  Microinstabilities exhibit a rich variety of behavior in stellarators due to
the many degrees of freedom in the magnetic geometry. It has recently been
found that certain stellarators (quasi-isodynamic ones with maximum-$J$
geometry) are partly resilient to trapped-particle instabilities, because
fast-bouncing particles tend to extract energy from these modes near marginal
stability. In reality, stellarators are never perfectly quasi-isodynamic, and
the question thus arises whether they still benefit from enhanced stability.
Here the stability properties of Wendelstein 7-X and a more quasi-isodynamic
configuration, QIPC, are investigated numerically and compared with the
National Compact Stellarator Experiment (NCSX) and the DIII-D tokamak. In
gyrokinetic simulations, performed with the gyrokinetic code GENE in the
electrostatic and collisionless approximation, ion-temperature-gradient modes,
trapped-electron modes and mixed-type instabilities are studied. Wendelstein
7-X and QIPC exhibit significantly reduced growth rates for all simulations
that include kinetic electrons, and the latter are indeed found to be
stabilizing in the energy budget. These results suggest that imperfectly
optimized stellarators can retain most of the stabilizing properties predicted
for perfect maximum-$J$ configurations.


  The main goal of the paper is to extract the aggregate demand and aggregate
supply shocks in Greece, Ireland, Italy and Portugal, as well as to examine the
correlation among the two types of shocks. The decomposition of the shocks was
achieved by using a structural vector autoregression that analyses the
relationship between the evolution of the gross domestic product and inflation
in the period 1997-2015. The goal of the paper is to confirm the aggregate
demand - aggregate supply model in the above-mentioned economies.


  In this work, we study the analytic properties of S-matrix for unstable
particles, which is defined as the residues on the unphysical sheets where
unstable poles reside. We demonstrate that anomalous thresholds associated with
UV physics are unavoidable for unstable particles. This is in contrast to
stable particles, where the anomalous thresholds are due to IR physics, set by
the scale of the external kinematics. As a result, any dispersive
representation for the amplitude will involve contributions from these
thresholds that are not computable from the IR theory, and thus invalidate the
general positivity bound. Indeed using toy models, we explicitly demonstrate
that the four-derivative couplings for unstable particles can become negative,
violating positivity bounds even for non-gravitational theories. Along the way,
we show that contributions from anomalous thresholds in a given channel can be
captured by the double discontinuity of that channel.


  Hard spherocylinders (cylinders of length $L$ and diameter $D$ capped at both
ends with two hemispheres) provide a suitable model for investigating
entropy-driven, mesophase formations in real colloidal fluids that are composed
of rigid rodlike molecules. We performed extensive Monte Carlo simulations of
this model fluid for elongations in the range $3 \leq L/D \leq 5$ and up to
$L/D = 20$, in order to investigate the relative importance of translational
and orientational correlations allowing for the emergence of nematic or smectic
order in the framework of the so-called residual multi-particle entropy (RMPE).
The vanishing of this quantity, which includes the re-summed contributions of
all spatial correlations involving more than two particles, signals the
structural changes which take place, at increasing densities, in the isotropic
fluid. We found that the ordering thresholds detected through the zero-RMPE
condition systematically correlate with the corresponding phase-transition
points, whatever the nature of the higher-density phase coexisting with the
isotropic fluid.


  We show that thresholds for fault-tolerant quantum computation are solely
determined by the quality of single-system operations if one allows for
d-dimensional systems with $8 \leq d \leq 32$. Each system serves to store one
logical qubit and additional auxiliary dimensions are used to create and purify
entanglement between systems. Physical, possibly probabilistic two-system
operations with error rates up to 2/3 are still tolerable to realize
deterministic high quality two-qubit gates on the logical qubits. The
achievable error rate is of the same order of magnitude as of the single-system
operations. We investigate possible implementations of our scheme for several
physical set-ups.


  Plasma-based parametric amplification using stimulated Brillouin scattering
offers a route to coherent x-ray pulses orders-of-magnitude more intense than
those of the brightest available sources. Brillouin amplification permits
amplification of shorter wavelengths with lower pump intensities than Raman
amplification, which Landau and collisional damping limit in the x-ray regime.
Analytic predictions, numerical solutions of the three-wave coupling equations,
and particle-in-cell simulations suggest that Brillouin amplification in
solid-density plasmas will allow compression of current x-ray free electron
laser pulses to sub-femtosecond durations and unprecedented intensities.


  We present Herschel dust continuum, James Clerk Maxwell Telescope CO(3-2)
observations and a search for [CII] 158 micron and [OI] 63 micron spectral line
emission for the brightest early-type dwarf satellite of Andromeda, NGC 205.
While direct gas measurements (Mgas ~ 1.5e+6 Msun, HI + CO(1-0)) have proven to
be inconsistent with theoretical predictions of the current gas reservoir in
NGC 205 (> 1e+7 Msun), we revise the missing interstellar medium mass problem
based on new gas mass estimates (CO(3-2), [CII], [OI]) and indirect
measurements of the interstellar medium content through dust continuum
emission. Based on Herschel observations, covering a wide wavelength range from
70 to 500 micron, we are able to probe the entire dust content in NGC 205
(Mdust ~ 1.1-1.8e+4 Msun at Tdust ~ 18-22 K) and rule out the presence of a
massive cold dust component (Mdust ~ 5e+5 Msun, Tdust ~ 12 K), which was
suggested based on millimeter observations from the inner 18.4 arcsec. Assuming
a reasonable gas-to-dust ratio of ~ 400, the dust mass in NGC 205 translates
into a gas mass Mgas ~ 4-7e+6 Msun. The non-detection of [OI] and the low
L_[CII]-to-L_CO(1-0) line intensity ratio (~ 1850) imply that the molecular gas
phase is well traced by CO molecules in NGC 205. We estimate an atomic gas mass
of 1.5e+4 Msun associated with the [CII] emitting PDR regions in NGC 205. From
the partial CO(3-2) map of the northern region in NGC 205, we derive a
molecular gas mass of M_H2 ~ 1.3e+5 Msun. [abridged]


  Spin qubits in quantum dots define an attractive platform for scalable
quantum information because of their compatibility with semiconductor
manufacturing, their long coherence times, and the ability to operate at
temperatures exceeding one Kelvin. Qubit logic can be implemented by pulsing
the exchange interaction or via driven rotations. Here, we show that these
approaches can be combined to execute a multitude of native two-qubit gates in
a single device, reducing the operation overhead to perform quantum algorithms.
We demonstrate, at a temperature above one Kelvin, single-qubit rotations
together with the two-qubit gates CROT, CPHASE and SWAP. Furthermore we realize
adiabatic, diabatic and composite sequences to optimize the qubit control
fidelity and the gate time. We find two-qubit gates that can be executed within
67 ns and by theoretically analyzing the experimental noise sources we predict
fidelities exceeding 99%. This promises fault-tolerant operation using quantum
hardware that can be embedded with classical electronics for quantum integrated
circuits.


  The equation of state for the pion gas is analyzed within the third virial
approximation. The second virial coefficient is found from the pion-pion-
scattering data, while the third one is considered as a free parameter. The
proposed model leads to a first-order phase transition from the pion gas to a
more dense phase at the temperature T_pt < 136 MeV. Due to relatively low
temperature this phase transition cannot be related to the deconfinement. This
suggests that a new phase of hadron matter - 'hot pion liquid' - may exist.


  We investigate temperature behavior up to two loop level in QED in the
background heat bath using real time formalism. The thermal correction to the
coupling constant in QED at low temperature are presented up to the two loop
level. It is observed that the removal of singularities at the two loop level
is only possible if the integrations of loop momenta are done in a specific
order. Some of the possible applications of the results are also indicated.


  In this paper, we give a relation between the Hilbert multiplicity and the
irreducible multiplicity. As an application, we characterize Ulrich modules in
term of the irreducible multiplicity.


  In the setting of finite reflection groups, we prove that the projection of a
Brownian motion onto a closed Weyl chamber is another Brownian motion normally
reflected on the walls of the chamber. Our proof is probabilistic and the
decomposition we obtain may be seen as a multidimensional extension of Tanaka's
formula for linear Brownian motion. The paper is closed with a description of
the boundary process through the local times at zero of the distances from the
initial process to the facets.


  Mixed communities of organisms are found in many environments (from the human
gut to marine ecosystems) and can have profound impact on human health and the
environment. Metagenomics studies the genomic material of such communities
through high-throughput sequencing that yields DNA subsequences for subsequent
analysis. A fundamental problem in the standard workflow, called binning, is to
discover clusters, of genomic subsequences, associated with the unknown
constituent organisms. Inherent noise in the subsequences, various biological
constraints that need to be imposed on them and the skewed cluster size
distribution exacerbate the difficulty of this unsupervised learning problem.
In this paper, we present a new formulation using a graph where the nodes are
subsequences and edges represent homophily information. In addition, we model
biological constraints providing heterophilous signal about nodes that cannot
be clustered together. We solve the binning problem by developing new
algorithms for (i) graph representation learning that preserves both homophily
relations and heterophily constraints (ii) constraint-based graph clustering
method that addresses the problems of skewed cluster size distribution.
Extensive experiments, on real and synthetic datasets, demonstrate that our
approach, called RepBin, outperforms a wide variety of competing methods. Our
constraint-based graph representation learning and clustering methods, that may
be useful in other domains as well, advance the state-of-the-art in both
metagenomics binning and graph representation learning.


  Municipal solid waste management (MSWM) is a challenging issue of urban
development in developing countries. Each country having different
socio-economic-environmental background, might not accept a particular disposal
method as the optimal choice. Selection of suitable disposal method in MSWM,
under vague and imprecise information can be considered as multi criteria
decision making problem (MCDM). In the present paper, TOPSIS (Technique for
Order Preference by Similarity to Ideal Solution) methodology is extended based
on credibility theory for evaluating the performances of MSW disposal methods
under some criteria fixed by experts. The proposed model helps decision makers
to choose a preferable alternative for their municipal area. A sensitivity
analysis by our proposed model confirms this fact.


  This entry for the SIGSPATIAL Special July 2010 issue on Similarity Searching
in Metric Spaces discusses the notion of intrinsic dimensionality of data in
the context of similarity search.


