bluuebunny/crossref_metadata_2025 huggingface dataset:
The Relationship Between Key Air Pollutants and Meteorological Parameters in Bolu Province Between 2020-2023
Authors: KARATAŞ Sıla
Published: July 2024

Atmosferde bulunan farklı kirleticilerin (zehirli gazlar, partikül madde, kimyasallar, biyolojik ajanlar vb.) hava kalitesi üzerinde zararlı etkiye sahip olmasına hava kirliliği denir. Bu kirleticiler genellikle enerji üretimi, otomobil
emisyonları, endüstriyel işlemler, tarımda kullanılan kimyasallar ve diğer insan çabalarının bir sonucu olarak üretilmektedir. Çevresel bozulma, sağlık sorunları ve iklim değişikliğinin tümü hava kirliliğinden kaynaklanabilir.
Bolu şehrinin hava ortamını 2020'den 2023'e kadar inceleyen kapsamlı bir çalışma projesinin sonuçlarını sunmaktadır. Azot dioksit (NO2), karbon monoksit (CO), kükürt dioksit (SO2), partiküller gibi temel kirleticilerin kapsamlı
bir analizi madde (PM2.5, PM10) ve partikül madde araştırmanın bir parçasıdır. Çalışma, gözlemlenen kirletici maddeleri tanımlayan mevsimsel ve günlük döngüleri araştıran karmaşık bir yaklaşım benimsiyor. Bu, yerel hava kalitesinin
dinamikleri üzerindeki olası etkilerinin ayrıntılı bir değerlendirmesine olanak tanır. Toplanan veriler, Bolu bölgesindeki belirli hava kalitesi önlemlerini kontrol eden zaman dinamiklerinin kritik bir şekilde anlaşılmasını sağlar.
Ayrıca kirletici konsantrasyonları ile iklim parametreleri arasındaki ilişkilerin eleştirel bir şekilde incelenmesi, hava kalitesi dinamiklerini etkileyen ana faktörleri açıklığa kavuşturur. Elde edilen sonuçlar, bölgedeki mevcut
hava kalitesi koşullarını iyileştirmeye yönelik uygun çözümleri belirlemek için gerekli yararlı bilgileri sağlar.
Temporal analysis of PM10 concentration with atmospheric boundary layer height variation in Ankara
Authors: TEMİZ Caner
Published: July 2024

This study investigated the relationship between the height of the atmospheric boundary layer (ABL) and variation in PM10 concentrations in Ankara during the course of 2023. By analyzing data from a nearby meteorological station and
an air quality measurement station it was found that the average PM10 level for the year was 51.5 µg/m³. The highest monthly average was reported in January at 90.99 µg/m³ while the lowest was recorded in April at 24.42 µg/m³.PM10
data varied according to the month. The ABL height changed dramatically with the season reaching heights of over 1000 m in summer and as low as 100 m in winter. Lower ABL heights and higher heating activities correlated with higher
PM10 levels. Higher PM10 concentrations have also been associated with winds from the east and southwest and a strong correlation was observed between the variation in PM10 air pollution levels and the use of fossil fuels for heating
throughout the winter. These results stress the impact of seasonal temperature variations on PM10 levels and ABL height indicating the need for focused approaches to enhance air quality particularly during winter.
Assessment of PM10, PM2.5, SO2, NO2, NO2, NOX, NO and O3 Pollutant Concentrations in Adana Çatalan Region for 2020-2023
Authors: Dürmen Nergiz
Published: July 2024

Bu çalışma, Adana Çatalan bölgesindeki hava kirliliği seviyelerini 2020-2023 yılları arasında analiz ederek, hava kirleticilerinin (PM10, PM2.5, SO2, NO2, NOx, NO ve O3) zaman içindeki değişimlerini ve bunların potansiyel sağlık etkilerini
incelemiştir.Sonuçlar, kirleticilerin gün içindeki ve mevsimsel değişimlerini göstermiştir. Ozon (O3) seviyelerinin öğleden sonra zirve yaptığı, PM10 ve PM2.5 seviyelerinin ise mevsimsel olarak değiştiği görülmüştür. NOx ve NO2
seviyeleri özellikle 2021 yılında artış göstermiştir.Genel olarak, hava kalitesi WHO standartlarına uygun olsa da, bazı dönemlerde kirletici seviyelerindeki artışlar potansiyel sağlık riskleri oluşturmuştur. Bu bulgular, hava kalitesini
iyileştirmek için endüstriyel faaliyetlerin ve trafik yoğunluğunun kontrol altına alınması gibi stratejilerin önemini vurgulamaktadır. Bu tür analizler, bölgedeki hava kalitesinin iyileştirilmesine yönelik politikaların geliştirilmesine
katkıda bulunmaktadır.
Computer-Controlled Automation of Coffee Bean Drying and Grinding System menggunakan Sensor Infra Red dan Sensor Fototransistor
Authors: Syahindra Wandi , Murlena Murlena
Published: July 2024

