  The observation of surface phonon dispersion using local probes can provide
important information related to local structural and thermal properties. In
this study, surface phonon modes on a Cu(100) surface were measured using the
inelastic tunneling spectroscopy of scanning tunneling microscopy (STM-IETS)
with atomically sharp tips. Different phonon modes were selectively measured
depending on the structures of the probing tips or the surfaces. Two different
surface phonon modes, at 19.0 meV on a clean Cu(100) surface and at 13.5 meV on
an oxygen-adsorbed Cu(100) surface, are explained by the selection rules.
Additionally, the spatial variation in STM-IETS showed surface stress
relaxation.


  The radical anion salt [Fe{HC(pz)3}2](TCNQ)3 demonstrating conductivity and
spin-crossover transition (SCO) associated with Fe(II) complex cation subsystem
has been synthesized and structurally characterized. A pronounced change of the
dc resistivity and a robust broadening of the EPR signal triggered by the SCO
transition are found. Enhanced EPR line broadening is interpreted in terms of
cross relaxation between the TCNQ and Fe(II) spin subsystems


  This list presents problems in the Reverse Mathematics of infinitary Ramsey
theory which I find interesting but do not personally have the techniques to
solve. The intent is to enlist the help of those working in Reverse Mathematics
to take on such problems, and the myriad of related questions one can infer
from them. A short bit of background and starting references are provided.


  SPLASH (the Southern Parkes Large-Area Survey in Hydroxyl) is a sensitive,
unbiased and fully-sampled survey of the Southern Galactic Plane and Galactic
Centre in all four ground-state transitions of the hydroxyl (OH) radical. The
survey provides a deep census of 1612-, 1665-, 1667- and 1720-MHz OH absorption
and emission from the Galactic ISM, and is also an unbiased search for maser
sources in these transitions. We present here first results from the SPLASH
pilot region, which covers Galactic longitudes 334 to 344 degrees and latitudes
of -2 to +2 degrees. Diffuse OH is widely detected in all four transitions,
with optical depths that are always small (averaged over the Parkes beam), and
with departures from LTE common even in the 1665- and 1667-MHz main lines. To a
3$\sigma$ sensitivity of 30 mK, we find no evidence of OH envelopes extending
beyond the CO-bright regions of molecular cloud complexes, and conclude that
the similarity of the OH excitation temperature and the level of the continuum
background is at least partly responsible for this. We detect masers and maser
candidates in all four transitions, approximately 50 per cent of which are new
detections. This implies that SPLASH will produce a substantial increase in the
known population of ground-state OH masers in the Southern Galactic Plane.


  This work is devoted to the study of the limiting behaviour of the Stokes
type fluid flows in porous media. The boundary conditions here are of the
Fourier-Neumann's type on the boundary of the holes. Under the periodic
hypothesis on the structure of the medium and on the coefficients of the
viscosity tensor, one convergence result is proved. Our approach is the well
known two-scale convergence method.


  Let $(A,\Theta)$ be a complex principally polarized abelian variety of
dimension $g\geq 4$. Based on vanishing theorems, differentiation techniques
and intersection theory, we show that whenever the theta divisor $\Theta$ is
irreducible, its multiplicity at any point is at most $g-2$. This improves work
of Koll\'ar, Smith-Varley, and Ein-Lazarsfeld. We also introduce some new ideas
to study the same type of questions for pluri-theta divisors.


  In this paper, we study an algorithm for solving a class of nonconvex and
nonsmooth nonseparable optimization problems. Based on proximal alternating
linearized minimization (PALM), we propose a new iterative algorithm which
combines two-step inertial extrapolation and Bregman distance. By constructing
appropriate benefit function, with the help of Kurdyka--{\L}ojasiewicz property
we establish the convergence of the whole sequence generated by proposed
algorithm. We apply the algorithm to signal recovery, quadratic fractional
programming problem and show the effectiveness of proposed algorithm.


  As a method for controlling active materials, researchers have suggested
designing patterns of activity on a substrate, which should guide the motion of
topological defects. To investigate this concept, we model the behavior of a
single defect of topological charge $+1/2$, moving in an activity gradient.
This modeling uses three methods: (1) approximate analytic solution of
hydrodynamic equations, (2) macroscopic, symmetry-based theory of the defect as
an effective oriented particle, and (3) numerical simulation. All three methods
show that an activity gradient aligns the defect orientation, and hence should
be useful to control defect motion.


  We develop convergent variational perturbation theory for quantum statistical
density matrices. The theory is applicable to polynomial as well as
nonpolynomial interactions. Illustrating the power of the theory, we calculate
the temperature-dependent density of a particle in a double-well and of the
electron in a hydrogen atom.


  We study hard-core bosons on the honeycomb lattice subjected to anisotropic
nearest-neighbor hopping along with anisotropic nearest-neighbor repulsion,
using a quantum Monte Carlo technique. At half-filling, we find a transition
from strong interacting-topological order to weak interacting-topological order
as function of the hopping anisotropy. The strong topological phase is
characterized by a finite topological entanglement entropy, while the weak
topological order is identified with a non-trivial value of the bipartite
entanglement entropy. Some of the order parameters and their derivatives
demonstrate abrupt changes when varying the parameters controlling the lattice
anistropies, thus revealing the nature of this interacting-topological phase
transition.


  This paper presents an innovative nano strain-amplifier employed to
significantly enhance the sensitivity of piezoresistive strain sensors.
Inspired from the dogbone structure, the nano strain-amplifier consists of a
nano thin frame released from the substrate, where nanowires were formed at the
centre of the frame. Analytical and numerical results indicated that a nano
strain-amplifier significantly increases the strain induced into a free
standing nanowire, resulting in a large change in their electrical conductance.
The proposed structure was demonstrated in p-type cubic silicon carbide
nanowires fabricated using a top down process. The experimental data showed
that the nano strain-amplifier can enhance the sensitivity of SiC strain
sensors at least 5.4 times larger than that of the conventional structures.
This result indicates the potential of the proposed strain-amplifier for
ultra-sensitive mechanical sensing applications.


  Brain tissue segmentation from multimodal MRI is a key building block of many
neuroscience analysis pipelines. It could also play an important role in many
clinical imaging scenarios. Established tissue segmentation approaches have
however not been developed to cope with large anatomical changes resulting from
pathology. The effect of the presence of brain lesions, for example, on their
performance is thus currently uncontrolled and practically unpredictable.
Contrastingly, with the advent of deep neural networks (DNNs), segmentation of
brain lesions has matured significantly and is achieving performance levels
making it of interest for clinical use. However, few existing approaches allow
for jointly segmenting normal tissue and brain lesions. Developing a DNN for
such joint task is currently hampered by the fact that annotated datasets
typically address only one specific task and rely on a task-specific
hetero-modal imaging protocol. In this work, we propose a novel approach to
build a joint tissue and lesion segmentation model from task-specific
hetero-modal and partially annotated datasets. Starting from a variational
formulation of the joint problem, we show how the expected risk can be
decomposed and optimised empirically. We exploit an upper-bound of the risk to
deal with missing imaging modalities. For each task, our approach reaches
comparable performance than task-specific and fully-supervised models.


  We use our disc formula for the Siciak-Zahariuta extremal function to
characterize the polynomial hull of a connected compact subset of complex
affine space in terms of analytic discs.


  We study processes of societal knowledge accumulation, where the validity of
a new unit of knowledge depends both on the correctness of its derivation and
on the validity of the units it depends on. A fundamental question in this
setting is: If a constant fraction of the new derivations is wrong, can
investing a constant fraction, bounded away from one, of effort ensure that a
constant fraction of knowledge in society is valid? Ben-Eliezer, Mikulincer,
Mossel, and Sudan (ITCS 2023) introduced a concrete probabilistic model to
analyze such questions and showed an affirmative answer to this question. Their
study, however, focuses on the simple case where each new unit depends on just
one existing unit, and units attach according to a $\textit{preferential
attachment rule}$.
  In this work, we consider much more general families of cumulative knowledge
processes, where new units may attach according to varied attachment mechanisms
and depend on multiple existing units. We also allow a (random) fraction of
insertions of adversarial nodes.
  We give a robust affirmative answer to the above question by showing that for
$\textit{all}$ of these models, as long as many of the units follow simple
heuristics for checking a bounded number of units they depend on, all errors
will be eventually eliminated. Our results indicate that preserving the quality
of large interdependent collections of units of knowledge is feasible, as long
as careful but not too costly checks are performed when new units are
derived/deposited.


  This work provides a general spectral analysis of size-structured two-phase
population models. Systematic functional analytic results are given. We deal
first with the case of finite maximal size. We characterize the irreducibility
of the corresponding $L^{1}$ semigroup in terms of properties of the different
parameters of the system. We characterize also the spectral gap property of the
semigroup. It turns out that the irreducibility of the semigroup implies the
existence of the spectral gap. In particular, we provide a general criterion
for asynchronous exponential growth. We show also how to deal with time
asymptotics in case of lack of irreducibility. Finally, we extend the theory to
the case of infinite maximal size.


  We present an edge-on Keplerian disc model to explain the main component of
the 12.2 and 6.7 GHz methanol maser emission detected toward NGC7538-IRS1 N.
The brightness distribution and spectrum of the line of bright masers are
successfully modeled with high amplification of background radio continuum
emission along velocity coherent paths through a maser disc. The bend seen in
the position-velocity diagram is a characteristic signature of differentially
rotating discs. For a central mass of 30 solar masses, suggested by other
observations, our model fixes the masing disc to have inner and outer radii of
about 350 AU and 1000 AU.


  Radiative deceleration of relativistic jets in active galactic nuclei as the
result of inverse Compton scattering of soft photons from accretion discs is
discussed. The Klein-Nishina (KN) cross section is used in the calculation of
the radiation force due to inverse Compton scattering. Our result shows that
deceleration due to scattering in the KN regime is important only for jets
starting with a bulk Lorentz factor larger than 1000. When the bulk Lorentz
factor satisfies this condition, particles scattering in the Thomson regime
contribute positively to the radiation force (acceleration), but those
particles scattering in the KN regime are dominant and the overall effect is
deceleration. In the KN limit, the drag due to Compton scattering, though less
severe than in the Thomson limit, strongly constrains the bulk Lorentz factor.
Most of the power from the deceleration goes into radiation and hence the
ability of the jet to transport significant power (in particle kinetic energy)
out of the subparsec region is severely limited. The deceleration efficiency
decreases significantly if the jet contains protons and the proton to electron
number density ratio satisfies the condition $n_p/n_{e0}>2\gamma_{\rm
min}/\mu_p$ where $\gamma_{\rm min}$ is the minimum Lorentz factor of
relativistic electrons (or positrons) in the jet frame and $\mu_p$ is the
proton to electron mass ratio.


  Transition metal phosphorous trichalcogenides, $M{\rm P}X_3$ ($M$ and $X$
being transition metal and chalcogen elements respectively), have been the
focus of substantial interest recently because of their possible magnetism in
the two-dimensional limit. Here we investigate material properties of the
compounds with $M$ = Mn and Ni employing $\textit{ab-initio}$ density
functional and dynamical mean-field calculations, especially their electronic
behavior under external pressure in the paramagnetic phase. Mott
metal-insulator transitions (MIT) are found to be a common feature for both
compounds, but their lattice structures show drastically different behaviors
depending on the relevant orbital degrees of freedom, i.e. $t_{\rm 2g}$ or
$e_{g}$. MnPS$_3$ undergoes an isosymmetric structural transition by forming
Mn-Mn dimers due to the strong direct overlap between the neighboring $t_{\rm
2g}$ orbitals, accompanied by a significant volume collapse and a spin-state
transition. In contrast, NiPS$_3$ and NiPSe$_3$, with their active $e_g$
orbital degrees of freedom, do not show a structural change at the MIT pressure
or deep in the metallic phase. Hence NiPS$_3$ and NiPSe$_3$ become rare
examples of materials hosting electronic bandwidth-controlled Mott MITs, thus
showing promise for ultrafast resistivity switching behavior.


  The IceCube Neutrino Observatory, completed in December 2010 and located at
the geographic South Pole, is the largest neutrino telescope in the world.
IceCube includes the more densely instrumented DeepCore subarray, which
increases IceCube's sensitivity at neutrino energies down to 10 GeV. DeepCore
has recently demonstrated sensitivity to muon neutrino disappearance from
atmospheric neutrino oscillation. A further extension is under consideration,
the Precision IceCube Next Generation Upgrade (PINGU) which would lower the
energy threshold below about 10 GeV. In particular, PINGU would be sensitive to
the effects of the neutrino mass hierarchy, which is one of the outstanding
questions in particle physics. Preliminary feasibility studies indicate that
PINGU can make a high significance determination of the mass hierarchy within a
few years of construction.


  The observation of the decay $\varXi^{-}_{b}\to J/\psi\varLambda K^{-}$ is
reported, using a data sample corresponding to an integrated luminosity of
$3~\mathrm{fb}^{-1}$, collected by the LHCb detector in $pp$ collisions at
centre-of-mass energies of $7$ and $8~\mathrm{TeV}$. The production rate of
$\varXi_{b}^{-}$ baryons detected in the decay $\varXi_{b}^{-}\to
J/\psi\varLambda K^{-}$ is measured relative to that of $\varLambda_{b}^{0}$
baryons using the decay $\varLambda_{b}^{0}\to J/\psi \varLambda$. Integrated
over the $b$-baryon transverse momentum $p_{\rm T}<25~\mathrm{GeV/}c $ and
rapidity $2.0<y<4.5$, the measured ratio is \begin{equation*}
\frac{f_{\varXi_{b}^{-}}}{f_{\varLambda_{b}^{0}}}\frac{\mathcal{B}(\varXi_{b}^{-}\to
J/\psi\varLambda K^{-})}{\mathcal{B}(\varLambda_{b}^{0}\to J/\psi
\varLambda)}=(4.19\pm 0.29~(\mathrm{stat})\pm0.15~(\mathrm{syst}))\times
10^{-2}, \end{equation*}where $f_{\varXi_{b}^{-}}$ and $f_{\varLambda_{b}^{0}}$
are the fragmentation fractions of $b\to\varXi_{b}^{-}$ and
$b\to\varLambda_{b}^{0}$ transitions, and $\mathcal{B}$ represents the
branching fraction of the corresponding $b$-baryon decay. The mass difference
between $\varXi_{b}^{-}$ and $\varLambda_{b}^{0}$ baryons is measured to be
\begin{equation*}
M(\varXi_{b}^{-})-M(\varLambda_{b}^{0})=177.08\pm0.47~(\mathrm{stat})\pm0.16~(\mathrm{syst}
)~\mathrm{MeV/}c^{2}. \end{equation*}


  In recent years, the rapid rise of video applications has led to an explosion
of Internet video traffic, thereby posing severe challenges to network
management. Therefore, effectively identifying and managing video traffic has
become an urgent problem to be solved. However, the existing video traffic
feature extraction methods mainly target at the traditional packet and flow
level features, and the video traffic identification accuracy is low.
Additionally, the issue of high data dimension often exists in video traffic
identification, requiring an effective approach to select the most relevant
features to complete the identification task. Although numerous studies have
used feature selection to achieve improved identification performance, no
feature selection research has focused on measuring feature distributions that
do not overlap or have a small overlap. First, this study proposes to extract
video-related features to construct a large-scale feature set to identify video
traffic. Second, to reduce the cost of video traffic identification and select
an effective feature subset, the current research proposes an adaptive
distribution distance-based feature selection (ADDFS) method, which uses
Wasserstein distance to measure the distance between feature distributions. To
test the effectiveness of the proposal, we collected a set of video traffic
from different platforms in a campus network environment and conducted a set of
experiments using these data sets. Experimental results suggest that the
proposed method can achieve high identification performance for video scene
traffic and cloud game video traffic identification. Lastly, a comparison of
ADDFS with other feature selection methods shows that ADDFS is a practical
feature selection technique not only for video traffic identification, but also
for general classification tasks.


  Materials that demonstrate large magnetoresistance have attracted significant
interest for many decades. Recently, extremely large tunnel magnetoresistance
(TMR) has been reported by several groups across ultrathin CrI$_3$ by
exploiting the weak antiferromagnetic coupling between adjacent layers. Here,
we report a comparative study of TMR in all three chromium trihalides (CrX$_3$,
X= Cl, Br, or I) in the two-dimensional limit. As the materials exhibit
different transition temperatures and interlayer magnetic ordering in the
ground state, tunneling measurements allow for an easy determination of the
field-temperature phase diagram for the three systems. By changing sample
thickness and biasing conditions, we then demonstrate how to maximize and
further tailor the TMR response at different temperatures for each material. In
particular, near the magnetic transition temperature, TMR is non-saturating up
to the highest fields measured for all three compounds owing to the large,
field-induced exchange coupling.


  A physically-motivated function was developed to accurately determine the
total absorption peak in an electromagnetic calorimeter and to overcome biases
present in many commonly used methods. The function is the convolution of a
detector resolution function with the sum of a delta function, which represents
the complete absorption of energy, and a tail function, which describes the
partial absorption of energy and depends on the detector materials and
structures. Its performance was tested with the simulation of three typical
cases. The accuracy of the extracted peak value, resolution, and peak area was
improved by an order of magnitude on average, relative to the Crystal Ball
function.


  The phase Hamiltonian of armchair carbon nanotubes at half-filling and away
from it is derived from the microscopic lattice model by taking the long range
Coulomb interaction into account. We investigate the low energy properties of
the system using the renormalization group method. At half-filling, the ground
state is a Mott insulator with spin gap, in which the bound states of electrons
at different atomic sublattices are formed. The difference from the recent
results [Phys. Rev. Lett. 79, 5082 (1997)] away half-filling is clarified.


  Suppose $G$ is an amenable locally compact group. If $\{F_\gamma\} =
\{F_\gamma\}_{\gamma\in\Gamma}$ is a F\o{}lner net for $G$, associate it with
the net $\{\chi_{F_\gamma} / |F_\gamma|\} \subset L_1(G) \subset
L_\infty^*(G)$. Thus, every accumulation point of $\{F_\gamma\}$ is a
topological left-invariant mean on $G$. The following are examples of results
proved in the present thesis:
  (1) There exists a F\o{}lner net which has as its accumulation points a set
of $2^{2^{\kappa}}$ distinct topological left-invariant means on $G$, where
$\kappa$ is the smallest cardinality of a covering of $G$ by compact subsets.
  (2) If $G$ is unimodular and $\mu$ is a topological left-invariant mean on
$G$, there exists a F\o{}lner net which has $\mu$ as its unique accumulation
point.
  (3) Suppose $L \subset G$ is a lattice subgroup. There is a natural bijection
of the left-invariant means on $L$ with the topological left-invariant means on
$G$ if and only if $G/L$ is compact.
  (4) Every topological left-invariant mean on $G$ is also topological
right-invariant if and only if $G$ has precompact conjugacy classes.
  These results lie at the intersection of functional analysis with general
topology. Problems in this area can often be solved with standard tools when
$G$ is $\sigma$-compact or metrizable, but require more interesting arguments
in the general case.


  The idea to extract information on magnetically different phases from
magnetic measurements is very attractive and many efforts were made in this
area. One of the most popular direction is to use the Preisach model formalism
to analyze the 2D Preisach distribution function (PDF) obtained either from
first order reversal curves (FORC) or minor loops measurements. Only these two
sentences, because Arxiv says - Bad character in field Abstract. I do not see
any bad character in my Abstract.


  A non-orthogonal multiple access (NOMA) inspired integrated sensing and
communication (ISAC) system is investigated. A dual-functional base station
(BS) serves multiple communication users while sensing multiple targets, by
transmitting the non-orthogonal superposition of the communication and sensing
signals. A NOMA inspired interference cancellation scheme is proposed, where
part of the dedicated sensing signal is treated as the virtual communication
signals to be mitigated at each communication user via successive interference
cancellation (SIC). Based on this framework, the transmitted communication and
sensing signals are jointly optimized to match the desired sensing beampattern,
while satisfying the minimum rate requirement and the SIC condition at the
communication users. Then, the formulated non-convex optimization problem is
solved by invoking the successive convex approximation (SCA) to obtain a
near-optimal solution. The numerical results show the proposed NOMA-inspired
ISAC system can achieve better performance than the conventional ISAC system
and comparable performance to the ideal ISAC system where all sensing
interference is assumed to be removed unconditionally.


