  We present an improved method of reconstructing New Physics (NP) masses from
invariant mass endpoints. While the traditional method focuses on a single NP
decay, our method considers the decays of two or more NP particles ($ABC...$)
in a grander decay chain: $ anything \to ABC... \to ... \to jets + leptons$.
Though the center-of-mass energy $E_{CM}$ of `anything' varies unpredictably at
a hadron collider, a sample of many events nonetheless expresses features of
threshold production $E_{CM} = m_A + m_B + ...$: invariant masses constructed
from the final jet and lepton momenta are correlated in a way that makes their
threshold endpoints visually obvious in a scatterplot. We illustrate this
technique for the production of two neutralinos in the MSSM: $anything \to
\widetilde{\chi}_{i}^0 \widetilde{\chi}_{j}^0$ ($i,j=2,3,4$) which subsequently
decay via on- or off-shell sleptons to four leptons. Assuming the relevant SUSY
spectrum is below $1 TeV$ and squarks/gluinos eventually decay to neutralinos,
our MC study shows that one low-luminosity year at the LHC ($10-30 fb^{-1}$)
can quantitatively determine on- versus off-shell decays and find the relevant
neutralino and slepton masses to less than 10 percent.


  Making inferences from data streams is a pervasive problem in many modern
data analysis applications. But it requires to address the problem of
continuous model updating and adapt to changes or drifts in the underlying data
generating distribution. In this paper, we approach these problems from a
Bayesian perspective covering general conjugate exponential models. Our
proposal makes use of non-conjugate hierarchical priors to explicitly model
temporal changes of the model parameters. We also derive a novel variational
inference scheme which overcomes the use of non-conjugate priors while
maintaining the computational efficiency of variational methods over conjugate
models. The approach is validated on three real data sets over three latent
variable models.


  In the frame of the study of a new sample of large angular size radio
galaxies selected from the NRAO VLA Sky Survey, we have made radio observations
of J2114+820, a low power radio galaxy with an angular size of 6'. Its radio
structure basically consists of a prominent core, a jet directed in north-west
direction and two extended S-shaped lobes. We have also observed the optical
counterpart of J2114+820, a bright elliptical galaxy with a strong unresolved
central component. The optical spectrum shows broad emission lines. This fact,
together with its low radio power and FR-I type morphology, renders J2114+820 a
non-trivial object from the point of view of the current unification schemes of
radio loud active galactic nuclei.


  In Physical Human--Robot Interaction (pHRI) grippers, humans and robots may
contribute simultaneously to actions, so it is necessary to determine how to
combine their commands. Control may be swapped from one to the other within
certain limits, or input commands may be combined according to some criteria.
The Assist-As-Needed (AAN) paradigm focuses on this second approach, as the
controller is expected to provide the minimum required assistance to users.
Some AAN systems rely on predicting human intention to adjust actions. However,
if prediction is too hard, reactive AAN systems may weigh input commands into
an emergent one. This paper proposes a novel AAN reactive control system for a
robot gripper where input commands are weighted by their respective local
performances. Thus, rather than minimizing tracking errors or differences to
expected velocities, humans receive more help depending on their needs. The
system has been tested using a gripper attached to a sensitive robot arm, which
provides evaluation parameters. Tests consisted of completing an on-air planar
path with both arms. After the robot gripped a person's forearm, the path and
current position of the robot were displayed on a screen to provide feedback to
the human. The proposed control has been compared to results without assistance
and to impedance control for benchmarking. A statistical analysis of the
results proves that global performance improved and tracking errors decreased
for ten volunteers with the proposed controller. Besides, unlike impedance
control, the proposed one does not significantly affect exerted forces, command
variation, or disagreement, measured as the angular difference between human
and output command. Results support that the proposed control scheme fits the
AAN paradigm, although future work will require further tests for more complex
environments and tasks.


  We propose a data-driven Neural Network (NN) optimization framework to
determine the optimal multi-period dynamic asset allocation strategy for
outperforming a general stochastic target. We formulate the problem as an
optimal stochastic control with an asymmetric, distribution shaping, objective
function. The proposed framework is illustrated with the asset allocation
problem in the accumulation phase of a defined contribution pension plan, with
the goal of achieving a higher terminal wealth than a stochastic benchmark. We
demonstrate that the data-driven approach is capable of learning an adaptive
asset allocation strategy directly from historical market returns, without
assuming any parametric model of the financial market dynamics. Following the
optimal adaptive strategy, investors can make allocation decisions simply
depending on the current state of the portfolio. The optimal adaptive strategy
outperforms the benchmark constant proportion strategy, achieving a higher
terminal wealth with a 90% probability, a 46% higher median terminal wealth,
and a significantly more right-skewed terminal wealth distribution. We further
demonstrate the robustness of the optimal adaptive strategy by testing the
performance of the strategy on bootstrap resampled market data, which has
different distributions compared to the training data.


  We present a strategy designed to separate several possible origins of the
well-known enhancement of the Delta{I}=1/2 amplitude in non-leptonic kaon
decays. In particular, we seek to disentangle the contribution of physics at
the typical QCD scale (soft-gluon exchange) from the effects at the scale of
the charm quark mass. This is achieved by considering QCD with an unphysically
light charm quark, so that the theory possesses an approximate SU(4)_L x
SU(4)_R chiral symmetry. By computing the relevant operator matrix elements and
monitoring their values as the charm quark mass departs from the
SU(4)-symmetric situation, the role of the charm quark can be assessed. We
study the influence of the charm quark mass in Chiral Perturbation Theory.
First results from lattice simulations in the SU(4)-symmetric limit are also
discussed.


  We argue the equivalence between the infrared conformal field theory of the
3d $\mathcal{N}=8$ supersymmetric Yang-Mills theories of ABCD ($U(N), SO(2N+1),
Sp(2N), O(2N)$) gauge groups and the ABJ(M) theories of $U(N)_k\times U(\tilde
N)_{-k}$ for $k=1,2$. We support this duality by comparing the superconformal
index of the IR limit of these super Yang-Mills theories and that of those
ABJ(M) models. Especially we find the match between two indices of (mirror dual
of) the $\mathcal{N}=8$ U(N) SYM and of $U(N)_1\times U(N)_{-1}$ ABJM model.
Also we take large $N$ limit of ABCD super Yang-Mills theories with additional
fundamental hyper-multiplets and infer the large N limit of $\mathcal{N}=8$
ABCD theories themselves, finding the expected gravitational duals. With the
additional input on finite N, we argue the equivalence of Yang-Mills and ABJ(M)
theories for all N. We further explore similar dualities to Chern-Simons matter
theories for $\mathcal{N}=4$ Yang-Mills theories related by mirror symmetry.


  We propose a generalization of Heisenberg picture quantum mechanics in which
a Lagrangian and Hamiltonian dynamics is formulated directly for dynamical
systems on a manifold with non--commuting coordinates, which act as operators
on an underlying Hilbert space. This is accomplished by defining the Lagrangian
and Hamiltonian as the real part of a graded total trace over the underlying
Hilbert space, permitting a consistent definition of the first variational
derivative with respect to a general operator--valued coordinate. The
Hamiltonian form of the equations is expressed in terms of a generalized
bracket operation, which is conjectured to obey a Jacobi identity. The
formalism permits the natural implementation of gauge invariance under
operator--valued gauge transformations. When an operator Hamiltonian exists as
well as a total trace Hamiltonian, as is generally the case in complex quantum
mechanics, one can make an operator gauge transformation from the Heisenberg to
the Schr\"odinger picture. When applied to complex quantum mechanical systems
with one bosonic or fermionic degree of freedom, the formalism gives the usual
operator equations of motion, with the canonical commutation relations emerging
as constraints associated with the operator gauge invariance. More generally,
our methods permit the formulation of quaternionic quantum field theories with
operator--valued gauge invariance, in which we conjecture that the operator
constraints act as a generalization of the usual canonical commutators.


  We reanalyze microlensing events in the published list of anomalous events
that were observed from the OGLE lensing survey conducted during 2004-2008
period. In order to check the existence of possible degenerate solutions and
extract extra information, we conduct analyses based on combined data from
other survey and follow-up observation and consider higher-order effects. Among
the analyzed events, we present analyses of 8 events for which either new
solutions are identified or additional information is obtained. We find that
the previous binary-source interpretations of 5 events are better interpreted
by binary-lens models. These events include OGLE-2006-BLG-238,
OGLE-2007-BLG-159, OGLE-2007-BLG-491, OGLE-2008-BLG-143, and OGLE-2008-BLG-210.
With additional data covering caustic crossings, we detect finite-source
effects for 6 events including OGLE-2006-BLG-215, OGLE-2006-BLG-238,
OGLE-2006-BLG-450, OGLE-2008-BLG-143, OGLE-2008-BLG-210, and OGLE-2008-BLG-513.
Among them, we are able to measure the Einstein radii of 3 events for which
multi-band data are available. These events are OGLE-2006-BLG-238,
OGLE-2008-BLG-210, and OGLE-2008-BLG-513. For OGLE-2008-BLG-143, we detect
higher-order effect induced by the changes of the observer's position caused by
the orbital motion of the Earth around the Sun. In addition, we present
degenerate solutions resulting from the known close/wide or ecliptic
degeneracy. Finally, we note that the masses of the binary companions of the
lenses of OGLE-2006-BLG-450 and OGLE-2008-BLG-210 are in the brown-dwarf
regime.


  We consider the process $K_L \ra \mu^\pm e^\mp \nu \overline{\nu}$ at next to
leading order in chiral perturbation theory. This process occurs in the
standard model at second order in the weak interaction and constitutes a
potential background in searches for new physics through the modes $K_L \ra
\mu^\pm e^\mp$. We find that the same cut, $M_{\mu e}>489$~MeV, used to remove
the sequential decays $K_{l3}\ra \pi_{l2}$ pushes the $B(K_L \ra \mu^\pm e^\mp
\nu \overline{\nu})$ to the $10^{-23}$ level, effectively removing it as a
background.


  We carry out the non-perturbative renormalization of the chromo-magnetic
operator in Heavy Quark Effective Theory. At order 1/m of the expansion, the
operator is responsible for the mass splitting between the pseudoscalar and
vector B mesons. We obtain its two-loop anomalous dimension in a Schr"odinger
functional scheme by successive one-loop conversions to the lattice MS scheme
and the MS-bar scheme. We then compute the scale evolution of the operator
non-perturbatively in the N_f=0 theory between $\mu \approx 0.3$ GeV and $\mu
\approx 100$ GeV, where contact is made with perturbation theory. The overall
renormalization factor that converts the bare lattice operator to its
renormalization group invariant form is given for the Wilson gauge action and
two standard discretizations of the heavy-quark action. As an application, we
find that this factor brings the previous quenched predictions of the B* - B
mass splitting closer to the experimental value than found with a perturbative
renormalization. The same renormalization factor is applicable to the
spin-dependent potentials of Eichten and Feinberg.


