  We obtain the instability of Type (II) Lawson-Osserman cones in Euclidean
spaces, and thus provide a family of (uncountably many) unstable solutions with
singularity to the Dirichlet problem for minimal graphs of high codimension
versus smooth unstable ones by Lawson-Osserman through a min-max technique. To
our knowledge, these are the first examples of non-smooth unstable minimal
graphs and unlikely detectible through the mean curvature flow or min-max
theory.


  Highly collimated betatron radiation from a laser wakefield accelerator is a
promising tool for spectroscopic measurements. Therefore there is a requirement
to create spectrometers suited to the unique properties of such a source. We
demonstrate a spectrometer which achieves an energy resolution of < 5 eV at 9
keV and is angularly resolving the x-ray emission allowing the reference and
spectrum to be recorded at the same time. The single photon analysis is used to
significantly reduce the background noise. Theoretical performance of various
configurations of the spectrometer is calculated by a ray-tracing algorithm.
The properties and performance of the spectrometer including the angular and
spectral resolution are demonstrated experimentally on absorption above the
K-edge of a Cu foil backlit by laser-produced betatron radiation x-ray beam.


  The 2-rank of a compact Lie group $G$ is the maximal possible rank of the
elementary 2-subgroup ${\mathbb Z}_{2}\times... {\mathbb Z}_{2}$ of $G$. The
study of 2-ranks (and $p$-rank for any prime $p$) of compact Lie groups was
initiated in 1953 by A. Borel and J.-P. Serre. Since then the 2-ranks of
compact Lie groups have been investigated by many mathematician. The 2-ranks of
compact Lie groups relate closely with several important areas in mathematics.
  In this article, we survey important results concerning 2-ranks of compact
Lie groups. In particular, we present the complete determination of 2-ranks of
compact connected simple Lie groups $G$ via the 2-numbers introduced by B. Y.
Chen and T. Nagano in [Un invariant g\'em\'etrique riemannien, C. R. Acad. Sci.
Paris, 295 (1982), 389--391] and [A Riemannian geometric invariant and its
applications to a problem of Borel and Serre, Trans. Amer. Math. Soc. 308
(1988), 273--297].


  In the present work we use the Levelt's valuation theory to describe all
monodromy representations that can be realized by Riemann equation. Also we
show that if the monodromy of Riemann equation lies in $SL(2,\mathbb{C})$, then
such a monodromy can be realized by a more special Riemann-Sturm-Liouville
equation as well. After all the criterion for hypergeometric equation to have
monodromy in $SL(2,\mathbb{Z})$ is presented.


  We start with a simple introduction into the renormalization group (RG) in
quantum field theory and give an overview of the renormalization group method.
The third section is devoted to essential topics of the renorm-group use in the
QFT. Here, some fresh results are included.
  Then we turn to the remarkable proliferation of the RG ideas into various
fields of physics. The last section summarizes an impressive recent progress of
the "QFT renormalization group" application in mathematical physics.


  Updated LHC data on the new 126 GeV boson during the 7 and 8 TeV runnings
strengthen the standard model Higgs boson interpretation further. Through the
global $\chi^2$ analysis, we investigate whether the new particle could be one
of the scalar particles in two Higgs doublet models. Four types (Type I, II, X
and Y) are comprehensively studied. Taking the recent analysis on the
spin-parity of the new boson, we consider two scenarios: the new boson is
either the light CP-even one ($h^0$) or the heavy CP-even one ($H^0$). It is
found that both scenarios are consistent with the new data, not only in the
parameter regions near the decoupling limit but also in other regions far from
the decoupling limit. In addition, the current data are compatible with the
possibility that the light Higgs boson $h^0$ is hidden in the mass window of
90-100 GeV. The diphoton or $\tau\tau$ channel can provide a probe of this
possibility by the enhanced signal rates.


  Multiagent reinforcement learning algorithms (MARL) have been demonstrated on
complex tasks that require the coordination of a team of multiple agents to
complete. Existing works have focused on sharing information between agents via
centralized critics to stabilize learning or through communication to increase
performance, but do not generally look at how information can be shared between
agents to address the curse of dimensionality in MARL. We posit that a
multiagent problem can be decomposed into a multi-task problem where each agent
explores a subset of the state space instead of exploring the entire state
space. This paper introduces a multiagent actor-critic algorithm and method for
combining knowledge from homogeneous agents through distillation and
value-matching that outperforms policy distillation alone and allows further
learning in both discrete and continuous action spaces.


  Testing is recommended for all close contacts of confirmed COVID-19 patients.
However, existing group testing methods are oblivious to the circumstances of
contagion provided by contact tracing. Here, we build upon a well-known
semi-adaptive pool testing method, Dorfman's method with imperfect tests, and
derive a simple group testing method based on dynamic programming that is
specifically designed to use the information provided by contact tracing.
Experiments using a variety of reproduction numbers and dispersion levels,
including those estimated in the context of the COVID-19 pandemic, show that
the pools found using our method result in a significantly lower number of
tests than those found using standard Dorfman's method, especially when the
number of contacts of an infected individual is small. Moreover, our results
show that our method can be more beneficial when the secondary infections are
highly overdispersed.


  Recently, leveraging BERT pre-training to improve the phoneme encoder in text
to speech (TTS) has drawn increasing attention. However, the works apply
pre-training with character-based units to enhance the TTS phoneme encoder,
which is inconsistent with the TTS fine-tuning that takes phonemes as input.
Pre-training only with phonemes as input can alleviate the input mismatch but
lack the ability to model rich representations and semantic information due to
limited phoneme vocabulary. In this paper, we propose MixedPhoneme BERT, a
novel variant of the BERT model that uses mixed phoneme and sup-phoneme
representations to enhance the learning capability. Specifically, we merge the
adjacent phonemes into sup-phonemes and combine the phoneme sequence and the
merged sup-phoneme sequence as the model input, which can enhance the model
capacity to learn rich contextual representations. Experiment results
demonstrate that our proposed Mixed-Phoneme BERT significantly improves the TTS
performance with 0.30 CMOS gain compared with the FastSpeech 2 baseline. The
Mixed-Phoneme BERT achieves 3x inference speedup and similar voice quality to
the previous TTS pre-trained model PnG BERT


  We examine properties of the inner and outer horizon thermodynamics of
Taub-NUT (Newman-Unti-Tamburino) and Kerr-Taub-NUT (KTN) black hole (BH) in
four dimensional \emph{Lorentzian geometry}. We compare and contrasted these
properties with the properties of Reissner Nordstr{\o}m (RN) BH and Kerr BH. We
focus on "area product", "entropy product", "irreducible mass product" of the
event horizon and Cauchy horizons. Due to mass-dependence, we speculate that
these products have no beautiful quantization feature. Nor does it has any
universal property. We further observe that the \emph{First law} of BH
thermodynamics and \emph {Smarr-Gibbs-Duhem} relations do not hold for Taub-NUT
(TN) and KTN BH in Lorentzian regime. The failure of these aforementioned
features are due to presence of the non-trivial NUT charge which makes the
space-time to be asymptotically non-flat, in contrast with RN BH and Kerr BH.
The another reason of the failure is that Lorentzian TN and Lorentzian KTN
geometry contains \emph{Dirac-Misner type singularity}, which is a
manifestation of a non-trivial topological twist of the manifold. The black
hole \emph{mass formula} and \emph{Christodoulou-Ruffini mass formula} for TN
and KTN BHs are also computed. This thermodynamic product formulae gives us
further understanding to the nature of BH entropy (inner and outer) at the
microscopic level.


  In BRST-quantised Yang-Mills theory the existence of BRST symmetry imposes
significant constraints on the analytic structure of the continuum theory. In
particular, the presence of this symmetry in the non-perturbative regime
implies that any on-shell state with vanishing norm must have an associated
partner state with identical mass, but negative inner product. In this work we
demonstrate that for quantum chromodynamics (QCD) this constraint gives rise to
an interconnection between the ghost and gluon spectra, and in doing so
provides a non-trivial test of whether BRST symmetry is realised
non-perturbatively. By analysing infrared lattice data for the minimal Landau
gauge ghost propagator in pure $\mathrm{SU}(3)$ Yang-Mills theory, and
comparing this with previous results for the gluon propagator, we show that
this interconnection is violated, and hence conclude that continuum and current
lattice formulations of Yang-Mills theory in Landau gauge represent two
distinct realisations of the theory.


  Rochlin proved that a closed 4-dimensional connected smooth oriented manifold
$X^4$ with vanishing second Stiefel-Whitney class has signature $\sigma(X)$
divisible by 16. This was generalized by Kervaire and Milnor to the statement
that if $\xi \in H_2(X;\mathbb{Z})$ is an integral lift of an element in
$H_2(X; \mathbb{Z}/2\mathbb{Z})$ that is dual to $w_2(X)$, and if $\xi$ can be
represented by an embedded sphere in $X$, then the self-intersection number
$\xi^2$ is divisible by 16. This was subsequently generalized further by
Rochlin and various alternative proofs of this result where given by Freedman,
Kirby, and Matsumoto. We give further generalizations of this result concerning
4-manifolds with boundary. Given a smooth compact orientable four manifold
$X^4$ with integral homology sphere boundary and a connected orientable
characteristic surface with connected boundary $F^2$ properly embedded in $X$,
we prove a theorem relating the Arf invariant of $\partial F$, and the Arf
invariant of $F$, and the Rochlin invariant of $\partial X$. We then proceed to
generalize this result to the case where $X$ is a topological compact
orientable 4-manifold (which brings in the Kirby-Siebenmann invariant),
$\partial F$ is not connected (which brings in the condition of being proper as
a link), $F$ is not orientable (which brings in Brown invariants), and finally
where $\partial X$ is an arbitrary 3-manifold (which brings in pin structures).
The final result gives a "combinatorial" description of the Kirby-Siebenmann
invariant of a compact orientable 4-manifold with nonempty boundary.


  Conventional scattering theory is incomplete in that it does not adequately
describe the behaviour of the wave function at macroscopic distances from the
scattering reaction volume. In scattering experiments particles are incident
from sources at macroscopic distance and measured at macroscopic distance from
the microscopic reaction volume. Standard experimental procedure is to describe
asymptotic particle motion by classical mechanics. However, this transition to
classical mechanics is not accounted for in standard quantum scattering theory.
Hence, we revisit conventional scattering theory with the introduction of
semiclassical propagators to describe the wave function in both incident and
outgoing asymptotic scattering channels. This description leads to the
manifestation of classical trajectories in the quantum wave function both
before and after the collision. It includes the case of extraction with
external fields as in modern multi-particle detectors. We derive the asymptotic
Kemble imaging theorem (IT) limit to demonstrate how formal quantum scattering
theory contains implicit classical mechanics threaded throughout the asymptotic
wave functions.


  The following source coding problem was introduced by Birk and Kol: a sender
holds a word $x\in\{0,1\}^n$, and wishes to broadcast a codeword to $n$
receivers, $R_1,...,R_n$. The receiver $R_i$ is interested in $x_i$, and has
prior \emph{side information} comprising some subset of the $n$ bits. This
corresponds to a directed graph $G$ on $n$ vertices, where $i j$ is an edge iff
$R_i$ knows the bit $x_j$. An \emph{index code} for $G$ is an encoding scheme
which enables each $R_i$ to always reconstruct $x_i$, given his side
information. The minimal word length of an index code was studied by
Bar-Yossef, Birk, Jayram and Kol (FOCS 2006). They introduced a graph
parameter, $\minrk_2(G)$, which completely characterizes the length of an
optimal \emph{linear} index code for $G$. The authors of BBJK showed that in
various cases linear codes attain the optimal word length, and conjectured that
linear index coding is in fact \emph{always} optimal.
  In this work, we disprove the main conjecture of BBJK in the following strong
sense: for any $\epsilon > 0$ and sufficiently large $n$, there is an
$n$-vertex graph $G$ so that every linear index code for $G$ requires codewords
of length at least $n^{1-\epsilon}$, and yet a non-linear index code for $G$
has a word length of $n^\epsilon$. This is achieved by an explicit
construction, which extends Alon's variant of the celebrated Ramsey
construction of Frankl and Wilson.
  In addition, we study optimal index codes in various, less restricted,
natural models, and prove several related properties of the graph parameter
$\minrk(G)$.


  We point out that in some situations it is possible to use matrix model
techniques a la Dijkgraaf-Vafa to perturbatively compute D-brane instanton
effects. This provides an explanation in terms of stringy instantons of the
results in hep-th/0311181. We check this proposal in some simple scenarios. We
point out some interesting consequences of this observation, such as the fact
that it gives a perturbative way of computing stringy multi-instanton effects.
It also provides a further interpretation of D-brane instantons as residual
instantons of higgsed supergroups.


  We investigate the observational signatures of many-field inflation and
present analytic expressions for the spectral index as a function of the prior.
For a given prior we employ the central limit theorem and the horizon crossing
approximation to derive universal predictions. These include a specific
dependence on the prior choice for initial conditions that has not been seen in
previous studies. Our main focus is on quadratic inflation, for which the
initial conditions statistics decouple from those of the mass distribution,
while other monomials are also briefly discussed. We verify the validity of our
calculations by comparing to full numerical simulations with 100 fields using
the transport method.


  Diabetic retinopathy (DR) is one of the most common eye conditions among
diabetic patients. However, vision loss occurs primarily in the late stages of
DR, and the symptoms of visual impairment, ranging from mild to severe, can
vary greatly, adding to the burden of diagnosis and treatment in clinical
practice. Deep learning methods based on retinal images have achieved
remarkable success in automatic DR grading, but most of them neglect that the
presence of diabetes usually affects both eyes, and ophthalmologists usually
compare both eyes concurrently for DR diagnosis, leaving correlations between
left and right eyes unexploited. In this study, simulating the diagnostic
process, we propose a two-stream binocular network to capture the subtle
correlations between left and right eyes, in which, paired images of eyes are
fed into two identical subnetworks separately during training. We design a
contrastive grading loss to learn binocular correlation for five-class DR
detection, which maximizes inter-class dissimilarity while minimizing the
intra-class difference. Experimental results on the EyePACS dataset show the
superiority of the proposed binocular model, outperforming monocular methods by
a large margin.


  We prove that for a topological space $X$, an equiconnected space $Z$ and a
Baire-one mapping $g:X\to Z$ there exists a separately continuous mapping
$f:X^2\to Z$ with the diagonal $g$, i.e. $g(x)=f(x,x)$ for every $x\in X$.
Under a mild assumptions on $X$ and $Z$ we obtain that diagonals of separately
continuous mappings $f:X^2\to Z$ are exactly Baire-one functions, and diagonals
of mappings $f:X^2\to Z$ which are continuous on the first variable and
Lipschitz (differentiable) on the second one, are exactly the functions of
stable first Baire class.


  We extend the concept of polynomial time approximation algorithms to apply to
problems for hierarchically specified graphs, many of which are
PSPACE-complete. Assuming P != PSPACE, the existence or nonexistence of such
efficient approximation algorithms is characterized, for several standard graph
theoretic and combinatorial problems. We present polynomial time approximation
algorithms for several standard PSPACE-hard problems considered in the
literature. In contrast, we show that unless P = PSPACE, there is no polynomial
time epsilon-approximation for any epsilon>0, for several other problems, when
the instances are specified hierarchically. We present polynomial time
approximation algorithms for the following problems when the graphs are
specified hierarchically: {minimum vertex cover}, {maximum 3SAT}, {weighted max
cut}, {minimum maximal matching}, {bounded degree maximum independent set}
  In contrast, we show that unless P = PSPACE, there is no polynomial time
epsilon-approximation for any epsilon>0, for the following problems when the
instances are specified hierarchically: {the number of true gates in a monotone
acyclic circuit when all input values are specified} and {the optimal value of
the objective function of a linear program} It is also shown that unless P =
PSPACE, a performance guarantee of less than 2 cannot be obtained in polynomial
time for the following problems when the instances are specified
hierarchically: {high degree subgraph}, {k-vertex connected subgraph}, and
{k-edge connected subgraph}


  We consider a $\varphi$ Josephson junction, which has a bistable zero-voltage
state with the stationary phases $\psi=\pm\varphi$. In the non-zero voltage
state the phase "moves" viscously along a tilted periodic double-well
potential. When the tilting is reduced quasistatically, the phase is retrapped
in one of the potential wells. We study the viscous phase dynamics to determine
in which well ($-\varphi$ or $+\varphi$) the phase is retrapped for a given
damping, when the junction returns from the finite-voltage state back to
zero-voltage state. In the limit of low damping the $\varphi$ Josephson
junction exhibits a butterfly effect --- extreme sensitivity of the destination
well on damping. This leads to an impossibility to predict the destination
well.


  We present 4 new measurements of nitrogen abundances and one upper limit in
damped Lyman alpha absorbers (DLAs) obtained by means of high resolution (FWHM
\~ 7 km/s) UVES/VLT spectra. In addition to these measurements we have compiled
data from all DLAs with measurements of nitrogen and alpha-capture elements (O,
S or Si) available in the literature, including all HIRES/Keck and UVES/VLT
data for a total of 33 systems, i.e. the largest sample investigated so far. We
find that [N/alpha] ratios are distributed in two groups: 75% of the DLAs show
a mean value of [N/alpha] = -0.87 with a scatter of 0.16 dex, while the
remaining 25% shows ratios clustered at [N/alpha] = -1.45 with an even lower
dispersion of 0.05 dex. The high [N/alpha] plateau is consistent with the one
observed in metal-poor HII regions of blue compact dwarf (BCD) galaxies
([N/alpha] = -0.73 +/- 0.13), while the [N/alpha] ~ -1.5 values are the lowest
ever observed in any astrophysical site. These low [N/alpha] ratios are real
and not due to ionization effects. They provide a crucial evidence against the
primary production of N by massive stars as responsible for the plateau at
-0.9/-0.7 dex observed in DLAs and BCD galaxies. The transition between the
low-N ([N/alpha] ~ -1.5) and high-N ([N/alpha] ~ -0.9) DLAs occurs at a
nitrogen abundance of [N/H] ~ -2.8, suggesting that the separation may result
from some peculiarity of the nitrogen enrichment history. The [N/alpha] ~ -1.5
values and their low dispersion are consistent with a modest production of
primary N in massive stars; however, due to the limited sample, specially for
the low-N DLAs, we cannot exclude a primary origin in intermediate mass stars
as responsible for the low N abundances observed.


  Random constraint satisfaction problems (CSPs) have been widely studied both
in AI and complexity theory. Empirically and theoretically, many random CSPs
have been shown to exhibit a phase transition. As the ratio of constraints to
variables passes certain thresholds, they transition from being almost
certainly satisfiable to unsatisfiable. The exact location of this threshold
has been thoroughly investigated, but only for certain common classes of
constraints. In this paper, we present new bounds for the location of these
thresholds in boolean CSPs. Our main contribution is that our bounds are fully
general, and apply to any fixed constraint function that could be used to
generate an ensemble of random CSPs. These bounds rely on a novel Fourier
analysis and can be easily computed from the Fourier spectrum of a constraint
function. Our bounds are within a constant factor of the exact threshold
location for many well-studied random CSPs. We demonstrate that our bounds can
be easily instantiated to obtain thresholds for many constraint functions that
had not been previously studied, and evaluate them experimentally.


  We prove a version of the Mayer-Vietoris sequence for De Rham differential
forms in diffeological spaces. It is based on the notion of a generating family
instead of that of a covering by open subsets.


  Human pose estimation is a fundamental and appealing task in computer vision.
Traditional frame-based cameras and videos are commonly applied, yet, they
become less reliable in scenarios under high dynamic range or heavy motion
blur. In contrast, event cameras offer a robust solution for navigating these
challenging contexts. Predominant methodologies incorporate event cameras into
learning frameworks by accumulating events into event frames. However, such
methods tend to marginalize the intrinsic asynchronous and high temporal
resolution characteristics of events. This disregard leads to a loss in
essential temporal dimension data, crucial for discerning distinct actions. To
address this issue and to unlock the 3D potential of event information, we
introduce two 3D event representations: the Rasterized Event Point Cloud
(RasEPC) and the Decoupled Event Voxel (DEV). The RasEPC collates events within
concise temporal slices at identical positions, preserving 3D attributes with
statistical cues and markedly mitigating memory and computational demands.
Meanwhile, the DEV representation discretizes events into voxels and projects
them across three orthogonal planes, utilizing decoupled event attention to
retrieve 3D cues from the 2D planes. Furthermore, we develop and release
EV-3DPW, a synthetic event-based dataset crafted to facilitate training and
quantitative analysis in outdoor scenes. On the public real-world DHP19
dataset, our event point cloud technique excels in real-time mobile
predictions, while the decoupled event voxel method achieves the highest
accuracy. Experiments on EV-3DPW demonstrate that the robustness of our
proposed 3D representation methods compared to traditional RGB images and event
frame techniques under the same backbones. Our code and dataset have been made
publicly available at https://github.com/MasterHow/EventPointPose.


