HCB: Enabling Compact Block in Ethereum Network with Secondary Pool and Transaction Prediction

Compact block, which replaces transactions in the block with their hashes, is an effective means to speed up block propagation in the Bitcoin network. The compact block mechanism in Bitcoin counts on the fact that many nodes may already have the transactions (or most of the transactions) in the block, therefore sending the complete block containing the full transactions is unnecessary. This fact, however, does not hold in the Ethereum network. Adopting compact block directly in Ethereum may degrade the block propagation speed significantly because the probability of a node not having a transaction in the sending block is relatively high in Ethereum and requesting the missing transactions after receiving the compact block takes much additional time. This paper proposes hybrid-compact block (HCB), an efficient compact block propagation scheme for Ethereum and other similar blockchains. First, we develop a Secondary Pool to store the low-fee transactions, which are removed from the primary transaction pool, to conserve storage space. As simple auxiliary storage, the Secondary Pool does not affect the normal block processing of the primary pool in Ethereum. Second, we design a machine learning-based transaction prediction module to precisely predict the missing transactions caused by network latency and selfish behaviors. We implemented our HCB scheme and other compact-block-like schemes (as benchmarks) and deployed a number of worldwide nodes over the Ethereum MainNet to experimentally investigate them. Experimental results show that HCB performs best among the existing compact-block-like schemes and can reduce propagation time by more than half with respect to the current block propagation scheme in Ethereum

Monitoring of the central blood pressure waveform via a conformal ultrasonic device.

Continuous monitoring of the central-blood-pressure waveform from deeply embedded vessels, such as the carotid artery and jugular vein, has clinical value for the prediction of all-cause cardiovascular mortality. However, existing non-invasive approaches, including photoplethysmography and tonometry, only enable access to the superficial peripheral vasculature. Although current ultrasonic technologies allow non-invasive deep-tissue observation, unstable coupling with the tissue surface resulting from the bulkiness and rigidity of conventional ultrasound probes introduces usability constraints. Here, we describe the design and operation of an ultrasonic device that is conformal to the skin and capable of capturing blood-pressure waveforms at deeply embedded arterial and venous sites. The wearable device is ultrathin (240 μm) and stretchable (with strains up to 60%), and enables the non-invasive, continuous and accurate monitoring of cardiovascular events from multiple body locations, which should facilitate its use in a variety of clinical environments

Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity

Small interfering RNAs (siRNAs) induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated a powerful tool named “siRNApred” with a new mixed feature set to predict siRNA activity. To improve the prediction accuracy, we proposed 2-3NTs as our new features. A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS) algorithm. Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity. “siRNApred” is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy

Control of Emission Characteristics of Perovskite Lasers through Optical Feedback

Recent progress on perovskite lasers has shown the large potential for such materials to become a basis for commercially available microlasers in the near feature. Herein, distributed feedback (DFB) lasers based on vacuum‐processed CsPbBr 3 are investigated. The expansion of the DFB structure from 1D to 2D suppresses parasitic amplified spontaneous emission (ASE), resulting in the multiple‐time‐enhanced lasing output. Further, the photoluminescence and lasing behavior of 1D and 2D DFB structures are explored through the k‐space imaging analysis

A Three-Dimensional Inorganic Analogue of 9,10-Diazido-9,10-Diboraanthracene: A Lewis Superacidic Azido Borane with Reactivity and Stability

Herein, we report the facile synthesis of a three-dimensional (3D) inorganic analogue of 9,10-diazido-9,10-dihydrodiboraantracene, which turned out to be a monomer in both the solid and solution state, and thermally stable up to 230 °C, representing a rare example of azido borane with boosted Lewis acidity and stability in one. Apart from the classical acid-base and Staudinger reactions, E−H bond activation (E=B, Si, Ge) was investigated. While the reaction with B−H (9-borabicyclo[3.3.1]nonane) led directly to the 1,1-addition on N$_{α}$ upon N$_{2}$ elimination, the Si−H (Et$_{3}$SiH, PhMe$_{2}$SiH) activation proceeded stepwise via 1,2-addition, with the key intermediates 5$_{int}$ and 6$_{int}$ being isolated and characterized. In contrast, the cooperative Ge−H was reversible and stayed at the 1,2-addition step

