IA Scholar Query: Equivalent Approximation Algorithms for Node Cover.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgSat, 31 Dec 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440A Survey on Concept Drift in Process Mining
https://scholar.archive.org/work/hvmkupdorzf5df4tts42gzykjm
Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version. We conducted a systematic literature review on the intersection of these areas, and thus, we review concept drift in PM and bring forward a taxonomy of existing techniques for drift detection and online PM for evolving environments. Existing works depict that (i) PM still primarily focuses on offline analysis, and (ii) the assessment of concept drift techniques in processes is cumbersome due to the lack of common evaluation protocol, datasets, and metrics.Denise Maria Vecino Sato, Sheila Cristiana De Freitas, Jean Paul Barddal, Edson Emilio Scalabrinwork_hvmkupdorzf5df4tts42gzykjmSat, 31 Dec 2022 00:00:00 GMTAn Algorithmic Study of Fully Dynamic Independent Sets for Map Labeling
https://scholar.archive.org/work/by4kwstrpzgk3fvpxqnu3yoeiq
Map labeling is a classical problem in cartography and geographic information systems that asks to place labels for area, line, and point features, with the goal to select and place the maximum number of independent (i.e., overlap-free) labels. A practically interesting case is point labeling with axis-parallel rectangular labels of common size. In a fully dynamic setting, at each timestep, either a new label appears or an existing label disappears. Then, the challenge is to maintain a maximum cardinality subset of pairwise independent labels with sublinear update time. Motivated by this, we study the maximal independent set ( MIS ) and maximum independent set ( Max-IS ) problems on fully dynamic (insertion/deletion model) sets of axis-parallel rectangles of two types: (i) uniform height and width and (ii) uniform height and arbitrary width; both settings can be modeled as rectangle intersection graphs. We present the first deterministic algorithm for maintaining an MIS (and thus a 4-approximate Max-IS ) of a dynamic set of uniform rectangles with polylogarithmic update time. This breaks the natural barrier of \( \Omega (\Delta) \) update time (where \( \Delta \) is the maximum degree in the graph) for vertex updates presented by Assadi et al. (STOC 2018). We continue by investigating Max-IS and provide a series of deterministic dynamic approximation schemes. For uniform rectangles, we first give an algorithm that maintains a 4-approximate Max-IS with \( O(1) \) update time. In a subsequent algorithm, we establish the trade-off between approximation quality \( 2(1+\frac{1}{k}) \) and update time \( O(k^2\log n) \) , for \( k\in \mathbb {N} \) . We conclude with an algorithm that maintains a 2-approximate Max-IS for dynamic sets of unit-height and arbitrary-width rectangles with \( O(\log ^2 n + \omega \log n) \) update time, where \( \omega \) is the maximum size of an independent set of rectangles stabbed by any horizontal line. We implement our algorithms and report the results of an experimental comparison exploring the trade-off between solution quality and update time for synthetic and real-world map labeling instances. We made several major observations in our empirical study. First, the original approximations are well above their respective worst-case ratios. Second, in comparison with the static approaches, the dynamic approaches show a significant speedup in practice. Third, the approximation algorithms show their predicted relative behavior. The better the solution quality, the worse the update times. Fourth, a simple greedy augmentation to the approximate solutions of the algorithms boost the solution sizes significantly in practice.Sujoy Bhore, Guangping Li, Martin Nöllenburgwork_by4kwstrpzgk3fvpxqnu3yoeiqSat, 31 Dec 2022 00:00:00 GMTEarly cephalopod evolution clarified through Bayesian phylogenetic inference
https://scholar.archive.org/work/tw43rrpbfnht3oezkik4aculc4
