bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonpenalty Machine Learning Constraint Handling Using PSO‐SVM for Structural Optimization
Authors: Rosso Marco M. , Cucuzza Raffaele , Di Trapani Fabio , Marano Giuseppe C.
Published: February 2021

Firstly formulated to solve unconstrained optimization problems, the common way to solve constrained ones with the metaheuristic particle swarm optimization algorithm (PSO) is represented by adopting some penalty functions. In this paper, a new nonpenalty‐based constraint handling approach for PSO is implemented, adopting a supervised classification machine learning method, the support vector machine (SVM). Because of its generality, constraint handling with SVM appears more adaptive both to nonlinear and discontinuous boundary. To preserve the feasibility of the population, a simple bisection algorithm is also implemented. To improve the search performances of the algorithm, a relaxation function of the constraints is also adopted. In the end part of this paper, two numerical literature benchmark examples and two structural examples are discussed. The first structural example refers to a homogeneous constant cross‐section simply supported beam. The second one refers to the optimization of a plane simply supported Warren truss beam. The obtained results in terms of objective function demonstrate that this new approach represents a valid alternative to solve constrained optimization problems even in structural optimization field. Furthermore, as demonstrated by the Warren truss beam problem, this new algorithm provides an optimal structural design which represents also a good solution from the technical point of view with a trivial rounding‐off that does not jeopardize significantly the optimization design process.
Estimation of Sea Level Change in the South China Sea from Satellite Altimetry Data
Authors: Liu Shanwei , Jiao Yue , Sun Qinting , Jiang Jinghui
Published: February 2021

The South China Sea is China’s largest marginal sea area, and it is rich in oil and gas mineral resources; thus, estimating its sea level changes is of practical significance. Based on linear and nonlinear sea level change characteristics, this paper decomposes 1992–2019 monthly mean sea level anomaly time series in the South China Sea into trend, seasonal, and random terms. This paper compares the seasonal autoregressive integrated moving average (SARIMA) and Prophet models for estimating the trend and seasonal terms and the long short-term memory (LSTM) and radial basis function (RBF) models for estimating random terms, and the more suitable models were selected. A Prophet-LSTM combined model was developed based on the accuracy results. This paper uses the combined model to study the effect of known data length on the experimental results and determines the best prediction duration. The results show that the combined model is suitable for short-term and medium-term estimations of 12–36 months. The accuracy at 36 months is 0.962 cm, which proves that the combined model has high application value for estimating sea level changes in the South China Sea.
Investigating the Impacts of Transaction Cost under a Tradable Credit Scheme with Heterogenous Users
Authors: Zhang Fang , Lu Jian , Hu Xiaojian , Liu Tenghui
Published: February 2021

In this paper, the impacts of transaction cost are investigated under a tradable credit scheme (TCS) considering user heterogeneity. Under the credit scheme, a certain number of credits are initially distributed among all the travelers for a specific O-D pair, and a link-specific number of credits are charged from travelers using that link. The scheme allows for free trading of the credits among travelers, and both the sellers and buyers need to pay an extra transaction cost, which is associated with trading volume. Travelers in the network are assumed to be heterogenous with a discrete value of time (VOT). For a given tradable credit scheme and discrete VOT set, the combined network user equilibrium (UE) and credit-trading market equilibrium (ME) are formulated as a variational inequality (VI) problem, and the conditions for the uniqueness of the network flow pattern and the credit price at equilibrium are established. A bisection-based trial-and-error method is proposed to solve the proposed VI problems. Based on the simulation results, the computational advantages of the proposed method are demonstrated. Then, an example network is presented to investigate the effect of transaction cost in different kinds of markets. It is found that the implementation of transaction cost can suppress trading volume and either elevate or drive down the equilibrium credit price. Besides, it is also found that users with the lowest VOT suffer the most from the increase in transaction cost, while those with the higher VOT are more likely to experience a reduction in travel cost with the implementation of TCS.
New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
Authors: Li Haiying , Wu Yulian , Wang Fenghui
Published: February 2021

The split feasibility problem

SFP

has received much attention due to its various applications in signal processing and image reconstruction. In this paper, we propose two inertial relaxed

C
Q

algorithms for solving the split feasibility problem in real Hilbert spaces according to the previous experience of applying inertial technology to the algorithm. These algorithms involve metric projections onto half-spaces, and we construct new variable step size, which has an exact form and does not need to know a prior information norm of bounded linear operators. Furthermore, we also establish weak and strong convergence of the proposed algorithms under certain mild conditions and present a numerical experiment to illustrate the performance of the proposed algorithms.
Properties of Gobi Aggregate and Sulfide‐Rich Tailings Cemented Paste Backfill and Its Application in a High‐Stress Metal Mine
Authors: Deng D. Q. , Liang Y. H. , Huangfu F. C.
Published: February 2021

