Phenomenological Research Awards

  Words as Social Tools (WAT): A Reprise Introduction Language is more than a means of communication; it is a social tool that shapes interactions, relationships, and societies. The concept of Words as Social Tools (WAT) explores how language functions beyond its literal meaning, influencing emotions, perceptions, and behaviors. This reprise delves into the role of words in social contexts and their impact on human interactions. The Power of Words in Social Interaction Words are not just carriers of information; they are powerful instruments that can build or break relationships. From daily conversations to persuasive speeches, language facilitates cooperation, resolves conflicts, and fosters social bonds. Psychological studies suggest that words influence cognition and emotional states, demonstrating the profound impact language has on our lives. 1. Words as Emotional Catalysts Language is a key player in emotional regulation. Positive words can uplift and encourage, while negati...

  Empowering Students Through Lived Experience: Co-Designed Eating Disorders Education In recent years, there has been a growing awareness of the importance of integrating lived experiences into educational programs, particularly when addressing sensitive topics like eating disorders. Traditional educational models often rely on clinical or textbook knowledge, but emerging research highlights the value of incorporating personal narratives and co-designed learning experiences to create a deeper impact on students. The Power of Co-Designed Education Co-designed education refers to a collaborative learning approach where students, educators, and individuals with lived experience work together to develop course content. This method fosters a more engaging and empathetic learning environment. In the context of eating disorders education, this approach allows students to gain insights beyond medical definitions—understanding the emotional, psychological, and social dimensions of the cond...

  Title: Explainable Machine Learning Model for Assessing Health Status in Patients with Comorbid Coronary Heart Disease and Depression Introduction Coronary heart disease (CHD) and depression often coexist, significantly impacting patient health outcomes. Traditional diagnostic methods face challenges in effectively assessing health status in such cases. Machine learning (ML) offers a promising solution, but the need for explainability remains crucial for clinical adoption. This blog explores the development and validation of an explainable ML model to assess patient health status in those with comorbid CHD and depression. Understanding Explainable AI in Healthcare Explainable artificial intelligence (XAI) enhances transparency in ML models, helping healthcare professionals interpret predictions. Unlike black-box models, explainable ML provides insights into key risk factors, enabling better clinical decision-making. Model Development The ML model was trained using patient data, ...

  Priors for Natural Image Statistics: How They Shape Confidence in Perceptual Decisions Human perception is a marvel of evolution, constantly adapting to interpret the complex world around us. One intriguing aspect of perception is how priors —expectations based on natural image statistics—affect the confidence in our perceptual decisions. What Are Natural Image Priors? Natural image statistics refer to patterns, structures, and regularities commonly found in the visual world. For instance, smooth gradients, edges, and repetitive textures are prevalent in natural scenes. Our brain, through experience, develops a repository of these priors, which act as a framework for interpreting new sensory inputs. How Priors Influence Perceptual Decisions When we encounter visual information, our brain compares it against stored priors to infer meaning. This process is particularly significant under uncertainty, such as when images are noisy or ambiguous. Confidence Boost Through Familiarity : ...

  Exploring the Versatile Biological Activities of Thiosemicarbazones and Their Metal Complexes Thiosemicarbazones (TSCs) and their metal complexes are fascinating compounds with broad-spectrum biological activities. These small organic molecules, characterized by the thiosemicarbazone functional group (-C(=S)-NH-NH2), have gained significant attention for their diverse pharmacological applications. Key Biological Activities Anticancer Potential : TSCs exhibit potent anticancer properties by targeting specific enzymes like ribonucleotide reductase, disrupting DNA synthesis and repair, and inducing apoptosis in cancer cells. Their metal complexes, especially those with iron and copper, show enhanced cytotoxicity. Antibacterial and Antifungal Properties : The ability of TSCs to chelate essential metal ions disrupts microbial enzyme systems, making them effective against resistant bacterial and fungal strains. Antiviral Activity : TSCs have shown promise against viral diseases, includ...