  Control over spontaneous emission rate is important for improving efficiency
in different semiconductor applications including lasers, LEDs and
photovoltaics. Usually, an emitter should be placed inside the cavity to
increase spontaneous emission rate, although it is technologically challenging.
Here we experimentally demonstrate a phenomenon of super-radiance observed in a
cavity-less periodic Bragg structure based on InAs monolayer-thick multiple
quantum wells (MQW). The collective super-radiant mode shows enhanced emission
rate for specific angles and frequencies. This behaviour correlates with the
calculations demonstrating individual spots of enhanced Purcell coefficient
near the Bragg condition curve. This study provides a perspective for
realization of surface emitting cavity-less lasers with distributed feedback.


  Many adaptive optics systems operate by measuring the distortion of the
wavefront in one wavelength range and performing the scientific observations in
a second, different wavelength range. One common technique is to measure
wavefront distortions at wavelengths <~1 micron while operating the science
instrument at wavelengths >~1 micron. The index of refraction of air decreases
sharply from shorter visible wavelengths to near-infrared wavelengths.
Therefore, because the adaptive optics system is measuring the wavefront
distortion in one wavelength range and the science observations are performed
at a different wavelength range, residual image motion occurs and the maximum
exposure time before smearing of the image can be significantly limited. We
demonstrate the importance of atmospheric differential refraction, present
calculations to predict the effect of atmospheric differential refraction, and
finally discuss the implications of atmospheric differential refraction for
several current and proposed observatories.


  We discuss the moduli space of nine dimensional N=1 supersymmetric
compactifications of M theory / string theory with reduced rank (rank 10 or
rank 2), exhibiting how all the different theories (including M theory
compactified on a Klein bottle and on a Mobius strip, the Dabholkar-Park
background, CHL strings and asymmetric orbifolds of type II strings on a
circle) fit together, and what are the weakly coupled descriptions in different
regions of the moduli space. We argue that there are two disconnected
components in the moduli space of theories with rank 2. We analyze in detail
the limits of the M theory compactifications on a Klein bottle and on a Mobius
strip which naively give type IIA string theory with an uncharged orientifold
8-plane carrying discrete RR flux. In order to consistently describe these
limits we conjecture that this orientifold non-perturbatively splits into a
D8-brane and an orientifold plane of charge (-1) which sits at infinite
coupling. We construct the M(atrix) theory for M theory on a Klein bottle (and
the theories related to it), which is given by a 2+1 dimensional gauge theory
with a varying gauge coupling compactified on a cylinder with specific boundary
conditions. We also clarify the construction of the M(atrix) theory for
backgrounds of rank 18, including the heterotic string on a circle.


  The wav2vec 2.0 and integrated spectro-temporal graph attention network
(AASIST) based countermeasure achieves great performance in speech
anti-spoofing. However, current spoof speech detection systems have fixed
training and evaluation durations, while the performance degrades significantly
during short utterance evaluation. To solve this problem, AASIST can be
improved to AASIST2 by modifying the residual blocks to Res2Net blocks. The
modified Res2Net blocks can extract multi-scale features and improve the
detection performance for speech of different durations, thus improving the
short utterance evaluation performance. On the other hand, adaptive large
margin fine-tuning (ALMFT) has achieved performance improvement in short
utterance speaker verification. Therefore, we apply Dynamic Chunk Size (DCS)
and ALMFT training strategies in speech anti-spoofing to further improve the
performance of short utterance evaluation. Experiments demonstrate that the
proposed AASIST2 improves the performance of short utterance evaluation while
maintaining the performance of regular evaluation on different datasets.


  We have found one of the possible conditions under which the Beltrami
equation with degeneration of ellipticity has a continuous solution of the
Sobolev class. With some additional requirements, this solution is homeomorphic


  This paper considers a family of second-order parabolic equations in
divergence form with rapidly oscillating and time-dependent periodic
coefficients and an interface between two periodic structures. Following a
framework initiated by Blanc, Le Bris and Lions and a generalized two-scale
expansion in divergence form of elliptic homogenization with an interface by
Josien, we can determine the effective (or homogenized) equation with the
coefficient matrix being piecewise constant and discontinuous across the
interface. Moreover, we obtain the $O(\varepsilon)$ convergence rates in
$L^{2(d+2)/{d}}_{x,t}$ with $\varepsilon$-smoothing method and the uniform
interior Lipschitz estimates via compactness argument.


  The objective of this paper is to formulate two distinct supersymmetric
(SUSY) extensions of the Gauss-Weingarten and Gauss-Codazzi (GC) equations for
conformally parametrized surfaces immersed in a Grassmann superspace, one in
terms of a bosonic superfield and the other in terms of a fermionic superfield.
We perform this analysis using a superspace-superfield formalism together with
a SUSY version of a moving frame on a surface. In constrast with the classical
case, where we have three GC equations, we obtain six such equations in the
bosonic SUSY case and four such equations in the fermionic SUSY case. In the
fermionic case the GC equations resemble the form of the classical GC
equations. We determine the Lie symmetry algebra of the classical GC equations
to be infinite-dimensional and perform a subalgebra classification of the
one-dimensional subalgebras of its largest finite-dimensional subalgebra. We
then compute superalgebras of Lie point symmetries of the bosonic and fermionic
SUSY GC equations respectively, and classify the one-dimensional subalgebras of
each superalgebra into conjugacy classes. We then use the symmetry reduction
method to find invariants, orbits and reduced systems for two one-dimensional
subalgebras for the classical case, two one-dimensional subalgebras for the
bosonic SUSY case and two one-dimensional subalgebras for the fermionic SUSY
case. We find explicit solutions of these reduced SUSY systems, which
correspond to different surfaces immersed in a Grassmann superspace. Within
this framework for the SUSY versions of the GC equations, a geometrical
interpretation of the results is discussed.


  We construct conforming finite elements for the spaces
$H(\text{sym}\,\text{Curl})$ and $H(\text{dev}\,\text{sym}\,\text{Curl})$.
Those are spaces of matrix-valued functions with symmetric or
deviatoric-symmetric $\text{Curl}$ in a Lebesgue space, and they appear in
various models of nonstandard solid mechanics. The finite elements are not
$H(\text{Curl})$-conforming. We show the construction, prove conformity and
unisolvence, and point out optimal approximation error bounds.


  The existing observational data on possible variations of fundamental
physical constants (FPC) confirm more or less confidently only a variability of
the fine structure constant $\alpha$ in space and time. A model construction
method is described, where variations of $\alpha$ and other FPCs (including the
gravitational constant $G$) follow from the dynamics of extra space-time
dimensions in the framework of curvature-nonlinear multidimensional theories of
gravity. An advantage of this method is a unified approach to variations of
different FPCs. A particular model explaining the observable variations of
$\alpha$ in space and time has been constructed. It comprises a FRW cosmology
with accelerated expansion, perturbed due to slightly inhomogeneous initial
data.


  We present a list of galaxies within 100 Mpc, which we call the Gravitational
Wave Galaxy Catalogue (GWGC), that is currently being used in follow-up
searches of electromagnetic counterparts from gravitational wave searches. Due
to the time constraints of rapid follow-up, a locally available catalogue of
reduced, homogenized data is required. To achieve this we used four existing
catalogues: an updated version of the Tully Nearby Galaxy Catalog, the Catalog
of Neighboring Galaxies, the V8k catalogue and HyperLEDA. The GWGC contains
information on sky position, distance, blue magnitude, major and minor
diameters, position angle, and galaxy type for 53,255 galaxies. Errors on these
quantities are either taken directly from the literature or estimated based on
our understanding of the uncertainties associated with the measurement method.
By using the PGC numbering system developed for HyperLEDA, the catalogue has a
reduced level of degeneracies compared to catalogues with a similar purpose and
is easily updated. We also include 150 Milky Way globular clusters. Finally, we
compare the GWGC to previously used catalogues, and find the GWGC to be more
complete within 100 Mpc due to our use of more up-to-date input catalogues and
the fact that we have not made a blue luminosity cut.


  Recent work has explored video action recognition as a video-text matching
problem and several effective methods have been proposed based on large-scale
pre-trained vision-language models. However, these approaches primarily operate
at a coarse-grained level without the detailed and semantic understanding of
action concepts by exploiting fine-grained semantic connections between actions
and body movements. To address this gap, we propose a contrastive
video-language learning framework guided by a knowledge graph, termed KG-CLIP,
which incorporates structured information into the CLIP model in the video
domain. Specifically, we construct a multi-modal knowledge graph composed of
multi-grained concepts by parsing actions based on compositional learning. By
implementing a triplet encoder and deviation compensation to adaptively
optimize the margin in the entity distance function, our model aims to improve
alignment of entities in the knowledge graph to better suit complex
relationship learning. This allows for enhanced video action recognition
capabilities by accommodating nuanced associations between graph components. We
comprehensively evaluate KG-CLIP on Kinetics-TPS, a large-scale action parsing
dataset, demonstrating its effectiveness compared to competitive baselines.
Especially, our method excels at action recognition with few sample frames or
limited training data, which exhibits excellent data utilization and learning
capabilities.


  Given a basic process algebra (BPA) and two stack symbols, the BPA
bisimilarity problem asks whether the two stack symbols are bisimilar. We show
that this problem is EXPTIME-hard.


  This paper formulates bottom-up visual saliency as center surround
conditional entropy and presents a fast and efficient technique for the
computation of such a saliency map. It is shown that the new saliency
formulation is consistent with self-information based saliency,
decision-theoretic saliency and Bayesian definition of surprises but also faces
the same significant computational challenge of estimating probability density
in very high dimensional spaces with limited samples. We have developed a fast
and efficient nonparametric method to make the practical implementation of
these types of saliency maps possible. By aligning pixels from the center and
surround regions and treating their location coordinates as random variables,
we use a k-d partitioning method to efficiently estimating the center surround
conditional entropy. We present experimental results on two publicly available
eye tracking still image databases and show that the new technique is
competitive with state of the art bottom-up saliency computational methods. We
have also extended the technique to compute spatiotemporal visual saliency of
video and evaluate the bottom-up spatiotemporal saliency against eye tracking
data on a video taken onboard a moving vehicle with the driver's eye being
tracked by a head mounted eye-tracker.


  We discuss new exact solutions to nonminimally extended Einstein-Yang-Mills
equations describing spherically symmetric static wormholes supported by the
gauge field of the Wu-Yang type in a dark energy environment. We focus on the
analysis of three types of exact solutions to the gravitational field
equations. Solutions of the first type relate to the model, in which the dark
energy is anisotropic, i.e., the radial and tangential pressures do not
coincide. Solutions of the second type correspond to the isotropic pressure
tensor; in particular, we discuss the exact solution, for which the dark energy
is characterized by the equation of state for a string gas. Solutions of the
third type describe the dark energy model with constant pressure and energy
density. For the solutions of the third type, we consider in detail the problem
of horizons and find constraints for the parameters of nonminimal coupling and
for the constitutive parameters of the dark energy equation of state, which
guarantee that the nonminimal wormholes are traversable.


  New technological advancements in wireless networks have enlarged the number
of connected devices. The unprecedented surge of data volume in wireless
systems empowered by artificial intelligence (AI) opens up new horizons for
providing ubiquitous data-driven intelligent services. Traditional cloudcentric
machine learning (ML)-based services are implemented by centrally collecting
datasets and training models. However, this conventional training technique
encompasses two challenges: (i) high communication and energy cost and (ii)
threatened data privacy. In this article, we introduce a comprehensive survey
of the fundamentals and enabling technologies of federated learning (FL), a
newly emerging technique coined to bring ML to the edge of wireless networks.
Moreover, an extensive study is presented detailing various applications of FL
in wireless networks and highlighting their challenges and limitations. The
efficacy of FL is further explored with emerging prospective beyond
fifth-generation (B5G) and sixth-generation (6G) communication systems. This
survey aims to provide an overview of the state-ofthe-art FL applications in
key wireless technologies that will serve as a foundation to establish a firm
understanding of the topic. Lastly, we offer a road forward for future research
directions.


  We prove three main results: all Langlands-Shahidi automorphic $L$-functions
over function fields are rational; after twists by highly ramified characters
our automorphic $L$-functions become polynomials; and, if $\pi$ is a globally
generic cuspidal automorphic representation of a split classical group or a
unitary group ${\bf G}_n$ and $\tau$ a cuspidal (unitary) automorphic
representation of a general linear group, then $L(s,\pi \times \tau)$ is
holomorphic for $\Re(s) > 1$ and has at most a simple pole at $s=1$. We also
prove the holomorphy and non-vanishing of automorphic exterior square,
symmetric square and Asai L-functions for $\Re(s) > 1$. Finally, we complete
previous results on functoriality for the classical groups over function
fields.


  We present results of MUSE-ALMA Halos, an ongoing study of the Circumgalactic
Medium (CGM) of galaxies ($z \leq$ 1.4). Using multi-phase observations we
probe the neutral, ionised and molecular gas in a sub-sample containing six
absorbers and nine associated galaxies in the redshift range $z \sim 0.3-0.75$.
Here, we give an in-depth analysis of the newly CO-detected galaxy Q2131-G1
($z=0.42974$), while providing stringent mass and depletion time limits for the
non-detected galaxies. Q2131-G1 is associated with an absorber with column
densities of $\textrm{log}(N_\textrm{HI}/\textrm{cm}^{-2}) \sim 19.5$ and
$\textrm{log}(N_{\textrm{H}_2}/\textrm{cm}^{-2}) \sim 16.5$, has a star
formation rate of $\textrm{SFR} = 2.00 \pm 0.20 \; \textrm{M}_{\odot}
\textrm{yr}^{-1}$, a dark matter fraction of $f_\textrm{DM}(r_{1/2}) = 0.24 -
0.54$ and a molecular gas mass of $M_\textrm{mol} = 3.52 ^{+3.95}_{-0.31}
\times 10^9 \; \textrm{M}_{\odot}$ resulting in a depletion time of
$\tau_\textrm{dep} < 4.15 \; \textrm{Gyr}$. Kinematic modelling of both the CO
(3--2) and [OIII] $\lambda 5008$ emission lines of Q2131-G1 shows that the
molecular and ionised gas phases are well aligned directionally and that the
maximum rotation velocities closely match. These two gas phases within the disk
are strongly coupled. The metallicity, kinematics and orientation of the atomic
and molecular gas traced by a two-component absorption feature is consistent
with being part of the extended rotating disk with a well-separated additional
component associated with infalling gas. Compared to emission-selected samples,
we find that HI-selected galaxies have high molecular gas masses given their
low star formation rate. We consequently derive high depletion times for these
objects.


  We address two important questions in gravitational-wave astronomy. What is
the astrophysical formation scenario leading to black-hole binary mergers? Did
some of the merging black holes form hierarchically through previous
generations of mergers? Leveraging fast-to-generate astrophysical simulations
from the rapster code and a random forest algorithm, we develop a pipeline to
accurately classify the most likely generation and formation scenario of
dynamically formed BHs on an event-by-event basis. We test our framework on
four merger events with features suggesting a dynamical origin: the large total
mass event GW190521, GW190412 (with large mass asymmetry), and two events with
effective spins antialigned with the orbital angular momentum (GW191109 and
GW200225). Within the models we consider, and assuming these events to be
formed dynamically, we find that one of the component black holes in GW190521
formed from a previous merger with high probability ($\gtrsim 85\%$). GW190521,
GW191109 and GW200225 are compatible with formation through three-body
interactions, while the most likely formation channel for GW190412 are two-body
captures. We also rule out that GW191109 contains only first-generation black
holes with a probability of 97$\%$. Our pipeline could be useful to identify
the evolutionary path of individual GW observations once it is trained on more
comprehensive sets of binary formation simulations.


  We present an overview of the recent abundant measurements for charm
production at RHIC. The significant information of charm cross sections in
different collision system at 200 GeV and charmed hadron freeze-out and flow
properties extracted from these measurements are presented. The heavy flavor
energy loss in the medium and heavy flavor related azimuthal correlations in
heavy ion collisions are also discussed.


  Low-Rank Representation (LRR) highly suffers from discarding the locality
information of data points in subspace clustering, as it may not incorporate
the data structure nonlinearity and the non-uniform distribution of
observations over the ambient space. Thus, the information of the observational
density is lost by the state-of-art LRR models, as they take a constant number
of adjacent neighbors into account. This, as a result, degrades the subspace
clustering accuracy in such situations. To cope with deficiency, in this paper,
we propose to consider a hypergraph model to facilitate having a variable
number of adjacent nodes and incorporating the locality information of the
data. The sparsity of the number of subspaces is also taken into account. To do
so, an optimization problem is defined based on a set of regularization terms
and is solved by developing a tensor Laplacian-based algorithm. Extensive
experiments on artificial and real datasets demonstrate the higher accuracy and
precision of the proposed method in subspace clustering compared to the
state-of-the-art methods. The outperformance of this method is more revealed in
presence of inherent structure of the data such as nonlinearity, geometrical
overlapping, and outliers.


  We present results of inelastic neutron scattering experiments performed for
the compound Magnetic and neutron spectroscopic properties of the tetrameric
nickel compound $[Mo_{12}O_{28}(\mu_2-OH)_9(\mu_3-OH)_3{Ni(H_2O)_3}_4] $\cdot$
13H_2O$, which is a molecular magnet with antiferromagnetically coupled Ni2+
ions forming nearly ideal tetrahedra in a diamagnetic molybdate matrix. The
neutron spectroscopic data are analyzed together with high-field magnetization
data (taken from the literature) which exhibit four steps at non-equidistant
field intervals. The experimental data can be excellently described by
antiferromagnetic Heisenberg-type exchange interactions as well as an axial
single-ion anisotropy within a distorted tetrahedron of Ni2+ ions characterized
by X-ray single-crystal diffraction. Our analysis contrasts to recently
proposed models which are based on the existence of extremely large biquadratic
(and three-ion) exchange interactions and/or on a strong field dependence of
the Heisenberg coupling parameters.


  The strategies adopted by individuals to select relevant information to pass
on are central to understanding problem solving by groups. Here we use
agent-based simulations to revisit a cooperative problem-solving scenario where
the task is to find the common card in decks distributed to the group members.
The agents can display only a sample of their cards and we explore different
strategies to select those samples based on the confidences assigned to the
cards. An agent's confidence that a particular card is the correct one is given
by the number of times it observed that card in the decks of the other agents.
We use a Gibbs distribution to select the card samples with the temperature
measuring the strength of a noise that prevents the agents to correctly rank
the cards. The group is guaranteed to find the common card in all runs solely
in the infinite temperature limit, where the cards are sampled regardless of
their confidences. In this case, we obtain the scaling form of the time
constant that characterizes the asymptotic exponential decay of the failure
probability. For finite time, however, a finite temperature yields a
probability of failure that is several orders of magnitude lower than in the
infinite temperature limit. The available experimental results are consistent
with the decision-making model for finite temperature only.


  Since the development of Boson sampling, there has been a quest to construct
more efficient and experimentally feasible protocols to test the computational
complexity of sampling from photonic states. In this paper we interpret and
extend the results presented in [Phys. Rev. Lett. 119, 170501 (2017)]. We
derive an expression that relates the probability to measure a specific photon
output pattern from a Gaussian state to the \textit{hafnian} matrix function
and us it to design a Gaussian Boson sampling protocol. Then, we discuss the
advantages that this protocol has relative to other photonic protocols and the
experimental requirements for Gaussian Boson Sampling. Finally, we relate it to
the previously most general protocol, Scattershot Boson Sampling [Phys. Rev.
Lett. 113, 100502 (2014)]


  We consider existence of periodic boundary value problems of nonlinear second
order ordinary differential equations. Under certain half Lipschitzian type
conditions several existence results are obtained. As applications positive
periodic solutions of some $\phi$-Laplacian type equations and Duffing type
equations are investigated.


  The angular dependence of the gravitational radiation emitted in compact
binary mergers and gravitational collapse is usually separated using
spin-weighted spherical harmonics ${}_sY_{\ell m}$ of spin weight $s$, that
reduce to the ordinary spherical harmonics $Y_{\ell m}$ when $s=0$. Teukolsky
first showed that the perturbations of the Kerr black hole that may be produced
as a result of these events are separable in terms of a different set of
angular functions: the spin-weighted spheroidal harmonics ${}_sS_{\ell m n}$,
where $n$ denotes the "overtone index" of the corresponding Kerr quasinormal
mode frequency $\omega_{\ell m n}$. In this paper we compute the complex-valued
scalar products of the ${}_sS_{\ell m n}$'s with the ${}_sY_{\ell m}$'s
("spherical-spheroidal mixing coefficients") and with themselves
("spheroidal-spheroidal mixing coefficients") as functions of the dimensionless
Kerr parameter $j$. Tables of these coefficients and analytical fits of their
dependence on $j$ are available online for use in gravitational-wave source
modeling and in other applications of black-hole perturbation theory.


