bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Speed Matching Affecting Contrarotating Fan’s Performance Using Wireless Sensor Network including Big Data and Numerical Simulation
Authors: Luan Hengxuan , Weng Liyuan , Liu Ranhui , Luan Yuanzhong , Li Dongmin
Published: September 2018

This paper describes the investigations performed to better understand two‐stage rotor speed matching in a contrarotating fan. In addition, this study develops a comprehensive measuring and communication system for a contrarotating fan using ZigBee network. The investigation method is based on three‐dimensional RANS simulations; the RANS equations are solved by the numerical method in conjunction with a SST turbulence model. A wireless measurement system using big data method is first designed, and then a comparison is done with experimental measurements to outline the capacity of the numerical method. The results show that when contrarotating fan worked under designed speed, performance of two‐stages rotors could not be matched as the designed working condition was deviated. Rotor 1 had huge influences on flow rate characteristics of a contrarotating fan. Rotor 2 was influenced by flow rates significantly. Under large flow rate condition, the power capability of rotor 2 became very weak; under working small flow rate condition, overloading would take place to class II motor. In order to solve the performance mismatch between two stages of CRF under nondesigned working conditions, under small flow rate condition, the priority shall be given to increase of the speed of rotor 1, while the speed of rotor 2 shall be reduced appropriately; under large flow rate condition, the speed of rotor 1 shall be reduced and the speed of rotor 2 shall be increased at the same time.
AndroClass: An Effective Method to Classify Android Applications by Applying Deep Neural Networks to Comprehensive Features
Authors: Reyhani Hamedani Masoud , Shin Dongjin , Lee Myeonggeon , Cho Seong-Je , Hwang Changha
Published: September 2018

Android application (app) stores contain a huge number of apps, which are manually classified based on the apps’ descriptions into various categories. However, the predefined categories or apps descriptions are usually not very accurate to reflect the real functionalities of apps, thereby leading to misclassify the apps, which may cause serious security issues and unreliability problem in the app store. Therefore, the automatic app classification is an important demand to construct a secure, reliable, integrated, and easy to navigate app store. In this paper, we propose an effective method called AndroClass to automatically classify apps based on their real functionalities by using rich and comprehensive features representing the actual functionalities of the apps. AndroClass performs three steps of feature extraction, feature refinement, and classification. In the feature extraction step, we extract 14 various features for each app by utilizing a unified tool suite. In the feature refinement step, we apply Random Forest algorithm to refine the features. In the classification step, we combine refined features into a single one and AndroClass is equipped with K‐Nearest Neighbor, Naive Bayes, Support Vector Machine, and Deep Neural Network to classify apps. On the contrary to the existing methods, all the utilized features in AndroClass are stable and clearly represent the actual functionalities of the app, AndroClass does not pose any issues to the user privacy, and our method can be applied to classify unreleased or newly released apps. The results of extensive experiments with two real-world datasets and a dataset constructed by human experts demonstrate the effectiveness of AndroClass where the classification accuracy of AndroClass with the latter dataset is 83.5%.
Transforming Retinal Photographs to Entropy Images in Deep Learning to Improve Automated Detection for Diabetic Retinopathy
Authors: Lin Gen-Min , Chen Mei-Juan , Yeh Chia-Hung , Lin Yu-Yang , Kuo Heng-Yu , Lin Min-Hui , Chen Ming-Chin , Lin Shinfeng D. , Gao Ying , Ran Anran , Cheung Carol Y.
Published: September 2018

Entropy images, representing the complexity of original fundus photographs, may strengthen the contrast between diabetic retinopathy (DR) lesions and unaffected areas. The aim of this study is to compare the detection performance for severe DR between original fundus photographs and entropy images by deep learning. A sample of 21,123 interpretable fundus photographs obtained from a publicly available data set was expanded to 33,000 images by rotating and flipping. All photographs were transformed into entropy images using block size 9 and downsized to a standard resolution of 100 × 100 pixels. The stages of DR are classified into 5 grades based on the International Clinical Diabetic Retinopathy Disease Severity Scale: Grade 0 (no DR), Grade 1 (mild nonproliferative DR), Grade 2 (moderate nonproliferative DR), Grade 3 (severe nonproliferative DR), and Grade 4 (proliferative DR). Of these 33,000 photographs, 30,000 images were randomly selected as the training set, and the remaining 3,000 images were used as the testing set. Both the original fundus photographs and the entropy images were used as the inputs of convolutional neural network (CNN), and the results of detecting referable DR (Grades 2–4) as the outputs from the two data sets were compared. The detection accuracy, sensitivity, and specificity of using the original fundus photographs data set were 81.80%, 68.36%, 89.87%, respectively, for the entropy images data set, and the figures significantly increased to 86.10%, 73.24%, and 93.81%, respectively (all p values <0.001). The entropy image quantifies the amount of information in the fundus photograph and efficiently accelerates the generating of feature maps in the CNN. The research results draw the conclusion that transformed entropy imaging of fundus photographs can increase the machinery detection accuracy, sensitivity, and specificity of referable DR for the deep learning-based system.
QSAR Study of (5-Nitroheteroaryl-1,3,4-Thiadiazole-2-yl) Piperazinyl Derivatives to Predict New Similar Compounds as Antileishmanial Agents
Authors: Ousaa Abdellah , Elidrissi Bouhya , Ghamali Mounir , Chtita Samir , Aouidate Adnane , Bouachrine Mohammed , Lakhlifi Tahar
Published: September 2018

