  We present the science case for surveys with the Tianlai dish array
interferometer tuned to the $\left[ 1300, 1400 \right] \mathrm{MHz}$ frequency
range. Starting from a realistic generation of mock visibility data according
to the survey strategy, we reconstruct a map of the sky and perform a
foreground subtraction. We show that a survey of the North Celestial Polar cap
during a year of observing time and covering an area of $150 \, \mathrm{deg^2}$
would reach a sensitivity of $ 1.5-2 \, \mathrm{mK} $ per $1 \, \mathrm{MHz}
\times 0.25^2 \, \mathrm{deg^2 }$ voxel and be marginally impacted by
mode-mixing. Tianlai would be able to detect a handful $(\sim 10)$ of nearby
massive \HI clumps as well as a very strong cross-correlation signal of 21\,cm
intensity maps with the North Celestial Cap Survey optical galaxies. We have
also studied the performance of a mid-latitude survey, covering $\sim 1500 \,
\mathrm{deg^2}$ centered on a declination of $\delta=55^\circ$, which overlaps
the Sloan Digital Sky Survey footprint. Despite a higher noise level for the
mid-latitude survey, as well as significant distortions due to mode mixing,
Tianlai would be able to detect a highly significant cross-correlation between
the 21\,cm signal and the Sloan spectroscopic galaxy sample. Using the
extragalactic signals from either or both of these surveys, it will be possible
to assess the impact of calibration uncertainties, antenna pattern
uncertainties, sources of noise, and mode mixing for future surveys requiring
higher sensitivity.


  Over the last few years, machine learning based methods have been applied to
extract information from news flow in the financial domain. However, this
information has mostly been in the form of the financial sentiments contained
in the news headlines, primarily for the stock prices. In our current work, we
propose that various other dimensions of information can be extracted from news
headlines, which will be of interest to investors, policy-makers and other
practitioners. We propose a framework that extracts information such as past
movements and expected directionality in prices, asset comparison and other
general information that the news is referring to. We apply this framework to
the commodity "Gold" and train the machine learning models using a dataset of
11,412 human-annotated news headlines (released with this study), collected
from the period 2000-2019. We experiment to validate the causal effect of news
flow on gold prices and observe that the information produced from our
framework significantly impacts the future gold price.


  Batra and Casas (1976) claimed that 'a strong Rybczynski result' arises in
the three-factor two-good general equilibrium trade model. In subsequent
comments, Suzuki (1983) contended that this could not be the case. Among his
comments, Suzuki found that the set of three equations holds for the
Allen-partial elasticity of substitution under the assumption of perfect
complementarity, and he applied these to his analysis. In the following, I
demonstrate that these are impossible, hence his dissenting proof is not
plausible.


  This paper details our speaker diarization system designed for multi-domain,
multi-microphone casual conversations. The proposed diarization pipeline uses
weighted prediction error (WPE)-based dereverberation as a front end, then
applies end-to-end neural diarization with vector clustering (EEND-VC) to each
channel separately. It integrates the diarization result obtained from each
channel using diarization output voting error reduction plus overlap
(DOVER-LAP). To harness the knowledge from the target domain and results
integrated across all channels, we apply self-supervised adaptation for each
session by retraining the EEND-VC with pseudo-labels derived from DOVER-LAP.
The proposed system was incorporated into NTT's submission for the distant
automatic speech recognition task in the CHiME-7 challenge. Our system achieved
65 % and 62 % relative improvements on development and eval sets compared to
the organizer-provided VC-based baseline diarization system, securing third
place in diarization performance.


  In this paper a class of expanding lorentzian traversable wormholes is
discussed.


  We study what two-stage least squares (2SLS) identifies in models with
multiple treatments under treatment effect heterogeneity. Two conditions are
shown to be necessary and sufficient for the 2SLS to identify positively
weighted sums of agent-specific effects of each treatment: average conditional
monotonicity and no cross effects. Our identification analysis allows for any
number of treatments, any number of continuous or discrete instruments, and the
inclusion of covariates. We provide testable implications and present
characterizations of choice behavior implied by our identification conditions.


  We discuss a string-net construction on 2-framed surfaces, taking as
algebraic input a finite, rigid tensor category, which is neither assumed to be
pivotal nor semi-simple. It is shown that circle categories of our framed
string-net construction essentially compute Drinfeld centers twisted by powers
of the double dual functor.


  A 12.5 GHz-spaced optical frequency comb locked to a Global Positioning
disciplined oscillator for near-IR spectrograph calibration is presented. The
comb is generated via filtering a 250 MHz-spaced comb. Subsequency nonlinear
broadening of the 12.5 GHz comb extends the wavelength range to cover 1380 nm
to 1820 nm, providing complete coverage over the H-band transmission widow of
Earth's atmosphere. Finite suppression of spurious sidemodes, optical linewidth
and instability of the comb have been examined to estmiate potential wavelength
biases in spectrograph calibration. Sidemode suppression varies between 20 db
and 45 dB, and the optical linewidth is ~350 kHz at 1550 nm. The comb frequency
uncertainty is bounded by +/- 30 kHz (corresponding to a radial velocity of +/-
5 cm/s), limited by the Global Positioning System disciplined oscillator
reference. These results indicate this comb can readily support radial velocity
measurements below 1 m/s in the near-IR.


  Considering the diffraction of a plane wave by a periodically corrugated
half-space, we show that the transformation of the refracting medium from
positive/negative phase-velocity to negative/positive phase-velocity type has
an influence on the diffraction efficiencies. This effect increases with
increasing corrugation depth, owing to the presence of evanescent waves in the
troughs of the corrugated interface.


  This paper introduce the notion of output contraction that expands the
contraction notion to the time-varying nonlinear systems with output. It
pertains to the systems' property that any pair of outputs from the system
converge to each other exponentially. This concept exhibits a more expansive
nature when contrasted with another generalized contraction framework known as
partial contraction. The first result establishes a connection between the
output contraction of a time-varying system and the output exponential
stability of its variational system. Subsequently, we derive a sufficient
condition for achieving output contraction in time-varying systems by applying
the output contraction Lyapunov criterion. Finally, we apply the results to
analyze the output exponential stability of nonlinear time-invariant systems.


  This paper democratizes neural information retrieval to scenarios where large
scale relevance training signals are not available. We revisit the classic IR
intuition that anchor-document relations approximate query-document relevance
and propose a reinforcement weak supervision selection method, ReInfoSelect,
which learns to select anchor-document pairs that best weakly supervise the
neural ranker (action), using the ranking performance on a handful of relevance
labels as the reward. Iteratively, for a batch of anchor-document pairs,
ReInfoSelect back propagates the gradients through the neural ranker, gathers
its NDCG reward, and optimizes the data selection network using policy
gradients, until the neural ranker's performance peaks on target relevance
metrics (convergence). In our experiments on three TREC benchmarks, neural
rankers trained by ReInfoSelect, with only publicly available anchor data,
significantly outperform feature-based learning to rank methods and match the
effectiveness of neural rankers trained with private commercial search logs.
Our analyses show that ReInfoSelect effectively selects weak supervision
signals based on the stage of the neural ranker training, and intuitively picks
anchor-document pairs similar to query-document pairs.


  We propose a numerical recipe for risk evaluation defined by a backward
stochastic differential equation. Using dual representation of the risk
measure, we convert the risk valuation to a stochastic control problem where
the control is a certain Radon-Nikodym derivative process. By exploring the
maximum principle, we show that a piecewise-constant dual control provides a
good approximation on a short interval. A dynamic programming algorithm extends
the approximation to a finite time horizon. Finally, we illustrate the
application of the procedure to financial risk management in conjunction with
nested simulation and on an multidimensional portfolio valuation problem.


  Glasses have a large excess of low-frequency vibrational modes in comparison
with most crystalline solids. We show that such a feature is a necessary
consequence of the weak connectivity of the solid, and that the frequency of
modes in excess is very sensitive to the pressure. We analyze in particular two
systems whose density D(w) of vibrational modes of angular frequency w display
scaling behaviors with the packing fraction: (i) simulations of jammed packings
of particles interacting through finite-range, purely repulsive potentials,
comprised of weakly compressed spheres at zero temperature and (ii) a system
with the same network of contacts, but where the force between any particles in
contact (and therefore the total pressure) is set to zero. We account in the
two cases for the observed a) convergence of D(w) toward a non-zero constant as
w goes to 0, b) appearance of a low-frequency cutoff w*, and c) power-law
increase of w* with compression. Differences between these two systems occur at
lower frequency. The density of states of the modified system displays an
abrupt plateau that appears at w*, below which we expect the system to behave
as a normal, continuous, elastic body. In the unmodified system, the pressure
lowers the frequency of the modes in excess. The requirement of stability
despite the destabilizing effect of pressure yields a lower bound on the number
of extra contact per particle dz: dz > p^(1/2), which generalizes the Maxwell
criterion for rigidity when pressure is present. This scaling behavior is
observed in the simulations. We finally discuss how the cooling procedure can
affect the microscopic structure and the density of normal modes.


  Stochastic variational inference offers an attractive option as a default
method for differentiable probabilistic programming. However, the performance
of the variational approach depends on the choice of an appropriate variational
family. Here, we introduce automatic structured variational inference (ASVI), a
fully automated method for constructing structured variational families,
inspired by the closed-form update in conjugate Bayesian models. These
convex-update families incorporate the forward pass of the input probabilistic
program and can therefore capture complex statistical dependencies.
Convex-update families have the same space and time complexity as the input
probabilistic program and are therefore tractable for a very large family of
models including both continuous and discrete variables. We validate our
automatic variational method on a wide range of low- and high-dimensional
inference problems. We find that ASVI provides a clear improvement in
performance when compared with other popular approaches such as the mean-field
approach and inverse autoregressive flows. We provide an open source
implementation of ASVI in TensorFlow Probability.


