The adsorption of Pb(II) ions onto bentonite and activated carbon was investigated. The effects of pH, initial adsorbent dosage, contact time and temperature were studied in batch experiments. The maximum adsorption capacities for bentonite and activated carbon were 0.0364 and 0.015 mg/mg, respectively. Thermodynamic parameters such as Gibbs free energy change, Enthalpy change and Entropy change have been calculated. These thermodynamic parameters indicated that the adsorption process was thermodynamically spontaneous under natural conditions and the adsorption was endothermic in nature. Experimental data were also tested in terms of adsorption kinetics, the results showed that the adsorption processes followed well pseudo second- order

Aim: The current study was aimed to determine the relationship between the orthodontic force applied by monobloc and the salivary level of alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) enzymes, considering the time factor after insertion of the appliance and whether there is a correlation between these enzymes. Materials and methods: A sample of 28 growing patients requiring orthodontic treatment with myofunctional appliance (Monoblock) was taken for the current study with an age range 9 to 12 years,all patients had Angle's class II division 1 malocclusion with no or mild crowding, the sample was selected using simple random sampling. Only 16 subjects (10 males and 6 females) were included who follow certain inclusion criteria.

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty