bluuebunny/crossref_metadata_2025 huggingface dataset:
Accuracy of Patient-Specific 3D Printed Drill Guides in the Placement of a Canine Coxofemoral Toggle Pin through a Minimally Invasive Approach
Authors: Darrow Brett G. , Snowdon Kyle A. , Hespel Adrien
Published: November 2020

Objective The aim of this study was to evaluate the accuracy of patient-specific three-dimensional printed drill guides (3D-PDG) for the placement of a coxofemoral toggle via a minimally invasive approach.

Materials and Methods Pre-procedure computed tomography (CT) data of 19 canine cadaveric hips were used to design a cadaver-specific 3D-PDG that conformed to the proximal femur. Femoral and acetabular bone tunnels were drilled through the 3D-PDG, and a coxofemoral toggle pin was placed. The accuracy of tunnel placement was evaluated with post-procedure CT and gross dissection.

Results Coxofemoral toggle pins were successfully placed in all dogs. Mean exit point translation at the fovea capitis was 2.5 mm (0.2–7.5) when comparing pre- and post-procedure CT scans. Gross dissection revealed the bone tunnel exited the fovea capitis inside (3/19), partially inside (12/19) and outside of (4/19) the ligament of the head of the femur. Placement of the bone tunnel through the acetabulum was inside (16/19), partially inside (1/19) and outside (2/19) of the acetabular fossa. Small 1 to 2 mm articular cartilage fragments were noted in 10 of 19 specimens.

Clinical Significance Three-dimensional printed drill guide designed for coxofemoral toggle pin application is feasible. Errors are attributed to surgical execution and identification of the borders of the fovea capitis on CT data. Future studies should investigate modifications to 3D-PDG design and methods. Three-dimensional printed drill guide for coxofemoral toggle pin placement warrants consideration for use in select clinical cases of traumatic coxofemoral luxation.
Discontinued Use of Outpatient Portable Intermittent Pneumatic Compression Devices May Be Safe for Venous Thromboembolism Prophylaxis in Primary Total Knee Arthroplasty Using Low-Dose Aspirin
Authors: Tang Alex , Zak Stephen , Lygrisse Katherine , Slover James , Meftah Morteza , Lajam Claudette , Schwarzkopf Ran , Macaulay William
Published: November 2020

Venous thromboembolism (VTE) is a rare, but serious complication following total knee arthroplasty (TKA). Current VTE guidelines recommend pharmacologic agents with or without intermittent pneumatic compression devices (IPCDs). At our institution, both 81-mg aspirin (ASA) twice a day (BID) and portable IPCDs were previously prescribed to TKA patients at standard risk for VTE, but the IPCDs were discontinued and patients were treated with ASA alone going forward. The aim of this study is to determine if discontinued use of outpatient IPCDs is safe and does not increase the rate of VTE or any other related complications in patients following TKA. A retrospective review of 2,219 consecutive TKA cases was conducted, identifying patients with VTE, bleeding complications, infection, and mortality within 90 days postoperatively. Patients were divided into two cohorts. Patients in cohort one received outpatient IPCDs for a period of 14 days (control), while those in cohort two did not (ASA alone). All study patients received inpatient IPCDs and were maintained on 81-mg ASA BID for 28 days. A posthoc power analysis was performed using a noninferiority margin of 0.25 (α = 0.05; power = 80%), which showed that our sample size was fully powered for noninferiority for our reported deep vein thrombosis (DVT) rates, but not for pulmonary embolism (PE) rates. A total of 867 controls and 1,352 patients treated with ASA alone were identified. Only two control patients were diagnosed with a PE (0.23%), while one patient in the ASA alone group had DVT (0.07%). There was no statistical difference between these rates (p = 0.33). Furthermore, no differences were found in bleeding complications (p = 0.12), infection (p = 0.97), or 90-day mortality rates (p = 0.42) between both groups. The discontinued use of outpatient portable IPCDs is noninferior to outpatient IPCD use for DVT prophylaxis. Our findings suggest that this protocol change may be safe and does not increase the rate of VTE in standard risk patients undergoing TKA while using 81-mg ASA BID.
Birth Weight Standard Deviation Score is a Significant Determinant of Serum Urotensin-II Levels at Term-Equivalent Age in Preterm Infants
Authors: Ebata Akio , Nakano Yuya , Ujiie Gakuto , Ishii Yoko , Shimizu Takeshi , Fujii Takanari , Mizuno Katsumi
Published: November 2020

Objective Urotensin II (U-II) is a potent vasoconstrictor peptide, and increased U-II levels are associated with atherosclerosis and hypertension in adults. Low birth weight (LBW) infants have higher risks of such diseases in the future. A small number of nephrons is one of possible mechanism underlying these risks in LBW infants, while vascular elasticity and cardiac function might be another important factor. The objective of this study is to evaluate U-II levels in preterm LBW infants at an early stage of life and determine perinatal factors associated with U-II levels.

