bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model
Authors: Wu Xiaofei , Zhu Shuzhen , Zhou Junjie
Published: August 2020

This paper captures the RMB exchange rate volatility using the Markov-switching GARCH (MSGARCH) models and traditional single-regime GARCH models. Through the Markov Chain Monte Carlo (MCMC) method, the model parameters are estimated to study the volatility dynamics of the RMB exchange rate. Furthermore, we compare the MSGARCH models to the single-regime GARCH specifications in terms of Value-at-Risk (VaR) prediction accuracy. According to the Deviance information criterion method, the research shows that MSGARCH models outperform the single-regime specifications in capturing the complexity of RMB exchange rate volatility. After the RMB exchange rate reform in 2015, the volatility is more asymmetric and persistent, and the probability of being in the turbulent volatility regime is significantly increased. The continuous escalation of Sino-US trade friction has increased the VaR of RMB exchange rate log-returns. From the evaluation results of the actual over expected exceedance ratio (AE), the conditional coverage (CC) test, and the dynamic quantile (DQ) test, we find strong evidence that two-regime MSGARCH models could forecast VaR more accurately, which provides practical value for China’s foreign exchange management authorities to manage the financial risk.
A Propensity Score Cohort Study on the Long-Term Safety and Efficacy of Sleeve Gastrectomy in Patients Older Than Age 60
Authors: Molero Judith , Olbeyra Romina , Vidal Josep , Torres Ferran , Cañizares Silvia , Andreu Alba , Ibarzabal Ainitze , Jiménez Amanda , de Hollanda Ana , Moizé Violeta , Flores Lilliam
Published: August 2020

Background. Bariatric surgery (BS) in older obese subjects (>60 years of age) has risen in the past decade and will continue to rise in the coming years due to ageing of the population. Aim. To evaluate the short- (12 months) and long-term (60 months) results of laparoscopic sleeve gastroscopy (LSG) in patients older than age 60. Methods. We performed a retrospective review of patients prospectively included in a database from January 2007 to December 2013. All patients >60 [older group (OG)] who had undergone LSG were included. The control group (CG) included patients aged 50 to 59 years who had undergone LSG during the same period. Results. 116 (8.4 % of total surgery) and 145 patients were included in the OG and CG, respectively. BS in patients >60 years increased from 2.4% in 2003 to 14% in the last 2 years of the study. After inverse probability of treatment weighting (IPTW) analysis, all absolute standardized differences were <0.15. A 60-month follow-up was attained in 90% of patients in the OG and 74% in the CG. There were no significant differences in postoperative complications between the two groups. At 12 and 60 months after LSG, both groups achieved a similar body mass index. There was no statistical difference in the percentage of resolution of type 2 diabetes, hypertension, dyslipidemia, and SAHS between the two groups. In both groups, all the nutritional parameters evaluated remained within the normal range throughout the study. Conclusions. LSG provides acceptable outcomes and is safe in older adults indicating that age should not be a limitation to perform BS in this population.
New Signal Constellation Pairs for the ZTM-OFDM-IM System
Authors: Li Shuang , Kang Seog Geun
Published: August 2020

In this paper, we investigate new signal constellation pairs for mapping active subcarriers of the zero-padded trimode orthogonal frequency division multiplexing with index modulation (ZTM-OFDM-IM) systems. In the presented system, one of a constellation pair is the same as the one used in the previous work, and the other is a constellation larger than the one used in the previous work. It increases the minimum Euclidean distance between the subblocks of the ZTM-OFDM-IM system with new constellation pairs under the constraint of the same spectral efficiency. Computer simulation in AWGN and frequency-selective fading channels shows that the new ZTM-OFDM-IM system has a much lower bit error rate than OFDM-IM and dual-mode OFDM-IM and slightly outperforms the system with conventional constellation pairs. Since the proposed constellation pairs prove the error performance improvement of the system, it is considered that a further study on generalized design of the constellation pair for the ZTM-OFDM-IM system is necessary in the future.
Effective Methane Extraction Radius after High-Pressure Water Jet Slotting
Authors: Ke Hu , Binwei Xia , Chengwei Liu , Yiyu Lu
Published: August 2020

The effective radius of methane extraction after high-pressure water jet slotting is the most important parameter for borehole optimization and extraction time planning. We applied a steady flow model and thermal-hydrological-mechanical (THM) coupling model to calculate the effective radius after high-pressure water jet slotting. Field measurements at the Zhongliangshan coal mine show that both the steady flow model and the THM coupling model can accurately represent the effective radius, and the THM coupling model provides further information regarding extraction time. After that, a variety of factors, including extraction time, coal burial depth, slot radius, initial permeability, and initial methane pressure, are discussed. The effective radius of a slotted borehole is 1.94 times larger than that of a conventional borehole.
Antimycobacterial and PknB Inhibitory Activities of Venezuelan Medicinal Plants
Authors: Aranaga C. A. , Fraile S. , Torres A. , Falco A. , Michelangeli F. , Takiff H.
Published: August 2020

