  We study the excludable public project model where the decision is binary
(build or not build). In a classic excludable and binary public project model,
an agent either consumes the project in its whole or is completely excluded. We
study a setting where the mechanism can set different project release time for
different agents, in the sense that high-paying agents can consume the project
earlier than low-paying agents. The release delay, while hurting the social
welfare, is implemented to incentivize payments to cover the project cost. The
mechanism design objective is to minimize the maximum release delay and the
total release delay among all agents.
  We first consider the setting where we know the prior distribution of the
agents' types. Our objectives are minimizing the expected maximum release delay
and the expected total release delay. We propose the single deadline
mechanisms. We show that the optimal single deadline mechanism is
asymptotically optimal for both objectives, regardless of the prior
distribution. For small number of agents, we propose the sequential unanimous
mechanisms by extending the largest unanimous mechanisms from [Ohseto 2000]. We
propose an automated mechanism design approach via evolutionary computation to
optimize within the sequential unanimous mechanisms.
  We next study prior-free mechanism design. We propose the group-based optimal
deadline mechanism and show that it is competitive against an undominated
mechanism under minor technical assumptions.


  This work addresses the task of generating English sentences from Abstract
Meaning Representation (AMR) graphs. To cope with this task, we transform each
input AMR graph into a structure similar to a dependency tree and annotate it
with syntactic information by applying various predefined actions to it.
Subsequently, a sentence is obtained from this tree structure by visiting its
nodes in a specific order. We train maximum entropy models to estimate the
probability of each individual action and devise an algorithm that efficiently
approximates the best sequence of actions to be applied. Using a substandard
language model, our generator achieves a Bleu score of 27.4 on the LDC2014T12
test set, the best result reported so far without using silver standard
annotations from another corpus as additional training data.


  Intraday variability (IDV) of the radio emission from active galactic nuclei
is now known to be predominantly due to interstellar scintillation (ISS). The
MASIV (The Micro-Arcsecond Scintillation-Induced Variability) survey of 443
flat spectrum sources revealed that the IDV is related to the radio flux
density and redshift. A study of the physical properties of these sources has
been severely handicapped by the absence of reliable redshift measurements for
many of these objects. This paper presents 79 new redshifts and a critical
evaluation of 233 redshifts obtained from the literature. We classify
spectroscopic identifications based on emission line properties, finding that
78% of the sources have broad emission lines and are mainly FSRQs. About 16%
are weak lined objects, chiefly BL Lacs, and the remaining 6% are narrow line
objects. The gross properties (redshift, spectroscopic class) of the MASIV
sample are similar to those of other blazar surveys. However, the extreme
compactness implied by ISS favors FSRQs and BL Lacs in the MASIV sample as
these are the most compact object classes. We confirm that the level of IDV
depends on the 5\,GHz flux density for all optical spectral types. We find that
BL Lac objects tend to be more variable than broad line quasars. The level of
ISS decreases substantially above a redshift of about two. The decrease is
found to be generally consistent with ISS expected for beamed emission from a
jet that is limited to a fixed maximum brightness temperature in the source
rest frame.


  The correlation energies of various atoms in their excited-states are
estimated by modelling the Coulomb hole following the previous work by
Chakravorty and Clementi. The parameter in the model is fixed by making the
corresponding Coulomb hole to satisfy the exact constraint of charge
neutrality.


  In decentralized finance (DeFi), lenders can offer flash loans to borrowers,
i.e., loans that are only valid within a blockchain transaction and must be
repaid with fees by the end of that transaction. Unlike normal loans, flash
loans allow borrowers to borrow large assets without upfront collaterals
deposits. Malicious adversaries use flash loans to gather large assets to
exploit vulnerable DeFi protocols. In this paper, we introduce a new framework
for automated synthesis of adversarial transactions that exploit DeFi protocols
using flash loans. To bypass the complexity of a DeFi protocol, we propose a
new technique to approximate the DeFi protocol functional behaviors using
numerical methods (polynomial linear regression and nearest-neighbor
interpolation). We then construct an optimization query using the approximated
functions of the DeFi protocol to find an adversarial attack constituted of a
sequence of functions invocations with optimal parameters that gives the
maximum profit. To improve the accuracy of the approximation, we propose a
novel counterexample driven approximation refinement technique. We implement
our framework in a tool named FlashSyn. We evaluate FlashSyn on 16 DeFi
protocols that were victims to flash loan attacks and 2 DeFi protocols from
Damn Vulnerable DeFi challenges. FlashSyn automatically synthesizes an
adversarial attack for 16 of the 18 benchmarks. Among the 16 successful cases,
FlashSyn identifies attack vectors yielding higher profits than those employed
by historical hackers in 3 cases, and also discovers multiple distinct attack
vectors in 10 cases, demonstrating its effectiveness in finding possible flash
loan attacks.


  Through the lens of non-commutative function theory, we examine a
non-selfadjoint variant of the Kadison--Singer problem on extensions of pure
states. More precisely, given a unital subspace $M$ of a $C^*$-algebra $B$, we
aim to characterize those pure states on $M$ admitting a unique extension to a
state on $B$. We find naturally occurring examples where every pure state has
this property. In the more structured setting of a subalgebra $A$ of $B$, we
shed light on the uniqueness of extensions via the existence of excisions in
$A$, in the sense of Akemann--Anderson--Pedersen. Certain non-commutative peak
points, both in the state space and in the representation space of $B$, play a
crucial role in our analysis. In particular, the question of abundance of
non-commutative peak points is addressed.


  With the rapid development of imaging sensor technology in the field of
remote sensing, multi-modal remote sensing data fusion has emerged as a crucial
research direction for land cover classification tasks. While diffusion models
have made great progress in generative models and image classification tasks,
existing models primarily focus on single-modality and single-client control,
that is, the diffusion process is driven by a single modal in a single
computing node. To facilitate the secure fusion of heterogeneous data from
clients, it is necessary to enable distributed multi-modal control, such as
merging the hyperspectral data of organization A and the LiDAR data of
organization B privately on each base station client. In this study, we propose
a multi-modal collaborative diffusion federated learning framework called
FedDiff. Our framework establishes a dual-branch diffusion model feature
extraction setup, where the two modal data are inputted into separate branches
of the encoder. Our key insight is that diffusion models driven by different
modalities are inherently complementary in terms of potential denoising steps
on which bilateral connections can be built. Considering the challenge of
private and efficient communication between multiple clients, we embed the
diffusion model into the federated learning communication structure, and
introduce a lightweight communication module. Qualitative and quantitative
experiments validate the superiority of our framework in terms of image quality
and conditional consistency.


  We calculate the persistent spin current inside a quantum ring as a function
of the strength of the Rashba or Dresselhaus spin-orbit interaction. We provide
analytical results for the spin current of a one-dimensional (1D) ring of
non-interacting electrons for comparison. Furthermore, we calculate the time
evolution in the transient regime of a two-dimensional (2D) quantum ring
connected to electrically biased semi-infinite leads using a
time-convolutionless non-Markovian generalized master equation. In the latter
case, the electrons are correlated via the Coulomb interaction and the ring can
be embedded in a photon cavity with a single mode of linearly polarized photon
field. The electron-electron and electron-photon interactions are described by
exact numerical diagonalization. The photon field can be polarized
perpendicular or parallel to the charge transport. We find a pronounced charge
current dip associated with many-electron level crossings at the
Aharonov-Casher phase $\Delta\Phi=\pi$, which can be disguised by linearly
polarized light. Qualitative agreement is found for the spin currents of the 1D
and 2D ring. Quantatively, however, the spin currents are weaker in the more
realistic 2D ring, especially for weak spin-orbit interaction, but can be
considerably enhanced with the aid of a linearly polarized electromagnetic
field. Specific spin current symmetries relating the Dresselhaus spin-orbit
interaction case to the Rashba one are found to hold for the 2D ring in the
photon cavity.


  Let m>=1 be an arbitrary fixed integer and let N_m(x) count the number of odd
integers u<=x such that the order of 2 modulo u is not divisible by m. In case
m is prime estimates for N_m(x) were given by H. Mueller that were subsequently
sharpened into an asymptotic estimate by the present author. Mueller on his
turn extended the author's result to the case where m is a prime power and gave
bounds in the case m is not a prime power. Here an asymptotic for N_m(x) is
derived that is valid for all integers m. This asymptotic would easily have
followed from Mueller's approach were it not for the fact that a certain
Diophantine equation has non-trivial solutions. All solutions of this equation
are determined. We also generalize to other base numbers than 2. For a very
sparse set of these numbers Mueller's approach does work.


  The anomalous plasmon linewidth dispersion (PLD) measured in K by vom Felde,
Sprosser-Prou, and Fink (Phys. Rev. B 40, 10181 (1989)), has been attributed to
strong dynamical electron-electron correlations. On the basis of ab initio
response calculations, and detailed comparison with experiment, we show that
the PLD of K is, in fact, dominated by decay into particle-hole excitations
involving empty states of d-symmetry. For Li, we shed new light on the physics
of the PLD. Our all-electron results illustrate the importance of ab initio
methods for the study of electronic excitations.


  In this paper, convergence rates of the spectral distributions of quaternion
self-dual Hermitian matrices are investigated. We show that under conditions of
finite 6th moments, the expected spectral distribution of a large quaternion
self-dual Hermitian matrix converges to the semicircular law in a rate of
$O(n^{-1/2})$ and the spectral distribution itself converges to the
semicircular law in rates $O_p(n^{-2/5})$ and $O_{a.s.}(n^{-2/5+\eta})$. Those
results include GSE as a special case.


  The pandemic caused by the SARS-CoV-2 virus has exposed many flaws in the
decision-making strategies used to distribute resources to combat global health
crises. In this paper, we leverage reinforcement learning and optimization to
improve upon the allocation strategies for various resources. In particular, we
consider a problem where a central controller must decide where to send testing
kits to learn about the uncertain states of the world (active learning); then,
use the new information to construct beliefs about the states and decide where
to allocate resources. We propose a general model coupled with a tunable
lookahead policy for making vaccine allocation decisions without perfect
knowledge about the state of the world. The lookahead policy is compared to a
population-based myopic policy which is more likely to be similar to the
present strategies in practice. Each vaccine allocation policy works in
conjunction with a testing kit allocation policy to perform active learning.
Our simulation results demonstrate that an optimization-based lookahead
decision making strategy will outperform the presented myopic policy.


