Welcome to SciWaveBulletin, your dynamic source for the latest scientific advancements and knowledge. Our name combines "Sci," a short and powerful abbreviation for science, with "Wave," symbolizing the ever-flowing current of scientific progress. The term "Bulletin" signifies our commitment to providing regular updates and in-depth information on the most recent discoveries and trends in the scientific world. ISSN: 2584-1912 Publisher: EduPub Nexus Journal Type: Open Access Format: Online(e-Journal) Publication Language: English only Frequency: Quarterly (4 issues Annually) Review Process: Double Blind Peer review APC/Publication Fee: Free (till December 2024) Subject Category: Engineering, Science & Technology Subscription Fee: Contact Publisher for Subscription SciWaveBulletin Established in 2023, the journal is dedicated to delivering high-quality, peer-reviewed content to the scientific community. We uphold the rigorous standards of double-blind peer review to ensure the integrity and validity of the research we publish. Our commitment to excellence is mirrored in our publication schedule, offering four issues per year, each packed with the latest scientific findings and innovations. As an open-source journal, we are proud to provide free access to our content, ensuring that knowledge and discovery remain accessible to all. With an ISSN of 2584-1912, our journal is a trusted resource for researchers, scholars, and enthusiasts seeking valuable insights and groundbreaking discoveries in the world of science.
Quantifying Knowledge of Metrics and Measures in Modern Library Science
The content of this study attempts to get the role of measurement within contemporary library science and will deliver a comprehensive analysis on how performance and services are affected to the maximum in our country´s library systems. The research includes all manner of libraries, including universities, public libraries, special libraries, etc., and makes use of both quantitative and qualitative research methods for the purposes. The chief subject of study will include the historical development of library science; how the metrics currently employed have been interpreted; as well as the problems and opportunities that accompany present efforts to appraise the impact of library services. This research includes cases of successful metrics-driven change which analyze the impact of information literacy initiatives and evaluates the effect of outreach programs. This research project also treats the future of library science through the discovery. These results speak to the fluid character of digital-age library services, while suggesting that innovative techniques seam to be a necessity for adaptation and even growth of any durability in the new environment.
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Location Tracking Drives Modern Company Expansion
Location data is now a valuable commodity in our perpetually active, always-connected world. By capitalizing on its potential, businesses may boost operations, increase customer engagement, gain an edge in the marketplace, and open a treasure chest of opportunities. In this article, we'll take a peek at how location tracking has changed modern business, how it's used in different industries, and what moral dilemmas occur from utilizing it. Use of a smartphone's real-time geodata for the purpose to offer information, entertainment, or security is known as location-based services (LBS). Customers can use their services to check in at a variety of locations, including cafes, shops, concerts, and restaurants. Businesses tend to offer incentives, such as discounts, coupons, or prizes, to customers who check in at their venues.
Revolutionizing Cancer Therapy using Nanobots at the Frontier of Precision Medicine
New cancer treatment trials are necessary due to the various severe side effects of chemotherapy and the non-specific distribution of drugs. Scientists have been endeavouring to enhance anti-cancer therapy by employing various drug delivery systems (DDS) to more accurately target tumour cells. Due to progress in the field of nanotechnology, medical therapy has significantly expanded, including the utilization of DNA nanobots to identify various forms of cancer cells. Nanobots, which are minuscule robots engineered to function at the cellular level, possess significant potential for transforming cancer treatment. These are little devices, specifically developed to locate and eradicate cancer cells with accuracy, while leaving unaffected healthy tissues. The current design of the nanobots enables them to identify and distinguish 12 distinct types of cancer cells. The purpose of this review paper is to emphasize the significance, functionality, and utilization of nanobots.
Machine Learning and Cloud Computing Case Study for Online App Usage Tracking
Scalability, data processing, and real-time insights are not present in traditional online app usage tracking. ML can overcome these restrictions and open new possibilities with cloud data, in accordance with this study. In our case study, cloud data and ML boosted how a fitness software tracked user activity hours. Cloud systems store and manage massive amounts of user activity logs, device data, and network traffic of program usage. ML systems can learn trends, predict user behavior, and gain insights from this data. Fitness app data accuracy, user experience, and scalability improved with these technologies. On other web app domains, this method can improve user engagement tracking and personalization.
Copyright (c) 2023 Authors and SciWaveBulletin
Navigating Financial Complexity: Language Processing Insights for Modern Businesses
Complex financial markets generate massive volumes of unstructured text data from news, publications, social media, and analyst comments. NLP can assist investors and traders make real-time judgments using this data. Analysis of markets This article reviews NLP advancements in three main areas. Generally favorable, negative, or neutral opinions toward companies, industries, or markets. Conversational tone predicts market and investor confidence using machine learning and sentiment lexicons. Finance conversation topic discovery. NLP algorithms may find hidden patterns and investment possibilities by identifying frequently occurring keywords, phrases, and entities in vast text corpora. Classifying critical events like profits, mergers, and regulations. NLP can warn traders and improve real-time trading decisions by gathering vital news and financial data. Sentiment analysis and transaction volume are used in stock market case studies. Market mood may affect trading performance, since numerical models link favorable sentiment to stock price increases. The importance of active trading in price changes is shown by regular trade volumes.
Unveiling Data's Tapestry: Challenges, Opportunities, and Netflix's Analytical Triumph
The exponential expansion of data collection and the development of better methods for processing and analyzing it have been the primary drivers of the data analytics industry's meteoric rise in popularity in the last several years. This article explores the present state of data analytics, focusing on its possible problems, prospects, and growth trajectory. The decision-making processes, operational efficiency, and innovative capabilities of firms, organizations, and communities in all kinds of different industries have been profoundly affected by this rise. To further demonstrate the significance of data analytics to Netflix's success, the article includes a case study of the firm. The ever-changing IT business offers many possibilities and risks. Technology has constantly transformed our digital lives, affecting industry-defining professions. AI has gone from science fiction to our digital lives, from chatbots to autonomous automobiles. This revolution relied on big data analytics, machine learning, and AI. Machine learning, a subset of data science, has enabled astonishing discoveries and projections by teaching computers new abilities and knowledge without human interaction. The results illustrate data analytics' problems and prospects, explaining Netflix's analytical success. Netflix's complex audience analytics ecosystem is examined in this research.
Tantalum Extraction and Its Wide-Ranging Significance
Tantalum is a transition metal with atomic number 73. It has a shiny, silvery-gray appearance and offers a distinctive set of characteristics that give it significant value in a range of applications. Tin is commonly found in association with niobium (Nb) and tantalum (Ta). Cassiterite (SnO2) is the primary tin mineral, typically containing substantial quantities of both niobium (Nb) and tantalum (Ta) compounds. A significant portion of these components are left behind in the slag that is produced at the end of the industrial process, which occurs during the extraction and refining stages of the tin manufacturing process. Those slags are already capable of being considered as a potential and significant source of refractory metals such as tantalum and niobium due to their potential. The mining sector is vital to the nation's gross domestic product (GDP), and tantalum is an important component of that industry. The extraordinary element tantalum is discussed in this abstract, along with its extraction, important properties, and many applications.
Quantum Field Theory: Advanced Calculations in Nonperturbative Regimes
A number of sophisticated mathematical techniques, including the Functional Renormalization Group and Operator Product Expansion, are used in this research work in order to investigate the nonperturbative characteristics of quantum field theories. A comprehensive investigation of the scale-dependent effective action is carried out in this work. Emergent mass scales, critical phenomena, and confinement are all taken into consideration. A full knowledge of nonperturbative dynamics may be obtained via the use of numerical and analytical results, while the investigation of complicated quantum field theories can be optimized by partnerships between theory and computing. The discoveries provide a substantial contribution to the development of theoretical physics, hence opening up new options for future study and growth across several disciplines.