Study Design The study population consisted of 57 preterm LBW infants (26 males and 31 females), including 49 appropriate for gestational age (AGA) and 8 small for gestational age (SGA) infants, born at a gestational age of ≤34 weeks with a mean birth weight of 1,589 g. Serum U-II levels were measured at term-equivalent age to evaluate perinatal factors related to serum U-II levels.

Results Preterm SGA infants had significantly higher serum U-II levels than preterm AGA infants at term-equivalent age (p = 0.019). Serum U-II levels in preterm LBW infants at term-equivalent age were inversely correlated with birth weight standard deviation (SD) score in a simple regression analysis (r =  − 0.395, p = 0,002) and the correlation was maintained in the multiple regression analysis.

Conclusion Our results indicate that birth weight SD score might be associated with serum U-II levels in preterm LBW infants at term-equivalent age. Further studies are required to determine whether U-II levels at an early stage of life might influence the risk of atherosclerosis and hypertension.

Key Points
Blood Management in Total Knee Arthroplasty: A Nationwide Analysis from 2011 to 2018
Authors: Warren Jared A. , McLaughlin John P. , Molloy Robert M. , Higuera Carlos A. , Schaffer Jonathan L. , Piuzzi Nicolas S.
Published: November 2020

Both advances in perioperative blood management, anesthesia, and surgical technique have improved transfusion rates following primary total knee arthroplasty (TKA), and have driven substantial change in preoperative blood ordering protocols. Therefore, blood management in TKA has seen substantial changes with the implementation of preoperative screening, patient optimization, and intra- and postoperative advances. Thus, the purpose of this study was to examine changes in blood management in primary TKA, a nationwide sample, to assess gaps and opportunities. The American College of Surgeons National Surgical Quality Improvement Program database was used to identify TKA (n = 337,160) cases from 2011 to 2018. The following variables examined, such as preoperative hematocrit (HCT), anemia (HCT <35.5% for females and <38.5% for males), platelet count, thrombocytopenia (platelet count < 150,000/µL), international normalized ration (INR), INR > 2.0, bleeding disorders, preoperative, and postoperative transfusions. Analysis of variances were used to examine changes in continuous variables, and Chi-squared tests were used for categorical variables. There was a substantial decrease in postoperative transfusions from high of 18.3% in 2011 to a low of 1.0% in 2018, (p < 0.001), as well as in preoperative anemia from a high of 13.3% in 2011 to a low of 9.5% in 2016 to 2017 (p < 0.001). There were statistically significant, but clinically irrelevant changes in the other variables examined. There was a HCT high of 41.2 in 2016 and a low of 40.4 in 2011 to 2012 (p < 0.001). There was platelet count high of 247,400 in 2018 and a low of 242,700 in 201 (p < 0.001). There was a high incidence of thrombocytopenia of 5.2% in 2017 and a low of low of 4.4% in 2018 (p < 0.001). There was a high INR of 1.037 in 2011 and a low of 1.021 in 2013 (p < 0.001). There was a high incidence of INR >2.0 of 1.0% in 2012 to 2015 and a low of 0.8% in 2016 to 2018 (p = 0.027). There was a high incidence of bleeding disorders of 2.9% in 2013 and a low of 1.8% in 2017 to 2018 (p < 0.001). There was a high incidence of preoperative transfusions of 0.1% in 2011 to 2014 and a low of <0.1% in 2015 to 2018 (p = 0.021). From 2011 to 2018, there has been substantial decreases in patients receiving postoperative transfusions after primary TKA. Similarly, although a decrease in patients with anemia was seen, there remains 1 out 10 patients with preoperative anemia, highlighting the opportunity to further improve and address this potentially modifiable risk factor before surgery. These findings may reflect changes during TKA patient selection, optimization, or management, and emphasizes the need to further advance multimodal approaches for perioperative blood management of TKA patients. This is a Level III study.
Accretion disks around naked singularities
Authors: Guo Jun-Qi , Joshi Pankaj S , Narayan Ramesh , Zhang Lin
Published: November 2020

We investigate here the thermal properties of accretion disks in a spacetime for some galactic density profiles in spherical symmetry. The matter distributions have a finite outer radius with a naked central singularity. The luminosities of the accretion disks for some density profile models are found to be higher than those for a Schwarzschild black hole of the same mass. The slopes for the luminosity distributions with respect to frequencies are significantly different, especially at higher frequencies, from that in the Schwarzschild black hole case. Such features may be used to distinguish black holes from naked singularities. The efficiencies for the conversion of mass energy of the accreting gas into radiation and the strength of naked singularities are analyzed. The novel feature that we find is, the strength of the singularity is different depending on the profiles considered, and the stronger the singularity is, the higher is the efficiency for the accretion disk.
Event horizon wrinklification
Authors: McInnes Brett , Ong Yen Chin
Published: November 2020

The possible existence of stable black holes with entropies larger than the corresponding Schwarzschild black hole has been discussed extensively. The recently proposed ‘rough’ black holes provide a concrete example of this. The fear is that, in accordance with the second law of thermodynamics, the familiar smooth-skinned black holes might spontaneously ‘wrinklify’ into such an object. We show that this fear is to some extent justified, in the sense that AdS black holes with more entropy than the AdS-Schwarzschild black hole of the same mass do exist.
Scattering of axial gravitational wave pulses by monopole black holes and QNMs: a semianalytic approach
Authors: Gußmann Alexander
Published: November 2020

We study scattering of short Gaussian pulses of axial gravitational waves by a spherically symmetric black hole that has swallowed one or more global monopoles. We qualitatively show how the response of the black hole to the impinging pulses depends both on the number of monopoles the black hole has swallowed and on the symmetry breaking scale of the model which gave rise to the monopoles. We use semianalytical methods to determine the corresponding quasinormal modes that get excited by the impinging pulses and that get imprinted in the black hole’s response to the pulses. When generalized to the case of rotating black holes, such modes are also expected to show up in various other dynamical processes such as the ringdown phase of a binary black hole merger in case at least one of the companion black holes of the binary has swallowed one or more global monopoles.
Rotating and charged Gauss–Bonnet BTZ black holes
Authors: Hennigar Robie A , Kubizňák David , Mann Robert B
Published: November 2020

We obtain charged and rotating black hole solutions to the novel 3D Gauss–Bonnet theory of gravity recently proposed, both of which generalize the Banados–Teitelboim–Zanelli (BTZ) metric. The charged solutions are obtained in the Maxwell and Born–Infeld theories and feature ‘universal thermodynamics’—identical to the thermodynamics of their Einstein cousins. The rotating Gauss–Bonnet BTZ black holes are quite exceptional and are not of constant curvature. They possess an ergoregion and outer horizon, but do not have an inner horizon. We present their basic properties and show that they break the universality of thermodynamics present for their static charged counterparts. Extending our considerations to higher dimensions, we also obtain novel 4D Gauss–Bonnet rotating black strings.
Time-resolved quantum beats in the fluorescence of helium resonantly excited by XUV radiation
Authors: LaForge A C , Benediktovitch A , Sukharnikov V , Krušič Š , Žitnik M , Debatin M , Falcone R W , Asmussen J D , Mudrich M , Michiels R , Stienkemeier F , Badano L , Callegari C , Di Fraia M , Ferianis M , Giannessi L , Plekan O , Prince K C , Spezzani C , Rohringer N , Berrah N
Published: November 2020

We report on the observation of time-resolved quantum beats in the helium fluorescence from the transition 1s3p → 1s2s, where the initial state is excited by XUV free electron laser radiation. The quantum beats originate from the Zeeman splitting of the magnetic substates due to an external magnetic field. We perform a systematic study of this effect and discuss the possibilities of studying this phenomenon in the XUV and x-ray regime.
Establishment of a Reax force field to study SF6 gas over-thermal decomposition
Authors: Zeng Fuping , Li Haotian , Zhang Mingxuan , Li Chen , Yao Qiang , Tang Ju
Published: November 2020

This paper focuses on the problem of missing parameters in the Reax force field containing S and F elements. First, density functional theory was used to scan SF6 and low-fluoride sulfide molecules to obtain the basic dataset for the Reax force field. The Monte Carlo method was then used to perform fitting optimization and quality verification of the established force field. Based on the established force field, molecular dynamics studies were carried out on the over-thermal decomposition of a SF6 gas-insulating medium, and infrared spectra were obtained, describing the vibration characteristics of SF6 and low-fluoride sulfide molecules. According to the vibration modes revealed by the infrared spectra, a potential-energy surface scan was performed. This paper focuses on the analysis of the total energy, potential energy and kinetic energy of SF6 and low-fluoride sulfide molecules moving at different temperatures. The results show that the energy error of the established force field is about 10% when describing the bonding and breaking processes of SF6, SF5, SF4, SF3 and SF2 molecules, which verifies the reliability of the reactive force field method when used to describe molecular behavior. The research work detailed in this paper lays the foundation for the next systematic study of the microscopic physical mechanisms of SF6 over-thermal decomposition.
Measuring how much an object has a ring-like shape
Authors: Žunić Joviša
Published: November 2020

An image-based algorithmic tool for measuring how much an object’s shape looks like a ring is presented. The objects whose shapes have such a structure appear in nature very often, e.g. in nanotechnology, biology, medicine, industry, etc. The method proposed has several formal desirable properties, including invariance ones. In addition, the method is easy to implement and is robust (e.g. with respect to noise).
Green synthesis as a simple and rapid route to protein modified magnetic nanoparticles for use in the development of a fluorometric molecularly imprinted polymer-based assay for detection of myoglobin
Authors: Sullivan Mark V , Stockburn William J , Hawes Philippa C , Mercer Tim , Reddy Subrayal M
Published: November 2020

We have developed a low-cost molecularly imprinted polymer (MIP)-based fluorometric assay to directly quantify myoglobin in a biological sample. The assay uses a previously unreported method for the development of microwave-assisted rapid synthesis of aldehyde functionalized magnetic nanoparticles, in just 20 min. The aldehyde functionalized nanoparticles have an average size of 7.5 nm ± 1.8 and saturation magnetizations of 31.8 emu g−1 with near-closed magnetization loops, confirming their superparamagnetic properties. We have subsequently shown that protein tethering was possible to the aldehyde particles, with 0.25 ± 0.013 mg of myoglobin adsorbed to 20 mg of the nanomaterial. Myoglobin-specific fluorescently tagged MIP (F-MIP) particles were synthesized and used within the assay to capture myoglobin from a test sample. Excess F-MIP was removed from the sample using protein functionalized magnetic nanoparticles (Mb-SPION), with the remaining sample analyzed using fluorescence spectroscopy. The obtained calibration plot of myoglobin showed a linear correlation ranging from 60 pg ml−1 to 6 mg ml−1 with the limit of detection of 60 pg ml−1. This method was successfully used to detect myoglobin in spiked fetal calf serum, with a recovery rate of more than 93%.
In situ probing of the thermal treatment of h-BN towards exfoliation
Authors: Yan Zhengyu , Abdelkader Amor , Day Sarah , Tang Chiu , Casiraghi Cinzia , Mirihanage Wajira
Published: November 2020

Two-dimensional (2D) hexagonal boron nitride (h-BN) is becoming increasingly interesting for wider engineering applications. Thermal exfoliation is being suggested as a facile technology to produce large quantities of 2D h-BN. Further optimization of the process requires fundamental understanding of the exfoliation mechanism, which is hardly realized by ex situ techniques. In this study, in situ synchrotron x-ray powder diffraction experiments are conducted while heat treating bulk h-BN up to 1273 K. During the heating process, linear expansion of c-axis is observed and the contraction of a-axis up to around 750 K is consistent with previous research. However, a changing behavior from contraction to expansion in a-axis direction is newly observed when heating over 750 K. With the consideration of previous thermally oxidation studies, a hypothesis of thermal assisted exfoliation with oxygen interstitial and substitution of nitrogen at high temperature is proposed.
Particle trajectories and its charging behaviors: effect of gas type and electric field
Authors: Sun Jixing , Zhi Qingyun , Cui Boyuan , Bian Kai , Chen Weijiang , Yan Xianglian
Published: November 2020

Conductive particles in the gas insulated transmission lines (GIL) induce the breakdown between electrodes or the flashover along insulators. To solve the problem of particle moving and realize the particle-moving regulation, particle trajectories should firstly be determined in air and SF6. This paper presents the results of particle trajectories and its charging behaviors at vacuum and SF6, respectively. Metal particles with different materials and sizes were introduced and the charge quantity was calculated. The results showed that the particle lift-off electric field in SF6 was higher than that in air under the same gas pressure, that is, the charge on particle in SF6 was about 0.789 times lower than that in air under the same condition. Besides, the lift-off electric field of particle increased with the pressure increase of SF6. The charge on particle was affected by the concentration of electric field near particle and the electrical negative features of SF6. The work provided the data support for development of DC GIL in particle defect suppression.
Evaluating the image quality of combined positron emission tomography-magnetic resonance images acquired in the pelvic radiotherapy position
Authors: Wyatt Jonathan J , Howell Elizabeth , Lohezic Maelene , McCallum Hazel M , Maxwell Ross J
Published: November 2020

Positron emission tomography-magnetic resonance (PET-MR) scanners could improve radiotherapy planning through combining PET and MR functional imaging. This depends on acquiring high quality and quantitatively accurate images in the radiotherapy position. This study evaluated PET-MR image quality using a flat couch and coil bridge for pelvic radiotherapy. MR and PET image quality phantoms were imaged in three setups: phantom on the PET-MR couch with anterior coil on top (diagnostic), phantom on a flat couch with coil on top (couch), and phantom on the flat couch with coil on a coil bridge (radiotherapy). PET images were also acquired in each setup without the anterior coil. PET attenuation correction of the flat couch and coil bridge were generated using kilovoltage computed tomography (CT) images and of the anterior coil using megavoltage CT images. MR image quality was substantially affected, with MR signal to noise ratio (SNR) relative to the diagnostic setup of 89% ± 2% (mean ± standard error of the mean, couch) and 54% ± 1% (radiotherapy), likely due to the increased distance between the patient and receive coils. The reduction impacted the low-contrast detectability score: 23 ± 1 (diagnostic), 19.7 ± 0.3 (couch) and 15 ± 1 (radiotherapy). All other MR metrics agreed within one standard error. PET quantitative accuracy was also affected, with measured activity with anterior coil being different to diagnostic without anterior coil by −16.7% ± 0.2% (couch) and −17.7 ± 0.1% (radiotherapy), without attenuation correction modification. Including the couch and coil bridge attenuation correction reduced this difference to −7.5% ± 0.1%, and including the anterior coil reduced this to −2.7% ± 0.1%. This was better than the diagnostic setup with anterior coil (difference −8.3% ± 0.2%). This translated into greater PET SNR performance for the fully corrected radiotherapy setup compared to diagnostic with coil. However contrast recovery was unchanged by the modified attenuation correction, with the diagnostic setup remaining ∼2% better. Quantitative PET in the radiotherapy setup is possible if appropriate attenuation correction is used. Pelvic radiotherapy PET-MR imaging protocols will need to consider the impact on PET-MR image quality.
Toward a general quasi-linear approach for the instabilities of bi-Kappa plasmas. Whistler instability
Authors: Moya P S , Lazar M , Poedts S
Published: November 2020

