Long short-term memory networks for earthquake detection in Venezuelan regions

Reliable earthquake detection and location algorithms are necessary to properly catalog and analyze the continuously growing seismic records. This paper reports the results of applying Long Short-Term Memory (LSTM) networks to single-station three-channel waveforms for P-wave earthquake detection in western and north central regions of Venezuela. Precisely, we apply our technique to study the seismicity along the dextral strike-slip Boconó and La Victoria - San Sebastián faults, with complex tectonics driven by the interactions between the South American and Caribbean plates.Peer ReviewedPostprint (author's final draft

Variance Loss in Variational Autoencoders

In this article, we highlight what appears to be major issue of Variational Autoencoders, evinced from an extensive experimentation with different network architectures and datasets: the variance of generated data is significantly lower than that of training data. Since generative models are usually evaluated with metrics such as the Frechet Inception Distance (FID) that compare the distributions of (features of) real versus generated images, the variance loss typically results in degraded scores. This problem is particularly relevant in a two stage setting, where we use a second VAE to sample in the latent space of the first VAE. The minor variance creates a mismatch between the actual distribution of latent variables and those generated by the second VAE, that hinders the beneficial effects of the second stage. Renormalizing the output of the second VAE towards the expected normal spherical distribution, we obtain a sudden burst in the quality of generated samples, as also testified in terms of FID.Comment: Article accepted at the Sixth International Conference on Machine Learning, Optimization, and Data Science. July 19-23, 2020 - Certosa di Pontignano, Siena, Ital

CLARIN-IT: State of Affairs, Challenges and Opportunities

This paper gives an overview on the Italian national CLARIN consortium as it currently stands two years after its creation at the end of 2015. It thus discusses the current state of affairs of the consortium on several aspects, especially with regards to members. It also discusses the events and initiatives that have been undertaken, as well as the ones that are planned in the close future. It finally outlines the conclusions of a user survey performed to understand the expectations of a targeted user population and provides indications regarding the next steps planned

Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

A seasonal survey of living benthic foraminifera was performed in 2013 in the Gulf of Trieste (N Adriatic Sea) to compare two marine coastal sites with different degrees of anthropogenic influence. An assessment of ecological quality statuses showed that the station located near the end of an urban pipeline (Ser station), has worse ecological conditions than the site located in a protected marine area (Res station) all year around. Stressed conditions at Ser station were mainly related to high contents of total organic carbon (TOC) and Zn in the bioavailable fraction, which were a limiting factor for the studied foraminiferal communities. Ammonia tepida, Bolivina spp., and Bulimina spp., which characterised this station, were the most tolerant taxa of the studied assemblage. Conversely, Elphidium spp., H. depressula, N. iridea, Quiqueloculina spp., R. nana and Textularia spp., could be considered less tolerant species as they benefitted from the less stressful conditions recorded at Res station, despite slightly higher concentrations of some potentially toxic elements (PTEs), especially Pb, being recorded in this station in comparison to Ser station. Furthermore, foraminiferal assemblages were found to be quite resilient over an annual cycle, being able to recover from a seasonal unbalanced state to a mature one. The beginning of spring and latest summer would be the best period to assess the ecological quality status to avoid any under- or overestimation of the health of the environment

A CONTENT-BASED IMMERSIVE EXPERIENCE OF BASILICA OF SANT'AMBROGIO IN MILAN: FROM 3D SURVEY TO VIRTUAL REALITY

One of the challenges of the Digital Cultural Heritage (DCH) field is the creation of coherent HBIMs and the dissemination of the collected historical data. The latest development of new technologies has the great potential to realise virtual content-based immersive experiences that are easily available by both experts and non-expert users. On the other hand, they require specific skills and a holistic approach to the study of the building that involves different disciplines.The research that has been carried out for the last five years on one of the greatest monuments in Milan, the Basilica of Sant'Ambrogio, adopted this comprehensive methodology. Although the church is a very well-known building, its turbulent history remains in a certain aspect hidden to the large public. This paper shows the workflow that has been developed for the Basilica, starting from the 3D survey to the historical data acquisition and the study on the church itself, based on a ‘virtual subtraction process’, till the creation of a Virtual Reality experience. This one is the first step of a wider project on eXtended reality (Virtual/Mixed/Augmented Reality) that intends to make the gathered knowledge of the Basilica available to the public.</p

Contribution of X-ray Fluorescence Techniques in Cultural Heritage Materials Characterisation

