bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Berberine in the Prevention of HIF‐1α Activation to Alleviate Adipose Tissue Fibrosis in High‐Fat‐Diet‐Induced Obese Mice
Authors: Hu Meilin , Wu Fan , Luo Jinlong , Gong Jing , Fang Ke , Yang Xueping , Li Jingbin , Chen Guang , Lu Fuer
Published: December 2018

Berberine (BBR) is the main active ingredient of a traditional Chinese herb Coptis chinensis. It has been reported to exhibit beneficial effects in treating diabetes and obesity. However, the underlying mechanism has not been fully elucidated. Adipose tissue fibrosis is a hallmark of obesity‐associated adipose tissue dysfunction. HIF‐1α plays a key role in adipose tissue fibrosis, which closely linked to metabolic dysfunction in obese state. We hypothesized that BBR may alleviate obesity‐induced adipose tissue fibrosis and associated metabolic dysfunction through inhibition of HIF‐1α. To test this hypothesis, we treated high fat diet (HFD) feeding mice with different dose of BBR (100 mg/kg, 200 mg/kg, and 300 mg/kg) for 8 weeks. We found that BBR treatment greatly decreased the body weight gain and reduced insulin resistance induced by HFD. Data also revealed that BBR improved histologic fibrous of epididymal white adipose tissue (eWAT) and was accompanied with inhibition of the abnormal synthesis and deposition of extracellular matrix (ECM) proteins, such as collagen and fibronectin. We also found that BBR treatment suppressed the expression of HIF‐1α and decreased the mRNA expression of LOX in epididymal adipose tissue, which plays a key role in fibrosis development. Taken together, these results suggest that BBR can regulate metabolic homeostasis and suppress adipose tissue fibrosis through inhibiting the expression of HIF‐1α.
An Interaction of Anionic- and Cationic-Rich Mixed Surfactants in Aqueous Medium through Physicochemical Properties at Three Different Temperatures
Authors: Sachin K. M. , Karpe Sameer A. , Singh Man , Bhattarai Ajaya
Published: December 2018

The mixed micellization of aqueous binary mixtures of DTAB-rich and SDS-rich surfactants, comprising sodium dodecyl sulfate (SDS) and dodecyltrimethylammonium bromide (DTAB) is studied in aqueous solution by using the physicochemical properties (PCPs) at three different temperatures (T = 293.15, 298.15, and 303.15 K) andP=0.1  MPa. The DTAB concentration is varied from 0.0001 to 0.03 M/mol·L−1in the ∼0.01 M/mol·L−1SDS solution, while the concentration of SDS is varied from 0.001 to 0.015 M/mol·L−1in the ∼0.005 M/mol·L−1DTAB. The stable formulations have been obtained by employing the DTAB-rich and SDS-rich surfactants solutions in 3 : 1 ratio. Therefore, different phases and aggregated states formed in the ternary combinations of DTAB/SDS/H2O have been identified and described. The calculated PCPs have been utilized for determining the nature of the solute-solvent interaction (SLS0I). With increasing surfactants concentration, the polarisation of the solution also increases along with an increase in relative viscosity (ηr), viscous relaxation time (τ), and surface excess concentration (Γmax). However, the surface area of the molecule (Amin), hydrodynamic volume (Vh), and hydrodynamic radius (Rh) decrease along with an increase in surfactants concentration.
Entamoeba Histolytica: Updates in Clinical Manifestation, Pathogenesis, and Vaccine Development
Authors: Kantor Micaella , Abrantes Anarella , Estevez Andrea , Schiller Alan , Torrent Jose , Gascon Jose , Hernandez Robert , Ochner Christopher
Published: December 2018

Entamoeba histolyticais the responsible parasite of amoebiasis and remains one of the top three parasitic causes of mortality worldwide. With increased travel and emigration to developed countries, infection is becoming more common in nonendemic areas. Although the majority of individuals infected withE. histolyticaremain asymptomatic, some present with amoebic colitis and disseminated disease. As more is learned about its pathogenesis and the host’s immune response, the potential for developing a vaccine holds promise. This narrative review outlines the current knowledge regardingE. histolyticaandE. disparand insight in the development of a vaccine.
Fecal Elastase Levels Predict Honeycombing in Pancreas Detected with Endoscopic Ultrasound
Authors: Akay Sinan , Şirin Burcu , Ünsal Belkıs
Published: December 2018

