bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectroscopic investigation of non-thermal plasma generated in atmospheric pressure ‘Plasma Pencil’
Authors: Anjum Zakia , rehman N. U. , Younus Maria , Sarwar Sajjad
Published: May 2020

Plasma generated at atmospheric pressure has widespread applications in the field of plasma medicine. In this paper, spectroscopic investigations of homemade capacitively coupled, atmospheric pressure RF plasma pencil is reported. Optical emission spectroscopy (OES) technique is employed to characterize the plasma. Variation in rotational/gas temperature [Formula: see text], [Formula: see text] atomic density, dissociation fraction [Formula: see text] and normalized intensities of [Formula: see text], [Formula: see text] and [Formula: see text] radiation is monitored as a function of discharge parameters like RF power and different gases concentration. [Formula: see text] of [Formula: see text] mixture is estimated from [Formula: see text] band head of R branch of first negative system of nitrogen [Formula: see text], [Formula: see text], [Formula: see text] using Boltzmann plot technique. Similarly, [Formula: see text] band head of second positive system (SPS) of nitrogen [Formula: see text], [Formula: see text], [Formula: see text] is also used to estimate [Formula: see text] by fitting synthetic spectra over the experimentally recorded spectrum. It is noted that [Formula: see text] increases with increase in RF power, but it decreases with increase in [Formula: see text] concentration in the mixture. [Formula: see text] atomic density and dissociation fraction [Formula: see text], estimated from [Formula: see text] line at 750 nm and [Formula: see text] line at 844 nm using actinometry technique, show increasing trend with RF power and [Formula: see text] concentration in the mixture up to 0.7% [Formula: see text] in the mixture. The normalized [Formula: see text] radiation intensities; [Formula: see text], [Formula: see text] and [Formula: see text] show the increasing trend with increase in RF power up to 0.3% [Formula: see text] concentration in the mixture.
Empirical Evaluation of Texture Features and Classifiers for Liver Disease Diagnosis
Authors: Sinduja A. , Suruliandi A. , Raja S. P.
Published: May 2020

The liver cancer is one of the most common fatal diseases worldwide, and its early detection through medical imaging is a major contributor to the reduction in mortality from certain cancer. This paves the way to work on diagnosing liver diseases effectively. An accurate diagnosis of liver disease in CT image requires an efficient description of textures and classification methods. This paper performs comparative analysis on proposed texture feature descriptor with the different existing texture features with various classifiers to classify six types of diffused and focal liver diseases. The classification of liver diseases is done in two stages. In first stage, features like segmentation based fractal texture analysis, counting label occurrence matrix, local configuration pattern, eXtended center-symmetric local binary pattern and the proposed local symmetric tetra pattern are used for extracting information from the CT liver structure and classifiers like support vector machine, [Formula: see text]-nearest neighbor, and naive Bayes are used for classifying the pathologic liver. When pathologic conditions are detected, the best feature descriptors and classifiers are used to classify the results into any of six exclusive pathologic liver diseases, in second stage. The experiments are carried out in medically validated liver datasets containing normal and six-disease category of liver. The first experiment is analyzed using sensitivity, specificity, and accuracy. The second experiment is evaluated using precision, recall, BCR, and F-measure. The results demonstrate that the local symmetric tetra pattern with [Formula: see text]-nearest neighbor classifier culminates in a state-of-the-art performance for diagnosing liver diseases.
Fruit Fly-Based Artificial Neural Network Classifier with Kernel-Based Fuzzy c-Means Clustering for Satellite Image Classification
Authors: Kumar Sandeep , Suresh L.
Published: May 2020

Image segmentation and classification are the major challenges to satellite imagery. Also, the identification of unique objects in the satellite image is a significant aspect in the application of remote sensing. Many satellite image classification techniques have been presented earlier. However, the accuracy of the image classification has to be further improved. So that, optimal artificial neural network with kernel-based fuzzy c-means ([Formula: see text]) clustering based satellite image classification is proposed in this paper. Initially, the images are segmented with the help of KFCM algorithm. Then, color features and gray level co-occurrence matrix (GLCM) features to be extracted from the segmented regions. Then, these extracted features are given to the OANN classifier. Based on these features, segmented regions are classified as building, road, shadow, and tree. To enhance the performance of the classifier, the weight values are optimally selected with the help of fruit fly algorithm. Simulation results show that the performance of proposed classifier outperforms that of the existing filters in terms of accuracy.
Political Misinformation
Authors: Jerit Jennifer , Zhao Yangzi
Published: May 2020

Misinformation occurs when people hold incorrect factual beliefs and do so confidently. The problem, first conceptualized by Kuklinski and colleagues in 2000, plagues political systems and is exceedingly difficult to correct. In this review, we assess the empirical literature on political misinformation in the United States and consider what scholars have learned since the publication of that early study. We conclude that research on this topic has developed unevenly. Over time, scholars have elaborated on the psychological origins of political misinformation, and this work has cumulated in a productive way. By contrast, although there is an extensive body of research on how to correct misinformation, this literature is less coherent in its recommendations. Finally, a nascent line of research asks whether people's reports of their factual beliefs are genuine or are instead a form of partisan cheerleading. Overall, scholarly research on political misinformation illustrates the many challenges inherent in representative democracy.
Partisan Gerrymandering and Political Science
Authors: McGhee Eric
Published: May 2020

Recent years have seen a tremendous surge of public interest in partisan gerrymandering, including robust reform efforts and multiple high-profile court cases. Political scientists have played an important role in this debate, reaching an unusually high level of public engagement. Yet this public-facing period has to some extent obscured promising avenues for future research within the discipline. I review the history of political science and redistricting and describe how research on this topic has been shaped by the newfound interest. The goals of the law differ from those of political science, so research that focuses squarely on the former often misses opportunities to advance the latter. I lay out the contours of this difference and then suggest reframing the existing metrics of partisan gerrymandering to make them useful for more traditionally scientific questions. Finally, I offer some ideas about what those future questions might look like when reframed in this way.
Ecology, Structure, and Evolution of Shigella Phages
Authors: Subramanian Sundharraman , Parent Kristin N. , Doore Sarah M.
Published: May 2020

Numerous bacteriophages—viruses of bacteria, also known as phages—have been described for hundreds of bacterial species. The Gram-negative Shigella species are close relatives of Escherichia coli, yet relatively few previously described phages appear to exclusively infect this genus. Recent efforts to isolate Shigella phages have indicated these viruses are surprisingly abundant in the environment and have distinct genomic and structural properties. In addition, at least one model system used for experimental evolution studies has revealed a unique mechanism for developing faster infection cycles. Differences between these bacteriophages and other well-described model systems may mirror differences between their hosts’ ecology and defense mechanisms. In this review, we discuss the history of Shigella phages and recent developments in their isolation and characterization and the structural information available for three model systems, Sf6, Sf14, and HRP29; we also provide an overview of potential selective pressures guiding both Shigella phage and host evolution.
Design Principles to Govern Electrode Fabrication for the Lithium Trivanadate Cathode
Authors: Mayilvahanan Karthik , Brady Nicholas , McCarthy Alison H. , Wang Lei , Marschilok Amy C. , Takeuchi Kenneth , Takeuchi Esther , West Alan C.
Published: May 2020

A full depth of discharge mathematical model for the lithium trivanadate cathode, considering lithiation of the layered α-phase, phase change, and lithiation of the rock-salt like β-phase at lower potentials, is developed. The coupled electrode-scale and crystal-scale model is fit to electrochemical data, and additionally validated with operando EDXRD. There is good agreement between the simulated and measured spatial variation of the volume fraction of the β-phase. This mathematical model is used to guide electrode fabrication, accounting for both ionic and electronic transport effects. Values of three design parameters—electrode thickness, porosity, and volume fraction of conductor—are identified, and the sensitivity of the energy density to these design parameters is quantified. The model is also used to investigate electrode design to create electrodes that deliver the maximum achievable energy density under the constraint that the α to β-phase transition is avoided, since phase change has been demonstrated to reduce cycle life. The energy density sacrificed to avoid phase change decreases at higher discharge rates, but the target values for electrode fabrication remain the same as those when optimizing the electrode for the full depth of discharge.
Performances of Solid Oxide Cells with La0.97Ni0.5Co0.5O3−δ as Air-Electrodes
Authors: Ma Qianli , Dierickx Sebastian , Vibhu Vaibhav , Sebold Doris , de Haart Lambertus G. J. , Weber André , Guillon Olivier , Menzler Norbert H.
Published: May 2020

Based on previous studies of perovskites in the quasi-ternary system LaFeO3–LaCoO3–LaNiO3, La0.97Ni0.5Co0.5O3 (LNC) is chosen as the most promising air-electrode material in the series for solid oxide cells (SOCs). The properties of the material itself have been investigated in detail. However, the evaluation of LNC97 air electrodes in practical SOCs is still at a very early stage. In the present study, SOCs were prepared based on LNC97 air electrodes. The I-U performance of the SOCs in both solid oxide fuel cell (SOFC) and solid oxide electrolysis cell (SOEC) modes, i.e. reversible SOCs (r-SOCs), was investigated systematically for different air-electrode designs, temperatures and fuel gases. In general, the performance of the r-SOCs tested in the present study is higher than the published results of other LaFeO3–LaCoO3–LaNiO3-based SOCs and is comparable to or even better than state-of-the-art La1−xSrxFe1−yCoyO3 (LSCF)-based SOCs. Mid-term operation of about 1000 h for SOCs in both SOFC and SOEC modes primarily proved the stability of LNC97-based air electrodes. Impedance spectra were systematically applied to understand the polarization processes of the SOCs.
Lipopolysaccharides transport during fat absorption in rodent small intestine
Authors: Akiba Yasutada , Maruta Koji , Takajo Takeshi , Narimatsu Kazuyuki , Said Hyder , Kato Ikuo , Kuwahara Atsukazu , Kaunitz Jonathan D.
Published: May 2020

We report direct in vivo confirmation of transcellular lipopolysaccharides (LPS) uptake from the intestine into the portal vein (PV) involving CD36 and lipid rafts, with minor uptake via the canonical chylomicron pathway. The gut hormone glucagon-like peptide-2 (GLP-2) inhibited uptake into the PV. These data suggest that the bulk of LPS absorption is via the PV to the liver, helping clarify the mechanism of LPS transport into the PV as part of the “gut-liver” axis. These data do not support the paracellular transport of LPS, which has been implicated in the pathogenesis of the “leaky gut” syndrome.
Antibiotic exposure postweaning disrupts the neurochemistry and function of enteric neurons mediating colonic motor activity
Authors: Hung Lin Y. , Parathan Pavitha , Boonma Prapaporn , Wu Qinglong , Wang Yi , Haag Anthony , Luna Ruth Ann , Bornstein Joel C. , Savidge Tor C. , Foong Jaime P. P.
Published: May 2020

The period during and immediately after weaning is an important developmental window when marked shifts in gut microbiota can regulate the maturation of the enteric nervous system (ENS). Because microbiota-derived signals that modulate ENS development are poorly understood, we examined the physiological impact of the broad spectrum of antibiotic, vancomycin-administered postweaning on colonic motility, neurochemistry of enteric neurons, and neuronal excitability. The functional impact of vancomycin on enteric neurons was investigated by Ca2+ imaging in Wnt1-Cre;R26R-GCaMP3 reporter mice to characterize alterations in the submucosal and the myenteric plexus, which contains the neuronal circuitry controlling gut motility. 16S rDNA sequencing of fecal specimens after oral vancomycin demonstrated significant deviations in microbiota abundance, diversity, and community composition. Vancomycin significantly increased the relative family rank abundance of Akkermansiaceae, Lactobacillaceae, and Enterobacteriaceae at the expense of Lachnospiraceae and Bacteroidaceae. In sharp contrast to neonatal vancomycin exposure, microbiota compositional shifts in weaned animals were associated with slower colonic migrating motor complexes (CMMCs) without mucosal serotonin biosynthesis being altered. The slowing of CMMCs is linked to disruptions in the neurochemistry of the underlying enteric circuitry. This included significant reductions in cholinergic and calbindin+ myenteric neurons, neuronal nitric oxide synthase+ submucosal neurons, neurofilament M+ enteric neurons, and increased proportions of cholinergic submucosal neurons. The antibiotic treatment also increased transmission and responsiveness in myenteric and submucosal neurons that may enhance inhibitory motor pathways, leading to slower CMMCs. Differential vancomycin responses during neonatal and weaning periods in mice highlight the developmental-specific impact of antibiotics on colonic enteric circuitry and motility.
Depletion of macrophages slows the early progression of renal injury in obese Dahl salt-sensitive leptin receptor mutant rats
Authors: Poudel Bibek , Shields Corbin A. , Brown Andrea K. , Ekperikpe Ubong , Johnson Tyler , Cornelius Denise C. , Williams Jan M.
Published: May 2020

Recently, we reported that obese Dahl salt-sensitive (SS) leptin receptor mutant (SSLepRmutant) rats display progressive renal injury. The present study demonstrated that the early development of renal injury in the SSLepRmutant strain is associated with an increase in the renal infiltration of macrophages compared with lean SS rats. We also examined whether depletion of macrophages with clodronate would reduce the early progression of renal injury in the SSLepRmutant strain. Four-week-old SS and SSLepRmutant rats were treated with either vehicle (PBS) or clodronate (50 mg/kg ip, 2 times/wk) for 4 wk. While the administration of clodronate did not reduce renal macrophage infiltration in SS rats, clodronate decreased macrophages in the kidneys of SSLepRmutant rats by >50%. Interestingly, clodronate significantly reduced plasma glucose, insulin, and triglyceride levels and markedly improved glucose tolerance in SSLepRmutant rats. Treatment with clodronate had no effect on the progression of proteinuria or renal histopathology in SS rats. In the SSLepRmutant strain, proteinuria was markedly reduced during the first 2 wk of treatment (159 ± 32 vs. 303 ± 52 mg/day, respectively). However, after 4 wk of treatment, the effect of clodronate was no longer observed in the SSLepRmutant strain (346 ± 195 vs. 399 ± 50 mg/day, respectively). The kidneys from SSLepRmutant rats displayed glomerular injury with increased mesangial expansion and renal fibrosis versus SS rats. Treatment with clodronate significantly decreased glomerular injury and renal fibrosis in the SSLepRmutant strain. Overall, these data indicate that the depletion of macrophages improves metabolic disease and slows the early progression of renal injury in SSLepRmutant rats.
The Predictive Role of PIK3CA Mutation Status on PI3K Inhibitors in HR+ Breast Cancer Therapy: A Systematic Review and Meta‐Analysis
Authors: Wang Mingming , Li Jin , Huang Jiangsheng , Luo Mei
Published: May 2020

Aim. To evaluate the impact of PIK3CA mutation status on clinical outcomes of HR+ breast cancer treated with PI3K inhibitors. Methods. A comprehensive literature search was conducted in online databases from inception to December 31, 2019. The main characteristics and prognostic data of each eligible study were extracted. The odds ratio (OR) for the overall response rate (ORR) and hazard ratio (HR) for progression‐free survival (PFS) were estimated using the fixed‐effects Mantel‐Haenszel model. Results. A total of 8 studies involving 2670 patients were included for analysis. Overall, the clinical outcomes of PI3K inhibitors were significantly influenced by PIK3CA mutation status in HR+ breast cancer. After the treatment of PI3K inhibitors, HR+ breast cancer patients with PIK3CA mutations presented better ORR (PIK3CA-mutated group: OR = 1.98 [95% CI, 1.46 to 2.70]; PIK3CA wild‐type group: OR = 1.09 [95% CI, 0.78 to 1.53]) and better PFS (PIK3CA‐mutated group: HR = 0.65 [95% CI, 0.55 to 0.76]; PIK3CA wild‐type group: HR = 0.87 [95% CI, 0.70 to 1.09]). No publication bias was detected for ORR and PFS in our analysis. Conclusion. In this meta‐analysis, it suggests that the association between clinical outcomes of PI3K inhibitors and PIK3CA mutation status is dramatic. PIK3CA mutations were a favorable factor in the clinical outcomes of HR+ breast cancer treated with PI3K inhibitors.
Improvement in the Analytical Capabilities of LA-ICP-MS for High Spatial Resolution U-Pb Dating of Zircon Using Mixed-Gas Plasma
Authors: Shenghua Liu , Xin Wang , Huixia Shi , Hui Zhang , Bingbing Liu
Published: May 2020

In this work, a novel method for high spatial resolution U-Pb dating of zircon by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) at 10–16 μm spot diameter has been proposed. This was achieved by introducing 2% (v/v) water-ethanol vapours into ICP in combination with the shielded torch system to increase the sensitivity and suppress the isotopic fractionation effect. Precise and accurate concordant U-Pb ages for Plešovice, GJ-1, and 91500 zircons were obtained using the proposed method, and the results agreed well with the isotope dilution-thermal ionization mass spectrometry (ID-TIMS) and LA-ICP-MS within 2σ, except for the ages obtained using dry plasma at 10 μm spot diameter. Additionally, the effects of plasma condition (dry plasma or 2% (v/v) ethanol plasma) and spot size (10, 16, 24, or 32 μm) on precision (RSD), accuracy (RE), and uncertainty (2σ) of the 206Pb/238U ages have been studied. The results indicated that increasing the spot diameter and introducing 2% (v/v) water-ethanol vapours into ICP significantly improved the precision, accuracy, and uncertainty for small spot diameters (10 and 16 μm), while it exhibited little influence for intermediate spot diameters (24 and 32 μm). Furthermore, the effects of spot size and plasma condition on the precision, accuracy, and uncertainty strongly depended on the sensitivity of analytes.
Adaptive Joint Lossy Source-Channel Coding for Multihop IoT Networks
Authors: Ez-zazi Imad , Arioua Mounir , El Oualkadi Ahmed
Published: May 2020

We consider monitoring applications in multihop wireless sensor networks (WSNs), where nodes rely on limited batteries so that energy efficiency and reliability are of paramount importance. Typically, lossy compression is aimed at saving transmission energy, yet affects the quality of transmitted data over lossy channels. Accordingly, using error correction coding (ECC) along with compression is required to guarantee both energy efficiency and high-fidelity reconstruction. In this paper, we analyze the energy efficiency of the joint use of lossy compression along with ECC, with the twofold objective of extending the network lifetime and assuring reliability. Specifically, we consider an adaptive joint lossy source-channel coding (JLSCC) system, where the energy efficiency and reliability performances depend on both the compression and the coding rates. Therein, we first carry out a performance analysis of JLSCC, considering realistic models of communication and computational energies, when the communication is performed over a Rayleigh fading channel. Then, we evaluate the performance of the JLSCC system compared to lossy compression and ECC systems in both end-to-end and multihop communications. Our results reveal that an adaptive JLSCC results in substantial energy saving while guaranteeing the required reliability performance, compared to both lossy compression and channel coding systems, that cannot be efficient for both energy and reliability. Instead, the JLSCC system is proved to be energy efficient for small distance end-to-end communication and large-scale multihop network, while leading to satisfactory reliability performance.
Wasserstein Generative Adversarial Network and Convolutional Neural Network (WG-CNN) for Bearing Fault Diagnosis
Authors: Yin Hang , Li Zhongzhi , Zuo Jiankai , Liu Hedan , Yang Kang , Li Fei
Published: May 2020

In recent years, intelligent fault diagnosis technology with deep learning algorithms has been widely used in industry, and they have achieved gratifying results. Most of these methods require large amount of training data. However, in actual industrial systems, it is difficult to obtain enough and balanced sample data, which pose challenges in fault identification and classification. In order to solve the problems, this paper proposes a data generation strategy based on Wasserstein generative adversarial network and convolutional neural network (WG-CNN), which uses generator and discriminator to conduct confrontation training, expands a small sample set into a high-quality dataset, and uses one-dimensional convolutional neural network (1D-CNN) to learn sample characteristics and classify different fault types. Experimental results over the standard Case Western Reserve University (CWRU) bearing fault diagnosis benchmark dataset showed that the proposed method has obvious and satisfactory fault diagnosis effect with 100% classification accuracy for few-shot learning. In different noise environments, this method also has excellent performance.
The Formation Mechanism of Green Dairy Industry Chain from the Perspective of Green Sustainable Development
Authors: Chen Hongli , Liu Xiuli
Published: May 2020

