Quality Assessment of Different Industrial Effluents for Irrigation in Agriculture

Islam, Mazharul; Rahman, G. K. M. Mustafizur; Karim, A. J. M. S.; Miah, Mahin; Saleque, M Abu

doi:10.17265/2159-581x/2015.02.006

Cited by 6 publications

(7 citation statements)

References 13 publications

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“…Neural network models have been used in recent studies to detect water quality (Sarkar and Pandey, 2015), assessment of watersheds (Ahmed et al, 2019;Samantaray et al, 2019), biodiversity (Gagne et al, 2020;Jahani and Saffariha, 2020;Morshed et al, 2022), land-use changes (Islam et al, 2018;Saputra and Lee, 2019;Yatoo et al, 2020), and forecasting droughts (Ali et al, 2017;Dehghani et al, 2017;Dikshit et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Forecasting Volume of Corn Production through Neural Network Model: A Post-harvest Monitoring Tool

2023

Int. J. Biosci.

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The paper deals with the forecasting of volume (in tonnes) of corn production relative to the harvested farmed area during the second semester of agricultural cropping. Time series data used were obtained from the open stat database published by the Philippine Statistics Authority from the second semester of 1987 to second semester of 2022. Artificial Neural Network (ANN) models were developed, trained and validated to forecast the volume of corn production. Statistical errors such as Root Mean Square Error (RMSE) were computed and compared to identify the most suitable model to forecast the corresponding volume. ANN ( ) model was identified and used to forecast the volume of corn production. The two sets of data, namely actual and forecast volumes of production, were found to have statistically no significant difference, which implies that the model gives forecast values that are relatively close to the actual ones.

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Section: Methodsmentioning

confidence: 99%

Forecasting Volume of Corn Production through Neural Network Model: A Post-harvest Monitoring Tool

2023

Int. J. Biosci.

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“…The separation of spin energy is 23.0 eV, which is the characteristic value for the Zn 2 + oxidation state. [40] The peak was located 528.92 eV is related to lattice oxygen and the peak centered at 530.61 eV correspond to oxygen defect or vacancies. [41] These vacancies have the ability to attract extra dissolved oxygen to the ZnO surface, increasing the amount of superoxide anion active species enhance the photocatalytic dye degradation.…”

Section: Characterization Of Zno Nanostructuresmentioning

confidence: 99%

Facile Fabrication of ZnO Nanoparticles for efficient dye degradation: Effect of Adipic Acid in photocatalytic activity

Demir¹,

Özbay²,

Kamış³

et al. 2023

ChemistrySelect

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Photocatalysis is the most environmentally benign and efficient method for degrading organic dyes in water purification. Herein, the synthesis of ZnO nanoparticles was achieved by simple homogeneous chemical precipitation via the support of adipic acid and followed the calcination process at elevated temperatures. Based on the physical and morphological characterization analysis, the high crystallinity hexagonal structure with uniform granular shape morphology of the ZnO nanoparticles was formed with a band gap of 3.2 eV. The photocatalytic performance of the ZnO nanoparticles was investigated with the degradation of methylene blue (M.B.) dye as a model compound in an aqueous medium under UV light irradiation. The optimal ZnO‐700 nanoparticles demonstrated the highest photocatalytic activity thanks to their large surface area and numerous oxygen vacancies. More importantly, a small amount of photocatalyst (0.4 g/L) successfully degraded M.B. dye from an aqueous solution with 100 % efficiency within just 11 minutes of irradiation time under UV light with protective photocatalytic activity 4 sequential cycles. Besides, in‐depth photocatalysis experiments present that via a facile two‐step synthesis method, the as‐prepared ZnO photocatalysts depict enhanced chemical stability in a harsh environment and efficient photodegradation.

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“…28−33 In the biomedical field, rotating electric fields can be used to rotate cells, capsules, and micro-and nanobiological machines. 34−39 In other aspects, the rotating electric fields can also be used for electropumping of water in nanochannels, 40−43 curling of graphene nanoribbons, 44 and colloidal particle self-assembly, 45−49 etc.…”

Section: ■ Introductionmentioning

confidence: 99%

Droplet Rolling Transport on Hydrophobic Surfaces Under Rotating Electric Fields: A Molecular Dynamics Study

Liu,

Jing

2023

Langmuir

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Driving droplets by electric fields is usually achieved by controlling their wettability, and realizing a flexible operation requires complex electrode designs. Here, we show by molecular dynamics methods the droplet transport on hydrophobic surfaces in a rolling manner under a rotating electric field, which provides a simpler and promising way to manipulate droplets. The droplet internal velocity field shows the rolling mode. When the contact angle on the solid surface is 144.4°, the droplet can be transported steadily at a high velocity under the rotating electric field (E = 0.5 V nm −1 , ω = π/20 ps −1 ). The droplet center-of-mass velocities and trajectories, deformation degrees, dynamic contact angles, and surface energies were analyzed regarding the electric field strength and rotational angular frequency. Droplet transport with a complex trajectory on a two-dimensional surface is achieved by setting the electric field, which reflects the programmability of the driving method. Nonuniform wettability stripes can assist in controlling droplet trajectories. The droplet transport on the three-dimensional surface is studied, and the critical conditions for the droplet passing through the surface corners and the motion law on the curved surface are obtained. Droplet coalescence has been achieved by surface designs.

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Quality Assessment of Different Industrial Effluents for Irrigation in Agriculture

Cited by 6 publications

References 13 publications

Forecasting Volume of Corn Production through Neural Network Model: A Post-harvest Monitoring Tool

Forecasting Volume of Corn Production through Neural Network Model: A Post-harvest Monitoring Tool

Facile Fabrication of ZnO Nanoparticles for efficient dye degradation: Effect of Adipic Acid in photocatalytic activity

Droplet Rolling Transport on Hydrophobic Surfaces Under Rotating Electric Fields: A Molecular Dynamics Study

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