Adsorption is a widely used method for the treatment of dissolved contaminants. Various agro-industrial wastes have been explored as potential adsorbents, showing high efficiency in dye removal. Each adsorbate-adsorbent pair needs kinetic, and equilibrium models to scale up this process. In this work, the equilibrium, kinetics and thermodynamics of the corn Tuza-Red 40 system were evaluated under batch system at ph = 2.0 at temperatures of 25, 40, and 55 °C. The Langmuir, Freundlich and Temkin models were selected for the isotherm representation, while the Lagergren, Ho, and Elovich equations for the kinetics of the process. The Freundlich model presented the best fit to the isotherms, the adsorption kinetics was best described by the Ho equation, and the values for Gibbs free energy and entropy indicated the spontaneity and feasibility of the process.

The content of flavonoids in mesophyll cells of wheat was studied under the condition of enhanced UV-B radiation intensity. In this experiment, four groups of six days of control were treated with He-Ne laser group (L), enhanced UV-B radiation group (B), He-Ne laser and UV-B combined treatment group (B + L ), Normal light group (CK). Since the flavonoids carry some unsubstituted hydroxyl or glycosyl groups, it is a polar compound. By the 'similar compatibility' principle, they have some level of solubility in polar solvents, such as methanol, ethanol, n-butanol, propanol, and water. In this experiment, 70% ethanol was used to extract flavonoids. Finally, the total content of flavonoids in mesophyll cells was determined by visible spectrophotometry. The OD value of flavonoids was determined by rutin reagent 'The standard curves because rutin is a representative of flavonoids, it scavenging the role of free radicals significantly. The results showed that when the UV-B UV radiation intensity was enhanced, the content of flavonoids in wheat mesophyll cells increased, that is, the content of flavonoids in wheat leaves was higher than that in UV-B Strength was positively correlated. The results showed that the content of flavonoids in the mesophyll cells of the four control groups was the same as that of the B group> BL group> CK group> L group. With the prolonging of the treatment time of wheat, the content of flavonoids in wheat leaves at jointing-booting stage was significantly higher than that in seedling stage and panicle stage. This means that flavonoids are a protective substance that absorbs UV-B in plants, that is, the absorption of UV-B by flavonoids reduces the damage of UV-B to organs in plants [8] [10]; UV-B The smaller the damage, the less the content of flavonoids; laser damage caused by UV-B have a certain role in the repair. In this study, we further studied the effect of enhanced UV-B radiation on the content of flavonoids in mesophyll cells of wheat. The effects of UV-B radiation on the content of flavonoids in wheat were studied. Whether it has a very important significance for wheat has become a stress [5].

The growing of plants hydroponically is a soilless form of growing in modern day agriculture. It helps to make feed available for animals throughout the season since it is not affected by what is faced by field grown crops. The use of animal waste, that is, their faeces, in the growth of forage was compared with commercial hydroponics solutions as a way of looking for a reduction in the cost incurred in the purchase of commercial hydroponics solutions. The study evaluated the use of organic nutrient solutions (ONS) alongside a standard/commercial nutrient solution in growing crops hydroponically on the growth, dry matter yield, water use efficiency, and chemical composition of hydroponic maize fodder. The ONS used were formulated from the dried faeces of cattle, poultry, rabbits, and swine. The prepared organic nutrient solutions with the control were used in growing the maize seeds for 10 days, and growth, yield, and chemical composition were determined. Results show the highest (196 g) dry matter yield for maize hydroponic fodder irrigated with poultry ONS. Similarly, maize irrigated with poultry ONS was significantly (P < 0.05) higher in CP content, while it was not significantly different from maize irrigated with cattle, swine, and commercial solutions. A lower water use efficiency value (0.19 kg DM/m³) was recorded for maize irrigated with cattle ONS. According to the study, irrigating maize with different organic nutrient solutions produced maize fodder with a higher yield and a similar chemical composition as the commercial nutrient solution. 

Environmental Education (EE) programs are of crucial importance. EE are aimed at global citizenship to generate new knowledge and new, more participatory and conscious ways of acting in the environment. This study, therefore, wants to verify the effectiveness of a training intervention that is based on education on climate change issues and on the active participation of subjects in the dimension of the small psychological group. At the intervention 309 students took part, equally distributed by gender (52.1% males), 64.4% enrolled in primary school, 35.6% enrolled in lower secondary school. A quantitative protocol was administered to evaluate the effectiveness of the intervention. The study shows an increase in pro-environmental behaviors and their stability even after 15–30 days. The intervention seems to be effective in triggering pro-environmental behaviors and maintaining them in the following weeks. The results of this study highlight the need to develop environmental education pro-grams in schools to increase levels of knowledge and awareness on the issue of climate change.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks’ performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.