Background and Study Aims. We aimed to demonstrate the association between fecal elastase levels and Rosemont categories in patients with chronic changes in pancreas detected with endoscopic ultrasound. Patients and Methods. Patients were selected consecutively from endosonography examinations performed for upper gastrointestinal subepithelial lesions and for pancreas evaluation. Pancreas imaging findings were categorized according to the Rosemont criteria using echoendoscope. Patients who were indeterminate of, suggestive of, and consistent with chronic pancreatitis were included in the study. Fecal elastase measurements were performed after the patients were qualified to participate in the study according to endosonography findings. Results. Seventy patients were included in the study. 54 of them were male. Mean age of the patients was 51.7 ± 10.2 year. There were 36 patients in the indetermine group for chronic pancreatitis. Mean fecal elastase level was 507.1 ± 14.6 μg/g in the indeterminate group. There were 24 patients in the suggestive group of chronic pancreatitis. Mean fecal elastase level was 400.4 ± 121.4 μg/g in the suggestive group of chronic pancreatitis. There were 10 patients, in the consistent group with chronic pancreatitis. Mean fecal elastase level was 134.8 ± 86.1. The difference between the three groups of fecal elastase values was statistically significant compared with Kruskal Wallis test. Ordinal logistic regression analysis showed that there was a significant relation between endosonografic categories and fecal elastase values with Nagelkerke value of 0.704. Conclusions. Fecal elastase levels of each of the endosonographic categories were significantly different from each other. Also, fecal elastase values can predict chronic changes in pancreas detected with endoscopic ultrasound.
IgG Antibodies to GlcNAcβand Asialo-GM2 (GA2) Glycans as Potential Markers of Liver Damage in Chronic Hepatitis C and the Efficacy of Antiviral Treatment
Authors: Smorodin Eugeniy , Sergeyev Boris , Kurtenkov Oleg , Kuznetsova Tatiana , Geller Julia
Published: December 2018

Total serum IgG level is a surrogate marker of hepatitis C (HC) severity. Antibodies (Abs) to microbial glycans could be markers of HC severity caused by the translocation of microbial products. The level of anti-glycan (AG) Abs was analysed in serum samples of patients (n=128) with chronic HC in ELISA using fourteen synthetic glycans present in microbes and adhesins to evaluate the association of Abs with clinical parameters and the efficacy of antiviral treatment. The anti-GlcNAcβIgG level was significantly higher in patients with fibrosis (P=0.021) and severe portal inflammation (P<0.001) regardless of other clinical parameters. The ROC curve analysis showed sensitivity of 0.59, specificity of 0.84, and AUC of 0.71 in discriminating F0 from F1–4 (HCV genotype-1b-infected patients). The level of anti-GA2 Abs before Peg-IFN/RBV treatment was significantly higher in nonsustained viral response (non-SVR) to treatment than in SVR (P=0.033). ROC analysis showed sensitivity of 0.62, specificity of 0.70, and AUC of 64. Correlations of AG Abs to clinical parameters were found. The quantification of anti-GlcNAcβAbs deserves attention in assessment of the hepatic damage while anti-GA2 Abs may be a sign of immune response related to the antiviral treatment.
Complexity of a Microblogging Social Network in the Framework of Modern Nonlinear Science
Authors: Dmitriev Andrey , Kornilov Vasily , Maltseva Svetlana
Published: December 2018

Recent developments in nonlinear science have caused the formation of a new paradigm called the paradigm of complexity. The self‐organized criticality theory constitutes the foundation of this paradigm. To estimate the complexity of a microblogging social network, we used one of the conceptual schemes of the paradigm, namely, the system of key signs of complexity of the external manifestations of the system irrespective of its internal structure. Our research revealed all the key signs of complexity of the time series of a number of microposts. We offer a new model of a microblogging social network as a nonlinear random dynamical system with additive noise in three‐dimensional phase space. Implementations of this model in the adiabatic approximation possess all the key signs of complexity, making the model a reasonable evolutionary model for a microblogging social network. The use of adiabatic approximation allows us to model a microblogging social network as a nonlinear random dynamical system with multiplicative noise with the power‐law in one‐dimensional phase space.
Effect of Fiber Post-Resin Matrix Composition on Bond Strength of Post-Cement Interface
Authors: Alnaqbi Ibtisam O. M. , Elbishari Haitham , Elsubeihi Emad S.
Published: December 2018

Objective. To evaluate the influence of 3 different post-resin matrix systems cemented with dual-cure resin cement in simulated root canals made of PMMA acrylic sheet. Methods. 3 types of fiber posts (n = 60) with different resin matrixes divided into 3 groups: group 1 cross-linked FRC Postec Plus post (n = 20), group 2 cross-linked Rely X post (n = 20), and group 3 Interpenetrated IPN Everstick post (n = 20). All posts were cemented using Multilink Automix dual-cure cement. Posts were cemented into acrylic blocks in order to purely test the strength of cement-post interface. After one week storage at 37°C, two sections of 1 mm thickness from middle-third were subjected to micro-push-out test at crosshead speed 0.5 mm/min. Results. The data were analyzed using one-way analysis of variance (ANOVA). The variable fiber post-matrix system was found to significantly affect the push-out bond strength (p<0.001). Group 2 exhibited that the highest mean push-out bond strength was (5.36 + 2.3 MPa), and group 3 showed the lowest mean push-out (0.41 + 0.4 MPa). There was significant difference among the groups regarding the failure mode as chi-square test revealed (p<0.001). Conclusion. Prefabricated cross-linked posts with epoxy-based matrix demonstrated higher bond strength than prefabricated cross-linked posts with Bis-GMA-based matrix and posts with semi-IPN matrix when luted with dimethacrylate-based dual-cured resin cement.
The Tropical Matrix Groups with Symmetric Idempotents
Authors: Yang Lin
Published: December 2018

In this paper we study the semigroup Mn(T) of all n×n tropical matrices under multiplication. We give a description of the tropical matrix groups containing a diagonal block idempotent matrix in which the main diagonal blocks are real matrices and other blocks are zero matrices. We show that each nonsingular symmetric idempotent matrix is equivalent to this type of block diagonal matrix. Based upon this result, we give some decompositions of the maximal subgroups of Mn(T) which contain symmetric idempotents.
Long‐Time Predictive Modeling of Nonlinear Dynamical Systems Using Neural Networks
Authors: Pan Shaowu , Duraisamy Karthik
Published: December 2018

We study the use of feedforward neural networks (FNN) to develop models of nonlinear dynamical systems from data. Emphasis is placed on predictions at long times, with limited data availability. Inspired by global stability analysis, and the observation of strong correlation between the local error and the maximal singular value of the Jacobian of the ANN, we introduce Jacobian regularization in the loss function. This regularization suppresses the sensitivity of the prediction to the local error and is shown to improve accuracy and robustness. Comparison between the proposed approach and sparse polynomial regression is presented in numerical examples ranging from simple ODE systems to nonlinear PDE systems including vortex shedding behind a cylinder and instability‐driven buoyant mixing flow. Furthermore, limitations of feedforward neural networks are highlighted, especially when the training data does not include a low dimensional attractor. Strategies of data augmentation are presented as remedies to address these issues to a certain extent.
Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System
Authors: Chen Guang , Cao Hu , Aafaque Muhammad , Chen Jieneng , Ye Canbo , Röhrbein Florian , Conradt Jörg , Chen Kai , Bing Zhenshan , Liu Xingbo , Hinz Gereon , Stechele Walter , Knoll Alois
Published: December 2018

Neuromorphic vision sensor is a new passive sensing modality and a frameless sensor with a number of advantages over traditional cameras. Instead of wastefully sending entire images at fixed frame rate, neuromorphic vision sensor only transmits the local pixel-level changes caused by the movement in a scene at the time they occur. This results in advantageous characteristics, in terms of low energy consumption, high dynamic range, sparse event stream, and low response latency, which can be very useful in intelligent perception systems for modern intelligent transportation system (ITS) that requires efficient wireless data communication and low power embedded computing resources. In this paper, we propose the first neuromorphic vision based multivehicle detection and tracking system in ITS. The performance of the system is evaluated with a dataset recorded by a neuromorphic vision sensor mounted on a highway bridge. We performed a preliminary multivehicle tracking-by-clustering study using three classical clustering approaches and four tracking approaches. Our experiment results indicate that, by making full use of the low latency and sparse event stream, we could easily integrate an online tracking-by-clustering system running at a high frame rate, which far exceeds the real-time capabilities of traditional frame-based cameras. If the accuracy is prioritized, the tracking task can also be performed robustly at a relatively high rate with different combinations of algorithms. We also provide our dataset and evaluation approaches serving as the first neuromorphic benchmark in ITS and hopefully can motivate further research on neuromorphic vision sensors for ITS solutions.
Influence of Incorporating Silver Nanoparticles in Protease Treatment on Fiber Friction, Antistatic, and Antibacterial Properties of Wool Fibers
Authors: Memon Hafeezullah , Wang Hua , Yasin Sohail , Halepoto Adeel
Published: December 2018

This study was conducted by analyzing the effect of surface treatment on wool using varying percentages of protease (3%, 6%, and 9%) with incorporating silver nanoparticles and by varying pH (i.e., pH = 4 and pH = 7). The comparison of fiber surface morphology and the FTIR analysis was done to characterize the nanocoating. The results showed that the antistatic and antibacterial effect on the samples treated at 3% protease and 6% protease were better than the samples treated at 9% protease. Correspondingly, the samples treated at pH 4 had better antistatic and antibacterial properties than those treated at pH 7. Sulfur compounds play a key role in interaction and absorption of silver nanoparticles.
Solid-Liquid Phase Equilibria of the Ternary System (NaCl + CH3OH + H2O) at 298.15, 308.15, 318.15 K, and 0.1 MPa
Authors: Shi Jian , Hu Jiayin , Li Long , Guo Yafei , Yu Xiaoping , Deng Tianlong
Published: December 2018

The phase equilibrium of the ternary system (NaCl + CH3OH + H2O) at 298.15, 308.15, 318.15 K, and 0.1 MPa has been investigated by the isothermal dissolution equilibrium method. Solubilities and physicochemical properties including refractive index (nD) and density (ρ) in the ternary system were determined experimentally. According to the experimental data, the phase diagrams and diagrams of physicochemical properties versus sodium chloride concentration in the solvents at 298.15, 308.15, and 318.15 K were plotted, respectively. The experimental results showed that the system did not cause stratification and the equilibrium solid phase was anhydrous sodium chloride. Neither double salt nor solid solution was found at the three temperatures. The physicochemical properties of the ternary system change regularly with the increase of sodium chloride concentration in the solution, and the solvation effect of CH3OH on NaCl was significant. Moreover, the calculated values of NaCl solubility data based on the CNIBS/R-K equations agreed well with the experimental results, and the thermodynamic functions in the dissolution process of NaCl in the CH3OH-H2O binary system were also calculated for further investigation of NaCl dissolution process.
Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System
Authors: Wei Yu , Ning Sun
Published: December 2018

In recent years, many researchers have applied complex network theory to urban public transport network to construct complex network and analyze its network performance. The original analysis method generally uses the Space L and Space R model to establish a simple link between public sites but ignores the organic link between the overall network system and the line subsystem. As an important part of urban public transport system, subway plays an important role in alleviating traffic pressure. In this paper, a supernetwork model of Nanjing metro network is established by using the supernetwork method. Three parameters, node‐hyperedge degree, hyperedge‐node degree, and hyperedge degree, are proposed to describe the model. The model is compared with the traditional Space L and Space P models. The study on the supernetwork model of Nanjing metro complex network shows that the network density, network centrality, and network clustering coefficient are large, and the average network distance is small, which meets the requirements of traffic planning and design. In this study, the subway line is considered as a subsystem and further simplified as a node, so that the complex network analysis method can be applied to the new supernetwork model, expanding the thinking of complex network research.
An Empirical Evaluation on Vibrotactile Feedback for Wristband System
Authors: Wang Feng , Zhang Wanna , Luo Wei
Published: December 2018

With the rapid development of mobile computing, wearable wrist worn is becoming more and more popular. But the current vibrotactile feedback patterns of most wrist-worn devices are too simple to enable effective interaction in nonvisual scenarios. In this paper, we propose the wristband system with four vibrating motors placed in different positions in the wristband, providing multiple vibration patterns to transmit multisemantic information for users in eyes-free scenarios. However, we just applied five vibrotactile patterns in experiments (positional up and down, horizontal diagonal, clockwise circular, and total vibration) after contrastive analyzing nine patterns in a pilot experiment. The two experiments with the same 12 participants perform the same experimental process in labs and outdoors. According to the experimental results, users can effectively distinguish the five patterns both in lab and outside, with approximately 90% accuracy (except clockwise circular vibration of outside experiment), proving these five vibration patterns can be used to output multisemantic information. The system can be applied to eyes-free interaction scenarios for wrist-worn devices.
Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency
Authors: Zhang Junling , Qi Xiaowen , Liang Changyong
Published: December 2018

Continuous environmental concerns regarding construction industry have been driving general constructors of mega infrastructure projects to incorporate green contractors. Although conventional multiple attributes decision‐making (MADM) methodologies have provided feasible ways to select contractor, high complexity in scenarios of megaprojects still challenges existing MADM methods in concurrently accommodating three key issues of decision hesitancy, attributes interdependency, and group attitudinal character. To elicit decision‐makers’ hesitant fuzzy assessments more objectively and comprehensively, we define an expression tool called interval‐valued dual hesitant fuzzy uncertain unbalanced linguistic set (IVDHF_UUBLS) and develop aggregation operators through its operations. To exploit attributes interdependency, we establish a synthesized attributes’ weighting model to fuse an attributes interdependency‐based weighting vector and an argument‐dependent weighting vector, which are, respectively, derived through Decision‐Making and Trial Evaluation Laboratory (DEMATEL) technique and maximizing deviation method. To effectively utilize decision‐makers’ group attitudinal characters, we also develop a TOPSIS‐based method to rationally transform group ideal attitudes into order‐inducing vectors. On the strength of the above methods, an integrated MADM approach is then constructed. Finally, illustrative case study and experiments are conducted to validate our approach.
State Identification of ECS Turbine Bearing Based on Fractal Dimension
Authors: Li Chenchen , Han Qingpeng , Zhu Rui , Zhu Qingyu
Published: December 2018

According to nonlinear characteristics of vibration signals measured on the turbine used in the aircraft environment control system (ECS), the ensemble empirical mode decomposition (EEMD) together with fractal dimension analysis is investigated in the paper to extract characteristic quantities for the goal of fault diagnosis of turbine bearings. Firstly, in order to filter noise signal vibration and advance signal‐to‐noise signals under different statements of bearings, including normal bearing, inner ring fault, outer ring fault, and cage fault, are decomposed by EEMD. Then correlation dimension of those signals phase is calculated, contrasted, and analyzed after space reconstruction. The experimental result shows that the correlation dimension, as nonlinear geometric invariants, can be used as the characteristic quantity of ECS turbine bearing on running state. Moreover, this method can accurately and effectively identify the running state of the bearing.
Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection
Authors: Kiatwanidvilai Somyot , Praserttaweelap Rawinun
Published: December 2018

Decision and control of SCARA robot in HGA (head gimbal assembly) inspection line is a very challenge issue in hard disk drive (HDD) manufacturing. The HGA circuit called slider FOS is a part of HDD which is used for reading and writing data inside the disk with a very small dimension, i.e., 45 × 64 µm. Accuracy plays an important role in this inspection, and classification of defects is very crucial to assign the action of the SCARA robot. The robot can move the inspected parts into the corresponding boxes, which are divided into 5 groups and those are “Good,” “Bridging,” “Missing,” “Burn,” and “No connection.” A general image processing technique, blob analysis, in conjunction with neurofuzzy c-means (NFC) clustering with branch and bound (BNB) technique to find the best structure in all possible candidates was proposed to increase the performance of the entire robotics system. The results from two clustering techniques which are K-means, Kohonen network, and neurofuzzy c-means were investigated to show the effectiveness of the proposed algorithm. Training results from the 30x microscope inspection with 300 samples show that the best accuracy for clustering is 99.67% achieved from the NFC clustering with the following features: area, moment of inertia, and perimeter, and the testing results show 92.21% accuracy for the conventional Kohonen network. The results exhibit the improvement on the clustering when the neural network was applied. This application is one of the progresses in neurorobotics in industrial applications. This system has been implemented successfully in the HDD production line at Seagate Technology (Thailand) Co. Ltd.
Robust Exponential Stability of Switched Complex‐Valued Neural Networks with Interval Parameter Uncertainties and Impulses
Authors: Xu Xiaohui , Xue Huanbin , Peng Yiqiang , Xu Quan , Yang Jibin
Published: December 2018

In this paper, dynamic behavior analysis has been discussed for a class of switched complex‐valued neural networks with interval parameter uncertainties and impulse disturbance. Sufficient conditions for guaranteeing the existence, uniqueness, and global robust exponential stability of the equilibrium point have been obtained by using the homomorphism mapping theorem, the scalar Lyapunov function method, the average dwell time method, and M‐matrix theory. Since there is no result concerning the stability problem of switched neural networks defined in complex number domain, the stability results we describe in this paper generalize the existing ones. The effectiveness of the proposed results is illustrated by a numerical example.
Stabilization and Synchronization of Uncertain Zhang System by Means of Robust Adaptive Control
Authors: Pérez-Cruz J. Humberto
Published: December 2018

Standard adaptive control is the preferred approach for stabilization and synchronization of chaotic systems when the structure of such systems is a priori known but the parameters are unknown. However, in the presence of unmodeled dynamics and/or disturbance, this approach is not effective anymore due to the drift of the parameter estimations, which eventually causes the instability of the closed‐loop system. In this paper, a robustifying term, which consists of a saturation function, is used to avoid this problem. The robustifying term is added to the adaptive control law. Consequently, the learning law is also modified. The boundedness of the states and the parameter estimations is rigorously and thoroughly proven by means of Lyapunov like analysis based on Barbalat’s lemma. On these new conditions, the convergence to zero cannot be achieved due to the presence of unmodeled dynamics and/or disturbance. However, it is still possible to guarantee the asymptotic convergence to a bounded zone around zero. The width of this zone can be adjusted by the designer. The performance of this robust approach is verified by numerical simulations. Although, for simplicity, this strategy is only applied to the stabilization and synchronization of Zhang system, the procedure can easily be generalized to a broad class of chaotic systems.
Study on the Performance of High‐Speed Rail Damage of Four Different Materials
Authors: Hu Jiajie , Zhong Wen , Liu Qiyue
Published: December 2018

For four types of railway rails, corresponding rolling tests have been executed by using the JD‐1 wheel/rail simulation device based on the Hertz simulation method, which can ensure the reciprocal contact condition between simulation rail and wheel under experimental conditions approximate to practical contact conditions. The results indicate that, for the rail material which has a higher hardness, the wear volume was less and the plastic deformation layer was thinner after the rolling test, but the crack propagation was more significant and the fatigue damage was severer, showing that its wear resistance was better. The analysis shows that the fatigue resistance of U71Mn rail was better, and considering fatigue is the main failure type for high‐speed rail, so it is more suited to the high‐speed railway.
A Damage Classification Approach for Structural Health Monitoring Using Machine Learning
Authors: Tibaduiza Diego , Torres-Arredondo Miguel Ángel , Vitola Jaime , Anaya Maribel , Pozo Francesc
Published: December 2018

Inspection strategies with guided wave‐based approaches give to structural health monitoring (SHM) applications several advantages, among them, the possibility of the use of real data from the structure which enables continuous monitoring and online damage identification. These kinds of inspection strategies are based on the fact that these waves can propagate over relatively long distances and are able to interact sensitively with and uniquely with different types of defects. The principal goal for SHM is oriented to the development of efficient methodologies to process these data and provide results associated with the different levels of the damage identification process. As a contribution, this work presents a damage detection and classification methodology which includes the use of data collected from a structure under different structural states by means of a piezoelectric sensor network taking advantage of the use of guided waves, hierarchical nonlinear principal component analysis (h‐NLPCA), and machine learning. The methodology is evaluated and tested in two structures: (i) a carbon fibre reinforced polymer (CFRP) sandwich structure with some damages on the multilayered composite sandwich structure and (ii) a CFRP composite plate. Damages in the structures were intentionally produced to simulate different damage mechanisms, that is, delamination and cracking of the skin.
Congenital Midline Cervical Cleft and W-Plasty: Our Experience
Authors: Bahakim Abdullah , Francois Martine , Van Den Abbeele Thierry
Published: December 2018

