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#Influenced To Care: Comparing Human And Virtual Influencers In Promoting Eco-Friendly Fashion
No full textIn the era of digital media and rapid advancements in artificial intelligence, a new type of influencer has emerged as a key player in shaping consumer behavior: the virtual or AI influencer. Over the past few years, these influencers have gained significant popularity, prompting major international brands with notable success. As consumer demand for sustainability and eco-friendly products grows, and as brands seek effective channels and message sources to communicate these values, the intersection of virtual influencers and sustainable messaging has created an intriguing research gap, particularly in the fashion industry.
Fashion brands, striving to overcome skepticism and accusations of greenwashing around their eco-labeled products, are continually searching for credible channels and message sources. Influencers, with their active and engaged follower bases, have long been a valuable asset for these brands. This study seeks to explore the effectiveness of human versus virtual influencers in promoting sustainable fashion, examining which type of influencer yields better results.
The research model investigates the role of influencer-message congruence in influencing consumer engagement and purchase intentions, as well as whether the influencer’s credibility—specifically trustworthiness and expertise—serves as a mediating factor. To address these research questions, the study employs a 2x2 experimental design, manipulating Influencer Type (Human vs. Virtual) and Influencer-Message Congruence (Congruent vs. Incongruent), and targets Generation Z consumers. Data was collected through an online survey, with 311 valid responses, and analyzed using PLS-SEM.
The findings reveal significant differences between the two types of influencers in driving post-engagement, with marginal evidence for purchase intentions, depending on congruence. Trustworthiness mediates the relationship between influencer type and consumer responses, while expertise does not significantly mediate purchase intentions. However, both dimensions of source credibility mediate the relationship between influencer type and post-engagement. Additionally, message congruence moderates the relationship between influencer type and source credibility
Climate Change Policies and Good Governance in Egypt
Get PDFEgypt recognizes the impacts of climate change and is particularly vulnerable because of its high-density population, economic burden and geographical location. In response, Egypt established National Climate Change Council in 2016. In 2022, the council issued “National Climate Change Strategy 2050” to integrate and align the efforts of government bodies to adapt and mitigate climate change risks. One of the strategic goals of “National Climate Change Strategy 2050” is to enhance climate governance in Egypt as a critical tool. This study attempts to evaluate climate change policies in the context of good governance by using a tool developed by World Bank named Worldwide Governance Indicators (WGI). The study follows qualitative descriptive approach and employs mixed methods, including semi-structured interviews, surveys, and Qualitative Comparative Analysis (QCA). Total of 42 semi-structured interviews include 15 interviews with climate change experts, 14 with teachers, and 14 with parents. These methods are used to evaluate the extent to which good governance principles are reflected in climate change policies. The survey explores the general knowledge about climate change among higher education to assess awareness levels. Climate change education in primary schools is examined by reviewing the curriculum of primary schools from years 1 to 5 and interviewing teachers and parents. Principles of good governance in climate change policies are analyzed from data collected from interviews with 15 experts in the climate change filed. This analysis is conducted through Fuzzy Set Qualitative Comparative (FSQCA) software, applying WGI criteria as independent variables, with principles of good governance as an outcome. The study finds that while Egypt is making different efforts to align with principles of good governance, there is room for improvement at the coordination and awareness levels.
KEYWORDS: Climate governance, WGI, Climate change policies, FSQCA
Detecting Electrical Submersible Pump (ESP) Failures and Estimating Run Life Using Artificial Neural Networks
Get PDFElectric Submersible Pumps (ESPs) are one of the important artificial lift methods for sustaining production in mature and high-water-cut wells; but may suffer frequent failures due to mechanical, electrical, hydraulic, chemical, and operational failures. These failures can yield substantial deferred production and intervention costs. Plenty of ESP installations are fitted with downhole sensors. Yet, it is observed that the current industry practice underutilizes the wealth of available sensor and operational data and lacks standardized, explainable failure-type identification and classification.
In this thesis, a comprehensive Machine Learning (ML) and Deep Learning (DL) framework was introduced for ESPs that simultaneously estimates remaining useful life (RUL) while predicting and classifying failure types. The RUL prediction module achieves high accuracy (R² \u3e 0.96; MAE \u3c 10 days) through supervised algorithms specifically designed for the ESPs\u27 dataset dynamics. Concurrently, the failure classification module identifies ten distinct failure types with F1 scores exceeding 0.95, utilizing a suite of complementary algorithms. The datasets were cleaned and preprocessed to address missing values, inconsistencies, and other data quality issues. Various strategies were applied for splitting the data into training, validation, and test sets. Model tuning included parameter adjustment and techniques such as SMOTE-Tomek resampling to address class imbalance and to prevent data leakage. Additionally, a novel two-step Integrated Failure Modes and Root Cause (IFMRC) framework is introduced: it first classifies observable component-level failure modes, then attributes latent root causes—including design deficiencies, operational misalignment, and equipment degradation—thereby significantly improving diagnostic granularity and system interpretability.
Validation on a dataset of over 4,000 ESP installations from Egypt’s Western Desert demonstrates state-of-the-art predictive fidelity under time-aware, cluster-specific cross-validation. Three field case studies validate the model’s performance; multiclass failure prediction in one of the wells, where the model identified recurrent failures; RUL forecasting in another well achieving a $704,000 saving in predicting failure 12 days before it occurs; and IFMRC diagnostics in another specific well case enabled enhanced root cause identification. This work integrates statistical analysis, failure mechanics, and field operations to advance predictive modeling. The resulting framework establishes a scalable methodology—empirically validated through field applications—that extends equipment lifespan and reduces costly interventions in data-rich oilfield environments
Multilateral Organizations and Health Emergency Management During Crisis: The Case Study of The World Health Organization During Covid-19 Pandemic
Get PDFMultilateral organizations, such as the World Health Organization (WHO), play a key role in managing health emergencies during crises. During the COVID-19 pandemic, WHO achieved significant progress by supporting countries with technical assistance, guidelines, and essential resources. As well as providing technical guidance, sharing information, and coordinating among member states. This experience highlighted the importance of WHO in tackling global public health problems and showed how multilateral collaboration can help address complex challenges. Moreover, risk and crisis communication proved to be a critical part of WHO’s response, ensuring that clear and timely information reached the public and stakeholders. Despite these efforts, multilateral organizations faced several challenges in their emergency response during COVID-19. These included issues related to financial constraints, management complexities, political challenges, and concerns about credibility and trust. This research aims to explore WHO’s crisis management during the COVID-19 pandemic, identify areas for improvement, and develop strategies to enhance credibility and communication of the organization with funding challenges and social media driven dynamics. A qualitative research study is conducted using a case study approach focused on WHO’s response during the pandemic during the period from 2020 to 2024. The research findings revealed both strengths and weaknesses in WHO’s crisis management and emergency response. Emphasizing the need for a clear response strategy and effective communication, while also recognizing the internal and external challenges WHO is facing. Providing lessons from the pandemic to highlight areas that require improvement for robust emergency management and enhanced future emergency responses
Architecture for the poor -- Hassan Fathy
No full textThis presentation discusses the work of Hassan Fathy, the Egyptian Architect, with a particular focus on his Architecture for the Poor
The impact of family governance mechanisms on conflict in Moroccan family businesses
No full textPurpose: This study explores the impact of family governance mechanisms on conflicts among family members in Moroccan family businesses. It aims to identify the main sources of intra-family conflict and assess how governance practices contribute to their mitigation.
Design/methodology/approach: The research adopts a qualitative, exploratory approach based on semi-structured interviews conducted with leaders of ten Moroccan family businesses. This method allowed for an in- depth understanding of both conflict dynamics and governance practices specific to the Moroccan cultural and entrepreneurial context.
Findings: The study reveals that key sources of conflict include divergence of interests, role conflict, successor incompetence, shared management responsibilities, and gender-based discrimination. While literature highlights formal mechanisms such as family councils and constitutions, the Moroccan context is marked by a preference for informal governance practices—such as unwritten family values, informal task division, and emotional value preservation—which are perceived as more adaptable and culturally acceptable. These practices play a significant role in reducing family tension and supporting generational transition.
Originality/Research limitations/implications: This research enriches the scarce empirical literature on family conflict and governance in emerging economies, particularly in North Africa. A major limitation is the sample size and the qualitative nature of the study, which restricts generalization. Nevertheless, the study offers a grounded basis for future quantitative validation.
Practical implications: Business families can benefit from understanding how culturally adapted governance practices—such as fostering shared values, informal communication, and role clarity—can reduce destructive conflict and strengthen business sustainability.