By constructing an evolutionary game model of green dairy industry chain from the perspective of green sustainable development, this paper analyzed the evolution process of strategy selection of dairy farmers and dairy enterprises under the supervision of the government. The study found the following. (1) In the absence of supervision, even if the initial cooperation willingness of dairy farmers and dairy enterprises is strong, once the additional cost of their input of “green production” is less than the additional benefit, they will eventually choose noncooperative strategy. (2) In the case of government supervision, when the government punishment or subsidy is not strong enough, the strategic choice of dairy farmers and dairy enterprises will fluctuate repeatedly, and the game equilibrium cannot be reached. However, when the government punishments and subsidies are strong enough, dairy farmers and dairy enterprises will choose to cooperate in their own interests. At this time, government subsidies have a greater impact on the evolution of bilateral cooperation than government punishments. (3) The reduction of green production cost can promote the formation of the green dairy industry chain, which is conducive to the green dairy industry chain system to achieve an ideal equilibrium state.
Genome-Wide Analysis, Characterization, and Expression Profile of the Basic Leucine Zipper Transcription Factor Family in Pineapple
Authors: Liu Yanhui , Chai Mengnan , Zhang Man , He Qing , Su Zhenxia , Priyadarshani S. V. G. N. , Liu Liping , Dong Guanxi , Qin Yuan
Published: May 2020

This study identified 57 basic leucine zipper (bZIP) genes from the pineapple genome, and the analysis of these bZIP genes was focused on the evolution and divergence after multiple duplication events in relation to the pineapple genome fusion. According to bioinformatics analysis of a phylogenetic tree, the bZIP gene family was divided into 11 subgroups in pineapple, Arabidopsis, and rice; gene structure and conserved motif analyses showed that bZIP genes within the same subgroup shared similar intron-exon organizations and motif composition. Further synteny analysis showed 17 segmental duplication events with 27 bZIP genes. The study also analyzed the pineapple gene expression of bZIP genes in different tissues, organs, and developmental stages, as well as in abiotic stress responses. The RNA-sequencing data showed that AcobZIP57 was upregulated in all tissues, including vegetative and reproductive tissues. AcobZIP28 and AcobZIP43 together with the other 25 bZIP genes did not show high expression levels in any tissue. Six bZIP genes were exposed to abiotic stress, and the relative expression levels were detected by quantitative real-time PCR. A significant response was observed for AcobZIP24 against all kinds of abiotic stresses at 24 and 48 h in pineapple root tissues. Our study provides a perspective for the evolutionary history and general biological involvement of the bZIP gene family of pineapple, which laid the foundation for future functional characterization of the bZIP genes in pineapple.
Distributed Optimal Control for a Class of Switched Nonlinear Systems with the State Time Delay
Authors: Duan Yuxing , Su Baili
Published: May 2020

This paper is focused on a kind of distributed optimal control design for a class of switched nonlinear systems with the state time delay which have a prescribed switching sequence. Firstly, we design a bounded controller to make the system stable for each mode of the nominal system. Then, a distributed optimal controller which can satisfy input constraint is designed based on the bounded stabilization controller. A sufficient condition to guarantee ultimate boundedness of the system is given based on appropriate assumption. The significance of this paper is that distributed optimal control method is applied to switched nonlinear systems with the state time delay. Finally, a simulation example is given to verify the effectiveness of the proposed method.
A Globally Optimal Robust Design Method for Complex Systems
Authors: Chen Yue , Shi Jian , Yi Xiao-jian
Published: May 2020

The uncertainty of the engineering system increases with the growing complexity of the engineering system; therefore, the tolerance to the uncertainty is essential. In the design phase, the output performance should reach the design criterion, even under large variations of design parameters. The tolerance to design parameter variations may be measured by the size of a solution space in which the output performance is guaranteed to deliver the required performance. In order to decouple dimensions, a maximum solution hyperbox, expressed by intervals with respect to each design parameter, is sought. The proposed approach combines the metaheuristic algorithm with the DIRECT algorithm where the former is used to seek the maximum size of hyperbox, and the latter is used as a checking technique that guarantees the obtained hyperbox is indeed a solution hyperbox. There are three advantages of the proposed approach. First, it is a global search and has a considerable high possibility to produce the globally maximum solution hyperbox. Second, it can be used for both analytically known and black-box performance functions. Third, it guarantees that any point selected within the obtained hyperbox satisfies the performance criterion as long as the performance function is continuous. Furthermore, the proposed approach is illustrated by numerical examples and real examples of complex systems. Results show that the proposed approach outperforms the GHZ and CES-IA methods in the literature.
Structural Balance Control of Complex Dynamical Networks Based on State Observer for Dynamic Connection Relationships
Authors: Gao Zilin , Wang Yinhe , Xiong Jiang , Pan Yong , Huang Yuanyuan
Published: May 2020

This paper investigates the observer-based structural balance control for a class of complex dynamical networks. Generally speaking, a complete complex dynamical network is composed of two coupled subsystems, which are called node subsystem (NS) and connection relationship subsystem (CS), respectively. Similar to synchronization and stabilization of networks, the structural balance is another phenomenon of networks and determined by the state of connection relationships. However, it is not feasible to design the controller for the CS directly because the states of the connection relationships are difficult to be measured accurately in practical applications. In order to solve this problem, a state observer for the CS has been designed. Thus, the structural balance controller in the CS can be directly designed by using the estimation information of the state observer. Then, with the help of the Lyapunov stability theory, it is proved that the CS can asymptotically track a given structural balance matrix under the influence of the observer-based controller. Finally, the results derived from this paper are demonstrated by performing a numerical example.
The Prevalence of Dental Caries in Primary Dentition in 3‐ to 5‐Year‐Old Preschool Children in Northern China
Authors: Zhang Kaiqiang , Li Jian , Lu Zhenfu
Published: May 2020

Objectives. To investigate the prevalence and factors promoting caries in primary dentition of 3‐5‐year‐old children in Northeast China. Materials and Methods. Data of 1,229 children aged 3 to 5 years were randomly selected. The caries prevalence and other indicators were assessed, and the results analyzed by SPSS. A questionnaire was also given to the children’s guardians to ascertain the potential risk factors associated with caries. Results. The decayed, missing, and filled teeth (dmft) index in children aged 3, 4, and 5 years old was 3.17, 5.13, and 6.07, respectively, while the caries prevalence rate was 62.16%, 75.89%, and 87.28% accordingly. The incidence of caries among rural children was higher than that in urban areas. Regarding oral health awareness, it was found that parents in urban areas had more accurate perceptions of oral health problems. It was also noted that the children’s brushing habits were worrying. Family economic and medical resources are not the main causes of serious dental caries in rural areas. Conclusions. The oral health status of children aged 3‐5 years is not optimistic. Many parents have a low awareness of oral health. Strengthening the promotion of oral health knowledge is an effective way to change the situation.
Identification and Validation of Prognostically Relevant Gene Signature in Melanoma
Authors: Gao Yali , Li Yaling , Niu Xueli , Wu Yutong , Guan Xiuhao , Hong Yuxiao , Chen Hongduo , Song Bing
Published: May 2020

Background. Currently, effective genetic markers are limited to predict the clinical outcome of melanoma. High‐throughput multiomics sequencing data have provided a valuable approach for the identification of genes associated with cancer prognosis. Method. The multidimensional data of melanoma patients, including clinical, genomic, and transcriptomic data, were obtained from The Cancer Genome Atlas (TCGA). These samples were then randomly divided into two groups, one for training dataset and the other for validation dataset. In order to select reliable biomarkers, we screened prognosis‐related genes, copy number variation genes, and SNP variation genes and integrated these genes to further select features using random forests in the training dataset. We screened for robust biomarkers and established a gene‐related prognostic model. Finally, we verified the selected biomarkers in the test sets (GSE19234 and GSE65904) and on clinical samples extracted from melanoma patients using qRT‐PCR and immunohistochemistry analysis. Results. We obtained 1569 prognostic‐related genes and 1101 copy‐amplification, 1093 copy‐deletions, and 92 significant mutations in genomic variants. These genomic variant genes were closely related to the development of tumors and genes that integrate genomic variation. A total of 141 candidate genes were obtained from prognosis‐related genes. Six characteristic genes (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) were selected by random forest feature selection, many of which have been reported to be associated with tumor progression. Cox regression analysis was used to establish a 6‐gene signature. Experimental verification with qRT‐PCR and immunohistochemical staining proved that these selected genes were indeed expressed at a significantly higher level compared with the normal tissues. This signature comprised an independent prognostic factor for melanoma patients. Conclusions. We constructed a 6‐gene signature (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) as a novel prognostic marker for predicting the survival of melanoma patients.
Bifurcation Behaviors of Steady-State Solution to a Discrete General Brusselator Model
Authors: Ma Ruyun , Zhao Zhongzi
Published: May 2020

We study the local and global bifurcation of nonnegative nonconstant solutions of a discrete general Brusselator model. We generalize the linear u in the standard Brusselator model to the nonlinear fu. Assume that f∈C0,∞,0,∞ is a strictly increasing function, and f′f−1a∈0,∞. Taking b as the bifurcation parameter, we obtain that the solution set of the problem constitutes a constant solution curve and a nonconstant solution curve in a small neighborhood of the bifurcation point b0j,f−1a,ab/f−1a2. Moreover, via the Rabinowitz bifurcation theorem, we obtain the global structure of the set of nonconstant solutions under the condition that fs/s2 is nonincreasing in 0,∞. In this process, we also make a priori estimation for the nonnegative nonconstant solutions of the problem.
Optimal Reinsurance Strategy for an Insurer and a Reinsurer with Generalized Variance Premium Principle
Authors: Li Danping , Shen Chaohai
Published: May 2020

This paper focuses on the optimal reinsurance problem with consideration of joint interests of an insurer and a reinsurer. In our model, the risk process is assumed to follow a Brownian motion with drift. The insurer can transfer the risk to the reinsurer via proportional reinsurance, and the reinsurance premium is calculated according to the variance and standard deviation premium principles. The objective is to maximize the expected exponential utility of the weighted sum of the insurer’s and the reinsurer’s terminal wealth, where the weight can be viewed as a regularization parameter to measure the importance of each party. By applying stochastic control theory, we establish the Hamilton–Jacobi–Bellman equation and obtain explicit expressions of optimal reinsurance strategies and optimal value functions. Furthermore, we provide some numerical simulations to illustrate the effects of model parameters on the optimal reinsurance strategies.
Study on the Home Health Caregiver Scheduling Problem under a Resource Sharing Mode considering Differences in Working Time and Customer Satisfaction
Authors: Wang Heping , He Yuke , Li Yan , Wang Fuyu
Published: May 2020

