Journal for Research in Applied Sciences and Biotechnology

Cascabela thevetia Ethnobotanical, Phytochemistry, Pharmacological Activities and Medicinal Uses: A Detailed Study

Prakash Pralhad Sarwade — 2024-11-16

There are a few different names for the member of the Apocynaceae family known as Cascabela thevetia. Some of these names include digoxin, lucky nut, and yellow oleander. The lovely and evergreen Cascabela thevetia is a dicotyledonous shrub that is known for its evergreen nature. There are a number of countries in Central and South America, as well as a number of Asian nations, where the Cascabela thevetia plant is indigenous. These countries include India and Sri Lanka. The Cascabela thevetia plant has been found to have a wide variety of secondary metabolites, such as alkaloids, flavonoids, steroids, terpenoids, tannins, saponins, and cardiac glycosides. These plants include a number of cardiac glycosides, including neriifolin, thevetin A, thevetin B, and oleandrin, and each and every one of them is dangerous. The leaves of the plant are used in traditional medicine not just for their alleged medicinal benefits, but also for their diuretic and cardiotonic effects. The pharmacological activity of a number of plant components, including seeds, flowers, bark, fruits, and leaves, has been reported in a number of different experiments. It is common for T. peruviana to be the cause of toxicological emergencies in tropical and subtropical climates all over the world. Numerous cardiac glycosides, including neriifolin, oleandrin, thevetin A, and thevetin B, are discovered in this potentially hazardous plant. These glycosides are only a few examples. After consuming oleander, some of the symptoms that may manifest themselves include hyperkalaemia, nausea, vomiting, diarrhoea, and abdominal pain. Oliander can also cause diarrhoea. The purpose of this review is to provide a comprehensive data collection that includes information on morphology, cultivation and propagation, distribution, phytochemistry, traditional uses, and pharmacological qualities.

Role of Pyrimidine Derivatives in the Treatment of Cancer

Prakash Pralhad Sarwade — 2024-11-12

The study of the chemistry of pyrimidines is contributing to the expansion of research into the therapeutic applications of these compounds. In the field of medicinal chemistry, the sheer number of pyrimidine synthesis methods and reactions that are available opens up a world of possibilities. These investigations have been inspired by the fact that pyrimidines can be used as building blocks for a wide variety of compounds that have a physiological effect. The pyrimidine ring and its fused derivatives, which include pyrazolo[3,4-d]pyrimidine, pyrido[2,3-d]pyrimidine, quinazoline, and furo[2,3-d]pyrimidine, have garnered a great deal of attention due to the extensive variety of biological potential that they possess. In addition, fused pyrimidines are considered to be bioisosteres with purines. As a consequence of this, numerous substances, such as pyrimidine and derivatives of fused pyrimidine, have demonstrated promising anticancer potential. Pyrimidine compounds have been shown to possess a number of beneficial qualities, including antibacterial, anticancer, anti-inflammatory, antidiabetic, and analgesic effects. The purpose of this study is to shed light on the anticancer significance of certain fused pyrimidine derivatives and privileged pyrimidines through the use of various types of inhibition. Additionally, the study reveals structure-activity relationships and provides specifics regarding the synthetic compounds that were utilized in the construction of these scaffolds. The hope is that this research will assist medicinal chemists in the development of highly selective pyrimidine anticancer agents. The focus of this review article is on recent research on synthetic pyrimidine compounds that have anticancer effects. Additionally, the paper examines the chemistry and biological activities of pyrimidines.

Adversarial Machine Learning Approaches for Strengthening Cybersecurity in Intrusion Detection Systems

Rahul Gandhi — 2023-10-31

In this study, adversarial machine learning to enhance IDS’s capability to counterattack sophisticated cyberattacks employed in the investigation. This paper describes challenges in practice of adversarial techniques, performance measurement and ethical issues. In the research proposal, the authors describe the comprehensive and multi-level method of detecting artifacts, building complex models, and gathering data. Researchers stressed important conclusions regarding aggressiveness of privacy-preserving methods, the need for developing new performance metrics, and the tension between robust model and detection performance. The research assists in developing IDS that are both efficient and formally correct in various contexts of a network.

Real-Time Data Pipelines for Feature Stores in Gaming

Robin Gupta — 2023-10-31

Machine learning models are used in content creation and generate real-time observations in gaming with a positive effect on both performance and production processes. However, the management and deployment of these features and metrics for the purposes of these benefits are critical. Looking at feature and metric stores data structures that are used for storing and retrieving feature and metric data for machine learning models. Feature stores are responsible for featuring storage and delivery for model training and features needed for model’s inferencing, whereas metric stores contain metrics required for the assessment of specific models. The adoption of these stores can drastically bring down the amount of development time and effort as well as enhance the aptitude of recognizing real time actions and quality of the game. It is therefore prudent and helpful for the reader to learn the basic concepts that underpin feature and metric store, the ways in which gaming application benefits from them, and the possible ways in which this technology can be developed further in the future.

Machine Learning on Encrypted Data: Analyzing Efficiency and Accuracy Trade-Offs

Kavitha Kumari — 2023-08-31

In this modern era, phishing has become a great problem. Because of this, it can be observed that the personal information of people is leaked from emails & websites. Hence, it is needed that these instances of phishing are to be reduced. In doing one of the best tools that can be used is Machine Learning. This is a process of using historical data for making prediction of future scenarios. In this project, the details of the approached that can be used for the detection of phishing are analyzed. Moreover, the algorithms that are used by ML for this purpose are also envisaged here. The description of the process of collection of data is presented here. In addition to this, the results that shows the effectiveness of ML in the detection of phishing is also discussed here.

Federated Learning in Privacy-Preserving Machine Learning: Balancing Model Accuracy and Data Security

Rajeev Agarwal — 2023-08-31

This research article provides information regarding the concerns of Privacy-Preserving Machine Learning (PPML) Techniques that includes Differential Privacy, Federated Learning, and Secure Multi-Party Computation. It is also noticed that Privacy Models are useful to achieve significant privacy and minimal loss in model accuracy. This further demonstrates that these kinds of strategies in the main application areas such as Healthcare, Banking, Internet-Of-Things (IOT), and Manufacturing, provides near-perfect privacy that can be useful while it meets minimal compromise in model accuracy. Some of the findings are enhanced data security, high accuracy of the chosen model, and ideas for future development.

Chronic Obstructive Pulmonary Disease (COPD): Diagnosis, Pathology, Clinical Presentation and Homoeopathic Management

Praveen Kumar Pathak — 2024-10-31

Chronic Obstructive Pulmonary Disease (COPD) is a very common problem worldwide now a day. COPD is preventable and treatable disease it is characterized by constant airflow limitation that is generally progressive and connected with an enhanced chronic inflammatory response in the airways and the lung to noxious particles or gases. Exacerbations and comorbidities contribute to the generally severity in individual patients of COPD. It remains a most important reason of morbidity and mortality globally and outcome in an economic and social burden that is both substantial and increasing.

The Impact of Pesticides on Groundwater Quality

Sumaya Assanousi Eshtiwi Lama — 2022-04-30

Pesticides have gotten to be exceptionally advantageous to agriculturists and to other individuals around the world as they can increment edit surrender and can give a number of other benefits or focal points to everybody straightforwardly or in a roundabout way. But due to dangers forced by the pesticides on environment and human wellbeing; concerns are raised around its security. The utilize of pesticides is causing genuine wellbeing impacts. Indeed at less concentration, pesticides are a major risk to environment. The pesticides are sullying water bodies and are causing water contamination. Be that as it may, the dangers of pesticides can't be dispensed with totally but they can outwit in another way. Able to minimize the hurtful or unfavorable impacts of pesticides by different ways like by applying elective trimming methods or through superior splashing equipment's.

Detailing of secure, way better and eco-friendly pesticides can reduce the unfavorable impacts related to utilize of pesticides. The chance of pesticides can be diminished in the event that we utilize pesticides in reasonable sum and utilize them as it were when essential or required.

Numerous individuals or agriculturists are not mindful of the harmfulness or destructive impacts of pesticides. They do not have any data related to sort of pesticides, their dangers, level of harming and preparatory measures they ought to take some time recently utilize them. Since of these things, tireless or poisonous chemicals are utilized to murder bugs, weeds or for other use which can cause purposefulness or inadvertent introduction. To play down the utilize of harmful pesticides, it is fundamental to make mindfulness among individuals.

A Study of The Geographical Information System (GIS) based Energy Station Identification and Frequency Analysis Using ETA

Ravindra Gupta — 2024-11-06

The energy corporation entity recently pays maximum attention to the environmental and social safe guards associated with its operations. In developing countries mainly suffers to balance the gap between generation and demand for effective operation by the energy utilities. An inadequate transmission capacity, non-uniform location of energy stations may lead to worst consequences when the occurrences of fault and may end up with black out. To overcome the above situation and to improve the stability of such system, In this research proposes a Geographical Information System (GIS) based identification of location of the uncertainty power stations and also a technique called Islanding Scheme to protect the severely affected system by measuring its frequency parameters. The severely disturbed large interconnected power system is divided into number of subsystems with two or more generating buses feeding its nearby loads by disintegrating the tie lines. The sample 50 bus test case system taken from Tamilnadu Electricity Board (TNEB), INDIA to analyze and simulate the results using Electrical Transient Analyzer Program (ETAP) and Geographical Information System (GIS). In this paper, ETAP and GIS effective software tools used for identify the energy station in various locations and analyzing the frequency status of different buses for better operation in electric utilities and thus ensure better management, enhance the improved stability by mapping the data and outage management.

Challenges in Influenza Control and Surveillance in the Republic of Kazakhstan

Mukhlis Hujatullah — 2024-11-02

The COVID-19 pandemic has significantly disrupted the circulation of influenza viruses in Kazakhstan, highlighting the vulnerabilities in the country’s public health infrastructure. This review critically examines the challenges faced in infiltrating and controlling influenza in Kazakhstan, particularly in light of the shifting epidemiological landscape post-pandemic. Key issues include the decline in influenza cases during the pandemic, which complicates the assessment of influenza epidemiology, vaccine effectiveness, and planning of vaccination campaigns. Although part of the Global Influenza Hospital Surveillance Network (GIHSN), Kazakhstan's surveillance systems face data collection, coordination, and public awareness gaps. The review discusses the prevalence of various influenza strains, the impact of zoonotic infections, and the necessity for improved monitoring frameworks. Additionally, the historical context of infectious disease control in Kazakhstan is explored, emphasising the need for enhanced international collaboration and targeted public health strategies. The findings underscore the importance of vaccination and robust surveillance to mitigate the risks of seasonal and pandemic influenza, advocating for a comprehensive approach to safeguard public health in Kazakhstan.

Advances in Transdermal Drug Delivery: The Development of Microneedle Technology for Improved Therapeutic Outcomes

Shivshankar M. Nagrik — 2024-11-14

Transdermal Drug Delivery Systems (TDDS) represent a significant advancement in therapeutic administration by allowing drugs to bypass the gastrointestinal system and first-pass hepatic metabolism, enhancing patient compliance, and enabling sustained drug release. However, traditional TDDS face limitations, including resistance from the skin's natural barrier and limited efficacy in delivering large or hydrophilic molecules. Microneedle (MN) technology offers a breakthrough solution, using minimally invasive micron-sized needles to bypass the stratum corneum, facilitating efficient drug delivery without significant pain or discomfort. This review explores the evolution and recent advancements in microneedle technology, highlighting its role in overcoming the limitations of conventional TDDS. Microneedles have been shown to enhance drug bioavailability, reduce side effects, and expand the range of deliverable therapeutics, including vaccines, insulin, and genetic materials. The development of bioinspired 4D microneedles further extends their application to diagnostics and cosmetic treatments, positioning MNs as a versatile tool in modern medicine. Key sections of the review focus on the types of microneedles—solid, coated, dissolving, hollow, and hydrogel-forming—and their respective fabrication methods, materials, and drug delivery mechanisms. The review also discusses the challenges related to scaling up production, ensuring consistent quality, and regulatory hurdles in achieving clinical approval. Future directions include the integration of microneedles with nanotechnology, combination therapies, and sustainable design, particularly in developing regions where biodegradable materials may address environmental and disposal concerns. The potential for microneedle technology to revolutionize transdermal drug delivery, diagnostics, and therapeutic monitoring is significant, with ongoing research paving the way for multifunctional applications that can reshape patient care and treatment modalities.

Investigation of Phytochemical and Antidepressants Activity of Cinnamon Powder Extract

Santosh Kumar S.R. — 2024-10-31

Neurodegenerative disease is the most common type of mobility issue, but unfortunately, there is now no medication that can alter the course of the disease. We don't know what causes this ailment. In mouse models of Parkinson's disease induced with 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine, the oral administration of cinnamon powder and sodium benzoate may prevent the death of dopaminergic cells, dysregulation of striatal neurotransmitters, and motor impairments. The mechanisms driving its function include controlling autophagy, antioxidant effects, Parkin, DJ-1, and glial cell line-derived neurotrophic factor activation, TLR/NF-κB pathway modulation, and excessive proinflammatory response prevention. Moreover, research carried out in both laboratory and living organism settings has shown that cinnamon extracts may impact the oligomerisation and aggregation of α-synuclein. This article's goal is to discuss recent findings about this phytochemical's potential as a novel treatment for Parkinson's disease (PD). We highlight additional areas of mechanism that require investigation and possible constraints that must be overcome before this phytochemical may be used in PD trials. Neurodegenerative disease is the most common type of mobility impairment, and unfortunately, there is now no medication that can alter this disease.

We don't know what causes this ailment. There has been a recent uptick in interest in medicinal plant use because of the novelty, safety, and relative affordability of this field. The characteristic flavour and aroma of cinnamon, a spice that is often used, may have neuroprotective effects on people with Parkinson's disease (PD) and other neurodegenerative diseases. The essential oils of Cinnamomum species, such as cinnamaldehyde and sodium benzoate, have shown in vitro that they can protect cells from oxidative stress, ROS generation, and autophagy dysregulation. Consequently, these oils may exert a neuroprotective effect. The in vivo evidence suggests that cinnamon powder and sodium benzoate, when administered orally to Parkinson's disease models in mice, may prevent the death of dopaminergic cells, dysregulation of striatal neurotransmitters, and motor deficits. In this essay, we will go over the latest research on this phytochemical and its potential as a novel treatment for Parkinson's disease (PD). Incorporating this phytochemical into experimental PD treatments requires further investigation into additional molecular aspects and the potential overcoming of constraints and obstacles.

Phytochemical Analysis, Antioxidant Activity of Wild Medicinal Plants of Himalayan Range

Prakash Pralhad Sarwade — 2024-10-31

Plants that are indigenous to the Himalayas have been exploited for their therapeutic properties for over 6,500 years. Using their deep knowledge of the local flora and fauna, traditional healers in the region are able to treat a wide variety of maladies with herbal treatments. People who live in rural areas of the Himalayas rely on wild medicinal plants for their health, and we need to do everything in our power to ensure that these plants continue to thrive in the harsh desert climate of the Himalayas. Raw materials that are obtained from wild plants are in high demand all around the world, particularly among pharmaceutical companies, ethnomedics, and practitioners of traditional medicine as well as other medical practitioners. India has been a top exporter of raw herbal medications all over the world. This is mostly due to the number of medicinal plants that can be found in the Himalayas. The aim of this study was to determine the Phytochemical analysis and antioxidant activity of various parts of 20 selected wild medicinal plants, found in the Himalayan regions in India, China, Nepal, Bhutan and Pakistan including Swertia bimaculate, Ficus neriifolia, Rubus treutleri, Periploca calophylla, G. depressa, Buddleja napaulensis, Habenaria edgeworthii, Pyracantha crenulate, Roscoea procera, Allium rubellum, Berberis chitria, Capsella bursa-pastoris, Artemisia maritima, C. glanduliferum, C. distans, Juniperus macropoda, Origanum vulgare, Valeriana jatamansi, Polygonatum verticillatum, Meconopsis aculeate and Fragaria nubicolais. There were several different parts of the species that were examined to determine their total polyphenol, flavonoid, alkaloid, saponin, and tannin concentrations. One fraction of the plant extracts was found to contain a higher quantity of phytochemicals when compared to the other portions. Through the utilisation of the DPPH and FRAP model systems, the antioxidant capacity of a number of different components was assessed. The high-performance liquid chromatography (HPLC) technique can be combined with the DPPH and/or ABTS tests in order to rapidly screen extracts for the presence of active chemicals.

The Impact of AI on Regulatory Compliance and Anti-Money Laundering Efforts in Payment Processing

Lohith Paripati — 2023-10-31

The paper elaborates on how AI is changing the face of regulatory compliance and anti-money laundering initiatives in the industry for processing payments. This can be done with artificial intelligence tools—natural language processing and machine learning algorithms—applied in areas such as document analysis, anomaly detection, and transaction monitoring. The paper points to increased detection rates, reduced false positives, and improved regulatory reporting associated with the use of AI within the KYC process and customer due diligence procedures more generally. It identifies how AI can transform the financial crime prevention landscape while also acknowledging such challenges as explainability, bias mitigation, and ethical concerns. Finally, some potential future paths in this area, like blockchain integration, federated learning, and the creation of more sophisticated explainable AI models for compliance systems, are discussed.

Climate Change Adaptation and Resource Resilience in Semi-Arid Regions: Strategies, Challenges, and Case Studies

Priyanka Rathore — 2024-10-29

Semi-arid regions face unique climate change challenges that threaten local ecosystems, agriculture, and water resources. This review explores climate adaptation strategies, resource resilience practices, and policy interventions tailored to semi-arid ecosystems, with a focus on Rajasthan, India, as a representative region. Key strategies include sustainable water resource management, soil conservation, and climate-smart agriculture. Through case studies and a comparative global analysis, this review underscores the importance of blending traditional and modern practices to enhance resilience and advocates for policy and technological innovation to support sustainable adaptation. Insights gained from this review may serve as a foundation for adaptation strategies applicable to other semi-arid regions globally.

Challenges and Solutions in Testing Mainframe Applications in Modern Banking

Ashwini Shivarudra — 2024-10-28

Because the foundation of their operations is still housed in legacy systems, banks continue to use them. Banks must modify their systems to remain competitive in light of the swift changes in technology and customer needs. Mainframe systems have been an integral part of corporate computing for many years, enabling critical applications across a range of industries, including banking, retail, and healthcare. There is rising interest in leveraging Application Programming Interfaces (APIs) to expose these old apps' data and features, hence accelerating the construction of new applications and maximising their capability and enabling their reuse. Nonetheless, there are several obstacles to overcome in the process of locating and making available APIs for various business use cases. In this study, we examine the difficulties involved in developing APIs for mainframe systems that are no longer in use and suggest a unique architecture to enable communication for a range of use cases. We performed a qualitative poll with nine mainframe developers, whose average experience was fifteen years, to evaluate the efficacy of our methodology. We were able to determine which APIs were candidates and how long it would take to implement them for two industry mainframe applications and the public mainframe application GENAPP thanks to the poll. We create a list of artefacts, such as screens, transactions, business rules, inter-micro service calls, control flow blocks, and data accesses, in order to identify APIs. IBM Watsonx Code Assistant for Z Refactoring Assistant includes an implementation for computing API signatures. We proved the practicality of our technique by running the discovered APIs on an IBM Z mainframe system to assess their accuracy.

Implementing Agile Testing Methodologies in Banking Software Project

Ashwini Shivarudra — 2022-10-31

Agile software development has been increasingly popular in a number of sectors in recent years. Financial businesses are used to this tendency since it requires them to respond to changes in their business environments more swiftly. Agile approaches have emerged to address the limitations of old ones. In response to the ever-changing and dynamic nature of the business environment, software development businesses are increasingly implementing agile methodologies. The word "Agile" originally arose in the disciplines of software development and project management around thirty years ago. It is used to research with wide-ranging implications, and it is utilized at different levels and in different circumstances. Scrum, kanban, large-scale scrum (LeSS), spotify model, continuous integration, Scaled Agile Lean Development (SCALeD), and many more variations of the agile methodology have emerged. Initially implemented at the individual software development and team level, agile has developed into projects, programs, solutions, and portfolios over time, ultimately reaching full-service growth into an enterprise level framework. In order to examine agile methodologies, models, and practices in a less researched area of the banking and financial services industry—from software development and modelling to large-scale case study organization levels—a unique methodology to surveying the literature has been presented in this paper. The study's conclusion outlines the contributing variables, best practices, advantages, and lessons that professionals in the banking and financial services industries may apply to create a simplified, agile deployment.

Influenza A as a True Zoonotic Pathogen: Transmission through Reservoir Hosts

Neyazi Ghulam Rabani — 2024-10-27

Influenza A virus (IAV) represents a considerable global health threat due to its rapid mutation rates and broad host range, facilitating cross-species transmission and enabling the virus to evade immune defenses. This review explores the molecular mechanisms underlying IAV's pathogenicity, focusing on its zoonotic potential through reservoir hosts, such as wild birds and swine. The virus's ability to undergo antigenic shift and drift allows it to continually adapt to new hosts and environments, posing challenges for control and treatment. Current antiviral therapies are limited by the emergence of resistant strains, underscoring the necessity for innovative vaccine development and treatment strategies. By examining IAV's molecular evolution, immune evasion tactics, and transmission dynamics, this review highlights the critical need for enhanced surveillance, improved therapeutic options, and international cooperation to mitigate future outbreaks. A deeper understanding of these processes is essential to inform public health efforts and combat the persistent threat of IAV.

Integrating Non-SAP Systems with SAP Environments on AWS: Strategies for Seamless Operations

Sachin Bhatt — 2023-12-31

This paper comprises a discussion of the implementation of non-SAP systems in relation to SAP environments on AWS with emphasis on issue identification and best practices. Some primary topics for the conversation are middleware and integration platforms and tools, APIs, and data exchanging strategies, AWS Glue and Lambda. This paper reflects on architectural factors and security factors which are crucial for integration. It also offers insights into the modern technologies like Artificial Intelligence, Blockchain, serverless computing and their roles in future integration evolution. The results stress the need for coherence in integration to make it both run smoothly in terms of operations as well as strategically.

AI-Powered Strategies for Addressing Fiber Nonlinearity in High-Capacity Elastic Optical Networks

Hitesh Solanki — 2023-10-31

To fulfill the rising need for high-capacity and flexible communication systems, Elastic Optical Networks (EONs) have emerged as a possible alternative. However, the growing transmission rates and intricate modulation formats in EONs present substantial difficulties, such as fiber nonlinearity, which may deteriorate signal quality and restrict the network's performance. The fundamental components of EONs are fiber Nonlinear Interference (NLI) modeling and monitoring. Traditionally, they were created and studied independently. Furthermore, for heterogeneous dynamic optical networks, the previously suggested approaches' accuracy must still be increased. In this study, we demonstrate how Artificial Intelligence (AI) is used in NLI monitoring and modeling. We specifically propose to measure the drawbacks of the most current fiber nonlinearity estimates using AI approaches. The Gaussian Noise (GN) framework is used as an instance and Binary Differential-Support Vector Machine (BD-SVM) is used to demonstrate an important enhancement. In addition, we suggest combining modeling and monitoring strategies with AI for a more accurate prediction of NLI variation. Extensive simulations with 2411 connections are done to compare and assess the efficacy of various systems. The results of these simulations demonstrate that the AI-aided modeling and monitoring combo works better than other possible solutions.

Advanced Big Data Mining Techniques for Early Detection of Heart Attacks in Clinical Data

Ritesh Chaturvedi — 2023-06-30

Heart attacks are among the most dangerous ailments that people may develop. The key to controlling cardiovascular disease is to compare, contrast, and mine enormous volumes of data in a sequence that may be used to identify, control, and treat persistent problems, such as heart attacks. Forecasting, preventing, monitoring, and diagnosing cardiovascular diseases may be done through huge efficiency via big data analytics, which is well-known in the business sector for its useful application in regulating, comparing, and supervising enormous datasets. Big data technologies or methods used to mine massive databases for information include Hadoop, data mining, and visualization. Those fresh ideas, which have a wide range of uses, might be helpful in several industries, include medical. In this paper, we extend a big data mining pattern using a machine learning method to forecast the frequency of heart attacks from medical databases. Data preprocessing using the z- score normalization and feature extraction using Linear Discriminant Analysis (LDA) and classification using the Improved Random Forest (IRF). We generate enhanced presentation intensity with accuracy, precision, recall, and F- measure throughout the forecast model for heart disease with the IRF.

Harnessing Data Mining for Early Detection and Prognosis of Cancer: Techniques and Challenges

Ritesh Chaturvedi — 2023-02-28

Cancer is one of the leading causes of mortality worldwide. In 2018, there were approximately 1,735,350 new instances of cancer identified in the United States alone, and 609,640 individuals passed away as a direct result of the disease. Cancers include skin melanoma, lung bronchus cancer, breast cancer, prostate cancer, colon and rectum cancer, bladder cancer, kidney and renal pelvis cancer, and others. Cancer has risen to prominence in the scientific community due to the wide variety of cancers and the enormous number of people it affects. There is still active research on cancer prevention and diagnostic strategies. Using data mining methods, we sought to create a reliable and workable system for cancer diagnosis. Machine learning techniques may assist professionals in creating tools that enable early cancer detection. To improve cancer diagnosis rates, this research aims to introduce a novel machine learning method called the Elephant herding optimized logistic regression (EHOLR) strategy. Histogram equalization (HE) was used for preprocessing the acquired cancer data, and linear discriminant analysis (LDA) was used to extract the data's features. Finally, cancer detection is accomplished using our recommended strategy. The effectiveness of the suggested strategy is then assessed using the performance matrix, namely accuracy, recall, and precision.

A Review on Green Synthesized Metal Nanoparticles Applications

Santosh Kumar S.R. — 2024-10-23

Nanotechnology pertains to the manipulation of materials at exceedingly small scales, specifically between 1 and 100 nanometers. Materials at this scale exhibit significantly different properties compared to the same materials at larger scales. An emerging trend is the utilization of nanoparticles (NPs) to address environmental issues. Metallic nanoparticles are among the several nanoparticles that are extensively utilized in environmentally sustainable endeavors. A sustainable, economical, and enduring approach is to synthesize nanoparticles through a more ecologically friendly procedure instead of a physical or chemical method. Plant components primarily function as reducing and capping agents in eco-friendly synthesis. Diverse metallic nanoparticles of various sizes and shapes have been created utilizing extracts from plant materials, including leaves, bark, fruits, and flowers. The synthesis of Nobel laureate metal nanoparticles is essential to the medical sector. A diverse array of glycosides and phenolic compounds constitutes numerous organic constituents in plants, facilitating the synthesis of metal nanoparticles. The absence of detrimental by-products in metal nanoparticle synthesis is the primary significance of green synthesis. The nanoparticles generated by an eco-friendly approach demonstrate several significant biological activity. A substantial body of literature demonstrates that the synthesized nanoparticles are efficacious against both gram-positive and gram-negative bacteria, including E. coli, Bacillus subtilis, Klebsiella pneumoniae, and Pseudomonas fluorescens. The synthesized nanoparticles not only display antifungal efficacy against several cancer cell lines, including those of breast cancer, but also demonstrate antifungal activity against Trichophyton simii, Trichophyton mentagrophytes, and Trichophyton rubrum. Moreover, they exhibit potent antioxidant properties. The dimensions and morphology of these metal nanoparticles substantially influence their functionalities. Particles characterized by a large surface area and diminutive size provide significant potential for medical applications. This paper aims to provide a comprehensive summary of current advancements in the synthesis of nanoparticles utilizing biological entities and their numerous potential applications.