  We present a rapid and stain-free quantitative viral plaque assay using
lensfree holographic imaging and deep learning. This cost-effective, compact,
and automated device significantly reduces the incubation time needed for
traditional plaque assays while preserving their advantages over other virus
quantification methods. This device captures ~0.32 Giga-pixel/hour phase
information of the objects per test well, covering an area of ~30x30 mm^2, in a
label-free manner, eliminating staining entirely. We demonstrated the success
of this computational method using vesicular stomatitis virus (VSV), herpes
simplex virus (HSV-1) and encephalomyocarditis virus (EMCV). Using a neural
network, this stain-free device automatically detected the first cell lysing
events due to the VSV viral replication as early as 5 hours after the
incubation, and achieved >90% detection rate for the VSV plaque-forming units
(PFUs) with 100% specificity in <20 hours, providing major time savings
compared to the traditional plaque assays that take at least 48 hours.
Similarly, this stain-free device reduced the needed incubation time by ~48
hours for HSV-1 and ~20 hours for EMCV, achieving >90% detection rate with 100%
specificity. We also demonstrated that this data-driven plaque assay offers the
capability of quantifying the infected area of the cell monolayer, performing
automated counting and quantification of PFUs and virus-infected areas over a
10-fold larger dynamic range of virus concentration than standard viral plaque
assays. This compact, low-cost, automated PFU quantification device can be
broadly used in virology research, vaccine development, and clinical
applications.


  The ad-hoc querying process is slow and error prone due to inability of
business experts of accessing data directly without involving IT experts. The
problem lies in complexity of means used to query data. We propose a new
natural language- and semistar ontology-based ad-hoc querying approach which
lowers the steep learning curve required to be able to query data. The proposed
approach would significantly shorten the time needed to master the ad-hoc
querying and to gain the direct access to data by business experts, thus
facilitating the decision making process in enterprises, government
institutions and other organizations.


  The behaviour of like-charge and unlike-charge second factorial moments in
$e^+e^-$ reactions is discussed. It is argued that Monte Carlo calculation with
the help of generators JETSET 7.4 and HERWIG 5.8 points to the conclusion that
the only nontrivial cause of intermittency are Bose-Einstein correlations of
identical particles.


  Recently, large language models (LLMs) have expanded into various domains.
However, there remains a need to evaluate how these models perform when
prompted with commonplace queries compared to domain-specific queries, which
may be useful for benchmarking prior to fine-tuning domain-specific downstream
tasks. This study evaluates LLMs, specifically Gemma-2B and Gemma-7B, across
diverse domains, including cybersecurity, medicine, and finance, compared to
common knowledge queries. This study employs a comprehensive methodology to
evaluate foundational models, encompassing problem formulation, data analysis,
and the development of novel outlier detection techniques. This methodological
rigor enhances the credibility of the presented evaluation frameworks. This
study focused on assessing inference time, response length, throughput,
quality, and resource utilization and investigated the correlations between
these factors. The results indicate that model size and types of prompts used
for inference significantly influenced response length and quality. In
addition, common prompts, which include various types of queries, generate
diverse and inconsistent responses at irregular intervals. In contrast,
domain-specific prompts consistently generate concise responses within a
reasonable time. Overall, this study underscores the need for comprehensive
evaluation frameworks to enhance the reliability of benchmarking procedures in
multidomain AI research.


  MicroRNAs (miRNAs) are small non-coding RNAs which regulate gene expression
by binding to the 3' UTR of the corresponding messenger RNAs. We construct
miRNA co-target networks for 22 different species using a target prediction
database, MicroCosm Tagets. The miRNA pairs of individual species having one or
more common target genes are connected and the number of co-targets are
assigned as the weight of these links. We show that the link-weight
distributions of all the species collapse remarkably onto each other when
scaled suitably. It turns out that the scale-factor is a measure of complexity
of the species. A simple model, where targets are chosen randomly by miRNAs,
could provide the correct scaling function and explain the universality.


  The topology of the Internet has typically been measured by sampling
traceroutes, which are roughly shortest paths from sources to destinations. The
resulting measurements have been used to infer that the Internet's degree
distribution is scale-free; however, many of these measurements have relied on
sampling traceroutes from a small number of sources. It was recently argued
that sampling in this way can introduce a fundamental bias in the degree
distribution, for instance, causing random (Erdos-Renyi) graphs to appear to
have power law degree distributions. We explain this phenomenon analytically
using differential equations to model the growth of a breadth-first tree in a
random graph G(n,p=c/n) of average degree c, and show that sampling from a
single source gives an apparent power law degree distribution P(k) ~ 1/k for k
< c.


  The structure of the generic prioritary sheaf on the projective plane is
given, when it cannot be semi-stable


  We present four training and prediction schedules from the same
character-level recurrent neural network. The efficiency of these schedules is
tested in terms of model effectiveness as a function of training time and
amount of training data seen. We show that the choice of training and
prediction schedule potentially has a considerable impact on the prediction
effectiveness for a given training budget.


  Human skeleton point clouds are commonly used to automatically classify and
predict the behaviour of others. In this paper, we use a contrastive
self-supervised learning method, SimCLR, to learn representations that capture
the semantics of skeleton point clouds. This work focuses on systematically
evaluating the effects that different algorithmic decisions (including
augmentations, dataset partitioning and backbone architecture) have on the
learned skeleton representations. To pre-train the representations, we
normalise six existing datasets to obtain more than 40 million skeleton frames.
We evaluate the quality of the learned representations with three downstream
tasks: skeleton reconstruction, motion prediction, and activity classification.
Our results demonstrate the importance of 1) combining spatial and temporal
augmentations, 2) including additional datasets for encoder training, and 3)
and using a graph neural network as an encoder.


  A common metaphor for describing development is a rugged "epigenetic
landscape" where cell fates are represented as attracting valleys resulting
from a complex regulatory network. Here, we introduce a framework for
explicitly constructing epigenetic landscapes that combines genomic data with
techniques from spin-glass physics. Each cell fate is a dynamic attractor, yet
cells can change fate in response to external signals. Our model suggests that
partially reprogrammed cells are a natural consequence of high-dimensional
landscapes, and predicts that partially reprogrammed cells should be hybrids
that co-express genes from multiple cell fates. We verify this prediction by
reanalyzing existing datasets. Our model reproduces known reprogramming
protocols and identifies candidate transcription factors for reprogramming to
novel cell fates, suggesting epigenetic landscapes are a powerful paradigm for
understanding cellular identity.


  We construct \emph{intrinsic} metrics on the Strichartz hexacarpet using
weight functions and show that these metrics do \emph{not} satisfy the chain
condition. We give uniform Harnack inequality on the approximating graphs of
the Strichartz hexacarpet with respect to the intrinsic metrics instead of
graph metrics.


  Myxococcus xanthus cells self-organize into aligned groups, clusters, at
various stages of their lifecycle. Formation of these clusters is crucial for
the complex dynamic multi-cellular behavior of these bacteria. However, the
mechanism underlying the cell alignment and clustering is not fully understood.
Motivated by studies of clustering in self-propelled rods, we hypothesized that
M. xanthus cells can align and form clusters through pure mechanical
interactions among cells and between cells and substrate. We test this
hypothesis using an agent-based simulation framework in which each agent is
based on the biophysical model of an individual M. xanthus cell. We show that
model agents, under realistic cell flexibility values, can align and form cell
clusters but only when periodic reversals of cell directions are suppressed.
However, by extending our model to introduce the observed ability of cells to
deposit and follow slime trails, we show that effective trail-following leads
to clusters in reversing cells. Furthermore, we conclude that mechanical cell
alignment combined with slime-trail-following is sufficient to explain the
distinct clustering behaviors observed for wild-type and non-reversing M.
xanthus mutants in recent experiments. Our results are robust to variation in
model parameters, match the experimentally observed trends and can be applied
to understand surface motility patterns of other bacterial species.


  We use the benefits and components of classical computers every day. However,
there are many types of problems which, as they grow in size, their
computational complexity grows larger than classical computers will ever be
able to solve. Quantum computing (QC) is a computation model that uses quantum
physical properties to solve such problems. QC is at the early stage of
large-scale adoption in various industry domains to take advantage of the
algorithmic speed-ups it has to offer. It can be applied in a variety of areas,
such as computer science, mathematics, chemical and biochemical engineering,
and the financial industry. The main goal of this paper is to give an overview
to chemical and biochemical researchers and engineers who may not be familiar
with quantum computation. Thus, the paper begins by explaining the fundamental
concepts of QC. The second contribution this publication tries to tackle is the
fact that the chemical engineering literature still lacks a comprehensive
review of the recent advances of QC. Therefore, this article reviews and
summarizes the state of the art to gain insight into how quantum computation
can benefit and optimize chemical engineering issues. A bibliography analysis
covers the comprehensive literature in QC and analyzes quantum computing
research in chemical engineering on various publication topics, using Clarivate
analytics covering the years 1990 to 2020. After the bibliographic analysis,
relevant applications of QC in chemical and biochemical engineering are
highlighted and a conclusion offers an outlook of future directions within the
field.


  In this didactical note I review in depth the rationale for using generalised
canonical distributions in quantum statistics. Particular attention is paid to
the proper definitions of quantum entropy and quantum relative entropy, as well
as to quantum state reconstruction on the basis of incomplete data. There are
two appendices in which I outline how generalised canonical distributions link
to the conventional formulation of statistical mechanics, and how classical
probability calculus emerges at the macroscopic level.


  With the recent progresses on the Type II supernovae, we attempt to
investigate whether there does exist new physics beyond the standard
cosmological paradigm, i.e., the cosmological constant $\Lambda$ plus cold dark
matter ($\Lambda$CDM). Constraining four alternative cosmological models with a
data combination of currently available Type II supernovae calibrated by the
standard color method, Type Ia supernovae, baryon acoustic oscillations, cosmic
microwave background and cosmic chronometers, at the $1\sigma$ confidence
level, we find that: (i) a spatially flat universe is supported for the
non-flat $\Lambda$CDM model; (ii) the constrained equation of state of dark
energy $\omega$ is consistent with the $\Lambda$CDM hypothesis for the
$\omega$CDM model where $\omega$ is a free parameter; (iii) for the decaying
vacuum model, there is no evidence of interaction between dark matter and dark
energy in the dark sector of the universe; (iv) there is also no hint of
dynamical dark energy for the dark energy density-parametrization scenario. It
is very obvious that a larger Type II supernovae sample is required, if we
expect to draw definitive conclusions about the formation and evolution of the
universe.


