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Impact of financial management on perceived succession success of family businesses
Full text linkThis thesis examines the factors that influence perceived succession success in family-owned small businesses (F-OSBs), with a focus on the roles of financial management capabilities, financial heuristics, financial literacy, and fintech usage. Recognizing that family control over financial matters can lead to conflicts of interest and jeopardize financial stability, the study examines how financial management capabilities (audit, fraud, risk, and working capital management) impact succession outcomes, with fintech serving as a moderating mechanism to reduce familial influence and enhance longevity. Primary data were collected from successors in Malaysian F-OSBs, typically in chair or director roles, and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Findings indicate that audit and risk management positively impact perceived succession success, particularly with fintech support, while fraud and working capital management show mixed results. The study also explores financial heuristics—anchoring, herd bias, mental accounting, and risk aversion—revealing that while some biases positively correlate with perceived succession success, risk aversion negatively influences it. Financial literacy moderates specific heuristics, notably enhancing the influence of herd bias and risk aversion on succession. Additionally, financial socialization, mediated by financial literacy and fintech usage, plays a significant role in perceived succession success, especially for risk-averse successors who enhance financial literacy but are less inclined to adopt fintech. These findings highlight the importance of financial management skills, financial literacy, and selective fintech integration in achieving successful succession in Malaysian F-OSBs. These provide insights for families to tailor strategies that ensure business continuity across generations. This study is situated in the rich and diverse context of Malaysia, offering a distinctive and valuable lens through which to examine the phenomena under investigation
TBMSCCN: Two Branch Multi Scale Convolutional Correlation Network for Steady State Visual Evoked Potential Classification
Full text linkIn recent years, artificial neural networks have been effectively used to improve the target recognition performance of steady-state visual evoked potential (SSVEP) based Brain-Computer interfaces (BCIs). However, these models require the collection of a large number of calibration trials from users, which typically results in a poor user experience. When fewer calibration trials are acquired this leads to insufficient training of model parameters and weak recognition performance. To tackle these issues, this study proposes a two-branch multi- scale convolutional correlation network (TBMSCCN) in which a correlation network framework is introduced to reduce the model training parameters and prior knowledge of the SSVEP is used to enhance the model representation ability and convergence. First, a multi-scale temporal convolution module is designed to learn local temporal dependencies in a parallel two- branch feature extraction module. Next, a contrastive loss function is constructed in the latent feature space, which can guide the model to learn the intra-class consistent features while speeding up model convergence. Finally, a group convolution module is used as a decision layer to reduce the network parameters, while learning distinguishability features between targets and non-targets. Our offline tests on two public datasets show that proposed TBMSCCN method outperforms TRCA, eTRCA, DNN, Conv-CA and Bi-SiamCA in individual calibration scenarios, which can achieve an average information transform rates (ITRs) of 378.03 ± 139.18 bit/min and 198.92 ± 111.27 bit/min on the “Benchmark” dataset and the “Beta” dataset respectively. Additionally, proposed TBMSCCN method outperform FBCCA, ttCCA, EEGNet, and TST-CFSR in calibration-free scenarios. Furthermore, an online Chinese spelling experiment confirmed the real-world effectiveness of the proposed method. The proposed model has the characteristics of low parameter and strong robustness, which can facilitate the practical engineering application of SSVEP-Based-BCI system. The code is available at https://github.com/xinjieHe123/TBMSCCN
The changing meaning of left-right in UK politics
Full text linkAfter a turbulent decade of politics, dominated by the UK’s referendum on and exit from the EU, how do British voters think about the left-right space of political competition? How do they place themselves on a left-right self-placement scale, and how does this relate to multiple dimensions of ideological values? Did the EU referendum create a new realignment or dealignment within the electorate, or did it simply reflect already existing divisions? The three papers in this thesis use an exploration of measures of ideology over ten years in British politics to explore these questions. Increasingly, as highlighted by the EU referendum, British politics has been dominated by issues on the cultural, rather than economic, dimension of political conflict. This thesis explores the way the mass public has increasingly incorporated their cultural values into their own left-right self-placement. The first paper finds that economic values have become less predictive of left-right self-placement over time as cultural values have become more predictive of left-right self-placement, particularly for those on the right. The second paper finds that the EU referendum crystallised pre-existing ideological divisions within the Labour coalition, while it seemed to create new ideological divisions within the Conservative coalition. In my third paper, an original survey experiment finds that priming respondents on the cultural dimension shifts their left-right self-placement towards their cultural values. Alternatively, it finds no effect of priming on the economic dimension. These papers demonstrate a shift in British politics in the last decade, where cultural issues have become more central to how voters define their left-right self-placement. This has disrupted the coalitions of the two major parties and provides the grounds for a realignment in British politics, where the cultural dimension will exist alongside or even replace the economic dimension
Chilling Effect and Fake News Laws: Lessons from East and Southeast Asia
No full textSo-called “fake news laws” refer to legislation that criminalises or restricts the dissemination of false or misleading information likely to cause public harm, particularly online. While often justified as necessary to combat disinformation, such laws risk enabling governments to dominate public discourse and suppress dissent. Although widely criticised for their chilling effect on freedom of expression, there is no consistent framework for assessing this impact across legal systems, especially beyond the Western context.
This study introduces the Chilling Effect Ranking (CER), a structured analytical tool grounded in legal scholarship and international human rights standards. Applying CER to seven East and Southeast Asian jurisdictions — China, Hong Kong, Taiwan, Singapore, Malaysia, Japan and South Korea — the paper identifies significant variation in the severity of chilling effects, ranging from high (e.g. Singapore, China) to moderate (e.g. Taiwan, Japan). The findings suggest that these effects stem not from the mere existence of such laws, but from flaws in their legal design. The CER offers practical guidance for policymakers aiming to regulate harmful content without eroding fundamental rights
Hearing attitudes: tone of voice and its effects on listeners’ wellbeing and disclosure
Full text linkThis thesis investigates how speakers’ vocal expressions shape listeners’ affective and behavioural responses across interpersonal, workplace, and cross-cultural contexts. Specifically, it addresses three key research questions. First, how might a speaker’s interested-sounding voice elicit listeners’ disclosure and wellbeing differently than an uninterested-sounding voice, and how do these outcomes vary across cultures? (Chapter 2). Second, do differing voice patterns influence work commitment, state of wellbeing, and flourishing among listeners? (Chapter 3). Third, what psychological impacts, disclosure responses, and affective states arise when listeners are exposed to varying voice patterns across real-life contexts? (Chapter 4). The overarching aim of this thesis is to examine how the nuances of vocal tone (beyond the semantic language) affect relational dynamics, emotional states, and behavioural outcomes. Employing both experimental and cross-cultural methodologies, the studies provide empirical evidence that vocal tone not only communicates affect but also carries the power to shape disclosure, wellbeing, and commitment in diverse settings
An Improved Aggregation-Based Signcryption for Secure Drone to Ground Station Communication System
Full text linkSecure and efficient communication in drone-assisted networks is critical for maintaining the integrity
of cyber-physical systems. This paper presents a rigorous cryptographic analysis of an existing
aggregation-based signcryption scheme, revealing key vulnerabilities, including susceptibility to
forgery, impersonation attacks, and inconsistencies in key generation and verification processes. To
overcome these limitations, we propose a novel aggregation-based signcryption framework built upon
hyperelliptic curve cryptography (HECC), offering enhanced security and lightweight computation.
The proposed scheme is formally proven to satisfy fundamental cryptographic properties, including
confidentiality, authentication, integrity, unforgeability, and impersonation resistance under the
hardness assumption of the hyperelliptic curve discrete logarithm problem (HECDLP). Performance
evaluation demonstrates that our approach achieves up to 36% reduction in computational cost and
12% lower communication overhead compared to the schemes of Verma et al. [1], Aithekar et al. [2],
and Ali et al. [3]. These results confirm the practical applicability of our design for secure and efficient
drone-to-ground station communication in resource-constrained environments
Four-Year Longitudinal Associations Between Effort in Physical Education Classes and Fitness Outcomes in UK Adolescents
Full text linkBackground: Student engagement and effort in physical education (PE) can influence long-term physical fitness development. This study examined whether self-reported effort in PE (ePE) predicts changes in physical fitness among English secondary school students. Methods: A 4-year longitudinal study involved 1422 adolescents from 9 public schools in the East of England. Assessments took place at years 7, 9, and 11 (year 7 = 12 [0.5] y), measuring aerobic fitness, muscular strength, and muscular power. ePE was self-reported using the Physical Activity Questionnaire for Adolescents. Latent growth curve models examined changes in fitness over time, and whether these associations were modified by sex, body mass index (BMI), or socioeconomic status (via Index of Multiple Deprivation). Results: Girls had lower baseline fitness and smaller gains over the 4-year period than boys across aerobic fitness, muscular power, and muscular strength. Higher baseline BMI and living in a disadvantaged area were associated with lower initial fitness, and changes in BMI influenced longitudinal changes in fitness. Baseline ePE positively predicted all baseline fitness measures, with aerobic fitness showing the strongest association. Change in ePE over time was the strongest predictor of improvements across all fitness components. Conclusion: Effort in PE classes supports long-term fitness development. Interventions that encourage students to be active and engaged in PE may benefit all adolescents, especially girls and those with higher BMI or from disadvantaged areas. These findings highlight the value of promoting effortful participation in PE to enhance adolescent health and physical fitness
OTFS-based Integrated Positioning and Communication Systems with Low-Resolution ADCs
Full text linkThis paper proposes a two-phase orthogonal time–frequency space (OTFS)-based integrated positioning and communication (IPAC) framework under realistic low-resolution analog-to-digital converters (ADCs). In the uplink phase, the positioning signal is used to estimate channel parameters, which are subsequently used to determine the user’s position. The spatial smoothing-multiple signal classification algorithm is introduced to estimate the angle-of-arrival, whereas an iterative interference cancellation scheme is conceived for the remaining parameters’ estimation. The corresponding Cramer–Rao lower bounds of channel parameters and user position are also derived. During the downlink communication phase, the estimated parameters are exploited to improve beamforming at the base station. Simulation results evaluate the impact of ADC quantizer resolutions. Specifically, it is shown that enhanced downlink bit error rate performance can be achieved with improved uplink positioning, while the use of low-resolution ADCs induces noticeable performance degradation in the OTFS-IPAC system
Increased benthic biodiversity and food web recovery after decommissioning of oil and gas infrastructure
Full text linkThere is a global increase in the decommissioning of offshore oil and gas (O&G) infrastructure at the end of its operating lifetime. However, there is strikingly limited empirical evidence for the environmental and ecological impacts of decommissioning. Here, we employed a meta-analytical approach on an industry benthic monitoring database to investigate the benthic biodiversity and food web properties of structures sampled in the short term ( 5 yr; scenario 3) after decommissioning. We found reduced species richness and simplified food webs in scenario 1, followed by the first signs of recovery in scenario 2, with a slightly higher proportion of intermediate species and density of food web connections. Food webs recovered further in scenario 3, with a much greater density of interactions, but also more links and longer food chains, while a reduction in generalism and connectance indicated an increased prevalence of specialist species. Our findings demonstrate disturbance risks associated with the decommissioning process in the short term, but a positive recovery trajectory over longer timescales. We highlight the importance of industry collecting more extensive and long-term data at multiple time points and covering different decommissioning types, establishing a standardized data workflow for integrating with available monitoring efforts, and improving stakeholder participation and data accessibility to support an environmentally sound decommissioning process
Universal Costas Matrices: Towards a General Framework for Costas Array Construction
Full text linkCostas arrays are a special type of permutation matrices with ideal autocorrelation and low cross-correlation properties, making them valuable for radar, wireless communication, and integrated sensing and communication applications. This paper presents a novel unified framework for analyzing and discovering new Costas arrays. We introduce Universal Costas Matrices (UCMs) and Universal Costas Frequency Matrices (UCFMs) and investigate their structural characteristics. A framework integrating UCMs and UCFMs is proposed to pave the way for future artificial intelligence-assisted Costas array discovery. Leveraging the structural properties of UCMs and UCFMs, a reconstruction-based search method is developed to generate UCMs from UCFMs. Numerical results demonstrate that the proposed approach significantly accelerates the search process and enhances structural insight into Costas array generation