  Human intention prediction provides an augmented solution for the design of
assistants and collaboration between the human driver and intelligent vehicles.
In this study, a multi-task sequential learning framework is developed to
predict future steering torques and steering postures based on the upper limb
neuromuscular Electromyography (EMG) signals. A single-right-hand driving mode
is particularly studied. For this driving mode, three different driving
postures are also evaluated. Then, a multi-task time-series transformer network
(MTS-Trans) is developed to predict the steering torques and driving postures.
To evaluate the multi-task learning performance, four different frameworks are
assessed. Twenty-one participants are involved in the driving simulator-based
experiment. The proposed model achieved accurate prediction results on the
future steering torque prediction and driving postures recognition for
single-hand driving modes. The proposed system can contribute to the
development of advanced driver steering assistant systems and ensure mutual
understanding between human drivers and intelligent vehicles.


  We present 1.3mm Submillimeter Array (SMA) observations at
$\sim$3$^{\prime\prime}$ resolution towards the brightest section of the
intermediate/massive star forming cluster NGC 2264-C. The millimetre continuum
emission reveals ten 1.3mm continuum peaks, of which four are new detections.
The observed frequency range includes the known molecular jet/outflow tracer
SiO (5-4), thus providing the first high resolution observations of SiO towards
NGC 2264-C. We also detect molecular lines of twelve additional species towards
this region, including CH$_3$CN, CH$_3$OH, SO, H$_2$CO, DCN, HC$_3$N, and
$^{12}$CO. The SiO (5-4) emission reveals the presence of two collimated, high
velocity (up to 30kms$^{-1}$ with respect to the systemic velocity) bi-polar
outflows in NGC 2264-C. In addition, the outflows are traced by emission from
$^{12}$CO, SO, H$_2$CO, and CH$_3$OH. We find an evolutionary spread between
cores residing in the same parent cloud. The two unambiguous outflows are
driven by the brightest mm continuum cores, which are IR-dark, molecular line
weak, and likely the youngest cores in the region. Furthermore, towards the RMS
source AFGL 989-IRS1, the IR-bright and most evolved source in NGC 2264-C, we
observe no molecular outflow emission. A molecular line rich ridge feature,
with no obvious directly associated continuum source, lies on the edge of a low
density cavity and may be formed from a wind driven by AFGL 989-IRS1. In
addition, 229GHz class I maser emission is detected towards this feature.


  Motivation: Epigenetic heterogeneity within a tumour can play an important
role in tumour evolution and the emergence of resistance to treatment. It is
increasingly recognised that the study of DNA methylation (DNAm) patterns along
the genome -- so-called `epialleles' -- offers greater insight into epigenetic
dynamics than conventional analyses which examine DNAm marks individually.
  Results: We have developed a Bayesian model to infer which epialleles are
present in multiple regions of the same tumour. We apply our method to reduced
representation bisulfite sequencing (RRBS) data from multiple regions of one
lung cancer tumour and a matched normal sample. The model borrows information
from all tumour regions to leverage greater statistical power. The total number
of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all
automatically inferred from the data. Uncertainty as to which epiallele an
observed sequencing read originated from is explicitly incorporated by
marginalising over the appropriate posterior densities. The degree to which
tumour samples are contaminated with normal tissue can be estimated and
corrected for. By tracing the distribution of epialleles throughout the tumour
we can infer the phylogenetic history of the tumour, identify epialleles that
differ between normal and cancer tissue, and define a measure of global
epigenetic disorder.


  In category theory circles it is well-known that the Schreier theory of group
extensions can be understood in terms of the Grothendieck construction on
indexed categories. However, it is seldom discussed how this relates to
extensions of monoids. We provide an introduction to the generalised
Grothendieck construction and apply it to recover classifications of certain
classes of monoid extensions (including Schreier and weakly Schreier extensions
in particular).


  We propose the two formalisms for obtaining the noncommutative spacetime in a
magnetic field. One is the first-order formalism and the other is the
second-order formalism. Although the noncommutative spacetime is realized
manifestly in the first-order formalism, the second-order formalism would be
more useful for calculating the physical quantities in the noncommutative
geometry than the first-order one. Several interesting points for string theory
and fractional quantum Hall effect are discussed. In particular, we point out
that the noncommutative geometry is closely related to the fractional quantum
Hall effect(FQHE).


  All three-dimensional matter-free spacetimes with negative cosmological
constant, compatible with cyclic symmetry are identified. The only cyclic
solutions are the 2+1 (BTZ) black hole with SO(2) x R isometry, and the
self-dual Coussaert-Henneaux spacetimes, with isometry groups SO(2) x SO(2,1)
or SO(2) x SO(2).


  We present MERLIN maps of the 22-GHz H2O masers around four low-mass
late-type stars (IK Tau U Ori, RT Vir and U Her), made with an angular
resolution of ~ 15 milliarcsec and a velocity resolution of 0.1 km s-1. The H2O
masers are found in thick expanding shells with inner radii ~ 6 to 16 au and
outer radii four times larger. The expansion velocity increases radially
through the H2O maser regions, with logarithmic velocity gradients of 0.5--0.9.
IK Tau and RT Vir have well-filled H2O maser shells with a spatial offset
between the near and far sides of the shell, which suggests that the masers are
distributed in oblate spheroids inclined to the line of sight. U Ori and U Her
have elongated poorly-filled shells with indications that the masers at the
inner edge have been compressed by shocks; these stars also show OH maser
flares. MERLIN resolves individual maser clouds, which have diameters of 2 -- 4
au and filling factors of only ~ 0.01 with respect to the whole H2O maser
shells. The CSE velocity structure gives additional evidence the maser clouds
are density bounded. Masing clouds can be identified over a similar timescale
to their sound crossing time (~2 yr) but not longer. The sizes and observed
lifetimes of these clouds are an order of magnitude smaller than those around
red supergiants, similar to the ratio of low-mass:high-mass stellar masses and
sizes. This suggests that cloud size is determined by stellar properties, not
local physical phenomena in the wind.


  We give a sufficient criterion for complex analyticity of nonlinear maps
defined on direct limits of normed spaces. This tool is then used to construct
new classes of (real and complex) infinite dimensional Lie groups:
  (a) groups of germs of analytic diffeomorphisms around a compact set in a
Banach space and
  (b) unions of ascending sequences of Banach Lie groups.


  We study collective excitations in hot rotating chiral media in presence of
magnetic field in kinetic theory, namely Chiral Heat Wave and its' mixings with
Chiral Vortical Wave and Chiral Magnetic Wave. Our results for velocities of
these waves have slight alterations from those obtained earlier. We explain the
origin of these alterations and also give the most general expressions for the
velocities of all these waves in hydrodynamic approach.


  Person retrieval faces many challenges including cluttered background,
appearance variations (e.g., illumination, pose, occlusion) among different
camera views and the similarity among different person's images. To address
these issues, we put forward a novel mask based deep ranking neural network
with a skipped fusing layer. Firstly, to alleviate the problem of cluttered
background, masked images with only the foreground regions are incorporated as
input in the proposed neural network. Secondly, to reduce the impact of the
appearance variations, the multi-layer fusion scheme is developed to obtain
more discriminative fine-grained information. Lastly, considering person
retrieval is a special image retrieval task, we propose a novel ranking loss to
optimize the whole network. The proposed ranking loss can further mitigate the
interference problem of similar negative samples when producing ranking
results. The extensive experiments validate the superiority of the proposed
method compared with the state-of-the-art methods on many benchmark datasets.


  We discuss leptogenesis constraints on the mass of the right-handed $W$-boson
($W_R$) in a TeV-scale Left-Right seesaw model (LRSM) for neutrino masses. For
generic Dirac mass of the neutrinos, i.e. with all Yukawa couplings $\lesssim
10^{-5.5}$, it has been pointed out that successful leptogenesis requires a
lower bound of 18 TeV on the $W_R$ mass, pushing it beyond the reach of LHC.
Such TeV-scale LRSM must, however, be parity-asymmetric for type-I seesaw to
give the observed neutrino masses. This class of models can accommodate larger
Yukawa couplings, which give simultaneous fits to charged-lepton and neutrino
masses, by invoking either cancellations or specific symmetry-textures for
Dirac ($M_D$) and Majorana ($M_N$) masses in the seesaw formula. We show that
in this case, the leptogenesis bound on $M_{W_R}$ can be substantially weaker,
i.e. $M_{W_R}\gtrsim 3$ TeV for $M_N \lesssim M_{W_R}$. This happens due to
considerable reduction of the dilution effects from $W_R$-mediated decays and
scatterings, while the washout effects due to inverse decays are under control
for certain parameter ranges of the Yukawa couplings. We also show that this
model is consistent with all other low energy constraints, such as lepton
flavor violation and neutrinoless double beta decay. Thus, a discovery of the
right-handed gauge bosons alone at the LHC will not falsify leptogenesis as the
mechanism behind the matter-antimatter asymmetry in our Universe.


  This study presents the development of large-area (18 $\times $ 18 $\times $
2 cm$^3$), high refractive index ($n \sim $1.05) hydrophobic silica aerogel
tiles for use as Cherenkov radiators. These transparent aerogel tiles will be
installed in a Cherenkov detector for the next-generation accelerator-based
particle physics experiment Belle II, to be performed at the High Energy
Accelerator Research Organization (KEK) in Japan. Cracking has been eliminated
from the prototype aerogel tiles by improving the supercritical carbon dioxide
(scCO$_2$) extraction procedure when drying the wet gel tiles. Finally, a
method of mass-producing aerogel tiles for the actual detector was established.
It was confirmed that the experimentally manufactured aerogel tiles meet the
required optical and hydrophobic characteristics and have a uniform tile
density.


  Black-box optimization (BBO) has become increasingly relevant for tackling
complex decision-making problems, especially in public policy domains such as
police districting. However, its broader application in public policymaking is
hindered by the complexity of defining feasible regions and the
high-dimensionality of decisions. This paper introduces a novel BBO framework,
termed as the Conditional And Generative Black-box Optimization (CageBO). This
approach leverages a conditional variational autoencoder to learn the
distribution of feasible decisions, enabling a two-way mapping between the
original decision space and a simplified, constraint-free latent space. The
CageBO efficiently handles the implicit constraints often found in public
policy applications, allowing for optimization in the latent space while
evaluating objectives in the original space. We validate our method through a
case study on large-scale police districting problems in Atlanta, Georgia. Our
results reveal that our CageBO offers notable improvements in performance and
efficiency compared to the baselines.


  We propose 360{\deg} Volumetric Portrait (3VP) Avatar, a novel method for
reconstructing 360{\deg} photo-realistic portrait avatars of human subjects
solely based on monocular video inputs. State-of-the-art monocular avatar
reconstruction methods rely on stable facial performance capturing. However,
the common usage of 3DMM-based facial tracking has its limits; side-views can
hardly be captured and it fails, especially, for back-views, as required inputs
like facial landmarks or human parsing masks are missing. This results in
incomplete avatar reconstructions that only cover the frontal hemisphere. In
contrast to this, we propose a template-based tracking of the torso, head and
facial expressions which allows us to cover the appearance of a human subject
from all sides. Thus, given a sequence of a subject that is rotating in front
of a single camera, we train a neural volumetric representation based on neural
radiance fields. A key challenge to construct this representation is the
modeling of appearance changes, especially, in the mouth region (i.e., lips and
teeth). We, therefore, propose a deformation-field-based blend basis which
allows us to interpolate between different appearance states. We evaluate our
approach on captured real-world data and compare against state-of-the-art
monocular reconstruction methods. In contrast to those, our method is the first
monocular technique that reconstructs an entire 360{\deg} avatar.


  Systems that are not smooth can undergo bifurcations that are forbidden in
smooth systems. We review some of the phenomena that can occur for
piecewise-smooth, continuous maps and flows when a fixed point or an
equilibrium collides with a surface on which the system is not smooth. Much of
our understanding of these cases relies on a reduction to piecewise linearity
near the border-collision. We also review a number of codimension-two
bifurcations in which nonlinearity is important.


  The C/Z_N orbifold of type II string theory has localized tachyons with m^2
ranging from -1+1/N to -2/N in units of 2/\alpha'. We show that by restricting
attention to the lightest tachyons it is possible to take a zero-slope limit
where N is taken to infinity while N\alpha' is held fixed. This is done by
applying Buscher duality in the angular direction of the cone to obtain a
supergravity solution on which the tachyons are gravitational instabilities. In
this picture, supergravity provides a natural off-shell description of the
tachyonic interactions. For example, the three-point couplings can be read off
easily (to leading order in 1/N) from the supergravity action, and are in
agreement with the on-shell couplings computed using CFT techniques.


  For nearby K dwarfs, the broadening of the observed Main Sequence at low
metallicities is much narrower than expected from isochrones with the standard
helium-to-metal enrichment ratio DY/DZ=2. Though the latter value fits well the
Main Sequence around solar metallicity, and agrees with independent
measurements from HII regions as well as with theoretical stellar yields and
chemical evolution models, a much higher DY/DZ~10 is necessary to reproduce the
broadening observed for nearby subdwarfs. This result resembles, on a milder
scale, the very high DY/DZ estimated from the multiple Main Sequences in Omega
Cen and NGC 2808. Although not "inverted" as in omega Cen, where the metal-rich
Main Sequence is bluer than the metal-poor one, the broadening observed for
nearby subdwarfs is much narrower than stellar models predict for a standard
helium content. We use this empirical evidence to argue that a revision of
lower Main Sequence stellar models, suggested from nearby stars, could
significantly reduce the helium content inferred for the subpopulations of
those globular clusters. A simple formula based on empirically calibrated
homology relations is constructed, for an alternative estimate of DY/DZ in
multiple main sequences. We find that, under the most favourable assumptions,
the estimated helium content for the enriched populations could decrease from
Y~0.4 to as low as Y~0.3.


  The Ruijsenaars-Schneider models are conventionally regarded as relativistic
generalizations of the Calogero integrable systems. Surprisingly enough, their
supersymmetric generalizations escaped attention. In this work, N=2
supersymmetric extensions of the rational and hyperbolic Ruijsenaars-Schneider
three-body models are constructed within the framework of the Hamiltonian
formalism. It is also known that the rational model can be described by the
geodesic equations associated with a metric connection. We demonstrate that the
hyperbolic systems are linked to non-metric connections.


  We point out that fractionalized bosonic charge excitations can explain the
recently discovered photo-induced superconducting-like response in
$\kappa\text{-(ET})_2\text{Cu}[\text{N(CN)}_2]\text{Br}$, an organic metal
close to the Mott transition. The pump laser exerts a periodic drive on the
fractionalized field, creating a non-equilibrium condensate, which gives a
Drude peak much narrower than the equilibrium scattering rate, hence
superconducting-like response. Our proposal illuminates new possibilities of
detecting fractionalization and can be readily tested in spin liquid candidates
and in cold atom systems.


  Cost-aware Targeted Viral Marketing (CTVM), a generalization of Influence
Maximization (IM), has received a lot of attentions recently due to its
commercial values. Previous approximation algorithms for this problem required
a large number of samples to ensure approximate guarantee. In this paper, we
propose an efficient approximation algorithm which uses fewer samples but
provides the same theoretical guarantees based on generating and using
important samples in its operation. Experiments on real social networks show
that our proposed method outperforms the state-of-the-art algorithm which
provides the same approximation ratio in terms of the number of required
samples and running time.


  In this paper, we study the cooperative robust output regulation problem for
linear uncertain multi-agent systems with both communication delay and input
delay by the distributed internal model approach. The problem includes the
leader-following consensus problem of linear multi-agent systems with
time-delay as a special case. We first generalize the internal model design
method to systems with both communication delay and input delay. Then, under a
set of standard assumptions, we have obtained the solution of the problem via
both the state feedback control and the output feedback control. In contrast
with the existing results, our results apply to general uncertain linear
multi-agent systems, accommodate a large class of leader signals, and achieve
the asymptotic tracking and disturbance rejection at the same time.


  Anti-protonic hydrogen and helium atoms are analyzed. Level shifts and width
are expressed in terms of $\bar{p}$-nucleon sub-threshold scattering lengths
and volumes. Experimental data are compared to results obtained from the 2009
version of the Paris $N\bar{N}$ interaction potential. Comparison with 1999
version is also made. Effects of $N\bar{N}$ quasi-bound states are discussed.
Atomic 2P hyperfine structure is calculated for antiprotonic deuterium and the
significance of new measurements is indicated.


  In this work, we present a quantized deep neural network deployed on a
low-power edge device, inferring learned motor-movements of a suspended robot
in a defined space. This serves as the fundamental building block for the
original setup, a robotic system for farms or greenhouses aimed at a wide range
of agricultural tasks. Deep learning on edge devices and its implications could
have a substantial impact on farming systems in the developing world, leading
not only to sustainable food production and income, but also increased data
privacy and autonomy.


  Euler solved the problem of the collapse of tall thin columns under
unexpectedly small loads in 1744. The analogous problem of the collapse of
circular elastic rings or tubes under external pressure was mathematically
intractable and only fully solved recently. In the context of carbon nanotubes,
an additional phenomenon was found experimentally and in atomistic simulations
but not explained: the collapse pressure of smaller diameter tubes deviates
below the continuum mechanics solution [Torres-Dias et al., Carbon 123, 145
(2017)]. Here, this deviation is shown to occur in discretized straight columns
and it is fully explained in terms of the phonon dispersion curve. This reveals
an unexpected link between the static mechanical properties of discrete systems
and their dynamics described through dispersion curves.


  We discuss how scattering amplitudes in 4d Minkowski spacetime which involve
multiple soft gravitons realize the algebra of BMS charges on the null
boundary. In particular, we show how the commutator of two such charges is
realized by the antisymmetrized consecutive soft limit of the double soft
amplitude. The commutator is found to be robust even in the presence of quantum
corrections, and the associated Lie algebra has an extension, which breaks the
BMS symmetry if the BMS algebra is taken to include the Virasoro algebra of
local superrotations. We discuss the implications of this structure for the
existence of a 2d CFT dual description for 4d scattering amplitudes.


  Coset constructions of $\mathcal{W}$-algebras have many applications, and
were recently given for principal $\mathcal{W}$-algebras of $A$, $D$, and $E$
types by Arakawa together with the first and third authors. In this paper, we
give coset constructions of the large and small $N=4$ superconformal algebras,
which are the minimal $\mathcal{W}$-algebras of $\mathfrak{d}(2,1;a)$ and
$\mathfrak{psl}(2|2)$, respectively. From these realizations, one finds a
remarkable connection between the large $N=4$ algebra and the diagonal coset
$C^{k_1, k_2} = \text{Com}(V^{k_1+k_2}(\mathfrak{sl}_2),
V^{k_1}(\mathfrak{sl}_2) \otimes V^{k_2}(\mathfrak{sl}_2))$, namely, as
two-parameter vertex algebras, $C^{k_1, k_2}$ coincides with the coset of the
large $N=4$ algebra by its affine subalgebra. We also show that at special
points in the parameter space, the simple quotients of these cosets are
isomorphic to various $\mathcal{W}$-algebras. As a corollary, we give new
examples of strongly rational principal $\mathcal{W}$-algebras of type $C$ at
degenerate admissible levels.


  We introduce and study the "kicked Hall system" (KHS), i.e., charged
particles periodically kicked in the presence of uniform magnetic
($\mathbf{B}$) and electric ($\mathbf{E}$) fields that are perpendicular to
each other and to the kicking direction. We show that for resonant values of
$B$ and $E$ and in the weak-chaos regime of sufficiently small nonintegrability
parameter $\kappa$ (the kicking strength), there exists a \emph{generic} family
of periodic kicking potentials for which the Hall effect from $\mathbf{B}$ and
$\mathbf{E}$ significantly suppresses the weak chaos, replacing it by
\emph{"superweak"} chaos (SWC). This means that the system behaves as if the
kicking strength were $\kappa ^2$ rather than $\kappa$. For $E=0$, SWC is known
to be a classical fingerprint of quantum antiresonance but it occurs under much
less generic conditions, in particular only for very special kicking
potentials. Manifestations of SWC are a decrease in the instability of periodic
orbits and a narrowing of the chaotic layers, relative to the ordinary
weak-chaos case. Also, for global SWC, taking place on an infinite "stochastic
web" in phase space, the chaotic diffusion on the web is much slower than the
weak-chaos one. Thus, the Hall effect can be relatively stabilizing for small
$\kappa$. In some special cases, the effect is shown to cause ballistic motion
for almost all parameter values. The generic global SWC on stochastic webs in
the KHS appears to be the two-dimensional closest analog to the Arnol'd web in
higher dimensional systems.


  We describe the correct cubic relation between the mass configuration of a
Kater reversible pendulum and its period of oscillation. From an analysis of
its solutions we conclude that there could be as many as three distinct mass
configurations for which the periods of small oscillations about the two pivots
of the pendulum have the same value. We also discuss a real compound Kater
pendulum that realizes this property.


  We propose a novel mechanism for the production of the Higgs boson in
inclusive hadronic collisions, which utilizes the presence of heavy quarks in
the proton wave function. In these inclusive reactions the Higgs boson acquires
the momenta of both the heavy quark and antiquark and thus carries 80% or more
of the projectile's momentum. We predict that the cross section ${d \sigma/d
x_F}(p \bar p \to H X)$ for the inclusive production of the Standard Model
Higgs coming from intrinsic bottom Fock states is of order 150 fb at LHC
energies, peaking in the region of $x_F \sim 0.9$. Our estimates indicate that
the corresponding cross section coming from gluon-gluon fusion at $x_F = 0.9$
is relatively negligible and therefore the peak from intrinsic bottom should be
clearly visible for experiments with forward detection capabilities. The
predicted cross section for the production of the Standard Model Higgs coming
from intrinsic heavy quark Fock states in the proton is sufficiently large that
detection at the Tevatron and the LHC may be possible.


  The aim of this short note is to present a proof of the existence of an
$A_\infty$-quasi-isomorphism between the $A_\infty$-$\mathrm
S(V^*)$-$\wedge(V)$-bimodule $K$, introduced in \cite{CFFR}, and the Koszul
complex $\mathrm K(V)$ of $\mathrm S(V^*)$, viewed as an $A_\infty$-$\mathrm
S(V^*)$-$\wedge(V)$-bimodule, for $V$ a finite-dimensional (complex or real)
vector space.


  Machine learning (ML) has entered the mobile era where an enormous number of
ML models are deployed on edge devices. However, running common ML models on
edge devices continuously may generate excessive heat from the computation,
forcing the device to "slow down" to prevent overheating, a phenomenon called
thermal throttling. This paper studies the impact of thermal throttling on
mobile phones: when it occurs, the CPU clock frequency is reduced, and the
model inference latency may increase dramatically. This unpleasant inconsistent
behavior has a substantial negative effect on user experience, but it has been
overlooked for a long time. To counter thermal throttling, we propose to
utilize dynamic networks with shared weights and dynamically shift between
large and small ML models seamlessly according to their thermal profile, i.e.,
shifting to a small model when the system is about to throttle. With the
proposed dynamic shifting, the application runs consistently without
experiencing CPU clock frequency degradation and latency increase. In addition,
we also study the resulting accuracy when dynamic shifting is deployed and show
that our approach provides a reasonable trade-off between model latency and
model accuracy.


  This is the first in a sequence of articles exploring the relationship
between commutative algebras and $E_\infty$-algebras in characteristic $p$ and
mixed characteristic. In this paper we lay the groundwork by defining a new
class of cohomology operations over $\mathbb F_p$ called cotriple products,
generalising Massey products. We compute the secondary cohomology operations
for a strictly commutative dg-algebra and the obstruction theories these
induce, constructing several counterexamples to characteristic 0 behaviour, one
of which answers a question of Campos, Petersen, Robert-Nicoud and Wierstra. We
construct some families of higher cotriple products and comment on their
behaviour. Finally, we distingush a subclass of cotriple products that we call
higher Steenrod operations and conclude with our main theorem, which says that
$E_\infty$-algebras can be rectified if and only if the higher Steenrod
operations vanish coherently.


  We consider a neural network architecture with randomized features, a
sign-splitter, followed by rectified linear units (ReLU). We prove that our
architecture exhibits robustness to the input perturbation: the output feature
of the neural network exhibits a Lipschitz continuity in terms of the input
perturbation. We further show that the network output exhibits a discrimination
ability that inputs that are not arbitrarily close generate output vectors
which maintain distance between each other obeying a certain lower bound. This
ensures that two different inputs remain discriminable while contracting the
distance in the output feature space.


  Neutrinos are likely the most poorly understood basic constituents of the
Standard Model. In order to investigate precisely their interactions one should
be able to create high intensity and well-collimated neutrino beams with known
flavor compositions. This is a challenging problem for neutrino experiments. We
propose a method of studying neutrino interactions based on the fact that a
charged lepton is able to manifest itself effectively, with a certain
probability, as a neutrino. The effective neutrino method may provide an
additional tool for probing neutrino-induced reactions at $e^+e^-$ and $ep$
colliders as well as at other facilities that use charged lepton beams. We
derive the distributions of the effective neutrinos in the charged leptons and
give examples of application of the method to electron-positron collisions.


  This paper is devoted to $C^2$ a priori estimates for strictly locally convex
radial graphs with prescribed Weingarten curvature and boundary in space forms.
By constructing two-step continuity process and applying degree theory
arguments, existence results in space forms are established for prescribed
Gauss curvature equation under the assumption of a strictly locally convex
subsolution.


  It has been argued recently that an inhomogeneous system could rotate
spontaneously in its ground state - hence a 'time crystal' which is periodic in
time. In this note we present a very simple example: a superfluid ring threaded
by a magnetic field which develops a charge density wave (CDW). A naive
calculation shows that diamagnetic currents cannot drive rotation of the CDW,
with a clear picture of the cancellation mechanism.


  The purpose of this paper is to propose a novel perspective, based on
Willems' "behavior theory", on the design of an unknown-input observer for a
given linear time-invariant discrete-time state-space model, with unknown
disturbances affecting both the state and the output equations. The problem is
first addressed assuming that the original system model is known, and later
assuming that the model is unknown but historical data satisfying a certain
assumption are available. In both cases, fundamental concepts in behavior
theory, as the projection of a behavior, the inclusion of a behavior in another
one, and the use of kernel and image representations, provide quite powerful
tools to determine necessary and sufficient conditions for the existence of an
unknown-input observer (UIO), as well as algorithms to design one of them, if
it exists.


  The paper gives a detailed presentation of a framework, embedded into the
simply typed higher-order logic and aimed at the support of sound and
structured reasoning about various properties of models of imperative programs
with interleaved computations. As a case study, a model of the Peterson's
mutual exclusion algorithm will be scrutinised in the course of the paper
illustrating applicability of the framework.


  The imaginary part of the Feynman amplitude of the $W$-loop contribution to
the Higgs decay into two gammas (viewed as a function of the square of the off
shell Higgs momentum) is finite and unambiguous. It is presented as the product
of an invariant amplitude ${\cal A}$ times a bilinear in the components of the
(on shell) photon momenta factor which takes the Ward identity into account.
The unsubtracted dispersion integral of ${\cal A}$ is convergent and reproduces
the amplitude computed by R. Gastmans, S.L. Wu and T.T. Wu [GWW]. In
particular, the decoupling theorem, criticized as an unjustified assumption in
a subsequent paper [SVVZ12], is obtained as a corollary. By contrast with the
currently used value (computed in [SVVZ]) our calculation provides a smaller
Higgs decay rate into 2 photons than the currently observed. If accepted as a
true prediction of the Standard Model, it would be a first indication for the
need of a New Physics.


  Automatic speech recognition systems usually rely on spectral-based features,
such as MFCC of PLP. These features are extracted based on prior knowledge such
as, speech perception or/and speech production. Recently, convolutional neural
networks have been shown to be able to estimate phoneme conditional
probabilities in a completely data-driven manner, i.e. using directly temporal
raw speech signal as input. This system was shown to yield similar or better
performance than HMM/ANN based system on phoneme recognition task and on large
scale continuous speech recognition task, using less parameters. Motivated by
these studies, we investigate the use of simple linear classifier in the
CNN-based framework. Thus, the network learns linearly separable features from
raw speech. We show that such system yields similar or better performance than
MLP based system using cepstral-based features as input.


  The end of Dennard scaling and the slowing of Moore's Law has put the energy
use of datacenters on an unsustainable path. Datacenters are already a
significant fraction of worldwide electricity use, with application demand
scaling at a rapid rate. We argue that substantial reductions in the carbon
intensity of datacenter computing are possible with a software-centric
approach: by making energy and carbon visible to application developers on a
fine-grained basis, by modifying system APIs to make it possible to make
informed trade offs between performance and carbon emissions, and by raising
the level of application programming to allow for flexible use of more energy
efficient means of compute and storage. We also lay out a research agenda for
systems software to reduce the carbon footprint of datacenter computing.


  We discuss some seemingly paradoxical yet valid effects of quantum physics in
information processing. Firstly, we argue that the act of ``doing nothing'' on
part of an entangled quantum system is a highly non-trivial operation and that
it is the essential ingredient underlying the computational speedup in the
known quantum algorithms. Secondly, we show that the watched pot effect of
quantum measurement theory gives the following novel computational possibility:
suppose that we have a quantum computer with an on/off switch, programmed ready
to solve a decision problem. Then (in certain circumstances) the mere fact that
the computer would have given the answer if it were run, is enough for us to
learn the answer, even though the computer is in fact not run.


  We present results from extensive molecular dynamics simulations of collapse
transitions of hydrophobic polymers in explicit water focused on understanding
effects of lengthscale of the hydrophobic surface and of attractive
interactions on folding. Hydrophobic polymers display parabolic, protein-like,
temperature-dependent free energy of unfolding. Folded states of small
attractive polymers are marginally stable at 300 K, and can be unfolded by
heating or cooling. Increasing the lengthscale or decreasing the polymer-water
attractions stabilizes folded states significantly, the former dominated by the
hydration contribution. That hydration contribution can be described by the
surface tension model, $\Delta G=\gamma (T)\Delta A$, where the surface
tension, $\gamma$, is lengthscale dependent and decreases monotonically with
temperature. The resulting variation of the hydration entropy with polymer
lengthscale is consistent with theoretical predictions of Huang and Chandler
(Proc. Natl. Acad. Sci.,97, 8324-8327, 2000) that explain the blurring of
entropy convergence observed in protein folding thermodynamics. Analysis of
water structure shows that the polymer-water hydrophobic interface is soft and
weakly dewetted, and is characterized by enhanced interfacial density
fluctuations. Formation of this interface, which induces polymer folding, is
strongly opposed by enthalpy and favored by entropy, similar to the
vapor-liquid interface.


  Supervised statistical classification is a vital tool for satellite image
processing. It is useful not only when a discrete result, such as feature
extraction or surface type, is required, but also for continuum retrievals by
dividing the quantity of interest into discrete ranges. Because of the high
resolution of modern satellite instruments and because of the requirement for
real-time processing, any algorithm has to be fast to be useful. Here we
describe an algorithm based on kernel estimation called Adaptive Gaussian
Filtering that incorporates several innovations to produce superior efficiency
as compared to three other popular methods: k-nearest-neighbour (KNN), Learning
Vector Quantization (LVQ) and Support Vector Machines (SVM). This efficiency is
gained with no compromises: accuracy is maintained, while estimates of the
conditional probabilities are returned. These are useful not only to gauge the
accuracy of an estimate in the absence of its true value, but also to
re-calibrate a retrieved image and as a proxy for a discretized continuum
variable. The algorithm is demonstrated and compared with the other three on a
pair of synthetic test classes and to map the waterways of the Netherlands.
Software may be found at: http://libagf.sourceforge.net.


  We derive rigorously one- and two-dimensional mean-field equations for cigar-
and pancake-shaped Bose-Einstein condensates (BEC) with higher order
interactions (HOI). We show how the higher order interaction modifies the
contact interaction of the strongly confined particles. Surprisingly, we find
that the usual Gaussian profile assumption for the strongly confining direction
is inappropriate for the cigar-shaped BEC case, and a Thomas-Fermi type profile
should be adopted instead. Based on the derived mean field equations, the
Thomas-Fermi densities are analyzed in presence of the contact interaction and
HOI. For both box and harmonic traps in one, two and three dimensions, we
identify the analytical Thomas-Fermi densities, which depend on the competition
between the contact interaction and the HOI.


  In this paper we study the performance of a bipartite network in which
customers arrive at the nodes of the network, but not all nodes are able to
serve their customers at all times. Each node can be either active or inactive,
and two nodes connected by a bond cannot be active simultaneously. This
situation arises in wireless random-access networks where, due to destructive
interference, stations that are close to each other cannot use the same
frequency band.
  We consider a model where the network is bipartite, the active nodes switch
themselves off at rate 1, and the inactive nodes switch themselves on at a rate
that depends on time and on which half of the bipartite network they are in. An
inactive node cannot become active when one of the nodes it is connected to by
a bond is active. The switching protocol allows the nodes to share activity
among each other. In the limit as the activation rate becomes large, we compute
the crossover time between the two states where one half of the network is
active and the other half is inactive. This allows us to assess the overall
activity of the network depending on the switching protocol. Our results make
use of the metastability analysis for hard-core interacting particle models on
finite bipartite graphs derived in an earlier paper. They are valid for a large
class of bipartite networks, subject to certain assumptions. Proofs rely on a
comparison with switching protocols that are not time-varying, through coupling
techniques.


  For "Riesz-like" kernels $K(x,y)=f(|x-y|)$ on $A\times A$, where $A$ is a
compact $d$-regular set $A\subset \mathbb{R}^p$, we prove a minimum principle
for potentials $U_K^\mu=\int K(x,y)d\mu(x)$, where $\mu$ is a Borel measure
supported on $A$. Setting $P_K(\mu)=\inf_{y\in A}U^\mu(y)$, the
$K$-polarization of $\mu$, the principle is used to show that if $\{\nu_N\}$ is
a sequence of measures on $A$ that converges in the weak-star sense to the
measure $\nu$, then $P_K(\nu_N)\to P_K(\nu)$ as $N\to \infty$. The continuous
Chebyshev (polarization) problem concerns maximizing $P_K(\mu)$ over all
probability measures $\mu$ supported on $A$, while the $N$-point discrete
Chebyshev problem maximizes $P_K(\mu)$ only over normalized counting measures
for $N$-point multisets on $A$. We prove for such kernels and sets $A$, that if
$\{\nu_N\}$ is a sequence of $N$-point measures solving the discrete problem,
then every weak-star limit measure of $\nu_N$ as $N \to \infty$ is a solution
to the continuous problem.


  We present high-precision photometry on 107 variable low-mass stars and brown
dwarfs in the ~3 Myr Sigma Orionis open cluster. We have carried out I-band
photometric monitoring within two fields, encompassing 153 confirmed or
candidate members of the low-mass cluster population, from 0.02 to 0.5 M_\odot.
We are sensitive to brightness changes on time scales from 10 minutes to two
weeks with amplitudes as low as 0.004 magnitudes, and find variability on these
time scales in nearly 70% of cluster members. We identify both periodic and
aperiodic modes of variability, as well as semi-periodic rapid fading events
that are not accounted for by the standard explanations of rotational
modulation of surface features or accretion. We have incorporated both optical
and infrared color data to uncover trends in variability with mass and
circumstellar disks. While the data confirm that the lowest-mass objects
(M<0.2M_\odot) rotate more rapidly than the 0.2-0.5 M_\odot members, they do
not support a direct connection between rotation rate and the presence of a
disk. Finally, we speculate on the origin of irregular variability in cluster
members with no evidence for disks or accretion.


  We examine the relationship between the mutual information between the output
model and the empirical sample and the generalization of the algorithm in the
context of stochastic convex optimization. Despite increasing interest in
information-theoretic generalization bounds, it is uncertain if these bounds
can provide insight into the exceptional performance of various learning
algorithms. Our study of stochastic convex optimization reveals that, for true
risk minimization, dimension-dependent mutual information is necessary. This
indicates that existing information-theoretic generalization bounds fall short
in capturing the generalization capabilities of algorithms like SGD and
regularized ERM, which have dimension-independent sample complexity.


  Gibbs' measures in the Sherrington-Kirkpatrick type models satisfy two
asymptotic stability properties, the Aizenman-Contucci stochastic stability and
the Ghirlanda-Guerra identities, which play a fundamental role in our current
understanding of these models. In this paper we show that one can combine these
two properties very naturally into one unified stability property.


  We show that a F_{q^2}-maximal curve of genus q(q-3)/6 in characteristic
three is either a non-reflexive space curve of degree q+1, or it is uniquely
determined up to F_{q^2}-isomorphism by a plane model of Artin-Schreier type


  The status of coupling constant unification (with and without a unification
of Yukawa couplings) is discussed. Uncertainties associated with the input
coupling constants, $m_{b}$ and $m_{t}$, threshold corrections at the low and
high scale, and possible nonrenormalizable operators are described and a
discrepancy between effective and physical scales is pointed out. Theoretical
uncertainties in the predictions of $\alpha_{s}(M_{Z})$, $m_{b}$, and the
unification scale, $M_{G}$, are discussed and estimated. Constraints on the
super-partner spectrum are found to be weak if uncertainties associated with
the high-scale are included. However, requiring $h_{b} = h_{\tau}$ at $M_{G}$
excludes $3 < \tan \beta < 40$ (for $m_{t} < 200$ GeV).


  We investigate the potential of the ILC for measuring anomalous quartic gauge
couplings, both in production of three electroweak gauge bosons as well as in
vector boson scattering. Any new physics that could possibly couple to the
electroweak gauge bosons is classified according to its spin and isospin
quantum numbers and parameterized in terms of resonance parameters like masses,
widths, magnetic moment form factors etc. By a maximum log-likelihood fit, the
discovery reach of a 1 TeV ILC for scalar, vector and tensor resonances is
examined.


  We propose a quasi-Monte Carlo algorithm for pricing knock-out and knock-in
barrier options under the Heston (1993) stochastic volatility model. This is
done by modifying the LT method from Imai and Tan (2006) for the Heston model
such that the first uniform variable does not influence the stochastic
volatility path and then conditionally modifying its marginals to fulfill the
barrier condition(s). We show this method is unbiased and never does worse than
the unconditional algorithm. Additionally the conditioning is combined with a
root finding method to also force positive payouts. The effectiveness of this
method is shown by extensive numerical results.


  When dealing with Fourier expansions using the third Jackson (also known as
Hahn-Exton) $q$-Bessel function, the corresponding positive zeros $j_{k\nu}$
and the "shifted" zeros, $qj_{k\nu}$, among others, play an essential role.
Mixing classical analysis with $q$-analysis we were able to prove asymptotic
relations between those zeros and the "shifted" ones, as well as the asymptotic
behavior of the third Jackson $q$-Bessel function when computed on the
"shifted" zeros. A version of a $q$-analogue of the Riemann-Lebesgue theorem
within the scope of basic Fourier-Bessel expansions is also exhibited.


  Transition metal dichalcogenides have been the subject of numerous studies
addressing technological applications and fundamental issues. Single-layer
PtSe2 is a semiconductor with a trivial bandgap, in contrast, its counterpart
with 25% of Se atoms substituted by Hg, Pt2HgSe3 (jacutingaite, a naturally
occurring mineral), is a 2D topological insulator with a large bandgap. Based
on ab-initio calculations, we investigate the energetic stability, and the
topological transition in Pt(HgxSe1-x)2 as a function of alloy concentration,
and the distribution of Hg atoms embedded in the PtSe2 host. Our findings
reveal the dependence of the topological phase with respect to the alloy
concentration and robustness with respect distribution of Hg. Through a
combination of our ab-initio results and a defect wave function percolation
model, we estimate the random alloy concentration threshold for the topological
transition to be only 9%. Our results expand the possible search for
non-trivial topological phases in random alloy systems.


  The top-quark mass is measured in the all-hadronic top-antitop quark decay
channel using proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$
= 8 TeV with the ATLAS detector at the CERN Large Hadron Collider. The data set
used in the analysis corresponds to an integrated luminosity of 20.2 fb$^{-1}$.
The large multi-jet background is modelled using a data-driven method. The
top-quark mass is obtained from template fits to the ratio of the three-jet to
the dijet mass. The three-jet mass is obtained from the three jets assigned to
the top quark decay. From these three jets the dijet mass is obtained using the
two jets assigned to the W boson decay. The top-quark mass is measured to be
173.72 $\pm$ 0.55 (stat.) $\pm$ 1.01 (syst.) GeV.


  We are concerned with a distributed approach to solve multi-cluster games
arising in multi-agent systems. In such games, agents are separated into
distinct clusters. The agents belonging to the same cluster cooperate with each
other to achieve a common cluster goal while a non-cooperative game is played
between the clusters. To be able to deal with the sparsity of information, as
each agent only knows a specific part of the problem, we combine
gradient-tracking and consensus methods for information distribution into an
algorithm that can solve both the cooperative and non-cooperative problem in a
single run. The constraints of the problem are taken into account by the
corresponding projection operators and linear convergence is proven given an
appropriate constant step size. The algorithm is applied to a day-ahead power
management problem, posed as a multi-cluster game, and its efficiency is
demonstrated by simulations.


