bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrospective Comparison of Age-Related Efficacy and Cost of Sugammadex and Neostigmine in Obese Female Patients Undergoing Elective Surgery
Authors: Alasu Miraç , Alkaya Solmaz Filiz
Published: December 2024

Aim: The purpose of the study is to compare the clinical impact and cost of sugammadex and neostigmine in obese, young-elderly patients.

Materials and Methods: In this study, the medical and anesthesia records of patients whose operation did not exceed 150 minutes and who used rocuronium as a muscle relaxant were evaluated retrospectively. Patients whose files were examined were divided into 4 groups according to age and drug given; Group YS: 2 mg/kg sugammadex between 20–60 years, Group ES: 2 mg/kg sugammadex between 60-80years, Group YN: 0.04 mg/kg neostigmin + 0.01 mg/kg atropine between 20–60 years, Group EN: 0.04 mg/kg neostigmin + 0.01 mg/kg atropine between 60–80 years. Time of TOF 25, 75, 90 recovery scores were recorded from the anesthesia records of the patients.

Results: Regarding the time to reach TOF 25,75,90, it was seen that the patients in Group YS and Group ES reached faster TOF values than Group YN and Group EN ( p<0,05). Compared with neostigmine, patients who were given sugammadex in the same age group were found to have faster recovery time and statistically significant differences (p<0,05).

Conclusion: Sugammadex provides rapid and effective reversal of moderate neuromuscular block compared to neostigmine, with a very low incidence of side effects and faster recovery times.
Bibliometric Analysis of The 40 Years Literature On Vertebral Fractures With Science Mapping Method
Authors: Karaoglu Ahmet
Published: December 2024

Each year, over 1.5 million individuals in the United States are diagnosed with vertebral compression fractures. The concept of bibliometrics pertains to the analysis of bibliographic data. The examination and visualization of the literature within a scientific discipline or its subcategories is referred to as science mapping. This study represents a comprehensive analysis of the literature on vertebral fractures. In our research, the Web of Science database was utilized for analyses, encompassing the period from 1980 to 2022. The analyses were divided into four categories: performance analysis, keyword analysis, thematic analysis, and co-citation network analysis. Word Cloud, Frequency Table, Trend Topics, and Co-occurrence Networks were examined. Thematic Maps and Thematic Evolution Maps were also constructed. Furthermore, a co-citation network analysis of articles was conducted. The analyzed articles were authored by 9,020 researchers. The annual increase in the number of publications was recorded as 9.54%. The average number of citations per document was 44.05. Approximately 18.7% of the articles were published through international collaborations, with Europe standing out prominently in this regard. Genant HK was identified as the author with the highest h- and g-indices. The most active institution was the University of California, San Francisco. The most frequently used keywords included Vertebral Fracture, Osteoporosis, and Bone Mineral Density. Over the past 40 years, the scientific literature on spinal fractures has been analyzed through science mapping. The developmental dynamics of this field have been identified.
Association of Troponin, C-Reactive protein, Albumin and C-Reactive protein/Albumin Ratios with Mortality in Intensive Care Unit Patients with Community-acquired Pneumonia
Authors: Can Nazım Onur , Arslan Şenol , Akpınar Furkan , Doru Halil İbrahim
Published: December 2024

Aim: Parameters used to determine prognosis in community-acquired pneumonia (CAP) patients often have limited clinical value. This study aims to examine the efficacy of CRP, albumin, CRP/albumin ratio and troponin elevation in predicting 30-day mortality in patients hospitalized in the intensive care unit with CAP.

Material and Methods: In this study, 200 patients (85 females and 115 males) older than 18 years of age with a diagnosis of CAP who were followed up in the intensive care unit after emergency department admission between January 1, 2023 and January 1, 2024 were included. Patients who underwent chest radiography and biochemical analyses, including complete blood count, CRP and albumin, within the first 24 hours, were divided into two groups: those who died and those who survived. Troponin, CRP, albumin, and CRP/albumin ratios were compared between the groups about mortality.

Results: The findings obtained in our study were as follows: Troponin, CRP, albumin and CRP/albumin ratio values differed significantly in patients with mortality. When ROC analysis was performed to determine the power of troponin, CRP, albumin and CRP/albumin ratio to predict mortality in the emergency department, it was found that troponin value was the strongest marker in terms of sensitivity with 82.25%. In terms of specificity, low albumin was the most specific parameter, with 82.50% and CRP/albumin ratio followed albumin with 72.50%.

Conclusion: We believe that CRP, albumin, CRP/albumin and troponin are significant predictors of 30 day mortality in patients with CAP hospitalized in the intensive care unit.
Is ChatGPT a Useful Tool for Ophthalmology Practice?
Authors: Yavrum Fuat , Özkoyuncu Dilara
Published: December 2024

Aim: This study aimed to assess ChatGPT-3.5's performance in ophthalmology, comparing its responses to clinical case-based and multiple-choice (MCQ) questions.

Methods: ChatGPT-3.5, an AI model developed by OpenAI, was employed. It responded to 98 case-based questions from "Ophthalmology Review: A Case-Study Approach" and 643 MCQs from "Review Questions in Ophthalmology" book. ChatGPT's answers were compared to the books, and statistical analysis was conducted.

Results: ChatGPT achieved an overall accuracy of 56.1% in case-based questions. Accuracy varied across categories, with the highest in the retina section (69.5%) and the lowest in the trauma section (38.2%). In MCQ, ChatGPT's accuracy was 53.5%, with the weakest in the optics section (32.6%) and the highest in pathology and uveitis (66.7% and 63.0%, respectively). ChatGPT performed better in case-based questions in the retina and pediatric ophthalmology sections than MCQ.

Conclusion: ChatGPT-3.5 exhibits potential as a tool in ophthalmology, particularly in retina and pediatric ophthalmology. Further research is needed to evaluate ChatGPT's clarity and acceptability for open-ended questions.
Bibliometric Analysis of the Joint Diseases and Related Surgery: Part-2: The period after the SCI-E
Authors: Aslan Ahmet , Asan Ahmet
Published: December 2024

Aim: The first part of this article, the pre-SCI-E period, was previously published in Acta Medica Alanya as ‘Bibliometric analysis of the Journal of Joint Diseases and Related Surgery (JDRS). In this article, in the second part of the study, the factors affecting citation and the definition of bibliometric data in the post-SCI-E period were investigated by scanning Google Scholar, Scopus and WOS.

Methods: This second study was designed as retrospective bibliometric. Articles were reviewed beginning from 2007 when the Journal covered by SCI-E, up to 2020 when it covered by PMC. Both authors scanned one by one the articles published in the JDRS Journal within the above stated time period, according to the Turkish-English or English titles and by using the information available on the journal's website for each article. At the end of year 2021 and in a 3 month period all articles were chronologically scanned in Google Scholar, Scopus, and Web of Science databases. All accessed articles were analyzed according to the characteristics and institutions of the authors, also language, type, topic, and discipline of the article.

Results: Scanning for Scopus, Google, and WOS showed that the mean number of citations were 7.69 ± 11.72 for Google Scholar, 5.11 ± 6.88 for Scopus, and 4.36 ± 6.18 for WOS. In the last step of the logistic regression model analysis performed with the backward stepwise method; the article year-volume, male author, foreign author, article subtopic (6), article type (2), article type (1), and article language (1) were found to be variables effective on having a citation. In the linear regression analysis, the male sex variable was found to be significant for citations in all databases. English as the article language was a significant variable in citations, in all databases and subvariables.

Conclusion: The results of this study showed that research articles and/or review articles contribute significantly to citations, and having English as the article language is important. Also, acceptance of articles that may call the attention of more than one specialty may increase the number of citations.
Is bilingualism really an advantage? What about individuals with autism?
Authors: Kara Tayfun , Aslan Ahmet
Published: December 2024

The prevalence of autism spectrum disorder (ASD) is rising globally, making the identification of at-risk groups increasingly important. The proportion of bilingual families has also increased in recent years. There are very few studies examining the relationship between ASD and bilingualism. Although bilingualism is considered an advantage in terms of child development, its consequences in the presence of ASD are unclear. Therefore, there is no consensus among professionals in this field on the subject of bilingualism. Being bilingual is a factor that should not be overlooked during interventions for children with ASD. More research is needed to examine the relationship between being bilingual and ASD longitudinally.
Digitalized Virtual Power Plants to Unlock the Value of Distributed Energy Resources in the Day-Ahead Market
Authors: Mouchaweh Moamar Sayed
Published: December 2024

Digitalized virtual power plants (DVPPs) are advanced software platforms that aggregate and optimally orchestrate a collection of distributed energy resources (DERs) to support grid balance and stability to alleviate stressed transmission and distribution lines and provide critical grid services. DVPPs could reach a total capacity equal to one or several nuclear power plants.
Introduction of Electric Vehicles in Saudi Arabia: Impacts on Oil Consumption, CO2 Emissions, and Electricity Demand
Authors: Javid Muhammad , Almestneer Raed
Published: December 2024

In this study, we project the number of internal combustion engine (ICE) vehicles in Saudi Arabia up to 2050. The projected number of vehicles is then used to project the oil demand and CO2 emissions associated with the road transport sector by 2050. On the basis of the projected number of ICE vehicles, we design three scenarios for developing electric vehicles (EVs) (high-, moderate-, and low-growth scenarios) to determine the impact of the expansion of EVs on future oil demand, CO2emissions, and electricity demand.
Uncertainty in Modeling the Demand for Materials from the Energy Sector at a Country-level: A Case Study of Saudi Arabia
Authors: Laing Timothy
Published: December 2024

