bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts économiques et sociaux d’une allocation destinée aux ménages modestes : application à un territoire d’outre-mer
Authors: Mathouraparsad Sébastien
Published: October 2024

Cet article propose une évaluation ex ante de la mise en place d’une allocation à destination des ménages modestes et qui serait réservée à de la consommation de biens et services locaux pour stimuler la production locale et l’emploi. À partir d’un modèle d’équilibre général calculable microsimulé appliqué à la Guadeloupe, nous comparons les effets d’une allocation locavore financée par octroi de mer versus TVA. Nous montrons que lorsque l’allocation est financée par octroi de mer, les effets sur la pauvreté sont meilleurs mais génèrent un ralentissement économique. Le financement par TVA conduit également à une diminution de la pauvreté mais stimule davantage l’emploi et génère une croissance pro-pauvre.
The Digital Transformation of Work
Authors: Sanyal Shouvik , G. Sathis Kumar
Published: October 2024

This chapter explores the transformative impact of automation and artificial intelligence on employment, productivity, and socioeconomic dynamics. It addresses critical questions about how automation will redefine job roles and labor markets, the essential skills for an automated economy, and how organizations and employees can adapt to these changes. The study aims to provide a comprehensive analysis of the disruptions and opportunities presented by automation, focusing on sectors likely to be affected, jobs at risk or evolving, and emerging skill requirements. Employing a mixed-methods approach, the research integrates qualitative and quantitative methodologies, including a thorough literature review, data analysis from labor market statistics, and expert interviews. The chapter is structured into key sections: an introduction outlining the significance of the topic, a literature review on existing theories and empirical studies, a methodology section detailing the research design, and a findings section presenting the analysis results. The discussion interprets these findings within broader economic and social contexts, and the conclusion summarizes key insights, policy recommendations, and suggestions for future research.
Integrating Intelligent Process Automation With Human Resource Management for Enhancing Efficiency and Strategic Decision-Making
Authors: Govindaraju Vimala , G. Sathis Kumar , Velusamy Kalyani
Published: October 2024

The integration of intelligent process automation (IPA) into diverse corporate processes has brought about a revolution in productivity and efficiency across industries as it continues to evolve. The vital role that human resources management (HRM) plays in utilizing IPA to optimize organizational advantages is examined in this research. It talks about how HRM may help with IPA implementation by emphasizing personnel planning, change management, and strategic alignment. The chapter emphasizes how important it is for HRM to deal with the issues brought on by IPA, including employee resistance, skills gaps, and workforce relocation. HRM can guarantee that workers continue to play a crucial role in the increasingly automated workplace by promoting a culture of continual learning and adaptability. This chapter also emphasizes the mutually beneficial interaction between HRM and IPA, stressing that the smooth cooperation of automated processes and human talent will be essential to the nature of work in the future.
Unleashing the Power of AI for Intelligent Investments
Authors: Nethravathi N. , Samanvitha C. , Dharmendra H. , Ananthan Sriram
Published: October 2024

The applications of artificial intelligence (AI) in finance and investing are discussed in this chapter, with a focus on stock market trading. For many years, investors have chosen stocks for trading and investment purposes by doing manual research and using their instincts. Historically, traders have chosen stocks by hand and using their intuition. Fundamental analysis, which involves examining and dissecting a company's financial statements, management, industry, and competitive landscape to ascertain its intrinsic worth, was a common tool used by stock pickers. Others employed technical analysis, which is examining historical volume and price data to spot trends and patterns. AI makes a variety of tasks easier, including as risk management, portfolio optimization, stock selection, market prediction, and automated trade execution. It is powered by data analysis and rules-based algorithms. It also highlights how AI has the ability to democratize access to wealth creation in the stock market, benefiting both experienced investors and novices looking for better trading results.
Human Evaluation in Large Language Model Testing
Authors: Dharmendra H. , Raghunandan G. , Sindhu A. N. , Samanvitha C. , Nethravathi N. , Elango Dinesh
Published: October 2024

LLMs excel in language tasks, but testing them effectively is tricky. Automated metrics help, but human evaluation is crucial for aspects like clarity, relevance, and ethics. This chapter explores methods and challenges of human LLM testing, including factors like fairness and user experience. The authors discuss a sample evaluation method and highlight ongoing efforts for robust evaluation to ensure responsible LLM development. Finally, they explore the use of LLMs in cybersecurity, showcasing their potential and challenges.
Integrating Sustainability Metrics Into Business Intelligence
Authors: Karthik Yazhini , Sujithra M. , Senthilkumar B.
Published: October 2024

