  We consider open supermembranes in eleven dimensions in the presence of
closed M-Theory five-branes. It has been shown that, in a flat space-time, the
world-volume action is kappa invariant and preserves a fraction of the eleven
dimensional supersymmetries if the boundaries of the membranes lie on the
five-branes. We calculate the reparametrisation anomalies due to the chiral
fermions on the boundaries of the membrane and examine their cancellation
mechanism. We show that these anomalies cancel with the aid of a classical term
in the world-volume action, provided that the tensions of the five-brane and
the membrane are related to the eleven dimensional gravitational constant in a
way already noticed in M-Theory.


  Humans have the natural ability to recognize actions even if the objects
involved in the action or the background are changed. Humans can abstract away
the action from the appearance of the objects and their context which is
referred to as compositionality of actions. Compositional action recognition
deals with imparting human-like compositional generalization abilities to
action-recognition models. In this regard, extracting the interactions between
humans and objects forms the basis of compositional understanding. These
interactions are not affected by the appearance biases of the objects or the
context. But the context provides additional cues about the interactions
between things and stuff. Hence we need to infuse context into the human-object
interactions for compositional action recognition. To this end, we first design
a spatial-temporal interaction encoder that captures the human-object (things)
interactions. The encoder learns the spatio-temporal interaction tokens
disentangled from the background context. The interaction tokens are then
infused with contextual information from the video tokens to model the
interactions between things and stuff. The final context-infused
spatio-temporal interaction tokens are used for compositional action
recognition. We show the effectiveness of our interaction-centric approach on
the compositional Something-Else dataset where we obtain a new state-of-the-art
result of 83.8% top-1 accuracy outperforming recent important object-centric
methods by a significant margin. Our approach of explicit human-object-stuff
interaction modeling is effective even for standard action recognition datasets
such as Something-Something-V2 and Epic-Kitchens-100 where we obtain comparable
or better performance than state-of-the-art.


  We consider properties of semi-classical orthogonal polynomials with respect
to the generalised Airy weight
\[\omega(x;t,\lambda)=x^{\lambda}\exp\left(-\tfrac13x^3+tx\right),\qquad x\in
\mathbb{R}^+,\] with parameters $\lambda>-1$ and $t\in \mathbb{R}$. We also
investigate the zeros and recurrence coefficients of the polynomials. The
generalised sextic Freud weight
\[\omega(x;t,\lambda)=|x|^{2\lambda+1}\exp\left(-x^6+tx^2\right), \qquad x\in
\mathbb{R},\] arises from a symmetrisation of the generalised Airy weight and
we study analogous properties of the polynomials orthogonal with respect to
this weight.


  The presence of embedded electronics and communication capabilities as well
as sensing and control in smart devices has given rise to the novel concept of
cyber-physical networks, in which agents aim at cooperatively solving complex
tasks by local computation and communication. Numerous estimation, learning,
decision and control tasks in smart networks involve the solution of
large-scale, structured optimization problems in which network agents have only
a partial knowledge of the whole problem. Distributed optimization aims at
designing local computation and communication rules for the network processors
allowing them to cooperatively solve the global optimization problem without
relying on any central unit. The purpose of this survey is to provide an
introduction to distributed optimization methodologies. Principal approaches,
namely (primal) consensus-based, duality-based and constraint exchange methods,
are formalized. An analysis of the basic schemes is supplied, and
state-of-the-art extensions are reviewed.


  The human face contains important and understandable information such as
personal identity, gender, age, and ethnicity. In recent years, a person's age
has been studied as one of the important features of the face. The age
estimation system consists of a combination of two modules, the presentation of
the face image and the extraction of age characteristics, and then the
detection of the exact age or age group based on these characteristics. So far,
various algorithms have been presented for age estimation, each of which has
advantages and disadvantages. In this work, we implemented a deep residual
neural network on the UTKFace data set. We validated our implementation by
comparing it with the state-of-the-art implementations of different age
estimation algorithms and the results show 28.3% improvement in MAE as one of
the critical error validation metrics compared to the recent works and also
71.39% MAE improvements compared to the implemented AlexNet. In the end, we
show that the performance degradation of our implemented network is lower than
1.5% when injecting 15 dB noise to the input data (5 times more than the normal
environmental noise) which justifies the noise tolerance of our proposed
method.


  Recurrent neural networks (RNNs) have been widely used to deal with sequence
learning problems. The input-dependent transition function, which folds new
observations into hidden states to sequentially construct fixed-length
representations of arbitrary-length sequences, plays a critical role in RNNs.
Based on single space composition, transition functions in existing RNNs often
have difficulty in capturing complicated long-range dependencies. In this
paper, we introduce a new Multi-zone Unit (MZU) for RNNs. The key idea is to
design a transition function that is capable of modeling multiple space
composition. The MZU consists of three components: zone generation, zone
composition, and zone aggregation. Experimental results on multiple datasets of
the character-level language modeling task and the aspect-based sentiment
analysis task demonstrate the superiority of the MZU.


  A recent high-field magnetization experiment found a phase transition of
unknown character in the layered, frustrated antiferromagnet RbCuCl_3, in a
transverse field (in the layers). Motivated by these results, we have examined
the magnetic structures predicted by a model of RbCuCl_3, using the classical
approximation. At small fields, we obtain the structure already known to be
optimal, an incommensurate (IC) spiral with wave vector q in the layers. At
higher fields, we find a staircase of long-period commensurate (C) phases
(separated initially by the low-field IC phase), then two narrow IC phases,
then a fourth IC phase (also with intermediate C phases), and finally the
ferromagnetically aligned phase at the saturation field H_S. The
three-sublattice C states familiar from the theory of the triangular
antiferromagnet are never optimal. The C phases and the two intermediate IC
phases were previously unknown in this context. The magnetization is
discontinuous at a field \approx 0.4H_S, in qualitative agreement with
experiment, though we find much fine structure not reported.


  Recent work introduced the model of learning from discriminative feature
feedback, in which a human annotator not only provides labels of instances, but
also identifies discriminative features that highlight important differences
between pairs of instances. It was shown that such feedback can be conducive to
learning, and makes it possible to efficiently learn some concept classes that
would otherwise be intractable. However, these results all relied upon perfect
annotator feedback. In this paper, we introduce a more realistic, robust
version of the framework, in which the annotator is allowed to make mistakes.
We show how such errors can be handled algorithmically, in both an adversarial
and a stochastic setting. In particular, we derive regret bounds in both
settings that, as in the case of a perfect annotator, are independent of the
number of features. We show that this result cannot be obtained by a naive
reduction from the robust setting to the non-robust setting.


  Methods have previously been developed for the approximation of Lyapunov
functions using radial basis functions. However these methods assume that the
evolution equations are known. We consider the problem of approximating a given
Lyapunov function using radial basis functions where the evolution equations
are not known, but we instead have sampled data which is contaminated with
noise. We propose an algorithm in which we first approximate the underlying
vector field, and use this approximation to then approximate the Lyapunov
function. Our approach combines elements of machine learning/statistical
learning theory with the existing theory of Lyapunov function approximation.
Error estimates are provided for our algorithm.


  The question is discussed of what is the speed of gravity (at the fundamental
non-perturbative level). The question is important, if nowhere else, in
discussing the problem of information "lost" in black holes. It turns out that
the duly defined "gravitational signal" generally may be causal, superluminal
and "semi-superluminal". In the class of globally hyperbolic spacetimes the two
last varieties coincide. And if some (often imposed, but not always satisfied)
conditions hold, the signals may be \emph{only} causal. In this sense the speed
of gravity does not exceed the speed of light.


  The (supermassive black hole mass, $M_\text{BH}$)-(bulge stellar mass,
$M_{\rm*,sph}$) relation is, obviously, derived using two quantities. We
endeavor to provide accurate values for the latter via detailed multicomponent
galaxy decompositions for the current full sample of 43 spiral galaxies having
directly measured $M_\text{BH}$ values; 35 of these galaxies have been alleged
to contain pseudobulges, 21 have water maser measurements, and three appear
bulgeless. This more than doubles the previous sample size of spiral galaxies
with a finessed image analysis. We have analyzed near-infrared images,
accounting for not only the bulge, disk (exponential, truncated, or inclined),
and bar but also for spiral arms and rings and additional central components
(active galactic nuclei (AGNs), etc.). A symmetric Bayesian analysis finds
$\log\left(M_\text{BH}/M_{\odot}\right)=\left(2.44_{-0.31}^{+0.35}\right)\log\left\{M_{\rm*,sph}/[\upsilon(1.15\times10^{10}\,M_{\odot})]\right\}+(7.24\pm0.12)$,
with $\upsilon$ a stellar mass-to-light ratio term. The level of scatter equals
that about the $M_{\rm BH}$-$\sigma_*$ relation. The nonlinear slope rules out
the idea that many mergers, coupled with the central limit theorem, produced
this scaling relation, and it corroborates previous observational studies and
simulations, which have reported a near-quadratic slope at the low-mass end of
the $M_\text{BH}$-$M_{\rm*,sph}$ diagram. Furthermore, bulges with AGNs follow
this relation; they are not offset by an order of magnitude, and models that
have invoked AGN feedback to establish a linear $M_{\rm BH}$-$M_{\rm*,sph}$
relation need revisiting. We additionally present an updated
$M_\text{BH}$-(S\'ersic index, $n_\text{sph}$) relation for spiral galaxy
bulges with a comparable level of scatter and a new $M_{\rm*,sph}$-(spiral-arm
pitch angle, $\phi$) relation.


  The magnetar 1E~1547$-$5408 recently exhibited two periods of outburst,
beginning on 2008 October 3 and 2009 January 22. Here we present an analysis of
the persistent radiative evolution and a statistical study of the burst
properties during the 2009 outburst using the {\em Swift} X-ray Telescope
(XRT). We find that the 1--10 keV flux increased by a factor of $\sim500$ and
hardened significantly, peaking $\sim6$ hours after the onset of the outburst.
The observed pulsed fraction exhibited an anti-correlation with phase-averaged
flux. Properties of the several hundred X-ray bursts during the 2009 outburst
were determined and compared to those from other magnetar outburst events. We
find that the peaks of the bursts occur randomly in phase but that the folded
counts that compose the bursts exhibit a pulse which is misaligned with the
persistent pulse phase. We also report a correlation between burst hardness and
flux. We compare the hardness-flux evolution of the persistent emission of both
outbursts to those from other magnetars and find that although there does exist
an overall trend, the degree of hardening for a given increase in flux is not
uniform from source to source. These results are discussed in the context of
previous results and within the magnetar model.


  The paper considers the sequence of the Motzkin words, which is constructed
according to formal features of natural numbers. We investigate the
decomposition of well-formed parentheses into the matched pairs of parentheses
(analogous to Prime Numbers). The point triangle of bracket pairs is
constructed and studied, as well as the numerical Motzkin triangle (similar to
Pascal's triangle). To calculate the Motzkin triangle, the graphical method of
stars and bars is used.


  Momentum is a popular technique to accelerate the convergence in practical
training, and its impact on convergence guarantee has been well-studied for
first-order algorithms. However, such a successful acceleration technique has
not yet been proposed for second-order algorithms in nonconvex optimization.In
this paper, we apply the momentum scheme to cubic regularized (CR) Newton's
method and explore the potential for acceleration. Our numerical experiments on
various nonconvex optimization problems demonstrate that the momentum scheme
can substantially facilitate the convergence of cubic regularization, and
perform even better than the Nesterov's acceleration scheme for CR.
Theoretically, we prove that CR under momentum achieves the best possible
convergence rate to a second-order stationary point for nonconvex optimization.
Moreover, we study the proposed algorithm for solving problems satisfying an
error bound condition and establish a local quadratic convergence rate. Then,
particularly for finite-sum problems, we show that the proposed algorithm can
allow computational inexactness that reduces the overall sample complexity
without degrading the convergence rate.


  Transition metal dipnictides (TMDs) have recently been identified as possible
candidates to host topology protected electronic band structure. These
materials belong to an isostructural family and show several exotic transport
properties. Especially, the large values of magnetoresistance (MR) and carrier
mobility have drawn significant attention from the perspective of technological
applications. In this report, we have investigated the magnetotransport and
Fermi surface properties of single crystalline MoAs$_{2}$, another member of
this group of compounds. Field induced resistivity plateau and a large MR have
been observed, which are comparable to several topological systems.
Interestingly, in contrast to other isostructural materials, the carrier
density in MoAs$_{2}$ is quite high and shows single-band dominated transport.
The Fermi pockets, which have been identified from the quantum oscillation, are
largest among the members of this group and have significant anisotropy with
crystallographic direction. Our first-principles calculations reveal a
substantial difference between the band structures of MoAs$_{2}$ and other
TMDs. The calculated Fermi surface consists of one electron pocket and another
'open-orbit' hole pocket, which has not been observed in TMDs so far.


  We developed a comprehensive semiclassical theory of solitons in one
dimensional systems at BCS-BEC crossover to provide a semiclassical explanation
of their excitation spectra. Our semiclassical results agree well with the
exact solutions on both the deep BCS and deep BEC side and explain
qualitatively the smooth crossover between them. Especially, we showed that the
minimum energy of the $S=1/2$ excitation is achieved exactly at the Fermi
momentum $k_F=\pi n/2$, where $nm_F$ ($m_F$ is the mass of the fermionic atom)
is the total mass density of the system. This momentum remains unchanged along
the whole crossover, whether the mass is contained in the bosonic molecules as
on the deep BEC side or in the fermionic atoms as on the deep BCS side. This
phenomenon comes about as a result of a special feature of one dimensional
systems that the conventional quasiparticle is not stable with respect to
soliton formation. It is valid not only in exactly solvable models but also on
the level of semiclassical theory. Besides, we also resolved the inconsistency
of existing semiclassical theory with the exact solution of soliton-like $S=0$
excitations on the deep BCS side by a new proposal of soliton configuration.


  Photon attenuation and scatter are the two main physical factors affecting
the diagnostic quality of SPECT in its applications in brain imaging. In this
work, we present a novel Bayesian Optimization approach for Attenuation
Correction (BOAC) in SPECT brain imaging. BOAC utilizes a prior model
parametrizing the head geometry and exploits High Performance Computing (HPC)
to reconstruct attenuation corrected images without requiring prior anatomical
information from complementary CT scans. BOAC is demonstrated in SPECT brain
imaging using noisy and attenuated sinograms, simulated from numerical
phantoms. The quality of the tomographic images obtained with the proposed
method are compared to those obtained without attenuation correction by
employing the appropriate image quality metrics. The quantitative results show
the capacity of BOAC to provide images exhibiting higher contrast and less
background artifacts as compared to the non-attenuation corrected MLEM images.


  Social intelligence is an important requirement for enabling robots to
collaborate with people. In particular, human path prediction is an essential
capability for robots in that it prevents potential collision with a human and
allows the robot to safely make larger movements. In this paper, we present a
method for predicting the trajectory of a human who follows a haptic robotic
guide without using sight, which is valuable for assistive robots that aid the
visually impaired. We apply a deep learning method based on recurrent neural
networks using multimodal data: (1) human trajectory, (2) movement of the
robotic guide, (3) haptic input data measured from the physical interaction
between the human and the robot, (4) human depth data. We collected actual
human trajectory and multimodal response data through indoor experiments. Our
model outperformed the baseline result while using only the robot data with the
observed human trajectory, and it shows even better results when using
additional haptic and depth data.


  We obtain a class of exact solutions of a Bessel-type differential equation,
which is a six-parameter linear ordinary differential equation of the second
order with irregular (essential) singularity at the origin. The solutions are
obtained using the Tridiagonal Representation Approach (TRA) as bounded series
of square integrable functions written in terms of the Bessel polynomial on the
real line. The expansion coefficients of the series are orthogonal polynomials
in the equation parameters space. We use our findings to obtain solutions of
the Schr\"odinger equation for some novel potential functions.


  We propose a quantum absorption refrigerator using the quantum physics of
resonant tunneling through quantum dots. The cold and hot reservoirs are
fermionic leads, tunnel coupled via quantum dots to a central fermionic cavity,
and we propose configurations in which the heat absorbed from the (very hot)
central cavity is used as a resource to selectively transfer heat from the cold
reservoir on the left, to the hot reservoir on the right. The heat transport in
the device is particle---hole symmetric; we find two regimes of cooling as a
function of the energy of the dots---symmetric with respect to the Fermi energy
of the reservoirs---and we associate them to heat transfer by electrons above
the Fermi level, and holes below the Fermi level, respectively. We also discuss
optimizing the cooling effect by fine-tuning the energy of the dots as well as
their linewidth, and characterize regimes where the transport is
thermodynamically reversible such that Carnot Coefficent of Performance is
achieved with zero cooling power delivered.


  We study the fusion of a proton with a nucleus with the emission of two
photons at low incident energy of the order of eV or smaller. We use a step
model for the repulsive potential between proton and the nuclei. We consider
the reaction both in free space and inside a medium. We make a simple model for
the medium by assuming a hard wall potential beyond a certain length scale.
This essentially leads to discretization of the energy spectrum which is
expected inside a medium and is seen both for a crystalline lattice structure
and for amorphous materials. We use second order perturbation theory to compute
the transition rate. We find that the rate in free space is very small. However
in medium, the rate may be substantial. Hence, we conclude that nuclear fusion
reactions may take place at low energies at observable rates.


  A Lefschetz-type coincidence theorem for two maps f,g:X->Y from an arbitrary
topological space X to a manifold Y is given: I(f,g)=L(f,g), the coincidence
index is equal to the Lefschetz number. It follows that if L(f,g) is not equal
to zero then there is an x in X such that f(x)=g(x). In particular, the theorem
contains some well-known coincidence results for (i) X,Y manifolds and (ii) f
with acyclic fibers.


  We review the theoretical status of the models including the multinucleon
emission channel in the calculation of quasielastic neutrino cross sections at
MiniBooNE kinematics.


  Large Language Models (LLMs) are increasingly integrated into software
applications. Downstream application developers often access LLMs through APIs
provided as a service. However, LLM APIs are often updated silently and
scheduled to be deprecated, forcing users to continuously adapt to evolving
models. This can cause performance regression and affect prompt design choices,
as evidenced by our case study on toxicity detection. Based on our case study,
we emphasize the need for and re-examine the concept of regression testing for
evolving LLM APIs. We argue that regression testing LLMs requires fundamental
changes to traditional testing approaches, due to different correctness
notions, prompting brittleness, and non-determinism in LLM APIs.


  If the recent indications of a possible state $\Phi$ with mass $\sim 750$ GeV
decaying into two photons reported by ATLAS and CMS in LHC collisions at 13 TeV
were to become confirmed, the prospects for future collider physics at the LHC
and beyond would be affected radically, as we explore in this paper. Even
minimal scenarios for the $\Phi$ resonance and its $\gamma \gamma$ decays
require additional particles with masses $\gtrsim \frac12 m_\Phi$. We consider
here two benchmark scenarios that exemplify the range of possibilities: one in
which $\Phi$ is a singlet scalar or pseudoscalar boson whose production and
$\gamma \gamma$ decays are due to loops of coloured and charged fermions, and
another benchmark scenario in which $\Phi$ is a superposition of (nearly)
degenerate CP-even and CP-odd Higgs bosons in a (possibly supersymmetric)
two-Higgs doublet model also with additional fermions to account for the
$\gamma \gamma$ decay rate. We explore the implications of these benchmark
scenarios for the production of $\Phi$ and its new partners at colliders in
future runs of the LHC and beyond, at higher-energy $pp$ colliders and at $e^+
e^-$ and $\gamma \gamma$ colliders, with emphasis on the bosonic partners
expected in the doublet scenario and the fermionic partners expected in both
scenarios.