  We rewrite $ N=2$ quantum super $W_{3}$ algebra, a nonlinear extended $N=2$
super Virasoro algebra, containing one additional primary superfield of
dimension $2$ which has no $U(1)$ charge, besides the super stress energy
tensor of dimension $1$ in $N=2$ superspace. The free superfield realization of
this algebra is obtained by two $N=2$ chiral fermionic superfields of dimension
$1/2$ satisfying $N=2$ complex $ U(1)$ Kac-Moody algebras.


  We analyze the influence of $\sigma$ meson exchange on the main nonmesonic
hypernuclear weak decay observables: the total rate, $\Gamma_{NM}$, the
neutron-to-proton branching ratio, $\Gamma_{n/p}$, and the proton asymmetry
parameter, $a_\Lambda$. The $\sigma$ meson exchange is added to the standard
strangeness-changing weak $\Lambda N\to NN$ transition potential, which
includes the exchange of the complete pseudoscalar and vector mesons octet
($\pi$, $\eta$, $K$, $\rho$, $\omega$, $K^*$). Using a shell model formalism,
the $\sigma$ meson weak coupling constants are adjusted to reproduce the recent
$\Gamma_{NM}$ and $\Gamma_{n/p}$ experimental data for $^5_{\Lambda}He$.
Numerical results for the remaining observables of $^5_{\Lambda}He$ and all the
observables of $^{12}_{\Lambda}C$ decays are presented. They clearly show that
the addition of the $\sigma$ meson, in spite of improving some observables
values, is not enough to reproduce simultaneously all the measurements, and the
puzzle posed by the experimental data remains unexplained.


  We take into account dynamical spin effects in the holographic light-front
pion wavefunction in order to predict the pion radius, decay constant, the pion
electromagnetic and photon-to-pion transition form factors. We report a
striking improvement in the description of all data.


  The extended electroweak $\mathrm{SU(3)_c \otimes SU(3)_L \otimes U(1)_X}$
symmetry framework "explaining" the number of fermion families is revisited.
While $331$-based schemes can not easily be unified within the conventional
field theory sense, we show how to do it within an approach based on D-branes
and (un)oriented open strings, on Calabi-Yau singularities. We show how the
theory can be UV-completed in a quiver setup, free of gauge and string
anomalies. Lepton and baryon numbers are perturbatively conserved, so neutrinos
are Dirac-type, and their lightness results from a novel TeV scale seesaw
mechanism. Dynamical violation of baryon number by exotic instantons could
induce neutron-antineutron oscillations, with proton decay and other dangerous
R-parity violating processes strictly forbidden.


  We study Hurewicz fibrations between finite T$_0$--spaces from a
combinatorial viewpoint and give strong conditions that a continuous map
between finite T$_0$--spaces must satisfy in order to be a Hurewicz fibration.
We also show that there exists a strong relationship between Hurewicz
fibrations between finite T$_0$--spaces and Grothendieck bifibrations. Finally
we give several interesting examples that illustrate this theory and show that
many of the assumptions of our results are necessary.


  The conventional GUI is more mechanical and does not recognize or communicate
emotions. The modern GUIs are trying to infer the likely emotional state and
personality of the user and communicate through a corresponding emotional
state.
  Emotions are expressed in graphical icons, sounds, pictures and other means.
The emotions are found to be useful in especially in communication software,
interactive learning systems, robotics and other adaptive environments. Various
mechanisms have been developed to express emotions through graphical user
interfaces. This article illustrates some interesting inventions selected from
US patent database.


  Due to computational requirements and numerical difficulties associated with
coordinate singularity in spherical geometry, fully dynamic 3D
magnetohydrodynamic (MHD) simulations of massive star winds are not readily
available. Here we report preliminary results of the first such a 3D simulation
using $\theta^1$ Ori C (O5.5 V) as a model. The oblique magnetic rotator
$\theta^1$ Ori C is a source of hard X-ray emitting plasma in its circumstellar
environment. Our numerical model can explain both the hardness and the location
of the X-ray emission from this star confirming that magnetically confined wind
shock (MCWS) is the dominating mechanism for hard Xrays in some massive stars.


  Stochastic Bloch equations which model the fluorescence of two level
molecules and atoms, NMR experiments and Josephson junctions are investigated
to illustrate the profound effect of multiplicative noise on the critical
frequency of a dynamical system. Using exact solutions and the cumulant
expansion we find two main effects: (i) even very weak noise may double or
triple the number of critical frequencies, which is related to an instability
of the system and (ii) strong multiplicative noise may induce a non-trivial
zero critical frequency thus wiping out the over-damped phase.


  Emulator is widely used to build dynamic analysis frameworks due to its
fine-grained tracing capability, full system monitoring functionality, and
scalability of running on different operating systemsand architectures.
However, whether the emulator is consistent with real devices is unknown. To
understand this problem, we aim to automatically locate inconsistent
instructions, which behave differently between emulators and real devices.
  We target ARM architecture, which provides machine readable specification.
Based on the specification, we propose a test case generator by designing and
implementing the first symbolic execution engine for ARM architecture
specification language (ASL). We generate 2,774,649 representative instruction
streams and conduct differential testing with these instruction streams between
four ARM real devices in different architecture versions (i.e., ARMv5, ARMv6,
ARMv7-a, and ARMv8-a) and the state-of-the-art emulators (i.e., QEMU). We
locate 155,642 inconsistent instruction streams, which cover 30% of all
instruction encodings and 47.8% of the instructions. We find undefined
implementation in ARM manual and implementation bugs of QEMU are the major
causes of inconsistencies. Furthermore, we discover four QEMU bugs, which are
confirmed and patched by thedevelopers, covering 13 instruction encodings
including the most commonly used ones (e.g.,STR,BLX). With the inconsistent
instructions, we build three security applications and demonstrate
thecapability of these instructions on detecting emulators, anti-emulation, and
anti-fuzzing.


  With the passage of time and as new types of storage devices are introduced
into the marketplace, contemporary devices will slowly lose their compatibility
with current operating systems and PC hardware. As a result, such legacy
devices will pose an analytical challenge to the field of digital forensics.
Dated technology, while still fully functional, is becoming increasingly
incompatible with most contemporary computing hardware and software and thus
cannot be properly examined in present-day digital forensic environments. This
fact will not be lost on those who utilize legacy hardware to commit criminal
acts. This paper describes the technical challenge of accessing legacy devices
by describing an effort to resuscitate a Bernoulli Drive, a portable storage
device manufactured in 1983 by Iomega Corporation. A number of lessons-learned
are provided and the implication of legacy devices to digital forensic science
is discussed.


  Recent CLEO results on electromagnetic and hadronic transitions in charmonium
and bottomonium systems are reviewed.


  Let s(A) denote the number of automorphisms of a model A of power omega_1. We
derive a necessary and sufficient condition in terms of trees for the existence
of an A with omega_1 < s(A) < 2^{omega_1}. We study the sufficiency of some
conditions for s(A)=2^{omega_1}. These conditions are analogous to conditions
studied by D.Kueker in connection with countable models.


  Ancient and medieval harbours connected via navigable and terrestrial routes
could be interpreted as elements of complex traffic networks. Based on evidence
from three projects in Priority Programme 1630 (Fossa Carolina, Inland harbours
in Central Europe and Byzantine harbours on the Balkan coasts) we present a
pioneer study to apply concepts and tools of network theory on archaeological
and on written evidence as well as to integrate this data into different
network models. Our diachronic approach allows for an analysis of the temporal
and spatial dynamics of webs of connectivity with a focus on the 1st millennium
AD. The combination of case studies on various spatial scales as well as from
regions of inland and maritime navigation (Central Europe respectively the Seas
around the Balkans) allows for the identification of structural similarities
respectively difference between pre-modern traffic systems across Europe. The
contribution is a first step towards further adaptions of tools of network
analysis as an instrument for the connection and comparison of data across the
projects of Priority Programme 1630.


  In this paper, we establish an $\ell^2$ decoupling inequality for the
hypersurface \[\Big\{(\xi_1,...,\xi_{n-1},\xi_1^m+...+\xi_{n-1}^m):
(\xi_1,...,\xi_{n-1}) \in [0,1]^{n-1}\Big\}\]associated with the decomposition
adapted to hypersufaces of finite type, where $n\geq 2$ and $m\geq 4$ is an
even number. The key ingredients of the proof include an $\ell^2$ decoupling
inequality for the hypersurfaces
  \[\Big\{(\xi_1,...,\xi_{n-1},\phi_1(\xi_1)+...+\phi_s(\xi_s)+\xi_{s+1}^m+...+\xi_{n-1}^m):
(\xi_1,...,\xi_{n-1}) \in [0,1]^{n-1}\Big\},\] $0 \leq s \leq n-1$, with
$\phi_1,...,\phi_s$ being $m$-nondegenerate.


  We study the essential dimension and essential p-dimension of the moduli
stack of vector bundles over a smooth orbifold curve containing a rational
point. We improve the known bounds on this essential dimension and obtain an
equality modulo the famous conjecture of Colliot-Thelene, Karpenko and
Merkurjev. In the case of essential p-dimension we obtain an equality.


  At a formal level, there appears to be no difficulty involved in introducing
a chemical potential for a globally conserved quantum number into the partition
function for space-time including a black hole. Were this possible, however, it
would provide a form of black hole hair, and contradict the idea that global
quantum numbers are violated in black hole evaporation. We demonstrate
dynamical mechanisms that negate the formal procedure, both for topological
charge (Skyrmions) and complex scalar-field charge. Skyrmions collapse to the
horizon; scalar-field charge fluctuates uncontrollably.


  We develop and analyze several different second-order algorithms for
computing a near-optimal solution path of a convex parametric optimization
problem with smooth Hessian. Our algorithms are inspired by a differential
equation perspective on the parametric solution path and do not rely on the
specific structure of the objective function. We present computational
guarantees that bound the oracle complexity to achieve a near-optimal solution
path under different sets of smoothness assumptions. Under the assumptions, the
results are an improvement over the best-known results of the grid search
methods. We also develop second-order conjugate gradient variants that avoid
exact computations of Hessians and solving of linear equations. We present
computational results that demonstrate the effectiveness of our methods over
grid search methods on both real and synthetic datasets. On large-scale
problems, we demonstrate significant speedups of the second-order conjugate
variants as compared to the standard versions of our methods.


