Browsing by Author "Khan, Ibrahim"

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Biogenic Synthesis of Silver Nanoparticles Using Rhazya stricta Extracts and Evaluation of Its Biological Activities
(Daffodil International University, 2022-07-21) Bawazeer, Sami; Rauf, Abdur; Emran, Talha Bin; Aljohani, Abdullah S. M.; Alhumaydhi, Fahad A.; Khan, Zidan; Ahmad, Laiba; Hemeg, Hassan A.; Muhammad, Naveed; Sharma, Rohit; Maalik, Aneela; Khan, Ibrahim
Rhazya stricta is a well-known medicinal plant and source of numerous potential secondary metabolites including steroids, alkaloids, and tannins. R. stricta possesses multimedical applications and used for curing of various diseases such as inflammation, diabetes, sore throat, infectious, helminthiasis, arthritis, and cancer. The current investigation deals with synthesizing AgNPs using aqueous and ethanol extracts of R. stricta. The synthesized R. stricta-AgNPs were characterized through UV-visible, Fourier transform infrared (FTIR), and atomic force microscopy (AFM) methods. The UV-visible analysis exhibited a characteristic absorption at 475 nm in R. stricta ethanol AgNPs while this peak was absent in R. stricta aqueous crude extract. The thermal stability of R. stricta-AgNPs demonstrated that by increasing the reduction time and temperature, the absorption of AgNPs also increased, leading to more stable NPs formation. The FTIR spectra showed a broad peak at 450-550 cm-1 that confirmed the occurrence of AgNPs of R. stricta. The AFM study of the synthesized AgNPs revealed the spherical shape and size ranging from 30 nm to 90 nm. In antioxidant and antibacterial study, the R. stricta-AgNPs exhibited good antioxidant activity (87.94% and 88.37%) than the ethanol crude extract (50.00% and 56.81%) at 100 μg/mL using DPPH assay. Maximum antibacterial activity was recorded against Gram-positive bacteria (Staphylococcus aureus), which was 15 and 0 mm, while against Gram-negative bacteria (Klebsiella pneumonia) was found to be 16 and 14 mm, respectively, whereas against Bacillus subtills, a poor activity was recorded as 14 for extract and 0 mm for AgNPs, respectively. In the acetic acid-induced writhing model, the percent effect of extract (100 mg/kg) and AgNPs (15 mg/kg) was 79.98 and 83.23, respectively. The maximum muscle coordination effect of extracts in the inclined plan and traction test was 44% and 38% at higher doses. A mild sedative effect was also recorded against extract and AgNPs. The significant () effect of extract was noted at 100 mg/kg while AgNPs was more significant () at the tested dose of 15 mg/kg. These findings have concluded that R. stricta-AgNPs is an effective bioreductant of AgNPs synthesis and exhibit several applications in distinctive biomedical and pharmaceutical industries.
DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
(BRAC University, 2022-09) Khan, Ibrahim; Noor, Jannatun
Moiré artifacts is a special type of noise which is rarely considered in deep learning based image processing tasks. But with the increasing number of digital screens like TV, laptop, desktop screens etc. it is becoming common to take pictures of these screens to quickly save information and a common aliasing effect in these screen cap ture images is moiré pattern. These kinds of artifacts in images appear when two repetitive patterns interfere with one another. Moiré patterns degrade the quality of photos. It affects the performance of other deep learning tasks using these images like classification, segmentation etc. As the moiré pattern is highly variant, has im balanced magnitude in different channels and sophisticated frequency distribution, they are difficult to be completely removed without affecting the main information of the underneath image. Because of its complex nature, most state-of-the-art im age restoration and denoising related methods fail to remove these artifacts. In this paper I proposed an effective wavelet based deep learning model for removing moiré patterns which outperforms all other state of the art by large margins. My pro posed model recovers the details of the moiré free image using the wavelet packet transform. The Residual Dense Module Network and Dilation Convolution Network of our model acquires moiré information from almost all frequency ranges. One for high frequency range and other for low frequency range.
Green Synthesis of Gold and Silver Nanoparticles Using Opuntia Dillenii Aqueous Extracts
(Daffodil International University, 2022-03-26) Ahmed, Anees; Rauf, Abdur; Hemeg, Hassan A.; Qureshi, Muhammad Nasimullah; Sharma, Rohit; Aljohani, Abdullah S. M.; Alhumaydhi, Fahad A.; Khan, Ibrahim; Alam, Amir; Rahman, Md. Mominur
In the present study, gold (Au) and silver (Ag) nanoparticles (NPs) were synthesized from aqueous extracts of Opuntia dillenii, characterized by various advanced techniques and investigated for antibacterial and antifungal potential. Phytochemical screening of O. dillenii showed the presence of alkaloids, betacyanin, saponins, tannins, flavonoids, and phlobatannins. The characterizations of the synthesized metal NPs were performed such as UV-visible spectrophotometer, FTIR (Fourier transform infrared) spectrophotometer, SEM (scanning electron microscopy) and EDX (energy-dispersive X-ray). Through the application of such advance techniques, the UV-visible spectrophotometer showed the bands of absorbance for AgNPs and AuNPs at 420 nm and 525 nm range, respectively. The FTIR spectra for both and AgNPs also appeared in the range of 4000-400 cm-1. SEM was performed for the textural and morphological characteristics of the NPs such as shape, size distribution, and surface structure. Elemental analysis was recorded for the synthesis of Au and AgNPs, which confirmed its purity. The O. dillenii extract and their synthesized Au and AgNPs showed a clear zone of inhibition against the E. coli, S. aureus, K. pneumonia, and P. aeruginosa bacteria and T. viride, C. albicans, C. krusei, and A. niger fungal species.