  We study the problem of knowledge tracing (KT) where the goal is to trace the
students' knowledge mastery over time so as to make predictions on their future
performance. Owing to the good representation capacity of deep neural networks
(DNNs), recent advances on KT have increasingly concentrated on exploring DNNs
to improve the performance of KT. However, we empirically reveal that the DNNs
based KT models may run the risk of overfitting, especially on small datasets,
leading to limited generalization. In this paper, by leveraging the current
advances in adversarial training (AT), we propose an efficient AT based KT
method (ATKT) to enhance KT model's generalization and thus push the limit of
KT. Specifically, we first construct adversarial perturbations and add them on
the original interaction embeddings as adversarial examples. The original and
adversarial examples are further used to jointly train the KT model, forcing it
is not only to be robust to the adversarial examples, but also to enhance the
generalization over the original ones. To better implement AT, we then present
an efficient attentive-LSTM model as KT backbone, where the key is a proposed
knowledge hidden state attention module that adaptively aggregates information
from previous knowledge hidden states while simultaneously highlighting the
importance of current knowledge hidden state to make a more accurate
prediction. Extensive experiments on four public benchmark datasets demonstrate
that our ATKT achieves new state-of-the-art performance. Code is available at:
\color{blue} {\url{https://github.com/xiaopengguo/ATKT}}.


  The GERDA experiment searches for neutrinoless double beta ($0\nu\beta\beta$)
decay in $^{76}$Ge using an array of high purity germanium (HPGe) detectors
immersed in liquid argon (LAr). Phase II of the experiment uses 30 new broad
energy germanium (BEGe) detectors with superior pulse shape discrimination
capabilities compared to the previously used semi-coaxial detector design. By
far the largest background component for BEGe detectors in GERDA are
n$^+$-surface events from $^{42}$K $\beta$ decays which are intrinsic in LAr.
The $\beta$ particles with up to 3.5 MeV can traverse the 0.5 to 0.9 mm thick
electrode and deposit energy within the region of interest for the
$0\nu\beta\beta$ decay. However, those events have particular pulse shape
features allowing for a strong discrimination. The understanding and simulation
of this background, showing a reduction by up to a factor 145 with pulse shape
discrimination alone, is presented in this work.


  This paper presents the maneuver of mouse pointer and performs various mouse
operations such as left click, right click, double click, drag etc using
gestures recognition technique. Recognizing gestures is a complex task which
involves many aspects such as motion modeling, motion analysis, pattern
recognition and machine learning. Keeping all the essential factors in mind a
system has been created which recognizes the movement of fingers and various
patterns formed by them. Color caps have been used for fingers to distinguish
it from the background color such as skin color. Thus recognizing the gestures
various mouse events have been performed. The application has been created on
MATLAB environment with operating system as windows 7.


  We study the family of ideals defined by mixed size minors of two-sided
ladders of indeterminates. We compute their Groebner bases with respect to a
skew-diagonal monomial order, then we use them to compute the height of the
ideals. We show that these ideals correspond to a family of irreducible
projective varieties, that we call mixed ladder determinantal varieties. We
show that these varieties are arithmetically Cohen-Macaulay. We characterize
the arithmetically Gorenstein ones, among those that satisfy a technical
condition. Our main result consists in proving that mixed ladder determinantal
varieties belong to the same G-biliaison class of a linear variety.


  Waste production, carbon dioxide atmospheric accumulation, and dependence on
finite natural resources are expressions of the unsustainability of the current
industrial networks that supply fuels, energy, and manufacturing products. In
particular, circular manufacturing supply chains and carbon control networks
are urgently needed. To model and design these and, in general, any material
networks, we propose to generalize the approach used for traditional networks
such as water and thermal power systems by using compartmental dynamical
thermodynamics and graph theory. The key idea is that the thermodynamic
compartments and their connections can be added, removed or modified as needed
to achieve a circular material flow. The design methodology is explained and
its application is illustrated through examples. In addition, we provide a
physics-based definition of circularity and, by implementing a nonlinear
compartmental control, we strengthen the connection between "Industry 4.0" and
"Sustainability". The paper source code is publicly available.


  In this paper we study a family of variance reduction methods with randomized
batch size---at each step, the algorithm first randomly chooses the batch size
and then selects a batch of samples to conduct a variance-reduced stochastic
update. We give the linear convergence rate for this framework for composite
functions, and show that the optimal strategy to achieve the optimal
convergence rate per data access is to always choose batch size of 1, which is
equivalent to the SAGA algorithm. However, due to the presence of cache/disk IO
effect in computer architecture, the number of data access cannot reflect the
running time because of 1) random memory access is much slower than sequential
access, 2) when data is too big to fit into memory, disk seeking takes even
longer time. After taking these into account, choosing batch size of $1$ is no
longer optimal, so we propose a new algorithm called SAGA++ and show how to
calculate the optimal average batch size theoretically. Our algorithm
outperforms SAGA and other existing batched and stochastic solvers on real
datasets. In addition, we also conduct a precise analysis to compare different
update rules for variance reduction methods, showing that SAGA++ converges
faster than SVRG in theory.


  Wireless communication at millimeter wave frequencies has attracted
considerable attention for the delivery of high-bit-rate connectivity to
unmanned aerial vehicles (UAVs). However, conducting the channel measurements
necessary to assess communication at these frequencies has been challenging due
to the severe payload and power restrictions in commercial UAVs. This work
presents a novel lightweight (approximately 1.3 kg) channel measurement system
at 28 GHz installed on a commercially available UAV. A ground transmitter
equipped with a horn antenna conveys sounding signals to a UAV equipped with a
lightweight spectrum analyzer. We demonstrate that the measurements can be
highly influenced by the antenna pattern as shaped by the UAV's frame. A
calibration procedure is presented to correct for the resulting angular
variations in antenna gain. The measurement setup is then validated on real
flights from an airstrip at distances in excess of 300 m.


  In this paper, we introduce the notion of BiHom-Lie conformal superalgebras.
We develop its representation theory and define the cohomology group with
coefficients in a module. Finally, we introduce conformal derivations of
BiHom-Lie conformal superalgebras and study some of their properties.


  We study singularity properties of word maps on semisimple algebraic groups
and Lie algebras, generalizing the work of Aizenbud-Avni in the case of the
commutator map.
  Given a word $w$ in a free Lie algebra $\mathcal{L}_{r}$, it induces a word
map $\varphi_{w}:\mathfrak{g}^{r}\rightarrow\mathfrak{g}$ for every semisimple
Lie algebra $\mathfrak{g}$. Given two words $w_{1}\in\mathcal{L}_{r_{1}}$ and
$w_{2}\in\mathcal{L}_{r_{2}}$, we define and study the convolution of the
corresponding word maps
$\varphi_{w_{1}}*\varphi_{w_{2}}:=\varphi_{w_{1}}+\varphi_{w_{2}}:\mathfrak{g}^{r_{1}+r_{2}}\rightarrow\mathfrak{g}$.
  We show that for any word $w\in\mathcal{L}_{r}$ of degree $d$, and any simple
Lie algebra $\mathfrak{g}$ with $\varphi_{w}(\mathfrak{g}^{r})\neq0$, one
obtains a flat morphism with reduced fibers of rational singularities
(abbreviated an (FRS) morphism) after taking $O(d^{4})$ self-convolutions of
$\varphi_{w}$. We deduce that a group word map of length $\ell$ becomes (FRS)
at $(e,\ldots,e)\in G^{r}$ after $O(\ell^{4})$ self-convolutions, for any
semisimple algebraic group $G$.
  We furthermore bound the dimensions of the jet schemes of the fibers of Lie
algebra word maps, and the fibers of group word maps in the case where
$G=\mathrm{SL}_{n}$. For the commutator word $\nu=[X,Y]$, we show that
$\varphi_{\nu}^{*4}$ is (FRS) for any semisimple Lie algebra, obtaining
applications in representation growth of compact $p$-adic and arithmetic
groups.
  The singularity properties we consider, such as the (FRS) property, are
intimately connected to the point count of fibers over finite rings of the form
$\mathbb{Z}/p^{k}\mathbb{Z}$. This allows us to relate them to properties of
some natural families of random walks on finite and compact $p$-adic groups. We
explore these connections, and provide applications to $p$-adic probabilistic
Waring type problems.


  Delamination is one of the major concerns for carbon fiber reinforced polymer
(CFRP) composites. Improving fracture toughness reduces delamination and allows
for the creation of multifunctional CFRP. In this study, polyaniline (PANI)
coated graphene nanoplatelets (GNP) are introduced in the interlaminar region
of CFRP pre-preg with the aid of environmentally friendly thermoplastic
polymer, polyvinylpyrrolidone (PVP). The GNP content is varied as 1, 3, and 5%
by weight with respect to PVP. The improvements in the fracture toughness are
investigated using a double cantilever beam test. An improvement of
approximately 79% in mode-I fracture toughness is observed with the addition of
5 wt% GNP with respect to PVP. Dynamic mechanical analysis results confirmed
the improvements in storage modulus but showed a decrease in glass transition
temperature with the addition of nanofiller. Various spectroscopic analysis and
imaging techniques were used to understand and evaluate the interactions of
nanocomposites with CFRP pre-preg.


  We find a recursive formula for the motivic Milnor fiber of an irreducible
plane curve, using the notions of a truncation and derived curve. We then apply
natural transformations to obtain a similar recursion for the Hodge-theoretic
spectrum.


  It is shown that if the exterior of a link L in the three sphere admits a
genus 2 Heegaard splitting, then L has Generalized Property R.


  The solar modulation of galactic cosmic rays (GCR) can be studied in detail
by examining long-term variations of the GCR energy spectrum (e.g. on the
scales of a solar cycle). With almost 20 years of data, the Electron Proton
Helium INstrument (EPHIN) onboard the SOlar and Heliospheric Observatory (SOHO)
is well suited for this kind of investigation. Although the design of the
instrument is optimized to measure proton and helium isotope spectra up to 50
MeV nucleon$^{-1}$ , the capability exists to determine proton energy spectra
from 250 MeV up to above 1.6 GeV. Therefore we developed a sophisticated
inversion method to calculate such proton spectra. The method relies on a
GEANT4 Monte Carlo simulation of the instrument and a simplified spacecraft
model that calculates the energy-response function of EPHIN for electrons,
protons and heavier ions. For validation purposes, proton spectra based on this
method are compared to various balloon missions and space instrumentation. As a
result we present annual galactic cosmic ray spectra from 1995 to 2014.


