  Following Nye and Berry's analogy with crystal dislocations, an approach to
the Burgers vector of a wave dislocation (phase singularity, optical vortex) is
proposed. It is defined to be a regularized phase gradient evaluated at the
phase singularity, and is computed explicitly. The screw component of this
vector is naturally related to the helicoidal twisting of wavefronts along a
vortex line, and is related to the helicity of the phase gradient. The edge
component is related to the nearby current flow (defined by the phase gradient)
perpendicular to the vortex, and the distribution of this component is found
numerically for random two-dimensional monochromatic waves.


  We discuss the quality required for the RF source used to trap neutral atoms
in RF-dressed potentials. We illustrate this discussion with experimental
results obtained on a Bose-Einstein condensation experiment with different RF
sources.


  We consider a model where sterile neutrinos can propagate in a large
compactified extra dimension giving rise to Kaluza-Klein (KK) modes and the
standard model left-handed neutrinos are confined to a 4-dimensional spacetime
brane. The KK modes mix with the standard neutrinos modifying their oscillation
pattern. We examine former and current experiments such as CHOOZ, KamLAND, and
MINOS to estimate the impact of the possible presence of such KK modes on the
determination of the neutrino oscillation parameters and simultaneously obtain
limits on the size of the largest extra dimension. We found that the presence
of the KK modes does not essentially improve the quality of the fit compared to
the case of the standard oscillation. By combining the results from CHOOZ,
KamLAND and MINOS, in the limit of a vanishing lightest neutrino mass, we
obtain the stronger bound on the size of the extra dimension as ~ 1.0(0.6)
micrometer at 99% C. L. for normal (inverted) mass hierarchy. If the lightest
neutrino mass turn out to be larger, 0.2 eV, for example, we obtain the bound ~
0.1 micrometer. We also discuss the expected sensitivities on the size of the
extra dimension for future experiments such as Double CHOOZ, T2K and NOvA.


  Adaptive robotics plays an essential role in achieving truly co-creative
cyber physical systems. In robotic manipulation tasks, one of the biggest
challenges is to estimate the pose of given workpieces. Even though the recent
deep-learning-based models show promising results, they require an immense
dataset for training. In this paper, two vision-based, multi-object grasp pose
estimation models (MOGPE), the MOGPE Real-Time and the MOGPE High-Precision are
proposed. Furthermore, a sim2real method based on domain randomization to
diminish the reality gap and overcome the data shortage. Our methods yielded an
80% and a 96.67% success rate in a real-world robotic pick-and-place
experiment, with the MOGPE Real-Time and the MOGPE High-Precision model
respectively. Our framework provides an industrial tool for fast data
generation and model training and requires minimal domain-specific data.


  Continuing the line of thought of an earlier work, we provide the first
infinite family of quadratic number fields with everywhere unramified Galois
extensions of Galois group $SL_2(5)$, the (unique) smallest nonsolvable group
for which this problem was previously open. Our approach also improves upon
previous work by yielding the first infinite family of real-quadratic fields
possessing an unramified Galois extension whose Galois group is perfect and not
generated by involutions. Our result also amounts to a new existence result on
quintic number fields with squarefree discriminant and additional local
conditions.


  The evaporation of water is ubiquitous in nature and industrial technologies.
The known mechanism for evaporation is "thermal evaporation" which highlights
the energy input for evaporation is via heat. Due to the weak absorption of
water to visible light, the first step to using solar energy to evaporate water
is usually by converting it into thermal energy through photothermal processes
via additional absorbing materials. Contrary to this conventional wisdom, we
report here strong absorption of photons in the visible spectrum at the
water-vapor interface by direct cleavage of water clusters via a process we
call photomolecular effect. We show that this process happens at the
water-vapor interface by measuring the dependence of the photomolecular
evaporation rate on the wavelength, the angle of incidence, and the
polarization of the incident light. The spectra signatures in the vapor phase
further support the photomolecular effect. Despite the long propagation lengths
of visible light in bulk water, we demonstrate that they can heat a thin layer
of fog easily, suggesting that this process is ubiquitous. The photomolecular
effect will have significant implications for the earth's water cycle, global
warming, plant transpiration, as well as different technologies involving the
evaporation of liquids from drying to power generation


  We investigate the horofunction boundary of the Hilbert geometry defined on
an arbitrary finite-dimensional bounded convex domain D. We determine its set
of Busemann points, which are those points that are the limits of
`almost-geodesics'. In addition, we show that any sequence of points converging
to a point in the horofunction boundary also converges in the usual sense to a
point in the Euclidean boundary of D. We prove that all horofunctions are
Busemann points if and only if the set of extreme sets of the polar of D is
closed in the Painleve-Kuratowski topology.


  A technique from stochastic portfolio theory [Fernholz, 1998] is applied to
analyse equity returns of Small, Mid and Large cap portfolios in an emerging
market through periods of growth and regional crises, up to the onset of the
global financial crisis. In particular, we factorize portfolios in the South
African market in terms of distribution of capital, change of stock ranks in
portfolios, and the effect due to dividends for the period Nov 1994 to May
2007. We discuss the results in the context of broader economic thinking to
consider capital flows as risk factors, turning around more established
approaches which use macroeconomic and socio-economic conditions to explain
Foreign Direct Investment (into the economy) and Net Portfolio Investment (into
equity and bond markets).


  Galaxy mergers are known to host abundant young massive cluster (YMC)
populations, whose formation mechanism is still not well-understood. Here, we
present a high-resolution galaxy merger simulation with explicit star formation
and stellar feedback prescriptions to investigate how mergers affect the
properties of the interstellar medium and YMCs. Compared with a controlled
simulation of an isolated galaxy, the mass fraction of dense and high-pressure
gas is much higher in mergers. Consequently, the mass function of both
molecular clouds and YMCs becomes shallower and extends to higher masses.
Moreover, cluster formation efficiency is significantly enhanced and correlates
positively with the star formation rate surface density and gas pressure. We
track the orbits of YMCs and investigate the time evolution of tidal fields
during the course of the merger. At an early stage of the merger, the tidal
field strength correlates positively with YMC mass, $\lambda_{\rm tid}\propto
M^{0.71}$, which systematically affects the shape of the mass function and age
distribution of the YMCs. At later times, most YMCs closely follow the orbits
of their host galaxies, gradually sinking into the center of the merger remnant
due to dynamical friction, and are quickly dissolved via efficient tidal
disruption. Interestingly, YMCs formed during the first passage, mostly in
tidal tails and bridges, are distributed over a wide range of galactocentric
radii, greatly increasing their survivability because of the much weaker tidal
field in the outskirts of the merger system. These YMCs are promising
candidates for globular clusters that survive to the present day.


  We revisit arguments that simple models of inflation with a small red tilt in
the scalar power spectrum generically yield an observable tensor spectrum. We
show that criteria for fine-tuning based upon the algebraic simplicity of the
potential depend strongly upon the explicit assumptions they incorporate,
particularly regarding the end of inflation. In addition, some models with
algebraically simple potentials require carefully tuned initial field
configurations, and not all types of fine-tuning are identifiable via the
algebraic simplicity of the potential. Conversely, in the absence of a strong
prior on the mechanism that ends inflation, we demonstrate the existence of
potentials with vanishingly small tensor amplitudes which are natural in terms
of both their algebraic form and initial conditions. We thus argue that
proposed experiments (CMBPol or BBO) which make highly sensitive measurements
of the tensor amplitude cannot definitively rule out the inflationary paradigm.


  Non-invasive prenatal testing or NIPT is currently among the top researched
topic in obstetric care. While the performance of the current state-of-the-art
NIPT solutions achieve high sensitivity and specificity, they still struggle
with a considerable number of samples that cannot be concluded with certainty.
Such uninformative results are often subject to repeated blood sampling and
re-analysis, usually after two weeks, and this period may cause a stress to the
future mothers as well as increase the overall cost of the test. We propose a
supplementary method to traditional z-scores to reduce the number of such
uninformative calls. The method is based on a novel analysis of the length
profile of circulating cell free DNA which compares the change in such profiles
when random-based and length-based elimination of some fragments is performed.
The proposed method is not as accurate as the standard z-score; however, our
results suggest that combination of these two independent methods correctly
resolves a substantial portion of healthy samples with an uninformative result.
Additionally, we discuss how the proposed method can be used to identify
maternal aberrations, thus reducing the risk of false positive and false
negative calls.
  Keywords: Next-generation sequencing, Cell-free DNA, Uninformative result,
Method, Trisomy, Prenatal testing


  On-chip ultraviolet to infrared (UV-IR) spectrum frequency metrology is of
crucial importance as a characterization tool for fundamental studies on
quantum physics, chemistry, and biology. Due to the strong material dispersion,
traditional techniques fail to demonstrate the device that can be applied to
generate coherent broadband spectrum that covers the full UV-IR wavelengths. In
this work, we explore several novel techniques for supercontinuum generation
covering near-UV to near-IR spectrum using AlN micro-photonic waveguides, which
is essential for frequency metrology applications: First, to create anomalous
dispersion, high order mode (TE10) was adopted, together with its carefully
designed high efficiency excitation strategies. Second, the spectrum was
broadened by soliton fission through third order dispersion and second harmonic
generation, by which directional energy transfer from near-IR to near-UV can be
obtained. Finally, high quality single crystalline AlN material was used to
provide broadband transparency from UV to IR. Under decently low pulse energy
of 0.36 nJ, the experimental spectrum from supercontinuum generation covers
from 490 nm to over 1100 nm, with a second harmonic generation band covering
from 405 nm to 425 nm. This work paves the way towards UV-IR full spectrum
on-chip frequency metrology applications.


  Recently, Target-oriented Multimodal Sentiment Classification (TMSC) has
gained significant attention among scholars. However, current multimodal models
have reached a performance bottleneck. To investigate the causes of this
problem, we perform extensive empirical evaluation and in-depth analysis of the
datasets to answer the following questions: Q1: Are the modalities equally
important for TMSC? Q2: Which multimodal fusion modules are more effective? Q3:
Do existing datasets adequately support the research? Our experiments and
analyses reveal that the current TMSC systems primarily rely on the textual
modality, as most of targets' sentiments can be determined solely by text.
Consequently, we point out several directions to work on for the TMSC task in
terms of model design and dataset construction. The code and data can be found
in https://github.com/Junjie-Ye/RethinkingTMSC.


