Ref HAL: hal-04523215_v1
Ref Arxiv: 2403.02279
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We compare three available models of graphene conductivity: a non-local Kubo model, a local model derived by Fialkovsky, and finally a non-local Quantum Field Theory based (QFT-b) model. The first two models are extensively used in the nanophotonic community. All these models are not ab-initio since they contain phenomenological parameters (like chemical potential and/or mass gap parameters), and are supposed to provide coherent results since they are derived from the same starting Hamiltonian. While we confirm that the local model is a proper limit of the non-local Kubo model, we find some inconsistencies in the QFT-b model as derived and used in literature. In particular, differently from the Kubo model, the QFT-b model does not satisfy the required Gauge invariance, and as a consequence it shows a plasma-like behavior for the interband transversal conductivity at low frequencies instead of the expected behavior (an almost constant conductivity as a function of frequency $\omega$ with a gap for frequencies $\hbar\omega < \sqrt{(\hbar v_{F}q)^{2} + 4m^{2}}$). The inconsistencies of QFT-b model predictions are due to a non-correct regularization-scheme which allows for the gauge invariance violation. We show how to correctly regularize the QFT-b model in order to satisfy the gauge invariance and, once also losses are correctly included, we show that the Kubo and QFT-b model exactly coincide. Our finding can be of relevant interest for both theory predictions and experimental tests in both the nanophotonic and Casimir effect communities.

Ref HAL: hal-04517451_v1
DOI: 10.1001/jamanetworkopen.2023.52844
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Importance : Pain is a common out-of-hospital symptom among patients, and opioids are often prescribed. Research suggests that overprescribing for acute traumatic pain is still prevalent, even when limits restricting opioid prescriptions have been implemented. Ketamine hydrochloride is an alternative to opioids in adults with out-of-hospital traumatic pain. Objective : To assess the noninferiority of intravenous ketamine compared with intravenous morphine sulfate to provide pain relief in adults with out-of-hospital traumatic pain. Design, Setting, and Participants : The Intravenous Subdissociative-Dose Ketamine Versus Morphine for Prehospital Analgesia (KETAMORPH) study was a multicenter, single-blind, noninferiority randomized clinical trial comparing ketamine hydrochloride (20 mg, followed by 10 mg every 5 minutes) with morphine sulfate (2 or 3 mg every 5 minutes) in adult patients with out-of-hospital trauma and a verbal pain score equal to or greater than 5. Enrollment occurred from November 23, 2017, to November 26, 2022, in 11 French out-of-hospital emergency medical units. Interventions : Patients were randomly assigned to ketamine (n = 128) or morphine (n = 123). Main Outcomes and Measures : The primary outcome was the between-group difference in mean change in verbal rating scale pain scores measured from the time before administration of the study drug to 30 minutes later. A noninferiority margin of 1.3 was chosen. Results : A total of 251 patients were randomized (median age, 51 [IQR, 34-69] years; 111 women [44.9%] and 140 men [55.1%] among the 247 with data available) and were included in the intention-to-treat population. The mean pain score change was −3.7 (95% CI, −4.2 to −3.2) in the ketamine group compared with −3.8 (95% CI, −4.2 to −3.4) in the morphine group. The difference in mean pain score change was 0.1 (95% CI, −0.7 to 0.9) points. There were no clinically meaningful differences for vital signs between the 2 groups. The intravenous morphine group had 19 of 113 (16.8% [95% CI, 10.4%-25.0%]) adverse effects reported (most commonly nausea [12 of 113 (10.6%)]) compared with 49 of 120 (40.8% [95% CI, 32.0%-49.6%]) in the ketamine group (most commonly emergence phenomenon [24 of 120 (20.0%)]). No adverse events required intervention. Conclusions and Relevance : In the KETAMORPH study of patients with out-of-hospital traumatic pain, the use of intravenous ketamine compared with morphine showed noninferiority for pain reduction. In the ongoing opioid crisis, ketamine administered alone is an alternative to opioids in adults with out-of-hospital traumatic pain. Trial Registration : ClinicalTrials.gov Identifier: NCT03236805

