The increasing discharge of dye-containing wastewater has become a serious environmental problem, requiring efficient and sustainable treatment technologies. In this study, poultry litter–derived biochar (BC) was prepared via pyrolysis at 550 °C and subsequently modified with chitosan to produce a composite adsorbent (BC/CS) for the removal of Congo Red (CR) from aqueous solutions. The materials were characterized using SEM, BET, XRD, FTIR, and XPS analyses. BET results showed that chitosan modification slightly decreased the specific surface area from 8.28 to 8.18 m²/g and pore volume from 0.035 to 0.030 cm³ /g, while introducing abundant amine and hydroxyl functional groups on the surface. Maximum adsorption occurred at pH 3, with equilibrium achieved within 35 min. The BC/CS composite exhibited a maximum adsorption capacity of 35.36 mg/g, which is approximately two times higher than that of raw BC (17.83 mg/g). Adsorption kinetics followed the pseudo-second-order model (R² > 0.999), indicating that the adsorption process may involve chemical interactions, while equilibrium data were well described by the Langmuir isotherm model (R² > 0.99), suggesting monolayer adsorption. In competitive adsorption experiments involving CR, MB, MR, and MO dyes, the CR adsorption capacity decreased by only 7.5% for BC/CS, indicating good selectivity. Furthermore, regeneration studies showed that BC/CS retained approximately 86% of its initial adsorption capacity after six adsorption–desorption cycles. These results demonstrate that chitosan-modified poultry litter biochar is an effective, low-cost, and sustainable adsorbent for the removal of anionic dyes from wastewater.
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
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Nowadays, there is a trend to promote the use of natural materials in dentistry. One of these compounds that has lately grown significantly in relevance in clinical research is
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Luminescent sensor membranes and sensor microplates are presented for continuous or high-throughput wide-range measurement of pH based on a europium probe.
Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20