A simple method was used to create a graphene oxide/chitosan (GO/CS) nanocomposite, which was then used in batch experiments to remove copper ions from industrial wastewater under various conditions of initial concentration, adsorbent weight, pH, and contact time. Maximum removal percentage equal to 99.4 % for initial copper ion concentration of 5x10^-2 mol/L at pH 6, time 75 min, temperature 25 °C, and adsorbing dose 0.1 g. The pseudo-second order kinetic model and the Freundlich isotherm adequately fit the experimental results. The process was spontaneous and endothermic, according to thermodynamic studies.

     In the present work, the possibility of treating many types of radioactive sources was examined practically. Six types of sealed radioactive sources were selected: ¹³⁷Cs, ¹³³Ba, ⁹⁰Sr, ¹⁵²Eu, ²²⁶Ra, and ²⁴¹Am. The sources were exposed to a neutron flux emitted from ²⁴¹Am/Be source for 33 days. The results showed a measurable reduction of activity for ²²⁶Ra, ²⁴¹Am, and ¹⁵²Eu, while the other radionuclides, ¹³⁷Cs, ¹³³Ba, and ⁹⁰Sr, showed less response to neutron incineration.

This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

In this paper, we have extracted Silica from rice husk ash (RHA) by sodium hydroxide to produce sodium silicate. 3-(chloropropyl)triethoxysilane (CPTES) functionalized with sodium silicate via a sol-gel method in one pot synthesis to prepare RHACCl. Chloro group in compound RHACCl replacement in iodo group to prepere RHACI. The FT-IR clearly showed absorption band of C-I at 580 cm^-1. Functionalized silica RHACI has high surface area (410 m²/g) and average pore diameter (3.8 nm) within mesoporous range. X-ray diffraction pattern showed that functionalized silica RHACI has amorphous phase .Thermogravemitric analysis (TGA) showed two decomposition stages and SEM morphology of RHACI showed that the particles have irregu

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

The preparation of the title compound, C₂₆H₂₅N, was achieved by the condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 molar ratio. There are two crystallographically independent molecules in the asymmetric unit. The two cyclohexyl rings adopt ananti-envelope conformation with the benzyl moiety adopting acisconformation with respect to the nitrogen atom of the phenanthridine segment. In the crystal, molecules are linked through C—H...N interactions into hydrogen-bonded chains that are further arranged into distinct layers by weak offset π–π interactions.

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.