  The lattice cluster theory (LCT) for the thermodynamics of polymer systems
has recently been reformulated to treat strongly interacting self-assembling
polymers composed of fully flexible linear telechelic chains [J. Dudowicz and
K. F. Freed, J. Chem. Phys. \textbf{136}, 064902 (2012)]. Here, we further
extend the LCT for linear telechelic polymer melts to include a description of
chain semiflexibility, which is treated by introducing a bending energy penalty
whenever a pair of consecutive bonds from a single chain lies along orthogonal
directions. An analytical expression for the Helmholtz free energy is derived
for the model of semiflexible linear telechelic polymer melts. The extension
provides a theoretical tool for investigating the influence of chain stiffness
on the thermodynamics of self-assembling telechelic polymers, and for further
exploring the influence of self-assembly on glass formation in such systems.


  The Tikhonov-Phillips method is widely used for regularizing ill-posed
inverse problems mainly due to the simplicity of its formulation as an
optimization problem. The use of different penalizers in the functionals
associated to the corresponding optimization problems has originated a variety
other methods which can be considered as "variants" of the traditional
Tikhonov-Phillips method of order zero. Such is the case for instance of the
Tikhonov-Phillips method of order one, the total variation regularization
method, etc. In this article we find sufficient conditions on the penalizers in
generalized Tikhonov-Phillips functionals which guarantee existence and
uniqueness and stability of the minimizers. The particular cases in which the
penalizers are given by the bounded variation norm, by powers of seminorms and
by linear combinations of powers of seminorms associated to closed operators,
are studied. Several examples are presented and a few results on image
restoration are shown.


  Constructing accurate and generalizable approximators for complex
physico-chemical processes exhibiting highly non-smooth dynamics is
challenging. In this work, we propose new developments and perform comparisons
for two promising approaches: manifold-based polynomial chaos expansion (m-PCE)
and the deep neural operator (DeepONet), and we examine the effect of
over-parameterization on generalization. We demonstrate the performance of
these methods in terms of generalization accuracy by solving the 2D
time-dependent Brusselator reaction-diffusion system with uncertainty sources,
modeling an autocatalytic chemical reaction between two species. We first
propose an extension of the m-PCE by constructing a mapping between latent
spaces formed by two separate embeddings of input functions and output QoIs. To
enhance the accuracy of the DeepONet, we introduce weight self-adaptivity in
the loss function. We demonstrate that the performance of m-PCE and DeepONet is
comparable for cases of relatively smooth input-output mappings. However, when
highly non-smooth dynamics is considered, DeepONet shows higher accuracy. We
also find that for m-PCE, modest over-parameterization leads to better
generalization, both within and outside of distribution, whereas aggressive
over-parameterization leads to over-fitting. In contrast, an even highly
over-parameterized DeepONet leads to better generalization for both smooth and
non-smooth dynamics. Furthermore, we compare the performance of the above
models with another operator learning model, the Fourier Neural Operator, and
show that its over-parameterization also leads to better generalization. Our
studies show that m-PCE can provide very good accuracy at very low training
cost, whereas a highly over-parameterized DeepONet can provide better accuracy
and robustness to noise but at higher training cost. In both methods, the
inference cost is negligible.


  The Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state in quasi-one-dimensional
systems with warped Fermi surfaces is examined in strong parallel magnetic
fields. It is shown that the state is extremely stable for field directions
around nontrivial optimum directions, at which the upper critical field
exhibits cusps, and that the stabilization is due to a Fermi-surface effect
analogous to the nesting effect for the spin density wave and charge density
wave. Interestingly, the behavior with cusps is analogous to that in a square
lattice system in which the hole density is controlled. For the organic
superconductor (TMTSF)_2ClO_4, when the hopping parameters obtained by previous
authors based on X-ray crystallography results are assumed, the optimum
directions are in quadrants consistent with the previous experimental
observations. Furthermore, near this set of parameters, we also find sets of
hopping parameters that more precisely reproduce the observed optimum in-plane
field directions. These results are consistent with the hypothesis that the
FFLO state is realized in the organic superconductor.


  The electron distribution of open-ended single-walled carbon nanotubes with
chirality indexes (7,0) and (5,5) in the field emission conditions was
calculated via a multi-scaled algorithm. The field emission images were
produced numerically. It was found that the emission patterns change with the
applied macroscopic field. Especially, the symmetry of the emission pattern of
the (7,0) carbon nanotube is breaking in the lower field but the breaking is
less obvious in the higher field. The enlargement factor increases with the
applied macroscopic field.


  The kaon energy in a nuclear medium and its dependence on kaon-nucleon and
nucleon-nucleon correlations is discussed. The transition from the Lenz
potential at low densities to the Hartree potential at high densities can be
calculated analytically by making a Wigner-Seitz cell approximation and
employing a square well potential. As the Hartree potential is less attractive
than the Lenz one, kaon condensation inside cores of neutron stars appears to
be less likely than previously estimated.


  In this paper we present a differential semantics of Lazy AR Propagation
(LARP) in discrete Bayesian networks. We describe how both single and multi
dimensional partial derivatives of the evidence may easily be calculated from a
junction tree in LARP equilibrium. We show that the simplicity of the
calculations stems from the nature of LARP. Based on the differential semantics
we describe how variable propagation in the LARP architecture may give access
to additional partial derivatives. The cautious LARP (cLARP) scheme is derived
to produce a flexible cLARP equilibrium that offers additional opportunities
for calculating single and multidimensional partial derivatives of the evidence
and subsets of the evidence from a single propagation. The results of an
empirical evaluation illustrates how the access to a largely increased number
of partial derivatives comes at a low computational cost.


  In this work, we provide an asymptotic analysis of the solutions to an
elliptic integro-differential equation. This equation describes the
evolutionary equilibria of a phenotypically structured population, subject to
selection, mutation, and both local and non-local dispersion in a spatially
heterogeneous, possibly patchy, environment. Considering small effects of
mutations, we provide an asymptotic description of the equilibria of the
phenotypic density. This asymptotic description involves a Hamilton-Jacobi
equation with constraint coupled with an eigenvalue problem. Based on such
analysis, we characterize some qualitative properties of the phenotypic density
at equilibrium depending on the heterogeneity of the environment. In
particular, we show that when the heterogeneity of the environment is low, the
population concentrates around a single phenotypic trait leading to a unimodal
phenotypic distribution. On the contrary, a strong fragmentation of the
environment leads to multi-modal phenotypic distributions.


  We discuss the efficient computation of performance, reliability, and
availability measures for Markov chains; these metrics, and the ones obtained
by combining them, are often called performability measures. We show that this
computational problem can be recasted as the evaluation of a bilinear forms
induced by appropriate matrix functions, and thus solved by leveraging the fast
methods available for this task. We provide a comprehensive analysis of the
theory required to translate the problem from the language of Markov chains to
the one of matrix functions. The advantages of this new formulation are
discussed, and it is shown that this setting allows to easily study the
sensitivities of the measures with respect to the model parameters. Numerical
experiments confirm the effectiveness of our approach; the tests we have run
show that we can outperform the solvers available in state of the art
commercial packages on a representative set of large scale examples.


  We study inhomogeneous one-dimensional Hubbard systems using the density
matrix renormalization group method. Different heterostructures are
investigated whose configuration is modeled varying parameters like the on-site
Coulomb potential and introducing local confining potentials. We investigate
their Luttinger liquid properties through the parameter K_rho, which
characterizes the decay of the density-density correlation function at large
distances. Our main goal is the investigation of possible realization of
engineered materials and the ability to manipulate physical properties by
choosing an appropriate spatial and/or chemical modulation.


  Cancer is one of the diseases that kill the most women in the world, with
breast cancer being responsible for the highest number of cancer cases and
consequently deaths. However, it can be prevented by early detection and,
consequently, early treatment. Any development for detection or perdition this
kind of cancer is important for a better healthy life. Many studies focus on a
model with high accuracy in cancer prediction, but sometimes accuracy alone may
not always be a reliable metric. This study implies an investigative approach
to studying the performance of different machine learning algorithms based on
boosting to predict breast cancer focusing on the recall metric. Boosting
machine learning algorithms has been proven to be an effective tool for
detecting medical diseases. The dataset of the University of California, Irvine
(UCI) repository has been utilized to train and test the model classifier that
contains their attributes. The main objective of this study is to use
state-of-the-art boosting algorithms such as AdaBoost, XGBoost, CatBoost and
LightGBM to predict and diagnose breast cancer and to find the most effective
metric regarding recall, ROC-AUC, and confusion matrix. Furthermore, our study
is the first to use these four boosting algorithms with Optuna, a library for
hyperparameter optimization, and the SHAP method to improve the
interpretability of our model, which can be used as a support to identify and
predict breast cancer. We were able to improve AUC or recall for all the models
and reduce the False Negative for AdaBoost and LigthGBM the final AUC were more
than 99.41\% for all models.


  Deep candidate generation (DCG) that narrows down the collection of relevant
items from billions to hundreds via representation learning has become
prevalent in industrial recommender systems. Standard approaches approximate
maximum likelihood estimation (MLE) through sampling for better scalability and
address the problem of DCG in a way similar to language modeling. However, live
recommender systems face severe exposure bias and have a vocabulary several
orders of magnitude larger than that of natural language, implying that MLE
will preserve and even exacerbate the exposure bias in the long run in order to
faithfully fit the observed samples. In this paper, we theoretically prove that
a popular choice of contrastive loss is equivalent to reducing the exposure
bias via inverse propensity weighting, which provides a new perspective for
understanding the effectiveness of contrastive learning. Based on the
theoretical discovery, we design CLRec, a contrastive learning method to
improve DCG in terms of fairness, effectiveness and efficiency in recommender
systems with extremely large candidate size. We further improve upon CLRec and
propose Multi-CLRec, for accurate multi-intention aware bias reduction. Our
methods have been successfully deployed in Taobao, where at least four-month
online A/B tests and offline analyses demonstrate its substantial improvements,
including a dramatic reduction in the Matthew effect.


