  In this work we present a search for (solar) chameleons with the CERN Axion
Solar Telescope (CAST). This novel experimental technique, in the field of dark
energy research, exploits both the chameleon coupling to matter ($\beta_{\rm
m}$) and to photons ($\beta_{\gamma}$) via the Primakoff effect. By reducing
the X-ray detection energy threshold used for axions from 1$\,$keV to 400$\,$eV
CAST became sensitive to the converted solar chameleon spectrum which peaks
around 600$\,$eV. Even though we have not observed any excess above background,
we can provide a 95% C.L. limit for the coupling strength of chameleons to
photons of $\beta_{\gamma}\!\lesssim\!10^{11}$ for $1<\beta_{\rm m}<10^6$.


  The intercept of the supercritical Pomeron is examined with the use of
different forms of the scattering amplitudes of the bare Pomeron. The
one-to-one correspondence between the eikonal phase and the ratio of the
elastic and total cross section is shown. Based on new experimental data of the
CDF Collaboration, the intercept and power of the logarithmic growth of the
bare and total Pomeron amplitude are analyzed. It is shown that as a result of
the eikonalization procedure, the bare QCD Pomeron becomes compatible with
experiment.


  With the implementation of the new EU regulation 2022/1426 regarding the
type-approval of the automated driving system (ADS) of fully automated
vehicles, scenario-based testing has gained significant importance in
evaluating the performance and safety of advanced driver assistance systems and
automated driving systems. However, the exploration and generation of concrete
scenarios from a single logical scenario can often lead to a number of similar
or redundant scenarios, which may not contribute to the testing goals.
  This paper focuses on the the goal to reduce the scenario set by clustering
concrete scenarios from a single logical scenario. By employing clustering
techniques, redundant and uninteresting scenarios can be identified and
eliminated, resulting in a representative scenario set. This reduction allows
for a more focused and efficient testing process, enabling the allocation of
resources to the most relevant and critical scenarios. Furthermore, the
identified clusters can provide valuable insights into the scenario space,
revealing patterns and potential problems with the system's behavior.


  In this paper, we consider multigroup multicast transmissions with different
types of service messages in an overloaded multicarrier system, where the
number of transmitter antennas is insufficient to mitigate all inter-group
interference. We show that employing a rate-splitting based multiuser
beamforming approach enables a simultaneous delivery of the multiple service
messages over the same time-frequency resources in a non-orthogonal fashion.
Such an approach, taking into account transmission power constraints which are
inevitable in practice, outperforms classic beamforming methods as well as
current standardized multicast technologies, in terms of both spectrum
efficiency and the flexibility of radio resource allocation.


  Low-rank matrix factorization (LRMF) has received much popularity owing to
its successful applications in both computer vision and data mining. By
assuming noise to come from a Gaussian, Laplace or mixture of Gaussian
distributions, significant efforts have been made on optimizing the (weighted)
$L_1$ or $L_2$-norm loss between an observed matrix and its bilinear
factorization. However, the type of noise distribution is generally unknown in
real applications and inappropriate assumptions will inevitably deteriorate the
behavior of LRMF. On the other hand, real data are often corrupted by skew
rather than symmetric noise. To tackle this problem, this paper presents a
novel LRMF model called AQ-LRMF by modeling noise with a mixture of asymmetric
Laplace distributions. An efficient algorithm based on the
expectation-maximization (EM) algorithm is also offered to estimate the
parameters involved in AQ-LRMF. The AQ-LRMF model possesses the advantage that
it can approximate noise well no matter whether the real noise is symmetric or
skew. The core idea of AQ-LRMF lies in solving a weighted $L_1$ problem with
weights being learned from data. The experiments conducted on synthetic and
real datasets show that AQ-LRMF outperforms several state-of-the-art
techniques. Furthermore, AQ-LRMF also has the superiority over the other
algorithms in terms of capturing local structural information contained in real
images.


  Breaking time-reversal symmetry in a Dirac semimetal Cd$_3$As$_2$ through
doping with magnetic ions or by the magnetic proximity effect is expected to
cause a transition to other topological phases (such as a Weyl semimetal). To
this end, we investigate the possibility of proximity-induced ferromagnetic
ordering in epitaxial Dirac semimetal (Cd$_3$As$_2$)/ferromagnetic
semiconductor (Ga$_{1-x}$Mn$_x$Sb) heterostructures grown by molecular beam
epitaxy. We report the comprehensive characterization of these heterostructures
using structural probes (atomic force microscopy, x-ray diffraction, scanning
transmission electron microscopy), angle-resolved photoemission spectroscopy,
electrical magneto-transport, magnetometry, and polarized neutron
reflectometry. Measurements of the magnetoresistance and Hall effect in the
temperature range 2 K - 20 K show signatures that could be consistent with
either a proximity effect or spin-dependent scattering of charge carriers in
the Cd$_3$As$_2$ channel. Polarized neutron reflectometry sets constraints on
the interpretation of the magnetotransport studies by showing that (at least
for temperatures above 6 K) any induced magnetization in the Cd$_3$As$_2$
itself must be relatively small ($<$ 14 emu/cm$^3$).


  Developing microphone array technologies for a small number of microphones is
important due to the constraints of many devices. One direction to address this
situation consists of virtually augmenting the number of microphone signals,
e.g., based on several physical model assumptions. However, such assumptions
are not necessarily met in realistic conditions. In this paper, as an
alternative approach, we propose a neural network-based virtual microphone
estimator (NN-VME). The NN-VME estimates virtual microphone signals directly in
the time domain, by utilizing the precise estimation capability of the recent
time-domain neural networks. We adopt a fully supervised learning framework
that uses actual observations at the locations of the virtual microphones at
training time. Consequently, the NN-VME can be trained using only multi-channel
observations and thus directly on real recordings, avoiding the need for
unrealistic physical model-based assumptions. Experiments on the CHiME-4 corpus
show that the proposed NN-VME achieves high virtual microphone estimation
performance even for real recordings and that a beamformer augmented with the
NN-VME improves both the speech enhancement and recognition performance.


  \alpha-(BEDT-TTF)2KHg(SCN)4 is considered to be in the charge-density-wave
(CDW) state below 8 K. We present new magnetoresistance data suggesting that
the material undergoes a series of field-induced CDW (FICDW) transitions at
pressures slightly exceeding the critical pressure Pc at which the zero-field
CDW state is destroyed. Further, we argue that a novel kind of FICDW
transitions, entirely determined by a superposition of the strong Pauli and
quantizing orbital effects of magnetic field on the CDW wavevector, arises when
the field is strongly tilted towards the conducting layers. These new
transitions can take place even in the case of a relatively well nested Fermi
surface. Finally we report on the superconducting (SC) state and its
coexistence with the CDW in the title compound under quasi-hydrostatic
pressure. Below Pc the material is most likely a heterogeneous SC/CDW mixture,
with the SC phase persisting down to ambient pressure. The SC onset temperature
appears to drastically increase upon entering the SC/CDW coexistence region.


  We reformulate the full quantum dynamics of spin systems using a phase space
representation based on SU(2) coherent states which generates an exact mapping
of the dynamics of any spin system onto a set of stochastic differential
equations. The new representation is superior in practice to an earlier phase
space approach based on Schwinger bosons, with the numerical effort scaling
only linearly with system size. By also implementing extrapolation techniques
from quasiclassical equations to the full quantum limit, we are able to extend
useful simulation times several fold. This approach is applicable in any
dimension including cases where frustration is present in the spin system. The
method is demonstrated by simulating quenches in the transverse field Ising
model in one and two dimensions


  I investigate the Poisson-sigma model on the classical and quantum level.
First I show how the interaction can be obtained by a deformation of the
classical master equation of an Abelian BF theory in two dimensions. On the
classical level this model includes various known two-dimensional field
theories, in particular the Yang-Mills theory. On the quantum level the
perturbation expansion of the path integral in the covariant gauge yields the
Kontsevich deformation formula. Finally I perform the calculation of the path
integral in a general gauge, and demonstrate how the derived partition function
reduces in the special case of a linear Poisson structure to the familiar form
of 2d Yang-Mills theory.


  Periodic structures resonantly coupled to excitonic media allow the existence
of extra intragap modes ('Braggoritons'), due to the coupling between Bragg
photon modes and 3D bulk excitons. This induces unique and unexplored
dispersive features, which can be tailored by properly designing the photonic
bandgap around the exciton resonance. We report that one-dimensional
Braggoritons realized with semiconductor gratings have the ability to mimic the
dispersion of quantum-well microcavity polaritons. This will allow the
observation of new nonlinear phenomena, such as slow-light-enhanced nonlinear
propagation and an efficient parametric scattering at two 'magic frequencies'.


  Grain size engineering, particularly reducing grain size into the
nanocrystalline regime, offers a promising pathway to further improve the
strength-to-weight ratio of Al alloys. Unfortunately, the fabrication of
nanocrystalline metals often requires non-equilibrium processing routes, which
typically limit the specimen size and require large energy budgets. In this
study, multiple dopant atoms in ternary Al alloys are deliberately selected to
enable segregation to the grain boundary region and promote the formation of
amorphous complexions. Three different fully dense bulk nanocrystalline Al
alloys (Al-Mg-Y, Al-Fe-Y, and Al-Ni-Y) with small grain sizes were successfully
fabricated using a simple powder metallurgy approach, with full densification
connected directly to the onset of amorphous complexion formation. All the
compositions demonstrate densities above 99% with grain sizes of <60 nm
following consolidation via hot pressing at 585 oC. The very fine grain
structure results in excellent mechanical properties, with nanoindentation
hardness values in the range of 2.2-2.8 GPa. Detailed microstructural
characterization verifies the segregation of all dopant species to grain
boundaries as well as the formation of amorphous complexions, which suggests
their influential role in aiding effective consolidation and endowing thermal
stability in the alloys. Moreover, nanorods with a core-shell structure are
also observed at the grain boundaries, which likely contribute to the
stabilization of the grain structure and high strength. Finally, intermetallic
particles with a sizes of hundreds of nanometers form. As a whole, the results
presented here demonstrate a general alloy design strategy of segregation and
boundary evolution pathway that enables the fabrication of multiple
nanocrystalline Al alloys with hierarchical microstructures and improved
performance.


  We consider a uniformly luminous radiating sphere and a static black hole
located in the center of that sphere. We give analytic formulas for radiation
stress-energy tensor components in such a configuration, for the observer
located at an arbitrary distance from the static black hole horizon.


  We prove an optimal $O(n \log n)$ mixing time of the Glauber dynamics for the
Ising models with edge activity $\beta \in \left(\frac{\Delta-2}{\Delta},
\frac{\Delta}{\Delta-2}\right)$. This mixing time bound holds even if the
maximum degree $\Delta$ is unbounded.
  We refine the boosting technique developed in [CFYZ21], and prove a new
boosting theorem by utilizing the entropic independence defined in [AJK+21].
The theorem relates the modified log-Sobolev (MLS) constant of the Glauber
dynamics for a near-critical Ising model to that for an Ising model in a
sub-critical regime.


  We introduce a novel paraphrastic augmentation strategy based on
sentence-level lexically constrained paraphrasing and discriminative span
alignment. Our approach allows for the large-scale expansion of existing
resources, or the rapid creation of new resources from a small,
manually-produced seed corpus. We illustrate our framework on the Berkeley
FrameNet Project, a large-scale language understanding effort spanning more
than two decades of human labor. Based on roughly four days of collecting
training data for the alignment model and approximately one day of parallel
compute, we automatically generate 495,300 unique (Frame, Trigger) combinations
annotated in context, a roughly 50x expansion atop FrameNet v1.7.


  Microbial communities assemble through a complex set of interactions between
microbes and their environment, and the resulting metabolic impact on the host
ecosystem can be profound. Microbial activity is known to impact human health,
plant growth, water quality, and soil carbon storage which has lead to the
development of many approaches and products meant to manipulate the microbiome.
In order to understand, predict, and improve microbial community engineering,
genome-scale modeling techniques have been developed to translate genomic data
into inferred microbial dynamics. However, these techniques rely heavily on
simulation to draw conclusions which may vary with unknown parameters or
initial conditions, rather than more robust qualitative analysis. To better
understand microbial community dynamics using genome-scale modeling, we provide
a tool to investigate the network of interactions between microbes and
environmental metabolites over time.
  Using our previously developed algorithm for simulating microbial communities
from genome-scale metabolic models (GSMs), we infer the set of
microbe-metabolite interactions within a microbial community in a particular
environment. Because these interactions depend on the available environmental
metabolites, we refer to the networks that we infer as \emph{metabolically
contextualized}, and so name our tool MetConSIN: \underline{Met}abolically
\underline{Con}textualized \underline{S}pecies \underline{I}nteraction
\underline{N}etworks.


  As shown recently, one can obtain additional information from the measured
charged particle multiplicity distributions, $P(N)$, by investigating the
so-called modified combinants, $C_j$, extracted from them. This information is
encoded in the observed specific oscillatory behaviour of $C_j$, which
phenomenologically can be described only by some combinations of compound
distributions based on the Binomial Distribution. So far this idea has been
checked in $pp$ and $e^+e^-$ processes (where observed oscillations are
spectacularly strong). In this paper, we continue observation of multiparticle
production from the modified combinants perspective by investigating
dependencies of the observed oscillatory patterns on type of colliding
particles, their energies and the phase space where they are observed. We also
offer some tentative explanations based on different types of compound
distributions and stochastic branching processes.


  We use the hydrodynamical EAGLE simulation to study the magnitude and origin
of the scatter in the stellar mass - halo mass relation for central galaxies.
We separate cause and effect by correlating stellar masses in the baryonic
simulation with halo properties in a matched dark matter only (DMO) simulation.
The scatter in stellar mass increases with redshift and decreases with halo
mass. At $z = 0.1$ it declines from 0.25 dex at $M_{200, \rm DMO} \approx
10^{11}$ M$_{\odot}$ to 0.12 dex at $M_{200, \rm DMO} \approx 10^{13}$
M$_{\odot}$, but the trend is weak above $10^{12}$ M$_{\odot}$. For $M_{200,
\rm DMO} < 10^{12.5}$ M$_{\odot}$ up to 0.04 dex of the scatter is due to
scatter in the halo concentration. At fixed halo mass, a larger stellar mass
corresponds to a more concentrated halo. This is likely because higher
concentrations imply earlier formation times and hence more time for accretion
and star formation, and/or because feedback is less efficient in haloes with
higher binding energies. The maximum circular velocity, $V_{\rm max, DMO}$, and
binding energy are therefore more fundamental properties than halo mass,
meaning that they are more accurate predictors of stellar mass, and we provide
fitting formulae for their relations with stellar mass. However, concentration
alone cannot explain the total scatter in the $M_{\rm star} - M_{200, \rm DMO}$
relation, and it does not explain the scatter in $M_{\rm star} -V_{\rm max,
DMO}$. Halo spin, sphericity, triaxiality, substructure and environment are
also not responsible for the remaining scatter, which thus could be due to more
complex halo properties or non-linear/stochastic baryonic effects.


  Perhaps surprisingly, it is possible to predict how long an algorithm will
take to run on a previously unseen input, using machine learning techniques to
build a model of the algorithm's runtime as a function of problem-specific
instance features. Such models have important applications to algorithm
analysis, portfolio-based algorithm selection, and the automatic configuration
of parameterized algorithms. Over the past decade, a wide variety of techniques
have been studied for building such models. Here, we describe extensions and
improvements of existing models, new families of models, and -- perhaps most
importantly -- a much more thorough treatment of algorithm parameters as model
inputs. We also comprehensively describe new and existing features for
predicting algorithm runtime for propositional satisfiability (SAT), travelling
salesperson (TSP) and mixed integer programming (MIP) problems. We evaluate
these innovations through the largest empirical analysis of its kind, comparing
to a wide range of runtime modelling techniques from the literature. Our
experiments consider 11 algorithms and 35 instance distributions; they also
span a very wide range of SAT, MIP, and TSP instances, with the least
structured having been generated uniformly at random and the most structured
having emerged from real industrial applications. Overall, we demonstrate that
our new models yield substantially better runtime predictions than previous
approaches in terms of their generalization to new problem instances, to new
algorithms from a parameterized space, and to both simultaneously.


  This note is devoted to the study of the links between the Hilbert function
of a subscheme X of the projective space, and its geometric properties. We will
assume that X is arithmetically Cohen-Macaulay, which allows us to characterize
its Hilbert function by a d integers, where d is the degree of X. We study in
this context the geometric description of special linear systems of dimension
maximal with respect to their degree on projective Gorenstein curves.


  The lightest baryon octet is studied within a covariant and confining
Nambu--Jona-Lasinio model. By solving the relativistic Faddeev equations
including scalar and axialvector diquarks, we determine the masses and axial
charges for \Delta S = 0 transitions. For the latter the degree of violation of
SU(3) symmetry arising because of the strange spectator quark(s) is found to be
up to 10%.


  In this paper we determine the noise properties needed for unconditional
security for the ideal Kirchhoff-Law-Johnson-Noise (KLJN) secure key
distribution system using simple statistical analysis. It has already been
shown using physical laws that resistors and Johnson-like noise sources provide
unconditional security. However real implementations use artificial noise
generators, therefore it is a question if other kind of noise sources and
resistor values could be used as well. We answer this question and in the same
time we provide a theoretical basis to analyze real systems as well.


  Air Traffic Flow and Capacity Management (ATFCM) is one of the constituent
parts of Air Traffic Management (ATM). The goal of ATFCM is to make airport and
airspace capacity meet traffic demand and, when capacity opportunities are
exhausted, optimise traffic flows to meet the available capacity. One of the
key enablers of ATFCM is the accurate estimation of future traffic demand. The
available information (schedules, flight plans, etc.) and its associated level
of uncertainty differ across the different ATFCM planning phases, leading to
qualitative differences between the types of forecasting that are feasible at
each time horizon. While abundant research has been conducted on tactical
trajectory prediction (i.e., during the day of operations), trajectory
prediction in the pre-tactical phase, when few or no flight plans are
available, has received much less attention. As a consequence, the methods
currently in use for pre-tactical traffic forecast are still rather
rudimentary, often resulting in suboptimal ATFCM decision making. This paper
proposes a machine learning approach for the prediction of airlines route
choices between two airports as a function of route characteristics, such as
flight efficiency, air navigation charges and expected level of congestion.
Different predictive models based on multinomial logistic regression and
decision trees are formulated and calibrated with historical traffic data, and
a critical evaluation of each model is conducted. We analyse the predictive
power of each model in terms of its ability to forecast traffic volumes at the
level of charging zones, proving significant potential to enhance pre-tactical
traffic forecast. We conclude by discussing the limitations and room for
improvement of the proposed approach, as well as the future developments
required to produce reliable traffic forecasts at a higher spatial and temporal
resolution.


  Depth estimation-based obstacle avoidance has been widely adopted by
autonomous systems (drones and vehicles) for safety purpose. It normally relies
on a stereo camera to automatically detect obstacles and make flying/driving
decisions, e.g., stopping several meters ahead of the obstacle in the path or
moving away from the detected obstacle. In this paper, we explore new security
risks associated with the stereo vision-based depth estimation algorithms used
for obstacle avoidance. By exploiting the weaknesses of the stereo matching in
depth estimation algorithms and the lens flare effect in optical imaging, we
propose DoubleStar, a long-range attack that injects fake obstacle depth by
projecting pure light from two complementary light sources.
  DoubleStar includes two distinctive attack formats: beams attack and orbs
attack, which leverage projected light beams and lens flare orbs respectively
to cause false depth perception. We successfully attack two commercial stereo
cameras designed for autonomous systems (ZED and Intel RealSense). The
visualization of fake depth perceived by the stereo cameras illustrates the
false stereo matching induced by DoubleStar. We further use Ardupilot to
simulate the attack and demonstrate its impact on drones. To validate the
attack on real systems, we perform a real-world attack towards a commercial
drone equipped with state-of-the-art obstacle avoidance algorithms. Our attack
can continuously bring a flying drone to a sudden stop or drift it away across
a long distance under various lighting conditions, even bypassing sensor fusion
mechanisms. Specifically, our experimental results show that DoubleStar creates
fake depth up to 15 meters in distance at night and up to 8 meters during the
daytime. To mitigate this newly discovered threat, we provide discussions on
potential countermeasures to defend against DoubleStar.


  Previous research has found that functional connectivity (FC) can accurately
predict the identity of a subject performing a task and the type of task being
performed. We replicate these results using a large dataset collected at the
OSU Center for Cognitive and Behavioral Brain Imaging. We also introduce a
novel perspective on task and subject identity prediction: BOLD Variability
(BV). Conceptually, BV is a region-specific measure based on the variance
within each brain region. BV is simple to compute, interpret, and visualize. We
show that both FC and BV are predictive of task and subject, even across
scanning sessions separated by multiple years. Subject differences rather than
task differences account for the majority of changes in BV and FC. Similar to
results in FC, we show that BV is reduced during cognitive tasks relative to
rest.


  One of the defining characteristics of human creativity is the ability to
make conceptual leaps, creating something surprising from typical knowledge. In
comparison, deep neural networks often struggle to handle cases outside of
their training data, which is especially problematic for problems with limited
training data. Approaches exist to transfer knowledge from problems with
sufficient data to those with insufficient data, but they tend to require
additional training or a domain-specific method of transfer. We present a new
approach, conceptual expansion, that serves as a general representation for
reusing existing trained models to derive new models without backpropagation.
We evaluate our approach on few-shot variations of two tasks: image
classification and image generation, and outperform standard transfer learning
approaches.


  Periodic waves are investigated in a system composed of a
Kuramoto-Sivashinsky - Korteweg-de Vries (KS-KdV) equation, which is linearly
coupled to an extra linear dissipative equation. The model describes, e.g., a
two-layer liquid film flowing down an inclined plane. It has been recently
shown that the system supports stable solitary pulses. We demonstrate that a
perturbation analysis, based on the balance equation for the field momentum,
predicts the existence of stable cnoidal waves (CnWs) in the same system. It is
found that the mean value U of the wave field u in the main subsystem, but not
the mean value of the extra field, affects the stability of the periodic waves.
Three different areas can be distinguished inside the stability region in the
parameter plane (L,U), where L is the wave's period. In these areas, stable
are, respectively, CnWs with positive velocity, constant solutions, and CnWs
with negative velocity. Multistability, i.e., the coexistence of several
attractors, including the waves with several maxima per period, appears at
large value of L. The analytical predictions are completely confirmed by direct
simulations. Stable waves are also found numerically in the limit of vanishing
dispersion, when the KS-KdV equation goes over into the KS one.


  We review our current understanding to the accretion and ejection processes
in Sgr A*. Roughly speaking, they correspond to the quiescent and flare states
of the source respectively. The high-resolution {\it Chandra} observations to
the gas at the Bondi radius combined with the Bondi accretion theory, the
spectral energy distribution from radio to X-ray, and the radio polarization
provide us strict constraints and abundant information to the theory of
accretion. We review these observational results and describe how the
advection-dominated accretion flow model explains these observations. Recently
more attentions have been paid to flares in Sgr A*. Many simultaneous
multi-wavelength campaigns have been conducted, aiming at uncovering the nature
of flares. The main observational properties of flares are briefly reviewed.
Especially, the time lag between the peaks of flare at two radio frequencies
strongly indicates that the flare is associated with ejection of radio-emitting
blobs from the underlying accretion flow. Such kind of episodic jets is
distinctive from the continuous jets and are quite common in black hole
systems. We introduce the magnetohydrodynamical model for the formation of
episodic jets recently proposed based on the analogy with the theory of coronal
mass ejection in the Sun. We point out that the various observational
appearances of flares should be explained in the framework of this model, since
ejection and flare originate from the same physical process.


  Equipping current decision-making tools with notions of fairness,
equitability, or other ethically motivated outcomes, is one of the top
priorities in recent research efforts in machine learning, AI, and
optimization. In this paper, we investigate how to allocate limited resources
to {locally interacting} communities in a way to maximize a pertinent notion of
equitability. In particular, we look at the dynamic setting where the
allocation is repeated across multiple periods (e.g., yearly), the local
communities evolve in the meantime (driven by the provided allocation), and the
allocations are modulated by feedback coming from the communities themselves.
We employ recent mathematical tools stemming from data-driven feedback online
optimization, by which communities can learn their (possibly unknown)
evolution, satisfaction, as well as they can share information with the
deciding bodies. We design dynamic policies that converge to an allocation that
maximize equitability in the long term. We further demonstrate our model and
methodology with realistic examples of healthcare and education subsidies
design in Sub-Saharian countries. One of the key empirical takeaways from our
setting is that long-term equitability is fragile, in the sense that it can be
easily lost when deciding bodies weigh in other factors (e.g., equality in
allocation) in the allocation strategy. Moreover, a naive compromise, while not
providing significant advantage to the communities, can promote inequality in
social outcomes.


  Acute Lymphoblastic Leukemia (ALL) is one of the most common types of
childhood blood cancer. The quick start of the treatment process is critical to
saving the patient's life, and for this reason, early diagnosis of this disease
is essential. Examining the blood smear images of these patients is one of the
methods used by expert doctors to diagnose this disease. Deep learning-based
methods have numerous applications in medical fields, as they have
significantly advanced in recent years. ALL diagnosis is not an exception in
this field, and several machine learning-based methods for this problem have
been proposed. In previous methods, high diagnostic accuracy was reported, but
our work showed that this alone is not sufficient, as it can lead to models
taking shortcuts and not making meaningful decisions. This issue arises due to
the small size of medical training datasets. To address this, we constrained
our model to follow a pipeline inspired by experts' work. We also demonstrated
that, since a judgement based on only one image is insufficient, redefining the
problem as a multiple-instance learning problem is necessary for achieving a
practical result. Our model is the first to provide a solution to this problem
in a multiple-instance learning setup. We introduced a novel pipeline for
diagnosing ALL that approximates the process used by hematologists, is
sensitive to disease biomarkers, and achieves an accuracy of 96.15%, an
F1-score of 94.24%, a sensitivity of 97.56%, and a specificity of 90.91% on ALL
IDB 1. Our method was further evaluated on an out-of-distribution dataset,
which posed a challenging test and had acceptable performance. Notably, our
model was trained on a relatively small dataset, highlighting the potential for
our approach to be applied to other medical datasets with limited data
availability.


  Deregulation of energy markets, penetration of renewables, advanced metering
capabilities, and the urge for situational awareness, all call for system-wide
power system state estimation (PSSE). Implementing a centralized estimator
though is practically infeasible due to the complexity scale of an
interconnection, the communication bottleneck in real-time monitoring, regional
disclosure policies, and reliability issues. In this context, distributed PSSE
methods are treated here under a unified and systematic framework. A novel
algorithm is developed based on the alternating direction method of
multipliers. It leverages existing PSSE solvers, respects privacy policies,
exhibits low communication load, and its convergence to the centralized
estimates is guaranteed even in the absence of local observability. Beyond the
conventional least-squares based PSSE, the decentralized framework accommodates
a robust state estimator. By exploiting interesting links to the compressive
sampling advances, the latter jointly estimates the state and identifies
corrupted measurements. The novel algorithms are numerically evaluated using
the IEEE 14-, 118-bus, and a 4,200-bus benchmarks. Simulations demonstrate that
the attainable accuracy can be reached within a few inter-area exchanges, while
largest residual tests are outperformed.


  We report on the design, deployment and signal analysis for shielded button
electrodes sensitive to electron cloud buildup at the Cornell Electron Storage
Ring. These simple detectors, derived from a beam-position monitor electrode
design, have provided detailed information on the physical processes underlying
the local production and lifetime of electron densities in the storage ring.
Digitizing oscilloscopes are used to record electron fluxes incident on the
vacuum chamber wall in 1024 time steps of 100 ps or more. The fine time steps
provide a detailed characterization of the cloud, allowing the independent
estimation of processes contributing on differing time scales and providing
sensitivity to the characteristic kinetic energies of the electrons making up
the cloud. By varying the spacing and population of electron and positron beam
bunches, we map the time development of the various cloud production and
re-absorption processes. The excellent reproducibility of the measurements also
permits the measurement of long-term conditioning of vacuum chamber surfaces.


  We exhibit the rich structure of the set of correlated equilibria by
analyzing the simplest of polynomial games: the mixed extension of matching
pennies. We show that while the correlated equilibrium set is convex and
compact, the structure of its extreme points can be quite complicated. In
finite games the ratio of extreme correlated to extreme Nash equilibria can be
greater than exponential in the size of the strategy spaces. In polynomial
games there can exist extreme correlated equilibria which are not finitely
supported; we construct a large family of examples using techniques from
ergodic theory. We show that in general the set of correlated equilibrium
distributions of a polynomial game cannot be described by conditions on
finitely many moments (means, covariances, etc.), in marked contrast to the set
of Nash equilibria which is always expressible in terms of finitely many
moments.


  We present a quantum sensing scheme achieving the ultimate quantum
sensitivity in the estimation of the transverse displacement between two
photons interfering at a balanced beam splitter, based on transverse-momentum
sampling measurements at the output. This scheme can possibly lead to enhanced
high-precision nanoscopic techniques, such as super-resolved single-molecule
localization microscopy with quantum dots, by circumventing the requirements in
standard direct imaging of cameras resolution at the diffraction limit, and of
highly magnifying objectives. Interestingly, we show that our interferometric
technique achieves the ultimate spatial precision in nature irrespectively of
the overlap of the two displaced photonic wavepackets, while its precision is
only reduced of a constant factor for photons differing in any non-spatial
degrees of freedom. This opens a new research paradigm based on the interface
between spatially resolved quantum interference and quantum-enhanced spatial
sensitivity.


  Nambu Quantum Mechanics, proposed in Phys. Lett. B536, 305 (2002), is a
deformation of canonical Quantum Mechanics in which only the time-evolution of
the "phases" of energy eigenstates is modified. We discuss the effect this
theory will have on oscillation phenomena, and place a bound on the deformation
parameters utilizing the data on the atmospheric neutrino mixing angle
$\theta_{23}$.


  We study relativistic stars in Hordenski theories that evade the
gravitational wave constraints and exhibit the Vainshtein mechanism, focusing
on a model based on the cubic Galileon Lagrangian. We derive the scalar field
profile for static spherically symmetric objects in asymptotically de Sitter
space-time with a linear time dependence. The exterior solution matches to the
black hole solution found in the literature. Due to the Vainshtein mechanism,
the stellar structure is indistinguishable from that of General Relativity with
the same central density as long as the radius of the star is shorter than the
Vainshtein radius. On the other hand, the scalar field is not suppressed beyond
the Vainshtein radius. These solutions have an additional integration constant
in addition to the mass of the star.


  Redundant sensing capabilities are often required in sensor network
applications due to various reasons, e.g. robustness, fault tolerance, or
increased accuracy. At the same time high sensor redundancy offers the
possibility of increasing network lifetime by scheduling sleep intervals for
some sensors and still providing continuous service with help of the remaining
active sensors. In this paper centralized and distributed algorithms are
proposed to solve the k-coverage sensing problem and maximize network lifetime.
When physically possible, the proposed robust Controlled Greedy Sleep Algorithm
provides guaranteed service independently of node and communication errors in
the network. The performance of the algorithm is illustrated and compared to
results of a random solution by simulation examples.


  The mutual control of the electric and magnetic properties of a multiferroic
solid is of fundamental and great technological importance. We report here on
the colossal magnetoelectric coupling effect of polycrystalline
La0.2Pb0.7Fe12O19. A large classic ferroelectric hysteresis loop with full
saturation and a strong magnetic hysteresis loop were observed simultaneously
in polycrystalline La0.2Pb0.7Fe12O19 due to the coexistence of an off-centered
FeO6 octahedron in its unit cell and electron spins in the partially filled 3d
orbits of the Fe3+ ions. The coupling voltage and capacity demonstrate giant
oscillations, along with magnetic field; the maximum magnetocapacitance ratio
exceeds 1.9E5 at 80 Hz. The substitution of La ions with Pb ions progressively
stabilized the conical spin structure, which gave rise to the spin-current
induced capacity oscillations upon magnetic field.


  The blinding of the Byzantine Emperor Constantine VI in Constantinople in
August 797 and his overthrow by his mother Eirene, who then until 802 ruled as
first female emperor of the Eastern Roman Empire, was used as legitimation for
the coronation of the Frankish King Charlemagne as emperor of the Romans on
December 25, 800, by contemporaries in Western Europe. Some observers in the
West may have even interpreted the downfall of the Eastern Roman emperor and
his replacement by a woman as sign of an impending collapse of the Roman Empire
and the entire world order as already expected, based on chiliastic
calculations. We equally find indications of apocalyptic expectations in
Constantinople, where the blinding of Constantine was linked with a spectacular
celestial manifestation of divine disapproval, a darkening of the sun for 17
days. In this paper, this obfuscation of the sun is compared with the
description of other atmospheric and climatic phenomena in the 8th and 9th
century as well as before and after this period. In addition, natural
scientific data is used to disprove earlier hypotheses on the physical
background to this event and to present a more probable scenario, i. e., the
impacts of one or more volcanic eruptions, for the darkening of 797 and other
phenomena, which provided a peculiar atmospheric framework for the
interpretation of the events between the downfall of Constantine VI and the
coronation of Charlemagne by contemporaries.


  A Brownian particle in a symmetric double well potential is used as a
representation for a single bit memory, where, the location of the particle in
either well denotes one of the two states of a single bit memory. This article
analyzes the effect of modifications to a symmetric double well potential on
the minimum heat dissipation associated with erasure of the information stored
in a single bit memory. Two types of modifications are considered, viz.,
overlap between the two wells and the asymmetry between the two wells of a bit
of memory. Moreover, the analysis presented here, takes into account the
uncertainty in the success of the erasure process. We quantify the effect of
the proposed modifications on the heat dissipation accompanying erasure of a
bit of information with a comparison to the Landauer's bound. In particular, we
conclude that the proposed modifications could result in the minimum heat
dissipation being lower than the Landauer's bound in quasi-static erasure
processes. Furthermore, we quantify the physical aspect ratio for designing a
memory bit which could improve memory density.


  In high-contrast space-based coronagraphs, one of the main limiting factors
for imaging the dimmest exoplanets is the time varying nature of the residual
starlight (speckles). Modern methods try to differentiate between the
intensities of starlight and other sources, but none incorporate models of
space-based systems which can take into account actuations of the deformable
mirrors. Instead, we propose formulating the estimation problem in terms of the
electric field while allowing for dithering of the deformable mirrors. Our
reduced-order approach is similar to intensity-based PCA (e.g. KLIP) although,
under certain assumptions, it requires a considerably lower number of modes of
the electric field. We illustrate this by a FALCO simulation of the WFIRST
hybrid Lyot coronagraph.


  We present spectroscopic observations for quasars Q0107-025A, Q0107-025B, and
Q0107-0232. For the first time, all data obtained with the Hubble Space
Telescope's GHRS and FOS for these three quasars are combined. Ly-alpha
absorbers selected from the spectra can be used to trace the coherence of the
intergalactic medium (IGM) on scales of 1-2 h_{70}^{-1} Mpc over the redshift
range 0.4 < z_a < 0.9. A new analysis of double and triple absorber
coincidences derived from the improved spectra is performed. Automated
line-selection algorithms were used to detect absorption lines in the QSO
spectra; coincident absorbers were identified across two and three sight lines
based on their proximity to each other in velocity space. A control simulation
designed to generate artificial absorption-line spectra was used to gauge the
significance of the coincidences. Four intervening metal line absorption
systems are detected, with three of the four coincident to the A and B sight
lines and one coincident across all three sight lines. This is evidence for
substantial clustering among the objects responsible for the metal-enriched
gas. By contrast, large scale coherence of the IGM gas is detectable but weak.
Fewer than half of the absorbers are coincident on scales of 1-2 h_{70}^{-1}
Mpc, a result that is significant at the 99% confidence level, and coherence
arises preferentially in the higher column density gas. Triple absorber
coincidences occur at a level that is significant at the 99% confidence level,
which indicates that the higher column density gas has a planar geometry.


  We present the first near-IR milli-arcsecond-scale image of a post-AGB binary
that is surrounded by hot circumbinary dust. A very rich interferometric data
set in six spectral channels was acquired of IRAS08544-4431 with the new RAPID
camera on the PIONIER beam combiner at the Very Large Telescope Interferometer
(VLTI). A broadband image in the \textit{H} band was reconstructed by combining
the data of all spectral channels using the SPARCO method. We spatially
separate all the building blocks of the IRAS08544-4431 system in our
milliarcsecond-resolution image. Our dissection reveals a dust sublimation
front that is strikingly similar to that expected in early-stage protoplanetary
disks, as well as an unexpected flux signal of $\sim$4\% from the secondary
star. The energy output from this companion indicates the presence of a compact
circum-companion accretion disk, which is likely the origin of the fast outflow
detected in H$\alpha$. Our image provides the most detailed view into the heart
of a dusty circumstellar disk to date. Our results demonstrate that binary
evolution processes and circumstellar disk evolution can be studied in detail
in space and over time.


  A periodic two-phase algebro-geometric solution of the focusing nonlinear
Schr\"odinger equation is constructed in terms of elliptic Jacobi
theta-functions. A dependence of this solution on the parameters of a spectral
curve is investigated. An existence of a real smooth finite-gap solution of NLS
equation with complex initial phase is proven. Degenerations of the constructed
solution to one-phase traveling wave solution and solutions in the form of the
plane waves are carried.


  Coupling constants of $S_{11}(1535)$ and $S_{11}(1650)$ resonances to
meson-baryon ($\pi N$, $\eta N$, $\eta^\prime N$, $KY$) are investigated in a
chiral quark model, complemented by inclusion of five-quark components in those
resonances. The known strong decay partial widths of both resonances are well
reproduced, provided sizeable strangeness components in the relevant wave
functions. %to excellent description for the strong decays of the above two
resonances, which %cannot be reproduced very well in the traditional chiral
quark model with or without %$SU(6)\otimes O(3)$ breaking. Finally, we find
that $S_{11}(1535)$ and $S_{11}(1650)$ %couple strongly to the channels with
strangeness.


  Most brain-computer interfaces (BCIs) based on functional near-infrared
spectroscopy (fNIRS) require that users perform mental tasks such as motor
imagery, mental arithmetic, or music imagery to convey a message or to answer
simple yes or no questions. These cognitive tasks usually have no direct
association with the communicative intent, which makes them difficult for users
to perform. In this paper, a 3-class intuitive BCI is presented which enables
users to directly answer yes or no questions by covertly rehearsing the word
'yes' or 'no' for 15 s. The BCI also admits an equivalent duration of
unconstrained rest which constitutes the third discernable task. Twelve
participants each completed one offline block and six online blocks over the
course of 2 sessions. The mean value of the change in oxygenated hemoglobin
concentration during a trial was calculated for each channel and used to train
a regularized linear discriminant analysis (RLDA) classifier. By the final
online block, 9 out of 12 participants were performing above chance (p<0.001),
with a 3-class accuracy of 83.8+9.4%. Even when considering all participants,
the average online 3-class accuracy over the last 3 blocks was 64.1+20.6%, with
only 3 participants scoring below chance (p<0.001). For most participants,
channels in the left temporal and temporoparietal cortex provided the most
discriminative information. To our knowledge, this is the first report of an
online fNIRS 3-class imagined speech BCI. Our findings suggest that imagined
speech can be used as a reliable activation task for selected users for the
development of more intuitive BCIs for communication.


  Time dependent CP-violation phenomena are a powerful tool to precisely
measure fundamental parameters of the Standard Model and search for New
Physics. The Belle II experiment at the SuperKEKB energy-asymmetric $e^+e^-$
collider is a substantial upgrade of the B factory facility at the Japanese KEK
laboratory. The design luminosity of the machine is
$8\times{10}^{35}~cm^{-2}s^{-1}$ and the Belle II experiment aims to record
$50~ab^{-1}$ of data, a factor of 50 more than its predecessor. From February
to July 2018, the machine has completed a commissioning run, achieved a peak
luminosity of $5.5\times10^{33}~cm^{-2}s^{-1}$ , and Belle II has recorded a
data sample of about $0.5~fb^{-1}$ . Main operation of SuperKEKB has started in
March 2019. This early data set is used to establish the performance of the
detector in terms of reconstruction efficiency of final states of interest for
the measurement of time dependent CP violation, such as $J/\psi K_0$ , $\eta'
K_0$, and $\phi K_0$. A first assessment of the B flavor tagging capabilities
of the experiment will be given, along with estimates of the Belle II
sensitivity to the CKM angles $\phi_1/\beta$ and $\phi_2/\alpha$ and to
potential New Physics contributions in penguin amplitudes dominated decays and
in $b\to s\gamma$ transitions. In this paper we will present estimates of the
sensitivity to $\phi_1$ in the golden channels $b\to c\bar{c} s$ and in the
penguin-dominated modes $B_0\to \eta' K_0,\quad\phi K_0,\quad
K_0\pi_0(\gamma)$. A study for the time-dependent analysis of
$B_0\to\pi_0\pi_0$, relevant for the measurement of $\phi_2$, and feasible only
in the clean environment of an $e^+e^-$ collider, will also be given.


  We investigate the use of Android permissions as the vehicle to allow for
quick and effective differentiation between benign and malware apps. To this
end, we extract all Android permissions, eliminating those that have zero
impact, and apply two feature ranking algorithms namely Chi-Square test and
Fisher's Exact test to rank and additionally filter them, resulting in a
comparatively small set of relevant permissions. Then we use Decision Tree,
Support Vector Machine, and Random Forest Classifier algorithms to detect
malware apps. Our analysis indicates that this approach can result in better
accuracy and F-score value than other reported approaches. In particular, when
random forest is used as the classifier with the combination of Fisher's Exact
test, we achieve 99.34\% in accuracy and 92.17\% in F-score with the false
positive rate of 0.56\% for the dataset in question, with results improving to
99.82\% in accuracy and 95.28\% in F-score with the false positive rate as low
as 0.05\% when only malware from three most popular malware families are
considered.


  Effective photon-photon luminosities are calculated for various realistic
hadron collider scenarios. The main characteristics of photon-photon processes
at relativistic heavy-ion colliders are established and compared to the
corresponding photon-photon luminosities at electron-positron and future Photon
Linear Colliders (PLC). Higher order corrections as well as inelastic processes
are discussed. It is concluded that feasible high luminosity Ca-Ca collisions
at the Large Hadron Collider (LHC) are an interesting option for photon-photon
physics up to about 100 GeV photon-photon CM energy.


  A number of lattices exhibit moat-like band structures, i.e. a band with
infinitely degenerate energy minima attained along a closed line in the
Brillouin zone. If such a lattice is populated with hard-core bosons, the
degeneracy prevents their condensation. At half-filling, the system is
equivalent to $s=1/2$ XY model at zero magnetic field, while absence of
condensation translates into the absence of magnetic order in the XY plane.
Here we show that the ground state breaks the time-reversal as well as
inversion symmetries. This state, which may be identified with the chiral spin
liquid, has a bulk gap and chiral gapless edge excitations. The applications of
the developed analytical theory include an explanation of recent numerical
findings and a suggestion for the chiral spin liquid realizations in
experiments with cold atoms in optical lattices.


  In this paper we make a detailed and self-contained study of the
conformalGauss map. Then, starting from the seminal work of R. Bryant and the
notion of conformal Gauss map, we recover many fundamental properties of
Willmore surfaces. We also get new results like some characterizations of
minimal and constant meancurvature (CMC) surfaces in term of their conformal
Gauss map behavior.


  We report Swift/BAT survey observations of the Tycho's supernova remnant,
performed over a period of 104 months since the mission's launch. The remnant
is detected with high significance (>10 sigma) below 50 keV. We detect
significant hard X-ray emission in the 60-85 keV band, above the continuum
level predicted by a simple synchrotron model. The location of the observed
excess is consistent with line emission from radioactive Titanium-44, so far
reported only for Type II supernova explosions. We discuss the implications of
these results in the context of the galactic supernova rate, and
nucleosynthesis in Type Ia supernova.


  Frobenius built a representation theory of finite groups in the process of
obtaining the irreducible factorization of the group determinant. Here, we give
a generalization of Frobenius' theorem. The generalization leads to a corollary
on irreducible representations of finite groups.


  We analyze the temperature dependence of CP violation effects in the Standard
Model by determining the effective action of its bosonic fields, obtained after
integrating out the fermions from the theory and performing a covariant
gradient expansion. We find non-vanishing CP violating terms starting at the
sixth order of the expansion, albeit only in the C odd/P even sector, with
coefficients that depend on quark masses, CKM matrix elements, temperature and
the magnitude of the Higgs field. The CP violating effects are observed to
decrease rapidly with temperature, which has important implications for the
generation of a matter-antimatter asymmetry in the early Universe. Our results
suggest that the cold electroweak baryogenesis scenario may be viable within
the Standard Model, provided the electroweak transition temperature is at most
of order 1 GeV.


  In this talk, based on the work \cite{cpviolation}, we refine our previous
analysis \cite{golden} of the sensitivity to leptonic CP violation and
$\tetaot$ at a neutrino factory in the LMA-MSW scenario, by exploring the full
range of these two parameters. We have discovered that there exist, at fixed
neutrino energy, $E_\nu$, and baseline, $L$, degenerate solutions. Although the
spectral analysis helps in disentangling fake from true solutions, a leftover
product of this degeneracy remains for a realistic detector, which we analyse.
Furthermore, we take into account the expected uncertainties on the solar and
atmospheric oscillation parameters and in the average Earth matter density
along the neutrino path. An intermediate baseline of O(3000) km is still the
best option to tackle CP violation, although a combination of two baselines
turns out to be very important in resolving degeneracies. This summary is based
on a talk given at NUFACT01, May 2001, Tsukuba (Japan).


  It is a well-known fact that mathematical functions that are timelimited (or
spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the
finite precision of measurement and computation unavoidably bandlimits our
observation and modeling scientific data, and we often only have access to, or
are only interested in, a study area that is temporally or spatially bounded.
In the geosciences we may be interested in spectrally modeling a time series
defined only on a certain interval, or we may want to characterize a specific
geographical area observed using an effectively bandlimited measurement device.
It is clear that analyzing and representing scientific data of this kind will
be facilitated if a basis of functions can be found that are "spatiospectrally"
concentrated, i.e. "localized" in both domains at the same time. Here, we give
a theoretical overview of one particular approach to this "concentration"
problem, as originally proposed for time series by Slepian and coworkers, in
the 1960s. We show how this framework leads to practical algorithms and
statistically performant methods for the analysis of signals and their power
spectra in one and two dimensions, and on the surface of a sphere.


  We report the quantitative experimental observation of the weak inertial-wave
turbulence regime of rotating turbulence. We produce a statistically steady
homogeneous turbulent flow that consists of nonlinearly interacting inertial
waves, using rough top and bottom boundaries to prevent the emergence of a
geostrophic flow. As the forcing amplitude increases, the temporal spectrum
evolves from a discrete set of peaks to a continuous spectrum. Maps of the
bicoherence of the velocity field confirm such a gradual transition between
discrete wave interactions at weak forcing amplitude, and the regime described
by weak turbulence theory (WTT) for stronger forcing. In the former regime, the
bicoherence maps display a near-zero background level, together with sharp
localized peaks associated with discrete resonances. By contrast, in the latter
regime the bicoherence is a smooth function that takes values of the order of
the Rossby number, in line with the infinite-domain and random-phase
assumptions of WTT. The spatial spectra then display a power-law behavior, both
the spectral exponent and the spectral level being accurately predicted by WTT
at high Reynolds number and low Rossby number.


  An intriguing potential signature of hydrodynamic behavior in relativistic
A+A reactions at Relativistic Heavy Ion Collider (RHIC) energies is conical
flow induced by fast supersonic particles traversing the hot and dense medium.
Here I present first results on the evolution of Mach shocks in 2->2 covariant
transport theory, in a static uniform medium.


  The BReast CAncer type 2 susceptibility protein (BRCA2) responds to DNA
damage by participating in homology-directed repair. BRCA2 deficiency
culminates in defective DNA damage repair (DDR) that when prolonged leads to
the accumulation of DNA damage causing cancer or apoptosis. Oxidative stress
promotes DNA damage and apoptosis and is a common mechanism through which
cardiovascular risk factors lead to endothelial dysfunction and
atherosclerosis. Herein, we show that endothelial BRCA2 plays a protective role
against atherosclerosis under hypercholesterolemic stress. We successfully
generated and characterized endothelial cell (EC)-specific BRCA2 knockout
(BRCA2endo) mice. To study the effect of EC-specific BRCA2-loss in
atherosclerosis, we generated and characterized BRCA2endo mice on
apolipoprotein E null background (ApoE-/-), fed them with high-fat diet (HFD)
and evaluated atherosclerosis. Baseline phenotyping of BRCA2endo mice did not
show any adverse effects in terms of DNA damage and apoptosis as well as
cardiac and metabolic function. However, using HFD-fed apolipoprotein E
knockout (ApoE-/-) background, we demonstrated that EC-specific loss of BRCA2
resulted in aortic plaque deposition and splenomegaly. Comparison of RNA
sequencing data from aortas of EC-specific BRCA2-deficient ApoE-/- and
BRCA2-intact ApoE-/- mice revealed a total of 530 significantly differentially
expressed genes with Protein Folding Response and Lipid Metabolism as the most
affected pathways. This study provides foundational knowledge regarding BRCA2
status and function in the cardiovascular system, and highlights the potential
of BRCA2 as a novel therapeutic target in prevention and treatment of
atherosclerosis. Our data indicate that BRCA2 mutation carriers may be at a
previously unrecognized risk of atherosclerosis in addition to breast and
ovarian cancer.


  The key numbers useful for describing the fission process are the mass number
of the primordial cluster of the fissioning system and the magic mass numbers
82 and 126 of the nascent light and heavy fragments. The mean mass number and
the mean atomic number of the light fragments are linked to the mass number and
to the atomic number of the primordial cluster by simple relationships. The
value 54 of the mean atomic number of the heavy fragments is predicted by the
nucleon phase model.


  We have proposed in previous papers that the high-frequency pair QPOs
observed in black-hole binaries with frequency ratio 3:2 are inertial-acoustic
oscillations (nearly horizontal oscillations with no node in the vertical
direction) or g-mode oscillations, which are resonantly excited on warped
relativistic disks. The resonance occurs through horizontal motions. In this
model the dimensionless spin parameter $a_*$ of the central sources can be
estimated when their masses are known from other observations. This estimate is
done for three sources (GRO J1665-40, XTE J1550-564, GRS 1915+105). For all of
them we have $a_*\leq 0.45$.


