Author Correction: The flying spider-monkey tree fern genome provides insights into fern evolution and arborescence (Nature Plants, (2022), 8, 5, (500-512), 10.1038/s41477-022-01146-6)

Correction to: Nature Plantshttps://doi.org/10.1038/s41477-022-01146-6, published online 9 May 2022. In the version of the article initially published, Dipak Khadka, who collected the samples in Nepal, was thanked in the Acknowledgements instead of being listed as an author. His name and affiliation (GoldenGate International College, Tribhuvan University, Battisputali, Kathmandu, Nepal) have been added to the authorship in the HTML and PDF versions of the article

Motivation and decision making in eSports spectatorship in China

With eSports gradually growing into a large and competitive industry, a plethora of literature has investigated eSports from various aspects, such as performance, wellbeing, sponsorship, or motivation for participants and spectators. Despite the widely acknowledged importance of eSports events, limited effort has been seen in the field of service quality and its impact on the level of spectators’ satisfaction and revisit behaviours. In addition, motivation of off-line eSports spectators who visit physical stadiums have received considerably less academic attention, compared to online spectators. China, as the largest and leading eSports market in the world, hosts a significant number of eSports events every year, including some of the highest-level international events. Using China, which is likely to remain the pioneer in eSports development around the world, as the context to investigate eSports events and spectators could provide insights for eSports researchers and practitioners in other countries.  In order to delineate the psychological pathway to explain and predict eSports events off-line spectators’ behaviours, a plethora of relevant literature was thoroughly reviewed to develop a measurement model of perceived service quality of eSports events and to establish hypotheses on relationship with its antecedent constructs (i.e., psychological needs and motivation) and consequent constructs (i.e., satisfaction and revisit intention). To test this psychological pathway, three research purposes were to be achieved. Firstly, the measurement model of perceived service quality was tested following a thorough and systematic scale development process, supporting the reliability and validity of the scale. Secondly, as the measurement of other constructs were adopted from different scales, their overall and internal model fits were tested using a confirmatory factor analysis (CFA) technique. Finally, the relationships among basic psychological needs, motivation, perceived service quality, satisfaction, and revisit intention were examined using structural equation modelling (SEM).  This research takes a shallow realist ontological position and an empiricist epistemological position, which forms the positivism research paradigm. Accordingly, a deductive strategy is adopted. Three rounds of data collection were completed from the 2020 S10 League of Legends World Finals in Shanghai, the 2021 and 2022 seasonal professional eSports events in multiple cities in China, respectively. The first dataset (N = 272) was used for Phase One in EFA to identify the dimensions for the proposed service quality model, which are competition quality, physical environment quality, event execution quality, and interaction quality. There were 20 items retained in total. The second dataset (N = 485) was used for Phase One in CFA tests. The results supported the four-dimensional measurement model in Phase One. The measurement models for the other constructs were also tested in Phase Two, and the CFAs supported the psychometric properties of the proposed measurement models (three-dimensional needs satisfaction, two-dimensional motivation, and unidimensional satisfaction and behavioural intention). The third dataset (N = 217) was used for Phase Three to test the hypothetical relationships in the structural model. The path analysis results supported 15 out of 19 hypotheses. This thesis makes significant contributions to the current spectating sport service quality literature and eSports studies by conceptualising and developing the measurement model for perceived service quality, which also empirically presents a full picture of the psychological process behind eSports offline spectators attendance behaviour. For practitioners, this thesis provides practical instruments to evaluate eSports event quality and to understand or predict eSports spectator future attendance, which potentially enables event organisers to better manage or improve eSports events.</p

Developing a conceptual model of service quality for eSports

In this paper, a conceptual model for service quality of eSports events was proposed including four dimensions: competition quality refers to the perceived quality of the actual game itself; physical environment quality dimension stands for the physical surroundings where the service is produced and delivered; event execution quality measures the intangible items in the peripheral service which can be directly designed or managed by the event organizer; and interaction quality measures the interaction among spectators, such as crowd experience or social factor. The validity of each dimension in other service industries and its suitability in the eSports context are both taken into consideration. At the current stage, the model is conceptualized from existing literature, thus demanding further qualitative and quantitative study

Remaining Useful Life Prediction of Aircraft Turbofan Engine Based on Random Forest Feature Selection and Multi-Layer Perceptron

The accurate prediction of the remaining useful life (RUL) of aircraft engines is crucial for improving engine safety and reducing maintenance costs. To tackle the complex issues of nonlinearity, high dimensionality, and difficult-to-model degradation processes in aircraft engine monitoring parameters, a new method for predicting the RUL of aircraft engines based on the random forest algorithm and a Bayes-optimized multilayer perceptron (MLP) was proposed here. First, the random forest algorithm was used to evaluate the importance of historical monitoring parameters of the engine, selecting the key features that significantly impact the engine’s lifetime operation cycle. Then, the single exponent smoothing (SES) algorithm was introduced for smoothing the extracted features to reduce the interference of original noise. Next, an MLP-based RUL prediction model was established using a neural network. The Bayes’ online parameter updating formula was used to solve the objective function and return the optimal parameters of the MLP training model and the minimum value of the evaluation index RMSE. Finally, the probability density function of the predicted RUL value of the aircraft engine was calculated to obtain the RUL prediction results.The effectiveness of the proposed method was verified and analyzed using the C-MAPSS dataset for turbofan engines. Experimental results show that, compared with several other methods, the RMSE of the proposed method in the FD001 test set decreases by 6.1%, demonstrating that the method can effectively improve the accuracy of RUL prediction for aircraft engines

A reexamination of Sport Motivation Scale-II in eSports spectatorship: Cross-validation of intrinsic motivation and integrated motivation

Although the discriminant validity issue between intrinsic and integrated motivations has been reported in several self-determination theory (SDT) studies, limited effort is seen on the investigation of this issue. This gap is calling for further studies, especially with increasing numbers of motivation studies applying the SDT in a new area, eSports. To fill the gap, using Sport Motivation Scale-II, this study assesses such discriminant validity of intrinsic and integrated motivations in the eSports context. Data (N = 425) were collected from eSports spectators and analyzed using CFA and a double cross-validation technique. The CFA showed that a correlation between two factors was very high (.995). The squared correlation coefficient (.99) was higher than the AVE values of intrinsic (.63) and integrated (.62) motivations, failing to discriminate each other. It also supported the one-factor model (AIC = 104.752 < 107.038; ECVI = .247 < .252) over the two-factor model in terms of the adequacy of the model. Thecross-validation results from two rounds of CVI test (.64 and .51 for one factor model; .68 and .52 for two-factor model) both supported the one-factor model. Therefore, when measuring eSports spectators’ motivation, their regulation is better explained when intrinsic motivation and integrated motivation are considered the same. This study provides a new perspective on the existing discussion and serves as a reference for future eSports researchers in this subject matter.</p