SEISMIC RELIABILITY-BASED DESIGN OF STRUCTURES EQUIPPED WITH DFPS

This work deals with seismic reliability-based design (SRBD) for softening and hardening structures equipped with double friction pendulum system (DFPS) isolators. The isolated system is represented by means of an equivalent 3dof model having a softening/hardening post-yield slope for the superstructure and velocity-dependent rules for the two surfaces of the DFP devices. The yielding characteristics of the superstructures are defined in compli-ance with the seismic hazard of L’Aquila site (Italy) and with NTC18 assuming ordinary characteristics. Considering several natural seismic records and the relevant random varia-bles, incremental dynamic analyses are carried out for assessing the seismic fragility and the seismic reliability of these systems. Finally, seismic reliability-based design (SRBD) curves for these systems are proposed

Seismic reliability-based design of softening structures equipped with double sliding devices

This study deals with seismic reliability-based design (SRBD) relationships in terms of beha-vior factors and displacement demands for softening structures equipped with double friction pendulum system (DFPS) bearings. An equivalent 3dof system having a softening post-yield slope is adopted to describe the superstructure behavior, whereas velocity-dependent laws are assumed to model the responses of the two surfaces of the DFPS. The yielding characte-ristics of the superstructures are defined for increasing behavior factors in compliance with the seismic hazard of L’Aquila site (Italy) and with NTC18 assuming a lifetime of 50 years. Considering several natural seismic records and building properties under the hypothesis of modelling the friction coefficients of the two surfaces of the DFPS as random variables, in-cremental dynamic analyses are performed to evaluate the seismic fragility and the seismic reliability of these systems. Finally, seismic reliability is assessed and seismic reliability-based design (SRBD) curves for the two surfaces of the double sliding devices are described

Fine-tuning or top-tuning? Transfer learning with pretrained features and fast kernel methods

The impressive performances of deep learning architectures is associated to massive increase of models complexity. Millions of parameters need be tuned, with training and inference time scaling accordingly. But is massive fine-tuning necessary? In this paper, focusing on image classification, we consider a simple transfer learning approach exploiting pretrained convolutional features as input for a fast kernel method. We refer to this approach as top-tuning, since only the kernel classifier is trained. By performing more than 2500 training processes we show that this top-tuning approach provides comparable accuracy w.r.t. fine-tuning, with a training time that is between one and two orders of magnitude smaller. These results suggest that top-tuning provides a useful alternative to fine-tuning in small/medium datasets, especially when training efficiency is crucial

Efficient Unsupervised Learning for Plankton Images

Monitoring plankton populations in situ is fundamental to preserve the aquatic ecosystem. Plankton microorganisms are in fact susceptible of minor environmental perturbations, that can reflect into consequent morphological and dynamical modifications. Nowadays, the availability of advanced automatic or semi-automatic acquisition systems has been allowing the production of an increasingly large amount of plankton image data. The adoption of machine learning algorithms to classify such data may be affected by the significant cost of manual annotation, due to both the huge quantity of acquired data and the numerosity of plankton species. To address these challenges, we propose an efficient unsupervised learning pipeline to provide accurate classification of plankton microorganisms. We build a set of image descriptors exploiting a two-step procedure. First, a Variational Autoencoder (VAE) is trained on features extracted by a pre-trained neural network. We then use the learnt latent space as image descriptor for clustering. We compare our method with state-of-the-art unsupervised approaches, where a set of pre-defined hand-crafted features is used for clustering of plankton images. The proposed pipeline outperforms the benchmark algorithms for all the plankton datasets included in our analysis, providing better image embedding properties

Seismic reliability-based design of hardening structures equipped with double sliding devices

This study deals with seismic reliability-based design (SRBD) relationships in terms of beha-vior factors and displacement demands for hardening structures equipped with double fric-tion pendulum system (DFPS) bearings. An equivalent 3dof system having a hardening post-yield slope is adopted to describe the superstructure behavior, whereas velocity-dependent laws are assumed to model the responses of the two surfaces of the DFPS. The yielding cha-racteristics of the superstructures are defined for increasing behavior factors in compliance with the seismic hazard of L’Aquila site (Italy) and with NTC18 assuming a lifetime of 50 years. Considering several natural seismic records and building properties under the hypo-thesis of modelling the friction coefficients of the two surfaces of the DFPS as random variables, incremental dynamic analyses are performed to evaluate the seismic fragility and the seismic reliability of these systems. Finally, seismic reliability is evaluated and seismic relia-bility-based design (SRBD) curves for the two surfaces of the double sliding devices are de-scribed

Environmental pollution from illegal waste disposal and health effects: A review on the triangle of Death.

The term “triangle of death” was used for the first time by Senior and Mazza in the journal The Lancet Oncology referring to the eastern area of the Campania Region (Southern Italy) which has one of the worst records of illegal waste dumping practices. In the past decades, many studies have focused on the potential of illegal waste disposal to cause adverse effects on human health in this area. The great heterogeneity in the findings, and the bias in media communication has generated great healthcare doubts, anxieties and alarm. This paper addresses a review of the up-to-date literature on the “triangle of death”, bringing together the available information on the occurrence and severity of health effects related to illegal waste disposal. The Scopus database was searched using the search terms “waste”, “Campania”, “Naples”, “triangle of death” and “human biomonitoring”. Despite the methodological and sampling heterogeneity between the studies, this review examines the evidence from published data concerning cancer incidence, childhood mortality and birth defects, so that the current situation, knowledge gaps and research priorities can be established. The review aims to provide a contribution to the scientific community, and to respond to the concerns of the general population

Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors

In this paper, we address the Sim2Real gap in the field of vision-based tactile sensors for classifying object surfaces. We train a Diffusion Model to bridge this gap using a relatively small dataset of real-world images randomly collected from unlabeled everyday objects via the DIGIT sensor. Subsequently, we employ a simulator to generate images by uniformly sampling the surface of objects from the YCB Model Set. These simulated images are then translated into the real domain using the Diffusion Model and automatically labeled to train a classifier. During this training, we further align features of the two domains using an adversarial procedure. Our evaluation is conducted on a dataset of tactile images obtained from a set of ten 3D printed YCB objects. The results reveal a total accuracy of 81.9%, a significant improvement compared to the 34.7% achieved by the classifier trained solely on simulated images. This demonstrates the effectiveness of our approach. We further validate our approach using the classifier on a 6D object pose estimation task from tactile data.Comment: 6 pages, submitted to ICRA 202

Self-administration of omalizumab: why not? A literature review and expert opinion

Introduction: Omalizumab is used to treat severe uncontrolled allergic asthma and chronic spontaneous urticaria (CSU), and is approved for self-administration in prefilled syringes. It is thus important to understand the advantages, critical issues, and indications for home administration.Areas covered: The present review summarizes the available evidence on home administration of omalizumab in asthma and CSU to illustrate the advantages derived from self-administration of patients in this setting.Expert opinion: The available data suggest that patients can safely administer biologics at home with suitable training, and that home administration is time saving and cost-effective. The majority of patients with severe asthma or CSU treated with omalizumab are likely to be suitable candidates for self-administration, which can be proposed to anyone that the clinician deems suitable. In addition to clinicians, pharmacists can also play a key role in managing patients who are prescribed home administration. A practical flow chart is proposed on selection of patients and their management during home administration. Self-administration of biologics can be considered as a valid alternative to traditional injections in a clinical setting, and the evidence has shown that no major issues need to be overcome in terms of safety or efficacy

The contribution to policies of an exposome-based approach to childhood obesity

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Identification of single nucleotide polymorphisms in Toll-like receptor candidate genes associated with tuberculosis infection in water buffalo (Bubalus bubalis)

Toll-like receptors play a key role in innate immunity by recognizing pathogens and activating appropriate responses. Pathogens express several signal molecules (pathogen-associated molecular patterns, PAMPs) essential for survival and pathogenicity. Recognition of PAMPs triggers an array of anti-microbial immune responses through the induction of various inflammatory cytokines. The objective of this work was to perform a case-control study to characterize the distribution of polymorphisms in three candidate genes (toll-like receptor 2, toll-like receptor 4, toll-like receptor 9) and to test their role as potential risk factors for tuberculosis infection in water buffalo (Bubalus bubalis)