Impact of atrial fibrillation on the cardiovascular system through a lumped-parameter approach

Atrial fibrillation (AF) is the most common arrhythmia affecting millions of people in the Western countries and, due to the widespread impact on the population and its medical relevance, is largely investigated in both clinical and bioengineering sciences. However, some important feedback mechanisms are still not clearly established. The present study aims at understanding the global response of the cardiovascular system during paroxysmal AF through a lumped-parameter approach, which is here performed paying particular attention to the stochastic modeling of the irregular heartbeats and the reduced contractility of the heart. AF can be here analyzed by means of a wide number of hemodynamic parameters and avoiding the presence of other pathologies, which usually accompany AF. Reduced cardiac output with correlated drop of ejection fraction and decreased amount of energy converted to work by the heart during blood pumping, as well as higher left atrial volumes and pressures are some of the most representative results aligned with the existing clinical literature and here emerging during acute AF. The present modeling, providing new insights on cardiovascular variables which are difficult to measure and rarely reported in literature, turns out to be an efficient and powerful tool for a deeper comprehension and prediction of the arrythmia impact on the whole cardiovascular system.Comment: 16 pages, 8 figures, 2 tables, Medical & Biological Engineering & Computing, 2014, Print ISSN: 0140-0118, Online ISSN: 1741-044

Role of stochastic forcing in coastal dune vegetation

The relevance and fragility of coastal dune systems are widely recognized. Various conceptual and numerical models have been formulated so far to cope with the threats that affect coastal systems worldwide. These models acknowledge the fundamental influence of vegetation in controlling coastal dunes stability but usually disregard some of the factors affecting coastal dynamics, such as the randomness of the driving forces. In agreement with these observations, a new model for the coastal dune vegetation is here briefly described, and one simplified version is applied to estimate the natural beach width

Hydrodynamic-Driven Stability Analysis of Morphological Patterns on Stalactites and Implications for Cave Paleoflow Reconstructions

A novel hydrodynamic-driven stability analysis is presented for surface patterns on speleothems, i.e., secondary sedimentary cave deposits, by coupling fluid dynamics to the geochemistry of calcite precipitation or dissolution. Falling film theory provides the solution for the flow-field and depth perturbations, the latter being crucial to triggering patterns known as crenulations. In a wide range of Reynolds numbers, the model provides the dominant wavelengths and pattern celerities, in fair agreement with field data. The analysis of the phase velocity of ridges on speleothems has a potential as a proxy of past film flow rates, thus suggesting a new support for paleoclimate analyse

Coherence resonance in paleoclimatic modeling

Through a unified mathematical framework, the stochastic behavior of three celebrated low-order lumped models, previously proposed for paleoclimate simulations, is considered. Due to the coherence resonance mechanism, the feedbacks between noise and the dynamical system reproduce the hallmark of the Pleistocene climate, i.e. the 100 ky pulsation, in a range of the model parameters that is unexpectedly wide and far from the original modeling setting. In this way, the issue of arbitrary coefficient tuning of lumped approaches in paleoclimatology can be partially bypassed. A stability analysis of the considered dynamical systems allowed the parameter space to be exploited, in order to separate the deterministic-dominated region from the stochastic-dominated region. Noise intensity is varied and the closeness in the parameter space to Hopf bifurcations and/ or bistable conditions is investigated in order to understand what conditions make the models prone to coherence resonance with a 100-ky pulsation, with or without the forcing induced by varying astronomical parameters

Density-Based Individual Tree Detection from Three-Dimensional Point Clouds

The use of three-dimensional point clouds in forestry is steadily increasing. Numerous algorithms to detect individual trees from point clouds and derive some fundamental inventory parameters have been proposed so far, but they usually provide higher accuracy in coniferous stands than in deciduous one. In the latter kind of stands, indeed, the tree identification is hampered by the geometrical round shape of the crowns, the interlacing branches of adjacent trees and the usual presence of understory vegetation. In an attempt to overcome these limitations, we developed an algorithm that is innovatively based on the areal point density of the three-dimensional cloud and that provides the height and coordinates of all the trees within a region of interest. In this work, we apply the algorithm to different situations, ranging from the regularly-arranged plantations to the very interlaced crowns of the naturally established stands, demonstrating how it is able to correctly detect most of the trees and recreate a map of their spatial distribution. We also test its capability to deal with relatively low point density and explore the possibility to use it to recreate time series of vegetation biomass. Finally, we discuss the algorithm’s limitations and potentialities, particularly focusing on its coupling to other existing tools to deal with a wider range of applications in forestry and land management

Rate Control Management of Atrial Fibrillation: May a Mathematical Model Suggest an Ideal Heart Rate?

