Grenoble Alpes University

A 33T cryogen-free superconducting magnet (33TCSM) project is now in progress at HFLSM, IMR, Tohoku University. The 33T-CSM consists of a f 68mm- 19 T REBCO (HTS) insert and a f 320mm-14 T CuNb/Nb3Sn and NbTi Rutherford (LTS) magnets. The 33T-CSM system has been installed and tested without the HTS insert in March 2024. The LTS outsert magnet consists of three CuNb/Nb3Sn Rutherford cable coils and two NbTi Rutherford cable coils with an epoxy impregnation. It can generate 14 T in a 320 mm bore with 879 A. This winding makes use of advanced high strength CuNb/ Nb3Sn strands specifically developed for the 33T-CSM project, enabling high stress design with about 275 MPa in the Nb3Sn coil at 14 T. The 19 T-HTS insert is designed based on the robust REBCO coil technology we proposed in previous works. For the cooling system, a 9W GM/JT cryocooler is used for the LTS coils, four 4K-GM cryocoolers cool the REBCO coils (1.5 W each at 4.2 K) and two single-stage cryocoolers are used for the radiation shield and current leads. Helium circulation with compressors ensure the thermal connection between the coils and the cryocoolers. The initial cooling is about 7.3 days from room temperature. The test of the 14 T LTS magnet was successfully completed up to 839 A with the nominal maximum electromagnetic stress of 275 MPa after one training quench.

A 33 T cryogen-free superconducting magnet (33 T-CSM) is under development. The 33 T-CSM consists of a REBCO insert coil and Nb3Sn/NbTi outsert coils. The REBCO insert coil is designed to generate 19 T in the external field of 14 T. The REBCO insert coil is composed of stacked 64 single pancake coils wound with two bundled REBCO tapes. The inner and outer diameters of the REBCO insert coil are 68 mm and 295 mm, respectively. The REBCO coil is impregnated with epoxy resin for conduction cooling. To prevent delamination of the superconducting layer by thermal stress, the fluorine-coated polyimide tape is co-wound with REBCO tapes and to prevent degradation of superconductivity by electromagnetic stress, reinforcing tape is also co-wound. According to 2D-FEM, it is shown that the circumferential strain ϵθ under applying electromagnetic force is 0.29%. The results of 2D-FEM also suggest that stress concentration occurs at the connection between the coil and the bus bar, and at the widthwise end of the REBCO tape. In this paper, the basic design of the insert coil and the results of FEM analysis will be described.

This chapter explores the design and assembly of nanostructured systems with inspiration from biology. Here we consider the biological inspiration as not the approach typically adopted, which is to construct synthetic materials inspired from nature. In contrast, the approach described in this chapter utilizes biological components in the assembly of smart nanostructured systems. We adapt the term “biological engineering” to describe a discipline that embodies this approach. Indeed, in 1970, this term was introduced formally with the intention to integrate engineering with biological systems to move beyond single disciplinary areas such as medicine, agriculture, or fermentation engineering. In this chapter, we further refine the discipline of “biological engineering” to be one that utilizes biological proteins, molecules, and lipids in combination with synthetic materials to assemble smart nanostructural systems. We illustrate this discipline with the assembly of nanostructured systems that are targeted for applications such as diagnostic, therapeutic, biofuel cell, or tissue enhancement/replacement in the body.

Is there anything more to discover? This is a question that scientists, clinicians, and engineers ask of themselves during their pursuit of the ways to explain the function of natural systems. Just when you think it is safe to turn off the computer, there is yet another publication of a new twist to an explanation for a physical, chemical, or biological function. The new twists are usually found at smaller and smaller observational scales, and hence the appetite for scientists, clinicians, and engineers to apply nanoscale measurements to their investigations. When applied to biomedical problems, this need for nanoscaled measurements is generally considered in the realm of nanobiotechnology, where the function of the cell membrane and membrane-incorporated proteins are important. Such studies have been previously described in the context of the nanobiotechnology of biomimetic membranes [1].

The phospholipid membrane is one of biology’s most pervasive structures and represents an ideal scaffold for a host of nanotechnology applications. Whether as a vehicle for the biological engineering of biomimetic technologies or for designing therapies to interface with the cell, a phospholipid membrane can provide the necessary molecular-level control of membrane-anchored proteins, glycopeptides, and glycolipids applications [1]. An elegant published example of a lipid membrane structure that illustrates this concept is the incorporation of two proteins that have a combined function to produce ATP [2]. This structure includes the proteins bacteriorhodopsin and the F0F1-ATPase complex. The structure is illustrated in Fig. 4.1.