Objectives. Congenital midline cervical cleft (CMCC) is a very uncommon congenital anomaly of the midline anterior neck, and although it has very pathognomonic features (including nipple-like protuberance), it could be mistaken for other congenital neck lesions, such as thyroglossal duct cyst and branchial apparatus anomalies. Thus, it represents a challenging diagnosis. In this 21-patient series, we discuss the clinical features of CMCC, its pathophysiology characteristics, and its modalities management. Material and Methods. We conducted a retrospective chart review of children presenting with CMCC at our institution, between January 1998 and January 2016. Results. Twenty-one patients were identified with CMCC. Ages ranged between 1 day and 14 years. The length of the lesion varied from 0.5 to 5 cm, and the size of the skin tag varied from 0.2 to 1.5cm. No other significant associated anomalies were found. Surgery was the mainstay treatment, and no recurrence was found. W-plasty was used in most patients to close the defect. Conclusion. With a little more than 200 published cases, our series represents the largest series worldwide. The lesion is usually isolated, and no further investigation is required. Surgery is the mainstay of treatment, with complete excision being usually curative. It should be treated at an early age to prevent complications. In our experience, W-plasty was a good alternative to the most commonly used Z-plasty, in skin closure, with respect to both aesthetic and functional results.
Sesame Yield Response to Deficit Irrigation and Water Application Techniques in Irrigated Agriculture, Ethiopia
Authors: Hailu E. K. , Urga Y. D. , Sori N. A. , Borona F. R. , Tufa K. N.
Published: December 2018

The study was conducted at Werer Agricultural Research Center, Addis Ababa, for two years, 2013 and 2015, during main seasons and for three years, 2012/13, 2013/14, and 2014/15, during the cool period cropping season (November to February) as in the local cropping calendar. The study was aimed at identifying optimum soil moisture stress for sesame and thereby determining appropriate water-saving irrigation methods and also productivity under limited water resource conditions. Nine treatments with three levels of irrigation water percentage based on evapotranspiration of the crop (ETc) (100% ETc, 75% ETc, and 50% ETc) and three types of furrow irrigation methods (alternate furrow, fixed furrow, and conventional furrow) were used. The study design was randomized complete block design (RCBD) with three replications. The yield of sesame had significant (p<0.05) variation among treatments due to deficit irrigation levels and application methods for sesame planted in main seasons. The highest mean yield of 937.50 kg/ha and 2797.6 kg/ha was obtained from the treatment of 50% ETc with alternate and conventional furrow application methods in 2013 and 2015, respectively. The combined mean yield of two years (2013–2015) showed different levels of deficit irrigation, and irrigation methods had a significant effect (p<0.05) on main season planted sesame. Hence, the highest mean yield of 1846.7 kg/ha was obtained from the application of 50% ETc with the conventional furrow application method. In the cool planting season, the highest mean yield of 528.55 kg/ha, 1432.3 kg/ha, and 1562.5 kg/ha was obtained from treatments of 50% ETc, 75% ETc, and 100% ETc with the conventional furrow application method in 2012/13, 2013/14, and 2014/15, respectively. Moreover, during the same period over years, combined analysis showed that the highest mean yield of 1053 kg/ha was obtained from application of 100% ETc with the conventional furrow application method. Thus, it is concluded that a deficit irrigation treatment of 50% ETc with the conventional furrow application method for main season and application of 100% ETc with the conventional furrow application method for cool planting season are best practices of water-saving strategies for irrigated agriculture system.
Mathematical Modeling of Ebola Virus Disease in Bat Population
Authors: EL Rhoubari Zineb , Besbassi Hajar , Hattaf Khalid , Yousfi Noura
Published: December 2018

Many scientific researches have demonstrated that bats can survive Ebola virus and they represent natural reservoirs of this zoonotic virus. In this study, we develop a generalized epizootic model for the transmission dynamics of Ebola virus disease (EVD) in bat population by taking into account the environment contamination. The transmission process is modeled by two general incidence functions that include many incidence rates used in infectious diseases modeling. We first prove that the model is epidemiologically and mathematically well-posed by showing the existence, positivity, and boundedness of solutions. By analyzing the characteristic equations and constructing suitable Lyapunov functionals, the stability analysis of equilibria is investigated.
A Multifactory Integrated Production and Distribution Scheduling Problem with Parallel Machines and Immediate Shipments Solved by Improved Whale Optimization Algorithm
Authors: Abdollahzadeh Vahid , Nakhaikamalabadi Isa , Hajimolana Seyyed Mohammad , Zegordi Seyyed Hesamoddin
Published: December 2018

This paper discusses the integrated scheduling of production and distribution operations in a multifactory supply chain with make‐to‐order production system. For the production side of the supply chain, we considered distributed parallel‐established factories with identical parallel machines available at each factory. We assumed that the factories could produce all customers’ orders with different production rates and costs. For the distribution side of the supply chain, we considered a limited number of homogeneous vehicles that immediately distribute the finalized orders to the customers. Then, a mixed‐integer nonlinear programming model is developed to determine the detailed scheduling of production and distribution that minimizes the total costs of the supply chain including production, distribution, and late delivery costs. To solve the real‐world scale problems, we developed a new whale optimization algorithm (WOA). Moreover, we conducted computational experiments by generating several test problems to evaluate the proposed algorithm. Statistical analysis showed that the proposed algorithm has better performance than traditional WOA for different scales of the problem. Moreover, it confirms the capability of the improved whale optimization algorithm (IWOA) to solve the medium‐scale instances; however, the results indicate the better performance of genetic algorithm (GA) for the large‐scale instances.
Using Compact 1H NMR, NIR, and Raman Spectroscopy Combined with Multivariate Data Analysis to Monitor a Biocatalyzed Reaction in a Microreaction System
Authors: Legner Robin , Wirtz Alexander , Jaeger Martin
Published: December 2018

