this system has a least
energy sign-changing solution, both two components of which have exactly two
nodal domains, and we also study the asymptotic behavior of solutions as
$\beta\to -\infty$ and phase separation is expected.


  Physical interaction between individuals plays an important role in human
motor learning and performance during shared tasks. Using robotic devices,
researchers have studied the effects of dyadic haptic interaction mostly
focusing on the upper-limb. Developing infrastructure that enables physical
interactions between multiple individuals' lower limbs can extend the previous
work and facilitate investigation of new dyadic lower-limb rehabilitation
schemes.
  We designed a system to render haptic interactions between two users while
they walk in multi-joint lower-limb exoskeletons. Specifically, we developed an
infrastructure where desired interaction torques are commanded to the
individual lower-limb exoskeletons based on the users' kinematics and the
properties of the virtual coupling. In this pilot study, we demonstrated the
capacity of the platform to render different haptic properties (e.g., soft and
hard), different haptic connection types (e.g., bidirectional and
unidirectional), and connections expressed in joint space and in task space.
With haptic connection, dyads generated synchronized movement, and the
difference between joint angles decreased as the virtual stiffness increased.
This is the first study where multi-joint dyadic haptic interactions are
created between lower-limb exoskeletons. This platform will be used to
investigate effects of haptic interaction on motor learning and task
performance during walking, a complex and meaningful task for gait
rehabilitation.


  Food choice is a complex phenomenon shaped by factors such as taste,
ambience, culture or weather. In this paper, we explore food-related tweeting
in different weather conditions. We inspect a Latvian food tweet dataset
spanning the past decade in conjunction with a weather observation dataset
consisting of average temperature, precipitation, and other phenomena. We find
which weather conditions lead to specific food information sharing;
automatically classify tweet sentiment and discuss how it changes depending on
the weather. This research contributes to the growing area of large-scale
social network data understanding of food consumers' choices and perceptions.


  The study of the acceleration of particles is an essential element of
research in the heliospheric science. Here, we discuss the predisposition to
the particle acceleration around coronal mass ejections (CMEs)-driven shocks
with corrugated wave-like features. We adopt these attributes on shocks formed
from disturbances due to the bimodal solar wind, CME deflection, irregular CME
expansion, and the ubiquitous fluctuations in the solar corona. In order to
understand the role of a wavy shock in particle acceleration, we define three
initial smooth shock morphologies each one associated with a fast CME. Using
polar Gaussian profiles we model these shocks in the low corona. We establish
the corrugated appearance on smooth shock by using combinations of wave-like
functions that represent the disturbances from medium and CME piston. For both
shock types, smooth and corrugated, we calculate the shock normal angles
between the shock normal and the radial upstream coronal magnetic field in
order to classify the quasi-parallel and quasi-perpendicular regions. We
consider that corrugated shocks are predisposed to different process of
particle acceleration due to irregular distributions of shock normal angles
around of the shock. We suggest that disturbances due to CME irregular
expansion may be a decisive factor in origin of particle acceleration. Finally,
we regard that accepting these features on shocks may be the start point for
investigating some questions in the sheath and shock, like downstream-jets,
instabilities, shock thermalization, shock stability, and injection particle
process.


  We characterize geometrically the semigroups generated by non-selfadjoint
quadratic differential operators $(e^{-tq^w})_{t\geq 0}$ enjoying local
smoothing effects and providing gains of integrability. More precisely, we
prove that the evolution operators $e^{-tq^w}$ map $L^{\mathfrak{p}}$ on
$L^{\mathfrak{q}} \cap C^\infty$, for all $1\leq \mathfrak{p} \leq \mathfrak{q}
\leq \infty$, if and only if the singular space of the quadratic operator $q^w$
is included in the graph of a linear map. We also provide quantitative
estimates for the associated operator norms in the short-time asymptotics $0<t
\ll 1$.