  The heat kernel associated with an elliptic second-order partial differential
operator of Laplace type acting on smooth sections of a vector bundle over a
Riemannian manifold, is studied. A general manifestly covariant method for
computation of the coefficients of the heat kernel asymptotic expansion is
developed. The technique enables one to compute explicitly the diagonal values
of the heat kernel coefficients, so called Hadamard-Minackshisundaram-De
Witt-Seeley coefficients, as well as their derivatives. The elaborated
technique is applicable for a manifold of arbitrary dimension and for a generic
Riemannian metric of arbitrary signature. It is very algorithmic, and well
suited to automated computation. The fourth heat kernel coefficient is computed
explicitly for the first time. The general structure of the heat kernel
coefficients is investigated in detail. On the one hand, the leading derivative
terms in all heat kernel coefficients are computed. On the other hand, the
generating functions in closed covariant form for the covariantly constant
terms and some low-derivative terms in the heat kernel coefficients are
constructed by means of purely algebraic methods. This gives, in particular,
the whole sequence of heat kernel coefficients for an arbitrary locally
symmetric space.


  Fix positive reals $a,b,c,d$, and let $h(x)$ be a real function behaving sort
of like $\sin x$ near 0. Then, provided $m$ grows linearly with $n$. there
exists a positive constant $C$ such that$$
  \prod_{j=0}^m\frac{h\left((cj+a)\frac{d}{n}\right)}{h\left((cj+b)\frac{d}{n}\right)}\sim
C n^{\frac{a-b}c}.
  $$


  Interstellar neutral hydrogen (HI) emission spectra manifest several families
of linewidths whose numerical values (34, 13 & 6 km/s) appear to be related to
the critical ionization velocities (CIVs) of the most abundant interstellar
atomic species. Extended new analysis of HI emission profiles shows that the 34
km/s wide component, probably corresponding to the CIV for helium, is
pervasive. The 34 km/s wide linewidth family is found in low-velocity (local)
neutral hydrogen (HI) profiles as well as in the so-called high-velocity
clouds. In addition, published studies of HI linewidths found in the Magellanic
Stream, Very-High-Velocity Clouds, and Compact High-Velocity Clouds, all of
which are believed to be intergalactic, have noted that typical values are of
the same order. If the critical ionization velocity effect does play a role in
interstellar space it may be expected to produce locally enhanced electron
densities where rapidly moving neutral gas masses interact with surrounding
plasma. Evidence is presented that suggests that this phenomenon is occurring
in interstellar space. It manifests as a spatial association between peaks in
HI structure offset with respect to peaks in high-frequency radio continuum
data obtained with the Wilkinson Microwave Anisotropy Probe.


  Graph products for groups were defined by Green in her thesis as a
generalization of both Cartesian and free products. In this paper we define the
corresponding graph product for reduced and maximal C*-algebras, von Neumann
algebras and quantum groups. We prove stability properties including permanence
properties of II_1-factors, the Haagerup property, exactness and under suitable
conditions the property of Rapid Decay for quantum groups.


  The heavy singlet Majorana neutrinos are introduced to generate the neutrino
mass in the so-called phenomenological type-I seesaw mechanism. The phenomena
induced by the heavy Majorana neutrinos are important to search for new
physics. In this paper, we explore the heavy Majorana neutrino production and
decay at future $e^{-}p$ colliders. The corresponding cross sections via $W$
and photon fusion are predicted for different collider energies. Combined with
the results of the heavy Majorana neutrino production via single $W$ exchange,
this work can provide helpful information to search for heavy Majorana
neutrinos at future $e^{-}p$ colliders.


  By studying Fe-doped ZnO pellets and thin films with various x-ray
spectroscopic techniques, and complementing this with density functional theory
calculations, we find that Fe-doping in bulk ZnO induces isovalent (and
isostructural) cation substitution (Fe2+ -> Zn2+). In contrast to this,
Fe-doping near the surface produces both isovalent and heterovalent
substitution (Fe3+ -> Zn2+). The calculations performed herein suggest that the
most likely defect structure is the single or double substitution of Zn with
Fe, although, if additional oxygen is available, then Fe substitution with
interstitial oxygen is even more energetically favourable. Furthermore, it is
found that ferromagnetic states are energetically unfavourable, and
ferromagnetic ordering is likely to be realized only through the formation of a
secondary phase (i.e. ZnFe2O4), or codoping with Cu.


  We prove the existence of closed hypersurfaces of prescribed scalar curvature
in globally hyperbolic Lorentzian manifolds provided there are barriers.


  Nested parallelism exists in scientific codes that are searching
multi-dimensional spaces. However, implementations of nested parallelism often
have overhead and load balance issues. The Orbital Analysis code we present
exhibits a sparse search space, significant load imbalances, and stopping when
the first solution is reached. All these aspects of the algorithm exacerbate
the problem of using nested parallelism effectively. In this paper, we present
an inspector/executor strategy for chunking such computations into parallel
wavefronts. The presented shared memory parallelization is no longer nested and
exhibits significantly less load imbalance. We evaluate this approach on an
Orbital analysis code, and we improve the execution time from the original
implementation by an order of magnitude. As part of a Graduate Computer Science
course in Parallel Programming models, we show how the approach can be
implemented in parallel Perl, Python, Chapel, Pthreads, and OpenMP. Future work
includes investigating how to automate and generalize the parallelization
approach.


  In the context of the LAUE project devoted to build a Laue lens prototype for
focusing celestial hard X-/soft gamma-rays, a Laue lens made of bent crystal
tiles, with 20 m focal length, is simulated. The focusing energy passband is
assumed to be 90--600 keV. The distortion of the image produced by the lens on
the focal plane, due to effects of crystal tile misalignment and radial
distortion of the crystal curvature, is investigated. The corresponding
effective area of the lens, its point spread function and sensitivity are
calculated and compared with those exhibited by a nominal Laue lens with no
misalignment and/or distortion. Such analysis is crucial to estimate the
optical properties of a real lens, in which the investigated shortcomings could
be present.


  It is shown that the acceleration of the universe can be understood by
considering a F(T) gravity models. For these F(T) gravity models, a variant of
the accelerating cosmology reconstruction program is developed. Some explicit
examples of F(T) are reconstructed from the background FRW expansion history.


  This paper proposes a methodology of model predictive control for alleviating
shallow drowsiness of office workers and thus improving their productivity. The
methodology is based on dynamically scheduling setting values for air
conditioning and lighting to minimize drowsiness level of office workers on the
basis of a prediction model that represents the relation between future
drowsiness level and combination of indoor temperature and ambient illuminance.
The prediction model can be identified by utilizing state-of-the-art drowsiness
estimation method. The proposed methodology was evaluated in regard to a real
routine task (performed by six subjects over five workdays), and the evaluation
results demonstrate that the proposed methodology improved the processing speed
of the task by 8.3% without degrading comfort of the workers.


  We define and sketch the generalized ergosphere of the Majumdar-Papapetrou
(MP) spacetime. In particular, we demonstrate the existence of closed orbits of
negative energy that live outside the event horizon of such a spacetime.
Relying on the Penrose process mechanism, we use these orbits to illustrate the
possibility of energy extraction from a MP binary black hole by particle
scattering. We also analyze the efficiency of the process, and construct
explicit examples that optimize the extraction of energy. Lastly, we show how
such concepts can be extended to a pair of non-coalescing Kerr black holes
described by the Cabrera-Munguia, Manko and Ruiz (CMMR) metric.


  L and T dwarfs emit most of their radiation in the near infrared and their
spectral energy distributions are dominated by strong molecular absorption
bands. These highly structured energy distributions lead to JHK magnitudes that
are extremely sensitive to the exact filter bandpass used. In the case of the T
dwarfs, the differences between commonly used photometric systems can be as
large as 0.4 mag at J and 0.5 mag at J-K. To address this problem, we have
synthesized J,H and K magnitudes for some of the common photometric systems and
present transformation equations. If the spectral type of the dwarf is known,
our transformations allow data to be converted between systems to 0.01 mag,
which is better than the typical measurement uncertainty. Transforming on the
basis of color alone is more difficult because of the degeneracy and intrinsic
scatter in near-infrared colors of L and T dwarfs; in this case J magnitudes
can only be transformed to < 0.05 mag and H and K to < 0.02 mag.


  A re-purposed Kepler mission could continue the search for nearly Earth-sized
planets in very short-period (< 1 day) orbits. Recent surveys of the Kepler
data already available have revealed at least a dozen such planetary
candidates, and a more complete and focused survey is likely to reveal more.
Given the planets' short orbital periods, building the requisite
signal-to-noise to detect the candidates by stacking multiple transits requires
a much shorter observational baseline than for longer-period planets, and the
transits are likely more robust against the much larger instrumental variations
anticipated for the modified Kepler pointing capabilities. Searching for these
unusual planets will also leverage the Kepler mission's already considerable
expertise in planetary transit detection and analysis. These candidates may
represent an entirely new class of planet. They may also provide unprecedented
insights into planet formation and evolution and sensitive probes for
planet-star interactions and the stellar wind. Whatever their origins and
natures, such planets would be particularly amenable to discovery by the
planned TESS mission, and a preliminary survey by Kepler could pave the way for
such TESS discoveries.


  In this paper, Wolbachia infection in a bisexual and diploid population with
a fixed cytoplasmic incompatibility rate $w$ and maternal transmission rate $d$
is studied as an evolution algebra. As the cytoplasmic incompatibility (CI) of
the population causes deaths in the offspring, the evolution algebra of this
model is not baric, and is a dibaric algebra if and only if the cytoplasmic
incompatibility rate $w$ is 1 and $d=1$. The idempotent elements are given in
terms of $d$ and $w$. Moreover, this algebra has no absolute nilpotent elements
when CI expression $w \neq 1$.


  We analyse a random motion of a particle on a fractal curve, using Langevin
approach. This involves defining a new velocity in terms of mass of the fractal
curve, as defined in recent work. The geometry of the fractal curve, hence
plays an important role in this analysis. A Langevin equation with a particular
noise model is thus proposed and solved using techniques of the newly developed
$F^\alpha$-Calculus .


