  In this paper, we introduce a new combinatorial curvature on triangulated
surfaces with inversive distance circle packing metrics. Then we prove that
this combinatorial curvature has global rigidity. To study the Yamabe problem
of the new curvature, we introduce a combinatorial Ricci flow, along which the
curvature evolves almost in the same way as that of scalar curvature along the
surface Ricci flow obtained by Hamilton \cite{Ham1}. Then we study the long
time behavior of the combinatorial Ricci flow and obtain that the existence of
a constant curvature metric is equivalent to the convergence of the flow on
triangulated surfaces with nonpositive Euler number. We further generalize the
combinatorial curvature to $\alpha$-curvature and prove that it is also
globally rigid, which is in fact a generalized Bower-Stephenson conjecture
\cite{BS}. We also use the combinatorial Ricci flow to study the corresponding
$\alpha$-Yamabe problem.


  We construct many irreducible polynomials within semigroups generated by sets
of the form $S=\{x^2+c_1,\dots,x^2+c_s\}$ under composition.


  The results of the spectral, energetical and temporal characteristics of
radiation in the presence of the photonic flame effect are presented.
Artificial opal posed on Cu plate at the temperature of liquid nitrogen boiling
point (77 K) being irradiated by nanosecond ruby laser pulse produces long-
term luminiscence with a duration till ten seconds with a finely structured
spectrum in the the antistocks part of the spectrum. Analogous visible
luminescence manifesting time delay appeared in other samples of the artificial
opals posed on the same plate. In the case of the opal infiltrated with
different nonlinear liquids the threshold of the luminiscence is reduced and
the spatial disribution of the bright emmiting area on the opal surface is
being changed. In the case of the putting the frozen nonlinear liquids on the
Cu plate long-term blue bright luminiscence took place in the frozen species of
the liquids. Temporal characteristics of this luminiscence are nearly the same
as in opal matrixes.


  Jupiter's banded structure undergoes strong temporal variations, changing the
visible and infrared appearance of the belts and zones in a complex and
turbulent way due to physical processes that are not yet understood. In this
study we use ground-based 5-$\mu$m infrared data captured between 1984 and 2018
by 8 different instruments mounted on the Infrared Telescope Facility in
Hawai'i and on the Very Large Telescope in Chile to analyze and characterize
the long-term variability of Jupiter's cloud-forming region at the 1-4 bar
pressure level. The data show a large temporal variability mainly at the
equatorial and tropical latitudes, with a smaller temporal variability at
mid-latitudes. We also compare the 5-$\mu$m-bright and -dark regions with the
locations of the visible zones and belts and we find that these regions are not
always co-located, specially in the southern hemisphere. We also present
Lomb-Scargle and Wavelet Transform analyzes in order to look for possible
periodicities of the brightness changes that could help us understand their
origin and predict future events. We see that some of these variations occur
periodically in time intervals of 4-8 years. The reasons of these time
intervals are not understood and we explore potential connections to both
convective processes in the deeper weather layer and dynamical processes in the
upper troposphere and stratosphere. Finally we perform a Principal Component
analysis to reveal a clear anticorrelation on the 5-$\mu$m brightness changes
between the North Equatorial Belt and the South Equatorial Belt, suggesting a
possible connection between the changes in these belts.


  In this article we study the local stabilization of the non-homogeneous
Navier- Stokes equations in a 2d channel around Poiseuille flow. We design a
feedback control of the velocity which acts on the inflow boundary of the
domain such that both the fluid velocity and density are stabilized around
Poiseuille flow provided the initial density is given by a constant added with
a perturbation, such that the perturbation is supported away from the lateral
boundary of the channel. Moreover the feedback control operator we construct
has finite dimensional range.


  We study b, c quark hadronization from QGP. We obtain the yields of charm and
bottom flavored hadrons within the statistical hadronization model. The
important novel feature of this study is that we take into account the high
strangeness and entropy content of QGP, conserving strangeness and entropy
yields at hadronization.


  We measure the frequencies of small-amplitude shape oscillations of a
magnetically-levitated water droplet. The droplet levitates in a
magnetogravitational potential trap. The restoring forces of the trap, acting
on the droplet's surface in addition to the surface tension, increase the
frequency of the oscillations. We derive the eigenfrequencies of the normal
mode vibrations of a spherical droplet in the trap and compare them with our
experimental measurements. We also consider the effect of the shape of the
potential trap on the eigenfrequencies.


  This paper proposes a novel transformer-based model architecture for medical
imaging problems involving analysis of vertebrae. It considers two applications
of such models in MR images: (a) detection of spinal metastases and the related
conditions of vertebral fractures and metastatic cord compression, (b)
radiological grading of common degenerative changes in intervertebral discs.
Our contributions are as follows: (i) We propose a Spinal Context Transformer
(SCT), a deep-learning architecture suited for the analysis of repeated
anatomical structures in medical imaging such as vertebral bodies (VBs). Unlike
previous related methods, SCT considers all VBs as viewed in all available
image modalities together, making predictions for each based on context from
the rest of the spinal column and all available imaging modalities. (ii) We
apply the architecture to a novel and important task: detecting spinal
metastases and the related conditions of cord compression and vertebral
fractures/collapse from multi-series spinal MR scans. This is done using
annotations extracted from free-text radiological reports as opposed to bespoke
annotation. However, the resulting model shows strong agreement with
vertebral-level bespoke radiologist annotations on the test set. (iii) We also
apply SCT to an existing problem: radiological grading of inter-vertebral discs
(IVDs) in lumbar MR scans for common degenerative changes.We show that by
considering the context of vertebral bodies in the image, SCT improves the
accuracy for several gradings compared to previously published model.


  If $X$ is a non-degenerate vector field on ${\bf R}$ and $H=-X^2$ we examine
conditions for the closure of $H$ to generate a continuous semigroup on
$L_\infty$ which extends to the $L_p$-spaces. We give an example which cannot
be extended and an example which extends but for which the real part of the
generator on $L_2$ is not lower semibounded.


  In this review we describe recent observational and theoretical developments
in our understanding of pulsar winds and pulsar-wind nebulae (PWNe). We put
special emphasis on the results from observations of well-characterized PWNe of
various types (e.g., torus-jet and bowshock-tail), the most recent MHD modeling
efforts, and the status of the flaring Crab PWN puzzle.


  We present a simple mechanism for obtaining large-field inflation, and hence
a gravitational wave signature, from string theory compactified on twisted
tori. For Nil manifolds, we obtain a leading inflationary potential
proportional to phi^(2/3) in terms of the canonically normalized field phi,
yielding predictions for the tilt of the power spectrum and the
tensor-to-scalar ratio, $n_s\approx 0.98$ and $r\approx 0.04$ with 60
e-foldings of inflation; we note also the possibility of a variant with a
candidate inflaton potential proportional to phi^(2/5). The basic mechanism
involved in extending the field range -- monodromy in D-branes as they move in
circles on the manifold -- arises in a more general class of compactifications,
though our methods for controlling the corrections to the slow-roll parameters
require additional symmetries.


  In this paper, we tackle the following problem: compute the gcd for several
univariate polynomials with parametric coefficients. It amounts to partitioning
the parameter space into ``cells'' so that the gcd has a uniform expression
over each cell and constructing a uniform expression of gcd in each cell. We
tackle the problem as follows. We begin by making a natural and obvious
extension of subresultant polynomials of two polynomials to several
polynomials. Then we develop the following structural theories about them.
  1. We generalize Sylvester's theory to several polynomials, in order to
obtain an elegant relationship between generalized subresultant polynomials and
the gcd of several polynomials, yielding an elegant algorithm.
  2. We generalize Habicht's theory to several polynomials, in order to obtain
a systematic relationship between generalized subresultant polynomials and
pseudo-remainders, yielding an efficient algorithm.
  Using the generalized theories, we present a simple (structurally elegant)
algorithm which is significantly more efficient (both in the output size and
computing time) than algorithms based on previous approaches.


  In reinforcement learning, wrappers are universally used to transform the
information that passes between a model and an environment. Despite their
ubiquity, no library exists with reasonable implementations of all popular
preprocessing methods. This leads to unnecessary bugs, code inefficiencies, and
wasted developer time. Accordingly we introduce SuperSuit, a Python library
that includes all popular wrappers, and wrappers that can easily apply lambda
functions to the observations/actions/reward. It's compatible with the standard
Gym environment specification, as well as the PettingZoo specification for
multi-agent environments. The library is available at
https://github.com/PettingZoo-Team/SuperSuit,and can be installed via pip.


  We consider rather general spin-$1/2$ lattices with large coordination
numbers $Z$. Based on the monogamy of entanglement and other properties of the
concurrence $C$, we derive rigorous bounds for the entanglement between
neighboring spins, such as $C\leq 1/\sqrt{Z}$, which show that $C$ decreases
for large $Z$. In addition, the concurrence $C$ measures the deviation from
mean-field behavior and can only vanish if the mean-field ansatz yields an
exact ground state of the Hamiltonian. Motivated by these findings, we propose
an improved mean-field ansatz by adding entanglement.


  Summarizing multiple disaster-relevant data streams simultaneously is
particularly challenging as existing Retrieve&Re-ranking strategies suffer from
the inherent redundancy of multi-stream data and limited scalability in a
multi-query setting. This work proposes an online approach to crisis timeline
generation based on weak annotation with Deep Q-Networks. It selects on-the-fly
the relevant pieces of text without requiring neither human annotations nor
content re-ranking. This makes the inference time independent of the number of
input queries. The proposed approach also incorporates a redundancy filter into
the reward function to effectively handle cross-stream content overlaps. The
achieved ROUGE and BERTScore results are superior to those of best-performing
models on the CrisisFACTS 2022 benchmark.


  We show that models of new particle physics containing massless pseudoscalar
fields super-weakly coupled to photons can be very efficiently probed with CMB
polarization anisotropies. The stochastic pseudoscalar fluctuations generated
during inflation provide a mechanism for converting E-mode polarization to
B-mode during photon propagation from the surface of last scattering. The
efficiency of this conversion process is controlled by the dimensionless ratio
H/(2\pi f_a), where H is the Hubble scale during inflation, and f_a^{-1} is the
strength of the pseudoscalar coupling to photons. The current observational
limits on the B-mode constrain this ratio to be less than 0.07, which in many
models of inflation translates to a sensitivity to values of f_a in excess of
10^{14} GeV, surpassing the sensitivity of other tests.


