  Quantum mechanics in the presence of $\delta$-function potentials is known to
be plagued by UV divergencies which result from the singular nature of the
potentials in question. The standard method for dealing with these divergencies
is by constructing self-adjoint extensions of the corresponding Hamiltonians.
Two particularly interesting examples of this kind are nonrelativistic spin
zero particles in $\delta$-function potential and Dirac particles in
Aharonov-Bohm magnetic background. In this paper we show that by extending the
corresponding Schr\"odinger and Dirac equations onto the flat noncommutative
space a well-defined quantum theory can be obtained. Using a star product and
Fock space formalisms we construct the complete sets of eigenfunctions and
eigenvalues in both cases which turn out to be finite.


  Motivation: Computational methods are essential to extract actionable
information from raw sequencing data, and to thus fulfill the promise of
next-generation sequencing technology. Unfortunately, computational tools
developed to call variants from human sequencing data disagree on many of their
predictions, and current methods to evaluate accuracy and computational
performance are ad-hoc and incomplete. Agreement on benchmarking variant
calling methods would stimulate development of genomic processing tools and
facilitate communication among researchers.
  Results: We propose SMaSH, a benchmarking methodology for evaluating human
genome variant calling algorithms. We generate synthetic datasets, organize and
interpret a wide range of existing benchmarking data for real genomes, and
propose a set of accuracy and computational performance metrics for evaluating
variant calling methods on this benchmarking data. Moreover, we illustrate the
utility of SMaSH to evaluate the performance of some leading single nucleotide
polymorphism (SNP), indel, and structural variant calling algorithms.
  Availability: We provide free and open access online to the SMaSH toolkit,
along with detailed documentation, at smash.cs.berkeley.edu.


  The objective of this paper is to further investigate various applications of
information Nonanticipative Rate Distortion Function (NRDF) by discussing two
working examples, the Binary Symmetric Markov Source with parameter $p$
(BSMS($p$)) with Hamming distance distortion, and the multidimensional
partially observed Gaussian-Markov source. For the BSMS($p$), we give the
solution to the NRDF, and we use it to compute the Rate Loss (RL) of causal
codes with respect to noncausal codes. For the multidimensional Gaussian-Markov
source, we give the solution to the NRDF, we show its operational meaning via
joint source-channel matching over a vector of parallel Gaussian channels, and
we compute the RL of causal and zero-delay codes with respect to noncausal
codes.


  Contrary to common expectation, a left-sneutrinos can occasionally be the
lightest supersymmet- ric particle. This has important implications in both
collider and dark matter studies. We show that same-sign tri-lepton (SS3L)
events at the Large Hadron Collider, with any lepton having opposite sign
vetoed, distinguish such scenarios, up to gluino masses exceeding 2 TeV. The
jets + M ET signal rate is somewhat suppressed in this case, thus enhancing the
scope of leptonic signals.


  Informational parsimony provides a useful inductive bias for learning
representations that achieve better generalization by being robust to noise and
spurious correlations. We propose \textit{information gating} as a way to learn
parsimonious representations that identify the minimal information required for
a task. When gating information, we can learn to reveal as little information
as possible so that a task remains solvable, or hide as little information as
possible so that a task becomes unsolvable. We gate information using a
differentiable parameterization of the signal-to-noise ratio, which can be
applied to arbitrary values in a network, e.g., erasing pixels at the input
layer or activations in some intermediate layer. When gating at the input
layer, our models learn which visual cues matter for a given task. When gating
intermediate layers, our models learn which activations are needed for
subsequent stages of computation. We call our approach \textit{InfoGating}. We
apply InfoGating to various objectives such as multi-step forward and inverse
dynamics models, Q-learning, and behavior cloning, highlighting how InfoGating
can naturally help in discarding information not relevant for control. Results
show that learning to identify and use minimal information can improve
generalization in downstream tasks. Policies based on InfoGating are
considerably more robust to irrelevant visual features, leading to improved
pretraining and finetuning of RL models.


  In this work we introduce an interbank network with stochastic dynamics
subject to an endogenous notion of distress contagion that accounts for worries
about future defaults within the network. Specifically, this entails a
forward-backward approach to the equilibrium dynamics, enforced by a
mark-to-market valuation adjustment for interbank claims, whereby the
conditional probabilities of future defaults are required to determine today's
balance sheets. Distinct from static models, the resulting distress contagion
acts as a stochastic volatility term which leads, endogenously, to volatility
clustering and a marked downside leverage effect. Moreover, by considering
multiple maturities, our model provides a systemic risk-aware term structure
for interbank claims. We present the analysis in two parts: (i) a single
maturity setting that closely matches the traditional interbank network
literature, and (ii) a multiple maturity setting to examine the impact of
systemic risk on the full term structure. Numerical case studies are presented
throughout to demonstrate the financial implications of this systemic risk
model.


  Maser transitions are commonly observed in media exhibiting a large range of
densities and temperatures. They can be used to obtain information on the
dynamics and physical conditions of the observed regions. In order to obtain
reliable constraints on the physical conditions prevailing in the masing
regions, it is necessary to model the excitation mechanisms of the energy
levels of the observed molecules. We present a numerical method that enables us
to obtain self-consistent solutions for both the statistical equilibrium and
radiative transfer equations. Using the standard maser theory, the method of
Short Characteristics is extended to obtain the solution of the
integro-differential radiative transfer equation, appropriate to the case of
intense masing lines. We have applied our method to the maser lines of the H2O
molecule and we compare with the results obtained with a less accurate
approach. In the regime of large maser opacities we find large differences in
the intensity of the maser lines that could be as high as several orders of
magnitude. The comparison between the two methods shows, however, that the
effect on the thermal lines is modest. Finally, the effect introduced by rate
coefficients on the prediction of H2O masing lines and opacities is discussed,
making use of various sets of rate coefficients involving He, o-H2 and p-H2. We
find that the masing nature of a line is not affected by the selected
collisional rates. However, from one set to the other the modelled line
opacities and intensities can vary by up to a factor ~2 and ~10 respectively.


  Dwell time has been widely used in various fields to evaluate content quality
and user engagement. Although many studies shown that content with long dwell
time is good quality, contents with short dwell time have not been discussed in
detail. We hypothesize that content with short dwell time is not always low
quality and does not always have low user engagement, but is instead related to
user interest. The purpose of this study is to clarify the meanings of short
dwell time browsing in mobile news application. First, we analyze the relation
of short dwell time to user interest using large scale user behavior logs from
a mobile news application. This analysis was conducted on a vector space based
on users click histories and then users and articles were mapped in the same
space. The users with short dwell time are concentrated on a specific position
in this space; thus, the length of dwell time is related to their interest.
Moreover, we also analyze the characteristics of short dwell time browsing by
excluding these browses from their click histories. Surprisingly, excluding
short dwell time click history, it was found that short dwell time click
history included some aspect of user interest in 30.87% of instances where the
cluster of users changed. These findings demonstrate that short dwell time does
not always indicate a low level of user engagement, but also level of user
interest.


  We study finite capable $p$-groups $G$ of nilpotency class 2 such that the
commutator subgroup $\gamma_2(G)$ of $G$ is cyclic and the center of $G$ is
contained in the Frattini subgroup of $G$.


  In this work, we present a novel meta-learning algorithm, i.e. TTNet, that
regresses model parameters for novel tasks for which no ground truth is
available (zero-shot tasks). In order to adapt to novel zero-shot tasks, our
meta-learner learns from the model parameters of known tasks (with ground
truth) and the correlation of known tasks to zero-shot tasks. Such intuition
finds its foothold in cognitive science, where a subject (human baby) can adapt
to a novel-concept (depth understanding) by correlating it with old concepts
(hand movement or self-motion), without receiving explicit supervision. We
evaluated our model on the Taskonomy dataset, with four tasks as zero-shot:
surface-normal, room layout, depth, and camera pose estimation. These tasks
were chosen based on the data acquisition complexity and the complexity
associated with the learning process using a deep network. Our proposed
methodology out-performs state-of-the-art models (which use ground truth)on
each of our zero-shot tasks, showing promise on zero-shot task transfer. We
also conducted extensive experiments to study the various choices of our
methodology, as well as showed how the proposed method can also be used in
transfer learning. To the best of our knowledge, this is the firstsuch effort
on zero-shot learning in the task space.


  In this paper, we highlight that the point group structure of elliptic curves
over finite or infinite fields, may be also observed on singular cubics with a
quadratic component. Starting from this, we are able to introduce in a very
general way a group's structure over any kind of conics. In the case of conics
over finite fields, we see that the point group is cyclic and lies on the
quadric; the straight line component plays a role which may be not explicitly
visible in the algebraic description of point composition, but it is
indispensable in the geometric description. Moreover, some applications to
cryptography are described, considering convenient parametrizations of the
conics. Finally, we perform an evaluation of the complexity of the operations
involved in the parametric groups and consequently in the cryptographic
applications.


  We consider a multi-user multiple input single output (MU-MISO) system
assisted by a reconfigurable intelligent surface (RIS). For such a system, we
aim to optimally select the RIS phase shifts and precoding vectors for
maximizing the effective rank of the weighted channel covariance matrix which
in turn improves the channel capacity. For a low-complex transmitter design, we
employ maximum ratio transmission (MRT) and minimum-mean square error (MMSE)
precoding schemes along with water-filling algorithm-based power allocation.
Further, we show that MRT and MMSE exhibit equivalent performance and become
optimal when the channel effective rank is maximized by optimally configuring
the RIS consisting of a large number of elements.


  Given two algebraic groups $G$, $H$ over a field $k$, we investigate the
representability of the functor of morphisms (of schemes) $\mathbf{Hom}(G,H)$
and the subfunctor of homomorphisms (of algebraic groups) $\mathbf{Hom}_{\rm
gp}(G,H)$. We show that $\mathbf{Hom}(G,H)$ is represented by a group scheme,
locally of finite type, if the $k$-vector space $\mathcal{O}(G)$ is
finite-dimensional; the converse holds if $H$ is not \'etale. When $G$ is
linearly reductive and $H$ is smooth, we show that $\mathbf{Hom}_{\rm gp}(G,H)$
is represented by a smooth scheme $M$; moreover, every orbit of $H$ acting by
conjugation on $M$ is open.


