Saturation induced coherence loss in coherent backscattering of light

We use coherent backscattering (CBS) of light by cold Strontium atoms to study the mutual coherence of light waves in the multiple scattering regime. As the probe light intensity is increased, the atomic optical transition starts to be saturated. Nonlinearities and inelastic scattering then occur. In our experiment, we observe a strongly reduced enhancement factor of the coherent backscattering cone when the intensity of the probe laser is increased, indicating a partial loss of coherence in multiple scattering

Light transport in cold atoms: the fate of coherent backscattering in the weak localization regime

The recent observation of coherent backscattering (CBS) of light by atoms has emphasized the key role of the velocity spread and of the quantum internal structure of the atoms. Firstly, using highly resonant scatterers imposes very low temperatures of the disordered medium in order to keep the full contrast of the CBS interference. This criterion is usually achieved with standard laser cooling techniques. Secondly, a non trivial internal atomic structure leads to a dramatic decrease of the CBS contrast. Experiments with Rubidium atoms (with a non trivial internal structure) and with Strontium (with the simplest possible internal structure) show this behaviour and confirm theoretical calculations

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis

\ua9 2023, The Author(s). Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model’s AUC was augmented from 67.26% (CI 67.25–67.28%) to 67.67% (CI 67.66–67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes

Tunnelling rates for the nonlinear Wannier-Stark problem

We present a method to numerically compute accurate tunnelling rates for a Bose-Einstein condensate which is described by the nonlinear Gross-Pitaevskii equation. Our method is based on a sophisticated real-time integration of the complex-scaled Gross-Pitaevskii equation, and it is capable of finding the stationary eigenvalues for the Wannier-Stark problem. We show that even weak nonlinearities have significant effects in the vicinity of very sensitive resonant tunnelling peaks, which occur in the rates as a function of the Stark field amplitude. The mean-field interaction induces a broadening and a shift of the peaks, and the latter is explained by analytic perturbation theory

Biomedical and therapeutic applications of biosurfactants

During the last years, several applications of biosurfactants with medical purposes have been reported. Biosurfactants are considered relevant molecules for applications in combating many diseases and as therapeutic agents due to their antibacterial, antifungal and antiviral activities. Furthermore, their role as anti-adhesive agents against several pathogens illustrate their utility as suitable anti-adhesive coating agents for medical insertional materials leading to a reduction of a large number of hospital infections without the use of synthetic drugs and chemicals. Biomedical and therapeutic perspectives of biosurfactants applications are presented and discussed in this chapter

Compact and robust laser system for onboard atom interferometry

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