Revamping Urban Mobility: Metro AFC and RFID Analysis
Automatic Fare Collection (AFC) and RFID technologies in Metro stations are examined in this article. The research analyzes their functions, effect, and future potential to demonstrate their role in urban mobility revolution. In today's busy cities, efficient and dependable transportation networks are crucial for economic growth, social cohesion, and environmental sustainability. Automatic Fare Collection (AFC) and Radio Frequency Identification (RFID) have transformed urban mobility, changing how commuters’ traverse. RFID technology enables contactless connection between smart cards and AFC gates. RFID chips in smart cards transmit unique radio signals that gate readers collect. These readers decipher tag data to validate user credentials and authorize access. This safe and efficient connection prevents fraud and unauthorized access to transactions.
Comprehensive Study of Data Mining Applications in Agriculture
Due to sensor and satellite data, the agriculture business is transforming rapidly. Data collection is driving this transformation, bringing unprecedented opportunity to improve agricultural operations, resource usage, and harvest yields. These data-driven insights might transform agriculture, boosting hopes for sustainable and efficient farming. Data mining, a sophisticated method for extracting insights from massive datasets, has great potential for unearthing new and relevant agricultural data. Data mining allows farmers to use large data to make better choices, increasing production and sustainability. Based on the content and case study, a comprehensive approach to data mining in agriculture includes preprocessing data to handle outliers and ensure consistency, exploratory data analysis to identify trends and correlations, decision trees, association rule mining, and predictive modeling like Random Forests. Cluster analysis and pattern recognition improve agricultural data interpretation, helping farmers choose the best methods and control diseases and pests. As seen in the case study, this complete methodology gives the agriculture sector practical information to maximize crop productivity and sustainability.
Natural Language Processing relevance to Online Business
NLP is essential for internet companies. Its language processing capabilities allow sophisticated apps that are changing the internet world. NLP's main effects on internet business are summarized in this abstract: NLP powers 24/7 customer care chatbots and virtual assistants that answer questions and process transactions. Sentiment research helps companies analyse client feedback and adjust services. NLP algorithms assess user behaviour and preferences to propose products and run marketing campaigns. NLP generates website, social media, and marketing content automatically. NLP's capacity to discover keywords and optimize content for individual audiences revolutionizes SEO. Businesses may use NLP to evaluate customer evaluations and detect patterns for content strategy. NLP analyses massive volumes of social media, news, and competition data. This helps firms follow market trends, evaluate customer attitude toward their brand and rivals, and find new possibilities. Online transaction security and fraud detection depend on NLP. NLP systems can detect questionable emails, phony reviews, and cyber-attacks by analysing text patterns and user behaviour, reducing risks and assuring safe online transactions. NLP helps firms reach foreign customers and meet various demands by bridging language gaps. NLP-powered machine translation removes language barriers and opens new markets with real-time content localization.
Exploring the Ecological Harmony of Organic Farming Practices
As global consciousness regarding the environmental consequences of human decisions has grown, organic farming has experienced a meteoric rise in popularity. It is an ecologically safe and sustainable method of agriculture that emphasizes the use of natural techniques for crop cultivation and livestock husbandry. Both the quality of the food and its safety are two significant aspects that have garnered an ever-increasing amount of attention from customers in general. Conventionally farmed foods have significant detrimental health impacts as a result of greater levels of pesticide residue, increased nitrate content, heavy metals, hormones, antibiotic residue, and the presence of genetically modified organisms. The production of food, fiber, and other agricultural goods may be accomplished via the use of organic farming. This is a holistic strategy that places an emphasis on the health of the land, the environment, and the people who are responsible for growing and consuming the food. The case study used in this study contrasts organic and conventional tomato production over three months. The research compares yield, cost, and environmental effect to show the trade-offs. It examines how farmers and stakeholders may balance economic returns and sustainable agriculture using hypothetical data.
