bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Nano-Cutting Fluid in New Cutting and Forming Processes on Heat Transfer Performance of Mechanical Engineering
Authors: Liu Wei
Published: July 2022

In order to strengthen the thermal conductivity of green cutting fluid and the influence of nano-cutting fluid from new cutting and forming processes on heat transfer performance of mechanical engineering, a research method was proposed based on the influence of nano-cutting fluid from new cutting and forming processes on heat transfer performance of mechanical engineering. The dispersion stability, thermal conductivity, and viscosity characteristics of the nanofluid were studied, and the effects of acidification treatment time, type and concentration of carbon tube particles, surfactants, and testing conditions on the above properties were analyzed. It was found that the filling rate of T321 was about 25% when CNTs were filled, and the optimal compounding ratio of the two surfactants, sodium dodecyl benzenesulfonic acid (SDBS) and Tween-80 (TW-80), for the preparation of stable dispersed nanofluids was 3 ∶ 7. The optimum ratio of compound active agent to carbon tube is 5 ∶ 1. When CNTs were acidified for about 9 h and dispersed in sufficient and stable condition, the thermal conductivity of the base liquid was increased by 110% by the composite, and the shape factor of CNTs had the most significant effect on the thermal conductivity. It was found that the composite nanofluids had higher thermal conductivity and lower viscosity than the nanofluids prepared by ordinary CNTs. This was due to the fact that surfaces of CNTs were chemically modified during the opening and internal filling process, so that the composite had better dispersion stability in the base fluid.
Development and Teaching Application of Japanese Corpus Based on Big Data
Authors: Liu Xuelin , Zhang Hua
Published: July 2022

The establishment of English and French corpora has provided great convenience for language application and research. However, in the field of Japanese language research, the construction of Japanese corpus has been slow due to the limitation of Japanese markup format. This paper discusses the scientificity, rationality, feasibility, and construction of “microcorpus” and “specialized corpus” for the application of Japanese corpus in Japanese language teaching. Textual corpus is a corpus that contains all text but no media such as audio and pictures, and it is mostly used in teaching. The Japanese language corpus is a corpus created by analyzing the existing Japanese classroom teaching situation in response to the current reform of Japanese language teaching mode. It is important for teaching Japanese in colleges and universities because it can help students to learn independently and improve their learning initiative and motivation. The teaching-based text corpus is a small corpus for Japanese language teaching and learning, which is derived from the teaching process. The corpus can be created independently on an ordinary PC machine through software, and the collected corpus can be imported into the corpus and used, which provides another way to improve students’ interest and learning ability on their own. Based on the search software, this paper selects representative novels from the Aozora Library and creates a simple corpus to serve the teaching of Japanese interpretation, which improves the teaching effect. At the same time, this paper discusses the boundaries and difficulties of individual self-built corpora with a view to making breakthroughs and progress in future research and development.
A Study on Early Death Prognosis Model in Adult Patients with Secondary Hemophagocytic Lymphohistiocytosis
Authors: Zhang Ruoxi , Cui Tingting , He Lingbo , Liu Menghan , Hua Zhengjie , Wang Zhao , Wang Yini
Published: July 2022

Background. The mortality risks for secondary hemophagocytic lymphohistiocytosis in the induction stage and investigated prognostic factors need to be further discussed. Objective. The aim of this study is to establish a clinical model for predicting early death in adult patients with secondary hemophagocytic lymphohistiocytosis. Design, Participants, and Main Measures. The baseline characteristics, laboratory examination results, and 8-week survival rate of 139 adult sHLH patients diagnosed from January 2018 to December 2018 were analyzed retrospectively, and a prognostic model was constructed with low-risk (score 0–2), medium-risk (score 3), and high-risk (score ≥ 4) as parameters. Key Results. Univariate analysis confirmed that early death was not related to the type of HLH but significantly related to the patient’s response to first-line treatment. The peripheral blood cell count was significantly decreased, C-reactive protein was higher, glutamyl transpeptidase and total bilirubin were higher, albumin was significantly lower, urea nitrogen was higher, hypocalcemia and hyponatremia, deep organ hemorrhage and D-dimer increased, cardiac function damage and HLH central involvement, sCD25 increased, and EB virus infection were predictive factors of early death. In the multivariate model, patients’ response to first-line treatment was a good predictor of overall survival, and hypocalcemia and deep organ bleeding were associated with poor survival. The risk factors were scored and graded according to the risk ratio. The 8-week overall survival rates of the low-risk group (82 cases), medium-risk group (36 cases), and high-risk group (21 cases) were 85.4%, 52.8%, and 23.8%, respectively (

P

 < 0.001). Conclusions. The early death of sHLH patients is closely related to some laboratory examination results. Attention should be paid to identify high-risk patients, choose effective first-line induction therapy, achieve deep remission as soon as possible, prevent deep organ bleeding, correct electrolyte disorders, and improve the early survival rate of sHLH patients.
Does Digital Economy Contribute to Regional Carbon Productivity? Evidence of China
Authors: Li Zheng , Pang Congling
Published: July 2022

