  Tokenization is a critical part of modern NLP pipelines. However,
contemporary tokenizers for Large Language Models are based on statistical
analysis of text corpora, without much consideration to the linguistic
features. I propose a linguistically motivated tokenization scheme, MorphPiece,
which is based partly on morphological segmentation of the underlying text. A
GPT-style causal language model trained on this tokenizer (called MorphGPT)
shows comparable or superior performance on a variety of supervised and
unsupervised NLP tasks, compared to the OpenAI GPT-2 model. Specifically I
evaluated MorphGPT on language modeling tasks, zero-shot performance on GLUE
Benchmark with various prompt templates, massive text embedding benchmark
(MTEB) for supervised and unsupervised performance, and lastly with another
morphological tokenization scheme (FLOTA, Hoffmann et al., 2022) and find that
the model trained on MorphPiece outperforms GPT-2 on most evaluations, at times
with considerable margin, despite being trained for about half the training
iterations.


  While microtask crowdsourcing provides a new way to solve large volumes of
small tasks at a much lower price compared with traditional in-house solutions,
it suffers from quality problems due to the lack of incentives. On the other
hand, providing incentives for microtask crowdsourcing is challenging since
verifying the quality of submitted solutions is so expensive that will negate
the advantage of microtask crowdsourcing. We study cost-effective incentive
mechanisms for microtask crowdsourcing in this paper. In particular, we
consider a model with strategic workers, where the primary objective of a
worker is to maximize his own utility. Based on this model, we analyze two
basic mechanisms widely adopted in existing microtask crowdsourcing
applications and show that, to obtain high quality solutions from workers,
their costs are constrained by some lower bounds. We then propose a
cost-effective mechanism that employs quality-aware worker training as a tool
to stimulate workers to provide high quality solutions. We prove theoretically
that the proposed mechanism, when properly designed, can obtain high quality
solutions with an arbitrarily low cost. Beyond its theoretical guarantees, we
further demonstrate the effectiveness of our proposed mechanisms through a set
of behavioral experiments.


  We develop the theory of global and local Weyl modules for the hyperspecial
maximal parabolic subalgebra of type $A_{2n}^{(2)}$. We prove that the
dimension of a local Weyl module depends only on its highest weight, thus
establishing a freeness result for global Weyl modules. Furthermore, we show
that the graded local Weyl modules are level one Demazure modules for the
corresponding affine Lie algebra. In the last section we derive the same
results for the special maximal parabolic subalgebras of the twisted affine Lie
algebras not of type $A_{2n}^{(2)}$.


  Local massive early-type galaxies are believed to have completed most of
their star formation $\sim10$Gyr ago and evolved without having substantial
star formation since. If so, their progenitors should have roughly solar
stellar metallicities ($Z_*$), comparable to their values today. We report the
discovery of two lensed massive ($\log M_*/M_\odot\sim11$), $z\sim2.2$ dead
galaxies, that appear markedly metal deficient given this scenario. Using
17-band $HST$+$K_{s}$+$Spitzer$ photometry and deep $HST$ grism spectra from
the GLASS and SN Refsdal follow-up campaigns covering features near
$\lambda_{\rm rest}\sim4000$\AA, we find these systems to be dominated by
A-type stars with $\log Z_*/Z_\odot=-0.40\pm0.02$ and $-0.49\pm0.03$
($30$-$40\%$ solar) under standard assumptions. The second system's lower
metallicity is robust to isochrone changes, though this choice can drive the
first system's from $\log Z_*/Z_\odot=-0.6$ to 0.1. If these two galaxies are
representative of larger samples, this finding suggests that evolutionary paths
other than dry minor-merging are required for these massive galaxies. Future
analyses with direct metallicity measurements-e.g., by the $James\ Webb\ Space\
Telescope$-will provide critical insight into the nature of such phenomena.


  This paper is a short summary of our recent work on the medians and means of
probability measures in Riemannian manifolds. Firstly, the existence and
uniqueness results of local medians are given. In order to compute medians in
practical cases, we propose a subgradient algorithm and prove its convergence.
After that, Fr\'echet medians are considered. We prove their statistical
consistency and give some quantitative estimations of their robustness with the
aid of upper curvature bounds. We also show that, in compact Riemannian
manifolds, the Fr\'echet medians of generic data points are always unique.
Stochastic and deterministic algorithms are proposed for computing Riemannian
p-means. The rate of convergence and error estimates of these algorithms are
also obtained. Finally, we apply the medians and the Riemannian geometry of
Toeplitz covariance matrices to radar target detection.


  The amplitude and phase noises of a dual-frequency vertical-external-cavity
surface-emitting laser (DF-VECSEL) operating at telecom wavelength are
theoretically and experimentally investigated in detail. In particular, the
spectral behavior of the correlation between the intensity noises of the two
modes of the DF-VECSEL is measured. Moreover, the correlation between the phase
noise of the radio-frequency (RF) beatnote generated by optical mixing of the
two laser modes with the intensity noises of the two modes is investigated. All
these spectral behaviors of noise correlations are analyzed for two different
values of the nonlinear coupling between the laser modes. We find that to
describe the spectral behavior of noise correlations between the laser modes,
it is of utmost importance to have a precise knowledge about the spectral
behavior of the pump noise, which is the dominant source of noise in the
frequency range of our interest (10 kHz to 35 MHz). Moreover, it is found that
the noise correlation also depends on how the spatially separated laser modes
of the DF-VECSEL intercept the noise from a multi-mode fiber-coupled laser
diode used for pumping both the laser modes. To this aim, a specific experiment
is reported, which aims at measuring the correlations between different spatial
regions of the pump beam. The experimental results are in excellent agreement
with a theoretical model based on modified rate equations.


  In this paper we solve an inverse resonance problem for the half-solid with
vanishing stresses on the surface: Lamb's problem. Using a semi-classical
approach we are able to simplify this three-dimensional problem of the elastic
wave equation for the half-solid as a Schr\"odinger equation with Robin
boundary conditions on the half-line. We obtain asymptotic values on the number
and the location of the resonances with respect to the wave number. Moreover,
we prove that the mapping from real compactly supported potentials to the Jost
functions in a suitable class of entire functions is one-to-one and onto and we
produce an algorithm in order to retrieve the shear modulus from the
eigenvalues and resonances.


  A long-range effective action is derived for strong-coupling lattice SU(2)
gauge theory in D=3 dimensions. It is shown that center vortices emerge as
stable saddlepoints of this action.


  An independent, automated method of decoding and transcribing oral speech is
known as automatic speech recognition (ASR). A typical ASR system extracts
feature from audio recordings or streams and run one or more algorithms to map
the features to corresponding texts. Numerous of research has been done in the
field of speech signal processing in recent years. When given adequate
resources, both conventional ASR and emerging end-to-end (E2E) speech
recognition have produced promising results. However, for low-resource
languages like Bengali, the current state of ASR lags behind, although the low
resource state does not reflect upon the fact that this language is spoken by
over 500 million people all over the world. Despite its popularity, there
aren't many diverse open-source datasets available, which makes it difficult to
conduct research on Bengali speech recognition systems. This paper is a part of
the competition named `BUET CSE Fest DL Sprint'. The purpose of this paper is
to improve the speech recognition performance of the Bengali language by
adopting speech recognition technology on the E2E structure based on the
transfer learning framework. The proposed method effectively models the Bengali
language and achieves 3.819 score in `Levenshtein Mean Distance' on the test
dataset of 7747 samples, when only 1000 samples of train dataset were used to
train.


  We show how to constrain inflationary models and reheating by using mixed
constraints. In particular we study the physics of the reheating phase after
inflation from observational constraints to the inflationary stage. We show
that it is possible to determine $\omega$, the equation of state during
reheating, by using the reported values of the spectral index and the {\it
full} number of $e$-folds $N(n_s,\omega)= N_H(n_s)+N_{re}(n_s,w)\approx 60$,
which includes the accelerated expansion and the reheating phase. We show that
the reheating number of $e$-folds $N_{re}$ is quite sensitive to this equation
of state. Requiring $N_{re}>0$ and a sensible value for the thermalization
scale $T_{re}$, demands in general a reheating phase with $\omega\neq 0$. We
exemplify the constraints with two particular examples: We show how the
Starobinsky model allows only large values of $T_{re}$ if the reheating phase
is dominated by dust ($w =0$), and if Primordial Black Hole production is
subdominant. For the case of $N=1$ Supergravity inflation, the extra parameter
of the potential provides the necessary freedom to afford lower-scale
thermalization in a dust-like reheating phase and yet our method serves to
determine the rest of the observable parameters.


  Free probabilistic considerations of type B first appeared in a paper by
Biane, Goodman and Nica in 2003. Recently, connections between type B and
infinitesimal free probability were put into evidence by Belinschi and
Shlyakhtenko (arXiv:0903.2721). The interplay between "type B" and
"infinitesimal" is also the object of the present paper. We study infinitesimal
freeness for a family of unital subalgebras A_1, ..., A_k in an infinitesimal
noncommutative probability space (A, phi, phi'), and we introduce a concept of
infinitesimal non-crossing cumulant functionals for (A, phi, phi'), obtained by
taking a formal derivative in the formula for usual non-crossing cumulants. We
prove that the infinitesimal freeness of A_1, ... A_k is equivalent to a
vanishing condition for mixed cumulants; this gives the infinitesimal
counterpart for a theorem of Speicher from "usual" free probability. We show
that the lattices of non-crossing partitions of type B appear in the
combinatorial study of (A, phi, phi'), in the formulas for infinitesimal
cumulants and when describing alternating products of infinitesimally free
random variables. As an application of alternating free products, we observe
the infinitesimal analogue for the well-known fact that freeness is preserved
under compression with a free projection. As another application, we observe
the infinitesimal analogue for a well-known procedure used to construct free
families of free Poisson elements. Finally, we discuss situations when the
freeness of A_1, ..., A_k in (A, phi) can be naturally upgraded to
infinitesimal freeness in (A, phi, phi'), for a suitable choice of a "companion
functional" phi'.


  We investigate how to define in a consistent way the probabilities of the
transitions between the "flavor" states of the two-level quantum system, which
is described by a non-Hermitian but parity and time-reversal (PT) symmetric
Hamiltonian. Explicit calculations are carried out to demonstrate the
conservation of probability if a proper definition of the final state is
adopted. Finally, this formalism is applied to two-flavor neutrino oscillations
$\nu^{}_\mu \to \nu^{}_\mu$ and $\nu^{}_\mu \to \nu^{}_\tau$ in vacuum, where
the exact PT symmetry requires the vacuum mixing angle to be maximal, which is
compatible with current neutrino oscillation experiments. A possible
generalization to the three-flavor case is briefly discussed.


  Motivated by the theory of crystallizations, we consider an equivalence
relation on the class of $3$-regular colored graphs and prove that up to this
equivalence (a) there exists a unique contracted 3-regular colored graph if the
number of vertices is $4m$ and (b) there are exactly two such graphs if the
number of vertices is $4m+2$ for each $m\geq 1$. Using this, we present a
simple proof of the classification of closed surfaces.


  In a recent paper [1] the scattering and transport of excess electrons in
liquid argon in the hydrodynamic regime was investigated, generalizing the
seminal works of Lekner and Cohen [2,3] with modern scattering theory
techniques and kinetic theory. In this paper, the discussion is extended to the
non-hydrodynamic regime through the development of a full multi-term space-time
solution of Boltzmann's equation for electron transport in gases and liquids
using a novel operator-splitting method. A Green's function formalism is
considered that enables flexible adaptation to various experimental systems.
The spatio-temporal evolution of electrons in liquids in the hydrodynamic
regime is studied for a benchmark model Percus-Yevick liquid as well as for
liquid argon. The temporal evolution of Franck-Hertz oscillations are observed
for liquids, with striking differences in the spatio-temporal development of
the velocity distribution function components between the uncorrelated gas and
true liquid approximations in argon. Transport properties calculated from the
non-hydrodynamic theory in the long time limit, and under steady-state Townsend
conditions, are benchmarked against hydrodynamic transport coefficients.


  New contributions to the short-distance b --> s eta' transition are
considered. They correspond to the quark and gluon content of eta'. Although
substantially larger than the referent QCD anomaly tail, they still cannot
account for the observed eta' enhancement.


  Context. Binary Cepheids play an important role in investigating the
calibration of the classical Cepheid period-luminosity relationship. Therefore
a thorough study of individual Cepheids belonging to binary systems is
necessary. Aims. Our aim is to determine the orbit of the binary system V1344
Aql using newly observed and earlier published spectroscopic and photometric
data. Methods. We collected new radial velocity observations using medium
resolution (${R \approx 11000}$ and ${R \lessapprox 20000}$) spectrographs and
we updated the pulsation period of the Cepheid based on available photometric
observations using $O-C$ diagram. Separating the pulsational and orbital radial
velocity variations for each observational season (year), we determined the
orbital solution for the system using $\chi^2$ minimisation. Results. The
updated pulsation period of the Cepheid estimated for the epoch of HJD
2458955.83 is 7.476826 days. We determined orbital elements for the first time
in the literature. The orbital period of the system is about 34.6 years, with
an eccentricity e = 0.22.


  In this chapter, an application of Mathematical Epidemiology to crop
vector-borne diseases is presented to investigate the interactions between
crops, vectors, and virus. The main illustrative example is the cassava mosaic
disease (CMD). The CMD virus has two routes of infection: through vectors and
also through infected crops. In the field, the main tool to control CMD
spreading is roguing. The presented biological model is sufficiently generic
and the same methodology can be adapted to other crops or crop vector-borne
diseases. After an introduction where a brief history of crop diseases and
useful information on Cassava and CMD is given, we develop and study a
compartmental temporal model, taking into account the crop growth and the
vector dynamics. A brief qualitative analysis of the model is provided,i.e.,
existence and uniqueness of a solution,existence of a disease-free equilibrium
and existence of an endemic equilibrium. We also provide conditions for local
(global) asymptotic stability and show that a Hopf Bifurcation may occur, for
instance, when diseased plants are removed. Numerical simulations are provided
to illustrate all possible behaviors. Finally, we discuss the theoretical and
numerical outputs in terms of crop protection.


  We study an integrable model of one-dimensional strongly correlated electrons
at finite temperature by explicit calculation of the correlation lengths of
various correlation functions. The model is invariant with respect to the
quantum superalgebra U_q(sl(2|1)) and characterized by the Hubbard interaction,
correlated hopping and pair-hopping terms. Using the integrability, the graded
quantum transfer matrix is constructed. From the analyticity of its
eigenvalues, a closed set of non-linear integral equations is derived which
describe the thermodynamical quantities and the finite temperature
correlations. The results show a crossover from a regime with dominating
density-density correlations to a regime with dominating superconducting pair
correlations. Analytical calculations in the low temperature limit are also
discussed.


  Omics data analysis is crucial for studying complex diseases, but its high
dimensionality and heterogeneity challenge classical statistical and machine
learning methods. Graph neural networks have emerged as promising alternatives,
yet the optimal strategies for their design and optimization in real-world
biomedical challenges remain unclear. This study evaluates various graph
representation learning models for case-control classification using
high-throughput biological data from Parkinson's disease and control samples.
We compare topologies derived from sample similarity networks and molecular
interaction networks, including protein-protein and metabolite-metabolite
interactions (PPI, MMI). Graph Convolutional Network (GCNs), Chebyshev spectral
graph convolution (ChebyNet), and Graph Attention Network (GAT), are evaluated
alongside advanced architectures like graph transformers, the graph U-net, and
simpler models like multilayer perceptron (MLP).
  These models are systematically applied to transcriptomics and metabolomics
data independently. Our comparative analysis highlights the benefits and
limitations of various architectures in extracting patterns from omics data,
paving the way for more accurate and interpretable models in biomedical
research.


  The engineering design process follows a series of standardized stages of
development, which have many aspects in common with software engineering. Among
these stages, the principle solution can be regarded as an analogue of the
design specification, fixing as it does the way the final product works. It is
usually constructed as an abstract sketch (hand-drawn or constructed with a CAD
system) where the functional parts of the product are identified, and geometric
and topological constraints are formulated. Here, we outline a semantic
approach where the principle solution is annotated with ontological assertions,
thus making the intended requirements explicit and available for further
machine processing; this includes the automated detection of design errors in
the final CAD model, making additional use of a background ontology of
engineering knowledge. We embed this approach into a document-oriented design
workflow, in which the background ontology and semantic annotations in the
documents are exploited to trace parts and requirements through the design
process and across different applications.


  The charged pion form factor, Fpi(Q^2), is an important quantity which can be
used to advance our knowledge of hadronic structure. However, the extraction of
Fpi from data requires a model of the 1H(e,e'pi+)n reaction, and thus is
inherently model dependent. Therefore, a detailed description of the extraction
of the charged pion form factor from electroproduction data obtained recently
at Jefferson Lab is presented, with particular focus given to the dominant
uncertainties in this procedure. Results for Fpi are presented for
Q^2=0.60-2.45 GeV^2. Above Q^2=1.5 GeV^2, the Fpi values are systematically
below the monopole parameterization that describes the low Q^2 data used to
determine the pion charge radius. The pion form factor can be calculated in a
wide variety of theoretical approaches, and the experimental results are
compared to a number of calculations. This comparison is helpful in
understanding the role of soft versus hard contributions to hadronic structure
in the intermediate Q^2 regime.


  Let $a$ and $b$ be positive integers. An even $[a,b]$-factor of a graph $G$
is a spanning subgraph $H$ such that for every vertex $v \in V(G)$, $d_H(v)$ is
even and $a \le d_H(v) \le b$. Matsuda conjectured that if $G$ is an $n$-vertex
2-edge-connected graph such that $n \ge 2a+b+\frac{a^2-3a}b - 2$, $\delta(G)
\ge a$, and $\sigma_2(G) \ge \frac{2an}{a+b}$, then $G$ has an even
$[a,b]$-factor. In this paper, we provide counterexamples, which are highly
connected. Furthermore, we give sharp sufficient conditions for a graph to have
an even $[a,b]$-factor. For even $an$, we conjecture a lower bound for
$\lambda_1(G)$ in an $n$-vertex graph to have an $[a,b]$-factor, where
$\lambda_1(G)$ is the largest eigenvalue of $G$.


  We consider a cognitive radio network scenario where a primary transmitter
and a secondary transmitter, respectively, communicate a message to their
respective primary receiver and secondary receiver over a packet-based wireless
link, using a joint automatic-repeat-request (ARQ) error control scheme. The
secondary transmitter assists in the retransmission of the primary message,
which improves the primary performance, and is granted limited access to the
transmission resources. Conventional ARQ, as well as two network-coding schemes
are investigated for application in the retransmission phase; namely the static
network-coding (SNC) scheme and the adaptive network-coding (ANC) scheme. For
each scheme we analyze the transmission process by investigating the
distribution of the number of transmission attempts and approximate it by
normal distributions. Considering both the cases of an adaptive frame size and
a truncated frame size, we derive analytical results on packet throughput and
infer that the ANC scheme outperforms the SNC scheme.


  We study a Vicsek-style model of self-propelled particles where ferromagnetic
and nematic alignment compete in both the usual "metric" version and in the
"metric-free" case where a particle interacts with its Voronoi neighbors. We
show that the phase diagram of this out-of-equilibrium XY model is similar to
that of its equilibrium counterpart: the properties of the fully-nematic model,
studied before in [F. Ginelli, F. Peruani, M. Baer, and H. Chat\'e, Phys. Rev.
Lett. 104, 184502 (2010)], are thus robust to the introduction of a modest bias
of interactions towards ferromagnetic alignment. The direct transitions between
polar and nematic ordered phases are shown to be discontinuous in the metric
case, and continuous, belonging to the Ising universality class, in the
metric-free version.


