A Study on Teachers’ Questioning Strategies for the Purpose of Improving Students’ Thinking Quality in Senior High School English Reading Teaching

Thinking quality is a key element in developing students’ creativity, critical thinking skills and critical thinking. In high school English teaching, questioning is an important means to develop students’ reading comprehension ability. However, the traditional way of teachers’ questioning is usually aimed at expressing the answers, neglecting the cultivation of thinking quality. The purpose of this paper is to explore the current situation and reasons of questioning in high school, and to explore the specific questioning strategies that can effectively train students’ thinking quality in high school English classes

Effects of span-to-depth ratios on moment connection damage evolution under catenary action

This paper proposes an improved method for determining the gravity resistance of a moment resisting beam-column assembly following an interior column loss. The proposed method accounts for the connection\u27s damage evolution and for the catenary mechanism developed by the assembly as it deflects downward. Through a full-scale laboratory test and finite element simulations, the complete responses of moment resisting beam-column assemblies including the connection\u27s damage evolution are investigated under different beam span-to-depth ratios. The welded unreinforced flange-bolted web (WUF-BW) connection method is used for its robustness in developing the catenary action. It is found that, under the same span-to-depth ratio, beam-column assemblies exhibit similar normalized load-rotation relationships, even with different beam depths. The assembly with a larger span-to-depth ratio is able to develop the gravity resistance earlier, and provides a higher ultimate resistance by developing a more effective catenary mechanism. On the other hand, the assembly with a smaller span-to-depth ratio exhibits a more ductile response. A simplified curve model of the gravity resistance development of a moment beam-column assembly with damage evolution has been proposed for a convenient assessment of the progressive collapse resistance following a central column loss

Seismic performance of concrete-filled SHS column-to-beam connections with slip-critical blind bolts

© 2020 Elsevier Ltd This paper investigates the use of slip-critical blind bolts to connect I-beams to concrete-filled steel square hollow section (SHS) columns. The strength and stiffness of the resulting joints are determined experimentally for the purpose of classifying them according to the Eurocode. Their suitability for use in special moment frames is also assessed through cyclic bending tests. Three types of beam sections are tested, being a compact welded section, a reduced beam (flange) section, and a reduced beam section with concrete slab at the top. All tested joints are full strength according to the Eurocode, allowing the connected beams to reach their respective plastic moment capacities. In addition, they are rigid for braced and unbraced frames, except for the reduced beam section specimen, which are semi-rigid only for unbraced frames according to the Eurocode. However, all specimens have sufficient ductility to be used in special moment frames, with no pinching effect in their hysteretic moment-rotation curves. Their initial rotational stiffness is dominated by the stiffness of the column flange in bending, which can be conservatively estimated using the formulation presented in this paper

Toward Real-time Simulation of Blood-Coil Interaction during Aneurysm Embolization

International audienceOver the last decade, remarkable progress has been made in the field of endovascular treatment of aneurysms. Technological advances continue to enable a growing number of patients with cerebral aneurysms to be treated with a variety of endovascular strategies, essentially using detachable platinum coils. Yet, coil embolization remains a very complex medical procedure for which careful planning must be combined with advanced technical skills in order to be successful. In this paper we propose a method for computing the complex blood flow patterns that take place within the aneurysm, and for simulating the interaction of coils with this flow. This interaction is twofold, first involving the impact of the flow on the coil during the initial stages of its deployment, and second concerning the decrease of blood velocity within the aneurysm, as a consequence of coil packing. We also propose an ap- proach to achieve real-time computation of coil-flow bilateral influence, necessary for interactive simulation. This in turns allows to dynamically plan coil embolization for two key steps of the procedure: choice and placement of the first coils, and assessment of the number of coils neces- sary to reduce aneurysmal blood velocity and wall pressure

Adaptive Virtual Impedance Droop Control Based on Consensus Control of Reactive Current

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the proposed control strategy. When the adjacent DG’s reactive power is not proportionally distributed, the current weight error term will generate a virtual impedance correction term through the proportional-integral controller based on the reactive current consensus control strategy, thus introducing adaptive virtual impedance to eliminate mismatches in output impedance between DGs. Reactive power auto-proportional distribution can be achieved without knowing the line impedance. At the same time, the power control loop is simplified and the virtual impedance compensation angle is employed to compensate the decreased reference voltage magnitude and varied phase angle due to the introduction of the virtual impedance, so the stability of the system can be improved. Finally, the correctness and effectiveness of the proposed strategy are verified by modeling analysis and microgrid simulations. Abstract It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the proposed control strategy. When the adjacent DG’s reactive power is not proportionally distributed, the current weight error term will generate a virtual impedance correction term through the proportional-integral controller based on the reactive current consensus control strategy, thus introducing adaptive virtual impedance to eliminate mismatches in output impedance between DGs. Reactive power auto-proportional distribution can be achieved without knowing the line impedance. At the same time, the power control loop is simplified and the virtual impedance compensation angle is employed to compensate the decreased reference voltage magnitude and varied phase angle due to the introduction of the virtual impedance, so the stability of the system can be improved. Finally, the correctness and effectiveness of the proposed strategy are verified by modeling analysis and microgrid simulations

Interactive Blood-Coil Simulation in Real-time during Aneurysm Embolization

International audienceOver the last decade, remarkable progress has been made in the field of endovascular treatment of aneurysms. Technological advances continue to make it possible for a growing number of patients with cerebral aneurysms to be treated with a variety of endovascular strategies, essentially using detachable platinum coils. Yet, coil embolization remains a very complex medical procedure for which careful planning must be combined with advanced technical skills in order to be successful. In this paper, we describe a complete process for patient-specific simulations of coil embolization, from mesh generation with medical datasets to computation of coil-flow bilateral influence. We propose a new method for simulating the complex blood flow patterns that take place within the aneurysm, and for simulating the interaction of coils with this flow. This interaction is twofold, first involving the impact of the flow on the coil during the initial stages of its deployment, and second concerning the decrease of blood velocity within the aneurysm, as a consequence of coil packing. We also propose an approach to achieve real-time computation of coil-flow bilateral influence, necessary for interactive simulation. This in turns allows to dynamically plan coil embolization for two key steps of the procedure: choice and placement of the first coils, and assessment of the number of coils necessary to reduce aneurysmal blood velocity and wall pressure. Finally, we provide the blood flow simulation results on several aneurysms with interesting clinical characteristics both in 2D and 3D, as well as comparisons with a commercial package for validation. The coil embolization procesure is simulated within an aneurysm, and pre- and post-operative status is reported

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism for Solving Large-Scale Economic Dispatch With Valve-Point Effects and Multiple Fuel Options

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The effectiveness of the CMFA method to solve economic dispatch problems with high nonlinearities is demonstrated using five classic test power systems. The solutions obtained are compared with the results of the original algorithm and several methods of optimization proposed in the previous literature. The high performance of the CMFA algorithm is demonstrated by its ability to achieve search solution quality and reliability, which reflected in minimum total cost, convergence speed, and consistency

Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models

With ever increasing parameters and computation, vision-language pre-trained (VLP) models exhibit prohibitive expenditure in downstream task adaption. Recent endeavors mainly focus on parameter efficient transfer learning (PETL) for VLP models by only updating a small number of parameters. However, excessive computational overhead still plagues the application of VLPs. In this paper, we aim at parameter and computation efficient transfer learning (PCETL) for VLP models. In particular, PCETL not only needs to limit the number of trainable parameters in VLP models, but also to reduce the computational redundancy during inference, thus enabling a more efficient transfer. To approach this target, we propose a novel dynamic architecture skipping (DAS) approach towards effective PCETL. Instead of directly optimizing the intrinsic architectures of VLP models, DAS first observes the significances of their modules to downstream tasks via a reinforcement learning (RL) based process, and then skips the redundant ones with lightweight networks, i.e., adapters, according to the obtained rewards. In this case, the VLP model can well maintain the scale of trainable parameters while speeding up its inference on downstream tasks. To validate DAS, we apply it to two representative VLP models, namely ViLT and METER, and conduct extensive experiments on a bunch of VL tasks. The experimental results not only show the great advantages of DAS in reducing computational complexity, e.g. -11.97% FLOPs of METER on VQA2.0, but also confirm its competitiveness against existing PETL methods in terms of parameter scale and performance. Our source code is given in our appendix

A (Near) Real-Time Simulation Method of Aneurysm Coil Embolization

International audienceA (Near) Real-Time Simulation Method of Aneurysm Coil Embolizatio