Dynamic Tests on a Steel Frame Equipped with Hysteretic and Visco-Re-Centring Energy Dissipating Bracing Systems

Abstract An extensive program of dynamic experimental tests, named JetPacs (Joint Experimental Testing on Passive and semiActive Control Systems), has been carried out at the Structural Laboratory of the University of Basilicata considering a 1:1.5 scaled three-dimensional steel frame, derived from a 2-storey, 1-bay prototype building. The JetPacs Project was developed within the RELUIS 2005-08 project, founded by Italian Dept. of Civil Protection. This work refers to the experimental tests on the model equipped with two different EDB systems based on Hysteretic Dampers (HD) and visco-re-centering devices (SMA+VD). The devices were designed with the purpose of limiting the inter-storey drifts so that the frame yielding is surely prevented. The visco-re-centering device was obtained by coupling Viscous Dampers (VD), with re-centering device based on shape memory alloy (SMA) wires, while the Hysteretic Damper was constituted by low-carbon U-shaped steel plates. The main objective of this paper is to compare the seismic response of the structure with SMA+VD and HD EDB's in order to calibrate a new performance based design procedure for the evaluation of the mechanical characteristics of SMA+VD devices. In this paper, the experimental results of the shaking table tests, in terms of comparison of both design solutions which lead to a comparable level of protection for the framed structure, are shown. The results obtained by numerical nonlinear time history analysis (NTHA) of both design solutions are also showed and compared with experimental ones

Small-scale distribution of metazoan meiofauna and sedimentary organic matter in subtidal sandy sediments (Mediterranean Sea)

While variations in sedimentary organic matter (OM) quantity, biochemical composition and nutritional quality as well as in meiofaunal abundance and assemblage composition at the macro- and mesoscale are relatively well known, information about variations at the microscale is much scarcer. To shed some light on this issue, we tested the null hypothesis by which abundance and composition of the meiofaunal assemblages, and the quantity, biochemical composition and nutritional quality of sedimentary organic matter in coastal shallow environments do not vary within a frame of 1 m2. No significant variation within the frame emerged for OM quantity, nutritional quality, biochemical composition and the abundance of meiofaunal assemblages. On the other hand, the composition of meiofaunal assemblages varied significantly within the frame and exhibited a clear segregation of assemblages farther to the shore, as a likely result of local micro-hydrodynamic conditions. Spatial autocorrelation analysis revealed that lipid and protein sedimentary contents had a random distribution, whereas carbohydrate and biopolymeric C contents and meiofaunal total abundance were characterized by a patchy distribution, with discrete peaks within the sub-frame squares (ca. 0.1 m2). Phytopigments showed a spatial positive autocorrelation distribution, following the micro-hydrodynamic pattern, with patches larger than the sub-frame square, but smaller than the entire one (1 m2). Overall, our results suggest that, within 1 m2 of subtidal sandy sediments, three replicates could be sufficient to assess correctly OM attributes and the abundance of meiofauna, but could be possibly inadequate for assessing meiofaunal assemblages’ composition at a finer scale (<1 m2)

Evaluating the autonomy of children with autism spectrum disorder in washing hands: A deep-learning approach

Monitoring children with Autism Spectrum Dis-order (ASD) during the execution of the Applied Behaviour Analysis (ABA) program is crucial to assess the progresses while performing actions. Despite its importance, this monitoring procedure still relies on ABA operators' visual observation and manual annotation of the significant events. In this work a deep learning (DL) based approach has been proposed to evaluate the autonomy of children with ASD while performing the hand-washing task. The goal of the algorithm is the automatic detection of RGB frames in which the ASD child washes his/her hands autonomously (no-aid frames) or is supported by the operator (aid frames). The proposed approach relies on a pre-trained VGG16 convolutional network (CNN) modified to fulfill the binary classification task. The performance of the fine-tuned VGG16 was compared against that of other CNN architectures. The fine-tuned VGG16 achieved the best performance with a recall of 0.92 and 0.89 for the no-aid and aid class, respectively. These results prompt the possibility of translating the presented methodology into the actual monitoring practice. The integration of the presented tool with other computer-aided monitoring systems into a single framework, will provide fully support to ABA operators during the therapy session

Nutritional quality of pasta sold on the italian market: The food labelling of italian products (FLIP) study

