This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m2/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of OG dye highly depends on H2O2 concentration (1.7-5.28 mM), catalyst dose (0.4-1.6 g/L), pH (2-7), initial OG concentration (25-75 mg/L), and temperature (20-50 ℃). Batch experiments showed that 94.8 % of 50 mg/L of OG dye was removed within the optimum peroxide concentration, dose, pH and temperature which were 3.52 mM, 1 g/L, 3, and 40℃ respectively along with 30 min contact time. The results of kinetic models showed that OG removal followed the second-order model. Finally, the thermodynamic study of reaction was also examined and concluded to endothermic reaction with 29.725 kJ/mol activation energy.
XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.
In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.
The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ
The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
... Show MoreAmorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.
This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.
Lactococcus lactis ssp. lactis isolated from raw milk was used for titanium dioxide (TiO2) nanoparticles biosynthesis. Biosynthesized TiO2 nanoparticles were characterized using UV-vis spectroscopy, Atomic Force Microscopy (AFM) (1.97 nm), X-ray diffraction (XRD) appa-ratus, Field Emission Scanning Electron Microscopy (FE-SEM), Energy dispersive X-ray anal-ysis (EDX) spectra and Fourier Transform Infrared Spectroscopy (FTIR). Result was 408.21 cm-1 that belong to anatase Titania. L. lactis ssp. Lactis isolates had the ability to synthesize TiO2 nanoparticles, the characterization results presented that the biosynthesized nanoparti-cles were at wavelength (344-347) nm; approving the formation of anatase phase of TiO2 NPs; spherical c
... Show More