bluuebunny/crossref_metadata_2025 huggingface dataset:
Starch and Plant Fiber Reinforced Biodegradable Composites with Open Cell Structures
Authors: Sun Xu , Cui Jin-Feng , Jia Xiu-Jie , Zhang Chuan-Wei , Li Fang-Yi , Li Jian-Feng , Li Jian-Yong , Chen Shuai , Xie Qi , Xu Jie
Published: June 2019

In order to figure out the effect of different starches on the properties of starch-based composites, new biodegradable composites with open cell structure were prepared through thermo-cavity foam molding using four different type starches (corn starch (CS), wheat starch (WS), potato
starch (PS), and sweet potato starch (SPS)) and sisal fibers as main raw materials. Mechanical properties of the biodegradable composites were tested. The order of tensile and compressive strength of the composites was as follows: SPS-based composite > CS-based composite > PS-based composite
> WS-based composite. Following X-ray diffraction, the infrared spectrum analysis, scanning electron microscopy, and viscosity test were employed to gain comprehensive views on the effect of the different starch microstructures on the properties of the biodegradable composites. X-ray diffraction
analysis showed that the crystalline index of the SPS and CS were lower than those of PS and WS. Amorphous starch more easily combined with the sisal fiber, which is the deep reason that the SPS-based composite had the best tensile strength. Moreover, the infrared spectrum analysis indicated
that SPS molecules demonstrated more hydroxyl groups than the others. The hydroxyl group in the SPS molecules formed more hydrogen bonds with the hydroxyl group in the sisal fibers. Scanning electron microscopy images showed that SPS bonded tightly with sisal fibers uniform open cell structure
in the biodegradable composites. The order of the viscosities of the different starch slurry was: WS slurry > PS slurry > CS slurry > SPS slurry. The lower the crystalline index of the starch, the larger the amorphous zone, the lower the viscosity of the starch slurry, and the better
the rheological properties are. In this case, the SPS and sisal fibers can combine well, and the SPS-based composites offer improved mechanical properties.
A Novel Amidase Signature Family Amidase from the Marine Actinomycete Salinispora arenicola CNS-205
Authors: Ma Yanling , Zhang Xinfeng , Chen Tianmei , Liu Fulai , Fang Shuting , Zeng Rong
Published: June 2019

We cloned a new gene from the amidase signature (AS) family, designated am , from the marine actinomycete Salinispora arenicola CNS-205. As indicated by bioinformatics analysis and site-directed mutagenesis, the AM (a gene encoding a putative amidase) protein belonged to the
AS family. AM was expressed, purified, and characterised in Escherichia coli BL21 (DE3), and the AM molecular mass was determined to be 51 kDa. The optimal temperature and pH were 40 °C and pH 8.0, respectively. AM exhibited a wide substrate spectrum and showed amidase, aryl acylamidase,
and acyl transferase activities. AM had high activity towards aromatic and aliphatic amides. The AM substrate specificity for anilides was very narrow, and only propanil could be used as an effective substrate. The extensive substrate range of AM indicates it may have broad potential applications
in biosynthetic processes and biodegradation.
Novel Wall Paint for Decorative Style of Retro Rammed-Earth Wall Based on Dry Hanging
Authors: He Ke , Liu Yong , He Yanting
Published: June 2019

Owing to its unique ornamental style, the decorative retro rammed-earth wall style has attracted widespread interest in recent years. With this motivation, a novel multi-coated rammed-earth paint using dry hanging has been studied. This paint could overcome the limitations of surface
material shedding and low strength in an extreme external environment. It has the advantages of low construction cost, simple production, low embodied energy, recyclability, and excellent performance. The alkali-resistance test of the paint was carried out in a high-concentration alkaline
solution. The paint demonstrated insignificant performance change after 96 h. It has also been determined that the weather resistance of the sample does not display any evidence of chalking after 10 cycles of freezing and heating experiments. Rain and sun exposure are considered extremely
important factors in durability of paint and were also tested for in the climatic chamber. The environmental parameters in the chamber were modeled based on the environment of southern China. Later, the coating product was tested according to the Chinese national standard of JG-T24-2000 (synthetic
resin emulsion sand wall structure), demonstrating excellent performance. Thus, the innovative products of earth wall paint discussed in this study have the potential to meet the needs of the market.
Influence of Different Additives on the Slagging of Corn Straw and Design of Compound Additives
Authors: Si Hongyu , Ren Wei , Sun Zichun , Hua Dongliang , Li Yan , Zhang Xiaodong , Mei Ning , Chen Lei , Sun Laizhi , Yang Shuangxia , Xie Xinping , Liang Xiaohui
Published: June 2019

Biomass is regarded as a desirable substitute for fossil fuel worldwide. However, serious slagging and corrosion occur during its combustion, hindering its application in large-scale energy production. In the present study, we aimed to investigate the effects of different additives,
such as MgCO3, CaCO3, Al2O3 and MgCO3–CaCO3–Al2O3, on the slagging characteristics of corn straw (CS). Our data showed that the effect of single additives on sintering intensity index (SII)
was ranked in an order as MgCO3 > CaCO3 > Al2O3, and such effect on softening temperature (ST) was ranked as Al2O3 > MgCO3 > CaCO3. The existence of SiO2, potassium salt and aluminum
silicate in CS was the primary factor causing slagging due to the formation of low-melting eutectics. The blend of additives initiated the occurrence of MgO, Ca2SiO4, Ca2Al2SiO7, KAlSiO4 and other compounds with high melting
point, which was favorable for slagging mitigation. Orthogonal design was applied to study the effects of compound additives on SII, K content in ash, combustion performance of CS and HCl emission, and an optimal combination of additives consisted of 2.0 wt.% MgCO3, 2.0 wt.% CaCO3
and 1.5 wt.% Al2O3 .
High Purity Chlorine Dioxide Generation Based on the Mixed Reductant: From the Laboratory to Industry
Authors: Xu Cuisheng , Hao Ningke , Zhan Lei , Wang Shiwei , Yao Shuangquan , Nie Shuangxi , Wang Shuangfei
Published: June 2019

Methanol was used as reducing agent in the chlorine dioxide generation technology, and sodium chlorate was reduced to form chlorine dioxide under acidic conditions. The side reaction during the preparation process would produce chlorine, which results in a high content of chlorine in
the product and leads to an increase in the amount of AOX formation during pulp bleaching. In this work, the chlorine dioxide generation technology based on the mixed reductant was developed. On the basis system based on the methanol method, a high-purity chlorine dioxide for pulp bleaching
was successfully produced using a vertical generator by adding a mixed reducing agent that contain hydrogen peroxide and sodium chloride. This invention can not only solve the problems of low conversion rate of sodium chlorate and high content of chlorine in the traditional methanol reduction
method, but also reduces the production cost. The chlorine content in the chlorine dioxide solution is reduced to less than 0.2 g/L.
A Robust Method for MR Image Segmentation and Multiple Scleroses Detection
Authors: Zouaoui H. , Moussaoui A. , Oussalah M. , Taleb-Ahmed A.
Published: June 2019

In the present article, we propose a new approach for the segmentation of the MR images of the Multiple Sclerosis (MS). The Magnetic Resonance Imaging (MRI) allows the visualization of the brain and it is widely used in the diagnosis and the follow-up of the patients suffering from
MS. Aiming to automate a long and tedious process for the clinician, we propose the automatic segmentation of the MS lesions. Our algorithm of segmentation is composed of three stages: segmentation of the brain into regions using the algorithm Fuzzy Particle Swarm Optimization (FPSO) in order
to obtain the characterization of the different healthy tissues (White matter, grey matter and cerebrospinal fluid (CSF)) after the extraction of white matter (WM), the elimination of the atypical data (outliers) of the white matter by the algorithm Fuzzy C-Means (FCM), finally, the use of
a Mamdani-type fuzzy model to extract the MS lesions among all the absurd data.
An Efficient Implementation of a Census-Based Stereo Matching and Its Applications in Medical Imaging
Authors: Lai Xiaobo , Xu Xiaomei , Zhang Jinyan , Fang Ying , Huang Zihe
Published: June 2019

Compared to most conventional efficient stereo matching algorithms that based on NCC (Normalized Cross-Correlation) or SAD (Sum of Absolute Difference), stereo matching based on census transform is robust to radiometric distortion. Thus, in the paper we propose a census-based efficient
implementation stereo algorithm for medical imaging. Firstly, census-based stereo matching is investigated, and its specific implementation process is analyzed in detail. Secondly, in order to simplify the calculation process and improve the efficiency, the moving window and memory organization
optimized techniques are used. The program runs on standard PC hardware utilizing various SSE2 instructions. Finally, stereo matching of four standard image pairs on the Middlebury image datasets and a paired cervical images obtained from clinical colposcope are implemented in an efficient
way. The experimental results on simulated and real medical images prove the effectiveness of the method for the computational cost.
Privacy Exposure Measure: A Privacy-Preserving Technique for Health-Related Web Search
Authors: Khan Rafiullah , Islam Muhammad Arshad , Ullah Mohib , Aleem Muhammad , Iqbal Muhammad Azhar
Published: June 2019

The increasing use of web search engines (WSEs) for searching healthcare information has resulted in a growing number of users posting personal health information online. A recent survey demonstrates that over 80% of patients use WSE to seek health information. However, WSE stores these
user's queries to analyze user behavior, result ranking, personalization, targeted advertisements, and other activities. Since health-related queries contain privacy-sensitive information that may infringe user's privacy. Therefore, privacy-preserving web search techniques such as anonymizing
networks, profile obfuscation, private information retrieval (PIR) protocols etc. are used to ensure the user's privacy. In this paper, we propose Privacy Exposure Measure (PEM), a technique that facilitates user to control his/her privacy exposure while using the PIR protocols. PEM assesses
the similarity between the user's profile and query before posting to WSE and assists the user in avoiding privacy exposure. The experiments demonstrate 37.2% difference between users' profile created through PEM-powered-PIR protocol and other usual users' profile. Moreover, PEM offers more
privacy to the user even in case of machine-learning attack.
Accommodate Data Loss in Monitoring Vital Signs Through Autoregressive Model
Authors: Khan Naeem , Khan Khushal , Khan Asfandyar , Alam Imtiaz , Khan Faheem Ullah , Khan Shafi Ullah , Ali Amjad
Published: June 2019

In this paper, the measurement of two vital signs including heartbeat and respiratory rate are discussed under two critical scenarios; namely subjection to noise and intermittent observations. Previously adopted scheme for finding the above mentioned vital signs was Fourier Transform
which couldn't handle non-stationary process. For a broader perspective, Wavelet Transform is employed in this paper which is equally applicable to stationary and non-stationary processes. In addition, the intermittent observation is a malfunction which may result in severe consequences in
measuring vital signs. In past, only noise-free data has been incorporated in tracing vital signs parameters. A Modified Robust Kalman Filter (MRKF) is designed to obtain optimum results in the presence of above two critical scenarios. Simulation results obtained on real data show that the
performance of MRKF produces similar vital signs as with clean and undistorted data.
EEG Signal Analysis for Automated Epilepsy Seizure Detection Using Wavelet Transform and Artificial Neural Network
Authors: Vani S. , Suresh G. R. , Balakumaran T. , Ashawise Cross T.
Published: June 2019

Electroencephalogram (EEG) measures electrical activity of the brain and proffers valuable insight of the brain dynamics. Accurate and careful analysis of EEG signal plays a prominent role in the diagnosis of brain diseases like epilepsy, brain tumor. EEG is the most significant method
used for epilepsy monitoring, diagnosis and rehabilitation. A patient-specific seizure detection model has been developed using Haar wavelet and Artificial Neural Network. HAAR Wavelet decomposition of multi-channel EEG with five scales is made and three frequency bands of EEG selected for
the consequent process. The conventional Haar wavelet transform (HWT) is replaced by a modified Haar wavelet transform whereas the number of multiplications and additions are reduced. The Haar wavelet reduces computational complexity from the existing Haar wavelet structure which consumes
only 1–3 ms based on the decomposition level to detect epilepsy.
A Study on Mobile Phone Addiction and Physical Pain Based on Characteristics of Mobile Phone Usage
Authors: Choi Young-Soon
Published: June 2019

This study is a descriptive correlation study to identify the characteristics of mobile phone usage, mobile phone addiction, and physical pain in university students and to identify the correlation between variables. The degree of addiction to the mobile phone was 32.10 points, and
pathological commitment is 1.86 points, living disorder 1.79 points, the loss control 2.19 points, compulsive symptoms 1.72 points. Subjects who experienced physical pain mobile phone use was 39.1%. Physical pain was lower in order of wrist, finger, neck, shoulder, and arm. There was a statistically
significant difference between mobile phone addicts and women, according to the average daily data usage time, the mobile phone addiction score of the group with high usage time was high. In the case of physical pain, it has been found that the use of mobile phones for a long period of time
due to loss of control among the mobile phone addiction causes the most physical pain. The purpose of this study was to investigate the characteristics of mobile phone use, mobile phone addiction symptom and physical pain in university students.
Computer-Aided Glaucoma Diagnosis Using Stochastic Watershed Transformation on Single Fundus Images
Authors: Diaz-Pinto Andres , Morales Sandra , Naranjo Valery , Navea Amparo
Published: June 2019

Glaucoma is a chronic eye disease and one of the major causes of permanent blindness. Since it does not show initial symptoms, early diagnosis is important to limit its progression. This paper presents an automatic optic nerve characterization algorithm for glaucoma diagnosis based
only on retinal fundus images. For optic cup segmentation, we used a new method based on the stochastic watershed transformation applied on the YIQ colour space to extract clinical indicators such as the Cup/Disc ratio, the area Cup/Disc ratio and the ISNT rule. Afterwards, an assessment between
normal and glaucomatous fundus images is performed. The proposed algorithm was evaluated on 6 different (private and public) databases containing 723 images (377 normal and 346 glaucomatous images) which achieved a specificity and sensitivity of 0.674 and 0.675, respectively. Moreover, an
F-score of 0.770 was obtained when evaluating this method on the publicly available database Drishti-GS1. A comparison of the proposed work with other state-of-the-art methods demonstrates the robustness of the proposed algorithm; because it was tested using images from different databases
with high variability, which is a common issue in this area. Additional comparisons with existing works for cup segmentation, that use the publicly available database Drishti-GS1, are also presented in this paper.
Gene Selection Using Parallel Lion Optimization Method in Microarray Data for Cancer Classification
Authors: Sampathkumar A. , Vivekanandan P.
Published: June 2019

In the field of bioinformatics research, a large volume of genetic data has been generated. Availability of higher throughput devices at lower cost has contributed to this generation of huge volumetric data. Handling such numerous data has become extremely challenging for selecting
the relevant disease-causing gene. The development of microarray technology provides higher chances of cancer diagnosis, by enabling to measure the expression level of multiple genes at the same stretch. Selecting the relevant gene by using classifiers for investigation of gene expression
data is a complicated process. Proper identification of gene from the gene expression datasets plays a vital role in improving the accuracy of classification. In this article, identification of the highly relevant gene from the gene expression data for cancer treatment is discussed in detail.
By using modified meta-heuristic approach, known as 'parallel lion optimization' (PLOA) for selecting genes from microarray data that can classify various cancer sub-types with more accuracy. The experimental results depict that PLOA outperforms than LOA and other well-known approaches, considering
the five benchmark cancer gene expression dataset. It returns 99% classification accuracy for the dataset namely Prostate, Lung, Leukemia and Central Nervous system (CNS) for top 200 genes. Prostate and Lymphoma dataset PLOA is 99.19% and 99.93% respectively. On evaluating the result with
other algorithm, the higher level of accuracy in gene selection is achieved by the proposed algorithm.
Preprocessing and Grading of Glioma Data Acquired from Multicenter
Authors: Zhao Guohua , Wu Yaping , He Mengyang , Bai Jie , Cheng Jingliang , Lin Yusong
Published: June 2019

Objectives: We developed a preprocessing flow for glioma multicenter data polymorphism and tested its effectiveness and availability through an improved ResNet network. We also explored if the current CapsNet model could be used for glioma grading. Materials and Methods:
We used 276 patients with glioma and two datasets to generate 4556 brain images after multi-center pretreatment was performed and introduced them to the improved ResNet and CapsNet models, and analyzed the predicted results of the model. Results: After using the pretreatment procedure
proposed in this study, we observed that the accuracy of the ResNet model significantly improved compared with that of the control group for the multicenter data. The accuracy, specificity, sensitivity, and Youden index were 93.85%, 93.93%, 93.79%, and 86.96%. The accuracy of the CapsNet for
grading glioma was up to 72.31%, but the results did not meet expectations. Other experiments showed that the CapsNet was insensitive to color discrimination. Conclusion: The pretreatment procedure proposed in this study shows effectiveness and usability for multicenter data. At present,
CapsNet for glioma grading needs further research and development.
[WITHDRAWN ARTICLE] ROC and Anova Analysis on Human Macrophage THP 1 Gene
Authors: Li Qingqing , Wu Jiang , Sun Fengxiang , Zheng Birong , Wang Shuxian , Li Yanyan , Chen Yong
Published: June 2019

WITHDRAWAL NOTICE In our paper entitled ROC and Anova Analysis on Human Macrophage THP 1 Gene, where the corresponding author is Qingqing Li, which was published in Journal of Medical Imaging and Health Informatics, 2019, Volume 9, pp.1246–1253, there is a conflict of interest between the authors of the article. We have found that the results in Figures 1 and 2 of the article may be unreliable under different growth states of the cells. Therefore, after careful consideration, we have decided to withdraw this paper with great regret. After resolution of the problematic results, we will resubmit the manuscript. We sincerely apologize for any inconvenience caused by the withdrawal of this article from the journal.
Automated Genomic Signal Processing for Diseased Gene Identification
Authors: Shen Tao , Nagai Yukari , Udayakumar M. , Narasimhan K. , Shriram R. K. Arvind , Mohanraj N. , Elamaran V.
Published: June 2019

Genomic signal processing (GSP) is the engineering discipline for the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Statistical
Computations on DNA Sequences is one of key areas in which GSP can be applied. In this paper, we apply DSP tools on trinucleotide repeat disorders (too many copies of a certain nucleotide triplet in the DNA) to classify any gene sequence into diseased/non-diseased state. Intially, we collected
the Gene sequences responsible for trinucleotide repeat disorders from NCBI. Then, we applied GSP techniques to convert the given gene sequence into an indicator sequence, and furthermore we apply Fast Fourier transforms (FFTs) and Discrete Wavelet Transforms (DWTs), followed by statistical
feature extraction and the obtained statistical features, fed into an Artificial Neural Network to predict the state of the input genomic sequence.
Cell Imaging via Multi-Electrode Array Using Microfluidic Chip
Authors: Fan Dayong , Yao Jiafeng
Published: June 2019

As a new medical detection method, electrical impedance tomography has been used in biology and medicine in recent years due to its advantages such as safety, non-invasiveness and radiation-free. In this paper, we designed a multi-electrode array microfluidic chip for the cell detection
with electrical impedance tomography. The microfluidic chip structure design, material selection and processing technology are emphatically described. Finally, the feasibility of microfluidic chip for the cell with electrical impedance tomography is verified by simulations with different cell
number and different electrodes excitation pattern.
Overall Survival Prediction for Colon Cancer Patients of 0–IV Stages With and Without Surgical Operation Through a Revised Taylor Series Expansion Algorithm: A Population-Based Study in Taiwan
Authors: Wang Tzu-Hwei , Chuang Chao-Hsun , Chiang Fu-Tsai , Chiu Shao-Wen , Peng Jia-Feng , Hwua Yi-Shi , Kittipayak Samrit , Pan Lung-Kwang
Published: June 2019

This study was aimed to predict the overall survival of colon cancer patients at various (0–IV) stages and provided a robust assessment of the expediency of a surgical operation for such patients. The proposed prediction algorithm was based on the well-known hit and target model
adopted for analyzing the cell death from the microscopic viewpoint and implied the application of the Taylor series expansion to the population-based survey dataset (in particular, to the population-based study of colon cancer patients in Taiwan covering the period from 2007 to 2016). In
the proposed algorithm, the fundamental degradation of patient's health was represented by a specific function comprising a single exponential term exp(–αt), which was multiplied by an additional term P(αt) that specified the recovery effect of a particular
therapy. The revised algorithm successfully predicted the colon cancer patients' overall survival at stages 0–IV and evaluated the expediency necessity of surgical operation for patients at various stages as well. For the above population-based survey dataset, the calculated lethal frequency
and average residual life of colon cancer patients who undergone surgical operation amounted to {0.029, 0.036, 0.058, 0.077, 0.236} yr–1 and {34.5, 27.8, 17.2, 13.0, 4.2} yr for stages 0–IV, respectively, while those for the respective groups of patients with no surgical
operation was assessed as {0.116, 0.181, 0.256, 0.203, 0.504} yr–1 and {8.6, 5.5, 3.9, 4.9, 2.0} yr, respectively. The proposed algorithm was also applied to interpret the overall survival of lung cancer patients at stages III and IV and exhibited a partial agreement with
the actual collected data.
Retinal Blood Vessel Segmentation with Improved Convolutional Neural Networks
Authors: Yang Dan , Ren Mengcheng , Xu Bin
Published: June 2019

Retinal blood vessel feature is one of crucial biomarkers for ophthalmologic and cardiovascular diseases, efficiency image segmentation technologies will help doctors diagnose these related diseases. We propose an improved deep CNN model to segment retinal blood vessels. Our method
includes three steps: Data augmentation, Image preprocessing methods and Model training. The data augmentation uses the rotation and image mirroring to make the training image better generalization. The CLAHE algorithm is used for image preprocessing, which can reduce the image noise and enhance
tiny retinal blood vessels features. Finally, we used a deep CNN model combined with U-Net and Dense-Net structure to train retinal blood vessel image. The result of proposed model was tested on public available dataset DRIVE, achieving an average accuracy 0.951, specificity 0.973, sensitivity
0.797 and the average AUC is 0.885. The results show its potential for clinical application.
Prevalence and determinants of vitamin D deficiency in infants and toddlers in the Netherlands: a pilot study
Authors: Hoevenaar-Blom Marieke P , Wielders Jos PM , Groeneveld Henk , de Leeuw Elly , Schmits Ruben JH , Pepermans Carolien , Pasker-de Jong Pieternel CM , Hogeman Paul HG
Published: June 2019

Background

Little is known of the vitamin D status of young infants and toddlers and its determinants in West Europe. The prevalence and determinants of vitamin D deficiency of children aged 6–48 months in the centre of the Netherlands (52°N) is investigated.

Methods

In a cross-sectional population study, randomly recruited infants and toddlers ( n = 150) were studied using an online questionnaire and a physical examination either in late summer ( n = 52) or in late winter ( n = 98). Vitamin D analysis was performed by capillary blood sampling using dried bloodspots plus LC-MS/MS.

Results

In late winter, 32% of the children were vitamin D deficient (<50 nmol/L 25OH vitamin D3) with 5% severely deficient (<25 nmol/L). In late summer, 2% were deficient. The odds of vitamin D deficiency were higher in children aged 24–48 months, for those not using formula milk and those not adhering to the supplementation guidelines.

Conclusion

One-third of Dutch infants and toddlers were found to be vitamin D deficient in late winter. Suggested strategies for raising the vitamin D status may include improving the adherence to supplementation, a sensible sun exposure or the use of fortified foods. Special attention is needed for the children aged 24–48 months.
Novel ketamine analogues cause a false positive phencyclidine immunoassay
Authors: Skaugen John M , Scoccimarro Anthony , Pizon Anthony F , Rymer Jacqueline A , Giannoutsos Spiros , Ekins Sean , Krasowski Matthew D , Tamama Kenichi
Published: June 2019

Background

Immunoassays are commonly used to test for drugs of abuse in patients in a variety of settings. The increasing prevalence of ‘designer’ drugs causes difficulties for the toxicology laboratory and may result in unexpected false positives and identification of unfamiliar compounds. Within the past decade, there have been a variety of ketamine and phencyclidine analogues identified, particularly as drugs of abuse.

Method

We present a case of intoxication with a novel ketamine analogue, deschloro-N-ethyl-ketamine, causing a false positive phencyclidine immunoassay. Additionally, we performed spiking studies and 2D molecular similarity calculations for deschloro-N-ethyl-ketamine, ketamine and three other analogues on the Siemens Viva-E EMIT-II phencyclidine assay to assess their cross-reactivity.

Results

Four of the tested compounds (deschloro-N-ethyl-ketamine, 3-methoxy-phencyclidine, 3-methoxy-eticyclidine and methoxetamine) cause false positive phencyclidine immunoassay results, while ketamine gives a negative result. The cross-reactivity data are in accord with the similarity calculations of these molecules, further validating the ability of 2D molecular similarity analysis to predict the molecular cross-reactivity in immunoassays.

