  Artificial Intelligence (AI) technology is based on theory and development of
computer systems able to perform tasks that normally require human
intelligence. In this context, deep learning is a family of computational
methods that allow an algorithm to program itself by learning from a large set
of examples that demonstrate the desired behavior. Application of these methods
to medical imaging can assist pathologists in the detection of cancer subtype,
gene mutations and/or metastases for applying appropriate therapies. The
purpose of this study is to show the emerging application of AI in medical
imaging to detect lung and breast cancer. Moreover, this study shows the
comparative evolutionary pathways of this emerging technology for three
critical cancers: lung, breast and thyroid. A main finding of this study is the
recognition that, since the late 1990, the sharp increase of technological
trajectories of AI technology applied in cancer imaging seems to be driven by
high rates of mortality of some types of cancer (e.g., lung and breast) in
order to find new techniques for a more accurate detection, characterization
and monitoring as well as to apply efficiently anticancer therapies that
increase the progression-free survival of patients: the so-called
mortality-driven AI technological trajectories. Results also suggest that this
new technology can generate a technological paradigm shift for diagnostic
assessment of any cancer type. However, application of these methods to medical
imaging requires further assessment and validation to assist pathologists to
increase the efficiency of their workflow in both routine tasks and critical
cases of diagnostics.


  We consider the problem of topological linearization of smooth (C infinity or
real analytic) control systems, i.e. of their local equivalence to a linear
controllable system via point-wise transformations on the state and the control
(static feedback transformations) that are topological but not necessarily
differentiable. We prove that local topological linearization implies local
smooth linearization, at generic points. At arbitrary points, it implies local
conjugation to a linear system via a homeomorphism that induces a smooth
diffeomorphism on the state variables, and, except at "strongly" singular
points, this homeomorphism can be chosen to be a smooth mapping (the inverse
map needs not be smooth). Deciding whether the same is true at "strongly"
singular points is tantamount to solve an intriguing open question in
differential topology.


  We use ACE/SWICS elemental composition data to compare the variations in
solar wind fractionation as measured by SWICS during the last solar maximum
(1999-2001), the solar minimum (2006-2009) and the period in which the Genesis
spacecraft was collecting solar wind (late 2001 - early 2004). We differentiate
our analysis in terms of solar wind regimes (i.e. originating from interstream
or coronal hole flows, or coronal mass ejecta). Abundances are normalized to
the low-FIP ion magnesium to uncover correlations that are not apparent when
normalizing to high-FIP ions. We find that relative to magnesium, the other
low-FIP elements are measurably fractionated, but the degree of fractionation
does not vary significantly over the solar cycle. For the high-FIP ions,
variation in fractionation over the solar cycle is significant: greatest for
Ne/Mg and C/Mg, less so for O/Mg, and the least for He/Mg. When abundance
ratios are examined as a function of solar wind speed, we find a strong
correlation, with the remarkable observation that the degree of fractionation
follows a mass-dependent trend. We discuss the implications for correcting the
Genesis sample return results to photospheric abundances.


  We study the Polycyclic Aromatic Hydrocarbons (PAH) bands, ionic emission
lines, and Mid-infrared continuum properties, in a sample of 171 emission line
galaxies taken from literature plus 15 new active galactic nuclei (AGN) Spitzer
spectra. The continuum shape steeply rises for longer wavelengths and can be
fitted with a warm blackbody distribution of T=150-300K. The brightest PAH
spectral bands (6.2, 7.7, 8.6, 11.3, and 12.7$\mu$m) and the forbidden emission
lines of [Si II] 34.8$\mu$m, [Ar II] 6.9, [S III] 18.7 and 33.4 were detected
in all the Starbursts and in ~80% of the Seyfert~2. Taking under consideration
only the PAH bands at 7.7$\mu$m, 11.3$\mu$m, and 12.7$\mu$m we find they are
present in ~80% of the Seyfert 1, while only half of this type of activity show
the 6.2$\mu$m and 8.6 PAH bands. The observed intensities ratios for neutral
and ionized PAHs (6.2/7.7 x 11.3/7.7) were compared to theoretical intensity
ratios, showing that AGNs have higher ionization fraction and larger PAH (> 180
carbon atoms) than SB galaxies. The ratio between the ionized (7.7) and the
neutral PAH bands (8.6 and 11.3) are distributed over different ranges for AGNs
and SB galaxies, suggesting that these ratios could depend on the ionization
fraction, as well as on the hardness of the radiation field. The ratio between
the 7.7 and 11.3 bands is nearly constant with the increase of [Ne III]15.5/[Ne
II], indicating that the fraction of ionized to neutral PAH bands does not
depend on the hardness of the radiation field. The equivalent width of both PAH
features show the same dependence with [Ne III]/[Ne II], suggesting that the
PAH, emitting either ionized (7.7) or neutral (11.3) bands, may be destroyed
with the increase of the hardness of the radiation field.


  Deep neural networks are susceptible to adversarial examples, posing a
significant security risk in critical applications. Adversarial Training (AT)
is a well-established technique to enhance adversarial robustness, but it often
comes at the cost of decreased generalization ability. This paper proposes
Robustness Critical Fine-Tuning (RiFT), a novel approach to enhance
generalization without compromising adversarial robustness. The core idea of
RiFT is to exploit the redundant capacity for robustness by fine-tuning the
adversarially trained model on its non-robust-critical module. To do so, we
introduce module robust criticality (MRC), a measure that evaluates the
significance of a given module to model robustness under worst-case weight
perturbations. Using this measure, we identify the module with the lowest MRC
value as the non-robust-critical module and fine-tune its weights to obtain
fine-tuned weights. Subsequently, we linearly interpolate between the
adversarially trained weights and fine-tuned weights to derive the optimal
fine-tuned model weights. We demonstrate the efficacy of RiFT on ResNet18,
ResNet34, and WideResNet34-10 models trained on CIFAR10, CIFAR100, and
Tiny-ImageNet datasets. Our experiments show that \method can significantly
improve both generalization and out-of-distribution robustness by around 1.5%
while maintaining or even slightly enhancing adversarial robustness. Code is
available at https://github.com/microsoft/robustlearn.


  In the last half-decade, the field of natural language processing (NLP) has
undergone two major transitions: the switch to neural networks as the primary
modeling paradigm and the homogenization of the training regime (pre-train,
then fine-tune). Amidst this process, language models have emerged as NLP's
workhorse, displaying increasingly fluent generation capabilities and proving
to be an indispensable means of knowledge transfer downstream. Due to the
otherwise opaque, black-box nature of such models, researchers have employed
aspects of linguistic theory in order to characterize their behavior. Questions
central to syntax -- the study of the hierarchical structure of language --
have factored heavily into such work, shedding invaluable insights about
models' inherent biases and their ability to make human-like generalizations.
In this paper, we attempt to take stock of this growing body of literature. In
doing so, we observe a lack of clarity across numerous dimensions, which
influences the hypotheses that researchers form, as well as the conclusions
they draw from their findings. To remedy this, we urge researchers make careful
considerations when investigating coding properties, selecting representations,
and evaluating via downstream tasks. Furthermore, we outline the implications
of the different types of research questions exhibited in studies on syntax, as
well as the inherent pitfalls of aggregate metrics. Ultimately, we hope that
our discussion adds nuance to the prospect of studying language models and
paves the way for a less monolithic perspective on syntax in this context.


  In this paper, we will define the Brauer algebras of Weyl types, and describe
some propositions of these algebras. Especially, we prove the result of type
$G_2$ to accomplish our project of Brauer algebras of non-simply laced types.


  Improving the effective action by the renormalization group (RG) with several
mass scales is an important problem in quantum field theories. A method based
on the decoupling theorem was proposed in \cite{Bando:1992wy} and
systematically improved \cite{Casas:1998cf} to take threshold effects into
account. In this paper, we apply the method to the Higgs-Yukawa model,
including wave-function renormalizations, and to a model with two real scalar
fields $(\varphi, h)$. In the Higgs-Yukawa model, even at one-loop level,
Feynman diagrams contain propagators with different mass scales and decoupling
scales must be chosen appropriately to absorb threshold corrections. On the
other hand, in the two-scalar model, the mass matrix of the scalar fields is a
function of their field values $(\varphi, h)$ and the resultant running
couplings obey different RGEs on a different point of the field space. By
solving the RGEs, we can obtain the RG improved effective action in the whole
region of the scalar fields.


  In 1968, Ore determined the maximum size of $k$-connected graphs with given
order and diameter. In this note, we give a new short proof.


  We present a theoretical study of solid carbon dioxide up to 50GPa and 1500K
using first-principles calculations. In this pressure-temperature range,
interpretations of recent experiments have suggested the existence of CO2
phases which are intermediate between molecular and covalent-bonded solids. We
reexamine the concept of intermediate phases in the CO2 phase diagram and
propose instead molecular structures, which provide an excellent agreement with
measurements.


  Diffusion models have been verified to be effective in generating complex
distributions from natural images to motion trajectories. Recent
diffusion-based methods show impressive performance in 3D robotic manipulation
tasks, whereas they suffer from severe runtime inefficiency due to multiple
denoising steps, especially with high-dimensional observations. To this end, we
propose a real-time robotic manipulation model named ManiCM that imposes the
consistency constraint to the diffusion process, so that the model can generate
robot actions in only one-step inference. Specifically, we formulate a
consistent diffusion process in the robot action space conditioned on the point
cloud input, where the original action is required to be directly denoised from
any point along the ODE trajectory. To model this process, we design a
consistency distillation technique to predict the action sample directly
instead of predicting the noise within the vision community for fast
convergence in the low-dimensional action manifold. We evaluate ManiCM on 31
robotic manipulation tasks from Adroit and Metaworld, and the results
demonstrate that our approach accelerates the state-of-the-art method by 10
times in average inference speed while maintaining competitive average success
rate.


  We look for observational signatures that could discriminate between
Newtonian and modified Newtonian (MOND) dynamics in the Milky Way, in view of
the advent of large astrometric and spectroscopic surveys. Indeed, a typical
signature of MOND is an apparent disk of "phantom" dark matter, which is
uniquely correlated with the visible disk-density distribution. Due to this
phantom dark disk, Newtonian models with a spherical halo have different
signatures from MOND models close to the Galactic plane. The models can thus be
differentiated by measuring dynamically (within Newtonian dynamics) the disk
surface density at the solar radius, the radial mass gradient within the disk,
or the velocity ellipsoid tilt angle above the Galactic plane. Using the most
realistic possible baryonic mass model for the Milky Way, we predict that, if
MOND applies, the local surface density measured by a Newtonist will be
approximately 78 Msun/pc2 within 1.1 kpc of the Galactic plane, the dynamically
measured disk scale-length will be enhanced by a factor of 1.25 with respect to
the visible disk scale-length, and the local vertical tilt of the velocity
ellipsoid at 1 kpc above the plane will be approximately 6 degrees. None of
these tests can be conclusive for the present-day accuracy of Milky Way data,
but they will be of prime interest with the advent of large surveys such as
GAIA.


  A 3-D porous apatite scaffold (B-HA), recently obtained through biomorphic
transformation of a natural wood, is investigated on its multi-scale porous
structure determining superior mechanical properties and biological behaviour.
B-HA shows hierarchical pore architecture with wide aligned channels
interconnected with smaller tubules, thus recapitulating in detail the
lymphatic network of the original wood template. As induced by its biomimetic
architecture, B-HA displays values of compression and tensile strength and
stiffness, higher than the values usually measured in sintered ceramics with
isotropic porosity. Furthermore, B-HA shows a ductility not common for a pure
ceramic body and a tensile strength higher than its compression strength, thus
occupying a zone in the Ashby chart where ceramics are usually not present.
Cell co-culture tests in bioreactor report encouraging results in enhancing the
complex tissue regeneration process, thus making B-HA very promising as a
scaffold able to promote bone regeneration, particularly for large bone
defects.


  Precise geolocalization is crucial for unmanned aerial vehicles (UAVs).
However, most current deployed UAVs rely on the global navigation satellite
systems (GNSS) or high precision inertial navigation systems (INS) for
geolocalization. In this paper, we propose to use a lightweight visual-inertial
system with a 2D georeference map to obtain accurate and consecutive geodetic
positions for UAVs. The proposed system firstly integrates a micro inertial
measurement unit (MIMU) and a monocular camera as odometry to consecutively
estimate the navigation states and reconstruct the 3D position of the observed
visual features in the local world frame. To obtain the geolocation, the visual
features tracked by the odometry are further registered to the 2D georeferenced
map. While most conventional methods perform image-level aerial image
registration, we propose to align the reconstructed points to the map points in
the geodetic frame; this helps to filter out the large portion of outliers and
decouples the negative effects from the horizontal angles. The registered
points are then used to relocalize the vehicle in the geodetic frame. Finally,
a pose graph is deployed to fuse the geolocation from the aerial image
registration and the local navigation result from the visual-inertial odometry
(VIO) to achieve consecutive and drift-free geolocalization performance. We
have validated the proposed method by installing the sensors to a UAV body
rigidly and have conducted two flights in different environments with unknown
initials. The results show that the proposed method can achieve less than 4m
position error in flight at 100m high and less than 9m position error in flight
about 300m high.


  We study the effect of going beyond the Gross-Pitaevskii theory on the
frequencies of collective oscillations of a trapped Bose gas in the large gas
parameter regime. We go beyond the Gross-Pitaevskii regime by including a
higher-order term in the interatomic correlation energy. To calculate the
frequencies we employ the sum-rule approach of many-body response theory
coupled with a variational method for the determination of ground-state
properties. We show that going beyond the Gross-Pitaevskii approximation
introduces significant corrections to the collective frequencies of the
compressional mode.


  Community detection is one of the most important problems in network
analysis. Among many algorithms proposed for this task, methods based on
statistical inference are of particular interest: they are mathematically sound
and were shown to provide partitions of good quality. Statistical inference
methods are based on fitting some random graph model (a.k.a. null model) to the
observed network by maximizing the likelihood. The choice of this model is
extremely important and is the main focus of the current study. We provide an
extensive theoretical and empirical analysis to compare several models: the
widely used planted partition model, recently proposed degree-corrected
modification of this model, and a new null model having some desirable
statistical properties. We also develop and compare two likelihood optimization
algorithms suitable for the models under consideration. An extensive empirical
analysis on a variety of datasets shows, in particular, that the new model is
the best one for describing most of the considered real-world complex networks
according to the likelihood of observed graph structures.


  Real-time bidding has emerged as an effective online advertising technique.
With real-time bidding, advertisers can position ads per impression, enabling
them to optimise ad campaigns by targeting specific audiences in real-time.
This paper proposes a novel method for real-time bidding that combines deep
learning and reinforcement learning techniques to enhance the efficiency and
precision of the bidding process. In particular, the proposed method employs a
deep neural network to predict auction details and market prices and a
reinforcement learning algorithm to determine the optimal bid price. The model
is trained using historical data from the iPinYou dataset and compared to
cutting-edge real-time bidding algorithms. The outcomes demonstrate that the
proposed method is preferable regarding cost-effectiveness and precision. In
addition, the study investigates the influence of various model parameters on
the performance of the proposed algorithm. It offers insights into the efficacy
of the combined deep learning and reinforcement learning approach for real-time
bidding. This study contributes to advancing techniques and offers a promising
direction for future research.


  The aim of this paper is to introduce and study Lie algebras and Lie groups
over noncommutative rings. For any Lie algebra $\gg$ sitting inside an
associative algebra $A$ and any associative algebra $\FF$ we introduce and
study the algebra $(\gg,A)(\FF)$, which is the Lie subalgebra of $\FF \otimes
A$ generated by $\FF \otimes \gg$. In many examples $A$ is the universal
enveloping algebra of $\gg$. Our description of the algebra $(\gg,A)(\FF)$ has
a striking resemblance to the commutator expansions of $\FF$ used by M.
Kapranov in his approach to noncommutative geometry. To each algebra $(\gg,
A)(\FF)$ we associate a ``noncommutative algebraic'' group which naturally acts
on $(\gg,A)(\FF)$ by conjugations and conclude the paper with some examples of
such groups.


  We express generalized Cauchy-Stieltjes transforms of some particular Beta
distributions (of ultraspherical type generating functions for orthogonal
polynomials) as a powered Cauchy-Stieltjes transform of some measure. For
suitable values of the power parameter, the latter measure turns out to be a
probability measure and its density is written down using Markov transforms.
The discarded values give a negative answer to a deformed free probability
unless a restriction on the power parameter is made. A particular symmetric
distribution interpolating between Wigner and arcsine distributions is
obtained. Its moments are expressed through a terminating hypergeometric series
interpolating between Catalan and shifed Catalan numbers. for small values of
the power parameter, the free cumulants are computed. Interesting opne problems
related to a deformed representation theory of the infinite symmetric group and
to a deformed Bozejko's convolution are discussed.


  The general conditions are discussed which quantum state purification
protocols have to fulfill in order to be capable of purifying Bell-diagonal
qubit-pair states, provided they consist of steps that map Bell-diagonal states
to Bell-diagonal states and they finally apply a suitably chosen
Calderbank-Shor-Steane code to the outcome of such steps. As a main result a
necessary and a sufficient condition on asymptotic correctability are
presented, which relate this problem to the magnitude of a characteristic
exponent governing the relation between bit and phase errors under the
purification steps. These conditions allow a straightforward determination of
maximum tolerable bit error rates of quantum key distribution protocols whose
security analysis can be reduced to the purification of Bell-diagonal states.


  The fate of the charge-neutral Dirac point in graphene in a high magnetic
field $H$ has been investigated at low temperatures ($T\sim$ 0.3 K). In samples
with small $V_0$ (the gate voltage needed to access the Dirac point), the
resistance $R_0$ at the Dirac point diverges steeply with $H$, signalling a
crossover to an insulating state in intense field. The approach to the
insulating state is highly unusual. Despite the steep divergence in $R_0$, the
profile of $R_0$ vs. $T$ in fixed $H$ saturates to a $T$-independent value
below 2 K, consistent with charge carrying gapless excitations.


  We study string theory duals of the expanding boost invariant conformal gauge
theory plasmas at strong coupling. The dual supergravity background is
constructed as an asymptotic late-time expansion, corresponding to
equilibration of the gauge theory plasma. The absence of curvature
singularities in the first few orders of the late-time expansion of the dual
gravitational background unambiguously determines the equilibrium equation of
the state, and the shear viscosity of the gauge theory plasma. While the
absence of the leading pole singularities in the gravitational curvature
invariants at the third order in late-time expansion determines the relaxation
time of the plasma, the subleading logarithmic singularity can not be canceled
within a supergravity approximation. Thus, a supergravity approximation to a
dual description of the strongly coupled boost invariant expanding plasma is
inconsistent. Nevertheless we find that the relaxation time determined from
cancellation of pole singularities is quite robust.


  This paper is concerned with the quasi-static rheology of packings of glass
spheres of diameter d (d=0.2mm, 0.7mm or 3mm). Stick-slip behaviour is observed
on small spheres, i.e d=0.2mm & 0.7mm ; one observes also in this case a
weakening of the rheology as the rate of deformation increases, and the larger
the rate the larger the weakening; this generates macroscopic instabilities and
stick-slip. Statistics of stick-slip events have been determined, which show
that the larger the sample the more regular (i.e. "periodic") the sick-slip,
the faster the strain rate the less periodic the events. One concludes that
this stick-slip is generated at the macroscopic level and comes from the
macroscopic rhelogical law. However when sample is small, local fluctuations
perturb the macroscopic events and trigger them erratically. Pacs # : 5.40 ;
45.70 ; 62.20 ; 83.70.Fn


  The purpose of this paper is to extend the definition of Frechet distance
which measures the distance between two curves to a distance (Frechet-Like
distance) which measures the similarity between two rooted trees. The
definition of Frechet-Like distance is as follows: Tow men start from the roots
of two trees. When they reach to a node with the degree of more than $2$, they
construct $k-1$ men which $k$ is the outgoing degree of the node and each man
monitor a man in another tree (there is a rope between them). The distance is
the minimum length of the ropes between the men and the men whom are monitored
and they all go forward (the geodesic distance between them to the root of the
tree increases) and reach to the leaves of the trees. Here, I prove that the
Frechet-Like distance between two trees is SNP-hard to compute.
  I modify the definition of Frechet-Like distance to measure the distance
between tow merge trees, and I prove the relation between the interleaving
distance and the modified Frechet-Like distance.


