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Flexible micro-supercapacitors with high-energy-density Ni(OH)<sub>2</sub> nanosheet: A scalable approach for enhanced volumetric performance
No full textInternational audienceMicro-supercapacitors are key for portable, self-powered electronics. Pseudocapacitive transition-metal hydroxides improve energy density but reduce power delivery. Volumetric capacitance is crucial for miniaturized systems with limited volume and surface area. In this work, large area, ultrathin 2D Ni(OH)2 nanosheets were utilized to fabricate a flexible, symmetric interdigitated solid-state micro supercapacitor, demonstrating their potential for advanced energy storage applications. Benefiting from the ultrathin structure, abundant availability of electroactive sites, and the optimized nanosheet utilization driven by planar ion diffusion, the fabricated device demonstrated superior electrochemical performance, even with the use of gel-based electrolyte. The device demonstrated a remarkable volumetric capacitance of 580 F cm−3 at 20 A cm−3 current density with superior cycling stability, maintaining ∼75 % of its initial capacitance after 10,000 charge-discharge cycles. The device achieved a competitive volumetric energy density of 40.3 mWh cm−3, comparable to that of certain micro batteries while maintaining a volumetric power density of 5 W cm−3. Importantly, this exceptional electrochemical performance remained consistent under various bending conditions. These results underscore the significant potential of 2D pseudocapacitive materials for the advancement of wearable and flexible energy storage devices
Customer insights for innovation : A framework and research agenda for marketing
No full textInternational audienceCustomer insights play a critical role in innovation. In recent years, articles studying customer insights for innovation have risen in marketing and other fields such as innovation, strategy, and entrepreneurship. However, the literature on customer insights for innovation grew fragmented and plagued by inconsistent definitions and ambiguity. The literature also lacks a precise classification of different domains of customer insights for innovation. This article offers four key contributions. First, it clearly and consistently defines customer insights for innovation. Second, it proposes a “customer insights process” that describes the activities firms and customer insights intermediaries (e.g., market research agencies) use to generate, disseminate, and apply customer insights for innovation. Third, it offers a synthesis of the knowledge on customer insights for innovation along ten domains of customer insights for innovation: (1) crowdsourcing, (2) co-creating, (3) imagining, (4) observing, (5) testing, (6) intruding, (7) interpreting, (8) organizing, (9) deciding, and (10) tracking. Fourth, the authors qualify and quantify the managerial importance and potential for scholarly research in these domains of customer insights for innovation. They conducted 12 in-depth interviews with executives at market research agencies such as Ipsos, Kantar, Nielsen, IQVIA, and GfK to do so. They surveyed 305 managers working in innovation, marketing, strategy, and customer experience. The article concludes with a research agenda for marketing aimed at igniting knowledge development in high-priority domains for customer insights for innovation.<br /
Est-ce qu'une intervention brève de pleine conscience améliore la performance ? Une étude exploratoire: Intervention brève de pleine conscience chez les coureurs
No full textInternational audienceThe effects of mindfulness-based interventions combined with a running programme on physical performance need further investigation. Studies often proposed a long mindfulness intervention with a low-intensity physical activity. This study aims to investigate the effects on physical performance of a brief mindfulness intervention with a running programme. Sixty-five trained runners were randomised in brief mindfulness or control groups. Intermittent maximum speed, heart rate variability and ratings of perceived exertion were performed at baseline, at 4 weeks and 8 weeks. Fat mass and physical fitness were assessed at baseline and 8 weeks after. A time*group interaction was detected for cardiorespiratory fitness tests (i.e. intermittent maximum speed and 3-min shuttle run tests). Cardiorespiratory fitness stagnated for the mindfulness group whereas it decreased significantly over time in the control group (p = 0.01). No time*group interactions were detected for the other outcomes (p > 0.05). Brief mindfulness intervention might potentially mitigate the fatigue-related performance decrements