  We develop a procedure that transforms any asymptotically normal estimator
into an asymptotically normal estimator whose distribution is robust to
arbitrary data contamination. More generally, our procedure transforms any
estimator whose asymptotic distribution has positive and continuous density at
the origin into an asymptotically normal estimator whose distribution is robust
to arbitrary contamination. In developing such a procedure we prove new general
properties of componentwise and geometric quantiles in both finite and infinite
dimensions.


  Ecological theory predicts that the soil seed bank stabilises the composition
of annual plant communities in the face of environmental variability. However,
long-term data on the community dynamics in the seed bank and the standing
vegetation are needed to test this prediction. We tested the hypothesis that
the composition of the seed bank undergoes lower temporal variability than the
standing vegetation in a nine-year study in Mediterranean, semi-arid, and arid
ecosystems. The composition of the seed bank was estimated by collecting soil
cores from the studied sites on an annual basis. Seedling emergence under
optimal watering conditions was measured in each soil core for three
consecutive years, to account for seed dormancy. In all sites, the composition
of the seed bank differed from the vegetation throughout the years.
Small-seeded and dormant-seeded species had a higher frequency in the seed bank
than in the standing vegetation. In contrast, functional group membership
(grasses vs. forbs) did not explain differences in species frequency between
the seed bank and the vegetation after controlling for differences between
grasses and forbs in seed mass and seed dormancy. Contrary to predictions, the
magnitude of year-to-year variability (the mean compositional dissimilarity
between consecutive years) was not lower in the seed bank than in the
vegetation in all sites. However, long-term compositional trends in the seed
bank were weaker than in the vegetation in the Mediterranean and semi-arid
sites. In the arid site where year-to-year variability was highest, no
long-term trends were observed. Overall, the effect of the seed bank on the
temporal variability of the vegetation in annual communities depends on site
conditions and time scale. While the year-to-year variability of the seed bank
is similar to the vegetation, the soil seed bank can buffer long-term trends.


  In this paper we obtain the required spatial density of base stations (BSs)
in a coordinated multi-point uplink cellular network to meet a chosen quality
of service metric. Our model assumes cooperation amongst two BSs and the
required density is obtained under shadowing and Rayleigh fading for different
LTE-A path loss models. The proposed approach guarantees that the worst-case
achievable rate in the entire coverage region is above a target rate with
chosen probability. Two models for the position of the BSs are considered: a
hexagonal grid and a Poisson point process (PPP) modified to set a minimum cell
size. First, for each cooperation region, the location with the minimum rate
coverage probability - the worst-case point - is determined. Next, accurate
closed-form approximations are obtained for the worst-case rate coverage
probability. The approximations presented are useful for the quick assessment
of network performance and can be utilized in parametric studies for network
design. Here, they are applied to obtain the required density of BSs to achieve
a target rate coverage probability. As an added benefit, the formulation here
quantifies the penalty in moving from a regular BS deployment (the grid model)
to a random BS deployment (the PPP model).


  We consider a modified cosmological history in which the presence of
beyond-the-Standard-Model physics causes the weak gauge sector,
$\mathrm{SU}(2)_L$, to confine before it is Higgsed. Under the assumption of
chiral symmetry breaking, quark and lepton weak doublets form condensates that
break the global symmetries of the Standard Model, including baryon and lepton
number, down to a $\mathrm{U}(1)$ subgroup under which only the weak singlet
fermions and Higgs transform. The weakly-coupled gauge group $\mathrm{SU}(3)_c
\times \mathrm{U}(1)_Y$ is also broken to an $\mathrm{SU}(2)_c \times
\mathrm{U}(1)_Q$ gauge group. The light states include (pseudo-)Goldstone
bosons of the global symmetry breaking, mostly-elementary fermions primarily
composed of the weak singlet quarks and leptons, and the gauge bosons of the
weakly-coupled gauge group. We discuss possible signatures from early Universe
cosmology including gravitational wave radiation, topological defects, and
baryogenesis.


  Along with the breakthrough of convolutional neural networks, learning-based
segmentation has emerged in many research works. Most of them are based on
supervised learning, requiring plenty of annotated data; however, to support
segmentation, a label for each pixel is required, which is obviously expensive.
As a result, the issue of lacking annotated segmentation data commonly exists.
Continuous learning is a promising way to deal with this issue; however, it
still has high demands on human labor for annotation. What's more, privacy is
highly required in segmentation data for real-world applications, which further
calls for on-device learning. In this paper, we aim to resolve the above issue
in an alternative way: Instead of supervised segmentation, we propose to
develop efficient unsupervised segmentation that can be executed on edge
devices. Based on our observation that segmentation can obtain high performance
when pixels are mapped to a high-dimension space, we for the first time bring
brain-inspired hyperdimensional computing (HDC) to the segmentation task. We
build the HDC-based unsupervised segmentation framework, namely "SegHDC". In
SegHDC, we devise a novel encoding approach that follows the Manhattan
distance. A clustering algorithm is further developed on top of the encoded
high-dimension vectors to obtain segmentation results. Experimental results
show SegHDC can significantly surpass neural network-based unsupervised
segmentation. On a standard segmentation dataset, DSB2018, SegHDC can achieve a
28.0% improvement in Intersection over Union (IoU) score; meanwhile, it
achieves over 300x speedup on Raspberry PI. What's more, for a larger size
image in the BBBC005 dataset, the existing approach cannot be accommodated to
Raspberry PI due to out of memory; on the other hand, SegHDC can obtain
segmentation results within 3 minutes while achieving a 0.9587 IoU score.


  An efficient computational scheme devised for investigations of ground state
properties of the electronically correlated systems is presented. As an
example, $(H_{2})_{n}$ chain is considered with the long-range
electron-electron interactions taken into account. The implemented procedure
covers: (i) single-particle Wannier wave-function basis construction in the
correlated state, (ii) microscopic parameters calculation, and (iii) ground
state energy optimization. The optimization loop is based on highly effective
process-pool solution - specific root-workers approach. The hierarchical,
two-level parallelism was applied: both shared (by use of Open
Multi-Processing) and distributed (by use of Message Passing Interface) memory
models were utilized. We discuss in detail the feature that such approach
results in a substantial increase of the calculation speed reaching factor of
$300$ for the fully parallelized solution.


  At present, there exists no consensus in the astronomical community regarding
either the bulk composition or the formation mechanism for the interstellar
object 1I/2017 U1 ('Oumuamua). With the goal of assessing the merits of the
various scenarios that have been suggested to explain 'Oumuamua's appearance
and observed properties, we report a number of new analyses and provide an
up-to-date review of the current hypotheses. We consider the interpretations
that can reconcile 'Oumuamua's observed non-Keplerian trajectory with the
non-detection of traditional cometary volatiles. We examine the ability of
these proposed formation pathways to populate the galaxy with sufficient
interstellar objects such that the detection of 'Oumuamua by Pan-STARRS would
be statistically-favored. We consider two exotic ices, hydrogen and nitrogen,
showing that the frigid temperature requirement for the former and the
necessary formation efficiency of the latter pose serious difficulties for
these interpretations. Via order-of-magnitude arguments and hydrodynamical
cratering simulations, we show that impacts on extrasolar Kuiper Belt analogues
are not expected to generate N2 ice fragments as large as 'Oumuamua. In
addition, we discuss observational tests to confirm the presence of these ices
in future interstellar objects. Next, we examine the explanations that
attribute 'Oumuamua's properties to other compositions: ultra-porous dust
aggregates and thin membranes powered by solar radiation pressure, among
others. While none of these hypotheses are perfectly satisfactory, we make
predictions that will be testable by the Vera Rubin Observatory to resolve the
tension introduced by 'Oumuamua.


  The branchings fractions of the rare $B_s$ decays are calculated in the
framework of the QCD-motivated relativistic quark model. The form factors of
the weak $B_s$ transitions to light mesons are expressed through the overlap
integral of the initial and final meson wave functions in the whole accessible
kinematical range. Explicit determination of the momentum transfer dependence
of the form factors without additional model assumptions and extrapolations
significantly improve the reliability of the obtained results. The approximate
analytical form of the form factors is given in order to simplify the
comparison with other predictions and experiment. The calculated form factors
are applied for the investigations of the rare semileptonic, radiative and
nonleptonic $B_s$ decays. The factorization approximation is used for the
description of the nonleptonic decays. All results agree well with available
experimental data.


  We consider the dynamics of a separable Continuous Time Random Walk (CTRW)
when the random walker is biased by a velocity field in a uniformly growing
domain. Concrete examples for such domains include growing biological cells or
lipid vesicles, biofilms and tissues, but also macroscopic systems such as
expanding aquifers during rainy periods, or the expanding universe. The
considered CTRW can be subdiffusive, normal diffusive or superdiffusive,
including the particular case of a L\'evy flight. We first consider the case of
zero velocity field. In the subdiffusive case, we reveal an interesting time
dependence of the kurtosis of the particle probability density function. In
particular, for a suitable parameter choice, we find that the propagator, which
is fat tailed at short times, may cross over to a Gaussian-like propagator. We
subsequently incorporate the effect of the velocity field and derive a
bi-fractional diffusion-advection equation encoding the time evolution of the
particle distribution. We apply this equation to study the mixing kinetics of
two diffusing pulses, whose peaks move towards each other under the action of
velocity fields acting in opposite directions. This deterministic motion of the
peaks, together with the diffusive spreading of each pulse, tends to increase
particle mixing, thereby counteracting the peak separation induced by the
domain growth. As a result of this competition, different regimes of mixing
arise. In the case of L\'evy flights, apart from the non-mixing regime, one has
two different mixing regimes in the long-time limit, depending on the exact
parameter choice: In one of these regimes, mixing is mainly driven by diffusive
spreading, while in the other mixing is controlled by the velocity fields
acting on each pulse. Possible implications for encounter-controlled reactions
in real systems are discussed.


  In crowded settings, the human brain can focus on speech from a target
speaker, given prior knowledge of how they sound. We introduce a novel
intelligent hearable system that achieves this capability, enabling target
speech hearing to ignore all interfering speech and noise, but the target
speaker. A naive approach is to require a clean speech example to enroll the
target speaker. This is however not well aligned with the hearable application
domain since obtaining a clean example is challenging in real world scenarios,
creating a unique user interface problem. We present the first enrollment
interface where the wearer looks at the target speaker for a few seconds to
capture a single, short, highly noisy, binaural example of the target speaker.
This noisy example is used for enrollment and subsequent speech extraction in
the presence of interfering speakers and noise. Our system achieves a signal
quality improvement of 7.01 dB using less than 5 seconds of noisy enrollment
audio and can process 8 ms of audio chunks in 6.24 ms on an embedded CPU. Our
user studies demonstrate generalization to real-world static and mobile
speakers in previously unseen indoor and outdoor multipath environments.
Finally, our enrollment interface for noisy examples does not cause performance
degradation compared to clean examples, while being convenient and
user-friendly. Taking a step back, this paper takes an important step towards
enhancing the human auditory perception with artificial intelligence. We
provide code and data at: https://github.com/vb000/LookOnceToHear.


  Graham has shown in Z. Physik B 26, 397-405 (1977) that a
fluctuation-dissipation relation can be imposed on a class of non-equilibrium
Markovian Langevin equations that admit a stationary solution of the
corresponding Fokker-Planck equation. The resulting equilibrium form of the
Langevin equation is associated with a nonequilibrium Hamiltonian. Here we
provide some explicit insight into how this Hamiltonian may loose its time
reversal invariance and how the "reactive" and "dissipative" fluxes loose their
distinct time reversal symmetries. The antisymmetric coupling matrix between
forces and fluxes no longer originates from Poisson brackets and the "reactive"
fluxes contribute to the ("housekeeping") entropy production, in the steady
state. The time-reversal even and odd parts of the nonequilibrium Hamiltonian
contribute in qualitatively different but physically instructive ways to the
entropy. We find instances where fluctuations due to noise are solely
responsible for the dissipation. Finally, this structure gives rise to a new,
physically pertinent instance of frenesy.


  The effects of Poissonian resetting at a constant rate $r$ on the reaction
time between a Brownian particle and a stochastically gated target are studied.
The target switches between a reactive state and a non-reactive one. We
calculate the mean time at which the particle subject to resetting hits the
target for the first time, while the latter is in the reactive state. The
search time is minimum at a resetting rate that depends on the target
transition rates. When the target relaxation rate is much larger than both the
resetting rate and the inverse diffusion time, the system becomes equivalent to
a partially absorbing boundary problem. In other cases, however, the optimal
resetting rate can be a non-monotonic function of the target rates, a feature
not observed in partial absorption.
  We compute the relative fluctuations of the first hitting time around its
mean and compare our results with the ungated case. The usual universal
behavior of these fluctuations for resetting processes at their optimum breaks
down due to the target internal dynamics.


  We consider the evaluation of first-order queries over classes of databases
with bounded expansion. The notion of bounded expansion is fairly broad and
generalizes bounded degree, bounded treewidth and exclusion of at least one
minor. It was known that over a class of databases with bounded expansion,
first-order sentences could be evaluated in time linear in the size of the
database. We give a different proof of this result. Moreover, we show that
answers to first-order queries can be enumerated with constant delay after a
linear time preprocessing. We also show that counting the number of answers to
a query can be done in time linear in the size of the database.


  We extend the notion of quasi-transitive orientations of graphs to
2-edge-coloured graphs. By relating quasi-transitive $2$-edge-colourings to an
equivalence relation on the edge set of a graph, we classify those graphs that
admit a quasi-transitive $2$-edge-colouring. As a contrast to
Ghouil\'{a}-Houri's classification of quasi-transitively orientable graphs as
comparability graphs, we find quasi-transitively $2$-edge-colourable graphs do
not admit a forbiddden subgraph characterization. Restricting the problem to
comparability graphs, we show that the family of uniquely quasi-transitively
orientable comparability graphs is exactly the family of comparabilty graphs
that admit no quasi-transitive $2$-edge-colouring.


  We introduce an effective field theory (EFT) for conformal impurity by
considering a pair of transversely displaced impurities and integrating out
modes with mass inversely proportional to the separation distance. This EFT
captures the universal signature of the impurity seen by a heavy local
operator. We focus on the case of conformal boundaries and derive universal
formulas from this EFT for the boundary structure constants at high energy. We
point out that the more familiar thermal EFT for conformal field theory is a
special case of this EFT with distinguished conformal boundaries. We also
derive, for general conformal impurities, non-positivity and convexity-like
constraints on the Casimir energy which determines the leading EFT coefficient.


  We precisely determine the infrared (IR) length scale of the no-core shell
model (NCSM). In the NCSM, the $A$-body Hilbert space is truncated by the total
energy, and the IR length can be determined by equating the intrinsic kinetic
energy of $A$ nucleons in the NCSM space to that of $A$ nucleons in a
$3(A-1)$-dimensional hyper-radial well with a Dirichlet boundary condition for
the hyper radius. We demonstrate that this procedure indeed yields a very
precise IR length by performing large-scale NCSM calculations for $^{6}$Li. We
apply our result and perform accurate IR extrapolations for bound states of
$^{4}$He, $^{6}$He, $^{6}$Li, $^{7}$Li. We also attempt to extrapolate NCSM
results for $^{10}$B and $^{16}$O with bare interactions from chiral effective
field theory over tens of MeV.


  Dwarf spheroidal galaxies are among the most promising targets for detecting
signals of Dark Matter (DM) annihilations. The H.E.S.S. experiment has observed
five of these systems for a total of about 130 hours. The data are re-analyzed
here, and, in the absence of any detected signals, are interpreted in terms of
limits on the DM annihilation cross section. Two scenarios are considered: i)
DM annihilation into mono-energetic gamma-rays and ii) DM in the form of pure
WIMP multiplets that, annihilating into all electroweak bosons, produce a
distinctive gamma-ray spectral shape with a high-energy peak at the DM mass and
a lower-energy continuum. For case i), upper limits at 95\% confidence level of
about $\langle \sigma v \rangle \lesssim 3 \times 10^{-25}$ cm$^3$ s$^{-1}$ are
obtained in the mass range of 400 GeV to 1 TeV. For case ii), the full spectral
shape of the models is used and several excluded regions are identified, but
the thermal masses of the candidates are not robustly ruled out.


  The old question of rotational braking of Ap Si stars is revisited on the
empirical side, taking advantage of the recent Hipparcos results. Field stars
with various evolutionary states are considered, and it is shown that the loose
correlation between their rotational period and their surface gravity is
entirely compatible with conservation of angular momentum. No evidence is found
for any loss of angular momentum on the Main Sequence, which confirms earlier
results based on less reliable estimates of surface gravity.
  The importance of reliable, fundamental Teff determinations of Bp and Ap
stars is emphasized.


  This paper studies an optimal stopping problem for L\'evy processes. We give
a justification of the form of the Snell envelope using standard results of
optimal stopping. We also justify the convexity of the value function, and
without a priori restriction to a particular class of stopping times, we deduce
that the smallest optimal stopping time is necessarily a hitting time. We
propose a method which allows to obtain the optimal threshold. Moreover this
method allows to avoid long calculations of the integro-differential
operatorused in the usual proofs.


  Depletion forces play a role in the compaction and de-compation of
chromosomal material in simple cells but it remains debatable whether they are
sufficient to account for chromosomal collapse. We present coarse-grained
molecular dynamics simulations, which reveal that depletion-induced attraction
is sufficient to cause the collapse of a flexible chain of large structural
monomers immersed in a bath of smaller depletants. These simulations use an
explicit coarse-grained computational model that treats both the supercoiled
DNA structural monomers and the smaller protein crowding agents as
combinatorial, truncated Lennard-Jones spheres. By presenting a simple
theoretical model, we quantitatively cast the action of depletants on
supercoiled bacterial DNA as an effective solvent quality. The rapid collapse
of the simulated flexible chromosome at the predicted volume fraction of
depletants is a continous phase transition. Additional physical effects to such
simple chromosome models, such as enthalpic interactions between structural
monomers or chain rigidity, are required if the collapse is to be a first-order
phase transition.


  Length extrapolation has attracted considerable attention recently since it
allows transformers to be tested on longer sequences than those used in
training. Previous research has shown that this property can be attained by
using carefully designed Relative Positional Encodings (RPEs). While these
methods perform well on a variety of corpora, the conditions for length
extrapolation have yet to be investigated. This paper attempts to determine
what types of RPEs allow for length extrapolation through a thorough
mathematical and empirical analysis. We discover that a transformer is certain
to possess this property as long as the series that corresponds to the RPE's
exponential converges. Two practices are derived from the conditions and
examined in language modeling tasks on a variety of corpora. As a bonus from
the conditions, we derive a new Theoretical Receptive Field (TRF) to measure
the receptive field of RPEs without taking any training steps. Extensive
experiments are conducted on the Wikitext-103, Books, Github, and WikiBook
datasets to demonstrate the viability of our discovered conditions. We also
compare TRF to Empirical Receptive Field (ERF) across different models, showing
consistently matched trends on the aforementioned datasets. The code is
available at https://github.com/OpenNLPLab/Rpe.


  We show how the coherent oscillations of a nanomechanical resonator can be
entangled with a microwave cavity in the form of a superconducting coplanar
resonator. Dissipation is included and realistic values for experimental
parameters are estimated.


  Development of new, high quality functional materials has been at the
forefront of condensed matter research. The recent advent of two-dimensional
black phosphorus has greatly enriched the material base of two-dimensional
electron systems. Significant progress has been made to achieve high mobility
black phosphorus two-dimensional electron gas (2DEG) since the development of
the first black phosphorus field-effect transistors (FETs)$^{1-4}$. Here, we
reach a milestone in developing high quality black phosphorus 2DEG - the
observation of integer quantum Hall (QH) effect. We achieve high quality by
embedding the black phosphorus 2DEG in a van der Waals heterostructure close to
a graphite back gate; the graphite gate screens the impurity potential in the
2DEG, and brings the carrier Hall mobility up to 6000 $cm^{2}V^{-1}s^{-1}$. The
exceptional mobility enabled us, for the first time, to observe QH effect, and
to gain important information on the energetics of the spin-split Landau levels
in black phosphorus. Our results set the stage for further study on quantum
transport and device application in the ultrahigh mobility regime.


  Perfect state transfer in graphs is a concept arising from quantum physics
and quantum computing. Given a graph $G$ with adjacency matrix $A_G$, the
transition matrix of $G$ with respect to $A_G$ is defined as $H_{A_{G}}(t) =
\exp(-\mathrm{i}tA_{G})$, $t \in \mathbb{R},\ \mathrm{i}=\sqrt{-1}$. We say
that perfect state transfer from vertex $u$ to vertex $v$ occurs in $G$ at time
$\tau$ if $u \ne v$ and the modulus of the $(u,v)$-entry of $H_{A_G}(\tau)$ is
equal to $1$. If the moduli of all diagonal entries of $H_{A_G}(\tau)$ are
equal to $1$ for some $\tau$, then $G$ is called periodic with period $\tau$.
In this paper we give a few sufficient conditions for NEPS of complete graphs
to be periodic or exhibit perfect state transfer.


  We investigate the localized surface modes in a structure consisting of the
cholesteric liquid crystal layer, a phase plate, and a metal layer. These modes
are analogous to the optical Tamm states. The nonreciprocal transmission of
polarized light propagating in the forward and backward directions is
established. It is demonstrated that the transmission spectrum can be
controlled by external fields acting on the cholesteric liquid crystal and by
varying the plane of polarization of the incident light. [The text is presented
both in English (pp 1-9) and in Russian (pp 10-19)]


  Using non-relativistic effective field theory, we derive a three-particle
analog of the Lellouch-L\"uscher formula at the leading order. This formula
relates the three-particle decay amplitudes in a finite volume with their
infinite-volume counterparts and, hence, can be used to study the
three-particle decays on the lattice. The generalization of the approach to
higher orders is briefly discussed.


  We introduce and discuss a hybrid quantum-mechanics molecular-mechanics
(QM-MM) approach for Car-Parrinello DFT simulations with pseudopotentials and
planewaves basis, designed for the treatment of periodic systems. In this
implementation the MM atoms are considered as additional QM ions having
fractional charges of either sign, which provides conceptual and computational
simplicity by exploiting the machinery already existing in planewave codes to
deal with electrostatics in periodic boundary conditions. With this strategy,
both the QM and MM regions are contained in the same supercell, which
determines the periodicity for the whole system. Thus, while this method is not
meant to compete with non-periodic QM-MM schemes able to handle extremely large
but finite MM regions, it is shown that for periodic systems of a few hundred
atoms, our approach provides substantial savings in computational times by
treating classically a fraction of the particles. The performance and accuracy
of the method is assessed through the study of energetic, structural, and
dynamical aspects of the water dimer and of the aqueous bulk phase. Finally,
the QM-MM scheme is applied to the computation of the vibrational spectra of
water layers adsorbed at the TiO$_2$ anatase (101) solid-liquid interface. This
investigation suggests that the inclusion of a second monolayer of H$_2$O
molecules is sufficient to induce on the first adsorbed layer, a vibrational
dynamics similar to that taking place in the presence of an aqueous
environment. The present QM-MM scheme appears as a very interesting tool to
efficiently perform molecular dynamics simulations of complex condensed matter
systems, from solutions to nanoconfined fluids to different kind of interfaces.


  In this paper we demonstrate continuous noisy speech recognition using
connectionist temporal classification (CTC) model on limited Chinese vocabulary
using electroencephalography (EEG) features with no speech signal as input and
we further demonstrate single CTC model based continuous noisy speech
recognition on limited joint English and Chinese vocabulary using EEG features
with no speech signal as input. We demonstrate our results using various EEG
feature sets recently introduced in [1] as well as we propose a new deep
learning architecture in this paper which can perform continuous speech
recognition using raw EEG signals on limited joint English and Chinese
vocabulary.


  Text simplification refers to the process of increasing the comprehensibility
of texts. Automatic text simplification models are most commonly evaluated by
experts or crowdworkers instead of the primary target groups of simplified
texts, such as persons with intellectual disabilities. We conducted an
evaluation study of text comprehensibility including participants with and
without intellectual disabilities reading unsimplified, automatically and
manually simplified German texts on a tablet computer. We explored four
different approaches to measuring comprehensibility: multiple-choice
comprehension questions, perceived difficulty ratings, response time, and
reading speed. The results revealed significant variations in these
measurements, depending on the reader group and whether the text had undergone
automatic or manual simplification. For the target group of persons with
intellectual disabilities, comprehension questions emerged as the most reliable
measure, while analyzing reading speed provided valuable insights into
participants' reading behavior.


  We present porous electrode theory for capacitive deionization (CDI) with
electrodes containing nanoparticles that consist of a redox-active
intercalation material. A geometry of a desalination cell is considered which
consists of two porous electrodes, two flow channels and an anion-exchange
membrane, and we use Nernst-Planck theory to describe ion transport in the
aqueous phase in all these layers. A single-salt solution is considered, with
unequal diffusion coefficients for anions and cations. Similar to previous
models for CDI and electrodialysis, we solve the dynamic two-dimensional
equations by assuming that flow of water, and thus the advection of ions, is
zero in the electrode, and in the flow channel only occurs in the direction
along the electrode and membrane. In all layers, diffusion and migration are
only considered in the direction perpendicular to the flow of water. Electronic
as well as ionic transport limitations within the nanoparticles are neglected,
and instead the Frumkin isotherm (or regular solution model) is used to
describe local chemical equilibrium of cations between the nanoparticles and
the adjacent electrolyte, as a function of the electrode potential. Our model
describes the dynamics of key parameters of the CDI process with intercalation
electrodes, such as effluent salt concentration, the distribution of
intercalated ions, cell voltage, and energy consumption.


  Finding the solutions to a system of multivariate polynomial equations is a
fundamental problem in mathematics and computer science. It involves evaluating
the polynomials at many points, often chosen from a grid. In most current
methods, such as subdivision, homotopy continuation, or marching cube
algorithms, polynomial evaluation is treated as a black box, repeating the
process for each point. We propose a new approach that partially evaluates the
polynomials, allowing us to efficiently reuse computations across multiple
points in a grid. Our method leverages the Compressed Sparse Fiber data
structure to efficiently store and process subsets of grid points. We
integrated our amortized evaluation scheme into a subdivision algorithm.
Experimental results show that our approach is efficient in practice. Notably,
our software \texttt{voxelize} can successfully enclose curves defined by two
trivariate polynomial equations of degree $100$, a problem that was previously
intractable.


  Recent experimental and theoretical advancements have led to significant
progress in our understanding of the electromagnetic structure of nucleons
($N$), nucleon excitations ($N^\ast$), and other baryons. These breakthroughs
have been made possible by the capabilities of modern facilities, enabling the
induction of photo- and electro-excitation of nucleon resonances. Recent
experimental advances have sparked notable developments in theoretical
approaches. New theoretical methods have been tested and proven to be robust,
marking the beginning of a new era in our understanding on baryons. We present
a comprehensive review of progress in experimental data on $\gamma^\ast N \to
N^\ast$ reactions. Additionally, we discuss various analyses and theoretical
results. Some of these methods have matured in their predictive power, offering
new perspectives on exotic hadrons with multiquark components. We place special
emphasis on both the low-$Q^2$ and large-$Q^2$ regions to reinforce crucial
physical constraints on observables that hold in these limits. Furthermore, we
illustrate that the combination of lattice QCD with chiral effective field
theory and quark models, respectively, proves beneficial in interpreting data
and applying constraints within those different regimes. As a practical
contribution and for future reference, we review the formulas for helicity
amplitudes, multipole form factors and the relations between these two sets of
functions for transitions to resonances with general spin $J \geq \frac{1}{2}$.
These formulas are ubiquitous and play a pivotal role in experimental and
theoretical studies on baryon structure. Notably, the multipole transition form
factors for $J \ge \frac{3}{2}$ resonances serve as valuable tools to test
perturbative QCD results in the large-$Q^2$ region, thanks to the correlations
between electric and magnetic transition form factors.


  Neural Radiance Fields (NeRFs) are trained to minimize the rendering loss of
predicted viewpoints. However, the photometric loss often does not provide
enough information to disambiguate between different possible geometries
yielding the same image. Previous work has thus incorporated depth supervision
during NeRF training, leveraging dense predictions from pre-trained depth
networks as pseudo-ground truth. While these depth priors are assumed to be
perfect once filtered for noise, in practice, their accuracy is more
challenging to capture. This work proposes a novel approach to uncertainty in
depth priors for NeRF supervision. Instead of using custom-trained depth or
uncertainty priors, we use off-the-shelf pretrained diffusion models to predict
depth and capture uncertainty during the denoising process. Because we know
that depth priors are prone to errors, we propose to supervise the ray
termination distance distribution with Earth Mover's Distance instead of
enforcing the rendered depth to replicate the depth prior exactly through
L2-loss. Our depth-guided NeRF outperforms all baselines on standard depth
metrics by a large margin while maintaining performance on photometric
measures.


  We report the first experimental observation of quantum holographic imaging
with entangled photon pairs, generated in a spontaneous parametric
down-conversion process. The signal photons play both roles of "object wave"
and "reference wave" in holography but are recorded by a point detector
providing only encoding information, while the idler photons travel freely and
are locally manipulated with spatial resolution. The holographic image is
formed by the two-photon correlation measurement, although both the signal and
idler beams are incoherent. According to the detection regime of the signal
photons, we analyze three types of quantum holography schemes: point detection,
coherent detection and bucket detection, which can correspond to classical
holography using a point source, a plane-wave coherent source and a spatially
incoherent source, respectively. Our experiment demonstrates that the
two-photon holography in the point detection regime is equivalent to the
one-photon holography using a point source. Physically, the quantum holography
experiment verifies that a pair of non-commutable physical quantities, the
amplitude and phase components of the field operator, can be nonlocally
measured through two-photon entanglement.


  We give explicit formulas to compute most of the decomposition numbers of
reductions modulo 2 of irreducible spin representations of symmetric groups
indexed by partitions with at most 2 parts. In many of the still open cases
small upper bounds are found.


