bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization-based clustering feature extraction approach for human emotion recognition
Authors: C. Agilan  , Lakshna Arun
Published: January 2025

Human emotions are mental health states that resolve without conscious effort and are followed by physiological effects in the face muscles that represent expressions. In many applications of human-computer interaction, nonverbal communication mechanisms such as emotions, eye movements, and motions are used. Since there is no contrast among the emotions of a face and there is also a lot of variety and complexity, identifying emotions is a difficult process. To model the face, the machine learning system leverages some open features. Automatic emotion recognition based on face expression is a fascinating study area that has been presented and utilized in a variety of fields, including safety, health, and human-machine interactions. Researchers in this subject are willing to develop strategies to understand, code, and extract facial expressions in order to improve computer prediction. Machine learning, being one of the most promising new fields, offers a wide range of applications. In recent years, the support vector clustering technique has gotten a lot of attention. In this research paper, the use of ant colony optimization (ACO) for creating k-cluster planes and assigning each data sample to the correct cluster is proposed in this study as an upgraded clustering approach. SVC is used in this improved technique to refine the clusters created by ACO. The human face expressions are segmented using this upgraded clustering method. The suggested clustering technique is compared to an existing segmentation approach for emotion recognition using a variety of criteria.
Evaluating the impact of MOOC participation on skill development in autonomous engineering colleges
Authors: R. Chandran  , J. Selvam
Published: January 2025

The integration of massive open online courses (MOOCs) in higher education has introduced new avenues for skill development and academic achievement. This study investigates the impact of MOOC participation on students’ academic performance within autonomous engineering colleges. Specifically, we examine whether students who engage in MOOCs achieve higher academic outcomes compared to their peers who follow traditional coursework only. A sample of 450 engineering students from autonomous colleges was surveyed regarding their MOOC participation, academic performance, and engagement levels. To analyze the hypothesis that MOOC participation positively influences academic performance, multiple statistical methods were employed. Descriptive statistics provided an overview of student participation and performance trends, while a t-test was used to compare academic performance scores between MOOC participants and non-participants. Regression analysis was applied to determine if MOOC participation is a significant predictor of academic success. Additionally, a Chi-square test examined the association between MOOC engagement and academic achievement. The results indicate that MOOC participation positively correlates with academic performance, supporting the hypothesis that MOOCs can serve as a valuable supplement to traditional education. These findings underscore the potential of MOOCs to enhance learning outcomes in engineering education and suggest that autonomous colleges might benefit from promoting MOOC engagement as part of their curriculum.
Fuzzy logic-driven scheduling for cloud computing operations: a dynamic and adaptive approach
Authors: A. Kalaiselvi  , A. Chandrabose
Published: January 2025

Cloud computing is a decentralized approach of providing and accessing computer services through the internet. The phrase «cloud computing» is commonly used to describe this setup. The term «cloud computing» refers to a method of running computer programs, data, and services over the internet from a central location rather than on individual users’ local machines. Cloud computing environments face the challenge of efficiently managing and scheduling diverse tasks to ensure optimal resource utilization and system performance. This paper introduces a fuzzy logic-based approach for scheduling cloud computing operations designed to handle the uncertainty and dynamic nature of task execution requirements. The proposed method incorporates fuzzy rules and membership functions to evaluate key parameters such as task priority, resource availability, and execution time. By modeling these uncertainties, the fuzzy logic system dynamically adjusts scheduling decisions to optimize load balancing and minimize delays. The approach offers flexibility in allocating resources and prioritizing tasks in real-time, adapting to fluctuating workloads and system conditions. Experimental simulations demonstrate the effectiveness of the fuzzy logic approach in enhancing system throughput and reducing task completion time, offering a robust solution for scheduling in heterogeneous and complex cloud environments. This method shows promise for improving the scalability and responsiveness of cloud-based operations. Comparisons with three separate scheduling algorithms the first come, first serve (FCFS) algorithm, the round robin (RR) strategy, and the Honeybee foraging (HF) algorithm, show that our method is quite effective. The experimental findings validate the efficacy of our algorithm.
Enhanced otpmization based support vector machine classification approach for the detection of knee arthritis
Authors: G. Hemamalini  , V. Maniraj
Published: January 2025

The accurate detection of knee arthritis is essential for effective medical diagnosis and treatment. In this study, we propose an enhanced classification approach using a support vector machine (SVM) coupled with Cuckoo search optimization (CSO) to improve the detection of knee arthritis. The classification challenge lies in tuning the hyperparameters of the SVM, specifically the penalty parameter (C) and the kernel function parameter (γ), which significantly influence the model’s performance. Traditional methods of hyperparameter tuning may be computationally expensive and prone to local minima. To address these challenges, we integrate CSO as an optimization algorithm for the efficient search of optimal hyperparameters. Cuckoo search optimization, inspired by the brood parasitism behavior of cuckoo birds, is applied to optimize the SVM hyperparameters by balancing exploration and exploitation during the search process. CSO efficiently explores the hyperparameter space and finds an optimal or near-optimal solution by minimizing the classification error. The hybrid approach aims to enhance the predictive accuracy and generalization ability of the SVM model. The proposed CSO-SVM framework is validated on a benchmark knee arthritis dataset, and the experimental results demonstrate a significant improvement in classification performance compared to traditional SVM and other optimization algorithms. The proposed model’s ability to optimize hyperparameters with CSO shows promise in achieving higher accuracy, precision, recall, and F1 score, making it a robust approach for knee arthritis detection.
An ensemble-based approach for sentiment analysis of covid-19 Twitter data using machine learning and deep learning techniques
Authors: M. Jayakandan  , A. Chandrabose
Published: January 2025

In the wake of the COVID-19 pandemic, social media platforms like Twitter have become critical channels for public expression, capturing a wide array of sentiments ranging from fear and anxiety to hope and optimism. This paper proposes an ensemble approach for automatic sentiment analysis of COVID-19-related tweets to extract valuable insights from large-scale data. The proposed method integrates multiple machine learning algorithms, including support vector machines (SVM), random forests, and deep learning models such as long short-term memory (LSTM) networks. By leveraging these diverse techniques, the ensemble model aims to improve classification accuracy and robustness in detecting positive, negative, and neutral sentiments. Feature extraction is optimized through natural language processing (NLP) techniques like term frequency-inverse document frequency (TF-IDF) and word embeddings. Experimental results on a publicly available COVID-19 Twitter dataset demonstrate the effectiveness of the proposed approach, showcasing its potential to contribute to public health monitoring, policy making, and understanding of public reactions during crises.
Enhanced regression method for weather forecasting
Authors: T. Malathi  , T. Dheepak
Published: January 2025

Weather prediction is gaining popularity very rapidly in the current era of artificial intelligence and Technologies. It is essential to predict the temperature of the weather for some time. Traditionally, weather predictions are performed with the help of large complex models of physics, which utilize different atmospheric conditions over a long period of time. These conditions are often unstable because of perturbations of the weather system, causing the models to provide inaccurate forecasts. The models are generally run on hundreds of nodes in a large high-performance computing (HPC) environment, which consumes a large amount of energy. In this paper, LightGBM Regression parameters are tuned by using an optimization technique. Differential evolution (DE) is used to optimize the LightGBM regressor for estimating and forecasting the weather in the fore coming days.
Chaotic-based optimization, based feature selection with shallow neural network technique for effective identification of intrusion detection
Authors: S. Hemalatha  , N. Vanjulavalli  , K. Sujith  , R. Surendiran
Published: January 2025

The work in this paper attempts to deal with intrusion detection using a chaotic-based optimization technique and feature selection + shallow neural networks. The idea of chaotic systems is used to get randomness in the feature selection process, which can enable a shallow neural network to perform better for intrusion detection. Experiments on benchmark datasets reveal the effectiveness of this proposed solution by significant improvements in detection accuracy, false positive reduction at run-time and computational efficiency as compared to conventional methods.
Funding agencies in Tamil Nadu State Universities: A scientometric perspective
Authors: U. Perachiselvi  , R. Balasubramani
Published: January 2025

Scientometrics is a significant area of information science because it offers a unique variety of tools and techniques for managing knowledge in social and organizational contexts as well as for maintaining and evaluating information resources. The multiple scientometric components of the articles published by Tamil Nadu’s top eight universities between 1989 and 2023 were examined in this study. Data analysis shows that the average growth rate is increasing at a 9.76% annual pace. This extensive study finds the subtle interactions between funding agencies and research productivity in Tamil Nadu’s state universities. A comprehensive assessment of the funding landscape is carried out by methodically gathering data from eight notable universities, including Alagappa University, Anna University, Annamalai University, and others. With a remarkable total of 19,524 funding agencies discovered across various roles within these universities, the breadth of support highlights the importance of external money in propelling research efforts. Notably, Anna University appears as a frontrunner, with 4,162 funding agencies, demonstrating a strong network of support. The findings highlight the relevance of understanding how funding agencies affect research ecosystems within academic institutions.
Application of data mining and machine learning approaches in the prediction of heart disease – A literature survey
Authors: S. Vanaja  , Hari Ganesh S
Published: January 2025

Heart disease remains a leading cause of mortality worldwide, emphasizing the urgent need for effective classification and prediction methodologies. This literature review explores various data mining and machine learning approaches utilized in the classification and prediction of heart disease. We systematically analyze a diverse range of techniques, including decision trees, support vector machines, artificial neural networks, and ensemble methods, highlighting their strengths and limitations. The review further examines pre-processing methods, feature selection, and extraction techniques that significantly impact model performance. Additionally, we discuss the integration of hybrid approaches and deep learning methods, showcasing their potential to enhance predictive accuracy. Recent advancements in data handling and algorithmic efficiency are also highlighted, demonstrating the promising role of machine learning in addressing the complexities of heart disease diagnosis. This review aims to provide a comprehensive understanding of current trends and future directions in heart disease classification and prediction, paving the way for improved diagnostic tools and health outcomes.
Modeling and Characterization of a Resonant Converter from a Hamiltonian Systems Perspective
Authors:   Universidad Nacional Autónoma de México, México, Sánchez-Contreras Agustín , Ortega-Velázquez Isaac ,   Universidad Nacional Autónoma de México, México, Espinosa-Pérez Gerardo ,   Universidad Nacional Autónoma de México, México, Rodríguez-Benítez Oscar Miguel ,   Universidad Nacional Autónoma de México, México
Published: January 2025

In this paper, Hamiltonian modeling methods for resonant converters, their advantages, properties and limitations are analyzed. The main contribution is to propose a non-extended order continuous Hamiltonian model that recovers the system signals and provides a practical scheme for model-based control. The advantages of the proposed modeling methodology is illustrated by studing the particular example given by current-fed resonant converter.
Thermoelectric Module Control Based on Fractional-Order Disturbance Estimation State Observers
Authors:   Universidad Tecnológica de la Mixteca, México, Montesinos-García Juan Javier , Barahona-Avalos Jorge Luis ,   Universidad Tecnológica de la Mixteca, México, Lugo-González Esther ,   Universidad Tecnológica de la Mixteca, México, Linares-Flores Jesús ,   Universidad Tecnológica de la Mixteca, México
Published: January 2025

This article presents a fractional-order control strategy based on an uncertainty estimator applied to thermoelectric modules. It is known that thermoelectric modules are nonlinear systems characterized by a polynomial-type nonlinear control input. The proposed control law does not require the linearization of the nonlinear control input, this is achieved through the use of a state observer that estimates certain components of the nonlinear system’s state, enabling the control law to counteract these elements and drive the system toward a desired state. To validate the theoretical results, experiments are conducted by implementing the control law on a platform comprising a buck-type DC/DC converter that powers a Peltier cell. Simulation results show the feasibility of the proposed strategy against classical controllers.
Արդարադատության դոկտրինալ և օրենսդրական հիմքերի պատմական զարգացման հիմնական ուղենիշները / Basic Stages of Historical Development of Doctrinal and Legislative Bases of Justice
Authors: Stepanyan Norayr V.
Published: January 2025

The idea of justice, as a demand for a fair and correct settlement of disputes by competent authorities within the framework of established procedures, arose in ancient times.
Its sources can be found in “Rigveda”, sacred texts of Indian peoples, “Avesta”, in the book of prophecies and sermons of old Iranian prophet Zoroaster, in the Bible, the Quran and other sacred writings.
Justice... What is the base of this word? What ideas did people put on the foundation on which this legal institution was built? How did the ideas of justice and law unite in this term and lay the foundation for the emergence of judiciary, which today is bulwark of any legal democratic state.
Analyzing the legal literature, it could be mentioned that issues regarding the statehood, law and justice concerned Aristotle, G.V.F. Hegel, H. Grotius, E. Kant, Plato, M. Cicero, Montesquieu and other famous thinkers. Later, their ideas were reflected in the works of our modern S. Alexeyev, D. Ikonnikova, D. Kerimov, A. Levchenkov, V. Nersesyants, A. Sachkov, V. Smorodinsk, V. Sokhantseva and other authors. However, the nature of justice is dynamic, justice is constantly developing under the influence of the transformation processes taking place in society and the state.
As justice is really one of the main, important directions typical of state activity, then numerous researchers in the field of state and theory of law and history, answering the first question, usually agreed that justice is equal to both the state and the law.
This theoretical conclusion is based on the following grounds;
• First, justice is fundamentally impossible without the existence of a certain legal basis, because its existence motivates the parties to seek protection in the state, including in the court, in case of violation of any specific subjective right. Indeed, if there is no law, neither the court is required, and if there is no court, then the normal operation of the law is also violated. In this case, the court gives life to the law and stands for “living right”.
• Second, the assumption that the court is considered the equal and adjacent to the law and the state, has been thoroughly confirmed by the historical monuments that have reached us. According to which, any legal system is impossible without a court, an institution of justice, which is envisaged for restoration of violated right and social justice.
Իրավունքից հրաժարումը առողջապահական իրավունքում / Waiver of Rights in Healthcare Law
Authors: Khachatryan Anna K.
Published: January 2025

The right to care for human health is a constitutional right, which creates responsibilities for the state in the field of medical care and service. However, it happens that a person himself renounces this right, as a result of which the state's intervention in the exercise of this right is limited. The work discusses the general characteristics of the refusal of the right to medical care and service, the refusal of the right to be informed about medical care and service, the refusal of medical care and service by special groups, and the refusal of special types of medical care are discussed separately. Such scientific methods as legal-comparative and analytical methods were used during the study. The purpose of the study is to clarify the concept of waiver of the right in the healthcare law and to highlight the limits of the legal possibility of the state's intervention in the case of a person's waiver of that right.
From surviving to thriving, management leadership in smart organizations in the post-pandemic era
Authors: Verenzuela-Barroeta Daniel Antonio , Querales-Ampueda Dayana Esther , Araque-Manrique Mariela Concepción , Salas-Hernández Adrián José
Published: January 2025

The objective of this research is to describe emerging managerial leadership in learning organizations for the post-pandemic era. With a descriptive approach, sources of information available in Google Scholar were analyzed, selected according to the criteria of the research protocol, complemented with the hermeneutics-dialectics of authors based on their academic-professional experience. The managerial leader must possess technical and social skills, as well as competencies to master relationships and links by combining influence, objectives and processes from a social perspective that denotes his personal mastery. Adopt a participatory, resilient, stimulating and systemic leadership style to build a management style that recognizes that its collaborators are biopsychosocial, sensitive beings with new needs that demand meaning and purpose. As a human talent management strategy, it uses emotional salary aimed at promoting psychosocial well-being, attracting and retaining talent, improving quality of life and converting team members into partners of the organization, committed to generating profitable benefits that They will be shared. This promotes the creation of productive knowledge to promote change and adaptability in conditions of uncertainty, as a source of organizational learning that constitutes a sustainable competitive advantage for intelligent organizations.
Beyond charisma on TikTok: Key attributes of content creators that attract and prefer audiences
Authors: Ramirez Martínez Catalina , Barrios Reina Sihmonne , Ortegón Cortázar Leonardo
Published: January 2025

TikTok is the fastest-growing social network due to both the features of the interface and the aspects related to content creators that are valued by audiences. Along these lines, research was conducted to explore the attraction and preference attributes of TikTok content creators from the perspective of their followers. The qualitative method was used through three focus group sessions with active users of this platform, guaranteeing groups of at least 8 participants whose transcripts were systematically analyzed with the support of Atlas Ti software. The results suggest that content creators stand out for a combination of key attributes. Authenticity requires the creator to develop a genuine image that projects trust and transparency, improving the connection with followers. Originality is linked to creativity and innovation in content, providing an important differentiating factor. Charisma is built through a combination of spontaneous personality and assertive communication, promoting closeness. Physical attractiveness causes significant interest in the initial perception, and the ability to influence allows the creator to impact the attitudes and decisions of their followers. These findings have several implications when collaborating with influencers on TikTok.
Nursing Caring Behavior Based on Jean Watson's Theory is Related to Anxiety Levels in Pre-Operative Patients
Authors: Nurhayati Nurhayati , Alfara Wina , Ritawati Ritawati , Simeulu Putro , Taufik Taufik
Published: January 2025

Background: Anxiety is the main cause of individual helplessness and accounts for around 15% of global morbidity. More than 28% of people experience anxiety at the age of 18 to old age, where anxiety is usually also associated with psychological conditions and declining individual health so that they must be hospitalized. Caring behavior carried out by nurses makes patients tend to be more comfortable and more optimistic about their recovery.
Purpose:  To find out the relationship between caring behavior of nurses based on Jean Watson's theory and the level of anxiety in pre-operative patients.
Methods: The type of quantitative research using correlational research design and Cross Sectional Study approach. The population used is pre-operative patients who are in the Regional General Hospital. The sampling method used is non-probability sampling with a sample of 44 respondents. Data collection was carried out through interviews and using the HARS questionnaire.
Results: The results of the Chi-Square Test show a p value of 0.004 < 0.05, which means that there is a significant relationship between the caring behavior of nurses based on Jean Watson's theory and the level of pre-operative patient anxiety at the Meuraxa Regional General Hospital, Banda Aceh.
Conclusion: There is a significant relationship between caring behavior of nurses based on Jean Watson's theory with the level of preoperative patient anxiety. The more frequently caring behavior is implemented by nurses, the patient's anxiety level will decrease.
Pain Management Intervention in Overcoming Dysmenorrhea in Adolescent Girls at the Bina Dakwah Islamic Boarding School, Loa Bakung District Samarinda
Authors: Adiasih Nisa Solikha , Safrudin Muhammad Bachtiar
Published: January 2025

Background: The setting of community health services in at-risk groups is often not optimal due to the distance of access to available health services, the lack of promotive efforts of health facilities in providing disease prevention education so that this will have an impact on community health deficiencies in adolescents and ineffective health maintenance. In order for the prevalence of dysmenorrhea problems in the community setting to be reduced, preventive management is needed, namely by reducing community health problems by carrying out several community health programs such as maintaining the management of pain problems as a result of dysmenorrhea symptoms.
Purpose:  To determine the level of knowledge and pain of dysmenorrhea in adolescents at the Bina Dakwah Islamic Boarding School, Loa Bakung District, Samarinda after pain management was carried out.
Methods: Descriptive research type through nursing process approach involving 5 respondents. The research instrument used Visual Analog Scale (VAS) to measure the pain scale and knowledge level questionnaire related to adolescent dysmenorrhea pain.
Results: Management of dysmenorrhea pain in adolescents through education, dysmenorrhea exercises, and reflexology massage resulted in an increase in the average pain score from 8.2 to 11.8. Meanwhile, for dysmenorrhea pain, there was a decrease on the 3rd day, namely from mild pain (scale 3 to 4) to no pain.
Conclusion: Providing dysmenorrhea management through education, dysmenorrhea exercises, and reflexology massage can increase knowledge and reduce pain in adolescents at the Bina Dakwah Islamic Boarding School, Loa Bakung District, Samarinda.
Application of Slow Deep Breathing Exercise in Reducing Pain Intensity in Pre-Operative Patients with Lateral Inguinal Hernia Sinistra: Case Study
Authors: Suwardi Suwardi , Nirwan Nirwan , Rimadeni Yeni , Oetama Saiful , Halimatussakdiah Halimatussakdiah
Published: January 2025

Background: Inguinal hernia occurs when there is a protrusion of the contents of a cavity through a weak part of the inguinal gap in the abdominal wall. The occurrence of inguinal hernia is caused by repeated and continuous increase in intra-abdominal pressure. The increase in inguinal hernia cases has now reached 20 million cases, most of which are suffered by late adults to the elderly with the main problem being acute pain and its management through herniotomy. Slow Deep Breathing Exercise is one of the non-pharmacological therapies that is often used to overcome acute pain felt by pre-operative patients.
Purpose:  To provide an overview of the application of slow deep breathing in the management of acute pain in preoperative patients with left lateral inguinal hernia treated at the Zainoel Abidin Regional General Hospital, Banda Aceh.
Methods: Descriptive research with case studies through the nursing process approach from assessment, nursing diagnosis, planning, implementation, and evaluation. The subject of the study was 1 Pre-Operative Hernia Inguinalis Lateralis Sinistra patient who was treated in the internal medicine room who was given Slow Deep Breathing Exercise intervention. The research instruments used to collect data were medical surgical nursing care sheets and pain measuring instruments using the Numeric Rating Scale.
Results: After implementing Slow Deep Breathing Exercise twice a day (duration 15 minutes during the intervention) for 3 days combined with oxygen therapy via nasal cannula (3 liters/minute), the patient's main problem, namely acute pain, decreased from a scale of 8 to 6 with all patient activities still being assisted.
Conclusion: Based on the research results, it can be concluded that the patient's problem, namely acute pain, was partially resolved through the Slow Deep Breathing Exercise intervention because the pain still often occurs with an uncertain duration and interferes with the patient's basic needs.
A Practical Approach to NSAID Allergy
Authors: Fahmy David , Wong-Pack Andrew
Published: January 2025

Nonsteroidal anti-inflammatory drugs (NSAIDs) are widely prescribed for pain management and inflammation. Acetylsalicylic acid (ASA) is a commonly used treatment for cardiovascular diseases including acute coronary syndromes. Reactions to NSAIDs can vary widely, ranging from exacerbation of underlying cutaneous and respiratory conditions to anaphylaxis and delayed hypersensitivity reactions (DHRs). A thorough clinical history is essential for diagnosing NSAID hypersensitivity, with a focus on the systems involved, reaction timing, and the presence and control of comorbid allergic conditions. Although commonly referred to as an allergy, the mechanisms behind these reactions are not solely IgE-mediated. As such, the authors will primarily use the term “hypersensitivity reactions” in concordance with the latest American Academy of Allergy, Asthma and Immunology (AAAAI) drug allergy practice parameter. While NSAID hypersensitivity reactions may cross-react among cyclooxygenase-1 (COX-1) inhibitors, reactions to selective cyclooxygenase-2 (COX-2) inhibitors are rare and they are typically well tolerated as alternative agents.
Cardiovascular Safety of Testosterone Replacement Therapy in Hypogonadal Men
Authors: Kissock Jagoda
Published: January 2025

Testosterone replacement therapy (TRT) aims to restore serum testosterone levels in men with hypogonadism. Symptoms associated with hypogonadism include reduced libido, erectile dysfunction, fatigue, depression, and loss of muscle mass and bone density. The primary purpose of TRT is to alleviate these symptoms and improve quality of life by restoring serum testosterone levels to the physiological range.
The prevalence of hypogonadism in men increases with age, affecting approximately 2–5% of middle-aged and older men and up to 20% of elderly men. Despite its therapeutic benefits, the cardiovascular safety of TRT remains a topic of debate and investigation. Cardiovascular disease is a leading cause of morbidity and mortality among men, and any therapy that might influence cardiovascular risk requires careful evaluation. Early observational studies raised concerns about potential adverse cardiovascular outcomes associated with TRT. These findings prompted regulatory agencies to issue warnings and recommend further research. In response, more recent trials, including the TRAVERSE Study, have provided new insights into the relationship between TRT and cardiovascular health. This article aims to provide a review of recent evidence on the cardiovascular safety of TRT.
The Role of Bisphosphonate Drug Holidays in the Management of Osteoporosis
Authors: Kim Sandra , Lau Adrian
Published: January 2025

Osteoporosis is a chronic skeletal disorder of compromised bone strength leading to an increased risk of fragility fractures, particularly with advancing age. More than 2 million Canadians are living with osteoporosis, and osteoporotic fractures are associated with considerable morbidity, increased mortality, and high economic burden to the healthcare system. The ultimate goal of osteoporosis pharmacotherapy is to reduce the risk of fragility fractures.
Bisphosphonates are the most widely used first-line medications for osteoporosis due to their robust anti-fracture efficacy and favourable safety profile, as demonstrated in short-term randomized placebo-controlled trials of 3-years duration with fracture outcome assessed as the primary endpoint. However, the optimal duration of bisphosphonate therapy has been questioned regarding their long‑term efficacy and safety given their long half‑life in bone. Prolonged use is associated with very rare but serious adverse complications such as atypical femoral fracture (AFF) and osteonecrosis of the jaw (ONJ). Moreover, while extension trials indicate that long‑term bisphosphonate therapy helps maintain bone density, the evidence supporting further fracture risk reduction with prolonged treatment is less convincing. Regarding concerns about rare adverse effects and the attenuated benefit-to-risk ratio with long‑term use, several professional organizations have issued guidelines suggesting bisphosphonate drug holidays. This approach aims to minimize prolonged exposure and mitigate rare risks while preserving some residual anti-fracture benefits from the persistent drug in the skeleton. Here, we review the role of bisphosphonate drug holidays in the long-term management of osteoporosis, the supporting evidence, recommended guidelines on treatment duration, along with key considerations for implementing a bisphosphonate drug holiday.
Treatment of Philadelphia Chromosome-negative Myeloproliferative Neoplasms in 2024: A Concise Review
Authors: Rajendra Akhil , Maze Dawn
Published: January 2025

In 1951, William Dameshek coined the term myeloproliferative disorders (MPDs) for diseases characterized by abnormal proliferation of one or more terminally differentiated myeloid cell lines in the peripheral blood.1,2 In 2008, the World Health Organization (WHO) renamed these disorders as myeloproliferative neoplasms (MPNs) in recognition of their clonal nature. There are currently two classification system for MPNs: WHO and International Consensus Classification (ICC), 2022.3,4 This review will focus on the Philadelphia chromosome-negative MPNs, which include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF).
The Evolving Landscape of DLBCL Treatment Beyond the First Line in 2024
Authors: Bosch Mark
Published: January 2025

The landscape for treating relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) in 2024 is rapidly evolving, with various treatment options emerging. Traditionally, salvage chemotherapy followed by autologous stem cell transplant (ASCT) has been the primary treatment for young, fit patients with R/R DLBCL, and only limited options exist for those ineligible for transplant. However, recent research and regulatory approvals, such as chimeric antigen receptor (CAR) T-cell and bispecific antibody therapies, have significantly improved our ability to treat patients previously considered palliative for R/R DLBCL.
Moreover, further research has demonstrated that these advanced technologies are not only effective in the transplant setting but also in individuals who are not traditionally eligible for ASCT and those with comorbid conditions. One anticipated development has been the provincial approvals of bispecific T-cell engagers (BiTEs), such as epcoritamab and glofitamab, which target CD20 and CD3. BiTE therapy holds promise as an off-the-shelf treatment option, potentially offering wider availability to patients compared to CAR T-celll therapy or even post‑CAR T-cell failure.
Recent Advances in Complementary and Alternative Therapies for Inflammatory Bowel Disease
Authors: Chambers Jason , Weizman Adam V.
Published: January 2025

Inflammatory bowel disease (IBD) is a chronic relapsing-remitting inflammatory condition of the gastrointestinal (GI) tract, primarily comprised of 2 major types: Crohn's disease (CD) and ulcerative colitis (UC). The pathogenesis of IBD is not fully elucidated but is thought to be multifactorial involving genetic, environmental, and immunological contributors. The incidence of IBD has been rising worldwide, particularly in developed nations. Canada, in particular, has one of the highest prevalence rates of IBD globally, with recent data indicating that over 320,000 Canadians are living with IBD, making it a significant public health concern.
The chronic nature of IBD, along with the severity of its symptoms, and the adverse effects occasionally attributed to management (e.g. immunosuppression, corticosteroids, surgical complications) can significantly reduce the quality of life for those affected. As such, many patients with IBD use complementary and alternative medicine (CAM) due to safety concerns of conventional therapy and a sense of greater control over their disease. CAM refers to a broad range of healthcare practices, such as herbal medicine, acupuncture, homeopathy, fecal microbiota transplants, and probiotics, which are not typically considered part of conventional western medicine. The use of CAM among patients with IBD is high, with current or past use of CAM ranging from 21-60% of IBD patients. Given the propensity of patients with IBD to seek CAM and the unfamiliarity that many medical practitioners have with the evidence of benefit/harm from these practices, this review seeks to summarize recent advances in clinical research on CAM use for IBD.
Management of Anemia in Inflammatory Bowel Disease
Authors: Sheasgreen Chris
Published: January 2025

Anemia is one of the most common complications of inflammatory bowel disease (IBD), with estimates of its prevalence varying from 9-74%. It is estimated to affect more than 1.2 billion people worldwide and evidence suggests that the incidence of anemia in people with IBD is almost double that of people without IBD (92.75 people with IBD per 1000 person-years vs 51.18 without IBD per 1000 person-years). Having a thorough approach to anemia in IBD is important because it is common and potentially dangerous, and because of its potential to arise from multiple different pathological and/or physiological processes.
THE THEME OF 'SPIRITUAL EXISTENCE IN NATURE' IN THE POEMS OF WILLIAM WORDSWORTH: A CRITICAL ANALYSIS
Authors: Shukla Dr. Ramesh Kumar
Published: January 2025

William Wordsworth (7 April 1770- 23 April 1850), was the poet of the movement of the romantic revival. He believed that an invisible power is working behind the whole activities of Nature. He was priest, harbinger, slave as well as master of Nature. Wordsworth with S.T. Coleridge, helped to launch the Romantic Age in English with the joint publication of Lyrical Ballad in 1798. He was poet Laureate from 1843 to 1850. One of his most famous works is Prelude (1799) that is a romantic epic and semi-autobiographical poem, considered his magnum opus. He has enriched English Literature with his large number of poems like Lucy Grey (1800), To Milton (1802), The Cuckoo (1802), Ode: Intimations of Immortality from Recollections of Early Childhood (1807), The Solitary Reaper (1807), Composed Upon Westminster Bridge (1807), The World Is Too Much With Us (1807), The Daffodils (1807), and so on. It was he who hosted the flag of Romanticism. He was highly influenced with French Revolution. This is why he advocated very first that the diction of the poetry should be the diction of such person who lived in the lap of Nature. He was always in the favor of liberalism in literature. For him Nature is teacher, guide, nurse, balm and panacea of all human miseries. There is a fragrance of ecofeminism in his literary works. He established a profound connection between man, spirituality and Nature. His work reveals a deep-rooted spiritual engagement with the natural world, positioning it as a source of solace, inspiration, and moral guidance. His poetry underscores Nature's capacity to evoke profound emotional and spiritual responses. Wordsworth's poetry offers a compelling exploration of the intricate relationship among man, Nature and spirituality. Through his lyrical evocations of the natural world, he invites readers to embark on a journey of self-discovery and spiritual enlightenment.
The Pattern of Over-the-Counter Medicines Dispensed in Pakistan
Authors: Raza Ali , Tufail Shazia , Pervaiz Zarabia
Published: January 2025

Over the counter(OTC) drugs is a term used to describe a medication dispensed in pharmacies without proper prescription. Over thecounter medicines have become a cornerstone of selfcarewithmillionsrelying on themfor quick relieffrom common ailments, from headaches and colds to allergies and digestive issues.
The Correlation of Serum Troponin Levels with Age and Gender in Healthy Individuals
Authors: Anwar Ambereen , Farzand Sadaf , Mariam Shaista , Bugvi Saima Mansoor
Published: January 2025

Background and Objectives: Cardiac Troponin (cTn) values play a pivotal role in the diagnosis of ischemic heart disease (IHD). The advent of high sensitivity assays of both cTnI and cTnT have revolutionized the way IHD is diagnosed and managed. These high sensitivity assays have also highlighted some hitherto unknown features of cTns. It is being suggested that healthy individuals have different values depending on their gender and age. This study was planned to study these differences in a healthy population.Methods: A total of 700 apparently healthy individuals, 350 males and 350 females were included in the study. Their ages were also noted. Their cTnI values were recorded and analyzed to find the effect of age and gender on their cTnI levels. cTn I hs was detected on immunoassay analyser Siemens Atellica® Solution IM 1300 Analyzer, USA. The cut off for normal was taken at 45.2 pg/ml as per the company's manual.Results: Males had mean=9.39+8.6 cTnI values and females had mean=6.57+5.66.There was a statistically significant difference in cTnI levels between males and females (p-value < 0.0001) with male subjects showing higher levels. Increasing age had a positive correlation with cTnI levels in both genders but it was not statistically significant (correlation coefficient, r, 0.178 for males and 0.246 for females).Conclusion: The reference ranges for cTn values should be separately defined for males and females. Increasing age may have an influence on the diagnostic performance of cTns.These factors should be taken into consideration so that decision for each patient is individualized instead of assuming that the binary threshold criteria is set in stone.Keywords: Cardiac troponin, ischemic heart disease, reference range, age, gender
Perbedaan Individual dalam Kecerdasan dan Kepribadian
Authors: Sutra Awaliyah Darfin  , Bunga Rosani  , Nur Salsa Nabila  , Gizki Maharani  , Andi Nilan Sari  , Nola Fauziah
Published: January 2025

Individual differences in intelligence and personality have a significant impact on various aspects of life, including academic achievement, social interaction, and professional performance. This study aims to explore the influence of interactions between emotional, cognitive, social intelligence, and personality dimensions on individual success. Based on the five journals reviewed, it was found that both factors influence each other and contribute to achieving positive outcomes in various areas of life. This analysis is expected to provide deeper insight into the importance of intelligence and personality in everyday life.
Implementasi Metode Supply Chain Operation Reference (SCOR) dan Analythical Hierarchy Process (AHP) Dalam Pengukuran Performansi Supply Chain Pada Koperasi X
Authors: Purwanti Purwanti  , Nila Wati  , Dinda Oe Mardy  , Suseno Suseno
Published: January 2025

Supply Chain Management is a concept or mechanism to increase the total productivity of the company in the supply chain through optimizing the time, location and quantity flow of materials from raw materials to semi-finished products and finished products. The measurement design framework is prepared based on the functions or scope in the Supply Chain which refers to the Supply Chain Operation Reference (SCOR) such as: Plan, Source, Make, Deliver, and Return, with a performance measurement system consisting of aspects of Reliability, Responsiveness, Flexibility, Cost and Asset. Research on the measurement of Supply Chain performance was conducted at the Koperasi X dairy business entity. By taking these measurements, it is hoped that business entities can find out what scope must be improved. By using the Analytical Hierarchy Process (AHP) calculation, the performance value is 67.53. this figure indicates that the Supply Chain performance is sufficient. Based on the analysis of each scope, it is known that the scope with the lowest final score is Make, which is 53.25. the proposed improvement steps to improve the shortcomings of each in the scope are adding product variations, procurement automation, sustainable technology utilization, and improving relationship with supplier. It is expected that these improvements can be implemented gradually for maximum business entity development.
Optimisasi Systematic Layout Planning dan Perbandingan Work Sampling untuk Efisiensi Waktu Produksi di UD Cantenan
Authors: Dimas Hendarjati Pamungkas  , Muhamad Samsul Huda  , Roby Septiawan  , Agung Joko Prasetya  , Rizki Anugrah Robby  , Ferida Yuamita
Published: January 2025

This research aims to increase production efficiency at UD Cantenan, an aluminum metal manufacturing industry, through the application of the Systematic Layout Planning (SLP) method, the Kanban system, and Work Sampling productivity analysis. The initial layout shows the material movement distance between workstations is 41 m², with daily material handling costs reaching IDR 105,544. Through the SLP method, the layout was improved so that the moving distance was reduced to 37 m², and material handling costs fell to IDR 70,626 per day. The Kanban system was implemented to visually improve production flow, minimize waiting time, and reduce inventory buildup. Kanban implementation increased product delivery accuracy from 70% to 95%. Furthermore, productivity analysis using Work Sampling showed a non-productive activity ratio of 53% and productive activity reaching 65%. Normal production time measurements yield an average of 14 minutes per unit, indicating increased work efficiency. A total budget plan for implementing relayout of IDR 5,203,000 was also prepared as part of company resource management. The results of this research show that the combination of SLP, Kanban, and Work Sampling methods can significantly increase operational efficiency, optimize facility layout, and reduce production time and costs.
Geospatial Analysis of Urban Poverty in Loralai District of Pakistan
Authors: Muhammad Tahir  , Said Qasim
Published: January 2025

This research aims to the socioeconomic factors contributing to urban poverty within 25 wards of Loralai District. The primary objective of the study is to assess the challenges faced by urban residents related to poverty and to map these poverty levels spatially using Geographic Information Systems (GIS). The primary data were collected through questionnaires. Variables including household income, loan amount received from banks, availability and type of automobile vehicle were used to assess the poverty level. These indicators were crucial in determining the overall poverty status of each ward. The findings revealed significant inequalities in poverty levels among the 25 urban wards of Loralai District (Annexure B). Wards 2,19, 20, 21, 22, 23, 24, and 25 were categorized as "very poor," with residents in these areas experiencing the most severe deprivation in terms of income and access to essential services. Wards 3,4,6, 7,11,12,16,17,18,19 and 18 were identified as "medium". In contrast, wards 1, 5, 6, 8, 9, 10, 13, 14 and 15 were classified as "rich" in comparison, showing better socioeconomic conditions, higher household incomes, and better access to services. The visual maps created through GIS allowed for the clear identification of patterns in urban poverty, making it easier to discern which wards are in need of targeted interventions. The spatial analysis of urban poverty provided by this research is crucial for policymakers, government officials, and development organizations to understand the area in need of resources and planning to alleviate poverty.