Partially unzipped carbon nanotubes as magnetic field sensors

The conductance, $G(E)$, through graphene nanoribbons (GNR) connected to a partially unzipped carbon nanotube (CNT) is studied in the presence of an external magnetic field applied parallel to the long axis of the tube by means of non-equilibrium Green's function technique. We consider (z)igzag and (a)rmchair CNTs that are partially unzipped to form aGNR/zCNT/aGNR or zGNR/aCNT/zGNR junctions. We find that the inclusion of a longitudinal magnetic field affects the electronic states only in the CNT region, leading to the suppression of the conductance at low energies. Unlike previous studies, for the zGNR/aCNT/zGNR junction in zero field, we find a sharp dip in the conductance as the energy approaches the Dirac point and we attribute this non-trivial behavior to the peculiar band dispersion of the constituent subsystems. We demonstrate that both types of junctions can be used as magnetic field sensors.Comment: final version to appear in Applied Physics Letter

The Ussana “Fm”: insight about the Sardinian rift from a syn-tectonic unit evolving through space and time

The meaning and the space-and-time variable depositional features of the Ussana “Fm” and of the related coeval units, base of the Late Oligocene - Miocene succession of the Sardinian rift, are discussed. These features, and the presence/absence itself of the Ussana Fm, are related to tectonic and paleomorphologic characters of the Sardinian rift shoulders and their evolution. The features of the Ussana Fm evidence the changing characteristics of the Sardinian rift up to the southern Corsica area. Giving the extremely variable characters of the stratigraphic sections of the Ussana Fm from S to N and also at short distance, a possible lithostratigrahic upgrade of the unit to litostratigrpahic group is proposed

Methods to characterize the real-world use of rollators using inertial sensors – a feasibility study

Rollators are widely used by people with mobility problems, but previous studies have been limited to self-report approaches when evaluating their real-world effectiveness. To support studies based on more robust datasets, a method to estimate mobility parameters, such as gait speed and distance traveled, in the real world is needed. Body-worn sensors offer one approach to the problem, but rollator-mounted sensors have some practical advantages providing direct insight into patterns of walking device used, an under-researched area. We present a novel method to estimate speed and distance traveled from a single rollator-mounted IMU. The method was developed using data collected from ten rollator users performing a series of walking tasks including obstacle negotiation. The IMU data is first pre-processed to account for noise, orientation offset, and rotation-induced accelerations. The method then uses a two-stage approach. First, activity classification is used to separate the rollator data into one of three classes (movement, turning, or other). Subsequently, the speed of movement and distance traveled is estimated, using a separate estimation model for each of the three classes. The results showed high classification accuracy (precision, recall, and F1 statistics all >0.9). Speed estimation showed mean absolute errors below 0.2 m/s. Estimates for distance traveled showed errors which ranged from 5% (straight line walking) to over 70%. The results showed some promise but further work with a larger data set is needed to confirm the performance of our approach

iPSCs-Based Neural 3D Systems: A Multidimensional Approach for Disease Modeling and Drug Discovery

Induced pluripotent stem cells (iPSCs)-based two-dimensional (2D) protocols have offered invaluable insights into the pathophysiology of neurological diseases. However, these systems are unable to reproduce complex cytoarchitectural features, cell-cell and tissue-tissue interactions like their in vivo counterpart. Three-dimensional (3D)-based culture protocols, though in their infancy, have offered new insights into modeling human diseases. Human neural organoids try to recapitulate the cellular diversity of complex tissues and can be generated from iPSCs to model the pathophysiology of a wide spectrum of pathologies. The engraftment of iPSCs into mice models and the improvement of differentiation protocols towards 3D cultures has enabled the generation of more complex multicellular systems. Consequently, models of neuropsychiatric disorders, infectious diseases, brain cancer and cerebral hypoxic injury can now be investigated from new perspectives. In this review, we consider the advancements made in modeling neuropsychiatric and neurological diseases with iPSC-derived organoids and their potential use to develop new drugs

Treatment of esophageal achalasia in children: Today and tomorrow

Esophageal achalasia (EA) is a rare esophageal motility disorder in children. Laparoscopic Heller myotomy (LHM) represents the treatment of choice in young patients. Peroral endoscopic myotomy (POEM) is becoming an alternative to LHM. The aim of this study is to evaluate the effectiveness, safety, and outcomes of POEM vs LHM in treatment of children with EA. Data of pediatric patients with EA, who underwent LHM and POEM from February 2009 to December 2013 in two centers, were collected. Eighteen patients (9 male, mean age: 11.6 years; range: 2-17 years) were included. Nine patients (6 male, mean age: 10.7 years; range: 2-16 years) underwent LHM, and the other 9 (3 males, mean age: 12.2 years; range: 6-17 years) underwent POEM procedure. Mean operation time was shorter in POEM group compared with LHM group (62/149 minutes). Myotomy was longer in POEM group than in LHM group (11/7 cm). One major complication occurred after LHM (esophageal perforation). No clinical and manometric differences were observed between LHM and POEM in follow-up. The incidence of iatrogenic gastroesophageal reflux disease was low (1 patient in both groups). Results of a midterm follow-up show that LHM and POEM are safe and effective treatments also in children. Besides, POEM is a mini-invasive technique with an inferior execution timing compared to LHM. A skilled endoscopic team is mandatory to perform this procedur

Unsupervised and supervised text similarity systems for automated identification of national implementing measures of European directives

The automated identification of national implementations (NIMs) of European directives by text similarity techniques has shown promising preliminary results. Previous works have proposed and utilized unsupervised lexical and semantic similarity techniques based on vector space models, latent semantic analysis and topic models. However, these techniques were evaluated on a small multilingual corpus of directives and NIMs. In this paper, we utilize word and paragraph embedding models learned by shallow neural networks from a multilingual legal corpus of European directives and national legislation (from Ireland, Luxembourg and Italy) to develop unsupervised semantic similarity systems to identify transpositions. We evaluate these models and compare their results with the previous unsupervised methods on a multilingual test corpus of 43 Directives and their corresponding NIMs. We also develop supervised machine learning models to identify transpositions and compare their performance with different feature sets

Reinforced Concrete Building with IED Detonation: Test and Simulation

There is growing concern about the possibility of a suicide bomber being immolated when the army forces or the law enforcement agencies discover the place where they prepare their material or simply find themselves inside a building. To study the possible effects that these improvised explosive devices (IEDs) would have on the structures, eight tests were carried out with various configurations of IEDs with vest bombs inside a reinforced concrete (including walls and roof) building constructed ad hoc for these tests. These vests were made with different explosives (black powder, ANFO, AN/AL, PG2). For the characterization of these tests, a high-speed camera and pressure and acceleration sensors were used. The structure behaved surprisingly well, as it withstood all the first seven detonations without apparent structural damage. In the last detonation, located on the ground and with a significant explosive charge, the structural integrity of the roof and some of the walls was compromised. The simulation of the building was carried out with the LS-DYNA software with a Lagrangian formulation for the walls, using the LBE (based on CONWEP) module for the application of the charge. Despite the difficulty of this simulation, the results obtained, in terms of applied pressures and measured accelerations, are acceptable with differences of about 20%