  We consider an optimization problem in which a (single) bat aims to exploit
the nectar in a set of $n$ cacti with the objective of maximizing the expected
total amount of nectar it drinks. Each cactus $i \in [n]$ is characterized by a
parameter $r_{i} > 0$ that determines the rate in which nectar accumulates in
$i$. In every round, the bat can visit one cactus and drink all the nectar
accumulated there since its previous visit. Furthermore, competition with other
bats, that may also visit some cacti and drink their nectar, is modeled by
means of a stochastic process in which cactus $i$ is emptied in each round
(independently) with probability $0 < s_i < 1$. Our attention is restricted to
purely-stochastic strategies that are characterized by a probability vector
$(p_1, \ldots, p_n)$ determining the probability $p_i$ that the bat visits
cactus $i$ in each round. We prove that for every $\epsilon > 0$, there exists
a purely-stochastic strategy that approximates the optimal purely-stochastic
strategy to within a multiplicative factor of $1 + \epsilon$, while exploiting
only a small core of cacti. Specifically, we show that it suffices to include
at most $\frac{2 (1 - \sigma)}{\epsilon \cdot \sigma}$ cacti in the core, where
$\sigma = \min_{i \in [n]} s_{i}$. We also show that this upper bound on core
size is asymptotically optimal as a core of a significantly smaller size cannot
provide a $(1 + \epsilon)$-approximation of the optimal purely-stochastic
strategy. This means that when the competition is more intense (i.e., $\sigma$
is larger), a strategy based on exploiting smaller cores will be favorable.


  Let $k$ be a field, $C\to \Spec k$ be a stable curve and let $G$ be a finite
group acting faithfully on the curve $C\to \Spec k$. In this article, we
compute the vector space $\Ext^1_G(\Omega_{C/k}, \O_C)$, the sheaf
$\Omega_{C/k}$ being the sheaf of relative differentials. This vector space is
naturally isomorphic to the set of first order $G$-equivariant deformations of
$C$. The computation we do here will be used in a future article.


  In this paper, we improve semantic segmentation by automatically learning
from Flickr images associated with a particular keyword, without relying on any
explicit user annotations, thus substantially alleviating the dependence on
accurate annotations when compared to previous weakly supervised methods.
  To solve such a challenging problem, we leverage several low-level cues (such
as saliency, edges, etc.) to help generate a proxy ground truth. Due to the
diversity of web-crawled images, we anticipate a large amount of 'label noise'
in which other objects might be present. We design an online noise filtering
scheme which is able to deal with this label noise, especially in cluttered
images. We use this filtering strategy as an auxiliary module to help assist
the segmentation network in learning cleaner proxy annotations. Extensive
experiments on the popular PASCAL VOC 2012 semantic segmentation benchmark show
surprising good results in both our WebSeg (mIoU = 57.0%) and weakly supervised
(mIoU = 63.3%) settings.


  Context: System Theoretic Process Analysis for Privacy (STPA-Priv) is a novel
privacy risk elicitation method using a top down approach. It has not gotten
very much attention but may offer a convenient structured approach and
generation of additional artifacts compared to other methods. Aim: The aim of
this exploratory study is to find out what benefits the privacy risk
elicitation method STPA-Priv has and to explain how the method can be used.
Method: Therefore we apply STPA-Priv to a real world health scenario that
involves a smart glucose measurement device used by children. Different kinds
of data from the smart device including location data should be shared with the
parents, physicians, and urban planners. This makes it a sociotechnical system
that offers adequate and complex privacy risks to be found. Results: We find
out that STPA-Priv is a structured method for privacy analysis and finds
complex privacy risks. The method is supported by a tool called XSTAMPP which
makes the analysis and its results more profound. Additionally, we learn that
an iterative application of the steps might be necessary to find more privacy
risks when more information about the system is available later. Conclusions:
STPA-Priv helps to identify complex privacy risks that are derived from
sociotechnical interactions in a system. It also outputs privacy constraints
that are to be enforced by the system to ensure privacy.


  I motivate and discuss non-minimal and non-universal models of supersymmetry
and supergravity consistent with string unification at $10^{16}$ GeV.


  We consider convex optimization problems with the objective function having
Lipshitz-continuous $p$-th order derivative, where $p\geq 1$. We propose a new
tensor method, which closes the gap between the lower
$O\left(\varepsilon^{-\frac{2}{3p+1}} \right)$ and upper
$O\left(\varepsilon^{-\frac{1}{p+1}} \right)$ iteration complexity bounds for
this class of optimization problems.
  We also consider uniformly convex functions, and show how the proposed method
can be accelerated under this additional assumption. Moreover, we introduce a
$p$-th order condition number which naturally arises in the complexity analysis
of tensor methods under this assumption.
  Finally, we make a numerical study of the proposed optimal method and show
that in practice it is faster than the best known accelerated tensor method. We
also compare the performance of tensor methods for $p=2$ and $p=3$ and show
that the 3rd-order method is superior to the 2nd-order method in practice.


  This paper presents a new approach to intra-cell pilot contamination in
crowded massive MIMO scenarios. The approach relies on two essential properties
of a massive MIMO system, namely near-orthogonality between user channels and
near-stability of channel powers. Signal processing techniques that take
advantage of these properties allow us to view a set of contaminated pilot
signals as a graph code on which iterative belief propagation can be performed.
This makes it possible to decontaminate pilot signals and increase the
throughput of the system. The proposed solution exhibits high performance with
large improvements over the conventional method. The improvements come at the
price of an increased error rate, although this effect is shown to decrease
significantly for increasing number of antennas at the base station.


  In this note the following is proved. Separable L-embedded spaces - that is
separable Banach spaces which are complemented in their biduals such that the
norm between the two complementary subspaces is additive - have property (X)
which, by a result of Godefroy and Talagrand, entails uniqueness of the space
as a predual.


  Automatic diagnosis of malignant melanoma highly depends on the segmentation
methods used for the suspicious lesion. We suggest the parameter selection
method (PSM) and maximum area method (MAM) for the segmentation of the lesion
to be diagnosed. Herein, these segmentation methods are compared to a skin
cancer expert's segmentation and three other conventional algorithms. The
diagnosis of malignant melanoma based on the two suggested, three conventional,
and expert's segmentation are compared with respect to sensitivity,
specificity, and accuracy.


  The scalar mode temperature fluctuations of the cosmic microwave background
has been derived in a spatially closed universe from two different methods.
First, by following the photon trajectory after the last scattering and then
from the Boltzmann equation in a closed background and the line of sight
integral method. An analytic expression for the temperature multipole
coefficient has been extracted at the hydrodynamical limit, where we have
considered some tolerable approximations. By considering a realistic set of
cosmological parameters taken from a fit to data from Planck, the TT power
spectrum in the scalar mode for the closed universe has been compared with
numerical one by using the CAMB code and also latest observational data. The
analytic result agrees with the numerical one on almost all scales. The peak
positions are in very good agreement with numerical result while the peak
heights agree with that to within 10% due to the approximations have been
considered for this derivation.


  A novel way of characterizing the process of reaching consensus for a social
system is given. The foundation of the characterization is based on the theorem
which states that the sufficient and necessary condition for a system to reach
the state of consensus is the occurrence of communicators, defined as the units
of the system that can directly communicate with all the others simultaneously.
A model is proposed to illustrate the characterization explicitly. The
existence of communicators provides an efficient way for unifying two systems
that a state of consensus is guaranteed after the mergence.


  The classical action of a two dimensional N=2 supersymmetric theory,
characterized by a general K\"{a}hler potential, is written down on a
non(anti)commutative superspace. The action has a power series expansion in
terms of the determinant of the non(anti)commutativity parameter
$C^{\alpha\beta}$. The theory is explicitly shown to preserve half of the N=2
supersymmetry, to all orders in (det C)^n. The results are further generalized
to include arbitrary superpotentials as well.


  Graphene oxide (GO) is widely used in different applications, however once
release into the environment it can change its structure and affect the
transport of important contaminants such as arsenic. In this work we show that
UV radiation, even in the range of 28-74 uW/cm2 of irradiance up to 120 h of
exposure, can induce important changes in the structure of graphene oxide, by
eliminating -OH and C=O functional groups. This reduction affected the
stability of graphene oxide in water by decreasing its zeta potential from 41
to 37 mV with the increase of the exposure time. Our results showed that after
24 h of UV exposure, As(III) adsorption capacity decreased from 5 mg/g to 4.7
mg/g, however after 48 h of irradiation the adsorption increased with time,
reaching 5.1 mg/g at 120 h under 74 uW/cm2 of irradiation. Computer modelling
showed that even a degraded GO structure can have an interaction energy of 53
kcal/mol with H3AsO3. Furthermore, we observed that despite clear changes in
surface composition and particle size, the reduction of graphene oxide
maintained a high degree of cytotoxicity since cell viability decreased to 60%
with a 50 ug/ml dose; except for the sample irradiated at 74 uW/cm2 for five
days, which showed 20% with the same concentration.


  The pomeron-pomeron interaction is studied in the perturbative approach of
BFKL-Bartels. The total pomeron-pomeron cross-section is proportional to
$\alpha_{s}^{4}s^{\Delta}/\sqrt {t_{1}t_{2}}$ where $\sqrt{s}$ is the c.m.
energy and $t_{1,2}$ are the virtualities of the colliding pomerons. Upon
calculating the coefficient the cross-section is found to be of the order 2.2
mb at $\sqrt{s}= 6$ TeV and $\sqrt{-t_{1}}\sim\sqrt{-t_{2}}\sim 1$ GeV/c.


  We present new results from the VLBA 2 cm Survey, an imaging survey of active
galactic nuclei (AGN) at sub-milliarcsecond resolution. We extend the
structural variability monitoring program of more than 130 extragalactic
parsec-scale radio jets from over 170 AGN to a total of eight years. The sample
is explored further in time for all sources, and intensively for individual
objects. We report new detailed results on the compact sources III Zw 2, AO
0235+16, and NRAO 512.


  In this paper we present two terminating tableau calculi for propositional
Dummett logic obeying the subformula property. The ideas of our calculi rely on
the linearly ordered Kripke semantics of Dummett logic. The first calculus
works on two semantical levels: the present and the next possible world. The
second calculus employs the usual object language of tableau systems and
exploits a property of the construction of the completeness theorem to
introduce a check which is an alternative to loop check mechanisms.


  Propagation of ion-acoustic solitary waves (IASWs) is studied using the
hydrodynamic equations coupled with the Poisson equation in a warm plasma
consisting of adiabatic ions and superthermal (Kappa distributed) electrons in
presence of an electron-beam component. In the linear limit, the dispersion
relation for ion-acoustic (IA) waves is obtained by linearizing of basic
equations. On the other hand, in the nonlinear analysis, an energy-balance like
equation involving Sagdeev's pseudo-potential is derived in order to
investigate arbitrary amplitude IA solitons. The Mach number range is
determined in which, propagation and characteristics of IA solitons are
analyzed both parametrically and numerically. The variation of amplitude and
width of electrostatic (ES) excitations as a result of superthermality (via)
and also the physical parameters (ion temperature, soliton speed, electron-beam
density and electron-beam velocity) are examined. A typical interaction between
IASWs and the electron-beam in plasma is confirmed. It is also found that ES
solitons with both negative polarity (rarefactive solitons) and positive
polarity (compressive solitons) can coexist in plasma. Furthermore, the small
but finite amplitude limit of IASWs is investigated and it is showed that this
limit is restricted to negative potential pulses.


  We study the separable complementation property (SCP) and its natural
variations in Banach spaces of continuous functions over compacta $K_{\mathcal
A}$ induced by almost disjoint families ${\mathcal A}$ of countable subsets of
uncountable sets. For these spaces, we prove among others that $C(K_{\mathcal
A})$ has the controlled variant of the separable complementation property if
and only if $C(K_{\mathcal A})$ is Lindel\"of in the weak topology if and only
if $K_{\mathcal A}$ is monolithic. We give an example of ${\mathcal A}$ for
which $C(K_{\mathcal A})$ has the SCP, while $K_{\mathcal A}$ is not monolithic
and an example of a space $C(K_{\mathcal A})$ with controlled and continuous
SCP which has neither a projectional skeleton nor a projectional resolution of
the identity. Finally, we describe the structure of almost disjoint families of
cardinality $\omega_1$ which induce monolithic spaces of the form $K_{\mathcal
A}$: They can be obtained from countably many ladder systems and pairwise
disjoint families applying simple operations.


  Recently, biclustering is one of the hot topics in bioinformatics and takes
the attention of authors from several different disciplines. Hence, many
different methodologies from a variety of disciplines are proposed as a
solution to the biclustering problem. As a consequence of this issue, a variety
of solutions makes it harder to evaluate the proposed methods. With this review
paper, we are aimed to discuss both analysis and visualization of biclustering
as a guide for the comparisons between brand new and existing biclustering
algorithms. Additionally, we concentrate on the tools that provide
visualizations with accompanied analysis techniques. Through the paper, we give
several references that are also a short review of the state of the art for the
ones who will pursue research on biclustering. The Paper outline is as follows;
we first give the visualization and analysis methods, then we evaluate each
proposed tool with the visualization contribution and analysis options,
finally, we discuss future directions for biclustering and we propose standards
for future work.


  Aims. To develop a deep-learning based system for recognition of subclinical
atherosclerosis on a plain frontal chest x-ray. Methods and Results. A
deep-learning algorithm to predict coronary artery calcium (CAC) score (the
AI-CAC model) was developed on 460 chest x-ray (80% training cohort, 20%
internal validation cohort) of primary prevention patients (58.4% male, median
age 63 [51-74] years) with available paired chest x-ray and chest computed
tomography (CT) indicated for any clinical reason and performed within 3
months. The CAC score calculated on chest CT was used as ground truth. The
model was validated on an temporally-independent cohort of 90 patients from the
same institution (external validation). The diagnostic accuracy of the AI-CAC
model assessed by the area under the curve (AUC) was the primary outcome.
Overall, median AI-CAC score was 35 (0-388) and 28.9% patients had no AI-CAC.
AUC of the AI-CAC model to identify a CAC>0 was 0.90 in the internal validation
cohort and 0.77 in the external validation cohort. Sensitivity was consistently
above 92% in both cohorts. In the overall cohort (n=540), among patients with
AI-CAC=0, a single ASCVD event occurred, after 4.3 years. Patients with
AI-CAC>0 had significantly higher Kaplan Meier estimates for ASCVD events
(13.5% vs. 3.4%, log-rank=0.013). Conclusion. The AI-CAC model seems to
accurately detect subclinical atherosclerosis on chest x-ray with elevated
sensitivity, and to predict ASCVD events with elevated negative predictive
value. Adoption of the AI-CAC model to refine CV risk stratification or as an
opportunistic screening tool requires prospective evaluation.


  In this article we address the problem of text passage alignment across
interlingual article pairs in Wikipedia. We develop methods that enable the
identification and interlinking of text passages written in different languages
and containing overlapping information. Interlingual text passage alignment can
enable Wikipedia editors and readers to better understand language-specific
context of entities, provide valuable insights in cultural differences and
build a basis for qualitative analysis of the articles. An important challenge
in this context is the trade-off between the granularity of the extracted text
passages and the precision of the alignment. Whereas short text passages can
result in more precise alignment, longer text passages can facilitate a better
overview of the differences in an article pair. To better understand these
aspects from the user perspective, we conduct a user study at the example of
the German, Russian and the English Wikipedia and collect a user-annotated
benchmark. Then we propose MultiWiki -- a method that adopts an integrated
approach to the text passage alignment using semantic similarity measures and
greedy algorithms and achieves precise results with respect to the user-defined
alignment. MultiWiki demonstration is publicly available and currently supports
four language pairs.


  The electron transport layer (ETL) plays a fundamental role in perovskite
solar cells. Recently, graphene-based ETLs have been proved to be good
candidate for scalable fabrication processes and to achieve higher carrier
injection with respect to most commonly used ETLs. In this work we
experimentally study the effects of different graphene-based ETLs in sensitized
MAPI solar cells. By means of time-integrated and picosecond time-resolved
photoluminescence techniques, the carrier recombination dynamics in MAPI films
embedded in different ETLs is investigated. Using graphene doped mesoporous
TiO2 (G+mTiO2) with the addition of a lithium-neutralized graphene oxide
(GO-Li) interlayer as ETL, we find that the carrier collection efficiency is
increased by about a factor two with respect to standard mTiO2. Taking
advantage of the absorption coefficient dispersion, we probe the MAPI layer
morphology, along the thickness, finding that the MAPI embedded in the ETL
composed by G+mTiO2 plus GO-Li brings to a very good crystalline quality of the
MAPI layer with a trap density about one order of magnitude lower than that
found with the other ETLs. In addition, this ETL freezes MAPI at the tetragonal
phase, regardless of the temperature. Graphene-based ETLs can open the way to
significant improvement of perovskite solar cells.


  We show that if a field k contains sufficiently many elements(for instance,
if k is infinite), and K is an algebraically closed field containing k, then
every linear algebraic k-group over K is k-isomorphic to Aut(A\otimes_kK),
where A is a finite dimensional simple algebra over k.


  The standard kinetic path integral for all spatially closed Brownian paths
(loops) of duration t weighted by the product mn is evaluated, where m and n
are the linking numbers of the Brownian loop with two arbitrary curves in 3D
space. The path integral thus indicates the extent to which these two linking
numbers are correlated, ranging from the value zero for far apart curves when
it is unlikely that the Brownian loop links with both, to (plus or minus)
infinity for nearly coincident curves. The result takes a form that loosely
resembles that for the mutual inductance of two current carrying curves in
magnetostatics, a double integral, but dependent on a single extra parameter,
the duration t of the path. The result for the equivalent two-dimensional
problem was given previously [Hannay 2018].


  In sterile neutrino (3+1) parameterisation, we observe that sterile phases
($\delta_{14},\delta_{24}$) are always together in oscillation probability,
even when the MSW effect is considered. We see that the difference between the
sterile phases has a more dominating effect over event rates compared to small
variations due to changes in individual values. In this work, we show the value
of sterile phase difference ($\delta_{14}-\delta_{24}$) that least affects the
parameter degeneracy resolution of $\delta_{13},\theta_{23}$ at long-baseline
experiments.


  We theoretically show that IV-VI semiconducting compounds with
low-temperature rhombohedral crystal structure represent a new potential
platform for topological semimetals. By means of minimal
$\mathbf{k}\cdot\mathbf{p}$ models we find that the two-step structural
symmetry reduction of the high-temperature rocksalt crystal structure,
comprising a rhombohedral distortion along the [111] direction followed by a
relative shift of the cation and anion sublattices, gives rise to topologically
protected Weyl semimetal and nodal line semimetal phases. We derive general
expressions for the nodal features and apply our results to SnTe showing
explicitly how Weyl points and nodal lines emerge in this system.
Experimentally, the topological semimetals could potentially be realized in the
low-temperature ferroelectric phase of SnTe, GeTe and related alloys.


  In Hindsight Experience Replay (HER), a reinforcement learning agent is
trained by treating whatever it has achieved as virtual goals. However, in
previous work, the experience was replayed at random, without considering which
episode might be the most valuable for learning. In this paper, we develop an
energy-based framework for prioritizing hindsight experience in robotic
manipulation tasks. Our approach is inspired by the work-energy principle in
physics. We define a trajectory energy function as the sum of the transition
energy of the target object over the trajectory. We hypothesize that replaying
episodes that have high trajectory energy is more effective for reinforcement
learning in robotics. To verify our hypothesis, we designed a framework for
hindsight experience prioritization based on the trajectory energy of goal
states. The trajectory energy function takes the potential, kinetic, and
rotational energy into consideration. We evaluate our Energy-Based
Prioritization (EBP) approach on four challenging robotic manipulation tasks in
simulation. Our empirical results show that our proposed method surpasses
state-of-the-art approaches in terms of both performance and sample-efficiency
on all four tasks, without increasing computational time. A video showing
experimental results is available at https://youtu.be/jtsF2tTeUGQ


  High-resolution simulations of supermassive black holes in isolated galaxies
have suggested the importance of short (~10 Myr) episodes of rapid accretion
caused by interactions between the black hole and massive dense clouds within
the host. Accretion of such clouds could potentially provide the dominant
source for black hole growth in high-z galaxies, but it remains unresolved in
cosmological simulations. Using a stochastic subgrid model calibrated by
high-resolution isolated galaxy simulations, we investigate the impact that
variability in black hole accretion rates has on black hole growth and the
evolution of the host galaxy. We find this clumpy accretion to more efficiently
fuel high-redshift black hole growth. This increased mass allows for more rapid
accretion even in the absence of high-density clumps, compounding the effect
and resulting in substantially faster overall black hole growth. This increased
growth allows the black hole to efficiently evacuate gas from the central
region of the galaxy, driving strong winds up to ~2500 km/s, producing outflows
~10x stronger than the smooth accretion case, suppressing the inflow of gas
onto the host galaxy, and suppressing the star formation within the galaxy by
as much as a factor of two. This suggests that the proper incorporation of
variability is a key factor in the co-evolution between black holes and their
hosts.


  This is a survey article on classical groups (over arbitrary division rings)
and their geometries.


  Flexible loads, i.e. the loads whose power trajectory is not bound to a
specific one, constitute a sizable portion of current and future electric
demand. This flexibility can be used to improve the performance of the grid,
should the right incentives be in place.
  In this paper, we consider the optimal decision making problem faced by a
flexible load, demanding a certain amount of energy over its availability
period, subject to rate constraints. The load is also capable of providing
Ancillary Services (AS) by decreasing or increasing its consumption in response
to signals from the Independent System Operator. Under arbitrarily distributed
and correlated Markovian energy and AS prices, we obtain the optimal policy for
minimizing expected total cost, which includes cost of energy and benefits from
AS provision, assuming no capacity reservation requirement for AS provision. We
also prove that the optimal policy has a multi-threshold form and can be
computed, stored and operated efficiently. We further study the effectiveness
of our proposed optimal policy and its impact on the grid.
  We show that, while optimal simultaneous consumption and AS provision under
real-time stochastic prices is achievable with acceptable computational burden,
the impact of adopting such real-time pricing schemes on the network might not
be as good as suggested by the majority of the existing literature. In fact, we
show that such price responsive loads are likely to induce peak-to-average
ratios much more than what is observed in the current distribution networks and
adversely affect the grid.


  Let $u_{2j}$ be the product of the odd positive integers $< 2j$. For $n$ an
integer $\ge 1$, define \[ f(x)=\sum_{j=0}^{n}a_j\frac{x^{2j}}{u_{2j+2}}, \]
where the $a_j$'s are arbitrary integers with $|a_0|=1$. In 1929, I. Schur
established a general theorem about the factorization of $f(x)$ in the case
that $|a_{n}| = 1$. We establish a more general result in which $|a_{n}|$ is
allowed to be larger, and show that the result is in some sense best possible.


  I contrast two possible attitudes towards a given branch of physics: as
inferential (i.e., as concerned with an agent's ability to make predictions
given finite information), and as dynamical (i.e., as concerned with the
dynamical equations governing particular degrees of freedom). I contrast these
attitudes in classical statistical mechanics, in quantum mechanics, and in
quantum statistical mechanics; in this last case, I argue that the
quantum-mechanical and statistical-mechanical aspects of the question become
inseparable. Along the way various foundational issues in statistical and
quantum physics are (hopefully!) illuminated.


  Exact solution of Dirac equation for a particle whose potential energy and
mass are inversely proportional to the distance from the force centre has been
found. The bound states exist provided the length scale $a$ which appears in
the expression for the mass is smaller than the classical electron radius
$e^2/mc^2$. Furthermore, bound states also exist for negative values of $a$
even in the absence of the Coulomb interaction. Quasirelativistic expansion of
the energy has been carried out, and a modified expression for the fine
structure of energy levels has been obtained. The problem of kinetic energy
operator in the Schr\"odinger equation is discussed for the case of
position-dependent mass. In particular, we have found that for highly excited
states the mutual ordering of the inverse mass and momentum operator in the
non-relativistic theory is not important.


  Highly eccentric binary systems appear in many astrophysical contexts,
ranging from tidal capture in dense star clusters, precursors of stellar
disruption by massive black holes, to high-eccentricity migration of giant
planets. In a highly eccentric binary, the tidal potential of one body can
excite oscillatory modes in the other during a pericenter passage, resulting in
energy exchange between the modes and the binary orbit. These modes exhibit one
of three behaviors over multiple passages: low-amplitude oscillations, large
amplitude oscillations corresponding to a resonance between the orbital
frequency and the mode frequency, and chaotic growth. We study these phenomena
with an iterative map, fully exploring how the mode evolution depends on the
pericenter distance and other parameters. In addition, we show that the
dissipation of mode energy results in a quasi-steady state, with gradual
orbital decay punctuated by resonances, even in systems where the mode
amplitude would initially grow stochastically. A newly captured star around a
black hole can experience significant orbital decay and heating due to the
chaotic growth of the mode amplitude and dissipation. A giant planet pushed
into a high-eccentricity orbit may experience a similar effect and become a hot
or warm Jupiter.


  Quantum networks are promising tools for the implementation of long-range
quantum communication. The characterization of quantum correlations in networks
and their usefulness for information processing is therefore central for the
progress of the field, but so far only results for small basic network
structures or pure quantum states are known. Here we show that symmetries
provide a versatile tool for the analysis of correlations in quantum networks.
We provide an analytical approach to characterize correlations in large network
structures with arbitrary topologies. As examples, we show that entangled
quantum states with a bosonic or fermionic symmetry can not be generated in
networks; moreover, cluster and graph states are not accessible. Our methods
can be used to design certification methods for the functionality of specific
links in a network and have implications for the design of future network
structures.


  We present a combined experimental and theoretical investigation of the 193
nm photolysis of the cyano-ester, methyl cyanoformate (MCF). Specifically,
nanosecond time-resolved infrared emission spectroscopy was used to monitor the
ro-vibrationally excited photoproducts generated in the photolysis reaction.
The signal-to-noise of all time-resolved spectra were enhanced using the
recently developed algorithm, spectral reconstruction analysis, which allowed
observation of previously obscured minor resonances, and revealed new
dissociation channels producing HCN and HNC. Spectral fit analysis of the
nascent HCN and electronically excited CN($A^2\Pi_1$) resonances yield a lower
bound estimate for the HCN quantum yield of ca. 0.42$\pm$0.24%.
Multi-configuration self-consistent field calculations were used to interrogate
the ground and four lowest energy singlet excited states of MCF. At 193 nm,
dissociation is predicted to occur predominantly on the repulsive S$_2$ state.
Nevertheless, minor pathways leading to the production of highly excited ground
state MCF are available via cascading internal conversion from nascent S$_2$
population. An automated transition-state search algorithm was employed to
identify the corresponding ground state dissociation channels, and
Rice-Ramsperger-Kassel-Marcus and Kinetic Monte Carlo kinetic simulations were
used to calculate the associated branching ratios. The proposed mechanism was
validated by direct comparison of the experimentally measured and
quasi-classical trajectory deduced nascent internal energy distribution of HCN,
which were found to be in near perfect agreement. The propensity for cyano
containing hydrocarbons to act as photolytic sources for ro-vibrationally
excited HCN and HNC, as well as their significance to astrophysical
environments, are discussed.


  The L\'evy-Ciesielski Construction of Brownian motion is used to determine
non-asymptotic estimates for the maximal deviation of increments of a Brownian
motion process $(W_{t})_{t\in \left[ 0,T\right] }$ normalized by the global
modulus function, for all positive $\varepsilon $ and $\delta $. Additionally,
uniform results over $\delta $ are obtained. Using the same method,
non-asymptotic estimates for the distribution function for the standard
Brownian motion normalized by its local modulus of continuity are obtained.
Similar results for the truncated Brownian motion are provided and play a
crucial role in establishing the results for the standard Brownian motion case.


  The search for a quantum theory of gravity has led to the discovery of
quantum many-body systems that are dual to gravitational models with quantum
properties. The perhaps most famous of these systems is the Sachdev-Ye-Kitaev
(SYK) model. It features maximal scrambling of quantum information, and opens a
potential inroad to experimentally investigating aspects of quantum gravity. A
scalable laboratory realisation of this model, however, remains outstanding.
Here, we propose a feasible implementation of the SYK model in cavity quantum
electrodynamics platforms. Through detailed analytical and numerical
demonstrations, we show how driving a cloud of fermionic atoms trapped in a
multi-mode optical cavity, and subjecting it to a spatially disordered AC-Stark
shift retrieves the physics of the SYK model, with random all-to-all
interactions and fast scrambling. Our work provides a blueprint for realising
the SYK model in a scalable system, with the prospect of studying holographic
quantum matter in the laboratory.


  We estimate the 1--D power spectrum and the integral density of neighbors in
14 QSO lines of sight. We discuss their variation with respect to redshift and
column density and compare the results with standard CDM models.


  In this paper we study the geometry of the moduli space of (non-strongly)
parabolic Higgs bundles over a Riemann surface with marked points. We show that
this space possesses a Poisson structure, extending the one on the dual of an
Atiyah algebroid over the moduli space of parabolic vector bundles. By
considering the case of full flags, we get a Grothendieck-Springer resolution
for all other flag types, in particular for the moduli spaces of twisted Higgs
bundles, as studied by Markman and Bottacin and used in the recent work of
Laumon-Ng\^o. We discuss the Hitchin system, and demonstrate that all these
moduli spaces are integrable systems in the Poisson sense.


  We find the first three (even) structure factor moments for a (non-quantum)
one-component Jellium made of particles living in three dimensions and
interacting with a Coulomb pair-potential plus a short-range term with either a
finite range or decaying exponentially fast at large distances. Starting from
the hierarchical Born-Green-Yvon equations we show that they are all form
invariant respect to the addition of the short-range term. We discuss the
relevance of the present study to interpret the failure of the moment sum-rules
of ionic-liquids at criticality.


  We propose a general scheme to generate entanglement encoded in the
photon-number basis, via a sequential resonant two-photon excitation of a
three-level system. We apply it to the specific case of a quantum dot
three-level system, which can emit a photon pair through a biexciton-exciton
cascade. The state generated in our scheme constitutes a tool for secure
communication, as the multipartite correlations present in the produced state
may provide an enhanced rate of secret communication with respect to a perfect
GHZ state.


  We prove the Central Limit Theorem for the Euler-Poincar\'e characteristic of
Berry's random wave model in a growing domain. We also show Gaussian
fluctuations for a class of Berry's mixture models that correspond to a
perturbation of the initial random field. Finally, some statistical
applications, explicit calculations of the variance of the perturbed Berry's
model and numerical investigations are provided to support our theoretical
results.


  We study the current-driven motion of metastable localized spin structures
with various topological charges in a (Pt$_{1-x}$Ir$_{x}$)/Fe bilayer on a
Pd(111) surface by combining atomistic spin model simulations with an approach
based on the generalized Thiele equation. We demonstrate that besides a
distinct dependence on the topological charge itself the dynamic response of
skyrmionic structures with topological charges $\mathrm{Q} = -1$ and
$\mathrm{Q}= 3$ to a spin-polarized current exhibits an orientation dependence.
We further show that such an orientation dependence can be induced by applying
an in-plane external field, possibly opening up a new pathway to the
manipulation of skyrmion dynamics.


  The semi classical cosmology approximation for a Friedman Robertson Walker
geometry coupled to a field is considered. A power series of the field with
coefficients that depend on the radius of the geometry is proposed, and the
equations for the coefficients are solved.


  Upcoming galaxy surveys aim to map the Universe with unprecedented precision,
depth and sky coverage. The galaxy bispectrum is a prime source of information
as it allows us to probe primordial non-Gaussianity (PNG), a key factor in
differentiating various models of inflation. On the scales where local PNG is
strongest, Doppler and other relativistic effects become important and need to
be included. We investigate the detectability of relativistic and local PNG
contributions in the galaxy bispectrum. We compute the signal-to-noise ratio
for the detection of the bispectrum including such effects. Furthermore, we
perform information matrix forecasts on the local PNG parameter $f_{\rm NL}$
and on the parametrised amplitudes of the relativistic corrections. Finally, we
quantify the bias on the measurement of $f_{\rm NL}$ that arises from
neglecting relativistic effects. Our results show that detections of both
first- and second-order relativistic effects are promising with forthcoming
spectroscopic survey specifications -- and are largely unaffected by the
uncertainty in $f_{\rm NL}$. Conversely, we show for the first time that
neglecting relativistic corrections in the galaxy bispectrum can lead to
$>\!1.5\sigma(f_{\rm NL})$ shift on the detected value of $f_{\rm NL}$,
highlighting the importance of including relativistic effects in our modelling.


  We give a tight bound for the triple intersection numbers of Paley graphs. In
particular, we show that any three vertices have a common neighbor in Paley
graphs of order larger than 25.


  We present a new technique for identifying stellar mass black holes in low
mass X-ray binaries (LMXBs), and apply it to XMM-Newton observations of M31. We
examine X-ray time series variability seeking power density spectra (PDS)
typical of LMXBs accreting at a low accretion rate (which we refer to as Type A
PDS); these are very similar for black hole and neutron star LMXBs. Galactic
neutron star LMXBs exhibit Type A PDS at low luminosities (~10^36--10^37 erg/s)
while black hole LMXBs can exhibit them at luminosities >10^38 erg/s. We
propose that Type A PDS are confined to luminosities below a critical fraction
of the Eddington limit, $l_c$ that is constant for all LMXBs; we have examined
asample of black hole and neutron star LMXBs and find they are all consistent
with $l_c$ = 0.10+/-0.04 in the 0.3--10 keV band. We present luminosity and PDS
data from 167 observations of X-ray binaries in M31 that provide strong support
for our hypothesis. Since the theoretical maximum mass for a neutron star is
\~3.1 M_Sun, we therefore assert that any LMXB that exhibits a Type A PDS at a
0.3--10 keV luminosity greater than 4 x 10^37 erg/s is likely to contain a
black hole primary. We have found eleven new black hole candidates in M31 using
this method. We focus on XMM-Newton observations of RX J0042.4+4112, an X-ray
source in M31 and find the mass of the primary to be 7+/-2 M_Sun, if our
assumptions are correct. Furthermore, RX J0042.4+4112 is consistently bright in
\~40 observations made over 23 years, and is likely to be a persistently bright
LMXB; by contrast all known Galactic black hole LMXBs are transient. Hence our
method may be used to find black holes in known, persistently bright Galactic
LMXBs and also in LMXBs in other galaxies.


  Marx (STOC~2010, J.~ACM 2013) introduced the notion of submodular width of a
conjunctive query (CQ) and showed that for any class $\Phi$ of Boolean CQs of
bounded submodular width, the model-checking problem for $\Phi$ on the class of
all finite structures is fixed-parameter tractable (FPT). Note that for
non-Boolean queries, the size of the query result may be far too large to be
computed entirely within FPT time. We investigate the free-connex variant of
submodular width and generalise Marx's result to non-Boolean queries as
follows: For every class $\Phi$ of CQs of bounded free-connex submodular width,
within FPT-preprocessing time we can build a data structure that allows to
enumerate, without repetition and with constant delay, all tuples of the query
result. Our proof builds upon Marx's splitting routine to decompose the query
result into a union of results; but we have to tackle the additional technical
difficulty to ensure that these can be enumerated efficiently.


  For A a separable unital C*-algebra and M a separable McDuff II_1-factor, we
show that the space Hom_w(A,M) of weak approximate unitary equivalence classes
of unital *-homomorphisms A \rightarrow M may be considered as a closed,
bounded, convex subset of a separable Banach space -- a variation on N. Brown's
convex structure Hom(N,R^U). When A is nuclear, Hom_w(A,M) is affinely
homeomorphic to the trace space of A, but in general Hom_w(A,M) and the trace
space of A do not share the same data (several examples are provided). We
characterize extreme points of Hom_w(A,M) in the case where either A or M is
amenable; and we give two different conditions -- one necessary and the other
sufficient -- for extremality in general. The universality of C*(F_\infty) is
reflected in the fact that for any unital separable A, Hom_w(A,M) may be
embedded as a face in Hom_w(C*(F_\infty),M). We also extend Brown's
construction to apply more generally to Hom(A,M^U).


  We consider the goal-oriented error estimates for a linearized iterative
solver for nonlinear partial differential equations. For the adjoint problem
and iterative solver we consider, instead of the differentiation of the primal
problem, a suitable linearization which guarantees the adjoint consistency of
the numerical scheme. We derive error estimates and develop an efficient
adaptive algorithm which balances the errors arising from the discretization
and use of iterative solvers. Several numerical examples demonstrate the
efficiency of this algorithm.


  In large wireless networks, acquiring full network state information is
typically infeasible. Hence, nodes need to flow the information and manage the
interference based on partial information about the network. In this paper, we
consider multi-hop wireless networks and assume that each source only knows the
channel gains that are on the routes from itself to other destinations in the
network. We develop several distributed strategies to manage the interference
among the users and prove their optimality in maximizing the achievable
normalized sum-rate for some classes of networks.


  The crystallography of displacive phase transformations can be described with
three types of matrices: the lattice distortion matrix, the orientation
relationship matrix, and the correspondence matrix. The paper gives some
formula to express them in crystallographic bases, orthonormal bases, and
reciprocal bases, and it explains how to use them to deduce the matrices of
inverse transformation. In the case of hard-sphere assumption, a continuous
form of the distortion matrix can be determined, and its derivative is
identified to the velocity gradient used in continuum mechanics. The
distortion, the orientation and the correspondence variants are determined by
coset decomposition with intersection groups that depend on the point groups of
the phases and on the type of transformation matrix. The stretch variants
required in the phenomenological theory of martensitic transformation should be
distinguished from the correspondence variants. The orientation variants and
the correspondence variants are also different; they are defined from the
geometric symmetries and algebraic symmetries, respectively. The concept of
orientation (ir)reversibility during thermal cycling is briefly and partially
treated by generalizing the orientation variants with n-cosets and graphs. Some
simple examples are given to show that there is no general relation between the
numbers of distortion, orientation and correspondence variants, and to
illustrate the concept of orientation variants formed by thermal cycling.


  Anomalous diffusion exists widely in polymer and biological systems. Pulsed
field gradient (PFG) techniques have been increasingly used to study anomalous
diffusion in NMR and MRI. However, the interpretation of PFG anomalous
diffusion is complicated. Moreover, there is not an exact signal attenuation
expression based on fractional derivatives for PFG anomalous diffusion, which
includes the finite gradient pulse width effect. In this paper, a new method, a
Mainardi-Luchko-Pagnini (MLP) phase distribution approximation, is proposed to
describe PFG fractional diffusion. MLP phase distribution is a non-Gaussian
phase distribution. From the fractional diffusion equation based on fractional
derivatives in both real space and phase space, the obtained probability
distribution function is a MLP distribution. The MLP distribution leads to a
Mittag-Leffler function based PFG signal attenuation rather than the
exponential or stretched exponential attenuation that is obtained from a
Gaussian phase distribution (GPD) under a short gradient pulse approximation.
The MLP phase distribution approximation is employed to get a complete signal
attenuation expression E{\alpha}(-Dfb*{\alpha},\b{eta}) that includes the
finite gradient pulse width effect for all three types of PFG fractional
diffusion. The results obtained in this study are in agreement with the results
from the literature. These results provide a new, convenient approximation
formalism to interpret complex PFG fractional diffusion experiments.


  Category theory has foundational importance because it provides conceptual
lenses to characterize what is important in mathematics. Originally the main
lenses were universal mapping properties and natural transformations. In recent
decades, the notion of adjoint functors has moved to center-stage as category
theory's primary tool to characterize what is important in mathematics. Our
focus here is to present a theory of adjoint functors. The basis for the theory
is laid by first showing that the object-to-object "heteromorphisms" between
the objects of different categories (e.g., insertion of generators as a set to
group map) can be rigorously treated within category theory. The heteromorphic
theory shows that all adjunctions arise from the birepresentations of the
heteromorphisms between the objects of different categories.


