bluuebunny/crossref_metadata_2025 huggingface dataset:
Early detection of elevated cardiac biomarkers to optimise risk stratification in patients with COVID-19
Authors: Stefanini Giulio G. , Chiarito Mauro , Ferrante Giuseppe , Cannata Francesco , Azzolini Elena , Viggiani Giacomo , De Marco Andrea , Briani Martina , Bocciolone Monica , Bragato Renato , Corrada Elena , Gasparini Gabriele L , Marconi Manuel , Monti Lorenzo , Pagnotta Paolo A , Panico Cristina , Pini Daniela , Regazzoli Damiano , My Ilaria , Kallikourdis Marinos , Ciccarelli Michele , Badalamenti Salvatore , Aghemo Alessio , Reimers Bernhard , Condorelli Gianluigi
Published: August 2020

Objective

Risk stratification is crucial to optimise treatment strategies in patients with COVID-19. We aimed to evaluate the impact on mortality of an early assessment of cardiac biomarkers in patients with COVID-19.

Methods

Humanitas Clinical and Research Hospital (Rozzano-Milan, Lombardy, Italy) is a tertiary centre that has been converted to the management of COVID-19. Patients with confirmed COVID-19 were entered in a dedicated database for cohort observational analyses. Outcomes were stratified according to elevated levels (ie, above the upper level of normal) of high-sensitivity cardiac troponin I (hs-TnI), B-type natriuretic peptide (BNP) or both measured within 24 hours after hospital admission. The primary outcome was all-cause mortality.

Results

A total of 397 consecutive patients with COVID-19 were included up to 1 April 2020. At the time of hospital admission, 208 patients (52.4%) had normal values for cardiac biomarkers, 90 (22.7%) had elevated both hs-TnI and BNP, 59 (14.9%) had elevated only BNP and 40 (10.1%) had elevated only hs-TnI. The rate of mortality was higher in patients with elevated hs-TnI (22.5%, OR 4.35, 95% CI 1.72 to 11.04), BNP (33.9%, OR 7.37, 95% CI 3.53 to 16.75) or both (55.6%, OR 18.75, 95% CI 9.32 to 37.71) as compared with those without elevated cardiac biomarkers (6.25%). A multivariate analysis identified concomitant elevation of both hs-TnI and BNP as a strong independent predictor of all-cause mortality (OR 3.24, 95% CI 1.06 to 9.93).

Conclusions

An early detection of elevated hs-TnI and BNP predicts mortality in patients with COVID-19. Cardiac biomarkers should be systematically assessed in patients with COVID-19 at the time of hospital admission in order to optimise risk stratification.
Prediction of immune checkpoint inhibition with immune oncology-related gene expression in gastrointestinal cancer using a machine learning classifier
Authors: Lu Zhihao , Chen Huan , Jiao Xi , Zhou Wei , Han Wenbo , Li Shuang , Liu Chang , Gong Jifang , Li Jian , Zhang Xiaotian , Wang Xicheng , Peng Zhi , Qi Changsong , Wang Zhenghang , Li Yanyan , Li Jie , Li Yan , Brock Malcolm , Zhang Henghui , Shen Lin
Published: August 2020

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of gastrointestinal cancer. However, biomarkers correlated with the efficacy of ICIs in gastrointestinal cancer are still lacking. In this study, we performed 395-plex immune oncology (IO)-related gene target sequencing in tumor samples from 96 patients with metastatic gastrointestinal cancer patients treated with ICIs, and a linear support vector machine learning strategy was applied to construct a predictive model. ResultsAll 96 patients were randomly assigned into the discovery (n=72) and validation (n=24) cohorts. A 24-gene RNA signature (termed the IO-score) was constructed from 395 immune-related gene expression profiling using a machine learning strategy to identify patients who might benefit from ICIs. The durable clinical benefit rate was higher in patients with a high IO-score than in patients with a low IO-score (discovery cohort: 92.0% vs 4.3%, p<0.001; validation cohort: 85.7% vs 17.6%, p=0.004). The IO-score may exhibit a higher predictive value in the discovery (area under the receiver operating characteristic curve (AUC)=0.97)) and validation (AUC=0.74) cohorts compared with the programmed death ligand 1 positivity (AUC=0.52), tumor mutational burden (AUC=0.69) and microsatellite instability status (AUC=0.59) in the combined cohort. Moreover, patients with a high IO-score also exhibited a prolonged overall survival compared with patients with a low IO-score (discovery cohort: HR, 0.29; 95% CI 0.15 to 0.56; p=0.003; validation cohort: HR, 0.32; 95% CI 0.10 to 1.05; p=0.04). Taken together, our results indicated the potential of IO-score as a biomarker for immunotherapy in patients with gastrointestinal cancers.
Gendered working environments as a determinant of mental health inequalities: a systematic review of 27 studies
Authors: Milner Allison , Scovelle Anna Joy , King Tania , Marck Claudia , McAllister Ashley , Kavanagh Anne , Shields Marissa , Török Eszter , Maheen Humaira , O"Neil Adrienne
Published: August 2020

Background

‘Gendered working environments’ describes the ways in which (1) differential selection into work, (2) variations in employment arrangements and working hours, (3) differences in psychosocial exposures and (4) differential selection out of work may produce varied mental health outcomes for men and women. The aim of this study was to conduct a systematic review to understand gender differences in mental health outcomes in relation to the components of gendered working environments.

Methods

The review followed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search approach and focused on studies published in 2008–2018. The protocol for the review was prospectively registered with PROSPERO (CRD42019124066).

Findings

Across the 27 cohort studies included in the review, we found that (1) there was inconclusive evidence on the effect of occupational gender composition on the mental health of men and women, (2) women’s mental health was more likely to be affected by long working hours than men’s; however, precarious employment was more likely to be negatively associated with men’s mental health, (3) exposure to traditional constructs of psychosocial job stressors negatively affected the mental health of both women and men, and (4) unemployment and retirement are associated with poorer mental health in both genders.

Interpretation

The findings from this review indicate that gendered working environments may affect the mental health of both men and women, but the association is dependent on the specific exposure examined. There is still much to be understood about gendered working environments, and future research into work and health should be considered with a gender lens.
Increasing density and cement content in stabilization of expansive soils: Conflicting or complementary procedures for reducing swelling?
Authors: Consoli Nilo Cesar , Tonini de Araújo Mariana , Tonatto Ferrazzo Suéllen , de Lima Rodrigues Vinícius , Gravina da Rocha Cecilia
Published: August 2020

The present study makes three contributions to the literature of expansive soils: (i) it proposes equations to predict soil swelling based on dry density and cement content, (ii) it checks the developed general equation by predicting the swelling of different expansive soils from the literature, and (iii) it designs experiments that investigate factors that have a significant influence on swelling. An experimental programme was carried out to analyse the expansion of bentonite–kaolin–cement blends. Different proportions of bentonite–kaolin, cement content, dry density, and moisture content were evaluated. A unique relation of the cement/porosity index was obtained for cement-stabilized expansive soils’ swelling; this index has been used before to portray strength, stiffness, and loss of mass of stabilized soils and is now shown to be applicable to describe swelling of expansive soils treated with Portland cement. In the present research, cement content and dry density are seen as conflicting parameters regarding the swelling of expansive soils, because increasing the amount of Portland cement reduces swelling and increasing the density (through compaction) causes higher expansion. A general swelling model is proposed and successfully checked with data from the literature; it is able to predict the swelling of expansive soils with different densities, expansive mineral, moisture content, and cement content.
Study on the finite element method of Hamiltonian system with chaos
Authors: Tang Qiong , Liu YangFan , Zheng Yujun , Xu ChengJie
Published: August 2020

By comparing with symplectic different methods, the quadratic element is an approximately symplectic method which can keep high accuracy approximate of symplectic structure for Hamiltonian chaos, and it is also energy conservative when there have chaos phenomenon. We use the quadratic finite element method to solve the H[Formula: see text]non–Heiles system, and this method was never used before. Combining with Poincar[Formula: see text] section, when we increase the energy of the systems, KAM tori are broken and the motion from regular to chaotic. Without chaos, three kinds of methods to calculate the Poincar[Formula: see text] section point numbers are the same, and the numbers are different with chaos. In long-term calculation, the finite element method can better keep dynamic characteristics of conservative system with chaotic motion.
Modeling the surface roughness in face-end milling process by using general insert at stable cutting conditions
Authors: Ky Le Hong , Nguyen Nhu-Tung , Do Duc Trung , Hoang Tien Dung , Le Hoang Anh
Published: August 2020

Predicting the quality of the machined components is the grandiose signification in industrial manufacturing. Calculation of the surface roughness is one of the most important elements to predict the quality of machined parts. In this paper, the surface roughness was modeled in the face-end mill process by using general rhombu insert. In the proposed mathematical model, with the stable milling condition, the surface roughness is formulated by a function of feed rate, and insert geometry such as nose radius and nose angle. An experimental method is proposed based on the stable milling condition to estimate the surface roughness. The developed surface roughness calculation model has been successfully verified by both simulation and experiment with very promising results. The average difference between predicted and experimental results is 7.59%. The proposed model can be applied to predict the surface roughness in face-end mill processes by using general insert at stable cutting condition.
MOLECULAR BIOLOGY AND BIOMECHANICS OF OSTEOPHYTE FORMATION IN ELBOW OSTEOARTHRITIS: A REVIEW
Authors: Ojaghi Reza
Published: August 2020

Managing osteophyte in elbow osteoarthritis (OA) is not an easy task. In the review of the subject hereby, the molecular biology and biomechanics of osteophyte formation will be addressed in composite detail. A number of basic and clinical science research studies that have evaluated the importance and significant role of growth factors, cytokines production, receptors expression, proteoglycans, and alarmins secretion will be included. At the same time, it is notable that the osteophyte formation has not been thoroughly evaluated with respect to its biomechanics, stress and strain pattern on the joint, and its relation to growth plate and the differences that may exist between animal and human joints. Namely, a few studies have begun to look at this particular aspect of osteophyte formation, which does not cover the issue of the graded biomechanical response to the osteophyte formation. The findings of this study can conclude that biomechanical understanding of osteophyte formation has the potential to give a better solution for medical and surgical management of osteophyte formation in different joints and particularly in elbow joint. As such, the proper management of elbow OA with its significant osteophyte formation requires a comprehensive understanding of biology and biomechanics of osteophyte formation.
HAPTOGLOBIN POLYMORPHISM AND CHRONIC TENDINOPATHY
Authors: Alzyoud Jihad A. M. , Abdelall Seham T. , Al-Shudiefat Abd Al-Rahman S. , Khalyaila Dawood Moh’d , Al Najjar Saleh A.
Published: August 2020

Introduction: Tendinopathy is a pathology of tendons of multifactorial origin displayed clinically as chronic degenerative tissue resulting in dysfunction and painful musculoskeletal system. Genetic implications in tendinopathy are not fully elucidated. Haptoglobin (Hp) polymorphism has been investigated for potential role in several diseases such as cardiovascular diseases. This study aims at investigating Hp polymorphism potential association with chronic tendinopathy in Jordan. Materials and Methods: A hospital-based case-control study, of 101 patients diagnosed with chronic tendinopathy and 104 age and gender matched controls, was employed and Hpphenotypes distributions were determined using Sodium Dodecyl Sulphate Polyacrylamide gel electrophoresis technique. Results: showed a significant association between tendinopathy cases and controls in relation to Hpphenotypes frequencies (Fisher’s Exact Test, [Formula: see text]). Odd ratios showed that the odds of tendinopathy cases in Hp2.1 group were reduced while odds in Hp2.2 and Hp1.1 were increased by 3.22 and 7.34 times, respectively, as likely compared to the controls. Conclusion: Results suggested that Hppolymorphism might play a role in chronic tendinopathy genesis.
POSTEROMEDIAL MENISCAL AND ANTERIOR CRUCIATE LIGAMENT STRAINS DURING DYNAMIC ACTIVITIES FOLLOWING ANTERIOR CRUCIATE LIGAMENT RECONSTRUCTION
Authors: Tomescu Sebastian , Bakker Ryan , Wasserstein David , Kalra Mayank , Nicholls Micah , Whyne Cari , Chandrashekar Naveen
Published: August 2020

Background: Meniscal strain patterns are not well understood during dynamic activities. Furthermore, the impact of ACL reconstruction on meniscal strain has not been thoroughly investigated. The purpose of this study was to characterize ACL and meniscal strain during dynamic activities and investigate the strain difference between ACL-intact and ACL-reconstructed ligament conditions. Methods: ACL and medial meniscal strain were measured in-vitro during gait, a double leg squat, and a single leg squat. For each activity kinematics and muscle forces were applied to seven cadaveric specimens using a dynamic knee simulator. Testing was performed in the ACL-intact and ACL-reconstructed ligament conditions. Results: Both the ACL and meniscus had distinct strain patterns that were found to have a significant interaction with knee angle during gait and double leg squat ([Formula: see text]). During gait, both tissues experienced lower strain during swing than stance (ACL: 3.0% swing, 9.1% stance; meniscus: 0.2% swing, 1.3% stance). Meniscal strain was not found to be different between ACL-intact and ACL-reconstructed conditions ([Formula: see text]). Conclusions: During dynamic activities, the strain in the meniscus was not altered between ACL ligament conditions. This indicates that meniscal mechanics after ACL reconstruction are similar to a healthy knee. These results help further the understanding of osteoarthritis risk after ACL reconstruction.
Quantum image encryption based on Lorenz hyper-chaotic system
Authors: Zhou Ri-Gui , Li Ying-Bin
Published: August 2020

According to the higher security of higher-dimensional chaotic system, a new scheme of quantum image encryption and decryption based on Lorenz hyper-chaotic system is proposed. The encryption process is mainly divided into two parts: the location information scrambling process and the color information replacement process. In the location information scrambling process, the pseudo-random sequence obtained by the Lorenz hyper-chaotic system is first sorted to obtain the corresponding position index sequence, and then the rows and columns of the position information are scrambled by the index sequence. In the process of color replacement, the change of pixel value is firstly diffused to each pixel through chaotic sequence, and then the information of each pixel is confused, so as to realize the process of color information replacement. Experimental analysis shows that the encryption scheme in this paper has a good effect.
Law of Approach to Magnetic Saturation in Nanocrystalline Pr2Co7Cx(x≤1): Effects of Carbonation
Authors: Yamkane Z. , Fersi R. , Rachid F. Z. , Moubah R. , Lassri H. , Mliki N. , Alleg S. , Sajieddine M. , Bessais L.
Published: August 2020

We report on the effect of Carbon insertion on the microstructure and magnetic properties of nanocrystalline Pr2Co7Cx([Formula: see text]). The Pr2Co7Cx were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and physical property measurement system (PPMS9) Quantum Design. Mean field theory was utilized to depict the temperature dependence of magnetization and deduce the exchange interactions. The approach to saturation magnetization was as well used. The results were interpreted in the framework of random magnetic anisotropy model. From such analysis, some fundamental parameters were extracted.
IDC Breast Cancer Detection Using Deep Learning Schemes
Authors: Kumar Kamlesh , Saeed Umair , Rai Athaul , Islam Noman , Shaikh Ghulam Muhammad , Qayoom Abdul
Published: August 2020

During the past few years, deep learning (DL) architectures are being employed in many potential areas such as object detection, face recognition, natural language processing, medical image analysis and other related applications. In these applications, DL has achieved remarkable results matching the performance of human experts. This paper presents a novel convolutional neural networks (CNN)-based approach for the detection of breast cancer in invasive ductal carcinoma tissue regions using whole slide images (WSI). It has been observed that breast cancer has been a leading cause of death among women. It also remains a striving task for pathologist to find the malignancy regions from WSI. In this research, we have implemented different CNN models which include VGG16, VGG19, Xception, Inception V3, MobileNetV2, ResNet50, and DenseNet. The experiments were performed on standard WSI slides data-set which include 163 patients of IDC. For performance evaluation, same data-set was divided into 113 and 49 images for training and testing, respectively. The testing was carried out separately over each model and the obtained results showed that our proposed CNN model achieved 83% accuracy which is better than the other models.
Relationship between the representative element volume and discontinuity parameters
Authors: Song Shengyuan , Xu Qiang , Chen Jianping , Wang Fengyan , Liu Ying , Liu Yufeng
Published: August 2020

We introduce an application of the discrete fracture network (DFN) model and 3D persistence to study the relationship between the representative element volume (REV) size and discontinuity information. To avoid the influence of heterogeneity on the distribution of discontinuities, the dam abutment rock mass of the Songta hydropower station is divided into eight statistically homogeneous domains based on the discontinuity orientation and trace length. An optimum DFN model is established for each homogeneous domain. Cubes of different sizes are extracted from the centre of the corresponding DFN model. Based on the discontinuity projection method, the 3D persistence values within the DFN model and each cube are calculated separately. The relative error of persistence for each cube and the DFN model are used to evaluate the size effect and to identify the REV size. Subsequently, the relationship between the determined REV size and the corresponding discontinuity information is systematically researched. Our results show that the discontinuity diameter, the volume density and the Fisher constant have separate linear relationships with the REV size. We present the empirical formulas for estimating the REV size according to the discontinuity diameter, the volume density and the Fisher constant.
Geophysical mapping of gypsum for exploration of reserves in the Nong Bua area of Thailand
Authors: Arjwech Rungroj , Everett Mark E. , Saengchomphu Sakhon , Somchat Kittipong , Pondthai Potpreecha
Published: August 2020

The increasing demand for gypsum as a raw material for construction projects motivates exploration for additional reserves. Electrical resistivity tomography (ERT) and seismic refraction geophysical methods, augmented with borehole and laboratory measurements on core samples, are used here to delineate the top, bottom and lateral boundaries of an important gypsum ore deposit in Thailand, an economically developing region. The gypsum-bearing formation is found throughout the study area to have an irregular upper boundary on account of karstic dissolution processes. The deeper transition from gypsum to anhydrite, however, is not constrained by the measurements. The P-wave velocity measured in the field is consistent with the core specimen measurements. The electrical resistivity of the core specimens, however, is substantially higher than the values measured in the field. The specimen measurements may depend on the presence of micro cracks, whereas electrical resistivity in the field may be affected by the enclosing clay-rich materials.
Mechanism underlying increased cardiac extracellular matrix deposition in perinatal nicotine-exposed offspring
Authors: Chuang Tsai-Der , Ansari Aamir , Yu Celia , Sakurai Reiko , Harb Amir , Liu Jie , Khorram Omid , Rehan Virender K.
Published: August 2020

Using an established rat model and cultured primary neonatal cardiac fibroblasts, we show that nicotine mediated MIAT induction as the underlying mechanism for the excessive cardiac collagen deposition. These observations provide mechanistic basis for the increased predisposition to cardiac dysfunction following perinatal cigarette/nicotine exposure and offer novel potential therapeutic targets.
Endothelial deficiency of insulin-like growth factor-1 receptor reduces endothelial barrier function and promotes atherosclerosis in Apoe-deficient mice
Authors: Higashi Yusuke , Sukhanov Sergiy , Shai Shaw-Yung , Danchuk Svitlana , Snarski Patricia , Li Zhaohui , Hou Xuwei , Hamblin Milton H. , Woods T. Cooper , Wang Meifang , Wang Derek , Yu Hong , Korthuis Ronald J. , Yoshida Tadashi , Delafontaine Patrice
Published: August 2020

Endothelial insulin-like growth factor-1 (IGF-1) receptor deficiency significantly elevated atherosclerotic burden in apolipoprotein E-deficient mice, mediated at least in part by downregulation of intercellular junction proteins and, thus, elevated endothelial permeability. This study revealed a novel role for IGF-1 in supporting endothelial barrier function. These findings suggest that IGF-1’s ability to promote endothelial barrier function may offer a novel therapeutic strategy for vascular diseases such as atherosclerosis.
An integrated approach to simulating the vulnerable atherosclerotic plaque
Authors: Mohammad Mirzaei Navid , Weintraub William S. , Fok Pak-Wing
Published: August 2020

In this article, we propose a quantitative framework to describe the evolution of atherosclerotic plaque. We use partial differential equations (PDEs) with macrophages, necrotic cells, oxidized lipids, oxygen concentration, and PDGF as primary variables coupled to a biomechanical model to describe vessel growth. A feature of our method is that it outputs color-coded vessel sections corresponding to regions of the plaque that are necrotic and fibrous, qualitatively similar to images generated by enhanced intravascular ultrasound.
Potential mechanism of left ventricular spherical remodeling: association of mitral valve complex-myocardium longitudinal tissue remodeling mismatch
Authors: Nagata Yasufumi , Iwataki Mai , Nabeshima Yosuke , Hei Soshi , Onoue Takeshi , Hayashi Atsushi , Otani Kyoko , Tsuda Yuki , Araki Masaru , Kim Dae-Hee , Song Jae-Kwan , Hayashida Akihiro , Toki Misako , Yuasa Toshinori , Mizukami Naoko , Nishimura Yosuke , Levine Robert A. , Otsuji Yutaka
Published: August 2020

Left ventricular (LV) spherical remodeling is associated with poor prognosis and less-effective cardiac performance, which commonly develops in dilated cardiomyopathy. However, its mechanism remains unclear. We hypothesized and subsequently clarified that less mitral valve complex (MVC) tissue longitudinal elongation relative to whole LV myocardial tissue longitudinal elongation is related to disproportionately less LV base longitudinal versus transverse myocardial tissue elongation, constituting spherical remodeling. This study suggests modification of MVC tissue elongation could be potential therapeutic targets.
Diet-induced obese mouse hearts tolerate an acute high-fatty acid exposure that also increases ischemic tolerance
Authors: Boardman Neoma T. , Pedersen Tina M. , Rossvoll Line , Hafstad Anne D. , Aasum Ellen
Published: August 2020

An acute myocardial fat-load leads to oxidative stress, oxygen wasting, mechanical inefficiency, hyperacetylation, and impaired mitochondrial function, which can contribute to reduced ischemic tolerance. Following obesity/insulin resistance, hearts were less affected by a high fat-load, which subsequently also improved ischemic tolerance. This study highlights that an acute fat-load affects normal and obese hearts differently and that obesity renders hearts less vulnerable to the disadvantageous effects of an acute fat-load.
Policies and Problems of Modernizing Ethnomedicine in China: A Focus on the Yi and Dai Traditional Medicines of Yunnan Province
Authors: Li Zhiyong , Li Caifeng , Zhang Xiaobo , Tang Shihuan , Yang Hongjun , Cui Xiuming , Huang Luqi
Published: August 2020

Yunnan is a multiethnic province in southwest China, rich in Materia medica resources, and is popularly known as the kingdom of plants. Biomedicine and public health industry have been the industrial pillars of Yunnan since 2016, which is the important pharmaceutical industrial base for Dai and Yi medicine in China. This review of the Yunnan ethnic medicine industry describes some of the problems to be solved in the development of sustainable ethnomedicine in China. We investigated Chinese patent medicines (CPMs) declared as ethnomedicine on the drug instructions and identified 28 Dai patent medicines (DPMs) and 73 Yi patent medicines (YPMs) that were approved for clinical use in China. In further research, the clinical indications of these CPMs were determined, and the quality standard of medicinal materials and their usage frequencies in DPMs and YPMs were investigated. We also collected and analyzed the data on use of botanical and animal sources of medicines, the rare and endangered medicinal materials, and toxic medicines in DPMs and YPMs. The application of zootherapy in Yi traditional medicine was introduced from its abundant ancient documents and records; based on the “YaGei” theory in Dai traditional medicine, toxic medicines can be relatively safe in DPMs. However, for promoting the Yunnan traditional medicine industry, it is necessary to strengthen medical research to expand evidence‐based clinical practice and balance ethnomedicine production and sustainable utilization of Materia medica resources, especially the animal sources of medicines, toxic medicines, and the protected wild resources reported in this survey. Only in this way can industrialization of ethnomedicine promote the improvement of human health.
Antimalarial Activity of the Leaf Latex ofAloe weloensis(Aloaceae) againstPlasmodium bergheiin Mice
Authors: Teka Tekleab , Awgichew Tadesse , Kassahun Haile
Published: August 2020

Background. Emergence of drug resistance and lack of therapeutic efficacy of modern antimalarial drugs are the most triggering factors for the searching of new lead compounds with different mechanisms of action. Medicinal plants with documented traditional uses are a viable option for treatment of malaria. Traditionally, the leaf latex ofAloe weloensishas been used in the treatment of malaria in Ethiopia. Hence, this study was undertaken to investigate the antimalarial activity of the leaf latex ofAloe weloensisinPlasmodium berghei-infected mice.Methods. A four-day suppressive test was employed to evaluate the antimalarial effect of the leaf latex of the plant againstP.bergheiin Swiss albino mice. Mice were randomly assigned in five groups of five animals in each and given 100, 200, and 400 mg/kg of the leaf latex, chloroquine 25 mg/kg, and distilled water. The level of parasitemia, packed cell volume, survival time, temperature, and body weight was used to determine the antimalarial activity.Results. The acute toxicity study indicated that the leaf latex ofA.weloensiscaused neither mortality nor signs and symptoms of toxicity at a dose of 2000 mg/kg. Furthermore, the 4-day suppressive test indicated that the latex ofthe plantexhibited a significant parasitemia reduction in a dose-dependent manner as compared to negative control. The leaf latex of the plant exhibited a percent inhibition of 13.05%, 41.87%, and 66.84% at doses of 100 mg/kg, 200 mg/kg, and 400 mg/kg, respectively. The chemosuppression of the antimalarial activity was statistically significant at 100 mg/kg (p<0.05), 200 mg/kg (p<0.01), and 400 mg/kg (p<0.01) as compared to negative control. All doses of the leaf latex prevented weight loss and reduction in temperature and packed cell volume and increased the survival time of infected mice.Conclusion. The results of this study demonstrated that the leaf latex ofAloe weloensispossessed antiplasmodial activity confirming the genuine traditional use of the plant as an antimalarial agent.
Deep Learning Technology for Weld Defects Classification Based on Transfer Learning and Activation Features
Authors: Ajmi Chiraz , Zapata Juan , Elferchichi Sabra , Zaafouri Abderrahmen , Laabidi Kaouther
Published: August 2020

Weld defects detection using X‐ray images is an effective method of nondestructive testing. Conventionally, this work is based on qualified human experts, although it requires their personal intervention for the extraction and classification of heterogeneity. Many approaches have been done using machine learning (ML) and image processing tools to solve those tasks. Although the detection and classification have been enhanced with regard to the problems of low contrast and poor quality, their result is still unsatisfying. Unlike the previous research based on ML, this paper proposes a novel classification method based on deep learning network. In this work, an original approach based on the use of the pretrained network AlexNet architecture aims at the classification of the shortcomings of welds and the increase of the correct recognition in our dataset. Transfer learning is used as methodology with the pretrained AlexNet model. For deep learning applications, a large amount of X‐ray images is required, but there are few datasets of pipeline welding defects. For this, we have enhanced our dataset focusing on two types of defects and augmented using data augmentation (random image transformations over data such as translation and reflection). Finally, a fine‐tuning technique is applied to classify the welding images and is compared to the deep convolutional activation features (DCFA) and several pretrained DCNN models, namely, VGG‐16, VGG‐19, ResNet50, ResNet101, and GoogLeNet. The main objective of this work is to explore the capacity of AlexNet and different pretrained architecture with transfer learning for the classification of X‐ray images. The accuracy achieved with our model is thoroughly presented. The experimental results obtained on the weld dataset with our proposed model are validated using GDXray database. The results obtained also in the validation test set are compared to the others offered by DCNN models, which show a best performance in less time. This can be seen as evidence of the strength of our proposed classification model.
Lithium-Ion Battery Parameters and State of Charge Joint Estimation Using Bias Compensation Least Squares and the Alternate Algorithm
Authors: Xiong Wei , Mo Yimin , Yan Cong
Published: August 2020

For safe and efficient operation of electric vehicles (EVs), battery management system is essential. Nevertheless, a challenge lying in battery management systems is how to obtain an algorithm for state of charge (SOC) estimation that has both high accuracy and low computational cost. For this purpose, the battery parameters and SOC joint estimation algorithm based on bias compensation least squares and alternate (BCLS-ALT) algorithm are proposed in this paper. The battery model parameters are identified online using the bias compensation least squares (BCLS), while the SOC is estimated applying the alternate (ALT) algorithm, which can switch the computational logic between H-infinity filter (HIF) and ampere-hour integral (AHI) to improve the computational efficiency and accuracy. The experimental results show that the accuracy of the SOC estimated by the BCLS-ALT algorithm is the highest, and the computational efficiency is also high, with the switching threshold SOCALT being set to 25%. Despite the 20% initial error and the 10% current drift, the proposed BCLS-ALT algorithm can obtain high accuracy and robustness of SOC estimation under different ambient temperatures and dynamic load profiles.
Wear Identification of Vibration Drilling Bit Based on Improved LMD and BP Neural Network
Authors: Shi Yaochen , Liu Hongyan , Zhang Xuechen , Li Qinghua , Guo Xiaocheng
Published: August 2020

In view of the low accuracy of single signal monitoring for the wear state of vibration drilling bit, a multisignal acquisition system for the wear state of ultrasonic axial vibration drilling bit is built to collect the drilling force, vibration, and acoustic emission signals under three different wear states. The drilling force, vibration and acoustic emission signals of the bit in the drilling process are processed by using wavelet decomposition technology, and the signals are extracted from the wear state of the bit, The wavelet energy coefficient with high state correlation is used as the feature parameter to identify the bit wear state. The feature parameter is trained by the combination of noise assisted LMD method and BP neural network. The experiment of single signal and multisignal fusion monitoring bit wear state is carried out, and the neural network structure is optimized according to the error. The results show that the accuracy of monitoring bit wear with a single signal of drilling force is 83.3%, the accuracy of monitoring bit wear with a single signal of vibration is 91.6%, the accuracy of monitoring bit wear with a single signal of acoustic emission is 91.6%, and the accuracy of monitoring bit wear with multisignal fusion is 95.8%; when the number of network layer is 4, the vibration is monitored with the fusion of force signal, acoustic emission signal, and vibration signal The accuracy of the state of drilling tool is up to 100%. The structure model of neural network is optimized reasonably to improve the recognition rate of bit wear in vibration drilling.
A Study of Fractional Differential Equation with a Positive Constant Coefficient via Hilfer Fractional Derivative
Authors: Ngo Van Hoa , Ho Vu
Published: August 2020

The aim of the paper is to consider the existence and uniqueness of solution of the fractional differential equation with a positive constant coefficient under Hilfer fractional derivative by using the fixed-point theorem. We also prove the bounded and continuous dependence on the initial conditions of solution. Besides, Hyers–Ulam stability and Hyers–Ulam–Rassias stability are discussed. Finally, we provide an example to demonstrate our main results.
Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators
Authors: Dachang Zhu , Baolin Du , Puchen Zhu , Wu Wenqiang
Published: August 2020

To achieve precise trajectory tracking of robotic manipulators in complex environment, the precise dynamic model, parameters identification, nonlinear characteristics, and disturbances are the factors that should be solved. Although parameters identification and adaptive estimate method were proposed for robotic control in many literature studies, the essential factors, such as coupling and friction, are rarely mentioned as it is difficult to build the precise dynamic model of the robotic manipulator. An adaptive backstepping sliding mode control is proposed to solve the precise trajectory tracking under external disturbances with complex environment, and the dynamic response characteristics of a two-link robotic manipulator are described in this paper. First, the Lagrange kinetic method is used to derive the precise dynamic model which includes the nonlinear factor with friction and coupling. Moreover, the dynamic model of two-link robotic manipulator is built. Second, the estimate function for the nonlinear part is selected, and backstepping algorithm is used for analyzing the stabilities of the sliding mode controller by using Lyapunov theory. Furthermore, the convergence of the proposed controller is verified subject to the external disturbance. At last, numerical simulation results are reported to demonstrate the effectiveness of the proposed method.
Geospatial Analysis of Urban Expansion Using Remote Sensing Methods and Data: A Case Study of Yangtze River Delta, China
Authors: Sun Wei , Shan Jie , Wang Zhiming , Wang Lei , Lu Dianmei , Jin Zhifeng , Yu Kun
Published: August 2020

Land use in the Yangtze River Delta in 2000 and 2017 was classified by the visual interpretation of Landsat satellite images. Then, these images were overlain with economic and physical geographical data to analyze the urban spatial expansion pattern and its physical constraints and socioeconomic influence factors by employing a combination of transition matrix analysis, expansion intensity indices, and equal-fan analysis. The results showed that from 2000 to 2017, there was a significant increase in built-up areas in the region, with rapid expansion in the core area. The northern and southern parts of the Yangtze River Delta experienced different urban spatial expansions, with a higher scale and rate in the cities along the Yangtze River and the coast in Jiangsu Province in the north than in Zhejiang Province in the south. Cities expanded towards megacities or hubs along the Yangtze River or the coast, indicating that urban expansion is influenced by preferential policies and urban planning factors in addition to the spillover effects of neighboring cities and the adjacency to seas or large rivers. Finally, urban expansion is significantly constrained by elevation, with cities at lower elevations or in flat terrain undergoing more rapid urban expansion and development.
Urban Traffic Travel Time Short-Term Prediction Model Based on Spatio-Temporal Feature Extraction
Authors: Kang Leilei , Hu Guojing , Huang Hao , Lu Weike , Liu Lan
Published: August 2020

In order to improve the accuracy of short-term travel time prediction in an urban road network, a hybrid model for spatio-temporal feature extraction and prediction of urban road network travel time is proposed in this research, which combines empirical dynamic modeling (EDM) and complex networks (CN) with an XGBoost prediction model. Due to the highly nonlinear and dynamic nature of travel time series, it is necessary to consider time dependence and the spatial reliance of travel time series for predicting the travel time of road networks. The dynamic feature of the travel time series can be revealed by the EDM method, a nonlinear approach based on Chaos theory. Further, the spatial characteristic of urban traffic topology can be reflected from the perspective of complex networks. To fully guarantee the reasonability and validity of spatio-temporal features, which are dug by empirical dynamic modeling and complex networks (EDMCN), for urban traffic travel time prediction, an XGBoost prediction model is established for those characteristics. Through the in-depth exploration of the travel time and topology of a particular road network in Guiyang, the EDMCN-XGBoost prediction model’s performance is verified. The results show that, compared with the single XGBoost, autoregressive moving average, artificial neural network, support vector machine, and other models, the proposed EDMCN-XGBoost prediction model presents a better performance in forecasting.
Effect of Moxibustion on Behavioral Changes and Expression of APP and BACE1 in Hippocampus of SAMP8 Mice
Authors: Ha Lue , Yang Bin , Wang Shaosong , An Yu , Wang Hao , Cui Yingxue
Published: August 2020

Objective. To observe the effect of moxibustion on cognitive function of aging mice, to observe the effect of moxibustion on protein and gene expression of APP metabolism pathway, and to explore the mechanism of action in moxibustion. Methods. 24 SAMP8 were randomly divided into 2 groups (12 in each group): moxibustion group and model group. 12 SAMR1 mice were used as blank controls. Mice in the moxibustion group were treated with moxibustion for 8 weeks, 10 minutes each time, 5 times a week, and for a total of 8 weeks. The model group and the blank group were treated with sham‐moxibustion. Behavior tests were used to detect the learning and memory ability of each group of mice. Immunohistochemical, western blot, and RT‐PCR were used to detect the protein and mRNA expression of APP and BACE1. Furthermore, the expressions of miR‐29 and miR‐101 were observed by RT‐PCR method to explore the mechanism of moxibustion at the genetic level. Results. In this study, relative to normal mice, we found that aging mice showed behavioral changes consistent with the onset of AD. However, moxibustion interventions were able to mitigate these effects to some degree in aging mice. In addition, moxibustion was proved to regulate APP metabolism pathway at protein and gene level through molecular biology tests. Conclusion. The data suggest that the effect of moxibustion intervention on cognitive function in aging mice is related to the regulation of genes and proteins involved in APP metabolism pathway; this may be a potential target for treating Alzheimer’s disease.
Dorsal Horn of Mouse Lumbar Spinal Cord Imaged with CLARITY
Authors: Sengul Gulgun , Liang Huazheng , Furlong Teri M. , Paxinos George
Published: August 2020

The organization of the mouse spinal dorsal horn has been delineated in 2D for the six Rexed laminae in our publication Atlas of the Spinal Cord: Mouse, Rat, Rhesus, Marmoset, and Human. In the present study, the tissue clearing technique CLARITY was used to observe the cyto‐ and chemoarchitecture of the mouse spinal cord in 3D, using a variety of immunohistochemical markers. We confirm prior observations regarding the location of glycine and serotonin immunoreactivities. Novel observations include the demonstration of numerous calcitonin gene‐related peptide (CGRP) perikarya, as well as CGRP fibers and terminals in all laminae of the dorsal horn. We also observed sparse choline acetyltransferase (ChAT) immunoreactivity in small perikarya and fibers and terminals in all dorsal horn laminae, while gamma aminobutyric acid (GABA) and glutamate decarboxylase‐67 (GAD67) immunoreactivities were found only in small perikarya and fibers. Finally, numerous serotonergic fibers were observed in all laminae of the dorsal horn. In conclusion, CLARITY confirmed the 2D immunohistochemical properties of the spinal cord. Furthermore, we observed novel anatomical characteristics of the spinal cord and demonstrated that CLARITY can be used on spinal cord tissue to examine many proteins of interest.
Potential Pharmacokinetic Drug‐Drug Interactions between Cannabinoids and Drugs Used for Chronic Pain
Authors: Vázquez Marta , Guevara Natalia , Maldonado Cecilia , Guido Paulo Cáceres , Schaiquevich Paula
Published: August 2020

Choosing an appropriate treatment for chronic pain remains problematic, and despite the available medication for its treatment, still, many patients complain about pain and appeal to the use of cannabis derivatives for pain control. However, few data have been provided to clinicians about the pharmacokinetic drug‐drug interactions of cannabinoids with other concomitant administered medications. Therefore, the aim of this brief review is to assess the interactions between cannabinoids and pain medication through drug transporters (ATP‐binding cassette superfamily members) and/or metabolizing enzymes (cytochromes P450 and glucuronyl transferases).
Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA‐Based Resting‐State fMRI Study
Authors: Xiong Hang , Guo Rong-Juan , Shi Hua-Wei
Published: August 2020

This study aimed to explore the role of the default mode network (DMN) and salience network (SN) in the assessment of pathophysiology of generalized anxiety disorder (GAD) through analyzing the characteristics of internal function connectivity (FC) and to investigate the relationship of FC with Hamilton anxiety (HAMA) scale scores in untreated GAD patients during a resting‐state functional magnetic resonance imaging (rs‐fMRI). Rs‐fMRI and HAMA scale scoring were performed in 51 GAD patients (31 GAD patients with liver stagnation transforming into fire type and 20 GAD patients with stagnation of liver‐Qi syndrome type) and 20 healthy controls. Spearman correlation analysis was performed to assess the association between HAMA scores and abnormal brain FC. Compared with healthy controls, the FC of the right medial prefrontal gyrus of the DMN and the right superior temporal gyrus of the SN increased significantly in the GAD patients (P < 0.001). However, the FC of the left middle frontal gyrus and bilateral medial superior frontal gyrus of the SN reduced significantly in the GAD patients with stagnation of liver‐Qi syndrome type as compared with healthy controls and GAD patients with liver stagnation transforming into fire type (P < 0.001). There was no relationship between abnormal brain FC and HAMA scores. In conclusion, the FC of the DMN and SN may be abnormal in the GAD patients at the resting state. The aberrant FC of some crucial brain regions of these networks may contribute to the pathophysiology of GAD.
3D Network Structural Poly (Aryl Ether Ketone)-Polybenzimidazole Polymer for High-Temperature Proton Exchange Membrane Fuel Cells
Authors: Jiang Junqiao , Qu Erli , Xiao Min , Han Dongmei , Wang Shuanjin , Meng Yuezhong
Published: August 2020

Poor mechanical property is a critical problem for phosphoric acid-doped high-temperature proton exchange membranes (HT-PEMs). In order to address this concern, in this work, a 3D network structural poly (aryl ether ketone)-polybenzimidazole (PAEK-cr-PBI) polymer electrolyte membrane was successfully synthesized through crosslinking reaction between poly (aryl ether ketone) with the pendant carboxyl group (PAEK-COOH) and amino-terminated polybenzimidazole (PBI-4NH2). PAEK-COOH with a poly (aryl ether ketone) backbone endows superior thermal, mechanical, and chemical stability, while PBI-4NH2 serves as both a proton conductor and a crosslinker with basic imidazole groups to absorb phosphoric acid. Moreover, the composite membrane of PAEK-cr-PBI blended with linear PBI (PAEK-cr-PBI@PBI) was also prepared. Both membranes with a proper phosphoric acid (PA) uptake exhibit an excellent proton conductivity of around 50 mS cm-1 at 170°C, which is comparable to that of the well-documented PA-doped PBI membrane. Furthermore, the PA-doped PAEK-cr-PBI membrane shows superior mechanical properties of 17 MPa compared with common PA-doped PBI. Based upon these encouraging results, the as-synthesized PAEK-cr-PBI gives a highly practical promise for its application in high-temperature proton exchange membrane fuel cells (HT-PEMFCs).