  We present magnetodielectric measurements in single crystals of the cubic
spin-1/2 compound Cu$_2$OSeO$_3$. A magnetic field-induced electric
polarization ($\vec{P}$) and a finite magnetocapacitance (MC) is observed at
the onset of the magnetically ordered state ($T_c = 59$ K). Both $\vec{P}$ and
MC are explored in considerable detail as a function of temperature (T),
applied field $\vec{H}_a$, and relative field orientations with respect to the
crystallographic axes. The magnetodielectric data show a number of anomalies
which signal magnetic phase transitions, and allow to map out the phase diagram
of the system in the $H_a$-T plane. Below the 3up-1down collinear ferrimagnetic
phase, we find two additional magnetic phases. We demonstrate that these are
related to the field-driven evolution of a long-period helical phase, which is
stabilized by the chiral Dzyalozinskii-Moriya term $D \vec{M}
\cdot(\bs{\nabla}\times\vec{M})$ that is present in this non-centrosymmetric
compound. We also present a phenomenological Landau-Ginzburg theory for the
ME$_H$ effect, which is in excellent agreement with experimental data, and
shows three novel features: (i) the polarization $\vec{P}$ has a uniform as
well as a long-wavelength spatial component that is given by the pitch of the
magnetic helices, (ii) the uniform component of $\vec{P}$ points along the
vector $(H^yH^z, H^zH^x, H^xH^y)$, and (iii) its strength is proportional to
$\eta_\parallel^2-\eta_\perp^2/2$, where $\eta_\parallel$ is the longitudinal
and $\eta_\perp$ is the transverse (and spiraling) component of the magnetic
ordering. Hence, the field dependence of P provides a clear signature of the
evolution of a conical helix under a magnetic field. A similar phenomenological
theory is discussed for the MC.


  This survey concerns regular graphs that are extremal with respect to the
number of independent sets, and more generally, graph homomorphisms. More
precisely, in the family of of $d$-regular graphs, which graph $G$
maximizes/minimizes the quantity $i(G)^{1/v(G)}$, the number of independent
sets in $G$ normalized exponentially by the size of $G$? What if $i(G)$ is
replaced by some other graph parameter? We review existing techniques,
highlight some exciting recent developments, and discuss open problems and
conjectures for future research.


  The excitation energies and ionization potentials of the atoms in the first
transition series are notoriously difficult to compute accurately. Errors in
calculated excitation energies can range from 1--4 eV at the Hartree-Fock
level, and errors as high as 1.5eV are encountered for ionization energies. In
the current work we present and discuss the results of a systematic study of
the first transition series using a spin-restricted Kohn-Sham
density-functional method with the gradient-corrected functionals of Becke and
Lee, Yang and Parr. Ionization energies are observed to be in good agreement
with experiment, with a mean absolute error of approximately 0.15eV; these
results are comparable to the most accurate calculations to date, the Quadratic
Configuration Interaction (QCISD(T)) calculations of Raghavachari and Trucks.
Excitation energies are calculated with a mean error of approximately 0.5eV,
compared with $\sim 1\mbox{eV}$ for the local density approximation and 0.1eV
for QCISD(T). These gradient-corrected functionals appear to offer an
attractive compromise between accuracy and computational effort.


  We review the mechanism and consequences of the "bridging-induced
attraction", a generic biophysical principle which underpins some existing
models for chromosome organisation in 3-D. This attraction, which was revealed
in polymer physics-inspired computer simulations, is a generic clustering
tendency arising in multivalent chromatin-binding proteins, and it provides an
explanation for the biogenesis of nuclear bodies and transcription factories
via microphase separation. Including post-translational modification reactions
involving these multivalent proteins can account for the fast dynamics of the
ensuing clusters, as is observed via microscopy and photobleaching experiments.
The clusters found in simulations also give rise to chromatin domains which
conform well with the observation of A/B compartments in HiC experiments.


  Meaningfully comparing language models is challenging with current
explanation methods. Current explanations are overwhelming for humans due to
large vocabularies or incomparable across models. We present TopEx, an
explanation method that enables a level playing field for comparing language
models via model-agnostic topics. We demonstrate how TopEx can identify
similarities and differences between DistilRoBERTa and GPT-2 on a variety of
NLP tasks.


  We present an experimental demonstration of high conversion efficiency
Betatron x-ray radiation from petawatt laser irradiated near critical plasmas.
Direct laser acceleration serves as the dominant regime when laser pulse of
~5e20 W/cm2 intensity is focused into plasmas with electron density of 3e20
/cm3. Electron beam with a charge of ~35 nC is accelerated up to a maximum
energy of 70 MeV and emit x-rays when oscillating in the laser field. The
deduced energy conversion efficiency from laser to x-rays is up to 1e-4, orders
of magnitude higher than other betatron regimes. Enhancement of acceleration
and radiation with sharp plasma density boundary is also obtained and further
interpretated with 2D particle-in-cell simulations.


  We have studied the magnetization of the recently discovered heavy fermion
superconductor UTe$_2$ up to 56 T in pulsed-magnetic fields. A first-order
metamagnetic transition has been clearly observed at $H_{\rm m}$ =34.9 T when
the magnetic field $H$ is applied along the orthorhombic hard-magnetization
$b$-axis. The transition has a critical end point at $\sim$11 K and 34.8 T,
where the first order transition terminates and changes into a crossover
regime. Using the thermodynamic Maxwell relation, we have evaluated the field
dependence of the Sommerfeld coefficient of the specific heat directly related
to the superconducting pairing. From the analysis, we found a significant
enhancement of the effective mass centered at $H_{\rm m}$, which is reminiscent
of the field-reentrant superconductivity of the ferromagnet URhGe in transverse
fields. We discuss the origin of their field-robust superconductivity.


  We present a new version of a dynamical spectral model for Large Eddy
Simulation based on the Eddy Damped Quasi Normal Markovian approximation
\cite{sao,chollet_lesieur}. Three distinct modifications are implemented and
tested. On the one hand, whereas in current approaches, a Kolmogorov-like
energy spectrum is usually assumed in order to evaluate the nonlocal transfer,
in our method the energy spectrum of the subgrid scales adapts itself
dynamically to the large-scale resolved spectrum; this first modification
allows in particular for a better treatment of transient phases and
instabilities, as shown on one specific example. Moreover, the model takes into
account the phase relationships of the small-scales, embodied for example in
strong localized structures such as vortex filaments. To that effect, phase
information is implemented in the treatment of the so-called eddy noise in the
closure model. Finally, we also consider the role that helical small scales may
play in the evaluation of the transfer of energy and helicity, the two
invariants of the primitive equations in the inviscid case; this leads as well
to intrinsic variations in the development of helicity spectra. Therefore, our
model allows for simulations of flows for a variety of circumstances and a
priori at any given Reynolds number. Comparisons with Direct Numerical
Simulations of the three-dimensional Navier-Stokes equation are performed on
fluids driven by an ABC (Beltrami) flow which is a prototype of fully helical
flows. Good agreements are obtained for physical and spectral behavior of the
large scales.


  Nanoscale biosensors are devices designed to detect analytes by combining
biological components and physicochemical detectors. One of the well known
methods of constructing these sensors is by using nanocantilevers. These
microscopic 'diving boards' are coated with binding probes that have an
affinity to a particular amino acid, enzyme or protein in living organisms.
When these probes attract some target particles, such as biomolecules, they
change the vibrating frequency of the cantilever. This process is random in
nature and produces fluctuations in the frequency and damping of the
cantilever. In this paper, we studied the effect of these fluctuations using a
stochastically perturbed classical harmonic oscillator.


  Political scientists often find themselves tracking amendments to political
texts. As different actors weigh in, texts change as they are drafted and
redrafted, reflecting political preferences and power. This study provides a
novel solution to the prob- lem of detecting amendments to political text based
upon minimum edit distances. We demonstrate the usefulness of two
language-insensitive, transparent, and efficient minimum-edit-distance
algorithms suited for the task. These algorithms are capable of providing an
account of the types (insertions, deletions, substitutions, and trans-
positions) and substantive amount of amendments made between version of texts.
To illustrate the usefulness and efficiency of the approach we replicate two
existing stud- ies from the field of legislative studies. Our results
demonstrate that minimum edit distance methods can produce superior measures of
text amendments to hand-coded efforts in a fraction of the time and resource
costs.


  Liquid scintillator (LS) is widely used in various neutrino oscillation
experiments, in particular, the reactor neutrino experiments. The complex
absorption and re-emission processes of optical photons are known to be an
important source of the non-linear and non-uniform response of LS detectors.
Precise simulation of light propagation in LS is highly desirable to model the
detector response and reduce the systematic errors. In this paper, we develop a
novel optical model which can completely deal with the competitive photon
absorption and subsequent re-emission processes of the LS components. It allows
to directly plug in the laboratory measurements of the LS components to model
any LS composition. Extensive measurements have been performed to obtain the
essential optical parameters for this model. We validate the model with a
bench-top experiment featuring a small LS volume. Furthermore, we demonstrate
that for any given detector geometry, this model provides the capability of
optimizing the LS recipe to maximize the light collection. It is valuable for
designing future LS-based detectors and improving the agreement between Monte
Carlo and data for current neutrino experiments.


  We present and discuss a list of some interesting points that are currently
open in nonextensive statistical mechanics. Their analytical, numerical,
experimental or observational advancement would naturally be very welcome.


  We describe a system to measure the Quantum Efficiency in the wavelength
range of 300 nm to 1100 nm of 40x40 mm n-channel CCD sensors for the
construction of the 3.2 gigapixel LSST focal plane. The technique uses a series
of instrument to create a very uniform flux of photons of controllable
intensity in the wavelength range of interest across the face the sensor. This
allows the absolute Quantum Efficiency to be measured with an accuracy in the
7% range. This system will be part of a production facility at Brookhaven
National Lab for the basic component of the LSST camera.


  We get some results about the factorization of $\phi_p(M) \in
{\mathbb{F}}_2[x]$, where $p$ is a prime number, $\phi_p$ is the corresponding
cyclotomic polynomial and $M$ is a Mersenne prime (polynomial). By the way, we
better understand the factorization of the sum of the divisors of $M^{2h}$, for
a positive integer $h$.