  A common approach for designing scalable algorithms for massive data sets is
to distribute the computation across, say $k$, machines and process the data
using limited communication between them. A particularly appealing framework
here is the simultaneous communication model whereby each machine constructs a
small representative summary of its own data and one obtains an
approximate/exact solution from the union of the representative summaries. If
the representative summaries needed for a problem are small, then this results
in a communication-efficient and round-optimal protocol. While many fundamental
graph problems admit efficient solutions in this model, two prominent problems
are notably absent from the list of successes, namely, the maximum matching
problem and the minimum vertex cover problem. Indeed, it was shown recently
that for both these problems, even achieving a polylog$(n)$ approximation
requires essentially sending the entire input graph from each machine.
  The main insight of our work is that the intractability of matching and
vertex cover in the simultaneous communication model is inherently connected to
an adversarial partitioning of the underlying graph across machines. We show
that when the underlying graph is randomly partitioned across machines, both
these problems admit randomized composable coresets of size $\widetilde{O}(n)$
that yield an $\widetilde{O}(1)$-approximate solution. This results in an
$\widetilde{O}(1)$-approximation simultaneous protocol for these problems with
$\widetilde{O}(nk)$ total communication when the input is randomly partitioned
across $k$ machines. We further prove the optimality of our results. Finally,
by a standard application of composable coresets, our results also imply
MapReduce algorithms with the same approximation guarantee in one or two rounds
of communication


  We study robustness properties of some iterative gradient-based methods for
strongly convex functions, as well as for the larger class of functions with
sector-bounded gradients, under a relative error model. Proofs of the
corresponding convergence rates are based on frequency-domain criteria for the
stability of nonlinear systems. Applications are given to inexact versions of
gradient descent and the Triple Momentum Method. To further emphasize the
usefulness of frequency-domain methods, we derive improved analytic bounds for
the convergence rate of Nesterov's accelerated method (in the exact setting) on
strongly convex functions.


  La2Mo2O9 (LAMOX) is a fast oxygen ion conductor which shows high oxygen ion
conductivities comparable to those of yttria-sabilized zirconia (YSZ) . LAMOX
is subject to a structural phase transition from the non-conductive monoclinic
form to the highly-conductive cubic form at about 580C. The origin of the
conductivity in cubic LAMOX has been suggested to be due to a "disorder" in the
O sub-lattice without any insight into the real distribution of the oxygen ion.
In this paper, thanks to the application of the neutron atomic pair
distribution function (PDF) analysis, we provided evidences that the local
structure of the cubic polymorph of LAMOX is exactly the same of that of the
monoclinic phase thus indicating that the structural phase transition is
actually a transition from a static to a dynamic distribution of the oxygen
defects. This work represent the first application of the atomic-pair
distribution function analysis to the study of an oxygen fast-oxide ion
conductor and clearly indicates that a more reliable and detailed description
of their local structure, particularly in the highly conductive phases, and can
lead to a better comprehension of the structure-property correlation, which is
the starting point for the design of new and optimized functional materials.


  An algorithm to compute a good basis of the Brieskorn lattice of a
cohomologically tame polynomial is described. This algorithm is based on the
results of C. Sabbah and generalizes the algorithm by A. Douai for convenient
Newton non-degenerate polynomials.


  Bayesian inference provides a methodology for parameter estimation and
uncertainty quantification in machine learning and deep learning methods.
Variational inference and Markov Chain Monte-Carlo (MCMC) sampling methods are
used to implement Bayesian inference. In the past three decades, MCMC sampling
methods have faced some challenges in being adapted to larger models (such as
in deep learning) and big data problems. Advanced proposal distributions that
incorporate gradients, such as a Langevin proposal distribution, provide a
means to address some of the limitations of MCMC sampling for Bayesian neural
networks. Furthermore, MCMC methods have typically been constrained to
statisticians and currently not well-known among deep learning researchers. We
present a tutorial for MCMC methods that covers simple Bayesian linear and
logistic models, and Bayesian neural networks. The aim of this tutorial is to
bridge the gap between theory and implementation via coding, given a general
sparsity of libraries and tutorials to this end. This tutorial provides code in
Python with data and instructions that enable their use and extension. We
provide results for some benchmark problems showing the strengths and
weaknesses of implementing the respective Bayesian models via MCMC. We
highlight the challenges in sampling multi-modal posterior distributions for
the case of Bayesian neural networks and the need for further improvement of
convergence diagnosis methods.


  The authors describe the largest existing publicly accessible radio source
database CATS (``astrophysical CATalogues Supporting system'';
http://cats.sao.ru). CATS contains more than 300 catalogues of objects detected
in different (but mostly radio) wavelength ranges. These include catalogues
from the largest existing surveys, like NVSS, FIRST, WENSS, TXS, GB6, IRAS,
ROSAT, PGC, MCG, etc. Thus CATS allows to draw samples of objects to study a
great variety of astrophysical problems. CATS also includes all of the largest
low-frequency catalogues published so far : UTR(10--25 MHz), Culgoora (80, 160
MHz), Cambridge (38, 151, 178 MHz), Miyun (232 MHz), WENSS (325 MHz), Texas
(365 MHz), Bologna and Molonglo (408 MHz) etc., and allows the user to operate
with them.


  Using a representation theoretic parameterization for the orbits in the
enhanced cyclic nilpotent cone, derived by the authors in a previous article,
we compute the fundamental group of these orbits. This computation has several
applications to the representation theory of the category of admissible
$D$-modules on the space of representations of the framed cyclic quiver. First,
and foremost, we compute precisely when this category is semi-simple. We also
show that the category of admissible $D$-modules has enough projectives.
Finally, the support of an admissible $D$-module is contained in a certain
Lagrangian in the cotangent bundle of the space of representations. Thus,
taking characteristic cycles defines a map from the $K$-group of the category
of admissible $D$-modules to the $\mathbb{Z}$-span of the irreducible
components of this Lagrangian. We show that this map is always injective, and a
bijection if and only if the monodromicity parameter is integral.


  Large language models (LLMs) have demonstrated exceptional performance in
planning the use of various functional tools, such as calculators and
retrievers, particularly in question-answering tasks. In this paper, we expand
the definition of these tools, centering on conceptual tools within the context
of dialogue systems. A conceptual tool specifies a cognitive concept that aids
systematic or investigative thought. These conceptual tools play important
roles in practice, such as multiple psychological or tutoring strategies being
dynamically applied in a single turn to compose helpful responses. To further
enhance the reasoning and planning capability of LLMs with these conceptual
tools, we introduce a multi-persona collaboration framework: Think-Plan-Execute
(TPE). This framework decouples the response generation process into three
distinct roles: Thinker, Planner, and Executor. Specifically, the Thinker
analyzes the internal status exhibited in the dialogue context, such as user
emotions and preferences, to formulate a global guideline. The Planner then
generates executable plans to call different conceptual tools (e.g., sources or
strategies), while the Executor compiles all intermediate results into a
coherent response. This structured approach not only enhances the
explainability and controllability of responses but also reduces token
redundancy. We demonstrate the effectiveness of TPE across various dialogue
response generation tasks, including multi-source (FoCus) and multi-strategy
interactions (CIMA and PsyQA). This reveals its potential to handle real-world
dialogue interactions that require more complicated tool learning beyond just
functional tools. The full code and data will be released for reproduction.


  We suggest a practical way to estimate the condensate fraction of an
interacting dilute Bose gas confined by an external harmonic potential as a
function of temperature and scattering length. It shows that an increase of the
scattering length produces an exponential decrease of condensate fraction.


  In previous works, we have developed a new Malliavin calculus on the Poisson
space based on the lent particle formula. The aim of this work is to prove
that, on the Wiener space for the standard Ornstein-Uhlenbeck structure, we
also have such a formula which permits to calculate easily and intuitively the
Malliavin derivative of a functional. Our approach uses chaos extensions
associated to stationary processes of rotations of normal martingales.


  The anharmonicity of phonons in solid is ultimately rooted in the chemical
bonding. However, the direct connection between phonon anharmoncity and
chemical bonding is difficult to make experimentally or theoretically, due
mainly to their complicated lattice structures. Here, with the help of density
functional theory based calculations, we discovery that electrostatic
inter-layer coupling in Bi$_2$O$_2$X (X=S,Se,Te) leads to intrinsically low
lattice thermal conductivity. We explain our discovery by the strong anharmonic
chemical bonding between Bi and chalcogen atoms. Our results shed light on the
connection between inter-layer chemical bonding and phonon anharmonicity, which
could be explored in a wide range of layered materials.


  We carried out a 2MASS J, H and K_s survey of infrared star clusters in the
Milky Way sector 230$^{\circ}$ $< \ell <$ 350$^{\circ}$. This zone was the
least studied in the literature, previously including only 12 infrared clusters
or stellar groups with $|b|<$ 10$^{\circ}$, according to the recent catalogue
by Bica et al. (2003). We concentrated efforts on embedded clusters, which are
those expected in the areas of known radio and optical nebulae. The present
study provides 179 new infrared clusters and stellar groups, which are
interesting targets for detailed future infrared studies. The sample of
catalogued infrared clusters and stellar groups in the Galaxy is now increased
by 63%.


  We present exact results for the degree distribution in a directed network
model that grows by node duplication (ND). Such models are useful in the study
of the structure and growth dynamics of gene regulatory networks and scientific
citation networks. Starting from an initial seed network, at each time step a
random node, a mother node, is selected for duplication. Its daughter node is
added to the network and duplicates each outgoing link of the mother node with
probability p. In addition, the daughter node forms a directed link to the
mother node itself. We obtain analytical results for the in-degree distribution
$P_t(K_{in}=k)$, and for the out-degree distribution $P_t(K_{out}=k)$ at time
t. The in-degrees follow a shifted power-law, so the network is asymptotically
scale free. In contrast, the out-degree distribution is narrow, and converges
to a Poisson distribution in the sparse network limit and to a Gaussian
distribution in the dense network limit. Such distinction between a broad
in-degree distribution and a narrow out-degree distribution is common in
empirical networks such as scientific citation networks. Using this we
calculate the mean degree $\langle K_{in}\rangle_t=\langle K_{out}\rangle_t$,
which converges to $1/(1-p)$ in the large network limit, for the whole range of
$0<p<1$. This is in contrast to the corresponding undirected network, which
exhibits a phase transition at $p=1/2$ such that for $p>1/2$ the mean degree
diverges in the large network limit. We also present analytical results for the
distribution of the number of upstream and downstream nodes from a random node.
The mean values $\langle N_{up}\rangle_t=\langle N_{down}\rangle_t$ scale
logarithmically with the network size, implying that only a small fraction of
pairs of nodes are connected by directed paths, unlike the undirected ND case
that consists of a single component, hence not a small-world network.