  Sparse computation offers a compelling solution for the inference of Large
Language Models (LLMs) in low-resource scenarios by dynamically skipping the
computation of inactive neurons. While traditional approaches focus on
ReLU-based LLMs, leveraging zeros in activation values, we broaden the scope of
sparse LLMs beyond zero activation values. We introduce a general method that
defines neuron activation through neuron output magnitudes and a tailored
magnitude threshold, demonstrating that non-ReLU LLMs also exhibit sparse
activation. To find the most efficient activation function for sparse
computation, we propose a systematic framework to examine the sparsity of LLMs
from three aspects: the trade-off between sparsity and performance, the
predictivity of sparsity, and the hardware affinity. We conduct thorough
experiments on LLMs utilizing different activation functions, including ReLU,
SwiGLU, ReGLU, and ReLU$^2$. The results indicate that models employing
ReLU$^2$ excel across all three evaluation aspects, highlighting its potential
as an efficient activation function for sparse LLMs. We will release the code
to facilitate future research.


  Multi-task learning (MTL) has been widely used in recommender systems,
wherein predicting each type of user feedback on items (e.g, click, purchase)
are treated as individual tasks and jointly trained with a unified model. Our
key observation is that the prediction results of each task may contain
task-specific knowledge about user's fine-grained preference towards items.
While such knowledge could be transferred to benefit other tasks, it is being
overlooked under the current MTL paradigm. This paper, instead, proposes a
Cross-Task Knowledge Distillation framework that attempts to leverage
prediction results of one task as supervised signals to teach another task.
However, integrating MTL and KD in a proper manner is non-trivial due to
several challenges including task conflicts, inconsistent magnitude and
requirement of synchronous optimization. As countermeasures, we 1) introduce
auxiliary tasks with quadruplet loss functions to capture cross-task
fine-grained ranking information and avoid task conflicts, 2) design a
calibrated distillation approach to align and distill knowledge from auxiliary
tasks, and 3) propose a novel error correction mechanism to enable and
facilitate synchronous training of teacher and student models. Comprehensive
experiments are conducted to verify the effectiveness of our framework in
real-world datasets.


  Let $n=2,3,4,5$ and let $X$ be a smooth complex projective hypersurface of
$\mathbb P^{n+1}$. In this paper we find an effective lower bound for the
degree of $X$, such that every holomorphic entire curve in $X$ must satisfy an
algebraic differential equation of order $k=n=\dim X$, and also similar bounds
for order $k>n$. Moreover, for every integer $n\ge 2$, we show that there are
no such algebraic differential equations of order $k<n$ for a smooth
hypersurface in $\mathbb P^{n+1}$.


  Magnetoelastic properties of the spin-1/2 Ising-Heisenberg model on doubly
decorated planar lattices partially amenable to lattice vibrations are examined
within the framework of the harmonic approximation and decoration-iteration
transformation. It is shown that the mutual interplay between quantum spin
fluctuations and local fluctuations of lattice spacings enhances typical
quantum features like the quantum reduction of the magnetization in the ground
state of the quantum antiferromagnetic phase, while it does not affect the
ground-state behaviour of the classical ferromagnetic phase by no means. It
also turns out that local fluctuations of lattice spacings are responsible for
a much more pronounced reduction of the critical temperature in the quantum
antiferromagnetic phase than in the classical ferromagnetic phase.


  As a result of the search for the identity of the chromophores responsible
for producing the diffuse interstellar bands, a comprehensive exposition of
experimental data is presented, which implicates the following molecules- 1.
The extremely stable organic molecules, magnesium tetrabenzoporphyrin (MgTBP)
and H2TBP. 2. A paraffin matrix (referred to as grains) containing TBPs. 3. A
low concentration of pyridine (also within the grains), whose transmission
window at 2175 Angstroms, accounts for the ubiquitous UV bump. The blue
emission spectra associated with the central star, HD44179, of the Red
Rectangle displays the fluorescence excitation spectra of bare MgTBP. This
unique spectrum matches the low temperature lab data of MgTBP in the vapor
phase. An effective grain temperature of 2.728 K (plus or minus 0.008) was
deduced, based on MgTBPs lowest measured vibrational state of 341 GHz.


  Spectral singularities are spectral points that spoil the completeness of the
eigenfunctions of certain non-Hermitian Hamiltonian operators. We identify
spectral singularities of complex scattering potentials with the real energies
at which the reflection and transmission coefficients tend to infinity, i.e.,
they correspond to resonances having a zero width. We show that a wave guide
modeled using such a potential operates like a resonator at the frequencies of
spectral singularities. As a concrete example, we explore the spectral
singularities of an imaginary PT-symmetric barrier potential and demonstrate
the above resonance phenomenon for a certain electromagnetic wave guide.


  This paper employs switching-algebraic techniques for the calculation of a
fundamental index of voting powers, namely, the total Banzhaf power. This
calculation involves two distinct operations: (a) Boolean differencing or
differentiation, and (b) computation of the weight (the number of true vectors
or minterms) of a switching function. Both operations can be considerably
simplified and facilitated if the pertinent switching function is symmetric or
it is expressed in a disjoint sum-of-products form. We provide a tutorial
exposition on how to implement these two operations, with a stress on
situations in which partial symmetry is observed among certain subsets of a set
of arguments. We introduce novel Boolean-based symmetry-aware techniques for
computing the Banzhaf index by way of two prominent voting systems. These are
scalar systems involving six variables and nine variables, respectively. The
paper is a part of our ongoing effort for transforming the methodologies and
concepts of voting systems to the switching-algebraic domain, and subsequently
utilizing switching-algebraic tools in the calculation of pertinent quantities
in voting theory.


  Here, we describe a method for the enhanced self-assembly of triblock Janus
colloids targeted to form a kagome lattice. Using computer simulations, we
demonstrate that the formation of this elusive structure can be significantly
improved by self-propelling or activating the colloids along the axis
connecting their hydrophobic hemispheres. The process by which metastable
aggregates are destabilized and transformed into the favored kagome lattice is
quite general, and we argue this active approach provides a systematic pathway
to improving the self-assembly of a large number of colloidal structures.


  This article describes lossless compression algorithms for multisets of
sequences, taking advantage of the multiset's unordered structure. Multisets
are a generalisation of sets where members are allowed to occur multiple times.
A multiset can be encoded na\"ively by simply storing its elements in some
sequential order, but then information is wasted on the ordering. We propose a
technique that transforms the multiset into an order-invariant tree
representation, and derive an arithmetic code that optimally compresses the
tree. Our method achieves compression even if the sequences in the multiset are
individually incompressible (such as cryptographic hash sums). The algorithm is
demonstrated practically by compressing collections of SHA-1 hash sums, and
multisets of arbitrary, individually encodable objects.


  Background and Aims: The methods with which prediction models are usually
developed mean that neither the parameters nor the predictions should be
interpreted causally. However, when prediction models are used to support
decision making, there is often a need for predicting outcomes under
hypothetical interventions. We aimed to identify published methods for
developing and validating prediction models that enable risk estimation of
outcomes under hypothetical interventions, utilizing causal inference: their
main methodological approaches, underlying assumptions, targeted estimands, and
potential pitfalls and challenges with using the method, and unresolved
methodological challenges.
  Methods: We systematically reviewed literature published by December 2019,
considering papers in the health domain that used causal considerations to
enable prediction models to be used for predictions under hypothetical
interventions.
  Results: We identified 4919 papers through database searches and a further
115 papers through manual searches, of which 13 were selected for inclusion,
from both the statistical and the machine learning literature. Most of the
identified methods for causal inference from observational data were based on
marginal structural models and g-estimation.
  Conclusions: There exist two broad methodological approaches for allowing
prediction under hypothetical intervention into clinical prediction models: 1)
enriching prediction models derived from observational studies with estimated
causal effects from clinical trials and meta-analyses; and 2) estimating
prediction models and causal effects directly from observational data. These
methods require extending to dynamic treatment regimes, and consideration of
multiple interventions to operationalise a clinical decision support system.
Techniques for validating 'causal prediction models' are still in their
infancy.


  We compute bounds and forecasts on screened modified gravity theories,
specialising to the chameleon model in Casimir force experiments. In
particular, we investigate the classical interaction between a plate and sphere
subject to a screened interaction of the chameleon type. We compare numerical
simulations of the field profile and the classical pressure exerted on the
sphere to analytical approximations for these non-linear field theories. In
particular, we focus on the proximity force approximation (PFA) and show that,
within the range of sphere sizes $R$ and plate-sphere distance $D$ simulated
numerically, the PFA does not reproduce the numerical results. This differs
from the case of linear field theories such as Newtonian gravity and a Yukawa
model where the PFA coincides with the exact results. We show that for
chameleon theories, the screening factor approximation (SFA) whereby the sphere
is modelled as a screened sphere embedded in the external field due to the
plates, fares better and can be used in the regime $D\gtrsim R$ to extract
constraints and forecasts from existing and forthcoming data. In particular, we
forecast that future Casimir experiments would corroborate the closing of the
parameter space for the simplest of chameleon models at the dark energy scale.


  This draft paper presents a workflow for creating User Personas with Large
Language Models, using the results of a Thematic Analysis of qualitative
interviews. The proposed workflow uses improved prompting and a larger pool of
Themes, compared to previous work conducted by the author for the same task.
This is possible due to the capabilities of a recently released LLM which
allows the processing of 16 thousand tokens (GPT3.5-Turbo-16k) and also due to
the possibility to offer a refined prompting for the creation of Personas. The
paper offers details of performing Phase 2 and 3 of Thematic Analysis, and then
discusses the improved workflow for creating Personas. The paper also offers
some reflections on the relationship between the proposed process and existing
approaches to Personas such as the data-driven and qualitative Personas.
Moreover, the paper offers reflections on the capacity of LLMs to capture user
behaviours and personality traits, from the underlying dataset of qualitative
interviews used for the analysis.


  Event argument extraction (EAE) is an important task for information
extraction to discover specific argument roles. In this study, we cast EAE as a
question-based cloze task and empirically analyze fixed discrete token template
performance. As generating human-annotated question templates is often
time-consuming and labor-intensive, we further propose a novel approach called
"Learning to Ask," which can learn optimized question templates for EAE without
human annotations. Experiments using the ACE-2005 dataset demonstrate that our
method based on optimized questions achieves state-of-the-art performance in
both the few-shot and supervised settings.


Every smooth homotopy 4-sphere is diffeomorphic to the 4-sphere.


