  We implement a new algorithm for listing all maximal cliques in sparse graphs
due to Eppstein, L\"offler, and Strash (ISAAC 2010) and analyze its performance
on a large corpus of real-world graphs. Our analysis shows that this algorithm
is the first to offer a practical solution to listing all maximal cliques in
large sparse graphs. All other theoretically-fast algorithms for sparse graphs
have been shown to be significantly slower than the algorithm of Tomita et al.
(Theoretical Computer Science, 2006) in practice. However, the algorithm of
Tomita et al. uses an adjacency matrix, which requires too much space for large
sparse graphs. Our new algorithm opens the door for fast analysis of large
sparse graphs whose adjacency matrix will not fit into working memory.


  This paper is concerned with the investigation of the regional
controllability of the time fractional diffusion equations. First, some
preliminaries and definitions of regional controllability of the system under
consideration are introduced, which promote the existence contributions on
controllability analysis. Then we analyze the regional controllability with
minimum energy of the time fractional diffusion equations on two cases: $B\in
\mathbf{L}\left(\mathbf{R}^m, L^2(\Omega) \right)$ and $B\notin
\mathbf{L}\left(\mathbf{R}^m, L^2(\Omega) \right)$. In the end, two
applications are given to illustrate our obtained results.


  Intent-detection and slot-filling are the two main tasks in natural language
understanding. In this study, we propose CTRAN, a novel encoder-decoder
CNN-Transformer-based architecture for intent-detection and slot-filling. In
the encoder, we use BERT, followed by several convolutional layers, and
rearrange the output using window feature sequence. We use stacked Transformer
encoders after the window feature sequence. For the intent-detection decoder,
we utilize self-attention followed by a linear layer. In the slot-filling
decoder, we introduce the aligned Transformer decoder, which utilizes a zero
diagonal mask, aligning output tags with input tokens. We apply our network on
ATIS and SNIPS, and surpass the current state-of-the-art in slot-filling on
both datasets. Furthermore, we incorporate the language model as word
embeddings, and show that this strategy yields a better result when compared to
the language model as an encoder.


  Spatial information is often expressed using qualitative terms such as
natural language expressions instead of coordinates; reasoning over such terms
has several practical applications, such as bus routes planning. Representing
and reasoning on trajectories is a specific case of qualitative spatial
reasoning that focuses on moving objects and their paths. In this work, we
propose two versions of a trajectory calculus based on the allowed properties
over trajectories, where trajectories are defined as a sequence of
non-overlapping regions of a partitioned map. More specifically, if a given
trajectory is allowed to start and finish at the same region, 6 base relations
are defined (TC-6). If a given trajectory should have different start and
finish regions but cycles are allowed within, 10 base relations are defined
(TC-10). Both versions of the calculus are implemented as ASP programs; we
propose several different encodings, including a generalised program capable of
encoding any qualitative calculus in ASP. All proposed encodings are
experimentally evaluated using a real-world dataset. Experiment results show
that the best performing implementation can scale up to an input of 250
trajectories for TC-6 and 150 trajectories for TC-10 for the problem of
discovering a consistent configuration, a significant improvement compared to
previous ASP implementations for similar qualitative spatial and temporal
calculi. This manuscript is under consideration for acceptance in TPLP.


  A secondary function of the mammals' respiratory system is during inspiration
to heat the air to body temperature and to saturate it with water before it
reaches the alveoli. Relying on a mathematical model, we comprehensively
analyze this function, considering all the terrestrial mammals (spanning six
orders of magnitude of the body mass, $M$) and focusing on the sole
contribution of the lungs to this air conditioning. The results highlight
significant differences between the small and the large mammals, as well as
between rest and effort, regarding the spatial distribution of heat and water
exchanges in the lungs, and in terms of regime of mass transfer taking place in
the lumen of the airways. Interestingly, the results show that the mammalian
lungs appear to be designed just right to fully condition the air at maximal
effort: all generations of the bronchial region of the lungs are mobilized for
this purpose. For mammals with a mass above a certain threshold ($\simeq 5$ kg
at rest and $\simeq 50$ g at maximal effort), it appears that the maximal value
of this evaporation rate scales as $M^{-1/8}$ at rest and $M^{-1/16}$ at
maximal effort and that around 40\% (at rest) or 50\% (at maximal effort) of
the water/heat extracted from the lungs during inspiration is returned to the
bronchial mucosa during expiration, independently of the mass, due to a subtle
coupling between different phenomena. This last result implies that, above
these thresholds, the amounts of water and heat extracted from the lungs by the
ventilation scale with the mass such as the ventilation rate (i.e. as $M^{3/4}$
at rest and $M^{7/8}$ at maximal effort). Finally, it is worth mentioning that
these amounts appear to remain limited, but not negligible when compared to
relevant global quantities, even at maximal effort (4-6\%).


  It is usual to consider that standards generate mixed feelings among
scientists. They are often seen as not really reflecting the state of the art
in a given domain and a hindrance to scientific creativity. Still, scientists
should theoretically be at the best place to bring their expertise into
standard developments, being even more neutral on issues that may typically be
related to competing industrial interests. Even if it could be thought of as
even more complex to think about developping standards in the humanities, we
will show how this can be made feasible through the experience gained both
within the Text Encoding Initiative consortium and the International
Organisation for Standardisation. By taking the specific case of lexical
resources, we will try to show how this brings about new ideas for designing
future research infrastructures in the human and social sciences.


  The concept of Fermi liquid lays a solid cornerstone to the understanding of
electronic correlations in quantum matter. This ordered many-body state
rigorously organizes electrons at zero temperature in progressively higher
momentum states, up to the Fermi surface. As such, it displays rigidity against
perturbations. Such rigidity generates Fermi-surface resonances which manifest
as longitudinal and transverse collective modes. Although these Fermi-liquid
collective modes have been analyzed and observed in electrically neutral liquid
helium, they remain unexplored in charged solid-state systems up to date. In
this paper I analyze the transverse shear response of charged three-dimensional
Fermi liquids as a function of temperature, excitation frequency and momentum,
for interactions expressed in terms of the first symmetric Landau parameter. I
consider the effect of momentum-conserving quasiparticle collisions and
momentum-relaxing scattering in relaxation-time approximation on the coupling
between photons and Fermi-surface collective modes, thus deriving the
Fermi-liquid optical conductivity and dielectric function. In the
high-frequency, long-wavelength excitation regime the electrodynamic response
entails two coherent and frequency-degenerate polaritons, and its spatial
nonlocality is encoded by a frequency- and interaction-dependent generalized
shear modulus; in the opposite high-momentum low-frequency regime anomalous
skin effect takes place. I identify observable signatures of propagating shear
collective modes in optical spectroscopy experiments, with applications to the
surface impedance and the optical transmission of thin films.


  We recently found that marine bacteria Vibrio alginolyticus execute a cyclic
3-step (run- reverse-flick) motility pattern that is distinctively different
from the 2-step (run-tumble) pattern of Escherichia coli. How this novel
swimming pattern is regulated by cells of V. alginolyticus is not currently
known, but its significance for bacterial chemotaxis is self- evident and will
be delineated herein. Using an approach introduced by de Gennes, we calculated
the migration speed of a cell executing the 3-step pattern in a linear chemical
gradient, and found that a biphasic chemotactic response arises naturally. The
implication of such a response for the cells to adapt to ocean environments and
its possible connection to E. coli 's response are also discussed.


  Bayesian entity resolution merges together multiple, noisy databases and
returns the minimal collection of unique individuals represented, together with
their true, latent record values. Bayesian methods allow flexible generative
models that share power across databases as well as principled quantification
of uncertainty for queries of the final, resolved database. However, existing
Bayesian methods for entity resolution use Markov monte Carlo method (MCMC)
approximations and are too slow to run on modern databases containing millions
or billions of records. Instead, we propose applying variational approximations
to allow scalable Bayesian inference in these models. We derive a
coordinate-ascent approximation for mean-field variational Bayes, qualitatively
compare our algorithm to existing methods, note unique challenges for inference
that arise from the expected distribution of cluster sizes in entity
resolution, and discuss directions for future work in this domain.


  Heteroepitaxy of functional thin films on single-crystal substrates is one of
the most general themes in electronic materials research. Here, we propose an
algorithm based on image processing for the rapid simulation of heteroepitaxial
relationships. The superposition and rotation of various lattice plane images
of the film and substrate, which were automatically generated from the crystal
structure, rapidly verified all domain matching patterns. Furthermore, the
comprehensive validation allowed us to discuss domain matching from multiple
perspectives, such as mismatch, matching period, and density of matching
lattice points. Therefore, the proposed algorithm will contribute to materials
informatics, streamlining a wide range of materials research for functional
thin films.


  In this paper, we propose a novel unsupervised text-to-speech (UTTS)
framework which does not require text-audio pairs for the TTS acoustic modeling
(AM). UTTS is a multi-speaker speech synthesizer that supports zero-shot voice
cloning, it is developed from a perspective of disentangled speech
representation learning. The framework offers a flexible choice of a speaker's
duration model, timbre feature (identity) and content for TTS inference. We
leverage recent advancements in self-supervised speech representation learning
as well as speech synthesis front-end techniques for system development.
Specifically, we employ our recently formulated Conditional Disentangled
Sequential Variational Auto-encoder (C-DSVAE) as the backbone UTTS AM, which
offers well-structured content representations given unsupervised alignment
(UA) as condition during training. For UTTS inference, we utilize a lexicon to
map input text to the phoneme sequence, which is expanded to the frame-level
forced alignment (FA) with a speaker-dependent duration model. Then, we develop
an alignment mapping module that converts FA to UA. Finally, the C-DSVAE,
serving as the self-supervised TTS AM, takes the predicted UA and a target
speaker embedding to generate the mel spectrogram, which is ultimately
converted to waveform with a neural vocoder. We show how our method enables
speech synthesis without using a paired TTS corpus. Experiments demonstrate
that UTTS can synthesize speech of high naturalness and intelligibility
measured by human and objective evaluations. Audio samples are available at our
demo page https://neurtts.github.io/utts_demo.