Background. Despite the routine prescription of rate control therapy for atrial fibrillation (AF), clinical evidence demonstrating a heart rate target is lacking. Aim of the present study was to run a mathematical model simulating AF episodes with a different heart rate (HR) to predict hemodynamic parameters for each situation. Methods. The lumped model, representing the pumping heart together with systemic and pulmonary circuits, was run to simulate AF with HR of 50, 70, 90, 110 and 130 bpm, respectively. Results. Left ventricular pressure increased by 56.7%, from 33.92+-37.56 mmHg to 53.15+-47.56 mmHg, and mean systemic arterial pressure increased by 27.4%, from 82.66+-14.04 mmHg to 105.29+-7.63 mmHg, at the 50 and 130 bpm simulations, respectively. Stroke volume (from 77.45+-8.5 to 39.09+-8.08 mL), ejection fraction (from 61.1+-4.4 to 39.32+-5.42%) and stroke work (SW, from 0.88+-0.04 to 0.58+-0.09 J) decreased by 49.5, 35.6 and 34.2%, at the 50 and 130 bpm simulations, respectively. In addition, oxygen consumption indexes (rate pressure product, RPP, tension time index per minute, TTI/min, and pressure volume area per minute, PVA/min) increased from the 50 to the 130 bpm simulation, respectively, by 185.7% (from 5598+-1939 to 15995+-3219 mmHg/min), 55.5% (from 2094+-265 to 3257+-301 mmHg s/min) and 102.4% (from 57.99+-17.9 to 117.37+-25.96 J/min). In fact, left ventricular efficiency (SW/PVA) decreased from 80.91+-2.91% at 50 bpm to 66.43+-3.72% at the 130 bpm HR simulation. Conclusion. Awaiting compulsory direct clinical evidences, the present mathematical model suggests that lower HRs during permanent AF relates to improved hemodynamic parameters, cardiac efficiency, and lower oxygen consumption.Comment: 9 page

A Density-Based Algorithm for the Detection of Individual Trees from LiDAR Data

Nowadays, LiDAR is widely used for individual tree detection, usually providing higher accuracy in coniferous stands than in deciduous ones, where the rounded-crown, the presence of understory vegetation, and the random spatial tree distribution may affect the identification algorithms. In this work, we propose a novel algorithm that aims to overcome these difficulties and yield the coordinates and the height of the individual trees on the basis of the point density features of the input point cloud. The algorithm was tested on twelve deciduous areas, assessing its performance on both regular-patterned plantations and stands with randomly distributed trees. For all cases, the algorithm provides high accuracy tree count (F-score > 0.7) and satisfying stem locations (position error around 1.0 m). In comparison to other common tools, the algorithm is weakly sensitive to the parameter setup and can be applied with little knowledge of the study site, thus reducing the effort and cost of field campaigns. Furthermore, it demonstrates to require just 2 points·m^−2 as minimum point density, allowing for the analysis of low-density point clouds. Despite its simplicity, it may set the basis for more complex tools, such as those for crown segmentation or biomass computation, with potential applications in forest modeling and management

Regional-scale analysis of dune-beach systems using Google Earth Engine

Coastal sand dunes provide a large variety of ecosystem services, among which the inland protection from marine floods. Nowadays, this protection is fundamental, and its importance will further increase in the future due to the rise of the sea level and storm violence induced by climate change. Despite the crucial role of coastal dunes and their potential application in mitigation strategies, the phenomenon of the coastal squeeze, which is mainly caused by the urban sprawl, is progressively reducing the extents of the areas where dune can freely undergo their dynamics, thus dramatically impairing their capability of providing ecosystem services. Aiming to embed the use of satellite images in the study of coastal foredune and beach dynamics, we developed a classification algorithm that uses the satellite images and server-side functions of Google Earth Engine (GEE). The algorithm runs on the GEE Python API and allows the user to retrieve all the available images for the study site and the chosen time period from the selected sensor collection. The algorithm also filters the cloudy and saturated pixels and creates a percentile-composite image over which it applies a random forest classification algorithm. The classification is finally refined by defining a mask for land pixels only. According to the provided training data and sensor selection, the algorithm can give different outcomes, ranging from sand and vegetation maps, beach width measurements, and shoreline time evolution visualization. This very versatile tool that can be used in a great variety of applications within the monitoring and understanding of the dune-beach systems and associated coastal ecosystem services. For instance, we show how this algorithm, combined with machine learning techniques and the assimilation of real data, can support the calibration of a coastal model that gives the natural extent of the beach width and that can be, therefore, used to plan restoration activities

Thin-film-induced morphological instabilities over calcite surfaces

Precipitation of calcium carbonate from water films generates fascinating calcite morphologies that have attracted scientific interest over past centuries. Nowadays, speleothems are no longer known only for their beauty but they are also recognized to be precious records of past climatic conditions, and research aims to unveil and understand the mechanisms responsible for their morphological evolution. In this paper, we focus on crenulations, a widely observed ripple-like instability of the the calcite–water interface that develops orthogonally to the film flow. We expand a previous work providing new insights about the chemical and physical mechanisms that drive the formation of crenulations. In particular, we demonstrate the marginal role played by carbon dioxide transport in generating crenulation patterns, which are indeed induced by the hydrodynamic response of the free surface of the water film. Furthermore, we investigate the role of different environmental parameters, such as temperature, concentration of dissolved ions and wall slope. We also assess the convective/absolute nature of the crenulation instability. Finally, the possibility of using crenulation wavelength as a proxy of past flows is briefly discussed from a theoretical point of view