  The M\"{o}ssbauer Effect(ME) is frequently used to investigate magnetically
ordered systems. One usually assumes that the magnetic order induces a
hyperfine magnetic field, $B_{hyperfine}$, at the ME active site. This is the
case in the ruthenates, where the temperature dependence of $B_{hyperfine}$ at
$^{99}$Ru sites tracks the temperature dependence of the ferromagnetic or
antiferromagnetic order. However this does not happen in the rare-earth
intermetallics, GdRu$_2$ and HoRu$_2$. Specific heat, magnetization, magnetic
susceptibility, M\"{o}ssbauer effect, and neutron diffraction have been used to
study the nature of the magnetic order in these materials. Both materials are
found to order ferromagnetically at 82.3 and 15.3 K, respectively. Despite the
ferromagnetic order of the rare earth moments in both systems, there is no
evidence of a correspondingly large $B_{hyperfine}$ in the M\"{o}ssbauer
spectrum at the Ru site. Instead the measured spectra consist of a narrow peak
at all temperatures which points to the absence of magnetic order. To
understand the surprising absence of a transferred hyperfine magnetic field, we
carried out {\it ab initio} calculations which show that spin polarization is
present only on the rare-earth site. The electron spin at the Ru sites is
effectively unpolarized and, as a result, $B_{hyperfine}$ is very small at
those sites. This occurs because the 4$d$ Ru electrons form broad conduction
bands rather than localized moments. These 4$d$ conduction bands are polarized
in the region of the Fermi energy and mediate the interaction between the
localized rare earth moments.


  We summarize our work on structures in different stages of aggregation, and
spanning a wide range in redshift. We emphasize our work on high resdhift
clusters. This comprises the analysis of ~7 square degrees using deep images
with several broad-band optical filters. We plan to complement these with near
IR observations in 4 m telescopes. Preliminary results of the analysis in a
field of 35 x 35 arcmin^2 indicate the detection of several candidates to be
clusters at redshifst z> 0.5. When all the fields are analyzed, we will have an
adequate sample for future detailed studies with the GTC.


  In modern computing systems, jobs' resource requirements often vary over
time. Accounting for this temporal variability during job scheduling is
essential for meeting performance goals. However, theoretical understanding on
how to schedule jobs with time-varying resource requirements is limited.
Motivated by this gap, we propose a \emph{new setting} of the stochastic
bin-packing problem in service systems that allows for \emph{time-varying} job
resource requirements, also referred to as `item sizes' in traditional
bin-packing terms. In this setting, a job or `item' must be dispatched to a
server or `bin' upon arrival. Its resource requirement may vary over time while
in service, following a Markovian assumption. Once the job's service is
complete, it departs from the system. Our goal is to minimize the expected
number of active servers, or `non-empty bins', in steady state.
  Under our problem formulation, we develop a job dispatch policy, named
Join-Reqesting-Server (JRS). Broadly, JRS lets each server independently
evaluate its current job configuration and decide whether to accept additional
jobs, balancing the competing objectives of maximizing throughput and
minimizing the risk of resource capacity overruns. The JRS dispatcher then
utilizes these individual evaluations to decide which server to dispatch each
arriving job to. The theoretical performance guarantee of JRS is in the
asymptotic regime where the job arrival rate scales large linearly with respect
to a scaling factor $r$. We show that JRS achieves an additive optimality gap
of $O(\sqrt{r})$ in the objective value, where the optimal objective value is
$\Theta(r)$. When specialized to constant job resource requirements, our result
improves upon the state-of-the-art $o(r)$ optimality gap. Our technical
approach highlights a novel policy conversion framework that reduces the policy
design problem into a single-server problem.


  Context. RR Lyrae stars are useful standard candles allowing one to derive
accurate distances for old star clusters. Based on the recent catalogues from
OGLE-IV and Gaia Early Data Release 3 (EDR3), the distances can be improved for
a few bulge globular clusters. Aims. The aim of this work is to derive an
accurate distance for the following six moderately metal-poor, relatively
high-reddening bulge globular clusters: NGC 6266, NGC 6441, NGC 6626, NGC 6638,
NGC 6642, and NGC 6717. Methods. We combined newly available OGLE-IV catalogues
of variable stars containing mean I magnitudes, with Clement's previous
catalogues containing mean V magnitudes, and with precise proper motions from
Gaia EDR3. Astrometric membership probabilities were computed for each RR
Lyrae, in order to select those compatible with the cluster proper motions.
Applying luminosity-metallicity relations derived from BaSTI $\alpha$-enhanced
models (He-enhanced for NGC 6441 and canonical He for the other clusters), we
updated the distances with relatively low uncertainties. Results. Distances
were derived with the I and V bands, with a $5-8\%$ precision. We obtained 6.6
kpc, 13.1 kpc, 5.6 kpc, 9.6 kpc, 8.2 kpc, and 7.3 kpc for NGC 6266, NGC 6441,
NGC 6626, NGC 6638, NGC 6642, and NGC 6717, respectively. The results are in
excellent agreement with the literature for all sample clusters, considering
the uncertainties. Conclusions. The present method of distance derivation,
based on recent data of member RR Lyrae stars, updated BaSTI models, and robust
statistical methods, proved to be consistent. A larger sample of clusters will
be investigated in a future work.


  We describe an inertial rotation sensor with a 30-cm cylindrical proof-mass
suspended from a pair of 14-${\mu}$m thick BeCu flexures. The angle between the
proof-mass and support structure is measured with a pair of homodyne
interferometers which achieve a noise level of $\sim 5\
\text{prad}/\sqrt{\text{Hz}}$. The sensor is entirely made of vacuum compatible
materials and the center of mass can be adjusted remotely.


  We introduce a new class of polynomials $\{P_{n}\}$, that we call polar
Legendre polynomials, they appear as solutions of an inverse Gauss problem of
equilibrium position of a field of forces with $n+1$ unit masses. We study
algebraic, differential and asymptotic properties of this class of polynomials,
that are simultaneously orthogonal with respect to a differential operator and
a discrete-continuous Sobolev type inner product.


  Approximate analytical solutions of the Dirac equation are obtained for the
Hellmann potential, Wei Hua potential and Varshni potential with any
$\kappa$-value for the cases having the Dirac equation pseudospin and spin
symmetries. Closed forms of the energy eigenvalue equations and the spinor wave
functions are obtained by using the Nikiforov-Uvarov method and some tables are
given to see the dependence of the energy eigenvalues on different quantum
number pairs ($n, \kappa$).


  This paper continues the work of two previous treatments of bunch lengthening
by a passive harmonic cavity in an electron storage ring. Such cavities,
intended to reduce the effect of Touschek scattering, are a feature of fourth
generation synchrotron light sources. The charge densities in the equilibrium
state are given by solutions of coupled Ha\"issinski equations, which are
nonlinear integral equations. If the only wake fields are from cavity
resonators, the unknowns can be the Fourier transforms of bunch densities at
the resonator frequencies. The solution scheme based on this choice of unknowns
proved to be deficient at the design current when multiple resonators were
included. Here we return to the conventional formulation of Ha\"issinski
equations in coordinate space, the unknowns being charge densities at mesh
points on a fine grid. This system would be awkward to solve by the Newton
method used previously, because the Jacobian matrix is very large. Here a new
solution is described, which is both Jacobian-free and much simpler. It is
based on an elementary fixed point iteration, accelerated by Anderson's method.
The scheme is notably fast and robust, accommodating even the case of extreme
over-stretching at current far beyond the design value. The Anderson method is
promising for many problems in accelerator theory and beyond, since it is quite
simple and can be used to attack all kinds of nonlinear and linear integral and
differential equations. Results are presented for ALS-U, with updated design
parameters. The model includes harmonic and main r.f. cavities, compensation of
beam loading of the main cavity by adjustment of the generator voltage, and a
realistic short range wake field (rather than the broad-band resonator wake
invoked previously).


  Hamiltonian dynamical systems possessing equilibria of ${saddle} \times
{centre} \times...\times {centre}$ stability type display \emph{reaction-type
dynamics} for energies close to the energy of such equilibria; entrance and
exit from certain regions of the phase space is only possible via narrow
\emph{bottlenecks} created by the influence of the equilibrium points. In this
paper we provide a thorough pedagogical description of the phase space
structures that are responsible for controlling transport in these problems. Of
central importance is the existence of a \emph{Normally Hyperbolic Invariant
Manifold (NHIM)}, whose \emph{stable and unstable manifolds} have sufficient
dimensionality to act as separatrices, partitioning energy surfaces into
regions of qualitatively distinct behavior. This NHIM forms the natural
(dynamical) equator of a (spherical) \emph{dividing surface} which locally
divides an energy surface into two components (`reactants' and `products'), one
on either side of the bottleneck. This dividing surface has all the desired
properties sought for in \emph{transition state theory} where reaction rates
are computed from the flux through a dividing surface. In fact, the dividing
surface that we construct is crossed exactly once by reactive trajectories, and
not crossed by nonreactive trajectories, and related to these properties,
minimizes the flux upon variation of the dividing surface.
  We discuss three presentations of the energy surface and the phase space
structures contained in it for 2-degree-of-freedom (DoF) systems in the
threedimensional space $\R^3$, and two schematic models which capture many of
the essential features of the dynamics for $n$-DoF systems. In addition, we
elucidate the structure of the NHIM.


  We consider the K_4-free process. In this process, the edges of the complete
n-vertex graph are traversed in a uniformly random order, and each traversed
edge is added to an initially empty evolving graph, unless the addition of the
edge creates a copy of K_4. Let M(n) denote the graph that is produced by that
process. We prove that a.a.s., the number of edges in M(n) is O( n^{8/5} (\ln
n)^{1/5} ). This matches, up to a constant factor, a lower bound of Bohman. As
a by-product, we prove the following Ramsey-type result: for every n there
exists a K_4-free n-vertex graph, in which the largest set of vertices that
doesn't span a triangle has size O( n^{3/5} (\ln n)^{1/5} ). This improves, by
a factor of (\ln n)^{3/10}, an upper bound of Krivelevich.


  We present explicit expressions for the lens equation for a cored isothermal
ellipsoidal gravitational lens as a single real sixth-order algebraic equation
in two approaches; 2-dimensional Cartesian coordinates and 3-dimensional polar
ones. We find a condition for physical solutions which correspond to at most
five images. For a singular isothermal ellipsoid, the sixth-order equation is
reduced to fourth-order one for which analytic solutions are well-known.
Furthermore, we derive analytic criteria for determining the number of images
for the singular lens, which give us simple expressions for the caustics and
critical curves. The present formulation offers a useful way for studying
galaxy lenses frequently modeled as isothermal ellipsoids.


