The model updating based on near infrared spectroscopy for the sex identification of silkworm pupae from different varieties by a semi-supervised learning with pre-labeling method

Abstract

It is effective to accurately discriminate the sex of silkworm pupae with the same varieties based on near infrared spectroscopy. However, when the model is promoted to classify new varieties of silkworm pupae, the model’s performance becomes worse, due to the cultivation environment and varieties changing. In the aims of improving the generalization ability and accuracy of the model, this paper proposed a model updating strategy based on semi-supervised learning. First, support vector machine identification model was built after the original spectra was pretreated by Savitzky-Golay convolution smoothing operation, which could effectively reduce spectra noise. Then, the support vector machine model gave the pre-labelings of unlabeled silkworm pupae in the updated set, which were divided into male samples and female samples. According to the correlation coefficients that calculated by Pearson correlation coefficient and Euclidean distance, a total of 8 reliable samples were selected from the male and female samples, respectively. The reliable samples were added to the original training set to update the original model. Finally, the updated model was used to test the test sets from the varieties of silkworm pupae that were the same with updated sets.The results showed the performance of the non-updated model for silkworm pupae from the three new varieties just reached 54.55%, 68.52%, 86.84%, respectively. The support vector machine model updated by using Pearson correlation coefficient improved the accuracy to 100%, 96.30%, 97.37%, and the model updated by Euclidean distance increased the identification accuracy of the three varieties that were not involved in the modeling to 100%, 75.93%, 92.10% respectively. The results showed that the performance of the model updated by Pearson correlation coefficient was better than Euclidean distance. The results revealed that the method based on semi-supervised learning could effectively solve the problem of poor universality for sex identification model.     

A Side-by-Side Single Sex Age-Structured Human Population Dynamic Model: Exact Solution and Model Validation

A side-by-side single sex age-structured population dynamic model is presented in this paper. The model consists of two coupled von Foerster-McKendrick-type quasi-linear partial differential equations, two initial conditions, and two boundary conditions. The state variables of the model are male and female population densities. The solutions of these partial differential equations provide explicit time and age dependence of the variables. The initial conditions define the male and female population densities at the initial time, while the boundary conditions compute the male and female births at zero-age by using fertility rates. The assumptions of the nontime-dependence of the death and fertility rates and a specific factorization of the migratory balances allow us to obtain exact solutions for male and female population densities. In addition, the hypotheses about the mathematical structure of the input variables are formulated, and the exact solution of the model is obtained. Next, the model is applied to the case study of Spain for the time period 1996–2004. Model validation demonstrates that this approach is a powerful prediction tool. Code and data are available upon request.     

Preparation of a strong-cation exchange monolith by a novel method and its application in the separation of IgG on high performance liquid chromatography

A strong cation-exchange poly(vinyl carboxylate-co-ethyleneglycol dimethacrylate) (poly(VC-co-EDMA)) monolithic column for high performance liquid chromatography (HPLC) has been prepared firstly by atom transfer radical polymerization (ATRP) without the expensive complexing ligand, in which vinyl carboxylate was used as the monomer, ethyleneglycol dimethacrylate as the cross linking agent, carbon tetrachloride as the initiator and ferrous chloride as the catalyst. Conditions of the polymerization have been studied and optimized. Morphology of monolithic materials was studied by scanning electronic microscopy. Chemical groups of the monolith were assayed by infrared spectra method and the pore size distribution was determined by a mercury porosimeter. Moreover, the monolith was modified to bear strong-cation exchange groups and tested on the separation of human immune globulin G (IgG) from human plasma in conjunction with HPLC. Good resolution was obtained in a short time (10 min) in the separation. The effects of pH and buffer concentration on the elution of IgG have been investigated. Moreover, frontal analytical method was used to get the IgG dynamic banding capacity of the monolith that was 3.0 mg g⁻¹. Besides, the monolith was also used to separate lysozyme from egg white and separate the mixture of papain, snailase and IgG.     

TSD based framework for mining the induction rules

Sex determination mainly encompasses two aspects: genotypic sex determination (GSD) and temperature-dependent sex determination (TSD). Genotypic sex determination performs its task by observing the presence of sex chromosomes. In many reptiles sex determination is greatly influenced by the environmental conditions such as temperature of the nest, weight and size of eggs. A nature inspired algorithm which mimics the mechanism of temperature dependent sex determination (TSD) has been introduced for mining the classification rules from datasets. A comparison of proposed TSD algorithm with other well known rule induction algorithms like PRISM, C4.5, 1-R, CN2, and NN has been evaluated on some bench mark datasets.     

