bluuebunny/crossref_metadata_2025 huggingface dataset:
Controls of Deep-Seated Faults and Folds on Hydrocarbon Fluid Migration and Accumulation in Sedimentary Basins: A Case Study from the Northwestern Sichuan Basin, China
Authors: Wang Xi , Liu Yin , Cao Jian , Liu Yiduo , Luo Bing , Wu Kongyou , Shi Zheng , Kang Hongbin
Published: December 2021

Deep-seated faults and folds of foreland basin systems have become important exploration targets in the recent years because they are crucial in controlling fluid migration and hydrocarbon accumulation. In this study, we analyzed the characteristics and formation history of these structures in the northwestern Sichuan Basin using recently acquired two-dimensional (2D) and three-dimensional (3D) seismic data. The seismic interpretation revealed that the thrust sheets, tectonic wedges, and foredeep were well developed in the northwestern Sichuan Basin from the mountain to the basin. Forward thrusts, fault-bend folds, and wedges are the main types of structures in the thrust sheets and tectonic wedges. The deep-seated faults and folds were easily recognized in the high-resolution 3D seismic data. The imbricate thrust faults that merged into detachment layers of the Lower Cambrian are the main types of structures in the foredeep, and they show a prominent strike-slip influence in the horizontal direction. The formation of these structures in the foredeep in the northwestern Sichuan Basin mainly endured two stages of thrusting, including those during the Middle-to-Late Triassic and Cenozoic. Based on the tectonic evolution and seismic data, we infer that these deep-seated faults and folds in the foredeep may have formed earlier than the northern Longmen Shan fold-and-thrust belts and they may have been initially active in the late of Early Triassic and reactive during the Cenozoic. Furthermore, evaporites in the Lower and Middle Triassic were crucial in forming these structures. The petroleum exploration data suggested that the deep-seated faults can facilitate hydrocarbon accumulation. The thrust faults in the foredeep were more likely to act as migration pathways for fluids instead of sealing barriers along the horizontal direction. The interconnected reservoirs of deep-seated folds possess a great potential to allow large-scale hydrocarbon accumulation. Our study provides a good example for evaluating the hydrocarbon exploration potential in the deeply buried area in the sedimentary basin.
Two Cases of Iatrogenic Lumbar Foraminal Disc Herniations
Authors: Taniguchi Ryota , Kawano Osamu , Maeda Takeshi , Nakajima Yasuharu , Morishita Yuichiro
Published: December 2021

Study Design. A case report. Objective. We report two cases of iatrogenic deterioration of lumbar foraminal disc herniations following lumbar disc injections. Summary of Background Data. Complications associated with discography were reported. However, only a few reports have thus far referred to the iatrogenic deterioration of lumbar foraminal disc herniations. Cases. 60-year-old and 74-year-old men were treated with MR images of L4-5 foraminal disc herniations without fragment in the spinal canal. The patients underwent discography and disc block for its diagnosis and treatment. After disc injections, both patients complained of deterioration of L4 radiculopathy. Results. On disco-CT or reexamined MR images after disc injections, herniated fragment was migrated from neural foramen to cranial central spinal canal with was not shown in previous MR images. The herniated fragments were extirpated by means of osteoplastic laminoplasty or transforaminal lumbar interbody fusion with facetectomy. The herniated fragments were migrated from neural foramen to cranial central spinal canal. Conclusions. The injection of liquid medicine into the nucleus led the intradiscal pressure increased, and the disc fragment might prolapsed through the raptured region of annulus fibrosus and migrated to cranial central spinal canal by anatomical reason. The disc injection may have a risk for deterioration of foraminal disc herniation. Our report is instructive for the management of discography for the diagnosis of foraminal disc herniations.
Microglia Polarization from M1 toward M2 Phenotype Is Promoted by Astragalus Polysaccharides Mediated through Inhibition of miR‐155 in Experimental Autoimmune Encephalomyelitis
Authors: Liu Xiaojun , Ma Jinyun , Ding Guiqing , Gong Qianyi , Wang Yuanhua , Yu Hua , Cheng Xiaodong
Published: December 2021

Activated microglia is considered to be major mediators of the neuroinflammatory environment in demyelinating diseases of the central nervous system (CNS). Activated microglia are mainly polarized into M1 type, which plays a role in promoting inflammation and demyelinating. However, the proportion of microglia polarized into M2 type is relatively low, which cannot fully play the role of anti‐inflammatory and resistance to demyelinating. Our previous study found that Astragalus polysaccharides (APS) has an immunomodulatory effect and can inhibit neuroinflammation and demyelination in experimental autoimmune encephalomyelitis (EAE), which is a classic animal model of CNS demyelinating disease. In this study, we found that APS was effective in treating EAE mice. It restored microglia balance by inhibiting the polarization of microglia to M1‐like phenotype and promoting the polarization of microglia to M2‐like phenotype in vivo and in vitro. miR‐155 is a key factor in regulating microglia polarization. We found that APS could inhibit the expression level of miR‐155 in vivo and in vitro. Furthermore, we performed transfection overexpression and blocking experiments. The results showed that miR‐155 mediated the polarization of microglia M1/M2 phenotype, while the selective inhibitor of miR‐155 attenuated the inhibition of APS on microglia M1 phenotype and eliminated the promotion of APS on microglia M2 phenotype. Microglia can secrete IL‐1α, TNF‐α, and C1q after polarizing into M1 type and induce the activation of A1 neurotoxic astrocytes, further aggravating neuroinflammation and demyelination. APS reduced the secretion of IL‐1α, TNF‐α, and C1q by activated microglia, thus inhibited the formation of A1 neurotoxic astrocytes. In summary, our study suggests that APS regulates the polarization of microglia from M1 to M2 phenotype by inhibiting the miR‐155, reduces the secretion of inflammatory factors, and inhibits the activation of neurotoxic astrocytes, thus effectively treating EAE.
[Retracted] Dynamic Analysis of College Physical Education Teaching Quality Evaluation Based on Network under the Big Data
Authors: Feng Bin
Published: December 2021

Improving the quality of college physical education is of great significance to facilitating the integrated development of students′ psyches and physical. Establishing a more systematic, effective, and social training needs of education quality evaluation hierarchy is also the centerpiece of the college physical culture education administration. Massive information technology provides new conception and methods to this, and supply advantage sustains for furtherance the education ecology development. Based on the network education system, this paper uses big data to quantify the evaluation indexes of physical education teaching, so as to actualize the timely dynamic evaluation of the process that is physical teaching and learning. This essay constructs the evaluation index system of college physical education teaching quality by combining mensurable and qualitative methods. On the basis of previous studies, an evaluation model of college physical education teaching quality based on artificial intelligence mass data calculation is designed. The experiment authenticates that the model evaluation risk coefficient is 1.93 lower than the optimized model. The experiment also proves that the model is conducive to elevating the education quality.
Chest Pain in a Psychiatric Patient Due to Clozapine-Induced Myopericarditis
Authors: Laws James L. , Kim Esther , Hung Rebecca , Lindenfeld JoAnn , Gupta Richa
Published: December 2021

Drug-induced myocarditis is a rare, but underrecognized complication of clozapine therapy for schizophrenia. We present a case of clozapine-induced myocarditis with recovery of cardiac function after drug cessation and summarize the literature to highlight the variable presentation of this condition.
Deep Learning-Based Framework for the Detection of Cyberattack Using Feature Engineering
Authors: Akhtar Muhammad Shoaib , Feng Tao
Published: December 2021

Digital systems are changing to security systems in contemporary days. It is time for the digital system to have sufficient security to defend against threats and attacks. The intrusion detection system can identify an anomaly from an external or internal source in the network system. Many kinds of threats are present, that is, active and passive. These dangers could lead to anomalies in the system by which data can be attacked and taken by attackers from the beginning to the destination. Machine learning nowadays is a developing topic; its applications are wide. We can forecast the future through machine learning and classify the right class. In this paper, we employed the new binary and multiclass classification model of Convolutional Neural Networks (CNNs) to identify the anomaly of the network system. In this respect, we used the NSLKDD dataset. Our model uses a Convolutional Neural Network (CNN) to conduct binary and multiclass classification. In both datasets, we build a DL-based DoS detection model. We focus on the DoS category in the most extensively used IDS dataset, KDD. As the name implies, CNN is the most extensively used the DL model for image recognition. Adding a pooling layer to the convolution layer minimizes the size of the feature data extracted from the image while maintaining I/O and spatial information. The CNN model has shown the promising results of multiclass and binary classification in terms of validation loss of 0.0012 at 11th epochs and validation accuracy of 98% and 99%, respectively.
Evaluation of Analgesia Effect after Ultrasound-Guided Laparoscopic Renal Surgery
Authors: You Xiaolei , Liu Wei
Published: December 2021

Kidney surgery involves placing the kidney in the iliac fossa of the lower abdomen on the right or left side. Studies have found that most kidney patients experience moderate to severe pain after surgery. The stress response caused by postoperative pain, especially visceral pain, not only aggravates the patient’s pain and irritability and aggravates the original complications but may also harm the early recovery of renal function and affect the survival of the kidney. Therefore, adequate postoperative analgesia for renal patients is essential. This paper combines ultrasound-guided laparoscopic technology to improve the postoperative analgesia effect of renal surgery and compares the data with experimental research methods. Through experimental research, it can be seen that the method proposed in this article has a certain effect, and ultrasound-guided laparoscopic technology can be used in follow-up clinical research to improve the analgesic effect of renal surgery.
Remote Sensing Image Land Classification Based on Deep Learning
Authors: Zhang Kai , Hu Chengquan , Yu Hang
Published: December 2021

