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Genuine, fake, or does it matter? Exploring engagement behavior driven by self-presentation
Get PDFCustomer engagement research assumes engagement is underpinned by pre-existing purchase or usage relationships and genuine cognitive or emotional connections with a brand. However, social media research reveals extensive activity motivated by self-presentation, resulting in content that lacks veracity. This paper explores self-presentation-driven engagement behaviors on social media and the brand relationships that drive them. A qualitative study employing semi-structured interviews with 30 Facebook users was conducted, revealing three types of engagement behaviors for self-presentation (EBSP) — “staged,” “fanciful,” and “faked” behaviors — and identifying their underlying brand relationships and consumer motivations that deviate from existing assumptions in engagement research. This study contributes by (1) introducing new types of engagement behaviors informed by self-presentation theory; (2) challenging assumptions about the brand relationships that support customer engagement; (3) reframing how engagement should be conceptualized and studied; and (4) revealing how engagement behaviors reflect differing levels of congruity between the self and brand
A mixed-methods investigation of coping, adaptation and health-related quality of life in individuals experiencing endometriosis
No full textObjective: The current mixed-methods study aimed to investigate how individuals experiencing endometriosis coped and adapted to their condition, and the extent to which coping predicted health-related quality of life (HRQoL) over time. Methods and Measures: We adopted a sequential, mixed-methods design incorporating a two-wave longitudinal survey and semi-structured interviews. In total, 408 participants diagnosed with endometriosis completed the enrolment survey, measuring demographics, clinical factors, and coping with 283 completing the follow-up survey assessing HRQoL a year later. Data was analysed through hierarchical regression analysis. Additionally, 30 semi-structured interviews were conducted and analysed using reflexive thematic analysis. Results: Quantitative data revealed that avoidant coping strategies and endometriosis-related information-seeking predicted reduced HRQoL, while trust in medical care was protective. Three themes were constructed from the qualitative data: disconnection from the body; balancing boundaries and self-care; and empowered adaptation. Integration of the datasets emphasised the importance of coping for HRQoL and wellbeing, revealing avoidance and positive adaptation as prominently employed coping strategies. Conclusion: The results position coping as an important therapeutic target in endometriosis care, particularly through fostering empowerment and adaptation to support HRQoL
Synapse types are spatially associated with regional hemodynamics in the mouse brain
Get PDFSynapses are the connections that transform neurons from simple electrically charged cells into complex circuits that support perception, cognition and action. Recent advances in single-punctum synapse mapping in mice make studying synapse diversity and differential expression possible. How do diverse synapses relate to the spatial patterning of whole-brain dynamics? Here we map the spatial distribution of multiple synapse types to >6 000 time-series features from fMRI recordings in awake mice to understand the comprehensive dynamical phenotype of multiple synapse types. We find that specific synapse types are associated with specific features of haemodynamics, including high-amplitude events and signal stationarity. These variations in synapse types and dynamics are associated with the structural and functional network embedding of brain regions. Finally, using two additional fMRI datasets in anaesthetized mice, we show that synaptic protein lifetime reflects differential synaptic engagement across behavioural states. Collectively, this work suggests that the spatial organization of microscale synapse types may shape whole-brain dynamics
The relationship between socially aversive personality of project managers and project performance : Evidence from the UAE
Get PDFWe study the relationship between socially aversive personality of project managers that influence behaviour, and project performance. Data from 409 project managers in the United Arab Emirates were collected using a 36-factor, workplace-focused dark personality questionnaire adapted from existing validated scales. Analysis was via Structural Equation Modelling (SPSS AMOS 29). Findings suggest that project managers: (i) exhibited higher Narcissism levels than Psychopathy or Machiavellianism; (ii) showed no significant variation in dark trait subscales by project characteristics; and (iii) display positively correlated dark trait subscales. Results also indicate: (iv) higher levels of each dark trait corresponding with a relationship to poorer project performance; and (v) Psychopathy's independent effect not being statistically significant. Given their negative relationship with project outcomes, organisations should prioritize identifying and managing these traits. Given the paucity of studies relating to this research, our study was exploratory in nature. Thus, this study serves as a primer on project-focused dark personality research and offers a novel perspective on the antecedents of project performance
Development of a high-sensitivity electrochemical immunoassay using a fully 3D-printed electrocatalytic microelectrode probe platform
No full textElectrochemical biosensors are a promising route to point-of-care diagnostics, yet their translation is hindered by the need for electrode surface functionalization, which introduces variability, increases cost and production complexity, and limits scalability and stability. Additive manufacturing using conductive filaments for rapid fabrication of three-dimensional (3D) electrodes overcomes these limitations. This study evaluates composite filaments comprising polylactic acid (PLA), carbon black (CB), and multiwalled carbon nanotubes (MWCNTs) for fused filament fabrication (FFF) of electrochemical electrodes for indirect detection via TMB+ measurement. Both the filament composition and electrode size were directly compared to determine the most suitable electrode architecture for sensitive measurements in complex samples. As a key novelty, the electrode diameter was reduced from 1 mm to the microscale to investigate the influence of electrode size on electron transfer efficiency. To improve measurement consistency and throughput, a 3D-printed assay accessory (“The Consistent Dipper”) was developed to guide electrode immersion and reduce movement during amperometric measurements. PLA/MWCNT microelectrodes exhibited increased current density and reduced background noise compared to carbon black filament electrodes. The MWCNT microelectrodes were subsequently applied to a cardiac troponin I (cTnI) electrochemical immunoassay and in undiluted human serum, a cTnI detection limit of 7.4 pg mL–1 was achieved, representing an approximately 19-fold improvement compared to PLA/MWCNT macroelectrodes (140 pg mL–1). Following optimization to reduce incubation times, a clinically relevant detection limit of 85 pg mL–1 was obtained within a total assay time of 1 h. By combining enhanced electrochemical performance with low-cost, flexible FFF-printed microelectrodes, this platform provides a scalable route to rapid immunodiagnostics. This study represents the first application of microscale 3D-printed PLA/MWCNT electrodes for clinical biomarker detection using a readily manufacturable sensor system
Exploring Unwarranted Disparities in Sentencing in Scotland
Get PDFThe report documents research commissioned to examine unwarranted sentencing disparities and how they can be reduced. It highlights the need to develop new sources of in-depth and meaningful data on sentencing patterns. The authors found that high quality data is essential to : the promotion of consistency in sentencing; the informed development of sentencing policy; and efforts to inform public knowledge and awareness of (and so confidence in) sentencing and the judiciary
Control design for wind-diesel hybrid power systems retrofitted with fuel cells
Get PDFInterest in isolated electrical systems powered by renewable energy has driven the development of alternatives to traditional Wind–Diesel Systems (WDS) due to their unwanted emissions and regulatory constraints. In this context, clean and efficient hybrid architectures are needed to comply with regulations and ensure stable operation under variations in user load and wind generation. This paper proposes an integrated isolated hybrid system consisting of a fuel cell replacing the Diesel Generator (DG). To fulfil the role of the synchronous generator in the diesel-group, the fuel cell operates under a Grid-Forming (GFM) control scheme, acting as a virtual synchronous machine that establishes the system’s voltage and frequency. The main aim of the hybrid system is for the wind turbine to supply most of the active power to the loads, thereby minimising hydrogen consumption. A key challenge in these systems is maintaining power balance, particularly preventing reverse flows in the fuel cell system, which has less margin than the diesel generator. In this paper, a Dump Load (DL) quickly dissipates excess power and prevents reverse power conditions. Overall, the proposed system eliminates the need for diesel generation, thereby eliminating emissions while maintaining operational stability. Simulation results demonstrate the correct functioning of the system in the presence of significant variations in load and wind power generation
