132 research outputs found
Derivatives combining the fragment of pyrazinamide and 4-aminosalicylic acid as antimycobacterial compounds
Get PDFCharles University Faculty of Pharmacy in Hradec Králové Department of Pharmaceutical chemistry and Pharmaceutical analysis Author: Petr Šlechta Supervisor: doc. PharmDr. Jan Zitko, Ph.D. Consultant: MSc. Ghada Basem Bouz, Ph.D. Title of diploma thesis: Derivatives combining the fragment of pyrazinamide and 4-aminosalicylic acid as antimycobacterial compounds According to WHO, tuberculosis (TB) is the leading cause of death from a single infectious organism worldwide and the number of cases with drug resistant TB is still increasing, creating the need for new antituberculotics. Therefore, we report design, synthesis and antimicrobial evaluation of a series of hybrid compounds combining different pyrazinamide derivates and p- aminosalicylic acid as potential antituberculotic agents. The compounds were prepared by mixing different pyrazinecarboxylic acids, after activation by 1,1'-carbonyldiimidazole, with p- aminosalicylic acid in dimethylsulfoxide as a solvent. Obtained compounds were in vitro tested for their antimycobacterial activity against M. tuberculosis H37Rv, M. tuberculosis H37Ra and four other mycobacterial strains. Prepared compounds were also in vitro screened for antibacterial, antifungal, and cytotoxic (HepG2) activity. Most compounds showed antimycobacterial activity in range of..
The Arab Intellectual as a Woman: The Writings of Ghada Samman
No full textGhada Samman (b. 1942) is a prominent literary figure with an established legacy across the Arabic-speaking world. Through her widely-acclaimed writings, the Syrian author, journalist, and critic occupies a unique position in Arab intellectual circles as a woman who combines a commitment to the peoples’ causes with an innovative literary style vividly capturing the estrangement faced by the modern Arab subject. Samman has spent her life in exile, first in Beirut and eventually settling in Paris when the Lebanese Civil War (1975-1990) escalated. She has published 10 poetry books, 6 short story collections, 5 novels, and 20 collections of essays. However, despite her influential writings, Samman is relatively unknown outside of the Arabic-speaking world and a negligible portion of her corpus has been translated into English. My presentation posits the reason for this exclusion being that the Anglophone world does not know where to place Samman as she refuses the mould of “women’s writing” to which the Western academy is accustomed. Hers is the broad, interdisciplinary concern of the intellectual, writing on themes of exile, diatribes against capitalism and classism, the liberation of sexuality from prescribed norms, as well as how patriarchal hegemonies victimise both men and women. Even in the Arabic-speaking world she has pushed back against reductive labelling of her work, writing in a 1987 article: ‘My allegiance is to my freedom and my faith in a woman’s ability to write great human literature. There’s no need to call it “feminist” when its defence of women is part and parcel of its defence of all who are oppressed in Arab societies.’ My presentation will explore the life and work of Ghada Samman from the position of an Arab intellectual rather than a limited (and expected) reading of her as a woman writer exclusively concerned with “women’s issues”
From Statistical Analysis to Deep Learning
No full textThis chapter explores the shift from traditional statistical analysis to advanced deep learning in quantitative decision-making. It argues for integrating classical paradigms—such as descriptive and inferential statistics conducted in tools like SPSS—with modern computational techniques to address complex, large-scale challenges. The discussion highlights the pivotal role of big data platforms, including Hadoop and Spark, in enabling real-time analytics and distinguishes core machine learning algorithms from deep neural architectures designed for unstructured data. Interdisciplinary case studies in healthcare, finance, and engineering demonstrate the practical synergy of these approaches. By embracing multi-paradigm strategies, the chapter offers insights into building transparent, scalable, and effective decision-support systems across diverse domains. It concludes by addressing challenges of ethics and governance and by pointing to future directions such as explainable AI and federated learning, emphasising that robust decision-making depends on a hybridised analytical framework
The influence of fear of failure on academic motivation and engagement.
