bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge-Driven Decision Making in Earth Monitoring Systems
Authors: B. Bharathi , P. T. Kalaivaani , V. Shree Gaayathri , M. Rajendiran
Published: December 2023

Earth monitoring systems are of crucial significance to the arena nowadays as they offer us essential data on this planet's environment, sources, and ecosystems. In earth monitoring structures, information-driven selection making is the process of utilizing facts-pushed techniques to inform selections regarding the real-time monitoring and control of natural disasters and other environmental phenomena. These objectives span the spectrum of decision-making, starting with the pursuit of informed choices that are grounded in accurate data and bolstered by objectivity. The capability of modeling strategies and this approach fosters collaborative problem-solving by facilitating the sharing of data and insights among stakeholders, aligning common objectives and shared expertise to inform the decision-making process, ultimately elevating the quality and efficiency of decisions in response to evolving environmental challenges. In conclusion, understanding extraction from earth monitoring structures is an essential system for assisting decision making via using statistics-driven techniques.
Neuro-Inspired Algorithms for Earthquake Monitoring and Prediction
Authors: R. Priyanka Pramila , Murugaraj Sadish Sendil , Kumar Sunil , S. R. Balaji
Published: December 2023

Neuro-inspired algorithms are a powerful device that can be used for earthquake monitoring and prediction. These algorithms can offer precious insights into the conduct of seismic activities and could cause better detection and caution structures. The goal of this chapter is to offer a concise evaluation of cutting-edge research on using neuro-inspired algorithms for earthquake tracking and prediction. In particular, the chapter will discuss the latest traits in information-based procedures and deep studying algorithms, in addition to the challenges and possibilities for advancing research in this area. Furthermore, capacity programs and regions of research will be discussed which could enjoy the use of these algorithms. Ultimately, this chapter can provide an impetus for the broader use of such algorithms and similarly progress in earthquake-related studies.
Well-Being and Mental Health Initiatives for Students in Universities
Authors: Aloka Peter J. O. , Omare Justine Momanyi , Owuor Emmily Achieng , Okongo Calvince , Owino Joshua
Published: December 2023

There are increased mental health and well-being concerns among students at universities worldwide. By adopting a conceptual review of literature, this chapter analyzed well-being and mental health initiatives for students in universities. On the bases of the literature review in this chapter, it is concluded that there is need for supportive work environments, mental health in universal health coverage, creating opportunities for student engagement, mentorship at various academic departments building social networks, and finally, individual coping strategies are also useful in enhancing well-being and mental health of academic staff at universities. It is recommended that universities should develop holistic mentorship for students so that this can take care of all aspects of their lives.
Personalized Recommendation Method of E-Commerce Products Based on In-Depth User Interest Portraits
Authors: Li Jingyi , Bao Shaowu
Published: December 2023

In dynamic e-commerce environments, researchers strive to understand users' interests and behaviors to enhance personalized product recommendations. Traditional collaborative filtering (CF) algorithms have encountered computational challenges such as similarity errors and user rating habits. This research addresses these issues by emphasizing user profiling techniques. This article proposes an innovative user profile updating technique that explores the key components of user profile (basic information, behavior, and domain knowledge). An enhanced kernel fuzzy mean clustering algorithm constructs a dynamic user portrait based on domain knowledge mapping. This dynamic portrait is combined with e-commerce personalized recommendation to improve the accuracy of inferring user interests, thus facilitating accurate recommendation on the platform. The method proposed in this article greatly improves the overall performance and provides strong support for developing smarter and more personalized e-commerce product recommendation systems.
A Web Semantic-Based Text Analysis Approach for Enhancing Named Entity Recognition Using PU-Learning and Negative Sampling
Authors: Zhang Shunqin , Zhang Sanguo , He Wenduo , Zhang Xuan
Published: December 2023

The NER task is largely developed based on well-annotated data. However, in many scenarios, the entities may not be fully annotated, leading to serious performance degradation. To address this issue, the authors propose a robust NER approach that combines a novel PU-learning algorithm and negative sampling. Unlike many existing studies, the proposed method adopts a two-step procedure for handling unlabeled entities, thereby enhancing its capability to mitigate the impact of such entities. Moreover, this algorithm demonstrates high versatility and can be integrated into any token-level NER model with ease. The effectiveness of the proposed method is verified on several classic NER models and datasets, demonstrating its strong ability to handle unlabeled entities. Finally, the authors achieve competitive performances on synthetic and real-world datasets.
E-Commerce Review Sentiment Analysis and Purchase Intention Prediction Based on Deep Learning Technology
Authors: Ma Xiaoye , Li Yanyan , Asif Muhammad
Published: December 2023

