  Using Scanning tunneling spectroscopy (STS), we report the correlation
between spatial gap inhomogeneity and the zinc (Zn) impurity resonance in
single crystals of
Bi$_{\mathrm{2}}$Sr$_{\mathrm{2}}$Ca(Cu$_{\mathrm{1-}x}$Zn$_{x}$)$_{\mathrm{2}}$O$_{\mathrm{8+}\delta}$
with different carrier (hole) concentrations ($p$) at a fixed Zn concentration
($x$ $\sim$ 0.5 % per Cu atom). In all the samples, the impurity resonance lies
only in the region where the gap value is less than $\sim$ 60 meV. Also the
number of Zn resonance sites drastically decreases with decreasing $p$, in
spite of the fixed $x$. These experimental results lead us to a conclusion that
the Zn impurity resonance does not appear in the large gap region although the
Zn impurity evidently resides in this region.


  Interconnected systems are an important class of mathematical models, as they
allow for the construction of complex, hierarchical, multiphysics, and
multiscale models by the interconnection of simpler subsystems. Lagrange--Dirac
mechanical systems provide a broad category of mathematical models that are
closed under interconnection, and in this paper, we develop a framework for the
interconnection of discrete Lagrange--Dirac mechanical systems, with a view
towards constructing geometric structure-preserving discretizations of
interconnected systems. This work builds on previous work on the
interconnection of continuous Lagrange--Dirac systems (Jacobs and Yoshimura
2014) and discrete Dirac variational integrators (Leok and Ohsawa 2011). We
test our results by simulating some of the continuous examples given in Jacobs
and Yoshimura 2014.


  FS Aur is famous for a variety of uncommon and puzzling periodic photometric
and spectroscopic variabilities. It was previously proposed that the precession
of a fast-rotating magnetically accreting white dwarf can successfully explain
these phenomena. We present a study of FS Aur based on two extensive sets of
optical photometric observations and three X-ray data sets in which we intended
to verify whether the observational properties of the long period modulations
observed in FS Aur and V455 And are similar in appearance to the spin
modulation in ordinary IPs. These new optical observations have revealed, for
the first time in photometric data, the variability with the presumed
precession period of the white dwarf, previously seen only spectroscopically.
We also found that the modulations with the precession and orbital periods are
evident in X-ray data. We show that the observed properties of FS Aur closely
resemble those of other intermediate polars, thus confirming this cataclysmic
variable as a member of the class.
  Our analysis of multicolour observations of intermediate polars has shown
that time-series analysis of colour indices appears to be a powerful technique
for revealing hidden variabilities and shedding light on their nature. We have
found that the (B-I) power spectrum of V1223 Sgr indicates the presence in the
data of the spin pulsation which is not seen in the optical light curve at all.
Also, the analysis of the colour indices of V455 And revealed the presence of
the photometric variations which, similarly to FS Aur, was previously observed
only spectroscopically.


  We first find a sufficient condition for a product of theta constants to be a
Siegel modular function of a given even level. And, when $K_{(2p)}$ denotes the
ray class field of $K=\mathbb{Q}(e^{2\pi i/5})$ modulo $2p$ for an odd prime
$p$, we describe a subfield of $K_{(2p)}$ generated by the special value of
certain theta constant by using Shimura's reciprocity law.


  The role of diffuse photospheric magnetic elements in the energy budget of
the upper layers of the Sun's atmosphere has been the recent subject of many
studies. This was made possible by the availability of high temporal and
spatial resolution observations of the solar photosphere, allowing large
numbers of magnetic elements to be tracked to study their dynamics. In this
work we exploit a long temporal series of seeing-free magnetograms of the solar
photosphere to study the effect of the turbulent convection in the excitation
of kink oscillations in magnetic elements. We make use of the empirical mode
decomposition technique (EMD) in order to study the transverse oscillations of
several magnetic flux tubes. This technique permits the analysis of
non-stationary time series like those associated to the horizontal velocities
of these flux tubes which are continuously advected and dispersed by granular
flows.
  Our primary findings reveal the excitation of low frequency modes of kink
oscillations, which are sub-harmonics of a fundamental mode with a $7.6 \pm
0.2$ minute periodicity. These results constitute a strong case for
observational proof of the excitation of kink waves by the buffeting of the
convection cells in the solar photosphere, and are discussed in light of their
possible role in the energy budget of the upper Sun's atmosphere.


  We present a calculation of the electromagnetic form factors of the $\rho^+$
meson. Our formalism is based on the point-form of relativistic quantum
mechanics. Electron-$\rho$-meson scattering is formulated as a coupled-channel
problem for a Bakamjian-Thomas mass operator, such that the dynamics of the
exchanged photon is taken explicitly into account. The $\rho$-meson current is
extracted from on-shell matrix elements of the optical potential of the
scattering process. As a consequence of the violation of cluster separability
in the Bakamjian-Thomas framework, our current includes additional, unphysical
contributions, which can be separated from the physical ones uniquely. Our
results for the form factors are in good agreement with other approaches.


  Detecting emotions directly from a speech signal plays an important role in
effective human-computer interactions. Existing speech emotion recognition
models require massive computational and storage resources, making them hard to
implement concurrently with other machine-interactive tasks in embedded
systems. In this paper, we propose an efficient and lightweight fully
convolutional neural network for speech emotion recognition in systems with
limited hardware resources. In the proposed FCNN model, various feature maps
are extracted via three parallel paths with different filter sizes. This helps
deep convolution blocks to extract high-level features, while ensuring
sufficient separability. The extracted features are used to classify the
emotion of the input speech segment. While our model has a smaller size than
that of the state-of-the-art models, it achieves higher performance on the
IEMOCAP and EMO-DB datasets.


  Shape is an important feature of physical systems although very seldom it is
addressed in the framework of a quantitative description approach. In this
paper we propose to interpret the shape of things as a physical manifestation
of the content of information associated with each thing and show that a change
of shape in a physical system is necessarily connected with a change of its
entropy and thus involves energy. We estimate the amount of energy dissipated
during a shape change and propose experimental tests to be performed in
nanoscale systems, to verify this prediction by measuring the expected
dissipation in few simple cases.


  We systematically establish the hyper-surface within the tan(beta), top quark
mass m_t, universal gaugino mass M_1/2, and vectorlike mass M_V parameter
volume which is compatible with the application of the No-Scale Supergravity
boundary conditions, particularly the vanishing of the Higgs bilinear soft term
B_mu, near to the Planck mass at the point M_F of ultimate F-lipped SU(5)
unification. M_F is elevated from the penultimate partial unification near the
traditional GUT scale at a mass M_32 by the inclusion of extra F-theory derived
heavy vectorlike multiplets. We demonstrate that simultaneous adherence to all
current experimental constraints, most importantly contributions to the muon
anomalous magnetic moment (g-2)_mu, the branching ratio limit on (b \to s
gamma), and the 7-year WMAP relic density measurement, dramatically reduces the
allowed solutions to a highly non-trivial "golden strip" with tan(beta) \sim
15, m_t = 173.0-174.4 GeV, M_1/2 = 455-481 GeV, and M_V = 691-1020 GeV,
effectively eliminating all extraneously tunable model parameters. We emphasize
that the consonance of the theoretically viable m_t range with the
experimentally established value is an independently correlated "postdiction".
The predicted range of M_V is testable at the Large Hadron Collider (LHC). The
partial lifetime for proton decay in the leading (e+|mu+) pi0 channels falls
around 4.6 X 10^34 Y, testable at the future DUSEL and Hyper-Kamiokande
facilities.


  We study the damping rate of massless Dirac fermions due to the U(1) gauge
field in (2+1)-dimensional quantum electrodynamics. In the absence of a Maxwell
term for the gauge field, the fermion damping rate
$\mathrm{Im}\Sigma(\omega,T)$ is found to diverge in both perturbative and
self-consistent results. In the presence of a Maxwell term, there is still
divergence in the perturbative results for $\mathrm{Im}\Sigma(\omega,T)$. Once
the Maxwell term is included into the self-consistent equations for fermion
self-energy and vacuum polarization functions, the fermion damping rate is free
of divergence and exhibits non-Fermi liquid behavior:
$\mathrm{Im}\Sigma(\omega,T) \propto \mathrm{max}(\sqrt{\omega},\sqrt{T})$.


  We develop a systematic approach to the calculation of scattering cross
sections in theories with violation of the Lorentz invariance taking into
account the whole information about the theory Lagrangian. As an illustration
we derive the Feynman rules and formulas for sums over polarizations in spinor
electrodynamics with Lorentz violating operators of dimensions four and six.
These rules are applied to compute the probabilities of several astrophysically
relevant processes. We calculate the rates of photon decay and vacuum Cherenkov
radiation along with the cross sections of electron-positron pair production on
background radiation and in the Coulomb field. The latter process is essential
for detection of photon-induced air showers in the atmosphere.


  We explore whether the generalized second law of thermodynamics is fulfilled
in the transition from a generic initial Einstein static phase to the
inflationary phase, with constant Hubble rate, and from the end of the latter
to the conventional thermal radiation dominated era of expansion. As it turns
out, the said law is satisfied provided the radiation component does not
contribute largely to the total energy of the static phase.


  I propose an alternative $f(R)$ theory of gravity constructed by applying the
function $f$ directly to the Ricci tensor instead of the Ricci scalar. The main
goal of this study is to derive the resulting modified Einstein equations for
the metric case with Levi-Civita connection, as well as for the general
nonmetric connection with torsion. The modification is then applied to the
Robertson-Walker metric so that the cosmological evolution corresponding to the
standard model can be studied. An appealing feature is that even in the vacuum
case, scenarios without initial singularity and exponential expansion can be
recovered. Finally, formulae for possible observational tests are given.


  This paper introduces the Fusemate probabilistic logic programming system.
Fusemate's inference engine comprises a grounding component and a variable
elimination method for probabilistic inference. Fusemate differs from most
other systems by grounding the program in a bottom-up way instead of the common
top-down way. While bottom-up grounding is attractive for a number of reasons,
e.g., for dynamically creating distributions of varying support sizes, it makes
it harder to control the amount of ground clauses generated. We address this
problem by interleaving grounding with a query-guided relevance test which
prunes rules whose bodies are inconsistent with the query. % This is done We
present our method in detail and demonstrate it with examples that involve
"time", such as (hidden) Markov models. Our experiments demonstrate competitive
or better performance compared to a state-of-the art probabilistic logic
programming system, in particular for high branching problems.


