  We demonstrate the growth of epitaxial Fe/Ba(Fe(1-x)Co(x))2As2 (Fe/Ba-122)
bilayers on MgO(001) and LSAT(001) single crystal substrates using Pulsed Laser
Deposition (PLD). By exploiting the metallic nature of the FeAs tetrahedron in
the Ba-122 crystal structure, we achieve a coherent interfacial bond between
bcc iron and Co-doped Ba-122. Tc values for both bilayers were close to that of
the PLD target. Direct observation of interfacial bonding between Fe and the
Ba-122 FeAs sublattice by atomic resolution transmission electron microscopy
implies that this bilayer architecture may work for other iron pnictide systems
and pave the way for the fabrication of superconducting/ferromagnetic
heterostructures.


  We present the strategy which has been used recently to optimize integrated
luminosity at the Fermilab Tevatron proton-antiproton collider. We use a
relatively simple model where we keep the proton intensity fixed, use
parameters from fits to the luminosity decay of recent stores as a function of
initial antiproton intensity (stash size), and vary the stash size to optimize
the integrated luminosity per week. The model assumes a fixed rate of
antiproton production, that a store is terminated as soon as the target stash
size for the next store is reached, and that the only downtime is due to store
turn-around time. An optimal range of stash sizes is predicted. Since the start
of Tevatron operations based on this procedure, we have seen an improvement of
approximately 35% in integrated luminosity. Other recent operational
improvements have been achieved by decreasing the shot-setup time and by
reducing beam-beam effects by making the proton and antiproton brightnesses
more compatible, for example by scraping protons to smaller emittances.


  In this work we investigated the question of how the molecular nature of the
dielectric media and the polymer-solvent dielectric mismatch affect the
collapse of a polyelectrolyte chain in solution by means of dissipative
particle dynamics simulations. First, we studied whether the explicit treatment
of dielectric media as polar beads instead of homogeneous dielectric background
results in a different system behavior. We showed that the explicit treatment
of polar beads facilitates the chain collapse, i.e. it occurs at smaller values
of the electrostatic strength parameter values ${\lambda}^2 \sim
Q^2/({\epsilon}kT)$. We believe that the main reason for such behavior is that
the dielectric response is in fact a collective effect, and the "effective"
dielectric permittivity is different from the bulk value when the charges are
close to each other and/or the density of the charges is high enough. This
implies that the value of ${\lambda}$ does not have a universal meaning due to
the small-scale effects related to the presence of polar species; therefore,
changing the total unit charge $Q$ or the temperature $kT$ is not equivalent to
changing ${\epsilon}$. Next, we investigated how the difference of the
dielectric permittivities of the polymer chain and solvent affects the
collapse. We showed the polar chain adapts less swollen conformations in the
polyelectrolyte regime and collapses easier compared to the case of non-polar
chain; the possible reasons for such behavior are discussed.


  A systematic program is developed for analyzing and cancelling local
anomalies on networks of intersecting orbifold planes in the context of
M-theory. Through a delicate balance of factors, it is discovered that local
anomaly matching on the lower-dimensional intersection of two orbifold planes
may require twisted matter on those planes which do not conventionally support
an anomaly (such as odd-dimensional planes). In this way, gravitational
anomalies can, in principle, tell us about (twisted) gauge groups on subspaces
which are not necessarily ten-, six- or two-dimensional. An example is worked
out for the case of an $S^1/{\bf Z}_2\times T^4/{\bf Z}_2$ orbifold and
possible implications for four-dimensional physics are speculated on.


  We re-evaluate the electromagnetic corrections to eta --> 3 pi decays at
next-to-leading order in the chiral expansion, arguing that effects of order
e^2(m_d-m_u) disregarded so far are not negligible compared to other
contributions of order e^2 times a light quark mass. Despite the appearance of
the Coulomb pole in eta --> pi+ pi- pi0 and cusps in eta --> 3 pi0, the overall
corrections remain small.


  We prove that foliations on the projective plane admitting a Liouvillian
first integral but not admitting a rational first integral always have
invariant algebraic curves of degree bounded by a function of the degree of the
foliation. We establish, for the same class of foliations, the existence of a
bound for the degree of the simplest integrating factor depending only on the
degree of the foliation and on the nature of its singularities. We also prove
the existence of invariant algebraic curves of small degree for foliations with
rational first integral and intermediate Kodaira dimension.


  Recently Arnold's $\St$ and $J^{\pm}$ invariants of generic planar curves
have been generalized to the case of generic planar wave fronts. We generalize
these invariants to the case of wave fronts on an arbitrary surface $F$. All
invariants satisfying the axioms which naturally generalize the axioms used by
Arnold are explicitly described. We also give an explicit formula for the
finest order one $J^+$-type invariant of fronts on an orientable surface $F\neq
S^2$. We obtain necessary and sufficient conditions for an invariant of
nongeneric fronts with one nongeneric singular point to be the Vassiliev-type
derivative of an invariant of generic fronts. As a byproduct, we calculate all
homotopy groups of the space of Legendrian immersions of $S^1$ into the
spherical cotangent bundle of a surface.


  We suggest that the solution to the cosmological vacuum energy puzzle is
linked to the infrared sector of the effective theory of gravity interacting
with standard model fields, with QCD fields specifically. We work in the
framework of low energy quantum gravity as an effective field theory. In
particular, we compute the vacuum energy in terms of QCD parameters and the
Hubble constant $H$ such that the vacuum energy is $\epsilon_{vac} \sim H \cdot
m_q\la\bar{q}q\ra /m_{\eta'} \sim (3.6\cdot 10^{-3} \text{eV})^4$, which is
amazingly close to the observed value today. The QCD ghost (responsible for the
solution of the $U(1)_A$ problem) plays a crucial r\^ole in the computation of
the vacuum energy, because the ghost's properties at very large but finite
distances slightly deviate (as $\sim H / \Lqcd $) from their infinite volume
Minkowski values. Another important prediction of this framework states that
the vacuum energy owes its existence to the asymmetry of the cosmos. Indeed,
this effect is a direct consequence of the embedding of our Universe on a
non-trivial manifold such as a torus with (slightly) different linear sizes.
Such a violation of cosmological isotropy is apparently indeed supported by
WMAP, and will be confirmed (or ruled out) by future PLANCK data.


  A search for flavor-changing neutral current interactions of the top quark
(t) and the Higgs boson (H) is presented. The search is based on a data sample
corresponding to an integrated luminosity of 137 fb$^{-1}$ recorded by the CMS
experiment at the LHC in proton-proton collisions at $\sqrt{s}$ = 13 TeV.
Events containing exactly one lepton (muon or electron) and at least three
jets, among which at least two are identified as originating from the
hadronization of a bottom quark, are analyzed. A set of deep neural networks is
used for kinematic event reconstruction, while boosted decision trees
distinguish the signal from the background events. No significant excess over
the background predictions is observed, and upper limits on the signal
production cross sections are extracted. These limits are interpreted in terms
of top quark decay branching fractions ($\mathcal{B}$) to the Higgs boson and
an up (u) or a charm quark (c). Assuming one nonvanishing extra coupling at a
time, the observed (expected) upper limits at 95% confidence level are
$\mathcal{B}$(t $\to$ Hu) $\lt$ 0.079 (0.11)% and $\mathcal{B}$(t $\to$ Hc)
$\lt$ 0.094 (0.086)%.


  This paper studies the iteration-complexity of new regularized hybrid
proximal extragradient (HPE)-type methods for solving monotone inclusion
problems (MIPs). The new (regularized HPE-type) methods essentially consist of
instances of the standard HPE method applied to regularizations of the original
MIP. It is shown that its pointwise iteration-complexity considerably improves
the one of the HPE method while approaches (up to a logarithmic factor) the
ergodic iteration-complexity of the latter method.


  We studied the solar surface flows (differential rotation and meridional
circulation) using a magnetic element feature tracking technique by which the
surface velocity is obtained using magnetic field data. We used the
line-of-sight magnetograms obtained by the Helioseismic and Magnetic Imager
aboard the Solar Dynamics Observatory from 01 May 2010 to 16 August 2017
(Carrington rotations 2096 to 2193) and tracked the magnetic element features
every hour. Using our method, we estimated the differential rotation velocity
profile. We found rotation velocities of $\sim$ 30 and -170 m s$^{-1}$ at
latitudes of 0$^{\circ}$ and 60$^{\circ}$ in the Carrington rotation frame,
respectively. Our results are consistent with previous results obtained by
other methods, such as direct Doppler, time-distance helioseismology, or cross
correlation analyses. We also estimated the meridional circulation velocity
profile and found that it peaked at $\sim$12 m s$^{-1}$ at a latitude of
45$^{\circ}$, which is also consistent with previous results. The dependence of
the surface flow velocity on the magnetic field strength was also studied. In
our analysis, the magnetic elements having stronger and weaker magnetic fields
largely represent the characteristics of the active region remnants and solar
magnetic networks, respectively. We found that magnetic elements having a
strong (weak) magnetic field show faster (slower) rotation speed. On the other
hand, magnetic elements having a strong (weak) magnetic field show slower
(faster) meridional circulation velocity. These results might be related to the
Sun's internal dynamics.


  To estimate the direction of arrival (DOA) of multiple speakers with methods
that use prototype transfer functions, frequency-dependent spatial spectra
(SPS) are usually constructed. To make the DOA estimation robust, SPS from
different frequencies can be combined. According to how the SPS are combined,
frequency fusion mechanisms are categorized into narrowband, broadband, or
speaker-grouped, where the latter mechanism requires a speaker-wise grouping of
frequencies. For a binaural hearing aid setup, in this paper we propose an
interaural time difference (ITD)-based speaker-grouped frequency fusion
mechanism. By exploiting the DOA dependence of ITDs, frequencies can be grouped
according to a common ITD and be used for DOA estimation of the respective
speaker. We apply the proposed ITD-based speaker-grouped frequency fusion
mechanism for different DOA estimation methods, namely the multiple signal
classification, steered response power and a recently published method based on
relative transfer function (RTF) vectors. In our experiments, we compare DOA
estimation with different fusion mechanisms. For all considered DOA estimation
methods, the proposed ITD-based speaker-grouped frequency fusion mechanism
results in a higher DOA estimation accuracy compared with the narrowband and
broadband fusion mechanisms.


