  This paper discusses the experiences gained from designing, deploying and
maintaining low-power wireless sensor networks in three geothermally active
remote locations in Iceland. The purpose of deploying the network was to
collect soil temperature data and investigate the impact of global warming on
(sub)Arctic climate and subsequent carbon release. Functional networks from
three sites with no direct access to power and the internet have been providing
researchers with insight into the warming impacts since 2021. The network
employs low-power wireless sensor nodes equipped with DASH7 communication
protocol, providing real-time data and remote access to sensors and instruments
deployed in the field. In addition to discussing the architecture and
deployment of the network, we conduct a primary analysis using models and
methods to demonstrate the feasibility of harvesting energy from the
temperature gradient between geothermally active soil and air.


  The applicability of computational fluid dynamics (CFD) based design tools
depend on the accuracy and complexity of the physical models, for example
turbulence models, which remains an unsolved problem in physics, and rotor
models that dictates the computational cost of rotorcraft and wind/hydro
turbine farm simulations. The research focuses on investigation of the ability
of neural networks to learn correlation between desired modeling variables and
flow parameters, thereby providing surrogate models. For the turbulence
modeling, the machine learned turbulence model is developed for unsteady
boundary layer flow, and the predictions are validated against DNS data and
compared with one-equation unsteady Reynolds Averaged NavierStokes (URANS)
predictions. The machine-learned model performs much better than the URANS
model due to its ability to incorporate the non-linear correlation between
turbulent stresses and rate-of-strain. The development of the surrogate rotor
model builds on the hypothesis that if a model can mimic the axial and
tangential momentum deficit generated by a blade resolved model, then it should
produce a qualitatively and quantitatively similar wake recovery. An initial
validation of the hypothesis was performed, which showed encouraging results.


  A new formulation of the spectral energy budget of kinetic and available
potential energies of the atmosphere is derived, with spherical harmonics as
base functions. Compared to previous formulations, there are three main
improvements: (i) the topography is taken into account, (ii) the exact
three-dimensional advection terms are considered and (iii) the vertical flux is
separated from the energy transfer between different spherical harmonics. Using
this formulation, results from two different high resolution GCMs are analyzed:
the AFES T639L24 and the ECMWF IFS T1279L91. The spectral fluxes show that the
AFES, which reproduces realistic horizontal spectra with a k^{-5/3} inertial
range at the mesoscales, simulates a strong downscale energy cascade. In
contrast, neither the k^{-5/3} vertically integrated spectra nor the downscale
energy cascade are produced by the ECMWF IFS.


  We give a characterization of the largest $2$-intersecting families of
permutations of $\{1,2,\ldots,n\}$ and of perfect matchings of the complete
graph $K_{2n}$ for all $n \geq 2$.


  This paper presents a substantial extension of our work published at ICLR.
Our ICLR work advocated for enhancing transferability in adversarial examples
by incorporating a Bayesian formulation into model parameters, which
effectively emulates the ensemble of infinitely many deep neural networks,
while, in this paper, we introduce a novel extension by incorporating the
Bayesian formulation into the model input as well, enabling the joint
diversification of both the model input and model parameters. Our empirical
findings demonstrate that: 1) the combination of Bayesian formulations for both
the model input and model parameters yields significant improvements in
transferability; 2) by introducing advanced approximations of the posterior
distribution over the model input, adversarial transferability achieves further
enhancement, surpassing all state-of-the-arts when attacking without model
fine-tuning. Moreover, we propose a principled approach to fine-tune model
parameters in such an extended Bayesian formulation. The derived optimization
objective inherently encourages flat minima in the parameter space and input
space. Extensive experiments demonstrate that our method achieves a new
state-of-the-art on transfer-based attacks, improving the average success rate
on ImageNet and CIFAR-10 by 19.14% and 2.08%, respectively, when comparing with
our ICLR basic Bayesian method. We will make our code publicly available.


  Extremely metal-poor (XMP) galaxies are chemically, and possibly dynamically,
primordial objects in the local Universe. Our objective is to characterize the
HI content of the XMP galaxies as a class, using as a reference the list of 140
known local XMPs compiled by Morales-Luis et al. (2011). We have observed 29
XMPs, which had not been observed before at 21 cm, using the Effelsberg radio
telescope. This information was complemented with HI data published in
literature for a further 53 XMPs. In addition, optical data from the literature
provided morphologies, stellar masses, star-formation rates and metallicities.
Effelsberg HI integrated flux densities are between 1 and 15 Jy km/s, while
line widths are between 20 and 120 km/s. HI integrated flux densities and line
widths from literature are in the range 0.1 - 200 Jy km/s and 15 - 150 km/s,
respectively. Of the 10 new Effelsberg detections, two sources show an
asymmetric double-horn profile, while the remaining sources show either
asymmetric (7 sources) or symmetric (1 source) single-peak 21 cm line profiles.
An asymmetry in the HI line profile is systematically accompanied by an
asymmetry in the optical morphology. Typically, the g-band stellar
mass-to-light ratios are ~0.1, whereas the HI gas mass-to-light ratios may be
up to 2 orders of magnitude larger. Moreover, HI gas-to-stellar mass ratios
fall typically between 10 and 20, denoting that XMPs are extremely gas-rich. We
find an anti-correlation between the HI gas mass-to-light ratio and the
luminosity, whereby fainter XMPs are more gas-rich than brighter XMPs,
suggesting that brighter sources have converted a larger fraction of their HI
gas into stars. The dynamical masses inferred from the HI line widths imply
that the stellar mass does not exceed 5% of the dynamical mass, while the
\ion{H}{i} mass constitutes between 20 and 60% of the dynamical mass.
(abridged)


  We study the collective behavior of Majorana modes in the vortex state of
chiral $p$-wave superconductors. Away from the isolated vortex limit, the
zero-energy Majorana states communicate with each other on a vortex lattice,
and form a coherent band structure with non-trivial topological character. We
revealed that the topological nature of Majorana bands changes sensitively via
quantum phase transitions in the two-dimensional (2D) systems, as sweeping
magnetic field or Fermi energy. Through the dimensional reduction, we showed
the existence of generic superconducting Weyl phase in a low magnetic field
region of quasi-2D-chiral superconductors.


  We extend the SU(3) (Polyakov) Nambu Jona-Lasinio in two ways: We introduce
the next to leading order contribution (in $N_c$) in the partition function.
This contribution contains explicit mesonic terms. We introduce a coupling
between the gluon field and the quark degrees of freedom which goes beyond a
simple rescaling of the critical temperature. With both these improvements we
can reproduce, for vanishing chemical potentials, the lattice results for the
thermal properties of a strongly interacting system like pressure, energy
density, entropy density, interaction measure and the speed of sound. Also the
expansion parameter towards small but finite chemical potentials agrees with
the lattice results. Extending the calculations to finite chemical potentials
(what does not require any new parameter) we find a first order phase
transition up to a critical end point of $T_{CEP}= 110\ MeV$ and $\mu_q = 320\
MeV$. For very large chemical potentials, we find agreement with pQCD
calculations. We calculate the mass of mesons and baryons as a function of
temperature and chemical potential and the transition between the hadronic and
the chirally restored phase. These calculations provide an equation of state in
the whole $T,\mu$ plane an essential ingredient for dynamical calculations of
ultra-relativistic heavy ion collisions but also for the physics of neutron
stars and neutron star collisions.


  We describe a quasi-optical multifrequency ESR spectrometer operating in the
75-225 GHz range and optimized at 210 GHz for general use in condensed matter
physics, chemistry and biology. The quasi-optical bridge detects the change of
mm wave polarization at the ESR. A controllable reference arm maintains a mm
wave bias at the detector. The attained sensitivity of 2x10^10 spin/G/(Hz)1/2,
measured on a dilute Mn:MgO sample in a non-resonant probe head at 222.4 GHz
and 300 K, is comparable to commercial high sensitive X band spectrometers. The
spectrometer has a Fabry-Perot resonator based probe head to measure aqueous
solutions, and a probe head to measure magnetic field angular dependence of
single crystals. The spectrometer is robust and easy to use and may be operated
by undergraduate students. Its performance is demonstrated by examples from
various fields of condensed matter physics.


  In the present work the detection, by means of a nondemolition measurement,
of a Yukawa term, coexisting simultaneously with gravity, has been considered.
In other words, a nondemolition variable for the case of a particle immersed in
a gravitational field containing a Yukawa term is obtained. Afterwards the
continuous monitoring of this nondemolition parameter is analyzed, the
corresponding propagator is evaluated, and the probabilities associated with
the possible measurement outputs are found. The relevance of these kind of
proposals in connection with some unified theories of elementary particles has
been underlined.


  A promising approach to achieve computational supremacy over the classical
von Neumann architecture explores classical and quantum hardware as Ising
machines. The minimisation of the Ising Hamiltonian is known to be NP-hard
problem for certain interaction matrix classes, yet not all problem instances
are equivalently hard to optimise. We propose to identify computationally
simple instances with an `optimisation simplicity criterion'. Such optimisation
simplicity can be found for a wide range of models from spin glasses to
k-regular maximum cut problems. Many optical, photonic, and electronic systems
are neuromorphic architectures that can naturally operate to optimise problems
satisfying this criterion and, therefore, such problems are often chosen to
illustrate the computational advantages of new Ising machines. We further probe
an intermediate complexity for sparse and dense models by analysing circulant
coupling matrices, that can be `rewired' to introduce greater complexity. A
compelling approach for distinguishing easy and hard instances within the same
NP-hard class of problems can be a starting point in developing a standardised
procedure for the performance evaluation of emerging physical simulators and
physics-inspired algorithms.


  A popular intermediary in the theory of artificial satellites is obtained
after the elimination of parallactic terms from the J2-problem Hamiltonian. The
resulting quasi-Keplerian system is in turn converted into the Kepler problem
by a torsion. When this reduction process is applied to unbounded orbits the
solution is made of Keplerian hyperbolae. For this last case, we show that the
torsion-based solution provides an effective alternative to the Keplerian
approximation customarily used in flyby computations. Also, we check that the
extension of the torsion-based solution to higher orders of the oblateness
coefficient yields the expected convergence of asymptotic solutions to the true
orbit.


  We establish a direct correspondence between two congruence poroperties for
finite algebras. The first property is that minimal sets of type i omit tails.
The second property is that congruence lattices omit pentagons of type i.


  We analyze forward-backward charge asymmetry of the lepton production in rare
decays $B\rightarrow X_s l^+l^-$ and $B\rightarrow K^* l^+l^-$, including
vector-resonance effects. Certain regions of phase space, in which the
asymmetry is sensitive to individual short-distance coefficients, are pointed
out. In particular, we suggest a method to test the coupling of the leptonic
axial vector current to the left-handed quark current experimentally.


  In a multi-channel marketing world, the purchase decision journey encounters
many interactions (e.g., email, mobile notifications, display advertising,
social media, and so on). These impressions have direct (main effects), as well
as interactive influence on the final decision of the customer. To maximize
conversions, a marketer needs to understand how each of these marketing efforts
individually and collectively affect the customer's final decision. This
insight will help her optimize the advertising budget over interacting
marketing channels. This problem of interpreting the influence of various
marketing channels to the customer's decision process is called marketing
attribution. We propose a Bayesian model of marketing attribution that captures
established modes of action of advertisements, including the direct effect of
the ad, decay of the ad effect, interaction between ads, and customer
heterogeneity. Our model allows us to incorporate information from customer's
features and provides usable error bounds for parameters of interest, like the
ad effect or the half-life of an ad. We apply our model on a real-world dataset
and evaluate its performance against alternatives in simulations.


  We discuss the properties of the gas of primordial `stringy' black holes
possibly formed in the high-curvature phase preceding the bouncing transition
to the phase of standard cosmological evolution. We show that the regime
dominated by such a string-hole gas can be consistently described by explicit
solutions of the string effective action including first-order $\alpha'$
corrections. We present a phase space analysis of the stability of such
solutions comparing the results obtained from different actions and including
the possibility of $O(d,d)$-symmetric configurations.


  We present multi-wavelength observations of a typical long duration GRB
120326A at $z=1.798$, including rapid observations using a submillimeter array
(SMA), and a comprehensive monitoring in X-ray and optical. The SMA observation
provided the fastest detection to date among seven submillimeter afterglows at
230 GHz. The prompt spectral analysis, using Swift and Suzaku yielded a
spectral peak energy of $E^{\rm src}_{\rm peak}=107.8^{+15.3}_{-15.3}$ keV and
equivalent isotropic energy of $E_{\rm iso}$ as $3.18^{+0.40}_{-0.32}\times
10^{52}$ erg. The temporal evolution and spectral properties in the optical
were consistent with the standard forward shock synchrotron with jet
collimation ($6^{\circ}.69\pm0^{\circ}.16$). The forward shock modeling using a
2D relativistic hydrodynamic jet simulation also determined the reasonable
burst explosion and the synchrotron radiation parameters for the optical
afterglow. The X-ray light curve showed no apparent jet break and the temporal
decay index relation between the X-ray and optical ($\alpha{\rm
o}-\alpha_{X}=-1.45\pm0.10$) indicated different radiation processes in the
X-ray and optical. Introducing synchrotron self-inverse Compton radiation from
reverse shock is a possible solution, and the detection and the slow decay of
the afterglow in submillimeter supports that this is a plausible idea. The
observed temporal evolution and spectral properties as well as forward shock
modeling parameters, enabled to determine reasonable functions to describe the
afterglow properties. Because half of events share similar properties in the
X-ray and optical to the current event, GRB120326A will be a benchmarks with
further rapid follow-ups, using submillimeter instruments such as SMA and ALMA.


  In this paper, we report on achieving hybridization effect in a Mie-based
dielectric metamolecule and provide their physically intuitive picture. The
hybridization results in the splitting of the initial overlapping resonance
dips, thus leading to two new collective resonance modes. It can be observed
via the displacement electric field distribution that the two modes behave as
the in-phase and out-of-phase oscillation of two meta-atoms, thus enhancing and
diminishing the intensity of electric field at the gap between two meta-atoms.
Moreover, since the two hybridized modes are caused by the interaction effect,
the enhancement amplitude can be adjusted by several coupling factors, like gap
distances and spot positions. Taking advantage of the two collective modes of
the dielectric metamolecule, certain locations in the metamolecule can be
applied as heating zones in microwave band and signal amplifier or shielding
zones in communication fields.


  Graph representation learning has attracted a surge of interest recently,
whose target at learning discriminant embedding for each node in the graph.
Most of these representation methods focus on supervised learning and heavily
depend on label information. However, annotating graphs are expensive to obtain
in the real world, especially in specialized domains (i.e. biology), as it
needs the annotator to have the domain knowledge to label the graph. To
approach this problem, self-supervised learning provides a feasible solution
for graph representation learning. In this paper, we propose a Multi-Level
Graph Contrastive Learning (MLGCL) framework for learning robust representation
of graph data by contrasting space views of graphs. Specifically, we introduce
a novel contrastive view - topological and feature space views. The original
graph is first-order approximation structure and contains uncertainty or error,
while the $k$NN graph generated by encoding features preserves high-order
proximity. Thus $k$NN graph generated by encoding features not only provide a
complementary view, but is more suitable to GNN encoder to extract discriminant
representation. Furthermore, we develop a multi-level contrastive mode to
preserve the local similarity and semantic similarity of graph-structured data
simultaneously. Extensive experiments indicate MLGCL achieves promising results
compared with the existing state-of-the-art graph representation learning
methods on seven datasets.


  Fault attacks enable adversaries to manipulate the control-flow of
security-critical applications. By inducing targeted faults into the CPU, the
software's call graph can be escaped and the control-flow can be redirected to
arbitrary functions inside the program. To protect the control-flow from these
attacks, dedicated fault control-flow integrity (CFI) countermeasures are
commonly deployed. However, these schemes either have high detection latencies
or require intrusive hardware changes. In this paper, we present EC-CFI, a
software-based cryptographically enforced CFI scheme with no detection latency
utilizing hardware features of recent Intel platforms. Our EC-CFI prototype is
designed to prevent an adversary from escaping the program's call graph using
faults by encrypting each function with a different key before execution. At
runtime, the instrumented program dynamically derives the decryption key,
ensuring that the code only can be successfully decrypted when the program
follows the intended call graph. To enable this level of protection on Intel
commodity systems, we introduce extended page table (EPT) aliasing allowing us
to achieve function-granular encryption by combing Intel's TME-MK and
virtualization technology. We open-source our custom LLVM-based toolchain
automatically protecting arbitrary programs with EC-CFI. Furthermore, we
evaluate our EPT aliasing approach with the SPEC CPU2017 and Embench-IoT
benchmarks and discuss and evaluate potential TME-MK hardware changes
minimizing runtime overheads.


  Morphosyntactic lexicons and word vector representations have both proven
useful for improving the accuracy of statistical part-of-speech taggers. Here
we compare the performances of four systems on datasets covering 16 languages,
two of these systems being feature-based (MEMMs and CRFs) and two of them being
neural-based (bi-LSTMs). We show that, on average, all four approaches perform
similarly and reach state-of-the-art results. Yet better performances are
obtained with our feature-based models on lexically richer datasets (e.g. for
morphologically rich languages), whereas neural-based results are higher on
datasets with less lexical variability (e.g. for English). These conclusions
hold in particular for the MEMM models relying on our system MElt, which
benefited from newly designed features. This shows that, under certain
conditions, feature-based approaches enriched with morphosyntactic lexicons are
competitive with respect to neural methods.


  We consider a parabolic-type PDE with a diffusion given by a fractional
Laplacian operator and with a quadratic nonlinearity of the 'gradient' of the
solution, convoluted with a singular term b. Our first result is the
well-posedness for this problem: We show existence and uniqueness of a (local
in time) mild solution. The main result is about blow-up of said solution, and
in particular we find sufficient conditions on the initial datum and on the
term b to ensure blow-up of the solution in finite time.


  An important "stability" theorem in shape theory, due to D.A. Edwards and R.
Geoghegan, characterizes those compacta having the same shape as a finite CW
complex. In this note we present straightforward and self-contained proof of
that theorem.


  Large pre-trained transformers are show-stealer in modern-day deep learning,
and it becomes crucial to comprehend the parsimonious patterns that exist
within them as they grow in scale. With exploding parameter counts, Lottery
Ticket Hypothesis (LTH) and its variants, have lost their pragmatism in
sparsifying them due to high computation and memory bottleneck of repetitive
train-prune-retrain routine of iterative magnitude pruning (IMP) which worsens
with increasing model size. This paper comprehensively studies induced sparse
patterns across multiple large pre-trained vision and language transformers. We
propose the existence of -- essential sparsity defined with a sharp dropping
point beyond which the performance declines much faster w.r.t the rise of
sparsity level, when we directly remove weights with the smallest magnitudes in
one-shot without re-training. We also find essential sparsity to hold valid for
N:M sparsity patterns as well as on modern-scale large language models
(Vicuna-7B). We also present an intriguing emerging phenomenon of abrupt
sparsification during the pre-training of BERT, i.e., BERT suddenly becomes
heavily sparse in pre-training after certain iterations. Moreover, our
observations also indicate a counter-intuitive finding that BERT trained with a
larger amount of pre-training data tends to have a better ability to condense
knowledge in comparatively relatively fewer parameters. Lastly, we investigate
the effect of the pre-training loss on essential sparsity and discover that
self-supervised learning (SSL) objectives trigger stronger emergent
sparsification properties than supervised learning (SL). Our codes are
available at \url{https://github.com/VITA-Group/essential_sparsity}.


  A general discussion is presented of the single logarithmic soft factor that
appears in two scale QCD observables in processes involving four partons. We
treat it as the ``fifth form factor'', accompanying the four collinear singular
Sudakov form factors attached to colliding and outgoing hard partons. The fifth
form factor is expressed in terms of the Casimir operators (squared colour
charges) of irreducible representations in the crossing $t$- and $u$-channels.
As an application we revisit the problem of large angle radiation in $gg\to gg$
and give a relatively simple solution and interpretation of the results. We
found an unexpected symmetry of the soft anomalous dimension under exchange of
internal and external variables of the problem whose existence calls for
explanation.


  Reconfigurable intelligent surfaces (RISs) are considered as potential
technologies for the upcoming sixth-generation (6G) wireless communication
system. Various benefits brought by deploying one or multiple RISs include
increased spectrum and energy efficiency, enhanced connectivity, extended
communication coverage, reduced complexity at transceivers, and even improved
localization accuracy. However, to unleash their full potential, fundamentals
related to RISs, ranging from physical-layer (PHY) modelling to RIS phase
control, need to be addressed thoroughly. In this paper, we provide an overview
of some timely research problems related to the RIS technology, i.e., PHY
modelling (including also physics), channel estimation, potential RIS
architectures, and RIS phase control (via both model-based and data-driven
approaches), along with recent numerical results. We envision that more efforts
will be devoted towards intelligent wireless environments, enabled by RISs.