  Type Ia supernova (SN Ia) light curves have a secondary maximum that exists
in the $r$, $i$, and near-infrared filters. The secondary maximum is relatively
weak in the $r$ band, but holds the advantage that it is accessible, even at
high redshift. We used Gaussian Process fitting to parameterise the light
curves of 893 SNe Ia from the Zwicky Transient Facility's (ZTF) second data
release (DR2), and we were able to extract information about the timing and
strength of the secondary maximum. We found $>5\sigma$ correlations between the
light curve decline rate ($\Delta m_{15}(g)$) and the timing and strength of
the secondary maximum in the $r$ band. Whilst the timing of the secondary
maximum in the $i$ band also correlates with $\Delta m_{15}(g)$, the strength
of the secondary maximum in the $i$ band shows significant scatter as a
function of $\Delta m_{15}(g)$. We found that the transparency timescales of 97
per cent of our sample are consistent with double detonation models, and that
SNe Ia with small transparency timescales ($<$ 32 d) reside predominantly in
locally red environments. We measured the total ejected mass for the normal SNe
Ia in our sample using two methods, and both were consistent with medians of
$1.3\ \pm \ 0.3$ and $1.2\ \pm\ 0.2$ solar masses. We find that the strength of
the secondary maximum is a better standardisation parameter than the SALT light
curve stretch ($x_1$). Finally, we identified a spectral feature in the $r$
band as Fe II, which strengthens during the onset of the secondary maximum. The
same feature begins to strengthen at $<$ 3 d post maximum light in 91bg-like
SNe. Finally, the correlation between $x_1$ and the strength of the secondary
maximum was best fit with a broken line, with a split at $x_1^0\ =\ -0.5\ \pm\
0.2$, suggestive of the existence of two populations of SNe Ia.


  The properties of maximum Lempel-Ziv complexity strings are studied for the
binary case. A comparison between MLZs and random strings is carried out. The
length profile of both type of sequences show different distribution functions.
The non-stationary character of the MLZs are discussed. The issue of
sensitiveness to noise is also addressed. An empirical ansatz is found that
fits well to the Lempel-Ziv complexity of the MLZs for all lengths up to $10^6$
symbols.


  We have developed a general technique to study the dynamics of the quantum
adiabatic evolution algorithm applied to random combinatorial optimization
problems in the asymptotic limit of large problem size $n$. We use as an
example the NP-complete Number Partitioning problem and map the algorithm
dynamics to that of an auxilary quantum spin glass system with the slowly
varying Hamiltonian. We use a Green function method to obtain the adiabatic
eigenstates and the minimum excitation gap, $g_{\rm min}={\cal O}(n 2^{-n/2})$,
corresponding to the exponential complexity of the algorithm for Number
Partitioning. The key element of the analysis is the conditional energy
distribution computed for the set of all spin configurations generated from a
given (ancestor) configuration by simulteneous fipping of a fixed number of
spins. For the problem in question this distribution is shown to depend on the
ancestor spin configuration only via a certain parameter related to the energy
of the configuration. As the result, the algorithm dynamics can be described in
terms of one-dimenssional quantum diffusion in the energy space. This effect
provides a general limitation on the power of a quantum adiabatic computation
in random optimization problems. Analytical results are in agreement with the
numerical simulation of the algorithm.


  An experimental approach in conducting NMR measurements at supercritical
parameters of state is discussed. A novel design of the high-pressure NMR cell
was developed which allowed eliminating the field inhomogeneity and, thus,
increasing the sensitivity of the experiment at the supercritical state.
Analysis of the MD simulations and NMR data showed that two conformers of
ibuprofen dominate in the solution in supercritical CO2 along the critical
isochore 1.3 \r{ho}cr(CO2). Conformer populations calculated from MD
simulations and from NMR spectra agree with each other


  The tensor-vector-scalar (TeVeS) model is considered a viable theory of
gravity. It produces the Milgrom's modified Newtonian dynamics in the
nonrelativistic weak field limit and is free from ghosts. This model has been
tested against various cosmological observations. Here we investigate whether
new observations such as the galaxy velocity power spectrum measured by 6dF and
the kinetic Sunyaev Zel'dovich effect power spectrum measured by ACT/SPT can
put further constraints on the TeVeS model. Furthermore, we perform the test of
TeVeS cosmology with a sterile neutrino by confronting to Planck data, and find
that it is ruled out by cosmic microwave background measurements from the
Planck mission.


  We calculate production rates for massless $(u,d)$ and massive $(s,c,b)$
quarks in pure glue and quark gluon plasmas to leading order in the strong
coupling constant $g$. The leading contribution comes from gluon decay into
$q\bar q$ pairs, using a thermal gluon propagator with finite thermal mass and
damping rate. The rate behaves as $\alpha_S^2(\ln 1/\alpha_S)^2 T^4$ when $m,
\alpha_S \rightarrow 0$ and depends linearly on the transverse gluon damping
rate for all values of the quark mass $m$. The light quark ($u$, $d$, $s$)
chemical equilibration time is approximately 10-100 $T^{-1}$ for $g=$2-3, so
that quarks are likely to remain far from chemical equilibrium in
ultrarelativistic nuclear collisions.


  Lattice spin models are useful for studying critical phenomena and allow the
extraction of equilibrium and dynamical properties. Simulations of such systems
are usually based on Monte Carlo (MC) techniques, and the main difficulty is
often the large computational effort needed when approaching critical points.
In this work, it is shown how such simulations can be accelerated with the use
of NVIDIA graphics processing units (GPUs) using the CUDA programming
architecture. We have developed two different algorithms for lattice spin
models, the first useful for equilibrium properties near a second-order phase
transition point and the second for dynamical slowing down near a glass
transition. The algorithms are based on parallel MC techniques, and speedups
from 70- to 150-fold over conventional single-threaded computer codes are
obtained using consumer-grade hardware.


  We propose an extension of tree-based space-partitioning indexing structures
for data with low intrinsic dimensionality embedded in a high dimensional
space. We call this extension an Angle Tree. Our extension can be applied to
both classical kd-trees as well as the more recent rp-trees. The key idea of
our approach is to store the angle (the "dihedral angle") between the data
region (which is a low dimensional manifold) and the random hyperplane that
splits the region (the "splitter"). We show that the dihedral angle can be used
to obtain a tight lower bound on the distance between the query point and any
point on the opposite side of the splitter. This in turn can be used to
efficiently prune the search space. We introduce a novel randomized strategy to
efficiently calculate the dihedral angle with a high degree of accuracy.
Experiments and analysis on real and synthetic data sets shows that the Angle
Tree is the most efficient known indexing structure for nearest neighbor
queries in terms of preprocessing and space usage while achieving high accuracy
and fast search time.


  We show that the holonomy of a connection defined on a principal composite
bundle is related by a non-abelian Stokes theorem to the composition of the
holonomies associated with the connections of the component bundles of the
composite. We apply this formalism to describe the non-abelian geometric phase
(when the geometric phase generator does not commute with the dynamical phase
generator). We find then an assumption to obtain a new kind of separation
between the dynamical and the geometric phases. We also apply this formalism to
the gauge theory of gravity in the presence of a Dirac spinor field in order to
decompose the holonomy of the Lorentz connection into holonomies of the linear
connection and of the Cartan connection.


  As part of University College Dublin's MSc in Space Science & Technology
curriculum, student teams, over the course of a single term, design, build,
launch (on a meteorological balloon), operate and recover their own payload on
a standardised platform. Each 'TupperSat' must be built from, or contained
within, a household plastic storage container, It must weigh less than 1kg, be
able to determine location, altitude, internal and external temperature and air
pressure, and be able to broadcast this information using an in-house
communications system. Students must also design and build a scientific payload
or novel technology demonstration to fly on their TupperSat. Notable examples
include an earth observation vegetation sensor, particle sample return,
gamma-ray detector, and air-bag landing system. The instructors play the role
of customer and launch authority. The students are provided with a number of
standard components including a Raspberry Pi single-board computer, a 5000 mAH
battery, high-altitude-compatible GPS unit, temperature and pressure sensors
and, a small low-power radio transceiver module developed specifically for the
course based on the LoRa standard. Teams are given a budget of EUR 100 ($115)
to purchase additional materials and to build their payload. The students learn
space industry practices by full immersion in a typical space project
development cycle. TupperSat design and payload concepts are pitched by the
student teams at a Preliminary Design Review; plans are well developed before a
Critical Design Review, and the team must pass a Flight Readiness Review before
being granted permission to launch. Good project management is crucial in order
to meet deadlines and secure a launch at the end of the term. As student
participation has grown, the module has been modified to allow for more
ambitious and challenging projects which further motivates the students.


  We show that the problem of constructing a real rational knot of a reasonably
low degree can be reduced to an algebraic problem involving the pure braid
group: expressing an associated element of the pure braid group in terms of the
standard generators of the pure braid group. We also predict the existence of a
real rational knot in a degree that is expressed in terms of the edge number of
its polygonal representation.


  This paper addresses an overview of the wireless sensor networks. It is shown
that MEMS/NEMS technologies and SIP concept are well suited for advanced
architectures. It is also shown analog architectures have to be compatible with
digital signal techniques to develop smart network of microsystem.


  Though state-of-the-art (SOTA) NLP systems have achieved remarkable
performance on a variety of language understanding tasks, they primarily focus
on questions that have a correct and a definitive answer. However, in
real-world applications, users often ask questions that don't have a definitive
answer. Incorrectly answering such questions certainly hampers a system's
reliability and trustworthiness. Can SOTA models accurately identify such
questions and provide a reasonable response?
  To investigate the above question, we introduce QnotA, a dataset consisting
of five different categories of questions that don't have definitive answers.
Furthermore, for each QnotA instance, we also provide a corresponding QA
instance i.e. an alternate question that ''can be'' answered. With this data,
we formulate three evaluation tasks that test a system's ability to 'identify',
'distinguish', and 'justify' QnotA questions. Through comprehensive
experiments, we show that even SOTA models including GPT-3 and Flan T5 do not
fare well on these tasks and lack considerably behind the human performance
baseline. We conduct a thorough analysis which further leads to several
interesting findings. Overall, we believe our work and findings will encourage
and facilitate further research in this important area and help develop more
robust models.


  We argue that it would be desirable to use Jeffreys' priors in the
construction of numerical model based probabilistic climate forecasts, in order
that those forecasts could be argued to be objective. Hitherto, this has been
considered computationally unfeasible. We propose an approximation that we
believe makes it feasible, and derive closed-form expressions for various
simple cases.


  In psycholinguistics, the creation of controlled materials is crucial to
ensure that research outcomes are solely attributed to the intended
manipulations and not influenced by extraneous factors. To achieve this,
psycholinguists typically pretest linguistic materials, where a common pretest
is to solicit plausibility judgments from human evaluators on specific
sentences. In this work, we investigate whether Language Models (LMs) can be
used to generate these plausibility judgements. We investigate a wide range of
LMs across multiple linguistic structures and evaluate whether their
plausibility judgements correlate with human judgements. We find that GPT-4
plausibility judgements highly correlate with human judgements across the
structures we examine, whereas other LMs correlate well with humans on commonly
used syntactic structures. We then test whether this correlation implies that
LMs can be used instead of humans for pretesting. We find that when
coarse-grained plausibility judgements are needed, this works well, but when
fine-grained judgements are necessary, even GPT-4 does not provide satisfactory
discriminative power.


