  We show that, if P\not=NP, there is a constant c > 1 such that there is no
c-approximation algorithm for the crossing number, even when restricted to
3-regular graphs.


  We review a possible non-minimal coupling (dilatonic) of a scalar field
(axion like particle) to electromagnetism, through experimental and
observational constraints. Such a coupling is motivated from recent quasar
spectrum observations that indicate a possible spatial and/or temporal
variation of the fine-structure constant. We consider a dilatonic coupling of
the form $B_F (\phi) = 1 + g\phi$. The strongest bound on the coupling
parameter $g$ is derived from weak equivalence principle tests, which impose $g
< 1.6 \times 10^{-17}GeV^{-1}$. This constraint is strong enough to rule out
this class of models as a cause for an observable cosmological variation of the
fine structure constant unless a chameleon mechanism is implemented. Also, we
argue that a similar coupling occurs in chameleon cosmology, another candidate
dark mater particle and we estimate the cosmological consequences by both
effects. It should be clarified that this class of models is not necessarily
ruled out in the presence of a chameleon mechanism which can freeze the
dynamics of the scalar field in high density laboratory regions.


  The (k,d)-hypersimplex is a (d-1)-dimensional polytope whose vertices are the
(0,1)-vectors that sum to k. When k=1, we get a simplex whose graph is the
complete graph with d vertices. Here we show how many of the well known graph
parameters and attributes of the complete graph extend to a more general case.
In particular we obtain explicit formulas in terms of d and k for the number of
vertices, vertex degree, number of edges and the diameter. We show that the
graphs are vertex transitive, hamilton connected, obtain the clique number and
show how the graphs can be decomposed into self-similar subgraphs. The paper
concludes with a discussion of the edge expansion rate of the graph of a
(k,d)-hypersimplex which we show is at least d/2, and how this graph can be
used to generate a random subset of {1,2,3,...,d} with k elements.


  We study theoretically the out-of-equilibrium transport properties of a
double quantum dot system in the Kondo regime. We model the system by means of
a two-impurity Anderson Hamiltonian. The transport properties are characterized
by Kondo effect properties, however, superimposed them, the system possesses
novel non-linear bistability behavior.


  It has been known for some time that the classical concept of radiation is
not covariant: for uniformly accelerated particles, it depends on the state of
motion of the observer relative to the particle emitting it. Moreover, recent
literature in the field of Quantum Field Theory in Curved Spacetimes suggests a
deep connection between bremsstrahlung and the Unruh effect, where zero-Rindler
energy particles have played a central role beyond constructing the radiation
contents of systems; as this is an unfamiliar concept, it seems unsettling to
deal with particles having no energy. This thesis studies such a connection in
both the classical and quantum perspectives, showing how the quantum Unruh
effect is responsible for the classical radiation detected for the electric and
gravitational cases, and studies the role of zero-Rindler-energy particles and
how they relate to the radiative field of uniformly accelerated particles.


  The classical Perron-Frobenius theory asserts that for two matrices $A$ and
$B$, if $0\leq B \leq A$ and $r(A)=r(B)$ with $A$ being irreducible, then
$A=B$. This was recently extended in Bernik et al. (2012) to positive operators
on $L_p(\mu)$ with either $A$ or $B$ being irreducible and power compact. In
this paper, we extend the results to irreducible operators on arbitrary Banach
lattices.


  In this paper, multiwavelength observations of remote coronal dimmings
related to an M1.1 circular-ribbon flare (CRF) in active region (AR) 12434 are
reported. The confined flare without a CME was observed by AIA and HMI on board
SDO on 2015 October 16. Global three-dimensional (3D) magnetic fields before
flare were obtained using the potential field source surface modeling. A few
minutes before the flare hard X-ray peak time (06:13:48 UT), small-scale, weak
dimming appeared $\sim$240$\arcsec$ away from the flare site, which can be
observed by AIA only in 131 and 171 {\AA}. Afterwards, long and narrow dimmings
became evident in all AIA EUV passbands except 304 {\AA}, while localized core
dimming was not clearly observed near the flare site. The large-area dimmings
extended southeastward and the areas increased gradually. The total area of
dimmings reaches (1.2$\pm0.4$)$\times$10$^4$ Mm$^2$ in 193 {\AA}. The maximal
relative intensity decreases in 171 and 193 {\AA} reach 90\% and 80\%,
respectively. Subsequently, the dimmings began to replenish and the area
decreased slowly, lasting for $\geq$3 hr. The remote dimmings and AR 12434 were
connected by large-scale coronal loops. The remote dimmings were associated
with the southwest footpoints of coronal loops with weak negative polarities.
Possible origins of remote dimmings are discussed.


  To simulate the dynamics of massless Dirac fermions in curved spacetimes with
one, two, and three spatial dimensions we construct tight-binding Hamiltonians
with spatially varying hoppings. These models represent tilted Weyl semimetals
where the tilting varies with position, in a manner similar to the light cones
near the horizon of a black hole. We illustrate the gravitational analogies in
these models by numerically evaluating the propagation of wave packets on the
lattice and then comparing them to the geodesics of the corresponding curved
spacetime. We also show that the motion of electrons in these spatially varying
systems can be understood through the conservation of energy and the
quasi-conservation of quasimomentum. This picture is confirmed by calculations
of the scattering matrix, which indicate an exponential suppression of any
noncontinuous change in the quasimomentum. Finally, we show that horizons in
the lattice models can be constructed also at finite energies using specially
designed tilting profiles.


  We prove the computational weakness of a model of tile assembly that has so
far resisted many attempts of formal analysis or positive constructions.
Specifically, we prove that, in Winfree's abstract Tile Assembly Model, when
restricted to use only noncooperative bindings, any long enough path that can
grow in all terminal assemblies is pumpable, meaning that this path can be
extended into an infinite, ultimately periodic path.
  This result can be seen as a geometric generalization of the pumping lemma of
finite state automata, and closes the question of what can be computed
deterministically in this model. Moreover, this question has motivated the
development of a new method called visible glues. We believe that this method
can also be used to tackle other long-standing problems in computational
geometry, in relation for instance with self-avoiding paths.
  Tile assembly (including non-cooperative tile assembly) was originally
introduced by Winfree and Rothemund in STOC 2000 to understand how to program
shapes. The non-cooperative variant, also known as temperature 1 tile assembly,
is the model where tiles are allowed to bind as soon as they match on one side,
whereas in cooperative tile assembly, some tiles need to match on several sides
in order to bind. In this work, we prove that only very simple shapes can
indeed be programmed, whereas exactly one known result (SODA 2014) showed a
restriction on the assemblies general non-cooperative self-assembly could
achieve, without any implication on its computational expressiveness. With
non-square tiles (like polyominos, SODA 2015), other recent works have shown
that the model quickly becomes computationally powerful.


  Representations of four dimensional superconformal groups are constructed as
fields on many different superspaces, including super Minkowski space, chiral
superspace, harmonic superspace and analytic superspace. Any unitary
irreducible representation can be given as a field on any one of these spaces
if we include fields which transform under supergroups. In particular, on
analytic superspaces, the fields are unconstrained. One can obtain all
representations of the N=4 complex superconformal group $PSL(4|4)$ with integer
dilation weight from copies of the Maxwell multiplet on $(4,2,2)$ analytic
superspace. This construction is compared with the oscillator construction and
it is shown that there is a natural correspondence between the oscillator
construction of superconformal representations and those carried by superfields
on analytic superspace.


  This volume contains the proceedings of the Sixth International Symposium on
Games, Automata, Logic and Formal Verification (GandALF 2015). The symposium
took place in Genoa, Italy, on the 21st and 22nd of September 2015. The
proceedings of the symposium contain the abstracts of three invited talks and
13 papers that were accepted after a careful evaluation for presentation at the
conference. The topics of the accepted papers cover algorithmic game theory,
automata theory, formal verification, and modal and temporal logics.


  Scene text retrieval aims to localize and search all text instances from an
image gallery, which are the same or similar to a given query text. Such a task
is usually realized by matching a query text to the recognized words, outputted
by an end-to-end scene text spotter. In this paper, we address this problem by
directly learning a cross-modal similarity between a query text and each text
instance from natural images. Specifically, we establish an end-to-end
trainable network, jointly optimizing the procedures of scene text detection
and cross-modal similarity learning. In this way, scene text retrieval can be
simply performed by ranking the detected text instances with the learned
similarity. Experiments on three benchmark datasets demonstrate our method
consistently outperforms the state-of-the-art scene text spotting/retrieval
approaches. In particular, the proposed framework of joint detection and
similarity learning achieves significantly better performance than separated
methods. Code is available at: https://github.com/lanfeng4659/STR-TDSL.


  Abstract It is shown that electrostatic plasma wakefields can efficiently
radiate at harmonics of the plasma frequency when the plasma has a positive
density gradient along the propagation direction of a driver. The driver
propagating at a sub-luminal group velocity excites the plasma wakefield with
the same phase velocity. However, due to the positive density gradient, the
wake phase velocity steadily increases behind the driver. As soon as the phase
velocity becomes super-luminal, the electrostatic wakefield couples efficiently
to radiative electromagnetic modes. The period of time when the phase velocity
stays above the speed of light depends on the density gradient scale length.
The wake radiates at harmonics of the plasma frequency in the teraherz (THz)
band. The angle of emission depends on the gradient scale and the time passed
behind the driver. For appropriate plasma and driver parameters, the wake can
radiate away nearly all its energy, which potentially results in an efficient,
narrow band and tunable source of THz radiation.


  We study geometrically thick and non-self gravitating equilibrium tori
orbiting a static spherically symmetric dyonic black hole with
quasi-topological electromagnetism. Our results show that the electric and
magnetic charges together with the coupling parameter in the quasi-topological
electromagnetism lead to a much richer class of equilibrium tori. There are a
range of parameters which allow for the existence of double tori. The
properties of double equilibrium tori become far richer. There exist
transitions between single torus and double tori solutions as we change the
specific angular momentum of the fluid. These properties of equilibrium tori
could help to understand the dyonic black hole and its thick accretion disk.