  Due to the recent re-allocation of the 5.9 GHz band by the US Federal
Communications Commission (FCC), it will be inevitable that dedicated
short-range communications (DSRC) and cellular vehicle-to-everything (C-V2X),
two representative technologies for V2X, have to address coexistence.
Especially, the distributed nature of DSRC makes it not trivial to control
congestions due to an asynchronous structure, which makes it inefficient to
disseminate a controlling signal. To this end, we propose a method to "lighten"
a distributed V2X networking. Technically, it is to allocate the backoff
counter according to the level of an accident risk to which a vehicle is
temporarily exposed. We provide an analysis framework based on a spatiotemporal
analysis. The numerical results show the improvement in the successful delivery
of basic safety messages (BSMs).


  Motivated by Stanley's $\mathbf{(3+1)}$-free conjecture on chromatic
symmetric functions, Foley, Ho\`{a}ng and Merkel introduced the concept of
strong $e$-positivity and conjectured that a graph is strongly $e$-positive if
and only if it is (claw, net)-free. In order to study strongly $e$-positive
graphs, they further introduced the twinning operation on a graph $G$ with
respect to a vertex $v$, which adds a vertex $v'$ to $G$ such that $v$ and $v'$
are adjacent and any other vertex is adjacent to both of them or neither of
them. Foley, Ho\`{a}ng and Merkel conjectured that if $G$ is $e$-positive, then
so is the resulting twin graph $G_v$ for any vertex $v$. Based on the theory of
chromatic symmetric functions in non-commuting variables developed by Gebhard
and Sagan, we establish the $e$-positivity of a class of graphs called tadpole
graphs. By considering the twinning operation on a subclass of these graphs
with respect to certain vertices we disprove the latter conjecture of Foley,
Ho\`{a}ng and Merkel. We further show that if $G$ is $e$-positive, the twin
graph $G_v$ and more generally the clan graphs $G^{(k)}_v$ ($k \ge 1$) may not
even be $s$-positive, where $G^{(k)}_v$ is obtained from $G$ by applying $k$
twinning operations to $v$.


  We have searched 101 Classical transneptunian objects for companions with the
Hubble Space Telescope. Of these, at least 21 are binary. The heliocentric
inclinations of the objects we observed range from 0.6-34 degrees. We find a
very strong anticorrelation of binaries with inclination. Of the 58 targets
that have inclinations of less than 5.5 degrees, 17 are binary, a binary
fraction of 29 +7/-6%. All 17 are similar-brightness systems. On the contrary,
only 4 of the 42 objects with inclinations greater than 5.5 degrees have
satellites and only 1 of these is a similar-brightness binary. This striking
dichotomy appears to agree with other indications that the low eccentricity,
non-resonant Classical transneptunian objects include two overlapping
populations with significantly different physical properties and dynamical
histories.


  We argue that the spatiotemporal dynamics of bred vectors in chaotic extended
systems are related to a kinetic roughening process in the Kardar-Parisi-Zhang
universality class. This implies that there exists a characteristic length
scale corresponding to the typical extend over which the finite-size
perturbation is actually correlated in space. This can be used as a
quantitative parameter to characterize the degree of projection of the bred
vectors into the dynamical attractor.


  The purpose of this paper is to establish the regularity the weak solutions
for a nonlinear biharmonic equation.


  We calculate the conformal anomaly from 5d Weyl gravity (with broken
conformal symmetry) which is conjectured to be supergravity dual to ${\cal
N}=2$ superconformal field theory via AdS/CFT correspondence. Its comparison
with ${\cal N}=2$ SCFT conformal anomaly (UV calculation) suggests that such
duality may exist subject to presence of sub-leading 1/N corrections to
cosmological and gravitational constants.


  Gamma-ray bursts (GRBs) are ideal probes of the Universe at high redshift (z
> 5), pinpointing the locations of the earliest star-forming galaxies and
providing bright backlights that can be used to spectrally fingerprint the
intergalactic medium and host galaxy during the period of reionization. Future
missions such as Gamow Explorer are being proposed to unlock this potential by
increasing the rate of identification of high-z GRBs to rapidly trigger
observations from 6-10 m ground telescopes, JWST, and the Extremely Large
Telescopes. Gamow was proposed to the NASA 2021 Medium-Class Explorer (MIDEX)
program as a fast-slewing satellite featuring a wide-field lobster-eye X-ray
telescope (LEXT) to detect and localize GRBs, and a 30 cm narrow-field
multi-channel photo-z infrared telescope (PIRT) to measure their photometric
redshifts using the Lyman-alpha dropout technique. To derive the PIRT
sensitivity requirement we compiled a complete sample of GRB
optical-near-infrared afterglows from 2008 to 2021, adding a total of 66 new
afterglows to our earlier sample, including all known high-z GRB afterglows. We
performed full light-curve and spectral-energy-distribution analyses of these
afterglows to derive their true luminosity at very early times. For all the
light curves, where possible, we determined the brightness at the time of the
initial finding chart of Gamow, at different high redshifts and in different
NIR bands. We then followed the evolution of the luminosity to predict
requirements for ground and space-based follow-up. We find that a PIRT
sensitivity of 15 micro-Jy (21 mag AB) in a 500 s exposure simultaneously in
five NIR bands within 1000s of the GRB trigger will meet the Gamow mission
requirement to recover > 80% of all redshifts at z > 5.


  It is well known in the literature that the momentum space associated to the
$\kappa$-Poincar\'e algebra is described by the Lie group
$\mathsf{A}\mathsf{N}(3)$. In this letter we show that the full
$\kappa$-Poincar\'e Hopf algebra structure can be obtained from rather
straightforward group-theoretic manipulations starting from the Iwasawa
decomposition of the of the $\mathsf{SO(1,4)}$ group.


  This paper provides a general overview of different perspectives and studies
on trust, offers a definition of trust, and provides factors that play a
substantial role in developing social trust, and shows from which perspectives
it can be fostered. The results showed that trust is playing an important role
in success for organizations involved in cross-national strategic partnerships.
Trust can reduce transaction costs, promotes inter-organizational
relationships, and improve subordinate relationships between managers.


  In the first part of the paper we generalize a descent technique due to
Harish-Chandra to the case of a reductive group acting on a smooth affine
variety both defined over arbitrary local field F of characteristic zero. Our
main tool is Luna slice theorem.
  In the second part of the paper we apply this technique to symmetric pairs.
In particular we prove that the pair (GL(n,C),GL(n,R)) is a Gelfand pair. We
also prove that any conjugation invariant distribution on GL(n,F) is invariant
with respect to transposition. For non-archimedean F the later is a classical
theorem of Gelfand and Kazhdan.
  We use the techniques developed here in our subsequent work [AG3] where we
prove an archimedean analog of the theorem on uniqueness of linear periods by
H. Jacquet and S. Rallis.


  In previous work \cite{W-Y-Z-local}, we studied the local well-posedness of
weak solution to the 1-D full compressible Navier-Stokes equation with initial
data of small total variation. Specifically, the local existence, the
regularity, and the uniqueness in certain function space of the weak solution
have been established. The basis for the previous study is the precise
construction of fundamental solution for heat equation with BV conductivity. In
this paper, we continue to investigate the global stability and the time
asymptotic behavior of the weak solution. The main step is to construct the
``effective Green's function'', which is the combination of the heat kernel
with BV coefficient in short time and the Green's function around constant
state in long time. The former one captures the quasi-linear nature of the
system, while the latter one respects the dissipative structure. Then the weak
solution is written into an integral system in terms of this ``effective
Green's function'', and the time asymptotic behavior is established based on a
priori estimate.


  We introduce a penalty term-based splitting algorithm with inertial effects
designed for solving monotone inclusion problems involving the sum of maximally
monotone operators and the convex normal cone to the (nonempty) set of zeros of
a monotone and Lipschitz continuous operator. We show weak ergodic convergence
of the generated sequence of iterates to a solution of the monotone inclusion
problem, provided a condition expressed via the Fitzpatrick function of the
operator describing the underlying set of the normal cone is verified. Under
strong monotonicity assumptions we can even show strong nonergodic convergence
of the iterates. This approach constitutes the starting point for investigating
from a similar perspective monotone inclusion problems involving linear
compositions of parallel-sum operators and, further, for the minimization of a
complexly structured convex objective function subject to the set of minima of
another convex and differentiable function.


  Super-symmetric tensors - a higher-order extension of scatter matrices - are
becoming increasingly popular in machine learning and computer vision for
modelling data statistics, co-occurrences, or even as visual descriptors.
However, the size of these tensors are exponential in the data dimensionality,
which is a significant concern. In this paper, we study third-order
super-symmetric tensor descriptors in the context of dictionary learning and
sparse coding. Our goal is to approximate these tensors as sparse conic
combinations of atoms from a learned dictionary, where each atom is a symmetric
positive semi-definite matrix. Apart from the significant benefits to tensor
compression that this framework provides, our experiments demonstrate that the
sparse coefficients produced by the scheme lead to better aggregation of
high-dimensional data, and showcases superior performance on two common
computer vision tasks compared to the state-of-the-art.


  Permutation is the different arrangements that can be made with a given
number of things taking some or all of them at a time. The notation P(n,r) is
used to denote the number of permutations of n things taken r at a time.
Permutation is used in various fields such as mathematics, group theory,
statistics, and computing, to solve several combinatorial problems such as the
job assignment problem and the traveling salesman problem. In effect,
permutation algorithms have been studied and experimented for many years now.
Bottom-Up, Lexicography, and Johnson-Trotter are three of the most popular
permutation algorithms that emerged during the past decades. In this paper, we
are implementing three of the most eminent permutation algorithms, they are
respectively: Bottom-Up, Lexicography, and Johnson-Trotter algorithms. The
implementation of each algorithm will be carried out using two different
approaches: brute-force and divide and conquer. The algorithms codes will be
tested using a computer simulation tool to measure and evaluate the execution
time between the different implementations.


  We present observations of four nearby early-type galaxies with previously
known nuclear stellar disks using two instruments on-board the Hubble Space
Telescope. We observed NGC4128, NGC4612, and NGC5308 with the Wide Field
Planetary Camera 2, and the same three galaxies, plus NGC4570, with the Space
Telescope Imaging Spectrograph. We have detected a red nucleus in NGC4128, a
blue nucleus in NGC4621, and a blue disk in NGC5308. Additionally, we have
discovered a blue disk-like feature with position angle ~15 degrees from the
major axis in NGC4621. In NGC5308 there is evidence for a blue region along the
minor axis. We discovered a blue transient on the images of NGC4128 at position
0.14" west and 0.32" north from the nucleus. The extracted kinematic profiles
belong to two groups: fast (NGC4570 and NGC5308) and kinematically disturbed
rotators (NGC4128 and NGC4621). We report the discovery of a kinematically
decoupled core in NGC4128. Galaxies have mostly old (10-14 Gyr) stellar
populations with large spread in metallicities (sub- to super-solar). We
discuss the possible formation scenarios, including bar-driven secular
evolution and the influence of mergers, which can explain the observed color
and kinematic features.


  As the scope of machine learning broadens, we observe a recurring theme of
algorithmic monoculture: the same systems, or systems that share components
(e.g. training data), are deployed by multiple decision-makers. While sharing
offers clear advantages (e.g. amortizing costs), does it bear risks? We
introduce and formalize one such risk, outcome homogenization: the extent to
which particular individuals or groups experience negative outcomes from all
decision-makers. If the same individuals or groups exclusively experience
undesirable outcomes, this may institutionalize systemic exclusion and
reinscribe social hierarchy. To relate algorithmic monoculture and outcome
homogenization, we propose the component-sharing hypothesis: if decision-makers
share components like training data or specific models, then they will produce
more homogeneous outcomes. We test this hypothesis on algorithmic fairness
benchmarks, demonstrating that sharing training data reliably exacerbates
homogenization, with individual-level effects generally exceeding group-level
effects. Further, given the dominant paradigm in AI of foundation models, i.e.
models that can be adapted for myriad downstream tasks, we test whether model
sharing homogenizes outcomes across tasks. We observe mixed results: we find
that for both vision and language settings, the specific methods for adapting a
foundation model significantly influence the degree of outcome homogenization.
We conclude with philosophical analyses of and societal challenges for outcome
homogenization, with an eye towards implications for deployed machine learning
systems.


  We show that electrons can couple to the neutron excitations in neutron stars
and find that this can limit their contribution to the transport properties of
dense matter, especially the shear viscosity. The coupling between electrons
and neutrons is induced by protons in the core, and by ions in the crust. We
calculate the effective electron-neutron interaction for the kinematics of
relevance to the scattering of degenerate electrons at high density. We use
this interaction to calculate the electron thermal conductivity, electrical
conductivity, and shear viscosity in the neutron star inner crust, and in the
core where we consider both normal and superfluid phases of neutron-rich
matter. In some cases, particularly when protons are superconducting and
neutrons are in their normal phase, we find that electron-neutron scattering
can be more important than the other scattering mechanisms considered
previously.


  We present the X-ray Luminosity Function (XLF) of the ROSAT Deep Cluster
Survey (RDCS) sample over the redshift range 0.05-0.8. Our results are derived
from a complete flux-limited subsample of 70 galaxy clusters, representing the
brightest half of the total sample, which have been spectroscopically
identified down to the flux limit of 4*10^{-14} erg/cm^2/s (0.5-2.0 keV) and
have been selected via a serendipitous search in ROSAT-PSPC pointed
observations. The redshift baseline is large enough that evolutionary effects
can be studied within the sample. The local XLF (z < 0.25) is found to be in
excellent agreement with previous determinations using the ROSAT All-Sky Survey
data. The XLF at higher redshifts, when combined with the deepest number counts
constructed to date (f>2*10^{-14} arg/cm^2/s), reveal no significant evolution
at least out to z=0.8, over a luminosity range 2*10^{42}-3*10^{44} erg/s in the
[0.5-2 keV] band. These findings extend the study of cluster evolution to the
highest redshifts and the faintest fluxes probed so far in X-ray surveys. They
complement and do not necessarily conflict with those of the Einstein Extended
Medium Sensitivity Survey, leaving the possibility of negative evolution of the
brightest end of the XLF at high redshifts.


  We consider the problem of channel estimation for uplink multiuser massive
MIMO systems, where, in order to significantly reduce the hardware cost and
power consumption, one-bit analog-to-digital converters (ADCs) are used at the
base station (BS) to quantize the received signal. Channel estimation for
one-bit massive MIMO systems is challenging due to the severe distortion caused
by the coarse quantization. It was shown in previous studies that an extremely
long training sequence is required to attain an acceptable performance. In this
paper, we study the problem of optimal one-bit quantization design for channel
estimation in one-bit massive MIMO systems. Our analysis reveals that, if the
quantization thresholds are optimally devised, using one-bit ADCs can achieve
an estimation error close to (with an increase by a factor of $\pi/2$) that of
an ideal estimator which has access to the unquantized data. The optimal
quantization thresholds, however, are dependent on the unknown channel
parameters. To cope with this difficulty, we propose an adaptive quantization
(AQ) approach in which the thresholds are adaptively adjusted in a way such
that the thresholds converge to the optimal thresholds, and a random
quantization (RQ) scheme which randomly generate a set of nonidentical
thresholds based on some statistical prior knowledge of the channel. Simulation
results show that, our proposed AQ and RQ schemes, owing to their wisely
devised thresholds, present a significant performance improvement over the
conventional fixed quantization scheme that uses a fixed (typically zero)
threshold, and meanwhile achieve a substantial training overhead reduction for
channel estimation. In particular, even with a moderate number of pilot symbols
(about 5 times the number of users), the AQ scheme can provide an achievable
rate close to that of the perfect channel state information (CSI) case.


  We analyze the phase diagram of an elementary statistical lattice model of
classical, discrete, spin variables, with nearest-neighbor ferro-magnetic
isotropic interactions in competition with chiral interactions along an axis.
At the mean-field level, we show the existence of para-magnetic lines of
transition to a region of modulated (helimagnetic) structures. We then turn to
the analysis of the analogous problem on a Cayley tree. Taking into account the
simplicity introduced by the infinite-coordination limit of the tree, we
explore several details of the phase diagrams in terms of temperature and a
parameter of competition. In particular, we characterize sequences of modulated
(helical) structures associated with devil's staircases of a fractal character.


  Interacting systems of events may exhibit cascading behavior where events
tend to be temporally clustered. While the cascades themselves may be obvious
from the data, it is important to understand which states of the system trigger
them. For this purpose, we propose a modeling framework based on
continuous-time Bayesian networks (CTBNs) to analyze cascading behavior in
complex systems. This framework allows us to describe how events propagate
through the system and to identify likely sentry states, that is, system states
that may lead to imminent cascading behavior. Moreover, CTBNs have a simple
graphical representation and provide interpretable outputs, both of which are
important when communicating with domain experts. We also develop new methods
for knowledge extraction from CTBNs and we apply the proposed methodology to a
data set of alarms in a large industrial system.


  With explosively escalating service demands, beyond fifth generation (B5G)
aims to realize various requirements for multi-service networks, i.e., higher
performance of mixed enhanced mobile broadband (eMBB) and ultra-reliable
low-latency communication (URLLC) services than 5G. To flexibly serve diverse
traffic, various functional split options (FSOs) are specified by 5G protocols
enabling different network functions. In order to improve signal qualities for
edge users, we consider FSO-based coordinated multi-point (CoMP) transmission
as a prominent technique capable of supporting high traffic demands. However,
due to conventional confined hardware processing capability, a processor
sharing (PS) model is introduced to deal with high latency for multi-service
FSO-based networks. Therefore, it becomes essential to assign CoMP-enhanced
functional split modes under PS model. A more tractable FSO-based network in
terms of ergodic rate and reliability is derived by stochastic geometry
approach. Moreover, we have proposed CoMP-enhanced functional split mode
allocation (CFSMA) scheme to adaptively assign FSOs to provide enhanced mixed
throughput and latency-aware services. The simulation results have validated
analytical derivation and demonstrated that the proposed CFSMA scheme optimizes
system spectrum efficiency while guaranteeing stringent latency requirement.
The proposed CFSMA scheme with the designed PS FFS-CoMP system outperforms the
benchmarks of conventional FCFS scheduling, non-FSO network, fixed FSOs, and
limited available FSO selections in open literature.


  A p-n junction maintained at above ambient temperature can work as a heat
engine, converting some of the supplied heat into electricity and rejecting
entropy by interband emission. Such thermoradiative cells have potential to
harvest low-grade heat into electricity. By analyzing the entropy content of
different spectral components of thermal radiation, we identify an approach to
increase the efficiency of thermoradiative cells via spectrally selecting
long-wavelength photons for radiative exchange. Furthermore, we predict that
the near-field photon extraction by coupling photons generated from interband
electronic transition to phonon polariton modes on the surface of a heat sink
can increase the conversion efficiency as well as the power generation density,
providing more opportunities to efficiently utilize terrestrial emission for
clean energy. An ideal InSb thermoradiative cell can achieve a maximum
efficiency and power density up to 20.4 % and 327 Wm-2, respectively, between a
hot source at 500K and a cold sink at 300K. However, sub-bandgap and
non-radiative losses will significantly degrade the cell performance.


  Artificial Intelligence (AI) approaches to problem-solving and
decision-making are becoming more and more complex, leading to a decrease in
the understandability of solutions. The European Union's new General Data
Protection Regulation tries to tackle this problem by stipulating a "right to
explanation" for decisions made by AI systems. One of the AI paradigms that may
be affected by this new regulation is Answer Set Programming (ASP). Thanks to
the emergence of efficient solvers, ASP has recently been used for
problem-solving in a variety of domains, including medicine, cryptography, and
biology. To ensure the successful application of ASP as a problem-solving
paradigm in the future, explanations of ASP solutions are crucial. In this
survey, we give an overview of approaches that provide an answer to the
question of why an answer set is a solution to a given problem, notably
off-line justifications, causal graphs, argumentative explanations and why-not
provenance, and highlight their similarities and differences. Moreover, we
review methods explaining why a set of literals is not an answer set or why no
solution exists at all.