  Inferring a decision maker's utility function typically involves an
elicitation phase where the decision maker responds to a series of elicitation
queries, followed by an estimation phase where the state-of-the-art is to
either fit the response data to a parametric form (such as the exponential or
power function) or perform linear interpolation. We introduce a Bayesian
nonparametric method involving Gaussian stochastic processes for estimating a
utility function. Advantages include the flexibility to fit a large class of
functions, favorable theoretical properties, and a fully probabilistic view of
the decision maker's preference properties including risk attitude. Using
extensive simulation experiments as well as two real datasets from the
literature, we demonstrate that the proposed approach yields estimates with
lower mean squared errors. While our focus is primarily on single-attribute
utility functions, one of the real datasets involves three attributes; the
results indicate that nonparametric methods also seem promising for
multi-attribute utility function estimation.


  Using superspace projection operators we provide a classification of (3/2,2)
off-shell supermultiplets which are realized in terms of a real axial vector
superfield, with or without compensating superfields. Any linearized
supergravity action is shown to be a superposition of those corresponding to
(i) old minimal supergravity, (ii) new minimal supergravity and (iii) the novel
(3/2,2) off-shell supermultiplet with 12+12 degrees of freedom obtained in
hep-th/0201096.


  Due a mistake in identifying the operators $O_9$ and $O_{10}$ which leads to
errorous expressions in eq. 9. With the correct expressions (exchange c_9 and
c_{10} in eq. 9), the analysis followed are invalide.


  We present the detection of 661 known pulsars observed with the Australian
SKA Pathfinder (ASKAP) telescope at 888 MHz as a part of the Rapid ASKAP
Continuum Survey (RACS). Detections were made through astrometric coincidence
and we estimate the false alarm rate of our sample to be ~0.5%. Using archival
data at 400 and 1400 MHz, we estimate the power law spectral indices for the
pulsars in our sample and find that the mean spectral index is -1.78 +/- 0.6.
However, we also find that a single power law is inadequate to model all the
observed spectra. With the addition of the flux densities between 150 MHz and 3
GHz from various imaging surveys, we find that up to 40% of our sample shows
deviations from a simple power law model. Using Stokes V measurements from the
RACS data, we measured the circular polarization fraction for 9% of our sample
and find that the mean polarization fraction is ~10% (consistent between
detections and upper limits). Using the dispersion measure (DM) derived
distance we estimate the pseudo luminosity of the pulsars and do not find any
strong evidence for a correlation with the pulsars' intrinsic properties.


  Sparsity has been recently introduced in cosmology for weak-lensing and CMB
data analysis for different applications such as denoising, component
separation or inpainting (i.e. filling the missing data or the mask). Although
it gives very nice numerical results, CMB sparse inpainting has been severely
criticized by top researchers in cosmology, based on arguments derived from a
Bayesian perspective. Trying to understand their point of view, we realize that
interpreting a regularization penalty term as a prior in a Bayesian framework
can lead to erroneous conclusions. This paper is by no means against the
Bayesian approach, which has proven to be very useful for many applications,
but warns about a Bayesian-only interpretation in data analysis, which can be
misleading in some cases.


  In the previous work, a new kind of inflation model was proposed, which has
the interesting property that its perturbation equation of motion gets a
correction of k^4, due to the non-linearity of the kinetic term. Nonetheless,
the scale-invariance of the power spectrum remains valid, both in large-k and
small-k limits. In this paper, we investigate in detail the spectral index, the
index running and the tensor/scalar ratio in this model, especially on the
potential-driven case, and compare the results to the current PLANCK/BICEP
observational data. We also discuss the tensor spectrum in this case, which is
expected to be tested by the future observations on primordial gravitational
waves.


  Vision Language Models (VLMs) are rapidly advancing in their capability to
answer information-seeking questions. As these models are widely deployed in
consumer applications, they could lead to new privacy risks due to emergent
abilities to identify people in photos, geolocate images, etc. As we
demonstrate, somewhat surprisingly, current open-source and proprietary VLMs
are very capable image geolocators, making widespread geolocation with VLMs an
immediate privacy risk, rather than merely a theoretical future concern. As a
first step to address this challenge, we develop a new benchmark, GPTGeoChat,
to test the ability of VLMs to moderate geolocation dialogues with users. We
collect a set of 1,000 image geolocation conversations between in-house
annotators and GPT-4v, which are annotated with the granularity of location
information revealed at each turn. Using this new dataset, we evaluate the
ability of various VLMs to moderate GPT-4v geolocation conversations by
determining when too much location information has been revealed. We find that
custom fine-tuned models perform on par with prompted API-based models when
identifying leaked location information at the country or city level; however,
fine-tuning on supervised data appears to be needed to accurately moderate
finer granularities, such as the name of a restaurant or building.


  A possible extension of the Standard Model to include lepton number as local
gauge symmetry is investigated. In such a model, anomalies are canceled by two
extra fermions doublet. After leptonic gauge symmetry spontaneously broken,
three active neutrinos may acquire non-zero Majorana masses through the
modified Type-II seesaw mechanism. Constraints on the model from electro-weak
precision measurements are studied. Due to the $Z_2$ discrete flavor symmetry,
right-handed Majorana neutrinos can serve as cold dark matter candidate of the
Universe. Constraint from dark matter relic abundance is calculated.


  We report on the variability of rotation periods of solar coronal layers with
respect to temperature (or, height). For this purpose, we have used the
observations from Atmospheric Imaging Assembly (AIA) telescope on board Solar
Dynamics Observatory (SDO) space mission. The images used are at the
wavelengths 94 {\AA}, 131 {\AA}, 171 {\AA}, 193 {\AA}, 211 {\AA}, and 335 {\AA}
for the period from 2012 to 2018. Analysis of solar full disk images obtained
at these wavelengths by AIA is carried out using flux modulation method.
Seventeen rectangular strips/bins at equal interval of 10 degrees (extending
from 80 degree South to 80 degree North on the Sun) are selected to extract a
time series of extreme ultraviolet (EUV) intensity variations to obtain
auto-correlation coefficient. The peak of Gaussian fit to first secondary
maxima in the autocorrelogram gives synodic rotation period. Our analysis shows
the differential rotation with respect to latitude as well as temperature (or,
height). In the present study, we find that the sidereal rotation periods of
different coronal layers decrease with increasing temperature (or, height).
Average sidereal rotation period at the lowest temperature (~ 600000 Kelvin)
corresponding to AIA-171 {\AA} which originates from the upper transition
region/quiet corona is 27.03 days. The sidereal rotation period decreases with
temperature (or, height) to 25.47 days at the higher temperature (~10 million
Kelvin) corresponding to the flaring regions of solar corona as seen in AIA-131
{\AA} observations.


  Bigraded Toda hierarchy $L_1^M(n)=L_2^N(n)$ is generalized to
$L_1^M(n)=L_2^{N}(n)+\sum_{j\in \mathbb
Z}\sum_{i=1}^{m}q^{(i)}_n\Lambda^jr^{(i)}_{n+1}$, which is the analogue of the
famous constrained KP hierarchy $L^{k}=
(L^{k})_{\geq0}+\sum_{i=1}^{m}q_{i}\partial^{-1}r_i$. It is known that
different bosonizations of fermionic KP hierarchy will give rise to different
kinds of integrable hierarchies. Starting from the fermionic form of
constrained KP hierarchy, bilinear equation of this generalized bigraded Toda
hierarchy (GBTH) are derived by using 2--component boson--fermion
correspondence. Next based upon this, the Lax structure of GBTH is obtained.
Conversely, we also derive bilinear equation of GBTH from the corresponding Lax
structure.


  We study nuclear high-spin states undergoing the transition to the fully
stretched configuration with maximum angular momentum I_max within the space of
valence nucleons. To this end, we perform a systematic theoretical analysis of
non-fully-stretched I_max-2 and I_max-1 f_{7/2}^n seniority isomers and
d_{3/2}^{-1} f_{7/2}^{n+1} intruder states in the A~44 nuclei from the lower-fp
shell. We employ two theoretical approaches: (i) the density functional theory
based on the cranked self-consistent Skyrme-Hartree-Fock method, and (ii) the
nuclear shell model in the full sdfp configuration space allowing for 1p-1h
cross-shell excitations. We emphasize the importance of restoration of broken
angular momentum symmetry inherently obscuring the mean-field treatment of
high-spin states. Overall good agreement with experimental data is obtained.


  The questions of dense definiteness and boundedness of composition operators
in $L^2$-spaces are studied by means of inductive limits of operators. Methods
based on projective systems of measure spaces and inductive limits of
$L^2$-spaces are developed. Illustrative examples are presented.


  Deep neural networks (DNNs) have shown to provide superb performance in many
real life applications, but their large computation cost and storage
requirement have prevented them from being deployed to many edge and
internet-of-things (IoT) devices. Sparse deep neural networks, whose majority
weight parameters are zeros, can substantially reduce the computation
complexity and memory consumption of the models. In real-use scenarios, devices
may suffer from large fluctuations of the available computation and memory
resources under different environment, and the quality of service (QoS) is
difficult to maintain due to the long tail inferences with large latency.
Facing the real-life challenges, we propose to train a sparse model that
supports multiple sparse levels. That is, a hierarchical structure of weights
are satisfied such that the locations and the values of the non-zero parameters
of the more-sparse sub-model area subset of the less-sparse sub-model. In this
way, one can dynamically select the appropriate sparsity level during
inference, while the storage cost is capped by the least sparse sub-model. We
have verified our methodologies on a variety of DNN models and tasks, including
the ResNet-50, PointNet++, GNMT, and graph attention networks. We obtain sparse
sub-models with an average of 13.38% weights and 14.97% FLOPs, while the
accuracies are as good as their dense counterparts. More-sparse sub-models with
5.38% weights and 4.47% of FLOPs, which are subsets of the less-sparse ones,
can be obtained with only 3.25% relative accuracy loss.


  Many science and engineering applications feature non-convex optimization
problems where the objective function can not be handled analytically, i.e. it
is a black box. Examples include design optimization via experiments, or via
costly finite elements simulations. To solve these problems, global
optimization routines are used. These iterative techniques must trade-off
exploitation close to the current best point with exploration of unseen regions
of the search space. In this respect, a new global optimization strategy based
on a Set Membership (SM) framework is proposed. Assuming Lipschitz continuity
of the cost function, the approach employs SM concepts to decide whether to
switch from an exploitation mode to an exploration one, and vice-versa. The
resulting algorithm, named SMGO (Set Membership Global Optimization) is
presented. Theoretical properties regarding convergence and computational
complexity are derived, and implementation aspects are discussed. Finally, the
SMGO performance is evaluated on a set of benchmark non-convex problems and
compared with those of other global optimization approaches.