  We have measured the magnetic susceptibilities of single crystals of
Cu_{1-x}Zn_xGeO_3 with extremely low Zn concentration (x) lower than
x=5x10^{-3} at very low temperatures to investigate the spin-Peierls and
antiferromagnetic transitions. The results show that the undoped CuGeO_3 has no
antiferromagnetic phase down to 12 mK and there exists an antiferromagnetic
long-range order with the easy axis along the $c$ axis for x down to
1.12(2)x10^{-3}. The minimum observed Neel temperature was 0.0285 K for
x=1.12(2)x10^{-3} sample. From the concentration dependence of the Neel
temperature it is concluded that there is no critical concentration for the
occurrence of the antiferromagnetic long-range order.


  In this paper, we deal with the problem of implementing an abstract machine
for a stochastic version of the Brane Calculus. Instead of defining an ad hoc
abstract machine, we consider the generic stochastic abstract machine
introduced by Lakin, Paulev\'e and Phillips. The nested structure of membranes
is flattened into a set of species where the hierarchical structure is
represented by means of names. In order to reduce the overhead introduced by
this encoding, we modify the machine by adding a copy-on-write optimization
strategy. We prove that this implementation is adequate with respect to the
stochastic structural operational semantics recently given for the Brane
Calculus. These techniques can be ported also to other stochastic calculi
dealing with nested structures.


  This paper presents a pedestrian hopping model and a traffic signal
scheduling strategy with consideration of both pedestrians and vehicles in the
urban traffic system. Firstly, a novel mathematical model consisting of several
logic constraints is proposed to describe the pedestrian flow in the urban
traffic network and its dynamics are captured by the hopping rule, which
depicts the changing capacity of each time interval from one waiting zone to
another. Based on the hopping mechanism, the pedestrian traffic light
scheduling problems are formulated by two different performance standards:
pedestrian delay and pedestrian unhappiness. Then the mathematical technique
and the meta-heuristic approach are both adopted to solve the scheduling
problem: Mixed integer linear programming (MILP) formulation for pedestrian
delay model and discrete harmony search algorithm (DHS) for both pedestrian
delay model and unhappiness model. Secondly, a mathematical model about the
vehicle traffic network, which captures drivers psychological responses to the
traffic light signals, is introduced. Thirdly, a traffic light scheduling
strategy to minimize the trade-off of the delays between pedestrians and
vehicles is proposed. Finally, we translate this traffic signal scheduling
problem for both pedestrians and vehicles into a MILP problem which can be
solved by several existing tools, e.g., GUROBI. Numerical simulation results
are provided to illustrate the effectiveness of our real-time traffic light
scheduling for pedestrian movement and the potential impact to the vehicle
traffic flows by the pedestrian movement.


  Employee data can be used to facilitate work, but their misusage may pose
risks for individuals. Inverse transparency therefore aims to track all usages
of personal data, allowing individuals to monitor them to ensure accountability
for potential misusage. This necessitates a trusted log to establish an
agreed-upon and non-repudiable timeline of events. The unique properties of
blockchain facilitate this by providing immutability and availability. For
power asymmetric environments such as the workplace, permissionless blockchain
is especially beneficial as no trusted third party is required. Yet, two issues
remain: (1) In a decentralized environment, no arbiter can facilitate and
attest to data exchanges. Simple peer-to-peer sharing of data, conversely,
lacks the required non-repudiation. (2) With data governed by privacy
legislation such as the GDPR, the core advantage of immutability becomes a
liability. After a rightful request, an individual's personal data need to be
rectified or deleted, which is impossible in an immutable blockchain.
  To solve these issues, we present Kovacs, a decentralized data exchange and
usage logging system for inverse transparency built on blockchain. Its
new-usage protocol ensures non-repudiation, and therefore accountability, for
inverse transparency. Its one-time pseudonym generation algorithm guarantees
unlinkability and enables proof of ownership, which allows data subjects to
exercise their legal rights regarding their personal data. With our
implementation, we show the viability of our solution. The decentralized
communication impacts performance and scalability, but exchange duration and
storage size are still reasonable. More importantly, the provided information
security meets high requirements. We conclude that Kovacs realizes
decentralized inverse transparency through secure and GDPR-compliant use of
permissionless blockchain.


  In this work we compute for the first time the so-called Complete-NLO
predictions for top-quark pair hadroproduction in association with at least one
isolated photon ($ t \bar t \gamma$). We also compute NLO QCD+EW predictions
for the similar case with at least two isolated photons ($ t \bar t
\gamma\gamma$) and for single-top hadroproduction in association with at least
one isolated photon. In addition, we complement our results with NLO QCD+EW
predictions of the hadronic and leptonic decays of top-quark including an
isolated photon. All these results have been obtained in a completely automated
approach, by extending the capabilities of the MadGraph5_aMC@NLO framework and
enabling the Complete-NLO predictions for processes with isolated photons in
the final state. We discuss the technical details of the implementation, which
involves a mixed EW renormalisation scheme for such processes.


  We measure how strong, localized contact adhesion between grains affects the
maximum static critical angle, theta_c, of a dry sand pile. By mixing dimer
grains, each consisting of two spheres that have been rigidly bonded together,
with simple spherical monomer grains, we create sandpiles that contain strong
localized adhesion between a given particle and at most one of its neighbors.
We find that tan(theta_c) increases from 0.45 to 1.1 and the grain packing
fraction, Phi, decreases from 0.58 to 0.52 as we increase the relative number
fraction of dimer particles in the pile, nu_d, from 0 to 1. We attribute the
increase in tan(theta_c(nu_d)) to the enhanced stability of dimers on the
surface, which reduces the density of monomers that need to be accomodated in
the most stable surface traps. A full characterization and geometrical
stability analysis of surface traps provides a good quantitative agreement
between experiment and theory over a wide range of nu_d, without any fitting
parameters.


  In this paper, we study a model relevant to semantics-aware goal-oriented
communications. More specifically, observations from an external process are
transmitted through status updates to a battery-powered receiver. From these
updates, the receiver is informed about the status of the process and if there
is sufficient energy, uses them to perform an actuation to achieve a goal. We
consider a wireless power transfer model where the destination receives energy
from a dedicated power transmitter and occasionally from the data transmitter.
We provide the analysis for the Age of Information (AoI). Furthermore, we
propose a new metric, namely the \textit{Age of Actuation (AoA) which is
relevant when the receiver utilizes the status updates to perform actions in a
timely manner}. We analytically characterize the AoA and we show that is a more
general metric than AoI. We provide the optimization problems for both metrics,
and we numerically evaluate our analytical results.


  OH231.8+4.2 is a well studied O-rich CSE around an intermediate-mass evolved
star that displays bipolar molecular outflows accelerated up to 400 km/s. OH231
also presents an exceptional molecular richness probably due to shock-induced
chemical processes. We report the first detection in this source of HNCO, HNCS,
HC3N and NO, with the IRAM-30m telescope in a sensitive mm-wavelength survey
towards this target. HNCO and HNCS are also first detections in CSEs. The
observed line profiles show that the emission arises in the massive central
component of the envelope and at the base of the fast lobes. The NO profiles
are broader than those of HNCO, HNCS, and HC3N, and most importantly, broader
than the line profiles of 13CO. This indicates that the NO abundance is
enhanced in the fast lobes relative to the slow, central parts. From LTE and
non-LTE excitation analysis, we estimate beam-average rotational temperatures
of 15-30 K (and, maybe, up to 55 K for HC3N) and fractional abundances of
X(HNCO)=[0.8-1]E-7, X(HNCS)=[0.9-1]E-8, X(HC3N)=[5-7]E-9 and X(NO)=[1-2]E-6. NO
is, therefore, amongst the most abundant N-bearing species in OH231. We have
performed thermodynamical chemical equilibrium and chemical kinetics models to
investigate the formation of these N-bearing species in OH231. The model
underestimates the observed abundances for HNCO, HNCS, and HC3N by several
orders of magnitude, which indicates that these molecules can hardly be
products of standard UV-photon and/or cosmic-ray induced chemistry in OH231,
and that other processes (e.g. shocks) play a major role in their formation.
For NO, the model abundance is compatible with the observed average value. The
new detections presented in this work corroborate the particularly rich
chemistry of OH231, which is likely profoundly influenced by shock-induced
processes, as proposed in earlier works.


  We present a simulation-based approach for generating barrier certificate
functions for safety verification of cyber-physical systems (CPS) that contain
neural network-based controllers. A linear programming solver is utilized to
find a candidate generator function from a set of simulation traces obtained by
randomly selecting initial states for the CPS model. A level set of the
generator function is then selected to act as a barrier certificate for the
system, meaning it demonstrates that no unsafe system states are reachable from
a given set of initial states. The barrier certificate properties are verified
with an SMT solver. This approach is demonstrated on a case study in which a
Dubins car model of an autonomous vehicle is controlled by a neural network to
follow a given path.


  We present a new decoding procedure to transmit classical information in a
quantum channel which, saturating asymptotically the Holevo bound, achieves the
optimal rate of the communication line. Differently from previous proposals, it
is based on performing a sequence of (projective) YES/NO measurements which in
N steps determines which codeword was sent by the sender (N being the number of
the codewords). Our analysis shows that as long as N is below the limit imposed
by the Holevo bound the error probability can be sent to zero asymptotically in
the length of the codewords.


  Consider an N x N matrix A for which zero is a defective eigenvalue. In this
case, the algebraic multiplicity of the zero eigenvalue is greater than the
geometric multiplicity. We show how an inflated (N+1) x (N+1) matrix L can be
constructed as a rank one perturbation to A, such that L is singular but no
longer defective, and the nullvectors of L can be easily related to the
nullvectors of A. The motivation for this construction comes from linear
stability analysis of an experimental reaction-diffusion system which exhibits
the Turing instability. The utility of this scheme is accurate numerical
computation of nullvector(s) corresponding to a defective zero eigenvalue. We
show that numerical computations on L yield more accurate eigenvectors than
direct computation on A.


  We prove convergence of renormalized correlations of primary fields, i. e.,
spins, disorders, fermions and energy densities, in the scaling limit of the
critical Ising model in arbitrary finitely connected domains, with fixed (plus
or minus) or free boundary conditions, or mixture thereof. We describe the
limits of correlations in terms of solutions of Riemann boundary value
problems, and prove their conformal covariance. Moreover, we prove fusion
rules, or operator product expansions, which describe asymptotics of the
scaling limits of the correlations as some of the points collide together. We
give explicit formulae for correlations in the case of simply-connected and
doubly-connected domains. Our presentation is self-contained, and the proofs
are simplified as compared to the previous work where particular cases are
treated.


  This paper presents an overview of results obtained during the CAWSES II
period on the short term variability of the Sun and how it affects the near
Earth space environment. CAWSES II was planned to examine the behavior of the
solar terrestrial system as the solar activity climbed to its maximum phase in
solar cycle 24. After a deep minimum following cycle 23, the Sun climbed to a
very weak maximum in terms of the sunspot number in cycle 24 (MiniMax24), so
many of the results presented here refer to this weak activity in comparison
with cycle 23. The short term variability that has immediate consequence to
Earth and geospace manifests as solar eruptions from closed field regions and
high speed streams from coronal holes. Both electromagnetic (flares) and mass
emissions (coronal mass ejections, CMEs) are involved in solar eruptions, while
coronal holes result in high speed streams that collide with slow wind forming
the so called corotating interaction regions (CIRs). Fast CMEs affect Earth via
leading shocks accelerating energetic particles and creating large geomagnetic
storms. CIRs and their trailing high speed streams (HSSs), on the other hand,
are responsible for recurrent small geomagnetic storms and extended (days) of
auroral zone activity, respectively. The latter lead to the acceleration of
relativistic magnetospheric killer electrons. One of the major consequences of
the weak solar activity is the altered physical state of the heliosphere that
has serious implications for the shock-driving and storm causing properties of
CMEs. Finally, a discussion is presented on extreme space weather events
prompted by the 2012 July 23 super storm event that occurred on the backside of
the Sun. Many of these studies were enabled by the simultaneous availability of
remote-sensing and in situ observations from multiple vantage points with
respect to the Sun Earth line.


  I give a short review of the current status of lattice QCD calculations of
the spectrum of charmonium.


  We review the current status of the data on neutrino masses and lepton mixing
and the prospects for measuring the CP-violating phases in the lepton sector.
The possible connection between low energy CP violation encoded in the Dirac
and Majorana phases of the Pontecorvo-Maki-Nakagawa-Sakata mixing matrix and
successful leptogenesis is emphasized in the context of seesaw extensions of
the Standard Model with a flavor symmetry Gf (and CP symmetry).


  We consider the propagation of polarized light in the medium with Maxwell
fish eye refraction index profile. We show that polarization violates the
additional symmetries of medium, so that ray trajectories no longer remain
closed. Then we suggest a modified, polarization-dependent Maxwell fish eye
refraction index which restores all symmetries of initial profile and yields
closed trajectories of polarized light. Explicit expressions for the
polarization dependent integrals of motion and the solutions of corresponding
ray trajectories are presented.


  Globular clusters harbor numerous millisecond pulsars, but long-period
pulsars ($P \gtrsim 100$ ms) are rarely found. In this study, we employed a
fast folding algorithm to analyze observational data from multiple globular
clusters obtained by the Five-hundred-meter Aperture Spherical radio Telescope
(FAST), aiming to detect the existence of long-period pulsars. We estimated the
impact of the median filtering algorithm in eliminating red noise on the
minimum detectable flux density ($S_{\rm min}$) of pulsars. Subsequently, we
successfully discovered two isolated long-period pulsars in M15 with periods
approximately equal to 1.928451 seconds and 3.960716 seconds, respectively. On
the $P-\dot{P}$ diagram, both pulsars are positioned below the spin-up line,
suggesting a possible history of partial recycling in X-ray binary systems
disrupted by dynamical encounters later on. According to timing results, these
two pulsars exhibit remarkably strong magnetic fields. If the magnetic fields
were weakened during the accretion process, then a short duration of accretion
might explain the strong magnetic fields of these pulsars.


  The temporal evolution of pulsed Spin Hall Effect - Spin Transfer Torque
(SHE-STT) driven auto-oscillations in a Yttrium Iron Garnet (YIG) / platinum
(Pt) microdisc is studied experimentally using time-resolved Brillouin Light
Scattering (BLS) spectroscopy. It is demonstrated that the frequency of the
auto-oscillations is different in the center and at the edge of the
investigated disc that is related to the simultaneous STT excitation of a
bullet and a non-localized spin-wave mode. Furthermore, the magnetization
precession intensity is found to saturate on a time scale of 20 ns or longer,
depending on the current density. For this reason, our findings suggest that a
proper ratio between the current and the pulse duration is of crucial
importance for future STT-based devices.


  The advent of renewable energy has huge implications for the design and
control of power grids. Due to increasing supply-side uncertainty, traditional
reliability constraints such as strict bounds on current, voltage and
temperature in a transmission line have to be replaced by computationally
demanding chance constraints. In this paper we use large deviations techniques
to study the probability of current and temperature overloads in power grids
with stochastic power injections, and develop corresponding safe capacity
regions. In particular, we characterize the set of admissible power injections
such that the probability of overloading of any line over a given time interval
stays below a fixed target. We show how enforcing (stochastic) constraints on
temperature, rather than on current, results in a less conservative approach
and can thus lead to capacity gains.


  We prove that there exists an absolute constant $\alpha >1$ with the
following property: if $K$ is a convex body in ${\mathbb R}^n$ whose center of
mass is at the origin, then a random subset $X\subset K$ of cardinality ${\rm
card}(X)=\lceil\alpha n\rceil $ satisfies with probability greater than
$1-e^{-n}$ {K\subseteq c_1n\,{\mathrm conv}(X),} where $c_1>0$ is an absolute
constant. As an application we show that the vertex index of any convex body
$K$ in ${\mathbb R}^n$ is bounded by $c_2n^2$, where $c_2>0$ is an absolute
constant, thus extending an estimate of Bezdek and Litvak for the symmetric
case.


  We present a new class of service for location based social networks, called
the Flexible Group Spatial Keyword Query, which enables a group of users to
collectively find a point of interest (POI) that optimizes an aggregate cost
function combining both spatial distances and keyword similarities. In
addition, our query service allows users to consider the tradeoffs between
obtaining a sub-optimal solution for the entire group and obtaining an
optimimized solution but only for a subgroup.
  We propose algorithms to process three variants of the query: (i) the group
nearest neighbor with keywords query, which finds a POI that optimizes the
aggregate cost function for the whole group of size n, (ii) the subgroup
nearest neighbor with keywords query, which finds the optimal subgroup and a
POI that optimizes the aggregate cost function for a given subgroup size m (m
<= n), and (iii) the multiple subgroup nearest neighbor with keywords query,
which finds optimal subgroups and corresponding POIs for each of the subgroup
sizes in the range [m, n]. We design query processing algorithms based on
branch-and-bound and best-first paradigms. Finally, we provide theoretical
bounds and conduct extensive experiments with two real datasets which verify
the effectiveness and efficiency of the proposed algorithms.


  This paper studies randomized quasi-Monte Carlo (QMC) sampling for
discontinuous integrands having singularities along the boundary of the unit
cube $[0,1]^d$. Both discontinuities and singularities are extremely common in
the pricing and hedging of financial derivatives and have a tremendous impact
on the accuracy of QMC. It was previously known that the root mean square error
of randomized QMC is only $o(n^{-1/2})$ for discontinuous functions with
singularities. We find that under some mild conditions, randomized QMC yields
an expected error of $O(n^{-1/2-1/(4d-2)+\epsilon})$ for arbitrarily small
$\epsilon>0$. Moreover, one can get a better rate if the boundary of
discontinuities is parallel to some coordinate axes. As a by-product, we find
that the expected error rate attains $O(n^{-1+\epsilon})$ if the
discontinuities are QMC-friendly, in the sense that all the discontinuity
boundaries are parallel to coordinate axes. The results can be used to assess
the QMC accuracy for some typical problems from financial engineering.


  The classic Coupon-Collector Problem (CCP) is generalized to the extent that
each coupons serves certain "purposes". Only basic probability theory is used.
Centerpiece rather is an algorithm that efficiently counts all $k$-element
transversals of a set system.


  We analyze the error of the WEB-S finite element method applied to elliptic
systems with non-cooperative dominant coupling,with a mixed
Dirichlet/Neumann/Robin boundary condition. This problem is strongly related to
a posteriori error estimates, giving computable bounds for computational errors
and detecting zones in the solution domain where such errors are too large and
certain mesh refinements should be performed. These results are based on an
extensive regularity analysis of the interface problems of concern.Finally, the
error analysis is illustrated by numerical experiments.


  We analyse archival CGRO-BATSE X-ray flux and spin frequency measurements of
GX 1+4 over a time span of 3000 days. We systematically search for time
dependent variations of torque luminosity correlation. Our preliminary results
indicate that the correlation shifts from being positive to negative on time
scales of few 100 days.


  This paper studies switching stabilization problems for general switched
nonlinear systems. A piecewise smooth control-Lyapunov function (PSCLF)
approach is proposed and a constructive way to design a stabilizing switching
law is developed. The switching law is constructed via the directional
derivatives of the PSCLF with a careful discussion on various technical issues
that may occur on the nonsmooth surfaces. Sufficient conditions are derived to
ensure stability of the closed-loop Filippov solutions including possible
sliding motions. The proposed PSCLF approach contains many existing results as
special cases and provides a unified framework to study nonlinear switching
stabilization problems with a systematic consideration of sliding motions.
Applications of the framework to switched linear systems with quadratic and
piecewise quadratic control-Lyapunov functions are discussed and results
stronger than the existing methods in the literature are obtained. Application
to stabilization of switched nonlinear systems is illustrated through an
numerical example.


  In this paper we study travelling front solutions for nonlocal equations of
the type \begin{equation} \partial_t u = N * S(u) + \nabla F(u), \qquad u(t,x)
\in \mathbf{R}^d. \end{equation} Here $N *$ denotes a convolution-type operator
in the spatial variable $x \in \mathbf{R}$, either continuous or discrete. We
develop a Morse-type theory, the Conley--Floer homology, which captures
travelling front solutions in a topologically robust manner, by encoding fronts
in the boundary operator of a chain complex. The equations describing the
travelling fronts involve both forward and backward delay terms, possibly of
infinite range. Consequently, these equations lack a natural phase space, so
that classic dynamical systems tools are not at our disposal. We therefore
develop, from scratch, a general transversality theory, and a classification of
bounded solutions, in the absence of a phase space. In various cases the
resulting Conley--Floer homology can be interpreted as a homological Conley
index for multivalued vector fields. Using the Conley--Floer homology we derive
existence and multiplicity results on travelling front solutions.


