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Grandiose narcissism associates with higher cognitive performance under stress through more efficient attention distribution: An eye-tracking study
No full textNarcissism is a part of the Dark Triad that consists also of the traits of Machiavellianism and psychopathy. Two main types of narcissism exist: grandiose and vulnerable narcissism. Being a Dark Triad trait, narcissism is typically associated with negative outcomes. However, recent research suggests that at least the grandiose type may be linked (directly or indirectly) to positive outcomes including lower levels of psychopathology, higher school grades in adolescents, deeper and more strategic learning in university students and higher cognitive performance in experimental settings. The current pre-registered, quasi-experimental study implemented eye-tracking to assess whether grandiose narcissism indirectly predicts cognitive performance through wider distribution of attention on the Raven’s Progressive Matrices task. Fifty-four adults completed measures of the Dark Triad, self-esteem and psychopathology. Eight months to one year later, participants completed the Raven’s, while their eye-movements were monitored during high stress conditions. When controlling for previous levels of psychopathology, grandiose narcissism predicted higher Raven’s scores indirectly, through increased variability in the number of fixations across trials. These findings suggest that grandiose narcissism predicts higher cognitive performance, at least in experimental settings, and call for further research to understand the implications of this seemingly dark trait for performance across various settings
Corporate Governance Practices and Microfinance Institutional Performance in Ghana
No full textMicrofinance is one effective way of alleviating poverty by providing access to credit and financial services to the unbanked who do not have access to these services from mainstream banking institutions. The failure of microfinance institutions (MFIs) in recent times has shifted the attention to the corporate governance (CG) of MFIs. CG is a system in which MFIs are governed and controlled in achieving their double-bottom objectives of financial and social performance. Stakeholders in the microfinance literature have attributed the failures of MFIs to poor CG practices in Ghana. Thus, this study critically examines the perceptions of corporate governance practices in Ghana and the relationship between CG mechanisms on the performance of MFIs. The study is quantitative and adopts both primary and secondary data. Questionnaires were used on a sample of 122 stakeholders (managers/deputy managers, board members, accountants, internal auditors, and other senior staff) of 17 MFIs across 5 regions in Ghana. A second set of questionnaires was used to collect CG mechanisms and social performance information from the 17 managers. Financial statements for the 2019 -2020 fiscal year were used to calculate ratios as financial performance indicators. Purposive and convenient sampling techniques were used. The study employed – Panel Ordinary Least Square (OLS) regression analysis to examine the relationship between CG mechanisms and MFI performance in Ghana. Descriptive statistics were used to examine the implementation of CG principles, challenges, and factors impacting the implementation of CG in MFIs in Ghana. The study found that MFIs in Ghana largely implemented Organisation for Economic Cooperation and Development (OECD) CG principles. The study identified challenges to CG implementation as well as factors that could impact the implementation of CG in MFIs in Ghana. The study uncovered a mixed result that board size has a significant negative association with (ROA and ROE) and a significant positive association with (OCR and YoGLP) of MFIs' financial performance. Board size has a significant negative relationship with MFIs' social performance measures (breadth of outreach and female borrowers). Board composition has no significant relation with MFIs' financial or social performance in Ghana. Female director presence on MFIs board is statistically positively associated with MFIs social performance (breadth of outreach). Based on the findings, the study suggests stringent monitoring regime and training for MFIs on CG, establishment of a central database for MFIs in Ghana to facilitate CG research in MFIs, facilitation of merger of selected MFIs to make them efficient and sustainable in their operations, a quota of female board member representation in MFIs among others. Finally, the study developed a CG model to aid the review of the Bank of Ghana CG Directive 2018 and the establishment of a national CG code in Ghana to promote economic development in Ghana. The major contribution of this study is the examination of CG in MFIs in Ghana. This research contributes to closing a significant gap in the literature about corporate governance practices in MFIs in Ghana. Undoubtedly, this study not only contribute to knowledge in Ghana but also to other developing countries with similar socio-economic and cultural environment
Being a woman is 100% significant to my experiences of ADHD and autism: Exploring the gendered implications of an adulthood AuDHD diagnosis