  We show that exceptional sequences in the abelian tube of rank $n$, which we
denote $\mathscr{ W}_n$, are related to exceptional sequences of type $B_n$ and
$C_n$ and to those of type $B_{n-1}$ and $C_{n-1}$. $\mathscr{W}_n$ has
$n^{n-1}$ exceptional sequences. These are in $1$-to-$n$ correspondence from
the $n^n$ "augmented" rooted labeled trees with $n$ vertices which, in turn,
are in bijection with exceptional sequences of type $B_n$ and $C_n$. By
determining the probability distribution of relative projectives in these
exceptional sequences, we show there are $(2n)!/n!$ signed exceptional
sequences in $\mathscr{W}_n$ and we show that these are in bijection with
signed exceptional sequences of type $B_{n-1}$ and $C_{n-1}$ by combining the
results of Buan-Marsh-Vatne and Igusa-Todorov.


  The interaction between combinatorics and algebraic and differential geometry
is very strong. While researching a problem of Hessian topology, we came across
a series of identities of binomial coefficients, which are useful for proving a
topological property of certain spaces whose elements are graphs of a class of
hyperbolic polynomials. These identities are proven by different methods in
combinatorics.


  In this paper, we propose a practical and effective approach allowing
designers to optimize multi-level cache size at the early system design phase.
Our key contribution is to generalize the reuse distance analysis method and
develop an effective and practical cache design optimization approach. We adopt
a simple scanning search method to locate optimal cache solutions in terms of
cache size, power consumption, or average data access delay. The proposed
approach is particularly useful for early-phase system designers and is
verified to be 150 to 250 times faster than the traditional simulation-based
approach. In addition, we also introduce a simplified analytical model and
provide designers insights about how cache design parameters may affect the
expected results. As a result, designers can make an adequate decision in the
early system design phase.


  In recent years, different studies have proposed and validated user models
(e.g., Bartle, BrainHex, and Hexad) to represent the different user profiles in
games and gamified settings. However, the results of applying these user models
in practice (e.g., to personalize gamified systems) are still contradictory.
One of the hypotheses for these results is that the user types can change over
time (i.e., user types are dynamic). To start to understand whether user types
can change over time, we conducted an exploratory study analyzing data from 74
participants to identify if their user type (Achiever, Philanthropist,
Socialiser, Free Spirit, Player, and Disruptor) had changed over time (six
months). The results indicate that there is a change in the dominant user type
of the participants, as well as the average scores in the Hexad sub-scales.
These results imply that all the scores should be considered when defining the
Hexad's user type and that the user types are dynamic. Our results contribute
with practical implications, indicating that the personalization currently made
(generally static) may be insufficient to improve the users' experience,
requiring user types to be analyzed continuously and personalization to be done
dynamically.


  We study non Hermitian quantum systems in noncommutative space as well as a
\cal{PT}-symmetric deformation of this space. Specifically, a
\mathcal{PT}-symmetric harmonic oscillator together with iC(x_1+x_2)
interaction is discussed in this space and solutions are obtained. It is shown
that in the \cal{PT} deformed noncommutative space the Hamiltonian may or may
not possess real eigenvalues depending on the choice of the noncommutative
parameters. However, it is shown that in standard noncommutative space, the
iC(x_1+x_2) interaction generates only real eigenvalues despite the fact that
the Hamiltonian is not \mathcal{PT}-symmetric. A complex interacting
anisotropic oscillator system has also been discussed.


  When trying to solve a computational problem, we are often faced with a
choice between algorithms that are guaranteed to return the right answer but
differ in their runtime distributions (e.g., SAT solvers, sorting algorithms).
This paper aims to lay theoretical foundations for such choices by formalizing
preferences over runtime distributions. It might seem that we should simply
prefer the algorithm that minimizes expected runtime. However, such preferences
would be driven by exactly how slow our algorithm is on bad inputs, whereas in
practice we are typically willing to cut off occasional, sufficiently long runs
before they finish. We propose a principled alternative, taking a
utility-theoretic approach to characterize the scoring functions that describe
preferences over algorithms. These functions depend on the way our value for
solving our problem decreases with time and on the distribution from which
captimes are drawn. We describe examples of realistic utility functions and
show how to leverage a maximum-entropy approach for modeling underspecified
captime distributions. Finally, we show how to efficiently estimate an
algorithm's expected utility from runtime samples.


  Semantic part segmentation provides an intricate and interpretable
understanding of an object, thereby benefiting numerous downstream tasks.
However, the need for exhaustive annotations impedes its usage across diverse
object types. This paper focuses on learning part segmentation from synthetic
animals, leveraging the Skinned Multi-Animal Linear (SMAL) models to scale up
existing synthetic data generated by computer-aided design (CAD) animal models.
Compared to CAD models, SMAL models generate data with a wider range of poses
observed in real-world scenarios. As a result, our first contribution is to
construct a synthetic animal dataset of tigers and horses with more pose
diversity, termed Synthetic Animal Parts (SAP). We then benchmark Syn-to-Real
animal part segmentation from SAP to PartImageNet, namely SynRealPart, with
existing semantic segmentation domain adaptation methods and further improve
them as our second contribution. Concretely, we examine three Syn-to-Real
adaptation methods but observe relative performance drop due to the innate
difference between the two tasks. To address this, we propose a simple yet
effective method called Class-Balanced Fourier Data Mixing (CB-FDM). Fourier
Data Mixing aligns the spectral amplitudes of synthetic images with real
images, thereby making the mixed images have more similar frequency content to
real images. We further use Class-Balanced Pseudo-Label Re-Weighting to
alleviate the imbalanced class distribution. We demonstrate the efficacy of
CB-FDM on SynRealPart over previous methods with significant performance
improvements. Remarkably, our third contribution is to reveal that the learned
parts from synthetic tiger and horse are transferable across all quadrupeds in
PartImageNet, further underscoring the utility and potential applications of
animal part segmentation.


  Quantum convolutional neural networks (QCNNs) are quantum circuits for
recognizing quantum phases of matter at low sampling cost and have been
designed for condensed matter systems in one dimension. Here we construct a
QCNN that can perform phase recognition in two dimensions and correctly
identify the phase transition from a Toric Code phase with
$\mathbb{Z}_2$-topological order to the paramagnetic phase. The network also
exhibits a noise threshold up to which the topological order is recognized. Our
work generalizes phase recognition with QCNNs to higher spatial dimensions and
intrinsic topological order, where exploration and characterization via
classical numerics become challenging.


  We examine whether large language models (LLMs) exhibit race- and
gender-based name discrimination in hiring decisions, similar to classic
findings in the social sciences (Bertrand and Mullainathan, 2004). We design a
series of templatic prompts to LLMs to write an email to a named job applicant
informing them of a hiring decision. By manipulating the applicant's first
name, we measure the effect of perceived race, ethnicity, and gender on the
probability that the LLM generates an acceptance or rejection email. We find
that the hiring decisions of LLMs in many settings are more likely to favor
White applicants over Hispanic applicants. In aggregate, the groups with the
highest and lowest acceptance rates respectively are masculine White names and
masculine Hispanic names. However, the comparative acceptance rates by group
vary under different templatic settings, suggesting that LLMs' race- and
gender-sensitivity may be idiosyncratic and prompt-sensitive.


  We propose a new least squares finite element method to solve the Poisson
equation. By using a piecewisely irrotational space to approximate the flux, we
split the classical method into two sequential steps. The first step gives the
approximation of flux in the new approximation space and the second step can
use flexible approaches to give the pressure. The new approximation space for
flux is constructed by patch reconstruction with one unknown per element
consisting of piecewisely irrotational polynomials. The error estimates in the
energy norm and $L^2$ norm are derived for the flux and the pressure. Numerical
results verify the convergence order in error estimates, and demonstrate the
flexibility and particularly the great efficiency of our method.


  Using a Bayesian framework, we quantify what current observations imply about
the history of the epoch of reionisation (EoR). We use a popular,
three-parameter EoR model, flexible enough to accommodate a wide range of
physically-plausible reionisation histories. We study the impact of various EoR
observations: (i) the optical depth to the CMB measured by Planck 2016; (ii)
the dark fraction in the Lyman $\alpha$ and $\beta$ forests; (iii) the redshift
evolution of galactic Ly$\alpha$ emission (so-called "Ly$\alpha$ fraction");
(iv) the clustering of Ly$\alpha$ emitters; (v) the IGM damping wing imprint in
the spectrum of QSO ULASJ1120+0641; (vi) and the patchy kinetic
Sunyaev-Zel'dovich signal. Combined, (i) and (ii) already place interesting
constraints on the reionisation history, with the epochs corresponding to an
average neutral fraction of (75, 50, 25) per cent, constrained at 1$\sigma$ to
$z= (9.21\substack{+1.22 -1.15}, 8.14\substack{+1.08 -1.00},
7.26\substack{+1.13 -0.96})$. Folding-in more model-dependent EoR observations
[(iii--vi)], strengthens these constraints by tens of per cent, at the cost of
a decrease in the likelihood of the best-fit model, driven mostly by (iii). The
tightest constraints come from (v). Unfortunately, no current observational set
is sufficient to break degeneracies and constrain the astrophysical EoR
parameters. However, model-dependent priors on the EoR parameters themselves
can be used to set tight limits by excluding regions of parameter space with
strong degeneracies. Motivated by recent observations of $z\sim7$ faint, lensed
galaxies, we show how a conservative upper limit on the virial temperature of
haloes which host reionising galaxies can constrain the escape fraction of
ionising photons to $f_{\rm esc} = 0.14\substack{+0.26 -0.09}$


  Hyperuniform disordered photonic materials (HDPM) are spatially correlated
dielectric structures with unconventional optical properties. They can be
transparent to long-wavelength radiation while at the same time have isotropic
band gaps in another frequency range. This phenomenon raises fundamental
questions concerning photon transport through disordered media. While optical
transparency is robust against recurrent multiple scattering, little is known
about other transport regimes like diffusive multiple scattering or Anderson
localization. Here we investigate band gaps, and we report Anderson
localization in two-dimensional stealthy HDPM using numerical simulations of
the density of states and optical transport statistics. To establish a unified
view, we propose a transport phase diagram. Our results show that, depending
only on the degree of correlation, a dielectric material can transition from
localization behavior to a bandgap crossing an intermediate regime dominated by
tunneling between weakly coupled states.


  A well-known conjecture in analytic number theory states that for every pair
of sets $X,Y\subset\mathbb{Z}/p\mathbb{Z}$, each of size at least $\log ^C p$
(for some constant $C$) we have that the number of pairs $(x,y)\in X\times Y$
such that $x+y$ is a quadratic residue modulo $p$ differs from $\frac12|X||Y|$
by $o\left(|X||Y|\right)$. We address the probabilistic analogue of this
question, that is for every fixed $\delta>0$, given a finite group $G$ and
$A\subset G$ a random subset of density $\frac12$, we prove that with high
probability for all subsets $|X|,|Y|\geq \log ^{2+\delta} |G|$, the number of
pairs $(x,y)\in X\times Y$ such that $xy\in A$ differs from $\frac12|X||Y|$ by
$o\left(|X||Y|\right)$.


  The art of the scientific presentation -- much like the art of the perfect
plot, the art of the compelling proposal, and the art of the killer job
application -- is generally not something we're taught in school. Therefore, in
classic Millennial style, one of the first things I did when I was asked to
write this piece was to ask Google, "how to give a scientific presentation," to
see what the Internet had to say. I've attempted to avoid boring you with
laundry lists of "do's" and "don'ts," as many of the top Google hits did.
However, I have incorporated a wide range of tips -- and some interesting
vignettes -- both from the online hive mind and from my approximately eight
years of regularly giving astronomy and radio-science presentations.


  In this work we study an alternative topological model for explaining the
observed acceleration of space-time, we answer the question of whether this
acceleration could be a consequence of the topology of the universe. For doing
that, we propose that the whole universe is composed of a four dimensional base
space, which represents space-time, endowed with a fiber forming a principal
fiber bundle. We analyze this hypothesis for a homogeneous and isotropic four
dimensional space-time and show that the effect of the fiber onto the base
space is that the space-time accelerates depending on the group of the fiber,
even in an oscillatory way, resembling the behavior of the universe according
to recent observations. We conclude that there is the possibility of the
accelerating behavior of the universe being due to its whole topology instead
of an exotic kind of matter.


  We introduce a time-dependent R-matrix theory generalised to describe double
ionization processes. The method is used to investigate two-photon double
ionization of He by intense XUV laser radiation. We combine a detailed
B-spline-based wavefunction description in a extended inner region with a
single-electron outer region containing channels representing both single
ionization and double ionization. A comparison of wavefunction densities for
different box sizes demonstrates that the flow between the two regions is
described with excellent accuracy. The obtained two-photon double ionization
cross sections are in excellent agreement with other cross sections available.
Compared to calculations fully contained within a finite inner region, the
present calculations can be propagated over the time it takes the slowest
electron to reach the boundary.


  Active matter spans a wide range of time and length scales, from groups of
cells and synthetic self-propelled particles to schools of fish, flocks of
birds, or even human crowds. The theoretical framework describing these systems
has shown tremendous success at finding universal phenomenology. However,
further progress is often burdened by the difficulty of determining the forces
that control the dynamics of the individual elements within each system.
Accessing this local information is key to understanding the physics dominating
the system and to create the models that can explain the observed collective
phenomena. In this work, we present a machine-learning model, a graph neural
network, that uses the collective movement of the system to learn the active
and two-body forces controlling the individual dynamics of the particles. We
verify our approach using numerical simulations of active brownian particles,
considering different interaction potentials and levels of activity. Finally,
we apply our model to experiments of electrophoretic Janus particles,
extracting the active and two-body forces that control the dynamics of the
colloids. Due to this, we can uncover the physics dominating the behavior of
the system. We extract an active force that depends on the electric field and
also area fraction. We also discover a dependence of the two-body interaction
with the electric field that leads us to propose that the dominant force
between these colloids is a screened electrostatic interaction with a constant
length scale. We expect that this methodology can open a new avenue for the
study and modeling of experimental systems of active particles.


  Many Java applications instantiate objects within the Java heap that are
persistent but seldom if ever referenced by the application. Examples include
strings, such as error messages, and collections of value objects that are
preloaded for fast access but they may include objects that are seldom
referenced. This paper describes a stack-based framework for detecting these
"cold" objects at runtime, with a view to marshaling and sequestering them in
designated regions of the heap where they may be preferentially paged out to a
backing store, thereby freeing physical memory pages for occupation by more
active objects. Furthermore, we evaluate the correctness and efficiency of
stack-based approach with an Access Barrier. The experimental results from a
series of SPECjvm2008 benchmarks are presented.


  The intrinsic volumes of a convex cone are geometric functionals that return
basic structural information about the cone. Recent research has demonstrated
that conic intrinsic volumes are valuable for understanding the behavior of
random convex optimization problems. This paper develops a systematic technique
for studying conic intrinsic volumes using methods from probability. At the
heart of this approach is a general Steiner formula for cones. This result
converts questions about the intrinsic volumes into questions about the
projection of a Gaussian random vector onto the cone, which can then be
resolved using tools from Gaussian analysis. The approach leads to new
identities and bounds for the intrinsic volumes of a cone, including a
near-optimal concentration inequality.


  We present a smoothed density-corrected $V_{\rm max}$ technique for building
a random catalog for property-dependent galaxy clustering estimation. This
approach is essentially based on the density-corrected $V_{\rm max}$ method of
Cole(2011), with three improvements to the original method. To validate the
improved method, we generate two sets of flux-limited samples from two
independent mock catalogs with different $k+e$ corrections. By comparing the
two-point correlation functions, our results demonstrate that the random
catalog created by the smoothed density-corrected $V_{\rm max}$ approach
provides a more accurate and precise measurement for both sets of mock samples
than the commonly used $V_{\rm max}$ method and redshift shuffled method. For
flux-limited samples and color-dependent subsamples, the accuracy for the
projected correlation function is well constrained within $1\%$ on the scale
$0.07 h^{-1}\rm Mpc - 30 h^{-1}\rm Mpc$. The accuracy of the redshift-space
correlation function is less than $2\%$ as well. Currently, it is the only
approach that holds promise for achieving the goal of high-accuracy clustering
measures for next-generation surveys.


  For encompassing the limitations of probabilistic coherence spaces which do
not seem to provide natural interpretations of continuous data types such as
the real line, Ehrhard and al. introduced a model of probabilistic higher order
computation based on (positive) cones, and a class of totally monotone
functions that they called "stable". Then Crubill{\'e} proved that this model
is a conservative extension of the earlier probabilistic coherence space model.
We continue these investigations by showing that the category of cones and
linear and Scott-continuous functions is a model of intuitionistic linear
logic. To define the tensor product, we use the special adjoint functor
theorem, and we prove that this operation is and extension of the standard
tensor product of probabilistic coherence spaces. We also show that these
latter are dense in cones, thus allowing to lift the main properties of the
tensor product of probabilistic coherence spaces to general cones. Last we
define in the same way an exponential of cones and extend measurability to
these new operations.


  We sketch some recent ideas proposed as the mechanism behind the puzzling
experimental results on baryon-antibaryon production in e+e- annihilation close
to threshold. The essential new point in the proposed mechanism is that it is a
two-stage process, with a coherent state of pions serving as an intermediary
between e+e- and the baryon-antibaryon system. Skyrmion-antiskyrmion
annihilation is proposed as a concrete computational framework for a
quantitative description of the baryon-antibaryon annihilation. We also point
out the possible connection to similarly puzzling data on baryon-antibaryon
production in photon-photon collision.


  This review article is devoted to analyze the main properties characterizing
the cosmological singularity associated to the homogeneous and inhomogeneous
Mixmaster model. After the introduction of the main tools required to treat the
cosmological issue, we review in details the main results got along the last
forty years on the Mixmaster topic. We firstly assess the classical picture of
the homogeneous chaotic cosmologies and, after a presentation of the canonical
method for the quantization, we develop the quantum Mixmaster behavior.
Finally, we extend both the classical and quantum features to the fully
inhomogeneous case. Our survey analyzes the fundamental framework of the
Mixmaster picture and completes it by accounting for recent and peculiar
outstanding results.


  Domain Adaptation (DA) is a highly relevant research topic when it comes to
image classification with deep neural networks. Combining multiple source
domains in a sophisticated way to optimize a classification model can improve
the generalization to a target domain. Here, the difference in data
distributions of source and target image datasets plays a major role. In this
paper, we describe based on a theory of visual factors how real-world scenes
appear in images in general and how recent DA datasets are composed of such. We
show that different domains can be described by a set of so called domain
factors, whose values are consistent within a domain, but can change across
domains. Many DA approaches try to remove all domain factors from the feature
representation to be domain invariant. In this paper we show that this can lead
to negative transfer since task-informative factors can get lost as well. To
address this, we propose Factor-Preserving DA (FP-DA), a method to train a deep
adversarial unsupervised DA model, which is able to preserve specific task
relevant factors in a multi-domain scenario. We demonstrate on CORe50, a
dataset with many domains, how such factors can be identified by standard
one-to-one transfer experiments between single domains combined with PCA. By
applying FP-DA, we show that the highest average and minimum performance can be
achieved.


  Using an analytical approach, the sensitivity to sin^2{2theta_13} with
infinite statistics in a spectral analysis is investigated in reactor neutrino
oscillation experiments with one reactor and two identical detectors. We derive
an useful formula for the sensitivity which depends only two parameters
sigma_db/\sqrt{n} (the uncorrelated bin-to-bin systematic error over the
square-root of the number of bins) and sigma_dB (the bin-to-bin correlated
detector specific systematic error).


  Denoising algorithms play a crucial role in medical image processing and
analysis. However, classical denoising algorithms often ignore explanatory and
critical medical features preservation, which may lead to misdiagnosis and
legal liabilities. In this work, we propose a new denoising method for medical
images that not only efficiently removes various types of noise, but also
preserves key medical features throughout the process. To achieve this goal, we
utilize a gradient-based eXplainable Artificial Intelligence (XAI) approach to
design a feature preserving loss function. Our feature preserving loss function
is motivated by the characteristic that gradient-based XAI is sensitive to
noise. Through backpropagation, medical image features before and after
denoising can be kept consistent. We conducted extensive experiments on three
available medical image datasets, including synthesized 13 different types of
noise and artifacts. The experimental results demonstrate the superiority of
our method in terms of denoising performance, model explainability, and
generalization.


  We apply the hydrodynamic model for the dynamics of matter created in p-Pb
collisions at 4.4TeV and d-Pb collisions at 3.11TeV. The fluctuating initial
conditions are calculated in the Glauber Monte-Carlo model for several
centrality classes. The expansion is performed event by event in
3+1-dimensional viscous hydrodynamics. Noticeable elliptic and triangular flows
appear in the distributions of produced particles.


  In preceding papers the author proposed a new mechanism of Cooper pair
formation that follows within an extended Heisenberg model. The new mechanism
operates in narrow, partly filled "superconducting" energy bands of special
symmetry and shows resemblances, and also great differences as compared with
the familiar BCS mechanism. In the present paper the resulting superconducting
state is interpreted as a state in which the spins are ordered within the k
space. In this picture, the peculiar features of the new mechanism, as compared
with the BCS mechanism, can be understood in a straightforward manner. On the
one hand, the new mechanism resembles the BCS picture, because the formation of
Cooper pairs is still mediated by bosons (having dominant phonon character in
the isotropic lattices of the conventional superconductors). On the other hand,
however, the pair formation is not the result of an attractive
electron-electron interaction mediated by these bosons. Rather, the bosons
carry the crystal-spin angular momentum $hbar$ and generate in a new way
constraining forces that constrain the electrons to form Cooper pairs. The
scale of the transition temperatures in conventional and high-temperature
superconductors is set by the excitation energies of stable crystal-spin-1
bosons that are different in isotropic and anisotropic materials.


  Recent advances have been made in learning of grasps for fully actuated
hands. A typical approach learns the target locations of finger links on the
object. When a new object must be grasped, new finger locations are generated,
and a collision free reach-to-grasp trajectory is planned. This assumes a
collision free trajectory to the final grasp. This is not possible with
underactuated hands, which cannot be guaranteed to avoid contact, and in fact
exploit contacts with the object during grasping, so as to reach an equilibrium
state in which the object is held securely. Unfortunately, these contact
interactions are i) not directly controllable, and ii) hard to monitor during a
real grasp. We overcome these problems so as to permit learning of
transferrable grasps for underactuated hands. We make two main technical
innovations. First, we model contact interactions during the grasp implicitly.
We do this by modelling motor commands that lead reliably to the equilibrium
state, rather than modelling contact changes themselves. This alters our
reach-to-grasp model. Second, we extend our contact model learning algorithm to
work with multiple training examples for each grasp type. This requires the
ability to learn which parts of the hand reliably interact with the object
during a particular grasp. Our approach learns from a rigid body simulation.
This enables us to learn how to approach the object and close the underactuated
hand from a variety of poses. From nine training grasps on three objects the
method transferred grasps to previously unseen, novel objects, that differ
significantly from the training objects, with an 80% success rate.


  The Comment claims the Huang et al. can be explained as a 2D Kondo effect and
as such does not represent a disappearance of metallic behavior. The density
dependence of the Kondo temperature is in good agreement with the data.


  Very high-energy (VHE; E>100 GeV) gamma-rays have been detected from a wide
range of astronomical objects, such as pulsar wind nebulae (PWNe), supernova
remnants (SNRs), giant molecular clouds, gamma-ray binaries, the Galactic
Center, active galactic nuclei (AGN), radio galaxies, starburst galaxies, and
possibly star-forming regions as well. At lower energies, observations using
the Large Area Telescope (LAT) onboard Fermi provide a rich set of data which
can be used to study the behavior of cosmic accelerators in the MeV to TeV
energy bands. In particular, the improved angular resolution of current
telescopes in both bands compared to previous instruments significantly reduces
source confusion and facilitates the identification of associated counterparts
at lower energies. In this paper, a comprehensive search for VHE gamma-ray
sources which are spatially coincident with Galactic Fermi/LAT bright sources
is performed, and the available MeV to TeV spectra of coincident sources are
compared. It is found that bright LAT GeV sources are correlated with TeV
sources, in contrast to previous studies using EGRET data. Moreover, a single
spectral component seems unable to describe the MeV to TeV spectra of many
coincident GeV/TeV sources. It has been suggested that gamma-ray pulsars may be
accompanied by VHE gamma-ray emitting nebulae, a hypothesis that can be tested
with VHE observations of these pulsars.


  A generalized connection between the quantum mechanical Bargmann invariants
and the geometric phases was established for the Dirac fermions. We extend that
formalism for the Majorana fermions by defining proper quantum mechanical ray
and Hilbert spaces. We then relate both the Dirac and Majorana type Bargmann
invariants to the rephasing invariant measures of CP violation with the
Majorana neutrinos, assuming that the neutrinos have lepton number violating
Majorana masses. We then generalize the recursive parametrization for studying
any unitary matrices to include the Majorana fermions, which could be useful
for studying the neutrino mixing matrix.


  The Lagrangian that is normally associated with Dirac neutrinos is analyzed
in a complete and simple way through field theory. It is found that the
elements of the neutrino mass matrix are field strength renormalization
constants and that the flavor fields can be directly applied to the
one-particle energy states through these rescaling factors. Moreover this
Lagrangian describes neutrinos which are in a state of mixed flavor at any
space-time point and therefore does not describe the phenomenology of neutrino
oscillations properly, except in the ultra-relativistic limit where such a
description is possible.


  We relate completions of infinitesimal Hecke algebras of sl2 to
noncommutative deformations of Kleinian singularities of type D of
Crawley-Boevey and Holland. As a consequence, we show an analogue of the
inequality of Bernstein and simplicity of generic maximal primitive quotients
of these algebras. We also establish Skryabin type equivalence for these
algebras.


  The search for neutrino-less double-beta decay has been a very active field
of research in the last decade. Neutrino-less double-beta decay may answer
essential open questions in neutrino physics. While double-beta decay
accompanied by the emission of two neutrinos is allowed by the Standard Model,
the neutrino-less process requires neutrinos to be Majorana particles.
Detecting this decay could determine the nature of neutrinos, the neutrino
effective mass, and the mass hierarchy. Xenon-136 and germanium-76 experiments
currently have the best sensitivities. For both isotopes the lifetime of
neutrino-less double-beta decay has been determined to be longer than 10^25
years, several orders of magnitude slower than the slowest process that has
been detected. In this paper the basic theory of neutrino-less double-beta
decay and its relationship to the neutrino mass are discussed. A review of the
experimental efforts underway to measure this decay is presented, along with
the status and sensitivity of current and near future searches.


  We give an example of an imaginary defined in certain valued fields with
analytic structure which cannot be coded in the `geometric' sorts which suffice
to code all imaginaries in the corresponding algebraic setting.


  We examine the prospects of using two alternative and complementary ways to
explore the regions that are favored by global constraints in two simple
unified supersymmetric models: the CMSSM and the NUHM. First, we consider
BR(Bs->\mu\mu), which has recently been for the first time measured by LHCb. In
the CMSSM we show that ultimate, but realistic, improvement in the
determination of the observable to about 5-10% around the Standard Model value
would strongly disfavor the A-funnel region, while not affecting much the other
favored regions. Second, we show that all the favored regions of the CMSSM will
be, for the most part, sensitive to direct dark matter searches in future
one-tonne detectors. A signal at low WIMP mass (<=450 GeV) and low
spin-independent cross section would then strongly favor the stau
coannihilation region while a signal at higher WIMP mass (~800 GeV to ~1.2 TeV)
would clearly point to the region where the neutralino is higgsino-like with
mass ~1 TeV. A nearly complete experimental testing of the CMSSM over multi-TeV
ranges of superpartner masses, far beyond the reach of direct SUSY searches at
the LHC, can therefore be achievable. In the NUHM, in contrast, similar favored
regions exist but a sample study reveals that even a precise determination of
BR(Bs->\mu\mu) would have a much less constraining power on the model,
including the A-funnel region. On the other hand, this could allow one to, by
detecting in one-tonne detectors a signal for 500 GeV<m_{\chi}<800 GeV,
strongly disfavor the CMSSM.


  In recent years, sketch-based 3D shape retrieval has attracted growing
attention. While many previous studies have focused on cross-modal matching
between hand-drawn sketches and 3D shapes, the critical issue of how to handle
low-quality and noisy samples in sketch data has been largely neglected. This
paper presents an uncertainty-aware cross-modal transfer network (UACTN) that
addresses this issue. UACTN decouples the representation learning of sketches
and 3D shapes into two separate tasks: classification-based sketch uncertainty
learning and 3D shape feature transfer. We first introduce an end-to-end
classification-based approach that simultaneously learns sketch features and
uncertainty, allowing uncertainty to prevent overfitting noisy sketches by
assigning different levels of importance to clean and noisy sketches. Then, 3D
shape features are mapped into the pre-learned sketch embedding space for
feature alignment. Extensive experiments and ablation studies on two benchmarks
demonstrate the superiority of our proposed method compared to state-of-the-art
methods.


  We prove a universal property for blow-ups in regularly immersed subschemes,
based on a notion we call "virtual effective Cartier divisor". We also
construct blow-ups of quasi-smooth closed immersions in derived algebraic
geometry.


  Using $su(N)$ Cartan subalgebra local bases parametrization of density
operator $\rho$, we prove that the Wu-Yang potentials of a general $N$-level
quantum system are completely expressed by $SU(N)$ gauge transformation. By
taking the $SU(2)$ Cartan subalgebra local basis as a local normalized
magnetization vector, we find that magnetic skyrmion and Wu-Yang magnetic
monopole have the same algebraic structure. Moreover, by taking the adiabatic
unitary evolution of magnetization as local gauge transformation, we verify
that the Wu-Yang potential of magnetic skyrmions is proportional to the Berry
connection, this means that magnetic skyrmion is quasi-magnetic monopole. The
exact relation between Wu-Yang potentials and Berry connection is discussed in
detail for the general $SU(N)$ case, i.e. the Berry connection for the pure or
mixed state is the weighted average of the $(N-1)$ Wu-Yang potentials.


  In many computer vision classification tasks, class priors at test time often
differ from priors on the training set. In the case of such prior shift,
classifiers must be adapted correspondingly to maintain close to optimal
performance. This paper analyzes methods for adaptation of probabilistic
classifiers to new priors and for estimating new priors on an unlabeled test
set. We propose a novel method to address a known issue of prior estimation
methods based on confusion matrices, where inconsistent estimates of decision
probabilities and confusion matrices lead to negative values in the estimated
priors. Experiments on fine-grained image classification datasets provide
insight into the best practice of prior shift estimation and classifier
adaptation, and show that the proposed method achieves state-of-the-art results
in prior adaptation. Applying the best practice to two tasks with naturally
imbalanced priors, learning from web-crawled images and plant species
classification, increased the recognition accuracy by 1.1% and 3.4%
respectively.


