La Northern Avenue a Yerevan e il piano urbanistico di Tamanian

A differenza di molte altre capitali dei paesi dell'area, come la vicina Tbilisi, che in anni recenti ha ceduto alla fascinazione e alle suggestioni di architetture spettacolari, perlopiù estranee al contesto, alla geografia ed al tessuto urbano, o di Baku, dove il restauro della città vecchia ha aperto le porte alla realizzazione di un gran numero di cattedrali dell’architettura globalizzata, Yerevan sta perseguendo, autonomamente e in controtendenza rispetto ai vicini, un proprio modello di sviluppo urbano, non incentrato sull’alterità e il conflitto con l’esistente, ma basato in gran parte sugli indirizzi contenuti nel piano di Alexander Tamanian del 1924.In contrast with its neighbour Tbilisi, which in recent years has yielded to the fascination and charm of spectacular architecture, mostly out of context, geography and urban fabric, or from Baku, where the restoration of the Old Town has opened up the doors to the realization of a large number of archistar-made buildings, Yerevan is pursuing an own model of urban development, not focused on the conflict with the existing fabric, but largely based on the addresses contained in the 1924 plan by Alexander Tamanian

Economic implications of food-related virtual water trade

L'abstract è presente nell'allegato / the abstract is in the attachmen

AFICILL: a single-cohort, retrospective study on Atrial Fibrillation In Critically ILL patients admitted to a medical sub-intensive care unit: implications for clinical management, outcomes and elaboration of new data-driven models

Introduction: atrial fibrillation (AF) is common among critically-ill patients, who are considered at increased cardioembolic and haemorragic risk. Consequently, anticoagulant therapy might be ineffective or harmful for an excess of haemorragic events which could not be counterbalanced by an adequate reduction of cardioembolic occurrences. Aims: main outcome (MO) was the composite of death or intensive care unit (ICU) transfer in a population of critically-ill subjects admitted to a medical subintensive care unit (sICU); we assessed (i) thromboembolic events (TEE) and major haemorrhages (MH); (ii) current guidelines (GL) adherence and related outcomes; (iii) performance of validated risk scores for TEE and MH; we engineered (iv) new scores adopting machine learning (ML) predicting MO, TEE, MH. Patients and Methods: single-center, retrospective study enrolling all the consecutive AF-affected patients admitted to a sICU for critical illness. Demographic, clinical, therapeutic and laboratoristic data were collected. Performance of CHA2DS2-VASc and HAS-BLED scores was evaluated. GL-adherence and its relationship with outcomes was studied. ML was used to engineer new predictive models. Results: we enrolled 1430 subjects; CHA2DS2-VASc (AUC:0.516;95%CI:0.472-0.560) and HAS-BLED (AUC:0.493;95%CI:0.443-0.543) did not predict TEE or MH; in-hospital warfarin use was associated to increased MO risk (OR:1.73;95%CI:1.06-2.83; p<0.05); low-molecular-weight-heparin use was not associated to an increased MO risk; antiplatelet drugs use was associated to MO risk reduction (OR:0.51;95%CI:0.34-0.78;p<0.002). GL-adherent treatment was associated to TEE risk reduction and MH and MO risk increase; ML identified specific features for MO, TEE, MH: ML-based classifiers outperformed CHA2DS2-VASc (AUC: from 0.516 to 0.90, p<0.0001) and HAS-BLED (AUC: from 0.493 to 0.82, p<0.0001). Discussion: AF-related outcomes cannot be predicted in critically-ill patients with currently validated methods. GL-adherence is associated to a significant TEE reduction, but also to MH and MO increase. ML algorithms can identify the most important features and shape specific scores able to outperform the classical models

Ultrasonic Inspection of Acoustically “Noisy” Materials

Ultrasonic inspection of large gas turbine rotor forgings made of IN706 (40Ni-15Cr-Ti-Nb superalloy) is complicated by the material’s anisotropic and nonuniform acoustic properties. These properties stem from the intrinsically coarse grain structure of IN706 in forgings weighing up to 22,000 pounds and having axial and radial dimensions up to 20 inches and 90 inches, respectively. Although recent advances in the melting and forging processes have helped to improve the material’s microstructure, many characteristics still preside which make ultrasonic inspection a challenge. The inspection and signal processing techniques described herein compensate for variations in the acoustic properties that we have observed from forging to forging as well as within any given forging. These techniques may be applied to a wide variety of applications dealing with acoustically noisy materials with nonuniform acoustic characteristics

Open-source Tools for Dense Facial Tissue Depth Mapping (FTDM) of Computed Tomography Models

Computed tomography (CT) scans provide anthropologists with a resource to generate three- dimensional (3D) digital skeletal material to expand quantification methods and build more standardized reference collections. The ability to visualize and manipulate the bone and skin of the face simultaneously in a 3D digital environment introduces a new way for forensic facial approximation practitioners to access and study the face. Craniofacial relationships can be quantified with landmarks or with surface processing software that can quantify the geometric properties of the entire 3D facial surface. This paper describes tools for the generation of dense facial tissue depth maps (FTDMs) using de-identified head CT scans of modern Americans from the public repository, The Cancer Imaging Archives (TCIA), and the open-source program Meshlab. CT scans of 43 females and 63 males from TCIA were segmented and converted to 3D skull and face models using Mimics and exported as stereolithography (STL) files. All subsequent processing steps were performed in Meshlab. Heads were transformed to a common orientation and coordinate system using the coordinates of nasion, left orbitale, and left and right porion. Dense FTDMs were generated on hollowed, cropped face shells using the Hausdorff sampling filter. Two new point clouds consisting of the 3D coordinates for both skull and face were colorized on an RGB scale from 0.0 (red) to 40.0 mm (blue) depth values and exported as polygon file format (PLY) models with tissue depth values saved in the “vertex quality” field. FTDMs were also split into 1.0 mm increments to facilitate viewing of common depths across all faces. In total, 112 FTDMs were generated for 106 individuals. Minimum depth values ranged from 1.2 mm to 3.4 mm, indicating a common range of starting depths for most faces regardless of weight, as well as common locations for these values over the nasal bones, lateral orbital margins, and forehead superior to the supraorbital border. Maximum depths were found in the buccal region and neck, excluding the nose. Individuals with multiple scans at visibly different weights presented the greatest differences within larger depth areas such as the cheeks and neck, with little to no difference in the thinnest areas. A few individuals with minimum tissue depths at the lateral orbital margins and thicker tissues over the nasal bones (\u3e 3.0 mm) suggested the potential influence of nasal bone morphology on tissue depths. This study produced visual quantitative representations of the face and skull for forensic facial approximation research and practice that can be further analyzed or interacted with using free software. The presented tools can be applied to pre-existing CT scans, traditional or cone-beam, adult or subadult individuals, with or without landmarks, and regardless of head orientation, for forensic applications as well as for studies of facial variation and facial growth. In contrast with other facial mapping studies, this method produced both skull and face points based on replicable geometric relationships producing multiple data outputs that are easily readable and software that is openly accessible

Allometric Variation of the Postcranial Skeleton in two South American Tamarins \u3cem\u3eSaguinus oedipus oedipus\u3c/em\u3e and \u3cem\u3eSaguinus fuscicollis illigeri\u3c/em\u3e (CALLITRICHIDAE, PRIMATES)

This research examines several aspects of allometry in the postcranial skeleton of two South American tamarins Saguinus oedipus oedipus and Saguinus fuscicollis illigeri. The statistical method used for analyzing these groups is reduced major axis regression. Bivariate plots are used to qualitatively evaluate group differences, particularly in regard to differing locomotor behavior. The allometric variation in the postcrania of these two species is described. Finally, allometric comparisons between these groups are made. Heterochronic terminology is used to describe the allometric patterning. The most important result of this study is that geometric similarity was determined to exist between the groups. The comparisons support the contention that Saguinus oedipus oedipus is, in allometric terms, a geometrically overgrown Saguinus fuscicollis illigeri. Analysis of the bivariate plots reveal that significant differences in slope values between the species examined may be related to the documented anatomical locomotor variability exhibited by S.o.oedipus and S.f.illigeri

Sol–gel synthesis and characterization of Co-doped LSGM perovskites

One of the major requirements for the development and commercialization of low-cost SOFCs is the reduction in the operating temperature. One of the methods to reach this aim is the use of solid electrolytes which exhibit superior ionic conductivity at intermediate temperatures (IT, T < 800 °C). Among these ionic conductors, doped LaGaO3 materials show high oxide ionic conductivity in the 600–800 °C range. These perovskites are usually prepared by time- and energy-consuming solid state reaction. In this paper, La0.8Sr0.2Ga0.8Mg0.2O2.8 (LSGM) and La0.8Sr0.20Ga0.8Mg0.2−xCoxO3−δ (LSGMC) powders containing different amounts of Co (x = 0.05, 0.085 and 0.10) were prepared from precursors synthesised by citrate sol–gel method. The precursors were calcined at 1000 °C (10 h) and dense high-purity pellets were obtained by pressing (300 MPa) and sintering in air at 1475 °C (5, 10 and 20 h). Sintered pellets of LSGM and LSGMC contained very small amounts (<1%) of SrLaGa3O7 and SrLaGaO4, respectively, as detected by X-ray diffraction (XRD) and by the combined use of scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The data clearly showed the feasibility of sol–gel methods to produce Co-doped LSGM perovskite type oxides

Using Topological Data Analysis for diagnosis pulmonary embolism

Pulmonary Embolism (PE) is a common and potentially lethal condition. Most patients die within the first few hours from the event. Despite diagnostic advances, delays and underdiagnosis in PE are common.To increase the diagnostic performance in PE, current diagnostic work-up of patients with suspected acute pulmonary embolism usually starts with the assessment of clinical pretest probability using plasma d-Dimer measurement and clinical prediction rules. The most validated and widely used clinical decision rules are the Wells and Geneva Revised scores. We aimed to develop a new clinical prediction rule (CPR) for PE based on topological data analysis and artificial neural network. Filter or wrapper methods for features reduction cannot be applied to our dataset: the application of these algorithms can only be performed on datasets without missing data. Instead, we applied Topological data analysis (TDA) to overcome the hurdle of processing datasets with null values missing data. A topological network was developed using the Iris software (Ayasdi, Inc., Palo Alto). The PE patient topology identified two ares in the pathological group and hence two distinct clusters of PE patient populations. Additionally, the topological netowrk detected several sub-groups among healthy patients that likely are affected with non-PE diseases. TDA was further utilized to identify key features which are best associated as diagnostic factors for PE and used this information to define the input space for a back-propagation artificial neural network (BP-ANN). It is shown that the area under curve (AUC) of BP-ANN is greater than the AUCs of the scores (Wells and revised Geneva) used among physicians. The results demonstrate topological data analysis and the BP-ANN, when used in combination, can produce better predictive models than Wells or revised Geneva scores system for the analyzed cohortComment: 18 pages, 5 figures, 6 tables. arXiv admin note: text overlap with arXiv:cs/0308031 by other authors without attributio