This experiment studied the influence law of the strength of CPB affected by tailings content, Gobi aggregate content, cement content, and slurry concentration. The results show, for the CPB with concentration of 77%, when the addition amount of cement reaches 20%, the addition amounts of tailings and Gobi aggregate change within the ranges of 12∼24% and 56∼68%, respectively. The strength of CPB has been gradually improved when the addition amount of Gobi aggregates decreases and the addition amount of tailings increases. In this case, the slump of CPB changes within the range of 26.5 cm∼26.9 cm while the strength of CPB changes within the range of 4.021∼6.845 MPa. Considering future utilization value of tailings, the addition amount is finally set at 16% in production, and the addition amount of Gobi aggregate is set at 64%; namely, tailings: Gobi aggregate = 20 : 80. When the addition amount of cement is 20% (cement/(tailings + Gobi aggregates) = 1 : 4), the strength of CPB reaches 5.62 MPa which meets the production requirement. When the heading machine is used for tunnelling mine roadway in bottom backfill of VCR stope, no collapse or delamination occurs without support, showing good stability and integrity of backfill. When the adjacent stope ore is mined, the backfill with cement content of 11.1%, 14.3%, 20%, and 25% is exposed. In the process of mining, no collapse or delamination occurs. Therefore, the proportion of various backfill materials applied in production is reasonable, being verified by the experiment and field test.
Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures
Authors: Abu-Hamdeh Nidal H. , Daqrouq Khaled , Mebarek-Oudina Fateh
Published: February 2021

Implementation of improved instruments is used to detect damage in an accurate manner and fully analyze its characteristics. An aluminum beam has been used in this work to identify cracks by using a vibration technique. The simulation of frequency response feature was conducted using a finite element model to provide average measures of intensities of vibration. Two forms of wavelet packet transform (WPT) entropies Shannon and log energy were applied to identify the position, width, and size of the crack. The results showed that with an increase in crack depth, the amplitude also increased at certain crack sizes and for all crack positions. For two crack depths of 1.6 mm and 0.16 mm having the same crack size and position 12 mm and 60 mm, respectively, a 4.5% increase in amplitude was observed at a crack depth of 1.6 mm. Moreover, the amplitude varied inversely with the position. A 12.6% increase in amplitude was observed at a crack depth of 1.6 mm rather than 0.16 mm, while both depths occurred at the same crack position (75 mm) and size (20 mm). Experimental validation was performed on a cantilever beam with one crack. The maximum absolute error found was 7.5% for the crack position and 9.1% for the crack size. With the increase in crack depth, the obtained results decrease the stiffness of a beam in a single crack case.
Knowledge Graph Question and Answer System for Mechanical Intelligent Manufacturing Based on Deep Learning
Authors: Shi Miaoyuan
Published: February 2021

With the development of deep learning and its wide application in the field of natural language, the question and answer research of knowledge graph based on deep learning has gradually become the focus of attention. After that, the natural language query is converted into a structured query sentence to identify the entities and attributes in the user’s natural language query and the specified entities and attributes are used to retrieve answers to the knowledge graph. Using the advantage of deep learning in capturing sentence information, it incorporates the attention mechanism to obtain the semantic vector of the relevant attributes in the query and uses the parameter sharing mechanism to insert candidate attributes into the triple in the same model to obtain the semantic vector of typical candidates. The experiment measured that under the 100,000 RDF dataset, the single entity query of the MIQE model does not exceed 3 seconds, and the connection query does not exceed 5 seconds. Under the one-million RDF dataset, the single entity query of the MIQE model does not exceed 8 seconds, and the connection query will not be more than 10 seconds. Experimental data show that the system of knowledge-answering questions of engineering of intelligent construction based on deep learning has good horizontal scalability.
SynoExtractor: A Novel Pipeline for Arabic Synonym Extraction Using Word2Vec Word Embeddings
Authors: Al-Matham Rawan N. , Al-Khalifa Hend S.
Published: February 2021

Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. Recently, research has focused on extracting semantic relations from word embeddings since they capture relatedness and similarity between words. However, using word embeddings alone poses problems for synonym extraction because it cannot determine whether the relation between words is synonymy or some other semantic relation. In this paper, we present a novel solution for this problem by proposing the SynoExtractor pipeline, which can be used to filter similar word embeddings to retain synonyms based on specified linguistic rules. Our experiments were conducted using KSUCCA and Gigaword embeddings and trained with CBOW and SG models. We evaluated automatically extracted synonyms by comparing them with Alma’any Arabic synonym thesauri. We also arranged for a manual evaluation by two Arabic linguists. The results of experiments we conducted show that using the SynoExtractor pipeline enhances the precision of synonym extraction compared to using the cosine similarity measure alone. SynoExtractor obtained a 0.605 mean average precision (MAP) for the King Saud University Corpus of Classical Arabic with 21% improvement over the baseline and a 0.748 MAP for the Gigaword corpus with 25% improvement. SynoExtractor outperformed the Sketch Engine thesaurus for synonym extraction by 32% in terms of MAP. Our work shows promising results for synonym extraction suggesting that our method can also be used with other languages.
Estimation of Suspended Sediment Load Using Artificial Intelligence‐Based Ensemble Model
Authors: Nourani Vahid , Gokcekus Huseyin , Gelete Gebre
Published: February 2021