  Context: Potentially hazardous asteroids (PHA) in Earth-crossing orbits pose
a constant threat to life on Earth. Several mitigation methods have been
proposed, and the most feasible technique appears to be the disintegration of
the impactor and the generation of a fragment cloud by explosive penetrators at
interception. However, mitigation analyses tend to neglect the effect of
orbital dynamics on the trajectory of fragments.
  Aims: We aim to study the effect of orbital dynamics of the impactor's cloud
on the number of fragments that hit the Earth, assuming different interception
dates. We investigate the effect of self-gravitational cohesion and the axial
rotation of the impactor.
  Methods: We computed the orbits of 10^5 fragments with a high-precision
direct N-body integrator of the eighth order, running on GPUs. We considered
orbital perturbations from all large bodies in the Solar System and the
self-gravity of the cloud fragments.
  Results: Using a series of numerical experiments, we show that orbital shear
causes the fragment cloud to adopt the shape of a triaxial ellipsoid. The shape
and alignment of the triaxial ellipsoid are strongly modulated by the cloud's
orbital trajectory and, hence, the impact cross-section of the cloud with
respect to the Earth. Therefore, the number of fragments hitting the Earth is
strongly influenced by the orbit of the impactor and the time of interception.
A minimum number of impacts occur for a well-defined orientation of the
impactor rotational axis, depending on the date of interception.
  Conclusions: To minimise the lethal consequences of an PHA's impact, a
well-constrained interception timing is necessary. A too-early interception may
not be ideal for PHAs in the Apollo or Aten groups. Thus, we find that the best
time to intercept PHA is when it is at the pericentre of its orbit.


  This paper proposes a new method to propagate uncertainties undergoing
nonlinear dynamics using the Koopman Operator (KO). Probability density
functions are propagated directly using the Koopman approximation of the
solution flow of the system, where the dynamics have been projected on a
well-defined set of basis functions. The prediction technique is derived
following both the analytical (Galerkin) and numerical (EDMD) derivation of the
KO, and a least square reduction algorithm assures the recursivity of the
proposed methodology.


  A deep neural network (DNN) that can reliably model muscle responses from
corresponding brain stimulation has the potential to increase knowledge of
coordinated motor control for numerous basic science and applied use cases.
Such cases include the understanding of abnormal movement patterns due to
neurological injury from stroke, and stimulation based interventions for
neurological recovery such as paired associative stimulation. In this work,
potential DNN models are explored and the one with the minimum squared errors
is recommended for the optimal performance of the M2M-Net, a network that maps
transcranial magnetic stimulation of the motor cortex to corresponding muscle
responses, using: a finite element simulation, an empirical neural response
profile, a convolutional autoencoder, a separate deep network mapper, and
recordings of multi-muscle activation. We discuss the rationale behind the
different modeling approaches and architectures, and contrast their results.
Additionally, to obtain a comparative insight of the trade-off between
complexity and performance analysis, we explore different techniques, including
the extension of two classical information criteria for M2M-Net. Finally, we
find that the model analogous to mapping the motor cortex stimulation to a
combination of direct and synergistic connection to the muscles performs the
best, when the neural response profile is used at the input.


  We perform two-dimensional hydrodynamical simulations of slowly rotating
accretion flows in the region of $ 0.01-7\, \mathrm{pc} $ around a supermassive
black holes with $ M_\mathrm{BH} = 10^{8} M_{\odot} $. The accretion flow is
irradiated by the photons from the central active galactic nucleus (AGN). In
addition to the direct radiation from the AGN, we have also included the
"re-radiation", i.e., the locally produced radiation by Thomson scattering,
line and bremsstrahlung radiation. Compare to our previous work, we have
improved the calculation of radiation force due to the Thomson scattering of
X-ray photons from the central AGN. We find that this improvement can
significantly increase the mass flux and velocity of outflow. We have compared
the properties of outflow --- including mass outflow rate, velocity, and
kinetic luminosity of outflow --- in our simulation with the observed
properties of outflow in AGNs and found that they are in good consistency. This
implies that the combination of line and re-radiation forces is the possible
origin of observed outflow in luminous AGNs.


  Gradients of voltage, pressure, temperature, and salinity can transport
objects in micro- and nanofluidic systems by well known mechanisms. Here we
report the discovery of a transport effect driven by viscosity gradients, which
cause an ionic current to flow inside a glass nanofluidic channel. Measurements
of the current are well described by a simple model wherein counterions in the
electric double layers near the surfaces drift in the direction of decreasing
viscosity with a drift speed equal to the gradient of the ions' local
diffusivity. Drift in a viscosity gradient is a consequence of multiplicative
(state-dependent) noise, which results from a particle's thermal fluctuations
depending on its position. This surprisingly large effect, measured in a highly
controlled nanofluidic environment, reveals fundamental behavior that is
relevant to a broad range of systems.


  We present a triple-Regge analysis of the available pp --> p + X high-energy
data accounting for absorptive corrections. We describe a model for high-energy
soft interactions which includes the whole set of multi-Pomeron (n --> m)
vertices, and give predictions for the LHC.


  We extend the construction of so-called encapsulated global
summation-by-parts operators to the general case of a mesh which is not
boundary conforming. Owing to this development, energy stable discretizations
of nonlinear and variable coefficient initial boundary value problems can be
formulated in simple and straightforward ways using high-order accurate
operators of generalized summation-by-parts type. Encapsulated features on a
single computational block or element may include polynomial bases, tensor
products as well as curvilinear coordinate transformations. Moreover, through
the use of inner product preserving interpolation or projection, the global
summation-by-parts property in extended to arbitrary multi-block or
multi-element meshes with non-conforming nodal interfaces.


  CUR matrix decomposition is a randomized algorithm that can efficiently
compute the low rank approximation for a given rectangle matrix. One limitation
with the existing CUR algorithms is that they require an access to the full
matrix A for computing U. In this work, we aim to alleviate this limitation. In
particular, we assume that besides having an access to randomly sampled d rows
and d columns from A, we only observe a subset of randomly sampled entries from
A. Our goal is to develop a low rank approximation algorithm, similar to CUR,
based on (i) randomly sampled rows and columns from A, and (ii) randomly
sampled entries from A. The proposed algorithm is able to perfectly recover the
target matrix A with only O(rn log n) number of observed entries. In addition,
instead of having to solve an optimization problem involved trace norm
regularization, the proposed algorithm only needs to solve a standard
regression problem. Finally, unlike most matrix completion theories that hold
only when the target matrix is of low rank, we show a strong guarantee for the
proposed algorithm even when the target matrix is not low rank.


  We discuss the role of the impact--parameter dependent quantities. Their use
along with the available experimental data on elastic scattering at the LHC
could serve for an additional insight into the asymptotics.


  In the quest to understand QCD there are a number of outstanding challenges.
Here we focus on one of these, namely what one expects to happen to the
structure of a hadron when it is immersed in a nuclear medium. We argue that
the necessary changes in the quark structure are intimately related to nuclear
binding and saturation. Some of the potential experimental implications of
these ideas are discussed.


  The Lie linearizability criteria are extended to complex functions for
complex ordinary differential equations. The linearizability of complex
ordinary differential equations is used to study the linearizability of
corresponding systems of two real ordinary differential equations. The
transformations that map a system of two nonlinear ordinary differential
equations into systems of linear ordinary differential equations are obtained
from complex transformations. Invariant criteria for linearization are given
for second order complex ordinary differential equations in terms of the
coefficients of the equations, as well as the corresponding real system, which
provide procedures for writing down the solutions of the equations.
Illustrative examples are given and discussed.


  We investigate an interesting correlation among dark matter phenomenology,
neutrino mass generation and GUT baryogenesis, based on the scotogenic model.
The model contains additional right-handed neutrinos $N$ and a second Higgs
doublet $\Phi$, both of which are odd under an imposed $Z_2$ symmetry. The
neutral component of $\Phi$, i.e. the lightest of the $Z_2$-odd particles, is
the dark matter candidate. Due to a Yukawa coupling involving $\Phi$, $N$ and
the Standard Model leptons, the lepton asymmetry is converted into the dark
matter asymmetry so that a non-vanishing $B-L$ asymmetry can arise from
$(B-L)$-conserving GUT baryogenesis, leading to a nonzero baryon asymmetry
after the sphalerons decouple. On the other hand, $\Phi$ can also generate
neutrino masses radiatively. In other words, the existence of $\Phi$ as the
dark matter candidate resuscitates GUT baryogenesis and realizes neutrino
masses.


  We investigate the optimality for model selection of the so-called slope
heuristics, $V$-fold cross-validation and $V$-fold penalization in a
heteroscedastic with random design regression context. We consider a new class
of linear models that we call strongly localized bases and that generalize
histograms, piecewise polynomials and compactly supported wavelets. We derive
sharp oracle inequalities that prove the asymptotic optimality of the slope
heuristics---when the optimal penalty shape is known---and $V$ -fold
penalization. Furthermore, $V$-fold cross-validation seems to be suboptimal for
a fixed value of $V$ since it recovers asymptotically the oracle learned from a
sample size equal to $1-V^{-1}$ of the original amount of data. Our results are
based on genuine concentration inequalities for the true and empirical excess
risks that are of independent interest. We show in our experiments the good
behavior of the slope heuristics for the selection of linear wavelet models.
Furthermore, $V$-fold cross-validation and $V$-fold penalization have
comparable efficiency.


  We report on the coexistence of powerful gas outflows observed in millimeter
and X-ray data of the Radio-Loud Narrow Line Seyfert 1 Galaxy IRAS 17020+4544.
Thanks to the large collecting power of the Large Millimeter Telescope, a
prominent line arising from the 12CO(1-0) transition was revealed in recent
observations of this source. The complex profile is composed by a narrow
double-peak line and a broad wing. While the double-peak structure may be
arising in a disk of molecular material, the broad wing is interpreted as the
signature of a massive outflow of molecular gas with an approximate bulk
velocity of -660 km/s. This molecular wind is likely associated to a
multi-component X-ray Ultra-Fast Outflow with velocities reaching up to ~0.1c
and column densities in the range 10^{21-23.9} cm^-2 that was reported in the
source prior to the LMT observations. The momentum load estimated in the two
gas phases indicates that within the observational uncertainties the outflow is
consistent with being propagating through the galaxy and sweeping up the gas
while conserving its energy. This scenario, which has been often postulated as
a viable mechanism of how AGN feedback takes place, has so far been observed
only in ULIRGs sources. IRAS 17020+4544 with bolometric and infrared luminosity
respectively of 5X10^{44} erg/s and 1.05X10^{11} L_sun appears to be an example
of AGN feedback in a NLSy1 Galaxy (a low power AGN). New proprietary
multi-wavelength data recently obtained on this source will allow us to
corroborate the proposed hypothesis.