Global control and elimination of tuberculosis are hindered by the high prevalence of drug-resistant strains, making the development of new drugs to fight tuberculosis a public health priority. In this study, we evaluated 118 extracts from 58 Venezuelan plant species for their ability to inhibit the growth of Mycobacterium tuberculosis mc26020, using the agar dilution method. Additionally, we determined the ability of these extracts to inhibit the activity of PknB protein, an essential M. tuberculosis serine/threonine kinase, using a high-throughput luminescent assay. Of the 118 extracts tested, 14 inhibited bacterial growth with a minimum inhibitory concentration ≤500 μg/ml, and 36 inhibited the kinase activity with a half-maximal inhibitory concentration <200 μg/ml. Five extracts inhibited M. tuberculosis growth and inhibited the activity of the kinase protein, suggesting that this could be the basis of their growth inhibition.
Feedback-Dubins-RRT Recovery Path Planning of UUV in an Underwater Obstacle Environment
Authors: Hao Bing , Yan Zheping , Dai Xuefeng , Yuan Qi
Published: August 2020

In this paper, a UUV (Unmanned Underwater Vehicle) recovery path planning method of a known starting vector and end vector is studied. The local structure diagram is designed depending on the distance and orientation information about the obstacles. According to the local structure diagram, a Rapidly exploring Random Tree (RRT) method with feedback is used to generate a 3D Dubins path that approaches the target area gradually, and the environmental characteristic of UUV reaching a specific target area is discussed. The simulation results demonstrate that this method can effectively reduce the calculation time and the amount of data storage required for planning. Meanwhile, the smooth spatial path generated can be used further to improve the feasibility of the practical application of UUV.
Food Insecurity among People Living with HIV/AIDS on ART Follower at Public Hospitals of Western Ethiopia
Authors: Oluma Adugna , Abadiga Muktar , Mosisa Getu , Etafa Werku , Fekadu Ginenus
Published: August 2020

Background. Food insecurity and HIV/AIDS are intertwined in a vicious cycle through nutritional, mental health, and behavioral pathways. Food insecurity is a potentially important barrier to the success of antiretroviral treatment, increased hospitalizations, and higher morbidity among HIV-infected individuals in resource-poor settings particularly in sub-Saharan Africa including Ethiopia. Therefore, the purpose of this study was to assess the prevalence of food insecurity among people living with HIV/AIDS on follow up at public hospitals of western Ethiopia. Methods. An institutional-based cross-sectional study design was conducted on a sample of 428 among people living with HIV/AIDS on follow up at public hospitals of western Ethiopia. A systematic random sampling technique was used to include all participants. Data was collected using interviewer-administered structured questionnaires. The data were entered into Epi data version 3.1 and then exported into Statistical Package for the Social Sciences window version 21 for analysis. Descriptive and inferential statistics were employed. Bivariable logistic and multivariable logistic analyses were used with AOR at CI 95% and p<0.05 were used. Result. The finding of the study revealed that the majority of the respondents 221(53.1%) were female. The mean age of the respondents was 32.92±7.304 years and 197 (47.4%) of the study participants were between 30 to 39 years’ age group. The level of food insecurity among PLWHA receiving ART therapy was 68.8% which was partitioned as mild (23.32%), moderate (29.09%), and severe (16.35%) food in secured. Being single [AOR=3.5071.377,8.934], illiterate [AOR=5.2341.747,15.686], cigarette smoking [AOR=3.5772.104,6.081], presence of anemia (AOR=2.6501.563,4.493], and inadequate dietary diversity [AOR=2.8701.088,7.569] were predictors of food insecurity. Conclusion. The prevalence of food insecurity was high. Educational status, marital status, cigarette smoking, presence of anemia, opportunistic infection, and inadequate dietary diversity were the major significant factors affecting food insecurity. We recommended a national health policy maker to integrate food and nutrition interventions as part of a package of care, treatment, and support services for people living with HIV and ART follower patients.
Numerical Investigation of the Wake Vortex-Related Flow Mechanisms in Transonic Turbines
Authors: Wang Guoliang , Ge Ning , Zhong Dongdong
Published: August 2020

As the core equipment of the power generation system, a gas turbine is an indispensable energy-converting device in the national industry. The flow inside a high-pressure turbine (HPT) is highly unsteady, which has a great influence on the aerothermal performance and structural strength. To better clarify the flow mechanism and guide the advanced design, the basic flow characteristics of transonic turbines are investigated in the paper by a modified scale-adaptive simulation (SAS) model based on the shear stress transport (SST) turbulence model. The numerical results reveal the formation and development of the secondary flow structures such as wake vortex, pressure wave, shock wave, and the interactions among them. The length and frequency characteristics of wake are in good agreement with the large eddy simulation (LES) and the experimental data. Based on the detailed flow information, the local loss analysis is performed using the entropy generation rate. In summary, the wake vortex-related flow is the main origin of unsteadiness and entropy loss in high-pressure turbine cascade.
Stem Cell-Based Therapeutic Approaches to Restore Sensorineural Hearing Loss in Mammals
Authors: Waqas Muhammad , Us-Salam Iram , Bibi Zainab , Wang Yunfeng , Li He , Zhu Zhongshou , He Shuangba
Published: August 2020