  [abridged] We present a strong-lensing analysis of MACSJ0717.5+3745, based on
the full depth of the Hubble Frontier Field (HFF) observations, which brings
the number of multiply imaged systems to 61, ten of which are spectroscopically
confirmed. The total number of images comprised in these systems rises to 165.
Our analysis uses a parametric mass reconstruction technique, as implemented in
the Lenstool software, to constrain a mass distribution composed of four
large-scale mass components + galaxy-scale perturbers. We find a superposition
of cored isothermal mass components to provide a good fit to the observational
constraints, resulting in a very shallow mass distribution for the smooth
(large-scale) component. Given the implications of such a flat mass profile, we
investigate whether a model composed of "peaky" non-cored mass components can
also reproduce the observational constraints. We find that such a non-cored
mass model reproduces the observational constraints equally well. Although the
total mass distributions of both models are consistent, as well as the
integrated two dimensional mass profiles, we find that the smooth and the
galaxy-scale components are very different. We conclude that, even in the HFF
era, the generic degeneracy between smooth and galaxy-scale components is not
broken, in particular in such a complex galaxy cluster. Consequently, insights
into the mass distribution of MACS J0717 remain limited, underlining the need
for additional probes beyond strong lensing. Our findings also have
implications for estimates of the lensing magnification: we show that the
amplification difference between the two models is larger than the error
associated with either model. This uncertainty decreases the area of the image
plane where we can reliably study the high-redshift Universe by 50 to 70%.


  Locally repairable codes have been investigated extensively in recent years
due to practical application in distributed storage as well as theoretical
interest. However, not much work on asymptotical behavior of locally repairable
codes has been done until now. In particular, there is a little result on
constructive lower bound on asymptotical behavior of locally repairable codes.
In this paper, we extend the construction given in \cite{BTV17} via
automorphism groups of function field towers. The main advantage of our
construction is to allow more flexibility of locality. Furthermore, we show
that the Gilbert-Varshamov type bound on locally repairable codes can be
improved for all sufficiently large alphabet size $q$.


  Ease of miniaturization and minimal maintenance are among the advantages for
replacing conventional batteries with vibratory energy harvesters in a wide of
range of disciplines and applications, from wireless communication sensors to
medical implants. However, the current harvesters do not extract energy from
the ambient vibrations in a very efficient and robust fashion, and hence, there
need to be more optimal harvesting approaches. In this paper, we introduce a
generic architecture for vibration energy harvesting and delineate the key
challenges in the field. Then, we formulate an optimal control problem to
maximize the harvested energy. Though possessing similar structure to that of
the standard LQG problem, this optimal control problem is inherently different
from the LQG problem and poses theoretical challenges to control community. As
the first step, we simplify it to a tractable problem of optimizing control
gains for a linear system subjected to Gaussian white noise excitation, and
show that this optimal problem has non-trivial optimal solutions in both time
and frequency domains.


  We study the energy transfer in the linear system $$ \begin{cases} \ddot
u+u+\dot u=b\dot v\\ \ddot v+v-\epsilon \dot v=-b\dot u \end{cases} $$ made by
two coupled differential equations, the first one dissipative and the second
one antidissipative. We see how the competition between the damping and the
antidamping mechanisms affect the whole system, depending on the coupling
parameter $b$.


  Carbon-enhanced metal-poor (CEMP) stars count for 9-25% of all the very
metal-poor stars of the halo. In at least some CEMP stars the chemical
enrichment is believed to be due to wind mass transfer in the past from an AGB
donor star on to a low-mass companion. However, binary population synthesis
models predict much lower CEMP fractions. As an alternative to the canonical
Bondi-Hoyle-Lyttleton (BHL) wind accretion model, recent hydrodynamical
simulations suggest an efficient mode of wind mass transfer, called wind
Roche-lobe overflow (WRLOF), can reproduce observations of AGB winds in binary
systems. We use our population synthesis model to test the consequences of
WRLOF on a population of CEMP stars. Compared to previous predictions based on
the BHL model we find a modest increase of the fraction of CEMP stars and
substantial differences in the distributions of carbon and periods in the
population of CEMP stars.


  Ferroelectricity in sputtered undoped-HfO$_2$ is attractive for composition
control for low power and non-volatile memory and logic applications. Unlike
doped HfO$_2$, evolution of ferroelectricity with annealing and film thickness
effect in sputter deposited undoped HfO$_2$ on Si is not yet reported. In
present study, we have demonstrated the impact of post metallization annealing
temperature and film thickness on ferroelectric properties in dopant-free
sputtered HfO$_2$ on Si-substrate. A rich correlation of polarization with
phase, lattice constant, and crystallite size and interface reaction is
observed. First, anneal temperature shows o-phase saturation beyond 600 oC
followed by interface reaction beyond 700 oC to show an optimal temperature
window on 600-700 oC. Second, thickness study at the optimal temperature window
shows an alluring o-phase crystallite scaling with thickness till a critical
thickness of 20 nm indicating that the films are completely o-phase. However,
the lattice constants (volume) are high in the 15-20 nm thickness range which
correlates with the enhanced value of 2Pr. Beyond 20 nm, crystallite scaling
with thickness saturates with the correlated appearance of m-phase and
reduction in 2Pr. The optimal thickness-temperature window range of 15-20 nm
films annealed at 600-700 oC show 2Pr of ~35.5 micro-C/cm$^2$ is comparable to
state-of-the-art. The robust wakeup-free endurance of ~$10^$8 cycles showcased
in the promising temperature-thickness window has been identified
systematically for non-volatile memory applications.


  The renormalization procedure is proved to be a rigorous way to get finite
answers in a renormalizable class of field theories. We claim, however, that it
is redundant if one reduces the requirement of finiteness to S-matrix elements
only and does not require finiteness of intermediate quantities like the
off-shell Green functions. We suggest a novel view on the renormalization
procedure. It is based on the usual BPHZ R-operation, which is equally
applicable to any local QFT, renormalizable or not. The key point is the
replacement of the multiplicative renormalization, used in renormalizable
theories, by an operation when the renormalization constants depend on the
fields and momenta that have to be integrated inside the subgraphs. This
approach does not distinguish between renormalizable and non-renormalizable
interactions and provides the basis for getting finite scattering amplitudes in
both cases. The arbitrariness of the subtraction procedure is fixed by imposing
a normalization condition on the scattering amplitude as a whole rather than on
an infinite series of new operators appearing in non-renormalizable theories.
  Using the property of locality of counter-terms, we get recurrence relations
connecting leading, subleading, etc., UV divergences in all orders of PT in any
local theory. This allows one to get generalized RG equations that have an
integro-differential form and sum up the leading logarithms. This way one can
cure the problem of violation of unitarity in non-renormalizable theories by
summing up the leading asymptotics. We illustrate the basic features of our
approach by several examples.
  Our main statement is that non-renormalizable theories are self-consistent,
they can be well treated within the usual BPHZ R-operation, and the
arbitrariness can be fixed to a finite number of parameters just as in the
renormalizable case.


  Accountability is the property of a system that enables the uncovering of
causes for events and helps understand who or what is responsible for these
events. Definitions and interpretations of accountability differ; however, they
are typically expressed in natural language that obscures design decisions and
the impact on the overall system. This paper presents a formal model to express
the accountability properties of cyber-physical systems. To illustrate the
usefulness of our approach, we demonstrate how three different interpretations
of accountability can be expressed using the proposed model and describe the
implementation implications through a case study. This formal model can be used
to highlight context specific-elements of accountability mechanisms, define
their capabilities, and express different notions of accountability. In
addition, it makes design decisions explicit and facilitates discussion,
analysis and comparison of different approaches.


  The issue of step-like anomalies in the tritium \beta-decay spectrum as
measured in the Troitsk-\nu-mass experiment is addressed in the context of the
new analysis in a systematic fashion using efficient statistical tests
specifically derived for the purpose. It is concluded that the presence of the
anomaly cannot be statistically asserted with a high confidence level.


  In this paper we develop general LP and ILP techniques to find an approximate
solution with improved objective value close to an existing solution. The task
of improving an approximate solution is closely related to a classical theorem
of Cook et al. in the sensitivity analysis for LPs and ILPs. This result is
often applied in designing robust algorithms for online problems. We apply our
new techniques to the online bin packing problem, where it is allowed to
reassign a certain number of items, measured by the migration factor. The
migration factor is defined by the total size of reassigned items divided by
the size of the arriving item. We obtain a robust asymptotic fully polynomial
time approximation scheme (AFPTAS) for the online bin packing problem with
migration factor bounded by a polynomial in $\frac{1}{\epsilon}$. This answers
an open question stated by Epstein and Levin in the affirmative. As a byproduct
we prove an approximate variant of the sensitivity theorem by Cook at el. for
linear programs.


  The aim of this paper is to give the text of a recent introduction to
nonlinear generalized functions exposed in my talk in the congress gf2011,
which was asked by several participants. Three representative topics were
presented: two recalls "Nonlinear generalized functions and their connections
with distribution theory", "Examples of applications", and a recent
development: "Locally convex topologies and compactness: a functional analysis
of nonlinear generalized functions".


  We investigate the dynamics of a boundary field coupled to a bulk field with
a linear coupling in an anti-de Sitter bulk spacetime bounded by a Minkowski
(Randall-Sundrum) brane. An instability criterion for the coupled boundary and
bulk system is found. There exists a tachyonic bound state when the coupling is
above a critical value, determined by the masses of the brane and bulk fields
and AdS curvature scale. This bound state is normalizable and localised near
the brane, and leads to a tachonic instability of the system on large scales.
Below the critical coupling, there is no tachyonic state and no bound state.
Instead, we find quasi-normal modes which describe stable oscillations, but
with a finite decay time. Only if the coupling is tuned to the critical value
does there exist a massless stable bound state, as in the case of zero coupling
for massless fields. We discuss the relation to gravitational perturbations in
the Randall-Sundrum brane-world.


  Topologically protected superfluid phases of $^3$He allow one to simulate
many important aspects of relativistic quantum field theories and quantum
gravity in condensed matter. Here we discuss a topological Lifshitz transition
of the effective quantum vacuum in which the determinant of the tetrad field
changes sign through a crossing to a vacuum state with a degenerate fermionic
metric. Such a transition is realized in polar distorted superfluid $^3$He-A in
terms of the effective tetrad fields emerging in the vicinity of the superfluid
gap nodes: the tetrads of the Weyl points in the chiral A-phase of $^3$He and
the degenerate tetrad in the vicinity of a Dirac nodal line in the polar phase
of $^3$He. The continuous phase transition from the $A$-phase to the polar
phase, i.e. in the transition from the Weyl nodes to the Dirac nodal line and
back, allows one to follow the behavior of the fermionic and bosonic effective
actions when the sign of the tetrad determinant changes, and the effective
chiral space-time transforms to anti-chiral "anti-spacetime". This condensed
matter realization demonstrates that while the original fermionic action is
analytic across the transition, the effective action for the orbital degrees of
freedom (pseudo-EM) fields and gravity have non-analytic behavior. In
particular, the action for the pseudo-EM field in the vacuum with Weyl fermions
(A-phase) contains the modulus of the tetrad determinant. In the vacuum with
the degenerate metric (polar phase) the nodal line is effectively a family of
$2+1$d Dirac fermion patches, which leads to a non-analytic $(B^2-E^2)^{3/4}$
QED action in the vicinity of the Dirac line.


  Sudden turn-on of a matter-wave source leads to characteristic oscillations
of the probability density which are the hallmark feature of diffraction in
time. The apodization of matter waves relies on the use of smooth aperture
functions which suppress such oscillations. The analytical dynamics arising
with different aperture functions are discussed systematically for switching-on
processes, and for single and many-pulse formation procedures. The possibility
and time scale of a revival of the diffraction-in-time pattern is also
analysed. Similar modulations in time of the pulsed output coupling in
atom-lasers are responsible for the dynamical evolution and characteristics of
the beam profile. For multiple pulses, different phase schemes and regimes are
described and compared. Strongly overlapping pulses lead to a saturated,
constant beam profile in time and space, up to the revival phenomenon.


  Mixed iodine-bromine perovskites used in solar cells undergo below a critical
temperature an intrinsic demixing into phases with different iodine-bromine
compositions. In addition, under illumination they show nucleation of an
iodine-rich phase. We predict from thermodynamic considerations that in mixed
iodine-bromine perovskites like MAPb(I$_{1-x}$Br$_x$)$_3$ the interplay of
these effects can lead to coexistence of a bromine-rich, iodine-rich, and
nearly iodine-pure nucleated phase. This three-phase coexistence occurs in a
region in the composition-temperature phase diagram near the critical point for
intrinsic demixing. We investigate the hysteresis in the evolution of this
coexistence when temperature or illumination intensity are cycled. Depending on
the particular way the coexistence is established, nearly iodine-pure nuclei
should form either in the iodine-rich phase only or both in the bromine-rich
and iodine-rich phases. Experimental verification of this fundamentally novel
type of light-tunable three-phase coexistence should be possible by a
combination of absorption and photoluminescence experiments.


  Recent technological advances have made it possible to simultaneously measure
multiple protein activities at the single cell level. With such data collected
under different stimulatory or inhibitory conditions, it is possible to infer
the causal relationships among proteins from single cell interventional data.
In this article we propose a Bayesian hierarchical modeling framework to infer
the signaling pathway based on the posterior distributions of parameters in the
model. Under this framework, we consider network sparsity and model the
existence of an association between two proteins both at the overall level
across all experiments and at each individual experimental level. This allows
us to infer the pairs of proteins that are associated with each other and their
causal relationships. We also explicitly consider both intrinsic noise and
measurement error. Markov chain Monte Carlo is implemented for statistical
inference. We demonstrate that this hierarchical modeling can effectively pool
information from different interventional experiments through simulation
studies and real data analysis.


  We consider the entropy of near extremal black holes with multiple charges in
the context of the recently proposed correspondence principle of Horowitz and
Polchinski, including black holes with two, three and four Ramond-Ramond
charges. We find that at the matching point the black hole entropy can be
accounted for by massless open strings ending on the D-branes for all cases
except a black hole with four Ramond-Ramond charges, in which case a possible
resolution in terms of brane-antibrane excitations is considered.


  In the domain of medical imaging, many supervised learning based methods for
segmentation face several challenges such as high variability in annotations
from multiple experts, paucity of labelled data and class imbalanced datasets.
These issues may result in segmentations that lack the requisite precision for
clinical analysis and can be misleadingly overconfident without associated
uncertainty quantification. We propose the PULASki for biomedical image
segmentation that accurately captures variability in expert annotations, even
in small datasets. Our approach makes use of an improved loss function based on
statistical distances in a conditional variational autoencoder structure
(Probabilistic UNet), which improves learning of the conditional decoder
compared to the standard cross-entropy particularly in class imbalanced
problems. We analyse our method for two structurally different segmentation
tasks (intracranial vessel and multiple sclerosis (MS) lesion) and compare our
results to four well-established baselines in terms of quantitative metrics and
qualitative output. Empirical results demonstrate the PULASKi method
outperforms all baselines at the 5\% significance level. The generated
segmentations are shown to be much more anatomically plausible than in the 2D
case, particularly for the vessel task. Our method can also be applied to a
wide range of multi-label segmentation tasks and and is useful for downstream
tasks such as hemodynamic modelling (computational fluid dynamics and data
assimilation), clinical decision making, and treatment planning.


  We obtain in a closed form the 1/N^2 contribution to the free energy of the
two Hermitian N\times N random matrix model with non symmetric quartic
potential. From this result, we calculate numerically the Yang-Lee zeros of the
2D Ising model on dynamical random graphs with the topology of a torus up to
n=16 vertices. They are found to be located on the unit circle on the complex
fugacity plane. In order to include contributions of even higher topologies we
calculated analytically the nonperturbative (sum over all genus) partition
function of the model Z_n = \sum_{h=0}^{\infty} \frac{Z_n^{(h)}}{N^{2h}} for
the special cases of N=1,2 and graphs with n\le 20 vertices. Once again the
Yang-Lee zeros are shown numerically to lie on the unit circle on the complex
fugacity plane. Our results thus generalize previous numerical results on
random graphs by going beyond the planar approximation and strongly indicate
that there might be a generalization of the Lee-Yang circle theorem for
dynamical random graphs.


  Scalar dark matter (DM), and axions in particular, have an irreducible
abundance of particles produced by freeze-in due to portal interactions with
the Standard Model plasma in the early Universe. In addition, vacuum
misalignment and other mechanisms can lead to the presence of a cold,
oscillating condensate. Therefore, generically, the evolution of the DM in both
forms, condensate and particles, needs to be studied simultaneously. In
non-equilibrium quantum field theory, the condensate and particles are
described by one- and two-point functions, respectively. The fundamental
coupled equations of motion (EoMs) of these objects are non-local. To simplify
the EoMs and bring them into a familiar form for relic abundance calculations,
we perform a Markovianization process for a quasi-harmonically oscillating
homogeneous condensate, leading to local EoMs for the particle distribution
function and the envelope function of condensate oscillation. This reduces the
dynamics to a pair of coupled Boltzmann equations, and we derive explicitly the
form of the collision operators for all particle and condensate interactions.


  Nonlinear state-space identification for dynamical systems is most often
performed by minimizing the simulation error to reduce the effect of model
errors. This optimization problem becomes computationally expensive for large
datasets. Moreover, the problem is also strongly non-convex, often leading to
sub-optimal parameter estimates. This paper introduces a method that
approximates the simulation loss by splitting the data set into multiple
independent sections similar to the multiple shooting method. This splitting
operation allows for the use of stochastic gradient optimization methods which
scale well with data set size and has a smoothing effect on the non-convex cost
function. The main contribution of this paper is the introduction of an encoder
function to estimate the initial state at the start of each section. The
encoder function estimates the initial states using a feed-forward neural
network starting from historical input and output samples. The efficiency and
performance of the proposed state-space encoder method is illustrated on two
well-known benchmarks where, for instance, the method achieves the lowest known
simulation error on the Wiener--Hammerstein benchmark.


  The vacuum of an accelerating observer is defined on the local inertial
frame, which is called a ``moving frame''. However, in the discussion of the
Unruh-deWitt detector, many papers define the vacuum on a fixed frame. This
paper discusses the Unruh-deWitt detector by defining the vacuum directly on
the local inertial frame, showing that the problem of the Stokes phenomenon can
be solved by using the exact WKB.


  In order to reduce the burden on caregivers, we developed an intelligent
electric wheelchair. We held workshops with caregivers, asked then regarding
the problems in caregiving, and developed problem-solving methods. In the
workshop, caregivers' physical fitness and psychology of the older adults were
found to be problems and a solution was proposed. We implemented a cooperative
operation function for multiple electric wheelchairs based on the workshop and
demonstrated it at a nursing home. By listening to older adults, we obtained
feedback on the automatic driving electric wheelchair. From the results of this
study, we discovered the issues and solutions to be applied to the intelligent
electric wheelchair.


  With a computer-aided approach based on the connection with equitable
partitions, we establish the uniqueness of the orthogonal array
OA$(1536,13,2,7)$, constructed in [D.G.Fon-Der-Flaass. Perfect $2$-Colorings of
a Hypercube, Sib. Math. J. 48 (2007), 740-745] as an equitable partition of the
$13$-cube with quotient matrix $[[0,13],[3,10]]$. By shortening the
OA$(1536,13,2,7)$, we obtain $3$ inequivalent orthogonal arrays
OA$(768,12,2,6)$, which is a complete classification for these parameters too.
After our computing, the first parameters of unclassified binary orthogonal
arrays OA$(N,n,2,t)$ attending the Friedman bound $N\ge 2^n(1-n/2(t+1))$ are
OA$(2048,14,2,7)$. Such array can be obtained by puncturing any binary
$1$-perfect code of length $15$. We construct orthogonal arrays with these and
similar parameters OA$(N=2^{n-m+1},n=2^m-2,2,t=2^{m-1}-1)$, $m\ge 4$, that are
not punctured $1$-perfect codes. Additionally, we prove that any orthogonal
array OA$(N,n,2,t)$ with even $t$ attending the bound $N \ge
2^n(1-(n+1)/2(t+2))$ induces an equitable $3$-partition of the $n$-cube.