  Interference is a ubiquitous problem in experiments conducted on two-sided
content marketplaces, such as Douyin (China's analog of TikTok). In many cases,
creators are the natural unit of experimentation, but creators interfere with
each other through competition for viewers' limited time and attention. "Naive"
estimators currently used in practice simply ignore the interference, but in
doing so incur bias on the order of the treatment effect. We formalize the
problem of inference in such experiments as one of policy evaluation.
Off-policy estimators, while unbiased, are impractically high variance. We
introduce a novel Monte-Carlo estimator, based on "Differences-in-Qs" (DQ)
techniques, which achieves bias that is second-order in the treatment effect,
while remaining sample-efficient to estimate. On the theoretical side, our
contribution is to develop a generalized theory of Taylor expansions for policy
evaluation, which extends DQ theory to all major MDP formulations. On the
practical side, we implement our estimator on Douyin's experimentation
platform, and in the process develop DQ into a truly "plug-and-play" estimator
for interference in real-world settings: one which provides robust, low-bias,
low-variance treatment effect estimates; admits computationally cheap,
asymptotically exact uncertainty quantification; and reduces MSE by 99\%
compared to the best existing alternatives in our applications.


  We study the search potential of heavy triplet leptons in Type III Seesaw
mechanism at future high-energy and high-luminosity muon colliders. The impact
of up-to-date neutrino oscillation results is taken into account on neutrino
parameters and the consequent decay patterns of heavy leptons in Type III
Seesaw. The three heavy leptons in the Casas-Ibarra parametrization with
diagonal unity matrix are distinguishable in their decay modes. We consider the
pair production of charged triplet leptons $E^+ E^-$ through both $\mu^+\mu^-$
annihilation and vector boson fusion (VBF) processes. The leading-order
framework of electroweak parton distribution functions are utilized to
calculate the VBF cross sections. The charged triplet leptons can be probed for
masses above $\sim 1$ TeV. The $E^+E^-\to ZZ\ell^+\ell^-$ channel can be
further utilized to fully reconstruct the three triplet leptons and distinguish
neutrino mass patterns. The pair production of heavy neutrinos $N$ and the
associated production $E^\pm N$ are only induced by VBF processes and lead to
lepton-number-violating (LNV) signature. We also study the search potential of
LNV processes at future high-energy muon collider with $\sqrt{s}=30$ TeV.


  This paper explores the time-domain equations of noble metals, in which Drude
model is adopted to describe the dielectric constant, to implement
three-dimensional particle-in-cell (PIC) simulations for the surface plasmon
excitation with the finite-difference time-domain method (FDTD). A
three-dimensional model for an electron bunch movement near the metal film is
constructed, and particle-in-cell (PIC) simulations are carried out with
various metal films of different thicknesses. The frequency of surface plasmon
obtained from PIC simulation is agreed with that from theory. Furthermore, the
surface plasmon wave properties of excitation and propagation with the metal
film is summarized by PIC results.


  An additive manufacturing method is presented for embedding optical
fibre-based pressure sensors into the lining of sports helmets to monitor head
impact in contact sports. Proof-of-concept thermoplastic polyurethane (TPU)
helmet padding segments with embedded sensors are demonstrated for their
sensitive shock-monitoring capabilities. The system offers a cost-effective
solution for manufacturing consumer products at scale, is unobtrusive, and can
be powered by medical-grade cell batteries requiring low maintenance.


  In this note we set-up an explicit 5D construction of AdS-fragmentation,
whereby a single black ring splits-up into a multi-black ring configuration.
Furthermore it is seen that these fragmented rings are equivalent to a direct
5D lift of 4D multi-center black holes. Along the way we also determine the
4D/5D transformations relevant for multi-center charges. It is seen that the
physical charges involved in black ring fragmentation are Page charges arising
due to 5D Chern-Simons terms. As an application of these methods, we reproduce
the total angular momentum of concentric black rings, originally due to
Gauntlett and Gutowski. Finally we provide a geometric interpretation of
fragmented black rings using the idea of split-spectral flows, which seeks to
study charge shifts of a given black ring due to fluxes generated in a
multi-ring background.


  The ALICE experiment, currently in the commissioning phase, will study
nucleus-nucleus and proton-proton collisions at the CERN Large Hadron Collider
(LHC). We review the ALICE heavy-flavour physics program and present a
selection of results on the expected performance for the case of proton-proton
collisions.


  The time evolution of cosmological parameters in early Universe at the
deconfinement transition is studied by an equation of state (EoS) which takes
into account the finite baryon density and the background magnetic field. The
non perturbative dynamics is described by the Field Correlator Method (FCM)
which gives, with a small number of free parameters, a good fit of lattice
data. The entire system has two components, i.e. the quark-gluon plasma and the
electroweak sector, and the solutions of the Friedmann equation show that the
scale factor, $a(t)$, and $H(t)= (1/a)da/dt$ are weakly dependent on the EoS,
but the deceleration parameter, $q(t)$, and the jerk, $j(t)$, are strongly
modified above the critical temperature $T_c$, corresponding to a critical time
$t_c \simeq 20-25 \mu s$. The time evolution of the cosmological parameters
suggest that above and around $T_c$ there is a transient state of acceleration
typical of a matter dominated Universe; this is entailed by the QCD strong
interaction driven by the presence of massive colored objects.


  We show that the classification of shearless and incompressible stationary
fluid flows on ultrastatic manifolds is equivalent to classifying the
isometries of the spatial sections. For a flow on R x S$^2$ this leaves only
one possibility, since on the 2-sphere all Killing fields are conjugate to each
other, and it is well-known that the gravity dual of such a (conformal) fluid
is the spherical KNAdS$_4$ black hole. On the other hand, in R x H$^2$ the
situation is more complicated, since the isometry group of H$^2$ admits
elliptic, parabolic and hyperbolic elements. One might thus ask what the
gravity duals of the flows corresponding to these three different cases are.
Answering this question is one of the scopes of this paper. In particular we
identify the black hole dual to a fluid that is purely translating on the
hyperbolic plane. Although this lies within the Carter-Plebanski (CP) class, it
has never been studied in the literature before, and represents thus in
principle a new black hole solution in AdS$_4$. For a rigidly rotating fluid in
R x H$^2$ (holographically dual to the hyperbolic KNAdS$_4$ solution), there is
a certain radius where the velocity reaches the speed of light, and thus the
fluid can cover only the region within this radius. Quite remarkably, it turns
out that the boundary of the hyperbolic KNAdS$_4$ black hole is conformal to
exactly that part of R x H$^2$ in which the fluid velocity does not exceed the
speed of light. We extend these results to establish a precise mapping between
possible flows on ultrastatic spacetimes (with constant curvature spatial
sections) and the parameter space of the CP solution. Finally, we show that the
alternative description of the hyperbolic KNAdS$_4$ black hole in terms of
fluid mechanics on R x S$^2$ or on flat space is dynamical and consists of a
contracting or expanding vortex.


  Three observational constraints can be placed on a warm-hot intergalactic
medium (WHIM) using \rosat PSPC pointed and survey data, the emission strength,
the energy spectrum, and the fluctuation spectrum. The upper limit to the
emission strength of the WHIM is 7.5 +/- 1.0 keV s^-1 cm^-2 sr^-1 keV^-1 in the
3/4 keV band, an unknown portion of which value may be due to our own Galactic
halo. The spectral shape of the WHIM emission can be described as thermal
emission with log T=6.42, although the true spectrum is more likely to come
from a range of temperatures. The values of emission strength and spectral
shape are in reasonable agreement with hydrodynamical cosmological models. The
autocorrelation function in the 0.44 keV < E < 1.21 keV band range, w(theta),
for the extragalactic soft X-ray background (SXRB) which includes both the WHIM
and contributions due to point sources, is less than about 0.002 for 10
arcminutes < theta < 20 arcminutes in the 3/4 keV band. This value is lower
than the Croft et al. (2000) cosmological model by a factor of about 5, but is
still not inconsistent with cosmological models. It is also found that the
normalization of the extragalactic power law component of the soft X-ray
background spectrum must be 9.5 +/- 0.9 keV s^-1 cm^-2 sr^-1 keV^-1 to be
consistent with the ROSAT All-Sky Survey.


  Transmission spectroscopy has been a workhorse technique over the past two
decades to constrain the physical and chemical properties of exoplanet
atmospheres. One of its classical key assumptions is that the portion of the
atmosphere it probes -- the terminator region -- is homogeneous. Several works
in the past decade, however, have put this into question for highly irradiated,
hot ($T_{eq}\gtrsim 1000$ K) gas giant exoplanets both empirically and via
3-dimensional modelling. While models predict clear differences between the
evening (day-to-night) and morning (night-to-day) terminators, direct
morning/evening transmission spectra in a wide wavelength range has not been
reported for an exoplanet to date. Under the assumption of precise and accurate
orbital parameters on WASP-39 b, here we report the detection of inhomogeneous
terminators on the exoplanet WASP-39 b, which allows us to retrieve its morning
and evening transmission spectra in the near-infrared ($2-5\ \mu$m) using JWST.
We observe larger transit depths in the evening which are, on average, $405 \pm
88$ ppm larger than the morning ones, also having qualitatively larger features
than the morning spectrum. The spectra are best explained by models in which
the evening terminator is hotter than the morning terminator by
$177^{+65}_{-57}$ K with both terminators having C/O ratios consistent with
solar. General circulation models (GCMs) predict temperature differences
broadly consistent with the above value and point towards a cloudy morning
terminator and a clearer evening terminator.


  We consider the Bloch-Torrey operator in $L^2(I,{\mathbb R}^3)$ where
$I\subseteq{\mathbb R}$. In contrast with the $L^2(I,{\mathbb R}^2)$ (as well
as the $L^2({\mathbb R}^k,{\mathbb R}^2)$) case considered in previous works.
We obtain that ${\mathbb R}_+$ is in the continuous spectrum for $I={\mathbb
R}$ as well as discrete spectrum outside the real line. For a finite interval
we find the left margin of the spectrum. In addition, we prove that the
Bloch-Torrey operator must have an essential spectrum for a rather general
setup in ${\mathbb R}^k$, and find an effective description for its domain.


  The set of degrees of maps $D(M,N)$, where $M,N$ are closed oriented
$n$-manifolds, always contains $0$ and the set of degrees of self-maps $D(M)$
always contains $0$ and $1$. Also, if $a,b\in D(M)$, then $ab\in D(M)$; a set
$A\subseteq\mathbb Z$ so that $ab\in A$ for each $a,b\in A$ is called
multiplicative. On the one hand, not every infinite set of integers (containing
$0$) is a mapping degree set [NWW] and, on the other hand, every finite set of
integers (containing $0$) is the mapping degree set of some $3$-manifolds
[CMV]. We show the following:
  (i) Not every multiplicative set $A$ containing $0,1$ is a self-mapping
degree set.
  (ii) For each $n\in\mathbb N$ and $k\geq3$, every $D(M,N)$ for $n$-manifolds
$M$ and $N$ is $D(P,Q)$ for some $(n+k)$-manifolds $P$ and $Q$.
  As a consequence of (ii) and [CMV], every finite set of integers (containing
$0$) is the mapping degree set of some $n$-manifolds for all $n\neq 1,2,4,5$.


  We briefly summarize the impact of the recent Planck measurements for string
inflationary models, and outline what might be expected to be learned in the
near future from the expected improvement in sensitivity to the primordial
tensor-to-scalar ratio. We comment on whether these models provide sufficient
added value to compensate for their complexity, and ask how they fare in the
face of the new constraints on non-gaussianity and dark radiation. We argue
that as a group the predictions made before Planck agree well with what has
been seen, and draw conclusions from this about what is likely to mean as
sensitivity to primordial gravitational waves improves.


  To confirm, or rule out, the possible hot spot nature of two previously
detected radio sources in the vicinity of the Cygnus X-3 microquasar.
  We present the results of a radio and near infrared exploration of the
several arc-minute field around the well known galactic relativistic jet source
Cygnus X-3 using the Very Large Array and the Calar Alto 3.5~m telescope.
  The data this paper is based on do not presently support the hot spot
hypothesis. Instead, our new observations suggest that these sources are most
likely background or foreground objects. Actually, none of them appears to be
even barely extended as would be expected if they were part of a bow shock
structure. Our near infrared observations also include a search for extended
emission in the Bracket $\gamma$ (2.166 $\mu$m) and $H_{2}$ (2.122 $\mu$m)
lines as possible tracers of shocked gas in the Cygnus X-3 surroundings. The
results were similarly negative and the corresponding upper limits are
reported.


  We generalize the Embedding Theorem of Eisenbud-Harris from classical
Brill-Noether theory to the setting of Hurwitz-Brill-Noether theory.
  More precisely, in classical Brill-Noether theory, the embedding theorem
states that a general linear series of degree d and rank r on a general curve
of genus g is an embedding if r is at least 3. If \(f \colon C \to
\mathbb{P}^1\) is a general cover of degree k, and L is a line bundle on C,
recent work of the authors shows that the splitting type of \(f_* L\) provides
the appropriate generalization of the pair (r, d) in classical Brill--Noether
theory.
  In the context of Hurwitz-Brill-Noether theory, the condition that r is at
least 3 is no longer sufficient to guarantee that a general such linear series
is an embedding. We show that the additional condition needed to guarantee that
a general linear series |L| is an embedding is that the splitting type of \(f_*
L\) has at least three nonnegative parts. This new extra condition reflects the
unique geometry of k-gonal curves, which lie on scrolls in \(\mathbb{P}^r\).


  Earlier it was described to which extent the Alexander polynomial in several
variables of an algebraic link in the Poincar\'e sphere determines the topology
of the link. It was shown that, except some explicitly described cases, the
Alexander polynomial of an algebraic link determines the combinatorial type of
the minimal resolution of the curve and therefore the topology of the
corresponding link. The Alexander polynomial of an algebraic link in the
Poincar\'e sphere coincides with the Poincar\'e series of the corresponding set
of curve valuations. The latter one can be defined as an integral over the
space of divisors on the $E_8$-singularity. Here we consider a similar integral
for rational double point surface singularities over the space of Weil divisors
called the Weil-Poincar\'e series. We show that, except a few explicitly
described cases the Weil-Poincar\'e series of a collection of curve valuations
on a rational double point surface singularity determines the topology of the
corresponding link. We give analogous statements for collections of divisorial
valuations.


  We present our study of $\pi-N$ scattering in the iso-spin $I=3/2$ channel
for the first time at the physical point. The calculation is performed using
$N_f=2+1+1$ flavors of twisted mass fermions with clover improvement at
physical pion mass. We compute energy levels for the rest frame and moving
frames up to a total momentum of $|\vec{P}|=\sqrt{3} \,\frac{2\pi}{L}$, and for
all the relevant ireducible representations of the lattice symmetry groups. We
perform a phase-shift analysis including $s\,(\ell=0)$ and $p\,(\ell=1)$ wave
phase shifts assuming a Breit-Wigner form and determine the parameters of the
$\Delta$ resonance.


  This work studies some aspects of the computational power of fully
asynchronous cellular automata (ACA). We deal with some notions of simulation
between ACA and Turing Machines. In particular, we characterize the updating
sequences specifying which are "universal", i.e., allowing a (specific family
of) ACA to simulate any TM on any input. We also consider the computational
cost of such simulations.


  We demonstrate that the fluctuation theorem of Gallavotti and Cohen can be
used to characterize the class of dynamics that arises in nonthermal systems of
collectively interacting particles driven over random quenched disorder. By
observing the frequency of entropy-destroying trajectories, we show that there
are specific dynamical regimes near depinning in which this theorem holds.
Hence the fluctuation theorem can be used to characterize a significantly wider
class of nonequilibrium systems than previously considered. We discuss how the
fluctuation theorem could be tested in specific systems where noisy dynamics
appear at the transition from a pinned to a moving phase such as in vortices in
type-II superconductors, magnetic domain walls, and dislocation dynamics.


  Deep rest-optical observations are required to accurately constrain the
stellar populations of $z\sim8$ galaxies. Due to significant limitations in the
availability of such data for statistically complete samples, observational
results have been limited to modest numbers of bright or lensed sources. To
revolutionize the present characterization of $z\sim8$ galaxies, we exploit the
ultradeep ($\sim27$ mag, $3\sigma$) Spitzer/IRAC $3.6\mu$m and $4.5\mu$m data,
probing the rest-frame optical at $z\sim8$, over $\sim200$ arcmin$^2$ of the
GOODS fields from the recently completed GOODS Re-ionization Era wide-Area
Treasury from Spitzer (GREATS) program, combined with observations in the
CANDELS UDS and COSMOS fields. We stacked $\gtrsim100$ $z\sim8$ Lyman-Break
galaxies in four bins of UV luminosity ($M_\mathrm{UV}\sim -20.7$ to $-18.4$)
and study their $H_\mathrm{160}-[3.6]$ and $[3.6]-[4.5]$ colors. We find young
ages ($\lesssim100$ Myr) for the three faintest stacks, inferred from their
blue $H_\mathrm{160}-[3.6]\sim 0$ mag colors, consistent with a negative Balmer
break. Meanwhile, the redder $H_\mathrm{160}-[3.6]$ color seen in the brightest
stack is suggestive of slightly older ages. We explored the existence of a
correlation between the UV luminosity and age, and find either no trend or
fainter galaxies being younger. The stacked SEDs also exhibit very red
$[3.6]-[4.5]\sim0.5$ mag colors, indicative of intense [OIII]+H$\beta$ nebular
emission and SFR. The correspondingly high specific star-formation rates,
sSFR$\gtrsim10$Gyr$^{-1}$, are consistent with recent determinations at similar
redshifts and higher luminosities, and support the co-evolution between the
sSFR and the specific halo mass accretion rate.


  The site preference and magnetic properties of Zn, Sn and Zn-Sn substituted
M-type strontium hexaferrite (SrFe$_{12}$O$_{19}$) have been investigated using
first-principles total energy calculations based on density functional theory.
The site occupancy of substituted atoms were estimated by calculating the
substitution energies of different configurations. The distribution of
different configurations during the annealing process at high temperature was
determined using the formation probabilities of configurations to calculate
magnetic properties of substituted strontium hexaferrite. We found that the
magnetization and magnetocrystalline anisotropy are closely related to the
distributions of Zn-Sn ions on the five Fe sites. Our calculation show that in
SrFe$_{11.5}$Zn$_{0.5}$O$_{19}$, Zn atoms prefer to occupy $4f_1$, $12k$, and
$2a$ sites with occupation probability of 78%, 19% and 3%, respectively, while
in SrFe$_{11.5}$SnO$_{19}$, Sn atoms occupy the $12k$ and $4f_2$ sites with
occupation probability of 54% and 46%, respectively. We also found that in
SrFe$_{11}$Zn$_{0.5}$Sn$_{0.5}$O$_{19}$, (Zn,Sn) atom pairs prefer to occupy
the ($4f_1$, $4f_2$), ($4f_1$, $12k$) and ($12k$, $12k$) sites with occupation
probability of 82%, 8% and 6%, respectively. Our calculation shows that the
increase of magnetization and the reduction of magnetic anisotropy in Zn-Sn
substituted M-type strontium hexaferrite as observed experimentally is due to
the occupation of (Zn,Sn) pairs at the ($4f_1$, $4f_2$) sites.


  This paper proposes KB-InfoBot -- a multi-turn dialogue agent which helps
users search Knowledge Bases (KBs) without composing complicated queries. Such
goal-oriented dialogue agents typically need to interact with an external
database to access real-world knowledge. Previous systems achieved this by
issuing a symbolic query to the KB to retrieve entries based on their
attributes. However, such symbolic operations break the differentiability of
the system and prevent end-to-end training of neural dialogue agents. In this
paper, we address this limitation by replacing symbolic queries with an induced
"soft" posterior distribution over the KB that indicates which entities the
user is interested in. Integrating the soft retrieval process with a
reinforcement learner leads to higher task success rate and reward in both
simulations and against real users. We also present a fully neural end-to-end
agent, trained entirely from user feedback, and discuss its application towards
personalized dialogue agents. The source code is available at
https://github.com/MiuLab/KB-InfoBot.


  Seriation methods order a set of descriptions given some criterion (e.g.,
unimodality or minimum distance between similarity scores). Seriation is thus
inherently a problem of finding the optimal solution among a set of
permutations of objects. In this short technical note, we review the
combinatorial structure of the classical seriation problem, which seeks a
single solution out of a set of objects. We then extend those results to the
iterative frequency seriation approach introduced by Lipo (1997), which finds
optimal subsets of objects which each satisfy the unimodality criterion within
each subset. The number of possible solutions across multiple solution subsets
is larger than $n!$, which underscores the need to find new algorithms and
heuristics to assist in the deterministic frequency seriation problem.


  Using the published KTeV sample of 2 million KL-> pi e nu decays and a new
form factor expansion with a rigorous bound on higher order terms, we present a
new determination of the KL->pi e nu form factor and phase space integral.
Compared to the previous KTeV result, the uncertainty in the new form factor
expansion is negligible and results in an overall uncertainty in the phase
space integral (IKe) that is a factor of two smaller: IKe = 0.15392 +- 0.00048
\.


  We investigate the radiation from an inertial scalar particle evolving in a
de Sitter expanding Universe. In the context of scalar QED the process is
generated by the first order term in the perturbation theory expansion of the
S-matrix. The partial transition probability is obtained and analysed, and
soft-photon emission is found to dominate overall. It has been argued that an
inertial particle evolving in dS spacetime loses physical momentum just as a
decelerated particle in Minkowski space does. It is thus expected that an
inertial charge will radiate in a similar way. We investigate the radiated
energy and make a qualitative comparison of the angular distribution of the
energy with the radiation pattern in the latter case.


  We build on a fine-grained analysis of session-based interaction as provided
by the linear logic typing disciplines to introduce the SAM, an abstract
machine for mechanically executing session-typed processes. A remarkable
feature of the SAM's design is its ability to naturally segregate and
coordinate sequential with concurrent session behaviours. In particular,
implicitly sequential parts of session programs may be efficiently executed by
deterministic sequential application of SAM transitions, amenable to
compilation, and without concurrent synchronisation mechanisms. We provide an
intuitive discussion of the SAM structure and its underlying design, and state
and prove its correctness for executing programs in a session calculus
corresponding to full classical linear logic CLL. We also discuss extensions
and applications of the SAM to the execution of linear and session-based
programming languages.


  We study the distribution of prime numbers under the unlikely assumption that
Siegel zeros exist. In particular we prove for \[ \sum_{n \leq X} \Lambda(n)
\Lambda(\pm n+h) \] an asymptotic formula which holds uniformly for $h = O(X)$.
Such an asymptotic formula has been previously obtained only for fixed $h$ in
which case our result quantitatively improves those of Heath-Brown (1983) and
Tao and Ter\"av\"ainen (2021).
  Since our main theorems work also for large $h$ we can derive new results
concerning connections between Siegel zeros and the Goldbach conjecture and
between Siegel zeros and primes in almost all very short intervals.


  In this work we consider the KAM renormalizability problem for small
pseudodifferential perturbations of the semiclassical isochronous transport
operator with Diophantine frequencies on the torus. Assuming that the symbol of
the perturbation is real analytic and globally bounded, we prove convergence of
the quantum Lindstedt series and describe completely the set of semiclassical
measures and quantum limits of the renormalized system. Each of these measures
is given by symplectic deformation of the Haar measure on an invariant torus
for the unperturbed classical system.


  It is well established that the product of the volume coefficient of thermal
expansion and the bulk modulus is nearly constant at temperatures higher than
the Debye temperature. Using this approximation allows predicting the values of
the bulk modulus. The derived analytical solution for the temperature
dependence of the isothermal bulk modulus has been applied to ten substances.
The good correlations to the experiments indicate that the expression may be
useful for substances for which bulk modulus data are lacking.


  Reconstructing samples from the training set of trained neural networks is a
major privacy concern. Haim et al. (2022) recently showed that it is possible
to reconstruct training samples from neural network binary classifiers, based
on theoretical results about the implicit bias of gradient methods. In this
work, we present several improvements and new insights over this previous work.
As our main improvement, we show that training-data reconstruction is possible
in the multi-class setting and that the reconstruction quality is even higher
than in the case of binary classification. Moreover, we show that using
weight-decay during training increases the vulnerability to sample
reconstruction. Finally, while in the previous work the training set was of
size at most $1000$ from $10$ classes, we show preliminary evidence of the
ability to reconstruct from a model trained on $5000$ samples from $100$
classes.


  Starting from a generalization of the standard axioms for a monoid we present
a stepwise development of various, mutually equivalent foundational axiom
systems for category theory. Our axiom sets have been formalized in the
Isabelle/HOL interactive proof assistant, and this formalization utilizes a
semantically correct embedding of free logic in classical higher-order logic.
The modeling and formal analysis of our axiom sets has been significantly
supported by series of experiments with automated reasoning tools integrated
with Isabelle/HOL. We also address the relation of our axiom systems to
alternative proposals from the literature, including an axiom set proposed by
Freyd and Scedrov for which we reveal a technical issue (when encoded in free
logic where free variables range over defined and undefined objects): either
all operations, e.g. morphism composition, are total or their axiom system is
inconsistent. The repair for this problem is quite straightforward, however.


  We give a complete, self-contained computation of the spectral data
parametrising Higgs bundles in the generic fibres of the
$\mathrm{SO}_{2n+1}$-Hitchin fibration where the Higgs fields are $L$-twisted
endomorphisms. Although the spectral data is known in the literature, we
develop a new approach to spectral data, which takes advantage of Hecke
modification. Further, we present the computation for the $\mathrm{Sp}_{2n}$
and $\mathrm{SO}_{2n}$ cases while clarifying some aspects of the
correspondence which are not well explained in the pre-existing literature. We
also compute the number of connected components of the generic fibres, and
demonstrate Langlands duality in the fibres via the canonical duality in the
fibres.


  A lot of attention has been devoted to multimedia indexing over the past few
years. In the literature, we often consider two kinds of fusion schemes: The
early fusion and the late fusion. In this paper we focus on late classifier
fusion, where one combines the scores of each modality at the decision level.
To tackle this problem, we investigate a recent and elegant well-founded
quadratic program named MinCq coming from the Machine Learning PAC-Bayes
theory. MinCq looks for the weighted combination, over a set of real-valued
functions seen as voters, leading to the lowest misclassification rate, while
making use of the voters' diversity. We provide evidence that this method is
naturally adapted to late fusion procedure. We propose an extension of MinCq by
adding an order- preserving pairwise loss for ranking, helping to improve Mean
Averaged Precision measure. We confirm the good behavior of the MinCq-based
fusion approaches with experiments on a real image benchmark.


  Resonance is an ubiquitous phenomenon present in many systems. In particular,
air resonance in cavities was studied by Hermann von Helmholtz in the 1850s.
Originally used as acoustic filters, Helmholtz resonators are rigid-wall
cavities which reverberate at given fixed frequencies. An adjustable type of
resonator is the so-called universal Helmholtz resonator, a device consisting
of two sliding cylinders capable of producing sounds over a continuous range of
frequencies. Here we propose a simple experiment using a smartphone and normal
bottle of tea, with a nearly uniform cylindrical section, which, filled with
water at different levels, mimics a universal Helmholtz resonator. Blowing over
the bottle, different sounds are produced. Taking advantage of the great
processing capacity of smartphones, sound spectra together with frequencies of
resonance are obtained in real time.


  After a general introduction to the field, we describe some recent results
concerning disorder effects on both `random walk models', where the random walk
is a dynamical process generated by local transition rules, and on `polymer
models', where each random walk trajectory representing the configuration of a
polymer chain is associated to a global Boltzmann weight. For random walk
models, we explain, on the specific examples of the Sinai model and of the trap
model, how disorder induces anomalous diffusion, aging behaviours and Golosov
localization, and how these properties can be understood via a strong disorder
renormalization approach. For polymer models, we discuss the critical
properties of various delocalization transitions involving random polymers. We
first summarize some recent progresses in the general theory of random critical
points : thermodynamic observables are not self-averaging at criticality
whenever disorder is relevant, and this lack of self-averaging is directly
related to the probability distribution of pseudo-critical temperatures
$T_c(i,L)$ over the ensemble of samples $(i)$ of size $L$. We describe the
results of this analysis for the bidimensional wetting and for the
Poland-Scheraga model of DNA denaturation.


  Let $a(x,\xi)$ be a real H\"ormander symbol of the type
$S_{0,0}^0(\mathbb{R}^{d}\times \mathbb{R}^d)$, let $F$ be a smooth function
with all its derivatives globally bounded, and let $K_\delta$ be the
self-adjoint Weyl quantization of the perturbed symbols $a(x+F(\delta\,
x),\xi)$, where $|\delta|\leq 1$. First, we prove that the Hausdorff distance
between the spectra of $K_\delta$ and $K_{0}$ is bounded by $\sqrt{|\delta|}$,
and we give examples where spectral gaps of this magnitude can open when
$\delta\neq 0$. Second, we show that the distance between the spectral edges of
$K_\delta$ and $K_0$ (and also the edges of the inner spectral gaps, as long as
they remain open at $\delta=0$) are of order $|\delta|$, and give a precise
dependence on the width of the spectral gaps.


  A flowing pair of particles in inertial microfluidics gives important
insights into understanding and controlling the collective dynamics of
particles like cells or droplets in microfluidic devices. They are applied in
medical cell analysis and engineering. We study the dynamics of a pair of solid
particles flowing through a rectangular microchannel using lattice Boltzmann
simulations. We determine the inertial lift force profiles as a function of the
two particle positions, their axial distance, and the Reynolds number.
Generally, the profiles strongly differ between particles leading and lagging
in flow and the lift forces are enhanced due to the presence of a second
particle. At small axial distances, they are determined by viscous forces,
while inertial forces dominate at large separations. Depending on the initial
conditions, the two-particle lift forces in combination with the Poiseuille
flow give rise to three types of unbound particle trajectories, called
moving-apart, passing, and swapping, and one type of bound trajectories, where
the particles perform damped oscillations. The damping rate scales with
Reynolds number squared, since inertial forces are responsible for driving the
particles to their steady-state positions.


  Trajectory clustering is an important operation of knowledge discovery from
mobility data. Especially nowadays, the need for performing advanced analytic
operations over massively produced data, such as mobility traces, in efficient
and scalable ways is imperative. However, discovering clusters of complete
trajectories can overlook significant patterns that exist only for a small
portion of their lifespan. In this paper, we address the problem of Distributed
Subtrajectory Clustering in an efficient and highly scalable way. The problem
is challenging because the subtrajectories to be clustered are not known in
advance, but they need to be discovered dynamically based on adjacent
subtrajectories in space and time. Towards this objective, we split the
original problem to three sub-problems, namely Subtrajectory Join, Trajectory
Segmentation and Clustering and Outlier Detection, and deal with each one in a
distributed fashion by utilizing the MapReduce programming model. The
efficiency and the effectiveness of our solution is demonstrated experimentally
over a synthetic and two large real datasets from the maritime and urban
domains and through comparison with two state of the art subtrajectory
clustering algorithms.


  The Chermak-Delgado lattice of a finite group is a modular, self-dual
sublattice of the lattice of subgroups. We prove that the Chermak-Delgado
lattice of a central product contains the product of the Chermak-Delgado
lattices of the relevant central factors. Furthermore, we obtain information
about heights of elements in the Chermak-Delgado lattice relative to their
heights in the Chermak-Delgado lattices of central factors. We also explore how
the central product can be used as a tool in investigating Chermak-Delgado
lattices.


  A fully renewable European power system comes with a variety of problems.
Most of them are linked to the intermittent nature of renewable generation from
the sources of wind and photovoltaics. A possible solution to balance European
generation and consumption are European hydro power with its seasonal and North
African Concentrated Solar Power with its daily storage characteristics. In
this paper, we investigate the interplay of hydro and CSP imports in a highly
renewable European power system. We use a large weather database and historical
load data to model the interplay of renewable generation, consumption and
imports for Europe. We introduce and compare different hydro usage strategies
and show that hydro and CSP imports must serve different purposes to maximise
benefits for the total system. CSP imports should be used to cover daily
deficits, whereas hydro power can cover seasonal imbalances. If hydro is used
in a "Hydro First" strategy, only around one quarter of North African Solar
Power could be exported to Europe, whereas this number increases to around
60\%, if a cooperative hydro strategy is used.


  We consider a moving target that we seek to learn from samples. Our results
extend randomized techniques developed in control and optimization for a
constant target to the case where the target is changing. We derive a novel
bound on the number of samples that are required to construct a probably
approximately correct (PAC) estimate of the target. Furthermore, when the
moving target is a convex polytope, we provide a constructive method of
generating the PAC estimate using a mixed integer linear program (MILP). The
proposed method is demonstrated on an application to autonomous emergency
braking.


  Since the seminal paper by Breiman in 2001, who pointed out a potential harm
of prediction multiplicities from the view of explainable AI, global analysis
of a collection of all good models, also known as a `Rashomon set,' has been
attracted much attention for the last years. Since finding such a set of good
models is a hard computational problem, there have been only a few algorithms
for the problem so far, most of which are either approximate or incomplete. To
overcome this difficulty, we study efficient enumeration of all good models for
a subclass of interpretable models, called rule lists. Based on a
state-of-the-art optimal rule list learner, CORELS, proposed by Angelino et al.
in 2017, we present an efficient enumeration algorithm CorelsEnum for exactly
computing a set of all good models using polynomial space in input size, given
a dataset and a error tolerance from an optimal model. By experiments with the
COMPAS dataset on recidivism prediction, our algorithm CorelsEnum successfully
enumerated all of several tens of thousands of good rule lists of length at
most $\ell = 3$ in around 1,000 seconds, while a state-of-the-art top-$K$ rule
list learner based on Lawler's method combined with CORELS, proposed by Hara
and Ishihata in 2018, found only 40 models until the timeout of 6,000 seconds.
For global analysis, we conducted experiments for characterizing the Rashomon
set, and observed large diversity of models in predictive multiplicity and
fairness of models.


  We provide a new construction of the Brownian disks, which have been defined
by Bettinelli and Miermont as scaling limits of quadrangulations with a
boundary when the boundary size tends to infinity. Our method is very similar
to the construction of the Brownian map, but it makes use of the positive
excursion measure of the Brownian snake which has been introduced recently.
This excursion measure involves a random continuous tree whose vertices are
assigned nonnegative labels, which correspond to distances from the boundary in
our approach to the Brownian disk. We provide several applications of our
construction. In particular, we prove that the uniform measure on the boundary
can be obtained as the limit of the suitably normalized volume measure on a
small tubular neighborhood of the boundary. We also prove that connected
components of the complement of the Brownian net are Brownian disks, as it was
suggested in the recent work of Miller and Sheffield. Finally, we show that
connected components of the complement of balls centered at the distinguished
point of the Brownian map are independent Brownian disks, conditionally on
their volumes and perimeters.


  We characterize the shape of spatial externalities in a continuous time and
space differential game with transboundary pollution. We posit a realistic
spatiotemporal law of motion for pollution (diffusion and advection), and
tackle spatiotemporal non-cooperative (and cooperative) differential games.
Precisely, we consider a circle partitioned into several states where a local
authority decides autonomously about its investment, production and depollution
strategies over time knowing that investment/production generates pollution,
and pollution is transboundary. The time horizon is infinite. We allow for a
rich set of geographic heterogeneities across states. We solve analytically the
induced non-cooperative differential game and characterize its long-term
spatial distributions. In particular, we prove that there exist a Perfect
Markov Equilibrium, unique among the class of the affine feedbacks. We further
provide with a full exploration of the free riding problem and the associated
border effect.


  This study explores the indirect impact of war damage on postwar fertility,
with a specific focus on Japan's air raids during World War II. Using 1935 and
1947 Kinki region town/village data and city air raid damage information, we
explored the "far-reaching effects" on fertility rates in nearby undamaged
areas. Our fixed-effects model estimates show that air raids influenced postwar
fertility within a 15-kilometer radius of the bombed cities. These impacts
varied based on bombing intensity, showing both positive and negative effects.
Moreover, a deeper analysis, using the Allied flight path as a natural
experiment, indicates that air raid threats and associated fear led to
increased postwar fertility, even in undamaged areas. This study highlights the
relatively unexplored indirect consequences of war on fertility rates in
neighboring regions and significantly contributes to the literature on the
relationship between wars and fertility.


  We briefly review the effective theory that describes the low energy
properties of QCD with three light quarks and a large number of colours, N_c,
and then discuss the mechanisms that forbid the Kaplan-Manohar transformation
in this framework.


  The present paper discusses a Non Destructive Evaluation (NDE) technique
involving Compton back-scattering. Two 15 cm x 15 cm x 15 cm cubical concrete
blocks were scanned for detection of voids. The setup used a PC controlled
gamma scattering scanning system. A 137Cs radioactive source of strength 153.92
GBq with lead shielding and a collimated and shielded 50% efficiency coaxial
HPGe detector providing high resolution energy dispersive analysis of the
scattered spectrum, were mounted on source and detector sub-assemblies
respectively. In one of the concrete blocks air cavities were created by
insertion of two hollow cylindrical plastic voids each of volume 71.6 cm3. Both
the concrete blocks, one normal and another with air cavities were scanned by
lateral and depth-wise motion in steps of 2.5 cm. The results show that the
scattering method is highly sensitive to changes in electronic and physical
densities of the volume element (VOXEL) under study. The voids have been
detected with a statistical accuracy of better than 0.1% and their positions
have been determined with good spatial resolution. A reconstruction algorithm
is developed for characterization of the block with voids. This algorithm can
be generally applied to such back-scattering experiments in order to determine
anomalies in materials.


  An angular analysis of the $B^0 \rightarrow K^{*0} e^+ e^-$ decay is
performed using a data sample, corresponding to an integrated luminosity of 3.0
${\mbox{fb}^{-1}}$, collected by the LHCb experiment in $pp$ collisions at
centre-of-mass energies of 7 and 8 TeV during 2011 and 2012. For the first time
several observables are measured in the dielectron mass squared ($q^2$)
interval between 0.002 and 1.120${\mathrm{\,Ge\kern -0.1em V^2\!/}c^4}$. The
angular observables $F_{\mathrm{L}}$ and $A_{\mathrm{T}}^{\mathrm{Re}}$ which
are related to the $K^{*0}$ polarisation and to the lepton forward-backward
asymmetry, are measured to be $F_{\mathrm{L}}= 0.16 \pm 0.06 \pm0.03$ and
$A_{\mathrm{T}}^{\mathrm{Re}} = 0.10 \pm 0.18 \pm 0.05$, where the first
uncertainty is statistical and the second systematic. The angular observables
$A_{\mathrm{T}}^{(2)}$ and $A_{\mathrm{T}}^{\mathrm{Im}}$ which are sensitive
to the photon polarisation in this $q^2$ range, are found to be
$A_{\mathrm{T}}^{(2)} = -0.23 \pm 0.23 \pm 0.05$ and
$A_{\mathrm{T}}^{\mathrm{Im}} =0.14 \pm 0.22 \pm 0.05$. The results are
consistent with Standard Model predictions.


  The granular gas is a paradigm for understanding the effects of inelastic
interactions in granular materials. Kinetic theory provides a general
theoretical framework for describing the granular gas. Its central result is
that the tail of the velocity distribution of a driven granular gas is a
stretched exponential that, counterintuitively, decays slower than that of the
corresponding elastic gas in equilibrium. However, a derivation of this result
starting from a microscopic model is lacking. Here, we obtain analytical
results for a microscopic model for a granular gas where particles with
two-dimensional velocities are driven homogeneously and isotropically by
reducing the velocities by a factor and adding a stochastic noise. We find two
universal regimes. For generic physically relevant driving, we find that the
tail of the velocity distribution is a Gaussian with additional logarithmic
corrections. Thus, the velocity distribution decays faster than the
corresponding equilibrium gas. The second universal regime is less generic and
corresponds to the scenario described by kinetic theory. Here, the velocity
distribution is shown to decay as an exponential with additional logarithmic
corrections, in contradiction to the predictions of the phenomenological
kinetic theory, necessitating a re-examination of its basic assumptions.


  A new approach to quantum mechanics based on independence of the Continuum
Hypothesis is proposed. In one-dimensional case, it is shown that the
properties of the set of intermediate cardinality coincide with quantum
phenomenology.


  Reinforcement Learning (RL) algorithms show amazing performance in recent
years, but placing RL in real-world applications such as self-driven vehicles
may suffer safety problems. A self-driven vehicle moving to a target position
following a learned policy may suffer a vehicle with unpredictable aggressive
behaviors or even being pursued by a vehicle following a Nash strategy. To
address the safety issue of the self-driven vehicle in this scenario, this
paper conducts a preliminary study based on a system of robots. A safe RL
framework with safety guarantees is developed for a robot being pursued but
with objectives covering more than capture-avoidance. Simulations and
experiments are conducted based on the system of robots to evaluate the
effectiveness of the developed safe RL framework.


  In this manuscript, we investigate deep invertible networks for EEG-based
brain signal decoding and find them to generate realistic EEG signals as well
as classify novel signals above chance. Further ideas for their regularization
towards better decoding accuracies are discussed.


  As an adoptive cellular therapy, Chimeric Antigen Receptor T-cell (CAR
T-cell) therapy has shown remarkable success in hematological malignancies, but
only limited efficacy against solid tumors. Compared with blood cancers, solid
tumors present a unique set of challenges that ultimately neutralize the
function of CAR T-cells. One such barrier is antigen heterogeneity -
variability in the expression of the antigen on tumor cells. Success of CAR
T-cell therapy in solid tumors is unlikely unless almost all the tumor cells
express the specific antigen that CAR T-cells target. A critical question for
solving the heterogeneity problem is whether CAR T therapy induces bystander
effects, such as antigen spreading. Antigen spreading occurs when CAR T-cells
activate other endogenous antitumor CD8 T cells against antigens that were not
originally targeted. In this work, we develop a mathematical model of CAR
T-cell therapy for solid tumors that takes into consideration both antigen
heterogeneity and bystander effects. Our model is based on in vivo treatment
data that includes a mixture of target antigen-positive and target
antigen-negative tumor cells. We use our model to simulate large cohorts of
virtual patients to gain a better understanding of the relationship between
bystander killing. We also investigate several strategies for enhancing the
bystander effect and thus increasing the overall efficacy of CAR T-cell therapy
for solid tumor.


  We consider the non-relativistic c -> \infty contraction limit of the (N=2k)-
extended D=4 superconformal algebra su(2,2;N), introducing in this way the
non-relativistic (N=2k)-extended Galilean superconformal algebra. Such a
Galilean superconformal algebra has the same number of generators as
su(2,2|2k). The usp(2k) algebra describes the non-relativistic internal
symmetries, and the generators from the coset u(2k)/usp(2k) become central
charges after contraction.


  Time plays an integral role in the realm of e-learning modules. plaimi
previously described a canvas for composing e-learning modules. By
transitivity, time needs to play an integral role in this canvas. This paper
investigates some of the ways it can play said role. Four angles are
considered: insights offered by viewing a module composition as a chronicle of
modules, the importance of length estimation in time allocation, heightening
retention via spaced repetition, and synchronisation attempts at facilitating
collaborative learning. The features discovered by this investigation are
discussed in a principled learning context, which particularly emphasises
academic learning time. Some concrete suggestions are made; to implement:
order-awareness, user estimation of module length, spaced-repetition-awareness,
and post-module self-assessment. Suggestions for further research are also
given.


  This paper deals with robust optimization applied to network flows. Two
robust variants of the minimum-cost integer flow problem are considered.
Thereby, uncertainty in problem formulation is limited to arc unit costs and
expressed by a finite set of explicitly given scenarios. It is shown that both
problem variants are NP-hard. To solve the considered variants, several
heuristics based on local search or evolutionary computing are proposed. The
heuristics are experimentally evaluated on appropriate problem instances.


  We study a linear price impact model including other liquidity takers, whose
flow of orders either follows a Poisson or a Hawkes process. The optimal
execution problem is solved explicitly in this context, and the closed-formula
optimal strategy describes in particular how one should react to the orders of
other traders. This result enables us to discuss the viability of the market.
It is shown that Poissonian arrivals of orders lead to quite robust Price
Manipulation Strategies in the sense of Huberman and Stanzl. Instead, a
particular set of conditions on the Hawkes model balances the self-excitation
of the order flow with the resilience of the price, excludes Price Manipulation
Strategies and gives some market stability.


  In the context of the local gauge group $SU(3)_c\otimes SU(3)_L\otimes
U(1)_X$, we look for possible four family models, where all the particles carry
ordinary electric charges. Thirteen different anomaly-free fermion structures
emerge, out of which only two are realistic. For the simplest physical
structure, we calculate the charged and neutral weak currents and the
tree-level Fermion masses. We also look for new sources of flavor changing
neutral currents in the quark sector, in connection with the upcoming
experimental results at the Large Hadron Collider.


  Nowadays, in many scientific and industrial fields there is an increasing
need for estimating treatment effects and answering causal questions. The key
for addressing these problems is the wealth of observational data and the
processes for leveraging this data. In this work, we propose a new model for
predicting the potential outcomes and the propensity score, which is based on a
neural network architecture. The proposed model exploits the covariates as well
as the outcomes of neighboring instances in training data. Numerical
experiments illustrate that the proposed model reports better treatment effect
estimation performance compared to state-of-the-art models.


  K*-charmonium dissociation reactions in hadronic matter are studied in the
Born approximation, in the quark-interchange mechanism, and with a
temperature-dependent quark potential. We obtain the temperature dependence of
unpolarized cross sections for K*-charmonium dissociation reactions which
produce charmed mesons and charmed strange mesons. We use the cross sections
for charmonium dissociation in collisions with pion, rho meson, kaon, vector
kaon, and eta meson to calculate dissociation rates of charmonium with the five
types of mesons. Because of the temperature dependence of the meson masses,
dissociation cross sections, and meson distribution functions, the charmonium
dissociation rates generally increase with the increase of temperature and
decrease with the increase of charmonium momentum from 2.2 GeV/c. We find that
the first derivative of the dissociation rate with respect to the charmonium
momentum is zero when the charmonium is at rest. While the eta + psi' and eta +
chi_c dissociation reactions can be neglected, the J/psi, psi', and chi_c
dissociation are caused by the collisions with pion, rho meson, kaon, vector
kaon, and eta meson.


  We outline two approaches to the construction of integrable hierarchies
associated with the theory of Gromov - Witten invariants of smooth projective
varieties. We argue that a comparison of these two approaches yields nontrivial
constraints on Chern numbers of varieties with semisimple quantum cohomology.


  Sustainability of common-pool resources hinges on the interplay between human
and environmental systems. However, there is still a lack of a novel and
comprehensive framework for modelling extraction of common-pool resources and
cooperation of human agents that can account for different factors that shape
the system behavior and outcomes. In particular, we still lack a critical value
for ensuring resource sustainability under different scenarios. In this paper,
we present a novel framework for studying resource extraction and cooperation
in human-environmental systems for common-pool resources. We explore how
different factors, such as resource availability and conformity effect,
influence the players' decisions and the resource outcomes. We identify
critical values for ensuring resource sustainability under various scenarios.
We demonstrate the observed phenomena are robust to the complexity and
assumptions of the models and discuss implications of our study for policy and
practice, as well as the limitations and directions for future research.


  The thermal multihadron production observed in different high energy
collisions poses many basic problems: why do even elementary, $e^+e^-$ and
hadron-hadron, collisions show thermal behaviour? Why is there in such
interactions a suppression of strange particle production? Why does the
strangeness suppression almost disappear in relativistic heavy ion collisions?
Why in these collisions is the thermalization time less than $\simeq 0.5$ fm/c?
We show that the recently proposed mechanism of thermal hadron production
through Hawking-Unruh radiation can naturally answer the previous questions.
Indeed, the interpretation of quark- antiquark pairs production, by the
sequential string breaking, as tunneling through the event horizon of colour
confinement leads to thermal behavior with a universal temperature, $T \simeq
170$ Mev,related to the quark acceleration, a, by $T=a/2\pi$. The resulting
temperature depends on the quark mass and then on the content of the produced
hadrons, causing a deviation from full equilibrium and hence a suppression of
strange particle production in elementary collisions. In nucleus-nucleus
collisions, where the quark density is much bigger, one has to introduce an
average temperature (acceleration) which dilutes the quark mass effect and the
strangeness suppression almost disappears.


  A proper ideal $I$ in a commutative ring with unity is called a
$z^\circ$-ideal if for each $a$ in $I$, the intersection of all minimal prime
ideals in $R$ which contain $a$ is contained in $I$. For any totally ordered
field $F$ and a completely $F$-regular topological space $X$, let $C(X,F)$ be
the ring of all $F$-valued continuous functions on $X$ and $B(X,F)$ the
aggregate of all those functions which are bounded over $X$. An explicit
formula for all the $z^\circ$-ideals in $A(X,F)$ in terms of ideals of closed
sets in $X$ is given. It turns out that an intermediate ring $A(X,F)\neq
C(X,F)$ is never regular in the sense of Von-Neumann. This property further
characterizes $C(X,F)$ amongst the intermediate rings within the class of
$P_F$-spaces $X$. It is also realized that $X$ is an almost $P_F$-space if and
only if each maximal ideal in $C(X,F)$ is $z^\circ$-ideal. Incidentally this
property also characterizes $C(X,F)$ amongst the intermediate rings within the
family of almost $P_F$-spaces.


  Three statistical studies, all published between 2004 and 2008 but without
referring to one another, assert a useful equivalence involving the hazard
ratio, a parameter estimated for time to event data by the frequently used
proportional hazards model. Stated generally, when the assumption of
proportional hazards is justified, the hazard ratio is equivalent to the odds
that a randomly chosen person from the group whose hazard is represented in the
ratio's numerator will experience the event of interest before a randomly
chosen person from the group represented by the ratio's denominator.


  We present a Magellan/MIKE high-resolution (R ~ 35,000) spectrum of the
ancient star SD 1313-0019 which has an iron abundance of [Fe/H] = -5.0, paired
with a carbon enhancement of [C/Fe] ~ 3.0. The star was initially identified by
Allende Prieto et al. in the BOSS survey. Its medium-resolution spectrum
suggested a higher metallicity of [Fe/H] = -4.3 due to the CaII K line blending
with a CH feature which is a common issue related to the search for the most
iron-poor stars. This star joins several other, similar stars with [Fe/H] <
-5.0 that all display a combination of low iron and high carbon abundances.
Other elemental abundances of SD 1313-0019 follow that of more metal-rich halo
stars. From fitting the abundance pattern with yields of Population III
supernova, we conclude that SD 1313-0019 had only one massive progenitor star
with 20 - 30 M_sun that must have undergone a mixing and fallback episode.
Overall, there are now five stars known with [Fe/H] < -5.0 (1D LTE abundances).
This population of second-generation stars strongly suggests massive first
stars that almost exclusively produced large amounts of carbon through stellar
winds and/or their mixing and fallback supernova explosions. As a consequence,
their natal clouds -- presumably some early minihalo structures -- contained
ample amounts of carbon and oxygen that likely facilitated the formation of
these first low-mass stars.


  Over the past five years, multi-marginal optimal transport, a generalization
of the well known optimal transport problem of Monge and Kantorovich, has begun
to attract considerable attention, due in part to a wide variety of emerging
applications. Here, we survey this problem, addressing fundamental theoretical
questions including the uniqueness and structure of solutions. The (partial)
answers to these questions uncover a surprising divergence from the classical
two marginal setting, and reflect a delicate dependence on the cost function.
We go one to describe two applications of the multi-marginal problem.