5G Technology is Revolutionizing the Wireless Industry with Unparalleled Efficiency
Wireless technology of the fifth generation, often known as 5G, ushers in a new era of increased speed, capacity, and connectivity in the field of telecommunications. This research investigates the characteristics, technologies, and possible impacts of 5G across a variety of industries. Real-time data sharing, high-definition video transmission, and immersive virtual reality experiences are all made possible by the peak data rates of 5G, which are 10 times faster than those of 4G. The millisecond latency of 5G makes it possible to achieve almost instantaneous communication, which opens up opportunities in areas such as industrial automation, remote surgery, and autonomous cars. The case study discussed in the study is to evaluate the effect that upgrading from 4G to 5G technology will have on the efficiency of mobile infrastructure. An examination of the download speeds of ten different devices showed a tremendous average speed boost, with 5G speeds averaging indicating the significant efficiency gain that can be achieved with the introduction of 5G. These results highlight the revolutionary effect that next-generation (5G) technology will have, which will greatly improve the performance of wireless networks.
Fraud Detection in Online Content Mining Relies on the Random Forest Algorithm
Web data mining extracts insights from the massive volume of Web data. This intelligence may improve search engine results, analyze consumer patterns, and detect fraud. Web content, structure, and use mining are the primary categories of web data mining. Web content mining analyzes text and multimedia on websites. online structure mining examines connections between online sites to determine web topology. Web use mining examines user clickstreams to understand browsing activity. Many methods, tools, and algorithms may be utilized for web data mining. Popular methods include keyword extraction, clustering, classification, and association rule mining. Web data mining technologies like Weka, RapidMiner, and KNIME are popular. Popular algorithms for web data mining include K-means, Naïve Bayes, and Apriori.
Bochner-Riesz Summability Below the Critical Index: Applications and Sharp Estimates
This research paper investigates the realm of Bochner-Riesz summability in two dimensions, providing distinct results and insights on the convergence properties of Fourier series. More precisely, the study examines the convergence properties of Fourier series. This article establishes two significant theorems: Theorem 4.1.1 offers proof that the Bochner-Riesz operator in L2(R2) is bounded for a certain multiplier function. However, this claim is contingent upon a crucial criterion. Theorem 4.1.2 presents precise estimates that indicate the logarithmic dependence on certain parameters and highlight the intricate behavior of the operator. These theorems have potential applications in signal processing and imaging, and they also serve as a solid foundation for comprehending harmonic analysis and singular integral operators. The last portion of the paper has some suggestions for further investigation. The proposals include doing research on higher dimensions, investigating the impact of additional variables, and exploring practical applications in real-world scenarios.
Millets for Health: Nutrigenomic Revelations and Innovative Processing Solutions
Millets are a collection of minuscule grain cereal crops that are cultivated in areas with limited fertility and rely on rainfall for irrigation. Millets are the most practical crops, making them an ideal match for the present circumstances of food insecurity, destitution, nutritional difficulties, and marginal agriculture. These crops are known for their high nutritional value and various test techniques revealed that the millet types had the highest antioxidant potential. Millets' antioxidant, anti-atherosclerogenic, anti-hypertensive, anti-inflammatory, hypoglycaemic, anti-tumorigenic, and antimicrobial characteristics have been a boon to human health, and they play an important part in nutrigenomics. Using current research as a foundation, this study delves deeply into millets' nutraceutical characteristics, possible health advantages, and processing. Millets including Pearl, Finger, Foxtail, Proso, Kodo, Little, and Barnyard Millet are nutritious powerhouses with different protein profiles. These antioxidant-rich grains are hypoglycemic, anti-atherosclerogenic, and anti-inflammatory. Malting, extrusion cooking, and fermentation improve millets' nutritional profiles, making them flexible for cooking. Albumins, globulins, prolamins, and glutelins make about 7-14% of the protein. Millets provide sustainable solutions for global food security and nutritional issues, albeit values vary by variety and processing.
