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The paper seeks to attempt to solve a decision‐making problem for breeding target character shown as an interval number.

A new comprehensive evaluation method is proposed based on similarity‐difference theory and interval number theory. Data from Winter Wheat Group I Variety Regional Test in Henan Province in 2009‐2010 were analysed using the proposed method.

The results showed that Zhou 99233 was a good variety; Yuxhan No. 7, An 05‐28, Xun K8, Jinyumai 378 and Zhoumai 18 were better ones; 08 luo 36,and Xuke 718 ordinary ones, and others worse ones. Based on this, the feasibility of the method was discussed. It showed that the proposed method had some obvious merits, such as simple arithmetic, convenient operation, flexible and practical, fast and effective.

The application of a live example indicated that its evaluation effect was satisfactory.

The paper succeeds in solving a decision‐making problem for breeding target character shown as an interval number.

The purpose of this paper is to attempt to solve a decision‐making problem for breeding target character showed as an interval number.

A new comprehensive evaluation method was proposed based on similarity‐difference theory and interval number theory. The data from Winter Wheat Group I Variety Regional Test in Henan Province in 2009‐2010 were analysed using the proposed method.

The results showed that Zhou 99233 was a good variety, Yuxhan No.7, An 05‐28, Xun K8, Jinyumai 378 and Zhoumai 18 were better ones, 08 luo 36, and Xuke 718 ordinary ones, and others worse ones. Based on this, the feasibility of the method was discussed. It showed that the proposed method had some obvious merits, such as arithmetic was simple, operation convenient, flexible and practical, fast and effective, etc.

Application to a living example indicated that its evaluation effect was satisfactory. Consequently, the application prospect of the method will be very vast.

The paper succeeds in solving a decision‐making problem for breeding target character shown as an interval number.

The Jurassic Park film franchise offers a complex portrayal of gender issues within a long-running science fiction action series, although not one without problematic moments. This chapter examines selected examples from the series to explore this complex picture. These include moments in the series that display female characters such as Ellie Sattler, Sarah Harding and Claire Dearing with power and agency and the top of their respective professions, noting that Jurassic Park is unusual among science fiction films for its presentation of such accomplished female characters. The chapter also addresses the sexualisation of the character Ian Malcolm and the role of the more typical ‘action star’ from later films, Owen Grady. Finally, it considers the question of sex-selection for the non-human characters, namely the dinosaurs, as significant plot points advance upon the premise that the entire dinosaur population in the series consists of non-breeding females, a fact that is later shown to be untrue. The chapter addresses each of these examples through key issues relating to the production, presentation, and violation of the human and non-human living body across the full Jurassic Park series.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose of this paper is to identify the risk factors that affect aquatic product quality in the “farming-supermarket docking” condition. This paper investigates how the investment scale can affect earnings and aquatic product quality assurance level. Also, it aims to determine an effective method for increasing aquatic product assurance level, coordinate the supply chain and improve management of the entire supply chain.

The authors construct a coordination model for quality risk control of the aquatic supply chain by simulating the model in a tilapia supply chain using the case study method. They applied Karush–Kuhn–Tucker conditions to analyze upstream enterprises (breeding base) and downstream enterprises (corresponding supermarket) under the conditions of sufficient or insufficient funds, Further, they consider the relationships among revenue, optimum quality assurance and investment scale at different capital positions; discuss the best cooperation conditions in four cases; and draw conclusions on ways to control quality risk.

The proposed coordination model is found to be effective in controlling aquatic product quality risk. The simulation results show that when the enterprise funds are sufficient, the sales prices, product freshness, quality assurance ability, collaboration and quality test ability have a positive influence on quality assurance level, whereas coefficient and price sensitivity have a negative influence on it. Additionally, it can obtain high-quality assurance levels and earnings in both breeding bases and supermarkets under the condition of adequate investment.

The study built a coordination model combined with the characteristics of the aquatic supply chain by adding the quality penalty mechanism, product freshness parameters and cost function in the “farming-supermarket docking” mode into the traditional principal–agent model. Research results are beneficial to enhancing the quality assurance level of the aquatic supply chain and improving the coordination level of the supply chain.

A striking feature of Jaques' work is his “no nonsense” attitude to the “manager‐subordinate” relationship. His blunt account of the origins of this relationship seems at first sight to place him in the legalistic “principles of management” camp rather than in the ranks of the subtler “people centred” schools. We shall see before long how misleading such first impressions can be, for Jaques is not making simplistic assumptions about the human psyche. But he certainly sees no point in agonising over the mechanism of association which brings organisations and work‐groups into being when the facts of life are perfectly straightforward and there is no need to be squeamish about them.

The paper starts from an observation of a discrepancy between the ambitions for sustainable change in the agro-industry and the actual changes being implemented. We offer one possible explanation by investigating the organizational structures conditioning change in this industry.

We apply a case study methodology, focusing on the Danish pig industry and its organizational conditions for change. Based on interviews and document analysis, and building on systems theory, we develop the concept of change structures, understood as decision premises that guide the change of further decision premises.

The analysis suggests that the pig industry’s change structures predominantly enable changes that cut costs and optimize the production, which may conflict with and possibly foreclose the changes needed to realize the industry’s sustainable ambitions. This conflict and its implications are not acknowledged by the industry.

The analysis indicates that the industry may be locked in its current form of organizational change. We suggest a way to overcome the lock-in by fostering organizational mechanisms that enable alternative interpretations to emerge internally. Without this, achieving the required sustainable change in the industry may hinge on stronger external regulation and support.

Conceptually, the notion of change structures supplements actor-oriented analytical approaches that focus on change agents and sense-making. Empirically, we contribute with an analysis of the conditions of possibility for sustainable change in an important yet understudied industry in organization studies; namely, the conventional agro-industry.

The chapter analyses the re-emergence of gene editing as an object of policy attention at the European Union (EU) level. Editing the genome of plants and/or animals has been a rather controversial component of all EU policies on agricultural biotechnology since the late 1980s. The chapter examines in detail the various initiatives that have been assumed for the regulation of gene editing at the EU level. Since the first political and legislative attempts, the field has been revolutionized with the development of the CRISPR-Cas9 system, which is comparatively much easier to design, produce, and use. Beyond the pure, safety-driven scientific questions, gene editing, in its contemporary form, raises a series of ethical and regulatory questions that are discussed in the context of the legal options and competences of the EU legislators. Special attention is paid to questions about the legal status of gene editing in Europe and the adequacy of the current GMO framework to deal with all the challenges associated with the latest scientific developments in the field of gene editing with a special focus on gene drive. Given the ongoing discussions regarding the ethical tenets of gene editing, the chapter investigates the question on whether there is a need to shape an EU-wide “intervention” that will address the complex and dynamic socio-ethical challenges of gene editing and puts forward a series of proposals for the framing of an inclusive framework that will be based on the need to re-enforce public trust in the EU governance of emerging technologies.

Hate speech is an expression of intense hatred. Twitter has become a popular analytical tool for the prediction and monitoring of abusive behaviors. Hate speech detection with social media data has witnessed special research attention in recent studies, hence, the need to design a generic metadata architecture and efficient feature extraction technique to enhance hate speech detection.

This study proposes a hybrid embeddings enhanced with a topic inference method and an improved cuckoo search neural network for hate speech detection in Twitter data. The proposed method uses a hybrid embeddings technique that includes Term Frequency-Inverse Document Frequency (TF-IDF) for word-level feature extraction and Long Short Term Memory (LSTM) which is a variant of recurrent neural networks architecture for sentence-level feature extraction. The extracted features from the hybrid embeddings then serve as input into the improved cuckoo search neural network for the prediction of a tweet as hate speech, offensive language or neither.

The proposed method showed better results when tested on the collected Twitter datasets compared to other related methods. In order to validate the performances of the proposed method, t-test and post hoc multiple comparisons were used to compare the significance and means of the proposed method with other related methods for hate speech detection. Furthermore, Paired Sample t-Test was also conducted to validate the performances of the proposed method with other related methods.

Finally, the evaluation results showed that the proposed method outperforms other related methods with mean F1-score of 91.3.

The main novelty of this study is the use of an automatic topic spotting measure based on naïve Bayes model to improve features representation.