  Sr$_2$IrO$_4$ is an extensively studied spin-orbit coupling induced insulator
with antiferromagnetic ground state. The delicate balance between competing
energy scales plays crucial role for its low temperature phase, and the route
of chemical substitution has often been used to tune these different energy
scales. Here, we report an evolution of structural, magnetic and electronic
properties in doped Sr$_2$Ir$_{1-x}$Cu$_x$O$_4$ ($x$ $\leq$ 0.2). The
substitution of Cu$^{2+}$ (3$d^9$) for Ir$^{4+}$ (5$d^5$) acts for electron
doping, though it tunes the related parameters such as, spin-orbit coupling,
electron correlation and Ir charge state. Moreover, both Ir$^{4+}$ and
Cu$^{2+}$ has single unpaired spin though it occupies different $d$-orbitals.
With Cu substitution, system retains its original structural symmetry but the
structural parameters show systematic changes. X-ray photoemission spectroscopy
measurements show Ir$^{4+}$ equivalently converts to Ir$^{5+}$ and a
significant enhancement in the density of states has been observed at the Fermi
level due to the contribution from the Cu 3$d$ orbitals, which supports the
observed decrease in the resistivity with Cu substitution. While the long-range
magnetic ordering is much weakened and the highest doped sample shows almost
paramagnetic-like behavior the overall system remains insulator. Analysis of
resistivity data shows mode of charge conduction in whole series follows
2-dimensional variable-range-hopping model but the range of validity varies
with temperature. Whole series of samples exhibit negative magnetoresistance at
low temperature which is considered to be a signature of weak localization
effect in spin-orbit coupled system, and its evolution with Cu appears to
follow the variation of resistivity with $x$.


  In this paper we study elliptic curves which have a number of points whose
coordinates are in arithmetic progression. We first motivate this diophantine
problem, prove some results, provide a number of interesting examples and,
finally point out open questions which focus on the most interesting aspects of
the problem for us.


  Over the years, web content has evolved from simple text and static images
hosted on a single server to a complex, interactive and multimedia-rich content
hosted on different servers. As a result, a modern website during its loading
time fetches content not only from its owner's domain but also from a range of
third-party domains providing additional functionalities and services. Here, we
infer the network of the third-party domains by observing the domains'
interactions within users' browsers from all over the globe. We find that this
network possesses structural properties commonly found in complex networks,
such as power-law degree distribution, strong clustering, and small-world
property. These properties imply that a hyperbolic geometry underlies the
ecosystem's topology. We use statistical inference methods to find the domains'
coordinates in this geometry, which abstract how popular and similar the
domains are. The hyperbolic map we obtain is meaningful, revealing the
large-scale organization of the ecosystem. Furthermore, we show that it
possesses predictive power, providing us the likelihood that third-party
domains are co-hosted; belong to the same legal entity; or merge under the same
entity in the future in terms of company acquisition. We also find that
complementarity instead of similarity is the dominant force driving future
domains' merging. These results provide a new perspective on understanding the
ecosystem's organization and performing related inferences and predictions.


  A variational solution of the coupled electron-phonon Boltzmann equations is
used to calculate the phonon drag contribution to the thermopower in a 1-D
system. A simple formula is derived for the temperature dependence of the
phonon drag in metallic, single-walled carbon nanotubes. Scattering between
different electronic bands yields nonzero values for the phonon drag as the
Fermi level varies.


  Molybdenum disulphide (MoS$_2$) has attracted much interest in recent years
due to its potential applications in a new generation of electronic devices.
Recently, it was shown that thin films of MoS$_2$ can become superconducting
with a highest $T_{c}$ of 10K when the material is heavily gated to the
conducting regime. In this work, using the group theoretical approach, we
determine the possible pairing symmetries of heavily gated MoS$_2$. Depending
on the electron-electron interactions, the material can support an exotic
spin-singlet $p +ip $-wave-like, an exotic spin-triplet s-wave-like and an
conventional spin-triplet $p$-wave pairing phases. Importantly, the exotic
spin-singlet $p+ip$-wave phase is a topological superconducting phase which
breaks time-reversal symmetry spontaneously and possesses chiral Majorana edge
states.


  Research on fractal networks is a dynamically growing field of network
science. A central issue is to analyze fractality with the so-called
box-covering method. As this problem is known to be NP-hard, a plethora of
approximating algorithms have been proposed throughout the years. This study
aims to establish a unified framework for comparing approximating box-covering
algorithms by collecting, implementing, and evaluating these methods in various
aspects including running time and approximation ability. This work might also
serve as a reference for both researchers and practitioners, allowing fast
selection from a rich collection of box-covering algorithms with a publicly
available codebase.


  We study smooth projective varieties with small dual variety using methods
from symplectic topology. We prove the affine parts of such varieties are
subcritical, and that the hyperplane class is invertible in their quantum
cohomology. We derive several topological and algebraic geometric consequences
from that. The main tool in our work is the Seidel representation associated to
Hamiltonian fibrations.


  We introduce an exact mapping of Clifford (stabilizer) random tensor networks
(RTNs) and monitored quantum circuits, onto a statistical mechanics model. With
Haar unitaries, the fundamental degrees of freedom ('spins') are permutations
because all operators commuting with the action of the unitaries on a tensor
product arise from permutations of the tensor factors ('Schur-Weyl duality').
For unitaries restricted to the smaller Clifford group, the set of commuting
operators, the 'commutant', forming the new 'spin' degrees of freedom, will be
larger. We use the recent full characterization of this commutant by Gross et
al., Comm. Math. Phys. 385, 1325 (2021), to construct the Clifford statistical
mechanics models for on-site Hilbert space dimensions which are powers of a
prime number $p$. We show that the Boltzmann weights are invariant under a
symmetry group involving orthogonal matrices with entries in the finite number
field ${\bf F}_p$. This implies that the symmetry group, and consequently all
universal properties of entanglement transitions in Clifford circuits and RTNs
will in general depend on, and only on the prime $p$. We show that Clifford
monitored circuits with on-site Hilbert space dimension $d=p^M$ are described
by percolation in the limits $d \to \infty$ at (a) $p=$ fixed but $M\to
\infty$, and at (b) $M= 1$ but $p \to \infty$. In the limit (a) we calculate
the effective central charge, and in the limit (b) we derive the following
universal minimal cut entanglement entropy $S_A =(\sqrt{3}/\pi)\ln p \ln L_A$
for $d=p$ large at the transition. We verify those predictions numerically, and
present extensive numerical results for critical exponents at the transition in
monitored Clifford circuits for prime number on-site Hilbert space dimension
$d=p$ for a variety of different values of $p$, and find that they approach
percolation values at large $p$.


  We introduce a polynomial spectral calculus that follows from the summation
by parts property of the Legendre-Gauss-Lobatto quadrature. We use the calculus
to simplify the analysis of two multidimensional discontinuous Galerkin
spectral element approximations.


  In quantum computation, amplitude estimation is a fundamental subroutine that
is utilized in various quantum algorithms. A general important task of such
estimation problems is to characterize the estimation lower bound, which is
referred to as quantum Cram\'er-Rao bound (QCRB), and to construct an optimal
estimator that achieves QCRB. This paper studies the amplitude estimation in
the presence of depolarizing noise with unknown intensity. The main difficulty
in this problem is that the optimal measurement depends on both the unknown
quantum state and the amplitude we aim to estimate. To deal with these issues,
we utilize the variational quantum circuits to approximate the (unknown)
optimal measurement basis combined with the 2-step adaptive estimation strategy
which was proposed in the quantum estimation theory.We numerically show that
the proposed method can nearly attain the QCRB.


  The implementation of screened hybrid functionals into the WIEN2k code, which
is based on the LAPW basis set, is reported. The Hartree-Fock exchange energy
and potential are screened by means of the Yukawa potential as proposed by
Bylander and Kleinman [Phys. Rev. B 41, 7868 (1990)] for the calculation of the
electronic structure of solids with the screened-exchange local density
approximation. Details of the formalism, which is based on the method of
Massidda, Posternak, and Baldereschi [Phys. Rev. B 48, 5058 (1993)] for the
unscreened Hartree-Fock exchange are given. The results for the
transition-energy and structural properties of several test cases are
presented. Results of calculations of the Cu electric-field gradient in Cu2O
are also presented, and it is shown that the hybrid functionals are much more
accurate than the standard local-density or generalized gradient
approximations.


  Most baryonic matter resides in the intergalactic medium (IGM), a diffuse gas
primarily composed of ionized hydrogen and helium, filling the space between
galaxies. Observations of such an environment are crucial to better
understanding the physical processes involved in such an environment. We
present an analysis of the IGM absorption using blazar spectra from the first
eROSITA all-sky survey (eRASS1) performed onboard of the
Spectrum-Roentgen-Gamma mission (SRG) and {\it XMM-Newton} X-ray observations.
First, we fitted the continuum spectra using a log-parabolic spectrum model and
fixed the Galactic absorption. Then, we included a collisional ionization
equilibrium model, namely {\tt IONeq}, to account for the IGM absorption. The
column density $N({\rm H})$ and metallicity ($Z$) were set as free parameters.
At the same time, the redshift of the absorber was fixed to half the blazar
redshift as an approximation of the full line-of-sight absorber. We measured
IGM-$N({\rm H})$ for 147 sources for SRG and 10 sources for {\it XMM-Newton}.
We found a clear trend between IGM-$N({\rm H})$ and the blazar redshifts which
scales as $(1+z)^{1.63\pm 0.12}$. The mean hydrogen density at $z=0$ is
$n_{0}=(2.75\pm 0.63)\times 10^{-7}$ cm$^{-3}$. The mean temperature over the
redshift range is $\log(T/K)=5.6\pm 0.6$ while the mean metallicity is
$Z=0.16\pm 0.09$. We found no acceptable fit using a power-law model for either
temperatures or metallicities as a function of the redshift. These results
indicate that the IGM contributes substantially to the total absorption seen in
the blazar spectra.


  We study a lattice sigma model which is expected to reflect Anderson
localization and delocalization transition for real symmetric band matrices in
3D, but describes the mixing measure for a vertex reinforced jump process too.
For this model we prove exponential localization at any temperature in a strip,
and more generally in any quasi-one dimensional graph, with pinning (mass) at
only one site. The proof uses a Mermin-Wagner type argument and a transfer
operator approach.