  Generative Adversarial Nets (GANs) represent an important milestone for
effective generative models, which has inspired numerous variants seemingly
different from each other. One of the main contributions of this paper is to
reveal a unified geometric structure in GAN and its variants. Specifically, we
show that the adversarial generative model training can be decomposed into
three geometric steps: separating hyperplane search, discriminator parameter
update away from the separating hyperplane, and the generator update along the
normal vector direction of the separating hyperplane. This geometric intuition
reveals the limitations of the existing approaches and leads us to propose a
new formulation called geometric GAN using SVM separating hyperplane that
maximizes the margin. Our theoretical analysis shows that the geometric GAN
converges to a Nash equilibrium between the discriminator and generator. In
addition, extensive numerical results show that the superior performance of
geometric GAN.


  Limited surface observations of turbulent heat fluxes result in incomplete
knowledge about the surface energy balance that drives the climate system.
Here, we developed a novel, purely physics-based analytical method grounded on
the thermodynamic principle of maximum power. The approach derives the
turbulent heat flux only from the four inputs of incoming and outgoing
radiations at the land surface. The proposed approach does not use any
parameterization, unlike the existing surface energy balance models, and hence
does not suffer from uncertainty due to the same. We validated our methodology
with 102 eddy covariance observation stations around the globe with different
land use land covers. Using the satellite observations from CERES at a spatial
resolution of 1 degree, we have obtained spatially distributed global
analytical estimates of Sensible (H), latent heat (LE), and land surface heat
storage (delQs) fluxes for the first time. For a global observed land Net
radiation of 84 W/m2 from the satellite, we found H, LE and delQs to be 42
W/m2, 40 W/m2 and 2 W/m2, respectively. The theoretical and precise estimates
of all surface energy balance components will improve our understanding of
surface warming for different land use land covers across the globe.


  This Ph.D. thesis collects results obtained investigating two different
aspects of modern unifying theories. In the first part I summarized results
achieved investigating simplicial aspects of string dualities. Exploiting
Boundary Conformal Field Theory techniques, I investigated the coupling between
random Regge triangulations and open string theory, discussing its implications
in gauge/gravity correspondence. The second part reports results obtained in
the paper hep-th/0309237, devoted to look for cosmological backgrounds of
superstring theories.


  We prove a CR Obata type result that if the first positive eigenvalue of the
sub-Laplacian on a compact strictly pseudoconvex pseudohermitian manifold with
a divergence free pseudohermitian torsion takes the smallest possible value
then, up to a homothety of the pseudohermitian structure, the manifold is the
standart Sasakian unit sphere. We also give a version of this theorem using the
existence of a function with traceless horizontal Hessian on a complete, with
respect to Webster's metric, pseudohermitian manifold.


  Understanding the collective dynamics in a many-body system has been a
central task in condensed matter physics. To achieve this task, we develop a
Hartree-Fock theory to study the collective oscillations of spinor Fermi
system, motivated by recent experiment on spin-9/2 fermions. We observe an
oscillation period shoulder for small rotation angles. Different from previous
studies, where the shoulder is found connected to the resonance from periodic
to running phase, here the system is always in a running phase in the two-body
phase space. This shoulder survives even in the many-body oscillations, which
could be tested in the experiments. We also show how these collective
oscillations evolve from two- to many-body. Our theory provides an alternative
way to understand the collective dynamics in large-spin Fermi systems.


  We want to introduce an atomic pendulum whose driving force (torque) is due
to the quantum vacuum fluctuations. Applying the well-known Casimir-Polder
effect to a special configuration (a combined structure of an atomic nanostring
and a conducting plate), an atomic pendulum (Casimir atomic pendulum) is
designed. Using practically acceptable data corresponding to the already known
world of nanotechnology and based on reasonable/reliable numerical estimates,
the period of oscillation for the pendulum is computed. This pendulum can be
considered as both a new Micro (Nano)-Eelectromechanical system and a new
simple vacuum machine. Its design may be considered as a first step towards
realizing the visualized vacuum (Casimir) clock!


  In quantum information, lifting is a systematic procedure that can be used to
derive---when provided with a seed Bell inequality---other Bell inequalities
applicable in more complicated Bell scenarios. It is known that the procedure
of lifting introduced by Pironio [J. Math. Phys. A 46, 062112 (2005)] preserves
the facet-defining property of a Bell inequality. Lifted Bell inequalities
therefore represent a broad class of Bell inequalities that can be found in
{\em all} Bell scenarios. Here, we show that the maximal value of {\em any}
lifted Bell inequality is preserved for both the set of nonsignaling
correlations and quantum correlations. Despite the degeneracy in the maximizers
of such inequalities, we show that the ability to self-test a quantum state is
preserved under these lifting operations. In addition, except for
outcome-lifting, local measurements that are self-testable using the original
Bell inequality---despite the degeneracy---can also be self-tested using {\em
any} lifted Bell inequality derived therefrom. While it is not possible to
self-test {\em all} the positive-operator-valued measure elements using an
outcome-lifted Bell inequality, we show that partial, but robust self-testing
statements on the underlying measurements can nonetheless be made from the
quantum violation of these lifted inequalities. We also highlight the
implication of our observations on the usefulness of using lifted Bell-like
inequalities as a device-independent witnesses for entanglement depth. The
impact of the aforementioned degeneracy on the geometry of the quantum set of
correlations is briefly discussed.


  Modern speech enhancement algorithms achieve remarkable noise suppression by
means of large recurrent neural networks (RNNs). However, large RNNs limit
practical deployment in hearing aid hardware (HW) form-factors, which are
battery powered and run on resource-constrained microcontroller units (MCUs)
with limited memory capacity and compute capability. In this work, we use model
compression techniques to bridge this gap. We define the constraints imposed on
the RNN by the HW and describe a method to satisfy them. Although model
compression techniques are an active area of research, we are the first to
demonstrate their efficacy for RNN speech enhancement, using pruning and
integer quantization of weights/activations. We also demonstrate state update
skipping, which reduces the computational load. Finally, we conduct a
perceptual evaluation of the compressed models to verify audio quality on human
raters. Results show a reduction in model size and operations of 11.9$\times$
and 2.9$\times$, respectively, over the baseline for compressed models, without
a statistical difference in listening preference and only exhibiting a loss of
0.55dB SDR. Our model achieves a computational latency of 2.39ms, well within
the 10ms target and 351$\times$ better than previous work.


  Developing robot perception systems for recognizing objects in the real-world
requires computer vision algorithms to be carefully scrutinized with respect to
the expected operating domain. This demands large quantities of ground truth
data to rigorously evaluate the performance of algorithms. This paper presents
the EasyLabel tool for easily acquiring high quality ground truth annotation of
objects at the pixel-level in densely cluttered scenes. In a semi-automatic
process, complex scenes are incrementally built and EasyLabel exploits depth
change to extract precise object masks at each step. We use this tool to
generate the Object Cluttered Indoor Dataset (OCID) that captures diverse
settings of objects, background, context, sensor to scene distance, viewpoint
angle and lighting conditions. OCID is used to perform a systematic comparison
of existing object segmentation methods. The baseline comparison supports the
need for pixel- and object-wise annotation to progress robot vision towards
realistic applications. This insight reveals the usefulness of EasyLabel and
OCID to better understand the challenges that robots face in the real-world.
  Copyright 20XX IEEE. Personal use of this material is permitted. Permission
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works.


  In this paper proof of the twin prime conjecture is going to be presented.
Originally very difficult problem (in observational space) has been transformed
into a simpler one (in generative space) that can be solved. It will be shown
that twin primes could be obtained through two stage sieve process, and that
will be used to show that exist infinite number of twin primes. The same
approach is used to prove the Polignac's conjecture for cousin primes.


  The upcoming Wide-Field Upgrade (WFU) has ushered in a new era of
instrumentation for the Hobby-Eberly Telescope (HET). Here, we present the
design, construction progress, and lab tests completed to date of the
blue-optimized second generation Low Resolution Spectrograph (LRS2-B). LRS2-B
is a dual-channel, fiber fed instrument that is based on the design of the
Visible Integral Field Replicable Unit Spectrograph (VIRUS), which is the new
flagship instrument for carrying out the HET Dark Energy eXperiment (HETDEX).
LRS2-B utilizes a microlens-coupled integral field unit (IFU) that covers a
7"x12" area on the sky having unity fill-factor with ~300 spatial elements that
subsample the median HET image quality. The fiber feed assembly includes an
optimized dichroic beam splitter that allows LRS2-B to simultaneously observe
370 nm to 470 nm and 460 nm to 700 nm at fixed resolving powers of R \approx
1900 and 1200, respectively. We discuss the departures from the nominal VIRUS
design, which includes the IFU, fiber feed, camera correcting optics, and
volume phase holographic grisms. Additionally, the motivation for the selection
of the wavelength coverage and spectral resolution of the two channels is
briefly discussed. One such motivation is the follow-up study of spectrally and
(or) spatially resolved Lyman-alpha emission from z ~ 2.5 star-forming galaxies
in the HETDEX survey. LRS2-B is planned to be a commissioning instrument for
the HET WFU and should be on-sky during quarter 4 of 2013. Finally, we mention
the current state of LRS2-R, the red optimized sister instrument of LRS2-B.


  This paper proposes a new semi-analytical approach for online time-domain
power system simulation. The approach applies the differential transformation
method (DTM) to the power system differential equation model to offline derive
a semi-analytical solution (SAS) having symbolic variables about time, the
initial state and system conditions. When simulation is online needed for a
contingency under the current system condition, the SAS can be evaluated in
real time to generate simulation results. Compared to the Adomian decomposition
method in obtaining a power system SAS, an SAS derived by the DTM adopts a
recursive form to avoid generating and storing its complete symbolic
expression, which makes both derivation and evaluation of the SAS more
efficient especially for multi-machine power systems. The optimal order of a
DTM-based SAS is studied for the best time performance of simulation. The paper
also designs a parallel computing strategy for power system simulation using
the DTM-based SAS. Tests on the IEEE 10-machine 39-bus system demonstrate
significant speedup of simulation using the proposed approach compared with the
Runge-Kutta method.