  We present the first measurements of kilowatt laser power with an uncertainty
less than 1 %. These represent progress toward the most accurate measurements
of laser power above 1 kW at 1070 nm wavelength and establish a more precise
link between force metrology and laser power metrology. Radiation pressure, or
photon momentum, is a relatively new method of non-destructively measuring
laser power. We demonstrate how a multiple reflection optical system amplifies
the pressure of a kilowatt class laser incoherently to improve the signal to
noise ratio in a radiation pressure-based measurement. With 14 incoherent
reflections of the laser, we measure a total uncertainty of 0.26 % for an input
power of 10 kW and 0.46 % for an input power of 1 kW at the 95 % confidence
level. These measurements of absolute power are traceable to the SI kilogram
and mark a state-of-the-art improvement in measurement precision by a factor of
four.


  N-body simulations are essential tools in physical cosmology to understand
the large-scale structure (LSS) formation of the Universe. Large-scale
simulations with high resolution are important for exploring the substructure
of universe and for determining fundamental physical parameters like neutrino
mass. However, traditional particle-mesh (PM) based algorithms use considerable
amounts of memory, which limits the scalability of simulations. Therefore, we
designed a two-level PM algorithm CUBE towards optimal performance in memory
consumption reduction. By using the fixed-point compression technique, CUBE
reduces the memory consumption per N-body particle toward 6 bytes, an order of
magnitude lower than the traditional PM-based algorithms. We scaled CUBE to 512
nodes (20,480 cores) on an Intel Cascade Lake based supercomputer with
$\simeq$95\% weak-scaling efficiency. This scaling test was performed in
"Cosmo-$\pi$" -- a cosmological LSS simulation using $\simeq$4.4 trillion
particles, tracing the evolution of the universe over $\simeq$13.7 billion
years. To our best knowledge, Cosmo-$\pi$ is the largest completed cosmological
N-body simulation. We believe CUBE has a huge potential to scale on exascale
supercomputers for larger simulations.


  Successive quadratic approximations (SQA) are numerically efficient for
minimizing the sum of a smooth function and a convex function. The iteration
complexity of inexact SQA methods has been analyzed recently. In this paper, we
present an algorithmic framework of inexact SQA methods with four types of line
searches, and analyze its global complexity under milder assumptions. First, we
show its well-definedness and some decreasing properties. Second, under the
quadratic growth condition and a uniform positive lower bound condition on
stepsizes, we show that the function value sequence and the iterate sequence
are linearly convergent. Moreover, we obtain a o(1/k) complexity without the
quadratic growth condition, improving existing O(1/k) complexity results. At
last, we show that a local gradient-Lipschitz-continuity condition could
guarantee a uniform positive lower bound for the stepsizes.


  We propose three novel pruning techniques to improve the cost and results of
inference-aware Differentiable Neural Architecture Search (DNAS). First, we
introduce Prunode, a stochastic bi-path building block for DNAS, which can
search over inner hidden dimensions with O(1) memory and compute complexity.
Second, we present an algorithm for pruning blocks within a stochastic layer of
the SuperNet during the search. Third, we describe a novel technique for
pruning unnecessary stochastic layers during the search. The optimized models
resulting from the search are called PruNet and establishes a new
state-of-the-art Pareto frontier for NVIDIA V100 in terms of inference latency
for ImageNet Top-1 image classification accuracy. PruNet as a backbone also
outperforms GPUNet and EfficientNet on the COCO object detection task on
inference latency relative to mean Average Precision (mAP).


  High-resolution ($R = \lambda /\Delta \lambda > 2000$) x-ray absorption and
emission line spectroscopy in the soft x-ray band is a crucial diagnostic for
the exploration of the properties of ubiquitous warm and hot plasmas and their
dynamics in the cosmic web, galaxy clusters, galaxy halos, intragalactic space,
and star atmospheres. Soft x-ray grating spectroscopy with $R > 10{,}000$ has
been demonstrated with critical-angle transmission (CAT) gratings. CAT gratings
combine the relaxed alignment and temperature tolerances and low mass of
transmission gratings with high diffraction efficiency blazed in high orders.
They are an enabling technology for the proposed Arcus grating explorer and
were selected for the Lynx design reference mission grating spectrometer
instrument. Both Arcus and Lynx require the manufacture of hundreds to perhaps
$\approx 2000$ large-area CAT gratings. We are developing new patterning and
fabrication process sequences that are conducive to large-format volume
processing on state-of-the-art 200 mm wafer tools. Recent x-ray tests on 200
nm-period gratings patterned using e-beam-written masks and 4x projection
lithography in conjunction with silicon pore focusing optics demonstrated $R
\approx 10^4$ at 1.49 keV. Extending the grating depth from 4 $\mu$m to 6
$\mu$m is predicted to lead to significant improvements in diffraction
efficiency and is part of our current efforts using a combination of deep
reactive-ion etching and wet etching in KOH solution. We describe our recent
progress in grating fabrication and report our latest diffraction efficiency
and modeling results.


  We discuss some properties of integrals associated with the free particle
wave packet, $\psi(x,t),$ which are solutions to the time-dependent
Schr$\ddot{o}$dinger equation for a free particle in one dimension. Some
noteworthy discussion is made in relation to integrals which have appeared in
the literature. We also obtain formulas for half-integer arguments of the
Riemann zeta function.


  A sequence of completely positive maps can be decomposed into quantum
trajectories. The geometric phase or holonomy of such a trajectory is
delineated. For nonpure initial states, it is shown that well-defined
holonomies can be assigned by using Uhlmann's concept of parallel transport
along the individual trajectories. We put forward an experimental realization
of the geometric phase for a quantum trajectory in interferometry. We argue
that the average over the phase factors for all quantum trajectories that build
up a given open system evolution, fails to reflect the geometry of the open
system evolution itself.


  The requirement that physical phenomena associated with gravitational
collapse should be duly reconciled with the postulates of quantum mechanics
implies that at a Planckian scale our world is not 3+1 dimensional. Rather, the
observable degrees of freedom can best be described as if they were Boolean
variables defined on a two-dimensional lattice, evolving with time. This
observation, deduced from not much more than unitarity, entropy and counting
arguments, implies severe restrictions on possible models of quantum gravity.
Using cellular automata as an example it is argued that this dimensional
reduction implies more constraints than the freedom we have in constructing
models. This is the main reason why so-far no completely consistent
mathematical models of quantum black holes have been found.
  Essay dedicated to Abdus Salam.


  In this paper, we give an explicit bound on the irreducibility of
mod-$\mathfrak{l}$ Galois representation for Drinfeld modules of arbitrary rank
without complex multiplication. This is a function field analogue of
Masser-W\"ustholz bound on irreducibility of mod-$\ell$ Galois representation
for elliptic curves over number field.


  We discuss the behaviour cooperative effects in the emitted light from a
system of two nitrogen-vacancy (NV) centers confined in a nanopillar having
dimensions close to the wavelength of the excitation pump. We experimentally
observe a $g^{(2)}(0) > 0.5 \to 1$ for the coupled emitter system and a drastic
decrease in the singlet and triplet lifetimes by a factor of $\approx 6$,
indicating an interaction between the two emitters, which indicates
superradiant behaviour. We theoretically study the dissipative dynamics of the
interaction of the emitter system with the excitation light at a finite
temperature for three cases (single emitter, two emitters with and without
dipole-dipole coupling) by solving the Lindblad master equation and providing
an analytical expression for the second-order correlation function. We observe
that from the master equation, the populations and coherences mix for the two
emitters' cases. Through this, we support our experimental results and discuss
superradiance from our system. Finally, we discover a reliable quantum random
number generation rate of $\sim 200$ kHz from the coupled emitter system, at
low pump powers.


  By adopting the same approach outlined in De Santis & Cassisi (1999), we
evaluate the absolute bolometric magnitude of the Zero Age Horizontal Branch
(ZAHB) at the level of the RR Lyrae variable instability strip in selected
galactic globular clusters. This allows us to estimate the ZAHB absolute visual
magnitude for these clusters and to investigate its dependence on the cluster
metallicity. The derived $M_V(ZAHB) - [Fe/H]$ relation, corrected in order to
account for the luminosity difference between the ZAHB and the mean RR Lyrae
magnitude, has been compared with some of the most recent empirical
determinations in this field, as the one provided by Baade-Wesselink analyses,
RR Lyrae periods, Hipparcos data for field variables and Main Sequence fitting
based on Hipparcos parallaxes for field subdwarfs. As a result, our relation
provides a clear support to the "long" distance scale. We discuss also another
method for measuring the distance to galactic globular clusters. This method is
quite similar to the one adopted for estimating the absolute bolometric
magnitude of the ZAHB but it relies only on the pulsational properties of the
Lyrae variables in each cluster. The reliability and accuracy of this method
has been tested by applying it to a sample of globulars for which, due to the
morphology of their horizontal branch (HB), the use of the commonly adopted
ZAHB fitting is a risky procedure.


  The identity of dark matter is one of the key outstanding problems in both
particle and astrophysics. In this thesis, I describe a number of complementary
searches for particle dark matter. I discuss how the impact of dark matter on
stars can constrain its interaction with nuclei, focussing on main sequence
stars close to the Galactic Centre, and on the first stars as seen through the
upcoming James Webb Space Telescope. The mass and annihilation cross-section of
dark matter particles can be probed with searches for gamma rays produced in
astronomical targets. Dwarf galaxies and ultracompact, primordially-produced
dark matter minihalos turn out to be especially promising in this respect. I
illustrate how the results of these searches can be combined with constraints
from accelerators and cosmology to produce a single global fit to all available
data. Global fits in supersymmetry turn out to be quite technically demanding,
even with the simplest predictive models and the addition of complementary data
from a bevy of astronomical and terrestrial experiments; I show how genetic
algorithms can help in overcoming these challenges.


  The Universal Intelligence Measure is a recently proposed formal definition
of intelligence. It is mathematically specified, extremely general, and
captures the essence of many informal definitions of intelligence. It is based
on Hutter's Universal Artificial Intelligence theory, an extension of Ray
Solomonoff's pioneering work on universal induction. Since the Universal
Intelligence Measure is only asymptotically computable, building a practical
intelligence test from it is not straightforward. This paper studies the
practical issues involved in developing a real-world UIM-based performance
metric. Based on our investigation, we develop a prototype implementation which
we use to evaluate a number of different artificial agents.


