bluuebunny/crossref_metadata_2025_split huggingface dataset:
Drawing Based Game for Teaching Scrum
Authors: Marek Krzysztof , Martyniuk-Sienkiewicz Kamila 
Published: January 2025

AbstractOver the years, the use of gamification in teaching different agile approaches become more popular. Many proposed solutions are based on moving tasks on physical or virtual boards. Some connect task realisation with the performance of simple, repetitive manual tasks. The approach described in this paper utilises the activity of drawing simple icons on post-its to mimic the active and creative aspect of e.g. software development. The described game allows for teaching multiple practices used in Scrum software development connected to software quality and requirements, including the importance of the Definition of Done, acceptance criteria and continuous improvement based on Sprint Review and Retrospective. Initial results are promising while working with students with no or almost no previous understanding of the software development process. Additionally, the game can be easily modified or extended to help with teaching other aspects of the Scrum software development process.
An Agile Mindset in a VUCA-World
Authors: Bangshøj Carolina Appel , Havstorm Tanja Elina , Algulin Åsa 
Published: January 2025

AbstractAs the world is heading into a new era of software development (SD) an Agile Mindset (AM) has been seen to provide valuable underlying guiding elements to navigate an increasingly interconnected, turbulent, and dynamic business landscape, a VUCA-world. This study investigates the topic of agile methods and an AM through multiple-case studies with IT professionals from four tech companies. The study gathers early-stage research data to better understand what an agile SD team member does on an everyday basis in their work to exercise and achieve an AM, and what factors in the organization are impacting them in being able to do so. VUCA has been utilized as a conceptual background through which the findings – AM means and influences – have been identified, concluding that there is still much to be harnessed and learned about the elements of an AM that can improve project success outcomes.
Stories Vs. User Stories: A Terminological Clarification
Authors: Franch Xavier , Steffe Hans-Jörg , Bühne Stan , López Lidia , Sturm Stefan 
Published: January 2025

AbstractUser stories are the main vehicle to describe user needs in Agile projects and Agile project developments. But being this concept universally agreed, we may find that not all work increments have a clear user-centric view. In this paper, we focus on the distinction between user-centric “user stories” and other type of simple narratives, which may be simply called “stories”, which can be at the same level of abstraction. We propose a conceptual model in the form of UML diagram, and associated definitions, to clarify this distinction. The model also makes clearer the distinction among (user) story and (user) story template, which is not always kept clear.
Generative AI for Test Driven Development: Preliminary Results
Authors: Mock Moritz , Melegati Jorge , Russo Barbara 
Published: January 2025

AbstractTest Driven Development (TDD) is one of the major practices of Extreme Programming for which incremental testing and refactoring trigger the code development. TDD has limited adoption in the industry, as it requires more code to be developed and experienced developers. Generative AI (GenAI) may reduce the extra effort imposed by TDD. In this work, we introduce an approach to automatize TDD by embracing GenAI either in a collaborative interaction pattern in which developers create tests and supervise the AI generation during each iteration or a fully-automated pattern in which developers only supervise the AI generation at the end of the iterations. We run an exploratory experiment with ChatGPT in which the interaction patterns are compared with the non-AI TDD regarding test and code quality and development speed. Overall, we found that, for our experiment and settings, GenAI can be efficiently used in TDD, but it requires supervision of the quality of the produced code. In some cases, it can even mislead non-expert developers and propose solutions just for the sake of the query.
Responsible AI in Agile Software Engineering - An Industry Perspective
Authors: Ulfsnes Rasmus , Moe Nils Brede , Emmerhoff Jostein , Floryan Marcin , Griva Anastasia , Gundelsby Jan Henrik , Barbala Astri Moksnes , Conboy Kieran 
Published: January 2025

