Statistical Deadband: A Novel Approach for Event-Based Data Reporting

Deadband algorithms are implemented inside industrial gateways to reduce the volume of data sent across different networks. By tuning the deadband sampling resolution by a preset interval Δ , it is possible to estimate the balance between the traffic rates of networks connected by industrial SCADA gateways. This work describes the design and implementation of two original deadband algorithms based on statistical concepts derived by John Bollinger in his financial technical analysis. The statistical algorithms proposed do not require the setup of a preset interval—this is required by non-statistical algorithms. All algorithms were evaluated and compared by computing the effectiveness and fidelity over a public collection of random pseudo-periodic signals. The overall performance measured in the simulations showed better results, in terms of effectiveness and fidelity, for the statistical algorithms, while the measured computing resources were not as efficient as for the non-statistical deadband algorithms

Monitoring Services for Industrial Applications

Sao Paulo Research Foundation (FAPESP) in Brazi

DHCP Hierarchical Failover (DHCP-HF) Servers over a VPN Interconnected Campus

This work presents a strategy to scale out the fault-tolerant dynamic host configuration protocol (DHCP) algorithm over multiple interconnected local networks. The proposed model is open and used as an alternative to commercial solutions for a multi-campus institution with facilities in different regions that are interconnected point-to-point using a dedicated link. When the DHCP scope has to be managed and structured over multiple geographic locations that are VPN connected, it requires physical redundancy, which can be provided by a failover server. The proposed solution overcomes the limitation placed on the number of failover servers as defined in the DHCP failover (DHCP-F) protocol, which specifies the use of one primary and one secondary server. Moreover, the presented work also contributes to improving the DHCP-F specification relative to a number of practical workarounds, such as the use of a virtualized DHCP server. Therefore, this research assumes a recovery strategy that is based on physical servers distributed among different locations and not centralized as clustered virtual machines. The proposed method was evaluated by simulations to investigate the impact of this solution in terms of network traffic generated over the VPN links in order to keep the failover service running using the proposed approach

Encrypted DNP3 Traffic Classification Using Supervised Machine Learning Algorithms

The Distributed Network Protocol (DNP3) is predominately used by the electric utility industry and, consequently, in smart grids. The Peekaboo attack was created to compromise DNP3 traffic, in which a man-in-the-middle on a communication link can capture and drop selected encrypted DNP3 messages by using support vector machine learning algorithms. The communication networks of smart grids are a important part of their infrastructure, so it is of critical importance to keep this communication secure and reliable. The main contribution of this paper is to compare the use of machine learning techniques to classify messages of the same protocol exchanged in encrypted tunnels. The study considers four simulated cases of encrypted DNP3 traffic scenarios and four different supervised machine learning algorithms: Decision tree, nearest-neighbor, support vector machine, and naive Bayes. The results obtained show that it is possible to extend a Peekaboo attack over multiple substations, using a decision tree learning algorithm, and to gather significant information from a system that communicates using encrypted DNP3 traffic

Third Party Certification of Agri-Food Supply Chain Using Smart Contracts and Blockchain Tokens

Every consumer’s buying decision at the supermarket influences food brands to make first party claims of sustainability and socially responsible farming methods on their agro-product labels. Fine wines are often subject to counterfeit along the supply chain to the consumer. This paper presents a method for efficient unrestricted publicity to third party certification (TPC) of plant agricultural products, starting at harvest, using smart contracts and blockchain tokens. The method is capable of providing economic incentives to the actors along the supply chain. A proof-of-concept using a modified Ethereum IGR token set of smart contracts using the ERC-1155 standard NFTs was deployed on the Rinkeby test net and evaluated. The main findings include (a) allowing immediate access to TPC by the public for any desired authority by using token smart contracts. (b) Food safety can be enhanced through TPC visible to consumers through mobile application and blockchain technology, thus reducing counterfeiting and green washing. (c) The framework is structured and maintained because participants obtain economic incentives thus leveraging it´s practical usage. In summary, this implementation of TPC broadcasting through tokens can improve transparency and sustainable conscientious consumer behaviour, thus enabling a more trustworthy supply chain transparency

IGR Token-Raw Material and Ingredient Certification of Recipe Based Foods Using Smart Contracts

The use of smart contracts and blockchain tokens to implement a consumer trustworthy ingredient certification scheme for commingled foods, i.e., recipe based, food products is described. The proposed framework allows ingredients that carry any desired property (including social or environmental customer perceived value) to be certified by any certification authority, at the moment of harvest or extraction, using the IGR Ethereum token. The mechanism involves the transfer of tokens containing the internet url published at the authority’s web site from the farmer all along the supply chain to the final consumer at each transfer of custody of the ingredient using the Cricital Tracking Event/Key Data Elements (CTE/KDE) philosophy of the Institute of Food Technologists (IFT). This allows the end consumer to easily inspect and be assured of the origin of the ingredient by means of a mobile application. A successful code implementation of the framework was deployed, tested and is running as a beta version on the Ethereum live blockchain as the IGR token. The main contribution of the framework is the possibility to ensure the true origin of any instance or lot of ingredient within a recipe to the customer, without harming the food processor legitimate right to protect its recipes and suppliers

Sudden Cardiac Death in Anabolic-Androgenic Steroid Users: A Literature Review

Background and objectives: Anabolic-androgenic steroids (AASs) are a group of synthetic molecules derived from testosterone and its related precursors. AASs are widely used illicitly by adolescents and athletes, especially by bodybuilders, both for aesthetic uses and as performance enhancers to increase muscle growth and lean body mass. When used illicitly they can damage health and cause disorders affecting several functions. Sudden cardiac death (SCD) is the most common medical cause of death in athletes. SCD in athletes has also been associated with the use of performance-enhancing drugs. This review aimed to focus on deaths related to AAS abuse to investigate the cardiac pathophysiological mechanism that underlies this type of death, which still needs to be fully investigated. Materials and Methods: This review was conducted using PubMed Central and Google Scholar databases, until 21 July 2020, using the following key terms: "((Sudden cardiac death) OR (Sudden death)) AND ((androgenic anabolic steroid) OR (androgenic anabolic steroids) OR (anabolic-androgenic steroids) OR (anabolic-androgenic steroid))". Thirteen articles met the inclusion and exclusion criteria, for a total of 33 reported cases. Results: Of the 33 cases, 31 (93.9%) were males while only 2 (61%) were females. Mean age was 29.79 and, among sportsmen, the most represented sports activity was bodybuilding. In all cases there was a history of AAS abuse or a physical phenotype suggesting AAS use; the total usage period was unspecified in most cases. In 24 cases the results of the toxicological analysis were reported. The most detected AASs were nandrolone, testosterone, and stanozolol. The most frequently reported macroscopic alterations were cardiomegaly and left ventricular hypertrophy, while the histological alterations were foci of fibrosis and necrosis of the myocardial tissue. Conclusions: Four principal mechanisms responsible for SCD have been proposed in AAS abusers: the atherogenic model, the thrombosis model, the model of vasospasm induced by the release of nitric oxide, and the direct myocardial injury model. Hypertrophy, fibrosis, and necrosis represent a substrate for arrhythmias, especially when combined with exercise. Indeed, AAS use has been shown to change physiological cardiac remodeling of athletes to pathophysiological cardiac hypertrophy with an increased risk of life-threatening arrhythmias

SRC Tyrosine Kinase Inhibitor and X-rays Combined Effect on Glioblastoma Cell Lines

CERVOXYInternational audienceGlioblastoma (GBM) is one of the most lethal types of tumor due to its high recurrence level in spite of aggressive treatment regimens involving surgery, radiotherapy and chemotherapy. Hypoxia is a feature of GBM, involved in radioresistance, and is known to be at the origin of treatment failure. The aim of this work was to assess the therapeutic potential of a new targeted c-SRC inhibitor molecule, named Si306, in combination with X-rays on the human glioblastoma cell lines, comparing normoxia and hypoxia conditions. For this purpose, the dose modifying factor and oxygen enhancement ratio were calculated to evaluate the Si306 radiosensitizing effect. DNA damage and the repair capability were also studied from the kinetic of γ-H2AX immunodetection. Furthermore, motility processes being supposed to be triggered by hypoxia and irradiation, the role of c-SRC inhibition was also analyzed to evaluate the migration blockage by wound healing assay. Our results showed that inhibition of the c-SRC protein enhances the radiotherapy efficacy both in normoxic and hypoxic conditions. These data open new opportunities for GBM treatment combining radiotherapy with molecularly targeted drugs to overcome radioresistance

Proton boron capture therapy (PBCT) induces cell death and mitophagy in a heterotopic glioblastoma model

Proton boron capture therapy (PBCT) in a preclinical glioblastoma model exhibits increased therapeutic effectiveness with an increased cell death and mitophagy, supporting its use as a scalable strategy to treat glioblastoma