38541 research outputs found
Sort by
Protective attitudes towards females: demonstrated in differential reactions to sex-differences research
No full textPeople tend to react less positively to findings or real-life situations (such as male- or female-dominated careers) when these favour males over females. To explore the reasons for this response, we conducted five studies. In Studies 1 (Western sample) and 2 (mostly Malaysian sample), we examined four independent variables—favoured sex, lead researcher sex, impact of sex-differences research, and participant sex—in relation to participants’ reactions to fictitious research on sex differences in intelligence. Mediators (perceived harmfulness and need to protect the disfavoured sex) and moderators (women-are-wonderful effect and political orientation) were also examined, with Study 2 adding social dominance orientation into the mix. Studies 3 (Western sample) and 4 (mostly Malaysian sample) explored the influence of favoured sex, sex-specific hurdles, and participant sex on reactions to the same fictitious research, using the same mediators and additional moderators, such as religiosity and feminist beliefs. Study 5, which included participants from South Africa, Poland, Mexico, the United Kingdom, Italy, and other countries, examined the effects of protagonist sex and age in a charity appeal, as well as participant sex, on donation willingness. While protagonist sex and age did not affect willingness to donate, female participants were generally more willing to donate than male participants. Overall, results indicate that participants reacted less positively to male�favouring sex differences research, especially if led by a male researcher, likely due to perceived harm to females. Certain groups—those with liberal political views, lower social dominance orientation, or a higher susceptibility to the women-are-wonderful effect—exhibited even less positive reactions. These findings support the greater-protectiveness-of-females (G-PROF) theory. Future research could further investigate the greater protectiveness of females across different contexts and continue to test whether differential reactions are driven by various types of perceived harm (e.g., tangible, non-physical, caused by a perpetrator, or naturally occurring, etc.)
Transcending time and space: a holistic exploration of the mechanisms underlying autobiographical memory retrieval
No full textAutobiographical memories are memories one has of their life experiences. Although decades of research have provided insights into the mechanisms underlying memory retrieval from different perspectives (e.g., biological, cognitive, evolutionary, forensic, and clinical), there is still much about the retrieval process that is not well understood. The present thesis, therefore, aimed to bridge the gaps in the literature by examining autobiographical memory retrieval at both between-subjects and within-subjects levels.
Given the multidimensional nature of autobiographical memory, the second chapter of this thesis explored whether and to what extent the six aspects of memory (i.e., memory accuracy, memory specificity, recollective experience, memory functionality, rumination, and executive functioning) are related. In the first study, 53 pairs of monozygotic and 39 pairs of dizygotic twins watched a video of a simulated theft and later answered a recognition test measuring accuracy for items in the video. In between, participants retrieved 10 personal events with the help of cues and rated these memories on recollective experience. They also completed questionnaires measuring functionality and rumination, along with five tasks measuring the mental flexibility, visuospatial processing, inhibition, and the forward and backward verbal learning processes of executive functioning. Findings from Study 1 revealed that not all aspects of autobiographical memory are related. Whereas rumination and memory functionality were related, memory accuracy, memory specificity, recollective experience, and executive functioning appeared to function more independently.
To validate the findings of Study 1, a second study was conducted with a sample of 153 undergraduate students from the University of Nottingham Malaysia. Participants followed the exact same procedure as Study 1. Although the results of Study 2 largely resembled those of Study 1, Study 2 additionally found an association between recollective experience and memory functionality.
Using the data from Study 1 of Chapter 2, Chapter 3 of this thesis examined whether the six aspects of autobiographical memory are heritable. Because most of the correlations from Studies 1 and 2 were not significant, we conducted two exploratory factor analyses to determine whether there were underlying factor structures across the different aspects. The factor analyses revealed one new factor: working memory capacity (which is a combination of visuospatial processing and forward and backward verbal learning). Despite some reliability issues, findings from Chapter 3 revealed support for additive genetic contributions to rumination and working-memory capacity.
Whereas the previous chapters examined memory retrieval on a between-subjects level, Chapter 4 goes a level lower, and examines autobiographical memory retrieval on a more within-subjects level. Studies have shown that visual imagery and working memory are both important during the retrieval of autobiographical memories. However, their exact contributions during memory retrieval remains unclear. To address this gap in the literature, Chapter 4 compared the relative contributions of visual imagery and working memory during the retrieval of autobiographical memories using a dual-task paradigm. In the first study, 46 participants retrieved their autobiographical memories while following a moving dot, viewing a Dynamic Visual Noise (DVN), or viewing a blank screen. The memories retrieved were then rated on phenomenological properties, such as recollective experience, vantage perspective, emotional intensity, and emotional valence. Due to some technical and methodological limitations in Study 1, a follow-up study was conducted with 95 participants. Findings from both studies revealed that inhibiting visual imagery processing only delayed the memory retrieval process but did not affect the phenomenological quality of the memory retrieved. Furthermore, although taxing the working memory delayed the retrieval process, the phenomenological quality of the memories remained unaffected.
The findings of the current thesis highlight the importance of examining autobiographical memory more holistically. For instance, the associations between functionality and rumination, and between functionality and recollective experience, found in the present thesis suggest potential mechanisms that warrant further investigation. Furthermore, because the present thesis found support for the influence of additive genetics on the rumination and working memory capacity aspects of autobiographical memory, future studies should aim to identify the genes associated with these different aspects as this would deepen our understanding of the contributions of additive genetics and the environment on autobiographical memory retrieval. A better understanding of autobiographical memory retrieval would also aid clinicians in increasing the efficiency of the treatment of different clinical disorders, like depression and PTSD. This in turn, would help people develop healthier coping strategies, and lead better lives
Stirring and bubbling mechanisms in a closed system for microalgae cultivation
No full textThe increased demand for microalgae in various industries, from bio-based to healthcare products, has attracted interest in creating a new hybrid cultivation system. Current cultivation systems apply bubbling or waterflow to create fluid turbulence and improve microalgae growth. It is understood that a specific rate of stirring motion exerts stress on microalgal cells, increasing the reactive oxygen species (ROS) levels, which could damage cells. However, some positive hormetic responses due to microalgae’s defensive mechanisms have promoted growth. Combining both mechanisms within a single cultivation system may help to double the growth-promoting effect on microalgae. Moreover, including stirring mechanisms within the cultivation system enhances the microalgae's growth. It is worthwhile to study the threshold value of the stirring speed and bubbling rate without damaging the microalgal cell. The biomass, protein, and carbohydrate contents are optimum (4.335 g/L, 0.575mg/mg, and 0.117 mg/mg, respectively) when the stirring speed is 360 rpm under a constant bubbling rate. On the other hand, the optimum bubbling rate was determined when the bubbling rate was 15 v/v% of the cultivation system (1L), which was 150 cc/min. The biomass, protein and carbohydrate content concentrations are 5.229 g/L, 0.577 mg/mg, and 0.087 mg/mg, respectively. A mathematical model is synthesised better to represent the relationship between both mechanisms and microalgae growth. SEM imaging of microalgal cells at different stirring speeds showed that increased stirring speed from 0 to 420 rpm contributed to cell disruption. The cell damage was most severe at a stirring speed of 420 rpm, indicating that a higher mechanical stress acted on the cell. The upscaling of the microalgae cultivation system from 1 L of a laboratory-scale photobioreactor to 5 L of an upscaled photobioreactor showed eminent success, where the biomass was able to reach approximately 5 times the biomass weight of a laboratory-scale photobioreactor (5.283 g/L to 27.860 g/L). The upscaled cultivation stirring and bubbling rates were set at a rounded value of 350 and 400 rpm, and 15 % of the total volume of the cultivation system, respectively, as determined from previous experiments. A study on the possible inclusion of machine learning (ML) was conducted using different methods to address high-level problems such as salinity, temperature, and nutrient concentrations. The usefulness and feasibility of ML in microalgae cultivation were discussed and elaborated on, along with its potential utilisation in the industry. A discussion on the use of the optimal stirring rate and bubbling rate in a closed system was presented, together with the importance of a closed system in an automated system with machine learning. The final goal of these experiments was to study the feasibility of a closed system with stirring and bubbling automated by machine learning
Underwriting decisions, shareholder participations, and investor identities: three essays on seasoned equity offering
No full textThis dissertation is composed of three independent yet thematically integrated research papers that investigate various aspects of seasoned equity offerings (SEOs) in the Hong Kong and Chinese stock markets. In general, the underwriting decisions of rights issues in Hong Kong Exchanges and Clearing Limited (HKEX) are discussed in the first research paper; the second research paper examines how participation rate and wealth transfer relate to the long-term stock performance of Chinese rights-issuing firms; and the third research paper investigates the determinants of Chinese issuing firms’ long-term stock performance when private placements are issued to different identities of investors and examines the issuers' price management mechanisms. While each paper addresses several distinct research questions, they share a common objective of providing valuable insights into seasoned equity offering strategies by examining issuing firms’ financing motivations, investor behaviour, and market mechanisms, thereby offering theoretical and practical implications for issuers, investors, and regulatory authorities.
