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In Dagum and Slottje's breakthrough contribution of on human capital (2000), the authors combine its microeconomic estimation as a standardized latent variable with the macroeconomic estimation of its average value in the population. The standardized latent variable is obtained applying the partial least squares method after transforming the qualitative indicators considered as investments in human capital and called formative indicators. This approach, however, does not take into account the effects of investing in human capital (reflective indicators), hence ignoring its economic definition. The main purpose of this paper is to introduce an improved statistical method of household human capital estimation as a standardized latent variable which is a function of both formative and reflective indicators. The latter is measured by household earned income, excluding income generated from wealth

Low respiratory tract infections (LRTI) represent the leading infectious cause of death worldwide and account for substantial use of healthcare resources. Physicians must adopt practices focused on improving outcomes and serum biomarker can help them in the management of patients with LRTI. Several studies have been carried out or are currently ongoing to evaluate the role of various biomarkers for the differential diagnosis, definition of prognosis, treatment and duration of antibiotic therapy in respiratory infections. The objective of this position paper of the Italian Society of Respiratory Diseases (SIMER) is to provide evidence-based recommendations for the use of biomarkers in routine clinical practice in the management of adult patients with LRTI. These guidelines capture the use of biomarkers both outside and inside the hospital, focused on community-acquired pneumonia, acute exacerbations of chronic obstructive pulmonary disease, hospital-acquired and ventilator-acquired pneumonia.

Wireless sensor networks (WSNs) are typically constituted by a large number of connected sensors (nodes), generally distributed at random on a given surface area. In such large-scale networks, the desired global system performance is achieved by gathering local information and decisions collected from each individual node. There exist three fundamental global issues on WSNs that we consider here, namely, full network connectivity, high coverage of the sensing area and reduced power consumption, thus improving on the network lifetime. Full connectivity can be obtained either by increasing the transmission range, at the expense of consuming higher transmission power, or by increasing the number of sensors, i.e. by increasing network costs. Both of them are closely related to global network lifetime, in the sense that the higher the power consumption or the more the number of active sensors present, the shorter the network lifetime (Wang et al., 2007) [1]. Here, we are interested in the minimal number of active nodes required for keeping the network functioning, while the problem of redundancy, i.e. having additional nodes kept in a sleeping mode for a certain period of time, can be implemented afterwards based on the present 'minimal' results. So the main question is, how can one design large-scale random networks in order to have both global connectivity and minimum number of active nodes reducing the total energy consumption? Although these questions have been addressed often in the past, a definite, simple predicting algorithm for achieving these goals does not exist so far. In this paper, we aim to discuss such a scheme and confront it with extensive simulations of random networks generated numerically. Specifically, we study the minimum number of nodes required to achieve full network connectivity, and present an analytical formula for estimating it. The results are in very good agreement with the numerical simulations as a function of transmission range. We also

Wireless sensor networks (WSNs) are typically constituted by a large number of connected sensors (nodes), generally distributed at random on a given surface area. In such large-scale networks, the desired global system performance is achieved by gathering local information and decisions collected from each individual node. There exist three fundamental global issues on WSNs that we consider here, namely, full network connectivity, high coverage of the sensing area and reduced power consumption, thus improving on the network lifetime. Full connectivity can be obtained either by increasing the transmission range, at the expense of consuming higher transmission power, or by increasing the number of sensors, i.e. by increasing network costs. Both of them are closely related to global network lifetime, in the sense that the higher the power consumption or the more the number of active sensors present, the shorter the network lifetime (Wang et al., 2007) [1]. Here, we are interested in the minimal number of active nodes required for keeping the network functioning, while the problem of redundancy, i.e. having additional nodes kept in a sleeping mode for a certain period of time, can be implemented afterwards based on the present 'minimal' results. So the main question is, how can one design large-scale random networks in order to have both global connectivity and minimum number of active nodes reducing the total energy consumption? Although these questions have been addressed often in the past, a definite, simple predicting algorithm for achieving these goals does not exist so far. In this paper, we aim to discuss such a scheme and confront it with extensive simulations of random networks generated numerically. Specifically, we study the minimum number of nodes required to achieve full network connectivity, and present an analytical formula for estimating it. The results are in very good agreement with the numerical simulations as a function of transmission range. We also

In this paper, we propose an original methodology by which to assess the construct of the situated social value of open data and we apply it to the healthcare domain in regard to information by which hospitals can be ranked to compare service providers. Our methodology encompasses a questionnaire-based user study and a method by which to rank information items by their perceived social value in situated scenarios. While the social component of the construct is addressed traditionally, the main asset of our contribution is to ground the assessment of information value on a multidimensional space of potential situations where that information can be perceived as valuable, and to inquiry the respondents of the user study about their empathized perceptions in daily life scenarios, which are defined to cover the dimensional space properly. The findings of the user study are reported and the implications on the construct assessment discussed in the aim to enable IS benchmarking and more focused interventions of data quality improvement.

This paper provides new empirical evidence about the impact of various technological policies upon firms' innovative behaviour. We take into consideration the role of policies for innovative activities and we focus on their interaction. While supply-side policies such as R&D subsidies and tax credits have been both extensively discussed in the literature and empirically investigated, the analysis of innovative public procurement is a growing trend in the literature, which still lacks robust empirical evidence. In this paper, we replicate the existing results on supply-side policies, surmise fresh empirical evidence on the outcome of innovative public procurement, and address the issue of possible interaction among the various tools. When controlling for the interaction with other policies, supply-side subsidies cease to be as effective as reported in previous studies and innovative public procurement seems to be more effective than other tools. The preliminary evidence suggests that technology policies exert the highest impact when different policies interact.

Fast neutron detectors with a sub-centimetric space resolution are required in order to qualify neutron beams in applications related to magnetically-controlled nuclear fusion plasmas and to spallation sources. Based on the results obtained with small area prototypes, the first medium-size (20 × 35.2 cm2 active area) nGEM detector has been realized for both the CNESM diagnostic system of the SPIDER NBI prototype for ITER and as a beam monitor for fast neutrons beam lines at spallation sources, too. The nGEM is a Triple GEM gaseous detector equipped with polyethylene layers used to convert fast neutrons into recoil protons through the elastic scattering process. This paper describes the performance of the medium-size nGEM detector tested at the VESUVIO beam line of the ISIS spallation source. Being this detector the actual largest area fast neutron detector based on the GEM technology, particular attention was paid in the study of detector response in different points over the active area. Measurements of GEM counting rate (both as a function of VGEM and of time) and of the capability of the detector to reconstruct the beam in different positions are presented. This detector serves as a basis for the realization of an even larger area detector that will be used in the MITICA NBI prototype for ITER that represents the evolution of SPIDER.

