8598 research outputs found
Sort by
Application of Analytical Methodologies to the Analysis of Food Flavoring Agents: Part III
Full text link
Feeding and Swallowing Disorders In Children With Autism: What Caregivers Need to Know
Full text linkThis study investigates the complex topic of feeding and swallowing disorders in children with autism, highlighting the significant challenges they pose, particularly related to sensory sensitivities and oral motor difficulties, and the persistent lack of understanding. We examine diagnostic criteria, risks, familial impacts, cultural nuances, and evidence-based intervention strategies, with a focus on practical guidance for caregivers, to equip them with resources for navigating these challenges (Schulz & Eden, 2016). Despite the prevalence of these disorders, many remain unaware of the struggles, underscoring the urgent need for targeted investigations and supportive measures. Specifically, this paper aims to provide Speech Language Pathologists with the tools to empower caregivers to better support families of autistic children facing feeding and swallowing difficulties (Gent et al., 2024)
Does Corruption Control Enhance ESG-Induced Firm Value? Insights from Machine Learning Analysis
No full textThis study adopts advanced causal machine learning (ML) techniques to investigate the impact of country-level corruption on the market valuation of firms’ environmental, social, and governance (ESG) performance. By employing double-debiased machine learning (DML) and linear regression analysis, we find that ESG performance positively influences firm value. This positive relationship is more pronounced for firms operating in countries with lower levels of corruption. The use of DML enhances effect identification and yields findings that closely align with those derived from linear regression, thereby providing robust support for the pivotal role of corruption control in enhancing ESG-induced firm value
Computational Modeling of Astrophysical Systems
No full textThis research project focuses on the computational modeling of astrophysical systems using Femap with NX Nastran. The goal was to simulate and analyze the vibrational behavior and structural deformation of celestial bodies under different material compositions and collision conditions. Materials such as iron, granite, titanium, and models for white dwarf stars were used to investigate how varying physical properties affect the systems\u27 dynamic responses. Both isotropic and anisotropic models were created to represent realistic astrophysical materials. Through static and modal analyses, the study explored how internal structure and material stiffness influence the reaction of celestial objects to applied forces and collisions. The findings provide insight into the fundamental physics governing star-like systems, offering a deeper understanding of how material properties impact deformation and vibrational modes during astrophysical events
Application of Analytical Methodologies to the Analysis of Food Flavoring Agents: Part II
Full text linkLU-167.027b, View of the Rotunda with students sitting on bench
No full texthttps://digitalcommons.longwood.edu/postcard/1031/thumbnail.jp