The material intensity of the energy transition has been a topic of growing importance in the literature and policymaking over the last decade. Much of this debate has been founded on a range of future demand forecasts of the material requirements of the energy transition, primarily at a global level. However, these forecasts have varied considerably, which has created uncertainty about what materials may be deemed critical, both in terms of future material needs and in securing future supply. In this work, we use a dynamic material flow model to estimate future material requirements at the country level and assess the material demands of the energy transition in Saudi Arabia under different scenarios. We vary the metrics related to demand and its contextualization in terms of supply, along with key underlying assumptions, to highlight crucial design questions future material demand estimation at the country level and areas in which uncertainties may arise.
Impact of Urban Traffic on Fuel Consumption Leveraging IoT Data: Case Study of Riyadh City
Authors: Yaseen Lama , Al-Hosain Nourah , Shatnawi Ibrahem , Muhsen Abdelrahman
Published: December 2024

This study explores the rising trend of traffic congestion in Riyadh and its impact on fuel consumption for passenger cars amid the challenges of rapid urbanization and increasing vehicle use. By utilizing real-time floating car data (FCD) collected by vehicles equipped with Global Positioning System (GPS) technology and communication systems, this study illustrates the potential of the Internet of Things (IoT) and smart city technologies in developing intelligent transportation systems and improving urban mobility management. A spatial analysis of the traffic flow dynamics in Riyadh, focusing on selected primary highways, reveals that driving on high-capacity roads tends to increase fuel consumption. We conducted an analysis at a mesoscopic level, representing traffic congestion in Riyadh on high-capacity roads. It shows that traffic congestion leads to up to a 29% increase in fuel consumption, primarily due to frequent stop-and-go driving behavior, reducing overall fuel efficiency. This study enhances our understanding of urban traffic patterns, providing policymakers with data-driven insights to help them create more sustainable road planning strategies to address the specific needs and challenges of urban mobility in cities.
Navigating the Trade and Climate Change Nexus
Authors: Monkelbaan Joachim
Published: December 2024

As global efforts to address environmental challenges intensify, the
intersection of trade and climate change has become increasingly significant.
On the one hand, trade can facilitate access to clean energy technologies,
foster the global diffusion of sustainable practices, and make production more
material- and energy-efficient. On the other hand, trade brings related risks by
encouraging the growth of carbon-intensive industries in countries with less
stringent environmental regulations, potentially exacerbating global emissions
through increased production and transportation (WTO 2022).
Implementation of file hashing and verification using HMAC-SHA3
Authors: Sikirat Damilola Mustapha  , Bharath Kumar Samanthula
Published: December 2024

Maintaining file integrity is crucial for security and operational dependability in industries like transportation infrastructure that depend on accurate data. This work introduces a File Integrity Management System (FIMS) that provides tamper-evident digital file verification using Hash-based Message Authentication Codes (HMAC) with SHA-3. This system is implemented in Java and consists of two main programs: VerifyHash compares computed and stored hashes to detect unauthorized file changes, and CreateHash produces and stores unique HMAC-SHA3 hashes for files. In high-security settings where undetected file modifications could jeopardize safety, compliance, and trust, FIMS provides a dependable method to confirm file integrity. The system's strong architecture and focus on data security make it highly applicable to sectors that value data authenticity, highlighting the significance of safe file management procedures.
Evaluating alloxan-induced diabetic rats
Authors: Ahamefula Sunday Ezekwe  , Karibo Amakiri Okari  , Peter Gift Wokocha  , Mike Tochi Achor  , Boma Ngo Fubara
Published: December 2024

The increasing incidence of diabetes and the adverse effects of chemical medications underscore the importance of exploring alternative non-pharmacological treatments. Vernonia amygdalina, a widely utilized medicinal herb, shows promising therapeutic potential. This study investigated the impact of aqueous leaf extracts of Vernonia amygdalina on various biochemical parameters in alloxan-induced diabetic rats.
Diabetes was induced in male Wistar rats through intraperitoneal injection of alloxan (150 mg/kg). The rats were then randomly divided into four groups: Group 1 (normal control), Group 2 (diabetic control), Group 3 (diabetic rats treated with Vernonia amygdalina at 80 mg/kg), and Group 4 (diabetic rats treated with glibenclamide at 5 mg/kg). The treatments were administered orally for 28 days.
Results showed that Vernonia amygdalina significantly reduced blood glucose and glycated hemoglobin levels in diabetic rats compared to untreated diabetic controls (P < 0.001). After 28 days of treatment, the extracts also notably improved altered biochemical parameters in diabetic rats versus the untreated controls (P < 0.05). Specifically, Vernonia amygdalina reduced elevated levels of alanine aminotransferase (ALT), aspartate transaminase (AST), and alkaline phosphatase (ALP) (P < 0.05). Additionally, the extract demonstrated hepatoprotective and nephroprotective properties, indicated by reductions in liver enzyme levels and improvements in kidney function markers.
In summary, the aqueous leaf extract of Vernonia amygdalina showed beneficial effects on selected biochemical markers in alloxan-induced diabetic rats, suggesting its potential role in diabetes management.
Effectiveness of a planned teaching programme among the high school students on hazards of plastic use at selected school of Gwalior (M.P.)
Authors: Sangeeta Baghel  , K. Sarojini
Published: January 2025

Humans are vulnerable to the short- and long-term health risks associated with plastics. Being the biggest user of plastic, the packaging industry can't turn a blind eye to the disastrous results of careless plastic consumption. Its hazardous effects and inability to break down in the environment make it a major concern. With the correct kind of early childhood education, we can improve children's health. Various sorts of information can be provided to youngsters in order to alter their lifestyle. Therefore, in order to phase out the use of plastic from daily life and safeguard the health, it is vital to have a planned teaching program that informs high school students about the hazards of plastic use. The area wise knowledge scores of post-tests were highly significant in all areas except regarding the use of plastics. There was no association of knowledge scores and selected variables like class of study, age, sex and religion. The results demonstrated that the proposed educational program was highly successful in raising high school students' awareness of the risks associated with plastic use.
The impact of Artificial Intelligence on medicine: Applications, challenges and perspectives
Authors: Carolina Fátima Gioia Nava  , Daniel Rodrigues Silva Filho  , Jeniffer Aparecida de Morais Rodrigues  , Sergiane Bisinoto Alves  , Pedro Paulo Damasceno Bezerra  , Lucas Cruz Barbosa  , Advisor Murillo de Sousa Pinto
Published: December 2024

Artificial Intelligence (AI) has emerged as a powerful tool in several areas of Medicine, including radiology, pathology, genomics and personalized medicine, providing significant advances in the efficiency and precision of medical care. This study aims to carry out a narrative review of the literature, exploring the potential of AI in clinical practice, both in its current applications and future perspectives. AI is capable of analyzing medical images, interpreting laboratory tests, processing genetic data and predicting disease risks, facilitating a more personalized and preventive approach to Medicine. However, the implementation of AI in the medical field faces important challenges, such as ethical, regulatory and data security issues, which require close collaboration between healthcare professionals, data scientists and regulators to ensure its ethical and effective use. Therefore, the need for continuous research that evaluates and promotes the responsible application of these emerging technologies in the health field is highlighted.
The therapeutic potential of cannabidiol in reducing symptoms of Amiotrophic Lateral Sclerosis: A bibliographic review
Authors: Carolina Fátima Gioia Nava  , Sergiane Bisinoto Alves  , Lucas Cruz Barbosa  , Pedro Henrique Gomes da Silva  , Digilany Aparecida de Souza Lemes  , Advisor Poliana Peres Ghazale
Published: December 2024

Introduction: Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease that results in the gradual loss of muscle control. There is currently no cure for ALS and treatment aims to alleviate symptoms and improve patients' quality of life. In this context, cannabidiol (CBD), a compound found in the cannabis plant, has been studied as a complementary therapy for ALS.
Objectives: This study consists of a literature review that aims to analyze the scientific evidence available on the use of CBD in the treatment of ALS.
Methodology: This is a bibliographic review based on the PubMed, LILACS, SciELO and Google Scholar platforms. The descriptors used were “treatment” AND “cannabidiol” AND “amyotrophic lateral sclerosis”. Studies in Portuguese, Spanish and English were included, from 2000 to 2024.
Results: With progress in neuroscience, cannabidiol emerges as a potential treatment for ALS, presenting anti-inflammatory and neuroprotective effects, in addition to benefits against anxiety and depression.
Conclusion: Therefore, the therapeutic potential of cannabidiol in Amyotrophic Lateral Sclerosis highlights that CBD has promising properties in relieving ALS symptoms and improving patients' quality of life. However, more research is essential to establish it as a standard treatment for ALS, including its interaction with other medications and safety as a therapeutic.
Conflict as a condition for the professional development of teachers and administrative staff
Authors: Dimitra Kostanasiou
Published: December 2024

In educational organizations, numerous employees with diverse personalities, perceptions, and ideologies interact, often leading to disagreements that may escalate into conflicts. An effective leader should not shy away from conflicts but instead, adopt a communication system to manage them for the organization's benefit. Additionally, conflicts can be an opportunity for professional development for both the leader and the educators.
This study deciphers the concept of conflict, its forms, and its sources. It demonstrates that conflicts are not solely negative but can have positive impacts, functioning as a condition for the professional growth of teachers and administrative staff. It also shows how establishing a communication system can contribute to effective conflict management. Lastly, through a case study, the role of leadership in fostering communication for the betterment of educational institutions is highlighted.
Evaluation of chemical quality characteristics of water collected from some groundwater sources in Tabuk City during 2024
Authors: Sameer Abdulmati Masoud Alsaedi
Published: January 2025

The evaluation of water quality for drinking purpose is differed from that of other purposes such as domestic uses, irrigation of for certain laboratory preparations. The aim of this study was to evaluate the chemical parameters of Tabuk groundwater compared to the local standards of drinking water quality. Samples were taken from 12 groundwater sources that are randomly selected to represent Tabuk City. Samples (500 ml) were taken from the main outlet pipe, and it were kept in clean and aseptic plastic containers. The chemical tests were conducted in the Laboratory, Food health and safety, municipality of Tabuk using the standard devices, methods and solutions. The obtained data were compared to the local quality standards of MEWA (2022). The results showed that, pH for all samples agreed with the local standard, as same as in EC, TDS and Hardness with exception of some samples. Also, the concentrations of Bicarbonate and nitrate for all samples did not exceed the upper standard limits, while sulfate and ammonia agreed with local limit of standard with some exceptions. The concentrations of fluoride and lead in all samples were far more below the upper limits, unlike the concentrations of chloride that more than 30-folds exceeded the upper limit in all samples. Lead is still far from its potential critical concentration. Ion most samples, the concentrations of Sodium and Potassium were below the upper standard limits. Moderate concentrations of Mg were recorded for most samples, but all samples contained low concentrations of Fe element far more than the upper required limit. The samples that did not agreed with the local standards should be investigated and the concentrations of Na, K, Mg and Fe should be considered seriously from their physiological requirements to human body.
Advanced geospatial analytics for evapotranspiration dynamics: Integration of Sentinel-1A and FAO Penman-Monteith method
Authors: Selvaprakash Ramalingam
Published: December 2024

Evapotranspiration (ET0) is vital for agriculture and environmental management, facing challenges from climate change. Optical remote sensing overcomes reliance on weather station data. The modeled ET0 using the FAO Penman-Monteith method and Partial Least Squares Regression on Sentinel-1A data with 2016-2017 meteorological archives. Comparative analyses revealed stability in transportation areas within deciduous forests and wetlands, contrasting temporal variations. ET0 was significantly influenced by relative humidity (RH) (70.80% to 89.89%), with temperature (T) playing a crucial role. Urban vegetated areas maintained stable T values (29.37°C), while forests exhibited dynamic T variations (24.24°C to 28.94°C). VH polarization captured diverse climatic influences, resulting in a broader range of dynamic ET0 values (7.38 to 10.76 mm/day) compared to VV polarization (6.74 to 9.34 mm/day). VH sensor performance varied; in October 2016 showed moderate accuracy R2 was 0.50 with slight underestimation Bias -0.08, while exceptional accuracy was seen in December 2017 R2 was 1.00 with positive bias (0.57) and excellent agreement KGE was 0.92. VV sensors in October 2016 had a firm fit R2 was 0.55, with moderate underestimation Bias -0.87, and in December 2017 displayed a good fit the R2 was 0.57, with slight overestimation Bias 0.44, and good agreement KGE 0.44. Integrating machine learning and satellite imagery enhances ET0 accuracy for real-time monitoring in adaptive management, addressing climate change, and showcasing sensor-specific variations. Future research should integrate multi-source synthetic aperture radar satellite data and machine learning for precise ET0 estimation in adaptive environmental management.
Interpretable machine learning approach for early cancer detection
Authors: Babajide Olakunle Afeni  , Peter Adetola Adetunji  , Ibrahim Olakunle Yakub  , Philip Adetayo Adetunji
Published: December 2024

Early cancer detection significantly improves treatment outcomes and patient survival rates. This study explores the efficacy of various machine learning models such as Logistic Regression, Support Vector Machine (SVM), Random Forest, XGBoost, and Neural Network in predicting early-stage cancer. Employing the Local Interpretable Model-agnostic Explanations (LIME) approach, we ensure model transparency and interpretability, which are essential for clinical application. The models were evaluated on a dataset with key features including cancer history, gender, smoking status, age, BMI, genetic risk, alcohol intake, and physical activity. Among the models, Random Forest and XGBoost demonstrated superior performance, achieving the highest balanced accuracy and AUC scores. LIME visualizations revealed that cancer history and gender were the most influential features across all models, with additional contributions from smoking status, age, and BMI. The study highlights the potential of tree-based models for accurate and interpretable cancer detection, providing clinicians with actionable insights. Our findings advocate for the integration of these models into clinical practice, enabling early intervention and personalized treatment strategies. Further research is recommended to validate these models in larger and more diverse populations and to explore the inclusion of additional medical data to enhance predictive accuracy.
MXenes as promising active materials for divalent metal-ion batteries: A review of recent advances
Authors: Yeonjin Baek  , Kiandokht Pakravan  , Francis Mekunye
Published: December 2024

MXenes are a new type of layered-dimensional (2D) materials consisting of transition metal carbides (nitrides and carbonitrides) that have received significant interest due to their intriguing properties. Its superior conductivity, large specific area, tunable chemistry, and layered structure have made it suitable for energy storage ever since its discovery. MXenes have shown great potential, especially in battery applications, including lithium-ion batteries, sodium-ion batteries, Li–S batteries, and zinc-ion batteries serving as excellent rate-performing electrode materials, good electron conductive substrates for active material, components for performance-enhancing composites and current collectors. Perhaps, the most important role MXene plays in electrochemical cells is serving as an active material for charge storage host. This review article discusses recent progress in the synthesis, characterization, and use of MXene as active materials in divalent ion battery applications with the aim of enhancing electrochemical performance. This review will also discuss the several charge storage mechanisms and performance enhancement of pure MXene or MXene-based composites in these battery systems. Lastly, the challenges and future prospects are summarized, offering an outlook on potential opportunities ahead for tailoring MXene as better active materials through tailoring microstructure.
Fraud detection in healthcare billing and claims
Authors: Tashin Azad  , Paul William
Published: December 2024

Healthcare fraud in billing and claims is a pervasive issue, costing the United States healthcare system billions of dollars annually. This paper provides a comprehensive exploration of how advanced technologies such as data analytics, machine learning, and anomaly detection can effectively combat fraudulent practices, including upcoding, phantom billing, and duplicate claims. By leveraging healthcare claims data, predictive models are developed to detect suspicious patterns in real time, assign risk scores to providers, and flag high-risk claims for further investigation. This approach enhances fraud detection accuracy, minimizes false positives, and enables efficient resource allocation for fraud mitigation. The proposed solutions include AI-powered fraud detection tools, automated alert systems, and continuous model training to adapt to evolving fraud tactics. These tools, when integrated into the claims processing workflow, facilitate proactive fraud prevention by identifying anomalies and streamlining investigation processes. Operational measures such as provider risk scoring and robust data-sharing frameworks complement these technical innovations, creating a multi-layered defense strategy. Additionally, the paper emphasizes the importance of policy initiatives, including enhanced staff training and inter-organizational collaboration, to foster a culture of vigilance and compliance. By combining cutting-edge technology with sound operational practices, this research aims to significantly reduce healthcare fraud, enhance system efficiency, and rebuild trust within the healthcare industry. The insights and recommendations presented in this study have broad implications for policymakers, healthcare providers, and insurers seeking to implement cost-effective and scalable fraud prevention strategies.
Enhancing accessibility and assistance through eye gaze tracking: The I alert approach
Authors: Poornima M  , Paramesha R  , Rohith M N
Published: January 2025

The growing demand for assistive technologies for individuals with physical disabilities has led to significant advancements in human-computer interaction (HCI). Eye gaze tracking, a promising input modality, offers a non-invasive and intuitive way to enhance accessibility and interaction. This paper presents iAlert, an innovative eye gaze-based alert system designed to provide timely assistance to individuals with limited mobility or communication abilities. By analyzing eye movements, iAlert aims to detect user intent and trigger appropriate responses, thereby facilitating improved interaction with the environment, enhancing safety, and offering real-time assistance in everyday tasks. This system holds great potential for improving the quality of life for individuals with physical impairments, elderly individuals, and others requiring assistive technologies.
The proposed methodology integrates eye gaze tracking with machine learning algorithms to build an intelligent alert system. Eye gaze data is captured using specialized hardware such as infrared sensors or cameras, which track the position and movement of the eyes. These gaze patterns are then pre-processed to remove noise and identify key features, such as fixations, saccades, and gaze direction. Machine learning models, specifically Convolutional Neural Networks (CNNs), are employed to classify the gaze data and predict user intent, allowing for real-time decision-making. A Support Vector Machine (SVM) classifier is used for detecting specific gestures or commands, such as a blink or a prolonged gaze, which are mapped to particular actions (e.g., triggering an alert, controlling a device, or communicating a need). The system adapts to user-specific behaviors over time through continuous learning, ensuring personalized assistance.
The expected results from the iAlert system are twofold: first, a high level of accuracy in detecting and responding to user gaze commands, and second, an enhanced user experience in terms of real-time responsiveness and adaptability. The system is expected to achieve over 90% accuracy in identifying user intent, especially in controlled environments. The integration of machine learning algorithms like CNNs and SVM is critical for ensuring robust classification of eye gaze data, reducing the error rate in real-time applications. Moreover, the machine learning approach allows the system to continuously improve through adaptive learning, providing more accurate and personalized responses over time. The importance of using these algorithms lies in their ability to handle complex, non-linear relationships within gaze data, enabling the system to function effectively across different users and contexts. By leveraging deep learning techniques, the iAlert system can scale for a wide range of assistive applications, making it a valuable tool for enhancing independence and accessibility for individuals with physical challenges
Characteristic of psoriatic arthritis patient with disease activity based on DAPSA score: A literature review
Authors: Azlia Kusuma Cahyani  , Lita Diah Rahmawati  , Yulia Nadar Indrasari  , Novira Widajanti
Published: December 2024

Psoriatic arthritis (PsA) is a chronic inflammation that affects peripheral and axial joints. The prevalence of PsA tends to increase in recent years. As many as 0.1 - 0.2% of the general population suffer from PsA. A study stated that out of 1,442,357 people with PsA, 21,825 deaths occurred. This mortality rate may continue to increase over time. PsA is most common in individuals aged 40 to 50 years with the incidence of PsA in men and women being almost equal. PsA cannot be underestimated and needs proper diagnosis and assessment of disease activity for good management. Early diagnosis is very important in PsA. The diagnosis of PsA can be made based on the Classification Criteria for Psoriatic Arthritis (CASPAR). Assessment of disease activity is essential in the management of PsA. Based on several studies, the most widely and easily used PsA disease activity assessment instrument is Disease Activity in Psoriatic Arthritis (DAPSA) score. Literature reviews on psoriatic arthritis patient with disease activity are still limited. Therefore, researchers are interested in conducting research on the characteristic of psoriatic arthritis patient with disease activity based on DAPSA score. However, further research is needed with more comprehensive variables to explore the characteristic and disease activity of psoriatic arthritis.
Biotechnology and artificial intelligence integration: A concise review of advanced application, advantages and challenges in healthcare
Authors: Meenakshi Devi Mudunuri  , Nagaraju Yalampati  , Akshay Kumar Voosala  , V. R. S. L. Asritha Kukunuri  , Sirisha Kudulla  , Y. B. Manju Latha  , V. Bhaskara Raju
Published: December 2024

Everyone is talking about artificial intelligence (AI) these days. Unprecedented new potential solutions are made possible when biotechnology and artificial intelligence breakthroughs are coupled. This can support significant Sustainable Development Goals and assist with a number of global issues. Food security, health and well-being sustainable energy, conscientious production and consumption, climate action, and life below water, safeguarding, restoring, and promoting the environmentally friendly forest management and the sustainable utilization of terrestrial ecosystems, preventing desertification, stopping and going backwards degradation, and stopping biodiversity loss are a few instances that are presently in the news. The biological sciences are now heavily reliant on artificial intelligence. Recent advances in artificial intelligence (AI) and biotechnology have brought about a convergence that could completely transform the healthcare industry. This review investigates the benefits and challenges of biotechnology in the healthcare industry by providing up-to-date case studies on its applications.
The differences in surface roughness and hardness of glass ionomers cement coated with vaseline and cocoa butter after immersion in UHT milk
Authors: Tsania Walida Salma  , Ilyas Yakob Nurul Nugraha  , Asti Meizarini  , Priyawan Rachmadi  , Intan Nirwana
Published: December 2024

Background: Dental caries affects 513.8 million children globally, and glass ionomer cement (GIC) is a common treatment due to its fluoride release. However, GIC is moisture-sensitive and prone to solubility during maturation. UHT milk, often consumed by children, disrupts ionic bonds on GIC surfaces affecting roughness and hardness. Increased surface roughness leads to plaque accumulation, while decreased surface hardness ensures compressive strength and abrasion resistance. Coating agents like vaseline and cocoa butter help preserve GIC properties by maintaining roughness and hardness.
Purpose: To analyze differences in surface roughness and hardness values of GIC treated with vaseline, cocoa butter, and without coating after being immersed in UHT milk for 7 days.
Methods: The experimental study used a post-test control group design with three groups of six specimens each, immersed in UHT milk for seven days. Groups included GIC without coating, coated with vaseline, and cocoa butter. The test results were then measured using a surface roughness tester and Vickers hardness tester and analyzed using the ANOVA.
Results: GIC coating with vaseline has the lowest value of surface roughness and highest surface hardness, followed by GIC coating with cocoa butter and without coating. However, the three groups did not have significant differences in statistical data analysis.
Conclusion: There is no difference in the surface roughness and hardness values of GIC without coating, coated with vaseline, or cocoa butter after being immersed in UHT milk for 7 days.
Study of the methanogenic potential of urban waste from the city of N’Djamena for recovery into biogas
Authors: Haroun Ali Adannou  , Dingammadji Richard  , Soukibe Kagonbe Voltaire  , N'Gueassembaye N'Gambainan  , Nguemadjita Christophe  , Aboubakar Chedikh Beye
Published: December 2024

The different types of urban waste as well as household waste are generally disposed of in open landfills affecting environmental sustainability. These wastes, by the release of contaminants such as leachates and greenhouse gases, increase the pollution potential of the sites. We recovered a quantity to carry out our experiments. The recovery of waste into biogas inevitably takes place in hermetically sealed enclosures called biodigesters. In this work we highlighted several types of waste at room temperature in a 0.75l can equipped with an empty inflatable balloon used for the recovery of biogas, which constituted our biodigester. Then a second experiment was carried out on the mesophilic temperature and the results were compared. The aim is to see the waste with the best biogas potential in terms of quality and quantity of production. The experiment consisted of working at an ambient temperature around 35°C±2 °C and up to 45 °C (mesophilic temperature). For this experiment we found that some bio-digesters started producing after two hours of time, the inflatable balloon increased in volume every hour up to 24 hours before and remained constant. We used the resources in terms of substrate and equipment of the Afric-Lab laboratory and that of the Physics-Chemistry department of the Higher Normal School of N'Djamena.
The influence of dietary and lifestyle factors on GERD-related dental erosion: A literature review
Authors: Miftachul Khoirunnisa Lestari  , Silvi Aurulia Aidatul Fitri  , Mirza Khairina  , Zilzala Irqon Ambiya
Published: December 2024

Background: Gastroesophageal reflux disease (GERD) is a chronic gastrointestinal disorder commonly associated with dental erosion. GERD-related dental erosion is influenced by various factors, including dietary habits and lifestyle choices.
Purpose: This article aims to review the influence of dietary and lifestyle factors on GERD-related dental erosion based on a literature review.
Methods: This study employed a literature review methodology, analyzing articles published between 2019 and 2024. Data sources were obtained from databases such as PubMed, Google Scholar, ScienceDirect, and Elsevier. A total of 8 articles met the inclusion criteria and were analyzed further.
Results: Studies indicate that the consumption of acidic foods and beverages, such as citrus fruits and carbonated drinks, exacerbates dental erosion in GERD patients. Lifestyle factors, such as late-night eating and caffeine consumption, were also found to increase the risk of dental erosion. Conversely, the consumption of milk was associated with a reduction in the severity of erosion. GERD also affects the salivary profile, including lowering the pH and buffering capacity of saliva, thereby increasing the risk of enamel demineralization.
Conclusion: Dietary and lifestyle factors play a significant role in increasing the risk of GERD-related dental erosion. A holistic management approach, including dietary modifications, lifestyle changes, and regular dental health monitoring, is necessary to reduce the impact of GERD on dental health.
Methodology for performance assessment of industrial robots
Authors: Daouda CAMARA  , Fadaba DANIOKO  , Bourama COULIBALY  , Mamadou DANSOKO
Published: December 2024

The study of industrial robots is particularly interesting in view of the many advantages that these robots offer in the production line. This paper aims to study manipulator arms in order to better understand the performance of manipulator arms. The recurring issue for the manipulator arms remains the analysis of their operating path patterns in a well-defined working space. We propose a methodology based, on the one hand, on the definition of the functional specifications of manipulator arms necessary for design and on the other hand, on the geometric modelling and control of these manipulator arms in Matlab/Simulink. The model thus constructed is capable of reproducing different trajectory configurations depending on the joint variables in a well-defined working space. The results of our model are consistent with those provided by the mathematical model using the Denavit-Hartenberg convention. According to two scenarios, the analysis of the trajectories of the manipulator arms’s end effector is carried out and especially on the SCARA, cartesian and spherical robots. This analysis generally reveals elliptic trajectories or lines described by the end effector of robots in relation to the plane linked to their base.
Effects of lead exposure on the lung volume of automobile battery workers in Anambra State
Authors: Chukwudi Joseph Anumudu  , John-Gideon Nwadialor  , Ogochukwu Fidelis Okoye  , Chika Elvis Onyeugo  , Ngozi C Chuka-Onwuokwu Okpala  , Kalu O Obasi  , Ifeyinwa Nkiruka Nwafia  , Chukwuma Walter Nwafia
Published: December 2024

Exposure to a heavy metal such as lead may induce various respiratory symptoms. Even though automobile battery recycling, repairs and lead smelting are common in Anambra State, there is no study on the effects of lead exposure on lung volumes of automobile battery workers in Anambra State of Nigeria. Hence, the need to carry out this research. The aim of this study was to evaluate the effect of lead exposure on the lung volumes of automobile battery workers in Anambra State. Respiratory symptoms were evaluated in a sample of two hundred respondents consisting of one hundred lead exposed workers and one hundred control subjects with similar ages using a pre-tested questionnaire. Height of the participants were measured using meter rule. Pulmonary function tests (PFT) were measured in the test group and in control group using a spirometer. Criterion for statistical significance was p ≤ 0.05. The result of this study showed a decrease in the mean value of peak expiratory flow (PEFR) in the test sgroup (297.74±81.29L/min) compared to control group (379.93±86.57L/min). This decrease was significant (p = 0.000). The results of this study showed that exposure to lead has significant effects on the lung volumes of automobile battery workers in Anambra State. The result of the study revealed that there was a significant positive correlation between height and forced expiratory volume in one second in the test group. Lead exposure may be responsible for respiratory symptoms in automobile battery workers.
Assessment of risk of dental caries among middle school children based on carbohydrate intake in Pune: Cross-sectional study
Authors: Zahir shaikh  , Rumaan Momin  , Neetu kadu  , Shagufta Shaheen
Published: December 2024

Introduction: This study aimed to evaluate the relationship between carbohydrate intake and the risk of dental caries among middle school children aged 11-15 years in Pune, Maharashtra, India.
Objective: Dental caries is a prevalent oral disease, particularly in this age group, as most permanent teeth have erupted, making them vulnerable to decay if proper oral hygiene and dietary habits are not maintained.
Methodology: A cross-sectional study was conducted among 197 students from various schools in Pune. Data were collected through questionnaires and clinical examinations done through DMFT & DMFS index, focusing on dietary habits, brushing frequency, and oral hygiene practices.
Result: The result of the study shows that there is a significant differences in oral hygiene practices based on intake of carbohydrate, with notable correlation between high carbohydrate intake and increased DMFT and DMFS scores. Specifically, children consuming >20% carbohydrates exhibited significantly higher mean DMFT (3.57 + 3.64) and DMFS mean scores (8.71 + 11.41) compared to those with lower carbohydrate intake <20% had low DMFT mean (1.98+1.57) and DMFS mean (3.07+2.99)
Conclusion: The study shows that Children consuming more carbohydrates diet showed more dental caries compared to those with less carbohydrate intake