  We prove two generalizations of the Cheeger's inequality. The first
generalization relates the second eigenvalue to the edge expansion and the
vertex expansion of the graph G, $\lambda_2 = \Omega(\phi^V(G) \phi(G))$, where
$\phi^V(G)$ denotes the robust vertex expansion of G and $\phi(G)$ denotes the
edge expansion of G. The second generalization relates the second eigenvalue to
the edge expansion and the expansion profile of G, for all $k \ge 2$,
$\lambda_2 = \Omega(\phi_k(G) \phi(G) / k)$, where $\phi_k(G)$ denotes the
k-way expansion of G. These show that the spectral partitioning algorithm has
better performance guarantees when $\phi^V(G)$ is large (e.g. planted random
instances) or $\phi_k(G)$ is large (instances with few disjoint non-expanding
sets). Both bounds are tight up to a constant factor.
  Our approach is based on a method to analyze solutions of Laplacian systems,
and this allows us to extend the results to local graph partitioning
algorithms. In particular, we show that our approach can be used to analyze
personal pagerank vectors, and to give a local graph partitioning algorithm for
the small-set expansion problem with performance guarantees similar to the
generalizations of Cheeger's inequality. We also present a spectral approach to
prove similar results for the truncated random walk algorithm. These show that
local graph partitioning algorithms almost match the performance of the
spectral partitioning algorithm, with the additional advantages that they apply
to the small-set expansion problem and their running time could be sublinear.
Our techniques provide common approaches to analyze the spectral partitioning
algorithm and local graph partitioning algorithms.


  We propose to use real-valued errors instead of classical bit flipping
intentional errors in the McEliece cryptosystem based on moderate-density
parity-check (MDPC) codes. This allows to exploit the error correcting
capability of these codes to the utmost, by using soft-decision iterative
decoding algorithms instead of hard-decision bit flipping decoders. However,
soft reliability values resulting from the use of real-valued noise can also be
exploited by attackers. We devise new attack procedures aimed at this, and
compute the relevant work factors and security levels. We show that, for a
fixed security level, these new systems achieve the shortest public key sizes
ever reached, with a reduction up to 25% with respect to previous proposals.


  Due to its excellent performance in rate and resolution, fully-digital (FD)
massive multiple-input multiple-output (MIMO) antenna arrays has been widely
applied in data transmission and direction of arrival (DOA) measurements, etc.
But it confronts with two main challenges: high computational complexity and
circuit cost. The two problems may be addressed well by hybrid analog-digital
(HAD) structure. But there exists the problem of phase ambiguity for HAD, which
leads to its low-efficiency or high-latency. Does exist there such a MIMO
structure of owning low-cost, low-complexity and high time efficiency at the
same time. To satisfy the three properties, a novel heterogeneous hybrid MIMO
receiver structure of integrating FD and heterogeneous HAD ($\rm{H}^2$AD-FD) is
proposed and corresponding multi-modal (MD)-learning framework is developed.
The framework includes three major stages: 1) generate the candidate sets via
root multiple signal classification (Root-MUSIC) or deep learning (DL); 2)
infer the class of true solutions from candidate sets using machine learning
(ML) methods; 3) fuse the two-part true solutions to achieve a better DOA
estimation. The above process form two methods named MD-Root-MUSIC and MDDL. To
improve DOA estimation accuracy and reduce the clustering complexity, a
co-learning-aided MD framework is proposed to form two enhanced methods named
CoMDDL and CoMD-RootMUSIC. Moreover, the Cramer-Rao lower bound (CRLB) for the
proposed $\rm{H}^2$AD-FD structure is also derived. Experimental results
demonstrate that our proposed four methods could approach the CRLB for
signal-to-noise ratio (SNR) > 0 dB and the proposed CoMDDL and MDDL perform
better than CoMD-RootMUSIC and MD-RootMUSIC, particularly in the extremely low
SNR region.


  We prove the trichotomy between transience to the right, transience to the
left and recurrence of one-dimensional nearest-neighbour random walks in
dynamic random environments under fairly general assumptions, namely:
stationarity under space-time translations, ergodicity under spatial
translations, and a mild ellipticity condition. In particular, the result
applies to general uniformly elliptic models and also to a large class of
non-uniformly elliptic cases that are i.i.d. in space and Markovian in time. An
immediate consequence is the recurrence of models that are symmetric with
respect to reflection through the origin.


  A totally nonnegative matrix is a real-valued matrix whose minors are all
nonnegative. In this paper, we concern with the totally nonnegative structure
of the finite Toda lattice, a classical integrable system, which is expressed
as a differential equation of square matrices. The Toda flow naturally
translates into a (multiplicative) linear flow on the (generalized) Jacobi
variety associated with some reducible rational curve $X$. This correspondence
provides an algebro-geometric characterization of the totally positive part of
the Toda equation. We prove that the totally nonnegative part of the finite
Toda lattice is isomorphic to a connected component of
$\mathrm{Jac}(X)_{\mathbb{R}}$, the real part of the generalized Jacobi variety
$\mathrm{Jac}(X)$, as semi-algebraic varieties.


  We study the Maximum Happy Vertices and Maximum Happy Edges problems. The
former problem is a variant of clusterization, where some vertices have already
been assigned to clusters. The second problem gives a natural generalization of
Multiway Uncut, which is the complement of the classical Multiway Cut problem.
Due to their fundamental role in theory and practice, clusterization and cut
problems has always attracted a lot of attention. We establish a new connection
between these two classes of problems by providing a reduction between Maximum
Happy Vertices and Node Multiway Cut. Moreover, we study structural and
distance to triviality parameterizations of Maximum Happy Vertices and Maximum
Happy Edges. Obtained results in these directions answer questions explicitly
asked in four works: Agrawal '17, Aravind et al. '16, Choudhari and Reddy '18,
Misra and Reddy '17.


  We have estimated centrality variation of chemical freeze-out parameters from
yield data at mid-rapidity of $\pi^\pm$, $K^\pm$ and $p$, $\bar{p}$ for
collision energies of RHIC (Relativistic Heavy Ion Collider), Beam Energy Scan
(RHIC-BES) program, and LHC (Large Hadron Collider). We have considered a
simple hadron resonance gas model and employed a formalism involving conserved
charges ($B, Q, S$) of QCD for parameterization. Along with temperature and
three chemical potentials ($T,\mu_B,\mu_Q,\mu_S$), a strangeness
under-saturation factor ($\gamma_S$) has been used to incorporate the partial
equilibration in the strange sector. Our obtained freeze-out temperature does
not vary much with centrality, whereas chemical potentials and $\gamma_S$ seem
to have a significant dependence. The strange hadrons are found to deviate from
a complete chemical equilibrium at freeze-out at the peripheral collisions.
This deviation appears to be more prominent as the collision energy decreases
at lower RHIC-BES energies. We have also shown that this departure from
equilibrium reduces towards central collisions, and strange particle
equilibration may happen after a threshold number of participants in $A$-$A$
collision.


  Pregel's vertex-centric model allows us to implement many interesting graph
algorithms, where optimization plays an important role in making it practically
useful. Although many optimizations have been developed for dealing with
different performance issues, it is hard to compose them together to optimize
complex algorithms, where we have to deal with multiple performance issues at
the same time. In this paper, we propose a new approach to composing
optimizations, by making use of the \emph{channel} interface, as a replacement
of Pregel's message passing and aggregator mechanism, which can better
structure the communication in Pregel algorithms. We demonstrate that it is
convenient to optimize a Pregel program by simply using a proper channel from
the channel library or composing them to deal with multiple performance issues.
We intensively evaluate the approach through many nontrivial examples. By
adopting the channel interface, our system achieves an all-around performance
gain for various graph algorithms. In particular, the composition of different
optimizations makes the S-V algorithm 2.20x faster than the current best
implementation.


  In this paper, we analyze the symbol error rate (SER) performance of the
simultaneous wireless information and power transfer (SWIPT) enabled three-node
differential decode-and-forward (DDF) relay networks, which adopt the power
splitting (PS) protocol at the relay. The use of non-coherent differential
modulation eliminates the need for sending training symbols to estimate the
instantaneous channel state information (CSI) at all network nodes, and
therefore improves the power efficiency, as compared with the coherent
modulation. However, performance analysis results are not yet available for the
state-of-the-art detectors such as the maximum-likelihood detector (MLD) and
approximate MLD. Existing works rely on the Monte-Carlo simulation method to
show the existence of an optimal PS ratio that minimizes the overall SER. In
this work, we propose a near-optimal detector with linear complexity with
respect to the modulation size. We derive an approximate SER expression and
prove that the proposed detector achieves the full diversity order. Based on
our expression, the optimal PS ratio can be accurately estimated without
requiring any Monte-Carlo simulation. We also extend the proposed detector and
its SER analysis for adopting the time switching (TS) protocol at the relay.
Simulation results verify the effectiveness of our proposed detector and the
accuracy of our SER results in various network scenarios for both PS and TS
protocols.


  The problem of three-dimensional combined magnetic and velocity shear driven
instabilities of a compressible magnetized jet modeled with a plane
neutral/current double vortex sheet in the framework of the resistive
magnetohydrodynamics is addressed. The resulting dynamics given by the
stream+current sheet interaction is analyzed and the effects of a variable
geometry of the basic fields are considered. Depending on the basic asymptotic
magnetic field configuration, a selection rule of the linear instability modes
can be obtained. Hence, the system follows a two-stage path developing either
through a fully three-dimensional dynamics with a rapid evolution of kink modes
leading to a final turbulent state, or rather through a driving two-dimensional
instability pattern that develops on parallel planes on which a
reconnection+coalescence process takes place.


  Based on new millimeter and radio observations, we reevaluate the total
hydrogen column density along the line of sight to the microquasar GRS 1915+105
to NH=(3.5 +/- 0.3) 10^22 cm^-2. Our value is consistent with the one derived
from X-ray measurements, namely (3.8 +/- 0.3) 10^22 cm^-2 (Ebisawa et al.
1998). Using the empirical law between the visual extinction and the total
column density of hydrogen, Av is found to 19.6 +/- 1.7 mag. This result is 7
mag lower than previously thought, and therefore, a reevaluation of infrared
fluxes after derredening is needed. The revisited kinematic study allows to
give a lower limit to the distance of GRS 1915+105, namely 6.0 kpc. Taking into
account the most accurate upper limit of distance inferred from radio data
(11.2 +/- 0.8 kpc; Fender et al. 1999) as well as this lower limit, this
implies a distance of 9.0 +/- 3.0 kpc .


