Articles 2024

Résumé: Purpose: This study aims at linking subtle changes of fixational eye movements (FEM) in controls and in patients with foveal drusen using adaptive optics retinal imaging in order to find anatomo-functional markers for pre-symptomatic age-related macular degeneration (AMD). Methods: We recruited 7 young controls, 4 older controls, and 16 patients with presymptomatic AMD with foveal drusen from the Silversight Cohort. A high-speed research-grade adaptive optics flood illumination ophthalmoscope (AO-FIO) was used for monocular retinal tracking of fixational eye movements. The system allows for sub-arcminute resolution, and high-speed and distortion-free imaging of the foveal area. Foveal drusen position and size were documented using gaze-dependent imaging on a clinical-grade AO-FIO. Results: FEM were measured with high precision (RMS-S2S = 0.0015 degrees on human eyes) and small foveal drusen (median diameter = 60 µm) were detected with high contrast imaging. Microsaccade amplitude, drift diffusion coefficient, and ISOline area (ISOA) were significantly larger for patients with foveal drusen compared with controls. Among the drusen participants, microsaccade amplitude was correlated to drusen eccentricity from the center of the fovea. Conclusions: A novel high-speed high-precision retinal tracking technique allowed for the characterization of FEM at the microscopic level. Foveal drusen altered fixation stability, resulting in compensatory FEM changes. Particularly, drusen at the foveolar level seemed to have a stronger impact on microsaccade amplitudes and ISOA. The unexpected anatomo-functional link between small foveal drusen and fixation stability opens up a new perspective of detecting oculomotor signatures of eye diseases at the presymptomatic stage.

Résumé: The location of the mobility edge is a long-standing problem in Anderson localization. In this Letter, we show that the effective confining potential introduced in the localization landscape (LL) theory predicts the onset of delocalization in 3D tight-binding models in a large part of the energy-disorder diagram. Near the edge of the spectrum, the eigenstates are confined inside the basins of the LL-based potential. The delocalization transition corresponds to the progressive merging of these basins, resulting in the percolation of this classically allowed region throughout the system. This approach, shown to be valid both in the cases of uniform and binary disorders despite their very different phase diagrams, allows us to reinterpret the Anderson transition in the tight-binding model: the mobility edge appears to be composed of two parts, one being understood as a percolation transition.

Résumé: In a previous paper [Phys. Rev. A 105, 042205 (2022)10.1103/PhysRevA.105.042205], the distribution of resonance poles in the complex plane of the wave number k associated to the multiple scattering of a quantum particle in a random point field was numerically discovered. This distribution presented two distinctive structures: a set of peaks at small k when the wavelength is larger than the interscatterer distance and a band almost parallel to the real axis at larger k. In this paper, a theoretical study based on wave transport theory is proposed to explain the origin of these structures and to predict their distribution in the complex k plane. First, it is shown that the peaks at small k can be understood using the effective wave equation for the average wave function over the disorder. Then, that the band at large k can be described by the Bethe-Salpeter equation for the square modulus of the wave function. This study is supported by careful comparisons with numerical simulations.

Résumé: The linear and nonlinear optical properties of metallic nanoparticles have attracted considerable experimental and theoretical research interest. To date, most researchers have focused primarily on exploiting their plasmon excitation enhanced near-field and far-field responses and related applications in sensing, imaging, energy harvesting, conversion, and storage. Among numerous plasmonic structures, nanoparticle dimers, being a structurally simple and easy-to-prepare system, hold significant importance in the field of nanoplasmonics. In highly symmetric plasmonic nanostructures, although the odd-order optical nonlinearity of the near-surface region will be improved because of the enhanced near-fields, even-order nonlinear processes such as second-harmonic generation (SHG) will still be quenched and thus optically forbidden. Under this premise, it is imperative to introduce structural symmetry breaking to realize plasmon-enhanced even-order optical nonlinearity. Here, we fabricate a series of nanoparticle dimers each composed of two gold nanospheres with different diameters and subsequently investigate their structural asymmetry dependent linear and nonlinear optical properties. We find that the SHG intensities of gold nanosphere dimers are significantly enhanced by structural asymmetry under off-resonance excitation while the plasmonic near-field enhancement mainly affects SHG under on-resonance excitation. Our results reveal that symmetry breaking will play an indispensable role when designing novel coupled plasmonic nanostructures with enhanced nonlinear optical properties.

Résumé: Purpose: Putative microglia were recently detected using adaptive optics ophthalmoscopy in healthy eyes. Here we evaluate the use of nonconfocal adaptive optics scanning light ophthalmoscopy (AOSLO) for quantifying the morphology and motility of presumed microglia and other immune cells in eyes with retinal inflammation from uveitis and healthy eyes. Design: Observational exploratory study. Participants: Twelve participants were imaged, including 8 healthy participants and 4 posterior uveitis patients recruited from the clinic of 1 of the authors (M.H.E.). Methods: The Pittsburgh AOSLO imaging system was used with a custom-designed 7-fiber optical fiber bundle for simultaneous confocal and nonconfocal multioffset detection. The inner retina was imaged at several locations at multiple timepoints in healthy participants and uveitis patients to generate time-lapse images. Main Outcome Measures: Microglia and macrophages were manually segmented from nonconfocal AOSLO images, and their morphological characteristics quantified (including soma size, diameter, and circularity). Cell soma motion was quantified across time for periods of up to 30 minutes and their speeds were calculated by measuring their displacement over time. Results: A spectrum of cell morphologies was detected in healthy eyes from circular amoeboid cells to elongated cells with visible processes, resembling activated and ramified microglia, respectively. Average soma diameter was 16.1 ± 0.9 μm. Cell movement was slow in healthy eyes (0.02 μm/sec on average), but macrophage-like cells moved rapidly in some uveitis patients (up to 3 μm/sec). In an eye with infectious uveitis, many macrophage-like cells were detected; during treatment their quantity and motility decreased as vision improved. Conclusions: In vivo adaptive optics ophthalmoscopy offers promise as a potentially powerful tool for detecting and monitoring inflammation and response to treatment at a cellular level in the living eye. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Résumé: The cocktail party effect is the capability to focus one's auditory attention on particular audio sources while ignoring other audio sources. We propose an experimental strategy to reproduce this ability by designing a time-dependent metasurface composed of independent active mirrors. Each active mirror is a programmable acoustic unit cell capable of hearing, computing, and re-emitting acoustic signals: each of them acts as a convolution filter. The proper configuration of the metasurface temporal filters allows one to establish an acoustic communication link between groups of individuals immersed in the noisy environment: a multiple-user multiple-input, multiple-output acoustic system is built.

Résumé: Very distinct strategies can be deployed to recognize and characterize an unknown environment or a shape. A recent and promising approach, especially in robotics, is to reduce the complexity of the exploratory units to a minimum. Here, we show that this frugal strategy can be taken to the extreme by exploiting the power of statistical geometry and introducing different invariant features. We show that an elementary robot devoid of any orientation or location system, exploring randomly, can access global information about an environment such as the values of the explored area and perimeter. The explored shapes are of arbitrary geometry and may even nonconnected. From a dictionary, this most simple robot can thus identify various shapes such as famous monuments and even read a text.

Résumé: Reconfigurable intelligent metasurfaces have been proposed as an efficient solution for improving wireless telecommunication systems in multiple-scattering or reverberating media. Concurrently, topology optimization has been successfully used as an inverse-design technique in many fields, and particularly in electromagnetics. In this work, we apply a gradient-based topology optimization for tuning the binary elements of a metasurface for a focusing goal in a complex environment. First, the metasurface unit cells are approximated as point sources and, then, the optimization problem is formulated. Afterwards, the proposed method is applied to find the optimal parameter sets for three distinct environments of increasing complexity, and the resulting focus for each case is demonstrated via numerical simulations. The combination of a reverberating cavity and a metasurface inside the latter is very powerful since everything can be solved analytically for focusing outside the cavity.

Résumé: Physical examination of the thorax is key to the clinical diagnosis of respiratory diseases. Among other examination techniques, palpation evaluates the transmission of high-frequency vibrations produced by vocalizations (tactile fremitus), which helps the physicians to identify abnormalities within the respiratory system. We propose the use of an airborne ultrasound surface motion camera (AUSMC) to quantitatively map the vibrations induced by subject vocalization. This approach could make the examination of vocal fremitus quantifiable, reproducible, and archivable. Massive data collection of vocal fremitus could allow using artificial intelligence algorithms to isolate vibration patterns that could help disease identification. Until now, in contrast, the interpretation of vocal fremitus has been subject to the physician’s experience and remains subjective. In the present work, we demonstrate the capabilities of the AUSMC to measure vocal fremitus thoracic vibration maps on 77 healthy volunteers. We have observed a spatial dependence of vibration maps on vocalization frequency. We observed that the left lung generates fewer surface vibrations than the right one, which was expected according to their respective dimensions. We also discuss the implications of our findings.

Résumé: Emotion is a complicated state of mind, which normally reflects human perceptions and attitudes. Proper recognition of emotional states and its quality plays crucial role for the detection of critical diseases and subsequent treatment procedures. Generally, multi-lead, complicated Electroencephalogram (EEG) based analysis predominate the characterization of emotion detection. Nowadays, user-friendly, rich-cardiac-information and wearable characteristics of the photoplethysmogram (PPG) signal are also being used to identify the emotional states. However, a majority of the reported emotion detection techniques mostly uses PPG signal in multimodality approach. In this paper, a simple methodology is proposed to identify multiple emotional states via the analysis of the PPG signal alone. Normally, emotion induced alteration in the heart rate causes variation in the blood ejection rate and a subsequent deviation in the balance of the systolic and the diastolic phases. Consequently, a specific time-domain characteristic is identified to quantify such imbalance and its variability is then used as a feature to discriminate between the five most prominent emotional states via a threshold-based classification technique. The algorithm presents superior performance while evaluated on the PPG data collected from the standard DEAP dataset with an average detection accuracy of 97.78%. Compared to existing literatures, the superior results establish the effectiveness of the proposed algorithm for the detection of multiple emotional states using PPG signal only. Moreover, the use of a single PPG feature and the application of a simple threshold-based classification technique also justify its promises for implementation in real-life, healthcare applications.

Résumé: Localisation microscopy of individual molecules allows one to bypass the diffraction limit, revealing cellular organisation on a nanometric scale. This method, which relies on spatial analysis of the signal emitted by molecules, is often limited to the observation of biological objects at shallow depths, or with very few aberrations. The introduction of a temporal parameter into the localisation process through a time-modulated excitation was recently proposed to address these limitations. This method, called ModLoc, is demonstrated here with an alternative flexible strategy. In this implementation, to encode the time-modulated excitation a digital micromirror device (DMD) is used in combination with a fast demodulation approach, and provides a twofold enhancement in localisation precision. Layout: Nowadays, we can use an optical microscope to observe how proteins are organised in 3D within a cell at the nanoscale. By carefully controlling the emission of molecules in both space and time, we can overcome the limitations set by the diffraction limit. This allows us to pinpoint the exact location of molecules more precisely. However, the usual spatial analysis method limits observations to shallow depths or causing low distortion of optical waves. To overcome these restrictions, a recent approach introduces a temporal element to the localisation process. This involves changing the illumination over time to enhance the precision of localisation. This method, known as ModLoc, is showcased here using a flexible and alternative strategy. In this setup, a matrix of micrometric mirrors, working together with a fast demodulation optical module, is used to encode and decode the time-modulated information. This combination results in a twofold improvement in localisation precision.

Résumé: Upon impact, the free surface of a solid metal may eject a cloud of fast and fine particles. Photon Doppler Velocimetry (PDV) is one of the optical diagnostics used to characterize these ejecta. Although the technique provides a direct way to estimate the particle velocities in the single scattering regime, it has been shown that multiple scattering cannot be neglected in real ejecta. Here, we derive a model for PDV measurements starting from the first principles of wave scattering. We establish rigorously the relationship between the specific intensity and the measured signal, as well as the Radiative Transport Equation (RTE) that describes the evolution of the specific intensity upon scattering and absorption in dynamic ejecta, including the effects of inelastic scattering and inhomogeneities in the optical properties. We also establish rigorously the connection between the Monte Carlo scheme used for numerical simulations and the solution to the RTE. Using numerical simulations, we demonstrate the crucial contribution of multiple scattering to PDV spectrograms as well as the effect of statistical inhomogeneities in particle size distribution. These results could substantially impact the analysis of ejecta by PDV.

Résumé: To produce sounds, we adjust the tension of our vocal folds to shape their properties and control the pitch. This efficient mechanism offers inspiration for designing reconfigurable materials and adaptable soft robots. However, understanding how flexible structures respond to a significant static strain is not straightforward. This complexity also limits the precision of medical imaging when applied to tensioned organs like muscles, tendons, ligaments and blood vessels among others. In this article, we experimentally and theoretically explore the dynamics of a soft strip subject to a substantial static extension, up to 180%. Our observations reveal a few intriguing effects, such as the resilience of certain vibrational modes to a static deformation. These observations are supported by a model based on the incremental displacement theory. This has promising practical implications for characterizing soft materials but also for scenarios where external actions can be used to tune properties.