  Typically, quantum mechanics is thought of as a linear theory with unitary
evolution governed by the Schr\"odinger equation. While this is technically
true and useful for a physicist, with regards to computation it is an
unfortunately narrow point of view. Just as a classical computer can simulate
highly nonlinear functions of classical states, so too can the more general
quantum computer simulate nonlinear evolutions of quantum states. We detail one
particular simulation of nonlinearity on a quantum computer, showing how the
entire class of $\mathbb{R}$-unitary evolutions (on $n$ qubits) can be
simulated using a unitary, real-amplitude quantum computer (consisting of $n+1$
qubits in total). These operators can be represented as the sum of a linear and
antilinear operator, and add an intriguing new set of nonlinear quantum gates
to the toolbox of the quantum algorithm designer. Furthermore, a subgroup of
these nonlinear evolutions, called the $\mathbb{R}$-Cliffords, can be
efficiently classically simulated, by making use of the fact that Clifford
operators can simulate non-Clifford (in fact, non-linear) operators. This
perspective of using the physical operators that we have to simulate
non-physical ones that we do not is what we call bottom-up simulation, and we
give some examples of its broader implications.


  In the classical statement of the plasma-vacuum interface problem in ideal
magnetohydrodynamics (MHD) one neglects the displacement current in the vacuum
region that gives the div-curl system of pre-Maxwell dynamics for the vacuum
magnetic field. For understanding the influence of the vacuum electric field on
the evolution of a plasma-vacuum interface we do not neglect the displacement
current and consider the full Maxwell equations in vacuum. For the case of an
incompressible plasma flow, by constructing an Hadamard-type ill-posedness
example for the constant coefficients linearized problem we find a necessary
and sufficient condition for the violent instability of a planar plasma-vacuum
interface. In particular, we prove that as soon as the unperturbed plasma and
vacuum magnetic fields are collinear, any nonzero unperturbed vacuum electric
field makes the planar interface violently unstable. This shows the necessity
of the corresponding non-collinearity condition for well-posedness and a
crucial role of the vacuum electric field in the evolution of a plasma-vacuum
interface.


  Purpose: To develop and validate a deep learning model for automatic
segmentation of geographic atrophy (GA) in color fundus images (CFIs) and its
application to study growth rate of GA. Participants: 409 CFIs of 238 eyes with
GA from the Rotterdam Study (RS) and the Blue Mountain Eye Study (BMES) for
model development, and 5,379 CFIs of 625 eyes from the Age-Related Eye Disease
Study (AREDS) for analysis of GA growth rate. Methods: A deep learning model
based on an ensemble of encoder-decoder architectures was implemented and
optimized for the segmentation of GA in CFIs. Four experienced graders
delineated GA in CFIs from RS and BMES. These manual delineations were used to
evaluate the segmentation model using 5-fold cross-validation. The model was
further applied to CFIs from the AREDS to study the growth rate of GA. Linear
regression analysis was used to study associations between structural
biomarkers at baseline and GA growth rate. A general estimate of the
progression of GA area over time was made by combining growth rates of all eyes
with GA from the AREDS set. Results: The model obtained an average Dice
coefficient of 0.72 $\pm$ 0.26 on the BMES and RS. An intraclass correlation
coefficient of 0.83 was reached between the automatically estimated GA area and
the graders' consensus measures. Eight automatically calculated structural
biomarkers (area, filled area, convex area, convex solidity, eccentricity,
roundness, foveal involvement and perimeter) were significantly associated with
growth rate. Combining all growth rates indicated that GA area grows
quadratically up to an area of around 12 mm$^{2}$, after which growth rate
stabilizes or decreases. Conclusion: The presented deep learning model allowed
for fully automatic and robust segmentation of GA in CFIs. These segmentations
can be used to extract structural characteristics of GA that predict its growth
rate.


  We consider the energy and the polar angle distributions of J/\psi's produced
via the color-singlet and the color-octet (^3S_1^{(8)}) mechanisms in Z^0 \to
J/\psi +X at LEP. Since both distributions of the J/\psi produced via
color-octet mechanism are significantly different from those via color-singlet
mechanism, these observables can be used as tests of color-octet production
mechanism for heavy quarkonia. We also discuss Z^0 \rightarrow \Upsilon + X and
W \to J/\psi ( or \Upsilon) + X in brief.


  Silicon photomultipliers (SiPMs) are being considered as potential
replacements for conventional photomultiplier tubes (PMTs). However, a
significant disadvantage of SiPMs is crosstalk (CT), wherein photons propagate
through other pixels, resulting in secondary avalanches. CT can be categorized
into internal crosstalk and external crosstalk based on whether the secondary
avalanche occurs within the same SiPM or a different one. Numerous methods
exist for quantitatively estimating the percentage of internal crosstalk (iCT).
However, external crosstalk (eCT) has not been extensively studied.
  This article presents a novel measurement method for the probability of
emitting an external crosstalk photon during a single pixel avalanche, using a
setup involving two identical SiPMs facing each other, and without the need for
complex optical designs. The entire apparatus is enclosed within a stainless
steel chamber, functioning as a light-tight enclosure, and maintained at liquid
nitrogen temperature. The experimental setup incorporates two Sensl J-60035
SiPM chips along with two 0.5-inch Hamamatsu Photonics (HPK) VUV4 S13370-6050CN
SiPM arrays. The findings show a linear relationship between the probability of
emitting an external crosstalk photon and the SiPM overvoltage for both SiPM
samples. Surprisingly, this novel measurement method also rovides measurements
of the SiPM photon detection efficiency (PDE) for eCT photons at low
temperature.


  Momentum resolved inelastic resonant x-ray scattering is used to map the
evolution of charge excitations over a large range of energies, momenta and
doping levels in the electron doped Mott insulator class
Nd$_{2-x}$Ce$_x$CuO$_4$. As the doping induced AFM-SC
(antiferromagnetic-superconducting) transition is approached, we observe an
anisotropic softening of collective charge modes over a large energy scale
along the Gamma to (\pi,\pi)-direction, whereas the modes exhibit broadening
($\sim$ 1 eV) with relatively little softening along Gamma to (\pi,0) with
respect to the parent Mott insulator (x=0). Our study indicates a systematic
collapse of the gap consistent with the scenario that the system dopes
uniformly with electrons even though the softening of the modes involves an
unusually large energy scale.


  Emerging non-volatile memories (NVMs) represent a disruptive technology that
allows a paradigm shift from the conventional von Neumann architecture towards
more efficient computing-in-memory (CIM) architectures. Several instrumentation
platforms have been proposed to interface NVMs allowing the characterization of
single cells and crossbar structures. However, these platforms suffer from low
flexibility and are not capable of performing CIM operations on NVMs.
Therefore, we recently designed and built the NeuroBreakoutBoard, a highly
versatile instrumentation platform capable of executing CIM on NVMs. We present
our preliminary results demonstrating a relative error < 5% in the range of 1
k$\Omega$ to 1 M$\Omega$ and showcase the switching behavior of a
HfO$_2$/Ti-based memristive cell.


  Vincent van Gogh's painting, The Starry Night, is an iconic piece of art and
cultural history. The painting portrays a night sky full of stars, with eddies
(spirals) both large and small. \cite{Kolmogorov1941}'s description of
subsonic, incompressible turbulence gives a model for turbulence that involves
eddies interacting on many length scales, and so the question has been asked:
is The Starry Night turbulent? To answer this question, we calculate the
azimuthally averaged power spectrum of a square region ($1165 \times 1165$
pixels) of night sky in The Starry Night. We find a power spectrum,
$\mathcal{P}(k)$, where $k$ is the wavevector, that shares the same features as
supersonic turbulence. It has a power-law $\mathcal{P}(k) \propto
k^{-2.1\pm0.3}$ in the scaling range, $34 \leq k \leq 80$. We identify a
driving scale, $k_\text{D} = 3$, dissipation scale, $k_\nu = 220$ and a
bottleneck. This leads us to believe that van Gogh's depiction of the starry
night closely resembles the turbulence found in real molecular clouds, the
birthplace of stars in the Universe.


  What are the limits of the existence of nuclei? What are the highest proton
numbers $Z$ at which the nuclear landscape and periodic table of chemical
elements cease to exist? These deceivably simple questions are difficult to
answer especially in the region of hyperheavy ($Z\geq 126$) nuclei. We present
the covariant density functional study of different aspects of the existence
and stability of hyperheavy nuclei. For the first time, we demonstrate the
existence of three regions of spherical hyperheavy nuclei centered around
($Z\sim 138, N\sim 230$), ($Z\sim 156, N\sim 310$) and ($Z\sim 174, N\sim 410$)
which are expected to be reasonably stable against spontaneous fission. The
triaxiality of the nuclei plays an extremely important role in the reduction of
the stability of hyperheavy nuclei against fission. As a result, the boundaries
of nuclear landscape in hyperheavy nuclei are defined by spontaneous fission
and not by the particle emission as in lower $Z$ nuclei. Moreover, the current
study suggests that only localized islands of stability can exist in hyperheavy
nuclei.


  Cross sections are calculated for single and double photon exchange in
ultraperipheral Pb+Pb collisions at the LHC. The particle production is
simulated with the DPMJET event generator. Large cross sections are found for
particle production around mid-rapidity making these processes an important
background to hadronic nuclear interactions at both the trigger and analysis
levels.


  Reinforcement Learning (RL) models have continually evolved to navigate the
exploration - exploitation trade-off in uncertain Markov Decision Processes
(MDPs). In this study, I leverage the principles of stochastic thermodynamics
and system dynamics to explore reward shaping via diffusion processes. This
provides an elegant framework as a way to think about exploration-exploitation
trade-off. This article sheds light on relationships between information
entropy, stochastic system dynamics, and their influences on entropy
production. This exploration allows us to construct a dual-pronged framework
that can be interpreted as either a maximum entropy program for deriving
efficient policies or a modified cost optimization program accounting for
informational costs and benefits. This work presents a novel perspective on the
physical nature of information and its implications for online learning in
MDPs, consequently providing a better understanding of information-oriented
formulations in RL.


  We show that, to a very good approximation, the ratio of the spin-flip to the
non-flip parts of the elastic proton-nucleus amplitude is the same as for
proton-nucleon scattering at very high energy. The result is used to do a
realistic calculation of the analyzing power A_N for pC scattering in the
Coulomb-nuclear interference (CNI) region of momentum transfer.


  In the past decade, sparse and low-rank recovery have drawn much attention in
many areas such as signal/image processing, statistics, bioinformatics and
machine learning. To achieve sparsity and/or low-rankness inducing, the
$\ell_1$ norm and nuclear norm are of the most popular regularization penalties
due to their convexity. While the $\ell_1$ and nuclear norm are convenient as
the related convex optimization problems are usually tractable, it has been
shown in many applications that a nonconvex penalty can yield significantly
better performance. In recent, nonconvex regularization based sparse and
low-rank recovery is of considerable interest and it in fact is a main driver
of the recent progress in nonconvex and nonsmooth optimization. This paper
gives an overview of this topic in various fields in signal processing,
statistics and machine learning, including compressive sensing (CS), sparse
regression and variable selection, sparse signals separation, sparse principal
component analysis (PCA), large covariance and inverse covariance matrices
estimation, matrix completion, and robust PCA. We present recent developments
of nonconvex regularization based sparse and low-rank recovery in these fields,
addressing the issues of penalty selection, applications and the convergence of
nonconvex algorithms. Code is available at https://github.com/FWen/ncreg.git.


  Understanding the processes that drive the formation of black holes (BHs) is
a key topic in observational cosmology. While the observed
$M_{\mathrm{BH}}$--$M_{\mathrm{Bulge}}$ correlation in bulge-dominated galaxies
is thought to be produced by major mergers, the existence of a
$M_{\mathrm{BH}}$--$M_{\star}$ relation, across all galaxy morphological types,
suggests that BHs may be largely built by secular processes. Recent evidence
that bulge-less galaxies, which are unlikely to have had significant mergers,
are offset from the $M_{\mathrm{BH}}$--$M_{\mathrm{Bulge}}$ relation, but lie
on the $M_{\mathrm{BH}}$--$M_{\star}$ relation, has strengthened this
hypothesis. Nevertheless, the small size and heterogeneity of current datasets,
coupled with the difficulty in measuring precise BH masses, makes it
challenging to address this issue using empirical studies alone. Here, we use
Horizon-AGN, a cosmological hydrodynamical simulation to probe the role of
mergers in BH growth over cosmic time. We show that (1) as suggested by
observations, simulated bulge-less galaxies lie offset from the main
$M_{\mathrm{BH}}$--$M_{\mathrm{Bulge}}$ relation, but on the
$M_{\mathrm{BH}}$--$M_{\star}$ relation, (2) the positions of galaxies on the
$M_{\mathrm{BH}}$--$M_{\star}$ relation are not affected by their merger
histories and (3) only $\sim$35 per cent of the BH mass in today's massive
galaxies is directly attributable to merging -- the majority ($\sim$65 per
cent) of BH growth, therefore, takes place gradually, via secular processes,
over cosmic time.


  Conservation laws and the associated hydrodynamic modes have important
consequences on the growth of higher R\'enyi entropies in isolated quantum
systems. It has been shown in various random unitary circuits and Hamiltonian
systems that the dynamics of the R\'enyi entropies in the presence of a U(1)
symmetry obey $S^{(n\geq 2)}(t) \propto t^{1/z}$, where $z$ is identified as
the dynamical exponent characterizing transport of the conserved charges. Here,
however, we demonstrate that this simple identification may not hold in certain
quantum systems with kinetic constraints. In particular, we study two types of
U(1)-symmetric quantum automaton circuits with XNOR and Fredkin constraints,
respectively. We find numerically that while spin transport in both models is
subdiffusive, the second R\'enyi entropy grows diffusively in the XNOR model,
and superdiffusively in the Fredkin model. For systems with XNOR constraint,
this distinction arises since the spin correlation function can be attributed
to an emergent tracer dynamics of tagged particles, whereas the R\'enyi
entropies are constrained by collective transport of the particles. Our results
suggest that care must be taken when relating transport and entanglement
entropy dynamics in generic quantum systems with conservation laws.


  In this paper we use finite vector spaces (finite dimension, over finite
fields) as a non-standard computational model of linear logic. We first define
a simple, finite PCF-like lambda-calculus with booleans, and then we discuss
two finite models, one based on finite sets and the other on finite vector
spaces. The first model is shown to be fully complete with respect to the
operational semantics of the language. The second model is not complete, but we
develop an algebraic extension of the finite lambda calculus that recovers
completeness. The relationship between the two semantics is described, and
several examples based on Church numerals are presented.


  We suggest that the Majorana neutrino should be regarded as a Bogoliubov
quasiparticle that is consistently understood only by use of a relativistic
analogue of the Bogoliubov transformation. The unitary charge conjugation
condition ${\cal C}\psi{\cal C}^{\dagger}=\psi$ is not maintained in the
definition of a quantum Majorana fermion from a Weyl fermion. This is remedied
by the Bogoliubov transformation accompanying a redefinition of the charge
conjugation properties of vacuum, such that a C-noninvariant fermion number
violating term (condensate) is converted to a Dirac mass. We also comment on
the chiral symmetry of a Majorana fermion; a massless Majorana fermion is
invariant under a global chiral transformation $\psi\rightarrow
\exp[i\alpha\gamma_{5}]\psi$ and different Majorana fermions are distinguished
by different chiral $U(1)$ charge assignments. The reversed process, namely,
the definition of a Weyl fermion from a well-defined massless Majorana fermion
is also briefly discussed.


  This paper investigates dual-layer non-orthogonally superimposed
transmissions for industrial internet of things (IoT) millimeter-wave
communications. Essentially, the overlayer is a ubiquitous multicast signal
devised to serve all the devices in coverage with a common message, i.e.,
critical control packet. The underlayer is a composite signal that consists of
private unicast messages. Due to safety implications, it is critical that all
devices can decode the multicast information. To ensure this requirement, we
jointly optimize the hybrid precoder, analog combiners, power allocation, and
fairness. Specifically, we incorporate a power splitting constraint between the
two overlaid signals and enforce supplementary per-device constraints to
guarantee multicast fairness. Performance is evaluated in terms of the spectral
efficiency, multicast fairness, and bit error rate, thus corroborating the
feasibility of our proposed scheme.


  We study the efficient approximability of basic graph and logic problems in
the literature when instances are specified hierarchically as in \cite{Le89} or
are specified by 1-dimensional finite narrow periodic specifications as in
\cite{Wa93}. We show that, for most of the problems $\Pi$ considered when
specified using {\bf k-level-restricted} hierarchical specifications or
$k$-narrow periodic specifications the following holds:
  \item Let $\rho$ be any performance guarantee of a polynomial time
approximation algorithm for $\Pi$, when instances are specified using standard
specifications. Then $\forall \epsilon > 0$, $ \Pi$ has a polynomial time
approximation algorithm with performance guarantee $(1 + \epsilon) \rho$. \item
$\Pi$ has a polynomial time approximation scheme when restricted to planar
instances. \end{romannum}
  These are the first polynomial time approximation schemes for PSPACE-hard
hierarchically or periodically specified problems. Since several of the
problems considered are PSPACE-hard, our results provide the first examples of
natural PSPACE-hard optimization problems that have polynomial time
approximation schemes. This answers an open question in Condon et. al.
\cite{CF+93}.


  We study the statistical properties of return intervals $r$ between
successive energy dissipation rates above a certain threshold $Q$ in
three-dimensional fully developed turbulence. We find that the distribution
function $P_Q(r)$ scales with the mean return interval $R_Q$ as
$P_Q(r)=R_Q^{-1}f(r/R_Q)$ except for $r=1$, where the scaling function $f(x)$
has two power-law regimes. The return intervals are short-term and long-term
correlated and possess multifractal nature. The Hurst index of the return
intervals decays exponentially against $R_Q$, predicting that rare extreme
events with $R_Q\to\infty$ are also long-term correlated with the Hurst index
$H_\infty=0.639$.


  Following earlier work on electron or hole liquids flowing through assemblies
with magnetic fluctuations, we have recently exposed a marked correlation of
the superconducting temperature Tc, for non s-wave pairing materials, with
coherence length xi and effective mass m*. The very recent study of Abanov et
al. [Europhys. Lett. 54, 488 (2001)] and the prior investigation of Monthoux
and Lonzarich [Phys. Rev. B 59, 14598 (1999)] have each focussed on the concept
of a spin-fluctuation temperature T_sf, which again is intimately related to
Tc. For the d-wave pairing via antiferromagnetic spin fluctuations in the
cuprates, these studies are brought into close contact with our own work, and
the result is that k_B T_sf ~ hbar^2 / m* xi^2. This demonstrates that xi is
also determined by such antiferromagnetic spin-fluctuation mediated pair
interaction. The coherence length in units of the lattice spacing is then
essentially given in the cuprates as the square root of the ratio of two
characteristic energies, namely: the kinetic energy of localization of a charge
carrier of mass m* in a specified magnetic correlation length to the hopping
energy. The quasi-2D ruthenate Sr_2RuO_4, with Tc ~ 1.3 K, has p-wave
spin-triplet pairing and so is also briefly discussed here.


  We present a comprehensive theoretical treatment of SUPCODE, a method for
generating dynamically corrected quantum gate operations, which are immune to
random noise in the environment, by using carefully designed sequences of soft
pulses. SUPCODE enables dynamical error suppression even when the control field
is constrained to be positive and uniaxial, making it particularly suited to
counteracting the effects of noise in systems subject to these constraints such
as singlet-triplet qubits. We describe and explain in detail how to generate
SUPCODE pulse sequences for arbitrary single-qubit gates and provide several
explicit examples of sequences that implement commonly used gates, including
the single-qubit Clifford gates. We develop sequences for noise-resistant
two-qubit gates for two exchanged-coupled singlet-triplet qubits by cascading
robust single-qubit gates, leading to a 35% reduction in gate time compared to
previous works. This cascade approach can be scaled up to produce gates for an
arbitrary-length spin qubit array, and is thus relevant to scalable quantum
computing architectures. To more accurately describe real spin qubit
experiments, we show how to design sequences that incorporate additional
features and practical constraints such as sample-specific charge noise models
and finite pulse rise times. We provide a detailed analysis based on randomized
benchmarking to show how SUPCODE gates perform under realistic $1/f^\alpha$
noise and find a strong dependence of gate fidelity on the exponent $\alpha$,
with best performance for $\alpha>1$. Our SUPCODE sequences can therefore be
used to implement robust universal quantum computation while accommodating the
fundamental constraints and experimental realities of singlet-triplet qubits.


  Large language models (LLMs) exhibit advanced reasoning skills, enabling
robots to comprehend natural language instructions and strategically plan
high-level actions through proper grounding. However, LLM hallucination may
result in robots confidently executing plans that are misaligned with user
goals or, in extreme cases, unsafe. Additionally, inherent ambiguity in natural
language instructions can induce task uncertainty, particularly in situations
where multiple valid options exist. To address this issue, LLMs must identify
such uncertainty and proactively seek clarification. This paper explores the
concept of introspective planning as a systematic method for guiding LLMs in
forming uncertainty--aware plans for robotic task execution without the need
for fine-tuning. We investigate uncertainty quantification in task-level robot
planning and demonstrate that introspection significantly improves both success
rates and safety compared to state-of-the-art LLM-based planning approaches.
Furthermore, we assess the effectiveness of introspective planning in
conjunction with conformal prediction, revealing that this combination yields
tighter confidence bounds, thereby maintaining statistical success guarantees
with fewer superfluous user clarification queries. Code is available at
https://github.com/kevinliang888/IntroPlan.


  In this study, we employ exact quantization rule (EQR) to derive the
analytical approximate l-wave solutions of the Schrodinger equation with the
general molecular oscillator (GMO). The energy eigenvalues equation and the
corresponding wave -functions have been obtained explicitly. Improved
Pekeris-type approximation Schemes have been used to deal with the orbital
centrifugal term. We have deduced expressions for the bound-state energy
eigenvalues of the Morse and shifted Deng-Fan oscillator as special cases of
the GMO, and computed their resulting bound-state energy eigenvalues for H2,
CO, HCl and LiH diatomic molecules. Our results are in good agreement with
other results in the literature.


  LCODE is a freely-distributed quasistatic 2D3V code for simulating plasma
wakefield acceleration, mainly specialized at resource-efficient studies of
long-term propagation of ultrarelativistic particle beams in plasmas. The beam
is modeled with fully relativistic macro-particles in a simulation window
copropagating with the light velocity; the plasma can be simulated with either
kinetic or fluid model. Several techniques are used to obtain exceptional
numerical stability and precision while maintaining high resource efficiency,
enabling LCODE to simulate the evolution of long particle beams over long
propagation distances even on a laptop. A recent upgrade enabled LCODE to
perform the calculations in parallel. A pipeline of several LCODE processes
communicating via MPI (Message-Passing Interface) is capable of executing
multiple consecutive time steps of the simulation in a single pass. This
approach can speed up the calculations by hundreds of times.


  Image degradation due to atmospheric turbulence is common while capturing
images at long ranges. To mitigate the degradation due to turbulence which
includes deformation and blur, we propose a generative single frame restoration
algorithm which disentangles the blur and deformation due to turbulence and
reconstructs a restored image. The disentanglement is achieved by decomposing
the distortion due to turbulence into blur and deformation components using
deblur generator and deformation correction generator respectively. Two paths
of restoration are implemented to regularize the disentanglement and generate
two restored images from one degraded image. A fusion function combines the
features of the restored images to reconstruct a sharp image with rich details.
Adversarial and perceptual losses are added to reconstruct a sharp image and
suppress the artifacts respectively. Extensive experiments demonstrate the
effectiveness of the proposed restoration algorithm, which achieves
satisfactory performance in face restoration and face recognition.


  Counterexamples to the 2-jet determination Chern-Moser Theorem in codimension
d>2 have recently been constructed. We extend the Chern-Moser approach for
hypersurfaces to real submanifolds of higher codimension in complex space to
derive results on jet determination for their automorphism group. Using these
techniques, we show that the 2-jet determination Chern-Moser Theorem holds in
codimension 2.


  We develop a theory that describes the response of non-reciprocal devices
employing 2-dimensional materials in the quantum Hall regime capacitively
coupled to external electrodes. As the conduction in these devices is
understood to be associated to the edge magnetoplasmons (EMPs), we first
investigate the EMP problem by using the linear response theory in the random
phase approximation. Our model can incorporate several cases, that were often
treated on different grounds in literature. In particular, we analyze plasmonic
excitations supported by smooth and sharp confining potential in 2-dimensional
electron gas, and in monolayer graphene, and we point out the similarities and
differences in these materials. We also account for a general time-dependent
external drive applied to the system. Finally, we describe the behavior of a
non-reciprocal quantum Hall device: the response contains additional resonant
features, which were not foreseen from previous models.


  In an effort to achieve our aims (getting larger quantum system) in the
recent reformulation of quantum mechanics without potential function [1-5], we
obtained a new quantum system associated with Meixner Pollaczek Orthogonal
polynomial class (hereby called Meixner - Pollaczek Quantum system). The energy
spectrum and wave function of the quantum system were given. To the best of our
knowledge, this quantum system is not found in physics literatures.


  Some families of graphs, such as the n-cubes and Sierpinski gaskets, are
self-similar. In this paper we show how such recursive structure can be used
systematically to prove isoperimetric theorems.


  In what follows, we are interested in an extension of a theorem of Nicholas
Katz, which will be useful in studying the cohomology of generalized arc spaces
develop by Hans Schoutens. As is well known, one is typically interested in the
motivic volume of a definable subset of $\mathcal{X} \times X \times
\mathbb{Z}^n$ where $\mathcal{X}$ is a scheme over $k((t))$ and $X$ the special
fiber of $\mathcal{X}$ . Schoutens has introduced the possibility of developing
a motivic integration for limit points other than $k[[t]]$.


  We present the first measurement of the muon neutrino spectrum at the T2K
near detector, ND280, using the data collected at the JPARC acc\ elerator
facility in Tokai, Japan. ND280 is located 280 meters downstream from the
target and 2.5$^\circ$ off-axis from the direction of the beam. The measured
spectrum at ND280 constrains the flux and cross section uncertainties\ in the
T2K oscillation analysis. We select inclusive charged-current (CC) events from
muon \ neutrinos in ND280. These are separated into a charged current
quasi-elastic (CCQE) enhanced sample and a CC non\ -QE sample. We then fit the
muon spectrum for both samples to extract flux and cross section parameters,
which are used as inputs into T2K's os\ cillation analysis. We separately
produce a flux-averaged differential inclusive CC cross-se\ ction in the
2-dimensional plane of muon momentum and angle. For the cross-section
measurement the flux is given by the MC and tuned to data from the NA61
experiment. We present the event selection, detector uncertainties, and final
measurement result for both the spectrum and for the cross-section.


  We present a detailed calculation of intensities of two-phonon and
four-phonon Raman peaks in graphene. Writing the low-energy hamiltonian of the
interaction of electrons with the crystal vibrations and the electromagnetic
field from pure symmetry considerations, we describe the system in terms of
just a few independent coupling constants, considered to be parameters of the
theory. The electron scattering rate is introduced phenomenologically as
another parameter. The results of the calculation are used to extract
information about these parameters from the experimentally measured Raman peak
intensities.


  We use elastic and inelastic neutron scattering (INS) to study the
antiferromagnetic (AF) phase transitions and spin excitations in the
two-dimensional (2D) zig-zag antiferromagnet FePSe$_3$. By determining the
magnetic order parameter across the AF phase transition, we conclude that the
AF phase transition in FePSe$_3$ is first-order in nature. In addition, our INS
measurements reveal that the spin waves in the AF ordered state have a large
easy-axis magnetic anisotropy gap, consistent with an Ising Hamiltonian, and
possible biquadratic magnetic exchange interactions. On warming across $T_N$,
we find that dispersive spin excitations associated with three-fold rotational
symmetric AF fluctuations change into FM spin fluctuations above $T_N$. These
results suggest that the first-order AF phase transition in FePSe$_3$ may arise
from the competition between $C_3$ symmetric AF and $C_1$ symmetric FM spin
fluctuations around $T_N$, in place of a conventional second-order AF phase
transition.


  We consider the optimal stopping of a class of spectrally negative jump
diffusions. We state a set of conditions under which the value is shown to have
a representation in terms of an ordinary nonlinear programming problem. We
establish a connection between the considered problem and a stopping problem of
an associated continuous diffusion process and demonstrate how this connection
may be applied for characterizing the stopping policy and its value. We also
establish a set of typically satisfied conditions under which increased
volatility as well as higher jump-intensity decelerates rational exercise by
increasing the value and expanding the continuation region.


  We introduce a Newtonian model for the deformations of a compressible,
autogravitating, and continuously stratified neutron star. The present
framework can be applied to a number of astrophysical scenarios as it allows us
to account for a great variety of loading forces. In this first analysis, the
model is used to study the impact of a frozen adiabatic index in the estimate
of rotation-induced deformations: we assume a polytropic equation of state for
the matter at equilibrium but, since chemical reactions may be slow, the
perturbations with respect to the unstressed configuration are modelled by
using a different adiabatic index. We quantify the impact of a departure of the
adiabatic index from its equilibrium value on the stressed stellar
configuration and we find that a small perturbation can cause large variations
both in displacements and strains. As a first practical application, we
estimate the strain developed between two large glitches in the Vela pulsar
showing that, starting from an initial unstressed configuration, it is not
possible to reach the breaking threshold of the crust, namely to trigger a
starquake. In this sense, the hypothesis that starquakes could trigger the
unpinning of superfluid vortices is challenged and, for the quake to be a
possible trigger, the solid crust must never fully relax after a glitch, making
the sequence of starquakes in a neutron star an history-dependent process.


  Advanced feedforward control methods enable mechatronic systems to perform
varying motion tasks with extreme accuracy and throughput. The aim of this
paper is to develop a data-driven feedforward controller that addresses input
nonlinearities, which are common in typical applications such as semiconductor
back-end equipment. The developed method consists of parametric inverse-model
feedforward that is optimized for tracking error reduction by exploiting ideas
from iterative learning control. Results on a simulated set-up indicate
improved performance over existing identification methods for systems with
nonlinearities at the input.


  We argue that key characteristics of the enigmatic transition at $T_0= 17.5K
$ in $URu_2Si_2$ indicate that the hidden order is a density wave formed within
a band of composite quasiparticles, whose detailed structure is determined by
local physics. We expand on our proposal (with J.A. Mydosh) of the hidden order
as incommnesurate orbital antiferromagnetism and present experimental
predictions to test our ideas. We then turn towards a microscopic description
of orbital antiferromagnetism, exploring possible particle-hole pairings within
the context of a simple one-band model. We end with a discussion of recent
high-field and thermal transport experiment, and discuss their implications for
the nature of the hidden order.