This study aims to design and implement an automation system for drying and grinding coffee beans using infrared sensors and phototransistors controlled by a computer. Traditional methods are often inefficient and have a high risk of contamination. The automation system, utilizing advanced sensor technology, is expected to improve the efficiency and cleanliness of the coffee bean processing. The research methodology involves designing a system consisting of key components such as infrared sensors to detect moisture, phototransistors to measure light intensity, and actuators driven by stepper motors and DC motors. The research results show that this system can reduce drying and grinding time, improve process accuracy, and decrease manual labor involvement. Simulations and system prototypes demonstrate that this automation system can be practically applied, enhancing the efficiency and cleanliness of the coffee bean processing. In conclusion, this automation system can reduce contamination risk, increase productivity, and lower operational costs in the coffee processing industry.
Project-Based Learning with Scratch to Improve Students’ Creative Thinking Ability: Systematic Literature Review
Authors: Winarko Gemintang Cinta
Published: July 2024

Creative thinking abilities are crucial for students, particularly within the realm of mathematics, to tackle real-world challenges effectively. Regrettably, many students encounter difficulties in nurturing their creative thinking abilities due to the inadequate teaching methods and educational resources employed by instructors. As a result, there is a pressing demand for inventive teaching approaches and materials, with project-based learning using Scratch emerging as one such innovative method to foster students' creative thinking proficiencies. This research, which encompassed a systematic review, concludes that the utilization of the Project-based Learning approach with Scratch as an educational tool can indeed enhance students' creative thinking abilities in the context of mathematics education. Furthermore, it recommends further development by harnessing applications like Scratch or other visual programming tools and exploring alternative research models for comparative analysis.
MENINGKATKAN KUALITAS KUNING TELUR ITIK PEKING DI KELOMPOK PETERNAK KARYA MANDIRI KECAMATAN LABUAPI LOMBOK BARAT
Authors: Indarsih Budi , Tamzil Mohammad Hasil , Haryani Ni Ketut Dewi , Jaya I Nyoman Sukartha , Asnawi Asnawi
Published: July 2024

Itik Peking merupakan salah satu itik tipe dwiguna yang saat ini oleh peternak itik di Lombok dipelihara sebagai itik petelur. Kuning telur merupakan salah satu indikator kualitas. Jagung kuning merupakan  bahan utama pakan itik untuk mensuplai xantofil untuk warna kuning telur, akan tetapi harganya mahal. Ganggang hijau merupakan alternative pewarna kuning telur alami yang mudah didapat tanpa membutuhkan biaya. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kemampuan dan ketrampilan peternak itik Peking untuk menghasilkan telur yang berkualitas. Kegiatan ini mendorong peternak mencari bahan pakan alternative itik Peking yang murah. Metode: Kegiatan ini dapat berlangsung atas kerjasama antara Kelompok Peternak Itik Karya Mandiri dengan Fakultas Peternakan Unram.  Rangkaian kegiatan dimulai dengan metode ceramah, diskusi dan demonstrasi. Materi meliputi:  kualitas telur dan metode meningkatkan kualitas telur serta manfaat menghasilkan produk yang berkualitas. Diskusi dan tanya jawab menunjukkan bahwa kegiatan ini membuka wawasan masyarakat dan mampu membangkitkan semangat usaha. Kegiatab meyakinkan peternak bahwa menuju ke kualitas telur yang lebih baik merupakan langkah yang harus dilakukan untuk mampu bersaing lebih luas. Ganggang hijau merupakan salah satu sumber xantofil alami untuk meningkatkan warna kuning telur. Produksi telur tidak mengalami penurunan dengan pemberian ganggang hijau. Pigmentasi warna kuning telur score 11-12 Roche yolk color fan dengan pakan 4% ganggang hijau. Score kuning telur karena pakan mengandung ganggang hijau ini lebih tinggi dibanding formula peternak tanpa hijauan. Kegiatan membuktikan bahwa kualitas telur dapat dicapai dengan bahan pakan alternative yang murah dan mengharapkan adanya bimbingan secara berkelanjutan.
VÍTIMAS DE QUEIMADURAS: A IMPORTÂNCIA DOS PRIMEIROS SOCORROS PARA UM ATENDIMENTO PRÉ HOSPITALAR EFETIVO
Authors: Santos Isabela Dheniffer , Lima Bruno Cassiano de
Published: July 2024

VÍTIMAS DE QUEIMADURAS: A IMPORT NCIA DOS PRIMEIROS SOCORROS PARA UM ATENDIMENTO PRÉ HOSPITALAR EFETIVO

INTRODUÇÃO: Os acidentes por queimaduras é uma importante temática para saúde pública brasilei
ESPORTE E LAZER NO SÉCULO XXI : Educação, Gestão e Políticas Públicas
Authors: Pereira Álex Sousa , Santos Diego Ramires Silva , Silva Alysson Dos Anjos
Published: July 2024

Neste livro, "Esporte e Lazer no Século XXI", a metáfora do rizoma revela uma trama interconectada, onde cada platô representa uma nova perspectiva sobre o ensino de esportes coletivos, a gestão esportiva, o lazer e as políticas públicas. Aqui, o conhecimento se desdobra como uma teia infinita, sem começo ou fim, cada ideia alimentando a próxima numa dança audaciosa e poética. Exploramos como a Educação Física pode transcender o tecnicismo, promovendo uma formação integral e crítica. Desafiamos as normas tradicionais, propondo abordagens inovadoras que integram a gestão eficaz e políticas inclusivas, refletindo sobre novos horizontes para o esporte e o lazer em nossa sociedade.
O PAPEL DA ENFERMAGEM NO CUIDADO À MULHER SUBMETIDA À PUNÇÃO ASPIRATIVA MAMÁRIA: UMA REVISÃO NARRATIVA
Authors: Batista Luciana Moreira , Lisboa Maria Júlia Sarmento , Ribeiro Helen Rosy Gomes , Santos Sandy Costa dos
Published: July 2024