  Dark Matter is a hypothetical particle proposed to explain the missing matter
expected from the cosmological observation. The motivation of Dark Matter is
overwhelming however as it is mainly deduced from its gravitational
interaction, for it does little to pinpoint what Dark Matter really is. In
WIMPs Miracle, weakly interactive massive particle being the Dark Matter
candidate is correctly producing the current thermal relic density at weak
scale, implying the possibility of producing and detecting it in Large Hadron
Collider. Assuming WIMPs being the maverick particle within collider, it is
expected to be pair produced in association with a Standard Model particle. The
presence of the WIMPs pair is inferred from the Missing Transverse Energy (MET)
which is the vector sum of the imbalance in the transverse momentum plane
recoils a Standard Model Particle. The collider is able to produce light mass
Dark Matter which the traditional detection fail to detect due to the small
momentum transfer involved in the interaction; on the other hand, the
traditional detection is robust in detecting a higher Dark matter masses but
the collider is su ered from the parton distribution function suppression.
Topologically the processes are similar to the scattering processes in the
direct detection thus complementary to the traditional Dark Matter detection.
The collider searches are strongly motivated as the results are usually
translated to the annihilation and scattering rates at more traditional Dark
Matter-oriented experiments, thus a concordance approach is adapted. An
overview of Dark Matter searches at the Large Hadron Collider will be covered
in this paper.


  Thermoelectric power, S(T) of the Mg1-xAlxB2 system has been measured for x =
0.0, 0.1, 0.2, 0.4, 0.6, 0.8 and 1.0. XRD, resistivity and magnetization
measurements are also presented. It has been found that the thermoelectric
power is positive for x = 0.4 and is negative for x = 0.6 over the entire
temperature range studied up to 300 K. The thermoelectric power of x = 0.4
samples vanishes discontinuously below a certain temperature, implying
existence of superconductivity. In general, the magnitude of the thermoelectric
power increases with temperature up to a certain temperature, and then it
starts to decrease towards zero base line. In order to explain the observed
behavior of the thermoelectric power, we have used a model in which both
diffusion and phonon drag processes are combined by using a phenomenological
interpolation between the low and high temperature behaviors of the
thermoelectric power. The considered model provides an excellent fit to the
observed data. It is further found that Al doping enhances the Debye
temperature.


  Transfer learning (TL) is becoming a powerful tool in scientific applications
of neural networks (NNs), such as weather/climate prediction and turbulence
modeling. TL enables out-of-distribution generalization (e.g., extrapolation in
parameters) and effective blending of disparate training sets (e.g.,
simulations and observations). In TL, selected layers of a NN, already trained
for a base system, are re-trained using a small dataset from a target system.
For effective TL, we need to know 1) what are the best layers to re-train? and
2) what physics are learned during TL? Here, we present novel analyses and a
new framework to address (1)-(2) for a broad range of multi-scale, nonlinear
systems. Our approach combines spectral analyses of the systems' data with
spectral analyses of convolutional NN's activations and kernels, explaining the
inner-workings of TL in terms of the system's nonlinear physics. Using
subgrid-scale modeling of several setups of 2D turbulence as test cases, we
show that the learned kernels are combinations of low-, band-, and high-pass
filters, and that TL learns new filters whose nature is consistent with the
spectral differences of base and target systems. We also find the shallowest
layers are the best to re-train in these cases, which is against the common
wisdom guiding TL in machine learning literature. Our framework identifies the
best layer(s) to re-train beforehand, based on physics and NN theory. Together,
these analyses explain the physics learned in TL and provide a framework to
guide TL for wide-ranging applications in science and engineering, such as
climate change modeling.


  Provenance is a record that describes how entities, activities, and agents
have influenced a piece of data; it is commonly represented as graphs with
relevant labels on both their nodes and edges. With the growing adoption of
provenance in a wide range of application domains, users are increasingly
confronted with an abundance of graph data, which may prove challenging to
process. Graph kernels, on the other hand, have been successfully used to
efficiently analyse graphs. In this paper, we introduce a novel graph kernel
called provenance kernel, which is inspired by and tailored for provenance
data. It decomposes a provenance graph into tree-patterns rooted at a given
node and considers the labels of edges and nodes up to a certain distance from
the root. We employ provenance kernels to classify provenance graphs from three
application domains. Our evaluation shows that they perform well in terms of
classification accuracy and yield competitive results when compared against
existing graph kernel methods and the provenance network analytics method while
more efficient in computing time. Moreover, the provenance types used by
provenance kernels also help improve the explainability of predictive models
built on them.


  The space-time symmetry of noncommutative quantum field theories with a
deformed quantization is described by the twisted Poincar\'e algebra, while
that of standard commutative quantum field theories is described by the
Poincar\'e algebra. Based on the equivalence of the deformed theory with a
commutative field theory, the correspondence between the twisted Poincar\'e
symmetry of the deformed theory and the Poincar\'e symmetry of a commutative
theory is established. As a by-product, we obtain the conserved charge
associated with the twisted Poincar\'e transformation to make the twisted
Poincar\'e symmetry evident in the deformed theory. Our result implies that the
equivalence between the commutative theory and the deformed theory holds in a
deeper level, i.e., it holds not only in correlation functions but also in
(different types of) symmetries.


  According to the "Hilbert Space Fundamentalism" Thesis, all features of a
physical system, including the 3D-space, a preferred basis, and factorization
into subsystems, uniquely emerge from the state vector and the Hamiltonian
alone. I give a simplified account of the proof from arXiv:2102.08620 showing
that such emerging structures cannot be both unique and physically relevant.


  This paper presents a system which can recognise hand poses & gestures from
the Indian Sign Language (ISL) in real-time using grid-based features. This
system attempts to bridge the communication gap between the hearing and speech
impaired and the rest of the society. The existing solutions either provide
relatively low accuracy or do not work in real-time. This system provides good
results on both the parameters. It can identify 33 hand poses and some gestures
from the ISL. Sign Language is captured from a smartphone camera and its frames
are transmitted to a remote server for processing. The use of any external
hardware (such as gloves or the Microsoft Kinect sensor) is avoided, making it
user-friendly. Techniques such as Face detection, Object stabilisation and Skin
Colour Segmentation are used for hand detection and tracking. The image is
further subjected to a Grid-based Feature Extraction technique which represents
the hand's pose in the form of a Feature Vector. Hand poses are then classified
using the k-Nearest Neighbours algorithm. On the other hand, for gesture
classification, the motion and intermediate hand poses observation sequences
are fed to Hidden Markov Model chains corresponding to the 12 pre-selected
gestures defined in ISL. Using this methodology, the system is able to achieve
an accuracy of 99.7% for static hand poses, and an accuracy of 97.23% for
gesture recognition.


  We introduce quasi-invariant polynomials for an arbitrary finite complex
reflection group W. Unlike in the Coxeter case, the space Q_k of
quasi-invariants of a given multiplicity is not, in general, an algebra but a
module over the coordinate ring of some (singular) affine variety X_k. We
extend the main results of Etingof, Ginzburg and the first author (see [BEG])
to this setting: in particular, we show that the variety X_k and the module Q_k
are Cohen-Macaulay, and the rings of differential operators on X_k and Q_k are
simple rings, Morita equivalent to the Weyl algebra A_n(C), where n = dim X_k .
Our approach relies on representation theory of complex Cherednik algebras and
is parallel to that of [BEG]. As a by-product, we prove the existence of shift
operators for an arbitrary complex reflection group, confirming a conjecture of
Dunkl and Opdam. Another result is a proof of a conjecture of Opdam, concerning
certain operations (KZ twists) on the set of irreducible representations of W.


  E infinity ring spectra were defined in 1972, but the term has since acquired
several alternative meanings. The same is true of several related terms. The
new formulations are not always known to be equivalent to the old ones and even
when they are, the notion of "equivalence" needs discussion: Quillen equivalent
categories can be quite seriously inequivalent. Part of the confusion stems
from a gap in the modern resurgence of interest in E infinity structures. E
infinity ring spaces were also defined in 1972 and have never been redefined.
They were central to the early applications and they tie in implicitly to
modern applications. We summarize the relationships between the old notions and
various new ones, explaining what is and is not known. We take the opportunity
to rework and modernize many of the early results. New proofs and perspectives
are sprinkled throughout.


  We present a method of constructing monoidal, braided monoidal, and symmetric
monoidal bicategories from corresponding types of monoidal double categories
that satisfy a lifting condition. Many important monoidal bicategories arise
naturally in this way, and applying our general method is much easier than
explicitly verifying the coherence laws of a monoidal bicategory for each
example. Abstracting from earlier work in this direction, we express the
construction as a functor between locally cubical bicategories that preserves
monoid objects; this ensures that it also preserves monoidal functors,
transformations, adjunctions, and so on. Examples include the monoidal
bicategories of algebras and bimodules, categories and profunctors, sets and
spans, open Markov processes, parametrized spectra, and various functors
relating them.


  We present ab initio results for the electron-phonon interaction of the
\Gamma-point phonons in the tetragonal high-temperature phase of La2CuO4.
Eigenfrequencies and eigenvectors for the symmetry-allowed phonon modes are
calculated with the full-potential augmented plane wave+local orbitals method
using the frozen phonon approach. It is found that the \Gamma-point phonons
with the strongest electron-phonon interaction are the A{2u} modes with 236
cm^{-1}, 131 cm^{-1} and 476 cm^{-1}. To take effect of strong electron on-site
interaction into account we use generalized tight-binding method that results
in the interaction of phonons with Hubbard fermions forming quasiparticle's
band structure. Finally, the matrix elements of Hubbard fermion-phonon
interaction and their reduction due to strong electron correlation are
obtained.


  Updated standard model predictions for $D_{(s)} \to P l^+ l^-$, $l=e,\mu$,
$P=\pi,K$ and inclusive decays are presented. Model-independent constraints on
$|\Delta C|=|\Delta U|=1$ Wilson coefficients are worked out. New physics (NP)
opportunities arise in semileptonic branching ratios for very large couplings
only, however, are not excluded outside the resonance regions yet. The NP
potential of resonance-assisted CP asymmetries and angular observables is
worked out. Predictions are given for leptoquark models, and include lepton
flavor violating and dineutrino decays. Whether NP can be seen depends on
flavor patterns, and vice versa.


  In models with an enhanced coupling of the Higgs boson to the bottom quark,
the dominant production mechanism in hadronic collisions is often the partonic
sub-process, bg ->bH. We derive the weak corrections to this process and show
that they can be accurately approximated by an "Improved Born Approximation".
At the Tevatron, these corrections are negligible and are dwarfed by PDF and
scale uncertainties for M_H < 200 GeV. At the LHC, the weak corrections are
small for M_H < 500 GeV. For large Higgs boson masses, the corrections become
significant, and are ~18% for M_H ~ 1 TeV at E_CM=10 TeV.


