  We present the results from a joint Suzaku/NuSTAR broad-band spectral
analysis of 3C 390.3. The high quality data enables us to clearly separate the
primary continuum from the reprocessed components allowing us to detect a high
energy spectral cut-off ($E_\text{cut}=117_{-14}^{+18}$ keV), and to place
constraints on the Comptonization parameters of the primary continuum for the
first time. The hard over soft compactness is 69$_{-24}^{+124}$ and the optical
depth 4.1$_{-3.6}^{+0.5}$, this leads to an electron temperature of
$30_{-8}^{+32}$ keV. Expanding our study of the Comptonization spectrum to the
optical/UV by studying the simultaneous Swift-UVOT data, we find indications
that the compactness of the corona allows only a small fraction of the total
UV/optical flux to be Comptonized. Our analysis of the reprocessed emission
show that 3C 390.3 only has a small amount of reflection (R~0.3), and of that
the vast majority is from distant neutral matter. However we also discover a
soft X-ray excess in the source, which can be described by a weak ionized
reflection component from the inner parts of the accretion disk. In addition to
the backscattered emission, we also detect the highly ionized iron emission
lines Fe XXV and Fe XXVI.


  We examine various physical processes that may explain the shallow high-mass
slope of the IMF as well as the low SFR in star-forming molecular clouds (MCs)
in the Central Molecular Zone (CMZ). We show that the strong tidal field and
the tidal shear experienced by the CMZ have opposite effects on the collapse of
density fluctuations and nearly compensate, but in any case have a negligible
impact and can not explain these unusual properties. Similarly, we show that
the intense magnetic field in the CMZ provides a negligible pressure support
and, for the high densities at play should not modify the probability density
function (PDF) of the turbulent gas flow in the clouds, thus affecting
negligibly the slope of the IMF. However, we show that, in contrast to MCs in
the Galactic disk, the ones in the CMZ experience only one single episode of
turbulence injection at large scale, most likely due dominantly to bar gas
inflow. Indeed, their rather short lifetime, due to their high mean densities,
is similar to one typical turbulence crossing time. Consequently, according to
the Hennebelle-Chabrier theory of star formation, within this 'single
turbulence episode' scenario, the cloud experiences one single field of
turbulence induced density fluctuations, leading eventually to gravitationally
unstable prestellar cores. As shown in Hennebelle & Chabrier (2013}, this
yields a flatter IMF than usual and leads to the correct observed slope for the
CMZ star-forming clouds. Similarly, this single large scale turbulence event
within the cloud lifetime yields a 5 to 6 lower SFR than under usual MW cloud
conditions, again in agreement with the observed values. Therefore, we suggest
that this 'single large scale turbulence injection' episode can explain both
the shallow IMF high-mass slope and low SFR of clouds in the CMZ.


  An unconventional pairing mechanism in the heavy-fermion material
$\mathrm{URu_{2}Si_{2}}$ is studied. We propose a mixed singlet-triplet
$d$-density wave to be the hidden-order state in $\mathrm{URu_{2}Si_{2}}$. The
exotic order is topologically nontrivial and supports a charge $2e$ skyrmionic
spin texture, which is assumed to fractionalize into merons and antimerons at
the deconfined quantum critical point. The interaction between these fractional
particles results in a (pseudo)spin-singlet chiral $d$-wave superconducting
state, which breaks time reversal symmetry. Therefore, it is highly likely to
produce a nonzero signal of the polar Kerr effect at the onset of the
superconductivity, consistent with recent experiments. In addition, the nodal
structures of the possible pairing functions in our model are consistent with
the thermodynamic experiments in $\mathrm{URu_{2}Si_{2}}$.


  Two rods made from sol-gel silica have been doped with Ce ions or co-doped
with Ce and Tb ions respectively. First, a thermoluminescence (TL)
characterization of the trapping and luminescence parameters is carried out to
understand the physical mechanisms involved following the irradiation of these
rods and to evaluate their dosimetric properties. The optically stimulated
luminescence (OSL) and the radioluminescence (RL) responses as a function of
respectively absorbed dose and dose rate are assessed. The OSL response of both
rods is linear as a function of the absorbed dose. The RL sensitivity of both
rods proves not only to be extremely high but also shows a linear behavior over
more than 6 decades, allowing real-time detection of dose rates as low as few
$\mu$Gy s$^{-1}$, a threshold that to our knowledge, has never been reached.
The results from RL and OSL show that these silica-based doped rods are
potentially suitable for medical dosimetry and environmental monitoring around
nuclear sites.


  A Lie (super)algebra with a non-degenerate invariant symmetric bilinear form
will be called a NIS-Lie (super)algebra. The double extension of a NIS-Lie
(super)algebra is the result of simultaneously adding to it a central element
and an outer derivation so that the larger algebra has also a NIS. Affine loop
algebras, Lie (super)algebras with symmetrizable Cartan matrix over any field,
Manin triples, symplectic reflection (super)algebras are among the Lie
(super)algebras suitable to be doubly extended.
  We consider double extensions of Lie superalgebras in characteristic 2, and
concentrate on peculiarities of these notions related with the possibility for
the bilinear form, the center, and the derivation to be odd. Two Lie
superalgebras we discovered by this method are indigenous to the characteristic
2.


  When an NLP model is trained on text data from one time period and tested or
deployed on data from another, the resulting temporal misalignment can degrade
end-task performance. In this work, we establish a suite of eight diverse tasks
across different domains (social media, science papers, news, and reviews) and
periods of time (spanning five years or more) to quantify the effects of
temporal misalignment. Our study is focused on the ubiquitous setting where a
pretrained model is optionally adapted through continued domain-specific
pretraining, followed by task-specific finetuning. We establish a suite of
tasks across multiple domains to study temporal misalignment in modern NLP
systems. We find stronger effects of temporal misalignment on task performance
than have been previously reported. We also find that, while temporal
adaptation through continued pretraining can help, these gains are small
compared to task-specific finetuning on data from the target time period. Our
findings motivate continued research to improve temporal robustness of NLP
models.


  Let f_n^r(k) be the number of 132-avoiding permutations on n letters that
contain exactly r occurrences of 12... k, and let F_r(x;k) and F(x,y;k) be the
generating functions defined by $F_r(x;k)=\sum_{n\gs0} f_n^r(k)x^n$ and
$F(x,y;k)=\sum_{r\gs0}F_r(x;k)y^r$. We find an explcit expression for F(x,y;k)
in the form of a continued fraction. This allows us to express F_r(x;k) for
$1\ls r\ls k$ via Chebyshev polynomials of the second kind.


  Various combinatorial optimization NP-hard problems can be reduced to finding
the minimizer of an Ising model, which is a discrete mathematical model. It is
an intellectual challenge to develop some mathematical tools or algorithms for
solving the Ising model. Over the past decades, some continuous approaches or
algorithms have been proposed from physical, mathematical or computational
views for optimizing the Ising model such as quantum annealing, the coherent
Ising machine, simulated annealing, adiabatic Hamiltonian systems, etc..
However, the mathematical principle of these algorithms is far from being
understood. In this paper, we reveal the mathematical mechanism of dynamical
system algorithms for the Ising model by Morse theory and variational methods.
We prove that the dynamical system algorithms can be designed to minimize a
continuous function whose local minimum points give all the candidates of the
Ising model and the global minimum gives the minimizer of Ising problem. Using
this mathematical mechanism, we can easily understand several dynamical system
algorithms of the Ising model such as the coherent Ising machine, the
Kerr-nonlinear parametric oscillators and the simulated bifurcation algorithm.
Furthermore, motivated by the works of C. Conley, we study transit and capture
properties of the simulated bifurcation algorithm to explain its convergence by
the low energy transit and capture in celestial mechanics. A detailed
discussion on $2$-spin and $3$-spin Ising models is presented as application.


  We show that the fundamental group of the complement of an arrangement of
complex lines in the complex plane is a free group if and only if the
arrangement is a union of parallel lines.


  Site diluted spin-1/2 Ising and spin-1 Blume Capel (BC) models in the
presence of transverse field interactions are examined by introducing an
effective-field approximation that takes into account the multi-site
correlations in the cluster of a considered lattice with an improved
configurational averaging technique. The critical concentration below which the
transition temperature reduces to zero is determined for both models, and the
estimated values are compared with those obtained by the other methods in the
literature. It is found that diluting the lattice sites by non magnetic atoms
may cause some drastic changes on some of the characteristic features of the
model. Particular attention has been paid on the global phase diagrams of a
spin-1 BC model, and it has also been shown that the conditions for the
occurrence of a second order reentrance in the system is rather complicated,
since the existence or extinction of reentrance is rather sensitive to the
competing effects between D/J, \Omega/J and c.


  Herding behavior has become a familiar phenomenon to investors, carrying the
potential danger of both undervaluing and overvaluing assets, while also
threatening market stability. This study contributes to the literature on
herding behavior by using a more recent dataset to cover the most impactful
events of recent years. To our knowledge, this is the first study examining
herding behavior across three different types of investment vehicle.
Furthermore, this is also the first study observing herding at a community
(subset) level. Specifically, we first explore this phenomenon in each separate
type of investment vehicle, namely stocks, US ETFs and cryptocurrencies, using
the widely recognized Cross Sectional Absolute Deviation (CSAD) model. We find
similar herding patterns between stocks and US ETFs, while these traditional
assets reveal a distinction from cryptocurrencies. Subsequently, the same
experiment is implemented on a combination of all three investment vehicle
types. For a deeper investigation, we adopt graph-based techniques such as
Minimum Spanning Tree (MST) and Louvain community detection to partition the
given combination into smaller subsets whose assets are most similar to each
other, then seek to detect the herding behavior on each subset. We find that
herding behavior exists at all times across all types of investment vehicle at
a subset level, although the herding might not manifest at the superset level.
Additionally, this herding behavior tends to stem from specific events that
solely impact that subset of assets. Given these findings, investors can
construct an appropriate investment strategy composed of their choice of
investment vehicles they are interested in.


  Estimating out-of-distribution (OOD) uncertainty is a central challenge for
safely deploying machine learning models in the open-world environment.
Improved methods for OOD detection in multi-class classification have emerged,
while OOD detection methods for multi-label classification remain underexplored
and use rudimentary techniques. We propose JointEnergy, a simple and effective
method, which estimates the OOD indicator scores by aggregating energy scores
from multiple labels. We show that JointEnergy can be mathematically
interpreted from a joint likelihood perspective. Our results show consistent
improvement over previous methods that are based on the maximum-valued scores,
which fail to capture joint information from multiple labels. We demonstrate
the effectiveness of our method on three common multi-label classification
benchmarks, including MS-COCO, PASCAL-VOC, and NUS-WIDE. We show that
JointEnergy can reduce the FPR95 by up to 10.05% compared to the previous best
baseline, establishing state-of-the-art performance.