Suspended sediment modeling is an important subject for decision‐makers at the catchment level. Accurate and reliable modeling of suspended sediment load (SSL) is important for planning, managing, and designing of water resource structures and river systems. The objective of this study was to develop artificial intelligence‐ (AI‐) based ensemble methods for modeling SSL in Katar catchment, Ethiopia. In this paper, three single AI‐based models, that is, support vector machine (SVM), adaptive neurofuzzy inference system (ANFIS), feed‐forward neural network (FFNN), and one conventional multilinear regression (MLR) modes, were used for SSL modeling. Besides, four different ensemble methods, neural network ensemble (NNE), ANFIS ensemble (AE), weighted average ensemble (WAE), and simple average ensemble (SAE), were developed by combining the outputs of the four single models to improve their predictive performance. The study used two‐year (2016‐2017) discharge and SSL data for training and verification of the applied models. Determination coefficient (DC) and root mean square error (RMSE) were used to evaluate the performances of the developed models. Based on the performance measure results, the ANFIS model provides higher efficiency than the other developed single models. Out of all developed ensemble models, the nonlinear ANFIS model combination method was found to be the most accurate method and could increase the efficiency of SVM, MLR, ANFIS, and FFNN models by 19.02%, 37%, 9.73%, and 16.3%, respectively, at the verification stage. Overall, the proposed ensemble models in general and the AI‐based ensemble in particular provide excellent performance in SSL estimation.
Banana Production Trends, Cultivar Diversity, and Tissue Culture Technologies Uptake in Kenya
Authors: Wahome Caroline N. , Maingi John M. , Ombori Omwoyo , Kimiti Jacinta M. , Njeru Ezekiel M.
Published: February 2021

Banana (Musa acuminate L) is the world’s most widely known and distributed fruit and is a great contributor to food security in the developing world. However, many limiting factors affect banana farming, which cut across sociodemographic factors and agronomic and management practices. The current study was carried in three counties, including Kisii, Nyamira, and Embu. The study aimed to assess agronomic practices, banana production practices (main banana cultivars, source of planting materials), market information, and awareness of tissue culture bananas. Sample size was determined using the Snedecor and Cochran formula, and data were collected using structured questionnaires, observation, and face to face interviews from 90 smallholder farmers. Data obtained were analysed using Statistical Package for Social Sciences (SPSS) version 22.0, and Microsoft Excel was used to generate tables and graphs. Results indicated that banana production in Kisii, Nyamira, and Embu were limited by several factors including pests and diseases, limited access to quality disease-free planting materials, access to extension services, especially in Kisii and Nyamira, as well as access to agrochemicals. Declining production as well as limited market access also adversely affected production in these regions. Most farmers chose cultivars according to the availability of planting materials, suitability to the region, productivity, as well as market demand. The most predominant cultivar in Kisii and Nyamira was the Ng’ombe which was planted by about 90% and 73.3% of the respondents, respectively. In Embu, the most common cultivar was Israel and was planted by 96% of the respondents. More than 50% of the farmers in Kisii, Nyamira, and Embu cited lack of awareness of tissue-cultured bananas. None of the respondents in the study sites carried out any value addition processes on bananas thus limiting exploitation of a major revenue source. There was low adoption of tissue-cultured banana cultivation with the highest recorded number of respondents growing tissue-cultured banana reported in Embu (36%), followed by Kisii (10%) and lastly Nyamira (3.3%), as well as limited knowledge of tissue culture technology in three counties with 60% of the respondents in Kisii, Nyamira, and Embu indicating limited knowledge of the tissue-cultured banana varieties. This could potentially lead to a decline in production due to the use of potentially diseased planting materials. Creating awareness with the aid of relevant authorities on the potential benefits of utilizing disease-free tissue-cultured bananas and adopting low-cost tissue culture technology will significantly boost banana production in these regions and the country as a whole. The results of this study could be used by relevant stakeholders to increase banana productivity in the study areas.
Research on Collaborative Governance of Smart Government Based on Blockchain Technology: An Evolutionary Approach
Authors: Shan Shaonan , Duan Xia , Zhang Ying , Zhang Ting Ting , Li Hui
Published: February 2021

Smart government is an important means of optimizing government management, improving the government decision-making capacity, and pushing forward the public service. When the smart government process applies, the dire straits of collaborative governance among the different participants could not be ignored usually caused by maximizing their profits. Based on the current research, this paper introduces the blockchain technology into the smart government system and establishes a smart government platform architecture. Meanwhile, to analyse the evolutionary and stable strategies of the three parties under the blockchain technology, the evolutionary game model including functional departments, local governments, and end users as the main players is established on account of the bounded rationality. By examining the “blockchain + government service” in Beijing with the systemic dynamics theory, this paper changes the influencing factors simulated by changing the parameter assignment, to determine the evolutionary stable equilibrium under different external conditions. The results show that local government supervision plays a leading role in the process of collaborative governance of smart government based on blockchain technology; meanwhile, effective cost control is a key factor affecting the evolutionary stability strategy (ESS). Besides, the “decentralized” structure, “distrust” architecture, and “precision” mechanism of the blockchain are verified for the effect of the evolution process. Among them, precision service and flat management improve the possibility of collaborative governance, but the impact of the trust mechanism is not obvious. Therefore, the collaborative governance model of smart government based on blockchain technology is loaded with far-reaching significance for promoting the modernization of China’s governance capacity and governance system.
Neutrophil‐Lymphocyte Ratio as an Initial Screening Biomarker for Differential Diagnosis of Cushing’s Syndrome from Nonfunctional Adenoma in Patients with an Adrenal Mass
Authors: Wang Wei , Wang Jianing , Shen Cheng , Zhu Sainan , Gao Ying , Zhang Junqing
Published: February 2021