  The observation of the hot gas surrounding Sgr $A^*$ and a few other nearby
galactic nuclei imply that electron and proton mean free paths are comparable
to the gas capture radius. So, the hot accretion flows is likely to proceed
under week-collision conditions. Hence, thermal conduction has been suggested
as a possible mechanism by which the sufficient extra heating is provided in
hot ADAF accretion disks. We consider the effects of thermal conduction in the
presence of a toroidal magnetic field in an advection-dominated accretion flow
around a compact object. For a steady-state structure of such accretion flows a
set of self-similar solutions are presented. We find two types solutions which
represent high and slow accretion rate. They have different behaviors with
saturated thermal conduction parameter, $\phi$.


  It is well known that the $(-1)$-evaluation of the enumerator polynomials of
permutations (resp. derangements) by the number of excedances gives rise to
tangent numbers (resp. secant numbers). Recently, two distinct $q$-analogues of
the latter result have been discovered by Foata and Han, and Josuat-Verg\`es,
respectively. In this paper, we will prove some general continued fractions
expansions formulae, which permits us to give a unified treatment of
Josuat-Verg\`es' two formulae and also to derive a new $q$-analogue of the
aforementioned formulae. Our approach is based on a $(p,q)$-analogue of tangent
and secant numbers via continued fractions and also the generating function of
permutations with respect to the quintuple statistic consisting of fixed point
number, weak excedance number, crossing number, nesting number and inversion
number. We also give a combinatorial proof of Josuat-Verg\`es' formulae by
using a new linear model of derangements.


  Magnetic Resonance Spectroscopic Imaging (MRSI) is an essential tool for
quantifying metabolites in the body, but the low spatial resolution limits its
clinical applications. Deep learning-based super-resolution methods provided
promising results for improving the spatial resolution of MRSI, but the
super-resolved images are often blurry compared to the experimentally-acquired
high-resolution images. Attempts have been made with the generative adversarial
networks to improve the image visual quality. In this work, we consider another
type of generative model, the flow-based model, of which the training is more
stable and interpretable compared to the adversarial networks. Specifically, we
propose a flow-based enhancer network to improve the visual quality of
super-resolution MRSI. Different from previous flow-based models, our enhancer
network incorporates anatomical information from additional image modalities
(MRI) and uses a learnable base distribution. In addition, we impose a guide
loss and a data-consistency loss to encourage the network to generate images
with high visual quality while maintaining high fidelity. Experiments on a
1H-MRSI dataset acquired from 25 high-grade glioma patients indicate that our
enhancer network outperforms the adversarial networks and the baseline
flow-based methods. Our method also allows visual quality adjustment and
uncertainty estimation.


  The level $2$ mapping class group of an orientable closed surface can be
generated by squares of Dehn twists about non-separating curves. On the other
hand, the level $2$ mapping class group $\mathcal{M}_2(N_g)$ of a
non-orientable closed surface $N_g$ can not be generated by only Dehn twists,
and so it can not be generated by squares of Dehn twists about non-separating
curves. In this paper, we prove that the Dehn twist subgroup of
$\mathcal{M}_2(N_g)$ can not be generated by squares of Dehn twists about
non-separating curves either. As an application, we give a finite generating
set for the subgroup of $\mathcal{M}_2(N_g)$ generated by Dehn twist about
separating curves and squares of Dehn twists about non-separating curves.
Moreover, we examine about actions on non-separating simple closed curves of
$N_g$ by $\mathcal{M}_2(N_g)$.


  A major challenge for any theory of quantum gravity is to quantize general
relativity while retaining some part of its geometrical character. We present
new evidence for the idea that this can be achieved by directly quantizing
space itself. We compute the Bohr-Sommerfeld volume spectrum of a tetrahedron
and show that it reproduces the quantization of a grain of space found in loop
gravity.


  We demonstrate a technique for performing stochastic simulations of
conditional master equations. The method is scalable for many quantum-field
problems and therefore allows first-principles simulations of multimode bosonic
fields undergoing continuous measurement, such as those controlled by
measurement-based feedback. As examples, we demonstrate a 53-fold speed
increase for the simulation of the feedback cooling of a single trapped
particle, and the feedback cooling of a quantum field with 32 modes, which
would be impractical using previous brute force methods.


  Cosmological hydrogen recombination has recently been the subject of renewed
attention because of its importance for predicting the power spectrum of cosmic
microwave background anisotropies. It has become clear that it is necessary to
account for a large number n >~ 100 of energy shells of the hydrogen atom,
separately following the angular momentum substates in order to obtain
sufficiently accurate recombination histories. However, the multi-level atom
codes that follow the populations of all these levels are computationally
expensive, limiting recent analyses to only a few points in parameter space. In
this paper, we present a new method for solving the multi-level atom
recombination problem, which splits the problem into a computationally
expensive atomic physics component that is independent of the cosmology, and an
ultrafast cosmological evolution component. The atomic physics component
follows the network of bound-bound and bound-free transitions among excited
states and computes the resulting effective transition rates for the small set
of "interface" states radiatively connected to the ground state. The
cosmological evolution component only follows the populations of the interface
states. By pre-tabulating the effective rates, we can reduce the recurring cost
of multi-level atom calculations by more than 5 orders of magnitude. The
resulting code is fast enough for inclusion in Markov Chain Monte Carlo
parameter estimation algorithms. It does not yet include the radiative transfer
or high-n two-photon processes considered in some recent papers. Further work
on analytic treatments for these effects will be required in order to produce a
recombination code usable for Planck data analysis.


  The clumpy disc, or inhomogeneous accretion flow, has been proposed to
explain the properties of accreting black hole systems. However, the
observational evidences remain to be explored. In this work, we calculate the
profiles of Fe K{\alpha} lines emitted from the inhomogeneous accretion flow
through the ray-tracing technique, in order to find possible observable signals
of the clumps. Compared with the skewed doublepeaked profile of the continuous
standard accretion disc, the lines show a multi-peak structure when the
emissivity index is not very steep. The peaks and wings are affected by the
position and size of the cold clumps. When the clump is small and is located in
the innermost region, due to the significant gravitational redshift, the blue
wing can overlap with the red wing of the outer cold disc/clump, forming a fake
peak or greatly enhancing the red peak. Given high enough resolution, it is
easier to constrain the clumps around the supermassive black holes than the
clumps in stellar mass black holes due to the thermal Doppler effect.


  A significant fraction of main-sequence stars are encircled by dusty debris
discs, where the short-lived dust particles are replenished through collisions
between planetesimals. Most destructive collisions occur when the orbits of
smaller bodies are dynamically stirred up, either by the gravitational effect
of locally formed Pluto-sized planetesimals (self-stirring scenario), or via
secular perturbation caused by an inner giant planet (planetary stirring). The
relative importance of these scenarios in debris systems is unknown. Here we
present new Herschel Space Observatory imagery of 11 discs selected from the
most massive and extended known debris systems. All discs were found to be
extended at far-infrared wavelengths, five of them being resolved for the first
time. We evaluated the feasibility of the self-stirring scenario by comparing
the measured disc sizes with the predictions of the model calculated for the
ages of our targets. We concluded that the self-stirring explanation works for
seven discs. However, in four cases, the predicted pace of outward propagation
of the stirring front, assuming reasonable initial disc masses, was far too low
to explain the radial extent of the cold dust. Therefore, for HD 9672, HD
16743, HD 21997, and HD 95086, another explanation is needed. We performed a
similar analysis for {\ss} Pic and HR 8799, reaching the same conclusion. We
argue that planetary stirring is a promising possibility to explain the disk
properties in these systems. In HR 8799 and HD 95086 we may already know the
potential perturber, since their known outer giant planets could be responsible
for the stirring process. Our study demonstrates that among the largest and
most massive debris discs self-stirring may not be the only active scenario,
and potentially planetary stirring is responsible for destructive collisions
and debris dust production in a number of systems.


  We present a framework for designing efficient distributed data structures
for multi-dimensional data. Our structures, which we call skip-webs, extend and
improve previous randomized distributed data structures, including skipnets and
skip graphs. Our framework applies to a general class of data querying
scenarios, which include linear (one-dimensional) data, such as sorted sets, as
well as multi-dimensional data, such as d-dimensional octrees and digital tries
of character strings defined over a fixed alphabet. We show how to perform a
query over such a set of n items spread among n hosts using O(log n / log log
n) messages for one-dimensional data, or O(log n) messages for
fixed-dimensional data, while using only O(log n) space per host. We also show
how to make such structures dynamic so as to allow for insertions and deletions
in O(log n) messages for quadtrees, octrees, and digital tries, and O(log n /
log log n) messages for one-dimensional data. Finally, we show how to apply a
blocking strategy to skip-webs to further improve message complexity for
one-dimensional data when hosts can store more data.


  We present an exact analytical solution for a one-dimensional zigzag
waveguide array with first and second neighbor interactions. It is found that
the waveguide system possess a classical analog to the displaced squeezed
number states. The exact solution was compared directly with the numerical
solution showing a perfect agreement between both results. The implication of a
linear index of refraction changing as a function of the site number is also
studied. In this case, we show that the first neighbor interaction strongly
influences the periodicity of Bloch oscillations.


  We calculate the single-spin and double-spin asymmetry differential cross
sections for the polarized hadron scattering $PP \to l^+ l^- + jet$ up to
$O(\alpha_s)$ by the helicity amplitude method. Numerical results of the
differential cross sections, which can be used to probe the spin contents of
the proton, are obtained with several sets of polarized parton distribution
functions.


  A new class of rings, the class of left localizable rings, is introduced. A
ring $R$ is left localizable if each nonzero element of $R$ is invertible in
some left localization $S^{-1}R$ of the ring $R$. Explicit criteria are given
for a ring to be a left localizable ring provided the ring has only finitely
many maximal left denominator sets (eg, this is the case if a ring has a left
Artinian left quotient ring). It is proved that a ring with finitely many
maximal left denominator sets is a left localizable ring iff its left quotient
ring is a direct product of finitely many division rings. A characterization is
given of the class of rings that are finite direct product of left localization
maximal rings.


  Many modern machine learning classifiers are shown to be vulnerable to
adversarial perturbations of the instances. Despite a massive amount of work
focusing on making classifiers robust, the task seems quite challenging. In
this work, through a theoretical study, we investigate the adversarial risk and
robustness of classifiers and draw a connection to the well-known phenomenon of
concentration of measure in metric measure spaces. We show that if the metric
probability space of the test instance is concentrated, any classifier with
some initial constant error is inherently vulnerable to adversarial
perturbations.
  One class of concentrated metric probability spaces are the so-called Levy
families that include many natural distributions. In this special case, our
attacks only need to perturb the test instance by at most $O(\sqrt n)$ to make
it misclassified, where $n$ is the data dimension. Using our general result
about Levy instance spaces, we first recover as special case some of the
previously proved results about the existence of adversarial examples. However,
many more Levy families are known (e.g., product distribution under the Hamming
distance) for which we immediately obtain new attacks that find adversarial
examples of distance $O(\sqrt n)$.
  Finally, we show that concentration of measure for product spaces implies the
existence of forms of "poisoning" attacks in which the adversary tampers with
the training data with the goal of degrading the classifier. In particular, we
show that for any learning algorithm that uses $m$ training examples, there is
an adversary who can increase the probability of any "bad property" (e.g.,
failing on a particular test instance) that initially happens with
non-negligible probability to $\approx 1$ by substituting only $\tilde{O}(\sqrt
m)$ of the examples with other (still correctly labeled) examples.


  (abbreviated) In this paper we develop a consistent WKBJ formalism, together
with a formal first order perturbation theory for calculating the properties of
the inertial modes of a uniformly rotating coreless body (modelled as a
polytrope and referred hereafter to as a planet) under the assumption of a
spherically symmetric structure. The eigenfrequencies, spatial form of the
associated eigenfunctions and other properties we obtained analytically using
the WKBJ eigenfunctions are in good agreement with corresponding results
obtained by numerical means for a variety of planet models even for global
modes with a large scale distribution of perturbed quantities. This indicates
that even though they are embedded in a dense spectrum, such modes can be
identified and followed as model parameters changed and that first order
perturbation theory can be applied. This is used to estimate corrections to the
eigenfrequencies as a consequence of the anelastic approximation, which we
argue here to be small when the rotation frequency is small. These are compared
with simulation results in an accompanying paper with a good agreement between
theoretical and numerical results. The results reported here may provide a
basis of theoretical investigations of inertial waves in many astrophysical and
other applications, where a rotating body can be modelled as a uniformly
rotating barotropic object, for which the density has, close to its surface, an
approximately power law dependence on distance from the surface.


  We consider two classes of linear kinetic equations: with constant collision
frequency and constant mean free path of gas molecules (i.e., frequency of
molecular collisions, proportional to the modulus molecular velocity). Based
homogeneous Riemann boundary value problem with a coefficient equal to the
ratio of the boundary values dispersion function, develops the theory of the
half-space orthogonality of generalized singular eigenfunctions corresponding
characteristic equations, which leads separation of variables. And in this two
boundary value problems of the kinetic theory (diffusion light component of a
binary gas and Kramers problem about isothermal slip) shows the application of
the theory orthogonality eigenfunctions for analytical solutions these tasks.


  People's daily activities in the urban environment are complex and vary by
individuals. Existing studies using mobile phone data revealed distinct and
recurrent transitional activity patterns, known as mobility motifs, in people's
daily lives. However, the limitation in using only a few inferred activity
types hinders our ability to examine general patterns in detail. We proposed a
mobility network approach with geographic context-aware Twitter data to
investigate granular daily activity patterns in the urban environment. We first
utilized publicly accessible geo-located tweets to track the movements of
individuals in two major U.S. cities: Chicago and Greater Boston, where each
recorded location is associated with its closest land use parcel to enrich its
geographic context. A direct mobility network represents the daily location
history of the selected active users, where the nodes are physical places with
semantically labeled activity types, and the edges represent the transitions.
Analyzing the isomorphic structure of the mobility networks uncovered 16 types
of location-based motifs, which describe over 83% of the networks in both
cities and are comparable to those from previous studies. With detailed and
semantically labeled transitions between every two activities, we further
dissected the general location-based motifs into activity-based motifs, where
16 common activity-based motifs describe more than 57% transitional behaviors
in the daily activities in the two cities. The integration of geographic
context from the synthesis of geo-located Twitter data with land use parcels
enables us to reveal unique activity motifs that form the fundamental elements
embedded in complex urban activities.


  In collisionless and weakly collisional plasmas, such as hot accretion flows
onto compact objects, the magnetorotational instability (MRI) can differ
significantly from the standard (collisional) MRI. In particular, pressure
anisotropy with respect to the local magnetic-field direction can both change
the linear MRI dispersion relation and cause nonlinear modifications to the
mode structure and growth rate, even when the field and flow perturbations are
small. This work studies these pressure-anisotropy-induced nonlinearities in
the weakly nonlinear, high-ion-beta regime, before the MRI saturates into
strong turbulence. Our goal is to better understand how the saturation of the
MRI in a low collisionality plasma might differ from that in the collisional
regime. We focus on two key effects: (i) the direct impact of self-induced
pressure-anisotropy nonlinearities on the evolution of an MRI mode, and (ii)
the influence of pressure anisotropy on the "parasitic instabilities" that are
suspected to cause the mode to break up into turbulence. Our main conclusions
are: (i) The mirror instability regulates the pressure anisotropy in such a way
that the linear MRI in a collisionless plasma is an approximate nonlinear
solution once the mode amplitude becomes larger than the background field (just
as in MHD). This implies that differences between the collisionless and
collisional MRI become unimportant at large amplitudes. (ii) The break up of
large amplitude MRI modes into turbulence via parasitic instabilities is
similar in collisionless and collisional plasmas. Together, these conclusions
suggest that the route to magnetorotational turbulence in a collisionless
plasma may well be similar to that in a collisional plasma, as suggested by
recent kinetic simulations. As a supplement to these findings, we offer
guidance for the design of future kinetic simulations of magnetorotational
turbulence.


  We derive a priori interior Hessian estimates for semiconvex solutions to the
sigma-2 equation. An elusive Jacobi inequality, a transformation rule under the
Legendre-Lewy transform, and a mean value inequality for the still nonuniformly
elliptic equation without area structure are the key to our arguments.
Previously, this result was known for almost convex solutions.


  Finding large "cliquish" subgraphs is a classic NP-hard graph problem. In
this work, we focus on finding maximum $s$-clubs and $s$-plexes, i.e., graphs
of diameter $s$ and graphs where each vertex is adjacent to all but $s$
vertices. Preprocessing based on Turing kernelization is a standard tool to
tackle these problems, especially on sparse graphs. We provide a new
parameterized analysis for the Turing kernelization and demonstrate their
usefulness in practice. Moreover, we provide evidence that the new theoretical
bounds indeed better explain the observed running times than the existing
theoretical running time bounds. To this end, we suggest a general method to
compare how well theoretical running time bounds fit to measured running times.


  We consider a Branching Random Walk on $\R$ whose step size decreases by a
fixed factor, $0<b<1$, with each turn. This process generates a random
probability measure on $\R$, that is, the limit of uniform distribution among
the $2^n$ particles of the $n$-th step. We present an initial investigation of
the limit measure and its support. We show, in particular, that (1) for almost
every $b>1/2$ the limit measure is almost surely (a.s.) absolutely continuous
with respect to the Lebesgue measure, but for Pisot $1/b$ it is a.s. singular;
(2) for all $b > (\sqrt{5}-1)/2$ the support of the measure is a.s. the closure
of its interior; (3) for Pisot $1/b$ the support of the measure is
``fractured'': it is a.s. disconnected and the components of the complement are
not isolated on both sides.


  We study the maximum weight convex polytope problem, in which the goal is to
find a convex polytope maximizing the total weight of enclosed points. Prior to
this work, the only known result for this problem was an $O(n^3)$ algorithm for
the case of $2$ dimensions due to Bautista et al. We show that the problem
becomes $\mathcal{NP}$-hard to solve exactly in $3$ dimensions, and
$\mathcal{NP}$-hard to approximate within $n^{1/2-\epsilon}$ for any $\epsilon
> 0$ in $4$ or more dimensions. %\polyAPX-complete in $4$ dimensions even with
binary weights. We also give a new algorithm for $2$ dimensions, albeit with
the same $O(n^3)$ running time complexity as that of the algorithm of Bautsita
et al.


  Random Pulse Width Modulation (RPWM) has been successfully applied in power
electronics for nearly 30 years. The effects of the various possible RPWM
strategies on the Power Spectral Density have been thoroughly studied. Despite
the effectiveness of RPWM in spreading harmonic content, an appeal is
consistently made to maintain the textbook Pulse Width Modulation scheme 'on
average'. Random Switching (RS) does away with this notion and
probabilistically operates the switch. In addition to fulfilling several
optimality conditions, including being the only viable switching strategy at
the theoretical limit of performance and having lower switching losses than any
other RPWM; RS allows for design of the DC behaviour separately from that of
the PSD. The pulse amplitude probability affects the DC and total PSD. The
first and second moment of the pulse length probability distribution affects
the shape of the envelope of the noise of the PSD. The minimum pulse length
acts like a selective harmonic filter. The PSD can therefore be shaped without
external filtering by changing these probabilities. Gaussian and Huffman pulse
length probabilities are shown to be good choices depending on whether
real-time PSD control or spectrum usage are the design goal. In addition, it is
shown that C\'uk's state space averaging model applies to RS, with $D \to p$,
hence no new tools are needed to understand the low frequency behavior or
control performance. A benefit of closed loop random switching is that no
filtering of the controlled variable is required. Randomly responding in a
biased manner dependent on the error is hence shown to be useful. There are
several good reasons to consider RS for high performance applications.


  In this paper the interrelation between geomagnetic pulsations and variations
in frequency Doppler shift (Fd) of the ionosphere-reflected radio signal is
under investigation. The experiment on simultaneous recording of Fd variations
and geomagnetic pulsations was organised at high latitude station in Norilsk
(geomagnetic latitude and longitude 64.2 N, 160.4 E, L=5.3) during
Febrary-April of 1995-98. Thirty cases of simultaneous recording of duration
from 10 min to two hour were analysed: 6 cases of simultaneous recording of
variations Fd and regular geomagnetic pulsations Pc5; and 25 cases of recording
of Fd variations and irregular pulsations Pi2.
  On the basis of experimental results, the following conclusions have been
drawn: a) Hydromagnetic waves in the range of regular Pc5 pulsations, when
interacting with the ionospheric F2 layer, make the main contribution to
short-period Fd variations. The possible mechanism of Fd variations are
oscillations of electron density, associated with distribution of a
hydromagnetic wave in an ionosphere. b) There exists an unquestionable
interrelation between Fd variations of the sporadic E layer-reflected radio
signal and irregular Pi2 pulsations, but for some reasons it is traced poorly.


  An efficient third-order discrete unified gas kinetic scheme (DUGKS) with
efficiency is presented in this work for simulating continuum and rarefied
flows. By employing two-stage time-stepping scheme and the high-order DUGKS
flux reconstruction strategy, third-order of accuracy in both time and space
can be achieved in the present method. It is also analytically proven that the
second-order DUGKS is a special case of the present method. Compared with the
high-order lattice Boltzmann equation {LBE} based methods, the present method
is capable to deal with the rarefied flows by adopting the Newton-Cotes
quadrature to approximate the integrals of moments. Instead of being
constrained by the second-order (or lower-order) of accuracy in time splitting
scheme as in the conventional high-order Runge-Kutta (RK) based kinetic
methods, the present method solves the original BE, which overcomes the
limitation in time accuracy. Typical benchmark tests are carried out for
comprehensive evaluation of the present method. It is observed in the tests
that the present method is advantageous over the original DUGKS in accuracy and
capturing delicate flow structures. Moreover, the efficiency of the present
third-order method is also shown in simulating rarefied flows.


  We examine here the nature of the central singularity forming in the
spherically symmetric collapse of a dust cloud and it is shown that this is
always a strong curvature singularity where gravitational tidal forces diverge
powerfully. An important consequence is that the nature of the naked
singularity forming in the dust collapse turns out to be stable against the
perturbations in the initial data from which the collapse commences.


  ``Composable core-sets'' are an efficient framework for solving optimization
problems in massive data models. In this work, we consider efficient
construction of composable core-sets for the determinant maximization problem.
This can also be cast as the MAP inference task for determinantal point
processes, that have recently gained a lot of interest for modeling diversity
and fairness. The problem was recently studied in [IMOR'18], where they
designed composable core-sets with the optimal approximation bound of $\tilde
O(k)^k$. On the other hand, the more practical Greedy algorithm has been
previously used in similar contexts. In this work, first we provide a
theoretical approximation guarantee of $O(C^{k^2})$ for the Greedy algorithm in
the context of composable core-sets; Further, we propose to use a Local Search
based algorithm that while being still practical, achieves a nearly optimal
approximation bound of $O(k)^{2k}$; Finally, we implement all three algorithms
and show the effectiveness of our proposed algorithm on standard data sets.


  The innumerable shapes of plant leaves present a challenge to the explanatory
power of biophysical theory. A model is needed that can produce these shapes
with a small set of parameters. This paper presents a simple model of leaf
shape based on a growth algorithm, which governs the growth rate of leaf tissue
in two dimensions and hence the outline of the leaf. The growth of leaf lobes
is governed by the position of leaf veins. This model gives an approximation to
a wide variety of higher plant leaf shapes. The variation of leaf shapes found
in closely related plants is discussed in terms of variability in the growth
algorithms. The model can be extended to more complex leaf types.


  In this paper, we propose and analyze a mixed formulation for the
Kelvin-Voigt-Brinkman-Forchheimer equations for unsteady viscoelastic flows in
porous media. Besides the velocity and pressure, our approach introduces the
vorticity as a further unknown. Consequently, we obtain a three-field mixed
variational formulation, where the aforementioned variables are the main
unknowns of the system. We establish the existence and uniqueness of a solution
for the weak formulation, and derive the corresponding stability bounds,
employing a fixed-point strategy, along with monotone operators theory and
Schauder theorem. Afterwards, we introduce a semidiscrete continuous-in-time
approximation based on stable Stokes elements for the velocity and pressure,
and continuous piecewise polynomial spaces for the vorticity. Additionally,
employing backward Euler time discretization, we introduce a fully discrete
finite element scheme. We prove well-posedness, derive stability bounds, and
establish the corresponding error estimates for both schemes. We provide
several numerical results verifying the theoretical rates of convergence and
illustrating the performance and flexibility of the method for a range of
domain configurations and model parameters.


  The electron transport through the nanotube junctions which connect the
different metallic nanotubes by a pair of a pentagonal defect and a heptagonal
defect is investigated by Landauer's formula and the effective mass
approximation. From our previous calculations based on the tight binding model,
it has been known that the conductance is determined almost only by two
parameters,i.e., the energy in the unit of the onset energy of more than two
channels and the ratio of the radii of the two nanotubes. The conductance is
calculated again by the effective mass theory in this paper and a simple
analytical form of the conductance is obtained considering a special boundary
conditions of the envelop wavefunctions. The two scaling parameters appear
naturally in this treatment. The results by this formula coincide fairly well
with those of the tight binding model.
  The physical origin of the scaling law is clarified by this approach.


  Provenance is an increasing concern due to the ongoing revolution in sharing
and processing scientific data on the Web and in other computer systems. It is
proposed that many computer systems will need to become provenance-aware in
order to provide satisfactory accountability, reproducibility, and trust for
scientific or other high-value data. To date, there is not a consensus
concerning appropriate formal models or security properties for provenance. In
previous work, we introduced a formal framework for provenance security and
proposed formal definitions of properties called disclosure and obfuscation.
  In this article, we study refined notions of positive and negative disclosure
and obfuscation in a concrete setting, that of a general-purpose programing
language. Previous models of provenance have focused on special-purpose
languages such as workflows and database queries. We consider a higher-order,
functional language with sums, products, and recursive types and functions, and
equip it with a tracing semantics in which traces themselves can be replayed as
computations. We present an annotation-propagation framework that supports many
provenance views over traces, including standard forms of provenance studied
previously. We investigate some relationships among provenance views and
develop some partial solutions to the disclosure and obfuscation problems,
including correct algorithms for disclosure and positive obfuscation based on
trace slicing.


  We present the first smart phone tool that is capable of self-compilation,
mutation and viral spreading. Our autonomous app does not require a host
computer to alter its functionality, change its appearance and lacks the normal
necessity of a central app store to spread among hosts. We pioneered survival
skills for mobile software in order to overcome disrupted Internet access due
to natural disasters and human made interference, like Internet kill switches
or censored networks. Internet kill switches have proven to be an effective
tool to eradicate open Internet access and all forms of digital communication
within an hour on a country-wide basis. We present the first operational tool
that is capable of surviving such digital eradication.


  Owing to its true direct bandgap and tunable bandgap energies,GeSn alloys are
increasingly attractive as gain media for mid-IR lasers that can be
monolithically integrated on Si. Demonstrations of optically pumped GeSn laser
at room under pulsed condition and at cryogenic temperature under
continuous-wave excitation show great promise of GeSn lasers to be efficient
electrically injected light sources on Si. Here we report electrically injected
GeSn lasers using Fabry-Perot cavity with 20, 40, and 80 micron ridge widths. A
maximum operating temperature of 140 K with lasing threshold of 0.756 kA/cm2 at
77 K and emitting wavelength of 2722 nm at 140 K was obtained. The lower
threshold current density compared to previous works was achieved by reducing
optical loss and improving the optical confinement. The peak power was measured
as 2.2 mW/facet at 77 K.


  We present an empirical study of price reversion after the executed
metaorders. We use a data set with more than 8 million metaorders executed by
institutional investors in the US equity market. We show that relaxation takes
place as soon as the metaorder ends:{while at the end of the same day it is on
average $\approx 2/3$ of the peak impact, the decay continues the next days,
following a power-law function at short time scales, and converges to a
non-zero asymptotic value at long time scales (${\sim 50}$ days) equal to
$\approx 1/2$ of the impact at the end of the first day.} Due to a significant,
multiday correlation of the sign of executed metaorders, a careful
deconvolution of the \emph{observed} impact must be performed to extract the
estimate of the impact decay of isolated metaorders.


  We apply the Dynamical Mean Field (DMFT) approximation to the real, scalar
phi^4 quantum field theory. By comparing to lattice Monte Carlo calculations,
perturbation theory and standard mean field theory, we test the quality of the
approximation in two, three, four and five dimensions. The quantities
considered in these tests are the critical coupling for the transition to the
ordered phase and the associated critical exponents nu and beta. We also map
out the phase diagram in four dimensions. In two and three dimensions, DMFT
incorrectly predicts a first order phase transition for all bare quartic
couplings, which is problematic, because the second order nature of the phase
transition of lattice phi^4-theory is crucial for taking the continuum limit.
Nevertheless, by extrapolating the behaviour away from the phase transition,
one can obtain critical couplings and critical exponents. They differ from
those of mean field theory and are much closer to the correct values. In four
dimensions the transition is second order for small quartic couplings and turns
weakly first order as the coupling increases beyond a tricritical value. In
dimensions five and higher, DMFT gives qualitatively correct results, predicts
reasonable values for the critical exponents and considerably more accurate
critical couplings than standard mean field theory. The approximation works
best for small values of the quartic coupling. We investigate the change from
first to second order transition in the local limit of DMFT which is
computationally much less intensive. We also discuss technical issues related
to the convergence of the non-linear self-consistency equation solver and the
solution of the effective single-site model using Fourier-space Monte Carlo
updates in the presence of a phi^4-interaction.


  We consider asynchronous communication over point-to-point discrete
memoryless channels. The transmitter starts sending one block codeword at an
instant that is uniformly distributed within a certain time period, which
represents the level of asynchronism. The receiver, by means of a sequential
decoder, must isolate the message without knowing when the codeword
transmission starts but being cognizant of the asynchronism level A. We are
interested in how quickly can the receiver isolate the sent message,
particularly in the regime where A is exponentially larger than the codeword
length N, which we refer to as `strong asynchronism.'
  This model of sparse communication may represent the situation of a sensor
that remains idle most of the time and, only occasionally, transmits
information to a remote base station which needs to quickly take action.
  The first result shows that vanishing error probability can be guaranteed as
N tends to infinity while A grows as Exp(N*k) if and only if k does not exceed
the `synchronization threshold,' a constant that admits a simple closed form
expression, and is at least as large as the capacity of the synchronized
channel. The second result is the characterization of a set of achievable
strictly positive rates in the regime where A is exponential in N, and where
the rate is defined with respect to the expected delay between the time
information starts being emitted until the time the receiver makes a decision.
  As an application of the first result we consider antipodal signaling over a
Gaussian channel and derive a simple necessary condition between A, N, and SNR
for achieving reliable communication.


  We explore CO-CH4 quench kinetics in the atmospheres of substellar objects
using updated time-scale arguments, as suggested by a thermochemical kinetics
and diffusion model that transitions from the thermochemical-equilibrium regime
in the deep atmosphere to a quench-chemical regime at higher altitudes. More
specifically, we examine CO quench chemistry on the T dwarf Gliese 229B and CH4
quench chemistry on the hot-Jupiter HD 189733b. We describe a method for
correctly calculating reverse rate coefficients for chemical reactions, discuss
the predominant pathways for CO-CH4 interconversion as indicated by the model,
and demonstrate that a simple time-scale approach can be used to accurately
describe the behavior of quenched species when updated reaction kinetics and
mixing-length-scale assumptions are used. Proper treatment of quench kinetics
has important implications for estimates of molecular abundances and/or
vertical mixing rates in the atmospheres of substellar objects. Our model
results indicate significantly higher Kzz values than previously estimated near
the CO quench level on Gliese 229B, whereas current model-data comparisons
using CH4 permit a wide range of Kzz values on HD 189733b. We also use updated
reaction kinetics to revise previous estimates of the Jovian water abundance,
based upon the observed abundance and chemical behavior of carbon monoxide. The
CO chemical/observational constraint, along with Galileo entry probe data,
suggests a water abundance of approximately 0.51-2.6x solar (for a solar value
of H2O/H2=9.61E-04) in Jupiter's troposphere, assuming vertical mixing from the
deep atmosphere is the only source of tropospheric CO.


  Many biological and soft matter processes occur at high speeds in complex 3D
environments, and developing imaging techniques capable of elucidating their
dynamics is an outstanding experimental challenge. Here, we introduce Fourier
Synthesis Optical Diffraction Tomography (FS-ODT), a novel approach for
high-speed quantitative phase imaging capable of recording the 3D refractive
index at kilohertz rates. FS-ODT introduces new pattern generation and inverse
computational strategies that multiplex tens of illumination angles in a single
tomogram, dramatically increasing the volumetric imaging rate. We validate
FS-ODT performance by imaging samples of known composition and accurately
recovering the refractive index for increasing pattern complexity. We further
demonstrate the capabilities of FS-ODT for probing complex systems by studying
the hindered diffusion of colloids in solution and the motility of
single-cellular bacterial swimmers. We believe that FS-ODT is a promising
approach for unlocking challenging imaging regimes in biophysics and soft
matter that have been little explored, including understanding the physical
interactions of colloids and microswimmers with their viscous 3D environment
and the interplay between these stimuli and the molecular response of
biological systems.


  Much progress has been made recently on text classification with methods
based on neural networks. In particular, models using attention mechanism such
as BERT have shown to have the capability of capturing the contextual
information within a sentence or document. However, their ability of capturing
the global information about the vocabulary of a language is more limited. This
latter is the strength of Graph Convolutional Networks (GCN). In this paper, we
propose VGCN-BERT model which combines the capability of BERT with a Vocabulary
Graph Convolutional Network (VGCN). Local information and global information
interact through different layers of BERT, allowing them to influence mutually
and to build together a final representation for classification. In our
experiments on several text classification datasets, our approach outperforms
BERT and GCN alone, and achieve higher effectiveness than that reported in
previous studies.


  We first review the accelerating, rotating and charged Plebanski-Demianski
(PD) black hole, which includes the Kerr-Newman rotating black hole and the
Taub-NUT spacetime. The main feature of this black hole is that it has 4
horizons like event horizon, Cauchy horizon and two accelerating horizons. In
the non-extremal case, the surface area, entropy, surface gravity, temperature,
angular velocity, Komar energy and irreducible mass on the event horizon and
Cauchy horizon are presented for PD black hole. The entropy product,
temperature product, Komar energy product and irreducible mass product are
found for event horizon and Cauchy horizon. Also their sums are also found for
both horizons. All these relations are found to be depend on mass of the PD
black hole and other parameters. So all the products are not universal for PD
black hole. The entropy and area bounds for two horizons are investigated. Also
we found the Christodoulou-Ruffini mass for extremal PD black hole. Finally,
using first law of thermodynamics, we also found the Smarr relation for PD
black hole.


  In studying secondary gamma-ray emissions from Primordial Black Holes (PBHs),
the production of scalar particles like pions and axion-like particles (ALPs)
via Hawking radiation is crucial. While previous analyses assumed relativistic
production, asteroid-mass PBHs, relevant to upcoming experiments like AMEGO-X,
likely produce pions and ALPs non-relativistically when their masses exceed 10
MeV. To account for mass dependence in Hawking radiation, we revisit the
greybody factors for massive scalars from Schwarzschild black holes, revealing
significant mass corrections to particle production rates compared to the
projected AMEGO-X sensitivity. We highlight the importance of considering
non-relativistic $\pi^0$ production in interpreting PBH gamma-ray signals,
essential for determining PBH properties. Additionally, we comment on the
potential suppression of pion production due to form factor effects when
producing extended objects via Hawking radiation. We also provide an example
code for calculating the Hawking radiation spectrum of massive scalar
particles.


  Let $n$ and $m$ be positive integers such that $n<m$. In this paper we
compute the density of rectangular unimodular $n$ by $m$ matrices over the ring
of algebraic integers of a number field.


  We investigate the relationship between the spectral gap delta E_0 and the
localization length xi in general one-particle systems. A relationship for
many-body systems between the spectral gap and the exponential clustering has
been derived from the Lieb-Robinson bound, which reduces to the inequality xi
le const. times delta E_0^{-1} for one-particle systems. This inequality,
however, turned out not to be optimal qualitatively. As a refined upper bound,
we here prove the inequality xi le const. times delta E_0^{-1/2} in general
one-particle systems. Our proof is not based on the Lieb-Robinson bound, but on
our complementary inequality related to the uncertainty principle [T. Kuwahara,
J. Phys. A: Math. Theor. 46 (2013)]. We give a specific form of the upper bound
and test its tightness in the tight-binding Hamiltonian with a diagonal
impurity, where the localization length behaves as xi ~ delta E_0^{-1/2}. We
ensure that our upper bound is quantitatively tight in the case of
nearest-neighbor hopping.


  Noncentrosymmetric superconductors (NCSs) with broken inversion symmetry can
have spin-dependent order parameters (OPs) with mixed parity which can also
have nodes in the pair potential as well as the energy spectra. These nodes are
distinct features that are not present in conventional superconductors. They
appear as points or lines in the momentum space where the latter can have
angular or radial geometries dictated by the dimensionality, the lattice
structure and the pairing interaction.
  In this work we study the nodes in time reversal symmetry (TRS) preserving
NCSs at the OP, the pair potential, and the energy spectrum levels. Nodes are
examined by using spin independent pairing interactions respecting the
rotational $C_{\infty v}$ symmetry in the presence of spin-orbit coupling
(SOC). The pairing symmetries and the nodal topology are affected by the
relative strength of the pairing channels which is studied for the mixed
singlet-triplet, pure singlet, and pure triplet. Complementary to the angular
line nodes widely present in the literature, the $C_{\infty v}$ symmetry here
allows radial line nodes (RLNs) due to the nonlinear momentum dependence in the
OPs. The topology of the RLNs in the mixed case shows a distinctly different
characterization than the half-spin quantum vortex at the Dirac point. We apply
this NCS physics to the inversion symmetry broken exciton condensates (ECs) in
double quantum wells where the point and the RLNs can be found. On the other
hand, for a pure triplet condensate, two fully gapped and topologically
distinct regimes exist, separated by a QSHI-like zero energy superconducting
state with even number of Majorana modes. We also remark on how the point and
the RLNs can be manipulated, enabling an external control on the
topology.tions.


  Let $\xi$ be a L\'{e}vy process and $I_\xi(t):=\int_{0}^te^{-\xi_s}\mathrm{d}
s$, $t\geq 0,$ be the exponential functional of L\'{e}vy processes on
deterministic horizon. Given that $\lim_{t\to \infty}\xi_t=-\infty$ we evaluate
for general functions $F$ an upper bound on the rate of decay of
$\mathbb{E}\left(F(I_\xi(t))\right)$ based on an explicit integral criterion.
When $\mathbb{E}\left(\xi_1\right)\in\left(-\infty,0\right)$ and
$\mathbb{P}\left(\xi_1>t\right)$ is regularly varying of index $\alpha>1$ at
infinity, we show that the law of $I_\xi(t)$, suitably normed and rescaled,
converges weakly to a probability measure stemming from a new generalisation of
the product factorisation of classical exponential functionals. These results
substantially improve upon the existing literature and are obtained via a novel
combination between Mellin inversion of the Laplace transform of
$\mathbb{E}\left(I^{-a}_{\xi}(t)\mathbf{1}_{\left\{I_{\xi}(t)\leq
x\right\}}\right)$, $a\in (0,1)$, $x\in(0,\infty],$ and Tauberian theory
augmented for integer-valued $\alpha$ by a suitable application of the
one-large jump principle in the context of the de Haan theory. The methodology
rests upon the representation of the aforementioned Mellin transform in terms
of the recently introduced bivariate Bernstein-gamma functions for which we
develop the following new results of independent interest (for general $\xi$):
we link these functions to the $q$-potentials of $\xi$; we show that their
derivatives at zero are finite upon the finiteness of the aforementioned
integral criterion; we offer neat estimates of those derivatives along complex
lines. These results are useful in various applications of the exponential
functionals themselves and in different contexts where properties of bivariate
Bernstein-gamma functions are needed. $\xi$ need not be non-lattice.


  We consider the detection and initial guess problems for the LISA
gravitational wave detector. The detection problem is the problem of how to
determine if there is a signal present in instrumental data and how to identify
it. Because of the Doppler and plane-precession spreading of the spectral power
of the LISA signal, the usual power spectrum approach to detection will have
difficulty identifying sources. A better method must be found. The initial
guess problem involves how to generate {\it a priori} values for the parameters
of a parameter-estimation problem that are close enough to the final values for
a linear least-squares estimator to converge to the correct result. A useful
approach to simultaneously solving the detection and initial guess problems for
LISA is to divide the sky into many pixels and to demodulate the Doppler
spreading for each set of pixel coordinates. The demodulated power spectra may
then be searched for spectral features. We demonstrate that the procedure works
well as a first step in the search for gravitational waves from monochromatic
binaries.


  Voice controlled virtual assistants (VAs) are now available in smartphones,
cars, and standalone devices in homes. In most cases, the user needs to first
"wake-up" the VA by saying a particular word/phrase every time he or she wants
the VA to do something. Eliminating the need for saying the wake-up word for
every interaction could improve the user experience. This would require the VA
to have the capability to detect the speech that is being directed at it and
respond accordingly. In other words, the challenge is to distinguish between
system-directed and non-system-directed speech utterances. In this paper, we
present a number of neural network architectures for tackling this
classification problem based on using only acoustic features. These
architectures are based on using convolutional, recurrent and feed-forward
layers. In addition, we investigate the use of an attention mechanism applied
to the output of the convolutional and the recurrent layers. It is shown that
incorporating the proposed attention mechanism into the models always leads to
significant improvement in classification accuracy. The best model achieved
equal error rates of 16.25 and 15.62 percents on two distinct realistic
datasets.


  Unlike traditional programs (such as operating systems or word processors)
which have large amounts of code, machine learning tasks use programs with
relatively small amounts of code (written in machine learning libraries), but
voluminous amounts of data. Just like developers of traditional programs debug
errors in their code, developers of machine learning tasks debug and fix errors
in their data. However, algorithms and tools for debugging and fixing errors in
data are less common, when compared to their counterparts for detecting and
fixing errors in code. In this paper, we consider classification tasks where
errors in training data lead to misclassifications in test points, and propose
an automated method to find the root causes of such misclassifications. Our
root cause analysis is based on Pearl's theory of causation, and uses Pearl's
PS (Probability of Sufficiency) as a scoring metric. Our implementation, Psi,
encodes the computation of PS as a probabilistic program, and uses recent work
on probabilistic programs and transformations on probabilistic programs (along
with gray-box models of machine learning algorithms) to efficiently compute PS.
Psi is able to identify root causes of data errors in interesting data sets.


  Recent data on the differential angular distribution for the transfer
reaction $^{11}$Li(p,d)$^{10}$Li at $E/A=5.7$ MeV in inverse kinematics are
analysed within the DWBA reaction framework, using the overlap functions
calculated within a three-body model of $^{11}$Li. The weight of the different
$^{10}$Li configurations in the system's ground state is obtained from the
structure calculations unambiguously. The effect of the $^{9}$Li spin in the
calculated observables is also investigated. We find that, although all the
considered models succeed in reproducing the shape of the data, the magnitude
is very sensitive to the content of $p_{1/2}$ wave in the $^{11}$Li
ground-state wave function. Among the considered models, the best agreement
with the data is obtained when the $^{11}$Li ground state contains a $\sim$31\%
of $p_{1/2}$ wave in the $n$-$^9$Li subsystem. Although this model takes into
account explicitly the splitting of the $1^+$ and $2^+$ resonances due to the
coupling of the $p_{1/2}$ wave to the $3/2^-$ spin of the core, a similar
degree of agreement can be achieved with a model in which the $^{9}$Li spin is
ignored, provided that it contains a similar p-wave content.


  We consider an eigenvalue problem for a divergence form elliptic operator
$A_\epsilon$ with high contrast periodic coefficients with period $\epsilon$ in
each coordinate, where $\epsilon$ is a small parameter. The coefficients are
perturbed on a bounded domain of `order one' size. The local perturbation of
coefficients for such operator could result in emergence of localized waves -
eigenfunctions with corresponding eigenvalues lying in the gaps of the
Floquet-Bloch spectrum. We prove that, for the so-called double porosity type
scaling, the eigenfunctions decay exponentially at infinity, uniformly in
$\epsilon$. Then, using the tools of two-scale convergence for high contrast
homogenization, we prove the strong two-scale compactness of the eigenfunctions
of $A_\epsilon$. This implies that the eigenfunctions converge in the sense of
the strong two-scale convergence to the eigenfunctions of a two-scale limit
homogenized operator $A_0$, consequently establishing `asymptotic one-to-one
correspondence' between the eigenvalues and the eigenfunctions of these two
operators. We also prove by direct means the stability of the essential
spectrum of the homogenized operator with respect to the local perturbation of
its coefficients. That allows us to establish not only the strong two-scale
resolvent convergence of $A_\epsilon$ to $A_0$ but also the Hausdorff
convergence of the spectra of $A_\epsilon$ to the spectrum of $A_0$, preserving
the multiplicity of the isolated eigenvalues.


  Dynamics of a cluster of chaotic oscillators on a network are studied using
coupled maps. By introducing the association schemes, we obtain coupling
strength in the adjacency matrices form, which satisfies Markov matrices
property. We remark that in general, the stability region of the cluster of
oscillators at the synchronization state is characterized by Lyapunov exponent
which can be defined based on the N-coupled map. As a detailed physical
example, dynamics of microbubble cluster in an ultrasonic field are studied
using coupled maps. Microbubble cluster dynamics have an indicative highly
active nonlinear phenomenon, were not easy to be explained. In this paper, a
cluster of microbubbles with a thin elastic shell based on the modified
Keller-Herring equation in an ultrasonic field is demonstrated in the framework
of the globally coupled map. On the other hand, a relation between the
microbubble elements is replaced by a relation between the vertices. Based on
this method, the stability region of microbubbles pulsations at complete
synchronization state has been obtained analytically. In this way, distances
between microbubbles as coupling strength play the crucial role. In the
stability region, we thus observe that the problem of the study of dynamics of
N-microbubble oscillators reduce to that of a single microbubble. Therefore,
the important parameters of the isolated microbubble such as applied pressure,
driving frequency and the initial radius have effective behavior on the
synchronization state.


  36 single genes of six plants inferred 18 unique trees using maximum
parsimony. Such incongruence is an important issue and how to reconstruct the
congruent tree still is one of the most challenges in molecular phylogenetics.
For resolving this problem, a genome-wide EST data mining approach was
systematically investigated by retrieving a large size of EST data of 144
shared genes of six green plants from GenBank. The results show that the
concatenated alignments approach overcame incongruence among single-gene
phylogenies and successfully reconstructed the congruent tree of six species
with 100% jackknife support across each branch when 144 genes was used.
Jackknife supports of correct branches increased with number of genes linearly,
but those of wrong branches also increased linearly. For inferring the
congruent tree, the minimum 30 genes were required. This approach may provide
potential power in resolving conflictions of phylogenies.
  Keywords: Genome-wide; Data mining; EST; Phylogeny; Congruent tree; Jackknife
support; Plants.


  The ultralight boson represents a promising dark matter candidate exhibiting
unique wave-like behaviors. These properties could transfer to the dark
mediator, such as the kinetic mixing dark photon, which can be a link between
the dark and Standard Model sectors, resulting in periodic oscillations of its
mass. We propose a method to detect ultralight dark matter using dark mediators
in collider and beam dump experiments, distinguishing it from conventional
atomic, molecular, and optical methods. The time-varying nature of dark
mediator mass exhibits a double-peak spectrum, reducing traditional constraints
by 1 to 2 orders of magnitude, due to decreased luminosity exposure in each
resonant mass bin. To enhance sensitivity, we utilize event time-stamps in the
CMS Open Data and demonstrate that this technique boosts sensitivity by
approximately one order of magnitude compared to the time-blind method.
Moreover, it proves effective in detecting the invisible decay of the dark
mediator.


  The word creativity originally described a concept from human psychology, but
in the realm of computational creativity (CC), it has become much more. The
question of what creativity means when it is part of a computational system
might be considered core to CC. Pinning down the meaning of creativity, and
concepts like it, becomes salient when researchers port concepts from human
psychology to computation, a widespread practice extending beyond CC into
artificial intelligence (AI). Yet, the human processes shaping human-inspired
computational systems have been little investigated. In this paper, we question
which human literatures (social sciences, psychology, neuroscience) enter AI
scholarship and how they are translated at the port of entry. This study is
based on 22 in-depth, semi-structured interviews, primarily with human-inspired
AI researchers, half of whom focus on creativity as a major research area. This
paper focuses on findings most relevant to CC. We suggest that which human
literature enters AI bears greater scrutiny because ideas may become
disconnected from context in their home discipline. Accordingly, we recommend
that CC researchers document the decisions and context of their practices,
particularly those practices formalizing human concepts for machines.
Publishing reflexive commentary on human elements in CC and AI would provide a
useful record and permit greater dialogue with other disciplines.


  Several analytical models have been used in this work to describe the
evolution of death cases arising from coronavirus (COVID-19). The Death or `D'
model is a simplified version of the SIR (susceptible-infected-recovered)
model, which assumes no recovery over time, and allows for the
transmission-dynamics equations to be solved analytically. The D-model can be
extended to describe various focuses of infection, which may account for the
original pandemic (D1), the lockdown (D2) and other effects (Dn). The evolution
of the COVID-19 pandemic in several countries (China, Spain, Italy, France, UK,
Iran, USA and Germany) shows a similar behavior in concord with the D-model
trend, characterized by a rapid increase of death cases followed by a slow
decline, which are affected by the earliness and efficiency of the lockdown
effect. These results are in agreement with more accurate calculations using
the extended SIR model with a parametrized solution and more sophisticated
Monte Carlo grid simulations, which predict similar trends and indicate a
common evolution of the pandemic with universal parameters.


  Research studies have shown no qualms about using data driven deep learning
models for downstream tasks in medical image analysis, e.g., anatomy
segmentation and lesion detection, disease diagnosis and prognosis, and
treatment planning. However, deep learning models are not the sovereign remedy
for medical image analysis when the upstream imaging is not being conducted
properly (with artefacts). This has been manifested in MRI studies, where the
scanning is typically slow, prone to motion artefacts, with a relatively low
signal to noise ratio, and poor spatial and/or temporal resolution. Recent
studies have witnessed substantial growth in the development of deep learning
techniques for propelling fast MRI. This article aims to (1) introduce the deep
learning based data driven techniques for fast MRI including convolutional
neural network and generative adversarial network based methods, (2) survey the
attention and transformer based models for speeding up MRI reconstruction, and
(3) detail the research in coupling physics and data driven models for MRI
acceleration. Finally, we will demonstrate through a few clinical applications,
explain the importance of data harmonisation and explainable models for such
fast MRI techniques in multicentre and multi-scanner studies, and discuss
common pitfalls in current research and recommendations for future research
directions.


  We discuss possibility of describing solar, atmospheric and LSND results with
four neutrinos forming two quasi-degenerate pairs. The simplest versions of
this 2+2 scheme with either $\nu_e$ or $\nu_\mu$ mixing exclusively with
sterile neutrino is disfavored by the SNO and atmospheric neutrino results
respectively. A generalized scheme with sterile state participating in both the
solar and atmospheric oscillations is still allowed. We show thasolar and
atmospheric oscillations is still allowed. We show that the complex pattern of
mixing needed for this purpose follows from a simple L_e+L_\mu-L_\tau-L_s
symmetry. Specific form of L_e+L_\mu-L_\tau-L_s symmetric mass matrix is
determined from experimental results. Two theoretical schemes which lead to
this form and a proper breaking of L_e+L_\mu-L_\tau-L_s symmetry are discussed.


  Companies use banners extensively to promote their products, and the
intelligent automatic synthesis of banners is a challenging event. Under the
premise of inputting only a small amount of information such as product, text
and size, it can synthesize styles with high freedom and richness, but at the
same time, it must satisfy the design specifications of advertisers for
advertising and scenes. We propose an intelligent banner design framework that
strikes a balance between creative freedom and design rules, called
smartbanner. Smartbanner consists of planner, actuator, adjuster and generator.
The banner is synthesized through the combined framework, which fully liberates
the designer and reduces the threshold and cost of design. It increases the
click-through rate by 30%, improves the human efficiency of designers by 500%
under the condition of ensuring the quality of creation, and synthesizes
hundreds of millions of pictures in batches throughout the year.


  Context: IGRJ11014-6103 is one of the still unidentified hard X-ray INTEGRAL
sources, reported for the first time in the 4th IBIS/ISGRI catalog. Aims: We
investigated the nature of IGR J11014-6103 by carrying out a multiwavelength
analysis of the available archival observations performed in the direction of
the source. Methods: We present first the results of the timing and spectral
analysis of all the X-ray observations of IGR J11014-6103 carried out with
ROSAT, ASCA, Einstein, Swift, and XMM-Newton, and then use them to search for
possible counterparts to the source in the optical, infra-red, radio and
gamma-ray domain. Results: Our analysis revealed that IGR J11014-6103 is
comprised of three different X-ray emitting regions: a point-like source, an
extended object and a cometary-like "tail" (~4 arcmin). A possible radio
counterpart positionally coincident with the source was also identified.
Conclusions: Based on these results, we suggest that the emission from IGR
J11014-6103 is generated by a pulsar wind nebula produced by a high-velocity
pulsar. IGR J11014-6103 might be the first of these systems detected with
INTEGRAL IBIS/ISGRI.


  The Southern Wide-field Gamma-ray Observatory (SWGO) Collaboration is
currently engaged in design and prototyping work towards the realisation of
this future gamma-ray facility. SWGO will complement CTA and the existing
ground-particle based-detectors of the Northern Hemisphere (HAWC and LHAASO)
with a very wide field and high duty cycle view of the southern sky. Here I
summarise the status of the project and plans for the future, including
expectations for sensitivity and science targets as well as the status of the
site search and technological developments.


  We present a hydro-dynamical simulation at sub-parsec and few solar mass
resolution of a merger between two gas-rich dwarf galaxies. Our simulation
includes a detailed model for the multi-phase interstellar medium (ISM) and is
able to follow the entire formation history of spatially resolved star
clusters, including feedback from individual massive stars. Shortly after the
merger we find a population of $\sim 900$ stellar clusters with masses above
$10^{2.5}\; \rm{M_\odot}$ and a cluster mass function (CMF), which is well
fitted with a power-law with a slope of $\alpha=-1.70\pm0.08$. We describe here
in detail the formation of the three most massive clusters (M$_{*} \gtrsim
10^5$ M$_\odot$), which populate the high-mass end of the CMF. The simulated
clusters form rapidly on a timescale of $6$-$8$ Myr in converging flows of
dense gas. The embedded merger phase has extremely high star formation rate
surface densities of $\Sigma_\mathrm{SFR}>10\; \mathrm{M}_\odot\;
\mathrm{yr}^{-1}\; \mathrm{kpc}^{-2}$ and thermal gas pressures in excess of
$P_{\rm th}\sim10^7 \; \mathrm{k}_{\rm B}\;(\rm K\;\mathrm{cm}^{-3})^{-1}$. The
formation process is terminated by rapid gas expulsion driven by the first
generation of supernovae, after which the cluster centers relax and both their
structure and kinematics become indistinguishable from observed local globular
clusters. The simulation presented here provides a general model for the
formation of metal-poor globular clusters in chemically unevolved starbursting
environments of low-mass dwarf galaxies, which are common at high redshifts.


  A basic problem in information theory is the following: Let $\mathbf{P} =
(\mathbf{X}, \mathbf{Y})$ be an arbitrary distribution where the marginals
$\mathbf{X}$ and $\mathbf{Y}$ are (potentially) correlated. Let Alice and Bob
be two players where Alice gets samples $\{x_i\}_{i \ge 1}$ and Bob gets
samples $\{y_i\}_{i \ge 1}$ and for all $i$, $(x_i, y_i) \sim \mathbf{P}$. What
joint distributions $\mathbf{Q}$ can be simulated by Alice and Bob without any
interaction?
  Classical works in information theory by G{\'a}cs-K{\"o}rner and Wyner answer
this question when at least one of $\mathbf{P}$ or $\mathbf{Q}$ is the
distribution on $\{0,1\} \times \{0,1\}$ where each marginal is unbiased and
identical. However, other than this special case, the answer to this question
is understood in very few cases. Recently, Ghazi, Kamath and Sudan showed that
this problem is decidable for $\mathbf{Q}$ supported on $\{0,1\} \times
\{0,1\}$. We extend their result to $\mathbf{Q}$ supported on any finite
alphabet.
  We rely on recent results in Gaussian geometry (by the authors) as well as a
new \emph{smoothing argument} inspired by the method of \emph{boosting} from
learning theory and potential function arguments from complexity theory and
additive combinatorics.


  Using the operators of taking upper and lower cones in a poset with a unary
operation, we define operators M(x,y) and R(x,y) in the sense of multiplication
and residuation, respectively, and we show that by using these operators, a
general modification of residuation can be introduced. A relatively
pseudocomplemented poset can be considered as a prototype of such an operator
residuated poset. As main results we prove that every Boolean poset as well as
every pseudo-orthomodular poset can be organized into a (left) operator
residuated structure. Some results on pseudo-orthomodular posets are presented
which show the analogy to orthomodular lattices and orthomodular posets.


  The Galactic supergiant B[e] star CI Camelopardalis (CI Cam) was the first
sgB[e] star detected during an X-ray outburst. The star brightened to $\sim$2
Crab in the X-ray regime within hours before decaying to a quiescent level in
less than 2 weeks, clearly indicative of binarity. Since the outburst of CI
Cam, a number of sgB[e] stars have been identified as X-ray overluminous for a
single star (i.e. $L_X > 10^{-7}~L_{bol}$). This small population has recently
expanded to include two Ultra Luminous X-ray sources (ULX), Holmberg II X-1 and
NGC300 ULX-1/supernova imposter SN2010da. We revisit CI Cam to investigate its
behaviour over several timescales and shed further light on the nature of the
compact object in the system, its X-ray outburst in 1998 and the binary system
parameters. We analyse archival XMM-Newton EPIC-pn spectra and light curves
along with new data from Swift and NuSTAR. We also present high-resolution
MERCATOR/HERMES optical spectra, including a spectrum taken 1.02 days after our
NuSTAR observation. Despite being in quiescence, CI Cam is highly X-ray
variable on timescales of days, both in terms of total integrated flux and
spectral shape. We interpret these variations by invoking the presence of an
accreting compact companion immersed in a dense, highly structured, aspherical
circumstellar envelope. The differences in the accretion flux and circumstellar
extinction represent either changes in this environment, triggered by variable
mass loss from the star, or the local conditions to the accretor due to its
orbital motion. We find no evidence for pulsations in the X-ray light curve. CI
Cam has many similarities with SN2010da across mid-IR, optical and X-ray
wavelengths suggesting that, subject to distance determination for CI Cam, if
CI Cam was located in an external galaxy its 1998 outburst would have led to a
classification as a supernova imposter.


  Area laws for entanglement in quantum many-body systems give useful
information about their low-temperature behaviour and are tightly connected to
the possibility of good numerical simulations. An intuition from quantum
many-body physics suggests that an area law should hold whenever there is
exponential decay of correlations in the system, a property found, for
instance, in non-critical phases of matter. However, the existence of quantum
data-hiding state--that is, states having very small correlations, yet a volume
scaling of entanglement--was believed to be a serious obstruction to such an
implication. Here we prove that notwithstanding the phenomenon of data hiding,
one-dimensional quantum many-body states satisfying exponential decay of
correlations always fulfil an area law. To obtain this result we combine
several recent advances in quantum information theory, thus showing the
usefulness of the field for addressing problems in other areas of physics.


  Based on deleting-item central limit theory, the classical Donsker's theorem
of partial-sum process of independent and identically distributed (i.i.d.)
random variables is extended to incomplete partial-sum process. The incomplete
partial-sum process Donsker's invariance principles are constructed and derived
for general partial-sum process of i.i.d random variables and empirical process
respectively, they are not only the extension of functional central limit
theory, but also the extension of deleting-item central limit theory. Our work
enriches the random elements structure of weak convergence.


  We prove existence and multiplicity results for a $N$-Laplacian problem with
a critical exponential nonlinearity that is a natural analog of the
Brezis-Nirenberg problem for the borderline case of the Sobolev inequality.
This extends results in the literature for the semilinear case $N = 2$ to all
$N \ge 2$. When $N > 2$ the nonlinear operator $- \Delta_N$ has no linear
eigenspaces and hence this extension requires new abstract critical point
theorems that are not based on linear subspaces. We prove new abstract results
based on the ${\mathbb Z}_2$-cohomological index and a related pseudo-index
that are applicable here.


  Cosmic ray muon tomography is a novel technology to detect high-Z material. A
prototype of TUMUTY with 73.6 cm x 73.6 cm large scale position sensitive MRPC
detectors has been developed and is introduced in this paper. Three test kits
have been tested and image is reconstructed using MAP algorithm. The
reconstruction results show that the prototype is working well and the objects
with complex structure and small size (20 mm) can be imaged on it, while the
high-Z material is distinguishable from the low-Z one. This prototype provides
a good platform for our further studies of the physical characteristics and the
performances of cosmic ray muon tomography.


  We investigate the interactions of Weakly Interacting Massive Particles
(WIMPs) with nuclei in the human body. We are motivated by the fact that WIMPs
are excellent candidates for the dark matter in the Universe. Our estimates use
a 70 kg human and a variety of WIMP masses and cross-sections. The
contributions from individual elements in the body are presented and it is
found that the dominant contribution is from scattering off of oxygen
(hydrogen) nuclei for the spin-independent (spin-dependent) interactions. For
the case of 60 GeV WIMPs, we find that, of the billions of WIMPs passing
through a human body per second, roughly ~10 WIMPs hit one of the nuclei in the
human body in an average year, if the scattering is at the maximum consistent
with current bounds on WIMP interactions. We also study the 10-20 GeV WIMPs
with much larger cross-sections that best fit the DAMA, COGENT, and CRESST data
sets and find much higher rates: in this case as many as $10^5$ WIMPs hit a
nucleus in the human body in an average year, corresponding to almost one a
minute. Though WIMP interactions are a source of radiation in the body, the
annual exposure is negligible compared to that from other natural sources
(including radon and cosmic rays), and the WIMP collisions are harmless to
humans.


  In this paper we study the convex problem of optimizing the sum of a smooth
function and a compactly supported non-smooth term with a specific separable
form. We analyze the block version of the generalized conditional gradient
method when the blocks are chosen in a cyclic order. A global sublinear rate of
convergence is established for two different stepsize strategies commonly used
in this class of methods. Numerical comparisons of the proposed method to both
the classical conditional gradient algorithm and its random block version
demonstrate the effectiveness of the cyclic block update rule.


  Making topological authentication from theory to practical application is an
important and challenging task. More and more researchers pay attention on
coming quantum computation, privacy data protection, lattices and cryptography.
Research show the advantages of topological authentications through graph
operations, various matrices, graph colorings and graph labelings are: related
with two or more different mathematical areas, be not pictures, there are huge
number of colorings and labelings, rooted on modern mathematics, diversity of
asymmetric ciphers, simplicity and convenience, easily created,
irreversibility, computational security, provable security, and so on.
Topological authentications based on various graph homomorphisms,
degree-sequence homomorphisms, graph-set homomorphisms. Randomly topological
coding and topological authentications are based on Hanzi authentication,
randomly adding-edge-removing operation, randomly leaf-adding algorithms, graph
random increasing techniques, operation graphic lattice and dynamic networked
models and their spanning trees and maximum leaf spanning trees. Realization of
topological authentication is an important topic, we study: number-based
strings generated from colored graphs, particular graphs (complete graphs,
trees, planar graphs), some methods of generating public-keys. some techniques
of topologically asymmetric cryptosystem are: W-type matching labelings,
dual-type labelings, reciprocal-type labelings, topological homomorphisms,
indexed colorings, graphic lattices, degree-sequence lattices, every-zero
Cds-matrix groups of degree-sequences, every-zero graphic groups, graphic
lattices having coloring closure property, self-similar networked lattices.


  Pretrained large generative language models have shown great performance on
many tasks, but exhibit low compositional generalization abilities. Scaling
such models has been shown to improve their performance on various NLP tasks
even just by conditioning them on a few examples to solve the task without any
fine-tuning (also known as in-context learning). In this work, we look at the
gap between the in-distribution (ID) and out-of-distribution (OOD) performance
of such models in semantic parsing tasks with in-context learning. In the ID
settings, the demonstrations are from the same split (test or train) that the
model is being evaluated on, and in the OOD settings, they are from the other
split. We look at how the relative generalization gap of in-context learning
evolves as models are scaled up. We evaluate four model families, OPT, BLOOM,
CodeGen and Codex on three semantic parsing datasets, CFQ, SCAN and GeoQuery
with different number of exemplars, and observe a trend of decreasing relative
generalization gap as models are scaled up.


  We give a proof for the H\"older continuity of functions in the parabolic De
Giorgi classes in metric measure spaces. We assume the measure to be doubling,
to support a weak $(1,p)$-Poincar\'e inequality and to satisfy the annular
decay property.


  Physical systems contain information which can be divided between classical
and quantum information. Classical information is locally accessible and allows
one to perform tasks such as physical work, while quantum information allows
one to perform tasks such as teleportation. It is shown that these two kinds of
information are complementarity in the sense that two parties can either gain
access to the quantum information, or to the classical information but not
both. This complementarity has a form very similar to the complementarities
usually encountered in quantum mechanics. For pure states, the entanglement
plays the role of Planck's constant. We also find another class of
complementarity relations which applies to operators, and is induced when two
parties can only perform local operations and communicate classical. In order
to formalize this notion we define the restricted commutator. Observables such
as the parity and phase of two qubits commute, but their restricted commutator
is non-zero. It is also found that complementarity is pure in the sense that
can be ''decoupled'' from the uncertainty principle.


  Transforming natural language questions into SQL queries is crucial for
precise data retrieval from electronic health record (EHR) databases. A
significant challenge in this process is detecting and rejecting unanswerable
questions that request information beyond the database's scope or exceed the
system's capabilities. In this paper, we introduce a novel text-to-SQL
framework that robustly handles out-of-domain questions and verifies the
generated queries with query execution.Our framework begins by standardizing
the structure of questions into a templated format. We use a powerful large
language model (LLM), fine-tuned GPT-3.5 with detailed prompts involving the
table schemas of the EHR database system. Our experimental results demonstrate
the effectiveness of our framework on the EHRSQL-2024 benchmark benchmark, a
shared task in the ClinicalNLP workshop. Although a straightforward fine-tuning
of GPT shows promising results on the development set, it struggled with the
out-of-domain questions in the test set. With our framework, we improve our
system's adaptability and achieve competitive performances in the official
leaderboard of the EHRSQL-2024 challenge.


  We present a data-driven inference method that can synthesize a
photorealistic texture map of a complete 3D face model given a partial 2D view
of a person in the wild. After an initial estimation of shape and low-frequency
albedo, we compute a high-frequency partial texture map, without the shading
component, of the visible face area. To extract the fine appearance details
from this incomplete input, we introduce a multi-scale detail analysis
technique based on mid-layer feature correlations extracted from a deep
convolutional neural network. We demonstrate that fitting a convex combination
of feature correlations from a high-resolution face database can yield a
semantically plausible facial detail description of the entire face. A complete
and photorealistic texture map can then be synthesized by iteratively
optimizing for the reconstructed feature correlations. Using these
high-resolution textures and a commercial rendering framework, we can produce
high-fidelity 3D renderings that are visually comparable to those obtained with
state-of-the-art multi-view face capture systems. We demonstrate successful
face reconstructions from a wide range of low resolution input images,
including those of historical figures. In addition to extensive evaluations, we
validate the realism of our results using a crowdsourced user study.


  We explore the dependence of the thermally activated barrier crossing rate on
various model parameters for a dimer that undergoes a Brownian motion on a
piecewise linear bistable potential employing the method of adiabatic
elimination of fast variable. By introducing a different model system and
approaches than the previous works \cite{c4,c5}, not only we recapture the
previous results but we further show that systematic elimination of the fast
changing variable leads to an effective Kramers type potential. It is shown
that for rigid dimer, the escape rate $R$ monotonously decreases with $k$. On
the other hand, in the presence of time varying force, the signal to noise
ratio (SNR) attains a pronounced peak at particular barrier height $U_{0}$.


  A model for kinetic roughening of one-dimensional interfaces is presented
within an intrinsic geometry framework that is free from the standard
small-slope and no-overhang approximations. The model is meant to probe the
consequences of the latter on the Kardar-Parisi-Zhang (KPZ) description of
non-conserved, irreversible growth. Thus, growth always occurs along the local
normal direction to the interface, with a rate that is subject to fluctuations
and depends on the local curvature. Adaptive numerical techniques have been
designed that are specially suited to the study of fractal morphologies and can
support interfaces with large slopes and overhangs. Interface
self-intersections are detected, and the ensuing cavities removed. After
appropriate generalization of observables such as the global and local surface
roughness functions, the interface scaling is seen in our simulations to be of
the Family-Vicsek type for arbitrary curvature dependence of the growth rate,
KPZ scaling appearing for large sytems sizes and sufficiently large noise
amplitudes.


  We revisit the role of primordial black holes (PBHs) as potential dark matter
(DM) candidates, particularly focusing on light asteroid-mass PBHs. These PBHs
are expected to emit particles through Hawking evaporation that can generate
cosmic rays (CRs), eventually producing other secondary radiations through
their propagation in the Milky Way, in addition to prompt emissions. Here, we
perform a comprehensive analysis of CR signals resulting from PBH evaporation,
incorporating the full CR transport to account for reacceleration and diffusion
effects within the Milky Way. In particular, we revisit the $e^\pm$ flux
produced by PBHs, using Voyager 1, and study for the first time the diffuse
X-ray emission from the up-scattering of Galactic ambient photons due to
PBH-produced $e^\pm$ via the inverse Compton effect using XMM-Newton data, as
well as the morphological information of the diffuse 511 keV line measured by
INTEGRAL/SPI. In doing so, we provide leading constraints on the fraction of DM
that can be in form of PBHs in a conservative way, whilst also testing how
different assumptions on spin and mass distributions affect our conclusions.