Linking teacher beliefs, practices and student inquiry-based learning in a CSCL environment: A tale of two teachers

The links uncovered by research connecting teacher beliefs to classroom practice and student inquiry-based learning are tenuous. This study aims at examining (a) how teacher beliefs influenced practices; and (b) how the influence on practices, in turn, impacted student inquiry learning in a CSCL environment. Through a fine-grained comparative analysis of two cases, this study explores how two teachers with different collections of beliefs enacted the same mathematics lesson on division and fractions in a CSCL environment premised on inquiry principles, and what the connections between different enactments and students’ progressive inquiry process and outcomes were. The findings suggest that the two teachers’ adherence to different beliefs led to different practices, which in turn contributed to different student learning processes and outcomes. We interpret these differences that shaped the students’ opportunities for progressive inquiry in the CSCL environment. We conclude that the teacher holding “innovation-oriented” beliefs tended to enact the lesson in patterns of inquiry-principle-based practices and technology-enhanced orchestration; these patterns interacted with each other to contribute to student inquiry learning and effective use of technology affordances.     

An efficient initialization approach of Q-learning for mobile robots

This article demonstrates that Q-learning can be accelerated by appropriately specifying initial Q-values using dynamic wave expansion neural network. In our method, the neural network has the same topography as robot work space. Each neuron corresponds to a certain discrete state. Every neuron of the network will reach an equilibrium state according to the initial environment information. The activity of the special neuron denotes the maximum cumulative reward by following the optimal policy from the corresponding state when the network is stable. Then the initial Q-values are defined as the immediate reward plus the maximum cumulative reward by following the optimal policy beginning at the succeeding state. In this way, we create a mapping between the known environment information and the initial values of Q-table based on neural network. The prior knowledge can be incorporated into the learning system, and give robots a better learning foundation. Results of experiments in a grid world problem show that neural network-based Q-learning enables a robot to acquire an optimal policy with better learning performance compared to conventional Q-learning and potential field-based Qlearning.     

Site occupations and ordering behaviour of O phase in Ti2AlNb—based intermetallics

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Novel Mo-V Oxide Catalysts with Nanospheres as Templates for the Selective Oxidation of Acrolein to Acrylic Acid

Catalysis Letters - Novel Mo-V-PMMA and Mo-V-PS catalysts are prepared by addition of hard polymethyl methacrylate (PMMA) and polystyrene (PS) nanospheres into Mo/V compounds in the preparation...     

Facile synthesis of nitrogen and oxygen co-doped hierarchical porous carbon materials for high performance super capacitors

Journal of Porous Materials - Nitrogen and oxygen co-doped hierarchical porous carbons (NOPCs) is prepared by the pyrolysis of polyethylene glycol-200 (PEG) and triazine carbon forming agent (CFA)...     

Thermal cross-linking and anti-meltdrop properties of copolyester containing phosphorus/magnesium salt composites by in situ polymerization

Polyester is widely used in household products because of its good mechanical properties and wears resistance, but polyester is easy to ignite and inclined to produce droplet, so its application range is limited. The cross-linkable magnesium hydroxide nanoparticles were incorporated into flame-retardant polyester, which enables the phosphorus-containing copolyester with thermal cross-linking and anti-meltdrop properties. The nanoparticles were achieved by in situ polymerization and acted as a nucleating agent for improving the crystalline properties of the copolyester. Furthermore, the nanoparticles also enhanced anti-meltdrop properties and reduced the heat and gas release during the combustion process of the copolyester. The maximum heat release rate and total smoke release reduced by 39.8% and 74.4% compared with pure polyester. Specifically, the combustion products of the nanoparticles and phosphorus flame retardant could act a barrier role by covering the carbon layer to isolate air and heat, thereby resulting in excellent anti-meltdrop properties. The simple modification method reported here realizes the collaborative modification of flame retardant and anti-meltdrop properties of phosphorous flame-retardant copolyesters by thermal cross-linking.     

Annexin 1 Is a Component of eATP-Induced Cytosolic Calcium Elevation in Arabidopsis thaliana Roots

Extracellular ATP (eATP) has long been established in animals as an important signalling molecule but this is less understood in plants. The identification of Arabidopsis thaliana DORN1 (Does Not Respond to Nucleotides) as the first plant eATP receptor has shown that it is fundamental to the elevation of cytosolic free Ca²⁺ ([Ca²⁺]_cyt) as a possible second messenger. eATP causes other downstream responses such as increase in reactive oxygen species (ROS) and nitric oxide, plus changes in gene expression. The plasma membrane Ca²⁺ influx channels involved in eATP-induced [Ca²⁺]_cyt increase remain unknown at the genetic level. Arabidopsis thaliana Annexin 1 has been found to mediate ROS-activated Ca²⁺ influx in root epidermis, consistent with its operating as a transport pathway. In this study, the loss of function Annexin 1 mutant was found to have impaired [Ca²⁺]_cyt elevation in roots in response to eATP or eADP. Additionally, this annexin was implicated in modulating eATP-induced intracellular ROS accumulation in roots as well as expression of eATP-responsive genes.     

Operational optimization of a building-level integrated energy system considering additional potential benefits of energy storage

As a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.     

Zr－1Nb合金吸氢性能研究

研究了１３种不同加工热处理制度的Ｚｒ－１Ｎｂ合金在堆外高压釜内３６０℃、１９ＭＰａ水中的吸氢性能，对其影响因素和吸氢机理进行了分析，并讨论了吸氢动力学，建立了吸氢动力学方程，计算了吸氢动力学参数。