The Multi-Rule Quality Control System (MRQCS) is a tool currently employed by the Centers for Disease Control and Prevention (CDC) to evaluate and compare laboratory performance. We have applied the MRQCS to a comparison of instructor and computer-led pre-laboratory lectures for a supplemental learning experiment. Students in general chemistry and analytical chemistry from both two- and four-year institutions performed two laboratory experiments as part of their normal laboratory curriculum. The first laboratory experiment was a foundational learning experiment in which all the students were introduced to Beer-Lambert's Law and spectrophotometric light absorbance measurements. The foundational learning experiment was instructor-led only, and participant performance was evaluated against a mean characterized value. The second laboratory experiment was a supplemental learning experiment in which students were asked to build upon the methodology they learned in the foundational learning experiment and apply it to a different analyte. The instruction type was varied randomly into two delivery modes, participants receiving either instructor-led or computer-led pre-laboratory instruction. The MRQCS was applied and determined that no statistical difference was found to exist in the QC (quality control) passing rates between the participants in the instructor-led instruction and the participants in the computer-led instruction. These findings demonstrate the successful application of the MRQCS to evaluate knowledge and technology transfer.
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http://dx.doi.org/10.1021/acs.jchemed.6b00964 | DOI Listing |
ACS Appl Mater Interfaces
December 2024
TCS Research, Sahyadri Park 2, Rajiv Gandhi Infotech Park, Hinjewadi Phase 3, Pune 411057, India.
Realization of a sustainable hydrogen economy in the future requires the development of efficient and cost-effective catalysts for its production at scale. MXenes (MX) are a class of 2D materials with 'n' layers of carbon or nitrogen (X) interleaved by 'n+1' layers of transition metal (M) and have emerged as promising materials for various applications including catalysts for hydrogen evolution reaction (HER). Their properties are intimately related to both their composition and their atomic structure.
View Article and Find Full Text PDFBehav Brain Funct
December 2024
Department of Pharmacology, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan.
The large-conductance calcium- and voltage-activated potassium (BK) channels, encoded by the KCNMA1 gene, play important roles in neuronal function. Mutations in KCNMA1 have been found in patients with various neurodevelopmental features, including intellectual disability, autism spectrum disorder (ASD), or attention deficit hyperactivity disorder (ADHD). Previous studies of KCNMA1 knockout mice have suggested altered activity patterns and behavioral flexibility, but it remained unclear whether these changes primarily affect immediate behavioral adaptation or longer-term learning processes.
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December 2024
College of Sciences, National University of Defense Technology, 410073, Changsha, China.
Deep Convolutional Neural Networks (DCNNs), due to their high computational and memory requirements, face significant challenges in deployment on resource-constrained devices. Network Pruning, an essential model compression technique, contributes to enabling the efficient deployment of DCNNs on such devices. Compared to traditional rule-based pruning methods, Reinforcement Learning(RL)-based automatic pruning often yields more effective pruning strategies through its ability to learn and adapt.
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December 2024
College of Electrical Engineering, Anhui Polytechnic University, Wuhu, 241000, Anhui, China.
The quantity of cable conductors is a crucial parameter in cable manufacturing, and accurately detecting the number of conductors can effectively promote the digital transformation of the cable manufacturing industry. Challenges such as high density, adhesion, and knife mark interference in cable conductor images make intelligent detection of conductor quantity particularly difficult. To address these challenges, this study proposes the YOLO-cable model, which is an improvement made upon the YOLOv10 model.
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December 2024
Department of Memory Neuroscience, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, 173-0015, Japan.
Retention of acquired learning memory is essential for reasonable behavior and crisis avoidance of individuals. Therefore, establishment of a system suitable for analysis of the retention/attenuation of acquired memory is desired. In the present study, mice were conducted on the repeated rotor-rod test, consisting of two series of experiments (Series 1 and 2) of 10 trials each.
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