  We discuss several problems in quasiclassical physics for which approximate
solutions were recently obtained by a new method, and which can also be solved
by novel versions of the Born-Oppenheimer approximation. These cases include
the so-called bouncing ball modes, low angular momentum states in perturbed
circular billiards, resonant states in perturbed rectangular billiards, and
whispering gallery modes. Some rare, special eigenstates, concentrated close to
the edge or along a diagonal of a nearly rectangular billiard are found. This
kind of state has apparently previously escaped notice.


  Uncertainty quantification (UQ) is a vital step in using mathematical models
and simulations to take decisions. The field of cardiac simulation has begun to
explore and adopt UQ methods to characterise uncertainty in model inputs and
how that propagates through to outputs or predictions. In this perspective
piece we draw attention to an important and under-addressed source of
uncertainty in our predictions -- that of uncertainty in the model structure or
the equations themselves. The difference between imperfect models and reality
is termed model discrepancy, and we are often uncertain as to the size and
consequences of this discrepancy. Here we provide two examples of the
consequences of discrepancy when calibrating models at the ion channel and
action potential scales. Furthermore, we attempt to account for this
discrepancy when calibrating and validating an ion channel model using
different methods, based on modelling the discrepancy using Gaussian processes
(GPs) and autoregressive-moving-average (ARMA) models, then highlight the
advantages and shortcomings of each approach. Finally, suggestions and lines of
enquiry for future work are provided.


  Using the technique of finite field dependent BRST transformations we show
that the classical massive Yang-Mills theory and the pure Yang-Mills theory
whose gauge symmetry is broken by a gauge fixing term are identical from the
view point of quantum gauge symmetry. The explicit infinitesimal
transformations which leave the massive Yang-Mills theory BRST invariant are
given.


  We investigate the addition of constraints on the function image and its
derivatives for the incorporation of prior knowledge in symbolic regression.
The approach is called shape-constrained symbolic regression and allows us to
enforce e.g. monotonicity of the function over selected inputs. The aim is to
find models which conform to expected behaviour and which have improved
extrapolation capabilities. We demonstrate the feasibility of the idea and
propose and compare two evolutionary algorithms for shape-constrained symbolic
regression: i) an extension of tree-based genetic programming which discards
infeasible solutions in the selection step, and ii) a two population
evolutionary algorithm that separates the feasible from the infeasible
solutions. In both algorithms we use interval arithmetic to approximate bounds
for models and their partial derivatives. The algorithms are tested on a set of
19 synthetic and four real-world regression problems. Both algorithms are able
to identify models which conform to shape constraints which is not the case for
the unmodified symbolic regression algorithms. However, the predictive accuracy
of models with constraints is worse on the training set and the test set.
Shape-constrained polynomial regression produces the best results for the test
set but also significantly larger models.


  Tuning machine parameters of particle accelerators is a repetitive and
time-consuming task that is challenging to automate. While many off-the-shelf
optimization algorithms are available, in practice their use is limited because
most methods do not account for safety-critical constraints in each iteration,
such as loss signals or step-size limitations. One notable exception is safe
Bayesian optimization, which is a data-driven tuning approach for global
optimization with noisy feedback. We propose and evaluate a step-size limited
variant of safe Bayesian optimization on two research facilities of the Paul
Scherrer Institut (PSI): a) the Swiss Free Electron Laser (SwissFEL) and b) the
High-Intensity Proton Accelerator (HIPA). We report promising experimental
results on both machines, tuning up to 16 parameters subject to 224
constraints.


  We present a global study of the simplest scalar phantom dark matter model.
The best fit parameters of the model are determined by simultaneously imposing
(i) relic density constraint from WMAP, (ii) 225 live days data from direct
experiment XENON100, (iii) upper limit of gamma-ray flux from Fermi-LAT
indirect detection based on dwarf spheroidal satellite galaxies, and (iv) the
Higgs boson candidate with a mass about 125 GeV and its invisible branching
ratio no larger than 40% if the decay of the Higgs boson into a pair of dark
matter is kinematically allowed. The allowed parameter space is then used to
predict annihilation cross sections for gamma-ray lines, event rates for three
processes mono-b jet, single charged lepton and two charged leptons plus
missing energies at the Large Hadron Collider, as well as to evaluate the muon
anomalous magnetic dipole moment for the model.


  We investigate the baryon asymmetry in the supersymmetry
Dine-Fischler-Srednicki-Zhitnitsky axion model without R-parity. It turns out
that the R-parity violating terms economically explain the atmospheric
mass-squared difference of neutrinos and the appropriate amount of baryon
asymmetry through the Affleck-Dine mechanism. In this model, the axion is a
promising candidate for the dark matter and the axion isocurvature perturbation
is suppressed due to the large field values of Peccei-Quinn fields. Remarkably,
in some parameter regions explaining the baryon asymmetry and the axion dark
matter abundance, the proton decay will be explored in future experiments.


  Multialgebras (or hyperalgebras, or non-deterministic algebras) have been
very much studied in Mathematics and in Computer Science. In 2016 Carnielli and
Coniglio introduced a class of multialgebras called swap structures, as a
semantic framework for dealing with several logics of formal inconsistency (or
LFIs) which cannot be semantically characterized by a single finite matrix. In
particular, these LFIs are not algebraizable by the standard tools of abstract
algebraic logic. In this paper, the first steps towards a theory of
non-deterministic algebraization of logics by swap structures are given.
Specifically, a formal study of swap structures for LFIs is developed, by
adapting concepts of universal algebra to multialgebras in a suitable way. A
decomposition theorem similar to Birkhoff's representation theorem is obtained
for each class of swap structures. Moreover, when applied to the 3-valued
algebraizable logic J3 the usual class of algebraic models is recovered, and
the swap structures semantics became twist-structures semantics (as introduced
by Fidel-Vakarelov). This fact, together with the existence of a functor from
the category of Boolean algebras to the category of swap structures for each
LFI, which is closely connected with Kalman's functor, suggests that swap
structures can be considered as non-deterministic twist structures, opening so
interesting possibilities for dealing with non-algebraizable logics by means of
multialgebraic semantics.


  Weakly supervised video anomaly detection aims to identify abnormal events in
videos using only video-level labels. Recently, two-stage self-training methods
have achieved significant improvements by self-generating pseudo labels and
self-refining anomaly scores with these labels. As the pseudo labels play a
crucial role, we propose an enhancement framework by exploiting completeness
and uncertainty properties for effective self-training. Specifically, we first
design a multi-head classification module (each head serves as a classifier)
with a diversity loss to maximize the distribution differences of predicted
pseudo labels across heads. This encourages the generated pseudo labels to
cover as many abnormal events as possible. We then devise an iterative
uncertainty pseudo label refinement strategy, which improves not only the
initial pseudo labels but also the updated ones obtained by the desired
classifier in the second stage. Extensive experimental results demonstrate the
proposed method performs favorably against state-of-the-art approaches on the
UCF-Crime, TAD, and XD-Violence benchmark datasets.


  The resonant band is a useful notion for the computation of the nontrivial
monodromy eigenspaces of the Milnor fiber of a real line arrangement. In this
article, we develop the resonant band description for the cohomology of the
Aomoto complex. As an application, we prove that real 4-nets do not exist.


  Dilation surfaces are geometric surfaces modelled after the complex plane
whose structure group is generated by the groups of translations and dilations.
For any dilation surface, for any direction $\theta$ in $S^1$, there exists a
foliation on the surface called the directional foliation in direction
$\theta$. In this Thesis, we prove a structure theorem for the directional
foliations on dilation surfaces using a decomposition theorem established by
C.J. Gardiner in the 1980s. We show that given a directional foliation on any
dilation surface, there exists a decomposition of the surface into finitely
many subsurfaces on which the foliation structure is in one of four possible
cases: completely periodic, Morse-Smale, minimal or Cantor-like. We further
prove that in the last two cases, the first return map on a segment transversal
to the foliation is semi-conjugated to a minimal interval exchange
transformation. As a corollary, we obtain an analogous result for affine
interval exchange transformations. Throughout the thesis, we accompany our
results with an explicit example of a dilation surface called the Disco
surface. We analyze the directional foliations on the Disco surface that
exhibit non-trivially recurrent behaviour and explain geometrically why these
foliations accumulate to a Cantor set.


  We argue that brane anti-brane inflation in string theory de-Sitter vacua of
Kachru-Kallosh-Linde-Trivedi (KKLT) is captured by the dynamics of a D3-brane
probe in the local KKLT model constructed in hep-th/0203041. This provides a
framework to study in a controllable way corrections to the inflationary slow
roll parameter \eta due to conformal symmetry breaking in a warped geometry
throat. We compute the leading correction to \eta for the inflation in the
Klebanov-Tseytlin throat geometry. We find that in certain regime this
correction tends to decrease \eta. Computations in a different regime suggest
however that it is unlikely that \eta << 1 can be achieved with the D3-brane
throat inflation.


  Autonomous vehicles often make complex decisions via machine learning-based
predictive models applied to collected sensor data. While this combination of
methods provides a foundation for real-time actions, self-driving behavior
primarily remains opaque to end users. In this sense, explainability of
real-time decisions is a crucial and natural requirement for building trust in
autonomous vehicles. Moreover, as autonomous vehicles still cause serious
traffic accidents for various reasons, timely conveyance of upcoming hazards to
road users can help improve scene understanding and prevent potential risks.
Hence, there is also a need to supply autonomous vehicles with user-friendly
interfaces for effective human-machine teaming. Motivated by this problem, we
study the role of explainable AI and human-machine interface jointly in
building trust in vehicle autonomy. We first present a broad context of the
explanatory human-machine systems with the "3W1H" (what, whom, when, how)
approach. Based on these findings, we present a situation awareness framework
for calibrating users' trust in self-driving behavior. Finally, we perform an
experiment on our framework, conduct a user study on it, and validate the
empirical findings with hypothesis testing.


  Cloud services and other shared third-party infrastructures allow individual
content providers to easily scale their services based on current resource
demands. In this paper, we consider an individual content provider that wants
to minimize its delivery costs under the assumptions that the storage and
bandwidth resources it requires are elastic, the content provider only pays for
the resources that it consumes, and costs are proportional to the resource
usage. Within this context, we (i) derive worst-case bounds for the optimal
cost and competitive cost ratios of different classes of "cache on $M^{th}$
request" cache insertion policies, (ii) derive explicit average cost
expressions and bounds under arbitrary inter-request distributions, (iii)
derive explicit average cost expressions and bounds for short-tailed
(deterministic, Erlang, and exponential) and heavy-tailed (Pareto)
inter-request distributions, and (iv) present numeric and trace-based
evaluations that reveal insights into the relative cost performance of the
policies. Our results show that a window-based "cache on $2^{nd}$ request"
policy using a single threshold optimized to minimize worst-case costs provides
good average performance across the different distributions and the full
parameter ranges of each considered distribution, making it an attractive
choice for a wide range of practical conditions where request rates of
individual file objects typically are not known and can change quickly.