  The State of Tripura lies in northeast India which is considered to be one of
the most seismically active regions of the world. In the present study, a
realistic Probabilistic Seismic Hazard Assessment (PSHA) of Tripura State based
on improved seismogenic sources considering layered polygonal sources
corresponding to hypo-central depth range of 0 to 25 km, 25 to 70 km and 70 to
180 km, respectively and data driven selection of suitable Ground Motion
Prediction Equations (GMPEs) in a logic tree framework is presented. Analyses
have been carried out by formulating a layered seismogenic source zonation
together with smooth-gridded seismicity. Using the limited accelerogram records
available, most suitable GMPEs have been selected after performing a thorough
quantitative assessment and thus the uncertainty in selecting appropriate GMPEs
in PSHA has been addressed by combining them with proper weight factor. The
computations of seismic hazard are carried out in a higher resolution of grid
interval of 0.05 $\degree$ X 0.05 $\degree$. The probabilistic seismic hazard
distribution in terms of Peak Ground Acceleration (PGA) and 5% damped Pseudo
Spectral Acceleration (PSA) at different time periods for 10% and 2%
probability of exceedance in 50 years at engineering bedrock level have been
presented. The final results show significant improvements over the previous
studies, which is reflecetd in the local variation of the hazard maps. The
design response spectra at engineering bedrock level can be computed for any
location in the study region from the hazard distributions. The results will be
useful for earthquake resistant design and construction of structures in this
region.


  Modern sequence to sequence neural TTS systems provide close to natural
speech quality. Such systems usually comprise a network converting
linguistic/phonetic features sequence to an acoustic features sequence,
cascaded with a neural vocoder. The generated speech prosody (i.e. phoneme
durations, pitch and loudness) is implicitly present in the acoustic features,
being mixed with spectral information. Although the speech sounds natural, its
prosody realization is randomly chosen and cannot be easily altered. The
prosody control becomes an even more difficult task if no prosodic labeling is
present in the training data. Recently, much progress has been achieved in
unsupervised speaking style learning and generation, however human inspection
is still required after the training for discovery and interpretation of the
speaking styles learned by the system. In this work we introduce a fully
automatic method that makes the system aware of the prosody and enables
sentence-wise speaking pace and expressiveness control on a continuous scale.
While being useful by itself in many applications, the proposed prosody control
can also improve the overall quality and expressiveness of the synthesized
speech, as demonstrated by subjective listening evaluations. We also propose a
novel augmented attention mechanism, that facilitates better pace control
sensitivity and faster attention convergence.


  In this paper, we present a data science automation system called Prediction
Factory. The system uses several key automation algorithms to enable data
scientists to rapidly develop predictive models and share them with domain
experts. To assess the system's impact, we implemented 3 different interfaces
for creating predictive modeling projects: baseline automation, full
automation, and optional automation. With a dataset of online grocery shopper
behaviors, we divided data scientists among the interfaces to specify
prediction problems, learn and evaluate models, and write a report for domain
experts to judge whether or not to fund to continue working on. In total, 22
data scientists created 94 reports that were judged 296 times by 26 experts. In
a head-to-head trial, reports generated utilizing full data science automation
interface reports were funded 57.5% of the time, while the ones that used
baseline automation were only funded 42.5% of the time. An intermediate
interface which supports optional automation generated reports were funded
58.6% more often compared to the baseline. Full automation and optional
automation reports were funded about equally when put head-to-head. These
results demonstrate that Prediction Factory has implemented a critical amount
of automation to augment the role of data scientists and improve business
outcomes.


  Block2 is an open source framework to implement and perform density matrix
renormalization group and matrix product state algorithms. Out-of-the-box it
supports the eigenstate, time-dependent, response, and finite-temperature
algorithms. In addition, it carries special optimizations for ab initio
electronic structure Hamiltonians and implements many quantum chemistry
extensions to the density matrix renormalization group, such as dynamical
correlation theories. The code is designed with an emphasis on flexibility,
extensibility, and efficiency, and to support integration with external
numerical packages. Here we explain the design principles and currently
supported features and present numerical examples in a range of applications.


  The deep reinforcement learning community has made several independent
improvements to the DQN algorithm. However, it is unclear which of these
extensions are complementary and can be fruitfully combined. This paper
examines six extensions to the DQN algorithm and empirically studies their
combination. Our experiments show that the combination provides
state-of-the-art performance on the Atari 2600 benchmark, both in terms of data
efficiency and final performance. We also provide results from a detailed
ablation study that shows the contribution of each component to overall
performance.


  In a recent paper Mahler {\em et al.} have argued that the experiments of
Kocsis {\em et al.} provide experimental evidence for Bohmian mechanics.
Unfortunately these experiments used relativistic, zero rest mass photons
whereas Bohmian mechanics is based on non-relativistic Schr\"{o}dinger
particles having non-zero rest mass. The experimental results can be accounted
for in terms of a different approach based on the electromagnetic field that
was already outlined by Bohm in an appendix of the second of his 1952 papers. A
subsequent development of this approach by Bohm, Hiley, Holland, Kaloyerou, Lam
and Dewdney, shows in detail how this theory accounts for experimental quantum
phenomena in general. Using this theory, we are led to the conclusion that the
experiments have constructed mean momentum flow lines by measuring the real
part of what we term the weak Poynting vector. These results support and
clarify the analysis of Bliokh {\em et al}. The experimental flow lines can be
constructed independently of the number of photons in the beam leading to the
conclusion that flow lines cannot be interpreted as `photon trajectories'. We
discuss exactly how the notion of a photon arises in the field approach in the
light of weak values.


  Admitting the validity of Lorentz transformations for the space as time
coordinates of the same event we derive their differential form in order to
underline the correct prerequisites for the application of time and length
contraction or dilation effects. Furthermore we quantify the simultaneity error
occurring in the relativity theory. Having done this, we analyse the root cause
of these effects and identify it with a finite phase velocity associated with
the moving frame. We define this phase velocity by analogy to the de Broglie
wave associated with a moving particle. Based on this construct we demonstrate
that the phase of the de Broglie waves further extended for stationary
particles is a relativistic invariant being the same for all corresponding
observers. Also the phase of the electromagnetic waves transporting energy at
light speed is a relativistic invariant. Therefore the universe and its matter
/ energy may be seen as a superposition of waves propagating such that their
phase is the same for all corresponding observers. The wave phase may replace
the time as an invariant and universal reference.


  We predict novel topological phases with broken time-reversal symmetry
supporting the coexistence of opposite chiral edge states, which are
fundamentally different from the photonic spin-Hall, valley-Hall, and
higher-order topological phases. We find a fine-grained categorization of Chern
insulators, their band topologies characterized by identical Chern number are
completely different. Furthermore, we prove that different topologies cause
zeros in their Bloch wavefunction overlaps, which imprint the band gap closing
and appear at the degenerate points of topological phase transition. The Bloch
wavefunction overlaps predict the reflection and refraction at a topological
time boundary, and the overlap zeros ensure the existence of vanishing revival
amplitude at critical times even though different topologies before and after
the time boundary have identical Chern number. Our findings create new
opportunities for topological metamaterials, uncover the topological feature
hidden in the time boundary effect as a probe of topology, and open a venue for
the exploration of the rich physics originating from the long-range couplings.


  In this paper we review and update the Amaral-Gay Ducati-Betemps-Soyez
saturation model, by testing it against the recent H1-ZEUS combined data on
deep inelastic scattering, including heavy quarks in the dipole amplitude. We
obtain that this model, which is based on traveling wave solutions of the
Balitsky-Kovchegov equation and built in the momentum space framework, yields
very accurate descriptions of the reduced cross section,
$\sigma_{r}(x,y,Q^{2})$, as well as DIS structure functions such as
$F_{2}(x,Q^{2})$ and $F_{L}(x,Q^{2})$, all measured at HERA. Additionally, it
provides good descriptions of heavy quark structure functions, $F_{2}^{cc}$ and
$F_{2}^{bb}$ at small-$x$ and $Q^{2}\lesssim 60$ GeV$^{2}$. We also use the
improved model to make predictions for structure functions to be measured in
the near future at LHeC.


  Single-phase perovskite 5 at.% Mn-doped and undoped polycrystalline BaTiO3
thin films have been grown under different oxygen partial pressures by pulsed
laser deposition on platinum-coated sapphire substrates. Ferroelectricity is
only observed for the Mn-doped and undoped BaTiO3 thin films grown under
relatively high oxygen partial pressure. Compared to undoped BaTiO3, Mn-doped
BaTiO3 reveals a low leakage current, increased dielectric loss, and a
decreased dielectric constant. Ferromagnetism is seen on Mn-doped BaTiO3 thin
films prepared under low oxygen partial pressure and is attributed to the
formation of bound magnetic polarons (BMPs). This BMP formation is enhanced by
oxygen vacancies. The present work confirms a theoretical work from C. Ederer
and N. Spaldin on ferroelectric perovskites [Nature Mat. 3, 849 (2004)] which
shows that the existence of ferroelectricity is incompatible with the existence
of a spontaneous magnetization in Mn-doped BaTiO3 thin films.


  We study a gossip protocol called forwarding without repeating (FWR). The
objective is to spread multiple rumors over a graph as efficiently as possible.
FWR accomplishes this by having nodes record which messages they have forwarded
to each neighbor, so that each message is forwarded at most once to each
neighbor. We prove that FWR spreads a rumor over a strongly connected digraph,
with high probability, in time which is within a constant factor of optimal for
digraphs with bounded out-degree. Moreover, on digraphs with bounded out-degree
and bounded number of rumors, the number of transmissions required by FWR is
arbitrarily better than that of existing approaches. Specifically, FWR requires
O(n) messages on bounded-degree graphs with n nodes, whereas classical
forwarding and an approach based on network coding both require {\omega}(n)
messages. Our results are obtained using combinatorial and probabilistic
arguments. Notably, they do not depend on expansion properties of the
underlying graph, and consequently the message complexity of FWR is arbitrarily
better than classical forwarding even on constant-degree expander graphs, as n
\rightarrow \infty. In resource-constrained applications, where each
transmission consumes battery power and bandwidth, our results suggest that
using a small amount of memory at each node leads to a significant savings.