during the preparatory phase. The cardiorespiratory fitness decrease for the control group could be explained by the high training load during this time of the season. The stagnation in the mindfulness group might be illustrated by the development of some psychological skills.Les effets de la pleine conscience (PC) combinée à un programme de course à pied incluant de hautes intensités manquent de clarté. Les études ont généralement mobilisé des interventions longues de PC combinées avec une activité physique de faible intensité. L'objectif de cette étude était d'examiner les effets d’une intervention brève de PC associée à un programme de course incluant de hautes intensités sur des marqueurs physiques influençant la performance des coureurs à pied. Soixante-cinq coureurs entraînés ont été randomisés soit dans le groupe PC, soit dans le groupe contrôle. La vitesse maximale intermittente (VMI), la variabilité de la fréquence cardiaque et la perception de l'effort ont été évaluées au départ (T0), à 4 semaines (T1) et à 8 semaines (T2). La masse grasse et la condition physique ont été mesurées à T0 et à T2. Une interaction temps*groupe a été observée pour les tests évaluant l'endurance cardiorespiratoire (ECR) (i.e., VMI et le 3 minutes navette). Alors que le niveau d'ECR est resté stable dans le groupe PC, celui-ci a significativement diminué au fil du temps dans le groupe contrôle (p = 0,01). Aucune interaction temps*groupe n’a été détectée pour les autres variables (p > 0,05). L'intégration de la PC dans le quotidien des coureurs pourrait potentiellement atténuer la diminution des performances liée à la fatigue durant la phase préparatoire. La baisse de l'ECR dans le groupe contrôle pourrait être expliquée par l'augmentation progressive de la charge d’entraînement durant cette période de la saison. En revanche, la stagnation observée dans le groupe PC pourrait être illustrée par le développement de certaines habiletés psychologiques
Deep Reinforcement Learning-Based Approaches for Optimizing Healthcare Transportation
No full textInternational audienceRecent advancements in Artificial Intelligence (AI), particularly in Deep Reinforcement Learning (DRL) [2], offer promising alternatives for solving Ambulance Routing Problem (ARP) [3]. DRL enables agents to learn optimal policies directly from interactions with the environment, bypassing the need to re-run algorithms for every instance. In contrast to classical solutionbased methods (heuristics and metaheuristics) [5], DRL is a policy-based approach where, once trained, the agent can generalize to solve new instances without requiring retraining. This characteristic is particularly advantageous for large-scale ARPs, where diverse instances are common and solution speed is critical. Additionally, DRL's potential to handle dynamic problems, such as stochastic demand and travel times, makes it a compelling approach for real-world ARPs.</div
Use of Natural Biomolecules in Animal Feed to Enhance Livestock Reproduction
No full textInternational audienceFeed additives are crucial in livestock production, enhancing performance, health, and reproductive efficiency. Recently, there has been a shift toward natural biomolecules as feed additives, specifically targeting improved reproductive outcomes and sperm quality. This transition arises from concerns about antibiotic misuse, antimicrobial resistance, and consumer preferences for eco-friendly products, along with the superior bioavailability, lower toxicity, and reduced environmental impact of natural biomolecules compared to synthetic alternatives. Collaboration among researchers, veterinarians, nutritionists, and regulators is essential to ensure safe and effective livestock management. The review explores advancements in using vital biomolecules in reproductive processes, including plant-derived bioactives such as phytochemicals and antioxidants. It investigates not only the mechanisms but also the intricate interactions of these compounds with animals' hormonal and physiological systems. Additionally, the review critically assesses challenges and prospects related to incorporating natural biomolecules into livestock practices. The potential benefits include enhanced reproductive efficiency and improved sperm quality. However, successful implementation requires understanding factors like precise dosing, potential interactions, and long-term health impacts. Overall, this comprehensive review highlights recent research, technological strides, and the future potential of integrating natural biomolecules into animal diets
Titre : Intelligence artificielle et lombalgie chronique : une approche multidimensionnelle pour personnaliser les soins de rééducation.