No full textThe influence of fear of failure on academic motivation and engagement
Cluster Analysis
No full textCluster analysis is an unsupervised learning method that organises related data points into groups based on shared attributes. This technique identifies underlying patterns in datasets without prior labelling, focusing on maximising internal similarity among items within a cluster while maintaining clear distinctions between different clusters. It is used across various disciplines to uncover hidden structures and inform decision-making processes. The methodology employs algorithms to evaluate similarities and differences, ensuring that elements within a cluster exhibit greater similarity than those in other clusters
Structural Equation Modelling
No full textStructure Equation Modelling (SEM) is a comprehensive statistical technique used for testing and estimating causal relationships (Kline, 2023). It is a multivariate approach that combines features of factor analysis and multiple regression, allowing for the examination of complex relationships among observed and latent variables. SEM is particularly useful when dealing with multiple variables and their interdependencies, making it a powerful tool in social sciences, psychology, marketing, and other fields. It enables researchers to test hypotheses about the relationships between observed variables and their underlying constructs (latent variables), as well as the direct and indirect effects among these constructs (Kline, 2023). SEM is a versatile and robust statistical method that allows researchers to explore and test complex relationships among variables, providing a comprehensive understanding of the underlying structure of a set of observed and unobserved variables (Kline, 2023)
The modulatory role of extrinsic motivation in the relationship between fear of failure and student engagement
Get PDFTeachers often employ various techniques to motivate and engage students. They may choose to use positive fear appeals as a motivational tactic to stimulate fear that will result in students making greater efforts to avoid failure or they may employ extrinsic incentives to engage students. This study examined the modulatory role of extrinsic motivation, as a differentiated construct, in the relationship between fear of failure and student engagement. Data were collected using self-reported instruments and analysed using moderation and mediation analyses. Extending the motivation literature, this study, sheds new light on the positivemodulatory role of extrinsic motivation regulations in the relationship between fear of failure and student engagement. Contributions to practice are implied; there is a need for educators to understand the role of self-imposed and self-endorsed behaviours in influencing engagement among students with high and low fear of failure. Comprehending the complexity of the learning environment in light of the complex nature of human behaviours is considered essential to improving teaching and learning
Teacher Retention Reimagined
No full textThis chapter addresses the pressing issue of teacher retention through a creative, solutions-oriented lens, moving beyond traditional methods proven inadequate. It presents a comprehensive framework of innovative, evidence-informed strategies to make teaching both sustainable and fulfilling. Key themes include empowering teachers as innovators through teacher-led labs, broadening horizons via sabbaticals and micro-credentials, and amplifying teacher voice through leadership pathways. The chapter also explores wellbeing initiatives such as arts integration, flexible policies, and community building practices that foster belonging. To reduce burnout, it highlights workload reducing technologies and peer support systems like mentoring and residencies. Finally, it outlines ways to sustain a culture of growth and joy through gamified professional development and risk-friendly environments. Drawing on real world examples and recent research, it offers practical solutions to inspire leaders and policymakers to reimagine teacher retention as a dynamic, future ready endeavour
Breaking Barriers:Evidence-Based Approaches to Gender Equity in Mathematics Education
No full textDespite progress in educational access, gender disparities still shape mathematics learning and achievement. This chapter analyses gender equity in mathematics education, examining systemic factors behind these disparities and offering evidence-based strategies for inclusivity. It highlights the importance of equity for individual growth and a diverse STEM workforce. The chapter critiques curriculum design and representation, exposing historical biases in textbooks and problem-solving roles, and suggests guidelines for more inclusive content. It explores classroom dynamics, revealing gendered patterns in teacher-student interactions and peer collaboration, and recommends pedagogical approaches for balanced engagement. The discussion examines the pivotal role of teacher training and bias mitigation, reviewing programmes that raise awareness of implicit biases and foster reflective practice. Assessment tools for pedagogical equity are discussed, along with interventions and policy recommendations to sustain change and encourage ongoing innovation toward equitable mathematics education
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