The hair cells that reside in the cochlear sensory epithelium are the fundamental sensory structures responsible for understanding the mechanical sound waves evoked in the environment. The intense damage to these sensory structures may result in permanent hearing loss. The present strategies to rehabilitate the hearing function include either hearing aids or cochlear implants that may recover the hearing capability of deaf patients to a limited extent. Therefore, much attention has been paid on developing regenerative therapies to regenerate/replace the lost hair cells to treat the damaged cochlear sensory epithelium. The stem cell therapy is a promising approach to develop the functional hair cells and neuronal cells from endogenous and exogenous stem cell pool to recover hearing loss. In this review, we specifically discuss the potential of different kinds of stem cells that hold the potential to restore sensorineural hearing loss in mammals and comprehensively explain the current therapeutic applications of stem cells in both the human and mouse inner ear to regenerate/replace the lost hair cells and spiral ganglion neurons.
A Survey on Services Provision and Distribution of Official and Commercial Intellectual Property Platforms
Authors: Wang Yang , Gui Haijin , Ma Lei
Published: August 2020

Next generation of Information Technologies (IT), such as edging/cloud computing, cybersecurity, and artificial intelligence, has been in a rapid development and therefore concerned wide areas. Management of Intellectual Property Rights (IPR) plays an increasingly important role on knowledge design and engineering, innovation and patent management, intangible assets audition, R&D, and so forth; however, it also meets the challenges from proper platform and service provision, especially when large-scale mobile and distributed requirements become popular. In this paper, Intellectual Property Platforms and corresponding commercial tools have been collected, investigated, and reviewed, involving official platforms in China, USA, EU, and another 6 countries, as well as 12 intellectual property analysis tools commonly used online. Detailed comparison and discussion have been undertaken in order to find potential challenges and opportunities for improved service provision, for example, searching privacy preservation, cloud/edge-based service offloading and efficient distribution, and ontology-based intelligent IPR engineering, which can possibly be commercialised in the near future.
Distributed Security Framework for Reliable Threat Intelligence Sharing
Authors: Preuveneers Davy , Joosen Wouter , Bernal Bernabe Jorge , Skarmeta Antonio
Published: August 2020

Computer security incident response teams typically rely on threat intelligence platforms for information about sightings of cyber threat events and indicators of compromise. Other security building blocks, such as Network Intrusion Detection Systems, can leverage the information to prevent malicious adversaries from spreading malware across critical infrastructures. The effectiveness of threat intelligence platforms heavily depends on the willingness to share among organizations and the responsible use of sensitive information that may potentially harm the reputation of the reporting organization. The challenge that we address is the lack of trust in the source providing the threat intelligence and the information itself. We enhance our security framework TATIS—offering fine-grained protection for threat intelligence platform APIs—with distributed ledger capabilities to enable reliable and trustworthy threat intelligence sharing with the ability to audit the provenance of threat intelligence. We have implemented and evaluated the feasibility of our distributed framework on top of the Malware Information Sharing Platform (MISP) solution, and we evaluate the performance impact using real-world open-source threat intelligence feeds.
Effect and Safety of Transcutaneous Auricular Vagus Nerve Stimulation on Recovery of Upper Limb Motor Function in Subacute Ischemic Stroke Patients: A Randomized Pilot Study
Authors: Wu Dandong , Ma Jingxi , Zhang Liping , Wang Sanrong , Tan Botao , Jia Gongwei
Published: August 2020

Background. Transcutaneous auricular vagus nerve stimulation (taVNS) is regarded as a potential method for recovery in stroke. The effectiveness of taVNS in acute and subacute stroke should be further discussed as previously, only a few small-scale trials have focused on chronic stroke patients. The objective of this study is to investigate the effect and safety of taVNS on upper limb motor function in subacute ischemic stroke patients. Methods. Twenty-one subacute ischemia stroke patients with single upper limb motor function impairment were enrolled and randomly assigned to conventional rehabilitation training with real or sham taVNS, delivered for 15 consecutive days. Electrodes were fixed to the cymba conchae of the left ear with or without electrical stimulation. Conventional rehabilitation training was performed immediately after the end of real or sham taVNS by the same therapists. Baseline assessments were performed on day 0 of enrollment, and posttreatment evaluations were performed at 15 days, 4 weeks, and 12 weeks after the first intervention. The assessment included the upper limb Fugl-Meyer assessment (FMA-U), the Wolf motor function test (WMFT), the Functional Independence Measurement (FIM), and Brunnstrom stage. Heart rate (HR) and blood pressure (BP) were measured before and after each taVNS intervention. At the same time, any adverse effects were observed during the procedure. Outcomes were assessed by a blind evaluator. Results. There were no significant differences in FMA-U, WMFT, FIM, and Brunnstrom scores between the two groups at baseline (P>0.05). At the endpoint, the FMA-U, WMFT, and FIM scores were significantly higher than before treatment (P<0.05), and there was a significantly greater improvement of those measurements in taVNS group compared with sham-taVNS group (P<0.05). Significant improvements in FMA-U score were found between groups at follow-up. Only one case of skin redness occurred during the study. Conclusions. This study revealed that taVNS appeared to be beneficial to the recovery of upper limb motor function in subacute ischemia stroke patients without obvious adverse effects. Trial registration. This trial is registered with ChiCTR1800019635 on 20 November 2018 (http://www.chictr.org.cn/showproj.aspx?proj=32961).
A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling
Authors: Zhong Junda , Liu Peng , Li Shuang , Huang Xiaomin , Zhang Qunhui , Huang Jianyu , Guo Yan , Chen Meixiang , Ruan Zheng , Qin Changyu , Xu Lin
Published: August 2020

Three-dimensional speckle tracking echocardiography (3D STE) is an emerging noninvasive method for predicting left ventricular remodeling (LVR) after acute myocardial infarction (AMI). Previous studies analyzed the predictive value of 3D STE with traditional models. However, no models that contain comprehensive risk factors were assessed, and there are limited data on the comparison of different 3D STE parameters. In this study, we sought to build a machine learning model for predicting LVR in AMI patients after effective percutaneous coronary intervention (PCI) that contains the majority of the clinical risk factors and compare 3D STE parameters values for LVR prediction. We enrolled 135 first-onset AMI patients (120 males, mean age 54 ± 9 years). All patients went through a 3D STE and a traditional transthoracic echocardiography 24 hours after reperfusion. A second echocardiography was repeated at the three-month follow-up to detect LVR (defined as a 20 percent increase in left ventricular end-diastolic volume). Six models were constructed using 15 risk factors. A receiver operator characteristic curve and four performance measurements were used as evaluation methods. Feature importance was used to compare 3D STE parameters. 26 patients (19.3%) had LVR. Our evaluation showed that RF can best predict LVR with the best AUC of 0.96. 3D GLS was the most valuable 3D STE parameters, followed by GCS, global area strain, and global radial strain (feature importance 0.146, 0.089, 0.087, and 0.069, respectively). To sum up, RF models can accurately predict the LVR after AMI, and 3D GLS was the best 3D STE parameters in predicting the LVR.
Design and Performance Evaluation of a Deep Neural Network for Spectrum Recognition of Underwater Targets
Authors: Liu Dali , Zhao Xuchen , Cao Wenjing , Wang Wei , Lu Yi
Published: August 2020

Due to the complexity of the underwater environment, underwater acoustic target recognition (UATR) has always been challenging. Although deep neural networks (DNN) have been used in UATR and some achievements have been made, the performance is not satisfactory when recognizing underwater targets with different Doppler shifts, signal-to-noise ratios (SNR), and interferences. In the paper, a one-dimensional convolutional neural network (1D-CNN) was proposed to recognize the line spectrums of Detection of Envelope Modulation on Noise (DEMON) spectrums of underwater target-radiated noise. Datasets of targets with different Doppler shifts, SNRs, and interferences were designed to evaluate the generalization performance of the proposed CNN. Experimental results show that compared with traditional multilayer perceptron (MLP) networks, the 1D-CNN model better performs in recognition of targets with different Doppler shifts and SNRs. The outstanding generalization ability of the proposed model shows that it is suitable for practical engineering applications.
Mushroom Toxicity Recognition Based on Multigrained Cascade Forest
Authors: Wang Yingying , Du Jixiang , Zhang Hongbo , Yang Xiuhong
Published: August 2020

Due to the tastiness of mushroom, this edible fungus often appears in people’s daily meals. Nevertheless, there are still various mushroom species that have not been identified. Thus, the automatic identification of mushroom toxicity is of great value. A number of methods are commonly employed to recognize mushroom toxicity, such as folk experience, chemical testing, animal experiments, and fungal classification, all of which cannot produce quick, accurate results and have a complicated cycle. To solve these problems, in this paper, we proposed an automatic toxicity identification method based on visual features. The proposed method regards toxicity identification as a binary classification problem. First, intuitive and easily accessible appearance data, such as the cap shape and color of mushrooms, were taken as features. Second, the missing data in any of the features were handled in two ways. Finally, three pattern-recognition methods, including logistic regression, support vector machine, and multigrained cascade forest, were used to construct 3 different toxicity classifiers for mushrooms. Compared with the logistic regression and support vector machine classifiers, the multigrained cascade forest classifier had better performance with an accuracy of approximately 98%, enhancing the possibility of preventing food poisoning. These classifiers can recognize the toxicity of mushrooms—even that of some unknown species—according to their appearance features and important social and application value.
A Novel Blockchain Identity Authentication Scheme Implemented in Fog Computing
Authors: Wang Huijuan , Jiang Yong
Published: August 2020

In a fog computing environment, lots of devices need to be authenticated in order to keep the platform being secured. To solve this problem, we turn to blockchain techniques. Unlike the identification cryptographic scheme based on elliptic curves, the proposed 2-adic ring identity authentication scheme inherits the high verification efficiency and high key distribution of sequence ciphers of 2-adic ring theory, and this algorithm adds identity hiding function and trading node supervision function by design. The main designed application scenario of this solution is applicable to the consortium blockchain, and the master nodes are mutually trusting cooperative relations. The node transaction verification and block generation consensus algorithm designed in this solution can be implemented in a set of algorithms, which has higher verification efficiency and easier to be deployed than other solutions. This scheme can be widely used in the fog computing environment.
Optimal Utilization of Light Energy in Semiclosed Greenhouse Using Three-Dimensional Cucumber Model
Authors: Qian Tingting , Zheng Xiuguo , Yang Juan , Xu Yeying , Wang Yan , Zhou Qiang , Lu Shenglian , Ding Xiaotao
Published: August 2020

In the east of China, low temperature and light energy in winter are the main factors for the decline in cucumber yield, as well as in greenhouses without supplementary light. Optimal utilization of light energy is critical to increase cucumber yield. In this study, experimental measurements were conducted in two scenarios, April to May (Apr-May) and November to December (Nov-Dec) 2015, respectively, to analyze leaf development, dry matter accumulation, and yield of cultivated cucumber. Statistical analysis showed that leaves grew in Nov-Dec had larger leaf area and lower dry matter than leaves grew in Apr-May. This revealed that the dry matter accumulation rate per unit area was lower in winter. To be precise, the yield 0.174 kg/m2 per day in Nov-Dec was 35.3% lower than the yield in Apr-May. Environmental monitoring data showed that there was no significant difference in the average temperature between two scenarios, but the light intensity in Nov-Dec was only 2/3 of that in Apr-May. Three-dimensional (3D) cucumber canopy models were used in this study to quantify the effects of weak light on dry matter production in Nov-Dec. Three 3D canopies of cucumber were reconstructed with 20, 25, and 30 leaves per plant, respectively, by using a parametric modeling method. Light interception of three canopies from 8:00 to 15:00 on 4 November 2015 was simulated by using the radiosity-graphic combined model (RGM) with an hourly time step. CO2 assimilation per unit area was calculated using the FvCB photosynthetic model. As a result, the effects of light intensity and CO2 concentration on the photosynthetic rate were considered. The leaf photosynthesis simulation result showed that during the daytime in winter, the RuBP regeneration-limited assimilation Aj was always less than the Rubisco-limited assimilation Ac. This means that the limiting factor affecting the photosynthesis rate in winter was rather light intensity. As the CO2 concentration in the greenhouse was utmost in the morning, increasing the light intensity and therefrom increasing the canopy light interception at this time will be highly beneficial to increase the yield production. Through a comparative analysis of photosynthetic characteristics in these three virtual 3D canopies, the 25-leaf canopy was the best-performed canopy structure in photosynthetic production in winter. This study provides an insight into the light deficiency for yield production in winter and a solution to make optimal use of light in the greenhouse.
GABAergic System in Stress: Implications of GABAergic Neuron Subpopulations and the Gut-Vagus-Brain Pathway
Authors: Hou Xueqin , Rong Cuiping , Wang Fugang , Liu Xiaoqian , Sun Yi , Zhang Han-Ting
Published: August 2020

Stress can cause a variety of central nervous system disorders, which are critically mediated by the γ-aminobutyric acid (GABA) system in various brain structures. GABAergic neurons have different subsets, some of which coexpress certain neuropeptides that can be found in the digestive system. Accumulating evidence demonstrates that the gut-brain axis, which is primarily regulated by the vagus nerve, is involved in stress, suggesting a communication between the “gut-vagus-brain” pathway and the GABAergic neuronal system. Here, we first summarize the evidence that the GABAergic system plays an essential role in stress responses. In addition, we review the effects of stress on different brain regions and GABAergic neuron subpopulations, including somatostatin, parvalbumin, ionotropic serotonin receptor 5-HT3a, cholecystokinin, neuropeptide Y, and vasoactive intestinal peptide, with regard to signaling events, behavioral changes, and pathobiology of neuropsychiatric diseases. Finally, we discuss the gut-brain bidirectional communications and the connection of the GABAergic system and the gut-vagus-brain pathway.
UB-LSTM: A Trajectory Prediction Method Combined with Vehicle Behavior Recognition
Authors: Xiao Haipeng , Wang Chaoqun , Li Zhixiong , Wang Rendong , Bo Cao , Sotelo Miguel Angel , Xu Youchun
Published: August 2020

In order to make an accurate prediction of vehicle trajectory in a dynamic environment, a Unidirectional and Bidirectional LSTM (UB-LSTM) vehicle trajectory prediction model combined with behavior recognition is proposed, and then an acceleration trajectory optimization algorithm is proposed. Firstly, the interactive information with the surrounding vehicles is obtained by calculation, then the vehicle behavior recognition model is established by using LSTM, and the vehicle information is input into the behavior recognition model to identify vehicle behavior. Then, the trajectory prediction model is established based on Unidirectional and Bidirectional LSTM, and the identified vehicle behavior and the input information of the behavior recognition model are input into the trajectory prediction model to predict the horizontal and vertical speed and coordinates of the vehicle in the next 3 seconds. Experiments are carried out with NGSIM data sets, and the experimental results show that the mean square error (MSE) between the predicted trajectory and the actual trajectory obtained by this method is 0.124, which is 97.2% lower than that of the method that does not consider vehicle behavior and directly predicts the trajectory. The test loss is 0.000497, which is 95.68% lower than that without considering vehicle behavior. The predicted trajectory is obviously optimized, closer to the actual trajectory, and the performance is more stable.
Modified Support Vector Machine for Detecting Stress Level Using EEG Signals
Authors: Gupta Richa , Alam M. Afshar , Agarwal Parul
Published: August 2020

Stress is categorized as a condition of mental strain or pressure approaches because of upsetting or requesting conditions. There are various sources of stress initiation. Researchers consider human cerebrum as the primary wellspring of stress. To study how each individual encounters stress in different forms, researchers conduct surveys and monitor it. The paper presents the fusion of 5 algorithms to enhance the accuracy for detection of mental stress using EEG signals. The Whale Optimization Algorithm has been modified to select the optimal kernel in the SVM classifier for stress detection. An integrated set of algorithms (NLM, DCT, and MBPSO) has been used for preprocessing, feature extraction, and selection. The proposed algorithm has been tested on EEG signals collected from 14 subjects to identify the stress level. The proposed approach was validated using accuracy, sensitivity, specificity, and F1 score with values of 96.36%, 96.84%, 90.8%, and 97.96% and was found to be better than the existing ones. The algorithm may be useful to psychiatrists and health consultants for diagnosing the stress level.
Network Meta-Analysis of the Safety of Drug Therapy for Cardiogenic Shock
Authors: Liao Xianyong , Qian Lin , Zhang Song , Chen Xiang , Lei Jing
Published: August 2020