Kappa distributions are ubiquitous in space and astrophysical poorly collisional plasmas, such as the solar wind, suggesting that microscopic and macroscopic properties of these non-equilibrium plasmas are highly conditioned by the wave–particle interactions. The present work addresses the evolution of anisotropic bi-Kappa (or bi-κ-)distributions of electrons triggering instabilities of electromagnetic electron-cyclotron (or whistler) modes. The new quasi-linear approach proposed here includes time variations of the κ parameter during the relaxation of temperature anisotropy. Numerical results show that κ may increase for short interval of times at the beginning, but then decreases toward a value lower than the initial one, while the plasma beta and temperature anisotropy indicate a systematic relaxation. Our results suggest that the electromagnetic turbulence plays an important role on the suprathermalization of the plasma, ultimately lowering the parameter κ. Even though the variation of κ is in general negative (

Δ
κ
<
0

) this variation seems to depend of the initial conditions of anisotropic electrons, which can vary very much in the inner heliosphere.
Double explosive transitions to synchronization and cooperation in intertwined dynamics and evolutionary games
Authors: Li Xuelong , Dai Xiangfeng , Jia Danyang , Guo Hao , Li Shudong , Cooper Garth D , Alfaro-Bittner Karin , Perc MatjaŽ , Boccaletti Stefano , Wang Zhen
Published: November 2020

Collective behavior, from murmurations to synchronized beating of heart cells, governs some of the most beautiful and important aspects of nature. Likewise, cooperation—the act of sacrificing personal benefits for the common good—is one of the pillars of social evolution, and it is the basis for the emergence of collective organized actions from single-cell organisms to modern human societies. Here we merge these two phenomena into a single model, considering an ensemble of networked oscillators, where each oscillator can be either a cooperator or a defector, and with only cooperators contributing to synchrony. At the same time, the value of the order parameter in the neighborhood of each oscillator is considered as an effective local temperature which determines the strategy updating procedure in the evolutionary game. The emergence of cooperation is thus intertwined with that of synchronization, producing a novel and fascinating dynamics which includes a double explosive transition.
Deterministic secure quantum communication with and without entanglement
Authors: Elsayed Tarek A
Published: November 2020

We present a protocol for sending a message over a quantum channel with different layers of security that will prevent an eavesdropper from deciphering the message without being detected. The protocol has two versions where the bits are encoded in either pairs of entangled photons or separate photons. Unlike many other protocols, it requires a one-way, rather than a two-way, quantum channel and does not require a quantum memor. A quantum key is used to encrypt the message and both the key and the message are sent over the quantum channle with the same quantum encoding technique. The key is sent only if no eavesdropper is detected.
Dirac equation in (1 + 1) dimensional curved space-time: Bound states and bound states in continuum
Authors: Ghosh P , Roy P
Published: November 2020

We study Dirac equation in (1 + 1) dimensional curved space-time. In particular, it is shown that bound states can be found in the presence of interactions in certain curved spaces. It has also been shown that solutions of the free particle Dirac equation when mapped to some suitable curved spaces become bound states in continuum. A number of examples have been considered and complete solutions have been obtained analytically in each case.
Impact of referencing scheme on decoding performance of LFP-based brain-machine interface
Authors: Ahmadi Nur , Constandinou Timothy G , Bouganis Christos-Savvas
Published: November 2020

Objective. There has recently been an increasing interest in local field potential (LFP) for brain-machine interface (BMI) applications due to its desirable properties (signal stability and low bandwidth). LFP is typically recorded with respect to a single unipolar reference which is susceptible to common noise. Several referencing schemes have been proposed to eliminate the common noise, such as bipolar reference, current source density (CSD), and common average reference (CAR). However, to date, there have not been any studies to investigate the impact of these referencing schemes on decoding performance of LFP-based BMIs. Approach. To address this issue, we comprehensively examined the impact of different referencing schemes and LFP features on the performance of hand kinematic decoding using a deep learning method. We used LFPs chronically recorded from the motor cortex area of a monkey while performing reaching tasks. Main results. Experimental results revealed that local motor potential (LMP) emerged as the most informative feature regardless of the referencing schemes. Using LMP as the feature, CAR was found to yield consistently better decoding performance than other referencing schemes over long-term recording sessions. Significance. Overall, our results suggest the potential use of LMP coupled with CAR for enhancing the decoding performance of LFP-based BMIs.
RETRACTED: Research on the Reform of Accounting Teaching Mode under the Impact of Artificial Intelligence
Authors: Yue Jingyuan
Published: November 2020