Process analytical technology aims at process knowledge and process improvement, efficiency, and sustainability. A prerequisite is process monitoring. The combination of microreaction systems and spectroscopy proved suitable due to dimension and compound reduction and real-time monitoring capabilities. Compact 1H NMR, NIR, and Raman spectroscopy were used to monitor the biocatalyzed hydrolysis and esterification of acetic anhydride to isoamyl acetate using immobilized Candida antarctica lipase B (CALB) in a microreaction system in real-time. To facilitate the identification of signals suitable for the extraction of concentration-time (c-t) graphs, 2D heterocorrelation spectra were generated through covariance transformations applied to 1D Raman, NIR, and NMR data. By means of this purely mathematical statistical procedure, the relevant signals of the process media were assigned to educts and products and thus made applicable for univariate data evaluation. The data obtained were interpreted in terms of a first-order kinetic model, and corresponding reaction rate constants were extracted. An alternative, elegant, and fit-for-automation approach for the kinetic analysis of the spectra was demonstrated in using multivariate curve resolution (MCR). The results of the univariate and multivariate approaches were comparable with regard to reaction rates and concentrations. While the manual integration of the 1H NMR spectra followed by univariate analysis allowed to establish a concentration profile of the final product isoamyl acetate hence revealing more details, multivariate analysis was found more suitable for process automation.
Numerical Simulation Study on Root Stones Loss in Dam Buttress Engineering
Authors: Yao Chi , Yang Changming , Lan Yan , Jiang Qinghui , Jiang Shuihua , Yang Jianhua
Published: December 2018

In order to study the loss of root stones under action of water flow in dam buttress, based on Flow-3D, a mathematical model was established. At first, the physical experiment was carried out about water drag force on a 0.04 m×0.04 m×0.04 m cubic block. And then a numerical flume model about this experiment was established in Flow-3D software. The values of drag force were compared between the numerical and experimental results, and the percentage of error was less than 5%. Thus, the numerical model in Flow-3D was accurate and available. Then, a numerical simulation on root stones loss in an actual dam buttress project was carried out. Since the actual flow is turbulent, the RNGk-εturbulence model was used. And VOF method, FAVOR technology, and GMO model were also used in this simulation. The numerical results showed flow depth, pressure, velocity, turbulent energy, and root stones loss. Because water level of the inflow increased with time continuously, flow depth and velocity also increased, and the root stones would be lost. The increase in flow velocity was the fastest in the dam head, and the start time of root stones loss was also the earliest. The most serious area of root stones loss is the dam head, and the serious second area is the upper cross corner. Those root stones would have the farthest lost distance in the dam head. The root stones loss was also serous in the upstream face. However, the root stones in the upstream face and the down cross corner were less affected by water flow, so there were no root stones loss phenomena. Thus, in the actual project, the dam head, the upper cross corner, and the upstream face should get more attention.
Research on Decision‐Making of Complex Venture Capital Based on Financial Big Data Platform
Authors: Luo Tao
Published: December 2018

The prediction of stock premium has always been a hot issue. By predicting stock premiums to provide a way for companies to respond to financial risk investments, companies can avoid investment failures. In this paper, under the financial big data platform, bootstrap resampling technology and long short‐term memory (LSTM) are used to predict the value of the stock premium within 20 months. First, using the theme crawler, jsoup page parsing, Solr search, and Hadoop architecture to build a platform for financial big data. Secondly, based on the block bootstrap resampling technology, the existing data information is expanded to make full use of the existing data information. Then, based on the LSTM network, the stock premium in 20 months is predicted and compared with the values predicted by support vector machine regression (SVR), and the SSE and R‐square average indicators are calculated, respectively. The calculation results show that the SSE value of LSTM is lower than SVR, and the R‐square value of LSTM is higher than SVR, which means that the effect of LSTM prediction is better than SVR. Finally, based on the forecast results and evaluation indicators of the stock premium, we provide countermeasures for the company’s financial risk investment.
Correlation of Triiodothyronine Level with In-Hospital Cardiac Function and Long-Term Prognosis in Patients with Acute Myocardial Infarction
Authors: She Jianqing , Feng Jiahao , Deng Yangyang , Sun Lizhe , Wu Yue , Guo Manyun , Liang Xiao , Li Jingjin , Xia Yulong , Yuan Zuyi
Published: December 2018