To search for newer and potent antileishmanial drugs, a series of 36 compounds of 5-(5-nitroheteroaryl-2-yl)-1,3,4-thiadiazole derivatives were subjected to a quantitative structure-activity relationship (QSAR) analysis for studying, interpreting, and predicting activities and designing new compounds using several statistical tools. The multiple linear regression (MLR), nonlinear regression (RNLM), and artificial neural network (ANN) models were developed using 30 molecules having pIC50 ranging from 3.155 to 5.046. The best generated MLR, RNLM, and ANN models show conventional correlation coefficients R of 0.750, 0.782, and 0.967 as well as their leave-one-out cross-validation correlation coefficients RCV of 0.722, 0.744, and 0.720, respectively. The predictive ability of those models was evaluated by the external validation using a test set of 6 molecules with predicted correlation coefficients Rtest of 0.840, 0.850, and 0.802, respectively. The applicability domains of MLR and MNLR transparent models were investigated using William’s plot to detect outliers and outsides compounds. We expect that this study would be of great help in lead optimization for early drug discovery of new similar compounds.
Effect of Fungal Solid-State Fermented Product in Broiler Chicken Nutrition on Quality and Safety of Produced Breast Meat
Authors: Marcinčák Slavomír , Klempová Tatiana , Bartkovský Martin , Marcinčáková Dana , Zdolec Nevijo , Popelka Peter , Mačanga Ján , Čertík Milan
Published: September 2018

The aim of this work was to analyse the effect of addition of 10% (w/w) fermented bioproduct into commercial broiler feed on fatty acid profile, lipid oxidative stability, and sensory properties of chicken breast meat. The fermented bioproduct was prepared by fermentation of cornmeal by filamentous fungiUmbelopsis isabellinaCCF 2412 in solid-state fermentation (SSF) process and the final bioproduct was enriched with gamma-linolenic acid and beta-carotene. In the experiment, 80 pieces of 1-day-old chickens COBB 500 were used. Half of them (control group) were fed only with commercial feed. Chickens of the experimental group were fed with commercial feed, and, from the11thday of age until the time of slaughter (39thday), 10% of commercial feed was replaced with fermented bioproduct. Application of fermented bioproduct into commercial feed mixture positively influenced profile of fatty acids in breast meat. The amount of gamma-linolenic, alpha-linolenic, and oleic acids in fat of breast muscles was increased and n-6/n-3 ratio was significantly decreased. Profile and content of PUFAs did not change after thermal treatment of meat. Oxidative stability of fat and sensory properties of the meat during the storage (4°C, 7 days) of meat were not affected by fermented bioproduct.
Improving Bias Estimation Precision via a More Accuracy Radar Bias Model
Authors: Yong Xiaoju , Wu Youli , Tu Mingwu , Du Xiaowei , Zhang Shuang
Published: September 2018

Radar bias estimation is an important part of a multisensor tracking system. Because the radar bias models in current efforts are not sufficiently accurate, the bias estimation accuracy is not satisfied. First, a general radar bias model, in which the importance of the sensor-target pair-related bias is emphasized, is proposed in this paper. Moreover, the target-sensor pair-related bias is considered on the grounds of the impact of atmospheric refraction on the electromagnetic wave propagation path. Second, by using the augmented state vector with the target state and radar bias, a dynamic equation and measurement equation under the IMM framework are obtained. Last, the IMM-UKF estimator is utilized to obtain the target state and radar bias simultaneously. The numerical simulations show that the accuracy of the bias estimation together with the target states estimation can be improved via the proposed radar bias model.
Parameter Estimation Method of Mixture Distribution for Construction Machinery
Authors: Zhai Xinting , Wang Jixin , Chen Jinshi
Published: September 2018

Due to the harsh working environment of the construction machinery, a simple distribution cannot be used to approximate the shape of the rainflow matrix. In this paper, the Weibull-normal (W-n) mixture distribution is used. The lowest Akaike information criterion (AIC) value is employed to determine the components number of the mixture. A parameter estimation method based on the idea of optimization is proposed. The method estimates parameters of the mixture by maximizing the log likelihood function (LLF) using an intelligent optimization algorithm (IOA), genetic algorithm (GA). To verify the performance of the proposed method, one of the already existing methods is applied in the simulation study and the practical case study. The fitting effects of the fitted distributions are compared by calculating the AIC and chi-square (χ2) value. It can be concluded that the proposed method is feasible and effective for parameter estimation of the mixture distribution.
A Numerical Method for Solving Elliptic Interface Problems Using Petrov-Galerkin Formulation with Adaptive Refinement
Authors: Wang Liqun , Hou Songming , Shi Liwei
Published: September 2018

Elliptic interface problems have wide applications in engineering and science. Non-body-fitted grid has the advantage of saving the cost of mesh generation. In this paper, we propose a Petrov-Galerkin formulation using non-body-fitted grid for solving elliptic interface problems. In this method, adaptive mesh refinement is employed for cells with large errors. The new mesh still has all triangles being right triangles of the same shape. Numerical experiments show side-by-side comparison that to obtain the same accuracy, our new method has much less overall CPU time compared with the previous method even with some cost on mesh generation.
Antibacterial and Antibiotic-Potentiating Activities of Thirteen Cameroonian Edible Plants against Gram-Negative Resistant Phenotypes
Authors: Nayim Paul , Mbaveng Armelle T. , Wamba Brice E. N. , Fankam Aimé G. , Dzotam Joachim K. , Kuete Victor
Published: September 2018

