bluuebunny/crossref_metadata_2025_split huggingface dataset:
Science with society: Challenges of early‐stage researchers engaging with transdisciplinary research in sustainability science
Authors: Thapa Kaustubh , Vermeulen Walter J. V. , Deutz Pauline 
Published: April 2022

AbstractThe ongoing social and ecological crises create urgency in academia and elsewhere to devise actionable problem‐solving knowledge to tackle sustainability challenges. Transdisciplinary research (TDR) represents a problem‐solving methodology for sustainability problems. TDR requires researchers to get out in the real world and engage with other societal actors to jointly produce such problem‐solving knowledge for research to have a societal impact. This radical process of doing “science with society” instead of “science for society” is becoming more urgent and relevant. However, a transdisciplinary (TD) researcher faces challenges: often, institutions have limited readiness for facilitating TDR, a researcher has to juggle the roles of an academic and changemaker simultaneously and needs new ways of doing science. The research process requires enough manoeuvring space to incorporate reflexivity, adaptiveness, and emergence based on the research context. The research uses case studies, interviews, reflections, and document analysis from two finished and one ongoing TDR PhDs in sustainability science and connects them with the TD literature. Based on previous and ongoing TDR by early‐stage researchers (ESRs), this article identifies and discusses six TDR challenges ESRs in sustainability sciences might face.
Severity classification of software code smells using machine learning techniques: A comparative study
Authors: Abdou Ashraf , Darwish Nagy 
Published: April 2022

AbstractCode smell is a software characteristic that indicates bad symptoms in code design which causes problems related to software quality. The severity of code smells must be measured because it will help the developers when determining the priority of refactoring efforts. Recently, several studies focused on the prediction of design patterns errors using different detection tools. Nowadays, there is a lack of empirical studies regarding how to measure severity of code smells and which learning model is best to detect the severity of code smells. To overcome such gap, this paper focuses on measuring the severity classification of code smells depending on several machine learning models such as regression models, multinominal models, and ordinal classification models. The Local Interpretable Model Agnostic Explanations (LIME) algorithm was further used to explain the machine learning model's predictions and interpretability. On the other side, we extract the prediction rules generated by the Projective Adaptive Resonance Theory (PART) algorithm in order to study the effectiveness of using software metrics to predict code smells. The results of the experiments have shown that the accuracy of severity classification model is enhanced than baseline and ranking correlation between the predicted and actual model reaches 0.92–0.97 by using Spearman's correlation measure.
Communication strategies for moral rebels: How to talk about change in order to inspire self‐efficacy in others
Authors: Brouwer Claire , Bolderdijk Jan‐Willem , Cornelissen Gert , Kurz Tim 
Published: April 2022

AbstractCurrent carbon‐intensive lifestyles are unsustainable and drastic social changes are required to combat climate change. To achieve such change, moral rebels (i.e., individuals who deviate from current behavioral norms based on ethical considerations) may be crucial catalyzers. However, the current literature holds that moral rebels may do more harm than good. By deviating from what most people do, based on a moral concern, moral rebels pose a threat to the moral self‐view of their observers who share but fail to uphold that concern. Those observers may realize that their behavior does not live up to their moral values, and feel morally inadequate as a result. Work on “do‐gooder derogation” demonstrates that rebel‐induced threat can elicit defensive reactance among observers, resulting in the rejection of moral rebels and their behavioral choices. Such findings suggest that advocates for social change should avoid triggering moral threat by, for example, presenting nonmoral justifications for their choices. We challenge this view by arguing that moral threat may be a necessary ingredient to achieve social change precisely because it triggers ethical dissonance. Thus, instead of avoiding moral justifications, it may be more effective to harness that threat. Ethical dissonance may offer the fuel needed for observers to engage in self‐improvement after being exposed to moral rebels, provided that observers feel capable of changing. Whether or not observers feel capable of changing, however, depends on how rebels communicate their moral choices to others—how they talk about change.This article is categorized under:
Perceptions, Behaviour and Communication of Climate Change > Behaviour Change and Responses
Applying AI to Manage Acute and Chronic Clinical Condition
Authors: Hagan Rachael , Gillan Charles J. , Shyamsundar Murali 
Published: April 2022