Objectives. (1) To conduct a network meta-analysis of clinical drugs used for cardiogenic shock and (2) provide evidence for the selection of medication for the treatment of this condition. Methods. PubMed, EMBASE, Cochrane library, China HowNet (CNKI), Wanfang database, and Weipu database were searched using keywords Dopamine, Dobutamine, Epinephrine, Adrenaline, Norepinephrine, Noradrenaline, Milrinone, Natriuretic peptide, Recombinant human brain natriuretic peptide, Levosimendan, Cardiac shock, and Cardiogenic shock. We select literature according to prespecified inclusion and exclusion criteria and record data such as drug type, mortality, and adverse reactions. Results. Twenty-eight of 1387 articles met inclusion criteria, comprising 1806 patients who suffered from cardiogenic shock. Dopamine, dobutamine, epinephrine, norepinephrine, milrinone, recombinant human brain natriuretic peptide, and levosimendan were all commonly used in the treatment of cardiogenic shock. Milrinone was most effective at reducing mortality and had the lowest incidence of adverse reactions. Conclusion. This network meta-analysis demonstrated that milrinone was the most effective medication at reducing mortality and adverse events in patients suffering from cardiogenic shock.
Larvicidal Activity and Histopathological Effect of Averrhoa bilimbi Fruit Extract on Aedes aegypti from Surabaya, Indonesia
Authors: Rohmah Etik A. , Subekti Sri , Rudyanto Marcellino
Published: August 2020

Averrhoa bilimbi has been long thought to have biological activity. The aim of this study was to determine the activity of primary and secondary metabolites from A. bilimbi fruit extract on Aedes aegypti larvae mortality and midgut histopathology. Experiment was performed to third-instar Ae. aegypti larvae collected from Surabaya, which then exposed to A. bilimbi crude fruit extract at various concentration for 24 hours. After exposure, larvae were evaluated of its mortality and fixed in 2.5% neutral buffer formalin before processed and sectioned into histological slides and stained with hematoxylin-eosin (HE). Statistical analysis was performed using Spearman rank correlation to determine histopathological damage on midgut of Ae. aegypti larvae. Phytochemical screening of A. bilimbi crude fruit extract found that it contained saponins, tannins, and terpenoids. Minimum concentration able to induce mortality on Ae. aegypti larvae (LC50) was 977 ppm, while LC90 was at 1380 ppm. Severe alteration of larvae midgut was found after 24 hours exposure to 2000 ppm extract. Features of damage mostly found in larvae midgut were disruption of the microvilli, columnar cell vacuolization, epithelial nucleus crossed midgut lumen, and basal membrane damage. Damage caused by fruit extract in midgut of Ae. aegypti third instar larvae inhibited development of larvae. This study reported first finding of histopathological effect of A. bilimbi fruits extract on Ae. aegypti larvae midgut. Result of study was expected to contribute to better understand extract bioactivity of this plant to be applied as natural larvicide for Ae. aegypti.
Testing the Performance of Various Polymeric Antiscalants for Mitigation of Sb-Rich Precipitates Mimicking Stibnite-Based Geothermal Deposits
Authors: Çiftçi Celal , Karaburun Emre , Tonkul Serhat , Baba Alper , Demir Mustafa M. , Yeşilnacar Mehmet İrfan
Published: August 2020

Scaling is frequently observed in geothermal fields and reduces the energy harvesting of power plants. Recently, Sb-rich deposits have developed in many fields around the world. Various polymeric macromolecules have been used as antiscalants to mitigate the formation of scale. Testing potential commercial antiscalants in field conditions is a tedious and costly process. The artificial synthesis of geothermal deposits in the lab is a more practical and economical way to test the performance of antiscalants. This study obtained a Sb-rich deposit by refluxing SbCl3 and Na2S·3H2O in 18 h. The product was found to be a mixture of Sb2O3 and Sb2S3. We examined the performance of antiscalants such as poly(ethylene glycol), poly(vinyl pyrrolidone), Gelatin, and poly(vinyl alcohol) of various molecular weights at 5 to 100 ppm. The formation of Sb2S3 is suppressed in the presence of the polymeric antiscalants. The dosage was found to be critical for the solubilization of Sb-rich deposits. Gelatin of 5 ppm showed the highest performance under the conditions employed in this study. While low dosages improve the concentration of [Sb3+], high dosages are required to increase the solubility of [S2-]. Moreover, the amount of deposit is reduced by 12.4% compared to the reference (in the absence of any polymeric molecules). Thus, comparatively, Gelatin shows the most promising performance among the molecules employed.
A Minimum Defense Cost Calculation Method for Attack Defense Trees
Authors: Xu Bingfeng , Zhong Zhicheng , He Gaofeng
Published: August 2020