  In every point of a K\"ahler manifold there exist special holomorphic
coordinates well adapted to the underlying geometry. Comparing these K\"ahler
normal coordinates with the Riemannian normal coordinates defined via the
exponential map we prove that their difference is a universal power series in
the curvature tensor and its iterated covariant derivatives and devise an
algorithm to calculate this power series to arbitrary order. As a byproduct we
generalize K\"ahler normal coordinates to the class of complex affine manifolds
with (1,1)-curvature tensor. Moreover we describe the Spencer connection on the
infinite order Taylor series of the K\"ahler normal potential and obtain
explicit formulas for the Taylor series of all relevant geometric objects on
symmetric spaces.


  With the advances in e-Sciences and the growing complexity of scientific
analyses, more and more scientists and researchers are relying on workflow
systems for process coordination, derivation automation, provenance tracking,
and bookkeeping. While workflow systems have been in use for decades, it is
unclear whether scientific workflows can or even should build on existing
workflow technologies, or they require fundamentally new approaches. In this
paper, we analyze the status and challenges of scientific workflows,
investigate both existing technologies and emerging languages, platforms and
systems, and identify the key challenges that must be addressed by workflow
systems for e-science in the 21st century.


  Modular Galois representations into GL_2(F_p) with cyclotomic determinant
arise from elliptic curves for p = 2,3,5. We show (by constructing explicit
examples) that such elliptic curves cannot be chosen to have conductor as small
as possible at all primes other than p. Our proof involves finding all elliptic
curves of conductor 85779, a custom computation carried out for us by Cremona.
This leads to a counterexample to a conjecture of Lario and Rio. For p > 5, we
construct irreducible representations with cyclotomic determinant that do not
arise from any elliptic curve over Q.


  In this paper, we prove that for every Finsler metric on the 2-dimensional
sphere there exist at least two distinct prime closed geodesics. For the case
of the two-sphere, this solves an open problem posed by D. V. Anosov in 1974.


  A non-iterative method is presented for the factorization step of sector
decomposition method, which separates infrared divergent part from loop
integration. This method is based on a classification of asymptotic behavior of
polynomials. The problem is converted to ones for convex body in Euclidean
space. They are solved with algorithms developed in computational geometry. A
test implementation shows that this method produces less number of decomposed
sectors than usual iterative sector decompositions.


  The intricate interplay between spin and lattice degrees of freedom in
two-dimensional magnetic materials plays a pivotal role in modifying their
magnetic characteristics, engendering hybrid quasiparticles, and implementing
functional devices. Herein, we present our comprehensive and in-depth
investigations on magnetic and lattice excitations of MnPSe3-xSx (x = 0, 0.5,
and 1.5) alloys, utilizing temperature- and polarization-dependent Raman
scattering. Our experimental results reveal the occurrence of multiple phase
transitions, evidenced by notable changes in phonon self-energy and the
appearance or splitting of phonon modes. These emergent phases are tied to the
development of long and short-range spin-spin correlations, as well as to spin
reorientations or magnetic instabilities. Our analysis of two-magnon
excitations as a function of temperature and composition showcases their
hybridization with phonons whose degree weakens with increasing x. Moreover,
the suppression of spin-dependent phonon intensity in chemically
most-disordered MnPSe3-xSx (x = 1.5) suggests that chalcogen substitution
offers a control knob of tuning spin and phonon dynamics by modulating
concurrently superexchange pathways and a degree of trigonal distortions.


  A unique feature of the complex band structures of moir\'e materials is the
presence of minivalleys, their hybridization, and scattering between them. Here
we investigate magneto-transport oscillations caused by scattering between
minivalleys - a phenomenon analogous to magneto-intersubband oscillations - in
a twisted double bilayer graphene sample with a twist angle of 1.94{\deg}. We
study and discuss the potential scattering mechanisms and find an
electron-phonon mechanism and valley conserving scattering to be likely.
Finally, we discuss the relevance of our findings for different materials and
twist angles.


  We report on highly accurate calculations of Born-Oppenheimer potentials for
excited $n\,\Sigma^{+}$ states of the hydrogen molecule for all possible
combinations of singlet/triplet and gerade/ungerade symmetries up to $n=7$. A
relative accuracy of $10^{-10}$ (0.00002 cm$^{-1}$) or better is achieved for
all the internuclear distances and all the excited states under consideration
-- an improvement with respect to the best results available in the literature
by at least 6 orders of magnitude. Presented variational calculations rely on
efficient evaluation of molecular integrals with the explicitly correlated
exponential basis in arbitrary precision arithmetics.


  A correlation between astrophysical high-energy neutrinos and blazars has
been suggested by various authors. In particular, a likely association between
IceCube events and intermediate and high-energy peaked BL Lac objects has led
to a sample of 47 objects having a high probability of being neutrino sources.
In the first paper of this series we reported optical spectroscopy of 17
objects, which together with data taken from the literature covered 80 per cent
of the sample. Here we present spectroscopy obtained at large aperture
telescopes of a further 17 objects (plus four additional targets), which
completes the sample coverage. For twelve objects we are able to determine the
redshift (0.07 < z <1.6), while for the others we set a lower limit on it,
based on either the robust detection of intervening absorption systems or on an
estimation derived from the absence of spectral signatures of the host galaxy.
With these new data we expand and reinforce the main results of our previous
papers, namely the fact that in terms of their broad-band properties our
sources appear to be indistinguishable from the rest of the blazar population
and the relatively large (>34 per cent and possibly as high as 80 per cent)
fraction of masquerading BL Lac objects, for which the low equivalent width of
the emission lines is due to the brightness of the boosted continuum, rather
than being an intrinsic property, in our sample.


  Recent development in compressed sensing (CS) has revealed that the use of a
special design of measurement matrix, namely the spatially-coupled matrix, can
achieve the information-theoretic limit of CS. In this paper, we consider the
measurement matrix which consists of the spatially-coupled \emph{orthogonal}
matrices. One example of such matrices are the randomly selected discrete
Fourier transform (DFT) matrices. Such selection enjoys a less memory
complexity and a faster multiplication procedure. Our contributions are the
replica calculations to find the mean-square-error (MSE) of the Bayes-optimal
reconstruction for such setup. We illustrate that the reconstruction thresholds
under the spatially-coupled orthogonal and Gaussian ensembles are quite
different especially in the noisy cases. In particular, the spatially coupled
orthogonal matrices achieve the faster convergence rate, the lower measurement
rate, and the reduced MSE.


  Astronomy is at times a science of unexpected discovery. When it is, and if
we are lucky, new intellectual territories emerge to challenge our views of the
cosmos. The recent indirect detections using high-precision Doppler
spectroscopy of now more than one hundred giant planets orbiting more than one
hundred nearby stars is an example of such rare serendipity. What has been
learned has shaken our preconceptions, for none of the planetary systems
discovered to date is like our own. However, the key to unlocking a planet's
chemical, structural, and evolutionary secrets is the direct detection of the
planet's light. I review the embryonic theory of the spectra, atmospheres, and
light curves of irradiated giant planets and put this theory into the context
of the many proposed astronomical campaigns to image them.


  In-depth understanding of the retarded oxidation phenomenon observed during
the oxidation of silicon nanostructures is proposed. The wet thermal oxidation
of various silicon nanostructures such as nanobeams, concave/convex nanorings
and nanowires exhibits an extremely different and complex behavior. Such
effects have been investigated by the modeling of the mechanical stress
generated during the oxidation process explaining the retarded regime. The
model describes the oxidation kinetics of silicon nanowires down to a few
nanometers while predicting reasonable and physical stress levels at the
Si/SiO$_{2}$ interface by correctly taking into account the relaxation effects
in silicon oxide through plastic flow.


  In $4$-dimensional pure compact $U(1)$ lattice gauge theory, we analyse
topological aspects of the dynamics of monopoles across the deconfinement phase
transition. We do this using tools from Topological Data Analysis (TDA). We
demonstrate that observables constructed from the zeroth and first homology
groups of monopole current networks may be used to quantitatively and robustly
locate the critical inverse coupling $\beta_{c}$ through finite-size scaling.
Our method provides a mathematically robust framework for the characterisation
of topological invariants related to monopole currents, putting on firmer
ground earlier investigations. Moreover, our approach can be generalised to the
study of Abelian monopoles in non-Abelian gauge theories.


  Efficiency is an important issue in designing video architectures for action
recognition. 3D CNNs have witnessed remarkable progress in action recognition
from videos. However, compared with their 2D counterparts, 3D convolutions
often introduce a large amount of parameters and cause high computational cost.
To relieve this problem, we propose an efficient temporal module, termed as
Temporal Enhancement-and-Interaction (TEI Module), which could be plugged into
the existing 2D CNNs (denoted by TEINet). The TEI module presents a different
paradigm to learn temporal features by decoupling the modeling of channel
correlation and temporal interaction. First, it contains a Motion Enhanced
Module (MEM) which is to enhance the motion-related features while suppress
irrelevant information (e.g., background). Then, it introduces a Temporal
Interaction Module (TIM) which supplements the temporal contextual information
in a channel-wise manner. This two-stage modeling scheme is not only able to
capture temporal structure flexibly and effectively, but also efficient for
model inference. We conduct extensive experiments to verify the effectiveness
of TEINet on several benchmarks (e.g., Something-Something V1&V2, Kinetics,
UCF101 and HMDB51). Our proposed TEINet can achieve a good recognition accuracy
on these datasets but still preserve a high efficiency.


  We performed simulations of self-gravitating hydrodynamic turbulence to model
the formation of filaments, clumps and cores in molecular clouds. We find that
when the mass on the initial computational grid is comparable to the Jeans
mass, turbulent pressure is able to prevent gravitational collapse. When the
turbulence has damped away sufficiently, gravitational collapse can occur, and
the resulting structure closely resembles the pre-singularity collapse of an
isothermal sphere of Penston (1969). If several Jeans masses are initially
placed on the grid, turbulence may not be sufficient to prevent collapse before
turbulence can be significantly damped. In this case, the cores have density
structures which are considerably shallower than expected for an isothermal
gas, and resemble the solutions for a logatropic equation of state.


  The scarcity of large parallel corpora is an important obstacle for neural
machine translation. A common solution is to exploit the knowledge of language
models (LM) trained on abundant monolingual data. In this work, we propose a
novel approach to incorporate a LM as prior in a neural translation model (TM).
Specifically, we add a regularization term, which pushes the output
distributions of the TM to be probable under the LM prior, while avoiding wrong
predictions when the TM "disagrees" with the LM. This objective relates to
knowledge distillation, where the LM can be viewed as teaching the TM about the
target language. The proposed approach does not compromise decoding speed,
because the LM is used only at training time, unlike previous work that
requires it during inference. We present an analysis of the effects that
different methods have on the distributions of the TM. Results on two
low-resource machine translation datasets show clear improvements even with
limited monolingual data.


  In the hierarchical formation model, galaxy clusters grow by accretion of
smaller groups or isolated galaxies. During the infall into the centre of a
cluster, the properties of accreted galaxies change. In particular, both
observations and numerical simulations suggest that its dark matter halo is
stripped by the tidal forces of the host.
  We use galaxy-galaxy weak lensing to measure the average mass of dark matter
haloes of satellite galaxies as a function of projected distance to the centre
of the host, for different stellar mass bins. Assuming that the stellar
component of the galaxy is less disrupted by tidal stripping, stellar mass can
be used as a proxy of the infall mass. We study the stellar to halo mass
relation of satellites as a function of the cluster-centric distance to measure
tidal stripping.
  We use the shear catalogues of the DES science verification archive, the
CFHTLenS and the CFHT Stripe 82 (CS82) surveys, and we select satellites from
the redMaPPer catalogue of clusters. For galaxies located in the outskirts of
clusters, we find a stellar to halo mass relation in good agreement with the
theoretical expectations from \citet{moster2013} for central galaxies. In the
centre of the cluster, we find that this relation is shifted to smaller halo
mass for a given stellar mass. We interpret this finding as further evidence
for tidal stripping of dark matter haloes in high density environments.


  A leading candidate for the extragalactic source of high energy cosmic rays
is the Fermi engine mechanism, in which protons confined by magnetic fields are
accelerated to very high energy through repeated scattering by plasma shock
fronts. In the process of acceleration, collisions of trapped protons with the
ambient plasma produce pions which decay to electromagnetic energy and
neutrinos. For optically thin sources, a strong connection between the emerging
cosmic rays and secondary neutrinos can be established. In this context, we
show the feasibility of using the Glashow resonance as a discriminator between
the $pp$ and $p\gamma$ interactions in Fermi engines as sources of neutrinos.
In particular, we demonstrate how three years of observation at the km$^3$
IceCube facility can serve as a filter for the dominance of the $pp$
interaction at the source.


  This article describes the application of recently introduced complex
networks concepts and methods to the characterization and analysis of cortical
bone structure. Three-dimensional reconstructions of the system of channels
underlying bone structure are obtained by using histological and computer
graphics methods and then represented in terms of complex networks.
Conﬂuences of two or more channels are represented as nodes, while the
interconnecting channels are expressed as edges. The hierarchical backbone (the
tree with maximum depth) of such a network is obtained and understood to
correspond to the main structure underlying the channel system. The remainder
of the network is shown to correspond to geographical communities, suggesting
that the bone channel structure involves a number of regular communities
appended along the hierarchical backbone. It is shown that such additional
edges play a crucial role in enhancing the network resilience and in reducing
the shortest paths in both topology and geometry.The recently introduced
concept of fractal dimension of a network (cond-mat/0503078) is then correlated
with the resilience of the several components of the bone channel structure to
obstruction and failure, with important implications for the understanding of
the organization and robustness of cortical bone structure.


  The usage of deep learning is being escalated in many applications. Due to
its outstanding performance, it is being used in a variety of security and
privacy-sensitive areas in addition to conventional applications. One of the
key aspects of deep learning efficacy is to have abundant data. This trait
leads to the usage of data which can be highly sensitive and private, which in
turn causes wariness with regard to deep learning in the general public.
Membership inference attacks are considered lethal as they can be used to
figure out whether a piece of data belongs to the training dataset or not. This
can be problematic with regards to leakage of training data information and its
characteristics. To highlight the significance of these types of attacks, we
propose an enhanced methodology for membership inference attacks based on
adversarial robustness, by adjusting the directions of adversarial
perturbations through label smoothing under a white-box setting. We evaluate
our proposed method on three datasets: Fashion-MNIST, CIFAR-10, and CIFAR-100.
Our experimental results reveal that the performance of our method surpasses
that of the existing adversarial robustness-based method when attacking
normally trained models. Additionally, through comparing our technique with the
state-of-the-art metric-based membership inference methods, our proposed method
also shows better performance when attacking adversarially trained models. The
code for reproducing the results of this work is available at
\url{https://github.com/plll4zzx/Evaluating-Membership-Inference-Through-Adversarial-Robustness}.


  Topos quantum mechanics, developed by Isham et. al., creates a topos of
presheaves over the poset V(N) of abelian von Neumann subalgebras of the von
Neumann algebra N of bounded operators associated to a physical system, and
established several results, including: (a) a connection between the
Kochen-Specker theorem and the non-existence of a global section of the
spectral presheaf; (b) a version of the spectral theorem for self-adjoint
operators; (c) a connection between states of N and measures on the spectral
presheaf; and (d) a model of dynamics in terms of V(N). We consider a
modification to this approach using not the whole of the poset V(N), but only
its elements of height at most two. This produces a different topos with
different internal logic. However, the core results (a)--(d) established using
the full poset V(N) are also established for the topos over the smaller poset,
and some aspects simplify considerably. Additionally, this smaller poset has
appealing aspects reminiscent of projective geometry.


  We point out that an important portion of the high energy of the cosmic rays
from extragalactic sources can be attributed to a Hilbertian repulsive effect,
which is a consequence of Einstein equations without cosmological term.


  Ad hominem attacks are those that target some feature of a person's character
instead of the position the person is maintaining. These attacks are harmful
because they propagate implicit biases and diminish a person's credibility.
Since dialogue systems respond directly to user input, it is important to study
ad hominems in dialogue responses. To this end, we propose categories of ad
hominems, compose an annotated dataset, and build a classifier to analyze human
and dialogue system responses to English Twitter posts. We specifically compare
responses to Twitter topics about marginalized communities (#BlackLivesMatter,
#MeToo) versus other topics (#Vegan, #WFH), because the abusive language of ad
hominems could further amplify the skew of power away from marginalized
populations. Furthermore, we propose a constrained decoding technique that uses
salient $n$-gram similarity as a soft constraint for top-$k$ sampling to reduce
the amount of ad hominems generated. Our results indicate that 1) responses
from both humans and DialoGPT contain more ad hominems for discussions around
marginalized communities, 2) different quantities of ad hominems in the
training data can influence the likelihood of generating ad hominems, and 3) we
can use constrained decoding techniques to reduce ad hominems in generated
dialogue responses.


  Change detection is widely applied in remote sensing image analysis. Existing
methods require training models separately for each dataset, which leads to
poor domain generalization. Moreover, these methods rely heavily on large
amounts of high-quality pair-labelled data for training, which is expensive and
impractical. In this paper, we propose a multimodal contrastive learning
(ChangeCLIP) based on visual-language pre-training for change detection domain
generalization. Additionally, we propose a dynamic context optimization for
prompt learning. Meanwhile, to address the data dependency issue of existing
methods, we introduce a single-temporal and controllable AI-generated training
strategy (SAIN). This allows us to train the model using a large number of
single-temporal images without image pairs in the real world, achieving
excellent generalization. Extensive experiments on series of real change
detection datasets validate the superiority and strong generalization of
ChangeCLIP, outperforming state-of-the-art change detection methods. Code will
be available.


  It is challenging to control the quality of online information due to the
lack of supervision over all the information posted online. Manual checking is
almost impossible given the vast number of posts made on online media and how
quickly they spread. Therefore, there is a need for automated rumour detection
techniques to limit the adverse effects of spreading misinformation. Previous
studies mainly focused on finding and extracting the significant features of
text data. However, extracting features is time-consuming and not a highly
effective process. This study proposes the BERT- based pre-trained language
models to encode text data into vectors and utilise neural network models to
classify these vectors to detect misinformation. Furthermore, different
language models (LM) ' performance with different trainable parameters was
compared. The proposed technique is tested on different short and long text
datasets. The result of the proposed technique has been compared with the
state-of-the-art techniques on the same datasets. The results show that the
proposed technique performs better than the state-of-the-art techniques. We
also tested the proposed technique by combining the datasets. The results
demonstrated that the large data training and testing size considerably
improves the technique's performance.


  In this paper we introduce a maximal divisorial set in the arc space of a
variety. The generalized Nash problem is reduced to a translation problem of
the inclusion of two maximal divisorial sets. We study this problem and show a
counter example to the most natural expectation even for a non-singular
variety.


  We confirm and extend our previous detection of a population of intergalactic
globular clusters in Abell 1185, and report the first discovery of an
intergalactic globular cluster in the nearby Virgo cluster of galaxies. The
numbers, colors and luminosities of these objects can place constraints on
their origin, which in turn may yield new insights to the evolution of galaxies
in dense environments.


  We present MonteCUBES ("Monte Carlo Utility Based Experiment Simulator"), a
software package designed to sample the neutrino oscillation parameter space
through Markov Chain Monte Carlo algorithms. MonteCUBES makes use of the GLoBES
software so that the existing experiment definitions for GLoBES, describing
long baseline and reactor experiments, can be used with MonteCUBES. MonteCUBES
consists of two main parts: The first is a C library, written as a plug-in for
GLoBES, implementing the Markov Chain Monte Carlo algorithm to sample the
parameter space. The second part is a user-friendly graphical Matlab interface
to easily read, analyze, plot and export the results of the parameter space
sampling.


  Integrated sensing and communication (ISAC) has been envisioned as a
promising technology to tackle the spectrum congestion problem for future
networks. In this correspondence, we investigate to deploy a reconfigurable
intelligent surface (RIS) in an ISAC system for achieving better performance.
In particular, a multi-antenna base station (BS) simultaneously serves multiple
single-antenna users with the assistance of a RIS and detects potential
targets. The active beamforming of the BS and the passive beamforming of the
RIS are jointly optimized to maximize the achievable sum-rate of the
communication users while satisfying the constraint of beampattern similarity
for radar sensing, the restriction of the RIS, and the transmit power budget.
An efficient alternating algorithm based on the fractional programming (FP),
majorization-minimization (MM), and manifold optimization methods is developed
to convert the resulting non-convex optimization problem into two solvable
sub-problems and iteratively solve them. Simulation studies illustrate the
advancement of deploying RIS in ISAC systems and the effectiveness of the
proposed algorithm.


  We characterize the canonical diagonal subalgebra of the C*-algebra
associated with a generalized Boolean dynamical system. We also introduce a
particular commutative subalgebra, which we call the abelian core, in our
C*-algebra. We then establish a uniqueness theorem under the assumptions that B
and L are countable, which says that a *-homomorphism of our C*-algebra is
injective if and only if its restriction to the abelian core is injective.


  Purpose: To provide a critical review of Bergman's 2001 study on the Deep
Web. In addition, we bring a new concept into the discussion, the Academic
Invisible Web (AIW). We define the Academic Invisible Web as consisting of all
databases and collections relevant to academia but not searchable by the
general-purpose internet search engines. Indexing this part of the Invisible
Web is central to scientific search engines. We provide an overview of
approaches followed thus far. Design/methodology/approach: Discussion of
measures and calculations, estimation based on informetric laws. Literature
review on approaches for uncovering information from the Invisible Web.
Findings: Bergman's size estimate of the Invisible Web is highly questionable.
We demonstrate some major errors in the conceptual design of the Bergman paper.
A new (raw) size estimate is given. Research limitations/implications: The
precision of our estimate is limited due to a small sample size and lack of
reliable data. Practical implications: We can show that no single library alone
will be able to index the Academic Invisible Web. We suggest collaboration to
accomplish this task. Originality/value: Provides library managers and those
interested in developing academic search engines with data on the size and
attributes of the Academic Invisible Web.


  Let $(X,T^{1,0}X)$ be a compact orientable embeddable three dimensional
strongly pseudoconvex CR manifold and let ${\rm P\,}$ be the associated CR
Paneitz operator. In this paper, we show that (I) ${\rm P\,}$ is self-adjoint
and ${\rm P\,}$ has $L^2$ closed range. Let $N$ and $\Pi$ be the associated
partial inverse and the orthogonal projection onto ${\rm Ker\,}{\rm P\,}$
respectively, then $N$ and $\Pi$ enjoy some regularity properties. (II) Let
$\hat{\mathcal{P}}$ and $\hat{\mathcal{P}_0}$ be the space of $L^2$ CR
pluriharmonic functions and the space of real part of $L^2$ global CR functions
respectively. Let $S$ be the associated Szeg\"o projection and let $\tau$,
$\tau_0$ be the orthogonal projections onto $\hat{\mathcal{P}}$ and
$\hat{\mathcal{P}_0}$ respectively. Then, $\Pi=S+\ol S+F_0$, $\tau=S+\ol
S+F_1$, $\tau_0=S+\ol S+F_2$, where $F_0, F_1, F_2$ are smoothing operators on
$X$. In particular, $\Pi$, $\tau$ and $\tau_0$ are Fourier integral operators
with complex phases and $\hat{\mathcal{P}}^\perp\bigcap{\rm Ker\,}{\rm P\,}$,
$\hat{\mathcal{P}_0}^\perp\bigcap\hat{\mathcal{P}}$,
$\hat{\mathcal{P}_0}^\perp\bigcap{\rm Ker\,}{\rm P\,}$ are all finite
dimensional subspaces of $C^\infty(X)$ (it is well-known that
$\hat{\mathcal{P}_0}\subset\hat{\mathcal{P}}\subset{\rm Ker\,}{\rm P\,}$).
(III) ${\rm Spec\,}{\rm P\,}$ is a discrete subset of $\Real$ and for every
$\lambda\in{\rm Spec\,}{\rm P\,}$, $\lambda\neq0$, $\lambda$ is an eigenvalue
of ${\rm P\,}$ and the associated eigenspace $H_\lambda({\rm P\,})$ is a finite
dimensional subspace of $C^\infty(X)$.


  Tetravex is a widely played one person computer game in which you are given
$n^2$ unit tiles, each edge of which is labelled with a number. The objective
is to place each tile within a $n$ by $n$ square such that all neighbouring
edges are labelled with an identical number. Unfortunately, playing Tetravex is
computationally hard. More precisely, we prove that deciding if there is a
tiling of the Tetravex board is NP-complete. Deciding where to place the tiles
is therefore NP-hard. This may help to explain why Tetravex is a good puzzle.
This result compliments a number of similar results for one person games
involving tiling. For example, NP-completeness results have been shown for: the
offline version of Tetris, KPlumber (which involves rotating tiles containing
drawings of pipes to make a connected network), and shortest sliding puzzle
problems. It raises a number of open questions. For example, is the infinite
version Turing-complete? How do we generate Tetravex problems which are truly
puzzling as random NP-complete problems are often surprising easy to solve? Can
we observe phase transition behaviour? What about the complexity of the problem
when it is guaranteed to have an unique solution? How do we generate puzzles
with unique solutions?


  We show that the characters of all highest weight modules over an affine Lie
algebra with the highest weight away from the critical hyperplane are
meromorphic functions in the positive half of Cartan subalgebra, their
singularities being at most simple poles at zeros of real roots. We obtain some
information about these singularities.


  The three-dimensional strongly screened vortex-glass model is studied
numerically using methods from combinatorial optimization. We focus on the
effect of disorder strength on the ground state and found the existence of a
disorder-driven normal-to-superconducting phase transition. The transition
turns out to be a geometrical phase transition with percolating vortex loops in
the ground state configuration. We determine the critical exponents and provide
evidence for a new universality class of correlated percolation.


  The simplex algorithm has been successfully used for many years in solving
linear programming (LP) problems. Due to the intensive computations required
(especially for the solution of large LP problems), parallel approaches have
also extensively been studied. The computational power provided by the modern
GPUs as well as the rapid development of multicore CPU systems have led OpenMP
and CUDA programming models to the top preferences during the last years.
However, the desired efficient collaboration between CPU and GPU through the
combined use of the above programming models is still considered a hard
research problem. In the above context, we demonstrate here an excessively
efficient implementation of standard simplex, targeting to the best possible
exploitation of the concurrent use of all the computing resources, on a
multicore platform with multiple CUDA-enabled GPUs. More concretely, we present
a novel hybrid collaboration scheme which is based on the concurrent execution
of suitably spread CPU-assigned (via multithreading) and GPU-offloaded
computations. The experimental results extracted through the cooperative use of
OpenMP and CUDA over a notably powerful modern hybrid platform (consisting of
32 cores and two high-spec GPUs, Titan Rtx and Rtx 2080Ti) highlight that the
performance of the presented here hybrid GPU/CPU collaboration scheme is
clearly superior to the GPU-only implementation under almost all conditions.
The corresponding measurements validate the value of using all resources
concurrently, even in the case of a multi-GPU configuration platform.
Furthermore, the given implementations are completely comparable (and slightly
superior in most cases) to other related attempts in the bibliography, and
clearly superior to the native CPU-implementation with 32 cores.


  We construct a faithful and conservative functor from prisms to
$C_{p^\infty}$-Tambara functors; in appropriate situations, this gives an
algebraic description of $\underline\pi_0{\mathrm{TC}^-}$. We also present two
integral variants using the generalized $n$-series of Devalapurkar-Misterka.
The construction is based on the "twisted $I$-adic" or "$(p^\bullet)_q$"
filtration, and is closely related to $q$-divided powers. To verify the axioms,
we introduce a new technique for constructing Tambara functors, inspired by
transversal prisms. We apply this to give a conceptual construction of
Molokov's de Rham-Witt comparison map, and generalize it to a triangle
sandwiching prismatic theory between theories built from Witt vectors and
adjunction of $p$-power roots.


  We critically review recent and earlier results on isotope effects in cuprate
superconductors and emphasize that the sample preparation and the isotope
exchange and back exchange are crucial in understanding and interpreting the
data. Only extremely careful preparation techniques yield reliable results and
permit differentiation between real isotope effects and marginal ones. The
former are substantial and highlight the lattice vibrational importance in
cuprate superconductors.


  This paper presents a contribution to the study of bibliographic corpora in
the context of science mapping. Starting from a graph representation of
documents and their textual dimension, we observe that stochastic block models
(SBMs) can provide a simultaneous clustering of documents and words that we
call a domain-topic model. Previous work by (Gerlach et al., 2018) investigated
the resulting topics, or word clusters, while ours focuses on the study of the
document clusters, which we call domains. To enable the synthetic description
and interactive navigation of domains, we introduce measures and interfaces
relating both types of clusters, which reflect the structure of the graph and
the model. We then present a procedure that, starting from the document
clusters, extends the block model to also cluster arbitrary metadata attributes
of the documents. We call this procedure a domain-chained model, and our
previous measures and interfaces can be directly transposed to read the
metadata clusters. We provide an example application to a corpus that is
relevant to current STS research, and an interesting case for our approach: the
1995-2017 collection of abstracts presented at ASCO, the main annual oncology
research conference. Through a sequence of domain-topic and domain-chained
models, we identify and describe a particular group of domains in ASCO that
have notably grown through the last decades, and which we relate to the
establishment of "oncopolicy" as a major concern in oncology.


  A relation between the Goldstein-Petrich hierarchy for plane curves and the
Toda lattice hierarchy is investigated. A representation formula for plane
curves is given in terms of a special class of $\tau$-functions of the Toda
lattice hierarchy. A representation formula for discretized plane curves is
also discussed.


  The Boussingesq equations was introduced in understanding the coupling nature
of the thermodynamics and the fluid dynamics. We show the existence of
continuous periodic weak solutions of the Boussinesq equations which satisfies
the prescribed kinetic energy or some other prescribed property. Our results
represent the conversions between internal energy and mechanical energy.