  We discuss a new description for the Roper resonance, the first nucleon
excited state of JP = 1/2+, in a model of strong diquark correlations. Treating
the scalar-isoscalar and axial-vector--isovector diquarks as independent
degrees of freedom, two states having nucleon quantum numbers are constructed.
Due to the scalar and axial-vector nature of the diquarks, the two nucleon
states have different internal structure of spin and isospin. This yields the
mass splitting of order several hundreds MeV, and hence the two states are
identified with the nucleon and Roper. We demonstrate this scenario in a simple
two channel problem.


  As quantum devices become more complex and the requirements on these devices
become more demanding, it is crucial to be able to verify the performance of
such devices in a scalable and reliable fashion. A cornerstone task in this
challenge is quantifying how close an experimentally prepared quantum state is
to the desired one. Here we present a method to construct an estimator for the
quantum state fidelity that is compatible with any measurement protocol. Our
method provides a confidence interval on this estimator that is guaranteed to
be nearly minimax optimal for the specified measurement protocol. For a
well-chosen measurement scheme, our method is competitive in the number of
measurement outcomes required for estimation. We demonstrate our method using
simulations and experimental data from a trapped-ion quantum computer and
compare the results to state-of-the-art techniques. Our method can be easily
extended to estimate the expectation value of any observable, such as
entanglement witnesses.


  In this paper we develop a new explicit method to studying rational points
near manifolds and obtain optimal lower bounds on the number of rational points
of bounded height lying at a given distance from an arbitrary non-degenerate
curve. This generalises previous results for analytic non-degenerate curves.
Furthermore, the main results are also proved in the inhomogeneous setting.
Applications of the main theorem include the Khintchine-Jarn\'ik type theorem
for divergence for arbitrary non-degenerate curve in $\mathbb{R}^n$.


  We undertake a study of conic bundle threefolds $\pi\colon X\to W$ over
geometrically rational surfaces whose associated discriminant covers
$\tilde{\Delta}\to\Delta\subset W$ are smooth and geometrically irreducible.
First, we determine the structure of the group $\mathrm{CH}^2 X_{\overline{k}}$
of rational equivalence classes of curves. Precisely, we construct a
Galois-equivariant group homomorphism from $\mathrm{CH}^2X_{\overline{k}}$ to a
group scheme associated to the discriminant cover $\tilde{\Delta}\to \Delta$ of
$X$. The target group scheme is a generalization of the Prym variety of
$\tilde{\Delta}\to\Delta$ and so our result can be viewed as a generalization
of Beauville's result that the algebraically trivial curve classes on
$X_{\overline{k}}$ are parametrized by the Prym variety.
  We apply our structural result on curve classes to study the refined
intermediate Jacobian torsor (IJT) obstruction to rationality introduced by
Hassett--Tschinkel and Benoist--Wittenberg. The first case of interest is $W =
\mathbb P^2$ and $\Delta$ is a smooth plane quartic. In this case, we show that
the IJT obstruction characterizes rationality when the ground field has less
arithmetic complexity (precisely, when the $2$-torsion in the Brauer group of
the ground field is trivial). We also show that a hypothesis of this form is
necessary by constructing, over any $k \subset\mathbb R$, a conic bundle
threefold with $\Delta$ a smooth quartic where the IJT obstruction vanishes,
yet $X$ is irrational over $k$.


  We study the phases of doped spin S=1/2 quantum antiferromagnets on the
square lattice, as they evolve from paramagnetic Mott insulators with valence
bond solid (VBS) order at zero doping, to superconductors at moderate doping.
The interplay between density wave/VBS order and superconductivity is
efficiently described by the quantum dimer model, which acts as an effective
theory for the total spin S=0 sector. We extend the dimer model to include
fermionic S=1/2 excitations, and show that its mean-field, static gauge field
saddle points have projective symmetries (PSGs) similar to those of `slave'
particle U(1) and SU(2) gauge theories. We account for the non-perturbative
effects of gauge fluctuations by a duality mapping of the S=0 dimer model. The
dual theory of vortices has a PSG identical to that found in a previous paper
(L. Balents et al., cond-mat/0408329) by a duality analysis of bosons on the
square lattice. The previous theory therefore also describes fluctuations
across superconducting, supersolid and Mott insulating phases of the present
electronic model. Finally, with the aim of describing neutron scattering
experiments, we present a phenomenological model for collective S=1 excitations
and their coupling to superflow and density wave fluctuations.


  The practical deployment of Neural Radiance Fields (NeRF) in rendering
applications faces several challenges, with the most critical one being low
rendering speed on even high-end graphic processing units (GPUs). In this
paper, we present ICARUS, a specialized accelerator architecture tailored for
NeRF rendering. Unlike GPUs using general purpose computing and memory
architectures for NeRF, ICARUS executes the complete NeRF pipeline using
dedicated plenoptic cores (PLCore) consisting of a positional encoding unit
(PEU), a multi-layer perceptron (MLP) engine, and a volume rendering unit
(VRU). A PLCore takes in positions \& directions and renders the corresponding
pixel colors without any intermediate data going off-chip for temporary storage
and exchange, which can be time and power consuming. To implement the most
expensive component of NeRF, i.e., the MLP, we transform the fully connected
operations to approximated reconfigurable multiple constant multiplications
(MCMs), where common subexpressions are shared across different multiplications
to improve the computation efficiency. We build a prototype ICARUS using
Synopsys HAPS-80 S104, a field programmable gate array (FPGA)-based prototyping
system for large-scale integrated circuits and systems design. We evaluate the
power-performance-area (PPA) of a PLCore using 40nm LP CMOS technology. Working
at 400 MHz, a single PLCore occupies 16.5 $mm^2$ and consumes 282.8 mW,
translating to 0.105 uJ/sample. The results are compared with those of GPU and
tensor processing unit (TPU) implementations.


  Superconducting stiffness $\rho_s$ and coherence length $\xi$ are usually
determined by measuring the penetration depth $\lambda$ of a magnetic field and
the upper critical field $H_{c2}$ of a superconductor (SC), respectively.
However, in magnetic SC, e.g. some of the iron-based, this could lead to
erroneous results since the internal field could be very different from the
applied one. To overcome this problem in Fe$_{1+y}$Se$_x$Te$_{1-x}$ with $x
\sim 0.5$ and $y \sim 0$ (FST), we measure both quantities with the
Stiffnessometer technique. In this technique, one applies a rotor-free vector
potential $\textbf{A}$ to a superconducting ring and measures the current
density $\textbf{j}$ via the ring's magnetic moment $\textbf{m}$. $\rho_s$ and
$\xi$ are determined from London's equation $\textbf{j}=-\rho_s\textbf{A}$ and
its range of validity. This method is particularly accurate at temperatures
close to the critical temperature $T_c$. We find weaker $\rho_s$ and longer
$\xi$ than existing literature reports, and critical exponents which agree
better with expectations based on the Ginzburg-Landau theory.


  The fact that no evidence of new physics was found so far by LHC experiments
has led some to call for the abandonment of the naturalness criterion. Others,
on the contrary, have felt the need to break a lance in its defense by claiming
that it should not be dismissed too quickly, but rather only reshaped to fit
new needs. In this paper we argue that present pro or contra naturalness
debates often miss an important historical point: that naturalness is
essentially a hazily defined notion which, in the course of more than four
decades, has been steadily, and often not coherently, shaped by its interplay
with different branches of model-building in high-energy physics and cosmology
on the one side, and new experimental results on the other side. The paper
endeavours to clear up some of the physical and philosophical haze by taking a
closer look back at the origin of naturalness in the 1970s and 1980s, with
particular attention to the early work of Kenneth Wilson.


  The quantum dynamics of an ensemble of interacting electrons in an array of
random scatterers is treated using a new numerical approach for the calculation
of average values of quantum operators and time correlation functions in the
Wigner representation. The Fourier transform of the product of matrix elements
of the dynamic propagators obeys an integral Wigner-Liouville-type equation.
Initial conditions for this equation are given by the Fourier transform of the
Wiener path integral representation of the matrix elements of the propagators
at the chosen initial times. This approach combines both molecular dynamics and
Monte Carlo methods and computes numerical traces and spectra of the relevant
dynamical quantities such as momentum-momentum correlation functions and
spatial dispersions. Considering as an application a system with fixed
scatterers, the results clearly demonstrate that the many-particle interaction
between the electrons leads to an enhancement of the conductivity and spatial
dispersion compared to the noninteracting case.


  High-frequency linear accelerators are very suitable for carbon ion therapy,
thanks to the reduced operational costs and the high beam quality with respect
to synchrotrons, which are presently the only available technology for this
application. In the framework of the development of a new linac for carbon ion
therapy, this article describes the design of a compact 750 MHz Radio Frequency
Quadrupole (RFQ) with trapezoidal vanes. A new semi-analytic approach to design
the trapezoidal-vane RFQ is introduced together with the relevant beam dynamics
properties. The RFQ is split into two decoupled rf cavities, both of which make
use of a novel dipole detuning technique by means of length adjustment. The
splitting is described both from the rf and the beam dynamics point of view.
The paper concludes with the rf design of the full structure, including maximum
surface field and thermal studies.


  This paper presents the design of InterPSS simulation engine, including its
object model, open software architecture, and software development process.
Several advanced applications, including an integrated transmission and
distribution co-simulation, an electromagnetic transient and phasor domain
hybrid simulation, and InterPSS integration with a market simulator, have been
developed by either extending InterPSS simulation engine or integrating it with
other programs and/or platforms. These advanced applications show that the open
architecture combined with the comprehensive modeling and simulation
capabilities make InterPSS a very attractive option for the research and the
future new power system simulation application development.


  The relativistic equivalent of the Schr\"odinger equation for a two particle
bound state having the total angular momentum $S$ is written in the form of a
Lorentz covariant set of equations (p_1^mu+p_2^mu+Omega^mu)Psi(p_1,p_2;P)
chi_S(\vec{p}_1,\vec{p}_2)=P^mu Psi(p_1,p_2;P) chi_S(\vec{p}_1,\vec{p}_2) where
the operators Omega^mu are the components of a 4-vector quasipotential. The
solution of this set is a stationary function representing the distribution of
spins and internal momenta in a reference frame where the momentum of the bound
system is P^\mu.
  The contribution of the operators Omega^mu to the bound state momentum is
assumed to be the 4-momentum of a vacuum-like effective field entering the
bound system as an independent component. It is shown that a state made of free
quarks and of the effective field has definite mass and can be normalized like
a single particle state.
  The generalization to the case of three or more particles is immediate.


  A quantum dynamical model of two interacting spins, with chaotic and regular
components, is investigated using a finite two-particles symmetrized basis.
Chaotic eigenstates give rise to an equilibrium occupation number distribution
in close agreement with the Bose-Einstein distribution despite the small number
of particles ($n=2$). However, the corresponding temperature differs from that
derived from the standard Canonical Ensemble. On the other side, an acceptable
agreement with the latter is restored by artificially randomizing the model.
Different definitions of temperature are then discussed and compared .


  We present photometric measurements of two superflares observed on a very
young brown dwarf CFHT-BD-Tau 4, observed during Campaign 13 of the
\textit{Kepler K2} mission. The stronger of the two superflares brightened by a
factor of $\sim$48 relative to the quiescent photospheric level, with an
increase in \textit{Kepler} magnitude $\Delta \tilde{K_{p}}$ = -4.20. It has an
equivalent duration of $\sim$107 hour, a flare duration of 1.7 day, and an
estimated total bolometric (ultraviolet/optical/infrared) energy up to 2.1
$\times$ 10$^{38}$ erg. The weaker of the two superflares is a complex
(multipeaked) flare with an estimated total bolometric (UV/optical/IR) energy
up to 4.7 $\times$ 10$^{36}$ erg. They are the strongest flares observed on any
brown dwarf so far. The flare energies are strongly dependent on the value of
visual extinction parameter $A_{V}$ used for extinction correction. If we apply
a solar flare-model to interpret the two superflares, we find that the magnetic
fields are required to be stronger by as much as an order of magnitude than
previous reports of field measurements in CFHT-BD-Tau 4 by Reiners et al.
(2009b). On the other hand, if we interpret our data in terms of accretion, we
find that the requisite rate of accretion for the stronger superflare exceeds
the rates which have been reported for other young brown dwarfs.


  We investigate a Lie algebra-type $ \kappa$-deformed Minkowski space-time
with undeformed Lorentz algebra and mutually commutative vector-like Dirac
derivatives. There are infinitely many realizations of $ \kappa$-Minkowski
space. The coproduct and the star product corresponding to each of them are
found. Utilizing the properties of the {\em{natural}} realization, we construct
a scalar field theory on $ \kappa$-deformed Minkowski space and show that it is
equivalent to the scalar, nonlocal, relativistically invariant field theory on
the ordinary Minkowski space.


  We prove that the light-cone time cut-off on the multiverse defines the same
probabilities as a causal patch with initial conditions in the longest-lived
metastable vacuum. This establishes the complete equivalence of two measures of
eternal inflation which naively appear very different (though both are
motivated by holography). The duality can be traced to an underlying geometric
relation which we identify.


  To measure the fault diagnosis capability of a multiprocessor system with
faulty links, Zhu et al. [Theoret. Comput. Sci. 758 (2019) 1--8] introduced the
$h$-edge tolerable diagnosability. This kind of diagnosability is a
generalization of the concept of traditional diagnosability. In this paper, as
complement to the results in [Theoret. Comput. Sci. 760 (2019) 1--14], we
completely determine the $h$-edge tolerable diagnosability of balanced
hypercubes $BH_n$ under the PMC model and the MM$^*$ model. Thus, the
traditional diagnosability of $BH_n$ is also determined.


  The results presented in this paper clearly suggest that a coherent framework
may exist which connects the topics of heavy-ion molecular resonances,
hyperdeformation effects, and fission shape isomerism. New data on
particle-particle-$\gamma$ triple coincidences of the $^{28}$Si+$^{28}$Si
reaction at a beam energy corresponding to the population of a conjectured
J$^{\pi}$ = 38$^{+}$ resonance in $^{56}$Ni are presented. The absence of
alignment of the spins of the outgoing fragments with respect to the orbital
angular momentum is found to be in contrast with the alignment as measured for
the $^{24}$Mg+$^{24}$Mg resonances. A molecular-model picture is presented to
suggest a "butterfly" motion of two oblate $^{28}$Si nuclei interacting in a
equator-to-equator molecular configuration.


  Using a three-current model for heat, spin-up and spin-down electrons, the
thermodynamics of irreversible processes predicts that a temperature gradient
gives rise to a spin current under the conditions used to measure what is
called the spin Seebeck effect. A diffusive current proportional to a gradient
of the chemical potential is known in thermochemistry as a Soret effect or
thermophoresis.


  We present a feasibility study of top-quark mass measurement using the energy
distribution of a lepton from a W boson in a top quark decay in pp collisions
at the LHC. The proposed method requires only the lepton energy distribution at
the parton level. The analysis is performed in the lepton + jets final state by
using fast simulation data corresponding to an integrated luminosity of
approximately 20 fb-1 at 14 TeV. Events with exactly one lepton, at least 3
jets and at least 1 b jet are selected. The lepton energy distribution at the
parton level is obtained by applying the bin-by-bin unfolding technique. The
study shows that the pole mass of the top quark can be measured within an
uncertainty of 1 GeV.


  Conventional therapy approaches limit surgeons' dexterity control due to
limited field-of-view. With the advent of robot-assisted surgery, there has
been a paradigm shift in medical technology for minimally invasive surgery.
However, it is very challenging to track the position of the surgical
instruments in a surgical scene, and accurate detection & identification of
surgical tools is paramount. Deep learning-based semantic segmentation in
frames of surgery videos has the potential to facilitate this task. In this
work, we modify the U-Net architecture named U-NetPlus, by introducing a
pre-trained encoder and re-design the decoder part, by replacing the transposed
convolution operation with an upsampling operation based on nearest-neighbor
(NN) interpolation. To further improve performance, we also employ a very fast
and flexible data augmentation technique. We trained the framework on 8 x 225
frame sequences of robotic surgical videos, available through the MICCAI 2017
EndoVis Challenge dataset and tested it on 8 x 75 frame and 2 x 300 frame
videos. Using our U-NetPlus architecture, we report a 90.20% DICE for binary
segmentation, 76.26% DICE for instrument part segmentation, and 46.07% for
instrument type (i.e., all instruments) segmentation, outperforming the results
of previous techniques implemented and tested on these data.


  The $D^+ \to K^-\pi^+\pi+$ decay have been observed in LHCb collaboration
with thousands of events per second from $K\pi$ threshold. The theoretical
treatment of this decay includes a rich dynamic behaviour that mix weak and
strong interactions in a non trivial way. In the present work we show recently
progress on $D^+ \to K^-\pi^+\pi+$ decay within a effective hadronic formalism.
The weak sector followed a similar formalism from heavy meson ChPT, where quark
c is an external object of SU(3) Goldstone bosons sector and final states
interactions description is based in three-body model. The results concerning
the vector weak transition revealed a very interesting new scenario in s-wave
phase-shift: agrees well with data in the elastic region, and it starts from
$-60$ degrees. Up to now the reason way the experimental phase starts at
negative degrees($\approx - 138$) was a mystery. However, we show that this
behaviour is a consequence of interference between a correct weak vertex
dynamic, dominated by $\rho$ meson propagator, and a rescattering model to the
final state interaction. Therefore, this work represent a progress in the
understanding of $D^+ \to K^-\pi^+\pi+$ and could be applied to other decays.


  The statistical properties of the carrier density profile of graphene in the
ground state in the presence particle-particle interaction and random charged
impurity in zero gate voltage has been recently obtained by Najafi \textit{et
al.} (Phys. Rev E95, 032112 (2017)). The non-zero chemical potential ($\mu$) in
gated graphene has non-trivial effects on electron-hole puddles, since it
generates mass in the Dirac action and destroys the scaling behaviors of the
effective Thomas-Fermi-Dirac theory. We provide detailed analysis on the
resulting spatially inhomogeneous system in the framework of the
Thomas-Fermi-Dirac theory for the Gaussian (white noise) disorder potential. We
show that, the chemical potential in this system as a random surface, destroys
the self-similarity, and the charge field is non-Gaussian. We find that the
two-body correlation functions are factorized to two terms: a pure function of
the chemical potential and a pure function of the distance. The spatial
dependence of these correlation functions is double-logarithmic, e.g. the
two-point density correlation $D_2(r,\mu)\propto
\mu^2\exp\left[-\left(-a_D\ln\ln r^{\beta_D}\right)^{\alpha_D} \right]$
($\alpha_D=1.82$, $\beta_D=0.263$ and $a_D=0.955$). The Fourier power spectrum
function behaves like $\ln(S(q))=-\beta_S^{-a_S}\left(\ln q \right)^{a_S}+2\ln
\mu$ ($a_S=3.0\pm 0.1$ and $\beta_S=2.08\pm 0.03$) in contrast to the ordinary
Gaussian rough surfaces for which $a_S=1$ and
$\beta_S=\frac{1}{2}(1+\alpha)^{-1}$, ($\alpha$ being the roughness exponent).
The geometrical properties are however similar to the un-gated ($\mu=0$) case,
with the exponents that are reported in the text.


  We investigate $\pi\rho$ scattering based on the coupled-channel formalism
with the $\pi\rho$ and $K\bar{K}^*$ ($\bar{K}K^*$) channels included. We
construct the kernel amplitudes by using the meson-exchange model and compute
the coupled integral equation for $\pi\rho$ scattering. By performing the
partial-wave expansion, we show explicitly that the $a_1(1260)$ meson is
dynamically generated by the coupled-channel formalism. The $a_1$ meson only
appears by including the $K\bar{K}^*$ ($\bar{K}K^*$) channel. We obtain the
pole position of the $a_1$ meson as $\sqrt{s_R} = (1170.7 - i 173.0)$ MeV. We
conclude that the $a_1$ meson can be interpreted as a kaon and vector kaon
molecular state.


  The Ensemble Kalman Filters (EnKF) employ a Monte-Carlo approach to represent
covariance information, and are affected by sampling errors in operational
settings where the number of model realizations is much smaller than the model
state dimension. To alleviate the effects of these errors EnKF relies on
model-specific heuristics such as covariance localization, which takes
advantage of the spatial locality of correlations among the model variables.
This work proposes an approach to alleviate sampling errors that utilizes a
locally averaged-in-time dynamics of the model, described in terms of a
climatological covariance of the dynamical system. We use this covariance as
the target matrix in covariance shrinkage methods, and develop a stochastic
covariance shrinkage approach where synthetic ensemble members are drawn to
enrich both the ensemble subspace and the ensemble transformation. We
additionally provide for a way in which this methodology can be localized
similar to the state-of-the-art LETKF method, and that for a certain model
setup, our methodology significantly outperforms it.


