Experimental Evaluation of Solar-Powered Desalination Ponds in Waste Water Treatment

The purpose of this research is to examine a desalination pond that is experimental in size and uses solar energy for its heating. The solar pond is the major components of a zero discharge desalinate progression (ZDDP), as shown below. The projected ZDDP may treat the sewage waste water produced by the petrochemical complex's purification unit, resulting in the productivity of both fresh water and salt. The solar desalination pond that was researched and utilized the evaporation distillation process. A solar desalination pond's primary function is that of a batch stage. The experiment results are presented after an introduction of the solar powered desalinate pond and the distillation procedure. The results prove that the proposed solar-powered pond can be realistically executed. The proposed solar-powered pond to a standard solar-powered pond in terms of the rate at which it gains distilled water were compared

Artificial Intelligence for Forecasting the Prevalence of COVID-19 Pandemic: An Overview

Since the discovery of COVID-19 at the end of 2019, a significant surge in forecasting publications has been recorded. Both statistical and artificial intelligence (AI) approaches have been reported; however, the AI approaches showed a better accuracy compared with the statistical approaches. This study presents a review on the applications of different AI approaches used in forecasting the spread of this pandemic. The fundamentals of the commonly used AI approaches in this context are briefly explained. Evaluation of the forecasting accuracy using different statistical measures is introduced. This review may assist researchers, experts and policy makers involved in managing the COVID-19 pandemic to develop more accurate forecasting models and enhanced strategies to control the spread of this pandemic. Additionally, this review study is highly significant as it provides more important information of AI applications in forecasting the prevalence of this pandemic

DNA and protein targeting 1,2,4-triazole based water soluble dinickel(II) complexes enhances antiproliferation and lactate dehydrogenase inhibition

Water soluble dinickel(II) complexes Ni-2(L)(2)(1-2)](NO3)(4) (1-2), where L1-2 are triazole based dinucleating ligands, were synthesized and characterized. The DNA binding, protein binding, DNA hydrolysis and anticancer properties were investigated. The interactions of complexes 1 and 2 with calf thymus DNA were studied by spectroscopic techniques, including absorption and fluorescence spectroscopy. The DNA binding constant values of the complexes 1 and 2 were found to be 2.36 x 10(5) and 4.87 x 10(5) M-1 and the binding affinities are in the following order: 2 > 1. Both the dinickel(II) complexes 1 and 2, promoted the hydrolytic cleavage of plasmid pBR322 DNA under both anaerobic and aerobic conditions. Kinetic data for DNA hydrolysis promoted by 1 and 2 under physiological conditions give the observed rate constants (k(obs)) of 5.05 +/- 0.2 and 5.65 +/- 0.1 h(-1), respectively, which shows 10(8)-fold rate acceleration over the uncatalyzed reaction of ds-DNA. Meanwhile, the interactions of the complex with BSA have also been studied by spectroscopy. Both the complexes 1 and 2 display strong binding propensity and the binding constant (K-b), number of binding sites (n) were obtained are 0.71 x 10(6) 1.47] and 5.62 x 10(6) 1.98] M-1, respectively. The complexes 1 and 2 also promoted the apoptosis against human carcinoma (HeLa, and BeWo) cancer cells. Cytotoxicity of the complexes was further confirmed by lactate dehydrogenase enzyme level in cancer cell lysate and content media. (c) 2013 Elsevier Ltd. All rights reserved

DNA and protein targeting 1,2,4-triazole based water soluble dinickel(II) complexes enhances antiproliferation and lactate dehydrogenase inhibition

Water soluble dinickel(II) complexes [Ni2(L)21–2](NO3)4 (1–2), where L1–2 are triazole based dinucleating ligands, were synthesized and characterized. The DNA binding, protein binding, DNA hydrolysis and anticancer properties were investigated. The interactions of complexes 1 and 2 with calf thymus DNA were studied by spectroscopic techniques, including absorption and fluorescence spectroscopy. The DNA binding constant values of the complexes 1 and 2 were found to be 2.36 × 105 and 4.87 × 105 M−1 and the binding affinities are in the following order: 2 > 1. Both the dinickel(II) complexes 1 and 2, promoted the hydrolytic cleavage of plasmid pBR322 DNA under both anaerobic and aerobic conditions. Kinetic data for DNA hydrolysis promoted by 1 and 2 under physiological conditions give the observed rate constants (kobs) of 5.05 ± 0.2 and 5.65 ± 0.1 h−1, respectively, which shows 108-fold rate acceleration over the uncatalyzed reaction of ds-DNA. Meanwhile, the interactions of the complex with BSA have also been studied by spectroscopy. Both the complexes 1 and 2 display strong binding propensity and the binding constant (Kb), number of binding sites (n) were obtained are 0.71 × 106 [1.47] and 5.62 × 106 [1.98] M−1, respectively. The complexes 1 and 2 also promoted the apoptosis against human carcinoma (HeLa, and BeWo) cancer cells. Cytotoxicity of the complexes was further confirmed by lactate dehydrogenase enzyme level in cancer cell lysate and content media

Detecting the invasive fall armyworm pest incidence in farm fields of southern India using Sentinel-2A satellite data

Damage of fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) on sorghum from the farmers’ fields of southern India was assessed using space-borne data. Comparison of the Sentinel-2A satellite data of pre and post infestation periods revealed reduction in Leaf Area Index (LAI) in the infested fields. Groundtruth data confirmed that FAW infestation reduced LAI by 49.7%, biomass by 32.5% and grain yield by 51.8%. Infestation at Panicle Initiation (PI) stage caused maximum yield loss compared to flag leaf visible and boot stages. The interaction results showed FAW infestation at different crop stages had significant effect on biomass and yield, but not on LAI. Regression analysis with spectral vegetation indices revealed LAI (R2: 0.82) and NDVI (R2: 0.80) were significantly superior in identifying FAW infestation from the satellite data. This study demonstrates feasibility of site specific pest management and prevents further spread of the invasive FAW