  We give the classification of T-duals of the flat background in four
dimensions with respect to one-, two-, and three-dimensional subgroups of the
Poincar\'e group using non-Abelian T-duality with spectators. As duals we find
backgrounds for sigma models in the form of plane-parallel waves or
diagonalizable curved metrics often with torsion. Among others, we find exactly
solvable time-dependent isotropic pp-wave, singular pp-waves, or generalized
plane wave (K-model).


  A method for the detection of changes in the expectation in univariate
sequences is provided. Moving sum processes are studied. These rely on the
selection of a tuning bandwidth. Here, a framework to overcome bandwidth
selection is presented - the bandwidth adjusts gradually. For that, moving sum
processes are made dependent on both time and the bandwidth: the domain becomes
a triangle. On the triangle, paths are constructed which systematically lead to
change points. An algorithm is provided that estimates change points by
subsequent consideration of paths. Strong consistency for the number and
location of change points is shown. Simulations support estimation precision. A
companion R-package mscp is made available on CRAN.


  The plane wave method is most widely used for solving the Kohn-Sham equations
in first-principles materials science computations. In this procedure, the
three-dimensional (3-dim) trial wave functions' fast Fourier transform (FFT) is
a regular operation and one of the most demanding algorithms in terms of the
scalability on a parallel machine. We propose a new partitioning algorithm for
the 3-dim FFT grid to accomplish the trade-off between the communication
overhead and load balancing of the plane waves. It is shown by qualitative
analysis and numerical results that our approach could scale the plane wave
first-principles calculations up to more nodes.


  3D modeling has long been an important area in computer vision and computer
graphics. Recently, thanks to the breakthroughs in neural representations and
generative models, we witnessed a rapid development of 3D modeling. 3D human
modeling, lying at the core of many real-world applications, such as gaming and
animation, has attracted significant attention. Over the past few years, a
large body of work on creating 3D human avatars has been introduced, forming a
new and abundant knowledge base for 3D human modeling. The scale of the
literature makes it difficult for individuals to keep track of all the works.
This survey aims to provide a comprehensive overview of these emerging
techniques for 3D human avatar modeling, from both reconstruction and
generation perspectives. Firstly, we review representative methods for 3D human
reconstruction, including methods based on pixel-aligned implicit function,
neural radiance field, and 3D Gaussian Splatting, etc. We then summarize
representative methods for 3D human generation, especially those using large
language models like CLIP, diffusion models, and various 3D representations,
which demonstrate state-of-the-art performance. Finally, we discuss our
reflection on existing methods and open challenges for 3D human avatar
modeling, shedding light on future research.


  We consider the role of the Ward identity in dealing with the transport
properties of an interacting system forming a d-wave modulated charge-density
wave or staggered flux phase. In particular, we address this issue from the
point of view of the restricted optical-conductivity sum rule. Our aim is to
provide a controlled approximation for the current-current correlation function
which allows us also to determine analytically the corresponding sum rule. By
analyzing the role of the vertex functions in both the microscopic interacting
model and in the effective mean-field Hamiltonian, we propose a non-standard
low-energy sum-rule for this system. We also discuss the possible applicability
of these results for the description of cuprate superconductors in the
pseudogap regime.


  There have been extensive studies of a random walk among a field of immobile
traps (or obstacles), where one is interested in the probability of survival as
well as the law of the random walk conditioned on its survival up to time $t$.
In contrast, very little is known when the traps are mobile. We will briefly
review the literature on the trapping problem with immobile traps, and then
review some recent results on a model with mobile traps, where the traps are
represented by a Poisson system of independent random walks on ${\mathbb Z}^d$.
Some open questions will be given at the end.


  Helioseismology puts strong constraints on the internal sound speed and on
the rotation profile in the radiative zone. Young stars of solar type are more
active and faster rotators than the Sun. So we begin to build models which
include different rotation histories and compare the results with all the solar
observations. The profiles of the rotation we get have interesting consequence
for the introduction of magnetic field in the radiative zone. We discuss also
the impact of mass loss deduced from measured flux of young stars. We deduce
from these comparisons some quantitative effect of the dynamical processes
(rotation, magnetic field and mass loss) of these early stages on the present
sound speed and density. We show finally how we can improve our present
knowledge of the radiative zone with PICARD and GOLFNG.


  In the present work, we are interested in the properties of nuclear matter at
zero temperature in the presence of strong magnetic fields using the lowest
order constraint variational (LOCV) method employing $AV_{18}$ nuclear
potential. Our results indicate that in the absence of a magnetic field, the
energy per particle is a symmetric function of the spin polarization parameter.
This shows that for the nuclear matter, the spontaneous phase transition to a
ferromagnetic state does not occur. However, we have found that for the
magnetic fields $ B\gtrsim 10 ^ {18}\ G$, the symmetry of energy is broken and
the energy has a minimum at a positive value of the spin polarization
parameter. We have also found that the effect of magnetic field on the value of
energy is more significant at the low densities. Our calculations show that at
lower densities, the spin polarization parameter is more sensitive to the
magnetic field.


  In this paper, we propose a deep learning approach to tackle the automatic
summarization tasks by incorporating topic information into the convolutional
sequence-to-sequence (ConvS2S) model and using self-critical sequence training
(SCST) for optimization. Through jointly attending to topics and word-level
alignment, our approach can improve coherence, diversity, and informativeness
of generated summaries via a biased probability generation mechanism. On the
other hand, reinforcement training, like SCST, directly optimizes the proposed
model with respect to the non-differentiable metric ROUGE, which also avoids
the exposure bias during inference. We carry out the experimental evaluation
with state-of-the-art methods over the Gigaword, DUC-2004, and LCSTS datasets.
The empirical results demonstrate the superiority of our proposed method in the
abstractive summarization.


  We demonstrate time resolved driving of two-photon blue sideband transitions
between superconducting qubits and a transmission line resonator. Using the
sidebands, we implement a pulse sequence that first entangles one qubit with
the resonator, and subsequently distributes the entanglement between two
qubits. We show generation of 75% fidelity Bell states by this method. The full
density matrix of the two qubit system is extracted using joint measurement and
quantum state tomography, and shows close agreement with numerical simulation.
The scheme is potentially extendable to a scalable universal gate for quantum
computation.


  Single crystal X-ray diffraction measurements were performed on
one-dimensional mixed valence vanadium bronze $\beta$-SrV$_6$O$_{15}$ in which
a metal-insulator transition exists at 170 K. Above 170 K the P2$_1$/a
structure with zigzag order of Sr in the tunnels of vanadium is confirmed. In
the structure below 170 K, the P2$_1$/a space group is retained with a b-axis
threefold increase and a charge order appears. A Bond Valence Sum analysis
shows that the charge order may consist in clusters of V$^{4+}$ regularly
spaced along 1D direction.


  The discovery of the peculiar supernova (SN) 1998bw and its possible
association with the gamma-ray burst (GRB) 980425$^{1,2,3}$ provide new clues
to the understanding of the explosion mechanism of very massive stars and to
the origin of some classes of gamma-ray bursts. Its spectra indicate that
SN~1998bw is a type Ic supernova$^{3,4}$, but its peak luminosity is unusually
high compared with typical type Ic supernovae$^3$. Here we report our findings
that the optical spectra and the light curve of SN 1998bw can be well
reproduced by an extremely energetic explosion of a massive carbon+oxygen (C+O)
star. The kinetic energy is as large as $\sim 2-5 \times 10^{52}$ ergs, more
than ten times the previously known energy of supernovae. For this reason, the
explosion may be called a `hypernova'. Such a C+O star is the stripped core of
a very massive star that has lost its H and He envelopes. The extremely large
energy, suggesting the existence of a new mechanism of massive star explosion,
can cause a relativistic shock that may be linked to the gamma-ray burst.


  We consider a high dimensional binary classification problem and construct a
classification procedure by minimizing the empirical misclassification risk
with a penalty on the number of selected features. We derive non-asymptotic
probability bounds on the estimated sparsity as well as on the excess
misclassification risk. In particular, we show that our method yields a sparse
solution whose l0-norm can be arbitrarily close to true sparsity with high
probability and obtain the rates of convergence for the excess
misclassification risk. The proposed procedure is implemented via the method of
mixed integer linear programming. Its numerical performance is illustrated in
Monte Carlo experiments.


  The chemical bonding in an epitaxial ZrB2 film is investigated by Zr K-edge
(1s) X-ray absorption near-edge structure (XANES) and extended X-ray absorption
fine structure (EXAFS) spectroscopies and compared to the ZrB2 compound target
from which the film was synthesized as well as a bulk {\alpha}-Zr reference.
Quantitative analysis of X-ray Photoelectron Spectroscopy spectra reveals at
the surface: ~5% O in the epitaxial ZrB2 film, ~19% O in the ZrB2 compound
target and ~22% O in the bulk {\alpha}-Zr reference after completed sputter
cleaning. For the ZrB2 compound target, X-ray diffraction (XRD) shows weak but
visible -111, 111, and 220 peaks from monoclinic ZrO2 together with peaks from
ZrB2 and where the intensity distribution for the ZrB2 peaks show a randomly
oriented target material. For the bulk {\alpha}-Zr reference no peaks from any
crystalline oxide were visible in the diffractogram recorded from the
0001-oriented metal. The Zr K-edge absorption from the two ZrB2 samples
demonstrate more pronounced oscillations for the epitaxial ZrB2 film than in
the bulk ZrB2 attributed to the high atomic ordering within the columns of the
film. The XANES exhibits no pre-peak due to lack of p-d hybridization in ZrB2,
but with a chemical shift towards higher energy of 4 eV in the film and 6 eV
for the bulk compared to {\alpha}-Zr (17.993 keV) from the charge-transfer from
Zr to B. The 2 eV larger shift in bulk ZrB2 material suggests higher oxygen
content than in the epitaxial film, which is supported by XPS. In EXAFS, the
modelled cell-edge in ZrB2 is slightly smaller in the thin film (a=3.165 {\AA},
c=3.520 {\AA}) in comparison to the bulk target material (a=3.175 {\AA},
c=3.540 {\AA}) while in hexagonal closest-packed metal ({\alpha}-phase, a=3.254
{\AA}, c=5.147 {\AA}).


  This is the second paper in a series where we propose a method of indirectly
measuring large scale structure using information from small scale
perturbations. The idea is to build a quadratic estimator from small scale
modes that provides a map of structure on large scales. We demonstrated in the
first paper that the quadratic estimator works well on a dark-matter-only
N-body simulation at a snapshot of $z=0$. Here we generalize the theory to the
case of a light cone halo catalog with a non-cubic region taken into
consideration. We successfully apply the generalized version of the quadratic
estimator to the light cone halo catalog based on an N-body simulation of
volume $\sim15.03\,(h^{-1}\,\rm Gpc)^3$. The most distant point in the light
cone is at a redshift of $1.42$, indicating the applicability of our method to
next generation of galaxy surveys.


  The symmetry of the superconductivity in Bechgaard salts is still unknown,
though the triplet pairing has been established by Hc2 and NMR for (TMTSF)2PF6.
The large upper critical field at T = 0K (Hc2 ~ 5 Tesla) both for H || a and H
|| b also indicates strongly the triplet pairing.
  Here we start with a low energy effective Hamiltonian and study the
temperature dependence of the corresponding Hc2(T)'s.
  The present analysis suggests that one chiral f-wave superconductor should be
the most likely candidate near the upper critical field.


  In the following paper, we generalize the geometrical framework of qubit
decoherence to higher dimensions. The quantum mixed state is represented by the
probability distribution, which is the K\"ahler function on the projective
Hilbert space. The Markovian master equation for density operators turns out to
be equivalent to the Fokker-Planck equation for quantum probability
distributions. Several examples are analyzed, featuring different
generalizations of the Pauli channel.


  Examining the relationship between vulnerability of the built environment and
community recovery is crucial for understanding disaster resilience. Yet, this
relationship is rather neglected in the existing literature due to previous
limitations in the availability of empirical datasets needed for such analysis.
In this study, we combine fine-resolution flood damage claims data (composed of
both insured and uninsured losses) and human mobility data (composed of
millions of movement trajectories) during the 2017 Hurricane Harvey in Harris
County, Texas, to specify the extent to which vulnerability of the built
environment (i.e., flood property damage) affects community recovery (based on
the speed of human mobility recovery) locally and regionally. We examine this
relationship using a spatial lag, spatial reach, and spatial decay models to
measure the extent of spillover effects of residential damage on community
recovery. The findings show that: first, the severity of residential damage
significantly affects the speed of community recovery. A greater extent of
residential damage suppresses community recovery not only locally but also in
the surrounding areas. Second, the spatial spillover effect of residential
damage on community recovery speed decays with distance from the highly damaged
areas. Third, spatial areas display heterogeneous spatial decay coefficients,
which are associated with urban structure features such as the density of
points-of-interest facilities and roads. These findings provide a novel
data-driven characterization of the spatial diffusion of residential flood
damage effects on community recovery and move us closer to a better
understanding of complex spatial processes that shape community resilience to
hazards. This study also provides valuable insights for emergency managers and
public officials seeking to mitigate the non-local effects of residential
damage.


  Near-concentric cavities are excellent tools for enhancing atom--light
interaction as they combine a small mode volume with a large optical access for
atom manipulation. However, they are sensitive to longitudinal and transverse
misalignment. To address this sensitivity, we present a compact near-concentric
optical cavity system with a residual cavity length variation $\delta L_{C,
rms}$=36(9) pm. A key part of this system is a cage-like tensegrity mirror
support structure that allows to correct for longitudinal and transverse
misalignment. The system is stable enough to allow the use of mirrors with
higher cavity finesse to enhance the atom--light coupling strength in
cavity-QED applications.


  We have succeeded in synthesizing of single crystals of a new intermetallic
compound, Ce$_{3}$Rh$_{4}$Pb$_{13}$. Magnetic susceptibility measurements
indicate that the Ce moments are highly localized, despite the metallic
character of the electrical resistivity. Heat capacity measurements reveal that
the cubic crystal electric field lifts the six-fold degeneracy of the Ce$^{3+}$
ground state, with the quartet state separated by approximately 60 K from the
doublet ground state. The magnetic field dependence of the heat capacity at low
temperature indicates a further splitting of the doublet, but no sign of
magnetic order was found above 0.35 K.


  A measurement of the direct CP violating charge asymmetries of the Dalitz
plot linear slopes $A_g=(g^+-g^-)/(g^++g^-)$ in $K^\pm\to\pi^\pm\pi^+\pi^-$ and
$K^\pm\to\pi^\pm\pi^0\pi^0$ decays by the NA48/2 experiment at CERN SPS is
presented. A new technique of asymmetry measurement involving simultaneous
$K^+$ and $K^-$ beams and a large data sample collected allowed a result of an
unprecedented precision. The charge asymmetries were measured to be
$A^c_g=(-1.5\pm2.2)\times10^{-4}$ with $3.11\times 10^9$
$K^{\pm}\to\pi^\pm\pi^+\pi^-$ decays, and $A^n_g=(1.8\pm1.8)\times10^{-4}$ with
$9.13\times 10^7$ $K^{\pm}\to\pi^\pm\pi^0\pi^0$ decays. The precision of the
results is limited mainly by the size of the data sample.


  We investigate non-stationary orthogonal wavelets based on a non-stationary
interpolatory subdivision scheme reproducing a given set of exponentials. The
construction is analogous to the construction of Daubechies wavelets using the
subdivision scheme of Deslauriers-Dubuc. The main result is the smoothness of
these Daubechies type wavelets.


  Improving the reliability and spectral efficiency of wireless systems is a
key goal in wireless systems. However, most efforts have been devoted to
improving data channel capacity, whereas control-plane capacity bottlenecks are
often neglected. In this paper, we propose a means of improving the
control-plane capacity and reliability by shrinking the bit size of a key
signaling message - the 5G Downlink Control Information (DCI). In particular, a
transformer model is studied as a probability distribution estimator for
Arithmetic coding to achieve lossless compression. Feature engineering, neural
model design, and training technique are comprehensively discussed in this
paper. Both temporal and spatial correlations among DCI messages are explored
by the transformer model to achieve reasonable lossless compression
performance. Numerical results show that the proposed method achieves 21.7%
higher compression ratio than Huffman coding in DCI compression for a
single-cell scheduling scenario.


  Locating each node in a wireless sensor network is essential for starting the
monitoring job and sending information about the area. One method that has been
used in hard and inaccessible environments is randomly scattering each node in
the area. In order to reduce the cost of using GPS at each node, some nodes
should be equipped with GPS (anchors), Then using the belief propagation
algorithm, locate other nodes. The number of anchor nodes must be reduced since
they are expensive. Furthermore, the location of these nodes affects the
algorithm's performance. Using multi-objective optimization, an algorithm is
introduced in this paper that minimizes the estimated location error and the
number of anchor nodes. According to simulation results, This algorithm
proposes a set of solutions with less energy consumption and less error than
similar algorithms.


  We establish a noncommutative Blackwell--Ross inequality for supermartingales
under a suitable condition which generalize Khan's works to the noncommutative
setting. We then employ it to deduce an Azuma-type inequality.


  We consider the practical and classical setting where the seller is using an
exploration stage to learn the value distributions of the bidders before
running a revenue-maximizing auction in a exploitation phase. In this two-stage
process, we exhibit practical, simple and robust strategies with large utility
uplifts for the bidders. We quantify precisely the seller revenue against
non-discounted buyers, complementing recent studies that had focused on
impatient/heavily discounted buyers. We also prove the robustness of these
shading strategies to sample approximation error of the seller, to bidder's
approximation error of the competition and to possible change of the
mechanisms.


  We consider extremal correlation functions, involving arbitrary number of BPS
(chiral or twisted chiral) operators and exactly one anti-BPS operator in 2D
N=(2,2) theories. These correlators define the structure constants in the rings
generated by the BPS operators with their operator product expansions. We
present a way of computing these correlators from the sphere partition function
of a deformed theory using localization. Relating flat space and sphere
correlators is nontrivial due to operator mixing on the sphere induced by
conformal anomaly. We discuss the supergravitational source of this
complication and a resolution thereof. Finally, we demonstrate the process for
the Quintic GLSM and the Landau-Ginzburg minimal models.


  Recent research has shown the potential of Model-based Reinforcement Learning
(MBRL) to enhance energy efficiency of Heating, Ventilation, and Air
Conditioning (HVAC) systems. However, existing methods rely on black-box
thermal dynamics models and stochastic optimizers, lacking reliability
guarantees and posing risks to occupant health. In this work, we overcome the
reliability bottleneck by redesigning HVAC controllers using decision trees
extracted from existing thermal dynamics models and historical data. Our
decision tree-based policies are deterministic, verifiable, interpretable, and
more energy-efficient than current MBRL methods. First, we introduce a novel
verification criterion for RL agents in HVAC control based on domain knowledge.
Second, we develop a policy extraction procedure that produces a verifiable
decision tree policy. We found that the high dimensionality of the thermal
dynamics model input hinders the efficiency of policy extraction. To tackle the
dimensionality challenge, we leverage importance sampling conditioned on
historical data distributions, significantly improving policy extraction
efficiency. Lastly, we present an offline verification algorithm that
guarantees the reliability of a control policy. Extensive experiments show that
our method saves 68.4% more energy and increases human comfort gain by 14.8%
compared to the state-of-the-art method, in addition to an 1127x reduction in
computation overhead. Our code and data are available at
https://github.com/ryeii/Veri_HVAC


  We study the stability of cosmological scaling solutions within the class of
spatially homogeneous cosmological models with a perfect fluid subject to the
equation of state p_gamma=(gamma-1) rho_gamma (where gamma is a constant
satisfying 0 < gamma < 2) and a scalar field with an exponential potential. The
scaling solutions, which are spatially flat isotropic models in which the
scalar field energy density tracks that of the perfect fluid, are of physical
interest. For example, in these models a significant fraction of the current
energy density of the Universe may be contained in the scalar field whose
dynamical effects mimic cold dark matter. It is known that the scaling
solutions are late-time attractors (i.e., stable) in the subclass of flat
isotropic models. We find that the scaling solutions are stable (to shear and
curvature perturbations) in generic anisotropic Bianchi models when gamma <
2/3. However, when gamma > 2/3, and particularly for realistic matter with
gamma >= 1, the scaling solutions are unstable; essentially they are unstable
to curvature perturbations, although they are stable to shear perturbations. We
briefly discuss the physical consequences of these results.


