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Background: The increasing demand for electricity, coupled with an imbalanced supply and demand, population growth, and climate change, has prompted the shift from conventional to non-conventional energy systems. However, the unreliability and intermittency of the latter pose a challenge to their feasibility. To address this challenge, a proposal has been made to explore the combination of two renewable energy sources (RES) using a unique DC-DC converter topology, with the aim of meeting the load demand in a sustainable and efficient manner. Objective: The focus of this research was to explore solutions for the challenges associated with operating RES independently, including issues with intermittency, weather dependence, and meeting load demands. The proposed hybrid system features exclusively RES, offering a promising approach to reducing carbon footprint. Ultimately, we aimed to develop a CUK-SEPIC-based converter that can effectively integrate two independent RES to satisfy the load demand of a standalone application. Method: Effective hybrid power generation through RES is a complex challenge, but it has been found that combining solar and biomass energy sources is one of the best options for achieving this goal. To tap into these sources, it is essential to have a suitable power electronic converter, and the CUK-SEPIC converter has been chosen for its many benefits. The features of this converter have been described in detail. The integration of solar and biomass energy sources is achieved using this converter, which has been designed and mathematically modeled in the MATLAB/Simulink environment to ensure optimal performance. To validate the effectiveness of the proposed converter, a comparison with existing power electronic converters has been done using the MATLAB/Simulink platform. Results: The hybrid power generation system model has been comprehensively developed in this work using the sophisticated MATLAB/Simulink environment. The input and output parameters have been diligently estimated through an extensive simulation process. The research has yielded valuable insights, indicating that the CUK-SEPIC converter exhibits an impressive power conversion efficiency of 96.57%, along with an overall step-up ratio of 5.25 and significantly reduced ripple content. Conclusion: Upon conducting a comprehensive analysis of the CUK-SEPIC DC-DC converter, it has been observed that the proposed system exhibits significant promise in rectifying the reliability issues commonly associated with renewable energy power generation. Therefore, it is recommended that this system be considered for implementation in rural electrification initiatives. Furthermore, it is worth noting that this system represents one of the most recent developments in the field of renewable energy power generation technology.

Background: This paper presents a novel approach to enhance the efficiency of solar cells by employing a modified spin coating technique with a Zinc oxide (ZnO) solution. Spin coating, known for its ability to achieve uniform, thin coatings on flat to moderately curved surfaces, serves as the central method in this research. The study meticulously investigates various factors affecting the coating process, including the volume of the solution, spinning speed, and spinning duration. To optimize these factors effectively, the Taguchi approach is employed, aiming to achieve the desired ZnO layer thickness and uniformity. The experimental findings reveal that the most favorable results are obtained when implementing a 3-second spin cycle at a rapid spin speed of 2000 rpm while using a ZnO solution volume of 5 microliters. Furthermore, advanced techniques such as scanning electron microscopy (SEM) are harnessed to scrutinize the surface characteristics of the ZnO layer and its interaction with the solution. To gauge the quality of the coatings, the signal-tonoise ratio (SNR) main impact plot is thoughtfully utilized. Subsequent in-depth analysis, employing the analysis of variance (ANOVA) technique, delves into the intricate relationship between the experimental parameters and the response parameter. The research outcomes are nothing short of remarkable, showcasing that the modified spin coating technique significantly elevates the efficiency of coated solar cells, ultimately achieving an impressive efficiency rate of 5.4%. In summation, this study introduces a pioneering spin coating technique tailored for solar cell applications with ZnO solution, leading to substantial enhancements in efficiency. The thorough optimization of process parameters through the Taguchi technique, coupled with the comprehensive analysis of experimental results via ANOVA, not only advances the comprehension of the coating process but also paves the way for more efficient and sustainable solar cell applications in the future. Methods: The research systematically explored critical factors affecting the coating process for solar cells, optimizing the ZnO layer's thickness and uniformity. The ideal parameters identified were a 3-second spin cycle at 2000 rpm with a ZnO solution volume of 5 microliters. Quality assessment was done using the signal-to-noise ratio (SNR) main impact plot, and further analysis via ANOVA revealed intricate parameter relationships. These findings offer a precise and efficient method for improving solar cell coatings, promising enhanced efficiency in renewable energy production. Results: The research achieved a minimum film thickness of 4.2 micrometers and revealed a correlation between spinning speed and film thickness. Solar cell efficiency reached an impressive 5.4% post-ZnO coating. The modified spin coating device outperformed conventional methods, enhancing efficiency by 5% to 10%. These results signify a significant breakthrough in improving solar cell performance and hold promise for more efficient solar energy production. Conclusion: This research optimized the spin coating process to apply ZnO solution to solar cells, achieving the desired film thickness. Ideal parameters were found: 2000 rpm spinning speed, three seconds spinning duration, and four microliters of solution. This resulted in a minimum film thickness of 4.2 micrometers. Higher spinning speeds correlated with thinner films, as shown in a contour plot. Solar cell efficiency reached 5.4% after the ZnO coating. A redesigned spin coating device outperformed conventional methods, improving efficiency by 5% to 10%. This modified technique holds promise for more efficient solar panel production.

