Analysis of Multi-Element Blended Course Teaching and Learning Mode Based on Student-Centered Concept under the Perspective of “Internet+”

The integration of Internet and education has changed students’ learning environment and affected their learning behavior, which poses a greater challenge to the traditional teaching mode. Through the SWOT analysis of the “student centered” multi-element blended teaching mode in the era of “Internet + education”, it is concluded that the adaptability of learners themselves and the mismatch between teachers’ educational ideas and this teaching model delay the development of education to a certain extent. Some suggestions are put forward, such as strengthening the supervision and guidance, implementing the teaching and learning model scientifically, improving teachers’ ideology and comprehensive quality, and making full use of the characteristics of Internet opening, sharing and collaboration to construct the public service system and platform of national educational resources

Data Files: Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

This data supports the research project Bi-objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity and a final report published on NITC’s website. Dataset collected through multiple sources and organized into different formats including CSV format, JSON format, shapefile and code repository. Context: The research project develops a bi-objective model that aims to help transit agencies to optimally deploy BEB while considering both capital investment and environmental equity. The unique spatio-temporal characteristic of BEB system, charging limitations (on-route and in-depot charging), and operational constraints are also considered and incorporated into the model

Enabling Decision-Making in Battery Electric Bus Deployment through Interactive Visualization

The transit industry is rapidly transitioning to battery-electric fleets because of the direct environmental and financial benefits they could offer, such as zero emissions, less noise, and lower maintenance costs. Yet the unique spatiotemporal characteristics associated with transit system charging requirements, as well as various objectives when prioritizing the fleet electrification, requires the system operators and/or decision-makers to fully understand the status of the transit system and energy/power system in order to make informed deployment decisions. A recently completed NITC project, No. 1222 titled An Electric Bus Deployment Framework for Improved Air Quality and Transit Operational Efficiency, developed a bi-objective spatiotemporal optimization model for the strategic deployment of the Battery Electric Bus (BEB) to minimize the cost of purchasing BEBs, on-route and in-depot charging stations, and to maximize environmental equity for disadvantaged populations. As agencies such as the Utah Transit Authority (UTA) adopt the model and results, they desire to have a tool that could enable detailed spatiotemporal monitoring of components for the BEB system (e.g., locations of BEBs, the state-of-charge of batteries, charging station energy consumption at each specific timestamp), so that the integration of BEBs into the power/grid system as well as its operating condition could be better understood. To this end, this Translate Research to Practice grant will support the development of a visualization tool that allows transit operators/planners as well as decision-makers to explore the interdependency of the BEB transit system and energy infrastructure in both spatial and temporal dimensions with high resolution. The tool will be built on the scenario-based optimization modeling effort in NITC Project No. 1222, and allow agencies to make phase-wise (short-, mid-, or long-term) decisions based on investment resources and strategic goals. This project will also develop a guidebook to provide step-by-step guidance on data compilation for BEB analysis, model input, model implementation, and results interpretation. It will further detail how the developed visualization tool is structured and designed to ensure results exploration across transit operation and energy consumption. Both the guidebook and the tool will be directly useful to practitioners to easily implement our optimization model for their own transit network, and allow them to build interactive visualizations to assist with decision-making

Cloning and expression analysis of potassium channel gene NKT3 from Nicotiana tabacum

Potassium (K+) is the predominant inorganic ion of plant cells. K+ channels in higher plant cells play an important role in regulating the influx and efflux of K+ from cells, and activity of these channels might be involved in plant stress resistance. A completely new K+ channel gene of Nicotiana tabacum was obtained through homologous cloning strategy. The complete cDNA sequence was submitted to the National Center for Biotechnology Information (NCBI) GenBank, designated as NKT3 and the accession number is FJ230956. The phylogenetic analysis indicated that NKT3 is located at the branch of weak-inwardly rectifying K+ channels and might be a member of the Shaker family. The spatial and temporal expression of the gene was also investigated. NKT3 is expressed abundantly in the roots, while little in the leaves of N. tabacum. It might be involved in the process of K+ acquirement and release in tobacco roots.Keywords: Potassium channel gene, NKT3, RACE, Nicotiana tabacu

Thermal properties and kinetic analysis of pyrolysis products of nicotine salts from e-cigarettes using pyrolysis-gas chromatography/mass spectrometry

Volatile organic chemicals (VOCs) released from e-cigarettes are a special source of air pollutants. In this work, we investigated the VOCs released from six nicotine salts (namely, nicotine benzoate, nicotine tartrate, nicotine citrate, nicotine malate, nicotine lactate, and nicotine levulinate) that are commonly used in e-cigarettes. The pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and thermogravimetric methods were used to analyze the thermogravimetric characteristics and product release behavior of different nicotine salts. Moreover, the kinetic models and thermodynamic parameters of nicotine salts during the thermal decomposition process were obtained. Thermogravimetric characteristic parameters of six nicotine salts showed significant differences. By the use of Py-GC/MS, our data showed that the pyrolysis products of nicotine salts were mainly from nicotine, acid anhydrides, carboxylic acids, and N-heterocycles, while more than 90% of the nicotine of citrate, tartrate, and malate was transferred to smoke. The result revealed that activation energies of the nicotine salts range from 21.26 to 74.10 kJ mol-1, indicating that the pyrolysis of the nicotine salts is a non-spontaneous heat absorption process, and the organic acid was the key factor affecting the release of nicotine into the ambient air

Application of Permutation Entropy and Permutation Min-Entropy in Multiple Emotional States Analysis of RRI Time Series

This study’s aim was to apply permutation entropy (PE) and permutation min-entropy (PME) over an RR interval time series to quantify the changes in cardiac activity among multiple emotional states. Electrocardiogram (ECG) signals were recorded under six emotional states (neutral, happiness, sadness, anger, fear, and disgust) in 60 healthy subjects at a rate of 1000 Hz. For each emotional state, ECGs were recorded for 5 min and the RR interval time series was extracted from these ECGs. The obtained results confirm that PE and PME increase significantly during the emotional states of happiness, sadness, anger, and disgust. Both symbolic quantifiers also increase but not in a significant way for the emotional state of fear. Moreover, it is found that PME is more sensitive than PE for discriminating non-neutral from neutral emotional states.Facultad de Ingenierí

Multi-energy X-ray linear-array detector enabled by the side-illuminated metal halide scintillator

Conventional scintillator-based X-ray imaging typically captures the full spectral of X-ray photons without distinguishing their energy. However, the absence of X-ray spectral information often results in insufficient image contrast, particularly for substances possessing similar atomic numbers and densities. In this study, we present an innovative multi-energy X-ray linear-array detector that leverages side-illuminated X-ray scintillation using emerging metal halide Cs3Cu2I5. The negligible self-absorption characteristic not only improves the scintillation output but is also beneficial for improving the energy resolution for the side-illuminated scintillation scenarios. By exploiting Beer's law, which governs the absorption of X-ray photons with different energies, the incident X-ray spectral can be reconstructed by analyzing the distribution of scintillation intensity when the scintillator is illuminated from the side. The relative error between the reconstructed and measured X-ray spectral was less than 5.63 %. Our method offers an additional energy-resolving capability for X-ray linear-array detectors commonly used in computed tomography (CT) imaging setups, surpassing the capabilities of conventional energy-integration approaches, all without requiring extra hardware components. A proof-of-concept multi-energy CT imaging system featuring eight energy channels was successfully implemented. This study presents a simple and efficient strategy for achieving multi-energy X-ray detection and CT imaging based on emerging metal halides