Objective. Assessing excess adrenal hormones is important in patients with adrenal mass. Current screening tests for excess cortisol hormones are complex, so it cannot be done sometimes due to the limited medical resources. The aim of the study was to evaluate whether the neutrophil‐lymphocyte ratio (NLR) can be used as an initial screening biomarker for Cushing’s syndrome (CS) in patients with an adrenal mass. Methods. This retrospective study included a total of 185 patients with CS and 185 patients with nonfunctional adrenal adenoma (matched 1 : 1 by sex, body mass index, and discharge date). The NLR was compared between the two groups. The association between NLR and serum and urinary cortisol concentrations was analyzed, and an NLR cut‐off value for CS screening was calculated. Results. NLR (3.38 (2.33, 5.45) vs. 2.13 (1.74, 3.00), P < 0.001) was significantly higher in the CS group than in the nonfunctional adenoma group. In CS patients, the NLR was positively associated with serum cortisol concentrations at 8 am, with 24‐hour urine free cortisol and with serum cortisol after a 1 mg dexamethasone suppression test (P < 0.001 each). An NLR cut‐off of 2.2 had a sensitivity of 80.0% and a specificity of 54.05%. The weighted Youden index for the NLR was similar to that of the 24‐hour urine free cortisol and late‐night serum cortisol tests, which are recommended initial tests for CS diagnosis. Conclusion. The NLR may be useful for initial screening for CS among patients with an adrenal mass as an easy and convenient marker.
Chinese Poplar Propolis Inhibits MDA-MB-231 Cell Proliferation in an Inflammatory Microenvironment by Targeting Enzymes of the Glycolytic Pathway
Authors: Li Junya , Liu Hui , Liu Xinying , Hao Shengyu , Zhang Zihan , Xuan Hongzhuan
Published: February 2021

Propolis is rich in flavonoids and has excellent antitumor activity. However, little is known about the potential effects of propolis on glycolysis in tumor cells. Here, the antitumor effects of propolis against human breast cancer MDA-MB-231 cells in an inflammatory microenvironment stimulated with lipopolysaccharide (LPS) were investigated by assessing the key enzymes of glycolysis. Propolis treatment obviously inhibited MDA-MB-231 cell proliferation, migration and invasion, clone forming, and angiogenesis. Proinflammatory mediators, including tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, and IL-6, as well as NLRP3 inflammasomes, were decreased following propolis treatment when compared with the LPS group. Moreover, propolis treatment significantly downregulated the levels of key enzymes of glycolysis–hexokinase 2 (HK2), phosphofructokinase (PFK), pyruvate kinase muscle isozyme M2 (PKM2), and lactate dehydrogenase A (LDHA) in MDA-MB-231 cells stimulated with LPS. After treatment with 2-deoxy-D-glucose (2-DG), an inhibitor of glycolysis, the inhibitory effect of propolis on migration was not significant when compared with the LPS group. In addition, propolis increased reactive oxygen species (ROS) levels and decreased mitochondrial membrane potential. Taken together, these results indicated that propolis targeted key enzymes of glycolysis to suppress the proliferation of MDA-MB-231 cells in an inflammatory microenvironment. These studies provide a molecular basis for propolis as a natural anticancer agent against breast cancer.
Photodynamic Therapy for Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis
Authors: Lin Jiao , Ni Guangcheng , Ding Tingting , Lei Shangxue , Zhong Liang , Liu Na , Pan Keran , Chen Ting , Zeng Xin , Xu Hao , Li Taiwen , Dan Hongxia
Published: February 2021

To assess the efficacy of photodynamic therapy (PDT) for oral squamous cell carcinoma (OSCC), literature on this topic from Embase, PubMed, and Web of Science were obtained and analyzed. The response and recurrence rates with 95% confidence intervals (CI) were calculated using the DerSimonia–Laird method. The pooled complete response (CR) rate from the included studies was 0.799 (95% CI: 0.708–0.867), while the overall response (OR) rate was 0.967 (95% CI: 0.902–0.989). The recurrence rate (RR) was 0.158 (95% CI: 0.090–0.264). A subgroup analysis of lesion site, photosensitizer, laser type, radiant exposure, and power density revealed no statistically significant differences. In general, PDT is effective for the treatment of early OSCC. Investigations on the influence of PDT on the survival of OSCC patients, optimization of the treatment regimen, and evaluation of response after treatment are still needed.
The Fractional Strain Influence on a Solid Sphere under Hyperbolic Two-Temperature Generalized Thermoelasticity Theory by Using Diagonalization Method
Authors: Youssef Hamdy M. , El-Bary Alaa A. , Al-Lehaibi Eman A. N.
Published: February 2021

This article constructs a mathematical model based on fractional-order deformations for a one-dimensional, thermoelastic, homogenous, and isotropic solid sphere. In the context of the hyperbolic two-temperature generalized thermoelasticity theory, the governing equations have been established. Thermally and without deformation, the sphere’s bounding surface is shocked. The singularities of the functions examined at the center of the world were decreased by using L’Hopital’s rule. Numerical results with different parameter fractional-order values, the double temperature function, radial distance, and time have been graphically illustrated. The two-temperature parameter, radial distance, and time have significant effects on all the studied functions, and the fractional-order parameter influences only mechanical functions. In the hyperbolic two-temperature theory as well as in one-temperature theory (the Lord-Shulman model), thermal and mechanical waves spread at low speeds in the thermoelastic organization.
Preparation and Kinetic Studies of Cross-Linked Chitosan Beads Using Dual Crosslinkers of Tripolyphosphate and Epichlorohydrin for Adsorption of Methyl Orange
Authors: Sabarudin Akhmad , Madjid Armeida D. R.
Published: February 2021

Preparation of cross-linked chitosan beads using dual crosslinkers of tripolyphosphate (TPP) and epichlorohydrin (ECH) for the adsorption and kinetic studies of methyl orange (MO) had been carried out. FTIR spectra showed that TPP could act as the protecting agent of the NH2 group of chitosan and ECH reacted with the primary hydroxyl group of chitosan. Various concentrations of TPP, ECH, and immersing time in the TPP solution for bead formation were studied. The effect of pH and kinetics of adsorption were investigated to define the mechanism of adsorption and rate-limiting step. As a result, pH 3, 10% (w/v) TPP, 5% (v/v) ECH, and 12 h immersing time in TPP were selected as the optimum conditions for preparing the beads as indicated by the highest adsorption amount of MO. The cross-linked chitosan beads’ adsorption capacity for MO under optimum condition was found to be 79.55 mg/g with the adsorption rate constant (k) of 1.29 × 10−3/min. Furthermore, it was found that a low concentration of ECH could maintain the stability of chitosan in acidic conditions, whereas the concentration of TPP and immersing time controlled pore size and morphology of chitosan beads. The mechanism of adsorption of MO was controlled by the pore and rigidity of cross-linked chitosan beads. Bulk diffusion acted as a rate-limiting step, and a high concentration of MO inhibited diffusion and adsorption itself.
A Framework for Human Activity Recognition Based on WiFi CSI Signal Enhancement
Authors: Yang Jieming , Liu Yanming , Liu Zhiying , Wu Yun , Li Tianyang , Yang Yuehua
Published: February 2021

With the advancement of wireless technologies and sensing methodologies, many studies have shown that wireless signals can sense human behaviors. Human activity recognition using channel state information (CSI) in commercial WiFi devices plays an important role in many applications. In this paper, a framework for human activity recognition was constructed based on WiFi CSI signal enhancement. Firstly, the sensitivity of different antennas to human activity was studied. An antenna selection algorithm was proposed, which can make a choice of the antenna automatically based on their sensitivity in accordance with different activities. Secondly, two signal enhancement approaches, which can strengthen the active signals and weaken the inactive signals, were proposed to extract the active interval caused by human activity. Finally, an activity segmentation algorithm was proposed to detect the start and end time of activity. In order to verify and evaluate the methods, extensive experiments have been conducted in real indoor environments. The experimental results have demonstrated that our solutions can eliminate a large number of redundant information brought by insensitive and inactive signals. Our research results can be put into use to improve recognition accuracy significantly and decrease the cost of recognition time.
A Hyper-Heuristic Heterogeneous Multisensor Node Scheme for Energy Efficiency in Larger Wireless Sensor Networks Using DEEC-Gaussian Algorithm
Authors: Aroba Oluwasegun Julius , Naicker Nalindren , Adeliyi Timothy
Published: February 2021

A wireless sensor network (WSN) is an intellect-sustainable network that comprises multiple spatially distributed sensor nodes and several sink nodes that collect data from sensors. WSNs remain an active research area in the literature due to challenging factors such as the selection of sensor location according to a given premise, finding optimal routing algorithm, and ensuring energy efficiency and consumption. Minimizing energy and prolonging the network lifetime in the WSNs are the focus of this research work. In the literature, a clustering approach is used in grouping sensor nodes into clusters and is seen as an effective technique used in optimizing energy consumption in WSNs. Hence, in this paper, we put forward a novel clustering-based approach by amalgamating the Gaussian elimination method with the Distributed Energy-Efficient Clustering to produce DEEC_Gaussian (DEEC_Gaus) to stabilize energy efficiency optimization in WSNs. We took the advantages of DEEC and Gaussian elimination algorithms to resolve energy efficiency problems in WSNs. DEEC presents attributes such as increased heterogeneity performance level, clustering stability in operation, and energy efficiency which helps to prolong network lifetime while the Gaussian elimination algorithm added an additional advantage to improve and optimize energy efficiency, to aggregate packets of operations performed in the network lifestyle of energy efficiency in WSNs. The simulations were carried out using MATLAB software with 1000 to 1500 nodes. The performance of the proposed work was compared with state-of-the-art algorithms such as DEEC, DDEEC, and EDEEC_E. The simulated results presented show that the proposed DEEC-Gauss outperformed the three other conventional algorithms in terms of network lifetime, first node dead, tenth node dead, alive nodes, and the overall timing of the packets received at the base station. The results showed that the proposed hyper-heuristic heterogeneous multisensor DEEC-Gauss algorithm presented an average percentage of 3.0% improvement for the tenth node dead (TND) and further improvement of 4.8% for the first node dead (FND). When the performance was compared to the state-of-the-art algorithms in larger networks, the overall delivery was greatly improved and optimized.
Network Pharmacology Strategy to Investigate the Pharmacological Mechanism of Siwu Decoction on Primary Dysmenorrhea and Molecular Docking Verification
Authors: Jiang Dandan , Wang Xiaoyan , Tian Lijun , Zhang Yufeng
Published: February 2021

