Multiscale Integration Research Articles

Multiscale pore‐network representation of heterogeneous carbonate rocks

AbstractA multiscale network integration approach introduced by Jiang et al. (2013) is used to generate a representative pore‐network for a carbonate rock with a pore size distribution across several orders of magnitude. We predict the macroscopic flow parameters of the rock utilising (i) 3‐D images captured by X‐ray computed microtomography and (ii) pore‐network flow simulations. To capture the multiscale pore size distribution of the rock, we imaged four different rock samples at different resolutions and integrated the data to produce a pore‐network model that combines information at several length‐scales that cannot be recovered from a single tomographic image. A workflow for selection of the number and length‐scale of the required input networks for the network integration process, as well as fine tuning the model parameters is presented. Mercury injection capillary‐pressure data were used to evaluate independently the multiscale networks. We explore single‐scale, two‐scale, and three‐scale network models and discuss their representativeness by comparing simulated capillary‐pressure versus saturation curves with laboratory measurements. We demonstrate that for carbonate rocks with wide pore size distributions, it may be required to integrate networks extracted from two or three discrete tomographic data sets in order to simulate macroscopic flow parameters.

A uniformly accurate (UA) multiscale time integrator Fourier pseudospectral method for the Klein–Gordon–Schrödinger equations in the nonrelativistic limit regime

A multiscale time integrator Fourier pseudospectral (MTI-FP) method is proposed and analyzed for solving the Klein-Gordon-Schr\"{o}dinger (KGS) equations in the nonrelativistic limit regime with a dimensionless parameter $0<\varepsilon\le1$ which is inversely proportional to the speed of light. In fact, the solution to the KGS equations propagates waves with wavelength at $O(\varepsilon^2)$ and $O(1)$ in time and space, respectively, when $0<\varepsilon\ll 1$, which brings significantly numerical burdens in practical computation. The MTI-FP method is designed by adapting a multiscale decomposition by frequency to the solution at each time step and applying the Fourier pseudospectral discretization and exponential wave integrators for spatial and temporal derivatives, respectively. We rigorously establish two independent error bounds for the MTI-FP at $O(\tau^2/\varepsilon^2+h^{m_0})$ and $O(\varepsilon^2+h^{m_0})$ for $\varepsilon\in(0,1]$ with $\tau$ time step size, $h$ mesh size and $m_0\ge 4$ an integer depending on the regularity of the solution, which imply that the MTI-FP converges uniformly and optimally in space with exponential convergence rate if the solution is smooth, and uniformly in time with linear convergence rate at $O(\tau)$ for $\varepsilon\in(0,1]$ and optimally with quadratic convergence rate at $O(\tau^2)$ in the regime when either $\varepsilon=O(1)$ or $0<\varepsilon\le \tau$. Thus the meshing strategy requirement (or $\varepsilon$-scalability) of the MTI-FP is $\tau=O(1)$ and $h=O(1)$ for $0<\varepsilon\ll 1$, which is significantly better than classical methods. Numerical results demonstrate that our error bounds are optimal and sharp. Finally, the MTI-FP method is applied to study numerically convergence rates of the KGS equations to the limiting models in the nonrelativistic limit regime.

Hydrologic Impacts of Thawing Permafrost—A Review

Core Ideas This review synthesizes the state of the science in permafrost hydrology. Observed and projected hydrologic impacts of permafrost thaw are discussed. Characterization, modeling, and knowledge gaps of permafrost systems are identified. Translating results between multiple scales in cold regions presents a challenge. Opportunities for advancement in the field of permafrost hydrology are described. Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process‐based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.

ChemInform Abstract: Multiscale and Multicomponent Layer by Layer Assembly of Optical Thin Films Triggered by Electrochemical Coupling Reactions of N‐Alkylcarbazoles

AbstractReview: [46 refs.

Conserved roles for cytoskeletal components in determining laterality.

Consistently-biased left-right (LR) patterning is required for the proper placement of organs including the heart and viscera. The LR axis is especially fascinating as an example of multi-scale pattern formation, since here chiral events at the subcellular level are integrated and amplified into asymmetric transcriptional cascades and ultimately into the anatomical patterning of the entire body. In contrast to the other two body axes, there is considerable controversy about the earliest mechanisms of embryonic laterality. Many molecular components of asymmetry have not been widely tested among phyla with diverse bodyplans, and it is unknown whether parallel (redundant) pathways may exist that could reverse abnormal asymmetry states at specific checkpoints in development. To address conservation of the early steps of LR patterning, we used the Xenopus laevis (frog) embryo to functionally test a number of protein targets known to direct asymmetry in plants, fruit fly, and rodent. Using the same reagents that randomize asymmetry in Arabidopsis, Drosophila, and mouse embryos, we show that manipulation of the microtubule and actin cytoskeleton immediately post-fertilization, but not later, results in laterality defects in Xenopus embryos. Moreover, we observed organ-specific randomization effects and a striking dissociation of organ situs from effects on the expression of left side control genes, which parallel data from Drosophila and mouse. Remarkably, some early manipulations that disrupt laterality of transcriptional asymmetry determinants can be subsequently "rescued" by the embryo, resulting in normal organ situs. These data reveal the existence of novel corrective mechanisms, demonstrate that asymmetric expression of Nodal is not a definitive marker of laterality, and suggest the existence of amplification pathways that connect early cytoskeletal processes to control of organ situs bypassing Nodal. Counter to alternative models of symmetry breaking during neurulation (via ciliary structures absent in many phyla), our data suggest a widely-conserved role for the cytoskeleton in regulating left-right axis formation immediately after fertilization of the egg. The novel mechanisms that rescue organ situs, even after incorrect expression of genes previously considered to be left-side master regulators, suggest LR patterning as a new context in which to explore multi-scale redundancy and integration of patterning from the subcellular structure to the entire bodyplan.

Multiscale and multicomponent layer by layer assembly of optical thin films triggered by electrochemical coupling reactions of N -alkylcarbazoles

Abstract The integration of multiscale and multicomponent of molecules and nanoparticles into thin films for applications requires the abilities of controlled their processing and assembly, which has been an great challenge because of the difficulty in manipulating the various materials such as small molecules, complexes, polymers, and inorganic nanomaterials through synergetic combinations of chemical or physical fabrications. Eletropolymerization is of great significance to fabricate polymeric film materials straight on the conductive substrates with tunable morphologies and thicknesses. However, unlimited electrochemical reactions(polymerization) have been usually leading to disadvantageous in ill-defined structure and highly doped state. Thanks to finding of exceptional electrochemical reaction (oligomerization) of N -alkylcarbazole, electrochemical layer by layer assembly has emerged as a promising strategy for a wide library of applications. The capability of this strategy can manipulate various molecules and nanoparticles into the scale and component controllable thin films. Unlike other electropolymerizable precursors such as aniline and thiophene, the resulting di- N -alkylcarbazole is transparent in the visible light region and thus does not impair the intrinsic properties of the components in the film. This account highlights of the typical findings in investigating both single- and multi- components thin films as a forum for discussing new opportunities in exploiting novel designs and applications of optical thin films.

Parareal Multiscale Methods for Highly Oscillatory Dynamical Systems

We introduce a new strategy for coupling the parallel in time (parareal) iterative methodology with multiscale integrators. Following the parareal framework, the algorithm computes a low-cost approximation of all slow variables in the system using an appropriate multiscale integrator, which is refined using parallel fine scale integrations. Convergence is obtained using an alignment algorithm for fast phase-like variables. The method may be used either to enhance the accuracy and range of applicability of the multiscale method in approximating only the slow variables, or to resolve all the state variables. The numerical scheme does not require that the system is split into slow and fast coordinates. Moreover, the dynamics may involve hidden slow variables, for example, due to resonances. We propose an alignment algorithm for almost-periodic solutions, in which case convergence of the parareal iterations is proved. The applicability of the method is demonstrated in numerical examples.

A Uniformly Accurate Multiscale Time Integrator Pseudospectral Method for the Dirac Equation in the Nonrelativistic Limit Regime