A central issue in biological data analysis is that uncertainty, resulting from different factors of variability, may change the effect of the events being investigated. Therefore, robustness is a fundamental step to be considered. Robustness refers to the ability of a process to cope well with uncertainties, but the different ways to model both the processes and the uncertainties lead to many alternative conclusions in the robustness analysis. In this paper we apply a framework allowing to deal with such questions for mass spectrometry data. Specifically, we provide robust decisions when testing hypothesis over a case/control population of subject measurements (i.e. proteomic profiles). To this concern, we formulate (i) a reference model for the observed data (i.e., graphs), (ii) a reference method to provide decisions (i.e., test of hypotheses over graph properties) and (iii) a reference model of variability to employ sources of uncertainties (i.e., random graphs). We apply these models to a realcase study, analyzing the mass spectrometry profiles of the most common type of Renal Cell Carcinoma; the Clear Cell variant.

This paper introduces provenance, a software package within the statistical programming environment R, which aims to facilitate the visualisation and interpretation of large amounts of sedimentary provenance data, including mineralogical, petrographic, chemical and isotopic provenance proxies, or any combination of these. provenance comprises functions to: (a) calculate the sample size required to achieve a given detection limit; (b) plot distributional data such as detrital zircon U-Pb age spectra as Cumulative Age Distributions (CADs) or adaptive Kernel Density Estimates (KDEs); (c) plot compositional data as pie charts or ternary diagrams; (d) correct the effects of hydraulic sorting on sandstone petrography and heavy mineral composition; (e) assess the settling equivalence of detrital minerals and grain-size dependence of sediment composition; (f) quantify the dissimilarity between distributional data using the Kolmogorov-Smirnov and Sircombe-Hazelton distances, or between compositional data using the Aitchison and Bray-Curtis distances; (e) interpret multi-sample datasets by means of (classical and nonmetric) Multidimensional Scaling (MDS) and Principal Component Analysis (PCA); and (f) simplify the interpretation of multi-method datasets by means of Generalised Procrustes Analysis (GPA) and 3-way MDS. All these tools can be accessed through an intuitive query-based user interface, which does not require knowledge of the R programming language. provenance is free software released under the GPL-2 licence and will be further expanded based on user feedback.

In this paper, we describe the upper Cisuralian Safetdara and Gundara formations of the Darvaz mountains, North Pamir, which were part of the Kunlun Arc, developed along the active Eurasian margin. The Safetdara Formation comprises massive limestones (mainly cyanobacterial, Tubiphytes and Archaeolithoporella boundstones) alternating with well-bedded bioclastic and oncoidal limestones and an interval of recessive shales. The formation crops out above the Chelamchi Formation consisting of turbiditic siltstones and sandstones with bioclastic silty limestones yielding massive limestone olistoliths. The Gundara Formation consists of fine sandstones at the base, followed by well-bedded marly bioclastic, oncoidal and microbial limestones, bearing a rich silicified brachiopod fauna in life-position. Two new taxa have been identified in this association: the cemented coralliform Gundaria insolita n. gen. n. sp. and the pedicle attached Hemileurus politus n. sp. The inferred environmental setting is that of shoal deposits of warm, shallow, high energy, clear marine waters for the Safetdara Formation. The agglutinated microbial reefs to cluster reefs of the Gundara Formation were probably growing in a muddier, quieter and probably slightly deeper setting. The foraminifers of the Brevaxina Zone suggest a Bolorian age for the top of the Chelamchi Formation, the Safetdara Formation and the base of the Gundara Formation. Kungurian conodonts have been found in the lower part of the Safetdara Formation. The biostratigraphic data from the sedimentary succession of North Pamir, integrated with those already obtained from Southeast Pamir, allow to refine the correlations between the Tethyan regional scale and the International Time Scale. In particular, it seems now clear that the Bolorian and the lower part of the Kubergandian correlate to the Kungurian.

Future research in High Energy Cosmic Ray Physics concerns fundamental questions on their origin, acceleration mechanism, and composition. Unambiguous measurements of the energy spectra and of the composition of cosmic rays at the "knee" region could provide some of the answers to the above questions. Only ground based observations, which rely on sophisticated models describing high energy interactions in the earth's atmosphere, have been possible so far due to the extremely low particle rates at these energies. A calorimeter based space experiment can provide not only flux measurements but also energy spectra and particle identification, especially when coupled to a dE/dx measuring detector, and thus overcome some of the limitations plaguing ground based experiments. For this to be possible very large acceptances are needed if enough statistic is to be collected in a reasonable time. This contrasts with the lightness and compactness requirements for space based experiments. A novel idea in calorimetry is discussed here which addresses these issues while limiting the mass and volume of the detector. In fact a small prototype is currently being built and tested with ions. In this paper the results obtained will be presented in light of the simulations performed.

Standard 3D mesh generation algorithms may produce a low quality tetrahedral mesh, i.e., a mesh where the tetrahedra have very small dihedral angles. In this paper, we propose a series of operations to recover these badly-shaped tetrahedra. In particular, we will focus on the shape of these undesired mesh elements by proposing a novel method to distinguish and classify them. For each of these configurations, we apply a suitable sequence of operations to get a higher mesh quality. Finally, we employ a random algorithm to avoid locks and loops in the procedure. The reliability of the proposed mesh optimization algorithm is numerically proved with several examples.

FLARES is a project for an innovative detector technology to be applied to rare event searches, and in particular to neutrinoless double beta decay experiments. Its novelty is the enhancement and optimization of the collection of the scintillation light emitted by ultra-pure crystals through the use of arrays of high performance silicon photodetectors cooled to 120 K. This would provide scintillation detectors with 1% level energy resolution, with the advantages of a technology offering relatively simple low cost mass scalability and powerful background reduction handles, as requested by future neutrinoless double beta decay experimental programs. The performances of a first production of matrices of Silicon Drift Detectors are presented and discussed in this paper.