AbstractThere is a rapid emergence of tools, methods, and guidance for the use of AI across all parts of the software development process, from requirements gathering to code generation to testing and user feedback. However, AI raises many concerns regarding responsible use, and there is a need to understand and develop principles for what responsible software development entails in practice in an agile context, as well as carefully evaluate the incorporation of AI tools and methods in software engineering. We draw on experience from Bespot, Knowit, Schibsted, and Spotify to identify challenges faced by companies pioneering the use of AI in their software development efforts and start charting a roadmap for responsible AI in software engineering.
A Journey Through SPACE
Authors: Wivestad Viggo Tellefsen , Ulfsnes Rasmus 
Published: January 2025

AbstractThis study examines the influence of perceived changes in productivity in the context of introducing AI Coding Assistants, specifically GitHub Copilot, within two large-scale agile organizations. Using a cross-sectional survey, we measured self-reported changes in productivity using the SPACE framework. Our comparative analysis suggests several perceived benefits of AI Code Assistant adoption, though with a more conservative impact than previously reported. Further, a correlational analysis employing Kendall’s tau and PLSR with 10-fold cross-validation suggests that perceived changes to productivity are moderately associated only with four of the nine features tested, namely job satisfaction, flow, task completion speed, and ability to focus on satisfying work. However, the SPACE framework’s ability to fully capture perceived productivity was further challenged, indicating discrepancies in its dimensions of “Performance” and “Communication and collaboration”.
Hybrid Meetings in Agile Software Development
Authors: Stray Viktoria , Moe Nils Brede , Semsøy Susanne 
Published: January 2025

AbstractHybrid meetings, which combine in-person and virtual participants, are becoming increasingly common in modern agile workplaces. Despite their prevalence, these meetings often lead to asymmetric participation. In this study, we explored the nature of participation asymmetries in hybrid meetings and identified the technical and social factors contributing to these disparities. We analyzed anonymized access card data, observed hybrid meetings, and conducted interviews with employees in a large-scale Norwegian software development organization. Our findings reveal that the employees preferred to go to the office on Tuesdays and Wednesdays. In hybrid meetings, we found reduced engagement from virtual participants compared to those co-located at the office, especially in the absence of a clear speaking order. Social-driven asymmetries included difficulties in entering conversations, missing remarks and non-verbal cues, and being left out of pre- and post-meeting discussions. Physical presence in meetings was found to be crucial for newly onboarded team members. Future research should investigate what fosters inclusive meeting practices to improve engagement and collaboration in hybrid work environments.
Crypto-Asset White Papers and Marketing Communications Post the MiCA Regulation
Authors: Cobos María-Teresa Otero 
Published: January 2025

AbstractThis paper comprehensively analyses the regulatory framework applicable to disclosure and transparency tools used in promoting crypto assets, particularly in the context of the MiCA Regulation. The paper focuses on the information a crypto-asset white paper should contain and all relevant details about marketing communications, such as advertising messages and marketing material. In commercial communications, the work delves into Directive (EU) 2019/1024 and Regulation (EU) No. 596/2014 to examine the rules and guidelines related to the content of crypto-asset advertising posted by professional social media profiles. This will highlight how the authorities are working to prevent the publication of false, misleading, or incomplete information on these issues.
PSD3 and the Regulation on Payment Services in the Context of Crypto Assets as a Means of Payment
Authors: Herrera Lucía Alvarado 
Published: January 2025

AbstractThe Markets in Crypto-Assets (MiCA) Regulation establishes legal rules for crypto-assets that have a financial use and fall outside the scope of Union legislative acts on financial services. Among these crypto assets, it pays special attention to stablecoins, the so-called MiCA electronic money tokens and asset-referenced tokens, which are characterised by serving as a payment function. It is precisely this function of being a means of payment that raises the question of whether the transactions carried out with these crypto assets, or at least some of them, can be qualified as payment services, to which the legal framework for payment services, contained mainly (but not exclusively) in the Second Payment Services Directive (PSD2), currently under revision, would apply. This paper deals with the relationship between the two sets of rules (MiCA and PSD2). It analyses to what extent the existing and planned rules (PSD3 and Payment Services Regulation) can be applied to or somehow cover electronic money tokens and asset-referenced tokens.
Crypto Assets and Financial Data Space Regulation in the EU’s Hybrid System of Hard and Soft Law
Authors: Pastor Sempere Carmen 
Published: January 2025

AbstractThe new data economy needs diverse financial data from many data holders, far removed from the data a traditional bank would hold. This paper outlines the new vision for the common European Financial Data Space, where multiple interconnected data ecosystems, like the internet, are designed to empower individuals by placing them at the centre. This seeks to keep the financial sector of the European Union in tune with the digital transformation while ensuring, at the same time, the security and confidence of consumers. For these reasons, the EU seeks open finance and a legal framework that underpins a new regulatory approach based on coregulation, comprising a hybrid system of hard law and soft law for the exchange of financial data. This regulatory proposal is FiDA [proposal for a Financial Data Access regulation]. The paper also examines the proposed legal regime and its coordination with the current regulation of new crypto assets and their financial data. It examines the basis for and explores the limitations of the latest legal framework for regulating access to financial data. The current regulation that will be referred to is the existing regulation on crypto-assets (Markets in Crypto-assets- MiCA, access to payment data (such as Open banking, Payment Services Directive, PSD2), and the eIDAS 2, as well as the proposal for the modernisation of the existing EU Payment Services Directive (Open Finance, PSD3 and FiDA).
Web Technologies for Decentralised Identity
Authors: Rodríguez-Doncel Víctor 
Published: January 2025

AbstractThis chapter analyses technologies that support decentralised identity on the Web. The World Wide Web Consortium, which maintains the technical specifications of the Web, has consistently advocated for decentralised models for sharing information. Some of their latest recommendations include the specification of a Decentralised Identifier (DID) and a Verifiable Credential (VC) following the Semantic Web principles. The claims contained in these credentials can be algorithmically verified without the intervention of authorities. These technologies are often associated with implementing the Self-Sovereign Identity paradigm, and this chapter evaluates whether this will happen in practice, particularly in the context of the financial sector. Whereas some privacy concerns are identified, the integrated use of DID, VC and Open Digital Rights Language ODRL will present clear benefits in at least some commercial settings.
Uncovering the Fungal Community Composition of Alive and Dead Posidonia oceanica Matte
Authors: Frasca Sara , Alabiso Annamaria , D’Andrea Marco Maria , Migliore Luciana 
Published: January 2025

AbstractPosidonia oceanica retains a large amount of carbon within its belowground recalcitrant structure, the ‘matte,’ which is characterized by low oxygen availability and biodegradation. Fungi may play a pivotal role in carbon sequestration within the matte, even if little/no information is available. To fill this gap, we profiled fungal communities from the upper and lower layers of alive and dead matte, by using an ITS2-5.8S rDNA metabarcoding approach. The study was conducted in a shallow coastal stretch of the Aegean Sea (Crete). Then, 184 operational taxonomic units were identified, predominantly belonging to Ascomycota, in alive and dead matte. Nevertheless, their composition significantly differed: the host-specific Posidoniomyces atricolor was dominant in alive but not in dead matte, while fast-growing saprotrophs, potentially accelerating the decomposition rate, increased in dead matte. These findings lay the groundwork for future investigations on the possible increase of biodegradation under the changing environmental conditions.
Using incomplete and incorrect plans to shape reinforcement learning in long-sequence sparse-reward tasks
Authors: Müller Henrik , Berg Lukas , Kudenko Daniel 
Published: January 2025