The widespread application of artificial intelligence (AI) has brought impact to the traditional accounting industry. Colleges and universities should clarify the reform of accounting teaching in the era of big data, innovate teaching systems, reform teaching modes, and solve the problems encountered by students to ensure them can adapt to the current development of the times. This article will discuss the reform of accounting teaching mode under the impact of AI. There are problems in the process, but the the colleges and universities need to play the guiding role.
Innovative Research on the Teaching Mode of Piano Group Lessons in Higher Vocational Preschool Education Based on AI
Authors: Gang Liang
Published: November 2020

The current AI technology has penetrated into many aspects of the education field (as shown in figure 1), and has made innovations in teaching models, courses and systems. Based on the background of AI, the preschool piano group teaching of higher vocational education has gradually become a mode of personalized learning, adaptive learning, deep learning, and human-computer collaborative learning. This article will analyze the current situation of piano group lesson teaching and propose innovative strategies to improve piano group lesson teaching in higher vocational preschool education.
Research on the Practice of Talent Cultivation Based on the Improvement of Innovation Ability ——Taking Electrical Engineering Automation Technology As An Example
Authors: Jin Jing , Chen Yuanyuan
Published: November 2020

It is in the key period of institutions of higher learning education reform now. For electrical engineering automation students in education and training, in order to further improve their innovation and practice ability, colleges and universities can develop regular way of talent training scheme and cooperation between colleges to cultivate talents. It can improve the level of colleges of electrical engineering automation teaching and promote the employment.
A WaveNet based Ion Channel prediction Method
Authors: Teng Yukun , Chen Deheng , Zhou Yichun , Vegh Nathaniel M. , Zhang Ren
Published: November 2020

There are many diseases associated with the dysfunction of ion channels. Ion channels are a class of proteins embedded in cell membranes that serve principle physiological functions such as memorization, learning and pain signaling. In order to help scientists learn more about ion channels and how they cause diseases, a team in Liverpool University published a public dataset about Ion channels. This paper presents a Wavenet based model to predict the number of Ion channels open at each time point. Wavenet is a type of deep neural network designed for one-dimensional signals. We used the Kalman filter to denoise the original signals and compared WaveNet with classical machine learning methods like SVM and Naïve Bayes to show the superior performance of the WaveNet model.
An Implementation Method of Zero-trust Architecture
Authors: Chuan Tao , Lv Yao , Qi Zhenfei , Xie Linjiang , Guo Wei
Published: November 2020

With the development of the Internet, the company network architecture is also undergoing profound changes, and the boundaries between the original internal network and external network are becoming increasingly blurred with the emergence of cloud services. More and more company businesses are deployed on the cloud server, which increases the risk of data exchange between the cloud server and the intranet. An implementation method of zero-trust architecture is proposed in this paper to apply to this scenario. The method can ensure safe and reliable data exchange when the external application server accesses the internal network, effectively protect network communication and business access while not affecting the original internal network protection measures, and make the company network safer and controllable.
Geometry Embedded Multi-Task Network for Lane Detection and Classification
Authors: Zhao Zhendong , Yue Xiaotian , Sun Pengfei , Xie Jiexin
Published: November 2020

Lane detection and classification are key and fundamental problems in the field of autonomous driving. Deep learning based multi-task network is commonly built with convolutional neural networks (CNNs) to handle these problems. Although existing methods have demonstrated the capability to capture the pixel-level representation and global guidance, the local geometric relationship of lanes are not taken into account to deal with the lanes with weak appearance coherence. This paper proposes geometry embedded multi-task network (GEMNet) with three branch layers, including bounding box regression, lane mask and lane classification. Convolutional operations are applied to feature maps generated by the top hidden layer of bounding box regression branch to explore the semantic context via geometric relationship. Moreover, it is able to facilitate the weight optimization in the shared layers and other branch layers simultaneously. GEMNet is evaluated on Cordova1 and Washington1 datasets, and Experimental results show that the proposed method outperforms the state-of-the art approaches. F1-Score can reach 0.906 and 0.881 with respect to Cordova1 and Washington1 datasets, respectively.
Design and Implementation of Automatic Exercises Evaluation System for Programming Courses
Authors: Liu Mingtao , Xu Rui , Wang Yunyu , Li Zhiyang , Zhang Xin
Published: November 2020

The evaluation of students’ exercise process is an important part of the formative evaluation for programming courses. However, it is difficult for teachers to complete the evaluation of each student’s exercise process manually. This paper proposes a design of an automatic exercises evaluation system, which can automatically analyse the amount of students’ exercise codes and help teachers to complete the evaluation. The system uses Python’s Pyhook3 library to monitor the keyboard input of the student’s computer. After text segmentation is performed on the student’s input code, the amount of the student’s exercise codes is statistically analysed, and the result can be used as an important indicator of the formative evaluation. Through the trial, it is found that there is a certain proportional relationship between the evaluation given by the system and the final test result of the students, which indicates the system can give a relatively objective evaluation of the students’ learning process.
Sentiment analysis of commodity reviews based on ALBERT-LSTM
Authors: Wang Hanqi , Hu Xiaoli , Zhang Huibing
Published: November 2020