No full textIntroduction:Low back pain, affecting 83% of the French population during their lifetime, represents a major public health issue. For 10% of patients, it becomes chronic, significantly affecting their quality of life. Although programs such as Functional Spine Restoration (RFR®) include educational approaches to deconstruct erroneous beliefs, the medium-term effectiveness remains uncertain. This study would propose to identify the determining factors allowing to maintain the benefits acquired post-rehabilitation.Methodology:This prospective and multicenter study would explore the social and personal factors influencing the effectiveness of care. Interviews, physical assessments and self-questionnaires will be carried out at several times (before, after, and at 4 and 6 months post-program). Patients will be classified into subgroups using Machine Learning tools (Random Forest, XGBoost), allowing to better understand their response to care.Discussion:The analysis would highlight heterogeneity in the response to treatments, emphasizing the need for individualized care. Stratifying patients into "responders" and "non-responders" would allow for more appropriate interventions.Conclusion:The integration of artificial intelligence techniques into the personalization of care could improve the effectiveness of functional rehabilitation programs. These tools would offer the possibility of better targeting interventions according to the individual specificities of patients with chronic low back pain, thus optimizing clinical and therapeutic results.Introduction :La lombalgie, touchant 83 % de la population française au cours de leur vie, représente un enjeu majeur de santé publique. Pour 10 % des patients, elle devient chronique, affectant significativement leur qualité de vie. Bien que des programmes comme la Restauration Fonctionnelle du Rachis (RFR®) incluent des approches éducatives pour déconstruire les croyances erronées, l'efficacité à moyen terme reste incertaine. Cette étude proposerait d'identifier les facteurs déterminants permettant de maintenir les bénéfices acquis post-rééducation.Méthodologie :Cette étude prospective et multicentrique explorerait les facteurs sociaux et personnels influençant l’efficacité des soins. Des entretiens, des bilans physiques et des auto-questionnaires seront réalisés à plusieurs moments (avant, après, et à 4 et 6 mois post-programme). Les patients seront classés en sous-groupes à l’aide d’outils de Machine Learning (Random Forest, XGBoost), permettant de mieux comprendre leur réponse aux soins.Discussion :L'analyse mettrait en évidence une hétérogénéité dans la réponse aux traitements, soulignant la nécessité d'une prise en soin individualisée. La stratification des patients en "répondants" et "non-répondants" permettrait de proposer des interventions mieux adaptées.Conclusion :L'intégration des techniques d’intelligence artificielle dans la personnalisation des soins pourrait améliorer l’efficacité des programmes de rééducation fonctionnelle. Ces outils offriraient la possibilité de mieux cibler les interventions selon les spécificités individuelles des patients atteints de lombalgie chronique, optimisant ainsi les résultats cliniques et thérapeutiques
Directional crack propagation and optimization strategies for multi-hole shaped charge blasting in tunnel construction
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Bi5O7I supported chitosan nanocomposite a robust, highly efficient, and sustainable catalyst for methyl orange pand 4-nitrophenol reduction
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Computationally Intensive Research: Advancing a Role for Secondary Analysis of Qualitative Data
No full textInternational audienceThis paper draws attention to the potential of computational methods in reworking data generated in past qualitative studies. While qualitative inquiries often produce rich data through rigorous and resource-intensive processes, much of this data often remains unused. In this paper, we first make a general case for secondary analysis of qualitative data by discussing its benefits, distinctions, and epistemological aspects. We then argue for opportunities with computationally intensive secondary analysis, highlighting the possibility of drawing on data assemblages spanning multiple contexts and time frames to address cross-contextual and longitudinal research phenomena and questions. We propose a scheme to perform computationally intensive secondary analysis and advance ideas on how this approach can help facilitate the development of innovative research designs. Finally, we enumerate some key challenges and ongoing concerns associated with qualitative data sharing and reuse.</p