  We investigate observable signatures of a first-order quantum chromodynamics
(QCD) phase transition in the context of core collapse supernovae. To this end,
we conduct axially symmetric numerical relativity simulations with multi-energy
neutrino transport, using a hadron-quark hybrid equation of state (EOS). We
consider four non-rotating progenitor models, whose masses range from $9.6$ to
$70$ M$_\odot$. We find that the two less massive progenitor stars (9.6 and
11.2 M$_\odot$) show a successful explosion, which is driven by the neutrino
heating. They do not undergo the QCD phase transition and leave behind a
neutron star (NS). As for the more massive progenitor stars (50 and 70
M$_\odot$), the proto-neutron star (PNS) core enters the phase transition
region and experiences the second collapse. Because of a sudden stiffening of
the EOS entering to the pure quark matter regime, a strong shock wave is formed
and blows off the PNS envelope in the 50 M$_\odot$ model. Consequently, the
remnant becomes a quark core surrounded by hadronic matters, leading to the
formation of the hybrid star. However for the 70 M$_\odot$ model, the shock
wave cannot overcome the continuous mass accretion and it readily becomes a
black hole. We find that the neutrino and gravitational wave (GW) signals from
supernova explosions driven by the hadron-quark phase transition are detectable
for the present generation of neutrino and GW detectors. Furthermore, the
analysis of the GW detector response reveals unique kHz signatures, which will
allow us to distinguish this class of supernova explosions from failed and
neutrino-driven explosions.


  In this paper, we present and prove some generalizations of some inequalities
for the $p$-Gamma, $q$-Gamma and $k$-Gamma functions. Our approach makes use of
the series representations of the psi, $p$-psi, $q$-psi and $k$-psi functions.


  We study the enumerativity of Gromov-Witten invariants where the domain curve
is fixed in moduli and required to pass through the maximum possible number of
points. We say a Fano manifold satisfies asymptotic enumerativity if such
invariants are enumerative whenever the degree of the curve is sufficiently
large. Lian and Pandharipande speculate that every Fano manifold satisfies
asymptotic enumerativity. We give the first counterexamples, as well as some
new examples where asymptotic enumerativity holds. The negative examples
include special hypersurfaces of low Fano index and certain projective bundles,
and the new positive examples include many Fano threefolds and all smooth
hypersurfaces of degree $d \leq (n+3)/3$ in $\mathbb{P}^n$.


  An explicit formula is derived for the electromagnetic (EM) field scattered
by one small impedance particle $D$ of an arbitrary shape. If $a$ is the
characteristic size of the particle, $\lambda$ is the wavelength, $a<<\lambda$
and $\zeta$ is the boundary impedance of $D$, $[N,[E,N]]=\zeta [N,H]$ on $S$,
where $S$ is the surface of the particle, $N$ is the unit outer normal to $S$,
and $E$, $H$ is the EM field, then the scattered field is $E_{sc}=[\nabla
g(x,x_1), Q]$. Here $g(x,y)=\frac{e^{ik|x-y|}}{4\pi |x-y|}$, $k$ is the wave
number, $x_1\in D$ is an arbitrary point, and $Q=-\frac{\zeta |S|}{i\omega
\mu}\tau \nabla \times E_0$, where $E_0$ is the incident field, $|S|$ is the
area of $S$, $\omega$ is the frequency, $\mu$ is the magnetic permeability of
the space exterior to $D$, and $\tau$ is a tensor which is calculated
explicitly. The scattered field is $O(|\zeta| a^2)>> O(a^3)$ as $a\to 0$ when
$\lambda$ is fixed and $\zeta$ does not depend on $a$. Thus, $|E_{sc}|$ is much
larger than the classical value $O(a^3)$ for the field scattered by a small
particle. It is proved that the effective field in the medium, in which many
small particles are embedded, has a limit as $a\to 0$ and the number $M=M(a)$
of the particles tends to $\infty$ at a suitable rate. Thislimit solves a
linear integral equation. The refraction coefficient of the limiting medium is
calculated analytically. This yields a recipe for creating materials with a
desired refraction coefficient.


  We numerically and experimentally show that all photons generated by
spontaneous parametric down-conversion (SPDC) follow a transverse amplitude
similar to that of the pump. This amplitude transfer from pump to SPDC is
revealed in the Fourier image plane of the down-converted photons restricted by
an aperture. We also observe a considerable shift of the image plane from the
actual Fourier plane, when size of the aperture is gradually increased. The
shift of the Fourier image of down-converted photons affects the quality of
spatial mode-based projection in various quantum correlation experiments with
parametric down-converted photon pairs. The results may be useful in
applications of down-converted photons for quantum imaging and quantum
communication.


  This paper studies certain embedded spheres in closed affine manifolds. For
$n \geq 3$, we investigate the dome bodies in a closed affine $n$-manifold $M$
with its boundary homeomorphic to a sphere under the assumption that a
developing map restricted to a component of $\partial\hat{M}$ is an embedding
onto a strictly convex sphere in $\mathbb{A}^n$. By using the recurrent
property of an incomplete geodesic we show that dome bodies are compact. Then a
maximal dome body is a closed solid ball bounded by a component of
$\partial\hat{M}$, and hence equals $\hat{M}$. The main theorem is that the
standard ball in an affine space can only bound one compact affine manifold
inside, namely the solid ball.


  The Yang-Lee edge singularity is an intriguing critical phenomenon
characterized by nonunitary field theory. However, its experimental realization
for interacting many-body systems remains elusive. We show that Yang-Lee edge
singularities, regarded as many-body exceptional points, can be observed using
both the self-normal and the associated-biorthogonal Loschmidt echoes,
leveraging the advantages of nonunitary dynamics in non-Hermitian systems. The
Loschmidt echoes are demonstrated to display unitary dynamics in the
$\mathcal{PT}$-symmetric regime but exhibit nonunitary dynamics in the
$\mathcal{PT}$ symmetry-broken regime, leading to a sharp change near an
exceptional point. We hereby identify exceptional points in both the
non-Hermitian transverse field Ising model and the Yang-Lee model, and
determine the critical exponent that is consistent with nonunitary conformal
field theory. This work provides a direct observation of Yang-Lee edge
singularities in non-Hermitian many-body systems arising from nonunitary
dynamics.


  The post-2020 global biodiversity framework needs ambitious, research-based
targets. Estimating the accelerated extinction risk due to climate change is
critical. The International Union for Conservation of Nature (IUCN) measures
the extinction risk of species. Automatic methods have been developed to
provide information on the IUCN status of under-assessed taxa. However, these
compensatory methods are based on current species characteristics, mainly
geographical, which precludes their use in future projections. Here, we
evaluate a novel method for classifying the IUCN status of species benefiting
from the generalisation power of species distribution models based on deep
learning. Our method matches state-of-the-art classification performance while
relying on flexible SDM-based features that capture species' environmental
preferences. Cross-validation yields average accuracies of 0.61 for status
classification and 0.78 for binary classification. Climate change will reshape
future species distributions. Under the species-environment equilibrium
hypothesis, SDM projections approximate plausible future outcomes. Two extremes
of species dispersal capacity are considered: unlimited or null. The projected
species distributions are translated into features feeding our IUCN
classification method. Finally, trends in threatened species are analysed over
time and i) by continent and as a function of average ii) latitude or iii)
altitude. The proportion of threatened species is increasing globally, with
critical rates in Africa, Asia and South America. Furthermore, the proportion
of threatened species is predicted to peak around the two Tropics, at the
Equator, in the lowlands and at altitudes of 800-1,500 m.


  The fist documented speculations on light were found in oriental and Greek
schools of philosophy. The investigations on the light in India were rooted way
back to the ancient era. The Indian Samkhya, Nyaya, and Vaisheshika identified
light or fie (Tejas) as one of the key elements among the fie elementary things
of the universe. The pioneering results of optics and spectroscopy were
witnessed in the era of stellar people like Sir Jagadish Chandra Bose and Sir C
V Raman. The research has then taken a new directive into the development of
nonlinear optics and photonics after the invention of the laser. The present
article reviews the past few decades pioneering works of Prof. D Narayana Rao,
an experimental physicist, in the context of optics and photonics in India. The
most notable contributions of Prof Rao, introduced in India for the fist time,
are white-light interferometry, degenerate four-wave mixing (DFWM), electric
field induced second harmonic generation (EFISHG), incoherent laser
spectroscopy (using dye laser), and femtosecond lasers for creating
nano/microstructures.


  Given a $D$-module $M$ generated by a single element, and a polynomial $f$,
one can construct several $D$-modules attached to $M$ and $f$ and can define
the notion of the (generalized) $b$-function following M. Kashiwara. These
modules are closely related to the localization and the local cohomology of
$M$. We show that the $b$-function, if it exists, controls these modules and
present general algorithms for computing these modules and the $b$-function (if
it exists) without any further assumptions. For these algorithms, we
reformulate the localization algorithm for $D$-modules.


  Solving inverse problems continues to be a challenge in a wide array of
applications ranging from deblurring, image inpainting, source separation etc.
Most existing techniques solve such inverse problems by either explicitly or
implicitly finding the inverse of the model. The former class of techniques
require explicit knowledge of the measurement process which can be unrealistic,
and rely on strong analytical regularizers to constrain the solution space,
which often do not generalize well. The latter approaches have had remarkable
success in part due to deep learning, but require a large collection of
source-observation pairs, which can be prohibitively expensive. In this paper,
we propose an unsupervised technique to solve inverse problems with generative
adversarial networks (GANs). Using a pre-trained GAN in the space of source
signals, we show that one can reliably recover solutions to under determined
problems in a `blind' fashion, i.e., without knowledge of the measurement
process. We solve this by making successive estimates on the model and the
solution in an iterative fashion. We show promising results in three
challenging applications -- blind source separation, image deblurring, and
recovering an image from its edge map, and perform better than several
baselines.


  Apparent parallels between natural language and biological sequence have led
to a recent surge in the application of deep language models (LMs) to the
analysis of antibody and other biological sequences. However, a lack of a
rigorous linguistic formalization of biological sequence languages, which would
define basic components, such as lexicon (i.e., the discrete units of the
language) and grammar (i.e., the rules that link sequence well-formedness,
structure, and meaning) has led to largely domain-unspecific applications of
LMs, which do not take into account the underlying structure of the biological
sequences studied. A linguistic formalization, on the other hand, establishes
linguistically-informed and thus domain-adapted components for LM applications.
It would facilitate a better understanding of how differences and similarities
between natural language and biological sequences influence the quality of LMs,
which is crucial for the design of interpretable models with extractable
sequence-functions relationship rules, such as the ones underlying the antibody
specificity prediction problem. Deciphering the rules of antibody specificity
is crucial to accelerating rational and in silico biotherapeutic drug design.
Here, we formalize the properties of the antibody language and thereby
establish not only a foundation for the application of linguistic tools in
adaptive immune receptor analysis but also for the systematic immunolinguistic
studies of immune receptor specificity in general.