Sentiment analysis of product reviews has now become one of the important research directions in the field of NLP, which is of great significance in helping merchants better understand user preferences and providing decision-making basis for other users to purchase products. Existing product review sentiment analysis models based on deep learning mostly use traditional word vector models. It is difficult to obtain the contextual semantic information of words, and there is a problem of “polysemous one word”. A product review sentiment analysis model combining ALBERT and LSTM is proposed. First, we use the ALBERT pre-training model to get the word vector containing sequence and semantic information. Then we use the LSTM model that can obtain long-distance semantic features for training. Finally, the emotional polarity of product reviews is classified and output through the emotional polarity discrimination layer. The experimental results on the data set of digital products of JD Mall show that the F1 value of the ALBERT-LSTM model is improved compared with the ALBERT and LSTM models.
A review of intelligent equipment development and and its auto-test technology
Authors: Kang Weijie , Xiao Jiyang , Chen Xin , Wen Bincheng
Published: November 2020

With the development of artificial intelligence technology, the intelligent level of equipment is gradually improved, and its internal structure is becoming more and more complicated. This not only facilitates users’ use, but also improves their maintenance and auto-test requirements. Taking flight simulator and other intelligent equipment as examples, this paper introduces the development history and research status of flight simulator and embedded training, and combs the development history and research status of intelligent equipment auto-test technology, which mainly involves test resource matching and fault diagnosis.
Design of Embedded Intelligent Car Control System Based on Android
Authors: Liu Jianying
Published: November 2020

With the rapid development of artificial intelligence technology, Unmanned intelligent vehicle technology, more and more people pay attention to it, it will change the way people live and travel, it can be applied to all aspects of urban construction and social development. Aiming at the instability of the intelligent car in the process of automatic driving, an embedded intelligent car control system based on Android is designed. Cortex-A9 is the core of the main control platform of the system, connect seven function modules, and through the data receiving module of the controller, it is connected with the Android application control system of the host computer, each function module can work independently and cooperate with each other, realize the automatic control of intelligent car, the intelligent car can move forward by itself, identify the path, grab the goods, patrol the line, avoid obstacles, and can run smoothly and quickly, at the same time, it can accept the manual control of Android interface.
Application of virtual reality technology in intelligent cold chain logistics system
Authors: Yao Li Juan , Li Jie , Han Jing Jing
Published: November 2020

The origin of virtual reality technology can be traced back to the 1950s decades ago. In recent years, with the rapid improvement of computer graphics processing, computing ability and other technologies, virtual reality technology and equipment began to mature. Starting from the application and development of virtual reality technology in various fields, this paper analyzes the basic application process of virtual reality technology, and describes the value and content of its application in the intelligent system of cold chain logistics.
Prediction analysis of shield vertical attitude based on GRU
Authors: Li Liang , Hu Changming , Hou Yajun
Published: November 2020

To solve the active control of the shield vertical attitude, this paper established the GRU model to realize the prediction of the pitch angle, which can reflect the shield vertical attitude. Firstly, the tunneling parameters, geological parameters and geometric parameters were selected as the influencing factors sets, and a series of data pre-processing strategies were established. And then, the GRU model was established, mainly including the division of training data, the optimization of hyperparameters, the determination of the objective function and optimization algorithm. Eventually, the shield interval from Chengdu was used to verify the new model. As a result, compared with the BP model and LSTM model, it could be found that the MGRU model had higher accuracy. This study could provide references for the prediction and help the engineers to realize the active control in the field of the shield attitude.
A white-box impersonation attack on the FaceID system in the real world
Authors: Guo Lu , Zhang Hua
Published: November 2020

The arcface model maximizes the classification boundary in the angular space, and is one type of the best models in the current face recognition model. We propose a mask sticker attack method to realize the impersonation attack of arcface model. The method specifically uses a parabolic transformation to simulate the bending situation of a sticker on a mask, and uses a multi-stage PGD attack to generate a adversarial sticker. Finally, the adversarial sticker is attached to the mask worn by the attacker to perform an impersonation attack. On targets of different skin colors, ages and genders, the method proposed in this article has an attack success rate of 0.65, and the final cosine similarity between attacker with mask sticker and target can reach about 0.5-0.7. In addition, we discuss the effect of sticker location and size on attack effect, as well as the generalization of this method on other models.
Data Augmentation For Chinese Text Classification Using Back-Translation
Authors: Ma Jun , Li Langlang
Published: November 2020

Text classification is a basic task in natural language processing. When the amount of data is insufficient, the classification accuracy will be greatly affected. We propose to use the back-translation method to expand three Chinese data sets used for text classification, and then train and predict the data sets through deep learning classification model. The results prove that using back-translation to expand the data is particularly helpful on a smaller dataset, it also can reduce the unbalanced distribution of samples and improve the classification performance.
Scheduling problem with release time and nested machining set constraints
Authors: Liu Xiaohua , Li Shuguang
Published: November 2020