  Cepheids are fundamental objects astrophysically in that they hold the key to
a CMB independent estimate of Hubble's constant. A number of researchers have
pointed out the possibilities of breaking degeneracies between Omega_Matter and
H0 if there is a CMB independent distance scale accurate to a few percent (Hu
2005). Current uncertainties in the distance scale are about 10% but future
observations, with, for example, the JWST, will be capable of estimating H0 to
within a few percent. A crucial step in this process is the Cepheid PL
relation. Recent evidence has emerged that the PL relation, at least in optical
bands, is nonlinear and that neglect of such a nonlinearity can lead to errors
in estimating H0 of up to 2 percent. Hence it is important to critically
examine this possible nonlinearity both observationally and theoretically.
Existing PC/PL relations rely exclusively on evaluating these relations at mean
light. However, since such relations are the average of relations at different
phases. Here we report on recent attempts to compare theory and observation in
the multiphase PC/PL planes. We construct state of the art Cepheid pulsations
models appropriate for the LMC/Galaxy and compare the resulting PC/PL relations
as a function of phase with observations. For the LMC, the (V-I) period-color
relation at minimum light can have quite a narrow dispersion (0.2-0.3 mags) and
thus could be useful in placing constraints on models. At longer periods, the
models predict significantly redder (by about 0.2-0.3 mags) V-I colors. We
discuss possible reasons for this and also compare PL relations at various
phases of pulsation and find clear evidence in both theory and observations for
a nonlinear PL relation.


  The Stefan-Boltzmann constant arose from photon densities inside a cavity,
but inside matter photon mode densities are material specific. Photon speeds
are governed by the mode they occupy, so mode densities can be expressed in
terms of speed. Cavity intensities at temperature \(T_{K}\) combined
\(\left[\frac {8\pi k^4}{c^3h^3}\right] T_{K }^4\) with \(({\pi^4}/{15})\). A
material dependent number from summation of internal photon spectral energy
densities replaces \(\frac {\pi^4}{15}\). Spectral densities are presented for
water, germanium and silver. Output intensity combines revised hemispherical
emittance \(\epsilon_{Q,H}\) based on these densities, with universal factor
\(\left[\frac {8\pi k^4}{c^3h^3}\right] T_{K }^4\). Emitted radiance after
interface internal reflectance of directionally invariant internal radiance
elements defines \(\epsilon_{Q,H}\). Predicted internal densities are
verifiable using measured external spectral intensities, provided refraction
upon exit is accounted for in emissivity, which the Kirchhoff rule neglects.
Virtual bound state photon resonances are predicted in dielectrics and
observed.


  Recently, Caro, Patk\'os, and Tuza (2022) introduced the concept of connected
Tur\'an number. We study a similar parameter in Ramsey theory. Given two graphs
$G_1$ and $G_2$, the size Ramsey number $\hat{r}(G_1,G_2)$ refers to the
smallest number of edges in a graph $G$ such that for any red-blue
edge-coloring of $G$, either a red subgraph $G_1$ or a blue subgraph $G_2$ is
present in $G$. If we further restrict the host graph $G$ to be connected, we
obtain the connected size Ramsey number, denoted as $\hat{r}_c(G_1,G_2)$.
Erd\H{o}s and Faudree (1984) proved that $\hat r(nK_2,K_{1,m})=mn$ for all
positive integers $m,n$. In this paper, we concentrate on the connected analog
of this result. Rahadjeng, Baskoro, and Assiyatun (2016) provided the exact
values of $\hat r_c(nK_2,K_{1,m})$ for $n=2,3$. We establish a more general
result: for all positive integers $m$ and $n$ with $m\ge (n^2+2pn+n-3)/2$, we
have $\hat r_c(nK_{1,p},K_{1,m})=n(m+p)-1$. As a corollary, $\hat
r_c(nK_2,K_{1,m})=nm+n-1$ for $m\ge (n^2+3n-3)/2$. We also propose a conjecture
for the interested reader.


  Systematic uncertainties that have been subdominant in past large-scale
structure (LSS) surveys are likely to exceed statistical uncertainties of
current and future LSS data sets, potentially limiting the extraction of
cosmological information. Here we present a general framework (PCA
marginalization) to consistently incorporate systematic effects into a
likelihood analysis. This technique naturally accounts for degeneracies between
nuisance parameters and can substantially reduce the dimension of the parameter
space that needs to be sampled. As a practical application, we apply PCA
marginalization to account for baryonic physics as an uncertainty in cosmic
shear tomography. Specifically, we use CosmoLike to run simulated likelihood
analyses on three independent sets of numerical simulations, each covering a
wide range of baryonic scenarios differing in cooling, star formation, and
feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV
(Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in
cosmological constraints if baryonic physics is not accounted for. We then show
that PCA marginalization (employing at most 3 to 4 nuisance parameters) removes
this bias. Our study demonstrates that it is possible to obtain robust, precise
constraints on the dark energy equation of state even in the presence of large
levels of systematic uncertainty in astrophysical processes. We conclude that
the PCA marginalization technique is a powerful, general tool for addressing
many of the challenges facing the precision cosmology program.


  Correlated two-dimensional (2D) layers, like 1T-phases of TaS2, TaSe2 and
NbSe2, exhibit rich tunability through varying interlayer couplings, which
promotes the understanding of electron-correlation in the 2D limit. However,
the coupling mechanism is, so far, poorly understood and was tentatively
ascribed to interactions among the d_(z^2 ) orbitals of Ta or Nb atoms. Here,
we theoretically show that the interlayer hybridization and localization
strength of interfacial Se pz orbitals, rather than Nb d_(z^2 ) orbitals,
govern the variation of electron-correlated properties upon interlayer sliding
or twisting in correlated magnetic 1T-NbSe2 bilayers. Each of the both layers
is in a star-of-David (SOD) charge-density-wave phase. Geometric and electronic
structures, and magnetic properties of 28 different stacking configurations
were examined and analyzed using density-functional-theory calculations. We
found that the SOD contains a localized region (Reg-L), in which interlayer Se
pz hybridization plays a paramount role in varying the energy levels of the two
Hubbard bands. These variations lead to three electronic transitions among four
insulating states, which demonstrated the effectiveness of interlayer
interactions to modulate correlated magnetic properties in a prototypical
correlated magnetic insulator.


  Let $\nu$ be the Furstenberg measure associated with a non-elementary
probability measure $\mu$ on SL_2(R). We show that, when $\mu$ has a finite
second moment, the Fourier coefficients of $\nu$ tend to zero at infinity. In
other words, $\nu$ is a Rajchman measure. This improves a recent result of
Jialun Li.


  The construction and the symmetries of Chern-Simons vortices in harmonic and
uniform magnetic force backgrounds found by Ezawa, Hotta and Iwazaki, and by
Jackiw and Pi are generalized using the non-relativistic Kaluza-Klein-type
framework presented in our previous paper. All Schrodinger-symmetric
backgrounds are determined.


  Strongly interacting bosonic particles in a tight-binding periodic potential
superimposed by a weak parabolic trap is a paradigm for many cold atom
experiments. Here, after revisiting the single particle problem, we study
interaction-bound dimers of bosonic atoms in the combined lattice and parabolic
potential. We consider both repulsively- and attractively-bound dimers and find
pronounced differences in their behaviour. We identify conditions under which
attractive and repulsive dimers exhibit analogous dynamics. Our studies reveal
that coherent transport and periodic oscillations of appropriately prepared
one- and two-atom wavepackets can be achieved, which may facilitate information
transfer in optical lattice based quantum computation schemes.


  Mechanical restoring forces acting on ferroelastic domain walls displaced
from the equilibrium positions in epitaxial films are calculated for various
modes of their cooperative translational oscillations. For vibrations of the
domain-wall superlattice with the wave vectors corresponding to the center and
boundaries of the first Brillouin zone, the soft modes are singled out that are
distinguished by a minimum magnitude of the restoring force. It is shown that,
in polydomain ferroelectric thin films, the soft modes of wall vibrations may
create enormously large contribution to the film permittivity.


  The Atacama Large Millimeter/submillimeter Array (ALMA) is a powerful tool
for high-resolution mapping of comets, but the main interferometer (comprised
of 50x12-m antennas) is insensitive to the largest coma scales due to a lack of
very short baselines. In this work, we present a new technique employing ALMA
autocorrelation data (obtained simultaneously with the interferometric
observations), effectively treating the entire 12-m array as a collection of
single-dish telescopes. Using combined autocorrelation spectra from 28 active
antennas, we recovered extended HCN coma emission from comet C/2012 S1 (ISON),
resulting in a fourteen-fold increase in detected line brightness compared with
the interferometer. This resulted in the first detection of rotational emission
from H^13CN in this comet. Using a detailed coma radiative transfer model
accounting for optical depth and non-LTE excitation effects, we obtained an
H^12CN/H^13CN ratio of 88+-18, which matches the terrestrial value of 89,
consistent with a lack of isotopic fractionation in HCN during comet formation
in the protosolar accretion disk. The possibility of future discoveries in
extended sources using autocorrelation spectroscopy from the main ALMA array is
thus demonstrated.


  Developing machine learning models can be seen as a process similar to the
one established for traditional software development. A key difference between
the two lies in the strong dependency between the quality of a machine learning
model and the quality of the data used to train or perform evaluations. In this
work, we demonstrate how different aspects of data quality propagate through
various stages of machine learning development. By performing a joint analysis
of the impact of well-known data quality dimensions and the downstream machine
learning process, we show that different components of a typical MLOps pipeline
can be efficiently designed, providing both a technical and theoretical
perspective.


  For a finite group $G$, the vertices of the prime graph $\Gamma(G)$ are the
primes that divide $|G|$, and two vertices $p$ and $q$ are connected by an edge
if and only if there is an element of order $pq$ in $G$. Prime graphs of
solvable groups as well as groups whose noncyclic composition factors have
order divisible by exactly three distinct primes have been classified in
graph-theoretic terms. In this paper, we begin to develop a general theory on
the existence of edges in the prime graph of an arbitrary $T$-solvable group,
that is, a group whose composition factors are cyclic or isomorphic to a fixed
nonabelian simple group $T$. We then apply these results to classify the prime
graphs of $T$-solvable groups for, in a suitable sense, most $T$ such that
$|T|$ has exactly four prime divisors. We find that these groups almost always
have a 3-colorable prime graph complement containing few possible triangles.


  Indecomposable symmetric Lorentzian manifolds of non-constant curvature are
called Cahen-Wallach spaces. Their isometry classes are described by continuous
families of real parameters. We derive necessary and sufficient conditions for
the existence of compact quotients of Cahen-Wallach spaces in terms of these
parameters.