  Quantum shot noise probes the dynamics of charge transfers through a quantum
conductor, reflecting whether quasiparticles flow across the conductor in a
steady stream, or in syncopated bursts. We have performed high-sensitivity shot
noise measurements in a quantum dot obtained in a silicon
metal-oxide-semiconductor field-effect transistor. The quality of our device
allows us to precisely associate the different transport regimes and their
statistics with the internal state of the quantum dot. In particular, we report
on large current fluctuations in the inelastic cotunneling regime,
corresponding to different highly-correlated, non-Markovian charge transfer
processes. We have also observed unusually large current fluctuations at low
energy in the elastic cotunneling regime, the origin of which remains to be
fully investigated.


  This paper studies a 4-approximation algorithm for k-prize collecting Steiner
tree problems. This problem generalizes both k-minimum spanning tree problems
and prize collecting Steiner tree problems. Our proposed algorithm employs two
2-approximation algorithms for k-minimum spanning tree problems and prize
collecting Steiner tree problems. Also our algorithm framework can be applied
to a special case of k-prize collecting traveling salesman problems.


  For the GLS and Bjorken DIS sum rules we compare fixed-order NNLO
perturbative QCD estimates, and all-orders resummed estimates, with the
available data, in order to assess the reliability of fixed-order perturbation
theory at rather small Q^2 values. Fits are also performed for non-perturbative
power corrections using a recently proposed model.


  Microarray technology is known as one of the most important tools for
collecting DNA expression data. This technology allows researchers to
investigate and examine types of diseases and their origins. However,
microarray data are often associated with challenges such as small sample size,
a significant number of genes, imbalanced data, etc. that make classification
models inefficient. Thus, a new hybrid solution based on multi-filter and
adaptive chaotic multi-objective forest optimization algorithm (AC-MOFOA) is
presented to solve the gene selection problem and construct the Ensemble
Classifier. In the proposed solution, to reduce the dataset's dimensions, a
multi-filter model uses a combination of five filter methods to remove
redundant and irrelevant genes. Then, an AC-MOFOA based on the concepts of
non-dominated sorting, crowding distance, chaos theory, and adaptive operators
is presented. AC-MOFOA as a wrapper method aimed at reducing dataset
dimensions, optimizing KELM, and increasing the accuracy of the classification,
simultaneously. Next, in this method, an ensemble classifier model is presented
using AC-MOFOA results to classify microarray data. The performance of the
proposed algorithm was evaluated on nine public microarray datasets, and its
results were compared in terms of the number of selected genes, classification
efficiency, execution time, time complexity, and hypervolume indicator
criterion with five hybrid multi-objective methods. According to the results,
the proposed hybrid method could increase the accuracy of the KELM in most
datasets by reducing the dataset's dimensions and achieve similar or superior
performance compared to other multi-objective methods. Furthermore, the
proposed Ensemble Classifier model could provide better classification accuracy
and generalizability in microarray data compared to conventional ensemble
methods.


  Bounding box regression is an important component in object detection. Recent
work achieves promising performance by optimizing the Intersection over
Union~(IoU). However, IoU-based loss has the gradient vanish problem in the
case of low overlapping bounding boxes, and the model could easily ignore these
simple cases. In this paper, we propose Side Overlap~(SO) loss by maximizing
the side overlap of two bounding boxes, which puts more penalty for low
overlapping bounding box cases. Besides, to speed up the convergence, the
Corner Distance~(CD) is added into the objective function. Combining the Side
Overlap and Corner Distance, we get a new regression objective function,
\textit{Side and Corner Align Loss~(SCALoss)}. The SCALoss is well-correlated
with IoU loss, which also benefits the evaluation metric but produces more
penalty for low-overlapping cases. It can serve as a comprehensive similarity
measure, leading to better localization performance and faster convergence
speed. Experiments on COCO, PASCAL VOC, and LVIS benchmarks show that SCALoss
can bring consistent improvement and outperform $\ell_n$ loss and IoU based
loss with popular object detectors such as YOLOV3, SSD, Faster-RCNN. Code is
available at: \url{https://github.com/Turoad/SCALoss}.


  In this paper, the design and the performance of a prototype detector based
on MicroMegas technology with two detection planes in a common gas volume is
discussed. The detector is suited for the forward region of LHC detectors,
addressing the high-rate environment and limited available space. Each
detection plane has an active area of 9x9 cm^2 with a two-dimensional strip
readout and is separated by a common gas region with a height of 14 mm. A
micro-mesh, working as a cathode, is placed in the middle of the common gas
volume separating it into two individual cells. This setup allows for an angle
reconstruction of incoming particles with a precision of 2 mrad. Since this
design reduces the impact of multiple scattering effects by the reduced
material budget, possible applications for low energy beam experiments can be
envisioned. The performance of the prototype detector has been tested with a
4.4 GeV electron beam, provided by the test beam facility at DESY.


  Non-equilibrium transport properties and energy conversion performance of a
molecular photo-voltaic cell are analyzed using the Lindblad master equation
within the open quantum systems approach. The method allows us to calculate the
dynamics of a system driven by several non-equilibrium sources (a situation we
call "strong non-equilibrium"), which is the natural operating condition of
photovoltaic cells. We include both coherent and incoherent processes and treat
electrons, photon, and phonons on an equal footing. We find that decoherence
plays a crucial role in determining both the overall efficiency of the
photovoltaic conversion and the optimal energy configuration of the system.
Specifically, decoherence leads to better performance, due to a faster
relaxation of the excited electrons to the electrodes. We also examine the
effect of coherent interference on the efficiency. The approach we propose in
this letter is suitable for studying transport and energy conversion in other
nanoscale systems at non-equilibrium, where both coherent and incoherent
processes take place.


  We have theoretically investigated nonlinear free-carrier absorption of
terahertz radiation in InAs/AlSb heterojunctions. By considering multiple
photon process and conduction-valence interband impact ionization (II), we have
determined the field and frequency dependent absorption rate. It is shown that
(i) electron-disorder scatterings are important at low to intermediate field,
and (ii) most importantly, the high field absorption is dominated by II
processes. Our theory can satisfactorily explain a long standing experimental
result on the nonlinear absorption in THz regime.


  A new strategy for eliminating photocurrent losses due to the metal contacts
on the front of a solar cell was proposed, simulated, and tested. By placing
triangular cross-section lines of low refractive index on top of the contacts,
total-internal reflection at the interface of the low-index triangles and the
surrounding material can direct light away from the metal and into the
photoactive absorber. Simulations indicated that losses can be eliminated for
any incident angle, and that yearly energy production improvements commensurate
with the metallized area are possible. Proof of principle experiments were
carried out to eliminate the reflective losses of a commercial solar cell's
busbar contact. Spatially resolved laser beam induced current measurements
demonstrated that reflection losses due to the busbar were reduced by voids
with triangular cross-section.


  In this note we consider the global convergence properties of the
differential equation $\dot{\Theta}=(\Theta^{T}-\Theta)\Theta$ with
$\Theta\in{SO(n)}$, which is a gradient flow of the function
$f:SO(n)\rightarrow\mathbb{R},\Theta\mapsto{2n-2\tr{\Theta}}$. Many of the
presented results are not new, but scattered throughout literature. The
motivation of this note is to summarize and extend the convergence results
known from literature. Rather than giving an exhaustive list of references, the
results are presented in a self-contained fashion.


  The anisotropic optical response of the layered, nodal-line semimetal ZrSiS
at ambient and high pressure is investigated by frequency-dependent
reflectivity measurements for the polarization along and perpendicular to the
layers. The highly anisotropic optical conductivity is in very good agreement
with results from density functional theory calculations and confirms the
anisotropic character of ZrSiS. Whereas the in-plane optical conductivity shows
only modest pressure-induced changes, we found strong effects on the
out-of-plane optical conductivity spectrum of ZrSiS, with the appearance of two
prominent excitations. These pronounced pressure-induced effects can neither be
attributed to a structural phase transition according to our single-crystal
x-ray diffraction measurements, nor can they be explained by electronic
correlation and electron-hole pairing effects, as revealed by theoretical
calculations. Our findings are discussed in the context of the recently
proposed excitonic insulator phase in ZrSiS.


  With focus on the cosmological evolution of linear perturbations of matter
and geometry, we calculate the equivalent expressions to that of the Newtonian
and Synchronous gauges within the framework of Unimodular Gravity, being these
two gauges commonly used and implemented in Boltzmann codes. An important
aspect of our analysis is the inclusion of the energy-momentum current
violation, as well as its perturbations. Moreover, for the first time we
demonstrate that it is possible to fix both gauges consistently, although as it
has been already noticed in previous literature, neither of them is recovered
in the sense of the dynamics given in General Relativity for matter and metric
fluctuations. Specifically, we show that since the unimodular constraint at the
level of linear perturbations lead to only one degree of freedom of scalar
modes of metric fluctuations, the dynamics in Unimodular Gravity forces to keep
the anisotropic stress in the Newtonian gauge, whereas the cold dark matter
comoving frame can not be set in the Synchronous gauge. The physical
implications on the density contrast of cold dark matter is reviewed, and the
Sachs-Wolfe effect is obtained and compared with previous results in the
literature of cosmological perturbations in Unimodular Gravity.


  In \cite{FGLNP}, Fox, Gromov, Lafforgue, Naor and Pach, in a respond to a
question of Gromov \cite{G}, constructed bounded degree geometric expanders,
namely, simplical complexes having the affine overlapping property. Their
explicit constructions are finite quotients of $\tilde{A_d}$-buildings, for
$d\geq 2$, over local fields. In this paper, this result is extended to general
high rank Bruhat-Tits buildings.


  Engineering of ferroelectric domain structures enables direct control over
the switching dynamics and is crucial for tuning the functional properties of
ferroelectrics for various applications, ranging from capacitors to future
nanoelectronics. Here, we investigate domain formation in poly- and single
crystalline improper ferroelectric DyMnO3. We show that a non-uniform
grain-size distribution in the polycrystals facilitates the coexistence of
multi-scale domains, varying by up to one order of magnitude in size. This
unusual domain structure originates from an inverted domain-size/grain-size
dependence that is intrinsic to the hexagonal manganite polycrystals, expanding
previous studies towards non-uniform grain-size distributions. Our results
demonstrate that the micrometer-sized grains in DyMnO3 represent individual
ferroelectric units with a characteristic domain structure, giving a new
dimension to domain engineering in ferroelectric polycrystals with non-uniform
microstructures.