  A new class of nonparametric prior distributions, termed Beta-Binomial
stick-breaking process, is proposed. By allowing the underlying length random
variables to be dependent through a Beta marginals Markov chain, an appealing
discrete random probability measure arises. The chain's dependence parameter
controls the ordering of the stick-breaking weights, and thus tunes the model's
label-switching ability. Also, by tuning this parameter, the resulting class
contains the Dirichlet process and the Geometric process priors as particular
cases, which is of interest for fast convergence of MCMC implementations. Some
properties of the model are discussed and a density estimation algorithm is
proposed and tested with simulated datasets.


  The current statistical procedures implemented in statistical software
packages for pooling of diagnostic test accuracy data include hSROC regression
and the bivariate random-effects meta-analysis model (BRMA). However, these
models do not report the overall mean but rather the mean for a central study
with random-effect equal to zero and have difficulties estimating the
correlation between sensitivity and specificity when the number of studies in
the meta-analysis is small and/or when the between-study variance is relatively
large. This tutorial on advanced statistical methods for meta-analysis of
diagnostic accuracy studies discusses and demonstrates Bayesian modeling using
CopulaDTA package in R to fit different models to obtain the meta-analytic
parameter estimates. The focus is on the joint modelling of sensitivity and
specificity using copula based bivariate beta distribution. Essentially, we
extend the work of Nikoloulopoulos by: i) presenting the Bayesian approach
which offers flexibility and ability to perform complex statistical modelling
even with small data sets and ii) including covariate information, and iii)
providing an easy to use code. The statistical methods are illustrated by
re-analysing data of two published meta-analyses. Modelling sensitivity and
specificity using the bivariate beta distribution provides marginal as well as
study-specific parameter estimates as opposed to using bivariate normal
distribution (e.g., in BRMA) which only yields study-specific parameter
estimates. Moreover, copula based models offer greater flexibility in modelling
different correlation structures in contrast to the normal distribution which
allows for only one correlation structure.


  We give a generalization of toric symplectic geometry to Poisson manifolds
which are symplectic away from a collection of hypersurfaces forming a normal
crossing configuration. We introduce the tropical momentum map, which takes
values in a generalization of affine space called a log affine manifold. Using
this momentum map, we obtain a complete classification of such manifolds in
terms of decorated log affine polytopes, hence extending the classification of
symplectic toric manifolds achieved by Atiyah, Guillemin-Sternberg, Kostant,
and Delzant.


  In this paper we develop a sysmatical theory for topological orders by the
projected p-wave superconducting (SC) wave-functions and unify the different
topological orders for spin models into the fermionic picture. We found that
the energy for the fermions at k=(0,0), (0, pi), (pi, 0), (pi, pi) acts as a
topological invariable to characterize 16 universal classes of different
topological orders for the spin models with translation invariance. Based on
the projected p-wave SC wave-functions the topological properties for the known
topological orders in the exact solved spin models are obtained. Finally new
types of topological orders are predicted.


  The order parameters of dynamical chiral symmetry breaking in QCD, the
dynamical mass of quarks and the chiral condensates, are evaluated by
numerically solving the Non-Perturbative Renormalization Group (NPRG)
equations. We employ an approximation scheme beyond ``the ladder'', that is,
beyond the (improved) ladder Schwinger-Dyson equations. The chiral condensates
are enhanced compared with the ladder ones, which is phenomenologically
favorable. The gauge dependence of the order parameters is fairly reduced in
this scheme.


  When utilized effectively, Supercloud heterogeneous systems have the
potential to significantly enhance performance. Our ReDSEa tool-chain automates
the mapping, load balancing, scheduling, parallelism, and overlapping processes
for the Triangular System Solver (TS) on a heterogeneous system consisting of a
Huawei Kunpeng ARM multi-core CPU and an Ascend 910 AI HW accelerator. We
propose an LLVM compiler tool-chain that a) leverages compiler analysis and b)
utilizes novel performance models exploring recursive, iterative, and blocked
computation models. Our tool-chain facilitates a speedup of up to 16x compared
to an optimized 48-core CPU-only implementation.


  Electromagnetic materials possessing parity-time symmetry have received
significant attention since it was discovered that the eigenmodes of these
materials possess either real-frequency eigenvalues or the eigenfrequencies
appear in complex-conjugate pairs. Interestingly, some eigenstates of these
systems show thresholdless $\mathcal{PT}$ transitions to the complex-conjugate
regime, some exhibit a transition as a function of the degree of
non-Hermiticity and some show no $\mathcal{PT}$ transition at all. While
previous work has provided some insight on the nature of $\mathcal{PT}$
transitions, this work lays out a general and rigorous mathematical framework
that is able to predict, based on symmetry alone, whether an eigenmode will
exhibit a thresholdless $\mathcal{PT}$ transition or no $\mathcal{PT}$
transition at all. Developed within the context of ferromagnetic solids,
Heesh-Shubnikov group theory is an extension of classical group theory that is
applicable to antiunitary operators. This work illustrates the Heesh-Shubnikov
approach by categorizing the modes of a two-dimensionally periodic photonic
lattice that possesses $\mathcal{PT}$ symmetry.


  Self consistent quantum approaches are used to study the instabilities of
finite nuclear systems. The frequencies of multipole density fluctuations are
determined as a function of dilution and temperature, for several isotopes. The
spinodal region of the phase diagrams is determined and it appears that
instabilities are reduced by finite size effects. The role of surface and
volume instabilities is discussed. It is indicated that the important chemical
effects associated with mechanical disruption may lead to isospin
fractionation.


  We study the nature of the phase transition at high temperature and high
density in lattice gauge theories by focusing on the probability distribution
function, which represents the probability that a certain density will be
realized in a heat bath. The probability distribution function is obtained by
constructing a canonical partition function by fixing the number of particles
from the grand partition function. However, if the Z3 center symmetry, which is
important for understanding the finite temperature phase transition of SU(3)
lattice gauge theory, is maintained on a finite lattice, the probability
distribution function is always zero, except when the number of particles is a
multiple of 3. For U(1) gauge theory, this problem is more extreme. The
probability distribution becomes zero when the particle number is not zero. In
this study, we find a solution to this problem and propose a method of avoiding
the sign problem, which is an important problem at finite density, using the
center symmetry. This problem is essentially the same as the problem that the
expectation value of the Polyakov loop is always zero when calculating with
finite volume. In the case of U(1) lattice gauge theory with heavy fermions,
numerical simulations are actually performed, and we demonstrate that the
probability distribution function at a finite density can be calculated by the
method proposed in this study.


  We study the problem of Diophantine approximation on lines in R^2 with prime
numerator and denominator.


  Scenario generation is a fundamental and crucial tool for decision-making in
power systems with high-penetration renewables. Based on big historical data, a
novel federated deep generative learning framework, called Fed-LSGAN, is
proposed by integrating federated learning and least square generative
adversarial networks (LSGANs) for renewable scenario generation. Specifically,
federated learning learns a shared global model in a central server from
renewable sites at network edges, which enables the Fed-LSGAN to generate
scenarios in a privacy-preserving manner without sacrificing the generation
quality by transferring model parameters, rather than all data. Meanwhile, the
LSGANs-based deep generative model generates scenarios that conform to the
distribution of historical data through fully capturing the spatial-temporal
characteristics of renewable powers, which leverages the least squares loss
function to improve the training stability and generation quality. The
simulation results demonstrate that the proposal manages to generate
high-quality renewable scenarios and outperforms the state-of-the-art
centralized methods. Besides, an experiment with different federated learning
settings is designed and conducted to verify the robustness of our method.


  The puzzles of direct dark matter searches can be solved in the scenario of
dark atoms, which bind hypothetical, stable, lepton-like particles with charge
$-2n$, where $n$ is any natural number, with $n$ nuclei of primordial helium.
Avoid experimental discovery because they form with primary helium neutral
atom-like states $OHe$ ($X~-$ helium), called "dark" atoms. The proposed
solution to this problem involves rigorous proof of the existence of a
low-energy bound state in the dark atom interaction with nuclei. It implies
self-consistent account for nuclear attraction and Coulomb repulsion in such an
interaction. We approach the solution of this problem by numerical modeling to
reveal the essence of the processes of dark atom interaction with nuclei. We
start with the classical three-body problem, to which the effects of quantum
physics are added. The numerical model of the dark atom interaction was
developed for $O^{--}$ having a charge of $-2$, bound with He in Bohr-like
$OHe$ dark atom and for $-2n$ charged $X$ bound with $n$ $\alpha$-particle
nucleus in the Thomson-like atom $XHe$. The development of our approach should
lead to the solution of the puzzles of direct dark matter searches in the
framework of dark atom hypothesis.


  In this paper we study the complete reducibility of representations of
infinite-dimensional Lie algebras from the perspective of the representation
theory of vertex algebras.


  We compute the bi-Hamiltonian cohomology of an arbitrary dispersionless
Poisson pencil in a single dependent variable using a spectral sequence method.
As in the KdV case, we obtain that $BH^p_d(\hat{F}, d_1,d_2)$ is isomorphic to
$\mathbb{R}$ for $(p,d)=(0,0)$, to $C^\infty (\mathbb{R})$ for $(p,d)=(1,1)$,
$(2,1)$, $(2,3)$, $(3,3)$, and vanishes otherwise.


  Let $C$ be a smooth irreducible projective algebraic curve defined over the
complex numbers. The notion of the Clifford index of $C$ was extended a few
years ago to semistable bundles of any rank. Recent work has been focussed
mainly on the rank-2 Clifford index, although interesting results have also
been obtained for the case of rank 3. In this paper we extend this work,
obtaining improved lower bounds for the rank-3 Clifford index. This allows the
first computations of the rank-3 index in non-trivial cases and examples for
which the rank-3 index is greater than the rank-2 index.


  We consider the entropy of higher spin black holes in 2+1 dimensions using
the conical singularity approach. By introducing a conical singularity along a
non contractible cycle and carefully evaluating its contribution to the Chern
Simons action, we derive a simple expression for the entropy of a general
stationary higher spin black hole. The resulting formula is shown to satisfy
the first law of thermodynamics, and yields agreement with previous results
based on integrating the first law.


