bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Willingness of Mobile Advertisement Users Based on TAM Model
Authors: Su Qiaoqin
Published: May 2024

This study aims to explore the framework of the technology acceptance model (TAM) to examine how subjective norms, perceived precision, and perceived control can positively influence users’ willingness to adopt mobile ads by enhancing perceived usefulness. In the context of the rapid development of the digital era, mobile advertising serves as an important marketing tool. Its user acceptance directly impacts the marketing effectiveness of enterprises. Therefore, a profound comprehension of the key factors that influence user adoption of mobile ads is crucial for designing more effective mobile ad strategies. In this study, we collected the attitudes and responses of users from various backgrounds towards mobile advertising and conducted data analysis using a structural equation model. The study found that subjective norms, perceived accuracy, and perceived control are important factors influencing users’ perceived usefulness. Additionally, perceived usefulness significantly and positively impacts users’ willingness to adopt mobile ads.
Evolution of AI in Academic Research
Authors: Kawatra Mansi Batra
Published: May 2024

The progression of artificial intelligence (AI) in academic study is a fascinating exploration of the past, characterized by important achievements, revolutionary advancements, and a relentless pursuit to expand the limits of human understanding. Within the present academic environment, artificial intelligence (AI) has a ubiquitous influence that can be found in a variety of fields, including instruction, research, and administration. Individualized learning experiences are provided by intelligent tutoring systems, which are powered by machine learning algorithms. These systems are able to adjust to the specific requirements of each learner. Applications of artificial intelligence in data analysis, predictive modeling, and pattern recognition are beneficial to research processes because they speed up the discovery of scientific knowledge across an array of fields. The primary aim is to explore the historical development, pivotal contributions, emerging trends, and future directions of AI within the academic realm.
Augmenting Research
Authors: Agrawal Vivek , Bhardwaj Shivam , Pathak Neeraj , Dixit Jitendra Kumar , Agarwal Sucheta , Momin Mujtaba M.
Published: May 2024

The growing power of artificial intelligence (AI) is fundamentally altering the landscape of academic research. AI-powered tools are streamlining tasks like literature reviews, manuscript drafting, and reference generation, empowering researchers to delve deeper into their work and foster innovation within their fields. Natural language processing (NLP) capabilities of AI tools facilitate rapid and comprehensive literature reviews, identifying emerging trends, gaps, and interconnected themes. This integration of AI in academic research signifies a paradigm shift, offering unprecedented opportunities for exploration and discovery. However, as AI tools become more commonplace, reviewers and editors must maintain vigilance. While these tools enhance efficiency, there's a risk that their use may compromise the scientific integrity of research. Therefore, striking a balance between leveraging AI's advantages and preserving the rigor of scientific discourse is imperative.
The Use of Artificial Intelligence Tools in Academic Writing With Agronomic Direction
Authors: Lebedeva Nadezhda Anatolievna
Published: May 2024

In the context of agricultural science, the academic writing is of great importance, as articles of academicians and scientists make available all their developments available for studying the experiences around the world. This contributes not only to the exchange of experience, but also to expand the practical knowledge in agrarian topics to different continents and countries, spreading the developments of economical agriculture for solving problems with food on a global scale. Therefore, the use of artificial intelligence in the field of agrarian academic writing can be as positive results, so has risks of incorrect research of certain issues. This chapter sets itself the goal of considering the pros and cons of using artificial intelligence tools in academic writing with an agronomic focus, taking into account the specifics of the basic concept of academic writing and new artificial intelligence tools. The novelty of this work lies in the fact that developments of Ukrainian scientists can serve as interesting theoretical material for foreign colleagues.
AI-Enhanced Hypothesis Development and Research Questions
Authors: Srivastava Anugamini Priya , Shetye Swati Krutarth
Published: May 2024

This chapter explores how artificial intelligence (AI) transforms research by aiding in research questions identification and hypothesis development. It aims to equip researchers with insights into leveraging AI tools effectively, driving innovation and advancing knowledge in diverse fields. AI integration revolutionizes research methodologies, offering speed and accuracy in literature review and data analysis. From natural language processing to expert systems, AI empowers researchers to formulate hypotheses grounded in theory and empirical evidence. Readers will understand AI's transformative potential in research, enabling them to uncover new insights, address complex questions, and enhance research rigor responsibly. Practical insights will empower researchers to integrate AI effectively, driving innovation and advancing scholarship.
AI-Powered Data Collection and Analysis
Authors: Srivastava Anugamini Priya
Published: May 2024

In the ever-evolving landscape of research, the integration of artificial intelligence (AI) has ushered in a new era of data collection and analysis, particularly in qualitative research. Traditionally, qualitative research has been characterized by labor-intensive processes, including manual data collection and time-consuming analysis. However, AI-powered tools have revolutionized these practices, offering researchers, including students at various academic levels, efficient and powerful methods for data collection, screening, and analysis. In this chapter, the authors embark on an exciting journey to explore myriad possibilities of utilizing different AI tools to streamline the qualitative research process.
AI Tools for Efficient Writing and Editing in Academic Research
Authors: Abinaya M. , Vadivu G.
Published: May 2024