In financial literature many have been the attempts to overcome the option pricing drawbacks that affect the Black and Scholes model. Starting from the Tsallis deformation of the usual exponential function, this paper presents, in a complete market setup, a class of deformed geometric Brownian motions flexible enough to reproduce fat tails and to capture the volatility behavior observed in models that consider both stochastic volatility and jumps.

The ITER neutral beam test facility under construction in Padova will host two experimental devices: SPIDER, a 100 kV negative H/D RF beam source, and MITICA, a full scale, 1 MeV deuterium beam injector. SPIDER will start operations in 2016 while MITICA is expected to start during 2019. Both devices feature a beam dump used to stop the produced deuteron beam. Detection of fusion neutrons produced between beam-deuterons and dump-implanted deuterons will be used as a means to resolve the horizontal beam intensity profile. The neutron detection system will be placed right behind the beam dump, as close to the neutron emitting surface as possible thus providing the map of the neutron emission on the beam dump surface. The system uses nGEM neutron detectors. These are Gas Electron Multiplier detectors equipped with a cathode that also serves as neutron-proton converter foil. The cathode is designed to ensure that most of the detected neutrons at a point of the nGEM surface are emitted from the corresponding beamlet footprint (with dimensions of about 40×22 mm2) on the dump front surface. The size of the nGEM detector for SPIDER is 352 mm×200 mm. Several smaller size prototypes have been successfully made in the last years and the experience gained on these detectors has led to the production of the full size detector for SPIDER during 2014. This nGEM has a read-out board made of 256 pads (arranged in a 16×16 matrix) each with a dimension of 22 mm×13 mm. This paper describes the production of this detector and its tests (in terms of beam profile reconstruction capability, uniformity over the active area, gamma rejection capability and time stability) performed on the ROTAX beam-line at the ISIS spallation source (Didcot-UK).

To quantitatively map regional lateral spread hazard considering a complete portfolio of possible earthquakes is fundamental for a seismic risk assessment over large spatial coverage. This paper presents a probabilistic model of liquefaction-induced lateral spread considering seismic randomness and uncertainty of soil properties. This model enables quantitative maps of lateral spread displacement at any exceedance probability in a specified time period, or exceedance probability of any pre-defined displacement threshold. Two mapping procedures are illustrated through a case study by generating hazard maps of lateral spread based on available cone penetration test data. These maps highlight the hotspots susceptible to serious lateral spread displacements, providing useful information on need of project-specific in-depth geotechnical investigation. The mapping procedure is based on either geostatistical interpolation or stochastic simulation. The geostatistical interpolation method has the merit to be less computationally expensive, while the stochastic simulation method seems more rational as it explicitly model the uncertainty of soil parameters and their spatial structure.

Rock avalanches are large flow-like movements of fragmented rock that can cause extensive and rapid topographic changes, for which very few quantitative data are available. This paper analyses the geomorphological and hydrological impact of the 3 million m3 Thurwieser rock avalanche (2004, Italian Central Alps) by using Terrestrial Laser Scanner, airborne Lidar and GNSS data collected from 2005 to 2014. Sediment yield with respect to the normal valley regime, the dynamic and mass balance of affected glaciers, and the reorganization of superficial and groundwater flow networks are quantified. In the middle portion of the avalanche deposit, a natural sediment trap collected sediments from a new stream channel developed along the upper portion of the deposit and from a lateral drainage basin. This made possible to assess the 10-year impact of the rock avalanche on the sediment yield, which increased from about 120 to about 400 t km-2·a-1.The rock avalanche partially covered a glacier with a shallow debris layer that acted as a thermal insulator, limiting ice ablation and producing a 10-m high scarp between the free surface of the glacier and the debris-covered portion. A reduction of 75% of ice ablation was observed due to thermal insulation. The rock avalanche filled a tributary valley, splitting the original drainage basin in two. Under ordinary flows, seepage occurs within the avalanche deposit along the old valley axis. During high flow conditions, a new stream channel is activated along the middle and lower margin of the deposit, which has produced a new alluvial fan on the main valley floor. The fan evolution is described up to the present volume of about 2000 m3.

The liquid fraction of digestate produced by agricultural biogas plants is rich in macro and micronutrients that are valuable for the culturing of microalgae. Nonetheless, the high ammonium concentration may cause toxicity and the high optical density may reduce light penetration, negatively affecting the biomass production rate. Dilution with fresh water has been frequently suggested as a mean for improving the digestate characteristics in view of microalgal culturing. In this paper, the feasibility of culturing microalgae on undiluted raw digestate or on digestate after pretreatment by stripping and adsorption was investigated. First, adsorption tests were performed using commercial activated carbon from wood in order to identify appropriate conditions for optical density (OD) reduction. Up to 88% reduction was obtained by dosing 40 g L− 1 after 24 h of contact time. Then, culturing tests were performed on a microalgal inoculum including mainly Chlorella spp. and Scenedesmus spp. under controlled temperature and light conditions during 6–14 weeks. Raw, stripped, and stripped and adsorbed digestate samples were tested. The biomass production rate increased from 27 ± 13 mg TSS L− 1 d− 1 on raw digestate, to 82 ± 18 mg TSS L− 1 d− 1 by using stripped digestate, and to 220 ± 78 mg TSS L− 1 d− 1 by using the stripped and adsorbed digestate. Moreover, nitrification was constantly suppressed when using the stripped and adsorbed digestate, while relevant nitrite built-up was observed when using raw and stripped digestate. These results suggest that microalgae are able to grow on the raw digestate, provided that long hydraulic retention times are applied. A much faster growth (up to 10 times) can be obtained by pretreating the liquid fraction of digestate by stripping and adsorption, which may be an effective means of improving th