Aiming at the problems of high-resolution remote sensing images with many features and low classification accuracy using a single feature description, a remote sensing image land classification model based on deep learning from the perspective of ecological resource utilization is proposed. Firstly, the remote sensing image obtained by Gaofen-1 satellite is preprocessed, including multispectral data and panchromatic data. Then, the color, texture, shape, and local features are extracted from the image data, and the feature-level image fusion method is used to associate these features to realize the fusion of remote sensing image features. Finally, the fused image features are input into the trained depth belief network (DBN) for processing, and the land type is obtained by the Softmax classifier. Based on the Keras and TensorFlow platform, the experimental analysis of the proposed model shows that it can clearly classify all land types, and the overall accuracy, F1 value, and reasoning time of the classification results are 97.86%, 87.25%, and 128 ms, respectively, which are better than other comparative models.
Formulation and Quality Control of Orally Disintegrating Tablets (ODTs): Recent Advances and Perspectives
Authors: Ghourichay Mohammadali Poursharifi , Kiaie Seyed Hossein , Nokhodchi Ali , Javadzadeh Yousef
Published: December 2021

Orally disintegrating tablets (ODTs) rapidly disintegrate or dissolve in the oral cavity without using water. Demand for ODTs has increased, and the field has overgrown in the pharmaceutical industry and academia. It is reported that ODTs have several advantages over other conventional tablets. Since some of them are absorbed from the mouth, pharynx, and esophagus as the saliva passes down into the stomach, in such cases, the bioavailability of the drug improves meaningfully. Furthermore, the immediate release property of ODTs makes them a popular oral dosage form in patients with swallowing challenges, children, and for cases with a need for rapid onset of action. The current review article explains the features of active ingredients and excipients used in the formulation of ODTs, discusses multiple ODT formulation and preparation techniques with their merits and demerits, and also, offers remedies for problems associated with ODTs. Moreover, quality control steps and required considerations are presented.
[Retracted] Artificial Intelligence‐Based Deep Fusion Model for Pan‐Sharpening of Remote Sensing Images
Authors: Iskanderani Ahmed I. , Mehedi Ibrahim M. , Aljohani Abdulah Jeza , Shorfuzzaman Mohammad , Akhter Farzana , Palaniswamy Thangam , Latif Shaikh Abdul , Latif Abdul , Jannat Rahtul
Published: December 2021

During the past two decades, many remote sensing image fusion techniques have been designed to improve the spatial resolution of the low‐spatial‐resolution multispectral bands. The main objective is fuse the low‐resolution multispectral (MS) image and the high‐spatial‐resolution panchromatic (PAN) image to obtain a fused image having high spatial and spectral information. Recently, many artificial intelligence‐based deep learning models have been designed to fuse the remote sensing images. But these models do not consider the inherent image distribution difference between MS and PAN images. Therefore, the obtained fused images may suffer from gradient and color distortion problems. To overcome these problems, in this paper, an efficient artificial intelligence‐based deep transfer learning model is proposed. Inception‐ResNet‐v2 model is improved by using a color‐aware perceptual loss (CPL). The obtained fused images are further improved by using gradient channel prior as a postprocessing step. Gradient channel prior is used to preserve the color and gradient information. Extensive experiments are carried out by considering the benchmark datasets. Performance analysis shows that the proposed model can efficiently preserve color and gradient information in the fused remote sensing images than the existing models.
Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling
Authors: Chengyue Yu , Prabhu M. , Goli Mahendar , Sahu Anoop Kumar
Published: December 2021

Nowadays, Blockchain Technology (BCT) is contributing toward addressing the challenges of complex industrial systems (CISs). The BCT reduces the complexity of cash data storage as well as retrieval system of finance, marketing, supply chain, inventory, and other departments. The objective of the present study is to investigate the factors, which affect the intention of professionals to adapt the BCT in the CISs by using an extension of the technology acceptance model. To fulfill the research objective, a theoretical research model is constituted by multiple hypotheses (H1–H6), i.e., perceived usefulness, perceived ease of use, perceived innovativeness, knowledge, risk, and trust after conducting the relevant literature survey in the context of BCT. Next, each hypothesis is tested by exploring the survey data of a sample of 287 professionals of different BCT user’s companies such as retailing, e‐commerce, manufacturing, and construction. Survey data is analyzed by executing the structural equation modeling with AMOS software. The factors and latent constructs loadings, reliability, convergent, discriminant, model fit‐measurement, structural model, and the path analysis are conducted. The results reveal that the H1, H2, and H4–H6 dropped the positive impact and effect on professionals’ intention to use the BCT in CISs. But, H3 has no effect for enhancing the intention of professionals to use BCT.
Application of MGGP, ANN, MHBMO, GRG, and Linear Regression for Developing Daily Sediment Rating Curves
Authors: Niazkar Majid , Zakwan Mohammad
Published: December 2021

A data-driven relationship between sediment and discharge of a river is among the most erratic relationships in river engineering due to the existence of an inevitable scatter in sediment rating curves. Recently, Multigene Genetic Programming (MGGP), as a machine learning (ML) method, has been proposed to develop data-driven models for various phenomena in the field of hydrology and water resource engineering. The present study explores the capability of MGGP-based models to develop daily sediment ratings of two gauging sites with 30-year sediment-discharge data, which was utilized previously in the literature. The results obtained by MGGP were compared with those achieved by an empirical model and Artificial Neural Network (ANN). The coefficients of the empirical model were calibrated using linear and nonlinear regression models (Generalized Reduced Gradient (GRG) and the Modified Honey Bee Mating Optimization (MHBMO) algorithm). According to the comparative analysis, the mean absolute error (MAE) at the two gauging stations reduced from 516.54 to 519.23 obtained by nonlinear regression to 447.26 and 504.23 achieved by MGGP, respectively. Similarly, all other performance indices indicated the suitability and accuracy of MGGP in developing sediment ratings. Therefore, it was demonstrated that ML-based models, particularly MGGP-based models, outperformed the empirical models for estimating sediment loads.
Effect of Coupling Agent on Softwood Kraft Nanocellulose Fibril-Reinforced Polylactic Acid Biocomposite
Authors: Saeed Usman , Rathur Sami Ullah , AlTuraif Hamad , Bamufleh Hisham
Published: December 2021

The nanocellulose fibril produced by using natural sources can be used in developing sustainable and green products. The useful features of nanocellulose fibril can include valuable physical properties, appropriate surface chemistry, low toxicity, and biocompatibility. The study presented shows the use of polylactic acid with five different percentages of nanocellulose fibril and the use of 3% maleic anhydride as a coupling agent. The maleic anhydride acts as coupling agent which improves the thermochemical and thermomechanical characteristics of the end product. The addition of 3% maleic anhydride as coupling agent with 10% nanocellulose fibril improved the impact strength up to 14.3%, elastic modulus up to 40.6%, and tensile strength up to 30.1%. Furthermore, the dynamic mechanical analysis result indicates that the inclusion of maleic anhydride improved the toughness by reducing the

tan
δ

peak and increases the storage modulus. Finally, the scanning electron micrograph shows that the interfacial compatibility between nanocellulose fibril and polylactic acid matrix is improved with the addition of maleic anhydride.
Optimization Model of Cross‐Border E‐commerce Payment Security by Blockchain Finance
Authors: Chen Tung-Chun , Liang Yu-Shen , Ko Po-Sheng , Huang Jui-Chan
Published: December 2021

Cross‐border trade is also changing and innovating. Electronic payment has become the core application of modern cross‐border e‐commerce. However, although electronic payment has brought convenience and efficiency to enterprises and social life, there are also many problems in transaction information security. These problems not only hinder the development of electronic payment but also bring hidden dangers to people’s property security. Therefore, an encryption algorithm of e‐commerce was proposed, and its algorithm security and risk control mode was further studied by means of case analysis, empirical analysis, and comparative analysis. Experimental data show that blockchain technology is a breakthrough. The aim of the study is to explore its application in specific circumstances and strive to make the new e‐payment mode in line with international standards.
Statistical Inferences of Burr XII Lifetime Models under Joint Type-1 Competing Risks Samples
Authors: Abushal Tahani A. , Soliman A. A. , Abd-Elmougod G. A.
Published: December 2021

The problem of statistical inference under joint censoring samples has received considerable attention in the past few years. In this paper, we adopted this problem when units under the test fail with different causes of failure which is known by the competing risks model. The model is formulated under consideration that only two independent causes of failure and the unit are collected from two lines of production and its life distributed with Burr XII lifetime distribution. So, under Type-I joint competing risks samples, we obtained the maximum likelihood (ML) and Bayes estimators. Interval estimation is discussed through asymptotic confidence interval, bootstrap confidence intervals, and Bayes credible interval. The numerical computations which described the quality of theoretical results are discussed in the forms of real data analyzed and Monte Carlo simulation study. Finally, numerical results are discussed and listed through some points as a brief comment.
High Expression of JMJD4 Is a Potential Diagnostic and Prognostic Marker of Renal Cell Carcinoma
Authors: Yan Hao , Bao Yewei , Lin Zongming
Published: December 2021