  Corporations today face increasing demands for the timely and effective
delivery of customer service. This creates the need for a robust and accurate
automated solution to what is formally known as the ticket routing problem.
This task is to match each unresolved service incident, or "ticket", to the
right group of service experts. Existing studies divide the task into two
independent subproblems - initial group assignment and inter-group transfer.
However, our study addresses both subproblems jointly using an end-to-end
modeling approach. We first performed a preliminary analysis of half a million
archived tickets to uncover relevant features. Then, we devised the UFTR, a
Unified Framework for Ticket Routing using four types of features (derived from
tickets, groups, and their interactions). In our experiments, we implemented
two ranking models with the UFTR. Our models outperform baselines on three
routing metrics. Furthermore, a post-hoc analysis reveals that this superior
performance can largely be attributed to the features that capture the
associations between ticket assignment and group assignment. In short, our
results demonstrate that the UFTR is a superior solution to the ticket routing
problem because it takes into account previously unexploited interrelationships
between the group assignment and group transfer problems.


  We present our preliminary BIMA CO(1-0) images of II~Zw~96 which show huge
molecular gas concentrations outside the merging disks. The dominant extra-disk
CO concentrations in II~Zw~96 correspond to the two star-forming ``knots''
hidden by dust, whereas the others are associated with the two spiral disks.
The unique huge CO concentrations, $\approxgt 5$ kpc away from the merging
nuclei, account for $\approxgt 50 %$ of the total CO emission, yet only at a
moderate gas surface density as compared with that of ultraluminous infrared
galaxies (ULIGs). We tentatively conclude that the huge extra-disk gas
concentrations are most likely the overlap region of the gas disks, not
necessarily coinciding with the stellar disks overlap region. The gas disks
overlap region could be formed prior to the merging of the stellar disks and
become the overlap regions found between the disks like that in Arp~244 (the
``Antennae'' galaxies). These overlap regions would eventually nurture the {\it
extreme starbursts} and evolve into the extended gas disk surrounding the
double nuclei in final merging in most ULIGs.


  Two peculiar stars showing an apparent extremely broadened and strong NaI D
absorption have been discovered in surveys for cool white dwarfs by Oppenheimer
et al. (2001) and Harris et al. (SDSS, 2003). We discuss the nature of these
objects using PHOENIX atmosphere models for metal-poor brown dwarfs/very low
mass stars, and new white dwarf LTE and NLTE models for hydrogen- and
helium-dominated atmospheres with metals. These include complete molecular
formation in chemical equilibrium and a model for the alkali resonance line
broadening based on the damping profiles of Allard et al. (2003), as well as
new molecular line opacities for metal hydrides. First results of our
calculations indicate good agreement with a hydrogen-dominated WD atmosphere
with a Na abundance roughly consistent with a state of high accretion. We
analyse deviations of the abundances of Na, K, Mg and Ca from the cosmic
pattern and comment on implications of these results for standard accretion
scenarios.


  We show that wave maps from Minkowski space $\R^{1+n}$ to a sphere $S^{m-1}$
are globally smooth if the initial data is smooth and has small norm in the
critical Sobolev space $\dot H^{n/2}$, in all dimensions $n \geq 2$. This
generalizes the results in the prequel [math.AP/0010068] of this paper, which
addressed the high-dimensional case $n \geq 5$. In particular, in two
dimensions we have global regularity whenever the energy is small, and global
regularity for large data is thus reduced to demonstrating non-concentration of
energy.


  Token repetition is a typical form of multi-modal problem in fully
non-autoregressive translation (NAT). In this work, we revisit the multi-modal
problem in recently proposed NAT models. Our study reveals that these advanced
models have introduced other types of information redundancy errors, which
cannot be measured by the conventional metric - the continuous repetition
ratio. By manually annotating the NAT outputs, we identify two types of
information redundancy errors that correspond well to lexical and reordering
multi-modality problems. Since human annotation is time-consuming and
labor-intensive, we propose automatic metrics to evaluate the two types of
redundant errors. Our metrics allow future studies to evaluate new methods and
gain a more comprehensive understanding of their effectiveness.


  In this chapter we review phenomenological models of seizure like activity.
We discuss dynamical mechanisms for seizure onset and offset, preictal spikes,
spike and wave complexes and status epilepticus, highlighting the role played
by the bifurcation structure of the model, the presence of noise and the
emergence of multiple interacting time-scales. These models can be used to
build large-scale patient specific brain network models serving as in-silico
platforms to test clinical hypothesis and perform virtual surgeries. They
suggest innovative treatment strategies, such as minimally invasive ablations
or stimulations that fully exploit the network and dynamical properties of the
system, or even modulation of variables and parameters to force the system in
safer regions of the bifurcation diagram. We discuss insights from
phenomenological models that can help to foster our understanding of the
mechanisms underlying epileptic seizures.


  Two-qubit operations may be characterized by their capacities for
communication, both with and without free entanglement, and their capacity for
creating entanglement. We establish a set of inequalities that give an ordering
to the capacities of two-qubit unitary operations. Specifically, we show that
the capacities for entanglement creation and bidirectional communication
without entanglement assistance are at least as great as half the bidirectional
communication capacity with entanglement assistance. In addition, we show that
the bidirectional communication that can be performed using an ensemble may be
increased via a two-qubit unitary operation by twice the operation's capacity
for entanglement.


  The rising complexity of cyber threats calls for a comprehensive reassessment
of current security frameworks in business environments. This research focuses
on Stealth Data Exfiltration, a significant cyber threat characterized by
covert infiltration, extended undetectability, and unauthorized dissemination
of confidential data. Our findings reveal that conventional defense-in-depth
strategies often fall short in combating these sophisticated threats,
highlighting the immediate need for a shift in information risk management
across businesses. The evolving nature of cyber threats, driven by advancements
in techniques such as social engineering, multi-vector attacks, and Generative
AI, underscores the need for robust, adaptable, and comprehensive security
strategies. As we navigate this complex landscape, it is crucial to anticipate
potential threats and continually update our defenses. We propose a shift from
traditional perimeter-based, prevention-focused models, which depend on a
static attack surface, to a more dynamic framework that prepares for inevitable
breaches. This suggested model, known as MESA 2.0 Security Model, prioritizes
swift detection, immediate response, and ongoing resilience, thereby enhancing
an organizations ability to promptly identify and neutralize threats,
significantly reducing the consequences of security breaches. This study
suggests that businesses adopt a forward-thinking and adaptable approach to
security management to stay ahead of the ever-changing cyber threat landscape.


  Since the innovation of the ubiquitous Kalman filter more than five decades
back it is well known that to obtain the best possible estimates the tuning of
its statistics $X_0$, $P_0$, $\Theta$, $R$ and $Q$ namely initial state and
covariance, unknown parameters, and the measurement and state noise covariances
is very crucial. The earlier tweaking and other systematic approaches are
reviewed but none has reached a simple and easily implementable approach for
any application. The present reference recursive recipe based on multiple
filter passes through the data leads to a converged `statistical equilibrium'
solution. It utilizes the pre, post, and smoothed state estimates and their
corresponding measurements and the actual measurements as well as their
covariances to balance the state and measurement equations and form generalized
cost functions. The filter covariance at the end of each pass is heuristically
scaled up by the number of data points and further trimmed to provide the $P_0$
for subsequent passes. A simultaneous and proper choice for $Q$ and $R$ based
on the filter sample statistics and certain other covariances leads to a stable
filter operation providing the results after few iterations. When only $R$ is
present in the data by minimizing the `innovation' cost function using the non
filter based Newton Raphson optimization results served as an anchor for
matching and tuning the filter statistics. When both $R$ and $Q$ are present in
the data the consistency between the injected noise sequences and their
statistics provided a simple route and confidence in the present approach. A
typical simulation study of a spring, mass, damper system with a weak non
linear spring constant shows the present approach out performs earlier
techniques. The Part-2 of the paper further consolidates the present approach
based on an analysis of real airplane flight test data.


  We establish large deviations properties valid for almost every sample path
of a class of stationary mixing processes $(X_1,..., X_n,...)$. These
properties are inherited from those of $S_n=\sum_{i=1}^nX_i$ and describe how
the local fluctuations of almost every realization of $S_n$ deviate from the
almost sure behavior. These results apply to the fluctuations of Brownian
motion, Birkhoff averages on hyperbolic dynamics, as well as branching random
walks. Also, they lead to new insights into the "randomness" of the digits of
expansions in integer bases of Pi. We formulate a new conjecture, supported by
numerical experiments, implying the normality of Pi.


  We reanalyze the binary-neutron-star signals, GW170817 and GW190425, focusing
on the inspiral regime to avoid uncertainties on waveform modeling in the
postinspiral regime. We use post-Newtonian waveform models as templates, which
are theoretically rigid and efficiently describe the inspiral regime. We study
potential systematic difference in estimates of the binary tidal deformability
$\tilde{\Lambda}$ by using different descriptions for the point-particle
dynamics and tidal effects. We find that the estimates of $\tilde{\Lambda}$
show no significant systematic difference among three models for the
point-particle parts: TF2, TF2g, and TF2+, when they employ the same tidal
model. We compare different tidal descriptions given by different
post-Newtonian orders in the tidal phase. Our results indicate that the
estimates of $\tilde{\Lambda}$ slightly depend on the post-Newtonian order in
the tidal phase and an increase in the tidal post-Newtonian order does not lead
to a monotonic change in the estimate of $\tilde{\Lambda}$. We also compare the
estimate of $\tilde{\Lambda}$ obtained by the post-Newtonian tidal model and
numerical-relativity calibrated tidal models. We find that the post-Newtonian
model gives slightly larger estimate of $\tilde{\Lambda}$ and wider posterior
distribution than the numerical-relativity calibrated models. According to
Bayesian model comparison, it is difficult to identify a preference among the
post-Newtonian orders by relying on the GW170817 and GW190425 data. Our results
indicate no preference among numerical-relativity calibrated tidal models over
the post-Newtonian model. Additionally, we present constraints on
equation-of-state models for neutron stars with the post-Newtonian model, which
show that the GW170817 data disfavor less compact models, though they are
slightly weaker constraints than the numerical-relativity calibrated tidal
models.


  We have calculated inclusive one-- and two--jet production in photon--photon
collisions in next--to--leading order superimposing direct, single resolved and
double resolved cross sections. The results are compared with recent
experimental data from the TOPAZ and AMY collaborations at TRISTAN. Good
agreement is found between experiment and the theoretical results.