  We study the effect of isospin degree of freedom on the balance energy
(E$_{bal}$) as well as its mass dependence throughout the mass range 48-270 for
two sets of isobaric systems with N/Z = 1 and 1.4 at different colliding
geometries ranging from central to peripheral ones. Our findings reveal the
dominance of Coulomb repulsion in isospin effects on E$_{bal}$ as well as its
mass dependence throughout the range of the colliding geometry. Our results
also indicate that the effect of symmetry energy and nucleon-nucleon cross
section on E$_{bal}$ is uniform throughout the mass range and throughout the
colliding geometry. We also present the counter balancing of nucleon-nucleon
collisions and mean field by reducing the Coulomb and the counter balancing of
Coulomb and mean filed by removing the nucleon-nucleon collisions.


  Vacillating tableaux are sequences of integer partitions that satisfy
specific conditions. The concept of vacillating tableaux stems from the
representation theory of the partition algebra and the combinatorial theory of
crossings and nestings of matchings and set partitions. In this paper, we
further investigate the enumeration of vacillating tableaux and derive multiple
combinatorial identities and integer sequences relating to the number of
vacillating tableaux, simplified vacillating tableaux, and limiting vacillating
tableaux.


  Overfitting in deep learning has been the focus of a number of recent works,
yet its exact impact on the behavior of neural networks is not well understood.
This study analyzes overfitting by examining how the distribution of logits
alters in relation to how much the model overfits. Specifically, we find that
when training with few data samples, the distribution of logit activations when
processing unseen test samples of an under-represented class tends to shift
towards and even across the decision boundary, while the over-represented class
seems unaffected. In image segmentation, foreground samples are often heavily
under-represented. We observe that sensitivity of the model drops as a result
of overfitting, while precision remains mostly stable. Based on our analysis,
we derive asymmetric modifications of existing loss functions and regularizers
including a large margin loss, focal loss, adversarial training and mixup,
which specifically aim at reducing the shift observed when embedding unseen
samples of the under-represented class. We study the case of binary
segmentation of brain tumor core and show that our proposed simple
modifications lead to significantly improved segmentation performance over the
symmetric variants.


  In moir\'e materials with flat electronic bands and suitable quantum
geometry, strong correlations can give rise to novel topological states of
matter. The nontrivial band topology of twisted molybdenum ditelluride
(tMoTe$_2$) -- responsible for its fractional quantum anomalous Hall (FQAH)
states -- is predicted to arise from a layer-pseudospin skyrmion lattice.
Tracing the layer polarization of wavefunctions within the moir\'e unit cell
can thus offer crucial insights into the band topology. Here, we use scanning
tunneling microscopy and spectroscopy (STM/S) to probe the layer-pseudospin
skyrmion textures of tMoTe$_2$. We do this by simultaneously visualizing the
moir\'e lattice structure and the spatial localization of its electronic
states. We find that the wavefunctions associated with the topological flat
bands exhibit a spatially-dependent layer polarization within the moir\'e unit
cell. This is in excellent agreement with our theoretical modeling, thereby
revealing a direct microscopic connection between the structural properties of
tMoTe$_2$ and its band topology. Our work enables new pathways for engineering
FQAH states with strain, as well as future STM studies of the intertwined
correlated and topological states arising in gate-tunable devices.


  The detection and characterization of gravitational wave signals from compact
binary coalescence events relies on accurate waveform templates in the
frequency domain. The stationary phase approximation (SPA) can be used to
compute closed-form frequency-domain waveforms for non-precessing,
quasi-circular binary inspirals. However, until now, no fast frequency-domain
waveforms have existed for generic, spin-precessing quasi-circular compact
binary inspirals. Templates for these systems have had to be computed via a
discrete Fourier transform of finely sampled time-domain waveforms, which is
far more computationally expensive than those constructed directly in the
frequency-domain, especially for those systems that are dominated by the
inspiral part. There are two obstacles to deriving frequency-domain waveforms
for precessing systems: (i) the spin-precession equations do not admit
closed-form solutions for generic systems; (ii) the SPA fails catastrophically.
Presently there is no general solution to the first problem, so we must resort
to numerical integration of the spin precession equations. This is not a
significant obstacle, as numerical integration on the slow precession timescale
adds very little to the computational cost of generating the waveforms. Our
main result is to solve the second problem, by providing an alternative to the
SPA that we call the method of Shifted Uniform Asymptotics, or SUA, that cures
the divergences in the SPA. The construction of frequency-domain templates
using the SUA can be orders of magnitude more efficient than the time-domain
ones obtained through a discrete Fourier transform. Moreover, this method is
very faithful to the discrete Fourier transform, with mismatches on the order
of $10^{-5}$.


  In a recent paper (Phys. Rev. Lett. 123, 210602), Kozin and Kyriienko claim
to realize "genuine" ground state time crystals by studying models with
long-ranged and infinite-body interactions. Here we point out that their models
are doubly problematic: they are unrealizable ${\it and}$ they violate well
established principles for defining phases of matter. Indeed with infinite body
operators allowed, almost all quantum systems are time crystals. In addition,
one of their models is highly unstable and another amounts to isolating, via
fine tuning, a single degree of freedom in a many body system--allowing for
this elevates the pendulum of Galileo and Huygens to a genuine time crystal.


  Strongly interacting non-equilibrium systems are of great fundamental
interest, yet their inherent complexity make then notoriously hard to analyze.
We demonstrate that the dynamics of the Bose-Hubbard model, which by itself
evades solvability, can be solved exactly at any interaction strength in the
presence of loss tuned to a rate matching the hopping amplitude. Remarkably,
the full solvability of the corresponding Liouvillian, and the integrability of
the pertinent effective non-Hermitian Hamiltonian, survives the addition of
disorder and generic boundary conditions. By analyzing the Bethe ansatz
solutions we find that even weak interactions change the qualitative features
of the system, leading to an intricate dynamical phase diagram featuring
non-Hermitian Mott-skin effects, disorder induced localization, highly
degenerate exceptional points, and a Bose glass-like phase of fragmented
condensates. We discuss realistic implementations of this model with cold
atoms.


  We present ultraviolet (UV) integrated colors of 44 Galactic globular
clusters (GGCs) observed with the Galaxy Evolution Explorer (GALEX) in both FUV
and NUV bands. We find for the first time that GCs associated with the
Sagittarius dwarf galaxy have (FUV-V) colors systematically redder than GGCs
with the same metallicity. M31 GCs show almost the same UV colors as GGCs,
while M87 are systematically bluer. We speculate about the presence of an
interesting trend, suggesting that the UV color of GCs may be correlated with
the mass of the host galaxy, in the sense that more massive galaxies possess
bluer clusters.


  The coupling between band structure and magnetism can lead to intricate Fermi
surface modifications. Here we report on the comprehensive study of the
Shubnikov-de Haas (SdH) effect in two rare-earth-based magnetic Weyl
semimetals, NdAlSi and CeAlSi$_{0.8}$Ge$_{0.2}$. The results show that the
temperature evolution of topologically nontrivial Fermi surfaces strongly
depends on magnetic configurations. In NdAlSi, the SdH frequencies vary with
temperature in both the paramagnetic state and the magnetically ordered state
with a chiral spin texture, but become temperature independent in the
high-field fully polarized state. In CeAlSi$_{0.8}$Ge$_{0.2}$, SdH frequencies
are temperature-dependent only in the ferromagnetic state with magnetic fields
applied along the $c$ axis. First-principles calculations suggest that the
notable temperature and magnetic-configuration dependence of Fermi surface
morphology can be attributed to strong exchange coupling between the conduction
electrons and local magnetic moments.


  Biomedical interaction networks have incredible potential to be useful in the
prediction of biologically meaningful interactions, identification of network
biomarkers of disease, and the discovery of putative drug targets. Recently,
graph neural networks have been proposed to effectively learn representations
for biomedical entities and achieved state-of-the-art results in biomedical
interaction prediction. These methods only consider information from immediate
neighbors but cannot learn a general mixing of features from neighbors at
various distances. In this paper, we present a higher-order graph convolutional
network (HOGCN) to aggregate information from the higher-order neighborhood for
biomedical interaction prediction. Specifically, HOGCN collects feature
representations of neighbors at various distances and learns their linear
mixing to obtain informative representations of biomedical entities.
Experiments on four interaction networks, including protein-protein, drug-drug,
drug-target, and gene-disease interactions, show that HOGCN achieves more
accurate and calibrated predictions. HOGCN performs well on noisy, sparse
interaction networks when feature representations of neighbors at various
distances are considered. Moreover, a set of novel interaction predictions are
validated by literature-based case studies.


  We revisit LHC searches for heavy invisible particles by exploiting QCD
initial state radiation. We recast a dijet signal region in a general multijet
plus MET search by ATLAS. We find that non-trivial mass limit can be obtained
for various models of the electroweakino sector with the present data in
hadronic channels. The winos are bound to be heavier than $m_{\tilde W} \gtrsim
{160}$ GeV and higgsinos $m_{\tilde h} \gtrsim {100}$ GeV, depending on the
chargino-neutralino mass splitting. The expected exclusion limits at the LHC
Run 3 with $\mathcal{L} = 300$ fb$^{-1}$ increase to $m_{\tilde W} \gtrsim
{200}$ GeV and $m_{\tilde h} \gtrsim {130}$ GeV for winos and higgsino,
respectively. This is the first LHC limit for promptly decaying nearly
mass-degenerate winos.


  A few electron double electrostatic lateral quantum dot can be transformed
into a few electron triple quantum dot by applying a different combination of
gate voltages. Quadruple points have been achieved at which all three dots are
simultaneously on resonance. At these special points in the stability diagram
four occupation configurations are possible. Both charge detection and
transport experiments have been performed on this device. In this short paper
we present data and confirm that transport is coherent by observing a Pi phase
shift in magneto-conductance oscillations as one passes through the quadruple
point.


  We develop a system for modeling hand-object interactions in 3D from RGB
images that show a hand which is holding a novel object from a known category.
We design a Convolutional Neural Network (CNN) for Hand-held Object Pose and
Shape estimation called HOPS-Net and utilize prior work to estimate the hand
pose and configuration. We leverage the insight that information about the hand
facilitates object pose and shape estimation by incorporating the hand into
both training and inference of the object pose and shape as well as the
refinement of the estimated pose. The network is trained on a large synthetic
dataset of objects in interaction with a human hand. To bridge the gap between
real and synthetic images, we employ an image-to-image translation model
(Augmented CycleGAN) that generates realistically textured objects given a
synthetic rendering. This provides a scalable way of generating annotated data
for training HOPS-Net. Our quantitative experiments show that even noisy hand
parameters significantly help object pose and shape estimation. The qualitative
experiments show results of pose and shape estimation of objects held by a hand
"in the wild".