  The characterisation of the brain as a "connectome", in which the connections
are represented by correlational values across timeseries and as summary
measures derived from graph theory analyses, has been very popular in the last
years. However, although this representation has advanced our understanding of
the brain function, it may represent an oversimplified model. This is because
the typical fMRI datasets are constituted by complex and highly heterogeneous
timeseries that vary across space (i.e., location of brain regions). We compare
various modelling techniques from deep learning and geometric deep learning to
pave the way for future research in effectively leveraging the rich spatial and
temporal domains of typical fMRI datasets, as well as of other similar
datasets. As a proof-of-concept, we compare our approaches in the homogeneous
and publicly available Human Connectome Project (HCP) dataset on a supervised
binary classification task. We hope that our methodological advances relative
to previous "connectomic" measures can ultimately be clinically and
computationally relevant by leading to a more nuanced understanding of the
brain dynamics in health and disease. Such understanding of the brain can
fundamentally reduce the constant specialised clinical expertise in order to
accurately understand brain variability.


  We have searched for bound states in the pion-Lambda-nucleon system by
solving the nonrelativistic Faddeev equations, as well as a relativistic
version, with input separable pion-nucleon, pion-Lambda, and Lambda-nucleon
interactions. A bound-state solution, driven by the Delta(1232) and Sigma(1385)
p-wave meson-baryon resonances, was found in the channel (I,JP)=(3/2,2+),
provided the Lambda lab momentum at which the Lambda-nucleon S=1,L=0,J=1 phase
shift becomes negative is larger than about 750-800 MeV/c. Other strange and
charmed pion-baryon-baryon systems that might have bound states of a similar
nature are listed.


  We demonstrate a z-axis accelerometer which uses waveguided light to sense
proof mass displacement. The accelerometer consists of two stacked rings (one
fixed and one suspended above it) forming an optical ring resonator. As the
upper ring moves due to z-axis acceleration, the effective refractive index
changes, changing the optical path length and therefore the resonant frequency
of the optical mode. The optical transmission changes with acceleration when
the laser is biased on the side of the optical resonance. This silicon nitride
"Cavity-enhanced OptoMechanical Accelerometer" (COMA) has a sensitivity of 22
percent-per-g optical modulation for our highest optical quality factor (Q_o)
devices


  The anomalous hysteresis is reported in photo current density-voltage (J-V)
curves of perovskite solar cells. The origins responsible for hysteresis are
primarily attributed to ferroelectricity, trapping/de-trapping, and ions
migration. Meanwhile, a switchable photovoltaic effect is disclosed in lateral
structure perovskite solar cells, where a p-i-n structure is formed after
poling the device with a reverse bias. Considering the normal sandwiched
structure of perovskite solar cells, i.e. the intrinsic perovskite layer is
situated in an electric field built by p-type (Spiro-OMeTAD) and n-type (TiO2)
layers, the poling process also works in such devices. The migration of ions
will induce a new electric field with opposite direction as inherent built-in
electric field. As a consequence, less collection of photogenerated carriers is
predicted due to the built-in electric field is partially screened. Here, the
ions induced electric field is experimentally demonstrated by exploring the
external quantum efficiency (EQE) spectra under various forward voltage biases.
The anomalous hysteresis observed on J-V curves is explained based on the
insight of ions migrations under bias voltage. The external applied voltage
presents significant influence on the stability of solar cells. Meanwhile, a
novel phenomenon of negative capacitance is initially detected at low
frequency, which is ascribed to the position reversal of negatively and
positively charged ions under forward bias.


  We consider well-quasi-order for classes of permutation graphs which omit
both a path and a clique. Our principle result is that the class of permutation
graphs omitting $P_5$ and a clique of any size is well-quasi-ordered. This is
proved by giving a structural decomposition of the corresponding permutations.
We also exhibit three infinite antichains to show that the classes of
permutation graphs omitting $\{P_6,K_6\}$, $\{P_7,K_5\}$, and $\{P_8,K_4\}$ are
not well-quasi-ordered.


  Continuing the study of perverse sheaves on the nilpotent cone of a
$\mathbb{Z}/m$-graded Lie algebra initiated by Lusztig--Yun, we study in this
work the parabolic induction and introduce the notion of supercuspidal sheaves
on the nilpotent cone. One of our main results shows that simple perverse
sheaves with nilpotent singular support (called bi-orbital sheaves) are
produced by parabolic induction from supercuspidal sheaves. As application, we
provide a proof for a theorem announced by I. Grojnowski on the parametrisation
of simple modules of affine Hecke algebras at roots of unity via
Deligne--Langlands--Lusztig parameters with nilpotent singular support.


  Despite remarkable progress in text-to-SQL semantic parsing in recent years,
the performance of existing parsers is still far from perfect. Specifically,
modern text-to-SQL parsers based on deep learning are often over-confident,
thus casting doubt on their trustworthiness when deployed for real use. In this
paper, we propose a parser-independent error detection model for text-to-SQL
semantic parsing. Using a language model of code as its bedrock, we enhance our
error detection model with graph neural networks that learn structural features
of both natural language questions and SQL queries. We train our model on
realistic parsing errors collected from a cross-domain setting, which leads to
stronger generalization ability. Experiments with three strong text-to-SQL
parsers featuring different decoding mechanisms show that our approach
outperforms parser-dependent uncertainty metrics. Our model could also
effectively improve the performance and usability of text-to-SQL semantic
parsers regardless of their architectures. (Our implementation is available at
https://github.com/OSU-NLP-Group/Text2SQL-Error-Detection)


  We present a new method for manufacturing complex-valued harmonic morphisms
from a wide class of Riemannian Lie groups. This yields new solutions from an
important family of homogeneous Hadamard manifolds. We also give a new method
for constructing left-invariant foliations on a large class of Lie groups
producing harmonic morphisms


  This paper presents a novel anomaly detection methodology termed Statistical
Aggregated Anomaly Detection (SAAD). The SAAD approach integrates advanced
statistical techniques with machine learning, and its efficacy is demonstrated
through validation on real sensor data from a Hardware-in-the-Loop (HIL)
environment within the automotive domain. The key innovation of SAAD lies in
its ability to significantly enhance the accuracy and robustness of anomaly
detection when combined with Fully Connected Networks (FCNs) augmented by
dropout layers. Comprehensive experimental evaluations indicate that the
standalone statistical method achieves an accuracy of 72.1%, whereas the deep
learning model alone attains an accuracy of 71.5%. In contrast, the aggregated
method achieves a superior accuracy of 88.3% and an F1 score of 0.921, thereby
outperforming the individual models. These results underscore the effectiveness
of SAAD, demonstrating its potential for broad application in various domains,
including automotive systems.


  Relying on paired synthetic data, existing learning-based Computational
Aberration Correction (CAC) methods are confronted with the intricate and
multifaceted synthetic-to-real domain gap, which leads to suboptimal
performance in real-world applications. In this paper, in contrast to improving
the simulation pipeline, we deliver a novel insight into real-world CAC from
the perspective of Unsupervised Domain Adaptation (UDA). By incorporating
readily accessible unpaired real-world data into training, we formalize the
Domain Adaptive CAC (DACAC) task, and then introduce a comprehensive Real-world
aberrated images (Realab) dataset to benchmark it. The setup task presents a
formidable challenge due to the intricacy of understanding the target
aberration domain. To this intent, we propose a novel Quntized Domain-Mixing
Representation (QDMR) framework as a potent solution to the issue. QDMR adapts
the CAC model to the target domain from three key aspects: (1) reconstructing
aberrated images of both domains by a VQGAN to learn a Domain-Mixing Codebook
(DMC) which characterizes the degradation-aware priors; (2) modulating the deep
features in CAC model with DMC to transfer the target domain knowledge; and (3)
leveraging the trained VQGAN to generate pseudo target aberrated images from
the source ones for convincing target domain supervision. Extensive experiments
on both synthetic and real-world benchmarks reveal that the models with QDMR
consistently surpass the competitive methods in mitigating the
synthetic-to-real gap, which produces visually pleasant real-world CAC results
with fewer artifacts. Codes and datasets will be made publicly available.


  An internal field induced resonant intensity enhancement of Raman scattering
of phonon excitations in InAs nanowires is reported. The experimental
observation is in good agreement with the simulated results for the scattering
of light under varying incident wavelengths, originating from the enhanced
internal electric field in an infinite dielectric cylinder. Our analysis
demonstrates the combined effect of the first higher lying direct band gap
energy (E1) and the refractive index of the InAs nanowires in the internal
field induced resonant Raman scattering. Furthermore, the difference in the
relative contribution of electro-optic effect and deformation potential in
Raman scattering of nanowires and bulk InAs over a range of excitation energies
is discussed by comparing the intensity ratio of their LO and TO phonon modes.


  I present an argument, based on the topology of the universe, why there are
three generations of fermions. The argument implies a preferred unified gauge
group of SU(5), but with SO(10) representations of the fermions. The breaking
pattern $SU(5) \to SU(3) \times SU(2) \times U(1)$ is preferred over the
pattern $SU(5) \to SU(4) \times U(1)$. On the basis of the argument one expects
an asymmetry in the microwave data, which might have been detected already.


  We propose a new sheaf-theoretical method for the calculation of the
monodromy zeta functions of Milnor fibrations. As an application, classical
formulas of Kushnirenko and Varchenko etc. concerning polynomials on $\CC^n$
will be generalized to polynomial functions on any toric variety.


  The main result of this paper is a sharp upper bound on the first positive
eigenvalue of Dirac operators in two dimensional simply connected $C^3$-domains
with infinite mass boundary conditions. This bound is given in terms of a
conformal variation, explicit geometric quantities and of the first eigenvalue
for the disk. Its proof relies on the min-max principle applied to the squares
of these Dirac operators. A suitable test function is constructed by means of a
conformal map. This general upper bound involves the norm of the derivative of
the underlying conformal map in the Hardy space $\mathcal{H}^2(\mathbb{D})$.
Then, we apply known estimates of this norm for convex and for nearly circular,
star-shaped domains in order to get explicit geometric upper bounds on the
eigenvalue. These bounds can be re-interpreted as reverse Faber-Krahn-type
inequalities under adequate geometric constraints.


  Modern distributed systems are highly dynamic and scalable, requiring
monitoring solutions that can adapt to rapid changes. Monitoring systems that
rely on external probes can only achieve adaptation through expensive
operations such as deployment, undeployment, and reconfiguration. This poster
paper introduces ReProbes, a class of adaptive monitoring probes that can
handle rapid changes in data collection strategies. ReProbe offers controllable
and configurable self-adaptive capabilities for data transmission, collection,
and analysis methods. The resulting architecture can effectively enhance probe
adaptability when qualitatively compared to state-of-the-art monitoring
solutions.


  We consider a regularization problem whose objective function consists of a
convex fidelity term and a regularization term determined by the $\ell_1$ norm
composed with a linear transform. Empirical results show that the
regularization with the $\ell_1$ norm can promote sparsity of a regularized
solution. It is the goal of this paper to understand theoretically the effect
of the regularization parameter on the sparsity of the regularized solutions.
We establish a characterization of the sparsity under the transform matrix of
the solution. When the fidelity term has a special structure and the transform
matrix coincides with a identity matrix, the resulting characterization can be
taken as a regularization parameter choice strategy with which the
regularization problem has a solution having a sparsity of a certain level. We
study choices of the regularization parameter so that the regularization term
alleviates the ill-posedness and promote sparsity of the resulting regularized
solution. Numerical experiments demonstrate that choices of the regularization
parameters can balance the sparsity of the solutions of the regularization
problem and its approximation to the minimizer of the fidelity function.


  Possible instrumental set--ups for the measurement of CMB polarization are
reviewed in this article. We discuss existing and planned instruments, putting
special emphasis on observational, instrumental, and data processing issues for
the detection of very low polarization signals of prime cosmological interest.
A short prospective summary is included.


  DASI has ended a 34-year quest to detect the CMB polarization, sounding the
starting gun for a new race to peer further back in time, with more precision
than ever before. Many more CMB polarization experiments are in progress or
planned. NASA's recently launched Microwave Anisotropy Probe (MAP) should
detect the large-angle polarization induced by early star formation. This
should be followed by increasingly precise ground and balloon experiments
leading to the Launch of the European Space Agency's Planck satellite in 2007.
If the recent past is any indication, studies of the CMB will continue to
advance cosmology, even after Planck.


  Based on the entropy-area relation from Nouicer's generalised uncertainty
principle (GUP), we derive the GUP modified Friedmann equations from the first
law of thermodynamics at apparent horizon. We find a minimum apparent horizon
due to the minimal length notion of GUP. We show that the energy density of
universe has a maximum and finite value at the minimum apparent horizon. Both
minimum apparent horizon and maximum energy density imply the absence of the
Big Bang singularity. Moreover, we investigate the GUP effects on the
deceleration parameter for flat case. Finally, we examine the validity of
generalised second law (GSL) of thermodynamics. We show that GSL always holds
in a region enclosed by apparent horizon for the GUP effects. We also
investigate the GSL in $\Lambda CDM$ cosmology and find that the total entropy
change of universe has a maximum value in the presence of GUP effects. To
better grasp the effects of Nouicer's GUP on cosmology, we compare our results
with those obtained from quadratic GUP (QGUP).


  We propose a generalization of Springer representations to the context of
groups over a global function field. The global counterpart of the Grothendieck
simultaneous resolution is the parabolic Hitchin fibration. We construct an
action of the affine Weyl group on the direct image complex of the parabolic
Hitchin fibration. In particular, we get representations of the affine Weyl
group on the cohomology of parabolic Hitchin fibers, providing the first step
towards a global Springer theory.


  In this paper, we consider the hypothesis that fractions of dark matter could
be constituted by primordial black holes (PBHs). To test this possibility, we
work out the observational properties of a static black hole embedded in the
dark matter envelope made of a PBH source. The corresponding modifications of
geometry due to such a physical system are investigated, with a particular
focus on the accretion disk luminosity in spiral galaxies. The impact of the
PBH presence is analyzed through modification of the disk luminosity and
kinematic quantities. Thus, we discuss possible constraints on the PBH
abundance in view of the most recent theoretical bounds. The results of our
study indicate that suitable PBH masses are
$M_\text{PBH}\in[10^6,10^{12}]M_\odot$ for PBH fractions
$f_\text{PBH}\in[10^{-3},1]$. In particular, a comparison with the predictions
of the exponential sphere density profile for dark matter suggests that the
best-matching configuration is achieved for $f_\text{PBH}=1$ and
$M_\text{PBH}=10^6 M_\odot$. Consequences with respect to the current knowledge
on primordial black hole physics are discussed.


  Recently, with the growing popularity of mobile devices as well as video
sharing platforms (e.g., YouTube, Facebook, TikTok, and Twitch), User-Generated
Content (UGC) videos have become increasingly common and now account for a
large portion of multimedia traffic on the internet. Unlike professionally
generated videos produced by filmmakers and videographers, typically, UGC
videos contain multiple authentic distortions, generally introduced during
capture and processing by naive users. Quality prediction of UGC videos is of
paramount importance to optimize and monitor their processing in hosting
platforms, such as their coding, transcoding, and streaming. However, blind
quality prediction of UGC is quite challenging because the degradations of UGC
videos are unknown and very diverse, in addition to the unavailability of
pristine reference. Therefore, in this paper, we propose an accurate and
efficient Blind Video Quality Assessment (BVQA) model for UGC videos, which we
name 2BiVQA for double Bi-LSTM Video Quality Assessment. 2BiVQA metric consists
of three main blocks, including a pre-trained Convolutional Neural Network
(CNN) to extract discriminative features from image patches, which are then fed
into two Recurrent Neural Networks (RNNs) for spatial and temporal pooling.
Specifically, we use two Bi-directional Long Short Term Memory (Bi-LSTM)
networks, the first is used to capture short-range dependencies between image
patches, while the second allows capturing longrange dependencies between
frames to account for the temporal memory effect. Experimental results on
recent large-scale UGC VQA datasets show that 2BiVQA achieves high performance
at lower computational cost than most state-of-the-art VQA models. The source
code of our 2BiVQA metric is made publicly available at:
https://github.com/atelili/2BiVQA


  Light field cameras have been proved to be powerful tools for 3D
reconstruction and virtual reality applications. However, the limited
resolution of light field images brings a lot of difficulties for further
information display and extraction. In this paper, we introduce a novel
learning-based framework to improve the spatial resolution of light fields.
First, features from different dimensions are parallelly extracted and fused
together in our multi-dimension fusion architecture. These features are then
used to generate dynamic filters, which extract subpixel information from
micro-lens images and also implicitly consider the disparity information.
Finally, more high-frequency details learned in the residual branch are added
to the upsampled images and the final super-resolved light fields are obtained.
Experimental results show that the proposed method uses fewer parameters but
achieves better performances than other state-of-the-art methods in various
kinds of datasets. Our reconstructed images also show sharp details and
distinct lines in both sub-aperture images and epipolar plane images.


  We construct a class $\Theta_{\mathscr{R}}$ of homomorphisms from a Specht
module $S_{\mathbb{Z}}^{\lambda}$ to a signed permutation module
$M_{\mathbb{Z}}(\alpha|\beta)$ which generalises James's construction of
homomorphisms whose codomain is a Young permutation module. We show that any
$\phi \in
\operatorname{Hom}_{{\mathbb{Z}}\mathfrak{S}_{n}}\big(S_{\mathbb{Z}}^\lambda,
M_{\mathbb{Z}}(\alpha|\beta)\big)$ lies in the $\mathbb{Q}$-span of
$\Theta_{\text{sstd}}$, a subset of $\Theta_{\mathscr{R}}$ corresponding to
semistandard $\lambda$-tableaux of type $(\alpha|\beta)$. We also study the
conditions for which $\Theta^{\mathbb{F}}_{\mathrm{sstd}}$ - a subset of
$\operatorname{Hom}_{\mathbb{F}\mathfrak{S}_{n}}\big(S_{\mathbb{F}}^\lambda,M_{\mathbb{F}}(\alpha|\beta)\big)$
induced by $\Theta_{\mathrm{sstd}}$ - is linearly independent, and show that it
is a basis for
$\operatorname{Hom}_{\mathbb{F}\mathfrak{S}_{n}}\big(S_{\mathbb{F}}^\lambda,M_{\mathbb{F}}(\alpha|\beta)\big)$
when $\mathbb{F}\mathfrak{S}_{n}$ is semisimple.


  We have mapped the protostellar jet HH 211 in 342 GHz continuum, SiO
($J=8-7$), and CO ($J=3-2$) emission at $\sim$ \arcs{1} resolution with the
Submillimeter Array (SMA). Thermal dust emission is seen in continuum at the
center of the jet, tracing an envelope and a possible optically thick compact
disk (with a size $<$ 130 AU) around the protostar. A knotty jet is seen in CO
and SiO as in \H2{}, but extending closer to the protostar. It consists of a
chain of knots on each side of the protostar, with an interknot spacing of
$\sim$ \arcs{2}$-$\arcs{3} or 600$-$900 AU and the innermost pair of knots at
only $\sim$ \arcsa{1}{7} or 535 AU from the protostar. These knots likely trace
unresolved internal (bow) shocks (i.e., working surfaces) in the jet, with a
velocity range up to $\sim$ 25 \vkm{}. The two-sided mass-loss rate of the jet
is estimated to be $\sim (0.7-2.8)\times 10^{-6}$ \solarmass{} yr$^{-1}$. The
jet is episodic, precessing, and bending. A velocity gradient is seen
consistently across two bright SiO knots (BK3 and RK2) perpendicular to the jet
axis, with $\sim$ 1.5$\pm$0.8 \vkm{} at $\sim$ 30$\pm$15 AU, suggesting a
presence of a jet rotation. The launching radius of the jet, derived from the
potential jet rotation, is $\sim$ 0.15$-$0.06 AU in the inner disk.


  The stellar initial mass function (IMF) is the key to understanding the
matter cycle in the Universe. Edwin Salpeter's paper of 1955 founded this
research field. Evidence today, however, challenges the initial mass function
as an invariant probability distribution function.


  We present a parallel implementation of a map-making algorithm for CMB
anisotropy experiments which is both fast and efficient. We show for the first
time a Maximum Likelihood, minimum variance map obtained by processing the
entire data stream expected from the Planck Surveyor, under the assumption of a
symmetric beam profile. Here we restrict ourselves to the case of the 30 GHz
channel of the Planck Low Frequency Instrument. The extension to Planck higher
frequency channels is straightforward. If the satellite pointing periodicity is
good enough to average data that belong to the same sky circle, then the code
runs very efficiently on workstations. The serial version of our code also runs
on very competitive time-scales the map-making pipeline for current and
forthcoming balloon borne experiments.