  Non-volatile memory (NVM) devices that reliably operate at temperatures above
300 $^\circ$C are currently non-existent and remains a critically unmet
challenge in the development of high-temperature (T) resilient electronics,
necessary for many emerging, complex computing and sensing in harsh
environments. Ferroelectric Al$_x$Sc$_{1-x}$N exhibits strong potential for
utilization in NVM devices operating at very high temperatures (> 500
$^\circ$C) given its stable and high remnant polarization (PR) above 100
$\mu$C/cm$^2$ with demonstrated ferroelectric transition temperature (TC) >
1000 $^\circ$C. Here, we demonstrate an Al$_{0.68}$Sc$_{0.32}$N ferroelectric
diode based NVM device that can reliably operate with clear ferroelectric
switching up to 600 $^\circ$C with distinguishable On and Off states. The
coercive field (EC) from the Pulsed I-V measurements is found to be -5.84 (EC-)
and +5.98 (EC+) (+/- 0.1) MV/cm at room temperature (RT) and found to decrease
with increasing temperature up to 600 $^\circ$C. The devices exhibit high
remnant polarizations (> 100 $\mu$C/cm$^2$) which are stable at high
temperatures. At 500 $^\circ$C, our devices show 1 million read cycles and
stable On-Off ratio above 1 for > 6 hours. Finally, the operating voltages of
our AlScN ferrodiodes are < 15 V at 600 $^\circ$C which is well matched and
compatible with Silicon Carbide (SiC) based high temperature logic technology,
thereby making our demonstration a major step towards commercialization of NVM
integrated high-T computers.


  The tilings of lozenges in 2 dimensions and of rhomboedra in 3 dimensions are
studied when they are constrained by fixed boundary conditions. We establish a
link between those conditions and free or periodic boundary ones: the entropy
is written as a functional integral which is treated via a saddle-point method.
Then we can exhibit the dominant states of the statistical ensemble of tilings
and show that they can display a strong structural inhomogeneity caused by the
boundary. This inhomogeneity is responsible for a difference of entropy between
the studied fixed boundary tilings and free boundary ones. This method uses a
representation of tilings by membranes embedded in a higher-dimensional
hypercubic lattice. It is illustrated in the case of 60 degree lozenge tilings.


  A conservation law theorem stated by N. Ibragimov along with its subsequent
extensions are shown to be a special case of a standard formula that uses a
pair consisting of a symmetry and an adjoint-symmetry to produce a conservation
law through a well-known Fr\'echet derivative identity. Also, the connection of
this formula (and of Ibragimov's theorem) to the standard action of symmetries
on conservation laws is explained, which accounts for a number of major
drawbacks that have appeared in recent work using the formula to generate
conservation laws. In particular, the formula can generate trivial conservation
laws and does not always yield all non-trivial conservation laws unless the
symmetry action on the set of these conservation laws is transitive. It is
emphasized that all local conservation laws for any given system of
differential equations can be found instead by a general method using
adjoint-symmetries. This general method is a kind of adjoint version of the
standard Lie method to find all local symmetries and is completely algorithmic.
The relationship between this method, Noether's theorem, and the
symmetry/adjoint-symmetry formula is discussed.


  Recently Alexander and Gulyaev have suggested that the apparent decrease in
impact broadening of radio recombination lines seen at high principal quantum
number n may be a product of the data reduction process, possibly resulting
from the presence of noise on the telescope spectra that is not present on the
calculated comparison spectra. This is an interesting proposal. However, there
are serious problems with their analysis that need to be pointed out. Perhaps
the most important of these is the fact that for principal quantum numbers
below n = 200, where the widths are not in question, their processed generated
profile widths do not fit the widths of the processed lines obtained at the
telescope. After processing, the halfwidths of the generated and telescope
profiles must agree below n = 200 if we are to believe that the processed
generated linewidths above n = 200 are meaningful. Theirs do not. Furthermore,
we find that after applying the linewidth reduction factors found by Alexander
and Gulyaev for their noise added profiles to our generated profiles to
simulate their noise adding effect, the processed widths we obtain still do not
come close to explaining the narrowing seen in the telescope lines for n values
in the range 200 < n < 250. It is concluded that what is needed to solve this
mystery is a completely new approach using a different observing technique
instead of simply a further manipulation of the frequency-switched data.


  In the Two-dimensional Bin Packing (2BP) problem, we are given a set of
rectangles of height and width at most one and our goal is to find an
axis-aligned nonoverlapping packing of these rectangles into the minimum number
of unit square bins. The problem admits no APTAS and the current best
approximation ratio is $1.406$ by Bansal and Khan [SODA'14]. A well-studied
variant of the problem is Guillotine Two-dimensional Bin Packing (G2BP), where
all rectangles must be packed in such a way that every rectangle in the packing
can be obtained by recursively applying a sequence of end-to-end axis-parallel
cuts, also called guillotine cuts. Bansal, Lodi, and Sviridenko [FOCS'05]
obtained an APTAS for this problem. Let $\lambda$ be the smallest constant such
that for every set $I$ of items, the number of bins in the optimal solution to
G2BP for $I$ is upper bounded by $\lambda\operatorname{opt}(I) + c$, where
$\operatorname{opt}(I)$ is the number of bins in the optimal solution to 2BP
for $I$ and $c$ is a constant. It is known that $4/3 \le \lambda \le 1.692$.
Bansal and Khan [SODA'14] conjectured that $\lambda = 4/3$. The conjecture, if
true, will imply a $(4/3+\varepsilon)$-approximation algorithm for 2BP.
According to convention, for a given constant $\delta>0$, a rectangle is large
if both its height and width are at least $\delta$, and otherwise it is called
skewed. We make progress towards the conjecture by showing $\lambda = 4/3$ for
skewed instance, i.e., when all input rectangles are skewed. Even for this
case, the previous best upper bound on $\lambda$ was roughly 1.692. We also
give an APTAS for 2BP for skewed instance, though general 2BP does not admit an
APTAS.


  The OPERA neutrino detector in the underground Gran Sasso Laboratory (LNGS)
has been designed to perform the first detection of neutrino oscillations in
direct appearance mode through the study of the $\nu_\mu\rightarrow\nu_\tau$
channel. The hybrid apparatus consists of an emulsion/lead target complemented
by electronic detectors and it is placed in the high energy long-baseline CERN
to LNGS beam (CNGS) 730 km away from the neutrino source. Runs with CNGS
neutrinos were successfully carried out in 2008 and 2009. After a brief
description of the beam, the experimental setup and the procedures used for the
analysis of the neutrino events, we describe the topology and kinematics of a
first candidate $\nu_\tau$ charged-current event satisfying the kinematical
selection criteria. The background calculations and their cross-check are
explained in detail and the significance of the event is assessed.


  This PHD thesis is concerned with uncertainty relations in quantum
probability theory, state estimation in quantum stochastics, and natural
bundles in differential geometry. After some comments on the nature and
necessity of decoherence in open systems and its absence in closed ones, we
prove sharp, state-independent inequalities reflecting the Heisenberg
principle, the necessity of decoherence and the impossibility of perfect joint
measurement. These bounds are used to judge how far a particular measurement is
removed from the optimal one. We do this for a qubit interacting with the
quantized EM field, continually probed using homodyne detection. We calculate
to which extent this joint measurement is optimal. We then propose a two-step
strategy to determine the (possibly mixed) state of n identically prepared
qubits, and prove that it is asymptotically optimal in a local minimax sense,
using `Quantum Local Asymptotic Normality' for qubits. We propose a physical
implementation of QLAN, based on interaction with the quantized EM field. In
differential geometry, a bundle is called `natural' if diffeomorphisms of the
base lift to automorphisms of the bundle. We slightly extend this notion to
`infinitesimal naturality', requiring only vector fields (infinitesimal
diffeomorphisms) to lift. We classify these bundles. Physical fields that
transform under (infinitesimal) space-time transformations must be described in
terms of (infinitesimally) natural bundles. All spin structures are
infinitesimally natural. Our framework thus encompasses Fermionic fields, for
which the notion of a natural bundle is too restrictive. Interestingly,
generalized spin structures (e.g. spin-c structures) are not always
infinitesimally natural. We classify the ones that are. Depending on the gauge
group at hand, this can significantly reduce the number of allowed space-time
topologies.


  The present work reports a general method for the calculation of t he
polarizability of a truncated sphere on a substrate. A multipole ex pansion is
used, where the multipoles are not necessarily localized in the center of the
sphere but can freely move on the revolution axis. From the weak formulation of
the boundary conditions, an infinite set of linear equations for the multipole
coefficients is derived. To obta in this set, the interaction between the
island and the substrate is t aken into account by the technique of image
multipoles. For numerical implementation, this set is truncated at an arbitrary
mu ltipole order. The accuracy of the method is jugded through the stabil ity
of the truncated sphere polarizability and the the fulfilment of t he boundary
conditions which are demonstrated to be satisfied in large regions of the
parameter space. This method brings an improvement wit h respect to the
Bedeaux's case \cite{Wind87a,Wind87b} where the multi poles are located in the
center of the sphere.


  We discuss in a statistical physics framework the idea that ``the whole is
less than the parts'', as sometimes advocated by sociologists in view of the
intrinsic complexity of humans, and try to reconcile this idea with the
statistical physicists wisdom according to which ``the whole is more than the
sum of its parts'' due to collective phenomena. We consider a simple mean-field
model of interacting agents having an intrinsic complexity modeled by a large
number of internal configurations. We show by analytically solving the model
that interactions between agents lead, in some parameter range, to a
`standardization' of agents in the sense that all agents collapse in the same
internal state, thereby drastically suppressing their complexity. Slightly
generalizing the model, we find that agents standardization may lead to a
global order if appropriate interactions are included. Hence, in this simple
model, both agents standardization and collective organization may be viewed as
two sides of the same coin.


