Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Relationship Between Shipping Accessibility and Maritime Transport Demand: the Case of Mainland China

Networks and Spatial Economics - The relationship between shipping accessibility and maritime transport demand is studied based on the relationship between production and consumption and stochastic...     

Long-term sustained-released in situ gels of a water-insoluble drug amphotericin B for mycotic arthritis intra-articular administration: preparation,in vitro and in vivo evaluation

Amphotericin B (AMB) was often used in intra-articular injection administration for fungal arthritis, because it could often bring a satisfactory therapeutic efficacy and a minimum systemic toxic side effect. However, because of the multiple operations and the frequent injections, the compliance of the patients was bad. Therefore, to develop a long-term sustained-released preparation of AMB for mycotic arthritis intra-articular administration is of great significance. The purpose of present study was to develop a long-term sustained-released in situ gel of a water-insoluble drug AMB for mycotic arthritis intra-articular administration. Based on the evaluations of the in vitro properties of the formulations, the formulation containing 10% (w/w) ethanol, 15% (w/w) PG, 0.75% (w/w) HA, 5% (w/w) purified soybean oil, 0.03% (w/w) α-tocopherol, 15% (w/w) water and 55% (w/w) glyceryl monooleate was selected as a suitable intra-articular injectable in situ gel drug delivery system for water-insoluble drug AMB. Furthermore, the results of the in vivo study on rabbits showed that the selected formulation was a safe and effective long-term sustained-released intra-articular injectable AMB preparation. Therefore, the presented in situ AMB gel could reduce the frequency of the administration in the AMB treatment of fungal arthritis, and then would get a good patient compliance.     

Nanomaterials for radiotherapeutics-based multimodal synergistic cancer therapy

Over the past decade, numerous studies have attempted to enhance the effectiveness of radiotherapy (external beam radiotherapy and internal radioisotope therapy) for cancer treatment. However, the low radiation absorption coefficient and radiation resistance of tumors remain major critical challenges for radiotherapy in the clinic. With the development of nanomedicine, nanomaterials in combination with radiotherapy offer the possibility to improve the efficiency of radiotherapy in tumors. Nanomaterials act not only as radiosensitizers to enhance radiation energy, but also as nanocarriers to deliver therapeutic units in combating radiation resistance. In this review, we discuss opportunities for a synergistic cancer therapy by combining radiotherapy based on nanomaterials designed for chemotherapy, photodynamic therapy, photothermal therapy, gas therapy, genetic therapy, and immunotherapy. We highlight how nanomaterials can be utilized to amplify antitumor radiation responses and describe cooperative enhancement interactions among these synergistic therapies. Moreover, the potential challenges and future prospects of radio-based nanomedicine to maximize their synergistic efficiency for cancer treatment are identified.