Readers embark on a journey exploring AI's profound impact on content creation. It begins by tracing AI's evolution, underscoring its pivotal role in modern content production. The narrative delves deep into AI mechanisms, decoding algorithms, and the significance of natural language processing. It meticulously analyses AI tool classifications, emphasizing their benefits in content generation, writing style enhancement, and grammar checks. The chapter illuminates AI's role in boosting productivity and creativity, offering practical guidance on tool selection. Importantly, it stresses human proofreading's unique touch in the final editing phase. Anticipating future advancements, it envisions seamless integration of AI and human creativity in popular writing platforms.
Transformative Horizons
Authors: Pathak Ankita , Mishra Sunil , Quttainah Majdi Anwar
Published: May 2024

ChatGPT has played a revolutionary role in the field of scientific research. The usage of ChatGPT has contributed to the advancement of knowledge in numerous fields. The first section of the chapter explains the fundamental ideas of ChatGPT, emphasizing its contextual awareness and natural language processing powers. In addition, ChatGPT's incorporation into scientific research represents a paradigm change by providing faster data processing, simplified literature reviews, and creative hypothesis formulation. The benefits are evident in its ability to enhance efficiency, foster interdisciplinary collaboration, and democratize access to scientific knowledge. However, challenges include ethical considerations, biases in training dataset, and the imperative of ensuring model transparency. Striking a balance between ChatGPT's capabilities and addressing these limitations is crucial for realizing its full potential as a transformative force in advancing scientific inquiry.
An Efficient Technique to Perform 3D Visualization on Clinical Image Datasets
Authors: Haryal Prabhjyot kaur , Rattan Punam
Published: May 2024

The main idea behind this work is to present three-dimensional (3D) image visualization through two-dimensional (2D) images that comprise various images. 3D image visualization is one of the essential methods for excerpting data from given pieces. The main goal of this work is to figure out the outlines of the given 3D geometric primitives in each part, and then integrate these outlines or frames to reconstruct 3D geometric primitives. The proposed technique is very useful and can be applied to many kinds of images. The experimental results showed a very good determination of the reconstructing process of 2D images.
Federated Learning for Privacy Preservation in Healthcare
Authors: Kondaveeti Hari Kishan , Simhadri Chinna Gopi , Mangapathi Srileakhana , Vatsavayi Valli Kumari
Published: May 2024

This chapter delves into fundamental concepts of privacy preservation and federated learning (FL) in healthcare. Emphasizing the importance of privacy in healthcare data, it explores ethical and regulatory considerations surrounding sensitive patient information. The history and significance of FL, distinct from traditional centralized machine learning, are discussed, highlighting its relevance in addressing privacy concerns. The limitations of centralized ML are contrasted with FL's advantages, particularly in preserving privacy. Techniques such as FL averaging, aggregation, and secure multi-party computation (SMPC) for privacy-preserving model updates are examined. Real-world examples illustrate their application in healthcare scenarios. The chapter concludes by addressing technical and ethical challenges linked to FL in healthcare, emphasizing its potential to balance patient data protection with AI advancements. Privacy concerns persist in healthcare AI, making FL a promising solution. The discussion extends to emerging trends and potential breakthroughs in this dynamic field.
Federated Learning for Private Cancer Diagnosis With Exascale Computing
Authors: Vembu N. R. , Maiti Niladri , Kadiervel K. , Choudhury Amarendranath , Pinnamaneni Rajasekhar
Published: May 2024

This study delves into the intersection of federated learning, privacy preservation, and exascale computing to advance the field of cancer diagnosis. Employing a federated learning framework, the research addresses the imperative need for collaborative, yet privacy-conscious, approaches to healthcare data analysis. Focusing on human cancer diagnosis and detection, the authors leverage the power of exascale computing to handle massive datasets distributed across diverse medical institutions. The proposed methodology ensures privacy by design, enabling secure model training without centralized data aggregation. The findings showcase the efficacy of federated learning and exascale computing in achieving accurate and timely cancer diagnoses while upholding patient privacy, thus paving the way for transformative advancements in personalized and secure healthcare analytics
Secure and Privacy-Preserving Federated Learning With Explainable Artificial Intelligence for Smart Healthcare Systems
Authors: Komalasari Rita
Published: May 2024

With the escalating global population, the healthcare sector faces unprecedented challenges, necessitating innovative solutions. Deep learning (DL) and federated learning (FL) have emerged as pivotal technologies, yet challenges persist in data privacy, security, and model interpretability, especially in healthcare applications. This research addresses these challenges by proposing robust frameworks for secure, privacy-preserving federated learning with explainable artificial intelligence in smart healthcare systems. The objective is to enhance the security, performance, and privacy of healthcare systems, ensuring their resilience and effectiveness in real-world scenarios. The research employs a literature approach. This comprehensive approach establishes a foundation for the future development of smart healthcare systems, fostering trust, transparency, and efficiency in healthcare decision-making processes.
AI-Driven Software Development Lifecycle Optimization
Authors: Goel Pawan Kumar , Komal Km , Vashishth Nitish
Published: May 2024