The cyberphysical system (CPS) is becoming the infrastructure of society. Unfortunately, the CPS is vulnerable to cyberattacks, which may cause environmental pollution, property losses, and even casualties. Furthermore, in contrast to the conventional Internet, the devices in CPSs are more specific, and the device systems may not be upgraded or installed with new programs during their life spans. The selection of the best defense nodes for defeating cyberattacks is quite challenging in CPSs. To overcome this issue, several attack-defense modeled methods have been proposed. However, few existing studies have considered the defense cost, which is usually a determinant in practice. In this paper, we propose a method for choosing optimal defense nodes that (1) can defeat specific attacks and (2) are inexpensive. First, the atom attack defense tree (A2DTree) is proposed by adding constraints to the conventional attack defense tree (ADTree). Second, the algebraic method is used to efficiently calculate the minimum defense cost. On this basis, a minimum defense cost calculation tool is designed and implemented. Finally, the effectiveness of the proposed method is verified with two typical case studies, and a comparative experiment of related work is carried out. The results show that the method can correctly and efficiently identify the optimal defense nodes and calculate the minimum defense cost of a CPS.
Compound Heterozygous Mutations in TMC1 and MYO15A Are Associated with Autosomal Recessive Nonsyndromic Hearing Loss in Two Chinese Han Families
Authors: Xu Pengcheng , Xu Jun , Peng Hu , Yang Tao
Published: August 2020

Genetic hearing loss is a common sensory disorder, and its cause is highly heterogeneous. In this study, by targeted next-generation sequencing of 414 known deafness genes, we identified compound heterozygous mutations p.R34X/p.M413T in TMC1 and p.S3417del/p.R1407T in MYO15A in two recessive Chinese Han deaf families. Intrafamilial cosegregation of the mutations with the hearing phenotype was confirmed in both families by the Sanger sequencing. Auditory features of the affected individuals are consistent with that previously reported for recessive mutations in TMC1 and MYO15A. The two novel mutations identified in this study, p.M413T in TMC1 and p.R1407T in MYO15A, are classified as likely pathogenic according to the guidelines of ACMG. Our study expanded the mutation spectrums of TMC1 and MYO15A and illustrated that genotype-phenotype correlation in combination with next-generation sequencing may improve the accuracy for genetic diagnosis of deafness.
Study on a Large-Scale Persistent Strong Dense Fog Event in Central and Eastern China
Authors: Wang Hongbin , Zhang Zhiwei , Liu Duanyang , Zhu Yuying , Zhang Xuerong , Yuan Chengsong
Published: August 2020

A large-scale persistent strong dense fog (SDF) event that occurred from December 30, 2016, to January 5, 2017, in central and eastern China is analyzed by using a variety of data, including high-resolution satellite and surface observations, meteorological tower observations, fine-resolution sounding observations, and NCEP/NCAR reanalysis data. The results show the following: (1) The SDF event has the characteristics of long duration, wide influence range, large intensity, and serious air pollution. During the study period, there are 531 stations with SDF events, covering an area of over 360,000 km2. There were five stations in Hebei province where the fog lasted for more than 77 hours, and even some stations did not dissipate during the day. (2) Radiation fog and advection fog alternate in this SDF event, namely, radiation fog (20:00 BT on December 30 to 14:00 on January 1), advection radiation fog (20:00 on January 1 to 08:00 on January 2), radiation fog (night on January 2 to daytime on January 3), and advection radiation fog (night on January 3 to January 5). The characteristic of radiation fog is that the central and eastern part of China was controlled by “L” type high pressure. In the stage of advection radiation fog, the combined effect of weak cold advection and radiation cooling leads to the occurrence of SDF. (3) Regarding the duration of the fog event, the inversion structure is continuously maintained at night and in the morning near the stratum, and when the fog intensity is strong, the inversion intensity is correspondingly large, the fog top is lower than the inversion layer top, and the top of the SDF is between 80 and 400 meters.
Differential Electroanalysis of Dopamine in the Presence of a Large Excess of Ascorbic Acid at a Nickel Oxide Nanoparticle-Modified Glassy Carbon Electrode
Authors: Althagafi Zahrah T. , Althakafy Jalal T. , Al Jahdaly Badriah A. , Awad Mohamed I.
Published: August 2020

Electrochemical determination of dopamine (DA) in the presence of a large excess of ascorbic acid (AA) in their coexistence at a nickel oxide nanoparticle-modified preoxidized glassy carbon electrode (GCox/nano-NiOx) is achieved. The GCox/nano-NiOx electrode is prepared by electrodeposition of nickel nanoparticles (nano-Ni) onto an electrochemically activated glassy carbon (GC) electrode, and the thus prepared nano-Ni were subjected to electrochemical oxidation in alkaline medium for the formation of nickel oxide (NiOx). Modified electrodes were electrochemically and morphologically characterized. The effect of loading level of nickel was investigated by changing the number of potential cycles for the deposition of nano-Ni, i.e., 1, 2, 5, and 10 potential cycles, in the potential range from 0 to -1.0 V vs. SCE. Also, the experimental and instrumental parameters were optimized. Experimental results showed that the modified electrode differentiates well the oxidation peaks of DA and AA enabling the electrochemical determination of DA in the presence of a large excess of AA. Remarkably, it is found that the oxidation current of DA is 2 times larger than that of AA even the concentration of AA is about 5 times larger than that of DA. The LOD and LOQ of DA were calculated and were found to equal 0.69 and 2.3 mM, respectively. This offers the advantage of simple and selective detection of DA free of the interference of AA in real samples.
The Influence of Radiation on Confinement Properties of Nuclear Waste Glasses
Authors: Malkovsky Viktor I. , Yudintsev Sergey V. , Ojovan Michael I. , Petrov Vladislav A.
Published: August 2020