  We prove that, up to isomorphism and anti-isomorphism, there are only two
semigroups which are the union of two copies of the free monogenic semigroup.
Similarly, there are only nine semigroups which are the union of three copies
of the free monogenic semigroup. We provide finite presentations for each of
these semigroups.


  In this work, an experimental investigation of an accordion-like system with
embedded magnetic inclusion is carried out. It is shown that the way that this
structure deforms when subjected to an external magnetic field depends on the
magnetic moment of the embedded magnets and the length of the arms. Stacking of
the accordion-like system leads to the formation of hexagonal honeycombs that
can have a negative, zero, and positive Poisson's ratio. Variation in the
configuration attained depends on the relative positioning of the magnetic
inclusion and the applied magnetic field. In particular, one of the hexagonal
honeycomb arrangements was able to switch between a conventional and a
re-entrant configuration upon the reversal of the external magnetic field. For
all structures considered, the dimensions can be controlled through the
external magnetic field allowing for a high degree of turnability. Furthermore,
their behaviour can be altered in real time. The practical implications of the
results are of interest since they indicate that these structures can be
adopted in numerous applications, such in the design of scaffoldings for
deployable structures, actuators, variable pored sieves, and sound proofing
systems.


  We report on current-voltage measurements of the zero-field
normal-superconducting phase transition in thin films of
Pr$_{2-x}$Ce$_x$CuO$_{4-y}$ as a function of doping. We find that the small
size of the critical regime in these materials ($\approx 25$ mK) gives rise to
mean-field behavior at the phase transition with a static exponent of $\nu
\approx 0.5$ for all dopings (in contrast to hole-doped
$\mathrm{YBa_{2}Cu_{3}O_{7-\delta}}$). We also find mean-field behavior in the
dynamic exponent $z$. This indicates that Pr$_{2-x}$Ce$_x$CuO$_{4-y}$ behaves
similarly to conventional superconductors in contrast to other cuprate
superconductors. However, as the transition width in our samples decreases, the
dynamic critical exponent approaches $z=1.5$, similar to the critical exponent
found in hole-doped $\mathrm{YBa_{2}Cu_{3}O_{7-\delta}}$.


  This paper presents a novel frequency-responsive control scheme for
demand-side resources, such as electric water heaters. A frequency-dependent
control law is designed to provide damping from distributed energy resources
(DERs) in a fully decentralized fashion. This local control policy represents a
frequency-dependent threshold for each DER that ensures that the aggregate
response provides damping during frequency deviations. The proposed
decentralized policy is based on an adaptation of a packet-based DER
coordination scheme where each device send requests for energy access (also
called an "energy packet") to an aggregator. The number of previously accepted
active packets can then be used a-priori to form an online estimate of the
aggregate damping capability of the DER fleet in a dynamic power system. A
simple two-area power system is used to illustrate and validate performance of
the decentralized control policy and the accuracy of the online damping
estimating for a fleet of 400,000 DERs.


  Training deep generative models usually requires a large amount of data. To
alleviate the data collection cost, the task of zero-shot GAN adaptation aims
to reuse well-trained generators to synthesize images of an unseen target
domain without any further training samples. Due to the data absence, the
textual description of the target domain and the vision-language models, e.g.,
CLIP, are utilized to effectively guide the generator. However, with only a
single representative text feature instead of real images, the synthesized
images gradually lose diversity as the model is optimized, which is also known
as mode collapse. To tackle the problem, we propose a novel method to find
semantic variations of the target text in the CLIP space. Specifically, we
explore diverse semantic variations based on the informative text feature of
the target domain while regularizing the uncontrolled deviation of the semantic
information. With the obtained variations, we design a novel directional moment
loss that matches the first and second moments of image and text direction
distributions. Moreover, we introduce elastic weight consolidation and a
relation consistency loss to effectively preserve valuable content information
from the source domain, e.g., appearances. Through extensive experiments, we
demonstrate the efficacy of the proposed methods in ensuring sample diversity
in various scenarios of zero-shot GAN adaptation. We also conduct ablation
studies to validate the effect of each proposed component. Notably, our model
achieves a new state-of-the-art on zero-shot GAN adaptation in terms of both
diversity and quality.


  We present the host galaxies of four apparently non-repeating fast radio
bursts (FRBs), FRBs 20181223C, 20190418A, 20191220A, and 20190425A, reported in
the first Canadian Hydrogen Intensity Mapping Experiment (CHIME/FRB) catalog.
Our selection of these FRBs is based on a planned hypothesis testing framework
where we search all CHIME/FRB Catalog-1 events that have low extragalactic
dispersion measure (< 100 pc cm$^{-3}$), with high Galactic latitude (|b| >
10$\deg$) and saved baseband data. We associate the selected FRBs to galaxies
with moderate to high star-formation rates located at redshifts between 0.027
and 0.071. We also search for possible multi-messenger counterparts, including
persistent compact radio and gravitational wave (GW) sources, and find none.
Utilizing the four FRB hosts from this study along with the hosts of 14
published local Universe FRBs (z < 0.1) with robust host association, we
conduct an FRB host demographics analysis. We find all 18 local Universe FRB
hosts in our sample to be spirals (or late-type galaxies), including the host
of FRB 20220509G, which was previously reported to be elliptical. Using this
observation, we scrutinize proposed FRB source formation channels and argue
that core-collapse supernovae are likely the dominant channel to form FRB
progenitors. Moreover, we infer no significant difference in the host
properties of repeating and apparently non-repeating FRBs in our local Universe
FRB host sample. Finally, we find the burst rates of these four apparently
non-repeating FRBs to be consistent with those of the sample of localized
repeating FRBs observed by CHIME/FRB. Therefore, we encourage further
monitoring of these FRBs with more sensitive radio telescopes.


  For a particle that is constrained on an ($N-1$)-dimensional ($N\geq2$)
curved surface, the Cartesian components of its momentum in $N$-dimensional
flat space is believed to offer a proper form of momentum for the particle on
the surface, which is called the geometric momentum as it depends on the mean
curvature. Once the momentum is made general covariance, the spin connection
part can be interpreted as a gauge potential. The present study consists in two
parts, the first is a discussion of the general framework for the general
covariant geometric momentum. The second is devoted to a study of a Dirac
fermion on a two-dimensional sphere and we show that there is the generalized
total angular momentum whose three cartesian components form the $su(2)$
algebra, obtained before by consideration of dynamics of the particle, and we
demonstrate that there is no curvature-induced geometric potential for the
fermion.


  Uncertainty quantification in automated image analysis is highly desired in
many applications. Typically, machine learning models in classification or
segmentation are only developed to provide binary answers; however, quantifying
the uncertainty of the models can play a critical role for example in active
learning or machine human interaction. Uncertainty quantification is especially
difficult when using deep learning-based models, which are the state-of-the-art
in many imaging applications. The current uncertainty quantification approaches
do not scale well in high-dimensional real-world problems. Scalable solutions
often rely on classical techniques, such as dropout, during inference or
training ensembles of identical models with different random seeds to obtain a
posterior distribution. In this paper, we show that these approaches fail to
approximate the classification probability. On the contrary, we propose a
scalable and intuitive framework to calibrate ensembles of deep learning models
to produce uncertainty quantification measurements that approximate the
classification probability. On unseen test data, we demonstrate improved
calibration, sensitivity (in two out of three cases) and precision when being
compared with the standard approaches. We further motivate the usage of our
method in active learning, creating pseudo-labels to learn from unlabeled
images and human-machine collaboration.


  We investigate the infrared (IR) properties of cool, evolved stars in the
Small Magellanic Cloud (SMC), including the red giant branch (RGB) stars and
the dust-producing red supergiant (RSG) and asymptotic giant branch (AGB) stars
using observations from the Spitzer Space Telescope Legacy program entitled:
"Surveying the Agents of Galaxy Evolution in the Tidally-stripped, Low
Metallicity SMC", or SAGE-SMC. The survey includes, for the first time, full
spatial coverage of the SMC bar, wing, and tail regions at infrared (IR)
wavelengths (3.6 - 160 microns). We identify evolved stars using a combination
of near-IR and mid-IR photometry and point out a new feature in the mid-IR
color-magnitude diagram that may be due to particularly dusty O-rich AGB stars.
We find that the RSG and AGB stars each contribute ~20% of the global SMC flux
(extended + point-source) at 3.6 microns, which emphasizes the importance of
both stellar types to the integrated flux of distant metal-poor galaxies. The
equivalent SAGE survey of the higher-metallicity Large Magellanic Cloud
(SAGE-LMC) allows us to explore the influence of metallicity on dust
production. We find that the SMC RSG stars are less likely to produce a large
amount of dust (as indicated by the [3.6]-[8] color). There is a higher
fraction of carbon-rich stars in the SMC, and these stars appear to able to
reach colors as red as their LMC counterparts, indicating that C-rich dust
forms efficiently in both galaxies. A preliminary estimate of the dust
production in AGB and RSG stars reveals that the extreme C-rich AGB stars
dominate the dust input in both galaxies, and that the O-rich stars may play a
larger role in the LMC than in the SMC.


  This paper presents a cooperative multi-robot multi-target tracking framework
aimed at enhancing the efficiency of the heterogeneous sensor network and,
consequently, improving overall target tracking accuracy. The concept of
normalized unused sensing capacity is introduced to quantify the information a
sensor is currently gathering relative to its theoretical maximum. This
measurement can be computed using entirely local information and is applicable
to various sensor models, distinguishing it from previous literature on the
subject. It is then utilized to develop a distributed coverage control strategy
for a heterogeneous sensor network, adaptively balancing the workload based on
each sensor's current unused capacity. The algorithm is validated through a
series of ROS and MATLAB simulations, demonstrating superior results compared
to standard approaches that do not account for heterogeneity or current usage
rates.


