Kidney Injury Caused by Preeclamptic Pregnancy Recovers Postpartum in a Transgenic Rat Model

Preeclampsia (PE) is characterized by the onset of hypertension (≥140/90 mmHg) and presence of proteinuria (>300 mg/L/24 h urine) or other maternal organ dysfunctions. During human PE, renal injuries have been observed. Some studies suggest that women with PE diagnosis have an increased risk to develop renal diseases later in life. However, in human studies PE as a single cause of this development cannot be investigated. Here, we aimed to investigate the effect of PE on postpartum renal damage in an established transgenic PE rat model. Female rats harboring the human-angiotensinogen gene develop a preeclamptic phenotype after mating with male rats harboring the human-renin gene, but are normotensive before and after pregnancy. During pregnancy PE rats developed mild tubular and glomerular changes assessed by histologic analysis, increased gene expression of renal damage markers such as kidney injury marker 1 and connective-tissue growth factor, and albuminuria compared to female wild-type rats (WT). However, four weeks postpartum, most PE-related renal pathologies were absent, including albuminuria and elevated biomarker expression. Only mild enlargement of the glomerular tuft could be detected. Overall, the glomerular and tubular function were affected during pregnancy in the transgenic PE rat. However, almost all these pathologies observed during PE recovered postpartum.     

Visualization of Ethereum P2P network topology and peer properties

Ethereum is arguably the second most popular cryptocurrency-based network after Bitcoin. Both use the distributed ledger technology known as the blockchain, which is considered secure. However, the provided security level is proportional to the number of connected nodes, the number of influential nodes, and the supported amount of hash power. Thus, the knowledge of the network properties and nodes' behavior is helpful to protect the network from possible attacks such as double-spending attacks, DDoS attacks, 51% attacks, and Sybil attacks. This paper proposes a node discovery mechanism, which performs a P2P link discovery on the Ethereum main network. For that, we develop Search-node, a modified version of Ethereum client that searches for all participating nodes in the blockchain network, stores the node information in the Bucket, and then processes the peer discovery method. Based on the collected data, we first visualize the Ethereum network topology and analyze the attributes of the network such as node degree, path length, diameter, and clustering coefficient. We then analyze the node properties and provide analytical results regarding the relationship between nodes, heavily connected nodes, node geo-distribution, security issues, and possible attacks over the influential nodes. As a result, we have identified 68,406 nodes with a total of 642,034 edges. By analyzing the collected data, we have found that the diameter in the Ethereum network is equal to 8. The node degree is over 19, which is two times higher than the default configuration.     

Removal of toxic contaminants from water by sustainable green synthesised non‐toxic silver nanoparticles

The study describes the synthesis of silver nanoparticles using 21 different plant extracts having medicinal properties. Molecular ultraviolet‐visible spectroscopy shows that the λ _max of nanoparticles synthesised by different plant extracts varied and ranged between 400 and 468 nm. The ultraviolet results revealed that although synthesis of nanoparticles occurred by all plant extracts successfully, their size varies, this was further confirmed by differential light scattering. The synthesised nanoparticles were investigated for their antimicrobial properties. The most promising silver nanoparticles Ocimum sanctum and Artemisia annua assisted were further characterised using transmission electron microscopy and energy dispersive X‐ray spectroscopy (EDX). EDX data confirms that synthesised nanoparticles are highly pure. Further these two plant assisted nanoparticles were studied for chemocatalytic and adsorptive properties. The silver nanoparticles from Ocimum sanctum can catalyse the reduction of 4‐nitrophenol (63%) within 20 min in the presence of NaBH₄, whereas Artemisia annua assisted silver nanoparticles did not show significant chemocatalytic activity. Both the promising nanoparticles can efficiently adsorb textile dyes from aqueous solutions. These synthesised nanoparticles were also exploited to remove microbial and other contaminants from Yamuna River water. The nanoparticles show excellent antimicrobial properties and can be reused repeatedly.Inspec keywords: antibacterial activity, nanofabrication, silver, dyes, light scattering, visible spectra, microorganisms, X‐ray diffraction, transmission electron microscopy, X‐ray chemical analysis, catalysis, nanoparticles, ultraviolet spectra, adsorption, reduction (chemical)Other keywords: sustainable green synthesised nontoxic silver nanoparticles, silver nitrate, molecular ultraviolet–visible spectroscopy, plant assisted nanoparticles, plant extracts, Ocimum sanctum, Artemisia annua, E. coli, C. albicans, plasmon absorbance, differential light scattering, energy dispersive X‐ray spectroscopy, 4‐nitrophenol, chemocatalytic activity, Yamuna River water, antimicrobial properties, time 20.0 min, time 5.0 min to 240.0 hour, size 1.0 nm to 5.0 nm, size 5.0 nm to 20.0 nm, wavelength 400.0 nm to 468.0 nm, NaBH₄ , Ag     

Bitcoin's dynamic peer‐to‐peer topology

Topology discovery is a prerequisite when investigating the network properties; with the enormous number of Bitcoin users and performance issues, it becomes critical to analyse the network in a fashion that makes it possible to detect all Bitcoin's nodes and understand their behaviour. In massive, dynamic, and distributed peer‐to‐peer (P2P) networks like Bitcoin, where thousands of updates occur per second, it is hard to obtain an accurate topology representing the structure of the network as a graph with nodes and links by using the traditional local measurement approaches based on batches, offline data, or on the discovery of the topology around a small set of nodes and then combine them to discover an approximate network topology. All of which present some limitation when applying them on blockchain‐based networks. In this paper, we propose a topology discovery system that performs a real‐time data collection and analysis for Bitcoin P2P links, which assembles incoming nodes information for deeper graph analysis processing. The topology discovery system allows us to gain knowledge on the Bitcoin network size, the network stability in terms of reachable, churn, and well‐connected nodes, as well as some data regarding the effects of some countries' Internet infrastructure on Bitcoin traffic.     

Reducing the propagation delay of compact block in Bitcoin network

Bitcoin is a Blockchain-based network in which thousands of nodes are directly connected and communicate via a gossip-based flooding protocol. Mined blocks are propagated to all participating nodes in the network through a CBR (compact block relay) protocol developed to reduce the block propagation delay. However, propagation delay persists. The relay time between nodes must be measured and analyzed to determine the cause of the delay and provide solutions for reducing block propagation time. Previously, we measured the relay time and investigated the cause of the delay. According to the findings of the previous study, the delay of the relay time occurs when assembling compact blocks, depending on whether transactions are requested. In this paper, we find the reasons for requesting transactions. The reasons are due to the transaction propagation method and the characteristics of the transaction itself. We propose a solution based on this. It is a method of reducing probability of requesting transactions by using the compact block's “PREFILLEDTXN” to send the transactions expected to be requested with the block. The probability of requesting is reduced by up to 67% when transactions that have just entered the memory pool are propagated by PREFILLEDTXN. The block relay time is reduced by up to 44% as a result. Finally, this research reduces block relay time between nodes.     

Design of an H∞ controller for the Delta robot: experimental results

This paper deals with an efficient implementation of an H∞ multi-variable controller on the three degrees of freedom (DOF) parallel robot namely the ‘Delta robot’. The H∞ controller is designed by the mixed sensitivity approach in which the sensitivity function matrix S and the complementary sensitivity function matrix T are taken into account. For this purpose, a nonlinear analytical dynamic state model is developed and a tangent linearization procedure is used to obtain a multi-variable linear model around a functional point. Real-time experiments were performed to compare the centralized H∞ controller with a classical decentralized Proportional Integral Derivative (PID) controller. Experimental tracking results show that the performances of the PID compared to those of the H∞ decrease when the movement dynamic is increased. At high dynamic (12 Ge), it is shown that the maximum tracking error and the error around the stop positions of the H∞ are, respectively, 80 and 60% of the PID. The experiments of the load variation have proven that the H∞ is more robust than the PID. The steady-state root mean square error of the H∞ is less than 60% of the one obtained using the PID controller.