Social implications: By promoting conflict mitigation strategies, this study supports the resilience and continuity of family firms, which are central to Morocco’s economic and social fabric, particularly in terms of employment and long-term value creatio
The Legal Framework of Foster Care in Egypt: A Gender Analysis of Alternative Families and Patrilineal Structures
Get PDFThe thesis explores women’s legal representation and agency over their non-biological children, and how the foster care system in Egypt either reinforces or deconstructs existing gender roles. Hence from a sociological perspective, it accounts for foster and alternative care laws in Egypt and the amendments thereof, to examine social relationships against the backdrop of more conventional, biological families, and kinship relations. In simple terms, studying foster and alternative care laws in Egypt is crucial to grasp how non-biological families are shaped in comparison to the more conventional bonds within biological families and traditional kinship relations, while accounting for the Christian religious minority. This examination can shed light on how these legal frameworks influence the dynamics of support, caregiving, and emotional ties within Egyptian society, offering valuable insights into how the subject is produced and the complex interplay between legal structures and social relationships, with gender, law, and religion being at the core of the analysis
Incorporating Sustainability in Facility Layout Planning Algorithms and Assessing Hybridization Techniques on an Egyptian Case Study
No full textDue to the growing consequences faced as a result of global warming and climate change; humanity has come together to take an inclusive stance to combat this serious phenomena and work towards a more sustainable future. Large amounts of carbon dioxide emissions are a major contributor to global warming, and a vast proportion of this emission come from industrial and commercial facilities. Hence, if industrial facilities are built with a larger focus on carbon footprint, it will yield a significant reduction in global emissions throughout the lifetime of the facility and will constitute a huge milestone in the journey to Net Zero. This research focuses on advancing facility layout planning (FLP) methodologies through the integration of sustainability metrics and the combination of different layout improvement techniques. Using an industrial adhesives facility in Cairo as a case study, the study evaluates the effectiveness of ALDEP and CRAFT algorithms and their combination in achieving improved layouts. Key metrics include reductions in material handling (MH) costs, carbon dioxide emissions, and adjacency-based scoring (ABS) improvements. The study incorporates a quantitative carbon emission penalty factor to align cost efficiency with environmental sustainability, resulting in 27.3% annual cost saving in material handling costs, and 41% annual cost reduction in material handling costs factoring in the sustainability penalty. As shown by the mentioned cost reductions; replacing traditional diesel-powered material handling equipment (MHE) with electric alternatives, the improved facility layout achieved significant reductions in operational costs and environmental impact. The analysis highlights that ALDEP trial 5 provided the most efficient layout, with increased production rates, improved ABS, and significant cost and carbon emission reductions. Combination of ALDEP and CRAFT improved the performance of lower-quality layouts and the initial facility, but yielded no improvement for the best-performing ALDEP trial due to the size limitations and small scale of the facility. This study emphasizes the importance of incorporating sustainability metrics into FLP methodologies and provides a modified framework for designing cost-effective and environmentally sustainable industrial facilities
UNRWA and Palestinian Refugee-ness: Material Bureaucracy and Political Potential
No full textThis thesis investigates the ways Palestine refugees and UNRWA engaged with the material objects of humanitarianism in the context of Palestinian displacement. In particular, the focus is on UNRWA’s basic ration program and the techniques of humanitarian governance illustrated by the use of ration cards that shaped and were shaped by the refugee population. The research asks how the ration card, as both a contested site of governmental rationality and object of political meaning-making, functioned as a technique for defining the Palestine refugee identity. To answer this question, the thesis draws on literature and conceptual work rooted in critiques of humanitarianism, governmentality and material bureaucracy. The thesis begins with a history of UNRWA’s own bureaucratic regime, followed by an exploration of the ways Palestine refugees leveraged ration cards within that regime to make political claims. The research then turns to the fragility of material bureaucracy in the Palestinian humanitarian context and implications for UNRWA’s authority over the refugee population, as well as the alternative forms of documentation discussed but never actualized. The thesis culminates in considering different forms of refugee resistance to UNRWA’s humanitarian governance as embodied in the ration card regime and engages with the tension between the humanitarian depoliticization of the Palestinian refugee space and the efforts of refugees themselves to exert a measure of agency in such conditions. Looking to the present moment, findings suggest that the contemporary threat to both Palestine refugees and UNRWA itself has its roots in the dynamics that arose during the Agency’s basic ration program between 1950 and 1982
A Robust Framework for Graph Construction in Vision Graph Neural Networks
No full textIn Computer Vision, the method of representing an image has a profound effect on the performance of a model. Traditionally speaking, an image is treated as a grid of pixels and can be processed via Convolution Neural Net- works (CNN). An image can also be treated as a sequence of patches. Vision Transformers and MLP-Mixers (Multi-Layer Perceptron Mixers) are two types of models that process an image as a sequence. A more generic representation than grids and sequences would be graphs. That is why Vision Graph Neural Network (ViG) construct a graph for an image and process the image as a graph of patches. However, graph construction is based on K-Nearest Neighbors (k-NN). Using k-NN to construct a graph could lead to missing important edges while enforcing other less important edges in order to satisfy the ”k” constraint on each node’s neighborhood. To overcome this challenge, we present two graph construction methodologies. The first is called Similarity Thresholded Graph Construction (STGC), while the other is called Learnable Reparameterized Graph Construction (LRGC). In STGC, an edge is picked if it has a normalized similarity score higher than a pre-defined threshold. In addition, to fight oversmoothing, we present a decreasing threshold framework. Using STGC, we show experimentally that our model outperforms the State Of The Art graph-based models on ImageNet image classification without introducing a computational overhead. For LRGC, which does not need any hyper-parameter tuning, similarity scores are replaced by learnable attention scores and the threshold for each layer becomes learnable. We prove that LRGC achieves a similar performance to the best hyper-parameter combination of STGC on Imagenette without the need for tuning hyper-parameters