Using Beatboxing for Creative Rehabilitation After Laryngectomy:Experiences From a Public Engagement Project

Laryngectomy is the surgical removal of the larynx (voice box), usually performed in patients with advanced stages of throat cancer. The psychosocial impact of losing the voice is significant, affecting a person’s professional and social life in a devastating way, and a proportion of this patient group subsequently must overcome depression (22–30%) and social isolation (40%). The profound changes to anatomical structures involved in voicing and articulation, as a result of surgery, radiotherapy or chemotherapy (separately or in combination with one another), introduce challenges faced in speech rehabilitation and voice production that complicate social reintegration and quality of life. After laryngectomy, breathing, voicing, articulation and tongue movement are major components in restoring communication. Regular exercise of the chest, neck and oropharyngeal muscles, in particular, is important in controlling these components and keeping the involved structures supple. It is, however, a difficult task for a speech therapist to keep the patient engaged and motivated to practice these exercises. We have adopted a multidisciplinary approach to explore the use of basic beatboxing techniques to create a wide variety of exercises that are seen as fun and interactive and that maximize the use of the structures important in alaryngeal phonation. We herein report on our empirical work in developing patients’ skills, particularly relating to voiced and unvoiced consonants to improve intelligibility. In collaboration with a professional beatboxing performer, we produced instructional online video materials to support patients working on their own and/or with support from speech therapists. Although the present paper is focused predominantly on introducing the structure of the conducted workshops, the rationale for their design and the final public engagement performance, we also include feedback from participants to commence the critical discourse about whether this type of activity could lead to systematic underlying research and robustly assessed interventions in the future. Based on this exploratory work, we conclude that the innovative approach that we employed was found to be engaging, useful, informative and motivating. We conclude by offering our views regarding the limitations of our work and the implications for future empirical research

Accompagner la démarche de management stratégique de l’exploitation agricole

Développer la démarche de management stratégique dans les exploitations agricoles est une façon d’améliorer leurs performances dans le contexte actuel de l’agriculture. Les auteurs proposent un itinéraire méthodologique qui vise à accompagner les exploitants agricoles dans la construction de stratégies et dans leur traduction opérationnelle. Structuré en trois étapes, il aide à organiser la réflexion autour de la stratégie, puis à la formaliser, pour ensuite la piloter grâce à un tableau de bord stratégique. Le lien entre ces trois étapes est assuré par la construction d’une carte causale. Cet itinéraire a été construit dans le cadre du programme de recherche-action PerfEA avec des établissements publics locaux d’enseignement agricole. L’itinéraire s’adresse à tout type d’exploitation agricole et sa mise en œuvre nécessite la présence d’un conseiller.Strategic management is a relevant approach to support farmers in managing their farm and in coping with the current agricultural challenges. In this article we propose a methodological route which aims at enabling farmers to design their strategy and to implement them. The route is organized along three steps: it helps to organize the strategic thinking; to formalize the strategy by defining priorities and strategic lines; to draw up a strategic monitoring plan (the balanced scorecard). The link between the different steps is provided by the design of a causal mapping. This methodological route was built within an action research project entitled PerfEA (Global Performance for Farm) including farms belonging to public training schools. It suits all kind of farms and requires an agricultural adviser to accompany farmers in the design process of the strategy and its implementation

Overview on the management of radioactive waste from fusion facilities: ITER, demonstration machines and power plants