Determination of steroid sex hormones in wastewater by stir bar sorptive extraction based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material and liquid chromatographic analysis

In this study, a simple and rapid method was developed for the determination of seven steroid hormones in wastewater. Sample preparation and analysis were performed by stir bar sorptive extraction (SBSE) based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material (SBSEM) combined with high-performance liquid chromatography with diode array detection. To achieve the optimum extraction performance, several main parameters, including extraction and desorption time, pH value and contents of inorganic salt in the sample matrix, were investigated. Under the optimized experimental conditions, the method showed good linearity and repeatability, as well as advantages such as sensitivity, simplicity, low cost and high feasibility. The extraction performance of SBSEM to the target compounds also compared with commercial SBSE which used polydimethylsiloxane as coating. Finally, the proposed method was successfully applied to the determination of the target compounds in wastewater samples. The recoveries of spiked target compounds in real samples ranged from 48.2% to 110%.     

(6Z,9Z,12Z)-6,9,12-Octadecatriene and (3Z,6Z,9Z,12Z)-3,6,9,12-icosatetraene, the novel sex pheromones produced by emerald moths

(6Z,9Z,12Z)-6,9,12-Octadecatriene and (3Z,6Z,9Z,12Z)-3,6,9,12-icosatetraene, hydrocarbons unsaturated more highly than usual lepidopteran Type II pheromones, were identified from geometrid females of Hemithea tritonaria and Thalassodes immissaria intaminata, respectively. The triene was synthesized by a double Wittig reaction between hexanal and an ylide derived from (Z)-1,6-diiodo-3-hexene, and the tetraene was synthesized by a coupling between (Z)-3-undecenal and an ylide derived from (3Z,6Z)-1-iodo-3,6-nonadiene. Each synthetic compound attracted males of the corresponding emerald moths in a field.     

Fractional and Amino-Acid Composition of Wheat Grain Cultivated in Uzbekistan

Wheat grain cultivated in Uzbekistan had an increased content of water-soluble proteinaceous and relatively low gliadin and glutelin fractions. The amino-acid content in the studied varieties depended on the amount of protein in the grain.     

亚洲玉米螟性信息素的简便合成

从Z-15-二十四碳烯酸(1)出发, 经关键中间体13-十四碳烯-1-醇醋酸酯(4)。以CoCl2-Ph3P-NaBH4为催化体系异构化合成亚洲玉米螟性信息素Z/E-12-十四碳烯-1-醇醋酸酯(5)。经GC测定, 其Z、E比例接近1:1。     

Multiple monolithic fiber solid‐phase microextraction based on a polymeric ionic liquid with high‐performance liquid chromatography for the determination of steroid sex hormones in water and urine

The development of a simple and sensitive analytical approach that combines multiple monolithic fiber solid‐phase microextraction with liquid desorption followed by high‐performance liquid chromatography with diode array detection is proposed for the determination of trace levels of seven steroid sex hormones (estriol, 17β‐estradiol, testosterone, ethinylestradiol, estrone, progesterone and mestranol) in water and urine matrices. To extract the target analytes effectively, multiple monolithic fiber solid‐phase microextraction based on a polymeric ionic liquid was used to concentrate hormones. Several key extraction parameters including desorption solvent, extraction and desorption time, pH value and ionic strength in sample matrix were investigated in detail. Under the optimal experimental conditions, the limits of detection were found to be in the range of 0.027–0.12 μg/L. The linear range was 0.10–200 μg/L for 17β‐estradiol, 0.25–200 μg/L estriol, ethinylestradiol and estrone, and 0.50–200 μg/L for the other hormones. Satisfactory linearities were achieved for analytes with the correlation coefficients above 0.99. Acceptable method reproducibility was achieved by evaluating the repeatability and intermediate precision with relative standard deviations of both less than 8%. The enrichment factors ranged from 54‐ to 74‐fold. Finally, the proposed method was successfully applied to the analysis of steroid sex hormones in environmental water samples and human urines with spiking recoveries ranged from 75.6 to 116%.     

茄黄斑螟性信息素化学结构的毛细管色谱/质谱测定

本文介绍用毛细管色谱/质谱联用技术,测定出茄黄斑螟性信息素化学结构为E_n—16:Ac。