  Magnetism in SmPd2Al3 was investigated on a single crystal by magnetometry
and neutron diffraction. SmPd2Al3 represents a distinctive example of the Sm
magnetism exhibiting complex magnetic behavior at low temperatures with four
consecutive magnetic phase transitions at 3.4, 3.9, 4.3 and 12.5 K. The rich
magnetic phase diagram of this compound reflects the specific features of the
Sm3+ ion, namely the energy nearness of the ground-state multiplet J = 5/2 and
the first excited multiplet J = 7/2 in conjunction with strong crystal field
influence. Consequently, a significantly reduced Sm magnetic moment in
comparison with the theoretical Sm3+ free-ion value is observed. Despite the
strong neutron absorption by natural samarium and the small Sm magnetic moment
(~ 0.2 {\mu}B) we have successfully determined the magnetic k-vector (1/3, 1/3,
0) of the phase existing in the temperature interval 12.5 - 4.3 K. This
observation classifies the SmPd2Al3 compound as a magnetically frustrated
system. The complex magnetic behavior of this material is further illustrated
by kinetic effects of the magnetization inducing rather complicated magnetic
structure with various metastable states.


  We consider a mixed hybrid finite element formulation for coupled
poromechanics. A stabilization strategy based on a macro-element approach is
advanced to eliminate the spurious pressure modes appearing in
undrained/incompressible conditions. The efficient solution of the stabilized
mixed hybrid block system is addressed by developing a class of block
triangular preconditioners based on a Schur-complement approximation strategy.
Robustness, computational efficiency and scalability of the proposed approach
are theoretically discussed and tested using challenging benchmark problems on
massively parallel architectures.


  The random-order or secretary model is one of the most popular beyond-worst
case model for online algorithms. While it avoids the pessimism of the
traditional adversarial model, in practice we cannot expect the input to be
presented in perfectly random order. This has motivated research on ``best of
both worlds'' (algorithms with good performance on both purely stochastic and
purely adversarial inputs), or even better, on inputs that are a mix of both
stochastic and adversarial parts. Unfortunately the latter seems much harder to
achieve and very few results of this type are known.
  Towards advancing our understanding of designing such robust algorithms, we
propose a random-order model with bursts of adversarial time steps. The
assumption of burstiness of unexpected patterns is reasonable in many contexts,
since changes (e.g. spike in a demand for a good) are often triggered by a
common external event. We then consider the Knapsack Secretary problem in this
model: there is a knapsack of size $k$ (e.g., available quantity of a good),
and in each of the $n$ time steps an item comes with its value and size in
$[0,1]$ and the algorithm needs to make an irrevocable decision whether to
accept or reject the item.
  We design an algorithm that gives an approximation of $1 -
\tilde{O}(\Gamma/k)$ when the adversarial time steps can be covered by $\Gamma
\ge \sqrt{k}$ intervals of size $\tilde{O}(\frac{n}{k})$. In particular,
setting $\Gamma = \sqrt{k}$ gives a $(1 - O(\frac{\ln^2
k}{\sqrt{k}}))$-approximation that is resistant to up to a $\frac{\ln^2
k}{\sqrt{k}}$-fraction of the items being adversarial, which is almost optimal
even in the absence of adversarial items. Also, setting $\Gamma =
\tilde{\Omega}(k)$ gives a constant approximation that is resistant to up to a
constant fraction of items being adversarial.


  We give out the time evolution solution of simultaneous amplitude and phase
damping for any continuous variable state. For the simultaneous amplitude and
phase damping of a wide class of two- mode entangled Gaussian states, two
analytical conditions of the separability are given. One is the sufficient
condition of separability. The other is the condition of PPT separability where
the Peres-Horodecki criterion is applied. Between the two conditions there may
exist bound entanglement. The simplest example is the simultaneous amplitude
and phase damping of a two-mode squeezed vacuum state. The damped state is
non-Gaussian.


  The aim of this work is to characterize physical properties of Ultra Luminous
Infrared Galaxies (ULIRGs) and Luminous Infrared Galaxies (LIRGs) detected in
the far-infrared (FIR) 90um band in the AKARI Deep Field-South (ADF-S) survey.
In particular, we want to estimate the AGN contribution to the [U]LIRGs'
infrared emission and which types of AGNs are related to their activity. We
examined 69 galaxies at z>0.05 detected at 90um by the AKARI satellite in the
ADF-S, with optical counterparts and spectral coverage from the ultraviolet to
the FIR. We used two independent spectral energy distribution fitting codes:
one fitting the SED from FIR to FUV (CIGALE) and gray-body + power spectrum fit
for the infrared part of the spectra (CMCIRSED) in order to identify a
subsample of [U]LIRGs, and to estimate their properties. Based on the CIGALE
SED fitting, we have found that [U]LIRGs selected at the 90um AKARI band
compose ~56% of our sample (we found 17 ULIRGs and 22 LIRGs, spanning over the
redshift range 0.06<z<1.23). Their physical parameters, such as stellar mass,
star formation rate (SFR), and specific SFR are consistent with the ones found
for other samples selected at IR wavelengths. We have detected a significant
AGN contribution to the MIR luminosity for 63% of LIRGs and ULIRGs. Our LIRGs
contain Type 1, Type 2, and intermediate types of AGN, whereas for ULIRGs, a
majority (more than 50%) of AGN emission originates from Type 2 AGNs. The
temperature--luminosity and temperature--mass relations for the dust component
of ADF--S LIRGs and ULIRGs indicate that these relations are shaped by the dust
mass and not by the increased dust heating. We conclude that LIRGs contain Type
1, Type 2, and intermediate types of AGNs, with an AGN contribution to the MIR
emission at the median level of 13+/-3%, whereas the majority of ULIRGs contain
Type 2 AGNs, with a median AGN fraction equal to 19+/-8%.


  We report deep, single-dish 21 cm observations of NGC 1052-DF2, taken with
the Green Bank Telescope. NGC 1052-DF2, proposed to be lacking in dark matter,
is currently classified as an ultra-diffuse galaxy in the NGC 1052 group. We do
not detect the galaxy, and derive an upper limit on the HI, mass. The galaxy is
extremely gas-poor, and we find that a $3\sigma \, M_{HI}$ detection at a
distance of 19 Mpc and using a line width of 3.2 km $\rm s^{-1}$ would have an
upper limit of $M_{HI,lim} < 5.5 \times 10^5$ M$_{\odot}$. At this mass limit,
the gas fraction of neutral gas mass to stellar mass is extremely low, at
$M_{HI}$/M$_{*}$ $\, < \, 0.0027$. This extremely low gas fraction, comparable
to Galactic dwarf spheroidals and gas-poor dwarf ellipticals, implies that
either the galaxy is within the virial radius of NGC1052, where its gas has
been stripped due to its proximity to the central galaxy, or that NGC 1052-DF2
is at distance large enough to inhibit detection of its gas. We also estimated
the upper limit of the HI mass of NGC 1052-DF2 resided at 13 Mpc. This would
give an HI mass of $M_{HI,lim} < 2.5 \times 10^5$ M$_{\odot}$, and an HI gas
fraction of $M_{HI}$/M$_{*}$r $\, < \, 0.0012$, becoming even more extreme.
While the dark matter fraction would be less extreme at this distance, the
neutral gas fraction would be unprecedented for an object in a low density
environment.


  Several important tasks in medical image analysis can be stated in the form
of an optimization problem whose feasible solutions are connected subgraphs.
Examples include the reconstruction of neural or vascular structures under
connectedness constraints. We discuss the minimum cost connected subgraph
(MCCS) problem and its approximations from the perspective of medical
applications. We propose a) objective-dependent constraints and b) novel
constraint generation schemes to solve this optimization problem exactly by
means of a branch-and-cut algorithm. These are shown to improve scalability and
allow us to solve instances of two medical benchmark datasets to optimality for
the first time. This enables us to perform a quantitative comparison between
exact and approximative algorithms, where we identify the geodesic tree
algorithm as an excellent alternative to exact inference on the examined
datasets.


  In this paper, we study augmented Lagrangian functions for nonlinear
semidefinite programming (NSDP) problems with exactness properties. The term
exact is used in the sense that the penalty parameter can be taken
appropriately, so a single minimization of the augmented Lagrangian recovers a
solution of the original problem. This leads to reformulations of NSDP problems
into unconstrained nonlinear programming ones. Here, we first establish a
unified framework for constructing these exact functions, generalizing Di Pillo
and Lucidi's work from 1996, that was aimed at solving nonlinear programming
problems. Then, through our framework, we propose a practical augmented
Lagrangian function for NSDP, proving that it is continuously differentiable
and exact under the so-called nondegeneracy condition. We also present some
preliminary numerical experiments.


  The projection of sample measurements onto a reconstruction space represented
by a basis on a regular grid is a powerful and simple approach to estimate a
probability density function. In this paper, we focus on Riesz bases and
propose a projection operator that, in contrast to previous works, guarantees
the bona fide properties for the estimate, namely, non-negativity and total
probability mass $1$. Our bona fide projection is defined as a convex problem.
We propose solution techniques and evaluate them. Results suggest an improved
performance, specifically in circumstances prone to rippling effects.


  The measurement of a reaction cross section from a pulse height spectrum is a
ubiquitous problem in experimental nuclear physics. In $\gamma$-ray
spectroscopy, this is accomplished frequently by measuring the intensity of
full-energy primary transition peaks and correcting the intensities for
experimental artifacts, such as detection efficiencies and angular
correlations. Implicit in this procedure is the assumption that full-energy
peaks do not overlap with any secondary peaks, escape peaks, or environmental
backgrounds. However, for complex $\gamma$-ray cascades, this is often not the
case. Furthermore, this technique is difficult to adapt for coincidence
spectroscopy, where intensities depend not only on the detection efficiency,
but also the detailed decay scheme. We present a method that incorporates the
intensities of the entire spectrum (e.g., primary and secondary transition
peaks, escape peaks, Compton continua, etc.) into a statistical model, where
the transition intensities and branching ratios can be determined using
Bayesian statistical inference. This new method provides an elegant solution to
the difficulties associated with analyzing coincidence spectra. We describe it
in detail and examine its efficacy in the analysis of
$^{18}$O(p,$\gamma$)$^{19}$F and $^{25}$Mg(p,$\gamma$)$^{26}$Al resonance data.
For the $^{18}$O(p,$\gamma$)$^{19}$F reaction, the measured branching ratios
improve upon the literature values, with a factor of 4 reduction in the
uncertainties.