Objective. To study the pharmacological mechanisms of Siwu decoction (SWD) on primary dysmenorrhea (PDM) and verify with molecular docking. Methods. The  Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to acquire the active compounds and their corresponding target genes. The GeneCards database was utilized in the search for target genes that were associated with PDM. The intersection genes from the active target genes of SWD and those associated with PDM represented the active target genes of SWD that act on PDM. The Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were both carried out by RGUI 3.6.1 and Cytoscape 3.6.0 software. Cytoscape was also utilized for creating a compound-target network, and a protein-protein interaction (PPI) network was created through the STRING database. Molecular docking simulations of the macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Results. We identified 14 active compounds as well as 97 active target genes of SWD by using the TCMSP. We compared the 97 active target genes of SWD to the 299 target genes related to PDM, and 23 active target genes for SWD that act on PDM which correlated with 11 active compounds were detected. The compound-target network as well as the PPI network were created, in addition to selecting the most essential compounds and their targets in order to create a key compound-target network. The most essential compounds were kaempferol, beta-sitosterol, stigmasterol, and myricanone. The key targets were AKT1, PTGS2, ESR1, AHR, CASP3, and PGR. Lastly, molecular docking was used to confirm binding of the target with its corresponding compound. Conclusion. The pharmacological mechanisms of SWD that act on PDM were investigated, and the active compounds in the SWD for treating PDM were further verified.
A Novel Sensor for In Situ Detection of Freeze‐Thaw Characteristics in Plants from Stem Temperature and Water Content Measurements
Authors: Gao Chao , Tian Hao , Zhao Yandong
Published: February 2021

Freezing is a typical abiotic stress on plants, which can induce physiological damages of plants. A better understanding of plant freeze‐thaw characteristics contributes to solving some hot issues in plant physiology, such as cold resistance and cold acclimation. This article presents a novel sensor for in situ detection of freeze‐thaw characteristics in plants based on stem temperature and water content. The measuring circuit of stem temperature was designed based on constant current source and platinum resistance. The measuring circuit of stem water content was designed based on standing wave ratio and the dielectric properties of stem tissue. The temperature resolution of the compound sensor is less than 0.1°C. The MAE and RMSE of temperature measurement are approximately 0.57°C and 0.65°C, respectively. The volumetric water content resolution of the compound sensor is less than 0.05%. The MAE and RMSE of volumetric water content measurement are approximately 1.59% and 1.81%, respectively. Moreover, a mathematical model for describing the freeze‐thaw characteristics of plant stem was established and solved based on the compound sensor. Then, some freeze‐thaw indicators including stem water content, ice content, freezing depth, freezing velocity, thawing depth, and thawing velocity were solved and used to interpret the freeze‐thaw rules of plant stem. It can be concluded that the freeze‐thaw velocity is closely related to the physicochemical properties of plant stem which also change dynamically in the freeze‐thaw cycle.
lncRNA MALAT1 Regulates Mouse Granulosa Cell Apoptosis and 17β‐Estradiol Synthesis via Regulating miR‐205/CREB1 Axis
Authors: Sun Lei , Zhang Pengju , Lu Wenfa
Published: February 2021

Metastasis‐associated lung adenocarcinoma transcript 1 (MALAT1), a known long noncoding RNA, was reported to play a crucial role in follicular growth and ovarian disease. However, the physiological function of MALAT1 in mouse granulosa cells (mGCs) remains largely unclear. The aims of this study were to determine the biological function and molecular mechanism of MALAT1 in mGCs. We knocked down MALAT1 in mGCs by using siRNA against MALAT1. We found that knockdown of MALAT1 promoted apoptosis and caspase‐3/9 activities in mGCs. Enzyme‐linked immunosorbent assay demonstrated that knockdown of MALAT1 significantly decreased the production of estradiol (E2) and progesterone (P4) in mGCs. Mechanistically, MALAT1 serves as a competing endogenous RNA (ceRNA) to sponge microRNA‐205 (miR‐205), thereby facilitating its downstream target of cyclic AMP response element‐ (CRE‐) binding protein 1 (CREB1). Furthermore, CREB1 overexpression or miR‐205 downregulation partially recovered the effect of MALAT1 depletion in mGCs. In summary, these findings suggested that MALAT1 regulated apoptosis and estradiol synthesis of mGCs through the miR‐205/CREB1 axis.
Efficient Topology for DC-DC Boost Converter Based on Charge Pump Capacitor for Renewable Energy System
Authors: Malik Muhammad Zeeshan , Tirth Vineet , Ali Amjad , Farooq Ajmal , Algahtani Ali , Verma Rajesh , Islam Saiful , Irshad Kashif , Abdalla Ahmed N.
Published: February 2021