This work was designed to investigate the antibacterial activities of methanol extracts from thirteen Cameroonian edible plants and their antibiotic-potentiating effects against Gram-negative multidrug-resistant (MDR) phenotypes. The broth microdilution method was used to evaluate the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of the extracts, as well as their antibiotic-potentiating activities. The phytochemical screening of the extracts was carried out according to the standard methods. The results of phytochemical tests revealed the presence of sterols, polyphenols, and tannins in most of the tested extracts, with the other classes of secondary metabolites being selectively distributed. Tested extracts showed variable antibacterial activities with MIC values ranging from 64 to 1024 μg/mL. However, some extracts were significantly active against certain bacterial strains: seeds extract of Theobroma cacao (64 μg/mL) against Escherichia coli AG100Atet and Klebsiella pneumoniae K24, and the bark extract of Uapaca guineensis against E. coli ATCC 8739. The leaves extract of T. cacao displayed the best MBC values (256 μg/mL) against E. aerogenes EA27. Some tested extracts included extracts from the leaves of T. cacao and P. vulgaris, and the seeds of D. edulis and barks A. indica has selectively improved (2- to 64-fold) the antibacterial activities of some of the tested antibiotics, chloramphenicol (CHL), tetracycline (TET), kanamycin (KAN), streptomycin (STR), and erythromycin (ERY), against more than 70% of tested MDR bacteria. The findings of this work showed that tested plant extracts and particularly those from T. cacao and Phaseolus vulgaris can be used alone or in combination with conventional antibiotics in the treatment of infections involving multiresistant bacteria.
Robust Preview Control for a Class of Uncertain Discrete-Time Lipschitz Nonlinear Systems
Authors: Yu Xiao , Liao Fucheng , Deng Jiamei
Published: September 2018

This paper considers the design of the robust preview controller for a class of uncertain discrete-time Lipschitz nonlinear systems. According to the preview control theory, an augmented error system including the tracking error and the known future information on the reference signal is constructed. To avoid static error, a discrete integrator is introduced. Using the linear matrix inequality (LMI) approach, a state feedback controller is developed to guarantee that the closed-loop system of the augmented error system is asymptotically stable with H∞ performance. Based on this, the robust preview tracking controller of the original system is obtained. Finally, two numerical examples are included to show the effectiveness of the proposed controller.
Moxibustion‐Simulating Bipolar Radiofrequency Suppresses Weight Gain and Induces Adipose Tissue Browning via Activation of UCP1 and FGF21 in a Mouse Model of Diet‐Induced Obesity
Authors: Koh Young Jun , Lee Ju-Hee , Park Sung Yun
Published: September 2018

Background. Obesity is a pathological condition associated with various diseases including diabetes, stroke, arthritis, infertility, and heart disease. Moxibustion is widely used to prevent and manage obesity in traditional Asian medicine. We tested our hypothesis that moxibustion‐simulating bipolar radiofrequency (M‐RF) can suppress total body and white adipose tissue (WAT) weight gain via induction of WAT browning in a mouse model of diet‐induced obesity (DIO). Methods. We designed an M‐RF device that could accurately adjust the depth and temperature at which heat stimulation was administered into the abdomen of DIO mice. High‐fat‐fed male C57BL/6 mice were treated with the M‐RF device every two or three days for three weeks. We then harvested WAT and serum from the mice and measured total body and WAT weight, size of adipocytes, mitochondrial contents, features of the dead adipocyte environment, and levels of uncoupling protein 1 (UCP1) and fibroblast growth factor 21 (FGF21). Results. Heat stimulation by M‐RF in DIO mice resulted in precise temperature adjustment in the mice abdomen, with variance less than 1°C. Additionally, M‐RF stimulation inhibited body and WAT weight gain, resulting in increased formation of beige adipocytes, increased mitochondrial content, and decreased formation of dead adipocytes in WAT. Moreover, treatment of M‐RF induced expression of UCP1 and FGF21 in serum and/or epididymal WATs in DIO mice. Conclusion. Heat stimulation by M‐RF treatment induced upregulation of UCP1 and FGF21 expression in serum and/or WATs, which was correlated with reduced total body and WAT weight gain in DIO mice.
Adaptive Backstepping Fuzzy Neural Network Fractional‐Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller
Authors: Fei Juntao , Liang Xiao
Published: September 2018

An adaptive fractional‐order nonsingular terminal sliding mode controller for a microgyroscope is presented with uncertainties and external disturbances using a fuzzy neural network compensator based on a backstepping technique. First, the dynamic of the microgyroscope is transformed into an analogical cascade system to guarantee the application of a backstepping design. Then, a fractional‐order nonsingular terminal sliding mode surface is designed which provides an additional degree of freedom, higher precision, and finite convergence without a singularity problem. The proposed control scheme requires no prior knowledge of the unknown dynamics of the microgyroscope system since the fuzzy neural network is utilized to approximate the upper bound of the lumped uncertainties and adaptive algorithms are derived to allow online adjustment of the unknown system parameters. The chattering phenomenon can be reduced simultaneously by the fuzzy neural network compensator. The stability and finite time convergence of the system can be established by the Lyapunov stability theorem. Finally, simulation results verify the effectiveness of the proposed controller and the comparison of root mean square error between different fractional orders and integer order is given to signify the high precision tracking performance of the proposed control scheme.
Parameters Influencing PET Imaging Features: A Phantom Study with Irregular and Heterogeneous Synthetic Lesions
Authors: Gallivanone Francesca , Interlenghi Matteo , D’Ambrosio Daniela , Trifirò Giuseppe , Castiglioni Isabella
Published: September 2018