  Denote by $G$ a finite group and let $\psi(G)$ denote the sum of element
orders in $G$. In 2009, H.Amiri, S.M.Jafarian Amiri and I.M.Isaacs proved that
if $|G|=n$ and $G$ is non-cyclic, then $\psi(G)<\psi(C_n)$, where $C_n$ denotes
the cyclic group of order $n$. In 2018 we proved that if $G$ is non-cyclic
group of order $n$, then $\psi(G)\leq \frac 7{11}\psi(C_n)$ and equality holds
if $n=4k$ with $(k,2)=1$ and $G=(C_2\times C_2)\times C_k$. In this paper we
proved that equality holds if and only if $n$ and $G$ are as indicated above.
Moreover we proved the following generalization of this result: Theorem 4. Let
$q$ be a prime and let $G$ be a non-cyclic group of order $n$, with $q$ being
the least prime divisor of $n$. Then $\psi(G)\leq \frac
{((q^2-1)q+1)(q+1)}{q^5+1}\psi(C_n)$, with equality if and only if $n=q^2k$
with $(k,q)=1$ and $G=(C_q\times C_q)\times C_k$. Notice that if $q=2$, then
$\frac {((q^2-1)q+1)(q+1)}{q^5+1}=\frac 7{11}$.


  We introduce TempoCave, a novel visualization application for analyzing
dynamic brain networks, or connectomes. TempoCave provides a range of
functionality to explore metrics related to the activity patterns and modular
affiliations of different regions in the brain. These patterns are calculated
by processing raw data retrieved functional magnetic resonance imaging (fMRI)
scans, which creates a network of weighted edges between each brain region,
where the weight indicates how likely these regions are to activate
synchronously. In particular, we support the analysis needs of clinical
psychologists, who examine these modular affiliations and weighted edges and
their temporal dynamics, utilizing them to understand relationships between
neurological disorders and brain activity, which could have a significant
impact on the way in which patients are diagnosed and treated. We summarize the
core functionality of TempoCave, which supports a range of comparative tasks,
and runs both in a desktop mode and in an immersive mode. Furthermore, we
present a real-world use case that analyzes pre- and post-treatment connectome
datasets from 27 subjects in a clinical study investigating the use of
cognitive behavior therapy to treat major depression disorder, indicating that
TempoCave can provide new insight into the dynamic behavior of the human brain.


  Many crucial biological processes rely on networks of protein-protein
interactions. Predicting the effect of amino acid mutations on protein-protein
binding is vital in protein engineering and therapeutic discovery. However, the
scarcity of annotated experimental data on binding energy poses a significant
challenge for developing computational approaches, particularly deep
learning-based methods. In this work, we propose SidechainDiff, a
representation learning-based approach that leverages unlabelled experimental
protein structures. SidechainDiff utilizes a Riemannian diffusion model to
learn the generative process of side-chain conformations and can also give the
structural context representations of mutations on the protein-protein
interface. Leveraging the learned representations, we achieve state-of-the-art
performance in predicting the mutational effects on protein-protein binding.
Furthermore, SidechainDiff is the first diffusion-based generative model for
side-chains, distinguishing it from prior efforts that have predominantly
focused on generating protein backbone structures.


  Safety guarantees and security-latency problem of Nakamoto consensus have
been extensively studied in the last decade with a bounded delay model. Recent
studies have shown that PoW protocol is secure under random delay models as
well. In this paper, we analyze the security-latency problem, i.e., how secure
a block is, after it becomes k-deep in the blockchain, under general random
delay distributions. We provide tight and explicit bounds which only require
determining the distribution of the number of Poisson arrivals during the
random delay. We further consider potential effects of recent Bitcoin halving
on the security-latency problem by extending our results.


  With dc magnetisation and polarized neutron reflectometry we studied the
ferromagnetic response of YBa$_2$Cu$_3$O$_7$/La$_{2/3}$Ca$_{1/3}$MnO$_3$
(YBCO/LCMO) multilayers that are grown with pulsed laser deposition. We found
that whereas for certain growth conditions (denoted as A-type) the
ferromagnetic moment of the LCMO layer is strongly dependent on the structural
details of the YBCO layer on which it is deposited, for others (B-type) the
ferromagnetism of LCMO is much more robust. Both kinds of multilayers are of
similar structural quality, but electron energy-loss spectroscopy (EELS)
studies with a scanning transmission electron microscope reveal an enhanced
average Mn oxidation state of +3.5 for the A-type as opposed to the B-type
samples for which it is close to the nominal value of +3.33. The related,
additional hole doping of the A-type LCMO layers, which likely originates from
La and/or Mn vacancies, can explain their fragile ferromagnetic order since it
places them close to the boundary of the ferromagnetic order at which even weak
perturbations can induce an antiferromagnetic or glassy state. On the other
hand, we show that the B-type samples allow one to obtain YBCO/LCMO
heterostructures with very thick YBCO layers and, yet, strongly ferromagnetic
LCMO layers.


  'Ghost Rods' are periodic structures in a two-dimensional flow that have an
effect on material lines that is similar to real stirring rods. An example is a
periodic island: material lines exterior to it must wrap around such an island,
because determinism forbids them from crossing through it. Hence, islands act
as topological obstacles to material lines, just like physical rods, and lower
bounds on the rate of stretching of material lines can be deduced from the
motion of islands and rods. Here, we show that unstable periodic orbits can
also act as ghost rods, as long as material lines can 'fold' around the orbit,
which requires the orbit to be parabolic. We investigate the factors that
determine the effective size of ghost rods, that is, the magnitude of their
impact on material lines.


  Stroke is the second leading cause of death worldwide. Machine learning
classification algorithms have been widely adopted for stroke prediction.
However, these algorithms were evaluated using different datasets and
evaluation metrics. Moreover, there is no comprehensive framework for stroke
data analytics. This paper proposes an intelligent stroke prediction framework
based on a critical examination of machine learning prediction algorithms in
the literature. The five most used machine learning algorithms for stroke
prediction are evaluated using a unified setup for objective comparison.
Comparative analysis and numerical results reveal that the Random Forest
algorithm is best suited for stroke prediction.


  Humans solving algorithmic (or) reasoning problems typically exhibit solution
times that grow as a function of problem difficulty. Adaptive recurrent neural
networks have been shown to exhibit this property for various
language-processing tasks. However, little work has been performed to assess
whether such adaptive computation can also enable vision models to extrapolate
solutions beyond their training distribution's difficulty level, with prior
work focusing on very simple tasks. In this study, we investigate a critical
functional role of such adaptive processing using recurrent neural networks: to
dynamically scale computational resources conditional on input requirements
that allow for zero-shot generalization to novel difficulty levels not seen
during training using two challenging visual reasoning tasks: PathFinder and
Mazes. We combine convolutional recurrent neural networks (ConvRNNs) with a
learnable halting mechanism based on Graves (2016). We explore various
implementations of such adaptive ConvRNNs (AdRNNs) ranging from tying weights
across layers to more sophisticated biologically inspired recurrent networks
that possess lateral connections and gating. We show that 1) AdRNNs learn to
dynamically halt processing early (or late) to solve easier (or harder)
problems, 2) these RNNs zero-shot generalize to more difficult problem settings
not shown during training by dynamically increasing the number of recurrent
iterations at test time. Our study provides modeling evidence supporting the
hypothesis that recurrent processing enables the functional advantage of
adaptively allocating compute resources conditional on input requirements and
hence allowing generalization to harder difficulty levels of a visual reasoning
problem without training.


  It is usually assumed that the Bose crystal at $T=0$ corresponds to the
genuine ground state of a Bose system, i.e., this state is non-degenerate and
is described by the wave function without nodes. By means of symmetry analysis
we show that the ground state of a Bose system of any density should correspond
to a liquid or gas, but not to a crystal. The main point is that any
anisotropic state of a system of spinless bosons is degenerate. We prove this
for an infinite three-dimensional (3D) system and a finite ball-shaped 3D
system. One can expect that it is true also for a finite system of any form.
Therefore, the anisotropic state cannot be the genuine ground state. Hence, a
zero-temperature natural 3D crystal should correspond to an excited state of a
Bose system. The wave function $\Psi^{c}_{0}$ of a zero-temperature 3D Bose
crystal is proposed for zero boundary conditions. Apparently, such
$\Psi^{c}_{0}$ corresponds to a local minimum of energy (absolute minimum
corresponds to a liquid). Those properties yield the possibility of existence
of superfluid liquid H$_{2}$, Ne, Ar, and other inert elements. We propose
several possible experimental ways of obtaining them.


  We study broken symmetry states at integer Landau level fillings in
multivalley quantum Hall systems whose low energy dispersions are anisotropic.
When the Fermi surface of individual pockets lacks twofold rotational symmetry,
like in Bismuth (111) and in Sn$_{1-x}$Pb$_x$Se (001) surfaces, interactions
tend to drive the formation of quantum Hall ferroelectric states. We
demonstrate that the dipole moment in these states has an intimate relation to
the Fermi surface geometry of the parent metal. In quantum Hall nematic states,
like those arising in AlAs quantum wells, we demonstrate the existence of
unusually robust skyrmion quasiparticles.


  In the paper we state and prove theorem describing the upper bound on number
of the graphs that have fixed number of vertices |V| and can be colored with
the fixed number of n colors. The bound relates both numbers using power of 2,
while the exponent is the difference between |V| and n. We also state three
conjectures on the number of graphs that have fixed number of vertices |V| and
chromatic number n.


  Context. AGB stars go through a process of strong mass-loss that involves
pulsations of the atmosphere, which extends to a region where the conditions
are adequate for dust grains to form. Radiation pressure acts on these grains
which, coupled to the gas, drive a massive outflow. The details of this process
are not clear, including which molecules are involved in the condensation of
dust grains.
  Aims. To study the role of the SiO molecule in the process of dust formation
and mass-loss in M-type AGB stars.
  Methods. Using the IRAM NOEMA interferometer we observed the $^{28}$SiO and
$^{29}$SiO $J=3-2$, $v=0$ emission from the inner circumstellar envelope of the
evolved stars IK Tau and IRC+10011. We computed azimuthally averaged emission
profiles to compare the observations to models using a molecular excitation and
ray-tracing code for SiO thermal emission.
  Results. We observed circular symmetry in the emission distribution. We also
found that the source diameter varies only marginally with radial velocity,
which is not the expected behavior for envelopes expanding at an almost
constant velocity. The adopted density, velocity, and abundance laws, together
with the mass-loss rate, which best fit the observations, give us information
on the chemical behavior of the SiO molecule and its role in the dust formation
process.
  Conclusions. The results indicate that there is a strong coupling between the
depletion of gas phase SiO and gas acceleration in the inner envelope. This
could be explained by the condensation of SiO into dust grains.


