Optimal Fully Electric Vehicle load balancing with an ADMM algorithm in Smartgrids

In this paper we present a system architecture and a suitable control methodology for the load balancing of Fully Electric Vehicles at Charging Station (CS). Within the proposed architecture, control methodologies allow to adapt Distributed Energy Resources (DER) generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at local level a Load Area Controller (LAC) optimally calculates the FEVs charging sessions, while at higher level a Macro Load Area Aggregator (MLAA) provides DER with energy production profiles, and LACs with energy withdrawal profiles. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.Comment: This paper has been accepted for the 21st Mediterranean Conference on Control and Automation, therefore it is subjected to IEEE Copyrights. See IEEE copyright notice at http://www.ieee.org/documents/ieeecopyrightform.pd

Electric Vehicles Charging Control based on Future Internet Generic Enablers

In this paper a rationale for the deployment of Future Internet based applications in the field of Electric Vehicles (EVs) smart charging is presented. The focus is on the Connected Device Interface (CDI) Generic Enabler (GE) and the Network Information and Controller (NetIC) GE, which are recognized to have a potential impact on the charging control problem and the configuration of communications networks within reconfigurable clusters of charging points. The CDI GE can be used for capturing the driver feedback in terms of Quality of Experience (QoE) in those situations where the charging power is abruptly limited as a consequence of short term grid needs, like the shedding action asked by the Transmission System Operator to the Distribution System Operator aimed at clearing networks contingencies due to the loss of a transmission line or large wind power fluctuations. The NetIC GE can be used when a master Electric Vehicle Supply Equipment (EVSE) hosts the Load Area Controller, responsible for managing simultaneous charging sessions within a given Load Area (LA); the reconfiguration of distribution grid topology results in shift of EVSEs among LAs, then reallocation of slave EVSEs is needed. Involved actors, equipment, communications and processes are identified through the standardized framework provided by the Smart Grid Architecture Model (SGAM).Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

Triggering trigeminal neuralgia

Introduction: Although it is widely accepted that facial pain paroxysms triggered by innocuous stimuli constitute a hallmark sign of trigeminal neuralgia, very few studies to date have systematically investigated the role of the triggers involved. In the recently published diagnostic classification, triggered pain is an essential criterion for the diagnosis of trigeminal neuralgia but no study to date has been designed to address this issue directly. In this study, we set out to determine, in patients with trigeminal neuralgia, how frequently triggers are present, which manoeuvres activate them and where cutaneous and mucosal trigger zones are located. Methods: Clinical characteristics focusing on trigger factors were collected from 140 patients with trigeminal neuralgia, in a cross-sectional study design. Results: Provocation of paroxysmal pain by various trigger manoeuvres was reported by 136 of the 140 patients. The most frequent manoeuvres were gentle touching of the face (79%) and talking (54%). Trigger zones were predominantly reported in the perioral and nasal region. Conclusion: This study confirms that in trigeminal neuralgia, paroxysmal pain is associated with triggers in virtually all patients and supports the use of triggers as an essential diagnostic feature of trigeminal neuralgia

Acetyl-L-carnitine in painful peripheral neuropathy: a systematic review

Acetyl-L-carnitine (ALC) has shown a neuroprotective effect in patients with peripheral neuropathies of different etiologies. Preclinical studies demonstrated a central anti-nociceptive action, both in neuropathic and nociceptive pain models. The present review aims to provide the knowledge on the efficacy of ALC in patients with painful peripheral neuropathy, based on the evidence. Consistent with the PRISMA statement, authors searched PubMed, Embase and the Cochrane Database of Systematic Reviews for relevant papers, including those issued before April 2018. Two authors independently selected studies for inclusion and data extraction: only trials including patients with a diagnosis of peripheral neuropathy and involving at least 10 patients were considered for the purposes of this review. Fourteen clinical trials were revised, to provide the level of evidence for neuropathy. To assess the global efficacy of ALC in painful peripheral neuropathy, a meta-analysis of four randomized controlled trials was performed. Mean difference in pain reduction as measured on a 10-cm VAS, and 95% CIs were used for pooling continuous data from each trial. Four randomized controlled trials tested ALC in patients with neuropathy secondary to diabetes and to antiretroviral therapy for HIV. Compared to placebo, ALC produced a significant pain reduction equal to 20.2% (95% CI: 8.3%-32.1%, P<0.0001) with respect to baseline. Clinical trials also showed beneficial effects on nerve conduction parameters and nerve fiber regeneration, with a good safety profile. These data indicate that ALC provides an effective and safe treatment in patients with painful peripheral neuropathy. We recommend further studies to assess the optimal dose and duration of the therapeutic effect (also after treatment withdrawal)

First-principles study of amorphous germanium under pressure

In this paper we present the study of the modifications of structural propertiesof a-Ge due to the application of external pressure. The investigations are carried out in the framework of density functional theory via first-principles molecular dynamics (FPMD)

b-Initio Molecular Dynamics Simulation of High Temperature GeO2

We made a series of molecular dynamic simulations to get a representative, high temperature GeO2 system to eventually be quenched down to room temperature so as to obtain an amorphous system to be studied under pressure for comparison to experimental results. We carefully generated an initial configuration such that all simulations have entirely been carried out by ab-initio methods in the range 10K-3000K

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings