Blockchain-based life cycle assessment: An implementation framework and system architecture

Life cycle assessment (LCA) is widely used for assessing the environmental impacts of a product or service. Collecting reliable data is a major challenge in LCA due to the complexities involved in the tracking and quantifying inputs and outputs at multiple supply chain stages. Blockchain technology offers an ideal solution to overcome the challenge in sustainable supply chain management. Its use in combination with internet-of-things (IoT) and big data analytics and visualization can help organizations achieve operational excellence in conducting LCA for improving supply chain sustainability. This research develops a framework to guide the implementation of Blockchain-based LCA. It proposes a system architecture that integrates the use of Blockchain, IoT, and big data analytics and visualization. The proposed implementation framework and system architecture were validated by practitioners who were experienced with Blockchain applications. The research also analyzes system implementation costs and discusses potential issues and solutions, as well as managerial and policy implications

Cloud-based control of industrial cyber-physical systems

This paper presents an implementation of a control algorithm to a cloud system. The motivation is that cloud implementations of low-level systems in the production industry are gradually becoming more common. Microsoft Azure platform is utilized for the cloud-based control and the case is tested using a customized laboratory model, which can be presented as an agent in a typical production system. The model offers the regulation of a ball on an inclined surface and uses two asynchronous motors connected to frequency converters to control the position of the ball. These frequency converters are controlled by a Programmable Logic Controller (PLC). Windows Communication Foundation (WCF) services and Azure IoT Hub were selected to be used with the cloud-based control system. Experimental results have shown our solution can control the system with sampling period equal or higher than 100ms. The latency of WCF service is at around 100ms and latency of Azure IoT Hub is at around 1000ms, so the prediction algorithms could be implemented in the cloud for the latter. This research also shows the feasibility of migrating machine learning algorithms that demand high computing power to the cloud to reduce the computing burden on the local control units

Cloud-based control of industrial cyber-physical systems

This paper presents an implementation of a control algorithm to a cloud system. The motivation is that cloud implementations of low-level systems in the production industry are gradually becoming more common. Microsoft Azure platform is utilized for the cloud-based control and the case is tested using a customized laboratory model, which can be presented as an agent in a typical production system. The model offers the regulation of a ball on an inclined surface and uses two asynchronous motors connected to frequency converters to control the position of the ball. These frequency converters are controlled by a Programmable Logic Controller (PLC). Windows Communication Foundation (WCF) services and Azure IoT Hub were selected to be used with the cloud-based control system. Experimental results have shown our solution can control the system with sampling period equal or higher than 100ms. The latency of WCF service is at around 100ms and latency of Azure IoT Hub is at around 1000ms, so the prediction algorithms could be implemented in the cloud for the latter. This research also shows the feasibility of migrating machine learning algorithms that demand high computing power to the cloud to reduce the computing burden on the local control units

System architecture for blockchain based transparency of supply chain social sustainability

Social sustainability is a major concern in global supply chains for protecting workers from exploitation and for providing a safe working environment. Although there are stipulated standards to govern supply chain social sustainability, it is not uncommon to hear of businesses being reported for noncompliance issues. Even reputable firms such as Unilever have been criticized for production labor exploitation. Consumers now increasingly expect sellers to disclose information on social sustainability, but sellers are confronted with the challenge of traceability in their multi-tier global supply chains. Blockchain offers a promising future to achieve instant traceability in supply chain social sustainability. This study develops a system architecture that integrates the use of blockchain, internet-of-things (IoT) and big data analytics to allow sellers to monitor their supply chain social sustainability efficiently and effectively. System implementation cost and potential challenges are analyzed before the research is concluded

Internet of Things (IoT)-Enabled Accountability in Source Separation of Household Waste for a Circular Economy in China

Source separation is regarded as a best practice for sustainable waste management, which is essential for a transition to a circular economy to recover value from waste. However, its implementation in China has faced many difficulties which are primarily inherent in the public’s behaviour towards source separation of household waste. Based on multiple cases of innovative use of the Internet of Things (IoT) technologies in China in recent years, this study establishes the concept of IoT-enabled accountability in household waste source separation by utilising the lens of accountability theory. Moreover, this research advances several propositions on the multiple dimensions of accountability mechanism to influence user behaviours. The study’s findings provide guidance to governments, technology providers and waste management organisations on the use of IoT-based technological solutions for sustainable waste management. It stimulates future research on the use of IoT technologies in managing people’s behaviour in a range of contexts beyond waste management alone. The study contributes to the growing literature on smart waste management

Mass Azithromycin Distribution and Community Microbiome: A Cluster-Randomized Trial.