  Nd2Fe14B magnetic nanoparticles have been successfully produced using a
surfactant-assisted ball milling technique. The nanoparticles with different
size about 6, 20 and 300 nm were obtained by a size-selection process.
Spin-reorientation transition temperature of the NdFeB nanoparticles was then
determined by measuring the temperature dependence of DC and AC magnetic
susceptibility. It was found that the spin-reorientation transition temperature
(Tsr) of the nanoparticles is strongly size dependent, i.e., Tsr of the 300 nm
particles is lower than that of raw materials and a significant decrease was
observed in the 20 nm particles.


  We review the origin of soft supersymmetry-breaking terms in N=1 supergravity
models of particle physics. We first consider general formulae for those terms
in general models with a hidden sector breaking supersymmetry at an
intermediate energy scale. The results for some simple models are given. We
then consider the results obtained in some simple superstring models in which
particular assumptions about the origin of supersymmetry breaking are made.
These are models in which the seed of supersymmetry breaking is assumed to be
originated in the dilaton/moduli sector of the theory.


  The calculation of the trajectories in the Sun-Earth-Mars system will be
performed in two different models, both in the framework of Newtonian
mechanics. First model is well-known Copernican system, which assumes the Sun
is at rest and all the planets orbit around it. Second one is less-known model
developed by Tycho Brahe (1546-1601), according to which the Earth stands
still, the Sun orbits around the Earth, and other planets orbit around the Sun.
The term "Neo-tychonian system" refers to the assumption that orbits of distant
masses around the Earth are synchronized with the Sun's orbit. It is the aim of
this paper to show the kinematical and dynamical equivalence of these systems,
under the assumption of Mach's principle.


  BPS Wilson loops in supersymmetric gauge theories have been the subjects of
active research since they are often amenable to exact computation. So far most
of the studies have focused on loops that do not intersect. In this paper, we
derive exact results for intersecting 1/8 BPS Wilson loops in N=4
supersymmetric Yang-Mills theory, using a combination of supersymmetric
localization and the loop equation in 2d gauge theory. The result is given by a
novel matrix-model-like representation which couples multiple contour integrals
and a Gaussian matrix model. We evaluate the integral at large N, and make
contact with the string worldsheet description at strong coupling. As an
application of our results, we compute exactly a small-angle limit (and more
generally near-BPS limits) of the cross anomalous dimension which governs the
UV divergence of intersecting Wilson lines. The same quantity describes the
soft anomalous dimension of scattering amplitudes of W-bosons in the Coulomb
branch.


  Recent results from linear perturbation theory suggest that first-order
cosmological quark-hadron phase transitions occurring as deflagrations may be
``borderline'' unstable, and those occurring as detonations may give rise to
growing modes behind the interface boundary. However, since nonlinear effects
can play important roles in the development of perturbations, unstable behavior
cannot be asserted entirely by linear analysis, and the uncertainty of these
recent studies is compounded further by nonlinearities in the hydrodynamics and
self-interaction fields. In this paper we investigate the growth of
perturbations and the stability of quark-hadron phase transitions in the early
Universe by solving numerically the fully nonlinear relativistic hydrodynamics
equations coupled to a scalar field with a quartic self-interaction potential
regulating the transitions. We consider single, perturbed, phase transitions
propagating either by detonation or deflagration, as well as multiple phase and
shock front interactions in 1+2 dimensional spacetimes.


  Hexagonal boron nitride (h-BN) is brittle, however, its atomic-scale
structural engineering can lead to unprecedented physical properties. Here we
report the bulk synthesis of high-density crystalline h-BN solids by using
high-temperature spark plasma sintering (SPS) of micron size h-BN powders. In
addition to the high mechanical strength and ductile response of such
materials, we have obtained anomalous values of dielectric constant beyond
theoretical limits, high thermal conductivity, and exceptional neutron
radiation shielding capability. Through exhaustive characterizations we reveal
that SPS induces non-basal plane crystallinity, twisting of layers, and
facilitates inter-grain fusion with a high degree of in-plane alignment across
macroscale dimensions, resulting in near-theoretical density and anomalous
properties. Our findings highlight the importance of material design, via new
approaches such as twisting and interconnections between atomically thin
layers, to create novel ceramics with properties that could go beyond their
intrinsic theoretical predictions.


  Using transfer operator and fundamental measure theories, we examine the
structural and thermodynamic properties of hard rectangles confined between two
parallel hard walls. The side lengths of the rectangle ($L$ and $D$, $L>D$) and
the pore width ($H$) are chosen such that maximum two layers are allowed to
form in planar order ($L$ is parallel to the wall), while only one in
homeotropic order ($D$ is parallel to the wall). We observe three different
structures: (i) a low density fluid phase with parallel alignment to the wall,
(ii) an intermediate and high density fluid phase with two layers and planar
ordering and (iii) a dense single fluid layer with homeotropic ordering. The
appearance of these phases and the change in the ordering direction with
density is a consequence of the varying close packing structures with $L$ and
$H$. Interestingly, even three different structures can be observed with
increasing density if $L$ is close to $H$.


  We consider a lognormal diffusion process having a multisigmoidal logistic
mean, useful to model the evolution of a population which reaches the maximum
level of the growth after many stages. Referring to the problem of statistical
inference, two procedures to find the maximum likelihood estimates of the
unknown parameters are described. One is based on the resolution of the system
of the critical points of the likelihood function, and the other is on the
maximization of the likelihood function with the simulated annealing algorithm.
A simulation study to validate the described strategies for finding the
estimates is also presented, with a real application to epidemiological data.
Special attention is also devoted to the first-passage-time problem of the
considered diffusion process through a fixed boundary.


  Manifold learning is a popular and quickly-growing subfield of machine
learning based on the assumption that one's observed data lie on a
low-dimensional manifold embedded in a higher-dimensional space. This thesis
presents a mathematical perspective on manifold learning, delving into the
intersection of kernel learning, spectral graph theory, and differential
geometry. Emphasis is placed on the remarkable interplay between graphs and
manifolds, which forms the foundation for the widely-used technique of manifold
regularization. This work is written to be accessible to a broad mathematical
audience, including machine learning researchers and practitioners interested
in understanding the theorems underlying popular manifold learning algorithms
and dimensionality reduction techniques.


  We propose a scalable, efficient and accurate approach to retrieve 3D models
for objects in the wild. Our contribution is twofold. We first present a 3D
pose estimation approach for object categories which significantly outperforms
the state-of-the-art on Pascal3D+. Second, we use the estimated pose as a prior
to retrieve 3D models which accurately represent the geometry of objects in RGB
images. For this purpose, we render depth images from 3D models under our
predicted pose and match learned image descriptors of RGB images against those
of rendered depth images using a CNN-based multi-view metric learning approach.
In this way, we are the first to report quantitative results for 3D model
retrieval on Pascal3D+, where our method chooses the same models as human
annotators for 50% of the validation images on average. In addition, we show
that our method, which was trained purely on Pascal3D+, retrieves rich and
accurate 3D models from ShapeNet given RGB images of objects in the wild.


  A general formalism to find the density profile of a slowly rotating stellar
object in modified gravity is presented. We derive a generic Lane-Emden
equation and its analytical solution for a wide class of modified theories of
gravity.


  The bodies of snakes, such as king cobras, are very soft so that it is nearly
impossible for them to raise their heads higher than around one meter. By
direct measurement, we were only possible to hold the body of a freshly killed
cobra vertically at around 0.05 m. Here, for the first time it is reported that
the king cobra can control the effective elastic modulus of its body so that it
can raise its head up to several tens of centimeters. The effective elastic
modulus is enhanced by increasing the pressure of air trapped inside the
respiration channel, which is similar to increasing the stiffness of a thin
plastic tube by filling it with air at pressure above atmospheric pressure. The
neck height increases with the effective elastic modulus according to a scaling
relationship. It was also simply proved that the peak of force or constriction
pressure is proportional to the snakes diameter. This work may provide a
physical foundation underlying the mechanical properties of slender animals.


  Gravity coupled three--dimensional $\sigma$--model describing the stationary
Einstein--Maxwell--dilaton system with general dilaton coupling is studied.
Killing equations for the corresponding five--dimensional target space are
integrated. It is shown that for general coupling constant $\alpha$ the
symmetry algebra is isomorphic to the maximal solvable subalgebra of $sl(3,R)$.
For two critical values $\alpha =0$ and $\alpha =\sqrt{3}$, Killing algebra
enlarges to the full $sl(3,R)$ and $su(2,1)\times R$ algebras respectively,
which correspond to five--dimensional Kaluza--Klein and four--dimensional
Brans--Dicke--Maxwell theories. These two models are analyzed in terms of the
unique real variables. Relation to the description in terms of complex Ernst
potentials is discussed. Non--trivial discrete maps between different subspaces
of the target space are found and used to generate new arbitrary--$\alpha$
solutions to dilaton gravity.


  A strong differential transverse collective flow is predicted for the first
time to occur in heavy-ion collisions at balance energies. We also give a novel
explanation for the disappearance of the total transverse collective flow at
the balance energies. It is further shown that the differential flow especially
at high transverse momenta is a useful microscope capable of resolving the
balance energy's dual sensitivity to both the nuclear equation of state and
in-medium nucleon-nucleon cross sections in the reaction dynamics.


  We examine the linear stability of fluid interfaces subjected to a shear
flow. Our main object is to generalize previous work to arbitrary Atwood
number, and to allow for surface tension and weak compressibility. The
motivation derives from instances in astrophysical systems where mixing across
material interfaces driven by shear flows may significantly affect the
dynamical evolution of these systems.


  Multi-behavior recommendation, which exploits auxiliary behaviors (e.g.,
click and cart) to help predict users' potential interactions on the target
behavior (e.g., buy), is regarded as an effective way to alleviate the data
sparsity or cold-start issues in recommendation. Multi-behaviors are often
taken in certain orders in real-world applications (e.g., click>cart>buy). In a
behavior chain, a latter behavior usually exhibits a stronger signal of user
preference than the former one does. Most existing multi-behavior models fail
to capture such dependencies in a behavior chain for embedding learning. In
this work, we propose a novel multi-behavior recommendation model with
cascading graph convolution networks (named MB-CGCN). In MB-CGCN, the
embeddings learned from one behavior are used as the input features for the
next behavior's embedding learning after a feature transformation operation. In
this way, our model explicitly utilizes the behavior dependencies in embedding
learning. Experiments on two benchmark datasets demonstrate the effectiveness
of our model on exploiting multi-behavior data. It outperforms the best
baseline by 33.7% and 35.9% on average over the two datasets in terms of
Recall@10 and NDCG@10, respectively.