  The warming trend of the last decades is now so strong that it is discernible
in local temperature observations. This opens the possibility to compare the
trend to the warming predicted by comprehensive climate models (GCMs), which up
to now could not be verified directly to observations on a local scale, because
the signal-to-noise ratio was too low. The observed temperature trend in
western Europe over the last decades appears much stronger than simulated by
state-of-the-art GCMs. The difference is very unlikely due to random
fluctuations, either in fast weather processes or in decadal climate
fluctuations. In winter and spring, changes in atmospheric circulation are
important; in spring and summer changes in soil moisture and cloud cover. A
misrepresentation of the North Atlantic Current affects trends along the coast.
Many of these processes continue to affect trends in projections for the 21st
century. This implies that climate predictions for western Europe probably
underestimate the effects of anthropogenic climate change.


  The electromagnetic (EM) signal of a binary neutron star (BNS) merger depends
sensitively on the total binary mass, $M_{\rm tot}$, relative to various
threshold masses set by the neutron star (NS) equation-of-state (EOS),
parameterized through the NS maximum mass, $M_{\rm TOV}$, and characteristic
radius, $R_{1.6}$. EM observations of a BNS merger detected through its
gravitational wave (GW) emission, which are of sufficient quality to ascertain
the identity of the merger remnant, can therefore constrain the values of
$M_{\rm TOV}$ and $R_{1.6}$, given the tight connection between $M_{\rm tot}$
and the well-measured chirp mass. We elucidate the present and future landscape
of EOS constraints from BNS mergers, introducing the "Multi-Messenger Matrix",
a mapping between GW and EM measurables that defines the ranges of event chirp
masses which provide the most leverage on constraining the EOS. By simulating a
population of BNS mergers drawn from the Galactic double NS mass distribution
we show that $\sim 10$ joint detections can constrain $M_{\rm TOV}$ and
$R_{1.6}$ to several percent level where systematic uncertainties may become
significant. Current EOS constraints imply that most mergers will produce
supramassive or hypermassive remnants, a smaller minority (possibly zero) will
undergo prompt-collapse, while at most only a few percent of events will form
indefinitely stable NSs. In support of the envisioned program, we advocate in
favor of LIGO/Virgo releasing chirp mass estimates as early as possible to the
scientific community, enabling observational resources to be allocated in the
most efficient way to maximize the scientific gain from multi-messenger
discoveries.


  The virtual viewpoint is perceived as a new technique in virtual navigation,
as yet not supported due to the lack of depth information and obscure camera
parameters. In this paper, a method for achieving close-up virtual view is
proposed and it only uses optical flow to build parallax effects to realize
pseudo 3D projection without using depth sensor. We develop a bidirectional
optical flow method to obtain any virtual viewpoint by proportional
interpolation of optical flow. Moreover, with the ingenious application of the
optical-flow-value, we achieve clear and visual-fidelity magnified results
through lens stretching in any corner, which overcomes the visual distortion
and image blur through viewpoint magnification and transition in Google Street
View system.


  Portfolio optimization is a primary component of the decision-making process
in finance, aiming to tactfully allocate assets to achieve optimal returns
while considering various constraints. Herein, we proposed a method that uses
the knapsack-based portfolio optimization problem and incorporates the quantum
computing capabilities of the quantum walk mixer with the quantum approximate
optimization algorithm (QAOA) to address the challenges presented by the
NP-hard problem. Additionally, we present the sequential procedure of our
suggested approach and demonstrate empirical proof to illustrate the
effectiveness of the proposed method in finding the optimal asset allocations
across various constraints and asset choices. Moreover, we discuss the
effectiveness of the QAOA components in relation to our proposed method.
Consequently, our study successfully achieves the approximate ratio of the
portfolio optimization technique using a circuit layer of p >= 3, compared to
the classical best-known solution of the knapsack problem. Our proposed methods
potentially contribute to the growing field of quantum finance by offering
insights into the potential benefits of employing quantum algorithms for
complex optimization tasks in financial portfolio management.


  We obtain several essential self-adjointness conditions for a Schroedinger
type operator D*D+V acting in sections of a vector bundle over a manifold M.
Here V is a locally square-integrable bundle map. Our conditions are expressed
in terms of completeness of certain metrics on M; these metrics are naturally
associated to the operator. We do not assume a priori that M is endowed with a
complete Riemannian metric. This allows us to treat e.g. operators acting on
bounded domains in the euclidean space.
  For the case when the principal symbol of the operator is scalar, we
establish more precise results. The proofs are based on an extension of the
Kato inequality which modifies and improves a result of Hess, Schrader and
Uhlenbrock.


  The ablation of solid tin surfaces by an 800-nanometer-wavelength laser is
studied for a pulse length range from 500 fs to 4.5 ps and a fluence range
spanning 0.9 to 22 J/cm^2. The ablation depth and volume are obtained employing
a high-numerical-aperture optical microscope, while the ion yield and energy
distributions are obtained from a set of Faraday cups set up under various
angles. We found a slight increase of the ion yield for an increasing pulse
length, while the ablation depth is slightly decreasing. The ablation volume
remained constant as a function of pulse length. The ablation depth follows a
two-region logarithmic dependence on the fluence, in agreement with the
available literature and theory. In the examined fluence range, the ion yield
angular distribution is sharply peaked along the target normal at low fluences
but rapidly broadens with increasing fluence. The total ionization fraction
increases monotonically with fluence to a 5-6% maximum, which is substantially
lower than the typical ionization fractions obtained with nanosecond-pulse
ablation. The angular distribution of the ions does not depend on the laser
pulse length within the measurement uncertainty. These results are of
particular interest for the possible utilization of fs-ps laser systems in
plasma sources of extreme ultraviolet light for nanolithography.


  We consider the problem of inference for nonlinear, multivariate diffusion
processes, satisfying It\^o stochastic differential equations (SDEs), using
data at discrete times that may be incomplete and subject to measurement error.
Our starting point is a state-of-the-art correlated pseudo-marginal
Metropolis-Hastings algorithm, that uses correlated particle filters to induce
strong and positive correlation between successive likelihood estimates.
However, unless the measurement error or the dimension of the SDE is small,
correlation can be eroded by the resampling steps in the particle filter. We
therefore propose a novel augmentation scheme, that allows for conditioning on
values of the latent process at the observation times, completely avoiding the
need for resampling steps. We integrate over the uncertainty at the observation
times with an additional Gibbs step. Connections between the resulting
pseudo-marginal scheme and existing inference schemes for diffusion processes
are made, giving a unified inference framework that encompasses Gibbs sampling
and pseudo marginal schemes. The methodology is applied in three examples of
increasing complexity. We find that our approach offers substantial increases
in overall efficiency, compared to competing methods.


  We study non-interacting automorphic quantum scalar fields with positive mass
in two-dimensional de Sitter space. We find that there are no Hadamard states
which are de Sitter invariant except in the periodic case, extending the result
of Epstein and Moschella for the anti-periodic case. We construct the two-point
Wightman functions for the non-Hadamard de Sitter-invariant states by
exploiting the fact that they are functions of the geodesic distance between
the two points satisfying an ordinary differential equation. We then examine a
certain Hadamard state, which is not de Sitter invariant, and show that it is
approximately a thermal state with the Gibbons-Hawking temperature when
restricted to a static region of the spacetime.


  Network pruning is an effective measure to alleviate the storage and
computational burden of deep neural networks arising from its high
overparameterization. Thus raises a fundamental question: How sparse can we
prune a deep network without sacrifice on the performance? To address this
problem, in this work we'll take a first principles approach, i.e. we directly
impose the sparsity constraint on the original loss function and then
characterize the necessary and sufficient condition of the sparsity
(\textit{which turns out to nearly coincide}) by leveraging the notion of
\textit{statistical dimension} in convex geometry. Through this fundamental
limit, we're able to identify two key factors that determine the pruning ratio
limit, i.e., weight magnitude and network flatness. Generally speaking, the
flatter the loss landscape or the smaller the weight magnitude, the smaller
pruning ratio. In addition, we provide efficient countermeasures to address the
challenges in computing the pruning limit, which involves accurate spectrum
estimation of a large-scale and non-positive Hessian matrix. Moreover, through
the lens of the pruning ratio threshold, we can provide rigorous
interpretations on several heuristics in existing pruning algorithms. Extensive
experiments are performed that demonstrate that the our theoretical pruning
ratio threshold coincides very well with the experiments. All codes are
available at: https://github.com/QiaozheZhang/Global-One-shot-Pruning


  Fluorescent nuclear track detectors (FNTDs) based on Al2O3:C,Mg single
crystal combined with confocal microscopy provide 3D information on ion tracks
with a resolution only limited by light diffraction. FNTDs are also ideal
substrates to be coated with cells to engineer cell-fluorescent ion track
hybrid detectors. This radiobiological tool enables a novel platform linking
cell responses to physical dose deposition on a sub-cellular level in proton
and heavy ion therapies. To achieve spatial correlation between single ion hits
in the cell coating and its biological response the ion traversals have to be
reconstructed in 3D using the depth information gained by the FNTD read-out.
FNTDs were coated with a confluent human lung adenocarcinoma epithelial cell
layer. Carbon ion irradiation of the hybrid detector was performed
perpendicular and angular to the detector surface. In-situ imaging of the
fluorescently labeled cell layer and the FNTD was performed in a sequential
read-out. Making use of the trajectory information provided by the FNTD the
accuracy of 3D track reconstruction of single particles traversing the hybrid
detector was studied. The accuracy is strongly influenced by the irradiation
angle and therefore by complexity of the FNTD signal. Perpendicular irradiation
results in highest accuracy with error of smaller than 0.10{\deg}. The ability
of FNTD technology to provide accurate 3D ion track reconstruction makes it a
powerful tool for radiobiological investigations in clinical ion beams, either
being used as a substrate to be coated with living tissue or being implanted in
vivo.


  This work presents a family of parsimonious Gaussian process models which
allow to build, from a finite sample, a model-based classifier in an infinite
dimensional space. The proposed parsimonious models are obtained by
constraining the eigen-decomposition of the Gaussian processes modeling each
class. This allows in particular to use non-linear mapping functions which
project the observations into infinite dimensional spaces. It is also
demonstrated that the building of the classifier can be directly done from the
observation space through a kernel function. The proposed classification method
is thus able to classify data of various types such as categorical data,
functional data or networks. Furthermore, it is possible to classify mixed data
by combining different kernels. The methodology is as well extended to the
unsupervised classification case. Experimental results on various data sets
demonstrate the effectiveness of the proposed method.