We propose and rigourously analyze a multiscale time integrator Fourier pseudospectral (MTI-FP) method for the (linear) Dirac equation with a dimensionless parameter $\varepsilon\in(0,1]$ which is inversely proportional to the speed of light. In the nonrelativistic limit regime, i.e., $0<\varepsilon\ll 1$, the solution exhibits highly oscillatory propagating waves with wavelength $O(\varepsilon^2)$ and $O(1)$ in time and space, respectively. Due to the rapid temporal oscillation, designing and analyzing numerical methods with uniform error bounds in $\varepsilon\in(0,1]$ is quite challenging. We present the MTI-FP method based on properly adopting a multiscale decomposition of the solution of the Dirac equation and applying the exponential wave integrator with appropriate numerical quadratures. By a careful study of the error propagation and using the energy method, we establish two independent error estimates via two different mathematical approaches as $h^{m_0}+\frac{\tau^2}{\varepsilon^2}$ and $h^{m_0}+\tau^2+\varepsilon^2$, where $h$ is the mesh size, $\tau$ is the time step, and $m_0$ depends on the regularity of the solution. These two error bounds immediately imply that the MTI-FP method converges uniformly and optimally in space with exponential convergence rate if the solution is smooth, and uniformly in time with linear convergence rate at $O(\tau)$ for all $\varepsilon\in(0,1]$ and optimally with quadratic convergence rate at $O(\tau^2)$ in the regimes when either $\varepsilon=O(1)$ or $0<\varepsilon\lesssim \tau$. Numerical results are reported to demonstrate that our error estimates are optimal and sharp. Finally, the MTI-FP method is applied to study numerically the convergence rates of the solution of the Dirac equation to those of its limiting models when $\varepsilon\to0^+$.

The Granites - Tanami Orogen Subsurface Geometry as Revealed by and Integrated Potential Field Geophysical and Geological Study

The Granites Tanami Orogen (GTO) in central Australia is a significant gold producing province. Future exploration will be facilitated by determining the structural controls on mineralisation and crustal evolution of the orogen. A whole of crust model has been generated through the multi-scale integration and interpretation of geophysical, geological and remote sensing data. The architecture of the orogen is that of a basin that has been inverted, deformed and intruded during: a) the collision between the Kimberley and Tanami basins along the Halls Creek Orogen to form the North Australian Craton; and b) during the amalgamation of the North Australian Craton with the Central Australia Craton. These continent-continent collisions have resulted in a complex structural framework, which is further complicated by deep weathering and extensive regolith across the region. Reconnaissance style outcrop mapping coupled with potential field interpretation has identified two main phases of deformation. The first regional deformation event resulted in north- to northeast-trending isoclinal fold trains of wavelengths ~10 km or greater. These folds are recognised through the interpretation of joint gravity and magnetic anomalies and are confirmed in outcrop. Gold mineralisation within the GTO is coincident with the second regional deformation event, which is recognised in regional aeromagnetic data as poly-phase deformational interference patterns caused by the refolding of earlier folds around axes trending E to ESE. This defining of upper crustal architecture to structural features observable in sparse outcrop coverage could not be sufficiently identified without this combined geology and geophysical approach.

A New Technique for Multi-Oriented Scene Text Line Detection and Tracking in Video

Text detection and tracking in video is challenging due to contrast, resolution and background variations, and different orientations and text movements. In addition, the presence of both caption and scene texts in video aggravates the problem because these two text types differ in characteristics significantly . This paper proposes a new technique for detecting and tracking video texts of any orientation by using spatial and temporal information, respectively. The technique explores gradient directional symmetry at component level for smoothing edge components before text detection. Spatial information is preserved by forming Delaunay triangulation in a novel way at this level, which results in text candidates. Text characteristics are then proposed in a different way for eliminating false text candidates , which results in potential text candidates. Then grouping is proposed for combining potential text candidates regardless of orientation based on the nearest neighbor criterion. To tackle the problems of multi-font and multi-sized texts, we propose multi-scale integration by a pyramid structure, which helps in extracting full text lines. Then, the detected text lines are tracked in video by matching the subgraphs of triangulation. Experimental results for text detection and tracking on our video dataset, the benchmark video datasets, and the natural scene image benchmark datasets show that the proposed method is superior to the state-of-the-art methods in terms of recall, precision , and F-measure.

Data-Driven Modelling of Biological Multi-Scale Processes

Publishers, 2015 Biological processes involve a variety of spatial and temporal scales. A holistic under- standing of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathemati- cal and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction us- ing reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.

Multiscale Self-coordination of Bidimensional Empirical Mode Decomposition in Image Fusion

The bidimensional empirical mode decomposition (BEMD) algorithm with high adaptability is more suitable to process multiple image fusion than traditional image fusion. However, the advantages of this algorithm are limited by the end effects problem, multiscale integration problem and number difference of intrinsic mode functions in multiple images decomposition. This study proposes the multiscale self-coordination BEMD algorithm to solve this problem. This algorithm outside extending the feather information with the support vector machine which has a high degree of generalization, then it also overcomes the BEMD end effects problem with conventional mirror extension methods of data processing, . The coordination of the extreme value point of the source image helps solve the problem of multiscale information fusion. Results show that the proposed method is better than the wavelet and NSCT method in retaining the characteristics of the source image information and the details of the mutation information inherited from the source image and in significantly improving the signal-to-noise ratio.

MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.

Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.

LinkRbrain: multi-scale data integrator of the brain.

LinkRbrain is an open-access web platform for multi-scale data integration and visualization of human brain data. This platform integrates anatomical, functional, and genetic knowledge produced by the scientific community. The linkRbrain platform has two major components: (1) a data aggregation component that integrates multiple open databases into a single platform with a unified representation; and (2) a website that provides fast multi-scale integration and visualization of these data and makes the results immediately available. LinkRbrain allows users to visualize functional networks or/and genetic expression over a standard brain template (MNI152). Interrelationships between these components based on topographical overlap are displayed using relational graphs. Moreover, linkRbrain enables comparison of new experimental results with previous published works. Previous tools and studies illustrate the opportunities of data mining across multiple tiers of neuroscience and genetic information. However, a global systematic approach is still missing to gather cognitive, topographical, and genetic knowledge in a common framework in order to facilitate their visualization, comparison, and integration. LinkRbrain is an efficient open-access tool that affords an integrative understanding of human brain function.

Fundamental controls on fluid flow in carbonates: current workflows to emerging technologies

Abstract The introduction reviews topics relevant to the fundamental controls on fluid flow in carbonate reservoirs and to the prediction of reservoir performance. The review provides research and industry contexts for papers in this volume only. A discussion of global context and frameworks emphasizes the value yet to be captured from compare and contrast studies. Multidisciplinary efforts highlight the importance of greater integration of sedimentology, diagenesis and structural geology. Developments in analytical and experimental methods, stimulated by advances in the materials sciences, support new insights into fundamental (pore-scale) processes in carbonate rocks. Subsurface imaging methods relevant to the delineation of heterogeneities in carbonates highlight techniques that serve to decrease the gap between seismically resolvable features and well-scale measurements. Methods to fuse geological information across scales are advancing through multiscale integration and proxies. A surge in computational power over the last two decades has been accompanied by developments in computational methods and algorithms. Developments related to visualization and data interaction support stronger geoscience–engineering collaborations. High-resolution and real-time monitoring of the subsurface are driving novel sensing capabilities and growing interest in data mining and analytics. Together, these offer an exciting opportunity to learn more about the fundamental fluid-flow processes in carbonate reservoirs at the interwell scale.

Agricultural land use changes – a scenario-based sustainability impact assessment for Brandenburg, Germany

Decisions for agricultural management are taken at farm scale. However, such decisions may well impact upon regional sustainability. Two of the likely agricultural management responses to future challenges are extended use of irrigation and increased production of energy crops. The drivers for these are high commodity prices and subsidy policies for renewable energy. However, the impacts of these responses upon regional sustainability are unknown. Thus, we conducted integrated impact assessments for agricultural intensification scenarios in the federal state of Brandenburg, Germany, for 2025. One Irrigation scenario and one Energy scenario were contrasted with the Business As Usual (BAU) scenario. We applied nine indicators to analyze the economic, social and environmental effects at the regional, in this case district scale, which is the smallest administrative unit in Brandenburg. Assessment results were discussed in a stakeholder workshop involving 16 experts from the state government.The simulated area shares of silage maize for fodder and energy were 29%, 37% and 49% for the BAU, Irrigation, and Energy scenarios, respectively. The Energy scenario increased bio-electricity production to 41% of the demand of Brandenburg, and it resulted in CO2 savings of up to 3.5milliontons. However, it resulted in loss of biodiversity, loss of landscape scenery, increased soil erosion risk, and increased area demand for water protection requirements. The Irrigation scenario led to yield increases of 7% (rapeseed), 18% (wheat, sugar beet), and 40% (maize) compared to the BAU scenario. It also reduced the year-to-year yield variability. Water demand for irrigation was found to be in conflict with other water uses for two of the 14 districts. Spatial differentiation of scenario impacts showed that districts with medium to low yield potentials were more affected by negative impacts than districts with high yield potentials.In this first comprehensive sustainability impact assessment of agricultural intensification scenarios at regional level, we showed that a considerable potential for agricultural intensification exists. The intensification is accompanied by adverse environmental and socio-economic impacts. The novelty lies in the multiscale integration of comprehensive, agricultural management simulations with regional level impact assessment, which was achieved with the adequate use of indicators. It provided relevant evidence for policy decision making. Stakeholders appreciated the integrative approach of the assessment, which substantiated ongoing discussions among the government bodies. The assessment approach and the Brandenburg case study may stay exemplary for other regions in the world where similar economic and policy driving forces are likely to lead to agricultural intensification.

