bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Data Gathering Algorithm For Wireless Sensor Networks Using Artificial Intelligence
Authors: Ch Swapna , Budyal Vijayashree R 
Published: June 2021

Abstract
The most challenging task in wireless sensor network is energy efficiency, as energy is the major constraint in the wireless sensor network to improve the life time of the network. Hence developing algorithms to improve network life time is the major task. In wireless sensor network most of the energy is wasted while gathering the data, hence an efficient algorithm which conserves energy has to be designed. Thus our proposed work A Novel Data Gathering Algorithm for Wireless Sensor Networks using Artificial Intelligence (NDGAI) uses mobile element and deals with the conservation of energy while gathering the data. Appropriate clustering, cluster leader selection and proper path determination of mobile element helps to conserve energy and improve the over all network life time. In our proposed work initially the clusters are forged by using Amended Expectation Maximization(AEM) algorithm, which is the maximum likelihood estimate. It is used along with Gap statistic method to find the optimal number of clusters. AEM algorithm helps in obtaining the centres of the cluster with maximum number of nodes near the cluster centres. For each cluster, Cluster Leader (CL) is selected by using Fuzzy Logic. Fuzzy logic selects the node which is near to the cluster centre by using parameters such as Closeness of node to the Cluster Centroid, direction of node towards base station, number of Neighbouring Nodes. After the CL’s are determined, to reduce the path length virtual points(VP) are selected so that mobile element reaches this virtual point and collects the data. These VP’s are selected only when the CL has data in it. The mobile elements can reach these virtual points intelligently by using optimal path,that is obtained by using hybrid of Particle Swarm Optimization and Artificial Bee Colony algorithm. Thus the mobile element travels in the optimal path and gathers the data from the entire network intelligently and efficiently with less amount of energy. With this approach the performance and life time of the network is improved while gathering the data. The simulation results are compared with Scalable Grid-Based Data Gathering Algorithm for Environmental Monitoring Wireless Sensor Networks (SGBDN) and proved that the proposed method is better than SGBDN .
Robust H∞ Control of Networked System In Microgrid Under Random Packet Loss
Authors: Feng Yiwei , Ma Jing , Wang Xin 
Published: June 2021

Abstract
The desire for sustainable development has led to the advancement of renewable energy generation through microgrids, and the control and stability of microgrids pose serious challenges to the popularization of microgrids. This article focuses on the stability and performance of the microgrid, and due to its limited channel bandwidth and other factors, may result in the loss of random packets from the sensor to the controller and from the controller to the actuator. To solve the problem, this paper designed a feedback controller based on the observer and robust H∞ control method and has established Bernoulli packet loss model. The proposed controller enables the networked control system robust exponential stability in the sense of mean square. Finally, the correctness and effectiveness of the proposed controller is verified by MATLAB simulation.
Efficient Classification of Horizontal And Vertical EOG Signals For Human Computer Interaction
Authors: Abdel-Samei Abdel-Gawad A. , S.Ali Ahmed , El-Samie Fathi E. Abd , M.Brisha Ayman 
Published: June 2021

Abstract
Human-computer interaction (HCI) using Electrooculography (EOG) has been a growing area of research in recent years. The HCI provides communication channels between the human and the external device. Today, EOG is one of the most important biomedical signals for measuring and analyzing the direction of eye movements. The EOG is used to produce both activities in vertical and horizontal directions of human eye movements. In this paper, different human eye movement tasks from vertical and horizontal directions are studied. The dataset of EOG signals were obtained from Electroencephalography (EEG) electrodes from 27 healthy people, 14 males and 13 females. This process resulted from two dipole signals, the vertical-EOG signals and the horizontal-EOG signals. These signals were filtered by band-pass at 0.5–5Hz. A total of 54 datasets from these 27 healthy individuals, each lasting 30 seconds, were given. The Bo-Hjorth parameter was implemented for feature extraction on the preprocessed EOG signals. For classification, Decision Tree (DT), K-Nearest Neighbor (KNN), Ensemble Classifier (EC), Kernel Naive Bayes (KNB) and Support Vector Machine (SVM)) were utilized. The obtained results reveal that the best classifiers on horizontal and vertical signals are the Support Vector Machine (SVM), the Cosine KNN and the Ensemble Subspace Discriminant with having 100% percentage accuracies. Through designing the proposed algorithm for feature extraction, the highest performance of classification can be obtained for rehabilitation purposes and other applications that help the handicapped to take decisions for better life quality, by providing possible human interaction with a computer.
A Novel Group Mobility Model for Software Defined Future Mobile Networks
Authors: A Sureshkumar , D Surendran 
Published: June 2021