Experimental Study on the Atomization and Chemiluminescence Characteristics of Ethanol Flame

The breakup regime in ethanol diffusion flame under different conditions was studied by the high speed camera system combined with the UV camera system. Spray angle and Weber number (We) were used to represent the change of breakup regime. With the increases of spray angle and We, the breakup mode changes from the Rayleigh-type breakup regime to the superpulsating regime. The reaction area and intensity of ethanol flames under different breakup regimes could be discussed by the OH⁎ distribution. From Rayleigh-type breakup regime to superpulsating breakup regime, the OH⁎ distribution increased and the oxidation-reduction reaction area expanded. At the condition of superpulsating breakup mode, the intensity of OH⁎ was significantly higher than that of other modes. The flame luminous length can be obtained by the OH⁎ emission, and OH⁎ distribution reflects the structure of flame. When the breakup regime changes from the fiber-type breakup regime to the superpulsating regime, the flame luminous length increases suddenly

Utilizing Selected Di-and Trinucleotides of siRNA to Predict RNAi Activity

Small interfering RNAs (siRNAs) induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated a powerful tool named "siRNApred" with a new mixed feature set to predict siRNA activity. To improve the prediction accuracy, we proposed 2-3NTs as our new features. A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS) algorithm. Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity. "siRNApred" is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy

Prolonged Inhibitory Effects of Repeated Tibial Nerve Stimulation on the Micturition Reflex in Decorticated Rats

Objective: This study aimed to determine whether a short-term repeated stimulation of tibial nerve afferents induces a prolonged modulation effect on the micturition reflex in a decorticated rat model. Material and Methods: Fifteen female Sprague-Dawley rats (250-350 g) were fully decorticated and paralyzed in the study. Tibial nerve stimulation (TNS) was delivered by inserting two pairs of needle electrodes close to the nerves at the level of the medial malleolus. Constant flow cystometries (0.07 mL/min) at approximately ten-minute intervals were performed, and the micturition threshold volume (MTV) was recorded and used as a dependent variable. After four to five stable recordings, the tibial nerves of both sides were stimulated continuously for five minutes at 10 Hz and at an intensity of three times the threshold for alpha-motor axons. Six same stimulations were applied repeatedly, with an interval of five minutes between each stimulation. Mean MTV was calculated on the basis of several cystometries in each half-hour period before, during, and after the six repeated TNS. Results: During the experiment, all the animals survived in good condition with relatively stable micturition reflexes, and a significant increase in MTV was detected after TNS. The strongest effect (mean = 178%) was observed during the first 30 minutes after six repeated stimulations. This obvious threshold increase remained for at least five hours. Conclusions: A prolonged poststimulation modulatory effect on the micturition reflex was induced by short-term repeated TNS in decorticated rats. This study provides a theoretical explanation for the clinical benefit of TNS in patients with overactive bladder and suggests decorticated rats as a promising model for further investigation of the neurophysiological mechanisms underlying the bladder inhibitory response induced by TNS.Funding Agencies|Medical Scienti fic Research Foundation of Guangdong Province, China; Natural Science Foundation of Guangdong Province, China; National Natural Science Foundation of China; Chinese Postdoctoral Science Foundation; [2013A806]; [B2020011]; [2016A030307033]; [81802551]; [2020M672593]</p

Integrated Mobility for Individuals in Smarter Cities: a Crowd-sourcing approach

We present an ongoing research on an Integrated Real-time Mobility Assistant (IRMA). IRMA is a software system that targets the personal mobility in a near future scenario, based on green, shared and public transports. IRMA architecture includes smartphone applications and a set of web services to gather and interpret any relevant source of information, that includes open data, crowd data and big data. The technology is SOA/EDA (Service Oriented Architecture / Event Driven Architecture) and the service will gather and interpret any relevant source of information on transport resources and their availability. Information includes user generated content through a crowdsourcing service and data from/to social networks. Our paper provides a review of current crowdsourcing approaches to a smart and collaborative mobility, and proposes a future application scenario. IRMA, after being proved on test cases, will be tested by the students of University of Pavia