  We determine the O(alpha_s^2) corrections to the partonic hemisphere soft
function relevant for thrust and jet mass distributions in e+e- annihilation in
the dijet limit. In this limit the distributions can be described by a
factorization theorem that sums large logarithmic terms and separates
perturbative from nonperturbative effects. Using the known O(alpha_s^2)
contributions of the jet functions and the hard coefficients in the
factorization theorem, constraints from renormalization group evolution and
nonabelian exponentiation, and results from numerical integration of
O(alpha_s^2) QCD matrix elements, the O(alpha_s^2) corrections of the soft
function can be determined unambiguously. We study the impact of subtracting
contributions related to the O(Lambda_QCD) renormalon in the partonic threshold
using the soft function gap proposed recently by Hoang and Stewart, and we
discuss the importance to account for the renormalization group evolution of
the gap parameter. As a byproduct we also present the previously unknown
next-to-next-to-leading logarithmic anomalous dimensions for the hard
coefficient that appear in the factorization theorem for the double
differential invariant mass distribution for heavy quark pair production at
high energies in the resonance region proven by Fleming etal.


  Mason and Remmel introduced a basis for quasisymmetric functions known as the
row-strict quasisymmetric Schur functions. This basis is generated
combinatorially by fillings of composition diagrams that are analogous to the
row-strict tableaux that generate Schur functions. We introduce a modification
known as Young row-strict quasisymmetric Schur functions, which are generated
by row-strict Young composition fillings. After discussing basic combinatorial
properties of these functions, we define a skew Young row-strict quasisymmetric
Schur function using the Hopf algebra of quasisymmetric functions and then
prove this is equivalent to a combinatorial description. We also provide a
decomposition of the skew Young row-strict quasisymmetric Schur functions into
a sum of Gessel's fundamental quasisymmetric functions and prove a
multiplication rule for the product of a Young row-strict quasisymmetric Schur
function and a Schur function.


  Shopping in VR malls has been regarded as a paradigm shift for E-commerce,
but most of the conventional VR shopping platforms are designed for a single
user. In this paper, we envisage a scenario of VR group shopping, which brings
major advantages over conventional group shopping in brick-and-mortar stores
and Web shopping: 1) configure flexible display of items and partitioning of
subgroups to address individual interests in the group, and 2) support social
interactions in the subgroups to boost sales. Accordingly, we formulate the
Social-aware VR Group-Item Configuration (SVGIC) problem to configure a set of
displayed items for flexibly partitioned subgroups of users in VR group
shopping. We prove SVGIC is NP-hard to approximate within $\frac{32}{31} -
\epsilon$. We design an approximation algorithm based on the idea of Co-display
Subgroup Formation (CSF) to configure proper items for display to different
subgroups of friends. Experimental results on real VR datasets and a user study
with hTC VIVE manifest that our algorithms outperform baseline approaches by at
least 30.1% of solution quality.


  Let a sequence of conformal Riemannian metrics $\{g_k=u_k^2g_0\}$ be
isospectral to $g_0$ over a compact boundaryless smooth 4-dimension manifold
$(M,g_0)$. We prove that the subsequence of conformal factors $\{u_k\}$
converges to $u$ weakly in $W^{2,p}_{loc}(M\setminus \mathcal{S})$ for some
$p<2$, where $\mathcal{S}$ is a finite set of points and $u\in W^{2,p}(M,g_0)$.
Moreover, if the isospectral invariant $\frac{\int_M
R(g_k)dV_{g_k}}{6\sqrt{\mathrm{Vol}(M,g_k)}}$ is strictly smaller than the
Yamabe constant of the standard sphere $\mathbb{S}^4$, then the subsequence of
distance functions $\{d_k\}$ defined by $\{g_k\}$ uniformly converges to $d_u$
and the subsequence of metric spaces $\{(M,d_k)\}$ converges to the metric
space $(M,d_u)$ in the Gromov-Hausdorff topology, where $d_u$ is the distance
function defined by $u^2g_0$.


  We propose a non-parametric method to cluster mixed data containing both
continuous and discrete random variables. The product space of continuous and
categorical sample spaces is approximated locally by analyzing neighborhoods
with cluster patterns. Detection of cluster patterns on the product space is
determined by using a modified Chi-square test. The proposed method does not
impose a global distance function which could be difficult to specify in
practice. Results from simulation studies have shown that our proposed methods
out-performed the benchmark method, AutoClass, for various settings.


  Output power of resonant-tunneling-diode (RTD) terahertz (THz) emitters can
be modulated by the bias modulation similar to a semiconductor laser. This
property is useful for applications of the THz waves to wireless communications
and radars. In this paper, we theoretically analyze the modulation-frequency
dependence of the output response using an equivalent circuit of the RTD-THz
oscillator. It is shown that there exists an intrinsic cutoff frequency of
modulation in RTD, which is independent of the external circuit that supplies
the modulation signal to the oscillator. This cutoff frequency is determined by
the time constant given by the capacitance of RTD divided by the absolute value
of negative differential conductance minus loss conductance of the oscillator,
and is about 100 GHz for typical RTD-THz oscillators. We also analyze the
effect of external feedback injection on the modulation characteristics. If the
period of the modulation frequency is equal to an integral multiple of the
round-trip time of the feedback, a dip or peak occurs in the modulation
response of the output, depending on whether the THz carrier components in the
output and the feedback are in phase or out of phase. We also discuss the
possibility of increase in cutoff frequency by the feedback with short
round-trip time.


  In 1996, A. Norton and D. Sullivan asked the following question: If
$f:\mathbb{T}^2\rightarrow\mathbb{T}^2$ is a diffeomorphism,
$h:\mathbb{T}^2\rightarrow\mathbb{T}^2$ is a continuous map homotopic to the
identity, and $h f=T_{\rho} h$ where $\rho\in\mathbb{R}^2$ is a totally
irrational vector and $T_{\rho}:\mathbb{T}^2\rightarrow\mathbb{T}^2,\, z\mapsto
z+\rho$ is a translation, are there natural geometric conditions (e.g.
smoothness) on $f$ that force $h$ to be a homeomorphism? In [ J. Wang and Z.
Zhang, GAFA 2018 ], the first author and Z. Zhang gave a negative answer to the
above question in the $C^{\infty}$ category: In general, not even the infinite
smoothness condition can force $h$ to be a homeomorphism. In this article, we
give a negative answer in the $C^{\omega}$ category: We construct a
real-analytic conservative and minimal totally irrational pseudo-rotation of
$\mathbb{T}^2$ that is semi-conjugate to a translation but not conjugate to a
translation, which simultaneously answers a question raised in [ J. Wang and Z.
Zhang, GAFA 2018 ].


  We obtain a magnetically charged regular black hole in general relativity.
The source to the Einstein field equations is nonlinear electrodynamic field in
a physically reasonable model of nonlinear electrodynamics (NED). "Physically"
here means the NED model is constructed on the basis of three conditions: the
Maxwell asymptotic in the weak electromagnetic field limit; the presence of
vacuum birefringence phenomenon; and satisfying the weak energy condition
(WEC). In addition, we analyze the thermodynamic properties of the regular
black hole in two ways. According to the usual black hole thermodynamics, we
calculate the heat capacity at constant charge, from which we know the smaller
black hole is more stable. We also employ the horizon thermodynamics to discuss
the thermodynamic quantities, especially the heat capacity at constant
pressure.


  Non-Hermitian properties of open quantum systems and their applications have
attracted much attention in recent years. While most of the studies focus on
the characteristic nature of non-Hermitian systems, here we focus on the
following issue: A non-Hermitian system can be a subsystem of a Hermitian
system as one can clearly see in Feshbach projective operator (FPO) formalism.
In this case, the orthogonality of the eigenvectors of the total (Hermitian)
system must be sustained, despite the eigenvectors of the subsystem
(non-Hermitian) satisfy the bi-orthogonal condition. Therefore, one can predict
that there must exist some remarkable processes that relate the non-Hermitian
subsystem and the rest part, and ultimately preserve the Hermiticity of the
total system. In this paper, we study such processes in open elliptical
microcavities. The inner part of the cavity is a non-Hermitian system, and the
outer part is the coupled bath in FPO formalism. We investigate the correlation
between the inner- and the outer-part behaviors associated with the avoided
resonance crossings (ARCs), and analyze the results in terms of a trade-off
between the relative difference of self-energies and collective Lamb shifts.
These results come from the conservation of the orthogonality in the total
Hermitian quantum system.


  Branching is an essential element of streamer discharge dynamics but today it
is understood only qualitatively. The variability and irregularity observed in
branched streamer trees suggest that stochastic terms are relevant for the
description of streamer branching. We here consider electron density
fluctuations due to the discrete particle number as a source of stochasticity
in positive streamers in air at standard temperature and pressure. We derive a
quantitative estimate for the branching distance that agrees within a factor of
2 with experimental values. As branching without noise would occur later, if at
all, we conclude that stochastic particle noise is relevant for streamer
branching in air at atmospheric pressure.


  The paper describes the straightforward method of calculation of anomalous
absorption of ordinary wave due to transformation into plasma wave in the
upper-hybrid resonance region of magnetized plasma with random irregularities.
The method is based on the general approach to calculation of scattering or
transformation cross-sections in magnetized plasma. The expressions for
anomalous attenuation obtained in the paper take into account the thermal
motions of the particles and have a wide area of application. Numeric
estimations of anomalous absorption for different conditions are carried out.


  Single molecule magnets (SMMs) with single-ion anisotropies $\mathbf d$,
comparable to exchange interactions J, between spins have recently been
synthesized. In this paper, we provide theoretical insights into the magnetism
of such systems. We study spin chains with site spins, s=1, 3/2 and 2 and
on-site anisotropy $\mathbf d$ comparable to the exchange constants between the
spins. We find that large $\mathbf d$ leads to crossing of the states with
different $M_S$ values in the same spin manifold of the $\mathbf d = 0$ limit.
For very large $\mathbf d$'s we also find that the $M_S$ states of the higher
energy spin states descend below the $M_S$ states of the ground state spin
manifold. Total spin in this limit is no longer conserved and describing the
molecular anisotropy by the constants $D_M$ and $E_M$ is not possible. However,
the total spin of the low-lying large $M_S$ states is very nearly an integer
and using this spin value it is possible to construct an effective spin
Hamiltonian and compute the molecular magnetic anisotropy constants $D_M$ and
$E_M$. We report effect of finite sizes, rotations of site anisotropies and
chain dimerization on the effective anisotropy of the spin chains.


  Atomic frequency comb (AFC) made of an ensemble of atoms with a periodic
optical resonance was originally proposed as a viable approach for quantum
memory for photons. In this paper, we examine the quantum cloning capacity of
an AFC in terms of the spectral distribution of the atomic populations in the
energy levels associated by the optical transition. Expressions are derived for
the memory readout efficiency, signal to noise ratio, and fidelity for an input
at the single photon level. When applied to a square toothed AFC, our analysis
shows that there is a region where amplification from the excited state results
in greater than unit recall efficiency, while maintaining a fidelity greater
than the classical limit.