Role of Herbal Essential Oil in Cervical Cancer: A Systematic Review

Shailendra Sah — 2024-10-22

Cancer of the cervix is a disease that is ubiquitous and frequently severe, and it affects women all over the world. Conventional treatment methods, which include surgical procedures, chemotherapy, and radiation therapy, have been shown to dramatically enhance survival rates; nevertheless, these methods are frequently accompanied with adverse effects and difficulties that might have an influence on the quality of life of a patient. In recent years, there has been a growing interest in the utilisation of essential oils in the cancer treatment and management of cervical cancer. This review offers a comprehensive investigation into the function that various essential oils play in the development of cervical cancer. It also includes insights into the possible advantages of these oils as well as the body of research that has been conducted on them. Additionally, the analysis dives into the future directions and issues that will be faced in this developing industry, with a particular focus on advancements in delivery methods and interesting research areas. For the purpose of enhancing the anticancer qualities of essential oils, the encapsulation of essential oils with solid lipid nanoparticles, the nanoemulsification of essential oils, or the combining of essential oils with conventional treatments have all demonstrated promising results. This review attempts to provide a comprehensive viewpoint, balancing the potential of these natural therapies with the obstacles and issues that need to be addressed. As the employment of essential oils in the treatment or management of cervical cancer continues to develop, this study will attempt to provide a comprehensive perspective. The study will attempt to strike a balance between the potential of these natural treatments and the obstacles and issues that need to be addressed.

Examining the Impact of Climate Change on Agriculture Products in the Province of Jawzjan (Case Study: Certain Villages in Sheberghan City)

Mohammad Ayoob MAKHDOM — 2024-10-11

A region's weather and climate patterns are impacted by climate change over an extended period of time. Rising temperatures, altered precipitation patterns, rising sea levels and other modifications to meteorological conditions are some of these changes. Numerous facets of existence, including the environment, economy, and human communities, may be significantly impacted by climate change. Significant repercussions of climate change are possible, particularly in the agricultural sector. The production of food crops may be impacted by these changes because agricultural goods are dependent on local climate and weather. Pests and plant diseases may also become more prevalent due to climate change. Accordingly, higher temperatures and changed precipitation patterns can foster the growth of pests and illnesses, which will lower agricultural yields. Investigating how climate change affects agricultural products in Sheberghan City, Jawzjan Province, is the goal of this study. A questionnaire was used in fieldwork to perform this study. Six communities inside Sheberghan City—Toka, Qowchin, Jalalabad, Seshanba, Nokar Abad, and Afghan Tapa—were given 100 questionnaires in all. Four different types of questionnaires were produced and designed for the survey portion of this study. Of the 100 responders, 26 worked as farmers, 37 as gardeners, 8 as teachers, and 29 as traders in agricultural products. Using the SPSS26 program, the research was analyzed. The results showed that agricultural goods are significantly impacted by climate change, highlighting the significance of agriculture and agricultural products in the economy. The research findings indicate that the utilization of contemporary technology, such as smart irrigation systems and smart systems, can be one of the elements in growing agricultural products, and that the development of climate-adaptive agricultural methods can boost agricultural products. Farmers' interest can also be raised by government encouragement and assistance. The general conclusion that can be drawn from looking at the aforementioned elements is that agricultural products have been impacted by climate change and the creation of farmers' techniques for adapting to it.

Therapeutic Potential of Quercetin and their Compound Against Ovarian Cancer: New Approaches & Application

M. Duraipandian — 2024-10-11

Ovarian cancer is an exceptionally perilous form of cancer as it develops within the female reproductive system. Finding effective therapy platforms for ovarian cancer has been difficult because to the diverse array of molecular pathways and genetic alterations involved in its development. Therefore, it is imperative to discover novel therapeutic methodologies and advance their development. Medicinal herbs possess the capacity to independently or in combination with other pharmaceuticals, effectively treat malignancies such as ovarian cancer. Quercetin possesses remarkable anti-inflammatory and anti-cancer properties, making it one among numerous natural compounds with such qualities. Quercetin has demonstrated cytotoxicity against ovarian cancer cells in both laboratory experiments (in vitro) and live animal tests (in vivo). The potential anti-cancer effects of quercetin, particularly in relation to ovarian cancer, have not been extensively studied in human trials, despite encouraging findings from laboratory and animal experiments. Hence, it seems that quercetin could potentially be utilized in clinical trials as a therapeutic agent, either on its own or in conjunction with other chemotherapeutic drugs. This article will outline the primary aspects of quercetin's anti-cancer characteristics and thereafter concentrate on its application in the treatment of ovarian cancer.

Effects of Exercise on Hormones in Women with Polycystic Ovary Syndrome

Kavita Narayan Gaisamudre (Sarwade) — 2024-10-11

Numerous reproductive-aged women are impacted by polycystic ovary syndrome (PCOS), an endocrine-gynecology condition. While a risk factor for polycystic ovarian syndrome (PCOS) has been identified, much about the disease's origins and pathophysiology is still up in the air. We searched PubMed and ClinicalTrials.gov extensively for results pertaining to the utilisation of repurposed pharmaceuticals in order to acquire information about the causes and treatments of polycystic ovarian syndrome (PCOS) for this study. We looked at everything that could be causing polycystic ovary syndrome. In addition, the data for both the most commonly prescribed PCOS medications and those that have been repurposed are summarised in the tables. Insulin resistance, inflammation, environmental toxicants, epigenetics, oxidative stress, hyperandrogenism, stress, and nutrition were all part of the internal components that were reviewed. Altering one's way of life and making use of complementary and alternative medicine is often the first line of defence against illness for many people. There is some evidence that certain medications and supplements may be effective in treating polycystic ovarian syndrome (PCOS). These chemicals include mucolytic medicines, thiazolidinediones, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, 3-hydroxy-3-methyl-3-glutaryl-coenzyme A (HMG-CoA) reductase inhibitors, and glucose-like peptide-1 receptor agonists.

DSM Systems for Multi-Processor Architectures Using AI-Driven Test Case Generation

Devendra Arya — 2022-10-31

This research paper explores the critical domain of automated. It also examines automated test execution frameworks, real-time monitoring solutions, and advanced verification and validation techniques. The findings of this study contribute to the advancement of DSM testing methodologies and provide valuable insights for both researchers and practitioners in the field of distributed systems and parallel computing. The research highlights the challenges faced in DSM testing, such as scalability issues and non-determinism, and proposes future directions for research, including the integration of artificial intelligence and cloud-based testing platforms.

Cross-Domain Transfer Learning for Demand Forecasting: Using Social Media Sentiment from Related Industries

Sweta Kumari — 2022-06-30

This study examines various window-based techniques, including time-based, size-based, and hybrid approaches, and evaluates their effectiveness in improving extract performance. Through extensive analysis and empirical testing, we demonstrate that window-based strategies can significantly reduce processing time and resource utilization while maintaining data consistency and integrity. This research paper investigates the application of window-based refresh strategies to enhance the performance of data extracts in large-scale data management systems. Traditional extract, transform, load (ETL) processes often struggle with the increasing volume and velocity of data in modern environments. Window-based refresh strategies offer a promising solution by focusing on specific subsets of data during each refresh cycle. This paper shall be devoted to assessing the efficiency of window-based refresh strategies related to the issues described above. The primary research goals are: Propose a general framework with which to apply window-based refresh strategies during the data extract process. Assess the performance benefits derived from applying different types of approaches based on window-based forms as opposed to conventional full and incremental extracts.

Self-Supervised Learning for Demand Forecasting Using Sparse and Noisy Social Media Sentiment Data

Rekha Singh — 2022-06-30

This research work focuses on the foundational principles of SLO monitoring, architectural considerations for high-volume data processing systems, and advanced techniques for implementing and scaling SLO monitoring solutions. The research includes areas like metric selection, instrumentation techniques, data collection strategies, statistical analysis, and emerging trends in the field. It is a synthesis of current literature and industry practices that presents an organized guide for organizations that want to implement robust SLO monitoring in their data processing infrastructure.

Morphometric Characterization of Nematode Parasites Infecting Periplaneta americana in Bulandshahr, Uttar Pradesh

Anjani Rani — 2022-06-30

This study investigates the morphometric characterization and distribution of nematode parasites infecting Periplaneta americana in Bulandshahr, Uttar Pradesh. The research aimed to identify the nematode species prevalent in various environments and analyze their impact on cockroach populations. Specimens of P. americana were collected from diverse sites, including sewage areas, urban kitchens, and garbage dumps, and examined for nematode infections. The study identified three primary nematode species—Rhabditis blumi, Heterorhabditis bacteriophora, and Steinernema carpocapsae—through microscopic and morphometric analyses. Statistical analysis revealed a significant correlation between environmental factors such as moisture and organic matter availability with nematode prevalence. The highest parasite load was found in sewage areas, where cockroaches exhibited behavioral changes and increased mortality. These findings suggest that parasitic nematodes play a crucial role in controlling P. americana populations, particularly in heavily contaminated environments. The study also highlights the potential use of entomopathogenic nematodes in integrated pest management strategies as an eco-friendly alternative to chemical pesticides. The research contributes to a better understanding of the ecological and biological significance of nematode parasitism in cockroaches and its implications for public health, emphasizing the need for sustainable pest control measures in urban environments.

Building Resilient Data Ingestion Pipelines for Third-Party Vendor Data Integration

Balachandar Paulraj — 2022-04-30

In this report, the author provides a review of the design and operation of the resilient data ingestion architecture with a particular emphasis on the issues associated with third-party data vendor integration. As more and more companies have made information a principal factor in their business strategies, it has become equally imperative to obtain external data in a coherent manner. This paper describes ways of handling Enhanced Data Ingestion Reliability Efficiency and Adaptability and other challenges such as Data quality Error Handling and Scalability.

Effect of Different Levels of Nitrogen, Phosphorus and Potassium Fertilizers on Yield of Cucumber (Cucumis sativus L.) Under The Climatic Conditions of Takhar Province

Abdul Bari Andeshmand — 2024-10-18

The experiment was carried out in the research farm of Agriculture Faculty, Takhar University under the title of the effect of nitrogen fertilizer with different amounts of phosphorus and potassium fertilizers on cucumber yield under the climatic conditions of Takhar Province, Afghanistan. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications and four treatments. Treatments T₁ without of any fertilizer, T₂ nitrogen 80 kg ha^-1, phosphorus fertilizer 100 kg ha^-1, and potassium fertilizer 85 kg ha^-1. T₃ nitrogen fertilizer 80 kg ha^-1, phosphorus fertilizer 120 kg ha^-1and potassium fertilizer 95 kg ha^-1. T₄ nitrogen fertilizer 80 kg ha^-1, phosphorus fertilizer 140 kg ha^-1and potassium fertilizer 105 kg ha^-1. In the order of information related to fruit length, fruit diameter, weight per fruit, weight per plant, fruit yield per hectare in tons was registered. The maximum fruit length (19.39 cm), fruit diameter (4.80 cm), weight per fruit (184.87 gr), fruit weight per plant (2.86 kg) and performance per hectare (61.37 tons) in T₄ with nitrogen fertilizer 80 kg ha^-1, phosphorus fertilizer 140 kg ha^-1and potassium fertilizer 105 kg ha^-1were found, while the lowest recorded data was from T₁ i.e. control. From this experiment, it can be said that the use of NPK fertilizer with the use of 80 kg of nitrogen fertilizer ha^-1, 140 kg of phosphorus fertilizer ha^-1 and 105 kg of potassium fertilizer ha^-1 for cucumber cultivation caused better growth and performance in the field of Takhar University.

Impact of Climate Change on Neurodevelopmental Disorders in Pediatrics

Srihari Padmanabhan — 2024-02-29

The present work aims at analyzing the effects of the climate change on neurodevelopmental disorders in children. The document dwells on the importance of neuro-toxic stressors in pollution and climatic changes affect neurological risks in children. Specifically, this research will examine the following questions: the causal mechanisms by which climate change impacts neurodevelopment; the related health consequences on children; and protective strategies for these populations. Through these linkages, the paper underscores the need for policy change and community mobilisation to protect children as they are affected by climate change.

Environmental Neurochemistry and Neurodevelopmental Disorders in Pediatrics

Srihari Padmanabhan — 2023-10-31

Neurochemistry about environment and neurodevelopmental disorders in children is the interesting part of the analysis of the research paper. This paper focuses on the effects brought on by toxins in the environment such as heavy metals and pesticides to a developing brain and common disorder relating to ADHD as well as autism spectrum disorders. Placing the focus on policy and community intervention, as well as to determine the effective step for intervention, this study examines the biochemical pathways to neurotoxic exposures. Therefore, the aim of this current study is to enhance knowledge on risks to the environment in order to afford optimal neurodevelopment to children.

A Review of Therapeutic and Medicinal Uses of Fenugreek (Trigonella foenum-graceum L.)

Chanda Shaheen — 2024-10-18

Current lifestyle and excessive use of synthetic fertilizers in agriculture field promote an unhealthy lifestyle that urges the researchers looking for a healthy and beneficial diet. Numerous crop plants have nutritional, functional, nutraceutical, and therapeutic properties. Fenugreek (Trigonella foenum gracium) is a popular crop known for these qualities and is beneficial in the human diet. It is an annual plant from the Leguminosae family that is commonly grown in the Mediterranean and Asian countries. It is mostly grown for its spices, though it can also be used for food (feed) and medicinal (antioxidant, antibacterial, anti-inflammatory, and hypoglycemic properties). Fenugreek is famous for its versatile uses, grown under moderate conditions (drought and salinity), white flowering herb, and self-pollinated plant. Fenugreek composition consists of various nutrients like vitamins, minerals, proteins, lipids, fibre, amino acids, and bioactive compounds that are used for medicinal purposes. Due to higher fibre content fenugreek is called a food stabilizer and emulsifying agent for changing food texture. Fenugreek has numerous health benefits, including the ability to lower blood sugar, heart problems, menstrual cramps, anti-cancer, reduce inflammation, and support healthy skin and hair. This review highlights the nutritional value of fenugreek with various health and medicinal benefits. Despite its multiple advantages, this review paper also discussed health problems associated with the usage of fenugreek, such as allergies and possible adverse effects linked with fenugreek use.