This chapter suggests looking at how business intelligence and sustainability measures might be combined, with an emphasis on environmental, social, and governance (ESG) aspects. Businesses are becoming more and more aware of the need to include environmental, social, and governance (ESG) factors into their operational frameworks in the present era of data-driven decision-making. The purpose of this chapter is to examine how businesses may easily integrate ESG measures into their current business intelligence frameworks by utilising advanced analytics and AI-driven processes. In addition to enhancing sustainability initiatives, this integration reduces risks related to social and environmental challenges and promotes long-term value creation. This chapter will explain the basic ideas, challenges, possibilities, and best practices associated with integrating ESG aspects into business information. It will present tangible instances and case studies to illustrate the pragmatic implementation of these methodologies.
Leveraging AI and Machine Learning for Predictive Analytics in Business Intelligence
Authors: Sharma Mansi , Kumar Praveen , Gundewar Swapnil
Published: October 2024

In today's tech landscape, business intelligence (BI) is essential, especially with advanced technologies emerging. This study delves into the transformative potential of artificial intelligence and machine learning in predictive analytics, offering crucial insights into data. The chapter provides an extensive overview, focusing on the future of predictive analytics in BI. It highlights real-time applications, featuring practical work and case studies. Key practices for integrating AI and predictive analytics are introduced, covering data preparation, cleaning, preprocessing, feature engineering, and exploratory data analysis. Integration of ML with BI facilitates visualization, report generation, interactive dashboards, and real-time monitoring. However, manual analysis of complex datasets poses challenges, risking valuable insights. This chapter explores how ML automates the identification of patterns, extracting insights. Key challenges and advantages in integrating machine learning into BI frameworks are also discussed.
The Role of AI and ML in Shaping Predictive Analytics for Modern Business Intelligence
Authors: Thomas Riya , Sujithra M. , Senthilkumar B.
Published: October 2024

In modern business, data drives informed decision-making, with AI and BI ushering in a new era of predictive analytics essential for sustainable success. This chapter explores leveraging AI and ML for predictive analytics in BI, covering its mission, methodologies, challenges, applications, and future trends. Predictive analytics, enhanced by AI and ML, enables data-driven decisions by anticipating market trends, identifying opportunities, and optimizing resources. Key methodologies include data preprocessing, algorithm selection, model training, and evaluation, illustrated through real-world examples. Despite its benefits, challenges such as data quality, model interpretability, ethical issues, and resource constraints remain, with strategies provided to address these. Case studies in retail, healthcare, finance, and manufacturing showcase predictive analytics' impact on decision-making and efficiency. The chapter concludes by emphasizing the transformative potential of AI and ML in predictive analytics, equipping readers with the knowledge to drive success in the digital era.
Personalization and Customer Relationship Management (CRM) in AI-Powered Business Intelligence
Authors: Basak Abhishek , Sanyal Mousami , Siraji Shirin , Manimaran A.
Published: October 2024

This chapter explores specifically how Customer Relationship Management (CRM) systems are embedded within a wider web of AI-driven BI systems employed in business. It starts with the basics: a definition, a description, and, most important of all, the value of CRM to present-day business strategies. The next part discusses theoretical frameworks that drive CRM and reveals the application of AI to improve the operational efficiency of both CRM and BI applications. The chapter continues the discussion of how AI facilitates advanced customer archetypes of engagement with dynamic personalization and predictive analytics for customer churn. The empirical implementations are also highlighted concentrating on two or three types of useful machine learning algorithms and data mining techniques. Real-world case studies are discussed to provide practical examples of ways of using these technologies. Finally, the chapter lists current problems and challenges and it pinpoints the existing and potential future trends in customer relationship management.
Optimizing Supply Chain With AI-Powered BI Systems
Authors: Barala Sourabh , Manimaran A. , Natarajan Arul Kumar
Published: October 2024

This chapter focuses on how artificial Intelligence (AI)-based business intelligence (BI) systems can be used to optimize supply chains. It starts with an introduction to the basics of supply chains and supply chain management processes and then moves on to an explanation of business intelligence systems. The discussion then progresses to the application of BI systems in the supply chain specifically in the improvement of demand forecasting, inventory management, and logistics among others. Lastly, the chapter explores various ways in which BI systems can be enhanced through the incorporation of AI technologies by providing real-time analysis, prediction, and automation. Thus, the chapter reveals the positive impact and practical application of the AI-powered BI systems in the context of supply chain Optimization.
Utilizing Business Intelligence and Machine Learning in CRM Data to Reduce Customer Churn in E-commerce Platforms
Authors: Tiwari Praket Pati , Yuktha G. P. , Manimaran A.
Published: October 2024

In the ever-changing world of online business, keeping clients to achieve long-term growth and profitability is crucial. This work uses customer relationship management (CRM) data and machine learning techniques to reduce customer turnover. Initially, the previous CRM data is employed to identify clients no longer affiliated with the platform. Through analyzing prior encounters, such as reviews and purchase histories, valuable information about them preferences and complaints can be obtained. More precisely, negative comments are isolated to identify areas where the product might be improved or eliminated from the e-commerce catalogue. Furthermore, predictive analytics methods are utilized to improve client involvement and contentment. The proposed approach combines CRM data analysis with machine learning algorithms such as Logistic Regression, Decision Tree, SVM, Random Forest, and XGBoost to provide a proactive strategy for reducing customer churn in e-commerce platforms.
Using a Military-Civilian Partnership to Enhance Clinical Readiness and Sustainment for Air Force Critical Care Nurses
Authors: Armon Jennifer L. , Lucca Yvette , Salas Roman Aguon
Published: October 2024

Background

Decreases in size, capability, clinical volumes, case mixes, and complex care opportunities in military treatment facilities contribute to the atrophy of clinical skills among medical professionals in these facilities.