  While question answering over knowledge bases (KBQA) has shown progress in
addressing factoid questions, KBQA with numerical reasoning remains relatively
unexplored. In this paper, we focus on the complex numerical reasoning in KBQA
and propose a new task, NR-KBQA, which necessitates the ability to perform both
multi-hop reasoning and numerical reasoning. We design a logic form in Python
format called PyQL to represent the reasoning process of numerical reasoning
questions. To facilitate the development of NR-KBQA, we present a large dataset
called MarkQA, which is automatically constructed from a small set of seeds.
Each question in MarkQA is equipped with its corresponding SPARQL query,
alongside the step-by-step reasoning process in the QDMR format and PyQL
program. Experimental results of some state-of-the-art QA methods on the MarkQA
show that complex numerical reasoning in KBQA faces great challenges.


  Muon Colliders have unique technical and physics advantages and disadvantages
when compared with both hadron and electron machines. They should thus be
regarded as complementary. Parameters are given of 4 TeV and 0.5 TeV high
luminosity \mumu colliders, and of a 0.5 TeV lower luminosity demonstration
machine. We discuss the various systems in such muon colliders, starting from
the proton accelerator needed to generate the muons and proceeding through muon
cooling, acceleration and storage in a collider ring. Problems of detector
background are also discussed.


  It is well-known that the size of propositional classical proofs can be huge.
Proof theoretical studies discovered exponential gaps between normal or cut
free proofs and their respective non-normal proofs. The aim of this work is to
study how to reduce the weight of propositional deductions. We present the
formalism of proof-graphs for purely implicational logic, which are graphs of a
specific shape that are intended to capture the logical structure of a
deduction. The advantage of this formalism is that formulas can be shared in
the reduced proof.
  In the present paper we give a precise definition of proof-graphs for the
minimal implicational logic, together with a normalization procedure for these
proof-graphs. In contrast to standard tree-like formalisms, our normalization
does not increase the number of nodes, when applied to the corresponding
minimal proof-graph representations.


  As contributions to the Ramanujan theory of elliptic functions to alternative
bases, Li-Chien Shen has developed families of elliptic functions from the
hypergeometric functions $F(\tfrac{1}{3}, \tfrac{2}{3}; \tfrac{1}{2} ;
\bullet)$ and $F(\tfrac{1}{4}, \tfrac{3}{4}; \tfrac{1}{2} ; \bullet)$. We apply
his methods to the hypergeometric function $F(\tfrac{1}{6}, \tfrac{5}{6};
\tfrac{1}{2} ; \bullet)$.


  Inspired by certain interesting recent extensions of the gamma, beta and
hypergeometric matrix functions, we introduce here new extension of the gamma
and beta matrix function. We also introduce new extensions of the Gauss
hypergeometric matrix function, confluent hypergeometric matrix function,
Appell matrix function and Lauricella matrix function of three variables in
terms of the new extended beta matrix function. Then we investigate certain
properties of these extended matrix functions such as the integral
representations, differential formulae and recurrence relations.


  The class framework developed for vertex reconstruction in CMS is described.
We emphasize how we proceed to develop a flexible, efficient and reliable piece
of reconstruction software. We describe the decomposition of the algorithms
into logical parts, the mathematical toolkit, and the way vertex reconstruction
integrates into the CMS reconstruction project ORCA. We discuss the tools that
we have developed for algorithm evaluation and optimization and for code
release.


  We derive bounds on the path length $\zeta$ of gradient descent (GD) and
gradient flow (GF) curves for various classes of smooth convex and nonconvex
functions. Among other results, we prove that: (a) if the iterates are linearly
convergent with factor $(1-c)$, then $\zeta$ is at most $\mathcal{O}(1/c)$; (b)
under the Polyak-Kurdyka-Lojasiewicz (PKL) condition, $\zeta$ is at most
$\mathcal{O}(\sqrt{\kappa})$, where $\kappa$ is the condition number, and at
least $\widetilde\Omega(\sqrt{d} \wedge \kappa^{1/4})$; (c) for quadratics,
$\zeta$ is $\Theta(\min\{\sqrt{d},\sqrt{\log \kappa}\})$ and in some cases can
be independent of $\kappa$; (d) assuming just convexity, $\zeta$ can be at most
$2^{4d\log d}$; (e) for separable quasiconvex functions, $\zeta$ is
${\Theta}(\sqrt{d})$. Thus, we advance current understanding of the properties
of GD and GF curves beyond rates of convergence. We expect our techniques to
facilitate future studies for other algorithms.


  We analyze a simple randomized subgradient method for approximating solutions
to stochastic systems of convex functional constraints, the only input to the
algorithm being the size of minibatches. By introducing a new notion of what is
meant for a point to approximately solve the constraints, determining bounds on
the expected number of iterations reduces to determining a hitting time for a
compound Bernoulli process, elementary probability. Besides bounding the
expected number of iterations quite generally, we easily establish
concentration inequalities on the number of iterations, and more interesting,
we establish much-improved bounds when a notion akin to H\"{o}lderian growth is
satisfied, for all degrees of growth, not just the linear growth of
piecewise-linear convex functions or the quadratic growth of strongly convex
functions. Finally, we establish the analogous results under a slight
modification to the algorithm which results in the user knowing with high
confidence an iterate is in hand that approximately solves the system. Perhaps
surprisingly, the iteration bounds here are deterministic -- all of the
probability gets wrapped into the confidence level (albeit at the expense of
potentially large minibatches).


  We explore the relationship among the magnetic ordering in real space, the
resulting spin texture on the Fermi surface, and the related superconducting
gap structure in non-collinear antiferromagnetic metals without spin-orbit
coupling. Via a perturbative approach, we show that a non-collinear magnetic
ordering in a metal can generate a momentum-dependent spin texture on its Fermi
surface, even in the absence of spin-orbit coupling, if the metal has more than
three sublattices in its magnetic unit cell. Thus, our theory naturally extends
the idea of altermagnetism to non-collinear spin structures. When
superconductivity is developed in a magnetic metal, as the gap-opening
condition is strongly constrained by the spin texture, the nodal structure of
the superconducting state is also enforced by the magnetism-induced spin
texture. Taking the non-collinear antiferromagnet on the kagome lattice as a
representative example, we demonstrate how the Fermi surface spin texture
induced by noncollinear antiferromagnetism naturally leads to odd-parity
spin-triplet superconductivity with nontrivial topological properties.


  We briefly report on our result that, if there exists a realization of a Hopf
algebra $H$ in a $H$-module algebra $A$, then their cross-product is equal to
the product of $A$ itself with a subalgebra isomorphic to $H$ and commuting
with $A$. We illustrate its application to the Euclidean quantum groups in
$N\ge 3$ dimensions.


  By a combination of Hartree-Fock simulations, exact diagonalization, and
perturbative calculations, we investigate the ground-state properties of
disorder-free circular quantum dots formed in a graphene monolayer. Taking the
reference chemical potential at the Dirac point, we study N \leq 15 interacting
particles, where the fine structure constant {\alpha} parametrizes the Coulomb
interaction. We explore three different theoretical concepts: (i) Sucher's
positive projection ("no-pair") approach, (ii) a more general Hamiltonian
conserving both N and the number of additional electron-hole pairs, and (iii)
the full quantum electrodynamics (QED) problem, where only N is conserved. We
find that electron-hole pair production is important for {\alpha} 1. This
corresponds to a reconstruction of the filled Dirac sea and is a finite-size
version of the bulk excitonic instability. We also address the effects of an
orbital magnetic field.


  The magnetic proximity effect is a fundamental feature of heterostructures
composed of layers of topological insulators and magnetic materials since it
underlies many potential applications in devices with novel quantum
functionality. Within density functional theory we study magnetic proximity
effect at the 3D topological insulator/magnetic insulator (TI/MI) interface in
Bi$_2$Se$_3$/MnSe(111) system as an example. We demonstrate that a gapped
ordinary bound state which spectrum depends on the interface potential arises
in the immediate region of the interface. The gapped topological Dirac state
also arises in the system owing to relocation to deeper atomic layers of
topological insulator. The gap in the Dirac cone is originated from an
overlapping of the topological and ordinary interfacial states. This result
being also corroborated by the analytic model, is a key aspect of the magnetic
proximity effect mechanism in the TI/MI structures.


  Online communities, like Wikipedia, produce valuable public information
goods. Whereas some of these communities require would-be contributors to
create accounts, many do not. Does this requirement catalyze cooperation or
inhibit participation? Prior research provides divergent predictions but little
causal evidence. We conduct an empirical test using longitudinal data from 136
natural experiments where would-be contributors to wikis were suddenly required
to log in to contribute. Requiring accounts leads to a small increase in
account creation, but reduces both high- and low-quality contributions from
registered and unregistered participants. Although the change deters a large
portion of low-quality participation, the vast majority of deterred
contributions are of higher quality. We conclude that requiring accounts
introduces an undertheorized tradeoff for public goods production in
interactive communication systems.


  The general expression for the local matrix $L(\theta)$ of a quantum chain
with the site space in any representation of $su(3)$ is obtained. This is made
by generalizing $L(\theta)$ from the fundamental representation and imposing
the fulfilment of the Yang-Baxter equation. Then, a non-homogeneous spin chain
combining different representations of $su(3)$ is solved by a method inspired
in the nested Bethe ansatz. The solution for the eigenvalues of the trace of
the monodromy matrix is given as two coupled Bethe equations. A conjecture
about the solution of a chain with the site states in different representations
of $su(n)$ is presented.


  The unexpectedly strong 21cm absorption signal detected by the EDGES
experiment suggests that the baryonic gas was colder at redshift $z\sim 17$
than predicted in the standard scenario. We discuss a mechanism to lower the
baryon temperature after recombination. We introduce a stable,
negatively-charged particle with a non-negligible cosmological abundance, such
that the universe remains charge-neutral but the electron and proton numbers
are no longer equal. The deficit of electrons during recombination results in
an earlier decoupling of the baryon gas temperature from that of the CMB. This
implies a smaller ratio of the gas and CMB temperature at $z\sim 17$. The
parameter space of the mechanism where the 21 cm absorption signal is
significantly enhanced is probed by the CMB spectrum, cooling of stars and
supernovae, and colliders. Nevertheless, we find viable regions corresponding
to sub-eV or MeV-scale milli-charged particles, or to TeV-scale multi-charged
particles.


