  This paper proposes a preliminary work on a Conditional Task and Motion
Planning algorithm able to find a plan that minimizes robot efforts while
solving assigned tasks. Unlike most of the existing approaches that replan a
path only when it becomes unfeasible (e.g., no collision-free paths exist), the
proposed algorithm takes into consideration a replanning procedure whenever an
effort-saving is possible. The effort is here considered as the execution time,
but it is extensible to the robot energy consumption. The computed plan is both
conditional and dynamically adaptable to the unexpected environmental changes.
Based on the theoretical analysis of the algorithm, authors expect their
proposal to be complete and scalable. In progress experiments aim to prove this
investigation.


  An edge clique cover of a graph is a set of cliques that covers all edges of
the graph. We generalize this concept to "$K_t$ clique cover", i.e. a set of
cliques that covers all complete subgraphs on $t$ vertices of the graph, for
every $t \geq 1$. In particular, we extend a classical result of Erd\"os,
Goodman, and P\'osa (1966) on the edge clique cover number ($t = 2$), also
known as the intersection number, to the case $t = 3$. The upper bound is
tight, with equality holding only for the Tur\'an graph $T(n,3)$. We also
extend an algorithm of Scheinerman and Trenk (1999) to solve a weighted version
of the $K_t$ clique cover problem on a superclass of chordal graphs. We also
prove that the $K_t$ clique cover problem is NP-hard.


  We generalise the dynamic Laplacian introduced in (Froyland, 2015) to a
dynamic $p$-Laplacian, in analogy to the generalisation of the standard
$2$-Laplacian to the standard $p$-Laplacian for $p>1$. Spectral properties of
the dynamic Laplacian are connected to the geometric problem of finding
"coherent" sets with persistently small boundaries under dynamical evolution,
and we show that the dynamic $p$-Laplacian shares similar geometric
connections. In particular, we prove that the first eigenvalue of the dynamic
$p$-Laplacian with Dirichlet boundary conditions exists and converges to a
dynamic version of the Cheeger constant introduced in (Froyland, 2015) as
$p\rightarrow 1$. We develop a numerical scheme to estimate the leading
eigenfunctions of the (nonlinear) dynamic $p$-Laplacian, and through a series
of examples we investigate the behaviour of the level sets of these
eigenfunctions. These level sets define the boundaries of sets in the domain of
the dynamics that remain coherent under the dynamical evolution.


  We derive a formula predicting dynamical tunneling rates from regular states
to the chaotic sea in systems with a mixed phase space. Our approach is based
on the introduction of a fictitious integrable system that resembles the
regular dynamics within the island. For the standard map and other kicked
systems we find agreement with numerical results for all regular states in a
regime where resonance-assisted tunneling is not relevant.


  We study a structured linear program (LP) that emerges in the need of ranking
candidates or items in personalized recommender systems. Since the candidate
set is only known in real time, the LP also needs to be formed and solved in
real time. Latency and user experience are major considerations, requiring the
LP to be solved within just a few milliseconds. Although typical instances of
the problem are not very large in size, this stringent time limit appears to be
beyond the capability of most existing (commercial) LP solvers, which can take
$20$ milliseconds or more to find a solution. Thus, reliable methods that
address the real-world complication of latency become necessary. In this paper,
we propose a fast specialized LP solver for a structured problem with diversity
constraints. Our method solves the dual problem, making use of the piece-wise
affine structure of the dual objective function, with an additional screening
technique that helps reduce the dimensionality of the problem as the algorithm
progresses. Experiments reveal that our method can solve the problem within
roughly 1 millisecond, yielding a 20x improvement in speed over efficient
off-the-shelf LP solvers. This speed-up can help improve the quality of
recommendations without affecting user experience, highlighting how
optimization can provide solid orthogonal value to machine-learned recommender
systems.


  Generating novel and useful concepts is essential during the early design
stage to explore a large variety of design opportunities, which usually
requires advanced design thinking ability and a wide range of knowledge from
designers. Growing works on computer-aided tools have explored the retrieval of
knowledge and heuristics from design data. However, they only provide stimuli
to inspire designers from limited aspects. This study explores the recent
advance of the natural language generation (NLG) technique in the artificial
intelligence (AI) field to automate the early-stage design concept generation.
Specifically, a novel approach utilizing the generative pre-trained transformer
(GPT) is proposed to leverage the knowledge and reasoning from textual data and
transform them into new concepts in understandable language. Three concept
generation tasks are defined to leverage different knowledge and reasoning:
domain knowledge synthesis, problem-driven synthesis, and analogy-driven
synthesis. The experiments with both human and data-driven evaluation show good
performance in generating novel and useful concepts.


  To improve the quality of experience (QoE), especially under moderate to high
traffic demand, it is important to understand the impact of the network and
application QoS on user experience. This paper comparatively evaluates the
impact of impairments, their intensity and temporal dynamics, on user
engagement in the context of video streaming. The analysis employed two large
YouTube datasets. To characterize the user engagement and the impact of
impairments, several new metrics were defined. We assessed whether or not there
is a statistically significant relationship between different types of
impairments and QoE and user engagement metrics, taking into account not only
the characteristics of the impairments but also the covariates of the session
(e.g., video duration, mean datarate). After observing the relationships across
the entire dataset, we tested whether these relationships also persist under
specific conditions with respect to the covariates. The introduction of several
new metrics and of various covariates in the analysis are two innovative
aspects of this work. We found that the number of negative bitrate changes
(BR-) is a stronger predictor of abandonment than rebufferrings (RB). Even
positive bitrate changes (BR+) are associated with increases in abandonment.
Specifically, BR+ in low resolution sessions is not well received. Temporal
dynamics of the impairments have also an impact: a BR- that follows much later
a RB appears to be perceived as a worse impairment than a BR- that occurs
immediately after a RB. These results can be used to guide the design of the
video streaming adaptation as well as suggest which parameters should be varied
in controlled field studies.


  We present some results on (co)limits of diagrams in $\infty$-categories, as
well as those in $(n, 1)$-categories. In particular, we deduce a way to reshape
colimit diagrams into simplicial ones, and a characterisations of
$n$-cofinality for functor between $\infty$-categories. Some basics on
$n$-siftedness are also briefly treated.


  In this paper, we investigate scalar-induced gravitational waves (GWs)
generated in the post-inflationary universe to infer new limits on warm
inflation. We specifically examine the evolution of primordial GWs produced by
scalar perturbations produced during the radiation-dominated epoch. For this
purpose, we assume a weak regime of warm inflation under the slow-roll
approximation, with a dissipation coefficient linearly dependent on the
temperature of the radiation bath. We then derive analytical expressions for
the curvature power spectrum and the scalar index, in the cases of chaotic and
exponential potentials of the inflationary field. Subsequently, we compare the
theoretical predictions regarding the relic energy density of GWs with the
stochastic GW background signal recently detected by the NANOGrav collaboration
through the use of pulsar timing array measurements. In so doing, we obtain
numerical constraints on the free parameters of the inflationary models under
study. Finally, we conduct a model selection analysis through the Bayesian
inference method to measure the statistical performance of the different
theoretical scenarios.


  We discuss the possibility of a direct access to transversity distributions
by measuring the double transverse spin asymmetry A_TT in p pbar --> J/Psi + X
--> l^- l^+ + X processes at future GSI-HESR experiments with polarized protons
and anti-protons. In the J/Psi resonance production region, with 30 < s < 45
GeV^2, both the cross-section and A_TT are expected to be sufficiently large to
allow a measurement of h_1^q(x,M^2); numerical estimates are given.


  The crystallographic, magnetic and thermal properties of BiMn2PO6 and
BiZn2PO6 were investigated by x-ray diffraction, magnetic susceptibility \chi,
heat capacity Cp, and 31P NMR measurements as well as by density-functional
band-theory calculations. Both compounds show a strong monotonic lattice
softening on cooling, where the Debye temperature decreases by a factor of two
from \Theta_D=650K at T=300K to \Theta_D=300K at T=2K. The \chi(T) data for
BiMn2PO6 above 150K follow a Curie-Weiss law with a Curie constant consistent
with a S=5/2 with g=2 and an antiferromagnetic (AFM) Weiss temperature
\theta_CW= -78K. The \chi data indicate long-range AFM ordering below TN=30K,
confirmed by a sharp lambda-type peak in Cp(T) at 28.8K. The band-theory
calculations indicate that BiMn2PO6 is an AFM compound with dominant
interactions J1/kB= 6.7K and J3/kB= 5.6K along the legs and rungs of a two-leg
spin-ladder, respectively. In addition to the long-range AFM ordering at
TN=30K, a second transition at 10 K is observed from the \chi and NMR
measurements but is not evident in the Cp data. The Cp data at low T suggest a
significant contribution from AFM spin waves moving in three dimensions and the
absence of a spin-wave gap. A detailed analysis of the NMR spectra indicates
commensurate magnetic order between 10K and 30K and a possible incommensurate
modulation and/or spin canting below 10K. The commensurate order is consistent
with microscopic simulations that yield a collinear Neel-type AFM spin
arrangement both within and between the ladders, despite the presence of
multiple weak interactions frustrating this magnetic structure. Frustration for
AFM ordering and 1D spatial anisotropy of the 3D spin interactions are
manifested in the frustration ratio f=|{\theta}CW|/TN=2.6, indicating a
suppression of TN from 68K in the absence of these effects to 30K in BiMn2PO6.


  In this paper we discuss the basic properties of a discrete distribution
introduced by Harris in 1948 and obtain a characterization of it. The
divisibility properties of the distribution are also studied. We derive the
moment and maximum likelihood estimators for both the parameters and verify
them by simulated observations.


  In [Steinerberger, Q. Appl. Math., 79:3, 419-429, 2021] and [Shao, SIAM J.
Matrix Anal. Appl. 44(1), 212-239, 2023], two new types of Kaczmarz algorithms,
which share some similarities, for consistent linear systems were proposed.
These two algorithms not only compete with many previous Kaczmarz algorithms
but, more importantly, reveal some interesting new geometric properties of
solutions to linear systems that are not obvious from the standard viewpoint of
the Kaczmarz algorithm. In this paper, we comprehensively study these two
algorithms. First, we theoretically analyse the algorithms given in
[Steinerberger, Q. Appl. Math., 79:3, 419-429, 2021] for solving least squares.
Second, we extend the two algorithms to block versions and provide their
theoretical convergence rates. Our numerical experiments also verify the
efficiency of these algorithms. Third, as a theoretical complement, we address
some key questions left unanswered in [Shao, SIAM J. Matrix Anal. Appl. 44(1),
212-239, 2023].


  The static second hyperpolarizability is derived from the space-fractional
Schr\"{o}dinger equation in the particle-centric view. The Thomas-Reiche-Kuhn
sum rule matrix elements and the three-level ansatz determines the maximum
second hyperpolarizability for a space-fractional quantum system. The total
oscillator strength is shown to decrease as the space-fractional parameter
$\alpha$ decreases, which reduces the optical response of a quantum system in
the presence of an external field. This damped response is caused by the
wavefunction dependent position and momentum commutation relation. Although the
maximum response is damped, we show that the one-dimensional quantum harmonic
oscillator is no longer a linear system for $\alpha \neq 1$, where the second
hyperpolarizability becomes negative before ultimately damping to zero at the
lower fractional limit of $\alpha \rightarrow 1/2$.


  The temperature dependence of ultrafast photoinduced reflectivity transients
is reported in Nd$_{0.5}$Sr$_{0.5}$MnO$_{3}$ thin film. The photoinduced
reflectivity shows a complex response with very different temperature
dependences on different timescales. The response on the sub-ps timescale
appears to be only weakly sensitive to the 270K-metal-insulator phase
transition. Below $\sim 160$ K the sub-ps response displays a two component
behavior indicating inhomogeneity of the film resulting from the substrate
induced strain. On the other hand, the slower response on the 10-100 ps
timescale is sensitive only to the metal-insulator phase transition and is in
agreement with some previously published results. The difference in the
temperature dependences of the responses on nanosecond and $\mu $s timescales
indicates that thermal equilibrium between the different degrees of fredom is
established relatively slowly - on a nanosecond timescale.


  We review some of the recent developments which have enabled the heavy quark
mass to be incorporated into both the calculation of the hard-scattering cross
section and the PDFs. We compare and contrast some of the schemes that have
been used in recent global PDF analyses, and look at issues that arise when
these calculations are extended to NNLO.


  The nonthermal filaments in the Galactic Center constitute one of the great
mysteries of this region of the Galaxy. We summarise the observational data on
these filaments and critically review the various theories which currently
outnumber the observed filaments. We summarise out theory for the longest of
these filaments, the Snake, and discuss the relevance of this model for the
other filaments in the Galactic Center region. The physics involved in our
model for the Snake involves much of the physics that has dominated the career
of Professor Don Melrose. In particular, the diffusion of relativistic
electrons in the Snake is determined from the theory of resonant scattering by
Alfv\'en waves.


  To leading order in displacement size, the scattering of electrons in a Cu-O
plane from O displacements perpendicular to that plane is due to spin-orbit
coupling. This scattering is investigated with the following results: (1) As a
consequence of time-reversal symmetry, spin fluctuations, which can strongly
enhance scattering from a spin impurity, do not enhance spin-orbit scattering;
and (2) for a superconductor with a $d_{x^2-y^2}$ gap function, pair-breaking
from spin-orbit scattering can be strong, particularly in a structurally
disordered phase in which locally CuO$_6$ octahedra tilt as in the orthorhombic
phase of La$_2$CuO$_4$, but globally the average structure is tetragonal. These
results are discussed in the context of the (La,Nd)-(Sr,Ba)-Cu-O system where
certain structural transitions are observed to suppress superconductivity.


  We present a exactly soluble model for financial time series that mimics the
long range volatility correlations known to be present in financial data.
Although our model is `monofractal' by construction, it shows apparent
multiscaling as a result of a slow crossover phenomenon on finite time scales.
Our results suggest that it might be hard to distinguish apparent and true
multifractal behavior in financial data. Our model also leads to a new family
of stable laws for sums of correlated random variables.


  In molecular electronic conduction, exotic lattice morphologies often give
rise to exotic behaviors. Among 2D systems, graphene is a notable example.
Recently, a stable amorphous version of graphene called Monolayer Amorphous
Carbon (MAC) was synthesized. MAC poses a new set of questions regarding the
effects of disorder on conduction. In this Letter, we perform ensemble-level
computational analysis of the coherent electronic transmission through MAC
nano-fragments in search of defining characteristics. Our analysis, relying on
a semi-empirical Hamiltonian (Pariser-Parr-Pople) and Landauer theory, showed
that states near the Fermi energy ($E_F$) in MAC inherit partial
characteristics of analogous surface states in graphene nano-fragments. Away
from $E_F$, current is carried by a set of delocalized states which transition
into a subset of insulating interior states at the band edges. Finally, we also
found that quantum interference between the frontier orbitals is a common
feature among MAC nano-fragments.


  Very recently, a new graphene-like crystalline, hole-free, 2D-single-layer
carbon nitride C3N, has been fabricated by polymerization of
2,3-diaminophenazine and used to fabricate a field-effect transistor device
with an on-off current ratio reaching (Adv. Mater. 2017, 1605625). Heat
dissipation plays a vital role in its practical applications, and therefore the
thermal transport properties need to be explored urgently. In this paper, we
perform first-principles calculations combined with phonon Boltzmann transport
equation to investigate the phononic thermal transport properties of monolayer
C3N, and meanwhile, a comparison with graphene is given. Our calculated
intrinsic lattice thermal conductivity of C3N is 380 W/mK at room temperature,
which is one order of magnitude lower than that of graphene (3550 W/mK at 300
K), but is greatly higher than many other typical 2D materials. The underlying
mechanisms governing the thermal transport were thoroughly discussed and
compared to graphene, including group velocities, phonon relax time, the
contribution from phonon branches, phonon anharmonicity and size effect. The
fundamental physics understood from this study may shed light on further
studies of the newly fabricated 2D crystalline C3N sheets.


  Let $S_{g,p}$ denote the genus $g$ orientable surface with $p$ punctures. We
show that nested train track sequences constitute $O((g,p)^{2})$-quasiconvex
subsets of the curve graph, effectivizing a theorem of Masur and Minsky. As a
consequence, the genus $g$ disk set is $O(g^{2})$-quasiconvex. We also show
that splitting and sliding sequences of birecurrent train tracks project to
$O((g,p)^{2})$-unparameterized quasi-geodesics in the curve graph of any
essential subsurface, an effective version of a theorem of Masur, Mosher, and
Schleimer.


  It is well-known that the canonical commutation relation $[x,p]=i$ can be
realized only on an infinite-dimensional Hilbert space. While any finite set of
experimental data can also be explained in terms of a finite-dimensional
Hilbert space by approximating the commutation relation, Occam's razor prefers
the infinite-dimensional model in which $[x,p]=i$ holds on the nose. This
reasoning one will necessarily have to make in any approach which tries to
detect the infinite-dimensionality. One drawback of using the canonical
commutation relation for this purpose is that it has unclear operational
meaning. Here, we identify an operationally well-defined context from which an
analogous conclusion can be drawn: if two unitary transformations $U,V$ on a
quantum system satisfy the relation $V^{-1}U^2V=U^3$, then
finite-dimensionality entails the relation $UV^{-1}UV=V^{-1}UVU$; this
implication strongly fails in some infinite-dimensional realizations. This is a
result from combinatorial group theory for which we give a new proof. This
proof adapts to the consideration of cases where the assumed relation
$V^{-1}U^2V=U^3$ holds only up to $\eps$ and then yields a lower bound on the
dimension.


  Dialogue state tracking (DST) aims to record user queries and goals during a
conversational interaction achieved by maintaining a predefined set of slots
and their corresponding values. Current approaches decide slot values opaquely,
while humans usually adopt a more deliberate approach by collecting information
from relevant dialogue turns and then reasoning the appropriate values. In this
work, we focus on the steps needed to figure out slot values by proposing a
model named Chain-of-Thought-Explanation (CoTE) for the DST task. CoTE, which
is built on the generative DST framework, is designed to create detailed
explanations step by step after determining the slot values. This process leads
to more accurate and reliable slot values. More-over, to improve the reasoning
ability of the CoTE, we further construct more fluent and high-quality
explanations with automatic paraphrasing, leading the method CoTE-refined.
Experimental results on three widely recognized DST benchmarks-MultiWOZ 2.2,
WoZ 2.0, and M2M-demonstrate the remarkable effectiveness of the CoTE.
Furthermore, through a meticulous fine-grained analysis, we observe significant
benefits of our CoTE on samples characterized by longer dialogue turns, user
responses, and reasoning steps.


  For the moduli stack $\mathcal{M}_{g,n/\mathbb{F}_p}$ of smooth curves over
$\text{Spec}~\mathbb{F}_p$ with the function field $K$, we show that if
$g\geq3$, then the only $K$-rational points of the generic curve over $K$ are
its $n$ tautological points. Furthermore, we show that if $g\geq4$ and $n=0$,
then Grothendieck's Section Conjecture holds for the generic curve over $K$.
This is an extension of Hain's work in characteristic $0$ to positive
characteristics.


  The 3x+1 Conjecture asserts that the T-orbit of every positive integer
contains 1, where T maps x\mapsto x/2 for x even and x\mapsto (3x+1)/2 for x
odd. A set S of positive integers is sufficient if the orbit of each positive
integer intersects the orbit of some member of S. In a previous paper it was
shown that every arithmetic sequence is sufficient.
  In this paper we further investigate the concept of sufficiency. We construct
sufficient sets of arbitrarily low asymptotic density in the natural numbers.
We determine the structure of the groups generated by the maps x\mapsto x/2 and
x\mapsto (3x+1)/2 modulo b for b relatively prime to 6, and study the action of
these groups on the directed graph associated to the 3x+1 dynamical system.
From this we obtain information about the distribution of arithmetic sequences
and obtain surprising new results about certain arithmetic sequences. For
example, we show that the forward T-orbit of every positive integer contains an
element congruent to 2 mod 9, and every non-trivial cycle and divergent orbit
contains an element congruent to 20 mod 27. We generalize these results to find
many other sets that are strongly sufficient in this way.
  Finally, we show that the 3x+1 digraph exhibits a surprising and beautiful
self-duality modulo 2^n for any n, and prove that it does not have this
property for any other modulus. We then use deeper previous results to
construct additional families of nontrivial strongly sufficient sets by showing
that for any k<n, one can "fold" the digraph modulo 2^n onto the digraph modulo
2^k in a natural way.


  Mainstream knowledge management researchers generally agree that knowledge
extracted from unstructured data and semi-structured data have become
imperative for organizational strategic decision making. In this research, we
develop a framework that captures and analyses unstructured data using machine
learning techniques and integrates knowledge and insight gained from the data
into traditional knowledge management systems. Unlike most frameworks published
in the literature that focuses on a specific type of unstructured data, our
frameworks cut across the varieties of unstructured data ranging from textual
data from social network sites, online forums, discussion boards, reviews to
audio data, image data and video data. We highlight some pre-processing and
processing techniques for these data and also highlight some standard output.
We evaluate the framework by developing a textual data application programming
interface (API) using python and beautiful soup and we perform sentiment
analysis on the students review data collected through the API.


  Several algorithms for similarity search employ seeding techniques to quickly
discard very dissimilar regions. In this paper, we study theoretical properties
of lossless seeds, i.e., spaced seeds having full sensitivity. We prove that
lossless seeds coincide with languages of certain sofic subshifts, hence they
can be recognized by finite automata. Moreover, we show that these subshifts
are fully given by the number of allowed errors k and the seed margin l. We
also show that for a fixed k, optimal seeds must asymptotically satisfy l ~
m^(k/(k+1)).


  Unpulsed, high-energy emission from pulsar binaries can be attributed to the
interaction of a pulsar wind with that of a companion star. At the shock
between the outflows, particles carried away from the pulsar magnetosphere are
accelerated and radiate both in synchrotron and inverse Compton processes. This
emission constitutes a significant fraction of the pulsar spin-down luminosity.
It is not clear however, how the highly magnetized pulsar wind could convert
its mainly electromagnetic energy into the particles with such high efficiency.
Here we investigate a scenario in which a pulsar striped wind converts into a
strong electromagnetic wave before reaching the shock. This mode can be thought
of as a shock precursor that is able to accelerate particles to
ultrarelativistic energies at the expense of the electromagnetic energy it
carries. Radiation of the particles leads to damping of the wave. The
efficiency of this process depends on the physical conditions imposed by the
external medium. Two regimes can be distinguished: a high density one, where
the EM wave cannot be launched at all and the current sheets in the striped
wind are first compressed by an MHD shock and subsequently dissipate by
reconnection, and a low density one, where the wind can first convert into an
electromagnetic wave in the shock precursor, which then damps and merges into
the surroundings. Shocks in binary systems can transit from one regime to
another according to binary phase. We discuss possible observational
implications for these objects.


  Current density distributions in active integrated circuits (ICs) result in
patterns of magnetic fields that contain structural and functional information
about the IC. Magnetic fields pass through standard materials used by the
semiconductor industry and provide a powerful means to fingerprint IC activity
for security and failure analysis applications. Here, we demonstrate high
spatial resolution, wide field-of-view, vector magnetic field imaging of static
(DC) magnetic field emanations from an IC in different active states using a
Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent
nitrogen-vacancy (NV) quantum defects near the surface of a transparent diamond
substrate placed on the IC to image magnetic fields. We show that QDM imaging
achieves simultaneous $\sim10$ $\mu$m resolution of all three vector magnetic
field components over the 3.7 mm $\times$ 3.7 mm field-of-view of the diamond.
We study activity arising from spatially-dependent current flow in both intact
and decapsulated field-programmable gate arrays (FPGAs); and find that QDM
images can determine pre-programmed IC active states with high fidelity using
machine-learning classification methods.


  Given a set of incomplete observations, we study the nonparametric problem of
testing whether data are Missing Completely At Random (MCAR). Our first
contribution is to characterise precisely the set of alternatives that can be
distinguished from the MCAR null hypothesis. This reveals interesting and novel
links to the theory of Fr\'echet classes (in particular, compatible
distributions) and linear programming, that allow us to propose MCAR tests that
are consistent against all detectable alternatives. We define an
incompatibility index as a natural measure of ease of detectability, establish
its key properties, and show how it can be computed exactly in some cases and
bounded in others. Moreover, we prove that our tests can attain the minimax
separation rate according to this measure, up to logarithmic factors. Our
methodology does not require any complete cases to be effective, and is
available in the R package MCARtest.


  Routing of messages in Vehicular Ad-hoc Networks (VANETs) is challenging due
to obstacle shadowing regions with high vehicle densities, which leads to
frequent disconnection problems and blocks radio wave propagation between
vehicles. Previous researchers used multi-hop, vehicular cloud or roadside
infrastructures to solve the routing issue among the vehicles, but they suffer
from significant packet delays and frequent packet losses arising from obstacle
shadowing. We proposed a vehicular cloud based hybrid technique called
Hybrid-Vehcloud to disseminate messages in obstacle shadowing regions, and
multi-hop technique to disseminate messages in non-obstacle shadowing regions.
The novelty of our approach lies in the fact that our proposed technique
dynamically adapts between obstacle shadowing and non-obstacle shadowing
regions. Simulation based performance analysis of Hybrid-Vehcloud showed
improved performance over Cloud-assisted Message Downlink Dissemination Scheme
(CMDS), Cross-Layer Broadcast Protocol (CLBP) and Cloud-VANET schemes at high
vehicle densities.


  Existence and uniqueness of solutions for nonlocal Cahn-Hilliard equations
with degenerate potential is shown. The nonlocality is described by means of a
symmetric singular kernel not falling within the framework of any previous
existence theory. A convection term is also taken into account. Building upon
this novel existence result, we prove convergence of solutions for this class
of nonlocal Cahn-Hilliard equations to their local counterparts, as the
nonlocal convolution kernels approximate a Dirac delta. Eventually, we show
that, under suitable assumptions on the data, the solutions to the nonlocal
Cahn-Hilliard equations exhibit further regularity, and the nonlocal-to-local
convergence is verified in a stronger topology.


  Large Language Model-based (LLM-based) Text-to-SQL methods have achieved
important progress in generating SQL queries for real-world applications. When
confronted with table content-aware questions in real-world scenarios,
ambiguous data content keywords and non-existent database schema column names
within the question leads to the poor performance of existing methods. To solve
this problem, we propose a novel approach towards Table Content-aware
Text-to-SQL with Self-Retrieval (TCSR-SQL). It leverages LLM's in-context
learning capability to extract data content keywords within the question and
infer possible related database schema, which is used to generate Seed SQL to
fuzz search databases. The search results are further used to confirm the
encoding knowledge with the designed encoding knowledge table, including column
names and exact stored content values used in the SQL. The encoding knowledge
is sent to obtain the final Precise SQL following multi-rounds of
generation-execution-revision process. To validate our approach, we introduce a
table-content-aware, question-related benchmark dataset, containing 1,692
question-SQL pairs. Comprehensive experiments conducted on this benchmark
demonstrate the remarkable performance of TCSR-SQL, achieving an improvement of
at least 13.7% in execution accuracy compared to other state-of-the-art
methods.


  Bollerslev et al. (2006) study the cross-covariances for squared returns
under the Heston (1993) stochastic volatility model. In order to obtain these
cross-covariances the authors use an incorrect expression for the distribution
of the squared returns. Here we will obtain the correct distribution of the
squared returns and check that, under this new distribution, the result in
Appendix A.2 in Bollerslev et al. (2006) still holds.


  Several kinds of differential relations for polynomial components of almost
Belyi maps are presented. Saito's theory of free divisors give particularly
interesting (yet conjectural) logarithmic action of vector fields. The
differential relations implied by Kitaev's construction of algebraic Painleve
VI solutions through pull-back transformations are used to compute almost Belyi
maps for the pull-backs giving all genus 0 and 1 Painleve VI solutions in the
Lisovyy-Tykhyy classification.


  This paper presents an end-to-end system for fact extraction and verification
using textual and tabular evidence, the performance of which we demonstrate on
the FEVEROUS dataset. We experiment with both a multi-task learning paradigm to
jointly train a graph attention network for both the task of evidence
extraction and veracity prediction, as well as a single objective graph model
for solely learning veracity prediction and separate evidence extraction. In
both instances, we employ a framework for per-cell linearization of tabular
evidence, thus allowing us to treat evidence from tables as sequences. The
templates we employ for linearizing tables capture the context as well as the
content of table data. We furthermore provide a case study to show the
interpretability our approach. Our best performing system achieves a FEVEROUS
score of 0.23 and 53% label accuracy on the blind test data.


  We demonstrate the correspondence between quantum mechanical and quantum
field theoretical descriptions of Mossbauer neutrino oscillations. First, we
compute the combined rate $\Gamma$ of Mossbauer neutrino emission, propagation,
and detection in quantum field theory, treating the neutrino as an internal
line of a tree level Feynman diagram. We include explicitly the effect of
homogeneous line broadening due to fluctuating electromagnetic fields in the
source and detector crystals and show that the resulting formula for $\Gamma$
is identical to the one obtained previously (Akhmedov et al., arXiv:0802.2513)
for the case of inhomogeneous line broadening. We then proceed to a quantum
mechanical treatment of Mossbauer neutrinos and show that the oscillation,
coherence, and resonance terms from the field theoretical result can be
reproduced if the neutrino is described as a superposition of Lorentz-shaped
wave packet with appropriately chosen energies and widths. On the other hand,
the emission rate and the detection cross section, including localization and
Lamb-Mossbauer terms, cannot be predicted in quantum mechanics and have to be
put in by hand.


  We complete the program of 2012.15792 about perturbative approaches for
$\mathcal{N}=2$ superconformal quiver theories in four dimensions. We consider
several classes of observables in presence of Wilson loops, and we evaluate
them with the help of supersymmetric localization. We compute Wilson loop
vacuum expectation values, correlators of multiple coincident Wilson loops and
one-point functions of chiral operators in presence of them acting as
superconformal defects. We extend this analysis to the most general case
considering chiral operators and multiple Wilson loops scattered in all the
possible ways among the vector multiplets of the quiver. Finally, we identify
twisted and untwisted observables which probe the orbifold of $AdS_5\times S^5$
with the aim of testing possible holographic perspectives of quiver theories in
$\mathcal{N}=2$.


  A voting center is in charge of collecting and aggregating voter preferences.
In an iterative process, the center sends comparison queries to voters,
requesting them to submit their preference between two items. Voters might
discuss the candidates among themselves, figuring out during the elicitation
process which candidates stand a chance of winning and which do not.
Consequently, strategic voters might attempt to manipulate by deviating from
their true preferences and instead submit a different response in order to
attempt to maximize their profit. We provide a practical algorithm for
strategic voters which computes the best manipulative vote and maximizes the
voter's selfish outcome when such a vote exists. We also provide a careful
voting center which is aware of the possible manipulations and avoids
manipulative queries when possible. In an empirical study on four real-world
domains, we show that in practice manipulation occurs in a low percentage of
settings and has a low impact on the final outcome. The careful voting center
reduces manipulation even further, thus allowing for a non-distorted group
decision process to take place. We thus provide a core technology study of a
voting process that can be adopted in opinion or information aggregation
systems and in crowdsourcing applications, e.g., peer grading in Massive Open
Online Courses (MOOCs).


  We introduce a generalized Spiking Locally Competitive Algorithm (LCA) that
is biologically plausible and exhibits adaptability to a large variety of
neuron models and network connectivity structures. In addition, we provide
theoretical evidence demonstrating the algorithm's convergence in optimization
problems of signal recovery. Furthermore, our algorithm demonstrates superior
performance over traditional optimization methods, such as FISTA, particularly
by achieving faster early convergence in practical scenarios including signal
denoising, seismic wave detection, and computed tomography reconstruction.
Notably, our algorithm is compatible with neuromorphic chips, such as Loihi,
facilitating efficient multitasking within the same chip architecture - a
capability not present in existing algorithms. These advancements make our
generalized Spiking LCA a promising solution for real-world applications,
offering significant improvements in execution speed and flexibility for
neuromorphic computing systems.


  We consider the possibility that a mass of ~10^{-5}-10^{-3} Msun flows back
from the dense shell of planetary nebulae and is accreted by the central star
during the planetary nebula phase. This backflowing mass is expected to have a
significant specific angular momentum even in (rare) spherical planetary
nebulae, such that a transient accretion disk might be formed. This mass might
influence the occurrence and properties of a very late thermal pulse (VLTP),
and might even trigger it. For example, the rapidly rotating outer layer, and
the disk if still exist, might lead to axisymmetrical mass ejection by the
VLTP. Unstable burning of accreted hydrogen might result in a mild flash of the
hydrogen shell, also accompanied by axisymmetrical ejection.


  Recent data point in the direction of a cosmological constant dominated
universe. We investigate the role of supersymmetric QCD with N_f < N_c as a
possible candidate for dynamical cosmological constant (``quintessence''). We
take in full consideration the multi-scalar nature of the model, allowing for
different initial conditions for the N_f independent scalar VEVs and studying
the coupled system of N_f equations of motion. The issues related to the
coupling of the scalars with other cosmological fields are also addressed.


  Ammonium tetrathiomolybdate (ATM) spontaneously self assembles on Au
electrodes forming a hydrophilic, air stable, pH (3-11) tolerant multilayer
that is stable over a reasonably large potential window. The ATM functionalized
Au electrodes can adsorb iron porphyrin catalysts and act as O2 reducing
electrodes. These electrodes are stable enough to perform rotating disk
electrochemistry (RDE) as well as rotating ring disk electrochemistry (RRDE)
experiments. The X-ray photoelectron spectroscopy (XPS) data indicate that the
sulphide atoms of ATM anchors a single ATM layer on to Au and the subsequent
layers grow vertically due to the presence of hydrogen bonding NH4+
counter-ions. The formation and growth of these ATM adlayers is investigated
using atomic force microscopy (AFM), scanning electron microscopy (SEM) and a
series of electrochemical data. The ATM functionalized Au electrodes have
double layer capacitance comparable to those reported for Au electrode bearing
short chain alkyl thiol self assembled monolayer (SAM). Importantly, the rate
of interfacial charge transfer (CT) can be tuned by controlling the thickness
of the adlayers by simply adjusting the deposition time. Importantly the
kinetics of a catalyst adsorbed on this ATM adlayer can be switched from mass
transfer limited to CT limited regime by adjusting the deposition time.


  The final version of this paper has been published in IEEEXplore available at
http://ieeexplore.ieee.org/document/7727213. Please cite this paper as:
Amirhossein Tavanaei, Timothee Masquelier, and Anthony Maida, Acquisition of
visual features through probabilistic spike-timing-dependent plasticity. IEEE
International Joint Conference on Neural Networks. pp. 307-314, IJCNN 2016.
  This paper explores modifications to a feedforward five-layer spiking
convolutional network (SCN) of the ventral visual stream [Masquelier, T.,
Thorpe, S., Unsupervised learning of visual features through spike timing
dependent plasticity. PLoS Computational Biology, 3(2), 247-257]. The original
model showed that a spike-timing-dependent plasticity (STDP) learning algorithm
embedded in an appropriately selected SCN could perform unsupervised feature
discovery. The discovered features where interpretable and could effectively be
used to perform rapid binary decisions in a classifier. In order to study the
robustness of the previous results, the present research examines the effects
of modifying some of the components of the original model. For improved
biological realism, we replace the original non-leaky integrate-and-fire
neurons with Izhikevich-like neurons. We also replace the original STDP rule
with a novel rule that has a probabilistic interpretation. The probabilistic
STDP slightly but significantly improves the performance for both types of
model neurons. Use of the Izhikevich-like neuron was not found to improve
performance although performance was still comparable to the IF neuron. This
shows that the model is robust enough to handle more biologically realistic
neurons. We also conclude that the underlying reasons for stable performance in
the model are preserved despite the overt changes to the explicit components of
the model.


  RR Lyrae stars are one of the primary distance indicators for old stellar
populations such as globular clusters, dwarf galaxies and galaxies. Typically,
fundamental-mode RR Lyr stars are used for distance measurements, and their
accuracy is strongly limited by the dependence of absolute magnitudes on
metallicity, in both the optical and infrared bands. Here, we report the
discovery of a period-(period ratio)-metallicity relation for double-mode RR
Lyr stars, which can predict metallicity as accurately as the low-resolution
spectra. With theoretical and observational evidence, we propose that the
period-luminosity relation of double-mode RR Lyr stars is not affected by the
metallicity. Combining the Large Magellanic Cloud distance and Gaia parallaxes,
we calibrate the zero point of the period-luminosity relation to an error of
0.022 mag, which means that in the best case double-mode RR Lyr stars can
anchor galaxy distances to an accuracy of 1.0%. For four globular clusters and
two dwarf galaxies, we obtain distances using double-mode RR Lyr stars with a
distance accuracy of 2-3% and 1-2%, respectively. With future telescopes such
as the China Space Station Telescope and the Vera C. Rubin Observatory,
double-mode RR Lyr stars will be established as an independent distance ladder
in the near-field universe.


  Quantum error correction is an essential component for practical quantum
computing on noisy quantum hardware. However, logical operations on
error-corrected qubits require a significant resource overhead, especially for
high-precision and high-fidelity non-Clifford rotation gates. To address this
issue, we propose a postselection-based algorithm to efficiently prepare
resource states for gate teleportation. Our algorithm achieves fault tolerance,
demonstrating the exponential suppression of logical errors with code distance,
and it applies to any stabilizer codes. We provide analytical derivations and
numerical simulations of the fidelity and success probability of the algorithm.
We benchmark the method on surface code and show a factor of 100 to 10,000
reduction in space-time overhead compared to existing methods. Overall, our
approach presents a promising path to reducing the resource requirement for
quantum algorithms on error-corrected and noisy intermediate-scale quantum
computers.


  The purpose of this paper is the discussion of a pair of coupled linear
oscillators that has recently been proposed as a model of a system of two
optical resonators. By means of an algebraic approach we show that the
frequencies of the classical and quantum-mechanical interpretations of the
optical phenomenon are exactly the same. Consequently, if the classical
frequencies are real, then the quantum-mechanical eigenvalues are also real.


  While metamaterials are often desirable for near-field functions, such as
perfect lensing, or cloaking, they are often quantified by their response to
plane waves from the far field. Here, we present a theoretical analysis of the
local density of states near lattices of discrete magnetic scatterers, i.e.,
the response to near field excitation by a point source. Based on a
point-dipole theory using Ewald summation and an array scanning method, we can
swiftly and semi-analytically evaluate the local density of states (LDOS) for
magnetoelectric point sources in front of an infinite two-dimensional (2D)
lattice composed of arbitrary magnetoelectric dipole scatterers. The method
takes into account radiation damping as well as all retarded electrodynamic
interactions in a self-consistent manner. We show that a lattice of magnetic
scatterers evidences characteristic Drexhage oscillations. However, the
oscillations are phase shifted relative to the electrically scattering lattice
consistent with the difference expected for reflection off homogeneous magnetic
respectively electric mirrors. Furthermore, we identify in which source-surface
separation regimes the metasurface may be treated as a homogeneous interface,
and in which homogenization fails. A strong frequency and in-plane position
dependence of the LDOS close to the lattice reveals coupling to guided modes
supported by the lattice.


  We look at the limit distributions of sums of deterministic chaotic variables
in unimodal maps and find a remarkable renormalization group (RG) structure
associated to the operation of increment of summands and rescaling. In this
structure - where the only relevant variable is the difference in control
parameter from its value at the transition to chaos - the trivial fixed point
is the Gaussian distribution and a novel nontrivial fixed point is a
multifractal distribution that emulates the Feigenbaum attractor, and is
universal in the sense of the latter. The crossover between the two fixed
points is explained and the flow toward the trivial fixed point is seen to be
comparable to the chaotic band merging sequence. We discuss the nature of the
Central Limit Theorem for deterministic variables.


  Text detoxification has the potential to mitigate the harms of toxicity by
rephrasing text to remove offensive meaning, but subtle toxicity remains
challenging to tackle. We introduce MaRCo, a detoxification algorithm that
combines controllable generation and text rewriting methods using a Product of
Experts with autoencoder language models (LMs). MaRCo uses likelihoods under a
non-toxic LM (expert) and a toxic LM (anti-expert) to find candidate words to
mask and potentially replace. We evaluate our method on several subtle toxicity
and microaggressions datasets, and show that it not only outperforms baselines
on automatic metrics, but MaRCo's rewrites are preferred 2.1 $\times$ more in
human evaluation. Its applicability to instances of subtle toxicity is
especially promising, demonstrating a path forward for addressing increasingly
elusive online hate.


  The Fock-Hilbert space generated by a single-particle interaction-free
Wightman field is augmented by introducing non-trivial multi-particle (that is,
multi-point, multilinear) quantum fields, which is justified insofar as Haag's
theorem establishes that free field Fock-Hilbert spaces cannot model bound or
interacting states. Two Gaussian constructions are given: one that modifies the
combinatoric factors and masses associated with products of propagators and a
second for which locality is determined by the center of mass of the
n-particles and relative separations of the n-particles determine the strength
of resonance; it is shown how the two constructions may also be used together.
Finally, a method is given for generating non-Gaussian n-particle quantum
fields that quite closely tracks familiar interacting quantum fields but that
is significantly better-defined and that offers a much richer algebraic
structure for future use.