  The aim of the present paper is the study of some classes of real
hypersurfaces equipped with the condition \phi l = l \phi, (l = R(., \xi, \xi))


  We discuss the synthesis of some short-lived isotopes and of 23Na in
thermally pulsing AGB stars with initial mass of 2 Msun and two different
metallicities (Z=1.5e-2, corresponding to the metal amount in the Sun, and
Z=1e-4), representative of disk and halo stars, respectively. The different
nucleosynthesis channels are illustrated in some details. As previously found,
the 13C formed after each third dredge up episode is usually completely
consumed by alpha captures before the onset of the subsequent thermal pulse,
releasing neutrons. This is the most efficient neutron source in low mass AGB
stars and the resulting s-process nucleosynthesis is at the origin of the solar
main component. However, in the solar metallicity model, we find that the
temperature of the first formed 13C pocket remains too low during the
interpulse and the 13C is not completely burnt, being partially engulfed in the
convective zone generated by the following thermal pulse. Due to the rapid
convective mixing in this zone, the 13C is exposed to a larger temperature and
a nucleosynthesis characterized by a relatively high neutron density develops.
The main effect is the strong enhancement of isotopes located beyond some
critical branching in the neutron-capture path, like 60Fe, otherwise only
marginally produced during a standard s-process nucleosynthesis.


  It is argued that the initial cosmological singularity is isotropic in
spatially inhomogeneous brane-world models. This implies that brane cosmology
may naturally give rise to a set of initial data that provide the conditions
for inflation to subsequently take place, consequently offering a plausible
solution to the initial conditions problem in cosmology.


  In this paper, we compute the Lawson homology groups and Deligne-Beilinson
cohomology groups for Fulton-MacPherson configuration spaces. The explicit
formulas are given.


  The validation and parallel implementation of a numerical method for the
solution of the time-dependent Dirac equation is presented. This numerical
method is based on a split operator scheme where the space-time dependence is
computed in coordinate space using the method of characteristics. Thus, most of
the steps in the splitting are calculated exactly, making for a very efficient
and unconditionally stable method. We show that it is free from spurious
solutions related to the fermion-doubling problem and that it can be
parallelized very efficiently. We consider a few simple physical systems such
as the time evolution of Gaussian wave packets and the Klein paradox. The
numerical results obtained are compared to analytical formulas for the
validation of the method.


  Complex networks have been successfully used to describe the spread of
diseases in populations of interacting individuals. Conversely, pairwise
interactions are often not enough to characterize social contagion processes
such as opinion formation or the adoption of novelties, where complex
mechanisms of influence and reinforcement are at work. Here we introduce a
higher-order model of social contagion in which a social system is represented
by a simplicial complex and contagion can occur through interactions in groups
of different sizes. Numerical simulations of the model on both empirical and
synthetic simplicial complexes highlight the emergence of novel phenomena such
as a discontinuous transition induced by higher-order interactions. We show
analytically that the transition is discontinuous and that a bistable region
appears where healthy and endemic states co-exist. Our results help explain why
critical masses are required to initiate social changes and contribute to the
understanding of higher-order interactions in complex systems.


  Blockchain technology has revolutionized the financial landscape, with
cryptocurrencies gaining widespread adoption for their decentralized and
transparent nature. As the sentiment expressed on social media platforms can
significantly influence cryptocurrency discussions and market movements,
sentiment analysis has emerged as a crucial tool for understanding public
opinion and predicting market trends. Motivated by the aim to enhance sentiment
analysis accuracy in the cryptocurrency domain, this paper investigates
fine-tuning techniques on large language models. This paper also investigates
the efficacy of supervised fine-tuning and instruction-based fine-tuning on
large language models for unseen tasks. Experimental results demonstrate a
significant average zero-shot performance gain of 40% after fine-tuning,
highlighting the potential of this technique in optimizing pre-trained language
model efficiency. Additionally, the impact of instruction tuning on models of
varying scales is examined, revealing that larger models benefit from
instruction tuning, achieving the highest average accuracy score of 75.16%. In
contrast, smaller-scale models may experience reduced generalization due to the
complete utilization of model capacity. To gain deeper insight about how
instruction works with these language models, this paper presents an
experimental investigation into the response of an instruction-based model
under different instruction tuning setups. The investigation demonstrates that
the model achieves an average accuracy score of 72.38% for short and simple
instructions. This performance significantly outperforms its accuracy under
long and complex instructions by over 12%, thereby effectively highlighting the
profound significance of instruction characteristics in maximizing model
performance.


  Although the conductance of a closed Aharonov-Bohm interferometer, with a
quantum dot on one branch, obeys the Onsager symmetry under magnetic field
reversal, it needs not be a periodic function of this field: the conductance
maxima move with both the field and the gate voltage on the dot, in an apparent
breakdown of `phase rigidity'. These experimental findings are explained
theoretically as resulting from multiple electronic paths around the
interferometer ring. Data containing several Coulomb blockade peaks, whose
shapes change with the magnetic flux, are fitted to a simple model, in which
each resonant level on the dot couples to a different path around the ring.


  With recent advances in graphical user interfaces, more and more tasks on
computers have become easier to perform. Out of the belief that creating
computer programs can also be one of them, visual programming languages (VPLs)
have emerged. The goal of VPLs is to shift a part of work from the programmer
to the IDE so that the programmer can focus more on algorithm logic than the
syntax of the implementation programming language. In this article, the methods
required to build a VPL are presented, with an emphasis on a novel method of
code generation in a WHILE language. Also, the methods for achieving basic
principles of VPLs will be shown - suitable visual presentation of information
and guiding the programmer in the right direction using constraints. These
methods are demonstrated on an example of vIDE, a VPL based on the Eclipse
integrated development environment (IDE). The design of vIDE with respect to
the Eclipse Graphical Modeling Framework (GMF) is described. The concept of a
flowchart graphical notation is examined in contrast with the algorithm model
it maps to. Finally, the disambiguity of the model representation of an
algorithm is discussed and the methods for transforming it to an actual
implementation in a programming language.


  To automatically test web applications, crawling-based techniques are usually
adopted to mine the behavior models, explore the state spaces or detect the
violated invariants of the applications. However, in existing crawlers, rules
for identifying the topics of input text fields, such as login ids, passwords,
emails, dates and phone numbers, have to be manually configured. Moreover, the
rules for one application are very often not suitable for another. In addition,
when several rules conflict and match an input text field to more than one
topics, it can be difficult to determine which rule suggests a better match.
This paper presents a natural-language approach to automatically identify the
topics of encountered input fields during crawling by semantically comparing
their similarities with the input fields in labeled corpus. In our evaluation
with 100 real-world forms, the proposed approach demonstrated comparable
performance to the rule-based one. Our experiments also show that the accuracy
of the rule-based approach can be improved by up to 19% when integrated with
our approach.


  We show that a straightforward extension of a simple learning model based on
the Hebb rule, the previously introduced Association-Reinforcement-Hebb-Rule,
can cope with "delayed", unspecific reinforcement also in the case of
structured data and lead to perfect generalization.


  Pattern forming instabilities induced by ultralow frequency sinusoidal
voltages were studied in a rod-like nematic liquid crystal by microscopic
observations and simultaneous electric current measurements. Two pattern
morphologies, electroconvection (EC) and flexodomains (FD), were distinguished;
both appearing as time separated flashes within each half period of driving. A
correlation was found between the time instants of the EC flashes and that of
the nonlinear current response. The voltage dependence of the pattern contrast
C(U) for EC has a different character than that for the FD. The flattening of
C(U) at reducing the frequency was described in terms of an imperfect
bifurcation model. Analysing the threshold characteristics of FD the
temperature dependence of the difference |e_1-e_3| of the flexoelectric
coefficients were also determined by considering elastic anisotropy.


  The trie-based radix sort algorithm stores pairwise different infinite binary
strings in the leaves of a binary tree in a way that the Ulam-Harris coding of
each leaf equals a prefix (that is, an initial segment) of the corresponding
string, with the prefixes being of minimal length so that they are pairwise
different. We investigate the {\em radix sort tree chains} -- the tree-valued
Markov chains that arise when successively storing infinite binary strings
$Z_1,\ldots, Z_n$, $n=1,2,\ldots$ according to the trie-based radix sort
algorithm, where the source strings $Z_1, Z_2,\ldots$ are independent and
identically distributed. We establish a bijective correspondence between the
full Doob--Martin boundary of the radix sort tree chain with a {\em symmetric
Bernoulli source} (that is, each $Z_k$ is a fair coin-tossing sequence) and the
family of radix sort tree chains for which the common distribution of the $Z_k$
is a diffuse probability measure on $\{0,1\}^\infty$. In essence, our result
characterizes all the ways that it is possible to condition such a chain of
radix sort trees consistently on its behavior "in the large".


  A less complex and more straightforward program is a crucial factor that
enhances its maintainability and makes writing secure and bug-free programs
easier. However, due to its heavy workload and the risks of breaking the
working programs, programmers are reluctant to do code refactoring, and thus,
it also causes the loss of potential learning experiences. To mitigate this, we
demonstrate the application of using a large language model (LLM), GPT-3.5, to
suggest less complex versions of the user-written Python program, aiming to
encourage users to learn how to write better programs. We propose a method to
leverage the prompting with few-shot examples of the LLM by selecting the
best-suited code refactoring examples for each target programming problem based
on the prior evaluation of prompting with the one-shot example. The
quantitative evaluation shows that 95.68% of programs can be refactored by
generating 10 candidates each, resulting in a 17.35% reduction in the average
cyclomatic complexity and a 25.84% decrease in the average number of lines
after filtering only generated programs that are semantically correct.
Furthermore, the qualitative evaluation shows outstanding capability in code
formatting, while unnecessary behaviors such as deleting or translating
comments are also observed.


  We show that when $d \geq 3$ and $m>2$, the Nef cone of the Hilbert scheme
$Hilb_{P_{d,m}(T)}(G(k,n))$ is a cone spanned by 6 classes in general case,
where $P_{d,m}(T)=\binom{T+m}{m}-\binom{T+m-d}{m}$.


  In this report we have pointed out that magnetic hysteresis loop can be used
as a probe to distinguish a single layer from a many layer graphitic structure.
Chemically we have synthesized graphitic oxide (GO) and reduced graphitic oxide
(RGO) for this investigation. We observe ferromagnetic like hysteresis loops
for both GO and RGO below a certain applied critical magnetic field and above
this critical field we observe cross-over of the positive magnetization to
negative magnetization leading to diamagnetic behaviour. This cross-over is
more dominant for the case of many layer graphitic structure. Upon annealing of
GO in air the critical cross-over field decreases and the magnetization
increases for multilayer graphitic structure. Possible reasons for all these
observations and phenomena is presented here.


  We study coupled dynamics on networks using symbolic dynamics. The symbolic
dynamics is defined by dividing the state space into a small number of regions
(typically 2), and considering the relative frequencies of the transitions
between those regions. It turns out that the global qualitative properties of
the coupled dynamics can be classified into three different phases based on the
synchronization of the variables and the homogeneity of the symbolic dynamics.
Of particular interest is the {\it homogeneous unsynchronized phase} where the
coupled dynamics is in a chaotic unsynchronized state, but exhibits (almost)
identical symbolic dynamics at all the nodes in the network. We refer to this
dynamical behaviour as {\it symbolic synchronization}. In this phase, the local
symbolic dynamics of any arbitrarily selected node reflects global properties
of the coupled dynamics, such as qualitative behaviour of the largest Lyapunov
exponent and phase synchronization. This phase depends mainly on the network
architecture, and only to a smaller extent on the local chaotic dynamical
function. We present results for two model dynamics, iterations of the
one-dimensional logistic map and the two-dimensional H\'enon map, as local
dynamical function.


  Here we discuss $r-$shake slice knots, and their relation to corks, we then
prove that $0$-shake slice knots are slice.


  The 1-D theory of flow in the arteries yields an equation for the wave speed
in terms of the density of blood and the distensibility of the vessel. By means
of this equation there is a duality between the equation for the wave speed and
the tube law describing the area of the vessel as a function of pressure. We
explore this duality for the equations for wave speed and tube laws that are
most commonly used in theoretical arterial hemodynamics. We see that there are
qualitative differences between these laws and the experimental data on wave
speed in canine arteries measured by Anliker and his colleagues 50 years ago.
We suggest an empirical equation for wave speed (and its dual tube law) that
fits the experimental data as well as the common expectation that arteries
become stiffer as the pressure increases. We conclude with a cautionary
historical tale about the differences between the theoretical predictions and
the experimental measurements of the speed of sound in air that persisted for
more than 200 years.


  The problem of finding a formulation of Noether's theorem in noncommutative
geometry is very important in order to obtain conserved currents and charges
for particles in noncommutative spacetimes. In this paper, we formulate
Noether's theorem for translations of kappa-Minkowski noncommutative spacetime
on the basis of the 5-dimensional kappa-Poincare' covariant differential
calculus. We focus our analysis on the simple case of free scalar theory. We
obtain five conserved Noether currents, which give rise to five energy-momentum
charges. By applying our result to plane waves it follows that the
energy-momentum charges satisfy a special-relativity dispersion relation with a
generalized mass given by the fifth charge. In this paper we provide also a
rigorous derivation of the equation of motion from Hamilton's principle in
noncommutative spacetime, which is necessary for the Noether analysis.


  Linear residualization is a common practice for confounding adjustment in
machine learning (ML) applications. Recently, causality-aware predictive
modeling has been proposed as an alternative causality-inspired approach for
adjusting for confounders. The basic idea is to simulate counterfactual data
that is free from the spurious associations generated by the observed
confounders. In this paper, we compare the linear residualization approach
against the causality-aware confounding adjustment in anticausal prediction
tasks, and show that the causality-aware approach tends to (asymptotically)
outperform the residualization adjustment in terms of predictive performance in
linear learners. Importantly, our results still holds even when the true model
is not linear. We illustrate our results in both regression and classification
tasks, where we compared the causality-aware and residualization approaches
using mean squared errors and classification accuracy in synthetic data
experiments where the linear regression model is mispecified, as well as, when
the linear model is correctly specified. Furthermore, we illustrate how the
causality-aware approach is more stable than residualization with respect to
dataset shifts in the joint distribution of the confounders and outcome
variables.


  Prompt engineering is an increasingly important skill set needed to converse
effectively with large language models (LLMs), such as ChatGPT. Prompts are
instructions given to an LLM to enforce rules, automate processes, and ensure
specific qualities (and quantities) of generated output. Prompts are also a
form of programming that can customize the outputs and interactions with an
LLM. This paper describes a catalog of prompt engineering techniques presented
in pattern form that have been applied to solve common problems when conversing
with LLMs. Prompt patterns are a knowledge transfer method analogous to
software patterns since they provide reusable solutions to common problems
faced in a particular context, i.e., output generation and interaction when
working with LLMs. This paper provides the following contributions to research
on prompt engineering that apply LLMs to automate software development tasks.
First, it provides a framework for documenting patterns for structuring prompts
to solve a range of problems so that they can be adapted to different domains.
Second, it presents a catalog of patterns that have been applied successfully
to improve the outputs of LLM conversations. Third, it explains how prompts can
be built from multiple patterns and illustrates prompt patterns that benefit
from combination with other prompt patterns.


  Monopole bubbling effect is screening of magnetic charges of singular Dirac
monopoles by regular 't Hooft-Polyakov monopoles. We study properties of weak
coupling perturbative series in the presence of monopole bubbling effects as
well as instantons. For this purpose, we analyze supersymmetric 't Hooft loop
in four dimensional $\mathcal{N}=2$ supersymmetric gauge theories with
Lagrangians and non-positive beta functions. We show that the perturbative
series of the 't Hooft loop is Borel summable along positive real axis for
fixed instanton numbers and screened magnetic charges. It turns out that the
exact result of the 't Hooft loop is the same as the sum of the Borel
resummations over instanton numbers and effective magnetic charges. We also
obtain the same result for supersymmetric dyonic loops.


  In this paper, we study the relativistic correction to Bekenstein-Hawking
entropy in the canonical ensemble and isothermal-isobaric ensemble and apply it
to the cases of non-rotating BTZ and AdS-Schwarzschild black holes. This is
realized by generalizing the equations obtained using Boltzmann-Gibbs(BG)
statistics with its relativistic generalization, Kaniadakis statistics, or
$\kappa$-statistics. The relativistic corrections are found to be logarithmic
in nature and it is observed that their effect becomes appreciable in the
high-temperature limit suggesting that the entropy corrections must include
these relativistically corrected terms while taking the aforementioned limit.
The non-relativistic corrections are recovered in the $\kappa\rightarrow 0$
limit.


  The properties of infinite matter and finite nuclei are studied by using the
chiral sigma model in the framework of the relativistic mean field theory. We
reconstruct an extended chiral sigma model in which the omega meson mass is
generated dynamically by the sigma condensation in the vacuum in the same way
as the nucleon mass. All the parameters of chiral sigma model are essentially
fixed from the hadron properties in the free space. In nuclear matter, the
saturation property comes out right, but the incompressibility is too large and
the scalar and vector potentials are about a half of the phenomenological ones,
respectively. This fact is reflected to the properties of finite nuclei. We
calculate N = Z even-even mass nuclei between N = 16 and N = 34. The extended
chiral sigma model without the pion mean field leads to the result that the
magic number appears at N = 18 instead of N = 20 and the magic number does not
appear at N = 28 due to the above mentioned nuclear matter properties. The
latter problem, however, could be removed by the introduction of the finite
pion mean field with the appearance of the magic number at N = 28. We find that
the energy differences between the spin-orbit partners are reproduced by the
finite pion mean field which is completely a different mechanism from the
standard spin-orbit interaction.


  We give an update of our ongoing survey for intracluster light (ICL), in a
sample of distant Abell clusters. We find that the amount of intracluster
starlight is comparable to that seen in nearby clusters, and that tidal debris
appears to be common.


  Any kind of quantum resource useful in different information processing tasks
is vulnerable to several types of environmental noise. Here we study the
behaviour of quantum correlations such as entanglement and steering in
two-qubit systems under the application of the generalised amplitude damping
channel and propose some protocols towards preserving them under this type of
noise. First, we employ the technique of weak measurement and reversal for the
purpose of preservation of correlations. We then show how the evolution under
the channel action can be seen as an unitary process. We use the technique of
weak measurement and most general form of selective positive operator valued
measure (POVM) to achieve preservation of correlations for a significantly
large range of parameter values.


  Today's software stacks for autonomous vehicles rely on HD maps to enable
sufficient localization, accurate path planning, and reliable motion
prediction. Recent developments have resulted in pipelines for the automated
generation of HD maps to reduce manual efforts for creating and updating these
HD maps. We present FlexMap Fusion, a methodology to automatically update and
enhance existing HD vector maps using OpenStreetMap. Our approach is designed
to enable the use of HD maps created from LiDAR and camera data within
Autoware. The pipeline provides different functionalities: It provides the
possibility to georeference both the point cloud map and the vector map using
an RTK-corrected GNSS signal. Moreover, missing semantic attributes can be
conflated from OpenStreetMap into the vector map. Differences between the HD
map and OpenStreetMap are visualized for manual refinement by the user. In
general, our findings indicate that our approach leads to reduced human labor
during HD map generation, increases the scalability of the mapping pipeline,
and improves the completeness and usability of the maps. The methodological
choices may have resulted in limitations that arise especially at complex
street structures, e.g., traffic islands. Therefore, more research is necessary
to create efficient preprocessing algorithms and advancements in the dynamic
adjustment of matching parameters. In order to build upon our work, our source
code is available at https://github.com/TUMFTM/FlexMap_Fusion.


  We present predictions for proton skins based on isospin-asymmetric equations
of state derived microscopically from high-precision chiral few-nucleon
interactions. Moreover, we investigate the relation between the neutron skin of
a nucleus and the difference between the proton radii of the corresponding
mirror nuclei.


  The low-lying eigenstates of a one-dimensional (1D) system of many
impenetrable point bosons and one moving impurity particle with repulsive
zero-range impurity-boson interaction are found for all values of the
impurity-boson mass ratio and coupling constant. The moving entity is a
polaron-like composite object consisting of the impurity clothed by a co-moving
gray soliton. The special case with impurity-boson interaction of point
hard-core form and impurity-boson mass ratio $m_i/m$ unity is first solved
exactly as a special case of a previous Fermi-Bose (FB) mapping treatment of
soluble 1D Bose-Fermi mixture problems. Then a more general treatment is given
using second quantization for the bosons and the second-quantized form of the
FB mapping, eliminating the impurity degrees of freedom by a Lee-Low-Pines
canonical transformation. This yields the exact solution for arbitrary $m_i/m$
and impurity-boson interaction strength.