The liquid fraction of digestate produced by agricultural biogas plants is rich in macro and micronutrients that are valuable for the culturing of microalgae. Nonetheless, the high ammonium concentration may cause toxicity and the high optical density may reduce light penetration, negatively affecting the biomass production rate. Dilution with fresh water has been frequently suggested as a mean for improving the digestate characteristics in view of microalgal culturing. In this paper, the feasibility of culturing microalgae on undiluted raw digestate or on digestate after pretreatment by stripping and adsorption was investigated. First, adsorption tests were performed using commercial activated carbon from wood in order to identify appropriate conditions for optical density (OD) reduction. Up to 88% reduction was obtained by dosing 40 g L− 1 after 24 h of contact time. Then, culturing tests were performed on a microalgal inoculum including mainly Chlorella spp. and Scenedesmus spp. under controlled temperature and light conditions during 6–14 weeks. Raw, stripped, and stripped and adsorbed digestate samples were tested. The biomass production rate increased from 27 ± 13 mg TSS L− 1 d− 1 on raw digestate, to 82 ± 18 mg TSS L− 1 d− 1 by using stripped digestate, and to 220 ± 78 mg TSS L− 1 d− 1 by using the stripped and adsorbed digestate. Moreover, nitrification was constantly suppressed when using the stripped and adsorbed digestate, while relevant nitrite built-up was observed when using raw and stripped digestate. These results suggest that microalgae are able to grow on the raw digestate, provided that long hydraulic retention times are applied. A much faster growth (up to 10 times) can be obtained by pretreating the liquid fraction of digestate by stripping and adsorption, which may be an effective means of improving th

We show that recogniser P systems with active membranes can be augmented with a priority over their set of rules and any number of membrane charges without loss of generality, as they can be simulated by standard P systems with active membranes, in particular using only two charges. Furthermore, we show that more general accepting conditions, such as sending out several, possibly contradictory results and keeping only the first one, or rejecting by halting without output, are also equivalent to the standard accepting conditions. The simulations we propose are always without significant loss of efficiency, and thus the results of this paper can hopefully simplify the design of algorithms for P systems with active membranes.

In this paper we propose a method for logo recognition using deep learning. Our recognition pipeline is composed of a logo region proposal followed by a Convolutional Neural Network (CNN) specifically trained for logo classification, even if they are not precisely localized. Experiments are carried out on the FlickrLogos-32 database, and we evaluate the effect on recognition performance of synthetic versus real data augmentation, and image pre-processing. Moreover, we systematically investigate the benefits of different training choices such as class-balancing, sample-weighting and explicit modeling the background class (i.e. no-logo regions). Experimental results confirm the feasibility of the proposed method, that outperforms the methods in the state of the art.

Social networking sites are an increasingly important tool for career development, especially for highly skilled individuals. Moreover, they may constitute valuable sources of data for scholars and policy makers. However, little research has been conducted on the use by highly skilled individuals of those social networks. In this paper, we focus on PhD graduates, who play an important role in the innovation process and in particular in knowledge creation and diffusion. We seek to increase understanding of the determinants that induce PhD graduates to register on LinkedIn and to develop wider or narrower networks. Controlling for the most relevant individual characteristics, we find that (i) PhD holders moving to the industry sector are more likely to have a LinkedIn account and to have a larger network of connections in LinkedIn; (ii) PhD holders are more likely to use LinkedIn if they have co-authors abroad; and (iii) they have wider networks if they have moved abroad after obtaining their PhD. In light of our analyses, we discuss the usefulness of – and main concerns about – the adoption of LinkedIn as a new data source for research and innovation studies.

Assortativity was first introduced by Newman and has been extensively studied and applied to many real world networked systems since then. Assortativity is a graph metric and describes the tendency of high degree nodes to be directly connected to high degree nodes and low degree nodes to low degree nodes. It can be interpreted as a first order measure of the connection between nodes, i.e. the first autocorrelation of the degree–degree vector. Even though assortativity has been used so extensively, to the author's knowledge, no attempt has been made to extend it theoretically. Indeed, Newman assortativity is about “being adjacent”, but even though two nodes may not by connected through an edge, they could have possibly a strong level of connectivity through a large number of walks and paths between them. This is the scope of our paper. We introduce, for undirected and unweighted networks, higher order assortativity by extending the Newman index based on a suitable choice of the matrix driving the connections. Higher order assortativity be defined for paths, shortest paths and random walks of a given length. The Newman assortativity is a particular case of each of these measures when the matrix is the adjacency matrix, or, in other words, the autocorrelation is of order 1. Our higher order assortativity indices help discriminating networks having the same Newman index and may reveal new topological network features. An application to airline network (Italy and US) and to Enron email network, as well as examples and simulations, are discussed.

This paper introduces a new method for face verification across large age gaps and also a dataset containing variations of age in the wild, the Large Age-Gap (LAG) dataset, with images ranging from child/young to adult/old. The proposed method exploits a deep convolutional neural network (DCNN) pre-trained for the face recognition task on a large dataset and then fine-tuned for the large age-gap face verification task. Fine-tuning is performed in a Siamese architecture using a contrastive loss function. A feature injection layer is introduced to boost verification accuracy, showing the ability of the DCNN to learn a similarity metric leveraging external features. Experimental results on the LAG dataset show that our method is able to outperform the face verification solutions in the state of the art considered.

We consider how the orthology/paralogy information can be corrected in order to represent a gene tree, a problem that has recently gained interest in phylogenomics. Interestingly, the problem is related to the Minimum CoGraph Editing problem on the relation graph that represents orthology/paralogy information, where we want to minimize the number of edit operations on the given relation graph in order to obtain a cograph. In this paper we provide both theoretical and experimental results on the Minimum CoGraph Editing problem. On the theoretical side, we provide approximation algorithms for bounded degree relation graphs, for the general problem and for the problem restricted to deletion of edges. On the experimental side, we present a genetic algorithm for Minimum CoGraph Editing and we provide an experimental evaluation of the genetic algorithm on synthetic data.

We consider how the orthology/paralogy information can be corrected in order to represent a gene tree, a problem that has recently gained interest in phylogenomics. Interestingly, the problem is related to the Minimum CoGraph Editing problem on the relation graph that represents orthology/paralogy information, where we want to minimize the number of edit operations on the given relation graph in order to obtain a cograph. In this paper we provide both theoretical and experimental results on the Minimum CoGraph Editing problem. On the theoretical side, we provide approximation algorithms for bounded degree relation graphs, for the general problem and for the problem restricted to deletion of edges. On the experimental side, we present a genetic algorithm for Minimum CoGraph Editing and we provide an experimental evaluation of the genetic algorithm on synthetic data.

The CLARO8 chip has been designed for single-photon counting in the upgraded RICH detector of the LHCb experiment at CERN. The chip has 8 channels with 5 ns peaking time and a recovery time better than 25 ns. Each channel is made of a charge amplifier with 2-bit settable attenuation, plus a comparator with a 6-bit settable threshold, and the configuration register is protected against Single Event Upsets by triple modular redundancy. In order to ensure stable operation of the upgraded RICH detectors over the expected lifetime of the experiment after the upgrade, the performance of the CLARO8 in high radiation fields has been assessed. These chips will be exposed, during the whole upgrade running phase, to a total ionizing dose of 200 krad, a neutron fluence of 3×10121 MeV neq/cm2and a high energy hadrons fluence of 1.2×1012cm−2. Systematic irradiation campaigns have been performed using ions, protons and mixed-field high-energy hadron beams. This paper describes the radiation hardness campaign of the CLARO8 chips and the main results of its extensive characterisation.

In the article “Engineering geology-A fifty year perspective”(Juang et al., 2016), which celebrated the 50th anniversary of Engineering Geology, the authors described Engineering Geology for Engineering Projects (EGEP) together with Geological Engineering and Geotechnical Engineering (GEGE) as important elements of Engineering Geology. For example, four-hundred and twelve papers were published in Engineering Geology from 1986–1995. Among which, one-hundred and twenty (about 30%) were related to EGEP. The research topics mainly included design and construction of foundations, tunnels, and slopes (eg dams, embankments, landslides). However, the papers published on EGEP and GEGE declined significantly from 2006 to 2015. It was speculated that the worldwide economic recession that began in 2008 might have contributed to the decline of infrastructure development and the number of …

Petrographic classifications of sand and sandstone proposed more than half a century ago are still in use, although they were formulated at a time when depositional and post-depositional sedimentary processes were poorly understood, and before the relationships between tectonics and sedimentation could be interpreted in modern plate-tectonic terms. As a consequence, too many scientific articles and technical reports are still encumbered with obsolete concepts, graphical tools, and ambiguous terminology that make sediment descriptions awkward and misleading. A renovation that treasures the legacy of the pioneers is required. The descriptive petrographic classification of sand and sandstone proposed in this paper is based on the quasi-universally used Gazzi-Dickinson point-counting method, and simply translates into words ternary compositions of quartz, feldspar, and lithic fragments without introducing any new names. The classic QFL plot is subdivided into 15 fields - labelled by adjectives introduced long ago by K.A.W. Crook and endorsed by W.R. Dickinson and more recently by G.J. Weltje - which reflect relative abundances of the three main framework components (provided they exceed 10%QFL). According to standard use, the less abundant component goes first, the more abundant last (e.g., litho-feldspatho-quartzose composition translates into Q > F > L > 10%QFL). For lithic-rich sand and sandstone, information on the prevailing rock fragment type can be added by an additional free adjective (e.g., metamorphiclastic, carbonaticlastic), as proposed long ago by R.V. Ingersoll. For lithic-poor feldspatho-quartzose and quartzose sand and sandstone, further formal subdivisions are proposed based on the Q/F ratio, thus reaching a total of 18 compositional fields overall. Modern sand known to be derived from different source rocks and found in major world's rivers, deserts, and deep-sea fans fits in the pigeonholes defined by the relative abundance of quartz, feldspa

Proteomics is acquiring a pivotal role in the comprehensive understanding of human biology. Biochemical processes involved in complex diseases, such as neurodegenerative diseases, diabetes and cancer, can be identified by combining proteomics analysis and bioinformatics tools. In the last ten years, the main output of differential proteomics investigations evolved from long lists of proteins to the generation of new hypotheses and their functional verification. The Journal of Proteomics participated to this progress, reporting more and more biologically-oriented papers with functional interpretation of proteomics data. This change in the field was due to both technological development and novel strategies in exploiting the deep characterization of proteomes. In this review, we explore several approaches that allow proteomics to turn functional. In particular, systems biology tools for data analysis are now routinely used to interpret results, thus defining the biological meaning of differentially abundant proteins. Moreover, by considering the importance of protein-protein interactions and the composition of macromolecular complexes, interactomics is complementing the information given by differential quantitative proteomics. Eventually, terminomics is unveiling new functions for cleaved proteoforms, by analyzing the effect of proteolysis globally. Significance: Proteomics is rapidly evolving not only technologically but also strategically. The correct interpretation of proteomics data can reveal new functions of proteins in several biological backgrounds. Systems biology tools allow researchers to formulate new hypotheses to be further functionally tested. Interactomics is shedding new light on protein complexes truly involved in biochemical pathways and how their alteration can lead to dysfunctionality (in disease pathogenesis, for example). Terminomics is revealing the function of new discovered proteoforms and attributing a novel role to proteolysis. This review

This work presents a numerical method for the simulation of landslides generated impulse waves and its application to the historical Vajont case study. The computational tool is based on the Particle Finite Element Method (PFEM), a Lagrangian strategy that combines the finite element solution of the governing equations with an efficient remeshing strategy to deal with large deformation problems. After presenting the numerical formulation, different landslide impulse wave problems with Froude number ranging from 0.5 to 2.8, are analyzed to validate the proposed methodology. The computational method is shown to be able to reproduce accurately the landslide runout, the momentum transfer between the sliding material and the impounded water, and the consequent wave propagation observed in experimental physical models. Then, the PFEM model is applied to the numerical simulation of the Vajont disaster, which is analyzed with a fully-resolved three-dimensional model. The numerical results are discussed and compared to the post-event observations and the numerical results of other computational methods. The results in terms of landslide velocity and runout, geometry of the deposit, maximum water runup, dam overtopping wave, and water discharge in the downstream valley are in good agreement with observations and reconstructions. The calibration and validation performed for this study form the basis for the PFEM analyses presented in a companion paper finalized to simulate different scenarios of the Vajont rockslide considered in the experimental tests done a year before the disaster.

Prediction of multi-hazard slope stability events requires an informed and judicious choice of the possible scenarios. An incorrect definition of landslide conditions in terms of expected failure volume, material behavior, or boundary conditions can lead to inaccurate predictions and, in turn, to wrong engineering and risk management decisions. Reduced-scale experiments carried out two years before the Vajont disaster were carried out with a material not representative of the actual rockslide behavior and failed in not considering the simultaneous failure of the whole landslide body. Based on these inappropriate assumptions, the physical models led to wrong estimates of the safety operational level for the Vajont reservoir. This work uses the Particle Finite Element Method (PFEM) to analyze the implications of the wrong hypotheses considered in the pre-event experiments, simulating numerically the Vajont disaster for different sliding volumes and material properties. The use of the PFEM for the accurate assessment of the consequences of landslides impinging in water reservoirs has been already validated in a companion paper. In this work, we demonstrate the capabilities of a robust and reliable numerical modeling approach for the simulation of different scenarios, assessing what could have been a safe operational reservoir level in the case of a landslide generated impulse wave. The three-dimensional analyses were run with a high mesh resolution and demonstrate the suitability and robustness of the PFEM model for large-scale landslide and multi-hazard events simulation.

New technologies are changing the way engineers work within the construction sector. Newly developed software solutions have provided effective methods to explore the design space at the interface between Structural Engineering and Architecture, allowing more efficient design strategies. These technologies are based on the integration of parametric generation and visualisation of geometries with powerful numerical solvers, employing user-customised routines. While the construction industry is rapidly moving the design of new construction towards a fully digitalised process, the assessment and the analysis of existing structures with such tools are still largely unexplored. In this context, a visual script for the structural assessment of out-of-plane mechanisms in historic masonry structures subject to seismic loading has recently been proposed by the authors. This relies on two successive steps of analysis, which are integrated into a digital work-flow. Datasets describing the geometric configuration of masonry structures are employed to automatically generate a non-linear Finite Element (FE) model and investigate possible collapse modes. A preliminary global analysis is performed using the commercial software ABAQUS CAE. This, in combination with the Control Surface Method (CSM), allows identifying the most likely failure mechanisms which are described by the geometry of the macro-blocks. The parametric modelling of the macro-blocks geometry allows exploring the domain of possible solutions using the upper bound method of limit analysis. A Genetic Algorithms (GA) solver is used to refine the geometry of the macro-blocks and search the minimum of the upper-bound load multipliers, which guarantees equilibrium. The script is implemented in the visual programming environment offered by Rhino3D+Grasshopper. In this paper, a set of parametric analyses considering various input variables such as friction coefficient and opening incidence are performed to verify both the

In recent years, there has been an increasing interest in extracting and annotating tables on the Web. This activity allows the transformation of text data into machine-readable formats to enable the execution of various artificial intelligence tasks, e.g. semantic search and dataset extension. Semantic Table Interpretation is the process of annotating elements in a table. Current approaches are mainly based on lexical matching algorithms that rely on metadata associated with tables or custom Knowledge Graphs. Their main limitations are due to the lack of metadata, the little use of contextual semantics, and the incompleteness of the proposed methods that do not include all the necessary steps. In this paper, we propose a comprehensive approach and a tool that provides an unsupervised method to annotate independent tables, possibly without header row or other external information. The approach is based on the definition of a context created from the elements within the table in order to discriminate among matching entities found in shared Knowledge Graphs and create high-quality annotations. The approach has achieved excellent results in an international challenge, thus proving its effectiveness.

In recent years, there has been an increasing interest in extracting and annotating tables on the Web. This activity allows the transformation of text data into machine-readable formats to enable the execution of various artificial intelligence tasks, e.g. semantic search and dataset extension. Semantic Table Interpretation is the process of annotating elements in a table. Current approaches are mainly based on lexical matching algorithms that rely on metadata associated with tables or custom Knowledge Graphs. Their main limitations are due to the lack of metadata, the little use of contextual semantics, and the incompleteness of the proposed methods that do not include all the necessary steps. In this paper, we propose a comprehensive approach and a tool that provides an unsupervised method to annotate independent tables, possibly without header row or other external information. The approach is based on the definition of a context created from the elements within the table in order to discriminate among matching entities found in shared Knowledge Graphs and create high-quality annotations. The approach has achieved excellent results in an international challenge, thus proving its effectiveness.

Rockfall is a dangerous hazard on steep and susceptible slope. However, it is not easy to identify potential rockfalls on cliff mountains. Traditionally, rockfall risk analysis ignores the temporal evolution of risk due to the changes of the elements at risk, or changes in the annual probability. This may lead to an underestimation of risk in time. In this paper, we present an innovative approach for a dynamic risk analysis, and we demonstrate this approach for the ShenXianjJu scenic area case study, where rockfall represent a threat for thousands of tourists each year. Moreover, we studied the role of rock mass quality in controlling the rockfall potential and rockfall volume, since this may lead to significant changes of rockfall risk in space. We describe the use of Unmanned Aerial Vehicle, Terrestrial LiDAR and detailed field surveys to identify 34 potential rockfalls on slopes where historical rockfalls have occurred. Within ignimbrite and rhyolite rock masses rockfall blocks range in size between large and very large. Andesite derived rockfalls are characterized by medium-size to large block size. Faulted and fractured ignimbrite and rhyolite rock masses within the fault damage zone exhibit small-very small rockfall block sizes. Based on the identified potential rockfalls in the study area, we quantified the dynamic risk by considering the temporal–spatial changes of tourist activity. To demonstrate the methodology, two potential rockfalls on two heavily-used tourist routes were selected. For these scenarios we quantified the annual probability of occurrence, the reach probability, the dynamic temporal-spatial probability, and the vulnerability of tourists. The dynamic temporal probability was also calculated considering different visiting periods (e.g., working days, weekends, holidays), showing significant changes in the risk level among the different visiting periods and with time. Some of the investigated scenarios were within the ALARP zone in the first y

The use of Silicon Photomultipliers (SiPMs) in high radiation environments (e.g. detectors at collider experiments) or in outdoor conditions (e.g. LIDAR applications), requires to deal with a high level of dark count noise. An undesired effect emerging under these conditions is the self-heating of the SiPM due to a large power dissipation that causes variations of the breakdown voltage and thus affects operating parameters such as gain and PDE. A method to evaluate the heat dissipation properties of different SiPM packages and the temperature stability of SiPMs during operation under extremely high dark count rates (larger than 30 GHz) is presented in this paper. Starting from a condition in which the SiPM is at thermal equilibrium with the environment, a change in the current measured under intense illumination with a LED can be attributed to a temperature variation of the SiPM due to self-heating. Under certain assumptions, a quantitative estimate of the local change of temperature can be obtained if certain parameters of the SiPM are known: gain, photon detection efficiency, equivalent charge factor and drift of the SiPM breakdown voltage with temperature. The method is applied to evaluate the thermal conductivity of different SiPM package configurations, which is a key requirement for reliable operation in conditions of extremely high dark count rate. Among the SiPM package configurations tested, the one consisting of a ceramic substrate coupled to a copper heat sink provided the best performance in terms of good heat dissipation with less than 0.5 °C temperature variation for 100 mW dissipated power.