  By developing a molecular dynamics model of bacterial chemotaxis, we present
the first investigation of tracer statistics in bacterial suspensions where
chemotactic effects are considered. We demonstrate that the non-Gaussian
statistics of full-coated tracer arises from the athermal bacterial noise.
Moreover, Janus (half-coated) tracer performs a composite random walk combining
power-law-tail distributed L\'{e}vy flights with Brownian jiggling at low
coating concentration, but turns to an enhanced directional transport (EDT)
when coating concentration is high. Unlike conventional self-propelled
particles, upon increasing coating concentration, the direction of EDT
counterintuitively reverses from along to against the tracer orientation. Both
these transitions are identified to be second-order, with the phase boundaries
meeting at a triple point. A theoretical modeling that reveals the origin of
such anomalous transport behaviors is proposed. Our findings reveal the
fundamental nonequilibrium physics of active matter under external stimuli, and
underscore the crucial role of asymmetrical environment in regulating the
transport processes in biological systems.


  Manifold learning flows are a class of generative modelling techniques that
assume a low-dimensional manifold description of the data. The embedding of
such a manifold into the high-dimensional space of the data is achieved via
learnable invertible transformations. Therefore, once the manifold is properly
aligned via a reconstruction loss, the probability density is tractable on the
manifold and maximum likelihood can be used to optimize the network parameters.
Naturally, the lower-dimensional representation of the data requires an
injective-mapping. Recent approaches were able to enforce that the density
aligns with the modelled manifold, while efficiently calculating the density
volume-change term when embedding to the higher-dimensional space. However,
unless the injective-mapping is analytically predefined, the learned manifold
is not necessarily an efficient representation of the data. Namely, the latent
dimensions of such models frequently learn an entangled intrinsic basis, with
degenerate information being stored in each dimension. Alternatively, if a
locally orthogonal and/or sparse basis is to be learned, here coined canonical
intrinsic basis, it can serve in learning a more compact latent space
representation. Toward this end, we propose a canonical manifold learning flow
method, where a novel optimization objective enforces the transformation matrix
to have few prominent and non-degenerate basis functions. We demonstrate that
by minimizing the off-diagonal manifold metric elements $\ell_1$-norm, we can
achieve such a basis, which is simultaneously sparse and/or orthogonal.
Canonical manifold flow yields a more efficient use of the latent space,
automatically generating fewer prominent and distinct dimensions to represent
data, and a better approximation of target distributions than other manifold
flow methods in most experiments we conducted, resulting in lower FID scores.


  Attosecond pulses in the soft-X-ray (SXR) to water-window energy region offer
the tools for creating and studying target specific localized inner-shell
electrons or holes in materials, enable monitoring or controlling charge and
energy flows in a dynamic system on attosecond timescales. Recently, a number
of laboratories have reported generation of continuum harmonics in the
hundred-electron-volt to kilovolt region with few-cycle long-wavelength
mid-infrared lasers. These harmonics have the bandwidth to support pulses with
duration of few- to few-ten attoseconds. But harmonics generated in a gas
medium have attochirps that cannot be fully compensated by materials over a
broad spectral range; thus, realistically what are the typical shortest
attosecond pulses that one can generate? To answer this question, it is
essential that the temporal attosecond pulses be accurately characterized. By
re-analyzing the soft X-ray harmonics reported in three recent experiments
\cite{chang_natcom2017,Thomas_OE2017,Bieger_2017PRX} using a newly developed
broadband phase retrieval algorithm, we show that their generated attosecond
pulses are all longer than about 60 as. Since broadband pulses tend to have
high-order chirps away from the spectral center of the pulse, the algorithm has
to be able to retrieve accurately the phase over the whole bandwidth. Our
re-evaluated pulse durations are found to be longer than those previously
reported. We also introduce the autocorrelation (AC) of the streaking
spectrogram. By comparing the ACs from the experiments and from the retrieved
SXR pulses, the accuracy of the retrieved results can be directly visualized to
ensure that correct phases have been obtained. Our retrieval method is fast and
accurate, and it shall provide a powerful tool for the metrology of
few-ten-attosecond pulses in the future.


  We study the effect of phase slips in a quasi 1d superconducting channel
along which a current flows and report a new phenomenon where an avalanche of
phase slips occurs. This limits the critical current in thin films and wires
and drives the system to a topological phase transition at a temperature lower
than the bulk critical temperature. We describe the mechanism of such a
catastrophic phase slip avalanche and, following Kosterlitz and Thouless, we
use group renormalization techniques to derive an exact analytical expression
for the critical current as a function of film width and temperature. Our
results are in very good agreement with, and reproduce, the available
experimental data on superconducting MgB$_2$ thin films. The phenomenon we
describe is very general and can be used in the construction of new devices
where the superconducting state can coexist with the normal state.


  By recasting indirect inference estimation as a prediction rather than a
minimization and by using regularized regressions, we can bypass the three
major problems of estimation: selecting the summary statistics, defining the
distance function and minimizing it numerically. By substituting regression
with classification we can extend this approach to model selection as well. We
present three examples: a statistical fit, the parametrization of a simple real
business cycle model and heuristics selection in a fishery agent-based model.
The outcome is a method that automatically chooses summary statistics, weighs
them and use them to parametrize models without running any direct
minimization.


  We used the superconductors in the SuperCon database to construct element
vectors and then perform unsupervised learning of their critical temperatures
(T$_c$). Only the chemical composition of superconductors was used in this
procedure. No physical predictors (neither experimental nor computational) of
any kind were used. We achieved the coefficient of determination
R$^2$$\simeq$0.93, which is comparable and in some cases higher then similar
estimates using other artificial intelligence techniques. Based on this machine
learning model, we predicted several new superconductors with high critical
temperatures. We also discuss the factors that limit the learning process and
suggest possible ways to overcome them.


  A complete numerical solution of the evolution equation for parton
multiplicities in quark and gluon jets with initial conditions at threshold is
presented. Data on both hadron and jet multiplicities in e+e- annihilation are
well described with a common normalization, giving further support to the
picture of Local Parton Hadron Duality. Predictions for LEP-II energies are
presented. Furthermore we study the sensitivity to the cutoff parameter Q_0 and
the scale of alpha_s.


  We report on recent results on particle mixing and oscillations in quantum
field theory. We discuss the role played in cosmology by the vacuum condensate
induced by the neutrino mixing phenomenon. We show that it can contribute to
the dark energy of the universe.


  Rich galaxy clusters are powerful probes of both cosmological and galaxy
evolution parameters. The CNOC cluster survey was primarily designed to
distinguish between Omega=1 and Omega~0.2 cosmologies. Projected foreground and
background galaxies provide a field sample of comparable size. The results
strongly support a low-density universe. The luminous cluster galaxies are
about 10-30% fainter, depending on color, than the comparable field galaxies,
but otherwise they show a slow and nearly parallel evolution. On the average,
there is no excess star formation when galaxies fall into clusters. These data
provide the basis for a simple Lambda measurement using the survey's clusters
and the field data. The errors in Omega_M, Lambda, sigma_8 and galaxy evolution
parameters could be reduced to a few percent with a sample of a few hundred
clusters spread over the 0<z<1 range.


  Variable selection plays a fundamental role in high-dimensional data
analysis. Various methods have been developed for variable selection in recent
years. Well-known examples are forward stepwise regression (FSR) and least
angle regression (LARS), among others. These methods typically add variables
into the model one by one. For such selection procedures, it is crucial to find
a stopping criterion that controls model complexity. One of the most commonly
used techniques to this end is cross-validation (CV) which, in spite of its
popularity, has two major drawbacks: expensive computational cost and lack of
statistical interpretation. To overcome these drawbacks, we introduce a
flexible and efficient test-based variable selection approach that can be
incorporated into any sequential selection procedure. The test, which is on the
overall signal in the remaining inactive variables, is based on the maximal
absolute partial correlation between the inactive variables and the response
given active variables. We develop the asymptotic null distribution of the
proposed test statistic as the dimension tends to infinity uniformly in the
sample size. We also show that the test is consistent. With this test, at each
step of the selection, a new variable is included if and only if the $p$-value
is below some pre-defined level. Numerical studies show that the proposed
method delivers very competitive performance in terms of variable selection
accuracy and computational complexity compared to CV.


  Rapid developments in synthetic aperture (SA) systems, which generate a
larger aperture with greater angular resolution than is inherently possible
from the physical dimensions of a single sensor alone, are leading to novel
research avenues in several signal processing applications. The SAs may either
use a mechanical positioner to move an antenna through space or deploy a
distributed network of sensors. With the advent of new hardware technologies,
the SAs tend to be denser nowadays. The recent opening of higher frequency
bands has led to wide SA bandwidths. In general, new techniques and setups are
required to harness the potential of wide SAs in space and bandwidth. Herein,
we provide a brief overview of emerging signal processing trends in such
spatially and spectrally wideband SA systems. This guide is intended to aid
newcomers in navigating the most critical issues in SA analysis and further
supports the development of new theories in the field. In particular, we cover
the theoretical framework and practical underpinnings of wideband SA radar,
channel sounding, sonar, radiometry, and optical applications. Apart from the
classical SA applications, we also discuss the quantum electric-field-sensing
probes in SAs that are currently undergoing active research but remain at
nascent stages of development.


An elementary argument to show nonexistence.


  We prove that each measure $\mu$ in $R^4$ admits an equipartition by 4
hyperplanes, provided that it is symmetric with respect to a 2-dimensional,
affine subspace $L$ of $R^4$. Moreover we show, by computing the complete
obstruction in the relevant group of normal bordisms, that without the symmetry
condition, a naturally associated topological problem has a negative solution.
The computation is based on the Koschorke's exact singularity sequence and the
remarkable properties of the essentially unique, balanced binary Gray code in
dimension 4.


  The theory of interaction-based evolution argues that, at the most basic
level of analysis, there is a third alternative for how adaptive evolution
works besides a) accidental mutation and natural selection and b) Lamarckism,
namely, c) information provided by natural selection on the fit between the
organism and its environment is absorbed by non-accidental mutation. This
non-accidental mutation is non-Lamarckian yet useful for evolution, and is due
to evolved and continually evolving mutational mechanisms operating in the germ
cells. However, this theory has left a fundamental problem open: If mutational
mechanisms are not Lamarckian---if they are not "aware" of the environment and
the macroscale phenotype---then how could heritable novelty be due to anything
other than accidental mutation? This paper aims to address this question by
arguing the following. Mutational mechanisms can be broadly construed as
enacting local simplification operations on the DNA in germ cells, along with
gene duplication. The joint action of these mutational operations and natural
selection provides simplification under performance pressure. This joint action
creates from preexisting biological interactions new elements that have the
inherent capacity to come together into unexpected useful interactions with
other such elements, thus explaining nature's tendency for cooption. Novelty
thus arises not from a local genetic accident but from gradual network-level
evolution. Many empirical observations are explained from this perspective,
from cooption and gene fusion at the molecular level, to the evolution of
behavior and instinct at the organismal level. Finally, the nature of
mutational mechanisms and the need to study them in detail are described, and a
connection is drawn between evolution and learning.


  Integrating real-time, complex social signal processing into robotic systems
-- especially in real-world, multi-party interaction situations -- is a
challenge faced by many in the Human-Robot Interaction (HRI) community. The
difficulty is compounded by the lack of any standard model for human
representation that would facilitate the development and interoperability of
social perception components and pipelines. We introduce in this paper a set of
conventions and standard interfaces for HRI scenarios, designed to be used with
the Robot Operating System (ROS). It directly aims at promoting
interoperability and re-usability of core functionality between the many
HRI-related software tools, from skeleton tracking, to face recognition, to
natural language processing. Importantly, these interfaces are designed to be
relevant to a broad range of HRI applications, from high-level crowd
simulation, to group-level social interaction modelling, to detailed modelling
of human kinematics. We demonstrate these interface by providing a reference
pipeline implementation, packaged to be easily downloaded and evaluated by the
community.


  Surrogate risk minimization is an ubiquitous paradigm in supervised machine
learning, wherein a target problem is solved by minimizing a surrogate loss on
a dataset. Surrogate regret bounds, also called excess risk bounds, are a
common tool to prove generalization rates for surrogate risk minimization.
While surrogate regret bounds have been developed for certain classes of loss
functions, such as proper losses, general results are relatively sparse. We
provide two general results. The first gives a linear surrogate regret bound
for any polyhedral (piecewise-linear and convex) surrogate, meaning that
surrogate generalization rates translate directly to target rates. The second
shows that for sufficiently non-polyhedral surrogates, the regret bound is a
square root, meaning fast surrogate generalization rates translate to slow
rates for the target. Together, these results suggest polyhedral surrogates are
optimal in many cases.


  Mid-infrared spectrum can be recorded from almost any material making the
mid-infrared spectroscopy an extremely important and widely used sample
characterization and analytical technique. However, sensitivity photoconductive
detectors operate primarily in the near-infrared (NIR) but not in the
mid-infrared making the NIR more favorable for accurate spectral analysis.
Although absorption cross-section of vibrational modes in near-infrared is
orders of magnitude smaller compared to the fundamental vibrations in
mid-infrared, different concepts were proposed to increase the detectability of
weak molecular transitions overtones. Yet, the contribution of magneto-photonic
structures in near-infrared absorption effect has never been explored so far.
Here we propose high-Q magneto-photonic structures for a super-sensitive
detection of weak absorption resonances in near-infrared. We analyze the
contributions of both magnetic and non-magnetic photonic crystal (PC)
configurations to the detection of weak molecular transitions overtones. Our
results constitute an important step towards development of highly sensitive
spectroscopic tools based on high-Q magneto-photonic sensors.


  We have performed a precision atomic interferometry experiment on testing the
universality of free fall (UFF) considering atoms' spin degree of freedom. Our
experiment employs the Bragg atom interferometer with $^{87}$Rb atoms either in
hyperfine state $\left| {F = 1,{m_F} = 0} \right\rangle $ or $\left| {F =
2,{m_F} = 0} \right\rangle $, and the wave packets in these two states are
diffracted in one pair of Bragg beams alternatively, which can help suppress
the common-mode systematic errors. We have obtained an
E$\rm{\ddot{o}}$tv$\rm{\ddot{o}}$s ratio $\eta = \left( { 0.9 \pm 2.7} \right)
\times {10^{ - 10}}$, and set a new record on the precision with a nearly 5
times improvement. Our experiment gives stronger restrictions on the possible
UFF breaking mechanism.


  We use the very high resolution, fully cosmological simulations from the
Aquarius project, coupled to a semi-analytical model of galaxy formation, to
study the phase-space distribution of halo stars in "solar neighbourhood"-like
volumes. We find that this distribution is very rich in substructure in the
form of stellar streams for all five stellar haloes we have analysed. These
streams can be easily identified in velocity space, as well as in spaces of
pseudo-conserved quantities such as E vs. Lz. In our best-resolved local
volumes, the number of identified streams ranges from ~ 300 to 600, in very
good agreement with previous analytical predictions, even in the presence of
chaotic mixing. The fraction of particles linked to (massive) stellar streams
in these volumes can be as large as 84%. The number of identified streams is
found to decrease as a power-law with galactocentric radius. We show that the
strongest limitation to the quantification of substructure in our
poorest-resolved local volumes is particle resolution rather than strong
diffusion due to chaotic mixing.


  We consider viscosity solutions to nonlinear uniformly parabolic equations in
nondivergence form on a Riemannian manifold $M$, with the sectional curvature
bounded from below by $-\kappa$ for $\kappa\geq 0$. In the elliptic case, Wang
and Zhang \cite{WZ} recently extended the results of \cite{Ca} to nonlinear
elliptic equations in nondivergence form on such $M$, where they obtained the
Harnack inequality for classical solutions. We establish the Harnack inequality
for nonnegative {\it viscosity solutions} to nonlinear uniformly {\it parabolic
equations} in nondivergence form on $M$.
  The Harnack inequality of nonnegative viscosity solutions to the elliptic
equations is also proved.


  In a proof of the three gaps theorem, a class of permutations known as the
S\'{o}s permutations was introduced. It is known that a S\'{o}s permutation, as
a sequence, satisfies a certain recurrence (S\'{o}s's recurrence), however,
whether the converse holds remains unknown. On the other hand, the inverses of
S\'{o}s permutations have been studied also. It has been reported that such a
permutation satisfies a congruential recurrence as a sequence. The converse
problem of this fact, i.e., whether a permutation satisfying the congruential
recurrence is the inverse of a S\'{o}s permutation, is also unsolved, except
for a finite number of the degrees of the permutations. This paper relates the
set of permutations satisfying the congruential recurrence to other sets of
permutations and gives upper bounds for their cardinalities. The upper bounds
are in fact tight. In particular, the set of permutations satisfying the
congruential recurrence has the same cardinality as that of S\'{o}s
permutations, giving the affirmative answer to the above unsolved problem as a
corollary. As another corollary, it is shown that all permutation, which is
regarded as a congruential quasi-progression of diameter 1 in that the set
formed by the first order differences modulo the degree of the permutation is a
singleton or a set of two successive integers, is the inverse of a S\'{o}s
permutation with an elementary operation called as shift applied. As an
application of these facts, we present a procedure that lifts the set of the
inverses of the S\'{o}s permutations of a given degree to the set of the same
kind with the degree increased by one, without referring to the underlying
parameters defining the S\'{o}s permutations or the Farey sequence associated
to them.


  Modern society's reliance on power systems is at risk from the escalating
effects of wind-related climate change. Yet, failure to identify the intricate
relationship between wind-related climate risks and power systems could lead to
serious short- and long-term issues, including partial or complete blackouts.
Here, we develop a comprehensive framework to assess China's power system
resilience across various climate change scenarios, enabling a holistic
evaluation of the repercussions induced by wind-related climate change. Our
findings indicate that China's current wind projects and planning strategies
could be jeopardized by wind-related climate change, with up to a 12\% decline
in regional wind power availability. Moreover, our results underscore a
pronounced vulnerability of power system resilience amidst the rigors of
hastened climate change, unveiling a potential amplification of resilience
deterioration, even approaching fourfold by 2060 under the most severe
scenario, relative to the 2020 benchmark. This work advocates for strategic
financial deployment within the power sector aimed at climate adaptation,
enhancing power system resilience to avert profound losses from long-term,
wind-influenced climatic fluctuations.


  Recommender systems have been investigated for many years, with the aim of
generating the most accurate recommendations possible. However, available data
about new users is often insufficient, leading to inaccurate recommendations;
an issue that is known as the cold-start problem. A solution can be active
learning. Active learning strategies proactively select items and ask users to
rate these. This way, detailed user preferences can be acquired and as a
result, more accurate recommendations can be offered to the user. In this
study, we compare five active learning algorithms, combined with three
different predictor algorithms, which are used to estimate to what extent the
user would like the item that is asked to rate. In addition, two modes are
tested for selecting the items: batch mode (all items at once), and sequential
mode (the items one by one). Evaluation of the recommender in terms of rating
prediction, decision support, and the ranking of items, showed that sequential
mode produces the most accurate recommendations for dense data sets.
Differences between the active learning algorithms are small. For most active
learners, the best predictor turned out to be FunkSVD in combination with
sequential mode.


  Phototaxis is an important reaction to light displayed by a wide range of
motile microorganisms. Flagellated eukaryotic microalgae in particular, like
the model organism Chlamydomonas reinhardtii, steer either towards or away from
light by a rapid and precisely timed modulation of their flagellar activity.
Cell steering, however, is only the beginning of a much longer process which
ultimately allows cells to determine their light exposure history. This process
is not well understood. Here we present a first quantitative study of the long
timescale phototactic motility of Chlamydomonas at both single cell and
population levels. Our results reveal that the phototactic strategy adopted by
these microorganisms leads to an efficient exposure to light, and that the
phototactic response is modulated over typical timescales of tens of seconds.
The adaptation dynamics for phototaxis and chlorophyll fluorescence show a
striking quantitative agreement, suggesting that photosynthesis controls
quantitatively how cells navigate a light field.


  We consider quadratic three-dimensional differential systems having a Hopf
singular point. We study the cyclicity when the singular point is a center on
the center manifold using higher order developments of the Lyapunov constants.
As a result, we make a chart of the cyclicity by establishing the lower bounds
for several known systems in the literature, among them the Rossler, Lorenz and
Moon-Rand systems. Moreover, we obtain an example of a jerk system for which is
possible to bifurcate 12 limit-cycles from the center, which is a new lower
bound for three-dimensional quadratic systems.