Histone demethylase JMJD4 is a burgeoning tumor marker, which has been proven to be associated with colon cancer, but the role it plays in kidney cancer has not yet been investigated. In the present study, we evaluated whether JMJD4 can be a prognostic marker of patients with clear cell renal cell carcinoma (ccRCC) using data from public platform and in vitro experiments. Our results revealed that the expression of JMJD4 is higher in cancerous tissue than in normal tissues (

p
<
0.001

). High expression of JMJD4 is associated with a poor overall survival (OS) of ccRCC as compared with low expression of JMJD4 (

p
=
0.015

). JMJD4 showed significant relevance with M stage (

p
=
0.016

), gender (

p
=
0.003

), OS (0.018), disease-specific survival (DSS) (0.007), and percussion free interval (PFI) (0.041). Univariate and multivariate Cox analyses demonstrated that high JMJD4 expression had independent predictive value for OS in ccRCC patients (

hazard
 
ratio
 

HR

=
1.563

,

95
%
confidence
 
interval
 

CI

=
1.055
‐
2.316

, and

p
=
0.026

). Besides, in vitro experiments confirmed that high expression of JMJD4 can significantly promote the invasion ability (

p
<
0.001

), cloning ability (

p
<
0.001

), and proliferation (

p
<
0.001

) of renal cell carcinoma. In summary, high JMJD4 expression may be a prognostic marker in patients with kidney cancer.
Digital Mining Algorithm of English Translation Course Information Based on Digital Twin Technology
Authors: Yang Juan
Published: December 2021

Cross‐language communication puts forward higher requirements for information mining in English translation course. Aiming at the problem that the frequent patterns in the current digital mining algorithms produce a large number of patterns and rules, with a long execution time, this paper proposes a digital mining algorithm for English translation course information based on digital twin technology. According to the results of word segmentation and tagging, the feature words of English translation text are extracted, and the cross‐language mapping of text is established by using digital twin technology. The estimated probability of text translation is maximized by corresponding relationship. The text information is transformed into text vector, the semantic similarity of text is calculated, and the degree of translation matching is judged. Based on this data dimension, the frequent sequence is constructed by transforming suffix sequence into prefix sequence, and the digital mining algorithm is designed. The results of example analysis show that the execution time of digital mining algorithm based on digital twin technology is significantly shorter than that based on Apriori and Map Reduce, and the mining accuracy rate reached more than 80%, which has good performance in processing massive data.
An Effective Harmonic Suppression Method Based on Linear Active Disturbance Rejection Control for Copper Electrowinning Rectifier
Authors: Cui Yang , Liu Cheng , Cheng Yanming , Al Shurafa Mahmoud , Lee Ilkyoo , Niu Jing
Published: December 2021

Because the harmonics in the production process of copper electrowinning have an important impact on the electrical energy consumption, it is necessary to suppress the harmonics effectively. In this paper, a copper electrowinning rectifier with double inverse star circuit is selected as a study object in which a large number of harmonics mainly including the 5th, 7th, 11th, and 13th harmonics are generated and injected back into the power grid. The total harmonic distortion rate of the power grid is up to 29.19% before filtering. Therefore, a method combining the induction filtering method and the active filtering method is proposed to carry out comprehensive filtering. Simulation results demonstrate that the total harmonic distortion rate of the system decreases to 4.20%, which indicates that the proposed method can track the corresponding changes of harmonics when the load changes in real time and filter them out. In order to ensure and improve the effect of active filter, a current harmonic tracking control method based on linear active disturbance rejection control is proposed. Simulation results show that the total harmonic distortion rate decreases to 3.34%, which is also lower than that of hysteresis control. Compared with the conventional single filtering method, the new filtering method combining induction filtering with active filtering based on linear active disturbance rejection control in the copper electrowinning rectifier has obvious advantages.
Contribution Modeling on Condition Evaluation of Asphalt Pavement Using Uncertainty Measurement and Entropy Theory
Authors: Li Jue , Wei Hui , Yao Yongsheng , Hu Xin , Wang Lei
Published: December 2021

In view of the deficiency that traditional pavement performance evaluation index did not consider the influence of their difference on weight, the grade of the evaluation index also did not take into account intermediate state and the impact of uncertainty on the evaluation results, a determination method of pavement performance evaluation index weight based on entropy theory was developed. The unascertained measurement function of evaluation index was performed by left‐half ladder distribution, and unascertained measurement matrix was obtained. The index weight was calculated by minimum entropy theory, and the practicability of this method was verified through a concrete example finally. The results show that there were different weights in different samples, which depended on index measurement function and were the overall characterization of comprehensive measurement of every index. The method which is based on the given weighting factor did not conform to the engineering facts. It was difficult to identify the importance of the pavement performance evaluation index in different samples. The balance of the various indexes is better to be considered in the proposed method, and the comprehensive situation of pavement performance is really reflected, which improves the evaluation of the reliability.
Association of Age-Related Cataract Risk with High Polygenetic Risk Scores Involved in Galactose-Related Metabolism and Dietary Interactions
Authors: Jee Donghyun , Kang Suna , Park Sunmin
Published: December 2021

Introduction: Cataracts are associated with the accumulation of galactose and galactitol in the lens. We determined the polygenetic risk scores for the best model (PRSBM) associated with age-related cataract (ARC) risk and their interaction with diets and lifestyles in 40,262 Korean adults aged over 50 years belonging to a hospital-based city cohort. Methods: The genetic variants for ARC risk were selected in lactose and galactose metabolism-related genes with multivariate logistic regression using PLINK 1.9 version. PRSBM from the selected genetic variants were estimated by generalized multifactor dimensionality reduction (GMDR) after adjusting for covariates. The interactions between the PRSBM and each lifestyle factor were determined to modulate ARC risk. Results: The genetic variants for ARC risk related to lactose and galactose metabolism were SLC2A1_rs3729548, ST3GAL3_rs3791047, LCT_rs2304371, GALNT5_rs6728956, ST6GAL1_rs2268536, GALNT17_rs17058752, CSGALNACT1_rs1994788, GALNTL4_rs10831608, B4GALT6_rs1667288, and A4GALT_ rs9623659. In GMDR, the best model included all ten genetic variants. The highest odds ratio for a single SNP in the PRSBM was 1.26. However, subjects with a high-PRSBM had a higher ARC risk by 2.1-fold than a low-PRSBM after adjusting for covariates. Carbohydrate, dairy products, kimchi, and alcohol intake interacted with PRSBM for ARC risk, where participants with high-PRSBM had a much higher ARC risk than those with low-PRSBM when consuming diets with high carbohydrate and low dairy product and kimchi intake. However, only with low alcohol intake, the participants with high-PRSBM had a higher ARC risk than those with low-PRSBM. Conclusion: Adults aged >50 years having high-PRSBM may modulate dietary habits to reduce ARC risk.
Realistic mathematics education: An approach to improve problem solving ability in primary school
Authors: Nugraheni Lutfi Putri , Marsigit Marsigit
Published: December 2021

Mathematical problem solving was an crucial skill to be mastered by primary school student so that will help student to unravel their problems encountered in everyday life. By using the realistic mathematics approach, stundents learn mathematical concept based on reality or scope around students. This study aimed to develop an eligible learning materials and test the effectiveness of learning materials based on realistic mathematics education to enhance the problem solving skill of primary school students. This research and development study was conducted in Sawangan Subdistrict, Magelang Regency, Central Java, Indonesia. The testing subjects consisted of 12 students in the the preliminary field, there were 42 students in the main field, and 90 students in the operational field that divided into experiment dan control class. The data were collected by interviews, observation, and tests. The analyzing N-gain score and t-test with a significant level of 0.05 done to find out th effectiveness of the teaching materials. The developed of realistic mathematics eduation learning materials is feasible and effective in improving problem solving skill with significance value of 0.000 (p≤0.05). It can enhance the problem solving skills of 4th grade elementary school.
Impact of the society’s perception on teachers’ professionalism
Authors: Fauziah Arifah , Kim Maksim , Aye Mulunesh , Hakizimana Venant , Hur Ju
Published: December 2021

An effective teaching contributes to the students’ performance and this depends on qualified-trained teachers, school administration, parents and conducive environment for teaching and learning. It is proven that students are more successful in their academic achievements, in the societies where teachers perceive their profession as their job. This paper explores the impact of the society’s perception on teachers’ professionalism. The method employed in this paper is qualitative by using interview technique and used audio-recorded to ensure a complete transcript. The result indicated that in some developing countries including Cameroon, Kenya and Fiji has various reasons for their job. Teaching profession was affected by how the society considers teachers whereby they are perceived as disadvantaged population who cannot fully take part in the social and economic activities due to the fact that their salary is very low compared other public servants. This low salary and loss of respect of teachers by the society lead to the job dissatisfaction and made the teaching profession as a transitional job before waiting to move to another different professional field.
Rethinking active learning program for primary English teachers through connoisseurship technique
Authors: Kulachit Nippita , Nuangchalerm Prasart
Published: December 2021

From the importance of Englishin world of internationally communicated,  the problems of learning management in each area seems to be differenced, language and culture are needed for recognizing, active learning is called for  effectiveness instruction, and primary English teachers need to prepared in modern classroom. This research employed evaluative research to employ active learning for primary English teachers through professional program. Data were collected by setting a connoisseurship technique. Seven experts are appointed and read carefully a tentative program for primary English teachers. The connoisseurship technique allowed all experts share their experiences and ideas to promote active learning in freely. Video recording and note taking were recorded during the validation activity. Active learning program for primary English teachers is approved before implementation in different school contexts. The uncertainty situations, COVID-19 pandemic may be affected to schooling, teachers have to redesign lesson. The implementation though active online learning is needed to discuss and rethinking how it be effectively in authentic classroom.
Adaptation, validity and reliability study of the “Internet Addiction Scale for Adolescents” into Albanian
Authors: Basha Ertan , Telaku Naim , Mustafa Armen
Published: December 2021