Local Problem

The COVID-19 pandemic resulted in a 39% decline in admissions to a military critical care unit. The decrease in patient census contributed to skill sustainment challenges.

Methods

To identify methods to combat skill atrophy, the CINAHL and PubMed databases were searched using the terms peacetime effect, military-civilian partnership, and skill sustainment. Active-duty critical care nurses stationed at a military treatment facility implemented a military-civilian partnership with a civilian medical facility for clinical skill sustainment.

Results

One year after implementation, 39 critical care nurses had completed 511 shifts, gaining clinical experiences seldom achieved at the military facility. A survey of these nurses demonstrated that 8 of 17 (47%) gained experience treating patients requiring intra-aortic balloon pumps or continuous renal replacement therapy, 6 of 17 (36%) gained experience with patients requiring a ventricular assist device, 12 of 17 (71%) acquired hands-on experience with intracranial pressure monitoring, and 14 of 17 (82%) reported vasoactive intravenous infusion manipulation.

Conclusions

This article highlights the importance of evaluating clinical practice within the military health system, developing military-civilian partnerships, and removing military-civilian partnership barriers for nurses and other health care professionals. Failure to implement military-civilian partnerships may adversely affect the clinical competency of the military nurse force.
The John Sealy Hospital Fire Evacuation
Authors: Wheeler-McAnally Rachel
Published: October 2024

Advances in fire safety and building construction have made fires in modern health care facilities uncommon and easily contained. Therefore, emergent hospital evacuations resulting from an internal fire are rare. On January 4, 2017, a fire occurred at the John Sealy Hospital, part of the University of Texas Medical Branch at Galveston, resulting in emergent evacuation of the hospital building and an adjacent office and patient care building. The internal emergency response system was quickly activated, and more than 100 patients and 200 staff members were evacuated within 27 minutes with no fire- or smoke-related injuries. Obstacles encountered during the evacuation process included difficulties with communication and confirming patient count in a timely manner. This article describes the emergent hospital evacuation during the fire, summarizes the subsequent reflections of a multiagency after-action review, and issues a call to action for further research and publication on emergency patient evacuation.
Critical Care Nursing and Mass Casualty Response During Operation Allies Refuge
Authors: Bhatta Elizabeth A. M. , DeCarli Nathaniel J. , Duffy Julie R. , McAdams Brandie
Published: October 2024

Operation Allies Refuge started in July 2021 with implications for critical care nurses, both military and civilian, serving at the US Army’s Landstuhl Regional Medical Center in Landstuhl, Germany. Cultural and logistical concerns and complications were at the forefront of care provided to Afghan evacuees during the operation and were exacerbated by a mass casualty event on August 26, 2021, when a suicide bomber attacked the Abbey Gate of Hamid Karzai International Airport in Kabul, Afghanistan. This article discusses the issues that affected care, including language barriers, supply shortages, cultural differences, mass evacuation during a pandemic, and management of the mass casualty event by the critical care team. The information is compiled into a summary of lessons learned to assist in future management of emergency evacuee care within our military and civilian health care systems.
Biofilm biofertilizer enhances bioactive compounds including antioxidant activity in hybrid rice grains
Authors: Rathnathilaka Thilini , Premarathna Mahesh , Madawala Sumedha , Seneviratne Gamini
Published: October 2024

Excessive use of chemical fertilizers (CF) in rice cultivation has adversely affected soil and crop productivity and human and environmental health. This has led to the introduction of bio-organic inputs like biofilm biofertilizers (BFBF), which have been shown to increase crop yields and soil quality with reduced CF use. However, the effect of the BFBF on rice grain quality has been understudied. The present study investigated the effect of BFBF on bioactive compounds in rice grains, including antioxidants, which are essential in protecting against diseases related to oxidative stress. The study compared two practices i.e. CF practice and BFBF practice, using six hybrid rice varieties. Harvested grain samples were analyzed for total phenolics (TPC), flavonoids (TFC), and Gamma amino butyric acid (GABA) contents, and antioxidant capacity (TAC). Results showed that the BFBF significantly (p < 0.05) increased TPC, TFC, and GABA in most rice varieties. The TAC was also significantly (p < 0.05) higher (30-200%) in the rice grains produced by the BFBF practice. In conclusion, the BFBF alters the biochemical processes of the rice plant leading to improved medicinal properties showing its potential to produce high-quality rice, which is essential to improve human health.
Effect of Music on Working Memory of Female Operators Working in a Medical Infusion Set Assembly Company
Authors: Abbasi Melika , Esmaeili Reza , Pourabdian Siamak , Shakerian Mahnaz
Published: October 2024

Aim:

With the increasing presence of individuals, particularly women, in the workplace, it becomes imperative to prioritize the well-being of employees. Numerous interventions exist to enhance working conditions, and one such intervention is the incorporation of music. This research aims to investigate the correlation between music exposure and the working memory of female operators employed in a medical infusion set assembly company.

Methods:

The study involved the assessment of 81 employees from the assembly unit of a company specializing in the production of infusion sets. The current research is an interventional study, the data of which were collected by the method of interview and cognitive tests (N-back test). The evaluation was conducted under two conditions: with background music and without background music. The research focused on assessing the working memory and productivity (task performance) of the participants.

Results:

The mean age of the participants in this study was 37 ± 33.09 years, with a mean work history of 0.2 ± 1.3 years. Furthermore, 56.7% of the participants were married. The results of the study showed that productivity was significantly better in the music-playing mode (P = 0.005). Furthermore, the results of the N-back test significantly showed an increase in correct answers in the condition of playing music (P < 0.05).

Conclusions:

The integration of background music in the workplace emerges as a beneficial factor, contributing to enhanced working memory and improved performance among female employees.
Preoperative prostate magnetic resonance imaging does not impact surgical outcomes of radical prostatectomy
Authors: Bozorgmehr Christopher K. , Wang Johnny , Gross James T. , Pickersgill Nicholas A. , Vetter Joel M. , Ippolito Joseph E. , Kim Eric H.
Published: October 2024

Objective:

We reviewed our institutional experience of radical prostatectomy with and without preoperative multiparametric magnetic resonance imaging (mpMRI) to assess the impact of preoperative prostate mpMRI on surgical outcomes of radical prostatectomy.

Methods:

We identified patients at our institution who underwent radical prostatectomy for prostate cancer (PCa) between January 2012 and December 2017 (n = 1044). Using propensity scoring analysis, patients who underwent preoperative mpMRI (n = 285) were matched 1:1 to patients who did not receive preoperative mpMRI (n = 285). Multivariable regression analysis was performed to identify factors predictive of operative time, estimated blood loss (EBL), lymph node yield, rates of complications within 30 days, and positive surgical margin (PSM).

Results:

There were no significant differences in operative time, EBL, PSM, lymph node yield, or complication rates between the two cohorts. Multivariable analysis demonstrated that preoperative mpMRI was not predictive of the measured perioperative outcomes. Significant comorbidity (Charlson Comorbidity Index ≥3) was the sole predictor of perioperative complications (P = 0.015). Increasing biopsy Gleason score predicted increased lymph node yield (P < 0.001). The probability of PSM was associated with increasing preoperative prostate-specific antigen (odds ratio 1.036, P = 0.009). Body mass index was a predictor of operative time (P = 0.016) and EBL (P = 0.001).

Conclusions:

Although preoperative mpMRI has an important role in the diagnosis and staging of PCa, it does not impact perioperative radical prostatectomy outcomes. Our findings do not support the routine use of preoperative mpMRI for surgical planning in patients already diagnosed with clinically localized PCa.
Performance and Clinical Implications of VI-RADS in detecting muscle invasion in bladder tumors: A prospective observational study
Authors: Reddy Bommireddy V. , Gali Kasi Viswanath , Chawla Arun , Singh Anshuman , Bhaskara Sunil Pillai , Hegde Padmaraj
Published: October 2024

Introduction:

Bladder cancer staging is pivotal for guiding therapeutic decisions. In this study, the primary objective was to assess the diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI), The study aimed to classify bladder tumors as either nonmuscle-invasive bladder cancers or muscle-invasive bladder cancers (MIBC) using the Vesical Imaging Reporting and Data System (VI-RADS) scoring. A secondary objective of the study focused on the accuracy of biparametric magnetic resonance imaging (bpMRI) in comparison to mpMRI.

Methods:

Thirty-three patients with bladder tumors were enrolled and underwent both mpMRI and bpMRI scoring assessments. VI-RADS scores were assigned and subsequently compared with histopathological findings posttransurethral resection of bladder tumor., Statistical measures included sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for VI-RADS scores at cutoff thresholds of ≥4 and 5.

Results:

MpMRI at a VI-RADS cutoff of ≥4 yielded an 83.33% sensitivity and 100% specificity, with a diagnostic accuracy of 90.91%. At a cutoff of 5, sensitivity was 100%, specificity was 77.27%, and diagnostic accuracy was 84.85%. bpMRI at a cutoff of ≥4 showed an 80% sensitivity and 100% specificity, with diagnostic accuracy matching mpMRI at 90.91%.