  This paper investigates how the speed of code review is affected by the code
quality, activity and usage in the context of MediaWiki extensions. The median
time to merge is compared against several other variables which are collected
using a variety of manual methods and APIs. The results are graphed where
possible and statistical analysis is used to determine the significance of the
results. The paper finds that the number of reviewers voting on code and
whether the extension has a steward affects the median time to merge. Finally,
conclusions are drawn and further research topics are recommended.


  We provide three statistical model prescriptions for the bolometric
corrections appropriate for B-type stars as a function of: 1) T_eff, 2) T_eff,
log g, and 3) T_eff, log g, [M/H]. These statistical models have been
calculated for 27 different filters, including those of the Gaia space mission,
and were derived based on two different grids of bolometric corrections
assuming LTE and LTE+NLTE, respectively. Previous such work has mainly been
limited to a single photometric passband without taking into account NLTE
effects on the bolometric corrections. Using these statistical models, we
calculate the luminosities of 34 slowly pulsating B-type (SPB) stars with
available spectroscopic parameters, to place them in the Hertzsprung-Russell
diagram and compare their position to the theoretical SPB instability strip. We
find that excluding NLTE effects has no significant impact on the derived
luminosities for the temperature range 11500-21000 K. We conclude that
spectroscopic parameters are needed in order to achieve meaningful luminosities
of B-type stars. The three prescriptions for the bolometric corrections are
valid for any galactic B-type star with effective temperatures and surface
gravities in the ranges 10000-30000 K and 2.5-4.5 dex, respectively, covering
regimes below the Eddington limit.


  In the present paper, new classes of wavelet functions are presented in the
framework of Clifford analysis. Firstly, some classes of orthogonal polynomials
are provided based on 2-parameters weight functions. Such classes englobe the
well known ones of Jacobi and Gegenbauer polynomials when relaxing one of the
parameters. The discovered polynomial sets are next applied to introduce new
wavelet functions. Reconstruction formula as well as Fourier-Plancherel rules
have been proved.


  This paper focuses on supergravity duals of BPS states in N=4 super
Yang-Mills. In order to describe these duals, we begin with a sequence of
breathing mode reductions of IIB supergravity: first on S^3, then S^3 x S^1,
and finally on S^3 x S^1 x CP^1. We then follow with a complete supersymmetry
analysis, yielding 1/8, 1/4 and 1/2 BPS configurations, respectively (where in
the last step we take the Hopf fibration of S^3). The 1/8 BPS geometries, which
have an S^3 isometry and are time-fibered over a six-dimensional base, are
determined by solving a non-linear equation for the Kahler metric on the base.
Similarly, the 1/4 BPS configurations have an S^3 x S^1 isometry and a
four-dimensional base, whose Kahler metric obeys another non-linear,
Monge-Ampere type equation.
  Despite the non-linearity of the problem, we develop a universal bubbling AdS
description of these geometries by focusing on the boundary conditions which
ensure their regularity. In the 1/8 BPS case, we find that the S^3 cycle
shrinks to zero size on a five-dimensional locus inside the six-dimensional
base. Enforcing regularity of the full solution requires that the interior of a
smooth, generally disconnected five-dimensional surface be removed from the
base. The AdS_5 x S^5 ground state corresponds to excising the interior of an
S^5, while the 1/8 BPS excitations correspond to deformations (including
topology change) of the S^5 and/or the excision of additional droplets from the
base. In the case of 1/4 BPS configurations, by enforcing regularity
conditions, we identify three-dimensional surfaces inside the four-dimensional
base which separate the regions where the S^3 shrinks to zero size from those
where the S^1 shrinks.


  In this paper, I show that a Yang-Mills force with a
U(1)$\timesSU(2)\times$SU(2) group symmetry predicts solar system observations
of gravitational behavior as well as binary pulsar precession provided that
mass is redefined as intrinsic static pressure and all stress-energy-momentum
tensors are, thus, traceless. Using a homogeneous, isotropic universe model, I
show that this theory explains the accelerating expansion of the universe
directly from group symmetry with no ad hoc constants and predicts that
antimatter and matter gravitationally repel one another (antimatter "falls"
up). In addition, because it is a generic massless Yang-Mills theory, it is a
renormalizable quantum theory.


  The highly forbidden $^2$S$_{1/2} \rightarrow ^2$F$_{7/2}$ electric octupole
transition in $^{171}$Yb$^+$ is a potential candidate for a redefinition of the
SI second. We present a measurement of the absolute frequency of this optical
transition, performed using a frequency link to International Atomic Time to
provide traceability to the SI second. The $^{171}$Yb$^+$ optical frequency
standard was operated for 76% of a 25-day period, with the absolute frequency
measured to be 642 121 496 772 645.14(26) Hz. The fractional uncertainty of
$4.0 \times 10 ^{-16}$ is comparable to that of the best previously reported
measurement, which was made by a direct comparison to local caesium primary
frequency standards.


  In this paper, we study the following fractional Schr\"{o}dinger equation
with prescribed mass \begin{equation*} \left\{ \begin{aligned}
&(-\Delta)^{s}u=\lambda u+a(x)|u|^{p-2}u,\quad\text{in $\mathbb{R}^{N}$},\\
&\int_{\mathbb{R}^{N}}|u|^{2}dx=c^{2},\quad u\in H^{s}(\mathbb{R}^{N}),
\end{aligned} \right. \end{equation*} where $0<s<1$, $N>2s$,
$2+\frac{4s}{N}<p<2_{s}^{*}:=\frac{2N}{N-2s}$, $c>0$, $\lambda\in \mathbb{R}$
and $a(x)\in C^{1}(\mathbb{R}^{N},\mathbb{R}^{+})$ is a potential function. By
using a minimax principle, we prove the existence of bounded state normalized
solution under various conditions on $a(x)$.


  Using the new data from the OECD-WTO world network of economic activities we
construct the Google matrix $G$ of this directed network and perform its
detailed analysis. The network contains 58 countries and 37 activity sectors
for years 1995, 2000, 2005, 2008, 2009. The construction of $G$, based on
Markov chain transitions, treats all countries on equal democratic grounds
while the contribution of activity sectors is proportional to their exchange
monetary volume. The Google matrix analysis allows to obtain reliable ranking
of countries and activity sectors and to determine the sensitivity of
CheiRank-PageRank commercial balance of countries in respect to price
variations and labor cost in various countries. We demonstrate that the
developed approach takes into account multiplicity of network links with
economy interactions between countries and activity sectors thus being more
efficient compared to the usual export-import analysis. Our results highlight
the striking increase of the influence of German economic activity on other
countries during the period 1995 to 2009 while the influence of Eurozone
decreases during the same period. We compare our results with the similar
analysis of the world trade network from the UN COMTRADE database. We argue
that the knowledge of network structure allows to analyze the effects of
economic influence and contagion propagation over the world economy.


  Dry (i.e. dissipationless) merging has been proposed as the main driver of
the observed size evolution of early-type galaxies (ETGs). The actual role of
this mechanism is questioned by the tightness of the local stellar mass-size
relation of ETGs. Combining this observed scaling law with simple merging
models, which should bracket cosmologically motivated merging histories, we
draw the following conclusions: 1) local massive ETGs can have assembled at
most ~45% of their stellar mass via dry mergers; 2) extreme fine tuning is
required for this to be the case.


  Making moral judgments is an essential step toward developing ethical AI
systems. Prevalent approaches are mostly implemented in a bottom-up manner,
which uses a large set of annotated data to train models based on crowd-sourced
opinions about morality. These approaches have been criticized for
overgeneralizing the moral stances of a limited group of annotators and lacking
explainability. This work proposes a flexible top-down framework to steer
(Large) Language Models (LMs) to perform moral reasoning with well-established
moral theories from interdisciplinary research. The theory-guided top-down
framework can incorporate various moral theories. Our experiments demonstrate
the effectiveness of the proposed framework on datasets derived from moral
theories. Furthermore, we show the alignment between different moral theories
and existing morality datasets. Our analysis exhibits the potential and flaws
in existing resources (models and datasets) in developing explainable moral
judgment-making systems.


  For a two-dimensional (2D) hole system (confined within Ge layers of a
multilayered p-Ge/Ge_{1-x}Si_x heterostructure) described by Luttinger
Hamiltonian with the g-factor highly anisotropic for orientations of magnetic
field perpendicular and parallel to the 2D plane (g_perp >> g_par), reported is
an observation of low-temperature transition from metallic (dR/dT > 0) to
insulator (dR/dT < 0) behavior of resistivity R(T) induced by a perpendicular
magnetic field B. The revealed positive magnetoresistance scales as a function
of B/T. We attribute this finding to a suppression of the triplet channel of
electron-electron (hole-hole) interaction due to Zeeman splitting in the hole
spectrum.


  Recently, variational auto-encoder (VAE) based approaches have made
impressive progress on improving the diversity of generated responses. However,
these methods usually suffer the cost of decreased relevance accompanied by
diversity improvements. In this paper, we propose a novel multimodal response
generation framework with exemplar augmentation and curriculum optimization to
enhance relevance and diversity of generated responses. First, unlike existing
VAE-based models that usually approximate a simple Gaussian posterior
distribution, we present a Gaussian mixture posterior distribution (i.e,
multimodal) to further boost response diversity, which helps capture complex
semantics of responses. Then, to ensure that relevance does not decrease while
diversity increases, we fully exploit similar examples (exemplars) retrieved
from the training data into posterior distribution modeling to augment response
relevance. Furthermore, to facilitate the convergence of Gaussian mixture prior
and posterior distributions, we devise a curriculum optimization strategy to
progressively train the model under multiple training criteria from easy to
hard. Experimental results on widely used SwitchBoard and DailyDialog datasets
demonstrate that our model achieves significant improvements compared to strong
baselines in terms of diversity and relevance.