Archaeometry and cultural heritage have lately taken advantage of developments in scientific techniques, offering valuable information to archaeology, art history, and conservation science, involving both instrumental and non-instrumental approaches. Among the possible techniques, X-Ray fluorescence (XRF) has become one of the most applied techniques for cultural heritage elemental material characterization due to its user friendliness; fast, short acquisition times; portability; and most of all, its absolutely non-destructive nature. For this reason, besides being often a first choice for a preliminary overall materials investigation, XRF spectrometers and spectra data handling methods have continuously improved, giving rise to many variations of the same technique; portable spectrometers, micro-probes, and large area scanners are all variations of a very flexible technique. This Special Issue collects papers dealing with most of the analytical techniques related to XRF spectroscopy appropriate for applications to Cultural Heritage materials. We dedicate this Special Issue to the loving memory of Professor Mario Milazzo, a pioneer of Archaeometry in Italy, awarded in 2002 the Gold Medal for Culture by the Italian President. He is remembered as a generous and pleasant man with an insightful, logical mind, who was able to find an appropriate joke for every situation. Many of us following his footsteps in the research field of applied physics for Cultural Heritage still appreciate his vision, teaching, and impact on our lives

Balancing reconstruction error and Kullback-Leibler divergence in Variational Autoencoders

In the loss function of Variational Autoencoders there is a well known tension between two components: the reconstruction loss, improving the quality of the resulting images, and the Kullback-Leibler divergence, acting as a regularizer of the latent space. Correctly balancing these two components is a delicate issue, easily resulting in poor generative behaviours. In a recent work, Dai and Wipf obtained a sensible improvement by allowing the network to learn the balancing factor during training, according to a suitable loss function. In this article, we show that learning can be replaced by a simple deterministic computation, helping to understand the underlying mechanism, and resulting in a faster and more accurate behaviour. On typical datasets such as Cifar and Celeba, our technique sensibly outperforms all previous VAE architectures

Comparing the latent space of generative models

Different encodings of datapoints in the latent space of latent-vector generative models may result in more or less effective and disentangled characterizations of the different explanatory factors of variation behind the data. Many works have been recently devoted to the explorationof the latent space of specific models, mostly focused on the study of how features are disentangled and of how trajectories producing desired alterations of data in the visible space can be found. In this work we address the more general problem of comparing the latent spaces of different models, looking for transformations between them. We confined the investigation to the familiar and largely investigated case of generative models for the data manifold of human faces. The surprising, preliminary result reported in this article is that (provided models have not been taught or explicitly conceived to act differently) a simple linear mapping is enough to pass from a latent space to another while preserving most of the information

Design of novel delivery systems to probe alternative routes of administration for a self-amplifying RNA rabies vaccine

Current vaccine design aims to develop safer vaccines based on one or few selected antigens. RNA-based vaccines can be engineered to encode any antigen of interest and have the potential for rapid, inexpensive and scalable manufacturing and have an acceptable safety profile. Moreover, they enable in situ antigen expression, mimicking a real viral infection hence eliciting robust humoral and cellular-mediated immune responses. RNA vaccines therefore represent a versatile tool to fight infectious diseases and emerging pathogens effectively and rapidly. Furthermore, the antigen can be designed in a self-amplifying RNA (SAM) to enhance the immunogenicity and to reduce the therapeutic dose compared to conventional non-amplifying mRNA vaccines.;RNAs can be encapsulated in delivery systems to protect them against degradation upon injection and to facilitate their delivery in host cells. Among them, lipid-based delivery systems and, more specifically, lipid nanoparticles (LNPs) are efficient non-viral delivery systems for RNA and SAM vaccines. Within this thesis, a panel of cationic LNPs (cLNPs), based on existing cationic lipids (e.g. DOTAP and DDA), was designed to deliver a SAM vaccine. The rabies virus was used as a model, as there is an established correlate of protection (neutralising antibodies) and there exist efficacious vaccines in the market (e.g. Rabipur) to be used as comparators. To this end, a SAM vaccine encoding the rabies virus glycoprotein (RVG), the only target for neutralising antibodies, was used;Microfluidics-based methods for producing cLNPs of desired physicochemical properties were developed and optimal operating parameters (e.g. total flow rate and flow rate ratio) were established. Most promising SAM-cLNP candidates were chosen according to their physicochemical attributes, their ability to protect SAM from enzymatic degradation and their capacity to associate with cells and to induce antigen expression. These formulations were well retained at the injection site when administered intramuscularly or intradermally, while they were rapidly cleared following intranasal administration.;On the other hand, SAM-cLNPs induced protective levels of anti-RVG antibodies following intramuscular injection in mice and RVG-specific polyfunctional T cell responses even with a dose as low as 0.15 μg RVG-SAM. Remarkably, the immune responses elicited by SAM-cLNPs were comparable to Rabipur, a commercial vaccine based on an inactivated rabies virus, and a cationic nanoemulsion, a safe and well-established SAM delivery system which is currently being investigated in a phase I clinical trial in humans (as of September 2019). Intradermal administration of SAM-cLNPs resulted in similar humoral and cell-mediated immune responses, while significantly weaker immune responses were achieved when administered intranasally.Current vaccine design aims to develop safer vaccines based on one or few selected antigens. RNA-based vaccines can be engineered to encode any antigen of interest and have the potential for rapid, inexpensive and scalable manufacturing and have an acceptable safety profile. Moreover, they enable in situ antigen expression, mimicking a real viral infection hence eliciting robust humoral and cellular-mediated immune responses. RNA vaccines therefore represent a versatile tool to fight infectious diseases and emerging pathogens effectively and rapidly. Furthermore, the antigen can be designed in a self-amplifying RNA (SAM) to enhance the immunogenicity and to reduce the therapeutic dose compared to conventional non-amplifying mRNA vaccines.;RNAs can be encapsulated in delivery systems to protect them against degradation upon injection and to facilitate their delivery in host cells. Among them, lipid-based delivery systems and, more specifically, lipid nanoparticles (LNPs) are efficient non-viral delivery systems for RNA and SAM vaccines. Within this thesis, a panel of cationic LNPs (cLNPs), based on existing cationic lipids (e.g. DOTAP and DDA), was designed to deliver a SAM vaccine. The rabies virus was used as a model, as there is an established correlate of protection (neutralising antibodies) and there exist efficacious vaccines in the market (e.g. Rabipur) to be used as comparators. To this end, a SAM vaccine encoding the rabies virus glycoprotein (RVG), the only target for neutralising antibodies, was used;Microfluidics-based methods for producing cLNPs of desired physicochemical properties were developed and optimal operating parameters (e.g. total flow rate and flow rate ratio) were established. Most promising SAM-cLNP candidates were chosen according to their physicochemical attributes, their ability to protect SAM from enzymatic degradation and their capacity to associate with cells and to induce antigen expression. These formulations were well retained at the injection site when administered intramuscularly or intradermally, while they were rapidly cleared following intranasal administration.;On the other hand, SAM-cLNPs induced protective levels of anti-RVG antibodies following intramuscular injection in mice and RVG-specific polyfunctional T cell responses even with a dose as low as 0.15 μg RVG-SAM. Remarkably, the immune responses elicited by SAM-cLNPs were comparable to Rabipur, a commercial vaccine based on an inactivated rabies virus, and a cationic nanoemulsion, a safe and well-established SAM delivery system which is currently being investigated in a phase I clinical trial in humans (as of September 2019). Intradermal administration of SAM-cLNPs resulted in similar humoral and cell-mediated immune responses, while significantly weaker immune responses were achieved when administered intranasally

The relationship between urinary organophosphate pesticide metabolites and asthma-related outcomes at 12-month follow-up in school children residing in informal settlements in the Western Cape

Background: Evidence on the relationship between pesticide exposure and respiratory outcomes is mostly from farm workers. In most settings, poor /rich there is limited information on non-agricultural settings, particularly in children. Objective: This study investigated the relationship between urinary concentrations of the organophosphate pesticide (OP) metabolites and asthma-related outcomes among schoolchildren in four informal settlements in the Western Cape in South Africa. Methods: This study was a longitudinal study of 590 schoolchildren, with a 12-month follow up period. A standardised questionnaire adopted from the International Study of Asthma and Allergies in Childhood (ISAAC) was administered to caregivers for child's respiratory symptoms and household characteristics. Spirometry and fractional-exhaled nitric oxide (FeNO), including a phadiatop test (atopy status) and urinary dialkyl phosphate (DAP) metabolites diethylphosphate (DEP), dimethylthiophosphate (DMTP)] were measured at baseline and follow-up. Dimethylphosphate (DMP) was measured only at baseline. Results: Mean ages of schoolchildren were (9.9 ± 0.91 years) and median DAP was 32.9 ng/ml (18.4 – 52.9 ng/ml) at baseline. Incidence proportions of new asthma outcome cases at 12- months were 2.2 % doctor diagnosed asthma, 17.8 % asthma-symptom score ≥ 2, 14.5 % forced expiratory volume 1< lower limit of normal, and 5.9 % airway inflammation across all areas. In the linear mixed and fixed effect model, no consistent patterns of increased risk of new asthma-associated outcomes at the 12-month was found. However, there was a significant increase in airway inflammation (β:2.99 (95% CI: 0.48 - 5.50) in the 3rd DEP quintile (1.9 – 3.0 ng/mL) compared to the reference quintile (1.10 ng/ml). Conclusion: DAP concentrations among school children were found to be higher than those of children in other settings. However, the study did not find consistent associations between urinary concentrations of DAP metabolites and asthma related outcomes over a 12-month follow-up period among schoolchildren. Future studies with a longer follow-up period and repeated OP pesticide biomonitoring are recommended