  Due to the fact that quality of service requirements are not very strict for
all traffic types, more calls of higher priority can be accommodated by
reducing some bandwidth allocation for the bandwidth adaptive calls. The
bandwidth adaptation to accept a higher priority call is more than that of a
lower priority call. Therefore, the multi-level bandwidth adaptation technique
improves the overall forced call termination probability as well as provides
priority of the traffic classes in terms of call blocking probability without
reducing the bandwidth utilization. We propose a novel bandwidth adaptation
model that releases multi-level of bandwidth from the existing multimedia
traffic calls. The amount of released bandwidth is decided based on the
priority of the requesting traffic calls and the number of existing bandwidth
adaptive calls. This prioritization of traffic classes does not reduce the
bandwidth utilization. Moreover, our scheme reduces the overall forced call
termination probability significantly. The proposed scheme is modeled using the
Markov Chain. The numerical results show that the proposed scheme is able to
provide negligible handover call dropping probability as well as significantly
reduced new call blocking probability of higher priority calls without
increasing the overall forced call termination probability.


  The 2x3 channel pseudo Vertex Position Detector (pVPD) in the STAR experiment
at RHIC has been upgraded to a 2x19 channel detector in the same acceptance,
called the Vertex Position Detector (VPD). This detector is fully integrated
into the STAR trigger system and provides the primary input to the minimum-bias
trigger in Au+Au collisions. The information from the detector is used both in
the STAR Level-0 trigger and offline to measure the location of the primary
collision vertex along the beam pipe and the event "start time" needed by other
fast-timing detectors in STAR. The offline timing resolution of single detector
channels in full-energy Au+Au collisions is ~100 ps, resulting in a start time
resolution of a few tens of picoseconds and a resolution on the primary vertex
location of ~1 cm.


  Long-tailed object detection faces great challenges because of its extremely
imbalanced class distribution. Recent methods mainly focus on the
classification bias and its loss function design, while ignoring the subtle
influence of the regression branch. This paper shows that the regression bias
exists and does adversely and seriously impact the detection accuracy. While
existing methods fail to handle the regression bias, the class-specific
regression head for rare classes is hypothesized to be the main cause of it in
this paper. As a result, three kinds of viable solutions to cater for the rare
categories are proposed, including adding a class-agnostic branch, clustering
heads and merging heads. The proposed methods brings in consistent and
significant improvements over existing long-tailed detection methods,
especially in rare and common classes. The proposed method achieves
state-of-the-art performance in the large vocabulary LVIS dataset with
different backbones and architectures. It generalizes well to more difficult
evaluation metrics, relatively balanced datasets, and the mask branch. This is
the first attempt to reveal and explore rectifying of the regression bias in
long-tailed object detection.


  The spatial, kinematic, and elemental-abundance structure of the Milky Way's
stellar disk is complex, and has been difficult to dissect with local
spectroscopic or global photometric data. Here, we develop and apply a rigorous
density modeling approach for Galactic spectroscopic surveys that enables
investigation of the global spatial structure of stellar sub-populations in
narrow bins of [\alpha/Fe] and [Fe/H], using 23,767 G-type dwarfs from
SDSS/SEGUE. We fit models for the number density of each such mono-abundance
component, properly accounting for the complex spectroscopic SEGUE sampling of
the underlying stellar population. We find that each mono-abundance
sub-population has a simple spatial structure that can be described by a single
exponential in both the vertical and radial direction, with continuously
increasing scale heights (~200 pc to 1 kpc) and decreasing scale lengths (>4.5
kpc to 2 kpc) for increasingly older sub-populations, as indicated by their
lower metallicities and [\alpha/Fe] enhancements. That the abundance-selected
sub-components with the largest scale heights have the shortest scale lengths
is in sharp contrast with purely geometric `thick--thin disk' decompositions.
To the extent that [\alpha/Fe] is an adequate proxy for age, our results
directly show that older disk sub-populations are more centrally concentrated,
which implies inside-out formation of galactic disks. The fact that the largest
scale-height sub-components are most centrally concentrated in the Milky Way is
an almost inevitable consequence of explaining the vertical structure of the
disk through internal evolution. Whether the simple spatial structure of the
mono-abundance sub-components, and the striking correlations between age, scale
length, and scale height can be plausibly explained by satellite accretion or
other external heating remains to be seen.


  Teleportation of optical field states (as continuous quantum variables) is
usually described in terms of Wigner functions. This is in marked contrast to
the theoretical treatment of teleportation of qubits. In this paper we show
that by using the holomorphic representation of the canonical commutation
relations, teleportation of continuous quantum variables can be treated in
complete analogy to the case of teleportation of qubits. In order to emphasize
this analogy, short descriptions of the basic experimental schemes both for
teleportation of qubits and of continuous variables are included. We conclude
our paper with a brief discussion of the effectiveness of our description of
continuous variable teleportation and of the role of localization of quantum
states in teleportation problems.


  Channel Pruning has been long studied to compress CNNs, which significantly
reduces the overall computation. Prior works implement channel pruning in an
unexplainable manner, which tends to reduce the final classification errors
while failing to consider the internal influence of each channel. In this
paper, we conduct channel pruning in a white box. Through deep visualization of
feature maps activated by different channels, we observe that different
channels have a varying contribution to different categories in image
classification. Inspired by this, we choose to preserve channels contributing
to most categories. Specifically, to model the contribution of each channel to
differentiating categories, we develop a class-wise mask for each channel,
implemented in a dynamic training manner w.r.t. the input image's category. On
the basis of the learned class-wise mask, we perform a global voting mechanism
to remove channels with less category discrimination. Lastly, a fine-tuning
process is conducted to recover the performance of the pruned model. To our
best knowledge, it is the first time that CNN interpretability theory is
considered to guide channel pruning. Extensive experiments on representative
image classification tasks demonstrate the superiority of our White-Box over
many state-of-the-arts. For instance, on CIFAR-10, it reduces 65.23% FLOPs with
even 0.62% accuracy improvement for ResNet-110. On ILSVRC-2012, White-Box
achieves a 45.6% FLOPs reduction with only a small loss of 0.83% in the top-1
accuracy for ResNet-50.


  Quantum simulation algorithms often require numerous ancilla qubits and deep
circuits, prohibitive for near-term hardware. We introduce a framework for
simulating quantum channels using ensembles of low-depth circuits in place of
many-qubit dilations. This naturally enables simulations of open systems, which
we demonstrate by preparing damped many-qubit GHZ states on ibm_hanoi. The
technique further inspires two Hamiltonian simulation algorithms with
asymptotic independence of the spectral precision, reducing resource
requirements by several orders of magnitude for a benchmark system.


  We present an algorithm for factoring linear differential operators with
coefficients in a finite separable extension of F p (x). Our methods rely on
specific tools arising in positive characteristic: p-curvature, structure of
simple central algebras and p-Riccati equations.


  The use of micro-Raman spectroscopy, through chemical bond nano-scale probes,
allows the changes in conformations (alpha helix -> beta sheet), chain
orientation, disconnection of disulfide bonds (-20%) and the increase of intra
and inter-chain distances during the strain to be distinguished. The
combination of micro-Raman spectroscopy and a allows a quantitative measure of
the extension of chemical bonds in the peptidic chain during loading. The
nano-structural transformations of keratin during the strain of human hair in a
dry environment (40-60 % relative humidity) and saturated with water have been
studied. The water permits the sliding of the chains and decreases the bond
energy hair. Spectral analyses and 2D correlation are two coherent and
independent methods to follow change the Raman probes which are sensitive to
structural . The between nano-mechanical (Raman) and micro-mechanical
(strain/stress) analyses confirms the validity of the experimental results,
tools and principles used, as well as the agreement with the structural model
of keratin fibres described by Chapman & Hearle.


  We report the multi-frequency observations of two pulsars: J1740+1000 and
B1800-21, using the Giant Metrewave Radio Telescope and the Green Bank
Telescope. The main aim of these observations was to estimate the flux density
spectrum of these pulsars, as both of them were previously reported to exhibit
gigahertz-peaked spectra. J1740+1000 is a young pulsar far from the Galactic
plane and the interpretation of its spectrum was inconclusive in the light of
the recent flux density measurements. Our result supports the gigahertz-peaked
interpretation of the PSR J1740+1000 spectrum. B1800-21 is a Vela-like pulsar
near the W30 complex, whose spectrum exhibit a significant change between 2012
and 2014 year. Our analysis shows that the current shape of the spectrum is
similar to that observed before 2009 and confirms that the observed spectral
change happen in a time-scale of a few years.


  We study the partition function Z_{G(nk,k)}(Q,v) of the Q-state Potts model
on the family of (non-planar) generalized Petersen graphs G(nk,k). We study its
zeros in the plane (Q,v) for 1<= k <= 7. We also consider two specializations
of Z_{G(nk,k)}, namely the chromatic polynomial P_{G(nk,k)}(Q) (corresponding
to v=-1), and the flow polynomial Phi_{G(nk,k)}(Q) (corresponding to v=-Q). In
these two cases, we study their zeros in the complex Q-plane for 1 <= k <= 7.
We pay special attention to the accumulation loci of the corresponding zeros
when n -> infinity. We observe that the Berker-Kadanoff phase that is present
in two-dimensional Potts models, also exists for non-planar recursive graphs.
Their qualitative features are the same; but the main difference is that the
role played by the Beraha numbers for planar graphs is now played by the
non-negative integers for non-planar graphs. At these integer values of Q,
there are massive eigenvalue cancellations, in the same way as the eigenvalue
cancellations that happen at the Beraha numbers for planar graphs.


  A graph $G$ is $r$-equitably $k$-colorable if its vertex set can be
partitioned into $k$ independent sets, any two of which differ in size by at
most $r$. The $r$-equitable chromatic threshold of a graph $G$, denoted by
$\chi_{r=}^*(G)$, is the minimum $k$ such that $G$ is $r$-equitably
$k'$-colorable for all $k'\ge k$. Let $G\times H$ denote the Kronecker product
of graphs $G$ and $H$. In this paper, we completely determine the exact value
of $\chi_{r=}^*(K_m\times K_n)$ for general $m,n$ and $r$. As a consequence, we
show that for $r\ge 2$, if $n\ge \frac{1}{r-1}(m+r)(m+2r-1)$ then $K_m\times
K_n$ and its spanning supergraph $K_{m(n)}$ have the same $r$-equitable
colorability, and in particular $\chi_{r=}^*(K_m\times
K_n)=\chi_{r=}^*(K_{m(n)})$, where $K_{m(n)}$ is the complete $m$-partite graph
with $n$ vertices in each part.