For the makespan minimization problem on parallel machines in the presence of nested machining set restrictions, which is strongly NP-hard, we present the first polynomial time approximation scheme, and give the rigorous mathematical analysis for its approximation ratio.
Research on the characteristics of the growth risk sources of new ventures based on Immune Theory
Authors: Yang Bo , Yao Yuqi
Published: November 2020

Under the background of the national strategy of “mass innovation and entrepreneurship” and the information age, it is very important to use the artificial immune theory to characterize the growth risk sources of new ventures and make them become the quantitative index features available for the model. It can lay the foundation for the construction of risk identification model of new ventures. First of all, through the in-depth analysis of the characteristics of the growth risk of the new venture, the source of the growth risk is defined according to the classification of the growth risk of the new venture; then, through combing and summarizing the relevant research at home and abroad, this paper analyzes the influencing factors of R & D risk source, product risk source, management risk source and social network risk source, verifies and selects through empirical research, and constructs the identification index system on this basis; finally, the growth risk characteristic structure of new ventures based on artificial immunity is constructed, and risk identification indicators are engineered to transform qualitative indicators into quantitative indicators for model experiments. It provides a basic reference for the establishment of the new enterprise growth risk identification model, so as to effectively meet the in-depth decision support, information mining and discovery in the growth process of the new enterprise, thereby promoting the stable and healthy growth of the new enterprise.
Research and implementation of no-tillage information monitoring strategy based on Hadoop
Authors: Yang Hongwei , Xue Fucheng , Gao Sheng , Zhu Hongmei , Li Li
Published: November 2020

Based on the Hadoop, this paper uses linear regression algorithm to study the intelligent monitoring strategy of no-tillage information. In this paper, the regional computers in this system use Flume and Kafka to transfer large amounts of farming information from local node databases to HDFS (Hadoop Distributed File System), then process this data with Spark, whatever, the system uses time series linear regression algorithm to predict the fault of no-tillage. Compared with the no-tillage designed before, the system described in this paper not only reduces time delay but also improves the fault tolerance of data storage and the system stability. Field experiments have proved that the research of this strategy has an accuracy rate of up to 90%, which reduces the huge economic losses caused by machine failure.
Research on GPU-based Real-time Smoke Simulation Volume Rendering Algorithm
Authors: Deng Dingsheng
Published: November 2020

With the continuous development of the current film industry and animation industry, in the current smoke simulation, based on the use of GPU, real-time smoke simulation can be realized, so that real-time smoke simulation can be enhanced to achieve more smoke simulation. The ideal effect makes people have a better visual experience. The purpose of this article is to study the GPU-based real-time smoke simulation volume rendering algorithm. This paper proposes a method of setting different transfer functions based on different positions of the imaging plane. By setting different transfer functions for different positions of the imaging plane, different tissue structures can be drawn at one time for comparison and observation. However, setting different transfer functions based on the coordinate information of the imaging plane cannot fully display the volume data information. This paper implements a method of setting different transfer functions based on different spatial positions in the object space, and sets different transfer function schemes for the region of interest in the object space. Highlight, rotate or zoom the drawn object to observe the structure of the region of interest at any angle and size. In addition, this paper realizes the rapid volume cutting of volume rendering results, which is convenient for observing the organization structure information of the occluded position or designated area. Experimental results show that the algorithm in this paper can be used to control the random motion of smoke in three-dimensional space in virtual and real scenes, and can complete various interactive simulations of smoke and obstacles.
Rule Extraction Algorithm of Ordered Decision Information System
Authors: Mo Jing-Lan
Published: November 2020

In ordered decision information system, an improved LEM2 algorithm (DRI-LEM2) is proposed based on the generalized decision function, aiming at the low efficiency and low quality of LEM2 algorithm in extracting rules. The algorithm computes the candidate attribution-value pair set according to the generalized decision function, and removes redundant attribution-value pair from the candidate attribution-value pair set to gradually reduce the size of the property-value pair set. Through UCI experiments, it is proved that the improved LEM2 algorithm (DRI-LEM2) based on dominance relations can effectively improve the efficiency and quality of rules extraction.
A review of research on detection of fake commodity reviews
Authors: Tang Haoxing , Cao Hui
Published: November 2020

With the development of the Internet era, more and more consumers are shopping online. Product reviews can influence consumers’ consumption decisions. Fake review detection is a valuable research. From the perspective of research data content, it can be divided into two categories: review content based and review metadata; from the perspective of fake review detection method, it can be divided into four categories: rule-based, graph-based model, machine-learning based and deep learning based. Common data sets are also introduced.
A method of lowering the background in low-level radio-activity measurements
Authors: Li Yan , Zhao Hongtao , Zhao Xiaowen , Wu Peng
Published: November 2020

This paper discusses the main source of background in detecting radioactivity of low-level radiation and the methods to reduce the background in practical application.