  Objective. To analyse quantitatively the articles published during 2008_2017
about the academic social networking site ResearchGate. Methods. A scoping
bibliometric review of documents retrieved using Google Scholar was conducted,
limited to publications that contained the word "ResearchGate" in their title
and were published from 2008 to 2017. Results. The search yielded 159
documents, once a preliminary list of 386 documents retrieved from Google
Scholar was filtered, which eliminated about 60% of the results that were
bibliographic citations and not documents. Papers in journals were the most
numerous type of documents (n73; 46%), followed by conference papers (n_31;
19.5 %). Contributing eight publications, two Spanish scholars (Delgado
Lopez-Cozar and Orduna Malea, who were coauthors in each case) were the most
prolific authors writing on this topic during the ten-year period. The keywords
most used in the documents were "ResearchGate" and "Altmetrics". The
publications were cited frequently since 2014 (more than 90% of the total cites
fell in that period), and those with more than one author were the most cited
ones. The authors of the documents were mainly librarians and information
science professionals, who wrote primarily as co-authors with colleagues from
their own institutions, mostly published in English. Conclusions. Interest in
ResearchGate has grown since 2015, as evident from the number of articles
published and the citations they received. Keywords. Academic social networks,
bibliometrics, scholarly communication


  We systematically map out the jamming transition of all 2D bidisperse
mixtures of frictionless disks in the hard particle limit. The critical volume
fraction, mean coordination number, number of rattlers, structural order
parameters, and bulk modulus each show a rich variation with mixture
composition and particle size ratio, and can therefore be tuned by choosing
certain mixtures. We identify two local minima in the critical volume fraction,
both of which have low structural order; one minimum is close to the widely
studied 50:50 mixture of particles with a ratio of radii of 1:1.4. We also
identify a region at low size ratios characterized by increased structural
order and high rattler fractions, with a corresponding enhancement in the
stiffness.


  Recommender systems for TV program have been studied for the realization of
personalized TV Electronic Program Guides. In this paper, we propose automatic
emotion Arabic speech recognition in order to achieve an intelligent remote
control. In addition, the TV can estimate our interests and preferences by
observing our behavior to watch and have a conversation on topics that might be
interesting to us.


  The existence of 10$^9$ M$_{\odot}$ black holes (BH) in massive galaxies by
$z \ sim$ 7 is one of the great unsolved mysteries in cosmological structure
formation. One theory argues that they originate from the black holes of Pop
III stars at $z \sim$ 20 and then accrete at the Eddington limit down to the
epoch of reionization, which requires that they have constant access to rich
supplies of fuel. Because early numerical simulations suggested that Pop III
stars were $\gtrsim$ 100 M$_{\odot}$, the supermassive black hole seeds
considered up to now were 100 - 300 M$_{\odot}$. However, there is a growing
numerical and observational consensus that some Pop III stars were tens of
solar masses, not hundreds, and that 20 - 40 M$_{\odot}$ black holes may have
been much more plentiful at high redshift. However, we find that natal kicks
imparted to 20 - 40 M$_{\odot}$ Pop III BHs during formation eject them from
their halos and hence their fuel supply, precluding them from Eddington-limit
growth. Consequently, supermassive black holes are far less likely to form from
low-mass Pop III stars than from very massive ones.


  A multilevel coded modulation scheme is studied that uses solely binary polar
codes and Honda-Yamamoto probabilistic shaping. The scheme is shown to achieve
the capacity of discrete memoryless channels with input alphabets of
cardinality a power of two. The performance of finite-length implementations is
compared to polar-coded probabilistic amplitude shaping and constant
composition distribution matching.


  The ionosphere is the main driver of a series of systematic effects that
limit our ability to explore the low frequency (<1 GHz) sky with radio
interferometers. Its effects become increasingly important towards lower
frequencies and are particularly hard to calibrate in the low signal-to-noise
ratio regime in which low-frequency telescopes operate. In this paper we
characterize and quantify the effect of ionospheric-induced systematic errors
on astronomical interferometric radio observations at ultra-low frequencies
(<100 MHz). We also provide guidelines for observations and data reduction at
these frequencies with the Low Frequency Array (LOFAR) and future instruments
such as the Square Kilometre Array (SKA). We derive the expected systematic
error induced by the ionosphere. We compare our predictions with data from the
Low Band Antenna (LBA) system of LOFAR. We show that we can isolate the
ionospheric effect in LOFAR LBA data and that our results are compatible with
satellite measurements, providing an independent way to measure the ionospheric
total electron content (TEC). We show how the ionosphere also corrupts the
correlated amplitudes through scintillations. We report values of the
ionospheric structure function in line with the literature. The systematic
errors on the phases of LOFAR LBA data can be accurately modelled as a sum of
four effects (clock, ionosphere 1st, 2nd, and 3rd order). This greatly reduces
the number of required calibration parameters, and therefore enables new
efficient calibration strategies.


  Evolutionary synthesis models for star clusters of various metallicities
including gaseous emission during the lifetime of the ionising stars are used
to model star cluster systems comprising two populations: an old metal-poor
globular clusters (GC) population similar to that of the Milky Way halo and a
second GC population of arbitrary metallicity. We investigate the time
evolution of color distributions and luminosity functions for the two GC
populations in comparison with observations on E/S0 galaxies. We show that
multi-passband data for GC populations give clues to the relative ages and
metallicities of blue and red subpopulations and help constrain formation
scenarios for their parent galaxies.


  The groundstate energy and binding energy of an exciton, confined in a^M
quantum disk, are calculated as a function of an external magnetic field. The
confinement potential is a hard wall of finite height. The diamagnetic shift is
investigated for magnetic fields up to 40$T$. Our results are applied to
$In_{y}Al_{1-y}As/Al_{x}Ga_{1-x}As$ self-assembled quantum dots and very good
agreement with experiments is obtained. Furthermore, we investigated the
influence of the dot size on the diamagnetic shift by changing the disk radius.
The exciton excited states are found as a function of the magnetic field. The
relative angular momentum is not a quantum number and changes with the magnetic
field strength.


  We carried out detailed kinematic studies of the complex of multiple HI and
HII shells that represent the only region of ongoing star formation in the
dwarf irregular galaxy IC 1613. We investigated the ionized-gas kinematics by
using Fabry--Perot H-alpha observations with the 6-m Special Astrophysical
Observatory telescope and the neutral-gas kinematics by using VLA 21-cm radio
observations. We identified three extended (300-350 pc) neutral shells with
which the brightest HII shells in the complex of star formation are associated.
The neutral-gas kinematics in the complex has been studied for the first time
and the H~I shells were found to expand at a velocity of 15--18 km/s. We
constructed velocity ellipses for all HII shells in the complex and refined
(increased) the expansion velocities of most of them. The nature of the
interacting ionized and neutral shells is discussed.


  The chiral source and its mechanism in the molecular system are of great
significance in many fields. In this work, we proposed visualized methods to
investigate physical mechanism of chiral molecule, where the electric and
magnetic interactions are visualized with the transitional electric dipole
moment, the transitional magnetic dipole moment and the transitional electric
quadrupole moment, and their tensor product. The relationship between molecular
ROA response and molecular structure was analyzed in an intuitive way. The
relationship between chromophore chirality and molecular vibration mode are
revealed via interaction between the transition electric dipole moment and the
transition magnetic dipole moment. The molecular chirality is derived from the
anisotropy of the molecular transition electric dipole moment and the
transition magnetic dipole moment. The anisotropic dipole moment localized
molecular chromophore is the source of the vibration mode in which the ROA
responds to the reverse.


  We measure directed flow ($v_1$) for charged particles in Au+Au and Cu+Cu
collisions at $\sqrt{s_{NN}} =$ 200 GeV and 62.4 GeV, as a function of
pseudorapidity ($\eta$), transverse momentum ($p_t$) and collision centrality,
based on data from the STAR experiment. We find that the directed flow depends
on the incident energy but, contrary to all existing models, not on the size of
the colliding system at a given centrality. We extend the validity of the
limiting fragmentation concept to different collision systems, and investigate
possible explanations for the observed sign change in $v_1(p_t)$.


  The question of the onset of the homochirality on prebiotic Earth still
remains a fundamental question in the quest for the origin of life. Recent
works in this field introduce the concept of recycling, rather than the
traditional open-flow system described by Frank. This approach has been
criticized by Blackmond et al. They claimed that such systems are
thermodynamically impossible, except in the cases where non-microreversible
reactions are introduced, like in photochemical reactions, or under the
influence of physical actions (e.g. by crystal crushing). This point of view
reveals misunderstandings about this model of a recycled system, overlooks the
possibility of energy exchanges that could take place in prebiotic systems, and
leads the authors to unawarely remove the activation reaction and energy source
from their "non-equilibrium" models. It is especially important to understand
what are the concepts behind the notion of recycled systems, and of activation
reactions. These points are fundamental to comprehending how chemical systems
-- and especially prebiotic chemical systems -- can be maintained in
non-equilibrium steady states, and how free energy can be used and exchanged
between systems. The proposed approach aims at the decomposition of the
problem, avoiding to embrace the whole system at the same time.


  We present high resolution simulations of a multiple merger of three disk
galaxies including the evolution of magnetic fields performed with the
N-body/SPH code Gadget. For the first time, we embed the galaxies in a
magnetized, low-density medium, thus modeling an ambient IGM. The simulations
include radiative cooling and a model for star formation and supernova
feedback. The progenitor disks have initial magnetic seed fields in the range
of 10e-9 to 10e-6 G and the IGM has initial fields of 10e-12 to 10e-9 G. The
simulations are compared to a run excluding magnetic fields. We show that the
propagation of interaction-driven shocks depends significantly on the initial
magnetic field strength. The shocks propagate faster in simulations with
stronger initial field, suggesting that the shocks are supported by magnetic
pressure. The Mach numbers of the shocks range from approximately M=1.5 for the
non-magnetized case up to M=6 for the highest initial magnetization, resulting
in higher temperatures of the shock heated IGM gas. The magnetic field in the
system saturates rapidly after the mergers at ~ 10e-6 G within the galaxies and
~ 10e-8 G in the IGM independent of the initial value. These field strengths
agree with observed values and correspond to the equipartition value of the
magnetic pressure with the turbulent pressure in the system. We also present
synthetic radio and polarization maps for different phases of the evolution
showing that shocks driven by the interaction produce a high amount of
polarized emission. These idealized simulations indicate that magnetic fields
play an important role for the hydrodynamics of the IGM during galactic
interactions. We also show that even weak seed fields are efficiently
strengthened during multiple galactic mergers. This interaction driven
amplification might have been a key process for the magnetization of the
Universe.


  Let $G$ be a finite abelian group with $\exp(G)$ the exponent of $G$. Then
$\mathsf W(G)$ denotes the set of cross numbers of minimal zero-sum sequences
over $G$ and $\mathsf w(G)$ denotes the set of all cross numbers of non-trivial
zero-sum free sequences over $G$. It is clear that $\mathsf W(G)$ and $\mathsf
w(G)$ are bounded subsets of $\frac{1}{\exp(G)}\mathbb{N}$ with maximum $
\mathsf K(G)$ and $\mathsf k(G)$, respectively (here $\mathsf{K}(G)$ and
$\mathsf{k}(G)$ denote the large and the small cross number of $G$,
respectively). We give results on the structure of $\mathsf W(G)$ and $\mathsf
w(G)$. We first show that both sets contain long arithmetic progressions and
that only close to the maximum there might be some gaps. Then, we provide
groups for which $\mathsf W(G)$ and $\mathsf w(G)$ actually are arithmetic
progressions, and argue that this is rather a rare phenomenon. Finally, we
provide some results in case there are gaps.


  We present PERIN, a novel permutation-invariant approach to sentence-to-graph
semantic parsing. PERIN is a versatile, cross-framework and language
independent architecture for universal modeling of semantic structures. Our
system participated in the CoNLL 2020 shared task, Cross-Framework Meaning
Representation Parsing (MRP 2020), where it was evaluated on five different
frameworks (AMR, DRG, EDS, PTG and UCCA) across four languages. PERIN was one
of the winners of the shared task. The source code and pretrained models are
available at https://github.com/ufal/perin.


  We prove Strichartz estimates for the Schr\"odinger equation which are
scale-invariant up to an $\varepsilon$-loss on products of odd-dimensional
spheres. Namely, for any product of odd-dimensional spheres
$M=\mathbb{S}^{d_1}\times\cdots\times\mathbb{S}^{d_r}$ (so that $M$ is of
dimension $d=d_1+\cdots+d_r$ and rank $r$) equipped with rational metrics, the
following Strichartz estimate \begin{equation*} \|e^{it\Delta}f\|_{L^p(I\times
M)}\leq C_\varepsilon\|f\|_{H^{\frac{d}{2}-\frac{d+2}{p}+\varepsilon}(M)}
\end{equation*} holds for any $p\geq 2+\frac{8(s-1)}{sr}$, where
$$s=\max\left\{\frac{2d_i}{d_i-1}, i=1,\ldots,r\right\}.$$


  Various physical properties of the pyrochlore oxide Y2-xBixIr2O7 have been
studied. The magnetizations M measured under the conditions of the
zero-field-cooling(ZFC) and the field-cooling(FC) have different values below
the temperature T=TG. The anomalous T-dependence of the electrical
resistivities r and the thermoelectric powers S observed at around TG indicates
that the behavior of the magnetization is due to the transition to the state
with the spin freezing. In this spin-frozen state, the Hall resistivities rH
measured with the ZFC and FC conditions are found to have different values,
too, in the low temperature phase (T<TG). Possible mechanisms which induce such
the hysteretic behavior are discussed.


  It is demonstrated by SQUID magnetization measurements that (Ga,Mn)As films
can exhibit rich characteristics of magnetic anisotropy depending not only to
the epitaxial strain but being strongly influenced by the hole and Mn
concentration, and temperature. This behavior reflects the spin anisotropy of
the valence subbands and corroborates predictions of the mean field Zener model
of the carrier mediated ferromagnetism in III-V diluted magnetic semiconductors
with Mn. At the same time the existence of in-plane uniaxial anisotropy with
[110] the easy axis is evidenced. This is related to the top/bottom symmetry
breaking, resulting in the lowering of point symmetry of (Ga,Mn)As to the
C_{2v} symmetry group. The latter mechanism coexists with the hole-induced
cubic anisotropy, but takes over close to T_C.


  Grand Unified Theories (GUTs) usually predict wrong Standard Model (SM)
fermion mass relation m_e/m_{\mu} = m_d/m_s toward low energies. To solve this
problem, we consider the Generalized Minimal Supergravity (GmSUGRA) models,
which are GUTs with gravity mediated supersymmetry breaking and higher
dimensional operators. Introducing non-renormalizable terms in the super- and
K\"ahler potentials, we can obtain the correct SM fermion mass relations in the
SU(5) model with GUT Higgs fields in the {\bf 24} and {\bf 75} representations,
and in the SO(10) model. In the latter case the gauge symmetry is broken down
to SU(3)_C X SU(2)_L X SU(2)_R X U(1)_{B-L}, to flipped SU(5)X U(1)_X, or to
SU(3)_C X SU(2)_L X U(1)_1 X U(1)_2. Especially, for the first time we generate
the realistic SM fermion mass relation in GUTs by considering the
high-dimensional operators in the K\"ahler potential.


  We investigate the fairness issue in classification, where automated
decisions are made for individuals from different protected groups. In
high-consequence scenarios, decision errors can disproportionately affect
certain protected groups, leading to unfair outcomes. To address this issue, we
propose a fairness-adjusted selective inference (FASI) framework and develop
data-driven algorithms that achieve statistical parity by controlling the false
selection rate (FSR) among protected groups. Our FASI algorithm operates by
converting the outputs of black-box classifiers into R-values, which are both
intuitive and computationally efficient. These R-values serve as the basis for
selection rules that are provably valid for FSR control in finite samples for
protected groups, effectively mitigating the unfairness in group-wise error
rates. We demonstrate the numerical performance of our approach using both
simulated and real data.


  We deal with the problem of preserving various versions of completeness in (<
kappa) --support iterations of forcing notions, generalizing the case ``S
--complete proper is preserved by CS iterations for a stationary co-stationary
S subseteq omega_1''. We give applications to Uniformization and the Whitehead
problem. In particular, for a strongly inaccessible cardinal kappa and a
stationary set S subseteq kappa with fat complement we can have uniformization
for < A_delta : delta in S'>, A_delta subseteq delta = sup A_delta,
cf(delta)=otp(A_delta) and a stationary non-reflecting set S' subseteq S .


  We study the surface and bulk electronic structure of the room-temperature
ferromagnet Co:TiO2 anatase films using soft and hard x-ray photoemission
spectroscopy with probe sensitivities of ~1 nm and ~10 nm, respectively. We
obtain direct evidence of metallic Ti$^{3+}$ states in the bulk, which get
suppressed to give a surface semiconductor, thus indicating a surface-bulk
dichotomy. X-ray absorption and high-sensitivity resonant photoemission
spectroscopy reveal Ti$^{3+}$ electrons at the Fermi level (E$_F$) and
high-spin Co$^{2+}$ electrons occurring away from E$_F$. The results show the
importance of the charge neutrality condition: Co$^{2+}$ + V$_{O}$$^{2-}$ +
2Ti$^{4+}$ $\leftrightarrow$ Co$^{2+}$ + 2Ti$^{3+}$ (V$_O$ is oxygen vacancy),
which gives rise to the elusive Ti 3d carriers mediating ferromagnetism via the
Co 3d-O 2p-Ti 3d exchange interaction pathway of the occupied orbitals.


  Machine learning algorithms are increasingly used to make or support
decisions in a wide range of settings. With such expansive use there is also
growing concern about the fairness of such methods. Prior literature on
algorithmic fairness has extensively addressed risks and in many cases
presented approaches to manage some of them. However, most studies have focused
on fairness issues that arise from actions taken by a (single) focal
decision-maker or agent. In contrast, most real-world systems have many agents
that work collectively as part of a larger ecosystem. For example, in a lending
scenario, there are multiple lenders who evaluate loans for applicants, along
with policymakers and other institutions whose decisions also affect outcomes.
Thus, the broader impact of any lending decision of a single decision maker
will likely depend on the actions of multiple different agents in the
ecosystem. This paper develops formalisms for firm versus systemic fairness,
and calls for a greater focus in the algorithmic fairness literature on
ecosystem-wide fairness - or more simply systemic fairness - in real-world
contexts.


  Bayesian inference provides a rigorous framework to encapsulate our knowledge
and uncertainty regarding various physical quantities in a well-defined and
self-contained manner. Utilising modern tools, such Bayesian models can be
constructed with a remarkable flexibility, leaving us totally free to carefully
choose which assumption should be strictly enforced and which should on the
contrary be relaxed. The practical evaluation of these assumptions, together
with the data-driven selection or averaging of models, also appears in a very
natural way. In this presentation, I discuss its application in the context of
lattice QCD and its common statistical problems. As a concrete illustration, I
present a few parametric and non-parametric hierarchical models applied to
actual correlator data, from single exponential fits to spectral functions.


  Magnetohydrodynamic (MHD) turbulence is an important agent of energetic
particle acceleration. Focusing on the compressible properties of magnetic
turbulence, we adopt test particle method to study the particle acceleration
from Alfv\'en, slow and fast modes in four turbulence regimes that may appear
in a realistic astrophysical environment. Our studies show that (1) the
second-order Fermi mechanism drives the acceleration of particles in the
cascade processes of three modes by particle-turbulence interactions,
regardless of whether the shock wave appears; (2) not only can the power
spectra of maximum acceleration rates reveal the inertial range of compressible
turbulence, but also recover the scaling and energy ratio relationship between
the modes; (3) fast mode dominates the acceleration of particles, especially in
the case of super-Alfv\'enic and supersonic turbulence, slow mode dominates the
acceleration for sub-Alfv\'enic turbulence in the very high energy range, and
the acceleration of Alfv\'en mode is significant at the early stage of the
acceleration; (4) particle acceleration from three modes results in a power-law
distribution in the certain range of evolution time. From the perspective of
particle-wave mode interaction, this paper promotes the understanding for both
the properties of turbulence and the behavior of particle acceleration, which
will help insight into astrophysical processes involved in MHD turbulence.


  We analyze the dynamics of growth of the number of congressmen supporting the
resolution HR1207 to audit the Federal Reserve. The plot of the total number of
co-sponsors as a function of time is of "Devil's staircase" type. The
distribution of the numbers of new co-sponsors joining during a particular day
(step height) follows a power law. The distribution of the length of intervals
between additions of new co-sponsors (step length) also follows a power law. We
use a modification of Bak-Tang-Wiesenfeld sandpile model to simulate the
dynamics of Congress and obtain a good agreement with the data.


  Modeling hand-object manipulations is essential for understanding how humans
interact with their environment. While of practical importance, estimating the
pose of hands and objects during interactions is challenging due to the large
mutual occlusions that occur during manipulation. Recent efforts have been
directed towards fully-supervised methods that require large amounts of labeled
training samples. Collecting 3D ground-truth data for hand-object interactions,
however, is costly, tedious, and error-prone. To overcome this challenge we
present a method to leverage photometric consistency across time when
annotations are only available for a sparse subset of frames in a video. Our
model is trained end-to-end on color images to jointly reconstruct hands and
objects in 3D by inferring their poses. Given our estimated reconstructions, we
differentiably render the optical flow between pairs of adjacent images and use
it within the network to warp one frame to another. We then apply a
self-supervised photometric loss that relies on the visual consistency between
nearby images. We achieve state-of-the-art results on 3D hand-object
reconstruction benchmarks and demonstrate that our approach allows us to
improve the pose estimation accuracy by leveraging information from neighboring
frames in low-data regimes.


