Feiyu Li¹, Siqi Zuo¹, Yongzhou Chi¹, Chunying Du¹, Zhaopeng Shen¹, Xihong Han^2,3, Xiaohui Wang^2,*, Peng Wang^1,*

Journal of Renewable Materials, Vol.8, No.11, pp. 1519-1529, 2020, DOI:10.32604/jrm.2020.011453 - 28 September 2020

Abstract Drought is one of the major abiotic stresses that affect plant growth and reduce agricultural productivity. Use of algal extract as a biostimulant is gaining increased attention from researchers. This study aimed to investigate the potential of Ulva prolifera extract (UE) as a biostimulant when enzymatically extracted under conditions of water deficit. UE treatments (0.02%, 0.06%, and 0.1%) significantly improved the shoot length, root length, and dry weight of roots after 120 h of drought stress relative to that in treatment with the negative control. An increase in catalase (CAT) and peroxidase (POD) activity was also More >

Shengwen Guo, Yuanyuan Tong, Liting Bai, Peiyao Zhang, Xin Duan^*, Jinping Liu^*

Congenital Heart Disease, Vol.15, No.5, pp. 275-285, 2020, DOI:10.32604/CHD.2020.011894 - 23 September 2020

Abstract Objective: Serum ferritin has been identified as a prognostic marker in patients with a variety of diseases. In the present study we aim to determine the prevalence of risk factors and outcomes for hyperferritinemia in children undergoing cardiac surgery with cardiopulmonary bypass for congenital heart defects. Methods: The serum ferritin levels of 457 children between the ages of twentyeight days and three years undergoing cardiopulmonary bypass surgery between June 1, 2017 and June 1, 2018 were analyzed. The prevalence of early postoperative hyperferritinemia was investigated; hyperferritinemia was defined as a ferritin level ≥250 ng/ml. Multivariable regression… More >

Bichen Che¹, Long Liu^2,*, Huali Zhang¹

Journal on Internet of Things, Vol.2, No.4, pp. 145-162, 2020, DOI:10.32604/jiot.2020.010035 - 22 September 2020

Abstract With the rapid development and widespread application of the IoT, the at-tacks against IoT vulnerabilities have become more complex and diverse. Most of the previous research focused on node vulnerability and its risk analysis. There is little information available about the importance of the location of the node in the system. Therefore, an estimation mechanism is proposed to assess the key node of the IoT system. The estimation of the key node includes two parts: one is the utilization relationship between nodes, and the other is the impact on the system after the node is… More >

XINGXING ZHU^1,2, TIANFENG HUA^1,2, MINGFEI WU³, JIATIAN WU^1,2, JIANCHAO HONG^1,2, MIN YANG^1,2,*

BIOCELL, Vol.44, No.3, pp. 431-441, 2020, DOI:10.32604/biocell.2020.010323 - 22 September 2020

Abstract Post-resuscitation myocardial dysfunction (PRMD) is the most severe myocardial ischemia-reperfusion injury (MIRI) and is characterized by difficult treatment and poor prognosis. Research has shown the protective effects of the rational use of ivabradine (IVA) against PRMD; however, the molecular mechanisms of IVA remain unknown. In this study, an ischemia-reperfusion injury (IRI) model was established using hypoxic chambers. The results demonstrated that pretreatment with IVA reduced IRI-induced cytotoxicity and apoptosis. IVA attenuated mitochondrial damage, eliminated excess reactive oxygen species (ROS), suppressed IRI-induced ATP and NAD⁺ , and increased the AMP/ATP ratio. We further found that IVA increased More >

HAZAEL RAMIRO CEJA-GÁLVEZ¹, ERANDIS DHENI TORRES-SÁNCHEZ¹, JUAN HERIBERTO TORRES-JASSO², ARTURO VILLALOBOS ORNELAS¹, JOEL SALAZAR-FLORES^1,*

BIOCELL, Vol.44, No.3, pp. 363-370, 2020, DOI:10.32604/biocell.2020.09147 - 22 September 2020

Abstract Paraoxonase-1 (PON1) is an important enzyme in various pathologies such as pesticide poisoning, diabetes, atherosclerosis, neuronal disorders, and cancer, due to its multifunctional activity since it acts on different metabolites. However, one of its main functions is the hydrolysis of organophosphate (OP) compounds from pesticides that cause fatal poisoning at the level of the central nervous system (CNS). The objective of this review was to investigate whether the structure, genetics, and function of PON1 affect the metabolism of organophosphate pesticides or other abnormalities. Information was selected from articles in the database PubMed–NCBI (https://www.ncbi.nlm.nih.gov/ pubmed/) with More >

SHYAM BADU¹, SANJAY PRABHAKAR^1,2, RODERICK MELNIK^1,3,*

BIOCELL, Vol.44, No.3, pp. 279-291, 2020, DOI:10.32604/biocell.2020.010916 - 22 September 2020

Abstract Photosynthesis is a fundamental process in biosciences and biotechnology that influences profoundly the research in other disciplines. In this paper, we focus on the characterization of fundamental components, present in pigment-protein complexes, in terms of their spectroscopic properties such as infrared spectra, nuclear magnetic resonance, as well as nuclear quadrupole resonance, which are of critical importance for many applications. Such components include chlorophylls and bacteriochlorophylls. Based on the density functional theory method, we calculate the main spectroscopic characteristics of these components for the Fenna-Matthews-Olson light-harvesting complex, analyze them and compare them with available experimental results. More >

Fei Yang^1,2,#, Xiaoqing Zhang^1,*,#, Yong Zhu³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 365-382, 2020, DOI:10.32604/cmes.2020.010798 - 18 September 2020

Abstract Heart arrhythmia is a group of irregular heartbeat conditions and is usually detected by electrocardiograms (ECG) signals. Over the past years, deep learning methods have been developed to classify different types of heart arrhythmias through ECG based on computer-aided diagnosis systems (CADs), but these deep learning methods usually cannot trade-off between classification performance and parameters of deep learning methods. To tackle this problem, this work proposes a convolutional neural network (CNN) model named PDNet to recognize different types of heart arrhythmias efficiently. In the PDNet, a convolutional block named PDblock is devised, which is comprised More >

Jiabin Wang^*, Kai Peng

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 345-363, 2020, DOI:10.32604/cmes.2020.011046 - 18 September 2020

Abstract In many existing multi-view gait recognition methods based on images or video sequences, gait sequences are usually used to superimpose and synthesize images and construct energy-like template. However, information may be lost during the process of compositing image and capture EMG signals. Errors and the recognition accuracy may be introduced and affected respectively by some factors such as period detection. To better solve the problems, a multi-view gait recognition method using deep convolutional neural network and channel attention mechanism is proposed. Firstly, the sliding time window method is used to capture EMG signals. Then, the… More >

Malik Javed Akhtar¹, Zahur Ahmad¹, Rashid Amin^{1, *}, Sultan H. Almotiri², Mohammed A. Al Ghamdi², Hamza Aldabbas³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2639-2663, 2020, DOI:10.32604/cmc.2020.011485 - 16 September 2020

Abstract A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data… More >

Tahir Abbas Khan¹, Sagheer Abbas¹, Allah Ditta², Muhammad Adnan Khan^{3, *}, Hani Alquhayz⁴, Areej Fatima³, Muhammad Farhan Khan⁵

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2591-2605, 2020, DOI:10.32604/cmc.2020.011892 - 16 September 2020

Abstract The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer… More >