  Magnus proved that, given two elements $x$ and $y$ of a finitely generated
free group $F$ with equal normal closures $\langle x\rangle^F=\langle
y\rangle^F$, then $x$ is conjugated either to $y$ or $y^{-1}$. More recently,
this property, called the Magnus property, has been generalized to oriented
surface groups.
  In this paper, we consider an analogue property for profinite surface groups.
While Magnus property, in general, does not hold in the profinite setting, it
does hold in some restricted form. In particular, for ${\mathscr S}$ a class of
finite groups, we prove that, if $x$ and $y$ are \emph{algebraically simple}
elements of the pro-${\mathscr S}$ completion $\hat{\Pi}^{\mathscr S}$ of an
orientable surface group $\Pi$, such that, for all $n\in{\mathbb N}$, there
holds $\langle x^n\rangle^{\hat{\Pi}^{\mathscr S}}=\langle
y^n\rangle^{\hat{\Pi}^{\mathscr S}}$, then $x$ is conjugated to $y^s$ for some
$s\in(\hat{\mathbb Z}^{\mathscr S})^\ast$. As a matter of fact, a much more
general property is proved and further extended to a wider class of profinite
completions.
  The most important application of the theory above is a generalization of the
description of centralizers of profinite Dehn twists to profinite Dehn
multitwists.


  We study the equation state of strongly interacting quark matter within a
NJL-like model in which the chiral condensates and the color superconducting
gaps are computed self-consistently as a function of the baryon density. A
vector interaction term is added to the Lagrangian in order to render the quark
matter equation of state stiffer. For the low density hadronic phase we use a
relativistic mean field model. The phase transition to quark matter is computed
by a Maxwell construction. We show that stable CFL cores in hybrid stars are
possible if the superconducting gap is sufficiently large. Moreover we find
stable stellar configurations in which two phase transitions occur, a first
transition from hadronic matter to 2SC quark matter and a second transition
from 2SC quark matter to CFL quark matter.


  Normalizing flow is a generative modeling approach with efficient sampling.
However, Flow-based models suffer two issues: 1) If the target distribution is
manifold, due to the unmatch between the dimensions of the latent target
distribution and the data distribution, flow-based models might perform badly.
2) Discrete data might make flow-based models collapse into a degenerate
mixture of point masses. To sidestep such two issues, we propose PaddingFlow, a
novel dequantization method, which improves normalizing flows with
padding-dimensional noise. To implement PaddingFlow, only the dimension of
normalizing flows needs to be modified. Thus, our method is easy to implement
and computationally cheap. Moreover, the padding-dimensional noise is only
added to the padding dimension, which means PaddingFlow can dequantize without
changing data distributions. Implementing existing dequantization methods needs
to change data distributions, which might degrade performance. We validate our
method on the main benchmarks of unconditional density estimation, including
five tabular datasets and four image datasets for Variational Autoencoder (VAE)
models, and the Inverse Kinematics (IK) experiments which are conditional
density estimation. The results show that PaddingFlow can perform better in all
experiments in this paper, which means PaddingFlow is widely suitable for
various tasks. The code is available at:
https://github.com/AdamQLMeng/PaddingFlow.


  Among unidentified gamma-ray sources in the galactic plane, there are some
that present significant variability and have been proposed to be high-mass
microquasars. To deepen the study of the possible association between variable
low galactic latitude gamma-ray sources and microquasars, we have applied a
leptonic jet model based on the microquasar scenario that reproduces the
gamma-ray spectrum of three unidentified gamma-ray sources, 3EG J1735-1500, 3EG
J1828+0142 and GRO J1411-64, and is consistent with the observational
constraints at lower energies. We conclude that if these sources were generated
by microquasars, the particle acceleration processes could not be as efficient
as in other objects of this type that present harder gamma-ray spectra.
Moreover, the dominant mechanism of high-energy emission should be synchrotron
self-Compton (SSC) scattering, and the radio jets may only be observed at low
frequencies. For each particular case, further predictions of jet physical
conditions and variability generation mechanisms have been made in the context
of the model. Although there might be other candidates able to explain the
emission coming from these sources, microquasars cannot be excluded as
counterparts. Observations performed by the next generation of gamma-ray
instruments, like GLAST, are required to test the proposed model.


  We investigate an atomic $\Lambda$-system with one transition coupled to a
laser field and a flat continuum of vacuum modes and the other transition
coupled to field modes near the edge of a photonic band gap. The system
requires simultaneous treatment of Markovian and non-Markovian dissipation
processes, but the photonic band gap continuum can not be eliminated within a
density matrix treatment. Instead we propose a formalism based on Monte-Carlo
wavefunctions, and we present results relevant to an experimental
characterization of a structured continuum.


  The linear-algebraic lambda-calculus and the algebraic lambda-calculus are
untyped lambda-calculi extended with arbitrary linear combinations of terms.
The former presents the axioms of linear algebra in the form of a rewrite
system, while the latter uses equalities. When given by rewrites, algebraic
lambda-calculi are not confluent unless further restrictions are added. We
provide a type system for the linear-algebraic lambda-calculus enforcing strong
normalisation, which gives back confluence. The type system allows an abstract
interpretation in System F.


  BCC transition metals (TMs) exhibit complex temperature and strain-rate
dependent plastic deformation behaviour controlled by individual crystal
lattice defects. Classical empirical and semi-empirical interatomic potentials
have limited capability in modelling defect properties such as the screw
dislocation core structures and Peierls barriers in the BCC structure. Machine
learning (ML) potentials, trained on DFT-based datasets, have shown some
successes in reproducing dislocation core properties. However, in group VB TMs,
the most widely-used DFT functionals produce erroneous shear moduli C44 which
are undesirably transferred to machine-learning interatomic potentials, leaving
current ML approaches unsuitable for this important class of metals and alloys.
Here, we develop two interatomic potentials for BCC vanadium (V) based on (i)
an extension of the partial electron density and screening parameter in the
classical semi-empirical modified embedded-atom method (XMEAM-V) and (ii) a
recent hybrid descriptor in the ML Deep Potential framework (DP-HYB-V). We
describe distinct features in these two disparate approaches, including their
dataset generation, training procedure, weakness and strength in modelling
lattice and defect properties in BCC V. Both XMEAM-V and DP-HYB-V reproduce a
broad range of defect properties relevant to plastic deformation and fracture.
In particular, XMEAM-V reproduces nearly all mechanical and thermodynamic
properties at DFT accuracies and with C44 near experimental value. XMEAM-V also
naturally exhibits the anomalous slip at 77 K widely observed in group VB and
VIB TMs and outperforms all existing, publically available interatomic
potentials for V. The XMEAM thus provides a practical path to developing
accurate and efficient interatomic potentials for nonmagnetic BCC TMs and
possibly multi-principal element TM alloys.


  It is shown that an extra magnetization is induced by an onset of the
equal-spin-pairing of spin triplet superconductivity if the energy dependence
of the density of states of quasiparticles exists in the normal state. It turns
out that the effect is observable in Sr_2RuO_4 due to the existence of van Hove
singularity in the density of states near the Fermi level, explaining the extra
contribution in the Knight shift reported by Ishida et al. It is also quite
non-trivial that this effect exists even without external magnetic field, which
implies that the time reversal symmetry is spontaneously broken in the spin
space.


  Using a method developped in [1] and [2], we prove the existence of weak non
trivial solutions to fourth order elliptic equations with singularities and
with critical Sobolev growth.


  In recent years, deep learning has been widely used in SAR ATR and achieved
excellent performance on the MSTAR dataset. However, due to constrained imaging
conditions, MSTAR has data biases such as background correlation, i.e.,
background clutter properties have a spurious correlation with target classes.
Deep learning can overfit clutter to reduce training errors. Therefore, the
degree of overfitting for clutter reflects the non-causality of deep learning
in SAR ATR. Existing methods only qualitatively analyze this phenomenon. In
this paper, we quantify the contributions of different regions to target
recognition based on the Shapley value. The Shapley value of clutter measures
the degree of overfitting. Moreover, we explain how data bias and model bias
contribute to non-causality. Concisely, data bias leads to comparable
signal-to-clutter ratios and clutter textures in training and test sets. And
various model structures have different degrees of overfitting for these
biases. The experimental results of various models under standard operating
conditions on the MSTAR dataset support our conclusions. Our code is available
at https://github.com/waterdisappear/Data-Bias-in-MSTAR.


  Unprecedented possibilities of quadruped robots have driven much research on
the technical aspects of these robots. However, the social perception and
acceptability of quadruped robots so far remain poorly understood. This work
investigates whether the way we design quadruped robots' behaviors can affect
people's perception of safety in interactions with these robots. We designed
and tested a dominant and submissive personality for the quadruped robot
(Boston Dynamics Spot). These were tested in two different walking scenarios
(head-on and crossing interactions) in a 2x2 within-subjects study. We
collected both behavioral data and subjective reports on participants'
perception of the interaction. The results highlight that participants
perceived the submissive robot as safer compared to the dominant one. The
behavioral dynamics of interactions did not change depending on the robot's
appearance. Participants' previous in-person experience with the robot was
associated with lower subjective safety ratings but did not correlate with the
interaction dynamics. Our findings have implications for the design of
quadruped robots and contribute to the body of knowledge on the social
perception of non-humanoid robots. We call for a stronger standing of felt
experiences in human-robot interaction research.


  Ferrers diagram rank-metric codes were introduced by Etzion and Silberstein
in 2009. In their work, they proposed a conjecture on the largest dimension of
a space of matrices over a finite field whose nonzero elements are supported on
a given Ferrers diagram and all have rank lower bounded by a fixed positive
integer $d$. Since stated, the Etzion-Silberstein conjecture has been verified
in a number of cases, often requiring additional constraints on the field size
or on the minimum rank $d$ in dependence of the corresponding Ferrers diagram.
As of today, this conjecture still remains widely open. Using modular methods,
we give a constructive proof of the Etzion-Silberstein conjecture for the class
of strictly monotone Ferrers diagrams, which does not depend on the minimum
rank $d$ and holds over every finite field. In addition, we leverage on the
last result to also prove the conjecture for the class of MDS-constructible
Ferrers diagrams, without requiring any restriction on the field size.