A Comprehensive Analysis of Cloud Computing Impact on Digital Transformation in E-India
Cloud computing is transforming how businesses and consumers use resources. Cloud computing has great potential to speed Digital India's digital transformation. Cloud computing has shaped the Digital India vision in many ways, and this paper examines its effects on different sectors and offers methods for cloud adoption. Cloud computing has many benefits that support Digital India. On-demand access to scalable and elastic computing resources facilitates collaboration, creativity, and empowerment. Cloud computing also saves infrastructure administration costs and improves data security. The purpose of this article is to present a pragmatic strategy that is anchored in real-world measurements and qualitative evaluations. In addition to highlighting the theoretical advantages of cloud computing in Digital India, this study also provides a pragmatic approach. These results are offered with the intention of assisting stakeholders in making well-informed choices on cloud adoption, which will ultimately result in a digital transformation path that is more streamlined and has a greater effect on the country.
Exploring the Intersection of Fuzzy Logic and Quantum Logic: A New Frontier in Non-Classical Logics
Fuzzy logic can handle ambiguity and uncertainty. Quantum physics led to the development of quantum logic, which, unlike fuzzy logic, is based on projectors' vector subspaces. The two theories' relationship is fascinating. These non-classical logics provide viable solutions for handling intricacy, uncertainty, and information processing in a variety of disciplines. The applications of fuzzy-quantum logics in artificial intelligence, decision-making, control systems, and quantum computing are covered in this article along with possible future research paths in the field. We also look at the evolution of quantum fuzzy information theory as well as the application of quantum logic theory to fuzzy logic and other non-classical logics. We also stress the potential of mixed algorithms and optimisation methods based on fuzzy-quantum logics to address challenging issues. We wrap up by highlighting the importance of additional study in these fields and summarising the overall results. The suggested study directions could help non-classical logics progress by producing fresh ideas, theories, and applications that might have an effect on a number of different disciplines and stimulate innovation there
Predicting Uterine Fibroids with Multiple Classifiers: An Analysis
Many companies actively use data mining. Healthcare data mining is becoming more common and important. All parties in healthcare can benefit from data mining. Health insurance companies may use data mining to help them spot instances of fraud and abuse, businesses can use it to inform decisions about their relationships with customers, doctors can use it to discover new, more cost-effective therapies, and individuals can enjoy better, more affordable health care overall. Traditional methods cannot process and analyze healthcare transactions' vast amounts of data in today's culture. Data mining helps turn large amounts of data into decision-making knowledge. This post examines healthcare data mining applications. Data mining is also discussed in healthcare for treatment effectiveness evaluation, healthcare management, customer management, and fraud or abuse detection. It also shows how a healthcare data mining tool may identify uterine fibroids risk factors.
Structural Modification in Oleanolic Acid for Antiviral Activity
Oleanolic acid (OA) is a triterpene of the pentacyclic oleanane-type that is derived from several edible and medicinal plants. It exhibits a wide spectrum of pharmacological effects and possesses significant therapeutic potential. The usage of Oleanolic acid doesn’t have wide application, to increase its therapeutic effects several studies on structural changes of OA have been conducted. The objective is to study and explain current developments in medicinal chemistry of OA derivatives, with a focus on the structural modification of OA in recent years (2010–21). Most causes of worldwide deaths are Herpes, Hepatitis, Human immune deficiency virus (HIV) and influenza. There is a critical need for the discovery of new and robust antiviral medications, as evidenced by the dearth of efficient treatments or vaccines for the addressing the many viral diseases through prevention and therapy as well as the sharp rise in new viruses that are resistant to drug. Natural products drug discovery is one of the most valuable sources. There are several different techniques and chromatography platforms that may be utilized in order to extract and isolate oleanolic acid, which is a pentacyclic triterpenoid found in a broad variety of plant species, including fruits and vegetables. This study found that modification of Oleanolic acid structure at various sites for antiviral activity.