  We study the class of simple C*-algebras introduced by Villadsen in his
pioneering work on perforated ordered K-theory. We establish six equivalent
characterisations of the proper subclass which satisfies the strong form of
Elliott's classification conjecture: two C*-algebraic (Z-stability and
approximate divisibility), one K-theoretic (strict comparison of positive
elements), and three topological (finite decomposition rank, slow dimension
growth, and bounded dimension growth). The equivalence of Z-stability and
strict comparison constitutes a stably finite version of Kirchberg's
characterisation of purely infinite C*-algebras. The other equivalences
confirm, for Villadsen's algebras, heretofore conjectural relationships between
various notions of good behaviour for nuclear C*-algebras.


  A generalization of the Cooper pairing mechanism is proposed which allows for
a triplet state of lower energy. This is achieved by incorporating spin into
the canonical commutation relations and by modifying the $\delta$ potential
contact interaction. The gap equation contain as solutions both singlet and
triplet states. It is shown that the triplet state is lower in energy than the
singlet state which may explain the spin-triplet superconductivity observed in
heavy fermion compound UPt3 and in Sr$_2$RuO$_4$.


  Recent works show that speech separation guided diarization (SSGD) is an
increasingly promising direction, mainly thanks to the recent progress in
speech separation. It performs diarization by first separating the speakers and
then applying voice activity detection (VAD) on each separated stream. In this
work we conduct an in-depth study of SSGD in the conversational telephone
speech (CTS) domain, focusing mainly on low-latency streaming diarization
applications. We consider three state-of-the-art speech separation (SSep)
algorithms and study their performance both in online and offline scenarios,
considering non-causal and causal implementations as well as continuous SSep
(CSS) windowed inference. We compare different SSGD algorithms on two widely
used CTS datasets: CALLHOME and Fisher Corpus (Part 1 and 2) and evaluate both
separation and diarization performance. To improve performance, a novel, causal
and computationally efficient leakage removal algorithm is proposed, which
significantly decreases false alarms. We also explore, for the first time,
fully end-to-end SSGD integration between SSep and VAD modules. Crucially, this
enables fine-tuning on real-world data for which oracle speakers sources are
not available. In particular, our best model achieves 8.8% DER on CALLHOME,
which outperforms the current state-of-the-art end-to-end neural diarization
model, despite being trained on an order of magnitude less data and having
significantly lower latency, i.e., 0.1 vs. 1 s. Finally, we also show that the
separated signals can be readily used also for automatic speech recognition,
reaching performance close to using oracle sources in some configurations.


  We study the minor relation for algebra homomorphims in finitely generated
quasivarieties that admit a logarithmic natural duality. We characterize the
minor homomorphism posets of finite algebras in terms of disjoint unions of
dual partition lattices and investigate reconstruction problems for
homomorphisms.


  In this paper, the symplectic genus for any 2-dimensional class in a
4-manifold admitting a symplectic structure is introduced, and its relation
with the minimal genus is studied. It is used to describe which classes in
rational and irrational ruled manifolds are realized by connected symplectic
surfaces. In particular, we completely determine which classes with square at
least -1 in such manifolds can be represented by embedded spheres. Moreover,
based on a new characterization of the action of the diffeomorphism group on
the intersection forms of a rational manifold, we are able to determine the
orbits of the diffeomorphism group on the set of classes represented by
embedded spheres of square at least -1 in any 4-manifold admitting a symplectic
structure.


  The paper discusses methods, forms and safety issues of social network usage
for school students. Taking into consideration the growing interest of students
to electronic communication in social networks (ESN), it was described their
place in the information educational environment. There were made the
classification of objects and use of ESN to help teachers and school authority
to teach students in the corporate social network. The basic components of
corporate social networks were revealed: forms of learning activity
(individual, group, and collective), forms of learning (quiz, debates,
discussions, photo-story, essay contest, a virtual tour, mini design web quest,
and conference video-lesson), and database. They were defined particular
aspects of the use of certain forms for students training in ESN according to
the type of social objects (messages, individual messages, video files, photos,
audio files, documents, comments, and blitz-survey). Student safety when using
ESN is discussed as well.


  Recently, the Multilinear Compressive Learning (MCL) framework was proposed
to efficiently optimize the sensing and learning steps when working with
multidimensional signals, i.e. tensors. In Compressive Learning in general, and
in MCL in particular, the number of compressed measurements captured by a
compressive sensing device characterizes the storage requirement or the
bandwidth requirement for transmission. This number, however, does not
completely characterize the learning performance of a MCL system. In this
paper, we analyze the relationship between the input signal resolution, the
number of compressed measurements and the learning performance of MCL. Our
empirical analysis shows that the reconstruction error obtained at the
initialization step of MCL strongly correlates with the learning performance,
thus can act as a good indicator to efficiently characterize learning
performances obtained from different sensor configurations without optimizing
the entire system.


  In core-collapse supernovae, neutrinos and antineutrinos are initially
subject to significant self-interactions induced by weak neutral currents,
which may induce strong-coupling effects on the flavor evolution (collective
transitions). The interpretation of the effects is simplified when self-induced
collective transitions are decoupled from ordinary matter oscillations, as for
the matter density profile that we discuss. In this case, approximate
analytical tools can be used (pendulum analogy, swap of energy spectra). For
inverted neutrino mass hierarchy, the sequence of effects involves:
synchronization, bipolar oscillations, and spectral split. Our simulations
shows that the main features of these regimes are not altered when passing from
simplified (angle-averaged) treatments to full, multi-angle numerical
experiments.


  In these notes, we carefully analyze the properties of the "ramified"
Seiberg-Witten equations associated with supersymmetric configurations of the
Seiberg-Witten abelian gauge theory with surface operators on an oriented
closed four-manifold X. We find that in order to have sensible solutions to
these equations, only surface operators with certain parameters and embeddings
in X, are admissible. In addition, the corresponding "ramified" Seiberg-Witten
invariants on X with positive scalar curvature and b^+_2 > 1, vanish, while if
X has b^+_2 = 1, there can be wall-crossings whence the invariants will jump.
In general, for each of the finite number of basic classes that corresponds to
a moduli space of solutions with zero virtual dimension, the perturbed
"ramified" Seiberg-Witten invariants on Kahler manifolds will depend - among
other parameters associated with the surface operator - on the monopole number
"l" and the holonomy parameter "alpha". Nonetheless, the (perturbed) "ramified"
and ordinary invariants are found to coincide, albeit up to a sign, in some
examples.


  Automatic lane detection is a crucial technology that enables self-driving
cars to properly position themselves in a multi-lane urban driving
environments. However, detecting diverse road markings in various weather
conditions is a challenging task for conventional image processing or computer
vision techniques. In recent years, the application of Deep Learning and Neural
Networks in this area has proven to be very effective. In this project, we
designed an Encoder- Decoder, Fully Convolutional Network for lane detection.
This model was applied to a real-world large scale dataset and achieved a level
of accuracy that outperformed our baseline model.


  A necessary and sufficient condition for an inner function F in the upper
half-plane (UHP) to satisfy F = E*/E where E is a de Branges function is
presented. Since F_E =E^*/E is an inner function for any de Branges function E,
and the map that takes f to f/E is an isometry of the de Branges space H(E)
onto S(F_E), the orthogonal complement of F_E H^2, there is a natural bijective
correspondence between de Branges spaces of entire functions and the set of
subspaces S(F), for which F= E*/E for some de Branges function E. Under the
canonical isometry of H^2(UHP) onto H^2(D) the subspaces S(F_E) become certain
invariant subspaces for the backwards shift in H^2(D).
  I have been informed that the results contained in this paper are not new.
Most of the results in this paper can be found, for example, in Theorem 2.7,
Section 2.8, and Lemma 2.1 of V. Havin and J. Mashregi, "Admissable majorants
for model spaces of H^2, Part I: slow winding of the generating inner
function", Canad. J. Math. Vol. 55 (6), 2003 pp. 12311263. For this reason I
have withdrawn this article.


  It is now widely accepted that most ultraluminous X-ray sources (ULXs) are
binary systems whose large (above $10^{39}$ erg s$^{-1}$) apparent luminosities
are explained by super-Eddington accretion onto a stellar-mass compact object.
Many of the ULXs, especially those containing magnetized neutron stars, are
highly variable; some exhibit transient behaviour. Large luminosities might
imply large accretion discs that could be therefore prone to the
thermal-viscous instability known to drive outbursts of dwarf novae and
low-mass X-ray binary transient sources. The aim of this paper is to extend and
generalize the X-ray transient disc-instability model to the case of large
(outer radius larger than $10^{12}$ cm) accretion discs and apply it to the
description of systems with super-Eddington accretion rates at outburst and, in
some cases, super-Eddington mass transfer rates. We have used our
disc-instability-model code to calculate the time evolution of the accretion
disc and the outburst properties. We show that, provided that self-irradiation
of the accretion disc is efficient even when the accretion rate exceeds the
Eddington value, possibly due to scattering back of the X-ray flux emitted by
the central parts of the disc on the outer portions of the disc, heating fronts
can reach the disc's outer edge generating high accretion rates. We also
provide analytical approximations for the observable properties of the
outbursts. We have reproduced successfully the observed properties of galactic
transients with large discs, such as V404 Cyg, as well as some ULXs such as M51
XT-1. Our model can reproduce the peak luminosity and decay time of ESO 243-39
HLX-1 outbursts if the accretor is a neutron star. Observational tests of our
predicted relations between the outburst duration and decay time with peak
luminosity would be most welcome.


  In this paper, we studied the repeatability and accuracy of the ray
simulation for one kind of Asymmetric Resonant Cavities (ARCs)
Half-Quadrupole-Half-Circle shaped cavity, and confirmed the robustness of the
directionality about the shape errors. Based on these, we proposed a
hill-climbing algorithm to optimize the ARCs for unidirectional emission.
Different evaluation functions of directionality were tested and we suggested
using the function of energy contained in a certain angle for highly collimated
and unidirect ional emission. By this method, we optimized the ARCs to obtain
about 0.46 of the total radiated energy in divergence angle of 40 degree in the
far field. This optimization method is very powerful for the shape engineering
of ARCs and could be applied in future studies of ARCs with specific emission
properties.


  Probing vacuum structures deformed by high intense fields is of great
interest in general. In the context of quantum electrodynamics (QED), the
vacuum exposed by a linearly polarized high-intensity laser field is expected
to show birefringence. We consider the combination of a 10 PW laser system to
pump the vacuum and 1 GeV photons to probe the birefringent effect. The vacuum
birefringence can be measured via the polarization flip of the probe
$\gamma$-rays which can also be interpreted as phase retardation of probe
photons. We provide theoretically how to extract phase retardation of GeV probe
photons via pair-wise topology of the Bethe-Heitler process in a polarimeter
and then evaluate the measurability of the vacuum birefringence via phase
retardation given a concrete polarimeter design with a realistic set of laser
parameters and achievable pulse statistics.