AbstractComputer systems deployed in hospital environments, particularly physiological and biochemical real-time monitoring of patients in an Intensive Care Unit (ICU) environment, routinely collect a large volume of data that can hold very useful information. However, the vast majority are either not stored and lost forever or are stored in digital archives and seldom re-examined. In recent years, there has been extensive work carried out by researchers utilizing Machine Learning (ML) and Artificial Intelligence (AI) techniques on these data streams, to predict and prevent disease states. Such work aims to improve patient outcomes, to decrease mortality rates and decrease hospital stays, and, more generally, to decrease healthcare costs.This chapter reviews the state of the art in that field and reports on our own current research, with practicing clinicians, on improving ventilator weaning protocols and lung protective ventilation, using ML and AI methodologies for decision support, including but not limited to Neural Networks and Decision Trees. The chapter considers both the clinical and Computer Science aspects of the field. In addition, we look to the future and report how physiological data holds clinically important information to aid in decision support in the wider hospital environment.
Using a Legal Knowledge Graph for Multilingual Compliance Services in Labor Law, Contract Management, and Geothermal Energy
Authors: Kaltenboeck Martin , Boil Pascual , Verhoeven Pieter , Sageder Christian , Montiel-Ponsoda Elena , Calleja-Ibáñez Pablo 
Published: April 2022

AbstractThis chapter provides insights about the work done and the results achieved by the Horizon 2020-funded Innovation Action “Lynx—Building the Legal Knowledge Graph for Smart Compliance Services in Multilingual Europe.” The main objective of Lynx is to create an ecosystem of multilingual, smart cloud services to manage compliance based on a Legal Knowledge Graph (LKG), which integrates and links heterogeneous compliance data sources including legislation, case law, regulations, standards, and private contracts. The chapter provides a short introduction in regards to the market needs, gives an overview of the Lynx services available on the Lynx Services Platform (LySP), and provides valuable insights into three real-world compliance solutions developed on top of LySP together with Lynx’s industry partners, namely, (1) Labor Law (Cuatrecasas, Spain), (2) Contract Management (Cybly, Austria), and (3) Geothermal Energy (DNV.GL, the Netherlands).
Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case
Authors: Alexopoulos Andreas , Becerra Yolanda , Boehm Omer , Bravos George , Chatzigiannakis Vasilis , Cugnasco Cesare , Demetriou Giorgos , Eleftheriou Iliada , Fodor Lidija , Fotis Spiros , Ioannidis Sotiris , Jakovetic Dusan , Kallipolitis Leonidas , Katusic Vlatka , Kavakli Evangelia , Kopanaki Despina , Leventis Christoforos , Marcos Mario Maawad , de Pozuelo Ramon Martin , Martínez Miquel , Milosevic Nemanja , Montanera Enric Pere Pages , Ristow Gerald , Ruiz-Ocampo Hernan , Sakellariou Rizos , Sirvent Raül , Skrbic Srdjan , Spais Ilias , Vasiliadis Giorgos , Vinov Michael 
Published: April 2022

AbstractA large number of EU organisations already leverage Big Data pools to drive value and investments. This trend also applies to the banking sector. As a specific example, CaixaBank currently manages more than 300 different data sources (more than 4 PetaBytes of data and increasing), and more than 700 internal and external active users and services are processing them every day. In order to harness value from such high-volume and high-variety of data, banks need to resolve several challenges, such as finding efficient ways to perform Big Data analytics and to provide solutions that help to increase the involvement of bank employees, the true decision-makers. In this chapter, we describe how these challenges are resolved by the self-service solution developed within the I-BiDaaS project. We present three CaixaBank use cases in more detail, namely, (1)analysis of relationships through IP addresses, (2)advanced analysis of bank transfer payment in financial terminalsand (3)Enhanced control of customers in online banking, and describe how the corresponding requirements are mapped to specific technical and business KPIs. For each use case, we present the architecture, data analysis and visualisation provided by the I-BiDaaS solution, reporting on the achieved results, domain-specific impact and lessons learned.
Big Data-Driven Industry 4.0 Service Engineering Large-Scale Trials: The Boost 4.0 Experience
Authors: Lázaro Oscar , Alonso Jesús , Figueiras Paulo , Costa Ruben , Graça Diogo , Garcia Gisela , Canepa Alessandro , Calefato Caterina , Vallini Marco , Fournier Fabiana , Hazout Nathan , Skarbovsky Inna , Poulakidas Athanasios , Sipsas Konstantinos 
Published: April 2022