  The sudden onset of the coronavirus (SARS-CoV-2) pandemic has resulted in
tremendous loss of human life and economy in more than 210 countries and
territories around the world. While self-protections such as wearing mask,
sheltering in place and quarantine polices and strategies are necessary for
containing virus transmission, tens of millions people in the U.S. have lost
their jobs due to the shutdown of businesses. Therefore, how to reopen the
economy safely while the virus is still circulating in population has become a
problem of significant concern and importance to elected leaders and business
executives. In this study, mathematical modeling is employed to quantify the
profit generation and the infection risk simultaneously from the point of view
of a business entity. Specifically, an ordinary differential equation model was
developed to characterize disease transmission and infection risk. An algebraic
equation is proposed to determine the net profit that a business entity can
generate after reopening and take into account the costs associated of several
protection/quarantine guidelines. All model parameters were calibrated based on
various data and information sources. Sensitivity analyses and case studies
were performed to illustrate the use of the model in practice.


  We present a comprehensive review of formation and control of single photon
sources from two dimensional materials. We critically analyze the creation and
control of these quantum emitters both at room and at low temperature.
Deterministic formation and position controlled methodology is elaborated and
pictorially explained. We enlist major single photon sources from various two
dimensional and non two dimensional resources. Plasmonic waveguides and the
interfacing of single photon sources with them are critically analyzed and
reviewed. Furthermore, we envisize the geometry of plasmonic waveguides for
maximum coupling of single photons.


  We relate two conjectures which have been raised for classification of
Leavitt path algebras. For purely infinite simple unital Leavitt path algebras,
it is conjectured that K_0 classifies them completely. For arbitrary Leavitt
path algebras, it is conjectured that K^{\gr}_0 classifies them completely
\cite{hazann}. We show that for two finite graphs with no sinks (which their
associated Leavitt path algebras include the purely infinite simple ones) if
their K^{\gr}_0-groups of their Leavitt path algebras are isomorphic then their
K_0-groups are isomorphic as well.


  The formation of plasmoid chains is explored for the first time within the
context of the Taylor problem, in which magnetic reconnection is driven by a
small amplitude boundary perturbation in a tearing-stable slab plasma
equilibrium. Numerical simulations of a magnetohydrodynamical model of the
plasma show that for very small plasma resistivity and viscosity, the linear
inertial phase is followed by a nonlinear Sweet-Parker evolution, which gives
way to a faster reconnection regime characterized by a chain of plasmoids
instead of a slower Rutherford phase.


  We show that a set of parallel 3-brane probes near a conifold singularity can
be mapped onto a configuration of intersecting branes in type IIA string
theory. The field theory on the probes can be explicitly derived from this
formulation. The intersecting-brane metric for our model is obtained using
various dualities and related directly to the conifold metric. The M-theory
limit of this model is derived and turns out to be remarkably simple. The
global symmetries and counting of moduli are interpreted in the M-theory
picture.


  Graph Neural Networks (GNNs) have garnered widespread attention for their
potential to address the challenges posed by graph representation learning,
which face complex graph-structured data across various domains. However, due
to the inherent complexity and interconnectedness of graphs, accurately
annotating graph data for training GNNs is extremely challenging. To address
this issue, we have introduced Partial Label Learning (PLL) into graph
representation learning. PLL is a critical weakly supervised learning problem
where each training instance is associated with a set of candidate labels,
including the ground-truth label and the additional interfering labels. PLL
allows annotators to make errors, which reduces the difficulty of data
labeling. Subsequently, we propose a novel graph representation learning method
that enables GNN models to effectively learn discriminative information within
the context of PLL. Our approach utilizes potential cause extraction to obtain
graph data that holds causal relationships with the labels. By conducting
auxiliary training based on the extracted graph data, our model can effectively
eliminate the interfering information in the PLL scenario. We support the
rationale behind our method with a series of theoretical analyses. Moreover, we
conduct extensive evaluations and ablation studies on multiple datasets,
demonstrating the superiority of our proposed method.


  The divisor function $\sigma(n)$ denotes the sum of the divisors of the
positive integer $n$. For a prime $p$ and $m \in \mathbb{N}$, the $p$-adic
valuation of $m$ is the highest power of $p$ which divides $m$. Formulas for
$\nu_{p}(\sigma(n))$ are established. For $p=2$, these involve only the odd
primes dividing $n$. These expressions are used to establish the bound
$\nu_{2}(\sigma(n)) \leq \lceil\log_{2}(n) \rceil$, with equality if and only
if $n$ is the product of distinct Mersenne primes, and for an odd prime $p$,
the bound is $\nu_{p}(\sigma(n)) \leq \lceil \log_{p}(n) \rceil$, with equality
related to solutions of the Ljunggren-Nagell diophantine equation.


  We investigate experimentally the influence of current flow through two
independent quantum point contacts to a nearby double quantum dot realized in a
GaAs-AlGaAs heterostructure. The observed current through the double quantum
dot can be explained in terms of coupling to a bosonic bath. The temperature of
the bath depends on the power generated by the current flow through the quantum
point contact. We identify the dominant absorption and emission mechanisms in a
double quantum dot as an interaction with acoustic phonons. The experiment
excludes coupling of a double quantum dot to shot noise generated by quantum
point contact as the dominant mechanism.


  We consider a periodic vortex lattice in a rotating Bose-Einstein condensed
gas, where the centrifugal potential is exactly compensated by the external
harmonic trap. By introducing a gauge transformation which makes the
Hamiltonian periodic, we solve numerically the 2D Gross-Pitaevskii equation
finding the exact mean field ground state. In particular, we explore the
crossover between the Thomas-Fermi regime, holding for large values of the
coupling constant, and the lowest Landau level limit, corresponding to the
weakly interacting case. Explicit results are given for the equation of state,
the vortex core size, as well as the elastic shear modulus, which is crucial
for the calculation of the Tkachenko frequencies.


  Mass is one of the most important parameters for determining the true nature
of an astronomical object. Yet, many published exoplanets lack a measurement of
their true mass, in particular those detected thanks to radial velocity (RV)
variations of their host star. For those, only the minimum mass, or $m\sin i$,
is known, owing to the insensitivity of RVs to the inclination of the detected
orbit compared to the plane-of-the-sky. The mass that is given in database is
generally that of an assumed edge-on system ($\sim$90$^\circ$), but many other
inclinations are possible, even extreme values closer to 0$^\circ$ (face-on).
In such case, the mass of the published object could be strongly underestimated
by up to two orders of magnitude. In the present study, we use GASTON, a tool
recently developed in Kiefer et al. (2019) & Kiefer (2019) to take advantage of
the voluminous Gaia astrometric database, in order to constrain the inclination
and true mass of several hundreds of published exoplanet candidates. We find 9
exoplanet candidates in the stellar or brown dwarf (BD) domain, among which 6
were never characterized. We show that 30 Ari B b, HD 141937 b, HD 148427 b, HD
6718 b, HIP 65891 b, and HD 16760 b have masses larger than 13.5 M$_\text{J}$
at 3-$\sigma$. We also confirm the planetary nature of 27 exoplanets among
which HD 10180 c, d and g. Studying the orbital periods, eccentricities and
host-star metallicities in the BD domain, we found distributions with respect
to true masses consistent with other publications. The distribution of orbital
periods shows of a void of BD detections below $\sim$100 days, while
eccentricity and metallicity distributions agree with a transition between BDs
similar to planets and BDs similar to stars about 40-50 M$_\text{J}$.


  We study kinetic and jamming properties of a space covering process in one
dimension. The stochastic process is defined as follows: Seeds are nucleated
randomly in space and produce rays which grow with a constant velocity. The
growth stops upon collision with another ray. For arbitrary distributions of
the growth velocity, the exact coverage, velocity and size distributions are
evaluated for both simultaneous and continuous nucleation. In general,
simultaneous nucleation exhibits a stronger dependence on the details of the
growth velocity distribution in the asymptotic time regime. The coverage in the
continuous case exhibits a universal $1/t$ approach to the jammed state, while
an inhomogeneous version of the process leads to nonuniversal $t^{-p_+}$ decay,
with $0\le p_+\le 1$ the fraction of right growing rays.


  Cosmic Microwave Background anomalies suggest that the Universe is slightly
anisotropic, so a Cosmological Model that does not satisfy the Cosmological
Principle is necessary. Anisotropic Bianchi models have been studied given that
they would be necessary to understand the early stages of the Universe. In this
paper, we analyze qualitatively the behavior of the cosmological redshift in a
Bianchi type I model after a coordinate transformation in three cases: vacuum
with no vanishing cosmological constant $\Lambda \not= 0$, universe dominated
by dust and universe dominated by radiation.


  Dynamical Lie-algebraic method for the construction of local quantum
invariants of motion in non-integrable many-body systems is proposed and
applied to a simple but generic toy model, namely an infinite kicked $t-V$
chain of spinless fermions. Transition from integrable via {pseudo-integrable
(\em intermediate}) to quantum ergodic (quantum mixing) regime in parameter
space is investigated. Dynamical phase transition between ergodic and
intermediate (neither ergodic nor completely integrable) regime in
thermodynamic limit is proposed. Existence or non-existence of local
conservation laws corresponds to intermediate or ergodic regime, respectively.
The computation of time-correlation functions of typical observables by means
of local conservation laws is found fully consistent with direct calculations
on finite systems.


  In this paper we present the {\tt C++} package {\tt CRunDec} which implements
all relevant formulae needed for the running and decoupling for the strong
coupling constant and light quark masses. Furthermore, several formulae are
implemented which can be used to transform the heavy quark masses among
different renormalization schemes. {\tt CRunDec} is the {\tt C++} version on
the {\tt Mathematica} package {\tt RunDec} containing several updates and
improvements.


  The application and successful utilization of technological resources in
developing solutions to health, safety, and economic issues caused by COVID-19
indicate the importance of technology in curbing COVID-19. Also, the medical
field has had to race against tie to develop and distribute the COVID-19
vaccine. This endeavour became successful with the vaccines created and
approved in less than a year, a feat in medical history. Currently, much work
is being done on data collection, where all significant factors impacting the
disease are recorded. These factors include confirmed cases, death rates,
vaccine rates, hospitalization data, and geographic regions affected by the
pandemic. Continued research and use of technological resources are highly
recommendable-the paper surveys list of packages, applications and datasets
used to analyse COVID-19.


  Following a recent study by Das and Pernice [Nucl. Phys. B561, (1999) 357],
we have carefully analyzed the half-harmonic oscillator. In contrast to their
observations, our analysis reveals that the spectrum does not allow for a zero
energy ground state and hence the supersymmetry is broken when the domain is
restricted to the positive half of the real axis.


  Conventional supervised super-resolution (SR) approaches are trained with
massive external SR datasets but fail to exploit desirable properties of the
given test image. On the other hand, self-supervised SR approaches utilize the
internal information within a test image but suffer from computational
complexity in run-time. In this work, we observe the opportunity for further
improvement of the performance of SISR without changing the architecture of
conventional SR networks by practically exploiting additional information given
from the input image. In the training stage, we train the network via
meta-learning; thus, the network can quickly adapt to any input image at test
time. Then, in the test stage, parameters of this meta-learned network are
rapidly fine-tuned with only a few iterations by only using the given
low-resolution image. The adaptation at the test time takes full advantage of
patch-recurrence property observed in natural images. Our method effectively
handles unknown SR kernels and can be applied to any existing model. We
demonstrate that the proposed model-agnostic approach consistently improves the
performance of conventional SR networks on various benchmark SR datasets.


  In this paper we propose and analyze inexact and stochastic versions of the
CGALP algorithm developed in the authors' previous paper, which we denote
ICGALP, that allows for errors in the computation of several important
quantities. In particular this allows one to compute some gradients, proximal
terms, and/or linear minimization oracles in an inexact fashion that
facilitates the practical application of the algorithm to computationally
intensive settings, e.g. in high (or possibly infinite) dimensional Hilbert
spaces commonly found in machine learning problems. The algorithm is able to
solve composite minimization problems involving the sum of three convex proper
lower-semicontinuous functions subject to an affine constraint of the form
$Ax=b$ for some bounded linear operator $A$. Only one of the functions in the
objective is assumed to be differentiable, the other two are assumed to have an
accessible prox operator and a linear minimization oracle. As main results, we
show convergence of the Lagrangian to an optimum and asymptotic feasibility of
the affine constraint as well as weak convergence of the dual variable to a
solution of the dual problem, all in an almost sure sense. Almost sure
convergence rates, both pointwise and ergodic, are given for the Lagrangian
values and the feasibility gap. Numerical experiments verifying the predicted
rates of convergence are shown as well.


  The on-top pair density [$\Pi(\mathrm{\mathbf{r}})$] is a local
quantum-chemical property that reflects the probability of two electrons of any
spin to occupy the same position in space. Being the simplest quantity related
to the two-particle density matrix, the on-top pair density is a powerful
indicator of electron correlation effects, and as such, it has been extensively
used to combine density functional theory and multireference wavefunction
theory. The widespread application of $\Pi(\mathrm{\mathbf{r}})$ is currently
hindered by the need for post-Hartree--Fock or multireference computations for
its accurate evaluation. In this work, we propose the construction of a machine
learning model capable of predicting the CASSCF-quality on-top pair density of
a molecule only from its structure and composition. Our model, trained on the
GDB11-AD-3165 database, is able to predict with minimal error the on-top pair
density of organic molecules, bypassing completely the need for $\textit{ab
initio}$ computations. The accuracy of the regression is demonstrated using the
on-top ratio as a visual metric of electron correlation effects and
bond-breaking in real-space. In addition, we report the construction of a
specialized basis set, built to fit the on-top pair density in a single
atom-centered expansion. This basis, cornerstone of the regression, could be
potentially used also in the same spirit of the resolution-of-the-identity
approximation for the electron density.


  We present a prototype of an automatic page turning system that works
directly on real scores, i.e., sheet images, without any symbolic
representation. Our system is based on a multi-modal neural network
architecture that observes a complete sheet image page as input, listens to an
incoming musical performance, and predicts the corresponding position in the
image. Using the position estimation of our system, we use a simple heuristic
to trigger a page turning event once a certain location within the sheet image
is reached. As a proof of concept we further combine our system with an actual
machine that will physically turn the page on command.


  A practical and scalable multicast beamformer design in multi-input
multi-output~(MIMO) coded caching~(CC) systems is introduced in this paper. The
proposed approach allows multicast transmission to multiple groups with
partially overlapping user sets using receiver dimensions to distinguish
between different group-specific streams. Additionally, it provides flexibility
in accommodating various parameter configurations of the MIMO-CC setup and
overcomes practical limitations, such as the requirement to use successive
interference cancellation~(SIC) at the receiver, while achieving the same
degrees-of-freedom~(DoF). To evaluate the proposed scheme, we define the
symmetric rate as the sum rate of the partially overlapping streams received
per user, comprising a linear multistream multicast transmission vector and the
linear minimum mean square error~(LMMSE) receiver. The resulting non-convex
symmetric rate maximization problem is solved using alternative optimization
and successive convex approximation~(SCA). Moreover, a fast iterative
Lagrangian-based algorithm is developed, significantly reducing the
computational overhead compared to previous designs. The effectiveness of our
proposed method is demonstrated by extensive simulations.


  Radiation controls the dynamics and energetics of many astrophysical
environments. To capture the coupling between the radiation and matter,
however, is often a physically complex and computationally expensive endeavour.
We develop a numerical tool to perform radiation-hydrodynamics simulations in
various configurations at an affordable cost. We build upon the finite volume
code MPI-AMRVAC to solve the equations of hydrodynamics on multi-dimensional
adaptive meshes and introduce a new module to handle the coupling with
radiation. A non-equilibrium, flux-limiting diffusion approximation is used to
close the radiation momentum and energy equations. The time-dependent radiation
energy equation is then solved within a flexible framework, accounting fully
for radiation forces and work terms and further allowing the user to adopt a
variety of descriptions for the radiation-matter interaction terms (the
'opacities'). We validate the radiation module on a set of standard testcases
for which different terms of the radiative energy equation predominate. As a
preliminary application to a scientific case, we calculate spherically
symmetric models of the radiation-driven and optically thick supersonic
outflows from massive Wolf-Rayet stars. This also demonstrates our code's
flexibility, as the illustrated simulation combines opacities typically used in
static stellar structure models with a parametrised form for the enhanced
line-opacity expected in supersonic flows. This new module provides a
convenient and versatile tool to perform multi-dimensional and high resolution
radiative-hydrodynamics simulations in optically thick environments with the
MPI-AMRVAC code. The code is ready to be used for a variety of astrophysical
applications, where a first target for us will be multi-dimensional simulations
of stellar outflows from Wolf-Rayet stars.


  The proliferation of online misinformation has posed significant threats to
public interest. While numerous online users actively participate in the combat
against misinformation, many of such responses can be characterized by the lack
of politeness and supporting facts. As a solution, text generation approaches
are proposed to automatically produce counter-misinformation responses.
Nevertheless, existing methods are often trained end-to-end without leveraging
external knowledge, resulting in subpar text quality and excessively repetitive
responses. In this paper, we propose retrieval augmented response generation
for online misinformation (RARG), which collects supporting evidence from
scientific sources and generates counter-misinformation responses based on the
evidences. In particular, our RARG consists of two stages: (1) evidence
collection, where we design a retrieval pipeline to retrieve and rerank
evidence documents using a database comprising over 1M academic articles; (2)
response generation, in which we align large language models (LLMs) to generate
evidence-based responses via reinforcement learning from human feedback (RLHF).
We propose a reward function to maximize the utilization of the retrieved
evidence while maintaining the quality of the generated text, which yields
polite and factual responses that clearly refutes misinformation. To
demonstrate the effectiveness of our method, we study the case of COVID-19 and
perform extensive experiments with both in- and cross-domain datasets, where
RARG consistently outperforms baselines by generating high-quality
counter-misinformation responses.


  The self-simulational theory of temporal extension describes an
information-theoretically formalized mechanism by which the width of subjective
temporality emerges from the architecture of self-modelling. In this paper, the
perspective of the free energy principle will be assumed, to cast the emergence
of subjective temporality, along with a mechanism for duration estimation, from
first principles of the physics of self-organization. Using active inference, a
deep parametric generative model of temporal inference is simulated, which
realizes the described dynamics on a computational level. Two biases (i.e.
variations) of time-perception naturally emerge from the simulation. This
concerns the intentional binding effect (i.e. the subjective compression of the
temporal interval between voluntarily initiated actions and subsequent sensory
consequences) and empirically documented alterations of subjective time
experience in deep and concentrated states of meditative absorption. Generally,
numerous systematic and domain-specific variations of subjective time
experience are computationally explained, as enabled by integration with
current active inference accounts mapping onto the respective domains. This
concerns the temporality modulating role of negative valence, impulsivity,
boredom, flow-states, and near death-experiences, amongst others. The
self-simulational theory of temporal extension, from the perspective of the
free energy principle, explains how the subjective temporal Now emerges and
varies from first principles, accounting for why sometimes, subjective time
seems to fly, and sometimes, moments feel like eternities; with the
computational mechanism being readily deployable synthetically.


  Finsler geometry naturally appears in the description of various physical
systems. In this review I divide the emergence of Finsler geometry in physics
into three categories: as dual description of dispersion relations, as most
general geometric clock and as geometry being compatible with the relevant
Ehlers-Pirani-Schild axioms. As Finsler geometry is a straightforward
generalisation of Riemannian geometry there are many attempts to use it as
generalized geometry of spacetime in physics. However, this generalisation is
subtle due to the existence of non-trivial null directions. I review how a
pseudo-Finsler spacetime geometry can be defined such that it provides a
precise notion of causal curves, observers and their measurements as well as a
gravitational field equation determining the Finslerian spacetime geometry
dynamically. The construction of such Finsler spacetimes lays they foundation
for comparing their predictions with observations, in astrophysics as well as
in laboratory experiments.


  We present a combination of measurements of the mass of the top quark,
$m_{\rm top}$, performed by the CDF and D0 experiments at the Tevatron collider
and the ATLAS and CMS experiments at the Large Hadron Collider (LHC). The
Tevatron data correspond to an integrated luminosity of up to 8.7 fb${^{-1}}$
of proton-antiproton collisions from Run II of the Tevatron at a centre-of-mass
energy of 1.96 TeV. The LHC data correspond to an integrated luminosity of up
to 4.9 fb${^{-1}}$ of proton-proton collisions from the run at a centre-of-mass
energy of 7 TeV. The combination includes measurements in the $t\bar t\to$
lepton+jets, $t\bar t\to$ dilepton, $t\bar t\to$ all jets and $t\bar t\to$
$E_{\rm T}^{\rm miss}$+jets final states. The resulting combined measurement of
$m_{\rm top}$ is $173.34 \pm 0.27 \mbox{(stat)} \pm 0.71 \mbox{(syst)}$ GeV,
with a total uncertainty of $0.76$ GeV.


  In training deep neural networks for semantic segmentation, the main limiting
factor is the low amount of ground truth annotation data that is available in
currently existing datasets. The limited availability of such data is due to
the time cost and human effort required to accurately and consistently label
real images on a pixel level. Modern sandbox video game engines provide open
world environments where traffic and pedestrians behave in a pseudo-realistic
manner. This caters well to the collection of a believable road-scene dataset.
Utilizing open-source tools and resources found in single-player modding
communities, we provide a method for persistent, ground truth, asset annotation
of a game world. By collecting a synthetic dataset containing upwards of
$1,000,000$ images, we demonstrate real-time, on-demand, ground truth data
annotation capability of our method. Supplementing this synthetic data to
Cityscapes dataset, we show that our data generation method provides
qualitative as well as quantitative improvements---for training networks---over
previous methods that use video games as surrogate.


  Recently, some studies have utilized the Markov Decision Process for
diversifying (MDP-DIV) the search results in information retrieval. Though
promising performances can be delivered, MDP-DIV suffers from a very slow
convergence, which hinders its usability in real applications. In this paper,
we aim to promote the performance of MDP-DIV by speeding up the convergence
rate without much accuracy sacrifice. The slow convergence is incurred by two
main reasons: the large action space and data scarcity. On the one hand, the
sequential decision making at each position needs to evaluate the
query-document relevance for all the candidate set, which results in a huge
searching space for MDP; on the other hand, due to the data scarcity, the agent
has to proceed more "trial and error" interactions with the environment. To
tackle this problem, we propose MDP-DIV-kNN and MDP-DIV-NTN methods. The
MDP-DIV-kNN method adopts a $k$ nearest neighbor strategy, i.e., discarding the
$k$ nearest neighbors of the recently-selected action (document), to reduce the
diversification searching space. The MDP-DIV-NTN employs a pre-trained
diversification neural tensor network (NTN-DIV) as the evaluation model, and
combines the results with MDP to produce the final ranking solution. The
experiment results demonstrate that the two proposed methods indeed accelerate
the convergence rate of the MDP-DIV, which is 3x faster, while the accuracies
produced barely degrade, or even are better.


  We provide a description of the transverse momentum spectrum of single
inclusive forward jets produced at the LHC, at the center-of-mass energies of 7
and 13 TeV, using the high energy factorization (HEF) framework. We
subsequently study double inclusive forward jet production and, in particular,
we calculate contributions to azimuthal angle distributions coming from double
parton scattering. We also compare our results for double inclusive jet
production to those obtained with the Pythia Monte Carlo generator. This
comparison confirms that the HEF resummation acts like an initial state parton
shower. It also points towards the need to include final state radiation
effects in the HEF formalism.


  Let $f\colon X\to\mathbb{A}^1_k$ be a morphism from a smooth variety to an
affine line with an isolated singular point. For such a singularity, we have
two invariants. One is a non-degenerate symmetric bilinear form (de Rham), and
the other is the vanishing cycles complex (\'etale).
  In this article, we give a formula which expresses the local epsilon factor
of the vanishing cycles complex in terms of the bilinear form. In particular,
the sign of the local epsilon factor is determined by the discriminant of the
bilinear form. This formula can be thought as a refinement of the Milnor
formula, which compares the total dimension of the vanishing cycles and the
rank of the bilinear form.
  In characteristic $2$, we find a generalization of the Arf invariant, which
can be regarded as an invariant for non-degenerate quadratic singularities, to
general isolated singularities.


  We derive a general expression for the absorptive part of the one-loop photon
polarization tensor in a strongly magnetized quark-gluon plasma at nonzero
baryon chemical potential. To demonstrate the application of the main result in
the context of heavy-ion collisions, we study the effect of a nonzero baryon
chemical potential on the photon emission rate. The rate and the ellipticity of
photon emission are studied numerically as a function the transverse momentum
(energy) for several values of temperature and chemical potential. When the
chemical potential is small compared to the temperature, the rates of the quark
and antiquark splitting processes (i.e., $q\rightarrow q +\gamma$ and
$\bar{q}\rightarrow \bar{q} +\gamma$, respectively) are approximately the same.
However, the quark splitting gradually becomes the dominant process with
increasing the chemical potential. We also find that increasing the chemical
potential leads to a growing total photon production rate but has only a small
effect on the ellipticity of photon emission. The quark-antiquark annihilation
($q+\bar{q}\rightarrow \gamma$) also contributes to the photon production, but
its contribution remains relatively small for a wide range of temperatures and
chemical potentials investigated.


  Radiation from the blazar class of of active galactic nuclei (AGN) exhibits
fast time variability which is usually ascribed to instabilities in the
emission region near the central supermassive black hole. The variability time
scale is generally faster in higher energy region, and data recently provided
by the {\it Fermi} Gamma-ray Space Telescope in the GeV energy band enable a
detailed study of the temporal behavior of AGN. Due to its wide field-of-view
in the scanning mode, most sky regions are observed for several hours per day
and daily light curves of many AGN have been accumulated for more than 4 years.
  In this paper we investigate the time variability of 15 well-detected AGNs by
studying the normalized power spectrum density (NPSD) of their light curves in
the GeV energy band. One source, 3C 454.3, shows a specific time scale of
$6.8\times10^5$ s, and this value suggests, assuming the internal shock model,
a mass for the central black hole of $(10^8$--$10^{10})M_\odot$ which is
consistent with other estimates. It also indicates the typical time interval of
ejected blobs is $(7$--$70)$ times the light crossing time of the Schwarzschild
radius.


  Recent image classification algorithms, by learning deep features from
large-scale datasets, have achieved significantly better results comparing to
the classic feature-based approaches. However, there are still various
challenges of image classifications in practice, such as classifying noisy
image or image-set queries and training deep image classification models over
the limited-scale dataset. Instead of applying generic deep features, the
model-based approaches can be more effective and data-efficient for robust
image and image-set classification tasks, as various image priors are exploited
for modeling the inter- and intra-set data variations while preventing
over-fitting. In this work, we propose a novel Joint Statistical and Spatial
Sparse representation, dubbed \textit{J3S}, to model the image or image-set
data for classification, by reconciling both their local patch structures and
global Gaussian distribution mapped into Riemannian manifold. To the best of
our knowledge, no work to date utilized both global statistics and local patch
structures jointly via joint sparse representation. We propose to solve the
joint sparse coding problem based on the J3S model, by coupling the local and
global image representations using joint sparsity. The learned J3S models are
used for robust image and image-set classification. Experiments show that the
proposed J3S-based image classification scheme outperforms the popular or
state-of-the-art competing methods over FMD, UIUC, ETH-80 and YTC databases.


  Social Coding Sites (SCSs) are social media services for sharing software
development projects on the Web, and many open source projects are currently
being developed on SCSs. One of the characteristics of SCSs is that they
provide a platform on social networks that encourages collaboration between
developers with the same interests and purpose. For example, external
developers can easily report bugs and improvements to the project members. In
this paper, we investigate keys to the success of projects on SCSs based on
large data consisting of more than three hundred thousand projects. We focus on
the following three perspectives: 1) the team structure, 2) social activity
with external developers, and 3) content developed by the project. To evaluate
the success quantitatively, we define activity, popularity and sociality as
success indexes. A summary of the findings we obtained by using the techniques
of correlation analysis, social network analysis and topic extraction is as
follows: the number of project members and the connectivity between the members
are positively correlated with success indexes. Second, projects that
faithfully tackle change requests from external developers are more likely to
be successful. Third, the success indexes differ between topics of softwares
developed by projects. Our analysis suggests how to be successful in various
projects, not limited to social coding.


  SuperFGD, a highly granular scintillator detector, is under construction to
reduce systematic uncertainties in the T2K experiment in order to improve the
sensitivity to CP-violation in neutrino oscillations. SuperFGD will be
comprised of about 2x10^6 small (10x10x10 mm^3) optically isolated polystyrene
based plastic scintillator cubes with three orthogonal holes 1.5 mm in
diameter. The readout of scintillating light from each cube is provided by
three wavelength shifting fibers inserted into the three holes and coupled to
MPPC micropixel photosensors. The cubes are covered with a white chemical
reflector for optical isolation. The technology of making these cubes, their
mechanical properties, their main characteristics obtained during tests with
cosmic muons and at the CERN beamline, and the results of the temperature tests
are presented in this paper.


  The group of affine transformations with rational coefficients, $aff(Q)$,
acts naturally on the real line, but also on the $p$-adic fields. The aim of
this note is to show that all these actions are necessary and sufficient to
represent bounded $\mu$-harmonic functions for a probability measure $\mu$ on
$aff(Q)$ that is supported by a finitely generated sub-group, that is to
describe the Poisson boundary.


  We present two new extractions of the QCD coupling constant at the Z pole,
$\alpha_S(m_Z)$, from detailed comparisons of inclusive W and Z hadronic decays
data to state-of-the-art perturbative Quantum Chromodynamics calculations at
next-to-next-to-next-to-leading order (N$^{3}$LO) accuracy, incorporating the
latest experimental and theoretical developments. In the W boson case, the
total width computed at N$^{3}$LO is used for the first time in the extraction.
For the Z boson pseudo-observables, the N$^{3}$LO results are complemented with
the full two- and partial three-loop electroweak corrections recently made
available, and the experimental values are updated to account for newly
estimated LEP luminosity biases. A combined reanalysis of the Z boson data
yields $\alpha_S(m_Z) = 0.1203 \pm 0.0028$, with a 2.3\% uncertainty reduced by
about 7\% compared to the previous state-of-the-art. From the combined W boson
data, a value of $\alpha_S(m_Z) = 0.101 \pm 0.027$ is extracted, with still
large experimental uncertainties but also reduced compared to previous works.
The levels of theoretical and parametric precision required in the context of
QCD coupling determinations with permil uncertainties from high-statistics W
and Z boson samples expected at future $e^+e^-$ colliders such as the FCC-ee,
are discussed in detail.