  The magnetoplasmon spectrum of a magnetically modulated two-dimensional
electron gas (MM2DEG) is investigated. We derive the inter and intra Landau
band magnetoplasmon spectrum within the self consistent field approach. The
derivation is performed at zero temperature as well as at finite temperature.
Results are presented for the inter and intra Landau band magnetoplasmon
spectrum as a function of the inverse magnetic field. As a result of magnetic
modulation, magnetic Weiss oscillations are found to occur in the
magnetoplasmon spectrum. Furthermore, our finite temperature theory facilitates
analysis of effects of temperature on the magnetoplasmon spectrum. The results
are compared with those obtained for an electrically modulated 2DEG system. In
addition, we derive and discuss the effects of simultaneous electric and
magnetic modulations on the magnetoplasmon spectrum of 2DEG when the
modulations are in phase as well as when they are out of phase. Magnetic
oscillations are affected by the relative phase of the two modulations and
position of the oscillations depends on the relative strength of the two
modulations in the former case while we find complete suppression of Weiss
oscillations for particular relative strength of the modulations in the latter
case.


  Information on globular clusters (GC) formation mechanisms can be gathered by
studying the chemical signature of the multiple populations that compose these
stellar systems. In particular, we are investigating the anticorrelations among
O, Na, Al, and Mg to explore the influence of cluster mass and environment on
GCs in the Milky Way and in extragalactic systems. We present here the results
obtained on NGC 6139 which, on the basis of its horizontal branch morphology,
had been proposed to be dominated by first-generation stars. In our extensive
study based on high resolution spectroscopy, the first for this cluster, we
found a metallicity of [Fe/H]= -1.579 +/- 0.015 +/- 0.058 (rms=0.040 dex, 45
bona fide member stars) on the UVES scale defined by our group. The stars in
NGC 6139 show a chemical pattern normal for GCs, with a rather extended Na-O
(and Mg-Al) anticorrelation. NGC 6139 behaves like expected from its mass and
contains a large fraction (about two thirds) of second-generation stars.


  Intense hard x-ray pulses from a free-electron laser induce irreversible
structural damage in a perovskite oxide epitaxial heterostructure when pulse
fluences exceed a threshold value. The intensity of x-ray diffraction from a
25-nm thick epitaxial BiFeO$_{3}$ layer on a SrTiO$_{3}$ substrate measured
using a series of pulses decreases abruptly with a per-pulse fluence of 2.7 x
10$^{6}$ photons ${\mu}$m$^{-2}$ at 9.7 keV photon energy, but remains constant
for 1.3 x 10$^{6}$ photons ${\mu}$m$^{-2}$ or less. The damage resulted in the
destruction of the BiFeO$_{3}$ thin film within the focal spot area and the
formation of a deep cavity penetrating into the STO substrate via the removal
of tens of nanometers of material per pulse. The damage threshold occurs at a
fluence that is insufficient to heat the absorption volume to the melting
point. The morphology of the ablated sample is consistent with fracture rather
than melting. Together these results indicate that the damage occurs via a
non-thermal process consistent with ultrafast ionization of the absorption
volume.


  Mn-based transition metal Zintl compounds in the 14-1-11 phase are known to
host complex atomic and magnetic structures owing to their intricate crystal
structure. Among them, Ba14MnBi11 stands out as one of the least understood
compounds, with experimental measurements and theoretical findings largely
inconsistent. Following up on the earlier attempt [D. Sanchez-Portal et al.,
PRB 65, 144414 (2002)] at establishing a connection between metallicity and
magnetism through a DFT-based analysis, our work aims to provide additional
insights to resolve the existing contradictions. Our key finding is that the
magnetic ground state is very susceptible to charge doping. DFT calculations
for stoichiometric Ba14MnBi11 give a rather stable ferromagnetic metallic
ground state. However, by adding exactly one additional electron per Mn, the
system becomes semiconducting and the magnetic ground state becomes weakly
antiferromagnetic (AF). On the other hand, upon small hole doping the system
transitions to a special type of AF state known as altermagnetic ordering. The
observed trends suggest that hole and electron doping-induced phase transitions
likely result from different underlying mechanisms, influencing various
exchange pathways. Additionally, our projected density-of-states along with
bandstructure analyses indicate that, besides the largest hole contribution
coming from the tetrahedral unit of Bi, the isolated Bi sites also play a
substantial role and the dispersive bands near VBM suggest a rather complex
hybridization network involving both Bi band characters. Through a
comprehensive comparison of available data and our analysis, we propose that
the inconsistency in magnetic states between experimental findings and DFT
calculations is due to nonstoichiometric effects, likely impurities or defects.


  A graph $H$ is common if its Ramsey multiplicity, i.e., the minimum number of
monochromatic copies of $H$ contained in any $2$-edge-coloring of $K_n$, is
asymptotically the same as the number of monochromatic copies in the random
$2$-edge-coloring of $K_n$. Erd\H{o}s conjectured that every complete graph is
common, which was disproved by Thomason in the 1980s. Till today, a
classification of common graphs remains a widely open challenging problem.
Grzesik, Lee, Lidick\'y and Volec [Combin. Prob. Comput. 31 (2022), 907--923]
conjectured that every $k$-apex of any connected Sidorenko graph is common. We
prove for $k\le 5$ that the $k$-apex of any tree is common.


  With the aim of designing automated tools that assist in the video game
quality assurance process, we frame the problem of identifying bugs in video
games as an anomaly detection (AD) problem. We develop State-State Siamese
Networks (S3N) as an efficient deep metric learning approach to AD in this
context and explore how it may be used as part of an automated testing tool.
Finally, we show by empirical evaluation on a series of Atari games, that S3N
is able to learn a meaningful embedding, and consequently is able to identify
various common types of video game bugs.


  We present an open source math-aware Question Answering System based on Ask
Platypus. Our system returns as a single mathematical formula for a natural
language question in English or Hindi. This formulae originate from the
knowledge-base Wikidata. We translate these formulae to computable data by
integrating the calculation engine sympy into our system. This way, users can
enter numeric values for the variables occurring in the formula. Moreover, the
system loads numeric values for constants occurring in the formula from
Wikidata. In a user study, our system outperformed a commercial computational
mathematical knowledge engine by 13%. However, the performance of our system
heavily depends on the size and quality of the formula data available in
Wikidata. Since only a few items in Wikidata contained formulae when we started
the project, we facilitated the import process by suggesting formula edits to
Wikidata editors. With the simple heuristic that the first formula is
significant for the article, 80% of the suggestions were correct.


  Human parsing is for pixel-wise human semantic understanding. As human bodies
are underlying hierarchically structured, how to model human structures is the
central theme in this task. Focusing on this, we seek to simultaneously exploit
the representational capacity of deep graph networks and the hierarchical human
structures. In particular, we provide following two contributions. First, three
kinds of part relations, i.e., decomposition, composition, and dependency, are,
for the first time, completely and precisely described by three distinct
relation networks. This is in stark contrast to previous parsers, which only
focus on a portion of the relations and adopt a type-agnostic relation modeling
strategy. More expressive relation information can be captured by explicitly
imposing the parameters in the relation networks to satisfy the specific
characteristics of different relations. Second, previous parsers largely ignore
the need for an approximation algorithm over the loopy human hierarchy, while
we instead address an iterative reasoning process, by assimilating generic
message-passing networks with their edge-typed, convolutional counterparts.
With these efforts, our parser lays the foundation for more sophisticated and
flexible human relation patterns of reasoning. Comprehensive experiments on
five datasets demonstrate that our parser sets a new state-of-the-art on each.


  An experimental investigation of a new interaction connected with the
existence of the cosmological vectorial potential, has been carried out. On its
basis, a new method of energy generation with the use of a plasma generator,
has been studied. The experimental results and complete analysis of errors in
the experiments are presented.


  We study the dynamics of spatially homogeneous and isotropic spacetimes
containing a fluid undergoing microscopic velocity diffusion in a cosmological
scalar field. After deriving a few exact solutions of the equations, we
continue by analyzing the qualitative behavior of general solutions. To this
purpose we recast the equations in the form of a two dimensional dynamical
system and perform a global analysis of the flow. Among the admissible
behaviors, we find solutions that are asymptotically de-Sitter both in the past
and future time direction and which undergo accelerated expansion at all times.


  Cadmium zinc telluride (CdZnTe, CZT) radiation detectors are suitable for a
variety of applications, due to their high spatial resolution and spectroscopic
energy performance at room temperature. However, state-of-the-art detector
systems require high-performance readout electronics. Though an
application-specific integrated circuit (ASIC) is an adequate solution for the
readout, requirements of high dynamic range and high throughput are not
available in any commercial circuit. Consequently, the present study develops
the analog front-end electronics with operational amplifiers for an 8x8
pixelated CZT detector. For this purpose, we modeled an electrical equivalent
circuit of the CZT detector with the associated charge-sensitive amplifier
(CSA). Based on a detailed network analysis, the circuit design is completed by
numerical values for various features such as ballistic deficit,
charge-to-voltage gain, rise time, and noise level. A verification of the
performance is carried out by synthetic detector signals and a pixel detector.
The experimental results with the pixel detector assembly and a 22Na
radioactive source emphasize the depth dependence of the measured energy. After
pulse processing with depth correction based on the fit of the weighting
potential, the energy resolution is 2.2% (FWHM) for the 511 keV photopeak.


  Transport through molecular devices with weak tunnel coupling to the leads
but with strong coupling to a single vibrational mode is considered in the case
where the vibration is damped by coupling to the environment. In particular, we
investigate what influence the electrostatic coupling of the charge on the
molecule to the vibrational modes of the environment has on the $I$-$V$
characteristics. We find that, for comparable characteristic length scales of
the van-der-Waals and electrostatic interaction of the molecule with the
environmental vibrational modes, the $I$-$V$ characteristics are qualitatively
changed from what one would expect from orthogonality catastrophe and develop a
steplike discontinuity at the onset of conduction. For the case of very
different length scales, we recover dissipation consistent with modeling the
electrostatic forces as an external influence on the system comprised of
molecule and substrate, which implies the appearance of orthogonality
catastrophe, in accord with previous results.


