A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market

The competing risks technique is applied to the analysis of times to execution and cancellation of limit orders submitted on an electronic trading platform. Time-to-execution is found to be more sensitive to the limit price variation than time-to-cancellation, even though it is less sensitive to the limit order size. More importantly, investors who aim to reduce the expected time-to-execution for their limit orders without inducing any significant increase in the risk of subsequent cancellation should submit their orders when the market depth is smaller on the side of their orders or when the market depth is greater on the opposite side of their orders. We also provide a new diagnostic plots method for evaluating the goodness-of-fit of different competing risks models.Market microstructure, limit order, competing risks, hazard rate, frailty

Jamming Transition of Point-to-Point Traffic Through Cooperative Mechanisms

We study the jamming transition of two-dimensional point-to-point traffic through cooperative mechanisms using computer simulation. We propose two decentralized cooperative mechanisms which are incorporated into the point-to-point traffic models: stepping aside (CM-SA) and choosing alternative routes (CM-CAR). Incorporating CM-SA is to prevent a type of ping-pong jumps from happening when two objects standing face-to-face want to move in opposite directions. Incorporating CM-CAR is to handle the conflict when more than one object competes for the same point in parallel update. We investigate and compare four models mainly from fundamental diagrams, jam patterns and the distribution of cooperation probability. It is found that although it decreases the average velocity a little, the CM-SA increases the critical density and the average flow. Despite increasing the average velocity, the CM-CAR decreases the average flow by creating substantially vacant areas inside jam clusters. We investigate the jam patterns of four models carefully and explain this result qualitatively. In addition, we discuss the advantage and applicability of decentralized cooperation modeling.Comment: 17 pages, 14 figure

Tunable-Focus Liquid Lens through Charge Injection

Liquid lenses are the simplest and cheapest optical lenses, and various studies have been conducted to develop tunable-focus liquid lenses. In this study, a simple and easily implemented method for achieving tunable-focus liquid lenses was proposed and experimentally validated. In this method, charges induced by a corona discharge in the air were injected into dielectric liquid, resulting in “electropressure” at the interface between the air and the liquid. Through a 3D-printed U-tube structure, a tunable-focus liquid lens was fabricated and tested. Depending on the voltage, the focus of the liquid lens can be adjusted in large ranges (−∞ to −9 mm and 13.11 mm to ∞). The results will inspire various new liquid-lens applications

Modeling Instance Interactions for Joint Information Extraction with Neural High-Order Conditional Random Field

Prior works on joint Information Extraction (IE) typically model instance (e.g., event triggers, entities, roles, relations) interactions by representation enhancement, type dependencies scoring, or global decoding. We find that the previous models generally consider binary type dependency scoring of a pair of instances, and leverage local search such as beam search to approximate global solutions. To better integrate cross-instance interactions, in this work, we introduce a joint IE framework (CRFIE) that formulates joint IE as a high-order Conditional Random Field. Specifically, we design binary factors and ternary factors to directly model interactions between not only a pair of instances but also triplets. Then, these factors are utilized to jointly predict labels of all instances. To address the intractability problem of exact high-order inference, we incorporate a high-order neural decoder that is unfolded from a mean-field variational inference method, which achieves consistent learning and inference. The experimental results show that our approach achieves consistent improvements on three IE tasks compared with our baseline and prior work

Improving yield and water use efficiency of apple trees through intercrop-mulch of crown vetch (Coronilla varia L.) combined with different fertilizer treatments in the Loess Plateau

Improving water use efficiency (WUE) and soil fertility is relevant for apple production in drylands. The effects of intercrop-mulch (IM) of crown vetch (Coronilla varia L.) combined with different fertilizer treatments on WUE of apple trees and soil fertility of apple orchards were assessed over three years (2011, 2013 and 2014). A split-plot design was adopted, in which the main treatments were IM and no intercrop-mulch (NIM). Five sub-treatments were established: no fertilization (CK); nitrogen and phosphorus fertilizer (NP); manure (M); N, P and potassium fertilizer (NPK); and NPK fertilizer combined with manure (NPKM). Due to mowing and mulching each month during July–September, the evapotranspiration for IM was 17.3% lower than that of NIM in the dry year of 2013. Additionally, the soil water storage of NPKM treatment was higher than that of CK during the experimental period. Thus, single fruit weight and fruit number per tree increased with IM and NPKM application. Moreover, applying NPKM with IM resulted in the highest yield (on average of three years), which was 73.25% and 130.51% greater than that of CK in IM and NIM, respectively. The WUE of NPKM combined with IM was also the highest in 2013 and 2014 (47.69 and 56.95% greater than applying IM alone). In addition, due to application of IM combined with NPKM, soil organic matter was increased by 25.8% compared with that of CK (in NIM). Additionally, application of IM combined with NPKM obtained more economic net return, compared to other combinations. Therefore, applying NPKM with IM is recommended for improving apple production in this rain-fed agricultural area