This study presents the findings from several field campaigns carried out in Lake Idro (Northern Italy), a deep (124 m) meromictic-subalpine lake, whose water column is subdivided in a mixolimnion (~0–40 m) and a monimolimnion (~40–124 m). Hydrochemical data highlight two main peculiarities characterizing the Lake Idro meromixis: a) presence of a high manganese/iron ratio (up to 20 mol/mol), b) absence of a clear chemocline between the two main layers. The high manganese content contributed to the formation of a stable manganese dominated deep turbid stratum (40–65 m), enveloping the redoxcline (~45–55 m) in the upper monimolimnion. The presence of this turbid stratum in Lake Idro is described for the first time in this study. The paper examines the distribution of dissolved and particulate forms of transition metals (Mn and Fe), alkaline earth metals (Ca and Mg), and other macro-constituents or nutrients (S, P, NO3-N, NH4-N), discussing their behavior over the redoxcline, where the main transition processes occur. Field measurements and theoretical considerations suggest that the deep turbid stratum is formed by a complex mixture of manganese and iron compounds with a prevalence of Mn(II)/Mn(III) in different forms including dissolved, colloidal, and fine particles, that give to the turbid stratum a white-pink opalescent coloration. The bacteria populations show a clear stratification with the upper aerobic layer dominated by the heterotrophic Flavobacterium sp., the turbid stratum hosting a specific microbiological pool, dominated by Caldimonas sp., and the deeper anaerobic layer dominated by the sulfur-oxidizing and denitrifier Sulfuricurvum sp. The occurrence in August 2010 of an anomalous lake surface coloration lasting about four weeks and developing from milky white-green to red-brown suggests that the upper zone of the turbid stratum could be eroded during intense weather-hydrological conditions with the final red-brown coloration resulting from the oxidatio

Rare event physics demands very detailed background control, high-performance detectors, and custom analysis strategies. Cryogenic calorimeters combine all these ingredients very effectively, representing a promising tool for next-generation experiments. CUPID-0 is one of the most advanced examples of such a technique, having demonstrated its potential with several results obtained with limited exposure. In this paper, we present a further application. Exploiting the analysis of delayed coincidence, we can identify the signals caused by the 220Rn-216Po decay sequence on an event-by-event basis. The analysis of these events allows us to extract the time differences between the two decays, leading to a new evaluation of 216Po half-life, estimated as ms.

Taxonomies are the mainstay of the semantic web as they aim at organising knowledge in concepts linked by IS-A relationships. However, keeping such hierarchies updated and able to represent the domain from which they have been drawn is still a time-consuming, costly and error prone activity. Here, word embeddings have proven to be effective in catching lexicon and semantic similarities to enrich taxonomies from text data. This, in turn, would require to evaluate the generated embeddings to estimate the extent to which they encode the semantic similarity derived from the hierarchy itself. In this paper, we propose and implement MEET-LM, a methodology that aims at generating and evaluating embeddings from a text corpus preserving the co-hyponymy relations synthesised from a domain-specific taxonomy. We apply MEET-LM to a real-life dataset of 2M+ vacancies related to ICT-jobs, framed within the research activities of an EU project that collects millions of Online Job Vacancies and classifies them within the European standard hierarchy ESCO. To show MEET-LM is useful in practice, we also trained a neural network to classify co-hyponym relations using the selected embeddings as features. Our experiments reach 99.4% of accuracy and 86.5% of f1-score.

In this paper we deal with finitely generated superalgebras with superinvolution, satisfying a non-trivial identity, whose multiplicities of the cocharacters are bounded by a constant. Along the way, we prove that the codimension sequence of such algebras is polynomially bounded if and only if their colength sequence is bounded by a constant.

The Lyndon factorization of a word has been largely studied and recently variants of it have been introduced and investigated with different motivations. In particular, the canonical inverse Lyndon factorization ICFL(w) of a word w, introduced in [1], maintains the main properties of the Lyndon factorization since it can be computed in linear time and it is uniquely determined. In this paper we investigate new properties of this factorization with the aim of exploring their use in some classical queries on w. The main property we prove is related to a classical query on words. We prove that there are relations between the length of the longest common prefix (or longest common extension) lcp(x,y) of two different suffixes x,y of a word w and the maximum length M of two consecutive factors of ICFL(w). More precisely, M is an upper bound on the length of lcp(x,y). A main tool used in the proof of the above result is a property that we state for factors mi with nonempty borders in ICFL(w): a nonempty border of mi cannot be a prefix of the next factor mi+1. Another interesting result relates sorting of global suffixes, i.e., suffixes of a word w, and sorting of local suffixes, i.e., suffixes of products of factors in ICFL(w). This is the counterpart for ICFL(w) of the compatibility property, proved in [2,3] for the Lyndon factorization. Roughly, the compatibility property allows us to extend the mutual order between suffixes of products of the (inverse) Lyndon factors to the suffixes of the whole word. The last property we prove focuses on the Lyndon factorizations of a word and its factors. It suggests that the Lyndon factorizations of two words sharing a common overlap could be used to capture the common overlap of these two words.

In this paper we show that the rank of every chiral polytope having a Suzuki group as automorphism group is 3. This gives a positive answer to a conjecture of Isabel Hubard and Dimitri Leemans.

Peucedanum ostruthium (L.) W.D.J.Koch (Apiaceae) is an alpine medicinal plant traditionally used as a panacea to treat various ailments. For the first time, its phytotoxic and nematotoxic properties were investigated. The inhibitory activity toward germination and seedling growth of the weeds Echinochloa oryzoides (Ard.) Fritsch and Lolium multiflorum Lam. was evaluated by two in vitro assays, carried out on filter paper and soil, using different aqueous extract concentrations (1, 10, and 20 %) and 0.25 g of powder of P. ostruthium leaves, inflorescences, and rhizomes. The study showed that all samples were more effective on L. multiflorum than E. oryzoides with p-values = 0.000 on both substrate types. Nevertheless, in all cases, the soil mitigated the P. ostruthium effects. Regarding nematicidal activity, the leaf extract was the most active against larvae and adults of the nematode Panagrolaimus rigidus. According to the motility test, their death was 85.6 ± 2.7 % and 90.5 ± 3.1 % 24 h after treatment. Lastly, NMR and UPLC-HR-MS analyses led to the identification of several compounds in the aqueous extracts, including mono- and di-substituted chlorogenic acids, flavonol glycosides, coumarins, and furanocoumarin glycosides. 5-Caffeoylquinic acid was the most abundant phenolic component in all plant organs.

Natural gas in clathrate hydrates is regarded as a potential energy source that has received increased attention to optimize production strategies with controllable impacts on the environment. This paper investigates possible instability of a gently sloping reservoir of oceanic hydrates induced by gas production using the huff-puff method through a horizontal well. The geomechanical stability of the slope is analyzed within the framework of the limit equilibrium method by considering the dynamic change in the pore pressure and the strength parameters of the slope during gas production. The production process is simulated by a coupled analysis of heat and flow transport considering thermal effects of hydrate dissociation and formation, and the time-dependent pore pressure and strength parameters are attained from this analysis and passed to the slope stability analysis. Parametric studies are performed to screen the optimal production scenario under different site conditions. Being part of the huff-puff production process, thermal stimulation during the huff stage poses a risk of production-induced instability to the slope. Overpressure is the dominant cause for slope failure, and strength reduction due to hydrate dissociation plays a secondary role in the studied scenario. The production-induced slope failure likely takes place at a site with interbedded geological structures that promote overpressure expansion in a laterally extending band beneath the potential failure surface. Thus, the geological structures should be properly modelled in reservoir simulations, as they could impact the production effectiveness and geomechanical response of the reservoir remarkably. This study demonstrates a need for a multi-objective optimization procedure to seek the overall optimal production strategy, since the economically optimal option is not necessarily free of risk of production-induced geo-hazards.

A recent popular approach to portfolio selection aims at diversifying risk by looking for the so called Risk Parity portfolios. These are defined by the condition that the risk contributions of all assets to the global risk of the portfolio are equal. The Risk Parity approach has been originally introduced for the volatility risk measure. In this paper we consider expectiles as risk measures, we refine results on their differentiability and additivity, and we show how to define Risk Parity portfolios when the expectiles are used. Furthermore, we propose three different classes of methods for practically finding Risk Parity portfolios with respect to expectiles, and we compare the accuracy and efficiency of these methods on real-world data. Expectiles are also used as risk measures in the classical risk-return approach to portfolio selection, where we present a new linear programming formulation.

Classification of high-dimensional spectroscopic data is a common task in analytical chemistry. Well-established procedures like support vector machines (SVMs) and partial least squares discriminant analysis (PLS-DA) are the most common methods for tackling this supervised learning problem. Nonetheless, interpretation of these models remains sometimes difficult, and solutions based on feature selection are often adopted as they lead to the automatic identification of the most informative wavelengths. Unfortunately, for some delicate applications like food authenticity, mislabeled and adulterated spectra occur both in the calibration and/or validation sets, with dramatic effects on the model development, its prediction accuracy and robustness. Motivated by these issues, the present paper proposes a robust model-based method that simultaneously performs variable selection, outliers and label noise detection. We demonstrate the effectiveness of our proposal in dealing with three agri-food spectroscopic studies, where several forms of perturbations are considered. Our approach succeeds in diminishing problem complexity, identifying anomalous spectra and attaining competitive predictive accuracy considering a very low number of selected wavelengths.

The reconstruction of individual geometries from medical imaging is quite a standard in the framework of patient-specific medicine. A major drawback in such a context is represented by noise inherent to the data acquisition. Low signal-to-noise ratios can negatively impact extraction algorithms, and result in artefacts or poor quality of the reconstructed meshes. Direct application of numerical methods on such meshes can yield misleading results. Indeed, artefacts and badly shaped elements may corrupt numerical simulations or induce relevant errors in the computation of meaningful geometrical quantities, such as the curvature or the geodesic surface distance. In this paper, we propose a denoising procedure to remove artefacts from a triangular mesh of a three-dimensional closed surface which represents a brain cortex. For this purpose, we combine a smoothing technique (i.e., the Taubin or the HC-Laplacian smoothing) with an edge-flipping algorithm. To control the denoising procedure, we introduce a stopping criterion that takes into account both the improvement of the mesh quality and the loss of volume enclosed by the surface. On a brain cortical surface reconstructed from Magnetic Resonance Imaging (MRI) data, we first perform a tuning analysis of the parameters involved in the smoothing algorithm, then we investigate the effectiveness of the denoising procedure. Finally, as an example of relevant geometrical feature, we study the improvement generated by the proposed algorithm on the computation of the cortical curvature.

In this paper we provide a non-clausal tableau calculus for the minimum satisfiability problem. Moreover we describe how to adapt it to some variants. Our starting point is a calculus for non-clausal maximum satisfiability problem.

Taking into account axial symmetry in the covariance function of a Gaussian random field is essential when the purpose is modelling data defined over a large portion of the sphere representing our planet. Axially symmetric covariance functions admit a convoluted spectral representation that makes modelling and inference difficult. This motivates the interest in devising alternative strategies to attain axial symmetry, an appealing option being longitudinal integration of isotropic random fields on the sphere. This paper provides a comprehensive theoretical framework to model longitudinal integration on spheres through a nonparametric Bayesian approach. Longitudinally integrated covariances are treated as random objects, where the randomness is implied by the randomised spectrum associated with the covariance function. After investigating the topological support induced by our construction, we give the posterior distribution a thorough inspection. A Bayesian nonparametric model for the analysis of data defined on the sphere is described and implemented, its performance investigated by means of the analysis of both simulated and real data sets.