  We classify integrable Hamiltonian equations in 3D with the Hamiltonian
operator d/dx, where the Hamiltonian density h(u, w) is a function of two
variables: dependent variable u and the non-locality w such that w_x=u_y. Based
on the method of hydrodynamic reductions, the integrability conditions are
derived (in the form of an involutive PDE system for the Hamiltonian density
h). We show that the generic integrable density is expressed in terms of the
Weierstrass elliptic functions. Dispersionless Lax pairs, commuting flows and
dispersive deformations of the resulting equations are also discussed.


  This paper presents some properties and applications of "transversal
operators". Two transversal operators are presented: a "translation" operator T
and a "dilation" operator D. Such operators are used in common analysis systems
including Fourier series analysis, Fourier analysis, Gabor analysis,
multiresolution analysis (MRA), and wavelet analysis. Like the unitary Fourier
transform operator F, the transversal operators T and D are unitary.
Demonstrations of the usefulness of these three unitary operators are found in
the proofs of results found in some common analytic systems including MRA
analysis and wavelet analysis.


  This paper presents a solution for the Flow Graphs case of the Transformation
Tool Contest 2013, using the Eclectic model transformation tool. The solution
makes use of several languages of Eclectic, showing how it is possible to
combine them to address a non-trivial transformation problem in a concise and
modulary way.


  In the mid 1990's Seiberg and Witten determined the exact low energy
effective action of $\mathcal{N}=2$ supersymmetric Yang-Mills theory with gauge
group $SU(2)$. Later, in the early 2000's Nekrasov calculated this action
directly using localisation techniques. This work serves as an introduction to
the area, developing both approaches and reconciling their results.


  We present results of 2 mm observations of the Crab Nebula, obtained using
the Goddard-IRAM Superconducting 2 Millimeter Observer (GISMO) bolometer camera
on the IRAM 30 m telescope. Additional 3.3 mm observations with the MUSTANG
bolometer array on the Green Bank Telescope are also presented. The integrated
2 mm flux density of the Crab Nebula provides no evidence for the emergence of
a second synchrotron component that has been proposed. It is consistent with
the radio power law spectrum, extrapolated up to a break frequency of
log(nu_{b} [GHz]) = 2.84 +/- 0.29 or nu_{b} = 695^{+651}_{-336} GHz. The Crab
Nebula is well-resolved by the ~16.7" beam (FWHM) of GISMO. Comparison to radio
data at comparable spatial resolution enables us to confirm significant spatial
variation of the spectral index between 21 cm and 2 mm. The main effect is a
spectral flattening in the inner region of the Crab Nebula, correlated with the
toroidal structure at the center of the nebula that is prominent in the near-IR
through X-ray regime.


  The purpose of this study is to find transient X-ray sources in M31, and to
investigate and classify their nature. Three X-ray transients were observed
with Swift. For each of the three X-ray transients we use the Swift X-ray and
optical data together with observations from XMM-Newton and Chandra to
investigate the lightcurves and the spectra of the outburst, and thereby to
identify the source types. The outburst of XMMU J004215.8+411924 lasted for
about one month. The source had a hard power-law spectrum with a photon index
of 1.6. It was previously identified as a Be/X-ray binary based on the optical
identification with a star. However, we show that with improved source
coordinates it is clear that the optical source is not the counterpart to the
X-ray source. The source SWIFT J004217.3+411532 had a bright outburst, after
which it slowly decayed over half a year. The spectrum was soft, corresponding
to a thermal accretion disk with innermost temperature of 250-600 eV. The
source was not seen in the optical, and the soft spectrum indicates that the
source is most likely a black hole low mass X-ray binary. M31N 2006-11a is a
nova that was previously observed in the optical. We detected it both in X-rays
and UV with Swift half a year after the optical maximum, after which it decayed
below the Swift detection threshold within a month. The spectrum of the X-ray
transient can be modelled by a black-body with a temperature of 50 eV. We use
catalogues of X-ray transients in M31 to estimate their rate, and we find a
lower limit of 9/yr.


  A linear arrangement (LA) is an assignment of distinct integers to the
vertices of a graph. The cost of an LA is the sum of lengths of the edges of
the graph, where the length of an edge is defined as the absolute value of the
difference of the integers assigned to its ends. For many application one hopes
to find an LA with small cost. However, it is a classical NP-complete problem
to decide whether a given graph $G$ admits an LA of cost bounded by a given
integer. Since every edge of $G$ contributes at least one to the cost of any
LA, the problem becomes trivially fixed-parameter tractable (FPT) if
parameterized by the upper bound of the cost. Fernau asked whether the problem
remains FPT if parameterized by the upper bound of the cost minus the number of
edges of the given graph; thus whether the problem is FPT ``parameterized above
guaranteed value.'' We answer this question positively by deriving an algorithm
which decides in time $O(m+n+5.88^k)$ whether a given graph with $m$ edges and
$n$ vertices admits an LA of cost at most $m+k$ (the algorithm computes such an
LA if it exists). Our algorithm is based on a procedure which generates a
problem kernel of linear size in linear time for a connected graph $G$. We also
prove that more general parameterized LA problems stated by Serna and Thilikos
are not FPT, unless P=NP.


  We have designed photonic crystal suspended membranes with optimized optical
and mechanical properties for cavity optomechanics. Such resonators sustain
vibration modes in the megahertz range with quality factors of a few thousand.
Thanks to a two-dimensional square lattice of holes, their reflectivity at
normal incidence at 1064 nm reaches values as high as 95%. These two features,
combined with the very low mass of the membrane, open the way to the use of
such periodic structures as deformable end-mirrors in Fabry-Perot cavities for
the investigation of cavity optomechanical effects


  The sequence $3, 5, 9, 11, 15, 19, 21, 25, 29, 35,\dots$ consists of odd legs
in right triangles with integer side lengths and prime hypotenuse. We show that
the upper density of this sequence is zero, with logarithmic decay. The same
estimate holds for the sequence of even legs in such triangles. We expect our
upper bound, which involves the Erd\H{o}s--Ford--Tenenbaum constant, to be
sharp up to a double-logarithmic factor. We also provide a nontrivial lower
bound. Our techniques involve sieve methods, the distribution of Gaussian
primes in narrow sectors, and the Hardy--Ramanujan inequality.


  We introduce the notion of continuous invertibility on a compact set for
volatility models driven by a Stochastic Recurrence Equation (SRE). We prove
the strong consistency of the Quasi Maximum Likelihood Estimator (QMLE) when
the optimization procedure is done on a continuously invertible domain. This
approach gives for the first time the strong consistency of the QMLE used by
Nelson in \cite{nelson:1991} for the EGARCH(1,1) model under explicit but non
observable conditions. In practice, we propose to stabilize the QMLE by
constraining the optimization procedure to an empirical continuously invertible
domain. The new method, called Stable QMLE (SQMLE), is strongly consistent when
the observations follow an invertible EGARCH(1,1) model. We also give the
asymptotic normality of the SQMLE under additional minimal assumptions.


  As techniques for graph query processing mature, the need for optimization is
increasingly becoming an imperative. Indices are one of the key ingredients
toward efficient query processing strategies via cost-based optimization. Due
to the apparent absence of a common representation model, it is difficult to
make a focused effort toward developing access structures, metrics to evaluate
query costs, and choose alternatives. In this context, recent interests in
covering-based graph matching appears to be a promising direction of research.
In this paper, our goal is to formally introduce a new graph representation
model, called Minimum Hub Cover, and demonstrate that this representation
offers interesting strategic advantages, facilitates construction of candidate
graphs from graph fragments, and helps leverage indices in novel ways for query
optimization. However, similar to other covering problems, minimum hub cover is
NP-hard, and thus is a natural candidate for optimization. We claim that
computing the minimum hub cover leads to substantial cost reduction for graph
query processing. We present a computational characterization of minimum hub
cover based on integer programming to substantiate our claim and investigate
its computational cost on various graph types.


  The pseudogap phase is considered as a new state of matter in the phase
string model of the doped Mott insulator, which is composed of two distinct
regimes known as upper and lower pseudogap phases, respectively. The former
corresponds to the formation of spin singlet pairing and the latter is
characterized by the formation of the Cooper pair amplitude and described by a
generalized Gingzburg-Landau theory. Elementary excitation in this phase is a
charge-neutral object carrying spin-1/2 and locking with a supercurrent vortex,
known as spinon-vortex composite. Here thermally excited spinon-vortices
destroy the phase coherence and are responsible for nontrivial Nernst effect
and diamagnetism. The transport entropy and core energy associated with a
spinon-vortex are determined by the spin degrees of freedom. Such a spontaneous
vortex liquid phase can be also considered as a spin liquid with a finite
correlation length and gapped S=1/2 excitations, where a resonancelike
non-propagating spin mode emerges at the antiferromagnetic wavevector with a
doping-dependent characteristic energy. A quantitative phase diagram in the
parameter space of doping, temperature, and magnetic field is determined.
Comparisons with experiments are also made.


  The transverse momentum ($p_{\mathrm T}$) spectra for identified charged
pions, protons and anti-protons from $p$+$p$ and $d$+Au collisions are measured
around midrapidity ($\mid$y$\mid$ $<$ 0.5) over the range of 0.3 $<$
$p_{\mathrm T}$ $<$ 10 GeV/$c$ at $\sqrt{s_{\mathrm {NN}}}$ = 200 GeV. The
charged pion and proton+anti-proton spectra at high p_{T} in p+p collisions
have been compared with the next-to-leading order perturbative quantum
chromodynamic (NLO pQCD) calculations with a specific fragmentation scheme. The
p/pi^{+} and pbar/pi^{-}has been studied at high p_{T}. The nuclear
modification factor (R_{dAu}) shows that the identified particle Cronin effects
around midrapidity are significantly non-zero for charged pions and to be even
larger for protons at intermediate p_{T} (2 < p_{T} < 5 GeV/c).


  Thermonuclear burning on the surface of accreting neutron stars is observed
to stabilize at accretion rates almost an order of magnitude lower than
theoretical models predict. One way to resolve this discrepancy is by including
a base heating flux that can stabilize the layer. We focus our attention on
pure helium accretion, for which we calculate the effect of a base heating flux
on the critical accretion rate at which thermonuclear burning stabilizes. We
use the MESA stellar evolution code to calculate $\dot m_{\rm crit}$ as a
function of the base flux, and derive analytic fitting formulae for $\dot
m_{\rm crit}$ and the burning temperature at that critical accretion rate,
based on a one-zone model. We also investigate whether the critical accretion
rate can be determined by examining steady-state models only, without
time-dependent simulations. We examine the argument that the stability boundary
coincides with the turning point $dy_{\rm burn}/d\dot m=0$ in the steady-state
models, and find that it does not hold outside of the one-zone, zero base flux
case. A linear stability analysis of a large suite of steady-state models is
also carried out, which yields critical accretion rates a factor of $\sim3$
larger than the MESA result, but with a similar dependence on base flux.
Lastly, we discuss the implications of our results for the ultracompact X-ray
binary 4U~1820-30.