  Our ab initio all-electron relativistic Dirac*Fock (DF) calculations for the
octahedral (Oh) Ubq(CO)6 and Ubq(OC)6 predict atomization energies (Ae) of
50.25 (47.93) and 43.43 (44.88 ) eV, respectively where the corresponding
non-relativistic calculated Ae's are given in parenthesis. Our calculated DF
and NR isomerization energies (E iso) for Ubq (CO) 6 = Ubq (OC) 6 are 6.83 and
3.05 eV, respectively. Our calculated DF (NR) energy for the reaction Ubq + 6CO
= Ubq (CO)6 is -4.31 (-4.30) eV, while the energy of the isomeric reaction Ubq
+ 6CO = Ubq(OC)6 is 2.52 ( -1.25 ) eV, respectively. The relativistic effects
increase the Eiso of Ubq (CO)6 by ~3.78 eV , decrease the Ubq-C bond distance
by 0.12 angstroms and have a negligible effect on the C-O bond distance as
expected. These are the first results of relativistic effects for isomerztion
energy and atomization energy of the superheavy Ubq (CO)6 and Ubq(OC)6. The
bond distances Ubq-C and Ubq-O optimized at the DF level of theory for Ubq(CO)6
and Ubq(OC)6 are 2.572 and 2.559 angstroms, while the corresponding optimized
bond distances Ubq-C and Ubq-O at the NR level of theory are 2.691 and 3.616
angstroms, respectively. Both our DF and NR calculations clearly predict the
formation of both the isomers Ubq(CO)6 and Ubq(OC), and the former is predicted
to be more stable at the DF level of theory by ~7 eV than the latter.No such
calculations have been reported before for systems of such superheavy elements.


  The present study explores the intricacies of causal relationship extraction,
a vital component in the pursuit of causality knowledge. Causality is
frequently intertwined with temporal elements, as the progression from cause to
effect is not instantaneous but rather ensconced in a temporal dimension. Thus,
the extraction of temporal causality holds paramount significance in the field.
In light of this, we propose a method for extracting causality from the text
that integrates both temporal and causal relations, with a particular focus on
the time aspect. To this end, we first compile a dataset that encompasses
temporal relationships. Subsequently, we present a novel model, TC-GAT, which
employs a graph attention mechanism to assign weights to the temporal
relationships and leverages a causal knowledge graph to determine the adjacency
matrix. Additionally, we implement an equilibrium mechanism to regulate the
interplay between temporal and causal relations. Our experiments demonstrate
that our proposed method significantly surpasses baseline models in the task of
causality extraction.


  This paper concerns the study of a broad class of minimal time functions
corresponding to control problems with constant convex dynamics and closed
target sets in arbitrary Banach spaces. In contrast to other publications, we
do not impose any nonempty interior and/or calmness assumptions on the initial
data and deal with generally non-Lipschitzian minimal time functions. The major
results present refined formulas for computing various subgradients of minimal
time functions under minimal requirements in both cases of convex and nonconvex
targets. Our technique is based on advanced tools of variational analysis and
generalized differentiation.


  Positrons beam dump experiments have unique features to search for very
narrow resonances coupled superweakly to $e^+ e^-$ pairs. Due to the continue
loss of energy from soft photon bremsstrahlung, in the first few radiation
lengths of the dump a positron beam can continuously scan for resonant
production of new resonances via $e^+$ annihilation off an atomic $e^-$ in the
target. In the case of a dark photon $A'$ kinetically mixed with the photon,
this production mode is of first order in the electromagnetic coupling
$\alpha$, and thus parametrically enhanced with respect to the $O(\alpha^2)$
$e^+e^- \to \gamma A'$ production mode and to the $O(\alpha^3)$ $A'$
bremsstrahlung in $e^--$nucleon scattering so far considered. If the lifetime
is sufficiently long to allow the $A'$ to exit the dump, $A' \to e^+e^-$ decays
could be easily detected and distinguished from backgrounds. We explore the
foreseeable sensitivity of the Frascati PADME experiment in searching with this
technique for the $17\,$MeV dark photon invoked to explain the $^8$Be anomaly
in nuclear transitions.


  The security of multivariate cryptosystems and digital signature schemes
relies on the hardness of solving a system of polynomial equations over a
finite field. Polynomial system solving is also currently a bottleneck of
index-calculus algorithms to solve the elliptic and hyperelliptic curve
discrete logarithm problem. The complexity of solving a system of polynomial
equations is closely related to the cost of computing Groebner bases, since
computing the solutions of a polynomial system can be reduced to finding a
lexicographic Groebner basis for the ideal generated by the equations. Several
algorithms for computing such bases exist: We consider those based on repeated
Gaussian elimination of Macaulay matrices. In this paper, we analyze the case
of random systems, where random systems means either semi-regular systems, or
quadratic systems in n variables which contain a regular sequence of n
polynomials. We provide explicit formulae for bounds on the solving degree of
semi-regular systems with m > n equations in n variables, for equations of
arbitrary degrees for m = n+1, and for any m for systems of quadratic or cubic
polynomials. In the appendix, we provide a table of bounds for the solving
degree of semi-regular systems of m = n + k quadratic equations in n variables
for 2 <= k; n <= 100 and online we provide the values of the bounds for 2 <= k;
n <= 500. For quadratic systems which contain a regular sequence of n
polynomials, we argue that the Eisenbud-Green-Harris Conjecture, if true,
provides a sharp bound for their solving degree, which we compute explicitly.


  A gauge-averaging functional of the axial type is studied for simple
supergravity at one loop about flat Euclidean four-space bounded by a
three-sphere, or two concentric three-spheres. This is a generalization of
recent work on the axial gauge in quantum supergravity on manifolds with
boundary. Ghost modes obey nonlocal boundary conditions of the spectral type,
in that half of them obey Dirichlet or Neumann conditions at the boundary. In
both cases, they give a vanishing contribution to the one-loop divergence. The
admissibility of noncovariant gauges at the classical level is also proved.


  We study the geometry of the Hbeta broad emission region by comparing the
M_BH values derived from Hbeta through the virial relation with those obtained
from the host galaxy luminosity in a sample of 36 low redshift (z around 0.3)
quasars. This comparison lets us infer the geometrical factor f needed to
de-project the line-of-sight velocity component of the emitting gas. The wide
range of f values we found, together with the strong dependence of f on the
observed line width, suggests that a disc-like model for the broad line region
is preferable to an isotropic model, both for radio loud and radio quiet
quasars. We examined similar observations of the CIV line and found no
correlation in the width of the two lines. Our results indicate that an
inflated disc broad line region, in which the Carbon line is emitted in a flat
disc while Hbeta is produced in a geometrically thick region, can account for
the observed differences in the width and shape of the two emission lines.


  We construct several types of multi-valued solutions to the Monge-Ampere
equation in higher dimensions.


  In this paper, we introduce a new way of constructing and decoding
multipermutation codes. Multipermutations are permutations of a multiset that
may consist of duplicate entries. We first introduce a new class of matrices
called multipermutation matrices. We characterize the convex hull of
multipermutation matrices. Based on this characterization, we propose a new
class of codes that we term LP-decodable multipermutation codes. Then, we
derive two LP decoding algorithms. We first formulate an LP decoding problem
for memoryless channels. We then derive an LP algorithm that minimizes the
Chebyshev distance. Finally, we show a numerical example of our algorithm.


  Examining the physical properties of materials - particularly of toxic
liquids - under a wide range of thermodynamic states is a challenging problem
due to the extreme conditions the material has to be exposed to. Such
temperature and pressure regimes, which result in a change of refractive index
and sound velocity can be accessed by optoacoustic interactions such as
Brillouin-Mandelstam scattering. Here we experimentally demonstrate
Brillouin-Mandelstam measurements of nanoliter volumes of liquids in extreme
thermodynamic regimes. We use a fully-sealed liquid-core optical fiber
containing carbon disulfide; within this waveguide, which exhibits tight
optoacoustic confinement and a high Brillouin gain of (32.2 $\pm$ 0.8) 1/(Wm),
we are able to conduct spatially resolved measurements of the Brillouin
frequency shift. Knowledge of the local Brillouin response enables us to
control the temperature and pressure independently over a wide range. We
observe and measure the material properties of the liquid core at very large
positive pressures (above 1000 bar), substantial negative pressures (below -300
bar) and we explore the isobaric and isochoric regimes. The extensive
thermodynamic control allows the tunability of the Brillouin frequency shift of
more than 40% using only minute volumes of liquid. This work opens the way for
future studies of liquids under a variety of conventionally hard-to-reach
conditions.


  The topology of an instant messaging system is described. Statistical
measures of the network are given and compared with the statistics of a
comparable random graph. The scale-free character of the network is examined
and implications are given for the structure of social networks and instant
messenger security.


  We construct a symmetric spectrum representing the G-equivariant K-theory of
C*-algebras for a compact group or a proper groupoid G. Our spectrum is
functorial for equivariant *-homomorphisms. We use this to establish the
additivity of the canonical traces for endomorphisms of strongly dualisable
objects in the bootstrap class in equivariant KK, in analogy to previous
results for traces in stable homotopy theory. As an application, we prove an
equivariant analogue of the Lefschetz trace formula for Hodgkin Lie groups.


  We have investigated the Josephson coupling between two s-wave
superconductors separated by the ferromagnetic trilayers with noncollinear
magnetization. We find that the long-range triplet critical current will
oscillate with the strength of the exchange field and the thickness of the
interface layer, when the interface magnetizations are orthogonal to the
central magnetization. This feature is induced by the spatial oscillations of
the spin-triplet state |\uparrow\downarrow>+|\downarrow\uparrow> in the
interface layer. Moreover, the critical current can exhibit a characteristic
nonmonotonic behavior, when the misalignment angle between interface
magnetization and central ferromagnet increases from 0 to \pi/2. This peculiar
behavior will take place under the condition that the original state of the
junction with the parallel magnetizations is the \pi state.


  The structural asymmetry of two-dimensional (2D) Janus transition metal
dichalcogenides (TMDs) produces internal dipole moments that result in
interesting electronic properties. These properties differ from the regular
(symmetric) TMD structures that the Janus structures are derived from. In this
study, we, at first, examine adsorption and diffusion of a single Li atom on
regular MX2and Janus MXY (M = Mo, W; XY =S, Se, Te) TMD structures at various
concentrations using first principles calculations within density functional
theory. To gain more physical insight and prepare for future investigations of
regular TMD and Janus materials, we applied a supervised machine learning (ML)
model that uses cluster-wise linear regression to predict the adsorption
energies of Li on top of 2D TMDs. We developed a universal representation with
few descriptors that take into account the intrinsic dipole moment and the
electronic structure of regular and Janus 2D layers, the side where the
adsorption takes place and the concentration dependence of adatom doping. This
representation can easily be generalized to be used for other impurities and 2D
layer combinations, including alloys as well. At last, we focus on analyzing
these structures as possible anodes in battery applications. We conducted Li
diffusion, open-circuit-voltage and storage capacity simulations. We report
that Lithium atoms are found to easily migrate between transition metal (Mo, W)
top sites for each considered case, and in these respects many of the examined
Janus materials are comparable or superior to graphene and to regular TMDs. The
results imply that theexamined Janus structures should perform well as
electrodes in Li-ion batteries.


  Models of coevolution have recently been studied, in which a species is
defined by a genome in the form of a bitstring, and the interactions between
species i and j are given by a fixed matrix with independent, randomly
distributed elements M_{ij}. A consequence of the stochastic independence is
that species whose genotypes differ even by a single bit may have completely
different phenotypes. This is clearly unrealistic, as closely related species
should be similar in their interactions with the rest of the ecosystem. Here we
therefore study a model, in which the M_{ij} are correlated to a controllable
degree. We calculate, both analytically and numerically, the correlation
function for matrix elements M_{ij} and M_{kl} versus the Hamming distance
between the bitstrings representing the species. We compare Monte Carlo
simulations of coevolution models with uncorrelated and correlated
interactions. In particular, we consider the lifetimes of individual species.
The species-lifetime distribution is close to a power law with an exponent near
-2 in both uncorrelated and correlated cases. The durations of quasi-steady
states and power spectral densities for the diversity indices display
noticeable differences. However, some qualitative features, like 1/f behaviour
in power spectral densities for the diversity indices, are not affected by the
correlations in the interaction matrix.


  The paper contains theorems on extending sections of line bundles from
divisors to the ambient space, inspired by various results of Siu, Kawamata,
and especially Hacon-McKernan and Takayama. Applications are given to
basepoint-freeness, to the invariance of analogues of plurigenera and of part
of the boundary of the pseudo-effective cone in families, and to a simplified
approach towards part of the results used for proving the existence of flips by
Hacon-McKernan.


  In this note we give equivalent characterizations for a fractional
Triebel-Lizorkin space $F^s_{p,q}(\Omega)$ in terms of first-order differences
in a uniform domain $\Omega$. The characterization is valid for any positive,
non-integer real smoothness $s\in \mathbb{R}_+\setminus \mathbb{N}$ and
{indices $1\leq p<\infty$, $1\leq q \leq \infty$} as long as the fractional
part $\{s\}$ is greater than $d/p-d/q$.


  Performing fully general relativistic simulations taking account of
microphysical processes is one of long standing problems in numerical
relativity. One of main difficulties in implementation of weak interactions in
the general relativistic framework lies on the fact that the characteristic
timescale of weak interaction processes (the WP timescale) in hot dense matters
is much shorter than the dynamical timescale. Numerically this means that stiff
source terms appears in the equations so that an implicit scheme is in general
necessary to stably solve the relevant equations. Otherwise a very short
timestep will be required to solve them explicitly. Furthermore, in the
relativistic framework, the Lorentz factor is coupled with the rest mass
density and the energy density. The specific enthalpy is also coupled with the
momentum. Due to these couplings, it is very complicated to recover the
primitive variables and the Lorentz factor from conserved quantities. At the
current status, no implicit procedure have been proposed except for the case of
the spherical symmetry. Therefore, an approximate, explicit procedure is
developed in the fully general relativistic framework in this paper as an first
implementation of the microphysics toward a more realistic sophisticated model.
The procedure is based on the so-called neutrino leakage schemes which is based
on the property that the characteristic timescale in which neutrinos leak out
of the system (the leakage timescale) is much longer than the WP timescale. In
this paper, I present a detailed neutrino leakage scheme and a simple and
stable method for solving the equations explicitly in the fully general
relativistic framework. I also perform a test simulation to check the validity
of the present method, showing that it works fairly well.


  Collaborative training of neural networks leverages distributed data by
exchanging gradient information between different clients. Although training
data entirely resides with the clients, recent work shows that training data
can be reconstructed from such exchanged gradient information. To enhance
privacy, gradient perturbation techniques have been proposed. However, they
come at the cost of reduced model performance, increased convergence time, or
increased data demand. In this paper, we introduce PRECODE, a PRivacy EnhanCing
mODulE that can be used as generic extension for arbitrary model architectures.
We propose a simple yet effective realization of PRECODE using variational
modeling. The stochastic sampling induced by variational modeling effectively
prevents privacy leakage from gradients and in turn preserves privacy of data
owners. We evaluate PRECODE using state of the art gradient inversion attacks
on two different model architectures trained on three datasets. In contrast to
commonly used defense mechanisms, we find that our proposed modification
consistently reduces the attack success rate to 0% while having almost no
negative impact on model training and final performance. As a result, PRECODE
reveals a promising path towards privacy enhancing model extensions.


  In a granular gas, inelastic collisions produce an instability in which the
constituent particles cluster heterogeneously. These clusters then interact
with each other, further decreasing their kinetic energy. We report experiments
of the free collisions of dense clusters of particles in a two-dimensional
geometry. The particles are composed of solid CO$_{2}$, which float nearly
frictionlessly on a hot surface due to sublimated vapor. After two dense
clusters of $\approx$ 100 particles collide, there are two distinct stages of
evolution. First, the translational kinetic energy rapidly decreases by over
90% as a "jamming front" sweeps across each cluster. Subsequently, the kinetic
energy decreases more slowly as the particles approach the container
boundaries. In this regime, the measured velocity distributions are
non-Gaussian with long tails. Finally, we compare our experiments to computer
simulations of colliding, two-dimensional, granular clusters composed of
circular, viscoelastic particles with friction.


  Robots operating in real world settings must navigate and maintain safety
while interacting with many heterogeneous agents and obstacles. Multi-Agent
Control Barrier Functions (CBF) have emerged as a computationally efficient
tool to guarantee safety in multi-agent environments, but they assume perfect
knowledge of both the robot dynamics and other agents' dynamics. While
knowledge of the robot's dynamics might be reasonably well known, the
heterogeneity of agents in real-world environments means there will always be
considerable uncertainty in our prediction of other agents' dynamics. This work
aims to learn high-confidence bounds for these dynamic uncertainties using
Matrix-Variate Gaussian Process models, and incorporates them into a robust
multi-agent CBF framework. We transform the resulting min-max robust CBF into a
quadratic program, which can be efficiently solved in real time. We verify via
simulation results that the nominal multi-agent CBF is often violated during
agent interactions, whereas our robust formulation maintains safety with a much
higher probability and adapts to learned uncertainties


  We study a generalization of the recently introduced order-preserving pattern
matching, where instead of looking for an exact copy of the pattern, we only
require that the relative order between the elements is the same. In our
variant, we additionally allow up to k mismatches between the pattern and the
text, and the goal is to construct an efficient algorithm for small values of
k. For a pattern of length m and a text of length n, our algorithm detects an
order-preserving occurrence with up to k mismatches in O(n(loglogm + kloglogk))
time.


  The topography and the electrical properties are two crucial characteristics
in determining roles and functionalities of materials. Conductive atomic force
microscopy (CAFM) is widely recognized for its ability to independently measure
the topology and conductivity. The increasing trend towards miniaturization in
electrical devices and sensors has encouraged an urgent demand for enhancing
the accuracy of CAFM characterization. However, the possibility of topography
interference with the measured current during CAFM scanning leads to an
inaccurate estimation of the sample's conductivity. Herein, we investigated the
topography-dependent current originating from variation in capacitance between
the probe and sample during CAFM testing. Based on the linear dependence
between the current and the first derivative of height derived from topographic
mapping, the calibration method has been proposed to eliminate the current
error that is attributed to the variation in height on sample surfaces. This
method is evaluated on one-dimensional ZnO nanowire, two-dimensional (2D) NbOI2
flake, and biological lotus leaf, further demonstrating the feasibility and
university of this method. This work effectively addresses the challenge of
topographic crosstalk in CAFM characterization, which provides significant
benefits for research on demanding high-accuracy CAFM measurements.


  In recent years, Discriminative Correlation Filter (DCF) based tracking
methods have achieved great success in visual tracking. However, the
multi-resolution convolutional feature maps trained from other tasks like image
classification, cannot be naturally used in the conventional DCF formulation.
Furthermore, these high-dimensional feature maps significantly increase the
tracking complexity and thus limit the tracking speed. In this paper, we
present a deep and shallow feature learning network, namely DSNet, to learn the
multi-level same-resolution compressed (MSC) features for efficient online
tracking, in an end-to-end offline manner. Specifically, the proposed DSNet
compresses multi-level convolutional features to uniform spatial resolution
features. The learned MSC features effectively encode both appearance and
semantic information of objects in the same-resolution feature maps, thus
enabling an elegant combination of the MSC features with any DCF-based methods.
Additionally, a channel reliability measurement (CRM) method is presented to
further refine the learned MSC features. We demonstrate the effectiveness of
the MSC features learned from the proposed DSNet on two DCF tracking
frameworks: the basic DCF framework and the continuous convolution operator
framework. Extensive experiments show that the learned MSC features have the
appealing advantage of allowing the equipped DCF-based tracking methods to
perform favorably against the state-of-the-art methods while running at high
frame rates.


  We describe a quantum state tomography scheme which is applicable to a system
described in a Hilbert space of arbitrary finite dimensionality and is
constructed from sequences of two measurements. The scheme consists of
measuring the various pairs of projectors onto two bases --which have no
mutually orthogonal vectors--, the two members of each pair being measured in
succession. We show that this scheme implies measuring the joint
quasi-probability of any pair of non-degenerate observables having the two
bases as their respective eigenbases. The model Hamiltonian underlying the
scheme makes use of two meters initially prepared in an arbitrary given quantum
state, following the ideas that were introduced by von Neumann in his theory of
measurement.


  Prompting methods recently achieve impressive success in few-shot learning.
These methods modify input samples with prompt sentence pieces, and decode
label tokens to map samples to corresponding labels. However, such a paradigm
is very inefficient for the task of slot tagging. Since slot tagging samples
are multiple consecutive words in a sentence, the prompting methods have to
enumerate all n-grams token spans to find all the possible slots, which greatly
slows down the prediction. To tackle this, we introduce an inverse paradigm for
prompting. Different from the classic prompts mapping tokens to labels, we
reversely predict slot values given slot types. Such inverse prompting only
requires a one-turn prediction for each slot type and greatly speeds up the
prediction. Besides, we propose a novel Iterative Prediction Strategy, from
which the model learns to refine predictions by considering the relations
between different slot types. We find, somewhat surprisingly, the proposed
method not only predicts faster but also significantly improves the effect
(improve over 6.1 F1-scores on 10-shot setting) and achieves new
state-of-the-art performance.