The aim of this study was to verify the dimensions of Internet addiction in Albanian. This study employed “Internet Addiction Scale for Adolescents” to determine internet addiction. The verification of language equivalence, the scale form was administered to 164 university students studying at AAB College Faculty of Psychology and 61 High School students studying at the British School of Kosovo (altogether 245). In addition, the Cronbach Alpha internal srability coefficient was found to be .828. It was observed that the factor load values of the scale items varied between .56 and .72. The Kaiser-Meyer-Olkin coefficient (KMO) was 0.82 and the Bartlett x2 Sphericity value was 605,874 (p.000). In confirmatory factor analysis, it was seen that the one-dimensional structure of the scale provided a good fit. [x2=63.168, df=26, x2/df=2.42 RMSEA=.077, RMR=.069, S-RMR=.049, GFI=.95, AGFI=.91, CFI=.94, NNFI=.90, IFI=.94]. The findings obtained as a result of the validity factor analysis and the reliability of the scale show that the Albanian scale is valid and reliable.
Synthesis of research report of personnel: Case study on Faculty of Education, Mahasarakham University
Authors: Singporn Rungthip , Nuangchalerm Prasart
Published: December 2021

The purpose of this research was to synthesize research report of personnel in the Faculty of Education, Mahasarakham University. There were 81 research reports funded by Faculty of Education, Mahasarakham University between the academic years of 2012-2019 were employed. The research revealed that most of research concerning teacher development amounting to 69 researches, followed by research report of the support staff amounting to 12 researches. Most of research reports were basic research, applied research, and collaborative teaching research amounting to 55 researches, followed by production research and development of personnel that emphasized on the concept of learning based on the actual situation amounting to 11 researches. The greatest number of research was produced and published in 2018, 23 researches, and in 2019, 13 researches. They were publishing in Thai journals, total of 75 research. The utilization of research to apply for policy benefits, 75 research and for public in four research. Research methodology employed 50 operational researches, 29 quasi-experimental researches, 33 researches to studies, 25 comparative researches and 16 researches to find correlation.
Comparison of curriculum implementation between public and private schools based on Adiwiyata
Authors: Susilo Mohamad Joko , Junanah Junanah , Dewantoro M Hajar
Published: December 2021

The curriculum is the heart of education, whose job determines the life or death of a school. This study aimed to compare the implementation of Adiwiyata school curriculum between public and private school in junior high schools, especially in Bantul Regency, Yogyakarta, Indonesia. Data collection techniques by means of literature studies. Data analysis techniques were carried out with qualitative comparative analysis. The results showed that: public and private schools in junior high schools in Bantul Regency, had fulfilled the four main components of the Adiwiyata curriculum, in terms of objectives, content, methods, and evaluation. The implementation of Adiwiyata curriculum in each public and private school varies according to the characteristics and potential of each school.
Intelligent stability margin improvement using series and shunt controllers
Authors: Karami Mahdi , Mariun Norman , Radzi Mohd Amran Mohd , Varamini Gohar
Published: December 2021

Electric market always prefers to use full capacity of existing power system to control the costs. Flexible alternate current transmission system (FACTS) devices introduced by Electric Power Research Institute (EPRI) to increase the usable capacity of power system. Placement of FACTS controllers in power system is a critical issue to reach their maximum advantages. This article focused on the application of FACTS devices to increase the stability of power system using artificial intelligence. Five types of series and shunt FACTS controllers are considered in this study. Continuation power flow (CPF) analysis used to calculate the collapse point of power systems. Controlling parameters of FACTS devices including their locations are determined using real number representation based genetic algorithm (RNRGA) in order to improve the secure margin of operating condition of power system. The 14 and 118 buses IEEE standard test systems are utilized to verify the recommended method. The achieved results manifestly proved the effectiveness of proposed intelligent method to increase the stability of power system by determining the optimum location and size of each type of FACTS devices.
Simulation of boost AC-AC converter using single-phase matrix converter
Authors: Duranay Zeynep Bala , Guldemir Hanifi
Published: December 2021

Generally, AC-AC converters are implemented using thyristors. These converters generate harmonics and have a low power factor. To eliminate these problems matrix converters (MC) are become used as AC-AC converter. Matrix converters have the capability of being used as frequency changer, rectifier, inverter and chopper. In this work, it is proposed to achieve the desired output of AC-AC Boost converter using single phase matrix converter (SPMC). The operation of single-phase AC-AC boost converter using MC is studied in this paper. The output voltage of this boost converter is higher than the AC input supply voltage. insulated gate bipolar transistors (IGBTs) are used as the switching elements in the SPMC power circuit. Sinusoidal Pulse width modulation (SPWM) technique is applied to generate switching signals to obtain the output voltage. The model of the matrix converter is constructed in MATLAB/Simulink programming software package. The behavior of SPMC is simulated with various switching frequencies. The simulation results together with harmonic spectrum and total harmonic distortion (THD) values are presented. Successful operation of boost SPMC is achieved.
A grid interconnected nested neutral point clamped inverter with voltage synchronization using synchronous reference frame controller
Authors: Bogimi Sirisha
Published: December 2021

