Walchand College of Engineering is a college in the city of Sangli, Maharashtra, India. The WCE campus is situated on nearly 90 acres of land in Vishrambag, roughly midway between the twin cities of Sangli and Miraj.The college was established in 1947 by the Dhondumama Sathe and began with an undergraduate course in Civil Engineering with a capacity of 60 students. It was affiliated with Bombay University in 1947. After Pune University was set up in 1948, the college became affiliated with Pune University. In 1955, the college was renamed after Walchand Hirachand, an industrialist. Since the establishment of Shivaji University, at Kolhapur in 1962, Walchand College of Engineering, Sangli has been affiliated with Shivaji University. Since 2007, it has been an autonomous college offering the B.Tech. degree in Maharashtra with 'financial and academic autonomy'. It is known for its vast campus and placement.
The interplay between metal ions and biological macromolecules is fundamental to life, governing processes such as enzymatic catalysis, electron transfer, and structural stability. This review, “Role of Metal Ions in Biological Systems: Structure, Function, and Therapeutic Implications,” summarizes the roles of essential and non-essential metals in the human body. Metalloproteins and metalloenzymes utilize the coordination chemistry, redox properties, and Lewis acidity of ions like Fe2+, Cu2+, Zn2+ Mg2+, and Mn2+ to facilitate complex biochemical reactions. Metals are categorized based on their biological importance, highlighting both structural and functional roles. Zinc stabilizes protein structures such as zinc fingers involved in DNA binding, while iron is crucial for oxygen transport in hemoglobin and electron transfer in mitochondria. Proper metal ion homeostasis is essential, as imbalance can lead to disorders such as iron-deficiency anemia, immune dysfunction, or toxicity from metal overload and heavy metals. The review also addresses therapeutic and diagnostic applications. Platinum-based drugs like cisplatin, carboplatin, and oxaliplatin are widely used in cancer treatment due to their DNA cross-linking ability. In diagnostics, gadolinium enhances MRI imaging, while technetium-99m is used in nuclear medicine. Emerging applications, including gold nanoparticles, further demonstrate the expanding role of metals in modern medicine.
For the first time, polycrystalline copper tin hydroxide [CuSn(OH)6] was used as an active and reliable photocatalyst to study the photocatalytic degradation of Navy Blue textile dye. The microcubes were produced using a rapid and scalable co-precipitation method, which produced excellent crystallinity and homogeneity. XRD, SEM, and EDS were used to extensively evaluate the structural, morphological, and elemental studies, respectively. UV-visible diffused reflectance spectroscopy was utilised to assess the optical characteristics of produced microcubes. The as-synthesised CuSn(OH)6 microcubes shown exceptional catalytic activity towards the degradation of Navy Blue dye when exposed to visible light. The polycrystalline particles' cube-shaped morphology offered a large surface area, which improved adsorption and photocatalytic efficacy. With the use of UV-visible spectroscopy to measure the degradation efficiency, it was discovered that a considerable amount of dye was removed in a little period of time. Within 180 minutes, the dye solution's absorbance peak had decreased by around 91%. As the pH of the Navy Blue dye solution rises, photocatalytic degradation performance increases until it reaches the ideal pH of 7 with 98% degradation efficiency. CuSn(OH)6 microcubes were tested against four bacterial strains: S. aureus (NCIM-2654), B. cereus (NCIM-2703), P. vulgaris (NCIM-2813), and P. aeruginosa (NCIM-5032) to determine whether they could be used as a stable photocatalyst for the degradation of Navy Blue organic dye and antibacterial activity. Therefore, it can be concluded that CuSn(OH)6 NPs have significant potential in biomedicine and exhibit both photocatalytic and antimicrobial activities.
The power infrastructure is facing difficulties due to the explosive growth in the electric vehicle industry. Especially because of the rise in electricity consumption brought by the traditional grid-dependent charging. Reliance on grid-based charging is the primary cause of this strain on the power system infrastructure. In addition to burdening the infrastructure, relying solely on the grid lessens the environmental advantages of EV adoption. A conventional EV charging system increases carbon emissions, reduces the benefits of carbon credits associated with clean energy usage and tend to increase the health issues. To recover this, the proposed work develops a novel sustainable EV charging system for commercial buildings using photovoltaic forecasting. The system integrates PV as a primary/preferable energy source, supported by battery storage and the electrical grid to maintain supply during low generation and peak demand periods. In this work, a charging system provides real-time data for PV forecasting, which is to be used for selecting the charging source as per the availability of solar energy and the energy needed, which avoids user inconvenience in trip planning. For the charging schedule, we can select either greedy charging mode or adaptive mode, and according to that mode selection EV gets charged. In this paper, the proposed framework is specially designed for commercial buildings where EVs remain parked during sunlight hours, which enables cost-effective and eco-friendly charging.
Under these circumstances, when we are still under the threat of various strains of coronavirus, RT-PCR is a long manual testing procedure that may generally result in a few hours to two days. This proposed system looks to create a model that uses a radiology based technique for detection. X-ray images are used for detecting the coronavirus. The aim of this study is to detect the patients whose x-rays are taken to check whether they are affected by COVID-19 or not. The dataset contains X-ray scans of people with Pneumonia, Normal and COVID-19 patients. This research work contains the implementation of VGG19, INCEPTION V3 and ResNet-50, the three algorithms, and a comparison of their results. For the image classification task, Convolution Neural Network (CNN) models take a crucial role. Evaluation of the model is performed using different metrics.
