End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

Knowledge graph embedding has been an active research topic for knowledge base completion, with progressive improvement from the initial TransE, TransH, DistMult et al to the current state-of-the-art ConvE. ConvE uses 2D convolution over embeddings and multiple layers of nonlinear features to model knowledge graphs. The model can be efficiently trained and scalable to large knowledge graphs. However, there is no structure enforcement in the embedding space of ConvE. The recent graph convolutional network (GCN) provides another way of learning graph node embedding by successfully utilizing graph connectivity structure. In this work, we propose a novel end-to-end Structure-Aware Convolutional Network (SACN) that takes the benefit of GCN and ConvE together. SACN consists of an encoder of a weighted graph convolutional network (WGCN), and a decoder of a convolutional network called Conv-TransE. WGCN utilizes knowledge graph node structure, node attributes and edge relation types. It has learnable weights that adapt the amount of information from neighbors used in local aggregation, leading to more accurate embeddings of graph nodes. Node attributes in the graph are represented as additional nodes in the WGCN. The decoder Conv-TransE enables the state-of-the-art ConvE to be translational between entities and relations while keeps the same link prediction performance as ConvE. We demonstrate the effectiveness of the proposed SACN on standard FB15k-237 and WN18RR datasets, and it gives about 10% relative improvement over the state-of-the-art ConvE in terms of HITS@1, HITS@3 and [email protected]: The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019

Sequential Appointment Scheduling Considering Walk-In Patients

This paper develops a sequential appointment algorithm considering walk-in patients. In practice, the scheduler assigns an appointment time for each call-in patient before the call ends, and the appointment time cannot be changed once it is set. Each patient has a certain probability of being a no-show patient on the day of appointment. The objective is to determine the optimal booking number of patients and the optimal scheduling time for each patient to maximize the revenue of all the arriving patients minus the expenses of waiting time and overtime. Based on the assumption that the service time is exponentially distributed, this paper proves that the objective function is convex. A sufficient condition under which the profit function is unimodal is provided. The numerical results indicate that the proposed algorithm outperforms all the commonly used heuristics, lowering the instances of no-shows, and walk-in patients can improve the service efficiency and bring more profits to the clinic. It is also noted that the potential appointment is an effective alternative to mitigate no-show phenomenon

Blockholder Mutual Fund Participation in Private In-House Meetings

The Shenzhen Stock Exchange (SZSE) in China is unique worldwide in requiring disclosure of the timing, participants, and selected content of private in-house meetings between firm managers and outsider investors. We investigate whether these private meetings benefit hosting firms and their major outside institutional investors—blockholder mutual funds (i.e., funds with ownership ≥5%). Using a large data set of SZSE firms, we find that blockholder mutual funds have more access to private in-house meetings, and top management is more likely to be present, especially when a meeting is associated with negative news. Furthermore, when blockholder mutual funds attend negative-news meetings with top management, they are less likely to sell shares, their investment relationship with the hosting firm lasts longer, and hosting firms experience lower postmeeting stock return volatility. These findings suggest that private in-house meetings are an informative disclosure channel that improves social bonding between top management and blockholder mutual funds in ways that benefit hosting firms

Electrospray synthesis of PLGA TIPS microspheres

We successfully demonstrate the synthesis of polymer microspheres using a single electrospray source, and show their physical characterisation. Electrospray has proven to be a versatile method to manufacture particles, giving tight control over size with quasi-monodisperse size distributions. It is a liquid atomisation technique that generates a monodisperse population of highly charged liquid droplets over a broad size range (nanometres to tens of microns). The droplets contain liquid precursors for the in-flight synthesis of particles, and control over the trajectory of these droplets can be precisely manipulated with the use of electric fields to drive them to a grounded substrate. This study reports a method to synthesize poly(lactic-co-glycolic) acid (PLGA) microspheres using the electrospray and thermally induced phase separation (TIPS) techniques, followed by subsequent freeze-drying, for particle production. These microspheres are of interest as vehicles for controlled drug release systems

Spatial Variability of Relative Sea-Level Rise in Tianjin, China: Insight from InSAR, GPS, and Tide-Gauge Observations

The Tianjin coastal region in Bohai Bay, Northern China, is increasingly affected by storm-surge flooding which is exacerbated by anthropogenic land subsidence and global sea-level rise (SLR). We use a combination of synthetic aperture radar interferometry (InSAR), continuous GPS (CGPS), and tide-gauge observations to evaluate the spatial variability of relative SLR (RSLR) along the coastline of Tianjin. Land motion obtained by integration of 2 tracks of Sentinel-1 SAR images and 19 CGPS stations shows that the recent land subsidence in Tianjin downtown is less than 8 mm/yr, which has significantly decreased with respect to the last 50 years (up to 110 mm/yr in the 1980s). This might benefit from the South-to-North Water Transfer Project which has provided more than 1.8 billion cubic meters of water for Tianjin city since 2014 and reduced groundwater consumption. However, subsidence centers have shifted to suburbs, especially along the coastline dominated by reclaimed harbors and aquaculture industry, with localized subsidence up to 170 mm/yr. Combining InSAR observations with sea level records from tide-gauge stations reveals spatial variability of RSLR along the coastline. We find that, in the aquaculture zones along the coastline, the rates of land subsidence are as high as 82 mm/yr due to groundwater extraction for fisheries, which subsequently cause local sea levels to rise nearly 30 times faster than the global average. New insights into land subsidence and local SLR could help the country's regulators to make decisions on ensuring the sustainable development of the coastal aquaculture industry