The classical polarization theory needs to be changed in gas phase


  We tackle the novel class discovery in point cloud segmentation, which
discovers novel classes based on the semantic knowledge of seen classes.
Existing work proposes an online point-wise clustering method with a simplified
equal class-size constraint on the novel classes to avoid degenerate solutions.
However, the inherent imbalanced distribution of novel classes in point clouds
typically violates the equal class-size constraint. Moreover, point-wise
clustering ignores the rich spatial context information of objects, which
results in less expressive representation for semantic segmentation. To address
the above challenges, we propose a novel self-labeling strategy that adaptively
generates high-quality pseudo-labels for imbalanced classes during model
training. In addition, we develop a dual-level representation that incorporates
regional consistency into the point-level classifier learning, reducing noise
in generated segmentation. Finally, we conduct extensive experiments on two
widely used datasets, SemanticKITTI and SemanticPOSS, and the results show our
method outperforms the state of the art by a large margin.


  Despite not having a clear meaning, public perception and awareness makes the
term cyber Pearl Harbor an important part of the public discourse. This paper
considers what the term has meant and proposes its decomposition based on three
different aspects of the historical Pearl Harbor attack, allowing the lessons
from Pearl Harbor to be applied to threats and subjects that may not align with
all aspects of the 1941 attack. Using these three definitions, prior attacks
and current threats are assessed and preparation for and response to cyber
Pearl Harbor events is discussed.


  The derivatives of the identity functor on spaces in Goodwillie calculus
forms an operad in spectra. Antolin-Camarena computed the mod 2 homology of
free algebras over this operad for 1-connected spectra. In this present paper
we carry out similar computations for mod p homology for odd primes p.


  With rapid progress made in language qualities such as fluency and
consistency via large language models (LLMs), there has been increasing
interest in assessing alignment with diverse human preferences. Traditional
metrics heavily rely on lexical similarity with human-written references and
have been observed to suffer from a poor correlation with human evaluation.
Furthermore, they ignore the diverse preferences of humans, a key aspect in
evaluating open-ended tasks like story generation. Inspired by these
challenges, we introduce an interpretable open-ended evaluation framework PerSE
to assess the alignment with a specific human preference. It is tuned to deduce
the specific preference from a given personal profile and evaluate the
alignment between the generation and the personal preference. PerSE also
explains its assessment by a detailed comment or several fine-grained scores.
This enhances its interpretability, making it more suitable to tailor a
personalized generation. Our 13B LLaMA-2-based PerSE shows a 15.8% increase in
Kendall correlation and a 13.7% rise in accuracy on zero-shot reviewers
compared to GPT-4. It also outperforms GPT-4 by 46.01% in the Kendall
correlation on new domains, indicating its transferability.


  Let $G\subset \C P^n$ be a linearly convex compact with smooth boundary,
$D={\C}P^n\setminus G$, and let $D^* \subset (\C P^n)^*$ be the dual domain.
Then for an algebraic, not necessarily reduced, complete intersection
subvariety $V$ of dimension $d$ we construct an explicit inversion formula for
the complex Radon transform $R_V:\ H^{d,d-1}(V\cap D)\to H^{1,0}(D^*)$, and
explicit formulas for solutions of an appropriate boundary value problem for
the corresponding system of differential equations with constant coefficients
on $D^*$.


  The nature of galaxies selected at submillimeter wavelengths (SMGs, S_850 > 3
mJy), some of the bolometrically most luminous objects at high redshifts, is
still elusive. In particular their star formation histories and source of
emission are not accurately constrained. In this paper we introduce a new
approach to analyse the SMG data. Namely, we present the first self-consistent
UV-to-radio spectral energy distribution fits of 76 SMGs with spectroscopic
redshifts using all photometric datapoints from ultraviolet to radio
simultaneously. We find that they are highly star-forming (median star
formation rate 713 MSun yr^-1 for SMGs at z>0.5), moderately dust-obscured
(median A_V~2 mag), hosting significant stellar populations (median stellar
mass 3.7x10^11 MSun) of which only a minor part has been formed in the ongoing
starburst episode. This implies that in the past, SMGs experienced either
another starburst episode or merger with several galaxies. The properties of
SMGs suggest that they are progenitors of present-day elliptical galaxies. We
find that these bright SMGs contribute significantly to the cosmic star
formation rate density (~20%) and stellar mass density (~30-50%) at redshifts
2-4. Using number counts at low fluxes we find that as much as 80% of the
cosmic star formation at these redshifts took place in SMGs brighter than 0.1
mJy. We find evidence that a linear infrared-radio correlation holds for SMGs
in an unchanged form up to redshift of 3.6, though its normalization is offset
from the local relation by a factor of ~2.1 towards higher radio luminosities.
We present a compilation of photometry data of SMGs and determinations of
cosmic SFR and stellar mass densities.


  We present a study on the gender balance, in speakers and attendees, at the
recent major astronomical conference, the American Astronomical Society meeting
223, in Washington, DC. We conducted an informal survey, yielding over 300
responses by volunteers at the meeting. Each response included gender data
about a single talk given at the meeting, recording the gender of the speaker
and all question-askers. In total, 225 individual AAS talks were sampled. We
analyze basic statistical properties of this sample. We find that the gender
ratio of the speakers closely matched the gender ratio of the conference
attendees. The audience asked an average of 2.8 questions per talk. Talks given
by women had a slightly higher number of questions asked (3.2$\pm$0.2) than
talks given by men (2.6$\pm$0.1). The most significant result from this study
is that while the gender ratio of speakers very closely mirrors that of
conference attendees, women are under-represented in the question-asker
category. We interpret this to be an age-effect, as senior scientists may be
more likely to ask questions, and are more commonly men. A strong dependence on
the gender of session chairs is found, whereby women ask disproportionately
fewer questions in sessions chaired by men. While our results point to laudable
progress in gender-balanced speaker selection, we believe future surveys of
this kind would help ensure that collaboration at such meetings is as inclusive
as possible.


  A simple mechanical spring-block model is introduced for studying
magnetization phenomena and in particularly the Barkhausen noise. The model
captures and reproduces the accepted microscopic picture of domain wall
movement and pinning. Computer simulations suggest that this model is able to
reproduce the main characteristics of hysteresis loops and Barkhausen jumps. In
the thermodynamic limit the statistics of the obtained Barkhausen jumps follows
several scaling laws, in qualitative agreement with the experimental results.
The simplicity of the model and the invoked mechanical analogies makes it
attractive for computer simulations and pedagogical purposes.


  We show that a 2-knot group discovered in the course of a census of
4-manifolds with small triangulations is an HNN extension with finite base and
proper associated subgroups, and has the smallest base among such knot groups.


  The Landau equation and the Boltzmann equation are connected through the
limit of grazing collisions. This has been proved rigorously for certain
families of Boltzmann operators concentrating on grazing collisions. In this
contribution, we study the collision kernels associated to the two-particle
scattering via a finite range potential $\Phi(x)$ in three dimensions. We then
consider the limit of weak interaction given by $\Phi_\epsilon(x) = \epsilon
\Phi(x)$. Here $\epsilon\rightarrow 0$ is the grazing parameter, and the rate
of collisions is rescaled to obtain a non-trivial limit. The grazing collisions
limit is of particular interest for potentials with a singularity of order
$s\geq 0$ at the origin, i.e. $\phi(x) \sim |x|^{-s}$ as $|x|\rightarrow 0$.
For $s\in [0,1]$, we prove the convergence to the Landau equation with
diffusion coefficient given by the Born approximation, as predicted in the
works of Landau and Balescu. On the other hand, for potentials with $s>1$ we
obtain the non-cutoff Boltzmann equation in the limit. The Coulomb singularity
$s=1$ appears as a threshold value with a logarithmic correction to the
diffusive timescale, the so-called Coulomb logarithm.


  Stuttering is a speech disorder influencing over 70 million people worldwide,
including 13 million in China. It causes low self-esteem among other
detrimental effects on people who stutter (PwS). Although prior work has
explored approaches to assist PwS, they primarily focused on western contexts.
In our formative study, we found unique practices and challenges among Chinese
PwS. We then iteratively designed an online tool, CoPracTter, to support
Chinese PwS practicing speaking fluency with 1) targeted stress-inducing
practice scenarios, 2) real-time speech indicators, and 3) personalized timely
feedback from the community. We further conducted a seven-day deployment study
(N=11) to understand how participants utilized these key features. To our
knowledge, it is the first time such a prototype was designed and tested for a
long time with multiple PwS participants online simultaneously. Results
indicate that personalized practice with targeted scenarios and timely feedback
from a supportive community assisted PwS in speaking fluently, staying
positive, and facing similar real-life circumstances.


  Using high-resolution data from the Galactic Arecibo L-Band Feed Array HI
(GALFA-HI) survey, we show that linear structure in Galactic neutral hydrogen
(HI) correlates with the magnetic field orientation implied by Planck 353 GHz
polarized dust emission. The structure of the neutral interstellar medium is
more tightly coupled to the magnetic field than previously known. At high
Galactic latitudes, where the Planck data are noise-dominated, the HI data
provide an independent constraint on the Galactic magnetic field orientation,
and hence the local dust polarization angle. We detect strong
cross-correlations between template maps constructed from estimates of dust
intensity combined with either HI-derived angles, starlight polarization
angles, or Planck 353 GHz angles. The HI data thus provide a new tool in the
search for inflationary gravitational wave B-mode polarization in the cosmic
microwave background, which is currently limited by dust foreground
contamination.


  For years, many studies employed sentiment analysis to understand the
reasoning behind people's choices and feelings, their communication styles, and
the communities which they belong to. We argue that gaining more in-depth
insight into moral dimensions coupled with sentiment analysis can potentially
provide superior results. Understanding moral foundations can yield powerful
results in terms of perceiving the intended meaning of the text data, as the
concept of morality provides additional information on the unobservable
characteristics of information processing and non-conscious cognitive
processes. Therefore, we studied latent moral loadings of Syrian White
Helmets-related tweets of Twitter users from April 1st, 2018 to April 30th,
2019. For the operationalization and quantification of moral rhetoric in
tweets, we use Extended Moral Foundations Dictionary in which five
psychological dimensions (Harm/Care, Fairness/Reciprocity, In-group/Loyalty,
Authority/Respect and Purity/Sanctity) are considered. We show that people tend
to share more tweets involving the virtue moral rhetoric than the tweets
involving the vice rhetoric. We observe that the pattern of the moral rhetoric
of tweets among these five dimensions are very similar during different time
periods, while the strength of the five dimension is time-variant. Even though
there is no significant difference between the use of Fairness/Reciprocity,
In-group/Loyalty or Purity/Sanctity rhetoric, the less use of Harm/Care
rhetoric is significant and remarkable. Besides, the strength of the moral
rhetoric and the polarization in morality across people are mostly observed in
tweets involving Harm/Care rhetoric despite the number of tweets involving the
Harm/Care dimension is low.