Conclusions:

This prospective analysis demonstrates that VI-RADS scoring with mpMRI provides reliable diagnostic accuracy for bladder cancer staging. mpMRI exhibits high sensitivity and specificity at a cutoff of ≥ 4, making it a robust tool for MIBC detection. bpMRI is an effective alternative in select patients. The study validates the use of VI-RADS scoring in clinical practice for effective treatment planning.
Artificial intelligence in prostate cancer: The potential of machine learning models and neural networks to predict biochemical recurrence after robot-assisted radical prostatectomy
Authors: Singh Gurpremjit , Agrawal Mayank , Talwar Gagandeep , Kankaria Sanket , Sharma Gopal , Ahluwalia Puneet , Gautam Gagan
Published: October 2024

Introduction:

This study aimed to evaluate the usefulness of machine learning (ML) and neural network (NN) models versus traditional statistical methods for estimating biochemical recurrence (BCR) in men following robot-assisted radical prostatectomy (RARP).

Methods:

Patients who underwent RARP from November 2011 to July 2022 were taken in the study. Patients with BCR were assigned to Group 2, whereas those without BCR were placed in Group 1. Preoperative and postoperative parameters, together with demographic data, were recorded in the database. This study used one NN, the radial basis function NN (RBFNN), and two ML approaches, the K-nearest neighbor and XGboost ML models, to predict BCR.

Results:

Following the application of exclusion criteria, 516 patients were deemed eligible for the study. Of those, 234 (45.3%) developed BCR, and 282 (54.7%) did not. The results showed that the median follow-up period was 24 (15–42) months, and the median BCR diagnosis was 12.23 ± 15.58 months. The area under the curve (AUC) for the Cox proportional hazard analysis was 0.77. The receiver-operating characteristic curves (AUCs) for the XGBoost and K closest neighbor models were 0.82 and 0.69, respectively. The RBFNN’s AUC was 0.82.

Conclusions:

The classical statistical model was outperformed by XGBoost and RBFNN models in predicting BCR.
Effectiveness and safety of rocuronium or nitroglycerin plus ropivacaine on pain during intravenous regional anesthesia: A double–blind randomized controlled trial
Authors: Alikhani Shiva , Modir Hesameddin , Moshiri Esmail , Kamali Alireza , Shahtaheri Seyed Yosef
Published: October 2024

Objective:

To compare the effects of adding rocuronium and nitroglycerin to ropivacaine in intravenous regional anesthesia (IVRA) on pain and hemodynamic parameters.

Methods:

This randomized controlled trial was done in 2023. Participants were 177 candidates for forearm operation surgery under IVRA selected from Valiasr Hospital, Arak, Iran. They were allocated by block randomization to three different groups, namely nitroglycerin group, rocuronium group and control group. Hemodynamic parameters were recorded before tourniquet application up to postoperative recovery time. Sensory block and motor block onset and duration and pain were also evaluated. The data analysis was carried out by IMB SPSS software 20.0.

Results:

177 Eligible patients were included in study, with 59 in each group. Time to sensory and motor block onset in the nitroglycerin group was significantly less than the other groups and the time of motor block in the rocuronium group was statistically higher than the control and the nitroglycerin groups (P<0.001). Seven participants in the nitroglycerin group experienced headache and three from the rocuronium group experienced dizziness. The side effects occurrence in the nitroglycerin group was more prevalent than in the control and rocuronium groups (P=0.009).

Conclusions:

Nitroglycerin significantly reduces the time to sensory and motor block onset, while rocuronium is more effective in prolonging the time of motor block. Although there is no difference between nitroglycerin and rocuronium respecting the pain score and opioid need administration, nitroglycerin is associated with a higher prevalence of medication side effects. Therefore, both nitroglycerin and rocuronium can be used as adjuvant for IVRA. The final choice relies on patients’ conditions and anesthesiologists’ judgment.
Erythema nodosum leprosum in a patient with lepromatous leprosy: A case report
Authors: Sunil Kumar Salkapuram , Sivannan Srinivasan , Balasubramaniyam Saranya , Elumalai Karthikeyan
Published: October 2024

Rationale:

Lepromatous leprosy is a skin condition. Erythema nodosum leprosum (ENL) aids in its diagnosis. ENL is a type- 2 immune response, whereas lepra ENL is characterized by a hypersensitivity reaction and an exaggerated immune response through a different pathway.

Patient's Concern:

A 40-year-old male patient, previously diagnosed with lepromatous leprosy, displayed painful skin lesions on his extremities.

Diagnosis:

Type-2 lepra reaction, specifically erythema nodosum leprosum.

Interventions:

The patient was initially treated with 100 mg dapsone daily and then with fusidic acid, prednisone, and other MDT agents, after development of dapsone resisitance. After type- 2 lepra reaction was lessened in just two weeks, the regimen was adjusted to prednisolone (up to 2 g daily), thalidomide (300 mg daily), minocycline (1.5 g daily), ofloxacin (1 g twice daily), and pentoxifylline (400 mg three times daily) over a six-month period.

Outcomes:

The treatment effectively reduced the type-2 lepra reaction and improved the patient's skin lesions and overall health.

Lessons:

Healthcare providers should maintain a high level of awareness regarding the symptoms and medical history associated with ENL to facilitate timely diagnosis and appropriate management strategies. It is critical to tailor treatment to each patient’s symptoms and responses for successful management. Consistent monitoring of inflammatory markers and regular follow-up appointments play vital roles in preventing complications and ensuring positive outcomes for patients with ENL.
Tai Chi and its Impact on Health
Authors: Mahalakshmi A. L. , Shaji J. C. Helen
Published: October 2024

Tai Chi Chuan, often referred to as the “great ultimate,” possesses the remarkable ability to empower those who are physically frail, uplift individuals who are ailing, restore vigor to the debilitated, and still have confidence in those who are timid. In this holistic manner, Tai Chi Chuan serves as a comprehensive practice that caters to diverse physical and mental conditions. Recent research findings underscore the varied and extensive health advantages of Tai Chi, spanning multiple health domains such as cardiovascular health, osteoporosis, rheumatic arthritis, knee arthritis, psychoneuroimmunology, diabetes mellitus, polycystic ovarian disease, obesity, metabolic disorders, and functional disability. Tai Chi was first established by Zhang, a Taoist monk, during the 12th century. It is worth noting that the gentle influence of Tai Chi on muscles and joints ensures its suitability for individuals of all ages. In addition, its affordability and minimal equipment requirements make it accessible for both individual and group practice. Over time, Tai Chi has evolved into an effective strategy for managing stress and anxiety. Often described as “movement as a form of contemplation,” It fosters a sense of tranquility and inner peace. Specific Tai Chi movements are recognized for their ability to soothe emotions, enhance mental focus, and bolster the immune system. The deliberate and unhurried pace of Tai Chi promotes relaxation, proper posture, and equilibrium, contributing to a balanced state of being. The practice of Tai Chi not only contributes to maintaining youthful vitality as one ages but also makes a substantial contribution to overall health and well-being. Tai Chi seamlessly embodies both the essence of martial arts and exercise. Tai Chi as exclusively one or the other would be an oversimplification. Instead, Tai Chi elegantly blends elements of exercise and martial intent. While it certainly serves as a form of exercise, it simultaneously encompasses martial objectives. Importantly, Tai Chi’s historical origins underscore its martial prowess, a facet that should not be overlooked. The techniques of Tai Chi were meticulously honed in the context of life-and-death combat, an aspect that practitioners should acknowledge.
Skill Training in Undergraduate Students of Prosthodontics Using the Modified Peyton’s Method
Authors: Singhania Ashika , Pisulkar Sweta Kale , Sathe Seema , Paul Priyanka
Published: October 2024

Introduction:

Dentistry schools have always used simulation training. Any professional education program that makes appropriate use of simulation can help trainees clarify their clinical abilities without running the risk of endangering patients while they are learning. The literature is currently debating whether teaching strategies work best in skill laboratories. The Peyton method, which is intended for a 1:1 student–teacher ratio, is one of these. To overcome this, the modified Peyton’s method was created, allowing each student to practice their specific skill at least once. Therefore, the objective was to assess and contrast the modified Peyton’s technique with traditional instruction for prosthodontics undergraduate students’ skill development.

Materials and Methods:

This prospective interventional study aimed to do an interventional trial in a dental context by taking alginate imprints utilizing the dental skill laboratory, and compare traditional training methods with the modified Peyton’s approach. A total of 68 students in the third BDS were split into two equal groups at random. Each group included 30 students. Group B was split up into six groups and instructed using a modified Peyton’s approach; Group A was evaluated using an objective structured practical examination (OSPE) and a posttest.

Results:

By the end of the trial, pupils who had been taught utilizing modified Peyton had improved to a score of 5 on the posttest and OSPE. When comparing the modified Peyton group’s mean OSPE score to the traditional teaching method, it was higher. The feedback obtained of the students taught using the modified Peyton’s group proved that this method helps in easy understanding of the skill.

Conclusions:

The knowledge gain seen through the pretest and posttest scores in the modified Peyton’s group was considerably higher when compared with the conventional mode of teaching. Thus, teaching pupils the modified Peyton’s approach will help them acquire new skills.
Relationship of Overweight and Obesity with Chronic Kidney Disease: A Narrative Review
Authors: Jha Roshan Kumar
Published: October 2024