The stage of social aging and further deepening of population aging has been witnessed in China. The demand for home care is increasingly growing; meanwhile, medical human resources are insufficient. In this context, a home health caregiver scheduling problem under the resource sharing mode is studied in this paper. Under such mode, two types of caregivers, i.e., full-time caregiver and part-time caregiver, are regarded as the main labor force by HHC institutions. In HHC planning, different working times for the two kinds of caregivers will need to be considered. Consequently, in this paper, a corresponding mathematical model is established and a hybrid algorithm that combines the whale optimization algorithm (WOA) with the particle swarm optimization (PSO) algorithm is proposed to solve the model. The proposed algorithm is compared with the existing algorithms to verify its effectiveness through three example tests of different scales and Solomon example. Finally, the resource sharing model is compared with the traditional model through a case, and the rationality of home health caregiver scheduling in the resource sharing model is discussed in terms of cost structure and customer satisfaction.
Mucilage Extracted from Dragon Fruit Peel (Hylocereus undatus) as Flocculant for Treatment of Dye Wastewater by Coagulation and Flocculation Process
Authors: Le Oanh Thi Hoang , Tran Le Nhat , Doan Van Thi , Pham Quang Van , Ngo Anh Van , Nguyen Huan Huu
Published: May 2020

Dye wastewater from textile industries shows very low biodegradability due to high molecular weight and complex structures of dyes. So far, the most simple method for treatment of this type of wastewater has been coagulation and flocculation. This study determined the removal of turbidity and other pollutants from dye wastewater by mucilage extracted from the peel of dragon fruit (Hylocereus undatus) and its effect in reducing synthetic chemical polyaluminum chloride (PACl) used in coagulation and flocculation (CF) process. The removal of turbidity in a sequent CF process using PACl and dragon fruit mucilage was investigated based on Jar tests. Maximum coagulation efficiencies of PACl were typically observed at pH 4.0-6.0 and PACl concentrations of about 100-150 mg/L depending on types of wastewater, whereas optimal settling times were 30-60 minutes, respectively. The addition of dragon fruit mucilage (0.5-50 mg/L) after PACl (75-245 mg/L) resulted in turbidity removal efficiencies up to 95%. The addition of mucilage extracted from dragon fruit peels was proven to increase turbidity removal efficiency and decrease PACl use. The increase of turbidity removal was often estimated at 10-32%, whereas PACl used was about 3-10% less compared to total PACl needed for obtaining comparable efficiency when used alone. The flocculation activity of mucilage was also compared to polyacrylamide (PAM)—a synthetically organic flocculant. Since the peel of a dragon fruit is an abundant agriculture waste in Vietnam, using its extracted mucilage as a flocculant is an environmentally friendly method.
Assessment of Exposure to Sexually Explicit Materials and Substance Abuse among High-School Adolescents in North Shewa Zone: Application of Logistic Regression Analysis
Authors: Woldeamanuel Berhanu Teshome , Anteneh Leul Mekonnen , Yohannes Yordanos Berihun , Aga Merga Abdissa
Published: May 2020

Background. The use of substances such as cigarettes, khat, alcohol, and other illicit drugs like hashish, heroine, cannabis, and cocaine is a global major public threat, which affects young adult people particularly in developing countries. This study aims to assess the risk factors associated with substance use and exposure to sexually explicit materials among high-school adolescents in north Shewa zone, Oromia region. Method. A cross-sectional study was conducted to assess substance use and exposure to sexually explicit materials among high-school adolescents in North Shewa zone, Oromiya, Ethiopia, using a structured self-administered questionnaire adapted from the 2008 “Community That Care Youth Survey” for adolescent substance use and problem behaviors. The study used descriptive statistics and logistic regression analysis to identify the significant factors associated with substance use and exposure to sexually explicit materials among high school adolescents in the study area. Result. The prevalence of lifetime and current substance use was 47.7% (95% CI: 0.427, 0.527) and 30.4% (95% CI: 0.258, 0.350), respectively. 17.8% use khat in their life and 16.6% used khat in the past 30 days; 42.2% ever used alcohol and 26.1% currently uses alcohol; 4.8% and 4.5% used cigarette in lifetime and in the past 30 days, while 16.4% use other illicit drugs in lifetime and 8.4% use illicit drugs in the past 30 days, respectively. Distributions of substance use by sex indicate that male adolescents are more like likely 61.1% use substances than females. While, the prevalence of exposure to sexually explicit materials among high school adolescents was 35.8% (95% CI: 0.310, 0.406). Factors positively associated with increased substance use were being male (OR = 2.334, 95% CI: 1.549, 9.926), living through high level of family conflict (OR = 6.25, 95% CI: 1.745, 10.00), poor family management OR = 27.084, 95% CI: 1.624, 45.56), peer pressure (OR = 12.882, 95% CI: 1.882, 88.153), poor academic performance (OR = 14.48, 95% CI: 1.290, 162.58), and low school commitment (OR = 11.951, 95% CI: 1.418, 100.73). While, being male (OR = 7.52, 95% CI: 2.611, 21.739), age 14–16 (OR = 0.201, 95% CI: 0.071, 0.565), friends watch/read sexually explicit materials (OR = 5.376, 95% CI: 1.010, 28.571), and khat chewing (OR = 12.5, 95% CI: 2.924, 25.632) were factors significantly associated with high-school adolescents exposure to sexually explicit materials. Conclusion. The magnitude of prevalence for substance uses and exposure to sexually explicit materials in the study area was still higher. Therefore, interventions that focus on family management, peer pressure, and school commitment are required to decrease the prevalence of substance uses and exposure to sexually explicit materials among high-school adolescents.
Sitagliptin on Carotid Intima-Media Thickness in Type 2 Diabetes Mellitus Patients and Anemia: A Subgroup Analysis of the PROLOGUE Study
Authors: Lu Zhengri , Ma Genshan , Chen Lijuan
Published: May 2020

