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Aligning generalization between humans and machines
No full textRecent advances in artificial intelligence (AI)—including generative approaches—have resulted in technology that can support humans in scientific discovery and forming decisions, but may also disrupt democracies and target individuals. The responsible use of AI and its participation in human–AI teams increasingly shows the need for AI alignment, that is, to make AI systems act according to our preferences. A crucial yet often overlooked aspect of these interactions is the different ways in which humans and machines generalize. In cognitive science, human generalization commonly involves abstraction and concept learning. By contrast, AI generalization encompasses out-of-domain generalization in machine learning, rule-based reasoning in symbolic AI, and abstraction in neurosymbolic AI. Here we combine insights from AI and cognitive science to identify key commonalities and differences across three dimensions: notions of, methods for, and evaluation of generalization. We map the different conceptualizations of generalization in AI and cognitive science along these three dimensions and consider their role for alignment in human–AI teaming. This results in interdisciplinary challenges across AI and cognitive science that must be tackled to support effective and cognitively supported alignment in human–AI teaming scenarios
Legal Challenges to Enhancing Coherence and Effectiveness in EU Foreign and Security Policy
No full textThis paper examines and expands upon the legal options for enhancing coherence and effectiveness within the Common Foreign and Security Policy (CFSP) by leveraging existing decisionmaking procedures. In response to calls from European Union (EU) institutions and several Member States, it explores avenues within the current treaty framework to improve CFSP performance and overcome blockages caused by the unanimity rule. Beyond evaluating the potential use of Qualified Majority Voting (QMV) in CFSP, the paper also highlights the EU’s recent efforts to employ trade instruments for foreign policy objectives, as well as the increasing role of the Commission in the Union’s security and defence policy. The central argument of this paper is that the coherence between various Union policies serves as the key to improving its effectiveness in foreign and security policy
Lignocellulosic biomass to biochar:An overview on impact of production technologies on biochar yield and techno-economics
No full textBiochar technology is getting attention globally due to its multifaceted potential in removing contaminants from wastewater, storing energy as supercapacitor, enhancing soil health, and addressing environmental challenges as a negative emission technology. The aim of this study is to review the conversion of different types of lignocellulosic biomass into biochar using various thermochemical conversion methods. The physiochemical properties of produced biochar using different characterization techniques have been reviewed. Slow pyrolysis consistently produces higher biochar yields (up to approximately 79 %) compared to fast pyrolysis, gasification, or flash carbonization, which primarily focus on generating bio-oil or syngas. Smaller biomass particles enhance heat transfer, and may lead to reduced yields due to the accelerated pyrolysis process. Lower temperatures and lignin-rich biomass promote higher solid yields, whereas higher temperatures facilitate carbonization but result in reduced biochar yield. Further, the economic viability of biochar production from large-scale industrial units and small-scale portable systems is reported as per the existing literature and the selling price of biochar produced from small scale units is found to be higher. This review suggested that the major challenges in biochar technology include but not limited to advanced harvesting techniques, improved logistics, decentralized efficient and economical biochar production units, method of biochar addition to soil etc. Future research in this technology should focus on tailoring biochar properties for specific applications, optimizing pyrolysis conditions and post-processing techniques, and exploring alternative feedstocks to enhance sustainability, efficiency, and versatility.</p
Privacy-preserving power estimation for DC microgrids:A differentially private distributed fusion filtering approach
No full textThis paper explores the privacy-preserving power estimation problem in DC microgrids with plug-and-play functionality. To safeguard the privacy of data associated with distributed generation units, a novel differentially private distributed fusion filtering algorithm is proposed. Under some mild assumptions, such as collective observability and bounded system parameters, the security, optimality of the gain matrix, consistency, and stability of the designed filters are ensured. Finally, simulation experiments demonstrate the effectiveness of the proposed algorithm.</p