  RNA duplex stability depends strongly on ionic conditions, and inside cells
RNAs are exposed to both monovalent and multivalent ions. Despite recent
advances, we do not have general methods to quantitatively account for the
effects of monovalent and multivalent ions on RNA stability, and the
thermodynamic parameters for secondary structure prediction have only been
derived at 1M [Na$^+$]. Here, by mechanically unfolding and folding a 20 bp RNA
hairpin using optical tweezers, we study the RNA thermodynamics and kinetics at
different monovalent and mixed monovalent/Mg$^{2+}$ salt conditions. We measure
the unfolding and folding rupture forces and apply Kramers theory to extract
accurate information about the hairpin free energy landscape under tension at a
wide range of ionic conditions. We obtain non-specific corrections for the free
energy of formation of the RNA hairpin and measure how the distance of the
transition state to the folded state changes with force and ionic strength. We
experimentally validate the Tightly Bound Ion model and obtain values for the
persistence length of ssRNA. Finally, we test the approximate rule by which the
non-specific binding affinity of divalent cations at a given concentration is
equivalent to that of monovalent cations taken at 100 fold that concentration
for small molecular constructs.


  For $l$-homogeneous linear differential operators $\mathcal{A}$ of constant
rank, we study the implication $v_j\rightharpoonup v$ in $X$ and $\mathcal{A}
v_j\rightarrow \mathcal{A} v$ in $W^{-l}Y$ implies $F(v_j)\rightsquigarrow
F(v)$ in $Z$, where $F$ is an $\mathcal{A}$-quasiaffine function and
$\rightsquigarrow$ denotes an appropriate type of weak convergence. Here $Z$ is
a local $L^1$-type space, either the space $\mathscr{M}$ of measures, or $L^1$,
or the Hardy space $\mathscr{H}^1$; $X,\, Y$ are $L^p$-type spaces, by which we
mean Lebesgue or Zygmund spaces. Our conditions for each choice of $X,\,Y,\,Z$
are sharp. Analogous statements are also given in the case when $F(v)$ is not a
locally integrable function and it is instead defined as a distribution. In
this case, we also prove $\mathscr{H}^p$-bounds for the sequence $(F(v_j))_j$,
for appropriate $p<1$, and new convergence results in the dual of H\"older
spaces when $(v_j)$ is $\mathcal{A}$-free and lies in a suitable negative order
Sobolev space $W^{-\beta,s}$. The choice of these H\"older spaces is sharp, as
is shown by the construction of explicit counterexamples. Some of these results
are new even for distributional Jacobians.


  The best current methods for exactly computing the number of satisfying
assignments, or the satisfying probability, of Boolean formulas can be seen,
either directly or indirectly, as building 'decision-DNNF' (decision
decomposable negation normal form) representations of the input Boolean
formulas. Decision-DNNFs are a special case of 'd-DNNF's where 'd' stands for
'deterministic'. We show that any decision-DNNF can be converted into an
equivalent 'FBDD' (free binary decision diagram) -- also known as a 'read-once
branching program' (ROBP or 1-BP) -- with only a quasipolynomial increase in
representation size in general, and with only a polynomial increase in size in
the special case of monotone k-DNF formulas. Leveraging known exponential lower
bounds for FBDDs, we then obtain similar exponential lower bounds for
decision-DNNFs which provide lower bounds for the recent algorithms. We also
separate the power of decision-DNNFs from d-DNNFs and a generalization of
decision-DNNFs known as AND-FBDDs. Finally we show how these imply exponential
lower bounds for natural problems associated with probabilistic databases.


  Density functional theory was used to study the nonmagnetic (NM) and
ferromagnetic (FM) phases of face-centered cubic cerium. Functionals of four
levels of approximations for the exchange-correlation energy were used: LDA,
PBE, LDA/PBE+$U$, and YS-PBEh. The latter two contain an adjustable parameter,
the onsite Coulomb repulsion parameter $U$ for LDA/PBE+$U$ and the fraction
$\alpha_x$ of Hartree-Fock exchange for YS-PBEh, which were varied in order to
study their influence on the results. By supposing that, as a first
approximation, the NM and FM solutions can be identified to the observed
$\alpha$ and $\gamma$ phases, respectively, it is concluded that while a small
value of $U$ or $\alpha_x$ leads to the correct trend for the stability
ordering of the two phases, larger values are necessary for a more appropriate
(but still not satisfying) description of the electronic structure.


  In simulations of compressible flows, the conservative finite difference
method (FDM) based on the nonlinear upwind schemes, e.g. WENO5, might violate
free-stream preserving (FP), due to the loss of the geometric conservation law
(GCL) identity when applied on the curvilinear grids. Although some techniques
on FP have been proposed previously, no general rule is given for this issue.
In this paper, by rearranging the upwind dissipation of the nonlinear schemes
as a combination of sub-stencil reconstructions (taking WENO5 as an example),
it can be proved that the upwind dissipation diminishes under the uniform flow
condition if the metrics yield an identical value under the same schemes with
these reconstructions, making the free-stream condition be preserved. According
to this sufficient condition, the novel FP metrics are constructed for WENO5
and WENO7. By this means the original forms of these WENO schemes can be kept.
In addition, the accuracy of these schemes can be retained as well with a
simple accuracy compensation by replacing the central part fluxes with a
high-order one. Various validations indicate that the present FP schemes retain
the great capability to resolve the smooth regions accurately and capture the
discontinuities robustly.


  We aim to develop an AI agent that can watch video clips and have a
conversation with human about the video story. Developing video understanding
intelligence is a significantly challenging task, and evaluation methods for
adequately measuring and analyzing the progress of AI agent are lacking as
well. In this paper, we propose the Video Turing Test to provide effective and
practical assessments of video understanding intelligence as well as
human-likeness evaluation of AI agents. We define a general format and
procedure of the Video Turing Test and present a case study to confirm the
effectiveness and usefulness of the proposed test.


  Topological insulators have gapless states at their boundaries while trivial
insulators generically do not. We consider loops in the spaces of Hamiltonians
of topologically trivial Bloch insulators, and show that there exist loops for
which the boundary gap must necessarily close at some point or points along the
loop. We show that some of these loops may be regarded, depending on the
symmetry class of the insulator and its physical dimension, as defining pumps
of charge, fermion parity, and in more exotic cases of other quantities such as
a $Z_2$ parity.


  This article summarizes the basic facts and ideas concerning the formation
and evolution of cataclysmic variables (CVs). It is shown why the formation of
CVs must involve huge losses of mass and orbital angular momentum, very likely
via a common envelope evolution. A brief discussion of the principles of the
long-term evolution of semi-detached binaries follows. Finally a brief sketch
of CV evolution is given.


  In domains like automotive, safety-critical features are increasingly
realized by software. Some features might even require fail-operational
behavior, so that they must be provided even in the presence of random hardware
failures. A new fault-tolerant SW/HW architecture for electric vehicles
provides inherent safety capabilities that enable fail-operational features. In
this paper we introduce a formal model of this architecture and an approach to
calculate valid deployments of mixed-critical software-components to the
execution nodes, while ensuring fail-operational behavior of certain
components. Calculated redeployments cover the cases in which faulty execution
nodes have to be isolated. This allows to formally analyze which set of
features can be provided under decreasing available execution resources.


  Isomonodromic deformations are nothing but symmetries of the Zakharov-Shabat
(isospectral) hierarchy, both the basic ones (belonging to the hierarchy) and
additional, restricted to the submanifold of solutions to the string equation.


  A specific asymptotic expansion at large Reynolds numbers (R)for the long
wavelength perturbation of a non stationary anisotropic helical solution of the
force less Navier-Stokes equations (Trkal solutions) is effectively constructed
of the Beltrami type terms through multi scaling analysis. The asymptotic
procedure is proved to be valid for one specific value of the scaling
parameter,namely for the square root of the Reynolds number (R).As a result
large scale structures arise as gradient lines of the energy determined by the
initial conditions for two anisotropic Beltrami flows of the same helicity.The
same intitial conditions determine the boundaries of the vortex-velocity tubes,
containing both streamlines and vortex lines


  We study structural changes of adaptive networks in the co-evolutionary
susceptible-infected-susceptible (SIS) network model along its phase
transition. We clarify to what extent these changes can be used as
early-warning signs for the transition at the critical infection rate
$\lambda_c$ at which the network collapses and the system disintegrates. We
analyze the interplay between topology and node-state dynamics near
criticality. Several network measures exhibit clear maxima or minima close to
the critical threshold that could potentially serve as early-warning signs.
These measures include the $SI$ link density, triplet densities, clustering,
assortativity and the eigenvalue gap. For the $SI$ link density and triplet
densities the maximum is found to originate from the co-existence of two power
laws. Other network quantities, such as the degree, the branching ratio, or the
harmonic mean distance, show scaling with a singularity at $\lambda=0$ and not
at $\lambda_c$, which means that they are incapable of detecting the
transition.


  Spin dynamics in ferromagnetic $p$-(Ga,Mn)As ($x$ = 0.011, $T_{C}$ = 30 K)
has been studied by carefully comparing the decay time of the photo-induced
reflectivity change with the transient behavior of polar Kerr rotation induced
by photo-generated carrier spins with a femtosecond light pulse of various
polarizations. As to the rising process, the rate of Kerr rotation is found
comparable to the generation rate of spin-polarized carriers. For the decay
process, the Kerr rotation and reflectivity signal both show the same decay
rate at above the $T_{C}$, whereas, below the $T_{C}$, the former becomes
slower than the latter. The magnitude of Kerr rotation suggests that 10$^{2}$
Mn spins are revolved by injecting one hole spin. On the basis of these
observations, collective rotation of ferromagnetically coupled Mn spins is
discussed in terms of $p$-$d$ exchange interaction and successive transverse
spin relaxation. Development of another long-lived behavior under external
perpendicular magnetic fields is also disclosed.


  The rapid development and deployment of vehicle technologies offer
opportunities to re-think the way traffic is managed. This paper capitalizes on
vehicle connectivity and proposes an economic instrument and corresponding
cooperative framework for allocating priority at intersections. The framework
is compatible with a variety of existing intersection control approaches.
Similar to free markets, our framework allows vehicles to trade their time
based on their (disclosed) value of time. We design the framework based on
transferable utility games, where winners (time buyers) pay losers (time
sellers) in each game. We conduct simulation experiments of both isolated
intersections and an arterial setting. The results show that the proposed
approach benefits the majority of users when compared to other mechanisms both
ones that employ an economic instrument and ones that do not. We also show that
it drives travelers to estimate their value of time correctly, and it naturally
dissuades travelers from attempting to cheat.


  This paper considers the problem of fault detection and localization in
active distribution networks using PMUs. The proposed algorithm consists in
computing a set of weighted least squares state estimates whose results are
used to detect, characterize and localize the occurrence of a fault. Moreover,
a criteria to minimize the number of PMUs required to correctly perform the
proposed algorithm is defined. Such a criteria, based on system observability
conditions, allows the design of an optimization problem to set the positions
of PMUs along the grid, in order to get the desired fault localization
resolution. The performances of the strategy are tested via simulations on a
benchmark distribution system.


  Thermal rectification and negative differential thermal conductance were
realized in harmonic chains in this work. We used the generalized
Caldeira-Leggett model to study the heat flow. In contrast to the most previous
studies considering only the linear system-bath coupling, we considered the
nonlinear system-bath coupling based on recent experiment [A. Eichler \emph{et
al.}, Nat. Nanotech. \textbf{6}, 339 (2011)]. When the linear coupling constant
is weak, the multiphonon processes induced by the nonlinear coupling allow more
phonons transport across the system-bath interface and hence the heat current
is enhanced. Consequently, thermal rectification and negative differential
thermal conductance are achieved when the nonlinear couplings are asymmetric.
However, when the linear coupling constant is strong, the umklapp processes
dominate the multiphonon processes. Nonlinear coupling suppresses the heat
current. Thermal rectification is also achieved. But the direction of
rectification is reversed comparing to the results of weak linear coupling
constant.


  This paper presents the first time series clustering benchmark utilizing all
time series datasets currently available in the University of California
Riverside (UCR) archive -- the state of the art repository of time series data.
Specifically, the benchmark examines eight popular clustering methods
representing three categories of clustering algorithms (partitional,
hierarchical and density-based) and three types of distance measures
(Euclidean, dynamic time warping, and shape-based). We lay out six restrictions
with special attention to making the benchmark as unbiased as possible. A
phased evaluation approach was then designed for summarizing dataset-level
assessment metrics and discussing the results. The benchmark study presented
can be a useful reference for the research community on its own; and the
dataset-level assessment metrics reported may be used for designing evaluation
frameworks to answer different research questions.


  Using vertical and complete lifts, any left invariant Riemannian metric on a
Lie group induces a left invariant Riemannian metric on the tangent Lie group.
In the present article we study the Riemannian geometry of tangent bundle of
two families of Lie groups. The first one is the family of special Lie groups
considered by J. Milnor and the second one is the class of Lie groups with
one-dimensional commutator groups. The Levi-Civita connection, sectional and
Ricci curvatures have been investigated.


  In order to study the temperature dependence of the quark-hadron phase
structure and the QCD equation of state in vanishing and finite magnetic field,
the SU(3) Polyakov linear-sigma model is utilized. In mean field approximation,
the dependence of various magnetic properties such as magnetization, magnetic
susceptibility and magnetic catalysis is analyzed in finite magnetic field.
Furthermore, the influences of finite magnetic field on the temperature
dependence of some transport properties (viscosity and conductivity) from
Green-Kubo correlation are characterized.


  Using the SMA and VLA, we have imaged the massive protocluster NGC6334I(N) at
high angular resolution (0.5"~650AU) from 6cm to 0.87mm, detecting 18 new
compact continuum sources. Three of the new sources are coincident with
previously-identified water masers. Together with the previously-known sources,
these data bring the number of likely protocluster members to 25 for a
protostellar density of ~700 pc^-3. Our preliminary measurement of the
Q-parameter of the minimum spanning tree is 0.82 -- close to the value for a
uniform volume distribution. All of the (nine) sources with detections at
multiple frequencies have SEDs consistent with dust emission, and two (SMA1b
and SMA4) also have long wavelength emission consistent with a central
hypercompact HII region. Thermal spectral line emission, including CH3CN, is
detected in six sources: LTE model fitting of CH3CN(J=12-11) yields
temperatures of 72-373K, confirming the presence of multiple hot cores. The
fitted LSR velocities range from -3.3 to -7.0 km/s, with an unbiased mean
square deviation of 2.05 km/s, implying a dynamical mass of 410+-260 Msun for
the protocluster. From analysis of a wide range of hot core molecules, the
kinematics of SMA1b are consistent with a rotating, infalling Keplerian disk of
diameter 800AU and enclosed mass of 10-30 Msun that is perpendicular (within 1
degree) to the large-scale bipolar outflow axis. A companion to SMA1b at a
projected separation of 0.45" (590AU; SMA1d), which shows no evidence of
spectral line emission, is also confirmed. Finally, we detect one 218.440GHz
and several 229.7588GHz Class-I methanol masers.


  In this paper, we compute the conjugacy classes and the list of irreducible
characters of GSp(4,q), where q is odd. We also determine precisely which
irreducible characters are non-cuspidal and which are generic. These characters
are then used to compute dimensions of certain subspaces of fixed vectors of
smooth admissible non-supercuspidal representations of GSp(4,F), where F is a
non-archimedean local field of characteristic zero with residue field of order
q.


  Q-operators for generalised eight vertex models associated to higher spin
representations of the Sklyanin algebra are constructed by Baxter's first
method and Fabricius's method, when the anisotropy parameter is rational.


  Canonical methods are not sufficient to properly quantize space-like axial
gauges. In this paper, we obtain guiding principles which allow the
construction of an extended Hamiltonian formalism for pure space-like axial
gauge fields. To do so, we clarify the general role residual gauge fields play
in the space-like axial gauge Schwinger model. In all the calculations we fix
the gauge using a rule, $n{\cdot}A=0$, where $n$ is a space-like constant
vector and we refer to its direction as $x_-$. Then, to begin with, we
construct a formulation in which the quantization surface is space-like but not
parallel to the direction of $n$. The quantization surface has a parameter
which allows us to rotate it, but when we do so we keep the direction of the
gauge field fixed. In that formulation we can use canonical methods. We
bosonize the model to simplify the investigation. We find that the
antiderivative, $({\partial}_-)^{-1}$, is ill-defined whatever quantization
coordinates we use as long as the direction of $n$ is space-like. We find that
the physical part of the dipole ghost field includes infrared divergences.
However, we also find that if we introduce residual gauge fields in such a way
that the dipole ghost field satisfies the canonical commutation relations, then
the residual gauge fields are determined so as to regularize the infrared
divergences contained in the physical part. The propagators then take the form
prescribed by Mandelstam and Leibbrandt. We make use of these properties to
develop guiding principles which allow us to construct consistent operator
solutions in the pure space-like case where the quantization surface is
parallel to the direction of $n$ and canonical methods do not suffice.


  $ $The usage of generative artificial intelligence (AI) tools based on large
language models, including ChatGPT, Bard, and Claude, for text generation has
many exciting applications with the potential for phenomenal productivity
gains. One issue is authorship attribution when using AI tools. This is
especially important in an academic setting where the inappropriate use of
generative AI tools may hinder student learning or stifle research by creating
a large amount of automatically generated derivative work. Existing plagiarism
detection systems can trace the source of submitted text but are not yet
equipped with methods to accurately detect AI-generated text. This paper
introduces the idea of direct origin detection and evaluates whether generative
AI systems can recognize their output and distinguish it from human-written
texts. We argue why current transformer-based models may be able to self-detect
their own generated text and perform a small empirical study using zero-shot
learning to investigate if that is the case. Results reveal varying
capabilities of AI systems to identify their generated text. Google's Bard
model exhibits the largest capability of self-detection with an accuracy of
94\%, followed by OpenAI's ChatGPT with 83\%. On the other hand, Anthropic's
Claude model seems to be not able to self-detect.


  Large-amplitude molecular motions which occur during isomerization can cause
significant changes in electronic structure. These variations in electronic
properties can be used to identify vibrationally-excited eigenstates which are
localized along the potential energy surface. This work demonstrates that
nuclear quadrupole hyperfine interactions can be used as a diagnostic marker of
progress along the isomerization path in both the HC14N/H14NC and DC15N/D15NC
chemical systems. Ab initio calculations at the CCSD(T)/cc-pCVQZ level indicate
that the hyperfine interaction is extremely sensitive to the chemical bonding
of the quadrupolar 14N nucleus and can therefore be used to determine in which
potential well the vibrational wavefunction is localized. A natural bonding
orbital analysis along the isomerization path further demonstrates that
hyperfine interactions arise from the asphericity of the electron density at
the quadrupolar nucleus. Using the CCSD(T) potential surface, the quadrupole
coupling constants of highly-excited vibrational states are computed from a
one-dimensional internal coordinate path Hamiltonian. The excellent agreement
between ab initio calculations and recent measurements demonstrates that
nuclear quadrupole hyperfine structure can be used as a diagnostic tool for
characterizing localized HCN and HNC vibrational states.


  Learning control from pixels is difficult for reinforcement learning (RL)
agents because representation learning and policy learning are intertwined.
Previous approaches remedy this issue with auxiliary representation learning
tasks, but they either do not consider the temporal aspect of the problem or
only consider single-step transitions, which may cause learning inefficiencies
if important environmental changes take many steps to manifest. We propose
Hierarchical $k$-Step Latent (HKSL), an auxiliary task that learns multiple
representations via a hierarchy of forward models that learn to communicate and
an ensemble of $n$-step critics that all operate at varying magnitudes of step
skipping. We evaluate HKSL in a suite of 30 robotic control tasks with and
without distractors and a task of our creation. We find that HKSL either
converges to higher or optimal episodic returns more quickly than several
alternative representation learning approaches. Furthermore, we find that
HKSL's representations capture task-relevant details accurately across
timescales (even in the presence of distractors) and that communication
channels between hierarchy levels organize information based on both sides of
the communication process, both of which improve sample efficiency.


  We have undertaken an unprecedentedly large 1.1 millimeter continuum survey
of three nearby star forming clouds using Bolocam at the Caltech Submillimeter
Observatory. We mapped the largest areas in each cloud at millimeter or
submillimeter wavelengths to date: 7.5 sq. deg in Perseus (Paper I), 10.8 sq.
deg in Ophiuchus (Paper II), and 1.5 sq. deg in Serpens with a resolution of
31", detecting 122, 44, and 35 cores, respectively. Here we report on results
of the Serpens survey and compare the three clouds. Average measured angular
core sizes and their dependence on resolution suggest that many of the observed
sources are consistent with power-law density profiles. Tests of the effects of
cloud distance reveal that linear resolution strongly affects measured source
sizes and densities, but not the shape of the mass distribution. Core mass
distribution slopes in Perseus and Ophiuchus (alpha=2.1+/-0.1 and
alpha=2.1+/-0.3) are consistent with recent measurements of the stellar IMF,
whereas the Serpens distribution is flatter (alpha=1.6+/-0.2). We also compare
the relative mass distribution shapes to predictions from turbulent
fragmentation simulations. Dense cores constitute less than 10% of the total
cloud mass in all three clouds, consistent with other measurements of low
star-formation efficiencies. Furthermore, most cores are found at high column
densities; more than 75% of 1.1 mm cores are associated with Av>8 mag in
Perseus, 15 mag in Serpens, and 20-23 mag in Ophiuchus.