Résumé: Nowadays, automated analysis of the electrocardiogram (ECG) signal is a popular choice to facilitates easy and expert-independent detection of lethal cardiovascular diseases (CVDs). Although, a majority of the state-of-the-art algorithms are found to be lagging due to the use of complicated methodologies, limited dataset, high feature dimension, feature selection or intense classification techniques. In this research an original, easy-to-use ECG based methodology is proposed for completely automated identification of multiple types of critical CVDs. Primarily, after preprocessing the algorithm uses a simplified technique for exact detection of ECG fiducial points. Then, based on detected fiducial points, some well interpretable and prominent ECG time domain features are efficiently extracted and a binary feature matrix has been derived using those features from different leads. Finally, a distinctive score is evaluated from the binary feature matrix calculating the sum of weighted feature value and only by utilizing the score,discrimination between the various types of CVDs is highly detectable. Proficiency of the algorithm is widely evaluated on the 12-lead ECG signal data collected from Physikalisch-Technische-Bundesanstalt (PTB) and PTB-XL database. The algorithm presents promising outcome with average accuracy, sensitivity and specificity of 99.43%, 98.27% and 99.59%, respectively. Evidently, the algorithm is capable enough and efficient as well in comparison with other reported techniques till date. Moreover, the use of a unique score derived from the binary matrix ascertains the exact detection of multiple cardiac abnormalities and the superior classification accuracy makes the algorithm promising for personal computerized health monitoring applications.

Résumé: 3D ceramic architectures are captivating geometrical features with an immense demand in optics. In this work, an additive manufacturing (AM) approach for printing alkaline-earth perovskite 3D microarchitectures is developed. The approach enables custom-made photoresists suited for two-photon lithography, permitting the production of alkaline-earth perovskite (BaZrO3, CaZrO3, and SrZrO3) 3D structures shaped in the form of octet-truss lattices, gyroids, or inspired architectures like sodalite zeolite, and C60 buckyballs with micrometric and nanometric feature sizes. Alkaline-earth perovskite morphological, structural, and chemical characteristics are studied. The optical properties of such perovskite architectures are investigated using cathodoluminescence and wide-field photoluminescence emission to estimate the lifetime rate and defects in BaZrO3, CaZrO3, and SrZrO3. From a broad perspective, this AM methodology facilitates the production of 3D-structured mixed oxides. These findings are the first steps toward dimensionally refined high-refractive-index ceramics for micro-optics and other terrains like (photo/electro)catalysis.

Résumé: In vitro cellular models denote a crucial part of drug discovery programs as they aid in identifying successful drug candidates based on their initial efficacy and potency. While tremendous headway has been achieved in improving 2D and 3D culture techniques, there is still a need for physiologically relevant systems that can mimic or alter cellular responses without the addition of external biochemical stimuli. A way forward to alter cellular responses is using physical cues, like 3D topographical inorganic substrates, to differentiate macrophage-like cells. Herein, protein secretion and gene expression markers for various macrophage subsets cultivated on a 3D topographical substrate are investigated. The results show that macrophages differentiate into anti-inflammatory M2-type macrophages, secreting increased IL-10 levels compared to the controls. Remarkably, these macrophage cells are differentiated into the M2d subset, making up the main component of tumour-associated macrophages (TAMs), as measured by upregulated Il-10 and Vegf mRNA. M2d subset differentiation is attributed to the topographical substrates with 3D fractal-like geometries arrayed over the surface, else primarily achieved by tumour-associated factors in vivo. From a broad perspective, this work paves the way for implementing 3D topographical inorganic surfaces for drug discovery programs, harnessing the advantages of in vitro assays without external stimulation and allowing the rapid characterisation of therapeutic modalities in physiologically relevant environments.

Résumé: A contactless method based on acousto-elastic transmission matrix analysis is proposed to recover the modal properties of weakly damped mechanical structures. The matrix is acquired using eight loudspeakers and a laser vibrometer probing hundreds of points. The matrix analysis is particularly interesting in case of overlapping modes. The proposed measurement set-up and associated data processing using the Singular Value Decomposition are applied to two symmetric samples, a gear and two monobloc impellers. Further analysis are performed taking advantage of their particular modal behavior, common to many rotationally symmetric structures. The method also enables to clearly identify the effect of damages on the modal organization. Additionally, the setup can also be used to excite specific patterns on the elastic structures. Finally, the acousto-elastic results are compared to the ones obtained with a classical impact hammer and high resolution algorithms.