  Scintillation materials convert high-energy radiation to optical light
through a complex multi-stage process. The last stage of the process is light
emission via spontaneous emission, which usually governs and limits the
scintillator emission rate and light yield. For decades, the quest for faster
emission rate and greater light yield motivated the frontier of scintillators
research to focus on developing better materials and dopants. Here, we
experimentally demonstrate a fundamentally different, recently proposed concept
for enhancing the scintillation rate and yield: the Purcell effect. The Purcell
effect is a universal enhancement mechanism for spontaneous emission by
engineering the optical environment. In scintillators, such an enhancement
arises from engineering the nanoscale geometry within the scintillation bulk,
which thus applies universally to any scintillating material and dopant. We
design and fabricate a thin multilayer nanophotonic scintillator, demonstrating
Purcell-enhanced scintillation, achieving a 50% enhancement in emission-rate
and an 80% enhancement in light yield. We demonstrate the potential of our
device for realizing these enhancements in real-life settings for X-ray
applications, also due to the robustness of the nanophotonic design to
fabrication disorder. Our results show the bright prospects of bridging
nanophotonics and scintillators science, toward reduced radiation dosage and
increased resolution for high-energy particles detection.


  We have a lot of relation to the encoding and the Theory of Information, when
considering thinking. This is a natural process and, at once, the complex thing
we investigate. This always was a challenge - to understand how our mind works,
and we are trying to find some universal models for this. A lot of ways have
been considered so far, but we are looking for Something, we seek for
approaches. And the goal is to find a consistent, noncontradictory view, which
should at once be enough flexible in any dimensions to allow to represent
various kinds of processes and environments, matters of different nature and
diverse objects. Developing of such a model is the destination of this article.


  The nature of chiral phase transition of massless two flavor QCD depends on
the fate of flavor singlet axial symmetry $U_A(1)$ at the critical temperature
($T_c$). Assuming that a finite $U_A(1)$ breaking remains at $T_c$, the
corresponding three dimensional effective theory is composed of four massless
and four massive scalar fields. We study the renormalization group flow of the
effective theory in the $\epsilon$-expansion, using a mass dependent
renormalization scheme, and determine the region of the attractive basin
flowing into the $O(4)$ fixed point with a focus on its dependence on the size
of the $U_A(1)$ breaking. The result is discussed from a perspective of the
decoupling of massive fields. It is pointed out that, although the effective
theory inside the attractive basin eventually reaches the $O(4)$ fixed point,
the approaching rate, one of the universal exponents, is different from that of
the standard $O(4)$ model. We present the reason for this peculiarity, and
propose a novel possibility for chiral phase transition in two-flavor QCD.


  Reinforcement learning from human feedback (RLHF) is a variant of
reinforcement learning (RL) that learns from human feedback instead of relying
on an engineered reward function. Building on prior work on the related setting
of preference-based reinforcement learning (PbRL), it stands at the
intersection of artificial intelligence and human-computer interaction. This
positioning offers a promising avenue to enhance the performance and
adaptability of intelligent systems while also improving the alignment of their
objectives with human values. The training of large language models (LLMs) has
impressively demonstrated this potential in recent years, where RLHF played a
decisive role in directing the model's capabilities toward human objectives.
This article provides a comprehensive overview of the fundamentals of RLHF,
exploring the intricate dynamics between RL agents and human input. While
recent focus has been on RLHF for LLMs, our survey adopts a broader
perspective, examining the diverse applications and wide-ranging impact of the
technique. We delve into the core principles that underpin RLHF, shedding light
on the symbiotic relationship between algorithms and human feedback, and
discuss the main research trends in the field. By synthesizing the current
landscape of RLHF research, this article aims to provide researchers as well as
practitioners with a comprehensive understanding of this rapidly growing field
of research.


  We present ALMA 870-um (345GHz) observations of two sub-millimetre galaxies
(SMGs) drawn from an ALMA study of the 126 sub-millimeter sources from the
LABOCA Extended Chandra Deep Field South Survey (LESS). The ALMA data identify
the counterparts to these previously unidentified sub-millimeter sources and
serendipitously detect bright emission lines in their spectra which we show are
most likely to be [C II]157.74um emission yielding redshifts of z=4.42 and
z=4.44. This blind detection rate within the 7.5-GHz bandpass of ALMA is
consistent with the previously derived photometric redshift distribution of
SMGs and suggests a modest, but not dominant (<25%), tail of 870-um selected
SMGs at z>4. We find that the ratio of L_CII/L_FIR in these SMGs is much higher
than seen for similarly far-infrared-luminous galaxies at z~0, which is
attributed to the more extended gas reservoirs in these high-redshift ULIRGs.
Indeed, in one system we show that the [C II] emission shows hints of extended
emission on >3kpc scales. Finally, we use the volume probed by our ALMA survey
to show that the bright end of the [C II] luminosity function evolves strongly
between z=0 and z~4.4, reflecting the increased ISM cooling in galaxies as a
result of their higher star-formation rates. These observations demonstrate
that even with short integrations, ALMA is able to detect the dominant fine
structure cooling lines from high-redshift ULIRGs, measure their energetics and
trace their evolution with redshift.


  As phenomena that necessarily emerge from the collective behavior of
interacting particles, phase transitions continue to be difficult to predict
using statistical thermodynamics. A recent proposal called the topological
hypothesis suggests that the existence of a phase transition could perhaps be
inferred from changes to the topology of the accessible part of the
configuration space. This paper instead suggests that such a topological change
is often associated with a dramatic change in the configuration space geometry,
and that the geometric change is the actual driver of the phase transition.
More precisely, a geometric change that brings about a discontinuity in the
mixing time required for an initial probability distribution on the
configuration space to reach steady-state is conjectured to be related to the
onset of a phase transition in the thermodynamic limit. This conjecture is
tested by evaluating the diffusion diameter and $\epsilon$-mixing time of the
configuration spaces of hard disk and hard sphere systems of increasing size.
Explicit geometries are constructed for the configuration spaces of these
systems, and numerical evidence suggests that a discontinuity in the
$\epsilon$-mixing time coincides with the solid-fluid phase transition in the
thermodynamic limit.


  We prove an estimate for the rank of the intersection of free subgroups in
virtually free groups, which is analogous to the Hanna Neumann inequality for
subgroups in a free group and to the S.V. Ivanov estimate for subgroups in free
products of groups. We also prove a more general estimate for the rank of the
intersection of free subgroups in the fundamental group of a finite graph of
groups with finite edge groups.


  We derive from first principles the Kubo formulas for the stress-stress
response function at zero wavevector that can be used to define the full
complex frequency-dependent viscosity tensor, both with and without a uniform
magnetic field. The formulas in the existing literature are frequently
incomplete, incorrect, or lack a derivation; in particular, Hall viscosity is
overlooked. Our approach begins from the response to a uniform external strain
field, which is an active time-dependent coordinate transformation in d space
dimensions. These transformations form the group GL(d,R) of invertible
matrices, and the infinitesimal generators are called strain generators. These
enable us to express the Kubo formula in different ways, related by Ward
identities; some of these make contact with the adiabatic transport approach.
For Galilean-invariant systems, we derive a relation between the stress
response tensor and the conductivity tensor that is valid at all frequencies
and in both the presence and absence of a magnetic field. In the presence of a
magnetic field and at low frequency, this yields a relation between the Hall
viscosity, the q^2 part of the Hall conductivity, the inverse compressibility
(suitably defined), and the diverging part of the shear viscosity (if any);
this relation generalizes a result found recently. We show that the correct
value of the Hall viscosity at zero frequency can be obtained (at least in the
absence of low-frequency bulk and shear viscosity) by assuming that there is an
orbital spin per particle that couples to a perturbing electromagnetic field as
a magnetization per particle. We study several examples as checks on our
formulation.


  We consider the Fourier restriction operators associated to certain
degenerate curves in R^d for which the highest torsion vanishes. We prove
estimates with respect to affine arclength and with respect to the Euclidean
arclength measure on the curve. The estimates have certain uniform features,
and the affine arclength results cover families of flat curves.


  This is the third of a series of papers on a new equivariant cohomology that
takes values in a vertex algebra, and contains and generalizes the classical
equivariant cohomology of a manifold with a Lie group action a la H. Cartan. In
this paper, we compute this cohomology for spheres and show that for any simple
connected group G, there is a sphere with infinitely many actions of G which
have distinct chiral equivariant cohomology, but identical classical
equivariant cohomology. Unlike the classical case, the description of the
chiral equivariant cohomology of spheres requires a substantial amount of new
structural theory, which we fully develop in this paper. This includes a
quasi-conformal structure, equivariant homotopy invariance, and the values of
this cohomology on homogeneous spaces. These results rely on crucial features
of the underlying vertex algebra valued complex that have no classical
analogues.


  The recent discovery of high redshift dusty galaxies implies a rapid dust
enrichment of their interstellar medium (ISM). To interpret these observations,
we run a cosmological simulation in a 30$h^{-1}$ cMpc/size volume down to $z
\approx 4$. We use the hydrodynamical code dustyGadget, which accounts for the
production of dust by stellar populations and its evolution in the ISM. We find
that the cosmic dust density parameter ($\Omega_{\rm d}$) is mainly driven by
stellar dust at $z \gtrsim 10$, so that mass- and metallicity-dependent yields
are required to assess the dust content in the first galaxies. At $z \lesssim
9$ the growth of grains in the ISM of evolved systems
(Log$(M_{\star}/M_{\odot})>8.5$) significantly increases their dust mass, in
agreement with observations in the redshift range $4 \lesssim z < 8$. Our
simulation shows that the variety of high redshift galaxies observed with ALMA
can naturally be accounted for by modeling the grain-growth timescale as a
function of the physical conditions in the gas cold phase. In addition, the
trends of dust-to-metal (DTM) and dust-to-gas (${\cal D}$) ratios are
compatible with the available data. A qualitative investigation of the
inhomogeneous dust distribution in a representative massive halo at $z \approx
4$ shows that dust is found from the central galaxy up to the closest
satellites along polluted filaments with $\rm Log({\cal D}) \leq -2.4$, but
sharply declines at distances $d \gtrsim 30$ kpc along many lines of sight,
where $\rm Log({\cal D}) \lesssim -4.0$.


  We show that for all epsilon > 0, there is a constant C(epsilon) > 0 such
that for all elliptic curves E defined over a number field F with j(E) in Q we
have #E(F)[tors] \leq C(epsilon)[F:Q]^{5/2+epsilon}. We pursue further bounds
on the size of the torsion subgroup of an elliptic curve over a number field
E/F that are polynomial in [F:Q] under restrictions on j(E). We give an
unconditional result for j(E) lying in a fixed quadratic field that is not
imaginary of class number one as well as two further results, one conditional
on GRH and one conditional on the strong boundedness of isogenies of prime
degree for non-CM elliptic curves.


