bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Covid-19 on Social Relations among Jordanian Families in Amman
Authors: Alhajjaj Huda A. , Taha Sara A.
Published: November 2023

Objectives: This study aims to investigate how the Covid-19 pandemic affected social relations among Jordanian families, including social and parental relationships. Furthermore, it aims to highlight the influence of the pandemic on family cohesiveness and stability.
Methods: A qualitative technique was used, being effective in extracting information on the influence of Covid-19 on Jordanian family relations (BTS Academy, 2018). The members of the study sample were sixteen Jordanian couples having children living in Amman. They were interviewed during November 2021.
Results: The results reveal that Covid-19 has a significant impact on social relations among family members, because of drastic and dramatic changes in the social and economic lifestyle. These changes contributed to the increase of violence between spouses. Surprisingly, the results show that, during the pandemic, the level of disagreement and conflict between parents and children was reduced. The results also indicate that Covid-19 had an influence not only on family interactions, but also on family atmosphere, namely the stability and coherence within that atmosphere.
Conclusions: The research recommends providing online counseling sessions by family-focused institutions to couples to assist them in adapting to the changes that have occurred in their relationships throughout the epidemic.
Spatial Inequities in Advanced Placement® STEM Success: Investigating Rural Disparities in Examination Results
Authors: Boles Kelly L. , Domingue Benjamin
Published: November 2023

This study investigates the geographic landscape of student success on Advanced Placement® (AP®) examinations. Using a licensed, proprietary dataset containing the full population of AP® exams (N = 16,993,460) taken in the U.S. between 2016 and 2019, we conduct a series of multivariate regressions to estimate possible associations between a student’s school locale and AP® exam outcomes. These models include state by exam by year fixed effects and covariates to adjust for student and community demographics. We find that AP® examination success varies by geographic locale, with sizable gaps occurring between rural/non-rural students. These rural/non-rural differences widen in AP® STEM, with rural students generally scoring lower (-0.227 points ) and city students, higher (0.122 points ) than their suburban peers. These disparities widen in highly technical, high math-demand fields, as well as for the two more distant/remote locale classifications when rural is disaggregated into subtypes.
The Impact of Capital Structure, Firm Size, Growth, And Profitability on Firm Value
Authors: Irsad Moch , Sudarsi Sri , Kartika Andi
Published: November 2023

The study aims to be carried to ascertain the effect of capital structure, firm's size, growth, and profitability upon firm value. Previous research on corporate value produced inconsistent results, indicating that more research is required to assess firm worth. In the 2019-2021 period, Third-party information in the structure of annual reports on transportation sector firms collected from the IDX site is applied by researchers. Purposive sampling was utilized in this study. Data analysis approaches such as descriptive statistical analysis and multiple linear regression analysis were used in this study. First, descriptive statistics, classical hypothesis testing, multiple linear regression analysis, and hypothesis testing are accomplished. According to the results of this study, firm size and profitability have an impact on firm value, however capital structure and growth have no impact on firm value.
Persepsi Nilai Mampu Memediasi Terwujudnya Kepuasan Pelanggan
Authors: Wafa Riki Siril , Sujito Sujito , Kuswardani DC
Published: November 2023

This Research Is To Examine And Analyze The Effect Of Customer Experience, Customer Expectations And Perceived Quality On Customer Satisfaction With Perceived Value As An Intervening Variable In An Empirical Study On Zeta Green At Pt Dipo Technology. The Problem Faced By Pt Dipo Technology Is An Increase In Complaints From Customers And A Decreased Percentage Of Satisfaction. This Research Was Conducted Using The Quantitative Research Method And Analyzed Using Smartpls 4. The Population In This Study Were Customers Who Had Purchased Zeta Green Products More Than Once, A Total Of 171 People. The Sample Used Was 120 People. The Determination Of The Sample In This Study Used Non-Probability Sampling And The Sampling Technique Was Purposive Sampling. The Results Of The Analysis Show That Customer Experience, Customer Expectations And Perceived Quality Have A Positive And Significant Effect On Perceived Value And Customer Satisfaction. Perceived Value Is Able To Mediate The Effect Of Customer Experience, Customer Expectations And Perceived Quality On Customer Satisfaction. Based On The Adjusted R Square Value, It Explains That Customer Experience, Customer Expectations, Perceived Quality And Perceived Value Affect Customer Satisfaction By 81.3% And The Rest Is Explained By Other Variables Not Present In The Study.
Pengaruh Marketing Mix Terhadap Kepuasan Dan Loyalitas Konsumen Generasi Muda
Authors: Atmaja R.Ferry Bakti , Saputro Seno Hadi , Isnanto R. Burham , Alkodri Ari Amir
Published: November 2023

The younger generation is increasingly playing an important role in many areas of life in line with the development of science and technology. In the economic field, youth has played a role as an economic driver, both as a businessman and as a potential target market for company owners. By understanding the right marketing strategy according to the character of this segment, the company will be able to gain increased market share and long-term profits. This research is a quantitative study intending to find the effect of the marketing mix strategy consisting of Product, Price, Place, Promotion, People, Process and Physical Evidence on customer satisfaction and loyalty in the culinary field. Data was collected using a questionnaire technique and analyzed through Moderated Regression Analysis. The results of this study are that Promotion has an effect of 0.374 on loyalty, People has an effect of 0.172 and Place has an effect of 0.240 while other factors cannot be proven to have an effect. The Satisfaction variable is only able to mediate and strengthen the influence on the People factor
Silybum Marianum'un Broiler Böbreğinde Methomyl Hasarına Karşı Etkilerinin Patolojik ve Biyokimyasal Olarak Araştırılması
Authors: KILINÇ Bahadır , ORUÇ Ertan
Published: November 2023

Bu çalışmada broilerlerde Methomyl toksikasyonuna bağlı oluşan böbrek hasarına karşı Silybum marianum tohumu tozunun koruyucu/önleyici ya da iyileştirici etkilerinin araştırılması amaçlanmıştır. 28 gün olarak planlanlanan çalışmada Konrol grubu (KONT), Methomyl grubu (MET), Silybum marianum tohumu tozu grubu (SMT) ve Methomyl+Silybum marianum tohumu tozu grubu (MET+SMT) olmak üzere her birisinde 32 hayvan bulunan 4 farklı grup oluşturuldu. Methomyl 20 ppm, Silybum marianum tohumu tozu ise 10 gr/kg olarak yemlere ilave edildi. Deneme süresince haftalık olarak her bir gruptan 8 hayvanın nekropsileri yapılarak biyokimyasal ve histopatolojik incelemeler için örnekler alındı. Biyokimyasal incelemeler için alınan serum örneklerinden total protein, kreatinin ve ürik asit parametrelerin ölçümleri yapıldı. Histopatolojik incelemelerde ise böbreklerde hiperemi, tubulus epitellerinde dejenerasyon ve nekroz, Bowman kapsülünde kalınlaşma, intertubuler alanda kanama ve yangısal hücre infiltrasyonu, tubulus bazal membranlarında kalınlaşma bulguları değerlendirildi. Çalışmada her hafta kan serumlarında yapılan analizlerde kreatinin, ürik asit ve total protein değerleri KONT ve SMT gruplarında benzer bulunurken, MET gruplarında, KONT ve SMT gruplarına kıyasla istatistiksel olarak yüksek saptanmıştır. MET+SMT grubunda ise ilgili parametrelerin değerleri MET grubuna göre düşük olduğu görülmüştür. Methomyl verilen tüm gruplarda, böbrek dokularında 14’üncü gün ölçümlerde belirginleşen, 21 ve 28’inci günlerde zamana bağlı olarak şiddeti artan hasar meydana gelmiştir. Koruyucu/iyileştirici amaçla verilen Silybum marianum’un ise biyokimyasal ve histopatolojik düzeyde hasarları azalttığı gözlemlenmiştir.
“White Empiricism” and “The Racialization of Epistemology in Physics”: A Critical Analysis*
Authors: Sokal Alan
Published: November 2023

I critically analyze the reasoning in Chanda Prescod-Weinstein’s article “Making Black women scientists under white empiricism: The racialization of epistemology in physics”.
The Word That Dare Not Speak Its Name
Authors: Caughie Pamela L.
Published: November 2023

This essay asks, when does our effort to avoid offending students interfere with our ability to teach them? Rehearsing conflicts over language and terminology, over who can speak and what can be said, from my four-decade career as a literature professor, critical theorist, and gender scholar, I confront contemporary efforts to censor certain words, to prohibit certain kinds of inquiry, and to limit who can speak about certain subjects by placing recent incidents in relation to previous debates in academia and the public sphere. The university classroom and scholarly peer-reviewed journals have long served as spaces where established viewpoints can be questioned, knowledge can be challenged, and identities can be probed. Increasingly, however, we see classroom curricula under attack, books banned, language policed, and viewpoints prohibited, with teachers, students, and scholars self-censoring as a result. What happens when words are prohibited, and research subjects are deemed off limit, because some fear they may harm fragile young students or readers? Refusing to have that conversation, to allow scholars and teachers to debate controversial positions openly, itself does the harm. Through examples drawn from my teaching and scholarship, and drawing on newspaper editorials and academic publications, I model a means for working through this seeming impasse encapsulated by the title phrase, “the word that dare not speak its name.”
Enhancing Realistic Remaining Useful Life Prediction using Multi-Fidelity Physic-Informed Neural Network Approach
Authors: Noh Yoojeong , Mochammad Solichin , Kim Nam Ho
Published: November 2023

The prediction of remaining useful life (RUL) for a component requires a certain failure threshold to be reached. However, using only monitoring data available up to the current time in prognosis can lead to unrealistic RUL predictions. To address this issue, this study proposes a multi-fidelity approach that uses discrepancy predictions to inform a physical model for RUL estimation. Discrepancy predictions are obtained by training the difference between low- and high-fidelity models using a neural network. The low- and high-fidelity models are constructed using the exponential function and monitoring data from experimental work, respectively. As the exponential function has a monotonically increasing trend, a multi-fidelity model can lead to realistic RUL predictions. This proposed method was tested on several failure cases involving rotating components, such as bearings and unbalanced cooling fans. The results show that the proposed method yields realistic and accurate RUL predictions, despite the lack of available monitoring data.
Sensitivity enhanced method for fault detection and prediction of elevator doors using a margin maximized hyperspace
Authors: Kim Minjae , Son Seho , Oh Kiyong
Published: November 2023

This paper proposes novel fault classification and prediction method by addressing a margin maximized hyperspace (MMH) to solve the problems absent of any label at highly imbalanced dataset, which is a frequent but challenging problem in real-world industries. The proposed method features three characteristics. First, knowledge-based feature manipulation is executed using reference and feedback physical properties and the manipulated features are used for training the proposed neural network because the features contain rich information for classifying and predicting faults of the system of interest. Second, VAE transforms high-dimensional input features to a low-dimensional feature space. This nonlinear space transformation reduces the complexity of the classification securing high accuracy and robustness of fault classification in the MMH. Third, the acquired MMH through VAE with Bayesian optimization statistically allocates two extremes of major (normal) and minor (faulty) clusters at origin and unity at the feature space, indicating that sensitivity of fault prediction is maximized. The method would be highly effective in that the model only focuses on separating major and minor clusters deciding each health condition but ignores minor differences within the clusters which confuse users. The effect of the method is demonstrated with field measurements of an elevator door stroke dataset comprising normal, degradation, and faulty states in open and close strokes. The systematic analysis shows that these characteristics contribute to improve accuracy and robustness for fault classification. Specifically, knowledge-based feature manipulation improves the accuracy, and VAE enhances sensitivity on separating each cluster and locational constancy. Moreover, the MMH is effective to predict potential fault without any label for a highly imbalanced dataset. The proposed method provides remaining useful lifetime (RUL) using distances from normal and faulty clusters at the MMH, which enables to quantitatively provide RUL of the system without any definition of RUL. Considering that many systems deployed on fields lack information for fault life or residual useful life, the proposed method would be practical and effective for real world applications.
Grey-box Approach for the Prognostic and Health Management of Lithium-Ion Batteries
Authors: Cancelliere Francesco , Girard Sylvain , Bourinet Jean-Marc , Broggi Matteo
Published: November 2023

The Lithium-Ion Batteries (LIB) industry is rapidly growing and is expected to continue expanding exponentially in the next decade. LIBs are already widely used in everyday life, and their demand is expected to increase further, particularly in the automotive sector. The European Union has introduced a new law to ban Internal Combustion Engines from 2035, pushing for the adoption of electric vehicles and increasing the need for more efficient and reliable energy storage solutions such as LIBs. As a result, the establishment of Gigafactories in Europe and the United States is accelerating to meet the growing demand and partially reduce dependencies on China, which is currently the main producer of LIBs.

To fully realize the potential of LIBs and ensure their safe and sustainable use, it is crucial to optimize their useful life and develop reliable and robust methodologies for estimating their state of health and predicting their remaining useful life. This requires a comprehensive understanding of LIB behavior and the development of effective prognostic and health management approaches that can accurately predict battery degradation, plan for maintenance and replacements, and improve battery performance and lifespan.

This work, funded by the GREYDIENT project, a European consortium aiming to advance the state of the art in the grey-box approach, combines physical modeling (white box) and machine learning (black box) techniques to demonstrate the grey-box effectiveness in the Prognostic and Health Management. The grey-box approach here proposed consist in a combination of a physical battery model whose degradation parameters are estimated online at every cycle by a Multi-Layer Perceptron Particle Filter (MLP-PF).

An electrochemical degradation model of a Lithium-Ion battery cell has been derived by use of Modelica. The model simulates the output voltage of the cell, while the degradation over time is simulate through the variation of 3 parameters: qMax (maximum number of Lithium-Ions available), R0 (Internal Resistance) and D (Diffusion Coefficient). To validate the model we resorted to the well-known NASA Battery Dataset, which has also been used to infer the optimal values of the three hidden degradation parameters at every cycle, to obtain their Run-to-Failure history. Then, the physical model is combined the MLP-PF: a MLPArtificial Neural Network is firstly trained on the Run-to-Failure degradation processes of the model parameters, allowing the propagation of the parameters in the future and the corresponding estimation of the battery Remaining Use ful Life (RUL). The MLP is then updated online by a Particle Filter every time a new measurement is available from the Battery Management System (BMS), providing flexibility to this method, needed for the electrochemical nature of the batteries, and allowing the propagation of uncertainties.
Battery State-of-Health Aware Path Planning for a Mars Rover
Authors: Salinas-Camus Mariana , Kulkarni Chetan , Orchard Marcos
Published: November 2023

A rover mission consists of visiting waypoints to gather scientific samples based on set requirements. However, rovers face operational uncertainties during the mission, affecting the performance of its electrical and mechanical components and overall mission success. Hence, it is critical to have a decision-making framework that is aware of the health state of the components when planning the path of the vehicle. In particular, battery degradation, and consequently the battery State of Health (SOH), can affect the optimality of decisions made by the autonomous system in the long term. This paper presents a decision-making system that incorporates information on the energy drawn from the battery (based on the velocity of the vehicle), terrain conditions, and model-based prognostic modules to assess impact on the battery state of charge (SoC). The decision-making system was formulated as a Markov Decision Process (MDP) to reach the goal destination by sending commands in a determined amount of time, while maintaining the battery SoC within the policy stated. The MDP problem was programmed using the open-source framework POMDPs.jl, which has a variety of online and offline solvers. To solve the MDP problem online, we used Monte Carlo Tree Search (MCTS). Results from simulations demonstrate the effect that battery degradation and charging plans have on decision-making.
Signal pre-processing techniques for fault signature enhancement in a bearing health monitoring system used in the automotive industry
Authors: Jafarzadeh Ehsan , Rahimifard Sara , Sant Anna Paola , Cao Yu , Tenney Frances , Sadjadi Hossein
Published: November 2023

Traditional internal combustion engine vehicles have low transmission bearing failure rates in their lifespans. However, the prolonged lifespan of electric and autonomous vehicles can surpass the reliable life of bearing designs, which poses a risk of bearing failure and loss of propulsion. Compared to replacing bearings on a fixed schedule to ensure reliability, a bearing health monitoring system is a more cost-effective solution. Despite extensive research on bearing condition monitoring, implementing well-known methods such as vibration spectrum analysis in vehicles can be challenging due to vibrations from vehicle components and the road. This paper explores and compares the effect of various pre-processing techniques on the spectrum of a faulty bearing with various fault levels. To achieve this objective, faults with the width size of 0.1 mm (mild), 0.5 mm (moderate) and 2 mm (severe) were injected into the inner race of a ball bearing. A bench setup was then used to capture the vibrations of multiple vehicle components including the faulty ball bearing under various speed/ load conditions. Phase domain transform, envelope and Fourier transform were used as the core signal processing steps, and advanced signal processing methods for removing discrete frequencies from other components and enhancing the fault signature were explored. 4 health indicators were then developed from the vibration spectrum of the vibration signals and calculated for the captured data. Next, for each fault level, the area under Receiver operating characteristic (ROC) curve was calculated and used as a metric to compare the performance of our health monitoring system for classification of faulty and healthy bearings. For our best health indicator, the results show that applying minimum entropy deconvolution, and spectral kurtosis-based band pass filtering increases the ROC area from 0.40, 0.99, 1.0 to 0.86, 1.0 and 1.0 for the mild, moderate, and severe inner race faults, respectively. This implies that although applying only phase domain transform, envelope and Fourier transform might be enough for moderate and severe faults, advanced signal processing is needed to enhance the fault signature for early detection of mild faults.
Deep Regression Network with Prediction Confidence in Time Series Application for Asset Health Estimation
Authors: Huang Hao , Subramanian Arun , Saxena Abhinav , Virani Nurali , Iyer Naresh
Published: November 2023

Many works have been focused in developing detection, monitoring and prediction routines for asset health estimation system. Classic machine learning based models benefit from quality of physics-informed features available from domain knowledge. This, however, can be labor intensive and is limited by quality of features developed through available knowledge. Deep learning based approach, if successful, can alleviate this laborious step. On the other hand, users often need to decide whether or not to trust an algorithmic prediction while the true error in the prediction is unknown. In this work, we propose a deep learning based regression network that output both prediction value and confidence score for asset health estimation in short intermittent transients time series application. In the experimental study, we show that our model has low prediction error given short intermittent transients multivariate time series as input. Furthermore, our model also provides a confidence score for each prediction that is highly negatively correlated with true prediction error. Experiments show that by setting an acceptance threshold on confidence score, our model can reach an averaged improvement of 20% on the prediction quality with 90% coverage.
Operational Wheel Flat Detector in Railway Vehicles
Authors: Erdozain Ibon , Blanco Blas , Baeza Luis , Alonso Asier
Published: November 2023

Maintenance of railway systems is shifting from being based on scheduled interventions to a continuous regime based on the actual status of assets. This change is supported mainly on three pillars: the development of new sensors and signal processing techniques, the capability to store and analyze all the information gathered by this huge amount of new sensors, and the capability of modifying dynamically the maintenance plans. This paper presents a new wayside system for detecting flats whose development has been based on combining physical models with Machine Learning Techniques. Physical models are used to understand the phenomena, define the key indicators to characterize the phenomena and generate synthetic data to train Machine Learning algorithms. Subsequently, regression models are generated to relate the key parameters with the flat severity. The last part of the paper is focused on validating the proposed methodology in a real environment.
Context-aware machine learning for estimating the remaining useful life of bearings under varying speed operating conditions
Authors: Hosseinli Seyed Ali , Ooijevaar Ted , Gryllias Konstantinos
Published: November 2023

Remaining useful life estimation is a crucial and complicated task in predictive maintenance in order to reduce downtime and avoid catastrophic breakdowns in industrial plants. Thanks to the recent advances in our machine learning era, deep learning models can effectively deal with modeling complex phenomena such as the bearing degradation process, specifically under varying operating conditions. However, obtaining large labeled datasets for training the data-dependent deep learning models is challenging and expensive. To overcome this limitation, a phenomenological model has been used in this study as an effective approach to creating synthetic run-to-failure datasets under varying operating conditions. The suggested methodology is able to adjust synthetic run-to-failure datasets to the different periodic speed profiles, including the speed ranges that pass the resonance frequency of the structure. A Context-aware Domain Adversarial Neural Network is proposed to remove the domain shift between the simulated signals and the real ones as well as enable the deep learning model to understand the varying speed operating conditions and the sequential order of the measurements. The simulated signals are used as the source domain and a limited number of the real signals are used as the unlabeled samples for the domain adaptation task. Context awareness is introduced to the network by integrating contextual information into the architecture of the Domain Adversarial Neural Network, leading to an improvement in the model performance and its generalization ability. A dataset captured in a bearing test rig is adopted to verify the proposed method. Results show that context awareness can result in better performance and also more robust predictions against major speed changes in varying speed scenarios compared to the non-context-aware models.
Diagnostic Signal Method for Fault Identification of Electro-Hydraulic Servo Actuators
Authors: Liu Zihan , Kambali Prashant , Nataraj Chandrashekhar
Published: November 2023

In this paper, we develop a fault identification approach for electro-hydraulic servo actuators based on injecting a pre-defined diagnostic signal into the system and then extracting fault-related features from the phase space topology. Next, we build regression models using an artificial neural network, which maps the feature space to fault space to identify the faults represented by the system’s parameters. The performance of the proposed fault identification approach is evaluated when the degradation of permanent armature occurs. The effect of parametric faults on the dynamics is studied and discussed. The different excitation of the system is considered, and the robustness of the proposed method under the condition of noise is also explored. The obtained results indicate the effectiveness of injected diagnostic signals in enriching the dynamics of the system and increasing the quality of extracted features and the accuracy of trained artificial neural networks.
Interpolate and Extrapolate Machine Learning Models using An Unsupervised Method
Authors: Liu Peng
Published: November 2023

The 2023 PHM North America Data Challenge is intriguing because it requires one to predict outcomes and use data patterns that training models do not see. Modern machine learning models based on gradient boosting and neural networks are not designed to address such issues in usually circumstances. Our final approach to address the challenge consists of five steps. In our approach, we use an unsupervised method besides machine learning models to address the challenge.
Gearbox Degradation Prediction through Deep CNN and Bayesian Optimization
Authors: Shen Kai
Published: November 2023

The original dataset, recorded at a high sampling rate of 20,480 Hz, presents a considerable volume of data. To facilitate efficient processing and analysis, we implement a data reduction strategy, which involves downsampling the signal to a more manageable frequency of 2,048 Hz.
Implementasi Pola Asuh Demokratis dalam Pembentukan Karakter Kejujuran Anak Usia Dini di Desa Sikapas Mandailing Natal
Authors: Nasution Asrija Murni , P Fuji Rahmadi
Published: November 2023

Parental care is the main pillar in forming the character of honesty in young children. Democratic parenting is considered as parenting that is relevant and appropriate to be applied to young children who have changes in attitudes and daily activities. Suhuas Mandailing Natal Village is a village that is rich in culture and ethnicity. The culture that is owned will have an impact on the care provided by parents. The aim of this research is to determine the implementation of democratic parenting in forming the honest character of early childhood. The method used in this research is qualitative with data collection techniques using participant observation and in-depth interviews. All existing data is analyzed using the stages of data condensation, data display and verification. The findings in this research are that the democratic parenting pattern that is implemented for children is providing close attention and warmth to children, discussing every activity and rule that is applied to children consistently, providing a good example by getting used to saying and behaving well. Parents who implement democratic parenting will find it easier to instill the character value of honesty in their children. The formation of the character of honesty must start from the parents, children will observe and imitate the honest activities carried out by their parents throughout their lives.
Pengaruh Pembelajaran Kontekstual terhadap Hasil Belajar dalam Pembelajaran Pendidikan Pancasila Kelas IV SDN 06 Pontianak Utara
Authors: Khairunnisa Khairunnisa , Salimi Asmayani , Ghasya Dyoty Auliya Vilda
Published: November 2023

This study aims to describe the Effect of Contextual Learning on Learning Outcomes in Pancasila Education Learning Class IV SDN 06 North Pontianak. The research method used is an experimental method with a quasi-experimental design and nonequivalent control group research plan. A sample of 47 students used a purposive sampling technique. In collecting research data using measurement techniques and data collection tools in research is a written test. The results of the study can be concluded that: The learning outcomes of the control class and the experimental class in learning Pancasila education with the calculation of data analysis in the experimental class with an average pre-test score of 43.77 and a post-test average score of 77. In the control class the score average student learning outcomes pre-test 51.9 and post-test 56.8. There are differences in learning outcomes in the experimental class and control class by testing the normality known pre-test and post-test data Xcount ≤ Xtable = 7.815, then the data is normally distributed. Apart from that, the researchers also carried out a homogeneity of variance test, from the results obtained Fcount ≤ Ftable = 2.024. There is an effect of contextual learning on the learning outcomes of class IV Pancasila education is the polled variance formula, namely t-test (Polled Variance) at level = 5% and (dk =〖n〗_(1+) n_2-2= 45) obtained t_(count > ) t_table or 8.5 > 2.0. Then the alternative hypothesis (Ha) is accepted and the null hypothesis (Ho) is rejected. This means that there is an influence of contextual learning on the learning outcomes of Pancasila education. Post test data calculated using the effect size formula was obtained at 1.17 with high criteria. This proves that the application of contextual learning has a high influence on the learning outcomes of Pancasila class IV SDN 06 Pontianak Utara.
Pengembangan Komik Digital pada Pembelajaran IPAS Kelas IV Sekolah Dasar Negeri 35 Pontianak Selatan
Authors: Yurti Yurti , Kresnadi Hery , Salimi Asmayani
Published: November 2023