Aim. To evaluate reproducibility and stability of radiomic features as effects of the use of different volume segmentation methods and reconstruction settings. The potential of radiomics in really capturing the presence of heterogeneous tumor uptake and irregular shape was also investigated. Materials and Methods. An anthropomorphic phantom miming real clinical situations including synthetic lesions with irregular shape and nonuniform radiotracer uptake was used. 18F-FDG PET/CT measurements of the phantom were performed including 38 lesions of different shape, size, lesion-to-background ratio, and radiotracer uptake distribution. Different reconstruction parameters and segmentation methods were considered. COVs were calculated to quantify feature variations over the different reconstruction settings. Friedman test was applied to the values of the radiomic features obtained for the considered segmentation approaches. Two sets of test-retest measurement were acquired and the pairwise intraclass correlation coefficient was calculated. Fifty-eight morphological and statistical features were extracted from the segmented lesion volumes. A Mann–Whitney test was used to evaluate significant differences among each feature when calculated from heterogeneous versus homogeneous uptake. The significance of each radiomic feature in terms of capturing heterogeneity was evaluated also by testing correlation with gold standard indexes of heterogeneity and sphericity. Results. The choice of the segmentation method has a strong impact on the stability of radiomic features (less than 20% can be considered stable features). Reconstruction affects the estimate of radiomic features (only 26% are stable). Thirty-one radiomic features (53%) resulted to be reproducible, 11 of them are able to discriminate heterogeneity. Among these, we found a subset of 3 radiomic features strongly correlated with GS heterogeneity index that can be suggested as good features for retrospective evaluations.
Bladder Cancer–Specific Nuclear Matrix Proteins-4 May Be a Potential Biomarker for Non-Muscle-Invasive Bladder Cancer Detection
Authors: Wang Zhi-Yong , Li Hong-Yang , Wang Hao , Chi Qiang , Liu Ying , Li Xiu-Ming
Published: September 2018

Aims. Bladder cancer–specific nuclear matrix protein-4 (BLCA-4) is a protein expressed mainly in bladder cancer tissues. Therefore, the aim of this study was to investigate its assisting diagnostic potential in non-muscle-invasive bladder cancer (NMIBC). Methods. Twenty patients with NMIBC, 20 with benign prostatic hyperplasia (BPH), and 20 normal controls were included in this study. Blood and urine samples were collected from all patients. Moreover, cancer foci and adjacent tissue samples were collected from NMIBC patients, and normal bladder tissue samples were collected from patients with BPH. A competitive enzyme-linked immunosorbent assay was used to determine the BLCA-4 level in serum and urine, and immunohistochemistry was used to examine BLCA-4 expression in bladder cancer, adjacent, and normal tissues. Results. Median urinary BLCA-4 levels in the NMIBC, BPH, and normal control groups were 0.759 ng/mL, 0.309 ng/mL, and 0.171 ng/mL, respectively. Urinary BLCA-4 level was significantly higher in the NMIBC group than in the other 2 groups (P<0.01); meanwhile, the BPH group was higher than the normal control group (P<0.05). Median serum BLCA-4 levels in the NMIBC, BPH, and normal control groups were 5.680 ng/mL, 5.928 ng/mL, and 5.473 ng/mL, respectively, showing no significant difference among groups (P>0.05). Conclusion. As a new marker of bladder cancer, urinary BLCA-4 level detection might apply for clinical diagnosis or postoperative monitoring for NMIBC.
A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography
Authors: Dong Suyu , Luo Gongning , Wang Kuanquan , Cao Shaodong , Li Qince , Zhang Henggui
Published: September 2018

Segmentation of the left ventricle (LV) from three-dimensional echocardiography (3DE) plays a key role in the clinical diagnosis of the LV function. In this work, we proposed a new automatic method for the segmentation of LV, based on the fully convolutional networks (FCN) and deformable model. This method implemented a coarse-to-fine framework. Firstly, a new deep fusion network based on feature fusion and transfer learning, combining the residual modules, was proposed to achieve coarse segmentation of LV on 3DE. Secondly, we proposed a method of geometrical model initialization for a deformable model based on the results of coarse segmentation. Thirdly, the deformable model was implemented to further optimize the segmentation results with a regularization item to avoid the leakage between left atria and left ventricle to achieve the goal of fine segmentation of LV. Numerical experiments have demonstrated that the proposed method outperforms the state-of-the-art methods on the challenging CETUS benchmark in the segmentation accuracy and has a potential for practical applications.
An Automated Approach for Epilepsy Detection Based on Tunable Q-Wavelet and Firefly Feature Selection Algorithm
Authors: Sharaf Ahmed I. , El-Soud Mohamed Abu , El-Henawy Ibrahim M.
Published: September 2018

Detection of epileptic seizures using an electroencephalogram (EEG) signals is a challenging task that requires a high level of skilled neurophysiologists. Therefore, computer-aided detection provides an asset to the neurophysiologist in interpreting the EEG. This paper introduces a novel approach to recognize and classify the epileptic seizure and seizure-free EEG signals automatically by an intelligent computer-aided method. Moreover, the prediction of the preictal phase of the epilepsy is proposed to assist the neurophysiologist in the clinic. The proposed method presents two perspectives for the EEG signal processing to detect and classify the seizures and seizure-free signals. The first perspectives consider the EEG signal as a nonlinear time series. A tunable Q-wavelet is applied to decompose the signal into smaller segments called subbands. Then a chaotic, statistical, and power spectrum features sets are extracted from each subband. The second perspectives process the EEG signal as an image; hence the gray-level co-occurrence matrix is determined from the image to obtain the textures of contrast, correlation, energy, and homogeneity. Due to a large number of features obtained, a feature selection algorithm based on firefly optimization was applied. The firefly optimization reduces the original set of features and generates a reduced compact set. A random forest classifier is trained for the classification and prediction of the seizures and seizure-free signals. Afterward, a dataset from the University of Bonn, Germany, is used for benchmarking and evaluation. The proposed approach provided a significant result compared with other recent work regarding accuracy, recall, specificity, F-measure, and Matthew’s correlation coefficient.
Aggressive Metastatic GATA3-Positive Sarcomatoid Carcinoma with Rapid Progression and Invasion of the Liver
Authors: Shaukat Irfan , Padgett Charles , Inayat Maimoona , Höti Naseruddin , Mustafa Sadaf
Published: September 2018

Objective. GATA3-positive sarcomatoid carcinoma has never been documented in the past. It is a case of aggressive tumor, positive for GATA3, which should be further studied for its prognostic and therapeutic significance.
Dynamics, Chaos Control, and Synchronization in a Fractional‐Order Samardzija‐Greller Population System with Order Lying in (0, 2)
Authors: Al-khedhairi A. , Askar S. S. , Matouk A. E. , Elsadany A. , Ghazel M.
Published: September 2018

This paper demonstrates dynamics, chaos control, and synchronization in Samardzija‐Greller population model with fractional order between zero and two. The fractional‐order case is shown to exhibit rich variety of nonlinear dynamics. Lyapunov exponents are calculated to confirm the existence of wide range of chaotic dynamics in this system. Chaos control in this model is achieved via a novel linear control technique with the fractional order lying in (1, 2). Moreover, a linear feedback control method is used to control the fractional‐order model to its steady states when 0 < α < 2. In addition, the obtained results illustrate the role of fractional parameter on controlling chaos in this model. Furthermore, nonlinear feedback synchronization scheme is also employed to illustrate that the fractional parameter has a stabilizing role on the synchronization process in this system. The analytical results are confirmed by numerical simulations.
Supporting Continuous Skyline Queries in Dynamically Weighted Road Networks
Authors: Tang Yingfeng , Chen Shiping
Published: September 2018

The paper focuses on the design of an optimum method for handling the continuous skyline query problem in road networks. Existing studies on processing the continuous skyline query focus exclusively on static road networks, which are limited because the state of roads in road networks is constantly changing. Therefore, to apply current methods for dynamically weighted road networks, a distributed skyline query method based on a grid partition method has been proposed in this paper. The method adopts the concepts of a distributed computing framework and road network preprocessing computations in which multiple parallel computing nodes are allocated and organized in grids. Using this approach, the road network map is simplified to a hub graph with much smaller scale such that the query load of the central node can be significantly reduced. The theoretical analysis and experimental results both indicate that, by using the proposed method, the system can achieve quick response time for users as well as a good balance between response times and accuracy. Therefore, it can be concluded that using the proposed method is beneficial for handling continuous skyline queries in a dynamically weighted road network.
A New Erosion Model for Wind‐Induced Structural Vibrations
Authors: Yan Keqin , Zhang Yi , Cheng Tao
Published: September 2018

In recent years, computational fluid dynamics (CFD) method has been widely utilized in simulating wind‐induced snow drifting. In the simulating process, the erosion flux is the main controlling factor which can be calculated by the product of erosion coefficient and the differences between the flow stress and threshold stress. The erosion coefficient is often adopted as an empirical constant which is believed not to change with time and space. However, in reality, we do need to consider the influences of snow diameter, density, and wind speed on the erosion coefficient. In this technical note, a function of air density, sow particle density, snow particle radius, and snow particle strength bond is proposed for the erosion coefficient. Based on an experiment study, the effects of these parameters in erosion coefficient is analyzed and discussed. The probability distribution and value range of erosion coefficient are also presented in this technical note. The applicability of this approach is also demonstrated in a numerical study for predicting the snow distributions around a cube structure. The randomness of the structural vibrations is studied with details.
Free Testosterone Reflects Metabolic as well as Ovarian Disturbances in Subfertile Oligomenorrheic Women
Authors: Antonio L. , Pauwels S. , Laurent M. R. , Vanschoubroeck D. , Jans I. , Billen J. , Claessens F. , Decallonne B. , De Neubourg Diane , Vermeersch P. , Vanderschueren D.
Published: September 2018

Background. Diagnosing polycystic ovary syndrome (PCOS) is based on ovulatory dysfunction, ovarian ultrasound data, and androgen excess. Total testosterone is frequently used to identify androgen excess, but testosterone is mainly bound to sex hormone-binding globulin (SHBG) and albumin. Only 1-2% of nonprotein-bound testosterone (so-called free testosterone) is biologically active and responsible for androgen action. Moreover, automated immunoassays which are frequently used for female testosterone measurements are inaccurate.Objective. To assess the clinical usefulness of liquid chromatography-tandem mass spectrometry measured testosterone and calculated free testosterone in subfertile women attending a fertility clinic with oligomenorrhea and suspected PCOS.Methods.Hormonal and metabolic parameters were evaluated, and ovarian ultrasound was performed. Total testosterone was measured by liquid chromatography-tandem mass spectrometry. Free testosterone was calculated from total testosterone and SHBG.Results. Sixty-six women were included in the study. Total testosterone was associated with ovarian volume and antral follicle count but not with metabolic parameters. However, SHBG and calculated free testosterone were associated with both ovarian ultrasound and metabolic parameters, such as BMI and insulin resistance.Conclusions. Assessing SHBG and free testosterone is important in evaluating androgen excess in subfertile women with ovulatory dysfunction and suspected PCOS, as it reflects both ovarian and metabolic disturbances.
A Characterization of the Existence of a Fundamental Bounded Resolution for the Space Cc(X) in Terms of X
Authors: Ferrando Juan Carlos
Published: September 2018

We characterize in terms of the topology of a Tychonoff space X the existence of a bounded resolution for CcX that swallows the bounded sets, where CcX is the space of real-valued continuous functions on X equipped with the compact-open topology.
Genome-Wide DNA Methylation Analysis during Osteogenic Differentiation of Human Bone Marrow Mesenchymal Stem Cells
Authors: Cao Yangyang , Yang Haoqing , Jin Luyuan , Du Juan , Fan Zhipeng
Published: September 2018

Bone marrow mesenchymal stem cells (BMSCs) nowadays are regarded as promising candidates in cell-based therapy for the regeneration of damaged bone tissues that are either incurable or intractable due to the insufficiency of current therapies. Recent studies suggest that BMSCs differentiate into osteoblasts, and that this differentiation is regulated by some specific patterns of epigenetic modifications, such as DNA methylation. However, the potential role of DNA methylation modification in BMSC osteogenic differentiation is unclear. In this study, we performed a genome-wide study of DNA methylation between the noninduced and induced osteogenic differentiation of BMSCs at day 7. We found that the majority of cytosines in a CpG context were methylated in induced BMSCs. Our results also revealed that, along with the induced osteogenic differentiation in BMSCs, the average genomic methylation levels and CpG methylation in transcriptional factor regions (TFs) were increased, the CpG methylation level of various genomic elements was mainly in the medium-high methylation section, and CpG methylation levels in the repeat element had highly methylated levels. The GO analysis of differentially methylated region- (DMR-) associated genes (DMGs) showed that GO terms, including cytoskeletal protein binding (included in Molecular Function GO terms), skeletal development (included in Biological Process GO terms), mesenchymal cell differentiation (included in Biological Process GO terms), and stem cell differentiation (included in Biological Process), were enriched in the hypermethylated DMGs. Then, the KEGG analysis results showed that the WNT pathway, inositol phosphate metabolism pathway, and cocaine addiction pathway were more correlative with the DMRs during the induced osteogenic differentiation in BMSCs. In conclusion, this study revealed the difference of methylated levels during the noninduced and induced osteogenic differentiation of BMSCs and provided useful information for future works to characterize the important function of epigenetic mechanisms on BMSCs’ differentiation.
Condition-Based Predictive Order Model for a Mechanical Component following Inverse Gaussian Degradation Process
Authors: Wang Cheng , Xu Jianxin , Wang Hongjun , Zhang Zhenming
Published: September 2018

An efficient condition-based predictive spare ordering approach is the key to guarantee safe operation, improve service quality, and reduce maintenance costs under a predefined lower availability threshold. In this paper, we propose a condition-based predictive order model (CBPO) for a mechanical component, whose degradation path is modeled as inverse Gaussian (IG) process with covariate effect. The CBPO is dependent on the remaining useful life (RUL), random lead-time, speed-up lead-time degree, and availability threshold. RUL estimation is obtained through the IG degradation process at each inspection time. Both regular lead-time and expedited lead-time considered in RUL-based spare ordering policy can be cost-effective and reduce losses caused by unexpected failure. Speed-up lead-time can meet the urgent needs for spare parts on site. The decision variable of CBPO is the spare ordering time. Based on the CBPO under the lower availability threshold constraint, the objective of this study is to determine the optimal spare ordering time such that the expected cost rate is minimized. Finally, a case study of the mechanical spindle is presented to illustrate the proposed model and sensitivity analysis on critical parameters is performed.
Evaluation of Novel Prostate-Specific Membrane Antigen-Targeted Near-Infrared Imaging Agent for Fluorescence-Guided Surgery of Prostate Cancer
Authors: Kularatne Sumith A. , Thomas Mini , Myers Carrie H. , Gagare Pravin , Kanduluru Ananda K. , Crian Christa J. , Cichocki Brandy N.
Published: September 2018

Purpose:

The ability to locate and remove all malignant lesions during radical prostatectomy leads not only to prevent biochemical recurrence (BCR) and possible side effects but also to improve the life expectancy of patients with prostate cancer. Fluorescence-guided surgery (FGS) has emerged as a technique that uses fluorescence to highlight cancerous cells and guide surgeons to resect tumors in real time. Thus, development of tumor-specific near-infrared (NIR) agents that target biomarkers solely expressed on prostate cancer cells will enable to assess negative tumor margins and affected lymph nodes.

Experimental Design:

Because PSMA is overexpressed in prostate cancer cells in >90% of the prostate cancer patient population, a prostate-specific membrane antigen (PSMA)-targeted NIR agent (OTL78) was designed and synthesized. Optical properties, in vitro and in vivo specificity, tumor-to-background ratio (TBR), accomplishment of negative surgical tumor margins using FGS, pharmacokinetics (PKs) properties, and preclinical toxicology of OTL78 were then evaluated in requisite models.

Results:

OTL78 binds to PSMA-expressing cells with high affinity, concentrates selectively to PSMA-positive cancer tissues, and clears rapidly from healthy tissues with a half-time of 17 minutes. It also exhibits an excellent TBR (5:1) as well as safety profile in animals.

Conclusions:

OTL78 is an excellent tumor-specific NIR agent for use in fluorescence-guided radical prostatectomy and FGS of other cancers.
A First-in-Human Study of Novel Cereblon Modulator Avadomide (CC-122) in Advanced Malignancies
Authors: Rasco Drew W. , Papadopoulos Kyriakos P. , Pourdehnad Michael , Gandhi Anita K. , Hagner Patrick R. , Li Yan , Wei Xin , Chopra Rajesh , Hege Kristen , DiMartino Jorge , Shih Kent
Published: September 2018

Purpose:

Avadomide is a novel, small-molecule therapeutic agent that modulates cereblon E3 ligase activity and exhibits potent antitumor and immunomodulatory activities. This first-in-human phase I study (NCT01421524) evaluated the safety and clinical activity of avadomide in patients with advanced solid tumors, non-Hodgkin lymphoma (NHL), and multiple myeloma.

Patients and Methods:

Thirty-four patients were treated with avadomide in 7 dose-escalation cohorts using a 3 + 3 design (0.5–3.5 mg, 28-day continuous dosing cycles). The primary objectives were to determine the dose-limiting toxicity (DLT), nontolerated dose (NTD), maximum tolerated dose (MTD), recommended phase II dose, and pharmacokinetics of avadomide. The secondary objective was to determine preliminary avadomide efficacy. Exploratory objectives included evaluation of pharmacodynamic effects of avadomide.

Results:

DLTs were reported in 2 patients, and grade ≥3 treatment-emergent adverse events (TEAEs) occurred in 14 patients (41%). The most common TEAEs (≥15%) were fatigue, neutropenia, and diarrhea. The NTD and MTD were 3.5 and 3.0 mg, respectively. Of 5 patients with NHL, 1 achieved a complete response, and 2 had partial responses. Although no objective responses were observed in patients with solid tumors, 5 of 6 patients with brain cancer experienced nonprogression of ≥6 months. A dose-dependent relationship between Aiolos degradation in peripheral B and T cells occurred within 5 hours of the first dose of avadomide administered, starting at 0.5 mg.

Conclusions:

Avadomide monotherapy demonstrated acceptable safety and favorable pharmacokinetics in patients with solid tumors, NHL, and multiple myeloma. In addition, 3 objective responses were observed in NHL.
Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer
Authors: Corredor Germán , Wang Xiangxue , Zhou Yu , Lu Cheng , Fu Pingfu , Syrigos Konstantinos , Rimm David L. , Yang Michael , Romero Eduardo , Schalper Kurt A. , Velcheti Vamsidhar , Madabhushi Anant
Published: September 2018

Purpose:

The presence of a high degree of tumor-infiltrating lymphocytes (TIL) has been proven to be associated with outcome in patients with non–small cell lung cancer (NSCLC). However, recent evidence indicates that tissue architecture is also prognostic of disease-specific survival and recurrence. We show a set of descriptors (spatial TIL, SpaTIL) that capture density, and spatial colocalization of TILs and tumor cells across digital images that can predict likelihood of recurrence in early-stage NSCLC.

Experimental Design:

The association between recurrence in early-stage NSCLC and SpaTIL features was explored on 301 patients across four different cohorts. Cohort D1 (n = 70) was used to identify the most prognostic SpaTIL features and to train a classifier to predict the likelihood of recurrence. The classifier performance was evaluated in cohorts D2 (n = 119), D3 (n = 112), and D4 (n = 112). Two pathologists graded each sample of D1 and D2; intraobserver agreement and association between manual grading and likelihood of recurrence were analyzed.

Results:

SpaTIL was associated with likelihood of recurrence in all test sets (log-rank P < 0.02). A multivariate Cox proportional hazards analysis revealed an HR of 3.08 (95% confidence interval, 2.1–4.5, P = 7.3 × 10−5). In contrast, agreement among expert pathologists using tumor grade was moderate (Kappa = 0.5), and the manual TIL grading was only prognostic for one reader in D2 (P = 8.0 × 10−3).

Conclusions:

A set of features related to density and spatial architecture of TILs was found to be associated with a likelihood of recurrence of early-stage NSCLC. This information could potentially be used for helping in treatment planning and management of early-stage NSCLC.

See related commentary by Peled et al., p. 1449
Tretinoin Loaded Nanoemulsion for Acne Vulgaris: Fabrication, Physicochemical and Clinical Efficacy Assessments
Authors: Sabouri Mahsa , Samadi Aniseh , Ahmad Nasrollahi Saman , Farboud Effat Sadat , Mirrahimi Bahareh , Hassanzadeh Hournaz , Nassiri Kashani Mansour , Dinarvand Rassoul , Firooz Alireza
Published: September 2018

Background and Aim: Acne vulgaris is a common inflammatory skin condition which is treated using Tretinoin (TRE), a widely used retinoid. Nano emulations (NEs) are colloidal nano-sized particles that enhance the therapeutic efficacy of TRE and minimize adverse effects. This study is aimed at developing a TRE-loaded NE (NE-TRE) and at assessing the therapeutic effects of the formulation in acne vulgaris lesions, compared to conventional 0.05% TRE emulsion. Method: The high energy emulsification method was used to make NE-TRE. After obtaining stable NE, particle characterization and physicochemical properties were evaluated under accelerated conditions. Conducting a clinical study, we compared the therapeutic effects of NE-TRE and 0.05% TRE emulsion by comparing the number of acne lesions and porphyrin production in both sides of the face. Results and Conclusion: We successfully developed stable nanoparticles. It was a stable oil-in-water emulsion with particle size of about 150 nm, and containing circular and separated particles. In a pilot clinical study, the number of acne lesions as well as the size and intensity of porphyrin production significantly reduced after topical application of NE-TRE. This formula shows proper efficiency and good loading capacity of TRE in the drug delivery system.
Does Maternal Body Mass Index Affect the Quantity of Circulating Fetal Cells Available to Use for Cell-Based Noninvasive Prenatal Test in High-Risk Pregnancies?
Authors: Kruckow Sofie , Schelde Palle , Hatt Lotte , Ravn Katarina , Petersen Olav Bjørn , Uldbjerg Niels , Vogel Ida , Singh Ripudaman
Published: September 2018

We present the first study that investigates the effect of maternal body mass index (BMI) on the quantity of circulating fetal cells available to use in cell-based noninvasive prenatal test (cbNIPT). cbNIPT has been proposed as a superior alternative to noninvasive prenatal test from cell-free fetal DNA. Kølvraa et al. [Prenat Diagn. 2016 Dec; 36(12): 1127–34] established that cbNIPT can be performed on as few as one fetal cell, and Vestergaard et al. [Prenat Diagn. 2017 Nov; 37(11): 1120–4] demonstrated that these fetal trophoblast cells could be used successfully in cbNIPT to detect chromosomal and sub-chromosomal abnormalities. This study on 91 pregnant women with high-risk pregnancies suggests that cbNIPT should not be hampered by an increased BMI because every pregnancy, irrespective of the BMI, has rendered fetal cells for downstream genetic analysis. The mean number of fetal cells per sample was 12.6, with a range of 1–43 cells in one sample. ANOVA showed that increasing maternal BMI tends to decrease the number of fetal cells, but not significantly.
Optimization of Canine Placenta Decellularization: An Alternative Source of Biological Scaffolds for Regenerative Medicine
Authors: Matias Gustavo de Sá Schiavo , Rigoglio Nathia Nathaly , Carreira Ana Claudia Oliveira , Romagnolli Patricia , Barreto Rodrigo da Silva Nunes , Mess Andrea Maria , Miglino Maria Angelica , Fratini Paula
Published: September 2018

Due to the scarcity of tissues and organs for transplantation, the demand for bioengineered tissues is increasing with the advancement of technologies and new treatments in human and animal regenerative medicine. Thus, decellularized placental extracellular matrix (ECM) has emerged as a new tool for the production of biological scaffolds for subsequent recellularization and implantation for recovery of injured areas or even for replacement of organ and tissue fractions. To be classified as an ideal biological scaffold, the ECM must be acellular and preserve its proteins and physical features to be useful for cellular adhesion. In this context, we developed a process of decellularization of canine placentas with 35 and 40 days of gestation using dodecyl sulfate sodium under immersion and agitation in sterile conditions. Before use of this scaffold in recellularization processes, the decellularization efficiency needs to be confirmed by the absence of cellular content and an irrelevant amount of reminiscent DNA. Both vasculature architecture and ECM proteins, such as collagen types I, III, and IV, laminin, and fibronectin, were preserved with our method. In this way, we established a new biological scaffold model that could be used for recellularization in regenerative medicine of tissues.
Late-Life Depression versus Amnestic Mild Cognitive Impairment: Alzheimer’s Disease Incidence in 4 Years of Follow-Up
Authors: Lauriola Michele , Mangiacotti Antonio , D’Onofrio Grazia , Cascavilla Leandro , Paris Francesco , Ciccone Filomena , Greco Monica , Paroni Giulia , Seripa Davide , Greco Antonio
Published: September 2018

Background/Aim: The aim of the study was to evaluate the prognostic power of late-life depression (LLD) compared with amnestic mild cognitive impairment (aMCI) for the onset of Alzheimer’s disease (AD) within 4 years of follow-up. Methods: We estimated the incidence of AD in 60 patients presenting with aMCI, 115 patients suffering of LLD treated with antidepressants with good compliance, and 66 healthy control (HC) patients, followed for 4 years. Results: The risk to develop AD, within 4 years, was 68.33% for aMCI and 49.57% for LLD. In AD patients 5.60% deteriorated without depression, and 72.20% deteriorated with depression after 4 years of follow-up (p < 0.0001). No HC patients deteriorated to AD or any other dementia type. Conclusion: In our results, aMCI was the first predictive condition that increased the risk to develop AD. Depression is a potentially preventable medical condition across the lifespan and may be a modifiable risk factor.