This research explores the integration of artificial intelligence (AI) into the software development lifecycle (SDLC) to optimize processes and address evolving industry demands. Against a backdrop of increased complexity in software projects, the study investigates historical context, emphasizing the imperative for AI infusion in SDLC. The primary objective is to illuminate how AI strategically enhances various SDLC stages, elucidating specific challenges it addresses. Employing a multifaceted approach, including literature reviews, case studies, and empirical analyses, the research showcases AI's role in automated code generation, intelligent code reviews, predictive maintenance, AI-powered testing, and dynamic resource allocation. Results demonstrate increased development speed, improved code quality, proactive issue identification, and efficient resource utilization. The chapter synthesizes key insights, underscoring AI's transformative impact on software development efficiency and product quality.
Industry-Specific Applications of AI and ML
Authors: Singhal Saurabh , Sharma Ajeet Kumar , Singh Akhilesh Kumar , Pandey Anand , Sharma Avinash Kumar
Published: May 2024

Artificial intelligence in healthcare has the potential to enhance diagnostics, patient care, and medical research. However, trust in AI-driven decision-making processes is crucial as AI systems become more complex. Explainable artificial intelligence (XAI) is a strategy to ensure AI-driven healthcare solutions are efficient and understandable to healthcare professionals and patients. XAI can improve medical practitioners' decision-making processes, increase trust in AI recommendations, and boost patient-doctor communication. Applications include medical imaging, predictive analytics, drug development, and tailored treatment plans. The chapter discusses the ethical and regulatory implications of AI in healthcare, focusing on patient data privacy and security. Future XAI trends will focus on improving patient outcomes and healthcare service quality by making AI systems accessible and consistent with ethical norms.
Reinforcement Learning in Bug Triaging
Authors: Singh Neetu , Singh Sandeep Kumar
Published: May 2024

The bug cold start problem in software engineering arises when managing new bugs without historical data, challenging bug triaging systems. Reinforcement learning (RL) aids bug triaging, but conventional RL struggles with limited data. Advanced RL methods like bandits and DQN adapt to sparse data, enhancing decision-making. ML-based and RL-based approaches are explored to overcome this issue. Ethical concerns, interpretability, and exploration-exploitation trade-offs in RL are considered. Future research in RL shows promise in addressing the cold start problem across domains like bug triaging and e-commerce, with strategies such as improved exploration, transfer learning, hybrid approaches, and AutoML gaining traction.
A Retrospective Cohort Study on the Impact of Maternal Body Mass Index and Gestational Weight Gain on Maternal and Fetal Outcomes
Authors: Patange R. P. , Patil Yamini , Chawla Jasmine Kaur , Kshirsagar N. S.
Published: May 2024

The purpose of this initial study was to look at the connections between gestational weight increase and the mother's and fetus's outcomes in the first trimester of pregnancy and their link to each other. This retrospective cohort study was conducted at two tertiary care hospitals with pregnant women enrolled during the first trimester. Information was gathered from self-reported questionnaires and electronic health records on maternal BMI, gestational weight gain, and maternal and foetal outcomes. Multiple logistic regression models were used to evaluate relationships between maternal BMI, gestational weight increase, and pregnancy outcomes. There were 500 participants in the study. An increased risk of hypertensive diseases, gestational Diabetes, and caesarean section deliveries has been linked to higher maternal BMI. A higher risk of macrosomia, intrauterine growth restriction (IUGR), and preterm birth were associated with lower maternal BMI. A higher incidence of gestational Diabetes and hypertensive diseases was linked to gestational weight growth that was below the advised range. On the other hand, rapid weight increase was associated with an increased risk of macrosomia, IUGR, and premature birth. Combined research showed that the greatest risk of gestational Diabetes and hypertensive problems was associated with obese women who gained weight over what was indicated. In summary, comprehending the intricate connections among maternal body mass index, gestational weight increase, and pregnancy consequences is essential for enhancing prenatal care and mitigating the hazards linked to maternal obesity and unwarranted weight growth. More study is required to understand the underlying mechanisms further and create evidence-based methods for improving the health of both the mother and the foetus.
Efficient Noise Removal From Preterm Baby Retinopathy Images Using Various Filtering Approaches
Authors: Hubert G. , Priscila S. Silvia
Published: May 2024

For healthcare practitioners to perform reliable and precise assessments, assuring early detection and appropriate treatment of retinal illnesses, high-quality, noise-free images, is essential. An essential step in improving the reliability and precision of medical diagnoses is the reduction of noise from premature newborns' retinopathy photos. Effective noise removal can be accomplished by using various filters and methods. In recent days, research has been on the effectiveness of noise removal methods is available, specifically the homomorphic filter (HF), laplacian of gaussian (LOG) filter and adaptive filter (AF), with a focus on improving the clarity of retinopathy photos in preterm infants. The authors carefully compared the results with those of homomorphic, LOG, and adaptive filters via thorough testing and assessment criteria such as mean squared error (MSE), peak signal-to-noise ratio (PSNR), and Structural similarity index (SSIM). Applying the LOG filter produced better outcomes for each studied output parameter, producing MSE of 0.000119, PSNR of 42.34and SSIM of 0.998, respectively. The tool used for execution is Python.
A Prospective Study on Phenylephrine and Glycopyrrolate for Hemodynamics in Cesarean Delivery Under Spinal Anesthesia
Authors: Naik Shraddha , Hippalgaonkar Amruta , Gandhi Soudamini , Shamsi Sharick
Published: May 2024

During routine caesarean births, spinal anaesthesia causes hemodynamic reactions that complicate anaesthesia. Hypotension and bradycardia can harm the mother and foetus. This prospective study examined the safety and efficacy of intravenous glycopyrrolate and phenylephrine in decreasing these responses. Phenylephrine (n = 53), glycopyrrolate (n = 55), and control (Placebo) were randomly assigned to 162 elective caesarean deliveries under spinal anaesthesia. Hemodynamic parameters, maternal bradycardia and hypotension, neonatal outcomes, side effects, and mother satisfaction were assessed. Phenylephrine and glycopyrrolate reduced maternal hypotension compared to the control group (15 percent for phenylephrine, 11 percent for glycopyrrolate, and 33 percent for control). Similarly, maternal bradycardia decreased in intervention groups (7 percent in phenylephrine, 5 percent in glycopyrrolate, and 17 percent in control). Phenylephrine and glycoproscarcinol enhanced neonatal outcomes with higher Apgar ratings at one and five minutes. In the intervention groups, tachycardia, nausea/vomiting, and maternal discomfort decreased. Using phenylephrine and glycopyrrolate increased maternal satisfaction. Intravenous glycopyrrolate and phenylephrine regulate hemodynamic responses after spinal anaesthesia caesarean birth. These interventions reduce bradycardia and hypotension in mothers, improving mother and infant comfort and health. The good safety record and better mother satisfaction underline the need to tailor anaesthesia to each parturient. Phenylephrine and glycopyrrolate may improve the safety and satisfaction of women and their newborns during caesarean deliveries, but further research is needed to solve research limitations.
An Innovative Methodological Approach to Analysing Social Media Movements
Authors: Connolly Emma Anne
Published: May 2024

Social media movements take place in an increasingly volatile technological landscape. Researchers who want to analyse their spread must navigate methodological challenges relating to data accessibility, combining qualitative and quantitative data, and remaining attentive to the shifting technological affordances of social media platforms. In response to key challenges, the paper outlines an innovative, three-fold methodological approach to the analysis of social media movements integrating three strands: the Linguistic, Material, and Processual (LMP). Using the hashtag #JeSuisCharlie as a case study, the paper demonstrates how an LMP approach can provide richer insights into social media movements which would be missed by most current methods. Its low-cost design, flexible approach, and technical accessibility equips the researcher in anticipation of further change in the technical landscape. The framework outlined in the paper can be applied to other social media platforms.
A Web-Based Assessment and Evaluation System for Architectural Design Studio Modules
Authors: Azmy Ahmed , Alabdullatief Aasem , Altassan Abdulrahman , Mokhtar Hala
Published: May 2024

Architectural design studio modules are known to be difficult to teach and/or assess. To acquire design skills, typically, students have several design modules during their program and several projects for each module. However, traditional project assessment and evaluation lacks consistency, objectivity and fairness. Furthermore, monitoring student progress over the different projects and over the different modules and different semesters is very difficult and needs much time and effort. This work presents a web-based system developed to support fair rubrics-based assessment and evaluation of design projects and to provide in-depth analysis of students' results. It also links between the results over the different projects and the different modules and provides feedback about students' skills and weaknesses in a simple form thus allowing progressive learning. The system has been tested and evaluated and the results show its simplicity, reliability and effectiveness.
The Role of Deep Learning in Supply Chain Collaboration and Cooperation
Authors: Cai Junjie , Sharkawi Ismawati , Taasim Shairil Izwan
Published: May 2024

In today's globalized and technologically advanced business landscape, supply chain collaboration is crucial for enterprises seeking to gain a competitive edge, enhance operational efficiency, and adapt to market dynamics. Traditional methods often fall short in managing the complexities and rapid changes within supply chains. This study introduces an innovative deep learning model, combining BERT, GAT, and RL, to address these challenges effectively. The model demonstrates its prowess in processing supply chain data, accurately predicting market trends, and optimizing decision-making processes. By leveraging deep learning, this research not only expands theoretical applications in supply chain management but also provides practical tools to boost operational efficiency, highlighting the immense potential and practical value of deep learning technology in modern supply chain management.
Carbon gas sensors synthesized using acacia auriculiformis tree branches to detect methanol, ethanol, acetone vapors and ammonia gas
Authors: Ranasinghe R. A. S. R. , Rathnathilaka K. A. C. , Karunarathna P. G. D. C. K. , Samarasekara P.
Published: May 2024

Metal oxides and carbon are the prime candidates of gas sensor devices. For the inaugural instance, carbonaceous particulate matter was meticulously derived from the branches of Acacia auriculiformis tree indigenous to Sri Lanka to detect vapor and gas. It is worth noting that biomass derived carbon had hitherto remain unexplored in the realm of vapor and gas detection. Carbon films were fabricated via the doctor blade method. The resistivity characteristic of these carbon samples exhibited discernible variations upon exposure to methanol, ethanol, acetone vapors, and ammonia gas. Notably, the gas-sensing properties of sample derived from the central core and the outer shell of Acacia auriculiformis tree branches were independently assessed in these vapors and gas at ambient temperature. Various analytical techniques, including X-ray diffraction (XRD), UVvisible absorption spectroscopy, Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM), were judiciously employed to scrutinize the structural attribute, optical band gap, chemical composition and surface morphology of the aforementioned carbon film samples, respectively. XRD analyses unequivocally confirmed the successful formation of carbonaceous films. FTIR spectra conspicuously delineated the presence of oxygen within the carbon films. Importantly, the optical band gap of our carbon films manifested within the range characteristic of organic carbon. Furthermore, the resistance of the carbon films demonstrated a significant reduction upon adsorption of each vapor. It is noteworthy that while gas sensitivities and response times were superior for carbon derived from the central core of the Acacia tree branches, the recovery times were notably expedited for carbon synthesized from the outer shell of these branches. The zenith of gas sensitivity, an impressive 187%, was recorded in response to 1000 ppm of methanol vapor, when employing carbon sourced from the central core of the acacia tree branches.
Evaluation of Electromagnetic Therapy in the Treatment of Severe Dysmenorrhea in Young Women of Basrah
Authors: Al Hassan Raya Muslim , Abdullah Nawal Mustafa , Al Tawry Ali Mohammad Jawad
Published: May 2024

Introduction:

Primary dysmenorrhea (PD) is a public disease of young female worldwide, it affects their daily performances. Severe recurrent uterine cramps are the main complaints in 90% of adolescents and 50% of reproductive-age females. This study aimed to evaluate the use of magnetic field therapy in the treatment of severe dysmenorrhea grade 3 and provide an encouraging goal to continue daily work without pain.

Methods:

Two hundred and fifty female patients were recruited in this study from gynecological clinics in Basrah, southern Iraq. All had severe dysmenorrhea, patients were subjected to a questionnaire form, Visual Analog Scale, and verbal multidimensional scoring system to determine the pain intensity and grade of dysmenorrhea. Only 38 young females had severe dysmenorrhea grade 3 with ages ranging from 16 to 28 years with a mean age of 22.04 ± 1.43 years and body mass index 23.81 ± 1.94, patients subjected to electromagnetic field therapy (EMFT), two sessions per week for 20 min each for 6 weeks. Three categories were assessed, working ability, associated symptoms, and drugs used. Data were collected and statistically analyzed using SPSS version 22.

Results:

The present study showed statistically significant progress (P < 0.05) in reducing pain, rare physical and mental complaints, and improved working ability with no need for drugs in majority of patients.

Conclusion:

EMFT has better results than other methods in relieving pain and symptoms of dysmenorrhea with a settled lifestyle.
Dietary intervention in acne management: review of the literature and future prospective
Authors: Cacciapuoti Sara , Annunziata Maria C. , Megna Matteo , Villani Alessia , Martora Fabrizio , Fabbrocini Gabriella , Potestio Luca
Published: May 2024

Acne is a common skin disease, affecting millions of subjects worldwide. Several processes and mechanisms have been identified in acne pathogenesis. Among these, it is known that acne or its worsening is also related to metabolic factors and nutritional influences. In this scenario, we carried out a review of the current literature in order to investigate the role of diet in acne disease, offering a wide perspective for possible clinical applications. A total of 55 manuscripts were considered. In particular, the role of the Western diet, glycemic index, glycemic load, dairy products, fats, fatty acids, Mediterranean diet, ketogenic diet, and dietary supplements in acne management has been investigated. On one hand, dairy products, foods with high glycemic load and glycemic index, fatty acids and fats seem to worsen the severity; on the other hand, Mediterranean and ketogenic diet, and oral supplements seem to improve the disease. Despite the conflicting results and conclusions in the scientific literature about the impact of nutrition in acne, mainly related to the severla limitations of the study design, several prospective, controlled, well-designed studies have recently demonstrated the role of some specific nutrition influenced mediators on acne severity.
The effect of narrowband ultraviolet B on tissue level of interleukin-15 and interleukin-15 receptor alpha subunit in active nonsegmental vitiligo cases: an interventional cohort study
Authors: Youssef Randa , Emad Nourhan , Shaker Olfat , Mogawer Rania M.
Published: May 2024

Background

Vitiligo is an acquired depigmenting skin disorder in which CD8 effector and memory T-cells contribute to its pathogenesis and recurrence. Interleukin (IL)-15 contributes to CD8 effector T-cell cytotoxicity and CD8 memory T-cell survival and maturation.

Objective

To evaluate the effect of total narrowband ultraviolet B (NB-UVB) on tissue levels of IL-15 and IL-15 receptor alpha (IL-15Ra) in active nonsegmental vitiligo.

Patients and methods

The patients were assessed clinically for vitiligo extent and activity before and after treatment. Perilesional skin biopsies were taken from 30 vitiligo patients before and after 48 sessions of NB-UVB and from 30 healthy controls. Tissue levels of IL-15 and IL-15 Ra were evaluated by enzyme-linked immunosorbent assay before and after treatment to evaluate the effect of NB-UVB on them.

Results

Before NB-UVB treatment, the tissue levels of both IL-15 and IL-15Ra were significantly higher in vitiligo patients than controls; moreover, they were significantly higher than those after NB-UVB treatment. In contrast, after NB-UVB treatment, no statistically significant difference was detected between the patients and controls. The levels of IL-15 and IL-15Ra were significantly correlated, whereas they were not correlated with either vitiligo activity or extent.

Conclusion

IL-15 and IL-15Ra were higher in vitiligo patients than controls before treatment. However, their tissue levels were normalized after treatment with NB-UVB, emphasizing its therapeutic potential.
Fractional CO2 laser, platelet rich plasma and combination of both in treatment of female pattern hair loss
Authors: Tawfik Abeer , Gahdan Noha , Nosseir Moataz
Published: May 2024

Background

Female pattern hair loss (FPHL) is one of the most common chronic problems seen by dermatologists worldwide. Hair loss has a significant influence on the quality of life and is associated with low self-esteem and depression.

The treatment modalities vary from medical approaches to surgical interventions. However, limited perceived efficacy of a therapeutic regimen may lead to premature stoppage of treatment.

Objective

To evaluate the efficacy of platelet rich plasma (PRP), fractional CO2 laser and combination of both in treatment of FPHL.

Patients and methods

This is a split-scalp prospective interventional study in which thirty patients presenting with FPHL received PRP in one area, fractional CO2 in another one, combined fractional CO2 and PRP in a third one and saline intradermal injection in the fourth area in frontal and mid scalp region of scalp. The sessions were scheduled every 2 weeks for 4 sessions, then monthly for 2 months. Patients were evaluated after each session and 3months after the last session. The results were evaluated by trichoscopic and folliscopic examination in the four examined areas. Assessment of treatment response was done according to the count of terminal and vellus hair, the thickness and density of hair shafts and the percentage of change, determined by folliscopic examination. Patients’ satisfaction and side effects were evaluated.

Results

There was significant difference between the studied groups as regards percentage of change of terminal hair, vellus hair, hair thickness and hair density after treatment. Pairwise comparisons showed that the combined group was statistically better than either PRP, fractional CO2, or saline group as regards all studied parameters (P value was <0.05 for each).

Conclusion

Combination of fractional CO2 laser and topical PRP application would have a synergistic effect in treatment of FPHL. The technique would be an excellent alternative to injections in order to stimulate hair growth in patients with FPHL.
Assessment of peripheral blood toll-like receptor 2 expression and vitamin D serum level as predictors of response to intralesional vitamin D in the treatment of warts
Authors: Sanad Eman M. K. , Sanad Rana R. , Shahat Amany K. , Hamed Ahmed M.
Published: May 2024

Background

Warts are common dermatological conditions caused by human papilloma virus. Most treatments for human papilloma virus rely on the destruction of involved tissue. The role of vitamin D injection in treating warts is thought to be via regulating cell proliferation and differentiation through the upregulation of vitamin D receptors and the induction of antimicrobial peptides.

Objective

To assess the clinical efficacy and safety of intralesional vitamin D in the treatment of cutaneous warts and also the significance of peripheral blood toll-like receptors 2 (TLR2) expression and serum levels of 25-hydroxyvitamin D in predicting the therapeutic success.

Patients and methods

In this prospective interventional study, 50 patients of cutaneous warts were subjected to history taking, proper dermatological examination, and peripheral venous blood collection for detection of TLR2 mRNA expression and a serum level of 25 (OH) D. Vitamin D3 was slowly injected into the base of the largest or the oldest wart at 2-week intervals.

Results

A total of 34 (69.4%) patients showed response to intralesional Vitamin D [21 (42.9%) showed complete resolution of all lesions, 13 (26.5%) showed partial clearing] and 15 (30.6%) patients showed poor or no response after four sessions. Serum level of vitamin D did not show a significant relation with treatment response. TLR2 expression was higher in the group showing complete response.

Conclusion

Intralesional vitamin D injection offers a safe and cost-effective therapy for different types of cutaneous warts. TLR2 expression in patients’ serum can be used to predict response to treatment by intralesional vitamin D, with better response in patients with higher expression.
Exploring the Impact of Orthodontic Treatment on Temporomandibular Joint Health
Authors: Pradhan Devina , Almalki Sultan A. , Sharma Richa , Mishra Samvit , Pathak Apurva , Jethlia Ankur , Makkad Ramanpal S.
Published: May 2024

ABSTRACT

Background:

Currently, one of the most prevalent oral abnormalities is malocclusion. There is a rising percentage of patients who are willing to undertake orthodontic procedures.

Aim:

To evaluate the impact of orthodontic treatment on the morphology of temporomandibular joint (TMJ) in patients with malocclusion associated with TMJ abnormality such as skeletal class II deep bite malocclusion using CBCT.

Methods and Materials:

In total, 80 patients who underwent orthodontic treatment for skeletal class II deep bite malocclusion over a duration of 3 years were included. Parameters of the morphology of the condyle and glenoid fossa on CBCT scan both before and after orthodontic therapy were measured.