  The supermassive black hole, Sagittarius A* (Sgr A*), at the centre of the
Milky Way undergoes regular flaring activity which is thought to arise from the
innermost region of the accretion flow. We performed the monitoring
observations of the Galactic Centre to study the flux-density variations at 3mm
using the Australia Telescope Compact Array (ATCA) between 2010 and 2014. We
obtain the light curves of Sgr A* by subtracting the contributions from the
extended emission around it, and the elevation and time dependent gains of the
telescope. We perform structure function analysis and the Bayesian blocks
representation to detect flare events. The observations detect six instances of
significant variability in the flux density of Sgr A* in three observations,
with variations between 0.5 to 1.0 Jy, which last for 1.5 $-$ 3 hours. We use
the adiabatically expanding plasmon model to explain the short time-scale
variations in the flux density. We derive the physical quantities of the
modelled flare emission, such as the source expansion speed $v_{\mathrm{exp}}$,
source sizes, spectral indices, and the turnover frequency. These parameters
imply that the expanding source components are either confined to the immediate
vicinity of Sgr A* by contributing to the corona or the disc, or have a bulk
motion greater than $v_{\mathrm{exp}}$. No exceptional flux density variation
on short flare time-scales was observed during the approach and the flyby of
the dusty S-cluster object (DSO/G2). This is consistent with its compactness
and the absence of a large bow shock.


  In the standard model of cosmology, structure emerges out of non-rotational
flow and the angular momentum of collapsing halos is induced by tidal torques.
The growth of halo angular momentum in the linear and quasi-linear phases is
associated with a shear, curl-free, flow and it is well described within the
linear framework of tidal torque theory (TTT). However, TTT is rendered
irrelevant as haloes approach turn around and virialization. At that stage the
flow field around halos has non-zero vorticity. Using a cosmological
simulation, we have examined the importance of the curl of the velocity field
(vorticity) in determining halo spin, finding a strong alignment between the
two. We have also examined the alignment of vorticity with the principle axes
of the shear tensor, finding that it tends to be perpendicular to the axis
along which material is collapsing fastest (e1). This behavior is independent
of halo masses and cosmic web environment. Our results agree with previous
findings on the tendency of halo spin to be perpendicular to e1, and of the
spin of (simulated) halos and (observed) galaxies to be aligned with the
large-scale structure. Our results imply that angular momentum growth proceeds
in two distinct phases. In the first phase angular momentum emerges out of a
shear, curl-free, potential flow, as described by TTT. In the second phase, in
which haloes approach virialization, the angular momentum emerges out of a
vortical flow and halo spin becomes strongly aligned with the vorticity of the
ambient flow field.


  The planet candidates discovered by the Kepler mission provide a rich sample
to constrain the architectures and relative inclinations of planetary systems
within approximately 0.5 AU of their host stars. We use the triple-transit
systems from the Kepler 16-months data as templates for physical triple-planet
systems and perform synthetic transit observations. We find that all the Kepler
triple-transit and double-transit systems can be produced from the
triple-planet templates, given a low mutual inclination of around five degrees.
Our analysis shows that the Kepler data contains a population of planets larger
than four Earth radii in single-transit systems that can not arise from the
triple-planet templates. We explore the hypothesis that high-mass counterparts
of the triple-transit systems underwent dynamical instability to produce a
population of massive double-planet systems of moderately high mutual
inclination. We perform N-body simulations of mass-boosted triple-planet
systems and observe how the systems heat up and lose planets, most frequently
by planet-planet collisions, yielding transits in agreement with the large
planets in the Kepler single-transit systems. The resulting population of
massive double-planet systems can nevertheless not explain the additional
excess of low-mass planets among the observed single-transit systems and the
lack of gas-giant planets in double-transit and triple-transit systems.
Planetary instability of systems of triple gas-giant planets can be behind part
of the dichotomy between systems hosting one or more small planets and those
hosting a single giant planet. The main part of the dichotomy, however, is more
likely to have arisen already during planet formation when the formation,
migration or scattering of a massive planet, triggered above a threshold
metallicity, suppressed the formation of other planets in sub-AU orbits.


  Wireless power transfer (WPT) is a viable source of energy for wirelessly
powered communication networks (WPCNs). In this paper, we first consider WPT
from an energy access point (E-AP) to multiple energy receivers (E-Rs) to
obtain the optimal policy that maximizes the WPT efficiency. For this purpose,
we formulate the problem of maximizing the total average received power of the
E-Rs subject to the average and peak power level constraints of the E-AP. The
formulated problem is a non-convex stochastic optimization problem. Using some
stochastic optimization techniques, we tackle the challenges of this problem
and derive a closed-form expression for the optimal solution, which requires
the explicit knowledge of the distribution of channel state information (CSI)
in the network. We then propose a near-optimal algorithm that does not require
any explicit knowledge of the CSI distribution and prove that the proposed
algorithm attains a near-optimal solution within a guaranteed gap to the
optimal solution. We next consider fairness among the E-Rs and propose a
quality of service (QoS) aware fair policy that maximizes a generic network
utility function while guaranteeing the required QoS of each E-R. Finally, we
study a practical wirelessly powered communication scenario in which the E-Rs
utilize their energy harvested through WPT to transmit information to the E-AP.
We optimize the received information at the E-AP under its average and peak
transmission power constraints and the fairness constraints of the E-Rs.
Numerical results show the significant performance of our proposed solutions
compared to the state-of-the-art baselines.


  A genuine notion of black holes can only be obtained in the fundamental
framework of quantum gravity resolving the curvature singularities and giving
an account of the statistical mechanical, microscopic degrees of freedom able
to explain the black hole thermodynamical properties. As for all quantum
systems, a quantum realization of black holes requires an operator algebra of
the fundamental observables of the theory which is introduced in this study
based on aspects of loop quantum gravity. From the eigenvalue spectra of the
quantum operators for the black hole area, charge and angular momentum, it is
demonstrated that a strict bound on the extensive parameters, different from
the relation arising in classical general relativity, holds, implying that the
extremal black hole state can neither be measured nor can its existence be
proven. This is, as turns out, a result of the specific form of the chosen
angular momentum operator and the corresponding eigenvalue spectrum, or rather
the quantum measurement process of angular momentum. Quantum mechanical
considerations and the lowest, non-zero eigenvalue of the loop quantum gravity
black hole mass spectrum indicate, on the one hand, a physical Planck scale
cutoff of the Hawking temperature law and, on the other hand, give upper and
lower bounds on the numerical value of the Immirzi parameter. This analysis
provides an approximative description of the behavior and the nature of quantum
black holes.


  It is important to map the large-scale matter distribution in the local
Universe for cosmological studies, such as the tracing of the large-scale
peculiar velocity flow, the characterisation of the environment for different
astronomical objects, and for precision measurements of cosmological
parameters. We used X-ray luminous clusters to map this matter distribution and
find that about 51% of the groups and clusters are members of superclusters
which occupy only a few percent of the volume. In this paper we provide a
detailed description of these large-scale structures. With a friends-to-friends
algorithm, we find eight superclusters with a cluster overdensity ratio of at
least two with five or more galaxy group and cluster members in the cosmic
volume out to z = 0.03. The four most prominent ones are the Perseus-Pisces,
the Centaurus, the Coma, and the Hercules supercluster, with lengths from about
40 to over 100 Mpc and estimated masses of 0.6 - 2.2 10^16 Msun. The largest of
these structures is the Perseus-Pisces supercluster. The four smaller
superclusters include the Local and the Abell 400 supercluster and two
superclusters in the constellations Sagittarius and Lacerta. We provide
detailed maps, member catalogues, and physical descriptions of the eight
superclusters. By constructing superclusters with a range of cluster
sub-samples with different lower X-ray luminosity limits, we show that the main
structures are always reliably recovered.


  The dynamics of distributed sources is described by nonlinear partial
differential equations. Lagrangian analytical solutions of these (and
associated) equations are obtained and discussed in the context of Lagrangian
modeling - from the Lagrangian invariants to dynamics. Possible applications of
distributed sources and sinks to geophysical fluid dynamics and to the
cosmology are indicated.


  We describe here some new results concerning the Lorentzian Barrett-Crane
model, a well-known spin foam formulation of quantum gravity. Generalizing an
existing finiteness result, we provide a concise proof of finiteness of the
partition function associated to all non-degenerate triangulations of
4-manifolds and for a class of degenerate triangulations not previously shown.
This is accomplished by a suitable re-factoring and re-ordering of integration,
through which a large set of variables can be eliminated. The resulting
formulation can be interpreted as a ``dual variables'' model that uses
hyperboloid variables associated to spin foam edges in place of representation
variables associated to faces. We outline how this method may also be useful
for numerical computations, which have so far proven to be very challenging for
Lorentzian spin foam models.


  Let $n$, $k$ and $l$ be integers with $1\leq k<l\leq n-1$. The set-inclusion
graph $G(n,k,l)$ is the graph whose vertex set consists of all $k$- and
$l$-subsets of $[n]=\{1,2,\ldots,n\}$, where two distinct vertices are adjacent
if one of them is contained in another. In this paper, we determine the
spectrum and automorphism group of $G(n,k,l)$, respectively.


  We investigate near threshold neutral pion photoproduction off protons to
fourth order in heavy baryon chiral perturbation theory in the light of the new
data from MAMI. We show that the unitarity cusp at the secondary \pi^+ n
threshold is in agreement with expectations from the final state theorem. We
also analyze the fourth order corrections to the P-wave low-energy theorems and
show that potentially large Delta-isobar contributions are cancelled by
sizeable pion loop effects. This solidifies the parameter free third order
predictions, which are in excellent agreement with the data.


  We study the effect of the meson cloud dressing in the octet baryon to
decuplet baryon electromagnetic transitions. Combining the valence quark
contributions from the covariant spectator quark model with those of the meson
cloud estimated based on the flavor SU(3) cloudy bag model, we calculate the
transition magnetic form factors at $Q^2=0$ ($Q^2=-q^2$ and $q$ the
four-momentum transfer), and also the decuplet baryon electromagnetic decay
widths. The result for the $\gamma^\ast \Lambda \to \Sigma^{\ast 0}$ decay
width is in complete agreement with the data, while that for the $\gamma^\ast
\Sigma^+ \to \Sigma^{\ast +}$ is underestimated the data by 1.4 standard
deviations. This achievement may be regarded as a significant advance in the
present theoretical situation.