  Belle II recently reported the first measurement of $B^+\to
K^++\mathrm{inv}$, which is $2.8\sigma$ above the Standard Model prediction. We
explore the available parameter space of new physics within Standard Model
effective field theory extended by sterile neutrinos ($\nu$SMEFT) and provide
predictions for the other $B\to K^{(\star)}+\mathrm{inv}$ decay modes and
invisible $B_s$ decays. We also briefly comment on charged current decays $B\to
D^{(\star)}\ell\bar\nu$ and possible ultraviolet completions of the relevant
$\nu$SMEFT operators.


  We consider a wide family of vehicle routing problem variants with many
complex and practical constraints, known as rich vehicle routing problems,
which are faced on a daily basis by C.H. Robinson (CHR). Since CHR has many
customers, each with distinct requirements, various routing problems with
different objectives and constraints should be solved. We propose a set
partitioning framework with a number of route generation algorithms, which have
shown to be effective in solving a variety of different problems. The proposed
algorithms have outperformed the existing technologies at CHR on 10 benchmark
instances and since, have been embedded into the company's transportation
planning and execution technology platform.


  In this thesis I explore the generality of the holographic principle in 2+1
(bulk) dimensions by looking at the possibility of having holographic
correspondences for non-AdS (higher-spin) spacetimes. The first part focuses on
Lobachevsky spacetimes with $\mathfrak{sl}(4,\mathbb{R})$ as well as
$\mathcal{W}^{(2)}_N$ symmetries, the asymptotic symmetry algebras and their
unitary representations. This results in a family of unitary
$\mathcal{W}^{(2)}_N$ models that can have both small and large central charge.
The focus of the second part is a possible holographic correspondence in
asymptotically flat spacetimes. This part covers limits from known AdS$_3$
results to flat space as well as a NO-GO result that forbids having flat space,
higher-spins and unitarity at the same time. In addition this part shows how to
consistently add (higher-spin) chemical potentials to flat space. As a
non-trivial check of a holographic correspondence in flat space I provide a way
to determine entanglement entropy (as well as thermal entropy of flat space
cosmologies) holographically in asymptotically flat spacetimes using Wilson
lines.


  Withdrawn due to the existence of the main result in Phys.Rev. D69 (2004)
105010, hep-th/0312266 (based on earlier results in JHEP 0304 (2003) 039,
hep-th/0212008).


  It is generalized Weyl conformal curvature tensor in the case of a conformal
mappings of a generalized Riemannian space in this paper. Moreover, it is found
universal generalizations of it without any additional assumption. A method
used in this paper may help different scientists in their researching.


  This paper presents a comprehensive evaluation of the potential of Quantum
Convolutional Neural Networks (QCNNs) in comparison to classical Convolutional
Neural Networks (CNNs) and Artificial / Classical Neural Network (ANN) models.
With the increasing amount of data, utilizing computing methods like CNN in
real-time has become challenging. QCNNs overcome this challenge by utilizing
qubits to represent data in a quantum environment and applying CNN structures
to quantum computers. The time and accuracy of QCNNs are compared with
classical CNNs and ANN models under different conditions such as batch size and
input size. The maximum complexity level that QCNNs can handle in terms of
these parameters is also investigated. The analysis shows that QCNNs have the
potential to outperform both classical CNNs and ANN models in terms of accuracy
and efficiency for certain applications, demonstrating their promise as a
powerful tool in the field of machine learning.


  Massive stars blow powerful winds and eventually explode as supernovae. By
doing so, they inject energy and momentum in the circumstellar medium, which is
pushed away from the star and piles up to form a dense and expanding shell of
gas. The effect is larger when many massive stars are grouped together in bound
clusters or associations. Large cavities form around clusters as a result of
the stellar feedback on the ambient medium. They are called superbubbles and
are characterised by the presence of turbulent and supersonic gas motions. This
makes star clusters ideal environments for particle acceleration, and potential
contributors to the observed Galactic cosmic ray intensity. The acceleration of
particles at star clusters and in their surroundings may provide a major
contribution to the observed CR flux. Moreover, it may explain the fine
structures observed in the chemical composition of these particles, and
possibly provide a solution to the puzzle of the origin of cosmic rays of
energies in the PeV range and beyond.


  Thermodynamic functions of ionic systems were evaluated analytically using
the Green's Function for Body Centered Cubic Lattices. The free energy density,
chemical potential, pressure, spinodals, and coulomb ionic potentials are
expressed in terms of hyper geometric functions 3F2 and complete elliptic
integrals


  This study proposes a novel super-resolution (or SR) framework for generating
high-resolution turbulent boundary layer (TBL) flow from low-resolution inputs.
The framework combines a super-resolution generative adversarial neural network
(SRGAN) with down-sampling modules (DMs), integrating the residual of the
continuity equation into the loss function. DMs selectively filter out
components with excessive energy dissipation in low-resolution fields prior to
the super-resolution process. The framework iteratively applies the SRGAN and
DM procedure to fully capture the energy cascade of multi-scale flow
structures, collectively termed the SRGAN-based energy cascade framework
(EC-SRGAN). Despite being trained solely on turbulent channel flow data (via
"zero-shot transfer"), EC-SRGAN exhibits remarkable generalization in
predicting TBL small-scale velocity fields, accurately reproducing wavenumber
spectra compared to DNS results. Furthermore, a super-resolution core is
trained at a specific super-resolution ratio. By leveraging this pre-trained
super-resolution core, EC-SRGAN efficiently reconstructs TBL fields at multiple
super-resolution ratios from various levels of low-resolution inputs,
showcasing strong flexibility. By learning turbulent scale invariance, EC-SRGAN
demonstrates robustness across different TBL datasets. These results underscore
EC-SRGAN potential for generating and predicting wall turbulence with high
flexibility, offering promising applications in addressing diverse TBL-related
challenges.


  Machine Teaching (MT) is an interactive process where a human and a machine
interact with the goal of training a machine learning model (ML) for a
specified task. The human teacher communicates their task expertise and the
machine student gathers the required data and knowledge to produce an ML model.
MT systems are developed to jointly minimize the time spent on teaching and the
learner's error rate. The design of human-AI interaction in an MT system not
only impacts the teaching efficiency, but also indirectly influences the ML
performance by affecting the teaching quality. In this paper, we build upon our
previous work where we proposed an MT framework with three components, viz.,
the teaching interface, the machine learner, and the knowledge base, and focus
on the human-AI interaction design involved in realizing the teaching
interface. We outline design decisions that need to be addressed in developing
an MT system beginning from an ML task. The paper follows the Socratic method
entailing a dialogue between a curious student and a wise teacher.


  We prove that the LS category of the symplectic group $Sp(n)$ is bounded
above by $\binom{n+1}{2}$. This is achieved by computing the number of critical
levels of a height function.


  With recent observational advancements, substantial amounts of photometric
and spectroscopic eclipsing binary data have been acquired. As part of an
ongoing effort to assemble a reliable pipeline for fully automatic data
analysis, we put Powell's direction set method to the test. The method does not
depend on numerical derivatives, only on function evaluations, and as such it
cannot diverge. Compared to differential corrections (DC) and Nelder & Mead's
downhill simplex (NMS) method, Powell's method proves to be more efficient in
terms of solution determination and the required number of iterations. However,
its application is still not optimal in terms of time cost. Causes for this
deficiency are identified and two steps toward the solution are proposed:
non-ortogonality of the parameter set should be removed and better initial
directions should be determined before the minimization is initiated. Once
these setbacks are worked out, Powell's method will probably replace DC and NMS
as the default minimizing algorithm in PHOEBE modeling package.


  Lithographically fabricated point contacts serve as important examples of
mesoscopic conductors, as electrodes for molecular electronics, and as
ultra-sensitive transducers for mechanical motion. We have developed a
reproducible technique for fabricating metallic point contacts though
electromigration. We employ fast analog feedback in a four-wire configuration
in combination with slower computer controlled feedback to avoid catastrophic
instability. This hybrid system allows electromigration to proceed while
dissipating approximately constant power in the wire. We are able to control
the final resistance of the point contact precisely below 5 k\Omega\ and to
within a factor of three when the target resistance approaches 12 k\Omega\
where only a single conducting channel remains.


  The vector Burgers equation is extended to include pressure gradients and
gravity. It is shown that within the framework of the Cole-Hopf transformation
there are no physical solutions to this problem. This result is important
because it clearly demonstrates that any extension of Burgers equation to more
interesting physical situations is strongly limited.


  In this paper, we would like to study the linear Cauchy problems for
semi-linear $\sigma$-evolution models with mixing a parabolic like damping term
corresponding to $\sigma_1 \in [0,\sigma/2)$ and a $\sigma$-evolution like
damping corresponding to $\sigma_2 \in (\sigma/2,\sigma]$. The main goals are
on the one hand to conclude some estimates for solutions and their derivatives
in $L^q$ setting, with any $q\in [1,\infty]$, by developing the theory of
modified Bessel functions effectively to control oscillating integrals
appearing the solution representation formula in a competition between these
two kinds of damping. On the other hand, we are going to prove the global (in
time) existence of small data Sobolev solutions in the treatment of the
corresponding semi-linear equations by applying $(L^{m}\cap L^{q})- L^{q}$ and
$L^{q}- L^{q}$ estimates, with $q\in (1,\infty)$ and $m\in [1,q)$, from the
linear models. Finally, some further generalizations will be discussed in the
end of this paper.


  We have identified a spiral arm lying beyond the Outer Arm in the first
Galactic quadrant ~15 kpc from the Galactic center. After tracing the arm in
existing 21 cm surveys, we searched for molecular gas using the CfA 1.2 meter
telescope and detected CO at 10 of 220 positions. The detections are
distributed along the arm from l = 13 deg, v = -21 km/s to l = 55 deg, v = -84
km/s and coincide with most of the main H I concentrations. One of the
detections was fully mapped to reveal a large molecular cloud with a radius of
47 pc and a molecular mass of ~50,000 Mo. At a mean distance of 21 kpc, the
molecular gas in this arm is the most distant yet detected in the Milky Way.
The new arm appears to be the continuation of the Scutum-Centaurus Arm in the
outer Galaxy, as a symmetric counterpart of the nearby Perseus Arm.


  Given any compact, Hausdorff space $K$ and $1<p<\infty$, we compute the
Szlenk and $w^*$-dentability indices of the spaces $C(K)$ and $L_p(C(K))$. We
show that if $K$ is compact, Hausdorff, scattered, $CB(K)$ is the
Cantor-Bendixson index of $K$, and $\xi$ is the minimum ordinal such that
$CB(K)\leqslant \omega^\xi$, then $Sz(C(K))=\omega^\xi$ and
$Dz(C(K))=Sz(L_p(C(K)))= \omega^{1+\xi}.$


  The interaction between kink and radiation in nonlinear one-dimensional real
scalar field is investigated. The process of discrete vibrational mode
excitation in $\phi^4$ model is considered. The role of this oscillations in
creation of kink and antikink is discussed. Numerical results are presented as
well as some attempts of analytical explanations. An intriguing fractal
structure in parameter space dividing regions with creation and without is also
presented.


  Supersymmetric SO(10) grand unified models with renormalizable Yukawa
couplings involving {\bf 10}, {\bf 126} and {\bf 120} Higgs fields have been
shown to give a very economical theory for understanding quark-lepton flavor in
a unified framework. In previous papers, we showed how nucleon decay can be
suppressed in these models without invoking cancellation, by choice of Yukawa
flavor texture within a type II seesaw framework for neutrinos that explains
all mixings and masses including the recently observed "large" $\theta_{13}$.
In this follow-up paper, we extend our earlier work to the case of type I
seesaw and show that the recently measured "large" $\theta_{13}$ can be
accommodated in this case while suppressing proton decay. We then point out
that the two cases (type I and II) lead to different testable predictions for
$B(\mu\to e+\gamma)$ and $B(\tau\to \mu (e) +\gamma)$ as well as different
flavor final states in nucleon decay. In particular, we find that for the type
I seesaw case, $B(\tau\to \mu +\gamma)$ can be observable while at the same
time suppressing $B(\mu\to e+\gamma)$, whereas in the type II seesaw case,
$B(\tau\to \mu +\gamma)$ is always suppressed whereas $B(\mu\to e+\gamma)$ is
observable.


  In this paper we prove that the limit set of any Weil-Petersson geodesic ray
with uniquely ergodic ending lamination is a single point in the Thurston
compactification of Teichm\"uller space. On the other hand, we construct
examples of Weil-Petersson geodesics with minimal nonuniquely ergodic ending
laminations and limit set a circle in the Thurston compactification.


  We propose a Bayesian nonparametric approach to the problem of jointly
modeling multiple related time series. Our approach is based on the discovery
of a set of latent, shared dynamical behaviors. Using a beta process prior, the
size of the set and the sharing pattern are both inferred from data. We develop
efficient Markov chain Monte Carlo methods based on the Indian buffet process
representation of the predictive distribution of the beta process, without
relying on a truncated model. In particular, our approach uses the sum-product
algorithm to efficiently compute Metropolis-Hastings acceptance probabilities,
and explores new dynamical behaviors via birth and death proposals. We examine
the benefits of our proposed feature-based model on several synthetic datasets,
and also demonstrate promising results on unsupervised segmentation of visual
motion capture data.


  This book contains the material of my research on stereotype duality theories
in geometry. It was intended as a continuation of my recently published
monograph in De Gruyter on stereotype spaces and algebras.


  Due to the increased availability of online reviews, sentiment analysis had
been witnessed a booming interest from the researchers. Sentiment analysis is a
computational treatment of sentiment used to extract and understand the
opinions of authors. While many systems were built to predict the sentiment of
a document or a sentence, many others provide the necessary detail on various
aspects of the entity (i.e. aspect-based sentiment analysis). Most of the
available data resources were tailored to English and the other popular
European languages. Although Persian is a language with more than 110 million
speakers, to the best of our knowledge, there is a lack of public dataset on
aspect-based sentiment analysis for Persian. This paper provides a manually
annotated Persian dataset, Pars-ABSA, which is verified by 3 native Persian
speakers. The dataset consists of 5,114 positive, 3,061 negative and 1,827
neutral data samples from 5,602 unique reviews. Moreover, as a baseline, this
paper reports the performance of some state-of-the-art aspect-based sentiment
analysis methods with a focus on deep learning, on Pars-ABSA. The obtained
results are impressive compared to similar English state-of-the-art.


  In the Landau theory of phase transitions one considers an effective
potential $\Phi$ whose symmetry group $G$ and degree $d$ depend on the system
under consideration; generally speaking, $\Phi$ is the most general
$G$-invariant polynomial of degree $d$. When such a $\Phi$ turns out to be too
complicate for a direct analysis, it is essential to be able to drop
unessential terms, i.e. to apply a simplifying criterion. Criteria based on
singularity theory exist and have a rigorous foundation, but are often very
difficult to apply in practice. Here we consider a simplifying criterion (as
stated by Gufan) and rigorously justify it on the basis of classical
Lie-Poincar\'e theory as far as one deals with fixed values of the control
parameter(s) in the Landau potential; when one considers a range of values, in
particular near a phase transition, the criterion has to be accordingly
partially modified, as we discuss. We consider some specific cases of group $G$
as examples, and study in detail the application to the
Sergienko-Gufan-Urazhdin model for highly piezoelectric perovskites.


  We consider the coupling between the equations of motion of a compressible
fluid in two and three space dimensions with Christov's equation for the heat
flux. Christov's equation is a frame indifferent formulation of the classical
model of Cattaneo that allows for the heat flux to be eliminated to obtain a
single hyperbolic equation for the temperature. The obtained system is written
in quasilinear form for the state variables density, velocity, temperature and
heat flux. It is then shown that this system is not of hyperbolic type as
consequence of the presence of the Lie-Oldroyd upper convected material
derivative involved in Christov's formulation.


  We provide answers to a question brought up by Erd\H{o}s about the
construction of Wetzel families in the absence of the continuum hypothesis - a
Wetzel family is a family $\mathcal{F}$ of entire functions on the complex
plane which pointwise assumes fewer than $\vert \mathcal{F} \vert$ values. To
be more precise, we show that the existence of a Wetzel family is consistent
with all possible values $\kappa$ of the continuum and, if $\kappa$ is regular,
also with Martin's Axiom. In the particular case of $\kappa = \aleph_2$ this
answers an open question asked by Kumar and Shelah. In the buildup to this
result, we are also solving an open question of Zapletal on strongly almost
disjoint functions. We also study a strongly related notion of sets exhibiting
a universality property via mappings by entire functions and show that these
consistently exist while the continuum equals $\aleph_2$.


  While recent works have indicated that federated learning (FL) may be
vulnerable to poisoning attacks by compromised clients, their real impact on
production FL systems is not fully understood. In this work, we aim to develop
a comprehensive systemization for poisoning attacks on FL by enumerating all
possible threat models, variations of poisoning, and adversary capabilities. We
specifically put our focus on untargeted poisoning attacks, as we argue that
they are significantly relevant to production FL deployments.
  We present a critical analysis of untargeted poisoning attacks under
practical, production FL environments by carefully characterizing the set of
realistic threat models and adversarial capabilities. Our findings are rather
surprising: contrary to the established belief, we show that FL is highly
robust in practice even when using simple, low-cost defenses. We go even
further and propose novel, state-of-the-art data and model poisoning attacks,
and show via an extensive set of experiments across three benchmark datasets
how (in)effective poisoning attacks are in the presence of simple defense
mechanisms. We aim to correct previous misconceptions and offer concrete
guidelines to conduct more accurate (and more realistic) research on this
topic.


  We have performed Raman-scattering measurements on high-quality single
crystals of the superconductors K$_{0.8}$Fe$_{1.6}$Se$_2$ ($T_c$ = 32 K),
Tl$_{0.5}$K$_{0.3}$Fe$_{1.6}$Se$_2$ ($T_c$ = 29 K), and
Tl$_{0.5}$Rb$_{0.3}$Fe$_{1.6}$Se$_2$ ($T_c$ = 31 K), as well as of the
insulating compound KFe$_{1.5}$Se$_2$. To interpret our results, we have made
first-principles calculations for the phonon modes in the ordered iron-vacancy
structure of K$_{0.8}$Fe$_{1.6}$Se$_2$. The modes we observe can be assigned
very well from our symmetry analysis and calculations, allowing us to compare
Raman-active phonons in the AFeSe compounds. We find a clear frequency
difference in most phonon modes between the superconducting and
non-superconducting potassium crystals, indicating the fundamental influence of
iron content. By contrast, substitution of K by Tl or Rb in
A$_{0.8}$Fe$_{1.6}$Se$_2$ causes no substantial frequency shift for any modes
above 60 cm$^{-1}$, demonstrating that the alkali-type metal has little effect
on the microstructure of the FeSe layer. Several additional modes appear below
60 cm$^{-1}$ in Tl- and Rb-substituted samples, which are vibrations of heavier
Tl and Rb ions. Finally, our calculations reveal the presence of "chiral"
phonon modes, whose origin lies in the chiral nature of the
K$_{0.8}$Fe$_{1.6}$Se$_2$ structure.


  We extend the classical primal-dual interior point method from the Euclidean
setting to the Riemannian one. Our method, named the Riemannian interior point
method, is for solving Riemannian constrained optimization problems. We
establish its local superlinear and quadratic convergence under the standard
assumptions. Moreover, we show its global convergence when it is combined with
a classical line search. Our method is a generalization of the classical
framework of primal-dual interior point methods for nonlinear nonconvex
programming. Numerical experiments show the stability and efficiency of our
method.


  We study the notion of duality in the context of graded manifolds. For graded
bundles, somehow like in the case of Gelfand representation and the duality:
points vs. functions, we obtain natural dual objects which belongs to a
different category than the initial ones, namely graded polynomial (co)algebra
bundles and free graded Weil (co)algebra bundles. Our results are then applied
to obtain elegant characterizations of double vector bundles and graded bundles
of degree 2. All these results have their supergeometric counterparts. For
instance, we give a simple proof of a nice characterisation of $N$-manifolds of
degree 2, announced in the literature.


  `Hot jupiters,' giant planets with orbits very close to their parent stars,
are thought to form farther away and migrate inward via interactions with a
massive gas disk. If a giant planet forms and migrates quickly, the
planetesimal population has time to re-generate in the lifetime of the disk and
terrestrial planets may form (Armitage 2003). We present results of simulations
of terrestrial planet formation in the presence of hot jupiters, broadly
defined as having orbital radii <= 0.5 AU. We show that terrestrial planets
similar to those in the Solar System can form around stars with hot jupiters,
and can have water contents equal to or higher than the Earth's. For small
orbital radii of hot jupiters (e.g. 0.15, 0.25 AU) potentially habitable
planets can form, but for semi-major axes of 0.5 AU or greater their formation
is suppressed. We show that the presence of an outer giant planet such as
Jupiter does not enhance the water content of the terrestrial planets, but
rather decreases their formation and water delivery timescales. We speculate
that asteroid belts may exist interior to the terrestrial planets in systems
with hot jupiters.


  In this paper, we introduce an \alpha -flow for the Yang-Mills functional in
vector bundles over four dimensional Riemannian manifolds, and establish global
existence of a unique smooth solution to the \alpha -flow with smooth initial
value. We prove that the limit of solutions of the \alpha -flow as \alpha\to 1
is a weak solution to the Yang-Mills flow. By an application of the \alpha
-flow, we then follow the idea of Sacks and Uhlenbeck to prove some existence
results for Yang-Mills connections and improve the minimizing result of the
Yang-Mills functional of Sedlacek.


  We propose a scheme for an exact efficient transformation of a tensor product
state of many identically prepared qubits into a state of a logarithmically
small number of qubits. Using a quadratic number of elementary quantum gates we
transform N identically prepared qubits into a state, which is nontrivial only
on the first log(N+1) qubits. This procedure might be useful for quantum
memories, as only a small portion of the original qubits has to be stored.
Another possible application is in communicating a direction encoded in a set
of quantum states, as the compressed state provides a high-effective method for
such an encoding.


  In this paper we deal with a classical problem in elementary number theory,
namely repeating decimals. We show how the digits of the period of the decimal
representation of any fraction $\frac{k}{m}$, where $k$ and $m$ are positive
integers arbitrarily chosen, can be obtained relying upon the graphs associated
with the iteration of a certain map over the finite set $\{0, 1, \dots, 10n-2
\}$ for a suitable integer $n$, which depends on $m$. In the last section of
the paper we generalize the results to any arbitrary choice of the base $B \geq
2$ for the representation of the fraction $\frac{k}{m}$.


  Assessing the effects of the energy transition and liberalization of energy
markets on resource adequacy is an increasingly important and demanding task.
The rising complexity in energy systems requires adequate methods for energy
system modeling leading to increased computational requirements. Furthermore,
with complexity, uncertainty increases likewise calling for probabilistic
assessments and scenario analyses. To adequately and efficiently address these
various requirements, new methods from the field of data science are needed to
accelerate current methods. With our systematic literature review, we want to
close the gap between the three disciplines (1) assessment of security of
electricity supply, (2) artificial intelligence, and (3) design of experiments.
For this, we conduct a large-scale quantitative review on selected fields of
application and methods and make a synthesis that relates the different
disciplines to each other. Among other findings, we identify metamodeling of
complex security of electricity supply models using AI methods and applications
of AI-based methods for forecasts of storage dispatch and (non-)availabilities
as promising fields of application that have not sufficiently been covered,
yet. We end with deriving a new methodological pipeline for adequately and
efficiently addressing the present and upcoming challenges in the assessment of
security of electricity supply.


  The staged commissioning of the Large Hadron Collider presents an opportunity
to map gross features of particle production over a significant energy range. I
suggest a visual tool - event displays in (pseudo)rapidity-transverse-momentum
space - as a scenic route that may help sharpen intuition, identify interesting
classes of events for further investigation, and test expectations about the
underlying event that accompanies large-transverse-momentum phenomena.


  The interferometers of Hanbury Brown and collaborators in the 1950s and 60s,
and their modern descendants now being developed (intensity interferometers)
measure the spatial power spectrum of the source from intensity correlations at
two points. The quantum optical theory of the Hanbury Brown and Twiss (HBT)
effect shows that more is possible, in particular the phase information can be
recovered by correlating intensities at three points (bispectrum). In this
paper we argue that such 3 point measurements are possible for bright stars
such as Sirius and Betelgeuse using off the shelf single photon counters with
collecting areas of the order of 100m2. It seems possible to map individual
features on the stellar surface. Simple diameter measurements would be possible
with amateur class telescopes.


  We review the construction (due to Brenner--Schr\"oer) of the Proj scheme
associated with a ring graded by a finitely generated abelian group. This
construction generalizes the well-known Grothendieck Proj construction for
$\mathbb{N}$-graded rings; we extend some classical results (in particular,
regarding quasi-coherent sheaves on such schemes) from the $\mathbb{N}$-graded
setting to this general setting, and prove new results that make sense only in
the general setting of Brenner--Schr\"oer. Finally, we show that flag varieties
of reductive groups, as well as some vector bundles over such varieties
attached to representations of a Borel subgroup, can be naturally interpreted
in this formalism.


  Generation of perpendicular effective magnetic field or perpendicular spins
({\sigma}z) is central for the development of energy-efficient, scalable, and
external-magnetic-field-free spintronic memory and computing technologies.
Here, we report the first identification and the profound impacts of a
significant effective perpendicular magnetic field that can arise from
asymmetric current spreading within magnetic microstrips and Hall bars. This
effective perpendicular magnetic field can exhibit all the three
characteristics that have been widely assumed in the literature to "signify"
the presence of a flow of {\sigma}z, i.e., external-magnetic-field-free current
switching of uniform perpendicular magnetization, a sin2{\phi}-dependent
contribution in spin-torque ferromagnetic resonance signal of in-plane
magnetization ({\phi} is the angle of the external magnetic field with respect
to the current, and a {\phi}-independent but field-dependent contribution in
the second harmonic Hall voltage of in-plane magnetization. This finding
suggests that it is critical to include current spreading effects in the
analyses of various spin polarizations and spin-orbit torques in magnetic
heterostructure. Technologically, our results provide perpendicular effective
magnetic field induced by asymmetric current spreading as a novel, universally
accessible mechanism for efficient, scalable, and external-magnetic-field-free
magnetization switching in memory and computing technologies.


  Edge computing promises to reshape the centralized nature of today's
cloud-based applications by bringing computing resources, at least in part,
closer to the user. Reasons include the increasing need for real-time
(short-delay, reliably-connected) computing and resource-demanding artificial
intelligence (AI) algorithms that overstrain mobile devices' batteries or
compute power but are too bandwidth-demanding to be offloaded to a distant
cloud. However, companies may need to run their protected business logic on
(untrusted) third-party edge devices, which can lead to serious issues due to
weaker security measures than in cloud environments. This article makes the
case for trusted edge computing (TEC), which focuses on developing concepts and
methods for protecting application providers' business logic (and thus their
intellectual property) specifically tailored to open edge infrastructures. This
article further discusses open challenges in TEC to be addressed in the future.
Otherwise, edge computing risks being a non-starter for most businesses due to
the inadequate and neglected protection of intellectual property.


  The study of neutral hydrogen emission and absorption in radio galaxies is
giving new and important insights on a variety of phenomena observed in these
objects. Such observations are helping to understand the origin of the host
galaxy, the effects of the interaction between the radio jet and the ISM, the
presence of fast gaseous outflows as well as jet-induced star formation. Recent
results obtained on these phenomena are summarized in this review. Although the
HI observations concentrate on nearby radio galaxies, the results also have
relevance for the high-z objects as all these phenomena are important, and
likely even more common, in high-redshift radio sources.


  We have studied high temperature thermal behavior of 1H, 1H, 2H,
2H-Perfluorooctyl-trichlorosilane (FOTS) and Octyltrichlorosilane (OTS)
molecules self assembled on titanium dioxide (TiO2) nanoparticles using
advanced microscopy and spectroscopy technique such as Scanning Electron
Microscope (SEM), Dynamic Light Scattering (DLS), X-Ray Diffraction (XRD) and
Fourier Transform Infrared Spectroscopy (FTIR). FOTS SAM and OTS SAM coated
TiO2 nanoparticles were heated to different temperature range from room
temperature (RT) to 550oC. We characterized nano-microstructure and size
distribution of FOTS SAM and OTS SAM coated TiO2 nanoparticles, which were
heat-treated to different peak temperatures, using SEM and DLS techniques. The
thermal stability and degradation of FOTS SAM and OTS SAM coated TiO2 were
carried out using FTIR spectroscopy. We found that FOTS SAM on TiO2 is very
stable up to 450oC and OTS on TiO2 is stable up to 250oC. Peak frequency, peak
intensity and full width half maxima (FWHM) of symmetric and asymmetric CF2 and
CH2 confirms our observation. In this study, we successfully synergized the
surface and temperature sensitive characteristics of FOTS/OTS SAM and TiO2
nanoparticles in order to use them for highly demanding surface and temperature
sensitive nanotechnology applications


  For an understanding of Galactic stellar populations in the SDSS filter
system well defined stellar samples are needed. The nearby stars provide a
complete stellar sample representative for the thin disc population. We compare
the filter transformations of different authors applied to the main sequence
stars from F to K dwarfs to SDSS filter system and discuss the properties of
the main sequence. The location of the mean main sequence in colour-magnitude
diagrams is very sensitive to systematic differences in the filter
transformation. A comparison with fiducial sequences of star clusters observed
in g',r',i' show good agreement. Theoretical isochrones from Padua and from
Dartmouth have still some problems especially in (r-i)-colour.


  Let $X$ be a smooth projective complex variety of maximal Albanese dimension,
and let $L \to X$ be a big line bundle. We prove that the moving Seshadri
constants of the pull-backs of $L$ to suitable finite abelian \'etale covers of
$X$ are arbitrarily large. As an application, given any integer $k\geq 1$,
there exists an abelian \'etale cover $p\colon X' \to X$ such that the adjoint
system $\big|K_{X'} + p^*L \big|$ separates $k$-jets away from the augmented
base locus of $p^*L$, and the exceptional locus of the pull-back of the
Albanese map of $X$ under $p$.


  We study the effects of supersymmetric contribution on both the B_d -> phi
K^0 and B^\pm -> phi K^\pm modes using the perturbative QCD approach. We
estimate the deviation of mixing-induced and direct CP asymmetries and discuss
the strong-phase dependence of them.


  A quantum channel is said to be a mixed-unitary channel if it can be
expressed as a convex combination of unitary channels. We prove that, given the
Choi representation of a quantum channel, it is NP-hard with respect to
polynomial-time Turing reductions to determine whether or not that channel is a
mixed-unitary channel. This hardness result holds even under the assumption
that the channel is not within an inverse-polynomial distance (in the dimension
of the space upon which it acts) of the boundary of the mixed-unitary channels.


  Motivated by the increasing use of and rapid changes in array technologies,
we consider the prediction problem of fitting a linear regression relating a
continuous outcome $Y$ to a large number of covariates $\mathbf {X}$, for
example, measurements from current, state-of-the-art technology. For most of
the samples, only the outcome $Y$ and surrogate covariates, $\mathbf {W}$, are
available. These surrogates may be data from prior studies using older
technologies. Owing to the dimension of the problem and the large fraction of
missing information, a critical issue is appropriate shrinkage of model
parameters for an optimal bias-variance trade-off. We discuss a variety of
fully Bayesian and Empirical Bayes algorithms which account for uncertainty in
the missing data and adaptively shrink parameter estimates for superior
prediction. These methods are evaluated via a comprehensive simulation study.
In addition, we apply our methods to a lung cancer data set, predicting
survival time ($Y$) using qRT-PCR ($\mathbf {X}$) and microarray ($\mathbf
{W}$) measurements.


  The existence of eta-mesic nuclei in which the eta meson is bound in a
nucleus by means of the strong interaction was postulated already in 1986,
albeit not yet confirmed it by experiment. The discovery of this new kind of an
exotic nuclear matter would be very important as it might allow for a better
understanding of the eta meson structure and its interaction with nucleons. The
search for eta-mesic helium 4He-eta is carried out with high statistics and
high acceptance with the WASA detector, installed at the cooler synchrotron
COSY of the Research Center Juelich. The search is conducted via the
measurement of the excitation function for selected decay channels of the
4He-eta system. In the experiment, performed in November 2010, two reactions
dd->(4He-eta)bs ->3He p pi- and dd->(4He-eta)bs ->3He p pi0 were measured with
a beam momentum ramped from 2.127GeV/c to 2.422GeV/c. The report includes the
description of the experimental method and status of the measurement.


  A critical aspect of Graph Neural Networks (GNNs) is to enhance the node
representations by aggregating node neighborhood information. However, when
detecting anomalies, the representations of abnormal nodes are prone to be
averaged by normal neighbors, making the learned anomaly representations less
distinguishable. To tackle this issue, we propose CAGAD -- an unsupervised
Counterfactual data Augmentation method for Graph Anomaly Detection -- which
introduces a graph pointer neural network as the heterophilic node detector to
identify potential anomalies whose neighborhoods are normal-node-dominant. For
each identified potential anomaly, we design a graph-specific diffusion model
to translate a part of its neighbors, which are probably normal, into anomalous
ones. At last, we involve these translated neighbors in GNN neighborhood
aggregation to produce counterfactual representations of anomalies. Through
aggregating the translated anomalous neighbors, counterfactual representations
become more distinguishable and further advocate detection performance. The
experimental results on four datasets demonstrate that CAGAD significantly
outperforms strong baselines, with an average improvement of 2.35% on F1, 2.53%
on AUC-ROC, and 2.79% on AUC-PR.


  This paper introduces a new generalized polynomial chaos expansion (PCE)
comprising measure-consistent multivariate orthonormal polynomials in dependent
random variables. Unlike existing PCEs, whether classical or generalized, no
tensor-product structure is assumed or required. Important mathematical
properties of the generalized PCE are studied by constructing orthogonal
decomposition of polynomial spaces, explaining completeness of orthogonal
polynomials for prescribed assumptions, exploiting whitening transformation for
generating orthonormal polynomial bases, and demonstrating mean-square
convergence to the correct limit. Analytical formulae are proposed to calculate
the mean and variance of a truncated generalized PCE for a general output
variable in terms of the expansion coefficients. An example derived from a
stochastic boundary-value problem illustrates the generalized PCE approximation
in estimating the statistical properties of an output variable for 12 distinct
non-product-type probability measures of input variables.


  The Jarzynski equality (JE), which relates works of non-equilibrium
trajectories to the free energy difference of the initial and final states of
the non-equilibrium process, provides an efficient way to calculate free
energies of systems in simulations and experiments. However, wider applications
of the JE are limited by the requirement that the initial distribution of
non-equilibrium trajectories must be equilibrium. Here we extend the JE to a
matrix form, the Jarzynski matrix equality (JME), which transforms the free
energies of metastable conformational regions in the initial system to that of
final one. Therefore, we can calculate the free energies from non-equilibrium
trajectories which started from an arbitrary initial distribution. We
demonstrate the application of the JME in toy models, Lennard-Jones fluids, and
polymer chain models, show its good efficiency in calculation of free energy
with a satisfactory accuracy. The JME extends applications of the
non-equilibrium method in estimate of free energy in complex system where the
initial global equilibrium is difficult to reach.


  For a Lie groupoid G we prove an analogous of the Baker-Campbell-Hausdorff
formula and we calculate the structure functions of the Lie algebroid
associated to G.


  Static type errors are a common stumbling block for newcomers to typed
functional languages. We present a dynamic approach to explaining type errors
by generating counterexample witness inputs that illustrate how an ill-typed
program goes wrong. First, given an ill-typed function, we symbolically execute
the body to synthesize witness values that make the program go wrong. We prove
that our procedure synthesizes general witnesses in that if a witness is found,
then for all inhabited input types, there exist values that can make the
function go wrong. Second, we show how to extend this procedure to produce a
reduction graph that can be used to interactively visualize and debug witness
executions. Third, we evaluate the coverage of our approach on two data sets
comprising over 4,500 ill-typed student programs. Our technique is able to
generate witnesses for around 85% of the programs, our reduction graph yields
small counterexamples for over 80% of the witnesses, and a simple heuristic
allows us to use witnesses to locate the source of type errors with around 70%
accuracy. Finally, we evaluate whether our witnesses help students understand
and fix type errors, and find that students presented with our witnesses show a
greater understanding of type errors than those presented with a standard error
message.


  We examine harmonic oscillator defects coupled to a photon field in the
environs of an optical fiber. Using techniques borrowed or extended from the
theory of two dimensional quantum fields with boundaries and defects, we are
able to compute exactly a number of interesting quantities. We calculate the
scattering S-matrices (i.e. the reflection and transmission amplitudes) of the
photons off a single defect. We determine using techniques derived from
thermodynamic Bethe ansatz (TBA) the thermodynamic potentials of the
interacting photon-defect system. And we compute several correlators of
physical interest. We find the photon occupancy at finite temperature, the
spontaneous emission spectrum from the decay of an excited state, and the
correlation functions of the defect degrees of freedom. In an extension of the
single defect theory, we find the photonic band structure that arises from a
periodic array of harmonic oscillators. In another extension, we examine a
continuous array of defects and exactly derive its dispersion relation. With
some differences, the spectrum is similar to that found for EM wave propagation
in covalent crystals. We then add to this continuum theory isolated defects, so
as to obtain a more realistic model of defects embedded in a frequency
dependent dielectric medium. We do this both with a single isolated defect and
with an array of isolated defects, and so compute how the S-matrices and the
band structure change in a dynamic medium.


  We present a study of the molecular gas in five closely-spaced
($R_{\perp}<20$ kpc) dual quasars ($L_{\rm
bol}\gtrsim10^{44}~\mathrm{erg~s}^{-1}$) at redshifts $0.4<z<0.8$ with the
Atacama Large Millimeter/submillimeter Array. The dual quasar phase represents
a distinctive stage during the interaction between two galaxies for
investigating quasar fueling and feedback effects on the gas reservoir. The
dual quasars were selected from the Sloan Digital Sky Survey and Subaru/Hyper
Suprime-Cam Subaru Strategic Program, with confirmatory spectroscopic
validation. Based on the detection of the CO J=2--1 emission line with Band 4,
we derived key properties including CO luminosities, line widths, and molecular
gas masses for these systems. Among the ten quasars of the five pairs, eight
have line detections exceeding $5\sigma$. The detected sources prominently
harbor substantial molecular gas reservoirs, with molecular gas masses
($M_{\text{molgas}}$) between $10^{9.6-10.5}~\mathrm{M_{\odot}}$, and molecular
gas-to-stellar mass ratios ($\mu_{\text{molgas}}$) spanning $18-97\%$. The
overall $\mu_{\text{molgas}}$ of these dual quasars agrees with that of
inactive star-forming main-sequence galaxies at comparable redshifts,
indicating no clear evidence of quenching. However, intriguing features in each
individual system show possible evidence of AGN feedback, matter transfer, and
compaction processes.


  Albeit structurally and electronically very similar, at low temperature the
quasi-one-dimensional vanadium sulfide BaVS3 shows a metal-to-insulator
transition via the appearance of a charge-density-wave state, while BaVSe3
apparently remains metallic down to zero temperature. This different behavior
upon cooling is studied by means of density functional theory and its
combination with the dynamical mean-field theory and the rotationally-invariant
slave-boson method. We reveal several subtle differences between these
chalcogenides that provide indications for the deviant behavior of BaVSe3 at
low temperature. In this regard, a smaller Hubbard U in line with an increased
relevance of the Hund's exchange J plays a vital role.


  Primordial black holes (PBHs) could provide the dark matter in various mass
windows below $10^2 M_{\odot}$ and those of $30 M_{\odot}$ might explain the
LIGO events. PBHs much larger than this might have important consequences even
if they provide only a small fraction of the dark matter. In particular, they
could generate cosmological structure either individually through through the
`seed' effect or collectively through the `Poisson' effect, thereby alleviating
some problems associated with the standard CDM scenario. If the PBHs all have a
similar mass and make a small contribution to the dark matter, then the seed
effect dominates on small scales, in which case PBHs could seed the
supermassive black holes in galactic nuclei or even galaxies themselves. If
they have a similar mass and provide the dark matter, the Poisson effect
dominates on all scales and the first bound clouds would form earlier than in
the usual scenario, with interesting observational consequences. If the PBHs
have an extended mass spectrum, which is more likely, they could fulfill all
three roles - providing the dark matter, binding the first bound clouds and
generating galaxies. In this case, the galactic mass function naturally has the
observed form, with the galaxy mass being simply related to the black hole
mass. The stochastic gravitational wave background from the PBHs in this
scenario would extend continuously from the LIGO frequency to the LISA
frequency, offering a potential goal for future surveys.


  We give necessary and sufficient conditions of the existence of a
left-invariant metric of strictly negative Ricci curvature on a solvable Lie
group the nilradical of whose Lie algebra $\mathfrak{g}$ is a filiform Lie
algebra $\mathfrak{n}$. It turns out that such a metric always exists, except
for in the two cases, when $\mathfrak{n}$ is one of the algebras of rank two,
$L_n$ or $Q_n$, and $\mathfrak{g}$ is a one-dimensional extension of
$\mathfrak{n}$, in which cases the conditions are given in terms of certain
linear inequalities for the eigenvalues of the extension derivation.