In an attempt to meet the global demand, renewable energy systems (RES) have gained an interest in it due to the availability of the resources, especially solar photovoltaic system that has been an importance since many years because of per watt cost reduction, improvement in efficiency, and abundant availability. Photovoltaic system in remote and rural areas is very useful where a grid supply is unavailable. In this scenario, power electronic converters are an integral part of the renewable energy systems particularly for electronic devices which are operated from renewable energy sources and energy storage system (fuel cell and batteries). In this article, a new topology of charge pump capacitor (CPC) which is based on high voltage gain technique DC-DC boost converter (DCBC) with dynamic modeling is proposed. To testify the efficacy of the introduced topology, a prototype has been developed in a laboratory, where input was given 10VDC and 80VDC output voltage achieved at the load side. Furthermore, the experimental result shows that the voltage stress of MOSFET switches is very less in comparison with the conventional boost converter with the same parameters as the proposed converter.
The Relationship between Serum Amyloid A Level and Cognitive Dysfunction in Patients with Vascular Dementia: Preliminary Findings
Authors: Xu Min , He Xiao-ying , Huang Pan
Published: February 2021

Objective. This study was aimed at investigating the relationship between serum amyloid A (SAA) levels and cognitive dysfunction in patients with vascular dementia (VAD). Methods. Using cross‐sectional research methods, 146 patients with VAD were selected as the VAD group and 70 normal people were selected as the NC group. Upon admission, the clinical and biochemical characteristics of the two groups of study subjects were collected, and the MMSE scale was used to assess cognitive function. A sandwich enzyme‐linked immunosorbent assay was used to detect SAA levels. Results. There was no significant difference in clinical data and biochemical characteristics in the VAD group (p > 0.05). Compared with the VAD group, the NC group has a higher level of education (p < 0.05). The SAA level of the VAD group was higher than that of the NC group, and there was a significant difference (p < 0.05). Spearman correlation analysis showed that SAA and MMSE in the VAD group were negatively correlated. Further multiple regression analysis showed that the serum amyloid A level is an independent risk factor for cognitive dysfunction in VAD patients. Conclusion. The level of SAA in VAD patients is significantly increased, which can be used as a potential peripheral blood marker to predict cognitive impairment in VAD patients.
Assessing Security of Software Components for Internet of Things: A Systematic Review and Future Directions
Authors: Liao Zitian , Nazir Shah , Khan Habib Ullah , Shafiq Muhammad
Published: February 2021

Software component plays a significant role in the functionality of software systems. Component of software is the existing and reusable parts of a software system that is formerly debugged, confirmed, and practiced. The use of such components in a newly developed software system can save effort, time, and many resources. Due to the practice of using components for new developments, security is one of the major concerns for researchers to tackle. Security of software components can save the software from the harm of illegal access and damages of its contents. Several existing approaches are available to solve the issues of security of components from different perspectives in general while security evaluation is specific. A detailed report of the existing approaches and techniques used for security purposes is needed for the researchers to know about the approaches. In order to tackle this issue, the current research presents a systematic literature review (SLR) of the present approaches used for assessing the security of software components in the literature by practitioners to protect software systems for the Internet of Things (IoT). The study searches the literature in the popular and well-known libraries, filters the relevant literature, organizes the filter papers, and extracts derivations from the selected studies based on different perspectives. The proposed study will benefit practitioners and researchers in support of the report and devise novel algorithms, techniques, and solutions for effective evaluation of the security of software components.
Determining Optimal Cutoffs for Exhaled Carbon Monoxide and Salivary Cotinine to Identify Smokers among Korean Americans in a Smoking Cessation Clinical Trial
Authors: Kim Sun S. , Kim Seongho , Gona Philimon N. , Ward Kenneth
Published: February 2021

Introduction. It is critical to accurately identify individuals who continue to smoke even after treatment, as this may prompt the use of more intensive and effective treatment strategies to help them attain complete abstinence. Aims. This study examined optimal cutoffs for exhaled carbon monoxide (CO) and salivary cotinine to identify smokers among Korean Americans in a smoking cessation clinical trial. Methods. CO and cotinine were measured three to four times over 12 months from the quit day. Statistical analysis was conducted using Receiver Operating Characteristic (ROC) curves. Results. A CO cutoff of 5 parts per million provided robust sensitivity (80.8-98.3%) and perfect specificity (100%), and a salivary cotinine cutoff of level 2 (30-100 ng/ml) provided the best sensitivity (91.2-95.6%) and perfect specificity (100%). Using these cutoffs, the agreement between self-reports and the two biomarkers ranged from 88.6% to 97.7%. The areas under ROC curves (AUCs) of exhaled CO ranged from 0.90 to 0.99, all of which were significant (all p values < 0.001), and the AUCs of salivary cotinine ranged from 0.96 to 0.98 (all p values < 0.001). Conclusion. Exhaled CO and salivary cotinine are complementary, and they should be used together to verify smoking abstinence for smokers in a clinical trial.
Intelligent Extremum Surrogate Modeling Framework for Dynamic Probabilistic Analysis of Complex Mechanism
Authors: Liu Jia-Qi , Feng Yun-Wen , Xue Xiao-Feng , Lu Cheng
Published: February 2021