  During the past century, the electromagnetic field momentum in material media
has been under debate in the Abraham-Minkowski controversy as convincing
arguments have been advanced in favor of both the Abraham and Minkowski forms
of photon momentum. Here we study the photon momentum and optical forces in
cavity structures in the cases of dynamical and steady-state fields. In the
description of the single-photon transmission process, we use a field-kinetic
one-photon theory. Our model suggests that in the medium photons couple with
the induced atomic dipoles forming polariton quasiparticles with the Minkowski
form momentum. The Abraham momentum can be associated to the electromagnetic
field part of the coupled polariton state. The polariton with the Minkowski
momentum is shown to obey the uniform center of mass of energy motion that has
previously been interpreted to support only the Abraham momentum. When
describing the steady-state nonequilibrium field distributions we use the
recently developed quantized fluctuational electrodynamics (QFED) formalism.
While allowing detailed studies of light propagation and quantum field
fluctuations in interfering structures, our methods also provide practical
tools for modeling optical energy transfer and the formation of thermal balance
in nanodevices as well as studying electromagnetic forces in optomechanical
devices.


  We propose a general model explanation system (MES) for "explaining" the
output of black box classifiers. This paper describes extensions to Turner
(2015), which is referred to frequently in the text. We use the motivating
example of a classifier trained to detect fraud in a credit card transaction
history. The key aspect is that we provide explanations applicable to a single
prediction, rather than provide an interpretable set of parameters. We focus on
explaining positive predictions (alerts). However, the presented methodology is
symmetrically applicable to negative predictions.


  The analytic quadrupole octupole axially symmetric model, which had
successfully predicted 226Ra and 226Th as lying at the border between the
regions of octupole deformation and octupole vibrations in the light actinides
using an infinite well potential (AQOA-IW), is made applicable to a wider
region of nuclei exhibiting octupole deformation, through the use of a Davidson
potential (AQOA-D). Analytic expressions for energy spectra and B(E1), B(E2),
B(E3) transition rates are derived. The spectra of 222-226Ra and 224,226Th are
described in terms of the two parameters phi_0 (expressing the relative amount
of octupole vs. quadrupole deformation) and beta_0 (the position of the minimum
of the Davidson potential), while the recently determined B(EL) transition
rates of 224Ra, presenting stable octupole deformation, are successfully
reproduced. A procedure for gradually determining the parameters appearing in
the B(EL) transitions from a minimum set of data, thus increasing the
predictive power of the model, is outlined.


  We compare Schwinger and complex powers methods to construct regularized
fermion currents. We show that although both of them are gauge invariant they
not always yield the same result.


  This work evaluates the potential root causes of fatigue using a
biomathematical model and a robust sample of aircrew rosters from the Brazilian
regular aviation. The fatigue outcomes derive from the software Sleep,
Activity, Fatigue, and Task Effectiveness Fatigue Avoidance Scheduling Tool
(SAFTE-FAST). The average minimum SAFTE-FAST effectiveness during critical
phases of flight decreases cubically with the number of shifts that elapse
totally or partially between mid-night and 6 a.m. within a 30-day period
($N_{NS}$). As a consequence, the relative fatigue risk increases by 23.3% (95%
CI, 20.4-26.2%) when increasing $N_{NS}$ from 1 to 13. The average maximum
equivalent wakefulness in critical phases also increases cubically with the
number of night shifts and exceeds 24 hours for rosters with $N_{NS}$ above 10.
The average fatigue hazard area in critical phases of flight varies
quadratically with the number of departures and landings within 2 and 6 a.m.
($N_{Wocl}$). These findings demonstrate that both $N_{NS}$ and $ N_{Wocl}$
should be considered as key performance indicators and be kept as low as
reasonably practical when building aircrew rosters. The effectiveness scores at
30 minute time intervals allowed a model estimate for the relative fatigue risk
as a function of the time of the day, whose averaged values show reasonable
qualitative agreement with previous measurements of pilot errors. Tailored
analyses of the SAFTE-FAST inputs for afternoon naps before night shifts,
commuting from home to station and vice-versa, and bedtime before early-start
shifts show relevant group effects ($p < 0.001$) comparing the groups with and
without afternoon naps, with one or two hours of commuting and with or without
the advanced bedtime feature of the SAFTE-FAST software, evidencing the need of
a better and more accurate understanding of these parameters when modelling
fatigue risk factors.


  We investigate absolutely continuous spectrum of generalized indefinite
strings. By following an approach of Deift and Killip, we establish stability
of the absolutely continuous spectra of two model examples of generalized
indefinite strings under rather wide perturbations. In particular, one of these
results allows us to prove that the absolutely continuous spectrum of the
isospectral problem associated with the conservative Camassa-Holm flow in the
dispersive regime is essentially supported on the interval $[1/4,\infty)$.


  In this paper, we study the dynamics of slow oscillations in Purkinje neurons
in vitro, and derive a strong association with a forced parametric oscillator
model. We demonstrate the precise rhythmicity of the oscillations in Purkinje
neurons, as well as a dynamic tunability of this oscillation using a
photo-switchable compound. We show that this slow oscillation can be induced in
every Purkinje neuron, having periods ranging between 10-25 seconds. Starting
from a Hodgkin-Huxley model, we also demonstrate that this oscillation can be
externally modulated, and that the neurons will return to their intrinsic
firing frequency after the forced oscillation is concluded. These results
signify an additional functional role of tunable oscillations within the
cerebellum, as well as a dynamic control of a time scale in the brain in the
range of seconds.


  Aims: We investigate magnetic tracers in the photosphere and the chromosphere
of the ultra-rapid rotator ($P\sim0.32d$) V530 Per, a cool member of the open
cluster $\alpha$ Persei, to characterize the short-term variability of the
magnetic activity and large-scale magnetic field of this prototypical young,
rapidly rotating solar-like star. Methods: With time-resolved
spectropolarimetric observations spread over four close-by nights, we
reconstructed the brightness distribution and large-scale magnetic field
geometry of V530 Per through Zeeman-Doppler imaging. Simultaneously, we
estimated the short-term variability of the surface through latitudinal
differential rotation. Using the same data set, we also mapped the spatial
distribution of prominences through tomography of H$\alpha$ emission. Results:
As in our previous study, a large dark spot occupies the polar region of V530
Per with smaller, dark, and bright spots at lower latitudes. The large-scale
magnetic field is dominated by a toroidal, mostly axisymmetric component. The
maximal radial field strength is equal to $\sim1$ kG. The surface differential
rotation is consistent with a smooth Sun-like shear d$\Omega = 0.053 \pm 0.004$
rad.d$^{-1}$, close to the solar shear level. The prominence pattern displays a
stable component that is confined close to the corotation radius. We also
observe rapidly evolving H$\alpha$ emitting structures, over timescales ranging
from minutes to days. The fast H$\alpha$ evolution was not linked to any
detected photospheric changes in the spot or magnetic coverage.


  Observational evidence from variety of sources points at an accelerating
universewhich is approximately spatially flat and with
$(\Omega_M,\Omega_{\Lambda})_0\approx(0.3,0.7)$. We have shown that for low
redshifts, $z\leq 0.2$, the metric of this cosmological model is equivalant to
the de Sitter metric within one percent error. Among various coordinate
descriptions for the flat de Sitter model two are most widely used, one yields
a non-static and FRW type, while the other gives a static and Schwarzschild
type metric. We have obtained the magnitude-redshift relation in the second
coordinate frame. Our result indicates a slope of 2.5 for small z. This is in
disagreement with observation which is close to the slope of 5. this test
discards the second and confirms the first coordinate frame as a comoving
reference frame for matter in de Sitter space. We anticipate this test
disqualifies any other solution of the field equations which asymptotically
approaches to the static de Sitter metric, e.g. the Schwarzschild-de Sitter
metric for space around a point mass m.


  Unbiased Learning to Rank (ULTR) aims to train unbiased ranking models from
biased click logs, by explicitly modeling a generation process for user
behavior and fitting click data based on examination hypothesis. Previous
research found empirically that the true latent relevance is mostly recoverable
through click fitting. However, we demonstrate that this is not always
achievable, resulting in a significant reduction in ranking performance. This
research investigates the conditions under which relevance can be recovered
from click data in the first principle. We initially characterize a ranking
model as identifiable if it can recover the true relevance up to a scaling
transformation, a criterion sufficient for the pairwise ranking objective.
Subsequently, we investigate an equivalent condition for identifiability,
articulated as a graph connectivity test problem: the recovery of relevance is
feasible if and only if the identifiability graph (IG), derived from the
underlying structure of the dataset, is connected. The presence of a
disconnected IG may lead to degenerate cases and suboptimal ranking
performance. To tackle this challenge, we introduce two methods, namely node
intervention and node merging, designed to modify the dataset and restore the
connectivity of the IG. Empirical results derived from a simulated dataset and
two real-world LTR benchmark datasets not only validate our proposed theory but
also demonstrate the effectiveness of our methods in alleviating data bias when
the relevance model is unidentifiable.


  We introduce here the equations of magneto-quantum-radiative hydrodynamics.
By rewriting them in a dimensionless form, we obtain a set of parameters that
describe scale-dependent ratios of all the characteristic hydrodynamic
quantities. We discuss how these dimensionless parameters relate to the scaling
between astrophysical observations and laboratory experiments.


  The prolific magnetar SGR 1900+14 showed two outbursts in the last decade and
has been closely monitored in the X-rays to track the changes in its radiative
properties. We use archival Chandra and XMM-Newton observations of SGR 1900+14
to construct a history of its spectrum and persistent X-ray flux spanning a
period of about seven years. We show that the decline of its X-ray flux in
these two outburst episodes follows the same trend. The flux begins to decline
promptly and rapidly subsequent to the flares, then decreases gradually for
about 600 days, at which point it resumes a more rapid decline. Utilizing the
high quality spectral data in each epoch, we also study the spectral
coevolution of the source with its flux. We find that neither the magnetic
field strength nor the magnetospheric properties change over the period spanned
by the observations, while the surface temperature as well as the inferred
emitting area both decline with time following both outbursts. We also show
that the source reached the same minimum flux level in its decline from these
two subsequent outbursts, suggesting that this flux level may be its steady
quiescent flux.


  Direct measurement of vertical and longitudinal sediment fluxes on migrating
sandy bedforms are extremely difficult to perform in both the field and
laboratory. In this study we use the LES--DEM (large eddy simulation--discrete
element method) solver SediFoam to examine the individual particle motions and
resulting fluxes in a domain of self-generated dunes. In SediFoam, the motions
of, and collisions among, the sediment grains as well as their interactions
with surrounding turbulent flows are resolved. The numerical simulations are
performed over a range of transport settings, spanning bedform inception
through washout conditions, to examine the individual particle dynamics. The
space-time evolution of dune surfaces is demonstrated. The self-generated dunes
are stable at relatively low Reynolds numbers, but then become increasingly
unstable at higher Reynolds numbers; eventually washing out as the number of
bypass grains and particles in suspension increase. Data from the simulation
are used to examine the vertical entrainment rate of particles and the
fractionation of total sediment load into bed and suspended fractions as a
function of transport conditions. The study also compares the sediment
transport rate obtained using the bedform geometry and celerity to the true
transport rate at different transport stages.


  Cherry tomato (Solanum Lycopersicum) is popular with consumers over the world
due to its special flavor. Soluble solids content (SSC) and firmness are two
key metrics for evaluating the product qualities. In this work, we develop
non-destructive testing techniques for SSC and fruit firmness based on
hyperspectral images and a corresponding deep learning regression model.
Hyperspectral reflectance images of over 200 tomato fruits are derived with
spectrum ranging from 400 to 1000 nm. The acquired hyperspectral images are
corrected and the spectral information is extracted. A novel
one-dimensional(1D) convolutional ResNet (Con1dResNet) based regression model
is prosed and compared with the state of art techniques. Experimental results
show that, with a relatively large number of samples our technique is 26.4\%
better than state of art technique for SSC and 33.7\% for firmness. The results
of this study indicate the application potential of hyperspectral imaging
technique in the SSC and firmness detection, which provides a new option for
non-destructive testing of cherry tomato fruit quality in the future.


  The infrared behavior of gluon and ghost propagators in Landau gauge
Yang-Mills theory has been at the center of an intense debate over the last
decade. Different solutions of the Dyson-Schwinger equations show a different
behavior of the propagators in the infrared: in the so-called scaling solutions
both propagators follow a power law, while in the decoupling solutions the
gluon propagator shows a massive behavior. The latest lattice results favor the
decoupling solutions. In this contribution, after giving a brief overview of
the present status of analytical and semi-analytical approaches to the infrared
regime of Landau gauge Yang-Mills theory, we will show how Callan-Symanzik
renormalization group equations in an epsilon expansion reproduce both types of
solutions and single out the decoupling solutions as the infrared-stable ones
for space-time dimensions greater than two, in agreement with the lattice
calculations.


  We explore the large set of linear transformations of Srivastava's $H_C$
triple hypergeometric function. This function has been recently linked to the
massive one-loop conformal scalar 3-point Feynman integral. We focus here on
the class of linear transformations of $H_C$ that can be obtained from linear
transformations of the Gauss $_2F_1$ hypergeometric function and, as $H_C$ is
also a three variable generalization of the Appell $F_1$ double hypergeometric
function, from the particular linear transformation of $F_1$ known as Carlson's
identity and some of its generalizations. These transformations are applied at
the level of the 3-fold Mellin-Barnes representation of $H_C$. This allows us
to use the powerful conic hull method of Phys. Rev. Lett. 127 (2021) no.15,
151601 for the evaluation of the transformed Mellin-Barnes integrals, which
leads to the desired results. The latter can then be checked numerically
against the Feynman parametrization of the conformal 3-point integral. We also
show how this approach can be used to derive many known (and less known)
results involving Appell double hypergeometric functions.


  It is characterized when coarsening functors between categories of graded
modules preserve injectivity of objects, and when they commute with graded
covariant Hom functors.


  We show that the empirical risk minimization (ERM) problem for neural
networks has no solution in general. Given a training set $s_1, \dots, s_n \in
\mathbb{R}^p$ with corresponding responses $t_1,\dots,t_n \in \mathbb{R}^q$,
fitting a $k$-layer neural network $\nu_\theta : \mathbb{R}^p \to \mathbb{R}^q$
involves estimation of the weights $\theta \in \mathbb{R}^m$ via an ERM: \[
\inf_{\theta \in \mathbb{R}^m} \; \sum_{i=1}^n \lVert t_i - \nu_\theta(s_i)
\rVert_2^2. \] We show that even for $k = 2$, this infimum is not attainable in
general for common activations like ReLU, hyperbolic tangent, and sigmoid
functions. A high-level explanation is like that for the nonexistence of best
rank-$r$ approximations of higher-order tensors --- the set of parameters is
not a closed set --- but the geometry involved for best $k$-layer neural
networks approximations is more subtle. In addition, we show that for smooth
activations $\sigma(x)= 1/\bigl(1 + \exp(-x)\bigr)$ and $\sigma(x)=\tanh(x)$,
such failure to attain an infimum can happen on a positive-measured subset of
responses. For the ReLU activation $\sigma(x)=\max(0,x)$, we completely
classifying cases where the ERM for a best two-layer neural network
approximation attains its infimum. As an aside, we obtain a precise description
of the geometry of the space of two-layer neural networks with $d$ neurons in
the hidden layer: it is the join locus of a line and the $d$-secant locus of a
cone.


  In the effort of achieving high-energetic ion beams from the interaction of
ultrashort laser pulses with a plasma, volumetric acceleration mechanisms
beyond Target Normal Sheath Acceleration have gained attention. A
relativisticly intense laser can turn a near critical density plasma slowly
transparent, facilitating a synchronized acceleration of ions at the moving
relativistic critical density front. While simulations promise extremely high
ion energies in in this regime, the challenge resides in the realization of a
synchronized movement of the ultra-relativistic laser pulse ($a_0\gtrsim 30$)
driven reflective relativistic electron front and the fastest ions, which
imposes a narrow parameter range on the laser and plasma parameters. We present
an analytic model for the relevant processes, confirmed by a broad parameter
simulation study in 1D- and 3D-geometry. By tayloring the pulse length plasma
density profile at the front side, we can optimize the proton acceleration
performance and extend the regions in parameter space of efficient ion
acceleration at the relativistic relativistic density surface.


  We provide an O(log log OPT)-approximation algorithm for the problem of
guarding a simple polygon with guards on the perimeter. We first design a
polynomial-time algorithm for building epsilon-nets of size O(1/epsilon log log
1/epsilon) for the instances of Hitting Set associated with our guarding
problem. We then apply the technique of Bronnimann and Goodrich to build an
approximation algorithm from this epsilon-net finder. Along with a simple
polygon P, our algorithm takes as input a finite set of potential guard
locations that must include the polygon's vertices. If a finite set of
potential guard locations is not specified, e.g. when guards may be placed
anywhere on the perimeter, we use a known discretization technique at the cost
of making the algorithm's running time potentially linear in the ratio between
the longest and shortest distances between vertices. Our algorithm is the first
to improve upon O(log OPT)-approximation algorithms that use generic net
finders for set systems of finite VC-dimension.


  Large Language Models (LLMs) have revolutionized various industries by
harnessing their power to improve productivity and facilitate learning across
different fields. One intriguing application involves combining LLMs with
visual models to create a novel approach to Human-Computer Interaction. The
core idea of this system is to create a user-friendly platform that enables
people to utilize ChatGPT's features in their everyday lives. uTalk is
comprised of technologies like Whisper, ChatGPT, Microsoft Speech Services, and
the state-of-the-art (SOTA) talking head system SadTalker. Users can engage in
human-like conversation with a digital twin and receive answers to any
questions. Also, uTalk could generate content by submitting an image and input
(text or audio). This system is hosted on Streamlit, where users will be
prompted to provide an image to serve as their AI assistant. Then, as the input
(text or audio) is provided, a set of operations will produce a video of the
avatar with the precise response. This paper outlines how SadTalker's run-time
has been optimized by 27.69% based on 25 frames per second (FPS) generated
videos and 38.38% compared to our 20FPS generated videos. Furthermore, the
integration and parallelization of SadTalker and Streamlit have resulted in a
9.8% improvement compared to the initial performance of the system.


  In a semiconductor, collective excitations of spin textures usually decay
rather fast due to D'yakonov-Perel' spin relaxation. The latter arises from
spin-orbit coupling, which induces wave-vector-dependent spin rotations that,
in conjunction with random disorder scattering, generate spin decoherence.
However, symmetries occurring under certain conditions can prevent the
relaxation of particular homogeneous and inhomogeneous spin textures. The
inhomogeneous spin texture, termed as persistent spin helix, is especially
appealing as it enables us to manipulate the spin orientation while retaining a
long spin lifetime. Recently, it was predicted that such symmetries can be
realized in zinc-blende two-dimensional electron gases if at least two
growth-direction Miller indices agree in modulus and the coefficients of the
Rashba and linear Dresselhaus spin-orbit couplings are suitably matched [PRL
117, 236801 (2016)]. In the present paper, we systematically analyze the impact
of the symmetry-breaking cubic Dresselhaus spin-orbit coupling, which
generically coexists in these systems, on the stability of the emerging spin
helices with respect to the growth direction. We find that, as an interplay
between orientation and strength of the effective magnetic field induced by the
cubic Dresselhaus terms, the spin relaxation is weakest for a low-symmetry
growth direction that can be well approximated by a [225] lattice vector. These
quantum wells yield a 30\% spin-helix lifetime enhancement compared to
[001]-oriented electron gases and, remarkably, require a negligible Rashba
coefficient. The rotation axis of the corresponding spin helix is only slightly
tilted out of the quantum-well plane. This makes the experimental study of the
spin-helix dynamics readily accessible for conventional optical spin
orientation measurements where spins are excited and detected along the
quantum-well growth direction.


  We prove that the divisor class group of any open Richardson variety in the
Grassmannian is trivial. Our proof uses Nagata's criterion, localizing the
coordinate ring at a suitable set of Pl\"ucker coordinates. We prove that these
Pl\"ucker coordinates are prime elements by showing that the subscheme they
define is an open subscheme of a positroid variety. Our results hold over any
field and over the integers.


  We investigate a first-order phase transition from hadronic matter to
antikaon condensed matter during the cooling stage of protoneutron stars. The
phase transition proceeds through the thermal nucleation of antikaon condensed
matter. In this connection we study the effect of shear viscosity on the
thermal nucleation rate of droplets of antikaon condensed matter. Here we adopt
the same equation of state for the calculation of shear viscosity and thermal
nucleation time. We compute the shear viscosity of neutron star matter composed
of neutrons, protons, electrons and muons using the relativistic mean field
model. The prefactor in the nucleation rate which includes the shear viscosity,
is enhanced by several orders of magnitude compared with the $T^4$
approximation of earlier calculations. Consequently the thermal nucleation time
in the $T^4$ approximation overestimates our result. Further the thermal
nucleation of an antikaon droplet might be possible in our case for surface
tension smaller than 20 MeV fm$^{-2}$.


  Current approaches to video analysis of human motion focus on raw pixels or
keypoints as the basic units of reasoning. We posit that adding higher-level
motion primitives, which can capture natural coarser units of motion such as
backswing or follow-through, can be used to improve downstream analysis tasks.
This higher level of abstraction can also capture key features, such as loops
of repeated primitives, that are currently inaccessible at lower levels of
representation. We therefore introduce Motion Programs, a neuro-symbolic,
program-like representation that expresses motions as a composition of
high-level primitives. We also present a system for automatically inducing
motion programs from videos of human motion and for leveraging motion programs
in video synthesis. Experiments show that motion programs can accurately
describe a diverse set of human motions and the inferred programs contain
semantically meaningful motion primitives, such as arm swings and jumping
jacks. Our representation also benefits downstream tasks such as video
interpolation and video prediction and outperforms off-the-shelf models. We
further demonstrate how these programs can detect diverse kinds of repetitive
motion and facilitate interactive video editing.


  A speech enhancement method based on probabilistic geometric approach to
spectral subtraction (PGA) performed on short time magnitude spectrum is
presented in this paper. A confidence parameter of noise estimation is
introduced in the gain function of the proposed method to prevent subtraction
of the overestimated and underestimated noise, which not only removes the noise
efficiently but also prevents the speech distortion. The noise compensated
magnitude spectrum is then recombined with the unchanged phase spectrum to
produce a modified complex spectrum prior to synthesize an enhanced frame.
Extensive simulations are carried out using the speech files available in the
NOIZEUS database in order to evaluate the performance of the proposed method.


  Robot grasping of deformable hollow objects such as plastic bottles and cups
is challenging as the grasp should resist disturbances while minimally
deforming the object so as not to damage it or dislodge liquids. We propose
minimal work as a novel grasp quality metric that combines wrench resistance
and the object deformation. We introduce an efficient algorithm to compute
required work to resist an external wrench for a manipulation task by solving a
linear program. The algorithm first computes the minimum required grasp force
and an estimation of the gripper jaw displacements based on the object
deformability at different locations measured with physical experiments. The
work done by the jaws is the product of the grasp force and the displacements.
The grasp quality metric is computed based on the required work under
perturbations of grasp poses to address uncertainties in actuation. We collect
460 physical grasps with a UR5 robot and a Robotiq gripper. Physical
experiments suggest the minimal work quality metric reaches 74.2% balanced
accuracy and is up to 24.2% higher than classical wrench-based quality metrics,
where the balanced accuracy is the raw accuracy normalized by the number of
successful and failed real-world grasps.


  Face anti-spoofing plays a crucial role in protecting face recognition
systems from various attacks. Previous model-based and deep learning approaches
achieve satisfactory performance for 2D face spoofs, but remain limited for
more advanced 3D attacks such as vivid masks. In this paper, we address 3D face
anti-spoofing via the proposed Hypergraph Convolutional Neural Networks
(HGCNN). Firstly, we construct a computation-efficient and posture-invariant
face representation with only a few key points on hypergraphs. The hypergraph
representation is then fed into the designed HGCNN with hypergraph convolution
for feature extraction, while the depth auxiliary is also exploited for 3D mask
anti-spoofing. Further, we build a 3D face attack database with color, depth
and infrared light information to overcome the deficiency of 3D face
anti-spoofing data. Experiments show that our method achieves the
state-of-the-art performance over widely used 3D and 2D databases as well as
the proposed one under various tests.


  Computer systems in the pipeline oil transporting that the greatest amount of
data can be gathered, analyzed and acted upon in the shortest amount of time.
Most operators now have some form of computer based monitoring system employing
either commercially available or custom developed software to run the system.
This paper presented the SCADA systems to oil pipeline in concordance to the
Romanian environmental reglementations.


  When the QCD axion is absent in full theory, the strong $CP$ problem has to
be explained by an additional mechanism, e.g., the left-right symmetry. Even
though tree-level QCD $\bar\theta$ parameter is restricted by the mechanism,
radiative corrections to $\bar\theta$ are mostly generated, which leads to a
dangerous neutron electric dipole moment (EDM). The ordinary method for
calculating the radiative $\bar\theta$ utilizes an equation $\bar \theta= -
\text{arg}\, \text{det}\, m_q^{\rm loop}$ based on the chiral rotations of
complex quark masses. In this paper, we point out that when full theory
includes extra heavy quarks, the ordinary method is unsettled for the extra
quark contributions and does not contain its full radiative corrections. We
formulate a novel method to calculate the radiative corrections to $\bar\theta$
through a direct loop-diagrammatic approach, which should be more robust than
the ordinary one. As an application, we investigate the radiative $\bar\theta$
in the minimal left-right symmetric model. We first confirm a seminal result
that two-loop level radiative $\bar\theta$ completely vanishes (corresponding
to one-loop corrections to the quark mass matrices). Furthermore, we estimate
the size of a non-vanishing radiative $\bar\theta$ at three-loop level. It is
found that the resultant induced neutron EDM is comparable to the current
experimental bound, and the expected size is restricted by the perturbative
unitarity bound in the minimal left-right model.


  Large Language Models (LLMs) have advanced automated writing assistance,
enabling complex tasks like co-writing novels and poems. However, real-world
writing typically requires various support and collaboration across stages and
scenarios. Existing research mainly examines how writers utilize single text
generators, neglecting this broader context. This paper introduces Inspo, a
web-based editor that incorporates various text generators and online crowd
workers. Through a three-phase user study, we examine writers' interactions
with Inspo for novel writing. Quantitative analyses of writing logs highlight
changes in participants' writing progress and the influence of various
text-generation models. Complementing this with qualitative insights from
semi-structured interviews, we illustrate participants' perceptions of these
models and the crowd. Based on the findings, we provide design recommendations
for the next generation of intelligent writing tools and discuss the potential
sociocultural implications of integrating AI and human input in the writing
process.


  Sites associated with high-mass star and cluster formation exhibit a
so-called hot core phase, characterized by high temperatures and column
densities of complex organic molecules. We built a comprehensive census of hot
core candidates towards the ALMA-IMF protoclusters based on the detection of
two CH3OCHO emission lines at 216.1 GHz. We used the source extraction
algorithm GExt2D to identify peaks of methyl formate (CH3OCHO) emission that is
a complex species commonly observed towards sites of star formation. We built
up a catalog of 76 hot core candidates with masses ranging from about 0.2 to 80
Msun , of which 56 are new detections. A large majority of these objects are
compact, rather circular, with deconvolved FWHM sizes of about 2300 au on
average. About 30% of our sample of methyl formate sources have core masses
above 8 Msun within sizes ranging from about 1000 au to 13400 au, which well
correspond to archetypical hot cores. The origin of the CH3OCHO emission toward
the lower-mass cores can be explained by a mixture of contribution from shocks,
or may correspond to objects in a more evolved state, i.e. beyond the hot core
stage. We find that the fraction of hot core candidates increases with the core
mass. The large fraction of hot core candidates towards the most massive cores
suggests that they rapidly enter the hot core phase and feedback effects from
the forming protostar(s) impact their environment on short time-scales.


  Brain age prediction using neuroimaging data has shown great potential as an
indicator of overall brain health and successful aging, as well as a disease
biomarker. Deep learning models have been established as reliable and efficient
brain age estimators, being trained to predict the chronological age of healthy
subjects. In this paper, we investigate the impact of a pre-training step on
deep learning models for brain age prediction. More precisely, instead of the
common approach of pre-training on natural imaging classification, we propose
pre-training the models on brain-related tasks, which led to state-of-the-art
results in our experiments on ADNI data. Furthermore, we validate the resulting
brain age biomarker on images of patients with mild cognitive impairment and
Alzheimer's disease. Interestingly, our results indicate that better-performing
deep learning models in terms of brain age prediction on healthy patients do
not result in more reliable biomarkers.


  Large scale, dynamical simulations have been performed for the two
dimensional octahedron model, describing the Kardar-Parisi-Zhang (KPZ) for
nonlinear, or the Edwards-Wilkinson (EW) class for linear surface growth. The
autocorrelation functions of the heights and the dimer lattice gas variables
are determined with high precision. Parallel random-sequential (RS) and
two-sub-lattice stochastic dynamics (SCA) have been compared. The latter causes
a constant correlation in the long time limit, but after subtracting it one can
find the same height functions as in case of RS. On the other hand the ordered
update alters the dynamics of the lattice gas variables, by increasing
(decreasing) the memory effects for nonlinear (linear) models with respect to
random-sequential. Additionally, we support the KPZ ansatz and the
Kallabis-Krug conjecture in $2+1$ dimensions and provide a precise growth
exponent value $\beta=0.2414(2)$. We show the emergence of finite size
corrections, which occur long before the steady state roughness is reached.


  Pre-trained language models have made great progress on dialogue tasks.
However, these models are typically trained on surface dialogue text, thus are
proven to be weak in understanding the main semantic meaning of a dialogue
context. We investigate Abstract Meaning Representation (AMR) as explicit
semantic knowledge for pre-training models to capture the core semantic
information in dialogues during pre-training. In particular, we propose a
semantic-based pre-training framework that extends the standard pre-training
framework (Devlin et al., 2019) by three tasks for learning 1) core semantic
units, 2) semantic relations and 3) the overall semantic representation
according to AMR graphs. Experiments on the understanding of both chit-chats
and task-oriented dialogues show the superiority of our model. To our
knowledge, we are the first to leverage a deep semantic representation for
dialogue pre-training.


  We explore the possibility that fermionic dark matter undergoes a BCS
transition to form a superfluid. This requires an attractive interaction
between fermions and we describe a possible source of this interaction induced
by torsion. We describe the gravitating fermion system with the Bogoliubov-de
Gennes formalism in the local density approximation. We solve the Poisson
equation along with the equations for the density and gap energy of the
fermions to find a self-gravitating, superfluid solution for dark matter halos.
In order to produce halos the size of dwarf galaxies, we require a particle
mass of $\sim 200\mathrm{eV}$. We find a maximum attractive coupling strength
before the halo becomes unstable. If dark matter halos do have a superfluid
component, this raises the possibility that they contain vortex lines.