  We investigate a densely packed, non-random arrangement of forty-six
chromosomes (46,XY) in human nuclei. Here, we model systems-level chromosomal
crosstalk by unifying intrinsic parameters (chromosomal length and number of
genes) across all pairs of chromosomes in the genome to derive an extrinsic
parameter called effective gene density. The hierarchical clustering and
underlying degeneracy in the effective gene density space reveal systems-level
constraints for spatial arrangement of clusters of chromosomes that were
previously unknown. Our findings corroborate experimental data on spatial
chromosomal arrangement in human nuclei, from fibroblast and lymphocyte cell
lines, thereby establishing that human genome constrains chromosomal
arrangement. We propose that this unified theory, which requires no additional
experimental input, may be extended to other eukaryotic species with annotated
genomes to infer their constrained self-organized spatial arrangement of
chromosomes.


  We show that a closed subscheme of a given locally noetherian scheme can be
constructed by prescribing it germs at all points of the ambient scheme in a
manner consistent with specialization of points, provided the resulting set of
all associated points of all the germs is locally finite. More generally, we
prove a similar result for constructing a coherent subsheaf of a coherent sheaf
by prescribing its stalks at all points in a manner consistent with
specializations of points, again provided the set of all associated points of
all the corresponding local quotients is locally finite.
  On any locally noetherian scheme, we show that there exists a unique global
section of any coherent sheaf which has a prescribed family of germs which is
consistent with specialization of points.
  It is not clear how to formulate an analogous result for constructing a
coherent sheaf in terms of prescribed stalks. Even when the set of all
associated points of all the prescribed stalks is locally finite, such a
construction need not succeed as we show with an example. This raises the
question of how to set up effective descent data for coherent sheaves purely in
terms of germs and their specializations.


  Social media, professional sports, and video games are driving rapid growth
in live video streaming, on platforms such as Twitch and YouTube Live. Live
streaming experience is very susceptible to short-time-scale network congestion
since client playback buffers are often no more than a few seconds.
Unfortunately, identifying such streams and measuring their QoE for network
management is challenging, since content providers largely use the same
delivery infrastructure for live and video-on-demand (VoD) streaming, and
packet inspection techniques (including SNI/DNS query monitoring) cannot always
distinguish between the two.
  In this paper, we design, build, and deploy ReCLive: a machine learning
method for live video detection and QoE measurement based on network-level
behavioral characteristics. Our contributions are four-fold: (1) We analyze
about 23,000 video streams from Twitch and YouTube, and identify key features
in their traffic profile that differentiate live and on-demand streaming. We
release our traffic traces as open data to the public; (2) We develop an
LSTM-based binary classifier model that distinguishes live from on-demand
streams in real-time with over 95% accuracy across providers; (3) We develop a
method that estimates QoE metrics of live streaming flows in terms of
resolution and buffer stall events with overall accuracies of 93% and 90%,
respectively; and (4) Finally, we prototype our solution, train it in the lab,
and deploy it in a live ISP network serving more than 7,000 subscribers. Our
method provides ISPs with fine-grained visibility into live video streams,
enabling them to measure and improve user experience.


  We designed a high-resolution compact spectrometer based on an
evanescently-coupled multimode spiral waveguide. Interference between the modes
in the waveguide forms a wavelength-dependent speckle pattern which is used as
a fingerprint to identify the input wavelength after calibration. Evanescent
coupling between neighboring arms of the spiral results in a non-resonant
broad-band enhancement of the spectral resolution. Experimentally, we
demonstrated a resolution of 0.01 nm at a wavelength of 1520 nm using a 250
{\mu}m radius spiral structure. Spectra containing 40 independent spectral
channels are recovered simultaneously and the operation bandwidth is
significantly increased by applying compressive sensing to sparse spectra
reconstruction.


  Ranking models are the main components of information retrieval systems.
Several approaches to ranking are based on traditional machine learning
algorithms using a set of hand-crafted features. Recently, researchers have
leveraged deep learning models in information retrieval. These models are
trained end-to-end to extract features from the raw data for ranking tasks, so
that they overcome the limitations of hand-crafted features. A variety of deep
learning models have been proposed, and each model presents a set of neural
network components to extract features that are used for ranking. In this
paper, we compare the proposed models in the literature along different
dimensions in order to understand the major contributions and limitations of
each model. In our discussion of the literature, we analyze the promising
neural components, and propose future research directions. We also show the
analogy between document retrieval and other retrieval tasks where the items to
be ranked are structured documents, answers, images and videos.


  We address the general features of event-by-event fluctuations of the
multiplicity of gluons produced in the scattering of a dilute hadron off a
large nucleus at high energy in the fragmentation region of the dilute hadron.
We relate these fluctuations to the stochasticity of the number of quanta
contained in the hadron at the time of the interaction. For simplicity, we
address the ideal case in which the hadron is an onium, and investigate
different kinematical regimes in rapidity and onium size. We show that at large
rapidity, the multiplicity distribution exhibits an exponential tail in the
large-multiplicity region, which is qualitatively consistent with the
proton-nucleus data. But interestingly enough, the exponential shape is
determined by confinement.


  An equation has been derived to predict unit cell volume of high entropy
alloys, HEA, by two different methods. Both treatments led to the same
equation. For cubic HEA lattice parameters were calculated. The predicted
lattice parameters were compared with those reported for 68 HEAs. Lattice
parameters were also calculated using the equivalent of Vegards law for these
alloys. Average errors were 0.52, and 0.42 when Vegards law, and the equation
derived in this work were used, respectively.


  In this paper, we perform a cost-benefit analysis of multiuser diversity in
single antenna broadcast channels. It is well known that multiuser diversity
can be beneficial but there is a significant cost associated with acquiring
instantaneous CSI. We perform a cost-benefit analysis of multiuser diversity
for 2 types of CSI feedback methods, dedicated feedback and SNR dependent
feedback, quantifying how many users should feedback CSI from a net throughput
perspective. Dedicated feedback, in which orthogonal resources are allocated to
each user, has significant feedback cost and this limits the amount of
available multiuser diversity that can be used. SNR dependent feedback method,
in which only users with SNR above a threshold attempt to feedback, has
relatively much smaller feedback cost and this allows for all of the available
multiuser diversity to be used. Next, we study the effect of single user
multiantenna techniques, which reduce the SNR variation, on the number of
feedback users neccessary. It is seen that a broadcast channel using single
user multiantenna techniques should reduce the number of feedback users with
the spatial dimension.


  Cross sections for 223,225Ra, 225Ac and 227Th production by the proton
bombardment of natural thorium targets were measured at proton energies below
200 MeV. Our measurements are in good agreement with previously published data
and offer a complete excitation function for 223,225Ra in the energy range
above 90 MeV. Comparison of theoretical predictions with the experimental data
shows reasonable-to-good agreement. Results indicate that accelerator-based
production of 225Ac and 223Ra below 200 MeV is a viable production method.


  We are concerned with the Cauchy problem for the KdV equation on the whole
line with an initial profile V_0 which is decaying sufficiently fast at +\infty
and arbitrarily enough (i.e., no decay or pattern of behavior) at -\infty. We
show that this system is completely integrable in a very strong sense. Namely,
the solution V(x,t) admits the Hirota {\tau}-function representation
  V(x,t)=-2\partial_{x}^2 logdet(I+M_{x,t})
  where M_{x,t} is a Hankel integral operator constucted from certain
scattering and spectral data suitably defined in terms of the Titchmarsh-Weyl
m-functions associated with the two half-line Schr\"odinger operators
corresponding to V_0. We show that V(x,t) is real meromorphic with respect to x
for any t>0. We also show that under a very mild additional condition on V_0
representation implies a strong well-posedness of the KdV equation with such
V_0's. Among others, our approach yields some relevant results due to Cohen,
Kappeler, Khruslov, Kotlyarov, Venakides, Zhang and others.


  Drought poses a significant threat to the delicate economies in subsaharan
Africa. This study investigates the influence of large scale ocean oscillation
on drought in West Africa. Standardized Precipitation Index for the region was
computed using monthly precipitation data from the Climate Research Unit during
the period 1961 -1990. The impact of three ocean oscillation indices - Southern
Ocean Index (SOI), Pacific Decadal Oscillation (PDO) and North Atlantic
Oscillation (NAO) on drought over West Africa was investigated using linear
correlation, co-integration test, mutual information and nonlinear
synchronization methods. SOI showed predominantly positive correlation with
drought over the region while PDO and NAO showed negative correlation. This was
confirmed by the co-integration tests. The nonlinear test revealed more complex
relationship between the indices and drought. PDO has lesser influence or
contribute less to the drought in the coastal region compared to the Sahel
region of West Africa.


  In this paper a method is introduced, to visualize bifurcated stent grafts in
CT-Data. The aim is to improve therapy planning for minimal invasive treatment
of abdominal aortic aneurysms (AAA). Due to precise measurement of the
abdominal aortic aneurysm and exact simulation of the bifurcated stent graft,
physicians are supported in choosing a suitable stent prior to an intervention.
The presented method can be used to measure the dimensions of the abdominal
aortic aneurysm as well as simulate a bifurcated stent graft. Both of these
procedures are based on a preceding segmentation and skeletonization of the
aortic, right and left iliac. Using these centerlines (aortic, right and left
iliac) a bifurcated initial stent is constructed. Through the implementation of
an ACM method the initial stent is fit iteratively to the vessel walls - due to
the influence of external forces (distance- as well as balloonforce). Following
the fitting process, the crucial values for choosing a bifurcated stent graft
are measured, e.g. aortic diameter, right and left common iliac diameter,
minimum diameter of distal neck. The selected stent is then simulated to the
CT-Data - starting with the initial stent. It hereby becomes apparent if the
dimensions of the bifurcated stent graft are exact, i.e. the fitting to the
arteries was done properly and no ostium was covered.