  A general expression for a relative invariant of a linear ordinary
differential equations is given in terms of the fundamental semi-invariant and
an absolute invariant. This result is used to established a number of
properties of relative invariants, and it is explicitly shown how to generate
fundamental sets of relative and absolute invariants of all orders for the
general linear equation. Explicit constructions are made for the linear ODE of
order five. The approach used for the explicit determination of invariants is
based on an infinitesimal method.


  The link between low-energy CP violation and leptogenesis became more
accessible with the understanding of flavor effects. However, a definite
well-motivated model where such a link occurs was still lacking. Adjoint SU(5)
is a simple grand unified theory where neutrino masses are generated through
the Type I and Type III seesaw mechanisms, and the lepton asymmetry is
generated by the fermionic triplet responsible for the Type III seesaw. We
focus exclusively on the case of inverted hierarchy for neutrinos, and we show
that successful flavored leptogenesis in this theory strongly points towards
low-energy CP violation. Moreover, since the range of allowed masses for the
triplet is very restricted, we find that the discovery at the LHC of new states
present in the theory, together with proton decay and unification of gauge
couplings, can conspire to provide a hint in favor of leptogenesis.


  We discuss how to classify the $c{\bar s}$ meson $D_{sJ}(3040)$ recently
discovered by the BaBar Collaboration. We consider four possible assignments,
together with signatures useful to distinguish among them.


  We study the sub-Laplacian of the $15$-dimensional unit sphere which is
obtained by lifting with respect to the Hopf fibration the Laplacian of the
octonionic projective space. We obtain in particular explicit formulas for its
heat kernel and deduce an expression for the Green function of a related
sub-Laplacian. As a byproduct we also obtain the spectrum of the sub-Laplacian,
the small-time asymptotics of the heat kernel and explicitly compute the
sub-Riemannian distance.


  Recent studies have evidenced that long-baseline (LBL) experiments are
sensitive to the extra CP-phases involved with light sterile neutrinos, whose
existence is suggested by several anomalous short-baseline (SBL) results. We
show that, within the 3+1 scheme, the combination of the existing SBL data with
the LBL results coming from the two currently running experiments NO$\nu$A and
T2K, enables us to simultaneously constrain two active-sterile mixing angles
$\theta_{14}$ and $\theta_{24}$ and two CP-phases $\delta_{13} \equiv \delta$
and $\delta_{14}$, albeit the information on the second CP-phase is still weak
at the moment. The two mixing angles are basically determined by the SBL data,
while the two CP-phases are constrained by the LBL experiments, once the
information coming from the SBL setups is taken into account. We also assess
the robustness/fragility of the estimates of the standard 3-flavor parameters
in the more general 3+1 scheme. To this regard we find that: i) the indication
of CP-violation found in the 3-flavor analyses persists also in the 3+1 scheme,
with $\delta_{13} \equiv \delta$ having still its best fit value around
$-\pi/2$; ii) the 3-flavor weak hint in favor of the normal hierarchy becomes
even less significant when sterile neutrinos come into play; iii) the weak
indication of non-maximal $\theta_{23}$ (driven by NO$\nu$A disappearance data)
persists in the 3+1 scheme, where maximal mixing is disfavored at almost the
90\% C.L. in both normal and inverted mass hierarchy; iv) the preference in
favor of one of the two octants of $\theta_{23}$ found in the 3-flavor
framework (higher octant for inverted mass hierarchy) is completely washed out
in the 3+1 scheme.


  Let T be an SMT solver with no theory solvers except for Quantifier
Instantiation. Given a set of first-order clauses S saturated by Resolution
(with a valid literal selection function) we show that T is complete if its
Trigger function is the same as the literal selection function. So if T halts
with a ground model G, then G can be extended to a model in the theory of S. In
addition for a suitable ordering, if all maximal literals are selected in each
clause, then T will halt on G, so it is a decision procedure for the theory S.
Also, for a suitable ordering, if all clauses are Horn, or all clauses are
2SAT, then T solves the theory S in polynomial time.


  Crowdsourcing is defined as the outsourcing of tasks to a crowd of
contributors. The crowd is very diverse on these platforms and includes
malicious contributors attracted by the remuneration of tasks and not
conscientiously performing them. It is essential to identify these contributors
in order to avoid considering their responses. As not all contributors have the
same aptitude for a task, it seems appropriate to give weight to their answers
according to their qualifications. This paper, published at the ICTAI 2019
conference, proposes a method, MONITOR, for estimating the profile of the
contributor and aggregating the responses using belief function theory.


  We explain an elementary topological construction of the Springer
representation on the homology of (topological) Springer fibers of types C and
D in the case of nilpotent endomorphisms with two Jordan blocks. The Weyl group
and component group actions admit a diagrammatic description in terms of cup
diagrams which appear in the definition of arc algebras of types B and D. We
determine the decomposition of the representations into irreducibles and relate
our construction to classical Springer theory. As an application we obtain
presentations of the cohomology rings of all two-block Springer fibers of types
C and D. Moreover, we deduce explicit isomorphisms between the Kazhdan-Lusztig
cell modules attached to the induced trivial module and the irreducible Specht
modules in types C and D.


  In this work, we present a numerical method that remedies the instabilities
of the conventional FDTD approach for solving Maxwell's equations in a
space-time dependent magneto-electric medium with direct application to the
simulation of the recently proposed spacetime cloak. We utilize a dual grid
FDTD method overlapped to the time domain to provide a stable approach for the
simulation of magneto-electric medium with time and space varying permittivity,
permeability and coupling coefficient. The developed method can be applied to
explore other new physical possibilities offered by spacetime cloaking,
metamaterials, and transformation optics.


  We study the properties of moving breathers in a bent DNA-related model with
short range interaction, due to the stacking of the base pairs, and long range
interaction, due to the finite dipole moment of the bonds within each base
pair. We show that the movement of a breather is hindered by the bending of the
chain as a particle in a potential barrier. We have also found that the
behaviour of moving breathers in an homogeneous bent chain and in a straight
chain with a small impurity is qualitatively equivalent.


  Pairwise learning corresponds to the supervised learning setting where the
goal is to make predictions for pairs of objects. Prominent applications
include predicting drug-target or protein-protein interactions, or
customer-product preferences. In this work, we present a comprehensive review
of pairwise kernels, that have been proposed for incorporating prior knowledge
about the relationship between the objects. Specifically, we consider the
standard, symmetric and anti-symmetric Kronecker product kernels,
metric-learning, Cartesian, ranking, as well as linear, polynomial and Gaussian
kernels. Recently, a O(nm + nq) time generalized vec trick algorithm, where n,
m, and q denote the number of pairs, drugs and targets, was introduced for
training kernel methods with the Kronecker product kernel. This was a
significant improvement over previous O(n^2) training methods, since in most
real-world applications m,q << n. In this work we show how all the reviewed
kernels can be expressed as sums of Kronecker products, allowing the use of
generalized vec trick for speeding up their computation. In the experiments, we
demonstrate how the introduced approach allows scaling pairwise kernels to much
larger data sets than previously feasible, and provide an extensive comparison
of the kernels on a number of biological interaction prediction tasks.


  In this paper, we reexamine the validity of using time quantified Monte Carlo
(TQMC) method [Phys. Rev. Lett. 84, 163 (2000); Phys. Rev. Lett. 96, 067208
(2006)] in simulating the stochastic dynamics of interacting magnetic
nanoparticles. The Fokker-Planck coefficients corresponding to both TQMC and
Langevin dynamical equation (Landau-Lifshitz-Gilbert, LLG) are derived and
compared in the presence of interparticle interactions. The time quantification
factor is obtained and justified. Numerical verification is shown by using TQMC
and Langevin methods in analyzing spin-wave dispersion in a linear array of
magnetic nanoparticles.


  Characterization of successful formulas in Public Announcement Logic (PAL) is
a well known open problem in Dynamic Epistemic Logic. Recently, Holliday and
ICard have given a complete characterization for the single agent case.
However, the problem for the multi-agent case is open. This paper gives a
partial solution to the problem, characterizing the subclass of the language
consisting of unary operators, and discusses methods to give a complete
solution.


  For compressive sensing of dynamic sparse signals, we develop an iterative
pursuit algorithm. A dynamic sparse signal process is characterized by varying
sparsity patterns over time/space. For such signals, the developed algorithm is
able to incorporate sequential predictions, thereby providing better
compressive sensing recovery performance, but not at the cost of high
complexity. Through experimental evaluations, we observe that the new algorithm
exhibits a graceful degradation at deteriorating signal conditions while
capable of yielding substantial performance gains as conditions improve.


  Almost three decades ago, the problem of long term polar wander on a dynamic
planet was formulated and simplified within the framework of normal mode
theory. The underlying simplifications have been debated ever since, recently
in a series of papers by Hu et al. 2017a, 2017b, and 2019, who clarify the role
of neglecting short-term relaxation modes of the body. However, the authors
still do not solve the governing equations in full, because they make
approximations to the Liouville equation (LE). In this paper I use a time
domain approach and for previously studied test loads I solve both the
relaxation of the body and the LE in full. I also compute the energy balance of
true polar wander (TPW) in order to analyze the existing LE approximations. For
fast rotating bodies such as the Earth, I show that the rotation axis is always
aligned with the maximum principal axis of inertia (w||MMOI) once free
oscillations are damped. The w||MMOI assumption is also re-derived
theoretically. Contrary to previous beliefs, I demonstrate that it is not
necessarily linked to the quasi-fluid simplification of the body's viscoelastic
response to loading and rotation, but that it is an expression of neglecting
the Coriolis and Euler forces in the equation of motion. For slowly rotating
bodies such as Venus, the full LE together with energy analysis indicate that
previous estimates of TPW in the normal direction need to be revisited. The
numerical code LIOUSHELL is made freely available.


  Let $\lambda_2(G)$ and $\kappa'(G)$ be the second largest eigenvalue and the
edge-connectivity of a graph $G$, respectively. Let $d$ be a positive integer
at least 3. For $t=1$ or 2, Cioaba proved sharp upper bounds for $\lambda_2(G)$
in a $d$-regular simple graph $G$ to guarantee that $\kappa'(G) \ge t+1$. In
this paper, we settle down for all $t \ge 3$.


