  Swarm robotic systems utilize collective behaviour to achieve goals that
might be too complex for a lone entity, but become attainable with localized
communication and collective decision making. In this paper, a behaviour-based
distributed approach to shape formation is proposed. Flocking into strategic
formations is observed in migratory birds and fish to avoid predators and also
for energy conservation. The formation is maintained throughout long periods
without collapsing and is advantageous for communicating within the flock.
Similar behaviour can be deployed in multi-agent systems to enhance
coordination within the swarm. Existing methods for formation control are
either dependent on the size and geometry of the formation or rely on
maintaining the formation with a single reference in the swarm (the leader).
These methods are not resilient to failure and involve a high degree of
deformation upon obstacle encounter before the shape is recovered again. To
improve the performance, artificial force-based interaction amongst the
entities of the swarm to maintain shape integrity while encountering obstacles
is elucidated.


  We investigate the variation of holographic complexity for two nearby target
states. Based on Nielsen's geometric approach, we find the variation only
depends on the end point of the optimal trajectory, a result which we designate
the first law of complexity. As an example, we examine the complexity=action
conjecture when the AdS vacuum is perturbed by a scalar field excitation, which
corresponds to a coherent state. Remarkably, the gravitational contributions
completely cancel and the final variation reduces to a boundary term coming
entirely from the scalar field action. Hence the null boundary of
Wheeler-DeWitt patch appears to act like the "end of the quantum circuit".


  Many recent works on 3D object detection have focused on designing neural
network architectures that can consume point cloud data. While these approaches
demonstrate encouraging performance, they are typically based on a single
modality and are unable to leverage information from other modalities, such as
a camera. Although a few approaches fuse data from different modalities, these
methods either use a complicated pipeline to process the modalities
sequentially, or perform late-fusion and are unable to learn interaction
between different modalities at early stages. In this work, we present
PointFusion and VoxelFusion: two simple yet effective early-fusion approaches
to combine the RGB and point cloud modalities, by leveraging the recently
introduced VoxelNet architecture. Evaluation on the KITTI dataset demonstrates
significant improvements in performance over approaches which only use point
cloud data. Furthermore, the proposed method provides results competitive with
the state-of-the-art multimodal algorithms, achieving top-2 ranking in five of
the six bird's eye view and 3D detection categories on the KITTI benchmark, by
using a simple single stage network.


  Video scene graph generation (VidSGG) aims to identify objects in visual
scenes and infer their relationships for a given video. It requires not only a
comprehensive understanding of each object scattered on the whole scene but
also a deep dive into their temporal motions and interactions. Inherently,
object pairs and their relationships enjoy spatial co-occurrence correlations
within each image and temporal consistency/transition correlations across
different images, which can serve as prior knowledge to facilitate VidSGG model
learning and inference. In this work, we propose a spatial-temporal
knowledge-embedded transformer (STKET) that incorporates the prior
spatial-temporal knowledge into the multi-head cross-attention mechanism to
learn more representative relationship representations. Specifically, we first
learn spatial co-occurrence and temporal transition correlations in a
statistical manner. Then, we design spatial and temporal knowledge-embedded
layers that introduce the multi-head cross-attention mechanism to fully explore
the interaction between visual representation and the knowledge to generate
spatial- and temporal-embedded representations, respectively. Finally, we
aggregate these representations for each subject-object pair to predict the
final semantic labels and their relationships. Extensive experiments show that
STKET outperforms current competing algorithms by a large margin, e.g.,
improving the mR@50 by 8.1%, 4.7%, and 2.1% on different settings over current
algorithms.


  Detecting the anomalous behavior of traffic is one of the important actions
for network operators. In this study, we applied term frequency - inverse
document frequency (TF-IDF), which is a popular method used in natural language
processing, to detect unusual behavior from network access logs. We mapped the
term and document concept to the port number and daily access history,
respectively, and calculated the TF-IDF. With this approach, we could obtain
ports frequently observed in fewer days compared to other port access
activities. Such access behaviors are not always malicious activities; however,
such information is a good indicator for starting a deeper analysis of traffic
behavior. Using a real-life dataset, we could detect two bot-oriented accesses
and one unique UDP traffic.


  One defines two ways of constructing rational maps derived from other
rational maps, in a characteristic-free context. The first introduces the
Newton complementary dual of a rational map. One main result is that this dual
preserves birationality and gives an involutional map of the Cremona group to
itself that restricts to the monomial Cremona subgroup and preserves de
Jonqui\`eres maps. In the monomial restriction this duality commutes with
taking inverse in the group, but is a not a group homomorphism. The second
construction is an iterative process to obtain rational maps in increasing
dimension. Starting with birational maps, it leads to rational maps whose
topological degree is under control. Making use of monoids, the resulting
construct is in fact birational if the original map is so. A variation of this
idea is considered in order to preserve properties of the base ideal, such as
Cohen--Macaulayness. Combining the two methods, one is able to produce explicit
infinite families of Cohen--Macaulay Cremona maps with prescribed dimension,
codimension and degree.


  We discuss recent advances in developing a mode-coupling theory of the glass
transition (MCT) of two-dimensional systems of active Brownian particles (ABP).
We specifically discuss the case of a single ABP tracer in a glass-forming
passive host suspension; a case that has recently been studied in experiments
on colloidal Janus particles. We employ event-driven Brownian dynamics (ED-BD)
computer simulations to test the ABP-MCT, and find good agreement between the
two for the MSD. The ED-BD simulation results also compare well to experimental
data, although a peculiar non-monotonic mapping of self-propulsion velocities
is required. The ABP-MCT predicts a specific self-propulsion dependence of the
Stokes-Einstein relation between the long-time diffusion coefficient and the
host-system viscosity that matches well the results from simulation. An
application of ABP-MCT within the integration-through transients (ITT)
framework to calculate the density-renormalized effective swim velocity of the
interacting ABP agrees qualitatively with the ED-BD simulation data at
densities close to the glass transition, and quantitatively for the full
density range only after the mapping of packing fractions employed for the
passive system.


  We study multihomogeneous spaces corresponding to ${\mathbb Z}^n$-graded
algebras over an algebraically closed field of characteristic 0 and their
relation with the description of $T$-varieties.


  Contrary to common belief, the requirement that supersymmetry exists and that
there are two Higgs doublets and no singlet at the electroweak energy scale
does not necessarily result in the minimal supersymmetric standard model
(MSSM). An interesting alternative is presented.


  Plasma-filled magnetospheres can extract energy from a spinning black hole
and provide the power source for a variety of observed astrophysical phenomena.
These magnetospheres are described by the highly nonlinear equations of
force-free electrodynamics, or FFE. Typically these equations can only be
solved numerically. In this paper we consider the FFE equations very near the
horizon of a maximally spinning black hole, where the energy extraction takes
place. Thanks to an enhanced conformal symmetry which appears in this
near-horizon region, we are able to analytically obtain several infinite
families of exact solutions of the full nonlinear equations.


  We have investigated spin and orbital magnetic moments of the Re 5d ion in
the double perovskites A2FeReO6 (A = Ba, Sr, Ca) by X-ray magnetic circular
dichroism (XMCD) at the Re L(2,3) edges. In these ferrimagnetic compounds an
unusually large negative spin and positive orbital magnetic moment at the Re
atoms was detected. The presence of a finite spin magnetic moment in a
'non-magnetic' double perovskite as observed in the double perovskite Sr2ScReO6
proves that Re has also a small, but finite intrinsic magnetic moment. We
further show for the examples of Ba and Ca that the usually neglected alkaline
earth ions undoubtedly also contribute to the magnetism in the ferrimagnetic
double perovskites.


  The Einstein-Vlasov-Fokker-Planck system describes the kinetic diffusion
dynamics of self-gravitating particles within the Einstein theory of general
relativity. We study the Cauchy problem for spatially homogeneous and isotropic
solutions and prove the existence of both global solutions and solutions that
blow-up in finite time depending on the size of certain functions of the
initial data. We also derive information on the large-time behavior of global
solutions and toward the singularity for solutions which blow-up in fine time.
Our results entail the existence of a phase of decelerated expansion followed
by a phase of accelerated expansion, in accordance with the physical
expectations in cosmology.


  The pyrochlore material Yb2Ti2O7 displays unexpected quasi-two-dimensional
(2D) magnetic correlations within a cubic lattice environment at low
temperatures, before entering an exotic disordered ground state below T=265mK.
We report neutron scattering measurements of the thermal evolution of the 2D
spin correlations in space and time. Short range three dimensional (3D) spin
correlations develop below 400 mK, accompanied by a suppression in the
quasi-elastic (QE) scattering below ~ 0.2 meV. These show a slowly fluctuating
ground state with spins correlated over short distances within a
kagome-triangular-kagome (KTK) stack along [111], which evolves to isolated
kagome spin-stars at higher temperatures. Furthermore, low-temperature specific
heat results indicate a sample dependence to the putative transition
temperature that is bounded by 265mK, which we discuss in the context of recent
mean field theoretical analysis.


  A new approach is developed to calculate temperature dependent Seebeck
coefficient of heavily doped systems by using Boltzmann transport theory and
electron density of states (DOS) obtained from density functional calculations.
This approach is applied to heavily doped La:STO with DOS from tetrahedral
method and Fermi energy using Fermi integrals. The calculated Seebeck
coefficient agrees with the experimental data nearly quantitatively, which
proved the accuracy of this approach. The influence of the Fermi energy and
asymmetry of DOS on the Seebeck coefficient is analyzed.


  A large body of research into semantic textual similarity has focused on
constructing state-of-the-art embeddings using sophisticated modelling, careful
choice of learning signals and many clever tricks. By contrast, little
attention has been devoted to similarity measures between these embeddings,
with cosine similarity being used unquestionably in the majority of cases. In
this work, we illustrate that for all common word vectors, cosine similarity is
essentially equivalent to the Pearson correlation coefficient, which provides
some justification for its use. We thoroughly characterise cases where Pearson
correlation (and thus cosine similarity) is unfit as similarity measure.
Importantly, we show that Pearson correlation is appropriate for some word
vectors but not others. When it is not appropriate, we illustrate how common
non-parametric rank correlation coefficients can be used instead to
significantly improve performance. We support our analysis with a series of
evaluations on word-level and sentence-level semantic textual similarity
benchmarks. On the latter, we show that even the simplest averaged word vectors
compared by rank correlation easily rival the strongest deep representations
compared by cosine similarity.


  We construct supersymmetric K field theories (i.e., theories with a
non-standard kinetic term) in 1+1 and 2+1 dimensions such that the bosonic
sector just consists of a nonstandard kinetic term plus a potential. Further,
we study the possibility of topological defect formation in these
supersymmetric models. Finally, we consider more general supersymmetric K field
theories where, again, topological defects exist in some cases.


  We study type II string vacua defined by torus compactifications accompanied
by T-duality twists. We realize the string vacua, specifically, by means of the
asymmetric orbifolding associated to the chiral reflections combined with a
shift, which are interpreted as describing the compactification on `T-folds'.
We discuss possible consistent actions of the chiral reflection on the
Ramond-sector of the world-sheet fermions, and explicitly construct
non-supersymmetric as well as supersymmetric vacua. Above all, we demonstrate a
simple realization of non-supersymmetric vacua with vanishing cosmological
constant at one loop. Our orbifold group is generated only by a single element,
which results in simpler models than those with such property known previously.


  We develop a density based topology optimization method for linear elasticity
based on the cut finite element method. More precisely, the design domain is
discretized using cut finite elements which allow complicated geometry to be
represented on a structured fixed background mesh. The geometry of the design
domain is allowed to cut through the background mesh in an arbitrary way and
certain stabilization terms are added in the vicinity of the cut boundary,
which guarantee stability of the method. Furthermore, in addition to standard
Dirichlet and Neumann conditions we consider interface conditions enabling
coupling of the design domain to parts of the structure for which the design is
already given. These given parts of the structure, called the nondesign domain
regions, typically represents parts of the geometry provided by the designer.
The nondesign domain regions may be discretized independently from the design
domains using for example parametric meshed finite elements or isogeometric
analysis. The interface and Dirichlet conditions are based on Nitsche's method
and are stable for the full range of density parameters. In particular we
obtain a traction-free Neumann condition in the limit when the density tends to
zero.


  In this paper we study a generalized Cahn-Hilliard equation which was
proposed by Gurtin. We prove the existence and uniqueness of a local-in-time
solution for a quasilinear version, that is, if the coefficients depend on the
solution and its gradient. Moreover we show that local solutions to the
corresponding semilinear problem exist globally as long as the physical
potential satisfies certain growth conditions. Finally we study the long-time
behaviour of the solutions and show that each solution converges to a
equilibrium as time tends to infinity.


  The TianQin space Gravitational Waves (GW) observatory will contain 3
geocentric and circularly orbiting spacecraft with an orbital radius of 10^5
km, to detect the GW in the milli-hertz frequency band. Each spacecraft pair
will establish a 1.7*10^5 km-long laser interferometer immersed in the solar
wind and the magnetospheric plasmas to measure the phase deviations induced by
the GW. GW detection requires a high-precision measurement of the laser phase.
The cumulative effects of the long distance and the periodic oscillations of
the plasma density may induce an additional phase noise. This paper aims to
model the plasma induced phase deviation of the inter-spacecraft laser signals,
using a realistic orbit simulator and the Space Weather Modeling Framework
(SWMF) model. Preliminary results show that the plasma density oscillation can
induce the phase deviations close to 2*10^-6 rad/Hz^1/2 or 0.3pm/Hz^1/2 in the
milli-hertz frequency band and it is within the error budget assigned to the
displacement noise of the interferometry. The amplitude spectrum density of
phases along three arms become more separated when the orbital plane is
parallel to the Sun-Earth line or during a magnetic storm. Finally, the
dependence of the phase deviations on the orbital radius is examined.


  In this paper we present two intrinsic algebraic definitions of tropical
variety motivated by the classical Zariski correspondence, one utilizing the
algebraic structure of the coordinate semiring of an affine supertropical
algebraic set, and the second based on the layered structure. We tie them to
tropical geometry, especially in connection with the dimension of an affine
variety.


  We discusses the charge asymmetry in $ B\rightarrow D\bar DK$ decays with an
invariant mass of the $D\bar D$ pair near the $\Psi(3770)$ resonance. Unlike $
\Psi (3770) $ decays in $ e^+e^- $ annihilation, in $B^+$ decays the
probability of $D^0\bar D^0$ production is almost three times higher than $D^+
D^-$. In $B^0$ decays, the ratio of these probabilities will be opposite. The
effect is explained by the fact that, in $B$ -meson decays, the $D\bar D$ pair
is produced in a superposition of isoscalar and isovector states, and only in
combination with $K$ -mesons the total state has $ 1/2 $ isospin. We present a
simple model in which the interference of the nonresonant isovector amplitude
with the resonant isoscalar amplitude explains the experimental data.


  It is generally believed that ensemble approaches, which combine multiple
algorithms or models, can outperform any single algorithm at machine learning
tasks, such as prediction. In this paper, we propose Bayesian convex and linear
aggregation approaches motivated by regression applications. We show that the
proposed approach is minimax optimal when the true data-generating model is a
convex or linear combination of models in the list. Moreover, the method can
adapt to sparsity structure in which certain models should receive zero
weights, and the method is tuning parameter free unlike competitors. More
generally, under an M-open view when the truth falls outside the space of all
convex/linear combinations, our theory suggests that the posterior measure
tends to concentrate on the best approximation of the truth at the minimax
rate. We illustrate the method through simulation studies and several
applications.


  Despite the low resistivity (~ 1 mohm cm), the metallic electrical transport
has not been commonly observed in the inverse spinel NiCo2O4, except in certain
epitaxial thin films. Previous studies have stressed the effect of valence
mixing and degree of spinel inversion on the electric conduction of NiCo2O4
films. In this work, we have studied the effect of microstructure by comparing
the NiCo2O4 epitaxial films grown on MgAl2O4 (111) and on Al2O3 (0001)
substrates. Although the optimal growth condition and the magnetic properties
are similar for the NiCo2O4/MgAl2O4 and the NiCo2O4/Al2O3, they show metallic
and semiconducting electrical transport respectively. Despite similar
temperature and field dependence of magnetization, the NiCo2O4/Al2O3 show much
larger magnetoresistance at low temperature. Post-growth annealing decreases
the resistivity of NiCo2O4/Al2O3, but the annealed films are still
semiconducting. The correlation between the structural correlation length and
the resistivity suggests that the microstructural disorder, generated by the
dramatic mismatch between the NiCo2O4 and Al2O3 crystal structures, may be the
origin of the absence of the metallic electrical transport in NiCo2O4. These
results reveal microstructural disorder as another key factor in controlling
the electrical transport of NiCo2O4, with potentially large magnetoresistance
for spintronics application.


  We use high spatial resolution stellar velocity maps from the Gemini GMOS
integral-field spectrograph (IFS) and wide-field velocity maps from the
McDonald Mitchell IFS to study the stellar velocity profiles and kinematic
misalignments from $\sim 200$ pc to $\sim 20$ kpc in 20 early-type galaxies
with stellar mass $M_* > 10^{11.7} M_\odot$ in the MASSIVE survey. While 80% of
the galaxies have low spins ($\lambda < 0.1$) and low rotational velocities ($<
50$ km/s) in both the central region and the main body, we find a diverse range
of velocity features and misalignment angles. For the 18 galaxies with
measurable central kinematic axes, 10 have well aligned kinematic axis and
photometric major axis, and the other 8 galaxies have misalignment angles that
are distributed quite evenly from $15^\circ$ to the maximal value of
$90^\circ$. There is a strong correlation between central kinematic
misalignment and galaxy spin, where all 4 galaxies with significant spins have
well aligned kinematic and photometric axes, but only 43% of the low-spin
galaxies are well aligned. The central and main-body kinematic axes within a
galaxy are not always aligned. When the two kinematic axes are aligned ($\sim
60$% of the cases), they are either also aligned with the photometric major
axis or orthogonal to it. We find 13 galaxies to also exhibit noticeable local
kinematic twists, and one galaxy to have a counter-rotating core. A diverse
assembly history consisting of multiple gas-poor mergers of a variety of
progenitor mass ratios and orbits is likely to be needed to account for the
predominance of low spins and the wide range of central and main-body velocity
features reported here for local massive ETGs.


  An iterative learning based economic model predictive controller (ILEMPC) is
proposed for repetitive tasks in this paper. Compared with existing works, the
initial feasible trajectory of the proposed ILEMPC is not restricted to be
convergent to an equilibrium so it can handle various types of control
objectives: stabilization, tracking a periodic trajectory and even pure
economic optimization. The controller can learn from the previous closed-loop
trajectory, resulting in a performance which is guaranteed to be no worse than
the previous one. Under some standard assumptions in model predictive control,
we show that recursive feasibility is ensured. Furthermore, for stabilization
problem, the convergence of each learned trajectory and the learning process
are established provided the initial trajectory is convergent. Numerical
examples show that the proposed control strategy works well for different types
of control tasks and systems.


  Being capable of sensing and behavioral adaptation in line with their
changing environments, cognitive cyber-physical systems (CCPSs) are the new
form of applications in future wireless networks. With the advancement of the
machine learning algorithms, the transmission scheme providing the best
performance can be utilized to sustain a reliable network of CCPS agents
equipped with self-decision mechanisms, where the interactions between each
agent are modeled in terms of service quality, security, and cost dimensions.
In this work, first, we provide network utility as a reliability metric, which
is a weighted sum of the individual utility values of the CCPS agents. The
individual utilities are calculated by mixing the quality of service (QoS),
security, and cost dimensions with the proportions determined by the
individualized user requirements. By changing the proportions, the CCPS network
can be tuned for different applications of next-generation wireless networks.
Then, we propose a secure transmission policy selection (STPS) mechanism that
maximizes the network utility by using the Markov-decision process (MDP). In
STPS, the CCPS network jointly selects the best performing physical layer
security policy and the parameters of the selected secure transmission policy
to adapt to the changing environmental effects. The proposed STPS is realized
by reinforcement learning (RL), considering its real-time decision mechanism
where agents can decide automatically the best utility providing policy in an
altering environment.