Multi-scale integration and predictability in resting state brain activity.

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

Reduction of false positives at vessel bifurcations in computerized detection of lung nodules

Objective: We describe a new false positive (FP) reduction method based on surface features in our computerized detection system for lung nodules and evaluate the method using clinical chest computed tomography (CT) scans. Methods: In our detection method, nodule candidates are extracted using volumetric curvature-based thresholding and region growing. For various sizes of nodules, we adopt multiscale integration based on Hessian eigenvalues. For each nodule candidate, two surface features are calculated to differentiate nodules and FPs at vessel bifurcations. These features are fed into a quadratic classifier based on the Mahalanobis distance ratio. Results: In an experimental study involving 16 chest CT scans, the average number of FPs was reduced from 107.5 to 14.1 per case at 90% sensitivity. Conclusions: This proposed FP reduction method is effective in removing FPs at vessel bifurcations.

Uniformly Accurate Multiscale Time Integrators for Highly Oscillatory Second Order Differential Equations

In this paper, two multiscale time integrators (MTIs), motivated from two types of multiscale decomposition by either frequency or frequency and amplitude, are proposed and analyzed for solving highly oscillatory second order differential equations with a dimensionless parameter $0<\varepsilon\le1$. In fact, the solution to this equation propagates waves with wavelength at $O(\varepsilon^2)$ when $0<\varepsilon\ll 1$, which brings significantly numerical burdens in practical computation. We rigorously establish two independent error bounds for the two MTIs at $O(\tau^2/\varepsilon^2)$ and $O(\varepsilon^2)$ for $\varepsilon\in(0,1]$ with $\tau>0$ as step size, which imply that the two MTIs converge uniformly with linear convergence rate at $O(\tau)$ for $\varepsilon\in(0,1]$ and optimally with quadratic convergence rate at $O(\tau^2)$ in the regimes when either $\varepsilon=O(1)$ or $0<\varepsilon\le \tau$. Thus the meshing strategy requirement (or $\varepsilon$-scalability) of the two MTIs is $\tau=O(1)$ for $0<\varepsilon\ll 1$, which is significantly improved from $\tau=O(\varepsilon^3)$ and $\tau=O(\varepsilon^2)$ requested by finite difference methods and exponential wave integrators to the equation, respectively. Extensive numerical tests and comparisons with those classical numerical integrators are reported, which gear towards better understanding on the convergence and resolution properties of the two MTIs. In addition, numerical results support the two error bounds very well.

Shear zone liquefaction in mass transport deposit emplacement: A multi-scale integration of seismic reflection and outcrop data

Abstract We present the integrated outcrop-geophysical study of two mass transport complexes, the exhumed Specchio unit in the Northern Apennines of Italy and the Holocene Poverty unit in the Hikurangi margin of New Zealand. The combination of micro- to meso-scale structural, stratigraphic and sedimentologic analyses carried on continuous three-dimensional outcrops, with large-scale structural and morphologic data deriving from seismic/acoustic imaging of the present-day continental margins, allow important considerations on submarine landslide processes and mechanisms through the broader (up-scaled and down-scaled) understanding of the mass transport-related structural associations. We compare the discontinuous high-amplitude, reverse-polarity reflectors observed within the Poverty with the syn-sedimentary, ductile shear zones found within the Specchio mass transport complex. The seismic signature of such structures suggests localized fluid overpressure along detachment/thrust zones due to shearing and loading of undrained, water-saturated, fine-grained material, developed along with the slide mass movement. The outcrop expression of these structures is tentatively attributed to m- to tens of m-thick shear zones comprising large amounts of sedimentary matrix which separate and accommodate the differential movements of the internal slide components (e.g. slide blocks, olistoliths). The sedimentary matrix is an unsorted, lithologically mixed medium characterized by a scale-invariant “block-in-matrix” fabric (i.e. brecciated, mud-supported), that injects, sustain and surrounds discrete slide elements (from particles to blocks) and interpreted as a hyper-concentrated (liquefied/fluidized) suspension of water and scattered sediments developed in fluid overpressure conditions. We highlight the fundamental role of shearing-related liquefaction as one of the main factors controlling slide mobility through the “lubrication” of the internal and basal friction forces. The analysis of such features can therefore provide important information for the characterization of mass transport deposits developed from potentially catastrophic, long run-out mass transport events, and consequently, to better understand their possible socio-economic impact in terms of tsunamigenic potential.