bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Ischemic Preconditioning and C1 Esterase Inhibitor Administration following Ischemia-Reperfusion Injury in a Rat Skin Flap Model
Authors: Masa Inmaculada , Casado-Sánchez César , Crespo-Lora Vicente , Ballestín Alberto 
Published: September 2020

Abstract
Background Ischemia-reperfusion (I/R) injury is a serious condition that can affect the success rate of microsurgical reconstructions of ischemic amputated limbs and complex tissue defects requiring free tissue transfers. The purpose of this study was to evaluate the effects of ischemic preconditioning (IPC) and C1 esterase inhibitor (C1-Inh) intravenous administration following I/R injury in a rat skin flap model.
Methods Superficial caudal epigastric skin flaps (3 cm × 7 cm) were performed on 50 Wistar rats that were randomly divided into five groups. Ischemia was not induced in the control group. All other flaps underwent 8 hours of ischemia prior to revascularization: I/R control group (8-hour ischemia), IPC group (preconditioning protocol + 8-hour ischemia), C1-Inh group (8-hour ischemia + C1-Inh), and IPC + C1-Inh group (preconditioning protocol + 8-hour ischemia + C1-Inh). Survival areas were macroscopically assessed after 1 week of surgery, and histopathological and biochemical evaluations were also measured.
Results There were no significant differences in flap survival between the treatment groups that were suffering 8 hours of ischemia and the control group. A significant increase in neovascularization and lower edema formation were observed in the IPC group compared with that in the I/R group. Biochemical parameters did not show any significant differences.
Conclusion Intravenous administration of C1-Inh did not significantly modulate I/R-related damage in this experimental model, but further research is needed. On the other hand, IPC reduces tissue damage and improves neovascularization, confirming its potential protective effects in skin flaps following I/R injury.
Streamer propagation along a profiled dielectric surface
Authors: Meyer H K H , Marskar R , Gjemdal H , Mauseth F 
Published: September 2020

Abstract
We investigate the propagation of positive streamers along a profiled dielectric surface in air at atmospheric pressure. Results from experiments and two-dimensional planar low-temperature plasma fluid simulations are presented and analysed. The test object consists of a disk-shaped high voltage electrode and a dielectric slab with 0.5 mm deep corrugations. The corrugated surface has a 47% larger surface area than the smooth reference surface. The experiments and simulations are performed at voltage levels that lead to either gap-bridging or arrested streamers. In both experiments and simulations, the streamers take a longer time to reach the ground electrode when propagating along the profiled surface than along the smooth reference surface. Also, arrested streamers stop closer to the high voltage electrode when a profiled surface is used. Streamers propagate closely along the surface profile in the simulations, which suggests that the observed surface profile effect is mainly a result of elongated streamer channels. Compared to the streamers propagating along the smooth surface, the elongated streamers on the profiled surface have less residual voltage at the streamer front to drive the streamer advancement.
Dissociative electron attachment cross sections for ro-vibrationally excited NO molecule and N
−
anion formation
Authors: Laporta V , Schneider I F , Tennyson J 
Published: September 2020

Abstract
Motivated by the huge need for data for non-equilibrium plasma modeling, a theoretical investigation of dissociative electron attachment to the NO molecule is performed. The calculations presented here are based on the local-complex-potential approach, taking into account five NO− resonances. Three specific channels of the process are studied, including the production of excited nitrogen atoms N(2D) and of its anions N−. Interpretation of the existing experimental data and their comparison with our theoretical result are given. A full set of ro-vibrationally-resolved cross sections and the corresponding rate coefficients are reported. In particular, a relatively large cross sections for N− ion formation at low energy of the incident electron and for vibrationally excited NO target are predicted. Finally, molecular rotation effects are discussed.
Plasma activation of N2, CH4and CO2: an assessment of the vibrational non-equilibrium time window
Authors: van de Steeg A W , Butterworth T , van den Bekerom D C M , Silva A F , van de Sanden M C M , van Rooij G J 
Published: September 2020

AbstractVibrational excitation potentially enhances the energy efficiency of plasma dissociation of stable molecules and may open new routes for energy storage and process electrification. Electron, vibrational and rotational temperatures were measured byin situThomson and Raman scattering in order to assess the opportunities and limitations of the essential vibration-translation non-equilibria in N2, CO2and CH4plasma. Electron temperatures of 1.1–2.8 eV were measured in N2and CH4. These are used to confirm predominant energy transfer to vibrations after an initial phase of significant electronic excitation and ionization. The vibrational temperatures initially exceed rotational temperatures by almost 8000 K in N2, by 900 K in CO2, and by 300 K in CH4. Equilibration is observed at the 0.1 ms timescale. Based on the vibrational temperatures, the vibrational loss rates for different channels are estimated. In N2, vibrational quenching via N atoms is identified as the dominant equilibration mechanism. Atomic nitrogen population reaches a mole fraction of more than 1%, as inferred from the afterglow emission decay, and explains a gas heating rate of 25 Kμs−1. CH4equilibration at 1200 K is predominantly caused by vibrational-translational relaxation in CH4–CH4collisions. As for CO2, vibrational-translational relaxation via parent molecules is responsible for a large fraction of the observed heating, whereas product-mediated VT relaxation is not significantly contributing. It is suggested that electronic excitation, followed by dissociation or quenching contributes to the remaining heat generation. In conclusion, the time window to profit from vibrational excitation under the present conditions is limiting practical application.
Conceptual design and multifield coupling behavior of magnetically propelled fish-like swimmers
Authors: Gao Wei , Wang Xingzhe 
Published: September 2020

Abstract
Composites reinforced with ferromagnetic particles have been widely used in various engineering areas and have been extensively attracted more attention for the past decade because of their magnetic dependent properties can be dramatically altered by applying a magnetic field. In this study, a conceptual model based on the soft composites filled with magnetoactive particles was proposed, and the numerical research of magneto-fluid-solid coupling behaviours for a soft biomimetic robot fish driven magnetically was carried out. Under the action of magnetic field, the magnetic sensitive materials distributed in specific parts of the robot fish body will deform and cause the whole body of the fish swinging, to flap the liquid and generate forward thrust, resulting in pushing the fish forward. The corresponding multifield coupling equations for the mechanism and responses of magnetically propelled fish-like swimmers were developed and simulated numerically using the COMSOL multiphysics software. The effects of the tail length, the modulus of magnetic sensitive materials and spatial arrangement feature on the swimming ability of the fish-like structure were analyzed in detail. The relevant results are expected to provide a theoretical guidance for the potential applications of such biomimetic devices in intelligent far-field driving, drug delivery and other fields.
Hand Gesture Recognition of Double-Channel EMG Signals Based on Sample Entropy and PSO-SVM
Authors: Zhang He , Su Mengwei 
Published: September 2020

Abstract
Considering wearable device requirements, such as injury-free, comfortable and light, a new method based on sample entropy and PSO-SVM for double-channel EMG signals recognition is proposed. First, the signal is segmented by using a non-overlapping adjacent sliding window. And the sample entropy of the valid information after signal in each window is decomposed by EMD is fast calculated to obtain a feature vector. Then the paper improved the PSO algorithm from two aspects. On the one hand, using a dynamic topology improved the impact of “premature” by replacing the global optimal value with neighborhood optimal value. On the other hand, in order to increase the probability of particles jumping out of local optimum, according to the principle of partition crossover, reset the particles that are trapped in local optimum. Next, the multi-window fusion decision result of the adaptive weight voting is used to identify the gesture. Finally, five methods are used to classify the five combined fingers movements about pinch gestures and compare with each other. The experimental results show that the algorithm (IPSO-SVM-WMV) combined sample entropy has strong robustness, real-time and anti-interference ability in double-channel EMGs signal recognition and the classification accuracy is better than PSO-SVM.
Music Style Transfer with Vocals Based on CycleGAN
Authors: Ye Hongliang , Zhu Wanning 
Published: September 2020

