48 research outputs found

    The Great Vessel Rarely Completes: Translating Corporate Sustainability

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    This thesis contributes to our understanding of Corporate Sustainability (CS) in Multinational Corporations (MNCs) by offering a non-western perspective. A review of the extant literature reveals CS-related studies are mainly based on theories and implications in and for western contexts. It leads us to question the definitions of CS that have been taken for granted in current management and organisation studies. This thesis argues CS should be considered as a non-fixed, contextual and culturally-sensitive notion. When the ideas of CS travel from western scholarship to Chinese organisation practices, the meanings are forever constructed, altered, and mobilised. This is beyond linguistic translation, and functions as a continuous stream of temporary hermeneutic processes of translating. This research explores how CS has been translated in a Japanese MNC in China (the organisation is called ‘OMG’ in the research). The ethnographic enquiry provides a visual and narrative representation of corporate culture as promoted in OMG; ‘Communal Vessel’ evolves as a translational construct symbolising the culturally-derived meanings of CS. The intrinsically oxymoronic meanings of ‘Communal Vessel’ can be drawn from classical Chinese philosophies, which could have implications for understanding contemporary organising practices in China, and globally. In summary, this thesis problematises the construction of CS, and contributes an indigenous, non-western way of understanding CS via an ethnographic representation focusing on processes of translating. The implications are summarised through an analysis of the classical phrase ‘The Great Vessel Rarely Completes’

    Plasma Mutagenesis of Haematococcus lacustris and Optimization of Culture Conditions for High-yield Astaxanthin Algae Strains

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    To further enhance the industrial utilization value of Haematococcus lacustris, the plasma mutagenesis of Haematococcus lacustris was carried out by an atmospheric and room temperature plasma (ARTP) mutagenesis equipment. The optimum input power and mutagenesis time for plasma mutagenesis were determined with lethal rate of algal cells as the index. After mutagenesis, high-yield astaxanthin mutant algae strains were obtained through primary screening of solid plate culture and secondary screening of liquid culture. Then, the culture conditions of high yield algal plants at vegetative growth stage were optimized by single-factor and orthogonal experiment with algae cell density as the index, and the suitable high light conditions for astaxanthin accumulation during astaxanthin induction stage were selected. The genetic stability of the high yielding mutant algae strains was observed after multiple subcultures under the optimized culture conditions. The results showed that the optimum conditions for plasma mutagenesis of Haematococcus lacustris were 240 W for 150 s or 400 W for 120 s. 11 Mutant alga strains with fast growth and high astaxanthin yield were obtained through primary screening and rescreening, wherein the strain HP3 grew fastest and had the highest astaxanthin yield. After culture, its cell density and astaxanthin yield were increased by 25.5% and 61.6% respectively compared with the original strain. After two-stage optimization, the cell density and astaxanthin yield of HP3 increased by 14.3% and 19.3% respectively, reaching 7.2×105 cell/mL and 31.264 mg/L. HP3 showed good growth and stable heredity. Its cell density and astaxanthin yield were similar to those of primary culture. The results have practical significance for the breeding of industrial algal strains producing astaxanthin from Haematococcus lacustris

    A dynamic learning method based on the Gaussian process for tunnel boring machine intelligent driving

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    Introduction: The application of intelligent learning methods to the mining of characteristics and rules of time-series data has gained increasing attention with the rapid development of deep learning. One critical application of such methods is the intelligent assistant driving of tunnel boring machines (TBMs), for which the optimization of driving parameters is essential to improve construction efficiency. However, existing prediction models for TBM parameters are “static” and cannot dynamically capture parameter evolution during real-time driving cycles.Methods: In this study, we propose a novel dynamic learning model for TBM parameters by introducing the Gaussian process to address this problem. The model can learn decision-making experiences from historical driving cycles, dynamically update the model based on small sample data from current driving cycles, and simultaneously achieve driving parameter prediction. We focused on real-time prediction of TBM parameters in a tunnel project in western China.Results: The results show that the average relative errors of predicted total thrust and torque values were 1.9% and 2.7%, respectively, and the prediction accuracy was higher than that of conventional models such as random forest and long short-term memory. The model fully exploited updating of small samples of parameters, reducing the average time cost of the model to 29.7 s, which satisfies the requirements of efficient application.Discussion: The dynamic learning strategy of time-series data adopted in this study provides a reference for other similar engineering applications. The proposed model can improve the prediction accuracy of TBM parameters, thus facilitating the optimization of driving parameters and enhancing the construction efficiency of tunnels.Conclusion: In summary, this study establishes a dynamic learning model of TBM parameters that can dynamically capture parameter evolution and achieve accurate real-time driving parameter prediction. The proposed model can contribute to the development of intelligent assistant driving of TBMs and similar engineering applications

    The Inclusiveness and Emptiness of <i>Gong Qi</i>: A Non-Anglophone Perspective on Ethics from a Sino-Japanese Corporation

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    This article introduces a non-Anglophone concept of gong qi(communal vessel, 慬晹) as a metaphor for ‘corporation’. It contributes an endogenous perspective from a Sino-Japanese organizational context that enriches mainstream business ethics literature, otherwise heavily reliant on Western traditions. We translate the multi-layered meanings of gong qi based on analysis of its ideograms, its references into classical philosophies, and contemporary application in this Japanese multinational corporation in China. Gong qi contributes a perspective that sees a corporation as an inclusive and virtuous social entity, and also addresses the elusive, implicit, and forever evolving nature of organizational life that is rarely noticed. We propose gong qi can be applied in other organizations and wider cultural contexts to show a new way of seeing and understanding business ethics and organization. Rather than considering virtue as a list of definable individual qualities, we suggest that the metaphor of gong qi reveals how virtue can be experienced as indeterminate, yet immanently present, like the substance of emptiness. This, then allows us to see the virtue of immanence, the beauty of implicitness, and hence, the efficacy of gong qi

    Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

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    We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∌50% that achieved nominal significance and ∌75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia
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