Comparative analysis of the differences between using LiDAR and contour-based DEMs for hydrological modeling of runoff generating debris flows in the Dolomites

Present work aims to explore the differences in hydrological modeling when using digital elevation models (DEMs) generated by points from LiDAR surveys and those digitized on the contour lines of the regional technical map (RTM) and their relevance for the simulation of debris flow triggering. Hydrological models for mountainous areas are usually based on digital elevation models (DEMs). DEMs are used to determine the flow path from each pixel, by which the basin is discretized, to the outlet. Hydrological simulations of runoff that triggered debris flows occurred in two rocky headwater basins of Dolomites, Fiames Dimai (area approximately 0.03 km2) and Cancia (area approximately 0.7 km2) are carried out using a DEM-based model designed for simulating runoff that descends from headwater areas. For each basin, the runoff is simulated using DEMs that are generated using points from LiDAR, and those digitized on the contour lines of the regional technical map, respectively. The results show that the peak discharge values corresponding to the simulations carried out using the LiDAR-based DEMs are higher than those corresponding to the simulations carried out using the RTM-based DEMs. Larger differences are observed for the Dimai basin, where the area corresponding to the RTM-based DEM is markedly smaller than the area corresponding to LiDAR-based DEM, whereas for the Cancia basin, the two areas are similar. Both the differences in the peak discharge and the basin area are due to the poor accuracy of the contour-based DEM (i.e., elevation accuracy), that is, a poor representation of the morphological features that leads to errors on the watershed divide and simplifications of the flow paths from each cell to the outlet. This result is highly relevant for estimating the triggering conditions of runoff generated debris flows. An incorrect simulated value of peak discharge can lead to errors both in planning countermeasures against debris flows and in predicting their occurrence

Optimizing the energy consumption of spiking neural networks for neuromorphic applications

In the last few years, spiking neural networks have been demonstrated to perform on par with regular convolutional neural networks. Several works have proposed methods to convert a pre-trained CNN to a Spiking CNN without a significant sacrifice of performance. We demonstrate first that quantization-aware training of CNNs leads to better accuracy in SNNs. One of the benefits of converting CNNs to spiking CNNs is to leverage the sparse computation of SNNs and consequently perform equivalent computation at a lower energy consumption. Here we propose an efficient optimization strategy to train spiking networks at lower energy consumption, while maintaining similar accuracy levels. We demonstrate results on the MNIST-DVS and CIFAR-10 datasets

The debris flow occurred at ru secco creek, venetian dolomites, on 4 august 2015: Analysis of the phenomenon, its characteristics and reproduction by models

On 4 August 2015, a very high intensity storm, 31.5 mm in 20 min (94.5 mm/h), hit the massif of Mount Antelao on the Venetian Dolomites triggering three stony debris \ufb02ows characterized by high magnitude. Two of them occurred in the historical sites of Rovina di Cancia and Rudan Creek and were stopped by the retaining works upstream the inhabited areas, while the third routed along the Ru Secco Creek and progressively reached the resort area and the village of San Vito di Cadore, causing fatalities and damages. The main triggering factor of the Ru Secco debris \ufb02ow was a large rock collapse on the northern cliffs of Mount Antelao occurred the previous autumn. The fallen debris material deposited on the Vallon d\u2019Antrimoia inclined plateau at the base of the collapsed cliffs and, below it, on the Ru Salvela Creek, covering it from the head to the con\ufb02uence with the Ru Secco Creek. The abundant runoff, caused by the high intensity rainfall on 4 August 2015, entrained about 52,500 m3 of the debris material laying on the Vallon d\u2019Antrimoia forming a debris \ufb02ow surge that hit and eroded the debris deposit covering the downstream Ru Salvela Creek, increasing its volume, about 110,000 m3 of mobilized sediments. This debris \ufb02ow routed downstream the con\ufb02uence, \ufb02ooding the parking of a resort area where three people died, and reached the village downstream damaging some buildings. A geomorphological analysis was initially carried out after surveying the whole basin. All liquid and solid-liquid contributions to the phenomenon were recognized together with the areas subjected to erosion and deposition. The elaboration of pre and post-event topographical surveys provided the map of deposition-erosion depths. Using the rainfall estimated by weather radar and corrected by the nearest rain gauge, about 0.8 km far, we estimated runoff by using a rainfall-runoff model designed for the headwater rocky basins of Dolomites. A triggering model provided the debris \ufb02ow hydrographs in the initiation areas, after using the simulated runoff. The initial solid-liquid surge hydrographs were, then, routed downstream by means of a cell model. The comparison between the simulated and estimated deposition-erosion pattern resulted satisfactory. The results of the simulation captured, in fact, the main features of the occurred phenomenon