This study aims to develop digital comics for science lessons in grade IV Elementary Schools that are suitable for use to assist the learning process in the independent curriculum. This research is a development research adapted from the Borg & Gall research model which includes potential and problem steps, data collection, product design, product validation, design revision, product testing and product revision. Quantitative data in this study were obtained from the validation of media and material experts, student responses and teacher responses, while qualitative data from this study were obtained from suggestions and comments from media experts, material experts, students and teachers. Research instruments in the form of interview guidelines and questionnaires. The data analysis technique used in this study is the feasibility analysis of digital comics from the media and material aspects, as well as the responses from students and teachers. The results of the study show that the feasibility of digital comic media shows an average value of 4.95 with the criteria of "Very Eligible" and the eligibility of digital comic material shows a percentage of 4.26 with the criteria of "Very Feasible". Then the students' responses to digital comics on a small scale get an average score of 4.75 while the large-scale average score gets an average score of 4.82 with the criteria of "Very Good" and the teacher's response to digital comics gets an average score -an average of 5 with the criteria of "Very Good".
Pemanfaatan Media Manipulatif dalam Pembelajaran Matematika untuk Meningkatkan Motivasi dan Hasil Belajar Siswa Kelas VI
Authors: Rahmat Rahmat , Asrori M. , Hairida Hairida
Published: November 2023

This study is a classroom action research that looks at whether manipulating media can improve motivation and learning results. Its goal is to describe how manipulative media are used in math learning. using descriptive methods carried out in four stages with direct observation techniques, questionnaire questionnaires and measurements using observation sheets, questionnaire sheets, and written tests in the form of fill-in-the-blank questions. Based on the analysis of the teacher's ability to design manipulative media, an average cycle of 1 meeting 1=3.33, meeting 2=3.44, cycle 2 meeting 1=3.67, meeting 2=3.89. The power of teachers to help students learn came from average cycle 1 meeting 1 = 3.30, meeting 2 = 3.48, cycle 2 meeting 1 = 3.65, meeting 2 = 3.87. Learning motivation was obtained on average pre-cycle = 71.15 / 56.92%, after cycle 1 = 85.12 / 68.10%, after cycle 2 = 101.94 / 81.60%.  Learning outcomes were obtained on average cycle 1 meeting 1=71.52, meeting 2=78.64, cycle 2 meeting 1=85.00, meeting 2=91.52. Based on these facts, we can say that manipulative media can make students more interested in learning and help them learn more.
Sistem Zonasi dan Implikasinya terhadap Sustainibilitas Mutu Pendidikan di SMAN 1 Narmada
Authors: Kutbi M. Amin
Published: November 2023

The New Student Admission System (PPDB) is one of the efforts to provide quality education with the goals of equalizing the quality of education and involving the community in the process. The limited school capacity has become a concern as centralized school selection has led to some schools having a shortage of students. The zoning system has been adopted as a solution to address this issue, where student selection is based on proximity to the school rather than academic achievement. This research focuses on the implementation of the zoning system at SMA Negeri 1 Narmada and its implications for education quality. A qualitative approach was employed, using interviews, observations, and documentation as data collection techniques. The data were analyzed using an interactive model consisting of data reduction, data display, and verification, with increased attentiveness and triangulation to ensure data validity. The findings indicate that the zoning system has been in place at SMA Negeri 1 Narmada since its implementation. This system has had a positive impact on education quality by diversifying the accepted students. The implications are evident in both academic and non-academic aspects, as students have excelled academically and in various competitions. The school's head adopted several strategies to maintain education quality, including setting school objectives, conducting supervision and evaluation of teaching, coordinating the curriculum, and monitoring student progress. With the implementation of the zoning system, SMA Negeri 1 Narmada has successfully achieved equalization of education quality and increased student participation in various learning aspects, thus strengthening the efforts to create a sustainable and high-quality education.
Managing Fault Lines in Nigeria’s Protracted Conflicts: The Inevitability of Multi-Track Diplomacy in the Jos Crises
Authors: ANIMASAWUN Gbemisola
Published: November 2023

The protracted crisis in Plateau State keeps worsening in terms of casualties and tenor. This is despite the continued intervention of the Nigerian State through measures such as military deployment and constitution of commissions of inquiry; which constitute Track-One approaches. Although, not without a history, recent manifestations of the conflict since 1999 when the fourth-republic commenced have been characterised by the use of more lethal weapons, poisoning of wells in the rural areas, mob attacks, reprisal attacks in and around Jos, bombings of religious gatherings and centres, house to house attacks,. ambush laying for vehicles during which commuters are ordered down for identification as indigenes and settlers before getting mauled; demarcation of areas along ethno-religious lines; all of these point to erupting contours of fault lines while portending a rehash of the genocide in Rwanda in 1994. These happenings indicate a worsening of the conflict which calls to question the efficacy of the approaches so far adopted by both the federal and state governments in effectively managing the crisis thereby necessitating an urgent change in approaches. In particular, the continued presence of the military seems not to be yielding the desired effects. Sequel to this, this paper proposes the combination of Tracks 1 (state) and Track 2 (NGOs and Professionals) of the Multi-Track-Diplomacy concept as a step forward. Based on secondary data, this article envisages that the provision of militaristic and nonmilitaristic infrastructure for peace by a combination of Track 1 and Track 2 in the conflict-ridden has potentials for sustainable peace and security
Observed Automobile Drivers’ Mobile Phone Use Rates in Ibadan Metropolis, Nigeria
Authors: Ipingbemi Olusiyi , Oyemami Olumami
Published: November 2023

The use of mobile phone while driving is a growing problem in both developed and developing countries. This problem was investigated among automobile drivers through fixed location observational survey in three residential densities in Ibadan Metropolis. The survey was undertaken for seven days between 7.00am and 7.00pm everyday. Both descriptive and inferential statistics were used for data analysis. The average phone use rates In low, medium and high. densities were 4.3%, 4.2% and 4.2% respectively. Daily pattern showed two peak periods coinciding with the conventional traffic volume peaks in all the zones. Also, drivers were more likely to use mobile phones 2 times during weekdays compared to weekends. Males were five times more likely to use cell phone than females. One-way ANOVA showed significant difference (p> 0.05) in the use of mobile phones among automobile drivers across the week. The paper advocates increased enlightenment on the dangers of phone use behind the wheels, improved surveillance, proper enforcement of existing legislation banning phone use while driving as well as tougher penalties..
Comparison of Perception of HIVIAIDS Risk and Sexual Risk Behaviours Among Youths with and without Disabilities in Oyo State, Nigeria
Authors: Umoren Anietie MI , Adejumo Adebayo A.
Published: November 2023

The study investigated the perception of HIV/AIDS risk and sexual risk behaviours among youths with disabilities (YWD) in comparison with youths without disabilities (comparison group). The study adopted a cross-sectional survey with 362 participants comprising 181 YWD with visual impaired 29(16%), physically challenged 40 (22.1%) and hearing impaired 112 (61.9%) and comparison group (N = 181). A 19-item structured questionnaire was used for data collection. The instrument was revalidated and found to be highly reliable and valid for the study. Kruskal-Wallis test for differences was used to determine the differences in perception of HIVIAIDS risk and sexual risk behaviours among the two groups as well as t-test. The results showed that there was a significant difference in perception of HIV/AIDS risk between YWD and the comparison group [X2 = (1) = 27.79, p < 0.01)] as well as a significant difference in sexual risk behaviours among the two groups [X2 = (1) = 23.117, p < 0.01)).. The t-test also revealed a significant difference between the groups on sexual risk behaviours [t(360) = 4.926, P < 0.01)]and HIV/AIDS risk [t(360) = 5.301, P < 0.01)). It was further reported that YWD recorded higher sexual risk behaviour (x = 9.35, SD = 4.137, n = 181) than the comparison group t= 7.48, SD = 3.00S, n =181). This trend was also reported on HIV/AIDS risk, with YWD recording higher (x= 14.56, SD =6.537, n = 181) than the comparison group t= 11.23, SD = 5.385, n = 181). The findings of the paper were duly discussed with far reaching recommendations for policy making. The study offers a new understanding of the perception of the HIV/AIDS risk and sexual risk behaviour in this group of youth population as well as provide relevant stakeholders with new vista in handling HIV/AIDS issues and sexuality of the disabled
Investigação de HTLV e fatores de risco para infecção das mulheres que realizam pré-natal de baixo risco em uma unidade de saúde na Amazônia Ocidental Brasileira
Authors: Catunda Maria Eugênia Seffair Lins de Albuquerque , Alecrim Maria das Graças Costa , Tavares Igor Castro
Published: November 2023

O HTLV-I é associado ao desenvolvimento de diversas doenças graves, entre elas a leucemia/linfoma de células T do adulto e a paraparesia espástica tropical/mielopatia associada ao HTLV-1, bem como inúmeras doenças correlacionadas à infecção. Objetivo: Verificar a ocorrência de casos de HTLV 1,2 em mulheres que realizam Pré-Natal de baixo risco e possíveis fatores de risco para infecção. Métodos: Foi realizado um estudo de prevalência, que buscou investigar a ocorrência do HTLV 1/2 em pacientes que realizaram Pré-Natal na Unidade Básica de Saúde UBS Alfredo Campos. Resultados: De um total de 382 amostras submetidas ao ELISA e ao rt-PCR, nenhuma das amostras positivaram. Das 382 pacientes entrevistas, 35/382(9,2%) possuem a idade média de 35 anos; 280/382(73,3%) são casadas, 96/382(25,1%) são solteiras e 6/382(1,6%) são viúvas; 164/382(42,1%) são donas de casa; 183/382(48%) são evangélicas; 276/3(72,2%) não concluíram o ensino médio; 325/382(85%) são procedentes de Manaus. Conclusão: este estudo sugere que ações de educação em saúde sejam intensificadas nesta população e a realização de mais estudos com a possibilidade de outros métodos diagnósticos que possam apresentar uma maior sensibilidade para detecção do HTLV.
La cultura escolar: Resultado de tensiones discursivas
Authors: Campo Figueroa Elvis Emir
Published: November 2023

Las instituciones educativas constituyen un espacio de interacción de fuerzas entre actores, agencias y campos de producción y reproducción discursiva, en los que se visibilizan ejercicios de poder y control en la transmisión de la cultura escolar.

