bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Proposed Intelligent Systems with Existing Models for Monitoring Heart Diseases
Authors: Janpreet Singh
Published: February 2025

These days, people are preoccupied with their everyday tasks, paying close attention to their work and other obligations while putting their health on the back burner. A growing number of individuals fall ill every day as a result of their hectic lifestyle and disrespect for their health. Hence, the majority of the population across the world affects by heart disease. Heart disease is one of the major causes of death globally, and early detection and monitoring are critical for effective treatment. Moreover, the use of machine learning is increasing quickly all around the world, particularly in the healthcare industry. Therefore, intelligent models can be developed or introduced by using machine learning approaches that predict the health of a patient’s heart from its risk factors. This paper presents a comparative study in which models are proposed using fuzzy logic and hybrid system and also their performances are compared with each other as well as existing models. The comparison is made by considering the classification accuracy of each model. The model which has the highest percentage of accuracy is considered as the most accurate model for the monitoring of heart disease. According to the results, it is found that the neuro fuzzy methodology assists in implementing an intelligent model which has 98.90 percent accuracy of a classification and also outperforms other existing models.
A Deep Learning Approach for Android Malware Detection Using Mixed Bytecode Images and Attention-Based ResNet
Authors: S. Girirajan
Published: February 2025

In an era, where apps are on the rise and taking over almost everything we do on our devices, detecting Android malware becomes of utmost importance. This work proposes a deep learning framework that can overcome those constraints in signature-based detection while against new and ever evolving flavors of malware. This technique consists in converting an Android application bytecode, into set of images which represent dynamic (behaviour and structure) features the program. It is these images that will be are basis for applying complex image classification methods effectively to detect malware. At the heart of this framework is an attention-amplified ResNet, one of the revolutionary convolutional neural network structures that can be used for image recognition. The introduction of the attention mechanism permits the model to pay more (less) attention on certain portions in the corresponding bytecode images, which helps boost its capacity for distinguishing benign and malicious applications with higher focus weights. The approach increases the generalization properties of a model to varying malware families and improves its adversarial robustness for withstanding new evasion strategies by using bytecode images that are mixed, i.e., original as well as augmented versions. Experiments on a large dataset of Android applications show that inaccuracy, precision and recall performed jointly polished than current models dosing malware detection. It turns out that the attention mechanism plays an important role for improving detection performance, especially on heavily obfuscated malware. Furthermore, the application of mixed bytecode images reduces false positives and increases accuracy to a level where such models can be deployed in practice. Our work provides support for the use of image-based analysis and deep learning in Android malware detection. This attention-based ResNet model will allow us to develop new, more complex security solutions that are better suited for today's ever-changing mobile threat environment.
Detection and Classification of Eye Disease using Deep Learning Algorithms
Authors: Amol Laxman Deokate
Published: February 2025

The early detection and management of multiple diseases are critical for improving patient outcomes, particularly in healthcare fields like ophthalmology. This paper proposes a novel approach to the prediction and classification of multiple diseases using ocular images, with an emphasis on determining the severity of these conditions. With the advancement of artificial intelligence (AI) and machine learning (ML), the integration of deep learning models has shown promising results in analyzing medical images for various disease detection tasks. The proposed methodology involves the use of ocular images, such as fundus images, OCT scans, and retinal photographs, to detect and classify a range of ocular diseases like diabetic retinopathy, glaucoma, age-related macular degeneration, and cataracts. By leveraging convolutional neural networks (CNNs) and other advanced machine learning algorithms, the system is trained on a large dataset of labeled ocular images. The model learns to identify key features in the images that are indicative of different diseases. Beyond classification, the system also incorporates severity analysis by assessing the degree of damage or progression of each condition. This is achieved by utilizing image segmentation techniques and quantitative measures such as lesion size, shape, and location, which are critical for evaluating the severity of the disease. The final output provides both the diagnosis and a severity score, enabling clinicians to prioritize treatment and interventions. The proposed system not only aims to assist ophthalmologists in routine screenings but also strives to improve accessibility to healthcare by enabling remote disease detection. By utilizing ocular images as a non-invasive diagnostic tool, this approach promises to enhance the efficiency and accuracy of multi-disease diagnosis, potentially leading to better patient care and outcomes in ophthalmology and beyond.
Spectral Clustering-Based Particle Swarm Optimization Algorithm for Document Clustering
Authors: T. Elavarasi
Published: February 2025

The process of automatically grouping documents into clusters such that the documents in one cluster are very comparable to the documents in the remaining clusters have been known as document clustering. Due to its broad application in a number of fields, including search engines, web mining, and information retrieval, it has been the subject of much research. It involves clustering documents that are identical to one another and calculating how identical they are. It facilitates simple navigation by offering effective document representation as well as visualization. Hence, this research paper plans to perform the document clustering using the nature inspired optimization technique. Initially, the dataset is manually gathered from different sources. Next, the data preparation has been done for extracting the text content from the published documents. These prepared data undergo pre-processing for removing the punctuations, stop words, and lowercase conversion. The features are extracted from these pre-processed data utilizing the Term Frequency-Inverse Document Frequency (TF-IDF) approach for extracting the keywords. The extracted features undergo the final clustering phase employing the spectral clustering algorithm, in which the parameter tuning has been done by the nature inspired optimization algorithm referred as Particle Swarm Optimization (PSO) with the consideration of silhouette score maximization as the objective function. This proposed spectral clustering-PSO clusters the final output into six classes such as data mining, deep learning, image, machine learning, network, and sports respectively. The proposed document clustering model describes its betterment over the remaining techniques with respect to distinct measures. The proposed spectral clustering-PSO in terms of silhouette score is 51.92%, 70.81%, 45.93%, and 20.89% better than JA-GWO, tpLDA, HDMA, and Net2Vec respectively. Similarly, the proposed spectral clustering-PSO in terms of davies bouldin score is 89.69%, 58.48%, 32.67%, and 13.99% advanced than JA-GWO, tpLDA, HDMA, and Net2Vec respectively.
A New Method to Find the Balanced Solution to the Transportation Problem with Fuzzy Sets of Type-2 for Supply and Demand
Authors: Barraq Subhi Kaml
Published: February 2025

The Transportation Problem is a fundamental problem widely studied in the Operational Research domain. The main objective of this paper is to contribute to a deeper study of the topics of fuzzy transportation problems of linear programming when the supply and demand are represented as a fuzzy set of type-2. Here, we are using a newly proposed method to solve a transportation problem with fuzzy sets type-2 of supply and demand to find a balanced solution. The membership function of a fuzzy set of type-2, which is the set of its feasible solutions, is constructed. The properties of this set are investigated, and the problems of choosing balanced solutions are considered. The newly proposed method of the fuzzy transportation problem is discussed with the help of an illustrative numerical example.
Exploring the Black Box of Relationship Between Place Attachment and Residential Renewable Energy Technologies - A Systematic Literature Review
Authors: Zhu Yijun
Published: February 2025

Introduction: Place attachment enables people to embrace sustainability discourses and deal with social change and action on renewable energy technologies, often deployed strategically for environmentally friendly consumption behaviors. Despite the growing number of studies examining the influence of place attachment of pro-environmental behaviors and renewable energy technologies, limited studies have explored the effectiveness of place attachment in influencing social acceptance and purchase intention of household renewable energy technologies through a literature synthesis. Thus, there has been no systematic consolidation of the research in place attachment to identify the effectiveness of place attachment established for their role in determining the social acceptance and purchase intention of renewable energy technologies to provide a detailed understanding of how it has evolved over the years to the researcher’s knowledge.
Objectives: This study aims to conduct a structured review and bridge the gap by examining the evolution of effectiveness of place attachment of renewable energy technologies in the last twenty years and offer further promising directions for future research by bibliometric analysis.
Methods: Based on the PRISMA four-stage identification, screening, eligibility, and study inclusion technique, this study explored the usefulness of bibliometric analysis for the analysis of 68 articles.
Results: Through bibliometric analysis, the leading authors, outlets, countries/regions, and articles of healthy aging research were visualized over 15 years (2010-2024). It provides a comprehensive overview of the effectiveness of place attachment in renewable energy technology research, demonstrates intellectual advances in the field, and detects promising research directions in the future.
Conclusions: The findings of the study identify influential authors, articles, and journals over 15 years (2010-2024), illustrate the intellectual structure of the literature, and better understanding the important of place attachment on renewable energy technology which provide an opportunity to improve energy promotion and transformation around the world to reduce carbon emissions.
Revolutionising Essay Writing Using Artificial Intelligence
Authors: Shirley Ling Jen
Published: February 2025

Introduction: With the emergence of Artificial Intelligence (AI), there is a need to integrate the latest technological tools such as generative AI in teaching essay writing. Thus, this study was carried out to examine the usefulness of Gemini AI in assisting students’ essay writing.
Objectives: The Research Objectives (RO) for this study are to examine: 

secondary school students’ Perceived Usefulness (PU) of Gemini
secondary school students’ Perceived Ease of Use (PEOU) of Gemini

Methods: The Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) of Gemini AI were analysed qualitatively through journal entries, participant observation, questionnaires and interviews.
Results: The findings show that students showed favourable responses towards the use of Gemini AI in assisting them in their essay writing. This is because Gemini AI does not only help students with generalisation of ideas and gaining new vocabulary, it also provides flexibility for them to learn at their own pace.
Conclusion: Hopefully, this study will bring useful insights to practitioners and researchers in using AI to teach essay writing to students.
Application of Soil Erosion Estimation using NRCS-CN Method for Dillai Watershed in Karbi Anglong District, Assam
Authors: Mindar Rongphar
Published: February 2025

Watershed degradation is thus a major environmental problem that impacts on agricultural yields and productivity, quality of water possessions, and stability of ecologies. The purpose of this research is to quantify the soil erosion rate in the Dillai watershed within the Karbi Anglong district of Assam using NRCS-CN technique. The NRCS-CN technique which is accepted as most effective and accurate choice is used to assess the runoff capability and the concomitant soil erosion.Geographic Information System (GIS) as well as remote detecting data are used simultaneously for delimiting of the watershed, valuation of the LULC, types of soil and hydrogeological prospect of the region. These are then used to estimate the curve number for the diverse hydrological soil groups as well as land use and land cover combinations. Runoff and rate of soil destruction are estimated by using rainwater data along with CN values.Information from the initial assessment indicates that areas within the watershed are differently exposed to soil erosion based on the topographical characteristics namely; slope, vegetation cover and rainfall intensity. The results give a useful estimation of spatial distribution of soil erosion risks and point out areas that are most important to conserve.Thus, this investigation demonstrates how the NRCS-CN method can be applied for estimation of soil erosion on mountainous regions and provides scientific justification for the reasons in which appropriate soil and water conservation measures needs be applied. It is hoped that the findings will be useful in helping the relevant authorities, policy makers, environmentalist and local government in preventing further cases of soil erosion and in effectively managing the watersheds identified in the Dillai area.
Analysis of Queuing Model having Multiple Servers with Environment Effects and with Retention of Impatient Consumers
Authors: Natasha
Published: February 2025

Through this paper, an innumerable definite latent alike queuing model with clients’ restiveness and the action of absorbing of annoyed clients in two different environments is analyzed. The findings of the model in stable position are attained by Matrix Approach.
EPI-PRED: Leveraging CNN and Bi-LSTM Models for Accurate Prediction of Enhancer-Promoter Interactions
Authors: G.Aruna Arumugam
Published: February 2025

The identification of Enhancers-promoter interactions (EPI’s) will assist in understanding the genetic regulation mechanisms. EPIs are determined through time-consuming and laborious testing techniques.  Several methods are being contributed to deal with this issue. Due to their promising ability to predict, DL-based techniques have been extensively employed in the genome-scale detection of EPIs recently. This study is to employ the  CNN and BiLSTM model named as “EPI-PRED”  in predicting the EPI’s with a set of features trained using the DL models in a python platform and it is successful predicted and  evaluated with the SEPT, EPI-Trans and TF-EPI models using sensitivity, Specificity , precision and accuracy . It outperforms the other state of art DL methods and offers a new avenues in medical research.
MindIntent: A Chatbot Using SVM for Identifying Mental Health Intervention Intentions
Authors: Varsha Jadhav
Published: February 2025

Mental health issues are increasingly acknowledged as vital, yet traditional support systems have limitations in availability, cost, and accessibility. Chatbots provide a scalable solution for real-time support, but their usefulness is dependent on correctly understanding user input. This work uses a Support Vector Machine (SVM) to improve chatbot performance in mental health applications by effectively dealing with high-dimensional data and discriminating between emotional states and intents. We created a chatbot by gathering and annotating text data, preprocessing it, and extracting features with tools like TF-IDF and word embeddings. The SVM model was trained on this data and implemented into the chatbot, allowing for real-time classification of user inputs and contextually relevant responses. Our results show that the SVM-powered chatbot excels at accurately categorizing users.
Federated Learning Based Model for Recommendation System Based in Health Care
Authors: Gaurav Goel
Published: February 2025

Precision Medicine is an emerging healthcare approach that focuses on tailoring treatments for individual patients. The implementation of patient-centred Decision Support Systems, including Health Recommender Systems, is a key component of this initiative, aimed at augmenting the accuracy and individualization of healthcare delivery. However, a significant challenge in developing these systems is the confidential nature of the medical data, as these systems require large volumes of data to function effectively. Unfortunately, medical data are distributed across multiple institutions and cannot be centralized due to privacy concerns. To overcome this challenge, this position paper presents an architecture that uses Federated Learning to build a HRS (Health Recommender System). Federated Learning enables the use of data from different institutions without requiring direct data sharing. To demonstrate the feasibility of this approach, we developed a Federated Drug Recommendation System designed to assist physicians in prescribing medications by utilizing historical data on disease-drug interactions and pharmaceutical information. As this is a position paper, we focus on presenting a proof-of-concept utilizing publicly available, non-sensitive datasets.
Optimizing Football World Cup Logistics and Operations with Information Systems
Authors: Abdulnaser S. H. Al-MSloum
Published: February 2025

Logistics and operations for such a big event like the Football World Cup need to be well-established and efficient. This article provides an account of the application of advanced information systems in managing and enhancing the flow of logistics and other operations during such events in general and logistics in particular. This paper, therefore, discusses how integrated solutions can be adopted by analysing a case of practice of these systems in Saudi Arabia. The modern applications of the tracking systems in real-time are based on two major technologies namely Geographic Information Systems (GIS) and the Internet of Things (IoT) to monitor and control the flow of vehicles and to decrease traffic jams when managing vehicle fleets. This is also useful for the current study is the application of predictive analytics in demand forecasting, resource availability, and transportation scheduling. Further, automation of business processes helps in stock control and timely delivery of products and services without stagnation. Blockchain technology is examined for the purpose of increasing information transparency in the supply chain, data accuracy and effective interaction between the participants. The case also shows the use of cloud-based solutions to support communication and collaboration between logistics teams to increase the flexibility of processes. This article compares how the increasing digital landscape of Saudi Arabia can act as a standard in terms of logistics for huge sporting events around the world, with an emphasis on the function of activities like logistics and operations management for the success of an occasion.
The Role of Cash Flow Statement in Reducing Liquidity Risks in a Number of Iraqi Commercial Banks
Authors: Karam Amer Khalil Al-Alaf
Published: February 2025

The current research aims to reveal the role of cash flow disclosure in reducing liquidity risks in a number of Iraqi commercial banks, as the research problem crystallized in identifying the appropriate financial indicators to measure and evaluate the bank liquidity ratio, which is an essential part of the research problem that stems from the lack of clear prior planning and a sound strategy that serves commercial banks, and to achieve what it aims for, the research adopted the (descriptive analytical) approach in presenting the intellectual frameworks, and processing the financial data of the banks in the study sample, which number (25) Iraqi commercial banks, so that the research reached a set of results, the most important of which is the existence of a close relationship between the quality of cash flow management and the level of banks' exposure to liquidity risks. Banks that are characterized by good management of their cash flows are able to face market fluctuations with higher efficiency.
Investigating the Factors Influencing Customer Purchase Decisions Driven by Social Media -The Study of Punjab
Authors: Varun Dua
Published: February 2025

This study looks at the effect of social media on internet shopping choices in Punjab, India, breaking down information from 500 respondents across five significant urban areas. Utilizing Levene's Test and MANOVA investigation, the examination uncovers huge relationships between online entertainment commitment and buying conduct. Findings demonstrate that item audits (73%), direct brand correspondence (75%), and special substance (75%) unequivocally impact buyer choices. Segment factors, especially pay levels and age gatherings, show eminent varieties in virtual entertainment driven buying designs.
A Flipped Classroom Approach as an Educational Tool for Economics Instruction
Authors: Charisma G. Lumayag
Published: February 2025

The traditional classroom strategy has evolved as a technological advancement that has been introduced into the academic learning environment nowadays. Through different improvement with the classroom arrangement and among other advances, the traditional classroom has shifted into flipped classrooms and geared its focus toward the students themselves in order to facilitate independent learning skills. To look into the effect of using flipped classroom model in teaching the Economics subject among undergraduate students, this paper sought to investigate this issue in a state university situated in the Philippines.  It has been observed and the results showed that proves that flipped classroom model improved the performance of students in learning Economics. Also, it was revealed in the study that there is a significant different between the performance of the students without or with flipped classroom strategy. Therefore, such a methodology of learning can be further designed as an educational tool for a better delivery of the instruction in Economics.
Sentiment Analysis of Educators and Learners on Google Classroom as an Online Learning Environment
Authors: Fernan H. Mendoza
Published: February 2025

Ideas surrounding online learning are rapidly evolving due to ongoing technological advancements that support innovative approaches. The widespread availability of information and communication technology (ICT), an expanded toolkit, and its integration into daily life, particularly within the academic domain, have become increasingly inevitable, particularly taking into account the COVID-19 epidemic. This study engages in a discussion about the utilization of Google Classroom as an online learning tool. By conducting sentiment analysis on the online learning experiences of educators and students, academic institutions can gain valuable insights into their students' needs, assess the effectiveness of current instructional methods, and foster meaningful learning experiences. Data were collected from 31 faculty members and 533 students at the Don Mariano Marcos Memorial State University-South La Union Campus. All participants were invited to partake in an online survey to share their experiences and potential challenges encountered during synchronous online instruction using Google Classroom. This research utilizes a mixed-method approach, integrating quantitative and qualitative approaches alongside machine learning applications. The findings suggest that both students and faculty members found the Google Classroom platform to be a valuable tool, motivating further exploration of optimal learning environments for blended learning.
First observations of filamentous cyanobacterial mats on whip black corals (Antipatharia: Stichopathes spp.) off Rapa Nui (Easter Island), Chile
Authors: Tapia-Guerra Jan M , Sellanes Javier , Gorny Matthias , Easton Erin E
Published: February 2025

This report documents the first occurrence of filamentous mats affecting whip-corals in mesophotic ecosystems on Rapa Nui. Observations in 2018 revealed mats covering coral branches at 113-131 m. Recent campaigns in 2022 and 2024 confirmed that the mats remain confined to Rapa Nui, with nearby seamount corals undisturbed since 2016.
Study of sleep problems and chronic pain. Comparative analysis between patients attending specialized services versus primary care
Authors: Martínez García Antonio Javier , Peiró Peiró Ana María , Ballester Navarro Purificación
Published: February 2025

Pain occupies a consultations in health services around the world, 20% in Spain. Half of these patients have sleep problems. It is important to evaluate how sleep is affected by pain intensity, comorbidities and treatment in patients in specialized services such as the Pain Unit (UDO), and the Pharmacy Office (OF) where they come from various specialties. Patients with and without complaints about their sleep were surveyed. All patients answered a questionnaire that covered clinical aspects (pain intensity), comorbidities that affected sleep (HAD- anxiety and depression), and sleep (Pittsburgh and MOS-S tests). RESULTS: 192 patients with pain were recruited (UDO=137, OF=55), aged between 46 and 77 years, all of them with pain intensity that ranged between 5.2/10 in the OF, and 6.9/10 in the UDO. High anxiety values ​​were found in the group of OF patients, as in those from the UDO, as well as high depression values ​​in a subgroup of the UDO patients. The sleep values ​​of the MOS-S tests were found to be especially altered (mainly shortness of breath and high drowsiness), and the Pittsburgh result gave a total value that indicated the need for medical control. Pain is a multidimensional entity, and there may be many aspects that may be worsening sleep. However, what is indisputable is that there is work to improve the quality of life of these patients.

Keywords: Pain; Chronic; Sleep; Anxiety; Depression
Novel drugs recently authorized by ema and fda (Q4, 2024)
Authors: Cuéllar Rodríguez Santiago
Published: February 2025

Fármacos de nueva aprobación – Newly approved drugs:
(B) SANGRE Y SISTEMA HEMATOPOYÉTICO: Hemofilia A y B: Marstacimab (Hympavzi®; EMA/FDA) y Concizumab (Alhemo®; EMA/FDA).(C) SISTEMA CARDIOVASCULAR: Taquicardia supraventricular: Landiolol (Rapiblyk®; FDA). Síndrome de quilomicronemia: Olezarsen (Tryngolza®; FDA). (J) ANTIINFECCIOSOS SISTÉMICOS: Infección urinaria: Sulopenem + Probenecid (Orlynvah®; FDA). Meningitis meningocócica (profilaxis): Vacuna Meningococo pentavalente (grupos A, B, C, W, Z) (Penbraya®) Pfizer (EMA/FDA). (L) AGENTES ANTINEOPLÁSICOS E INMUNOMODULADORES: Cáncer de pulmón: Ensartinib (Ensacove®; FDA). Adenocarcinoma gástrico: Zolbetuximab (Vyloy®; EMA/FDA). Cáncer de mama: Inavolisib (Itobeni®; FDA). Leucemia linfoblástica: Obecabtagene Autoleucel (Aucatzyl®; FDA). Leucemia aguda: Revumenib (Rebuforj®; FDA). Cáncer de vías biliares: Zanidatamab (Zihera®; FDA). Cáncer de pulmón, cáncer de páncreas: Zenocotuzumab (Bizengri®; FDA). Hiperplasia adrenal congénita: Crinecerfont (Crenessity®; FDA). Enfermedad aguda de injerto contra huésped: Remestemcel-L (Ryoncil®; FDA). Carcinoma cutáneo de células escamosas: Cosibelimab (Unloxcyt®; FDA). (N) SISTEMA NERVIOSO: Amiloidosis por transtiretina: Acoramidis (Attruby®; FDA). (R) SISTEMA RESPIRATORIO: Fibrosis quística (mucoviscidosis): Venzacaftor + Tezacaftor + Deutivacaftor (Alyftrek®; FDA).(S) ÓRGANOS SENSORIALES: (V) VARIOS: Revascularización de urgencia: Vaso de ingeniería tisular acelular (Symvess®; FDA).
INTSETINAL OBSTRUCTION IN PREGNANCY –A REVIEW
Authors: Singh Dr. Lallan , Kumari Dr. Rupam , Jaiswal Dr. Binod Kumar
Published: February 2025

Acute abdomen in pregnancy represents a unique diagnostic and therapeutic challenge. Acute abdominal pain in pregnancy can occur due to obstetric factors as well for reasons that are unrelated to pregnancy. The diagnostic approach of acute abdomen during pregnancy can be tricky owing to the altered clinical presentations brought about by the anatomical and physiological changes of gestation along with the reluctance to use certain radiological investigations for fear of harming the fetus. Delay in diagnosis and treatment can lead to adverse outcomes for both the mother and fetus Intestinal obstruction occurs rarely in pregnancy. The incidence is not increased in pregnancy as compared to non pregnant state. When a pregnant patient presents with abdominal pain we often consider obstetric causes like preterm labour, abruption or other common surgical problems but rarely suspect surgical conditions leading to intestinal obstruction. A delay in diagnosis and treatment can lead to serious problems in mother and fetus. In this article, we attempt to review and discuss the various etiologies, the current concepts of diagnosis, and treatment, with a view to developing a strategy for timely diagnosis and management of pregnant women presenting with acute abdominal pain due to intestinal obstruction.
COLORECTAL CARCINOMA –A REVIEW
Authors: Kumari Dr. Rupam , Singh Dr. Lallan , Jaiswal Dr. Binod Kumar
Published: February 2025

Colorectal cancer (CRC) is a common and lethal disease.The third most common cancer both in male and female is colorectal cancer (CRC) worldwide. In India, it is the fourth most common cause of cancer in males and third most common cause of cancer in females. The agestandardized rates of CRC in India havebeen estimated to be 4.2 and 3.2/100,000 formales and females, respectively, compared to 35.3 and 25.7, respectively, in the USA.It is estimated thatapproximately 149,500 newcases of largebowel cancer are diagnosed annually inthe UnitedStates, of which approximately 104,270 arise from colon and the remainder from the rectum..Approximately 52,980 Americans are expected to die of large bowel cancer each year. However, the incidence of CRC is increasing inyoung age especially indeveloping countries, which ismainly contributed by change inlifestyle and food habits.Although CRC mortality has been progressivelydeclining since 1990, at a current rateof approximately 1.6 to2.0 percent peryear , it still remains the third most common cause of cancer deathin the United States in women and thesecondleading cause of death inmen.In contrastto these declines, the incidence of CRC in men andwomen under the ageof 50 steadily increased at arate of 2.1 percent per yearfrom 1992 through 2012 and has continued toincrease since then . Theseincreases are driven predominantly by left-sidedcancers in general and rectal cancer in particular (3.9 percent per year) . Current literatures suggests that over 86 percent of those diagnosed under the age of 50 are symptomatic at diagnosis, and this is associated with more advanced stage at diagnosis and pooreroutcomes .At present, most guidelines suggest initiating screening at the age of 50 unlessindividuals haveinammatory bowel disease,a historyof abdominal radiation, apositive family history, or a predisposing inherited syndrome.CRC is diagnosed after the onset of symptoms, or through screening colonoscopy or fecal occult blood testing in the majority of patients. Screening of asymptomatic individuals for CRC is advocated by major societies and preventive care organizations. Screeninghas been shown todetect asymptomatic early stagemalignancy and improve mortality. However, while compliance with CRCscreening guidelines is steadily improving,it isstill relatively low.
Impact of Social Media Influencers on Behavior and Emotional Wellbeing of Adolescents
Authors: Liaquat Khilza , Muslim Dr. Imran Muslim
Published: February 2025

This research aims to assess the impact of social media influencerson the adolescent’s lifestyle and social well-being. The study used a survey of 102 respondents drawn from urban Pakistan using multistage cluster sampling and studied the social media trends and attitudes of the children. The results showed that adolescents using social media had less physical activity, altered relationships, and created different personas on different platforms. There were also social media users who sufferedfrom anxiety related to public sharing, but a huge number of them drew inspiration from the platform. The investigation pointed out the impact of social media on behavioral changes, planning, lifestyle management, sleeping, and studying.
Student Voice: Reviewing two decades of the literature to guide the next 20 years
Authors: Ashton-Hay Sally
Published: February 2025

Attention to students and their education experiences has become increasingly important in the 21st century. Student experience - particularly active and agentic practices captures in terms like 'student voice' and 'partnership' - was an obvious choice in response to Journal of University Teaching and Learning Practice (JUTLP) editors' commissioned series of  literature reviews analysing 20 years of the journal's publications. A hybrid method for the systematic review was guided by the question: What has been published about student voice and partnership in JUTLP, and how has this scholarship evolved over the journal's 20-year history? A student voice and partnership framework adapted from Fielding (2004, 2012) was developed to provide theoretical guidance for the review. In total, 92 publications were identified and described quantitatively (year, country, research design, etc) and qualitatively using reflexive thematic analysis. Overall, the findings show increased publications over time that document active student involvement in developing, shaping ,designing, evaluating or researching alongside staff. The upward trend of partnership is a marked change from early JUTLP publications that studied students as objects of research and sources of data with passive roles in education practices and student life activities. The trend is toward students as active, agentic participants, partners and leaders in shaping and influencing their education experiences. Moving into the next 20 years, the JUTLP community is urged to engage with students as co-authors, co-researchers, and co-designers to report on educational praxis with staff and to open up new avenues for student contributions to knowledge and the mission of JUTLP.
Sustainability in Harnessing Agroforestry for Climate Change Mitigation and Development - Climate Change Mitigation Practices for Agroforestry and Conservation of Agriculture for Restoration of Degraded Agro Ecosystems in the Gambia
Authors: Kijera Bala Musa
Published: February 2025

Agroforestry, a land management system that integrates trees, crops, and livestock, has emerged as a promising strategy
for climate change mitigation and sustainable development. This journal article explores the potential of agroforestry
in sequestering carbon, conserving biodiversity, improving soil health, and enhancing livelihoods. Drawing on recent
approaches to agroforestry on pilot in selected communities in the Gambia, this article highlights the multifaceted benefits
of agroforestry and provides insights into its role in building resilience to climate change, improve mitigation and fostering
environmental sustainability. Policy recommendations and future research directions are also discussed to promote the
adoption of agroforestry as a viable solution to address the challenges posed by climate change.
Composição física, físico-química e propriedades bioativas de frutos de genótipos de umbuzeiro (Spondias tuberosa Arruda) provenientes do sudoeste da Bahia
Authors: Moreira Marcilio Nunes , Moreira Élia Karina de Carvalho Costa , Souza Iago Hudson da Silva , Leite Neta Maria Terezinha Santos , Sandes Rafael Donizete Dutra , Mizobutsi Gisele Polete , Donato Sérgio Luiz Rodrigues , Narain Narendra
Published: February 2025

Típico da caatinga, o umbu é um fruto de relevância socioeconômica que garante fonte de renda e qualidade de vida aos produtores do semiárido brasileiro. Seu sabor exótico e excelentes propriedades nutricionais torna-o atrativo e aceito pelos consumidores, tanto in natura, quanto processado. Objetivou-se determinar a composição física, físico-química e nutricional de frutos de diferentes genótipos de umbuzeiro. Frutos de treze genótipos foram avaliados quanto às propriedades físicas e físico-químicas. Os frutos de massa superior (>50g) foram caracterizados quanto aos compostos bioativos, atividade antioxidante e compostos voláteis. A massa dos frutos variou de 7,15 a 78,09g, com rendimento médio de 70,62%. O acesso BGU 61 apresentou maior teor de umidade, acidez titulável e teor de cinzas. O acesso BGU44 apresentou maior ºBrix e pH. O genótipo BGU45 se destacou quanto aos compostos fenólicos totais (32,15 mg EAG/100g) e flavonoides totais (0,88 mg Quercetina/100g). No acesso BRS 68 encontrou-se o maior teor de carotenoides (35,3288µg de β caroteno/g de polpa). Os genótipos BGU45 e BGU44 apresentaram maior capacidade antioxidante pelos ensaios ABTS+•, DPPH•, FRAP e ORAC. Foram encontrados compostos voláteis específicos nos genótipos BGU45 (butyl acetate e humulene), BGU61 (γ-muurolene, β selinene, 3,7(11)-selinadiene, valencene e γ-selinene) e BGU75 (methyl hexanoate, 4 pentenyl butyrate, 1-hexanol, 1-octen-3-ol.). Conclui-se que os frutos do umbuzeiro devem ser explorados, pois são promissores e apontam níveis consideráveis de nutrientes e capacidade antioxidante, que oferecem benefícios à saúde e valor comercial.
Использование спекл-трекинг стресс-эхокардиографии в ранней диагностике нестабильной стенокардии
Authors: A
Published: February 2025

Спекл-трекинг эхокардиография и стресс-эхо представляют собой эффективные неинвазивные методы, предназначенные для ранней диагностики нестабильной стенокардии. Применение спекл-трекинга позволяет выявить миокардиальную дисфункцию на стадии, предшествующей снижению фракции выброса, что способствует улучшению прогностической оценки, особенно в случае обструктивных поражений коронарных артерий. Снижение показателя глобальной продольной деформации левого желудочка демонстрирует высокую чувствительность и положительное прогностическое значение, что делает данный метод особенно ценным для диагностики миокардиальной дисфункции. Стресс-эхо зарекомендовала себя как диагностический метод, способный выявить предикторы неблагоприятных сердечно-сосудистых событий. Отрицательные результаты стресс-эхо тесно связаны с повышением выживаемости пациентов. Оптимальное сочетание спекл-трекинга и стресс-эхо повышает точность диагностики и улучшает прогнозирование сердечно-сосудистой смертности
Toward AI-Aided Teleaudiology
Authors: Wasmann Jan-Willem
Published: February 2025

Around 1.5 billion people worldwide experience some level of hearing loss, yet most lack easy access to hearing tests, treatments, or suitable hearing devices. This thesis explores innovative ways to improve hearing care through teleaudiology—delivering hearing services online via smartphones—and artificial intelligence (AI). These methods aim to make hearing care more accessible in the future.

The research shows that individuals with severe to profound hearing loss, who use cochlear implants, can evaluate their hearing performance at home using self-administered tests. This may reduce the need to visit a clinic. Self-administered tests can also help fine-tune the settings of a cochlear implant. Additionally, we evaluated free speech-to-text apps that convert spoken words into text. The accuracy of these apps seems sufficient to help people with moderate to severe hearing loss follow conversations more easily.
Inovasi dalam Pembelajaran PPKN Menggunakan Media Tradisional dan Digital di Madrasah Ibtidaiyah
Authors: Salsabila Bilqis Salsabila Mayada , Salsabila Lailia , Nasir M.Fikri Abdun
Published: February 2025

The development of information and communication technology has brought significant changes to the world of education, including in Citizenship Education (PKN) learning.   This research aims to explore PKN learning innovations in the digital era with technology to improve student understanding.  The research method used is a comprehensive literature study from various related sources, such as journals, books and research reports. The research results show that the use of technology in PKN learning, such as interactive multimedia, digital simulations, and online learning, can increase students' interest, motivation, and understanding of PKN material.   Apart from that, the use of technology also enables more contextual, collaborative and student-centered learning.  However, the application of technology in PKN learning also has challenges, such as limited access to technology and teacher readiness to integrate technology effectively. This research concludes that PKN learning innovation in the digital era using technology can be a solution in improving the quality of education and preparing students to become active, critical and responsible citizens in the digital era.
Internalisasi Karakter Religius Dan Kepemimpinan Siswa Melalui Kegiatan Pramuka Di Sekolah Dasar Islam Surabaya
Authors: Wahzudi Muhammad , Ariyansyah Zuhal
Published: February 2025

This research is motivated by the rapid development of technology and information today, both from social media or other media, so it is necessary to internalize religious and leadership characters as a foundation so as not to be negatively affected by these developments and as an altenative media, namely through scouting activities. This study aims to analyze the process, supporting and inhibiting factors for internalizing the religious character and leadership of students through scouting activities at SDI Miftahul Ulum Surabaya. This type of research is descriptive qualitative. The research was conducted at SDI Miftahul Ulum Surabaya. The data collection techniques used included interviews, observation, and documentation. After the data is collected, the next step is to clarify the data according to the problem formulation, then analyze the data using descriptive analysis techniques, so that a research finding is drawn.
The results of this study are: 1) Internalization of the religious character of students through scout activities at SDI Miftahul Ulum Surabaya is carried out in three ways, namely aspects of aqidah (belief), sharia (religious practice), and akhlaq. 2) Internalization of the student's leadership spirit through scouting activities at SDI Miftahul Ulum Surabaya is carried out in three ways, namely multiplying self-potential, organizing (groups), and management (processing / managing).3) Supporting factors and inhibiting internalization of religious character and student leadership through There are four things in scouting activities at SDI Miftahul Ulum Surabaya, namely the support of the principal and parents of students, enthusiasm of students in participating in scouting activities, inadequatefacilities and very limited scout training time.
PELAKSANAAN KEGIATAN PENGAJIAN RUTIN KEAGAMAAN DALAM MEMBANGUN DAN MENGEMBANGKAN KEIMANAN PONDOK PESANTREN AR-ROYAN
Authors: Fathulliansyah Noor , David Bastian Sihombing  , Veby Senopati Silam
Published: February 2025

Pengajian dapat diartikan proses menuju kepada pembagian masyarakat melalui jalur agama. Bimbingan kepada masyarakat ini bisa dikatakan dakwah karena dakwah merupakan usaha meningkatkan pemahaman keagamaan untuk mengubah pandangan hidup, sikap batin, dan perilaku umat yang tidak sesuai dengan ajaran Islam menjadi sesuai dengan tuntunan syariat untuk memperoleh kebahagiaan hidup dunia dan akhirat. Jadi peranan secara fungsional adalah mengokohkan landasan hidup manusia Indonesia pada khususnya di bidang mental spritual keagamaan Islam dalam rangka meningkatkan kualitas hidupnya secara intergal, lahiriyah dan batiniyahnya, duniawiyah bersama. Sesuai tuntunan ajaran agama Islam yaitu iman dan taqwa yang melandasi kehidupan duniawi dalam segala bidang kegiatannya.
                Kegiatan Pelaksanaan pengajian rutin keagamaan dalam membangun dan mengembangkan keimanan pondok pesnatren Ar-royan dilaksanakan di Aula Pesanren Ar-royan, dengan m,emersiapkan kegiatan rutin yang dilaksanakan dan dipersiapkan oleh panitia tersebut dan tentunya juga dihadiri oleh masyarakat sekitar pada Pengajian Rutin tersebut, yang terjadwal setiap Hari Senin Sore hingga Malam disambung adanya Ceramah setelah pengajian terlaksanakan.
Hasil Pelaksanaan kegiatan  pengajian rutin keagamaan dalam membangun dan mengembangkan keimanan pondok pesantren Ar-royan. Sebagai salah satu pengabdian kepada masyarakat tentang penyampaian ilmu agama sebagai salah satu pedoman utama dalam menjalani sebuah kehidupan, dengan demikian baik pondok pesantren dan masyarakat sekitar juga dapat bergabung dalam menambah ilmu yang mana setiap pertemuan dengan judul yang berbeda-beda, tentunya menambah lebih pengetahuan agama yang didapat setelah kegiatan  pengajian rutin di saksikan.
BAKTI SOSIAL DONOR DARAH TARUNA-TARUNI AKADEMI MARITIM NUSANTARA BANJARMASIN SEBAGAI BENTUK KEPEDULIAN KESEHATAN TERHADAP DIRI SENDIRI DAN MASYARAKAT.
Authors: Wardhana Andri Ali , Akhmad Syahbudin  , Irnita Rosaria Santi  , Kamsariaty Kamsariaty , Firdaus Suwestian,  , Hadiansyah Hadiansyah
Published: February 2025

Bakti Sosial merupakan suatu kegiatan  dimana dengan adanya kegiatan ini kita dapat merapatkan kekerabatan kita, untuk mewujudkan rasa cinta kasih , rasa saling menolong,rasa saling peduli mahasiswa kepada masyarakat luas yang sedang membutuhkan uluran tangan mereka.Tujuan dari diadakan kegiatan bakti sosial masyarakat adalah untuk meningkatkan kepedulian dan rasa social terhadap kodisi masyarakat pedesaan yang makin hari makin memprihatinkan, baik dari segi kebutuhan ekonomi maupun dari segi lapangan pekerjaan, terciptanya masyarakat yang peduli terhadap sesama, memberi motivasi kepada masyarakat tentang pentingnya kesadaran dalam meningkatkan wawasan.
                Metode pelaksanaan di Aula Lanal Banjarmasin, pada agenda rutin dalam mengumpulkan pendonor darah yang suka rela dalam memberikan darah yang untuk diperlukan di beberapa rumah sakit sebagai stok agar lebih sigap dalam memberikan pelayanan bagi kepentingan bersama, hal ini tentu memudahkan dalam membantu orang lain yang segera membutuhkan darah sesuai yang duperlukan. Seperti pada kegiatan yang telah dilasakanakan Taruna-taruni Akademi Maritim Nusantara Banjarmasin, setelah melaloui proses tahapan dalam syarat pendonoran darah Taruna-taruni siap melaksanakan donor darah untuk masyarakat yang membutuhkan. Dengan demikian, kegiatan tersebut sebagai penganbdian kepada masyarakat atau pun kepedulian kepada kesehatan dan keselamatan pada diri sendiri dan orang lain yang membutuhkan.
                Pada hasil kegiatan donor darah yang langsung disumbangkan oleh taruna-taruni di Akademi Maritim Nusantara Banjarmasin tersebut, tentu membuahkan hasil bagi pihak rumah sakit yang memnbutuhkan sebagai stok cadangan darah bagi pihak yang terdesak, kegiatan sosial tersebut menjadi rutinitas kegiatan yang diselenggarakan dari Lanal Banjarmasin baik untuk umum maupun yang rela mendonorkan darah untuk kesehatan diri pribadi maupun menyemaltkan kesehatan orang lain sebagai bentuk rasa kasih dan rasa empati kepada manusia. Dengan demikian, pada kegiatgan bakti sosial donor darah tentu akan menjadi rutinitas taruna-taruni beserta dosen maupun staf fbagi yang lulus tahapan untuk siapm di donorkan kepada PMI tersebut.