Economic Space Trajectory through Different Regional Growth Models

Since the early 1990s, regional economic growth processes assume a key role in the EU policy agenda as a main tool to enhance social and economic convergence within the EU spatial landscape. Literature on regional economic growth and convergence provides some evidence on the most relevant factors affecting economic processes, mainly assuming homogeneity of production functions and steady state conditions in cross-section and panel regressions. In this framework, assuming a minimal definition of transitional steady state, econometric methods are adopted to identify regional characteristics and examine the determinants of different development models. The quantitative analysis is centred on - LSDV (Least Square Dummy Variables) estimates to cluster EU 11 regions (EU 13 excluding UK and Ireland due to lack of statistical data) by defining homogeneous latent structures affecting different transitional growth patterns; - coupled with multinomial conditional logit models to qualify the spatial distribution of expected vs actual regional gaps. Even conscious of the shortcomings of the described neoclassical production function convergence and divergence mechanisms, a sort of metaphor of substantive economic behaviour, three main findings for an explorative analysis are proposed i) the role of enlarged neoclassical production function and, at same time, its limited weight on average with respect to social and political factors as well as other stock fundamental determinants; ii) the deep differences of above defined weight of enlarged neoclassical production function at regional level in Europe; iii) the need for an adaptive governance of EU finance effort, within the same strategic objective of convergence.Economic regional growth, Panel models

Countercyclical contingent capital (CCC): possible use and ideal design

Contingent capital – any debt instrument that converts into equity when a predefined event occurs – has received increasing attention as a viable tool for allowing banks to raise capital when needed at relatively more affordable prices than common equity. While the debate has focused on contingent capital for systemically important financial institutions, this paper concentrates on its possible use for covering capital needs arising from the implementation of countercyclical buffers. We propose the introduction of countercyclical contingent capital (CCC) based on a double trigger. The interaction of the two triggers would determine a quasi-default status. Conversion would be required when the financial system is simultaneously facing aggregate problems and the individual bank – while still in a going concern status – shows weaknesses. Building on this proposal, the paper tests how different double triggers would have worked in the past and discusses the optimal design of the conversion mechanism and prudential treatment.Basel 2, capital buffer, procyclicality, contingent capital, financial crisis, reforms

Are We Using Autoencoders in a Wrong Way?

Autoencoders are certainly among the most studied and used Deep Learning models: the idea behind them is to train a model in order to reconstruct the same input data. The peculiarity of these models is to compress the information through a bottleneck, creating what is called Latent Space. Autoencoders are generally used for dimensionality reduction, anomaly detection and feature extraction. These models have been extensively studied and updated, given their high simplicity and power. Examples are (i) the Denoising Autoencoder, where the model is trained to reconstruct an image from a noisy one; (ii) Sparse Autoencoder, where the bottleneck is created by a regularization term in the loss function; (iii) Variational Autoencoder, where the latent space is used to generate new consistent data. In this article, we revisited the standard training for the undercomplete Autoencoder modifying the shape of the latent space without using any explicit regularization term in the loss function. We forced the model to reconstruct not the same observation in input, but another one sampled from the same class distribution. We also explored the behaviour of the latent space in the case of reconstruction of a random sample from the whole dataset

A full view on the dynamics of an impurity coupled to two one-dimensional fermionic baths

We consider a model for the motion of an impurity interacting with two parallel, one-dimensional (bosonized) fermionic baths. The impurity is able to move along any of the baths, and to jump from one to the other. We provide a perturbative expression for the state evolution of the system when the impurity is injected in one of the baths, with a given wave packet. The nontrivial choice of the unperturbed dynamics makes the approximation formally infinite-order in the impurity-bath coupling, allowing us to reproduce the orthogonality catastrophe. We employ the result for the state evolution to observe the dynamics of the impurity and its effect on the baths, in particular in the case when the wave packet is Gaussian. We observe and characterize the propagation of the impurity along the baths and the hopping between them. We also analyze the dynamics of the bath density and momentum density (i.e. the particle current), and show that fits an intuitive semi-classical interpretation. We also quantify the correlation that is established between the baths by calculating the inter-bath, equal-time spatial correlation functions of both bath density and momentum, finding a complex pattern. We show that this pattern contains information on both the impurity motion and on the baths themselves, and that these can be unveiled by taking appropriate "slices" of the time evolution.Comment: 26 pages, 14 figure

Comparison between automatic and conventional milking systems for milk coagulation properties and fatty acid composition in commercial dairy herds

AbstractThe aim of this study was to investigate the effect of milking dairy cows using conventional milking parlour (CMP) and automatic milking system (AMS) on milk coagulation properties and fatty acid (FA) composition. Milk coagulation traits were rennet coagulation time, curd-firming time and curd firmness. Data consisted of 10,476 individual milk samples collected from 918 Holstein–Friesian cows in 8 herds: four herds milked cows using a CMP and four using an AMS. A linear mixed model was used to investigate sources of variation for milk yield, traditional quality traits, coagulation properties and FA profile. On average, cows from AMS produced 1 kg/d more milk than cows from CMP. Rennet coagulation time was slightly longer (+1.2 min) and free FA content was greater (+0.16 mmol/100 g milk fat) in milk from cows milked in AMS than CMP. Overall, the milking system did not affect the FA concentration of milk. Results of the present study suggest that AMS can be adopted without detrimental effects on mil..