  In this paper, we present several possible anomaly-free implementations of
the Branco-Grimus-Lavoura (BGL) model with two Higgs doublets and one singlet
scalar. The model also includes three generations of massive neutrinos that get
their mass via a type-I seesaw mechanism. A particular anomaly-free
realization, which we dub $\nu$BGL-1 scenario, is subjected to an extensive
phenomenological analysis, from the perspective of flavour physics and collider
phenomenology.


  We investigate the interaction between light and molecular systems modeled as
quantum emitters coupled to a multitude of vibrational modes via a
Holstein-type interaction. We follow a quantum Langevin equations approach that
allows for analytical derivations of absorption and fluorescence profiles of
molecules driven by classical fields or coupled to quantized optical modes. We
retrieve analytical expressions for the modification of the radiative emission
branching ratio in the Purcell regime and for the asymmetric cavity
transmission associated with dissipative cross-talk between upper and lower
polaritons in the strong coupling regime. We also characterize the F\"{o}rster
resonance energy transfer process between donor-acceptor molecules mediated by
the vacuum or by a cavity mode.


  We investigate a simple class of type II string compactifications which
incorporate nongeometric "fluxes" in addition to "geometric flux" and the usual
H-field and R-R fluxes. These compactifications are nongeometric analogues of
the twisted torus. We develop T-duality rules for NS-NS geometric and
nongeometric fluxes, which we use to construct a superpotential for the
dimensionally reduced four-dimensional theory. The resulting structure is
invariant under T-duality, so that the distribution of vacua in the IIA and IIB
theories is identical when nongeometric fluxes are included. This gives a
concrete framework in which to investigate the possibility that generic string
compactifications may be nongeometric in any duality frame. The framework
developed in this paper also provides some concrete hints for how mirror
symmetry can be generalized to compactifications with arbitrary H-flux, whose
mirrors are generically nongeometric.


  Compiling applications as unikernels allows them to be tailored to diverse
execution environments. Dependency on a monolithic operating system is replaced
with linkage against libraries that provide specific services. Doing so in
practice has revealed a major barrier: managing the configuration matrix across
heterogenous execution targets. A realistic unikernel application depends on
hundreds of libraries, each of which may place different demands on the
different target execution platforms (e.g.,~cryptographic acceleration).
  We propose a modular approach to structuring large scale codebases that
cleanly separates configuration, application and operating system logic. Our
implementation is built on the \mirage unikernel framework, using the \ocaml
language's powerful abstraction and metaprogramming facilities. Leveraging
modules allows us to build many components independently, with only loose
coupling through a set of standardised signatures. Components can be
parameterized by other components and composed. Our approach accounts for
state, dependency ordering, and error management, and our usage over the years
has demonstrated significant efficiency benefits by leveraging compiler
features such as global link-time optimisation during the configuration
process. We describe our application architecture and experiences via some
practical applications of our approach, and discuss how library development in
\mirage can facilitate adoption in other unikernel frameworks and programming
languages.


  We report the discovery of nine metal-poor stars with high levels of
r-process enhancement (+0.81<[Eu/Fe]<+1.13), including six subgiants and three
stars on the red horizontal branch. We also analyze four previously-known
r-process-enhanced metal-poor red giants. From this sample of 13 stars, we draw
the following conclusions. (1) High levels of r-process enhancement are found
in a broad range of stellar evolutionary states, reaffirming that this
phenomenon is not associated with a chemical peculiarity of red giant
atmospheres. (2) Only 1 of 10 stars observed at multiple epochs shows radial
velocity variations, reaffirming that stars with high levels of r-process
enhancement are not preferentially found among binaries. (3) Only 2 of the 13
stars are highly-enhanced in C and N, indicating that there is no connection
between high levels of r-process enhancement and high levels of C and N. (4)
The dispersions in [Sr/Ba] and [Sr/Eu] are larger than the dispersions in
[Ba/Eu] and [Yb/Eu], suggesting that the elements below the second r-process
peak do not always scale with those in the rare earth domain, even within the
class of highly-r-process-enhanced stars. (5) The light-element (12<Z<30)
abundances of highly-r-process-enhanced stars are indistinguishable from those
with normal levels of r-process material at the limit of our data, 3.5 per cent
(0.015 dex) on average. The nucleosynthetic sites responsible for the large
r-process enhancements did not produce any detectable light-element abundance
signatures distinct from normal core-collapse supernovae.


  This is my Th\`ese d'Habilitation (HDR) on the topic of spinfoam models for
quantum gravity, which I presented in l'Ecole Normale Sup\'erieure de Lyon on
december 16 2010. The spinfoam framework is a proposal for a regularized path
integral for quantum gravity, inspired from Topological Quantum Field Theory
(TQFT) and state-sum models. It can also be seen as defining transition
amplitudes for the quantum states of geometry for Loop Quantum Gravity (LQG).


  The study of physiology demonstrates that the form (shape)of anatomical
structures dictates their functions, and analyzing the form of anatomies plays
a crucial role in clinical research. Statistical shape modeling (SSM) is a
widely used tool for quantitative analysis of forms of anatomies, aiding in
characterizing and identifying differences within a population of subjects.
Despite its utility, the conventional SSM construction pipeline is often
complex and time-consuming. Additionally, reliance on linearity assumptions
further limits the model from capturing clinically relevant variations. Recent
advancements in deep learning solutions enable the direct inference of SSM from
unsegmented medical images, streamlining the process and improving
accessibility. However, the new methods of SSM from images do not adequately
account for situations where the imaging data quality is poor or where only
sparse information is available. Moreover, quantifying aleatoric uncertainty,
which represents inherent data variability, is crucial in deploying deep
learning for clinical tasks to ensure reliable model predictions and robust
decision-making, especially in challenging imaging conditions. Therefore, we
propose SPI-CorrNet, a unified model that predicts 3D correspondences from
sparse imaging data. It leverages a teacher network to regularize feature
learning and quantifies data-dependent aleatoric uncertainty by adapting the
network to predict intrinsic input variances. Experiments on the LGE MRI left
atrium dataset and Abdomen CT-1K liver datasets demonstrate that our technique
enhances the accuracy and robustness of sparse image-driven SSM.


  The theoretical description of the thermodynamic properties of
ferromagnetic/superconductor/ferromagnetic (F/S/F) systems of nanoscopic scale
is proposed. Their superconducting characteristics strongly depend on the
mutual orientation of the ferromagnetic layers. In addition, depending on the
transparency of S/F interfaces, the superconducting critical temperature can
exhibit four different types of dependences on the thickness of the F-layer.
The obtained results permit to give some practical recommendations for the
spin-valve effect experimental observation. In this spin-valve sandwich, we
also expect a spontaneous transition from parallel to anti-parallel
ferromagnetic moment orientation, due to the gain in the superconducting
condensation energy.


  In this talk, I review the Color Glass Condensate theory of gluon saturation,
and its application to the early stages of heavy ion collisions.


  With the exponentially increased demands for large bandwidth, it is important
to think about the best network platform as well as the security and privacy of
the information in communication networks. Millimetre (mm)-waves and terahertz
(THz) with high carrier frequency are proposed as the enabling technologies to
overcome Shannons channel capacity limit of existing communication systems by
providing ultrawide bandwidth signals. Mm-waves and THz are also able to build
wireless links compatible with optical communication systems. However, most
solid-state components that can operate reasonably efficiently at these
frequency ranges (100GHz-10THz), especially sources and detectors, require
cryogenic cooling, as is a requirement for most quantum systems. Here, we show
that secure mm-waves and THz QKD can be achieved when the sources and detectors
operate at cryogenic temperatures down to T= 4K. We compare single-input
single-output (SISO) and multiple-input multiple-output (MIMO) Continuous
Variable THz Quantum Key Distribution (CVQKD) schemes and find the positive
secret key rate in the frequency ranges between f=100 GHz and 1 THz. Moreover,
we find that the maximum transmission distance could be extended, the secret
key rate could be improved in lower temperatures, and achieve a maximum secrete
communication distance of more than 5 km at f=100GHz and T=4K by using
1024*1024 antennas. Our results may contribute to the efforts to develop
next-generation secure wireless communication systems and quantum internet for
applications from inter-satellite and deep space, to indoor and short-distance
communications.


  We establish a full classification of degree $2$ codimension one
distributions on $\mathbb{P}^3$ according to invariants of their tangent
sheaves.


  With rapid growth in the amount of unstructured data produced by
memory-intensive applications, large scale data analytics has recently
attracted increasing interest. Processing, managing and analyzing this huge
amount of data poses several challenges in cloud and data center computing
domain. Especially, conventional frameworks for distributed data analytics are
based on the assumption of homogeneity and non-stochastic distribution of
different data-processing nodes. The paper argues the fundamental limiting
factors for scaling big data computation. It is shown that as the number of
series and parallel computing servers increase, the tail (mean and variance) of
the job execution time increase. We will first propose a model to predict the
response time of highly distributed processing tasks and then propose a new
practical computational algorithm to optimize the response time.


  This paper presents a nonlocal InSAR filter with the goal of generating
digital elevation models of higher resolution and accuracy from bistatic
TanDEM-X strip map interferograms than with the processing chain used in
production. The currently employed boxcar multilooking filter naturally
decreases the resolution and has inherent limitations on what level of noise
reduction can be achieved. The proposed filter is specifically designed to
account for the inherent diversity of natural terrain by setting several
filtering parameters adaptively. In particular, it considers the local fringe
frequency and scene heterogeneity, ensuring proper denoising of interferograms
with considerable underlying topography as well as urban areas. A comparison
using synthetic and TanDEM-X bistatic strip map datasets with existing InSAR
filters shows the effectiveness of the proposed techniques, most of which could
readily be integrated into existing nonlocal filters. The resulting digital
elevation models outclass the ones produced with the existing global TanDEM-X
DEM processing chain by effectively increasing the resolution from 12m to 6m
and lowering the noise level by roughly a factor of two.


  We used Bayesian methods to compare the predictions of probabilistic risk
assessment -- the theoretical tool used by the nuclear industry to predict the
frequency of nuclear accidents -- with empirical data. The existing record of
accidents with some simplifying assumptions regarding their probability
distribution is sufficient to rule out the validity of the industry's analyses
at a very high confidence level. We show that this conclusion is robust against
any reasonable assumed variation of safety standards over time, and across
regions. The debate on nuclear liability indicates that the industry has
independently arrived at this conclusion. We pay special attention to the
Indian situation, where we show that the existing operating experience provides
insufficient data to make any reliable claims about the safety of future
reactors. We briefly discuss some policy implications.