  Dyon loops give a contribution to the matrix element for light-by-light
scattering that violates parity and time-reversal symmetry. This effect induces
an electric dipole moment for the electron, of order $M^{-2}$, where $M$ is the
dyon mass. The current limit on the electric dipole moment of the electron
yields the lower mass bound $M>{\cal O}(1)~\mbox{TeV}$.


  Belavin's $(\mathbb{Z}/n\mathbb{Z})$-symmetric model is considered on the
basis of bosonization of vertex operators in the $A^{(1)}_{n-1}$ model and
vertex-face transformation. The corner transfer matrix (CTM) Hamiltonian of
$(\mathbb{Z}/n\mathbb{Z})$-symmetric model and tail operators are expressed in
terms of bosonized vertex operators in the $A^{(1)}_{n-1}$ model. Correlation
functions of $(\mathbb{Z}/n\mathbb{Z})$-symmetric model can be obtained by
using these objects, in principle. In particular, we calculate spontaneous
polarization, which reproduces the result by myselves in 1993.


  With the growing use of location-based services, location privacy attracts
increasing attention from users, industry, and the research community. While
considerable effort has been devoted to inventing techniques that prevent
service providers from knowing a user's exact location, relatively little
attention has been paid to enabling so-called peer-wise privacy--the protection
of a user's location from unauthorized peer users. This paper identifies an
important efficiency problem in existing peer-privacy approaches that simply
apply a filtering step to identify users that are located in a query range, but
that do not want to disclose their location to the querying peer. To solve this
problem, we propose a novel, privacy-policy enabled index called the PEB-tree
that seamlessly integrates location proximity and policy compatibility. We
propose efficient algorithms that use the PEB-tree for processing privacy-aware
range and kNN queries. Extensive experiments suggest that the PEB-tree enables
efficient query processing.


  Many problems in Science and Engineering give rise to linear integral
equations of the first kind with a smooth kernel. Discretization of the
integral operator yields a matrix, whose singular values cluster at the origin.
We describe the approximation of such matrices by adaptive cross approximation,
which avoids forming the entire matrix. The choice of the number of steps of
adaptive cross approximation is discussed. The discretized right-hand side
represents data that commonly are contaminated by measurement error. Solution
of the linear system of equations so obtained is not meaningful because the
matrix determined by adaptive cross approximation is rank-deficient. We remedy
this difficulty by using Tikhonov regularization and discuss how a fairly
general regularization matrix can be used. Computed examples illustrate that
the use of a regularization matrix different from the identity can improve the
quality of the computed approximate solutions significantly.


  We investigate the flow of two immiscible, viscous fluids in a rotating
Hele-Shaw cell, when one of the fluids is a ferrofluid and an external magnetic
field is applied. The interplay between centrifugal and magnetic forces in
determining the instability of the fluid-fluid interface is analyzed. The
linear stability analysis of the problem shows that a non-uniform, azimuthal
magnetic field, applied tangential to the cell, tends to stabilize the
interface. We verify that maximum growth rate selection of initial patterns is
influenced by the applied field, which tends to decrease the number of
interface ripples. We contrast these results with the situation in which a
uniform magnetic field is applied normally to the plane defined by the rotating
Hele-Shaw cell.


  We review the properties of quarkonia under strong magnetic fields. The main
phenomena are (i) mixing between different spin eigenstates, (ii) quark Landau
levels and deformation of wave function, (iii) modification of $\bar{Q}Q$
potential, and (iv) the motional Stark effect. For theoretical approaches, we
review (i) constituent quark models, (ii) effective Lagrangians, (iii) QCD sum
rules, and (iv) holographic approaches.


  At the core of portrait photography is the search for ideal lighting and
viewpoint. The process often requires advanced knowledge in photography and an
elaborate studio setup. In this work, we propose Holo-Relighting, a volumetric
relighting method that is capable of synthesizing novel viewpoints, and novel
lighting from a single image. Holo-Relighting leverages the pretrained 3D GAN
(EG3D) to reconstruct geometry and appearance from an input portrait as a set
of 3D-aware features. We design a relighting module conditioned on a given
lighting to process these features, and predict a relit 3D representation in
the form of a tri-plane, which can render to an arbitrary viewpoint through
volume rendering. Besides viewpoint and lighting control, Holo-Relighting also
takes the head pose as a condition to enable head-pose-dependent lighting
effects. With these novel designs, Holo-Relighting can generate complex
non-Lambertian lighting effects (e.g., specular highlights and cast shadows)
without using any explicit physical lighting priors. We train Holo-Relighting
with data captured with a light stage, and propose two data-rendering
techniques to improve the data quality for training the volumetric relighting
system. Through quantitative and qualitative experiments, we demonstrate
Holo-Relighting can achieve state-of-the-arts relighting quality with better
photorealism, 3D consistency and controllability.


  We develop a discrete differential geometry for surfaces of non-constant
negative curvature, which can be used to model various phenomena from the
growth of flower petals to marine invertebrate swimming. Specifically, we
derive and numerically integrate a version of the classical Lelieuvre formulas
that apply to immersions of $C^{1,1}$ hyperbolic surfaces of non-constant
curvature. In contrast to the constant curvature case, these formulas do not
provide an explicit method for constructing an immersion but rather describe an
immersion via an implicit set of equations. We propose an iterative method for
resolving these equations. Because we are interested in scenarios where the
curvature is a function of the intrinsic material coordinates, in particular,
on the geodesic distance from an origin, we suggest a fast marching method for
computing geodesic distance on manifolds. We apply our methods to generate
surfaces of non-constant curvature and demonstrate how one can introduce branch
points to account for the sort of multi-generational buckling and subwrinkling
observed in many applications.


  The difference between object-language and metalanguage is crucial for
logical analysis, but has yet not been examined for the field of computer
science. In this paper the difference is examined with regard to inferential
relations. It is argued that inferential relations in a metalanguage (like a
calculus for propositional logic) cannot represent conceptual relations of
natural language. Inferential relations govern our concept use and
understanding. Several approaches in the field of Natural Language
Understanding (NLU) and Natural Language Inference (NLI) take this insight in
account, but do not consider, how an inference can be assessed as a good
inference. I present a logical analysis that can assesss the normative
dimension of inferences, which is a crucial part of logical understanding and
goes beyond formal understanding of metalanguages.


  We study a baryogenesis mechanism operating in the context of hyperextended
inflation and making use of a coupling between the scalar field and a standard
model global current, such as B or B-L. The method is efficient at temperatures
at which these currents are not conserved due to some higher dimensional
operator. The particle physics and cosmological phenomenology are discussed. We
consider constraints stemming from nucleosynthesis and solar system
experiments.


  We present the MaNGA Dwarf galaxy, MaNDala, Value-Added-Catalog, VAC, from
the final release of the Sloan Digital Sky Survey-IV program. MaNDala consists
of 136 randomly selected bright dwarf galaxies with $M_{*}<10^{9.1}\odot$ and
$M_{g}>-18.5$ making it the largest Integral Field Spectroscopy homogeneous
sample of dwarf galaxies. We release a photometric analysis of the $g,r$ and
$z$ broadband imaging based on the DESI Legacy Imaging Surveys as well as the
spectroscopic analysis based on the Pipe3D SDSS-IV VAC. Our release includes
the surface brightness (SB), geometric parameters and color profiles, S\'ersic
fits as well as stellar population properties (such as, stellar ages,
metallicities, star formation histories), and emission lines fluxes within the
FOV and the effective radii of the galaxies. We find that the majority of the
MaNDala galaxies are star forming late-type galaxies with
$\langle{}n_{\text{Sersic,r}}\rangle\sim1.6$ that are centrals
(central/satellite dichotomy). MaNDala covers a large range of SB values (we
find 11 candidates of ultra diffuse galaxies and 3 compact ones), filling the
gap between classical dwarfs and low-mass galaxies in the Kormendy Diagram and
in the size-mass/luminosity relation, whichseems to flatten at
$10^8<M_{*}/\odot<10^{9}$ with $\langle{}R_{e,r}\rangle\sim2.7$ kpc. A large
fraction of MaNDala galaxies formed from an early low-metallicity burst of SF
but also of late SF events from more metal-enriched gas: half of the MaNDala
galaxies assembled $50\%$ of their mass at $\langle{}z\rangle>2$, while the
last $20\%$ was at $\langle{}z\rangle<0.3$. Finally, a bending of the
sSFR-$M_{*}$ relation at $M_{*}\sim10^{9}\odot$ for the main sequence galaxies
seems to be supported by MaNDala.


  Accurate automatic organ segmentation is an important yet challenging problem
for medical image analysis. The pancreas is an abdominal organ with very high
anatomical variability. This inhibits traditional segmentation methods from
achieving high accuracies, especially compared to other organs such as the
liver, heart or kidneys. In this paper, we present a holistic learning approach
that integrates semantic mid-level cues of deeply-learned organ interior and
boundary maps via robust spatial aggregation using random forest. Our method
generates boundary preserving pixel-wise class labels for pancreas
segmentation. Quantitative evaluation is performed on CT scans of 82 patients
in 4-fold cross-validation. We achieve a (mean $\pm$ std. dev.) Dice Similarity
Coefficient of 78.01% $\pm$ 8.2% in testing which significantly outperforms the
previous state-of-the-art approach of 71.8% $\pm$ 10.7% under the same
evaluation criterion.


  Given a temporal graph G, a source vertex s, and a departure time at source
vertex t_s, the earliest arrival time problem EAT is to start from s on or
after t_s and reach all the vertices in G as early as possible. Ni et al. have
proposed a parallel algorithm for EAT and obtained a speedup up to 9.5 times on
real-world graphs with respect to the connection-scan serial algorithm by using
multi-core processors.
  We propose a topology-driven parallel algorithm for EAT on public transport
networks and implement using general-purpose programming on the graphics
processing unit GPU. A temporal edge or connection in a temporal graph for a
public transport network is associated with a departure time and a duration
time, and many connections exist from u to v for an edge (u,v). We propose two
pruning techniques connection-type and clustering, and use arithmetic
progression technique appropriately to process many connections of an edge,
without scanning all of them. In the connection-type technique, the connections
of an edge with the same duration are grouped together. In the clustering
technique, we follow 24-hour format and the connections of an edge are
partitioned into 24 clusters so that the departure time of connections in the
i^{th} cluster is at least i-hour and at most i+1-hour. The arithmetic
progression technique helps to store a sequence of departure times of various
connections in a compact way. We propose a hybrid approach to combine the three
techniques connection-type, clustering and arithmetic progression in an
appropriate way. Our techniques achieve an average speedup up to 59.09 times
when compared to the existing connection-scan serial algorithm running on CPU.
Also, the average speedup of our algorithm is 12.48 times against the parallel
edge-scan-dependency graph algorithm running on GPU.


  This paper introduces an investigation of the healthcare monitoring systems
and their provisioning in the IoT platform. The different roles that exist in
healthcare systems are specified and modeled here. This paper also attempts to
introduce and propose a generic framework for the design and development of
context aware healthcare monitoring systems in the IoT platform. In such a
framework, the fundamental components of the healthcare monitoring systems are
identified and modelled as well as the relationship between these components.
The paper also stresses on the crucial role played by the AI field in
addressing resilient context aware healthcare monitoring systems.
Architecturally, this framework is based on a distributed layered architecture
where the different components are deployed over the physical layer, fog
platform and the cloud platform.


  We propose a domain adaptation method, MoDA, which adapts a pretrained
embodied agent to a new, noisy environment without ground-truth supervision.
Map-based memory provides important contextual information for visual
navigation, and exhibits unique spatial structure mainly composed of flat walls
and rectangular obstacles. Our adaptation approach encourages the inherent
regularities on the estimated maps to guide the agent to overcome the prevalent
domain discrepancy in a novel environment. Specifically, we propose an
efficient learning curriculum to handle the visual and dynamics corruptions in
an online manner, self-supervised with pseudo clean maps generated by style
transfer networks. Because the map-based representation provides spatial
knowledge for the agent's policy, our formulation can deploy the pretrained
policy networks from simulators in a new setting. We evaluate MoDA in various
practical scenarios and show that our proposed method quickly enhances the
agent's performance in downstream tasks including localization, mapping,
exploration, and point-goal navigation.


  We discuss gravity-like formulations of massive Abelian and non-Abelian gauge
field theories in four space-time dimensions with particular emphasis on the
issue of gauge invariance. Alternative descriptions in terms of antisymmetric
tensor fields and geometric variables, respectively, are analysed. In both
approaches St\"uckelberg degrees of freedom factor out. We also demonstrate, in
the Abelian case, that the massless limit for the gauge propagator, which does
not exist in the vector potential formulation, is well-defined for the
antisymmetric tensor fields.


  Dynamical phase transition in quantum many body systems is usually studied by
taking it in the ground state and then quenching a parameter to a new value. We
investigate here the dynamics when one performs the time evolution of a generic
state and observe that the rate function related to the Loschmidt echo shows
non-analytic behavior of two types, one related, and the other unrelated, to
the appearance of a quantum phase transition. Specifically, we consider a
quantum Ising chain in an initial configuration which is a generic
superposition of the eigenstates, and follow its dynamics under the transverse
Ising Hamiltonian with constant field. Depending on the the configuration of
the initial state, some singularities appear in the rate function which do not
correspond to the equilibrium phase transition of the Hamiltonian. However
another class of singularity is found having connection with the quantum
critical point. Some features of the singularities of the rate function have
been derived analytically and it is observed that the occupancy of
quasiparticle eigenstates plays the key role in triggering the
non-analyticities.


  Our study presents a new framework that incorporates the Analytic Hierarchy
Process (AHP) and Generative Pre-trained Transformer 4 (GPT-4) large language
model (LLM), bringing novel approaches to cybersecurity Multiple-criteria
Decision Making (MCDA). By utilizing the capabilities of GPT-4 autonomous
agents as virtual experts, we automate the decision-making process, enhancing
both efficiency and reliability. This new approach focuses on leveraging LLMs
for sophisticated decision analysis, highlighting the synergy between
traditional decision-making models and cutting-edge AI technologies. Our
innovative methodology demonstrates significant advancements in using AI-driven
agents for complex decision-making scenarios, highlighting the importance of AI
in strategic cybersecurity applications. The findings reveal the transformative
potential of combining AHP and LLMs, establishing a new paradigm for
intelligent decision support systems in cybersecurity and beyond.


  A recent model for property testing of probability distributions (Chakraborty
et al., ITCS 2013, Canonne et al., SICOMP 2015) enables tremendous savings in
the sample complexity of testing algorithms, by allowing them to condition the
sampling on subsets of the domain. In particular, Canonne, Ron, and Servedio
(SICOMP 2015) showed that, in this setting, testing identity of an unknown
distribution $D$ (whether $D=D^\ast$ for an explicitly known $D^\ast$) can be
done with a constant number of queries, independent of the support size $n$ --
in contrast to the required $\Omega(\sqrt{n})$ in the standard sampling model.
It was unclear whether the same stark contrast exists for the case of testing
equivalence, where both distributions are unknown. While Canonne et al.
established a $\mathrm{poly}(\log n)$-query upper bound for equivalence
testing, very recently brought down to $\tilde O(\log\log n)$ by Falahatgar et
al. (COLT 2015), whether a dependence on the domain size $n$ is necessary was
still open, and explicitly posed by Fischer at the Bertinoro Workshop on
Sublinear Algorithms (2014). We show that any testing algorithm for equivalence
must make $\Omega(\sqrt{\log\log n})$ queries in the conditional sampling
model. This demonstrates a gap between identity and equivalence testing, absent
in the standard sampling model (where both problems have sampling complexity
$n^{\Theta(1)}$).
  We also obtain results on the query complexity of uniformity testing and
support-size estimation with conditional samples. We answer a question of
Chakraborty et al. (ITCS 2013) showing that non-adaptive uniformity testing
indeed requires $\Omega(\log n)$ queries in the conditional model. For the
related problem of support-size estimation, we provide both adaptive and
non-adaptive algorithms, with query complexities $\mathrm{poly}(\log\log n)$
and $\mathrm{poly}(\log n)$, respectively.


  Every partial colouring of a Hamming graph is uniquely related to a partial
Latin hyper-rectangle. In this paper we introduce the $\Theta$-stabilized
$(a,b)$-colouring game for Hamming graphs, a variant of the $(a,b)$-colouring
game so that each move must respect a given autotopism $\Theta$ of the
resulting partial Latin hyper-rectangle. We examine the complexity of this
variant by means of its chromatic number. We focus in particular on the
bi-dimensional case, for which the game is played on the Cartesian product of
two complete graphs, and also on the hypercube case.


  Over the past thirty years, there has been considerable progress in the
design of natural language interfaces to databases. Most of this work has
concerned snapshot databases, in which there are only limited facilities for
manipulating time-varying information. The database community is becoming
increasingly interested in temporal databases, databases with special support
for time-dependent entries. We have developed a framework for constructing
natural language interfaces to temporal databases, drawing on research on
temporal phenomena within logic and linguistics. The central part of our
framework is a logic-like formal language, called TOP, which can capture the
semantics of a wide range of English sentences. We have implemented an
HPSG-based sentence analyser that converts a large set of English queries
involving time into TOP formulae, and have formulated a provably correct
procedure for translating TOP expressions into queries in the TSQL2 temporal
database language. In this way we have established a sound route from English
to a general-purpose temporal database language.


  We propose that the major 2012 outburst of the supernova impostor SN 2009ip
was powered by an extended and repeated interaction between the Luminous Blue
Variable (LBV) and a more compact companion. Motivated by the recent analysis
of Margutti et al. (2013) of ejected clumps and shells we consider two
scenarios. In both scenarios the major 2012b outburst with total (radiated +
kinetic) energy of ~5 x 10^{49} erg was powered by accretion of 2-5 solar
masses onto the companion during a periastron passage (the first passage) of
the binary system approximately 20 days before the observed maximum of the
light curve. In the first scenario, the surviving companion scenario, the
companion was not destructed and still exists in the system after the outburst.
It ejected partial shells (or collimated outflows or clumps) for two
consecutive periastron passages after the major one. The orbital period was
reduced from ~38 days to ~25 days as a result of the mass transfer process that
took place during the first periastron passage. In the second scenario, the
merger scenario, some partial shells/clumps were ejected also in a second
periastron passage that took place ~20 days after the first one. After this
second periastron passage the companion dived too deep into the LBV envelope to
launch more outflows, and merged with the LBV.


  We propose and investigate thermometry of a setup employing dual quantum dots
with staircase ground state configuration. The stair-case ground state
configuration actuates thermally controlled inelastic tunnelling, which
translates into a temperature sensitive conductance, thereby inducing
thermometry. The performance of the set-up is then analyzed employing quantum
master equation (QME) for such systems in the sequential tunnelling regime. In
particular, it is demonstrated that the system performance, in terms of
temperature sensitivity and efficiency, is maximum in the regime of low
temperature, making such system suitable for cryogenic thermometry. The
proposed set-up can pave the path towards realization of high performance
cryogenic nano temperature sensors.


  One of the very first steps astronomers working in stellar physics perform to
advance in their studies, is to determine the most common/relevant physical
parameters of the objects of study (effective temperature, bolometric
luminosity, surface gravity, etc.). Different methodologies exist depending on
the nature of the data, intrinsic properties of the objects, etc. One common
approach is to compare the observational data with theoretical models passed
through some simulator that will leave in the synthetic data the same imprint
than the observational data carries, and see what set of parameters reproduce
the observations best. Even in this case, depending on the kind of data the
astronomer has, the methodology changes slightly. After parameters are
published, the community tend to quote, praise and criticize them, sometimes
paying little attention on whether the possible discrepancies come from the
theoretical models, the data themselves or just the methodology used in the
analysis. In this work we perform the simple, yet interesting, exercise of
comparing the effective temperatures obtained via SED and more detailed
spectral fittings (to the same grid of models), of a sample of well known and
characterized young M-type objects members to different star forming regions
and show how differences in temperature of up to 350 K can be expected just
from the difference in methodology/data used. On the other hand we show how
these differences are smaller for colder objects even when the complexity of
the fit increases like for example introducing differential extinction. To
perform this exercise we benefit greatly from the framework offered by the
Virtual Observatory.


