ActiveAI: Introducing AI Literacy for Middle School Learners with Goal-based Scenario Learning

The ActiveAI project addresses key challenges in AI education for grades 7-9 students by providing an engaging AI literacy learning experience based on the AI4K12 knowledge framework. Utilizing learning science mechanisms such as goal-based scenarios, immediate feedback, project-based learning, and intelligent agents, the app incorporates a variety of learner inputs like sliders, steppers, and collectors to enhance understanding. In these courses, students work on real-world scenarios like analyzing sentiment in social media comments. This helps them learn to effectively engage with AI systems and develop their ability to evaluate AI-generated output. The Learning Engineering Process (LEP) guided the project's creation and data instrumentation, focusing on design and impact. The project is currently in the implementation stage, leveraging the intelligent tutor design principles for app development. The extended abstract presents the foundational design and development, with further evaluation and research to be conducted in the future

Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models

Contextualizing problems to align with student interests can significantly improve learning outcomes. However, this task often presents scalability challenges due to resource and time constraints. Recent advancements in Large Language Models (LLMs) like GPT-4 offer potential solutions to these issues. This study explores the ability of GPT-4 in the contextualization of problems within CTAT, an intelligent tutoring system, aiming to increase student engagement and enhance learning outcomes. Through iterative prompt engineering, we achieved meaningful contextualization that preserved the difficulty and original intent of the problem, thereby not altering values or overcomplicating the questions. While our research highlights the potential of LLMs in educational settings, we acknowledge current limitations, particularly with geometry problems, and emphasize the need for ongoing evaluation and research. Future work includes systematic studies to measure the impact of this tool on students' learning outcomes and enhancements to handle a broader range of problems

Contralateral versus ipsilateral protective effect against muscle damage of the elbow flexors and knee extensors induced by maximal eccentric exercise

The present study compared the ipsilateral repeated bout effect (IL-RBE) and contralateral repeated bout effect (CL-RBE) of the elbow flexors (EF) and knee flexors (KF) for the same interval between bouts to shed light on their mechanisms. Fifty-two healthy sedentary young (20–28 years) men were randomly assigned to the IL-EF, IL-KF, CL-EF, and CL-KF groups (n = 13/group). Thirty maximal eccentric contractions of the EF were performed in IL-EF and CL-EF, and 60 maximal eccentric contractions of the KF were performed in IL-KF and CL-KF, with a 2-week interval between bouts. Changes in muscle damage markers such as maximal voluntary contraction (MVC) torque, muscle soreness, and plasma creatine kinase activity, and proprioception measures before to 5 days post-exercise were compared between groups. Changes in all variables were greater (p \u3c 0.05) after the first than second bout for all groups, and the changes were greater (p \u3c 0.05) for the EF than KF. The changes in all variables after the second bout were greater (p \u3c 0.05) for the CL than IL condition for both EF and KF. The magnitude of the average protective effect was similar between CL-EF (33%) and CL-KF (32%), but slightly greater (p \u3c 0.05) for IL-EF (67%) than IL-KF (61%). These demonstrate that the magnitude of CL-RBE relative to IL-RBE was similar between the EF and KF (approximately 50%), regardless of the greater muscle damage for the EF than KF. It appears that the CL-RBE is more associated with neural adaptations at cerebrum, cerebellum, interhemispheric inhibition, and coricospinal tract, but the IL-RBE is induced by additional adaptations at muscles

LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs

LLMs have shown promise in replicating human-like behavior in crowdsourcing tasks that were previously thought to be exclusive to human abilities. However, current efforts focus mainly on simple atomic tasks. We explore whether LLMs can replicate more complex crowdsourcing pipelines. We find that modern LLMs can simulate some of crowdworkers' abilities in these "human computation algorithms," but the level of success is variable and influenced by requesters' understanding of LLM capabilities, the specific skills required for sub-tasks, and the optimal interaction modality for performing these sub-tasks. We reflect on human and LLMs' different sensitivities to instructions, stress the importance of enabling human-facing safeguards for LLMs, and discuss the potential of training humans and LLMs with complementary skill sets. Crucially, we show that replicating crowdsourcing pipelines offers a valuable platform to investigate (1) the relative strengths of LLMs on different tasks (by cross-comparing their performances on sub-tasks) and (2) LLMs' potential in complex tasks, where they can complete part of the tasks while leaving others to humans

Terpenoids from the Octocorals Menella sp. (Plexauridae) and Lobophytum crassum (Alcyonacea)

A new germacrane-type sesquiterpenoid, menelloide E (1), and a new cembrane-type diterpenoid, lobocrassin F (2), were isolated from the octocorals Menella sp. and Lobophytum crassum, respectively. The structures of terpenoids 1 and 2 were determined by spectroscopic and chemical methods and compound 2 was found to display a significant inhibitory effect on the release of elastase by human neutrophils