Influence of Impact Factor with Speed of Vehicle Under IRC Class AA and 70R Loading

Hamidullah — 2024-10-11

The impact factor is a critical parameter in bridge design, representing the additional dynamic forces that moving vehicles impose on the structure. This paper explores the influence of vehicle speed on the impact factor under two important loading conditions as per the Indian Road Congress (IRC) guidelines: IRC Class AA and 70R loading. Using theoretical approaches and Finite Element Method (FEM) simulations, we analyze how vehicle speed modifies the impact factor, leading to variations in structural response. The results highlight the relationship between vehicle speed, loading class, and impact factor, emphasizing the need for accurate dynamic modeling in bridge design.

Influence of Transient Static and Transient Dynamic Analysis on Deflection of Bridge Slab Using Finite Element Method in ANSYS

Hamidullah — 2024-10-11

The deflection behavior of bridge slabs is critical for ensuring structural safety and longevity. By using the Finite Element Method (FEM) in ANSYS, engineers can simulate and analyze the effects of both transient static and transient dynamic loads on bridge slabs. This paper explores how these two types of analyses affect the deflection behavior of a bridge slab. We present the mathematical formulations, practical applications, and a case study involving a bridge slab subjected to time-varying loads. The comparative results demonstrate the significant impact that the choice of analysis method has on predicting deflection and ultimately guiding structural design decisions.

Harnessing the Power of Renewable Energy: A Study of Sustainable Sources and Technologies

Shivani Pawar — 2024-09-19

This research investigates the capacity of renewable energy technologies to fulfill global energy requirements while mitigating environmental effects, concentrating on primary sources like sun, wind, hydropower, biomass, and geothermal energy. It evaluates the efficacy of various technologies for energy production, efficiency, economic viability, and reduction of carbon emissions. The findings underscore notable progress in solar and wind energy, demonstrating considerable efficiency enhancements (5% for solar PV, 10% for wind turbines) and cost reductions (67% and 64%, respectively) during the last decade. Hydropower is the most efficient energy source, converting 90% of available energy, albeit it is geographically constrained. The research highlights the environmental advantages, noting that renewable technologies substantially decrease CO₂ emissions—hydropower and wind energy prevent 250,000 and 120,000 metric tons of CO₂ annually, respectively. Nonetheless, obstacles such as the variability of solar and wind energy, elevated expenses associated with biomass and geothermal energy, and regional variations in implementation persist as substantial impediments. The research highlights the need for further developments in energy storage, grid modernization, and legislative assistance to expedite the worldwide shift towards renewable energy. This study synthesizes current statistics and trends, emphasizing the vital role of renewable energy in attaining a sustainable, low-carbon future, while also tackling ongoing economic and infrastructural problems.

The Impact of Job Stress on University Teachers' Career Development: The Mediating Role of Social Support

Mohammad Kazim Ameri — 2024-10-09

This article investigates the impact of job stress on the career development of Afghan university teachers, considering the mediating role of social support. Using a cluster sampling approach, data were collected from 370 teachers in both government and private universities through questionnaires. The analysis utilized SPSS and SPSS AMOS for regression analysis, guided by the Job Demand-Control-Support (JDCS) model.

Findings indicate a negative relationship between job stress and career development across all stages: early, mid, advanced, and continuing professional development. Higher job stress correlates with lower career development, while social support mitigates these negative effects. This underscores the need for interventions that address job stress and enhance social support to promote positive career outcomes for university teachers.

Leveraging Data-Driven Insights to Enhance Market Share in the Media Industry

Ankur Mehra — 2023-06-29

This comprehensive research paper explores the pivotal role of data-driven insights in augmenting market share within the media industry. The study investigates various facets of data analytics, including audience segmentation, content optimization, and personalization strategies. It delves into the technological infrastructure required for effective data analysis, examines consumer behaviour insights, and discusses monetization strategies informed by data. The paper also addresses competitive intelligence, content creation and distribution, organizational culture, regulatory compliance, and future trends in media analytics. By synthesizing current research and industry practices, this study provides a roadmap for media companies to leverage data-driven approaches for sustainable growth and competitive advantage.

Formulation Approaches for Deep Eutectic Solvents Solubilized APIs

Shweta Raj Rajeshwari — 2024-09-13

Increasing the efficacy of currently available medications is one of the pharmaceutical industry's main objectives. It is far simpler to develop current medications or enhance their efficacy than to create novel therapeutic candidates. This can be accomplished by altering deep eutectic solvents are prepared for solubility in the formulation techniques improvements made to different Active Pharmaceutical Ingredients (APIs).

Usually, to modify DES, compounds having hazardous profiles that were previously well-known determined. DESs are thought to function as solubilization carriers. The evolution Organic solvents such as ethanol and acetone ethers are typically needed for soluble medicines.

The melting of APIs is improved as a result. Along with improving the solubility of currently available medications, DESs also has a number of other uses.

Integration of Photonic Circuits in Electronics for Enhanced Data Processing and Transfer

Anjna Chetan — 2022-06-30

The rapid growth of data-intensive applications, such as artificial intelligence (AI), big data analytics, and cloud computing, has highlighted the limitations of traditional electronic circuits, particularly in terms of data transfer rates, processing power, and energy efficiency. This study explores the integration of photonic circuits with electronic systems as a viable solution to these challenges. By leveraging the speed and efficiency of photons for data transmission, photonic circuits promise substantial improvements over conventional electronic circuits. The research employs a mixed-method approach, combining experimental analysis with a comprehensive literature review. Experimental results demonstrate that hybrid photonic-electronic circuits can achieve up to ten times faster data processing speeds, a 30% reduction in power consumption, increased bandwidth, and reduced latency compared to traditional electronic systems. These advancements address key issues such as resistive losses and heat generation, offering enhanced performance for high-demand applications. However, challenges related to signal conversion and thermal management persist. Future research is needed to refine photonic-electronic integration and explore advanced technologies, including quantum photonics, to further enhance data processing capabilities. Overall, the study highlights the significant potential of photonic circuits to revolutionize data systems, providing a path towards next-generation computing technologies.

An Examination of the Biosafety and Ethical Guidelines in the Science Labs at Baniwaleed University

Abdulatti Othman Hammad — 2022-04-30

The aim of this study was to examine the prevalence rates of safety and work ethics in the academic laboratories of the Faculty of Science, Baniwaleed University among professors, technicians, students and workers. The data was collected through a questionnaire consisting of (11) questions applied to (30) professors, technicians, students and workers. The results showed that the majority of the segment used did not have sufficient information about safety and work ethics in the laboratories. The study produced a number of recommendations to help protect people, equipment and property in university laboratories.