  We establish Thom's jet transversality theorem for regular maps from an
affine algebraic manifold to an algebraic manifold satisfying a suitable
flexibility condition. It can be considered as the algebraic version of
Forstneri\v{c}'s jet transversality theorem for holomorphic maps from a Stein
manifold to an Oka manifold. Our jet transversality theorem implies genericity
theorems for regular maps of maximal ranks. As an application, it follows that
every connected compact locally flexible manifold is the image of a holomorphic
submersion from an affine space. We also show that every algebraically
degenerate subvariety of codimension at least two in a locally flexible
manifold has an Oka complement.


  The collinear hydrogen exchange reaction is a paradigm system for
understanding chemical reactions. It is the simplest imaginable atomic system
with $2$ degrees of freedom modeling a chemical reaction, yet it exhibits
behaviour that is still not well understood - the reaction rate decreases as a
function of energy beyond a critical value. Using lobe dynamics we show how
invariant manifolds of unstable periodic orbits guide trajectories in phase
space. From the structure of the invariant manifolds we deduce that
insufficient transfer of energy between the degrees of freedom causes a
reaction rate decrease. In physical terms this corresponds to the free hydrogen
atom repelling the whole molecule instead of only one atom from the molecule.
We further derive upper and lower bounds of the reaction rate, which are
desirable for practical reasons.


  We present N-body simulations of star clusters that initially evolve within a
strong compressive tidal field and then transition into extensive tidal fields
of varying strengths. While subject to compressive tides, clusters can undergo
significant heating due to two-body interactions and mass loss due to stellar
evolution. When the cluster transitions into an extensive tidal field it is
super-virialized, which leads to a rapid expansion and significant mass loss
before the cluster reaches virial equilibrium. After the transition, clusters
are significantly less massive, more extended and therefore more tidally
filling than clusters which have spent their entire lifetime in a similar
extensive tidal field.


  The Pentagon Operator Product Expansion represents polygonal Wilson loops in
planar $\mathcal{N}=4$ super Yang-Mills in terms of a series of flux tube
excitations for finite coupling. We demonstrate how to re-sum this series at
the one loop level for the hexagonal Wilson loop dual to the six-point MHV
amplitude. By summing over a series of effective excitations we find
expressions which integrate to logarithms and polylogarithms, reproducing the
known one-loop result.


  Reactive transport in porous media plays a pivotal role in subsurface
reservoir processes, influencing fluid properties and geochemical
characteristics. However, coupling fluid flow and transport with geochemical
reactions is computationally intensive, requiring geochemical calculations at
each grid cell and each time step within a discretized simulation domain.
Although recent advancements have integrated machine learning techniques as
surrogates for geochemical simulations, ensuring computational efficiency and
accuracy remains a challenge. This chapter investigates machine learning models
as replacements for a geochemical module in a reactive transport in porous
media simulation. We test this approach on a well-documented cation exchange
problem. While the surrogate models excel in isolated predictions, they fall
short in rollout predictions over successive time steps. By introducing
modifications, including physics-based constraints and tailored dataset
generation strategies, we show that machine learning surrogates can achieve
accurate rollout predictions. Our findings emphasize that, when judiciously
designed, machine learning surrogates can substantially expedite the cation
exchange problem without compromising accuracy, offering significant potential
for a range of reactive transport applications.


  We have simulated the ground states of quantum harmonic oscillators driven
either by constant forces of different magnitudes or time-dependent driving
forces. The expectation values of position for various combinations of mass,
natural angular frequency, and the coupling constant $\lambda$ were calculated
for both driving modes. For constant forcing, coherent states were obtained.
The results for both forcing scenarios match the theoretically expected values
almost exactly. For the simulations, the Metropolis algorithm was implemented
on a discrete time lattice to evaluate the imaginary time path integral of the
systems.


  The Gemini Planet Imager is a newly commissioned facility instrument designed
to measure the near-infrared spectra of young extrasolar planets in the solar
neighborhood and obtain imaging polarimetry of circumstellar disks. GPI's
science instrument is an integral field spectrograph that utilizes a HAWAII-2RG
detector with a SIDECAR ASIC readout system. This paper describes the detector
characterization and calibrations performed by the GPI Data Reduction Pipeline
to compensate for effects including bad/hot/cold pixels, persistence,
non-linearity, vibration induced microphonics and correlated read noise.


  In multi-stage radiotherapy, a patient is treated in several stages separated
by weeks or months. This regimen has been motivated mostly by radiobiological
considerations, but also provides an approach to reduce normal tissue dose by
exploiting tumor shrinkage. The paper considers the optimal design of
multi-stage treatments, motivated by the clinical management of large liver
tumors for which normal liver dose constraints prohibit the administration of
an ablative radiation dose in a single treatment.
  We introduce a dynamic tumor model that incorporates three factors: radiation
induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of
multi-stage radiotherapy is formulated as a mathematical optimization problem
in which the total dose to the liver is minimized, subject to delivering the
prescribed dose to the tumor. Based on the model, we gain insight into the
optimal administration of radiation over time, i.e. the optimal treatment gaps
and dose levels.
  We analyze treatments consisting of two stages in detail. The analysis
confirms the intuition that the second stage should be delivered just before
the tumor size reaches a minimum and repopulation overcompensates shrinking.
Furthermore, it was found that, for a large range of model parameters,
approximately one third of the dose should be delivered in the first stage. The
projected benefit of multi-stage treatments depends on model assumptions.
However, the model predicts large liver dose reductions by more than a factor
of two for plausible model parameters.
  The analysis of the tumor model suggests that substantial reduction in normal
tissue dose can be achieved by exploiting tumor shrinkage via an optimal design
of multi-stage treatments. This suggests taking a fresh look at multi-stage
radiotherapy for selected disease sites where substantial tumor regression
translates into reduced target volumes.


  The dependence of the Josephson Plasma Resonance (JPR) frequency in heavily
underdoped Bi2Sr2CaCu2O8+\delta on temperature and controlled pointlike
disorder, introduced by high-energy electron irradiation, is cross-correlated
and compared to the behavior of the ab-plane penetration depth. It is found
that the zero temperature plasma frequency, representative of the superfluid
component of the c-axis spectral weight, decreases proportionally with T_c when
the disorder is increased. The temperature dependence of the JPR frequency is
the same for all disorder levels, including pristine crystals. The reduction of
the c-axis superfluid density as function of disorder is accounted for by
pair-breaking induced by impurity scattering in the CuO2 planes, rather than by
quantum fluctuations of the superconducting phase. The reduction of the c-axis
superfluid density as function of temperature follows a T^{2}--law and is
accounted for by quasi-particle hopping through impurity induced interlayer
states.


  Hierarchical Temporal Memory (HTM) is a biologically inspired machine
intelligence technology that mimics the architecture and processes of the
neocortex. In this white paper we describe how to encode data as Sparse
Distributed Representations (SDRs) for use in HTM systems. We explain several
existing encoders, which are available through the open source project called
NuPIC, and we discuss requirements for creating encoders for new types of data.


  Motivated by the torus stability problem, in this work we study K\"ahler
metrics with almost non-negative scalar curvature on complex torus. We prove
that after passing to a subsequence, non-collapsing sequence of K\"ahler
metrics with almost non-negative scalar curvature will converge to flat torus
weakly.


  Jet fragmentation functions are measured for the first time in proton-proton
collisions for charged pions, kaons, and protons within jets recoiling against
a $Z$ boson. The charged-hadron distributions are studied longitudinally and
transversely to the jet direction for jets with transverse momentum 20 $<
p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The
data sample was collected with the LHCb experiment at a center-of-mass energy
of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple
differential distributions as a function of the hadron longitudinal momentum
fraction, hadron transverse momentum, and jet transverse momentum are also
measured for the first time. This helps constrain transverse-momentum-dependent
fragmentation functions. Differences in the shapes and magnitudes of the
measured distributions for the different hadron species provide insights into
the hadronization process for jets predominantly initiated by light quarks.


  Spontaneous synchronization is a remarkable collective effect observed in
nature, whereby a population of oscillating units, which have diverse natural
frequencies and are in weak interaction with one another, evolves to
spontaneously exhibit collective oscillations at a common frequency. The
Kuramoto model provides the basic analytical framework to study spontaneous
synchronization. The model comprises limit-cycle oscillators with distributed
natural frequencies interacting through a mean-field coupling. Although more
than forty years have passed since its introduction, the model continues to
occupy the centre-stage of research in the field of non-linear dynamics, and is
also widely applied to model diverse physical situations. In this brief review,
starting with a derivation of the Kuramoto model and the synchronization
phenomenon it exhibits, we summarize recent results on the study of a
generalized Kuramoto model that includes inertial effects and stochastic noise.
We describe the dynamics of the generalized model from a different yet a rather
useful perspective, namely, that of long-range interacting systems driven out
of equilibrium by quenched disordered external torques. A system is said to be
long-range interacting if the inter-particle potential decays slowly as a
function of distance. Using tools of statistical physics, we highlight the
equilibrium and nonequilibrium aspects of the dynamics of the generalized
Kuramoto model, and uncover a rather rich and complex phase diagram that it
exhibits, which underlines the basic theme of intriguing emergent phenomena
that are exhibited by many-body complex systems.


  Recent convolutional object detectors exploit multi-scale feature
representations added with top-down pathway in order to detect objects at
different scales and learn stronger semantic feature responses. In general,
during the top-down feature propagation, the coarser feature maps are upsampled
to be combined with the features forwarded from bottom-up pathway, and the
combined stronger semantic features are inputs of detector's headers. However,
simple interpolation methods (e.g. nearest neighbor and bilinear) are still
used for increasing feature resolutions although they cause noisy and blurred
features. In this paper, we propose a novel generator for super-resolving
features of the convolutional object detectors. To achieve this, we first
design super-resolved feature GAN (SRF-GAN) consisting of a detection-based
generator and a feature patch discriminator. In addition, we present SRF-GAN
losses for generating the high quality of super-resolved features and improving
detection accuracy together. Our SRF generator can substitute for the
traditional interpolation methods, and easily fine-tuned combined with other
conventional detectors. To prove this, we have implemented our SRF-GAN by using
the several recent one-stage and two-stage detectors, and improved detection
accuracy over those detectors. Code is available at
https://github.com/SHLee-cv/SRF-GAN.


  The shot noise of a one-dimensional wire interrupted by two barriers shows
interesting features related to the interplay between Coulomb blockade effects,
Luttinger correlations and discrete excitations. At small bias the Fano factor
reaches the lowest attainable value, 1/2, irrespective of the ratio of the two
junction resistances. At larger voltages this asymmetry is power-law
renormalized by the interaction strength. We discuss how the measurement of
current and these features of the noise allow to extract the Luttinger liquid
parameter.


  We present a dielectric study on the dynamics of supercooled glycerol during
crystallization. We explore the transformation into a solid phase in real time
by monitoring the temporal evolution of the amplitude of the dielectric signal.
Neither the initial nucleation or the crystal growth influence the liquid
dynamics visibly. For one of the samples studied, a tiny fraction of glycerol
remained in the disordered state after the end of the transition. We examined
the nature of the alpha relaxation in this frustrated crystal and find that it
is virtually identical to the bulk dynamics. In addition to that, we have found
no evidence that supercooled glycerol transforms into a peculiar phase where
either a new solid amorphous state or nano-crystals dispersed in a liquid
matrix are formed.


  We suggest an N=1 Lagrangian flowing in the infra-red to the N=2 rank one
superconformal field theory with E_6 flavor symmetry. We utilize this
description to compute several supersymmetric partition functions.


  We consider the tensor product of the completely depolarising channel on
$d\times d$ matrices with the map of Schur multiplication by a $k \times k$
correlation matrix and characterise, via matrix theory methods, when such a map
is a mixed (random) unitary channel. When $d=1$, this recovers a result of
O'Meara and Pereira, and for larger $d$ is equivalent to a result of Haagerup
and Musat that was originally obtained via the theory of factorisation through
von Neumann algebras. We obtain a bound on the distance between a given
correlation matrix for which this tensor product is nearly mixed unitary and a
correlation matrix for which such a map is exactly mixed unitary. This bound
allows us to give an elementary proof of another result of Haagerup and Musat
about the closure of such correlation matrices without appealing to the theory
of von Neumann algebras.


  We discuss discrimination of the scattering mechanisms on the basis of
functional dependencies of the large-$t$ elastic scattering suggested by the
recent data from the TOTEM experiment. It is shown that Orear exponent is in a
better agreement with the data than the power-like dependence used by the
TOTEM. This implies that the collective dynamics is dominating over the
point-like mechanism related to the scattering of the proton constituents.


  In this paper we continue the study of groups of trace class and consider in
particular the case of semi-direct products. One of the highlights is the
theorem saying that the semi-direct product of a semisimple Lie group G and its
Lie algebra is a trace class group if and only if G is compact.


  The structural and electronic properties in common anion (GaSb)_1/(InSb)_1
and common cation (InAs)_1/(InSb)_1 [111] ordered superlattices have been
determined using the local density total energy full potential linearized
augmented plane wave method. The influence of the ordering direction, strain
conditions and atomic substitution on the electronic properties of
technological and experimental interest (such as energy band-gaps and charge
carrier localization in the different sublattices) were determined. The results
show an appreciable energy band-gap narrowing compared to the band-gap averaged
over the constituent binaries, either in [001] ordered structures or (more
markedly) in the [111] systems; moreover energy band-gaps show an increasing
trend as the substrate lattice parameter is decreased. Finally, the systems
examined offer interesting opportunities for band-gap tuning as a function of
the growth condition (about 0.7 eV in (GaSb)_1/(InSb)_1 and 0.3 eV in
(InAs)_1/(InSb)_1).


  This paper presents a unified approach for localizing some relevant graph
topological indices via majorization techniques. Through this method, old and
new bounds are derived and numerical examples are provided, showing how former
results in the literature could be improved.


  Let \pi be a unitary cuspidal automorphic representation for GL(n) over a
number field. We establish upper bounds on the number of Hecke eigenvalues of
\pi equal to a fixed complex number. For GL(2), we also determine upper bounds
on the number of Hecke eigenvalues with absolute value equal to a fixed number
\gamma; in the case \gamma=0, this answers a question of Serre. These bounds
are then improved upon by restricting to non-dihedral representations. Finally,
we obtain analogous bounds for a family of cuspidal automorphic representations
for GL(3).


  Let $(X, \Delta)$ be a klt threefold pair with nef anti-log canonical bundle
$-(K_X+\Delta)$. We show that $\kappa(X, -(K_X+\Delta))\geq 0$. To do so, we
prove a more general equivariant non-vanishing result for anti-log canonical
bundles, which is valid in any dimension.


  We have carried out an observation of the CCS ($J_{N}$=2$_{1}-$1$_{0}$) line
with the Very Large Array in its D-configuration toward a protostellar core
L483 (IRAS~18140$-$0440). This is a candidate source of the newly found
carbon-chain rich environment called "Warm-Carbon-Chain-Chemistry (WCCC)",
according to the previous observations of carbon-chain molecules. The CCS
distribution in L483 is found to consist of two clumps aligned in the
northwest-southeast direction, well tracing the CCS ridge observed with the
single-dish radio telescope. The most remarkable feature is that CCS is
depleted at the core center. Such a CCS distribution with the central hole is
consistent with those of previously observed prestellar and protostellar cores,
but it is rather unexpected for L483. This is because the distribution of CS,
which is usually similar to that of CCS, is centrally peaked. Our results imply
that the CCS ($J_{N}$=2$_{1}-$1$_{0}$) line would selectively trace the outer
cold envelope in the chemically less evolved phase that is seriously resolved
out with the interferometric observation. Thus, it is most likely that the high
abundance of CCS in L483 relative to the other WCCC sources is not due to the
activity of the protostar, although it would be related to its younger chemical
evolutionary stage, or a short timescale of the prestellar phase.


  Markov processes are shown to be consistent with metastable states seen in
pulsar phenomena, including intensity nulling, pulse-shape mode changes,
subpulse drift rates, spindown rates, and X-ray emission, based on the
typically broad and monotonic distributions of state lifetimes. Markovianity
implies a nonlinear magnetospheric system in which state changes occur
stochastically, corresponding to transitions between local minima in an
effective potential. State durations (though not transition times) are thus
largely decoupled from the characteristic time scales of various magnetospheric
processes. Dyadic states are common but some objects show at least four states
with some transitions forbidden. Another case is the long-term intermittent
pulsar B1931+24 that has binary radio-emission and torque states with wide, but
non-monotonic duration distributions. It also shows a quasi-period of $38\pm5$
days in a 13-yr time sequence, suggesting stochastic resonance in a Markov
system with a forcing function that could be strictly periodic or
quasi-periodic. Nonlinear phenomena are associated with time-dependent activity
in the acceleration region near each magnetic polar cap. The polar-cap diode is
altered by feedback from the outer magnetosphere and by return currents from an
equatorial disk that may also cause the neutron star to episodically charge and
discharge. Orbital perturbations in the disk provide a natural periodicity for
the forcing function in the stochastic resonance interpretation of B1931+24.
Disk dynamics may introduce additional time scales in observed phenomena.
Future work can test the Markov interpretation, identify which pulsar types
have a propensity for state changes, and clarify the role of selection effects.


  It is developed the theory of the boundary behavior of homeomorphic solutions
of the Beltrami equations ${\bar{\partial}}f=\mu\,{\partial}f$ of the Sobolev
class $W^{1,1}_{\rm loc}$ with respect to prime ends of domains. On this basis,
under certain conditions on the complex coefficient ${\mu}$, it is proved the
existence of regular solutions of its Dirichlet problem in arbitrary simply
connected domains and pseudoregular as well as multivalent solutions in
arbitrary finitely connected domains with continuous boundary data in terms of
prime ends.


  Semantic labeling of coronary arterial segments in invasive coronary
angiography (ICA) is important for automated assessment and report generation
of coronary artery stenosis in the computer-aided diagnosis of coronary artery
disease (CAD). Inspired by the training procedure of interventional
cardiologists for interpreting the structure of coronary arteries, we propose
an association graph-based graph matching network (AGMN) for coronary arterial
semantic labeling. We first extract the vascular tree from invasive coronary
angiography (ICA) and convert it into multiple individual graphs. Then, an
association graph is constructed from two individual graphs where each vertex
represents the relationship between two arterial segments. Using the
association graph, the AGMN extracts the vertex features by the embedding
module, aggregates the features from adjacent vertices and edges by graph
convolution network, and decodes the features to generate the semantic mappings
between arteries. By learning the mapping of arterial branches between two
individual graphs, the unlabeled arterial segments are classified by the
labeled segments to achieve semantic labeling. A dataset containing 263 ICAs
was employed to train and validate the proposed model, and a five-fold
cross-validation scheme was performed. Our AGMN model achieved an average
accuracy of 0.8264, an average precision of 0.8276, an average recall of
0.8264, and an average F1-score of 0.8262, which significantly outperformed
existing coronary artery semantic labeling methods. In conclusion, we have
developed and validated a new algorithm with high accuracy, interpretability,
and robustness for coronary artery semantic labeling on ICAs.


  Coherent perfect absorption (CPA) describes the absence of all outgoing modes
from a lossy resonator, driven by lossless incoming modes. Here, we show that
for nanoresonators that also exhibit radiative losses, e.g. plasmonic
nanoantennas, a generalized version of CPA (gCPA) can be applied. In gCPA
outgoing modes are sup-pressed only for a subset of (guided plasmonic) modes
while other (radiative) modes are treated as additional loss channels - a
situation typically referred to as perfect impedance matching. Here we make use
of gCPA to show how to achieve perfect impedance matching between a single
nanowire plasmonic waveguide and a plasmonic nanoantenna. Antennas with both
radiant and subradiant characteristics are considered. We further demonstrate
potential applications in background-free sensing.


  The iteratively reweighted l1 algorithm is a widely used method for solving
various regularization problems, which generally minimize a differentiable loss
function combined with a nonconvex regularizer to induce sparsity in the
solution. However, the convergence and the complexity of iteratively reweighted
l1 algorithms is generally difficult to analyze, especially for non-Lipschitz
differentiable regularizers such as nonconvex lp norm regularization. In this
paper, we propose, analyze and test a reweighted l1 algorithm combined with the
extrapolation technique under the assumption of Kurdyka-Lojasiewicz (KL)
property on the objective. Unlike existing iteratively reweighted l1 algorithms
with extrapolation, our method does not require the Lipschitz differentiability
on the regularizers nor the smoothing parameters in the weights bounded away
from zero. We show the proposed algorithm converges uniquely to a stationary
point of the regularization problem and has local linear complexity--a much
stronger result than existing ones. Our numerical experiments show the
efficiency of our proposed method.


  In this paper we outline some mathematical questions that emerge from trying
to "turn the scientific method into math". Specifically, we consider the
problem of experiment planning (choosing the best experiment to do next) in
explicit probabilistic and information theoretic terms. We formulate this as an
information measurement problem; that is, we seek a rigorous definition of an
information metric to measure the likely information yield of an experiment,
such that maximizing the information metric will indeed reliably choose the
best experiment to perform. We present the surprising result that defining the
metric purely in terms of prediction power on observable variables yields a
metric that can converge to the classical mutual information measuring how
informative the experimental observation is about an underlying hidden
variable. We show how the expectation potential information metric can compute
the "information rate" of an experiment as well its total possible yield, and
the information value of experimental controls. To illustrate the utility of
these concepts for guiding fundamental scientific inquiry, we present an
extensive case study (RoboMendel) applying these metrics to propose sequences
of experiments for discovering the basic principles of genetics.


  We investigate the constant-roll inflation and the evolution of primordial
black holes (PBHs) with Barrow holographic dark energy (BHDE). Using the
modified Friedmann equation and the constant-roll condition in BHDE model, we
calculate the constant-roll parameters, the scalar spectral index parameter and
the tensor-to-scalar ratio with the chaotic potential $V_{0}\phi^{n}$. Then, we
show that a suitable value of the power exponent is $n=1$ by using the Planck
2018 data. Considering the accretion process and the evaporation due to Hawking
radiation, we discuss the evolution of PBHs in BHDE model and obtain that the
PBHs mass is in the mass window of PBHs.


  We give a formulation for descent of level structures on deformations of
formal groups, and study the compatibility between the descent and a norm
construction. Under this framework, we generalize Ando's construction of
H-infinity complex orientations for Morava E-theories associated to Honda
formal group laws over F_p. We show the existence and uniqueness of such an
orientation for any Morava E-theory associated to a formal group law over an
algebraic extension of F_p and, in particular, orientations for a family of
elliptic cohomology theories. These orientations correspond to coordinates on
deformations of formal groups which are compatible with norm maps along
descent.


  The one-loop corrections to the bottomonium mass spectrum due to the finite
charm mass are evaluated in the framework of the relativistic quark model. The
obtained corrections are compared with the results of perturbative QCD.


  The renormalization of the effective field theories (EFTs) in many-body
systems is the most pressing and challenging problem in modern nuclear ab
initio calculation. For general non-relativistic EFTs, we prove that the
renormalization group (RG) invariance can be achieved if and only if all
single-particle momenta are regulated with a universal cutoff \Lambda. For a
numerical demonstration, we construct a series of N^{2}LO chiral forces with
\Lambda varying from 250 MeV to 400 MeV. With all low energy constants fixed in
two- and three-nucleon systems, we reproduce the experimental binding energies
of ^{4}He and ^{16}O nearly independently of \Lambda. In contrast, all recent
nuclear EFT constructions regulate the relative momenta for Galilean
invariance, thus inherently break the RG invariance. This explains the
unpleasantly strong cutoff-dependences observed in recent ab initio
calculations. Our method can also be used to build RG-invariant EFTs with
non-perturbative interactions.


  Text-to-speech (TTS) acoustic models map linguistic features into an acoustic
representation out of which an audible waveform is generated. The latest and
most natural TTS systems build a direct mapping between linguistic and waveform
domains, like SampleRNN. This way, possible signal naturalness losses are
avoided as intermediate acoustic representations are discarded. Another
important dimension of study apart from naturalness is their adaptability to
generate voice from new speakers that were unseen during training. In this
paper we first propose the use of problem-agnostic speech embeddings in a
multi-speaker acoustic model for TTS based on SampleRNN. This way we feed the
acoustic model with speaker acoustically dependent representations that enrich
the waveform generation more than discrete embeddings unrelated to these
factors. Our first results suggest that the proposed embeddings lead to better
quality voices than those obtained with discrete embeddings. Furthermore, as we
can use any speech segment as an encoded representation during inference, the
model is capable to generalize to new speaker identities without retraining the
network. We finally show that, with a small increase of speech duration in the
embedding extractor, we dramatically reduce the spectral distortion to close
the gap towards the target identities.


  Gravitational waves from binary black holes have the potential to yield
information on both of the intrinsic parameters that characterize the compact
objects: their masses and spins. While the component masses are usually
resolvable, the component spins have proven difficult to measure. This
limitation stems in great part from our choice to inquire about the spins of
the most and least massive objects in each binary, a question that becomes
ill-defined when the masses are equal. In this paper we show that one can ask a
different question of the data: what are the spins of the objects with the
highest and lowest dimensionless spins in the binary? We show that this can
significantly improve estimates of the individual spins, especially for binary
systems with comparable masses. When applying this parameterization to the
first 13 gravitational-wave events detected by the LIGO-Virgo collaboration
(LVC), we find that the highest-spinning object is constrained to have nonzero
spin for most sources and to have significant support at the Kerr limit for
GW151226 and GW170729. A joint analysis of all the confident binary black hole
detections by the LVC finds that, unlike with the traditional parametrization,
the distribution of spin magnitude for the highest-spinning object has
negligible support at zero spin. Regardless of the parameterization used, the
configuration where all of the spins in the population are aligned with the
orbital angular momentum is excluded from the 90% credible interval for the
first ten events and from the 99% credible interval for all current confident
detections.


  The article "Interpolation and SAT-Based Model Checking" (McMillan, 2003)
describes a formal-verification algorithm, which was originally devised to
verify safety properties of finite-state transition systems. It derives
interpolants from unsatisfiable BMC queries and collects them to construct an
overapproximation of the set of reachable states. Although 20 years old, the
algorithm is still state-of-the-art in hardware model checking. Unlike other
formal-verification algorithms, such as k-induction or PDR, which have been
extended to handle infinite-state systems and investigated for program
analysis, McMillan's interpolation-based model-checking algorithm from 2003 has
not been used to verify programs so far. Our contribution is to close this
significant, two decades old gap in knowledge by adopting the algorithm to
software verification. We implemented it in the verification framework
CPAchecker and evaluated the implementation against other state-of-the-art
software-verification techniques on the largest publicly available benchmark
suite of C safety-verification tasks. The evaluation demonstrates that
McMillan's interpolation-based model-checking algorithm from 2003 is
competitive among other algorithms in terms of both the number of solved
verification tasks and the run-time efficiency. Our results are important for
the area of software verification, because researchers and developers now have
one more approach to choose from.


  This article studies the behaviour under liaison of the deficiency modules of
schemes that are not assumed to be Cohen-Macaulay. Our study uses in particular
a generalization of Serre duality, and gives a satisfactory description of this
behaviour in dimension at most three. On the way we show other properties of
linked schemes.


  Training and deploying the large language models requires a large mount of
computational resource because the language models contain billions of
parameters and the text has thousands of tokens. Another problem is that the
large language models are static. They are fixed after the training process. To
tackle these issues, in this paper, we propose to train and deploy the dynamic
large language model on blockchains, which have high computation performance
and are distributed across a network of computers. A blockchain is a secure,
decentralized, and transparent system that allows for the creation of a
tamper-proof ledger for transactions without the need for intermediaries. The
dynamic large language models can continuously learn from the user input after
the training process. Our method provides a new way to develop the large
language models and also sheds a light on the next generation artificial
intelligence systems.


  In this paper, we propose cylindrical distributions obtained by combining the
sine-skewed von Mises distribution (circular part) with the Weibull
distribution (linear part). This new model, the WeiSSVM, enjoys numerous
advantages: simple normalizing constant and hence very tractable density,
parameter-parsimony and interpretability, good circular-linear dependence
structure, easy random number generation thanks to known marginal/conditional
distributions, flexibility illustrated via excellent fitting abilities, and a
straightforward extension to the case of directional-linear data. Inferential
issues, such as independence testing, circular-linear respectively
linear-circular regression, can easily be tackled with our model, which we
apply on two real data sets. We conclude the paper by discussing future
applications of our model.


  A variety of heavy fermion superconductors, such as UCoGe, UGe$_2$, and URhGe
exhibit a striking coexistence of bulk ferromagnetism and superconductivity. In
these systems, the magnetic moment decreases with pressure, and vanishes at a
ferromagnetic quantum critical point (qcp). Remarkably, the superconductivity
in UCoGe varies smoothly with pressure across the qcp and exists in both the
ferromagnetic and paramagnetic regimes. We argue that in UCoGe, spin-orbit
interactions stabilize a time-reversal invariant odd-parity superconductor in
the high pressure paramagnetic regime. Based on a simple phenomenological
model, we predict that the transition from the paramagnetic normal state to the
phase where superconductivity and ferromagnetism coexist, is a first-order
transition.


  The ability of photonic crystal waveguides (PCWs) to confine and slow down
light makes them an ideal component to enhance the performance of various
photonic devices, such as optical modulators or sensors. However, the
integration of PCWs in photonic applications poses design challenges, most
notably, engineering the PCW mode dispersion and creating efficient coupling
devices. Here, we solve these challenges with photonic inverse design, and
experimentally demonstrate a slow-light PCW optical phased array (OPA) with a
wide steering range. Even and odd mode PCWs are engineered for a group index of
25, over a bandwidth of 20nm and 12nm, respectively. Additionally, for both PCW
designs, we create strip waveguide couplers and free-space vertical couplers.
Finally, also relying on inverse design, the radiative losses of the PCW are
engineered, allowing us to construct OPAs with a 20{\deg} steering range in a
20nm bandwidth.


