Drug Abuse-Induced Cardiac Arrhythmias: Mechanisms and Management

Toxicomania is a worldwide emerging problem threatening young population. Several reports highlighted its hazardous cardiovascular effects. Sudden cardiac death secondary to cardiac arrhythmias is the most occupying issue. Different forms of cardiac rhythm disorders may be induced by illicit drug abuse according to the type of drug and the mechanism involved. In this review, we exposed the main ventricular and supraventricular arrhythmia complicating the common recreational drugs, and we explained their different mechanisms as well as the particularities of management

Piezoelectret Sensors from Direct 3D-Printing onto Bulk Films

The development of piezoelectric sensors using ferroelectrets is a very active field that is increasingly gaining importance. Recently, 3D-printing ferroelectret sensors using fused deposition modeling technique has been extensively investigated due to its unparalleled advantages in terms of design flexibility and cost-effectiveness. Nevertheless, printed structures are more rigid than bulk materials due to the minimal printable thicknesses. In this work, we present a new method that combines the advantages of 3D-printing with the high performance of bulk materials by bonding both layers in the printing process. Hereby, a polylactic acid (PLA) filament is directly printed on a 20 μm-thick bulk PLA film to form well-defined structures. This structure is thermally bonded with another PLA bulk film to form the ferroelectret. In order to enhance the sensitivity of the ferroelectrets, an additional elastomeric layer is utilized. By varying the material and thickness of the elastomeric cover, piezoelectric d₃₃-coefficients of 713 pC N ⁻¹ and 229 pC N ⁻¹ are achieved using Ecoflex™ and foamed thermoplastic polyurethane (TPU), respectively. Increasing the thickness of the Ecoflex™ cover shows a significant increase of 259 % of the piezoelectric d₃₃-coefficient

Address Validation in Transportation and Logistics: A Machine Learning Based Entity Matching Approach

Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14–18, 2020, ProceedingsInternational audienceIn the Transportation and Logistics (TL) industry, address validation is crucial. Indeed, due to the huge number of parcel shipments that are moving worldwide everyday, incorrect addresses generates several shipment returns, leading to useless financial and ecological costs. In this paper, we propose an entity-matching approach and system for validating TL entities. The approach is based on Word Embedding and Supervised Learning techniques. Experiments carried out on a real dataset demonstrate the effectiveness of the approach

Approche supervisée pour l'appariement d'entités dans le domaine Transport et Logistique

International audienceL'appariement d'entités (Entity Matching) est un problème crucial pour l'intégration de données. Dans cet article, nous nous intéressons à l'appariement d'entités dans le domaine du Transport et Logistique lesquelles peuvent être définies par une structure (raison sociale, adresse). Aux difficultés usuelles qui caractérisent la problématique (typos, données manquantes ou redondantes, similarités sémantiques, etc.), s'ajoutent des spécificités « domaine » comme les abréviations et les acronymes dans les noms de sociétés ou l'absence d'un format standard pour les adresses. La solution que nous proposons s'appuie sur un processus en deux phases : 1) Standardisation des entités en vue de leur prétraitement et du parsing d'adresses (données textuelles), et 2) Appariement par apprentissage supervisé sur des représentations vectorielles sémantiques des entités obtenues par des techniques de représentation distribuée des mots. Les expérimentations menées sur un jeu de données réel illustrent la performance de la solution

A RoBERTa Based Approach for Address Validation

International audienceAddress verification is becoming more and more mandatory for businesses involved in parcel or mail delivery. Situations where shipments are returned or delivered to the wrong person (or legal entity) are harmful and may incur several costs to the stakeholders. Indeed, addresses often carry incorrect information that need to be corrected prior to any shipment process. In this paper we propose a 2-step address validation approach consisting of (1) standardization and (2) classification, both steps are based on RoBERTa, a pre-trained language model. Experiments have been conducted on real datasets and demonstrate the effectiveness of the approach in comparison to other methods

CoopECC: A Collaborative Cryptographic Mechanism for the Internet of Things

The emergence of IoT applications has risen the security issues of the big data sent by the IoT devices. The design of lightweight cryptographic algorithms becomes a necessity. Moreover, elliptic curve cryptography (ECC) is a promising cryptographic technology that has been used in IoT. However, connected objects are resource-constrained devices, with limited computing power and energy power. Driven by these motivations, we propose and develop a secure cryptographic protocol called CoopECC which leverages the organization of IoT nodes into cluster to distribute the load of cluster head (CH) among its cluster members. This technique proves that it optimizes the resource consumption of the IoT nodes including computation and energy consumption. Performance evaluation, done with TOSSIM simulator, shows that the proposed protocol CoopECC outperforms the original ECC algorithm, in terms of computation time, consumed energy, and the network’s lifespan