  In this study, we build on previous research to understand the conditions
within which the Wisdom of the Crowd (WoC) improves or worsens as a result of
showing individuals the predictions of their peers. Our main novel
contributions are: 1) a dataset of unprecedented size and detail; 2) we observe
the novel effect of the importance of the unimodality of the social information
shown to individuals: if one does not see only one clear peak in the
distribution of the crowd's predictions, the WoC is worsened after social
exposure; and 3) we estimate social learning weights that we use to show that
there exists individuals who are much better at learning from the crowd and can
be filtered to improve collective accuracy.


  We investigate the effect of a magnetic field on the extended Kitaev spin
liquid state through phonon dynamics. Using a constrained fermionic
self-consistent mean-field method, we analyze the quantum spin liquid (QSL)
ground state for the extended Kitaev model with both the Zeeman term and the
perturbative three-spin interaction term $\kappa$. Our results demonstrate the
dependence of the stability of the Kitaev QSL state on the field direction,
consistent with findings in the literature. Additionally, we calculate the
phonon dynamics for acoustic phonons coupled to the Majorana fermion
excitations of the Kitaev spin liquid state, discussing the temperature and
field evolution of these quantities.


  This paper discusses multi-skyrmions on the 3-sphere with variable radius L
using the rational map ansatz. For baryon number B = 3,...,9 this ansatz
produces the lowest energy solutions known so far. By considering the geometry
of the model we find an approximate analytic formula for the shape function.
This provides an insight why skyrmions have a shell-like structure.


  We formally link the concept of steering (a concept created by Schrodinger
but only recently formalised by Wiseman, Jones and Doherty [Phys. Rev. Lett.
98, 140402 (2007)] and the criteria for demonstrations of
Einstein-Podolsky-Rosen (EPR) paradox introduced by Reid [Phys. Rev. A, 40, 913
(1989)]. We develop a general theory of experimental EPR-steering criteria,
derive a number of criteria applicable to discrete as well as
continuous-variables observables, and study their efficacy in detecting that
form of nonlocality in some classes of quantum states. We show that previous
versions of EPR-type criteria can be rederived within this formalism, thus
unifying these efforts from a modern quantum-information perspective and
clarifying their conceptual and formal origin. The theory follows in close
analogy with criteria for other forms of quantum nonlocality (Bell-nonlocality,
entanglement), and because it is a hybrid of those two, it may lead to insights
into the relationship between the different forms of nonlocality and the
criteria that are able to detect them.


  This research report summarizes the progress of work carried out jointly by
the IRCCyN and the \'Ecole Polytechnique de Montr\'eal about the resolution of
the inverse problem for the seismic imaging of transmission overhead line
structure foundations. Several methods aimed at mapping the underground medium
are considered. More particularly, we focus on methods based on a bilinear
formulation of the forward problem on one hand (CSI, modified gradient, etc.)
and on methods based on a "primal" formulation on the other hand. The
performances of these methods are compared using synthetic data. This work was
partially funded by RTE (R\'eseau de Transport d'\'Electricit\'e), which has
initiated the project, and was carried out in collaboration with EDF R&D
(\'Electricit\'e de France - Recherche et D\'eveloppement).


  In this survey one discusses the notion of the Poincar\'e series of
multi-index filtrations, an alternative approach to the definition, a method of
computation of the Poincar\'e series based on the notion of integration with
respect to the Euler characteristic (or rather on an infinite-dimensional
version of it), generalizations of the notion of the multi-variable Poincar\'e
series based on the notion of the motivic integration, and relations of the
latter ones with some zeta functions over finite fields and with generating
series of Heegaard-Floer homologies of algebraic links.


  Currently, flight delays are common and they propagate from an originating
flight to connecting flights, leading to large disruptions in the overall
schedule. These disruptions cause massive economic losses, affect airlines'
reputations, waste passengers' time and money, and directly impact the
environment. This study adopts a network science approach for solving the delay
propagation problem by modeling and analyzing the flight schedules and
historical operational data of an airline. We aim to determine the most
disruptive airports, flights, flight-connections, and connection types in an
airline network. Disruptive elements are influential or critical entities in an
airline network. They are the elements that can either cause (airline
schedules) or have caused (historical data) the largest disturbances in the
network. An airline can improve its operations by avoiding delays caused by the
most disruptive elements. The proposed network science approach for disruptive
element analysis was validated using a case study of an operating airline. The
analysis indicates that potential disruptive elements in a schedule of an
airline are also actual disruptive elements in the historical data and they
should be considered to improve operations. The airline network exhibits
small-world effects and delays can propagate to any part of the network with a
minimum of four delayed flights. Finally, we observed that passenger
connections between flights are the most disruptive connection type. Therefore,
the proposed methodology provides a tool for airlines to build robust flight
schedules that reduce delays and propagation.


  The properties of high latitude dust are of great interest to extragalactic
astronomers and cosmologists. It is proposed here that essentially all high
Galactic latitude interstellar dust is at a typical temperature of about 20~K
(i.e. it is warm dust) and that if any cold high latitude interstellar dust
exists, its emission at mm-wavelengths is less than 5\%\ of that from the
primary component of warm dust observed by IRAS. Thus the IRAS maps reveal the
high latitude dust of import. The crucial issue is how the emissivity of the
dust scales with wavelength. The mm-wavelength emission in this warm dust only
model is consistent with roughly a wavelength%, $\lambda$, dependent emissivity
$\epsilon(\lambda) \propto \lambda^{-1.5}$. Such a dependence has been observed
in the infrared previously. What is new here is the proposal that this extends
to the mm-wavelength region. Proceedings of Workshop on Molecules, Dust, &
Backgrounds to be published in Planetary & Space Sciences


  We extensively study long-time dynamics and fate of topologically-ordered
state in toric code model evolving through projective measurement-only circuit.
The circuit is composed of several measurement operators corresponding to each
term of toric code Hamiltonian with magnetic-field perturbations, which is a
gauge-fixed version of a (2+1)-dimensional gauge-Higgs model. We employ a
cylinder geometry with distinct upper and lower boundaries to classify
stationary states after long-time measurement dynamics. The appearing
stationary states depend on measurement probabilities for each measurement
operator. The Higgs, confined and deconfined phases emerge in the time
evolution by the circuit. We find that both Higgs and confined phases are
separated from the deconfined phase by topological entanglement entropy. We
numerically clarify that both Higgs and confined phases are characterized by a
long-range order on the boundaries accompanying edge modes, and they shift with
each other by a crossover reflecting properties in the bulk phase diagram.


  In this work, we present SeqFormer for video instance segmentation. SeqFormer
follows the principle of vision transformer that models instance relationships
among video frames. Nevertheless, we observe that a stand-alone instance query
suffices for capturing a time sequence of instances in a video, but attention
mechanisms shall be done with each frame independently. To achieve this,
SeqFormer locates an instance in each frame and aggregates temporal information
to learn a powerful representation of a video-level instance, which is used to
predict the mask sequences on each frame dynamically. Instance tracking is
achieved naturally without tracking branches or post-processing. On
YouTube-VIS, SeqFormer achieves 47.4 AP with a ResNet-50 backbone and 49.0 AP
with a ResNet-101 backbone without bells and whistles. Such achievement
significantly exceeds the previous state-of-the-art performance by 4.6 and 4.4,
respectively. In addition, integrated with the recently-proposed Swin
transformer, SeqFormer achieves a much higher AP of 59.3. We hope SeqFormer
could be a strong baseline that fosters future research in video instance
segmentation, and in the meantime, advances this field with a more robust,
accurate, neat model. The code is available at
https://github.com/wjf5203/SeqFormer.


  We perform a proof-of-concept implementation of the massively parallel
algorithm (P.M. Lushnikov, Opt. Lett., v. 27, 939 (2002)) for simulation of
dispersion-managed wavelength-division-multiplexed optical fiber systems.
Linear scalability of the algorithm with the number of computer cores is
demonstrated. Exact result on the accuracy of the implemented algorithm is
found analytically and confirmed numerically as well as it is compared with to
accuracy of the standard split-step algorithm.


  In this work we study a rational extension $SROEL^R T$ of the low complexity
description logic SROEL, which underlies the OWL EL ontology language. The
extension involves a typicality operator T, whose semantics is based on Lehmann
and Magidor's ranked models and allows for the definition of defeasible
inclusions. We consider both rational entailment and minimal entailment. We
show that deciding instance checking under minimal entailment is in general
$\Pi^P_2$-hard, while, under rational entailment, instance checking can be
computed in polynomial time. We develop a Datalog calculus for instance
checking under rational entailment and exploit it, with stratified negation,
for computing the rational closure of simple KBs in polynomial time.


  When quark-gluon plasma emerges in the wake of a heavy-ion collision,
magnetic field created by the valence charges has already permitted the entire
interaction region. Evolution of this "initial" field in plasma is governed by
Maxwell equations in electrically conducting medium. As the plasma expands
external valence charges induce magnetic field that also contributes to the
total magnetic field in plasma. We solve the initial value problem describing
these processes and argue that the initial magnetic field often dominates over
the one induced by the valence charges. In particular, it grows approximately
proportional to the collision energy, unlike the induced component, which is
energy-independent. As a result, magnetic field has a significant
phenomenological influence on quark-gluon plasma at the LHC energies over its
entire lifetime.


  This paper studies a special kind of equilibrium termed as "balanced
equilibrium" which arises in the power allocation game defined in
\cite{allocation}. In equilibrium, each country in antagonism has to use all of
its own power to counteract received threats, and the "threats" made to each
adversary just balance out the threats received from that adversary. This paper
establishes conditions on different types of networked international
environments in order for this equilibrium to exist. The paper also links the
existence of this type of equilibrium on structurally balanced graphs to the
Hall's Maximum Matching problem and the Max Flow problem.


  In healthcare, thousands of safety incidents occur every year, but learning
from these incidents is not effectively aggregated. Analysing incident reports
using AI could uncover critical insights to prevent harm by identifying
recurring patterns and contributing factors. To aggregate and extract valuable
information, natural language processing (NLP) and machine learning techniques
can be employed to summarise and mine unstructured data, potentially surfacing
systemic issues and priority areas for improvement. This paper presents
I-SIRch:CS, a framework designed to facilitate the aggregation and analysis of
safety incident reports while ensuring traceability throughout the process. The
framework integrates concept annotation using the Safety Intelligence Research
(SIRch) taxonomy with clustering, summarisation, and analysis capabilities.
Utilising a dataset of 188 anonymised maternity investigation reports annotated
with 27 SIRch human factors concepts, I-SIRch:CS groups the annotated sentences
into clusters using sentence embeddings and k-means clustering, maintaining
traceability via file and sentence IDs. Summaries are generated for each
cluster using offline state-of-the-art abstractive summarisation models (BART,
DistilBART, T5), which are evaluated and compared using metrics assessing
summary quality attributes. The generated summaries are linked back to the
original file and sentence IDs, ensuring traceability and allowing for
verification of the summarised information. Results demonstrate BART's
strengths in creating informative and concise summaries.


  We consider the family of real (generalized) eigenfunctions of the adjacency
operator on $T_d$ - the $d$-regular tree. We show the existence of a unique
invariant Gaussian process on the ensemble and derive explicitly its covariance
operator. We investigate the typical structure of level sets of the process. In
particular we show that the entropic repulsion of the level sets is uniformly
bounded and prove the existence of a critical threshold, above which the level
sets are all of finite cardinality and below it an infinite component appears
almost surely.


  We present results from a deep (200 ks) Chandra observation of the early-type
galaxy NGC 4552 (M89) which is falling into the Virgo cluster. Previous
shallower X-ray observations of this galaxy showed a remnant gas core, a tail
to the South of the galaxy, and twin `horns' attached to the northern edge of
the gas core [machacek05a]. In our deeper data, we detect a diffuse, low
surface brightness extension to the previously known tail, and measure the
temperature structure within the tail. We combine the deep Chandra data with
archival XMM-Newton observations to put a strong upper limit on the diffuse
emission of the tail out to a large distance (10$\times$the radius of the
remnant core) from the galaxy center. In our two previous papers
[roediger15a,roediger15b], we presented the results of hydrodynamical
simulations of ram pressure stripping specifically for M89 falling into the
Virgo cluster and investigated the effect of ICM viscosity. In this paper, we
compare our deep data with our specifically tailored simulations and conclude
that the observed morphology of the stripped tail in NGC 4552 is most similar
to the inviscid models. We conclude that, to the extent the transport processes
can be simply modeled as a hydrodynamic viscosity, the ICM viscosity is
negligible. More generally, any micro-scale description of the transport
processes in the high-$\beta$ plasma of the cluster ICM must be consistent with
the efficient mixing observed in the stripped tail on macroscopic scales.


  The terrestrial planets are believed to have formed by violent collisions of
tens of lunar- to Mars-size protoplanets at time t<200 Myr after the
protoplanetary gas disk dispersal (t_0). The solar system giant planets rapidly
formed during the protoplanetary disk stage and, after t_0, radially migrated
by interacting with outer disk planetesimals. An early (t<100 Myr) dynamical
instability is thought to have occurred with Jupiter having gravitational
encounters with a planetary-size body, jumping inward by ~0.2-0.5 au, and
landing on its current, mildly eccentric orbit. Here we investigate how the
giant planet instability affected formation of the terrestrial planets. We
study several instability cases that were previously shown to match many solar
system constraints. We find that resonances with the giant planets help to
remove solids available for accretion near ~1.5 au, thus stalling the growth of
Mars. It does not matter, however, whether the giant planets are placed on
their current orbits at t_0 or whether they realistically evolve in one of our
instability models; the results are practically the same. The tight orbital
spacing of Venus and Earth is difficult to reproduce in our simulations,
including cases where bodies grow from a narrow annulus at 0.7-1 au, because
protoplanets tend to radially spread during accretion. The best results are
obtained in the narrow-annulus model when protoplanets emerging from the
dispersing gas nebula are assumed to have (at least) the Mars mass. This
suggests efficient accretion of the terrestrial protoplanets during the first
~10 Myr of the solar system.


  We explore a simple model for the high luminosity of SN 2006gy involving
photon diffusion of shock-deposited thermal energy. The distinguishing property
of the model is that the large ``stellar'' radius of 160 AU required to prevent
adiabatic losses is not the true stellar radius, but rather, the radius of an
opaque, unbound circumstellar envelope, created when 10 Msun was ejected in the
decade before the supernova in an eruption analogous to that of eta Carinae.
The supernova light is produced primarily by diffusion of thermal energy
following the passage of the blast wave through this shell. This model differs
from traditional models of supernova debris interacting with external CSM in
that here the shell is optically thick and the escape of radiation is delayed.
We show that any model attempting to account for SN2006gy's huge luminosity
with radiation emitted by ongoing CSM interaction fails for the following basic
reason: the CSM density required to achieve the observed luminosity makes the
same circumstellar envelope opaque, forcing a thermal diffusion solution. In
our model, the weaker CSM interaction giving rise to SN2006gy's characteristic
Type IIn spectrum and soft X-rays is not linked to the power source of the
visual continuum; instead, it arises after the blast wave breaks free of the
opaque shell into the surrounding wind. While a simple diffusion model can
explain the gross properties of the early light curve of SN2006gy, it predicts
that the light curve must plummet rapidly at late-times, unless an additional
power source is present.


  The existence of gravitational radiation is a natural prediction of any
relativistic description of the gravitational interaction. In this chapter, we
focus on gravitational waves, as predicted by Einstein's general theory of
relativity. First, we introduce those mathematical concepts that are necessary
to properly formulate the physical theory, such as the notions of manifold,
vector, tensor, metric, connection and curvature. Second, we motivate,
formulate and then discuss Einstein's equation, which relates the geometry of
spacetime to its matter content. Gravitational waves are later introduced as
solutions of the linearized Einstein equation around flat spacetime. These
waves are shown to propagate at the speed of light and to possess two
polarization states. Gravitational waves can interact with matter, allowing for
their direct detection by means of laser interferometers. Finally, Einstein's
quadrupole formulas are derived and used to show that nonspherical compact
objects moving at relativistic speeds are powerful gravitational wave sources.


  In 2017, a research paper compared 18 Time Series Classification (TSC)
algorithms on 85 datasets from the University of California, Riverside (UCR)
archive. This study, commonly referred to as a `bake off', identified that only
nine algorithms performed significantly better than the Dynamic Time Warping
(DTW) and Rotation Forest benchmarks that were used. The study categorised each
algorithm by the type of feature they extract from time series data, forming a
taxonomy of five main algorithm types. This categorisation of algorithms
alongside the provision of code and accessible results for reproducibility has
helped fuel an increase in popularity of the TSC field. Over six years have
passed since this bake off, the UCR archive has expanded to 112 datasets and
there have been a large number of new algorithms proposed. We revisit the bake
off, seeing how each of the proposed categories have advanced since the
original publication, and evaluate the performance of newer algorithms against
the previous best-of-category using an expanded UCR archive. We extend the
taxonomy to include three new categories to reflect recent developments.
Alongside the originally proposed distance, interval, shapelet, dictionary and
hybrid based algorithms, we compare newer convolution and feature based
algorithms as well as deep learning approaches. We introduce 30 classification
datasets either recently donated to the archive or reformatted to the TSC
format, and use these to further evaluate the best performing algorithm from
each category. Overall, we find that two recently proposed algorithms,
Hydra+MultiROCKET and HIVE-COTEv2, perform significantly better than other
approaches on both the current and new TSC problems.


  To every partial order P, one associates a polynomial $\mathbb{D}_P$ in 4
variables that enumerates the intervals of P according to 4 parameters. Some
symmetry properties of this polynomial are obtained for a specific family of
posets, the Tamari lattices. A ternary symmetry is proved for the polynomial in
3 variables obtained by setting one variable to 1. Another global symmetry is
conjectured. The set of synchronized intervals is described using a facet of
the Newton polytope. A relation to the statistics of the canopy of binary
planar trees is described.


  The input and output algebras of an infinite qubit system and their
representations are described.


  We investigate the role of phase transitions into the spontaneous emission
rate of quantum emitters embedded in a critical medium. Using a Landau-Ginzburg
approach, we find that, in the broken symmetry phase, the emission rate is
reduced or even suppressed due to the photon mass generated by the Higgs
mechanism. Moreover, we show that the spontaneous emission presents a
remarkable dependence upon the critical exponents associated to a given phase
transition, allowing for an optical determination of the universality class.
Our findings not only demonstrate that the Purcell effect constitutes an
efficient optical probe of distinct critical phenomena, but they also unveil
that a more general connection between phase transitions and spontaneous
emission exist, as previous experimental and numerical evidences suggest.


  We estimate the photon production rate from an SU(3) plasma at temperatures
of about 1.1Tc and 1.3Tc. Lattice results for the vector current correlator at
spatial momenta k ~ (2-6)T are extrapolated to the continuum limit and analyzed
with the help of a polynomial interpolation for the corresponding spectral
function, which vanishes at zero frequency and matches to high-precision
perturbative results at large invariant masses. For small invariant masses the
interpolation is compared with the NLO weak-coupling result, hydrodynamics, and
a holographic model. At vanishing invariant mass we extract the photon rate
which for k \gsim 3T is found to be close to the NLO weak-coupling prediction.
For k \lsim 2T uncertainties remain large but the photon rate is likely to fall
below the NLO prediction, in accordance with the onset of a strongly
interacting behaviour characteristic of the hydrodynamic regime.


  We incorporate some corrections inspired by loop quantum gravity into the
concept of gravitational collapse and propose a complete model of the dynamic
process. The model carries the essence of a mass-independent upper bound on the
curvature scalars originally found as a crucial feature of black holes in loop
quantum gravity. The quantum-inspired interior is immersed in a geometry filled
with null radiation and they are matched at a distinct boundary hypersurface.
The ultimate fate of the process depends on inhomogeneities of the metric
tensor cofficients. We find a critical parameter $\lambda$ embedded in the
inhomogeneity of the conformal factor of the interior metric. Examples with
$\lambda < 0$ enforce an eventual collapse to singularity and $\lambda > 0$
cases produce a non-singular collapse resulting in a loop-quantum-corrected
Schwarzschild geometry modulo a conformal factor. Interestingly, for $\lambda <
0$ as well, there exist situations where the quantum effects are able to cause
a bounce but fall short of preventing the ultimate formation of singularity.
The trapped surface formation condition is studied for $\lambda<0$ case to
infer about the visibility of the final singularity. Interestingly, we find a
possibility of formation of three horizons during the course of the collapse.
Eventually all of them merge into one single horizon which envelopes the final
singularity. For the non-singular case, there is a possibility that the sphere
can evolve into a wormhole throat whose radius is found to be inversely
proportional to the critical parameter $\lambda$. Depending on the nature of
evolution and the shell regions, the collapsing shells violate some standard
energy conditions which can be associated with the quantum inspired
corrections.