  Most work on manipulation assumes that all preferences are known to the
manipulators. However, in many settings elections are open and sequential, and
manipulators may know the already cast votes but may not know the future votes.
We introduce a framework, in which manipulators can see the past votes but not
the future ones, to model online coalitional manipulation of sequential
elections, and we show that in this setting manipulation can be extremely
complex even for election systems with simple winner problems. Yet we also show
that for some of the most important election systems such manipulation is
simple in certain settings. This suggests that when using sequential voting,
one should pay great attention to the details of the setting in choosing one's
voting rule. Among the highlights of our classifications are: We show that,
depending on the size of the manipulative coalition, the online manipulation
problem can be complete for each level of the polynomial hierarchy or even for
PSPACE. We obtain the most dramatic contrast to date between the
nonunique-winner and unique-winner models: Online weighted manipulation for
plurality is in P in the nonunique-winner model, yet is coNP-hard (constructive
case) and NP-hard (destructive case) in the unique-winner model. And we obtain
what to the best of our knowledge are the first P^NP[1]-completeness and
P^NP-completeness results in the field of computational social choice, in
particular proving such completeness for, respectively, the complexity of
3-candidate and 4-candidate (and unlimited-candidate) online weighted coalition
manipulation of veto elections.


  Taxonomies consist of machine-interpretable semantics and provide valuable
knowledge for many web applications. For example, online retailers (e.g.,
Amazon and eBay) use taxonomies for product recommendation, and web search
engines (e.g., Google and Bing) leverage taxonomies to enhance query
understanding. Enormous efforts have been made on constructing taxonomies
either manually or semi-automatically. However, with the fast-growing volume of
web content, existing taxonomies will become outdated and fail to capture
emerging knowledge. Therefore, in many applications, dynamic expansions of an
existing taxonomy are in great demand. In this paper, we study how to expand an
existing taxonomy by adding a set of new concepts. We propose a novel
self-supervised framework, named TaxoExpan, which automatically generates a set
of <query concept, anchor concept> pairs from the existing taxonomy as training
data. Using such self-supervision data, TaxoExpan learns a model to predict
whether a query concept is the direct hyponym of an anchor concept. We develop
two innovative techniques in TaxoExpan: (1) a position-enhanced graph neural
network that encodes the local structure of an anchor concept in the existing
taxonomy, and (2) a noise-robust training objective that enables the learned
model to be insensitive to the label noise in the self-supervision data.
Extensive experiments on three large-scale datasets from different domains
demonstrate both the effectiveness and the efficiency of TaxoExpan for taxonomy
expansion.


  We study axion cosmology in a 5D Universe, in the case of flat and warped
extra dimension. The comparison between theoretical predictions and
observations constrains the 5D axion decay constant and the 5D Planck mass,
which has to be taken into account in building 5D axion models. The framework
developed in this paper can be readily applied to other bulk fields in brane
universes.


  In this paper, we study the low regularity convergence problem for the
intermediate long wave equation (ILW), with respect to the depth parameter
$\delta>0$, on the real line and the circle. As a natural bridge between the
Korteweg-de Vries (KdV) and the Benjamin-Ono (BO) equations, the ILW equation
is of physical interest. We prove that the solutions of ILW converge in the
$H^s$-Sobolev space for $s>\frac12$, to those of BO in the deep-water limit (as
$\delta\to\infty$), and to those of KdV in the shallow-water limit (as
$\delta\to 0$). This improves previous convergence results by Abdelouhab, Bona,
Felland, and Saut (1989), which required $s>\frac32$ in the deep-water limit
and $s\geq2$ in the shallow-water limit. Moreover, the convergence results also
apply to the generalised ILW equation, i.e.~with nonlinearity $\partial_x
(u^k)$ for $k\geq 2$. Furthermore, this work gives the first convergence
results of generalised ILW solutions on the circle with regularity $s\geq
\frac34$. Overall, this study provides mathematical insights for the behaviour
of the ILW equation and its solutions in different water depths, and has
implications for predicting and modelling wave behaviour in various
environments.


  A search for centrally produced charmonium states has been presented. There
is no significant evidence for any charmonium production. An upper limit of 2
nb is found for the cross section of chic production using the decay chic(1P)->
J/psi gamma.


  Sunspots harboring umbrae of both magnetic polarities within a common
penumbra (delta-spots) are often but not always related to flares. We present
first near-infrared (NIR) observations (Fe I 1078.3 nm and Si I 1078.6 nm
spectra) obtained with the Tenerife Infrared Polarimeter (TIP) at the Vacuum
Tower Telescope (VTT) in Tenerife on 2012 June 17, which afford accurate and
sensitive diagnostics to scrutinize the complex fields along the magnetic
neutral line of a delta-spot within active region NOAA 11504. We examine the
vector magnetic field, line-of-sight (LOS) velocities, and horizontal proper
motions of this rather inactive delta-spot. We find a smooth transition of the
magnetic vector field from the main umbra to that of opposite polarity
(delta-umbra), but a discontinuity of the horizontal magnetic field at some
distance from the delta-umbra on the polarity inversion line. The magnetic
field decreases faster with height by a factor of two above the delta-umbra.
The latter is surrounded by its own Evershed flow. The Evershed flow coming
from the main umbra ends at a line dividing the spot into two parts. This line
is marked by the occurrence of central emission in the Ca II 854.2 nm line.
Along this line, high chromospheric LOS-velocities of both signs appear. We
detect a shear flow within the horizontal flux transport velocities parallel to
the dividing line.


  Myriad viruses use positive-strand RNA molecules as their genomes. Far from
being only a repository of genetic material, viral RNA performs numerous other
functions mediated by its physical structure and chemical properties. In this
chapter, we focus on its structure and discuss how long RNA molecules can be
treated as branched polymers through planar graphs. We describe the major
results that can be obtained by this approach, in particular the observation
that viral RNA genomes have a characteristic compactness that sets them aside
from similar random RNAs. We also discuss how different parameters used in the
current RNA folding software influence the resulting structures and how they
can be related to experimentally observable quantities. Finally, we show how
the connection to branched polymers can be extended to take advantage of known
results from polymer physics and can be further moulded to include additional
interactions, such as excluded volume or electrostatics.


  During the past few years, secure detections of cosmic shear have been
obtained, manifest in the correlation of the observed ellipticities of
galaxies. Constraints have already been placed on cosmological parameters, such
as the normalisation of the matter power spectrum sigma_8. One possible
systematic contaminant of the lensing correlation signal arises from intrinsic
galaxy alignment, which is still poorly constrained. Unlike lensing, intrinsic
correlations only pertain to galaxies with small physical separations, the
correlation length being a few Mpc. We present a new method that harnesses this
property, and isolates the lensing and intrinsic components of the galaxy
ellipticity correlation function using measurements between different redshift
slices. The observed signal is approximated by a set of template functions,
making no strong assumptions about the amplitude or correlation length of any
intrinsic alignment. We also show that the near-degeneracy between the matter
density parameter Omega_m and sigma_8 can be lifted using correlation function
tomography, even in the presence of an intrinsic alignment signal.


  We investigate the scale-dependence of Eulerian volume averages of scalar
functions on Riemannian three-manifolds. We propose a complementary view of a
Lagrangian scaling of variables as opposed to their Eulerian averaging on
spatial domains. This program explains rigorously the origin of the Ricci
deformation flow for the metric, a flow which, on heuristic grounds, has been
already suggested as a possible candidate for averaging the initial data set
for cosmological spacetimes.


  Context: The detection of the diffuse supernova neutrino background may be
imminent, but theoretical predictions are affected by substantial
uncertainties. AIMS. We calculate the signal and its uncertainty with the
present configuration of Super-Kamiokande and consider the possibility of
lowering the threshold by means of gadolinium loading. Methods: We model
neutrino emission following the analysis of SN1987A by Pagliaroli and
collaborators 2009 and use the number of expected events in the neutrino
detector as a free parameter of the fit. The best-fit value of this parameter
and its error are evaluated by means of standard maximum likelihood procedures,
taking into account properly the correlations. Results: The uncertainties in
the astrophysics of the emission dominates the total uncertainty in the
expected signal rate, which conservatively ranges from 0.3 to 0.9 events per
year and from 1.1 to 2.9 with gadolinium.


  A fairly uniform cosmic-ray (CR) distribution is observed near the Sun,
except in the nearby Eridu cloud, which shows an unexplained 30-50% deficit in
GeV to TeV CR flux. To explore the origin of this deficit, we studied the
Reticulum cloud, which shares notable traits with Eridu: a comparable distance
in the low-density region of the Local Valley and a filamentary structure of
atomic hydrogen extending along ordered magnetic-field lines that are steeply
inclined to the Galactic plane. Using 14 years of Fermi-LAT data in the 0.16 to
63 GeV energy band, we found that the gamma-ray emissivity in the Reticulum
cloud is fully consistent with the average spectrum measured in the solar
neighbourhood, but this emissivity, and therefore the CR flux, is 1.57 $\pm$
0.09 times larger than in Eridu across the whole energy band. The difference
cannot be attributed to uncertainties in gas mass. Nevertheless, we find that
the two clouds are similar in many respects at a parsec scale: both have
magnetic-field strengths of a few micro-Gauss in the plane of the sky; both are
in approximate equilibrium between magnetic and thermal pressures; they have
similar turbulent velocities and sonic Mach numbers; and both show
magnetic-field regularity with a dispersion in orientation lower than 10-15
degrees over large zones. The gas in Reticulum is colder and denser than in
Eridu, but we find similar parallel diffusion coefficients around a few times
1e28 cm2/s in both clouds if CRs above 1 GV in rigidity diffuse on resonant,
self-excited Alfv\'en waves that are damped by ion-neutral interactions. The
loss of CRs in Eridu remains unexplained, but these two clouds provide
important test cases to further study how magnetic turbulence, line tangling,
and ion-neutral damping regulate CR diffusion in the dominant gas phase of the
interstellar medium.


  We investigate the choice of stellar population for use as the Astrometric
Grid for the Space Interferometry Mission (SIM). SIM depends on the astrometric
stability of about 2000 stars, the so called Grid, against which the science
measures are referenced. Low metallicity, and thus relatively high luminosity K
giants are shown to be the population of choice, when available. The
alternative, nearby G dwarfs, are shown to be suseptable to unmodeled motions
induced by gas-giant planetary companions, should there be a significant
population of such companions.
  Radial velocity filtering is quite efficient in selecting Grid members from
the K giants with yields exceeding 50% if filtering at 30m/s (1-sigma) is
available. However if the binary fraction of the G dwarfs approaches 100% as
some studies suggest, the yield of stable systems would be in the range of 15%
at best (with 10m/s filtering). Use of the initial SIM measurement as a final
filter is shown not to be critical in either case, although it could improve
the yield of stable grid members.
  For a Grid composed of weak-lined K giants, the residual contamination by
large unmodeled motions will amount to about 3% (and rises to about 6% if a
60m/s radial velocity criterion is used). The selective introduction of
quadratic terms in the proper motion solutions during the post-mission phase of
data reduction can reduce contamination to a remarkable 1% or better in either
case.
  Analytic estimates based on circular orbits are developed which show how
these results come about.


  General-purpose robots coexisting with humans in their environment must learn
to relate human language to their perceptions and actions to be useful in a
range of daily tasks. Moreover, they need to acquire a diverse repertoire of
general-purpose skills that allow composing long-horizon tasks by following
unconstrained language instructions. In this paper, we present CALVIN
(Composing Actions from Language and Vision), an open-source simulated
benchmark to learn long-horizon language-conditioned tasks. Our aim is to make
it possible to develop agents that can solve many robotic manipulation tasks
over a long horizon, from onboard sensors, and specified only via human
language. CALVIN tasks are more complex in terms of sequence length, action
space, and language than existing vision-and-language task datasets and
supports flexible specification of sensor suites. We evaluate the agents in
zero-shot to novel language instructions and to novel environments and objects.
We show that a baseline model based on multi-context imitation learning
performs poorly on CALVIN, suggesting that there is significant room for
developing innovative agents that learn to relate human language to their world
models with this benchmark.


  We have considered the star formation properties of 1616 isolated galaxies
from the 2MASS XSC selected sample (2MIG) with the FUV GALEX magnitudes. This
sample was then compared with corresponding properties of isolated galaxies
from the Local Orphan Galaxies catalogue (LOG) and paired galaxies.
  We found that different selection algorithms define different populations of
isolated galaxies. The population of the LOG catalogue, selected from
non-clustered galaxies in the Local Supercluster volume, mostly consists of
low-mass spiral and late type galaxies. The SSFR upper limit in isolated and
paired galaxies does not exceed the value of ~dex(-9.4). This is probably
common for galaxies of differing activity and environment (at least at z<0.06).
The fractions of quenched galaxies are nearly twice as high in the paired
galaxy sample as in the 2MIG isolated galaxy sample. From the behaviour of
(S)SFR vs. M_* relations we deduced that the characteristic value influencing
evolutionary processes is the galaxy mass. However the environmental influence
is notable: paired massive galaxies with logM_*>11.5 have higher (S)SFR than
isolated galaxies. Our results suggest that the environment helps to trigger
the star formation in the highest mass galaxies. We found that the fraction of
AGN in the paired sample is only a little higher than in our isolated galaxy
sample. We assume that AGN phenomenon is probably defined by secular galaxy
evolution.


  In this paper we provide a new inequality useful for the proofs of strong
converse theorems in the multiterminal information theory. We apply this
inequality to the recent work by Tyagi and Watanabe on the strong converse
theorem for the Wyner-Ziv source coding problem to obtain a new strong converse
outer bound. This outer bound deviates from the Wyner-Ziv rate distortion
region with the order $O\left(\frac{1}{\sqrt{n}}\right)$ on the length $n$ of
source outputs.


  It is shown that the problem of the recursive restoration of the
Slavnov-Taylor (ST) identities at the quantum level for anomaly-free gauge
theories is equivalent to the problem of parameterizing the local approximation
to the quantum effective action in terms of ST functionals, associated with the
cohomology classes of the classical linearized ST operator. The ST functionals
of dimension <=4 correspond to the invariant counterterms, those of dimension
>4 generate the non-symmetric counterterms upon projection on the action-like
sector. At orders higher than one in the loop expansion there are additional
contributions to the non-invariant counterterms, arising from known lower order
terms. They can also be parameterized by using the ST functionals. We apply the
method to Yang-Mills theory in the Landau gauge with an explicit mass term
introduced in a BRST-invariant way via a BRST doublet. Despite being
non-unitary, this model provides a good example where the method devised in the
paper can be applied to derive the most general solution for the action-like
part of the quantum effective action, compatible with the fulfillment of the ST
identities and the other relevant symmetries of the model, to all orders in the
loop expansion. The full dependence of the solution on the normalization
conditions is given.


  Turbulent mixing layers in nature are often characterized by the presence of
a mean shear and an unstable buoyancy gradient between two streams of different
velocity. Depending on the relative strength of shear versus buoyancy, either
the former or the latter may dominate the turbulence and mixing between the two
streams. In this paper, we present a phenomenological theory that leads to the
identification of two distinct turbulent regimes: an early regime, dominated by
the mean shear, and a later regime dominated by the buoyancy. The main
theoretical result consists of the identification of a cross-over time-scale
that discerns between the shear- and the buoyancy-dominated turbulence. This
cross-over time depends on three large-scale constants of the flow, namely the
buoyancy difference, the velocity difference between the two streams, and the
gravitational acceleration. We validate our theory against direct numerical
simulations (DNSs) of a temporal turbulent mixing layer compounded with an
unstable stratification. We observe that the cross-over time correctly predicts
the transition from shear to buoyancy driven turbulence, in terms of turbulent
kinetic energy production, energy spectra scaling and mixing layer thickness.


  We report the first observation of the radiative charm decay $D^0 \to \rho^0
\gamma$ and the first search for $CP$ violation in decays $D^0 \to \rho^0
\gamma$, $\phi\gamma$, and $\overline{K}{}^{*0} \gamma$, using a data sample of
943 fb$^{-1}$ collected with the Belle detector at the KEKB asymmetric-energy
$e^+e^-$ collider. The branching fraction is measured to be $\mathcal{B}(D^0
\to \rho^0 \gamma)=(1.77 \pm 0.30 \pm 0.07) \times 10^{-5}$, where the first
uncertainty is statistical and the second is systematic. The obtained $CP$
asymmetries, $\mathcal{A}_{CP}(D^0 \to \rho^0 \gamma)=+0.056 \pm 0.152 \pm
0.006$, $\mathcal{A}_{CP}(D^0 \to \phi \gamma)=-0.094 \pm 0.066 \pm 0.001$, and
$\mathcal{A}_{CP}(D^0 \to \overline{K}{}^{*0} \gamma)=-0.003 \pm 0.020 \pm
0.000$, are consistent with no $CP$ violation. We also present an improved
measurement of the branching fractions $\mathcal{B}(D^0 \to \phi \gamma)=(2.76
\pm 0.19 \pm 0.10) \times 10^{-5}$ and $\mathcal{B}(D^0 \to \overline{K}{}^{*0}
\gamma)=(4.66 \pm 0.21 \pm 0.21) \times 10^{-4}$.


  Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented
performance in response generation, especially with visual inputs, enabling
more creative and adaptable interaction than large language models such as
ChatGPT. Nonetheless, multimodal generation exacerbates safety concerns, since
adversaries may successfully evade the entire system by subtly manipulating the
most vulnerable modality (e.g., vision). To this end, we propose evaluating the
robustness of open-source large VLMs in the most realistic and high-risk
setting, where adversaries have only black-box system access and seek to
deceive the model into returning the targeted responses. In particular, we
first craft targeted adversarial examples against pretrained models such as
CLIP and BLIP, and then transfer these adversarial examples to other VLMs such
as MiniGPT-4, LLaVA, UniDiffuser, BLIP-2, and Img2Prompt. In addition, we
observe that black-box queries on these VLMs can further improve the
effectiveness of targeted evasion, resulting in a surprisingly high success
rate for generating targeted responses. Our findings provide a quantitative
understanding regarding the adversarial vulnerability of large VLMs and call
for a more thorough examination of their potential security flaws before
deployment in practice. Code is at https://github.com/yunqing-me/AttackVLM.


  In this review (124 refs), several problems in radiolysis of saturated
hydrocarbons are examined. Special attention is paid to the chemistry of
radical cations, high-mobility holes, excited state and spur dynamics, magnetic
field and spin effects, and optically detected magnetic resonance spectroscopy.


  The seeding of vortex domain walls in V-shaped nanowires by a magnetic field
has been investigated via simulations and Scanning Electron Microscopy with
Polarization Analysis (SEMPA). It is found that the orientation of the magnetic
field can be used to purposely tune the chirality, polarity and position of
single vortex domain walls in soft magnetic nanowires.


  Providing functionalities that allow online social network users to manage in
a secure and private way the publication of their information and/or resources
is a relevant and far from trivial topic that has been under scrutiny from
various research communities. In this work, we provide a framework that allows
users to define highly expressive access policies to their resources in a way
that the enforcement does not require the intervention of a (trusted or not)
third party. This is made possible by the deployment of a newly defined
cryptographic primitives that provides - among other things - efficient access
revocation and access policy privacy. Finally, we provide an implementation of
our framework as a Facebook application, proving the feasibility of our
approach.


  Theoretical arguments along with observational data of YSO jets suggest the
presence of two steady components: a disk wind type outflow needed to explain
the observed high mass loss rates and a stellar wind type outflow probably
accounting for the observed stellar spin down.
  Each component's contribution depends on the intrinsic physical properties of
the YSO-disk system and its evolutionary stage. The main goal of this paper is
to understand some of the basic features of the evolution, interaction and
co-existence of the two jet components over a parameter space and when time
variability is enforced. Having studied separately the numerical evolution of
each type of the complementary disk and stellar analytical wind solutions in
Paper I of this series, we proceed here to mix together the two models inside
the computational box. The evolution in time is performed with the PLUTO code,
investigating the dynamics of the two-component jets, the modifications each
solution undergoes and the potential steady state reached.


  Polymer nanocomposites (PNCs) offer a broad range of thermophysical
properties that are linked to their compositions. However, it is challenging to
establish a universal composition-property relation of PNCs due to their
enormous composition and chemical space. Here, we address this problem and
develop a new method to model the composition-microstructure relation of a PNC
through an intelligent machine learning pipeline named nanoNET. The nanoNET is
a nanoparticles (NPs) distribution predictor, built upon computer vision and
image recognition concepts. It integrates unsupervised deep learning and
regression in a fully automated pipeline. We conduct coarse-grained molecular
dynamics simulations of PNCs and utilize the data to establish and validate the
nanoNET. Within this framework, a random forest regression model predicts the
NPs distribution in a PNC in a latent space. Subsequently, a convolutional
neural network-based decoder converts the latent space representation to the
actual radial distribution function (RDF) of NPs in the given PNC. The nanoNET
predicts NPs distribution in many unknown PNCs very accurately. This method is
very generic and can accelerate the design, discovery, and fundamental
understanding of composition-microstructure relations of PNCs and other
molecular systems.


  The stability of the phase difference between two white-light continua,
generated from the same 180-fs pulses at 1035\,nm, is assessed by a modified
Bellini-Hansch interferometer. Mutual spectral stability is studied as a
function of several parameters: position of the nonlinear crystal with respect
to the beam waist, interaction length, and pulse energy. Intensity-to-phase
coupling coefficients are measured and stability regions are identified.


  In many applications of deep learning, particularly those in image
restoration, it is either very difficult, prohibitively expensive, or outright
impossible to obtain paired training data precisely as in the real world. In
such cases, one is forced to use synthesized paired data to train the deep
convolutional neural network (DCNN). However, due to the unavoidable
generalization error in statistical learning, the synthetically trained DCNN
often performs poorly on real world data. To overcome this problem, we propose
a new general training method that can compensate for, to a large extent, the
generalization errors of synthetically trained DCNNs.


  We consider a U(1) x SU(2) gauge theory on the four-dimensional manifold S^1
x S^3. If we make the assumption that only gauge transformations connected to
the identity are allowed, the winding numbers of U(1) around S^1 and of SU(2)
around S^3 become topological conserved quantities. We derive the effective
theory for non-trivial winding numbers if all distances are small compared to
the radii of the spheres. In the non-abelian case the gauge bosons become
massive.


  We study the computational complexity of the graph modification problems
Threshold Editing and Chain Editing, adding and deleting as few edges as
possible to transform the input into a threshold (or chain) graph. In this
article, we show that both problems are NP-complete, resolving a conjecture by
Natanzon, Shamir, and Sharan (Discrete Applied Mathematics, 113(1):109--128,
2001). On the positive side, we show the problem admits a quadratic vertex
kernel. Furthermore, we give a subexponential time parameterized algorithm
solving Threshold Editing in $2^{O(\surd k \log k)} + \text{poly}(n)$ time,
making it one of relatively few natural problems in this complexity class on
general graphs. These results are of broader interest to the field of social
network analysis, where recent work of Brandes (ISAAC, 2014) posits that the
minimum edit distance to a threshold graph gives a good measure of consistency
for node centralities. Finally, we show that all our positive results extend to
the related problem of Chain Editing, as well as the completion and deletion
variants of both problems.


  Integral field spectrographs are major instruments to study the mechanisms
involved in the formation and the evolution of early galaxies. When combined
with multi-object spectroscopy, those spectrographs can behave as machines used
to derive physical parameters of galaxies during their formation process. Up to
now, there is only one available spectrograph with multiple integral field
units, e.g. FLAMES/GIRAFFE on the VLT. However, current ground based
instruments suffer from a degradation of their spatial resolution due to
atmospheric turbulence. In this article we describe the performance of FALCON,
an original concept of a new generation multi-object integral field
spectrograph with adaptive optics for the ESO Very Large Telescope. The goal of
FALCON is to combine high angular resolution (0.25 arcsec) and high spectral
resolution (R > 5000) in J and H bands over a wide field of view (10x10
arcmin2) in the VLT Nasmyth focal plane. However, instead of correcting the
whole field, FALCON will use multi-object adaptive optics (MOAO) to perform
locally on each scientific target the adaptive optics correction. This requires
then to use atmospheric tomography in order to use suitable natural guide stars
for wavefront sensing. We will show that merging MOAO and atmospheric
tomography allows us to determine the internal kinematics of distant galaxies
up to z=2 with a sky coverage of 50%, even for objects observed near the
galactic pole. The application of such a concept to Extremely Large Telescopes
seems therefore to be a very promising way to study galaxy evolution from z = 1
to redshifts as high as z = 7.


  The phase structure of four-fermion theories is thoroughly investigated with
varying temperature and chemical potential for arbitrary space-time dimensions
$(2 \leq D < 4)$ by using the 1/N expansion method. It is shown that the chiral
symmetry is restored in the theory under consideration for sufficiently high
temperature and/or chemical potential. The critical line dividing the symmetric
and broken phase is given explicitly. It is found that for space-time dimension
$2 \leq D < 3$ both the first-order and second-order phase transition occur
depending on the value of temperature and chemical potential while for $3 \leq
D < 4$ only the second-order phase transition exists.


  Ubiquitous mobile computing have enabled ride-hailing services to collect
vast amounts of behavioral data of riders and drivers and optimize supply and
demand matching in real time. While these mobility service providers have some
degree of control over the market by assigning vehicles to requests, they need
to deal with the uncertainty arising from self-interested driver behavior since
workers are usually free to drive when they are not assigned tasks. In this
work, we formulate the problem of passenger-vehicle matching in a sparsely
connected graph and proposed an algorithm to derive an equilibrium policy in a
multi-agent environment. Our framework combines value iteration methods to
estimate the optimal policy given expected state visitation and policy
propagation to compute multi-agent state visitation frequencies. Furthermore,
we developed a method to learn the driver's reward function transferable to an
environment with significantly different dynamics from training data. We
evaluated the robustness to changes in spatio-temporal supply-demand
distributions and deterioration in data quality using a real-world taxi
trajectory dataset; our approach significantly outperforms several baselines in
terms of imitation accuracy. The computational time required to obtain an
equilibrium policy shared by all vehicles does not depend on the number of
agents, and even on the scale of real-world services, it takes only a few
seconds on a single CPU.


  Pressure Poisson equation (PPE) reformulations of the incompressible
Navier-Stokes equations (NSE) replace the incompressibility constraint by a
Poisson equation for the pressure and a suitable choice of boundary conditions.
This yields a time-evolution equation for the velocity field only, with the
pressure gradient acting as a nonlocal operator. Thus, numerical methods based
on PPE reformulations, in principle, have no limitations in achieving high
order. In this paper, it is studied to what extent high-order methods for the
NSE can be obtained from a specific PPE reformulation with electric boundary
conditions (EBC). To that end, implicit-explicit (IMEX) time-stepping is used
to decouple the pressure solve from the velocity update, while avoiding a
parabolic time-step restriction; and mixed finite elements are used in space,
to capture the structure imposed by the EBC. Via numerical examples, it is
demonstrated that the methodology can yield at least third order accuracy in
space and time.


  Different flavors of quantum pseudorandomness have proven useful for various
cryptographic applications, with the compelling feature that these primitives
are potentially weaker than post-quantum one-way functions. Ananth, Lin, and
Yuen (2023) have shown that logarithmic pseudorandom states can be used to
construct a pseudo-deterministic PRG: informally, for a fixed seed, the output
is the same with $1-1/poly$ probability.
  In this work, we introduce new definitions for $\bot$-PRG and $\bot$-PRF. The
correctness guarantees are that, for a fixed seed, except with negligible
probability, the output is either the same (with probability $1-1/poly$) or
recognizable abort, denoted $\bot$. Our approach admits a natural definition of
multi-time PRG security, as well as the adaptive security of a PRF. We
construct a $\bot$-PRG from any pseudo-deterministic PRG and, from that, a
$\bot$-PRF.
  Even though most mini-crypt primitives, such as symmetric key encryption,
commitments, MAC, and length-restricted one-time digital signatures, have been
shown based on various quantum pseudorandomness assumptions, digital signatures
remained elusive. Our main application is a (quantum) digital signature scheme
with classical public keys and signatures, thereby addressing a previously
unresolved question posed in Morimae and Yamakawa's work (Crypto, 2022).
Additionally, we construct CPA secure public-key encryption with
tamper-resilient quantum public keys.


  By using the existing sharp estimates of density function for rotationally
invariant symmetric $\alpha$-stable L\'{e}vy processes and rotationally
invariant symmetric truncated $\alpha$-stable L\'{e}vy processes, we obtain
that Harnack inequalities hold for rotationally invariant symmetric
$\alpha$-stable L\'{e}vy processes with $\alpha\in(0,2)$ and Ornstein-Uhlenbeck
processes driven by rotationally invariant symmetric $\alpha$-stable L\'{e}vy
process, while logarithmic Harnack inequalities are satisfied for rotationally
invariant symmetric truncated $\alpha$-stable L\'{e}vy processes.


  In a paper from 1954 Marstrand proved that if K is a Borel subset of the
plane with Hausdorff dimension greater than 1, then its one-dimensional
projection has positive Lebesgue measure for almost-all directions. In this
article, we give a new proof of this theorem, extending the techniques
developed in a previous work.


  In the open problem session of the FPSAC'03, R.P.Stanley gave an open
problem. The purpose of this paper is to give a proof of this open problem. At
the end of this paper we present certain corollaries involving the Big Schur
functions and some polynomials arising from the Macdonald polynomials, which
generalize Stanley's open problem.


  A series of new physics scenarios predict the existence of the extra charged
gauge boson $W'$, which can induce charged-current (CC) non-standard neutrino
interactions (NSIs). The theoretical constraints on the simplified $W'$ model
and further on the CC NSI parameters $\widetilde{\epsilon}^{
qq'Y}_{\alpha\beta}$ from partial wave unitarity and $W'$ decays are
considered. The sensitivity of the process $p p \rightarrow W'\rightarrow
\ell\nu $ to the $W'$ model at the LHC and high-luminosity~(HL) LHC experiments
is investigated by estimating the expected constraints on
$\widetilde{\epsilon}^{qq'Y}_{\alpha\beta}$ ($\alpha = \beta = e $ or $\mu$)
using a Monte-Carlo~(MC) simulation. We find that the interference effect plays
an important role, and the LHC can strongly constrain
$\widetilde{\epsilon}^{qq'L}_{\alpha\beta}$. Compared with those at the $13
\;{\rm TeV}$ LHC with $\mathcal{L}=139\;{\rm fb}^{-1}$, the expected
constraints at the $14 \;{\rm TeV}$ LHC with $\mathcal{L}=3\;{\rm ab}^{-1}$ can
be strengthened to approximately one order of magnitude.