A nivel macro, se posicionan prácticas discursivas como la del Estado expresado en el marco legal y autoridades que normativizan y supervisan las acciones educativas, la de los gremios de docentes cuya posición censura las decisiones gubernamentales, Y la de organizaciones internacionales promotoras de reformas educativas; además de ellos, los discursos de orden subjetivo que proviene de los docentes, estudiantes y familias. Por esta razón, la comprensión de las instituciones educativas a partir del entramado comunicativo y las relaciones sociolingüísticas expresadas en códigos y pedagogías que configuran la transmisión de la cultura escolar y develan ejercicios de clasificación y enmarcamiento, aceptación y resistencia, como resultado de prácticas discursivas en todos los niveles, mediante un proceso reflexivo de indagación y exploración de significados y dispositivos inmersos en la cultura escolar, a partir de la estructuración del discurso pedagógico postulado por Basil Bernstein.
Preparation and characterization of new Mixed ligand complexes For some transition metal ions (bivalent) with Schiff- Mannich and Schiff base ligands
Authors: Safaa Mohammed Jawad Radhi  , Ibtihal Kadhim Kareem  , Nadia Sadiq Majeed
Published: November 2023

In this research, new mixed ligand complexes were prepared for complexes of some transitional element ions from the first transition series, which are: cobalt (II), nickel (II), and copper (II). The research included two paths:

First: The first path included the preparation of three polycyclic ligands derived from Isatin (L1, L2, and L3), all of these ligands were identified by measuring the melting point and infrared and ultraviolet-visible spectroscopy.

Second: The second path included the preparation of Mixed ligand complexes (L1and L2) with cobalt (II), nickel (II), and copper (II) ions. And Mixed ligand complexes (L1and L3) with ions of cobalt (II) and nickel (II). All the complexes of the new Mixed ligand were identified by the available analytical and spectroscopic methods. Based on the analytical data, the metal to ligands ratio was (1:1:1) and all complexes were characterized by various analytical techniques including (FT-IR and UV-Vis spectroscopy), CHN elemental analysis and determination using flame atomic absorption spectroscopy The percent magnetic susceptibility and molar conductivity of metal ions in the prepared complexes and these metal complexes dissolved in DMSO at a laboratory temperature of 1 × 10-3 M were also studied. by means of infrared (IR) spectra, and when compared to the spectrum of the free ligands, it was observed that some bands were displaced and others disappeared, or a change in shape and intensity occurred, which indicates a coordination occur between the metal ions and the prepared ligands. As well as the ultraviolet-visible spectrum. And detecting the presence of chloride ion inside or outside the coordination sphere. Depending on these obtained results, we were able to conclude that ligands of L1 and L2 behaves like a bi-chelate ligands, which led to the formation of mixed ligand complexes (L1, L2) with the proposed geometry of the proposed hexahedral symmetry in the presence of two chloride ions inside the coordination sphere. . Whereas, the L3 ligand behaved like a tetragonal ligand, which led to the formation of mixed ligand complexes (L2, L3) with the proposed geometry of the proposed hexahedral symmetry
The utilization of mechanical agitation of irrigation solution in endodontic treatment: case series
Authors: Taptun Yu. A. , Makeeva M. K. , Sharganova V. D. , Davreshyan G. K. , Gevorkyan A. A. , Zhukov A. I. , Gasbanov M. A. , Babina K. S. , Gimish I. V.
Published: November 2023

Aim. To evaluate the advantages of working with the Endoactivator device on the example of a series of clinical cases concerning the treatment of chronic apical periodontitis. Materials and methods. The series of clinical cases included five patients (two men and three women) who were treated for chronic apical periodontitis (diagnosis according to ICD-10 K04.5). The patients underwent endodontic treatment in two visits, namely, mechanical treatment with rotating nickel-titanium instruments, drug treatment using an Endoactivator device for sound activation of irrigation solutions and the introduction of calcium hydroxide between visits. Postoperative sensitivity was assessed according to the criteria: absent, low, medium and high. The patients informed the research doctors via messengers about the intensity of postoperative soreness. Results. Next results of postoperative sensitivity have been revealed: none of the patients noted high postoperative soreness, average soreness was noted by one patient, low soreness was noted by two patients and absence of soreness was noted by two patients. Conclusions: on the example of this series of clinical cases, convenient manipulation characteristics of the EndoActivator device were revealed. There were no cases of high postoperative sensitivity after operation of these devices in the presented series of cases. In all clinical cases, radiological methods confirm the positive dynamics of healing of periapical foci.