The aim of this randomized controlled trial was to assess the efficacy of a cream containing ceramides and magnesium (Cer-Mg) in the treatment of mild to moderate atopic dermatitis and to compare it with hydrocortisone and a commonly used emollient (unguentum leniens; cold cream). A total of 100 patients, randomized into 2 groups, were treated for 6 weeks simultaneously (left vs. right side of the body) with either Cer-Mg and hydrocortisone (group I) or Cer-Mg and emollient (group II). The primary outcome was a reduction in severity of lesions as assessed by (local) SCORAD (SCORing Atopic Dermatitis). Levels of trans-epidermal water loss (TEWL), skin hydration, and natural moisturizing factors (NMF) were then measured. After 6 weeks, group I showed comparable significant improvement in SCORAD and TEWL, while in group II, the decrease in SCORAD and TEWL was significantly greater after Cer-Mg compared with emollient. Finally, Cer-Mg cream was more effective in improving skin hydration and maintenance of levels of NMF than hydrocortisone and emollient.
This research aims to develop and evaluate a personalized mobile education system for New Zealand students, utilizing AI and UCD principles. The system will address the limited personalization in existing mobile education solutions, by providing tailored learning content and recommendations based on individual preferences, catering to the diverse needs of students. The study will employ a mixed-methods approach, including user research, persona development, user journey mapping, design, development, and evaluation. Participants, including New Zealand students, parents, and teachers, will be involved in several phases of research to ensure that user-centered design principles are effectively implemented. By demonstrating the potential of AI-powered personalization to improve the learning experience for students, this study contributes to the increasing use of AI algorithms and systems in education.
Meeting energy demands and generating profit to shareholders is a continuous quest for oil and gas companies. Production and business planning in integrated oil and gas operating companies is a complex process involving numerous organizations, historic data collection, modeling, prediction, and forecasting. Integrated business planning complexity intensifies due to the uncertain nature of past facts and future conditions. We propose a framework for integrating upstream and downstream production planning processes using data-driven models representing the upstream capacities, downstream processes, and a countrywide profit model. The upstream production model forecasts optimum capacity scenarios of the reservoir fluids with their compositional characteristics and hydraulic performance of the surface facilities while honoring business rules, and based on the various long-term expenditure scenarios, downtime requirements, and downstream demand schedules. An integrated optimization model for value chain has the potential to protect profitability for oil and gas companies in times of unbalanced market forces.
This research endeavors to develop and assess a customized mobile education system for students in New Zealand, employing the principles of artificial intelligence (AI) and user-centered design (UCD). The objective is to overcome the limited personalization observed in current mobile education solutions by offering tailored learning content and recommendations based on individual preferences, thereby accommodating the diverse requirements of students. A mixed-methods approach will be utilized, encompassing user research, persona development, user journey mapping, design, development, and evaluation. Participants, including New Zealand students, parents, and teachers, will actively engage in multiple research phases to ensure the effective implementation of user-centered design principles. By showcasing the potential of AI-driven personalization in enhancing the learning experience for students, this study contributes to the growing utilization of AI algorithms and systems within the educational context.
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