This study proposes a deep learning-based analytical model to conduct an in-depth study of the relationship between consumer trust, perceived benefits, and purchase intention. This model combines natural language processing and sentiment analysis, using the BERT-LSTNet-Softmax model to extract textual features in reviews and perform temporal predictions of consumer sentiment and purchase intention. Experimental results show that this model achieves excellent performance in the e-commerce field and provides a powerful tool for in-depth understanding of consumer purchasing decisions. This research promotes the application of deep learning technology in the field of e-commerce, helps to improve the accuracy of consumer purchase intentions, and provides more support for the development of the e-commerce market and consumer decision-making.
Embracing the future: The use of artificial intelligence (AI) in scientific paper writing
Authors:  Jayasena Dinesh D.
Published: December 2023

No abstract available
Insights of Circular economics practices in rice cultivation and processing - a review
Authors: Bandara K. M. N. T. K. , Kavindi G. A. G.
Published: December 2023

Reusing waste through various activities and efficient and effective use of resources have led to the circular economy as a further growth opportunity. The circular economy has spread in various directions like agriculture and industry. The main focus of circular economy is to minimize or eliminate the use of non-renewable inputs in a production system and to maximize or optimize the reuse of these materials within the same system. In addition, circular agriculture is expected to reduce environmental impacts through soil regeneration and input use. Activities in rice cultivation include sowing, fertilizing, watering, and harvesting, and these activities can be done using biological and other agricultural methods in an environmentally friendly way instead of chemical fertilizers, pesticides, and herbicides, and further minimizing the accumulation of waste. Burning rice straw and husks emits lot of CO2 into the environment. However, these can be used as raw materials for various industries. Rice residue is an excellent source of nutrients and beneficial for human health. Thus, circular economy methods can be used in rice cultivation by cultivating more productive and suitable rice varieties, reducing the amount of waste released into the environment in various ways, and using discarded waste as raw materials for industries. This study focuses on determining the applicability of circular economy methods to rice cultivation and processing. Accordingly, it appears that in the rice industry, circular economy methods are applied to reduce the release of unnecessary air and waste into the environment and effectively reuse the waste. This will create an eco-friendly and safe environment.
Myristica fragrans, Coriandrum sativum, Coscinium fenestratum, and bee honey important in Ayurvedic medicine: a review
Authors: Weerasinghe M. G. W. K. , Dahanayaka N.
Published: December 2023

Covid-19 is a worldwide pandemic disaster that has been steadily rising mortality rates and reported cases. Until today, scientists have struggled to find a therapy that is successful to control Covid-19. It has been a tough undertaking due to the mutagenic character of the viral agent. In this situation, it is necessary to concentrate on alternative methods to boost the immunity. One of the world's oldest medical systems, Ayurvedic medicine, dates back thousands of years. Myristica fragrans, Coriandrum sativum, Coscinium fenestratum and bee honey are four main ingredients that frequently utilized in Ayurvedic heeling system, especially for immunity boosting purposes. This review emphasises the medicinal properties of the mentioned ingredients in the Ayurvedic medicinal system. The goal of this review is to encourage conservation by enhancing utilization.
Misconceptions and their influence on chicken egg consumption pattern, buying behavior and attitudes among the urban and rural communities in Western Province of Sri Lanka
Authors: Ariyachandra A. D. S. P. , Alwis G. I. S. , Bandara G. R. M. L. , Mutucumarana R. K. , Basnayakea B. M. R. L.
Published: December 2023

Misconceptions and their influence on chicken egg consumption pattern, buying behaviour, and attitudes among the urban and rural communities in Western province of Sri Lanka were investigated. A total of 690 respondents representing Colombo, Gampaha, and Kalutara districts were interviewed using a pre-tested questionnaire. Chi-square analysis and the descriptive statistics were used to analyze the data. According to the results, 67.1% of respondents believed that the village chicken eggs are more nutritious than the commercial chicken eggs. The majority (95.4%) did not accept the fact that the brown eggs are nutritionally sound than the white shelled eggs. Of the total respondents, 46.2% trusted that the daily consumption of chicken eggs can lead to hypercholesterolemia and increases the risk of cardiac disorders. Information derived from the general public and social media were identified as the main sources of the misconceptions discussed. In conclusion, of all misconceptions tested two misconceptions: (1) the eggs from village chicken are nutritious than the commercial chicken eggs and (2) the chicken eggs when consumed daily can increase the risk of cardiac disorders, do exists. The study further concluded that the majority of the participants are willing to change their attitudes if it is guaranteed that both the village and commercial chicken eggs are coequally nutritious, and both white and brown eggs are safe to eat daily, infertile, and coequally nutritious.
Effect of incorporating Lacticaseibacillus rhamnosus GG and arrowroot (Maranta arundinacea) powder on physicochemical properties of buffalo milk curd
Authors: Dassanayake D. M. S. N. , Rasika D. M. D. , Kodithuwakku K. A. H. T. , Weerathilake W. A. D. V.
Published: December 2023

Syneresis is one of the common textural quality defects found in traditionally prepared buffalo milk curd (meekiri). The current study aimed to determine the effect of incorporating Lacticaseibacillus rhamnosus GG (LGG) and arrowroot (AR) powder alone and in combination on the physicochemical properties of buffalo milk curd over refrigerated storage. Four buffalo milk curd formulations were prepared: control curd (without probiotic and prebiotic), probiotic curd (with 2% LGG), prebiotic curd (with 3% AR powder), and synbiotic curd (with both 2% LGG and 3% AR powder). The syneresis, pH, titratable acidity, and textural properties (hardness, cohesiveness, gumminess, and adhesiveness) were evaluated over the refrigerated storage at d 1, 4, 7, and 10. The addition of LGG resulted in decreased syneresis and acidity, and increased hardness, gumminess, and chewiness. In contrast, AR positively affected decreased syneresis and acidity. LGG and AR powder in combination significantly lowered syneresis however negatively affected on the hardness, gumminess, and chewiness.
Advancement of microcontroller-based fire suppression system for enhanced safety in sugar cane plantations
Authors: Dissanayake H. C. , De Silva C. S. , Hapugoda K.
Published: December 2023

The occurrence of accidental fires in sugarcane plantations is a significant cause of pre-harvest loss in the sugar industry, particularly during arid seasons. This paper introduces the conceptualization and implementation of a microcontroller-based prototype system for mitigating accidental fires in sugar cane plantations. The proposed system encompasses two distinct subsystems: the field monitoring and the fire control unit. The Field monitoring system, deployed within the sugarcane field, assumes responsibility for fire detection via smoke detectors, infrared detectors, as well as carbon dioxide and carbon monoxide detectors, which are accompanied by a fire extinguishing mechanism. Conversely, the fire control unit, installed at the fire brigade office, establishes wireless communication with the field monitoring system through the global system for mobile communication (GSM) network. Upon detecting a fire, the microcontroller promptly dispatches a fire alert to the fire brigade while simultaneously activating water pumps to suppress the fire until the brigade arrives to fully extinguish it. Furthermore, the fire control unit triggers the fire alarm and exhibits the global positioning system (GPS) coordinates of the burning field to facilitate precise localization. The proposed system uses the Arduino-Mega and Arduino- Leonardo microcontroller platforms and is programmed using the C++ programming language in Visual-Studio-Code software and the Arduino integrated development environment. Designed prototype can detect fires and alert the fire brigade in less than twenty seconds and activate water pumps in less than one second after fire detection.
The Influence of Customer Perceived Risk on Online Purchasing Intention: with reference to Fast fashion Retail industry in Sri Lanka
Authors: Lakchan U. G. C. , Samaraweera G. C.
Published: December 2023

Consumers' lifestyles and behavioral habits have altered substantially since the advent of digital marketing platforms, which has a big influence on consumption. More significantly, despite the fact that internet buying has many benefits, some consumers are a little more skeptical about it. According to the literature, there are several restrictions that affect consumers' purchasing intentions for online consumption of retail fashions and a nation like Sri Lanka is not particularly strong for online transactions or online shopping. This study is primarily based on online consumers’ behavioral shopping intentions. The independent variable, customer perceived risk is comprised with Financial Risk, Product Risk, Information Security Risk, Time Risk, Psychological Risk and delivery Risk. This study uses the positivistic research paradigm and deductive approach. Accordingly, purposive sampling technique was used by delivering the 400 questionnaires to internet users in Colombo district. Accordingly, data were analyzed using SPSS software after removing outliers. To evaluate the data, the study employed descriptive statistics, correlation analysis, and regression analysis. According to the findings, Time risk was found to be not significant for purchasing online. Delivery Risk and Information security risk were the top-ranked determining variables among the major elements. Consequently, by reducing their perceived risk, this research assists in educating all dealers on how to draw clients to their online platform.
Does the Leadership Style Affect Team Members’ Project Satisfaction: Case Study of Sri Lankan IT Sector
Authors: Kodithuwakku D. S. A. W. , Korale-Gedara P.
Published: December 2023

Effective teamwork is an indispensable factor in the achievement of IT project success. Effective leadership is a key contributor to team member satisfaction, ensuring their active involvement and contentment within the IT project, all of which collectively lead to favorable project outcomes. This study assessed the effect of leadership style on team members' project satisfaction in IT companies. The study collected data from 81 IT team members working in ten IT companies from a population of over 35 IT companies. The results showed that the transactional leadership style had the greatest impact on team members' satisfaction with project completion. Interestingly, the study also found that the most prominent leadership style in the IT industry in Sri Lanka is the transformational leadership style. This study highlights the importance of selecting the right leadership style to ensure the success of IT projects.
Effect of Airport Efficiency Dimensions on International Tourists’ Satisfaction in Sri Lanka; with Reference to Bandaranaike International Airport
Authors: Madhushanka P. K. I. , Nawarathnae A. M. D. B. , Harshani G. H. V.
Published: December 2023

