Architectural Design and History

Presentazione del nuovo Corso di Laurea Magistrale in Architectural Design and History del Polo Territoriale di Mantova del Politecnico di Milano, in lingua inglese, sul rapporto tra progetto di architettura in contesti storici e storia dell'architettura

Comprehensive analysis of the membrane phosphoproteome regulated by oligogalacturonides in Arabidopsis thaliana

Early changes in the Arabidopsis thaliana membrane phosphoproteome in response to oligogalacturonides (OGs), a class of plant damage-associated molecular patterns (DAMPs), were analyzed by two complementary proteomic approaches. Differentially phosphorylated sites were determined through phosphopeptide enrichment followed by LC-MS/MS using label-free quantification; differentially phosphorylated proteins were identified by 2D-DIGE combined with phospho-specific fluorescent staining (phospho-DIGE). This large-scale phosphoproteome analysis of early OG-signaling enabled us to determine 100 regulated phosphosites using LC-MS/MS and 46 differential spots corresponding to 34 pdhosphoproteins using phospho-DIGE. Functional classification showed that the OG-responsive phosphoproteins include kinases, phosphatases and receptor-like kinases, heat shock proteins (HSPs), reactive oxygen species (ROS) scavenging enzymes, proteins related to cellular trafficking, transport, defense and signaling as well as novel candidates for a role in immunity, for which elicitor-induced phosphorylation changes have not been shown before. A comparison with previously identified elicitor-regulated phosphosites shows only a very limited overlap, uncovering the immune-related regulation of 70 phosphorylation sites and revealing novel potential players in the regulation of elicitor-dependent immunity

Changes in the microsomal proteome of tomato fruit during ripening

The variations in the membrane proteome of tomato fruit pericarp during ripening have been investigated by mass spectrometry-based label-free proteomics. Mature green (MG30) and red ripe (R45) stages were chosen because they are pivotal in the ripening process: MG30 corresponds to the end of cellular expansion, when fruit growth has stopped and fruit starts ripening, whereas R45 corresponds to the mature fruit. Protein patterns were markedly different: among the 1315 proteins identified with at least two unique peptides, 145 significantly varied in abundance in the process of fruit ripening. The subcellular and biochemical fractionation resulted in GO term enrichment for organelle proteins in our dataset, and allowed the detection of low-abundance proteins that were not detected in previous proteomic studies on tomato fruits. Functional annotation showed that the largest proportion of identified proteins were involved in cell wall metabolism, vesicle-mediated transport, hormone biosynthesis, secondary metabolism, lipid metabolism, protein synthesis and degradation, carbohydrate metabolic processes, signalling and response to stress

Distributed Training of Graph Convolutional Networks

The aim of this work is to develop a fully-distributed algorithmic framework for training graph convolutional networks (GCNs). The proposed method is able to exploit the meaningful relational structure of the input data, which are collected by a set of agents that communicate over a sparse network topology. After formulating the centralized GCN training problem, we first show how to make inference in a distributed scenario where the underlying data graph is split among different agents. Then, we propose a distributed gradient descent procedure to solve the GCN training problem. The resulting model distributes computation along three lines: during inference, during back-propagation, and during optimization. Convergence to stationary solutions of the GCN training problem is also established under mild conditions. Finally, we propose an optimization criterion to design the communication topology between agents in order to match with the graph describing data relationships. A wide set of numerical results validate our proposal. To the best of our knowledge, this is the first work combining graph convolutional neural networks with distributed optimization.Comment: Published on IEEE Transactions on Signal and Information Processing over Network

Optical properties of developing pip and stone fruit reveal underlying structural changes

Analyzing the optical properties of fruits represents a powerful approach for non-destructive observations of fruit development. With classical spectroscopy in the visible and near-infrared wavelength ranges, the apparent attenuation of light results from its absorption or scattering. In horticultural applications, frequently, the normalized difference vegetation index (NDVI) is employed to reduce the effects of varying scattering properties on the apparent signal. However, this simple approach appears to be limited. In the laboratory, with time-resolved reflectance spectroscopy, the absorption coefficient, μa, and the reduced scattering coefficient, μs′, can be analyzed separately. In this study, these differentiated optical properties were recorded (540-940 nm), probing fruit tissue from the skin up to 2 cm depth in apple (Malus × domestica 'Elstar') and plum (Prunus domestica 'Tophit plus') harvested four times (65-145 days after full bloom). The μa spectra showed typical peak at 670 nm of the chlorophyll absorption. The μs′ at 670 nm in apple changed by 14.7% (18.2-15.5 cm-1), while in plum differences of 41.5% (8.5-5.0 cm-1) were found. The scattering power, the relative change of μs′, was zero in apple, but enhanced in plum over the fruit development period. This mirrors more isotropic and constant structures in apple compared with plum. For horticultural applications, the larger variability in scattering properties of plum explains the discrepancy between commercially assessed NDVI values or similar indices and the absolute μa values in plum (R < 0.05), while the NDVI approach appeared reasonable in apple (R ≥ 0.80)

Clinical trial of time-resolved scanning optical mammography at 4 wavelengths between 683 and 975 nm

The first time-resolved optical mammograph operating beyond 900 nm (683, 785, 913, and 975 nm) is presently being used in a clinical trial to test the diagnostic potential of the technique in detecting and characterizing breast lesions. Between November 2001 and October 2002, 101 patients with malignant and benign lesions were analyzed retrospectively. Scattering plots, as derived from a homogeneous model, and late gated intensity images, to monitor spatial changes in the absorption properties, are routinely used. The intensity images available at four wavelengths provide sensitivity to the main tissue constituents (oxy- and deoxyhemoglobin, water, and lipids), in agreement with expected tissue composition and physiology, while the scattering plots mirror structural changes. Briefly, tumors are usually identified due to the strong blood absorption at short wavelengths, cysts to the low scattering, and fibroadenomas to low absorption at 913 nm and high at 975 nm, even though the optical features of fibroadenomas seem not to be uniquely defined. The effectiveness of the technique in localizing and discriminating different lesion types is analyzed as a function of various parameters (lesion size, compressed breast thickness, and breast parenchymal pattern).

Top-down cracking in Italian motorway pavements: A case study

Abstract Top-down cracking (TDC) is a distress affecting asphalt pavements and consists of longitudinal cracks that initiate on the pavement surface and propagate downwards. In general, TDC is more critical in the case of thick pavements with open-graded friction course (OGFC), which are the typical characteristics of Italian motorway pavements. Recent surveys showed the presence of many longitudinal cracks potentially ascribable to TDC on Italian motorways. Within this context, this study has two main objectives: 1) to define reliable identification criteria allowing to distinguish between TDC and the other types of longitudinal cracks observed and 2) based on the developed criteria, to quantify TDC in Italian motorway pavements. In this regard, a 200 km long trial network (400 km considering both directions) was studied, taking into account the effect of several variables (e.g. geometric characteristics, traffic level, wearing layer type and climate). For this purpose, images of the trial network acquired during pavement monitoring were visually analysed and some control cores were taken. Specific criteria (which can be used in a pavement management system, PMS) were developed to distinguish between the main types of longitudinal cracks observed on the trial network, i.e. TDC, cracks due to heavy vehicles tire blowout and construction joints, based on their geometric features on the pavement surface. It was found that TDC can affect up to 20–30 % of the slow traffic lane. Specifically, the highest TDC concentrations were observed for high traffic levels and OGFC, whereas TDC was absent in the case of a dense-graded wearing layer. Finally, surprisingly the concentration of tire blowout cracks was even higher than TDC. This study provides evidence on the fact that, for thick pavements with OGFC, TDC has to be considered a priority problem to be addressed in both pavement design and maintenance

Time-resolved reflectance spectroscopy as a management tool for late-maturing nectarine supply chain

The absorption coefficient of the fruit flesh at 670 nm (mu(a)), measured at harvest by time-resolved reflectance spectroscopy (TRS) is a good maturity index for early nectarine cultivars. A kinetic model has been developed linking the mu(a), expressed as the biological shift factor to softening during ripening. This allows shelf life prediction for individual fruit from the value of mu(a) at harvest and the fruit categorization into predicted softening and usability classes. In this work, the predictive capacity of a kinetic model developed using mu(a) data at harvest and firmness data within 1-2 d after harvest for a late maturing nectarine cultivar ('Morsiani 90') was tested for prediction and classification ability. Compared to early maturing cultivars, mu(a) at harvest had low values and low variability, indicating advanced maturity, whereas firmness was similar. Hence, fruit were categorized into six usability classes (from 'transportable-hard' to 'ready-to-eat-very soft') basing on mu(a) limits established analyzing firmness data in shelf life after harvest. The model was tested by comparing the predicted firmness and class of usability to the actual ones measured during ripening and its performance compared to that of models based on data during the whole shelf life at 20 degrees C after harvest and after storage at 0 degrees C and 4 degrees C. The model showed a classification ability very close to that of models based on data of the whole shelf life, and was able to correctly segregate the 'ready-to-eat-transportable', 'transportable' and 'transportable-hard' classes for ripening at harvest and after storage at 0 degrees C, and the 'ready-to-eat-very soft' and 'ready-to-eat-soft' classes for ripening after storage at 4 degrees C, with lower performance of models for fruit after storage at 4 degrees C respect to those of the other two ripening

Non-destructive analysis of anthocyanins in cherries by means of Lambert-Beer and multivariate regression based on spectroscopy and scatter correction using time-resolved analysis

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