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and “carbon peaking and carbon neutrality goals.” This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China’s digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development.
Energy Efficiency Improvement of Composite Energy Building Energy Supply System Based on Multiobjective Network Sensor Optimization
Authors: Huang Jingyun
Published: July 2022

In order to solve the problem of improving the energy efficiency of the energy supply system, the author proposes a method for improving the energy efficiency of the energy supply system of composite energy buildings based on multiobjective grid optimization, the method solves the energy efficiency improvement of the grid-optimized composite energy building energy supply system, with the increasing material needs of people, the traditional fossil energy consumption is increasing, and the environmental pollution problem is also becoming more and more serious, and people will face serious energy crisis. Due to the high proportion of coal in China’s energy, most thermal power plants use coal as fuel to generate electricity. In the process of coal combustion power generation, a large amount of air pollutants such as CO2, SO2, and Nox are produced, which destroys the ecological environment. In order to alleviate the energy crisis and reduce the emission of polluting gases, the development of renewable energy sources such as wind energy and solar energy is extremely important. Electricity supply and heat supply account for the main part of China’s energy consumption, 40% of China’s energy consumption is used for electricity supply, and 25% is used for heat supply. In terms of electricity supply, 12% of electricity is used for residential use, about 74% is used for industrial production, and 14% is used for commercial development.
Comparative Evaluation of the Optimal Auxiliary Function Method and Numerical Method to Explore the Heat Transfer between Two Parallel Porous Plates of Steady Nanofluids with Brownian and Thermophoretic Influences
Authors: Ullah Hakeem , Khan Rafaqat Ali , Fiza Mehreen , Islam Saeed , Al-Mekhlafi Seham M.
Published: July 2022

In this study, we used the newly established optimal approach, namely, optimal auxilary function method (OAFM) along with the Adams numerical solver technique in order to investigate the heat transfer between two permeable parallel plates of steady nanofluids (HTBTP-SNFs) through Brownian and thermophoretic consequences. The new scheme model (HTBTP-SNFs) in terms of partial differential equations (PDEs) is changed to nonlinear ordinary differential equations (ODEs) by utilizing similarity transformations. The OAFM and Adams numerical methods are used to solve the resulting ODEs with boundary conditions. The OAFM along with convergence and Adams numerical method are studied in detail. The influences of the physical parameters of HTBTP-SNFs model for instance porosity parameter (m), parameter of magnetic (M), parameter of Brownian (Nb), viscosity parameter (R), Schmidt number (Sc), thermophores parameter (Nt), and Prandlt number (Pr) are discussed with the help of tabular data and graphs. The reliability and effectiveness of the technique are achieved by equating the results available in the literature.
The Application of Artificial Intelligence Decision-Making Algorithm in Crisis Analysis and Optimization of the International Court System
Authors: Zhang Yuan , Zhao Yuepeng , Zhao Yueqin
Published: July 2022

Regardless of theoretical research or practical experience, the construction of international wisdom courts has produced a large number of wisdom achievements; however, the scientific convergence between the institutionalized logic of sustainable development and the existing practical achievements has not yet been realized, and there are still problems in the construction of smart courts, such as insufficient practical application, poor system coherence, and insufficient online litigation. Therefore, this study proposes a fusion CNN-GRU network result model that uses a text classification neural network structure convolutional neural network with a good effect to combine the GRU neural network model structure to carry out the task of recommending the law. Promote the development of the connotation of smart courts through the collaborative integration of artificial intelligence technology and system to promote the deep integration of judicial theory and intelligent technology, the deep integration of litigation needs and intelligent technology, and the deep integration of general technology and proprietary development to provide technical mechanisms and legal institutions for the construction of smart courts.
Digital Protection and Utilization of Folk Art Resources Using Virtual Reality Technology
Authors: Wang Shuo
Published: July 2022

Folk art is a “living fossil” of hisory, whose existence and evolution reflect the way people live and think. It is a one-of-a-kind way of communicating the process of human development to the rest of the world. However, as China’s economic development and cultural globalization accelerate, many folk arts are being severely harmed and lost. The emergence of virtual reality technology, which benefits from the advantages of virtual reality technology, has greatly strengthened the utilization and protection of folk art resources in recent years, with the rapid development of Internet technology. Virtual reality technology is a human-computer interaction experience technology that uses complex calculations to provide corresponding operational feedback to the senses of touch, hearing, vision, and balance. It is more reasonable and perfect to reconstruct and integrate the resource content and realize the digital utilization of folk art resources in this paper, which is based on the ALS collaborative filtering algorithm. This paper will make some necessary improvements to the original algorithm, which has met the requirements of virtual reality technology, through the comparison of algorithms. Finally, experiments show that the proposed algorithm’s accuracy is 85 percent higher than the original algorithms, and the data retrieval processing interval is more reasonable.
[Retracted] The Impact of Seeding Density and Nitrogen Rates on Forage Yield and Quality of Avena sativa L
Authors: Kanwal Aroosa , Zubair Dawood , Rehman Rao Mehboob ur , Ibrahim Muhammad , Bashir Muhammad Amjad , Maqbool Muhammad Mudassar , Imran Muhammad , Rehman Ubaid ur , Nasif Omaima , Ansari Mohammad Javed
Published: July 2022

Green forage is an excellent feed source for livestock. It is an integral part of livestock production to accomplish the demands for butter, milk, and other derivatives for human utilization. Livestock contributes 11.39% towards the gross domestic product of Pakistan and 58.33% in agricultural farming. Livestock face shortage or insufficient supply of green fodder during the winter season, which ultimately reduces milk yield. Oat (Avena sativa L.) is a major forage crop in the winter season; however, several biotic and abiotic factors negatively affect its yields. Low soil fertility, particularly nitrogen deficiency, is regarded as one of the few reasons responsible for the low forage yield of oat. Low organic matter content in the soil, suboptimal agronomic practices, and harsh climatic conditions are the other major reasons for low oat yield. Seed rate and different nitrogen rates significantly alter green forage yield and quality of oat. This study assessed the impact of different seeding densities and nitrogen (N) doses on the forage yield of oat. Three seeding densities (70, 80, and 90 kg ha-1) and five N doses (0, 40, 80, 120, and 160 kg ha-1) were included in the study. The interactive effect of seeding density and N doses significantly altered green forage yield and quality attributes of oat. The highest green forage yield (54.67 t ha-1) was noted for the interaction among 90 kg seed rate ha-1 and 160 kg N ha-1. Similarly, the highest germination count (140 m-2), number of tillers (5.97 m-2), plant height (122.97 cm), number of leaves per plant (24.50 m-2), leaf area per tiller (123.18 cm2), fresh weight (5.47 kg m-2), dry weight (1692 g m-2), dry matter yield (20.90 t ha-1), crude protein (10.54%), crude fiber (31.62%), and total ash (9.39%) were recorded for the interactive effect of 90 kg seed rate ha-1 and 160 kg N ha-1. Economic analysis revealed that interaction between 90 kg seed rate ha-1 with 120 and 160 kg N ha-1 was superior to others with higher benefit: cost ratio and net economic returns. It is recommended that the oat seed rate of forage oat crop must be kept at 90 kg ha-1 and it should be supplied 120 kg N ha-1 for higher yield, better quality, and more economic returns.
Robust Trajectory-Tracking Control of a Rotorcraft Using Immersion-and-Invariance-Based Adaptive Backstepping Control
Authors: Choi Yoo-Seung , Lee Il-Ryeong , An Jun-Young , Cho Moon-Gyeang , Kim Chang-Joo
Published: July 2022

This paper investigates an adaptive backstepping control based on the immersion-and-invariance (I&I) method for a rotorcraft’s trajectory-tracking control problem. To effectively cope with both parametric uncertainties and external disturbances affecting all forces and moments of a rotorcraft, the I&I-based disturbance observer is designed and combined with an adaptive backstepping controller. During the design process, a simple form of the observer structure is suggested, and the performance of the observer is analyzed using a candidate Lyapunov function. Then, the closed-loop stability of the adaptive controller is analyzed for both time-invariant and time-varying disturbances. Additionally, the tuning function-based adaptive backstepping controller is designed and used to investigate the outperformance achievable with the proposed method. Finally, comparative simulation results using a high-fidelity rotorcraft math model is provided to show the effectiveness of the proposed strategy.
Antibacterial Activity of Bismuth Oxide Nanoparticles Compared to Amikacin against Acinetobacter baumannii and Staphylococcus aureus
Authors: Jawad Kareem H. , Marzoog Thorria R. , Hasoon Buthenia A. , Sulaiman Ghassan M. , Jabir Majid S. , Ahmed Elsadig M. , Khalil Khalil A. A.
Published: July 2022

In this work, bismuth oxide nanoparticles (Bi2O3 NP) were prepared by laser ablation of a solid target in distilled water. The optical and structural properties of Bi2O3 NPs were studied using UV–VIS spectroscopy, energy‐dispersive X‐ray spectroscopy (EDS), transmission electron microscope (TEM), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR). The results showed that the average particle size is less than 20 nm. The antibacterial activity of the Bi2O3 NPs was determined and compared with amikacin against Acinetobacter baumannii and Staphylococcus aureus. The activity of Bi2O3 NPs was higher than the amikacin. Furthermore, the antibacterial activity of Bi2O3 NPs against S. aureus bacteria was higher than Acinetobacter baumannii; this result was confirmed by studying the effect of Bi2O3 NPs in bacterial biofilm formation in eyes contact lenses using atomic force microscopy (AFM) technique. Taken together, Bi2O3 NPs could be used as a preservative for contact lenses as eye drops to prevent the formation of microbial biofilms in contact lenses.
Rapid Determination of Aflatoxin B1 Contamination in Peanut Oil by Fourier Transform Near-Infrared Spectroscopy
Authors: Yao Wanqing , Liu Ruanshan , Xu Zhaocheng , Zhang Yuling , Deng Yingming , Guo Hongwei
Published: July 2022