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Exploring the dynamics of product quality and failures in export trade: A systematic literature review
Authors: Edim Eka James  , Altuğ Ocak  , Samuel Eventus Bernard
Published: July 2024

This study conducted a systematic literature review on product quality and failures in export trade, aiming to uncover causes, dimensions and practical steps for improvement. It examined 181 scholarly articles, employing in-depth content analysis and visual aids for clarity. The first finding of the study revealed that nine factors emerged as the major dimensions of goods quality in the export trade context, including: conformance, durability, reliability, features, aesthetics, usability, serviceability, environmental impact and innovation. The second finding revealed that thirteen factors emerged as the major dimensions of service quality in the export trade context, including: cultural sensitivity, service compliance, reliability, responsiveness, tangibility, competence, courtesy, credibility, transparency, security, consistent availability, service customization and service innovation. The third finding of the study revealed that twelve factors emerged as the key dimensions of goods failure in the export trade context, including: manufacturing defect, maintenance complexity, component failure, assembly failure, durability issues, performance flaw, user interface failure, inferior quality, packaging/design failure, product adaptation failure, logistics failure and technical incompatibility. Other findings were also made, and the study recommended that export companies should conduct thorough market research, prioritize cultural sensitivity, implement quality management systems, embrace manufacturing automation, and maintain strong supplier relationships to ensure consistent high-quality products and successful foreign market entry.
Impact of socio-demographic factors on knowledge of cervical cancer among women in rural Bangladesh: A cross-sectional study
Authors: Iffat Ara Begum  , Shihab-ul-Islam Rafi  , Zubaida Iftekhar  , Moshfequa Rahman Khan  , Sujit Kumar Banik  , Shamiul Bashir Plabon  , Ridwanul Islam  , Abu Ansar Md Rizwan
Published: July 2024

Introduction: Cervical cancer poses a significant public health challenge globally, particularly in low- and middle-income countries (LMICs) where it leads to substantial morbidity and mortality. In Bangladesh, cervical cancer is the second most common cancer among women, with socioeconomic factors, educational attainment, and access to healthcare being critical determinants of health outcomes. This study investigates the impact of socio-demographic factors on the knowledge of cervical cancer among women in rural Bangladesh. Method: An analytical cross-sectional study was conducted across four subdistricts: Bakergonj, Amtoli, Kumarkhali, and Jagannathpur. A sample size of 245 women aged 30 to 49 years was selected through systematic random sampling. Data were collected from November 2020 to February 2021 using structured questionnaires administered during face-to-face interviews. Knowledge was assessed based on responses to 15 questions about cervical cancer, with scores ranging from 0 to 15. Statistical analysis was performed to determine the associations between knowledge levels and socio-demographic variables. Results: The study revealed that only 17.14% of the respondents demonstrated good knowledge of cervical cancer, while 82.86% exhibited poor knowledge. Significant associations were found between knowledge levels and factors such as age, education, and household size. Notably, 15.38% of respondents aged 30-34 demonstrated good knowledge compared to only 12.82% of those aged 45-49 (P=0.022). Similarly, 100% of respondents with graduate or higher education had good knowledge (P=0.026). Smaller household sizes were also associated with better knowledge (P=0.047). Conclusion: The findings highlight substantial gaps in cervical cancer knowledge among rural women in Bangladesh, underscoring the need for targeted educational interventions. These interventions should focus on providing comprehensive information about HPV, cervical cancer, and screening methods, and addressing cultural stigmas and misconceptions.
Social cohesion and optimal development outcomes: A study through graph theory, Markov Chain and Artificial Intelligence
Authors: Sugata Sen  , Soumya Sengupta  , Santosh Nandi
Published: July 2024

Lack of cohesion among human beings is a major problem in modern India. This absence of cohesion appeared due to many historical, geographical and economic factors. It has ultimately culminated in differentiated development outcomes in India. This work wants to evaluate the effect of social cohesion on the development achievements. To that respect Graph theory, Markov chain analysis and Artificial Intelligence have been used. Here society has been conceived as a network of n agents. To initiate the Markov process the idea of Genetic Algorithm is used. On the other hand this work tries to measure the Cohesion Density Index for the concerned network and correlation with the time and apace complexity of that very network. This work actually compares the stationary states through Artificial Intelligence to find the most acceptable or optimum. It is concluded that the level of cohesion among different social groups can largely influence the expected outcome of any inclusionary development programme. This lack of cohesiveness within the Indian society due to some strong religio-philosophical reasons is one of the greatest challenges to India in achieving desired inclusive growth. In this paper it is shown that increasing the connectedness of the society can improve the efficiency of the development programs.
Antiretroviral adverse drug events reported among adult HIV patients in a Nigerian tertiary hospital: A retrospective study
Authors: Amaka Yves-Ann Ezeuko  , Sunday Odunke Nduka  , Martin Chukwunonso Nwofia  , Chioma Callista Ezeuko  , Obinna Ikechukwu Ekwunife
Published: July 2024