Bandaranaike International Airport plays a significant role rather than other international airports in Sri Lanka. Maintaining service efficiency and quality of the service have been challenged when it comes to passenger service delivery for last few years. It was a well-known fact that Bandaranaike International Airport has been listed out to the most inefficient international airports in South Asian Region. By using quantitative research approach and deductive reasoning the researcher has incorporated SPSS with Smart PLS statistical packages for the data analysis. Using simple and multiple linear regression analysis, the nature of the relationships has been measured between airport efficiency dimensions and international tourist satisfaction. 150 foreign tourists have participated for the sample and as for the findings, the researcher has found that, all the hypotheses are accepted denoting that relationships between independent variables and dependent variable are positive relationships and security is the most influential airport efficiency dimension.
Examining the Role of Inflation Moderation in Mitigating the Impact of Crude Oil Prices on Indonesia's Sharia Stock Market
Authors: Noval Noval , Nur Syamsu  , Syaakir Sofyan  , Rifai Rachmawati A.
Published: December 2023

This study investigates the impact of crude oil prices on Indonesia's Sharia stock market, considering inflation as a moderating variable to address existing debates in prior research. Utilizing data from June 2011 to December 2021, including the Indonesian Sharia Stock Index (ISSI), World Texas Intermediate (WTI), and inflation, the study employs Moderated Regression Analysis (MRA) to uncover significant positive correlations between crude oil prices and the Sharia stock market. The findings highlight the moderating role of inflation, indicating that the market weakens when crude oil prices rise alongside inflation and strengthens in the absence of inflationary pressures. Practical implications suggest portfolio diversification for investors to manage associated risks. The study contributes theoretically by introducing additional moderator variables and offers empirical insights, yet acknowledges limitations, advocating for further research to deepen the understanding of the complex relationship between crude oil prices, inflation, and the Sharia Stock Market in Indonesia.
Bayesian Analysis of Threshold Autoregressive Model with First Order Autoregressive Innovations
Authors: Ojo O. O.
Published: December 2023

Financial assets exhibit dramatic changes in behaviour. This work examined a two-regime Threshold autoregressive (TAR) models when the innovations follow a first-autoregressive order process. The Bayesian method is proposed to build in the linear first-order autoregressive process with identical distributed innovations. The practical usefulness of this method is demonstrated with simulated and real-life data using U.S.A quarterly real GDP as an example. In simulation experiments and real life example, an increase in first order process parameter, ρ value leads to better estimates in the proposed model. Also, the proposed model was compared with TAR model where the disturbance term does not exhibit regime switching. The proposed model performed well than the traditional TAR model using the simulated and real life data. An increase in first order process parameter, ρ will lead to better estimates and forecast. Hence, the proposed model performed well.
Career Perception on Banking Industry among Management Undergraduates
Authors: Zamma M. W. F. , Galhena B. L.
Published: December 2023

Career perception especially among management graduates is a vital phenomenon that is under exploration among academics. However, no previous research has been done on exploring this phenomenon in Sri Lankan context. Thus, addressing the knowledge gap in the literature, the main purpose of this study is to identify the significant factors determining career perception on banking industry among state university management undergraduates in Sri Lanka. Based on the extant literature four independent variables namely social status, physical working conditions, financial benefits, career growth were identified to address the research question of the study. The sample was derived from 152 third and final year management students from university of Ruhuna. Self-administered questionnaires were used to collect the necessary data. Multiple regression analysis was used to test the hypotheses. The study found that social status, physical working conditions, and financial benefits are significant factors explain the career perception on banking industry among respondents. These findings particularly would be beneficial to undergraduates and career counseling institutions as well as for the society at large.
Examining the Influence of Rural Road Network Development on Livelihood - A Case Study on Kilinochchi District
Authors: Ravikumar Nirubikaa , Banujan Kuhaneswaran , Aginthini A.
Published: December 2023

TThe population of Sri Lanka, an island country in the Asian zone, is projected to be about 22 million in mid-2030. In Sri Lanka, the transportation economy plays a significant role. Roads provide the benefits to enhance the socio-economic conditions of communities. Roads are linked to locations, individuals, and social and economic activities. Better road conditions promote better connections between rural and social and economic activities. While rural road investment is widely believed to reduce poverty, there has been little systematic analysis or evidence on whether rural roads affect people experiencing poverty or the impact. After the war ended in 2008, the government carried out some road projects nationwide. Kilinochchi district is also not exceptional. This study focused only on rural roads and how they relate to livelihood. A questionnaire survey was conducted, covering four dimensions; impact on (i) Transportation Services, (ii) Traveling Patterns, (iii) Village Profile, and (iv) Income and Welfare before and after the road projects in Kilinochchi District. One hundred twenty-two families were selected for the research. For the change in the aesthetic value of the village after the road development, none of the respondents rated it as reduced or reduced dramatically. Around 100 respondents accepted that school connectivity has significantly improved after road development. The study proves that road development positively impacts people’s social and economic practices.
Breast Cancer Detection using Image Processing and Machine Learning: A Comprehensive Review and Improved Segmentation Approach
Authors: Erandika D. D. H. , Piumi Ishanka U. A.
Published: December 2023

Breast cancer stands as one of the most prevalent health concerns for women. Early detection of breast cancer can significantly improve the chances of survival. In developed countries, more than 19.9% of women will die per year due to breast cancer. Regular breast cancer screening is an important way to detect cancer early. Image processing techniques are highly used for different types of cancer detection applications with medical screening. Segmentation of the breast tumor region is a critical step in image processing related to this manner. Lots of research work can be found on developing ways for detecting breast cancers. However still, there is a need for a standard and robust cancer region segmentation method. Right cancer region segmentation is significant for better feature extraction and better classification. This study presents a comprehensive literature review about technologies used with image enhancement and tumor segmentation. Further, the study proposes a robust approach to image enhancement and cancer region segmentation for breast cancer detection using image processing techniques and machine learning. In this work, mammograms are enhanced using Contrast Limited Adaptive Histogram Equalization and denoised using the Median blurring filter. This study enables an effective image segmentation approach with two stages: removing the background using thresholding, tumor region segmentation using a combination of thresholding, and Canny edge detection. Segmented tumor region’s features are extracted using the Gabor filter. Here the accuracy of the approach is compared with three main machine learning classifiers: Decision Tree, Random Forest, Multinomial Logistic Regression and mammograms are classified into three classes (malignant, benign and normal). Finally, an ensemble approach is proposed using the hard voting mechanism to improve the accuracy. With the dataset of mini-MIAS this proposed approach achieved 78.89% accuracy. Results demonstrated that the proposed breast cancer detection approach improves the performance of segmentation breast tumor regions.
Towards a More Intuitive Sinhala Chatbot: Leveraging NLU for Enhanced Intent Identification and Entity Extraction
Authors: Avishka Pasan , Ravikumar Nirubikaa , Banujan Kuhaneswaran , Gunasinghe Hansi
Published: December 2023

In the fast-paced and ever-changing world of conversational AI, chatbots have become essential interfaces for user interactions in various domains, especially when supporting different languages. This study delves into the development of chatbots and their ability to understand language, explicitly focusing on the Sinhala language. The effectiveness of two platforms, Rasa NLU and Microsoft LUIS, were compared in identifying and extracting intents. Both platforms showed proficiency, but Rasa stood out for its flexibility, cost-effectiveness and accurate intent recognition. A case study in the restaurant domain was conducted to demonstrate the system’s capabilities. An architecture was created that can interpret Sinhala expressions and analyze intents using the NLU engine. The study defined four intents: Food Ordering, Get In Touch, About Restaurant and None. The findings highlight how this architecture has the potential to accurately interpret intents during chatbot development regardless of the conversational language used. This research aims to contribute insights to developers, linguists and AI enthusiasts involved in language-specific chatbot development by emphasizing its promises and challenges.
Agnikarma and Dashamoola Kwatha in the Management of De Quervain’s Tenosynovitis – Case Series
Authors: Ganatra Riddhi , Joshi Foram , Dudhamal Tukaram Sambhaji
Published: December 2023

ABSTRACT

De Quervain’s tenosynovitis is a common painful orthopedic entity that involves a thickening of retinaculum sheaths of tendons, which covers the first dorsal compartment of the forearm. This study is to explore noninvasive Ayurvedic management for De Quervain’s disease. In this series of cases, Ayurveda management of four diagnosed cases of Quervain’s disease (Snayugata Vata) was found to be effective. All patients were treated with four sittings of Agnikarma by Shalaka (~thermal cauterization) at the interval of 7 days. Dashmoola Kwatha 20 ml orally twice a day empty stomach for 1 month was prescribed to each patient. Results showed significant improvement in pain relief and functional movement of the thumb was achieved in all four patients. The quality of work of all four patients was not affected after 18 months of treatment, and they are now living symptom-free and without any recurrence. Based on this case series, it can be said that parasurgical management along with adjuvant Ayurvedic drugs showed a promising role in the management of De Quervain’s disease.
Management of Acne Vulgaris with Homeopathic Treatment – A Case Series
Authors: Rath Padmalaya , Mondal Shirsendu , Thakur Tushita
Published: December 2023

ABSTRACT

Background:

Acne Vulgaris is a multi-factorial chronic inflammatory condition, in relation to sebum production of hair follicles under the action of sex hormones.

Methods:

This is a case series of five patients suffering from acne vulgaris were treated with homoeopathy successfully at the Dermatology OPD of DDPRCRI (H), Noida (UP), India. Global Acne Grading Score (GAGS) was used to assess clinical severity of acne. Majority of study population were in the age group of 18 to 40 years.

Results:

Face was the commonest site and pustules& cystic were the commonest form of acne at baseline. Three cases were observed to be of moderate and two were severe acne as per GAG Score at baseline. The selection of medicine was done on the basis of homoeopathic individualization, considering location, sensation, modalities (aggravation and amelioration factors) and concomitants of the symptoms in each case.