The first paper seeks to explain why a large number of issuers in the Hong Kong stock market still choose to have their rights issues underwritten despite the removal of mandatory full underwriting requirements since the third quarter of 2018. These issuers are required to disclose the intended use of proceeds in their rights issue announcements. Our findings indicate that rights issuers who intend to raise funds for debt repayment are particularly concerned about the guaranteed receipt of proceeds and demonstrate a strong preference for securing underwriting services from investment banks. We further highlight that the debt structure of issuing firms plays a crucial role in their intention to use the proceeds for debt repayment. Specifically, firms with high leverage and substantial short-term debt obligations generally have urgent funding needs, driving them to raise funds through rights issues to repay their debt.
Unlike the take-up rate, the participation rate reflects the actual involvement of existing shareholders in rights issues. When existing shareholders give up their rights to subscribe to new shares at a discount or do not fully subscribe to their pro-rata shares, these lead to a lower participation rate and an inevitable wealth transfer occurs from non-participating shareholders to participating shareholders. Compared with price discounts, the wealth transfer can better capture the interplay between price discounts, offer size, and participation rates in rights issues. The second paper investigates the association of participation rates and wealth transfers with issuing firms’ long-term stock performance, and we find that rights issues with higher shareholder participation rates and lower wealth transfers tend to exhibit superior long-term stock performance. Existing shareholders can play a certification role; therefore, both their participation rate and the wealth transfer among them convey credible information about the future stock performance of issuing firms. This offers a novel perspective for understanding the stock performance of firms conducting rights issues.
The third paper examines the long-term stock performance and potential stock price management associated with private placements in the Chinese stock market, with a particular focus on investor identity. Building on prior studies that have attempted to classify investor identities in various ways, this paper introduces a refined categorization that distinguishes among individual investors, strategic investors, and financial institutional investors, providing a more nuanced understanding of their differential impacts on long-term stock performance. The results show that private placements involving existing managers and financial institutional investors who are also the existing major shareholders are associated with a certification effect, whereas those involving strategic investors leading to the emergence of a controlling shareholder exhibit a monitoring effect. In the context of the Chinese stock market, where the China Securities Regulatory Commission (CSRC) imposes strict restrictions on discount rates and lock-up periods, issuers have strong incentives to engage in stock price management to implicitly compensate investors. Despite regulatory constraints, issuers retain flexibility in selecting the pricing benchmark day, which enables them to influence stock prices prior to issuance. This study thus further investigates whether firms strategically manage the timing of firm-issued news items disclosure to influence stock prices and examines the subsequent two-year stock performance following private placements. We find that issuers manage the timing of news releases around the pricing benchmark day to depress stock prices beforehand and inflate them afterward, thereby enabling investors to obtain greater implicit discounts. This study contributes to the literature by offering a more detailed investor classification and uncovering the mechanism of stock price management in Chinese private placements
IPO market performance and multi-dimensional market sentiment : evidence from Malaysia’s short-run, long-run, and regulatory changes perspectives
No full textThis study constructs a multi-dimensional Malaysian IPO Market Sentiment Index based on aggregated sentiment proxies spanning firm-specific, market-level, and macroeconomic dimensions. It investigates how this sentiment index explains IPO market performance in Malaysia through 3 key lenses: short-run share performance, long-run share performance, and the impact of regulatory changes.
Using a dataset of 571 IPOs listed on Bursa Malaysia from January 2000 to December 2020, the study measures short-run share performance via initial returns, and long-run share performance using cumulative average abnormal returns, buy-and-hold abnormal returns, and wealth relatives. Multiple regression models, interaction effects, binary regression models, and marginal probability analysis are employed to examine the relationships between market sentiment, fundamental factors, and IPO outcomes. Findings reveal that IPOs are significantly underpriced in the short-run, with offer price, oversubscription ratio, board listing, and hot issue market conditions as key determinants. Market sentiment plays a limited role in short-run share performance of IPO but interacts with several issue- and market-specific variables, suggesting that market sentiment effects are conditional rather than dominant during initial trading. In contrast, market sentiment significantly influences IPO’s long-run share performance. Behavioural factors, investor expectations, and market volatility become more relevant as firms transition into the post-listing phase. These results align with Shiller’s (1990) fads theory, which explains how investor over-optimism leads to mispricing that is eventually corrected over time. Additionally, the study also analyses the role of market sentiment and price-earnings (PE) towards IPO underpricing during regulatory changes. Quantile regression results show that sentiment influences are significantly stronger at higher PE quantiles, indicating that high-PE IPOs are more exposed to overvaluation risk during periods of heightened optimism or volatility. Additionally, comparative analysis between the pre- and post-2009 periods reveals a shift from sentiment-driven IPO valuations to more fundamental-based pricing under the disclosure-based regulatory framework.
This study contributes to the IPO literature by introducing a multi-dimensional market sentiment index tailored to Malaysia’s IPO context. It offers practical implications for investors seeking better timing strategies and for regulators aiming to distinguish between sentiment-driven and fundamental valuations. Overall, the study underscores the evolving role of market sentiment in IPO markets and its interaction with regulatory frameworks
Impacts of exceptional points and phase angle on the entanglement dynamics of two-qubit open quantum system
No full textThis study investigates the dynamics of two-qubit systems in open quantum environments, with a focus on the influence of exceptional points (EPs) and phase angle on entanglement dynamics. Two-qubit systems are pivotal in quantum information science, as they are the simplest system that reveals quantum entanglement, a crucial resource for quantum computing and communication. The research explores the effects of coupling, spontaneous emission, and environment on two-qubit states, specifically the -states, within the framework of the Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) or Lindblad master equation.
EPs are unique to non-Hermitian systems. They affect the system’s dynamics significantly when the system approaches EP. Analytical and numerical analyses reveal that third-order EPs occur at specific parameters for two-qubit system, leading to critical changes in eigenvalues and eigenvectors of the Liouvillian superoperator. The study demonstrates that EPs can enhance or suppress entanglement. The concurrence, a quantitative measure of entanglement, peaks around the EPs under certain initial conditions.
Furthermore, the impact of phase angle, , that parameterizes the relative phase of maximally entangled states is analyzed. For initial states labeled as in this thesis, the phase angle significantly influences concurrence evolution, enabling tunability of entanglement dynamics. In contrast, for other class of initial states labeled as , concurrence exhibits phase invariance, ensuring stability across the variations in . Besides this, the analysis shows that the maximum concurrence occurs around EP for some states, the phase angle can also be tuned to increase the concurrence for some initial states. These findings highlight the importance of both EPs and phase angle in optimizing entanglement generation and control.
This research offers valuable insights into the interplay between non-Hermitian physics and quantum entanglement, paving the way for advancements in quantum technologies. The outcomes provide possible practical implications in the field of quantum computation
Germline determinants of the immune response in Asian breast cancer
No full textBreast cancer is a complex disease with heterogeneity in tumour characteristics and treatment response. Recently, Asian breast cancer patients were reported to have elevated immune scores in comparison to Caucasian breast cancer patients, however, germline genetic determinants associated with immune scores in Asian breast cancer patients remain undercharacterised. This study aims to identify the germline genetic variants associated with heritable immune scores in Asian breast tumours and determine the cellular pathways that drive immune scores within this population.
By evaluating 112 immune scores that have previously been described in literature, we observed significantly higher heritability in Asian breast tumours compared to Caucasians. The major histocompatibility complex class-I (MHC-I) immune score had high heritability in both cohorts. By conducting a genome-wide association study (GWAS), the findings revealed, as predicted, the HLA locus on chromosome (chr) 6 in both Asian and Caucasian cohorts.
Regulatory T (Treg) cells, Immune non-small cell lung cancer (NSCLC) score, Triggering receptor expressed on myeloid cells 1 (TREM1) score and T follicular helper (Tfh) cells were the most heritable immune scores in Asian breast tumours. A total of 37 candidate SNPs were identified through GWAS. Expression quantitative trait loci (eQTL) analysis and a review of current literature revealed variants in TNFRSF13B, PRKCQ, IL2RA, and MIR149 as candidate cis-eQTL loci with potential roles in immune function and immune scores. Taken together, these findings suggest that there may be a population-specific genetic influence on heritable immune traits. This study identifies candidate variants that may underlie these observed differences
An investigation of neural information retrieval based temporal embeddings and knowledge extraction for scientific insight generation
No full textHumans today generate information at an unprecedented rate, leading to a vast accumulation of knowledge. This immense amount of data poses challenges in extracting both explicit information and implicit knowledge, predicting scientific events, and investigating scientific trends and trajectories. For decision-makers, it is particularly challenging to keep pace with this abundance to make informed decisions grounded in quantitative and up-to-date data. Current state-of-the-art methods, such as those employing Word2Vec models for semantic analysis, face several technical challenges when applied to vast and diverse datasets, including scalability issues, contextual ambiguity, difficulty in capturing implicit and explicit knowledge, and challenges with temporal embeddings. These models are also susceptible to bias and noise, and the impact of hyperparameter tuning on knowledge representation can lead to inconsistent results, further complicating their reliability for informed decision- making. While some existing research addresses the problem of knowledge evolution, they often fall short in handling large datasets, leading to scalability issues. Many studies focus primarily on changes in word meaning rather than the evolving relationships among entities, neglecting the broader context of temporal knowledge evolution. Additionally, the use of default hyperparameters in these models often overlooks their sensitivity to implicit and explicit knowledge extraction, resulting in inconsistent outcomes. Moreover, some techniques overly focus on event detection through specific text classifications, limiting their broader applicability in understanding complex knowledge dynamics over time. There is a lack of a coherent and efficient framework to represent, extract, and discover large-scale temporal knowledge to date. Therefore, this research aims to explore efficient, large-scale methodologies for extracting both explicit and implicit knowledge from extensive scientific literature and to build a big data, cloud-based knowledge evolution framework to identify scientific discoveries and their trajectories. Firstly, to build a large-scale knowledge evolution framework, it is important to study methods for efficient and accurate knowledge representation. To this end, as a case study, we investigate various embedding techniques for identifying relationships between underutilized crops and their attributes, such as global interest, vernacular and scientific names, and soil requirements. Word2Vec embeddings were analysed on extensive Wikipedia datasets, including multiple languages, and we found that our approach effectively identified relationships between underutilized crops and their attributes. These findings were then compared with an international database of crop characteristics, which showed a 76.11% accuracy in predicting soil classifications using scientific crop names, surpassing semantic relationship extraction methods in the literature. Following this case study, we identified a suitable embedding method for accurate knowledge representation, addressing the scalability issue by leveraging a cloud- based framework capable of processing vast datasets efficiently and maintaining high predictive accuracy. To create a coherent temporal representation of knowledge and classify it effectively, it is vital to generate high-quality embeddings for these temporal vector spaces. To this end, we evaluated various hyperparameter combinations of Word2Vec (the embedding method identified for achieving the first objective) against diverse Deep Neural Network (DNN) architectures to gauge their impact on classification tasks using the Amazon Customer Review dataset. The results from this dataset, which demonstrated a generic use case for understanding the implications of hyperparameters on downstream tasks such as classification, suggest that the hyperparameter tuning method and values could be effectively applied to the process of creating the temporal vector spaces, ensuring reliable knowledge representation across varying contexts and timeframes. Finally, based on the findings from investigations on Word2Vec-based knowledge representation and its hyperparameter tuning for optimized representation for downstream tasks, we propose our Continuous Knowledge Evolution Construction method, where knowledge is represented with its temporal element. The temporal vector space is a dynamic framework that captures the evolution of knowledge over time by constructing word embeddings that reflect changes in language and concept significance across different periods. In this method, Word2Vec is used to generate embeddings for each time slice of the dataset, such as monthly intervals. These embeddings are then aligned sequentially to form a continuum, allowing us to observe and analyse how the meanings and relationships of words and concepts shift over time. This approach enables the tracking of scientific trends, the emergence of new research areas, and the fading of older topics, providing a comprehensive view of the temporal evolution of knowledge within a given field. We evaluated the proposed framework on 2.3 million publications from the arXiv dataset, spanning science, mathematics, and physics. The framework generated hundreds of millions of predictions and captured relationships between scientific entities over time. We examined thousands of scientific entities, tracking them throughout our temporal knowledge evolution framework. Given the sheer volume of our findings, we relied on large-scale, cloud-based data analytics tools for data processing, storage, and visualization. This approach allowed us to establish 25 million temporal relationships between scientific entities, pinpoint specific scientific events, comprehend the trajectories of certain scientific trends, and discern overarching patterns in the evolution of science. The results highlighted that 76.2% of the scientific events and trends studied showed low variance, indicating a high level of predictive accuracy. To conclude, our research proposes a cloud-based temporal knowledge evolution framework to analyse the large-scale corpus of scientific literature. Through our investigation of text mining, embedding techniques, and DNNs, we elucidated implicit and explicit knowledge, uncovering millions of temporal relationships, and identifying key scientific events and trends. These results highlight the critical role of neural information retrieval of large-scale data in shaping our understanding of scientific knowledge evolution and aiding informed decision-making
Phenotypic and genetic investigation of plant phenological development, architecture and yield in winged bean (Psophocarpus tetragonolobus (L.) DC.)
No full textThe worsening effects of climate change and malnutrition have significantly impacted global food and nutrition security. Diversifying food sources through the cultivation of underutilised crops could mitigate these challenges and promote resilient agricultural food systems. Winged bean (Psophocarpus tetragonolobus (L.) DC.) is a protein-rich crop grown in humid tropical regions. With its various edible plant parts, broad distribution in the tropics, and adaptation to diverse local environmental conditions, it has notable trait variations for exploration in crop improvement. Research on winged bean genetic diversity has been limited in the past 50 years, primarily relying on phenotypic assessments without the utilisation of molecular markers. However, recent advancements in genotyping techniques have enabled the integration of phenotypic and genetic data. Molecular breeding accelerates the characterisation of diverse core collections, leading to cultivar development, contributing to global initiatives for dietary diversity and nutritional resilience.
A mini-core collection of winged bean comprising 22 accessions was formed from prior genetic diversity assessment of 91 accessions originating from seven countries, and two continents, using DArTseq SNP markers. Multi-locational trials of this mini core collection were carried out at three locations: the Field Research Centre of Crops for the Future Research Centre (CFF-FRC) in Semenyih, Malaysia (May 2019 to March 2020); the rainout shelter of the University of Nottingham Malaysia (UNM) in Semenyih, Malaysia (November 2020 to August 2021); and Fireflies Organic Farm (FF) in Broga, Malaysia (January to October 2021) in a randomised complete block design (RCBD). Among them, FP15 consistently exhibited shorter days to first flower (DtFF) and days to first pod (DtFP) within 79 and 81 days after sowing (DAS) at the CFF-FRC and 62 DAS and 64 DAS in the UNM rainout shelter, respectively with significant differences (p0.05) were found between phenological traits and yield traits. In contrast, significant positive correlations (p<0.05) were observed between architecture and yield-related traits, including stem length (StL) and pod length (PodLe) (r=0.791), PodLe and PodY (r=0.538), and PodLe and SY (r=0.526). These findings suggest that yield improvement could be achieved through selection based on plant architecture, particularly stem length, while phenological traits may have limited potential for direct yield selection. Nine accessions were identified based on their superior traits: FP15 and a57 for earliness in flowering and pod production, a10, a6, and a7 for consistent stem length, and a6, a13, a15, a35 and Ma3 for high pod yield and seed yield potential.
An in-field evaluation of 192 F2 lines (TF2) from a cross between i10 (high above-ground biomass, shorter pods) and FP15 (early flowering, early maturity, high harvest index) was conducted at Beacon Eco Farm, Mantin, Malaysia, from June to December 2022. The study assessed plant phenology, architecture, yield, and yield components in an RCBD with four blocks. Significant differences (p<0.001) were observed between parents for flowering initiation, pod production, and seed harvest, with F2 progenies showing intermediate trait values. Significant positive correlations were found between DtFF and DtFP (rs=0.707), DtFF and DtMS (rs=0.455), and DtFP and DtMS (rs=0.554) at p<0.001. No significant differences were found between parents for architectural traits including number of branches (NoB), sum of branches length (SoBL), and StL, but transgressive segregation occurred in the TF2 population. Both parents differed (p<0.05) in yield components such as seeds per pod (SPP), above-ground biomass (AGB), and harvest index (HI) while significant differences (p<0.001) were observed for PodLe, pod width (PodWi), and below-ground biomass (BGB). Five TF2 lines — L012, L013, L014, L015, and L109— produced up to 15,120 kg/ha of pods and 5,725 kg/ha of seeds, with early flowering and seed harvest comparable to FP15, making them distinguished candidates for selection and advancement to the F3 stage.
A genetic linkage map was constructed, followed by QTL analysis. Initially, a total of 4576 DArTseq SNP markers were filtered from 6025 SNP markers of 184 TF2 individual lines. A genetic linkage map consisting of ten linkage groups was constructed from 493 polymorphic SNP markers, with two linkage groups of Chromosome 03 were obtained. The map was 1053.3 cM in total. A total of 15 significant QTLs were identified for ten traits, including DtFF, DtFP, DtMS, 15th internode length (IntL15), 20th internode length (IntL20), NoB, pods per plant (PPP), PodLe, PodWi and seed colour (SC), distributed across six linkage groups: LG01, LG04, LG05, LG07, LG08, and LG09. These QTLs were major accounting for more than 15% of the phenotypic variation in each trait. Additionally, nine transcription factors potentially associated with germination, mature seed harvest, seed yield, seed colour and leaf chlorophyll content were identified.
In-field evaluation of subsequent F3 and F4 generations will aid in selecting superior lines and refining QTL mapping for marker-assisted breeding. Further study of trait inheritance will provide deeper insights into winged bean yield traits. Multi-location trials will help identify key trait correlations in phenology, architecture, and yield, laying the foundation for developing improved cultivars with early maturity and high yield potential. QTL mapping of genetic regions responsible for trait expression will inform future breeding, not only for winged bean but also for other crops facing similar challenges. Ultimately, this project contributes to the efforts aimed at improving global food and nutrition security by expanding the range of crops available and improving their yield potential to address changing environmental conditions
Interactive cultural narratives: unveiling the potential of the 3D serious game maker tool for Kristang culture
Full text linkCulture is a cornerstone of identity, yet many cultures face the risk of fading into obscurity despite efforts to preserve them through various mediums. Leveraging the concept of 3D serious games and basing the research on key learning theories like the maker pedagogy and multiliteracies theory, this research aims to educate children about culture by developing a 3D game maker tool that implements key elements of the researched learning theories. The goal is to empower users aged 12 and older to effortlessly create serious 3D cultural games in a first-person view, enriching the experience with IoT and AI features. Additionally, the tool facilitates gameplay of games crafted using the same platform, fostering social interaction and aligning with effective forms of learning.
Methodologically, an iterative design process was employed, starting with the creation of initial prototypes and interviews to discern optimal features and design principles. The tool was refined based on insights gathered from existing literature on serious game design guidelines, prioritizing user-friendly accessibility, and ensuring the learning theories are properly implemented. In the final trial, participants engaged in crafting 3D serious games using the tool, juxtaposed against a control group utilizing a conventional 2D storyboarding tool. Subsequently, participants immersed themselves in a serious game experience exploring Kristang culture, with learning gain, memory, and knowledge retention meticulously evaluated.
Despite its focus on Kristang culture, the tool's adaptable nature suggests its potential applicability to diverse cultural contexts. Findings indicate that the tool improved user experience and learning outcomes for Kristang cultural heritage education compared to control methods. However, limitations such as a small sample size and system constraints were encountered.
Research implications delve into the potential of the 3D serious game maker tool as an effective educational tool for children to learn about culture, contributing to the broader understanding of utilizing innovative technology for cultural education among younger demographics. Moreover, design guidelines established in the study lay a foundation for future research endeavors seeking to develop effective educational tools with a significant impact on learning outcomes. Practically, integrating the tool into classroom settings holds promise for fostering immersive and interactive cultural education experiences, augmenting traditional instruction, and facilitating collaborative learning. This research introduces an innovative educational tool that combines elements of the maker movement with experiential learning paradigms, addressing the gap of lack in 3D cultural maker educational tools that combine learning theories into their framework. This research aims to implement those learning theories into an engaging 3D game maker tool specifically for the Kristang culture.
In conclusion, the development of this innovative 3D serious game maker tool represents a significant stride towards cultural education for younger generations. Embracing the opportunities presented by this tool can pave the way for more inclusive and dynamic approaches to cultural learning, empowering children to explore, create, and celebrate diverse cultural narratives in a digital age
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