Search

In the pursuit of sustainable transportation solutions, Electric Vehicles (EVs) have emerged as a promising alternative. This research paper provides an in-depth exploration of the crucial role played by Battery Management Systems (BMS) and conducts a comprehensive comparative analysis of various energy storage technologies for Electric Vehicles. The paper begins by elucidating the intricate components and functions of BMS through an illustrative block diagram, emphasizing its significance in ensuring safe and optimal battery operation. The study then conducts a meticulous analysis of key battery attributes, including energy density, power density, capacity, charge/discharge rates, life cycles, and cost per kWh. Supported by simulated data, the comparative analysis sheds light on the distinct performance characteristics of different battery types - Lithium-ion (Li-Ion), Lithium Iron Phosphate (LiFePO4), Nickel-Metal Hydride (NiMH), and Ultracapacitor. The outcomes offer a comprehensive perspective on their strengths and trade-offs, providing valuable insights for selecting suitable energy storage solutions. By translating intricate technical information into meaningful insights, this research empowers EV industry stakeholders to make informed decisions for enhanced EV performance, economic viability, and sustainable electric mobility.

Automatic bokeh is one of the smartphone’s essential photography effects. This effect enhances the quality of the image where the subject background gets out of focus by providing a soft (i.e., diverse) background. Most smartphones have a single rear camera that is lacking to provide which effects need to be applied to which kind of images. To do the same, smartphones depend on different software to generate the bokeh effect on images. Blur, Color-point, Zoom, Spin, Big Bokeh, Color Picker, Low-key, High-Key, and Silhouette are the popular bokeh effects. With this wide range of bokeh types available, it is difficult for the user to choose a suitable effect for their images. Deep Learning (DL) models (i.e., MobileNetV2, InceptionV3, and VGG16) are used in this work to recommend high-quality bokeh effects for images. Four thousand five hundred images are collected from online resources such as Google images, Unsplash, and Kaggle to examine the model performance. 85% accuracy has been achieved for recommending different bokeh effects using the proposed model MobileNetV2, which exceeds many of the existing models.

The National Cancer Institute and the National Institute for Diabetes and Digestive and Kidney Diseases initiated the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC) in 2015 (the CPDPC's origin, structure, governance, and research objectives are described in another article in this journal). One of the key objectives of CPDPC is to assemble a cohort of 10,000 subjects 50 years or older with new-onset diabetes, called the NOD cohort. Using a define, enrich, and find early detection approach, the aims of the NOD study are to (a) estimate the 3-year probability of pancreatic ductal adenocarcinoma (PDAC) in NOD (define), (b) establish a biobank of clinically annotated biospecimens from presymptomatic PDAC and control new-onset type 2 diabetes mellitus subjects, (c) conduct phase 3 validation studies of promising biomarkers for identification of incident PDAC in NOD patients (enrich), and (d) provide a platform for development of a future interventional screening protocol for early detection of PDAC in patients with NOD that incorporates imaging studies and/or clinical algorithms (find). It is expected that 85 to 100 incidences of PDAC will be diagnosed during the study period in this cohort of 10,000 patients.

Tilorone dihydrochloride (tilorone) is an orally active interferon inducer with anticancer effects. The present study aimed to evaluate the anticancer effects of tilorone in breast cancer. MTT assay was done to measure the proliferation of MCF‐7 and MDA‐MB‐231 breast cancer cells after treatment with tilorone. Mammary carcinogenesis was induced by subcutaneous injection (35 mg/kg, 0.5 mL) of dimethylbenz[a]anthracene (DMBA) in mammary pads of Sprague Dawley (SD) rats. Tumors were allowed to grow for 16 weeks till their sizes reached to 550–700 mm3, and then treated with 10 and 20 mg/kg of tilorone and standard drug doxorubicin (4 mg/kg) twice a week for 3 weeks. Normal and disease‐control animals received normal saline. Tumor volumes and body weights were measured. Tumors were isolated to measure the levels of interferon‐β (IFN‐β), vascular endothelial growth factor‐A (VEGF‐A), P53 and inflammatory markers by enzyme‐linked immunosorbent assay (ELISA). Serum biochemistry, lipid peroxidation (LPO) and antioxidant enzymes were measured by standard methods. Histopathology and immunohistochemistry (IHC) of P53 was done in tumor sections. Tilorone reduced the proliferation of MCF‐7 and MDA‐MB‐231 cells with IC50 concentrations at 34.08 µM and 14.27 µM, respectively. Tilorone treatment showed reduced tumor volume, and increased survival with no significant changes in the body weights. Tilorone treatment also decreased levels of inflammatory markers and VEGF‐A and increased IFN‐β and P53 levels. Further, treatment with tilorone also decreased LPO and increased antioxidants levels. Histopathology of tumor sections showed normalizing morphology of treated animals. IHC of tumor sections showed increased levels of P53. In conclusion, tilorone has potential anticancer effects against breast cancer. [ABSTRACT FROM AUTHOR]