Pasta represents a staple food in many populations and, in recent years, an increasing number of pasta items has been placed on the market to satisfy needs and trends. The aims of this work were: (i) to investigate the nutritional composition of the different types of pasta currently sold in Italy by collecting the nutrition facts on their packaging; (ii) to compare energy, nutrient and salt content per 100 g and serving in fresh and dried pasta; (iii) to compare the nutrition declaration in pairs of products with and without different declarations (i.e., gluten free (GF), organic, and nutrition claims (NC)). A total of 756 items, made available by 13 retailers present on the Italian market, were included in the analysis. Data showed a wide difference between dried and fresh pasta, with high inter-type variability. A negligible amount of salt was observed in all types of pasta, except for stuffed products, which had a median high quantity of salt (>1 g/100 g and ~1.5 g/serving). Organic pasta had higher fibre and lower protein contents compared to conventional pasta. GF products were higher in carbohydrate and fat but lower in fibre and protein than not-GF products, while only a higher fibre content was found in pasta with NC compared to products not boasting claims. Overall, the results show high variability in terms of nutrition composition among the pasta items currently on the market, supporting the importance of reading and understanding food labels for making informed food choices

Insights into the G-rich VEGF-binding aptamer V7t1: when two G-quadruplexes are better than one!

The G-quadruplex-forming VEGF-binding aptamer V7t1 was previously found to be highly polymorphic in a K+-containing solution and, to restrict its conformational preferences to a unique, well-defined form, modified nucleotides (LNA and/or UNA) were inserted in its sequence. We here report an in-depth biophysical characterization of V7t1 in a Na+-rich medium, mimicking the extracellular environment in which VEGF targeting should occur, carried out combining several techniques to analyse the conformational behaviour of the aptamer and its binding to the protein. Our results demonstrate that, in the presence of high Na+ concentrations, V7t1 behaves in a very different way if subjected or not to annealing procedures, as evidenced by native gel electrophoresis, size exclusion chromatography and dynamic light scattering analysis. Indeed, not-annealed V7t1 forms both monomeric and dimeric G-quadruplexes, while the annealed oligonucleotide is a monomeric species. Remarkably, only the dimeric aptamer efficiently binds VEGF, showing higher affinity for the protein compared to the monomeric species. These findings provide new precious information for the development of improved V7t1 analogues, allowing more efficient binding to the cancer-related protein and the design of effective biosensors or theranostic devices based on VEGF targeting

Towards realistic laparoscopic image generation using image-domain translation

Background and ObjectivesOver the last decade, Deep Learning (DL) has revolutionized data analysis in many areas, including medical imaging. However, there is a bottleneck in the advancement of DL in the surgery field, which can be seen in a shortage of large-scale data, which in turn may be attributed to the lack of a structured and standardized methodology for storing and analyzing surgical images in clinical centres. Furthermore, accurate annotations manually added are expensive and time consuming. A great help can come from the synthesis of artificial images; in this context, in the latest years, the use of Generative Adversarial Neural Networks (GANs) achieved promising results in obtaining photo-realistic images. MethodsIn this study, a method for Minimally Invasive Surgery (MIS) image synthesis is proposed. To this aim, the generative adversarial network pix2pix is trained to generate paired annotated MIS images by transforming rough segmentation of surgical instruments and tissues into realistic images. An additional regularization term was added to the original optimization problem, in order to enhance realism of surgical tools with respect to the background. Results Quantitative and qualitative (i.e., human-based) evaluations of generated images have been carried out in order to assess the effectiveness of the method. ConclusionsExperimental results show that the proposed method is actually able to translate MIS segmentations to realistic MIS images, which can in turn be used to augment existing data sets and help at overcoming the lack of useful images; this allows physicians and algorithms to take advantage from new annotated instances for their training

Outcomes of feeding activity of the sea cucumber Holothuria tubulosa on quantity, biochemical composition, and nutritional quality of sedimentary organic matter

Introduction: Holothuria tubulosa is one of the most common sea cucumbers in the Mediterranean Sea, generally associated with organically enriched coastal sediments and seagrass beds. As a deposit-feeder, it is responsible for strong bioturbation processes and plays a putative key role in sedimentary carbon cycling and benthic trophodynamics. With the aim of exploring the potential use of holothuroids as a tool for remediating eutrophicated sediments, we investigated the effects of H. tubulosa on sedimentary organic matter quantity, biochemical composition, and nutritional quality. Methods: Holothuroids and associated samples of ambient sediments were collected in two sites located in the Central-Western Mediterranean Sea (Sardinia, Italy) and characterized by different trophic status backgrounds: the site of Oristano characterized by sandy-muddy sediments and the presence of mariculture plants (ranked as meso-eutrophic) and the site of Teulada characterized by sandy sediments and Posidonia oceanica meadows (ranked as oligo-mesotrophic). We compared the biochemical composition (proteins, carbohydrates, lipids) of ambient sediment vs sea cucumbers feces and the sedimentary protein content vs protein content in the sediments retrieved in different gut sections (esophagus, mid gut, end gut) of the holothuroid. Results: Our results reveal that holothuroids feeding on meso-eutrophic sediments can increase protein (1.5 times) and lipid (1.3 times) content through their defecation, thus making these substrates a more labile food source for other benthic organisms. We report here that H. tubulosa feeding on meso-eutrophic sediment is most likely able to actively select particles rich in labile organic matter with buccal tentacles, as revealed by the protein content in the esophagus that is up to 2-folds higher than that in the source sediment. According to the inverse relationship between assimilation rates and availability of organic substrates and the optimal foraging theory, H. tubulosa feeding on oligo-mesotrophic sediments showed potential assimilation of proteins ca. 25% higher than that of specimens feeding on meso-eutrophic sediments. Discussion: Our results reveal that H. tubulosa feeding on meso-eutrophic sediments can profoundly influence the benthic trophic status, specifically modifying the biochemical composition and nutritional quality of organic matter, thus paving the way to its possible use in bioremediation actions of eutrophicated sediments and in Integrated Multi-Trophic Aquaculture systems

