Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
Archivio istituzionale della ricerca - Alma Mater Studiorum Università di BolognaNot a member yet
336958 research outputs found
Sort by
Integration of statutory norms in computable contracts
No full textLegal contracts are governed not only by their explicit terms but also by statutory norms, a principle recognized
across legal systems. As contracts become computable and executable as code, ensuring compliance with these
norms becomes critical. This paper introduces a method for integrating legislative provisions into computable
contracts using the Stipula language, via a novel import construct. We distinguish between mandatory and
default imports to model imperative and optional legal norms, respectively, and define a mechanism to
enforce the priorities between these norms and contract’s provisions. This approach supports the automated
creation of legally compliant contracts and lays the foundation for a broader framework aimed at enhancing
the effectiveness of consumer rights through programmable legal tools
Clash-of-Leges: A Bilingual Dataset for Conflict Detection and Explanation in Statutory Law
Full text linkLegal conflicts between statutes or constitutional articles present a significant challenge in maintaining consistency and coherence within legal systems. Addressing these conflicts requires extensive human expertise, making the process labor-intensive and time-consuming. In this paper, we introduce Clash-of-Leges, a novel multilingual dataset derived from rulings by the Constitutional Court of the Italian Republic, designed to aid the automation of conflict detection and explanation between legal articles. We identify three key tasks: Conflict Classification, which determines whether two legal articles are in conflict; Conflict Explanation Generation, which provides detailed explanations for identified conflicts; and Reference Retrieval, which sources relevant legal bases and precedents to substantiate interpretations. These tasks are intended to facilitate the development of AI models that can automatically identify and explain contradictions between legal provisions
Optimized selectivity in CO2 electrochemical reduction using amorphous CuNi catalysts: insights from density functional theory and machine learning simulations
No full textAmorphous materials represent a promising platform for advancing CO2 electrochemical reduction due to their inherently diverse coordination environments. In this study, we demonstrate computationally the superior performance of amorphous CuNi alloys for CO2 electrochemical reduction. By integrating machine learning forcefields for efficient structure generation and density functional theory for subsequent structural refinement and property calculations, we reveal the potential of these disordered systems to outperform their crystalline counterparts. Machine learning forcefields can generate a bulk structure containing a mixture of Cu and Ni atoms, resulting in enhanced catalytic performance. Effective screening of the amorphous surfaces is used to identify undercoordinated Cu and Ni sites in the amorphous structure to synergistically promote selective CO production and favor ethanol formation over ethylene via the stabilization of the *COCHO intermediate, resulting in significantly lower Gibbs free energy changes compared to the crystalline counterpart. The varying atomic coordination environments on amorphous surfaces promote both C–C bond formation and subsequent proton-electron transfer, leading to ethanol formation. These findings demonstrate the superior catalytic performance of amorphous CuNi, highlighting its potential for efficient and selective electroreduction of CO2
A framework for integrated design of human–robot collaborative assembly workstations
No full textCollaborative robotics is increasingly considered in manufacturing to improve efficiency while reducing operators physical and cognitive workloads. However, the lack of comprehensive methodologies has limited the consistent implementation of human–robot collaborative workstations across industries. Existing approaches are often fragmented, require robotics expertise, and pose challenges for non-experts, leading to suboptimal station designs and inefficient task allocation. This study presents a structured design framework to transition traditional assembly processes into collaborative ones. The framework provides a practical, scalable solution for optimizing collaborative workstations, balancing performance, ergonomics, and industrial applicability. It starts from the analysis of the assembly tasks, followed by classification and allocation between human operators and robots, and concludes with virtual prototyping and performance optimization through simulation using a commercial tool. The adopted methodology integrates task analysis, ergonomic assessment, and workspace design to ensure accessible and efficient implementation. Validated through two industrial case studies involving a gear pump and a worm gearbox, the approach demonstrated significant reductions in cycle time and notable improvements in the ergonomic working conditions. Additionally, physical prototyping and testing conducted within a research collaborative cell further confirmed the achieved results
Impact of thermal protections insulation layer on solid rocket motor residual thrust
No full textThe aim of the paper is to reproduce thermal protection ablation in solid rocket motors focusing on how it affects rocket performance. A physical model able to predict thermal protection ablation behavior coupled with an internal ballistic simulator is outlined. The main outcome of the above-mentioned model is the estimation of the residual thrust occurring after burn-out at high altitudes. The evaluation of the residual thrust is especially important for solid rocket motors used as upper stages and after burn-out operations take place in vacuum. During these phases, residual thrust is generated by the expansion of pyrolysis gases produced by the ablation of thermal protection materials. The nozzle radiative power was identified as the main source causing thermal protection material to ablate. An investigation of a commercial motor performance is conducted and discussed. A detailed explanation of the numerical methods used is provided
Information-signaling in pre-trial bargaining: An experiment
No full textThis paper provides experimental evidence on the effectiveness of self-penalizing commitments as signaling mechanisms in pre-trial bargaining under asymmetric information, aimed at reducing trial rates. Using an online experiment (N=2,041), we design a novel two-type signaling game with asymmetric information, where one party possesses private information regarding the strength of its case, and proposes a take-it-or-leave-it settlement offer to an uninformed party. In the baseline scenario, the uninformed party must decide whether to accept the offer, or reject it and proceed to a costly trial. In our novel signaling treatments, the informed party can credibly commit ex ante to a costly monetary penalty contingent upon losing at trial. Consistent with theoretical predictions, our results show that self-penalizing commitments reduce trial rates. Informed parties are more likely to commit when they have strong cases; and uninformed parties interpret the commitment as a signal of merits, and are more likely to settle less-generous offers when these are coupled with a commitment. However, we also document departures from theory: effect magnitudes are generally smaller than expected; the commitment device is both under- and over-used across offer ranges; and, when committing is possible, buyers sometimes penalize its omission by rejecting otherwise generous offers
Do mission-oriented grant schemes shape the direction of science?
No full textA growing body of literature has examined how applying for and winning competitive project grants affects the career trajectory of scientists in terms of productivity, quality, social networks, and knowledge. However, the role of grant schemes in shaping the direction of scientific inquiry remains poorly understood. In this study, we investigate how the research of grant recipients, rejected applicants, and a set of comparable non-applicants working in the same fields relates thematically to a set of funding calls issued by the Swedish Foundation for Strategic Research. These calls are all of the ‘request for applications’ (RFA) type – i.e. targeting a specific type of research that the funder has identified and seeks to strengthen. We analyze the similarity between the topics embedded in applicants' research and the ones embedded in RFA calls. Applying a matching procedure followed by a difference-in-differences design, we find that applicants increase their topic similarity with the call more than non-applicants. However, we find no significant differences between the research of funded and rejected applicants – both groups shift their research in the direction of the call at a similar rate. These results cannot be explained by differences in post-call productivity. While we do not claim to have definitively disentangled the treatment from the selection effect on this issue, our findings have important implications for science policy and for our understanding of how the formulation of RFA calls shapes the direction of scientific inquiry
Search for magnetic monopoles with the complete ANTARES dataset
No full textThis study presents a search for magnetic monopoles using the full ANTARES dataset collected over 14 years (2008–2022). The interaction of monopoles with matter was modeled according to the Kazama, Yang and Goldhaber cross-section, and dedicated reconstruction strategies were applied to probe velocities both above and below the Cherenkov threshold. No signal consistent with monopoles was found. We derive 90% C.L. upper limits on the flux of relativistic monopoles at the level of 10 − 18 c m − 2 s − 1 s r − 1 , improving upon previous ANTARES results and confirming those obtained by IceCube and other neutrino telescopes. These results constitute the final contribution of ANTARES to the search for magnetic monopoles
Reframing Socio-Cultural Malaise in the Technocene: A psychosocial reading of Abe Kōbō’s Inter Ice Age 4 and Kazuo Ishiguro’s Klara and the Sun
Full text linkThis essay explores the role of emotionally intelligent machines in affecting human identity and social bonds through a psychosocial reading of Abe Kōbō’s Inter Ice Age 4 (1959) and Kazuo Ishiguro’s Klara and the Sun (2021). Despite decades of technological progress between the publication of the two works, both novels deal with alienation and loneliness in dystopian paradigms by portraying artificial intelligence (AI) as a solution. While the machines are expected to meet the emotional needs of humans, Inter Ice Age 4 employs AI to destabilize the Soviet Union’s political power during the Cold War and change the future of humanity; Klara and the Sun epitomizes the social isolation provoked by the dominance of virtual life, augmented reality, and AI surrogates. After an initial interdisciplinary framing of the psychosocial perspective on AI, this essay discusses how the two novels reframe the socio-cultural malaise of the “emotional technologies,” thus denouncing the individual alienation and the identity crisis raging in contemporary times, assessing anthropo-technological progress in human-machine interaction as a symptom of present insecurity
Do driver assistance systems mitigate passengers’ perceived risk when riding with a driver under the influence of alcohol? Evidence from a discrete choice experiment among youths
No full textRecently, the presence of Advanced Driver Assistance Systems (ADAS) on passenger cars has become extensive, also prompted by EU regulation mandating their inclusion in new vehicles. While ADAS are effective in reducing crash frequency, there is growing concern about a potential risk compensation effect – namely, that drivers or passengers may engage in riskier behavior due to a perceived increase in safety when ADAS are present. This study evaluates the trade-offs made by youths when assessing the risk of riding with a driver under the influence of alcohol, in the presence or absence of ADAS. We develop a discrete choice experiment and estimate several discrete choice models, including latent class and hybrid choice models. Our findings suggest that many respondents perceive ADAS as mitigating the danger associated with higher alcohol intake, implying that the presence of ADAS may unintentionally lower perceived risk and potentially encourage risk-taking behavior. Both model types reveal heterogeneity in preferences, with a significant association between perceived negative consequences of drink driving and the mitigating effect attributed to ADAS. Policy implications are discussed