  A search for new physics in proton-proton collisions having final states with
an electron or muon and missing transverse energy is presented. The analysis
uses data collected in 2012 with the CMS detector, at an LHC center-of-mass
energy of 8 TeV, and corresponding to an integrated luminosity of 19.7 inverse
femtobarns. No significant deviation of the transverse mass distribution of the
charged lepton-neutrino system from the standard model prediction is found.
Mass exclusion limits of up to 3.28 TeV at a 95% confidence level for a W'
boson with the same couplings as that of the standard model W boson are
determined. Results are also derived in the framework of split universal extra
dimensions, and exclusion limits on Kaluza-Klein W[KK,2] states are found. The
final state with large missing transverse energy also enables a search for dark
matter production with a recoiling W boson, with limits set on the mass and the
production cross section of potential candidates. Finally, limits are
established for a model including interference between a left-handed W' boson
and the standard model W boson, and for a compositeness model.


  Quantum confined Au nanoclusters exhibit molecule-like properties, including
atomic precision and discrete energy levels. The electrical conductivity of Au
nanocluster films can vary by several orders of magnitude, and is determined by
the strength of the electronic coupling between the individual nanoclusters in
the film. Similar to quantum confined, semiconducting quantum dots, the
electrical coupling in films is dependent on the size and structure of the Au
core and the length and conjugation of the organic ligands surrounding it.
Unlike quantum dots, however, semiconducting transport has not been reported in
Au nanocluster films. We demonstrate that through a simple yet careful choice
of cluster size and organic ligands, stable Au nanocluster films can
electronically couple and become semiconducting, exhibiting electric field
effect and photoconductivity. The molecule-like nature of the Au nanoclusters
is evidenced by a hopping transport mechanism reminiscent of doped, disordered
organic semiconductor films. These results demonstrate the potential of metal
nanoclusters as a solution processed material for semiconducting devices.


  We use discrete analogs of Riemann-Hilbert problem's methods to derive the
discrete Bessel kernel which describes the poissonized Plancherel measures for
symmetric groups. To do this we define discrete analogs of a Riemann-Hilbert
problem and of an integrable integral operator and show that computing the
resolvent of a discrete integrable operator can be reduced to solving a
corresponding discrete Riemann-Hilbert problem.
  We also give an example, explicitly solvable in terms of classical special
functions, when a discrete Riemann-Hilbert problem converges in a certain
scaling limit to a conventional one; the example originates from the
representation theory of the infinite symmetric group.


  Euclidean billiard partitions were recently introduced by Andrews, Dragovic
and Radnovic in their study of periodic trajectories of ellipsoidal billiards
in the Euclidean space. They are integer partitions into distinct parts such
that (E1) adjacent parts are never both odd; (E2) the smallest part is even. By
refining the framework of linked partition ideals, we establish a couple of
relevant trivariate generating function identities, from which the result of
Andrews, Dragovic and Radnovic follows as an immediate consequence.


  Low-cost sensing gloves for reconstruction posture provide measurements which
are limited under several regards. They are generated through an imperfectly
known model, are subject to noise, and may be less than the number of Degrees
of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of
the hand posture is an ill-posed problem, and performance can be very poor.
This paper examines the problem of estimating the posture of a human hand
using(low-cost) sensing gloves, and how to improve their performance by
exploiting the knowledge on how humans most frequently use their hands. To
increase the accuracy of pose reconstruction without modifying the glove
hardware - hence basically at no extra cost - we propose to collect, organize,
and exploit information on the probabilistic distribution of human hand poses
in common tasks. We discuss how a database of such an a priori information can
be built, represented in a hierarchy of correlation patterns or postural
synergies, and fused with glove data in a consistent way, so as to provide a
good hand pose reconstruction in spite of insufficient and inaccurate sensing
data. Simulations and experiments on a low-cost glove are reported which
demonstrate the effectiveness of the proposed techniques.


  We present an argument whose goal is to trace the origin of the
macroscopically irreversible behavior of Hamitonian systems of many degrees of
freedom. We use recent flexibility and rigidity results of symplectic
embeddings, quantified via the (stabilized) Fibonacci and Pell staircases, to
encode the underlying breadth of the possible initial conditions, which
alongside the multitude of degrees of freeedom of the underlying system give
rise to time-irreversibility.


  Class imbalance is an inherent problem in many machine learning
classification tasks. This often leads to trained models that are unusable for
any practical purpose. In this study we explore an unsupervised approach to
address these imbalances by leveraging transfer learning from pre-trained image
classification models to encoder-based Generative Adversarial Network (eGAN).
To the best of our knowledge, this is the first work to tackle this problem
using GAN without needing to augment with synthesized fake images.
  In the proposed approach we use the discriminator network to output a
negative or positive score. We classify as minority, test samples with negative
scores and as majority those with positive scores. Our approach eliminates
epistemic uncertainty in model predictions, as the P(minority) + P(majority)
need not sum up to 1. The impact of transfer learning and combinations of
different pre-trained image classification models at the generator and
discriminator is also explored. Best result of 0.69 F1-score was obtained on
CIFAR-10 classification task with imbalance ratio of 1:2500.
  Our approach also provides a mechanism of thresholding the specificity or
sensitivity of our machine learning system. Keywords: Class imbalance, Transfer
Learning, GAN, nash equilibrium


  Kaleidoscopic groups are a class of permutation groups recently introduced by
Duchesne, Monod, and Wesolek. Starting with a permutation group $\Gamma$, the
kaleidoscopic construction produces another permutation group
$\mathcal{K}(\Gamma)$ which acts on a Wa\.{z}ewski dendrite (a densely
branching tree-like compact space). In this paper, we study how the topological
dynamics of $\mathcal{K}(\Gamma)$ can be expressed in terms of the one of
$\Gamma$, when the group $\Gamma$ is transitive. By proving a Ramsey theorem
for decorated rooted trees, we show that the universal minimal flow (UMF) of
$\mathcal{K}(\Gamma)$ is metrizable iff $\Gamma$ is oligomorphic and the UMF of
$\Gamma$ is metrizable. More generally, we give concrete calculations, in an
appropriate model-theoretic framework, of the UMF of $\mathcal{K}(\Gamma)$ when
the UMF of a point stabilizer $\Gamma_c$ has a comeager orbit. Our results also
give a large class of examples of non-metrizable UMFs with a comeager orbit.
These results extend previous work of Kwiatkowska and Duchesne about the full
homeomorphism groups.


  In the domain of technology startups, biotechnology has often been considered
as specific. Their unique technology content, the type of founders and managers
they have, the amount of venture capital they raise, the time it takes them to
reach an exit as well as the technology clusters they belong to are seen as
such unique features. Based on extensive research from new databases, the
author claims that the biotechnology startups are not as different as it might
have been claimed: the amount of venture capital raised, the time to exit,
their geography are indeed similar and even their equity structure to founders
and managers have similarities. The differences still exist, for example the
experience of the founders, the revenue and profit level at exit.


  Coulomb drag between two unhybridized graphene sheets separated by a
dielectric spacer has recently attracted considerable theoretical interest. We
first review, for the sake of completeness, the main analytical results which
have been obtained by other authors. We then illustrate pedagogically the
minimal theory of Coulomb drag between two spatially-separated two-dimensional
systems of massless Dirac fermions which are both away from the
charge-neutrality point. This relies on second-order perturbation theory in the
screened interlayer interaction and on Boltzmann transport theory. In this
theoretical framework and in the low-temperature limit, we demonstrate that, to
leading (i.e. quadratic) order in temperature, the drag transresistivity is
completely insensitive to the precise intralayer momentum-relaxation mechanism
(i.e. to the functional dependence of the scattering time on energy). We also
provide analytical results for the low-temperature drag transresistivity for
both cases of "thick" and "thin" spacers and for arbitrary values of the
dielectric constants of the media surrounding the two Dirac-fermion layers.
Finally, we present numerical results for the low-temperature drag
transresistivity in the case in which one of the media surrounding the
Dirac-fermion layers has a frequency-dependent dielectric constant. We conclude
by suggesting an experiment that can potentially allow for the observation of
departures from the canonical Fermi-liquid quadratic-in-temperature behavior of
the transresistivity.


  In this paper we study the evolution of the dark energy parameter within the
scope of a spatially homogeneous and isotropic Friedmann-Robertson-Walker (FRW)
model filled with barotropic fluid and dark energy by revisiting the recent
results (Amirhashchi et al. in Chin. Phys. Lett. 28:039801, 2011a). To prevail
the deterministic solution we select the scale factor $a(t) =
\sqrt{t^{n}e^{t}}$ which generates a time-dependent deceleration parameter
(DP), representing a model which generates a transition of the universe from
the early decelerating phase to the recent accelerating phase. We consider the
two cases of an interacting and non-interacting two-fluid (barotropic and dark
energy) scenario and obtained general results. The cosmic jerk parameter in our
derived model is also found to be in good agreement with the recent data of
astrophysical observations under the suitable condition. The physical aspects
of the models and the stability of the corresponding solutions are also
discussed.


  Male reproductive health in both humans and animals is an important research
field in biological study. In order to characterize the morphology, the
motility and the concentration of the sperm cells, which are the most important
parameters to feature them, digital holography demonstrated to be an attractive
technique. Indeed, it is a labelfree, non-invasive and high-resolution method
that enables the characterization of live specimen. The review is intended both
for summarize the state-of-art on the semen analysis and recent achievement
obtained by means of digital holography and for exploring new possible
applications of digital holography in this field.


  We construct the complete effective chiral pion-nucleon Lagrangian in the
presence of virtual photons to one loop. As an application, we consider strong
and electromagnetic isospin violation for scattering of neutral pions off
nucleons. We show that for the scattering lengths these isospin violating terms
are of the same size as the purely hadronic ones. We also analyze
isospin-violating effects for the $\sigma$--term. These can be as large as 10%
for the absolute value but are negligible for the shift to the Cheng-Dashen
point.


  We present a fully relativistic and gauge invariant framework for calculating
the cross sections of dilepton production in nucleon-nucleon (NN) collisions
which is based on the meson-exchange approximation for the NN scattering
amplitudes. Predictions of our model are compared with those of other covariant
models that have been used to describe this reaction. We discuss the comparison
of our calculations with the old DLS and the recent HADES data.


  A problem of Banach asks whether every infinite-dimensional Banach space
which is isomorphic to all its infinite-dimensional subspaces must be
isomorphic to a separable Hilbert space. In this paper we prove a result of a
Ramsey-theoretic nature which implies an interesting dichotomy for subspaces of
Banach spaces. Combined with a result of Komorowski and Tomczak-Jaegermann,
this gives a positive answer to Banach's problem. We then generalize the
Ramsey-theoretic result and deduce a further dichotomy for Banach spaces with
an unconditional basis.