  System auditing is a powerful tool that provides insight into the nature of
suspicious events in computing systems, allowing machine operators to detect
and subsequently investigate security incidents. While auditing has proven
invaluable to the security of traditional computers, existing audit frameworks
are rarely designed with consideration for Real-Time Systems (RTS). The
transparency provided by system auditing would be of tremendous benefit in a
variety of security-critical RTS domains, (e.g., autonomous vehicles); however,
if audit mechanisms are not carefully integrated into RTS, auditing can be
rendered ineffectual and violate the real-world temporal requirements of the
RTS.
  In this paper, we demonstrate how to adapt commodity audit frameworks to RTS.
Using Linux Audit as a case study, we first demonstrate that the volume of
audit events generated by commodity frameworks is unsustainable within the
temporal and resource constraints of real-time (RT) applications. To address
this, we present Ellipsis, a set of kernel-based reduction techniques that
leverage the periodic repetitive nature of RT applications to aggressively
reduce the costs of system-level auditing. Ellipsis generates succinct
descriptions of RT applications' expected activity while retaining a detailed
record of unexpected activities, enabling analysis of suspicious activity while
meeting temporal constraints. Our evaluation of Ellipsis, using ArduPilot (an
open-source autopilot application suite) demonstrates up to 93% reduction in
audit log generation.


  Let $S_g$ denote a closed, orientable surface of genus $g \geq 2$ and
$\mathcal{C}(S_g)$ be the associated curve complex. The mapping class group of
$S_g$, $Mod(S_g)$ acts on $\mathcal{C}(S_g)$ by isometries. Since Dehn twists
about certain curves generate $Mod(S_g)$, one can ask how Dehn twists move
specific vertices in $\mathcal{C}(S_g)$ away from themselves. We show that if
two curves represent vertices at a distance $3$ in $\mathcal{C}(S_g)$ then the
Dehn twist of one curve about another yields two vertices at distance $4$. This
produces many tractable examples of distance $4$ vertices in
$\mathcal{C}(S_g)$. We also show that the minimum intersection number of any
two curves at a distance $4$ on $S_g$ is at most $(2g-1)^2$.


  We use recent 36 observational Hubble data (OHD) in the redshift range
$0.07\leq z\leq 2.36$, latest \textgravedbl joint light curves\textacutedbl
(JLA) sample, comprised of 740 type Ia supernovae (SNIa) in the redshift range
$0.01\leq z \leq 1.30$, and their joint combination datasets to constrain
anisotropic Bianchi type I (BI) dark energy (DE) model. To estimate model
parameters, we apply Hamiltonian Monte Carlo technique. We also compute the
covariance matrix for BI dark energy model by considering different datasets to
compare the correlation between model parameters. To check the acceptability of
our fittings, all results are compared with those obtained from 9 year WMAP as
well as Planck (2015) collaboration. Our estimations show that at 68\%
confidence level the dark energy equation of state (EOS) parameter for OHD or
JLA datasets alone varies between quintessence and phantom regions whereas for
OHD+JLA dataset this parameter only varies in phantom region. It is also found
that the current cosmic anisotropy is of order $\sim10^{-3}$ which imply that
the OHD and JLA datasets do not put tight constraint on this parameter.
Therefore, to constraint anisotropy parameter, it is necessary to use high
redshif dataset namely cosmic microwave background (CMB). Moreover, from the
calculation of $p$-value associated with $\chi^{2}$ statistic we observed that
non of the $\omega \mbox{BI}$ and flat $\omega\mbox{CDM}$ models rule out by
OHD or JLA datasets. The deceleration parameter is obtained as $q=-0.46^{+0.89
+0.36}_{-0.41 -0.37}$, $q=-0.619^{+0.12 +0.20}_{-0.095 -0.24}$, and
$q=-0.52^{+0.080 +0.014}_{-0.046 -0.15}$ for OHD, SNIa, and OHD+SNIa data
respectively.


  In order to clarify the ``superradiant'' conditions for the moving Josephson
vortices to excite in-phase AC electromagnetic fields over all junctions, we
perform large scale simulations of realistic dimensions for intrinsic Josephson
junctions under the layer parallel magnetic field. Three clear step-like
structures in the I-V curve are observed above a certain high field ($H > 1T$
in the present simulations), at which we find structural transitions in the
moving flux-line lattice. The Josephson vortex flow states are accordingly
classified into four regions (region I $\sim $ IV with increasing current), in
each of which the power spectrum for the electric field oscillations at the
sample edge are measured and typical snapshots for Josephson vortex
configurations are displayed. Among the four regions, especially in the region
III, an in-phase rectangular vortex lattice flow state emerges and the power
spectrum shows remarkably sharp peak structure, i.e., superradiant state.
Comparison of the simulation results with an eigenmode analysis for the
transverse propagating Josephson plasma oscillations reveals that the
resonances between Josephson vortex flow states and some of the eigenmodes are
responsible for the clear flux lattice structural transitions. Furthermore, the
theoretical analysis clarifies that the width of the superradiant state region
in the I-V characteristics enlarges with decreasing both the superconducting
and insulating layer thickness.


  Localization properties for Schr\"odinger means are studied in dimension
higher than one.


  Close to a zero temperature transition between ordered and disordered
electronic phases, quantum fluctuations can lead to a strong enhancement of the
electron mass and to the emergence of competing phases such as
superconductivity. A correlation between the existence of such a quantum phase
transition and superconductivity is quite well established in some heavy
fermion and iron-based superconductors and there have been suggestions that
high temperature superconductivity in the copper oxide materials (cuprates) may
also be driven by the same mechanism. Close to optimal doping, where the
superconducting transition temperature $T_c$ is maximum in the cuprates, two
different phases are known to compete with superconductivity: a poorly
understood pseudogap phase and a charge ordered phase. Recent experiments have
shown a strong increase in quasiparticle mass $m^*$ in the cuprate
YBa$_2$Cu$_3$O$_{7-\delta}$ as optimal doping is approached suggesting that
quantum fluctuations of the charge ordered phase may be responsible for the
high-$T_c$ superconductivity. We have tested the robustness of this correlation
between $m^*$ and $T_c$ by performing quantum oscillation studies on the
stoichiometric compound YBa$_2$Cu$_4$O$_8$ under hydrostatic pressure. In
contrast to the results for YBa$_2$Cu$_3$O$_{7-\delta}$, we find that in
YBa$_2$Cu$_4$O$_8$ the mass decreases as $T_c$ increases under pressure. This
inverse correlation between $m^*$ and $T_c$ suggests that quantum fluctuations
of the charge order enhance $m^*$ but do not enhance $T_c$.


  We study an axisymmetric metric satisfying the Petrov type D property with
some additional ansatze, but without assuming the vacuum condition. We find
that our metric in turn becomes conformal to the Kerr metric deformed by one
function of the radial coordinate. We then study the gravitational-wave
equations on this background metric in the case that the conformal factor is
unity. We find that under an appropriate gauge condition, the homogeneous wave
equations admit the separation of the variables, which is also helpful for
solving the nonhomogeneous equations. The resultant ordinary differential
equation for the radial coordinate gives a natural extension of the Teukolsky
equation.


  Let $G$ be a connected graph, the principal ratio of $G$ is the ratio of the
maximum and minimum entries of its Perron eigenvector. In 2007, Cioab\v a and
Gregory conjectured that among all connected graphs on $n$ vertices, the kite
graph attains the maximum principal ratio. In 2018, Tait and Tobin confirmed
the conjecture for sufficientlty large $n$. In this article, we show the
conjecture is true for all $n\geq 5000$.


  Characterising stellar and circumstellar properties of embedded young stellar
objects (YSOs) is mandatory for understanding the early stages of the stellar
evolution. This task requires the combination of both spectroscopy and
photometry, covering the widest possible wavelength range, to disentangle the
various protostellar components and activities. As part of the POISSON project,
we present a multi-wavelength spectroscopic and photometric investigation of
embedded YSOs in L1641, aimed to derive the stellar parameters and evolutionary
stages and to infer their accretion properties. Our database includes
low-resolution optical-IR spectra from the NTT and Spitzer (0.6-40 um) and
photometric data covering a spectral range from 0.4 to 1100 um, which allow us
to construct the YSOs spectral energy distributions (SEDs) and to infer the
main stellar parameters. The SED analysis allows us to group our 27 YSOs into
nine Class I, eleven Flat, and seven Class II objects. However, on the basis of
the derived stellar properties, only six Class I YSOs have an age of ~10^5 yr,
while the others are older 5x10^5-10^6 yr), and, among the Flat sources, three
out of eleven are more evolved objects (5x10^6-10^7 yr), indicating that
geometrical effects can significantly modify the SED shapes. Inferred mass
accretion rates (Macc) show a wide range of values (3.6x10^-9 to 1.2x10^-5
M_sun yr^-1), which reflects the age spread observed in our sample. Average
values of mass accretion rates, extinction, and spectral indices decrease with
the YSO class. The youngest YSOs have the highest Macc, whereas the oldest YSOs
do not show any detectable jet activity in either images and spectra. We also
observe a clear correlation among the YSO Macc, M*, and age, consistent with
mass accretion evolution in viscous disc models.


  We study stochastic motion under a nonlinear frictional force that levels off
with increasing velocity. Specifically, our frictional force is of the
so-called Coulomb-tanh type. At small speed, it increases approximately
linearly with velocity, while at large speed it approaches a constant
magnitude, similarly to solid (dry, Coulomb) friction. In one spatial
dimension, a formal analogy between the associated Fokker-Planck equation and
the Schr\"odinger equation for a quantum-mechanical oscillator in a nonharmonic
P\"oschl-Teller potential is revealed. Then, the stationary velocity statistics
can be treated analytically. From such analytical considerations, we determine
associated diffusion coefficients, which we confirm by agent-based simulations.
Moreover, from such simulations and from numerically solving the associated
Fokker-Planck equation, we find that the spatial distribution function,
starting from an initial Gaussian shape, develops tails that appear exponential
at intermediate time scales. At small magnitudes of stochastic driving, the
velocity distribution resembles the case of linear friction, while at large
magnitudes it rather approaches the case of solid (dry, Coulomb) friction. The
same is true for diffusion coefficients. In a certain sense, thus interpolating
between the two extreme cases of linear friction and solid (dry, Coulomb)
friction, our approach should be useful to describe several cases of practical
relevance. For instance, a reduced increase in friction with increasing
relative speed is typical of shear-thinning behavior. Therefore, driven motion
in shear-thinning environments is one specific example to which our description
may be applied.