  In this paper, we show how photocapacitance spectra can probe two dimensional
excitonic complexes and Fermi edge singularity as a function of applied bias
around 100 K. In lower density regimes (<1x1011cm^-2), the appearance of two
distinct peaks in the spectra are identified as a signature of coexistence of
both excitons and positively charged trions. We estimate the binding energy of
these trions as ~2.0 meV. In the higher density regimes (>1x10^11 cm^-2), we
observe a sharp spectral transition from trions to asymmetric shaped Fermi edge
singularity in the photocapacitance spectra around a particular reverse bias.
However, these signatures are absent from the photoluminescence spectra
measured under identical circumstances. Such dissimilarities clearly point out
that different many body physics govern these two spectral measurements. We
also argue why such quantum confined dipoles of spatially indirect trions can
have thermodynamically finite probability to survive even around 100 K.
Finally, our observations demonstrate that photocapacitance technique, which
was seldom used to detect trions in the past, can also be useful to detect the
traces of these spatially indirect excitonic complexes as well as Fermi edge
singularity even at 100 K. This is mainly due to enhanced sensitivity of such
dielectric measurements to dipolar changes within such heterojunction.


  One of the most fundamental tasks in data science is to assist a user with
unknown preferences in finding high-utility tuples within a large database. To
accurately elicit the unknown user preferences, a widely-adopted way is by
asking the user to compare pairs of tuples. In this paper, we study the problem
of identifying one or more high-utility tuples by adaptively receiving user
input on a minimum number of pairwise comparisons. We devise a single-pass
streaming algorithm, which processes each tuple in the stream at most once,
while ensuring that the memory size and the number of requested comparisons are
in the worst case logarithmic in $n$, where $n$ is the number of all tuples. An
important variant of the problem, which can help to reduce human error in
comparisons, is to allow users to declare ties when confronted with pairs of
tuples of nearly equal utility. We show that the theoretical guarantees of our
method can be maintained for this important problem variant. In addition, we
show how to enhance existing pruning techniques in the literature by leveraging
powerful tools from mathematical programming. Finally, we systematically
evaluate all proposed algorithms over both synthetic and real-life datasets,
examine their scalability, and demonstrate their superior performance over
existing methods.


  We propose a general path-integral definition of two-dimensional quantum
field theories deformed by an integrable, irrelevant vector operator
constructed from the components of the stress tensor and those of a $U(1)$
current. The deformed theory is obtained by coupling the original QFT to a flat
dynamical gauge field and "half" a flat dynamical vielbein. The resulting
partition function is shown to satisfy a geometric flow equation, which
perfectly reproduces the flow equations for the deformed energy levels that
were previously derived in the literature. The S-matrix of the deformed QFT
differs from the original S-matrix only by an overall phase factor that depends
on the charges and momenta of the external particles, thus supporting the
conjecture that such QFTs are UV complete, although intrinsically non-local.
For the special case of an integrable QFT, we check that this phase factor
precisely reproduces the change in the finite-size spectrum via the
Thermodynamic Bethe Ansatz equations.


  A magneto-orbital coupling mechanism is proposed to account for the weak
energy gap at the Fermi energy in the $(\pi,0)$ ordered SDW state of a
realistic three band model for iron pnictides involving $d_{xz}$, $d_{yz}$, and
$d_{xy}$ Fe orbitals. The orbital mixing terms between the $d_{xy}$ and
$d_{xz}/d_{yz}$ orbitals, which are important in reproducing the orbital
composition of the elliptical electron pockets at $(\pm \pi,0)$ and $(0,\pm
\pi)$, are shown to play a key role in the energy gap formation in the SDW
state.


  In this paper, adhesive contact of a rigid cylinder on an elastic power-law
graded half-space is studied analytically with the theory of weakly singular
integral equation and orthogonal polynomial method. Emphasis is placed on the
coupling effect between tangential and normal directions which was often
neglected in previous works. Our analysis shows that the coupling effect tends
to minimize the contact area in the compressive regime. The effect of bending
moment on the adhesion behavior is also examined. Like a pull-off force, there
also exist a critical bending moment at which the cylinder can be bended apart
from the substrate. However, unlike pull-off force, the critical bending moment
is insensitive to the gradient exponent of the graded material.


  Thermonuclear and core-collapse supernova remnants (SNRs) are the nebular
leftovers of defunct stars. Their morphology and emission properties provide
insights into the evolutionary history of the progenitor star. But while some
SNRs are spherical, as expected from a point-like explosion expanding into a
roughly uniform medium, many others exhibit complex non-spherical morphologies
which are often not easily explained. In this work, we use three-dimensional
magnetohydrodynamic simulations to show that rectangular and jet-like
morphologies can be explained by supernovae (SNe), either type Ia or type II,
expanding within anisotropic, bipolar stellar wind bubbles driven by the
progenitor star. The stellar wind has an anisotropic density distribution,
which channels the SN ejecta differently depending on the anisotropy
characteristics. We compute synthetic thermal (X-ray) and non-thermal
(synchrotron) emission maps from our numerical simulations to compare with
observations. We find rectangular morphologies are generated when the stellar
wind has a high mass loss rate and forms a dense, narrow disk at the equatorial
region. Instead, a jet-like or ear-like morphology is obtained when the stellar
wind develops a wide, dense disk. Stellar winds with low mass-loss rates do not
strongly influence the SNR morphology. Finally, our synthetic synchrotron and
X-ray maps for the high mass-loss rate case qualitatively agree with the
observations of the SNRs G332.5-5.6 and G290.1-0.8.


  Topological superconductors host new states of quantum matter which show a
pairing gap in the bulk and gapless surface states providing a platform to
realize Majorana fermions. Recently, alkaline-earth metal Sr intercalated
Bi2Se3 has been reported to show superconductivity with a Tc ~ 3 K and a large
shielding fraction. Here we report systematic normal state electronic structure
studies of Sr0.06Bi2Se3 (Tc ~ 2.5 K) by performing photoemission spectroscopy.
Using angle-resolved photoemission spectroscopy (ARPES), we observe a quantum
well confined two-dimensional (2D) state coexisting with a topological surface
state in Sr0.06Bi2Se3. Furthermore, our time-resolved ARPES reveals the
relaxation dynamics showing different decay mechanism between the excited
topological surface states and the two-dimensional states. Our experimental
observation is understood by considering the intra-band scattering for
topological surface states and an additional electron phonon scattering for the
2D states, which is responsible for the superconductivity. Our first-principles
calculations agree with the more effective scattering and a shorter lifetime of
the 2D states. Our results will be helpful in understanding low temperature
superconducting states of these topological materials.


  Non-congruence appears to be the most general form of phase transition in
cosmic matter and in the laboratory. In terrestrial applications
noncongruencemeans coexistence of phases with different chemical composition in
systems consisting of two (or more) chemical elements. It is just the case for
all phase transitions in high-temperature chemically reactive mixtures, which
are typical for uranium-bearing compounds in many nuclear energy devices, both
contemporary and perspective. As for cosmic matter, most of real and
hypothetical phase transitions without nuclear reactions, i.e., those in the
interiors of giant planets (solar and extrasolar), those in brown dwarfs and
other sub-stellar objects, as well as in the outer crust of compact stars, are
very plausible candidates for such type of phase transformations. Two exotic
phase transitions, the gas-liquid phase transition in dense nuclear matter and
the quark-hadron transition occuring in the interior of compact stars as well
as in high-energy heavy-ion collisions are under discussion as the most extreme
example of hypothetical non-congruence for phase transformations in High Energy
Density Matter.


  Single-source domain generalization (SDG) for object detection is a
challenging yet essential task as the distribution bias of the unseen domain
degrades the algorithm performance significantly. However, existing methods
attempt to extract domain-invariant features, neglecting that the biased data
leads the network to learn biased features that are non-causal and poorly
generalizable. To this end, we propose an Unbiased Faster R-CNN (UFR) for
generalizable feature learning. Specifically, we formulate SDG in object
detection from a causal perspective and construct a Structural Causal Model
(SCM) to analyze the data bias and feature bias in the task, which are caused
by scene confounders and object attribute confounders. Based on the SCM, we
design a Global-Local Transformation module for data augmentation, which
effectively simulates domain diversity and mitigates the data bias.
Additionally, we introduce a Causal Attention Learning module that incorporates
a designed attention invariance loss to learn image-level features that are
robust to scene confounders. Moreover, we develop a Causal Prototype Learning
module with an explicit instance constraint and an implicit prototype
constraint, which further alleviates the negative impact of object attribute
confounders. Experimental results on five scenes demonstrate the prominent
generalization ability of our method, with an improvement of 3.9% mAP on the
Night-Clear scene.


  The single-layer Mott insulator strontium iridate Sr$_2$IrO$_4$ was studied
using a scanning tunneling microscope. This measurement technique is unique due
to the transport properties of this Mott insulator allowing tunneling
measurements to be performed, even at cryogenic temperatures. We obtained
high-resolution images of the sample surface and the differential tunneling
conductance at different cryogenic temperatures. The differential conductance
is a direct measurement of the local electronic density of states which
provided an insulating gap consistent with optical conductivity, angle resolved
photoemission spectroscopy and resonant inelastic x-ray scattering (RIXS)
experiments. The observed widths of these features is broader than predicted by
the Slater approximation and narrower than predicted by dynamical mean field
theory. Additionally, the observed density of states due to magnetic
fluctuations is found in the derivative of the differential conductance and is
consistent with results from Raman scattering and RIXS. At low temperatures,
additional low-energy features were observed, suggesting a change in the
dispersion of the collective magnetic excitations, which is consistent with the
magnetic susceptibility.


  With the advent of deep learning models, face recognition systems have
achieved impressive recognition rates. The workhorses behind this success are
Convolutional Neural Networks (CNNs) and the availability of large training
datasets. However, we show that small human-imperceptible changes to face
samples can evade most prevailing face recognition systems. Even more alarming
is the fact that the same generator can be extended to other traits in the
future. In this work, we present how such a generator can be trained and also
extended to other biometric modalities, such as fingerprint recognition
systems.