Results:

The maximum cross-sectional area of the condyle decreased from 99.84 ± 18.89 mm2 to 81.32 ± 16.80 mm2 after orthodontic treatment. The anterior condyle oblique inclination increased from 34.14 ± 2.98° to 36.52 ± 3.41° after orthodontic therapy. The articular eminence to the FH plane angle increased from 29.65 ± 2.53° to 33.29 ± 4.18° after orthodontic therapy.

Conclusion:

Orthodontic treatment is significantly correlated with improvement in TMJ health in patients of malocclusion.
Intraoral Scanners: Mechanism, Applications, Advantages, and Limitations
Authors: Dhull Kanika Singh , Nagar Rohit , Mathur Pranshu , Shil Malabika , Jain Shrinidhi , Dureha Roli , Kapoor Abhay
Published: May 2024

ABSTRACT

In recent years, the field of dentistry has witnessed remarkable technological advancements, one of which is the development and widespread implementation of intraoral scanners. These devices have revolutionized the way dental professionals capture accurate impressions of patients’ oral cavities, offering several advantages over traditional impression-taking methods. To shed light on the impact of intraoral scanners on dentistry practice, this article explores their mechanism, uses, benefits, and limitations.
In vitro Investigation of Resin Tag Lengths of Three Commercially Available Pit and Fissure Sealants
Authors: Sahu Nayan J. , Panwar Pratyaksha S. , Dhanak Nupur R. , Samir P V , Najeeb Ajmal , Rayast Deepa
Published: May 2024

ABSTRACT

Aim:

The aim of this in vitro study was to perform a comparative evaluation of the length of resin tags produced by three different types of pit and fissure sealants (Embrace WetBond, Helioseal Clear, and Fuji VII) using scanning electron microscopy.

Materials and Methods:

Thirty extracted mandibular premolars were randomly divided into three groups of ten. Each group was treated with one of the sealants – Embrace WetBond, Helioseal Clear, or Fuji VII. Following cleaning and preparation, the sealants were applied according to the manufacturer’s instructions. Teeth were then sectioned and prepared for SEM investigation, and the length of resin tags was measured.

Results:

Scanning electron microscopy revealed Embrace WetBond produced significantly longer resin tags than Helioseal Clear and Fuji VII.

Conclusion:

The study concludes that Embrace WetBond sealant exhibited the longest resin tags, which may suggest a stronger mechanical bond to enamel.
Herbal Dentistry: Nurturing Oral Health with Natural Remedies
Authors: Duggal Surabhi , Chandrika P. Sindhu , Nasyam Fazil A. , Singh Dhirendra K. , Devraj Indira M. , Anand Charu
Published: May 2024

ABSTRACT

Herbal dentistry, also known as natural or holistic dentistry, is a field of dental care that utilizes natural remedies and herbal medicine to prevent and treat oral health issues. This approach focuses on the use of herbs, plant extracts, and other natural substances to promote oral hygiene and address dental problems. In recent years, there has been a growing interest in herbal dentistry as an alternative to conventional dental treatments. This comprehensive review aims to explore the use of herbal remedies in dentistry, their potential benefits, and their limitations.
IoT Product Design for User Experience and Technological Innovation in Virtual Reality Environments
Authors: Zhang Hao
Published: May 2024

INTRODUCTION: The rapid development of virtual reality technology and the Internet of Things (IoT) has provided new possibilities for user experience, and a variety of new products have emerged, especially in the field of painting, where the combination of these two provides a new platform for innovative artistic expression.OBJECTIVES: This study takes IoT products in the art field as an example to analyze the user experience in virtual reality environments and the impact of technological innovations on IoT products, as well as to explore the potentials and limitations of this emerging form of products and forms of painting.METHODS: In this study, the author constructed a virtual reality painting environment, utilized IoT technology to collect data from the user's painting process, and combined quantitative and qualitative analysis methods to assess user experience and technological innovation comprehensively.RESULTS: In the virtual reality environment, the user experience was significantly improved, and the users were more immersed in the painting process and felt more robust creativity and expression. Meanwhile, the application of Internet of Things (IoT) technology also provides more possibilities for drawing; for example, using smartpens makes the drawing process more smooth and natural.CONCLUSION: IoT painting with user experience and technological innovation in a virtual reality environment can provide a new creative platform for artists and bring a richer artistic experience to the audience, showing the feasibility and broad prospect of IoT products based on a virtual reality environment.
Translation surfaces: Dynamics and Hodge theory
Authors: Filip Simion
Published: May 2024

A translation surface is a multifaceted object that can be studied with the tools of dynamics, analysis, or algebraic geometry. Moduli spaces of translation surfaces exhibit equally rich features. This survey provides an introduction to the subject and describes some developments that make use of Hodge theory to establish algebraization and finiteness statements in moduli spaces of translation surfaces.
Copper, Sheet, Strip, and Plate Soft Annealed
Authors:   AMS D Nonferrous Alloys Committee
Published: May 2024

This specification covers unalloyed copper in the form of sheet, strip, and plate at least 0.015 inch (0.38 mm) in nominal thickness.
Proximate analysis and mineral contents of atella from traditional tella brewers in Jimma City, Ethiopia
Authors: Shifarew Tesfaye , Girma Asere Tsegaye , Yitibarek Menberu , Diro Abebe
Published: May 2024