  Nonequilibrium interfacial thermodynamics is formulated in the presence of
surface reactions for the study of diffusiophoresis in isothermal systems. As a
consequence of microreversibility and Onsager-Casimir reciprocal relations,
diffusiophoresis, i.e., the coupling of the tangential components of the
pressure tensor to the concentration gradients of solute species, has a
reciprocal effect where the interfacial currents of solutes is coupled to the
slip velocity. The presence of surface reactions is shown to modify the
diffusiophoretic and reciprocal effects at the fluid-solid interface. The
thin-layer approximation is used to describe the solution flowing near a
reactive solid interface. Analytic formulas describing the diffusiophoretic and
reciprocal effects are deduced in the thin-layer approximation and tested
numerically for the Poiseuille flow of a solution between catalytic planar
surfaces.


  Affordances, a concept rooted in ecological psychology and pioneered by James
J. Gibson, have emerged as a fundamental framework for understanding the
dynamic relationship between individuals and their environments. Expanding
beyond traditional perceptual and cognitive paradigms, affordances represent
the inherent effect and action possibilities that objects offer to the agents
within a given context. As a theoretical lens, affordances bridge the gap
between effect and action, providing a nuanced understanding of the connections
between agents' actions on entities and the effect of these actions. In this
study, we propose a model that unifies object, action and effect into a single
latent representation in a common latent space that is shared between all
affordances that we call the affordance space. Using this affordance space, our
system is able to generate effect trajectories when action and object are given
and is able to generate action trajectories when effect trajectories and
objects are given. In the experiments, we showed that our model does not learn
the behavior of each object but it learns the affordance relations shared by
the objects that we call equivalences. In addition to simulated experiments, we
showed that our model can be used for direct imitation in real world cases. We
also propose affordances as a base for Cross Embodiment transfer to link the
actions of different robots. Finally, we introduce selective loss as a solution
that allows valid outputs to be generated for indeterministic model inputs.


  Effects of medium polarization are studied for $^1S_0$ pairing in neutron and
nuclear matter. The screening potential is calculated in the RPA limit,
suitably renormalized to cure the low density mechanical instability of nuclear
matter. The selfenergy corrections are consistently included resulting in a
strong depletion of the Fermi surface. All medium effects are calculated based
on the Brueckner theory. The $^1S_0$ gap is determined from the generalized gap
equation. The selfenergy corrections always lead to a quenching of the gap,
which is enhanced by the screening effect of the pairing potential in neutron
matter, whereas it is almost completely compensated by the antiscreening effect
in nuclear matter.


  Effects of quantum and classical correlations on game theory are studied to
clarify the new aspects brought into game theory by the quantum mechanical
toolbox. In this study, we compare quantum correlation represented by a
maximally entangled state and classical correlation that is generated through
phase damping processes on the maximally entangled state. Thus, this also sheds
light on the behavior of games under the influence of noisy sources. It is
observed that the quantum correlation can always resolve the dilemmas in
non-zero sum games and attain the maximum sum of both players' payoffs, while
the classical correlation cannot necessarily resolve the dilemmas.


  Layered organic conductors (BEDO-TTF)_2ReO_4*H_2O (metal) and
(BEDT-TTF)_xDy(NO_3)_z (paramagnetic insulator) are studied by CW-EPR and SQUID
methods. A correlation in resonance and transport properties of both compounds
is attributed to a similar mechanism of fine anion ordering (AO) at T_AO=200 K.
Due to the hydrogen bonds motif the small configuration changes in anion
sub-lattice bring a profound effect on electronic properties. It is shown that
the spin system of (BEDO-TTF)_2ReO_4*H_2O consists of a fraction of delocalized
pi-type holes (I_epr=n(e_F)), I_epr(300K)=1,62*10^(-4) emu/mol and
antiferromagnetically correlated local moments S=1/2, chi_p(300K)=1,86*10^(-3)
emu/mol. The phase transition Me-Me at T_AO=203 K is detected by paramagnetic
relaxation and resisitivity but it is not observed in spin susceptibility.
Fraction of delocalized holes gradually decreases by factor 2 at cooling down
to 100 K, whereas contribution from local moments reaches maximum at 50 K and
falls to zero at 14 K. However, at 2 K total spin susceptibility is fully
recovered approaching 6*10^(-2) emu/mol. In turn, (BEDT-TTF)_xDy(NO_3)_z does
not have solvent bridges (H_2O) between neighboring anions and the disorder in
anion layer converts this compound into paramagnetic insulator. Moreover, the
anion metal-complexes Dy(NO_3)_z^n(-) contain magnetic ions Dy^3(+).
Nonetheless, the phase transition of similar origin is also detected at T=197 K
by ESR and resistivity measurements. Two spin sub-systems co-exist in this
compound: hopping local moments S=1/2 (BEDT-TTF^(+)), I_epr(300K)=6,3*10^(-4)
emu/mol and strongly localized 4f^9-electrons, J=15/2 (Dy^3(+)),
chi_p(300K)=4*10^(-2) emu/mol.


  We explore the possibility of CP violation in baryonic
$\Lambda_b\to(\Lambda_c^+, p^+)\pi^+\mu^-\mu^-$ decays which are mediated by
two Majorana sterile neutrino and are $|\Delta L|=2$ lepton number violating
processes. Appreciable CP asymmetry can be obtained if there are two on-shell
Majorana neutrinos that are quasi-degenerate in mass with the mass difference
of the order of average decay widths. We find that given the present
constraints on the heavy to light mixing element $|V_{\mu N}|$, the
$\Lambda_b\to p^+\pi^+\mu^-\mu^-$ and $\Lambda_b\to \Lambda_c^+\pi^+\mu^-\mu^-$
decay rates are suppressed but could be within the experimental reach at the
LHC. If searches of the modes are performed, then experimental limits on the
rates can be translated to constraints on the Majorana neutrino mass $m_N$ and
heavy to light mixing element squared $|V_{\mu N}|^2$. We show that the
constraints on the $(m_N, |V_{\mu N}|^2)$ parameter space coming from the
$|\Delta L| = 2$ baryonic decays are complementary to the bounds coming from
other processes.


  We study locally conformally balanced metrics on almost abelian Lie algebras,
namely solvable Lie algebras admitting an abelian ideal of codimension one,
providing characterizations in every dimension. Moreover, we classify
six-dimensional almost abelian Lie algebras admitting locally conformally
balanced metrics and study some compatibility results between different types
of special Hermitian metrics on almost abelian Lie groups and their compact
quotients. We end by classifying almost abelian Lie algebras admitting locally
conformally hyperk\"ahler structures.


  We show that, within mean-field theory, the density profile of a rapidly
rotating harmonically trapped Bose-Einstein condensate is of the Thomas-Fermi
form as long as the number of vortices is much larger than unity. Two forms of
the condensate wave function are explored: i) the lowest Landau level (LLL)
wave function with a regular lattice of vortices multiplied by a slowly varying
envelope function, which gives rise to components in higher Landau levels; ii)
the LLL wave function with a nonuniform vortex lattice. From variational
calculations we find it most favorable energetically to retain the LLL form of
the wave function but to allow the vortices to deviate slightly from a regular
lattice. The predicted distortions of the lattice are small, but in accord with
recent measurements at lower rates of rotation.


  A self-consistent electronic structure calculation based on the
Luttinger-Kohn model is performed on GaMnAs/GaAs multilayers. The Diluted
Magnetic Semiconductor layers are assumed to be metallic and ferromagnetic. The
high Mn concentration (considered as 5% in our calculation) makes it possible
to assume the density of magnetic moments as a continuous distribution, when
treating the magnetic interaction between holes and the localized moment on the
Mn(++) sites. Our calculation shows the distribution of heavy holes and light
holes in the structure. A strong spin-polarization is observed, and the charge
is concentrated mostly on the GaMnAs layers, due to heavy and light holes with
their total angular momentum aligned anti-parallel to the average
magnetization. The charge and spin distributions are analyzed in terms of their
dependence on the number of multilayers, the widths of the GaMnAs and GaAs
layers, and the width of lateral GaAs layers at the borders of the structure.


  SGR J1745$-$2900 is a magnetar near the Galactic center. X-ray observations
of this source found a decreasing X-ray luminosity accompanied by an enhanced
spindown rate. This negative correlation between X-ray luminosity and spindown
rate is hard to understand. The wind braking model of magnetars is employed to
explain this puzzling spindown behavior. During the release of magnetic energy
of magnetars, a system of particles may be generated. Some of these particles
remain trapped in the magnetosphere and may contribute to the X-ray luminosity.
The rest of the particles can flow out and take away the rotational energy of
the central neutron star. A smaller polar cap angle will cause the decrease of
X-ray luminosity and enhanced spindown rate of SGR J1745$-$2900. This magnetar
is expected to have a maximum spindown rate shortly.


  Simultaneously transmitting and reflecting reconfigurable intelligent surface
(STAR-RIS) is a novel technology which enables the full-space coverage. In this
letter, a multi STAR-RIS-aided system using non-orthogonal multiple access in
an uplink transmission is considered, where the multi-order reflections among
multiple STAR-RISs assist the transmission from the single-antenna users to the
multi-antenna base station. Specifically, the total sum rate maximization
problem is solved by jointly optimizing the active beamforming, power
allocation, transmission and reflection beamforming at the STAR-RIS, and
user-STAR-RIS assignment. To solve the non-convex optimization problem, a novel
deep reinforcement learning algorithm is proposed which integrates
meta-learning and deep deterministic policy gradient (DDPG), denoted by
Meta-DDPG. Numerical results demonstrate that our proposed Meta-DDPG algorithm
outperforms the conventional DDPG algorithm with $53\%$ improvement, while
multi-order reflections among multi STAR-RISs yields to $14.1\%$ enhancement in
the total data rate.


  Coherent control of the nitrogen-vacancy (NV) center in diamond's triplet
spin state has traditionally been accomplished with resonant ac magnetic fields
under the constraint of the magnetic dipole selection rule, which forbids
direct control of the $|-1>\leftrightarrow |+1>$ spin transition. We show that
high-frequency stress resonant with the spin state splitting can coherently
control NV center spins within this subspace. Using a bulk-mode mechanical
microresonator fabricated from single-crystal diamond, we apply intense ac
stress to the diamond substrate and observe mechanically driven Rabi
oscillations between the $|-1>$ and $|+1>$ states of an NV center spin
ensemble. Additionally, we measure the inhomogeneous spin dephasing time
($T_{2}^{*}$) of the spin ensemble using a mechanical Ramsey sequence and
compare it to the dephasing times measured with a magnetic Ramsey sequence for
each of the three spin qubit combinations available within the NV center ground
state. These results demonstrate coherent spin driving with a mechanical
resonator and could enable the creation of a phase-sensitive $\Delta$-system
within the NV center ground state.