  We present controllers that enable mobile robots to persistently monitor or
sweep a changing environment. The changing environment is modeled as a field
which grows in locations that are not within range of a robot, and decreases in
locations that are within range of a robot. We assume that the robots travel on
given closed paths. The speed of each robot along its path is controlled to
prevent the field from growing unbounded at any location. We consider the space
of speed controllers that can be parametrized by a finite set of basis
functions. For a single robot, we develop a linear program that is guaranteed
to compute a speed controller in this space to keep the field bounded, if such
a controller exists. Another linear program is then derived whose solution is
the speed controller that minimizes the maximum field value over the
environment. We extend our linear program formulation to develop a multi-robot
controller that keeps the field bounded. The multi-robot controller has the
unique feature that it does not require communication among the robots.
Simulation studies demonstrate the robustness of the controllers to modeling
errors, and to stochasticity in the environment.


  A standard technique in infinite dimensional holomorphy, which produced
several useful results, uses the Borel transform to represent linear
functionals on certain spaces of multilinear operators between Banach spaces as
multilinear operators. In this paper we develop a technique to represent linear
functionals, as linear operators, on spaces of multilinear operators that are
beyond the scope of the standard technique. Concrete applications to some well
studied classes of multilinear operators, including the class of compact
multilinear operators, and to one new class are provided. We can see, in
particular, that sometimes our representations hold under conditions less
restrictive than those of the related classical ones.


  Real-time fault detection for freight trains plays a vital role in
guaranteeing the security and optimal operation of railway transportation under
stringent resource requirements. Despite the promising results for deep
learning based approaches, the performance of these fault detectors on freight
train images, are far from satisfactory in both accuracy and efficiency. This
paper proposes a unified light framework to improve detection accuracy while
supporting a real-time operation with a low resource requirement. We firstly
design a novel lightweight backbone (RFDNet) to improve the accuracy and reduce
computational cost. Then, we propose a multi region proposal network using
multi-scale feature maps generated from RFDNet to improve the detection
performance. Finally, we present multi level position-sensitive score maps and
region of interest pooling to further improve accuracy with few redundant
computations. Extensive experimental results on public benchmark datasets
suggest that our RFDNet can significantly improve the performance of baseline
network with higher accuracy and efficiency. Experiments on six fault datasets
show that our method is capable of real-time detection at over 38 frames per
second and achieves competitive accuracy and lower computation than the
state-of-the-art detectors.


  Energy forecasting has a vital role to play in smart grid (SG) systems
involving various applications such as demand-side management, load shedding,
and optimum dispatch. Managing efficient forecasting while ensuring the least
possible prediction error is one of the main challenges posed in the grid
today, considering the uncertainty and granularity in SG data. This paper
presents a comprehensive and application-oriented review of state-of-the-art
forecasting methods for SG systems along with recent developments in
probabilistic deep learning (PDL) considering different models and
architectures. Traditional point forecasting methods including statistical,
machine learning (ML), and deep learning (DL) are extensively investigated in
terms of their applicability to energy forecasting. In addition, the
significance of hybrid and data pre-processing techniques to support
forecasting performance is also studied. A comparative case study using the
Victorian electricity consumption and American electric power (AEP) datasets is
conducted to analyze the performance of point and probabilistic forecasting
methods. The analysis demonstrates higher accuracy of the long-short term
memory (LSTM) models with appropriate hyper-parameter tuning among point
forecasting methods especially when sample sizes are larger and involve
nonlinear patterns with long sequences. Furthermore, Bayesian bidirectional
LSTM (BLSTM) as a probabilistic method exhibit the highest accuracy in terms of
least pinball score and root mean square error (RMSE).


  Cumulative resource constraints can model scarce resources in scheduling
problems or a dimension in packing and cutting problems. In order to
efficiently solve such problems with a constraint programming solver, it is
important to have strong and fast propagators for cumulative resource
constraints. One such propagator is the recently developed
time-table-edge-finding propagator, which considers the current resource
profile during the edge-finding propagation. Recently, lazy clause generation
solvers, i.e. constraint programming solvers incorporating nogood learning,
have proved to be excellent at solving scheduling and cutting problems. For
such solvers, concise and accurate explanations of the reasons for propagation
are essential for strong nogood learning. In this paper, we develop the first
explaining version of time-table-edge-finding propagation and show preliminary
results on resource-constrained project scheduling problems from various
standard benchmark suites. On the standard benchmark suite PSPLib, we were able
to close one open instance and to improve the lower bound of about 60% of the
remaining open instances. Moreover, 6 of those instances were closed.


  This paper presents theory and finite-difference time-domain (FDTD)
calculations for a single and arrays of sub-wavelength cylindrical holes in
metallic films presenting large transmission. These calculations are in
excellent agreement with experimental measurements. This effect has to be
understood in terms of the properties exhibited by the dielectric constant of
metals which cannot be treated as ideal metals for the purpose of transmission
and diffraction of light. We discuss the cases of well-differentiated metals
silver and tungsten. It is found that the effect of surface plasmons or other
surface wave excitations due to a periodical set of holes or other roughness at
the surface is marginal. The effect can enhance but also can depress the
transmission of the arrays as shown by theory and experiments. The peak
structure observed in experiments is a consequence of the interference of the
wavefronts transmitted by each hole and is determined by the surface array
period independently of the material. Without large transmission through a
single hole there is no large transmission through the array. We found that in
the case of Ag which at the discussed frequencies is a metal there are
cylindrical plasmons at the wall of the hole, as reported by Economu et al 30
years ago, that enhanced the transmission. But it turns out, as will be
explained, that for the case of W which behaves as a dielectric, there is also
a large transmission when compared with that of an ideal metal waveguide. To
deal with this problem one has to use the measured dielectric function of the
metals. We discuss thoroughly all these cases and compare with the data.


  The sequence of Ap\'ery numbers is the moment sequence in the sense of
Stieltjes. This is the short version of the proof. Appendix added for v.2


  A space-based galaxy redshift survey would have enormous power in
constraining dark energy and testing general relativity, provided that its
parameters are suitably optimized. We study viable space-based galaxy redshift
surveys, exploring the dependence of the Dark Energy Task Force (DETF)
figure-of-merit (FoM) on redshift accuracy, redshift range, survey area, target
selection, and forecast method. Fitting formulae are provided for convenience.
We also consider the dependence on the information used: the full galaxy power
spectrum P(k, P(k) marginalized over its shape, or just the Baryon Acoustic
Oscillations (BAO). We find that the inclusion of growth rate information
(extracted using redshift space distortion and galaxy clustering amplitude
measurements) leads to a factor of ~ 3 improvement in the FoM, assuming general
relativity is not modified. This inclusion partially compensates for the loss
of information when only the BAO are used to give geometrical constraints,
rather than using the full P(k) as a standard ruler. We find that a space-based
galaxy redshift survey covering ~20,000 deg^2 over 0.5< z < 2 with
\sigma_z/(1+z)<= 0.001 exploits a redshift range that is only easily accessible
from space, extends to sufficiently low redshifts to allow both a vast 3-D map
of the universe using a single tracer population, and overlaps with
ground-based surveys to enable robust modeling of systematic effects. We argue
that these parameters are close to their optimal values given current
instrumental and practical constraints.


  The predictability of a time series is determined by the sensitivity to
initial conditions of its data generating process. In this paper our goal is to
characterize this sensitivity from a finite sample by assuming few hypotheses
on the data generating model structure. In order to measure the distance
between two trajectories induced by a same noisy chaotic dynamic from two close
initial conditions, a symmetric Kullback-Leiber divergence measure is used. Our
approach allows to take into account the dependence of the residual variance on
initial conditions. We show it is linked to a Fisher information matrix and we
investigated its expressions in the cases of covariance-stationary processes
and ARCH($\infty$) processes. Moreover, we propose a consistent non-parametric
estimator of this sensitivity matrix in the case of conditionally
heteroscedastic autoregressive nonlinear processes. Various statistical
hypotheses can so be tested as for instance the hypothesis that the data
generating process is "almost" independently distributed at a given moment.
Applications to simulated data and to the stock market index S&P500 illustrate
our findings. More particularly, we highlight a significant relationship
between the sensitivity to initial conditions of the daily returns of the S&P
500 and their volatility.


  The classical table of integrals by I. S. Gradshteyn and I. M. Ryzhik
contains many definite integrals where the integrand is the product of a
rational function times the logarithm of another rational function. We begin
the systematic evaluation of these integrals.


  Industry 5.0 envisions close cooperation between humans and machines
requiring ultra-reliable and low latency communications (URLLC). The
Intelligent Reflecting Surface (IRS) has the potential to play a crucial role
in realizing wireless URLLC for Industry 5.0. IRS is forecast to be a key
enabler of 6G wireless communication networks as it can significantly improve
wireless network performance by creating a controllable radio environment. In
this paper, we first provide an overview of IRS technology and then
conceptualize the potential for IRS implementation in a future smart
manufacturing environment to support the emergence of Industry 5.0 with a
series of applications. Finally, to stimulate future research in this area, we
discuss the strength, open challenges, and opportunities of IRS technology in
modern smart manufacturing.


  This paper describes the design and implementation of GridCertLib, a Java
library leveraging a Shibboleth-based authentication infrastructure and the
SLCS online certificate signing service, to provide short-lived X.509
certificates and Grid proxies. The main use case envisioned for GridCertLib, is
to provide seamless and secure access to Grid/X.509 certificates and proxies in
web applications and portals: when a user logs in to the portal using
Shibboleth authentication, GridCertLib can automatically obtain a Grid/X.509
certificate from the SLCS service and generate a VOMS proxy from it. We give an
overview of the architecture of GridCertLib and briefly describe its
programming model. Its application to some deployment scenarios is outlined, as
well as a report on practical experience integrating GridCertLib into portals
for Bioinformatics and Computational Chemistry applications, based on the
popular P-GRADE and Django softwares.