a pore water pressure model calibration based on in situ test results

Abstract This paper proposes a procedure for the calibration of a simplified pore water pressure model implemented in 1D effective stress dynamic analyses. The calibration procedure is based on the cyclic strength of the soils as quantified using empirical correlations with in-situ tests, CPT and SPT. Specific relationships have been directly defined among the parameters of the pore water pressure model and the results of in-situ tests. All the steps for the definition of these relationships are described in detail. The proposed calibration procedure has been used to simulate the seismic response of two well-documented reclaimed sites where widespread liquefaction occurred: Port Island, in Kobe (Japan) and Treasure Island in California (US), struck by the 1995 Kobe and the 1989 Loma Prieta earthquakes, respectively. The results of the analyses have been compared to the actual site response as recorded by downhole acceleration arrays, showing that the proposed approach leads to a good estimate of the site response. Guidelines for calibration of the proposed model are finally provided, and the advantages and limitations of its use are discussed in detail

Ricognizione e documentazione di materiali archeologici dai contesti funerari ateniesi dall’Età del Bronzo finale alla Prima età del Ferro

Resoconto attività di ricerca 201

Postharvest UV-B exposure drives changes in primary metabolism, phenolic concentration, and volatilome profile in berries of different grape (Vitis vinifera L.) varieties

BACKGROUND The ultraviolet-B (UV-B) radiation can alter grape metabolism during berry development, but little is known on the effect of postharvest UV-B exposure. In this study, we evaluated the effect of postharvest UV-B exposure on berry primary and secondary metabolites in four grapevine varieties (Aleatico, Moscato bianco, Sangiovese, and Vermentino) in order to evaluate the possibility to increase the grape quality and its nutraceutical properties. RESULTS The treatment did not significantly affect the berry primary metabolism in terms of organic acids, carbohydrates, and amino acids profile, regardless of the variety. UV-B exposure reduced the total anthocyanin content, particularly the tri-substituted and di-substituted forms in Aleatico and Sangiovese, respectively. An overall negative effect of UV-B irradiation on the flavonols profile of Aleatico, Moscato bianco, and Vermentino berries was found, whereas it enhanced the quercetin, myricetin and kaempferol concentration in Sangiovese. The free fraction of berry volatile organic compounds increased in UV-B-treated Aleatico and Moscato bianco berries, especially C-13-norisoprenoids and volatile phenols, as well as key monoterpenes, such as the linalool derivatives. However, higher concentrations of glycosylated monoterpenes and C-13-norisoprenoids were measured in Sangiovese and Vermentino berries treated with UV-B. CONCLUSION This study provides new insights on the effect of postharvest UV-B radiation on berry secondary metabolism, highlighting a different modulation between varieties and suggesting the potential use of this technique to increase some nutraceutical and quality characteristics of grape berry

Axillary Ectopic Carcinoma of the Breast. Report of Two Cases with Different Clinical Presentation and Review of the Literature.

Aims: Primary ectopic breast cancer (PEBC) is a rare and often misdiagnosed condition. Through the discussion of two clinical cases, we want to focus on clinical presentation, outcomes and treatment of PEBC, to lead clinicians to awareness and optimal management. Methods: We present the case of a 47-year-old patient, with a 30 mm axillary mass, that was diagnosed as a PEBC (infiltrating lobular carcinoma, triple negative). The patient underwent systemic staging: diffuse metastatic bone lesions and leptomeningeal metastasis were found. The second patient is a 73-year-old woman with personal history of right breast tumor. She came to our attention for a 9 mm left axillary mass, suspicious for a metastatic lymph node. A fine-needle cytology revealed the absence of lymphoid cells but the presence of atypical epithelial cells, as in a primary breast carcinoma. She was treated with local excision and sentinel node biopsy. Results: The first patient presented with metastatic disease at the time of diagnosis and she deceased after three months from the diagnosis, despite systemic chemotherapy. The diagnosis was performed at an early stage in the second patient. She underwent surgery, complementary endocrine therapy and radiotherapy. She has no evident disease after two years from surgery. Conclusion: Primary ectopic breast cancer is a rare clinical entity, often misdiagnosed or diagnosed with a long delay. The treatment of PEBC is analogous to that of orthotopic breast cancer, but we strongly recommend to approach the patient with a multidisciplinary team to provide the best staging workout and therapie

Intra-varietal variability of Romanesco variety (Vitis vinifera L.)

Most historical sources that describe the presence of Romanesco variety in vine-growing areas of Lazio Region (Italy) highlighted the variability of morphological traits within the variety. This partly justifies the presence of different synonyms, true or presumed, reported by many authors for this grape variety. With the aim of analysing this variability, eight accessions related to the variety, collected in Lazio Region and grown in the DAFNE grape germplasm collection, have been characterized over five productive seasons. The ampelographic description was carried out using 50 OIV morphological descriptors and ampelometric analyses were carried out on mature leaves by SuperAmpelo software. The DNA of the different accessions, extracted from young leaves, was analyzed using 14 microsatellite loci. Furthermore, at harvest, the grapes of each accession were sampled to assess main compositive characteristics. Results showed differences among accessions on some ampelographic descriptors of the mature leaf, of the bunch, and on phenological stages. Microsatellite profiles allowed for classification of the accessions into three distinct groups. Qualitative analysis of the berry skin showed differences among accessions in the content of the main classes of phenolic compounds

Gene Expression Changes in the Motor Cortex Mediating Motor Skill Learning

The primary motor cortex (M1) supports motor skill learning, yet little is known about the genes that contribute to motor cortical plasticity. Such knowledge could identify candidate molecules whose targeting might enable a new understanding of motor cortical functions, and provide new drug targets for the treatment of diseases which impair motor function, such as ischemic stroke. Here, we assess changes in the motor-cortical transcriptome across different stages of motor skill acquisition. Adult rats were trained on a gradually acquired appetitive reach and grasp task that required different strategies for successful pellet retrieval, or a sham version of the task in which the rats received pellet reward without needing to develop the reach and grasp skill. Tissue was harvested from the forelimb motor-cortical area either before training commenced, prior to the initial rise in task performance, or at peak performance. Differential classes of gene expression were observed at the time point immediately preceding motor task improvement. Functional clustering revealed that gene expression changes were related to the synapse, development, intracellular signaling, and the fibroblast growth factor (FGF) family, with many modulated genes known to regulate synaptic plasticity, synaptogenesis, and cytoskeletal dynamics. The modulated expression of synaptic genes likely reflects ongoing network reorganization from commencement of training till the point of task improvement, suggesting that motor performance improves only after sufficient modifications in the cortical circuitry have accumulated. The regulated FGF-related genes may together contribute to M1 remodeling through their roles in synaptic growth and maturation.McGovern Institute for Brain Research at MITNational Institutes of Health (U.S.) ((NIH grant 1-RC1-NS068103-01)National Institutes of Health (U.S.) (NIH grant R01-MH084966)Roberto Rocca Education Program (Fellowship)Massachusetts Institute of Technology. Undergraduate Research Opportunities Program (Fellowship)Italy. Ministero dell'istruzione, dell'università e della ricerca (MIUR grant RBIN04H5AS)Italy. Ministero dell'istruzione, dell'università e della ricerca (MIUR grant RBLA03FLJC)Italy. Ministero dell'istruzione, dell'università e della ricerca (FIRB n. RBAP10L8TY

First Direct Observation of Collider Neutrinos with FASER at the LHC

We report the first direct observation of neutrino interactions at a particle collider experiment. Neutrino candidate events are identified in a 13.6 TeV center-of-mass energy $pp$ collision data set of 35.4 fb${}^{-1}$ using the active electronic components of the FASER detector at the Large Hadron Collider. The candidates are required to have a track propagating through the entire length of the FASER detector and be consistent with a muon neutrino charged-current interaction. We infer $153^{+12}_{-13}$ neutrino interactions with a significance of 16 standard deviations above the background-only hypothesis. These events are consistent with the characteristics expected from neutrino interactions in terms of secondary particle production and spatial distribution, and they imply the observation of both neutrinos and anti-neutrinos with an incident neutrino energy of significantly above 200 GeV.Comment: Submitted to PRL on March 24 202

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches