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Climate factors determine large-scale spatial patterns of stomatal index in Chinese herbaceous and woody dicotyledonous plants
No full textThe stomatal index (SI, %) and its response to climate factors (temperature and precipitation) can help our understanding of terrestrial carbon and water cycling and plant adaptation in the ecosystem, however, consensus has not yet been reached in this regard. In this study, we compiled an extensive dataset from the Chinese flora to investigate the response of SI to environmental change, including 891 herbaceous and woody species from 188 published papers. The results showed that mean values of the adaxial SI and abaxial SI for all species were 14.06 and 19.22, respectively, and the ratio of adaxial to abaxial SI was 0.84. For the adaxial SI, abaxial SI, and the ratio of adaxial to abaxial SI, the range of these values varied between 0.05–43.67, 0.01–48.17, and 0.03–4.31, respectively. Compared with woody plants, herbaceous plants showed higher values in both adaxial and abaxial SI. In terms of the impact of climate factors, the abaxial SI of herbaceous plants changed slower than the adaxial SI, while woody plants showed the opposite trend. Threshold effects of increased temperature and precipitation on SI were observed, indicating that SI responded differently to changes in climate factors at different levels. Climate factors play a crucial role in driving the adaxial SI than abaxial SI. Our findings highlight the significant challenges posed by divergent responses of SI in forecasting future water and carbon cycles associated with climatic and environmental change. © 2024 Elsevier B.V
Fault classification and localization of multi-machine-based ieee benchmark test case power transmission lines using optimizable weighted extreme learning machine
Get PDFAccurate fault diagnosis in transmission lines is crucial to ensure the reliability and stability of power grids. Conventional approaches often rely on expert knowledge or complex feature extraction methods, which are subjective and time-consuming. Additionally, many existing approaches use separate sub-algorithms for fault classification and localization. These are operating independently and sequentially. This research work proposes an innovative method for fault classification and localization in transmission lines using phasor measurement unit (PMU) data. The proposed method employs a Weighted Extreme Learning Machine (WELM) algorithm, which uses the variable data distribution across different fault classes through a weighted approach. The PMU data is generated by simulation using an IEEE 9-bus test system in the MATLAB simulation environment. The Maximal Overlap Discrete Wavelet Transform-based feature extraction technique is applied to derive input feature data to facilitate fault classification and localization. The WELM classifier is also optimized using the Grey Wolf Optimization (GWO) algorithm. The resulting GWO-optimized WELM (GWO-WELM) model, when trained on PMU data, achieves a remarkable fault classification accuracy of 99.83 % and fault localization accuracy of 95.48 %, respectively. These results demonstrate that the GWO-WELM model outperforms commonly used classifiers. Moreover, the proposed model shows robustness by accurately classifying the noisy data with a signal-to-noise ratio (SNR) of 10 dB (achieving 91.5 % accuracy in classification and 88.1 % accuracy in localization, respectively). © 2024 The Author(s
Women’s non-linear journeys into and through higher education are considered through an emergent research process that spans qualitative and post-qualitative practice
Get PDFFounded on and sustained through patriarchal thought and value systems, higher education remains a highly gendered and en/gendering institution. This reflects and simultaneously constitutes epistemological injustice, and creates a viscous cycle or de/privilege. Moreover, regionality de-centres and further marginalizes women academics, and those belonging to other equity groups experience compounding inequities. To understand the experiences of ‘becoming’ women academics within regional universities, we engaged a qualitative collaborative autoethnography and the post-qualitative practice of re-considering and re-inscribing ethnographic ‘data’ that glowed in us. These glowful data illuminated our ‘non-linear’ and non-teleological careering away from, around, and into academia, highlighting synergies between our ‘non-traditional’ academic pathways and (un)structured, in-the-making epistemological practice. In this paper, we share our ‘glowful’ process and consider the possibilities (and tensions) of engaging in research that occupies a space bordering qualitative and post-qualitative inquiry, designed to resist Cartesian and Positivist epistemologies and methodological practices. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
Implicit language policy in ethnic minority migrant community in urban China : a study of the linguistic landscape of “Little Lhasa”
No full textA key focus of linguistic landscape research is the interaction among local language policies, the visibility of minority languages on public signage, and the perceptions of residents regarding language use. In China, ongoing urbanization and eased household registration requirements have precipitated an influx of ethnic minority migrants from autonomous regions to urban locales. This migration raises crucial questions about the integration and acceptance of ethnic minority migrants within the sociolinguistic fabric of urban China. Combining a linguistic landscape analysis and interviews with public sign owners, this study examines attitudes towards Tibetan language and Tibetan migrants in “Little Lhasa” in Chengdu, a major city in western China. Our findings reveal that various social actors, including Han residents, the Neighbourhood Committee, and the municipal authorities, prudently leverage the semiotic potentials of the Tibetan script in crafting public signs. The visibility of Tibetan in the local linguistic landscape reflects ideologies of acceptance, hesitation, or concern regarding Tibetan migrants. Although Tibetan migrants have conceded aspects of their language use in exchange for integration into urban life, they have not yet gained wider community acceptance. This study offers an innovative linguistic landscape lens on the implicit language policy in an ethnic minority migrant community in urban China. It illuminates a reflective case where language planning is much needed for mitigating bias and misunderstanding in multi-ethnic communities. © The Author(s), under exclusive licence to Springer Nature B.V. 2024
Competing effect of jetting during microbubble-mediated sonothrombolysis
No full textSonothrombolysis is a technique that uses ultrasound and microbubbles to break down the clot. Despite its potential, it remains challenging to identify the right combination of ultrasound and microbubble properties that can lead to the best treatment of clots. To address this, a finite element model of a microbubble surrounded by blood and is next to a clot was developed to investigate the jetting behaviour of microbubbles using different combinations of microbubble radius and ultrasound pressure. Numerical results indicated a strong competing effect between jet velocity, jet width, and distance travelled by the bubble, which is likely due to the confining effect of clot. This effect can be detrimental to sonothrombolysis, especially when using smaller microbubbles. In addition, a higher ultrasound pressure was found to affect the jetting behaviour in a similar way as using a larger microbubble. The ability of the model to visualize the bubble behaviour in the fast temporal and the small spatial scale opens numerous opportunities for the optimisation and clinical translation of sonothrombolysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
Using complex adaptive systems (CAS) framework to assess success factors that lead to successful organizational change : a new way to understand change implementation for success
No full textPurpose: The purpose of this paper is to assess the success factors in a large organization that contributed to the success of organizational transformation (OT) through business diversification using a complex adaptive systems (CAS) framework. This assessment is done to determine how well the CAS framework can explain the success factors that contribute to the success of large-scale organizational change in complex organizations. If the CAS framework is capable of explaining the organizational factors that lead to the success of change implementation, the managers can employ this framework to increase the likelihood of success while implementing change. Design/methodology/approach: This study uses qualitative research methodology. The data were collected from the case study organization (CSO) through 40 in-depth semi-structured interviews and analyzed using thematic deductive analysis approach. Findings: The CAS framework explains the success factors that contribute to the success of OT through business diversification. Practical implications: This paper provides a comprehensive guide for change implementation by combining the insights from the CAS framework with identified success factors (for change implementation) from the case organization. Originality/value: The originality of this paper lies in extending the principles of existing change models, for successful change implementation by using the CAS framework. The prescribed change models and the CAS framework/complexity theory are two distinct sets of literature; this paper successfully merges the two to develop a comprehensive set of guidelines for change implementation. By doing so, this paper highlights the fact that alternative, non-linear, change approaches, instead of conventional multistep change models, can be effective in implementing large-scale organizational change successfully given the complexities of current organizational environments. © 2024, Emerald Publishing Limited
Learning landscapes through technology and movement : blurring boundaries for a more-than-human pedagogy
Get PDFInterest in the role of technology and movement is growing in outdoor environmental education (OEE) research. However, there are many unexamined assumptions involving both non-digital technology and movement for outdoor learners. In this paper, we explore learning landscapes through non-digital technology and movement involving canoe journeys in south-eastern Australia. We examine ways that technology and movement come together to help shape learning orientations through situated examples from OEE fieldwork. Our investigations utilise posthumanist and process-relational theories for exploring onto-epistemological dimensions of outdoor learning. We bring such theory into conversation with photos, videos and student essays to analyse our fieldwork contexts. We highlight that technology and movement cannot be taken for granted; rather, they help constitute the ways we come to know places. We also acknowledge some cultural and conceptual aspects that overlap to influence learning. This paper offers alternative insights for learning landscapes and the mediating influence of technologies. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
Adoption of immersive-virtual reality as an intrinsically motivating learning tool in parasitology
Get PDFVeterinary parasitology is study of parasitic diseases, treatment and prevention. It is a major component of animal health courses due to impacts parasites have on production and companion animals. Extant tertiary education in parasitology typically involves theory sessions coupled with practical experience. In this study we propose tertiary parasitology teaching would be enhanced through adoption of immersive Virtual Reality (I-VR) as an intrinsically motivating learning tool to complement their studies. To evaluate this adoption, a custom I-VR parasitology game was developed that tertiary veterinary science students experienced (n = 109), with feedback assessed using the Hedonic-Motivation System Adoption Model (HMSAM). HMSAM proved appropriate for measuring student’s hedonistic and utilitarian perspectives of I-VR experience with perceived ease of use, perceived usefulness, joy, ability to control, immersion levels and intention to use displaying significant positive relationships in derived model. However, in a departure from similar studies, the curiosity construct was not a useful predictor of intention to use in this context of a scaffolded, instructional application. This study highlights suitability of I-VR and provides a statistically robust evaluation method using a modified HMSAM to evaluate acceptance, usefulness, and ease of use of I-VR in tertiary education. © The Author(s) 2024
The Children’s Picture Books Lexicon (CPB-Lex) : a large-scale lexical database from children’s picture books
No full textThis article presents cpb-lex, a large-scale database of lexical statistics derived from children’s picture books (age range 0–8 years). Such a database is essential for research in psychology, education and computational modelling, where rich details on the vocabulary of early print exposure are required. Cpb-lex was built through an innovative method of computationally extracting lexical information from automatic speech-to-text captions and subtitle tracks generated from social media channels dedicated to reading picture books aloud. It consists of approximately 25,585 types (wordforms) and their frequency norms (raw and Zipf-transformed), a lexicon of bigrams (two-word sequences and their transitional probabilities) and a document-term matrix (which shows the importance of each word in the corpus in each book). Several immediate contributions of cpb-lex to behavioural science research are reported, including that the new cpb-lex frequency norms strongly predict age of acquisition and outperform comparable child-input lexical databases. The database allows researchers and practitioners to extract lexical statistics for high-frequency words which can be used to develop word lists. The paper concludes with an investigation of how cpb-lex can be used to extend recent modelling research on the lexical diversity children receive from picture books in addition to child-directed speech. Our model shows that the vocabulary input from a relatively small number of picture books can dramatically enrich vocabulary exposure from child-directed speech and potentially assist children with vocabulary input deficits. The database is freely available from the Open Science Framework repository: https://tinyurl.com/4este73c. © Crown 2023
Convolutional neural network regression for low-cost microalgal density estimation
Get PDFDensity of microalgae is critical information for production of algae in a closed cultivation system since it can be used to optimally control their growth rate, biomass concentration and quality of the products. Given advancement in image processing techniques and thanks to low-cost camera sensors, image based methods are increasingly widely utilized to indirectly estimate the density. Advantages of the image based techniques include being less invasive and more nondestructive and biosecured. However, most of the existing techniques rely on averaging all pixels of a microalgae image, which may eliminate crucial information of their spatial correlation. Therefore, in this work we propose to exploit a convolutional neural network (CNN) to efficiently extract information from the microalgae images, which are then employed to regress the density. Interestingly, the proposed deep CNN regression model accepts the whole color image as its input while the density is calculated in the output. The proposed CNN regression architecture was validated in real-world experiments where the microalgal strain Chlorella vulgaris was cultured and their images were captured by our low-cost camera sensor system. The obtained results demonstrate that the averaged estimation accuracy of the proposed model is 99.45% (± 0.68%) while the R2 value between the density predictions and the ground truths is 0.9997, which is highly accurate and practical. © 2024 The Author(s