Flavia Oliveira Monteiro da Silva Abreu^1,2,*, Taysse Holanda¹, Joice Farias do Nascimento¹, Henety Nascimento Pinheiro¹, Rachel Menezes Castelo¹, Hélcio Silva dos Santos³, Thais Benincá⁴, Patrícia da Silva Malheiros⁴, Júlio César Sousa Prado⁵, Raquel de Oliveira Fontenelle⁵, Maria Madalena de Camargo Forte²

Journal of Renewable Materials, Vol.12, No.2, pp. 285-304, 2024, DOI:10.32604/jrm.2023.043919

Abstract With the increase in antimicrobial resistance, it has become necessary to explore alternative approaches for combating and preventing diseases. DB-cinnamaldehyde (CNM) and Benzyl4-amino (B4AM) are bioactive compounds derived from chalcones but with restricted solubility in aqueous media. Nanoemulsions can enhance the solubility of compounds and can be a promising alternative in the development of novel antimicrobials, with reduced side effects and prolonged release. The objective of this study was to evaluate the stability of oil-in-water nanoemulsions loaded with two distinct types of chalcones at two different dosages, to propose a stable formulation with antimicrobial properties. Results showed that nanoemulsions presented… More > Graphic Abstract

Jiahe Ni^*

Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 79-88, 2022, DOI:10.32604/jihpp.2022.039751

Abstract Image generation is a hot topic in the academic recently, and has been applied to AI drawing, which can bring Vivid AI paintings without labor costs. In image generation, we represent the image as a random vector, assuming that the images of the natural scene obey an unknown distribution, we hope to estimate its distribution through some observation samples. Especially, with the development of GAN (Generative Adversarial Network), The generator and discriminator improve the model capability through adversarial, the quality of the generated image is also increasing. The image quality generated by the existing GAN based image generation model is… More >

Ayesha¹, Muhammad Javed Iqbal¹, Iftikhar Ahmad^2,*, Madini O. Alassafi², Ahmed S. Alfakeeh², Ahmed Alhomoud³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3647-3661, 2023, DOI:10.32604/cmc.2023.020916

Abstract Contemporarily numerous analysts labored in the field of Vehicle detection which improves Intelligent Transport System (ITS) and reduces road accidents. The major obstacles in automatic detection of tiny vehicles are due to occlusion, environmental conditions, illumination, view angles and variation in size of objects. This research centers on tiny and partially occluded vehicle detection and identification in challenging scene specifically in crowed area. In this paper we present comprehensive methodology of tiny vehicle detection using Deep Neural Networks (DNN) namely CenterNet. Substantially DNN disregards objects that are small in size 5 pixels and more false positives likely to happen in… More >