No full textThis article provides original insight into women’s experiences of adulthood diagnoses of ADHD and autism (AuDHD). Research exploring experiences of adulthood diagnoses of these conditions is emerging. Yet, there is no research about the gendered experiences of an adulthood AuDHD diagnosis. This article addresses this gap through Interpretative Phenomenological Analysis of email interviews with 6 late-diagnosed AuDHD women revealing the complex interplay between late diagnosis, being a woman, and combined diagnoses of ADHD and autism. It underscores how gender norms and stereotypes contribute to the oversight and dismissal of women’s neurodivergence. Interpretative Phenomenological Analysis reveals the inextricability of femininity and neurotypicality, the gendered burden, discomfort, and adverse consequences of masking, along with the adverse outcomes of insufficient masking. Being an undiagnosed AuDHD woman is a confusing and traumatising experience with profound and enduring repercussions. The impact of female hormones exacerbated participants’ struggles with (peri)menopause often being a catalyst for seeking diagnosis after decades of trauma. The epistemic injustice of not knowing they were neurodivergent compounded this trauma. Diagnosis enabled participants to overcome epistemic injustice and moved them into a feminist standpoint from which they challenge gendered inequalities relating to neurodiversity. This article aims to increase understanding and representation of late-diagnosed AuDHD women’s lived experiences. The findings advocate for trauma-informed pre- and post-diagnosis support which addresses the gendered dimension of women's experiences of being missed and dismissed as neurodivergent. There needs to be better clinical and public understanding of how AuDHD presents in women to prevent epistemic injustice
Unlocking the potential: leveraging blockchain technology for agri-food supply chain performance and sustainability
No full textPurpose
Blockchain technology (BCT) has emerged as a powerful tool for enhancing transparency and trust. However, the relationship between the benefits of BCT and agri-food supply chain performance (AFSCperf) remains underexplored. Therefore, the current study investigates the influence of BCT on AFSCperf and sustainability issues.
Design/methodology/approach
Through a comprehensive literature review, various benefits of BCT are identified. Subsequently, a research framework is proposed based on data collected from questionnaire surveys and personal visits to professionals in the agri-food industry. The proposed framework is validated using partial least square structural equation modelling (PLS-SEM).
Findings
The findings reveal that BCT positively impacts AFSCperf by improving traceability, transparency, food safety and quality, immutability and trust. Additionally, BCT adoption enhances stakeholder collaboration, provides a decentralised network, improves data accessibility and yields a better return on investment, resulting in the overall improvement in AFSCperf and socio-economic sustainability.
Practical implications
This study offers valuable practical insights for practitioners and academicians, establishing empirical links between the benefits of BCT and AFSCperf and providing a deeper understanding of BCT adoption.
Originality/value
Stakeholders, managers, policymakers and technology providers can leverage these findings to optimise the benefits of BCT in enhancing AFSCperf. Moreover, it utilises rigorous theoretical and empirical approaches, drawing on a multidisciplinary perspective encompassing food operations and supply chain literature, public policy, information technology, strategy, organisational theory and sustainability
Transitions in Mid-Baroque Music: Style, Genre and Performance
No full textThis collection focusses on the stylistic and cultural interchange that characterizes the musical period of the mid-Baroque (c.1650-1710). The idea of musical transition during this period is evident in two principal ways: geographical and chronological (the two often overlap). Chapters examine geographical transition by tracing the exchange of regional and national styles, while considering chronological evolution from the perspective of music theory, performance practice, source studies or specific repertoires. Studies range across instrumental and vocal music, both sacred and secular, and encompass some of the main European traditions prevalent at the time: Italian, German, French and English. The collection features contributions by leading scholars from the UK, the United States, Australasia and Europe
Practice and community nurses' views and experiences of helping people manage risk factors for recurrent lower limb cellulitis: A qualitative interview study
No full textBackground
Cellulitis is a painful infection of the skin and underlying tissues, commonly affecting the lower leg. Approximately one-third of people experience recurrence. Nurses who work in general practice (practice nurses) and see people at home (community or district nurses) could have an important role in managing risk factors for cellulitis, such as long-term leg swelling, wound care and skin care.
Objective
To explore practice and community nurses' views and experiences of helping people to manage risk factors for recurrent lower limb cellulitis.
Methods
Semi-structured, telephone interviews with 21 practice and community nurses in England from October 2020 to March 2021. Interviews were transcribed verbatim and analysed using reflexive thematic analysis.
Results
Nurses face multiple challenges when supporting people to manage risk factors for recurrent lower limb cellulitis. Key challenges include limited time and access to resources such as Doppler equipment, and the physical and psychosocial capabilities of patients to self-manage. Nurses identified potential strategies to overcome these challenges, such as placing greater emphasis on prevention and supporting self-management by providing resources for patients and support networks (paid and unpaid carers) to reinforce knowledge post-consultation and develop skills to self-care.
Conclusions
We identified a need to develop and evaluate resources, such as support materials, for nurses to use to help patients reduce their risk of recurrent cellulitis
Nature and human well-being: The olfactory pathway
No full textThe world is undergoing massive atmospheric and ecological change, driving unprecedented challenges to human well-being. Olfaction is a key sensory system through which these impacts occur. The sense of smell influences quality of and satisfaction with life, emotion, emotion regulation, cognitive function, social interactions, dietary choices, stress, and depressive symptoms. Exposures via the olfactory pathway can also lead to (anti-)inflammatory outcomes. Increased understanding is needed regarding the ways in which odorants generated by nature (i.e., natural olfactory environments) affect human well-being. With perspectives from a range of health, social, and natural sciences, we provide an overview of this unique sensory system, four consensus statements regarding olfaction and the environment, and a conceptual framework that integrates the olfactory pathway into an understanding of the effects of natural environments on human well-being. We then discuss how this framework can contribute to better accounting of the impacts of policy and land-use decision-making on natural olfactory environments and, in turn, on planetary health
An artificial neural network model for determining stress concentration factors for fatigue design of tubular T-joint under compressive loads
No full textPurpose
The stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.
Design/methodology/approach
A mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.
Findings
Using real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.
Practical implications
Engineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.
Originality/value
Precisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming
Artificial Intelligence Based Methods for Retrofit Projects: A Review of Applications and Impacts
No full textThe Architecture, Engineering and Construction (AEC) sector faces severe sustainability and efficiency challenges. In recent years, various initiatives have demonstrated how artificial intelligence can effectively address these challenges and improve sustainability and efficiency in the sector. In the context of retrofit projects, there is a continual rising interest in the deployment of Artificial Intelligence (AI) techniques and applications, but the complex nature of such projects requires critical insight into data, processes, and applications so that value can be maximised. This study aims to review AI applications and techniques that have been used in the context of retrofit projects. A review of existing literature on the use of artificial intelligence in retrofit projects within the construction industry was carried out through a thematic analysis. The analysis revealed the potential advantages and difficulties associated with employing AI techniques in retrofit projects, and also identified the commonly utilised techniques, data sources, and processes involved. This study provides a pathway to realise the broad benefits of AI applications for retrofit projects. This study adds to the AI body of knowledge domain by synthesizing the state-of-the-art of AI applications for Retrofit and revealing future research opportunities in this field to enhance the sustainability and efficiency of the AEC sector
Multimodal dementia identification using lifestyle and brain lesions, a machine learning approach
No full textDementia diagnosis often relies on expensive and invasive neuroimaging techniques that limit access to early screening. This study proposes an innovative approach for facilitating early dementia screening by estimating diffusion tensor imaging (DTI) measures using accessible lifestyle and brain imaging factors. Conventional DTI analysis, though effective, is often hindered by high costs and limited accessibility. To address this challenge, fuzzy subtractive clustering identified 14 influential variables from the Lifestyle for Brain Health and Brain Atrophy and Lesion Index frameworks, encompassing demographics, medical conditions, lifestyle factors, and structural brain markers. A multilayer perceptron (MLP) neural network was developed using these selected variables to predict fractional anisotropy (FA), a DTI metric reflecting white matter integrity and cognitive function. The MLP model achieved promising results, with a mean squared error of 0.000 878 on the test set for FA prediction, demonstrating its potential for accurate DTI estimation without costly neuroimaging techniques. The FA values in the dataset ranged from 0 to 1, with higher values indicating greater white matter integrity. Thus, a mean squared error of 0.000 878 suggests that the model’s predictions were highly accurate compared to the observed FA values. This multifactorial approach aligns with the current understanding of dementia’s complex etiology influenced by various biological, environmental, and lifestyle factors. By integrating readily available data into a predictive model, this method enables widespread, cost-effective screening for early dementia risk assessment. The proposed accessible screening tool could facilitate timely interventions, preventive strategies, and efficient resource allocation in public health programs, ultimately improving patient outcomes and caregiver burden