Aflatoxin B1 (AFB1) contamination in peanut oil brings about a significant threat to human health. A method based on Fourier transform near-infrared (FT-NIR) spectroscopy was developed for qualitative and quantitative analysis of AFB1 contamination in peanut oil. A total of 94 samples were collected in the transmission mode and processed by a derivative and smoothing filter. Principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLS) were applied to establish the qualitative and quantitative analysis models. It was demonstrated that the qualitative model could distinguish effectively between the positive and negative samples with identification accuracy up to 100%. The correlation coefficient (R2), the root mean square error of calibration (RMSCE), and the relative percent deviation (RPD) for the quantitative model were 0.951, 3.87%, and 4.52, respectively. There was a good linear relationship between the predicted and reference concentrations of the samples with a significant correlation coefficient of 0.981. The qualitative and quantitative analysis models developed in this work may provide reference for researchers engaged in nondestructive testing of food and agricultural products.
Digital Library Information Integration System Based on Big Data and Deep Learning
Authors: Lin Xiao , Zhang Ying , Wang Jiangong
Published: July 2022

In order to solve the defects of traditional text classification in digital library, the author proposes a method based on deep learning in the field of big data and artificial intelligence, which is applied to the digital library information integration system. On the basis of systematically sorting out the traditional text classification of digital library of this method, this paper proposes a digital library text classification model based on deep learning and uses the word vector method to represent text features, the convolutional neural network in the deep learning model is used to extract the essential features of text information, and experimental verification is carried out. Experimental results show that deep learning-based text classification model can effectively improve the accuracy (average 94.8%) and recall (average 94.5%) of text classification in digital libraries; compared with the traditional text classification method, the text classification method based on deep learning improves the average F1 value by about 11.6%. Conclusion. This method can not only improve the intelligence of the internal business of the digital library, but also improve the efficiency and quality of the information service of the digital library.
5-Alpha Reductase Inhibitor Use and Prostate Cancer Prevention: A Victim of the Times?
Authors: Hamilton Robert J.
Published: July 2022

Vaselkiv and colleagues present strong evidence of the long-term safety of 5-alpha reductase inhibitor (5-ARI) use. They demonstrated no association with developing advanced prostate cancer, nor dying of prostate cancer. This commentary covers the strengths and weaknesses of the article, and highlights the long and vacillating journey 5-ARIs and prostate cancer prevention have traveled. As 5-ARIs preferentially prevent low-grade prostate cancer, a fact confirmed in the study by Vaselkiv and colleagues, this commentary highlights how 5-ARI chemoprevention may be irrelevant now. With increasing use of active surveillance for low-grade prostate cancers found, and prebiopsy MRI and biomarkers shifting focus to only find those clinically significant cancers, it maybe that 5-ARIs are a victim of the times in their chemoprevention role.

See related article by Vaselkiv et al., p. 1460
Improved Sleep Quality Is Associated with Reduced Insulin Resistance in Cancer Survivors Undertaking Circuit, Interval-Based Exercise
Authors: Normann AJ , Kang D-W , Christopher CN , Norris MK , Dieli-Conwright CM
Published: July 2022

Purpose: Cancer patients often experience poor sleep quality, typically induced by cancer-related treatments, a sedentary lifestyle, and psychological distress, leading to an increased risk of metabolic dysregulation such as obesity and insulin resistance. In this novel 16-week pilot study, we examined the effect of a circuit-based aerobic and resistance exercise intervention on self-reported sleep quality in breast, prostate, and colorectal cancer survivors and explored the association between changes in sleep quality and insulin resistance. Methods: Survivors of breast, prostate or colorectal cancers who were sedentary, overweight or obese (BMI>25.0 kg/m2) were randomized to exercise (n=60) or usual care (n=30). The 16-week intervention included supervised moderate-vigorous aerobic (65-85% of VO2max) and resistance (65-85% of 1-repetition maximum) exercise performed in a circuit, interval fashion three times per week. Patient-reported sleep quality and insulin resistance were assessed at baseline and post-intervention using Pittsburgh Sleep Quality Index (PSQI) and Homeostasis Model of Assessment (HOMA-IR), respectively. Mean changes in PSQI score that are negative demonstrate improvements in sleep. Between-group differences were determined using repeated-measures analysis of variance. Associations between changes in PSQI and insulin resistance were computed using Pearson correlations. Results: Participants were 63.2±10.8 years old, obese (87%), female (55%), and completed chemotherapy + radiation therapy (75%). Adherence to the intervention was 92% and the retention rate was 100%. Post-intervention, the PSQI global score improved significantly in the exercise group when compared to usual care (mean between-group difference, -2.7; 95% CI, -4.2 to -0.6). Change in PSQI was inversely associated with change in HOMA-IR (r=-0.91; p<0.01) among the exercise group. Conclusions: A circuit, interval-based aerobic and resistance exercise intervention improved patient-reported sleep quality in breast, prostate, and colorectal cancer survivors. Additionally, this exercise-induced improvement in sleep-quality may result in reduced insulin resistance.
Multi-Level Factors Are Associated with Uptake of Cervical Cancer Screening in Sexual and Gender Diverse Adults Residing in Arizona
Authors: Nair UN , Madhivanan P , Saad ER , Adsul P
Published: July 2022