COVID-19 (Corona Virus Disease of 2019) is a global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. This disease has significantly impacted every aspect of people's lives, including their work style, leisure activities, and use of technology. Additionally, due to psychological factors or other reasons, there has been a surge in deaths from cardiovascular failure during the pandemic. As COVID-19 is a silent killer whose symptoms only become visible after significant damage has been done, constant monitoring of heart parameters is crucial to address this issue. This paper explores the emerging trends in monitoring vital signs such as the electrocardiogram (ECG), heart rate, respiration rate (breaths), related sensors, remote sensor organization, and telemedicine innovations. Furthermore, this paper discusses the potential application of non-contact radar-based remote monitoring for vital sign monitoring of affected patients.

All over the world, cancer death and prevalence are increasing. Breast cancer (BC) is the major cause of cancer mortality (15%) which makes it the most common cancer in women. BC is defined as the furious progression and quick division of breast cells. Novel nanotechnology-based approaches helped in improving survival rate, metastatic BC is still facing obstacles to treat with an expected overall 23% survival rate. This paper represents epidemiology, classification (non-invasive, invasive and metastatic), risk factors (genetic and non-genetic) and treatment challenges of breast cancer in brief. This review paper focus on the importance of nanotechnology-based nanoformulations for treatment of BC. This review aims to deliver elementary insight and understanding of the novel nanoformulations in BC treatment and to explain to the readers for enduring designing novel nanomedicine. Later, we elaborate on several types of nanoformulations used in tumor therapeutics such as liposomes, dendrimers, polymeric nanomaterials and many others. Potential research opportunities for clinical application and current challenges related to nanoformulations utility for the treatment of BC are also highlighted in this review. The role of artificial intelligence is elaborated in detail. We also confer the existing challenges and perspectives of nanoformulations in effective tumor management, with emphasis on the various patented nanoformulations approved or progression of clinical trials retrieved from various search engines.

Picture categorization is a fundamental task in vision recognition that aims to understand and label an image in its entirety. While object detection works with the categorization and placement of many elements inside an image, image classification often pertains to photographs containing a single object. The development of sophisticated parallel computers in tandem with the introduction of contemporary remote sensors has fundamentally changed the picture categorization theory. Various algorithms have been created to recognise objects of interest in pictures and then categorise them and practise. In recent years, a number of authors have offered a range of classification strategies. However, there are not many studies or comparisons of classification techniques in soft computing settings. These days, the use of soft computing techniques has improved the performance of classification methods. This work explores the use of soft computing for image classification for various applications. The study explores further details regarding new applications and various classification technique types. To promote greater study in this field, important problems and viable fixes for applications based on soft computing are also covered. As a result, researchers will find this survey study useful in implementing an optimal categorization method for multiple applications.

In the last decade, the manufacturing capacity of silicon, the dominant PV technology, has increasingly been concentrated in China. This has led to PV cost reduction of approximately 80%, while, at the same time, posing risks to PV supply chain security. Recent advancements of novel perovskite tandem PV technologies as an alternative to traditional silicon-based PV provide opportunities for diversification of the PV manufacturing capacity and for increasing the GHG emission benefit of solar PV. Against this background, we estimate the current and future cost-competitiveness and GHG emissions of a set of already commercialized as well as emerging PV technologies for different production locations (China, USA, EU), both at residential and utility-scale. We find EU and USA-manufactured thin-film tandems to have 2 to 4% and 0.5 to 2% higher costs per kWh and 37 to 40%and 32 to 35% less GHG emissions per kWh at residential and utility-scale, respectively. Our projections indicate that they will also retain competitive costs (up to 2% higher)and a 20% GHG emissions advantage per kWh in 2050.

: Power generation in today’s world is of utmost importance, due to which blockchain is used for the categorization and formation of decentralized structures. This paper has proposed decentralized energy generation using a nester, i.e., energy sharing without third-party intervention. Decentralized blockchain technology is applied to ensure power sharing between buyer and seller, and also to achieve efficient power transmission between prosumer and consumer. Energy management is associated with controlling and reducing energy consumption. Blockchain technology plays a major role in distributed power generation, for example, power-sharing (solar and wind energy), price fixation, energy transaction monitoring, and peer-to-peer power-sharing. These are operations performed by blockchain in renewable power generation. Solar power generation using blockchain technology can obtain an impact resting upon the power generation system. Distributed ledger is the key area of blockchain technology for recording and tracking each transaction in the distribution system to improve the efficiency of the overall transmission system. A smart contract is another important tool in the blockchain technology, which is issued to confirm an assent between buyer and seller before starting any energy transaction without external intervention and also to avoid time delay. Maximum power point tracking is conducted in PV cells using blockchain technology. Blockchain influences energy management systems to improve the utilization of energy, optimize energy usage, and also to reduce the cost.