Despite the excellent fossil record of cephalopods, their early evolution is poorly understood. Different, partly incompatible phylogenetic hypotheses have been proposed in the past, which reflected individual author's opinions on the importance of certain characters but were not based on thorough cladistic analyses. At the same time, methods of phylogenetic inference have undergone substantial improvements. For fossil datasets, which typically only include morphological data, Bayesian inference and in particular the introduction of the fossilized birth-death model have opened new possibilities. Nevertheless, many tree topologies recovered from these new methods reflect large uncertainties, which have led to discussions on how to best summarize the information contained in the posterior set of trees. Results We present a large, newly compiled morphological character matrix of Cambrian and Ordovician cephalopods to conduct a comprehensive phylogenetic analysis and resolve existing controversies. Our results recover three major monophyletic groups, which correspond to the previously recognized Endoceratoidea, Multiceratoidea, and Orthoceratoidea, though comprising slightly different taxa. In addition, many Cambrian and Early Ordovician representatives of the Ellesmerocerida and Plectronocerida were recovered near the root. The Ellesmerocerida is para-and polyphyletic, with some of its members recovered among the Multiceratoidea and early Endoceratoidea. These relationships are robust against modifications of the dataset. While our trees initially seem to reflect large uncertainties, these are mainly a consequence of the way clade support is measured. We show that clade posterior probabilities and tree similarity metrics often underestimate congruence between trees, especially if wildcard taxa are involved. Conclusions Our results provide important insights into the earliest evolution of cephalopods and clarify evolutionary pathways. We provide a classification scheme that is based on a robust phylogenetic analysis. Moreover, we provide some general insights on the application of Bayesian phylogenetic inference on morphological datasets. We support earlier findings that quartet similarity metrics should be preferred over the Robinson-Foulds distance when higher-level phylogenetic relationships are of interest and propose that using a posteriori pruned maximum clade credibility trees help in assessing support for phylogenetic relationships among a set of relevant taxa, because they provide clade support values that better reflect the phylogenetic signal.Alexander Pohle, Björn Kröger, Rachel C M Warnock, Andy H King, David H Evans, Martina Aubrechtová, Marcela Cichowolski, Xiang Fang, Christian Klugwork_tw43rrpbfnht3oezkik4aculc4Thu, 01 Dec 2022 00:00:00 GMTGreenhouse gas fluxes (CO2, N2O and CH4) of pea and maize during two cropping seasons: Drivers, budgets, and emission factors for nitrous oxide
https://scholar.archive.org/work/mes4uj2uhvgz7chba6nqjm4yle
Agriculture contributes considerably to the increase of global greenhouse gas (GHG) emissions. Hence, magnitude and drivers of temporal variations in carbon dioxide (CO 2 ), nitrous oxide (N 2 O) and methane (CH 4 ) fluxes in croplands are urgently needed to develop sustainable, climate-smart agricultural practices. However, our knowledge of GHG fluxes from croplands is still very limited. The eddy covariance technique was used to quantify GHG budgets and N 2 O emission factors (EF) for pea and maize in Switzerland. The random forest technique was applied for gap-filling N 2 O and CH 4 fluxes as well as to determine the relevance of environmental, vegetation vs. management drivers of the GHG fluxes during two cropping seasons. Environmental (i.e., net radiation, soil water content, soil temperature) and vegetation drivers (i.e., vegetation height) were more important drivers for GHG fluxes at field scale than time since management for the two crop species. Both crops acted as GHG sinks between sowing and harvest, clearly dominated by net CO 2 fluxes, while CH 4 emissions were negligible. However, considerable N 2 O emissions occurred in both crop fields early in the season when crops were still establishing. N 2 O fluxes in both crops were small later in the season when vegetation was tall, despite high soil water contents and temperatures. Results clearly show a strong and highly dynamic microbial-plant competition for N driving N 2 O fluxes at the field scale. The total loss was 1.4 kg N 2 O-N ha −1 over 55 days for pea and 4.8 kg N 2 O-N ha −1 over 127 days for maize. EFs of N 2 O were 1.5 % (pea) and 4.4 % (maize) during the cropping seasons, clearly exceeding the IPCC Tier 1 EF for N 2 O. Thus, sustainable, climate-smart agriculture needs to consider crop phenology and better adapt N supply to crop N demand for growth, particularly during the early cropping season when competition for N between establishing crops and soil microorganisms modulates N 2 O losses.Regine Maier, Lukas Hörtnagl, Nina Buchmannwork_mes4uj2uhvgz7chba6nqjm4yleFri, 25 Nov 2022 00:00:00 GMTNested Session Types
https://scholar.archive.org/work/cdzjx4x355eyjn7slpugmdj6di
Session types statically describe communication protocols between concurrent message-passing processes. Unfortunately, parametric polymorphism even in its restricted prenex form is not fully understood in the context of session types. In this article, we present the metatheory of session types extended with prenex polymorphism and, as a result, nested recursive datatypes. Remarkably, we prove that type equality is decidable by exhibiting a reduction to trace equivalence of deterministic first-order grammars. Recognizing the high theoretical complexity of the latter, we also propose a novel type equality algorithm and prove its soundness. We observe that the algorithm is surprisingly efficient and, despite its incompleteness, sufficient for all our examples. We have implemented our ideas by extending the Rast programming language with nested session types. We conclude with several examples illustrating the expressivity of our enhanced type system.Ankush Das, Henry Deyoung, Andreia Mordido, Frank Pfenningwork_cdzjx4x355eyjn7slpugmdj6diFri, 30 Sep 2022 00:00:00 GMTTools for Quantum Computing Based on Decision Diagrams
https://scholar.archive.org/work/buzllucb25a4xpyogsgazec4m4
With quantum computers promising advantages even in the near-term NISQ era, there is a lively community that develops software and toolkits for the design of corresponding quantum circuits. Although the underlying problems are different, expertise from the design automation community, which developed sophisticated design solutions for the conventional realm in the past decades, can help here. In this respect, decision diagrams provide a promising foundation for tackling many design tasks such as simulation, synthesis, and verification of quantum circuits. However, users of the corresponding tools often do not have a proper background or an intuition about how these methods based on decision diagrams work and what their strengths and limits are. In this work, we first review the concepts of how decision diagrams can be employed, e.g., for the simulation and verification of quantum circuits. Afterwards, in an effort to make decision diagrams for quantum computing more accessible, we then present a visualization tool for quantum decision diagrams, which allows users to explore the behavior of decision diagrams in the design tasks mentioned above. Finally, we present decision diagram-based tools for simulation and verification of quantum circuits using the methods discussed above as part of the open-source Munich Quantum Toolkit (MQT)—a set of tools for quantum computing developed at the Technical University of Munich and the Johannes Kepler University Linz and released under the MIT license. More information about the corresponding tools is available at https://github.com/cda-tum/ddsim . By this, we provide an introduction of the concepts and tools for potential users who would like to work with them as well as potential developers aiming to extend them.Robert Wille, Stefan Hillmich, Lukas Burgholzerwork_buzllucb25a4xpyogsgazec4m4Fri, 30 Sep 2022 00:00:00 GMTD8.4 - REACT Market Analysis
https://scholar.archive.org/work/ytjstcle5jgvph75nmloqeb35u
This plan includes an analysis of the market context for the solutions identified in REACT. It consists of a multi-level and multi-disciplinary analysis (e.g., PESTLE; Stakeholders' Mapping; focus on key technological and digital assets and competitors; leading initiatives at EU and global level supporting the sustainable energy transition of geographical islands).Thomas Messervey, Sara Momi, Cristina Barberowork_ytjstcle5jgvph75nmloqeb35uThu, 29 Sep 2022 00:00:00 GMTWorkshop Numerische Methoden in der Geotechnik : 12th & 13th of September 2022 Hamburg, Germany : conference proceedings
https://scholar.archive.org/work/lixdp5rcefdbjft3thqnvuwfp4
Numerische Verfahren sind zum Standardprozess in der Untersuchung von geotechnischen Bauwerken geworden. Mit stetig steigender Rechenleistung gewinnen Hybrid- und Kontinuumsansätze, die durch ausgefeilte Materialmodelle unterstützt werden, immer mehr an Bedeutung. Der Workshop "Numerische Methoden in der Geotechnik 2022" der Technischen Universität Hamburg (TUHH) unter Beteiligung des AK Numerik (DGGT) und der Bundesanstalt für Wasserbau (BAW) bringt internationale Wissenschaftlerinnen und Wissenschaftler und Fachleute zusammen, um neueste Erkenntnisse in Bezug auf die Entwicklung numerischer Methoden in der Geotechnik zu präsentieren und zu diskutieren. Dieser Tagungsband enthält die verschiedenen auf dem Workshop vorgetragenen Themen. Er soll die gewonnenen Erkenntnisse für zukünftige wissenschaftliche und praktische Anwendungen erhalten und sie mit der geotechnischen Community teilen.Jürgen Grabe, Sascha Henke, Marius Milatz, Gertraud Medicus, Torsten Wichtmann, Merita Tafili, Jan Machacek, Patrick Staubach, Luis Felipe Prada Sarmiento, Anne Stark, Michael Hicks, Ronald Brinkgreve, Sandro Brasile, Bart van Paassen, Thomas Nijssen, Salazar Rivera, Hauke Jürgens, Tim Pucker, Kristian Krabbenhoft, Hans-Peter Daxer, Franz Tschuchnigg, Helmut Schweiger, Antonia Nitsch, Carlos Eduardo Grandas Tavera, Alba Yerro, Alexander Chmelnizkij, Christoph Goniva, Marcel Kwakkel, Giovanni Viciconte, Christoph Kloss, Robert Seifried, Timo Hendrik Schmidt, Benedikt Kriegesmann, Elnaz Hadjiloo, Hatice Kaya-Sandt, Tobias Engel, Matthias Römer, Kurt-M. Borchert, Diaa Alkateeb, Thomas Meier, Jörg-Martin Hohberg, TUHH Universitätsbibliothekwork_lixdp5rcefdbjft3thqnvuwfp4Thu, 29 Sep 2022 00:00:00 GMTTopological Data Analysis in Time Series: Temporal Filtration and Application to Single-Cell Genomics
https://scholar.archive.org/work/sdqbn7ixmfhgzp7beoeqagvufu
The absence of a conventional association between the cell-cell cohabitation and its emergent dynamics into cliques during development has hindered our understanding of how cell populations proliferate, differentiate, and compete, i.e. the cell ecology. With the recent advancement of the single-cell RNA-sequencing (RNA-seq), we can potentially describe such a link by constructing network graphs that characterize the similarity of the gene expression profiles of the cell-specific transcriptional programs, and analyzing these graphs systematically using the summary statistics informed by the algebraic topology. We propose the single-cell topological simplicial analysis (scTSA). Applying this approach to the single-cell gene expression profiles from local networks of cells in different developmental stages with different outcomes reveals a previously unseen topology of cellular ecology. These networks contain an abundance of cliques of single-cell profiles bound into cavities that guide the emergence of more complicated habitation forms. We visualize these ecological patterns with topological simplicial architectures of these networks, compared with the null models. Benchmarked on the single-cell RNA-seq data of zebrafish embryogenesis spanning 38,731 cells, 25 cell types and 12 time steps, our approach highlights the gastrulation as the most critical stage, consistent with consensus in developmental biology. As a nonlinear, model-independent, and unsupervised framework, our approach can also be applied to tracing multi-scale cell lineage, identifying critical stages, or creating pseudo-time series.Baihan Linwork_sdqbn7ixmfhgzp7beoeqagvufuWed, 28 Sep 2022 00:00:00 GMTProcess-guidance improves predictive performance of neural networks for carbon turnover in ecosystems
https://scholar.archive.org/work/p3oycyw5uvcgdnhezezatnvwfq
Despite deep-learning being state-of-the-art for data-driven model predictions, it has not yet found frequent application in ecology. Given the low sample size typical in many environmental research fields, the default choice for the modelling of ecosystems and its functions remain process-based models. The process understanding coded in these models complements the sparse data and neural networks can detect hidden dynamics even in noisy data. Embedding the process model in the neural network adds information to learn from, improving interpretability and predictive performance of the combined model towards the data-only neural networks and the mechanism-only process model. At the example of carbon fluxes in forest ecosystems, we compare different approaches of guiding a neural network towards process model theory. Evaluation of the results under four classical prediction scenarios supports decision-making on the appropriate choice of a process-guided neural network.Marieke Wesselkamp, Niklas Moser, Maria Kalweit, Joschka Boedecker, Carsten F. Dormannwork_p3oycyw5uvcgdnhezezatnvwfqWed, 28 Sep 2022 00:00:00 GMTBudgeted Out-tree Maximization with Submodular Prizes
https://scholar.archive.org/work/a63gq5kp5fdvtexgnw7pkrlwhi
We consider a variant of the prize collecting Steiner tree problem in which we are given a directed graph D=(V,A), a monotone submodular prize function p:2^V →ℝ^+ ∪{0}, a cost function c:V →ℤ^+, a root vertex r ∈ V, and a budget B. The aim is to find an out-subtree T of D rooted at r that costs at most B and maximizes the prize function. We call this problem Directed Rooted Submodular Tree (DRSO). Very recently, Ghuge and Nagarajan [SODA 2020] gave an optimal quasi-polynomial-time O(log n'/loglog n')-approximation algorithm, where n' is the number of vertices in an optimal solution, for the case in which the costs are associated to the edges. In this paper, we give a polynomial-time algorithm for DRSO that guarantees an approximation factor of O(√(B)/ϵ^3) at the cost of a budget violation of a factor 1+ϵ, for any ϵ∈ (0,1]. The same result holds for the edge-cost case, to the best of our knowledge this is the first polynomial-time approximation algorithm for this case. We further show that the unrooted version of DRSO can be approximated to a factor of O(√(B)) without budget violation, which is an improvement over the factor O(Δ√(B)) given in [Kuo et al. IEEE/ACM Trans. Netw.2015] for the undirected and unrooted case, where Δ is the maximum degree of the graph. Finally, we provide some new/improved approximation bounds for several related problems, including the additive-prize version of DRSO, the maximum budgeted connected set cover problem, and the budgeted sensor cover problem.Gianlorenzo D'Angelo, Esmaeil Delfaraz, Hugo Gilbertwork_a63gq5kp5fdvtexgnw7pkrlwhiWed, 28 Sep 2022 00:00:00 GMTScheduling of Missions with Constrained Tasks for Heterogeneous Robot Systems
https://scholar.archive.org/work/duea23clefbahjc6uunvwo6hyy
We present a formal tasK AllocatioN and scheduling apprOAch for multi-robot missions (KANOA). KANOA supports two important types of task constraints: task ordering, which requires the execution of several tasks in a specified order; and joint tasks, which indicates tasks that must be performed by more than one robot. To mitigate the complexity of robotic mission planning, KANOA handles the allocation of the mission tasks to robots, and the scheduling of the allocated tasks separately. To that end, the task allocation problem is formalised in first-order logic and resolved using the Alloy model analyzer, and the task scheduling problem is encoded as a Markov decision process and resolved using the PRISM probabilistic model checker. We illustrate the application of KANOA through a case study in which a heterogeneous robotic team is assigned a hospital maintenance mission.Gricel Vázquezwork_duea23clefbahjc6uunvwo6hyyWed, 28 Sep 2022 00:00:00 GMTExpressive curves
https://scholar.archive.org/work/ujnsw6pourfldpeo55qqbmzcsm
We initiate the study of a class of real plane algebraic curves which we call expressive. These are the curves whose defining polynomial has the smallest number of critical points allowed by the topology of the set of real points of a curve. This concept can be viewed as a global version of the notion of a real morsification of an isolated plane curve singularity. We prove that a plane curve C is expressive if (a) each irreducible component of C can be parametrized by real polynomials (either ordinary or trigonometric), (b) all singular points of C in the affine plane are ordinary hyperbolic nodes, and (c) the set of real points of C in the affine plane is connected. Conversely, an expressive curve with real irreducible components must satisfy conditions (a)-(c), unless it exhibits some exotic behaviour at infinity. We describe several constructions that produce expressive curves, and discuss a large number of examples, including: arrangements of lines, parabolas, and circles; Chebyshev and Lissajous curves; hypotrochoids and epitrochoids; and much more.Sergey Fomin, Eugenii Shustinwork_ujnsw6pourfldpeo55qqbmzcsmWed, 28 Sep 2022 00:00:00 GMTA machine learning based column-and-row generation approach for integrated air cargo recovery problem
https://scholar.archive.org/work/pzqk5ttsv5hj7nyham3u32joay
Freighter airlines need to recover both aircraft and cargo schedules when disruptions happen. This process is usually divided into three sequential decisions to recovery flights, aircraft, and cargoes. This study focuses on the integrated recovery problem that makes aircraft and cargo recovery decisions simultaneously. We formulate two integrated models based on the flight connection network, one is the arc-based model, and the other is the string-based model. The arc-based model makes the flight delay decisions by duplicating flight copies, and is solved directly by commercial solvers such as Cplex. The string-based model makes the flight delay decisions in the variable generation process. The main difficulty of the string-based model is that the number of constraints grows with the newly generated flight delay decisions. Therefore, the traditional column generation method can not be applied directly. To tackle this challenge, we propose a machine learning based column-and-row generation approach. The machine learning method is used to uncover the critical delay decisions of short through connections in each column-and-row generation iteration by eliminating the poor flight delay decisions. We also propose a set of valid inequality constraints which can greatly improve the objective of LP relaxation solution and reduce the integral gap. The effectiveness and efficiency of our model is tested by simulated scenarios based on real operational data from the largest Chinese freighter airlines. The computational results show that a significant cost reduction can be achieved with the proposed string-based model in reasonable time.Lei Huang, Fan Xiao, Zhe Liangwork_pzqk5ttsv5hj7nyham3u32joayWed, 28 Sep 2022 00:00:00 GMTAn Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series
https://scholar.archive.org/work/3nkt6s4olrfm7pghecmgqezgnq
As a special infinite-order vector autoregressive (VAR) model, the vector autoregressive moving average (VARMA) model can capture much richer temporal patterns than the widely used finite-order VAR model. However, its practicality has long been hindered by its non-identifiability, computational intractability, and relative difficulty of interpretation. This paper introduces a novel infinite-order VAR model which, with only a little sacrifice of generality, inherits the essential temporal patterns of the VARMA model but avoids all of the above drawbacks. As another attractive feature, the temporal and cross-sectional dependence structures of this model can be interpreted separately, since they are characterized by different sets of parameters. For high-dimensional time series, this separation motivates us to impose sparsity on the parameters determining the cross-sectional dependence. As a result, greater statistical efficiency and interpretability can be achieved, while no loss of temporal information is incurred by the imposed sparsity. We introduce an ℓ_1-regularized estimator for the proposed model and derive the corresponding nonasymptotic error bounds. An efficient block coordinate descent algorithm and a consistent model order selection method are developed. The merit of the proposed approach is supported by simulation studies and a real-world macroeconomic data analysis.Yao Zhengwork_3nkt6s4olrfm7pghecmgqezgnqWed, 28 Sep 2022 00:00:00 GMTTEI2022 Conference Book
https://scholar.archive.org/work/fo5eliwof5bnnn3ms3vetgbpoi
A Book of Abstracts and more for the TEI2022 Conference!James Cummingswork_fo5eliwof5bnnn3ms3vetgbpoiWed, 28 Sep 2022 00:00:00 GMTMutual information-based group explainers with coalition structure for machine learning model explanations
https://scholar.archive.org/work/3gyreldgqbc7jmbl24leazwrpa
In this article, we study game-theoretical group explainers for machine learning (ML) models in a functional analytic setting as operators defined on appropriate functional spaces. Specifically, we focus on game values with coalition structure applied to random games based on the conditional and marginal expectation. In particular, we investigate the stability of the explanation operators which showcases the differences between the two games, such as showing that the marginal explanations can become unstable in the natural data-based metric. Furthermore, we formulate novel group explanation methodologies based on game values with coalition structure applied to both marginal and conditional games. They allow us to unify the two types of explanations and turn out to have lower complexity. In addition, we study the effect of predictor grouping on the stability of the corresponding explanation operators. Finally, we establish the two-step representation for a coalitional game value consisting of two game values and a family of intermediate games. We use this representation to generalize our grouping approach to the case of nested partitions represented by a parameterized partition tree. Specifically, we introduce a theoretical scheme that generates recursive coalitional game values and group explainers under a given partition tree structure and investigate the properties of the corresponding group explainers. We verify our results in a number of experiments with data where the predictors are grouped based on an information-theoretic measure of dependence.Alexey Miroshnikov, Konstandinos Kotsiopoulos, Khashayar Filom, Arjun Ravi Kannanwork_3gyreldgqbc7jmbl24leazwrpaWed, 28 Sep 2022 00:00:00 GMTFlavour-universal search for heavy neutral leptons with a deep neural network-based displaced jet tagger with the CMS experiment
https://scholar.archive.org/work/gb63ulsuuzhixe7bhaqbgb7a5q
This thesis describes a search for long-lived heavy neutral leptons using a dataset of 137/fb collected during the 2016-2018 proton-proton runs with the CMS detector. The search uses a final state containing two leptons and at least one hadronic jet. This is the first analysis at the Large Hadron Collider which considers universal mixing between the Standard Model and heavy neutral lepton species. The search makes heavy use of a deep neural network-based displaced jet tagging algorithm, originally developed to target heavy long-lived gluino decays. The tagger was trained on both simulation and proton-proton collision data using the domain adaptation technique, which significantly improved the modelling of its output in simulation. The tagger has excellent performance for a range of long-lived particle lifetimes and generalises well to various flavours of displaced jets. In this analysis, the backgrounds are estimated in an entirely data-driven manner. No evidence for heavy neutral leptons is observed, and upper limits are set for a wide range of heavy neutral lepton mass, lifetime, and mixing scenarios. This is the most sensitive search for heavy neutral leptons in the 1–12 GeV mass range to date.Vilius Cepaitis, Alexander Tapper, Science And Technology Facilities Councilwork_gb63ulsuuzhixe7bhaqbgb7a5qWed, 28 Sep 2022 00:00:00 GMTTopological descriptors of the parameter region of multistationarity: deciding upon connectivity
https://scholar.archive.org/work/mvwnbyfy4ja77b5qohobuv474q
Switch-like responses arising from bistability have been linked to cell signaling processes and memory. Revealing the shape and properties of the set of parameters that lead to bistability is necessary to understand the underlying biological mechanisms, but is a complex mathematical problem. We present an efficient approach to determine a basic topological property of the parameter region of multistationary, namely whether it is connected or not. The connectivity of this region can be interpreted in terms of the biological mechanisms underlying bistability and the switch-like patterns that the system can create. We provide an algorithm to assert that the parameter region of multistationarity is connected, targeting reaction networks with mass-action kinetics. We show that this is the case for numerous relevant cell signaling motifs, previously described to exhibit bistability. However, we show that for a motif displaying a phosphorylation cycle with allosteric enzyme regulation, the region of multistationarity has two distinct connected components, corresponding to two different, but symmetric, biological mechanisms. The method relies on linear programming and bypasses the expensive computational cost of direct and generic approaches to study parametric polynomial systems. This characteristic makes it suitable for mass-screening of reaction networks.Máté L. Telek, Elisenda Feliuwork_mvwnbyfy4ja77b5qohobuv474qWed, 28 Sep 2022 00:00:00 GMTEvaluating Hybrid Graph Pattern Queries Using Runtime Index Graphs
https://scholar.archive.org/work/wpedltg7dncw3lpwplbnugmeja
Graph pattern matching is a fundamental operation for the analysis and exploration ofdata graphs. In thispaper, we presenta novel approachfor efficiently finding homomorphic matches for hybrid graph patterns, where each pattern edge may be mapped either to an edge or to a path in the input data, thus allowing for higher expressiveness and flexibility in query formulation. A key component of our approach is a lightweight index structure that leverages graph simulation to compactly encode the query answer search space. The index can be built on-the-fly during query execution and does not have to be persisted to disk. Using the index, we design a multi-way join algorithm to enumerate query solutions without generating any potentially exploding intermediate results. We demonstrate through extensive experiments that our approach can efficiently evaluate a wide range / broad spectrum of graph pattern queries and greatly outperforms existing approaches and recent graph query engines/systems.Xiaoying Wu and Dimitri Theodoratos and Nikos Mamoulis and Michael Lanwork_wpedltg7dncw3lpwplbnugmejaWed, 28 Sep 2022 00:00:00 GMT