The purpose of this book is to draw biomimetic membrane technology into one of the central themes of nanobiotechnology for the development of novel medical diagnostic and therapeutic devices and hence to elucidate the significant role that biomimetic membrane technology has for the growth of the field of nanomedicine. There is a dichotomy of whether the starting point for advances in nanobiotechnology and nanomedicine lies in the realm of fundamental scientists to first seek knowledge in the basic functions of molecules that comprise biomimetic membranes or in the realm of clinicians and engineers who first seek to observe and characterize defined medical problems and needs. In those scenarios, the fundamental scientist will have the subsequent task to find a biomedical application of such fundamental knowledge and understanding. The clinician or engineer will have the subsequent task to find, or indeed reverse-engineer, a targeted understanding of the functions and principles that underlie the defined problem. This question of the preeminence of fundamental or applied research will continue to be the source of debate amongst scientists, clinicians, and engineers.

In this chapter, we will explore the practical aspects of biomimetic membrane technology in nanomedicine. This focus on practical aspects will include a description of a refined definition of the discipline of biological engineering. This refined discipline of biological engineering includes the aspect of human factors concurrently with technical factors, particularly when we consider the therapeutic and diagnostic needs for nanomedicine. Such needs rely upon medical devices, either implanted or in contact with the body of a patient. The enhancements to such medical devices will require them to be “smart,” in the sense that there will need to be an improved understanding and construction of such devices to provide for long-term two-way (duplex) communication of biological molecules and signals to and from the device to the body. Concurrently, the patient needs to be accepting of such innovative “smart” devices that will have the capability to function autonomously. That is, the patient needs to understand and provide permission for the “smart” device to function autonomously. Here we return to the roadmap presented in Chap. 2 (Fig. 2.14) and the six questions that are at the heart of the “medical device pull” to utilize skills of materials and engineering disciplines to design the “symbio-bot” that is required to solve the clinical needs. In this chapter, major questions to be answered at the various stages of this roadmap to “pull” the medical device are:

Aims We sought to characterize adverse events and deaths associated with the use of psychoactive substances in children and adolescents. Methods Two French Addictovigilance databases were analysed: spontaneous reports and deaths over the period 2016–2021, in subjects aged 10–<18 years. An unsupervised classification was implemented on consumption data (medications or nondrug substances [NDS]) to identify subject clusters. Results A total of 1544 spontaneous reports were analysed, comprising mainly boys (65.6%), aged on average 16 ± 1 years. Four clusters were identified: The cannabinoids users cluster (n = 597) was typified by the use of cannabis or/and synthetic cannabinoids (95.1%), with psychiatric (67.7%) and digestive disorders (16.7%). The medications/solvents/cannabidiol users cluster (n = 699) was distinguished by the use of medications or NDS including nitrous oxide/cannabidiol, with mainly neurological disorders (46.5%). The polydrug users cluster (n = 177) includes polyusers (98.3%) of NDS and medications. These users mainly have substance use disorders (63.8%). The psychotropic medications users cluster (n = 71) was characterized by the use of psychotropic medications. This cluster appeared to be correlated with psychiatric and organic disorders. The death database recorded 44 deaths, mainly in boys (61.4%) aged over 15 years. The main substances involved in the deaths were NDS (70.5%) and methadone. In 68.2% of cases, a single substance was responsible for the death. Conclusion The adverse events related to the abuse of psychoactive substances identified in children and adolescents and the emerging signals show the need for increased surveillance and the implementation of prevention campaigns adapted to each group of consumers.

This work identifies a novel antibacterial mechanism that targets the cell wall of the human pathogen Streptococcus pneumoniae. Unlike conventional cell-wall targeting antibiotics, which inhibit the natural cross-linking of the...

Passive seismic methods hold valuable information about the physical properties of the subsurface, enabling continuous, non‐intrusive monitoring of groundwater dynamics. This study introduces a novel methodology for monitoring near‐surface seismic attenuation variations using repetitive seismic noise sources. Our approach employs a single‐station technique to quantify seismic attenuation variations by evaluating the linear relationship between the frequency and spectrum amplitude variations. We applied this method in the Lyon water catchment area, utilizing train tremors as a continuous and stable seismic source. The case study demonstrates that seismic attenuation variations correlate strongly with environmental factors such as rainfall and significant changes in the water table due to a flood event. This methodology offers an effective and practical means to continuously monitor the subsurface seismic attenuation using opportune noise sources, providing valuable insights into groundwater dynamics and subsurface processes.