Conclusion:

After treatment all cases were observed to be of mild acne as per GAG Score. Homoeopathic medicines Calcarea Carb, Mercurius Sol, and Natrum Mur were found useful.
Ayurvedic Intervention in the Management of Premature Menopause
Authors: Soni Neeraj , Yadav Minu , Mangal Gopesh
Published: December 2023

ABSTRACT

Menstruation is a cyclic physiological process of uterine bleeding due to the shedding of the endometrium. A normal menstrual cycle plays an essential role in maintaining the woman’s health status during reproductive age. Premature menopause is defined as the cessation of menstruation at or below the age of 40. Premature ovarian failure (POF) is defined as when an ovarian failure occurs before the age of 40. The prevalence of premature ovarian insufficiency is estimated at 1% in the general population. The present case report documents the efficacy of Ayurvedic medication in a female aged 24 years who had commencement of menstruation after 4 years of amenorrhea postovarian cystectomy. The left ovary of the patient was removed during the surgery, and a small hypoplastic right ovary and uterus were visible in the ultrasonography. The levels of luteinizing hormone, follicle-stimulating hormone, and estradiol hormone in the patient were equivalent to postmenopausal individuals. She was also suspected of POF. The Ayurvedic management included Shamana Aushadh, Yoga, and Pathya Ahara Vihara for 3 months. The menstruation was visible after 1 month of Ayurvedic medication. The follow-up was done for 3 months. A marked improvement was also noted in the general health of the patient along with regularity in the menstrual cycle each month.
Analysis of causes of mortality in a tertiary care hospital according to the tenth revision, International Classification of Diseases
Authors: Das Bishnu Ram , Deori Manas Protim , Borah Abhishek , Kakoti Gitali
Published: December 2023

Background:

The statistics on causes of mortality are essential for planners, administrators and medical professionals in undertaking appropriate curative and preventive measures for various health problems.

Aims:

To evaluate the causes of death as per the International Classification of Diseases, Tenth Revision (ICD 10) amongst patients who died in Jorhat Medical College and Hospital (JMCH).

Materials and Methods:

A facility based retrospective analysis of death records was done as per ICD 10 in JMCH, Assam, from January 2020 to December 2020.

Results:

A total of 2373 deaths occurred in JMCH during the study period, and amongst them, 67.4% were males. Majority 17.8% of deaths were in the age group of below 1 year and the least 0.5% were in the age group of 1–4 years. The first leading cause of medically certified deaths was diseases of the circulatory system (I00 I99) 16.9%, followed by symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified (R00 R99) 14.9%. In the diseases of the circulatory system, death due to hypertensive diseases was the most common cause at 46.6%. Certain conditions originating in the perinatal period group were the leading cause of mortality, 79.9% in < 1 year and 27.3% in 1–4 year age group of children. While diseases of the circulatory system group were the leading cause of mortality, 24.1% in 45–54 years, 29.5% in 55–64 years, 26.2% in 65–69 years and 29.2% in more than 70 years.

Conclusion:

Our findings on various causes of death will help decision makers in formulating operational and strategic plans and making decisions.
Bridging the cancer care gap and inequities in radiation treatment in India: A narrative review
Authors: Gupta Nidhi , Chugh Yashika , Prinja Shankar
Published: December 2023

Cancer is the fifth leading cause of death in India, yet India's cancer care landscape remains fragmented. In this paper, we review the current state of access to radiation therapy and the inequities involved, as well as identify potential solutions to improve access to radiation therapy in cancer. We undertook this narrative literature review, which encompassed database searches (PubMed, Embase, Scopus) and scrutiny of the grey literature (Google Scholar, OpenGrey), using the search terms: “cancer care access disparities,” “radiotherapy accessibility challenges,” “out-of-pocket expenditure in cancer treatment,” “value-based cancer care models,” “cost-effective radiotherapy strategies,”and“resource-limited cancer care solutions.” Our search strategy focused on articles addressing barriers to radiation treatment, inequities in radiation treatment equipment, and optimal radiation techniques in resource-limited settings in India, thereby identifying key challenges and potential interventions. Of the 1933 articles initially retrieved, we included 46 for the preparation of this review. Among the various modalities utilized for the management of cancer, radiation treatment is the most resource-intensive, requiring expensive and dedicated infrastructure. Scarce infrastructure, perpetuating inequities across geographical regions and socioeconomic strata, is responsible for inequities in access to radiation treatment in India. With the advent of newer radiation techniques requiring specialized equipment for the delivery of advanced radiation treatment, these inequities widen in low- and middle-income countries such as India. The challenge lies in providing affordable and equitable radiation treatment without compromising on quality within India's diverse and populous expanse. Bridging these gaps mandates the improvement of the existing infrastructure, fostering local production of quality medical equipment like linear accelerators, establishing and adhering to country-specific standardized treatment guidelines based on volumes, optimally utilizing available equipment like indigenous telecobalt machines and cost-effectiveness evidence, establishment of rural cancer care centers, optimization of private sector capacities and economic support through national insurance schemes.
Association between coronary artery calcification score and air pollutant exposure: An explorative hospital-based study using microenvironmental modeling
Authors: Viramgami Ankit , Madia Mehul M. , Mansuri Moinuddhin , Rana Yashpal , Sheth Megha , Patel Samir , Garachh Millin , Vyas Pooja , Kotak Preet , Patel Niyati , Patel Dinesh , Balachandar Rakesh
Published: December 2023

Background and Objective:

This study aimed to explore the association between coronary artery calcification and air pollutant exposure from all potential sources using microenvironment modeling.