  The pairing symmetry in the electron mechanism for superconductivity is
explored when charge fluctuations coexist with spin fluctuations. The extended
Hubbard model is adopted to obtain, with the fluctuation exchange
approximation, a phase diagram against the on-site Coulomb repulsion U and the
off-site repulsion V for the square lattice with second-neighbor hopping t'. We
have found that (i) for large U(>9) a triplet superconductivity with a
sin(kx+ky) symmetry can appear just below the charge density wave phase. The
pairing is degenerate with sin(kx-ky), so a chiral sin(kx+ky)+isin(kx-ky) that
breaks the time reversal symmetry should result, which is a candidate for the
gap function on the gamma band of Sr2RuO4 and is consistent with a recent
measurement of the specific heat. (ii) By systematically deforming the Fermi
surface with varied t', we have identified the region where the triplet pairing
is most favored to be the region where the Fermi surface traverses the van Hove
singularity with the charge susceptibility strongly enhanced.


  The lattice studies of maximally supersymmetric Yang-Mills (MSYM) theory at
strong coupling and large N is important for verifying gauge/gravity duality.
Due to the progress made in the last decade, based on ideas from topological
twisting and orbifolding, it is now possible to study these theories on the
lattice while preserving an exact supersymmetry on the lattice. We present some
results from the lattice studies of two-dimensional MSYM which is related to
Type II supergravity. Our results agree with the thermodynamics of different
black hole phases on the gravity side and the phase transition
(Gregory--Laflamme) between them.


  The main object of study in this paper is the module $\Omega$ of K\"ahler
differentials of an extension of valuation rings. We show that in the case of
pure extensions $\Omega$ has a very good description. Namely, it is isomorphic
to the quotient of two modules defined by final segments in the value group of
the valuation. This allows us to describe the annihilator of $\Omega$ and to
give criteria for $\Omega$ to be finitely generated and to be finitely
presented. We also discuss how to relate the module of K\"ahler differentials
of pure extensions to minimal key polynomials.


  The semi-regular variable star V Canum Venaticorum (V CVn) is well-known for
its unusual linear polarization position angle (PA). Decades of observing V CVn
reveal a nearly constant PA spanning hundreds of pulsation cycles. This
phenomenon has persisted through variability that has ranged by 2 magnitudes in
optical brightness and through variability in the polarization amplitude over
0.3% and 6.9%. Additionally, the polarization fraction of V CVn varies
inversely with brightness.
  This paper presents polarization measurements obtained over three pulsation
cycles. We find that the polarization maximum does not always occur precisely
at the same time as the brightness minimum. Instead, we observe a small lead or
lag in relation to the brightness minimum, spanning a period of a few days up
to three weeks. Furthermore, the PA sometimes exhibits a non-negligible
rotation, especially at lower polarization levels.
  To elucidate the unusual optical behavior of V CVn, we present a list of
literature sources that also exhibit polarization variability with a roughly
fixed PA. We find this correlation occurs in stars with high tangential space
velocities, i.e., "runaway" stars, suggesting that the long-term constant PA is
related to how the circumstellar gas is shaped by the star's high-speed motion
through the interstellar medium.


  According to the World Health Organization (WHO), cancer is the second
leading cause of death worldwide, responsible for over 9.5 million deaths in
2018 alone. Brain tumors count for one out of every four cancer deaths.
Therefore, accurate and timely diagnosis of brain tumors will lead to more
effective treatments. Physicians classify brain tumors only with biopsy
operation by brain surgery, and after diagnosing the type of tumor, a treatment
plan is considered for the patient. Automatic systems based on machine learning
algorithms can allow physicians to diagnose brain tumors with noninvasive
measures. To date, several image classification approaches have been proposed
to aid diagnosis and treatment. For brain tumor classification in this work, we
offer a system based on deep learning, containing encoder blocks. These blocks
are fed with post-max-pooling features as residual learning. Our approach shows
promising results by improving the tumor classification accuracy in Magnetic
resonance imaging (MRI) images using a limited medical image dataset.
Experimental evaluations of this model on a dataset consisting of 3064 MR
images show 95.98% accuracy, which is better than previous studies on this
database.


  About a decade ago, using a specific expansion scheme, effective, on-brane
scalar tensor theories of gravity were proposed by Kanno and Soda (Phys.Rev.
{\bf D 66} 083506 ,(2002)) in the context of the warped two brane model of
Randall--Sundrum. The inter-related effective theories on both the branes were
derived with the space-time dependent radion field playing a crucial role.
Taking a re-look at this effective theory, we find cosmological and spherically
symmetric, static solutions sourced by a radion--induced, effective stress
energy, as well as additional, on-brane matter. The distance between the branes
(governed by the time or space dependent radion) is shown to be stable and
asymptotically non-zero, thereby setting aside any possibility of brane
collisions. It turns out that the inclusion of on-brane matter plays a decisive
role in stabilising the radion - a fact which we demonstrate through our
solutions.


  Dimensionality reduction is a critical step in scaling machine learning
pipelines. Principal component analysis (PCA) is a standard tool for
dimensionality reduction, but performing PCA over a full dataset can be
prohibitively expensive. As a result, theoretical work has studied the
effectiveness of iterative, stochastic PCA methods that operate over data
samples. However, termination conditions for stochastic PCA either execute for
a predetermined number of iterations, or until convergence of the solution,
frequently sampling too many or too few datapoints for end-to-end runtime
improvements. We show how accounting for downstream analytics operations during
DR via PCA allows stochastic methods to efficiently terminate after operating
over small (e.g., 1%) subsamples of input data, reducing whole workload
runtime. Leveraging this, we propose DROP, a DR optimizer that enables speedups
of up to 5x over Singular-Value-Decomposition-based PCA techniques, and exceeds
conventional approaches like FFT and PAA by up to 16x in end-to-end workloads.


  We consider the energy-efficiency of Multiple-Input Multiple-Output (MIMO)
systems with constrained received power rather than constrained transmit power.
A Energy-Efficient Water-Filling (EEWF) algorithm that maximizes the ratio of
the transmission rate to the total transmit power has been derived. The EEWF
power allocation policy establishes a trade-off between the transmission rate
and the total transmit power under the total receive power constraint. The
static and the uncorrelated fast fading Rayleigh channels have been considered,
where the maximization is performed on the instantaneous realization of the
channel assuming perfect information at both the transmitter and the receiver
with equal number of antennas. We show, based on Monte Carlo simulations that
the energy-efficiency provided by the EEWF algorithm can be more than an order
of magnitude greater than the energy-efficiency corresponding to capacity
achieving Water-Filling (WF) algorithm. We also show that the energy-efficiency
increases with both the number of antennas and the signal-to-noise ratio. The
corresponding transmission rate also increases but at a slower rate than the
Shannon capacity, while the corresponding total transmit power decreases with
the number of antennas.


  Document image restoration is a crucial aspect of Document AI systems, as the
quality of document images significantly influences the overall performance.
Prevailing methods address distinct restoration tasks independently, leading to
intricate systems and the incapability to harness the potential synergies of
multi-task learning. To overcome this challenge, we propose DocRes, a
generalist model that unifies five document image restoration tasks including
dewarping, deshadowing, appearance enhancement, deblurring, and binarization.
To instruct DocRes to perform various restoration tasks, we propose a novel
visual prompt approach called Dynamic Task-Specific Prompt (DTSPrompt). The
DTSPrompt for different tasks comprises distinct prior features, which are
additional characteristics extracted from the input image. Beyond its role as a
cue for task-specific execution, DTSPrompt can also serve as supplementary
information to enhance the model's performance. Moreover, DTSPrompt is more
flexible than prior visual prompt approaches as it can be seamlessly applied
and adapted to inputs with high and variable resolutions. Experimental results
demonstrate that DocRes achieves competitive or superior performance compared
to existing state-of-the-art task-specific models. This underscores the
potential of DocRes across a broader spectrum of document image restoration
tasks. The source code is publicly available at
https://github.com/ZZZHANG-jx/DocRes


  We study the problem of finding a minimal graph with prescribed boundary data
in arbitrary dimension and codimension. Existence, uniqueness, stability and
regularity are treated. We first present the well-known results for codimension
one: Jenkins-Serrin's existence theorem, convexity properties of the area which
give uniqueness and stability and De Giorgi's theorem for regularity. In higher
codimension we first discuss the counterexamples of Lawson and Osserman. Then
we present the recent results of Mu-Tao Wang: we use the mean curvature flow to
show existence for small boundary data and we prove a new Bernstein theorem
(also due to Mu-Tao Wang) which holds for every area-decreasing minimal graph.
We finally deduce from the Bernstein theorem that an area-decreasing minimal
graph is always smooth.


  Be stars are rapidly rotating B type stars. The origin of their rapid
rotation is not certain, but binary interaction remains to be a possibility. In
this work we investigate the formation of Be stars resulting from mass transfer
in binaries in the Galaxy. We calculate the binary evolution with both stars
evolving simultaneously and consider different possible mass accretion
histories for the accretor. From the calculated results we obtain the critical
mass ratios $q_{\rm cr}$ that determine the stability of mass transfer. We also
numerically calculate the parameter $\lambda$ in common envelope evolution, and
then incorporate both $q_{\rm cr}$ and $\lambda$ into the population synthesis
calculations. We present the predicted numbers and characteristics of Be stars
in binary systems with different types of companions, including helium stars,
white dwarfs, neutron stars, and black holes. We find that in Be/neutron star
binaries the Be stars can have a lower limit of mass $ \sim 8 M_{\odot}$ if
they are formed by stable (i.e., without the occurrence of common envelope
evolution) and nonconservative mass transfer. We demonstrate that isolated Be
stars may originate from both mergers of two main-sequence stars and disrupted
Be binaries during the supernova explosions of the primary stars, but mergers
seem to play a much more important role. Finally the fraction of Be stars which
have involved binary interactions in all B type stars can be as high as $ \sim
13%-30% $, implying that most of Be stars may result from binary interaction.


  Mechanical systems are usually modeled by second-order Ordinary Differential
Equations (ODE) which take the form $\ddot{q} = f(t, q, \dot{q})$. While
simulation methods tailored to these equations have been studied, using them in
direct optimal control methods is rare. Indeed, the standard approach is to
perform a state augmentation, adding the velocities to the state. The main
drawback of this approach is that the number of decision variables is doubled,
which could harm the performance of the resulting optimization problem. In this
paper, we present an approach tailored to second-order ODE. We compare it with
the standard one, both on theoretical aspects and in a numerical example.
Notably, we show that the tailored formulation is likely to improve the
performance of a direct collocation method, for solving optimal control
problems with second-order ODE of the more restrictive form $\ddot{q} = f(t,
q)$.