AbstractReinforcement learning (RL) agents naturally struggle with long-sequence sparse-reward tasks due to the lack of reward feedback during exploration and the problem of identifying the necessary action sequences required to reach the goal. Previous works have used abstract symbolic task knowledge models to speed up RL agents in these tasks by either splitting the task into easier to solve sub-tasks or by creating an artificial dense reward function. These approaches are often limited by their requirement of perfect symbolic knowledge models, which cannot be guaranteed when the abstract symbolic models are provided by humans and in real-world tasks. We introduce exponential plan-based reward shaping, which is able to leverage the ability to learn from experience of RL to compensate deficiencies in incomplete and incorrect abstract symbolic plans and use them to solve difficult tasks faster, while guaranteeing convergence to the optimal policy. Our approach is able to work with plans that miss important steps, include unnecessary extra steps, contain steps that refer ambiguously to both important and useless states, or encode an incorrect order of steps. We use action representations designed by human experts to automatically compute plans to capture the high-level task structure. The abstract symbolic subgoals defined by the plan are used to create dense reward feedback, which signals important states to the RL agent that should be achieved and explored to reach the goal. We show the theoretical advantages of our approach for plans with many steps and show its effectiveness empirically on multiple tasks with different kinds of incomplete or incorrect knowledge.
Explainable energy consumption and speed prediction in sustainable cities using deep learning
Authors: Abd El-Latif Eman I. , El-dosuky Mohamed 
Published: January 2025

AbstractThe idea of sustainable cities has drawn a lot of attention due to the quick expansion of metropolitan areas as well as the growing problems brought on by resource scarcity and climate change. Cities that prioritize sustainable practices are those that minimize their negative effects on the environment, maximize resource efficiency, and improve the standard of living for their citizens. Therefore, for sustainable cities, this paper uses the vehicle energy dataset (VED) to estimate travel times and calculate vehicle energy consumption. The dataset contains 12,609,170 road elevation tracks, 12,203,044 speed limit tracks, and 12,281,719 speed limit records with direction. An open-source routing engine called Valhalla is utilized to do a variety of tasks, including finding paths, matching maps, and creating maneuvers based on paths. The three primary stages of the suggested model are data pre-processing, feature extraction, and result interpretation. In the data pre-processing stage, null values are first eliminated and data normalization is implemented. Then, three techniques known as the gated recurrent unit (GRU), recurrent neural network (RNN), and long short-term memory (LSTM) are used to optimize the model. Finally, the results are interpreted through the use of SHAP (SHapley Additive explanations) in explainable artificial intelligence (XAI) techniques. The LSTM model yields the best prediction results, achieving 15.2662 RMSE, 11.7266 MAE, and 0.6696 R2 at 8 batch size, according to the evaluation results. Additional experiments are carried out in batch sizes of 8, 16, 32, and 64.The lowest metrics are produced by batch sizes of 64, while the best metrics are produced by batch sizes of 8.
Analytical model of induction heating buckling of a beam
Authors: Filkin Vladimir , Vetyukov Yury , Toth Florian 
Published: January 2025

AbstractInduction heating is an important technology for many engineering applications. Its modelling and analysis are challenging because it is a multiphysics phenomenon coupling geometrically nonlinear mechanics, electromagnetics and heat conduction. One of the challenges is buckling of thin plates and beams due to high temperatures and thermal gradients. The mechanical buckling changes the electromagnetic configuration of the model, thus changing the thermal solution, which affects mechanics back leading to a fully coupled problem. While this phenomenon has been studied numerically in the literature, it lacks an analytical treatment. We propose a closed-form analytical solution for the post-buckling deformation of induction heated beams. Using the solution, we conduct multiple parameter studies, aiming to gain a foundational understanding of the behaviour exhibited by the coupled system.
Taurine prevents mitochondrial dysfunction and protects mitochondria from reactive oxygen species and deuterium toxicity
Authors: Seneff Stephanie , Kyriakopoulos Anthony M. 
Published: January 2025

AbstractTaurine, although not a coding amino acid, is the most common free amino acid in the body. Taurine has multiple and complex functions in protecting mitochondria against oxidative-nitrosative stress. In this comprehensive review paper, we introduce a novel potential role for taurine in protecting from deuterium (heavy hydrogen) toxicity. This can be of crucial impact to either normal or cancer cells that have highly different mitochondrial redox status. Deuterium is an isotope of hydrogen with a neutron as well as a proton, making it about twice as heavy as hydrogen. We first explain the important role that the gut microbiome and the gut sulfomucin barrier play in deuterium management. We describe the synergistic effects of taurine in the gut to protect against the deleterious accumulation of deuterium in the mitochondria, which disrupts ATP synthesis by ATPase pumps. Moreover, taurine’s derivatives, N-chlorotaurine (NCT) and N-bromotaurine (NBrT), produced through spontaneous reaction of taurine with hypochlorite and hypobromite, have fascinating regulatory roles to protect from oxidative stress and beyond. We describe how taurine could potentially alleviate deuterium stress, primarily through metabolic collaboration among various gut microflora to produce deuterium depleted nutrients and deuterium depleted water, and in this way protect against leaky gut barrier, inflammatory bowel disease, and colon cancer.
Impact of COVID-19 Public Health Measures on Antiretroviral Therapy Use Among Ugandans Living with HIV in Sero-Different Couples
Authors: Muwonge Timothy R. , Feutz Erika , Nsubuga Rogers , Simoni Jane M. , Nambi Florence , Nakabugo Lylianne , Namanda Sylvia , Kibuuka Joseph , Thomas Dorothy , Katz Ingrid T. , Thomas Katherine K. , Ware Norma C. , Wyatt Monique A. , Kadama Herbert , Mujugira Andrew , Heffron Renee 
Published: January 2025

AbstractAntiretroviral therapy (ART) use and HIV suppression among people living with HIV (PLHIV) are critical for HIV control and prevention. Extreme restrictions on movement early during the COVID-19 pandemic in Uganda may have impeded the ability to initiate and sustain access to and use of ART. From our stepped-wedge cluster-randomized trial of an integrated PrEP and ART intervention for HIV-serodifferent couples at 12 ART clinics in Uganda, we identified participants who enrolled and had a 6-month post-ART initiation viral load measured before the beginning of the first COVID-19 lockdown (Period 1), participants whose enrollment and 6-month viral load measurement straddled pre-COVID and COVID lockdown times (Period 2), and participants whose enrollment and 6-month viral load were quantified entirely during COVID-19 (Period 3). ART and viral load data were abstracted from standard-of-care HIV clinic records. We used adjusted generalized estimating equation models to compare viral suppression between the different periods. We enrolled 1,381 PLHIV, including 896 (64.9%) in Period 1, 260 (18.8%) in Period 2, and 225 (16.3%) in Period 3. Almost all (1371, 99.3%) initiated ART within 90 days of enrollment and 59.2% had baseline CD4 > 350 cells/mm3. Among those enrolled, 88.8% of participants in Period 1 were virally suppressed (< 1000 copies/mL) within six months of ART initiation, 80.5% in Period 2, and 88.2% in Period 3. All pairwise comparisons demonstrated statistically similar levels of viral suppression. Despite COVID-19 lockdown measures, PLHIV in serodifferent partnerships successfully initiated ART and attained and maintained viral suppression.
How Teachers Envision Using Data Visualization Discussion Tasks in Classroom Instruction
Authors: Wilkerson Michelle H. , Kim John , Lee Hollylynne S. , Stokes David J. , Ferrell Matthew 
Published: January 2025

AbstractA growing number of teaching materials invite students to discuss the complex mathematical, contextual and social aspects of data visualizations. Orchestrating such discussions can be difficult, as this requires teachers to balance a variety of learning goals and student perspectives. This paper examines how teachers interact with data visualization discussion tasks—specifically, those that engage visualizations’ social complexities—as they consider using them in their own classrooms. Drawing from semi-structured clinical interviews with six U.S.-based teachers as they reviewed discussion tasks called Data Story Bytes, we explore: How did these teachers envision using these data visualization discussions in their classrooms? And, What mathematical, contextual, and/or social aspects of visualizations did teachers emphasize when engaging with the discussion task materials? We found that all teachers envisioned using data visualization discussions as lesson openers or routine activities, but they differed in their overall emphasis on the visualizations’ mathematical, contextual, or social aspects. Despite these differences, certain types of discussion prompts were associated with particular response patterns across all teachers, suggesting these task structures can help guide teachers to address a shared set of intended baseline goals for all three of these dimensions. Our findings represent a first step in understanding whether and how socially-oriented data discussion materials may be enacted in classrooms, and what additional design features and supports may be needed to help teachers do so productively.