Self-irradiation can affect durability of glasses used to immobilize high-level nuclear waste (HLW). The stability of glasses can also be indirectly affected by the radiolytic changes in contact water leading to decrease in its pH although this is unlikely to occur for disposal systems where the interaction of groundwater with glass is delayed to times when radiation dose rates are decreased to levels insignificant to cause such effects. Besides, interaction of the water influenced by radiation with other repository protective elements (container and bentonite) will suppress the radiolytic changes. Literature analysis shows practical absence or very weak effect of self-irradiation on structure and characteristics of borosilicate glasses with typical content of nuclear waste. Data for aluminophosphate glass used in Russia have showed that, after γ-irradiation with a dose of 6.2·107 Gy, the leaching rates of elements were decreased approximately twice relatively to pristine samples.
Vaginal Bleeding in an Infant with Extreme Prematurity
Authors: Poon Wing Yiu Sarah , Tung Joanna Yuet Ling
Published: August 2020

Background. Minipuberty of infancy refers to the transient activation of the hypothalamic-pituitary-gonadal (HPG) axis during the first few months of life. Studies have documented a more exaggerated and prolonged gonadotropin surge in preterm infants compared with term infants. We present a case of minipuberty presenting with vaginal bleeding at the corrected age of 3 months of life. Case Presentation. A former 23 + 6-week infant presented with intermittent vaginal bleeding in the diaper at the corrected age of 3 months. Physical exam showed bilateral breast buds of 0.5 cm–1 cm with no signs of pubarche. Investigations showed pubertal levels of luteinizing hormone (LH), follicle-stimulating hormone (FSH), and estradiol. As she was impressed to have exaggerated minipuberty due to extreme prematurity, no intervention was given. Repeated hormonal workup at the corrected age of 8 months showed decreasing trend of gonadotropin and estradiol levels. Vaginal bleeding resolved, and breast buds also regressed clinically. Conclusion. Our case illustrated that the robust surge of gonadotropin in an ex-premature infant can in fact result in endometrial maturation and present as vaginal bleeding. Though the mechanism of this alteration in the HPG axis in prematurity is not clearly understood, pediatricians should be aware of the benign and self-limiting nature of this phenomenon and avoid unnecessary intervention.
Adaptive CU Split Decision Based on Deep Learning and Multifeature Fusion for H.266/VVC
Authors: Zhao Jinchao , Wang Yihan , Zhang Qiuwen
Published: August 2020

With the development of technology, the hardware requirement and expectations of user for visual enjoyment are getting higher and higher. The multitype tree (MTT) architecture is proposed by the Joint Video Experts Team (JVET). Therefore, it is necessary to determine not only coding unit (CU) depth but also its split mode in the H.266/Versatile Video Coding (H.266/VVC). Although H.266/VVC achieves significant coding performance on the basis of H.265/High Efficiency Video Coding (H.265/HEVC), it causes significantly coding complexity and increases coding time, where the most time-consuming part is traversal calculation rate-distortion (RD) of CU. To solve these problems, this paper proposes an adaptive CU split decision method based on deep learning and multifeature fusion. Firstly, we develop a texture classification model based on threshold to recognize complex and homogeneous CU. Secondly, if the complex CUs belong to edge CU, a Convolutional Neural Network (CNN) structure based on multifeature fusion is utilized to classify CU. Otherwise, an adaptive CNN structure is used to classify CUs. Finally, the division of CU is determined by the trained network and the parameters of CU. When the complex CUs are split, the above two CNN schemes can successfully process the training samples and terminate the rate-distortion optimization (RDO) calculation for some CUs. The experimental results indicate that the proposed method reduces the computational complexity and saves 39.39% encoding time, thereby achieving fast encoding in H.266/VVC.
Channel and Feature Selection for a Motor Imagery-Based BCI System Using Multilevel Particle Swarm Optimization
Authors: Qi Yingji , Ding Feng , Xu Fangzhou , Yang Jimin
Published: August 2020

Brain-computer interface (BCI) is a communication and control system linking the human brain and computers or other electronic devices. However, irrelevant channels and misleading features unrelated to tasks limit classification performance. To address these problems, we propose an efficient signal processing framework based on particle swarm optimization (PSO) for channel and feature selection, channel selection, and feature selection. Modified Stockwell transforms were used for a feature extraction, and multilevel hybrid PSO-Bayesian linear discriminant analysis was applied to optimization and classification. The BCI Competition III dataset I was used here to confirm the superiority of the proposed scheme. Compared to a method without optimization (89% accuracy), the best classification accuracy of the PSO-based scheme was 99% when less than 10.5% of the original features were used, the test time was reduced by more than 90%, and it achieved Kappa values and F-score of 0.98 and 98.99%, respectively, and better signal-to-noise ratio, thereby outperforming existing algorithms. The results show that the channel and feature selection scheme can accelerate the speed of convergence to the global optimum and reduce the training time. As the proposed framework can significantly improve classification performance, effectively reduce the number of features, and greatly shorten the test time, it can serve as a reference for related real-time BCI application system research.