Methods:

The present study recruited consecutive consenting patients, who visiting the radiology division of the tertiary cardiac specialty hospital for coronary artery calcification (CAC) evaluation, after obtaining institutional human ethics approval. Fifty participants each with CAC scores <100, 100–399, and ≥400, categorized as low, intermediate, and high risk, respectively, were recruited. Details on basic demographics and exposure to the potential sources of air pollutants from individual microenvironments, namely indoors, workplace, and outdoors, were collected by interview, using prevalidated, semi-structured questionnaire by trained staff. The cumulative exposure was reported as exposure risk hours, from the individual microenvironments and total exposure was estimated using mathematical modeling. In addition, cumulative (particulate matter) PM2.5 exposure for participants residing adjacent to air monitoring stations was estimated. The association between exposure to air pollutants and risk for coronary artery disease was evaluated with standard statistics.

Results:

Basic demographics revealed a significant association between CAC groups and age (i.e., “low,” “intermediate,” and “high” risk were, respectively, 54.7 ± 10.12, 58.52 ± 8.89, and 64.38 ± 8.74 years, respectively) and gender; wherein higher age and male sex were associated with higher CAC scores. Cumulative PM2.5 exposure was significantly different among the risk categories (i.e., “low,” “intermediate,” and “high” risk were, respectively, 976.14 ± 371.7, 975.78 ± 433.2, and 1215.58 ± 265.5 units). Further, exposure to the potential pollutants at outdoors and at workplace was independently associated with high CAC risk with statistical significance (P < 0.05). While exposure to the potential pollutants recorded at indoors during the transit/commute to residence and workplace was not statistically associated with the CAC risk categories (P > 0.05).

Conclusion:

Exposure to air pollutants from the workplace and outdoors was significantly associated with higher coronary artery calcification, thereby increasing the risk for coronary artery diseases.
Early Detection of Pancreatic Cancer: Opportunities Provided by Cancer-induced Paraneoplastic Phenomena and Artificial Intelligence
Authors: Liao Wei-Chih
Published: December 2023

Objective:

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer, with a 5-year survival rate of only 11%. Surgery is the only potential cure for PDAC, but approximately 85% of patients present with unresectable tumors at diagnosis. The difficulty in early detection is attributed to the fact that early PDACs cause few or nonspecific symptoms and are frequently obscure or even invisible in imaging studies such as computed tomography (CT). This review aims to briefly summarize the status of screening/surveillance for PDAC and elaborate on the potential windows of opportunity for early detection through PDAC-induced paraneoplastic phenomena and artificial intelligence (AI)-augmented image analysis.

Data Sources:

Relevant studies and review articles were searched in PubMed.

Study Selection:

Studies and articles on human subjects were selected.

Results:

Surveillance for high-risk individuals with imaging-based tools (endoscopic ultrasound and magnetic resonance image) is now advocated, whereas screening for asymptomatic general populations is not warranted at present. Paraneoplastic syndromes, including pancreatic cancer-associated diabetes and cachexia, are prevalent in PDAC patients and may provide windows of opportunity for early detection. S100A9 and galectin-3 are novel PDAC-derived factors mediating pancreatic cancer-associated diabetes and have shown promise in facilitating the early detection of PDAC. Novel computer-aided detection tools based on AI technologies, including deep learning and radiomic analysis with machine learning, have achieved accurate detection and might supplement human interpretation to improve the sensitivity for early PDAC on CT images.

Conclusion:

Novel blood-based biomarkers and AI-augmented image analysis may be complementary and hold promise for the early detection of PDAC.
Combination of Anti-programmed Cell Death Protein 1 and Antiangiogenesis Displaying a Response Disparity between Pulmonary and Nonpulmonary Metastases
Authors: Chung Bing-Syuan , Lin Peng-Chan , Chen Shang-Hung , Yeh Yu-Min
Published: December 2023

Targeting the vascular endothelial growth factor-mediated immune suppression is a strategy to overcome the resistance of anti-programmed cell death protein 1/programmed death-ligand 1 (anti-PD-1/PD-L1) therapy. Here, we present two cases, including one case with leiomyosarcoma and the other one with microsatellite-stable colorectal cancer, receiving the combination of pembrolizumab and lenvatinib as salvage treatment. Both cases demonstrated a significant response in lung metastases; however, the nonpulmonary metastases progressed. These findings suggest that lung metastasis might have a distinct tumor immune microenvironment, and further studies to investigate the efficacy of PD-1/PD-L1-based combination therapy in patients with lung-limited metastases are warranted.
Left Kidney Undifferentiated Spindle Cell Sarcoma with Myeloid Cell Leukemia-1 Amplification: Therapeutic Response to Bortezomib, Venetoclax, and Dexamethasone Therapy
Authors: Tang Cheng-Yu , Yen Chueh-Chuan
Published: December 2023