  We propose a new interconnection relation for infinite-dimensional
port-Hamiltonian systems that enables the coupling of ports with different
spatial dimensions by integrating over the the surplus dimensions. To show the
practical relevance, we apply this interconnection to a model system of an
actively cooled gas turbine blade. We also show that this interconnection
relation behaves well with respect to a discretization in finite element space,
ensuring its usability for practical applications.


  The presence of nonanalyticity in observables is a manifestation of phase
transitions. Through the study of two paradigmatic topological models in one
and two dimensions, in this work we show that the circuit complexity based on
our specific quantification can reveal the occurrence of topological phase
transitions, both in and out of equilibrium, by the presence of nonanalyticity.
By quenching the system out of equilibrium, we find that the circuit complexity
grows linearly or quadratically in the short-time regime if the quench is
finished instantaneously or in a finite time, respectively. Notably, we find
that for both the sudden quench and the finite-time quench, a topological phase
transition in the pre-quench Hamiltonian will be manifested by the presence of
nonanalyticity in the first-order or second-order derivative of circuit
complexity with respect to time in the short-time regime, and a topological
phase transition in the post-quench Hamiltonian will be manifested by the
presence of nonanalyticity in the steady value of circuit complexity in the
long-time regime. We also show that the increase of dimension does not remove,
but only weakens the nonanalyticity of circuit complexity. Our findings can be
tested in quantum simulators and cold-atom systems.


  This paper explores a natural action of the group $\mathrm{PGL}_2(\mathbb
F_q)$ on the set of monic irreducible polynomials of degree at least two over a
finite field $\mathbb F_q$. Our main results deal with the existence and number
of fixed points and, in particular, we provide some improvements of previous
works.


  We provide examples of quasi-isometries for strongly convex domains in
$\mathbb C^n$ endowed with their Kobayashi distance.


  I present general analytic expressions for distance calculations (comoving
distance, time coordinate, and absorption distance) in the standard
$\Lambda$CDM cosmology, allowing for the presence of radiation and for non-zero
curvature. The solutions utilise the symmetric Carlson basis of elliptic
integrals, which can be evaluated with fast numerical algorithms that allow
trivial parallelisation on GPUs and automatic differentiation without the need
for additional special functions. I introduce a PyTorch-based implementation in
the phytorch.cosmology package and briefly examine its accuracy and speed in
comparison with numerical integration and other known expressions (for special
cases). Finally, I demonstrate an application to high-dimensional Bayesian
analysis that utilises automatic differentiation through the distance
calculations to efficiently derive posteriors for cosmological parameters from
up to $10^6$ mock type Ia supernovae using variational inference.


  By excluding some sets, which don't include any eigenvalue of a tensor, from
some existing eigenvalue inclusion sets, two new sets are given to locate all
eigenvalues of a tensor. And it is shown that these two sets are contained in
the Ger\v{s}gorin eigenvalue inclusion set of tensors provide by Qi (Journal of
Symbolic Computation 2005; 40:1302-1324) and the Brauer-type eigenvalue
inclusion set provide by Li et al. (Numer. Linear Algebra Appl. 2014; 21:39-50)
respectively. Two sufficient conditions such that the determinant of a tensor
is not zero are also provided.


  Recently, self-supervised learning (SSL) was shown to be vulnerable to
patch-based data poisoning backdoor attacks. It was shown that an adversary can
poison a small part of the unlabeled data so that when a victim trains an SSL
model on it, the final model will have a backdoor that the adversary can
exploit. This work aims to defend self-supervised learning against such
attacks. We use a three-step defense pipeline, where we first train a model on
the poisoned data. In the second step, our proposed defense algorithm
(PatchSearch) uses the trained model to search the training data for poisoned
samples and removes them from the training set. In the third step, a final
model is trained on the cleaned-up training set. Our results show that
PatchSearch is an effective defense. As an example, it improves a model's
accuracy on images containing the trigger from 38.2% to 63.7% which is very
close to the clean model's accuracy, 64.6%. Moreover, we show that PatchSearch
outperforms baselines and state-of-the-art defense approaches including those
using additional clean, trusted data. Our code is available at
https://github.com/UCDvision/PatchSearch


  In this article we study a piecewise linear discretization schemes for
transfer operators (Perron-Frobenius operators) associated with interval maps.
We show how these can be used to provide rigorous {\bf pointwise}
approximations for invariant densities of Markov interval maps. We also derive
the order of convergence of the approximate invariant density to the real one
in the $L^{\infty}$-norm. The outcome of this paper complements rigorous
results on $L^1$ approximations of invariant densities \cite{KMY} and recent
results on the formulae of escape rates of open dynamical systems \cite{KL2}.
We implement our computations on two examples (one rigorous and one
non-rigorous) to illustrate the feasibility and efficiency of our schemes.


  We focus on examining and working with an important category of computer
software called Services, which are provided as a part of newer Microsoft
Windows operating systems. A typical Windows user transparently utilizes many
of these services but is frequently unaware of their existence. Since some
services have the potential to create significant problems when they are
executing, it is important for a system administrator to identify which
services are running on the network, the types of processing done by each
service, and any interrelationships among the various services. This
information can then be used to improve the overall integrity of both the
individual computer where a questionable service is running and in aggregate an
entire network of computers.
  NCSA has developed an application called SMART (Services Monitoring And
Reporting Tool) that can be used to identify and display all services currently
running in the network. A commercial program called Hyena remotely monitors the
services on all computers attached to the network and exports this information
to SMART. SMART produces various outputs that the system administrator can
analyze and then determine appropriate actions to take. In particular, SMART
provides a color coordinated user interface to quickly identify and classify
both potentially hazardous services and also unknown services.


  In the presence of a magnetic field and weakly ionizing winds, ohmic
dissipation is expected to take place in the envelopes of Jovian and lower-mass
planets alike. While the process has been investigated on the former, there
have been no studies done on mini-Neptunes so far. From structure and thermal
evolution models, we determine that the required energy deposition for halting
the contraction of mini-Neptunes increases with planetary mass and envelope
fraction. Scaled to the insolation power, the ohmic heating needed is small
$\sim10^{-5}$ -- orders of magnitude lower than for exo-Jupiters $\sim
10^{-2}$. Conversely, from solving the magnetic induction equation, we find
that ohmic energy is dissipated more readily for lower-mass planets and those
with larger envelope fractions. Combining these two trends, we find that ohmic
dissipation in hot mini-Neptunes is strong enough to inflate their radii ($\sim
10^{15}$ W for $T_{eq}=1400K$). The implication is that the radii of hot
mini-Neptunes may be attributed in part to ohmic heating. Thus, there is a
trade-off between ohmic dissipation and H/He content for hot mini-Neptunes,
adding a new degeneracy for the interpretation of the composition of such
planets. In addition, ohmic dissipation would make mini-Neptunes more
vulnerable to atmospheric evaporation.


  We give an explicit description of toric sheaves on the weighted projective
plane $\mathbb{P}(a,b,c)$ viewed as a toric Deligne-Mumford stack. The integers
$(a,b,c)$ are not necessarily chosen coprime or mutually coprime allowing for
gerbe and root stack structures.
  As an application, we describe the fixed point locus of the moduli scheme of
stable rank 1 and 2 torsion free sheaves on $\mathbb{P}(a,b,c)$ with fixed
$K$-group class. Summing over all $K$-group classes, we obtain explicit
formulae for generating functions of the topological Euler characteristics.
  In the case of stable rank 2 locally free sheaves on $\mathbb{P}(a,b,c)$ with
$a,b,c \leq 2$ the generating functions can be expressed in terms of Hurwitz
class numbers and give rise to modular forms of weight $3/2$. This generalizes
Klyachko's computation on $\mathbb{P}^2$ and is consistent with $S$-duality
predictions from physics.


  Random walks are a series of up, down, and level steps that enumerate
distinct paths from $(0,0)$ to $(2n,0)$, where $n$ is the semi-length of the
path. We used these paths to analyze Catalan, Schr\"{o}der, and Motzkin number
sequences through a combination of matrix operations, quadratic functions, and
inductive reasoning. Our results revealed a number of distinct patterns, some
unnamed, between these number sequences and Pascal's triangle that can be
explained through generating functions, first returns, group theory, and the
Riordan matrix.
  Various proofs and properties of these number sequences are provided,
including each generating function, their respective first returns, and matrix
properties. These findings lead to a deeper understanding of combinatorics and
graph theory.


  The current paper is devoted to the asymptotic behavior of a class of
stochastic PDE. More precisely, with the help of the theory of integrated
semigroups and a crucial estimate of the random Stieltjes convolution, we study
the existence and smoothness of center-unstable invariant manifolds and
center-stable foliations for a class of stochastic PDE with non-dense domain
through the Lyapunov-Perron method. Finally, we give two examples about a
stochastic age-structured model and a stochastic parabolic equation to
illustrate our results.


  The MPC-in-the-head introduced in [IKOS07] has established itself as an
important paradigm to design efficient digital signatures. It has been
leveraged in the Picnic scheme [CDG+ 20] that reached the third round of the
NIST PQC Standardization process. It has also been used in [Beu20] to introduce
the Proof of Knowledge (PoK) with Helper paradigm. This construction permits to
design shorter signatures but induces a non negligible performance overhead as
it uses cut-and-choose. In this paper, we introduce the PoK leveraging
structure paradigm along with its associated challenge space amplification
technique. Our new approach to design PoK brings some improvements over the PoK
with Helper one. Indeed, we show how one can substitute the Helper in these
constructions by leveraging the underlying structure of the considered problem.
This approach does not suffer from the performance overhead inherent to the PoK
with Helper paradigm hence offers different trade-offs between security,
signature sizes and performances. We also present four new post-quantum
signature schemes. The first one is based on a new PoK with Helper for the
Syndrome Decoding problem. It relies on ideas from [BGKM22] and [FJR21] and
improve the latter using a new technique that can be seen as performing some
cut-and-choose with a meet in the middle approach. The three other signatures
are based on our new PoK leveraging structure approach and as such illustrate
its versatility. We provide new PoK related to the Permuted Kernel Problem
(PKP), Syndrome Decoding (SD) problem and Rank Syndrome Decoding (RSD) problem.
In practice, these PoK lead to comparable or shorter signatures than existing
ones. Indeed, considering (public key + signature), we get sizes below 9kB for
our signature related to the PKP problem, below 15kB for our signature related
to the SD problem and below 7kB for our signature related to the RSD problem.