  We continue our study of the density of the odd values of eta-quotients, here
focusing on the $m$-regular partition functions $b_m$ for $m$ even. Based on
extensive computational evidence, we propose an elegant conjecture which, in
particular, completely classifies such densities: Let $m = 2^j m_0$ with $m_0$
odd. If $2^j < m_0$, then the odd density of $b_m$ is $1/2$; moreover, such
density is equal to $1/2$ on every (nonconstant) subprogression $An+B$. If $2^j
> m_0$, then $b_m$, which is already known to have density zero, is identically
even on infinitely many non-nested subprogressions. This and all other
conjectures of this paper are consistent with our ''master conjecture'' on
eta-quotients presented in the previous work.
  In general, our results on $b_m$ for $m$ even determine behaviors
considerably different from the case of $m$ odd. Also interesting, it
frequently happens that on subprogressions $An+B$, $b_m$ matches the parity of
the multipartition functions $p_t$, for certain values of $t$. We make a
suitable use of Ramanujan-Kolberg identities to deduce a large class of such
results; as an example, $b_{28}(49n+12) \equiv p_3(7n+2) \pmod{2}$. Additional
consequences are several ''almost always congruences'' for various $b_m$, as
well as new parity results specifically for $b_{11}$.
  We wrap up our work with a much simpler proof of the main result of a recent
paper by Cherubini-Mercuri, which fully characterized the parity of $b_8$.


  The problem of rare and unknown words is an important issue that can
potentially influence the performance of many NLP systems, including both the
traditional count-based and the deep learning models. We propose a novel way to
deal with the rare and unseen words for the neural network models using
attention. Our model uses two softmax layers in order to predict the next word
in conditional language models: one predicts the location of a word in the
source sentence, and the other predicts a word in the shortlist vocabulary. At
each time-step, the decision of which softmax layer to use choose adaptively
made by an MLP which is conditioned on the context.~We motivate our work from a
psychological evidence that humans naturally have a tendency to point towards
objects in the context or the environment when the name of an object is not
known.~We observe improvements on two tasks, neural machine translation on the
Europarl English to French parallel corpora and text summarization on the
Gigaword dataset using our proposed model.


  We discuss rapidity-gap events between two jets produced at high momentum
transfer in $p$ $\bar{p}$ scattering, from the point of view of the soft energy
flow into the interjet region. We define a gap cross section and, in
perturbative QCD (pQCD), resum all the leading logarithms in the soft
intermediate energy. We show that the numerical result from our cross section
reproduces the shape of the D0 and CDF \cite{D0,CDF,D0fig} experimental data.


  Purpose: To evaluate the quality of deep learning reconstruction for
prospectively accelerated intraoperative magnetic resonance imaging (iMRI)
during resective brain tumor surgery.
  Materials and Methods: Accelerated iMRI was performed during brain surgery
using dual surface coils positioned around the area of resection. A deep
learning (DL) model was trained on the fastMRI neuro dataset to mimic the data
from the iMRI protocol. Evaluation was performed on imaging material from 40
patients imaged between 01.11.2021 - 01.06.2023 that underwent iMRI during
tumor resection surgery. A comparative analysis was conducted between the
conventional compressed sense (CS) method and the trained DL reconstruction
method. Blinded evaluation of multiple image quality metrics was performed by
two working neuro-radiologists and a working neurosurgeon on a 1 to 5 Likert
scale (1=non diagnostic, 2=poor, 3=acceptable, 4=good, 5=excellent), and the
favored reconstruction variant.
  Results: The DL reconstruction was strongly favored or favored over the CS
reconstruction for 33/40, 39/40, and 8/40 of cases for reader 1, 2, and 3,
respectively. Two of three readers consistently assigned higher ratings for the
DL reconstructions, and the DL reconstructions had a higher score than their
respective CS counterparts for 72%, 72%, and 14% of the cases for reader 1, 2,
and 3, respectively. Still, the DL reconstructions exhibited shortcomings such
as a striping artifact and reduced signal.
  Conclusion: DL shows promise to allow for high-quality reconstructions of
intraoperative MRI with equal to or improved perceived spatial resolution,
signal-to-noise ratio, diagnostic confidence, diagnostic conspicuity, and
spatial resolution compared to compressed sense.


  At proposed high energy linear e+e- colliders a large number of W bosons and
top quarks will be produced. We evaluate the potential precision to which the
decay branching ratios into the various quark species can be measured, implying
also the determination of the respective CKM matrix elements. Crucial is the
identification of the individual quark flavours, which can be achieved
independent of QCD models. For transitions involving up quarks the accuracy is
of the same order of magnitude as has been reached in hadron decays. We
estimate that for charm transitions a precision can be reached that is superior
to current and projected traditional kinds of measurements. The t->b
determination will be significantly improved, and for the first time a direct
measurement of the t->s transition can be made. In all cases such a
determination is complementary to the traditional way of extracting the CKM
matrix elements.


  We compute the phase diagram of a biased graphene bilayer. The existence of a
ferromagnetic phase is discussed with respect both to carrier density and
temperature. We find that the ferromagnetic transition is first order, lowering
the value of $U$ relatively to the usual Stoner criterion. We show that in the
ferromagnetic phase the two planes have unequal magnetization and that the
electronic density is hole like in one plane and electron like in the other.


  The nature of the BA function and its adjoint for KP-Toda is traced through
the averaging method in generating the Whitham equations, differentials, and
symplectic forms, with connections to EM duality.


  Extending work of Klyachko and Perling, we develop a combinatorial
description of pure equivariant sheaves of any dimension on an arbitrary
nonsingular toric variety $X$. Using geometric invariant theory (GIT), this
allows us to construct explicit moduli spaces of pure equivariant sheaves on
$X$ corepresenting natural moduli functors (similar to work of Payne in the
case of equivariant vector bundles). The action of the algebraic torus on $X$
lifts to the moduli space of all Gieseker stable sheaves on $X$ and we express
its fixed point locus explicitly in terms of moduli spaces of pure equivariant
sheaves on $X$. One of the problems arising is to find an equivariant line
bundle on the side of the GIT problem, which precisely recovers Gieseker
stability. In the case of torsion free equivariant sheaves, we can always
construct such equivariant line bundles. As a by-product, we get a
combinatorial description of the fixed point locus of the moduli space of
$\mu$-stable reflexive sheaves on $X$. As an application, we show in a sequel
how these methods can be used to compute generating functions of Euler
characteristics of moduli spaces of $\mu$-stable torsion free sheaves on
nonsingular complete toric surfaces.


  We classify twisted conjugacy classes of type D associated to the sporadic
simple groups. This is an important step in the program of the classification
of finite-dimensional pointed Hopf algebras with non-abelian coradical. As a
by-product we prove that every complex finite-dimensional pointed Hopf algebra
over the group of automorphisms of M12, J2, Suz, He, HN, T is the group
algebra. In the appendix we improve the study of conjugacy classes of type D in
sporadic simple groups.


  Following a problem posed by Lov\'asz in 1969, it is believed that every
connected vertex-transitive graph has a Hamilton path. This is shown here to be
true for cubic Cayley graphs arising from groups having a
$(2,s,3)$-presentation, that is, for groups $G=\la a,b| a^2=1, b^s=1, (ab)^3=1,
etc. \ra$ generated by an involution $a$ and an element $b$ of order $s\geq3$
such that their product $ab$ has order 3. More precisely, it is shown that the
Cayley graph $X=Cay(G,\{a,b,b^{-1}\})$ has a Hamilton cycle when $|G|$ (and
thus $s$) is congruent to 2 modulo 4, and has a long cycle missing only two
vertices (and thus necessarily a Hamilton path) when $|G|$ is congruent to 0
modulo 4.


  In this paper, we propose a workflow that uses Terrestrial Laser
Scanning(TLS) to semi-automatically monitor landslide and then test it in
practice. Firstly, several groups of TLS stations are set on different time to
collect the raw point cloud of the object mountain. Next, Hierarchical Merging
Based Multi-view (HMMR) registration algorithm is adapted to accomplish
single-phase multi-view registration.In order to analyze deformation between
multiple periods, Iterative Global Similarity Point (IGSP) algorithm is applied
to accomplish multiple-phase registration, which outperforms ICP in
experiments. Then the cloth simulation filtering (CSF) algorithm was used
together with manual post-processing to remove vegetation on the slope. After
that, the mountain slope's digital terrain model (DTM) is generated for each
period, and the distance between adjacent DTMs are calculated as the landslide
deformation mass. Furthermore, average deformation rate of the landslide
surface is calculated and analyzed.To validate the effectiveness of proposed
workflow, we uses the TLS data of five periods of the landslide in the Shanhou
village of northern Changshan Island from 2013 to 2015. The results indicate
that the method can obtain centimeter-level deformation monitoring accuracy
which can effectively monitor and analyze long-term landslide morphology and
trend as well as position the significant deformation area and determine the
type of landslide. In addition, the process can be automated to provide
end-to-end TLS based long-term landslide monitoring applications, providing
reference for monitoring and early warning of potential landslides.


  A magic square of order $n$ with all subsquares of possible orders
(ASMS$(n)$) is a magic square which contains a general magic square of each
order $k\in\{3, 4, \cdots, n-2\}$. Since the conjecture on the existence of an
ASMS was proposed in 1994, much attention has been paid but very little is
known except for few sporadic examples. A $k$-extended Langford sequence of
defect $d$ and length $m$ is equivalent to a partition of
$\{1,2,\cdots,2m+1\}\backslash\{k\}$ into differences $\{d,\cdots,d+m-1\}$. In
this paper, a construction of ASMS based on extended Langford sequence is
established. As a result, it is shown that there exists an ASMS$(n)$ for
$n\equiv\pm3\pmod{18}$, which gives a partial answer to Abe's conjecture on
ASMS.


  For two metric spaces $\mathbb X$ and $\mathcal Y$, the chromatic number
$\chi(\mathbb X;\mathcal Y)$ of $\mathbb X$ with forbidden $\mathcal Y$ is the
smallest $k$ such that there is a coloring of the points of $\mathbb X$ with
$k$ colors and no monochromatic copy of $\mathcal Y$. In this paper, we show
that for each finite metric space $\mathcal{M}$ that contains at least two
points the value $\chi\left(\mathbb R^n_\infty; \mathcal M \right)$ grows
exponentially with $n$. We also provide explicit lower and upper bounds for
some special $\mathcal M$.


  This paper describes a Dehn surgery approach to generating asymmetric
hyperbolic manifolds with two distinct lens space fillings. Such manifolds were
first identified
  in work of Dunfield-Hoffman-Licata as the result of a computer search of the
SnapPy census, but the current work establishes a topological framework for
constructing vastly many more such examples. We introduce the notion of a
``jointly primitive'' presentation of a knot and show that a refined version of
this condition ``longitudinally jointly primitive'' is equivalent to being
surgery dual to a $(1,2)$--knot in a lens space. This generalizes Berge's
equivalence between having a doubly primitive presentation and being surgery
dual to a $(1,1)$--knot in a lens space. Through surgery descriptions on a
seven-component link in $S^3$, we provide several explicit multi-parameter
infinite families of knots in lens spaces with longitudinal jointly primitive
presentations and observe among them all the examples previously seen in
Dunfield-Hoffman-Licata.


  Cytoskeletal motor proteins are involved in major intracellular transport
processes which are vital for maintaining appropriate cellular function. The
motor exhibits distinct states of motility: active motion along filaments, and
effectively stationary phase in which it detaches from the filaments and
performs passive diffusion in the vicinity of the detachment point due to
cytoplasmic crowding. The transition rates between motion and pause phases are
asymmetric in general, and considerably affected by changes in environmental
conditions which influences the efficiency of cargo delivery to specific
targets. By considering the motion of molecular motor on a single filament as
well as a dynamic filamentous network, we present an analytical model for the
dynamics of self-propelled particles which undergo frequent pause phases. The
interplay between motor processivity, structural properties of filamentous
network, and transition rates between the two states of motility drastically
changes the dynamics: multiple transitions between different types of anomalous
diffusive dynamics occur and the crossover time to the asymptotic diffusive or
ballistic motion varies by several orders of magnitude. We map out the phase
diagrams in the space of transition rates, and address the role of initial
conditions of motion on the resulting dynamics.


  We discuss a very naive but natural idea that time emerges as the holographic
dimension of gauge systems in euclidean space, which take statistic, e.g. Ising
model as concrete implementations. By identifying the renormalization group
flow of statistic models with the time flow of dual gravities, we get a
universe whose evolution history is qualitatively the same as our real world.
We comment highlights projected by this idea on the cosmological constant
problem and develop preliminary evidences for the validity of this idea.


  We demonstrate that the generalized Gell-Mann-Low theorem permits for a
systematic expansion around the nonrelativistic limit when applied to bound
states in the Wick-Cutkosky model, Yukawa theory, and QED (in Coulomb gauge).
We apply this expansion to obtain new results for the fine and hyperfine
structure of bound states in the cases of the Wick-Cutkosky model and Yukawa
theory, and reproduce correctly the fine and hyperfine structure of hydrogenic
systems.


  Accurate nuclear matrix elements (NMEs) for neutrinoless double beta decays
of candidate nuclei are important for the design and interpretation of future
experiments. Significant progress has been made in the modeling of these NMEs
from first principles. The NME for 48Ca shows a good agreement among three
different ab initio calculations starting from the same nuclear interaction
constructed within the chiral EFT and the same decay operator. These studies
open the door to ab initio calculations of the matrix elements for the decay of
heavier nuclei such as 76Ge, 130Te, and 136Xe. The ultimate goal is the
computation of NMEs in many-body calculations with controllable approximations,
using nuclear interactions and weak transition operators derived consistently
from chiral EFT. We are expecting more progress towards this goal in the near
future.


  The entanglement of the spin and orbital degrees of freedom through the
spin-orbit coupling has been actively studied in condensed matter physics. In
several iridium-oxide systems, the spin-orbital entangled state, identified by
the effective angular momentum $j_{\rm eff}$, can host novel quantum phases
with the help of electron correlations. Here, we show that a series of lacunar
spinel compounds, Ga$M_4X_8$ ($M$ = Nb, Mo, Ta, and W and $X$ = S, Se, and Te),
gives rise to a $\textit{molecular}$ $j_{\rm eff}$ state as a new spin-orbital
composite on which the low energy effective Hamiltonian is based. A wide range
of electron correlations is accessible by tuning the bandwidth under external
and/or chemical pressure, enabling us to investigate the interesting
cooperation between spin-orbit coupling and electron correlations. As
illustrative examples, a two-dimensional topological insulating phase and an
anisotropic spin Hamiltonian are investigated in the weak and strong coupling
regimes, respectively. Our finding can provide an ideal platform for exploring
$j_{\rm eff}$ physics and the resulting emergent phenomena.


  We analyze the constraints on coloured scalar bosons imposed by the current
LHC data at $\sqrt{s}=13$ TeV. Specifically, we consider an additional
electroweak doublet of colour-octet scalars, satisfying the principle of
Minimal Flavour Violation in order to fulfill the stringent experimental limits
on flavour-changing neutral currents. We demonstrate that coloured scalars with
masses below 800 GeV are already excluded, provided they are not fermiophobic.


  This paper proposes a new DC-AC converter with a less number of semiconductor
switches and therefore gate drive and control circuit components. A salient
feature of this inverter is its pure sinusoidal line-to-line voltages with no
need for output filter. Also, the proposed inverter improves the voltage
utilization factor of the input dc supply compared to four-switch three-phase
inverter (first best topology in the literature from the number of switches
point of view) and standard six-switch inverter with sine PWM. The proposed
inverter is capable of operating with a wide range of output voltages from zero
to the full value of the dc input voltage by appropriately altering
instantaneous duty-cycle. For the first time to our knowledge, in this paper, a
three-phase universal inverter with only three power-switch has been proposed.
For the purpose of providing a good compromise between fast transient response
and stability, a model predictive controller is proposed. All the design
expressions have been derived. A comparison with other DC-AC converters is
given to show the merits of the proposed converter. Finally, satisfactory
circuit operation is confirmed by experimental results from a laboratory
prototype.


  In this work we use matrix models to study the problem of strength
distributions. This is motivated by noticing near exponential fall offs of
strengths in calculated magnetic dipole excitations. We emphasize that the
quality of the exponential fall offs depend on the parameters in our matrices,
especially the relative size of the couplings to the unperturbed level
separations. We also find a matrix for which all transitions vanish.


  The canonical formalism of general relativity affords a particularly
interesting characterisation of the infamous hole argument. It also provides a
natural formalism in which to relate the hole argument to the problem of time
in classical and quantum gravity. In this paper, we examine the connection
between these two much discussed problems in the foundations of spacetime
theory along two interrelated lines. First, from a formal perspective, we
consider the extent to which the two problems can and cannot be precisely and
distinctly characterised. Second, from a philosophical perspective, we consider
the implications of various responses to the problems, with a particular focus
upon the viability of a `deflationary' attitude to the
relationalist/substantivalist debate regarding the ontology of spacetime.
Conceptual and formal inadequacies within the representative language of
canonical gravity will be shown to be at the heart of both the canonical hole
argument and the problem of time. Interesting and fruitful work at the
interface of physics and philosophy relates to the challenge of resolving such
inadequacies.


  We derive a local approximation for the correlation energy in two-dimensional
electronic systems. In the derivation we follow the scheme originally developed
by Colle and Salvetti for three dimensions, and consider a Gaussian
approximation for the pair density. Then, we introduce an ad-hoc modification
which better accounts for both the long-range correlation, and the
kinetic-energy contribution to the correlation energy. The resulting functional
is local, and depends parametrically on the number of electrons in the system.
We apply this functional to the homogeneous electron gas and to a set of
two-dimensional quantum dots covering a wide range of electron densities and
thus various amounts of correlation. In all test cases we find an excellent
agreement between our results and the exact correlation energies. Our
correlation functional has a form that is simple and straightforward to
implement, but broadly outperforms the commonly used local-density
approximation.


  Thermal face image analysis is favorable for certain circumstances. For
example, illumination-sensitive applications, like nighttime surveillance; and
privacy-preserving demanded access control. However, the inadequate study on
thermal face image analysis calls for attention in responding to the industry
requirements. Detecting facial landmark points are important for many face
analysis tasks, such as face recognition, 3D face reconstruction, and face
expression recognition. In this paper, we propose a robust neural network
enabled facial landmark detection, namely Deep Multi-Spectral Learning (DMSL).
Briefly, DMSL consists of two sub-models, i.e. face boundary detection, and
landmark coordinates detection. Such an architecture demonstrates the
capability of detecting the facial landmarks on both visible and thermal
images. Particularly, the proposed DMSL model is robust in facial landmark
detection where the face is partially occluded, or facing different directions.
The experiment conducted on Eurecom's visible and thermal paired database shows
the superior performance of DMSL over the state-of-the-art for thermal facial
landmark detection. In addition to that, we have annotated a thermal face
dataset with their respective facial landmark for the purpose of
experimentation.


  We present PICsar -- a new Particle in Cell code geared towards efficiently
simulating the magnetosphere of the aligned rotator. PICsar is a special
relativistic, electromagnetic, charge conservative code that can be used to
simulate arbitrary electromagnetics problems in axisymmetry. It features
stretchable body-fitted coordinates that follow the surface of a sphere,
simplifying the application of boundary conditions in the case of the aligned
rotator; a radiation absorbing outer boundary, which allows a steady state to
be set up dynamically and maintained indefinitely from transient initial
conditions; and algorithms for injection of charged particles into the
simulation domain. The code is parallelized using MPI and scales well to a
large number of processors. We discuss the numerical methods used in PICsar and
present tests of the code. In particular, we show that PICsar can accurately
and efficiently simulate the magnetosphere of the aligned monopole rotator in
the force free limit. We present simulations of the aligned dipole rotator in a
forthcoming paper.


  In this paper, we consider the initial-boundary value problem to the
nonhomogeneous incompressible Navier-Stokes equations. Local strong solutions
are established, for any initial data $(\rho_0, u_0)\in (W^{1,\gamma} \cap
L^\infty)\times H_{0,\sigma}^1$, with $\gamma>1$, and if $\gamma\geq2$, then
the strong solution is unique. The initial density is allowed to be
nonnegative, and in particular, the initial vacuum is allowed. The assumption
on the initial data is weaker than the previous widely used one that $(\rho_0,
u_0)\in (H^1 \cap L^\infty )\times(H_{0,\sigma}^1 \cap H^2)$, and no
compatibility condition is required.


  These notes accompany the open-source code published in GitHub which
implements a GPU-based line-segment, surface-triangle intersection algorithm in
CUDA. It mentions some relevant works and discusses issues specific to this
implementation. The goal is to provide software documentation and greater
clarity on collision buffer management which is sometimes omitted in online
literature. For real-world applications, CPU-based implementations of the test
are often deemed too slow to be useful. In contrast, the code described here
targets Nvidia GPU devices and offers a solution that is vastly more efficient
and scalable. The main API is also wrapped in Python. This geometry test is
applied in various engineering problems, so the software developed can be
reused in new situations.


  We present the results of a pencil-beam survey of the Kuiper Belt using the
Keck 10-m telescope. A single 0.01 square degree field is imaged 29 times for a
total integration time of 4.8 hr. Combining exposures in software allows the
detection of Kuiper Belt Objects (KBOs) having visual magnitude V < 27.9. Two
new KBOs are discovered. One object having V = 25.5 lies at a probable
heliocentric distance d = 33 AU. The second object at V = 27.2 is located at d
= 44 AU. Both KBOs have diameters of about 50 km, assuming comet-like albedos
of 4%.
  Data from all surveys are pooled to construct the luminosity function from
red magnitude R = 20 to 27. The cumulative number of objects per square degree,
N (< R), is fitted to a power law of the form log_(10) N = 0.52 (R - 23.5).
Differences between power laws reported in the literature are due mainly to
which survey data are incorporated, and not to the method of fitting. The
luminosity function is consistent with a power-law size distribution for
objects having diameters s = 50 to 500 km; dn ~ s^(-q) ds, where the
differential size index q = 3.6 +/- 0.1. The distribution is such that the
smallest objects possess most of the surface area, but the largest bodies
contain the bulk of the mass. Though our inferred size index nearly matches
that derived by Dohnanyi (1969), it is unknown whether catastrophic collisions
are responsible for shaping the size distribution. Implications of the absence
of detections of classical KBOs beyond 50 AU are discussed.


  Consider subcritical Bernoulli bond percolation with fixed parameter p<p_c.
We define a dependent site percolation model by the following procedure: for
each bond cluster, we colour all vertices in the cluster black with probability
r and white with probability 1-r, independently of each other. On the square
lattice, defining the critical probabilities for the site model and its dual,
r_c(p) and r_c^*(p) respectively, as usual, we prove that r_c(p)+r_c^*(p)=1 for
all subcritical p. On the triangular lattice, where our method also works, this
leads to r_c(p)=1/2, for all subcritical p. On both lattices, we obtain
exponential decay of cluster sizes below r_c(p), divergence of the mean cluster
size at r_c(p), and continuity of the percolation function in r on [0,1]. We
also discuss possible extensions of our results, and formulate some natural
conjectures. Our methods rely on duality considerations and on recent
extensions of the classical RSW theorem.


  Over the last years, Industrial Control Systems (ICS) have become
increasingly exposed to a wide range of cyber-physical threats. Efficient
models and techniques able to capture their complex structure and identify
critical cyber-physical components are therefore essential. AND/OR graphs have
proven very useful in this context as they are able to semantically grasp
intricate logical interdependencies among ICS components. However, identifying
critical nodes in AND/OR graphs is an NP-complete problem. In addition, ICS
settings normally involve various cyber and physical security measures that
simultaneously protect multiple ICS components in overlapping manners, which
makes this problem even harder. In this paper, we present an extended security
metric based on AND/OR hypergraphs which efficiently identifies the set of
critical ICS components and security measures that should be compromised, with
minimum cost (effort) for an attacker, in order to disrupt the operation of
vital ICS assets. Our approach relies on MAX-SAT techniques, which we have
incorporated in META4ICS, a Java-based security metric analyser for ICS. We
also provide a thorough performance evaluation that shows the feasibility of
our method. Finally, we illustrate our methodology through a case study in
which we analyse the security posture of a realistic Water Transport Network
(WTN).


  Accurate photometric redshifts for large samples of galaxies are among the
main products of modern multiband digital surveys. Over the last decade, the
Sloan Digital Sky Survey (SDSS) has become a sort of benchmark against which to
test the various methods. We present an application of a new method to the
estimation of photometric redshifts for the galaxies in the SDSS Data Release 9
(SDSS-DR9). Photometric redshifts for more than 143 million galaxies were
produced and made available at the URL:
http://dame.dsf.unina.it/catalog/DR9PHOTOZ/. The MLPQNA (Multi Layer Perceptron
with Quasi Newton Algorithm) model provided within the framework of the
DAMEWARE (DAta Mining and Exploration Web Application REsource) is an
interpolative method derived from machine learning models. The obtained
redshifts have an overall uncertainty of sigma=0.023 with a very small average
bias of about 3x10^-5, and a fraction of catastrophic outliers of about 5%.
This result is slightly better than what was already available in the
literature, particularly in terms of the smaller fraction of catastrophic
outliers.


  We introduce Thurstonian Boltzmann Machines (TBM), a unified architecture
that can naturally incorporate a wide range of data inputs at the same time.
Our motivation rests in the Thurstonian view that many discrete data types can
be considered as being generated from a subset of underlying latent continuous
variables, and in the observation that each realisation of a discrete type
imposes certain inequalities on those variables. Thus learning and inference in
TBM reduce to making sense of a set of inequalities. Our proposed TBM naturally
supports the following types: Gaussian, intervals, censored, binary,
categorical, muticategorical, ordinal, (in)-complete rank with and without
ties. We demonstrate the versatility and capacity of the proposed model on
three applications of very different natures; namely handwritten digit
recognition, collaborative filtering and complex social survey analysis.


  The Broad Histogram is a method allowing the direct calculation of the energy
degeneracy $g(E)$. This quantity is independent of thermodynamic concepts such
as thermal equilibrium. It only depends on the distribution of allowed (micro)
states along the energy axis, but not on the energy changes between the system
and its environment. Once one has obtained $g(E)$, no further effort is needed
in order to consider different environment conditions, for instance, different
temperatures, for the same system.
  The method is based on the exact relation between $g(E)$ and the
microcanonical averages of certain macroscopic quantities $N^{\rm up}$ and
$N^{\rm dn}$. For an application to a particular problem, one needs to choose
an adequate instrument in order to determine the averages $<N^{\rm up}(E)>$ and
$<N^{\rm dn}(E)>$, as functions of energy. Replacing the usual
fixed-temperature canonical by the fixed-energy microcanonical ensemble, new
subtle concepts emerge. The temperature, for instance, is no longer an external
parameter controlled by the user, all canonical averages being functions of
this parameter. Instead, the microcanonical temperature $T_{m}(E)$ is a
function of energy defined from $g(E)$ itself, being thus an {\bf internal}
(environment independent) characteristic of the system. Accordingly, all
microcanonical averages are functions of $E$.
  The present text is an overview of the method. Some features of the
microcanonical ensemble are also discussed, as well as some clues towards the
definition of efficient Monte Carlo microcanonical sampling rules.


  Let p be prime. A noncommutative p-solenoid is the C*-algebra of Z[1/p] x
Z[1/p] twisted by a multiplier of that group, where Z[1/p] is the additive
subgroup of the field Q of rational numbers whose denominators are powers of p.
In this paper, we survey our classification of these C*-algebras up to
*-isomorphism in terms of the multipliers on Z[1/p], using techniques from
noncommutative topology. Our work relies in part on writing these C*-algebras
as direct limits of rotation algebras, i.e. twisted group C*-algebras of the
group Z^2 thereby providing a mean for computing the K-theory of the
noncommutative solenoids, as well as the range of the trace on the K_0 groups.
We also establish a necessary and sufficient condition for the simplicity of
the noncommutative solenoids. Then, using the computation of the trace on K_0,
we discuss two different ways of constructing projective modules over the
noncommutative solenoids.


  Generation of optimal codes is a well known problem in coding theory. Many
computational approaches exist in the literature for finding record breaking
codes. However generating codes with long lengths $n$ using serial algorithms
is computationally very expensive, for example the worst case time complexity
of a Greedy algorithm is $\mathcal{O}(n\; 4^n)$. In order to improve the
efficiency of generating codes with long lengths, we propose and investigate
some parallel algorithms using General Purpose Graphic Processing Units
(GPGPU). This paper considers the implementation of parallel Greedy algorithm
using GPGPU-CUDA (Computed Unified Device Architecture) framework and discusses
various optimization techniques to accelerate the GPU code. The performance
achieved for optimized parallel implementations is more than two to three
orders of magnitude faster than that of serial implementation and shows a great
potential of GPGPU in the field of coding theory applications.


  We present an analytical method for determining the designability of protein
structures. We apply our method to the case of two-dimensional lattice
structures, and give a systematic solution for the spectrum of any structure.
Using this spectrum, the designability of a structure can be estimated. We
outline a heirarchy of structures, from most to least designable, and show that
this heirarchy depends on the potential that is used.


  The goal of this paper is to go further in the analysis of the behavior of
the number of descents in a random permutation. Via two different approaches
relying on a suitable martingale decomposition or on the Irwin-Hall
distribution, we prove that the number of descents satisfies a sharp large
deviation principle. A very precise concentration inequality involving the rate
function in the large deviation principle is also provided.


  We present a relativistic space-time diagram that displays in true magnitudes
the readings (daytimes) of two inertial reference frames clocks. One reference
frame is the rest frame for one clock. This diagram shows that two events
simultaneous in one reference frames are not compulsory simultaneous in the
other frame. This approach has a bi-dimensional character.


  We measure and study the evolution of the UV galaxy Luminosity Function (LF)
at z=3-5 from the largest high-redshift survey to date, the Deep part of the
CFHT Legacy Survey. We also give accurate estimates of the SFR density at these
redshifts. We consider ~100,000 Lyman-break galaxies at z~3.1, 3.8 & 4.8
selected from very deep ugriz images of this data set and estimate their
rest-frame 1600A luminosity function. Due to the large survey volume, cosmic
variance plays a negligible role. Furthermore, we measure the bright end of the
LF with unprecedented statistical accuracy. Contamination fractions from stars
and low-z galaxy interlopers are estimated from simulations. To correct for
incompleteness, we study the detection rate of simulated galaxies injected to
the images as a function of magnitude and redshift. We estimate the
contribution of several systematic effects in the analysis to test the
robustness of our results. We find the bright end of the LF of our u-dropout
sample to deviate significantly from a Schechter function. If we modify the
function by a recently proposed magnification model, the fit improves. For the
first time in an LBG sample, we can measure down to the density regime where
magnification affects the shape of the observed LF because of the very bright
and rare galaxies we are able to probe with this data set. We find an increase
in the normalisation, $\phi^{*}$, of the LF by a factor of 2.5 between z~5 and
z~3. The faint-end slope of the LF does not evolve significantly between z~5
and z~3. We do not find a significant evolution of the characteristic magnitude
in the studied redshift interval. The SFR density is found to increase by a
factor of ~2 from z~5 to z~4. The evolution from z~4 to z~3 is less eminent.


  The nested Kingman coalescent describes the dynamics of particles (called
genes) contained in larger components (called species), where pairs of species
coalesce at constant rate and pairs of genes coalesce at constant rate provided
they lie within the same species. We prove that starting from $rn$ species, the
empirical distribution of species masses (numbers of genes$/n$) at time $t/n$
converges as $n\to\infty$ to a solution of the deterministic
coagulation-transport equation $$
  \partial_t d \ = \ \partial_x ( \psi d ) \ + \ a(t)\left(d\star d - d
\right), $$ where $\psi(x) = cx^2$, $\star$ denotes convolution and $a(t)=
1/(t+\delta)$ with $\delta=2/r$. The most interesting case when $\delta =0$
corresponds to an infinite initial number of species. This equation describes
the evolution of the distribution of species of mass $x$, where pairs of
species can coalesce and each species' mass evolves like $\dot x = -\psi(x)$.
We provide two natural probabilistic solutions of the latter IPDE and address
in detail the case when $\delta=0$. The first solution is expressed in terms of
a branching particle system where particles carry masses behaving as
independent continuous-state branching processes. The second one is the law of
the solution to the following McKean-Vlasov equation $$ dx_t \ = \ - \psi(x_t)
\,dt \ + \ v_t\,\Delta J_t $$ where $J$ is an inhomogeneous Poisson process
with rate $1/(t+\delta)$ and $(v_t; t\geq0)$ is a sequence of independent rvs
such that $ {\mathcal L}(v_t) = {\mathcal L}(x_t)$. We show that there is a
unique solution to this equation and we construct this solution with the help
of a marked Brownian coalescent point process. When $\psi(x)=x^\gamma$, we show
the existence of a self-similar solution for the PDE which relates when
$\gamma=2$ to the speed of coming down from infinity of the nested Kingman
coalescent.


  The stabilization of steady state entanglement caused by action of a
classical driving field in the system of two-level atoms with the dipole
interaction accompanied by spontaneous emission is discussed. An exact solution
shows that the maximum amount of concurrence that can be achieved in Lamb-Dicke
limit is 0.43, which corresponds to the entanglement $\mathcal{E}_{max}=0.285$
ebit. Dependence of entanglement on interatomic distance and classical driving
field is examined numerically.


  With recent video object segmentation (VOS) benchmarks evolving to
challenging scenarios, we revisit a simple but overlooked strategy: restricting
the size of memory banks. This diverges from the prevalent practice of
expanding memory banks to accommodate extensive historical information. Our
specially designed "memory deciphering" study offers a pivotal insight
underpinning such a strategy: expanding memory banks, while seemingly
beneficial, actually increases the difficulty for VOS modules to decode
relevant features due to the confusion from redundant information. By
restricting memory banks to a limited number of essential frames, we achieve a
notable improvement in VOS accuracy. This process balances the importance and
freshness of frames to maintain an informative memory bank within a bounded
capacity. Additionally, restricted memory banks reduce the training-inference
discrepancy in memory lengths compared with continuous expansion. This fosters
new opportunities in temporal reasoning and enables us to introduce the
previously overlooked "temporal positional embedding." Finally, our insights
are embodied in "RMem" ("R" for restricted), a simple yet effective VOS
modification that excels at challenging VOS scenarios and establishes new state
of the art for object state changes (on the VOST dataset) and long videos (on
the Long Videos dataset). Our code and demo are available at
https://restricted-memory.github.io/.


  This paper addresses the growing demand for high-bandwidth wireless data
transmission by exploring Visible Light Communication (VLC) as an alternative
to Radio Frequency (RF) communication. In indoor scenarios, VLC systems utilize
existing lighting infrastructure for high-speed data transmission. To meet the
data rate demands of 5G and beyond, the paper proposes Non-Orthogonal Multiple
Access (NOMA) and introduces Empirical Fair Optical Power Allocation (EFOPA) to
simplify resource allocation in NOMA. EFOPA integrates NOMA with VLC, utilizing
the Artificial Bee Colony (ABC) optimization algorithm for offline resource
allocation planning. The approach then derives a simplified power allocation
equation from ABC outcomes, ensuring fair resource distribution among users.
EFOPA is compared against existing power allocation methods, demonstrating
superior fairness and reduced computational complexity. Numerical evaluations
reveal EFOPA consistently outperforms other methods across various channel
conditions, making it a robust and efficient solution for fair power allocation
in NOMA-VLC systems.


  A new approach to wavefunction collapse is prepared by an analysis of
semiclassical gravity. The fact that, in semiclassical gravity, superposed
states must share a common classical spacetime geometry, even if they prefer
(according to general relativity) differently curved spacetimes, leads to
energy increases of the states, when their mass distributions are different. If
one interprets these energy increases divided by Planck's constant as decay
rates of the states, one obtains the lifetimes of superpositions according to
the Diosi-Penrose criterion and reduction probabilities according to Born's
rule. The derivation of Born's rule for two-state superpositions can be adapted
to the typical quantum mechanical experiments with the help of a common
property of these experiments. It is that they lead to never more than two
different mass distributions at one location referring e.g. to the cases that a
particle "is", or "is not", detected at the location. From the characteristic
energy of the Diosi-Penrose criterion, an action is constructed whose
relativistic generalisation becomes obvious by a decomposition of the
Einstein-Hilbert action to the superposed states. In Part 2, semiclassical
gravity is enhanced to the so-called Dynamical Spacetime approach to
wavefunction collapse, which leads to a physical mechanism for collapse.


  The semihadronic tau decay width allows a clean extraction of the strong
coupling constant at low energies. We present a modification of the standard
"contour improved" method based on a derivative expansion of the Adler
function. The approach eliminates ambiguities coming from the existence of
different integral expressions for the semihadronic tau decay ratio. Compared
to the standard method, renormalization scale dependence is by more than a
factor two weaker in modified contour improved perturbation theory. The last
term of the expansion is reduced, and renormalization scheme dependence remains
approximately equal. The extracted QCD coupling at the tau mass scale is by
2$%$ lower than the "contour improved" value. We find
$\alpha_s(M_Z^2)=0.1211\pm 0.0010$.


  Materials following Murray's law are of significant interest due to their
unique porous structure and optimal mass transfer ability. However, it is
challenging to construct such biomimetic hierarchical channels with perfectly
cylindrical pores in synthetic systems following the existing theory. Achieving
superior mass transport capacity revealed by Murray's law in nanostructured
materials has thus far remained out of reach. We propose a Universal Murray's
law applicable to a wide range of hierarchical structures, shapes and
generalised transfer processes. We experimentally demonstrate optimal flow of
various fluids in hierarchically planar and tubular graphene aerogel structures
to validate the proposed law. By adjusting the macroscopic pores in such
aerogel-based gas sensors, we also show a significantly improved sensor
response dynamic. Our work provides a solid framework for designing synthetic
Murray materials with arbitrarily shaped channels for superior mass transfer
capabilities, with future implications in catalysis, sensing and energy
applications.


  Following recent Danish legislation promoting energy communities, we explore
how to enable these communities to provide grid services to distribution system
operators. In particular, we focus on "capacity limitation services", where we
propose a bilateral agreement in which an energy community is given reduced
grid import tariffs by setting a cap to its consumption level in certain hours.
This requires a coordination mechanism between the community manager and the
prosumers within the community. We enable this coordination by developing a
bilevel optimization model to be solved by the community manager, aiming to set
dynamic, i.e., time- and prosumer-differentiated, prices. This coordination
mechanism enabled by dynamic pricing ensures desirable market properties
including budget balance for the community manager and individual rationality
for prosumers, while encouraging (but not guaranteeing) a fair allocation of
collected benefits among prosumers.


  Starting from the continuum Dirac operator, I construct a renormalisation
group blocking which transforms the continuum action into a lattice action, and
I specifically consider the Wilson and overlap formalisms. For Wilson fermions
the inverse blocking is non-local and thus invalid. However, I proceed to
demonstrate that it is possible to construct a valid, local, blocking which,
though dependent on the lattice spacing, generates the lattice overlap fermion
action from the continuum action.
  Using this renormalisation group blocking for overlap fermions, I derive the
Ginsparg-Wilson equations and the lattice chiral symmetry. I suggest how the
construction of a lattice chiral gauge theory could follow naturally from this
approach.


  The phenomenon of arrest of an unstably-growing crack due to a curved weak
interface is investigated. The weak interface can produce the deviation of the
crack path, trapping the crack at the interface, leading to stable crack growth
for certain interface geometries. This idea could be used as a technical
solution for a new type of crack arrester, with a negligible impact on the
global stiffness, strength and weight of the structure. In order to exploit
this concept, an experimental campaign based on photo-elasticity and digital
image correlation is carried out, showing the capability of curved weak
interfaces to arrest cracks. The experiment is repeated for several geometrical
configurations through the modification of the interface curvature radii. The
phenomenon of crack deviation and subsequent arrest at the interface is also
investigated with the assistance of a computational model based on the finite
element method. The computational predictions provide the rationale for the
interpretation of the experimental observations, and distinguish between the
different behaviour of concave and convex interfaces. Consequently, as is shown
in the present study, the curved interface concept fosters new routes for the
attainment of structures with enhanced fracture resistance capacities, which
are of paramount importance for materials and components used in extreme
conditions.


  Photosynthetic starch reserves that accumulate in Arabidopsis leaves during
the day decrease approximately linearly with time at night to support
metabolism and growth. We find that the rate of decrease is adjusted to
accommodate variation in the time of onset of darkness and starch content, such
that reserves last almost precisely until dawn. Generation of these dynamics
therefore requires an arithmetic division computation between the starch
content and expected time to dawn. We introduce two novel chemical kinetic
models capable of implementing analog arithmetic division. Predictions from the
models are successfully tested in plants perturbed by a night-time light period
or by mutations in starch degradation pathways. Our experiments indicate which
components of the starch degradation apparatus may be important for appropriate
arithmetic division. Our results are potentially relevant for any biological
system dependent on a food reserve for survival over a predictable time period.