  Recommender systems are popular in e-commerce as they suggest items of
interest to users. Researchers have addressed the cold-start problem where
either the user or the item is new. However, the situation with both new user
and new item has seldom been considered. In this paper, we propose a cold-start
recommendation approach to this situation based on granular association rules.
Specifically, we provide a means for describing users and items through
information granules, a means for generating association rules between users
and items, and a means for recommending items to users using these rules.
Experiments are undertaken on a publicly available dataset MovieLens. Results
indicate that rule sets perform similarly on the training and the testing sets,
and the appropriate setting of granule is essential to the application of
granular association rules.


  We derive Ginsparg-Wilson relation for a lattice chiral symmetry in theories
with self-interacting fermions. Auxiliary scalar and pseudo-scalar fields are
introduced on a coarse lattice to give an effective description of the
fermionic interactions. We obtain particular solutions to the Ginsparg-Wilson
relation and other
  Ward-Takahashi identities in a closed form. These non-perturbative solutions
can be used to construct a chiral invariant action and an invariant
path-integral measure on the coarse lattice. The resulting partition function
exhibits the exact chiral symmetry in the fermionic system with the auxiliary
fields.


  Human-robot collaborative applications require scene representations that are
kept up-to-date and facilitate safe motions in dynamic scenes. In this letter,
we present an interactive distance field mapping and planning (IDMP) framework
that handles dynamic objects and collision avoidance through an efficient
representation. We define interactive mapping and planning as the process of
creating and updating the representation of the scene online while
simultaneously planning and adapting the robot's actions based on that
representation. The key aspect of this work is an efficient Gaussian Process
field that performs incremental updates and handles dynamic objects reliably by
identifying moving points via a simple and elegant formulation based on queries
from a temporary latent model. In terms of mapping, IDMP is able to fuse point
cloud data from single and multiple sensors, query the free space at any
spatial resolution, and deal with moving objects without semantics. In terms of
planning, IDMP allows seamless integration with gradient-based reactive
planners facilitating dynamic obstacle avoidance for safe human-robot
interactions. Our mapping performance is evaluated on both real and synthetic
datasets. A comparison with similar state-of-the-art frameworks shows superior
performance when handling dynamic objects and comparable or better performance
in the accuracy of the computed distance and gradient field. Finally, we show
how the framework can be used for fast motion planning in the presence of
moving objects both in simulated and real-world scenes. An accompanying video,
code, and datasets are made publicly available https://uts-ri.github.io/IDMP.


  The X-ray data around the North Ecliptic Pole (NEP) of the ROSAT All Sky
Survey have been used to construct a contiguous area survey consisting of a
sample of 445 individual X-ray sources above a flux of ~2x10^-14 erg cm^-2 s^-1
in the 0.5-2.0 keV energy band. The NEP survey is centered at RA (2000) = 18h
00m, DEC(2000) = +66deg 33arcmin and covers a region of 80.7 sq. deg at a
moderate Galactic latitude of b = 29.8deg. Hence, the NEP survey is as deep and
covers a comparable solid angle to the ROSAT serendipitous surveys, but is also
contiguous. We have identified 99.6% of the sources and determined redshifts
for the extragalactic objects. In this paper we present the optical
identifications of the NEP catalog of X-ray sources including basic X-ray data
and properties of the sources. We also describe with some detail the optical
identification procedure. The classification of the optical counterparts to the
NEP sources is very similar to that of previous surveys, in particular the
Einstein Extended Medium Sensitivity Survey (EMSS). The main constituents of
the catalog are active galactic nuclei (~49%), either type 1 or type 2
according to the broadness of their permitted emission lines. Stellar
counterparts are the second most common identification class (~34%). Clusters
and groups of galaxies comprise 14%, and BL Lacertae objects 2%. One non-AGN
galaxy, and one planetary nebula have also been found. The NEP catalog of X-ray
sources is a homogeneous sample of astronomical objects featuring complete
optical identification.


  One of the main limitations for the resolution of optical instruments is the
size of the sensor's pixels. In this paper we introduce a new sub pixel
resolution algorithm to enhance the resolution of images. This method is based
on the analysis of multi-images which are fast recorded during the fine
relative motion of image and pixel arrays of CCDs. It is shown that by applying
this method for a sample noise free image one will enhance the resolution with
order of error.


  Given a curve X of the form y^p = h(x) over a number field, one can use
descents to obtain explicit bounds on the Mordell-Weil rank of the Jacobian or
to prove that the curve has no rational points. We show how, having performed
such a descent, one can easily obtain additional information which may rule out
the existence of rational divisors on X of degree prime to p. This can yield
sharper bounds on the Mordell-Weil rank by demonstrating the existence of
nontrivial elements in the Shafarevich-Tate group. As an example we compute the
Mordell-Weil rank of the Jacobian of a genus 4 curve over Q by determining that
the 3-primary part of the Shafarevich-Tate group is isomorphic to Z/3 x Z/3.


  Extreme value theory is concerned with probabilistic and statistical
questions related to very high or very low values in sequences of random
variables and in stochastic processes. The subject has a rich mathematical
theory and also a long tradition of applications in a variety of areas. Among
many excellent books on the subject, Coles [2] while the book by concentrates
on data analysis and statistical inference for extremes. In this article, we
present a case study wherein we model annual maximum yearly rainfall data using
the generalized extreme value distribution. Also, we use R software for data
analysis and give the R codes in the appendix.


  \c{C}ukurova University Space Sciences and Solar Energy Research and
Application Center (UZAYMER) was founded in 1991. In this work, we present
current research in the fields of astronomy, astrophysics and solar energy and
the astronomical infrastructure of the center. In addition, the
astrometrological status of UZAYMER was investigated using long-term (20 years)
data from the AstroGIS database and moderate-term (7 years) measurements taken
from the meteorological station. Astronomical extinction coefficients, seeing
conditions and light pollution measurements of UZAYMER were also obtained.
Furthermore, the observation limits were determined for the UZAYMER 50 cm
telescope (UT50) and the observation efficiency was evaluated. UZAYMER has
reached a level that can support both national and international scientific
collaborations with its improved technical infrastructure and increased human
resources. With its annual number of clear nights, favorable weather conditions
and dark sky values, UZAYMER ranks 972 in Group A of the Suitability Index for
Astronomical Sites (SIAS) among the 2141 observatories.


  We present MCdevelop, a universal computer framework for developing and
exploiting the wide class of Stochastic Simulations (SS) software. This
powerful universal SS software development tool has been derived from a series
of scientific projects for precision calculations in high energy physics (HEP),
which feature a wide range of functionality in the SS software needed for
advanced precision Quantum Field Theory calculations for the past LEP
experiments and for the ongoing LHC experiments at CERN, Geneva. MCdevelop is a
"spin-off" product of HEP to be exploited in other areas, while it will still
serve to develop new SS software for HEP experiments. Typically SS involve
independent generation of large sets of random "events", often requiring
considerable CPU power. Since SS jobs usually do not share memory it makes them
easy to parallelize. The efficient development, testing and running in parallel
SS software requires a convenient framework to develop software source code,
deploy and monitor batch jobs, merge and analyse results from multiple parallel
jobs, even before the production runs are terminated. Throughout the years of
development of stochastic simulations for HEP, a sophisticated framework
featuring all the above mentioned functionality has been implemented. MCdevelop
represents its latest version, written mostly in C++ (GNU compiler gcc). It
uses Autotools to build binaries (optionally managed within the KDevelop 3.5.3
Integrated Development Environment (IDE) ). It uses the open-source ROOT
package for histogramming, graphics and the mechanism of persistency for the
C++ objects. MCdevelop helps to run multiple parallel jobs on any computer
cluster with NQS-type batch system.


  The tokenization of assets deployed to distributed ledger technology is
increasingly cited to revolutionize financial services by allowing
traditionally illiquid assets to be bought and sold on primary and secondary
markets increasing asset liquidity, transparency and reducing transaction
completion time. To realize these benefits it is important the token is
transferrable, that is, portable from one distributed ledger to another. In
this paper we survey current interoperability architectures and smart contract
languages, identifying factors affecting the portability of tokenized assets.
We propose a portability maturity model that can be used to help assess the
current state of technology and supporting market infrastructure.


  At equilibrium, thermodynamic and kinetic information can be extracted from
biomolecular energy landscapes by many techniques. However, while static,
ensemble techniques yield thermodynamic data, often only dynamic,
single-molecule techniques can yield the kinetic data that describes
transition-state energy barriers. Here we present a generalized framework based
upon dwell-time distributions that can be used to connect such static, ensemble
techniques with dynamic, single-molecule techniques, and thus characterize
energy landscapes to greater resolutions. We demonstrate the utility of this
framework by applying it to cryogenic electron microscopy (cryo-EM) and
single-molecule fluorescence resonance energy transfer (smFRET) studies of the
bacterial ribosomal pre-translocation complex. Among other benefits,
application of this framework to these data explains why two transient,
intermediate conformations of the pre-translocation complex, which are observed
in a cryo-EM study, may not be observed in several smFRET studies.


  Symmetries and conserved charges are investigated for linearised gravity and
its dual formulation in terms of the dual graviton field. Conserved charges are
constructed for the dual graviton theory as Noether charges associated with
invariances of the dual graviton. These invariances arise for gauge parameters
that are certain generalised Killing tensors. These electric-type charges for
the dual graviton are then shown to give magnetic-type charges for the
graviton. One of the magnetic-type gravitational charges obtained in this way
is the linearisation of the gravitational charge in $d\ge 5$ dimensions that
arises as a central charge in the supersymmetry algebra and is carried by
Kaluza-Klein monopoles. Solutions of linearised gravity carrying the magnetic
gravitational charges are discussed. The application of the approach used here
to other gauge theories is discussed.


  We analyzed the decays of $B^{+}\to {\bar {D}^0}+D^{+}_{sJ}(2S)$ and
$B^{+}\to\bar D^{0}+D^{+}_{sJ}(1D)$ by naive factorization method and model
dependent calculation based on the Bethe-Salpeter method, the branching ratios
are $Br({\bar {D}^0}D^{+}_{sJ}(2S))=(0.72\pm0.12)%$ and $Br({\bar
{D}^0}D^{+}_{sJ}(1D))=(0.027\pm0.007)%$. The branching ratio of decay $B^{+}\to
{\bar {D}^0}D^{+}_{sJ}(2S)\to {\bar {D}^0}D^0 K^+$ consist with the data of
Belle Collaboration, so we conclude that the new state $D^{+}_{sJ}(2700)$ is
the first excited state $D^{+}_{sJ}(2S)$.