  Energy in today's short-range wireless communication is mostly spent on the
analog- and digital hardware rather than on radiated power. Hence, purely
information-theoretic considerations fail to achieve the lowest energy per
information bit and the optimization process must carefully consider the
overall transceiver. In this paper, we propose to perform cross-layer
optimization, based on an energy-aware rate adaptation scheme combined with a
physical layer that is able to properly adjust its processing effort to the
data rate and the channel conditions to minimize the energy consumption per
information bit. This energy proportional behavior is enabled by extending the
classical system modes with additional configuration parameters at the various
layers. Fine grained models of the power consumption of the hardware are
developed to provide awareness of the physical layer capabilities to the medium
access control layer. The joint application of the proposed energy-aware rate
adaptation and modifications to the physical layer of an IEEE 802.11n system,
improves energy-efficiency (averaged over many noise and channel realizations)
in all considered scenarios by up to 44%.


  It is hoped that quantum computers will offer advantages over classical
computers for combinatorial optimization. Here, we introduce a feedback-based
strategy for quantum optimization, where the results of qubit measurements are
used to constructively assign values to quantum circuit parameters. We show
that this procedure results in an estimate of the combinatorial optimization
problem solution that improves monotonically with the depth of the quantum
circuit. Importantly, the measurement-based feedback enables approximate
solutions to the combinatorial optimization problem without the need for any
classical optimization effort, as would be required for the quantum approximate
optimization algorithm (QAOA). We experimentally demonstrate this
feedback-based protocol on a superconducting quantum processor for the
graph-partitioning problem MaxCut, and present a series of numerical analyses
that further investigate the protocol's performance.


  Although the sample of exoplanets in binaries has been greatly expanded, the
sample heterogeneity and observational bias are obstacles toward a clear figure
of exoplanet demographics in the binary environment. To overcome the obstacles,
we conduct a statistical study that focuses on S-type planetary systems
detected by the Radial Velocity method. We try to account for observational
biases by estimating, from available RV data, planet detection efficiencies for
each individual system. Our main results are as follows: (1) Single (multiple)
planetary systems are mostly found in close (wide) binaries with separation
aB<(>)100-300 AU. (2) In binaries, single and multiple-planet systems are
similar in 1-D distributions of mass and period as well as eccentricity (in
contrast to the "eccentricity dichotomy" found in single-star systems) but
different in the 2-D period-mass diagram. Specifically, there is a
rectangular-shaped gap in the period-mass diagram of single-planet systems but
not for multiples. This gap also depends on binary separation and is more
prominent in close binaries. (3) There is a rising upper envelope in the
period-mass diagram for planets in wide binaries as well as in single stars but
not in close binaries. More specifically, there is a population of massive
short period planets in close binaries but almost absent in wide binaries or
single stars. We suggest that enhanced planetary migration, collision, and /or
ejection in close binaries could be the potential underlying explanation for
these three features.


  We continue to present the results of the Byurakan Narrow Band Imaging Survey
(BNBIS). The main goal of this survey is to search for Herbig-Haro (HH) objects
and jets in Galactic dark clouds. In this work we present the results of the
search in the vicinity of infrared sources that are bright in the WISE survey
and embedded in the dark clouds. The survey is performed with the 1 m Schmidt
telescope of Byurakan Observatory, lately equipped with a new CCD detector,
which allows to obtain one square degree images of the sky in various filters.
Narrow-band filters were used to obtain Halpha and [S II] images, and a
medium-width filter was used for the continuum imaging. New HH flows and knots
were found near six embedded IR sources, which constitutes a significant
proportion of the objects observed. At least two of the newly found HH flows
(HH 1226 and HH 1227) lie in isolated dark clouds, thus pointing to active star
formation in these regions. Other flows are also located in detached and dense
globules or filaments. The length of the HH 1228 flow is about 1 pc; it has
also a molecular hydrogen counterpart of the same extension. Coordinates,
charts, detailed descriptions and distance estimates are provided. The lower
limits of bolometric luminosities of the source stars are typical for low-mass
young stellar objects.


  Populations evolving under the joint influence of recombination and
resampling (traditionally known as genetic drift) are investigated. First, we
summarise and adapt a deterministic approach, as valid for infinite
populations, which assumes continuous time and single crossover events. The
corresponding nonlinear system of differential equations permits a closed
solution, both in terms of the type frequencies and via linkage disequilibria
of all orders. To include stochastic effects, we then consider the
corresponding finite-population model, the Moran model with single crossovers,
and examine it both analytically and by means of simulations. Particular
emphasis is on the connection with the deterministic solution. If there is only
recombination and every pair of recombined offspring replaces their pair of
parents (i.e., there is no resampling), then the {\em expected} type
frequencies in the finite population, of arbitrary size, equal the type
frequencies in the infinite population. If resampling is included, the
stochastic process converges, in the infinite-population limit, to the
deterministic dynamics, which turns out to be a good approximation already for
populations of moderate size.


  Identifying the design of a failed implant is a key step in preoperative
planning of revision total joint arthroplasty. Manual identification of the
implant design from radiographic images is time consuming and prone to error.
Failure to identify the implant design preoperatively can lead to increased
operating room time, more complex surgery, increased blood loss, increased bone
loss, increased recovery time, and overall increased healthcare costs. In this
study, we present a novel, fully automatic and interpretable approach to
identify the design of total hip replacement (THR) implants from plain
radiographs using deep convolutional neural network (CNN). CNN achieved 100%
accuracy in identification of three commonly used THR implant designs. Such CNN
can be used to automatically identify the design of a failed THR implant
preoperatively in just a few seconds, saving time and improving the
identification accuracy. This can potentially improve patient outcomes, free
practitioners time, and reduce healthcare costs.


  In 1983 Conway and Gordon proved that any embedding of the complete graph
$K_7$ into $\mathbb{R}^3$ contains at least one nontrivial knot as its
Hamiltonian cycle. After their work knots (also links) are considered as
intrinsic properties of abstract graphs, and numerous subsequent works have
been continued until recently. In this paper we are interested in knotted
Hamiltonian cycles in linear embedding of $K_7$. Concretely it is shown that
any linear embedding of $K_7$ contains at most three figure-8 knots as its
Hamiltonian cycles.


  We establish the uniqueness of a smooth generalized bi-Schr\"odinger flow
from the one-dimensional flat torus into a compact locally Hermitian symmetric
space. The governing equation, which is satisfied by sections of the pull-back
bundle induced from the flow, is a fourth-order nonlinear dispersive partial
differential equation with loss of derivatives. To show the uniqueness, we
adopt an extrinsic approach to compare two solutions via an isometric embedding
into an ambient Euclidean space. We introduce an energy modifying the classical
$H^2$-energy for the difference of two solutions, the detailed estimate of
which enables us to eliminate the difficulty of the loss of derivatives. In
particular, we demonstrate how to decide the form of the modification by
exploiting the geometric structure of the locally Hermitian symmetric space.


  We derive the basic correlation functions of twist fields coming from
arbitrary twisted sectors in symmetric $Z_N$ orbifold conformal field theories,
keeping all the admissible marginal perturbations, in particular those
corresponding to the antisymmetric tensor background field. This allows a
thorough investigation of modular symmetries in this type of string
compactification. Such a study is explicitly carried out for the group
generated by duality transformations. Thus, apart from being of
phenomenological use, our couplings are also interesting from the mathematical
point of view as they represent automorphic functions for a large class of
discrete groups.


  A time-dependent model for the energy of a flaring solar active region is
presented based on a stochastic jump-transition model (Wheatland and Glukhov
1998; Wheatland 2008; Wheatland 2009). The magnetic free energy of the model
active region varies in time due to a prescribed (deterministic) rate of energy
input and prescribed (random) flare jumps downwards in energy. The model has
been shown to reproduce observed flare statistics, for specific
time-independent choices for the energy input and flare transition rates.
However, many solar active regions exhibit time variation in flare
productivity, as exemplified by NOAA active region AR 11029 (Wheatland 2010).
In this case a time-dependent model is needed. Time variation is incorporated
for two cases: 1. a step change in the rates of flare jumps; and 2. a step
change in the rate of energy supply to the system. Analytic arguments are
presented describing the qualitative behavior of the system in the two cases.
In each case the system adjusts by shifting to a new stationary state over a
relaxation time which is estimated analytically. The new model retains
flare-like event statistics. In each case the frequency-energy distribution is
a power law for flare energies less than a time-dependent rollover set by the
largest energy the system is likely to attain at a given time. For Case 1, the
model exhibits a double exponential waiting-time distribution, corresponding to
flaring at a constant mean rate during two intervals (before and after the step
change), if the average energy of the system is large. For Case 2 the
waiting-time distribution is a simple exponential, again provided the average
energy of the system is large. Monte Carlo simulations of Case~1 are presented
which confirm the analytic estimates. The simulation results provide a
qualitative model for observed flare statistics in active region AR 11029.


  We study the weak antilocalization (WAL) effect in the magnetoresistance of
narrow HgTe wires fabricated in quantum wells (QWs) with normal and inverted
band ordering. Measurements at different gate voltages indicate that the WAL is
only weakly affected by Rashba spin-orbit splitting and persists when the
Rashba splitting is about zero. The WAL signal in wires with normal band
ordering is an order of magnitude smaller than for inverted ones. These
observations are attributed to a Dirac-like topology of the energy bands in
HgTe QWs. From the magnetic-field and temperature dependencies we extract the
dephasing lengths and band Berry phases. The weaker WAL for samples with a
normal band structure can be explained by a non-universal Berry phase which
always exceeds \pi, the characteristic value for gapless Dirac fermions.


  We develop the quantum theory of a scalar field on LQC Bianchi I geometry. In
particular, we focus on single modes of the field: the evolution equation is
derived from the quantum scalar constraint, and it is shown that the same
equation can be obtained from QFT on an "classical" effective geometry. We
investigate the dependence of this effective space-time on the wavevector of
the mode (which could in principle generate a deformation in local
Lorentz-symmetry), focusing our attention on the dispersion relation. We prove
that when we disregard backreaction no Lorentz-violation is present, despite
the effective metric being different than the classical Bianchi I one. A
preliminary analysis of the correction due to inclusion of backreaction is
briefly discussed in the context of Born-Oppenheimer approximation.


  Discrete transformation for 3- waves problem is constructed in explicit form.
Generalization of this system on the matrix case in three dimensional space
together with corresponding discrete transformation is presented also.


  Some post-merger galaxies are known to undergo a starburst phase that quickly
depletes the gas reservoir and turns it into a red-sequence galaxy, though the
details are still unclear. Here we explore the pattern of recent star formation
in the central region of the post-merger galaxy NGC7252 using high resolution
UV images from the UVIT on ASTROSAT. The UVIT images with 1.2 and 1.4 arcsec
resolution in the FUV and NUV are used to construct a FUV-NUV colour map of the
central region. The FUV-NUV pixel colour map for this canonical post-merger
galaxy reveals a blue circumnuclear ring of diameter $\sim$ 10 " (3.2 kpc) with
bluer patches located over the ring. Based on a comparison to single stellar
population models, we show that the ring is comprised of stellar populations
with ages $\lesssim$ 300 Myr, with embedded star-forming clumps of younger age
($\lesssim$ 150Myr). The suppressed star formation in the central region, along
with the recent finding of a large amount of ionised gas, leads us to speculate
that this ring may be connected to past feedback from a central super-massive
black hole that has ionised the hydrogen gas in the central $\sim$ 4" $\sim$
1.3 kpc.


  One challenge that remains open in 3D deep learning is how to efficiently
represent 3D data to feed deep networks. Recent works have relied on volumetric
or point cloud representations, but such approaches suffer from a number of
issues such as computational complexity, unordered data, and lack of finer
geometry. This paper demonstrates that a mesh representation (i.e. vertices and
faces to form polygonal surfaces) is able to capture fine-grained geometry for
3D reconstruction tasks. A mesh however is also unstructured data similar to
point clouds. We address this problem by proposing a learning framework to
infer the parameters of a compact mesh representation rather than learning from
the mesh itself. This compact representation encodes a mesh using free-form
deformation and a sparse linear combination of models allowing us to
reconstruct 3D meshes from single images. In contrast to prior work, we do not
rely on silhouettes and landmarks to perform 3D reconstruction. We evaluate our
method on synthetic and real-world datasets with very promising results. Our
framework efficiently reconstructs 3D objects in a low-dimensional way while
preserving its important geometrical aspects.


  In this article we derive formula for probability $\Prob(\sup_{t\leq T}
(X(t)-ct)>u)$ where $X=\{X(t)\}$ is a spectrally positive L\'evy process and
$c\in\RL$. As an example we investigate the inverse Gaussian L\'evy process.


  An overview of the GW SAID and ITEP groups' effort to analyze pion
photoproduction on the neutron-target will be given. The disentanglement of the
isoscalar and isovector EM couplings of N* and Delta* resonances does require
compatible data on both proton and neutron targets. The final-state interaction
plays a critical role in the state-of-the-art analysis in extraction of the
gn-->piN data from the deuteron target experiments. Then resonance couplings
determined by the SAID PWA technique are then compared to previous findings.
The neutron program is important component of the current JLab, MAMI-C,
SPring-8, ELSA, and ELPH studies.


  The so-called Mpemba effect, i.e. the observation that the warmer of two
otherwise identical systems cools faster when both are refrigerated in the same
thermal reservoir, is a hotly debated topic in condensed mater physics and
statistical mechanics. Although it has been found in several non-equilibrium
model systems, its very existence in water, the system in which it has been
historically reported, is still open to question. Here we show using numerical
simulations that a Mpemba effect is indeed present in water. We find that the
effect occurs when equipartition of energy is not present in the initial state.
Interestingly, the effect is observed without the intervention of a phase
transition, and it is therefore seen to be a purely non-equilibrium relaxation
effect.


  We consider statistical hypothesis testing simultaneously over a fairly
general, possibly uncountably infinite, set of null hypotheses, under the
assumption that a suitable single test (and corresponding $p$-value) is known
for each individual hypothesis. We extend to this setting the notion of false
discovery rate (FDR) as a measure of type I error. Our main result studies
specific procedures based on the observation of the $p$-value process. Control
of the FDR at a nominal level is ensured either under arbitrary dependence of
$p$-values, or under the assumption that the finite dimensional distributions
of the $p$-value process have positive correlations of a specific type (weak
PRDS). Both cases generalize existing results established in the finite
setting. Its interest is demonstrated in several non-parametric examples:
testing the mean/signal in a Gaussian white noise model, testing the intensity
of a Poisson process and testing the c.d.f. of i.i.d. random variables.


  Language models trained on large-scale unfiltered datasets curated from the
open web acquire systemic biases, prejudices, and harmful views from their
training data. We present a methodology for programmatically identifying and
removing harmful text from web-scale datasets. A pretrained language model is
used to calculate the log-likelihood of researcher-written trigger phrases
conditioned on a specific document, which is used to identify and filter
documents from the dataset. We demonstrate that models trained on this filtered
dataset exhibit lower propensity to generate harmful text, with a marginal
decrease in performance on standard language modeling benchmarks compared to
unfiltered baselines. We provide a partial explanation for this performance gap
by surfacing examples of hate speech and other undesirable content from
standard language modeling benchmarks. Finally, we discuss the generalization
of this method and how trigger phrases which reflect specific values can be
used by researchers to build language models which are more closely aligned
with their values.


  We prove the Second Vanishing Theorem for local cohomology modules of an
unramified regular local ring in its full generality and provide a new proof of
the Second Vanishing Theorem in prime characteristic $p$. As an application of
our vanishing theorem for unramified regular local rings, we extend our
topological characterization of the highest Lyubeznik number of an
equi-characteristic local ring to the setting of mixed characteristic. An upper
bound of local cohomological dimension in mixed characteristic is also obtained
by partially extending Lyubeznik's vanishing theorem in prime characteristic
$p$ to mixed characteristic.


  We report on the Swift discovery of a second high-amplitude (factor 100)
outburst of the Seyfert 1.9 galaxy IC 3599, and discuss implications for
outburst scenarios. Swift detected this active galactic nucleus (AGN) again in
February 2010 in X-rays at a level of (1.50\plm0.11)$\times 10^{36}$ W (0.2-2.0
keV), which is nearly as luminous as the first outburst detected with ROSAT in
1990. Optical data from the Catalina sky survey show that the optical emission
was already bright two years before the Swift X-ray high-state. Our new Swift
observations performed between 2013 and 2015 show that IC 3599 is currently
again in a very low X-ray flux state. This repeat optical and X-ray outburst,
and the long optical duration, suggest that IC 3599 is likely not a tidal
disruption event (TDE). Instead, variants of AGN-related variability are
explored. The data are consistent with an accretion disk instability around a
black hole of mass on the order 10$^6$--10$^7$ M$_{\odot}$; a value estimated
using several different methods.


  We study the collider phenomenology of the minimal unified version of the
supersymmetry breaking scheme called Tree-level Gauge Mediation. We identify a
peculiar source of gaugino mass non-universality related to the necessary
SU(5)-breaking in the light fermion mass ratios and a gaugino mass sum rule at
the GUT scale, 3 M_2 + 2 M_3 = 5 M_1, which represents a smoking gun of this
scenario, together with the known tree-level sfermion mass ratio \tilde
m_{d^c,l} = \sqrt{2} \tilde m_{q,u^c,e^c}. The boundary conditions of the soft
SUSY breaking terms can be parameterised in terms of six relevant parameters
only (plus the sign of the \mu-parameter). We analyze the parameter space and
define three benchmark points, corresponding to the three possible NLSPs, a
bino- or wino-like neutralino or the stau. The LSP is the gravitino as in gauge
mediation. For these benchmark points we show possible signatures at the LHC
focusing on the Razor variable. We also comment on the Higgs mass.


  The number of academic papers being published is increasing exponentially in
recent years, and recommending adequate citations to assist researchers in
writing papers is a non-trivial task. Conventional approaches may not be
optimal, as the recommended papers may already be known to the users, or be
solely relevant to the surrounding context but not other ideas discussed in the
manuscript. In this work, we propose a novel embedding algorithm DocCit2Vec,
along with the new concept of ``structural context'', to tackle the
aforementioned issues. The proposed approach demonstrates superior performances
to baseline models in extensive experiments designed to simulate practical
usage scenarios.


  The evidence of environmental dependence of Type Ia supernova luminosity has
inspired recent discussion about whether the late-universe cosmic acceleration
is still supported by supernova data. We adopt the
$\Delta\mathrm{HR}/\Delta\mathrm{age}$ parameter, which describes the
dependence of supernova absolute magnitude on the age of supernova progenitor,
as an additional nuisance parameter. Using the Pantheon supernova data, a lower
bound $\ge 12\,\mathrm{Gyr}$ on the cosmic age, and a Gaussian prior $H_0 =
70\pm 2\,\mathrm{km\,s^{-1}Mpc^{-1}}$ on the Hubble constant, we reconstruct
the cosmic expansion history. Within the flat $\Lambda$ cold dark matter
($\Lambda$CDM) framework, we still find a $5.6\sigma$ detection of cosmic
acceleration. This is because a matter dominated decelerating universe would be
too young to accommodate observed old stars with age $\gtrsim
12\,\mathrm{Gyr}$. A decelerating but non-flat universe is marginally
consistent with the data, however, only in the presence of a negative spatial
curvature $\sim$ two orders of magnitude beyond the current constraint from
cosmic microwave background data. Finally, we propose a more general
Parameterization based on the cosmic Age (PAge), which is {\it not} directly
tied to the dark energy concept and hence is ideal for a null test of the
cosmic acceleration. We find that, for a magnitude evolution rate
$\Delta\mathrm{HR}/\Delta\mathrm{age} \lesssim
0.3\,\mathrm{mag}/5.3\,\mathrm{Gyr}$ (Kang et al. 2020), a spatially flat and
decelerating PAge universe is fully consistent with the supernova data and the
cosmic age bound, and has no tension with the geometric constraint from the
observed CMB acoustic angular scales.


  Calcium ruthenate ($CaRuO_3$) is widely believed to be located close to a
quantum critical point due to the strong non-Fermi-liquid behavior expressed in
the temperature dependence of electronic transport, specific heat, optical
conductivity, etc. However, the corresponding anomalous behavior, marking
crossover temperature regimes in the magnetic response of $CaRuO_3$, is still
lacking. Here we report detailed AC and DC magnetic susceptibility measurements
of $CaRuO_3$ and $CaRu_{0.97}Ti_{0.03}O_3$. The AC magnetic susceptibility
measurements of the $CaRuO_3$ show a slight dependence on the frequency of AC
magnetic field below ~ 40 K, and an additional subtle change of curvature
around 12 K. We interpret these results as a critical slowing down of spin
fluctuations towards T=0 K. We confirm these observations by magnetic
measurements of $CaRu_{0.97}Ti_{0.03}O_3$, which show a pronounced magnetic
response corresponding to the above temperatures.


  This paper presents TE-NeXt, a novel and efficient architecture for
Traversability Estimation (TE) from sparse LiDAR point clouds based on a
residual convolution block. TE-NeXt block fuses notions of current trends such
as attention mechanisms and 3D sparse convolutions. TE-NeXt aims to demonstrate
high capacity for generalisation in a variety of urban and natural
environments, using well-known and accessible datasets such as SemanticKITTI,
Rellis-3D and SemanticUSL. Thus, the designed architecture ouperforms
state-of-the-art methods in the problem of semantic segmentation, demonstrating
better results in unstructured environments and maintaining high reliability
and robustness in urbans environments, which leads to better abstraction.
Implementation is available in a open repository to the scientific community
with the aim of ensuring the reproducibility of results.


  Graph knowledge models and ontologies are very powerful modeling and re
asoning tools. We propose an effective approach to model network attacks and
attack prediction which plays important roles in security management. The goals
of this study are: First we model network attacks, their prerequisites and
consequences using knowledge representation methods in order to provide
description logic reasoning and inference over attack domain concepts. And
secondly, we propose an ontology-based system which predicts potential attacks
using inference and observing information which provided by sensory inputs. We
generate our ontology and evaluate corresponding methods using CAPEC, CWE, and
CVE hierarchical datasets. Results from experiments show significant capability
improvements comparing to traditional hierarchical and relational models.
Proposed method also reduces false alarms and improves intrusion detection
effectiveness.


  A version of massive gravity, namely conformal massive gravity, is employed
to study the behavior of thermodynamic geometry for both the static and the
rotating regular black holes. Whereas in thermodynamic geometry singularity can
be interpreted as the second phase transition, seeing such phenomena as heat
capacity behavior for both cases is investigated in detail. In addition, other
thermodynamic quantities like the entropy and the temperature are analyzed as
well. Another important property of the black holes is the so-called stability,
in which utilizing the first phase transition of the heat capacity is detailed,
for both cases, say the static and the spinning black holes. It is also
interestingly figured out that, the behavior of temperature of the uncharged
black holes in the presence of hair parameter, $\lambda$, can mimic the charged
ones. {The effects of scalar charge, $Q$, and hair parameters with both
positive and negative signs and how it affects key parameters in the study of
black holes are investigated as well.} To investigate the properties of the
black holes both regular thermodynamics and thermodynamic geometry approaches
are considered. Then one can observe that aiming to realize the physics of the
black holes, many complicated phenomena can be analyzed dramatically easier by
considering the latter approach.


  We study microwave background anisotropies induced by scaling seed
perturbations in a universe dominated by cold dark matter. Using a gauge
invariant linear perturbation analysis, we solve the perturbation equations on
super-horizon scales, for CMB anisotropies triggered by generic gravitational
seeds. We find that perturbations induced by seeds --- under very mild
restrictions --- are nearly isocurvature. Thus, compensation, which is mainly
the consequence of physically sensible initial conditions, is very generic.
  We then restrict our study to the case of scaling sources, motivated by
global scalar fields. We parameterize the energy momentum tensor of the source
by ``seed functions'' and calculate the Sachs-Wolfe and acoustic contributions
to the CMB anisotropies. We discuss the dependence of the anisotropy spectrum
on the parameters of the model considered. Even within the restricted class of
models investigated in this work, we find a surprising variety of results for
the position and height of the first acoustic peak as well as for the overall
amplitude. In particular, for certain choices of parameters, the spectrum
resembles very much the well known adiabatic inflationary spectrum, whereas for
others, the position of the first acoustic peak is significantly shifted
towards smaller angular scales.


  Bent-double radio sources have been used as a probe to measure the density of
intergalactic gas in galaxy groups. We carry out a series of high-resolution,
3D simulations of AGN jets moving through an external medium with a constant
density in order to develop a general formula for the radius of curvature of
the jets, and to determine how accurately the density of the intra-group medium
(IGM) can be measured. Our simulations produce curved jets ending in bright
radio lobes with an extended trail of low surface brightness radio emission.
The radius of curvature of the jets varies with time by only about 25%. The
radio trail seen in our simulations is typically not detected in known sources,
but may be detectable in lower resolution radio observations. The length of
this tail can be used to determine the age of the AGN. We also use our
simulation data to derive a formula for the kinetic luminosity of observed jets
in terms of the radius of curvature and jet pressure. In characterizing how
well observations can measure the IGM density, we find that the limited
resolution of typical radio observations leads to a systematic under-estimate
of the density of about 50%. The unknown angles between the observer and the
direction of jet propagation and direction of AGN motion through the IGM leads
to an uncertainty of about 50% in estimates of the IGM density. Previous
conclusions drawn using these sources, indicating that galaxy groups contain
significant reservoirs of baryons in their IGM, are still valid when
considering this level of uncertainty. In addition, we model the X-ray emission
expected from bent-double radio sources. We find that known sources in
reasonably dense environments should be detectable in ~100 ks Chandra
observations. X-ray observations of these sources would place constraints on
the IGM density and AGN velocity that are complementary to radio observations.


  The LHC will open up a new regime in high energy physics. The resultant
greatly expanded discovery reach makes it incumbant on LHC experimenters to be
prepared for discoveries, even in the very early days. To that end a variety of
Standard Model processes must be validated in any LHC experiment in order to
establish that the responses of the detector are well understood.


  We show that the convex hull of a monotone perturbation of a homogeneous
background conductivity in the $p$-conductivity equation is determined by
knowledge of the nonlinear Dirichlet-Neumann operator. We give two independent
proofs, one of which is based on the monotonicity method and the other on the
enclosure method. Our results are constructive and require no jump or
smoothness properties on the conductivity perturbation or its support.


  Happel constructed a fully faithful functor $\mathcal{H}
:\mathsf{D}^{\mathrm{b}}(\text{mod} \ \Lambda) \to
\underline{\text{mod}}^{\Bbb{Z}} \ \text{T}(\Lambda)$ for a finite dimensional
algebra $\Lambda$. He also showed that this functor $\mathcal{H}$ gives an
equivalence precisely when $\text{gldim } \Lambda < \infty$. Thus if
$\mathcal{H}$ gives an equivalence, then it provides a canonical tilting object
$\mathcal{H} (\Lambda)$ of $\underline{\text{mod}}^{\mathbb{Z}} \
\text{T}(\Lambda)$.
  In this paper we generalize Happel's functor $\mathcal{H}$ in the case where
$\text{T}(\Lambda)$ is replaced with a finitely graded IG algebra $A$. We study
when this functor is fully faithful or gives an equivalence. For this purpose
we introduce the notion of homologically well-graded (hwg) IG-algebra, which
can be characterized as an algebra posses a homological symmetry which, a
posteriori, guarantee that the algebra is IG. We prove that hwg IG-algebras is
precisely the class of finitely graded IG-algebras that Happel's functor is
fully faithful. We also identify the class that Happel's functor gives an
equivalence. As a consequence of our result, we see that if $\mathcal{H}$ gives
an equivalence, then it provides a canonical tilting object $\mathcal{H}(T)$ of
$\underline{\text{CM}}^{\Bbb{Z}} A$. For some special classes of finitely
graded IG algebras, our tilting objects $\mathcal{H}(T)$ coincide with tilting
object constructed in previous works.


  A high order, deterministic direct numerical method is proposed for the
nonrelativistic $2D_{\bf x} \times 3D_{\bf v}$ Vlasov-Maxwell system, coupled
with Fokker-Planck-Landau type operators. Such a system is devoted to the
modelling of electronic transport and energy deposition in the general frame of
Inertial Confinement Fusion applications. It describes the kinetics of plasma
physics in the nonlocal thermodynamic equilibrium regime. Strong numerical
constraints lead us to develop specific methods and approaches for validation,
that might be used in other fields where couplings between equations,
multiscale physics, and high dimensionality are involved. Parallelisation (MPI
communication standard) and fast algorithms such as the multigrid method are
employed, that make this direct approach be computationally affordable for
simulations of hundreds of picoseconds, when dealing with configurations that
present five dimensions in phase space.


  A numerical investigation of two-laser photoassociation (PA) spectroscopy on
spin-polarized metastable helium (He*) atoms is presented within the context of
experimental observation of the least-bound energy level in the scattering
potential and subsequent determination of the s-wave scattering length.
Starting out from the model developed by Bohn and Julienne [Phys. Rev. A
\textbf{60}, (1999) 414], PA rate coefficients are obtained as a function of
the parameters of the two lasers. The rate coefficients are used to simulate
one- and two-laser PA spectra. The results demonstrate the feasibility of a
spectroscopic determination of the binding energy of the least-bound level. The
simulated spectra may be used as a guideline when designing such an experiment,
whereas the model may also be employed for fitting experimentally obtained PA
spectra. In addition, the prospects for substantial modification of the He*
scattering length by means of optical Feshbach resonances are considered.
Several experimental issues relating to the numerical investigation presented
here are discussed.