BackgroundMass distributions of oral azithromycin have long been used to eliminate trachoma, and they are now being proposed to reduce childhood mortality. The observed benefit appears to be augmented with each additional treatment, suggesting a possible community-level effect. Here, we assess whether 2 biannual mass treatments of preschool children affect the community's gut microbiome at 6 months after the last distribution.MethodsIn this cluster-randomized controlled trial, children aged 1-60 months in the Dossa region of Niger were randomized at the village level to receive a single dose of azithromycin or placebo every 6 months. Fecal samples were collected 6 months after the second treatment for metagenomic deep sequencing. The prespecified primary outcome was the Euclidean PERMANOVA of the gut microbiome, or effectively the distance between the genus-level centroid at the community level, with the secondary outcome being the Simpson's α diversity.ResultsIn the azithromycin arm, the gut microbial structures were significantly different than in the placebo arm (Euclidean PERMANOVA, P < .001). Further, the diversity of the gut microbiome in the azithromycin arm was significantly lower than in the placebo arm (inverse Simpson's index, P = .005).ConclusionsTwo mass azithromycin administrations, 6 months apart, in preschool children led to long-term alterations of the gut microbiome structure and community diversity. Here, long-term microbial alterations in the community did not imply disease but were associated with an improvement in childhood mortality.Clinical trials registrationNCT02048007

From Open CNC systems to Cyber-Physical machine tools: a case study

The aim of next-generation Computer Numerical Control (CNC) is shifting from an open architecture, which has better flexibility, adaptability, versatility and expansibility, to a cyber-physical model, which offers real-time monitoring and control of the machining processes. This paper introduces a real case study to demonstrate such tendency from Open CNC systems to Cyber-Physical Machine Tools (CPMT) based on a low-power embedded platform. Firstly, a new open CNC architecture is presented, which is able to achieve high-precision, high-efficiency, and low-power consumption. Secondly, the open CNC architecture is extended to a CPMT by using Wireless Sensor Networks (WSN), where WSN is utilized to enable monitor and control the machining processes, and the integrated development platform is termed as CPMT. Finally, a case of health monitoring system for CPMT is designed and its system testing is carried out

Sensitivity of Mitochondrial Transcription and Resistance of RNA Polymerase II Dependent Nuclear Transcription to Antiviral Ribonucleosides

Ribonucleoside analogues have potential utility as anti-viral, -parasitic, -bacterial and -cancer agents. However, their clinical applications have been limited by off target effects. Development of antiviral ribonucleosides for treatment of hepatitis C virus (HCV) infection has been hampered by appearance of toxicity during clinical trials that evaded detection during preclinical studies. It is well established that the human mitochondrial DNA polymerase is an off target for deoxyribonucleoside reverse transcriptase inhibitors. Here we test the hypothesis that triphosphorylated metabolites of therapeutic ribonucleoside analogues are substrates for cellular RNA polymerases. We have used ribonucleoside analogues with activity against HCV as model compounds for therapeutic ribonucleosides. We have included ribonucleoside analogues containing 2′-C-methyl, 4′-methyl and 4′-azido substituents that are non-obligate chain terminators of the HCV RNA polymerase. We show that all of the anti-HCV ribonucleoside analogues are substrates for human mitochondrial RNA polymerase (POLRMT) and eukaryotic core RNA polymerase II (Pol II) in vitro. Unexpectedly, analogues containing 2′-C-methyl, 4′-methyl and 4′-azido substituents were inhibitors of POLRMT and Pol II. Importantly, the proofreading activity of TFIIS was capable of excising these analogues from Pol II transcripts. Evaluation of transcription in cells confirmed sensitivity of POLRMT to antiviral ribonucleosides, while Pol II remained predominantly refractory. We introduce a parameter termed the mitovir (mitochondrial dysfunction caused by antiviral ribonucleoside) score that can be readily obtained during preclinical studies that quantifies the mitochondrial toxicity potential of compounds. We suggest the possibility that patients exhibiting adverse effects during clinical trials may be more susceptible to damage by nucleoside analogs because of defects in mitochondrial or nuclear transcription. The paradigm reported here should facilitate development of ribonucleosides with a lower potential for toxicity