Abstract
In recent years, with the development of generative adversarial networks (GAN), the application of generative adversarial networks has gradually matured. An important application area for generating adversarial networks is called neural style transfer. In recent years, neural style transfer has played a major role in the field of image applications. However, it performed poorly in the music field. In addition, algorithms in the field of music style transfer have poor effect on the style transfer of music with vocals. Therefore, this paper extracts the CQT features and Mel spectrogram features of music, and then uses CycleGAN to transfer the styles of the CQT features and Mel spectrogram mapping pictures, and finally realizes the style transfer of music. On the classifier we trained, the average style transfer rate of music that meets our requirements reached 94.07%.
Research on Military Radio Fault Diagnosis Method Based on Fuzzy Neural Network
Authors: Wang Pan , Guo Wenpu , Yan Luhong 
Published: September 2020

Abstract
In view of the complexity, correlation and fuzziness of military radio faults, a fault diagnosis strategy combining fuzzy neural network with expert system is proposed, and the fault diagnosis method based on T-S fuzzy neural network is mainly studied. The fuzzy neural network model was established by MATLAB R2017a, and the simulation experiment was carried out. The experimental results show that the T-S fuzzy neural network model has good generalization ability, fault tolerance ability and self-adaptability, can quickly locate fault causes, greatly improve the diagnostic efficiency, and can be used in fault diagnosis of military radios.
Optimization and Application of GM(1,1) Model Based on Adams Formula
Authors: Shen Yan , Song Xingyu , Wang Xuesong , Han Shuai 
Published: September 2020

Abstract
Model of GM(1,1) uses the least square method to solve the parameters and the parameter value is one of the main sources of errors in the model of GM(1,1) prediction. In order to improve accuracy of the GM(1,1) prediction model, we construct an improved methods for parameter identification of the optimized models of GM(1,1) based on the fifth and sixth-order Adams implicit formula is proposed. At the same time, the optimized models of GM(1,1) is analysed and compared. Use data of the number of employees in the tertiary industry nationwide from 2014 to 2016 as the testing standard to verify the prediction effect of the improved GM(1,1) model. Numeral examples show that the improved GM(1,1) model has good applicability and effectively improves the prediction accuracy of the traditional model.
Voice Control System Based on Zynq FPGA
Authors: Liu Weili 
Published: September 2020

Abstract
In this paper, a speech recognition system is designed and the relevant hard-ware environment is built through Zynq FPGA AX7020 platform. In this system, the feature extraction of speech signals is based on MFCC (mel-frequency cepstrum coefficients). The algorithm in this system includes Pre-emphasis, Framing and Windowing, FFT, MFCC Parameter Calculation, VED Endpoint Detection and DTW Operations processes commonly used in speech system design. In this paper, the speech recognition algorithm is implemented on Zynq FPGA platform and also simulated in Matlab. At the same time, audio module AN831 is adopted in the hardware part to realize the sound acquisition function. Through the comparison of experimental data, it is found that the average recognition rate in Matlab simulation is 86.67%, while in Zynq FPGA platform test, the recognition rate is 80.67%. Using Zynq FPGA AX7020 as a platform to realize speech recognition, the recognition rate is higher than the traditional speech recognition technology.
Deep Belief Net-Based Fault Diagnosis of Flight Control System Sensors
Authors: Guo Yingnan , Ning Wenhui , Wan Fangyi 
Published: September 2020