  We study the Gross-Pitaevskii equation with a slowly varying smooth
potential, $V(x) = W(hx)$. We show that up to time $\log(1/h)/h $ and errors of
size $h^2$ in $H^1$, the solution is a soliton evolving according to the
classical dynamics of a natural effective Hamiltonian, $ (\xi^2 + \sech^2 * V
(x))/2 $. This provides an improvement ($ h \to h^2 $) compared to previous
works, and is strikingly confirmed by numerical simulations.


  Interior perfect fluid solutions for the Reissner-Nordstrom metric are
studied on the basis of a new classification scheme. General formulas are found
in many cases. Explicit new global solutions are given as illustrations. Known
solutions are briefly reviewed.


  Deep learning (DL) models are capable of successfully exploiting latent
representations in MR data and have become state-of-the-art for accelerated MRI
reconstruction. However, undersampling the measurements in k-space as well as
the over- or under-parameterized and non-transparent nature of DL make these
models exposed to uncertainty. Consequently, uncertainty estimation has become
a major issue in DL MRI reconstruction. To estimate uncertainty, Monte Carlo
(MC) inference techniques have become a common practice where multiple
reconstructions are utilized to compute the variance in reconstruction as a
measurement of uncertainty. However, these methods demand high computational
costs as they require multiple inferences through the DL model. To this end, we
introduce a method to estimate uncertainty during MRI reconstruction using a
pixel classification framework. The proposed method, PixCUE (stands for Pixel
Classification Uncertainty Estimation) produces the reconstructed image along
with an uncertainty map during a single forward pass through the DL model. We
demonstrate that this approach generates uncertainty maps that highly correlate
with the reconstruction errors with respect to various MR imaging sequences and
under numerous adversarial conditions. We also show that the estimated
uncertainties are correlated to that of the conventional MC method. We further
provide an empirical relationship between the uncertainty estimations using
PixCUE and well-established reconstruction metrics such as NMSE, PSNR, and
SSIM. We conclude that PixCUE is capable of reliably estimating the uncertainty
in MRI reconstruction with a minimum additional computational cost.


  Blockchain has been considered as an important technique to enable secure
management of virtual network functions and network slices. To understand such
capabilities of a blockchain, e.g. transaction confirmation time, demands a
thorough study on the transaction characteristics of the blockchain. This paper
presents a comprehensive study on the transaction characteristics of Bitcoin --
the first blockchain application, focusing on the underlying fundamental
processes. A set of results and findings are obtained, which provide new
insight into understanding the transaction and traffic characteristics of
Bitcoin. As a highlight, the validity of several hypotheses/assumptions used in
the literature is examined with measurement for the first time.


  Current end-to-end approaches to Spoken Language Translation (SLT) rely on
limited training resources, especially for multilingual settings. On the other
hand, Multilingual Neural Machine Translation (MultiNMT) approaches rely on
higher-quality and more massive data sets. Our proposed method extends a
MultiNMT architecture based on language-specific encoders-decoders to the task
of Multilingual SLT (MultiSLT). Our method entirely eliminates the dependency
from MultiSLT data and it is able to translate while training only on ASR and
MultiNMT data.
  Our experiments on four different languages show that coupling the speech
encoder to the MultiNMT architecture produces similar quality translations
compared to a bilingual baseline ($\pm 0.2$ BLEU) while effectively allowing
for zero-shot MultiSLT. Additionally, we propose using an Adapter module for
coupling the speech inputs. This Adapter module produces consistent
improvements up to +6 BLEU points on the proposed architecture and +1 BLEU
point on the end-to-end baseline.


  Using the fact that we only observe those modes which exit the Hubble horizon
during inflation, one can calculate the entanglement entropy of such
long-wavelength perturbations by tracing out unobservable sub-Hubble
fluctuations they are coupled to. On requiring that this perturbative
entanglement entropy, which increases with time, obey the covariant entropy
bound for an accelerating background, we find an upper bound on the duration of
inflation. This presents a new perspective on the (meta-)stability of de Sitter
spacetime and an associated lifetime for it.


  In this paper we consider three types of discrete operators stemming from
singular Radon transforms. We first extend an $\ell^p$ result for translation
invariant discrete singular Radon transforms to a class of twisted operators
including an additional oscillatory component, via a simple method of descent
argument. Second, we note an $\ell^2$ bound for quasi-translation invariant
discrete twisted Radon transforms. Finally, we extend an existing $\ell^2$
bound for a closely related non-translation invariant discrete oscillatory
integral operator with singular kernel to an $\ell^p$ bound for all $1< p<
\infty$. This requires an intricate induction argument involving layers of
decompositions of the operator according to the Diophantine properties of the
coefficients of its polynomial phase function.


  Semi-Markov processes are a generalization of Markov processes since the
exponential distribution of time intervals is replaced with an arbitrary
distribution. This paper provides an integro-differential form of the
Kolmogorov's backward equations for a large class of homogeneous semi-Markov
processes, having the form of an abstract Volterra integro-differential
equation. An equivalent evolutionary (differential) form of the equations is
also provided. Fractional equations in the time variable are a particular case
of our analysis. Weak limits of semi-Markov processes are also considered and
their corresponding integro-differential Kolmogorov's equations are identified.


  We examine how the qualitative structure of the Doppler peaks in the angular
power spectrum of the cosmic microwave anisotropy depends on the fundamental
nature of the perturbations which produced them. The formalism of Hu and
Sugiyama is extended to treat models with cosmic defects. We discuss how
perturbations can be ``active'' or ``passive'' and ``incoherent'' or
``coherent'', and show how causality and scale invariance play rather different
roles in these various cases. We find that the existence of secondary Doppler
peaks and the rough placing of the primary peak unambiguously reflect these
basic properties.


  This paper develops and implements a scalable methodology for (a) estimating
the noisiness of labels produced by a typical crowdsourcing semantic annotation
task, and (b) reducing the resulting error of the labeling process by as much
as 20-30% in comparison to other common labeling strategies. Importantly, this
new approach to the labeling process, which we name Dynamic Automatic Conflict
Resolution (DACR), does not require a ground truth dataset and is instead based
on inter-project annotation inconsistencies. This makes DACR not only more
accurate but also available to a broad range of labeling tasks. In what follows
we present results from a text classification task performed at scale for a
commercial personal assistant, and evaluate the inherent ambiguity uncovered by
this annotation strategy as compared to other common labeling strategies.


  We study the structure and evolution of the magnetic field of the quiet Sun
by investigating weak spectro-polarimetric signals. To this end, we observed a
quiet region close to the disk center with the German VTT in Tenerife, July 07,
2006. We recorded 38 scans of the same area. Each scan was eight arcsec wide
and observed within about 100 seconds. We used POLIS to simultaneously observe
Stokes profiles of the neutral iron lines at 630.15 and 630.25 nm, the Stokes-I
profile of the Ca II H line at 396.8 nm, and a continuum speckle channel at 500
nm. We witness two examples of magnetic flux cancellation of small-scale
opposite-polarity patches, followed by an enhanced chromospheric emission. In
each case, the two opposite-polarity patches gradually became smaller and,
within a few minutes, the smaller one completely disappeared. The larger patch
also diminished significantly. We provide evidence for a cancellation scenario
in the photosphere which leaves minor traces at the chromospheric level.


  The emergence of three-dimensional magneto-hydrodynamic (MHD) simulations of
stellar atmospheres has sparked a need for efficient radiative transfer codes
to calculate detailed synthetic spectra. We present RH 1.5D, a massively
parallel code based on the RH code and capable of performing Zeeman polarised
multi-level non-local thermodynamical equilibrium (NLTE) calculations with
partial frequency redistribution for an arbitrary amount of chemical species.
The code calculates spectra from 3D, 2D or 1D atmospheric models on a
column-by-column basis (or 1.5D). While the 1.5D approximation breaks down in
the cores of very strong lines in an inhomogeneous environment, it is
nevertheless suitable for a large range of scenarios and allows for faster
convergence with finer control over the iteration of each simulation column.
The code scales well to at least tens of thousands of CPU cores, and is
publicly available. In the present work we briefly describe its inner workings,
strategies for convergence optimisation, its parallelism, and some possible
applications.


  We use alternative quantisation of the D3-D5 system to explore properties of
a strongly coupled anyon material at finite density and temperature. We study
the transport properties of the material and find both diffusion and massive
holographic zero sound modes. By studying the anyon number conductivity we also
find evidence for the anyonic analogue of the metal-insulator transition.


  We report the first observation of gate-controlled field emission current
from a tungsten diselenide (WSe2) monolayer, synthesized by chemical-vapour
deposition on SiO2/Si substrate. Ni contacted WSe2 monolayer back-gated
transistors, under high vacuum, exhibit n-type conduction and drain-bias
dependent transfer characteristics, which are attributed to oxygen/water
desorption and drain induced Schottky barrier lowering, respectively. The
gate-tuned n-type conduction enables field emission, i.e. the extraction of
electrons by quantum tunnelling, even from the flat part of the WSe2
monolayers. Electron emission occurs under an electric field ~100 V {\mu}m^(-1)
and exhibit good time stability. Remarkably, the field emission current can be
modulated by the back-gate voltage. The first field-emission vertical
transistor based on WSe2 monolayer is thus demonstrated and can pave the way to
further optimize new WSe2 based devices for use in vacuum electronics.


  We consider a cell-free massive MIMO system with multiple antennas on the
users and access points. In previous works, the downlink spectral efficiency
(SE) has been evaluated using the hardening bound that requires no downlink
pilots. This approach works well when having single-antenna users. In this
paper, we show that much higher SEs can be achieved if downlink pilots are sent
since the effective channel matrix does not harden when having multi-antenna
users. We propose a pilot-based downlink estimation scheme and derive a new SE
expression that utilizes zero-forcing combining. We show numerically how the
number of users and user antennas affects the SE.


  In the present work, focusing on one of the most popular problems in modern
gravitation theories, we consider generalized Lanndau-Liftshitz energy-momentum
relation to calculate energy distribution of the Bianchi-Type VI spacetime in
$f(R)$ gravity. Additionally, the results are specified by using some
well-known $f(R)$-gravity models.