  An overview of the indirect constraints from flavour physics on
supersymmetric models is presented. We study in particular constraints from Bs
-> mu+mu- and B -> K* mu+mu-, emphasising on the new LHCb results. We show that
these rare transitions provide valuable information in the search for new
physics and are complementary to the direct searches.


  In a one-generation fermion condensate scheme of electroweak symmetry
breaking, it is proven based on Schwinger-Dyson equation in the real-time
thermal field theory in the fermion bubble diagram approximation that, at
finite temperature $T$ below the symmetry restoration temperature $T_c$, a
massive Higgs boson and three massless Nambu-Goldstone bosons could emerge from
the spontaneous breaking of electroweak group $SU_L(2)\times U_Y(1) \to U_Q(1)$
if the two fermion flavors in the one generation are mass-degenerate, thus
Goldstone Theorem is rigorously valid in this case. However, if the two fermion
flavors have unequal masses, owing to "thermal flactuation", the Goldstone
Theorem will be true only approximately for a very large momentum cut-off
$\Lambda$ in zero temperature fermion loop or for low energy scales. All
possible pinch singularities are proven to cancel each other, as is expected in
a real-time thermal field theory.


  The first normal emission experiment result on bcc Ni ultrathin film is
presented in comparison with the one on fcc Ni. Its agreement with band
structure calculation, by supplementing our former results on the magnetic
properties of bcc Ni, verifies from the electronic viewpoint the successful
epitaxy of this metastable phase of Ni which doesn't exist in nature.


  Software quality in use comprises quality from the user's perspective. It has
gained its importance in e-government applications, mobile-based applications,
embedded systems, and even business process development. User's decisions on
software acquisitions are often ad hoc or based on preference due to difficulty
in quantitatively measuring software quality in use. But, why is quality-in-use
measurement difficult? Although there are many software quality models, to the
authors' knowledge no works survey the challenges related to software
quality-in-use measurement. This article has two main contributions: 1) it
identifies and explains major issues and challenges in measuring software
quality in use in the context of the ISO SQuaRE series and related software
quality models and highlights open research areas; and 2) it sheds light on a
research direction that can be used to predict software quality in use. In
short, the quality-in-use measurement issues are related to the complexity of
the current standard models and the limitations and incompleteness of the
customized software quality models. A sentiment analysis of software reviews is
proposed to deal with these issues.


  The SciBooNE experiment (Fermilab) recently published results of a search for
charged current coherent pion production in neutrino mode: muon neutrinos
scattering on carbon. The results of this study are that no evidence for
coherent pion production is observed, and SciBooNE set 90% confidence level
upper limits on the cross section ratio of charged current coherent pion
production to the total charged current cross section. Recently proposed new
coherent pion models predict a production of charged current coherent pion
events just below the SciBooNE's upper limit. Motivated by this, we performed a
search for charged current coherent pion production using SciBooNE's collected
antineutrino data since antineutrino data are expected to be more sensitive to
look at coherent pion production than neutrino data. This paper describes
preliminary results of a search for antineutrino charged current coherent pion
production at the SciBooNE experiment.


  Seismic analyses of the CoRoT target HD 49933 have revealed a magnetic cycle.
Further insight reveals that frequency shifts of oscillation modes vary as a
function of frequency, following a similar pattern to that found in the Sun. In
this preliminary work, we use seismic constraint to compute structure models of
HD 49933 with the Asteroseismic Modeling Portal (AMP) and the CESAM code. We
use these models to study the effects of sound-speed perturbations in near
surface layers on p-mode frequencies.


  We present a possible orbit for the Southern Stream of stars in M31, which
connects it to the Northern Spur. Support for this model comes from the
dynamics of planetary nebulae (PNe) in the disk of M31: analysis of a new
sample of 2611 PNe obtained using the Planetary Nebula Spectrograph reveals ~20
objects whose kinematics are inconsistent with the normal components of the
galaxy, but which lie at the right positions and velocities to connect the two
photometric features via this orbit. The satellite galaxy M32 is coincident
with the stream both in position and velocity, adding weight to the hypothesis
that the stream comprises its tidal debris.


  A semi-linear parabolic problem is considered in a thin $3D$ star-shaped
junction that consists of several thin curvilinear cylinders that are joined
through a domain (node) of diameter $\mathcal{O}(\varepsilon).$
  The purpose is to study the asymptotic behavior of the solution
$u_\varepsilon$ as $\varepsilon \to 0,$ i.e. when the star-shaped junction is
transformed in a graph. In addition, the passage to the limit is accompanied by
special intensity factors $\{\varepsilon^{\alpha_i}\}$ and
$\{\varepsilon^{\beta_i}\}$ in nonlinear perturbed Robin boundary conditions.
  We establish qualitatively different cases in the asymptotic behaviour of the
solution depending on the value of the parameters $\{{\alpha_i}\}$ and
$\{\beta_i\}.$ Using the multi-scale analysis, the asymptotic approximation for
the solution is constructed and justified as the parameter $\varepsilon \to 0.$
Namely, in each case we derive the limit problem $(\varepsilon =0)$ on the
graph with the corresponding Kirchhoff transmission conditions (untypical in
some cases) at the vertex, define other terms of the asymptotic approximation
and prove appropriate asymptotic estimates that justify these coupling
conditions at the vertex and show the impact of the local geometric
heterogeneity of the node and physical processes in the node on some properties
of the solution.


  We previously proposed an intelligent automatic treatment planning framework
for radiotherapy, in which a virtual treatment planner network (VTPN) was built
using deep reinforcement learning (DRL) to operate a treatment planning system
(TPS). Despite the success, the training of VTPN via DRL was time consuming.
Also the training time is expected to grow with the complexity of the treatment
planning problem, preventing the development of VTPN for more complicated but
clinically relevant scenarios. In this study we proposed a knowledge-guided DRL
(KgDRL) that incorporated knowledge from human planners to guide the training
process to improve the training efficiency. Using prostate cancer intensity
modulated radiation therapy as a testbed, we first summarized a number of rules
of operating our in-house TPS. In training, in addition to randomly navigating
the state-action space, as in the DRL using the epsilon-greedy algorithm, we
also sampled actions defined by the rules. The priority of sampling actions
from rules decreased over the training process to encourage VTPN to explore new
policy that was not covered by the rules. We trained a VTPN using KgDRL and
compared its performance with another VTPN trained using DRL. Both VTPNs
trained via KgDRL and DRL spontaneously learned to operate the TPS to generate
high-quality plans, achieving plan quality scores of 8.82 and 8.43,
respectively. Both VTPNs outperformed treatment planning purely based on the
rules, which had a plan score of 7.81. VTPN trained with 8 episodes using KgDRL
was able to perform similarly to that trained using DRL with 100 episodes. The
training time was reduced from more than a week to 13 hours. The proposed KgDRL
framework accelerated the training process by incorporating human knowledge,
which will facilitate the development of VTPN for more complicated treatment
planning scenarios.


  Ernst Specker considered a particular feature of quantum theory to be
especially fundamental, namely that pairwise joint measurability of sharp
measurements implies their global joint measurability
(https://vimeo.com/52923835). To date, Specker's principle seemed incapable of
singling out quantum theory from the space of all general probabilistic
theories. In particular, its well-known consequence for experimental
statistics, the principle of consistent exclusivity, does not rule out the set
of correlations known as almost quantum, which is strictly larger than the set
of quantum correlations. Here we show that, contrary to the popular belief,
Specker's principle cannot be satisfied in any theory that yields almost
quantum correlations.


  The paper describes neural models developed for the DAGPap22 shared task
hosted at the Third Workshop on Scholarly Document Processing. This shared task
targets the automatic detection of generated scientific papers. Our work
focuses on comparing different transformer-based models as well as using
additional datasets and techniques to deal with imbalanced classes. As a final
submission, we utilized an ensemble of SciBERT, RoBERTa, and DeBERTa fine-tuned
using random oversampling technique. Our model achieved 99.24% in terms of
F1-score. The official evaluation results have put our system at the third
place.


  We present a calculation of the grand canonical partition function of a
serial metallic island system by the imaginary-time path integral formalism. To
this purpose, all electronic excitations in the lead and island electrodes are
described using Grassmann numbers. Coulomb charging energy of the system is
represented in terms of phase fields conjugate to the island charges. By the
large channel approximation, the tunneling action phase dependence can also be
determined explicitly. Therefore, we represent the partition function as a path
integral over phase fields with a path probability given in an analytically
known effective action functional. Using the result, we also propose a
calculation of the average electron number of the serial island system in terms
of the expectation value of winding numbers. Finally, as an example, we
describe the Coulomb blockade effect in the two-island system by the average
electron number and propose a method to construct the quantum stability
diagram.


  To build light-weight network, we propose a new normalization, Fine-grained
Batch Normalization (FBN). Different from Batch Normalization (BN), which
normalizes the final summation of the weighted inputs, FBN normalizes the
intermediate state of the summation. We propose a novel light-weight network
based on FBN, called Finet. At training time, the convolutional layer with FBN
can be seen as an inverted bottleneck mechanism. FBN can be fused into
convolution at inference time. After fusion, Finet uses the standard
convolution with equal channel width, thus makes the inference more efficient.
On ImageNet classification dataset, Finet achieves the state-of-art performance
(65.706% accuracy with 43M FLOPs, and 73.786% accuracy with 303M FLOPs),
Moreover, experiments show that Finet is more efficient than other state-of-art
light-weight networks.