Psychoimmunological effects of dioscorea in ovariectomized rats: role of anxiety level

<p>Abstract</p> <p>Background</p> <p>Anxiety levels in rats are correlated with interleukin-2 (IL-2) levels in the brain. The aim of the present study was to investigate the effects of dioscorea (wild yam), a Chinese medicine, on emotional behavior and IL-2 levels in the brain of ovariectomized (OVX) rats.</p> <p>Methods</p> <p>One month after ovariectomy, female Wistar rats were screened in the elevated plus-maze (EPM) test to measure anxiety levels and divided into low anxiety (LA) and high anxiety (HA) groups, which were then given dioscorea (250, 750, or 1500 mg/kg/day) by oral gavage for 27 days and were tested in the EPM on day 23 of administration and in the forced swim test (FST) on days 24 and 25, then 3 days later, the brain was removed and IL-2 levels measured.</p> <p>Results</p> <p>Compared to sham-operated rats, anxiety behavior in the EPM was increased in half of the OVX rats. After chronic dioscorea treatment, a decrease in anxiety and IL-2 levels was observed in the HA OVX rats. Despair behavior in the FST was inhibited by the highest dosage of dioscorea.</p> <p>Conclusion</p> <p>These results show that OVX-induced anxiety and changes in neuroimmunological function in the cortex are reversed by dioscorea treatment. Furthermore, individual differences need to be taken into account when psychoneuroimmunological issues are measured and the EPM is a useful tool for determining anxiety levels when examining anxiety-related issues.</p

Helicobacter pylori infection concomitant with metabolic syndrome further increase risk of colorectal adenomas

AIM: To investigate the association of colorectal adenomas with both Helicobacter pylori (H. pylori) infection and metabolic syndrome

New Energy Empowerment Using Kernel Principal Component Analysis in Insulated Gate Bipolar Transistors Module Monitoring

At present, energy exhausted and environmental pollution are important issues, vigorously promoting new energy and improving the utilization efficiency and management level of new energy is an important way to achieve sustainable social development. Insulated gate bipolar transistors are important components in power converters and are widely used in new energy generation, new energy vehicles, high-speed rail and industrial production. However, the power module&rsquo;s age is related to all aspects of its performance change, precluding the use of a single parameter to fully and accurately express the aging state. To monitor this state and evaluate the aging state, this study presents a method to analyze and process the state data of Insulated gate bipolar transistors power module aging tests using kernel principal component analysis and establishes a multi-dimensional grey model to evaluate the power module aging state. Using the temperature cycle aging test platform, the 7000 temperature cycling tests are implemented to accelerate the age of the power module to failure, the dynamic parameters of the power modules are measured after every 1000 cycles. During the accelerated aging process, the case temperature change rate, collector-emitter voltage drop Vce(SAT) and Miller platform of the gate signal of Vge are found to exhibit different variation trends at different aging stages. The result showed that multiple parameters are combined into integrated attributes to enable more accurate implementation of the state monitoring of power modules using the proposed method, which improves the status monitoring level of Insulated gate bipolar transistors modules. The proposed method is beneficial to improve the utilization efficiency and new energy source management level

Exploring the Electro-Thermal Parameters of Reliable Power Modules: Insulated Gate Bipolar Transistor Junction and Case Temperature

In the exploration of new energy sources and the search for a path to sustainable development the reliable operation of wind turbines is of great importance to the stability of power systems. To ensure the stable and reliable operation of the Insulated Gate Bipolar Transistor (IGBT) power module, in this work the influence of changes with aging of different electro-thermal parameters on the junction temperature and the case temperature was studied. Firstly, power thermal cycling tests were performed on the IGBT power module, and the I-V characteristic curve, switching loss and transient thermal impedance are recorded every 1000 power cycles, and then the electrical parameters (saturation voltage drop and switching loss) and the thermal parameters (junction-to-case thermal resistance) of the IGBT are obtained under different aging states. The obtained electro-thermal parameters are substituted into the established electro-thermal coupling model to obtain the junction temperature and the case temperature under different aging states. The degrees of influence of these electro-thermal parameters on the junction temperature and case temperature under different aging states are analyzed by the single variable method. The results show that the changes of the electro-thermal parameters under different aging states affects the junction temperature and the case temperature as follows: (1) Compared with other parameters, the transient thermal impedance has the greatest influence on the junction temperature, which is 60.1%. (2) Compared with other parameters, the switching loss has the greatest influence on the case temperature, which is 79.8%. The result provides a novel method for the junction temperature calculation model and lays a foundation for evaluating the aging state by using the case temperature, which has important theoretical and practical significance for the stable operation of power electronic systems