Introduction: Despite availability of effective screening practices for early detection and prevention of invasive cervical cancer, emerging research suggests lesbian, bisexual, and transgender (LBT) individuals are less likely to undergo routine cervical cancer screening (CCS). Systematically examining factors for low CCS uptake in this population using a socioecological lens is key to designing and implementing effective interventions to reduce cancer-related death and disease. As the first step to this approach, the purpose of the study was to examine multi-level factors associated with CCS in LBT adults residing within the state of Arizona. Methods: Self-identified LBT adults with a cervix between the ages of 18-50 were invited to complete a one-time online survey assessing sociodemographic characteristics, health seeking practices, and CCS behaviors. Results: Of the 273 participants who completed the study; 62.5% identified as cisgender, 28.7% as transgender/gender nonconforming. Over 35% were gay/lesbian, and 30.8% identified as bisexual. Almost a quarter of participants reported never having received a Pap test. Fifty-four percent of all participants reported feeling uncomfortable discussing their health needs with a healthcare provider and over 60% were unsure of proactively asking their primary care provider for a Pap test. While 75% of participants who reported never receiving a CCS were sexually active in the past 12 months (a risk factor for cervical cancer), 53% were not sure if getting a Pap test was important (vs. 10% of those who received a CCS). Compared to those who had received a CCS, those who had never been screened had significantly lower cancer screening self-efficacy scores (t=5.18; p<.001) and were less likely to know someone in their social network who had received CCS (70% vs 38%; p<.001) suggesting that social norms may impact screening behaviors in this population. Conclusion: Interventions to increase CCS in this population may need to target proximal (knowledge, self-efficacy) and distal factors (social support, and strategies to improve provider communication strategies) while taking into consideration community-partnership guided participatory and implementation science approaches.
The Association Between Cancer and Alzheimer's-Type Neuropathology: A Community-Based Cohort Study
Authors: Karanth SD , Katsumata Y , Nelson PT , Fardo DW , McDowell JK , Schmitt FA , Kryscio RJ , Browning SR , Abner EL
Published: July 2022

Background: Cancer and Alzheimer's disease are common diseases in aging populations. Intriguingly, prior research has reported a lower incidence of Alzheimer's disease dementia among individuals with a history of cancer. Both are prevalent and lethal conditions. The current study was conducted to investigate the association of cancer history with neuropathological and cognitive features. Methods: Data were drawn from elderly, longitudinally evaluated participants in a community-based cohort study of aging and dementia who came to autopsy at the University of Kentucky Alzheimer's Disease Research Center. The data were linked to the Kentucky Cancer Registry, which is a population-based state cancer surveillance system, to obtain cancer-related data. We examined the relationship between cancer history, clinical dementia diagnoses, Mini-Mental State examination test scores, and neuropathological features using inverse probability weighting to address confounding and selection bias. Results: Included participants (n = 785) had a mean ±SD age of death of 83.8 ±8.6 years; 60.1% were female. Positive cancer history was determined in 190 (24.2%) participants. The prevalence of at least one APOE ε4 allele was lower among participants with cancer history compared to cancer-free participants (32.6% vs 42.0%, P = 0.0063). Participants with cancer history had lower odds of MCI/Dementia, and higher cognitive test scores (e.g., comparing MMSE scores evaluated at six and < two years prior to death., P < 0.001). Cancer history was also associated with reduced odds of intermediate (III/IV) or severe (V/VI) Braak Neurofibrillary tangle stages, moderate/frequent neuritic plaques, moderate/frequent diffuse plaques, and moderate/severe cerebral amyloid angiopathy (all P<0.05). By contrast, TDP-43, √é±-synuclein, and cerebrovascular pathologies were not associated with cancer history. Conclusion: In this study, we showed that cancer history was associated with a lower burden of Alzheimer's disease pathology and clinical dementia. These findings provide an additional basis of support for prior epidemiological research reporting a protective association between cancer and Alzheimer's disease-type dementia.
Problematic Use of Video Games, Social Media, and Alcohol: Associations with Mother-Child Relationship
Authors: Wartberg Lutz , Kramer Michaela , Potzel Katrin , Kammerl Rudolf
Published: July 2022

Introduction: According to current concepts of developmental tasks, both the use of digital media and the consumption of psychotropic substances are age-typical challenges for adolescents. The majority overcomes these developmental tasks, but a substantial proportion of youth develops problematic usage patterns (e.g., of video games) or problematic consumption behavior (e.g., of alcohol). Empirical findings show the importance of family aspects for these problematic behavior patterns. Currently, it is not clear which specific areas of parent-child relationship are associated in each case and whether there are differences between substance-related and substance-unrelated problematic behavioral patterns. Methods: We surveyed 480 adolescents (45.2% females, mean age = 16.84 years) with standardized instruments regarding the mother-child relationship as well as problematic gaming, problematic social media use, and problematic alcohol use. We conducted correlation and multiple linear regression analyses (separately for problematic gaming, problematic social media use, and problematic alcohol use) as well as a multivariate multiple regression analysis. Results: In the regression analyses, more conflicts with the mother were related to all three behavioral patterns. However, lower cohesion was only statistically significantly associated with problematic alcohol use, but not with problematic gaming and problematic social media use, whereas lower autonomy and more frequent punishment of the child were statistically significantly related to problematic gaming and problematic social media use, but not to problematic alcohol use. Discussion/Conclusion: The findings indicate partially different relational dynamics for substance-related and substance-unrelated problem behaviors (interestingly, for cohesion and autonomy, the 95% confidence intervals of the standardized regression coefficients were not overlapping). The results of the present study could be used in family-based prevention approaches or in treatments in the clinical setting.
Hyper content e-module in information behavior course with the assistant of screencast
Authors: Johan Riche Cynthia , Rullyana Gema , Ardiansah Ardiansah
Published: July 2022

In the 21st century, continuous innovation and adaptation in every component of learning is required in education, both in the competency component, material content, strategy and media, as well as its evaluation. This study emphasized the development of an electronic or digital module in the information behavior course, it is one of the courses regarding the characteristics of the student activity level that accommodates information retrieval and strives to use appropriate information. The e-module design is developed utilize the 4D model by define, design, develop and disseminate. The participants of this research involved media experts, material experts and students of the Library and Information Science study program at two universities, which are are Universitas Pendidikan Indonesia and Universitas Negeri Malang, there are 20 people in total who used e-modules in limited dissemination on information behavior course. This research revealed the electronic module in the course, the emphasis of the module content design which is enriched with digital-based information sources or in another word called as hyper content that becomes a differentiator in presenting the module content, coupled with the power of audio and visual media or called as screencast. Through this research, lecturers able to prepare independent learning materials by utilizing digital technology.
Classification of covid patient image dataset using modified deep convolutional neural network system
Authors: Alagarsamy Manjunathan , Anbalagan Karthikram , Thangavel Yuvaraja , Sakkarai Jeevitha , Pauliah Jenopaul , Suriyan Kannadhasan
Published: July 2022

The number of people infected with the corona virus is steadily rising. Even after being treated and returned to normality, many who were impacted are still suffering from a variety of health problems. We suggest a new, more effective approach to dealing with this issue, as well as putting in place preventative measures to prevent the spread of disease. The modified convolutional neural networks (M-CNN) architecture is modified deepCNN architecture. Using existingcorona virus disease 2019(COVID-19) computerizedtomographyscan (CT scan) images, this suggested approach intends to develop a deep model for screening and forecasting the risk of disease propagation. The suggested model was trained using 1000 scan pictures from various sources, yielding a prediction accuracy of 93 percent, which is much greater than previous methods.
Window averaging to create LBP features for a color image
Authors: J. Qaryouti Ghazi M. , Krishan Monzer M. , Kanan Monther A. , M. Alasmer E. Ziad
Published: July 2022

Digital color images are widely used in various computer applications. Some of these applications such as digital image recognition systems require dealing with image classifiers which can be formed as a set of values representing the image. In this paper a simple method of image features victor creation will be proposed, the method will be tested and implemented, the obtained experimental results will be analyzed to ensure that each generated features victor is unique. The proposed method will be based on a window averaging, the window size can be easily changed without affecting the features victor size.
The effects of material’s features and feeding mechanism on high-gain antenna construction
Authors: A. Al-Falahi Hamed , Ahmed Smait Drai , Abduljabbar Rashid Sami , Nozad Mahmood Sarmad , Alani Sameer
Published: July 2022

This study investigates the performance of flexible, wideband antennas with high gain properties. The high gain feature can often be obtained by positioning a reflector in the same planes as the adjacent radiator. For flexibility, this survey discusses the antennas that were printed on the flexible substrate materials. Based on these properties, the antenna can be recognized in a variety of wireless applications, including wireless local-area-network (WLAN), Worldwide Interoperability for microwave access (WI-Max), wireless body area network (WBAN), and radio frequency identification (RFID), as well as wearable applications. The high-gain antennas are compact radio wave-based antennas that provide precise radio transmission management. Such antennas deliver more energy to the receiver, increasing the frequency of the received signal. By gathering more power, high-gain antennas may emit signals quicker. Furthermore, because directional antennas broadcast fewer signals from the main wave, interference may be greatly minimized. Finally, this article identifies the role of lightweight high gain flexible antennas in terms of their size, substrate materials, design, and feeding mechanisms, all of which can affect bandwidth, gain, radiation efficiency, and other important factors.
Performance enhancement of DCMLI fed DTC-PMSM drive in electric vehicle
Authors: Shriwastava Rakesh G. , Thakare Mohan P. , Bhadane Kishor Vinayak , Harne Mahesh S. , Wagh Nandkumar B.
Published: July 2022