  The James Webb Space Telescope will revolutionize transiting exoplanet
atmospheric science due to its capability for continuous, long-duration
observations and its larger collecting area, spectral coverage, and spectral
resolution compared to existing space-based facilities. However, it is unclear
precisely how well JWST will perform and which of its myriad instruments and
observing modes will be best suited for transiting exoplanet studies. In this
article, we describe a prefatory JWST Early Release Science (ERS) program that
focuses on testing specific observing modes to quickly give the community the
data and experience it needs to plan more efficient and successful future
transiting exoplanet characterization programs. We propose a multi-pronged
approach wherein one aspect of the program focuses on observing transits of a
single target with all of the recommended observing modes to identify and
understand potential systematics, compare transmission spectra at overlapping
and neighboring wavelength regions, confirm throughputs, and determine overall
performances. In our search for transiting exoplanets that are well suited to
achieving these goals, we identify 12 objects (dubbed "community targets") that
meet our defined criteria. Currently, the most favorable target is WASP-62b
because of its large predicted signal size, relatively bright host star, and
location in JWST's continuous viewing zone. Since most of the community targets
do not have well-characterized atmospheres, we recommend initiating preparatory
observing programs to determine the presence of obscuring clouds/hazes within
their atmospheres. Measurable spectroscopic features are needed to establish
the optimal resolution and wavelength regions for exoplanet characterization.
Other initiatives from our proposed ERS program include testing the instrument
brightness limits and performing phase-curve observations.(Abridged)


  Based on hyperbolic geometric considerations, Roger and Yang introduced an
extension of the Kauffman bracket skein algebra that includes arcs. In
particular, their skein algebra is a deformation quantization of a certain
commutative curve algebra, and there is a Poisson algebra homomorphism between
the curve algebra and the algebra of smooth functions on decorated Teichmuller
space. In this paper, we consider surfaces with punctures which is not the
3-holed sphere and which have an ideal triangulation without self-folded edges
or triangles. For those surfaces, we prove that Roger and Yang's Poisson
algebra homomorphism is injective, and the skein algebra they defined have no
zero divisors. A section about generalized corner coordinates for normal arcs
may be of independent interest.


  Sampling-based model-predictive controllers have become a powerful
optimization tool for planning and control problems in various challenging
environments. In this paper, we show how the default choice of uncorrelated
Gaussian distributions can be improved upon with the use of a colored noise
distribution. Our choice of distribution allows for the emphasis on low
frequency control signals, which can result in smoother and more exploratory
samples. We use this frequency-based sampling distribution with Model
Predictive Path Integral (MPPI) in both hardware and simulation experiments to
show better or equal performance on systems with various speeds of input
response.


  Although wireless and IP-based access to video content gives a new degree of
freedom to the viewers, the risk of severe block losses caused by transmission
errors is always present. The purpose of this paper is to present a new method
for concealing block losses in erroneously received video sequences. For this,
a motion compensated data set is generated around the lost block. Based on this
aligned data set, a model of the signal is created that continues the signal
into the lost areas. Since spatial as well as temporal informations are used
for the model generation, the proposed method is superior to methods that use
either spatial or temporal information for concealment. Furthermore it
outperforms current state of the art spatio-temporal concealment algorithms by
up to 1.4 dB in PSNR.


  In our recent paper entitled "Pairing mechanism of high-temperature
superconductivity: Experimental constraints" (to be published in Physica
Scripta, arXiv:1012.2368), we review some crucial experiments that place strong
constraints on the microscopic pairing mechanism of high-temperature
superconductivity in cuprates. In particular, we show that phonons rather than
spin-fluctuation play a predominant role in the microscopic pairing mechanism.
We further show that the intrinsic pairing symmetry in the bulk is not d-wave,
but extended s-wave (having eight line nodes) in hole-doped cuprates and
nodeless s-wave in electron-doped cuprates. In contrast, the author of the
Comment (to be published in Physica Scripta) argues that our conclusions are
unconvincing and even misleading. In response to the criticisms in the Comment,
we further show that our conclusions are well supported by experiments and his
criticisms are lack of scientific ground.


  We consider models for gamma-ray bursts in which a collimated jet expands
either into a homogeneous medium or into a stellar wind environment, and
calculate the expected afterglow temporal behavior. We show that (i) following
a break and a faster decay, afterglows should exhibit a flattening, which may
be detectable in both the radio and optical bands; (ii) Only observations at
times much shorter than a day can clearly distinguish between a fireball
interacting with a homogeneous medium and one interacting with a stellar wind.
  Using our results we demonstrate that constraints can be placed on progenitor
models. In particular, existing data imply that while some long duration bursts
may be produced by collapses of massive stars, it is almost certain that not
all long duration bursts are produced by such progenitors.


  Ever growing pixel acquisition rates in the fields of augmented reality,
autonomous driving and robotics have increased interest in solid state beam
scanning without moving parts. Modern photonic integrated laser ranging
advances towards passive beam steering solutions. Recently demonstrated imagers
based on focal plane arrays, nanophotonic metasurfaces, and optical phased
arrays enable unprecedented pixel resolution and measurement speed. However,
parallelization of >100 lasers and detectors - successfully implemented in
commercial time-of-flight sensors - has not been widely adopted for passive
scanning approaches. Here, we show both inertia-free and parallel light
detection and ranging (LiDAR) with microresonator frequency combs. We used 40
independent channels of a continuously scanned microresonator frequency comb
operated in the chaotic regime in combination with optical dispersive elements
to perform random modulation LiDAR with 2D passive beam steering.


  News articles typically mention numerous entities, a large fraction of which
are tangential to the story. Detecting the salience of entities in articles is
thus important to applications such as news search, analysis and summarization.
In this work, we explore new approaches for efficient and effective salient
entity detection by fine-tuning pretrained transformer models with
classification heads that use entity tags or contextualized entity
representations directly. Experiments show that these straightforward
techniques dramatically outperform prior work across datasets with varying
sizes and salience definitions. We also study knowledge distillation techniques
to effectively reduce the computational cost of these models without affecting
their accuracy. Finally, we conduct extensive analyses and ablation experiments
to characterize the behavior of the proposed models.


  We present a novel quantum algorithm for estimating Gibbs partition functions
in sublinear time with respect to the logarithm of the size of the state space.
This is the first speed-up of this type to be obtained over the seminal
nearly-linear time algorithm of \v{S}tefankovi\v{c}, Vempala and Vigoda [JACM,
2009]. Our result also preserves the quadratic speed-up in precision and
spectral gap achieved in previous work by exploiting the properties of quantum
Markov chains. As an application, we obtain new polynomial improvements over
the best-known algorithms for computing the partition function of the Ising
model, counting the number of $k$-colorings, matchings or independent sets of a
graph, and estimating the volume of a convex body.
  Our approach relies on developing new variants of the quantum phase and
amplitude estimation algorithms that return nearly unbiased estimates with low
variance and without destroying their initial quantum state. We extend these
subroutines into a nearly unbiased quantum mean estimator that reduces the
variance quadratically faster than the classical empirical mean. No such
estimator was known to exist prior to our work. These properties, which are of
general interest, lead to better convergence guarantees within the paradigm of
simulated annealing for computing partition functions.


  The chiral-odd transversity generalized parton distributions (GPDs) of the
nucleon can be accessed experimentally through the exclusive photoproduction
process gamma + N -> pi + rho + N', in the kinematics where the meson pair has
a large invariant mass and the final nucleon has a small transverse momentum,
provided the vector meson is produced in a transversally polarized state. We
calculate perturbatively the scattering amplitude at leading order in alpha_s.
We build a simple model for the dominant transversity GPD H_T(x,xi, t) based on
the concept of double distribution. We estimate the unpolarized differential
cross section for this process in the kinematics of the Jlab and COMPASS
experiments. Counting rates show that the experiment looks feasible with the
real photon beam characteristics expected at JLab@12 GeV, and with the quasi
real photon beam in the COMPASS experiment.


  Hydrogen atmosphere white dwarfs with metal lines, so-called DAZs, show
evidence for ongoing accretion of material onto their surfaces. Some DAZs are
known to have unresolved M dwarf companions, which could account for the
observed accretion through a stellar wind. I combine observed Ca abundances of
the DAZs with information on the orbital separation of their M dwarf companions
to infer the mass loss rate of the M dwarfs. I find that for three of the six
known DAZs with M dwarf companions, a stellar wind can plausibly explain the
observed accretion on the white dwarfs assuming Bondi-Hoyle accretion of solar
abundance stellar winds on the order of 10$^{-14}-10^{-16}\Msun$ yr$^{-1}$. The
rest of the sample have companions with orbits $\gtorder$ 1~AU, and require
companion mass loss rates of $> 10^{-11}\Msun$ yr$^{-1}$. I conclude that there
must be an alternative explanation for accretion of material onto DAZs with
widely separated companions. The inferred winds for two of the close binaries
are orders of magnitude smaller than typically assumed for the angular momentum
loss of red dwarf-white dwarf pairs due to magnetic braking from a stellar wind
and may seriously affect predictions for the formation rate of CVs with low
mass companions.


  We aim to summarize the current state of knowledge regarding Galactic Faraday
rotation in an all-sky map of the Galactic Faraday depth. For this we have
assembled the most extensive catalog of Faraday rotation data of compact
extragalactic polarized radio sources to date. In the map making procedure we
use a recently developed algorithm that reconstructs the map and the power
spectrum of a statistically isotropic and homogeneous field while taking into
account uncertainties in the noise statistics. This procedure is able to
identify some rotation angles that are offset by an integer multiple of pi. The
resulting map can be seen as an improved version of earlier such maps and is
made publicly available, along with a map of its uncertainty. For the angular
power spectrum we find a power law behavior with a power law index of -2.14 for
a Faraday sky where an overall variance profile as a function of Galactic
latitude has been removed, in agreement with earlier work. We show that this is
in accordance with a 3D Fourier power spectrum P(k) proportional to k^-2.14 of
the underlying field n_e times B_r under simplifying geometrical and
statistical assumptions.


  We evaluated the body wave attenuation parameter in Kopili region of
northeast India. Using the modified algorithm of coda normalization method, we
delineated frequency-dependent attenuation for both P and S waves. Taking more
than 300 seismograms as input, we comprehensively studied microearthquake
spectra in the frequency range of 1.5 to 12 Hz. The estimated values of
$Q_P^{-1}$ and $Q_S^{-1}$ show strong frequency dependence. The relationships
emerge to be $Q_P^{-1}=(23.8\pm 6)\times10^{-3}f^{-1.2\pm 0.008}$ and
$Q_S^{-1}=(10.2\pm 2)\times10^{-3}f^{-1.3\pm 0.02}$, respectively. The ratio
$Q_P^{-1}/Q_S^{-1}$ is found to be larger than unity for the entire frequency
band which implies profound seismic activity and macroscale heterogeneity
prevailing in the region. The study may act as the building block towards
determination of source parameter and hazard related studies in the region.


  We address an important gap in detecting political bias in news articles.
Previous works that perform document classification can be influenced by the
writing style of each news outlet, leading to overfitting and limited
generalizability. Our approach overcomes this limitation by considering both
the sentence-level semantics and the document-level rhetorical structure,
resulting in a more robust and style-agnostic approach to detecting political
bias in news articles. We introduce a novel multi-head hierarchical attention
model that effectively encodes the structure of long documents through a
diverse ensemble of attention heads. While journalism follows a formalized
rhetorical structure, the writing style may vary by news outlet. We demonstrate
that our method overcomes this domain dependency and outperforms previous
approaches for robustness and accuracy. Further analysis and human evaluation
demonstrate the ability of our model to capture common discourse structures in
journalism. Our code is available at:
https://github.com/xfactlab/emnlp2023-Document-Hierarchy


  For the solution of linear discrete ill-posed problems, in this paper we
consider the Arnoldi-Tikhonov method coupled with the Generalized Cross
Validation for the computation of the regularization parameter at each
iteration. We study the convergence behavior of the Arnoldi method and its
properties for the approximation of the (generalized) singular values, under
the hypothesis that Picard condition is satisfied. Numerical experiments on
classical test problems and on image restoration are presented.


  We introduce CRASH-AMR, a new version of the cosmological Radiative Transfer
(RT) code CRASH, enabled to use refined grids. This new feature allows us to
attain higher resolution in our RT simulations and thus to describe more
accurately ionisation and temperature patterns in high density regions. We have
tested CRASH-AMR by simulating the evolution of an ionised region produced by a
single source embedded in gas at constant density, as well as by a more
realistic configuration of multiple sources in an inhomogeneous density field.
While we find an excellent agreement with the previous version of CRASH when
the AMR feature is disabled, showing that no numerical artifact has been
introduced in CRASH-AMR, when additional refinement levels are used the code
can simulate more accurately the physics of ionised gas in high density
regions. This result has been attained at no computational loss, as RT
simulations on AMR grids with maximum resolution equivalent to that of a
uniform cartesian grid can be run with a gain of up to 60% in computational
time.


  This paper investigate on numerical analysis on modified Single-layer
approach to exterior Dirichlet problem of Laplace equation. We complete the
convergence and error analysis of Petrov-Galerkin and Galerkin-Collocation
methods with trigonometric basis for the induced modified Symm's integral
equation of the first kind on analytic boundary. Besides, utilizing the
composite trapezial quadrature formula and trigonometric interpolation to
handle the singularity in modified logarithmic kernel, we establish the
numerical procedure for implementation. On these numerical examples, we compare
the effect and efficiency of different Petrov-Galerkin and Galerkin-Collocation
methods.


  We discuss the role of some nonpartonic effects which lead to $N_p^{\pi^+}
\ne N_n^{\pi^+}$ and $N_p^{\pi^-} \ne N_n^{\pi^-}$ and may therefore modify the
conclusionon the $\bar d - \bar u$ asymmetry extracted from semi-inclusive
production of pions in DIS. Quantitative estimations for resolved photon and
exclusive $\rho^0$ are given as examples. The results are discussed in the
context of recent HERMES data.


  Our motivation in this paper is twofold. First, we study the geometry of a
class of exploration sets, called exit sets, which are naturally associated
with a 2D vector-valued GFF : $\phi : Z^2 \to R^N, N\geq 1$. We prove that,
somewhat surprisingly, these sets are a.s. degenerate as long as $N\geq 2$,
while they are conjectured to be macroscopic and fractal when $N=1$.
  This analysis allows us, when $N\geq 2$, to understand the percolation
properties of the level sets of $\{\|\phi(x)\|, x\in Z^2\}$ and leads us to our
second main motivation in this work: if one projects a spin $O(N+1)$ model
(classical Heisenberg model is $N=2$) down to a spin $O(N)$ model, we end up
with a spin $O(N)$ in a quenched disorder given by random conductances on
$Z^2$. Using the exit sets of the $N$-vector-valued GFF, we obtain a local and
geometric description of this random disorder in the limit $\beta\to \infty$.
This allows us to revisit a series of celebrated works by Patrascioiu and
Seiler ([PS92, PS93, PS02]) which argued against Polyakov's prediction that
spin $O(N+1)$ model is massive at all temperatures when $N\geq 2$ ([Pol75]). We
make part of their arguments rigorous and more importantly we provide the
following counter-example: we build ergodic environments of (arbitrary) high
conductances with (arbitrary) small and disconnected regions of low
conductances in which, despite the predominance of high conductances, the $XY$
model remains massive.
  Of independent interest, we prove that at high $\beta$, the transverse
fluctuations of a classical Heisenberg model are given by a $N=2$ vectorial
GFF. This is implicit in [Pol75] but we give here the first (non-trivial)
rigorous proof. Also, independently of the recent work [DF22], we show that
two-point correlation functions of the spin $O(N)$ model are given in terms of
certain percolation events in the cable graph for any $N\geq 1$.


  In this paper, two new classes of convex functions as a generalization of
convexity which is called (h-s)_{1,2}-convex functions are given. We also prove
some Hadamard-type inequalities and applications to the special means are
given.


  We have examined Faint Object Spectrograph data from the Hubble Space
Telescope Archive for CIV 1548,1550 absorption associated with 40 MgII
2796,2803 absorption-selected galaxies at 0.4 < z < 1.4. We report a strong
correlation between MgII kinematics, measured in 6 km/s resolution HIRES/Keck
spectra, and W_r(1548); this implies a physical connection between the
processes that produce "outlying velocity" MgII clouds and high ionization
galactic/halo gas. We found no trend in ionization condition,
W_r(1548)/W_r(2796), with galaxy-QSO line-of-sight separation for 13 systems
with confirmed associated galaxies, suggesting no obvious ionization gradient
with galactocentric distance in these higher redshift galaxies. We find
tentative evidence (2-sigma) that W_r(1548)/W_r(2796) is anti-correlated with
galaxy <B-K> color; if further data corroborate this trend, in view of the
strong CIV-MgII kinematics correlation, it could imply a connection between
stellar populations, star formation episodes, and the kinematics and ionization
conditions of halo gas at z~1.


  We study the hairy graph homology of a cyclic operad; in particular we show
how to assemble corresponding hairy graph cohomology classes to form cocycles
for ordinary graph homology, as defined by Kontsevich. We identify the part of
hairy graph homology coming from graphs with cyclic fundamental group as the
dihedral homology of a related associative algebra with involution. For the
operads Comm, Assoc and Lie we compute this algebra explicitly, enabling us to
apply known results on dihedral homology to the computation of hairy graph
homology. In addition we determine the image in hairy graph homology of the
trace map defined in [CKV], as a symplectic representation.
  For the operad Lie assembling hairy graph cohomology classes yields all known
non-trivial rational homology of Out(F_n). The hairy graph homology of Lie is
also useful for constructing elements of the cokernel of the Johnson
homomomorphism of a once-punctured surface.


  We investigate several problems in entanglement theory from the perspective
of convex optimization. This list of problems comprises (A) the decision
whether a state is multi-party entangled, (B) the minimization of expectation
values of entanglement witnesses with respect to pure product states, (C) the
closely related evaluation of the geometric measure of entanglement to quantify
pure multi-party entanglement, (D) the test whether states are multi-party
entangled on the basis of witnesses based on second moments and on the basis of
linear entropic criteria, and (E) the evaluation of instances of maximal output
purities of quantum channels. We show that these problems can be formulated as
certain optimization problems: as polynomially constrained problems employing
polynomials of degree three or less. We then apply very recently established
known methods from the theory of semi-definite relaxations to the formulated
optimization problems. By this construction we arrive at a hierarchy of
efficiently solvable approximations to the solution, approximating the exact
solution as closely as desired, in a way that is asymptotically complete. For
example, this results in a hierarchy of novel, efficiently decidable sufficient
criteria for multi-particle entanglement, such that every entangled state will
necessarily be detected in some step of the hierarchy. Finally, we present
numerical examples to demonstrate the practical accessibility of this approach.


  We address the issue of extending thermodynamics to nonequilibrium steady
states. Using driven stochastic lattice gases, we ask whether consistent
definitions of an effective chemical potential mu, and an effective temperature
T_e, are possible. mu and T_e are determined via coexistence, i.e., zero flux
of particles and energy between the driven system and a reservoir. In the
lattice gas with nearest-neighbor exclusion, temperature is not relevant, and
we find that the effective chemical potential, a function of density and drive
strength, satisfies the zeroth law, and correctly predicts the densities of
coexisting systems. In the Katz-Lebowitz-Spohn driven lattice gas both mu and
T_e need to be defined. We show analytically that in this case the zeroth law
is violated for Metropolis exchange rates, and determine the size of the
violations numerically. The zeroth law appears to be violated for generic
exchange rates. Remarkably, the system-reservoir coupling proposed by Sasa and
Tasaki [J. Stat. Phys. 125, 125 (2006)], is free of inconsistencies, and the
zeroth law holds. This is because the rate depends only on the state of the
donor system, and is independent of that of the acceptor.


  The basic concepts and predictions of the `dynamical' GRV parton
distributions for hadrons and photons are discussed. Comparisons of these
predictions with recent experimental results, especially from HERA, are
presented.


  The application of 3D ground-penetrating radar (3D-GPR) for subgrade distress
detection has gained widespread popularity. To enhance the efficiency and
accuracy of detection, pioneering studies have attempted to adopt automatic
detection techniques, particularly deep learning. However, existing works
typically rely on traditional 1D A-scan, 2D B-scan or 3D C-scan data of the
GPR, resulting in either insufficient spatial information or high computational
complexity. To address these challenges, we introduce a novel methodology for
the subgrade distress detection task by leveraging the multi-view information
from 3D-GPR data. Moreover, we construct a real multi-view image dataset
derived from the original 3D-GPR data for the detection task, which provides
richer spatial information compared to A-scan and B-scan data, while reducing
computational complexity compared to C-scan data. Subsequently, we develop a
novel \textbf{M}ulti-\textbf{V}iew \textbf{V}usion and \textbf{D}istillation
framework, \textbf{GPR-MVFD}, specifically designed to optimally utilize the
multi-view GPR dataset. This framework ingeniously incorporates multi-view
distillation and attention-based fusion to facilitate significant feature
extraction for subgrade distresses. In addition, a self-adaptive learning
mechanism is adopted to stabilize the model training and prevent performance
degeneration in each branch. Extensive experiments conducted on this new GPR
benchmark demonstrate the effectiveness and efficiency of our proposed
framework. Our framework outperforms not only the existing GPR baselines, but
also the state-of-the-art methods in the fields of multi-view learning,
multi-modal learning, and knowledge distillation. We will release the
constructed multi-view GPR dataset with expert-annotated labels and the source
codes of the proposed framework.


  Classification performance based on ImageNet is the de-facto standard metric
for CNN development. In this work we challenge the notion that CNN architecture
design solely based on ImageNet leads to generally effective convolutional
neural network (CNN) architectures that perform well on a diverse set of
datasets and application domains. To this end, we investigate and ultimately
improve ImageNet as a basis for deriving such architectures. We conduct an
extensive empirical study for which we train $500$ CNN architectures, sampled
from the broad AnyNetX design space, on ImageNet as well as $8$ additional well
known image classification benchmark datasets from a diverse array of
application domains. We observe that the performances of the architectures are
highly dataset dependent. Some datasets even exhibit a negative error
correlation with ImageNet across all architectures. We show how to
significantly increase these correlations by utilizing ImageNet subsets
restricted to fewer classes. These contributions can have a profound impact on
the way we design future CNN architectures and help alleviate the tilt we see
currently in our community with respect to over-reliance on one dataset.


  We present results for two different kinds of high order connections between
neurons acting as corrections to the Hopfield model. Equilibrium properties are
analyzed using the replica mean-field theory and compared with numerical
simulations. An optimal learning algorithm for fourth order connections is
given that improves the storage capacity without increasing the weight of the
higher order term. While the behavior of one of the models qualitatively
resembles the original Hopfield one, the other presents a new and very rich
behavior: depending on the strength of the fourth order connections and the
temperature, the system presents two distinct retrieval regions separated by a
gap, as well as several phase transitions. Also, the spin glass states seems to
disappear above a certain value of the load parameter $\alpha$, $\alpha_g$.


  SETI@home, a search for signals from extraterrestrial intelligence, has been
recording data at the Arecibo radio telescope since 1999. These data are sent
via the Internet to the personal computers of volunteers who have donated their
computers' idle time toward this search. To date, SETI@home volunteers have
detected more than 4.2 billion potential signals. While essentially all of
these potential signals are due to random noise processes, radio frequency
interference (RFI), or interference processes in the SETI@home instrumentation,
it is possible that a true extraterrestrial transmission exists within this
database. Herein we describe the process of interference removal being
implemented in the SETI@home post-processing pipeline, as well as those methods
being used to identify candidates worthy of further investigation.


  Multiple hypothesis testing is a significant problem in nearly all
neuroimaging studies. In order to correct for this phenomena, we require a
reliable estimate of the Family-Wise Error Rate (FWER). The well known
Bonferroni correction method, while simple to implement, is quite conservative,
and can substantially under-power a study because it ignores dependencies
between test statistics. Permutation testing, on the other hand, is an exact,
non-parametric method of estimating the FWER for a given $\alpha$-threshold,
but for acceptably low thresholds the computational burden can be prohibitive.
In this paper, we show that permutation testing in fact amounts to populating
the columns of a very large matrix ${\bf P}$. By analyzing the spectrum of this
matrix, under certain conditions, we see that ${\bf P}$ has a low-rank plus a
low-variance residual decomposition which makes it suitable for highly
sub--sampled --- on the order of $0.5\%$ --- matrix completion methods. Based
on this observation, we propose a novel permutation testing methodology which
offers a large speedup, without sacrificing the fidelity of the estimated FWER.
Our evaluations on four different neuroimaging datasets show that a
computational speedup factor of roughly $50\times$ can be achieved while
recovering the FWER distribution up to very high accuracy. Further, we show
that the estimated $\alpha$-threshold is also recovered faithfully, and is
stable.


  The empirical upper luminosity boundary $L_{\rm max}$ of cool supergiants,
often referred to as the Humphreys-Davidson limit, is thought to encode
information on the general mass-loss behaviour of massive stars. Further, it
delineates the boundary at which single stars will end their lives stripped of
their hydrogen-rich envelope, which in turn is a key factor in the relative
rates of Type-II to Type-Ibc supernovae from single star channels. In this
paper we have revisited the issue of $L_{\rm max}$ by studying the luminosity
distributions of cool supergiants (SGs) in the Large and Small Magellanic
Clouds (LMC/SMC). We assemble samples of cool SGs in each galaxy which are
highly-complete above $\log L/L_{\odot}$=5.0, and determine their spectral
energy distributions from the optical to the mid-infrared using modern
multi-wavelength survey data. We show that in both cases $L_{\rm max}$ appears
to be lower than previously quoted, and is in the region of $\log
L/L_{\odot}$=5.5. There is no evidence for $L_{\rm max}$ being higher in the
SMC than in the LMC, as would be expected if metallicity-dependent winds were
the dominant factor in the stripping of stellar envelopes. We also show that
$L_{\rm max}$ aligns with the lowest luminosity of single nitrogen-rich
Wolf-Rayet stars, indicating of a change in evolutionary sequence for stars
above a critical mass. From population synthesis analysis we show that the
Geneva evolutionary models greatly over-predict the numbers of cool SGs in the
SMC. We also argue that the trend of earlier average spectral types of cool SGs
in lower metallicity environments represents a genuine shift to hotter
temperatures. Finally, we use our new bolometric luminosity measurements to
provide updated bolometric corrections for cool supergiants.


  Models of inflation with antisymmetric tensor studied in the past are plagued
with ghost instability even in an unperturbed FRW background. We show that it
is possible to avoid ghosts in an unperturbed FRW background by considering the
most general kinetic term for antisymmetric tensor field. The kinetic part
acquires a new gauge symmetry violating term whose effect on perturbed modes is
to prevent the appearance of nondynamical modes, and thus avoid ghosts. For
completeness, we perform a check for gradient instability and derive the
conditions for perturbations to be free of gradient instability.


  In clinical radiology reports, doctors capture important information about
the patient's health status. They convey their observations from raw medical
imaging data about the inner structures of a patient. As such, formulating
reports requires medical experts to possess wide-ranging knowledge about
anatomical regions with their normal, healthy appearance as well as the ability
to recognize abnormalities. This explicit grasp on both the patient's anatomy
and their appearance is missing in current medical image-processing systems as
annotations are especially difficult to gather. This renders the models to be
narrow experts e.g. for identifying specific diseases. In this work, we recover
this missing link by adding human anatomy into the mix and enable the
association of content in medical reports to their occurrence in associated
imagery (medical phrase grounding). To exploit anatomical structures in this
scenario, we present a sophisticated automatic pipeline to gather and integrate
human bodily structures from computed tomography datasets, which we incorporate
in our PAXRay: A Projected dataset for the segmentation of Anatomical
structures in X-Ray data. Our evaluation shows that methods that take advantage
of anatomical information benefit heavily in visually grounding radiologists'
findings, as our anatomical segmentations allow for up to absolute 50% better
grounding results on the OpenI dataset as compared to commonly used region
proposals. The PAXRay dataset is available at
https://constantinseibold.github.io/paxray/.


  Spin-crossover molecules having a low-spin ground state and a low-lying
excited high-spin state are promising components for molecular electronics. We
theoretically examine one-dimensional spin-crossover chain molecules of the
type of Fe-II triazole complexes. The existence of the additional
low-spin/high-spin degree of freedom leads to rich behavior already in the
ground state. We obtain the complete ground-state phase diagram, taking into
account an elastic nearest-neighbor interaction, a ferromagnetic or
antiferromagnetic exchange interaction between the magnetic ions, and an
external magnetic field. Ground-state energies are calculated with high
numerical precision using the density-matrix renormalization group. Besides
pure low-spin, highspin, and alternating low-spin/high-spin phases we obtain a
number of periodic ground states with longer periods, which we discuss in
detail. For example, for antiferromagnetic coupling there exists a dimer phase
with a magnetic unit cell containing two high-spin ions forming a spin singlet
and a single low-spin ion, which is stabilized by the energy gain for singlet
formation.


  The paper presents a detailed description of the K-theory and K-homology of
C*-algebras generated by q-normal operators including generators and the index
pairing. The C*-algebras generated by q-normal operators can be viewed as a
q-deformation of the quantum complex plane. In this sense, we find deformations
of the classical Bott projections describing complex line bundles over the
2-sphere, but there are also simpler generators for the K_0-groups, for
instance 1-dimensional Powers-Rieffel type projections and elementary
projections belonging to the C*-algebra. The index pairing between these
projections and generators of the even K-homology group is computed, and the
result is used to express the K_0-classes of the quantized line bundles of any
winding number in terms of the other projections.


  The Burrows-Wheeler Transform (BWT) is an important technique both in data
compression and in the design of compact indexing data structures. It has been
generalized from single strings to collections of strings and some classes of
labeled directed graphs, such as tries and de Bruijn graphs. The BWTs of
repetitive datasets are often compressible using run-length compression, but
recently Baier (CPM 2018) described how they could be even further compressed
using an idea he called tunneling. In this paper we show that tunneled BWTs can
still be used for indexing and extend tunneling to the BWTs of Wheeler graphs,
a framework that includes all the generalizations mentioned above.


  In this paper, we investigate an alternative formulation for spin 3/2 field
equation. First we will review equation of motion of Dirac and Maxwell, and
then construct the equation for spin 3/2 in the similar fashion. Our method
actually a generalization of relativistic equation of motion based on spin
operator and Hamiltonian similar to Dirac and Maxwell equation in ref. [1] pp.
50. Furthermore, we could not bring the equation to the Klein Gordon limit for
every wave function component in spin 3/2 formalism.


  Initial population plays an important role in heuristic algorithms such as GA
as it help to decrease the time those algorithms need to achieve an acceptable
result. Furthermore, it may influence the quality of the final answer given by
evolutionary algorithms. In this paper, we shall introduce a heuristic method
to generate a target based initial population which possess two mentioned
characteristics. The efficiency of the proposed method has been shown by
presenting the results of our tests on the benchmarks.


  We study by exact diagonalization the two-dimensional t-J-Holstein model near
quarter filling by retaining only few phonon modes in momentum space. This
truncation allows us to incorporate the full dynamics of the retained phonon
modes. The behavior of the kinetic energy, the charge structure factor and
other physical quantities, show the presence of a transition from a delocalized
phase to a localized phase at a finite value of the electron-phonon coupling.
We have also given some indications that the e-ph coupling leads in general to
a suppression of the pairing susceptibility at quarter filling.


  As a serious attempt for constructing a new foundation for describing
micro-entities from a causal standpoint, it was explained before in [1, 2, 3]
that by unifying the concepts of information, matter and energy, each
micro-entity is assumed to be composed of a probability field joined to a
particle called a particle-field or PF system. In this essay, the relativistic
generalization of the PF theory has been considered. The equation of motion for
the PF system is derived in a form which is Lorentz-invariant. Moreover, based
on constitutional similarities to classical equations of motion, a well-defined
relativistic time-independent Schrodinger equation is derived, which is one of
our main achievements in developing a micro-relativistic physics of PF theory.
This relativistic Schrodinger equation is solved for a relativistic
micro-particle in one-dimensional box to find its eigenstate and energy
spectrum.


  Video captioning is one of the challenging problems at the intersection of
vision and language, having many real-life applications in video retrieval,
video surveillance, assisting visually challenged people, Human-machine
interface, and many more. Recent deep learning based methods have shown
promising results but are still on the lower side than other vision tasks (such
as image classification, object detection). A significant drawback with
existing video captioning methods is that they are optimized over cross-entropy
loss function, which is uncorrelated to the de facto evaluation metrics (BLEU,
METEOR, CIDER, ROUGE). In other words, cross-entropy is not a proper surrogate
of the true loss function for video captioning. To mitigate this, methods like
REINFORCE, Actor-Critic, and Minimum Risk Training (MRT) have been applied but
have limitations and are not very effective. This paper proposes an alternate
solution by introducing a dynamic loss network (DLN), providing an additional
feedback signal that reflects the evaluation metrics directly. Our solution
proves to be more efficient than other solutions and can be easily adapted to
similar tasks. Our results on Microsoft Research Video Description Corpus
(MSVD) and MSR-Video to Text (MSRVTT) datasets outperform previous methods.


  Sound wave propagation in a relativistic perfect fluid with a non-homogeneous
isentropic flow is studied in terms of acoustic geometry. The sound wave
equation turns out to be equivalent to the equation of motion for a massless
scalar field propagating in a curved space-time geometry. The geometry is
described by the acoustic metric tensor that depends locally on the equation of
state and the four-velocity of the fluid. For a relativistic supersonic flow in
curved space-time the ergosphere and acoustic horizon may be defined in a way
analogous the non-relativistic case. A general-relativistic expression for the
acoustic analog of surface gravity has been found.


  In simple models of the Milky Way, tidally disrupting satellites produce long
and thin---nearly one-dimensional---stellar streams. Using astrometric data
from the Gaia second data release and photometry from the Dark Energy Survey,
we demonstrate that the Jhelum stream, a stellar stream in the inner halo, is a
two-dimensional structure. The spatial distribution of highly probable Jhelum
members reveals a dense thin component and an associated diffuse, spatially
offset component. These two spatial components have indistinguishable proper
motions (at $\sigma\sim1\,\rm mas\,yr^{-1}$ level) and a similar ratio of blue
straggler to blue horizontal branch stars, which indicates a common origin for
the two components. The best-fit orbit to the narrow component (pericenter
$8\,\rm kpc$, apocenter $24\,\rm kpc$), however, does not explain the wide
component of the Jhelum stream. On the other hand, an older orbital wrap of
Jhelum's orbit traces the Indus stream, indicating a possible connection
between these two structures and additional complexity in Jhelum's formation.
Substructure in the Jhelum progenitor or precession of its tidal debris in the
Milky Way potential may explain the observed structure of Jhelum. Future
spectroscopic data will enable discrimination between these "nature" and
"nurture" formation scenarios. Jhelum adds to the growing list of cold stellar
streams that display complex morphologies and promise to reveal the dynamical
history of the Milky Way.


  We study analytic and arithmetic properties of the elliptic gamma function $$
\prod_{m,n=0}^\infty\frac{1-x^{-1}q^{m+1}p^{n+1}}{1-xq^mp^n}, \qquad |q|,|p|<1,
$$ in the regime $p=q$; in particular, its connection with the elliptic
dilogarithm and a formula of S. Bloch. We further extend the results to more
general products by linking them to non-holomorphic Eistenstein series and, via
some formulae of D. Zagier, to elliptic polylogarithms.


  We describe a general method of obtaining the constraints between area
variables in one approach to area Regge calculus, and illustrate it with a
simple example. The simplicial complex is the simplest tessellation of the
4-sphere. The number of independent constraints on the variations of the
triangle areas is shown to equal the difference between the numbers of
triangles and edges, and a general method of choosing independent constraints
is described. The constraints chosen by using our method are shown to imply the
Regge equations of motion in our example.


  We provide a relation between the geometric framework for $q$-Painlev\'{e}
equations and cluster Poisson varieties by using toric models of rational
surfaces associated with $q$-Painlev\'{e} equations. We introduce the notion of
seeds of $q$-Painlev\'{e} type by the negative semi-definiteness of symmetric
bilinear forms associated with seeds, and classify the mutation equivalence
classes of these seeds. This classification coincides with the classification
of $q$-Painlev\'{e} equations given by Sakai. We realize $q$-Painlev\'{e}
systems as automorphisms on cluster Poisson varieties associated with seeds of
$q$-Painlev\'{e} type.


  We propose a method for multiple hypothesis testing with familywise error
rate (FWER) control, called the i-FWER test. Most testing methods are
predefined algorithms that do not allow modifications after observing the data.
However, in practice, analysts tend to choose a promising algorithm after
observing the data; unfortunately, this violates the validity of the
conclusion. The i-FWER test allows much flexibility: a human (or a computer
program acting on the human's behalf) may adaptively guide the algorithm in a
data-dependent manner. We prove that our test controls FWER if the analysts
adhere to a particular protocol of "masking" and "unmasking". We demonstrate
via numerical experiments the power of our test under structured non-nulls, and
then explore new forms of masking.


  To quantify how well theoretical predictions of structural ensembles agree
with experimental measurements, we depend on the accuracy of forward models.
These models are computational frameworks that generate observable quantities
from molecular configurations based on empirical relationships linking specific
molecular properties to experimental measurements. Bayesian Inference of
Conformational Populations (BICePs) is a reweighting algorithm that reconciles
simulated ensembles with ensemble-averaged experimental observations, even when
such observations are sparse and/or noisy. This is achieved by sampling the
posterior distribution of conformational populations under experimental
restraints as well as sampling the posterior distribution of uncertainties due
to random and systematic error. In this study, we enhance the algorithm for the
refinement of empirical forward model (FM) parameters. We introduce and
evaluate two novel methods for optimizing FM parameters. The first method
treats FM parameters as nuisance parameters, integrating over them in the full
posterior distribution. The second method employs variational minimization of a
quantity called the BICePs score that reports the free energy of `turning on`
the experimental restraints. This technique, coupled with improved likelihood
functions for handling experimental outliers, facilitates force field
validation and optimization, as illustrated in recent studies (Raddi et al.
2023, 2024). Using this approach, we refine parameters that modulate the
Karplus relation, crucial for accurate predictions of J-coupling constants
based on dihedral angles between interacting nuclei. We validate this approach
first with a toy model system, and then for human ubiquitin, predicting six
sets of Karplus parameters. This approach, which does not rely on predetermined
parameters, enhances predictive accuracy and can be used for many applications.


  Leavitt path algebras of bi-separated graphs have been recently introduced by
R. Mohan and B. Suhas. These algebras provide a common framework for studying
various generalisations of Leavitt path algebras. In this paper we obtain
modules for the Leavitt path algebra $L(\dot E)$ of a finitely bi-separated
graph $\dot{E}=(E,C,D)$ by introducing the notion of a representation graph for
$\dot{E}$. Among these modules we find a class of simple modules. If the
bi-separation on $E$ is the Cuntz-Krieger bi-separation (and hence $L(\dot{E})$
is isomorphic to the usual Leavitt path algebra $L(E)$), one recovers the
celebrated Chen simple modules.


  We present a methodology for parallel acceleration of learning in the
presence of matrix orthogonality and unitarity constraints of interest in
several branches of machine learning. We show how an apparently sequential
elementary rotation parametrization can be restructured into blocks of
commutative operations using a well-known tool for coloring the edges of
complete graphs, in turn widely applied to schedule round-robin
(all-against-all) sports tournaments. The resulting decomposition admits an
algorithm to compute a fully-parametrized orthogonal matrix from its rotation
parameters in $O(n)$ sequential steps and one to compute the gradient of a
training loss with respect to its parameters in $O(n\log n)$ steps. We discuss
parametric restrictions of interest to generative modeling and present
promising performance results with a prototype GPU implementation.


  In the first part we analyze space $\mathcal G^*(\mathbb R^{n}_+)$ and its
dual through Laguerre expansions when these spaces correspond to a general
sequence $\{M_p\}_{p\in\mathbb N_0}$, where $^*$ is a common notation for the
Beurling and Roumieu cases of spaces. In the second part we are solving
equation of the form $Lu=f,\; L=\sum_{j=1}^ka_jA_j^{h_j}+cE^{d}_y+bP(x,D_x),$
where $f$ belongs to the tensor product of ultradistribution spaces over
compact manifolds without boundaries as well as ultradistribution spaces on
$\mathbb R^n_+$ and $\mathbb R^m$; $A_j, j=1,...,k$, $E_y$ and $P(x,D_x)$ are
operators whose eigenfunctions form orthonormal basis of corresponding
$L^2-$space. The sequence space representation of solutions enable us to study
the solvability and the hypoellipticity in the specified spaces of
ultradistributions.