  We show that contrary to appearances, Multimodal Type Theory (MTT) over a
2-category M can be interpreted in any M-shaped diagram of categories having,
and functors preserving, M-sized limits, without the need for extra left
adjoints. This is achieved by a construction called "co-dextrification" that
co-freely adds left adjoints to any such diagram, which can then be used to
interpret the "context lock" functors of MTT. Furthermore, if any of the
functors in the diagram have right adjoints, these can also be internalized in
type theory as negative modalities in the style of FitchTT. We introduce the
name Multimodal Adjoint Type Theory (MATT) for the resulting combined general
modal type theory. In particular, we can interpret MATT in any finite diagram
of toposes and geometric morphisms, with positive modalities for inverse image
functors and negative modalities for direct image functors.


  Decentralized recommender system does not rely on the central service
provider, and the users can keep the ownership of their ratings. This article
brings the theoretically well-studied matrix factorization method into the
decentralized recommender system, where the formerly prevalent algorithms are
heuristic and hence lack of theoretical guarantee. Our preliminary simulation
results show that this method is promising.


  We give explicit formulas for the first few coefficients of the
Alekseev-Torossian associator and a second Drinfeld associator. This is done by
analyzing the free and transitive action of the Grothendieck-Teichm\"uller
group and its Lie algebra $\mathfrak{grt}_1$ on the set of Drinfeld
associators. As a result we obtain that, up to a conjecture on multiple zeta
values, both associators are not rational.


  We discuss the results of computer model for the thermal emissivity of a
three-dimensional photonic band gap (PBG) crystal, specifically an inverted
opal structure. The thermal emittance for a range of frequencies and angles is
calculated.


  A rooted phylogenetic network is a directed acyclic graph with a single root,
whose sinks correspond to a set of species. As such networks are useful for
representing the evolution of species that have undergone reticulate evolution,
there has been great interest in developing the theory behind and algorithms
for constructing them. However, unlike evolutionary trees, these networks can
be highly non-planar, which can make them difficult to visualise and interpret.
Here we investigate properties of planar rooted phylogenetic networks and
algorithms for deciding whether or not rooted networks have certain special
planarity properties. In particular, we introduce three natural subclasses of
planar rooted phylogenetic networks and show that they form a hierarchy. In
addition, for the well-known level-k networks, we show that level-1, -2, -3
networks are always outer, terminal, and upward planar, respectively, and that
level-4 networks are not necessarily planar. Finally, we show that a regular
network is terminal planar if and only if it is pyramidal. Our results make use
of the highly developed field of planar digraphs, and we believe that the link
between phylogenetic networks and planar graphs should prove useful in future
for developing new approaches to both construct and visualise phylogenetic
networks.


  We solve N=(8,8) super Yang-Mills theory in 1+1 dimensions at strong coupling
to directly confirm the predictions of supergravity at weak coupling. We do our
calculations in the large-N_c approximation using Supersymmetric Discrete
Light-Cone Quantization with up to 3*10^{12} basis states. We calculate the
stress-energy correlator <T^{++}(r) T^{++}(0)> as a function of the separation
r and find that at intermediate values of r the correlator behaves as r^{-5} to
within errors as predicted by weak-coupling supergravity. We also present an
extension to significantly higher resolution of our earlier results for the
same correlator in the N=(2,2) theory and see that in this theory the
correlator has very different behavior at intermediate values of r.


  This note is an addendum to the paper `Global pluripotential theory over a
trivially valued field' by the present authors, in which we prove two results.
Let $X$ be an irreducible projective variety over an algebraically closed field
field $k$, and assume that $k$ has characteristic zero, or that $X$ has
dimension at most two. We first prove that when $X$ is smooth, the envelope
property holds for any numerical class on $X$. Then we prove that for $X$
possibly singular and for an ample numerical class, the Monge--Amp\`ere energy
of a bounded function is equal to the energy of its usc regularized
plurisubharmonic envelope.


  Exploiting multi-scale representations is critical to improve edge detection
for objects at different scales. To extract edges at dramatically different
scales, we propose a Bi-Directional Cascade Network (BDCN) structure, where an
individual layer is supervised by labeled edges at its specific scale, rather
than directly applying the same supervision to all CNN outputs. Furthermore, to
enrich multi-scale representations learned by BDCN, we introduce a Scale
Enhancement Module (SEM) which utilizes dilated convolution to generate
multi-scale features, instead of using deeper CNNs or explicitly fusing
multi-scale edge maps. These new approaches encourage the learning of
multi-scale representations in different layers and detect edges that are well
delineated by their scales. Learning scale dedicated layers also results in
compact network with a fraction of parameters. We evaluate our method on three
datasets, i.e., BSDS500, NYUDv2, and Multicue, and achieve ODS Fmeasure of
0.828, 1.3% higher than current state-of-the art on BSDS500. The code has been
available at https://github.com/pkuCactus/BDCN.


  Optical frequency comb generation in microresonators has attracted
significant attention over the past decade, as it offers the promising
potential for chip-scale optical frequency synthesis, optical clocks and
precise optical spectroscopy. However, accessing temporal dissipative Kerr
soliton (DKSs) is known to be severely hampered by thermal effects.
Furthermore, due to the degeneracy of soliton existence range with respect to
soliton number, deterministically accessing single soliton state is another
challenge. Here, we demonstrate stable and deterministic single soliton
generation in AlN-on-sapphire platform via auxiliary laser pumping scheme
without the requirement of fast control of the pump power and detuning.
Moreover, we reveal the underlying physics of soliton switching in a
dual-pumped microcomb, which is fully described by the Lugiato - Lefever
equation. The switching process is attributed to cross-phase modulation (XPM)
induced degeneracy lifting of the soliton existence range, corresponding to an
effective negative thermo-optic effect.


  Motivated by the search for potentially exactly solvable time-dependent
string backgrounds, we determine all homogeneous plane wave (HPW) metrics in
any dimension and find one family of HPWs with geodesically complete metrics
and another with metrics containing null singularities. The former generalises
both the Cahen-Wallach (constant $A_{ij}$) metrics to time-dependent HPWs,
$A_{ij}(t)$, and the Ozsvath-Sch\"ucking anti-Mach metric to arbitrary
dimensions. The latter is a generalisation of the known homogeneous metrics
with $A_{ij}\sim 1/t^2$ to a more complicated time-dependence. We display these
metrics in various coordinate systems, show how to embed them into string
theory, and determine the isometry algebra of a general HPW and the associated
conserved charges. We review the Lewis-Riesenfeld theory of invariants of
time-dependent harmonic oscillators and show how it can be deduced from the
geometry of plane waves. We advocate the use of the invariant associated with
the extra (timelike) isometry of HPWs for lightcone quantisation, and
illustrate the procedure in some examples.


  Entropy is a natural geometric quantity measuring the complexity of a surface
embedded in $\mathbb{R}^3$. For dynamical reasons relating to mean curvature
flow, Colding-Ilmanen-Minicozzi-White conjectured that the entropy of any
closed surface is at least that of the self-shrinking two-sphere. We prove this
conjecture for all closed embedded $2$-spheres. Assuming a conjectural Morse
index bound (announced recently by Marques-Neves), we can improve the result to
apply to all closed embedded surfaces that are not tori. Our results can be
thought of as the parabolic analog to the Willmore conjecture and our argument
is analogous in many ways to that of Marques-Neves on the Willmore problem. The
main tool is the min-max theory applied to the Gaussian area functional in
$\mathbb{R}^3$ which we also establish. To any closed surface in $\mathbb{R}^3$
we associate a four parameter canonical family of surfaces and run a min-max
procedure. The key step is ruling out the min-max sequence approaching a
self-shrinking plane, and we accomplish this with a degree argument. To
establish the min-max theory for $\mathbb{R}^3$ with Gaussian weight, the
crucial ingredient is a tightening map that decreases the mass of
non-stationary varifolds (with respect to the Gaussian metric of
$\mathbb{R}^3$) in a continuous manner.


  This project aims to study the feasibility and cost-effectiveness of using
edge computing for stream data processing in the context of Internet of Things
(IoT) in manufacturing in Europe. Two scenarios were considered: using edge
computing to reduce latency and using a popular public cloud provider. Both
scenarios demonstrated high throughput, with the edge computing scenario
slightly outperforming the public cloud scenario. The impact on resource
utilization was also measured, with the edge node showing slightly lower
resource usage than the cloud node. The experiment concluded that running the
system at the edge is more cost-efficient, but only using any Infrastructure as
a Service (IaaS) provider acting as the infrastructure provider. IaaS providers
will be crucial in offering edge solutions and identifying geographical areas
where regional data centers could be used as points of presence for low-latency
applications.
  Keywords: edge computing, stream data processing, Internet of Things (IoT),
manufacturing, Europe, latency, throughput, resource utilization,
cost-efficiency, infrastructure as a service (IaaS), regional data centers,
low-latency applications, cloud computing, feasibility study.


  Recent results in the literature indicate that artificial neural networks
(ANNs) can outperform the dynamic factor model (DFM) in terms of the accuracy
of GDP nowcasts. Compared to the DFM, the performance advantage of these highly
flexible, nonlinear estimators is particularly evident in periods of recessions
and structural breaks. From the perspective of policy-makers, however, nowcasts
are the most useful when they are conveyed with uncertainty attached to them.
While the DFM and other classical time series approaches analytically derive
the predictive (conditional) distribution for GDP growth, ANNs can only produce
point nowcasts based on their default training procedure (backpropagation). To
fill this gap, first in the literature, we adapt two different deep learning
algorithms that enable ANNs to generate density nowcasts for U.S. GDP growth:
Bayes by Backprop and Monte Carlo dropout. The accuracy of point nowcasts,
defined as the mean of the empirical predictive distribution, is evaluated
relative to a naive constant growth model for GDP and a benchmark DFM
specification. Using a 1D CNN as the underlying ANN architecture, both
algorithms outperform those benchmarks during the evaluation period (2012:Q1 --
2022:Q4). Furthermore, both algorithms are able to dynamically adjust the
location (mean), scale (variance), and shape (skew) of the empirical predictive
distribution. The results indicate that both Bayes by Backprop and Monte Carlo
dropout can effectively augment the scope and functionality of ANNs, rendering
them a fully compatible and competitive alternative for classical time series
approaches.


  Many biological tissues are viscoelastic, behaving as elastic solids on short
timescales and fluids on long timescales. This collective mechanical behavior
enables and helps to guide pattern formation and tissue layering. Here we
investigate the mechanical properties of three-dimensional tissue explants from
zebrafish embryos by analyzing individual cell tracks and macroscopic
mechanical response. We find that the cell dynamics inside the tissue exhibit
features of supercooled fluids, including subdiffusive trajectories and
signatures of caging behavior. We develop a minimal, three-parameter mechanical
model for these dynamics, which we calibrate using only information about cell
tracks. This model generates predictions about the macroscopic bulk response of
the tissue (with no fit parameters) that are verified experimentally, providing
a strong validation of the model. The best-fit model parameters indicate that
although the tissue is fluid-like, it is close to a glass transition,
suggesting that small changes to single-cell parameters could generate a
significant change in the viscoelastic properties of the tissue. These results
provide a robust framework for quantifying and modeling mechanically-driven
pattern formation in tissues.


  [Background] Neutrino-induced single-pion production (SPP) provides an
important contribution to neutrino-nucleus interactions, ranging from
intermediate to high energies. There exists a good number of low-energy models
in the literature to describe the neutrinoproduction of pions in the region
around the Delta resonance. Those models consider only lowest-order interaction
terms and, therefore, fail in the high-energy region (pion-nucleon invariant
masses, $W$>2 GeV).
  [Purpose] Our goal is to develop a model for electroweak SPP off the nucleon,
which is applicable to the entire energy range of interest for present and
future neutrino-oscillation experiments.
  [Method] We start with the low-energy model of [Phys.Rev.D76,033005(2007)],
which includes resonant contributions and background terms derived from the
pion-nucleon Lagrangian of chiral-perturbation theory. Then, from the
background contributions, we build a high-energy model using a Regge approach.
The low- and high-energy models are combined, in a phenomenological way, into a
hybrid model.
  [Results] The Hybrid model is identical to the low-energy model in the low-W
region, but, for W>2 GeV, it implements the desired high-energy behavior
dictated by Regge theory. We have tested the high-energy model by comparing
with one-pion production data from electron and neutrino reactions. The Hybrid
model is compared with electron-proton scattering data, with neutrino SPP data
and with the predictions of the NuWro Monte Carlo event generator.
  [Conclusions] Our model is able to provide satisfactory predictions of the
electroweak one-pion production cross section from pion threshold to high $W$.
Further investigation and more data are needed to better understand the
mechanisms playing a role in the electroweak SPP process in the high-W region,
in particular, those involving the axial current contributions.


  Amongst the many hundreds of transiting planet candidates discovered by the
Kepler Mission, one finds a large number of candidates with sizes between that
of the Earth and Neptune. The composition of these worlds is not immediately
obvious with no Solar System analog to draw upon and there exists some
ambiguity as to whether a given candidate is a rocky Super-Earth or a
gas-enveloped Mini-Neptune. The potential scientific value and observability of
the atmospheres of these two classes of worlds varies significantly and given
the sheer number of candidates in this size-range, there is evidently a need
for a quick, simple metric to rank whether the planets have an extended
atmosphere or not. In this work, we propose a way to calculate the 'minimum
atmospheric height' (R_MAH) using only a planet's radius and mass as inputs. We
assume and exploit the boundary condition that the bulk composition of a
solid/liquid Super-Earth cannot be composed of a material lighter than that of
water. Mass-radius loci above a pure-water composition planet correspond to
R_MAH>0. The statistical confidence of a planet maintaining an extended
atmosphere can be therefore easily calculated to provide a simple ranking of
target planets for follow-up observations. We also discuss how this metric can
be useful in the interpretation of the spectra of observed planetary
atmospheres.


  In this work, we deal with a notion of partially hyperbolic endomorphism. We
explore topological properties of this definition and we obtain, among other
results, obstructions to get center leaf conjugacy with the linear part, for a
class of partially hyperbolic endomorphism $C^1-$sufficiently close to a
hyperbolic linear endomorphism. Indeed such obstructions are related to the
number of center directions of a point. We provide examples illustrating these
obstructions. We show that for a manifold $M$ with dimension $n \geq 3,$
admitting a non-invertible partially hyperbolic endomorphisms, there is a $C^1$
open and dense subset $\mathcal{U}$ of all partially hyperbolic endomorphisms
with degree $d \geq n,$ such that any $f \in \mathcal{U}$ is neither $c$ nor
$u$ special.


  Residential segregation recently has shifted to more class or income-based in
the United States, and neighborhoods are undergoing significant changes such as
commuting patterns over time. To better understand the commuting inequality
across neighborhoods of different income levels, this research analyzes
commuting variability (in both distance and time) across wage groups as well as
stability over time using the CTPP data 1990-2010 in Baton Rouge. In comparison
to previous work, commuting distance is estimated more accurately by Monte
Carlo simulation of individual trips to mitigate aggregation error and scale
effect. The results based on neighborhoods mean wage rate indicate that
commuting behaviors vary across areas of different wage rates and such
variability is captured by a convex shape. Affluent neighborhoods tended to
commute more but highest-wage neighborhoods retreated for less commuting. This
trend remains relatively stable over time despite an overall transportation
improvement in general. A complementary analysis based on the distribution of
wage groups is conducted to gain more detailed insights and uncovers the
lasting poor mobility (e.g., fewer location and transport options) of the
lowest-wage workers in 1990-2010.


  We prove that any set-theoretic solution of the Yang-Baxter equation
associated to a dual weak brace is a strong semilattice of non-degenerate
bijective solutions. This fact makes use of the description of any dual weak
brace $S$ we provide in terms of strong semilattice $Y$ of skew braces
$B_\alpha$, with $\alpha \in Y$. Additionally, we describe the ideals of $S$
and study its nilpotency by correlating it to that of each skew brace
$B_\alpha$.


  In this paper, we study topological phase transition in a wire medium
operating at infrared frequencies. This transition occurs in the reciprocal
space between the indefinite (open-surface) regime of the metamaterial to its
dielectric (closed-surface) regime. Due to the spatial dispersion inherent to
wire medium, a hybrid regime turns out to be possible at the transition
frequency. Both such surfaces exist at the same frequency and touch one
another. At this frequency, all values of the axial wavevector correspond to
propagating spatial harmonics. The implication of this regime is the
overwhelming radiation enhancement. We numerically investigated the gain in
radiated power for a sub-wavelength dipole source submerged into such the
medium. In contrast to all previous works, this gain (called the Purcell
factor) turns out to be higher for an axial dipole than for a transversal one.


  By bosonizing the electronic t-J model exactly on any two-dimensional (2D)
lattices, and integrating out the gauge fluctuations combined to slave
particles beyond mean fields, we get a theory in terms of physical Cooper pair
and spin condensates. In the sense of mutual Berry phase they turns out to be
dual to each other. The mutual-duality is the missing key in the
resonant-valance-bond idea\cite{rvb} to work as a paradigm of doped 2D Mott
insulators. We argue that essential aspects of high-$T_c$ phenomenology find
natural solutions in the theory. We also provide interesting predictions for
systems on hexagonal lattices.


  The world population is projected to rapidly age over the next 30 years.
Given the increasing digital technology adoption amongst older adults,
researchers have investigated how technology can support aging populations.
However, little work has examined how technology can support older adults
during crises, despite increasingly common natural disasters, public health
emergencies, and other crisis scenarios in which older adults are especially
vulnerable. Addressing this gap, we conducted focus groups with older adults
residing in coastal locations to examine to what extent they felt technology
could support them during emergencies. Our findings characterize participants'
desire for tools that enhance community resilience-local knowledge,
preparedness, community relationships, and communication, that help communities
withstand disasters. Further, older adults' crisis technology preferences were
linked to their sense of control, social relationships, and digital readiness.
We discuss how a focus on community resilience can yield crisis technologies
that more effectively support older adults.


  The main features of the convolution model which, in the region of
two-nucleon (2N) and three-nucleon (3N) short-range correlations (SRC),
describes the one-nucleon momentum distribution n(k_1) and the spectral
function P(k_1,E) in terms of a convolution integral involving the relative
n_{rel}(k_{rel}) and the center-of-mass n_{c.m.}(K_{c.m.}) momentum
distributions of a nucleon-nucleon pair, are illustrated in detail. It is
stressed that the model, which stems from the universal property of
factorization exhibited by the nuclear wave function at short inter-nucleon
distances, is only applicable in a well-defined region of k_{rel} and K_{c.m.};
it is shown, in particular, that the requirement of factorization introduces a
severe constraint on the values of k_{rel} and K_{c.m.} that appear in the
convolution integral. Using ab-initio relative and c.m. momentum distributions
for ^3He, the validity of the convolution model is investigated by comparing
the model spectral function and momentum distributions with the ones resulting
from ab-initio calculations performed with realistic local NN interaction of
the Argonne family. It is shown that when the constraint on the value of
k_{rel} and K_{c.m.} are correctly taken into account and only 2N SRC are taken
into account, the convolution model is in good agreement with the ab-initio
spectral function in the region of the peak exhibited by the latter, whereas
far from the peak, particularly at high values of the removal energy, the model
spectral function can be qualitatively reconciled with the ab-initio spectral
function only by considering the effects of 3N SRC. As for the nucleon momentum
distribution, the effects of 3N SRC appears to be very small.


  We address the approximation of functionals depending on a system of
particles, described by stochastic differential equations (SDEs), in the
mean-field limit when the number of particles approaches infinity. This problem
is equivalent to estimating the weak solution of the limiting McKean-Vlasov
SDE. To that end, our approach uses systems with finite numbers of particles
and a time-stepping scheme. In this case, there are two discretization
parameters: the number of time steps and the number of particles. Based on
these two parameters, we consider different variants of the Monte Carlo and
Multilevel Monte Carlo (MLMC) methods and show that, in the best case, the
optimal work complexity of MLMC, to estimate the functional in one typical
setting with an error tolerance of $\mathrm{TOL}$, is $\mathcal
O\left({\mathrm{TOL}^{-3}}\right)$ when using the partitioning estimator and
the Milstein time-stepping scheme. We also consider a method that uses the
recent Multi-index Monte Carlo method and show an improved work complexity in
the same typical setting of $\mathcal
O\left(\mathrm{TOL}^{-2}\log(\mathrm{TOL}^{-1})^2\right)$. Our numerical
experiments are carried out on the so-called Kuramoto model, a system of
coupled oscillators.