Background: The use of Highly Active Antiretroviral Therapy (HAART) has changed HIV/AIDS from a near-certainly fatal illness to one that can be managed chronically. A significant constraint of HAART is the high prevalence of adverse drug events (ADE) among HIV patients taking them. Objectives: The study determined the frequency and severity of reported antiretroviral adverse events among HIV-infected adults (≥16 years) at the Institute of Human Virology (IHV) Clinic of Nnamdi Azikiwe University Teaching Hospital Nnewi, Anambra State, Nigeria, within five years. Antiretroviral therapies implicated in the reported adverse drug events were also determined. Method: Information on reported ADEs was extracted from the NAFDAC Pharmacovigilance forms in the Pharmacovigilance section of the IHV Clinic Pharmacy. The severity of ADEs was classified using the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) index for categorizing errors. Results: A hundred and nineteen (119) patients reported 161 ADEs within the 5-year study period (2017-2021). Most ADE reports came from females (74.53%) and patients 36-55 years old. Dizziness (31.1%), Rashes (14.3%), and Fatigue (13.0%) were prominent among all the ADE reports documented. TDF/3TC/EFV (57.8%) and AZT/3TC/NVP (11.8 %) combinations were the frequently implicated antiretroviral regimen. All the ADEs reported were mild (Category ‘E’). ADE reports appreciated in the second year and progressively declined afterwards. Conclusion: There is a need to improve the system for antiretroviral ADE reporting through sensitization and developing a specific tool that enhances ADE reports from patients and healthcare providers.
Effects of climate change on the availability of non-timber forest products (NTFPs) in the Kavonge and Museve hilltop forests in Kenya
Authors: Vandi Alex Saffa  , Harun Mutuma Kiruki  , Festus Mbatha Mutiso
Published: July 2024

The study evaluated the effects of climate change on the availability of NTFPS in Kavonge and Museve hilltop forests in Kitui County, Kenya. The specific study objective was to assess local community perception on rainfall and temperature patterns on NTFPs availability. A sample size of 120 respondents were selected for the study using the Yamane formula. A purposive sampling method was used to select villages within 5 kilometer radius to both hilltop forests and a systematic transect line design of 1km by 1km was used to select households for data collections. Data were collected by employing structured questionnaires, key informant interviews and focus groups discussions. The data was analyzed using descriptive statistics (frequencies, percentages, bar charts), chi-square test and logistic regression. The result revealed that majority 83.0% of respondents strongly agreed that climatic conditions of the area has changed. The results submit that 96% of the respondents perceived an increase in temperature pattern during this recent period of 2018-2023 while, 100% perceived a decrease in rainfall pattern during this recent period of 2018-2023. The logistic regression model results revealed that, age, education, occupation and residency period significantly (p < 0.05) influenced community perception of climate change (rainfall and temperature) patterns on NTFPs availability in the study area. It is ascertained that the Kavonge and Museve forests edge communities still rely on the available NTFPs as a safety net when faced with unfavorable circumstances, such as crop failure due to climate change. However, it was reported that the available quantities of NTFP are declining due to climate change. I conclude that, available NTFPs will continue to decrease if stringent sustainable utilization and management measures are not implemented.
A review on applications and uses of Artificial Intelligence
Authors: Adithiyaa D  , C. Alamelu
Published: July 2024

Artificial intelligence (AI) is a field of computer science which aims to mimic cognitive knowledge of humans to machines. The growth of AI in the past decade is tremendous and soon in the future it will be widely used in many fields. This growth might involve replacing humans or helping humans to finish their work quicker. Even though the use of AI is beneficial in all fields, it also has lots of limitations associated with it when used in any field. The potential barriers which hinder the growth of AI include the development of suitable algorithms, data security and privacy issues. Hence, it is crucial to analyse the advantages and limitations before implementing AI in any field to determine the role of AI in that particular field. AI’s growth is most notable in the four fields namely medicine, banking, education and agriculture. This paper analyses the uses and the applications of AI along with the advantages, drawbacks and limitations of using AI in each field.
Driving sustainable success: Achieving emission reductions and operational excellence in ultra-deepwater drilling
Authors: Muhammad Ahsan  , Mike Wen Cao
Published: July 2024

In the context of advancing sustainability goals, an operator faced challenges in drilling an ultra- deepwater exploration well offshore Malaysia, prompting the need for a solution to mitigate risks while minimizing environmental impact. Through a comprehensive life cycle analysis, emissions were quantified, and an emission baseline was established, laying the groundwork for achieving sustainability key performance indicators (KPIs). Baker Hughes' recommendation of their DELTA TEQ™ low-impact drilling fluid system, coupled with the unique rheology modifier additives, not only addressed operational challenges but also facilitated a significant 21% reduction in emissions. This integrated solution underscores a proactive approach towards sustainability in the oil and gas sector, leveraging data-driven insights to drive environmentally conscious practices and achieve overarching sustainability objectives.
Integration of Artificial Intelligence in supply chain management: challenges and opportunities in Uganda
Authors: Natuhwera Pius  , Onyango Laban Oliver Owin
Published: July 2024

Integrating Artificial Intelligence (AI) in supply chain management (SCM) signifies a significant advancement with profound implications for modern businesses, including those in Uganda. This research paper critically examines the challenges and opportunities associated with this integration, using Uganda as a case study. A comprehensive analysis of existing literature and specific insights from the Ugandan context identifies critical challenges such as data integration, technology adoption, and organizational readiness within the country. Additionally, it explores AI's diverse opportunities in optimizing supply chain processes for Ugandan businesses, including demand forecasting, inventory management, and logistics optimization within Uganda's unique operational landscape. Furthermore, the paper discusses the potential impact of AI integration on various stakeholders within Uganda's supply chain ecosystem, including suppliers, manufacturers, distributors, and customers. By synthesizing insights from academic research and industry practices in Uganda, this paper provides valuable insights for Ugandan businesses aiming to leverage AI technologies in their SCM strategies. Ultimately, this research contributes to a deeper understanding of the complexities of integrating AI in SCM within the Ugandan context and offers recommendations for addressing challenges while maximizing the opportunities presented by this transformative technology.
Deep learning in high-frequency trading: Conceptual challenges and solutions for real-time fraud detection
Authors: Halima Oluwabunmi Bello  , Adebimpe Bolatito Ige  , Maxwell Nana Ameyaw
Published: July 2024

High-frequency trading (HFT) has transformed financial markets by enabling rapid execution of trades, exploiting market inefficiencies, and optimizing trading strategies. However, this speed and complexity also present significant challenges for real-time fraud detection. Deep learning, a subset of machine learning, offers promising solutions to these challenges through its ability to analyze large volumes of data and uncover intricate patterns. This review explores the conceptual challenges and solutions associated with deploying deep learning for fraud detection in HFT environments. One of the primary challenges in implementing deep learning for HFT fraud detection is the sheer volume and velocity of data. HFT systems generate vast amounts of transactional data in milliseconds, necessitating highly efficient and scalable deep learning models. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are particularly suited for this task due to their ability to process and analyze sequential data efficiently. However, these models require substantial computational resources and sophisticated infrastructure to operate in real time. Another significant challenge is the need for high accuracy and low latency in fraud detection. False positives can lead to unnecessary interventions, while false negatives can result in undetected fraudulent activities. Deep learning models must be fine-tuned to balance these risks, employing techniques such as hyperparameter optimization and ensemble learning to enhance their predictive capabilities. Additionally, integrating real-time anomaly detection methods can help identify suspicious activities promptly, reducing the window of opportunity for fraudsters. Data quality and integrity also pose substantial challenges. HFT environments are susceptible to noise and outliers, which can distort model predictions. Ensuring high-quality data through rigorous preprocessing and anomaly filtering is crucial for the accuracy of deep learning models. Techniques such as data augmentation and normalization can further improve model robustness. To address these challenges, a hybrid approach combining deep learning with traditional statistical methods and rule-based systems can be effective. This approach leverages the strengths of each method, providing a comprehensive fraud detection framework that is both accurate and responsive. Additionally, ongoing model retraining and adaptation to evolving fraud patterns are essential to maintain the effectiveness of the system. In conclusion, while deep learning presents significant opportunities for enhancing real-time fraud detection in high-frequency trading, it also requires addressing challenges related to data volume, computational demands, accuracy, and data quality. By employing a hybrid approach and continually refining models, financial institutions can effectively mitigate fraud risks and safeguard their trading operations.
Adaptive machine learning models: Concepts for real-time financial fraud prevention in dynamic environments
Authors: Halima Oluwabunmi Bello  , Adebimpe Bolatito Ige  , Maxwell Nana Ameyaw
Published: July 2024

Adaptive machine learning models are revolutionizing real-time financial fraud prevention in dynamic environments, offering unparalleled accuracy and responsiveness to evolving fraud patterns. Financial institutions face constant threats from increasingly sophisticated fraud schemes that adapt and change over time. Traditional static models often fall short in addressing these rapidly shifting threats, necessitating the adoption of adaptive machine learning techniques. Adaptive machine learning models are designed to evolve continuously by learning from new data and adjusting to emerging fraud patterns. These models employ advanced algorithms, such as reinforcement learning, online learning, and deep learning, to maintain their effectiveness in detecting and preventing fraud. Reinforcement learning algorithms optimize detection strategies by receiving feedback from their actions, continually improving their decision-making processes. Online learning algorithms update models incrementally as new transaction data becomes available, ensuring that the models remain current and responsive. One of the key strengths of adaptive machine learning models is their ability to process vast amounts of data in real time. By leveraging technologies such as neural networks and ensemble learning, these models can analyze complex datasets, identify subtle anomalies, and detect fraudulent activities with high precision. Real-time data processing capabilities enable immediate detection and response to suspicious transactions, significantly reducing the risk of financial losses. Adaptive models also incorporate anomaly detection techniques to identify deviations from normal transaction behavior. By constantly learning from the latest data, these models can recognize previously unseen fraud patterns, providing a robust defense against novel threats. Additionally, the integration of explainable AI (XAI) techniques ensures that the decision-making processes of these models are transparent and interpretable, fostering trust and compliance with regulatory requirements. Implementing adaptive machine learning models for real-time fraud prevention involves addressing challenges such as data quality, computational efficiency, and model interpretability. Financial institutions must ensure the availability of high-quality data and invest in robust computational infrastructure to support real-time processing. Furthermore, adopting explainable AI techniques enhances model transparency and regulatory compliance. In conclusion, adaptive machine learning models offer a dynamic and effective solution for real-time financial fraud prevention. By continuously learning and adapting to new data, these models provide a resilient defense against evolving fraud schemes, enhancing the security and integrity of financial transactions. This adaptive approach not only mitigates financial risks but also strengthens the overall trustworthiness of financial systems.
The study of an innovative Eéducationnel practice in Greek students: The flipped learning
Authors: Rethemiotaki Irene
Published: July 2024