  The effective low-energy late-time description of many body systems near
thermal equilibrium provided by classical hydrodynamics in terms of dissipative
transport phenomena receives important corrections once the effects of
stochastic fluctuations are taken into account. One such physical effect is the
occurrence of long-time power law tails in correlation functions of conserved
currents. In the hydrodynamic regime $\vec{k} \rightarrow 0$ this amounts to
non-analytic dependence of the correlation functions on the frequency $\omega$.
In this article, we consider a relativistic fluid with a conserved global
$U(1)$ charge in the presence of a strong background magnetic field, and
compute the long-time tails in correlation functions of the stress tensor. The
presence of the magnetic field renders the system anisotropic. In the absence
of the magnetic field, there are three out-of-equilibrium transport parameters
that arise at the first order in the hydrodynamic derivative expansion, all of
which are dissipative. In the presence of a background magnetic field, there
are ten independent out-of-equilibrium transport parameters at the first order,
three of which are non-dissipative and the rest are dissipative. We provide the
most general linearized equations about a given state of thermal equilibrium
involving the various transport parameters in the presence of a magnetic field,
and use them to compute the long-time tails for the fluid.


Divisors with minimal discrepancy over cA points are classified


  We prove an explicit formula for the truncated Atiyah class of a bounded
complex of vector bundles. Furthermore, we show that the first truncated Chern
class of such a complex only depends on its determinant.


  We introduce a two-dimensional (2D) discrete nonlinear Schr\"{o}dinger (DNLS)
equation with self-attractive cubic nonlinearity in a rotating reference frame.
The model applies to a Bose-Einstein condensate stirred by a rotating strong
optical lattice, or light propagation in a twisted bundle of nonlinear fibers.
Two species of localized states are constructed: off-axis fundamental solitons
(FSs), placed at distance $R$ from the rotation pivot, and on-axis (R=0) vortex
solitons (VSs), with vorticities $% S=1$ and 2. At a fixed value of rotation
frequency $\Omega $, a stability interval for the FSs is found in terms of the
lattice coupling constant $C$, $% 0<C<C_{\mathrm{cr}}(R)$, with monotonically
decreasing $C_{\mathrm{cr}}(R)$. VSs with S=1 have a stability interval,
$\tilde{C}_{\mathrm{cr}%}^{(S=1)}(\Omega)<C<C_{\mathrm{cr}}^{(S=1)}(\Omega)$,
which exists for $% \Omega $ below a certain critical value,
$\Omega_{\mathrm{cr}}^{(S=1)}$. This implies that the VSs with S=1 are
\emph{destabilized} in the weak-coupling limit by the rotation. On the
contrary, VSs with S=2, that are known to be unstable in the standard DNLS
equation, with $\Omega =0$, are \emph{stabilized} by the rotation in region
$0<C<C_{\mathrm{cr}}^{(S=2)}$%, with $C_{\mathrm{cr}}^{(S=2)}$ growing as a
function of $\Omega $. Quadrupole and octupole on-axis solitons are considered
too, their stability regions being weakly affected by $\Omega \neq 0$.


  The fluctuations in the particle size distribution for processes of
fragmentation and aggregation are studied for stationary state regimes. The
system is described in terms of a stochastic process over an adequate tree
structure. The RMS fluctuations appear to scale with the square root of the
mean distribution, as in the case of sums of statistically independent events.
Implications for the applicability of a mean field description to fragmentation
and agglomeration processes, and possible relation with intermittency phenomena
in three dimensional turbulence are discussed.


  Let $\mathcal{A}$ and $\mathcal{U}$ be Banach algebras and $\theta$ be a
nonzero character on $\mathcal{A}$. Then the \textit{Lau product Banach
algebra} $\mathcal{A}\times_{\theta}\mathcal{U}$ associated with the Banach
algebras $\mathcal{A}$ and $\mathcal{U}$ is the $l^1$-direct sum
$\mathcal{A}\oplus\mathcal{U}$ equipped with the algebra multiplication
$(a,u)(a',u')=(ab,\theta(a)u'+\theta(a')u+uu')\,
(a,a'\in\mathcal{A},u,u'\in\mathcal{U})$ and $l^1$-norm. In this paper we shall
investigate the derivations and multipliers from this Banach algebras and study
the automatic continuity of these mappings. We also study continuity of the
derivations for some special cases of Banach algebra $\mathcal{U}$ and Banach
$\mathcal{A}\times_{\theta}\mathcal{U}$-bimodule $\mathcal{X}$ and establish
various results on the continuity of derivations and give some examples.


  The low-latitude ionosphere is a dynamic region with a wide range of
disturbances in temporal and spatial scales. The Giant Metrewave Radio
Telescope (GMRT) situated in the low-latitude region has demonstrated its
ability to detect various ionospheric phenomena. It can detect total electron
content (TEC) variation with precision of 1 mTECU and also can measure TEC
gradient with an accuracy of about $\rm7\times 10^{-4}\,TECU\,km^{-1}$. This
paper describes the spectral analysis of previously calculated TEC gradient
measurements and validates them by comparing their properties using two bands.
The analysis tracked individual waves associated with medium-scale traveling
ionospheric disturbances (MSTIDs) and smaller waves down to wavelengths of
$\sim$ 10 km. The ionosphere is found to have unanticipated changes during
sunrise hours, with waves changed propagation direction as the sun approached
the zenith. Equatorial spread\,$F$ disturbances during sunrise hours is
observed, along with smaller structures moving in the same direction.


  We describe the crystal structure and elementary magnetic properties of a
previously unreported ternary intermetallic compound, Cr4PtGa17, which
crystallizes in a rhombohedral unit cell in the noncentrosymmetric space group
R3m. The crystal structure is closely related to those of XYZ half-Heusler
compounds, where X, Y and Z are reported to be single elements only, occupying
three different face-centered cubic sublattices. The new material, Cr4PtGa17,
can be most straightforwardly illustrated by writing the formula as
(PtGa2)(Cr4Ga14)Ga (X=PtGa2, Y = Cr4Ga14, Z = Ga), that is, the X and Y sites
are occupied by clusters instead of single elements. The magnetic Cr occupies a
breathing pyrochlore lattice. Ferromagnetic ordering is found below TC ~61 K,
by both neutron diffraction and magnetometer studies, with a small, saturated
moment of ~0.25 muB/Cr observed at 2 K, making Cr4PtGa17 the first
ferromagnetically ordered material with a breathing pyrochlore lattice. A
magnetoresistance of ~140% was observed at 2 K. DFT calculations suggest that
the material has a nearly-half-metallic electronic structure. The new material,
Cr4PtGa17, the first realization of both a half-Heusler-type structure and a
breathing pyrochlore lattice, might pave a new way to achieve novel types of
half-Heusler compounds.


  We use the LOFAR Two-metre Sky Survey (LoTSS) Data Release I to identify the
groups of galaxies (and individual galaxies) from the Hickson Compact Groups
and Magnitude Limited Compact Groups samples that emit at the frequency of
150\,MHz, characterise their radio emission (extended or limited to the
galaxies), and compare new results to earlier observations and theoretical
predictions. The detection of 73 systems (and 7 more -- probably) out of 120,
of which as many as 17 show the presence of extended radio structures, confirms
the previous hypothesis of the common character of the magnetic field inside
galaxy groups and its detectability. In order to investigate the future
potential of low-frequency radio studies of galaxy groups, we also present a
more detailed insight into four radio-emitting systems, for which the strength
of the magnetic field inside their intergalactic medium (IGM) is calculated.
The estimated values are comparable to that found inside star-forming galaxies,
suggesting a dynamical and evolutionary importance of the magnetic field in
galaxy groups.


  Human dynamics is known to be inhomogeneous and bursty but the detailed
understanding of the role of human factors in bursty dynamics is still lacking.
In order to investigate their role we devise an agent-based model, where an
agent in an uncertain situation tries to reduce the uncertainty by
communicating with information providers while having to wait time for
responses. Here the waiting time can be considered as cost. We show that the
optimal choice of the waiting time under uncertainty gives rise to the bursty
dynamics, characterized by the heavy-tailed distribution of optimal waiting
time. We find that in all cases the efficiency for communication is relevant to
the scaling behavior of the optimal waiting time distribution. On the other
hand the cost turns out in some cases to be irrelevant depending on the degree
of uncertainty and efficiency.


  We study the synchronization and stability of power grids within the Kuramoto
phase oscillator model with inertia with a bimodal frequency distribution
representing the generators and the loads. We identify critical nodes through
solitary frequency deviations and Lyapunov vectors corresponding to unstable
Lyapunov exponents. To cure dangerous deviations from synchronization we
propose time-delayed feedback control, which is an efficient control concept in
nonlinear dynamic systems. Different control strategies are tested and compared
with respect to the minimum number of controlled nodes required to achieve
synchronization and Lyapunov stability. As a proof of principle, this
fast-acting control method is demonstrated using a model of the German power
transmission grid.


  The spectrum of the Io plasma torus in the range 905 - 1187 A was recorded at
0.26 A resolution by the Far Ultraviolet Spectroscopic Explorer (FUSE) on 2001
January 14. Five orbits of data were obtained with the west ansa of the torus
centered and tracked in the 30" x 30" apertures of the FUSE spectrographs for a
total observation time of 9740 seconds. This region of the spectrum is
dominated by transitions of S II, S III and S IV, whose multiplet structure is
nearly completely resolved. We confirm our earlier detection of emission from
resonance multiplets of Cl III and Cl II and derive an abundance of Cl^{+2} of
2.1% relative to S^{2+}, leading to an overall chlorine ion abundance in the
torus of slightly less than 1%. A number of features near 990 A remain
unidentified, and C III at 977 A is detected in two independent channels at the
3-sigma level. The inferred relative ion abundance of C^{2+} relative to S^{2+}
is 3.7 x 10^{-4}. We also present spectra at 0.085 A resolution taken on 2001
October 19 and 21 with the 4" x 20" aperture. In these spectra the observed
lines are resolved and their widths correspond to ion temperatures of 60 - 70
eV for all three sulfur ions.