  We present the first fast and detailed computation of the cosmological
recombination radiation released during the hydrogen (redshift z ~ 1300) and
helium (z ~ 2500 and z ~ 6000) recombination epochs, introducing the code
CosmoSpec. Our computations include important radiative transfer effects,
500-shell bound-bound and free-bound emission for all three species, the
effects of electron scattering and free-free absorption as well as interspecies
(HeII --> HeI --> HI) photon feedback. The latter effect modifies the shape and
amplitude of the recombination radiation and CosmoSpec improves significantly
over previous treatments of it. Utilizing effective multilevel atom and
conductance approaches, one calculation takes only ~ 15 seconds on a standard
laptop as opposed to days for previous computations. This is an important step
towards detailed forecasts and feasibility studies considering the detection of
the cosmological recombination lines and what one may hope to learn from the ~
6.1 photons emitted per hydrogen atom in the three recombination eras. We
briefly illustrate some of the parameter dependencies and discuss remaining
uncertainties in particular related to collisional processes and the neutral
helium atom model.


  We give a method for obtaining a handle decomposition of an $n$-manifold if
the manifold is given by isometric side-pairings of a polyhedron in $\en$,
$\sn$ or $\hn$. Every cycle of $k$-faces on the polyhedron corresponds to an
$(n-k)$-handle of the manifold.
  Two applications of the method are given. One helps recognize when a
noncompact hyperbolic 3-manifold is a complement of a link in $S^3$ (and
automatically produces the link diagram), the other shows that a topological
$S^4$ described by the author in \cite{Ivansic3} is diffeomorphic to the
standard differentiable $S^4$.


  Coherent population trapping (CPT) refers to the steady-state trapping of
population in a coherent superposition of two ground states which are coupled
by coherent optical fields to an intermediate state in a three-level atomic
system. Recently, CPT has been observed in an ensemble of donor bound spins in
GaAs and in single nitrogen vacancy centers in diamond by using a fluorescence
technique. Here we report the demonstration of CPT of an electron spin in a
single quantum dot (QD) charged with one electron.


  Time varying media recently emerged as promising candidates to fulfill the
dream of controlling the wave frequency without nonlinear effects. However,
frequency conversion remains limited by the dynamics of the variations of the
propagation properties. Here we propose a new concept of space-time cascade to
achieve arbitrary large frequency shifts by iterated elementary transformation
cycles. These cycles use an intermediate medium in which wave packets enter and
exit through non-commutative space and time interfaces. This concept avoids
high frequency or sub-wavelength demanding metamaterials. Upward and downward
frequency conversions are performed with 100% efficiency regardless of
impedance matching. As an example, we implement this concept with water waves
controlled by electrostriction and achieve frequency conversion cascades over a
range of 4 octaves.


  We establish that the geometric action of the absolute Galois group on the
\'etale fundamental group of moduli spaces of curves induces a Galois action on
its stack inertia subgroups, and that this action is given by cyclotomy
conjugacy. This result extends the special case of inertia without \'etale
factorisation previously established by the authors. It is here obtained in the
general case by comparing deformations of Galois actions.
  Since the stack inertia corresponds to the first level of the stack
stratification of the space, this results, by analogy with the arithmetic of
the Deligne-Mumford stratification, opens the way to a systematic Galois study
of the stack inertia through the corresponding stratification of the moduli
stack


  We study commutative Schur rings over the symplectic groups Sp$(n,2)$
containing the class $\mathcal C$ of symplectic transvections. We find the
possible partitions of $\mathcal C$ determined by the Schur ring. We show how
this restricts the possibilities for multiplicity one subgroups of Sp$(n,2)$.


  This paper considers three dichotomy concepts (exponential dichotomy, uniform
exponential dichotomy and strong exponential dichotomy) in the general context
of non-invertible evolution operators in Banach spaces. Connections between
these concepts are illustrated. Using the notion of Green function, we give
necessary conditions and sufficient ones for strong exponential dichotomy. Some
illustrative examples are presented to prove that the converse of some
implication type theorems are not valid.


  We have investigated the eclipse of the 23-ms pulsar J0737-3039A by its 2.8-s
companion PSR J0737-3039B in the recently discovered double pulsar system using
data taken with the Green Bank Telescope at 820 MHz. We find that the pulsed
flux density at eclipse is strongly modulated with half the periodicity of the
2.8-s pulsar. The eclipse occurs earlier and is deeper at those rotational
phases of B when its magnetic axis is aligned with the line of sight than at
phases when its magnetic axis is at right angles to the line of sight. This is
consistent with the eclipse of A being due to synchrotron absorption by the
shock-heated plasma surrounding B, the asymmetry arising from the higher plasma
densities expected in the B magnetosphere's polar cusps.


  Given an open set $\Omega\subset\mathbb{R}^3$. We deal with the spectral
study of Dirac operators of the form
$H_{a,\tau}=H+A_{a,\tau}\delta_{\partial\Omega}$, where $H$ is the free Dirac
operator in $\mathbb{R}^3$, $A_{a,\tau}$ is a bounded invertible, self-adjoint
operator in $\mathit{L}^{2}(\partial\Omega)^4$, depending on parameters
$(a,\tau)\in\mathbb{R}\times\mathbb{R}^n$, $n\geqslant1$. We investigate the
self-adjointness and the related spectral properties of $H_{a,\tau}$, such as
the phenomenon of confinement and the Sobolev regularity of the domain in
different situations.
  Our set of techniques, which is based on fundamental solutions and layer
potentials, allows us to tackle the above problems under mild geometric measure
theoretic assumptions on $\Omega$.


  Wide dynamic range (WDR) image tone mapping is in high demand in many
applications like film production, security monitoring, and photography. It is
especially crucial for mobile devices because most of the images taken today
are from mobile phones, hence such technology is highly demanded in the
consumer market of mobile devices and is essential for a good customer
experience. However, high-quality and high-performance WDR image tone mapping
implementations are rarely found in the mobile-end. In this paper, we introduce
a high performance, mobile-end WDR image tone mapping implementation. It
leverages the tone mapping results of multiple receptive fields and calculates
a suitable value for each pixel. The utilization of integral image and integral
histogram significantly reduce the required computation. Moreover, GPU parallel
computation is used to increase the processing speed. The experimental results
indicate that our implementation can process a high-resolution WDR image within
a second on mobile devices and produce appealing image quality.


  A wide range of problems in computational science and engineering require
estimation of sparse eigenvectors for high dimensional systems. Here, we
propose two variants of the Truncated Orthogonal Iteration to compute multiple
leading eigenvectors with sparsity constraints simultaneously. We establish
numerical convergence results for the proposed algorithms using a perturbation
framework, and extend our analysis to other existing alternatives for sparse
eigenvector estimation. We then apply our algorithms to solve the sparse
principle component analysis problem for a wide range of test datasets, from
simple simulations to real-world datasets including MNIST, sea surface
temperature and 20 newsgroups. In all these cases, we show that the new methods
get state of the art results quickly and with minimal parameter tuning.


  For Abelian p-groups, Goldsmith, Salce, et al., introduced the notion of
minimal full inertia. In parallel to this, we define the concept of minimal
characteristic inertia and explore those p-primary Abelian groups having
minimal characteristic inertia. We establish the surprising result that, for
each Abelian p-group A, the square A \oplus A has the minimal characteristic
inertia if, and only if, it has the minimal full inertia. We also obtain some
other relationships between these two properties. Specifically, we exhibit
groups which do not have neither of the properties, as well as we show via a
concrete complicated construction from ring/module theory that, for any prime
p, there is a p-group possessing the minimal characteristic inertia which does
not possess the minimal full inertia.


  Room temperature angle-dispersive x-ray diffraction measurements on
zircon-type EuVO4, LuVO4, and ScVO4 were performed up to 27 GPa. In the three
compounds we found evidence of a pressure-induced structural phase
transformation from zircon to a scheelite-type structure. The onset of the
transition is near 8 GPa, but the transition is sluggish and the low- and
high-pressure phases coexist in a pressure range of about 10 GPa. In EuVO4 and
LuVO4 a second transition to a M-fergusonite-type phase was found near 21 GPa.
The equations of state for the zircon and scheelite phases are also determined.
Among the three studied compounds, we found that ScVO4 is less compressible
than EuVO4 and LuVO4, being the most incompressible orthovanadate studied to
date. The sequence of structural transitions and compressibilities are
discussed in comparison with other zircon-type oxides.


  The current standard approach to scaling transformer language models trains
each model size from a different random initialization. As an alternative, we
consider a staged training setup that begins with a small model and
incrementally increases the amount of compute used for training by applying a
"growth operator" to increase the model depth and width. By initializing each
stage with the output of the previous one, the training process effectively
re-uses the compute from prior stages and becomes more efficient. Our growth
operators each take as input the entire training state (including model
parameters, optimizer state, learning rate schedule, etc.) and output a new
training state from which training continues. We identify two important
properties of these growth operators, namely that they preserve both the loss
and the "training dynamics" after applying the operator. While the
loss-preserving property has been discussed previously, to the best of our
knowledge this work is the first to identify the importance of preserving the
training dynamics (the rate of decrease of the loss during training). To find
the optimal schedule for stages, we use the scaling laws from (Kaplan et al.,
2020) to find a precise schedule that gives the most compute saving by starting
a new stage when training efficiency starts decreasing. We empirically validate
our growth operators and staged training for autoregressive language models,
showing up to 22% compute savings compared to a strong baseline trained from
scratch. Our code is available at https://github.com/allenai/staged-training.


  We prove a bifurcation and multiplicity result that is independent of the
dimension N for a critical p-Laplacian problem that is the analog of the
Brezis-Nirenberg problem for the quasilinear case. This extends a result in the
literature for the semilinear case.


  The physics goals of high luminosity particle accelerators, from LHC to
HL-LHC and to the next generation of lepton colliders, have set quite stringent
constraints on the future needs at the Instrumentation Frontier. Many
technologies are reaching their sensitivity limit and new approaches need to be
developed to overcome the currently irreducible technological challenges. The
timescales spanned by future projects in particle physics, ranging from few
years to many decades, constitute a challenge in itself, in addition to the
complexity and diversity of the required accelerator and detector R&D. This
paper summarizes advances and recent trends in the instrumentation techniques
for particle physics experiments, largely based on the presentations given at
the International Conference "Instrumentation for Colliding Beam Physics"
(INSTR-20), held at BINP Novosibirsk, Russia, from 24 to 28 February, 2020.