This paper focus on the simulation and hardware analysis of a diode clamped multilevel inverter (DCMLI) fed direct torque control (DTC) permanent magnet synchronous motor (PMSM) drive in electric vehicle (EV) application. DTC-PMSM drive is more used for torque and speed control. The existing DTC PMSM drive consists of torque and flux hysteresis comparators and suffers from variable switching frequency and torque ripples. These problems can be solved by using carrier-based space vector modulation (CBSVM) about torque and flux. In this proposed approach a DCMLI fed 4 poles, 0.5 HP DTC PMSM drive system is designed and simulated using carrier-based CBSVM. Simulation and experimental implementation are carried out in MATLAB environment and AVR Microcontroller respectively. The simulated performances are studied in steady-state and transient conditions for varying load, speed, and torque. The results of the DTC-PMSM drive system using CBSVM show that the proposed method can effectively reduce the torque ripple and maintain a constant speed and also improved driving performance of drive for electric vehicle applications.
Intelligent evacuation model in disaster mitigation
Authors: Safii M , Efendi Syahril , Zarlis Muhammad , Mawengkang Herman
Published: July 2022

Mitigation is a pre-disaster action that aims to prepare for a disaster situation. One of the mitigation activities is evacuation, which aims to reduce disaster-related losses. Because disaster damage cannot be predicted, dealing with evacuation efforts requires a dynamic model. This study will utilize a dynamic model that combines the game theory model for choosing the evacuation location and the open vehicle routing problem (OVRP) model for selecting evacuation routes to create an intelligent system. The game theory model will be used to supplement the selection of alternate evacuation locations by taking into account geographical features that are very uncertain in the event of a crisis. An evacuation route equipped with an OVRP model with the goal of optimizing travel time is required to mobilize disaster-affected people. With the development of the Intelligent Evacuation System idea, combining the two models will create a new model. The simulation model is evaluated using linear, interactive, and discrete optimizer (LINDO), which may minimize the evacuation time from the evacuation route to a safe destination by 50 minutes if there is no contra-flow to allow more people to be evacuated.
Mobile development: learn du’a for early childhood learners
Authors: Ariff Mohamed Imran Mohamed , Annuar Natasha Irina Khairul , Najmuddin Ahmad Farid , Ibrahim Ireen Munira , Arshad Noreen Izza , Ahmad Samsiah , Salleh Khairulliza Ahmad
Published: July 2022

This project stands by acknowledging the use of mobile technology is progressively popular among early childhood learners in recent years. But, an extensive systematic literature search on educational mobile technology and touchscreen indicated that most of the applications are not suitable for early childhood learners as it lacks several multimedia features. Therefore, this project designates the development procedure of an educational mobile application for early childhood learners, who are very receptive to new knowledge and information. As a proof of concept, the development of this application utilizes the learning of the Islamic du’a recitation. This application was designed using the android studio and the flutter software combined with the java programming language. Upon the development of this application, several testings were done and analyzed. The result shows that users were satisfied with the applications as most of the testing scores were highly rated. Based on these results, the usage of this newly mobile application can be suggested to be adopted by early childhood learners.
Random early detection-quadratic linear: an enhanced active queue management algorithm
Authors: Hassan Samuuel Oluwatosin , Nwaocha Vivian Ogochukwu , Rufai Adewole Usman , Odule Tola John , Enem Theophilus Aniemeka , Ogundele Lukman Adebayo , Usman Suleiman Abu
Published: July 2022

This paper identifies the lone linear drop function for computing the dropping probability between certain queue threshold values as a major weakness for the random early detection (RED) algorithm as it leads to large delay and queue instability. To address this concern, we propose an enhanced RED-based algorithm called random early detection-quadratic linear (referred to as “RED-QL”) active queue management (AQM) which leveraged the benefit of a quadratic packet drop function for a light-to moderate traffic load conditions together with a linear packet drop function for a heavy traffic load condition respectively. Results from ns-3 network simulator using different experimental scenarios clearly reveals that the proposed RED-QL algorithm yields a substantial reduction in delay performance and indeed a reduced average queue size than other three representative AQM algorithms. RED-QL is robust, easy to implement and deploy in routers (both in software and hardware) as no more than the packet drop probability profile of the classic RED’s algorithm implementation needs modest alteration.
Evaluation of brushless DC motor structure design for the electric impact using 3-D finite element analysis
Authors: Raja M. Senthil , Geethalakshmi B.
Published: July 2022