  This paper is devoted to the Moser-Trudinger inequality on smooth
riemanniansurfaces. We establish that the constants involved can be chosen to
depend on only 3parameters, which are the systole, isoperimetric constant and
curvature of the surface. Wehave two analogous statements, considering
respectively infinite-volume surfaces and closedsurfaces. As an application, we
show that there are sequences of coverings of a hyperbolicclosed surface which
admit a uniform Moser-Trudinger inequality.


  This paper describes a system developed to help University students get more
from their online lectures, tutorials, laboratory and other live sessions. We
do this by logging their attention levels on their laptops during live Zoom
sessions and providing them with personalised video summaries of those live
sessions. Using facial attention analysis software we create personalised video
summaries composed of just the parts where a student's attention was below some
threshold. We can also factor in other criteria into video summary generation
such as parts where the student was not paying attention while others in the
class were, and parts of the video that other students have replayed
extensively which a given student has not. Attention and usage based video
summaries of live classes are a form of personalised content, they are
educational video segments recommended to highlight important parts of live
sessions, useful in both topic understanding and in exam preparation. The
system also allows a Professor to review the aggregated attention levels of
those in a class who attended a live session and logged their attention levels.
This allows her to see which parts of the live activity students were paying
most, and least, attention to. The Help-Me-Watch system is deployed and in use
at our University in a way that protects student's personal data, operating in
a GDPR-compliant way.


  With the eminent confirmation or disproof of the existence of Higgs boson by
experiments on the LHC it is time to analyze in a non-dogmatic way the
suggestions to understand the origin of the mass. Here we analyze the recent
proposal according to which gravity is what is really responsible for the
generation of mass of all bodies. The great novelty of such mechanism is that
the gravitational field acts merely as a catalyst, once the final expression of
the mass does not depend either on the intensity or on the particular
characteristics of the gravitational field.


  We prove that the Maxwell-Schr\"odinger system in $\R^{3+1}$ is globally
well-posed in the energy space. The key element of the proof is to obtain a
short time wave packet parametrix for the magnetic Schr\"odinger equation,
which leads to linear, bilinear and trilinear estimates. These, in turn, are
extended to larger time scales via a bootstrap argument.


  We present full QCD and SUSY-QCD corrections to neutralino pair annihilation
into quark-antiquark pairs. We show results and numerically evaluate their
impact on the neutralino annihilation cross section and the relic density in
scenarios with non-universal gaugino masses. By comparing to the relic density
obtained from a pure leading order calculation, we demonstrate that the
corrections strongly influence the extraction of SUSY mass parameters from
cosmological data.


  We consider the question of when it is possible to force a degenerate scalar
oscillatory integral to decay as fast as a nondegenerate one by restricting the
support to the region where the Hessian determinant of the phase is bounded
below. We show in two dimensions that the desired outcome is not always
possible, but does occur for a broad class of phases which may be described in
terms of the Newton polygon. The estimates obtained are uniform with respect to
linear perturbation of the phase and uniform in the cutoff value of the Hessian
determinant. In the course of the proof, we investigate a
geometrically-invariant approach to making uniform estimates of qualitatively
nondegenerate oscillatory integrals. The approach illuminates a previously
unknown, fundamental relationship between the asymptotics of oscillatory
integrals and the Schr\"odinger equation.


  We investigate theoretically the many-body pairing of a strongly correlated
two-dimensional Fermi gas with and without negative confinement-induced
effective range. Using a strong-coupling effective field theory in the normal
state, we show that the specific heat at constant volume can be used as a
characteristic indicator of the crossover from the normal Fermi liquid to the
pseudogap state in two dimensions. We calculate the pseudogap formation
temperature through the specific heat at constant volume, examining the role of
a negative confinement-induced effective range on many-body pairing above the
superfluid transition. We compare our results with and without effective range
to the recent experimental measurement performed with radio-frequency
spectroscopy in Murthy et al.[Science359, 452-455 (2018)]. Although a good
qualitative agreement is found, we are not able to discriminate the effect of
the confinement-induced effect range in the experimental data.


  We show that a strong form (the fully faithful version) of the generating
hypothesis, introduced by Freyd in algebraic topology, holds in the derived
category of a ring R if and only if R is von Neumann regular. This extends
results of the second author. We also characterize rings for which the original
form (the faithful version) of the generating hypothesis holds in the derived
category of R. These must be close to von Neumann regular in a precise sense,
and, given any of a number of finiteness hypotheses, must be von Neumann
regular. However, we construct an example of such a ring that is not von
Neumann regular, and therefore does not satisfy the strong form of the
generating hypothesis.


  In his book on model categories, Hovey asked whether the 2-category
$\mathbf{Mod}$ of model categories admits a "model 2-category structure" whose
weak equivalences are the Quillen equivalences. We show that $\mathbf{Mod}$
does not have pullbacks and so cannot form a model 2-category. This lack of
pullbacks can be traced to the two-out-of-three axiom on the weak equivalences
of a model category. Accordingly, we define a premodel category to be a
complete and cocomplete category equipped with two nested weak factorization
systems. Combinatorial premodel categories form a complete and cocomplete
closed symmetric monoidal 2-category $\mathbf{CPM}$ whose tensor product
represents Quillen bifunctors. For a monoidal combinatorial premodel category
$V$, the 2-category $V\mathbf{CPM}$ of $V$-enriched combinatorial premodel
categories is simply the category of modules over $V$ (viewed as a monoid
object of $\mathbf{CPM}$), and therefore inherits the algebraic structure of
$\mathbf{CPM}$.
  The homotopy theory of a model category depends in an essential way on the
weak equivalences, so it does not extend directly to a general premodel
category. We develop a substitute homotopy theory for premodel categories
satisfying an additional property which holds automatically for model
categories and also for premodel categories enriched in a monoidal model
category. In particular, for a monoidal model category $V$, we obtain a notion
of Quillen equivalence of $V$-premodel categories which extends the one for
$V$-model categories. When $V$ is a tractable symmetric monoidal model
category, we construct a model 2-category structure on $V\mathbf{CPM}$ with
these Quillen equivalences as the weak equivalences, by adapting Szumi\l{}o's
construction of a fibration category of cofibration categories.


  Parity-odd asymmetries in the decay angular distribution of a W boson
produced with a hard jet in p\bar{p} collisions arise only from QCD
rescattering effects. If observed, these asymmetries will provide a first
demonstration that perturbative QCD calculation is valid for the absorptive
part of scattering amplitudes. We propose a simple observable to measure these
asymmetries and perform realistic Monte Carlo simulations at Tevatron energies.
It is shown that the Tevatron Run-II should provide sufficient statistics to
test the prediction.


  Catanese surfaces are regular surfaces of general type with $p_g=0$. They
specialize to double covers of Barlow surfaces. We prove that the $CH_0$ group
of a Catanese surface is equal to $\mathbb{Z}$, which implies the same result
for the Barlow surfaces. We will also give a conditional application (more
precisely, assuming the variational Hodge conjecture) of the same method to the
Chow motive of low degree $K3$ surfaces.


  Federated learning (FL) is able to manage edge devices to cooperatively train
a model while maintaining the training data local and private. One common
assumption in FL is that all edge devices share the same machine learning model
in training, for example, identical neural network architecture. However, the
computation and store capability of different devices may not be the same.
Moreover, reducing communication overheads can improve the training efficiency
though it is still a challenging problem in FL. In this paper, we propose a
novel FL method, called FedHe, inspired by knowledge distillation, which can
train heterogeneous models and support asynchronous training processes with
significantly reduced communication overheads. Our analysis and experimental
results demonstrate that the performance of our proposed method is better than
the state-of-the-art algorithms in terms of communication overheads and model
accuracy.


  Vertical (-201) and (010) beta-Ga2O3 Schottky barrier diodes (SBDs) were
fabricated on single-crystal substrates grown by edge-defined film-fed growth
(EFG) method. High resolution X-ray diffraction (HRXRD) and atomic force
microscopy (AFM) confirmed good crystal quality and surface morphology of the
substrates. The electrical properties of both devices, including
current-voltage (I-V) and capacitance-voltage (C-V) characteristics, were
comprehensively measured and compared. The (-201) and (010) SBDs exhibited
on-resistances (Ron) of 0.56 and 0.77 m{\Omega}cm2, turn-on voltages (Von) of
1.0 and 1.3 V, Schottky barrier heights (SBH) of 1.05 and 1.20 eV, electron
mobilities of 125 and 65 cm2/(Vs), respectively, with a high on-current of ~1.3
kA/cm2 and on/off ratio of ~109. The (010) SBD had a larger Von and SBH than
(-201) SBD due to anisotropic surface properties (i.e., surface Fermi level
pinning and band bending), as supported by X-ray photoelectron spectroscopy
(XPS) measurements. Temperature-dependent I-V also revealed the inhomogeneous
nature of the SBH in both devices, where (-201) SBD showed a more uniform SBH
distribution. The homogeneous SBH was also extracted: 1.33 eV for (-201) SBD
and 1.53 eV for (010) SBD. The reverse leakage current of the devices was well
described by the two-step trap-assisted tunneling model and the one-dimensional
variable range hopping conduction (1D-VRH) model. The (-201) SBD showed larger
leakage current due to its lower SBH and smaller activation energy. These
results indicate the crystalline anisotropy of beta-Ga2O3 can affect the
electrical properties of vertical SBDs and should be taken into consideration
when designing beta-Ga2O3 electronics.


  We consider the nonlinear heat equation with a nonlinear gradient term:
$\partial_t u =\Delta u+\mu|\nabla u|^q+|u|^{p-1}u,\; \mu>0,\; q=2p/(p+1),\;
p>3,\; t\in (0,T),\; x\in \R^N.$ We construct a solution which blows up in
finite time $T>0.$ We also give a sharp description of its blow-up profile and
show that it is stable with respect to perturbations in initial data. The proof
relies on the reduction of the problem to a finite dimensional one, and uses
the index theory to conclude. The blow-up profile does not scale as
$(T-t)^{1/2}|\log(T-t)|^{1/2},$ like in the standard nonlinear heat equation,
i.e. $\mu=0,$ but as $(T-t)^{1/2}|\log(T-t)|^{\beta}$ with
$\beta=(p+1)/[2(p-1)]>1/2.$ We also show that $u$ and $\nabla u$ blow up
simultaneously and at a single point, and give the final profile. In
particular, the final profile is more singular than the case of the standard
nonlinear heat equation.