Quantum Power Flow: Revolutionizing Power Systems Analysis
This research investigates the transformative potential of Quantum Power Flow (QPF) in power systems analysis. Leveraging quantum computing principles, the study explores quantum algorithms for power flow simulations to enhance computational efficiency and solution accuracy. The Quantum Power Flow method is introduced, addressing challenges arising from the growing complexity of power systems, especially with increased renewable energy integration. The mathematical foundation of the Quantum Power Flow method is detailed, emphasizing quantum parallelism and computational advantages. Experimental validation, simulations, and research case studies collectively establish the practical viability and versatility of the proposed quantum approach. A 5 and 3-bus power system case study illustrates its applicability. Acknowledging current quantum computing challenges, including error susceptibility, the study highlights ongoing advancements and error correction mechanisms' potential to overcome limitations. The research concludes by discussing broader implications of quantum power system analysis and outlining future research avenues. In summary, this research comprehensively explores Quantum Power Flow, offering theoretical insights and practical demonstrations. As quantum computing evolves, this study contributes to the paradigm shift in power system analysis, opening new horizons for research and application.
R-Based Machine Learning for Uterus Fibroid Detection and Prediction
The growth of benign tumors in the uterus is known as uterine fibroids. By the age of 50, they have affected as many as 70% of women, making them the most frequent gynecological condition. Although the majority of fibroids do not create any noticeable symptoms, a small number of them might lead to issues like heavy periods, pelvic pain, and infertility. For better patient outcomes, uterine fibroids should be detected and diagnosed early. Uterine fibroids can be accurately detected and predicted with the use of machine learning methods. Here, we provide an innovative approach to uterine fibroids detection and prediction in R-based Support Vector Machine (SVM). We test our approach against other machine learning methods using a dataset of patients with uterine fibroids.
Making Sustainable Agriculture Possible Through the Utilization of Plant-Microbe Interactions
Through the use of a controlled greenhouse experiment, this research analyzes the function that plant-microbe interactions play in the promotion of sustainable agriculture. In this study, we used a randomized complete block design to investigate the influence that arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) have on the development of wheat (Triticum aestivum) and soybeans (Glycine max). The results showed that there was a considerable improvement in the parameters of plant growth, notably in the group that was treated with AMF. This improvement included an increase in shoot height, root length, and biomass. While this was going on, indices of soil health showed that the soil that had been treated with AMF had a higher microbial diversity and it contained more nutrients. These results highlight the possibility of using certain plant-microbe interactions, in particular with AMF, to promote both the development of plants and the health of the soil in sustainable agriculture. The research underscores the relevance of these relationships in terms of minimizing dependency on synthetic inputs, lessening the effect on the environment, and supporting agricultural systems that are resilient.
Intelligent Cross-axis Solar Power Tracking System
The sun is an abundant and powerful renewable energy resource that plays a crucial role in sustainable energy production. With efficient power generation in mind, here is a system designed to make intelligent judgements based on a condition so that the solar panel is always tilted towards the maximum sunlight. The hybrid intelligent cross-axis solar power tracking system is built using the microcontroller, light sensors, solar panel, and motors. Here, there are two methods used namely, the Sun Position Algorithm and the other is using the sensors. The algorithm uses the azimuth angle and the sun’s altitude to identify the position of the sun depending on the geo location. For maximum power generation from the solar panel, we use the sensor-based technique to come into picture whenever the output voltage is less than the fixed threshold voltage using the Sun Position Algorithm.
