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Preface for the special issue on selected software artifacts from DisCoTec 2023:The 18th International Federated Conference on Distributed Computing Techniques
No full textThis special issue includes a selection of the artefacts presented at the 18th International Federated Conference on Distributed Computing Techniques (DiScoTec 2023), held at the NOVA University Lisbon (Lisbon, Portugal), in June 18-23, 2023. The federated conference included: COORDINATION 2023, the 25th International Conference on Coordination Models and Languages); DAIS 2023, the 23rd International Conference on Distributed Applications and Interoperable Systems; and FORTE 2023, the 43rd International Conference on Formal Techniques for Distributed Objects, Components, and Systems. All the three conferences welcomed submissions describing technological artefacts, including innovative prototypes supporting the modelling, development, analysis, simulation, or testing of systems in the broad spectrum of distributed computing subjects. The artefact evaluation chairs have selected a subset of high-quality accepted artefacts to be invited for submission to this special issue. Following the revision process, nine artefacts have been accepted to be part of this special issue. The published contributions include different types of artefacts, including programming libraries, frameworks, as well as tools for the analysis, verification, and simulation of distributed systems.</p
Evaluating Membership Inference Attacks in heterogeneous-data setups
No full textAmong all privacy attacks against Machine Learning (ML), membership inference attacks (MIA) attracted the most attention. In these attacks, the attacker is given an ML model and a data point, and they must infer whether the data point was used for training. The attacker also has an auxiliary dataset to tune their inference algorithm. Attack papers commonly simulate setups in which the attacker's and the target's datasets are sampled from the same distribution. This setting is convenient to perform experiments, but it rarely holds in practice. ML literature commonly starts with similar simplifying assumptions (i.e., "i.i.d." datasets), and later generalizes the results to support heterogeneous data distributions. Similarly, our work makes a first step in the generalization of the MIA evaluation to heterogeneous data. First, we design a metric to measure the heterogeneity between any pair of tabular data distributions. This metric provides a continuous scale to analyze the phenomenon. Second, we compare two methodologies to simulate a data heterogeneity between the target and the attacker. These setups provide opposite performances: 90% attack accuracy vs. 50% (i.e., random guessing). Our results show that the MIA accuracy depends on the experimental setup; and even if research on MIA considers heterogeneous data setups, we have no standardized baseline of how to simulate it. The lack of such a baseline for MIA experiments poses a significant challenge to risk assessments in real-world machine learning scenarios
Performance of efficient variants of the 2-Opt heuristic for the traveling salesperson problem
No full textWe analyze variants of the 2-opt local search heuristic for the Traveling Salesperson Problem (TSP) with guaranteed polynomial running-time. First we consider X-opt, a heuristic that removes intersecting pairs of edges from two-dimensional Euclidean instances. We show that the longest X-optimal tour may be approximately n/2 times longer than the optimal tour in the worst case. Moreover, even when the instance consists of n points placed uniformly at random in the unit square, the longest tour is Ω(n) times longer than the optimal tour. Next, we propose a new heuristic, which we call Y-opt, that is defined for all TSP instances, not just Euclidean ones. Y-opt has essentially the same approximation guarantees as the well-studied 2-opt. We furthermore evaluate the approximation performance of both X-opt and Y-opt numerically on random instances and compare them to 2-opt. While Y-opt behaves as predicted, we find that X-opt appears to have a constant approximation ratio on these instances in practice.</p
AI-driven personalized nutrition:RAG-based digital health solution for obesity and type 2 diabetes
No full textEffective management of obesity and type 2 diabetes is a major global public health challenge that requires evidence-based, scalable personalized nutrition solutions. Here, we present an artificial intelligence (AI) driven dietary recommendation system that generates personalized smoothie recipes while prioritizing health outcomes and environmental sustainability. A key feature of the system is the “virtual nutritionist”, an iterative validation framework that dynamically refines recipes to meet predefined nutritional and sustainability criteria. The system integrates dietary guidelines from the National Institute for Public Health and the Environment (RIVM), EUFIC, USDA FoodData Central, and the American Diabetes Association with retrieval-augmented generation (RAG) to deliver evidence-based recommendations. By aligning with the United Nations Sustainable Development Goals (SDGs), the system promotes plant-based, seasonal, and locally sourced ingredients to reduce environmental impact. We leverage explainable AI (XAI) to enhance user engagement through clear explanations of ingredient benefits and interactive features, improving comprehension across varying health literacy levels. Using zero-shot and few-shot learning techniques, the system adapts to user inputs while maintaining privacy through local deployment of the LLaMA3 model. In evaluating 1,000 recipes, the system achieved 80.1% adherence to health guidelines meeting targets for calories, fiber, and fats and 92% compliance with sustainability criteria, emphasizing seasonal and locally sourced ingredients. A prototype web application enables real-time, personalized recommendations, bridging the gap between AI-driven insights and clinical dietary management. This research underscores the potential of AI-driven precision nutrition to revolutionize chronic disease management by improving dietary adherence, enhancing health literacy, and offering a scalable, adaptable solution for clinical workflows, telehealth platforms, and public health initiatives, with the potential to significantly alleviate the global healthcare burden.</p
Preface:The 6th International Workshop on Requirements Engineering for Artificial Intelligence (RE4AI’25)
Get PDFThe Efficacy of Bereavement Interventions:A Systematic Umbrella Review