In the context of the non-destructive testing of pieces produced through additive manufacturing, this research focuses on investigating porosity using images obtained via scanning photothermal radiometry from Ti–6Al–4V samples. Variations in the material’s porosity as a function of the electron beam melting process parameters are revealed through photothermal images. The measured thermal signature is influenced by changes in the material’s apparent thermal diffusivity, which is affected by the presence of pores within the bulk material.

Insular agri-food systems face significant challenges due to their exposure to external shocks via trade dependencies, geographic isolation, and constrained land and natural resources. This study proposes a novel socio-metabolic analytical framework and applies it to investigate how external shocks propagate within the animal product supply systems (APSS) of La Reunion Island, a French overseas department. By conceptualizing APSS as a metabolic network, we analyze characteristics that influence three vulnerability factors: exposure, sensitivity, and incapacity to cope. To analyze shock propagation dynamics, this paper introduces the distinction between cascading and domino effects: cascading effects trace the sectors and stages impacted, while domino effects highlight how the nature of disruptions evolves as they spread. Using a mixed-methods approach, we map flow dynamics and identify critical interaction nodes susceptible to convey shock propagation clusters. Drawing on stakeholder insights, our empirical findings from disruptions during the COVID-19 pandemic, the Russo-Ukrainian war, and other events reveal the interplay of different cascading and domino effects influencing the availability, accessibility and stability of animal-based products. Our findings underscore a paradox: while import-dependent local APSS are highly exposed and present vulnerabilities to external shocks, they also buffer impacts on the food supply by ensuring some degree of autonomy. The results offer insights into the systemic vulnerabilities of insular agri-food systems and provide a framework for analyzing shock propagation in complex food supply networks.

Study objective The introduction of new medical devices into care units, or their replacement by new devices, is not always accompanied by implementation strategies that enable healthcare professionals to use them safely. Simulation is a relevant tool for reproducing critical care clinical situations without danger for the patients and providing training support. The aim of the study was to assess a simulation-based implementation method to accompany and reduce the risks associated with the deployment of a new invasive medical device in critical care units. Design Prospective mono-centric cross-over study. Setting In our hospital, the type of Invasive Arterial Blood Pressure Sensors (IABPS) for blood pressure (BP) monitoring and arterial sampling has been completely replaced by a new one with numerous differences. No specific training had been planned. Participants 66 intensive care unit (ICU) nurses from three ICUs with a total number of 39 beds were involved. Interventions The scenario and evaluation grid were designed by multi-disciplinary teams who received in-depth training on the new IABPS from the laboratory and the institution’s equipment specialists. Nurses in group A (GA) (n=33) started by using the IABPS on a simulation scenario and then received explanations on differences. Nurses in group B (GB) (n=33) received explanations and then used the IABPS on the simulation scenario. Nurses in GA and GB all had individual feedback on their errors at the end. Next, they listed the most important information they would give to a colleague if they had a few minutes to train him or her. They also completed an anonymous self-questionnaire to assess their satisfaction with the training and with the new IABPS. Main results The mean number of errors in the act of measuring BP and taking biological samples was statistically higher for GA, demonstrating the relevance of offering a training programme to support the deployment of a new device. The mean times to BP measurement and to collection were similar. Recommendations for asepsis of the sampling site were not followed. Recurrent errors were related to the ergonomics of the IABPS. Caregivers (n=55 questionnaires) appreciated the training and the new IABPS. Conclusions Simulation can be useful for both providing a training model and identifying the situations that would require dedicated training support. The simulation tool provided training and context to nurses before they use the new IAPBS in clinical practice. Simulation training has also led to a better understanding of the most common errors. Because of new IABPS widespread use, it was all the more important to prevent usage errors.

We focus on Bayesian inverse problems with Gaussian likelihood, linear forward model, and priors that can be formulated as a Gaussian mixture. Such a mixture is expressed as an integral of Gaussian density functions weighted by a mixing density over the mixing variables. Within this framework, the corresponding posterior distribution also takes the form of a Gaussian mixture, and we derive the closed-form expression for its posterior mixing density. To sample from the Gaussian posterior mixture, we propose to use the marginal then conditional sampler, which comprises two steps: First, we sample the mixing variables from the posterior mixing density, then we sample the variables of interest from Gaussian densities conditioned on the sampled mixing variables. However, the posterior mixing density is relatively difficult to sample from, especially in high dimensions. Therefore, we propose to replace the posterior mixing density by a dimension-reduced approximation, and we provide a bound in the Hellinger distance for the resulting approximate posterior. We apply the proposed approach to a posterior with Laplace prior, where we introduce two dimension-reduced approximations for the posterior mixing density. Our numerical experiments indicate that samples generated via the proposed approximations have very low correlation and are close to the exact posterior.

The symptoms of long COVID are well-documented. However, the long-term effects beyond 2 years remain poorly understood due to a lack of data. This systematic review and meta-analysis examined the prevalence of persistent symptoms in COVID-19 survivors 3 years following initial SARS-CoV-2 infection. PubMed, MEDLINE (Ovid), CENTRAL, Web of Science, Scopus, and Embase were searched from inception of the databases up to July 20, 2024, by two independent researchers for articles reporting on the prevalence of persistent symptoms 3 years' post-infection of people who survived COVID-19 infection. We employed a random-effect model for the pooled analysis, and the meta-analytical effect size was prevalence for the applicable end-points, I2 statistics, and quality assessment of included studies using the Newcastle-Ottawa Scale. Eleven articles were included after the literature search yielded 223 potentially relevant articles. We found that among patients with long COVID, fatigue, sleep disturbances, and dyspnea were the most common symptoms. Pooled analysis showed that the proportion of individuals experiencing at least one persistent symptom 3 years post-COVID-19 is 20% (95% confidence interval [CI]: 8–43). The prevalence of persistent symptoms was dyspnea (12%; 95% CI: 10–15), fatigue (11%; 95% CI: 6–20), insomnia (11%; 95% CI: 2–37), loss of smell (7%; 95% CI: 5–8), loss of taste (7%; 95% CI: 3–16), and anxiety (6%; 95% CI: 1–32). Prevalence of other findings include impaired diffusion capacity (42%; 95% CI: 34–50) and impaired forced expiratory volume in 1 s (10%; 95% CI: 8–12). Our findings confirm the persistence of unresolved symptoms 3 years post-COVID-19 infection, with implications for future research, healthcare policy, and patient care.

The assessment of acute non‐procedural pain in term neonates in maternity wards is challenging due to the difficulty in selecting an appropriate scale and the time‐consuming nature of the process. This can lead to inadequate neonatal pain management. To validate the EValuation ENfant DOuLeur (EVENDOL) pain scale for acute non‐procedural pain in term neonates in maternity units by comparing it with the Echelle Douleur et Inconfort du Nouveau‐né (EDIN) used as a reference. We hypothesized that EVENDOL would be equivalent to EDIN in assessing acute non‐procedural neonatal pain, with better appearance. Prospective multicentric non‐interventional open study. Term neonates over 37 weeks' gestation in the delivery room and postnatal care units, with or without acute non‐procedural pain, before and after analgesia. Cronbach's α coefficient, intraclass correlation (ICC), and correlation between EVENDOL and EDIN scores, documented by the researchers and the caregivers at rest and mobilization, before and after oral paracetamol, were measured. Ninety‐one neonates were included: 48 (51%) had pain and 43 (47%) had no pain. Before analgesia, the Cronbach coefficient was above 0.80, the ICC (25th–75th interquartile ranges [IQ]) were 0.84 (0.77–0.89) and 0.90 (0.85–0.93) at rest and mobilization, respectively. Seventeen patients received oral acetaminophen and were re‐assessed. Psychometric values remained good after analgesia (Cronbach coefficient above 0.80, ICC [IQ]: 0.65 [0.26–0.85] and 0.76 [0.45–0.91]) at rest and mobilization, respectively. The feasibility and ease of use were better for EVENDOL for researchers and caregivers. EVENDOL is suitable for the assessment of acute non‐procedural neonatal pain for term neonates in the maternity wards. Trial Registration: ClinicalTrials.gov identifier: NCT02819076, registered in June 2016 as EVENDOL scale validation for at term newborn

Output feedback control design for a class of reaction-diffusion equations with Dirichlet anti-collocated sensing and actuation subject to in-domain disturbances is addressed. Within this setting, we design a finite-dimensional dynamic output feedback controller ensuring closed-loop exponential stability and input-output stability with an explicit estimate of the input-output gain. The approach is based on the spectral decomposition of the open-loop infinite-dimensional system and on the use of a suitable Lyapunov functional candidate. Sufficient conditions in the form of matrix inequalities are given to ensure closed-loop stability. These conditions are shown to be always feasible and are employed to devise an optimal controller design algorithm based on the solutions to some linear matrix inequalities.