  In dynamic nuclear polarization (DNP) experiments, the compound is driven
out-of-equilibrium by microwave (MW) irradiation of the radical electron spins.
Their stationary state has been recently probed via electron double resonance
(ELDOR) techniques showing, at low temperature, a broad depolarization of the
electron paramagnetic resonance (EPR) spectrum under microwave irradiation. In
this theoretical manuscript, we develop a numerical method to compute exactly
the EPR spectrum in presence of dipolar interactions. Our results reproduce the
observed broad depolarisation and provide a microscopic justification for
spectral diffusion mechanism. We show the validity of the spin-temperature
approach for typical radical concentration used in dissolution DNP protocols.
In particular once the interactions are properly taken into account, the
spin-temperature is consistent with the non-monotonic behavior of the EPR
spectrum with a wide minimum around the irradiated frequency.


  We apply the structure theory of finite dimensional algebras in order to
deduce dimension formulas for spaces of period numbers, i.e., complex numbers
defined by integrals of algebraic nature. We get a complete and conceptually
clear answer in the case of $1$-periods, generalising classical results like
Baker's theorem on the logarithms of algebraic numbers and partial results in
Huber--W{\"u}stholz \cite{huber-wuestholz}.
  The application to the case of Mixed Tate Motives (i.e., Multiple Zeta
Values) recovers the dimension estimates of Deligne--Goncharov
\cite{deligne-goncharov}.


  In this paper, a reduced-order model (ROM) based on the proper orthogonal
decomposition and the discrete empirical interpolation method is proposed for
efficiently simulating time-fractional partial differential equations (TFPDEs).
Both linear and nonlinear equations are considered. We demonstrate the
effectiveness of the ROM by several numerical examples, in which the ROM
achieves the same accuracy of the full-order model (FOM) over a long-term
simulation while greatly reducing the computational cost. The proposed ROM is
then regarded as a surrogate of FOM and is applied to an inverse problem for
identifying the order of the time-fractional derivative of the TFPDE model.
Based on the Levenberg--Marquardt regularization iterative method with the
Armijo rule, we develop a ROM-based algorithm for solving the inverse problem.
For cases in which the observation data is either uncontaminated or
contaminated by random noise, the proposed approach is able to achieve accurate
parameter estimation efficiently.


  In this note we investigate the asymptotic behavior of plane shear thickening
fluids around a bounded obstacle. Different from the Navier-Stokes case
considered by Gilbarg-Weinberger in \cite{GW1978}, where the good structure of
the vorticity can be exploited and weighted energy estimates can be applied, we
have to overcome the nonlinear term of high order. The decay estimates of the
velocity was obtained by combining Point-wise Behavior Theorem in \cite{Galdi}
and Brezis-Gallouet inequality in \cite{BG1980} together, which is independent
of interest.


  We present a thermal and quantum-mechanical treatment of nuclear rotation
using the formalism of static path approximation (SPA) plus random-phase
approximation (RPA). Naive perturbation theory fails because of the presence of
zero-frequency modes due to dynamical symmetry breaking. Such modes lead to
infrared divergences. We show that composite zero-frequency excitations are
properly treated within the collective coordinate method. The resulting
perturbation theory is free from infrared divergences. Without the assumption
of individual random spin vectors, we derive microscopically the spin
distribution of the level density. The moment of inertia is thereby related to
the spin-cutoff parameter in the usual way. Explicit calculations are performed
for 56^Fe; various thermal properties are discussed. In particular, we
demonstrate that the increase of the moment of inertia with increasing
temperature is correlated with the suppression of pairing correlations.


  Offering incentives (e.g., coupons at Amazon, discounts at Uber and video
bonuses at Tiktok) to user is a common strategy used by online platforms to
increase user engagement and platform revenue. Despite its proven
effectiveness, these marketing incentives incur an inevitable cost and might
result in a low ROI (Return on Investment) if not used properly. On the other
hand, different users respond differently to these incentives, for instance,
some users never buy certain products without coupons, while others do anyway.
Thus, how to select the right amount of incentives (i.e. treatment) to each
user under budget constraints is an important research problem with great
practical implications. In this paper, we call such problem as a
budget-constrained treatment selection (BTS) problem.
  The challenge is how to efficiently solve BTS problem on a Large-Scale
dataset and achieve improved results over the existing techniques. We propose a
novel tree-based treatment selection technique under budget constraints, called
Large-Scale Budget-Constrained Causal Forest (LBCF) algorithm, which is also an
efficient treatment selection algorithm suitable for modern distributed
computing systems. A novel offline evaluation method is also proposed to
overcome an intrinsic challenge in assessing solutions' performance for BTS
problem in randomized control trials (RCT) data. We deploy our approach in a
real-world scenario on a large-scale video platform, where the platform gives
away bonuses in order to increase users' campaign engagement duration. The
simulation analysis, offline and online experiments all show that our method
outperforms various tree-based state-of-the-art baselines. The proposed
approach is currently serving over hundreds of millions of users on the
platform and achieves one of the most tremendous improvements over these
months.


  We present a modification of the $\Delta$SCF method of calculating energies
of excited states, in order to make it applicable to resonance calculations of
molecules adsorbed on metal surfaces, where the molecular orbitals are highly
hybridized. The $\Delta$SCF approximation is a density functional method
closely resembling standard density functional theory (DFT), the only
difference being that in $\Delta$SCF one or more electrons are placed in higher
lying Kohn-Sham orbitals, instead of placing all electrons in the lowest
possible orbitals as one does when calculating the ground state energy within
standard DFT. We extend the $\Delta$SCF method by allowing excited electrons to
occupy orbitals which are linear combinations of Kohn-Sham orbitals. With this
extra freedom it is possible to place charge locally on adsorbed molecules in
the calculations, such that resonance energies can be estimated. The method is
applied to N$_2$, CO and NO adsorbed on different metallic surfaces and
compared to ordinary $\Delta$SCF without our modification, spatially
constrained DFT and inverse-photoemission spectroscopy (IPES) measurements.
This comparison shows that the modified $\Delta$SCF method gives results in
close agreement with experiment, significantly closer than the comparable
methods. For N$_2$ adsorbed on ruthenium (0001) we map out a 2-dimensional part
of the potential energy surfaces in the ground state and the 2$\pi$-resonance.
Finally we compare the $\Delta$SCF approach on gas-phase N$_2$ and CO, to
higher accuracy methods. Excitation energies are approximated with accuracy
close to that of time-dependent density functional theory, and we see very good
agreement in the minimum shift of the potential energy surfaces in the excited
state compared to the ground state.


  We use the free entropy defined by D. Voiculescu to prove that the free group
factors can not be decomposed as closed linear spans of noncommutative
monomials in elements of nonprime subfactors or abelian $*$-subalgebras, if the
degrees of monomials have an upper bound depending on the number of generators.
The resulting estimates for the hyperfinite and abelian dimensions of free
group factors settle in the affirmative a conjecture of L. Ge and S. Popa (for
infinitely many generators).


  Both remote-sensing measurements using the interplanetary scintillation (IPS)
technique and in situ measurements by the Ulysses spacecraft show a bimodal
structure for the solar wind at solar minimum conditions. At present what makes
the fast wind fast and the slow wind slow still remains to be answered. While a
robust empirical correlation exists between the coronal expansion rate $f_c$ of
the flow tubes and the speeds $v$ measured in situ, further data analysis
suggests that $v$ depends on more than just $f_c$. We examine whether the
non-radial shape of field lines, which naturally accompanies any non-radial
expansion, could be an additional geometrical factor. We solved the transport
equations incorporating the heating due to turbulent Alfv\'en waves for an
electron-proton solar wind along curved field lines given by an analytical
magnetic field model, representative of a solar minimum corona. The field line
shape is found to influence substantially the solar wind parameters, reducing
the asymptotic speed by up to $\sim 130$ km s$^{-1}$, or by $\sim 28%$ in
relative terms, compared with the case neglecting the field line curvature.
This effect was interpreted in the general framework of energy addition in the
solar wind: Relative to the straight case, the field line curvature enhances
the effective energy deposition to the subsonic flow, resulting in a higher
proton flux and a lower terminal proton speed. Our computations suggest that
the field line curvature could be a geometrical factor which, in addition to
the tube expansion, substantially influences the solar wind speed. Furthermore,
at solar minima although the field line curvature unlikely affects the polar
fast solar wind, it does help make the wind at low latitudes slow, thereby
helping better reproduce the Ulysses measurements.


  We study the spin-resolved transport properties of T-shaped double quantum
dots coupled to ferromagnetic leads. Using the numerical renormalization group
method, we calculate the linear conductance and the spin polarization of the
current for various model parameters and at different temperatures. We show
that an effective exchange field due to the presence of ferromagnets results in
different conditions for Fano destructive interference in each spin channel.
This spin dependence of the Fano effect leads to perfect spin polarization, the
sign of which can be changed by tuning the dots' levels. Large spin
polarization occurs due to Coulomb correlations in the dot, which is not
directly coupled to the leads, while finite correlations in the
directly-coupled dot can further enhance this effect. Moreover, we complement
accurate numerical results with a simple qualitative explanation based on
analytical expressions for the zero-temperature conductance. The proposed
device provides a prospective example of an electrically-controlled, fully
spin-polarized current source, which operates without an external magnetic
field.


  A measurement of jet shapes in top-quark pair events using 1.8 fb(-1) of
sqrt(s) = 7 TeV pp collision data recorded by the ATLAS detector at the LHC is
presented. Samples of top-quark pair events are selected in both the
single-lepton and dilepton final states. The differential and integrated shapes
of the jets initiated by bottom-quarks from the top-quark decays are compared
with those of the jets originated by light-quarks from the hadronic W-boson
decays in the single-lepton channel. The light-quark jets are found to have a
narrower distribution of the momentum flow inside the jet area than b-quark
jets.


  Stochastic modeling of phylogenies raises five questions that have received
varying levels of attention from quantitatively inclined biologists. 1) How
large do we expect (from the model) the ration of maximum historical diversity
to current diversity to be? 2) From a correct phylogeny of the extant species
of a clade, what can we deduce about past speciation and extinction rates? 3)
What proportion of extant species are in fact descendants of still-extant
ancestral species, and how does this compare with predictions od models? 4)
When one moves from trees on species to trees on sets of species (whether
traditional higher order taxa or clades from PhyloCode), does one expect trees
to become more unbiased as a purely logical consequence of tree structure,
without signifying any real biological phenomenon? 5) How do we expect that
fluctuation rates for counts of higher order taxa should compare with
fluctuation rates for number of species? WE present a mathematician's view
based on an oversimplified modeling framework in which all these questions can
be studied coherently.


  The method of wavefront shaping to control optical properties of opaque media
is a promising technique for authentication applications. One of the main
challenges of this technique is the sensitivity of the wavefront-sample
coupling to translation and/or rotation. To better understand how translation
and rotation affect the wavefront- sample coupling we perform experiments in
which we first optimize reflection from an opaque surface--to obtain an optimal
wavefront--and then translate or rotate the surface and measure the new
reflected intensity pattern. By using the correlation between the optimized and
translated or rotated patterns we determine how sensitive the wavefront-sample
coupling is. These experiments are performed for different
spatial-light-modulator (SLM) bin sizes, beam-spot sizes, and nanoparticle
concentrations. We find that all three parameters affect the different
positional changes, implying that an optimization scheme can be used to
maximize the stability of the wavefront-sample coupling. We also develop a
model to simulate sample translation or rotation and its effect on the coupling
stability, with the simulation results being qualitatively consistent with
experiment.


  Particular complexity of linear quantum optical networks is deserved recently
certain attention due to possible implications for theory of quantum
computation. Two relevant models of bosons are discussed in presented work.
Symmetric product of Hilbert spaces produces rather abstract model. The second
one is obtained by quantization of harmonic oscillator. In contrast to
considered bosonic processes, so-called "fermionic linear optics" is
effectively simulated on classical computer. The comparison of bosonic and
fermionic case clarifies the controversy and the more elaborated oscillator
model provides a deeper analogy.


  For the system with two degrees of freedom, which is an analogue of the 4th
Appelrot class for a gyrostat of the Kowalevski type in a double force field
the problem of the classification of bifurcation diagrams is solved. The
separating set is built and its completeness is proved. All transformations
taking place in the diagrams are shown. The results serve as a necessary part
of solving the problem of obtaining the topological invariants for the Reyman -
Semenov-Tian-Shansky system.


  The variational autoencoder (VAE) is a generative model with continuous
latent variables where a pair of probabilistic encoder (bottom-up) and decoder
(top-down) is jointly learned by stochastic gradient variational Bayes. We
first elaborate Gaussian VAE, approximating the local covariance matrix of the
decoder as an outer product of the principal direction at a position determined
by a sample drawn from Gaussian distribution. We show that this model, referred
to as VAE-ROC, better captures the data manifold, compared to the standard
Gaussian VAE where independent multivariate Gaussian was used to model the
decoder. Then we extend the VAE-ROC to handle mixed categorical and continuous
data. To this end, we employ Gaussian copula to model the local dependency in
mixed categorical and continuous data, leading to {\em Gaussian copula
variational autoencoder} (GCVAE). As in VAE-ROC, we use the rank-one
approximation for the covariance in the Gaussian copula, to capture the local
dependency structure in the mixed data. Experiments on various datasets
demonstrate the useful behaviour of VAE-ROC and GCVAE, compared to the standard
VAE.


  In this paper we propose to investigate the transverse single spin asymmetry
in the inelastic $J/\Psi$ photoproduction in $p^\uparrow p$ and $p^\uparrow A$
collisions at RHIC energies. At leading order this process probes the gluon
Sivers function. We predict large values for the cross sections, which
indicates that its experimental analysis is, in principle, feasible. The
rapidity dependence of the single spin asymmetry is presented. We obtain that
the asymmetry is strongly dependent on the model used for the gluon Sivers
function and that it can be probed by the analysis of the $J/\Psi$ production
at forward rapidities. Our results indicate that a future experimental analysis
of this process can be useful to constrain the gluon Sivers function.


  In this paper, we study vacuum bubble collisions with various potentials
including gravitation, assuming spherical, planar, and hyperbolic symmetry. We
use numerical calculations from double-null formalism. Spherical symmetry can
mimic the formation of a black hole via multiple bubble collisions. Planar and
especially hyperbolic symmetry describes two bubble collisions. We study both
cases, when two true vacuum regions have the same field value or different
field values, by varying tensions. For the latter case, we also test symmetric
and asymmetric bubble collisions, and see details of causal structures. If the
colliding energy is sufficient, then the vacuum can be destabilized, and it is
also demonstrated. This double-null formalism can be a complementary approach
in the context of bubble collisions.


  The energy spectrum of central divalent impurity is calculated using the
effective mass approximation in a spherical quantum dot (QD). The dipole moment
and oscillator strength of interlevel transition is defined. The dependence of
linear absorption coefficient on the QD size and electromagnetic frequency is
analyzed. The obtained results are compared with the results of univalent
impurity.


  In this paper, we study the nonlinear stability of the composite wave
consisting of planar rarefaction and planar contact waves for viscous
conservation laws with degenerate flux under multi-dimensional periodic
perturbations. To the level of our knowledge, it is the first stability result
of the composite wave for conservation laws in several dimensions. Moreover,
the perturbations studied in the present paper are periodic, which keep
constantly oscillating at infinity. Suitable ansatz is constructed to overcome
the difficulty caused by this kind of perturbation and delicate estimates are
done on zero and non-zero modes of perturbations. We obtain satisfactory decay
rates for zero modes and exponential decay rates for non-zero modes.


  In contrast to fully connected networks, Convolutional Neural Networks (CNNs)
achieve efficiency by learning weights associated with local filters with a
finite spatial extent. An implication of this is that a filter may know what it
is looking at, but not where it is positioned in the image. Information
concerning absolute position is inherently useful, and it is reasonable to
assume that deep CNNs may implicitly learn to encode this information if there
is a means to do so. In this paper, we test this hypothesis revealing the
surprising degree of absolute position information that is encoded in commonly
used neural networks. A comprehensive set of experiments show the validity of
this hypothesis and shed light on how and where this information is represented
while offering clues to where positional information is derived from in deep
CNNs.


  For cohomological (resp. homological) coefficient systems ${\mathcal F}$
(resp. ${\mathcal V}$) on affine buildings $X$ with Coxeter data of type
$\widetilde{A}_d$ we give for any $k\ge1$ a sufficient local criterion which
implies $H^k(X,{\mathcal F})=0$ (resp. $H_k(X,{\mathcal V})=0)$. Using this
criterion we prove a conjecture of de Shalit on the acyclicity of coefficient
systems attached to hyperplane arrangements on the Bruhat-Tits building of the
general linear group over a local field. We also generalize an acyclicity
theorem of Schneider and Stuhler on coefficient systems attached to
representations.


  A lengthy bibliography of books referring to special and/or general
relativity is provided to give a background for discussions on the historical
use of the concept of relativistic mass.


  (Abridged) We use 95, 150, and 220GHz observations from the SPT to examine
the SZE signatures of a sample of 46 X-ray selected groups and clusters drawn
from ~6 deg^2 of the XMM-BCS. These systems extend to redshift z=1.02, have
characteristic masses ~3x lower than clusters detected directly in the SPT data
and probe the SZE signal to the lowest X-ray luminosities (>10^42 erg s^-1)
yet.
  We develop an analysis tool that combines the SZE information for the full
ensemble of X-ray-selected clusters. Using X-ray luminosity as a mass proxy, we
extract selection-bias corrected constraints on the SZE significance- and
Y_500-mass relations. The SZE significance- mass relation is in good agreement
with an extrapolation of the relation obtained from high mass clusters.
However, the fit to the Y_500-mass relation at low masses, while in good
agreement with the extrapolation from high mass SPT clusters, is in tension at
2.8 sigma with the constraints from the Planck sample. We examine the tension
with the Planck relation, discussing sample differences and biases that could
contribute.
  We also present an analysis of the radio galaxy point source population in
this ensemble of X-ray selected systems. We find 18 of our systems have 843 MHz
SUMSS sources within 2 arcmin of the X-ray centre, and three of these are also
detected at significance >4 by SPT. Of these three, two are associated with the
group brightest cluster galaxies, and the third is likely an unassociated
quasar candidate. We examine the impact of these point sources on our SZE
scaling relation analyses and find no evidence of biases. We also examine the
impact of dusty galaxies using constraints from the 220 GHz data. The stacked
sample provides 2.8$\sigma$ significant evidence of dusty galaxy flux, which
would correspond to an average underestimate of the SPT Y_500 signal that is
(17+-9) per cent in this sample of low mass systems.


  Of the over 5000 exoplanets that have been detected, only about a dozen have
ever been directly imaged. Earth-like exoplanets are on the order of 10 billion
times fainter than their host star in visible and near-infrared, requiring a
coronagraph instrument to block primary starlight and allow for the imaging of
nearby orbiting planets. In the pursuit of direct imaging of exoplanets, scalar
vortex coronagraphs (SVCs) are an attractive alternative to vector vortex
coronagraphs (VVCs). VVCs have demonstrated 2e-9 raw contrast in broadband
light but have several limitations due to their polarization properties. SVCs
imprint the same phase ramp as VVCs on the incoming light and do not require
polarization splitting, but they are inherently chromatic. Discretized phase
ramp patterns such as a wrapped staircase help reduce SVC chromaticity and
simulations show it outperforms a chromatic classical vortex in broadband
light. We designed, fabricated, and tested a wrapped staircase SVC, and here we
present the broadband characterization on the high contrast spectroscopy
testbed. We also performed wavefront correction on the in-air coronagraph
testbed at NASA's Jet Propulsion Laboratory and achieved an average raw
contrasts of 3.2e-8 in monochromatic light and 2.2e-7 across a 10% bandwidth.


  The correspondence between right triangles with rational sides, triplets of
rational squares in arithmetic succession and integral solutions of certain
quadratic forms is well known. We show how this correspondence can be extended
to the generalized notions of rational $\theta$-triangles, rational squares
occurring in arithmetic progressions and concordant forms. In our approach we
establish one-to-one mappings to rational points on certain elliptic curves and
examine in detail the role of solutions of the $\theta$-congruent number
problem and the concordant form problem associated with nontrivial torsion
points on the corresponding elliptic curves. This approach allows us to combine
and extend some disjoint results obtained by a number of authors, to clarify
some statements in the literature and to answer some hitherto open questions.