Investigating the Causes of Heart Failure in Northern Afghanistan

Ahmad Tamim Azizi — 2024-09-13

Heart failure is a cardiac disorder in which the heart is unable to pump enough blood to other organs. These conditions can be caused by a variety of causes, including cardiovascular disease, high blood pressure, inherited diseases, and other factors. Therefore, early identification of the symptoms of heart failure and its proper treatment is very important in order to prevent its subsequent complications and progression. The aim of this study was to investigate heart failure in patients in northern Afghanistan. The statistical population of this study consisted of all patients referred to public hospitals in the provinces (Balkh, Kunduz, Takhar, Samangan, and Badakhshan).

The statistical sample of the present study consists of (460) patients referred to public hospitals in the northern provinces of Afghanistan. Data were obtained using patients' files and distributing questionnaires to patients. The collected data were entered into SPSS 28 software and then analyzed. The findings showed that out of 460 patients, 130 were referred to Balkh State Hospital, 88 to Kunduz Provincial Hospital, 81 to Takhar Provincial Hospital, 68 to Samangan Provincial Hospital, and 93 to Badakhshan Provincial Hospital. The results showed that among the symptoms of heart failure in patients, the most symptoms were shortness of breath (21%), peripheral edema (16.8%), fatigue and weakness (16.5%), dizziness (14.8%), weight gain (12.2%), heart palpitations (10.2%), and abdominal swelling (8.3%).

The Role of Managed ETL Platforms in Reducing Data Integration Time and Improving User Satisfaction

Alok Gupta — 2022-04-30

Managed ETL (Extract, Transform, and Load) solutions are essential for enhancing data acquisition that enhances the user’s satisfaction. By automation and optimizing data activities of these systems, integration times are saved and there is an enhancement of system stability noticed. It also outlines how multiple ETL approaches are discussed with consideration of comprehensive criteria that involves the clarity of a method, its scaling capabilities, user-friendliness, and performance in real-life scenarios. The results revealed that the managed ETL systems have a higher operational experience, but it faces challenges such as integration and usability issues. There is still a need to focus on the optimization of the future development of ETL systems, other performance factors, and the characteristics of the industry for the future enhancement of the existing problems.

Importance-Performance Analysis of Factors Affecting the Sustainability and Development of Poultry Farms (Evidence from Broiler Farms in Baghlan Province, Afghanistan)

Muhammad Asef Shaiq — 2024-10-22

Ensuring adequate food supplies has become a critical issue with a rapidly growing global population and increasing demand for protein-rich foods. In Baghlan province, Afghanistan, many poultry farms have been forced to cease operations due to insufficient infrastructure and resources, leaving a significant gap in meeting the region's growing demand for poultry products. This study aims to identify the key factors affecting the sustainability and development of broiler farms in Baghlan province as perceived by farm owners. The primary research tool was a researcher-developed questionnaire, whose validity and reliability were confirmed. The study population comprised all broiler farm owners in Baghlan Province, from which a sample of 91 was selected using the Morgan table and complete enumeration sampling method. The findings revealed that approximately 54% of respondents expressed moderate satisfaction with their farms. Importance-Performance Analysis (IPA) was conducted to assess the relative importance and performance of various factors affecting the development and sustainability of the farms. The results indicated that having a qualified expert, the farmer's educational level, the poultry house ventilation system, and being a local resident were considered highly important factors for farm success but were underperforming. Based on limited existing research in the region, these findings provide valuable insights for enhancing poultry farm development and food security in Baghlan province and throughout Afghanistan. The study offers specific recommendations for addressing the identified challenges and improving the sustainability of poultry farming in the region.

An Overview about the Influenza a Virus

Ghulam Rabani Neyazi — 2024-09-13

As influenza A can cause pandemics and epidemics with high rates of morbidity and mortality, it continues to be a major worldwide health concern. It is critical to comprehend its development, implications, and upcoming difficulties. This review explores the historical background, molecular causes, and modern management approaches for influenza A. Influenza A presents difficulties due to its rapid mutation rates and capacity to infect a wide variety of hosts. Even if vaccination is the main preventive measure, existing tactics have drawbacks that call for the creation of novel solutions. The overview covers the molecular mechanisms underpinning influenza A's pathogenicity, as well as the virus's historical history and effects on human health. It also looks at modern methods of treating influenza A, such as antiviral medication and immunization. To lessen the threat posed by influenza A, the review looks ahead, highlighting future research challenges and initiatives. It emphasizes the significance of enhancing global surveillance efforts, developing novel treatment options, and improving vaccine responses.

Preliminary Observations on the Novel Approaches in Fuzzy Conformable Differential Calculus

Ahlaam Salih Ahmed — 2022-04-30

This paper presents a novel extension of fuzzy calculus by integrating it with conformable calculus to introduce the fuzzy conformable derivative, a mathematical tool designed to handle the complexities of systems characterized by both uncertainty and fractional-order dynamics. The study begins by defining the fuzzy conformable derivative of order Ψ, which combines the ability of fuzzy calculus to model vagueness with the flexibility of conformable derivatives to capture non-integer order behaviors. This concept is further extended to higher orders, specifically the second order (2Ψ) and arbitrary order pΨ, enabling the modeling of more complex, multi-order dynamics in fuzzy-valued functions. Key contributions include the formal definitions of these derivatives, the establishment of their properties, and the development of operational rules that extend classical calculus operations to fuzzy systems. Additionally, the paper demonstrates how these derivatives can be applied to solve fuzzy differential equations and approximate functions using Taylor series expansions. While the fuzzy conformable derivative offers a powerful framework for modeling complex systems, the study also identifies certain limitations, such as potential unboundedness of solutions and the non-adherence to classical mathematical laws in higher-order cases. Overall, this work provides a comprehensive approach to differentiating fuzzy-valued functions in systems where uncertainty and fractional-order dynamics play a critical role. The proposed methods open up new avenues for research and application in fields such as control systems, economics, and engineering, where traditional calculus methods may not suffice. Future research directions include refining these methods, exploring computational techniques, and applying the framework to a broader range of real-world problems.

Role of Sericulture in the Indian Economy

Y. Praveen Reddy — 2024-09-04

Sericulture, often known as silk farming, involves raising silkworms to make silk. Out of the five states that contribute to the majority of India's silk production—Karnataka, Andhra Pradesh, Tamil Nadu, West Bengal, and Jammu & Kashmir -98.5% comes from mulberry sericulture. Silk plays a vital role in Indian culture and tradition, with a rich history spanning over five millennia. Sericulture, especially in Karnataka, supports farmers' livelihoods and has significant economic potential. However, climate change poses a serious threat to global ecosystems, endangering species and affecting industries like sericulture. The Author uses the study variables for their study and also questionnaires, and statistical tools like SPSS and Excel for data presentation and calculation respectively also used statistical techniques like, Factor Analysis, Descriptive analysis, and Relatively Analysis. Sericulture enhances income, crop diversification, sustainability, and land use efficiency, supported by government policies and training. Sericulture is vital to India’s rural development, job creation, and exports. It supports millions of rural households, especially women and marginalized communities, by generating consistent income. As one of the world’s top silk producers, India benefits from government-backed sustainable practices, making sericulture crucial to its economy.