  EEG decoding systems based on deep neural networks have been widely used in
decision making of brain computer interfaces (BCI). Their predictions, however,
can be unreliable given the significant variance and noise in EEG signals.
Previous works on EEG analysis mainly focus on the exploration of noise pattern
in the source signal, while the uncertainty during the decoding process is
largely unexplored. Automatically detecting and reducing such decoding
uncertainty is important for BCI motor imagery applications such as robotic arm
control etc. In this work, we proposed an uncertainty estimation and reduction
model (UNCER) to quantify and mitigate the uncertainty during the EEG decoding
process. It utilized a combination of dropout oriented method and Bayesian
neural network for uncertainty estimation to incorporate both the uncertainty
in the input signal and the uncertainty in the model parameters. We further
proposed a data augmentation based approach for uncertainty reduction. The
model can be integrated into current widely used EEG neural decoders without
change of architecture. We performed extensive experiments for uncertainty
estimation and its reduction in both intra-subject EEG decoding and
cross-subject EEG decoding on two public motor imagery datasets, where the
proposed model achieves significant improvement both on the quality of
estimated uncertainty and the effectiveness of uncertainty reduction.


  If all new particles are too heavy to be directly produced in the future
Colliders, then the long sought New Physics (NP) could only appear in the form
of new interactions, beyond those of the Standard Model (SM). Many of the
processes that could be used to study these interactions, have already been
discussed in the literature. Here, I first briefly discuss the list of all not
yet excluded CP conserving such interactions, realized as $SU(3)\times SU(2)
\times U(1)$ gauge invariant $dim=6$ operators affecting the Higgs and the
quarks of the third family.
  Subsequently, I concentrate on the $\gamma t\bar t$ and $Zt\bar t$ vertices
generated by NP, and on the possibility to study them by using various spin
asymmetries accessible in $e^-e^+ \to t \bar t$, for polarized and unpolarized
beams. It is found that these asymmetries can fully determine the form of the
$\gamma t\bar t$ and $Zt\bar t$ couplings.


  Large-scale relativistic configuration-interaction method combined with
many-body perturbation theory is consistently applied to calculations of the
energy levels of the ground and inner-L-shell excited states of berylliumlike
ions in the range $10 \leq Z \leq 92$. The quantum electrodynamics, nuclear
recoil, and frequency-dependent Breit corrections are taken into account. The
obtained results are supplemented with the systematical estimation of the
uncertainties.


  We evaluate the performance of two 44 year ensemble seasonal hindcast time
series for the Nino3 index produced as part of the DEMETER project. We show
that the ensemble mean carries useful information out to six months. The
ensemble spread, however, only carries useful information out to four months in
one of the models, and two months in the other.


  We compare dense clumps and cores in a numerical simulation of molecular
clouds (MCs) undergoing global hierarchical collapse (GHC) to observations in
two MCs at different evolutionary stages, the Pipe and the G14.225 clouds, to
test the ability of the GHC scenario to follow the early evolution of the
energy budget and star formation activity of these structures. In the
simulation, we select a region that contains cores of sizes and densities
similar to the Pipe cores, and find that it evolves through accretion,
developing substructure similar to that of G14.225 cloud after $\sim 1.6$ Myr.
Within this region, we follow the evolution of the Larson ratio $\mathcal{L}
\equiv \sigma_{\rm v}/R^{1/2}$, where $\sigma_{\rm v}$ is the velocity
dispersion and $R$ is the size, the virial parameter $\alpha$, and the star
formation activity of the cores/clumps. In the simulation, we find that as the
region evolves: $i)$ its clumps have $\mathcal{L}$ and $\alpha$ values first
consistent with those of the Pipe substructures and later with those of
G14.225; $ii)$ the individual cores first exhibit a decrease in $\alpha$
followed by an increase when star formation begins; $iii)$ collectively, the
ensemble of cores/clumps reproduces the observed trend of lower $\alpha$ for
higher-mass objects, and $iv)$ the star formation rate and star formation
efficiency increase monotonically. We suggest that this evolution is due to the
simultaneous loss of externally-driven compressive kinetic energy and increase
of the self-gravity-driven motions. We conclude that the GHC scenario provides
a realistic description of the evolution of the energy budget of the clouds'
substructure at early times, which occurs simultaneously with an evolution of
the star formation activity.


  The standard disc formation scenario postulates that disc forms as the gas
cools and flows into the centre of the dark matter halo, conserving the
specific angular momentum. Major mergers have been shown to be able to destroy
or highly perturb the disc components. More recently, the alignment of the
material that is accreted to form the galaxy has been pointed out as a key
ingredient to determine galaxy morphology. However, in a hierarchical scenario
galaxy formation is a complex process that combines these processes and others
in a non-linear way so that the origin of galaxy morphology remains to be fully
understood. We aim at exploring the differences in the formation histories of
galaxies with a variety of morphology, but quite recent merger histories, to
identify which mechanisms are playing a major role. We analyse when minor
mergers can be considered relevant to determine galaxy morphology. We also
study the specific angular momentum content of the disc and central spheroidal
components separately. We used cosmological hydrodynamical simulations that
include an effective, physically motivated supernova feedback that is able to
regulate the star formation in haloes of different masses. We analysed the
morphology and formation history of a sample of 15 galaxies of a cosmological
simulation. We performed a spheroid-disc decomposition of the selected galaxies
and their progenitor systems. The angular momentum orientation of the merging
systems as well as their relative masses were estimated to analyse the role
played by orientation and by minor mergers in the determination of the
morphology. We found the discs to be formed by conserving the specific angular
momentum in accordance with the classical disc formation model. The specific
angular momentum of the stellar central spheroid correlates with the dark
matter halo angular momentum and determines a power law. Abridged


  Achieving localized light emission from monolayer two-dimensional (2D)
transition metal dichalcogenides (TMDs) embedded in the matrix of another TMD
has been theoretically proposed but not experimentally proven. In this study,
we used cathodoluminescence performed in a scanning transmission electron
microscope to unambiguously resolve localized light emission from 2D monolayer
MoSe2 nanodots of varying sizes embedded in monolayer WSe2 matrix. We observed
that the light emission strongly depends on the nanodot size wherein the
emission is dominated by MoSe2 excitons in dots larger than 85 nm, and by
MoSe2/WSe2 interface excitons below 50 nm. Interestingly, at extremely small
dot sizes (< 10 nm), the electron energy levels in the nanodot become
quantized, as demonstrated by a striking blue-shift in interface exciton
emission, thus inducing quantum confined luminescence. These results establish
controllable light emission from spatially confined 2D nanodots, which holds
potential to be generalized to other 2D systems towards future nanophotonic
applications.


  The Kerker effect has been generalized in nanophotonics and meta-optics, and
has recently been of great interest by relating to various fascinating
functionalities such as scattering management and perfect transmission,
reflection or absorption. One of the most interesting generalizations is the
resonant lattice Kerker effect in periodic nanostructures. However, its active
tuning has not been explored yet. Here, we report, for the first time, the
active control of the resonant lattice Kerker effect in periodic Ge2Se2Te5
nanodisks. By changing the crystalline fraction, we show that the electric
dipole lattice resonance (ED-LR), the magnetic dipole resonance (MDR), and thus
the resonant lattice Kerker effect are all red-shifted. We therefore realize
the transition from the ED-LR to the resonant lattice Kerker effect, which
enables multilevel tuning of reflection, transmission and absorption with
modulation depths above 86%. Taking advantage of the MDR redshifts, we also
observe broadband and multilevel tuning of transmission with modulation depth
of 87% over a broadband range of 588 nm. Our work establishes a new path for
designing high-performance active nanophotonic devices.


  We review our recent modeling of crystal nucleation and polycrystalline
growth using a phase field theory. First, we consider the applicability of
phase field theory for describing crystal nucleation in a model hard sphere
fluid. It is shown that the phase field theory accurately predicts the
nucleation barrier height for this liquid when the model parameters are fixed
by independent molecular dynamics calculations. We then address various aspects
of polycrystalline solidification and associated crystal pattern formation at
relatively long timescales. This late stage growth regime, which is not
accessible by molecular dynamics, involves nucleation at the growth front to
create new crystal grains in addition to the effects of primary nucleation.
Finally, we consider the limit of extreme polycrystalline growth, where the
disordering effect due to prolific grain formation leads to isotropic growth
patterns at long times, i.e., spherulite formation. Our model of spherulite
growth exhibits branching at fixed grain misorientations, induced by the
inclusion of a metastable minimum in the orientational free energy. It is
demonstrated that a broad variety of spherulitic patterns can be recovered by
changing only a few model parameters.


  In light of the rapid recent retreat of Arctic sea ice, a number of studies
have discussed the possibility of a critical threshold (or "tipping point")
beyond which the ice-albedo feedback causes the ice cover to melt away in an
irreversible process. The focus has typically been centered on the annual
minimum (September) ice cover, which is often seen as particularly susceptible
to destabilization by the ice-albedo feedback. Here we examine the central
physical processes associated with the transition from ice-covered to ice-free
Arctic Ocean conditions. We show that while the ice-albedo feedback promotes
the existence of multiple ice cover states, the stabilizing thermodynamic
effects of sea ice mitigate this when the Arctic Ocean is ice-covered during a
sufficiently large fraction of the year. These results suggest that critical
threshold behavior is unlikely during the approach from current perennial sea
ice conditions to seasonally ice-free conditions. In a further warmed climate,
however, we find that a critical threshold associated with the sudden loss of
the remaining wintertime-only sea ice cover may be likely.


  In this letter, a methodology is proposed to improve the scattering powers
obtained from model-based decomposition using Polarimetric Synthetic Aperture
Radar (PolSAR) data. The novelty of this approach lies in utilizing the
intrinsic information in the off-diagonal elements of the 3$\times$3 coherency
matrix $\mathbf{T}$ represented in the form of complex correlation
coefficients. Two complex correlation coefficients are computed between
co-polarization and cross-polarization components of the Pauli scattering
vector. The difference between modulus of complex correlation coefficients
corresponding to $\mathbf{T}^{\mathrm{opt}}$ (i.e. the degree of polarization
(DOP) optimized coherency matrix), and $\mathbf{T}$ (original) matrices is
obtained. Then a suitable scaling is performed using fractions \emph{i.e.,}
$(T_{ii}^{\mathrm{opt}}/\sum\limits_{i=1}^{3}T_{ii}^{\mathrm{opt}})$ obtained
from the diagonal elements of the $\mathbf{T}^{\mathrm{opt}}$ matrix.
Thereafter, these new quantities are used in modifying the Yamaguchi
4-component scattering powers obtained from $\mathbf{T}^{\mathrm{opt}}$. To
corroborate the fact that these quantities have physical relevance, a
quantitative analysis of these for the L-band AIRSAR San Francisco and the
L-band Kyoto images is illustrated. Finally, the scattering powers obtained
from the proposed methodology are compared with the corresponding powers
obtained from the Yamaguchi \emph{et. al.,} 4-component (Y4O) decomposition and
the Yamaguchi \emph{et. al.,} 4-component Rotated (Y4R) decomposition for the
same data sets. The proportion of negative power pixels is also computed. The
results show an improvement on all these attributes by using the proposed
methodology.


  The sensitivity of an atomic interferometer increases when the phase
evolution of its quantum superposition state is measured over a longer
interrogation interval. In practice, a limit is set by the measurement process,
which returns not the phase, but its projection in terms of population
difference on two energetic levels. The phase interval over which the relation
can be inverted is thus limited to the interval $[-\pi/2,\pi/2]$; going beyond
it introduces an ambiguity in the read out, hence a sensitivity loss. Here, we
extend the unambiguous interval to probe the phase evolution of an atomic
ensemble using coherence preserving measurements and phase corrections, and
demonstrate the phase lock of the clock oscillator to an atomic superposition
state. We propose a protocol based on the phase lock to improve atomic clocks
under local oscillator noise, and foresee the application to other atomic
interferometers such as inertial sensors.


  We study coded distributed matrix multiplication from an approximate recovery
viewpoint. We consider a system of $P$ computation nodes where each node stores
$1/m$ of each multiplicand via linear encoding. Our main result shows that the
matrix product can be recovered with $\epsilon$ relative error from any $m$ of
the $P$ nodes for any $\epsilon > 0$. We obtain this result through a careful
specialization of MatDot codes -- a class of matrix multiplication codes
previously developed in the context of exact recovery ($\epsilon=0$). Since
prior results showed that MatDot codes achieve the best exact recovery
threshold for a class of linear coding schemes, our result shows that allowing
for mild approximations leads to a system that is nearly twice as efficient as
exact reconstruction. As an additional contribution, we develop an optimization
framework based on alternating minimization that enables the discovery of new
codes for approximate matrix multiplication.


  We present the results obtained from a study of the variability of iron
emission lines in the high mass X-ray binary pulsar Cen X-3 during the eclipse,
eclipse-egress and out-of-eclipse phases using XMM-Newton observations. Three
iron emission lines at 6.4 keV, 6.7 keV, and 6.97 keV are clearly detected in
the spectrum of the pulsar during the entire observations, irrespective of
different binary phases. The properties of these emission lines are
investigated at different intensity levels. The flux level and equivalent width
of the emission lines change during the eclipse, eclipse-egress and
out-of-eclipse orbital phases. Based on the results obtained from the time
resolved spectral analysis, it is understood that the most probable emitting
region of 6.4 keV fluorescent line is very close to the neutron star whereas
the other two lines are produced in a region that is far from the neutron star,
probably in the highly photo-ionized wind of the companion star or in the
accretion disk corona.


  To entirely determine the resulting functions of one-loop integrals it is
necessary to find the correct analytic continuation to all relevant kinematical
regions. We argue that this continuation procedure may be performed in a
general and mathematical accurate way by using the ${\cal R}$ function notation
of these integrals. The two- and three-point cases are discussed explicitly in
this manner.


  PU learning refers to the classification problem in which only part of
positive samples are labeled. Existing PU learning methods treat unlabeled
samples equally. However, in many real tasks, from common sense or domain
knowledge, some unlabeled samples are more likely to be positive than others.
In this paper, we propose soft label PU learning, in which unlabeled data are
assigned soft labels according to their probabilities of being positive.
Considering that the ground truth of TPR, FPR, and AUC are unknown, we then
design PU counterparts of these metrics to evaluate the performances of soft
label PU learning methods within validation data. We show that these new
designed PU metrics are good substitutes for the real metrics. After that, a
method that optimizes such metrics is proposed. Experiments on public datasets
and real datasets for anti-cheat services from Tencent games demonstrate the
effectiveness of our proposed method.


  Microplasma jets are commonly used to treat samples in ambient air
atmosphere. The effect of admixing air into the effluent may severely affect
the composition of the emerging species. Here, the effluent of a He/O2
microplasma jet has been analyzed in a helium and in an air atmosphere by
molecular beam mass spectrometry. First, the composition of the effluent in air
has been recorded as a function of the distance to determine how fast air
admixes into the effluent. Then, the spatial distribution of atomic oxygen and
ozone in the effluent has been recorded in ambient air and compared to
measurements in a helium atmosphere. Additionally, a fluid model of the gas
flow with reaction kinetics of reactive oxygen species in the effluent has been
constructed. In ambient air, the O density declines only slightly faster with
the distance compared to a helium atmosphere. On the contrary, the O3 density
in ambient air increases significantly faster with the distance compared to a
helium atmosphere. This mysterious behavior can have big implication for the
use of similar jets in plasma medicine. It is shown that photodissociation of
O2 and O3 is not responsible for the observed effect. A reaction scheme
involving the reaction of plasma produced highly vibrationally excited O2 with
ground state O2 molecules is proposed as a possible explanation of the observed
densities. A very good agreement between measured and simulated densities is
achieved.


  The Large Area Telescope (LAT), Fermi's main instrument, is providing a new
view of the local energetic pulsar population. In addition to identifying a
pulsar origin of a large fraction of the bright unidentified Galactic EGRET
sources, the LAT results provide a great opportunity to study a sizable
population of high-energy pulsars. Correlations of their physical properties,
such as the trend of the luminosity versus the rotational energy loss rate,
help identify global features of the gamma-ray pulsar population. Several lines
of evidence, including the light curve and spectral features, suggest that
gamma-ray emission from the brightest pulsars arises largely in the outer
magnetosphere.


  In this work, we study the implications of the existence of a gauge
condensate to the mechanism of duality, a method based on the existence of
these condensates is presented and applied to the study of the dual equivalence
between self-dual (SD) and topologically massive Yang-Mills (TMYM) models.


  We prove the hypersymplectic flow of simple type on standard torus
$\mathbb{T}^4$ exists for all time and converges to the standard flat structure
modulo diffeomorphisms. This result in particular gives the first example of a
cohomogeneity-one $G_2$-Laplacian flow on a compact $7$-manifold which exists
for all time and converges to a torsion-free $G_2$ structure modulo
diffeomorphisms.


  In this article we study modified Kirchhoff-Schr\"odinger equations involving
critical Stein-Weiss type nonlinearity and $p$-Laplacian


  We prove that for every integer $n$, there exist infinitely many
$D(n)$-triples which are also $D(t)$-triples for $t\in\mathbb{Z}$ with $n\ne
t$. We also prove that there are infinitely many triples with the property
$D(-1)$ in $\mathbb{Z}[i]$ which are also $D(n)$-triple in $\mathbb{Z}[i]$ for
two distinct $n$'s other than $n = -1$ and these triples are not equivalent to
any triple with the property $D(1)$.


  Post-Silicon Tunable (PST) clock buffers are widely used in high performance
designs to counter process variations. By allowing delay compensation between
consecutive register stages, PST buffers can effectively improve the yield of
digital circuits. To date, the evaluation of manufacturing yield in the
presence of PST buffers is only possible using Monte Carlo simulation. In this
paper, we propose an alternative method based on graph transformations, which
is much faster, more than 1000 times, and computes a parametric minimum clock
period. It also identifies the gates which are most critical to the circuit
performance, therefore enabling a fast analysis-optimization flow.


  We sketch a quantum mechanical framework for the universe as a whole. Within
that framework we propose a program for describing the ultimate origin in
quantum cosmology of the quasiclassical domain of familiar experience and for
characterizing the process of measurement. Predictions in quantum mechanics are
made from probabilities for sets of alternative histories. Probabilities can be
assigned only to sets of histories that approximately decohere. Decoherence is
defined and the mechanism of decoherence is reviewed. Decoherence requires a
sufficiently coarse-grained description of alternative histories of the
universe. A quasiclassical domain consists of a branching set of alternative
decohering histories, described by a coarse graining that is maximally refined
consistent with decoherence, with individual branches that exhibit a high level
of classical correlation in time. A quasiclassical domain is emergent in the
universe as a consequence of the initial condition and the action function of
the elementary particles. It is an important question whether all the
quasiclassical domains are roughly equivalent or whether there are various
essentially inequivalent ones. A measurement is a correlation with variables in
a quasiclassical domain. An observer (or information gathering and utilizing
system) is a complex adaptive system that has evolved to exploit the relative
predictability of a quasiclassical domain. We suggest that resolution of many
of the problems of interpretation presented by quantum mechanics is to be
accomplished, not by further scrutiny of the subject as it applies to
reproducible laboratory situations, but rather by an examination of alternative
histories of the universe, stemming from its initial condition, and a study of
the problem of quasiclassical domains.


  This work considers the problem of the noisy binary search in a sorted array.
The noise is modeled by a parameter $p$ that dictates that a comparison can be
incorrect with probability $p$, independently of other queries. We state two
types of upper bounds on the number of queries: the worst-case and expected
query complexity scenarios. The bounds improve the ones known to date, i.e.,
our algorithms require fewer queries. Additionally, they have simpler
statements, and work for the full range of parameters. All query complexities
for the expected query scenarios are tight up to lower order terms. For the
problem where target prior is uniform over all possible inputs, we provide
algorithm with expected complexity upperbounded by $(\log_2 n + \log_2
\delta^{-1} + 3)/I(p)$, where $n$ is the domain size, $0\le p < 1/2$ is the
noise ratio, and $\delta>0$ is the failure probability, and $I(p)$ is the
information gain function. As a side-effect, we close some correctness issues
regarding previous work. Also, en route, we obtain new and improved query
complexities for the search generalized to arbitrary graphs. This paper
continues and improves upon the lines of research of Burnashev-Zigangirov
[Prob. Per. Informatsii, 1974], Ben-Or and Hassidim [FOCS 2008], Gu and Xu
[STOC 2023], and Emamjomeh-Zadeh et al. [STOC 2016], Dereniowski et al.
[SOSA@SODA 2019].