Abstract
Nowadays, a massive amount of data leads to cause network traffic and inflexible mobility in future mobile networks. A new Group Mobility Model (GMM) named MoMo is introduced that addresses the issue of the aforementioned problems. Even though, software defined network (SDN) is functional with network-rooted mobility protocols that enhance the network efficiency. Some existing network-rooted mobility administration methods still undergo handover delay, packet loss, and high signaling cost through handover processing. In this research work, SDN-based fast handover for GMM is proposed. Here, the neighbor number of evolving node transition probabilities of the mobile node (MN) and their obtainable resource probabilities are estimated. This makes a mathematical framework to decide the preeminent number of the evolving nodes and then allot these to mobile nodes virtually with all associations finished by the exploit of Open-Flow tables. The performance examination demonstrates that the proposed SDN rooted GMM technique has the enhanced performance than the conventional handover process and further technique by handover latency, signaling cost, network throughput, and packet loss.
A Novel Optimized Deep Learner with Lightweighted Encryption-Based Speaker Verification
Authors: Rathinaraja Sujiya , Eswaran Chandra 
Published: June 2021

Abstract
In the modern digitalized world, Speaker verification (SV) system is essential for authorizing the client’s credentials. To design an effective SV system, MGWOVSW-CAES-GMM system has been proposed. In this system, the Modified Grey Wolf Optimization (MGWO) technique was employed to optimize the variable sliding window size, FMPM features and training variables. The optimized features were watermarked and encrypted using a Chaotic-based Advanced Encryption Standard (CAES). Once the encryption process was completed, the encrypted features were forwarded to the recipient who executes the decryption and de-watermarking processes. At last, the decrypted features were classified using Gaussian Mixture Model (GMM) classifier. Conversely, MGWO has poor convergence rate and ineffective searching results. Hence, this article proposes an EEHOVSW-CAES-GMM system in which Enhanced Elephant Herding Optimization (EEHO) algorithm is applied instead of MGWO. On the contrary, the computational complexity of GMM classifier is high and its efficiency is less while increasing the number of features. For this reason, a Deep Neural Network (DNN) classifier is employed instead of GMM for recognizing the decrypted features and authorize the speaker’s identity. Besides, the parameters utilized in DNN topology are optimized using two different systems such as MGWOVSW-CAES-DNN and EEHOVSW-CAES-DNN for reducing the computational complexity and increasing the classification accuracy effectively when using more number of features. By using these classifiers, the speaker’s identity is verified and the attacks during the transmission are prevented with the highest security level.
Characterization of Biosurfactant From Pseudomonas Stutzeri SJ3 for Remediation of Crude Oil-Contaminated Soil
Authors: Harikrishnan Sekar , Jayalakshmi Singaram , Alsalhi Mohamad S. , Kartick Alager , Devanesan Sandhanasamy , Rajasekar Aruliah 
Published: June 2021

Abstract
In the present work, production of biosurfactant was studied from the bacterial strains isolated from the soil samples collected from oil contaminated sites in Karaikal ONGC, Puducherry, India. Six morphologically different hydrocarbonoclastic bacterial strains (SJ1-SJ6) isolated on oil agar plates were further screened for biosurfactant production. Based on the screening methods results of 26 mm oil displacement zone, positive results of drop collapse test, 68.14% emulsification index (E24) and 79.2% of bacterial adherence percentage, the isolate SJ3 was selected as the most potent strain and it was identified as P. stutzeri using standard biochemical and 16S rRNA gene sequencing-based methods. Optimization of the P. stutzeri strain showed 36 h incubation, 150 rpm agitation, pH 7.5, 37oC, 1% salinity, 2% glucose as carbon source and 1% yeast extract as nitrogen source were the ideal conditions for growth and the biosurfactant production was found to be growth dependent. The crude biosurfactant showed broad range of antibacterial activity against the bacterial pathogens tested. The P. stutzeri isolated from oil spill site showed biosurfactant with antibacterial activities.
Urban Environmental Legislation and Green Innovation
Authors: Zhang Fan , Han Qinqin , Shao Junjie 
Published: June 2021

Abstract
With the panel data of 218 prefecture-level cities from 2003 to 2017, this paper empirically tested whether urban environmental legislation realized Porter Hypothesis(PH) in China. After a series of model estimation and robustness tests, the results show that urban environmental legislation increased the number of local green patents, which means that the weak Porter Hypothesis was established. However, the urban environmental legislation did not lead to an increase in green total factor productivity(GTFP). In other words, the strong version of PH did not hold. Further analysis shows that urban environmental legislation led to the decline of GTFP and the increase of green patents in the west of China, but not in the east and central cities. Besides, the legislation did not promote GTFP improvement through green innovation in the short term, which means it did not realize process compensation.
Integrated static modelling and dynamic simulation framework for CO2 storage capacity in upper Qishn Clastics, S1A reservoir, Yemen
Authors: AlRassas Ayman Mutahar , Thanh Hung Vo , Ren Shaoran , Sun Renyuan , Hai Nam Le Nguyen , Lee Kang-Kun 
Published: June 2021

