A Review of Studies on Languaging and Second Language Learning (2006-2017)

Since Swain postulated the concept “languaging” in 2006 to capture the role of language production in second language (L2) learning, a growing body of empirical studies has been conducted on languaging. However, little research has reviewed these studies. The present paper reviews 15 empirical studies that were conducted over the past decade on languaging in L2 learning, followed Vygotsky’s socioculutral theory of mind, and directly took languaging as the treatment or part of the treatment. We distinguished task-prompted and teacher-imposed languaging in the paper. All studies reviewed focused on teacher-imposed languaging. On the basis of reviewing the foci and findings of the studies, we offer our critical comments and recommendations for future research

Availability Allocation of Networked Systems Using Markov Model and Heuristics Algorithm

It is a common practice to allocate the system availability goal to reliability and maintainability goals of components in the early design phase. However, the networked system availability is difficult to be allocated due to its complex topology and multiple down states. To solve these problems, a practical availability allocation method is proposed. Network reliability algebraic methods are used to derive the availability expression of the networked topology on the system level, and Markov model is introduced to determine that on the component level. A heuristic algorithm is proposed to obtain the reliability and maintainability allocation values of components. The principles applied in the AGREE reliability allocation method, proposed by the Advisory Group on Reliability of Electronic Equipment, and failure rate-based maintainability allocation method persist in our allocation method. A series system is used to verify the new algorithm, and the result shows that the allocation based on the heuristic algorithm is quite accurate compared to the traditional one. Moreover, our case study of a signaling system number 7 shows that the proposed allocation method is quite efficient for networked systems

Optimal capacity reliability design of networks based on genetic algorithm

The cost, capacity and reliability of components vary in different component types, and the optimal component combination is determined by minimizing the total cost under the constraint of network capacity reliability requirement. To solve the problem that the gradient method can only be applied for networks whose capacity and reliability of components monotonically increase with the cost, a general optimization model is presented, and a Genetic Algorithm (GA) method using the minimal path sets to calculate the network capacity reliability is proposed to solve this optimal capacity reliability design problem. The optimal types of both nodes and links can be obtained using our optimization method. Our case study on ARPA network shows that our algorithm is efficient for the problem with good convergence and search performance

Single-breath-hold photoacoustic computed tomography of the breast

We have developed a single-breath-hold photoacoustic computed tomography (SBH-PACT) system to reveal detailed angiographic structures in human breasts. SBH-PACT features a deep penetration depth (4 cm in vivo) with high spatial and temporal resolutions (255 µm in-plane resolution and a 10 Hz 2D frame rate). By scanning the entire breast within a single breath hold (~15 s), a volumetric image can be acquired and subsequently reconstructed utilizing 3D back-projection with negligible breathing-induced motion artifacts. SBH-PACT clearly reveals tumors by observing higher blood vessel densities associated with tumors at high spatial resolution, showing early promise for high sensitivity in radiographically dense breasts. In addition to blood vessel imaging, the high imaging speed enables dynamic studies, such as photoacoustic elastography, which identifies tumors by showing less compliance. We imaged breast cancer patients with breast sizes ranging from B cup to DD cup, and skin pigmentations ranging from light to dark. SBH-PACT identified all the tumors without resorting to ionizing radiation or exogenous contrast, posing no health risks

Jet mixing optimization using machine learning control

We experimentally optimize mixing of a turbulent round jet using machine learning control (MLC) following Li et al (2017). The jet is manipulated with one unsteady minijet blowing in wall-normal direction close to the nozzle exit. The flow is monitored with two hotwire sensors. The first sensor is positioned on the centerline 5 jet diameters downstream of the nozzle exit, i.e. the end of the potential core, while the second is located 3 jet diameters downstream and displaced towards the shear-layer. The mixing performance is monitored with mean velocity at the first sensor. A reduction of this velocity correlates with increased entrainment near the potential core. Machine Learning Control (MLC) is employed to optimize sensor feedback, a general open-loop broadband frequency actuation and combinations of both. MLC has identified the optimal periodic forcing with a small duty cycle as the best control policy employing only 400 actuation measurements, each lasting for 5 seconds. This learning rate is comparable if not faster than typical optimization of periodic forcing with two free parameters (frequency and duty cycle). In addition, MLC results indicate that neither new frequencies nor sensor feedback improves mixing further-contrary to many of other turbulence control experiments. The optimality of pure periodic actuation may be attributed to the simple jet flapping mechanism in the minijet plane. The performance of sensor feedback is shown to face a challenge for small duty cycles. The jet mixing results demonstrate the untapped potential of MLC in quickly learning optimal general control policies, even deciding between open- and closed-loop control.Comment: 15 pages, 14 figure

A hundred years after: endodormancy and the chilling requirement in subtropical trees

Endodormancy and the related chilling requirement synchronize the seasonal development of trees from the boreal and temperate regions under the climatic conditions prevailing at their native growing sites. The phenomenon of endodormancy has been known at the whole-plant level for 100 years, and in the last couple of decades, insights into the physiological and molecular basis of endodormancy and its release have also been obtained. Intriguingly, recent studies have shown experimentally that subtropical trees also show endodormancy and a chilling requirement. Motivated by the climatic differences between the subtropical and more northern zones, here we address the similarities and differences in endodormancy between trees growing in the subtropical zone and those growing in more northern zones