Nested neutral point clamped multi level inverter with inter connection to grid through the synchronous reference frame (SRF) controller for synchronization of voltage to the grid is demonstrated. The system's main feature is that voltage stress in each inverter switching device is kept to a minimum, and redundant inverter switching states are utilised for neutral point and flying capacitor voltage balancing with sinusoidal pulse-width modulation (PWM) technique, synchronisation to grid voltages, and power injection with low harmonic generation. The inverter receives its input from a photovoltaic (PV) source that is coupled to DC-DC booster converters that are regulated by the maximum power point tracking (MPPT) incremental conductance algorithm to maintain a constant dc voltage. The system is examined under various load conditions with MATLAB Simulink model.
A conceptual learner discipline management model for secondary schools in Mauritius
Authors: Jinot Belle Louis , Johannes Van Niekerk Eldridge
Published: December 2021

Learner discipline management is a major but challenging function of school leadership. Adolescents of the 21st century are complex in nature, and school stakeholders are having much difficulty to handle the problem of indiscipline in secondary schools. This paper aims at providing a conceptual model framework for learner discipline management. This model is the result of an empirical investigation conducted in four secondary schools. Focus group discussion and individual interviews were carried out with 80 participants, including 24 teachers, 24 learners, 24 parents, four school principals, and four school superintendents. The non-participant observation was also conducted in the four schools. Based on the conceptual, theoretical and empirical literature on positive, proactive, preventive and restorative discipline, the researcher proposed the model that considers all the research- and evidence-based strategies that are combined with the current effective measures prescribed by the Ministry of Education, Science and Technology of Mauritius. The model is framed within the context of the Nine Year Continuous Basic Education reform that requires a shift in the conception of discipline from the punitive or reactive approach to the positive approach. This paper formulates a conceptual model framework to implement in an attempt to prevent, reverse and restore discipline among learners in secondary schools.
Factors of academic stress: Do they impact English academic performance?
Authors: Tibus Erlinda D. , Ledesma Sybill Krizzia G.
Published: December 2021

This study investigated the college students’ level of academic performance and determined the impact of academic stress on their English academic performance. This employed a descriptive-exploratory research design with Exploratory Factor Analysis (EFA) and correlation analysis (Pearson r) as main analyses using statistical software. The result suggested that the students (N=250) have a moderate level of stress. Likewise, seven factors were generated through EFA but were reduced to four factors using parallel analysis, the factors are perceived personal stress, classroom stress, performance stress, and time management stress. In the correlation analysis, it was found out that perceived personal stress, classroom stress, and performance stress are significantly correlated except for time management stress. Moreover, these factors were found to have no significant relationship with the English grades of the students. With this result, it is concluded that despite having a moderate level of academic stress, students were able to manage them by using a plethora of coping mechanisms available. The institutions should offer prevention and intervention services that directly address the academic stress of the students to ensure academic success.
Students’ opinions on the need for interactive multimedia development for entrepreneurship learning
Authors: Budiarto Mochamad Kamil , Rejekiningsih Triana , Sudiyanto Sudiyanto
Published: December 2021

The use of information technology in education has the potential to have positive outcomes in the face of globalization. This study aimed to identify various needs in order to integrate technology into learning. The study employed a quantitative approach with a survey method to senior high schools. The questionnaire was used as a data collection instrument which was distributed to a research sample of 60 students who were randomly selected. The results revealed that students' attitudes toward the integration of technology into the learning process are inversely proportional to their use of learning media, which is still limited to the printed module. Students would like to create interactive multimedia as a medium for learning craftsmanship and entrepreneurship, based on the needs of students who are technologically literate and efforts to optimize the use of facilities that available at school.
Detection of potential errors in measurement results of madrasa admission instruments in Indonesia
Authors: Yusuf Ahmad , Kusaeri Kusaeri , Hidayatullah Ahmad , Novitasari Dian Candra Rini , Asyhar Ahmad Hanif
Published: December 2021

Madrasa (Islamic boarding school) in Indonesia have a strategic role in character building. At present madrasa education is still considered second class education. Besides, to improve the quality of madrasas can be started by improving the quality of the student national admission to all madrasas in Indonesia. This study aimed to trace the potential errors in the measurement results of Students National Admission of Madrasah Aliyah Negeri (SNPDB MAN-IC) 2020. Tracing was carried out on two aspects: i) Equality between test sets used based on evidence of test responses; and ii) Further tests on equality between question sets based on evidence of relationship between variables, taking into account the origin of the participating schools (MTs/JHS) and the origin of the participating regions (West, Central and East of Indonesia). This study involved 13,115 participants in 23 MAN-ICs throughout Indonesia in 2020. The materials tested comprised learning potential and academic ability (Mathematics, Natural Sciences, Social Studies, English, Arabic, and Islamic Religious Education). The study used achievement test with mathematics as a sample of test subjects. Based on the test response evidence, it was found that seven of the 15 questions were thought to have an indication of inequality between item sets. The results of tracing the evidence between variables indicated that it was the participants' origin of institutions that influenced the inequality between item sets. On the other hand, regional origin did not affect the inequality between item sets because the majority of participants came from the western region of Indonesia.