Introduction. Randomized clinical trials have not shown an additional clinical benefit of sitagliptin treatment over conventional treatment alone. However, studies of sitagliptin treatment have not examined the relationship between anemia and treatment group outcomes. Methods. The PROLOGUE study is a prospective clinical trial of 442 participants with type 2 diabetes mellitus (T2DM) randomized to sitagliptin treatment or conventional treatment which showed no treatment differences [Estimated mean (± standard error) common carotid intima-media thickness (CIMT) was 0.827±0.007 mm and 0.837±0.007 mm, respectively, with a mean difference of -0.009 mm (97.2% CI −0.028 to 0.011, p=0.309) at 24 mo of follow-up]. This is a post hoc subanalysis using data obtained from the PROLOGUE study; the study population was divided into anemic groups (n=94) and nonanemic group (n=343) based on hemoglobin level. And we analyzed for the changes in each CIMT parameter from baseline to 24 months in subgroups. Results. The treatment group difference in baseline-adjusted mean common carotid artery- (CCA-) IMT at 24 months was −0.003 mm (95% CI −0.022 to 0.015, p=0.718) in the nonanemic subgroup and −0.007 mm (95% CI −0.043 to 0.030, p=0.724) in the anemic subgroup. Although there were no significant differences in the other CIMT parameters between the treatment groups in the anemic subgroup, the changes in mean and max ICA-IMT at 24 months in the nonanemic subgroup were significantly lower in the sitagliptin group than the conventional group [−0.104 mm (95% CI −0.182 to −0.026), p=0.009 and −0.142 mm (−0.252 to −0.033), p=0.011, respectively]. Conclusion. These data suggest that nonanemia may indicate a potentially large subgroup of those with T2DM patients that sitagliptin therapy has a better antiatherosclerotic effect than conventional therapy. Further research is needed to confirm these preliminary observations.
Analytical, Numerical, and Experimental Investigations on Transverse Bending Responses of CFRP Square Tube Filled with Aluminum Foam
Authors: Yin Dejun , Zheng Jian , Xiong Chao , Yin Junhui , Li Baochen , Deng Huiyong , Zhu Xiujie
Published: May 2020

In order to explore the transverse bending responses of carbon fiber-reinforced polymer (CFRP) square tubes filled with aluminum foam, the three-point bending tests were carried out on an INSTRON machine, the full-field deformation measurement was performed using a 3D-DIC test system, the numerical model was established by ABAQUS/Explicit, and the bending stiffness was calculated by the improved analytical model based on shear-deformable beam theory. The discrepancies of experimental data, numerical results, and analytical predictions were acceptable, which were within 5%. The failure modes and mechanical properties of the filled tubes were experimentally captured and numerically predicted. Due to the filling effect of aluminum foam, the ultimate load, bending stiffness, and energy absorption of the filled CFRP square tubes increased, comparing to those of the hollow CFRP square tubes. With the increase of the aluminum foam density, the ultimate load, bending stiffness, and energy absorption of the filled tubes increased, while the specific ultimate load, specific bending stiffness, and specific energy absorption decreased.
A New Multiple-Distribution GAN Model to Solve Complexity in End-to-End Chromosome Karyotyping
Authors: Wu Yirui , Tan Xiao , Lu Tong
Published: May 2020

With significant development of Internet of medical things (IoMT) and cloud-fog-edge computing, medical industry is now involving medical big data to improve quality of service in patient care. Karyotyping refers classifying human chromosomes. However, performing karyotyping task generally requires domain expertise in cytogenetics, long-period experience for high accuracy, and considerable manual efforts. An end-to-end chromosome karyotype analysis system is proposed over medical big data to automatically and accurately perform chromosome related tasks of detection, segmentation, and classification. Facing image data generated and collected by means of edge computing, we firstly utilize visual feature to generate chromosome candidates with Extremal Regions (ER) technology. Due to severe occlusion and cross overlapping, we utilize ring radius transform to cluster pixels with same property to approximate chromosome shapes. To solve the problem of unbalanced and small dataset by covering diverse data patterns, we proposed multidistributed generated advertising network (MD-GAN) to perform data enhancement by generating additional training samples. Afterwards, we fine-tune CNN for chromosome classification task by involving generated and sufficient training images. Through experiments in self-collected datasets, the proposed method achieves high accuracy in tasks of chromosome detection, segmentation, and classification. Moreover, experimental results prove that MD-GAN-based data enhancement contributes to classification results of CNN to a certain extent.