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“Where are the staff?” Where did they go? From Brexit, Covid ‘19 and Cost Hikes to HR Leaders struggling to fill the talent gaps” – Navigating uncertainties in the UK Hospitality Workforce Market
No full textMembers of the United Kingdom (UK) voted to leave the European Union (EU) in 2016, with the official exit taking place on January 31, 2020. This event, colloquially referred to as “BREXIT,” ended the UK’s 47-year membership with the EU. The decision to leave the EU divided UK society, with some seeing it as a chance for the UK to “take back control” and rebuild its status as a global superpower, while others saw it as a regressive move, severing invaluable ties with their closest geographic and political allies. The “Brexit of 2016–2020” has brought about a great change in the way in which the UK interacts with Europe and the rest of the world
International Law and the End of Child Marriage: A Case Study of Nigeria
No full textChild marriage is defined as the union between a child under the age of 18 and an adult or another child and remains a prevalent issue globally, with significant implications for the well-being of affected individuals. UNFPA-UNICEF statistics reveal that 650 million girls and women have experienced marriage as minors worldwide. In Nigeria, recent data from 2019 shows worrying figures, indicating that 44 percent of girls and women aged 20 to 24 are married before reaching 18, with 18 percent marrying before 15. Child brides face overwhelming challenges, including limited economic and educational opportunities, heightened risks of domestic violence, maternal mortality, birth complications, and sexually transmitted infections.
This thesis undertakes a wholistic and broad analysis of the legal landscape surrounding child marriage in Nigeria, with particular focus on its placement within the constitutional framework. Remarkably, the issue of child marriage is placed under the 'residual list of the Nigerian Constitution thereby placing it within the jurisdiction of the States' Houses of Assembly. Consequently, the Child Rights Act of 2003, aimed at addressing child marriage, requires individual state-level domestication, leading to inconsistencies across the federation. This poses a significant obstacle, as nine states are yet to domesticate the Act, enabling child marriage, particularly in regions governed by religion-based personal laws.
Furthermore, this research analyses Nigeria's engagement with international mechanisms, such as the African Union and the United Nations, to fulfil its obligations in fighting child marriage. Through a critical analysis, this thesis argues that Nigeria falls short of meeting the international legal standards in addressing this issue. This research also argues that Nigeria can draw lessons from the regional and international framework to achieve its goal of ending child marriage.
Adopting a dual methodological approach, the research engages with both doctrinal and non-doctrinal methods. The doctrinal method analyses written domestic and international legal frameworks, while the non-doctrinal method will be used to analyse the intersection between law and society. Using this approach, this research recognizes the multifaceted nature of law's influence and acknowledges the socio-economic, cultural, and political factors shaping legal norms and practices, and vice versa.
In its argument for the eradication of child marriage, this research advocates for constitutional review and amendment, activation and implementation of international laws and instruments on child marriage and strengthening of institutions in Nigeria to better equip them to implement and enforce laws against child marriage at the national and state levels.
Finally, the thesis concludes by offering practical recommendations to enhance Nigeria's efforts in safeguarding the rights and well-being of girls exposed to the dangers of child marriage
DeepCon: Unleashing the Power of Divide and Conquer Deep Learning for Colorectal Cancer Classification
No full textColorectal cancer (CRC) is the second leading cause of cancer-related mortality. Precise diagnosis of CRC plays a crucial role in increasing patient survival rates and formulating effective treatment strategies. Deep learning algorithms have demonstrated remarkable proficiency in the precise categorization of histopathology images. In this paper, we introduce a novel deep learning model, termed DeepCon which incorporates the divide-and-conquer principle into the classification task. DeepCon has been methodically conceived to scrutinize the influence of acquired composition on the learning process, with a specific application to the classification of histology images related to CRC. Our model harnesses pre-trained networks to extract features from both the source and target domains, employing a two-stage transfer learning approach encompassing multiple loss functions. Our transfer learning strategy exploits a learned composition of decomposed images to enhance the transferability of extracted features. The efficacy of the proposed model was assessed using a clinically valid dataset of 5000 CRC images. The experimental results reveal that DeepCon when coupled with the Xception network as the backbone model and subjected to extensive fine-tuning, achieved a remarkable accuracy rate of 98.4% and an F1 score of 98.4
WeChat Gamification: Mobile Payment Impact on word of mouth and customer loyalty
No full textPurpose
This study aims to investigate how gamification, namely, WeChat’s cultural gifting function, improves emotional involvement among three generations (Y, X and silver) in mobile payments. It draws attention to the beneficial effects of cultural components and digital intimacy on gamified mobile payment systems.
Design/methodology/approach
The data were collected from Y, X and silver generation in Dalian, China. The users were well equipped with the WeChat pay features and had experience. The PLS-SEM software was used to assess the data.
Findings
The findings show that consumer word of mouth and loyalty are positively impacted by perceived utility, fun, and enjoyment. Besides, gamification components like fun and playfulness have a favourable effect on how useful mobile payments are judged to be. It demonstrates how delighted and ecstatic users are with WeChat Hongbao. In addition, the positive moderation effect of intimacy on the hypothesised connections shows that all three generations are likely to accept gamified money features. These results provide a substantial contribution to our comprehension of gamification in the context of mobile payment services for all three generations.
Originality/value
The study is distinctive because it focuses on how China’s three generations use WeChat Pay for routine transactions. The framework confirms that the gamification elements improve user performance and encourage continued usage of mobile payment systems
Back to the future revisited: A systematic literature review of performance-related pay in the public sector
No full textPerformance-related pay (PRP) has been part of public-sector pay structures in the past four decades. Despite public administration scholars denouncing its use in the public sector, PRP is being increasingly implemented in public organizations worldwide. Notwithstanding controversy over its use in the public sector, the last decade has seen a huge surge in its adoption. In order to assess the theoretical, empirical, and scientific reasoning for this interest we analyze the existing literature in order to identify the emerging discussions in this area and to provide a systematic review that can be used as guidance for future research. The review highlights the gaps in our current knowledge of PRP in the public sector and identifies factors affecting its success that have emerged from new research over the last fourteen years. After identifying these, we propose a number of important pathways that future research might take in order for public organizations globally to design optimal PRP schemes
Image Classifier for an Online Footwear Marketplace to Distinguish between Counterfeit and Real Sneakers for Resale
No full textThe sneaker industry is continuing to expand at a fast rate and will be worth over USD 120 billion in the next few years. This is, in part due to social media and online retailers building hype around releases of limited-edition sneakers, which are usually collaborations between well-known global icons and footwear companies. These limited-edition sneakers are typically released in low quantities using an online raffle system, meaning only a few people can get their hands on them. As expected, this causes their value to skyrocket and has created an extremely lucrative resale market for sneakers. This has given rise to numerous counterfeit sneakers flooding the resale market, resulting in online platforms having to hand-verify a sneaker’s authenticity, which is an important but time-consuming procedure that slows the selling and buying process. To speed up the authentication process, Support Vector Machines and a convolutional neural network were used to classify images of fake and real sneakers and then their accuracies were compared to see which performed better. The results showed that the CNNs performed much better at this task than the SVMs with some accuracies over 95%. Therefore, a CNN is well equipped to be a sneaker authenticator and will be of great benefit to the reselling industry
A systematic literature review on meta-heuristic based feature selection techniques for text classification
No full textFeature selection (FS) is a critical step in many data science-based applications, especially in text classification, as it includes selecting relevant and important features from an original feature set. This process can improve learning accuracy, streamline learning duration, and simplify outcomes. In text classification, there are often many excessive and unrelated features that impact performance of the applied classifiers, and various techniques have been suggested to tackle this problem, categorized as traditional techniques and meta-heuristic (MH) techniques. In order to discover the optimal subset of features, FS processes require a search strategy, and MH techniques use various strategies to strike a balance between exploration and exploitation. The goal of this research article is to systematically analyze the MH techniques used for FS between 2015 and 2022, focusing on 108 primary studies from three different databases such as Scopus, Science Direct, and Google Scholar to identify the techniques used, as well as their strengths and weaknesses. The findings indicate that MH techniques are efficient and outperform traditional techniques, with the potential for further exploration of MH techniques such as Ringed Seal Search (RSS) to improve FS in several applications
Genetic landscape for majority and minority HIV-1 drug resistance mutations in antiretroviral therapy naive patients in Accra, Ghana
No full textBackground
The successful detection of drug-resistance mutations (DRMs) in HIV-1 infected patients has improved the management of HIV infection. Next-generation sequencing (NGS) to detect low-frequency mutations is predicted to be useful for efficiently testing minority drug resistance mutations, which could contribute to virological failure. This study employed Sanger sequencing and NGS to detect and compare minority and majority drug resistance mutations in HIV-1 strains in treatment-naive patients from Ghana.
Method
From a previous study, 20 antiretroviral therapy (ART)-naive participants were selected for a cross-sectional study. Sanger sequencing and NGS techniques were used to detect the majority and minority HIV drug resistance (HIVDR) mutations, respectively, in the protease (PR) and partial reverse transcriptase (RT) genes. NGS detected mutations at 1 % and 5 % frequencies and Sanger sequencing at ≥20 % frequencies. The sequences obtained from NGS and Sanger sequencing platforms were submitted to the Stanford HIV drug resistance database for subtyping, mutation identification, and interpretations.
Results
Sequences from the twenty participants where the CRF02_AG was the predominant strain (16, 80 %) were analyzed. NGS detected 25 mutations in the RT and PR genes, compared to 21 mutations by Sanger sequencing. Minority DRMs were detected at the prevalence of 55.0 % with NGS against 35 % DRMs by Sanger sequencing. One of the patients had eight different HIVDR variants, with two minority variants. These mutations were directed against PI (K20I and D30DN), NNRTI (Y181C, M23LM and V108I) and NRTI (K65R, M184I, and D67N).
Conclusion
The study affirms the usefulness of genomic sequencing for drug resistance testing in HIV. It further shows that Sanger sequencing alone may not be adequate to detect mutations and that NGS capacity should be developed and deployed in the Ghanaian clinical settings for patients living with HIV
Exploration of the Mediating Role of Self-Compassion and Mindfulness on Orthorexia Nervosa and Perfectionism
No full textOrthorexia Nervosa (ON) is characterized by an excessive preoccupation with healthy eating, accompanied by increasingly restrictive dietary practices over time. In light of the increased attention to ON, it is noteworthy that the existing body of research, specifically with regard to mindfulness and self-compassion remains constrained in scope and depth. A total of 151 participants over the age of 18 completed scales measuring Orthorexia, Self-Compassion, Mindfulness, and Perfectionism. The findings revealed that individuals exhibiting high levels of ON tended to have low levels of self-compassion and mindfulness, along with high levels of perfectionism. Furthermore, the results indicated that self-compassion and mindfulness acted as mediators in the relationship between perfectionism and orthorexia nervosa. These findings deepen our comprehension of orthorexia and underscore the role of self-compassion and mindfulness, or their absence, as mediating factors in this context. The implications of these results and potential future directions are discussed