  The structural, electronic, magnetic, and vibrational properties of
LaFeSiH$_x$ for $x$ between 0 and 1 are investigated using density functional
calculations. We find that the electronic and magnetic properties are strongly
controlled by the hydrogen concentration $x$ in LaFeSiH$_x$. While fully
hydrogenated LaFeSiH has a striped antiferromagnetic ground state, the
underdoped LaFeSiH$_x$ for $x\leq0.75$ is not magnetic within the virtual
crystal approximation or with explicit doping of supercells. The
antiferromagnetic configuration breaks the symmetry of Fe $d$ orbitals and
increases electron-phonon coupling up to $50\%$, especially for modes in the
20-50 meV range that are associated with Fe atomic movement. We find competing
nearest and next-nearest neighbor exchange interactions and significant
spin-phonon coupling, qualitatively similar but smaller in magnitude compared
those found in LaOFeAs superconductors. The superconducting $T_c$ for
antiferromagnetic LaFeSiH$_x$, assuming conventional superconductivity via
McMillan's equation, therefore is computed to be 2-10 K, in contrast to
$T_c\approx0$ for the nonmagnetic material. We also predict that the
LaFeSiH$_x$ could be a good proton conductor due to phase stability with a wide
range of hydrogen concentration $x < 1$.


  This letter introduces a novel framework for dense Visual Simultaneous
Localization and Mapping (VSLAM) based on Gaussian Splatting. Recently Gaussian
Splatting-based SLAM has yielded promising results, but rely on RGB-D input and
is weak in tracking. To address these limitations, we uniquely integrates
advanced sparse visual odometry with a dense Gaussian Splatting scene
representation for the first time, thereby eliminating the dependency on depth
maps typical of Gaussian Splatting-based SLAM systems and enhancing tracking
robustness. Here, the sparse visual odometry tracks camera poses in RGB stream,
while Gaussian Splatting handles map reconstruction. These components are
interconnected through a Multi-View Stereo (MVS) depth estimation network. And
we propose a depth smooth loss to reduce the negative effect of estimated depth
maps. Furthermore, the consistency in scale between the sparse visual odometry
and the dense Gaussian map is preserved by Sparse-Dense Adjustment Ring (SDAR).
We have evaluated our system across various synthetic and real-world datasets.
The accuracy of our pose estimation surpasses existing methods and achieves
state-of-the-art performance. Additionally, it outperforms previous monocular
methods in terms of novel view synthesis fidelity, matching the results of
neural SLAM systems that utilize RGB-D input.


  We present a comprehensive study of the interaction of human serum albumin
(HSA) with poly(acrylic acid) (PAA; number average degree of polymerization:
25) in aqueous solution. The interaction of HSA with PAA is studied in dilute
solution as the function of the concentration of added salt (20 - 100 mM) and
temperature (25 - 37$^{\circ}$C). Isothermal titration calorimetry (ITC) is
used to analyze the interaction and to determine the binding constant and
related thermodynamic data. It is found that only one PAA chain is bound per
HSA molecule. The free energy of binding $\Delta G_b$ increases with
temperature significantly. $\Delta G_b$ decreases with increasing salt
concentration and is dominated by entropic contributions due to the release of
bound counterions. Coarse-grained Langevin computer simulations treating the
counterions in an explicit manner are used study the process of binding in
detail. These simulations demonstrate that the PAA chains are bound in the
Sudlow II site of the HSA. Moreover, $\Delta G_b$ is calculated from the
simulations and found to be in very good agreement with the measured data. The
simulations demonstrate clearly that the driving force of binding is the
release of counterions in full agreement with the ITC-data.


  Let $G$ be a graph on $n$ vertices with $r := \lfloor n/2 \rfloor$ and let
$\lambda_1 \geq...\geq \lambda_{n} $ be adjacency eigenvalues of $G$. Then the
H\"uckel energy of $G$, HE($G$), is defined as $$\he(G) = {ll}
  2\sum_{i=1}^{r} \lambda_i, & \hbox{if $n= 2r$;}
  2\sum_{i=1}^{r} \lambda_i + \lambda_{r+1}, & \hbox{if $n= 2r+1$.}
  $$ The concept of H\"uckel energy was introduced by Coulson as it gives a
good approximation for the $\pi$-electron energy of molecular graphs. We obtain
two upper bounds and a lower bound for HE$(G)$. When $n$ is even, it is shown
that equality holds in both upper bounds if and only if $G$ is a strongly
regular graph with parameters $(n, k, \lambda, \mu) = (4t^2 +4t +2, 2t^2 +3t
+1, t^2 +2t, t^2 + 2t +1),$ for positive integer $t$. Furthermore, we will give
an infinite family of these strongly regular graph whose construction was
communicated by Willem Haemers to us. He attributes the construction to J.J.
Seidel.


  The aim of this paper is to review and complete the study of geodesics on
G\"odel type spacetimes initiated in [8] and improved in [2] of the References.
In particular, we prove some new results on geodesic connectedness and geodesic
completeness for these spacetimes.


  The Dirac equation has been studied in which the Dirac matrices
$\hat{\boldmath$\alpha$}, \hat\beta$ have space factors, respectively $f$ and
$f_1$, dependent on the particle's space coordinates. The $f$ function deforms
Heisenberg algebra for the coordinates and momenta operators, the function
$f_1$ being treated as a dependence of the particle mass on its position. The
properties of these functions in the transition to the Schr\"odinger equation
are discussed. The exact solution of the Dirac equation for the particle motion
in the Coulomnb field with a linear dependence of the $f$ function on the
distance $r$ to the force centre and the inverse dependence on $r$ for the
$f_1$ function has been found.


  The experimental detection of the CE$\nu$NS allows the investigation of
neutrinos and neutrino sources with all-flavor sensitivity. Given its large
content in neutrons and stability, Pb is a very appealing choice as target
element. The presence of the radioisotope $^{210}$Pb (T$_{1/2}\sim$22 yrs)
makes natural Pb unsuitable for low-background, low-energy event searches. This
limitation can be overcome employing Pb of archaeological origin, where several
half-lives of $^{210}$Pb have gone by. We present results of a cryogenic
measurement of a 15g PbWO$_4$ crystal, grown with archaeological Pb (older than
$\sim$2000 yrs) that achieved a sub-keV nuclear recoil detection threshold. A
ton-scale experiment employing such material, with a detection threshold for
nuclear recoils of just 1 keV would probe the entire Milky Way for SuperNovae,
with equal sensitivity for all neutrino flavors, allowing the study of the core
of such exceptional events.


  Based on the isospin-dependent Boltzmann-Uehling-Uhlenbeck transport model
and the scaling model according to nucleon effective mass, effects of elastic
and inelastic NN scattering cross sections on pion-/pion+ in the neutron-rich
reaction of Ca48+Ca48 at a beam energy of 400 MeV/nucleon are studied. It is
found that cross-section effects of both NN elastic and inelastic scatterings
affect Delta_1232, pion- and pion+ production, as well as the value of
pion-/pion+.


  Random Walks-based Anomaly Detection (RWAD) is commonly used to identify
anomalous patterns in various applications. An intriguing characteristic of
RWAD is that the input graph can either be pre-existing or constructed from raw
features. Consequently, there are two potential attack surfaces against RWAD:
graph-space attacks and feature-space attacks. In this paper, we explore this
vulnerability by designing practical coupled-space attacks, investigating the
interplay between graph-space and feature-space attacks. To this end, we
conduct a thorough complexity analysis, proving that attacking RWAD is NP-hard.
Then, we proceed to formulate the graph-space attack as a bi-level optimization
problem and propose two strategies to solve it: alternative iteration
(alterI-attack) or utilizing the closed-form solution of the random walk model
(cf-attack). Finally, we utilize the results from the graph-space attacks as
guidance to design more powerful feature-space attacks (i.e., graph-guided
attacks). Comprehensive experiments demonstrate that our proposed attacks are
effective in enabling the target nodes from RWAD with a limited attack budget.
In addition, we conduct transfer attack experiments in a black-box setting,
which show that our feature attack significantly decreases the anomaly scores
of target nodes. Our study opens the door to studying the coupled-space attack
against graph anomaly detection in which the graph space relies on the feature
space.


  We present a numerical model of a collapsing radiating sphere, whose boundary
surface undergoes bouncing due to a decreasing of its inertial mass density
(and, as expected from the equivalence principle, also of the ``gravitational''
force term) produced by the ``inertial'' term of the transport equation. This
model exhibits for the first time the consequences of such an effect, and shows
that under physically reasonable conditions this decreasing of the
gravitational term in the dynamic equation may be large enough as to revert the
collapse and produce a bouncing of the boundary surface of the sphere.


  In an open information systems paradigm, real-time context-awareness is vital
for the success of cooperation, therefore dynamic security attributes of
partners should considered in coalition for avoiding security conflicts.
Furthermore, the cross-boundary asset sharing activities and risks associated
to loss of governance call for a continuous regulation of partners' behavior,
paying attention to the resource sharing and consuming activities. This paper
describes an attribute-based usage control policy shceme compline to this
needs. A concise syntax with EBNF is used to summarize the base policy model.
The semantics of negotiation process is disambiguated with abductive constraint
logic programming (ACLP) and Event Calculus (EC). Then we propose a policy
ratification method based on a policy aggregation algebra that elaborate the
request space and policy rule relation. This method ensures that, when policies
are aggregated due to resource sharing and merging activities, the resulting
policy correctly interprets the original security goals of the providers'
policies.


  We analyze heating and cooling processes in accretion disks in binaries. For
realistic parameters of the accretion disks in close binaries (with accretion
rates from 1e-12 to 1e-7 Msun/year and \alpha from 0.1 to 0.01), the gas
temperature in the outer parts of the disk is from 1e4 to 1e6 K. Our previous
gas-dynamical studies of mass transfer in close binaries indicate that, for hot
disks (with temperatures for the outer parts of the disk of several hundred
thousand K), the interaction between the stream from the inner Lagrange point
and the disk is shockless. To study the morphology of the interaction between
the stream and a cool accretion disk, we carried out three-dimensional modeling
of the flow structure in a binary for the case when the gas temperature in the
outer parts of the forming disk does not exceed 13600 K. The flow pattern
indicates that the interaction is again shockless. The computations provide
evidence that, as is the case for hot disks, the zone of enhanced energy
release (the "hot line") is located beyond the disk, and originates due to the
interaction between the circum-disk halo and the stream.


  The m-sophistication of a finite binary string x is introduced as a
generalization of some parameter in the proof that complexity of complexity is
rare. A probabilistic near sufficient statistic of x is given which length is
upper bounded by the m-sophistication of x within small additive terms. This
shows that m-sophistication is lower bounded by coarse sophistication and upper
bounded by sophistication within small additive terms. It is also shown that
m-sophistication and coarse sophistication can not be approximated by an upper
or lower semicomputable function, not even within very large error.


  Cross-identifications for 14,574 intrinsically luminous galactic stars
(mostly OB stars) to objects in the 2MASS survey have been determined using a
search box of +/-0.0015 degrees (+/- 5.4 arcsec) in both RA and Dec.
Instructions on obtaining the relevant files can be obtained at
othello.alma.edu/~reed/OB-2MASS.doc.