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Agricultural models, agricultural artificial intelligent, and data analysis technology, etc., exist in whole processes of information perceiving, transmission, processing and control for smart agriculture， thus they are the core technology of smart agriculture. To furtherly make the substances and functions of agricultural models clear, facilitate its further research and application, drive smart agriculture development with healthy, steady, and sustainable, methods of systematic analysis, comparison, and chart for relationship, etc. were used in this research. The definition, classification, functions of the agricultural models were theoretically analyzed. The relationships between the agricultural models and the elements and processes of the smart agriculture were expounded, which made the functions of agricultural models clear, provided some agricultural models examples applied in the smart agriculture. The important studies and application progresses of agricultural models were reviewed. The comparison results of agricultural models showed that the 4 levels of agricultural biological elements, 6 scales of agricultural environmental elements, 6 administrative levels of agricultural technological and economic elements, and the relevant approaches for modeling agricultural system need to be considered. The research and application of multi-space scales on environment elements in the agricultural models would have the larger potential. The combination of agricultural models with molecular genetics, perceiving, and artificial intelligence, the collaboration among public and private researchers, and food security challenges have been an important power for further development of agricultural models, linking agricultural models with various agricultural system modeling, databases, harmonious and open data, and decision-making support systems (DSS) would be focus on. The research and application of the agricultural models in China have formed crop model series with Chinese characteristics, joined in the world trends of the Agricultural Model Intercomparison and Improvement Project (AgMIP), the smart agriculture, and so on. They should be speedy graspe chances and accelerate development. The agricultural models is a quantitative express of relationships within or among the agricultural system elements. An important method with epistemological values of quantifying and synthesizing agricultural sciences, and will play an indispensible role in data achieving and processing for the smart agriculture combining perceiving techniques, and become a significant bridge and bond.

The copolymer P(AM-DMC), one kind of cationic polyacrylamide, was synthesized by using acrylamide (AM) and methacryloxyethyltrimethyl ammonium chloride (DMC) as monomers with ultraviolet initiation. The copolymer was characterized by Fourier transform infrared spectroscopy. The composition of the copolymer was determined from the chlorine content by silver nitrate titration. The effects of monomer feed ratio and conversion on the composition of copolymer were discussed. Reactivity ratios were determined by the Fineman-Ross, Kelen-Tudos and Yezrielev-Brokhina-Roskin methods, indicating that their positive order calculation results were very different with those of reverse order, when the reactivity ratios were determined by Fineman-Ross. However, their positive order and reverse order calculation results were similar when the reactivity ratios were determined by the Kelen-Tudos and Yezrielev-Brokhina-Roskin methods. Therefore, the reactivity ratios were determined using the average results of the Kelen-Tudos and Yezrielev-Brokhina-Roskin methods. The reactivity ratios of AM and DMC were 2.3398 and 0.2285, respectively. This result showed that the copolymerization of AM and DMC was a non-ideal random copolymerization. Furthermore, the content of AM segments decreased with the increase of AM feed content, but the content of DMC segments increased. Moreover, the sequence length distribution was irregular and narrow, because AM was prone to homopolymerization. [ABSTRACT FROM AUTHOR]

Neurofibrillary tangles are the main pathological feature of Alzheimer's disease. Insoluble tau protein is the major component of neurofibrillary tangles. Defects in the tau protein degradation pathway in neurons can lead to the accumulation of tau and its subsequent aggregation. Currently, contradictory results on the tau degradation pathway have been reported by different groups. This discrepancy is most likely due to different cell lines and methods used in those studies. In this study, we found that cycloheximide treatment induced mild activation of a ZVAD-sensitive protease in Drosophila Kc cells, resulting in cleavage of tau at its C-terminus; this cleavage could generate misleading tau protein degradation pattern results depending on the antibodies used in the assay. Because cycloheximide is a broadly used chemical reagent for the study of protein degradation, the unexpected artificial effect we observed here indicates that cycloheximide is not suitable for the study of tau degradation. Other methods, such as inducible expression systems and pulse-chase assays, may be more appropriate for studying tau degradation under physiological conditions. [ABSTRACT FROM AUTHOR]

In recent years, traceability systems have been developed as effective tools for improving the transparency of supply chains, thereby guaranteeing the quality and safety of food products. In this study, we proposed a cattle/beef supply chain traceability model and a traceability system based on radio frequency identification (RFID) technology and the EPCglobal network. First of all, the transformations of traceability units were defined and analyzed throughout the cattle/beef chain. Secondly, we described the internal and external traceability information acquisition, transformation, and transmission processes throughout the beef supply chain in detail, and explained a methodology for modeling traceability information using the electronic product code information service (EPCIS) framework. Then, the traceability system was implemented based on Fosstrak and FreePastry software packages, and animal ear tag code and electronic product code (EPC) were employed to identify traceability units. Finally, a cattle/beef supply chain included breeding business, slaughter and processing business, distribution business and sales outlet was used as a case study to evaluate the beef supply chain traceability system. The results demonstrated that the major advantages of the traceability system are the effective sharing of information among business and the gapless traceability of the cattle/beef supply chain.