The overexpression of myeloid cell leukemia-1 (MCL-1) has been identified in numerous hematologic malignancies and solid tumors. Currently, there are no selective MCL-1 inhibitors. Here, we present a case of left kidney undifferentiated spindle cell sarcoma with MCL-1 amplification. The tumor showed primary resistance to chemotherapy and immune checkpoint inhibitors. Combination therapy of bortezomib, venetoclax, and dexamethasone demonstrated a positive response, resulting in a stable tumor condition for 6 months. To our knowledge, this is the first report to mention the clinical efficacy of bortezomib, venetoclax, and dexamethasone therapy in an MCL-1-amplified solid tumor.
Incidental appendiceal neoplasms: Single-centre results
Authors: Ozdemir Hakan , Ozdemir Zehra Unal , Gul Mehmet O.
Published: December 2023

Background:

Histopathological examination of appendectomy specimens may reveal malignancies. Based on these results, either appendectomy is sufficient or sometimes a further treatment protocol can be needed. In this study, malignancy-diagnosed cases on appendectomy specimen were examined.

Methods:

Patients who underwent appendectomy between January 2013 and December 2018 with a pre-diagnosis of acute appendicitis were evaluated retrospectively and those cases with malignancy were included in the study. Patients’ age, sex, tumor type, tumor diameter, tumor grade, tumor localization, surgical margin, Ki-67 index, state of lymphovascular invasion, state of peri-neural invasion, and follow-up period duration were recorded.

Results:

On examination of 2336 appendectomy specimens, 16 patients (0.7%) were found to have neuroendocrine tumors (NET), 11 patients (0.5%) were found to have low-grade mucinous neoplasm (LAMN), and five patients (0.2%) were found to have primary appendix carcinomas. Appendix tumors usually present with acute appendicitis symptoms. Despite re-operation with right hemicolectomy (RHC) being required in the treatment of adenocarcinoma cases, appendectomy provides adequate treatment in most cases with NET and LAMN. With these tumors, which usually have a benign prognosis, it is important to perform the necessary screening in the postoperative period and not to interrupt follow-up.
Comparison of safety and efficacy of Netarsudil 0.02% and Bimatoprost 0.01% monotherapy and combination therapy in primary open-angle glaucoma and ocular hypertension
Authors: Shahid Saima , Rizvi Syed Wajahat A , Khan Adeeb A , Ashraf Humayoun , Akhter Afeefa
Published: December 2023

Purpose:

To study and compare the efficacy and safety profile of Rho-kinase inhibitor (netarsudil 0.02%) and prostaglandin analog (bimatoprost 0.01%) both as monotherapy and in combination.

Design:

Prospective, randomized, monocentric, open-label clinical trial.

Methods:

Patients ≥20 years of age with primary open-angle glaucoma or ocular hypertension (IOP >21 mmHg) were recruited and randomized to receive either netarsudil 0.02%, netarsudil 0.02% + bimatoprost 0.01%, or bimatoprost 0.01% once daily for a period of 12 weeks. IOP and side effects were documented at 4, 8, and 12 weeks.

Results:

The mean treated IOP ranged 17.51–18.57 mmHg for netarsudil, 15.80–16.46 mmHg for bimatoprost, and 14.00–14.87 mmHg for the combination therapy group. The mean IOP reduction from baseline at 4, 8, and 12 weeks was found to be statistically significant (P < 0.001) in all three groups. The safety profile of netarsudil/bimatoprost combination was consistent with each constituent individually. The only frequently observed ocular adverse event was conjunctival hyperemia, which was seen mostly in netarsudil and netarsudil + bimatoprost groups (P < 0.001).

Conclusion:

The IOP-lowering effect of netarsudil 0.02% once daily is non-inferior to bimatoprost 0.01% in patients with POAG and ocular hypertension with acceptable ocular safety, and the combination therapy achieved a higher IOP-lowering effect. This group of medications can be a useful adjunct in patients on maximal therapy.
Intraoperative optical coherence tomography–guided transconjunctival bleb suturing – A minimally invasive technique for managing overfiltering bleb
Authors: Angmo Dewang , Devi Chandra , Dada Tanuj
Published: December 2023

With the recent advancement in technologies, real-time integrated intraoperative optical coherence tomography (iOCT) microscopes are available, which facilitates surgical precision and also reduces the risk of complications. Two glaucoma patients with advanced glaucomatous optic neuropathy, who underwent uneventful trabeculectomy with 0.02% mitomycin C, developed persistent hypotony postoperatively till 4–6 weeks. On clinical examination, visual acuity was 1/60 with low intraocular pressure (IOP) of 4 mmHg. Elevated, overfiltering bleb was seen on slit-lamp examination, along with hypotonous maculopathy. Anterior segment optical coherence tomography (AS-OCT) showed multiple large hyporeflective fluid spaces suggestive of overfiltering bleb. Considering the risk of choroidal detachment and further deterioration of vision, iOCT-guided transconjunctival bleb suturing was planned. iOCT helped to identify the exact location of scleral flap, and transconjunctival suturing was done with successful outcomes in terms of improved IOP and visual acuity.