AbstractIn the last few years, the potential impact of big data on the manufacturing industry has received enormous attention. This chapter details two large-scale trials that have been implemented in the context of the lighthouse project Boost 4.0. The chapter introduces the Boost 4.0 Reference Model, which adapts the more generic BDVA big data reference architectures to the needs of Industry 4.0. The Boost 4.0 reference model includes a reference architecture for the design and implementation of advanced big data pipelines and the digital factory service development reference architecture. The engineering and management of business network track and trace processes in high-end textile supply are explored with a focus on the assurance of Preferential Certification of Origin (PCO). Finally, the main findings from these two large-scale piloting activities in the area of service engineering are discussed.
Distributed Big Data Analytics in a Smart City
Authors: Serrano Maria A. , Hadad Erez , Cavicchioli Roberto , Palmero Rut , Chiantore Luca , Amendola Danilo , Quiñones Eduardo 
Published: April 2022

AbstractThis chapter describes an actual smart city use-case application for advanced mobility and intelligent traffic management, implemented in the city of Modena, Italy. This use case is developed in the context of the European Union’s Horizon 2020 project CLASS [4]—Edge and Cloud Computation: A highly Distributed Software for Big Data Analytics. This use-case requires both real-time data processing (data in motion) for driving assistance and online city-wide monitoring, as well as large-scale offline processing of big data sets collected from sensors (data at rest). As such, it demonstrates the advanced capabilities of the CLASS software architecture to coordinate edge and cloud for big data analytics. Concretely, the CLASS smart city use case includes a range of mobility-related applications, including extended car awareness for collision avoidance, air pollution monitoring, and digital traffic sign management. These applications serve to improve the quality of road traffic in terms of safety, sustainability, and efficiency. This chapter shows the big data analytics methods and algorithms for implementing these applications efficiently.
Trade-Offs and Challenges of Serverless Data Analytics
Authors: García-López Pedro , Sánchez-Artigas Marc , Shillaker Simon , Pietzuch Peter , Breitgand David , Vernik Gil , Sutra Pierre , Tarrant Tristan , Juan-Ferrer Ana , París Gerard 
Published: April 2022

AbstractServerless computing has become very popular today since it largely simplifies cloud programming. Developers do no longer need to worry about provisioning or operating servers, and they have to pay only for the compute resources used when their code is run. This new cloud paradigm suits well for many applications, and researchers have already begun investigating the feasibility of serverless computing for data analytics. Unfortunately, today’s serverless computing presents important limitations that make it really difficult to support all sorts of analytics workloads. This chapter first starts by analyzing three fundamental trade-offs of today’s serverless computing model and their relationship with data analytics. It studies how by relaxing disaggregation, isolation, and simple scheduling, it is possible to increase the overall computing performance, but at the expense of essential aspects of the model such as elasticity, security, or sub-second activations, respectively. The consequence of these trade-offs is that analytics applications may well end up embracing hybrid systems composed of serverless and serverful components, which we call ServerMix in this chapter. We will review the existing related work to show that most applications can be actually categorized as ServerMix.
Biographische Orientierungen der Mittelschichten: gemeinschaftszentrierte Lebensführung, Berufsstolz-Lebensführung und investive Statusarbeit
Authors: Kumkar Nils C. , Holubek-Schaum Stefan , Gottschall Karin , Hollstein Betina , Schimank Uwe 
Published: April 2022

ZusammenfassungDieses Kapitel präsentiert die empirischen Ergebnisse hinsichtlich der vorgefundenen biographischen Orientierungen. Neben der investiven Statusarbeit, wie wir sie theoretisch konzipiert haben, zeigen sich in unseren Fällen noch zwei weitere Modi der Lebensführung, in denen Praktiken der investiven Statusarbeit zwar enthalten sind, aber anders biographisch ausgerichtet werden: eine gemeinschaftsorientierte Lebensführung und eine Lebensführung des Berufsstolzes. Ausgehend davon, dass allen Mittelschichtenangehörigen investive Statusarbeit als kulturell hegemoniale Vorstellung vom „guten Leben“ nahegelegt wird, ist ein Hauptergebnis unserer Untersuchung also, dass nicht alle dieser Anrufung nachkommen können oder wollen.10.1007/978-3-658-36566-0_2
Praktiken investiver Statusarbeit
Authors: Kumkar Nils C. , Holubek-Schaum Stefan , Gottschall Karin , Hollstein Betina , Schimank Uwe 
Published: April 2022