  The presence of dual active galactic nuclei (AGN) on scales of a few tens of
kpc can be used to study merger-induced accretion on supermassive black holes
(SMBHs) and offer insights about SMBH mergers, using dual AGNs as merger
precursors. In this study, we use the Romulus25 cosmological simulation to
investigate the properties and evolution of dual AGNs. We first analyze the
properties of AGNs ($L_{bol} > 10^{43} \rm erg/s$) and their neighboring SMBHs
(any SMBHs closer than 30 pkpc to an AGN) at $z \leq 2$. This is our underlying
population. Subsequently, we applied the luminosity threshold of $L_{bol} >
10^{43} erg/s$ to the neighboring SMBHs thereby identifying dual and multiple
AGNs in our simulation. We examined the properties and statistics of dual AGNs
in comparison to single AGNs. Our findings indicate an increase in the number
of both single and dual AGNs from lower to higher redshifts. All dual AGNs in
our sample resulted from major mergers. Compared with the single AGN
population, duals are characterized by a lower black hole to halo mass ratio.
We found that the properties of dual AGN host halos, including halo mass,
stellar mass, star formation rate (SFR), and gas mass, are generally consistent
with those of single AGN halos, albeit tending towards the higher end of their
respective property ranges. Our analysis uncovered a diverse array of
evolutionary patterns among dual AGNs, including rapidly evolving systems,
slower ones, and instances where SMBH mergers are ineffective.


  In this letter, we investigate the millimeter wave (mmWave) downlink
multiuser multiple-input multiple-output (MU-MIMO) system, adopting the dynamic
subarray architecture at the base station and considering the multi-stream
communication for each user. Aiming at maximizing the system spectral
efficiency, we propose a novel hybrid beamforming design. First, assuming no
inter-user interference (IUI), we easily get the optimal fully-digital
beamformers and combiners using the singular value decomposition of each user
channel and the waterfilling algorithm. Then, based on the obtained
fullydigital beamformers, we propose a Kuhn-Munkres algorithmassisted dynamic
hybrid beamforming design, which guarantees that each radio-frequency chain is
connected to at least one antenna. Finally, we propose to further project each
obtained digital beamformer onto the null space of all the other equivalent
user channels to cancel the IUI. Numerical results verify the superiority of
our proposed hybrid beamforming design.


  Experimental studies of synchronization properties on networks with
controlled connection topology can provide powerful insights into the physics
of complex networks. Here, we report experimental results on the influence of
connection topology on synchronization in fiber-optic networks of chaotic
optoelectronic oscillators. We find that the recently predicted non-monotonic,
cusp-like synchronization landscape manifests itself in the rate of convergence
to the synchronous state. We also observe that networks with the same number of
nodes, same number of links, and identical eigenvalues of the coupling matrix
can exhibit fundamentally different approaches to synchronization. This
previously unnoticed difference is determined by the degeneracy of associated
eigenvectors in the presence of noise and mismatches encountered in real-world
conditions.


  This paper presents the design, fabrication, and experimental
characterization of a peristaltic micropump. The micropump is composed of two
layers fabricated from polydimethylsiloxane (PDMS) material. The first layer
has a rectangular channel and two valve seals. Three rectangular mini
lightweight piezo-composite actuators are integrated in the second layer, and
used as actuation parts. Two layers are bonded, and covered by two polymethyl
methacrylate (PMMA) plates, which help increase the stiffness of the micropump.
A maximum flow rate of 900 mokroliter per min and a maximum backpressure of 1.8
kPa are recorded when water is used as pump liquid. We measured the power
consumption of the micropump. The micropump is found to be a promising
candidate for bio-medical application due to its bio-compatibility,
portability, bidirectionality, and simple effective design.


  The variety of minimal rational tangents associated to Hecke curves was used
by J.-M.Hwang [8] to prove the simplicity of the tangent bundle on the moduli
of vector bundles over a curve. In this paper, we use the tangent maps of the
symplectic and orthogonal Hecke curves to prove an analogous result for
symplectic and orthogonal bundles. In particular, we show the nondegeneracy of
the associated variety of minimal rational tangents, which implies the
simplicity of the tangent bundle on the moduli spaces of symplectic and
orthogonal bundles over a curve. We also show that for large enough genus, the
tangent map is an embedding for a general symplectic or orthogonal bundle.


  We report our in-depth study of Cd-Zn-Te (CZT) crystals to determine an
optimum pixel and guard band configuration for Hard X-ray imaging and
spectroscopy. We tested 20x20x5mm crystals with 8x8 pixels on a 2.46mm pitch.
We have studied different types of cathode / anode contacts and different pixel
pad sizes. We present the measurements of leakage current as well as spectral
response for each pixel. Our I-V measurement setup is custom designed to allow
automated measurements of the I-V curves sequentially for all 64 pixels,
whereas the radiation properties measurement setup allows for interchangeable
crystals with the same XAIM3.2 ASIC readout from IDEAS. We have tested multiple
crystals of each type, and each crystal in different positions to measure the
variation between individual crystals and variation among the ASIC channels. We
also compare the same crystals with and without a grounded guard band deposited
on the crystal side walls vs. a floating guard band and compare results to
simulations. This study was carried out to find the optimum CZT crystal
configuration for prototype detectors for the proposed Black-Hole Finder
mission, EXIST.


  We prove the existence of a traveling wave solution for a boundary reaction
diffusion equation when the reaction term is the combustion nonlinearity with
ignition temperature. A key role in the proof is plaid by an explicit formula
for traveling wave solutions of a free boundary problem obtained as singular
limit for the reaction-diffusion equation (the so-called high energy activation
energy limit). This explicit formula, which is interesting in itself, also
allows us to get an estimate on the decay at infinity of the traveling wave
(which turns out to be faster than the usual exponential decay).


  Let $k$ be a number field. We construct homogeneous spaces of $SL_{n,k}$ with
finite nilpotent non-abelian stabilizers for which the Brauer-Manin obstruction
does not explain the failure of strong approximation (resp. the failure of the
integral Hasse principle).


  We study the Hamiltonian formalism for second order and fourth order
nonlinear Schr\"{o}dinger equations. In the case of second order equation, we
consider cubic and logarithmic nonlinearities. Since the Lagrangians generating
these nonlinear equations are degenerate, we follow the Dirac-Bergmann
formalism to construct their corresponding Hamiltonians. In order to obtain
consistent equations of motion, the Dirac-Bergmann formalism imposes some set
of constraints which contribute to the total Hamiltonian along with their
Lagrange multipliers. The order of the Lagrangian degeneracy determines the
number of the primary constraints. Multipliers are determined by the time
consistency of constraints. If a constraint is not a constant of motion, a
secondary constraint is introduced to force the consistency. We show that for
both second order nonlinear Schr\"{o}dinger equations we only have primary
constraints, and the form of nonlinearity does not change the constraint
dynamics of the system. However, introducing a higher order dispersion changes
the constraint dynamics and secondary constraints are needed to construct a
consistent Hamilton equations of motion.


  As the use of cloud computing continues to rise, controlling cost becomes
increasingly important. Yet there is evidence that 30\% - 45\% of cloud spend
is wasted. Existing tools for cloud provisioning typically rely on highly
trained human experts to specify what to monitor, thresholds for triggering
action, and actions. In this paper we explore the use of reinforcement learning
(RL) to acquire policies to balance performance and spend, allowing humans to
specify what they want as opposed to how to do it, minimizing the need for
cloud expertise. Empirical results with tabular, deep, and dueling double deep
Q-learning with the CloudSim simulator show the utility of RL and the relative
merits of the approaches. We also demonstrate effective policy transfer
learning from an extremely simple simulator to CloudSim, with the next step
being transfer from CloudSim to an Amazon Web Services physical environment.


  As with any black hole, asymptotically anti-de Sitter Kerr black holes are
described by a small number of parameters, including a "mass parameter" $M$
that reduces to the AdS-Schwarzschild mass in the limit of vanishing angular
momentum. In sharp contrast to the asymptotically flat case, the horizon area
of such a black hole increases with the angular momentum parameter $a$ if one
fixes $M$, this appears to mean that the Penrose process in this case would
violate the Second Law of black hole thermodynamics. We show that the correct
procedure is to fix not $M$ but rather the "physical" mass $E=M/(1-a^2/L^2)^2$,
this is motivated by the First Law. For then the horizon area decreases with
$a$. We recommend that $E$ always be used as the mass in physical processes:
for example, in attempts to "over-spin" AdS-Kerr black holes.


  The tree-level q-map assigns to a projective special real (PSR) manifold of
dimension $n-1\geq 0$, a quaternionic K\"{a}hler (QK) manifold of dimension
$4n+4$. It is known that the resulting QK manifold admits a
$(3n+5)$-dimensional universal group of isometries (i.e. independently of the
choice of PSR manifold). On the other hand, in the context of Calabi-Yau
compactifications of type IIB string theory, the classical hypermultiplet
moduli space metric is an instance of a tree-level q-map space, and it is known
from the physics literature that such a metric has an
$\mathrm{SL}(2,\mathbb{R})$ group of isometries related to the
$\mathrm{SL}(2,\mathbb{Z})$ S-duality symmetry of the full 10d theory. We
present a purely mathematical proof that any tree-level q-map space admits such
an $\mathrm{SL}(2,\mathbb{R})$ action by isometries, enlarging the previous
universal group of isometries to a $(3n+6)$-dimensional group $G$. As part of
this analysis, we describe how the $(3n+5)$-dimensional subgroup interacts with
the $\mathrm{SL}(2,\mathbb{R})$-action, and find a codimension one normal
subgroup of $G$ that is unimodular. By taking a quotient with respect to a
lattice in the unimodular group, we obtain a quaternionic K\"ahler manifold
fibering over a projective special real manifold with fibers of finite volume,
and compute the volume as a function of the base. We furthermore provide a
mathematical treatment of results from the physics literature concerning the
twistor space of the tree-level q-map space and the holomorphic lift of the
$(3n+6)$-dimensional group of universal isometries to the twistor space.