Abstract
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and ...innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight ’Tangle’ based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions.
As a result of the proliferation of digital and network technologies in all facets of modern society, including the healthcare systems, the widespread adoption of Electronic Healthcare Records (EHRs) ...has become the norm. At the same time, Blockchain has been widely accepted as a potent solution for addressing security issues in any untrusted, distributed, decentralized application and has thus seen a slew of works on Blockchain-enabled EHRs. However, most such prototypes ignore the performance aspects of proposed designs. In this paper, a prototype for a Blockchain-based EHR has been presented that employs smart contracts with Hyperledger Fabric 2.0, which also provides a unified performance analysis with Hyperledger Caliper 0.4.2. The additional contribution of this paper lies in the use of a multi-hosted testbed for the performance analysis in addition to far more realistic Gossip-based traffic scenario analysis with Tcpdump tools. Moreover, the prototype is tested for performance with superior transaction ordering schemes such as Kafka and RAFT, unlike other literature that mostly uses SOLO for the purpose, which accounts for superior fault tolerance. All of these additional unique features make the performance evaluation presented herein much more realistic and hence adds hugely to the credibility of the results obtained. The proposed framework within the multi-host instances continues to behave more successfully with high throughput, low latency, and low utilization of resources for opening, querying, and transferring transactions into a healthcare Blockchain network. The results obtained in various rounds of evaluation demonstrate the superiority of the proposed framework.
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative ...peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary.
The aim was to investigate the effects of dietary supplementations of prebiotic, probiotic, and synbiotic on growth performance and carcass characteristics of broiler chickens.
A total of 360 ...1-day-old Vencobb broiler chickens of either sex were randomly assigned to four dietary treatments each consisting of three replicates and each replicate having 30 birds for 6 weeks. The dietary treatments were (1) control group with basal diet, (2) basal diet supplemented with prebiotic (at 400 g/tonne of starter as well as finisher ration), (3) basal diet supplemented with probiotic (at 100 g/tonne of starter ration and 50 g/tonne of finisher ration), and (4) basal diet supplemented with synbiotic(at 500 g/tonne of starter as well as finisher ration). The birds were provided with ad-libitum feed and drinking water during the entire experimental period.
The highest body weight observed in asynbiotic group, which was non-significantly (p>0.05) higher than thecontrol group. Prebiotic and probiotic groups showed lower body weight than synbiotic and control groups. A total feed intake did not show any significant (p>0.05) difference between experimental groups. There were no significant (p>0.05) differences in feed conversion ratio of broiler chickens in prebiotic, probiotic, and synbiotic groups as compared with control group. There was no significant (p>0.05) difference in the carcass traits with respect to dressing percentage, carcass percentage, heart weight, liver weight and gizzard weight, wing percentage, breast percentage, back percentage, thigh percentage, and drumstick percentage in Cobb broilers under study.
The growth performance and percentage of carcass yield did not show any significant increase by the dietary inclusion of prebiotic, probiotic, and synbiotic compared with unsupplemented control in a commercial broiler chicken.
In most business and residential organizations, Diesel Generators (DG) is a viable supplementary power source for ensuring an undisturbed power supply. The DG is a hybrid machine that generates ...electrical energy using a Diesel Engine (DE) and an Electric Generator (EG). By routinely monitoring crucial machine parameters, alternative power source efficiency can be improved. Furthermore, Condition Monitoring Systems (CMS) based on the Internet of Things (IoT) have supplanted the traditional equipment maintenance method. Predictive maintenance is also an important building block of Industry 4.0, whose entire process and performance can be fully understood by using IoT-enabled Remote Monitoring (RM) schemes. Firstly, this paper introduces a remote monitoring and data acquisition scheme to realize the concept of predictive maintenance. Secondly, this article discusses a strategy for real-time observation of DG parameters as well as a comprehensive analysis of various metrics. Thirdly, this research article includes a monitoring and analysis scheme of crucial factors in a DG, like the speed of an engine, voltage output, the current produced, power factor, coolant required, fuel consumption, and battery health. Different mathematical models are formulated by correlating experimental data and estimating the coefficients. Finally, to create suitable real-time warnings under critical circumstances, a fuzzy logic-based Decision Support System (DSS) and web-based integration elements are presented.
Background
Cardiotoxicity and related complications are well-known adverse effects of anticancer drugs like doxorubicin (DOX). A medicinal plant called
Rhododendron arboreum
is used by traditional ...healers of Sikkim in the treatment of heart ailments and has also been reported for widespread therapeutic effects in many clinical studies. Thus the present study has been designed to evaluate the protective effects of
Rhododendron arboreum
leaf extract (RALE) against DOX-induced cardiotoxicities.
Methods
Commencement of research with the collection of the
Rhododendron arboreum
leaves and drying it in the shade, the extraction was performed using the Soxhlet method with an ethanolic solvent. The phytoconstituents of the RALE were then quantified and qualitatively evaluated. Doxorubicin-induced cardiotoxicity was carried out using four groups consisting of six animals each. Doxorubicin was administered with a dose of 3 mg/kg injected intraperitoneally (i.p.) on the 1
st
,7
th
,14
th
,21
st
and 28
th
day of cumulative dose of 15 mg/kg throughout the experimental period with RALE treatment (250 mg/kg and 100 mg/kg) orally for 28 days. The influence of the treatment was analyzed by quantification of cardiac biomarkers and electrocardiographic method.
Results
The serum levels of cardiac biomarkers such as Lactate Dehydrogenase (LDH), Creatine kinase-N-acetyltransferase (CK-NAC), Creatine kinase-MB (CK-MB), Aspartate Transaminase (AST), Alanine Transaminase (ALT), which were elevated due to DOX-induced cardiotoxicity were significantly reduced in all RALE (250 mg/kg and 100 mg/kg) treated groups. Similarly, the electrocardiographic changes like prolonged QT interval, widening of QRS complex amplitude, undefined ST segment, arrhythmias and increased heart rate were also restored close to normal in all treated groups compared to the DOX control group.
Conclusion
Following the data observed during the study, results reported that
R. arboreum
possesses the free radical scavenging property, improved cardiotoxic laboratory parameters and restored reversible cellular injury due to existing of the principle constituent’s impact on proinflammatory mediators.
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