Deep Learning Based Robotic Tool Detection and Articulation Estimation with Spatio-Temporal Layers

Surgical-tool joint detection from laparoscopic images is an important but challenging task in computer-assisted minimally invasive surgery. Illumination levels, variations in background and the different number of tools in the field of view, all pose difficulties to algorithm and model training. Yet, such challenges could be potentially tackled by exploiting the temporal information in laparoscopic videos to avoid per frame handling of the problem. In this letter, we propose a novel encoder-decoder architecture for surgical instrument joint detection and localization that uses three-dimensional convolutional layers to exploit spatio-temporal features from laparoscopic videos. When tested on benchmark and custom-built datasets, a median Dice similarity coefficient of 85.1% with an interquartile range of 4.6% highlights performance better than the state of the art based on single-frame processing. Alongside novelty of the network architecture, the idea for inclusion of temporal information appears to be particularly useful when processing images with unseen backgrounds during the training phase, which indicates that spatio-temporal features for joint detection help to generalize the solution

Ulva as potential stimulant and attractant for a valuable sea urchin species: a chemosensory study

The green seaweed Ulva is close to becoming popular due to its suitability as potential feedstock production and for food items. However, there is a general lack of studies on the aversion or acceptability of this alga by marine organisms, particularly on its role as a chemoattractant and/or phagostimulant activity. Here we tested the effect of Ulva compressa and other biochemicals as potential chemostimulating compounds for a valuable sea urchin species, Paracentrotus lividus, selected as model species for our tests. Sea urchins’ chemical sensitivity was estimated by analysing movements of spines, pedicellariae, tube feet, and individual locomotion using an innovative bioassay. Our results showed that all forms of Ulva (fresh, defrosted, and fragmented) resulted in an effective stimulus, evoking in sea urchins strong responses with robust activation of spines and tube feet, where the defrosted one was the most stimulating. Among the amino acids tested, glycine, alanine, and glutamine produced a significant response, highlighting for the latter a concentration–response relationship. Sea urchins responded to glucose, not to fructose and sucrose. Spirulina resulted as the most effective stimulus, acting in a dose-dependent manner. Major results indicate the role of Ulva as a chemostimulant and strongly attractant for such herbivore species. From an applied point of view, the presence of potential Ulva’s feed-related compounds, acting as chemoattractants (to reduce food searching time) and/or feeding stimulants (to stimulate ingestion), would improve the several applications of Ulva in the formulation of the feeds for sustainable aquacultur

Chestnut Wood Mud as a Source of Ellagic Acid for Dermo-Cosmetic Applications

Ellagic acid (EA) has long been recognized as a very active antioxidant, anti-inflammatory, and antimicrobial agent. However, its low bioavailability has often hampered its applications in health-related fields. Here, we report a phospholipid vesicle-based controlled release system for EA, involving the exploitation of chestnut wood mud (CWM), an industrial by-product from chestnut tannin production, as a largely available and low-cost source of this compound. Two kinds of CWM with different particle size distributions, indicated as CWM-A and CWM-B (<100 and 32 µm, respectively), containing 5 ± 1% w/w EA, were incorporated into transfersomes. The latter were small in size (~100 nm), homogeneously dispersed, and negatively charged. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing/antioxidant power (FRAP) assays indicated up to three-fold improvement in the antioxidant properties of CWM upon incorporation into transfersomes. The kinetics of EA released under simulated physiological conditions were evaluated by UV-Vis spectroscopy and HPLC analysis. The best results were obtained with CWM-B (100% of EA gradually released after 37 days at pH 7.4). A stepwise increase in the antioxidant properties of the released material was also observed. Cell-based experiments confirmed the efficacy of CWM-B transfersomes as antioxidant agents in contrasting photodamage