Get PDFLearning Objectives After participating in this CME activity, the psychiatrist should be better able to: • Summarize findings from systematic reviews and meta-analyses on the efficacy of psychotherapeutic bereavement interventions. • Identify and apply key moderating factors (e.g., symptom severity, timing, age, gender) that influence intervention outcomes. • Analyze methodological limitations in the bereavement literature, including study design and review quality issues. Abstract In recent decades, there have been diverse reviews published on intervention program value for bereaved people. The variation and multiplicity of such reviews makes it difficult to obtain an overview of what is known about treatment effectiveness. In this systematic umbrella review, we explore the current knowledge base on psychotherapeutic bereavement intervention program efficacy. Thirty-three quantitative systematic reviews and/or meta-analyses published between January 2001 and October 2021 were included. Quality was assessed using the Assessment of Multiple Systematic Reviews criteria. Intervention efficacy was determined by rating overall conclusions into three categories according to strength of evidence: positive-unconditional, positive-conditional, and negative-no evidence. Our results indicate that bereavement interventions are generally helpful. Seven reviews indicated positive-unconditional support for bereavement interventions. Twenty-four reviews found positive-conditional support (i.e., some evidence of value, but efficacy did not apply in all circumstances or was constrained by database weaknesses or weak effects), and only two reviews indicated negative-no evidence for support. Notably, conclusions were generally limited by poor review quality and methodological concerns (e.g., lack of randomized controlled trials and follow-up studies). As such, we call for future empirical studies and review articles to abide by methodological quality standards. Furthermore, we recommend further study of the subgroup variables and intervention features that contribute to treatment efficacy.</p
From roadmap to a sustainable end-to-end individualized therapy pathway
Get PDFThe field of individualized, or N-of-1, therapy development is growing and increasingly gaining attention as a novel option for people with serious diseases, caused by unique genetic variants for whom approved therapies are not available. The N-of-1 taskforce of the International Rare Disease Research Consortium previously outlined a roadmap of aspects involved in N-of-1 therapy development and implementation. Here, this follow-up paper looks forward and reflects on how to address existing gaps to advance the current state of individualized interventions toward an integrated and sustainable treatment development model. It discusses what needs to be established for N-of-1 therapies to be developed and utilized at a larger scale, which involves features like sustainability; safety; efficacy; regulatory aspects; dedicated registries and data sharing; tools; long-term treatment monitoring; partnering with patient advocates; and reimbursement models. It closes with recommendations to shape the future of individualized therapies, focusing on ethical implications, education, creation of tools, incentives for data sharing, and innovative payment models.</p
Eco-Innovation and Earnings Management:Unveiling the Moderating Effects of Financial Constraints and Opacity in FTSE All-Share Firms
Get PDFOur research investigates the relationship between eco-innovation and earnings management among 567 firms listed on the FTSE All-Share Index from 2014 to 2022. By examining how sustainability-driven innovation influences financial reporting practices, we explore the strategic motivations behind income smoothing in firms engaged in environmental initiatives. The findings reveal a positive association between eco-innovation and earnings management, suggesting that firms may leverage eco-innovation not only for environmental signalling but also to project financial stability and meet stakeholder expectations. The analysis further uncovers that the propensity for earnings management is amplified in firms facing financial constraints, proxied by low Whited-Wu (WW) scores and weak sales performance, and in those characterised by high financial opacity. We employ a robust multi-method approach to address potential endogeneity and selection bias, including entropy balancing, propensity score matching (PSM), and the Heckman Test correction. Our research contributes to the literature by providing empirical evidence on the dual strategic role of eco-innovation—balancing sustainability signalling with earnings management—under varying financial conditions. The findings offer actionable insights for regulators, investors, and policymakers navigating the intersection of corporate transparency, financial health, and environmental responsibility.</p
Defining optimal orthogeriatric hip fracture care:a delphi consensus approach
Get PDFPurpose: Development of consensus-based recommendations on core and optimal elements of orthogeriatric hip-fracture care. Methods: An online Delphi survey was performed in the Netherlands. A total of 72 statements were derived from a framework encompassing all phases of care for older patients with a hip fracture. These statements were presented to the panelists in two rounds to identify elements for minimal and optimal orthogeriatric care. Panelists included professionals with experience in hip-fracture care and patient representatives. The level of agreement was measured using a 5-point Likert scale. Consensus was considered if > 75% of the panelists agreed or disagreed. Results: Ninety-two persons were invited to participate in the survey; 63 participated in the first round and 55 in the second round. One statement was added in the second round. Most participants had a background in geriatrics (36% in the second round) or trauma surgery/orthopaedics (20% in the second round). Consensus was reached on 48 statements for minimal orthogeriatric care and 60 statements for optimal orthogeriatric care. Conclusion: This study supports previously established recommendations for older adults with hip fractures. In addition, it offers practical recommendations for implementation of orthogeriatric care regarding both core and optimal care elements for hospitals at every different level of maturity and at every step in the care process. This may decrease the intra- and inter-hospital variability of clinical management of hip-fracture patients. Organizational and logistical elements present a barrier to overcoming the gap between the current practice and the optimal situation.</p