Atella is a by-product of Tella, a local brewed beverage. It is used as a food source to promote weight gain, development, and milk yield in cattle and sheep. The aim of this study was to analyze the physicochemical properties, nutritional composition, and mineral content of Atella. The samples of Atella were purposively collected from 25 Tella vendors in Jimma City, Ethiopia. The physicochemical properties and proximate analyses were performed using the AOAC method. The mineral contents of the samples were measured using flame atomic absorption spectrometry (FAAS). The results showed that the pH value was between 3.36 - 4.23, temperature (19.27 - 20.20 °C), conductivity (124.10 - 153.50 μS/cm), dry matter content (15.87 - 20.17%), crude protein content (16.47 - 18.72%), crude fat content (3.73 - 5.43%), crude fiber content (15.52 - 19.73%), total ash content (3.58 - 4.47%), carbohydrate content (35.02 - 40.50%), and gross energy (247.42 -271.13 kcal/g). The average concentrations of Ca, Mg, Fe, Cu, Cr, and Pb were 656.71, 274.74, 79.16, 7.73, 1.55, and 0.41 mg/kg, respectively. The results of the study show that Atella is a nutrient-rich source of essential nutrients, minerals, and energy.
KEY WORDS: Tella, Atella, Physicochemical properties, Proximate analysis, Mineral content
Bull. Chem. Soc. Ethiop. 2024, 38(4), 825-837.                                                         
DOI: https://dx.doi.org/10.4314/bcse.v38i4.1
Synthesis, spectroscopic, biological and structural characterizations for the gold(III), platinum(IV), and Ruthenium(III) ceftriaxone drug complexes
Authors: H. Alosaimi Eid
Published: May 2024

Three new metal complexes of ceftriaxone (cef), incorporating platinum(IV), gold(III), and ruthenium(III), were prepared. The complexes were prepared using a 1:2 molar ratio between ceftriaxone sodium salt (Na2cef) to AuCl3, PtCl4, and RuCl3 salts in methanol solvent. The as-synthesized complexes were characterized using microanalytical techniques for C, H, N, and S elements, magnetic and molar conductance measurements, as well as spectroscopic methods including FTIR, 1H NMR, and UV-Vis. The shape, morphology and size calculations have been examined using SEM, TEM, and X-ray diffraction data. The cef complexes were six-coordinate systems possessing a distorted octahedral geometry. Through the oxygen of both triazine and carboxylate moieties with the chemical formulae [Au(cef)2(Cl)(H2O)] (I), [Pt(cef)2(Cl)2] (II), and [Ru(cef)2(Cl)(H2O)] (III)  the antibiotic cef acts as a bidentate ligand towards three metal ions. The newly created complexes demonstrated antibacterial activity showing efficacy in comparison to the cef sodium ligands. In vitro, antibacterial assays against specific microorganisms were evaluated to assess the antibacterial activities of the complexes. Cytotoxicity assays for cef complexes were conducted for HepG-2 and MCF-7 cell lines, representing human hepatocellular carcinoma and breast cancer, respectively.  A value of 22.4 g and 26.2 g for 50% inhibitory concentration (IC50), respectively, for HepG-2 and MCF-7 were obtained for [Ru(cef)2(Cl)(H2O)] (III).
KEY WORDS: Ceftriaxone sodium, Gold, Ruthenium, Platinum, Complexes, FTIR, IC50
Bull. Chem. Soc. Ethiop. 2024, 38(4), 937-948.                                                      
DOI: https://dx.doi.org/10.4314/bcse.v38i4.10
In silico and in vitro study of pyrimidones synthesized with ethylenediamine- modified β-cyclodextrin: potential against ESBL E. coli
Authors: Rajapriyan Manojkumar , Masood Khan Javed , Khan R. Imran , M. Sajith Ayyiliath , Ali Padusha M. Syed
Published: May 2024

Modern organic synthesis is primarily focused on developing environmentally benign synthetic protocols by employing green chemistry principles. Accordingly, in our recent research work, we herein report the use of modified supramolecular host cyclodextrin as an effective solid based green catalyst for accessing structurally diverse and medicinally relevant pyrimidone architectures. The catalyst and the synthesized compounds 4 (a-r) were characterized using FT-IR, NMR and GC-mass spectroscopy. Major highlights of the reported work include the economical atom process, remarkably gentler reaction conditions, ease of operation, high isolated yields, and excellent catalyst turnover numbers. The molecular docking studies suggest that the compound 4n has hydrogen bonding, hydrophobic and π-pair interactions with the active site of the CXT M 15 receptor. Further, the in-vitro antibacterial study as well as the screening of anti-biofilm activity resulted in a BIC value of 76.79 ± 0.785% at a concentration of 10 µg/mL and morphological alterations induced by DHPMs against the ESBL E. coli strain aggregated with a good result.
KEY WORDS: Ethylenediamine modified β-CD, Multicomponent reaction, 3,4-dihydropyrimidin-2(1H)-ones DHPM derivatives, Solvent-free conditions, Reusability, Antibactercidal
Bull. Chem. Soc. Ethiop. 2024, 38(4), 1103-1118.                                                          
DOI: https://dx.doi.org/10.4314/bcse.v38i4.23