The purpose of this paper is to compare the effectiveness of using flipped teaching against traditional teaching, with active learning techniques, in physics and mathematics courses. The study was conducted on 100 middle and high school students who were first subjected to traditional teaching (control group) and then subjected to flipped teaching (experimental group). To check the effectiveness of the two methods, the students were submitted to an assessment test in the lesson taught with the two methods. To test the existence of a statistically significant difference between the performance of the two groups, the independent sample t-test and ANOVA test were used for continuous variables. In addition, multiple logistic regression analysis with Odds Ratios was used to predict student achievement depending on the teaching method used. The results of the study showed that there is no statistically significant difference in the average performance of students with the two teaching methods.
Effect of saliva pH on Candida albicans activity in the oral cavity
Authors: Muhammad Rafi Nurfaiz Arifin  , Alfonsus Sindhu Saputra Djaja  , Indeswati Diyatri
Published: July 2024

Background: Low saliva pH is supposed to increase Candida sp activity because low saliva pH can cause immunocompromising. Objective: To determine the effect of saliva pH on the activity of Candida albicans. Methods: Secondary data from literature studies were analyzed descriptively by presenting the results of research on the effect of saliva pH on the activity of Candida albicans. Results: The results of the study reveal that decreasing salivary pH can increase the activity of Candida albicans in the oral cavity, which is characterized by the growth of hyphae and colonization of the microbiota itself as well as manifestations that can be seen clinically, such as oral candidiasis. Conclusion: Salivary pH levels can influence the activity of Candida albicans in the oral cavity.
Obstacles to vaccination coverage for children aged 12 to 59 months in the Mangobo health zone from 2016 to 2019 in Kisangani (DR Congo)
Authors: LISANGI TULI Lucien  , ALAIMA MANDA Jacques  , VIHAMBA KOMBI Guylaine
Published: July 2024

Introduction: Vaccination saves lives and is one of the greatest medical successes in the history of humanity. It saves around three million lives every year worldwide. Specifically, the study aims to determine the obstacles to immunization coverage of children aged 12 to 59 months in the Mangobo Health Zone and to identify the gaps between the administrative immunization coverage of the Health Zone and the coverage of household surveys. Methods: Using a retrospective descriptive approach based on documentary analysis and interviews, we selected a sample of 150 children aged 12 to 59 months living in the Mangobo Health Zone between 2016 and 2019. Results: Adverse events (45.3%) and vaccine stock-outs in the health areas (30.7%) were found to be the main obstacles to child immunization in the Mangobo Health Zone. The differences between administrative vaccination coverage and household survey vaccination coverage are very significant: for the VAA 64.07% and the VAR 62.07%. Conclusion: In order to optimize immunization coverage, it is essential to implement an effective policy for the management of health facilities by the Central Office of the Health Zone and to set up an effective monitoring mechanism with the aim of producing reliable epidemiological data.
Research on the evaluation of rural revitalization level in Daqing City
Authors: Yuzhong Sun  , Denan Kong
Published: July 2024

Starting from a systematic perspective, this study divides the rural revitalization system into five subsystems: Prosperous industries, Ecological livability, Rural cultural civilization, Effective governance, and Prosperous life , as well as 14 secondary indicators based on the rural revitalization strategy. It uses the coefficient of variation method and relative weighting method to determine the weight of each indicator. Based on this, the fuzzy comprehensive evaluation method is used to calculate the level of rural revitalization in Daqing City. The research shows that due to the continuous development of the prosperous industries subsystem and the prosperous life subsystem in Daqing, the level of rural revitalization in Daqing City has continued to rise. However, the fluctuation of the ecological livability subsystem caused by the increase in clean fuel use and the decrease in rural greening in Daqing City requires continuous improvement in rural greening. Further increasing the consumption expenditure of rural residents in education, culture, and entertainment can promote the continuous rise of the rural cultural civilization subsystem.
Updates on some medicinal and ornamental plants- Ayurvedic medicines
Authors: Kiran P. Kolkar  , Ravindra B. Malabadi  , Sadiya MR  , Veena Sharada B  , Raju K. Chalannavar
Published: July 2024

This literature review paper highlights morphology, distribution, medicinal properties of commercially important tree species, Thespesia populnea, Terminalia arjuna, Butea monosperma (Palas), Silver oak (Grevillea robusta), Mangifera indica, Madhuca longifolia,Melia azadirachta, Michelia champaca, Moringa oleifera, Peltophorum pterocarpum, and Aegle marmelos. These plants have been used for centuries by local communities and traditional healers for their therapeutic and medicinal properties. Medicinal plants play a crucial role in the Western Ghats, both ecologically and culturally. The use of herbal medicines for the treatment of diseases is safe and traditional. Therefore, medicinal plants have been receiving great attention because of their safety. The Western Ghats harbors more than 7,500 flowering plant species, of which nearly 1,500 are recognized for their medicinal values by local communities and traditional healers. The Western Ghats population traditional medical practices frequently center on using plant-based treatments. These medicinal plants are carefully chosen, and preparation techniques have been perfected through many years of practice. Studies indicated that Mangifera indica possesses antidiabetic, anti-oxidant, anti-viral, cardiotonic, hypotensive, and anti-inflammatory properties. Mango contains Mangiferin, a polyphenolic antioxidant and a glucosyl xanthone, has strong antioxidant, anti lipid peroxidation, immunomodulation, cardiotonic, hypotensive, wound healing, antidegenerative and antidiabetic activities.
Strategic integration of cyber security in business intelligence systems for data protection and competitive advantage
Authors: Justine Chilenovu Ogborigbo  , Odunayo Sekinat Sobowale  , Emmanuel Iyere Amienwalen  , Yemisi Owoade  , Adeyemo Taiwo Samson  , Joshua Egerson
Published: July 2024

In the current world, business intelligence systems play a crucial role in guiding organizations on the best strategies to adopt depending on the analytical information and results obtained (Ahmad et al., 2020). Nonetheless, they are being used frequently and, hence, are vulnerable to ransom attacks, requiring appropriate security measures. This study examines the opportunities for BI solution providers to implement cybersecurity, mitigate risks, and gain competitive advantage. The study adopts a mixed-methods approach to the research involving a literature review study, self-complete questionnaires, interviews, and case studies among a variable of industry professionals. The observation in this research process shows that incorporating enhanced encryption methods, two-factor verification, monitoring, and security culture advancements leads to increased data security levels. Furthermore, apart from defending an organization from cyber-threats, properly implementing cyber security in BI systems ensures that an organization acquires better customer trust, compliance with regulations, and a competitive edge in the market. This paper outlines vital tactics and best practices businesses can apply to enhance, design, and implement robust cybersecurity strategies for organizational benefit. This research aims at the following question; How can cybersecurity be integrated in Business Intelligence (BI) systems considering the facts that businesses are adopting data-driven strategies in the current century? Since more organizations opt for BI systems to collect pertinent information and generate strategic decisions, the systems named remain vulnerable to grabs and threats. Similarly, the research on the role of cyber security is a prime example to show how it need not to be a risk factor but in fact could be a key strength.
Enhancing nutritional quality of Amaranthus cruentus (L.) with fertilisers and salicylic acid
Authors: Modupe Mary Okunlola  , Sifau Adenike Adejumo
Published: July 2024

Globally, deficiency of essential vitamins and minerals in major staple food crops is a great challenge to human health. The use of fertilisers and elicitors has been suggested as a sustainable approach to enhance food quality. Therefore, this study investigated the effects of compost at 5 and 10 t/ha, poultry manure at 5 and 10 t/ha, and NPK 15:15:15 fertiliser applied at rates of 50 and 100 kg N/ha, Salicylic Acid at 125 and 250 µM/L, and their combinations on the growth and food quality of Amaranthus cruentus, a globally consumed vegetable. The experiment was conducted in a screenhouse and arranged in a completely randomized design with three replicates. Data were collected on marketable yield, dry matter, chlorophyll, folate, zinc, iron, crude fibre, ash, and moisture contents. SA250+NPK50 enhanced the marketable yield by 88.0%, and SA125+NPK100 enhanced dry matter accumulation by 92.6% compared to the control. The combination of SA250+NPK50 also increased chlorophyll content by 67.0% relative to the control. Amaranthus cruentus treated with SA250+NPK50 had higher folate (285.00 µg/100g) and iron (348.00 mg/kg) contents than control (125.00 mg/kg and 138.00 mg/kg, respectively), while zinc (47.00 mg/kg) was highest in Amaranthus cruentus treated with SA250+CP10. In addition, Amaranthus cruentus treated with SA125+PM5 had significantly higher crude fibre (13.10%) and ash (12.35%) contents than the control. The combined application of 250 µM/L salicylic acid and 50 kg N/ha NPK fertiliser improved the yield and quality of Amaranthus cruentus, especially in terms of folate, iron, and zinc, which are important micronutrients for human health.
Generalized techniques for constructing the generating functions of some algebraic and rational functions
Authors: Chika Moore  , Justina Ebele Okeke  , Elias Ikechukwu Chukwuma
Published: July 2024

We construct generating functions for general forms of certain classes of algebraic and rational functions using only basic tools of Mathematics. This approach unifies, extends and generalizes several techniques of constructing generating functions.
Advancements in mobile antenna design: A comprehensive literature review
Authors: Iandae T Dosol  , Absalom A Nuestro  , Edwin R Arboleda
Published: July 2024

This study reviews the literature on antenna design in mobile applications, analyzing research, theses, and academic papers to summarize current developments, identify gaps, and suggest future research lines. The review aims to compile the most recent findings on mobile antenna design from respected English-language journals. The study analyzes forty articles discussing both advanced and traditional antenna designs, focusing on efficiency, noise reduction, SAR compliance, size restrictions, polarization, and gain. It emphasizes the importance of innovation and multidisciplinary methods to meet the changing needs of the global communication network. The review uses keywords such as "Antenna," "Antenna Design," "Mobile Antenna," and "Mobile Antenna Design" to find relevant studies across IEEE Xplore, Scopus, Web of Science, and Google Scholar.
Vaccine inequalities, hesitancy, and media-focused public health interventions in English-speaking West-African Countries
Authors: Abideen David Amodu  , Chukwuemeka Oluebube Ochuba  , Ibrahim Temitope Badirudeen  , Kingsley Okwuruoha Ikeokwu
Published: July 2024

Background: Vaccine hesitancy poses a significant challenge to public health efforts in English-speaking West-African countries amidst the COVID-19 pandemic. This study aims to examine the multifaceted factors contributing to vaccine hesitancy in the region, including issues of trust, misinformation, cultural beliefs, and access barriers. Methods: This study reviewed data from three African countries, Nigeria, Ghana, and the Gambia, to analyze attitudes towards vaccination. It also assessed variations in attitudes across these countries and compared them with attitudes in the western world. Qualitative and quantitative methods were employed to gather and analyze data on vaccine hesitancy and related factors. Results: The study found substantial variation in attitudes towards vaccination across the surveyed countries and compared to the western world. Factors contributing to vaccine hesitancy included historical injustices, misinformation, cultural beliefs, and access barriers such as limited healthcare infrastructure and vaccine supply constraints. Media-focused public health interventions were identified as crucial in addressing vaccine inequalities and enhancing vaccine acceptance. Conclusion: Overcoming vaccine hesitancy in West Africa requires tailored approaches that acknowledge and address historical injustices and inequities, emphasize culturally appropriate messaging, and utilize existing community infrastructure to deliver accurate information. Targeted communication strategies are essential to combat misinformation and enhance vaccine acceptance. By analyzing the intersection of vaccine hesitancy, media interventions, and public health challenges, this study underscores the need for comprehensive and community-engaged campaigns to promote vaccination and combat the spread of COVID-19 in West Africa.
Maternal factors associated with the occurrence of Low Birth Weight (LBW) Infants at the Haji Hospital, East Java Province
Authors: Gita Tri Wahyuni  , Euvanggelia Dwilda Ferdinandus  , Dominicus Husada  , Lilik Djuari
Published: July 2024

Introduction: Low birth weight infants are an indicator of public health problems. They are also included in the 100 core health conditions the World Health Organization (WHO) compiled. LBW Infants are still the cause of infant mortality in Indonesia. The infant mortality rate in Indonesia is still not reaching the SDGS target. Objective: This study aims to examine maternal factors associated with the occurrence of LBW Infants at the Haji Hospital, East Java Province Method: This study used a retrospective method with a case-control study design. This study took a sample of 258 infants with inclusion and exclusion criteria. Data collection uses secondary data in the form of collection carried out in the delivery and medical records room. Result: Bivariate analysis obtained the results of gestational age (p < 0.001), history of LBW infants (p = 0.03), anemia (p = 0.641), hypertension in pregnancy (p < 0.001), maternal illness (p < 0.001) with the occurrence of LBW infants. Based on multivariate analysis, mothers with gestational age <37 weeks had OR 8.667 (95%CI 4.509-16.659), a history of LBW infant had OR 10.736 (95%CI 1.895-60.809), hypertension in pregnancy OR 2.468 (95%CI 1.250-4.869), and maternal illness OR 3.212 (95%CI 1.301-7.932) times to experience LBW infants. Conclusion: This study highlights the burden of caring for LBW infants in the Haji Hospital in East Java province. Maternal factors need to be given special attention during pregnancy. Health promotion measures, early detection screening, and intervention of related factors need to be done so that the occurrence of LBW infants can be prevented.
The effect of providing education on parent's knowledge and behavior in completing the development monitoring checklist in the Mom and Child health book in the working area of Tarik Health Centre
Authors: Putri Prawati  , Budi Utomo  , Astika Gita Ningrum  , Ratna Dwi Jayanti
Published: July 2024

Introduction: Deviations in growth and development of toddlers can be detected as early as possible. Development monitoring can be carried out independently by parents using the Mom and Child Health book. The results of the Sidoarjo District Riskesdas 2018, the utilization of the Mom and Child Health Book in the development section is still lacking. This study aims to analyze the effect of education on changes in knowledge and behavior of filling out the development monitoring checklist in the Mom and Child Health Book by parents. Methods: This research method is pre-experimental designs with one group pretest-posttest design. The sample size was 77 respondents with sampling technique using multistage random sampling. The independent variable is the provision of education provided personally using the Mom and Child Health book owned by parents. The dependent variable is knowledge and behavior. The instruments used were questionnaires and Mom and Child Health books. Data analysis using Wilcoxon Signed Rank. Test. Results: The results showed that the knowledge category had increased. The good category from 43% to 87% and no one is in the less category. Wilcoxon Signed Rank Test results pretest-posttest data knowledge p = 0.001 (p < 0.05). The category of behavior that before being given education no one had filled out the development monitoring checklist at all from 77 respondents increased to 70.12%. Increased knowledge has a significant impact on changes in parental behavior in filling out the development monitoring checklist in the Mom and Child Health book. Conclusion: There is an effect of providing education on knowledge and behavior of filling out the developmental monitoring checklist in the Mom and Child Health book.