  Abridged: Using free-free emission measured in the Ka-band (26-40GHz) for 10
star-forming regions in the nearby galaxy NGC6946, including its starbursting
nucleus, we compare a number of SFR diagnostics that are typically considered
to be unaffected by interstellar extinction: i.e., non-thermal radio (i.e.,
1.4GHz), total infrared (IR; 8-1000um), and warm dust (i.e., 24um) emission,
along with the hybrid (obscured + unobscured) indicators of H\alpha+24um and
UV+IR. The 33GHz free-free emission is assumed to provide the most accurate
measure of the current SFR. Among the extranuclear star-forming regions, the
24um, H\alpha+24um and UV+IR SFR calibrations are in good agreement with the
33GHz free-free SFRs. However, each of the SFR calibrations relying on some
form of dust emission overestimate the nuclear SFR by a factor of ~2. This is
more likely the result of excess dust heating through an accumulation of
non-ionizing stars associated with an extended episode of star formation in the
nucleus rather than increased competition for ionizing photons by dust. SFR
calibrations using the non-thermal radio continuum yield values which only
agree with the free-free SFRs for the nucleus, and underestimate the SFRs from
the extranuclear star-forming regions by a factor of ~2. This result likely
arises from the CR electrons decaying within the starburst region with
negligible escape compared to the young extranuclear star-forming regions.
Finally, we find that the SFRs estimated using the total 33GHz emission agree
well with the free-free SFRs due to the large thermal fractions present at
these frequencies even when local diffuse backgrounds are not removed. Thus,
rest-frame 33GHz observations may act as a reliable method to measure the SFRs
of galaxies at increasingly high redshift without the need of ancillary radio
data to account for the non-thermal emission.


  Using a single quantum probe to sense other quantum objects offers distinct
advantages but suffers from some limitations that may degrade the sensing
precision severely, especially when the probe-target coupling is weak. Here we
propose a strategy to improve the sensing precision by using the quantum probe
to engineer the evolution of the target. We consider an exactly solvable model,
in which a qubit is used as the probe to sense the frequency of a harmonic
oscillator. We show that by applying adaptive periodic quantum control on the
qubit, the sensing precision can be enhanced from 1/T scaling with the total
time cost T to 1/T^{2} scaling, thus improving the precision by several orders
of magnitudes. Such improvement can be achieved without any direct access to
the oscillator and the improvement increases with decreasing probe-target
coupling. This provides a useful routine to ultrasensitive quantum sensing of
weakly coupled quantum objects.


  Restoring a sharp light field image from its blurry input has become
essential due to the increasing popularity of parallax-based image processing.
State-of-the-art blind light field deblurring methods suffer from several
issues such as slow processing, reduced spatial size, and a limited motion blur
model. In this work, we address these challenging problems by generating a
complex blurry light field dataset and proposing a learning-based deblurring
approach. In particular, we model the full 6-degree of freedom (6-DOF) light
field camera motion, which is used to create the blurry dataset using a
combination of real light fields captured with a Lytro Illum camera, and
synthetic light field renderings of 3D scenes. Furthermore, we propose a light
field deblurring network that is built with the capability of large receptive
fields. We also introduce a simple strategy of angular sampling to train on the
large-scale blurry light field effectively. We evaluate our method through both
quantitative and qualitative measurements and demonstrate superior performance
compared to the state-of-the-art method with a massive speedup in execution
time. Our method is about 16K times faster than Srinivasan et. al. [22] and can
deblur a full-resolution light field in less than 2 seconds.


  For a planar self-affine set satisfying the strong separation condition, it
has been recently proved that under mild assumptions the Hausdorff dimension
equals the affinity dimension. In this article, we continue this line of
research and our objective is to acquire more refined geometric information. In
a large class of non-carpet planar self-affine sets, we characterize Ahlfors
regularity, determine the Assouad dimension of the set and its projections, and
estimate the Hausdorff dimension of slices. We also demonstrate that the
Assouad dimension is not necessarily bounded above by the affinity dimension.


  The introduction of the schema.org vocabulary was a big step towards making
websites machine read- and understandable. Due to schema.org's RDF-like nature
storing annotations in a graph database is easy and efficient. In this paper
the authors show how they gather touristic data in the Austrian region of Tirol
and provide this data publicly in a knowledge graph. The definition of subsets
of the vocabulary is followed by providing means to map data sources
efficiently to schema.org and then store the annotated content into the graph.
To showcase the consumption of the touristic data four scenarios are described
which use the knowledge graph for real life applications and data analysis.


  Entanglement witnesses provide tools to detect entanglement in experimental
situations without the need of having full tomographic knowledge about the
state. If one estimates in an experiment an expectation value smaller than
zero, one can directly infer that the state has been entangled, or specifically
multi-partite entangled, in the first place. In this article, we emphasize that
all these tests - based on the very same data - give rise to quantitative
estimates in terms of entanglement measures: "If a test is strongly violated,
one can also infer that the state was quantitatively very much entangled". We
consider various measures of entanglement, including the negativity, the
entanglement of formation, and the robustness of entanglement, in the bipartite
and multipartite setting. As examples, we discuss several experiments in the
context of quantum state preparation that have recently been performed.


  We initiate the treatment of KMS states on uniform Roe algebras
$\mathrm{C}^*_u(X)$ for a class of naturally occurring flows on these algebras.
We show that KMS states on $\mathrm{C}^*_u(X)$ always factor through the
diagonal operators $\ell_\infty(X)$. We show the study of those states splits
into understanding their strongly continuous KMS states and the KMS states
which vanish on the ideal of compact operators. We show strongly continuous
states are always unique when they exist and we give explicit formulas for
them. We link the study of KMS states which vanish on the compacts to the
Higson corona of $X$ and provide lower bounds for the cardinality of the set of
extreme KMS states. Lastly, we apply our theory to the $n$-branching tree.


  Information-based uncertainty measures like Shannon entropy, Onicescu energy
and Fisher information (in position and momentum space) are employed to
understand the effect of \emph{symmetric and asymmetric} confinement in a
quantum harmonic oscillator. Also, the transformation of Hamiltonian into a
dimensionless form gives an idea of the composite effect of force constant and
confinement length ($x_c$). In symmetric case, a wide range of $x_{c}$ has been
taken up, whereas asymmetric confinement is dealt by shifting the minimum of
potential from origin keeping box length and boundary fixed. Eigenvalues and
eigenvectors for these systems are obtained quite accurately via an imaginary
time propagation scheme. For asymmetric confinement, a variation-induced exact
diagonalization procedure is also introduced, which produces very high-quality
results. One finds that, in symmetric confinement, after a certain
characteristic $x_{c}$, all these properties converge to respective values of
free harmonic oscillator. In asymmetric situation, excited-state energies
always pass through a maximum. For this potential, the classical turning-point
decreases, whereas well depth increases with the strength of asymmetry. Study
of these uncertainty measures reveals that, localization increases with an
increase of asymmetric parameter.


  We consider the projected gradient algorithm for the nonconvex best subset
selection problem that minimizes a given empirical loss function under an
$\ell_0$-norm constraint. Through decomposing the feasible set of the given
sparsity constraint as a finite union of linear subspaces, we present two
acceleration schemes with global convergence guarantees, one by same-space
extrapolation and the other by subspace identification. The former fully
utilizes the problem structure to greatly accelerate the optimization speed
with only negligible additional cost. The latter leads to a two-stage
meta-algorithm that first uses classical projected gradient iterations to
identify the correct subspace containing an optimal solution, and then switches
to a highly-efficient smooth optimization method in the identified subspace to
attain superlinear convergence. Experiments demonstrate that the proposed
accelerated algorithms are magnitudes faster than their non-accelerated
counterparts as well as the state of the art.


  We study the noise induced transport of an overdamped Brownian particle in
frictional ratchet systems in the presence of external Gaussian white noise
fluctuations. The analytical expressions for current and diffusion coefficient
are derived and the reliability or coherence of transport are discussed by
means of their ratio. We show that frictional ratchets exhibit larger coherence
as compared to the flashing and rocking ratchets.


  Quantum computing has the potential to outperform classical computers and is
expected to play an active role in various fields. In quantum machine learning,
a quantum computer has been found useful for enhanced feature representation
and high dimensional state or function approximation. Quantum-Classical hybrid
algorithms are proposed in recent years for this purpose under the
Noisy-Intermediate Scale Quantum computer (NISQ) environment. Under this
scheme, the role played by classical computer is the parameter tuning,
parameter optimization, and parameter update for the quantum circuit. In this
paper, we propose a gradient descent based backpropagation algorithm that can
efficiently calculate the gradient in parameter optimization and update the
parameter for quantum circuit learning, which outperforms the current parameter
search algorithms in terms of computing speed while presents the same or even
higher test accuracy.


  We derive the bulk viscous damping timescale of hybrid stars, neutron stars
with quark matter core. The r-mode instability windows of the stars show that
the theoretical results are consistent with the rapid rotation pulsar data,
which may give an indication for the existence of quark matter in the interior
of neutron stars. Hybrid stars instead of neutron or strange stars may lead to
submillisecond pulsars.


  Using metamaterial absorbers, we have shown that metallic layers in the
absorbers do not necessarily constitute undesired resistive heating problem for
photovoltaics. Tailoring the geometric skin depth of metals and employing the
natural bulk absorbance characteristics of the semiconductors in those
absorbers can enable the exchange of undesired resistive losses with the useful
optical absorbance in the active semiconductors. Thus, Ohmic loss dominated
metamaterial absorbers can be converted into photovoltaic near-perfect
absorbers with the advantage of harvesting the full potential of light
management offered by the metamaterial absorbers. Based on experimental
permittivity data for indium gallium nitride, we have shown that between
75%-95% absorbance can be achieved in the semiconductor layers of the converted
metamaterial absorbers. Besides other metamaterial and plasmonic devices, our
results may also apply to photodectors and other metal or semiconductor based
optical devices where resistive losses and power consumption are important
pertaining to the device performance.


  We show that the level sets of automorphisms of free groups with respect to
the Lipschitz metric are connected as subsets of Culler-Vogtmann space. In fact
we prove our result in a more general setting of deformation spaces. As
applications, we give metric solutions of the conjugacy problem for irreducible
automorphisms and the detection of reducibility. We additionally prove
technical results that may be of independent interest --- such as the fact that
the set of displacements is well ordered.


  A recent framework for generalizing the Erdos-Ko-Rado Theorem, due to
Holroyd, Spencer, and Talbot, defines the Erdos-Ko-Rado property for a graph in
terms of the graph's independent sets. Since the family of all independent sets
of a graph forms a simplicial complex, it is natural to further generalize the
Erdos-Ko-Rado property to an arbitrary simplicial complex. An advantage of
working in simplicial complexes is the availability of algebraic shifting, a
powerful shifting (compression) technique, which we use to verify a conjecture
of Holroyd and Talbot in the case of sequentially Cohen-Macaulay near-cones.


  Question answering over temporal knowledge graphs (KGs) efficiently uses
facts contained in a temporal KG, which records entity relations and when they
occur in time, to answer natural language questions (e.g., "Who was the
president of the US before Obama?"). These questions often involve three
time-related challenges that previous work fail to adequately address: 1)
questions often do not specify exact timestamps of interest (e.g., "Obama"
instead of 2000); 2) subtle lexical differences in time relations (e.g.,
"before" vs "after"); 3) off-the-shelf temporal KG embeddings that previous
work builds on ignore the temporal order of timestamps, which is crucial for
answering temporal-order related questions. In this paper, we propose a
time-sensitive question answering (TSQA) framework to tackle these problems.
TSQA features a timestamp estimation module to infer the unwritten timestamp
from the question. We also employ a time-sensitive KG encoder to inject
ordering information into the temporal KG embeddings that TSQA is based on.
With the help of techniques to reduce the search space for potential answers,
TSQA significantly outperforms the previous state of the art on a new benchmark
for question answering over temporal KGs, especially achieving a 32% (absolute)
error reduction on complex questions that require multiple steps of reasoning
over facts in the temporal KG.


  The introduction of COVID-19 lockdown measures and an outlook on return to
normality are demanding societal changes. Among the most pressing questions is
how individuals adjust to the pandemic. This paper examines the emotional
responses to the pandemic in a repeated-measures design. Data (n=1698) were
collected in April 2020 (during strict lockdown measures) and in April 2021
(when vaccination programmes gained traction). We asked participants to report
their emotions and express these in text data. Statistical tests revealed an
average trend towards better adjustment to the pandemic. However, clustering
analyses suggested a more complex heterogeneous pattern with a well-coping and
a resigning subgroup of participants. Linguistic computational analyses
uncovered that topics and n-gram frequencies shifted towards attention to the
vaccination programme and away from general worrying. Implications for public
mental health efforts in identifying people at heightened risk are discussed.
The dataset is made publicly available.


  Given a graph $G$, a vertex-colouring $\sigma$ of $G$, and a subset
$X\subseteq V(G)$, a colour $x \in \sigma(X)$ is said to be \emph{odd} for $X$
in $\sigma$ if it has an odd number of occurrences in $X$. We say that $\sigma$
is an \emph{odd colouring} of $G$ if it is proper and every (open)
neighbourhood has an odd colour in $\sigma$. The odd chromatic number of a
graph $G$, denoted by $\chi_o(G)$, is the minimum $k\in\mathbb{N}$ such that an
odd colouring $\sigma \colon V(G)\to [k]$ exists. In a recent paper, Caro,
Petru\v sevski and \v Skrekovski conjectured that every connected graph of
maximum degree $\Delta\ge 3$ has odd-chromatic number at most $\Delta+1$. We
prove that this conjecture holds asymptotically: for every connected graph $G$
with maximum degree $\Delta$, $\chi_o(G)\le\Delta+O(\ln\Delta)$ as $\Delta \to
\infty$. We also prove that $\chi_o(G)\le\lfloor3\Delta/2\rfloor+2$ for every
$\Delta$. If moreover the minimum degree $\delta$ of $G$ is sufficiently large,
we have $\chi_o(G) \le \chi(G) + O(\Delta \ln \Delta/\delta)$ and $\chi_o(G) =
O(\chi(G)\ln \Delta)$. Finally, given an integer $h\ge 1$, we study the
generalisation of these results to $h$-odd colourings, where every vertex $v$
must have at least $\min \{\deg(v),h\}$ odd colours in its neighbourhood. Many
of our results are tight up to some multiplicative constant.


  Q-learning with value function approximation may have the poor performance
because of overestimation bias and imprecise estimate. Specifically,
overestimation bias is from the maximum operator over noise estimate, which is
exaggerated using the estimate of a subsequent state. Inspired by the recent
advance of deep reinforcement learning and Double Q-learning, we introduce the
decorrelated double Q-learning (D2Q). Specifically, we introduce the
decorrelated regularization item to reduce the correlation between value
function approximators, which can lead to less biased estimation and low
variance. The experimental results on a suite of MuJoCo continuous control
tasks demonstrate that our decorrelated double Q-learning can effectively
improve the performance.


  We calculate elastic scattering of positronium (Ps) by the Xe atom using the
recently developed pseudopotential method [I. I. Fabrikant and G. F. Gribakin,
Phys. Rev. A 90, 052717 (2014)] and review general features of Ps scattering
from heavier rare-gas atoms: Ar, Kr, and Xe. The total scattering cross section
is dominated by two contributions: elastic scattering and Ps ionization
(breakup). To calculate the Ps ionization cross sections we use the
binary-encounter method for Ps collisions with an atomic target. Our results
for the ionization cross section agree well with previous calculations carried
out in the impulse approximation. Our total Ps-Xe cross section, when plotted
as a function of the projectile velocity, exhibits similarity with the
electron-Xe cross section for the collision velocities higher than 0.8 a.u.,
and agrees very well with the measurements at Ps velocities above 0.5 a.u.


  We have observed extended emission physically associated with 15 out of 16 UC
HII regions with large ratios of single-dish to VLA fluxes. We discuss their
implications for the age problem of UC HII regions and the evolution of HII
regions.


  We theoretically investigate the dynamics of atomic domain walls (DWs) in
antiferromagnets driven by a spin-orbit field. For a DW with the width of a few
lattice constants, we identify a Peierls-like pinning effect, with the
depinning field exponentially decaying with the DW width, so that a spin-orbit
field moderately larger than the threshold can drive the propagation of an
atomic DW in a step-wise manner. For a broad DW, the Peierls pinning is
negligibly small. However, the external spin-orbit field can induce a fast DW
propagation, accompanied by a significant shrinking of its width down to atomic
scales. Before stepping into the pinning region, noticeable spin waves are
emitted at the tail of the DW. The spin-wave emission event not only broadens
the effective width of the DW, but also pushes the DW velocity over the
magnonic barrier, which is generally believed to be the relativistic limit of
the DW speed. While the existing dynamic theory based on the continuum
approximation fails in the atomic scale, we develop an energy conversion theory
to interpret the DW dynamics beyond the relativistic limit.


  We derive new bounds on Lorentz violations in the electron sector from
existing data on high-energy astrophysical sources. Synchrotron and inverse
Compton data give precisely complementary constraints. The best bound on a
specific combination of electron Lorentz-violating coefficients is at the 6 x
10^(-20) level, and independent bounds are available for all the
Lorentz-violating c coefficients at the 2 x 10^(-14) level or better. This
represents an improvement in some bounds by fourteen orders of magnitude.


  An initial-value problem for an ordinary differential equation of the first
order, is considered. It is supposed that the right-hand side of the equation
is a continuous function defined on a set consisting of an open set and a part
of its bound. Sufficient conditions of the existence and of non-existence of a
solution through initial point belonging to the boundary part of the set of
definition, are presented.


  As the field of connectomics has matured, it has expanded from mapping the
existence of connections between brain components to measuring the strength of
connections. This information is increasingly accessible via methodologies such
as pairing functional magnetic resonance (MR) imaging and MR tractography in
the same human subject, as well as novel methods in non-human animals using
optogenetics. Systems and network neuroscience have in recent years focused
extensively on explaining correlation patterns of functional activity in the
brain in terms of the degree of connectedness of brain components, the
so-called functional connectivity-structural connectivity relationship (SC-FC).
What has been surprising has been how low the SC-FC correlations are. Why is it
that brain parts that are more well-connected appear not to engender more
correlated activity between them? Several explanations have been proposed but
one possibility has not been considered: perhaps more neural activity doesn't
imply more functional involvement. This article examines this possibility and
proposes a new general framework for understanding brain network dynamics based
on the design constraints of large-scale network communication systems. With
this new perspective, we may start to answer the article's main question, and
perhaps others.


  We investigate the magnetic response of nematic superconductors, presenting a
new approach to find vortex and skyrmion structures beyond
symmetry-constraining ans\"atze. Using this approach we show that nematic
superconductors form distinctive skyrmion stripes. Our approach lends itself to
accurate determination of the field distribution for muon spin rotation probes.
We use this to show that the skyrmion structure manifests as a double peak in
the field distribution, markedly different from the signal of standard vortex
lattices.


  We study chiral symmetry breaking for relativistic fermions, described by a
parity violating Lagrangian in 2+1-dimensions, in the presence of a heat bath
and a uniform external magnetic field. Working within their four-component
formalism allows for the inclusion of both parity-even and -odd mass terms.
Therefore, we can define two types of fermion anti-fermion condensates. For a
given value of the magnetic field, there exist two different critical
temperatures which would render one of these condensates identically zero,
while the other would survive. Our analysis is completely general: it requires
no particular simplifying hierarchy among the energy scales involved, namely,
bare masses, field strength and temperature. However, we do reproduce some
earlier results, obtained or anticipated in literature, corresponding to
special kinematical regimes for the parity conserving case. Relating the chiral
condensate to the one-loop effective Lagrangian, we also obtain the
magnetization and the pair production rate for different fermion species in a
uniform electric field through the replacement $B\to-iE$.


  The existence of efficient ion acceleration regimes in collective
laser-plasma interactions opens up the possibility to develop high-energy
physics facilities in conjunction with projects for inertial confinement
nuclear fusion (ICF) and neutron spallation sources. In this paper, we show
that the pulse compression requests to make operative these acceleration
mechanisms do not fall in contradiction with current technologies for high
repetition rate ICF drivers. In particular, we discuss explicitly a solution
that exploits optical parametric chirped pulse amplification and the intrinsic
modularity of the lasers aimed at ICF.


  Some recent publications by authors from the University of Maryland analyse
the fluctuations of multi-port model parameters in stochastic environments.
These authors use random matrix theory (RMT) for estimates concerning
eigenfunction expansions in cavities which show so-called ``wave chaos.'' A
universal relation between the variances of the fluctuations of multi-port
impedance parameters, of the same type as we had observed experimentally for
scattering parameters in mode stirred chambers, is analysed in detail. However,
contrary to our own observations, these recent papers claim that only the
impedance fluctuations satisfy universal variance ratios. In the present paper,
we detail our own approach to the problem which is based on electromagnetic
scattering theory. It is shown that universal variance ratios are obtained, for
any type of multi-port model, when the environment of the multi-port system is
described by a scattering operator, which is statistically isotropic in a sense
we make precise below. The only condition on the system is that the radiation
power correlation between the ports considered vanishes. This is to be compared
to the diagonality of the radiation impedance required for the Maryland results
to be valid.