The reliability analysis of complex mechanisms involves time-varying, high-nonlinearity, and multiparameters. The traditional way is to employ Monte Carlo (MC) simulation to achieve the reliability level, but this method consumes too much computing resources and is even computationally intractable. To improve the efficiency and accuracy of dynamic probabilistic analysis of complex mechanisms, an intelligent extremum surrogate modeling framework (IESMF, short for) is proposed based on extremum response surface method (ERSM), combined with artificial neural network (ANN) method and an improved optimize particle swarm optimization (PSO) method. Hereinto, the ERSM is used to simplify the dynamic process of output response to the extremum value of transient analysis; ANN is applied to establish a mathematical model between input variables and response, and the improved PSO method is utilized in search of initial weights and thresholds of the model. The effectiveness of the IESMF is demonstrated to perform the Rack-and-pinion steering mechanism (RPSM) reliability analysis. The results show that when the allowable value of gear root stress is equal to 850 MPa, the RPSM has a reliability degree of 0.9971. Through the validation process, it is illustrated that IESMF is accurate and efficient in dynamic probabilistic analysis of complex mechanisms, and its comprehensive performance is better than the MC method and ERSM. The research effort offers new ideas for the reliability estimation of a complex mechanism, thus enriching the method and theory of mechanical reliability design.
Experimental Investigation on the Load‐Carrying Capacity of Steel‐to‐Laminated Bamboo Dowel Connection I: Single Fastener with Slotted‐In Steel Plate under Tension
Authors: Cui Zhaoyan , Tu Liuhui , Xu Ming , Chen Zhongfan , Xu Qingfeng
Published: February 2021

The dowel‐type connection is widely applied in timber and bamboo structures. It is ambiguous regarding the calculation method of engineered bamboo connections completely referred to the timber design codes. The steel‐to‐laminated bamboo dowel connections with slotted‐in steel plate tests were conducted to investigate the mechanical performance under tension based on the ASTM‐D5652‐15. The effects of the thickness, dowel diameter, and end distance on the yield load, ultimate load, initial stiffness, and ductility of the connections were studied. The difference in the yield load for different end distance is negligible. With the same thickness of the connections, the lower the thickness to dowel diameter, the larger the load‐carrying capacity. The three typical yield modes and corresponding load‐displacement curves of the connections are observed. By considering the rigid‐plastic model, the theoretical equation for the connections is proposed and proven to fit well with the experimental results. It presents a better prediction for the load‐carrying capacity of steel‐to‐laminated bamboo dowel connections with slotted‐in steel plate.
In‐Line and Cross‐Flow Coupling Vibration Response Characteristics of a Marine Viscoelastic Riser Subjected to Two‐Phase Internal Flow
Authors: Chang Xueping , Fan Jinming , Yang Wenwu , Li Yinghui
Published: February 2021

This paper studies the in‐line and cross‐flow coupling vibration response characteristics of a marine viscoelastic riser subjected to two‐phase internal flow and affected by the combined effects of several parameters including the volume fraction of gas phase, sea water flow velocity, viscoelastic coefficient of the marine riser, axial tension amplitude, and the in‐line and cross‐flow coupling effect taking into account both the geometric and hydrodynamic nonlinearities. On the base of extended Hamilton’s principle for open systems, the dynamic equations of the marine viscoelastic riser subjected to the axial tension and gas‐liquid‐structure interaction are established. Two distributed and coupled van der Pol wake oscillators are utilized to model the fluctuating lift and drag coefficients, respectively. The finite element method is adopted to directly solve the highly coupled nonlinear fluid‐structure interaction equations. Model validations are firstly performed through comparisons with the published experimental data and numerical simulation results, and the characteristic curves of the in‐line and cross‐flow vibration pattern, the in‐line and cross‐flow displacement trajectories, the in‐line and cross‐flow space‐time response of displacement, and the in‐line and cross‐flow space‐time response of stress versus different parameters are obtained, respectively. The results show that the volume fraction of gas phase, sea water flow velocity, viscoelastic coefficient of marine riser, axial tension amplitude, the in‐line and cross‐flow coupling effect, and multiphase internal flow velocity have significant influences on the dynamic response characteristics of the marine viscoelastic riser. Furthermore, the maximum displacements and stresses of the marine viscoelastic riser can be increased or decreased depending on the internal flow velocity, and the critical internal flow velocities result in the increase of mode order for different cross‐flow velocities. It is also demonstrated that appropriate viscoelastic coefficients are very important to effectively suppress the maximum displacements and stresses.