  Determining plateau widths and energy gaps is the remaining task to fully
understand the electron transport that gives the fractional quantum Hall effect
at the lowest Landau level (LLL). We report that this determination is given by
the degree of multi-particle correlations that governs the split distance of
the fine structure of the LLL.We show that an electron flowing through an
incompressible strip formed in a Hall bar behaves as a quasiparticle comprising
the electron and its image, which replaces the confining potential of the
incompressible strip. This quasiparticle is a composite boson of spin unity.
Correlated quasiparticles having higher integral spins are induced by many-body
interactions. The Zeeman effect for these integral spins of the quasiparticles
yields fine splits in the LLL, which is responsible for the plateaus in Hall
resistivity at fractional fillings. With such a scheme, we explicitly reproduce
experimental Hall resistivity and energy gaps.


  The main goal of this work is to prove that every entire curve in a generic
hypersurface of degree greater than or equal to 593 in the complex projective
space of dimension 4 is algebraically degenerated i.e contained in a proper
subvariety.


  Based on the earlier work [S.-S. Lee, Nucl. Phys. B 832, 567 (2010)], we
derive a holographic dual for the D-dimensional U(N) lattice gauge theory from
a first principle construction. The resulting theory is a lattice field theory
of closed loops, dubbed as lattice loop field theory which is defined on a
(D+1)-dimensional space. The lattice loop field theory is well defined
non-perturbatively, and it becomes weakly coupled and local in the large N
limit with a large 't Hooft coupling.


  Recent deep learning models have achieved high performance in speech
enhancement; however, it is still challenging to obtain a fast and
low-complexity model without significant performance degradation. Previous
knowledge distillation studies on speech enhancement could not solve this
problem because their output distillation methods do not fit the speech
enhancement task in some aspects. In this study, we propose multi-view
attention transfer (MV-AT), a feature-based distillation, to obtain efficient
speech enhancement models in the time domain. Based on the multi-view features
extraction model, MV-AT transfers multi-view knowledge of the teacher network
to the student network without additional parameters. The experimental results
show that the proposed method consistently improved the performance of student
models of various sizes on the Valentini and deep noise suppression (DNS)
datasets. MANNER-S-8.1GF with our proposed method, a lightweight model for
efficient deployment, achieved 15.4x and 4.71x fewer parameters and
floating-point operations (FLOPs), respectively, compared to the baseline model
with similar performance.


  Over the last decades, excellent computational chemistry tools have been
developed. Integrating them into a single platform with enhanced accessibility
could help reaching their full potential by overcoming steep learning curves.
Recently, large-language models (LLMs) have shown strong performance in tasks
across domains, but struggle with chemistry-related problems. Moreover, these
models lack access to external knowledge sources, limiting their usefulness in
scientific applications. In this study, we introduce ChemCrow, an LLM chemistry
agent designed to accomplish tasks across organic synthesis, drug discovery,
and materials design. By integrating 18 expert-designed tools, ChemCrow
augments the LLM performance in chemistry, and new capabilities emerge. Our
agent autonomously planned and executed the syntheses of an insect repellent,
three organocatalysts, and guided the discovery of a novel chromophore. Our
evaluation, including both LLM and expert assessments, demonstrates ChemCrow's
effectiveness in automating a diverse set of chemical tasks. Surprisingly, we
find that GPT-4 as an evaluator cannot distinguish between clearly wrong GPT-4
completions and Chemcrow's performance. Our work not only aids expert chemists
and lowers barriers for non-experts, but also fosters scientific advancement by
bridging the gap between experimental and computational chemistry.


  In 2021, Wu et al. presented a multi-party quantum summation scheme
exploiting the entanglement properties of d-dimensional Bell states (Wu et al.
in Quantum Inf Process 20:200, 2021). In particular, the authors proposed a
three-party quantum summation protocol and then extended their work to a
multi-party case. It is claimed that their protocol is secure against outside
and participants' attacks. However, this work points out that Wu's protocol has
a loophole, i.e., two or more dishonest participants who meet a specific
location relationship can conspire to obtain the private inputs of some honest
participants without being detected. Accordingly, improvements are proposed to
address these issues.


  We consider the problem of quantum communication mediated by an optical
refocusing system, which is schematized as a thin lens with a finite pupil.
This model captures the basic features of all those situations in which a
signal is either refocused by a repeater for long distance communication, or it
is focused on a detector prior to the information decoding process. Introducing
a general method for linear optical systems, we compute the communication
capacity of the refocusing apparatus. Although the finite extension of the
pupil may cause loss of information, we show that the presence of the
refocusing system can substantially enhance the rate of reliable communication
with respect to the free-space propagation.


  Named Entity Recognition has been extensively investigated in many fields.
However, the application of sensitive entity detection for production systems
in financial institutions has not been well explored due to the lack of
publicly available, labeled datasets. In this paper, we use internal and
synthetic datasets to evaluate various methods of detecting NPI (Nonpublic
Personally Identifiable) information commonly found within financial
institutions, in both unstructured and structured data formats. Character-level
neural network models including CNN, LSTM, BiLSTM-CRF, and CNN-CRF are
investigated on two prediction tasks: (i) entity detection on multiple data
formats, and (ii) column-wise entity prediction on tabular datasets. We compare
these models with other standard approaches on both real and synthetic data,
with respect to F1-score, precision, recall, and throughput. The real datasets
include internal structured data and public email data with manually tagged
labels. Our experimental results show that the CNN model is simple yet
effective with respect to accuracy and throughput and thus, is the most
suitable candidate model to be deployed in the production environment(s).
Finally, we provide several lessons learned on data limitations, data labelling
and the intrinsic overlap of data entities.


  The realization of quantum gates in topological quantum computation still
confronts significant challenges in both fundamental and practical aspects.
Here, we propose a deterministic and fully topologically protected
measurement-based scheme to realize the issue of implementing Clifford quantum
gates on the Majorana qubits. Our scheme is based on rigorous proof that the
single-qubit gate can be performed by leveraging the neighboring Majorana qubit
but not disturbing its carried quantum information, eliminating the need for
ancillary Majorana zero modes (MZMs) in topological quantum computing.
Benefiting from the ancilla-free construction, we show the minimum measurement
sequences with four steps to achieve two-qubit Clifford gates by constructing
their geometric visualization. To avoid the uncertainty of the measurement-only
strategy, we propose manipulating the MZMs in their parameter space to correct
the undesired measurement outcomes while maintaining complete topological
protection, as demonstrated in a concrete Majorana platform. Our scheme
identifies the minimal operations of measurement-based topological and
deterministic Clifford gates and offers an ancilla-free design of topological
quantum computation.


  We study the rotational and vibrational heating of diatomic molecules placed
near a surface at finite temperature on the basis of macroscopic quantum
electrodynamics. The internal molecular evolution is governed by transition
rates that depend on both temperature and position. Analytical and numerical
methods are used to investigate the heating of several relevant molecules near
various surfaces. We determine the critical distances at which the surface
itself becomes the dominant source of heating and we investigate the transition
between the long-range and short-range behaviour of the heating rates. A simple
formula is presented that can be used to estimate the surface-induced heating
rates of other molecules of interest. We also consider how the heating depends
on the thickness and composition of the surface.


  We present parity measurements on a five-qubit lattice with connectivity
amenable to the surface code quantum error correction architecture. Using
all-microwave controls of superconducting qubits coupled via resonators, we
encode the parities of four data qubit states in either the $X$- or the
$Z$-basis. Given the connectivity of the lattice, we perform full
characterization of the static $Z$-interactions within the set of five qubits,
as well as dynamical $Z$-interactions brought along by single- and two-qubit
microwave drives. The parity measurements are significantly improved by
modifying the microwave two-qubit gates to dynamically remove non-ideal $Z$
errors.


  Hyperfine splitting in Bi$^{82+}$ and Pb$^{81+}$ ions was calculated using
continuum RPA approach with effective residual forces. To fix the parameters of
the theory the nuclear magnetic dipole moments of two one- particle and two
one-hole nuclei around $^{208}$Pb were calculated using the same approach. The
contribution from velocity dependent two-body spin- orbit residual interaction
was calculated explicitly. Additionally, the octupole moment of $^{209}$Bi and
the hfs in muonic bismuth atom were calculated as well in the same approach.
All the calculated observables, except the electronic hfs in $^{209}$Bi, are in
good agreement with the data. We argue for more accurate measurement of the
octupole moment and the muonic hfs for $^{209}$Bi.


  We investigate claims according to which the X-ray selection of AGN is not as
efficient compared to that based on [OIII] selection because of the effects of
X-ray absorption.We construct the predicted X-ray luminosity function both for
all Seyferts as well as separately for Seyfert-1 and Seyfert-2 type galaxies,
by combining the optical AGN [OIII] luminosity functions derived in SDSS with
the corresponding L_X-L_[OIII] relations. These relations are derived from
XMM-Newton observations of all Seyfert galaxies in the Palomar spectroscopic
sample of nearby galaxies after correction for X-ray absorption and optical
reddening. We compare the predicted X-ray luminosity functions with those
actually observed in the local Universe by HEAO-1, RXTE as well as INTEGRAL.
The last luminosity function is derived in the 17-60 keV region and thus is not
affected by absorption even in the case of Compton-thick sources. In the common
luminosity regions, the optically and X-ray selected Seyfert galaxies show
reasonable agreement. We thus find no evidence that the [OIII] selection
provides a more robust tracer of powerful AGN compared to the X-ray. Still, the
optical selection probes less luminous Seyferts compared to the current X-ray
surveys. These low luminosity levels, are populated by a large number of X-ray
unobscured Seyfert-2 galaxies.


  This document describes the communication language used in one multiagent
system environment for ecological simulations, based on EcoDynamo simulator
application linked with several intelligent agents and visualisation
applications, and extends the initial definition of the language. The agents
actions and perceptions are translated into messages exchanged with the
simulator application and other agents. The concepts and definitions used
follow the BNF notation (Backus et al. 1960) and is inspired in the Coach
Unilang language (Reis and Lau 2002).


  We establish connectedness of volume constrained minimisers of energies
involving surface tensions and convex potentials. By a previous result of
McCann, this implies that minimisers are convex in dimension two. This
positively answers an old question of Almgren. We also prove convexity of
minimisers when the volume constraint is dropped. Our proof is based on the
introduction of a new "two-point function" which measures the lack of convexity
and which gives rise to a negative second variation of the energy.


  Let $A$ be an Artin group. A partition $\mathcal{P}$ of the set of standard
generators of $A$ is called admissible if, for all $X,Y \in \mathcal{P}$, $X
\neq Y$, there is at most one pair $(s,t) \in X \times Y$ which has a relation.
An admissible partition $\mathcal{P}$ determines a quotient Coxeter graph
$\Gamma/\mathcal{P}$. We prove that, if $\Gamma/\mathcal{P}$ is either a forest
or an even triangle free Coxeter graph and $A_X$ is residually finite for all
$X \in \mathcal{P}$, then $A$ is residually finite.


  We consider a nonlocal parabolic PDE, which may be regarded as the standard
semilinear heat equation with power nonlinearity, where the nonlinear term is
divided by some Sobolev norm of the solution. In this paper, we are interested
in constructing blowup solutions under some critical regimes. We had a complete
new phenomenon of the blowup speed with a log correction term.


  Multi-Cell (MC) systems are present in mobile network operations from the
first generation to the fifth generation of wireless networks, and considers
the signals of all users to a base station (BS) centered in a cell. Cell-Free
(CF) systems works with a large number of distributed antennas serving users at
the same time. In this context, Multiple-input multiple-output (MIMO)
techniques are used in both topologies and result in performance gains and
interference reduction. In order to achieve the benefits mentioned, proper
precoder design and power allocation techniques are required in the downlink
(DL). In general, DL schemes assume perfect channel state information at the
transmitter (CSIT), which is not realistic. This paper studies MC and CF with
MIMO systems equipped with linear precoders in the DL and proposes an adaptive
algorithm to allocate power in the presence of imperfect CSIT. The proposed
robust adaptive power allocation outperforms standard adaptive and uniform
power allocation. Simulations also compare the performance of both systems
frameworks using minimum mean-square error (MMSE) precoders with robust
adaptive power allocation and adaptive power allocation.


  Approximately 18 percent of the 3.2 million smartphone applications rely on
integrated graphics processing units (GPUs) to achieve competitive performance.
Graphics performance, typically measured in frames per second, is a strong
function of the GPU frequency, which in turn has a significant impact on mobile
processor power consumption. Consequently, dynamic power management algorithms
have to assess the performance sensitivity to the frequency accurately to
choose the operating frequency of the GPU effectively. Since the impact of GPU
frequency on performance varies rapidly over time, there is a need for online
performance models that can adapt to varying workloads. This paper presents a
light-weight adaptive runtime performance model that predicts the frame
processing time of graphics workloads at runtime without apriori
characterization. We employ this model to estimate the frame time sensitivity
to the GPU frequency, i.e., the partial derivative of the frame time with
respect to the GPU frequency. The proposed model does not rely on any parameter
learned offline. Our experiments on commercial platforms with common GPU
benchmarks show that the mean absolute percentage error in frame time and frame
time sensitivity prediction are 4.2 and 6.7 percent, respectively.


  We present the applications of methods from nonlinear local harmonic analysis
in variational framework to calculations of nonlinear motions in
polynomial/rational approximations (up to any order) of arbitrary n-pole
fields. Our approach is based on the methods provided possibility to work with
dynamical beam/particle localization in phase space, which gives representions
via exact nonlinear high-localized eigenmodes expansions and allows to control
contribution to motion from each scale of underlying multiscale structure.


  Even before deep learning architectures became the de facto models for
complex computer vision tasks, the softmax function was, given its elegant
properties, already used to analyze the predictions of feedforward neural
networks. Nowadays, the output of the softmax function is also commonly used to
assess the strength of adversarial examples: malicious data points designed to
fail machine learning models during the testing phase. However, in this paper,
we show that it is possible to generate adversarial examples that take
advantage of some properties of the softmax function, leading to undesired
outcomes when interpreting the strength of the adversarial examples at hand.
Specifically, we argue that the output of the softmax function is a poor
indicator when the strength of an adversarial example is analyzed and that this
indicator can be easily tricked by already existing methods for adversarial
example generation.


  Thermal transport is a crucial probe for studying excitations in insulators.
In Mott insulators, the primary candidates for heat carriers are spins and
phonons, and which dominates the thermal conductivity is a persistent issue.
Typically, phonons dominate the longitudinal thermal conductivity while the
thermal Hall effect (THE) is primarily associated with spins, which requires
time-reversal symmetry breaking. The coupling between phonons and spins usually
depends on spin-orbit interaction and is relatively weak. Here, we propose a
new mechanism for this coupling and the associated THE: the skew scattering of
phonons via spin fluctuations by the scalar spin chirality. This coupling does
not require spin-orbit interaction and is ubiquitous in Mott insulators,
leading to a thermal Hall angle on the order of $10^{-3}$ to $10^{-2}$. Based
on this mechanism, we investigate the THE in YMnO$_3$ with a trimerized
triangular lattice where the THE beyond spins was recognized, and predict the
THE in the Kagome and square lattices.


  The evolution of diffusion models has greatly impacted video generation and
understanding. Particularly, text-to-video diffusion models (VDMs) have
significantly facilitated the customization of input video with target
appearance, motion, etc. Despite these advances, challenges persist in
accurately distilling motion information from video frames. While existing
works leverage the consecutive frame residual as the target motion vector, they
inherently lack global motion context and are vulnerable to frame-wise
distortions. To address this, we present Spectral Motion Alignment (SMA), a
novel framework that refines and aligns motion vectors using Fourier and
wavelet transforms. SMA learns motion patterns by incorporating
frequency-domain regularization, facilitating the learning of whole-frame
global motion dynamics, and mitigating spatial artifacts. Extensive experiments
demonstrate SMA's efficacy in improving motion transfer while maintaining
computational efficiency and compatibility across various video customization
frameworks.


  We extract from the double logarithmic contributions to DGLAP anomalous
dimensions for twist-two operators up to three-loops the magnon dispersion
relation for planar N=4 supersymmetric Yang-Mills. Perturbatively the magnon
dispersion relation agrees with the expansion of the anomalous dimension for
spin-one as well as with the non-collinear double logarithmic contributions to
the BFKL anomalous dimensions analytically extended to negative spin. The
all-loop expression for the magnon dispersion relation is determined by the
double logarithmic resummation of the corresponding Bethe-Salpeter equation. A
potential map relating the spin chain magnon to BFKL eigenfunctions in the
double logarithm approximation is suggested.


  Since the Voyager mission flybys in 1979, we have known the moon Io to be
extremely volcanically active as well as to be the main source of plasma in the
vast magnetosphere of Jupiter. Material lost from Io forms neutral clouds, the
Io plasma torus and ultimately the extended plasma sheet. This material is
supplied from the upper atmosphere and atmospheric loss is likely driven by
plasma-interaction effects with possible contributions from thermal escape and
photochemistry-driven escape. Direct volcanic escape is negligible. The supply
of material to maintain the plasma torus was estimated from various methods at
roughly one ton per second. Most of the time the magnetospheric plasma
environment of Io is stable on timescales from days to months. Similarly, Io's
atmosphere was found to have a stable average density on the dayside, although
it exhibits lateral, diurnal and seasonal variations. There is a potential
positive feedback in the Io torus supply: collisions of torus plasma with
atmospheric neutrals likely are a significant loss process, which increases
with torus density. The stability of the torus environment might be maintained
by limiting mechanisms of either torus supply from Io or the loss from the
torus by centrifugal interchange in the middle magnetosphere. Various
observations suggest that occasionally the plasma torus undergoes major
transient changes over a period of several weeks, apparently overcoming
possible stabilizing mechanisms. Such events (and more frequent minor changes)
are commonly explained by some kind of change in volcanic activity that
triggers a chain of reactions which modify the plasma torus state via a net
increase in supply of new mass. However, it remains unknown what kind of
volcanic event can trigger torus events, whether Io's atmosphere undergoes a
change before or during such magnetospheric events, and what processes could
enable such a change.


  It is shown analytically that the Dirac equation has no normalizable,
time-periodic solutions in a Reissner-Nordstrom black hole background; in
particular, there are no static solutions of the Dirac equation in such a
background field. The physical interpretation is that Dirac particles can
either disappear into the black hole or escape to infinity, but they cannot
stay on a periodic orbit around the black hole.


  Video feeds are often deliberately used as evidence, as in the case of CCTV
footage; but more often than not, the existence of footage of a supposed event
is perceived as proof of fact in the eyes of the public at large. This reliance
represents a societal vulnerability given the existence of easy-to-use editing
tools and means to fabricate entire video feeds using machine learning. And, as
the recent barrage of fake news and fake porn videos have shown, this isn't
merely an academic concern, it is actively been exploited. I posit that this
exploitation is only going to get more insidious. In this position paper, I
introduce a long term project that aims to mitigate some of the most egregious
forms of manipulation by embedding trustworthy components in the video
transmission chain. Unlike earlier works, I am not aiming to do tamper
detection or other forms of forensics -- approaches I think are bound to fail
in the face of the reality of necessary editing and compression -- instead, the
aim here is to provide a way for the video publisher to prove the integrity of
the video feed as well as make explicit any edits they may have performed. To
do this, I present a novel data structure, a video-edit specification language
and supporting infrastructure that provides end-to-end video provenance, from
the camera sensor to the viewer. I have implemented a prototype of this system
and am in talks with journalists and video editors to discuss the best ways
forward with introducing this idea to the mainstream.


  We study the dynamics of the non-classical correlations for few atom systems
in the presence of strong interactions for a number of recently developed
adiabatic state preparation protocols. We show that entanglement can be created
in a controlled fashion and can be attributed to two distinct sources, the
atom-atom interaction and the distribution of atoms among different traps.


  Using a novel observable that relies on the momentum difference of the two
most energetic subjets within a jet $\Delta S_{12}$ we study the internal
structure of high-energy jets simulated by several Monte Carlo event generators
that implement the partonic energy-loss in a dense partonic medium. Based on
inclusive jet and di-jet production we demonstrate that $\Delta S_{12}$ is an
effective tool to discriminate between different models of jet modifications
over a broad kinematic range. The new quantity, while preserving the colinear
and infrared safety of modern jet algorithms, it is experimentally attractive
because of its inherent resiliance against backgrounds of heavy-ion collisions.