Abstract
Carbon dioxide (CO2) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate the large-scale anthropogenic CO2 emission into the atmosphere. In this context, CO2 sequestration into depleted oil reservoirs is a practical approach as it boosts the oil recovery and facilitates the permanent storing of CO2 into the candidate sites. However, the estimation of CO2 storage capacity in subsurfaces is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO2 storage capacity in a clastic reservoir, S1A filed, Masila basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO2lab) for reducing the uncertainty assessment of CO2 storage capacity. Also, there is a significant difference between static and dynamic CO2 storage capacity. The static CO2 storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO2 simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work was found that the upper Qinshn sequence could store 15.64 Million tons without leakage. This result demonstrates that the potential of CO2 utilization is not only in this specific reservoir, but the further CO2 storage for the other clastics reservoirs is promising in the Masila Basin, Yemen.
Socio-ecological Systems Analysis of the Prevention and Control of Dengue in two Districts of Dar es Salaam City, Tanzania
Authors: Mboera Leonard E.G. , Sindato Calvin , Mremi Irene R. , Rumisha Susan F. , George Janeth , Ngolongolo Renfrid , Misinzo Gerald , Karimuribo Esron D. , Rweyemamu Mark M. , Haider Najmul , Hamid Muzamil Abdel , Kock Richard 
Published: June 2021

Abstract
Background: Since 2010, Tanzania has been experiencing frequent outbreaks of dengue. The objective of this study was to carry out a socio-ecological systems analysis and assess the readiness in dengue prevention and control in Kinondoni and Ilala districts of Dar es Salaam City, Tanzania.Methods: Twenty-seven key district officials responsible for human and animal health were involved in a socio-ecological systems framework analysis as regards to dengue. In addition, the readiness of the districts to respond to dengue outbreaks and the performance of the disease surveillance system was assessed.Results: The two districts were characterized by both urban and peri-urban ecosystems, with a mixture of planned and unplanned settlements which support breeding and proliferation of Aedes mosquitoes. The results indicate inadequate levels of readiness in the management and control of dengue outbreaks, in terms of clinical competence, diagnostic capacities, surveillance system and control/prevention measures. Mosquito breeding sites, especially discarded automobile tyres, were reported to be scattered in the districts. Constraining factors in implementing disease surveillance included both intrapersonal and interpersonal factors, lack of case management guidelines, difficult language used in standard case definitions, inadequate laboratory capacity, lack of appropriate rapid response teams, inadequate knowledge on outbreak investigation and inadequate capacities in data management. Conclusion: The two districts had limited readiness in the management and control of dengue, in terms of clinical competence, diagnostic capacities, surveillance system and prevention and control measures. These challenges require the immediate attention by the authorities, as they compromise the effectiveness of the national strategy for community health support.
Deterioration Characteristics and Energy Mechanism of Red-Bed Rocks Subjected to Drying-Wetting Cycles
Authors: Huang Kai , Zha Fusheng , Kang Bo , Sun Xianguo , Li Yunfeng , Su Jingwen 
Published: June 2021

Abstract
The red-bed rocks were chosen and studied by using uniaxial compressive experiment and scanning electron microscopy to investigate the effect of drying-wetting (D-W) cycles on the mechanical properties and microstructural characteristics of red-bed rock. Additionally, the energy mechanism of specimens subjected to drying-wetting cycles was also explained. Experimental results showed that, the stress-strain could be divided into four characteristic stages in the compression failure process. After subjecting to cycles of D-W, the stress-strain curve gradually changed from softening to hardening. At the same time, uniaxial compression strength (UCS) and elastic modulus dropped obviously, while Poisson’s ratio gradually raised. Microstructural analysis results indicated that the microstructure of the specimen surface was no longer dense and uniform, and the porosity of tested specimens significantly increased with D-W cycles increasing. As the porosity grew, UCS and elastic modulus gradually declined. According to the first law of thermodynamics, the process of rock failure was an event of energy transfer and conversion. As the number of D-W cycles increased, the energy density of specimens all present linear fell. From the perspective of the theory of energy dissipation, the dissipated energy was essential for rock failure, and closely related to the strength of the specimen. With D-W cycles increasing, the specimens were more prone to failure, and the dissipated energy required for failure decreased gradually.
Protective Effects of Rheum Turkestanicum Janischagainst Diethylnitrosamine-Induced Hepatocellular Carcinoma in Rats
Authors: Ghorbani Ahmad , Hosseini Azar , Mirzavi Farshad , Hooshmand Sara , Amiri Mohammad Sadegh , Jafarian Amir Hosein , Hasanpour Maedeh , Iranshahi Mehrdad , Soukhtanloo Mohammad , Khalife Ahmad , Rajabian Arezoo 
Published: June 2021