  In 1974 Allan Cruse provided necessary and sufficient conditions to extend an
$r\times s$ partial latin rectangle consisting of $t$ distinct symbols to a
latin square of order $n$. Here we provide some generalizations and
consequences of this result. Our results are obtained via an alternative proof
of Cruse's theorem.


  Mechanical stability of Ag and Cu printed and evaporated metallization lines
on polymer substrates is investigated by means of monotonic tensile and cyclic
bending tests. It is shown that lines which demonstrate good performance during
monotonic tests fail at lower strains during a cyclic bending tests. Evaporated
lines with the grain size of several hundreds of nanometers have good ductility
and consequently good stability during monotonic loading but at the same time
they fail at low strains during cyclic bending. Printed lines with
nanocrystalline microstructure, in contrast, demonstrate more intensive
cracking during monotonic loading but higher failure strains during cyclic
bending. Apart from the grain size effect, the effect of film thickness on the
saturation crack density after cyclic bending is also demonstrated. Thinner
films have higher crack density in accordance with the shear lag model.


  Standard Federated Learning (FL) techniques are limited to clients with
identical network architectures. This restricts potential use-cases like
cross-platform training or inter-organizational collaboration when both data
privacy and architectural proprietary are required. We propose a new FL
framework that accommodates heterogeneous client architecture by adopting a
graph hypernetwork for parameter sharing. A property of the graph hyper network
is that it can adapt to various computational graphs, thereby allowing
meaningful parameter sharing across models. Unlike existing solutions, our
framework does not limit the clients to share the same architecture type, makes
no use of external data and does not require clients to disclose their model
architecture. Compared with distillation-based and non-graph hypernetwork
baselines, our method performs notably better on standard benchmarks. We
additionally show encouraging generalization performance to unseen
architectures.


  Analytical (rational) mechanics is the mathematical structure of Newtonian
deterministic dynamics developed by D'Alembert, Langrange, Hamilton, Jacobi,
and many other luminaries of applied mathematics. Diffusion as a stochastic
process of an overdamped individual particle immersed in a fluid, initiated by
Einstein, Smoluchowski, Langevin and Wiener, has no momentum since its path is
nowhere differentiable. In this exposition, we illustrate how analytical
mechanics arises in stochastic dynamics from a randomly perturbed ordinary
differential equation $dX_t=b(X_t)dt+\epsilon dW_t$ where $W_t$ is a Brownian
motion. In the limit of vanishingly small $\epsilon$, the solution to the
stochastic differential equation other than $\dot{x}=b(x)$ are all rare events.
However, conditioned on an occurence of such an event, the most probable
trajectory of the stochastic motion is the solution to Lagrangian mechanics
with $\mathcal{L}=\|\dot{q}-b(q)\|^2/4$ and Hamiltonian equations with
$H(p,q)=\|p\|^2+b(q)\cdot p$. Hamiltonian conservation law implies that the
most probable trajectory for a "rare" event has a uniform "excess kinetic
energy" along its path. Rare events can also be characterized by the principle
of large deviations which expresses the probability density function for $X_t$
as $f(x,t)=e^{-u(x,t)/\epsilon}$, where $u(x,t)$ is called a large-deviation
rate function which satisfies the corresponding Hamilton-Jacobi equation. An
irreversible diffusion process with $\nabla\times b\neq 0$ corresponds to a
Newtonian system with a Lorentz force $\ddot{q}=(\nabla\times b)\times
\dot{q}+1/2\nabla\|b\|^2$. The connection between stochastic motion and
analytical mechanics can be explored in terms of various techniques of applied
mathematics, for example, singular perturbations, viscosity solutions, and
integrable systems.


  Within a formulation of $\pi\pi$ scattering, we investigate the use of the
finite-volume Hamiltonian approach to resolving scattering observables from
lattice QCD spectra. We consider spectra in the centre-of-mass and moving
frames for both S- and P-wave cases. Furthermore, we investigate the
multi-channel case. Here we study the use of the Hamiltonian framework as a
parametrization that can be fit directly to lattice spectra. Through this
method, the hadron properties, such as mass, width and coupling, can be
directly extracted from the lattice spectra.


  Let $S$ be a minimal irregular surface of general type, whose Albanese map
induces a hyperelliptic fibration $f:\,S \to B$ of genus $g$.We prove a
quadratic upper bound on the genus $g$, i.e., $g\leq
h\big(\chi(\mathcal{O}_S)\big)$, where $h$ is a quadratic function. We also
construct examples showing that the quadratic upper bounds can not be improved
to the linear ones. In the special case when $p_g(S)=q(S)=1$, we show that
$g\leq 14$.


  In their recent paper, Yan-Xiong Du et al. [Phys. Rev. A 84, 034103 (2011)]
claim to have found a non-Abelian adiabatic geometric phase associated with the
energy eigenstates of a large-detuned $\Lambda$ three-level system. They
further propose a test to detect the non-commutative feature of this geometric
phase. On the contrary, we show that the non-Abelian geometric phase picked up
by the energy eigenstates of a $\Lambda$ system is trivial in the adiabatic
approximation, while, in the exact treatment of the time evolution, this phase
is very small and cannot be separated from the non-Abelian dynamical phase
acquired along the path in parameter space.


  Healthy articular cartilage, covering the ends of bones in major joints such
as hips and knees, presents the most efficiently-lubricated surface known in
nature, with friction coefficients as low as 0.001 up to physiologically high
pressures. Such low friction is indeed essential for its well being. It
minimizes wear-and-tear and hence the cartilage degradation associated with
osteoarthritis, the most common joint disease, and, by reducing shear stress on
the mechanotransductive, cartilage-embedded chondrocytes (the only cell type in
the cartilage), it regulates their function to maintain homeostasis.
Understanding the origins of such low friction of the articular cartilage,
therefore, is of major importance in order to alleviate disease symptoms, and
slow or even reverse its breakdown. This progress report considers the relation
between frictional behavior and the cellular mechanical environment in the
cartilage, then reviews the mechanism of lubrication in the joints, in
particular focusing on boundary lubrication. Following recent advances based on
hydration lubrication, a proposed synergy between different molecular
components of the synovial joints, acting together in enabling the low
friction, has been proposed. Additionally, recent development of natural and of
bio-inspired lubricants is reviewed.


  In this note, we construct an equivalence of $\infty$-categories \[
\mathbf{H}^{\mathrm{fr},\mathrm{gp}}(S) \simeq
\mathbf{H}^{\mathrm{fr},\mathrm{gp}}_{\mathrm{zf}}(S) \] of group-like framed
motivic spaces with respect to the Nisnevich topology and the so-called Zariski
fibre topology generated by the Zariski one and the trivial fibre topology
introduced by Druzhinin, Kolderup, {\O}stv{\ae}r, when $S$ is a separated
noetherian scheme of finite dimension.
  In the base field case the Zariski fibre topology equals the Zariski
topology. For a non-perfect field $k$ an equivalence of $\infty$-categories of
Voevodsky's motives \[\mathbf{DM}(k)\simeq\mathbf{DM}_{\mathrm{zar}}(k)\] is
new already. The base scheme case is deduced from the result over residue
fields using the corresponding localisation theorems. Namely, the localisation
theorem for $\mathbf{H}^{\mathrm{fr},\mathrm{gp}}(S)$ was proved by Hoyois, and
the localisation theorem for
$\mathbf{H}^{\mathrm{fr},\mathrm{gp}}_{\mathrm{zf}}(S)$ is deduced in the
present article from the affine localisation theorem for the trivial fibre
topology proved by Druzhinin, Kolderup, {\O}stw{\ae}r.


  We show that counterexamples of Iyengar and Walker to the algebraic version
of Gunnar Carlsson's conjecture on the rank of the homology of a free complex
can be extended to examples over any finite group with many choices of the
complex.


  In order to provide a better basis for the study of mechanisms of
nucleosynthesis of the light elements beyond hydrogen and helium in the oldest
stars, the abundances of C, O, Mg, Si, P, S, K, and Ca have been derived from
UV-HST and visible-ESO high resolution spectra in the old, very metal-poor star
HD 84937, at a metallicity that is 1/200 that of the Sun's. For this halo
main-sequence turnoff star, the abundance determination of P and S are the
first published determinations. The LTE profiles of the lines were fitted to
the observed spectra. Wherever possible, we corrected the derived abundances
for non-LTE effects. Three-dimensional (3D) CO5BOLD model atmospheres have been
used to determine the abundances of C and O from molecular CH and OH bands. The
abundances of these light elements in HD 84937 are found to agree well with the
abundances in classical metal-poor stars. Our HD 84937 carbon abundance
determination points toward a solar (or mildly enhanced) value of [C/Fe]. The
modest overabundance of the alpha elements of even atomic number Z, typical of
halo turnoff stars, is confirmed in this example. The odd-Z element P is found
to be somewhat deficient in HD 84937, at [P/Fe]=-0.32, which is again
consistent with the handful of existing determinations for turnoff stars of
such low metallicity. We show that the abundance of oxygen, deduced from the OH
band from 3D computations, is not compatible with the abundance deduced from
the red oxygen triplet. This incompatibility is explained by the existence of a
chromosphere heating the shallow layers of the atmosphere where the OH band, in
3D computations, is mainly formed. The abundance ratios are compared to the
predictions of models of galactic nucleosynthesis and evolution


  A long-standing proposition is that by emulating the operation of the brain's
neocortex, a spiking neural network (SNN) can achieve similar desirable
features: flexible learning, speed, and efficiency. Temporal neural networks
(TNNs) are SNNs that communicate and process information encoded as relative
spike times (in contrast to spike rates). A TNN architecture is proposed, and,
as a proof-of-concept, TNN operation is demonstrated within the larger context
of online supervised classification. First, through unsupervised learning, a
TNN partitions input patterns into clusters based on similarity. The TNN then
passes a cluster identifier to a simple online supervised decoder which
finishes the classification task. The TNN learning process adjusts synaptic
weights by using only signals local to each synapse, and clustering behavior
emerges globally. The system architecture is described at an abstraction level
analogous to the gate and register transfer levels in conventional digital
design. Besides features of the overall architecture, several TNN components
are new to this work. Although not addressed directly, the overall research
objective is a direct hardware implementation of TNNs. Consequently, all the
architecture elements are simple, and processing is done at very low precision.