Conclusions

The cross-reactivity data of phencyclidine and ketamine analogues presented in this study could help toxicology laboratories and clinicians in evaluating unexpected results, particularly when novel PCP and ketamine analogues are being considered.
Effect of project-based learning on development of students’ creative thinking
Authors: Chen Shih-Yeh , Lai Chin-Feng , Lai Ying-Hsun , Su Yu-Sheng
Published: June 2019

In this paper, the study aims to inquire into the impact of integrating creative thinking teaching through project-based learning in the engineering course. In the beginning, the quasi-experiment is implemented in the engineering course. The lecture-based teaching strategy is applied to the control group, while the experimental group applied the project-based learning strategy. All of the students are asked to propose their draft scheme of final project in the middle term, and then implement one system prototype as the final project in the end of semester. The draft scheme and prototype are reviewed by experts for measuring whether creativity has increased or not. Finally, a satisfaction questionnaire is delivered to evaluate the students’ opinions about the experimental classroom. The results show that the project-based learning approach is able to promote the creative thinking of students, especially with regard to fluency and flexibility. Moreover, the students in their interview thought suitable creativity thinking tools are an approach that can promote their creativity significantly. Hence, the various creative thinking tools must be provided for students in order to take advantage of developing creativity thinking habits.
A low budget take-home control engineering laboratory for undergraduate
Authors: Tran Long Q , Radcliffe PJ , Wang Liuping
Published: June 2019

Take-home engineering laboratories bring benefits for both students and the university such as flexible access times and reduced load on laboratories. Traditional control engineering laboratories are not suitable for take-home activities as they tend to be expensive or dangerous. This paper proposes a low budget take-home control laboratory based on a simple thermal system which also shows the effects of hardware limitations including saturation, quantisation and sampling jitter. A thermal hardware kit has been designed which is low-cost, safe and portable. A full laboratory guide and tutorial for the usage of the kit with MATLAB/Simulink has been written and is publicly available. The efficacy of the proposed take-home laboratory was evaluated by exam results and feedback of students who undertook a control course at RMIT University. The student evaluation and exam results were very positive and the laboratory will be extended next year.
Dynamics and Limits of Regulatory Privatization: Reorganizing audit oversight in Russia
Authors: Alon Anna , Mennicken Andrea , Samsonova-Taddei Anna
Published: June 2019

Accounting and auditing are often cited as key sites where business regulation has been privatized, globalized and neoliberalized. Yet, these sites have also undergone a legitimacy crisis in recent years, marked by a shift from self-regulation to increased public oversight. This paper investigates these developments by reference to the evolution of a public/private audit oversight regime (audit of the auditors) in Russia. We show how, in the early stages of post-Soviet reforms, old state-administered forms of financial oversight were replaced with market-oriented arrangements (peer reviews) offered by newly founded private professional accountancy associations as a service to their members. Fifteen years later, the process of regulatory privatization culminated in a reinvigoration of public authority. Our longitudinal analysis highlights the pivotal role of the state in the liberalization of governance by showing how audit oversight privatization was not only enabled by, but also provided a condition for, the strengthening of government actors. We introduce the term ‘legislative layering’ to denote the mechanism that enabled public actors to redeploy themselves in the face of the rising market logic to ensure continuity in their regulatory objectives.
Computed tomography findings and in-hospital mortality in patients with rupture of type B aortic dissection
Authors: Otsuka Tetsuhiro , Sueyoshi Eijun , Tasaki Yutaro , Uetani Masataka
Published: June 2019

Background

The relationships between the computed tomography (CT) findings and outcomes of patients with ruptured type B aortic dissection have not been clarified.

Purpose

To evaluate the initial CT findings of patients with ruptured type B aortic dissection and investigate the relationships between the initial CT findings and in-hospital mortality.

Material and Methods

This study was approved by the institutional review board. Thirty-three patients were diagnosed with ruptured Stanford type B aortic dissection at our hospital between 2007 and 2016 (21 men, 12 women; mean age = 76.1±10.7 years). We retrospectively evaluated the initial CT findings of ruptured type B aortic dissection and the relationships between clinical factors and in-hospital mortality using logistic regression analysis.

Results

Type B aortic dissections ruptured in the acute and chronic phases in 23 and 10 patients, respectively. The initial CT images showed various findings, including an open false lumen (58%), arch involvement (88%), hematomas in the pleural space (55%), hematomas in the pericardial space (18%), and the extravasation of vascular contrast material (12%). The mean maximum diameter of the affected aorta was 49.5 ± 16.1 mm. Among the 33 patients, 14 died at hospital. Female gender (hazard ratio = 10.284; 95% confidence interval [CI] = 1.61–65.54; P = 0.0136) and the presence of a hematoma in the pleural space (hazard ratio = 6.803; 95% CI = 1.07–43.24; P = 0.0421) were found to be predictors of in-hospital mortality.

Conclusion

Female gender and the presence of a hematoma in the pleural space are significant predictors of in-hospital mortality in patients with ruptured type B aortic dissection.
Levetiracetam for prophylactic treatment of pediatric migraine: A randomized double-blind placebo-controlled trial
Authors: Montazerlotfelahi Hadi , Amanat Man , Tavasoli Ali Reza , Agah Elmira , Zamani Gholam Reza , Sander Josemir W , Badv Reza Shervin , Mohammadi Mahmoud , Dehghani Mahdieh , Heidari Morteza , Hosseini Seyed Ahmad , Salehi Mona , Ashrafi Mahmoud Reza
Published: June 2019

Introduction

Few drugs are available for migraine prophylaxis in children. Levetiracetam is a broad-spectrum anti-seizure drug that has been suggested to be effective in reducing adult migraine episodes. We assessed the safety and efficacy of levetiracetam in the prevention of pediatric migraine.