  A new selection phenomenon in nonlinear interface dynamics is predicted. A
generic class of exact regular unsteady multi-bubble solutions in a Hele-Shaw
cell is presented. These solutions show that the case where the asymptotic
bubble velocity, $U$, is twice greater than the velocity, $V$, of the uniform
background flow, i.e., $U = 2V$, is the only attractor of the dynamics.
Contrary to common belief, the predicted velocity selection requires neither
surface tension nor other external regularization.


  In this study, a new linear theory of tearing instability is shown, where the
modified LSC (Loureiro, Schekochihin, and Cowley) theory [36] developed from
the original LSC theory [8] is extended from inviscid-resistive MHD to
viscous-resistive MHD. In contrast to FKR [2] and original LSC theories, the
upstream open boundary condition is implemented at a finite point $\xi_c$,
which is an additional control parameter to determine the solutions. This paper
firstly studies when the resistivity and viscosity are uniform in space. In
addition, some variations in the nonuniformity are studied. It is shown that
the non-uniformity can enhance the linear growth rate, rather than uniform
case. Unexpectedly, this suggests that the forward cascade process of plasmoid
instability (PI) does not stop, i.e., the finite differential MHD simulations
fail. To stop the forward cascade, uniform viscosity is required not only in
the inner region of the current sheet but also in the outer region. In the
uniform case, the critical condition is predicted to be $2P_m/(S
\xi_{c})=0.06$, beyond which the tearing instability, i.e., the forward
cascade, stops. Here, $S$ is the Lundquist number, $P_m$ is the magnetic
Prandtl number, and $\xi_{c}$ is the distance between the upstream open
boundary and neutral sheet, where the current sheet thickness is fixed at
$\xi_0=1.307$. According to the critical condition, the resistivity and
viscosity employed in most MHD simulations of PI are too small to stop the
forward cascade. This critical condition may be also applicable for the trigger
problem of the current sheet destabilization in substorms and solar flares.


  The human mind is constituted by inner, subjective, private, first-person
conscious experiences that cannot be measured with physical devices or observed
from an external, objective, public, third-person perspective. The qualitative,
phenomenal nature of conscious experiences also cannot be communicated to
others in the form of a message composed of classical bits of information.
Because in a classical world everything physical is observable and
communicable, it is a daunting task to explain how an empirically unobservable,
incommunicable consciousness could have any physical substrates such as neurons
composed of biochemical molecules, water, and electrolytes. The challenges
encountered by classical physics are exemplified by a number of thought
experiments including the inverted qualia argument, the private language
argument, the beetle in the box argument and the knowledge argument. These
thought experiments, however, do not imply that our consciousness is
nonphysical and our introspective conscious testimonies are untrustworthy. The
principles of classical physics have been superseded by modern quantum physics,
which contains two fundamentally different kinds of physical objects:
unobservable quantum state vectors, which define what physically exists, and
quantum operators (observables), which define what can physically be observed.
Identifying consciousness with the unobservable quantum information contained
by quantum physical brain states allows for application of quantum information
theorems to resolve possible paradoxes created by the inner privacy of
conscious experiences, and explains how the observable brain is constructed by
accessible bits of classical information that are bound by Holevo's theorem and
extracted from the physically existing quantum brain upon measurement with
physical devices.


  We investigate the evolution of non-linear density perturbations by taking
into account the effects of deviations from spherical symmetry of a system.
Starting from the standard spherical top hat model in which these effects are
ignored, we introduce a physically motivated closure condition which specifies
the dependence of the additional terms on the density contrast, $\delta$. The
modified equation can be used to model the behaviour of an overdense region
over a sufficiently large range of $\delta$. The key new idea is a Taylor
series expansion in ($1/\delta$) to model the non-linear epoch. We show that
the modified equations quite generically lead to the formation of stable
structures in which the gravitational collapse is halted at around the virial
radius. The analysis also allows us to connect up the behaviour of individual
overdense regions with the non-linear scaling relations satisfied by the two
point correlation function.


  The PHENIX Collaboration has measured the ratio of the yields of $\psi(2S)$
to $\psi(1S)$ mesons produced in $p$$+$$p$, $p$$+$Al, $p$$+$Au, and
$^{3}$He$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV over the forward and
backward rapidity intervals $1.2<|y|<2.2$. We find that the ratio in $p$$+$$p$
collisions is consistent with measurements at other collision energies. In
collisions with nuclei, we find that in the forward ($p$-going or
$^{3}$He-going) direction, the relative yield of $\psi(2S)$ mesons to
$\psi(1S)$ mesons is consistent with the value measured in \pp collisions.
However, in the backward (nucleus-going) direction, the $\psi(2S)$ is
preferentially suppressed by a factor of $\sim$2. This suppression is
attributed in some models to breakup of the weakly-bound $\psi(2S)$ through
final state interactions with comoving particles, which have a higher density
in the nucleus-going direction. These breakup effects may compete with color
screening in a deconfined quark-gluon plasma to produce sequential suppression
of excited quarkonia states.


  Ion-Sensitive Field-Effect Transistors (ISFETs) form a wide-spread technology
for sensing, thanks to their label-free detection and intrinsic CMOS
compatibility. Their current sensitivity, {\Delta}ID/ID, for a given
{\Delta}pH, however, is limited by the thermionic limit for the Subthreshold
Slope (SS) of Metal-Oxide-Semiconductor Field-Effect Transistors(MOSFET) and by
the Nernst limit. Obtaining ISFETs with a steep slope transfer characteristics
is extremely challenging. In this paper we combine the merits of traditional
ISFETs with the performance boosts offered by the insertion of a Negative
Capacitor in series with the Gate contact. In the proposed tests with NC PZT
capacitors, we demonstrate experimentally a reduction of the SS by 44%,
combined with a current efficiency improvement of more than two times. As a
consequence of the steeper SS, the current sensitivity to pH is improved by
78%.


  We investigate the recently proposed Kerr/CFT correspondence in the context
of heterotic string theory. The Kerr/CFT correspondence states that the
near-horizon states of an extremal four (or higher) dimensional black hole
could be identified with a certain chiral conformal field theory under the
conjecture that the central charges from the non-gravitational fields vanish.
The corresponding Virasoro algebra is generated by a class of diffeomorphisms
which preserves the appropriate boundary conditions on the near-horizon
geometry. To understand the chiral conformal field theory, we consider the
class of extremal Kerr-Sen black hole (that contains three non-gravitational
fields) as a class of solutions in the low energy limit (effective field
theory) of heterotic string theory. We derive the expression of the conserved
charges for the extremal Kerr-Sen solutions that contain dilaton, abelian gauge
filed and antisymmetric tensor filed. We confirm and extend the validity of the
conjecture (that the central charges from the non-gravitational fields vanish)
for theories including antisymmetric tensor fields. We combine the calculated
central charges with the expected form of the temperature using the Cardy
formula to obtain the entropy of the extremal black hole microscopically; in
agreement with the macroscopic Bekenstein-Hawking entropy of the extremal black
hole.


  Thermal photons are thought to be the ideal probe to measure the temperature
of the quark-gluon plasma created in heavy ion collisions. PHENIX has measured
direct photons with p_T < 5 GeV/c via their internal conversions into e+e-
pairs in Au+Au collisions at sqrt(s_NN) = 200 GeV and has now provided a
baseline measurement from p+p data.


  We investigate the electronic structure of gap and band tail states in
amorphous silicon. Starting with two 216-atom models of amorphous silicon with
defect concentration close to the experiments, we systematically study the
dependence of electron localization on basis set, density functional and spin
polarization using the first principles density functional code Siesta. We
briefly compare three different schemes for characterizing localization:
information entropy, inverse participation ratio and spatial variance. Our
results show that to accurately describe defect structures within self
consistent density functional theory, a rich basis set is necessary. Our study
revealed that the localization of the wave function associated with the defect
states decreases with larger basis sets and there is some enhancement of
localization from GGA relative to LDA. Spin localization results obtained via
LSDA calculations, are in reasonable agreement with experiment and with
previous LSDA calculations on a-Si:H models.


  Participation research in online community has concentrated on popularity and
social interactions. In this paper the attention is shifted to the
conversational trees as the focus of analysis in order to achieve a measure of
deliberative participation. Three methods to measure consistent, central and
comprehensive participation (CCCP) in online conversations are proposed.


  We generalize results of P. Schneider and U. Stuhler for GL_l+1 to a
reductive algebraic group G defined and split over a non-archimedean local
field K. Following their lines, we prove that the generalized Steinberg
representations of G with coefficients in any abelian group are cyclic. When G
is semi-simple of adjoint type, we give an expression of these representations,
whenever it is possible and in particular for those that are of maximal degree,
in terms of the parahoric subgroups of G.


  We study a class of early dark energy models which has substantial amount of
dark energy in the early epoch of the universe. We examine the impact of the
early dark energy fluctuations on the growth of structure and the CMB power
spectrum in the linear approximation. Furthermore we investigate the influence
of the interaction between the early dark energy and the dark matter and its
effect on the structure growth and CMB. We finally constrain the early dark
energy model parameters and the coupling between dark sectors by confronting to
different observations.


  In this work we provide a thorough examination of the nonlinear dielectric
properties of a succinonitrile-glutaronitrile mixture, representing one of the
rare example of a plastic crystal with fragile glassy dynamics. The detected
alteration of the complex dielectric permittivity under high fields can be
explained considering the heterogeneous nature of glassy dynamics and a
field-induced variation of entropy. While the first mechanism was also found in
structural glass formers, the latter effect seems to be typical for plastic
crystals. Morover, the third harmonic component of the dielectric
susceptibility is reported, revealing a spectral shape as predicted for
cooperative molecular dynamics. In accord with the fragile nature of the glass
transition in this plastic crystal, we deduce a relatively strong temperature
dependence of the number of correlated molecules, in contrast to the much
weaker temperature dependence in plastic-crystalline cyclo-octanol, whose glass
transition is of strong nature.