Ref HAL: hal-04514863_v1
Ref Arxiv: 2310.20252
DOI: 10.1103/PhysRevB.109.064205
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We develop a machine learning model, which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic heterogeneity across a broad range of temperatures and time scales with excellent accuracy and transferability. We use the network transferability to predict dynamic heterogeneity down to the experimental glass transition temperature Tg, where structural relaxation cannot be analyzed using molecular dynamics simulations. The results indicate that the strength, the geometry, and the characteristic length scale of the dynamic heterogeneity evolve much more slowly near Tg compared to their evolution at higher temperatures. Our results show that machine learning techniques can provide physical insights on the nature of the glass transition that cannot be gained using conventional simulation techniques.

DOI: 10.1088/1361-6528/ad2f1c
Résumé:

We consider the system of two parallel sheets of graphene which are moving with relative parallel velocity $\vec{v}$ and calculate the Casimir energy by using the scattering approach. We analyze in detail the normal (perpendicular to the planes) Casimir force for two systems—graphene/graphene and ideal metal/graphene. In the non-relativistic case v ≪ vF, the relative correction to the Casimir energy $({{ \mathcal E }}_{v}-{{ \mathcal E }}_{0})/{{ \mathcal E }}_{0}$ is proportional to the (v/c)2 (the maximum value is 0.0033 for the gapeless case and v = vF) for the first system, and it is zero up to the Fermi velocity v = vF for system ideal metal/graphene.

Ref HAL: hal-04501077_v1
PMID 38424155
DOI: 10.1038/s41598-024-55186-3
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Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for example, to assess plant health and quality and monitor physiological traits or diseases. However, detecting functional and degraded plant tissues in-vivo without harming the plant is extremely challenging. New solutions are needed in ligneous and perennial species, for which the sustainability of plantations is crucial. To tackle this challenge, we developed a novel approach based on multimodal 3D imaging and artificial intelligence-based image processing that allowed a non-destructive diagnosis of inner tissues in living plants. The method was successfully applied to the grapevine ( Vitis vinifera L.). Vineyard’s sustainability is threatened by trunk diseases, while the sanitary status of vines cannot be ascertained without injuring the plants. By combining MRI and X-ray CT 3D imaging with an automatic voxel classification, we could discriminate intact, degraded, and white rot tissues with a mean global accuracy of over 91%. Each imaging modality contribution to tissue detection was evaluated, and we identified quantitative structural and physiological markers characterizing wood degradation steps. The combined study of inner tissue distribution versus external foliar symptom history demonstrated that white rot and intact tissue contents are key measurements in evaluating vines’ sanitary status. We finally proposed a model for an accurate trunk disease diagnosis in grapevine. This work opens new routes for precision agriculture and in-situ monitoring of tissue quality and plant health across plant species.

Commentaires: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. The extension of the Trainable Segmentation plugin is open-source, and available as a fork of Trainable Segmentation on GitHub https://github.com/Rocsg/Trainable_Segmentation/tree/Hyperweka.

Ref HAL: hal-04489381_v1
DOI: 10.1016/j.commatsci.2024.112848
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DOI: 10.1103/PhysRevB.109.125105
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Based on a tight-binding model for the electron system, we investigate the transfer of energy, momentum, and angular momentum mediated by electromagnetic fields among buckminsterfullerene ( C 60 ) and graphene nanostrips. Our nonequilibrium Green's function approach enables calculations away from local thermal equilibrium where the fluctuation-dissipation theorem breaks down. For example, the forces between C 60 and current-carrying nanostrips are predicted. It is found that the presence of current enhances the van der Waals attractive forces. For two current-carrying graphene strips rotated at some angle, the fluctuational force and torque are much stronger at the nanoscale compared to that of the static Biot-Savart law.