Methods

A randomized double-blind placebo-controlled trial was performed. Eligible participants were aged 4–17 years old with at least four migrainous episodes monthly or had severe disabling or intolerable episodes. Primary endpoints were the mean changes in monthly frequency and intensity of headaches from the baseline phase to the last month of the double-blind phase. Safety endpoint was the adverse effects reported.

Results

Sixty-one participants (31 taking levetiracetam and 30 taking placebo) completed the study. All had a significant reduction in frequency and intensity of episodes that was significantly greater in the levetiracetam arm. Sixty eight percent of individuals in the treatment group reported more than 50% reduction of episodes at the end of the trial compared with 30% in the placebo group ( p-value: 0.007). Irritability, day-time sedation, and mild tic were reported.

Conclusion

Levetiracetam may be useful in migraine prevention and may decrease migraine episodes and severity.

Trial Registration

The study is prospectively registered with Iranian Registry of Clinical Trials; IRCT.ir, number IRCT2017021632603N1.
A Validation Study of the Internet-Specific Epistemic Justification Inventory With Norwegian Preservice Teachers
Authors: Bråten Ivar , Brandmo Christian , Kammerer Yvonne
Published: June 2019

The purpose of this study was to validate a new inventory designed to measure epistemic beliefs concerning the justification of knowledge claims encountered on the Internet. Confirmatory factor analysis of the scores of 394 preservice teachers showed that a three-factor model including justification by authority, justification by multiple sources, and personal justification fit the data well. Moreover, latent variable structural equation modeling showed that these three types of justification beliefs differentially predicted aspects of Internet-specific reading motivation and engagement. Taken together, these results provide evidence for the construct validity of the inventory and lay the foundation for further validation work. The theoretical and educational significance of the study is discussed, and directions for future research are suggested.
A study on global optimization and deep neural network modeling method in performance-seeking control
Authors: Zheng Qiangang , Fu Dawei , Wang Yong , Chen Haoying , Zhang Haibo
Published: June 2019

In this article, a novel performance-seeking control method based on deep neural network and interval analysis is proposed to obtain a better engine performance. A deep neural network modeling method which has stronger representation capability than conventional neural network and can deal with big training data is adopted to establish an on-board model in the subsonic and supersonic cruising envelops. Meanwhile, a global optimization algorithm interval analysis is applied here to get a better engine performance. Finally, two simulation experiments are conducted to verify the effectiveness of the proposed methods. One is the on-board model modeling which compares the deep neural network with the conventional neural network, and the other is the performance-seeking control simulations comparing interval analysis with feasible sequential quadratic programming, particle swarm optimization, and genetic algorithm, respectively. These two experiments show that the deep neural network has much higher precision than the conventional neural network and the interval analysis gets much better engine performance than feasible sequential quadratic programming, particle swarm optimization, and genetic algorithm.
What do we know about public attitudes towards experts? Reviewing survey data in the United Kingdom and European Union
Authors: Dommett Katharine , Pearce Warren
Published: June 2019

Recent developments in contemporary politics have cast doubt on the status of expertise and led to the oft-repeated claim that the public have had enough of experts. In response, we review existing survey measures on experts and expertise in the European Union and United Kingdom with three main findings. First, there is insufficient survey data available to strongly support any claims regarding public attitudes to experts. Second, the evidence that does exist suggests broadly positive public attitudes towards experts, rather than the somewhat bleak commentary associated with descriptions of a ‘post-truth’ era. Third, there is scope for survey questions to provide improved macro-level descriptions of some of the attributes and expectations associated with experts, and that concepts from the academic literature can provide structure for such questions. Survey data has the potential to complement more granular, qualitative approaches as part of an interpretive social science approach.
Green’s functions for soft materials containing a hard line inhomogeneity
Authors: Pei Pengyu , Yang Guang , Gao Cun-Fa
Published: June 2019

The linear elastic plane deformation of a soft material containing a rigid line inhomogeneity subjected to a concentrated force, a concentrated moment, and a point heat source was studied. Distinct from the existing rigid line inhomogeneity model which neglects the deformation of the inhomogeneity induced by both the mechanical stresses and thermal expansion, the current model allows for the thermal expansion-induced stretch and rotation of the inhomogeneity. In this context, we derive the closed-form solution for the full stress field in the soft material by solving the corresponding Riemann–Hilbert problem. In particular, our solution can serve as the Green’s function to establish other analytical solutions for more practical and complicated problems in this area. Several numerical examples are presented to illustrate our closed-form solution corresponding to the thermal loading. It is found that the presence of the heat source contributes significantly to the rigid rotation of inhomogeneity, and the thermal expansion-induced stretch of the inhomogeneity has a great impact on the stress intensity factors at the inhomogeneity tips.
Spirit map and medium’s message: Searching for war dead in Vietnam
Authors: Hüwelmeier Gertrud
Published: June 2019

Popular religious practices such as communicating with the deceased take place in many parts of the world. In cases of death through violence, as in warfare, the living worry about the dead bodies of their loved ones as the lack of bodily remains makes it impossible to perform a proper burial. Vietnam is a valuable case study because it has experienced terrible violence in the 20th century. This article explores the pilgrimage of a group of brothers who searched for the bodily remains of their father in the late 1990s. He operated as a secret agent and was killed in 1957 when he crossed the border into South Vietnam. In their quest, the brothers consulted a ritual expert, who guided them from a distance. Drawing on this case study, the paper argues that filial piety, spirit mediumship, technology, and political history are deeply intertwined in post-revolutionary and late socialist Vietnam.
Does incidental exposure on social media equalize or reinforce participatory gaps? Evidence from a panel study
Authors: Heiss Raffael , Matthes Jörg
Published: June 2019

Existing research indicates that incidental exposure to political information on social media may function as an equalizer, stimulating political engagement among the politically detached. In this article, we challenge this notion and propose that there are good reasons to assume that incidental exposure may reinforce existing gaps. We test the equalizing against the reinforcing hypothesis using data from a two-wave panel study ( N = 559). We find a positive main effect of incidental exposure on low-effort digital participation. However, this effect was not conditional on political interest, as the equalizing assumption would have suggested. More interestingly, we found that the effect of incidental exposure on high-effort digital participation was conditional on political interest. However, against the assumption of equalization, individuals with low levels of political interest were negatively affected by incidental exposure, thus lending support for the reinforcement hypothesis. Possible reasons for these findings are discussed.
Representation of news related to culturally diverse population in Australian media
Authors: Rodrigues Usha M , Niemann Michael , Paradies Yin
Published: June 2019

The Australian media market has fragmented with audiences accessing news from various sources (mainstream media and/or social media) on a variety of platforms. In this fragmented market, we examine the media coverage of high-profile multicultural and transnational events and issues during a 6-month period, which potentially has adverse impact on social cohesion by contributing to negative attitudes towards minority communities. The article outlines outcomes of a classical content analysis of news and commentary available on Australian mainstream news sites, and a sentiment analysis of Twitter conversations around the same topics. We use Stuart Hall’s encoding decoding model to explain the outcomes of the two content analyses and consider the news coverage and social media news conversations of these prominent events/issues from the perspective of culturally diverse Australian audiences.
Human rights collectives as visual experts: the case of Syrian Archive
Authors: Ristovska Sandra
Published: June 2019

This article maps the institutional context that renders eyewitness video meaningful for human rights purposes. By looking closely at the work of Syrian Archive, this article argues that human rights collectives are positioning themselves as visual experts that both mimic established institutional modalities and help offset the lack of replicable workflows and clear visual standards for eyewitness video across journalism, the law and political advocacy. In doing so, this article illuminates the larger information networks that characterize the production, circulation and legitimacy of human rights videos today.
Enhanced HR-CLEAN-SC for resolving multiple closely spaced sound sources
Authors: Luesutthiviboon Salil , Malgoezar Anwar MN , Merino-Martinez Roberto , Snellen Mirjam , Sijtsma Pieter , Simons Dick G
Published: June 2019

The recently introduced high-resolution (HR)-CLEAN-SC algorithm for acoustic imaging provides ‘super-resolution’, i.e. the ability to discern sound sources located closer than the Rayleigh resolution limit. This is achieved by allowing the source markers to be relocated from the actual source locations within a certain constraint to avoid the combined influence of the other sound sources. The freedom to relocate the source markers to increase the performance of the algorithm depends on the maximum sidelobe level of the acoustic array used. This paper presents an ‘enhanced’ version of the HR-CLEAN-SC algorithm which benefits from low maximum sidelobe level array design. The source marker constraint μ is adapted to the maximum sidelobe level at each frequency. Application to up to four synthetic sound sources shows that the sources can be resolved at half the frequency associated with the Rayleigh resolution limit, when an acoustic array optimized for low maximum sidelobe level is used in combination with Enhanced HR-CLEAN-SC. This improves source discrimination compared to when the HR-CLEAN-SC algorithm is used with a benchmark acoustic array design. The results are confirmed by experimental validation in which up to four loudspeakers and the same array configurations as in the synthesized data case are used.
Positive experience with treatment is associated with better surgical outcome in trapeziometacarpal osteoarthritis
Authors: Tsehaie Jonathan , van der Oest Mark J. W. , Poelstra Ralph , Selles Ruud W. , Feitz Reinier , Slijper Harm P. , Hovius Steven E. R. , Porsius Jarry T. ,   the Hand-Wrist Study Group
Published: June 2019

The aim of this study was to investigate the association between patients’ experiences with trapeziometacarpal arthroplasty and treatment outcomes in terms of patient-reported outcome measures, grip and pinch strength. We included 233 patients who received a Weilby procedure for trapeziometacarpal osteoarthritis. Before surgery and 12 months after surgery, patients completed the Michigan Hand Outcomes Questionnaire, and their pinch and grip strengths were measured. At 3 months after surgery, a patient-reported experience measure was completed. Using regression analysis, significantly positive associations were found between the Michigan Hand questionnaire and the patient-reported experience measure, with the strongest significant associations being for patients’ experiences with information provision. No significant associations were found between the patients’ experience and strength outcomes. The results highlight the potential importance of positive experience with the treatment process to improve treatment outcomes in patients undergoing surgery for trapeziometacarpal osteoarthritis.

Level of evidence: IV