  Sequential projective measurements of non-commuting observables destroy
information about previous measurement outcomes, but weak measurements
conducted over short durations do not cause as much disturbance to the system,
and as a result, memory of previous outcomes may not be entirely eliminated. We
use Quantum State Diffusion to unravel a Lindblad equation, generating
numerical, stochastic trajectories for a spin 1/2 system and a system of two
entangled spin 1/2 subsystems, each undergoing a sequence of measurements of
S_{z} and S_{x} spin observables. The autocorrelation function of completed
S_{z} measurement outcomes for a range of lag times is then found. In a second
set of trajectories, the simulation is terminated if the system reaches the
vicinity of a chosen set of eigenstates of S_{z} and S_{x}: the `terminating
eigenstates', during the respective measurement intervals of the two
observables. From the generated trajectories, the `probability of termination'
that the system will arrive at one of the terminating eigenstates after a
certain number of measurements have been performed, can be calculated, as well
as the mean first passage, which is the number of measurements performed, on
average, before the simulation ends. Results can then be compared with
projective measurement Born rule statistics. We demonstrate that with short and
weak measurements the autocorrelation function of S_{z} can be non-zero for a
range of lag times, while it vanishes for strong, longer duration measurements
in agreement with the Born rule. The probability of termination and the mean
first passage increase under weaker and shorter measurements, revealing that
the system is able to avoid particular eigenstates of S_{z} and S_{x} for
extended periods of time. A bias can develop in favour of a return to the same
eigenstate visited in the previous measurement(s) of a given observable: a
memory effect.


  In the present paper we show how to obtain the well-known formula for Gauss
sums and the Gauss reciprocity low from the Poison summarizing formula by using
some ideas of renormalization and ergodic theories. We also apply our method to
obtain new simple derivation of the standard formula for p-adic Gauss
integrals.


  A group is combable if it can be represented by a language of words
satisfying a fellow traveller property; an automatic group has a synchronous
combing which is a regular language. This article surveys results for combable
groups, in particular in the case where the combing is a formal language.


  Identifying the network-wide forwarding behaviors of a packet is essential
for many network management applications. We present AP Classifier, a control
plane tool for packet be- havior identification. Experiments show that the
processing speed of AP Classifier is faster than existing tools by at least an
order of magnitude. Furthermore, AP Classifier uses very small memory and is
able to support real-time updates. We also present a network function outsource
framework with AP Classifier which can provide security properties.


  We present a class of orthogonal non-regular in a sense of Kalnins and Miller
(hence non-St\"ackel) coordinates which are R-separable in 3-dim. Helmholtz
equation. One family of parametric surfaces consists of parallel Dupin
cyclides, the other two consist of circular cones. This coordinate system is
used to simplify derivation of Friedlander's formulae for a general "simple
progressive solution of the wave equation" (modulated soliton of wave equation)
in $E^3$ and to correct some errors of his paper. The extended version of the
paper will be published soon.


  This paper describes the rapidly evolving and unusual supernova LSQ13ddu,
discovered by the La Silla-QUEST survey. LSQ13ddu displayed a rapid rise of
just 4.8$\pm$0.9 d to reach a peak brightness of $-$19.70$\pm$0.02 mag in the
$\mathit{LSQgr}$ band. Early spectra of LSQ13ddu showed the presence of weak
and narrow He I features arising from interaction with circumstellar material
(CSM). These interaction signatures weakened quickly, with broad features
consistent with those seen in stripped-envelope SNe becoming dominant around
two weeks after maximum. The narrow He I velocities are consistent with the
wind velocities of luminous blue variables but its spectra lack the typically
seen hydrogen features. The fast and bright early light curve is inconsistent
with radioactive $^{56}$Ni powering but can be explained through a combination
of CSM interaction and an underlying $^{56}$Ni decay component that dominates
the later time behaviour of LSQ13ddu. Based on the strength of the underlying
broad features, LSQ13ddu appears deficient in He compared to standard SNe Ib.


  Breast cancer is a common fatal disease for women. Early diagnosis and
detection is necessary in order to improve the prognosis of breast cancer
affected people. For predicting breast cancer, several automated systems are
already developed using different medical imaging modalities. This paper
provides a systematic review of the literature on artificial neural network
(ANN) based models for the diagnosis of breast cancer via mammography. The
advantages and limitations of different ANN models including spiking neural
network (SNN), deep belief network (DBN), convolutional neural network (CNN),
multilayer neural network (MLNN), stacked autoencoders (SAE), and stacked
de-noising autoencoders (SDAE) are described in this review. The review also
shows that the studies related to breast cancer detection applied different
deep learning models to a number of publicly available datasets. For comparing
the performance of the models, different metrics such as accuracy, precision,
recall, etc. were used in the existing studies. It is found that the best
performance was achieved by residual neural network (ResNet)-50 and ResNet-101
models of CNN algorithm.


  New, approximate, two-electron wavefunctions are introduced for the
two-electron atoms (cations), which account remarkably well for the
ground-state energies and the lowest-excxited states (where available). A new
scheme of electronic configurations is also proposed for the multi-electron
atoms.


  We have shown that bilinear conformal mapping can be used to transform 4-lead
internally shunted EMR semiconductor-metal hybrid structures to
galvanomagnetically equivalent externally shunted 4 lead structures. The latter
are compatible with the fabrication of nanoscale EMR devices while the former
are not. Mapped rectangular EMR van der Pauw plate exhibit very large EMR
values in both macroscopic and nanoscopic form. We have also shown that the
mapping procedure applied in the case of EMR will also be applicable to other
generalized EXX structures.


  We numerically investigate the motion of active artificial microswimmers
diffusing in a fuel concentration gradient. We observe that, in the steady
state, their probability density accumulates in the low-concentration regions,
whereas a tagged swimmer drifts with velocity depending in modulus and
orientation on how the concentration gradient affects the self-propulsion
mechanism. Under most experimentally accessible conditions, the particle drifts
toward the high-concentration regions (pseudo-chemotactic drift). A correct
interpretation of experimental data must account for such an "anti-Fickian"
behavior.


  Let $A \subset \mathbb{Z}^d$ be a finite set. It is known that the sumset
$NA$ has predictable size ($\vert NA\vert = P_A(N)$ for some $P_A(X) \in
\mathbb{Q}[X]$) and structure (all of the lattice points in some finite cone
other than all of the lattice points in a finite collection of exceptional
subcones), once $N$ is larger than some threshold. In previous work, joint with
Shakan, the first and third named authors established the first effective
bounds for both of these thresholds for an arbitrary set $A$. In this article
we substantially improve each of these bounds, coming much closer to the
corresponding lower bounds known.


  We present a technique which allows us to solve the Random Phase
Approximation equations with finite-range interactions and treats the continuum
part of the excitation spectrum without approximations. The interaction used in
the Hartree-Fock calculations to generate the single particle basis is also
used in the Continuum Random Phase Approximation calculations. We present
results for the electric dipole and quadrupole excitations in the $^{16}$O,
$^{22}$O, $^{24}$O, $^{40}$Ca, $^{48}$Ca and $^{52}$Ca nuclei. We compare our
results with those of the traditional discrete Random Phase Approximation, with
the continuum mean-field results and with the results obtained by a
phenomenological approach. We study the relevance of the continuum, of the
residual interaction and of the self-consistency. We also compare our results
with the available total photoabsorption cross section data. We compare our
photoabsorption cross section in $^4$He with that obtained by a calculation
which uses a microscopic interaction.


  Considering a minimal number of assumptions and in the context of the
timeless formalism, conditional probabilities are derived for subsequent
measurements in the non-relativistic regime. Only unitary transformations are
considered with detection processes described by generalized measurements
(POVM). One-time conditional probabilities are unambiguously derived via the
Gleason-Bush theorem, including for puzzling cases like the Wigner's friend
scenario where their form underlines the relativity aspect of measurements. No
paradoxical situations emerge and the roles of Wigner and Wigner can be seen by
his friend as being in a superposition.


  Mutual information is a nonlinear measure used in time series analysis in
order to measure the linear and non-linear correlations at any lag $\tau$. The
aim of this study is to evaluate some of the most commonly used mutual
information estimators, i.e. estimators based on histograms (with fixed or
adaptive bin size), $k$-nearest neighbors and kernels. We assess the accuracy
of the estimators by Monte-Carlo simulations on time series from nonlinear
dynamical systems of varying complexity. As the true mutual information is
generally unknown, we investigate the existence and rate of consistency of the
estimators (convergence to a stable value with the increase of time series
length), and the degree of deviation among the estimators. The results show
that the $k$-nearest neighbor estimator is the most stable and less affected by
the method-specific parameter.


  Purpose: We present the five-year in-orbit background evolution of
Insight-HXMT since the launch, as well as the effects of the background model
in data analysis. Methods: The backgrounds of the three main payloads, i.e.,
Low-Energy Telescope, Medium-Energy Telescope and High-Energy Telescope, are
described, respectively. The evolution of the background over time is obtained
by simply comparing the background in every year during the in-orbit operation
of Insight-HXMT. Results: The major observational characteristics of the
Insight-HXMT in-orbit background are presented, including the light curve,
spectrum, geographical distribution, and long-term evolution. The systematic
error in background estimation is investigated for every year. Conclusion: The
observational characteristics of the five-year in-orbit background are
consistent with our knowledge of the satellite design and the space
environment, and the background model is still valid for the latest
observations of Insight-HXMT.


  In this work, the elastic and thermodynamic properties of Pt$_{3}$Al under
high pressure are investigated using density functional theory within the
generalized gradient approximation. The results of bulk modulus and elastic
constants at zero pressure are in good agreement with the available theoretical
and experimental values. Under high pressure, all the elastic constants meet
the corresponding mechanical stability criteria, meaning that Pt$_{3}$Al
possesses mechanical stability. In addition, the elastic constants and elastic
modulus increase linearly with the applied pressure. According to the Poisson's
ratio $\nu$ and elastic modulus ratio ($B/G$), Pt$_{3}$Al alloy is found to be
ductile, and higher pressure can significantly enhance the ductility. Those
indicate that the elastic properties of Pt$_{3}$Al will be improved under high
pressure. Through the quasi-harmonic Debye model, we first successfully report
the variations of the Debye temperature $\Theta_\textrm{D}$, specific heats
$C_{P}$, thermal expansion coefficient $\alpha$, and Gr\"{u}neisen parameter
$\gamma$ under pressure range from 0 to 100 GPa and temperature range from 0 to
1000 K.