Abstract
The present study implements a model based on the deep belief net (DBN) into the sensor fault diagnosis of the flight control system. The principle of DBN system identification was adopted to simulate and establish a nonlinear observer of the unmanned aerial vehicle (UAV) for the online estimation of sensors’ output, which identified the fault type by analyzing the residuals of estimated data and the actual output. After the fault detection is completed, the measured value of the faulty sensor is isolated and replaced by the observer-generated value, in order to ensure the UAV normal flight. The proposed DBN model uses the data of normal flight control system sensors as training samples for offline training. A flight control digital simulation system was established to select the optimal DBN model via comparative test runs. Eventually, the common faults of sensors were analyzed and diagnosed online. The results obtained strongly indicate that the proposed method ensures a rapid and accurate diagnostics and isolation of faults, as well as provides a proper signal reconstruction.
Urbanisation’s contribution to climate warming in Great Britain
Authors: Bassett R , Young P J , Blair G S , Cai X-M , Chapman L 
Published: September 2020

Abstract
Urbanisation is changing the climate of the world we live in. In Great Britain (GB) 5.8% of the total land area is covered by artificial surfaces, increasing from 4.3% in 1975. Aside from associated loss of farmland, biodiversity and a range of ecosystem services, changing to urban form warms the Earth’s surface: the urban heat island (UHI) effect. Standard estimates of temperature changes do not account for urbanisation (i.e. use of rural-only stations or removal of urban bias in observations), meaning that anthropogenic modifications to the land surface may be causing the surface-level atmosphere to warm quicker than those estimates suggest. Using observations from a high-density urban monitoring network, we show that locally this warming (instantaneously) may be over 8 °C. Based on the relationships between UHI intensity, urban fraction and wind speed in this network, we create a statistical model and use it to estimate the current daily-mean urban warming across GB to be 0.04 °C [0.02 °C –0.06 °C]. Despite this climate contribution appearing small (94% of GB’s land cover for the time-being is still rural), we show that half of GB’s population currently live in areas with average daily-mean warming ∼0.4 °C. Under heatwave conditions our high estimates show 40% of GB’s population may experience over a 1 °C daily-mean UHI. Furthermore, simply due to urbanisation (1975–2014) we estimate GB is warming at a rate equivalent and in addition to 3.4% [1.9%–5.0%] of the observed surface-level warming calculated from background stations. In the fastest urbanising region, South East GB, we find that these warming rates are up to three times faster. The methodology is straightforward and can be readily extended to other countries or updated as future land cover data becomes available.
Dual drug delivery system based on pH-sensitive silk fibroin/alginate nanoparticles entrapped in PNIPAM hydrogel for treating severe infected burn wound
Authors: Rezaei Fatemeh , Damoogh Sheyda , Reis Rui L , Kundu Subhas C , Mottaghitalab Fatemeh , Farokhi Mehdi 
Published: September 2020

Abstract
Herein, the pH-sensitive vancomycin (VANCO) loaded silk fibroin-sodium alginate nanoparticles (NPs) embedded in poly(N-isopropylacrylamide) (PNIPAM) hydrogel containing epidermal growth factor (EGF) are introduced for treating chronic burn wound infections. The hybrid system was developed to control the release rates of an antibiotic and growth factor for optimal treatment of burn infections. VANCO had a pH responsive release behavior from the nanoparticle (NP) and showed higher release rate in an alkaline pH compared to the neutral pH during 10 d. About 30% of EGF was also released from the hydrogel within 20 d. The released VANCO and EGF preserved their bioactivity more than ∼ 80%. The suitable physico-chemical properties and cellular behaviors of PNIPAM hydrogel supported the proliferation and growth of the fibroblast cells. Furthermore, the higher re-epithelialization with good wound contraction rate, neovascular formation, and expression of transforming growth factor-beta were observed in S. aureus infected rat burn wound by using the hydrogel containing VANCO and EGF compared with untreated wounds and hydrogel alone. The wound infection was also significantly reduced in the groups treated with the hydrogels containing VANCO. Overall, in vitro and in vivo results suggested that developed hybrid system would be a promising construct to treat severe wound infection.
Smart wing load alleviation through optical fiber sensing, load identification, and deep reinforcement learning
Authors: Wada Daichi , Tamayama Masato , Murayama Hideaki 
Published: September 2020

Abstract
The use of optical fiber sensors has been considered to realize smart structures, which can sense and respond to environments. To develop this concept in aviation, this paper reports on a smart wing framework that senses and responds to the environment to alleviate the wing structural loads. The wing is equipped with optical fiber sensors that measure the strain distributions on the wing surface. Considering the strains, a group of neural networks determine the wing load distributions and angle of attacks. This information is fed into a controller that drives multiple flaps to re-distribute the loads. The controller is trained via a deep reinforcement learning technique. The wind tunnel experiments demonstrated that the proposed closed-loop control could alleviate the bending moment by 56.6% on average over the test duration from the initial state while the total load variations could be maintained within a range of ±5 N for 87.1% of the test duration. The proposed approach was also applicable to another scenario involving variations in the target loads, and the results indicated the generalized applicability of the neural-network-based controller trained via deep reinforcement learning.
Particle Gibbs sampling for Bayesian phylogenetic inference
Authors: Wang Shijia , Wang Liangliang 
Published: September 2020

Abstract

Motivation
The combinatorial sequential Monte Carlo (CSMC) has been demonstrated to be an efficient complementary method to the standard Markov chain Monte Carlo (MCMC) for Bayesian phylogenetic tree inference using biological sequences. It is appealing to combine the CSMC and MCMC in the framework of the particle Gibbs (PG) sampler to jointly estimate the phylogenetic trees and evolutionary parameters. However, the Markov chain of the PG may mix poorly for high dimensional problems (e.g. phylogenetic trees). Some remedies, including the PG with ancestor sampling and the interacting particle MCMC, have been proposed to improve the PG. But they either cannot be applied to or remain inefficient for the combinatorial tree space.

Results
We introduce a novel CSMC method by proposing a more efficient proposal distribution. It also can be combined into the PG sampler framework to infer parameters in the evolutionary model. The new algorithm can be easily parallelized by allocating samples over different computing cores. We validate that the developed CSMC can sample trees more efficiently in various PG samplers via numerical experiments.

Availability and implementation
The implementation of our method and the data underlying this article are available at https://github.com/liangliangwangsfu/phyloPMCMC.

Supplementary information
Supplementary data are available at Bioinformatics online.
COVID-Align: accurate online alignment of hCoV-19 genomes using a profile HMM
Authors: Lemoine Frédéric , Blassel Luc , Voznica Jakub , Gascuel Olivier 
Published: September 2020

Abstract

Motivation
The first cases of the COVID-19 pandemic emerged in December 2019. Until the end of February 2020, the number of available genomes was below 1000 and their multiple alignment was easily achieved using standard approaches. Subsequently, the availability of genomes has grown dramatically. Moreover, some genomes are of low quality with sequencing/assembly errors, making accurate re-alignment of all genomes nearly impossible on a daily basis. A more efficient, yet accurate approach was clearly required to pursue all subsequent bioinformatics analyses of this crucial data.

Results
hCoV-19 genomes are highly conserved, with very few indels and no recombination. This makes the profile HMM approach particularly well suited to align new genomes, add them to an existing alignment and filter problematic ones. Using a core of ∼2500 high quality genomes, we estimated a profile using HMMER, and implemented this profile in COVID-Align, a user-friendly interface to be used online or as standalone via Docker. The alignment of 1000 genomes requires ∼50 minutes on our cluster. Moreover, COVID-Align provides summary statistics, which can be used to determine the sequencing quality and evolutionary novelty of input genomes (e.g. number of new mutations and indels).

Availability and implementation
https://covalign.pasteur.cloud, hub.docker.com/r/evolbioinfo/covid-align.

Supplementary information
Supplementary data are available at Bioinformatics online.