The Gut Microbiota's Impact on Metabolic Wellness or Disease
Controlling the human gut microbiota by dietary interventions has the potential to prevent and cure metabolic illnesses. The human gut microbiota has a substantial influence on the health of the metabolic system. Within the scope of this investigation, a randomized controlled trial was used to investigate the effect of a particular dietary intervention on the microbiota of the gut, as well as the following influence that this intervention had on metabolic indicators. Significant improvements in metabolic outcomes were seen among the individuals in the intervention group. These improvements included a significant decrease in fasting glucose levels as well as positive changes in specific microbial taxa, such as an increase in the abundance of Bifidobacterium. These results provide insight on the prospect of using treatments that particularly target the microbiota in order to enhance metabolic health. Our understanding of the dynamic interplay between the microbiota in the gut and the metabolism of the host is improved as a result of this study, which provides essential insights for the development of future individualized strategies for the prevention and management of metabolic diseases.
Leveraging Artificial Intelligence to Revolutionize Healthcare: A Comprehensive Analysis
The advent of AI has brought about a sea change in the healthcare industry, opening up new possibilities for better clinical decision-making, better patient outcomes, and more efficient administrative operations. This extensive article explores the various ways AI might be used in healthcare, showing how it could solve some of the biggest problems in the field. Enhanced clinical decision-making, better patient outcomes, and simplified administrative operations are all possible thanks to the incorporation of artificial intelligence (AI), which has sparked a tsunami of transformation within the healthcare industry. This wave has reshaped traditional procedures and opened up paths that have never been explored before. This comprehensive investigation digs into the many ways in which artificial intelligence might be used in the healthcare industry, analyzing its potential to solve significant difficulties that are present in the sector. Furthermore, the study presents an investigation of the function that artificial intelligence plays in enhancing administrative efficiency within healthcare organizations. Artificial intelligence allows procedures to be optimized, hence reducing operational difficulties and improving resource allocation. This is accomplished via intelligent automation and insights powered by data. These factors, in turn, lead to the development of a healthcare infrastructure that is more effective and responsive.
Inclusive Review of Machine Learning in the Automotive Sector Today
The fast advancement of machine learning (ML) is driving a deep transformation in the automobile industry, which is now in the midst of this transformation. This game-changing technology is gradually being incorporated into many aspects of vehicle development, manufacturing, and functioning, which has resulted in significant improvements in terms of efficiency, safety, and customisation. In this study, a comprehensive analysis of machine learning applications within the automobile industry is presented, shining light on the far-reaching implications that machine learning has across a variety of industries. We investigate the influence that machine learning has had on the design of vehicles, the manufacturing processes, and the operational efficiency, highlighting the vital role that it has played in transforming the sector. This article provides an overview of the most important trends and future trajectories in the junction of machine learning and automotive technology. It also provides insights into the changing landscape of this dynamic sector. For the purpose of tackling difficulties related to overall equipment efficiency (OEE) and improving climate control systems, the research explicitly investigates the role that machine learning plays. The purpose of this comprehensive analysis is to contribute to a more in-depth knowledge of the current status of machine learning (ML) in the automobile industry as well as its possible implications for the future. This will be accomplished by offering a holistic viewpoint.
Efficient delivery of Antiepileptic Drugs (AED’s) and Nanomedicine for the treatment of epilepsy
A common brain disorder affecting people of all age groups is epilepsy. It is characterized by development of seizures. To control the frequency of seizures a broad group of AED’s (Antiepileptic drugs) were given. Epilepsy is a neurological disorder. The limited solubility and accessibility of AEDs across the blood brain barrier (BBB) have limited their oral administration. Because of their long-term drug release, low toxicity, and biocompatibility, nanomaterials were employed to administer AEDs. This paper describes about different types of AED’s and their structure, mechanism of action, and treatment of epilepsy using nanocarrier via blood brain barrier. Nanomaterials cross the BBB and used barrier for the diagnosis of epilepsy. This paper describes about various AED’s and nanomedicines for the treatment of epilepsy. Nanomaterials have been developed for efficient delivery of AED’s as well as imaging agents into CNS. These nanomedicines easily cross BBB to diagnose epilepsy. The intranasal administration route is more efficient way to deliver nanoagents for diagnosis of epilepsy.