  Complex network theory is a useful way to study many real systems. In this
paper, an anti-attack model based on complex network theory is introduced. The
mechanism of this model is based on dynamic compensation process and reverse
percolation process in P2P networks. The main purpose of the paper is: (i) a
dynamic compensation process can turn an attacked P2P network into a power-law
(PL) network with exponential cutoff; (ii) a local healing process can restore
the maximum degree of peers in an attacked P2P network to a normal level; (iii)
a restoring process based on reverse percolation theory connects the
fragmentary peers of an attacked P2P network together into a giant connected
component. In this way, the model based on complex network theory can be
effectively utilized for anti-attack and protection purposes in P2P networks.


  A two-fluid model developed originally to describe wave oscillations in the
vacuum arc centrifuge, a cylindrical, rapidly rotating, low temperature and
confined plasma column, is applied to interpret plasma oscillations in a RF
generated linear magnetised plasma (WOMBAT), with similar density and field
strength. Compared to typical centrifuge plasmas, WOMBAT plasmas have slower
normalised rotation frequency, lower temperature and lower axial velocity.
Despite these differences, the two-fluid model provides a consistent
description of the WOMBAT plasma configuration and yields qualitative agreement
between measured and predicted wave oscillation frequencies with axial field
strength. In addition, the radial profile of the density perturbation predicted
by this model is consistent with the data. Parameter scans show that the
dispersion curve is sensitive to the axial field strength and the electron
temperature, and the dependence of oscillation frequency with electron
temperature matches the experiment. These results consolidate earlier claims
that the density and floating potential oscillations are a resistive drift
mode, driven by the density gradient. To our knowledge, this is the first
detailed physics model of flowing plasmas in the diffusion region away from the
RF source. Possible extensions to the model, including temperature
non-uniformity and magnetic field oscillations, are also discussed.


  We elucidate why the 1-Wasserstein distance $W_1$ coincides with the area
between the two marginal cumulative distribution functions (CDFs). We first
describe the Wasserstein distance in terms of copulas, and then show that $W_1$
with the Euclidean distance is attained with the $M$ copula. Two random
variables whose dependence is given by the $M$ copula manifest perfect
(positive) dependence. If we express the random variables in terms of their
CDFs, it is intuitive to see that the distance between two such random
variables coincides with the area between the two CDFs.


  Deep Neural Networks (DNNs) have been successfully implemented across various
signal processing fields, resulting in significant enhancements in performance.
However, DNNs generally require substantial computational resources, leading to
significant economic costs and posing challenges for their deployment on
resource-constrained edge devices. In this study, we take advantage of spiking
neural networks (SNNs) and quantization technologies to develop an
energy-efficient and lightweight neuromorphic signal processing system. Our
system is characterized by two principal innovations: a threshold-adaptive
encoding (TAE) method and a quantized ternary SNN (QT-SNN). The TAE method can
efficiently encode time-varying analog signals into sparse ternary spike
trains, thereby reducing energy and memory demands for signal processing.
QT-SNN, compatible with ternary spike trains from the TAE method, quantifies
both membrane potentials and synaptic weights to reduce memory requirements
while maintaining performance. Extensive experiments are conducted on two
typical signal-processing tasks: speech and electroencephalogram recognition.
The results demonstrate that our neuromorphic signal processing system achieves
state-of-the-art (SOTA) performance with a 94% reduced memory requirement.
Furthermore, through theoretical energy consumption analysis, our system shows
7.5x energy saving compared to other SNN works. The efficiency and efficacy of
the proposed system highlight its potential as a promising avenue for
energy-efficient signal processing.


  We estimate the bulk Lorentz factor Gamma_0 of 31 GRBs using the measured
peak time of their afterglow light curves. We consider two possible scenarios
for the estimate of Gamma_0: the case of a homogeneous circumburst medium or a
wind density profile. The values of Gamma_0 are broadly distributed between few
tens and several hundreds with average values ~138 and ~66 for the homogeneous
and wind density profile, respectively. We find that the isotropic energy and
luminosity correlate in a similar way with Gamma_0, i.e. Eiso Gamma_0^2 and
Liso Gamma_0^2, while the peak energy Epeak Gamma_0. These correlations are
less scattered in the wind density profile than in the homogeneous case. We
then study the energetics, luminosities and spectral properties of our bursts
in their comoving frame. The distribution of Liso' is very narrow with a
dispersion of less than a decade in the wind case, clustering around
Liso'=5x10^48 erg/s. Peak photon energies cluster around Epeak'=6 keV. The
newly found correlations involving Gamma_0 offer a general interpretation
scheme for the spectral-energy correlations of GRBs. The Epeak-Eiso and
Epeak-Liso correlations are due to the different Gamma_0 factors and the
collimation-corrected correlation, Epeak-Egamma (obtained by correcting the
isotropic quantities for the jet opening angle theta_j), can be explained if
theta_j^2*Gamma_0=constant. Assuming the Epeak-Egamma correlation as valid, we
find a typical value of theta_j*Gamma_0 ~ 6-20, in agreement with the
predictions of magnetically accelerated jet models.


  Elliptical galaxies have dynamically hot ($\sigma_{1D}$ ~ 100 -- 300 km
s$^{-1}$) populations of stars, and presumably, smaller objects like comets.
Because interstellar minor bodies are moving much faster, they hit planets
harder and more often than in the local Galaxy. I estimate the rates for
Chicxulub-scale impacts on an Earth-size planet in elliptical galaxies as a
potential habitability constraint on intelligent life. Around most stars in a
normal elliptical galaxy, these planets receive only ~0.01 -- 0.1 Gyr$^{-1}$,
although hazardous rates may be common in certain compact early-type galaxies
and red nuggets. About 5% of the stellar mass is in a region where the rate is
>10 Gyr$^{-1}$, large enough to dominate the mass extinction rate. This
suggests that elliptical galaxies have an exclusion zone of order one hundred
parsecs in radius around their centers for the evolution of intelligent life.


  Based on a dynamic systems approach to the Landau-Ginzburg model, a phase
space description of the Earth System (ES) in the transition to the
Anthropocene is presented. It is shown that, for a finite amount of
human-driven change, there is a stable equilibrium state that is an attractor
of trajectories in the system's phase space and corresponds to a Hothouse Earth
scenario. Using the interaction between the components of the ES, it is argued
that, through the action of the Technosphere, mitigation strategies might arise
for which the deviation of the ES temperature from the Holocene average
temperature is smaller.


  Quantum entanglement generation is generally known to be impossible by any
classical means. According to Poisson statistics, coherent photons are not
considered quantum particles due to the bunching phenomenon. Recently, a
coherence approach has been applied to interpret quantum features such as the
Hong-Ou-Mandel (HOM) effect, Franson-type nonlocal correlation, and
delayed-choice quantum eraser, where the quantum feature is due to
basis-product superposition at the cost of 50 % photon loss. For this, it has
been understood that a fixed sum-phase relation between paired photons is the
bedrock of quantum entanglement. Here, coherently driven quantum features of
the HOM effects are presented using linear optics-based polarization-basis
control. Like quantum operator-based destructive interference in the HOM
theory, a perfectly coherent analysis shows the same photon bunching of the
paired coherent photons on a beam splitter, whereas individual output
intensities are uniform.


  Reconstructing and rendering 3D objects from highly sparse views is of
critical importance for promoting applications of 3D vision techniques and
improving user experience. However, images from sparse views only contain very
limited 3D information, leading to two significant challenges: 1) Difficulty in
building multi-view consistency as images for matching are too few; 2)
Partially omitted or highly compressed object information as view coverage is
insufficient. To tackle these challenges, we propose GaussianObject, a
framework to represent and render the 3D object with Gaussian splatting, that
achieves high rendering quality with only 4 input images. We first introduce
techniques of visual hull and floater elimination which explicitly inject
structure priors into the initial optimization process for helping build
multi-view consistency, yielding a coarse 3D Gaussian representation. Then we
construct a Gaussian repair model based on diffusion models to supplement the
omitted object information, where Gaussians are further refined. We design a
self-generating strategy to obtain image pairs for training the repair model.
Our GaussianObject is evaluated on several challenging datasets, including
MipNeRF360, OmniObject3D, and OpenIllumination, achieving strong reconstruction
results from only 4 views and significantly outperforming previous
state-of-the-art methods.


  In this work, we discuss the improvement that the joint network of LISA and
Taiji could provide on exploring two kinds of black hole formation mechanisms.
For astrophysical origin, we consider light seed and heavy seed scenarios, and
generate populations accordingly. We find that the joint network has the
potential to observe growing light seeds in the range 15 < z < 20, while single
detector can hardly see, which would shed light on the light seeding mechanism.
For the heavy seeds, the joint network only improves the signal-to-noise ratio.
For primordial origin, we calculate the event rate at z > 20 and detection
rates of LISA and the joint network. The joint network expands LISA's horizon
towards lower mass end, where the event rate is high, so we have better chance
observing primordial black holes with the joint network. We also estimate the
parameters using Fisher matrices of LISA and the joint network, and find that
the joint network significantly improves the estimation.


  Alday-Maldacena conjecture is that the area A_P of the minimal surface in
AdS_5 space with a boundary P, located in Euclidean space at infinity of AdS_5,
coincides with a double integral D_P along P, the Abelian Wilson average in an
auxiliary dual model. The boundary P is a polygon formed by momenta of n
external light-like particles in N=4 SYM theory, and in a certain n=infty limit
it can be substituted by an arbitrary smooth curve (wavy circle). The
Alday-Maldacena conjecture is known to be violated for n>5, when it fails to be
supported by the peculiar global conformal invariance, however, the structure
of deviations remains obscure. The case of wavy lines can appear more
convenient for analysis of these deviations due to the systematic method
developed in arXiv:0803.1547 for (perturbative) evaluation of minimal areas,
which is not yet available in the presence of angles at finite n. We correct a
mistake in that paper and explicitly evaluate the h^2\bar h^2 terms, where the
first deviation from the Alday-Maldacena duality arises for the wavy circle.