  By taking seriously the limits on observability which come from combining
relativistic quantum mechanics with general relativity, Ed Jones has shown that
the current measurements of the cosmological constant density
$\Omega_{\Lambda}\sim 0.7$ imply that the temperature scale at which it becomes
possible to discuss cosmological models is $\sim 5 Tev$ ($5.8\times 10^{16} \
^oK$). This is self-consistent with the assumption that the number of Planck
masses which make some sort of ``phase transition'' to this state is
$N_{Pk}\sim 4\times 10^{61}$. We review Jones' argument and the {\it bit-string
physics} calculation which gives the baryon-photon ratio at nucleosynthesis as
$\sim 2/256^4$, the dark matter-baryon ratio as $\sim 12.7$, and hence
$\Omega_m \sim 0.3$, in agreement with current observations. Accepting these
values for the two energy densities $\Omega_{\Lambda}+\Omega_m \sim 1$ in
accord with recent analyses of fluctuations in the CMB showing that space is
flat to about 6%. We conclude that experiments with particle accelerators in
the 5-10 Tev range must either show that current theory can adequately describe
the currently observed structure of our universe or force us to revise our
ideas about physics at a very fundamental level.


  We present radio observations of ultraluminous infrared galaxies (ULIRGs)
using the Giant Metrewave Radio Telescope (GMRT) and combine them with archival
multi-frequency observations to understand whether ULIRGs are the progenitors
of the powerful radio loud galaxies in the local Universe. ULIRGs are
characterized by large infrared luminosities ($L_{IR}>$10$^{12}$L$\odot$),
large dust masses ($\sim10^{8}M_{\odot}$) and vigorous star formation (star
formation rates $\sim$10-100 $M_{\odot}~$yr$^{-1}$). Studies show that they
represent the end stages of mergers of gas-rich spiral galaxies. Their
luminosity can be due to both starburst activity and active galactic nuclei
(AGN). We study a sample of 13 ULIRGs that have optically identified AGN
characteristics with 1.28~GHz GMRT observations. Our aim is to resolve any
core-jet structures or nuclear extensions and hence examine whether the ULIRGs
are evolving into radio loud ellipticals. Our deep, low frequency observations
show marginal extension for only one source. However, the integrated radio
spectra of 9 ULIRGs show characteristics that are similar to that of
GPS/CSS/CSO/young radio sources. The estimated spectral ages are 0.4 to 20 Myr
and indicate that they are young radio sources and possible progenitors of
radio galaxies. Hence, we conclude that although most ULIRGs do not show kpc
scale extended radio emission associated with nuclear activity, their radio
spectral energy distributions do show signatures of young radio galaxies.


  Although many Computer Science (CS) programs offer cybersecurity courses,
they are typically optional and placed at the periphery of the program. We
advocate to integrate cybersecurity as a crosscutting concept in CS curricula,
which is also consistent with latest cybersecurity curricular guidelines, e.g.,
CSEC2017. We describe our experience of implementing this crosscutting
intervention across three undergraduate core CS courses at a leading technical
university in Europe between 2018 and 2023, collectively educating over 2200
students. The security education was incorporated within CS courses using a
partnership between the responsible course instructor and a security expert,
i.e., the security expert (after consultation with course instructors)
developed and taught lectures covering multiple CSEC2017 knowledge areas. This
created a complex dynamic between three stakeholders: the course instructor,
the security expert, and the students. We reflect on our intervention from the
perspective of the three stakeholders -- we conducted a post-course survey to
collect student perceptions, and semi-supervised interviews with responsible
course instructors and the security expert to gauge their experience. We found
that while the students were extremely enthusiastic about the security content
and retained its impact several years later, the misaligned incentives for the
instructors and the security expert made it difficult to sustain this
intervention without organizational support. By identifying limitations in our
intervention, we suggest ideas for sustaining it.


  In previous works, we studied the isotropisation of Bianchi class A models
with a minimally coupled scalar field. In this paper, we extend these results
to the case of a non minimally coupled one. We first make the calculations in
the Einstein frame where the scalar field is minimally coupled to the curvature
but non minimally coupled to the perfect fluid. Then, we use a conformal
transformation to generalise our results to a scalar field non minimally
coupled to the curvature. Universe isotropisation for the Brans-Dicke and low
energy string theories are studied.


  It has been shown that named entity recognition (NER) could benefit from
incorporating the long-distance structured information captured by dependency
trees. We believe this is because both types of features - the contextual
information captured by the linear sequences and the structured information
captured by the dependency trees may complement each other. However, existing
approaches largely focused on stacking the LSTM and graph neural networks such
as graph convolutional networks (GCNs) for building improved NER models, where
the exact interaction mechanism between the two types of features is not very
clear, and the performance gain does not appear to be significant. In this
work, we propose a simple and robust solution to incorporate both types of
features with our Synergized-LSTM (Syn-LSTM), which clearly captures how the
two types of features interact. We conduct extensive experiments on several
standard datasets across four languages. The results demonstrate that the
proposed model achieves better performance than previous approaches while
requiring fewer parameters. Our further analysis demonstrates that our model
can capture longer dependencies compared with strong baselines.


  Two-dimensional (2D) topological insulator (TI) have been recognized as a new
class of quantum state of matter. They are distinguished from normal 2D
insulators with their nontrivial band-structure topology identified by the
$Z_2$ number as protected by time-reversal symmetry (TRS). 2D TIs have
intriguing spin-velocity locked conducting edge states and insulating
properties in the bulk. In the edge states, the electrons with opposite spins
propagate in opposite directions and the backscattering is fully prohibited
when the TRS is conserved. This leads to quantized dissipationless "two-lane
highway" for charge and spin transportation and promises potential
applications. Up to now, only very few 2D systems have been discovered to
possess this property. The lack of suitable material obstructs the further
study and application. Here, by using first-principles calculations, we propose
that the functionalized MXene with oxygen, M$_2$CO$_2$ (M=W, Mo and Cr), are 2D
TIs with the largest gap of 0.194 eV in W case. They are dynamically stable and
natively antioxidant. Most importantly, they are very likely to be easily
synthesized by recent developed selective chemical etching of transition-metal
carbides (MAX phase). This will pave the way to tremendous applications of 2D
TIs, such as "ideal" conducting wire, multifunctional spintronic device, and
the realization of topological superconductivity and Majorana modes for quantum
computing.


  We use a semantic interpretation to investigate the problem of defining an
expressive but decidable type system with bounded quantification. Typechecking
in the widely studied System Fsub is undecidable thanks to an undecidable
subtyping relation, for which the culprit is the rule for subtyping bounded
quantification. Weaker versions of this rule, allowing decidable subtyping,
have been proposed. One of the resulting type systems (Kernel Fsub) lacks
expressiveness, another (System Fsubtop) lacks the minimal typing property and
thus has no evident typechecking algorithm.
  We consider these rules as defining distinct forms of bounded quantification,
one for interpreting type variable abstraction, and the other for type
instantiation. By giving a semantic interpretation for both in terms of
unbounded quantification, using the dinaturality of type instantiation with
respect to subsumption, we show that they can coexist within a single type
system. This does have the minimal typing property and thus a simple
typechecking procedure.
  We consider the fragments of this unified type system over types which
contain only one form of bounded quantifier. One of these is equivalent to
Kernel Fsub, while the other can type strictly more terms than System Fsubtop
but the same set of beta-normal terms. We show decidability of typechecking for
this fragment, and thus for System Fsubtop typechecking of beta-normal terms.


  We begin by studying the surface area of an ellipsoid in n-dimensional
Euclidean space as the function of the lengths of the semi-axes. We write down
an explicit formula as an integral over the unit sphere in n-dimensions and use
this formula to derive convexity properties of the surface area, to give sharp
estimates for the surface area of a large-dimensional ellipsoid, to produce
asymptotic formulas for the surface area and the \emph{isoperimetric ratio} of
an ellipsoid in large dimensions, and to give an expression for the surface in
terms of the Lauricella hypergeometric function. We then write down general
formulas for the volumes of projections of ellipsoids, and use them to extend
the above-mentioned results to give explicit and approximate formulas for the
higher integral mean curvatures of ellipsoids. Some of our results can be
expressed as ISOPERIMETRIC results for higher mean curvatures.


  We consider building predictors when the data have missing values. We study
the seemingly-simple case where the target to predict is a linear function of
the fully-observed data and we show that, in the presence of missing values,
the optimal predictor may not be linear. In the particular Gaussian case, it
can be written as a linear function of multiway interactions between the
observed data and the various missing-value indicators. Due to its intrinsic
complexity, we study a simple approximation and prove generalization bounds
with finite samples, highlighting regimes for which each method performs best.
We then show that multilayer perceptrons with ReLU activation functions can be
consistent, and can explore good trade-offs between the true model and
approximations. Our study highlights the interesting family of models that are
beneficial to fit with missing values depending on the amount of data
available.


  Sources of bias in empirical studies can be separated in those coming from
the modelling domain (e.g. multicollinearity) and those coming from outliers.
We propose a two-step approach to counter both issues. First, by
decontaminating data with a multivariate outlier detection procedure and
second, by consistently estimating parameters of the production function. We
apply this approach to a panel of German field crop data. Results show that the
decontamination procedure detects multivariate outliers. In general,
multivariate outlier control delivers more reasonable results with a higher
precision in the estimation of some parameters and seems to mitigate the
effects of multicollinearity.


  A first measurement of the analysing power in the reaction p(pol)p --> pp eta
near the production threshold has been performed at the internal facility
COSY-11 at the COoler SYnchrotron COSY.


  Nowadays, many decision support applications need to exploit data that are
not only numerical or symbolic, but also multimedia, multistructure,
multisource, multimodal, and/or multiversion. We term such data complex data.
Managing and analyzing complex data involves a lot of different issues
regarding their structure, storage and processing, and metadata are a key
element in all these processes. Such problems have been addressed by classical
data warehousing (i.e., applied to "simple" data). However, data warehousing
approaches need to be adapted for complex data. In this paper, we first propose
a precise, though open, definition of complex data. Then we present a general
architecture framework for warehousing complex data. This architecture heavily
relies on metadata and domain-related knowledge, and rests on the XML language,
which helps storing data, metadata and domain-specific knowledge altogether,
and facilitates communication between the various warehousing processes.


  We present an experimental opportunity for the future to measure possible
violations to Newton's 1/r^2 law in the 0.1-10 meter range using Dynamic
gravity Field Generators (DFG) and taking advantage of the exceptional
sensitivity of modern interferometric techniques. The placement of a DFG in
proximity to one of the interferometer's suspended test masses generates a
change in the local gravitational field that can be measured at a high signal
to noise ratio. The use of multiple DFGs in a null experiment configuration
allows to test composition independent non-Newtonian gravity significantly
beyond the present limits. Advanced and third-generation gravitational-wave
detectors are representing the state-of-the-art in interferometric distance
measurement today, therefore we illustrate the method through their sensitivity
to emphasize the possible scientific reach. Nevertheless, it is expected that
due to the technical details of gravitational-wave detectors, DFGs shall likely
require dedicated custom configured interferometry. However, the sensitivity
measure we derive is a solid baseline indicating that it is feasible to
consider probing orders of magnitude into the pristine parameter well beyond
the present experimental limits significantly cutting into the theoretical
parameter space.


  VDB0-B195D is a massive, blue star cluster in M31. It was observed as part of
the Beijing-Arizona-Taiwan-Connecticut (BATC) Multicolor Sky Survey using 15
intermediate-band filters covering a wavelength range of 3000--10,000 \AA.
Based on aperture photometry, we obtain its spectral-energy distribution (SED)
as defined by the 15 BATC filters. We apply previously established relations
between the BATC intermediate-band and the Johnson-Cousins $UBVRI$ broad-band
systems to convert our BATC photometry to the standard system. A detailed
comparison shows that our newly derived $VRI$ magnitudes are fully consistent
with previous results, while our new $B$ magnitude agrees to within $2\sigma$.
In addition, we determine the cluster's age and mass by comparing its SED (from
3000 to 20,000{\AA}, comprising photometric data in the 15 BATC intermediate
bands, optical broad-band $BVRI$, and 2MASS near-infrared $JHK_{\rm s}$ data)
with theoretical stellar population synthesis models, resulting in age and mass
determinations of $60.0\pm 8.0$~Myr and $(1.1-1.6) \times 10^5 M_\odot$,
respectively. This age and mass confirms previous suggestions that VDB0-B195D
is a young massive cluster in M31.


  We prove a sufficient condition for synchronization for coupled
one-dimensional maps and estimate the size of the window of parameters where
synchronization takes place. It is shown that coupled systems on graphs with
positive eigenvalues (EVs) of the normalized graph Laplacian concentrated
around 1 are more amenable for synchronization. In the light of this condition,
we review spectral properties of Cayley, quasirandom, power-law graphs, and
expanders and relate them to synchronization of the corresponding networks. The
analysis of synchronization on these graphs is illustrated with numerical
experiments. The results of this paper highlight the advantages of random
connectivity for synchronization of coupled chaotic dynamical systems.


  This article concerns the Cauchy problem for the gravity-capillary water
waves system in general dimensions. We establish local well-posedness for
initial data in $H^s$, with $s > \frac{d}{2} + 2 - \mu$, with $\mu =
\frac{3}{14}$ and $\mu = \frac37$ in the cases $d = 1$ and $d \geq 2$
respectively. This represents an improvement over the the state-of-the-art low
regularity theory in $d \geq 2$ dimensions.


  In this work, the impact of recent measurements of heavy-flavour production
in $pp$ collisions on parton distribution functions (PDFs) and their
uncertainties is studied. In this regard, the absolute and normalised cross
sections of beauty hadron production measured by LHCb at center-of-mass energy
of 7 TeV and 13 TeV are separately included in the next-to-leading order (NLO)
global QCD analysis together with the measurements of the inclusive and
heavy-flavour production cross sections at HERA. It is illustrated that the
heavy-flavour data of the LHCb experiment impose additional constraints on the
PDFs, especially on the gluon distribution at low partonic fractions $x$ of the
proton momentum. One of the most important results of the present analysis is
the significant reduction of the gluon uncertainties in the region less than
$x=10^{-4}$ that can play a crucial rule in many areas of high energy physics
investigations.


  In this work, we investigate the period doubling phenomenon in the
periodically forced asymmetric Duffing oscillator. We use the known
steady-state asymptotic solution -- the amplitude-frequency implicit function
-- and known criterion for the existence of period doubling. Working in the
framework of differential properties of implicit functions we derive analytical
formulas for the birth of period-doubled solutions.


  Accurately predicting the performance of coronagraphs and tolerancing optical
surfaces for high-contrast imaging requires a detailed accounting of
diffraction effects. Unlike simple Fraunhofer diffraction modeling, near and
far-field diffraction effects, such as the Talbot effect, are captured by
plane-to-plane propagation using Fresnel and angular spectrum propagation. This
approach requires a sequence of computationally intensive Fourier transforms
and quadratic phase functions, which limit the design and aberration
sensitivity parameter space which can be explored at high-fidelity in the
course of coronagraph design. This study presents the results of optimizing the
multi-surface propagation module of the open source Physical Optics Propagation
in PYthon (POPPY) package. This optimization was performed by implementing and
benchmarking Fourier transforms and array operations on graphics processing
units, as well as optimizing multithreaded numerical calculations using the
NumExpr python library where appropriate, to speed the end-to-end simulation of
observatory and coronagraph optical systems. Using realistic systems, this
study demonstrates a greater than five-fold decrease in wall-clock runtime over
POPPY's previous implementation and describes opportunities for further
improvements in diffraction modeling performance.


  This is the proceeding of a talk given at Stringmath 2022. We introduce a
Cheeger-Simons type model for the differential extension of Anderson dual to
generalized homology theory with physical interpretations. This construction
generalizes the construction of the differential Anderson dual to bordism
homology theories, given in a previous work of Yonekura and the author.


  We propose a novel high resolution microscopy technique for enantio-specific
detection of chiral samples down to sub-100 nm size, based on force
measurement. We delve into the differential photo-induced optical force exerted
on an achiral probe in the vicinity of a chiral sample, when left and right
circularly polarized beams separately excite the sample-probe interactive
system. We analytically prove that the differential force is entangled with the
enantiomer type of the sample enabling enantio-specific detection of chiral
inclusions. Moreover, we demonstrate that the differential force is linearly
dependent on both the chiral response of the sample and the electric response
of the tip and is inversely related to the quartic power of probe-sample
distance. We provide physical insight into the transfer of optical activity
from the chiral sample to the achiral tip based on a rigorous analytical
approach. We support our theoretical achievements by several numerical
examples, highlighting the potential application of the derived analytic
properties. Lastly, we demonstrate the sensitivity of our method to
enantio-specify nanoscale chiral samples with chirality parameter in the order
of 0.01, and discuss how this could be further improved.


  Theory of quantum measurements is often classified as decision theory. An
event in decision theory corresponds to the measurement of an observable. This
analogy looks clear for operationally testable simple events. However, the
situation is essentially more complicated in the case of composite events. The
most difficult point is the relation between decisions under uncertainty and
measurements under uncertainty. We suggest a unified language for describing
the processes of quantum decision making and quantum measurements. The notion
of quantum measurements under uncertainty is introduced. We show that the
correct mathematical foundation for the theory of measurements under
uncertainty, as well as for quantum decision theory dealing with uncertain
events, requires the use of positive operator-valued measure that is a
generalization of projection-valued measure. The latter is appropriate for
operationally testable events, while the former is necessary for characterizing
operationally uncertain events. In both decision making and quantum
measurements, one has to distinguish composite non-entangled events from
composite entangled events. Quantum probability can be essentially different
from classical probability only for entangled events. The necessary condition
for the appearance of an interference term in the quantum probability is the
occurrence of entangled prospects and the existence of an entangled strategic
state of a decision maker or of an entangled statistical state of a measuring
device.


  We give a theoretical perspective on the vorticity and spin polarization in
heavy-ion collisions. We discuss the recent progress in spin hydrodynamics and
spin kinetic theory. We also discuss other effects caused by vorticity
including the chiral vortical effect and rotation-induced phase transitions.


  In this note we give a quantitative version of the following simple
observation: a discrete harmonic function on the lattice may vanish at each
point of a large cube without being zero identically, at the same time there is
a version of three balls theorem for discrete harmonic functions since they
resemble continuous ones on large scales.


  The Berry phase and curvature are studied for the Dirac nodal line semimetal
of single-component molecular conductor [Pd(dddt)$_2$]. Using two-band model on
the basis of a tight-binding model, it is shown that the Berry curvature,
$\bm{B}(\bm{k})$, exists along a loop of the nodal line, on which the Berry
phase is obtained from surface integral of $\bm{B}(\bm{k})$. The Berry phase,
which is called Zak phase, is also calculated from one-dimensional integral of
the Berry connection along a line between two equivalent points of boundaries
of Brillouin zone. The possible experiment is discussed in terms of the Berry
phase.


  We introduce a new and highly tractable structural model for spot and
derivative prices in electricity markets. Using a stochastic model of the bid
stack, we translate the demand for power and the prices of generating fuels
into electricity spot prices. The stack structure allows for a range of
generator efficiencies per fuel type and for the possibility of future changes
in the merit order of the fuels. The derived spot price process captures
important stylized facts of historical electricity prices, including both
spikes and the complex dependence upon its underlying supply and demand
drivers. Furthermore, under mild and commonly used assumptions on the
distributions of the input factors, we obtain closed-form formulae for
electricity forward contracts and for spark and dark spread options. As merit
order dynamics and fuel forward prices are embedded into the model, we capture
a much richer and more realistic dependence structure than can be achieved by
classical reduced-form models. We illustrate these advantages by comparing with
Margrabe's formula and a simple cointegration model, and highlight important
implications for the valuation of power plants.


  We conisder the brittle versus ductile behavior of aluminum in the framework
of the Peierls-model analysis of dislocation emission from a crack tip. To this
end, we perform first-principles quantum mechanical calculations for the
unstable stacking energy $\gamma_{us}$ of aluminum along the Shockley partial
slip route. Our calculations are based on density functional theory and the
local density approximation and include full atomic and volume relaxation. We
find that in aluminum $\gamma_{us} = 0.224$ J/m$^2$. Within the Peierls-model
analysis, this value would predict a brittle solid which poses an interesting
problem since aluminum is typically considered ductile. The resolution may be
given by one of three possibilites: (a) Aluminum is indeed brittle at zero
temperature, and becomes ductile at a finite temperature due to motion of
pre-existing dislocations which relax the stress concentration at the crack
tip. (b) Dislocation emission at the crack tip is itself a thermally activated
process. (c) Aluminum is actually ductile at all temperatures and the
theoretical model employed needs to be significantly improved in order to
resolve the apparent contradiction.


  An $s$-subset of codewords of a binary code $X$ is said to be an {\em
$(s,\ell)$-bad} in $X$ if the code $X$ contains a subset of other $\ell$
codewords such that the conjunction of the $\ell$ codewords is covered by the
disjunctive sum of the $s$ codewords. Otherwise, the $s$-subset of codewords of
$X$ is said to be an {\em $(s,\ell)$-good} in~$X$.mA binary code $X$ is said to
be a cover-free $(s,\ell)$-code if the code $X$ does not contain $(s,\ell)$-bad
subsets. In this paper, we introduce a natural {\em probabilistic}
generalization of cover-free $(s,\ell)$-codes, namely: a binary code is said to
be an almost cover-free $(s,\ell)$-code if {\em almost all} $s$-subsets of its
codewords are $(s,\ell)$-good. We discuss the concept of almost cover-free
$(s,\ell)$-codes arising in combinatorial group testing problems connected with
the nonadaptive search of defective supersets (complexes). We develop a random
coding method based on the ensemble of binary constant weight codes to obtain
lower bounds on the capacity of such codes.


  Although multiple COVID-19 vaccines have been available for several months
now, vaccine hesitancy continues to be at high levels in the United States. In
part, the issue has also become politicized, especially since the presidential
election in November. Understanding vaccine hesitancy during this period in the
context of social media, including Twitter, can provide valuable guidance both
to computational social scientists and policy makers. Rather than studying a
single Twitter corpus, this paper takes a novel view of the problem by
comparatively studying two Twitter datasets collected between two different
time periods (one before the election, and the other, a few months after) using
the same, carefully controlled data collection and filtering methodology. Our
results show that there was a significant shift in discussion from politics to
COVID-19 vaccines from fall of 2020 to spring of 2021. By using clustering and
machine learning-based methods in conjunction with sampling and qualitative
analysis, we uncover several fine-grained reasons for vaccine hesitancy, some
of which have become more (or less) important over time. Our results also
underscore the intense polarization and politicization of this issue over the
last year.


  A strengthened canonical quantization scheme for the constrained motion on a
curved hypersurface is proposed with introduction of the second category of
fundamental commutation relations between Hamiltonian and positions/momenta,
whereas those between positions and moments are categorized into the first. As
an $N-1$ ($N\geq2$) dimensional hypersurface is embedded in an N dimensional
Euclidean space, we obtain the proper momentum that depends on the mean
curvature. For the surface is the spherical one, a long-standing problem on the
form of the geometric potential is resolved in a lucid and unambiguous manner,
which turns out to be identical to that given by the so-called confining
potential technique. In addition, a new dynamical group SO(N,1) symmetry for
the motion on the sphere is demonstrated.


  We present results of a quenched calculation of the heavy-light and
quarkonium spectrum using the tadpole improved clover action. We resolve
completely the triplet chi P-states in quarkonium systems, and obtain evidence
for fine structure of the heavy-light P-states. Approximate scaling of the
hyperfine splittings is observed, producing results that are significantly
below experiment.


  This paper constructs a collection of discrete operators on the
$d$-dimensional lattice $\mathbb{Z}^{d}$, $d\geq 1$, which result from the
conditional expectation of martingale transform in the upper half-space
$\mathbb{R}^{d+1}_{+}$ constructed from Doob $h$-processes. Special cases of
these operators are what we call \textit{the probabilistic discrete Riesz
transforms.} When $d=1,$ they reduce to \textit{the probabilistic discrete
Hilbert transform} used by the first and third authors to resolve the
long-standing open problem concerning the $\ell^p$ norm, $1<p<\infty$, of the
discrete Hilbert transform on the integers $\mathbb{Z}$. The construction for
$d>1$ is motivated by a similar problem, Conjecture 5.5, concerning the norm of
the discrete Riesz transforms arising from discretizing singular integrals on
$\mathbb{R}^d$ as in the original paper of A. P. Calder\'on and A. Zygmund, and
subsequent works of A. Magyar, E. M. Stein, S. Wainger, L. B. Pierce and many
others, concerning operator norms in discrete harmonic analysis. For any $d\geq
1$, it is shown that the probabilistic discrete Riesz transforms have the same
$\ell^p$ norm as the continuous Riesz transforms on $\mathbb{R}^d$ which is
dimension independent and equals the norm of the classical Hilbert transform on
$\mathbb{R}$. Along the way we give a different proof, based on Fourier
transform techniques, of the key estimate used to identify the norm of the
discrete Hilbert transform.


  It has been recognized long ago that the presence of hot plasma in the inner
accretion disks around black holes could lead to the neutron production via
dissociation of helium nuclei. We show that, for a broad range of accretion
parameters, neutrons effectively decouple from protons and pile up in the inner
disk leading to the formation of self-sustained halo. This means that new
neutrons in the halo are supplied mainly by the splitting of helium nuclei in
their collisions with existing neutrons. Once formed, such a halo can exist
even if the proton temperature is much lower than the energy threshold of
helium dissociation. We show that neutron haloes can be the natural source of
relativistic electrons and positrons, providing characteristic comptonization
spectra and hard spectral tails observed in many black hole candidates, and
also giving rise to relativistic outflows. Deuterium gamma-ray line at 2.2 MeV
resulting from neutron capture is also expected at a level detectable by future
INTEGRAL mission. Furthermore, the presence of a neutron halo strongly affects
the dynamics of accretion and leads to the rich variety of transient dynamical
regimes.


  We present high-resolution capacitance dilatometry studies from 5 - 500 K of
untwinned YBa2Cu3Ox (Y123) single crystals for x ~ 6.95 and x = 7.0. Large
contributions to the thermal expansivities due to O-ordering are found for x ~
6.95, which disappear below a kinetic glass-like transition near room
temperature. The kinetics at this glass transition is governed by an energy
barrier of 0.98 +- 0.07 eV, in very good agreement with other O-ordering
studies. Using thermodynamic arguments, we show that O-ordering in the Y123
system is particularly sensitive to uniaxial pressure (stress) along the chain
axis and that the lack of well-ordered chains in Nd123 and La123 is most likely
a consequence of a chemical-pressure effect.


  The information that can be transmitted through a wireless channel, with
multiple-antenna equipped transmitter and receiver, is crucially influenced by
the channel behavior as well as by the structure of the input signal. We
characterize in closed form the probability density function (pdf) of the
output of MIMO block-fading channels, for an arbitrary SNR value. Our results
provide compact expressions for such output statistics, paving the way to a
more detailed analytical information-theoretic exploration of communications in
presence of block fading. The analysis is carried out assuming two different
structures for the input signal: the i.i.d. Gaussian distribution and a product
form that has been proved to be optimal for non-coherent communication, i.e.,
in absence of any channel state information. When the channel is fed by an
i.i.d. Gaussian input, we assume the Gramian of the channel matrix to be
unitarily invariant and derive the output statistics in both the noise-limited
and the interference-limited scenario, considering different fading
distributions. When the product-form input is adopted, we provide the
expressions of the output pdf as the relationship between the overall number of
antennas and the fading coherence length varies. We also highlight the relation
between our newly derived expressions and the results already available in the
literature, and, for some cases, we numerically compute the mutual information,
based on the proposed expression of the output statistics.


  Based on the idea that the vacuum fluctuations of electromagnetic fields can
induce instantaneous correlated dipoles, we study the far-zone Casimir-Polder
potential between two atoms in the Boulware, Unruh and Hartle-Hawking vacua
outside a Schwarzschild black hole. We show that, at spatial infinity, the
Casimir-Polder potential in the Boulware vacuum is similar to that in the
Minkowski vacuum in flat spacetime with a behavior of $R^{-7}$, so is in the
Unruh vacuum as a result of the backscattering of the Hawking radiation from
the black hole off the spacetime curvature. However, the interatomic
Casimir-Polder potential in the Hartle-Hawking vacuum behaves like that in a
thermal bath at the Hawking temperature. In the region near the event horizon
of the black hole, the modifications caused by the space-time curvature make
the interatomic Casimir-Polder potential smaller in all three vacuum states.


  Using Spitzer Space Telescope and Chandra X-ray Observatory data, we identify
YSOs in the Rosette Molecular Cloud (RMC). By being able to select cluster
members and classify them into YSO types, we are able to track the progression
of star formation locally within the cluster environments and globally within
the cloud. We employ nearest neighbor method (NNM) analysis to explore the
density structure of the clusters and YSO ratio mapping to study age
progressions in the cloud. We find a relationship between the YSO ratios and
extinction which suggests star formation occurs preferentially in the densest
parts of the cloud and that the column density of gas rapidly decreases as the
region evolves. This suggests rapid removal of gas may account for the low star
formation efficiencies observed in molecular clouds. We find that the overall
age spread across the RMC is small. Our analysis suggests that star formation
started throughout the complex around the same time. Age gradients in the cloud
appear to be localized and any effect the HII region has on the star formation
history is secondary to that of the primordial collapse of the cloud.


  Jet quenching in high-energy heavy-ion collisions can be used to probe
properties of hot and dense quark-gluon plasma. We provide a brief introduction
to the concept and framework for the study of jet quenching. Different
approaches and implementation of multiple scattering and parton energy loss are
discussed. Recent progresses in the theoretical and phenomenological studies of
jet quenching in heavy-ion collisions at RHIC and LHC are reviewed.


  In this note, we show that the satisfiability of equations and inequations
with recognisable constraints is decidable in groups that are virtually direct
products of finitely many hyperbolic groups.


  Ultrafast characterization and control of many-body interactions and
elementary excitations are critical to understanding and manipulating emergent
phenomena in strongly correlated systems. In particular, spin interaction plays
an important role in unconventional superconductivity, but efficient tools for
probing spin dynamics especially out of equilibrium, are still lacking. To
address this question, we develop a theory for nonresonant time-resolved Raman
scattering, which can be a generic and powerful tool for nonequilibrium
studies. We also use exact diagonalization to simulate the pump-probe dynamics
of correlated electrons in the square-lattice single-band Hubbard model.
Different ultrafast processes are shown to exist in the time-resolved Raman
spectra and dominate under different pump conditions. For high-frequency and
off-resonance pumps, we show that the Floquet theory works well in capturing
the softening of bimagnon excitation. By comparing the Stokes/anti-Stokes
spectra, we also show that effective heating dominates at small pump fluences,
while a coherent many-body effect starts to take over at larger pump amplitudes
and frequencies on resonance to the Mott gap. Time-resolved Raman scattering
thereby provides the platform to explore different ultrafast processes and
design material properties out of equilibrium.


  We introduce a novel algorithmic approach to content recommendation based on
adaptive clustering of exploration-exploitation ("bandit") strategies. We
provide a sharp regret analysis of this algorithm in a standard stochastic
noise setting, demonstrate its scalability properties, and prove its
effectiveness on a number of artificial and real-world datasets. Our
experiments show a significant increase in prediction performance over
state-of-the-art methods for bandit problems.


  Disordered systems exhibit universal excitation, referred to as the boson
peak, in the terahertz region. Meanwhile, the so-called fracton is expected to
appear in the nanoscale region owing to the self-similar structure of monomers
in polymeric glasses. We demonstrate that such excitations can be detected
using terahertz spectroscopy. For the interaction between terahertz light and
the vibrational density of states of the fractal structure, we formulate an
infrared light-vibration coupling coefficient for the fracton region.
Accordingly, we show that information concerning fractal and fracton dimensions
appears in the exponent of the absorption coefficient. Finally, using terahertz
time-domain spectroscopy and low-frequency Raman scattering, we experimentally
observe these universal excitations in a protein lysozyme system that has an
intrinsically disordered and self-similar nature in a single supramolecule.
These findings are applicable to disordered and polymeric glasses in general
and will be key to understanding universal dynamics of disordered systems by
terahertz light.


  Deconfined quantum criticality (DQC) arises from fractionalization of
quasi-particles and leads to fascinating behaviors beyond the
Landau-Ginzburg-Wilson (LGW) description of phase transitions. The unusual
aspects of DQC in equilibrium also suggest exotic phenomena out of equilibrium,
which are still largely unexplored. Here we study manifestations of DQC when
driving (quantum annealing) a two-dimensional quantum magnet through a critical
point separating antiferromagnetic and spontaneously dimerized ground states.
Numerical simulations show that the celebrated Kibble-Zurek scaling (KZS)
mechanism is inadequate for describing the annealing process. To explain our
results, we introduce the concept of dual asymmetric KZS, where a deconfinement
time enters in addition to the conventional relaxation time and the scaling
also depends on the direction in which the system is driven through the
critical point according to a duality principle connecting the topological
defects in the two phases. These defects -- spinons in the dimerized phase and
space-time hedgehogs in the antiferromagnetic phase -- require a much longer
time scale for equilibration than the amplitude of the order parameter. Beyond
the new insights into DQC, our scaling approach provides a new window into
out-of-equilibrium criticality with multiple length and time scales.


  We propose a scheme for encoding logical qubits in a subspace protected
against collective rotations around the propagation axis using the polarization
and transverse spatial degrees of freedom of single photons. This encoding
allows for quantum key distribution without the need of a shared reference
frame. We present methods to generate entangled states of two logical qubits
using present day down-conversion sources and linear optics, and show that the
application of these entangled logical states to quantum information schemes
allows for alignment-free tests of Bell's inequalities, quantum dense coding
and quantum teleportation.


  We derive general bounds on the linear response energy absorption rates of
periodically driven many-body systems of spins or fermions on a lattice. We
show that for systems with local interactions, energy absorption rate decays
exponentially as a function of driving frequency in any number of spatial
dimensions. These results imply that topological many-body states in
periodically driven systems, although generally metastable, can have very long
lifetimes. We discuss applications to other problems, including decay of highly
energetic excitations in cold atomic and solid-state systems.


  We prove that a.a.s. the maximum size of an induced subtree of the binomial
random graph $G(n,p)$ is concentrated in 2 consecutive points. We also prove
that, given a non-negative integer-valued function $t(k)<\varepsilon k^2$,
under a certain smoothness condition on this function, a.a.s. the maximum size
$k$ of an induced subgraph with exactly $t(k)$ edges of $G(n,p)$ is
concentrated in 2 consecutive points as well.


  ESS$\nu$SB is a proposed neutrino super-beam project at the ESS facility. We
study the performance of this setup in the presence of a light eV-scale sterile
neutrino, considering 540 km baseline with 2 years (8 years) of $\nu$
($\bar\nu$) run-plan. This baseline offers the possibility to work around the
second oscillation maximum, providing high sensitivity towards CP-violation
(CPV). We explore in detail its capability in resolving CPV generated by the
standard CP phase $\delta_{13}$, the new CP phase $\delta_{14}$, and the octant
of $\theta_{23}$. We find that the sensitivity to CPV induced by $\delta_{13}$
deteriorates noticeably when going from $3\nu$ to 4$\nu$ case. The two phases
$\delta_{13}$ and $\delta_{14}$ can be reconstructed with a 1$\sigma$
uncertainty of $\sim15^0$ and $ \sim35^0$ respectively. Concerning the octant
of $\theta_{23}$, we find poor sensitivity in both $3\nu$ and $4\nu$ schemes.
Our results show that a setup like ESS$\nu$SB working around the second
oscillation maximum with a baseline of 540 km, performs quite well to explore
CPV in 3$\nu$ scheme, but it is not optimal for studying CP properties in 3+1
scheme.


  This paper presents new lower and upper bounds for the compression rate of
binary prefix codes optimized over memoryless sources according to various
nonlinear codeword length objectives. Like the most well-known redundancy
bounds for minimum average redundancy coding - Huffman coding - these are in
terms of a form of entropy and/or the probability of an input symbol, often the
most probable one. The bounds here, some of which are tight, improve on known
bounds of the form L in [H,H+1), where H is some form of entropy in bits (or,
in the case of redundancy objectives, 0) and L is the length objective, also in
bits. The objectives explored here include exponential-average length, maximum
pointwise redundancy, and exponential-average pointwise redundancy (also called
dth exponential redundancy). The first of these relates to various problems
involving queueing, uncertainty, and lossless communications; the second
relates to problems involving Shannon coding and universal modeling. For these
two objectives we also explore the related problem of the necessary and
sufficient conditions for the shortest codeword of a code being a specific
length.


  We present an automated method to track and identify neurons in C. elegans,
called "fast Deep Learning Correspondence" or fDLC, based on the transformer
network architecture. The model is trained once on empirically derived
synthetic data and then predicts neural correspondence across held-out real
animals via transfer learning. The same pre-trained model both tracks neurons
across time and identifies corresponding neurons across individuals.
Performance is evaluated against hand-annotated datasets, including NeuroPAL
[1]. Using only position information, the method achieves 80.0% accuracy at
tracking neurons within an individual and 65.8% accuracy at identifying neurons
across individuals. Accuracy is even higher on a published dataset [2].
Accuracy reaches 76.5% when using color information from NeuroPAL. Unlike
previous methods, fDLC does not require straightening or transforming the
animal into a canonical coordinate system. The method is fast and predicts
correspondence in 10 ms making it suitable for future real-time applications.


  Model selection when designing deep learning systems for specific use-cases
can be a challenging task as many options exist and it can be difficult to know
the trade-off between them. Therefore, we investigate a number of state of the
art CNN models for the task of measuring kernel fragmentation in harvested corn
silage. The models are evaluated across a number of feature extractors and
image sizes in order to determine optimal model design choices based upon the
trade-off between model complexity, accuracy and speed. We show that accuracy
improvements can be made with more complex meta-architectures and speed can be
optimised by decreasing the image size with only slight losses in accuracy.
Additionally, we show improvements in Average Precision at an Intersection over
Union of 0.5 of up to 20 percentage points while also decreasing inference time
in comparison to previously published work. This result for better model
selection enables opportunities for creating systems that can aid farmers in
improving their silage quality while harvesting.


  We argue that black holes admit vortex structure. This is based both on a
graviton-condensate description of a black hole as well as on a correspondence
between black holes and generic objects with maximal entropy compatible with
unitarity, so-called saturons. We show that due to vorticity, a $Q$-ball-type
saturon of a calculable renormalizable theory obeys the same extremality bound
on the spin as the black hole. Correspondingly, a black hole with extremal spin
emerges as a graviton condensate with vorticity. This offers a topological
explanation for the stability of extremal black holes against Hawking
evaporation. Next, we show that in the presence of mobile charges, the global
vortex traps a magnetic flux of the gauge field. This can have
macroscopically-observable consequences. For instance, the most powerful jets
observed in active galactic nuclei can potentially be accounted for. As a
signature, such emissions can occur even without a magnetized accretion disk
surrounding the black hole. The flux entrapment can provide an observational
window to various hidden sectors, such as millicharged dark matter.


  The internal disorder of a D-dimensional hydrogenic system, which is strongly
associated to the non-uniformity of the quantum-mechanical density of its
physical states, is investigated by means of the shape complexity in the two
reciprocal spaces. This quantity, which is the product of the disequilibrium
and the Shannon entropic power, is mathematically expressed for both ground and
excited stationary states in terms of certain entropic functionals of Laguerre
and Gegenbauer (or ultraspherical) polynomials. Emphasis is made in the ground
and circular states.


  Corollary: Two germs of minimal real analytic CR-generic manifolds are
formally equivalent if and only if they are biholomorphic.


  The t<0 branch of pre-big bang cosmological scenarios is subject to a
gravitational wave instability. The unstable behaviour of tensor perturbations
is derived in a very simple way in Hwang's covariant and gauge-invariant
formalism developed for extended theories of gravity. A simple interpretation
of this instability as the effect of an "antifriction" is given, and it is
argued that a universe must eventually enter the expanding phase.


  Fire keeps claiming a large number of victims in building fires. Although
there are ways to minimize such events, fire drills are used to train the
building occupants for emergency situations. However, organizing and implement
these exercises is a complex task, and sometimes not sucessfull. Furthermore,
fire drills require the mobilization of some finantial resources and time, and
affect the normal functioning of the site where they occur. To overcome the
aforementioned issues, computer games have a set of features that might
overcome this problem. They offer engagement to their players, keeping them
focused, and providing training to real life situations. The game evaluate
users, providing them some feedback, making possible for the players to improve
their performance. The proposed methodology aims to study the viability of
using a game that recreates a fire drill in a 3D environment using Serious
Games. The information acquired through the player's performance is very
valuable and will be later used to implement an artificial population. A sample
of 20 subjects was selected to test the application. Preliminary results are
promising, showing that the exercise had a positive impact on users. Moreover,
the data acquired is of great important and will be later used to demonstrate
the possibility of creating an artificial population based on human behaviour.