Globally, chronic kidney disease (CKD) has become the foremost cause of global illness and death. Previously, it was considered a health issue in developed countries only; as of now, 4 out of 5 deaths occurring in low- and middle-income countries is due to chronic kidney disease. Obesity is defined as the accumulation of excessive body fat uncharacteristically, which may develop into impaired health. In literature, by the WHO, overweight is characterized by a body mass index (BMI) ≥25 kg/m2; and obesity is characterized by a BMI greater than or equal to 30 Kg/m2. The prevalence of obesity-associated renal disorders has become greater than before by 10-fold in recent years. Glomerulomegaly, enlargement of the glomerulus, is one of the characterized clinical features of obesity, followed by an increase in glomerular filtration rate. All prospective, retrospective cohort observational studies focused on assessing the relationship between higher BMI, overweight, obesity, and CKD were included. Articles published in Electronic databases (PubMed, CENTRAL, Web of Science, Google scholar) were analyzed for the present study. Obesity has been increasing with years, as of the data of 1975 to 2020 it has increased three times, categorically 13% of grown people aged 18 years and above were obese, 39% of adults were overweight, and the number of children under the age of 5 reported obese and, overweight was 39 million in 2020. Twenty-one studies were assessed based on the requirement, after which eight articles were included. Finding suggests central obesity has major role in impairment of renal function and resulting in CKD. It is clear that obesity has a very significant association with CKD. The present narrative review supports the hypothesis that a higher BMI of 25 or above, overweight, and obesity might be risk factors for CKD.
Exploring Adolescent Sexual Health: Knowledge, Attitude, and Communication with Parents in a Pilot Study
Authors: Rokade Vijay Premanand , Maurya Archana Tejnarayan
Published: October 2024

Background:

Adolescent sexual health (ASH) is a crucial aspect of public health, as it has a significant impact on the physical, mental, and social well-being of adolescents. Parents play a significant role in educating their children about ASH, but adolescents face many challenges communicating with their parents. This study aimed to assess the knowledge, attitude, and communication with parents of adolescents on ASH and evaluate the efficacy of the workshop method for ASH education on knowledge, attitude, and communication with their parents.

Materials and Methods:

This preexperimental study was conducted among 26 adolescents aged 13–18 years, using purposive sampling in the secondary schools of Nagpur city. The participants were divided into two groups: an experimental group (n = 13) and a control group (n = 13). A validated tool with three parts was used to collect data: demographic information, a knowledge questionnaire with 35 multiple-choice items, and an attitude scale with a communication checklist with 25 items. The workshop method was used to educate the experimental group. The data were analyzed using descriptive and inferential statistics.

Results:

The findings revealed that the adolescents had inadequate knowledge and attitudes toward ASH, and most reported poor communication with their parents. However, the workshop method was effective in improving the experimental group’s knowledge, attitudes, and communication.

Conclusion:

The study highlights the importance of addressing ASH education among adolescents and emphasizes the need for parental involvement. The workshop method effectively improved knowledge, attitudes, and communication among adolescents on ASH.
Assessment of the Need for Work-life Balance Among Dental Professionals
Authors: Parakh Himani , Makhmur Safeya , Demanna Sumant , Thosar Nilima , Rathi Nilesh , Chandra Aakriti
Published: October 2024

Background:

In the current fast-moving and dynamic professional world, establishing an optimal work-life balance has become a top priority for individuals who desire success at the workplace and in their personal lives as well. This article glimpses into the many aspects of work-life balance, discussing its importance, concerns, and some practical suggestions for achieving this balance. The objective of this study was to find out the awareness and knowledge regarding the necessity for work-life balance among dental professionals.

Materials and Methods:

A questionnaire consisting of 15 questions intended to assess the interdependency of work and nonwork day-to-day activities was asked to be filled out by the practicing dental professionals. The results were based on the responses recorded by 30 clinically active dentists from various areas of Maharashtra state.

Results:

The survey results provide a statistically nonsignificant difference in work-life balance among dentists as the statistical difference was <0.05. The inference of this study lays a foundation for ongoing discussions and actions aimed at further improving the work-life balance of dental practitioners, ultimately contributing to a healthier and more sustainable dental workforce.

Conclusion:

This study serves as an informative resource for dental professionals trying to negotiate the difficulties of today’s work-life balance while cultivating a way of life prioritizing holistic development.
Development of Neurospecific Assessment Scale for Nomophobics – An Observational Study
Authors: Chitra Jeba , Joshi Khushi Harshad
Published: October 2024

Background:

Nomophobia is a condition where people feel anxious or tense when they need to disconnect from their phone or other Internet-connected devices. Because of this elevated level of dependence on modern gadgets to offload the cognitive demands of life, anxiety develops when they are expected to be detached from it. The role of neurospecific domains such as cognitive flexibility, memory, attention, information processing, inhibitory control, and reward perception has previously been studied in nomophobics. However, there is no tool developed yet that quantifies the affection of these neurospecific domains in nomophobics.

Objective:

The objective of this study was to develop a scale for the assessment of “Neurospecific Domains” (in terms of memory, attention, cognitive flexibility, inhibitory control, information processing, and reward perception) among nomophobics.

Methods:

The neurospecific assessment scale for nomophobics (NSASN) was developed using a multistep method which included conceptualization and item generation followed by one round of expert validation of the item and of the scale. The content validity index was used to validate the various domains in the scale.

Results:

The computed content validity final score for Round 1 of the scale was found to be 0.79.

Conclusion:

The NSASN was developed to assess neurospecific domains among nomophobics and achieved a statistically satisfactory content validity.
Utility of Hemogram-based Parameter in Predicting Hospital Stay in Liver Cirrhosis: A 2-year Prospective Observational Study
Authors: Shah Param , Reddy Harshitha , Patil Rajvardhan , Kadam Abhinav , Kumar Sunil , Acharya Sourya , Agarwal Sachin , Vohra Mona
Published: October 2024

Introduction:

Hospitalized cirrhosis patients are a major financial burden on health-care systems. In this study, we attempted to evaluate the regular laboratory parameter like absolute eosinophil count (AEC), in liver cirrhosis in relation to length of hospital stay and severity grading systems such as the Child–Turcotte–Pugh (CTP) score and the model for end-stage liver disease (MELD).

Materials and Methods:

A prospective observational study was done in patients at a rural tertiary care hospital in central India, from October 2019 to September 2020. Calculation of AEC was done by automated complete blood counts in hemogram. Demographics of the patient, laboratory investigations, and outcomes of hospital stay were taken into consideration in the study. To identify predictors of hospital stay, a multivariate Cox regression analysis was used.

Results:

Among hemogram, with a cutoff value of ≤138, the AEC was found to be a significant predictor of lengthy hospital stays (≥7 days), with a 63.70% likelihood of properly predicting such stays. If AEC ≤138, then there was a 69.80% probability of prolonged hospital stays. Distribution of CTP score was comparable between hospital stay duration, i.e. <7 days and ≥7 days. Proportion of patients with MELD score with ≤9, was significantly higher if duration of hospital stay was <7 as compared to hospital stay duration ≥7 in MELD score 10-19.

Conclusions:

In hospitalized cirrhotic patients, among the hemogram, the AEC may be used as a low-cost warning indicator for clinical outcomes such as hospital stay.
Effect of Backward Walking on Treadmill with Inclination in Individuals with Forward Head Posture: A Comparative Study
Authors: Kamble Sanjivani , Kothari Parita , Kale Pratiksha , Joshi Jyoti , Kadam Aarti , Palekar Tushar J
Published: October 2024

Background:

Forward head posture (FHP) is one of the most common postural abnormalities found in undergraduates (18–30 years), with a prevalence rate of 73%. If the cervical spine is held in a protracted position, such as hyperextension of the upper cervical spine (C1-C3) and flexion of the lower cervical spine (C4-C7), it can cause changes in head posture, eventually leading to FHP.

Aims:

This study aimed to determine the effect of backward walking (BW) on the surface and on treadmill with inclination in individuals with FHP.

Objectives:

The objective of this study was to compare the effect of surface BW and BW on treadmill with inclination on the craniovertebral angle (CVA) and gait outcomes in individuals with FHP.

Materials and Methods:

Sixty-two participants were recruited and randomly assigned to the surface BW group (n = 31) and BW on treadmill with inclination (n = 31). Participants fulfilled the pre- and postassessment with a 2 weeks (three times per week) intervention of BW in conjunction with conventional exercises. The CVA was measured using Markus Bader ruler software. Gait outcomes were assessed using Neurocom Balance Master, walk across component was selected.

Results:

The present study implemented statistical tests such as paired t-test and unpaired t-test for the recorded data.

Conclusion:

BW has shown a significant difference in the CVA and some components of gait outcomes in within the group analysis, whereas in between the group analysis, there is a significant difference in some gait outcomes.
Neonatal Giant and Open Neural Tube Defects: Challenges and Lesions Learnt
Authors: Sharma Nitin , Sharma Shipra , Sharma Mini , Sharma Hemant
Published: October 2024

Abstract

Background:

Management of large/open neural tube defects (NTDs) is challenging and outcome is demanding.

Aims:

To analyze the outcomes in giant NTDs.

Materials and Methods:

The data between June 2017 and September 2022 were analyzed. Those with incomplete data, not giving consent or lost to follow-up, were excluded. All underwent closure using primary closure, Z plasty, or rhomboid flap. Dura closure was achieved with native dura augmented with thoracolumber fascia. The outcome was analyzed with respect to duration of surgery, blood loss, requirement of Z plasty for closure, wound infection, blackening of the flaps, cerebrospinal fluid leak, and features of sepsis.

Result:

164 out of 243 cases formed the study group. Mean age at presentation was 4 days (range 0–28 days). Mean duration of surgery was 2 days (range 1–3 days). Mean operating time was 1.15 hours (range 0.45–3.15 hours). Hydrocephalous was present in 146 cases and all required ventriculo peritoneal shunt. Lower limb paraplegia and spasticity were present in 63 and 23 cases. Skin closure was achieved by primary closure in 23, double Z plasty in 76, and rhomboid flap in 65 cases. Wound infection and blackening of flap were seen in 13 and 1 case in double Z plasty and 6 and 7 cases in rhomboid flap group, respectively (P = 0.7). cerebrospinal fluid leak was seen in 8 cases. Wound dehiscence and sepsis were seen in 10 and 28 cases, respectively.

Conclusion:

Management of large defect requires adequate planning. cerebrospinal fluid shunting and flap/Z plasty are often required.