  Semileptonic decays of $B$ mesons to the tau lepton, despite of experimental
difficulties, are of great importance. In particular they are sensitive probes
of models with extended Higgs sectors. The results of studies of semitauonic B
decays at Belle are presented.


  We report cumulants of the proton multiplicity distribution from dedicated
fixed-target Au+Au collisions at 3.0 GeV, measured by the STAR experiment in
the kinematic acceptance of rapidity ($y$) and transverse momentum ($p_{\rm
T}$) within $-0.5 < y<0$ and $0.4 < p_{\rm T} <2.0 $ GeV/$c$. In the most
central 0--5\% collisions, a proton cumulant ratio is measured to be
$C_4/C_2=-0.85 \pm 0.09 ~(\rm stat.) \pm 0.82 ~(\rm syst.)$, which is less than
unity, the Poisson baseline. The hadronic transport UrQMD model reproduces our
$C_4/C_2$ in the measured acceptance. Compared to higher energy results and the
transport model calculations, the suppression in $C_4/C_2$ is consistent with
fluctuations driven by baryon number conservation and indicates an energy
regime dominated by hadronic interactions. These data imply that the QCD
critical region, if created in heavy-ion collisions, could only exist at
energies higher than 3\,GeV.


  Recently, a renormalizable gravity theory with higher spatial derivatives in
four dimensions was proposed by Horava. The theory reduces to Einstein gravity
with a non-vanishing cosmological constant in IR, but it has improved UV
behaviors. The spherically symmetric black hole solutions for an arbitrary
cosmological constant, which represent the generalization of the standard
Schwarzschild-(A)dS solution, has also been obtained for the Horava-Lifshitz
theory. The exact asymptotically flat Schwarzschild type solution of the
gravitational field equations in Horava gravity contains a quadratic increasing
term, as well as the square root of a fourth order polynomial in the radial
coordinate, and it depends on one arbitrary integration constant. The IR
modified Horava gravity seems to be consistent with the current observational
data, but in order to test its viability more observational constraints are
necessary. In the present paper we consider the possibility of observationally
testing Horava gravity by using the accretion disk properties around black
holes. The energy flux, temperature distribution, the emission spectrum as well
as the energy conversion efficiency are obtained, and compared to the standard
general relativistic case. Particular signatures can appear in the
electromagnetic spectrum, thus leading to the possibility of directly testing
Horava gravity models by using astrophysical observations of the emission
spectra from accretion disks.


  We prove PSPACE-completeness of all but one problem in a large space of
pulling-block problems where the goal is for the agent to reach a target
destination. The problems are parameterized by whether pulling is optional, the
number of blocks which can be pulled simultaneously, whether there are fixed
blocks or thin walls, and whether there is gravity. We show NP-hardness for the
remaining problem, Pull?-1FG (optional pulling, strength 1, fixed blocks, with
gravity).


  We describe a novel technique for creating an artificial magnetic field for
ultra-cold atoms using a periodically pulsed pair of counter propagating Raman
lasers that drive transitions between a pair of internal atomic spin states: a
multi-frequency coupling term. In conjunction with a magnetic field gradient,
this dynamically generates a rectangular lattice with a non-staggered magnetic
flux. For a wide range of parameters, the resulting Bloch bands have
non-trivial topology, reminiscent of Landau levels, as quantified by their
Chern numbers.


  This is the second paper of the series aimed at understanding the ensemble of
instanton-dyons, now with two flavors of light dynamical quarks. The partition
function is appended by the fermionic factor, $(det T)^{N_f}$ and Dirac
eigenvalue spectra at small values are derived from the numerical simulation of
64 and 128 dyons. Those spectra show clear chiral symmetry breaking pattern at
high dyon density.


  The variation of the dark energy field is found under the assumption that the
dark energy is parametric and interacts with the cold dark matter. Considering
that the variation of the field could not exceed the Planck mass, we obtain
bounds on the coupling and adiabatic coefficients. Three parameterizations of
the adiabatic coefficients are considered and two coupling terms where the
energy flows from dark energy to dark matter, or the other way around.


  In this paper we study strong and weak bisimulation equivalences for
continuous-time Markov decision processes (CTMDPs) and the logical
characterizations of these relations with respect to the continuous-time
stochastic logic (CSL). For strong bisimulation, it is well known that it is
strictly finer than CSL equivalence. In this paper we propose strong and weak
bisimulations for CTMDPs and show that for a subclass of CTMDPs, strong and
weak bisimulations are both sound and complete with respect to the equivalences
induced by CSL and the sub-logic of CSL without next operator respectively. We
then consider a standard extension of CSL, and show that it and its sub-logic
without X can be fully characterized by strong and weak bisimulations
respectively over arbitrary CTMDPs.


  This study presents a method for constructing a sequence of approximate
solutions of increasing accuracy to general equilibrium models on nonlocal
domains. The method is based on a technique originated from dynamical systems
theory. The approximate solutions are constructed employing the Contraction
Mapping Theorem and the fact that solutions to general equilibrium models
converge to a steady state. The approach allows deriving the a priori and a
posteriori approximation errors of the solutions. Under certain nonlocal
conditions we prove the convergence of the approximate solutions to the true
solution and hence the Stable Manifold Theorem. We also show that the proposed
approach can be treated as a rigorous proof of convergence for the extended
path algorithm to the true solution in a class of nonlinear rational
expectation models.


  We consider unstable D0-branes of two dimensional string theory, described by
the boundary state of Zamolodchikov and Zamolodchikov [hep-th/0101152]
multiplied by the Neumann boundary state for the time coordinate $t$. In the
dual description in terms of the $c=1$ matrix model, this D0-brane is described
by a matrix eigenvalue on top of the upside down harmonic oscillator potential.
As suggested by McGreevy and Verlinde [hep-th/0304224], an eigenvalue rolling
down the potential describes D-brane decay. As the eigenvalue moves down the
potential to the asymptotic region it can be described as a free relativistic
fermion. Bosonizing this fermion we get a description of the state in terms of
a coherent state of the tachyon field in the asymptotic region, up to a
non-local linear field redefinition by an energy-dependent phase. This coherent
state agrees with the exponential of the closed string one-point function on a
disk with Sen's marginal boundary interaction for $t$ which describes D0-brane
decay.


  We provide a formalism to calculate the cubic interaction vertices of the
stable string bit model, in which string bits have $s$ spin degrees of freedom
but no space to move. With the vertices, we obtain a formula for one-loop
self-energy, i.e., the $\mathcal{O}\left(1/N^{2}\right)$ correction to the
energy spectrum. A rough analysis shows that, when the bit number $M$ is large,
the ground state one-loop self-energy $\Delta E_{G}$ scale as $M^{5-s/4}$ for
even $s$ and $M^{4-s/4}$ for odd $s$. Particularly, in $s=24$, we have $\Delta
E_{G}\sim 1/M$, which resembles the Poincar\'e invariant relation $P^{-}\sim
1/P^{+}$ in $(1+1)$ dimensions. We calculate analytically the one-loop
correction for the ground energies with $M=3$ and $s=1,\,2$. We then
numerically confirm that the large $M$ behavior holds for $s\leq4$ cases.


  We study the elasticity of fibrous materials composed of generalized stiff
polymers. It is shown that in contrast to cellular foam-like structures affine
strain fields are generically unstable. Instead, a subtle interplay between the
architecture of the network and the elastic properties of its building blocks
leads to intriguing mechanical properties with intermediate asymptotic scaling
regimes. We present exhaustive numerical studies based on a finite element
method complemented by scaling arguments.


  There is a long history of representing a quantum state using a
quasi-probability distribution: a distribution allowing negative values. In
this paper we extend such representations to deal with quantum channels. The
result is a convex, strongly monoidal, functorial embedding of the category of
trace preserving completely positive maps into the category of quasi-stochastic
matrices. This establishes quantum theory as a subcategory of quasi-stochastic
processes. Such an embedding is induced by a choice of minimal informationally
complete POVM's. We show that any two such embeddings are naturally isomorphic.
The embedding preserves the dagger structure of the categories if and only if
the POVM's are symmetric, giving a new use of SIC-POVM's, objects that are of
foundational interest in the QBism community. We also study general convex
embeddings of quantum theory and prove a dichotomy that such an embedding is
either trivial or faithful.


  Stereo video super-resolution (SVSR) aims to enhance the spatial resolution
of the low-resolution video by reconstructing the high-resolution video. The
key challenges in SVSR are preserving the stereo-consistency and
temporal-consistency, without which viewers may experience 3D fatigue. There
are several notable works on stereoscopic image super-resolution, but there is
little research on stereo video super-resolution. In this paper, we propose a
novel Transformer-based model for SVSR, namely Trans-SVSR. Trans-SVSR comprises
two key novel components: a spatio-temporal convolutional self-attention layer
and an optical flow-based feed-forward layer that discovers the correlation
across different video frames and aligns the features. The parallax attention
mechanism (PAM) that uses the cross-view information to consider the
significant disparities is used to fuse the stereo views. Due to the lack of a
benchmark dataset suitable for the SVSR task, we collected a new stereoscopic
video dataset, SVSR-Set, containing 71 full high-definition (HD) stereo videos
captured using a professional stereo camera. Extensive experiments on the
collected dataset, along with two other datasets, demonstrate that the
Trans-SVSR can achieve competitive performance compared to the state-of-the-art
methods. Project code and additional results are available at
https://github.com/H-deep/Trans-SVSR/


  An $r$-uniform supertree is a connected and acyclic hypergraph of which each
edge has $r$ vertices, where $r\geq 3$. We propose the concept of matching
energy for an $r$-uniform hypergraph, which is defined as the sum of the
absolute value of all the eigenvalues of its matching polynomial. With the aid
of the matching polynomial of an $r$-uniform supertree, three pairs of
$r$-uniform supertrees with the same spectral radius and the same matching
energy are constructed, and two infinite families of $r$-uniform supertrees
with the same spectral radius and the same matching energy are characterized.
Some known results about the graphs with the same spectra regarding to their
adjacency matrices can be naturally deduced from our new results.


  The non-perturbative nature of QCD at hadronic scales implied the development
of phenomenological approaches such as quark models or, more recently,
computer-based calculations using Lattice QCD. However, the unique properties
of heavy quarkonium systems allow an entire calculation in terms of
non-relativistic perturbative QCD. In this work, the bottomonium spectrum, up
to $n = 3$, and the ground state charmonium states, are analyzed in the
framework of Non-Relativistic Quantum Chromodynamics at N$^3$LO. For
bottomonium, finite charm quark mass effects in the QCD potential and the
$\overline{MS}$-pole mass relation are incorporated to the highest known order,
$\mathcal{O}(\varepsilon^3)$ in the $\Upsilon$-scheme counting. The bottom
quark pole mass is expressed in terms of the MSR mass, a low-scale
short-distance mass which cancels the $u = 1/2$ renormalon of the static
potential. We study the $n_\ell = 3$ and $n_\ell = 4$ schemes, finding a
negligible difference between the two if finite $m_c$ effects are smoothly
incorporated in the MSR mass definition. We find that bottomonium $n=3$ states
are not well behaved within perturbative NRQCD. Hence, fitting to the $n=1,2$
$b\bar b$ states we obtain $\overline{m}_b(\overline{m}_b) = 4.216\pm 0.039$
GeV. Similarly, from the lowest lying charmonium states we find
$\overline{m}_c(\overline{m}_c)=1.273 \pm 0.054$ GeV.


  Black holes as solutions to gravity theories, are generically identified by a
set of parameters. Some of these parameters are associated with black hole
physical conserved charges, like ADM charges. There can also be some "redundant
parameters." We propose necessary conditions for a parameter to be physical.
The conditions are essentially integrability and non-triviality of the charge
variations arising from "parametric variations," variation of the solution with
respect to the chosen parameters. In addition, we prove that variation of the
redundant parameters which do not meet our criteria do not appear in the first
law of thermodynamics. As an interesting application, we show that dilaton
moduli are redundant parameters for black hole solutions to
Einstein-Maxwell-(Axion)-Dilaton theories, because variations in dilaton moduli
would render entropy, mass, electric charges or angular momenta non-integrable.
Our results are in contrast with modification of the first law due to scalar
charges suggested in Gibbons-Kallosh-Kol paper arXiv:hep-th/9607108 and its
follow-ups. We also briefly discuss implications of our results for the
attractor behavior of extremal black holes.


  In this paper, the dataset used for the data challenge organised by
Conference on Sound and Music Technology (CSMT) is introduced. The CSMT data
challenge requires participants to identify whether a given piece of melody is
generated by computer or is composed by human. The dataset is formed by two
parts: development dataset and evaluation dataset. The development dataset
contains only computer generated melodies whereas the evaluation dataset
contain both computer generated melodies and human composed melodies. The aim
of the dataset is to examine whether it is possible to distinguish computer
generated melodies by learning the feature of generated melodies.


  We explore the electromagnetic gauge invariance of the hadron tensor of the
Drell-Yan process with one transversely polarized hadron. The special role is
played by the contour gauge for gluon fields. The prescription for the gluonic
pole in the twist 3 correlator is related to causality property and compared
with the prescriptions for exclusive hard processes. As a result of we get the
extra contributions, which naively do not have an imaginary phase. The single
spin asymmetry for the Drell-Yan process is enhanced by the factor of two.


  In an attempt to gather a deeper understanding of how convolutional neural
networks (CNNs) reason about human-understandable concepts, we present a method
to infer labeled concept data from hidden layer activations and interpret the
concepts through a shallow decision tree. The decision tree can provide
information about which concepts a model deems important, as well as provide an
understanding of how the concepts interact with each other. Experiments
demonstrate that the extracted decision tree is capable of accurately
representing the original CNN's classifications at low tree depths, thus
encouraging human-in-the-loop understanding of discriminative concepts.


  We offer an example of the second order Kawaguchi metric function the
extremal flow of which generalizes the flat space-time model of the
semi-classical spinning particle to the framework of the pseudo-Riemannian
space-time. The general shape of the variational Euler-Poisson equation of the
fourth order in the (pseudo-)Riemannian space is being developed too.


  We present a proof based on SEIR-models that shows it is impossible to
identify the level of under reporting based on traditional observables of the
disease dynamics alone. This means that the true attack rate must be determined
through other means.


  Suppose that $R$ is a ring essentially of finite type over a perfect field of
characteristic $p > 0$ and that $a \subseteq R$ is an ideal. We prove that the
set of $F$-jumping numbers of $\tau_b(R; a^t)$ has no limit points under the
assumption that $R$ is normal and $Q$-Gorenstein -- we do \emph{not} assume
that the $Q$-Gorenstein index is not divisible by $p$. Furthermore, we also
show that the $F$-jumping numbers of $\tau_b(R; \Delta, a^t)$ are discrete
under the more general assumption that $K_R + \Delta$ is $\bR$-Cartier.


  A spatio-temporal version of the well-known Omori-Utsu law of aftershock
sequences is proposed. This 'diffusive Omori-Utsu law' satisfies a nonlinear
partial differential equation (PDE). A similarity reduction is obtained that
reduces the PDE to an ordinary differential equation (ODE). A nonzero constant
solution of this ODE leads to the usual Omori-Utsu law. An exact and explicit
similarity solution is found that corresponds to the original Omori law. An
initial value problem for the 'diffusive Omori-Utsu law' is also considered,
and whose spatio-temporal dynamics are described by bounding functions that
satisfy nonlinear, but linearisable, PDEs. Numerical results are also provided.


  Individual differences in personality determine our preferences, traits and
values, which should similarly hold for the way we express ourselves. With
current advancements and transformations of technology and society, text-based
communication has become ordinary and often even surpasses natural voice
conversations -- with distinct challenges and opportunities. In this
exploratory work, we investigate the impact of personality on the tendency how
players of a team-based collaborative alternate reality game express themselves
affectively. We collected chat logs from eleven players over two weeks, labeled
them according to their affective state, and assessed the connection between
them and the five-factor personality domains and facets. After applying
multi-linear regression, we found a series of reasonable correlations between
(combinations of) personality variables and expressed affect -- as increased
confusion could be predicted by lower self-competence (C1), personal annoyance
by vulnerability to stress (N6) and expressing anger occured more often in
players that are prone to anxiety (N1), less humble and modest (A5), think less
carefully before they act (C6) and have higher neuroticism (N). Expanding the
data set, sample size and input modalities in subsequent work, we aim to
confirm these findings and reveal even more interesting connections that could
inform affective computing and games user research equally.


  We introduce BayesSim, a framework for robotics simulations allowing a full
Bayesian treatment for the parameters of the simulator. As simulators become
more sophisticated and able to represent the dynamics more accurately,
fundamental problems in robotics such as motion planning and perception can be
solved in simulation and solutions transferred to the physical robot. However,
even the most complex simulator might still not be able to represent reality in
all its details either due to inaccurate parametrization or simplistic
assumptions in the dynamic models. BayesSim provides a principled framework to
reason about the uncertainty of simulation parameters. Given a black box
simulator (or generative model) that outputs trajectories of state and action
pairs from unknown simulation parameters, followed by trajectories obtained
with a physical robot, we develop a likelihood-free inference method that
computes the posterior distribution of simulation parameters. This posterior
can then be used in problems where Sim2Real is critical, for example in policy
search. We compare the performance of BayesSim in obtaining accurate posteriors
in a number of classical control and robotics problems. Results show that the
posterior computed from BayesSim can be used for domain randomization
outperforming alternative methods that randomize based on uniform priors.


  If the vector glueball exists in the mass range that theory suggests, its
resonance production cross section can be seen in e+e- annihilation only if the
decay width is very narrow (< a few MeV). Otherwise it willbe observed only
indirectly through its mixing with psi(2S). A few tests of the glueball-psi'
mixing are proposed for future charm factories.


  Evolution of magnetization behaviour of cobalt film on nano patterned silicon
substrate, with film thickness, has been studied. In situ magneto-optical Kerr
effect measurements during film deposition allowed us to study genuine
thickness dependence of magnetization behaviour, all other parameters like
surface topology, deposition conditions remaining invariant. The film exhibits
uniaxial magnetic anisotropy, with its magnitude decreasing with increasing
film thickness. Analysis shows that anisotropy has contributions from both, i)
exchange energy which is volume dependent and, ii) stray dipolar fields at the
surface/interface. This suggests that local magnetization follows only
partially the topology of the rippled surface. As expected from energy
considerations, for small film thickness, the local magnetization closely
follows the surface contour of the ripples making the volume term as the
dominant contribution. With increasing film thickness, the local magnetization
gradually deviates from the local slope and approaches towards a uniform
magnetization along the macroscopic film plane making the surface term as the
dominant contribution. Significant deviation from the anisotropy energy
expected on the basis of theoretical considerations can be attributed to
several factors like, deviation of surface topology from an ideal sinusoidal
wave, breaks of continuity along the ripple direction, defects like pattern
dislocations, and possible decrease in surface modulation depth with increasing
film thickness.


  The kinematics of 150 carbon stars observed at moderate dispersion on the
periphery of the Small Magellanic Cloud are compared with the motions of
neutral hydrogen and early type stars in the Inter-Cloud region. The
distribution of radial velocities implies a configuration of these stars as a
sheet inclined at 73+/-4 degrees to the plane of the sky. The near side, to the
South, is dominated by a stellar component; to the North, the far side contains
fewer carbon stars, and is dominated by the neutral gas. The upper velocity
envelope of the stars is closely the same as that of the gas. This
configuration is shown to be consistent with the known extension of the SMC
along the line of sight, and is attributed to a tidally induced disruption of
the SMC that originated in a close encounter with the LMC some 0.3 to 0.4 Gyr
ago. The dearth of gas on the near side of the sheet is attributed to ablation
processes akin to those inferred by Weiner & Williams (1996) to collisional
excitation of the leading edges of Magellanic Stream clouds. Comparison with
pre LMC/SMC encounter kinematic data of Hardy, Suntzeff, & Azzopardi (1989) of
carbon stars, with data of stars formed after the encounter, of Maurice et al.
(1989), and Mathewson et al. (a986, 1988) leaves little doubt that forces other
than gravity play a role in the dynamics of the H I.


  Recent research demonstrates the effectiveness of using fine-tuned language
models~(LM) for dense retrieval. However, dense retrievers are hard to train,
typically requiring heavily engineered fine-tuning pipelines to realize their
full potential. In this paper, we identify and address two underlying problems
of dense retrievers: i)~fragility to training data noise and ii)~requiring
large batches to robustly learn the embedding space. We use the recently
proposed Condenser pre-training architecture, which learns to condense
information into the dense vector through LM pre-training. On top of it, we
propose coCondenser, which adds an unsupervised corpus-level contrastive loss
to warm up the passage embedding space. Retrieval experiments on MS-MARCO,
Natural Question, and Trivia QA datasets show that coCondenser removes the need
for heavy data engineering such as augmentation, synthesis, or filtering, as
well as the need for large batch training. It shows comparable performance to
RocketQA, a state-of-the-art, heavily engineered system, using simple small
batch fine-tuning.