Objective. The pathophysiologic mechanism of how thyroid function is related to the development and prognosis of acute myocardial infarction (AMI) remains under explored, and there has been a lack of clinical investigations. In this study, we investigate the relationship between triiodothyronine (T3) level and cardiac ejection fraction (EF) as well as probrain natriuretic peptide (NT-proBNP) on admission and subsequent prognosis in AMI patients. Methods. We measured admission thyroid function, NT-proBNP, and EF by echocardiography in 345 patients diagnosed with AMI. Simple and multiregression analyses were performed to investigate the correlation between T3 level and EF as well as NT-proBNP. Major adverse cardiovascular events (MACE), including new-onset myocardial infarction, acute heart failure, and cardiac death, were documented during the follow-up. 248 participants were separated into three groups based on T3 and free triiodothyronine (FT3) levels for survival analysis during a 2-year follow-up. Results. 345 patients diagnosed with AMI were included in the initial observational analysis. 248 AMI patients were included in the follow-up survival analysis. The T3 levels were found to be significantly positively correlated with EF (R square=0.042, P<0.001) and negatively correlated with admission NT-proBNP levels (R square=0.059, P<0.001), which is the same with the correlation between FT3 and EF (R square=0.053, P<0.001) and admission NT-proBNP levels (R square=0.108, P<0.001). Kaplan-Meier survival analysis revealed no significant difference with regard to different T3 or FT3 levels at the end of follow-up. Conclusions. T3 and FT3 levels are moderately positively correlated with cardiac function on admission in AMI patients but did not predict a long-time survival rate. Further studies are needed to explain whether longer-term follow-up would further identify the prognosis effect of T3 on MACE and all-cause mortality.
Two Proofs and One Algorithm Related to the Analytic Hierarchy Process
Authors: Pavluš Miron , Tomeš Rostislav , Malec Lukáš
Published: December 2018

36 years ago, Thomas Saaty introduced a new mathematical methodology, called Analytic Hierarchy Process (AHP), regarding the decision-making processes. The methodology was widely applied by Saaty and by other authors in the different human activity areas, like planning, business, education, healthcare, etc. but, in general, in the area of management. In this paper, we provide two new proofs for well-known statement that the maximal eigenvalue λmax is equal to n for the eigenvector problem Aw=λw, where A is, so-called, the consistent matrix of pairwise comparisons of type n×n (n≥ 2) with the solution vector w that represents the probability components of disjoint events. Moreover, we suggest an algorithm for the determination of the eigenvalue problem solution Aw=nw as well as the corresponding flowchart. The algorithm for arbitrary consistent matrix A can be simply programmed and used.
The Association of Radial Artery Pulse Wave Variables with the Pulse Wave Velocity and Echocardiographic Parameters in Hypertension
Authors: Qiao Li-jie , Qi Zhen , Tu Li-ping , Zhang Yu-hang , Zhu Li-ping , Xu Jia-tuo , Zhang Zhi-feng
Published: December 2018

This study aims at exploring the cardiovascular pathophysiological mechanism of TCM (traditional Chinese medicine) pulse by detecting the correlation between radial artery pulse wave variables and pulse wave velocity/echocardiographic parameters. Two hundred Chinese subjects were enrolled in this study, which were grouped into health control group, hypertension group, and hypertensive heart disease group. Physical data obtained in this study contained TCM pulse images at “Guan” position of the left hand, pulse wave velocity, and echocardiographic parameters. Linear and stepwise regression analysis was performed to assess the association of radial artery pulse wave variables with pulse wave velocity and echocardiographic parameters in the total population and in each different group. After adjusting for related confounding factors, decrease of t1, t5 and increase of h1, h3/h1 were statistically associated with arterial stiffness in the total population (P<0.05). Moreover, the correlation study in each group showed that the decrease of both t3 and h5 was also related to arterial stiffness (P<0.05). In terms of echocardiographic parameters, the height of dicrotic wave indicated by h5 was the most relevant pulse wave variable. For the health control, h5 was negatively associated with interventricular septal thickness (VST) and left ventricular posterior wall thickness (PWT) (P<0.05), while for the hypertension population and those with target‐organ damage to heart, increase of h5 might be associated with decrease of ejection fraction (EF) and increase of all the remaining echocardiographic parameters especially for left ventricular end‐systolic diameter (LVDs) and Left ventricular end‐diastolic diameter (LVDd) (P<0.05). In conclusion, we found radial artery pulse wave variables were in association with the arterial stiffness and echocardiographic changes in hypertension, which would provide an experimental basis for cardiovascular pathophysiological mechanism of radial artery pulse wave variables.
A New State Estimation Method with Radar Measurement Missing
Authors: Wang Hongjian , Li Cun , Wang Ying , Li Qing , Ban Xicheng
Published: December 2018

This paper describes a method that addresses the transient loss of observations in sea surface target state estimations. A six degrees of freedom swing platform fixed with a MiniRadaScan is used to simulate the loss of observations. The state transition model based on the historical observation data fit prediction is designed because the existing state estimation method can only use the system model prediction while the observation is missing. An observation data sliding window width adaptive adjustment strategy is proposed that can improve the fitting accuracy of the state transition model. To solve the problem where the weight value of the Gaussian components of the Gaussian mixture filter is not changed in the time update stage while the observation is missing, an adaptive adjustment strategy for the weight is proposed based on the Chapman‐Kolmogorov equation, which can improve the estimation precision under the conditions of the missing observation. The simulation test demonstrates the proposed accuracy and real‐time performance of the proposed algorithm.
Boundary Value Problems Governed by Superdiffusion in the Right Angle: Existence and Regularity
Authors: Dzhafarov Ramzet , Vasylyeva Nataliya
Published: December 2018

For α∈(1,2), we analyze a stationary superdiffusion equation in the right angle in the unknown u=u(x1,x2): Dx1αu+Dx2αu=f(x1,x2), where Dxα is the Caputo fractional derivative. The classical solvability in the weighted fractional Hölder classes of the associated boundary problems is addressed.