ZusammenfassungDas Kapitel schildert die empirischen Ergebnisse zu den investiven Praktiken, mit denen die drei Modi der Mittelschichten-Lebensführung vollzogen werden: Berufliche Arbeit, Bildungsanstrengungen, die Pflege sozialer Beziehungen, Geldanlagen auf dem Finanzmarkt und elterliches Entscheiden über den Bildungsweg der eigenen Kinder sind dabei die Hauptbetätigungsfelder. Auch bestimmte Begrenzungen investiver Statusarbeit werden aufgezeigt.
Lebensführung in den Mittelschichten: unaufgeregt beharrlich
Authors: Kumkar Nils C. , Holubek-Schaum Stefan , Gottschall Karin , Hollstein Betina , Schimank Uwe 
Published: April 2022

ZusammenfassungDas Kapitel zieht ein systematisches Fazit zu Erscheinungsformen und Bedingungen investiver Statusarbeit in den drei vorgefundenen Varianten und verortet unsere empirischen Befunde sodann im Verhältnis zu zentralen Einschätzungen prominenter zeitdiagnostischer Mittelschichtsstudien. Während diese eine teils verunsicherte, teils als Gewinner auftrumpfende Mitte in den Vordergrund stellen, machen wir auf die beharrliche Mitte aufmerksam - also auf jene, die unaufgeregt in Stimmungslage und Auftreten ein Leben führen, das durch die großen gesellschaftlichen Dynamiken wie Globalisierung, Ökonomisierung und Digitalisierung weder in exorbitante Höhen noch in ebensolche Tiefen getrieben wird.
Logarithmic corrections to the entropy of rotating black holes and black strings in AdS5
Authors: David Marina , Lezcano Alfredo González , Nian Jun , Pando Zayas Leopoldo A. 
Published: April 2022

Abstract
We investigate logarithmic corrections to the entropy of supersymmetric, rotating, asymptotically AdS5 black holes and black strings. Within the framework of the AdS/CFT correspondence, the entropy of these black objects is determined, on the field theory side, by the superconformal index and the refined topologically twisted index of $$ \mathcal{N} $$
N
= 4 supersymmetric Yang-Mills theory, respectively. We read off the logarithmic correction from those field-theoretic partition functions. On the gravity side, we take the near-horizon limit and apply the Kerr/CFT correspondence whose associated charged Cardy formula describes the degeneracy of states at subleading order and determines the logarithmic correction to the entropy. We find perfect agreement between these two approaches. Our results provide a window into precision microstate counting and demonstrate the efficacy of low-energy, symmetry-based approaches such as the Kerr/CFT correspondence for asymptotically AdS black objects under certain conditions.
Constraints on leptoquarks from lepton-flavour-violating tau-lepton processes
Authors: Husek Tomáš , Monsálvez-Pozo Kevin , Portolés Jorge 
Published: April 2022

Abstract
Leptoquarks are ubiquitous in several extensions of the Standard Model and seem to be able to accommodate the universality-violation-driven B-meson-decay anomalies and the (g −2)μ discrepancy interpreted as deviations from the Standard Model predictions. In addition, the search for lepton-flavour violation in the charged sector is, at present, a major research program that could also be facilitated by the dynamics generated by leptoquarks. In this article, we consider a rather wide framework of both scalar and vector leptoquarks as the generators of lepton-flavour violation in processes involving the tau lepton. We single out its couplings to leptoquarks, thus breaking universality in the lepton sector, and we integrate out leptoquarks at tree level, generating the corresponding dimension-6 operators of the Standard Model Effective Field Theory. In ref. [1] we obtained model-independent bounds on the Wilson coefficients of those operators contributing to lepton-flavour-violating hadron tau decays and ℓ–τ conversion in nuclei, with ℓ = e, μ. Hence, we use those results to translate the bounds into the couplings of leptoquarks to the Standard Model fermions.
RG flows and thermofield-double states in holography
Authors: Das Suman , Kundu Arnab 
Published: April 2022

AbstractIn this article, we consider a Renormalization Group flow of the Thermofield-Double state in a UV-complete description of Holography, by introducing a relevant deformation to the$$ \mathcal{N} $$N= 4 super Yang-Mills theory at strong coupling. This RG-flow is known to have a non-trivial, interacting$$ \mathcal{N} $$N= 1 fixed point at the IR. Geometrically, an RG-flow of the TFD-state naturally continues radially and inside the black hole event horizon and yields a Kasner-structure near singularity, as has been observed in recent works. We show that for a generic value of the deformation, the putative IR fixed point remains inside the black hole in a certain sense. By fine-tuning this deformation, the “fixed point” can be brought arbitrarily close to the event horizon, while always remaining inside. Physically, this distinguishes between the vanishing temperature limit of the RG-flows with the one at exactly zero temperature. We further discuss its general implications in the context of Holography, including a study of the recently-proposed Holographica-function, especially in the interior of the black hole. We also discuss how correlations between the two-copies of the TFD-state depend on this explicit RG-flow.
Stability of topological solitons, and black string to bubble transition
Authors: Bah Ibrahima , Dey Anindya , Heidmann Pierre 
Published: April 2022

Abstract
We study the existence of smooth topological solitons and black strings as locally-stable saddles of the Euclidean gravitational action of five dimensional Einstein-Maxwell theory. These objects live in the Kaluza-Klein background of four dimensional Minkowski with an S1. We compute the off-shell gravitational action in the canonical ensemble with fixed boundary data corresponding to the asymptotic radius of S1, and to the electric and magnetic charges that label the solitons and black strings. We show that these objects are locally-stable in large sectors of the phase space with varying lifetime. Furthermore, we determine the globally-stable phases for different regimes of the boundary data, and show that there can be Hawking-Page transitions between the locally-stable phases of the topological solitons and black strings. This analysis demonstrates the existence of a large family of globally-stable smooth solitonic objects in gravity beyond supersymmetry, and presents a mechanism through which they can arise from the black strings.
Dark matter and muon g − 2 anomaly via scale symmetry breaking
Authors: Ghorbani Parsa 
Published: April 2022

Abstract
The Standard Model (SM) without the Higgs mass term is scale invariant. Gildener and Weinberg generalized the scale invariant standard model (SISM) by including the multiplication of scalars in quartic forms. They pointed out that along the flat direction only one scalar -called the scalon- is classically massless and all other scalars are massive. Here we choose a SISM with one scalon and one heavy scalar and extend that further respecting the scale invariance by a vector-like lepton (VLL). By an appropriate choice of the flat direction, the heavy scalar enjoys the ℤ2 symmetry and is assumed as DM particle. The scalon connects the visible and dark sector via the Higgs-portal and by interacting with both the muon lepton and the VLL. The VLL is charged under U(1)Y and interacts with γ/Z bosons. We show that the model correctly accounts for the observed dark matter (DM) relic abundance in the universe, while naturally evading the current and future bounds from direct detection (DD) experiments. Moreover, the model is capable to explain the (g − 2)μ anomaly observed in Fermilab. We also show a feature in SISM scenarios which is not present in other Higgs-portal models; despite having the Higgs-portal term |H|2s2 (s being the scalon) in SISM, the effective potential after the electroweak symmetry breaking lacks an important expected vertex hs2. This property immediately forbids the tree-level invisible Higgs decay h → ss and the one-loop Higgs decay h → μ+μ−.
A General Simonenko Local Principle and Fredholm Condition for Isotypical Components
Authors: Baldare Alexandre 
Published: April 2022

AbstractIn this paper, we derive, from a general Simonenko’s local principle, Fredholm criteria for restriction to isotypical components. More precisely, we give a full proof, of the equivariant local principle for restriction to isotypical components of invariant pseudodifferential operators announced in Baldare et al. (Muenster J Math, 2021). Furthermore, we extend this result by relaxing the hypothesis made in the preceding quoted paper.