Learning Through an Expanded Arts Program

Robust carbon cycle science and effective carbon market governance depend on accurate monitoring, transparent modelling and credible representation of climate–economic feedbacks. Integrated Assessment Models (IAMs) such as RICE provide a long-standing framework for linking carbon emissions, climate dynamics and economic development and are widely used to inform mitigation pathways, carbon pricing and international climate policy. However, traditional IAMs rely on hand-calibrated parameters, simplified damage functions and fixed ethical assumptions, limiting their ability to integrate observational data, quantify uncertainty and support evidence-based carbon management. We build on recent advances in machine learning for climate policy and introduce RICE-N-JAX, a fully differentiable implementation of the multi-region RICE-N model (Zhang et al., 2025). RICE-N extends classical IAMs with multi-agent reinforcement learning to model strategic interactions and international climate negotiations. Our JAX-based reimplementation makes the entire climate–economic simulation fast and differentiable, including carbon emissions, climate response, production, trade, mitigation decisions and negotiation dynamics. Differentiability enables a new class of hybrid, data-driven climate–economic models. Our current research focuses on two key directions. First, we develop non-parametric hybrid damage functions in which the traditional analytical damage formulation is replaced by neural or spline-based surrogates trained on empirical and scenario data. This allows the damage–temperature relationship to be learned directly from data. Second, we perform inverse modelling of ethical and behavioural parameters, such as regional risk aversion, time preferences and mitigation bias, by calibrating the model against emissions, GDP and temperature trajectories from the Shared Socioeconomic Pathways (SSPs). This enables the recovery of latent normative assumptions embedded in scenario narratives and provides a data-informed basis for policy analysis. Finally, differentiability supports gradient-based calibration, uncertainty quantification, and sensitivity analysis of carbon price trajectories, mitigation pathways, and long-term climate impacts. We demonstrate a proof-of-concept end-to-end calibration of climate damage functions and show how parameter uncertainty propagates into future economic and emissions outcomes. By bridging process-based climate–economic theory with hybrid, knowledge-guided machine learning, RICE-N-JAX provides a foundation for fast and data-driven carbon-cycle modelling. The framework supports policy-relevant applications ranging from carbon pricing and climate clubs to carbon market design, illustrating how hybrid ML can strengthen the scientific basis of carbon management and climate mitigation.

Secure boot is a fundamental mechanism for establishing a hardware-rooted chain of trust in modern computing systems. While formal verification using interactive theorem provers like Rocq offers strong correctness guarantees, existing approaches are often tightly coupled to specific hardware configurations and cryptographic algorithms, making them brittle and difficult to reuse when system components change. In this work, we present a flexible and modular framework for formally verifying secure boot processes in Rocq. Our approach introduces a three-layer abstraction model-Feature, Axiom, and Theorem-that decouples high-level security properties from lowlevel implementation details. We abstract critical components such as storage media and cryptographic primitives (e.g., encryption, signatures, hash functions) as interfaces with welldefined operators and axiomatic correctness properties. All highlevel proofs are conducted based on these axioms, without depending on concrete implementations. When specific algorithms or hardware are chosen, the axioms become proof obligations to be verified locally. This separation ensures that changes in implementation-such as switching cryptographic primitives or storage types-do not invalidate existing proofs, enabling significant proof reuse. We demonstrate the applicability of our framework in modeling a realistic secure boot chain. Our work lays the foundation for scalable and maintainable formal verification of trust-sensitive system initialization processes.

ABSTRACT The untimely loss of a loved one is an excruciating ordeal. Renowned Victorian Scottish writer George MacDonald was obliged to face the recurring early deaths of family members all his lifetime. Drawing from the background of Victorian literature and his working experience in church, he forges a reconciliation with reality and realizes his self-preservation through religion. His masterpiece, At the Back of the North Wind, is the reflection of his life sufferings, inner world, and way of reconciliation with reality. By examining the characterization of Diamond and North Wind, two leading characters in the book, and the employment of his unique literary technique, this article aims to reveal his motivation in portraying the protagonist of the book—Diamond, a poor little boy living in London, and conclude MacDonald’s means of self-preservation, i.e., interpretation of early death: those who pass away at a young age are angels from heaven. After fulfilling their earthly missions, they return to a better realm they inherently belong to—Heaven. Hence, earthly life is only a fragment of human beings’ existence. MacDonald’s coming to terms with bereavement while facing death holds practical significance today, especially for the people suffering from the loss of loved ones during the COVID-19 pandemic.

Georges Bigot (1860-1927) est un peintre français japonisant qui a vécu dix-sept ans au Japon. Il rentre en France en 1899. En 1906, il est nommé « peintre du ministère des Colonies ». Ce statut lui permet de réaliser les images du Japon à son gré, quand les représentations de ce pays sont réduites au registre guerrier, en particulier dans les illustrations des journaux au tournant du siècle. Dès 1906, il commence à proposer ses dessins extrême-orientaux au public via l’imagerie d’Épinal. Le département des Estampes et de la photographie de la Bibliothèque nationale de France conserve quinze images japonaises de Bigot, où apparaît le « Japon sympathique ». Elles reflètent son expérience du pays et il s’y distingue de ses prédécesseurs, qui exposaient l’illusion du Japon rêvé ou la réalité militariste du Japon moderne. À travers l’image d’Épinal, Bigot annihile la dichotomie entre Japon fantasmé et Japon réel.

Report on HIKR design

EURAKNOS visuals and specifications to define the future vision for the e-KRP

Abstract This chapter is focused on understanding professional identity formation. Professional identity as “nurse” develops when a nurse reflects and internalizes the core values of the nursing profession. As students engage in continued personal and professional development while gaining new APN experiences in the clinical setting, their professional identity gains a stronger commitment to APN nursing. APN role transition involves role socialization aspects including the influence of experienced professional role models, immersion in a community of practice, clinical encounters with patients, the code of nursing ethics in the country, the scope of APN practice in the country, and support of the role from key stakeholders. Understanding self and the personal factors of role transition will guide professional identity formation. The last part of this chapter is focused on understanding barriers and facilitators that can impact successful role transition and/or professional identity formation including macro-level (perceived legal, regulatory, and economic barriers); meso-level (local institutional and/or community issues); micro-level (day-to-day practice environment); and self-placed personal transition stressors and facilitators. This chapter provides multiple interactive and introspective activities to aid the student seeking a structured process of APN professional identity and role transition.KeywordsAPN role transitionProfessional identityPersonal developmentSelf-conceptProfessional barriers

Analytical Research Infrastructures of Europe (ARIE) join forces to face threats such as COVID-19 and potential future crises. With this paper, the ARIE enhanced its cross-border, multidisciplinary collaboration to offer Europe a strong and valid weapon against the present COVID-19 challenge and other potential viral and microbial threats.