  Singing Voice Separation (SVS) tries to separate singing voice from a given
mixed musical signal. Recently, many U-Net-based models have been proposed for
the SVS task, but there were no existing works that evaluate and compare
various types of intermediate blocks that can be used in the U-Net
architecture. In this paper, we introduce a variety of intermediate spectrogram
transformation blocks. We implement U-nets based on these blocks and train them
on complex-valued spectrograms to consider both magnitude and phase. These
networks are then compared on the SDR metric. When using a particular block
composed of convolutional and fully-connected layers, it achieves
state-of-the-art SDR on the MUSDB singing voice separation task by a large
margin of 0.9 dB. Our code and models are available online.


  Dynamics and direct $C\P$ violation in three-body charmless decays of charged
$B$ mesons to a proton, an antiproton and a light meson (pion or kaon) are
studied using data, corresponding to an integrated luminosity of 1.0$
{\,fb}^{-1}$, collected by the ${LHCb}$ experiment in $pp$ collisions at a
center-of-mass energy of 7 TeV. Production spectra are determined as a function
of Dalitz-plot and helicity variables. The forward-backward asymmetry of the
light meson in the $p\bar p$ rest frame is measured. No significant $C\P$
asymmetry in $B^+ \to p \bar p K^+$ decay is found in any region of the Dalitz
plane. We present the first observation of the decay $B^+ \to \kern
0.1em\bar{\kern -0.1em\Lambda}(1520)(\to K^+\bar p)p$ near the $K^+\bar p$
threshold and measure $\mathcal{B}(B^+ \to \kern 0.1em\bar{\kern
-0.1em\Lambda}(1520)p)=(3.9^{+1.0}_{-0.9} (\mathrm{stat})\pm0.1
(\mathrm{syst})\pm0.3 (\mathrm{BF}))\times 10^{-7}$, where BF denotes the
uncertainty on secondary branching fractions.


  I give an overview of the basic concepts behind quantum error correction and
quantum fault tolerance. This includes the quantum error correction conditions,
stabilizer codes, CSS codes, transversal gates, fault-tolerant error
correction, and the threshold theorem.


  Federated Learning (FL) is an emerging paradigm in machine learning without
exposing clients' raw data. In practical scenarios with numerous clients,
encouraging fair and efficient client participation in federated learning is of
utmost importance, which is also challenging given the heterogeneity in data
distribution and device properties. Existing works have proposed different
client-selection methods that consider fairness; however, they fail to select
clients with high utilities while simultaneously achieving fair accuracy
levels. In this paper, we propose a fair client-selection approach that unlocks
threefold fairness in federated learning. In addition to having a fair
client-selection strategy, we enforce an equitable number of rounds for client
participation and ensure a fair accuracy distribution over the clients. The
experimental results demonstrate that FedFair^3, in comparison to the
state-of-the-art baselines, achieves 18.15% less accuracy variance on the IID
data and 54.78% on the non-IID data, without decreasing the global accuracy.
Furthermore, it shows 24.36% less wall-clock training time on average.


  Using ROSAT, we have made the first deep X-ray observations of NGC 7331,
discovering a nuclear X-ray source coincident with the previously determined
radio and optical nuclear centers. Positions, luminosities, and fluxes of X-ray
sources in the field are compared to previously identified radio and optical
sources. The nucleus of NGC 7331 has been analyzed to discern any new evidence
supporting the presence of a massive black hole (MBH), and comparisons are made
with other Low-Ionization Nuclear Emission-line Region (LINER) galaxies. The
flux ratio of core radio to soft X-ray emission in NGC 7331 is lower than in
other LINERs included in our sample.


  The classical 2D cosmological model of Callan, Giddings, Harvey and
Strominger possesses a global symmetry that is responsible for decoupling of
matter fields. The model is quantized on the basis of the extended phase space
method to allow an exhaustive, algebraic analysis to find potential anomalies.
Under a certain set of reasonable assumptions we show that neither the BRST
symmetry of the theory nor the global symmetry suffers from an anomaly. From
this we conclude that there is nothing to recognize the existence of black hole
and therefore nothing to radiate in their cosmological model.


  An infinite-dimensional version of Calogero-Moser operator of $BC$-type and
the corresponding Jacobi symmetric functions are introduced and studied,
including the analogues of Pieri formula and Okounkov's binomial formula. We
use this to describe all the ideals linearly generated by the Jacobi symmetric
functions and show that the deformed $BC(m,n)$ Calogero-Moser operators,
introduced in our earlier work, appear here in a natural way as the
restrictions of the $BC_{\infty}$ operator to the corresponding
finite-dimensional subvarieties. As a corollary we have the integrability of
these quantum systems and all the main formulas for the related super Jacobi
polynomials.


  We present the light curve data of a remarkable blazer 3C 454.3 (z=0.859) in
optical, X-ray, and gamma-ray bands. Since January 2008, we have been
monitoring this object using the 50 cm MITSuME, a optical telescope, and
detected several flares including extraordinary and simultaneous flares in the
$\gamma$-ray and optical bands in November 2010. Additionally, the Monitor of
All-sky Image (MAXI) has been observing 3C 454.3 continuously since August
2009. Using these data and gamma-ray flux observed with Fermi-LAT, we discuss
features and correlations of flux variations between the energy bands.


  NaBH4 is a very cheap and hydrogen rich material and a potential hydrogen
store. However, high temperature of its thermal decomposition (above
530{\deg}C) renders it inapplicable in practical use. Here, we have studied the
effect of addition of diverse V containing catalysts on thermal hydrogen
desorption. It turns out that mechanochemical doping of NaBH4 with vanadium
metal, its oxides or nanoparticles lowers the temperature of pyrolysis
significantly. Notably, NaBH4 milled for 3 hrs with 25 wt.% of V2O5 or VO2
releases ca. 70 % of stored hydrogen in the temperature range from ca.
370{\deg}C to 450{\deg}C. On the other hand, precursors and solvents used to
prepare rather uniform vanadium nanoparticles (ca. 4nm) suspended in THF or
less uniform and larger ones (ca. 28nm) in ortho difluorobenzene, have adverse
effect on purity of hydrogen evolved.


  Existing adversarial attacks against Object Detectors (ODs) suffer from two
inherent limitations. Firstly, ODs have complicated meta-structure designs,
hence most advanced attacks for ODs concentrate on attacking specific
detector-intrinsic structures, which makes it hard for them to work on other
detectors and motivates us to design a generic attack against ODs. Secondly,
most works against ODs make Adversarial Examples (AEs) by generalizing
image-level attacks from classification to detection, which brings redundant
computations and perturbations in semantically meaningless areas (e.g.,
backgrounds) and leads to an emergency for seeking controllable attacks for
ODs. To this end, we propose a generic white-box attack, LGP (local
perturbations with adaptively global attacks), to blind mainstream object
detectors with controllable perturbations. For a detector-agnostic attack, LGP
tracks high-quality proposals and optimizes three heterogeneous losses
simultaneously. In this way, we can fool the crucial components of ODs with a
part of their outputs without the limitations of specific structures. Regarding
controllability, we establish an object-wise constraint that exploits
foreground-background separation adaptively to induce the attachment of
perturbations to foregrounds. Experimentally, the proposed LGP successfully
attacked sixteen state-of-the-art object detectors on MS-COCO and DOTA
datasets, with promising imperceptibility and transferability obtained. Codes
are publicly released in https://github.com/liguopeng0923/LGP.git


  We present the first cluster catalog extracted from combined space-based
(Planck) and ground-based (South Pole Telescope; SPT-SZ) millimeter data. We
developed and applied a matched multi-filter (MMF) capable of dealing with the
different transfer functions and resolutions of the two datasets. We verified
that it produces results consistent with publications from Planck and SPT
collaborations when applied on the datasets individually. We also verified that
Planck and SPT-SZ cluster fluxes are consistent with each other. When applied
blindly to the combined dataset, the MMF generated a catalog of 419 detections
($S/N>5$), of which 323 are already part of the SPT-SZ or PSZ2 catalogs; 54 are
new SZ detections, which have been identified in other catalogs or surveys; and
42 are new unidentified candidates. The MMF takes advantage of the
complementarity of the two datasets, Planck being particularly useful for
detecting clusters at a low redshift ($z<0.3$), while SPT is efficient at
finding higher redshift ($z>0.3$) sources. This work represents a proof of
concept that blind cluster extraction can be performed on combined,
inhomogeneous millimeter datasets acquired from space and ground. This result
is of prime importance for planned ground-based cosmic microwave background
(CMB) experiments (e.g., Simons Observatory, CMB-S4) and envisaged CMB space
missions (e.g., PICO, Backlight) that will detect hundreds of thousands of
clusters in the low mass regime ($M_{500} \leqslant 10^{14} M_\odot$), for
which the various sources of intra-cluster emission (gas, dust, synchrotron)
will be of the same order of magnitude and hence require broad ground and space
frequency coverage with a comparable spatial resolution for adequate
separation.


  Learning from unordered sets is a fundamental learning setup, recently
attracting increasing attention. Research in this area has focused on the case
where elements of the set are represented by feature vectors, and far less
emphasis has been given to the common case where set elements themselves adhere
to their own symmetries. That case is relevant to numerous applications, from
deblurring image bursts to multi-view 3D shape recognition and reconstruction.
In this paper, we present a principled approach to learning sets of general
symmetric elements. We first characterize the space of linear layers that are
equivariant both to element reordering and to the inherent symmetries of
elements, like translation in the case of images. We further show that networks
that are composed of these layers, called Deep Sets for Symmetric Elements
(DSS) layers, are universal approximators of both invariant and equivariant
functions, and that these networks are strictly more expressive than Siamese
networks. DSS layers are also straightforward to implement. Finally, we show
that they improve over existing set-learning architectures in a series of
experiments with images, graphs, and point-clouds.


  Let $\mathrm{PG}(3,q)$ be the projective space of dimension three over the
finite field with $q$ elements. Consider a twisted cubic in $\mathrm{PG}(3,q)$.
The structure of the point-plane incidence matrix in $\mathrm{PG}(3,q)$ with
respect to the orbits of points and planes under the action of the stabilizer
group of the twisted cubic is described. This information is used to view
generalized doubly-extended Reed-Solomon codes of codimension four as
asymptotically optimal multiple covering codes.