  The machine translation (MT) task is typically formulated as that of
returning a single translation for an input segment. However, in many cases,
multiple different translations are valid and the appropriate translation may
depend on the intended target audience, characteristics of the speaker, or even
the relationship between speakers. Specific problems arise when dealing with
honorifics, particularly translating from English into languages with formality
markers. For example, the sentence "Are you sure?" can be translated in German
as "Sind Sie sich sicher?" (formal register) or "Bist du dir sicher?"
(informal). Using wrong or inconsistent tone may be perceived as inappropriate
or jarring for users of certain cultures and demographics. This work addresses
the problem of learning to control target language attributes, in this case
formality, from a small amount of labeled contrastive data. We introduce an
annotated dataset (CoCoA-MT) and an associated evaluation metric for training
and evaluating formality-controlled MT models for six diverse target languages.
We show that we can train formality-controlled models by fine-tuning on labeled
contrastive data, achieving high accuracy (82% in-domain and 73% out-of-domain)
while maintaining overall quality.


  We study the effect of time-fluctuating social influences on the formation of
polarization and consensus in a three-party community consisting of two types
of voters ("leftists" and "rightists") holding extreme opinions, and moderate
agents acting as "centrists". The former are incompatible and do not interact,
while centrists hold an intermediate opinion and can interact with extreme
voters. When a centrist and a leftist/rightist interact, they can become either
both centrists or both leftists/rightists. The population eventually either
reaches consensus with one of the three opinions, or a polarization state
consisting of a frozen mixture of leftists and rightists. As a main novelty,
here agents interact subject to time-fluctuating external influences favouring
in turn the spread of leftist and rightist opinions, or the rise of centrism.
We determine the fate of the population under various scenarios, and show how
the rate of change of external influences can drastically affect the
polarization and consensus probabilities, as well as the mean time to reach the
final state.


  We undertake the study of the charged Higgs bosons predicted by the model
with gauge symmetry $SU(3)_c \otimes SU(3)_L \otimes U(1)_X$. By considering
Yukawa mixing couplings between small ($\sim$ GeV) and large ($\sim$ TeV)
scales, we show that the hypercharge-one $H_1^{\pm}$ and hypercharge-two
$H_2^{\pm}$ Higgs bosons predicted by the model, can be simultaneously produced
in $pp$ collisions at different production rates. At low energy, the
$H_1^{\pm}$ bosons exhibit the same properties as the charged Higgs bosons from
a two Higgs doublet model (2HDM), while $H_2^{\pm}$ are additional like-charged
Higgs bosons from the underlying 3-3-1 model. Thus, the identification of
multiple like-charged Higgs boson resonances may test the compatibility of
theoretical models with experimental data. We study $H_{1,2}^{\pm}$ pair and
associated $tbH_{1,2}^{\pm}$ productions at CERN LHC collider. In particular,
we obtain that pair production can be as large as the single production in
gluon-gluon collisions due to the interchange of a heavy neutral $Z'$ gauge
boson predicted by the model. By considering decays to leptons $H_{1,2}^{\pm}
\rightarrow \tau \nu_{\tau}$, we obtain scenarios where small peaks of
$H_{2}^{\pm}$-boson events in transverse mass distributions can be identified
over the $H_{1}^{\pm}$ background.


  We characterize the two-photon excitation of an ultracold gas of Rubidium
atoms to Rydberg states analysing the induced atomic losses from an optical
dipole trap. Extending the duration of the Rydberg excitation to several ms,
the ground state atoms are continuously coupled to the formed positively
charged plasma. In this regime we measure the $n$-dependence of the blockade
effect and we characterise the interaction of the excited states and the ground
state with the plasma. We also investigate the influence of the
quasi-electrostatic trapping potential on the system, confirming the validity
of the ponderomotive model for states with $20\leq n\leq 120$.


  An $n$-by-$n$ bipartite graph is $H$-saturated if the addition of any missing
edge between its two parts creates a new copy of $H$. In 1964, Erd\H{o}s,
Hajnal and Moon made a conjecture on the minimum number of edges in a
$K_{s,s}$-saturated bipartite graph. This conjecture was proved independently
by Wessel and Bollob\'as in a more general, but ordered, setting: they showed
that the minimum number of edges in a $K_{(s,t)}$-saturated bipartite graph is
$n^2-(n-s+1)(n-t+1)$, where $K_{(s,t)}$ is the "ordered" complete bipartite
graph with $s$ vertices in the first color class and $t$ vertices in the
second. However, the very natural question of determining the minimum number of
edges in the unordered $K_{s,t}$-saturated case remained unsolved. This problem
was considered recently by Moshkovitz and Shapira who also conjectured what its
answer should be. In this short paper we give an asymptotically tight bound on
the minimum number of edges in a $K_{s,t}$-saturated bipartite graph, which is
only smaller by an additive constant than the conjecture of Moshkovitz and
Shapira. We also prove their conjecture for $K_{2,3}$-saturation, which was the
first open case.


  It is well known that differences in the average number of friends among
social groups can cause inequality in the average wage and/or unemployment
rate. However, the impact of social network structure on inequality is not
evident. In this paper, we show that not only the average number of friends but
also the heterogeneity of degree distribution can affect inter-group
inequality. A worker group with a scale-free network tends to be disadvantaged
in the labor market compared to a group with an Erd\H{o}s-R\'{e}nyi network
structure. This feature becomes strengthened as the skewness of the degree
distribution increases in scale-free networks. We show that the government's
policy of discouraging referral hiring worsens social welfare and can
exacerbate inequality.


  The question about the behavior of gaps between zeros of polynomials under
differentiation is classical and goes back to Marcel Riesz. In this paper, we
analyze a nonlocal nonlinear partial differential equation formally derived by
Stefan Steinerberger to model dynamics of roots of polynomials under
differentiation. Interestingly, the same equation has also been recently
obtained formally by Dimitri Shlyakhtenko and Terence Tao as the evolution
equation for free fractional convolution of a measure - an object in free
probability that is also related to minor processes for random matrices. The
partial differential equation bears striking resemblance to hydrodynamic models
used to describe the collective behavior of agents (such as birds, fish or
robots) in mathematical biology. We consider periodic setting and show global
regularity and exponential in time convergence to uniform density for solutions
corresponding to strictly positive smooth initial data. In the second part of
the paper we connect rigorously solutions of the Steinerberger's PDE and
evolution of roots under differentiation for a class of trigonometric
polynomials. Namely, we prove that the distribution of the zeros of the
derivatives of a polynomial and the corresponding solutions of the PDE remain
close for all times. The global in time control follows from the analysis of
the propagation of errors equation, which turns out to be a nonlinear
fractional heat equation with the main term similar to the modulated
discretized fractional Laplacian $(-\Delta)^{1/2}$.


  The coupled chemotaxis fluid system \begin{equation} \left\{
\begin{array}{llc} n_t=\Delta n-\nabla\cdot(n S(x,n,c)\cdot\nabla
c)-u\cdot\nabla n, &(x,t)\in \Omega\times (0,T), \displaystyle c_t=\Delta
c-nc-u\cdot\nabla c, &(x,t)\in\Omega\times (0,T), \displaystyle u_t=\Delta
u-(u\cdot\nabla )u+\nabla P+n\nabla\Phi,\quad \nabla\cdot u=0,
&(x,t)\in\Omega\times (0,T), \displaystyle \nabla c\cdot\nu=(\nabla
n-nS(x,n,c)\cdot\nabla c)\cdot\nu=0, \;\; u=0,&(x,t)\in \partial\Omega\times
(0,T), n(x,0)=n_{0}(x),\quad c(x,0)=c_{0}(x),\quad u(x,0)=u_0(x) & x\in\Omega,
\end{array} \right. \end{equation} where $S\in (C^2(\bar{\Omega}\times
[0,\infty)^2))^{N\times N}$, is considered in a bounded domain
$\Omega\subset\mathbb{R}^N$, $N\in\{2,3\}$, with smooth boundary. We show that
it has global classical solutions if the initial data satisfy certain smallness
conditions and give decay properties of these solutions.


  A modified version of relational quantum mechanics is developed based on the
three following ideas. An observer can develop an internally consistent
description of the universe but it will, of necessity, differ in particulars
from the description developed by any other observer. The state vector is
epistomological and relative to a given quantum system as in the original
relational quantum mechanics. If two quantum systems are entangled, they will
observe themselves to be in just one of the many states in the Schmidt
biorthonormal decomposition and not in a linear combination of many.


  Using a variational technique, we generalize the statistical physics approach
of learning from random examples to make it applicable to real data. We
demonstrate the validity and relevance of our method by computing approximate
estimators for generalization errors that are based on training data alone.


  The long and relatively faint gamma-ray burst GRB 060605 detected by
\emph{Swift}/BAT lasted about 20 sec. Its afterglow could be observed with
\emph{Swift}/XRT for nearly 1 day, while \emph{Swift}/UVOT could detect the
afterglow during the first 6 hours after the event. Here, we report on integral
field spectroscopy of its afterglow performed with PMAS/PPak mounted at the
Calar Alto 3.5 m telescope. In addition, we report on a detailed analysis of
XRT and UVOT data and on the results of deep late-time VLT observations that
reveal the GRB host galaxy. We find that the burst occurred at a redshift of
$z$=3.773, possibly associated with a faint, $R_C=26.4 \pm 0.3$ host. Based on
the optical and X-ray data, we deduce information on the SED of the afterglow,
the position of the cooling frequency in the SED, the nature of the circumburst
environment, its collimation factor, and its energetics. We find that the GRB
fireball was expanding into a constant-density medium and that the explosion
was collimated with a narrow half-opening angle of about 2.4 degrees. The
initial Lorentz factor of the fireball was about 250; however, its
beaming-corrected energy release in the gamma-ray band was comparably low. The
optical, X-ray afterglow, on the other hand, was rather luminous. Finally, we
find that the data are consistent within the error bars with an achromatic
evolution of the afterglow during the suspected jet break time at about 0.27
days after the burst.


  A design study of a horizontal neutron reflectometer adapted to the general
baseline of the long pulse European Spallation Source (ESS) is presented. The
instrument layout comprises solutions for the neutron guide, high-resolution
pulse shaping and beam bending onto a sample surface being so far unique in the
field of reflectometry. The length of this instrument is roughly 55 m, enabling
$\delta \lambda / \lambda$ resolutions from 0.5% to 10%. The incident beam is
focussed in horizontal plane to boost measurements of sample sizes of 1*1
cm{^2} and smaller with potential beam deflection in both downward and upward
direction. The range of neutron wavelengths untilized by the instrument is 2 to
7.1 (12.2, ...) {\AA}, if every (second, ...) neutron source ulse is used.
Angles of incidence can be set between 0{\deg} and 9{\deg} with a total
accessible q-range from 4*10^{-3} {\AA}^{-1} up to 1 {\AA}^{-1}. The instrument
operates both in {\theta}/{\theta} (free liquid surfaces) and
{\theta}/2{\theta} (solid/liquid, air/solid interfaces) geometry. The
experimental setup will in particular enable direct studies on ultrathin films
(d ~ 10 {\AA}) and buried monolayers to multilayered structures of up to 3000
{\AA} total thickness. The horizontal reflectometer will further foster
investigations of hierarchical systems from nanometer to micrometer length
scale, as well as their kinetics and dynamical properties, in particular under
load (shear, pressure, external fields). Polarization and polarization analysis
as well as the GISANS option are designed as potential modules to be
implemented separately in the generic instrument layout. The instrument is
highly flexible and offers a variety of different measurement modes. With
respect to its mechanical components the instrument is exclusively based on
current technology. Risks of failure for the chosen setup are minimum.


  Density functional calculations of the electronic structure are used to
elucidate the bonding of Li$_3$AlH$_6$. It is found that this material is best
described as ionic, and in particular that the [AlH$_6$]$^{3-}$ units are not
reasonably viewed as substantially covalent.


  We consider the question of whether the leading contribution to the
entanglement entropy in holographic CFTs is truly given by the expectation
value of a linear operator as is suggested by the Ryu-Takayanagi formula. We
investigate this property by computing the entanglement entropy, via the
replica trick, in states dual to superpositions of macroscopically distinct
geometries and find it consistent with evaluating the expectation value of the
area operator within such states. However, we find that this fails once the
number of semi-classical states in the superposition grows exponentially in the
central charge of the CFT. Moreover, in certain such scenarios we find that the
choice of surface on which to evaluate the area operator depends on the density
matrix of the entire CFT. This nonlinearity is enforced in the bulk via the
homology prescription of Ryu-Takayanagi. We thus conclude that the homology
constraint is not a linear property in the CFT. We also discuss the existence
of entropy operators in general systems with a large number of degrees of
freedom.


  We propose two experimental schemes to determine and so to realize the
Avogadro constant $N\_{A}$ at the level of 10$^{-7}$ or better with a watt
balance experiment and a cold atom experiment measuring $h/m(X)$ (where $h$ is
the Planck constant and $m(X)$ the mass of the atom $X$). We give some
prospects about achievable uncertainties and we discuss the opportunity to test
the existence of possible unknown correction factors for the Josephson effect
and quantum Hall effect.


  The Smithsonian/NASA ADS Abstract Service contains a wealth of data for
astronomers and librarians alike, yet the vast majority of usage consists of
rudimentary searches. Hints on how to obtain more focused search results by
using more of the various capabilities of the ADS are presented, including
searching by affiliation. We also discuss the classification of articles by
content and by referee status.
  The ADS is funded by NASA Grant NNG06GG68G-16613687.


  We describe a new complex system model of an evolving production economy.
This model is the simplest we can envisage which incorporates the new
observation that the rate of an economic production process depends only on the
minimum of its supplies of inputs. We describe how this condition gives rise to
a new type of complex multiple timescale dynamical evolution through a novel
type of bifurcation we call a `trapping bifurcation', which is also shown to be
one cause of non-equilibrium economic behaviour. Such dynamics is an example of
meta-level coupling which may also arise in other fields such as the
organization of a living cell as a network of molecular machines.


  As one of the first proposed topologically protected states, the quantum spin
Hall effect in graphene relies critically on the existence of a spin-dependent
gap at the K/K' points of the Brillouin zone. Using a tight-binding formulation
based on the method of invariants, we identify the origin of such an intrinsic
gap as the three-center interaction between the pi-orbitals caused by
spin-orbit interactions. This methodology incorporates all symmetry compliant
interactions previously neglected and has wider applications for comparisons
between first-principle calculations and the tight-binding method. It also
identifies a correction to the Haldane model and its generalization, which
incorporates the spin degrees of freedom and reproduces all the salient
features required for the quantum spin Hall effect in graphene.


  Bandit convex optimisation is a fundamental framework for studying
zeroth-order convex optimisation. These notes cover the many tools used for
this problem, including cutting plane methods, interior point methods,
continuous exponential weights, gradient descent and online Newton step. The
nuances between the many assumptions and setups are explained. Although there
is not much truly new here, some existing tools are applied in novel ways to
obtain new algorithms. A few bounds are improved in minor ways.


  The multiferroic behavior of the hypothetical Aurivillius compound Bi4Mn3O12
has been explored on the basis of density functional calculations. We find that
the tetragonal paraelectric phase of this material is ferromagnetic, showing
ferroelectric and antiferrodistortive instabilities similar to the ones
observed in its ferroelectric parent compound Bi4Ti3O12 . Our results indicate,
however, that the presence of Mn+4 ions at the B-sites shrinks the cell volume
and consequently the unstable polar mode, associated with the ferroelectric
polarization, is overcame by an antiferrodistortive distortion. In this way,
Bi4Mn3O12 exhibits incipient ferroelectricity at its equilibrium volume. We
show that the ferroelectric state can be favored by strain or partial
substitution of Mn with Ti.


  We demonstrate the realization of an electrically-driven integrated source of
surface plasmon polaritons. Light-emitting individual single-walled carbon
nanotube field effect transistors were fabricated in a plasmonic-ready
platform. The devices were operated at ambient condition to act as an
electroluminescence source localized near the contacting gold electrodes. We
show that photon emission from the semiconducting channel can couple to
propagating surface plasmons developing in the electrical terminals.
Momentum-space spectroscopy suggests that excited plasmon modes are bound to
the metal-glass interface. Our results underline the high degree of
compatibility between state-of-the art nano-optoelectronic devices and
plasmonic architectures.


  Machine learning (ML) models are increasingly deployed to production, calling
for efficient inference serving systems. Efficient inference serving is
complicated by two challenges: (i) ML models incur high computational costs,
and (ii) the request arrival rates of practical applications have frequent,
high, and sudden variations which make it hard to correctly provision hardware.
Model cascades are positioned to tackle both of these challenges, as they (i)
save work while maintaining accuracy, and (ii) expose a high-resolution
trade-off between work and accuracy, allowing for fine-grained adjustments to
request arrival rates. Despite their potential, model cascades haven't been
used inside an online serving system. This comes with its own set of
challenges, including workload adaption, model replication onto hardware,
inference scheduling, request batching, and more. In this work, we propose
CascadeServe, which automates and optimizes end-to-end inference serving with
cascades. CascadeServe operates in an offline and online phase. In the offline
phase, the system pre-computes a gear plan that specifies how to serve
inferences online. In the online phase, the gear plan allows the system to
serve inferences while making near-optimal adaptations to the query load at
negligible decision overheads. We find that CascadeServe saves 2-3x in cost
across a wide spectrum of the latency-accuracy space when compared to
state-of-the-art baselines on different workloads.


  Landau damping in weakly interacting Bose gases is investigated by means of
perturbation theory. Our approach points out the crucial role played by
Bose-Einstein condensation and yields an explicit expression for the decay rate
of elementary excitations in both uniform and non uniform gases. Systematic
results are derived for the phonon width in homogeneous gases interacting with
repulsive forces. Special attention is given to the low and high temperature
regimes.


  We show that the space of rooted tree-based phylogenetic networks is
connected under rooted nearest-neighbour interchange (rNNI) moves.


  We develop and study FPGA implementations of algorithms for charged particle
tracking based on graph neural networks. The two complementary FPGA designs are
based on OpenCL, a framework for writing programs that execute across
heterogeneous platforms, and hls4ml, a high-level-synthesis-based compiler for
neural network to firmware conversion. We evaluate and compare the resource
usage, latency, and tracking performance of our implementations based on a
benchmark dataset. We find a considerable speedup over CPU-based execution is
possible, potentially enabling such algorithms to be used effectively in future
computing workflows and the FPGA-based Level-1 trigger at the CERN Large Hadron
Collider.


  Is life a common outcome of physical and chemical processes in the universe?
Within our own solar system, a successful search for even primitive life, were
it to have an origin independent from life on Earth, would dramatically advance
a positive answer. The most stringent test for a second independent origin of
life on Earth would come from examination of either the most physically remote
from Earth, or the most exotic type, of planetary environments in which one
might plausibly imagine a form of life could exist. In this paper I argue that
Saturn's moon Titan is the best such target in our solar system. Further, Titan
might be a type example of a planetary environment abundant throughout the
cosmos.


  A filter for universal real-time prediction of band-limited signals is
presented. The filter consists of multiple time-delayed feedback terms in order
to accomplish anticipatory coupling, which again leads to a negative group
delay for frequencies in the baseband. The universality of the filter arises
from its property that it does not rely on a specific model of the signal.
Specifically, as long as the signal to be predicted is band-limited with a
known cutoff frequency, the filter order, the only parameter of the filter,
follows and the filter predicts the signal in real time up to a prediction
horizon that depends on the cutoff frequency, too. It is worked out in detail
how signal prediction arises from the negative group delay of the filter. Its
properties, including stability, are investigated theoretically, by numerical
simulations, and by application to a physiological signal. Possible control and
signal processing applications of this filter are discussed.


  In this paper, we prove the scattering for radial solutions to
energy-critical nonlinear Schr\"odinger equations with regular potentials in
defocusing case.


  We construct every finite-dimensional irreducible representation of the
simple Lie algebra of type $\mathsf{E}_{7}$ whose highest weight is a
nonnegative integer multiple of the dominant minuscule weight associated with
the type $\mathsf{E}_{7}$ root system. As a consequence, we obtain
constructions of each finite-dimensional irreducible representation of the
simple Lie algebra of type $\mathsf{E}_{6}$ whose highest weight is a
nonnegative integer linear combination of the two dominant minuscule
$\mathsf{E}$-weights. Our constructions are explicit in the sense that, if the
representing space is $d$-dimensional, then a weight basis is provided such
that all entries of the $d \times d$ representing matrices of the Chevalley
generators are obtained via explicit, non-recursive formulas. To effect this
work, we introduce what we call $\mathsf{E}_{6}$- and
$\mathsf{E}_{7}$-polyminuscule lattices that analogize certain lattices
associated with the famous special linear Lie algebra representation
constructions obtained by Gelfand and Tsetlin.