Temporal fact conflicts in LLMs : reproducibility insights from unifying DYNAMICQA and MULAN
Get PDFLarge Language Models (LLMs) often struggle with temporal fact conflicts due to outdated or evolving information in their training data. Two recent studies with accompanying datasets report opposite conclusions on whether external context can effectively resolve such conflicts. DYNAMICQA evaluates how effective external context is in shifting the model's output distribution, finding that temporal facts are more resistant to change. In contrast, MULAN examines how often external context changes memorised facts, concluding that temporal facts are easier to update. In this reproducibility paper, we first reproduce experiments from both benchmarks. We then reproduce the experiments of each study on the dataset of the other to investigate the source of their disagreement. To enable direct comparison of findings, we standardise both datasets to align with the evaluation settings of each study. Importantly, using an LLM, we synthetically generate realistic natural language contexts to replace MULAN's programmatically constructed statements when reproducing the findings of DYNAMICQA. Our analysis reveals strong dataset dependence: MULAN's findings generalise under both methodological frameworks, whereas applying MULAN's evaluation to DYNAMICQA yields mixed outcomes. Finally, while the original studies only considered 7B LLMs, we reproduce these experiments across LLMs of varying sizes, revealing how model size influences the encoding and updating of temporal facts. Our results highlight how dataset design, evaluation metrics, and model size shape LLM behaviour in the presence of temporal knowledge conflicts
The application of omics technologies in Type II diabetes mellitus research
Get PDFDiabetes mellitus represents a spectrum of chronic metabolic disorders characterized by elevated blood glucose levels (hyperglycemia), largely due to insulin deficiency or resistance. Type 2 diabetes mellitus (T2DM) is the most prevalent form, accounting for over 90% of diabetes cases globally. Its rising prevalence is a global concern, with projections indicating 783 million cases by 2045. T2DM leads to severe complications, including macrovascular diseases like cardiovascular events and microvascular issues such as retinopathy and neuropathy. Despite extensive research, the molecular mechanisms underlying T2DM are not fully understood. However, advancements in omics technologies, including genomics, proteomics, and metabolomics, have revolutionized diabetes research, notably in the following areas: ▪ The advent of single-cell sequencing has revealed cellular heterogeneity and dynamic changes during T2DM progression, paving the way for precision medicine approaches in diabetes research. ▪ Liquid chromatography-mass spectrometry (LC-MS)-based proteomics and metabolomics approaches have transformed T2DM research by enabling the discovery of early detection biomarkers, providing insights into key disease mechanisms and metabolic pathways, and facilitating the identification of novel therapeutic targets. Despite challenges, integrating multi-omics data holds promise for unravelling the complex molecular networks involved in T2DM. This review explores recent advancements in omics research, its impact on T2DM, and future directions in the field
A hybrid floating wind-wave energy platform for minimum power baseload
No full textWe develop a novel hybrid wind-wave energy platform for applications that require a minimum power baseload for continuous operation. The hybrid platform consists of three very large pontoons connected with mechanical hinges. The downstream pontoon carries a 5 MW wind turbine on deck. Wave energy is extracted trough hinge motion. By computing numerically a power matrix for wave energy conversion, and assuming mean power production for the wind turbine, we evaluate the performance of the hybrid platform. Rather than assessing performance in terms of power variability, performance is gauged by determining periods of time when the hybrid platform meets a minimum power threshold, in periods of time of absent wind power. The platform is assessed in three locations with different wind-wave correlation characteristics: One off the coast of Spain, one on the West and one on the East coast of Scotland. It is found that the platform has better performance in locations with high wave power density and low to intermediate wind-wave correlation indices. The hybrid concept, besides being modular and scalable, can meet the requirements of recently considered steady state applications to be deployed offshore. For example, hydrogen electrolysers, which require a minimum power supply for lasting operation
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