  The completion of Run 1 of the CERN Large Hadron Collider has seen the
discovery of the Higgs boson and an unprecedented number of precise
measurements of the Standard Model, while Run 2 operation has just started to
provide first data at higher energy. Upgrades of the LHC to high luminosity
(HL-LHC) and the experiments (ATLAS, CMS, ALICE and LHCb) will exploit the full
potential of the collider to discover and explore new physics beyond the
Standard Model. In this article, the experimental challenges and the physics
opportunities in proton-proton collisions at the HL-LHC are reviewed.


  We consider singular integrals associated to a classical Calder\'on-Zygmund
kernel $K$ and a hypersurface given by the graph of $\varphi(\psi(t))$ where
$\varphi$ is an arbitrary $C^1$ function and $\psi$ is a smooth convex function
of finite type. We give a characterization of those Calder\'on-Zygmund kernels
$K$ and convex functions $\psi$ so that the associated singular integral
operator is bounded on $L^2$ for all $C^1$ functions $\varphi$.


  The first detected gravitational wave from a neutron star merger was
GW170817. In this study, we present J-GEM follow-up observations of SSS17a, an
electromagnetic counterpart of GW170817. SSS17a shows a 2.5-mag decline in the
$z$-band from 1.7 days to 7.7 days after the merger. Such a rapid decline is
not comparable with supernovae light curves at any epoch. The color of SSS17a
also evolves rapidly and becomes redder for later epochs; the $z-H$ color
changed by approximately 2.5 mag in the period of 0.7 days to 7.7 days. The
rapid evolution of both the optical brightness and the color are consistent
with the expected properties of a kilonova that is powered by the radioactive
decay of newly synthesized $r$-process nuclei. Kilonova models with Lanthanide
elements can reproduce the aforementioned observed properties well, which
suggests that $r$-process nucleosynthesis beyond the second peak takes place in
SSS17a. However, the absolute magnitude of SSS17a is brighter than the expected
brightness of the kilonova models with the ejecta mass of 0.01 $\Msun$, which
suggests a more intense mass ejection ($\sim 0.03 \Msun$) or possibly an
additional energy source.


  Let $R=k[x_1,...,x_n]$ be the polynomial ring in $n$ variables over a field
$k$ and $I$ be a matroidal ideal of degree $d$. In this paper, we study the
unmixedness properties and the arithmetical rank of $I$. Moreover, we show that
$ara(I)=n-d+1$. This answer to the conjecture that made by H. J. Chiang-Hsieh
\cite[Conjecture]{C}.


  This article presents an empirical investigation into the determinants of
total revenue generated by counterfeit tokens on Uniswap. It offers a detailed
overview of the counterfeit token fraud process, along with a systematic
summary of characteristics associated with such fraudulent activities observed
in Uniswap. The study primarily examines the relationship between revenue from
counterfeit token scams and their defining characteristics, and analyzes the
influence of market economic factors such as return on market capitalization
and price return on Ethereum. Key findings include a significant increase in
overall transactions of counterfeit tokens on their first day of fraud, and a
rise in upfront fraud costs leading to corresponding increases in revenue.
Furthermore, a negative correlation is identified between the total revenue of
counterfeit tokens and the volatility of Ethereum market capitalization return,
while price return volatility on Ethereum is found to have a positive impact on
counterfeit token revenue, albeit requiring further investigation for a
comprehensive understanding. Additionally, the number of subscribers for the
real token correlates positively with the realized volume of scam tokens,
indicating that a larger community following the legitimate token may
inadvertently contribute to the visibility and success of counterfeit tokens.
Conversely, the number of Telegram subscribers exhibits a negative impact on
the realized volume of scam tokens, suggesting that a higher level of scrutiny
or awareness within Telegram communities may act as a deterrent to fraudulent
activities. Finally, the timing of when the scam token is introduced on the
Ethereum blockchain may have a negative impact on its success. Notably, the
cumulative amount scammed by only 42 counterfeit tokens amounted to almost
11214 Ether.


  Coronal loops trace out bipolar, arch-like magnetic fields above the Sun's
surface. Recent measurements that combine rotational tomography, extreme
ultraviolet imaging, and potential-field extrapolation have shown the existence
of large loops with inverted temperature profiles; i.e., loops for which the
apex temperature is a local minimum, not a maximum. These "down loops" appear
to exist primarily in equatorial quiet regions near solar minimum. We simulate
both these and the more prevalent large-scale "up loops" by modeling coronal
heating as a time-steady superposition of: (1) dissipation of incompressible
Alfven-wave turbulence, and (2) dissipation of compressive waves formed by mode
conversion from the initial population of Alfven waves. We found that when a
large percentage (> 99%) of the Alfven waves undergo this conversion, heating
is greatly concentrated at the footpoints and stable "down loops" are created.
In some cases we found loops with three maxima that are also gravitationally
stable. Models that agree with the tomographic temperature data exhibit higher
gas pressures for "down loops" than for "up loops," which is consistent with
observations. These models also show a narrow range of Alfven wave amplitudes:
3 to 6 km/s at the coronal base. This is low in comparison to typical observed
amplitudes of 20 to 30 km/s in bright X-ray loops. However, the large-scale
loops we model are believed to comprise a weaker diffuse background that fills
much of the volume of the corona. By constraining the physics of loops that
underlie quiescent streamers, we hope to better understand the formation of the
slow solar wind.


  Distributed architectures are used to improve performance and reliability of
various systems. Examples include drone swarms and load-balancing servers. An
important capability of a distributed architecture is the ability to reach
consensus among all its nodes. Several consensus algorithms have been proposed,
and many of these algorithms come with intricate proofs of correctness, that
are not mechanically checked. In the controls community, algorithms often
achieve consensus asymptotically, e.g., for problems such as the design of
human control systems, or the analysis of natural systems like bird flocking.
This is in contrast to exact consensus algorithm such as Paxos, which have
received much more recent attention in the formal methods community.
  This paper presents the first formal proof of an asymptotic consensus
algorithm, and addresses various challenges in its formalization. Using the Coq
proof assistant, we verify the correctness of a widely used consensus algorithm
in the distributed controls community, the Weighted-Mean Subsequence Reduced
(W-MSR) algorithm. We formalize the necessary and sufficient conditions
required to achieve resilient asymptotic consensus under the assumed attacker
model. During the formalization, we clarify several imprecisions in the paper
proof, including an imprecision on quantifiers in the main theorem.


  The extensive experimental and computational search for multifunctional
materials has resulted in the development of semiconductor and oxide systems,
such as (Ga,Mn)N, (Zn,Cr)Te, and HfO2, which exhibit surprisingly stable
ferromagnetic signatures despite having a small or nominally zero concentration
of magnetic elements. Here, we show that the ferromagnetism of (Zn,Cr)Te, and
the associated magnetooptical and magnetotransport functionalities, are
dominated by the formation of Cr-rich (Zn,Cr)Te metallic nanocrystals embedded
in the Cr-poor (Zn,Cr)Te matrix. Importantly, the formation of these
nanocrystals can be controlled by manipulating the charge state of Cr ions
during the epitaxy. The findings provide insight into the origin of
ferromagnetism in a broad range of semiconductors and oxides, and indicate
possible functionalities of these composite systems. Furthermore, they
demonstrate a bottom-up method for self-organized nanostructure fabrication
that is applicable to any system in which the charge state of a constituent
depends on the Fermi-level position in the host semiconductor.


  By using the series expansion techniques, we study the excitation spectrum
for the two-dimensional quantum spin systems with ladder, plaquette and
mixed-spin structures. We calculate the spin excitation gap and thus determine
the phase boundary between the spin-gap phase and the magnetically ordered
phase rather precisely. It is found that the phase diagram obtained improves
fairly well the one previously obtained via the ground-state susceptibility.


  Doping of strongly layered ionic oxides is an established paradigm for
creating novel electronic behavior. This is nowhere more apparent than in
superconductivity, where doping gives rise to high temperature
superconductivity in cuprates (hole-doped) and to surprisingly high Tc in HfNCl
(Tc=25.5K, electron-doped). First principles calculations of hole-doping of the
layered delafossite CuAlO2 reveal unexpectedly large doping-induced shifts in
spectral density, strongly in opposition to the rigid band picture that is
widely used as an accepted guideline. These spectral shifts, of similar origin
as the charge transfer used to produce negative electron affinity surfaces and
adjust Schottky barrier heights, drastically alter the character of the Fermi
level carriers, leading in this material to an O-Cu-O molecule-based carrier
(or polaron, at low doping) rather than a nearly pure-Cu hole as in a rigid
band picture. First principles linear response electron-phonon coupling (EPC)
calculations reveal, as a consequence, net weak EPC and no superconductivity
rather than the high Tc obtained previously using rigid band expectations.
These specifically two-dimensional dipole-layer driven spectral shifts provides
new insights into materials design in layered materials foe functionalities
besides superconductivity.


  Connected and cooperative driving requires precise calibration of the
roadside infrastructure for having a reliable perception system. To solve this
requirement in an automated manner, we present a robust extrinsic calibration
method for automated geo-referenced camera calibration. Our method requires a
calibration vehicle equipped with a combined GNSS/RTK receiver and an inertial
measurement unit (IMU) for self-localization. In order to remove any
requirements for the target's appearance and the local traffic conditions, we
propose a novel approach using hypothesis filtering. Our method does not
require any human interaction with the information recorded by both the
infrastructure and the vehicle. Furthermore, we do not limit road access for
other road users during calibration. We demonstrate the feasibility and
accuracy of our approach by evaluating our approach on synthetic datasets as
well as a real-world connected intersection, and deploying the calibration on
real infrastructure. Our source code is publicly available.


  Infinite sets of asymptotic soft-charges were recently shown to be related to
new symmetries of the $S$-matrix, spurring a large amount of research on this
and related questions. Notwithstanding, the raison-d'\^etre of these
soft-charges rests on less firm ground, insofar as their known derivations
through generalized Noether procedures tend to rely on the fixing of
(gauge-breaking) boundary conditions rather than on manifestly gauge-invariant
computations. In this article, we show that a geometrical framework anchored in
the space of field configurations singles out the known leading-order soft
charges in gauge theories. Our framework unifies the treatment of finite and
infinite regions, and thus it explains why the infinite enhancement of the
symmetry group is a property of asymptotic null infinity and should not be
expected to hold within finite regions, where at most a finite number of
physical charges -- corresponding to the reducibility parameters of the
quasi-local field configuration -- is singled out. As a bonus, our formalism
also suggests a simple proposal for the origin of magnetic-type charges at
asymptotic infinity based on spacetime (Lorentz) covariance rather than
electromagnetic duality.


  Lattice regularizations are pivotal in the non-perturbative quantization of
gauge field theories. Wilson's proposal to employ group-valued link fields
simplifies the regularization of gauge fields in principal fiber bundles,
preserving gauge symmetry within the discretized lattice theory. Maintaining
gauge symmetry is desirable as its violation can introduce unwanted degrees of
freedom. However, not all theories with gauge symmetries admit gauge-invariant
lattice regularizations, as observed in general relativity where the
diffeomorphism group serves as the gauge symmetry. In such cases, gauge
symmetry-breaking regularizations become necessary. In this paper, we argue
that a broken lattice gauge symmetry is acceptable as long as gauge symmetry is
restored in the continuum limit. We propose a method to construct the continuum
limit for a class of lattice-regularized Hamiltonian field theories, where the
regularization breaks the Lie algebra of first-class constraints. Additionally,
we offer an approach to represent the exact gauge group on the Hilbert space of
the continuum theory. The considered class of theories is limited to those with
first-class constraints linear in momenta, excluding the entire gauge group of
general relativity but encompassing its subgroup of spatial diffeomorphisms. We
discuss potential techniques for extending this quantization to the full gauge
group.


  Protection of silver mirror stacks from environmental degradation before
launching is crucial for space applications. Hereby, we report a comparative
study of the advanced protection of silver mirror stacks for space telescopes
provided by SiO2 and Al2O3 coatings in conditions of accelerated aging by
sulfidation. The model silver stack samples were deposited by cathodic
magnetron sputtering on a reference silica substrate for optical applications
and a surface-pretreated SiC substrate. Accelerated aging was performed in dry
and more severe wet conditions. Optical micrographic observations, surface and
interface analysis by Time-of Flight Secondary Ion Mass Spectrometry (ToF-SIMS)
and reflectivity measurements were combined to comparatively study the effects
of degradation. The results show a lower kinetics of degradation by accelerated
aging of the stacks protected by the alumina coating in comparable test
conditions.


  Quantum formulas, defined by Yao [FOCS '93], are the quantum analogs of
classical formulas, i.e., classical circuits in which all gates have fanout
one. We show that any read-once quantum formula over a gate set that contains
all single-qubit gates is equivalent to a read-once classical formula of the
same size and depth over an analogous classical gate set. For example, any
read-once quantum formula over Toffoli and single-qubit gates is equivalent to
a read-once classical formula over Toffoli and NOT gates. We then show that the
equivalence does not hold if the read-once restriction is removed. To show the
power of quantum formulas without the read-once restriction, we define a new
model of computation called the one-qubit model and show that it can compute
all boolean functions. This model may also be of independent interest.


  This thesis introduces the sequence to sequence model with Luong's attention
mechanism for end-to-end ASR. It also describes various neural network
algorithms including Batch normalization, Dropout and Residual network which
constitute the convolutional attention-based seq2seq neural network. Finally
the proposed model proved its effectiveness for speech recognition achieving
15.8% phoneme error rate on TIMIT dataset.


  These lectures provide an introduction to perturbative string theory and its
construction on spaces with background Ramond flux. Traditional covariant
quantization of the string and its connection with vertex operators and
conformal invariance of the worldsheet theory are reviewed. A supersymmetric
covariant quantization of the superstring in six and ten spacetime dimensions
is discussed. Correlation functions are computed with these variables.
Applications to strings in anti-de Sitter backgrounds with Ramond flux are
analyzed. Based on lectures presented at the Theoretical Advanced Study
Institute TASI 2001, June 3-29, 2001.


  A plausible explanation for the existence of additional light sterile
neutrinos is that they correspond to modulini, fermionic partners of moduli,
which propagate in new large dimensions. We discuss the phenomenological
implications of such states and show that solar neutrino oscillation is well
described by small angle MSW oscillation to the tower of Kaluza Klein states
associated with the modulini. In the optimal case the recoil electron energy
spectrum agrees precisely with the measured one, in contrast to the single
sterile neutrino case which is disfavoured. We also consider how all
oscillation phenomena can be explained in a model including bulk neutrino
states. In particular, we show that a naturally maximal mixing for atmospheric
neutrinos can be easily obtained.


  Divide a deck of $kn$ cards into $k$ equal piles and place them from left to
right. The standard shuffle $\sigma$ is performed by picking up the top cards
one by one from left to right and repeating until all cards have been picked
up. For every permutation $\tau$ of the $k$ piles, use $\rho_{\tau}$ to denote
the induced permutation on the $kn$ cards. The shuffle group $G_{k,kn}$ is
generated by $\sigma$ and the $k!$ permutations $\rho_{\tau}$. It was
conjectured by Cohen et al in 2005 that the shuffle group $G_{k,kn}$ contains
$A_{kn}$ if $k\geq3$, $(k,n)\ne\{4,2^f\}$ for any positive integer $f$ and $n$
is not a power of $k$. Very recently, Xia, Zhang and Zhu reduced the proof of
the conjecture to that of the $2$-transitivity of the shuffle group and then
proved the conjecture under the condition that $k\ge4$ or $k\nmid n$. In this
paper, we proved that the group $G_{3,3n}$ is $2$-transitive for any positive
integer $n$ which is a multiple of $3$ but not a power of $3$. This result
leads to the complete classification of the shuffle groups $G_{k,kn}$ for all
$k\ge2$ and $n\ge1$.


  We study the existence and uniqueness of the time evolution of a system of
infinitely many individuals, moving in a tunnel and subjected to a Cucker-Smale
type alignment dynamics with compactly supported communication kernels and to
short-range repulsive interactions to avoid collisions.


  The theory of the on-shell Sudakov form factor to all order of logarithms is
explained.


  We consider the optimal control of input-queued switches under a
cost-weighted variant of MaxWeight scheduling, for which we establish
theoretical properties that include showing the algorithm exhibits optimal
heavy-traffic queue-length scaling. Our results are expected to be of
theoretical interest more broadly than input-queued switches.


  Two-dimensional layered semiconductor black phosphorus (BP), a promising
pressure induced Dirac system as predicted by band structure calculations, has
been studied by $^{31}$P-nuclear magnetic resonance. Band calculations have
been also carried out to estimate the density of states $D(E)$. The temperature
and pressure dependences of nuclear spin lattice relaxation rate $1/T_1$ in the
semiconducting phase are well reproduced using the derived $D(E)$, and the
resultant pressure dependence of semiconducting gap is in good accordance with
previous reports, giving a good confirmation that the band calculation on BP is
fairly reliable. The present analysis of $1/T_1$ data with the complemental
theoretical calculations allows us to extract essential information, such as
the pressure dependences of $D(E)$ and chemical potential, as well as to
decompose observed $1/T_1$ into intrinsic and extrinsic contributions. An
abrupt increase in $1/T_1$ at 1.63GPa indicates that the semiconducting gap
closes, resulting in an enhancement of conductivity.


  Modern deep learning methods constitute incredibly powerful tools to tackle a
myriad of challenging problems. However, since deep learning methods operate as
black boxes, the uncertainty associated with their predictions is often
challenging to quantify. Bayesian statistics offer a formalism to understand
and quantify the uncertainty associated with deep neural network predictions.
This tutorial provides an overview of the relevant literature and a complete
toolset to design, implement, train, use and evaluate Bayesian Neural Networks,
i.e. Stochastic Artificial Neural Networks trained using Bayesian methods.


  Visible images have been widely used for motion estimation. Thermal images,
in contrast, are more challenging to be used in motion estimation since they
typically have lower resolution, less texture, and more noise. In this paper, a
novel dataset for evaluating the performance of multi-spectral motion
estimation systems is presented. All the sequences are recorded from a handheld
multi-spectral device. It consists of a standard visible-light camera, a
long-wave infrared camera, an RGB-D camera, and an inertial measurement unit
(IMU). The multi-spectral images, including both color and thermal images in
full sensor resolution (640 x 480), are obtained from a standard and a
long-wave infrared camera at 32Hz with hardware-synchronization. The depth
images are captured by a Microsoft Kinect2 and can have benefits for learning
cross-modalities stereo matching. For trajectory evaluation, accurate
ground-truth camera poses obtained from a motion capture system are provided.
In addition to the sequences with bright illumination, the dataset also
contains dim, varying, and complex illumination scenes. The full dataset,
including raw data and calibration data with detailed data format
specifications, is publicly available.


  It is pointed out that the current form of extrinsic equation of motion for a
particle constrained to remain on a hypersurface is in fact a half-finished
version for it is established without regard to the fact that the particle can
never depart from the geodesics on the surface. Once the fact be taken into
consideration, the equation takes that same form as that for centripetal force
law, provided that the symbols are re-interpreted so that the law is applicable
for higher dimensions. The controversial issue of constructing operator forms
of these equations is addressed, and our studies show the quantization of
constrained system based on the extrinsic equation of motion is favorable.


  The cw CCL being designed for the Accelerator Production of Tritium (APT)
project accelerates protons from 96MeV to 211MeV. It consists of 99 segments
each containing up to seven accelerating cavities. Segments are coupled by
intersegment coupling cavities and grouped into supermodules. The design method
needs to address not only basic cavity sizing for a given coupling and pi/2
mode frequency, but also the effects of high power densities on the cavity
frequency, mechanical stresses, and the structure's stop band during operation.
On the APT project, 3-D RF (Ansoft Corp.'s HFSS) and coupled RF/structural
(Ansys Inc.'s ANSYS) codes are being used to develop tools to address the above
issues and guide cooling channel design. The code's predictions are being
checked against available low power Aluminum models. Stop band behavior under
power will be checked once the tools are extended to CCDTL structures that have
been tested at high power. A summary of calculations made to date and agreement
with measured results will be presented.


  We study spatial analyticity properties of solutions of the Navier-Stokes
equations and obtain new growth rate estimates for the analyticity radius. We
also study stability properties of strong global solutions of the Navier-Stokes
equations with data in H^r, r greater or equal 1/2, and prove a stability
result for the analyticity radius.


  We present a necessary and sufficient condition for three qutrit density
matrices to be the one-particle reduced density matrices of a pure three-qutrit
quantum state. The condition consists of seven classes of inequalities
satisfied by the eigenvalues of these matrices. One of them is a generalization
of a known inequality for the qubit case. Some of these inequalities are proved
algebraically whereas the proof of the others uses the fact that a continuous
function of the state must have a minimum. Construction of states satisfying
these inequalities relies on a representation of the convex set of the allowed
set of eigenvalues in terms of corner points. We also present a result for a
more general quantum system concerning the nature of the boundary surface of
the set of the allowed set of eigenvalues.


  In the financial industry, credit scoring is a fundamental element, shaping
access to credit and determining the terms of loans for individuals and
businesses alike. Traditional credit scoring methods, however, often grapple
with challenges such as narrow knowledge scope and isolated evaluation of
credit tasks. Our work posits that Large Language Models (LLMs) have great
potential for credit scoring tasks, with strong generalization ability across
multiple tasks. To systematically explore LLMs for credit scoring, we propose
the first open-source comprehensive framework. We curate a novel benchmark
covering 9 datasets with 14K samples, tailored for credit assessment and a
critical examination of potential biases within LLMs, and the novel instruction
tuning data with over 45k samples. We then propose the first Credit and Risk
Assessment Large Language Model (CALM) by instruction tuning, tailored to the
nuanced demands of various financial risk assessment tasks. We evaluate CALM,
existing state-of-art (SOTA) methods, open source and closed source LLMs on the
build benchmark. Our empirical results illuminate the capability of LLMs to not
only match but surpass conventional models, pointing towards a future where
credit scoring can be more inclusive, comprehensive, and unbiased. We
contribute to the industry's transformation by sharing our pioneering
instruction-tuning datasets, credit and risk assessment LLM, and benchmarks
with the research community and the financial industry.


  Diffusion damping of the cosmic microwave background (CMB) power spectrum
results from imperfect photon-baryon coupling in the pre-recombination plasma.
At redshift $5 \times 10^4 < z < 2 \times 10^6$, the plasma acquires an
effective chemical potential, and energy injections from acoustic damping in
this era create $\mu$-type spectral distortions of the CMB. These $\mu$
distortions trace the underlying photon density fluctuations, probing the
primordial power spectrum in short-wavelength modes $k_\mathrm{S}$ over the
range $50 \ \mathrm{Mpc}^{-1} \lesssim k \lesssim 10^4 \ \mathrm{Mpc}^{-1}$.
Small-scale power modulated by long-wavelength modes $k_\mathrm{L}$ from
squeezed-limit non-Gaussianities introduces cross-correlations between CMB
temperature anisotropies and $\mu$ distortions. Under single-field inflation
models, $\mu \times T$ correlations measured from an observer in an inertial
frame should vanish up to a factor of $(k_\mathrm{L}/k_\mathrm{S})^2 \ll 1$.
Thus, any measurable correlation rules out single-field inflation models. We
forecast how well the next-generation ground-based CMB experiment CMB-S4 will
be able to constrain primordial squeezed-limit non-Gaussianity, parameterized
by $f_\mathrm{NL}$, using measurements of $C_{\ell}^{\mu T}$ as well as
$C_{\ell}^{\mu E}$ from CMB $E$ modes. Using current experimental
specifications and foreground modeling, we expect $\sigma(f_\mathrm{NL})
\lesssim 1000$. This is roughly four times better than the current limit on
$f_\mathrm{NL}$ using $\mu \times T$ and $\mu \times E$ correlations from
Planck and is comparable to what is achievable with LiteBIRD, demonstrating the
power of the CMB-S4 experiment. This measurement is at an effective scale of $k
\simeq 740 \ \text{Mpc}^{-1}$ and is thus highly complementary to measurements
at larger scales from primary CMB and large-scale structure.


  Our current understanding of the cosmic star formation history at z>3 is
primarily based on UV-selected galaxies (i.e., LBGs). Recent studies of
H-dropouts have revealed that we may be missing a large proportion of star
formation that is taking place in massive galaxies at z>3. In this work, we
extend the H-dropout criterion to lower masses to select optically dark/faint
galaxies (OFGs), in order to complete the census between LBGs and H-dropouts.
Our criterion (H> 26.5 mag & [4.5] < 25 mag) combined with a de-blending
technique is designed to select not only extremely dust-obscured massive
galaxies but also normal star-forming galaxies. In total, we identified 27 OFGs
at z_phot > 3 (z_med=4.1) in the GOODS-ALMA field, covering a wide distribution
of stellar masses with log($M_{\star}$/$M_{\odot}$) = 9.4-11.1. We find that up
to 75% of the OFGs with log($M_{\star}$/$M_{\odot}$) = 9.5-10.5 were neglected
by previous LBGs and H-dropout selection techniques. After performing stacking
analyses, the OFGs exhibit shorter gas depletion timescales, slightly lower gas
fractions, and lower dust temperatures than typical star-forming galaxies.
Their SFR_tot (SFR_ IR+SFR_UV) is much larger than SFR_UVcorr (corrected for
dust extinction), with SFR_tot/SFR_UVcorr = $8\pm1$, suggesting the presence of
hidden dust regions in the OFGs that absorb all UV photons. The average dust
size measured by a circular Gaussian model fit is R_e(1.13 mm)=1.01$\pm$0.05
kpc. We find that the cosmic SFRD at z>3 contributed by massive OFGs is at
least two orders of magnitude higher than the one contributed by equivalently
massive LBGs. Finally, we calculate the combined contribution of OFGs and LBGs
to the cosmic SFRD at z=4-5 to be 4 $\times$ 10$^{-2}$ $M_{\odot}$
yr$^{-1}$Mpc$^{-3}$, which is about 0.15 dex (43%) higher than the SFRD derived
from UV-selected samples alone at the same redshift.


  Let X be a complex-projective contact manifold whose second Betti-number is
one. It has long been conjectured that X should then be rational-homogeneous,
or equivalently, that there exists an embedding of X into a projective space
whose image contains lines.
  Using methods introduced in math.AG/0206193, we show that X is covered by a
compact family of rational curves, called "contact lines" that behave very much
like the lines on the rational homogeneous examples: if x in X is a general
point, then all contact lines through x are smooth, no two of them share a
common tangent direction at x, and the union of all contact lines through x
forms a cone over an irreducible, smooth base. As a corollary, we obtain that
the tangent bundle of X is stable.


  X-ray astronomy allows study of objects which may be associated with compact
objects, i.e. neutron stars or black holes, and also may contain strong
magnetic fields. Such objects are categorically non-spherical, and likely
non-circular when projected on the sky. Polarization allows study of such
geometric effects, and X-ray polarimetry is likely to become feasible for a
significant number of sources in the future. Potential targets for future X-ray
polarization observations are the high-mass X-ray binaries (HMXBs), which
consist of a compact object in orbit with an early type star. In this paper ws
show that X-ray polarization from HMXBs has a distinct signature which depends
on the source inclination and orbital phase. The presence of the X-ray source
displaced from the star creates linear polarization even if the primary wind is
spherically symmetric whenever the system is viewed away from conjunction.
Direct X-rays dilute this polarization whenever the X-ray source is not
eclipsed; at mid-eclipse the net polarization is expected to be small or zero
if the wind is circularly symmetric around the line of centers. Resonance line
scattering increases the scattering fraction, often by large factors, over the
energy band spanned by resonance lines. Real winds are not expected to be
spherically symmetric, or circularly symmetric around the line of centers,
owing to the combined effects of the compact object gravity and ionization on
the wind hydrodynamics. A sample calculation shows that this creates
polarization fractions ranging up to tens of percent at mid-eclipse.


  For first-order topological semimetals, non-Hermitian perturbations can drive
the Weyl nodes into Weyl exceptional rings having multiple topological
structures and no Hermitian counterparts. Recently, it was discovered that
higher-order Weyl semimetals, as a novel class of higher-order topological
phases, can uniquely exhibit coexisting surface and hinge Fermi arcs. However,
non-Hermitian higher-order topological semimetals have not yet been explored.
Here, we identify a new type of topological semimetals, i.e, a higher-order
topological semimetal with Weyl exceptional rings. In such a semimetal, these
rings are characterized by both a spectral winding number and a Chern number.
Moreover, the higher-order Weyl-exceptional-ring semimetal supports both
surface and hinge Fermi-arc states, which are bounded by the projection of the
Weyl exceptional rings onto the surface and hinge, respectively. Noticeably,
the dissipative terms can cause the coupling of two exceptional rings with
opposite topological charges, so as to induce topological phase transitions.
Our studies open new avenues for exploring novel higher-order topological
semimetals in non-Hermitian systems.


  In the last years measure-valued solutions started to be considered as a
relevant notion of solutions if they satisfy the so-called measure-valued --
strong uniqueness principle. This means that they coincide with a strong
solution emanating from the same initial data if this strong solution exists.
This property has been examined for many systems of mathematical physics,
including incompressible and compressible Euler system, compressible
Navier-Stokes system et al. and there are also some results concerning general
hyperbolic systems. Our goal is to provide a unified framework for general
systems, that would cover the most interesting cases of systems, and most
importantly, we give examples of equations, for which the aspect of
measure-valued -- strong uniqueness has not been considered before, like
incompressible magentohydrodynamics and shallow water magnetohydrodynamics.


  Let $G$ be a primitive permutation group of degree $n$ with nonabelian socle,
and let $k(G)$ be the number of conjugacy classes of $G$. We prove that either
$k(G)<n/2$ and $k(G)=o(n)$ as $n\rightarrow \infty$, or $G$ belongs to explicit
families of examples.


  We develop a consistent approach to Hamiltonian lattice gauge theory, using
the maximal-tree gauge. The various constraints are discussed and implemented.
An independent and complete set of variables for the colourless sector is
determined. A general scheme to construct the eigenstates of the electric
energy operator using a symbolic method is described. It is shown how the
one-plaquette problem can be mapped onto a N-fermion problem. Explicit
solutions for U(1), SU(2), SU(3), SU(4), and SU(5) lattice gauge theory are
shown.