In the absence of official standards and guidelines for nuclear fusion plants, fusion designers adopted, as far as possible, well-established standards for fission-based nuclear power plants (NPPs). This often implies interpretation and/or extrapolation, due to differences in structures, systems and components, materials, safety mitigation systems, risks, etc. This approach could result in the consideration of overconservative measures that might lead to an increase in cost and complexity with limited or negligible improvements. One important topic is the generation of radioactive waste in fusion power plants. Fusion waste is significantly different to fission NPP waste, i.e. the quantity of fusion waste is much larger. However, it mostly comprises low-level waste (LLW) and intermediate level waste (ILW). Notably, the waste does not contain many long-lived isotopes, mainly tritium and other activation isotopes but no-transuranic elements. An important benefit of fusion employing reduced-activation materials is the lower decay heat removal and rapid radioactivity decay overall. The dominant fusion wastes are primarily composed of structural materials, such as different types of steel, including reduced activation ferritic martensitic steels, such as EUROFER97 and F82H, AISI 316L, bainitic, and JK2LB. The relevant long-lived radioisotopes come from alloying elements, such as niobium, molybdenum, nickel, carbon, nitrogen, copper and aluminum and also from uncontrolled impurities (of the same elements, but also, e.g. of potassium and cobalt). After irradiation, these isotopes might preclude disposal in LLW repositories. Fusion power should be able to avoid creating high-level waste, while the volume of fusion ILW and LLW will be significant, both in terms of pure volume and volume per unit of electricity produced. Thus, efforts to recycle and clear are essential to support fusion deployment, reclaim resources (through less ore mining) and minimize the radwaste burden for future generations

From data extraction to analysis: a comparative study of ELISE capabilities in scientific literature

The exponential growth of scientific literature presents challenges for pharmaceutical, biotechnological, and Medtech industries, particularly in regulatory documentation, clinical research, and systematic reviews. Ensuring accurate data extraction, literature synthesis, and compliance with industry standards require AI tools that not only streamline workflows but also uphold scientific rigor. This study evaluates the performance of AI tools designed for bibliographic review, data extraction, and scientific synthesis, assessing their impact on decision-making, regulatory compliance, and research productivity. The AI tools assessed include general-purpose models like ChatGPT and specialized solutions such as ELISE (Elevated LIfe SciencEs), SciSpace/Typeset, Humata, and Epsilon. The evaluation is based on three main criteria: Extraction, Comprehension, and Analysis with Compliance and Traceability (ECACT) as additional dimensions. Human experts established reference benchmarks, while AI Evaluator models ensure objective performance measurement. The study introduces the ECACT score, a structured metric assessing AI reliability in scientific literature analysis, regulatory reporting and clinical documentation. Results demonstrate that ELISE consistently outperforms other AI tools, excelling in precise data extraction, deep contextual comprehension, and advanced content analysis. ELISE’s ability to generate traceable, well-reasoned insights makes it particularly well-suited for high-stakes applications such as regulatory affairs, clinical trials, and medical documentation, where accuracy, transparency, and compliance are paramount. Unlike other AI tools, ELISE provides expert-level reasoning and explainability, ensuring AI-generated insights align with industry best practices. ChatGPT is efficient in data retrieval but lacks precision in complex analysis, limiting its use in high-stakes decision-making. Epsilon, Humata, and SciSpace/Typeset exhibit moderate performance, with variability affecting their reliability in critical applications. In conclusion, while AI tools such as ELISE enhance literature review, regulatory writing, and clinical data interpretation, human oversight remains essential to validate AI outputs and ensure compliance with scientific and regulatory standards. For pharmaceutical, biotechnological, and Medtech industries, AI integration must strike a balance between automation and expert supervision to maintain data integrity, transparency, and regulatory adherence

Le codage morphologique chez l'apprenti lecteur

De nombreuses études mettent en avant l’importance du codage phonologique dans le début de l’apprentissage de la lecture. La conscience phonologique est un prédicteur important des capacités ultérieures en lecture (Muter, 1998). Cependant, depuis quelques années, la littérature fait ressortir une autre conscience prédictive des capacités de lecture : la conscience morphologique. Très tôt, dès la deuxième année de lecture, l’enfant est capable de segmenter un mot en sa racine et son affixe (Casalis et Louis-Alexandre, 2000). Chez l’adulte, les unités morphologiques sont traitées de manière orthographique. Or, en raison de l’importance du codage phonologique chez le lecteur débutant, une reconnaissance orthographique des morphèmes est peu probable. Un traitement phonologique des unités morphologiques est donc postulé. C’est ici le sens de cette recherche : connaître la nature du traitement des unités morphologiques chez l’apprenti lecteur