FORTH Institute of Applied and Computational Mathematics

Abstract Extreme nonlinear interactions of THz electromagnetic fields with matter are the next frontier in nonlinear optics. However, reaching this frontier in free space is limited by the existing lack of appropriate powerful THz sources. Here, we experimentally demonstrate that two-color filamentation of femtosecond mid-infrared laser pulses at 3.9 μm allows one to generate ultrashort sub-cycle THz pulses with sub-milijoule energy and THz conversion efficiency of 2.36%, resulting in THz field amplitudes above 100 MV cm −1 . Our numerical simulations predict that the observed THz yield can be significantly upscaled by further optimizing the experimental setup. Finally, in order to demonstrate the strength of our THz source, we show that the generated THz pulses are powerful enough to induce nonlinear cross-phase modulation in electro-optic crystals. Our work paves the way toward free space extreme nonlinear THz optics using affordable table-top laser systems.

We present a unified approach to improved $L^p$ Hardy inequalities in $\mathbf {R}^N$. We consider Hardy potentials that involve either the distance from a point, or the distance from the boundary, or even the intermediate case where the distance is taken from a surface of codimension $1<k<N$. In our main result, we add to the right hand side of the classical Hardy inequality a weighted $L^p$ norm with optimal weight and best constant. We also prove nonhomogeneous improved Hardy inequalities, where the right hand side involves weighted $L^q$ norms, $q \neq p$.

PURPOSE: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. METHODS: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. RESULT: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. CONCLUSION: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. CRITICAL RELEVANCE STATEMENT: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. KEY POINTS: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).

Bathymetry mapping forms the basis of understanding physical, economic, and ecological processes in the vastly biodiverse coastal fringes of our planet which are subjected to constant anthropogenic pressure. Here, we pair recent advances in cloud computing using the geospatial platform of the Google Earth Engine (GEE) with optical remote sensing technology using the open Sentinel-2 archive, obtaining low-cost in situ collected data to develop an empirical preprocessing workflow for estimating satellite-derived bathymetry (SDB). The workflow implements widely used and well-established algorithms, including cloud, atmospheric, and sun glint corrections, image composition and radiometric normalisation to address intra- and inter-image interferences before training, and validation of four SDB algorithms in three sites of the Aegean Sea in the Eastern Mediterranean. Best accuracy values for training and validation were R2 = 0.79, RMSE = 1.39 m, and R2 = 0.9, RMSE = 1.67 m, respectively. The increased accuracy highlights the importance of the radiometric normalisation given spatially independent calibration and validation datasets. Spatial error maps reveal over-prediction over low-reflectance and very shallow seabeds, and under-prediction over high-reflectance (&lt;6 m) and optically deep bottoms (&gt;17 m). We provide access to the developed code, allowing users to map bathymetry by customising the time range based on the field data acquisition dates and the optical conditions of their study area.

BACKGROUND: Careful review of published evidence has led to the postulate that the degree of lumbar lordosis may possibly influence the development and progression of spinal osteoarthritis, just as misalignment does in other joints. Spinal degeneration can ensue from the asymmetrical distribution of loads. The resultant lesions lead to a domino- like breakdown of the normal morphology, degenerative instability and deviation from the correct configuration. The aim of this study is to investigate whether a relationship exists between the sagittal alignment of the lumbar spine, as it is expressed by lordosis, and the presence of radiographic osteoarthritis. METHODS: 112 female subjects, aged 40-72 years, were examined in the Outpatients Department of the Orthopedics' Clinic, University Hospital of Heraklion, Crete. Lumbar radiographs were examined on two separate occasions, independently, by two of the authors for the presence of osteoarthritis. Lordosis was measured from the top of L1 to the bottom of L5 as well as from the top of L1 to the top of S1. Furthermore, the angle between the bottom of L5 to the top of S1 was also measured. RESULTS AND DISCUSSION: 49 women were diagnosed with radiographic osteoarthritis of the lumbar spine, while 63 women had no evidence of osteoarthritis and served as controls. The two groups were matched for age and body build, as it is expressed by BMI. No statistically significant differences were found in the lordotic angles between the two groups CONCLUSIONS: There is no difference in lordosis between those affected with lumbar spine osteoarthritis and those who are disease free. It appears that osteoarthritis is not associated with the degree of lumbar lordosis.

Many physical phenomena and properties of soft matter systems are characterized by an interplay of interactions and processes that span a wide range of length- and time scales. Computer simulation approaches require models, which cover these scales. These are typically multiscale models that combine and link different levels of resolution. In order to reach mesoscopic time- and length scales, necessary to access material properties, coarse-grained models are developed. They are based on microscopic, atomistic descriptions of systems and represent these systems on a coarser, mesoscopic level. While the connection between length scales can be established immediately, the link between the different time scales that takes into account the faster dynamics of the coarser system cannot be obtained directly. In this perspective paper we discuss methods that link the time scales in structure based multiscale models. Concepts which try to rigorously map dynamics of related models are limited to simple model systems, while the challenge in soft matter systems is the multitude of fluctuating energy barriers of comparable height. More pragmatic methods to match time scales are applied successfully to quantitatively understand and predict dynamics of one-component soft matter systems. However, there are still open questions. We point out that the link between the dynamics on different resolution levels can be affected by slight changes of the system, as for different tacticities. Furthermore, in two-component systems the dynamics of the host polymer and of additives are accelerated very differently.

Seagrasses are traversing the epoch of intense anthropogenic impacts that significantly decrease their coverage and invaluable ecosystem services, necessitating accurate and adaptable, global-scale mapping and monitoring solutions. Here, we combine the cloud computing power of Google Earth Engine with the freely available Copernicus Sentinel-2 multispectral image archive, image composition, and machine learning approaches to develop a methodological workflow for large-scale, high spatiotemporal mapping and monitoring of seagrass habitats. The present workflow can be easily tuned to space, time and data input; here, we show its potential, mapping 2510.1 km2 of P. oceanica seagrasses in an area of 40,951 km2 between 0 and 40 m of depth in the Aegean and Ionian Seas (Greek territorial waters) after applying support vector machines to a composite of 1045 Sentinel-2 tiles at 10-m resolution. The overall accuracy of P. oceanica seagrass habitats features an overall accuracy of 72% following validation by an independent field data set to reduce bias. We envision that the introduced flexible, time- and cost-efficient cloud-based chain will provide the crucial seasonal to interannual baseline mapping and monitoring of seagrass ecosystems in global scale, resolving gain and loss trends and assisting coastal conservation, management planning, and ultimately climate change mitigation.

Tunneling of electrons through a potential barrier is fundamental to chemical reactions, electronic transport in semiconductors and superconductors, magnetism, and devices such as terahertz oscillators. Whereas tunneling is typically controlled by electric fields, a completely different approach is to bind electrons into bosonic quasiparticles with a photonic component. Quasiparticles made of such light-matter microcavity polaritons have recently been demonstrated to Bose-condense into superfluids, whereas spatially separated Coulomb-bound electrons and holes possess strong dipole interactions. We use tunneling polaritons to connect these two realms, producing bosonic quasiparticles with static dipole moments. Our resulting three-state system yields dark polaritons analogous to those in atomic systems or optical waveguides, thereby offering new possibilities for electromagnetically induced transparency, room-temperature condensation, and adiabatic photon-to-electron transfer.

We conduct a comprehensive study of the Amorgos, Greece earthquake and tsunami of 1956 July 09, the largest such event in the Aegean Sea in the 20th century. Systematic relocation of the main shock and 34 associated events defines a rupture area measuring 75 40 km. The use of the Preliminary Determination of Focal Mechanism algorithm resolves the longstanding controversy about the focal geometry of the event, yielding a normal faulting mechanism along a plane dipping to the southeast, which expresses extensional tectonics in the back arc behind the Hellenic subduction zone. The seismic moment of 3.9 10 27 dyn cm is the largest measured in the past 100 yr in the Mediterranean Basin.

Hippocampal CA1 pyramidal cells, which receive γ-aminobutyric acid (GABA)ergic input from at least 18 types of presynaptic neuron, express 14 subunits of the pentameric GABA(A) receptor. The relative contribution of any subunit to synaptic and extrasynaptic receptors influences the dynamics of GABA and drug actions. Synaptic receptors mediate phasic GABA-evoked conductance and extrasynaptic receptors contribute to a tonic conductance. We used freeze-fracture replica-immunogold labelling, a sensitive quantitative immunocytochemical method, to detect synaptic and extrasynaptic pools of the alpha1, alpha2 and beta3 subunits. Antibodies to the cytoplasmic loop of the subunits showed immunogold particles concentrated on distinct clusters of intramembrane particles (IMPs) on the cytoplasmic face of the plasma membrane on the somata, dendrites and axon initial segments, with an abrupt decrease in labelling at the edge of the IMP cluster. Neuroligin-2, a GABAergic synapse-specific adhesion molecule, co-labels all beta3 subunit-rich IMP clusters, therefore we considered them synapses. Double-labelling for two subunits showed that virtually all somatic synapses contain the alpha1, alpha2 and beta3 subunits. The extrasynaptic plasma membrane of the somata, dendrites and dendritic spines showed low-density immunolabelling. Synaptic labelling densities on somata for the alpha1, alpha2 and beta3 subunits were 78-132, 94 and 79 times higher than on the extrasynaptic membranes, respectively. As GABAergic synapses occupy 0.72% of the soma surface, the fraction of synaptic labelling was 33-48 (alpha1), 40 (alpha2) and 36 (beta3)% of the total somatic surface immunolabelling. Assuming similar antibody access to all receptors, about 60% of these subunits are in extrasynaptic receptors.

We derive optimal order a posteriori error estimates for time discretizations by both the Crank–Nicolson and the Crank–Nicolson–Galerkin methods for linear and nonlinear parabolic equations. We examine both smooth and rough initial data. Our basic tool for deriving a posteriori estimates are second-order Crank–Nicolson reconstructions of the piecewise linear approximate solutions. These functions satisfy two fundamental properties: (i) they are explicitly computable and thus their difference to the numerical solution is controlled a posteriori, and (ii) they lead to optimal order residuals as well as to appropriate pointwise representations of the error equation of the same form as the underlying evolution equation. The resulting estimators are shown to be of optimal order by deriving upper and lower bounds for them depending only on the discretization parameters and the data of our problem. As a consequence we provide alternative proofs for known a priori rates of convergence for the Crank–Nicolson method.

Abstract Shallow nearshore coastal waters provide a wealth of societal, economic, and ecosystem services, yet their topographic structure is poorly mapped due to a reliance upon expensive and time intensive methods. Space‐borne bathymetric mapping has helped address these issues, but has remained largely dependent upon in situ measurements. Here we fuse ICESat‐2 lidar data with Sentinel‐2 optical imagery, within the Google Earth Engine cloud platform, to create openly available spatially continuous high‐resolution bathymetric maps at regional‐to‐national scales in Florida, Crete and Bermuda. ICESat‐2 bathymetric classified photons are used to train three Satellite Derived Bathymetry (SDB) methods, including Lyzenga, Stumpf, and Support Vector Regression algorithms. For each study site the Lyzenga algorithm yielded the lowest RMSE (approx. 10%–15%) when compared with validation data. We demonstrate a means of using ICESat‐2 for both model calibration and validation, thus cementing a pathway for fully space‐borne estimates of nearshore bathymetry in shallow, clear water environments.

For many years, Protected Areas (PA) have been an important tool for conserving nature. Recently, also societal aspects have been introduced into PA management via the introduction of the Ecosystem Services (ES) approach. This review discusses the historical background of PAs, PA management, and the ES approach. We then discuss the relevance and applicability of the ES approach for PA management, including the different definitions of ES, different classification methods, and the ways in which ES are measured. We conclude that there are still major challenges ahead in using the ES approach in PA management and so recommendations are given on the way in which the ES approach should be integrated into PA management.

Diphenylalanine (FF) is a very common peptide with many potential applications, both biological and technological, due to a large number of different nanostructures which it attains. The current work concerns a detailed study of the self-assembled structures of FF in two different solvents, an aqueous (H2O) and an organic (CH3OH) through simulations and experiments. Detailed atomistic molecular dynamics (MD) simulations of FF in both solvents have been performed, using an explicit solvent model. The self-assembling propensity of FF in water is obvious while in methanol a very weak self-assembling propensity is observed. We studied and compared structural properties of FF in the two different solvents and a comparison with a system of dialanine (AA) in the corresponding solvents was also performed. In addition, temperature-dependence studies were carried out. Finally, the simulation predictions were compared to new experimental data, which were produced in the framework of the present work. A very good qualitative agreement between simulation and experimental observations was found.

We examine the microstructural and mechanical changes which occur during oscillatory shear flow and reformation after flow cessation of an intermediate volume fraction colloidal gel using rheometry and Brownian Dynamics (BD) simulations. A model depletion colloid-polymer mixture is used, comprising a hard sphere colloidal suspension with the addition of non-adsorbing linear polymer chains. The results reveal three distinct regimes depending on the strain amplitude of oscillatory shear. Large shear strain amplitudes fully break the structure which results in a more homogenous and stronger gel after flow cessation. Intermediate strain amplitudes densify the clusters and lead to highly heterogeneous and weak gels. Shearing the gel to even lower strain amplitudes creates a less heterogonous stronger solid. These three regimes of shearing are connected to the microscopic shear-induced structural heterogeneity. A comparison with steady shear flow reveals that the latter does not produce structural heterogeneities as large as oscillatory shear. Therefore oscillatory shear is a much more efficient way of tuning the mechanical properties of colloidal gels. Moreover, colloidal gels presheared at large strain amplitudes exhibit a distinct nonlinear response characterized largely by a single yielding process while in those presheared at lower rates a two-step yielding process is promoted due to the creation of highly heterogeneous structures.

An important challenge in the field of three-dimensional ultrafast laser processing is to achieve permanent modifications in the bulk of silicon and narrow-gap materials. Recent attempts by increasing the energy of infrared ultrashort pulses have simply failed. Here, we establish that it is because focusing with a maximum numerical aperture of about 1.5 with conventional schemes does not allow overcoming strong nonlinear and plasma effects in the pre-focal region. We circumvent this limitation by exploiting solid-immersion focusing, in analogy to techniques applied in advanced microscopy and lithography. By creating the conditions for an interaction with an extreme numerical aperture near 3 in a perfect spherical sample, repeatable femtosecond optical breakdown and controllable refractive index modifications are achieved inside silicon. This opens the door to the direct writing of three-dimensional monolithic devices for silicon photonics. It also provides perspectives for new strong-field physics and warm-dense-matter plasma experiments.Ultrafast laser processing is a versatile three-dimensional photonic structuring method but it has been limited to wide band gap materials like glasses. Here, Chanal et al. demonstrate direct refractive-index modification in the bulk of silicon by extreme localization of the energy deposition.

Abstract Room temperature magnetic skyrmions in magnetic multilayers are considered as information carriers for future spintronic applications. Currently, a detailed understanding of the skyrmion stabilization mechanisms is still lacking in these systems. To gain more insight, it is first and foremost essential to determine the full real‐space spin configuration. Here, two advanced X‐ray techniques are applied, based on magnetic circular dichroism, to investigate the spin textures of skyrmions in [Ta/CoFeB/MgO] n multilayers. First, by using ptychography, a high‐resolution diffraction imaging technique, the 2D out‐of‐plane spin profile of skyrmions with a spatial resolution of 10 nm is determined. Second, by performing circular dichroism in resonant elastic X‐ray scattering, it is demonstrated that the chirality of the magnetic structure undergoes a depth‐dependent evolution. This suggests that the skyrmion structure is a complex 3D structure rather than an identical planar texture throughout the layer stack. The analyses of the spin textures confirm the theoretical predictions that the dipole–dipole interactions together with the external magnetic field play an important role in stabilizing sub‐100 nm diameter skyrmions and the hybrid structure of the skyrmion domain wall. This combined X‐ray‐based approach opens the door for in‐depth studies of magnetic skyrmion systems, which allows for precise engineering of optimized skyrmion heterostructures.

Multiscale modeling of polymers exchanges information between coarse and fine representations of molecules to capture material properties over a wide range of spatial and temporal scales. Restoring details at a finer scale requires us to generate information following embedded physics and statistics of the models at two different levels of description. Techniques designed to address this persistent challenge balance among accuracy, efficiency, and general applicability. In this work, we present an image-based approach for structural backmapping from coarse-grained to atomistic models with cis-1,4 polyisoprene melts as an illustrative example. Through machine learning, we train conditional generative adversarial networks on the correspondence between configurations at the levels considered. The trained model is subsequently applied to provide predictions of atomistic structures from the input coarse-grained configurations. The effect of different data representation schemes on training and prediction quality is examined. Our proposed backmapping approach shows remarkable efficiency and transferability over different molecular weights in the melt based on training sets constructed from oligomeric compounds. We anticipate that this versatile backmapping approach can be readily extended to other complex systems to provide high-fidelity initial configurations with minimal human intervention.

We design and demonstrate what we called shape-preserving “optical pin beams” (OPBs) that possess stable wavefronts against diffraction and ambient turbulence during free-space long distance propagation. Theoretically, we show that a laser beam passing through properly assembled phase elements paired with opposite transverse wavevectors can morph quickly into a stable optical field, exhibiting “self-focusing” dynamics during propagation without optical nonlinearity. The overall shape of such OPBs remains invariant, while their width can in principle be inversely proportional to the propagation distance, in contradistinction to conventional Bessel beams and radially symmetric Airy beams. Experimentally, utilizing a single photoetched mask, we demonstrate efficient generation and robust propagation of the OPB through atmospheric turbulence beyond kilometer distances. We envisage exciting opportunities arising from such OPBs, especially when propagation through turbulent environments is unavoidable.

High spatial and temporal resolution satellite remote sensing estimates are the silver bullet for monitoring of coastal marine areas globally. From 2000, when the first commercial satellite platforms appeared, offering high spatial resolution data, the mapping of coastal habitats and the extraction of bathymetric information have been possible at local scales. Since then, several platforms have offered such data, although not at high temporal resolution, making the selection of suitable images challenging, especially in areas with high cloud coverage. PlanetScope CubeSats appear to cover this gap by providing their relevant imagery. The current study is the first that examines the suitability of them for the calculation of the Satellite-derived Bathymetry. The availability of daily data allows the selection of the most qualitatively suitable images within the desired timeframe. The application of an empirical method of spaceborne bathymetry estimation provides promising results, with depth errors that fit to the requirements of the International Hydrographic Organization at the Category Zone of Confidence for the inclusion of these data in navigation maps. While this is a pilot study in a small area, more studies in areas with diverse water types are required for solid conclusions on the requirements and limitations of such approaches in coastal bathymetry estimations.