  We report on the design and operation of a 1D magneto-granular phononic
crystal composed of a chain of steel spherical beads on top of permanent
magnets. The magnetic field of the permanent magnets induces forces in the
granular structure. By changing its strength, we can tune the dynamic response
of the granular structure. We present experimental results with evidence of
coupled transversal-rotational modes, and zero group velocities modes. These
observations are well supported by a proposed model taking into account the
mechanical coupling between the beads and the magnets by linear stiffnesses and
including all degrees of freedom in translations and rotations.


  A generalization of non-perturbative QED model for high harmonic generation
is developed for the multi-mode optical field case. By introducing
classical-field-dressed quantized Volkov states analytically, a formula to
calculate HHG for hydrogen-like atom in ultrashort intense laser pulse is
obtained, which has a simple intuitive interpretation. The dressed state QED
model indicates a new perspective to understand HHG, for example, the presence
of the weak even-order harmonic photons, which has been verified by both
theoretical analysis and numerical computation. Long wavelength approximation
and strong field approximation are involved in the development of the
formalism.


  The electronic structure of an atom with Z <= 137 can be described by the
Dirac equation with the Coulomb field of a point charge Ze. It was believed
that the Dirac equation with Z > 137 is inconsistent and physically meaningless
because the formula for the lower energy level of the Dirac Hamiltonian
formally gives imaginary eigenvalues. But a strict mathematical consideration
shows that difficulties with the electronic spectrum for Z > 137 do not arise
if the Dirac Hamiltonian is correctly defined as a self-adjoint operator, see
[1]. In this article, we brie y summarize the main physical results of that
consideration in a form suitable for physicists with some additional new
details and numerical calculations of the electronic spectra.
  [1] B.L. Voronov, D.M. Gitman, and I.V. Tyutin, Theor. Math. Phys. 150(1)
(2007) 34


  We theoretically investigate the anomalous Hall effect in a system of
dense-packed ferromagnetic grains in the metallic regime. Using the formalism
recently developed for the conventional Hall effect in granular metals, we
calculate the residual anomalous Hall conductivity $\sigma_{xy}$ and
resistivity $\rho_{xy}$ and weak localization corrections to them for both
skew-scattering and side-jump mechanisms. We find that, unlike for
homogeneously disordered metals, the scaling relation between $\rho_{xy}$ and
the longitudinal resistivity $\rho_{xx}$ does not hold. The weak localization
corrections, however, are found to be in agreement with those for homogeneous
metals. We discuss recent experimental data on the anomalous Hall effect in
polycrystalline iron films in view of the obtained results.


  Given an i.i.d. sample $X_1,...,X_n$ with common bounded density $f_0$
belonging to a Sobolev space of order $\alpha$ over the real line, estimation
of the quadratic functional $\int_{\mathbb{R}}f_0^2(x) \mathrm{d}x$ is
considered. It is shown that the simplest kernel-based plug-in estimator
\[\frac{2}{n(n-1)h_n}\sum_{1\leq i<j\leq n}K\biggl(\frac{X_i-X_j}{h_n}\biggr)\]
is asymptotically efficient if $\alpha>1/4$ and rate-optimal if $\alpha\le1/4$.
A data-driven rule to choose the bandwidth $h_n$ is then proposed, which does
not depend on prior knowledge of $\alpha$, so that the corresponding estimator
is rate-adaptive for $\alpha \leq1/4$ and asymptotically efficient if
$\alpha>1/4$.


  How different cultures react and respond given a crisis is predominant in a
society's norms and political will to combat the situation. Often the decisions
made are necessitated by events, social pressure, or the need of the hour,
which may not represent the will of the nation. While some are pleased with it,
others might show resentment. Coronavirus (COVID-19) brought a mix of similar
emotions from the nations towards the decisions taken by their respective
governments. Social media was bombarded with posts containing both positive and
negative sentiments on the COVID-19, pandemic, lockdown, hashtags past couple
of months. Despite geographically close, many neighboring countries reacted
differently to one another. For instance, Denmark and Sweden, which share many
similarities, stood poles apart on the decision taken by their respective
governments. Yet, their nation's support was mostly unanimous, unlike the South
Asian neighboring countries where people showed a lot of anxiety and
resentment. This study tends to detect and analyze sentiment polarity and
emotions demonstrated during the initial phase of the pandemic and the lockdown
period employing natural language processing (NLP) and deep learning techniques
on Twitter posts. Deep long short-term memory (LSTM) models used for estimating
the sentiment polarity and emotions from extracted tweets have been trained to
achieve state-of-the-art accuracy on the sentiment140 dataset. The use of
emoticons showed a unique and novel way of validating the supervised deep
learning models on tweets extracted from Twitter.


  Recently, Sheppard et al. (2016) presented the discovery of seven new
trans-Neptunian objects with moderate eccentricities, perihelia beyond 40 AU,
and semimajor axes beyond 50 AU. Like the few previously known objects on
similar orbits, these objects' semimajor axes are just beyond the Kuiper belt
edge and clustered around Neptunian mean motion resonances (MMRs). These
objects likely obtained their observed orbits while trapped within MMRs, when
the Kozai-Lidov mechanism raised their perihelia and weakened Neptune's
dynamical influence. Using numerical simulations that model the production of
this population, we find that high-perihelion objects near Neptunian MMRs can
constrain the nature and timescale of Neptune's past orbital migration. In
particular, the population near the 3:1 MMR (near 62 AU) is especially useful
due to its large population and short dynamical evolution timescale. If Neptune
finishes migrating within ~100 Myrs or less, we predict over 90% of
high-perihelion objects near the 3:1 MMR will have semimajor axes within 1 AU
of each other, very near the modern resonance's center. On the other hand, if
Neptune's migration takes ~300 Myrs, we expect ~50% of this population to
reside in dynamically fossilized orbits over ~1 AU closer to the Sun than the
modern resonance. We highlight 2015 KH162 as a likely member of this fossilized
3:1 population. Under any plausible migration scenario, nearly all
high-perihelion objects in resonances beyond the 4:1 MMR (near 76 AU) reach
their orbits well after Neptune stops migrating and comprise a recently
generated, dynamically active population.


  We present a decentralized path-planning algorithm for navigating multiple
differential-drive robots in dense environments. In contrast to prior
decentralized methods, we propose a novel congestion metric-based replanning
that couples local and global planning techniques to efficiently navigate in
scenarios with multiple corridors. To handle dense scenes with narrow passages,
our approach computes the initial path for each agent to its assigned goal
using a lattice planner. Based on neighbors' information, each agent performs
online replanning using a congestion metric that tends to reduce the collisions
and improves the navigation performance. Furthermore, we use the Voronoi cells
of each agent to plan the local motion as well as a corridor selection strategy
to limit the congestion in narrow passages. We evaluate the performance of our
approach in complex warehouse-like scenes and demonstrate improved performance
and efficiency over prior methods. In addition, our approach results in a
higher success rate in terms of collision-free navigation to the goals.


  We show that leptophobic $Z'$ gauge bosons occur naturally in flipped SU(5)
and may shift $R_b$ in an interesting way without upsetting the good values of
$\Gamma_{had}$ and $R_c$. Within a string-derived version of the model, we
study three possible scenarios and the constraints imposed on model building
that would allow the new symmetry to remain unbroken down to low energies. Such
$Z'$ gauge boson has generation non-universal couplings to quarks that violate
parity maximally in the up-quark sector, and may contribute significantly to
spin asymmetries in polarized $pp$ scattering experiments now being prepared
for RHIC.


  Virtual telepresence is the future of online communication. Clothing is an
essential part of a person's identity and self-expression. Yet, ground truth
data of registered clothes is currently unavailable in the required resolution
and accuracy for training telepresence models for realistic cloth animation.
Here, we propose an end-to-end pipeline for building drivable representations
for clothing. The core of our approach is a multi-view patterned cloth tracking
algorithm capable of capturing deformations with high accuracy. We further rely
on the high-quality data produced by our tracking method to build a Garment
Avatar: an expressive and fully-drivable geometry model for a piece of
clothing. The resulting model can be animated using a sparse set of views and
produces highly realistic reconstructions which are faithful to the driving
signals. We demonstrate the efficacy of our pipeline on a realistic virtual
telepresence application, where a garment is being reconstructed from two
views, and a user can pick and swap garment design as they wish. In addition,
we show a challenging scenario when driven exclusively with body pose, our
drivable garment avatar is capable of producing realistic cloth geometry of
significantly higher quality than the state-of-the-art.


  An integral part of many algorithms for S-estimators of linear regression is
random subsampling. For problems with only continuous predictors simple random
subsampling is a reliable method to generate initial coefficient estimates that
can then be further refined. For data with categorical predictors, however,
random subsampling often does not work, thus limiting the use of an otherwise
fine estimator. This also makes the choice of estimator for robust linear
regression dependent on the type of predictors, which is an unnecessary
nuisance in practice. For data with categorical predictors random subsampling
often generates singular subsamples. Since these subsamples cannot be used to
calculate coefficient estimates, they have to be discarded. This makes random
subsampling slow, especially if some levels of categorical predictors have low
frequency, and renders the algorithms infeasible for such problems. This paper
introduces an improved subsampling algorithm that only generates nonsingular
subsamples. We call it nonsingular subsampling. For data with continuous
variables it is as fast as simple random subsampling but much faster for data
with categorical predictors. This is achieved by using a modified LU
decomposition algorithm that combines the generation of a sample and the
solving of the least squares problem.


  We study the drag force on uniformly moving inclusions which interact
linearly with dynamical free field theories commonly used to study soft
condensed matter systems. Drag forces are shown to be nonlinear functions of
the inclusion velocity and depend strongly on the field dynamics. The general
results obtained can be used to explain drag forces in Ising systems and also
predict the existence of drag forces on proteins in membranes due to couplings
to various physical parameters of the membrane such as composition, phase and
height fluctuations.