Abstract
Aim of the study Hepatocellular carcinoma (HCC) is common cancer that causes many deaths worldwide. Recent studies have reported anti-cancer effects of R. turkestanicum against various cell lines including leukemia cervical tumor, and breast cancer. In this study, we aimed to identify the effect of R. turkestanicum against diethylnitrosamine (DEN)-induced HCC. Methods Wistar rats were divided into four groups of control, DEN, DEN + 100 mg/kg or 400 mg/kg of hydroethanolic extract of the plant roots. Results After four months, the animals in the DEN group showed HCC foci in the liver, an increase of hepatic lipid peroxidation, attenuation of hepatic antioxidant capacity, an increase of blood liver enzymes (ALT, AST, and ALP), bilirubin, albumin, creatinine, glucose, and reduction of the body weight. The plant extract could decrease the levels of liver enzymes, total bilirubin, direct bilirubin, albumin, urea, and creatinine in the blood. Also, the extract attenuated oxidative stress and improved pathological changes in the liver. Quantitative real-time PCR revealed a decrease in gene expression of Wnt/β-catenin and Akt and an increase in PTEN as the tumor suppressor gene. Conclusion The extract of R. turkestanicum reduced DEN-induced liver changes through inhibiting oxidative stress and attenuating the expression of Wnt/β-catenin and Akt and elevating PTEN expression.
Exploration of the Mutual Effects Between Cation–π and Intramolecular Hydrogen Bond Interactions in the Different Complexes of Mesalazine with Metal Cations of Alkali and Alkaline-Earth: A DFT Study
Authors: Mohammadi Marziyeh , Alirezapour Fahimeh , Khanmohammadi Azadeh 
Published: June 2021

Abstract
In the current research, a comparative study of the interplay effects between cation–π and intramolecular hydrogen bond (IMHB) interactions is performed on the complexes of mesalazine with Li+, Na+, K+, Be2+, Mg2+ and Ca2+ cations using density functional theory (DFT). For this purpose, the mesalazine analogue and the equivalent values of 3-aminobenzoic acid complexes with the cited cations are selected as a set of reference points. In order to understand the mutual effects between these interactions, the descriptors of geometrical, binding energies, topological properties and charge transfer values are examined on complexes using the atoms in molecules (AIM) and natural bond orbital (NBO) analyses. Results indicate that with the exception of Be2+ complex, the coupling simultaneously weakens both of the interactions. Finally, the physical properties such as energy gap, chemical hardness as well as electronic chemical potential of complexes are systematically analyzed by using frontier molecular orbitals.
Associated with Immune Function, miR-150-5p is a Favorable Biomarker for Head and Neck Cancer Patients
Authors: Liu Zhi-Jie , Li-Sheng Li-Sheng , Wang Jing , Peng Li-Xia , Mei Yan , Li Chang-Zhi , Xu Liang , Meng Dong-Fang , Peng Xing-Si , Lang Yan-Hong , Wang Ming-Dian , Xie De-Huan , Guo Ling-Ling , Shu Di-Tian , Ding Liu-Yan , Huang Bi-Jun , Qian Chaonan 
Published: June 2021

Abstract
BackgroundAccumulating evidence has shown that dysregulated expression of microRNAs plays a key role in tumorigenesis. To explore the mechanisms of this we conducted this study.MethodsFive Gene Expression Omnibus datasets (GEO) datasets , GSE32960, GSE36682, GSE43039, GSE70970 and GSE118613 and head and neck squamous cell carcinoma data of The Cancer Genome Atlas (TCGA) were analysis in this study.ResultsBy analyzing the microRNA expression profile of nasopharyngeal carcinoma (NPC) in the five GEO datasets, we identified miR-150-5p as potential biomarker for patient survival. To explore the mechanisms of this, We examined the head and neck squamous cell carcinoma data of TCGA and found that miR-150-5p was correlated with high enrichment of tumor-infiltrating B cells, low enrichment of cancer-associated fibroblasts and down-regulated oncogenic pathways. miR-150-5p may also improve the immune response in the tumor microenvironment. These findings may explain how miR-150-5p improves outcome of head and neck squamous cell carcinoma patients including NPC. Additionally, the exosomal long non-coding RNA AC073130.1 was identified as a potential regulator of miR-150-5p. As miR-150-5p can also be released via exosomes, this study provides insight into the cross-talk of tumor cells and B cells in the tumor microenvironment via exosomal AC073130.1 and miR-150-5p. ConclusionMiR-150-5p improves outcome of head and neck squamous cell carcinoma patients by improving the immune response. There might be a cross-talk of tumor cells and B cells in the tumor microenvironment via exosomal AC073130.1 and miR-150-5p.