  Recent optical/UV data of Geminga (Mignani et al. 1998) have strengthen the
significance of the emission feature present over the thermal continuum best
fitting the EUV/soft X-ray data. Here we present a phenomenological model
interpreting the data in terms of an ion cyclotron feature, arising from a thin
outer layer of hot plasma covering Geminga's polar caps. The width of the
feature favours for Geminga the strongly oblique rotator configuration, as
already deduced from the soft X-ray data (Halpern & Ruderman 1993). Our
interpretation implies a magnetic field of 3 - 5 10d11 G, consistent with the
value deduced from the dynamical parameters of the pulsar. This would represent
the first case of an independent measurement of the surface magnetic field of
an isolated neutron star. The expected time modulation of Geminga's feature is
also discussed.


  Brillouin oscillation appears in picosecond ultrasonics for a transparent
specimen because of backward light scattering by moving strain pulse. Its
amplitude is comparable with those of other responses, such as pulse-echo
signals and through-thickness resonance, obscuring these
non-Brillouin-oscillation responses. We here find that Brillouin oscillation
can be suppressed in a transparent free-standing film by coating both sides
with metallic thin film of appropriate thickness and that this peculiar
behavior is caused by strain pulses generated on both sides with a slight phase
difference. This phenomenon allowed us to fabricate a
Brillouin-oscillation-free diamond free-standing film, which showed high
capability for sensor applications.


  We give an exponential separation between one-way quantum and classical
communication protocols for a partial Boolean function (a variant of the
Boolean Hidden Matching Problem of Bar-Yossef et al.) Earlier such an
exponential separation was known only for a relational problem. The
communication problem corresponds to a \emph{strong extractor} that fails
against a small amount of \emph{quantum} information about its random source.
Our proof uses the Fourier coefficients inequality of Kahn, Kalai, and Linial.
  We also give a number of applications of this separation. In particular, we
show that there are privacy amplification schemes that are secure against
classical adversaries but not against quantum adversaries; and we give the
first example of a key-expansion scheme in the model of bounded-storage
cryptography that is secure against classical memory-bounded adversaries but
not against quantum ones.


  We propose an effective model to describe the statistical properties of
exciton fine structure splitting (FSS) and polarization angle of quantum dot
ensembles (QDEs). We derive the distributions of FSS and polarization angle for
QDEs and show that their statistical features can be fully characterized using
at most three independent measurable parameters. The effective model is
confirmed using atomistic pseudopotential calculations as well as experimental
measurements for several rather different QDEs. The model naturally addresses
three fundamental questions that are frequently encountered in theories and
experiments: (I) Why the probability of finding QDs with vanishing FSS is
generally very small? (II) Why FSS and polarization angle differ dramatically
from QD to QD? and (III) Is there any direct connection between FSS, optical
polarization and the morphology of QDs? The answers to these fundamental
questions yield a completely new physical picture for understanding optical
properties of QDEs.


  Non-orthogonal multiple access (NOMA) and millimeter wave (mmWave) are two
key enabling technologies for the fifth-generation (5G) mobile networks and
beyond. In this paper, we consider uplink communications with a hybrid
beamforming structure and focus on improving the spectral efficiency (SE) and
energy efficiency (EE) of mmWave multiple-input multiple-output (MIMO)-NOMA
systems with enhanced user grouping and power allocation. Exploiting the
directionality feature of mmWave channels, we first propose a novel initial
agglomerative nesting (AGNES) based user grouping algorithm by taking advantage
of the channel correlations. It is noted that the optimization of the SE/EE is
a challenging task due to the non-linear programming nature of the
corresponding problem involving user grouping, beam selection, and power
allocation. Our idea is to decompose the overall optimization problem into a
mixed integer problem comprising of user grouping and beam selection only,
followed by a continuous problem involving power allocation and digital
beamforming design. To avoid the prohibitively high complexity of the
brute-force search approach, we propose two suboptimal low-complexity user
grouping and beam selection schemes, the direct AGNES (DIR-AGNES) scheme and
the successive AGNES (SUC-AGNES) scheme. We also introduce the quadratic
transform (QT) to recast the non-convex power allocation optimization problem
into a convex one subject to a minimum required data rate of each user. The
continuous problem is solved by iteratively optimizing the power and the
digital beamforming. Extensive simulation results have shown that our proposed
mmWave-NOMA design outperforms the conventional orthogonal multiple access
(OMA) scenario and the state-of-art NOMA schemes.


  Skin lesion analysis models are biased by artifacts placed during image
acquisition, which influence model predictions despite carrying no clinical
information. Solutions that address this problem by regularizing models to
prevent learning those spurious features achieve only partial success, and
existing test-time debiasing techniques are inappropriate for skin lesion
analysis due to either making unrealistic assumptions on the distribution of
test data or requiring laborious annotation from medical practitioners. We
propose TTS (Test-Time Selection), a human-in-the-loop method that leverages
positive (e.g., lesion area) and negative (e.g., artifacts) keypoints in test
samples. TTS effectively steers models away from exploiting spurious
artifact-related correlations without retraining, and with less annotation
requirements. Our solution is robust to a varying availability of annotations,
and different levels of bias. We showcase on the ISIC2019 dataset (for which we
release a subset of annotated images) how our model could be deployed in the
real-world for mitigating bias.


  Within the framework of chiral effective field theory, we study various
electromagnetic processes with light vector resonances: $K^{\ast}(892)\to
K\gamma$, $e^{+}e^{-}\to K^{\ast}(892)K $ and the $\omega\pi\gamma^\ast$ form
factors. With two multiplets of vector resonances being introduced, we fit the
decay widths of $K^{\ast0}\to K^{0}\gamma$, $K^{\ast+}\to K^{+}\gamma$, and the
pertinent measurements from the $e^{+}e^{-}\to K^{\ast \pm}(892)K^{\mp} $ cross
sections, such as moduli and relative phases between the isoscalar and
isovector components from BABAR collaboration, together with the $\omega\pi$
form factors from NA60, SND and CLEO collaborations. The values of resonance
couplings, masses and widths of the excited vector states $\rho'$ and $\phi'$
are then determined. The $\omega'$-$\phi'$ mixing angle is discussed and turns
out to be quite different from the ideal mixing case. Three sources of $SU(3)$
symmetry breaking effects in the $\Gamma(K^{\ast}\to K\gamma)$ decays are
identified and analyzed in detail.


  The status of tests of the standard electroweak model and of searches for new
physics in allowed nuclear $\beta$ decay and neutron decay is reviewed
including both theoretical and experimental developments. The sensitivity and
complementarity of recent and ongoing experiments are discussed with emphasis
on their potential to look for new physics. Measurements are interpreted using
a model-independent effective field theory approach enabling to recast the
outcome of the analysis in many specific new physics models. Special attention
is given to the connection that this approach establishes with high-energy
physics. A new global fit of available $\beta$-decay data is performed
incorporating, for the first time in a consistent way, superallowed $0^+\to
0^+$ transitions, neutron decay and nuclear decays. The constraints on exotic
scalar and tensor couplings involving left- or right-handed neutrinos are
determined while a constraint on the pseudoscalar coupling from neutron decay
data is obtained for the first time as well. The values of the vector and
axial-vector couplings, which are associated within the standard model to
$V_{ud}$ and $g_A$ respectively, are also updated. The ratio between the axial
and vector couplings obtained from the fit under standard model assumptions is
$C_A/C_V = -1.27510(66)$. The relevance of the various experimental inputs and
error sources is critically discussed and the impact of ongoing measurements is
studied. The complementarity of the obtained bounds with other low- and
high-energy probes is presented including ongoing searches at the Large Hadron
Collider.


  The mid- and far-IR spectral ranges are critical windows to characterize the
physical and chemical processes that transform the interstellar gas and dust
into stars and planets. Sources in the earliest phases of star formation and in
the latest stages of stellar evolution release most of their energy at these
wavelengths. Besides, the mid- and far-IR ranges provide key spectral
diagnostics of the gas chemistry (water, light hydrides, organic species ...),
of the prevailing physical conditions (H2, atomic fine structure lines...), and
of the dust mineral and ice composition that can not be observed from
ground-based telescopes. With the launch of JAXA's SPICA telescope,
uninterrupted studies in the mid- and far-IR will be possible since ESA's
Infrared Space Observatory (1995). In particular, SAFARI will provide full
access to the 34-210um waveband through several detector arrays and flexible
observing modes (from broadband photometry to medium resolution spectroscopy
with R~3,000 at 63um), and reaching very high line sensitivities (~10^-19
Wm^-2, 5sigma-1hr) within a large FOV (~2'x2'). Compared to previous far-IR
instruments (ISO/LWS, Akari/FIS, Spitzer/MIPS and Herschel/PACS), SAFARI will
provide a superior way to obtain fully-sampled spectro-images and continuous
SEDs of very faint and extended ISM sources in a wavelength domain not
accessible to JWST or ALMA. The much increased sensitivity of SPICA will allow
us to step forward and reveal not only the chemical complexity in the local
ISM, but also in the extragalactic ISM routinely.


  We study kaonic deuterium, the bound K^-d state A_(K d). Within a quantum
field theoretic and relativistic covariant approach we derive the energy level
displacement of the ground state of kaonic deuterium in terms of the amplitude
of K^-d scattering for arbitrary relative momenta. Near threshold our formula
reduces to the well-known DGBT formula. The S-wave amplitude of K^-d scattering
near threshold is defined by the resonances Lambda(1405), Sigma(1750) and a
smooth elastic background, and the inelastic channels K^- d -> NY and K^- d ->
NY pion, with Y = Sigma^(+/-), Sigma^0 and Lambda^0, where the final-state
interactions play an important role. The Ericson-Weise formula for the S-wave
scattering length of K^-d scattering is derived. The total width of the energy
level of the ground state of kaonic deuterium is estimated using the
theoretical predictions of the partial widths of the two-body decays A_(Kd) ->
NY and experimental data on the rates of the NY-pair production in the
reactions K^-d -> NY. We obtain Gamma_{1s} = (630 +/-100) eV. For the shift of
the energy level of the ground state of kaonic deuterium we predict
epsilon_(1s) = (353 +/-60)eV.


  Scanning tunneling microscopy and spectroscopy have been performed on
superconducting La$_{2-x}$Sr$_{x}$CuO$_{4}$ ($x=0.06, 0.12, 0.16$, and 0.21) at
4.2 K. Atomically resolved surface topography has been observed on the $ab$
surface, which exhibits a one-dimensional structure corresponding to the
buckling pattern of the orthorhombic phase. The tunneling spectra of all
samples exhibit kinks at about $\pm 5$ meV in addition to the energy gap,
indicating the existence of two energy scales. While the gap magnitude varies
on the length scale of a few nm and steadily increases upon underdoping, the
kink energy is spatially uniform on the surface and almost independent of the
doping level.


  We identify a large class of constant (complex) coefficient, second order
elliptic systems for which the Dirichlet problem in the upper-half space with
data in $L^p$-based Sobolev spaces, $1<p<\infty$, of arbitrary smoothness
$\ell$, is well-posed in the class of functions whose nontangential maximal
operator of their derivatives up to, and including, order $\ell$ is
$L^p$-integrable. This class includes all scalar, complex coefficient elliptic
operators of second order, as well as the Lam\'e system of elasticity, among
others.


  Gravitational waves (GWs) from merging binary black holes (BHs) enable
unprecedented tests of gravitational theories beyond Einstein's General
Relativity (GR) in highly nonlinear, dynamical regimes. Such GW measurements
require an accurate description of GW signatures that may arise in alternative
gravitational models. In this work, we focus on a class of higher-curvature
extensions of GR, the scalar-Gauss-Bonnet theories, where BHs can develop
scalar hair. In an inspiraling binary system, this leads to scalar-induced
tidal effects in the dynamics and radiation. We calculate the dominant
adiabatic dipolar tidal effects via an approximation scheme based on expansions
in post-Newtonian, higher-curvature, and tidal corrections. The tidal effects
depend on a characteristic scalar Love number, which we compute using BH
perturbation theory, and have the same scaling with GW frequency as the
higher-curvature corrections. We perform case studies to characterize the net
size and parameter dependencies of these effects, showing that at low
frequencies, tidal effects dominate over the higher-curvature contributions for
small couplings within current bounds, regardless of the total BH mass, while
at high frequencies they are subdominant. We further consider prospects
observing both of these regimes, which would be interesting for breaking
parameter degeneracies, with multiband detections of LISA and ground-based
detectors or the Einstein Telescope alone. We also assess the frequency range
of the transition between these regimes by numerically solving the energy
balance law. Our results highlight the importance of the dipolar scalar tidal
effects for BHs with scalar hair, which arise in several beyond-GR paradigms,
and provide ready-to-use inputs for improved GW constraints on Gauss-Bonnet
theories.


  Radiology report summarization (RRS) is crucial for patient care, requiring
concise "Impressions" from detailed "Findings." This paper introduces a novel
prompting strategy to enhance RRS by first generating a layperson summary. This
approach normalizes key observations and simplifies complex information using
non-expert communication techniques inspired by doctor-patient interactions.
Combined with few-shot in-context learning, this method improves the model's
ability to link general terms to specific findings. We evaluate this approach
on the MIMIC-CXR, CheXpert, and MIMIC-III datasets, benchmarking it against
7B/8B parameter state-of-the-art open-source large language models (LLMs) like
Meta-Llama-3-8B-Instruct. Our results demonstrate improvements in summarization
accuracy and accessibility, particularly in out-of-domain tests, with
improvements as high as 5% for some metrics.


  We describe how the reversion of a series is related to convolutional
recurrence relations for the series, and we place this relationship in the
context of Riordan arrays. As an example of the approach, we give new
recurrence relations for the sequences of Patalan numbers. We also consider the
concepts of recursive matrices and dual Riordan arrays, and their application
to previous work on the super Patalan numbers.


  Self-supervised methods based on contrastive learning have achieved great
success in unsupervised visual representation learning. However, most methods
under this framework suffer from the problem of false negative samples.
Inspired by the mean shift for self-supervised learning, we propose a new
simple framework, namely Multiple Sample Views and Queues (MSVQ). We jointly
construct three soft labels on-the-fly by utilizing two complementary and
symmetric approaches: multiple augmented positive views and two momentum
encoders that generate various semantic features for negative samples. Two
teacher networks perform similarity relationship calculations with negative
samples and then transfer this knowledge to the student network. Let the
student network mimic the similarity relationships between the samples, thus
giving the student network a more flexible ability to identify false negative
samples in the dataset. The classification results on four benchmark image
datasets demonstrate the high effectiveness and efficiency of our approach
compared to some classical methods. Source code and pretrained models are
available \href{https://github.com/pc-cp/MSVQ}{here}.


  In this paper, we construct a pointed CW complex called the magnitude
homotopy type for a given metric space $X$ and a real parameter $\ell \geq 0$.
This space is roughly consisting of all paths of length $\ell$ and has the
reduced homology group that is isomorphic to the magnitude homology group of
$X$.
  To construct the magnitude homotopy type, we consider the poset structure on
the spacetime $X\times\mathbb{R}$ defined by causal (time- or light-like)
relations. The magnitude homotopy type is defined as the quotient of the order
complex of an intervals on $X\times\mathbb{R}$ by a certain subcomplex.
  The magnitude homotopy type gives a covariant functor from the category of
metric spaces with $1$-Lipschitz maps to the category of pointed topological
spaces. The magnitude homotopy type also has a ``path integral'' like
expression for certain metric spaces.
  By applying discrete Morse theory to the magnitude homotopy type, we obtain a
new proof of the Mayer-Vietoris type theorem and several new results including
the invariance of the magnitude under sycamore twist of finite metric spaces.


  Event cameras detect changes in per-pixel intensity to generate asynchronous
`event streams'. They offer great potential for accurate semantic map retrieval
in real-time autonomous systems owing to their much higher temporal resolution
and high dynamic range (HDR) compared to conventional cameras. However,
existing implementations for event-based segmentation suffer from sub-optimal
performance since these temporally dense events only measure the varying
component of a visual signal, limiting their ability to encode dense spatial
context compared to frames. To address this issue, we propose a hybrid
end-to-end learning framework HALSIE, utilizing three key concepts to reduce
inference cost by up to $20\times$ versus prior art while retaining similar
performance: First, a simple and efficient cross-domain learning scheme to
extract complementary spatio-temporal embeddings from both frames and events.
Second, a specially designed dual-encoder scheme with Spiking Neural Network
(SNN) and Artificial Neural Network (ANN) branches to minimize latency while
retaining cross-domain feature aggregation. Third, a multi-scale cue mixer to
model rich representations of the fused embeddings. These qualities of HALSIE
allow for a very lightweight architecture achieving state-of-the-art
segmentation performance on DDD-17, MVSEC, and DSEC-Semantic datasets with up
to $33\times$ higher parameter efficiency and favorable inference cost (17.9mJ
per cycle). Our ablation study also brings new insights into effective design
choices that can prove beneficial for research across other vision tasks.


  Sparse matrix-matrix multiplication (SpGEMM) is a critical kernel widely
employed in machine learning and graph algorithms. However, real-world
matrices' high sparsity makes SpGEMM memory-intensive. In-situ computing offers
the potential to accelerate memory-intensive applications through high
bandwidth and parallelism. Nevertheless, the irregular distribution of
non-zeros renders SpGEMM a typical unstructured software. In contrast, in-situ
computing platforms follow a fixed calculation manner, making them structured
hardware. The mismatch between unstructured software and structured hardware
leads to sub-optimal performance of current solutions.
  In this paper, we propose SPLIM, a novel in-situ computing SpGEMM
accelerator. SPLIM involves two innovations. First, we present a novel
computation paradigm that converts SpGEMM into structured in-situ
multiplication and unstructured accumulation. Second, we develop a unique
coordinates alignment method utilizing in-situ search operations, effectively
transforming unstructured accumulation into high parallel searching operations.
Our experimental results demonstrate that SPLIM achieves 275.74$\times$
performance improvement and 687.19$\times$ energy saving compared to NVIDIA RTX
A6000 GPU.


  APIs are increasingly becoming new business assets for organizations and
consequently, API functionality and its pricing should be precisely defined for
customers. Pricing is typically composed by different plans that specify a
range of limitations, e.g., a Free plan allows 100 monthly requests while a
Gold plan has 10000 requests per month. In this context, the OpenAPI
Specification (OAS) has emerged to model the functional part of an API,
becoming a de facto industry standard and boosting a rich ecosystem of
vendor-neutral tools to assist API providers and consumers. In contrast, there
is no proposal for modeling API pricings (i.e. their plans and limitations) and
this lack hinders the creation of tools that can leverage this information. To
deal with this gap, this paper presents a pricing modeling framework that
includes: (a) Pricing4APIs model, a comprehensive and rigorous model of API
pricings, along SLA4OAI, a serialization that extends OAS; (b) an operation to
validate the description of API pricings, with a toolset (sla4oai-analyzer)
that has been developed to automate this operation. Additionally, we analyzed
268 real-world APIs to assess the expressiveness of our proposal and created a
representative dataset of 54 pricing models to validate our framework.


  We study the dispersive properties of the wave equation associated with the
shifted Laplace-Beltrami operator on Damek-Ricci spaces, and deduce Strichartz
estimates for a large family of admissible pairs. As an application, we obtain
global well-posedness results for the nonlinear wave equation.


  We present a spectroscopic analysis of an extremely rapidly rotating late
O-type star, VFTS102, observed during a spectroscopic survey of 30 Doradus.
VFTS102 has a projected rotational velocity larger than 500\kms\ and probably
as large as 600\kms; as such it would appear to be the most rapidly rotating
massive star currently identified. Its radial velocity differs by 40\kms\ from
the mean for 30 Doradus, suggesting that it is a runaway. VFTS102 lies 12 pcs
from the X-ray pulsar PSR J0537-6910 in the tail of its X-ray diffuse emission.
We suggest that these objects originated from a binary system with the
rotational and radial velocities of VFTS102 resulting from mass transfer from
the progenitor of PSR J0537-691 and the supernova explosion respectively.


  A binary game is introduced and analysed. N players have to choose one of the
two sides independently and those on the minority side win. Players uses a
finite set of ad hoc strategies to make their decision, based on the past
record. The analysing power is limited and can adapt when necessary.
Interesting cooperation and competition pattern of the society seem to arise
and to be responsive to the payoff function.


  I study the Chate-Manneville cellular automata rules on randomly connected
lattices. The periodic and quasi-periodic macroscopic behaviours associated
with these rules on finite-dimensional lattices persist on an
infinite-dimensional lattice with finite connectivity and symmetric bonds. The
lower critical connectivity for these models is at C=4 and the mean-field
connectivity, if finite, is not smaller than C=100. Autocorrelations are found
to decay as a power-law with a connectivity independent exponent approx. equal
to -2.5. A new intermitten chaotic phase is also discussed.


  Generalized Parton Distributions (GPDs) provide information on the
distribution of quarks in impact paarmeter space. For transversely polarized
nucleons, these impact parameter distributions are transversely distorted and
this deviation from axial symmetry leads on average to a net transverse force
from the spectators on the active quark in a DIS experiment. %The strength of
that force can be related to twist-3 PDFs. This force when acting along the
whole trajectory of the active quark leads to a transverse single-spin
asymmetries. For a longitudinally polarized nucleon target, the transverse
force implies a torque acting on the quark Orbital Angular Momentum (OAM). The
resulting change in OAM as the quark leaves the target equals the difference
between the Jaffe-Manohar and Ji OAMs.


  In recent years, weak lensing of the cosmic microwave background (CMB) has
emerged as a powerful tool to probe fundamental physics, such as neutrino
masses, primordial non-Gaussianity, dark energy, and modified gravity. The
prime target of CMB lensing surveys is the lensing potential, which is
reconstructed from observed CMB temperature $T$ and polarization $E$ and $B$
fields. Until very recently, this reconstruction has been performed with
quadratic estimators (QEs), which, although known to be suboptimal for
high-sensitivity experiments, are numerically efficient, and useful to make
forecasts and cross-check the results of more sophisticated likelihood-based
methods. It is expected that ongoing and near-future CMB experiments such as
AdvACT, SPT-3G and the Simons Observatory (SO), will also rely on QEs. Here, we
review different QEs, and clarify their differences. In particular, we show
that the Hu-Okamoto (HO02) estimator is not the absolute optimal lensing
estimator that can be constructed out of quadratic combinations of $T, E$ and
$B$ fields. Instead, we derive the global-minimum-variance (GMV) lensing
quadratic estimator. Although this estimator can be found elsewhere in the
literature, it was erroneously described as equivalent to the HO02 estimator,
and has never been used in real data analyses. Here, we show explicitly that
the HO02 estimator is suboptimal to the GMV estimator, with a reconstruction
noise larger by up to $\sim 9\%$ for a SO-like experiment. We further show that
the QE used in the Planck, and recent SPT lensing analysis are suboptimal to
both the HO02 and GMV estimator, and would have a reconstruction noise up to
$\sim 11\%$ larger than that of the GMV estimator for a SO-like experiment. In
addition to clarifying differences between different QEs, this work should thus
provide motivation to implement the GMV estimator in future lensing analyses
relying on QEs.


  We have studied the relativistic beamed outflow proposed to occur in the
collapsar model of gamma-ray bursts. A jet forms as a consequence of an assumed
energy deposition of $\sim 10^{50}- 10^{51}$ erg/s within a $30^{\circ}$ cone
around the rotation axis of the progenitor star. The generated jet flow is
strongly beamed ($\la$ few degrees) and reaches the surface of the stellar
progenitor (r $\approx 3 10^{10} $cm) intact. At break-out the maximum Lorentz
factor of the jet flow is about 33. Simulations have been performed with the
GENESIS multi-dimensional relativistic hydrodynamic code.


  Background: Real-time functional magnetic resonance imaging neurofeedback
(rtfMRI-nf) has proven to be a powerful technique to help subjects to gauge and
enhance emotional control. Traditionally, rtfMRI-nf has focused on emotional
regulation through self-regulation of amygdala. Recently, rtfMRI studies have
observed that regulation of a target brain region is accompanied by
connectivity changes beyond the target region. Therefore, the aim of present
study is to investigate the use of connectivity between amygdala and prefrontal
regions as the target of neurofeedback training in healthy individuals and
subjects with a life-time history of major depressive disorder (MDD) performing
an emotion regulation task. Method: Ten remitted MDD subjects and twelve
healthy controls (HC) performed an emotion regulation task in 4 runs of
rtfMRI-nf training followed by one transfer run without neurofeedback conducted
in a single session. The functional connectivity between amygdala and
prefrontal cortex was presented as a feedback bar concurrent with the emotion
regulation task. Participants' emotional state was measured by the Positive and
Negative Affect Schedule (PANAS) prior to and following the rtfMRI-nf.
Psychological assessments were used to determine subjects' history of
depression. Results: Participants with a history of MDD showed a trend of
decreasing functional connectivity across the four rtfMRI-nf runs, and there
was a marginally significant interaction between the MDD history and number of
training runs. The HC group showed a significant increase of frontal cortex
activation between the second and third neurofeedback runs. Comparing PANAS
scores before and after connectivity-based rtfMRI-nf, we observed a significant
decrease in negative PANAS score in the whole group overall, and a significant
decrease in positive PANAS score in the MDD group alone.


  The massive explosion and ubiquity of computing devices and the outreach of
the web have been the most defining events of the century so far. As more and
more people gain access to the internet, traditional know-something and
have-something authentication methods such as PINs and passwords are proving to
be insufficient for prohibiting unauthorized access to increasingly personal
data on the web. Therefore, the need of the hour is a user-verification system
that is not only more reliable and secure, but also unobtrusive and
minimalistic. Keystroke Dynamics is a novel Biometric Technique; it is not only
unobtrusive, but also transparent and inexpensive. The fusion of keystroke
dynamics and Face Recognition engenders the most desirable characteristics of a
verification system. Our implementation uses Hidden Markov Models (HMM) for
modelling the Keystroke Dynamics, with the help of two widely used Feature
Vectors: Keypress Latency and Keypress Duration. On the other hand, Face
Recognition makes use of the traditional Eigenfaces approach.The results show
that the system has a high precision, with a False Acceptance Rate of 5.4% and
a False Rejection Rate of 9.2%. Moreover, it is also future-proof, as the
hardware requirements, i.e. camera and keyboard (physical or on-screen), have
become an indispensable part of modern computing.


  One or more radio-frequency jumps are usually necessary for realizing a >=
100 AMeV/u proton or ion driver linac. Typically, such jumps happen in the
range of \b{eta} = 0.2-0.6 between the resonator structures fitting to this
\b{eta}-range, e.g. DTL, HWR, CCL or elliptical cavities. We propose to perform
the first frequency jump already at low energies (\b{eta} <= 0.1) between two
RFQ accelerators, which can bring some unique advantages. First studies have
been performed and the results proved that this idea is feasible and promising.
Many efforts have been and are being made to address the most critical issue
for the jumps i.e. the beam matching at the transition.


  We use SPH/N-body simulations to study the ram-pressure stripping of the gas
of dwarf galaxies orbiting in a disc galaxy. The effects of the gaseous disc
and halo on the satellites are analysed and the results are compared with the
observations of the dwarf spheroidals (and dwarf irregulars) in the Local
Group. The stripped gas is compared with the High Velocity Clouds. Finally, a
model of evolution of the dwarfs is proposed.


  This write up attempts to clarify a preprint by Markarian [2] which proves
This paper attempts to clarify a preprint of Markarian [2]. The preprint by
Markarian [2] proves the relative Riemann-Roch theorem using a result
describing how the HKR map fails to respect comultiplication. This paper
elaborates on the core computations in [2]. These computations show that the
HKR map twisted by the square root of the Todd genus "almost preserves" the
Mukai pairing. This settles a part of a conjecture of Caldararu[3]. The
relative Riemann-Roch theorem follows from this and a result of Caldararu[4].


  We explore the possibility of distinguishing the SM-like MSSM Higgs boson
from the SM Higgs boson via Higgs boson pair production at future muon
collider. We study the behavior of the production cross section in SM and MSSM
with Higgs boson mass for various choices of MSSM parameters tan \beta and
m\sub A. We observe that at fixed CM energy, in the SM, the total cross section
increases with the increase in Higgs boson mass whereas this trend is reversed
for the MSSM case. The changes that occur for the MSSM case in comparison to
the SM predictions are quantified in terms of the relative percentage deviation
in cross section. The observed large deviations in cross section for different
choices of Higgs mass suggest that the measurements of the cross section could
possibly distinguish the SM-like MSSM Higgs boson from the SM Higgs boson.


  We propose an extension of the quantum entropy power inequality for finite
dimensional quantum systems, and prove a conditional quantum entropy power
inequality by using the majorization relation as well as the concavity of
entropic functions also given by Audenaert, Datta, and Ozols [J. Math. Phys.
57, 052202 (2016)]. Here, we make particular use of the fact that a specific
local measurement after a partial swap operation (or partial swap quantum
channel) acting only on finite dimensional bipartite subsystems does not affect
the majorization relation for the conditional output states when a separable
ancillary subsystem is involved. We expect our conditional quantum entropy
power inequality to be useful, and applicable in bounding and analyzing several
capacity problems for quantum channels.


  We introduce generalized spatially coupled parallel concatenated codes
(GSC-PCCs), a class of spatially coupled turbo-like codes obtained by coupling
parallel concatenated codes (PCCs) with a fraction of information bits repeated
before the PCC encoding. GSC-PCCs can be seen as a generalization of the
original spatially coupled parallel concatenated convolutional codes (SC-PCCs)
proposed by Moloudi et al. [1]. To characterize the asymptotic performance of
GSC-PCCs, we derive the corresponding density evolution equations and compute
their decoding thresholds. We show that the proposed codes have some nice
properties such as threshold saturation and that their decoding thresholds
improve with the repetition factor $q$. Most notably, our analysis suggests
that the proposed codes asymptotically approach the capacity as $q$ tends to
infinity with any given constituent convolutional code.


  Numerous popular abstract strategy games ranging from Hex and Havannah to
Lines of Action belong to the class of connection games. Still, very few
complexity results on such games have been obtained since Hex was proved
PSPACE-complete in the early eighties. We study the complexity of two
connection games among the most widely played. Namely, we prove that Havannah
and TwixT are PSPACE-complete. The proof for Havannah involves a reduction from
Generalized Geography and is based solely on ring-threats to represent the
input graph. On the other hand, the reduction for TwixT builds up on previous
work as it is a straightforward encoding of Hex.