  In this manuscript, we investigate a $(p, q)$-Schr\"{o}dinger-Kirchhoff
equation involving a continuous positive potential that meets the del
Pino-Felmer type conditions.
  Using Recceri's classical variational approach, we prove the existence of
three weak solutions.


  We study the relationship between the local environment of galaxies and their
star formation rate (SFR) in the Great Observatories Origins Deep Survey,
GOODS, at z~1, from ultradeep imaging at 24 microns with the MIPS camera
onboard Spitzer. We show that the star formation-density relation observed
locally was reversed at z~1: the average SFR of an individual galaxy increased
with local galaxy density when the universe was less than half its present age.
Hierarchical galaxy formation models (simulated lightcones from the Millennium
model) predicted such a reversal to occur only at only at earlier epochs (z>2)
and at a lower level. We present a remarkable structure at z~1.016, containing
X-ray traced galaxy concentrations, which will eventually merge into a
Virgo-like cluster. This structure illustrates how the individual SFR of
galaxies increases with density at the ~1-2 Mpc scale. The SFR of z~1 galaxies
is found to correlate with stellar mass suggesting that mass plays a role in
the observed star formation-density trend. However the specific SFR (=SFR/M*)
decreases with stellar mass while it increases with galaxy density, which
implies that the environment does directly affect the star formation activity
of galaxies. Major mergers do not appear to be the unique or even major cause
for this effect since nearly half (46%) of the luminous infrared galaxies
(LIRGs) at z~1 present the HST-ACS morphology of spirals, while only a third
present a clear signature of major mergers. The remaining galaxies are divided
into compact (9%) and irregular (14%) galaxies. Moreover, the specific SFR of
major mergers is only marginally stronger than that of spirals. Reproducing the
SFR-density relation at z ~ 1 is a new challenge for models, requiring a
correct balance between mergers and in-situ star formation at early epochs.


  Ultraweak bioluminescence - the emission of biophotons - remains an
experimentally well-established, but theoretically poorly understood
phenomenon. This paper presents several related investigations into the
physical process of both spontaneous biophoton emission and delayed
luminescence. Since light intensities depend upon the modulus squared of their
corresponding electric fields we first make some general estimates about the
inherent electric fields within various biological systems. Since photon
emission from living matter following an initial excitation ("delayed
luminescence") typically does not follow a simple exponential decay law after
excitation we discuss such non-exponential decays from a general theoretical
perspective and argue that they are often to be expected and why. We then
discuss the dynamics behind some nonlinear rate equations, connecting them both
to biological growth rates and biophoton emission rates, noting a possible
connection with cancer. We then return to non-exponential decay laws seen for
delayed luminescence in an experimental context and again note a possible
connection with cancer.


  The combination of HIPPARCOS measurements with suitable ground-based
astrometric data improves significantly the accuracy of the proper motions of
bright stars. The comparison of both types of data allows us also to identify
and to eliminate, at least partially, cosmic errors in the
quasi-instantaneously measured HIPPARCOS data which are caused by undetected
astrometric binaries. We describe a simple averaging method for the combination
of two independent compilation catalogues. The combination of the basic FK5
with HIPPARCOS leads to the Sixth Catalogue of Fundamental Stars (FK6). The
accuracy of the FK6 proper motions is higher than that of HIPPARCOS by a factor
of about 2 in the single-star mode, and by a factor of more than 4 in the
long-term prediction mode which takes cosmic errors into account. We present
also the error budget for a combination of the Boss General Catalogue (GC) with
HIPPARCOS data. We point out problems with known binaries, and identify an
ensemble of 'astrometrically excellent stars'.


  An upper limit on the total annihilation cross section of dark matter (DM)
has recently been derived from the observed atmospheric neutrino background. We
show that comparable bounds are obtained for DM masses around the TeV scale by
observations of the diffuse gamma-ray flux by EGRET, because electroweak
bremsstrahlung leads to non-negligible electromagnetic branching ratios, even
if DM particles only couple to neutrinos at tree level. A better mapping and
the partial resolution of the diffuse gamma-ray background into astrophysical
sources by the GLAST satellite will improve this bound in the near future.


  In previous work of Gow, Ohmori, Lusztig and the author, the Schur indices of
all unipotent characters of finite groups of Lie type have been explicitly
determined except for six cases in groups of type $F_4$, $E_7$ and $E_8$. In
this paper, we show that the Schur indices of all cuspidal unipotent characters
for type $F_4$ and $E_8$ are~1, assuming that the group is defined over a field
of ``good'' characteristic. This settles four out of the six open cases. For
type $E_7$, we show that the Schur indices are at most~2.


  We investigate a simplified model for the strange stars in the framework of
Finslerian spacetime geometry, composed of charged fluid. It is considered that
the fluid consisting of three flavor quarks including a small amount of
non-interacting electrons to maintain the chemical equilibrium and assumed that
the fluid is compressible by nature. To obtain the simplified form of charged
strange star we considered constant flag curvature. Based on geometry, we have
developed the field equations within the localized charge distribution. We
considered that the strange quarks distributed within the stellar system are
compiled with the MIT bag model type of equation of state (EOS) and the charge
distribution within the system follows a power law. We represent the exterior
spacetime by the Finslerian Ressiner-Nordstr{\"o}m space-time. The maximum
anisotropic stress is obtained at the surface of the system. Whether the system
is in equilibrium or not, has been examined with respect to the
Tolman-Oppenheimer-Volkoff (TOV) equation, Herrera cracking concept, different
energy conditions and adiabatic index. We obtain that the total charge is of
the order of 10$^{20}$ C and the corresponding electric field is of around
10$^{22}$ V/m. The central density and central pressure vary inversely with the
charge. Varying the free parameter (charge constant) of the model, we find the
generalized mass-radius variation of strange stars and determine the maximum
limited mass with the corresponding radius. Furthermore, we also considered the
variation of mass and radius against central density respectively.


  We report the first clear evidence for the simultaneous presence of a low
frequency break and a QPO in the fluctuation power spectrum of a well known
ultraluminous X-ray source (ULX) in M82 using long XMM-Newton observations. The
break occurs at a frequency of 34.2_{-3}^{+6}mHz. The QPO has a centroid at
114.3\pm1.5mHz, a coherence Q~3.5 and an amplitude (rms) of 19% in the 2-10keV
band. The power spectrum is approximately flat below the break frequency and
then falls off above the break frequency as a power law with the QPO
superimposed. This form of the power spectrum is characteristic of the Galactic
X-ray binaries (XRBs) in their high or intermediate states. M82 X-1 was likely
in an intermediate state during the observation. The EPIC PN spectrum is well
described by a model comprising an absorbed power-law (Gamma~2) and an iron
line at ~6.6keV with a width sigma~0.2keV and an equivalent width of ~180eV.
Using the well established correlations between the power and energy spectral
parameters for XRBs, we estimate a black hole mass for M82 X-1 in the range of
25-520Msun including systematic errors that arise due to the uncertainty in the
calibration of the photon spectral index versus QPO frequency relation.


  Superconducting nanowires are very important due to their applications
ranging from quantum technology to astronomy. In this work, we implement a
non-invasive process to fabricate nanowires of high-$T_\text{c}$ superconductor
Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (BSCCO). We demonstrate that our nanowires
can be used as bolometers in the visible range with very high responsivity of
9.7 $\times$ 10$^{3}$ V/W. Interestingly, in a long (30 $\mu$m) nanowire of 9
nm thickness and 700 nm width, we observe bias current-dependent localized
spots of maximum photovoltage. Moreover, the scalability of the bolometer
responsivity with the normal state resistance of the nanowire could allow
further performance improvement by increasing the nanowire length in a meander
geometry. We observe phase slip events in nanowires with small cross-sections
(12 nm thick, 300 nm wide, and 3 $\mu$m long) at low temperatures. Our study
presents a scalable method for realizing sensitive bolometers working near the
liquid-nitrogen temperature.


  We follow the evolution of disk galaxies within a cluster that forms
hierarchically in a standard cold dark matter N-body simulation. At a redshift
z=0.5 we select several dark matter halos that have quiet merger histories and
are about to enter the newly forming cluster environment. The halos are
replaced with equilibrium high resolution model spirals that are constructed to
represent luminous examples of low surface brightness (LSB) and high surface
brightness (HSB) galaxies. Whilst the models have the same total luminosity,
\sim L_*, they have very different internal mass profiles, core radii and disk
scale lengths, however they all lie at the same place on the Tully-Fisher
relation. Due to their ``soft'' central potentials, LSB galaxies evolve
dramatically under the influence of rapid encounters with dark matter halos,
substructure and strong tidal shocks from the global cluster potential - galaxy
harassment. As much as 90% of the LSB disk stars are tidally stripped and
congregate in large diffuse tails that trace the orbital path of the galaxy and
form the diffuse intra-cluster light. The bound stellar remnants closely
resemble the dwarf spheroidals (dE's) that populate nearby clusters, with large
scale lengths and low central surface brightness.


  In reply to Vaidman's Comment [arXiv:1304.6689], we show that his claim that
our Protocol for Direct Counterfactual Quantum Communication [PRL 110, 170502
(2013), arXiv:1206.2042] is counterfactual only for one type of information bit
is wrong.


  One of the greatest challenges of science is to understand the current
accelerated expansion of the Universe. In this work, we show that by
considering the quantum nature of the gravitational field, its wavelength can
be associated with an effective Compton mass. We propose that this mass can be
interpreted as dark energy, with a Compton wavelength given by the size of the
observable Universe, implying that the dark energy varies depending on this
size. If we do so, we find that: 1.- Even without any free constant for dark
energy, the evolution of the Hubble parameter is exactly the same as for the
LCDM model, so we expect this model to have the same predictions as LCDM. 2.-
The density rate of the dark energy is $\Omega_{\Lambda}= 0.69$ which is a very
similar value as the one found by the Planck satellite $\Omega_{\Lambda}=
0.684$. 3.- The dark energy has this value because it corresponds to the actual
size of the radius of the Universe, thus the coincidence problem has a very
natural explanation. 4.-It is possible to find also a natural explanation to
why observations inferred from the local distance ladder find the value $H_0=
73$ km/s/Mpc for the Hubble constant. We show that if we take the variability
of the dark energy into account, they should measure $H_0= 67.3$ km/s/Mpc as
well. 5.-In this model the inflationary period contains a natural successful
graceful exit.