  It has been shown that temperature cycles on airless bodies of our Solar
System can cause damaging of surface materials. Nevertheless, propagation
mechanisms in the case of space objects are still poorly understood. Present
work combines a thermoelasticity model together with linear elastic fracture
mechanics theory to predict fracture propagation in the presence of thermal
gradients generated by diurnal temperature cycling and under conditions similar
to those existing on the asteroid Bennu. The crack direction is computed using
the maximal strain energy release rate criterion, which is implemented using
finite elements and the so-called G$\theta$ method (Uribe-Su\'arez et al. 2020.
Eng. Fracture Mech. 227:106918). Using the implemented methodology, crack
propagation direction for an initial crack tip in different positions and for
different orientations is computed. It is found that cracks preferentially
propagate in the North to South (N-S), in the North-East to South-West (NE-SW)
and in the North-West to South-East (NW-SE) directions. Finally, thermal
fatigue analysis was performed in order to estimate the crack growth rate.
Computed value is in good agreement with available experimental evidence.


  The photon model of light has been known for decades to be self-inconsistent
and controversial theory with numerous intrinsic conflicts. This paper revises
the model and explores its applicability for description of classical
electromagnetic fields. The revision discloses that the photon model fails for
fields in current-containing domains, as well as for near fields in
current-free regions. This drastically changes the hierarchy of optics theories
and the entire landscape of physics. In particular, quantum optics appears to
be not the most advanced theory, as it is commonly thought, but just an
improved version of geometrical optics with limited applicability, while
quantum electrodynamics turns out to provide a truncated description of
electromagnetic interactions.


  This research work introduces the structure of invariant and screen
semi-invariant lightlike submanifolds of a metallic semi-Riemannian manifold
with a quarter symmetric non-metric connection, elaborated with examples. It
delves into the characterization of integrability and parallelism of
distributions inherent in the structure of these submanifolds. Additionally, it
presents findings pertaining to totally geodesic foliations for invariant and
screen semi-invariant submanifolds.


  Thermodynamics of the near extremal black p-branes can be described by
collective motions of gravitationally interacting branes. This proposal is
called the p-soup model. In this paper, we check this proposal in the case of
black brane system which is asymptotically Friedmann-Lemaitre-Robertson-Walker
universe in an infinite distance. As a result, we can show that the
gravitationally interacting branes explain free energy, entropy, temperature
and other physical quantities in these systems. This implies that the
microstates of this kind of brane system can be also understood in the p-soup
model.


  Gauging of effective chiral quark models with non-local regulators is
discussed in the context of solitons. In particular, we show that with the
P-exponent method the current algebra is satisfied and the charges are properly
quantized.


  We observe a strong correlation between magnetization relaxation and
electrical resistivity in thin Permalloy (Ni$_{81}$Fe$_{19}$, ``Py'') films.
Electron scattering rates in the films were affected by varying film thickness
and deposition conditions. This shows that the magnetization relaxation
mechanism is analogous to ``bulk'' relaxation, where phonon scattering in bulk
is replaced by surface and defect scattering in thin films. Another interesting
finding is the increased magnetization damping with Pt layers adjacent to the
Py films. This is attributed to the strong spin-orbit coupling in Pt, resulting
in spin-flip scattering of electrons that enter from the Py.


  In this article we obtain $L^2$ bounds for strongly singular integrals along
curves in $\R^d;$ our results both generalise and extend to higher dimensions
those obtained by Chandarana in the plane. Moreover, we show that the operators
in question are bounded from $L\log L$ to weak $L^1$ at the critical exponent
$\alpha=0.$


  Aims: From observations of the K4III star Beta UMi we attempt to determine
whether oscillations or any other form of variability is present.
  Methods: A high-quality photometric time series of approximately 1000 days in
length obtained from the SMEI instrument on the Coriolis satellite is analysed.
Various statistical tests were performed to determine the significance of
features seen in the power density spectrum of the light curve.
  Results: Two oscillations with frequencies 2.44 and 2.92 microhertz have been
identified. We interpret these oscillations as consecutive overtones of an
acoustic spectrum, implying a large frequency spacing of 0.48 microhertz. Using
derived asteroseismic parameters in combination with known astrophysical
parameters, we estimate the mass of Beta UMi to be 1.3 +/- 0.3 solar masses.
Peaks of the oscillations in the power density spectrum show width, implying
that modes are stochastically excited and damped by convection. The mode
lifetime is estimated at 18 +/- 9 days.


  This document contains additional experiments concerned with the evaluation
of the Hierarchical Subspace Iteration Method, which is introduced
in~\cite{Nasikun2021}}


  Motivated by recent experimental results, we study beating dark-dark solitons
as a prototypical coherent structure that emerges in two-component
Bose-Einstein condensates. We showcase their connection to dark- bright
solitons via SO(2) rotation, and infer from it both their intrinsic beating
frequency and their frequency of oscillation inside a parabolic trap. We
identify them as exact periodic orbits in the Manakov limit of equal inter- and
intra-species nonlinearity strengths with and without the trap and showcase the
persistence of such states upon weak deviations from this limit. We also
consider large deviations from the Manakov limit illustrating that this
breathing state may be broken apart into dark-antidark soliton states. Finally,
we consider the dynamics and interactions of two beating dark-dark solitons in
the absence and in the presence of the trap, inferring their typically
repulsive interaction.


  We present the Fortran code SDECAY, which calculates the decay widths and
branching ratios of all the supersymmetric particles in the Minimal
Supersymmetric Standard Model, including higher order effects. Besides the
usual two-body decays of fermions and gauginos and the three-body decays of
charginos, neutralinos and gluinos, we have also implemented the three-body
decays of top squarks, and even the four-body decays of the top squark; the
important loop-induced decay modes are also included. The QCD corrections to
the two-body decays involving strongly interacting particles and the dominant
components of the electroweak corrections to all decay modes are implemented.


  We calculate the two-boson-exchange (TBE) corrections to the parity-violating
asymmetry of the elastic electron-proton scattering in a simple hadronic model
including the nucleon and the $\Delta(1232)$ intermediate states. We find that
$\Delta$ contribution $\delta_\Delta$ is, in general, comparable with the
nucleon contribution $\delta_N$ and the current experimental measurements of
strange-quark effects in the proton neutral weak current. The total TBE
corrections to the current extracted values of
  $G^{s}_{E}+\beta G^{s}_{M}$ in recent experiments are found to lie in the
range of $-7\sim +7%$.


  The article is dedicated to the memory of George Voronoi. It is concerned
with ($p$-adic) $L$-functions (in partially ($p$-adic) zeta functions) and
cyclotomic ($p$-adic) (multiple) zeta values. The beginning of the article
contains a short summary of the results on the Bernoulli numbers associated
with the studies of George Voronoi.
  Results on multiple zeta values have presented by D. Zagier, by P. Deligne
and A.Goncharov, by A. Goncharov, by F. Brown, by C. Glanois and others. S.
\"Unver have investigated p-adic multiple zeta values in the depth two.
Tannakian interpretation of p-adic multiple zeta values is given by H. Furusho.
Short history and connections among Galois groups, fundamental groups, motives
and arithmetic functions are presented in the talk by Y. Ihara. Results on
multiple zeta values, Galois groups and geometry of modular varieties has
presented by Goncharov. Interesting unipotent motivic fundamental group is
defined and investigated by Deligne and Goncharov. The framework of ($p$-adic)
$L$-functions and ($p$-adic) (multiple) zeta values is based on Kubota-Leopoldt
$p$-adic $L$-functions and arithmetic $p$-adic $L$-functions by Iwasawa.
Motives and ($p$-adic) (multiple) zeta values by Glanois and by \"Unver,
improper intersections of Kudla-Rapoport divisors and Eisenstein series by
Sankaran are reviewed. More fully the content of the article can be found at
the following table of contents (plan). Numerical examples are included.


  Convex (specifically semidefinite) relaxation provides a powerful approach to
constructing robust machine perception systems, enabling the recovery of
certifiably globally optimal solutions of challenging estimation problems in
many practical settings. However, solving the large-scale semidefinite
relaxations underpinning this approach remains a formidable computational
challenge. A dominant cost in many state-of-the-art (Burer-Monteiro
factorization-based) certifiable estimation methods is solution verification
(testing the global optimality of a given candidate solution), which entails
computing a minimum eigenpair of a certain symmetric certificate matrix. In
this letter, we show how to significantly accelerate this verification step,
and thereby the overall speed of certifiable estimation methods. First, we show
that the certificate matrices arising in the Burer-Monteiro approach
generically possess spectra that make the verification problem expensive to
solve using standard iterative eigenvalue methods. We then show how to address
this challenge using preconditioned eigensolvers; specifically, we design a
specialized solution verification algorithm based upon the locally optimal
block preconditioned conjugate gradient (LOBPCG) method together with a simple
yet highly effective algebraic preconditioner. Experimental evaluation on a
variety of simulated and real-world examples shows that our proposed
verification scheme is very effective in practice, accelerating solution
verification by up to 280x, and the overall Burer-Monteiro method by up to 16x,
versus the standard Lanczos method when applied to relaxations derived from
large-scale SLAM benchmarks.


  At present, only some special differential equations have explicit analytical
solutions. In general, no one thinks that it is possible to analytically find
the exact solution of nonlinear equations. In this article based on the idea
that the numerical scheme with zero truncation error can give rise to exact
solution, a general formula for the exact solution of the initial value problem
of nonlinear ordinary differential equations is obtained. Meanwhile, this
formula enables us to construct a numerical scheme with zero truncation error
for solving the nonlinear differential equations.


  Integrity constraints (ICs) provide a valuable tool for expressing and
enforcing application semantics. However, formulating constraints manually
requires domain expertise, is prone to human errors, and may be excessively
time consuming, especially on large datasets. Hence, proposals for automatic
discovery have been made for some classes of ICs, such as functional
dependencies (FDs), and recently, order dependencies (ODs). ODs properly
subsume FDs, as they can additionally express business rules involving order;
e.g., an employee never has a higher salary while paying lower taxes compared
with another employee.
  We address the limitations of prior work on OD discovery which has factorial
complexity in the number of attributes, is incomplete (i.e., it does not
discover valid ODs that cannot be inferred from the ones found) and is not
concise (i.e., it can result in "redundant" discovery and overly large
discovery sets). We improve significantly on complexity, offer completeness,
and define a compact canonical form. This is based on a novel polynomial
mapping to a canonical form for ODs, and a sound and complete set of axioms
(inference rules) for canonical ODs. This allows us to develop an efficient
set-containment, lattice-driven OD discovery algorithm that uses the inference
rules to prune the search space. Our algorithm has exponential worst-case time
complexity in the number of attributes and linear complexity in the number of
tuples. We prove that it produces a complete, minimal set of ODs (i.e., minimal
with regards to the canonical representation). Finally, using real and
synthetic datasets, we experimentally show orders-of-magnitude performance
improvements over the current state-of-the-art algorithm and demonstrate
effectiveness of our techniques.


  We simulate crystallisation of hard spheres with short-ranged attractive
potentials, as a model self-assembling system. We show how measurements of
correlation and response functions during assembly can be used to tune the
interaction parameters as assembly proceeds, in order to obtain high-quality
crystals. The method we use is independent of details of the interaction
potential and of the structure of the final crystal - we propose that it could
be applied to a wide range of self-assembling systems.


  In the framework of the HIFISTARS guaranteed time key programme, we measured
more than 70 molecular emission lines with high signal-to-noise ratio towards
VY CMa using the high-resolution HIFI spectrometer on board the Herschel
satellite. The kinematic information obtained from the measured water lines
supports the hypothesis of multiple outflow components. The observed
high-intensity maser lines give no indication for strong polarisation.


  The correlations between T, E modes and B modes in cosmic microwave
background (CMB) radiation, which are expected to vanish under parity symmetry,
have become a sensitive probe of the new physics beyond the standard model. In
this paper, we forecast the estimation of TB and EB cross power spectra using
NILC and cILC on AliCPT-1 simulations. We find that, NILC performs better than
cILC on TB and EB correlations in light of its lower uncertainties. In terms of
the birefringence angle estimation without assuming systematic errors, the
combination of CMB TB and EB spectrum from NILC cleaned simulations could reach
a sensitivity of $-0.049^\circ<\beta<0.056^\circ$ (95% CL).


  In this paper we study how certain families of aperiodic infinite words can
be used to produce aperiodic pseudorandom number generators (PRNGs) with good
statistical behavior. We introduce the \emph{well distributed occurrences}
(WELLDOC) combinatorial property for infinite words, which guarantees absence
of the lattice structure defect in related pseudorandom number generators. An
infinite word $u$ on a $d$-ary alphabet has the WELLDOC property if, for each
factor $w$ of $u$, positive integer $m$, and vector $\mathbf v\in\mathbb
Z_{m}^{d}$, there is an occurrence of $w$ such that the Parikh vector of the
prefix of $u$ preceding such occurrence is congruent to $\mathbf v$ modulo $m$.
(The Parikh vector of a finite word $v$ over an alphabet $\mathcal A$ has its
$i$-th component equal to the number of occurrences of the $i$-th letter of
$\mathcal A$ in $v$.) We prove that Sturmian words, and more generally
Arnoux-Rauzy words and some morphic images of them, have the WELLDOC property.
Using the TestU01 and PractRand statistical tests, we moreover show that not
only the lattice structure is absent, but also other important properties of
PRNGs are improved when linear congruential generators are combined using
infinite words having the WELLDOC property.


  We revisit the construction of self-dual field theory in 4l+2 dimensions
using Chern-Simons theory in 4l+3 dimensions, building on the work of Witten.
Careful quantization of the Chern-Simons theory reveals all the topological
subtleties associated with the self-dual partition function, including the
generalization of the choice of spin structure needed to define the theory. We
write the partition function for arbitrary torsion background charge, and in
the presence of sources. We show how this approach leads to the formulation of
an action principle for the self-dual field.


  We present a range of steady-state photoionization simulations, corresponding
to different assumed shell geometries and compositions, of the unseen
postulated rapidly expanding outer shell to the Crab Nebula. The properties of
the shell are constrained by the mass that must lie within it, and by limits to
the intensities of hydrogen recombination lines. In all cases the
photoionization models predict very strong emission from high ionization lines
that will not be emitted by the Crab's filaments, alleviating problems with
detecting these lines in the presence of light scattered from brighter parts of
the Crab. The NIR [Ne VI] $\lambda$7.652 $\mu$m line is a particularly good
case; it should be dramatically brighter than the optical lines commonly used
in searches. The C IV $\lambda1549\AA$ doublet is predicted to be the strongest
absorption line from the shell, which is in agreement with HST observations. We
show that the cooling timescale for the outer shell is much longer than the age
of the Crab, due to the low density. This means that the temperature of the
shell will actually "remember" its initial conditions. However, the
recombination time is much shorter than the age of the Crab, so the predicted
level of ionization should approximate the real ionization. In any case, it is
clear that IR observations present the best opportunity to detect the outer
shell and so guide future models that will constrain early events in the
original explosion.


  Multiterminal transport measurements on YBCO crystals in the vortex liquid
regime have shown nonlocal conductivity on length scales up to 50 microns.
Motivated by these results we explore the wavevector ({\bf k}) dependence of
the dc conductivity tensor, $\sigma_{\mu\nu} ({\bf k})$, in the Meissner,
vortex lattice, and disordered phases of a type-II superconductor. Our results
are based on time-dependent Ginzburg-Landau (TDGL) theory and on
phenomenological arguments. We find four qualitatively different types of
behavior. First, in the Meissner phase, the conductivity is infinite at $k=0$
and is a continuous function of $k$, monotonically decreasing with increasing
$k$. Second, in the vortex lattice phase, in the absence of pinning, the
conductivity is finite (due to flux flow) at $k=0$; it is discontinuous there
and remains qualitatively like the Meissner phase for $k>0$. Third, in the
vortex liquid regime in a magnetic field and at low temperature, the
conductivity is finite, smooth and {\it non-monotonic}, first increasing with
$k$ at small $k$ and then decreasing at larger $k$. This third behavior is
expected to apply at temperatures just above the melting transition of the
vortex lattice, where the vortex liquid shows strong short-range order and a
large viscosity. Finally, at higher temperatures in the disordered phase, the
conductivity is finite, smooth and again monotonically decreasing with $k$.
This last, monotonic behavi or applies in zero magnetic field for the entire
disordered phase, i.e. at all temperatures above $T_c$, while in


  We derive the period structure of several one-modulus Calabi-Yau manifolds.
With this knowledge we then obtain the generators of the duality group and the
mirror map that defines the physical variable $t$ representing the radius of
compactification. We also describe the fundamental region of $t$ and discuss
its relation with automorphic functions. As a byproduct of our analysis we
compute the non-perturbative corrections of Yukawa couplings.


  We show how combinatorial star products can be used to obtain strict
deformation quantizations of polynomial Poisson structures on $\mathbb R^d$,
generalizing known results for constant and linear Poisson structures to
polynomial Poisson structures of arbitrary degree. We give several examples of
nonlinear Poisson structures and construct explicit formal star products whose
deformation parameter can be evaluated to any real value of $\hbar$, giving
strict quantizations on the space of analytic functions on $\mathbb R^d$ with
infinite radius of convergence. We also address further questions such as
continuity of the classical limit $\hbar \to 0$, compatibility with
*-involutions, and the existence of positive linear functionals. The latter can
be used to realize the strict quantizations as *-algebras of operators on a
pre-Hilbert space which we demonstrate in a concrete example.


  Major astrophysical questions related to the formation and evolution of
structures, and more specifically of galaxy groups and clusters, will still be
open in the coming decade and beyond: what is the interplay of galaxy,
supermassive black hole, and intergalactic gas evolution in the most massive
objects in the Universe - galaxy groups and clusters? What are the processes
driving the evolution of chemical enrichment of the hot diffuse gas in
large-scale structures? How and when did the first galaxy groups in the
Universe, massive enough to bind more than 10^7 K gas, form? Focussing on the
period when groups and clusters assembled (0.5<z<2.5), we show that, due to the
continuum and line emission of this hot intergalactic gas at X-ray wavelengths,
Athena+, combining high sensitivity with excellent spectral and spatial
resolution, will deliver breakthrough observations in view of the
aforementioned issues. Indeed, the physical and chemical properties of the hot
intra-cluster gas, and their evolution across time, are a key to understand the
co-evolution of galaxy and supermassive black hole within their environments.


  Pinched flow fractionation is shown to be an efficient and selective way to
quickly separate particles by size in a very polydisperse semi-concentrated
suspension. In an effort to optimize the method, we discuss the quantitative
influence of the pinching intensity in the balance between the requirements of
selectivity and minimal dilution.


  The first flavor-tagged amplitude analysis of the decay D0 to the
self-conjugate final state K+K-pi+pi- is presented. Data from the CLEO II.V,
CLEO III, and CLEO-c detectors are used, from which around 3000 signal decays
are selected. The three most significant amplitudes, which contribute to the
model that best fits the data, are phirho0, K1(1270)+-K-+, and non-resonant
K+K-pi+pi-. Separate amplitude analyses of D0 and D0-bar candidates indicate no
CP violation among the amplitudes at the level of 5% to 30% depending on the
mode. In addition, the sensitivity to the CP-violating parameter gamma/phi3 of
a sample of 2000 B+ -> D0-tilde(K+K-pi+pi-)K+ decays, where D0-tilde is a D0 or
D0-bar, collected at LHCb or a future flavor facility, is estimated to be (11.3
+/- 0.3) degrees using the favored model.


  We investigate the fast transport of an atom or a packet of atoms by
different kinds of non-harmonic traps including power-law traps. The study is
based on the reverse engineering method. Exact results are obtained and applied
to design robust transport protocols. The optimization of the transport
trajectory is performed with classical trajectories, and remains valid for the
transport of a wave packet.


  The study examined the research data management and related services offered
by South Asian countries' academic libraries. Research applied quantitative
approach and survey research design method were used for this study. The survey
questionnaire was distributed randomly to academic library professionals in
five countries: Afghanistan, Bangladesh, India, Pakistan, and Sri Lanka. The
sample population comprised 67 library professionals from various institutes of
five countries. The study recommends that institutes or funding organizations
support staff to attend conferences and workshops on research data management,
library professionals have to join MOOC to take courses related to research
data services, Institute or professionals conduct in-house staff workshops and
presentations. The study also found that 64.2 per cent agreed compliance with
funder requirements and preservation are major issues.