Due to its environmental efficacy and economic effectiveness, a unique approach for extracting functional thermally sensitive bioactive components from food was recently developed. Cloud point extraction is one of the most effective alternative methods for extracting a wide range of organic and inorganic components from green surfactants. The extraction method is cloud point extraction by phase separation, which is a quick and easy approach that requires very little solvent and just a small amount of very non-flammable and non-volatile surfactant that is environmentally benign. The theoretical results of cloud point extraction's application in the food industry are summarized in this article. While presenting a series of introductions on how to extract cloud points, the benefits and applications of cloud points have been studied. The method of using cloud point extraction in food samples has been explained in this article. This method is simple, safe, cost-effective, and widely used to measure a variety of tissue samples, and it can detect analytes down to nanograms per millimeter. Spectrophotometric measurement of low levels of cadmium in some vegetables was also developed in the current study as one of the most important applications of the cloud point extraction method in the food industry.

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Aiming at the problem that it is difficult to achieve rapid and accurate detection of pesticide residues, the artificial neural network method is used to separate the mixed fluorescence spectra in the measurement of acetamiprid pesticide residues, and a fluorescence spectrum that can quickly detect the pesticide residues of acetamiprid on solid surfaces is designed. According to the back-propagation algorithm, the three-layer artificial neural network principle is used to detect the acetamiprid residue in the mixed system of acetamiprid and filter paper with severely overlapping fluorescence spectra. In the range of 340nm~400nm, using the fluorescence intensity values at 20 characteristic wavelengths as the characteristic network parameters, after network training and testing, the recovery rates of acetamiprid concentrations of 40mg/kg and 90mg/kg are 102% and 97%, respectively. The relative standard deviations of the determination results were 1.4% and 1.9%, respectively. The experimental results show that the BP neural network-assisted fluorescence spectroscopy method for the determination of acetamiprid pesticide residues on filter paper has the characteristics of fast network training, short detection period, and high measurement accuracy.

This study intends to conduct a juridical investigation of the regulation of the Professional Competency Test for health workers as regulated in various kinds of legislation today. As a normative study, this research uses a normative juridical method. The data used as a study is secondary data, focusing on various provisions governing Competency Tests, in general, and explicitly regulating the Competency Tests of health workers' professions. Data analysis was carried out qualitatively to assess the meaning of the existing legal rules. This descriptive-analytical research aims to provide an overview of the overall setting of the Competency Test. Furthermore, this study analyzed the purpose of implementing the Competency Test for health professionals. The application of general legal principles is also carried out in order to obtain optimum results. The study results indicate the need for a redefinition of the purpose of the National Competency Test, which can be applied to all health workers.