  We study the phase diagrams and thermodynamic properties of a system of
coexisting itinerant electrons and local pairs (LP), in the presence of
diagonal disorder. The model considered takes into account both the charge
exchange couplings, responsible for superconducting orderings, and the
density-density interactions, which can stabilize charge ordered states in the
system. Depending on the strength of the random on-site potential, the
interactions and the particle concentrations the model is found to exhibit
several various phases, including the homogeneous ones: superconducting (SC),
charge density wave (CDW) and nonordered (NO), as well as the phase separated
states (CDW-SC and CDW-NO).


  We present a method for achieving temporally and spatially precise
photoactivation of neurons without the need for genetic expression of
photosensitive proteins. Our method depends upon conduction of thermal energy
via absorption by a dye or carbon particles and does not require the presence
of voltage-gated channels to create transmembrane currents. We demonstrate
photothermal initiation of action potentials in Hirudo verbana neurons and of
transmembrane currents in Xenopus oocytes. Thermal energy is delivered by
focused 50 ms, 650 nm laser pulses with total pulse energies between 250 and
3500 \muJ. We document an optical delivery system for targeting specific
neurons that can be expanded for multiple target sites. Our method achieves
photoactivation reliably (70 - 90% of attempts) and can issue multiple pulses
(6-9) with minimal changes to cellular properties as measured by intracellular
recording. Direct photoactivation presents a significant step towards
all-optical analysis of neural circuits in animals such as Hirudo verbana where
genetic expression of photosensitive compounds is not feasible.


  The effect of redshift on the observation of distant galaxies is briefly
discussed emphasizing the possible sources of bias in the interpretation of
high-z data. A general energetic criterion to assess physical self-consistency
of evolutionary population synthesis models is also proposed, for a more
appropriate use of this important tool to investigate distinctive properties of
primeval galaxies.


  Swift is the only observatory which, due to its unique fast-slewing
capability and broad-band energy coverage, can detect outbursts from Supergiant
Fast X-ray Transients (SFXTs) from the very beginning and study their evolution
panchromatically. Thanks to its flexible observing scheduling, which makes
monitoring cost-effective, Swift has also performed a campaign that covers all
phases of the lives of SFXTs with a high sensitivity in the soft X-ray regime,
where most SFXTs had not been observed before. Our continued effort at
monitorning SFXTs with 2-3 observations per week (1-2 ks) with the Swift X-Ray
Telescope (XRT) over their entire visibility period has just finished its
second year. We report on our findings on the long-term properties of SFXTs,
their duty cycle, and the new outbursts caught by Swift during the second year.


  Quantum phase transitions are ubiquitous in many exotic behaviors of
strongly-correlated materials. However the microscopic complexity impedes their
quantitative understanding. Here, we observe thoroughly and comprehend the rich
strongly-correlated physics in two profoundly dissimilar regimes of quantum
criticality. With a circuit implementing a quantum simulator for the
three-channel Kondo model, we reveal the universal scalings toward different
low-temperature fixed points and along the multiple crossovers from quantum
criticality. Notably, an unanticipated violation of the maximum conductance for
ballistic free electrons is uncovered. The present charge pseudospin
implementation of a Kondo impurity opens access to a broad variety of
strongly-correlated phenomena.


  We extend all known black hole no-hair theorems to space-times endowed with a
positive cosmological constant $\Lambda.$ Specifically, we prove that static
spherical black holes with $\Lambda>0$ cannot support scalar fields in convex
potentials and Proca-massive vector fields in the region between black hole and
cosmic horizons. We also demonstrate the existence of at least one type of
quantum hair, and of exactly one charged solution for the Abelian Higgs model.
Our method of proof can be applied to investigate other types of quantum or
topological hair on black holes in the presence of a positive $\Lambda.$


  We study how the recent experimental results constrain the gauge sectors of
U(1) extensions of the standard model using a novel representation of the
parameter space. We determine the bounds on the mixing angle between the
massive gauge bosons, or equivalently, the new gauge coupling as a function of
the mass $M_{Z'}$ of the new neutral gauge boson $Z'$ in the approximate range
$(10^{-2},10^4)\,$GeV/$c^2$. We consider the most stringent bounds obtained
from direct searches for the $Z'$. We also exhibit the allowed parameter space
by comparing the predicted and measured values of the $\rho$ parameter and
those of the mass of the $W$ boson. Finally, we discuss the prospects of $Z'$
searches at future colliders.


  Wireless sensor network (WSN) has attracted researchers worldwide to explore
the research opportunities, with application mainly in health monitoring,
industry automation, battlefields, home automation and environmental
monitoring. A WSN is highly resource constrained in terms of energy,
computation and memory. WSNs deployment ranges from the normal working
environment up to hostile and hazardous environment such as in volcano
monitoring and underground mines. These characteristics of WSNs hold additional
set of challenges in front of the operating system designer. The objective of
this survey is to highlight the features and weakness of the opearting system
available for WSNs, with the focus on the current application demands. The
paper also discusses the operating system design issues in terms of
architecture, programming model, scheduling and memory management and support
for real time applications.


  Toy Stars are gas masses where the compressibility is treated without
approximations but gravity is replaced by a force which, for any pair of
masses, is along their line of centres and proportional to their separation.
They provide an invaluable resource for testing the suitability of numerical
codes for astrophysical gas dynamics. In this paper we derive the equations for
both small amplitude oscillations and non linear solutions for rotating and
pulsating Toy Stars in two dimensions, and show that the solutions can be
reduced to a small number of ordinary differential equations. We compare the
accurate solutions of these equations with Smoothed Particle Hydrodynamics
(SPH) simulations. The two dimensional Toy Star solutions are found to provide
an excellent benchmark for SPH algorithms, highlighting many of the strengths
and also some weaknesses of the method.


  We use cosmological hydrodynamic zoom-in simulations to study early structure
formation in two dark matter (DM) cosmologies, the standard CDM model, and a
thermal warm DM (WDM) model with a particle mass of $m_{\chi}c^{2}=3\
\mathrm{keV}$. We focus on DM haloes with virial masses $M\sim 10^{10}\
M_{\odot}$. We find that the first star formation activity is delayed by $\sim
200\ \mathrm{Myr}$ in the WDM model, with similar delays for metal enrichment
and the formation of the second generation of stars. However, the differences
between the two models in globally-averaged properties, such as star formation
rate density and mean metallicity, decrease towards lower redshifts ($z\lesssim
10$). Metal enrichment in the WDM cosmology is restricted to dense
environments, while low-density gas can also be significantly enriched in the
CDM case. The free-free contribution from early structure formation at
redshifts $z>6$ to the cosmic radio background (CRB) is $3_{-1.5}^{+13}\%$
($8_{-3.5}^{+33}\%$) of the total signal inferred from radio experiments such
as ARCADE 2, in the WDM (CDM) model. The direct detection of the
$\mathrm{H_{2}}$ emission from early structure formation ($z\gtrsim 7.2$),
originating from the low-mass haloes explored here, will be challenging even
with the next generation of far-infrared space telescopes, unless the signal is
magnified by at least a factor of 10 via gravitational lensing or shocks.
However, more massive haloes with $M\gtrsim 10^{12}\ M_{\odot}$ may be
observable for $z\gtrsim 10$, even without magnification, provided that our
extrapolation from the scale of our simulated haloes is valid.


  With recent advances on the dense low-earth orbit (LEO) constellation, LEO
satellite network has become one promising solution to providing global
coverage for Internet-of-Things (IoT) services. Confronted with the sporadic
transmission from randomly activated IoT devices, we consider the random access
(RA) mechanism, and propose a grant-free RA (GF-RA) scheme to reduce the access
delay to the mobile LEO satellites. A Bernoulli-Rician message passing with
expectation maximization (BR-MP-EM) algorithm is proposed for this
terrestrial-satellite GF-RA system to address the user activity detection (UAD)
and channel estimation (CE) problem. This BR-MP-EM algorithm is divided into
two stages. In the inner iterations, the Bernoulli messages and Rician messages
are updated for the joint UAD and CE problem. Based on the output of the inner
iterations, the expectation maximization (EM) method is employed in the outer
iterations to update the hyper-parameters related to the channel impairments.
Finally, simulation results show the UAD and CE accuracy of the proposed
BR-MP-EM algorithm, as well as the robustness against the channel impairments.


  We present a geometry-based discussion of possible vortex configurations in
the mixed state of anisotropic type-II superconductors. It is shown that, if
energy considerations assign six nearest neighbors to each vortex, two distinct
modifications of the vortex lattice are possible. It is expected that certain
conditions lead to a first order phase transition from one modification of the
vortex lattice to the other upon varying the external magnetic field.


  Extensions of the Standard Model often predict new chiral interactions for
top quark, which will contribute to top quark spin correlation and polarization
in $t\bar{t}$ production at the LHC. In this work, under the constraints from
the current Tevatron measurements, a comparative study of the spin correlation
and polarization is performed in three new physics models: the minimal
supersymmetric model without R-parity (RPV-MSSM), the third-generation enhanced
left-right model and the axigluon model. We find that the polarization
asymmetry may be enhanced to the accessible level in all these models while the
correction to the spin correlation may be detectable in the axigluon model and
the RPV-MSSM with $\lambda"$ couplings.


  Transport simulations are very valuable for extracting physics information
from heavy-ion collision experiments. With the emergence of many different
transport codes in recent years, it becomes important to estimate their
robustness in extracting physics information from experiments. We report on the
results of a transport code comparison project. 18 commonly used transport
codes were included in this comparison: 9 Boltzmann-Uehling-Uhlenbeck-type
codes and 9 Quantum-Molecular-Dynamics-type codes. These codes have been
required to simulate Au+Au collisions using the same physics input for mean
fields and for in-medium nucleon-nucleon cross sections, as well as the same
initialization set-up, the impact parameter, and other calculational parameters
at 100 and 400 AMeV incident energy. Among the codes we compare one-body
observables such as rapidity and transverse flow distributions. We also monitor
non-observables such as the initialization of the internal states of colliding
nuclei and their stability, the collision rates and the Pauli blocking. We find
that not completely identical initializations constitute partly for different
evolutions. Different strategies to determine the collision probabilities, and
to enforce the Pauli blocking, also produce considerably different results.
There is a substantial spread in the predictions for the observables, which is
much smaller at the higher incident energy. We quantify the uncertainties in
the collective flow resulting from the simulation alone as about $30\%$ at 100
AMeV and $13\%$ at 400 AMeV, respectively. We propose further steps within the
code comparison project to test the different aspects of transport simulations
in a box calculation of infinite nuclear matter. This should, in particular,
improve the robustness of transport model predictions at lower incident
energies where abundant amounts of data are available.