  Proximal operators are ubiquitous in inverse problems, commonly appearing as
part of algorithmic strategies to regularize problems that are otherwise
ill-posed. Modern deep learning models have been brought to bear for these
tasks too, as in the framework of plug-and-play or deep unrolling, where they
loosely resemble proximal operators. Yet, something essential is lost in
employing these purely data-driven approaches: there is no guarantee that a
general deep network represents the proximal operator of any function, nor is
there any characterization of the function for which the network might provide
some approximate proximal. This not only makes guaranteeing convergence of
iterative schemes challenging but, more fundamentally, complicates the analysis
of what has been learned by these networks about their training data. Herein we
provide a framework to develop learned proximal networks (LPN), prove that they
provide exact proximal operators for a data-driven nonconvex regularizer, and
show how a new training strategy, dubbed proximal matching, provably promotes
the recovery of the log-prior of the true data distribution. Such LPN provide
general, unsupervised, expressive proximal operators that can be used for
general inverse problems with convergence guarantees. We illustrate our results
in a series of cases of increasing complexity, demonstrating that these models
not only result in state-of-the-art performance, but provide a window into the
resulting priors learned from data.


  In this paper, we revisit a "relatively local" model proposed in
arXiv:1811.07241, where locality and dimensionality of space only emerges from
the entanglement structure of the state the system is in. Various quantities
such as butterfly velocity/ entanglement speed can be defined similarly, at
least in the regime where locality is well defined and a light cone structure
emerges in the correlation between sites. We find that the relations observed
between them in local models arXiv:1908.06993 are not respected. In particular,
we conjecture that the hierarchy of the interaction over different distances
provides different "layers" of light-cones. When long range interactions are
sufficiently suppressed, the effective light cones are dominated by linear
behaviors with little remnant of non-locality. This could potentially be used
as a physical smoking gun for emergent locality in non-local models.


  We employ the hemisphere comparison (HC) method and the dipole fitting (DF)
method to investigate the cosmic anisotropy in the recently released Pantheon
sample of type Ia supernovae (SNe Ia) and five combinations among Pantheon. For
the HC method, we find the maximum anisotropy level in the full Pantheon sample
is $\mathrm{AL}_{max}=0.361\pm0.070$ and corresponding direction
$(l,b)=({123.05^{\circ}}^{+11.25^{\circ}}_{-4.22^{\circ}},
{4.78^{\circ}}^{+1.80^{\circ}}_{-8.36^{\circ}})$. A robust check shows the
statistical significance of maximum anisotropy level is about $2.1\sigma$. We
also find that the Low-$z$ and SNLS subsamples have decisive impact on the
overall anisotropy while other three subsamples have little impact. Moreover,
the anisotropy level map significantly rely on the inhomogeneous distribution
of SNe Ia in the sky. For the DF method, we find the dipole anisotropy in the
Pantheon sample is very weak. The dipole magnitude is constrained to be less
than $1.16\times10^{-3}$ at $95\%$ confidence level. However, the dipole
direction is well inferred by MCMC method and it points towards
$(l,b)=({306.00^{\circ}}^{+82.95^{\circ}}_{-125.01^{\circ}},
{-34.20^{\circ}}^{+16.82^{\circ}}_{-54.93^{\circ}})$. This direction is very
close to the axial direction to the plane of SDSS subsample. It may imply that
SDSS subsample is the decisive part to the dipole anisotropy in the full
Pantheon sample. All these facts imply that the cosmic anisotropy found in
Pantheon sample significantly rely on the inhomogeneous distribution of SNe Ia
in the sky. More homogeneous distribution of SNe Ia is necessary to search for
a more convincing cosmic anisotropy.


  We report the identification of an extreme proto-cluster of galaxies in the
early Universe whose core (nicknamed Distant Red Core, DRC) is formed by at
least ten dusty star-forming galaxies (DSFGs), confirmed to lie at $z_{\rm
spec} = 4.002$ via detection of [CI](1-0), $^{12}$CO(6-5), $^{12}$CO(4-3),
$^{12}$CO(2-1) and ${\rm H_2O} (2_{11} - 2_{02})$ emission lines, detected
using ALMA and ATCA. The spectroscopically-confirmed components of the
proto-cluster are distributed over a ${\rm 260\, kpc \times 310\, kpc}$ region
and have a collective obscured star-formation rate (SFR) of $\sim 6500 \,
M_\odot \, {\rm yr}^{-1}$, considerably higher than has been seen before in any
proto-cluster of galaxies or over-densities of DSFGs at $z \gtrsim 4$. Most of
the star formation is taking place in luminous DSFGs since no Ly$\alpha$
emitters are detected in the proto-cluster core, apart from a Ly$\alpha$ blob
located next to one of the DRC dusty components and extending over $60\,{\rm
kpc}$. The total obscured SFR of the proto-cluster could rise to ${\rm SFR}
\sim 14,400 \, M_\odot \, {\rm yr}^{-1}$ if all the members of an over-density
of bright DSFGs discovered around DRC in a wide-field LABOCA 870-$\mu$m image
are part of the same structure. The total halo mass of DRC could be as high as
$\sim 4.4 \times 10^{13}\,M_\odot$ and could be the progenitor of a Coma-like
cluster at $z = 0$. The relatively short gas-depletion times of the DRC
components suggest either the presence of a mechanism able to trigger extreme
star formation simultaneously in galaxies spread over a few hundred kpc or the
presence of gas flows from the cosmic web able to sustain star formation over
several hundred million years.


  After a brief introduction to the overlap two examples relating to
topological properties of chiral fermion systems in interaction with gauge
fields are presented: It is shown how the overlap preserves the continuum
structure of exact fermionic zero modes in gauge backgrounds that are
instanton-like and why chiral anomalies are inevitable.


  We consider a magnetic impurity in a spin liquid state of a magnetic system
which is close to the quantum phase transition to the magnetically ordered
state. There is similarity between this problem and the Kondo problem. We
derive the impurity Green's function, consider renormalizations of the magnetic
moments of the impurity, calculate critical indexes for the magnetic
susceptibilities and finally consider specific heat and magnetic interaction of
two impurities.


  Semi-autonomous telerobotic systems allow both humans and robots to exploit
their strengths, while enabling personalized execution of a task. However, for
new soft robots with degrees of freedom dissimilar to those of human operators,
it is unknown how the control of a task should be divided between the human and
robot. This work presents a set of interaction paradigms between a human and a
soft growing robot manipulator, and demonstrates them in both real and
simulated scenarios. The robot can grow and retract by eversion and inversion
of its tubular body, a property we exploit to implement interaction paradigms.
We implemented and tested six different paradigms of human-robot interaction,
beginning with full teleoperation and gradually adding automation to various
aspects of the task execution. All paradigms were demonstrated by two expert
and two naive operators. Results show that humans and the soft robot
manipulator can split control along degrees of freedom while acting
simultaneously. In the simple pick-and-place task studied in this work,
performance improves as the control is gradually given to the robot, because
the robot can correct certain human errors. However, human engagement and
enjoyment may be maximized when the task is at least partially shared. Finally,
when the human operator is assisted by haptic feedback based on soft robot
position errors, we observed that the improvement in performance is highly
dependent on the expertise of the human operator.


  Recent measurements in high-multiplicity pp and p-A collisions have revealed
that these small collision systems exhibit collective-like behaviour, formerly
thought to be achievable only in heavy-ion collisions. To understand the
origins of these unexpected phenomena, event shape observables can be
exploited, as they serve as a powerful tool to disentangle soft and hard
contributions to particle production. Here, results on the production of light
flavor hadrons for different classes of unweighted transverse spherocity
($S_{\rm 0}^{p_{\rm T}= 1}$) and relative transverse activity ($R_{\rm{T}}$) in
high multiplicity pp collisions at $\sqrt{s}$ = 13 $\textrm{TeV}$ measured with
the ALICE detector are presented. Hadron-to-pion ratios in different $S_{\rm
0}^{p_{\rm T}= 1}$ and $R_{\rm{T}}$ classes are also presented and compared
with state-of-the-art QCD-inspired Monte Carlo event generators. The evolution
of charged particle average transverse momentum ($\langle p_{\rm T}\rangle$)
with multiplicity and $S_{\rm 0}^{p_{\rm T}= 1}$ is also discussed. In
addition, the system size dependence of charged particle production in pp,
p-Pb, and Pb-Pb collisions at $\sqrt{s_{\rm NN}}$= 5.02 TeV is presented.
Finally, within the same approach, we present a search for jet quenching
behavior in small collision systems.


  While uniform temperature has no effect on equilibrium properties of
hard-core systems, its gradient might substantially change their behaviour. In
particular, in hard-disk system subject to temperature difference $\Delta T$
disks are repelled from the hot boundary of the system and accumulate at the
cold one. Using event-driven molecular dynamics simulations we show that for
sufficiently large $\Delta T$ or coverage ratio $\rho^*$, crystal forms at the
cold boundary. In this spatially inhomogeneous system a significant decrease of
diffusivity of disks clearly marks the stationary interface between liquid and
crystal. Such a behaviour is also supported through calculation of the radial
distribution function and the bond order parameter. Simulations show that for
this nonequilibrium system the equipartition of energy holds and velocity obeys
the Boltzmann distribution.


  We study the signature change in a perfect fluid Friedmann-Robertson-Walker
quantum cosmological model. In this work the Schutz's variational formalism is
applied to recover the notion of time. This gives rise to a
Schrodinger-Wheeler-DeWitt equation with arbitrary ordering for the scale
factor. We use the eigenfunctions in order to construct wave packets and
evaluate the time-dependent expectation value of the scale factor which
coincides with the ontological interpretation. We show that these solutions
exhibit signature transitions from a finite Euclidean to a Lorentzian domain.
Moreover, such models are equivalent to a classical system where, besides the
perfect fluid, a repulsive fluid is present.


  Antonio Ros gave a lower bound for the first eigenvalue $\lambda_1$ of
$\Delta$ of a $P$-manifold $(M, g)$ in terms of the lower bound on the Ricci
curvature $Ric_M$ and asked what happened when this lower bound was achieved.
In this paper we look in to this question and show that there are strong
implications on the geometry and topology of the underlying manifold. In
particular we show that in case of spheres or real projective spaces we have
isometry with the standard metric. In other cases, with some additional
hypothesis, we again show isometry with standard models.


  Key issues in upcoming FDDI standards including low-cost fiber, twisted-pair,
SONET mapping, and FDDI follow-on LAN are discussed after a brief introduction
to FDDI and FDDI-II


  We carry out the Hamiltonian analysis of the local vacuum energy sequestering
model - a manifestly local and diffeomorphism invariant extension of general
relativity which has been shown to remove the radiatively unstable contribution
to the vacuum energy generated by matter loops. We find that the degravitation
of this UV sensitive quantity is enforced via global relations that are a
consequence of the model's peculiar constraint structure. We also show that the
model propagates the proper number of degrees of freedom and thus locally
reduces to general relativity on-shell.


  We report on the results from an ongoing program aimed at testing Newton's
law of gravity in the low acceleration regime using globular clusters. It is
shown that all clusters studied so far do behave like galaxies, that is, their
velocity dispersion profile flattens out at large radii where the acceleration
of gravity goes below 1e-8 cm/s/s, instead of following the expected Keplerian
fall off. In galaxies this behavior is ascribed to the existence of a dark
matter halo. Globular clusters, however, do not contain dark matter, hence this
result might indicate that our present understanding of gravity in the weak
regime of accelerations is incomplete and somehow incorrect.


  This work proposes a digital quantum simulation protocol for the linear
scattering process of bosons, which provides a simple extension to partially
distinguishable boson cases. Our protocol is achieved by combining the
boson-fermion correspondence relation and fermion to qubit encoding protocols.
As a proof of concept, we designed quantum circuits for generating the
Hong-Ou-Mandel dip by varying particle distinguishability. The circuits were
verified with the classical and quantum simulations using the IBM Quantum and
IonQ cloud services.


  Origin of turbulence in cold accretion disks, particularly in 3D, which is
expected to be hydrodynamic but not magnetohydrodynamic, is a big puzzle. While
the flow must exhibit some turbulence in support of the transfer of mass inward
and angular momentum outward, according to the linear perturbation theory it
should always be stable. We demonstrate that the 3D secondary disturbance to
the primarily perturbed disk which exhibits elliptical vortices into the system
solves the problem. This result is essentially applicable to the outer region
of accretion disks in active galactic nuclei where the gas is significantly
cold and neutral in charge and the magnetic Reynolds number is smaller than
10^4.


  Intelligent, large-scale IoT ecosystems have become possible due to recent
advancements in sensing technologies, distributed learning, and low-power
inference in embedded devices. In traditional cloud-centric approaches, raw
data is transmitted to a central server for training and inference purposes. On
the other hand, Federated Learning migrates both tasks closer to the edge nodes
and endpoints. This allows for a significant reduction in data exchange while
preserving the privacy of users. Trained models, though, may under-perform in
dynamic environments due to changes in the data distribution, affecting the
model's ability to infer accurately; this is referred to as concept drift. Such
drift may also be adversarial in nature. Therefore, it is of paramount
importance to detect such behaviours promptly. In order to simultaneously
reduce communication traffic and maintain the integrity of inference models, we
introduce FLARE, a novel lightweight dual-scheduler FL framework that
conditionally transfers training data, and deploys models between edge and
sensor endpoints based on observing the model's training behaviour and
inference statistics, respectively. We show that FLARE can significantly reduce
the amount of data exchanged between edge and sensor nodes compared to
fixed-interval scheduling methods (over 5x reduction), is easily scalable to
larger systems, and can successfully detect concept drift reactively with at
least a 16x reduction in latency.


  The catalytic role of dust grain surfaces in the thermal reaction CO2 + 2NH3
$\rightarrow$ NH4+NH2COO was recently demonstrated by our group. The rate
coefficients for the reaction at 80 K on the surface of nanometre-sized carbon
and silicate grains were measured to be up to three times higher compared to
the reaction rate coefficients measured on KBr. In this study, the reaction was
performed on carbon grains and on KBr in the extended temperature range of 50 -
80 K and with the addition of water ice. The reaction activation energy was
found to be about 3 times lower on grains compared to the corresponding ice
layer on KBr. Thus, the catalytic role of the dust grain surface in the studied
reaction can be related to a reduction of the reaction barrier. Addition of
water to NH3:CO2 ice on grains slowed the reaction down. At the H2O:CO2 ratio
of 5:1, the reaction was not detected on the experimental timescale. This
result calls into question the thermal formation of ammonium carbamate in dense
molecular clouds and outer regions of protostellar and protoplanetary
environments with dominating water ice mantle chemistry. However, it can still
happen in inner regions of protostellar and protoplanetary environments in
crystalline ices.


  The partial group algebra of a group G over a field K, denoted by K_{par}(G),
is the algebra whose representations correspond to the partial representations
of G over K-vector spaces. In this paper we study the structure of the partial
group algebra K_{par}(G), where G is a finite group. In particular, given two
finite abelian groups G_1 and G_2, we prove that if the characteristic of K is
zero, then K_{par}(G_1) is isomorphic to K_{par}(G_2) if and only if G_1 is
isomorphic to G_2.


  Many real-world scenarios require the random selection of one or more
individuals from a pool of eligible candidates. One example of especial social
relevance refers to the legal system, in which the jurors and judges are
commonly picked according to some probability distribution aiming to avoid
biased decisions. In this scenario, ensuring auditability of the random drawing
procedure is imperative to promote confidence in its fairness. With this goal
in mind, this article describes a protocol for random drawings specially
designed for use in legal systems. The proposed design combines the following
properties: security by design, ensuring the fairness of the random draw as
long as at least one participant behaves honestly; auditability by any
interested party, even those having no technical background, using only public
information; and statistical robustness, supporting drawings where candidates
may have distinct probability distributions. Moreover, it is capable of
inviting and engaging as participating stakeholders the main interested parties
of a legal process, in a way that promotes process transparency, public trust
and institutional resilience. An open-source implementation is also provided as
supplementary material.


  Millimeter wave (mmWave) will play a significant role as a 5G candidate in
facing the growing demand of enormous data rate in the near future. The
conventional mmWave standard, IEEE 802.11ad, considers establishing only one
mmWave link in wireless local area network (WLAN) to provide multi Gbps data
rate. But, mmWave has a tenuous channel which hinders it from providing such
rate. Hence, it's necessary to establish multiple mmWave links simultaneously
by deploying a multiple number of mmWave access points (APs) in 5G networks.
Unfortunately, applying conventional standard without any modifications for
mmWave concurrent transmission impedes mmWave APs from selecting optimum mmWave
concurrent links. Because IEEE 802.11ad standard associates the user equipment
(UEs) to mmWave APs using the link that has the maximum received power without
considering mutual interference between simultaneous links. In this paper, a
joint proportional fairness scheduling (JPFS) optimization problem for
establishing optimum mmWave concurrent transmission links is formulated. And,
to find a solution to this non-polynomial (NP) time problem, we use exhaustive
search (ES) scheme. Numerical simulation proves the effectiveness of using the
ES scheme to improve the system performance.


  Graded modal logics generalise standard modal logics via families of
modalities indexed by an algebraic structure whose operations mediate between
the different modalities. The graded "of-course" modality $!_r$ captures how
many times a proposition is used and has an analogous interpretation to the
of-course modality from linear logic; the of-course modality from linear logic
can be modelled by a linear exponential comonad and graded of-course can be
modelled by a graded linear exponential comonad. Benton showed in his seminal
paper on Linear/Non-Linear logic that the of-course modality can be split into
two modalities connecting intuitionistic logic with linear logic, forming a
symmetric monoidal adjunction. Later, Fujii et al. demonstrated that every
graded comonad can be decomposed into an adjunction and a 'strict action'. We
give a similar result to Benton, leveraging Fujii et al.'s decomposition,
showing that graded modalities can be split into two modalities connecting a
graded logic with a graded linear logic. We propose a sequent calculus, its
proof theory and categorical model, and a natural deduction system which we
show is isomorphic to the sequent calculus. Interestingly, our system can also
be understood as Linear/Non-Linear logic composed with an action that adds the
grading, further illuminating the shared principles between linear logic and a
class of graded modal logics.


  We report on hydrazine-sensing organic electrochemical transistors (OECTs)
with a design consisting in concentric annular electrodes. The design
engineering of these OECTs was motivated by the great potential of using OECT
sensing arrays in fields such as bioelectronics. In this work, PEDOT:PSS-based
OECTs have been studied as aqueous sensors, specifically sensitive to the
lethal hydrazine molecule. These amperometric sensors have many relevant
features for the development of hydrazine sensors, such as a sensitivity down
to 10-5 M of hydrazine in water, an order of magnitude higher selectivity for
hydrazine than for 9 other water soluble common analytes, the capability to
recover entirely its base signal after water flushing and a very low voltage
operation. The specificity for hydrazine to be sensed by our OECTs is caused by
its catalytic oxidation at the gate electrode and enables increasing the output
current modulation of the devices. This has permitted the device-geometry study
of the whole series of 80 micrometric OECT devices with sub-20-nm PEDOT:PSS
layers, channel lengths down to 1um and a specific device geometry of coplanar
and concentric electrodes. The numerous geometries unravel new aspects of the
OECT mechanisms governing the electrochemical sensing behaviours of the device,
more particularly the effect of the contacts which are inherent at the
micro-scale. By lowering the device cross-talking, micrometric gate-integrated
radial OECTs shall contribute to the diminishing of the readout invasiveness
and therefore promotes further the development of OECT biosensors.


  Biological microswimmers, like euglena, deform their body shape to swim
through tight confinements having length scales comparable to the microswimmer
length scale. Recently, it was shown that self-propelling active droplets can
also squeeze through tight microconfinements by elongating their shape.
However, the evolution of the hydrodynamic signature, or the velocity field,
generated by the active droplet, as it deforms its shape to swim through
increasingly tight microconfinements, has remained scarcely studied. Using
high-resolution fluorescence microscopy and $\mu$-Particle Image Velocimetry
(PIV) analysis, we show here that as the swimming active droplet deforms from a
spherical shape to a `stadium'-like shape, and eventually to an elongated
`capsule'-like shape in increasingly tighter microchannels, its hydrodynamic
signature changes from a `pusher'-like velocity field to a `puller'-like
velocity field, and finally to an asymmetric velocity field. We characterize
such alterations in the active droplet dynamics using the distributions of the
local velocity magnitude, axial and transverse components of the local flow
velocity, vorticity, and the filled micelle concentration. Finally, we use
finite-element based numerical simulations to explain the aforementioned
evolution of the velocity field stemming from the underlying physico-chemical
hydrodynamics in the presence of a thin lubrication film between the swimming
active droplet and the tight microconfinement walls. The present work provides
a comprehensive understanding of the chemo-hydrodynamic characteristics of
active droplets navigating extreme confined spaces, which can be beneficial for
many autonomous cargo-delivery applications.