Container-level Energy Observability in Kubernetes Clusters
No full textKubernetes has been for a number of years the default cloud orchestrator solution across multiple application and research domains. As such, optimizing the energy efficiency of Kubernetes-deployed workloads is of primary interest towards controlling operational expenses by reducing energy consumption at data center level and allocated resources at application level. A lot of research in this direction aims on reducing the total energy usage of Kubernetes clusters without establishing an understanding of their workloads, i.e. the applications deployed on the cluster. This means that there are untapped potential improvements in energy efficiency that can be achieved through, for example, application refactoring or deployment optimization. For all these cases a prerequisite is establishing fine-grained observability down to the level of individual containers and their power draw over time. A state-of-the-art tool approved by the Cloud-Native Computing Foundation, Kepler, aims to provide this functionality, but has not been assessed for its accuracy and therefore fitness for purpose. In this work we start by developing an experimental procedure to this goal, and we conclude that the reported energy usage metrics provided by Kepler are not at a satisfactory level. As a reaction to this, we develop KubeWatt as an alternative to Kepler for specific use case scenarios, and demonstrate its higher accuracy through the same experimental procedure as we used for Kepler
Musical abilities influence the use of durational prosodic cues in spoken word recognition
No full textProsody plays a fundamental role in both speech and music. In spoken language, word-level local prosodic cues, such as segment duration, contribute to word recognition. This study investigated whether individual differences in musical abilities are associated with the utilization of prosodic cues during spoken word recognition, both in speech-in-quiet and speech-on-speech conditions (i.e., in the presence of competing talkers). Using the visual world paradigm, we measured listeners' gaze fixations and pupil dilations toward images depicting a referent (e.g., hamster) and a competitor word (e.g., ham), while they simultaneously listened to utterances containing the referent word, whose segment duration either matched or mismatched the referent, with the mismatched duration signaling the competitor word. Participants with varying musical backgrounds completed tasks assessing rhythmic and melodic abilities, and a questionnaire evaluating overall musical sophistication. Our results revealed that listeners with higher scores across the three measures exhibited greater sensitivity to durational cues, as indicated by increased fixations to the competitor and greater pupil dilation when the durational cue mismatched the referent word, both in speech-in-quiet and speech-on-speech. These findings highlight that individual differences in musical abilities are associated with the use of prosodic cues during spoken word recognition. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p
Renal resistance trajectories during hypothermic machine perfusion in kidneys donated after circulatory death:Associations with donor characteristics and posttransplant outcomes—An analysis of COMPARE trial data
No full textRenal resistance (RR) during hypothermic perfusion is commonly used as a factor to assess kidney quality, with most studies focusing on terminal RR measurements. We fitted a linear model to the entire RR trajectory using data from the randomized Consortium for Organ Preservation in Europe COMPARE trial and explored the relationship between the RR trajectory, donor characteristics, and posttransplant outcomes, also assessing the prognostic value of terminal RR for delayed graft function (DGF). Donor weight (F = 5.32; P = .005) and cause of death (F = 2.91; P = .008) were associated with the RR trajectory, whereas active oxygenation had no effect (F = 1.12; P = .33). The RR trajectory did not predict DGF (F = 1.93; P = .15), biopsy-proven acute rejection (F = 0.41; P = .66), 1-year kidney function (F = 0.61; P = .54), or 1-year graft survival (F = 0.47; P = .63). Terminal RR independently predicted DGF (odds ratio 1.14; 95% CI, 1.009-1.298; P = .03) but had limited prognostic value (area under the receiver operating characteristic curve, 0.63; 95% CI, 0.55-0.71), aligning with previous research. Our findings suggest that the RR trajectory reflects the kidney's intrinsic response to perfusion, with donor weight and cause of death potentially influencing its progression. The absence of a relation between the RR trajectory and posttransplant outcomes stresses that using RR as a standalone criterion for kidney discard is not justified and may lead to unnecessary discard. Our findings also call for further validation in larger, more diverse cohorts.</p