In this article, an analytical model is deployed to optimize and design an interior permanent magnet brushless DC motor (IPMBLDC motor) when compared to theoretical structure of IPMBLDC. In this motor, assume air-gap of magnet assembly, distribution of flux density coefficient, selection of functional point in the permanent magnet, Torque density, and permanent magnet dimension compares with air-gap were deployed in an ideal design model. An equivalent circuit of magnetic field was improved and compare with the total flux density distribution and the torque density efficiency is based on initial ideal design factors. In finite element of MAXWELL 3D method, an electromagnetic field is investigated and used to verify an advanced equivalent circuit of magnetic field and improve the IPMBLDC motor factors. Finally, simulation results of IPMBLDC motor are verify and compare with ideal factors of IPMBLDC motor.
Factors affecting readiness toward online learning among medical students during COVID-19 pandemic in Indonesia
Authors: Wiranto Rony , Syakurah Rizma Adlia
Published: July 2022

The rapid spread of transmission COVID-19 leads to the government applied a regulation to close schools and colleges for a while, as an effort to stop the spread. It also has an impact on medical student education that can be threatened by their educational system. This study identified and analyzed the factors affecting the readiness of medical students for studying online during the COVID-19 pandemic. This was an observational analytic study with a cross-sectional approach. A total of 3,331 respondents from all over Indonesia participated in this study. An online questionnaire by Indonesian Medical Student Senate Association (Ikatan Senat Mahasiswa Kedokteran Indonesia/ISMKI) was used and distributed from April 9th, 2020 to June 21st, 2020. A Chi-square test (alternative: Fisher exact test) and logistic regression with significance alpha=0.05 used to analyze. The university origin (p=0.031, OR=1.130 (1.012–1.263)), internet connections (p=0.001, OR=1.387 (1.134–1.696)), and learning interaction models (p<0.000, OR=0.463 (0.384–0.558)) were affected medical students’ readiness for online learning.
Virtual worlds in distance learning
Authors: Cruz Vázquez Jonathan Axel , Ruiz Ledesma Elena Fabiola , Chavarría Báez Lorena
Published: July 2022

Virtual worlds are considered an additional proposal within the e-learning model. Online platforms have not been enough resources to be successful in the teaching and learning processes, therefore, it is necessary to search more options that contribute to their improvement. Virtual worlds, through inverse and visual experiences for the student, offer new panoramas that allow living situations and solving problems in different areas, such as mathematics. This article analyzes the opinion of higher-level students regarding the use of virtual worlds in their distance classes. Likewise, the virtual worlds provide help in improving teacher-student and student-student relationships. Some cases of educational institutions that integrated the use of virtual worlds into their classes are shown. A Likert-type scale questionnaire has been applied to a sample of 65 higher-level students. Its reliability was validated by means of Cronbach's alpha coefficients and Pearson's. It was found that students consider that the use of virtual worlds would improve class work and relationships between their peers and their teachers. It is remarkably undoubted that virtual worlds within education path are considered an excellent tool for e-learning. However, although the interest on the part of students is high, it is necessary to carry out more researching and developing procedures on the virtual worlds as an alternative to support learning. 
Free drawing learning to recognize children’s characters
Authors: Mayar Farida , Putra Febri Wandha , Fadli Rima Pratiwi
Published: July 2022

This descriptive qualitative study described the personality or characteristics of children based on the colors used in drawing activities. The subjects in this study were the Pembina Kindergarten students in the city of Padang, West Sumatra, Indonesia. They were determined by using snowball sampling technique. The data collected through observations and documentation analysis by researchers without being directly involved in activities. The data analysis technique used was an interactive model which consists of three activity lines: i) Data reduction; ii) Data display; and iii) Drawing conclusions and data verification. 
Online teaching in an Indonesian higher education institution: Student’s perspective
Authors: Habeahan Nova Lina Sari , Leba Seli Marlina Radja , Wahyuniar Wahyuniar , Tarigan Dina Br , Asaloei Sandra Ingried , Werang Basilius Redan
Published: July 2022

Online teaching has been pushed further as the best solution that addresses the challenges of colleges and universities closure during the COVID-19 pandemic. This study intended to disclose students’ perceptions of the online teaching. A quantitative survey approach was employed to collect data from a total of 175 students which were conveniently established from amongst students enrolled in academic year 2020/2021 at the Indonesian Language and Literature Education Department of Musamus University, Indonesia. Applying the SPSS software version 16 as the tool, obtained data were quantitatively analyzed using descriptive analysis of frequencies and percentages. The results showed the majority of respondent were disagreeing with the facts that they have an access to personal devices and that they can easily access to both internet and online classes. The majority of respondent were agreeing with the facts that teaching materials were well-planned and that various learning strategies were used to help students understand. The majority of respondent were agreeing with the facts that students were given opportunity to raise and answer the questions and that feedback given on students’ work are very helpful. Lecturers need to reach out and check students’ conditions before starting online teaching.