Due to the increase in pesticide usage the cost of food production has been drastically reduced worldwide. There are dangers related to the ever-increasing pesticide application especially to the non-target biota and to also to the environment at large. Pesticides bind with the active site of acetylcholinesterase (AChE) and inhibit the breakdown of acetylcholine and causes the blockage of synaptic transmission in cholinergic nerves. When AChE is inhibited, ChE accumulates and the nerve impulse cannot be stopped, leading to muscle contraction, paralysis and sometimes dead may occur. Pesticides and other chemicals that inhibit AChE activity can be able to cause abnormal behavioural patterns of the affected animals. The effects of AChE inhibition in vertebrate include vasodilation of blood vessels, slower heart rate, constriction of bronchioles and reduced secretion of mucus in the respiratory tract, intestinal cramps, secretion of saliva, sweat and tears, and constriction of eye pupil. The inhibition of the AChE activity will also definitely affect the optomotor behaviour of a fish which in turn will affect feeding capability, identification and avoidance of predators, and spatial orientation of the species. Carbamates, organophosphate and eserine are the major pesticides that inhibit the AChE activity of many animals. Cholinesterases including AChE have been considered as interesting biomarkers and biosensor for many years in the monitoring of environmental contamination. This is sensitive to selected organophosphate and carbamate pesticides and may be responding to low levels of contaminants in the environment, putatively by compounds other than or in addition to pesticides. In respect to the above AChE is regarded as a good Biosensor and biomarker in assessing pesticides and other chemical pollutants in the environment.
In the current article, we showcase various growth models like Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in the fitting and analysis of the COVID-19 epidemic trend as of 15 July 2020 in Indonesia in the form of the total number of SARS-CoV-2 infections. The MMF model was proved as the suitable model with the highest adjusted R2 value and lowest RMSE value. The Accuracy and Bias Factors values were near to unity (1.0). The parameters obtained from the MMF model consist of maximum growth rate (µm) (log) of 0.025 (95% CI from 0.020 to 0.028), curve constant (ï¤) that affects the inflection point of 0.770 (95% CI from 0.691 to 0.849), lower asymptote value (ï¢) of 0.297 (95% CI from 0.229 to 0.365) and maximal total number of cases (ymax) of 4,634,469 (95% CI from 1,967,886 to 15,417,005). The MMF forecast that the total number of cases in Indonesia on the coming 15th of August and 15th of September 2020 will be 113,179 (95% CI of 103,477 to 123,790) and 154,235 (95% CI of 136,542 to 174,220), respectively. The predictive capability of the model applied in this paper is likely a reliable tool for epidemiologist to monitor and evaluate the severity of COVID-19 death cases in Indonesia in few months to come. Undoubtedly, the models will be reexamined after every few months in the event unwarranted phenomena lead to an exponential increase or wave of new infection.
Atrazine is the second most widely used herbicide in Nigeria, an excellent polluter of surface and ground sources of water; it finds its way into the water bodies through percolation and surface run-off during rainy and dry season farming. The chemical has some effects on the ecosystem especially in aquatic habitats. different concentrations of atrazine have been prepared (0, 1, 2, 3, and 4 mg/l) and each treatment was replicated four times. a total number of twenty-five basins were used. Five test organisms (Clarias garipienus) were used in each basin. During 96-hour exposure, physicochemical parameters, morphological changes and abnormal behavior in the fish were observed. The research also considers biochemical changes in the kidney, liver and gills where the activities of cretinine, Urea, AST, ALT and Total bilirubin was assayed using colorimetric method. Based on the results obtained in this study, atrazine is found to be toxic to Clarias gariepinus. The result of the biochemical parameters and histological assay showed that Clarias gariepinus was seriously affected by atrazine. KEYWORDS
The use of agricultural by-products as a fish meal is an attempt to minimize the cost of fish production to aquaculturist and to also create a more environmentally friendly practice. Due to high demand of Tilapia fish, efforts to improve its growth performance is highly needed. The application of linearization technique by natural logarithm transformation, even though standard, is inaccurate and can just provide an estimated value for the single parameter measured; the specific growth rate. In this paper, for the first time we used various kinetics models such as Von Bertalanffy, Baranyi-Roberts, modified Schnute, modified Richards, modified Gompertz, modified Logistics and most recent Huang were used to get values for the above constants or parameters from Nile Tilapia Oreochromis niloticus growth on fed diets formulated from local ingredients in cages. At the end of the modelling exercise, Baranyi-Roberts model proved to be the finest model with the highest adjusted R2 value and lowest RMSE value. The Accuracy and Bias Factors values were close to unity (1.0). The kinetics modelling shows that the most satisfactory fitting is with the Baranyi-Roberts model. The use of Nile Tilapia growth models to obtained exact growth rate is advantageous for further development of secondary model and this work has revealed the capability of such models.
Different growth models such as Baranyi-Roberts, Von Bertalanffy, modified Gompertz, Morgan-Mercer-Flodin (MMF), modified Richards, modified Logistics and Huang utilized in fitting and analyzing the COVID-19 outbreak pattern showing the cumulative number of SARS-CoV-2 deaths in Indonesia as of 15 July 2020. Out of all the models tested MMF was found to be the best one considering its highest adjusted R2 and the lowest RMSE values. Parameter such Accuracy and Bias Factors were found to have values close to unity (1.0). Values generated from the MMF model includes the maximum growth of death rate (log) of 0.051 (95% CI from 0.34 to 0.49), the curve constant (d) that affects the inflexion point of 0.4212 (95% CI from 1.029 to 1.171), lower asymptote value ( b ) of -1.72 (95% CI from -2.53 to -1.22) and the maximal total number of death (ymax) of 889,201 (95% CI from 260,016 to 7,464,488). The MMF forecasted that the total death toll in Indonesia would be 5.315 (95 per cent CI from 5.079 to 5.562) and 6.857 (95 per cent CI from 6.450 to 7.289) on the 15th August and 15th September 2020 respectively. The prediction accuracy of the model used in this research article is a powerful tool for epidemiologists to monitor and evaluate the level the severity of COVID-19 in Indonesia in the coming months. Besides that, just like any other model, due to the intermittent nature of the COVID-19 dilemma both in the local and global context, these values must be considered with caution.
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