  Dispersion diagrams play a crucial role in examining, analyzing and designing
wave propagation in periodic structures. Despite their ubiquity and current
research interest, introductory papers and reference scripting tailored to
novel researchers in the field are lacking. This paper aims to address this
gap, by presenting a comprehensive educational resource for researchers
starting in the field of periodic structures and more specifically on the study
of dispersion relations captured by dispersion surfaces or curves in dispersion
diagrams. The objective is twofold. A first objective is to give a detailed
explanation of dispersion diagrams, with graphical illustrations. Secondly, a
documented Matlab code is provided to compute dispersion curves of 3D
structures with 2D periodicity using the so-called inverse approach. These
dispersion curves are obtained with numerical simulations using the finite
element method. The code is written for elastic wave propagation and orthogonal
periodicity directions, but can be extended to other types of linear wave
propagation, non-orthogonal periodicity directions or 1D and 3D periodicity.
The aim of this code is to serve as a starting point for novice researchers in
the field, to facilitate their understanding of different aspects of dispersion
diagrams and serve as a stepping stone in their future research.


  Mitigating losses from supply and demand volatility in the semiconductor
supply chain and market has traditionally been cast as a logistics and
forecasting problem. We investigate how the architecture of a family of chips
influences how it is affected by supply and demand uncertainties. We observe
that semiconductor supply chains become fragile, in part, due to single demand
paths, where one chip can satisfy only one demand. Chip architects can enable
multiple paths to satisfy a chip demand, which improves supply chain
resilience. Based on this observation, we study composition and adaptation as
architectural strategies to improve resilience to volatility and also introduce
a third strategy of dispersion. These strategies allow multiple paths to
satisfy a given chip demand. We develop a model to analyze the impact of these
architectural techniques on supply chain costs under different regimes of
uncertainties and evaluate what happens when they are combined. We present
several interesting and even counterintuitive observations about the product
configurations and market conditions where these interventions are impactful
and where they are not. In all, we show that product redesign supported by
architectural changes can mitigate nearly half of the losses caused by supply
and demand volatility. As far as we know, this is the first such investigation
concerning chip architecture.


  The original hypothesis about Three-stage origin of life (TOL) on the Earth
is developed and discussed. The role of the temperature factor in life origin
is considered. It is supposed, that three stages of abiogenesis (DNA world, RNA
world and the Protein world) consistently followed each other during Darwinian
evolution. At the same time, the natural directional selection of the most
stable macromolecules and effective catalytic reactions took place. The
direction of this selection is related to action of the principle of
{\guillemotleft}Increasing Independence from the Environment{\guillemotright}
(IIE) and is caused by temperature evolution of the atmosphere of the Earth.
The direction of Anagenesis and inevitability of occurrence of genetic
mechanisms is discussed.


  Modeling non Gaussian and non stationary signals and images has always been
one of the most important part of signal and image processing methods. In this
paper, first we propose a few new models, all based on using hidden variables
for modeling either stationary but non Gaussian or Gaussian but non stationary
or non Gaussian and non stationary signals and images. Then, we will see how to
use these models in independent component analysis (ICA) or blind source
separation (BSS). The computational aspects of the Bayesian estimation
framework associated with these prior models are also discussed.


  The rapidly growing demands for powerful AI algorithms in many application
domains have motivated massive investment in both high-quality deep neural
network (DNN) models and high-efficiency implementations. In this position
paper, we argue that a simultaneous DNN/implementation co-design methodology,
named Neural Architecture and Implementation Search (NAIS), deserves more
research attention to boost the development productivity and efficiency of both
DNN models and implementation optimization. We propose a stylized design
methodology that can drastically cut down the search cost while preserving the
quality of the end solution.As an illustration, we discuss this
DNN/implementation methodology in the context of both FPGAs and GPUs. We take
autonomous driving as a key use case as it is one of the most demanding areas
for high quality AI algorithms and accelerators. We discuss how such a
co-design methodology can impact the autonomous driving industry significantly.
We identify several research opportunities in this exciting domain.


  The characterization of solar surface differential rotation (SDR) from
disk-integrated chromospheric measurements has important implications for the
study of differential rotation and dynamo processes in other stars. Some
chromospheric lines, such as Ca II K, are very sensitive to the presence of
activity on the disk and are an ideal choice for investigating SDR in Sun-as-a
star observations. Past studies indicate that when the activity is low, the
determination of Sun's differential rotation from integrated-sunlight
measurements becomes uncertain. However, our study shows that using the proper
technique, SDR can be detected from these type of measurements even during
periods of extended solar minima. This paper describes results from the
analysis of the temporal variations of Ca II K line profiles observed by the
Integrated Sunlight Spectrometer (ISS) during the declining phase of Cycle 23
and the rising phase of Cycle 24, and discusses the signature of SDR in the
power spectra computed from time series of parameters derived from these
profiles. The described methodology is quite general, and could be applied to
photometric time series of other Main-Sequence stars for detecting differential
rotation.


  It is shown that pinning of an electron Wigner crystal by a small
concentration of charged impurities creates the finite density of charged
localized states near the Fermi level. In the case of residual impurities in
the spacer this density of states is related to nonlinear screening of a close
acceptor by a Wigner crystal vacancy. On the other hand, intentional doping by
a remote layer of donors is a source of a long range potential, which generates
dislocations in Wigner crystal. Dislocations in turn create charged localized
states near the Fermi level. In both cases Coulomb interaction of localized
states leads to the soft Coulomb gap and ES variable range hopping at low
enough temperatures.


  In this paper we propose an effective vision-based navigation method that
allows a multirotor vehicle to simultaneously reach a desired goal pose in the
environment while constantly facing a target object or landmark. Standard
techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual
Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast
maneuvers) do not allow to constantly maintain the line of sight with a target
of interest. Instead, we compute the optimal trajectory by solving a non-linear
optimization problem that minimizes the target re-projection error while
meeting the UAV's dynamic constraints. The desired trajectory is then tracked
by means of a real-time Non-linear Model Predictive Controller (NMPC): this
implicitly allows the multirotor to satisfy both the required constraints. We
successfully evaluate the proposed approach in many real and simulated
experiments, making an exhaustive comparison with a standard approach.


  A shear-free ray congruence on Minkowski space is a 3-parameter family of
null geodesics along which Lie transport of a complementary 2-dimensional
spacelike subspace (called the screen space) is conformal. Such congruences are
defined by complex analytic surfaces in the associated twistor space $\CP^3$
and are the basis of the construction of massless fields. On a more general
space-time, it is unclear how to couple the massless field with the
gravitational field. In this article we do this by considering the following
Cauchy-type problem: given a Riemannian 3-manifold $(M^3, g_0)$ endowed with a
unit vector field $U_0$ that is tangent to a conformal foliation, we require
that the pair extend to a space-time $({\mathcal M}, {\mathcal G})$ endowed
with a spacelike unit vector field $U_t$ in such a way that $U_t$
simultaneously generates null geodesics and is tangent to a conformal foliation
on spacelike slices $t=$ const.


  Let $\{L(t),t\geq 0\}$ be a L\'{e}vy process with representative random
variable $L(1)$ defined by the infinitely divisible logarithmic series
distribution. We study here the transition probability and L\'{e}vy measure of
this process. We also define two subordinated processes. The first one, $Y(t)$,
is a Negative-Binomial process $X(t)$ directed by Gamma process. The second
process, $Z(t)$, is a Logarithmic L\'{e}vy process $L(t)$ directed by Poisson
process. For them, we prove that the Bernstein functions of the processes
$L(t)$ and $Y(t)$ contain the iterated logarithmic function. In addition, the
L\'{e}vy measure of the subordinated process $Z(t)$ is a shifted L\'{e}vy
measure of the Negative-Binomial process $X(t)$. We compare the properties of
these processes, knowing that the total masses of corresponding L\'{e}vy
measures are equal.


  Tools for fighting cyber-criminal activities using new technologies are
promoted and deployed every day. However, too often, they are unnecessarily
complex and hard to use, requiring deep domain and technical knowledge. These
characteristics often limit the engagement of law enforcement and end-users in
these technologies that, despite their potential, remain misunderstood. For
this reason, in this study, we describe our experience in combining learning
and training methods and the potential benefits of gamification to enhance
technology transfer and increase adult learning. In fact, in this case,
participants are experienced practitioners in professions/industries that are
exposed to terrorism financing (such as Law Enforcement Officers, Financial
Investigation Officers, private investigators, etc.) We define training
activities on different levels for increasing the exchange of information about
new trends and criminal modus operandi among and within law enforcement
agencies, intensifying cross-border cooperation and supporting efforts to
combat and prevent terrorism funding activities. On the other hand, a game
(hackathon) is designed to address realistic challenges related to the dark
net, crypto assets, new payment systems and dark web marketplaces that could be
used for terrorist activities. The entire methodology was evaluated using
quizzes, contest results, and engagement metrics. In particular, training
events show about 60% of participants complete the 11-week training course,
while the Hackathon results, gathered in two pilot studies (Madrid and The
Hague), show increasing expertise among the participants (progression in the
achieved points on average). At the same time, more than 70% of participants
positively evaluate the use of the gamification approach, and more than 85% of
them consider the implemented Use Cases suitable for their investigations.


  Let $\mathbb{k}$ be an algebraically closed field. We give a complete
classification of non-connected pointed Hopf algebras of dimension $16$ with
char$\,\mathbb{k}=2$ that are generated by group-like elements and
skew-primitive elements. It turns out that there are infinitely many classes
(up to isomorphism) of pointed Hopf algebras of dimension 16. In particular, we
obtain infinitely many new examples of non-commutative non-cocommutative
finite-dimensional pointed Hopf algebras.


  In the approach to the stationary regime, a spaser exhibits complicated and
highly nonlinear dynamics with anharmonic oscillations.1 We demonstrate that
these oscillations are due to Rabi oscillations of the quantum dot in the field
of the nanoparticle. We show that the oscillations may or may not arise
dependent on the initial conditions.


  The 1/$N_c$ arguments are developed to classify the hadronic states in the
correlators. Arguments applied to the $\sigma$ meson correlator enable to
separate the instanton, glueball, and, in particular, the $\pi\pi$ scattering
states by $1/N_c$ from both 2q and 4q correlators. The bare resonance pole with
no mixing effects are analyzed with the QCD sum rules (QSR). The results
suggest the existence of nontrivial correlation for the mass reduction of 4q
system.


  We constructed an open multi-access network platform using open-source
hardware and software. The open multi-access network platform is characterized
by the flexible utilization of network functions, integral management and
control of wired and wireless access networks, zero-touch provisioning,
intelligent resource monitoring, and dynamic task offloading. We also propose
an application-driven dynamic task offloading that utilizes intelligent
resource monitoring to ensure effective task processing in edge and cloud
servers. For this purpose, we developed a mobile application and server
applications for the open multi-access network platform. To investigate the
feasibility and availability of our developed platform, we experimentally and
analytically evaluated the effectiveness of application-driven dynamic task
offloading and intelligent resource monitoring. The experimental results
demonstrated that application-driven dynamic task offloading could reduce
real-time task response time and traffic over metro and core networks.


  We investigate collective synchronous behaviors in random complex networks of
limit-cycle oscillators with the non-identical asymmetric coupling scheme, and
find a uniform coupling criticality of collective synchronization which is
independent of complexity of network topologies. Numerically simulations on
categories of random complex networks have verified this conclusion.


  We undertake a detailed study of the performance of maximum likelihood (ML)
estimators of the density matrix of finite-dimensional quantum systems, in
order to interrogate generic properties of frequentist quantum state
estimation. Existing literature on frequentist quantum estimation has not
rigorously examined the finite sample performance of the estimators and
associated methods of hypothesis testing. While ML is usually preferred on the
basis of its asymptotic properties - it achieves the Cramer-Rao (CR) lower
bound - the finite sample properties are often less than optimal. We compare
the asymptotic and finite-sample properties of the ML estimators and test
statistics for two different choices of measurement bases: the average case
optimal or mutually unbiased bases (MUB) and a representative set of suboptimal
bases, for spin-1/2 and spin-1 systems. We show that, in both cases, the
standard errors of the ML estimators sometimes do not contain the true value of
the parameter, which can render inference based on the asymptotic properties of
the ML unreliable for experimentally realistic sample sizes. The results
indicate that in order to fully exploit the information geometry of quantum
states and achieve smaller reconstruction errors, the use of Bayesian state
reconstruction methods - which, unlike frequentist methods, do not rely on
asymptotic properties - is desirable, since the estimation error is typically
lower due to the incorporation of prior knowledge.


  We discuss symmetry-driven squeezing and coherent states of few-particle
systems in magnetic fields. An operator approach using canonical
transformations and the SU(1,1) algebras is developed for considering Coulomb
correlations in the lowest Landau levels.


  A large fraction of online display advertising is sold via guaranteed
contracts: a publisher guarantees to the advertiser a certain number of user
visits satisfying the targeting predicates of the contract. The publisher is
then tasked with solving the ad serving problem - given a user visit, which of
the thousands of matching contracts should be displayed, so that by the
expiration time every contract has obtained the requisite number of user
visits. The challenges of the problem come from (1) the sheer size of the
problem being solved, with tens of thousands of contracts and billions of user
visits, (2) the unpredictability of user behavior, since these contracts are
sold months ahead of time, when only a forecast of user visits is available and
(3) the minute amount of resources available online, as an ad server must
respond with a matching contract in a fraction of a second.
  We present a solution to the guaranteed delivery ad serving problem using
{\em compact allocation plans}. These plans, computed offline, can be
efficiently queried by the ad server during an ad call; they are small, using
only O(1) space for contract; and are stateless, allowing for distributed
serving without any central coordination. We evaluate this approach on a real
set of user visits and guaranteed contracts and show that the compact
allocation plans are an effective way of solving the guaranteed delivery ad
serving problem.


  In this paper a new supersymmetric extension of conformal mechanics is put
forward. The beauty of this extension is that all variables have a clear
geometrical meaning and the super-Hamiltonian turns out to be the
Lie-derivative of the Hamiltonian flow of standard conformal mechanics. In this
paper we also provide a supersymmetric extension of the other conformal
generators of the theory and find their "square-roots". The whole superalgebra
of these charges is then analyzed in details. We conclude the paper by showing
that, using superfields, a constraint can be built which provides the exact
solution of the system.


  We construct asymptotically flat, spinning, regular on and outside an event
horizon, scalarised black holes (SBHs) in extended scalar-tensor-Gauss-Bonnet
models. They reduce to Kerr BHs when the scalar field vanishes. For an
illustrative choice of non-minimal coupling, we scan the domain of existence.
For each value of spin, SBHs exist in an interval between two critical masses,
with the lowest one vanishing in the static limit. Non-uniqueness with Kerr BHs
of equal global charges is observed; the SBHs are entropically favoured. This
suggests SBHs form dynamically from the spontaneous scalarisation of Kerr BHs,
which are prone to a scalar-triggered tachyonic instability, below the largest
critical mass. Phenomenologically, the introduction of BH spin damps the
maximal observable difference between comparable scalarised and vacuum BHs. In
the static limit, (perturbatively stable) SBHs can store over 20% of the
spacetime energy outside the event horizon; in comparison with Schwarzschild
BHs, their geodesic frequency at the ISCO can differ by a factor of 2.5 and
deviations in the shadow areal radius may top 40%. As the BH spin grows, low
mass SBHs are excluded, and the maximal relative differences decrease, becoming
of order $\sim$ few % for dimensionless spin $j\gtrsim 0.5$. This reveals a
spin selection effect: non-GR effects are only significant for low spin. We
discuss if and how the recently measured shadow size of the M87 supermassive
BH, constrains the length scale of the Gauss-Bonnet coupling.


  The present paper clarifies how to consistently take into account the
contribution of magnetic charges in the generalized Smarr mass formula by using
properly the Tomimatsu's representation of Komar integrals. It is shown in
particular that in all three examples of the dyonic solutions considered by us,
the sum of the two electromagnetic terms in Smarr's formula can be cast into
the form $\bar{\cal Q}\Phi^H_{ext}$, where ${\cal Q}$ is the complex charge and
$\Phi^H_{ext}$ the complex extension of the electric potential.


  The deformed double covering of E(2) group, denoted by $\tilde{E}_\kappa(2)$,
is obtained by contraction from the $SU_\mu(2)$. The contraction procedure is
then used for producing a new examples of differential calculi: 3D-left
covariant calculus on both $\tilde{E}_\kappa(2)$ and the deformed Euclidean
group $E_\kappa(2)$ and two different 4D-bicovariant calculi on
$\tilde{E}_\kappa(2)$ which correspond to the one 4D-bicovariant calculi on
$E_\kappa(2)$ described in Ref.\cite{b14}.


  The mechanism by which galaxies stop forming stars and get rid of their
interstellar medium (ISM) remains elusive. Here, we study a sample of more than
two thousand elliptical galaxies in which dust emission has been detected. This
is the largest sample of such galaxies ever analysed. We infer the timescale
for removal of dust in these galaxies and investigate its dependency on
physical and environmental properties. We obtain a dust removal timescale in
elliptical galaxies of $\tau$ = 2.26 $\pm$ 0.18 Gyr, corresponding to a
half-life time of 1.57 $\pm$ 0.12 Gyr. This timescale does not depend on
environment, stellar mass or redshift. We observe a departure of dusty
elliptical galaxies from the star formation rate vs. dust mass relation. This
is caused by the star-formation rates declining faster than the dust masses and
indicates that there exists an internal mechanism, which affects star
formation, but leaves the ISM intact. Morphological quenching together with
ionisation or outflows caused by older stellar populations (supernova type Ia
or planetary nebulae) are consistent with these observations.


  Portable miniaturized energy storage micro-supercapacitor has engrossed
significant attention due to its power source and energy storage capacity,
replacing batteries in ultra-small electronic devices. Fabrication with porous
and 2D graphitic nanomaterials with high conductivity and surface area signify
high performance of micro-supercapacitor. In order to satisfy the fast-growing
energy demands for the next-generation, we report performance and design of a
2D heterostructure of EDLC (g-C$_3$N$_4$) & pseudocapacitive (FeNi$_3$)
resulting low ionic diffusion path and prominent charge storage based on their
synergic functionalities. This heterostructure system shows an enhanced quantum
capacitance (38% enhancement) due to delocalized states near Fermi level.
Having achieved the areal capacitance of 19.21 mFcm$^{-2}$, capacitive
retention (94%), enhanced power density (17 fold) having ultrahigh energy
density of 0.30 Wh.cm$^{-3}$ and stability of the material even without any
obvious degradation after 1000 cycles, this smart heterostructure acts as a new
platform for designing high-performance in-plane micro-supercapacitor.


  Cais, Ellenberg and Zureick-Brown recently observed that over finite fields
of characteristic two, all sufficiently general smooth plane projective curves
of a given odd degree admit a non-trivial rational 2-torsion point on their
Jacobian. We extend their observation to curves given by Laurent polynomials
with a fixed Newton polygon, provided that the polygon satisfies a certain
combinatorial property. We also show that in each of these cases, the
sufficiently general condition is implied by being ordinary. Our treatment
includes many classical families, such as hyperelliptic curves of odd genus and
$C_{a,b}$ curves. In the hyperelliptic case, we provide alternative proofs
using an explicit description of the 2-torsion subgroup.


  Dipolar coupled homonuclear spins present challenging, yet useful systems for
quantum information processing. In such systems, eigenbasis of the system
Hamiltonian is the appropriate computational basis and coherent control can be
achieved by specially designed strongly modulating pulses. In this letter we
describe the first experimental implementation of the quantum algorithm for
numerical gradient estimation on the eigenbasis of a four spin system.


  The Discretizable Molecular Distance Geometry Problem (DMDGP) aims to
determine the three-dimensional protein structure using distance information
from nuclear magnetic resonance experiments. The DMDGP has a finite number of
candidate solutions and can be solved by combinatorial methods. We describe a
quantum approach to the DMDGP by using Grover's algorithm with an appropriate
oracle function, which is more efficient than classical methods that use brute
force. We show computational results by implementing our scheme on IBM quantum
computers with a small number of noisy qubits.


  The star HD 49385 is the first G-type solar-like pulsator observed in the
seismology field of the space telescope CoRoT. The satellite collected 137 days
of high-precision photometric data on this star, confirming that it presents
solar-like oscillations. HD 49385 was also observed in spectroscopy with the
NARVAL spectrograph in January 2009. Our goal is to characterize HD 49385 using
both spectroscopic and seismic data. The fundamental stellar parameters of HD
49385 are derived with the semi-automatic software VWA, and the projected
rotational velocity is estimated by fitting synthetic profiles to isolated
lines in the observed spectrum. A maximum likelihood estimation is used to
determine the parameters of the observed p modes. We perform a global fit, in
which modes are fitted simultaneously over nine radial orders, with degrees
ranging from l=0 to l=3 (36 individual modes). Precise estimates of the
atmospheric parameters (Teff, [M/H], log g) and of the vsini of HD 49385 are
obtained. The seismic analysis of the star leads to a clear identification of
the modes for degrees l=0,1,2. Around the maximum of the signal (nu=1013
microHz), some peaks are found significant and compatible with the expected
characteristics of l=3 modes. Our fit yields robust estimates of the
frequencies, linewidths and amplitudes of the modes. We find amplitudes of
about 5.6 +/- 0.8 ppm for radial modes at the maximum of the signal. The
lifetimes of the modes range from one day (at high frequency) to a bit more
than two days (at low frequency). Significant peaks are found outside the
identified ridges and are fitted. They are attributed to mixed modes.


  The phenomenon of Bose-like condensation, the continuous change of the
dimensionality of the particle distribution as a consequence of freezing out of
one or more degrees of freedom in the low particle density limit, is
investigated theoretically in the case of closed systems of massive bosons and
fermions, described by general single-particle hamiltonians. This phenomenon is
similar for both types of particles and, for some energy spectra, exhibits
features specific to multiple-step Bose-Einstein condensation, for instance the
appearance of maxima in the specific heat.
  In the case of fermions, as the particle density increases, another
phenomenon is also observed. For certain types of single particle hamiltonians,
the specific heat is approaching asymptotically a divergent behavior at zero
temperature, as the Fermi energy $\epsilon_{\rm F}$ is converging towards any
value from an infinite discrete set of energies: ${\epsilon_i}_{i\ge 1}$. If
$\epsilon_{\rm F}=\epsilon_i$, for any i, the specific heat is divergent at T=0
just in infinite systems, whereas for any finite system the specific heat
approaches zero at low enough temperatures. The results are particularized for
particles trapped inside parallelepipedic boxes and harmonic potentials.
  PACS numbers: 05.30.Ch, 64.90.+b, 05.30.Fk, 05.30.Jp


  We introduce Probabilistic Object Detection, the task of detecting objects in
images and accurately quantifying the spatial and semantic uncertainties of the
detections. Given the lack of methods capable of assessing such probabilistic
object detections, we present the new Probability-based Detection Quality
measure (PDQ).Unlike AP-based measures, PDQ has no arbitrary thresholds and
rewards spatial and label quality, and foreground/background separation quality
while explicitly penalising false positive and false negative detections. We
contrast PDQ with existing mAP and moLRP measures by evaluating
state-of-the-art detectors and a Bayesian object detector based on Monte Carlo
Dropout. Our experiments indicate that conventional object detectors tend to be
spatially overconfident and thus perform poorly on the task of probabilistic
object detection. Our paper aims to encourage the development of new object
detection approaches that provide detections with accurately estimated spatial
and label uncertainties and are of critical importance for deployment on robots
and embodied AI systems in the real world.


  In this paper, we investigate the effect of chiral-induced spin selectivity
(CISS) on the radical pair model of avian magnetoreception. We examine the
impact of spin selectivity on the avian compass sensitivity. In this analysis,
we also consider the dipolar and exchange interactions and observe their
interplay with CISS. We find that CISS results in multifold increase in avian
compass sensitivity. Interestingly, we also observe that CISS can counter the
deleterious effect of dipolar interaction and increase system sensitivity.The
analysis has been performed for both the toy model (only 1 nucleus) and a more
general case where we consider 4-nuclei from the cryptochrome radical pair
system. We observe that the CISS allows the radical pair model to have a more
realistic rate with good sensitivity. We also do analysis of functional window
of avian compass reported in behavioral experiments in functional window. We
could not find a parameter set where functional window can be observed along
with CISS.


  Using our photoionization code CIRRUS, we show that the study of proximity
effect on metal elements provides a possibility of placing constraints on the
spectral shape of the metagalactic UV background (MUVB). From theoretical point
of view, the most optimum indicator of the spectral shape of the MUVB is the
ratio OIV/OIII. Unlike previous thought, the ratio SiIV/CIV is not a good
indicator of the spectral shape because of its strong dependence on an
ionization parameter as well. We also find that the observed excess of CIV
systems in luminous QSOs may be a photoionization effect, but not a
gravitational lensing effect.


  We present a new perspective to the classification of topological phases in
free fermion insulators by generalizing the Jackiw-Rebbi model to arbitrary
dimensions. We show that a generalized Jackiw-Rebbi model where the Dirac mass
($m$) satisfies $m(x)=-m(-x)$ is invariant under a parity transformation ($P$)
that relates the $x>0$ half to the $x<0$ half. Determining the form of $P$
gives rise to a Clifford algebra that has been shown to give a complete
topological classification of free fermion insulators. Gapless edge states are
a natural consequence of our construction and their topological nature can be
understood from the fact that all gapless edge states at a given interface
transform similarly under $P$ (all odd or all even). A naive non-topological
model for states confined to the interface will allow both even and odd states.


  These notes contain some of the material I presented at TASI 96 on the
comparison of the standard model with precision electroweak data. After a
physical accounting of the dominant electroweak radiative corrections,
including the effects of initial state bremsstrahlung, I examine how data from
LEP and the SLC provides a clear test of the standard model. Apparent
discrepancies in the $R_b$ and $R_c$ ratios, and their physical resolution, are
also examined in some detail.


  We search for faint X-ray bursts with duration 10--300 seconds in the ROSAT
PSPC pointed observations with a total exposure of 1.6e7 seconds. We do not
detect any events shorter than ~100s, i.e. those that could be related to the
classic gamma-ray bursts. At the same time, we detect a number of long flares
with durations of several hundred seconds. Most, but not all, of the long
flares are associated with stars. If even a small number of those long flares,
that cannot identified with stars, are X-ray afterglows of GRB, the number of
X-ray afterglows greatly exceeds the number of BATSE GRB. This would imply that
the beaming factor of gamma-rays from the burst should be >100. The
non-detection of any short bursts in our data constrains the GRB counts at the
fluences 1--2.5 orders of magnitude below the BATSE limit. The constrained
burst counts are consistent with the extrapolation of the BATSE log N - log S
relation. Finally, our results do not confirm a reality of short X-ray flashes
found in the Einstein IPC data by Gotthelf, Hamilton and Helfand.


  For solving the longstanding materials science problem of correlating elastic
properties of a solid material to the formation of cracks we present a new
general concept. This concept is applied to the technologically most important
cracks of loading mode I for which we establish exact correlations by
introducing a localization length as a new material parameter. We study two
limiting cases of crack formation making use of analytic models determining the
material and direction dependent parameters by comparison to {\em ab initio}
density functional results. This is done for a variety of real materials in
order to test our approach for different types of bonding. For the most
interesting ideal brittle cleavage we find that the localization length is
-within a reasonable approximation- of constant value, which results in a
simple relation for the critical stress, presumably being useful for materials
engineering. Our results confirm that the proposed general concept results in
meaningful physical models which -for the first time- allow a rigorous and
simple correlation between elastic and mechanical properties.


  The slow dynamics in a glassy hard-sphere system is dominated by cage
breaking events, i.e., rearrangements where a particle escapes from the cage
formed by its neighboring particles. We study such events for an overdamped
colloidal system by the means of Brownian dynamics simulations. While it is
difficult to relate cage breaking events to structural mean field results in
bulk, we show that the microscopic dynamics of particles close to a wall can be
related to the anisotropic two-particle density. In particular, we study
cage-breaking trajectories, mean forces on a tracked particle, and the impact
of the history of trajectories. Based on our simulation results, we further
construct two different one-particle random-walk models - one without and one
with memory incorporated - and find the local anisotropy and the
history-dependence of particles as crucial ingredients to describe the escape
from a cage. Finally, our detailed study of a rearrangement event close to a
wall not only reveals the memory effect of cages, but leads to a deeper insight
into the fundamental mechanisms of glassy dynamics.


  In 2000, Hwang and Li proposed a remote user authentication scheme using
smart cards to solve the problems of Lamport scheme. Later, Chan- Chang, Shen-
Lin- Hwang and then Chang-Hwang pointed out some attacks on Hwang –
Li’s scheme. In 2003, Shen, Lin and Hwang also proposed a modified scheme
to remove these attacks. In the same year, Leung-Cheng-Fong-Chan showed that
modified scheme proposed by Shen-Lin-Hwang is still insecure. In 2004, Awasthi
and Lal enhanced Shen-Lin-Hwang’s scheme to overcome its security
pitfalls. This paper analyses that the user U/smart card does not provide
complete information for the execution and proper running of the login phase of
the Awasthi- Lal’s scheme. Furthermore, this paper also modifies the
Awasthi- Lal’s scheme for the proper functioning.


  The general framework for the renormalization group analysis of
self-organized critical sandpile models is formulated. The usual real space
renormalization scheme for lattice models when applied to nonequilibrium
dynamical models must be supplemented by feedback relations coming from the
stationarity conditions. On the basis of these ideas the Dynamically Driven
Renormalization Group is applied to describe the boundary and bulk critical
behavior of sandpile models. A detailed description of the branching nature of
sandpile avalanches is given in terms of the generating functions of the
underlying branching process.


  A selection of recent data referring to Pb+Pb collisions at the SPS CERN
energy of 158 GeV per nucleon is presented which might describe the state of
highly excited strongly interacting matter both above and below the
deconfinement to hadronization (phase) transition predicted by lattice QCD. A
tentative picture emerges in which a partonic state is indeed formed in central
Pb+Pb collisions which hadronizes at about T = 185 MeV, and expands its volume
more than tenfold, cooling to about 120 MeV before hadronic collisions cease.
We suggest further that all SPS collisions, from central S+S onward, reach that
partonic phase, the maximum energy density increasing with more massive
collision systems.


  Programming courses can be challenging for first year university students,
especially for those without prior coding experience. Students initially
struggle with code syntax, but as more advanced topics are introduced across a
semester, the difficulty in learning to program shifts to learning
computational thinking (e.g., debugging strategies). This study examined the
relationships between students' rate of programming errors and their grades on
two exams. Using an online integrated development environment, data were
collected from 280 students in a Java programming course. The course had two
parts. The first focused on introductory procedural programming and culminated
with exam 1, while the second part covered more complex topics and
object-oriented programming and ended with exam 2. To measure students'
programming abilities, 51095 code snapshots were collected from students while
they completed assignments that were autograded based on unit tests. Compiler
and runtime errors were extracted from the snapshots, and three measures --
Error Count, Error Quotient and Repeated Error Density -- were explored to
identify the best measure explaining variability in exam grades. Models
utilizing Error Quotient outperformed the models using the other two measures,
in terms of the explained variability in grades and Bayesian Information
Criterion. Compiler errors were significant predictors of exam 1 grades but not
exam 2 grades; only runtime errors significantly predicted exam 2 grades. The
findings indicate that leveraging Error Quotient with multiple error types
(compiler and runtime) may be a better measure of students' introductory
programming abilities, though still not explaining most of the observed
variability.


  High energy nuclear collisions manifest a variety of interesting phenomena
over a broad range of energy scales. Many of these phenomena are related to the
formation of a hot and dense state of deconfined quarks and gluons known as the
quark gluon plasma (QGP). Chief among these are the observed near inviscid
hydrodynamic expansion of the QGP, as measured through azimuthal anisotropy
coefficients of low-$p_\mathrm{T}$ final state hadrons $v_\mathrm{n}$, and the
loss of energy of high-$p_\mathrm{T}$ color charges as they traverse the QGP
which is observed as a quenching of strongly-interacting final state objects
like jets. Observations of these phenomena in Au+Au and Pb+Pb collisions at
RHIC and the LHC provide compelling evidence of QGP formation. Small collision
systems, like $p$+Pb, also show evidence for the creation droplets of QGP
through the observation of anisotropic flow; however, these systems show no
signs of the energy loss observed in large collision systems. Thus, small
systems are an ideal venue to explore the relationship between high- and
low-$p_\mathrm{T}$ QGP phenomena. Furthermore, the low ambient energy of $p$+Pb
compared to A+A collisions allow for the precise determination of perturbative
process rates which can be used to understand the nuclear modification of
nucleon parton densities.
  This dissertation explores $p$+Pb data collected with the ATLAS detector at
the LHC. The cross section and nuclear modification factor for prompt, isolated
photons are measured and compared to predictions from perturbative QCD
calculations and a model of initial state energy loss. Additionally, the
charged hadron azimuthal anisotropy coefficients, are measured via two-particle
correlations as a function of particle $p_\mathrm{T}$ and event centrality.
Results are shown from minimum bias events and events selected because of the
presence of a high-$p_\mathrm{T}$ jet.


  Graph neural networks (GNNs) have shown high potential for a variety of
real-world, challenging applications, but one of the major obstacles in GNN
research is the lack of large-scale flexible datasets. Most existing public
datasets for GNNs are relatively small, which limits the ability of GNNs to
generalize to unseen data. The few existing large-scale graph datasets provide
very limited labeled data. This makes it difficult to determine if the GNN
model's low accuracy for unseen data is inherently due to insufficient training
data or if the model failed to generalize. Additionally, datasets used to train
GNNs need to offer flexibility to enable a thorough study of the impact of
various factors while training GNN models.
  In this work, we introduce the Illinois Graph Benchmark (IGB), a research
dataset tool that the developers can use to train, scrutinize and
systematically evaluate GNN models with high fidelity. IGB includes both
homogeneous and heterogeneous academic graphs of enormous sizes, with more than
40% of their nodes labeled. Compared to the largest graph datasets publicly
available, the IGB provides over 162X more labeled data for deep learning
practitioners and developers to create and evaluate models with higher
accuracy. The IGB dataset is a collection of academic graphs designed to be
flexible, enabling the study of various GNN architectures, embedding generation
techniques, and analyzing system performance issues for node classification
tasks. IGB is open-sourced, supports DGL and PyG frameworks, and comes with
releases of the raw text that we believe foster emerging language models and
GNN research projects. An early public version of IGB is available at
https://github.com/IllinoisGraphBenchmark/IGB-Datasets.


  This is the first paper in a series. We develop a general deformation theory
of objects in homotopy and derived categories of DG categories. Namely, for a
DG module $E$ over a DG category we define four deformation functors $\Def
^{\h}(E)$, $\coDef ^{\h}(E)$, $\Def (E)$, $\coDef (E)$. The first two functors
describe the deformations (and co-deformations) of $E$ in the homotopy
category, and the last two - in the derived category. We study their properties
and relations. These functors are defined on the category of artinian (not
necessarily commutative) DG algebras.


  With this paper, we survey the research performed in the domain of browser
fingerprinting, while providing an accessible entry point to newcomers in the
field. We explain how this technique works and where it stems from. We analyze
the related work in detail to understand the composition of modern fingerprints
and see how this technique is currently used online. We systematize existing
defense solutions into different categories and detail the current challenges
yet to overcome.


  The spatial distribution of elemental abundances and their time evolution are
among the major constraints to disentangle the scenarios of formation and
evolution of the Galaxy. We used the sample of open clusters available in the
final release of the Gaia-ESO survey to trace the Galactic radial abundance and
abundance to iron ratio gradients, and their time evolution. We selected member
stars in 62 open clusters, with ages from 0.1 to about 7~Gyr, located in the
Galactic thin disc at Galactocentric radii from about 6 to 21~kpc. We analysed
the shape of the resulting [Fe/H] gradient, the average gradients [El/H] and
[El/Fe] combining elements belonging to four different nucleosynthesis
channels, and their individual abundance and abundance ratio gradients. We also
investigated the time evolution of the gradients dividing open clusters in
three age bins. The[Fe/H] gradient has a slope of -0.054 dex~kpc-1. We saw
different behaviours for elements belonging to different channels. We found
that the youngest clusters in the inner disc have lower metallicity than their
older counterpart and they outline a flatter gradient. We considered some
possible explanations, including the effects of gas inflow and migration. We
suggested that it might be a bias introduced by the standard spectroscopic
analysis producing lower metallicities in low gravity stars. To delineate the
shape of the `true' gradient, we should limit our analysis to stars with low
surface gravity logg>2.5 and xi<1.8 km~s-1. Based on this reduced sample, we
can conclude that the gradient has minimally evolved over the time-frame
outlined by the open clusters, indicating a slow and stationary formation of
the thin disc in the latest Gyr. We found a secondary role of clusters'
migration in shaping the gradient, with a more prominent role of migration for
the oldest clusters.


  The worldvolume theory of membrane is mathematically equivalent to
three-dimensional quantum gravity coupled to matter fields corresponding to the
target space coordinates of embedded membrane. In a recent paper
[arXiv:1503.08812] a new class of models are introduced that generate
three-dimensional random volumes, where the Boltzmann weight of each
configuration is given by the product of values assigned to the triangles and
the hinges. These triangle-hinge models describe three-dimensional pure gravity
and are characterized by semisimple associative algebras. In this paper, we
introduce matter degrees of freedom to the models by coloring simplices in a
way that they have local interactions. This is achieved simply by extending the
associative algebras of the original triangle-hinge models, and the profile of
matter field is specified by the set of colors and the form of interactions.
The dynamics of a membrane in $D$-dimensional spacetime can then be described
by taking the set of colors to be $\mathbb{R}^D$. By taking another set of
colors, we can also realize three-dimensional quantum gravity coupled to the
Ising model, the $q$-state Potts models or the RSOS models. One can actually
assign colors to simplices of any dimensions (tetrahedra, triangles, edges and
vertices), and three-dimensional colored tensor models can be realized as
triangle-hinge models by coloring tetrahedra, triangles and edges at a time.


  The Lyman-alpha forest is the large-scale structure probe for which we appear
to have modeling control to the highest wavenumbers. This makes the Lyman-alpha
forest of great interest for constraining the warmness/fuzziness of dark matter
and the timing of reionization processes. However, the standard statistic, the
Lyman-alpha forest power spectrum, is unable to strongly constrain the IGM
temperature-density relation, and this inability further limits how well other
high wavenumber-sensitive parameters can be constrained. With the aim of
breaking these degeneracies, we measure the power spectrum of the Lyman-beta
forest and its cross correlation with the coeval Lyman-alpha forest using the
one hundred spectra of z=3.5-4.5 quasars in the VLT/X-Shooter XQ-100 Legacy
Survey, motivated by the Lyman-beta transition's smaller absorption cross
section that makes it sensitive to somewhat higher densities relative to the
Lyman-alpha transition. Our inferences from this measurement for the IGM
temperature-density relation appear to latch consistently onto the recent tight
lower-redshift Lyman-alpha forest constraints. The z=3.4-4.7 trends we find
using the Lyman-alpha$-$Lyman-beta cross correlation show a flattening of the
slope of the temperature-density relation with decreasing redshift. This is the
trend anticipated from ongoing HeII reionization and there being sufficient
time to reach the asymptotic temperature-density slope after hydrogen
reionization completes. Furthermore, our measurements provide a consistency
check on IGM models that explain the Lyman-alpha forest, with the cross
correlation being immune to systematics that are uncorrelated between the two
forests, such as metal line contamination.


  The electric and magnetic fields are investigated on the basis of quantum
vacuum. The analysis of the electromagnetic energy and force indicates that an
electric field is a polarized distribution of the vacuum virtual dipoles, and
that a magnetic field in vacuum is a rearrangement of the vacuum polarization.
It means that an electromagnetic wave is a successional changing of the vacuum
polarization in space. Also, it is found that the average half length of the
virtual dipoles around an elementary charge is a=2.8 *10^(-15)m. The result
leads to the step distribution of the field energy around an electron, the
relation between the fine structure constant and the vacuum polarization
distribution, and an extremely high energy density of the electromagnetic
field.


  This work establishes fast rates of convergence for empirical barycenters
over a large class of geodesic spaces with curvature bounds in the sense of
Alexandrov. More specifically, we show that parametric rates of convergence are
achievable under natural conditions that characterize the bi-extendibility of
geodesics emanating from a barycenter. These results largely advance the
state-of-the-art on the subject both in terms of rates of convergence and the
variety of spaces covered. In particular, our results apply to
infinite-dimensional spaces such as the 2-Wasserstein space, where
bi-extendibility of geodesics translates into regularity of Kantorovich
potentials.


  A highly intriguing aspect in iron-pnictide superconductors is the
composition-dependent electronic structure, in particular the question if and
how charge carriers are introduced to the system upon substitution of Ba by
alkali metals or of Fe by other transition metals, TM. We report on a
systematic study of spatial structure and electronic states by x-ray
diffraction and x-ray absorption on a large number of compositions in the
(Ba,K)(Fe,TM)2As2 family. The coherent combination of detailed structural
information with an in-depth analysis of the electronic structure allows us to
sensitively disentangle (charge-carrier) "doping" effects from "substitutional"
effects. Results include a doping character that is site-decoupled, as well as
TM 3d energy-level schemes that exhibit non-standard level sequences and even
t2-e level crossings. Our study indicates that doping per se seems to play a
lesser role than expected for pnictide superconductivity and magnetism.


  An extensive study of single block copolymer knots containing two kinds of
monomers $A$ and $B$ is presented. The knots are in a solution and their
monomers are subjected to short range interactions that can be attractive or
repulsive. In view of possible applications in medicine and the construction of
intelligent materials, it is shown that several features of copolymer knots can
be tuned by changing the monomer configuration. A very fast and abrupt swelling
with increasing temperature is obtained in certain multiblock copolymers, while
the size and the swelling behavior at high temperatures may be controlled in
diblock copolymers. Interesting new effects appear in the thermal diagrams of
copolymer knots when their length is increased.


  Recently, In [Phys. Rev. Lett. 104, 018701 (2010)] the authors studied a
spatial network which is constructed from a regular lattice by adding
long-range edges (shortcuts) with probability $P_{ij}\sim r_{ij}^{-\alpha}$,
where $r_{ij}$ is the Manhattan length of the long-range edges. The total
length of the additional edges is subject to a cost constraint ($\sum r=C$).
These networks have fixed optimal exponent $\alpha$ for transportation
(measured by the average shortest-path length). However, we observe that the
degree in such spatial networks is homogenously distributed, which is far
different from real networks such as airline systems. In this paper, we propose
a method to introduce degree heterogeneity in spatial networks with total cost
constraint. Results show that with degree heterogeneity the optimal exponent
shifts to a smaller value and the average shortest-path length can further
decrease. Moreover, we consider the synchronization on the spatial networks and
related results are discussed. Our new model may better reproduce the features
of many real transportation systems.


  We propose a possibility to simulate the exciton-polariton (EP) system in the
lossless limit, which is not currently available in semiconductor
microcavities, by means of a simple optical dual-core waveguide, with one core
carrying the nonlinearity and operating close to the
zero-group-velocity-dispersion (GVD) point, and the other core being linear and
dispersive. Both 2D and 1D EP systems may be emulated by means of this optical
setting. In the framework of this system, we find that, while the uniform state
corresponding to the lower branch of the nonlinear dispersion relation is
stable against small perturbations, the upper branch is always subject to the
modulational instability (MI). The stability and instability are verified by
direct simulations too. We analyze collective excitations on top of the stable
lower-branch state, which include a Bogoliubov-like gapless mode and a gapped
one. Analytical results are obtained for the corresponding sound velocity and
energy gap. The effect of a uniform phase gradient (superflow) on the stability
is considered too, with a conclusion that the lower-branch state becomes
unstable above a critical wavenumber of the flux. Finally, we demonstrate that
the stable 1D state may carry robust dark solitons.


  We establish several non-existence results of positive scalar curvature (PSC)
on fiber bundles. We show under an incompressible condition of the fiber, for
$X^m$ a Cartan-Hadamard manifold or an aspherical manifold when $m=3$, the
fiber bundle over $X^m\#M^m$ ($m\ge 3$) with $K(\pi,1)$ fiber, $NPSC^+$(a
manifold class including enlargeable and Schoen-Yau-Schick ones) fiber, or spin
fiber of non-vanishing Rosenberg index carries no PSC metric, with necessary
dimension and spin compactible condition imposed. Furthermore, we show under a
homotopically nontrivial condition of the fiber, the $S^1$ principle bundle
over a closed 3-manifold admits PSC metric if and only if its base space does.
These partially answer a question of Gromov and extend some previous results of
Hanke, Schick and Zeidler concerning PSC obstruction on fiber bundles.


  We present new measures of the evolving scaling relations between stellar
mass, luminosity and rotational velocity for a morphologically-inclusive sample
of 129 disk-like galaxies with z_AB<22.5 in the redshift range 0.2<z<1.3, based
on spectra from DEIMOS on the Keck II telescope, multi-color HST ACS
photometry, and ground-based Ks-band imaging. A unique feature of our survey is
the extended spectroscopic integration times, leading to significant
improvements in determining characteristic rotational velocities for each
galaxy. Rotation curves are reliably traced to the radius where they begin to
flatten for ~90% of our sample, and we model the HST-resolved bulge and disk
components in order to accurately de-project our measured velocities,
accounting for seeing and dispersion. We demonstrate the merit of these
advances by recovering an intrinsic scatter on the stellar mass Tully-Fisher
relation a factor of 2-3 less than in previous studies at intermediate redshift
and comparable to that of locally-determined relations. With our increased
precision, we find the relation is well-established by <z>~1, with no
significant evolution to <z>~0.3, \DeltaM_stellar ~ 0.04+/-0.07 dex. A clearer
trend of evolution is seen in the B-band Tully-Fisher relation corresponding to
a decline in luminosity of \DeltaM_B ~ 0.85+/-0.28 magnitudes at fixed velocity
over the same redshift range, reflecting the changes in star formation over
this period. As an illustration of the opportunities possible when gas masses
are available for a sample such as ours, we show how our dynamical and stellar
mass data can be used to evaluate the likely contributions of baryons and dark
matter to the assembly history of spiral galaxies.


  Dementia is a progressive neurological disorder that profoundly affects the
daily lives of older adults, impairing abilities such as verbal communication
and cognitive function. Early diagnosis is essential for enhancing both
lifespan and quality of life for affected individuals. Despite its importance,
diagnosing dementia is complex and often necessitates a multimodal approach
incorporating diverse clinical data types. In this study, we fine-tune Wav2vec
and Word2vec baseline models using two distinct data types: audio recordings
and text transcripts. We experiment with four conditions: original datasets
versus datasets purged of short sentences, each with and without data
augmentation. Our results indicate that synonym-based text data augmentation
generally enhances model performance, underscoring the importance of data
volume for achieving generalizable performance. Additionally, models trained on
text data frequently excel and can further improve the performance of other
modalities when combined. Audio and timestamp data sometimes offer marginal
improvements. We provide a qualitative error analysis of the sentence
archetypes that tend to be misclassified under each condition, providing
insights into the effects of altering data modality and augmentation decisions.


  Killing vector fields in three dimensions play important role in the
construction of the related spacetime geometry. In this work we show that when
a three dimensional geometry admits a Killing vector field then the Ricci
tensor of the geometry is determined in terms of the Killing vector field and
its scalars. In this way we can generate all products and covariant derivatives
at any order of the ricci tensor. Using this property we give ways of solving
the field equations of Topologically Massive Gravity (TMG) and New Massive
Gravity (NMG) introduced recently. In particular when the scalars of the
Killing vector field (timelike, spacelike and null cases) are constants then
all three dimensional symmetric tensors of the geometry, the ricci and einstein
tensors, their covariant derivatives at all orders, their products of all
orders are completely determined by the Killing vector field and the metric.
Hence the corresponding three dimensional metrics are strong candidates of
solving all higher derivative gravitational field equations in three
dimensions.


  The most widely accepted model of the solar cycle is the flux transport
dynamo model. This model evolved out of the traditional $\alpha \Omega$ dynamo
model which was first developed at a time when the existence of the Sun's
meridional circulation was not known. In these models, the toroidal magnetic
field (which gives rise to sunspots) is generated by the stretching of the
poloidal field by solar differential rotation. The primary source of the
poloidal field in the flux transport models is attributed to the
Babcock--Leighton mechanism, in contrast to the mean-field $\alpha$-effect used
in earlier models. With the realization that the Sun has a meridional
circulation, which is poleward at the surface and is expected to be equatorward
at the bottom of the convection zone, its importance for transporting the
magnetic fields in the dynamo process was recognized. Much of our understanding
about the physics of both the meridional circulation and the flux transport
dynamo has come from the mean field theory obtained by averaging the equations
of MHD over turbulent fluctuations. The mean field theory of meridional
circulation makes clear how it arises out of an interplay between the
centrifugal and thermal wind terms. We provide a broad review of mean field
theories for solar magnetic fields and flows, the flux transport dynamo
modeling paradigm and highlight some of their applications to solar and stellar
magnetic cycles. We also discuss how the dynamo-generated magnetic field acts
on the meridional circulation of the Sun and how the fluctuations in the
meridional circulation, in turn, affect the solar dynamo. We conclude with some
remarks on how the synergy of mean field theories, flux transport dynamo
models, and direct numerical simulations can inspire the future of this field.


  Primordial black holes (PBHs) have long been suggested as a candidate for
making up some or all of the dark matter in the Universe. Most of the
theoretically possible mass range for PBH dark matter has been ruled out with
various null observations of expected signatures of their interaction with
standard astrophysical objects. However, current constraints are significantly
less robust in the 20 M_sun < M_PBH < 100 M_sun mass window, which has received
much attention recently, following the detection of merging black holes with
estimated masses of ~30 M_sun by LIGO and the suggestion that these could be
black holes formed in the early Universe. We consider the potential of advanced
LIGO (aLIGO) operating at design sensitivity to probe this mass range by
looking for peaks in the mass spectrum of detected events. To quantify the
background, which is due to black holes that are formed from dying stars, we
model the shape of the stellar-black-hole mass function and calibrate its
amplitude to match the O1 results. Adopting very conservative assumptions about
the PBH and stellar-black-hole merger rates, we show that ~5 years of aLIGO
data can be used to detect a contribution of >20 M_sun PBHs to dark matter down
to f_PBH<0.5 at >99.9% confidence level. Combined with other probes that
already suggest tension with f_PBH=1, the obtainable independent limits from
aLIGO will thus enable a firm test of the scenario that PBHs make up all of
dark matter.


  In this paper, we concentrate on power dilation systems
$\{f(z^k)\}_{k\in\mathbb{N}}$ in Dirichlet-type spaces $\mathcal{D}_t\
(t\in\mathbb{R})$. When $t\neq0$, we prove that $\{f(z^k)\}_{k\in\mathbb{N}}$
is orthogonal in $\mathcal{D}_t$ only if $f=cz^N$ for some constant $c$ and
some positive integer $N$. We also give complete characterizations of
unconditional bases and frames formed by power dilation systems for
Drichlet-type spaces.


  We study the Galois action attached to the Dwrok surfaces
$X_{\lambda}:X_0^4+X_1^4+X_2^4+X_3^4-4\lambda X_0X_1X_2X_3=0$ with parameter
$\lambda$ in a number field $F$. We show that when $X_{\lambda}$ has geometric
Picard number $19$, its N\'eron-Severi group $NS(\overline{X}_{\lambda})\otimes
\mathbb{Q}$ is a direct sum of quadratic characters. We provide two proofs to
this conclusion in our article. In particular, the geometrically proof
determines the conductor of each of quadratic characters. Our result matches
the one in \cite{Voight2}. With this decomposition, we give another proof to a
result of Wan.


  The breeder's equation is a cornerstone of quantitative genetics and is
widely used in evolutionary modeling. The equation which reads R=h^{2}S relates
response to selection R (the mean phenotype of the progeny) to the selection
differential S (mean phenotype of selected parents) through a simple
proportionality relation. The validity of this relation however relies strongly
on the normal (Gaussian) distribution of parent's genotype which is an
unobservable quantity and cannot be ascertained. In contrast, we show here that
if the fitness (or selection) function is Gaussian, an alternative, exact
linear equation in the form of R'=j^{2}S' can be derived, regardless of the
parental genotype distribution. Here R' and S' stand for the mean phenotypic
lag behind the mean of the fitness function in the offspring and selected
populations. To demonstrate this relation, we derive the exact functional
relation between the mean phenotype in the selected and the offspring
population and deduce all cases that lead to a linear relation between these
quantities. These computations, which are confirmed by individual based
numerical simulations, generalize naturally to the multivariate Lande's
equation \Delta\mathbf{\bar{z}}=GP^{-1}\mathbf{S} .


  We have investigated the stellar and interstellar content of the distant star
formation region IRAS 17591-2228 (WISE HII region GAL 007.47+0.06). It is
associated to a water maser, whose parallax distance is d=20.4^{+2.8} {-2.2}
kpc, supported by independent measurements of proper motion and radial
velocity. It is projected in the same direction as an extremely red (J-Ks ~ 6
mag) group of stars, and a shell of mid-infrared emission. We qualify the group
of stars as a cluster candidate, VVV CL177. Its radius spans between 0.45' and
1' and contains at least two young stellar objects with an extreme extinction
near Av ~ 40 mag. Yet more analysis will be required to determine is it is a
real single cluster associated with the water maser. The 13CO emissions at the
radial velocity of the maser corresponds to the mid-infrared emission.


  Although variational autoencoders (VAEs) represent a widely influential deep
generative model, many aspects of the underlying energy function remain poorly
understood. In particular, it is commonly believed that Gaussian
encoder/decoder assumptions reduce the effectiveness of VAEs in generating
realistic samples. In this regard, we rigorously analyze the VAE objective,
differentiating situations where this belief is and is not actually true. We
then leverage the corresponding insights to develop a simple VAE enhancement
that requires no additional hyperparameters or sensitive tuning.
Quantitatively, this proposal produces crisp samples and stable FID scores that
are actually competitive with a variety of GAN models, all while retaining
desirable attributes of the original VAE architecture. A shorter version of
this work will appear in the ICLR 2019 conference proceedings (Dai and Wipf,
2019). The code for our model is available at https://github.com/daib13/
TwoStageVAE.


  In this letter, we analyze a conceptual design for the operation of an Otto
cycle heat machine driven by adiabatic modifications on the electronic
effective mass. Such tailoring of it can be implemented, for instance, via the
application of external electron fields in some materials, as in Gallium
Nitride (GaN). We show that due both the energy quantization on this structure
and the adiabatic transformation of the effective mass, the machine performance
can be improved. The realization of classically inconceivable Otto machines,
with an incompressible working substance, can be realized as well. Our finds
hold in cases where the electronic effective mass, in the low temperature
regime, remains constant during the isochoric strokes.


  We present an overview of solar flares and associated phenomena, drawing upon
a wide range of observational data primarily from the RHESSI era. Following an
introductory discussion and overview of the status of observational
capabilities, the article is split into topical sections which deal with
different areas of flare phenomena (footpoints and ribbons, coronal sources,
relationship to coronal mass ejections) and their interconnections. We also
discuss flare soft X-ray spectroscopy and the energetics of the process. The
emphasis is to describe the observations from multiple points of view, while
bearing in mind the models that link them to each other and to theory. The
present theoretical and observational understanding of solar flares is far from
complete, so we conclude with a brief discussion of models, and a list of
missing but important observations.


  We introduce and examine some special classes of invariant
types$\unicode{x2014}$bi-invariant, strongly bi-invariant, extendibly
invariant, and reliably invariant types$\unicode{x2014}$and show that they are
related to certain model-theoretic tree properties.
  We show that the comb tree property (recently introduced by Mutchnik) is
equivalent to the failure of Kim's lemma for bi-invariant types and is implied
by the failure of Kim's lemma for reliably invariant types over invariance
bases. We show that every type over an invariance base extends to a reliably
invariant type$\unicode{x2014}$generalizing an unpublished result of Kruckman
and Ramsey$\unicode{x2014}$and use this to show that, under a reasonable
definition of Kim-dividing, Kim-forking coincides with Kim-dividing over
invariance bases in theories without the comb tree property. Assuming a
measurable cardinal, we characterize the comb tree property in terms of a form
of dual local character.
  We also show that the antichain tree property (introduced by Ahn and Kim)
seems to have a somewhat similar relationship to strong bi-invariance. In
particular, we show that NATP theories satisfy Kim's lemma for strongly
bi-invariant types and (assuming a measurable cardinal) satisfy a different
form of dual local character. Furthermore, we examine a mutual generalization
of the local character properties satisfied by NTP$_2$ and NSOP$_1$ theories
and show that it is satisfied by all NATP theories.
  Finally, we give some related minor results$\unicode{x2014}$a strengthened
local character characterization of NSOP$_1$ and a characterization of coheirs
in terms of invariant extensions in expansions$\unicode{x2014}$as well as a
pathological example of Kim-dividing.


  Metaverse aims for building a fully immersive virtual shared space, where the
users are able to engage in various activities. To successfully deploy the
service for each user, the Metaverse service provider and network service
provider generally localise the user first and then support the communication
between the base station (BS) and the user. A reconfigurable intelligent
surface (RIS) is capable of creating a reflected link between the BS and the
user to enhance line-of-sight. Furthermore, the new key performance indicators
(KPIs) in Metaverse, such as its energy-consumption-dependent total service
cost and transmission latency, are often overlooked in ultra-reliable low
latency communication (URLLC) designs, which have to be carefully considered in
next-generation URLLC (xURLLC) regimes. In this paper, our design objective is
to jointly optimise the transmit power, the RIS phase shifts, and the decoding
error probability to simultaneously minimise the total service cost and
transmission latency and approach the Pareto Front (PF). We conceive a
twin-stage central controller, which aims for localising the users first and
then supports the communication between the BS and users. In the first stage,
we localise the Metaverse users, where the stochastic gradient descent (SGD)
algorithm is invoked for accurate user localisation. In the second stage, a
meta-learning-based position-dependent multi-objective soft actor and critic
(MO-SAC) algorithm is proposed to approach the PF between the total service
cost and transmission latency and to further optimise the latency-dependent
reliability. Our numerical results demonstrate that ...


  In some theoretical analyses of microwave-induced magnetoresistance
oscillations in high-mobility two-dimensional systems, the "inelastic
relaxation time" $\tau_{in}$ due to electron-electron scattering is evaluated
using an equilibrium distribution function $f^0$ in the absence of radiation,
and it is concluded that $\tau_{in}$ is much larger than $\tau_{q}$, the
single-particle relaxation time due to impurity scattering. However, under the
irradiation of a microwave capable of producing magnetoresistance oscillation,
the distribution function of the high-mobility electron gas deviates remarkably
from $f^0$ at low temperatures. Estimating $\tau_{in}$ using an approximate
nonequilibrium distribution function rather than using $f^0$, one will find the
system to be in the opposite limit $1/\tau_{in}\ll 1/\tau_{q}$ even for T=0 K.
Therefore, models which depend on the assumption $1/\tau_{in}\gg 1/\tau_{q}$
may not be justifiable.


  We prove that braid invariants coming from quantum gl(N) separate braids, by
recalling that these invariants (properly decomposed) are all Vassiliev
invariants, showing that all Vassiliev invariants of braids arise in this way,
and reproving that Vassiliev invariants separate braids. We discuss some
corollaries of this result and of our method of proof.


  The quantization rules recently proposed by M. Navarro (and independently
I.V. Kanatchikov) for a finite-dimensional formulation of quantum field theory
are applied to the Klein-Gordon and the Dirac fields to obtain the quantum
equations of motion of both fields. In doing so several problems arise.
  Solving these difficulties leads us to propose a new classical canonical
formalism, which, in turn, leads us to new, improved rules of quantization. We
show that the new classical equations of motion and rules of quantization
overcome several known unsatisfactory features of the previous formalism. We
argue that the new formalism is a general improvement with respect to the
previous one.
  Further we show that the quantum field theory of the Dirac and Klein-Gordon
field describes particles with extra, harmonic-oscillator-like degrees of
freedom. We argue that these degrees of freedom should give rise to a
multi-particle interpretation of the formalism.