Incorporating Structured Sentences with Time-enhanced BERT for Fully-inductive Temporal Relation Prediction

Temporal relation prediction in incomplete temporal knowledge graphs (TKGs) is a popular temporal knowledge graph completion (TKGC) problem in both transductive and inductive settings. Traditional embedding-based TKGC models (TKGE) rely on structured connections and can only handle a fixed set of entities, i.e., the transductive setting. In the inductive setting where test TKGs contain emerging entities, the latest methods are based on symbolic rules or pre-trained language models (PLMs). However, they suffer from being inflexible and not time-specific, respectively. In this work, we extend the fully-inductive setting, where entities in the training and test sets are totally disjoint, into TKGs and take a further step towards a more flexible and time-sensitive temporal relation prediction approach SST-BERT, incorporating Structured Sentences with Time-enhanced BERT. Our model can obtain the entity history and implicitly learn rules in the semantic space by encoding structured sentences, solving the problem of inflexibility. We propose to use a time masking MLM task to pre-train BERT in a corpus rich in temporal tokens specially generated for TKGs, enhancing the time sensitivity of SST-BERT. To compute the probability of occurrence of a target quadruple, we aggregate all its structured sentences from both temporal and semantic perspectives into a score. Experiments on the transductive datasets and newly generated fully-inductive benchmarks show that SST-BERT successfully improves over state-of-the-art baselines

Monitoring and controlling index system research for coordinated development of public Traditional Chinese Medicine hospital in city

目的  从服务医院领导层决策的角度出发，构建适用于城市公立中医院的综合性管理控制指标体系，监控医院发展运行状况，预警医疗质量和医院安全等问题，为强化科学决策与管理，促进公立医院协调发展提供工具和思路。对象与方法  以河南省洛阳正骨医院为研究现场，通过文献分析法和专家访谈法构建中医医院管控指标框架，应用Delphi法对指标进行筛选。结果  确立了包括医疗质量、医院安全、中医特色、经营效益、创新能力和人力资源6大维度、20个二级指标，72个三级指标的城市公立中医院管控指标体系。讨论  管控指标体系可操作性强，体现了中医医院运营、发展特色，符合深化公立医院改革方向，对于加强公立中医院科学管理与考评具有重要参考和借鉴价值。Objective:To build a comprehensive monitoring and controlling index system for public Traditional Chinese Medicine (TCM) hospitals in city from the perspective of service hospital leadership decision, , to monitor the development of the hospital running and to warn medical quality and the security issues, in order to provide ideas for promoting the coordinated development of the hospital, and strengthening scientific management. Subjects and Methods: Based on the study on Luoyang Orthopedics Hospital, we build Chinese Medicine Hospital monitoring and controlling framework of indicators through literature analysis and expert interviews, and use Delphi method for indicators screening. Results: Establish a monitoring and controlling index system for the public TCM Hospitals in city which includes 6 dimensions such as medical quality, hospital safety, characteristics Chinese medicine treatment, operational performance, innovation ability, human resources, 20 second-class indicators, and 72 third-class indicators. Discuss: The quantification and maneuverability of monitoring and controlling index system reflects the operational needs and characteristics of TCM Hospitals and conforms to the national reform orientation for public hospitals, which probably has important reference values in reinforcing the scientific management and evaluation of the public hospitals

In-plane graphene/boron-nitride heterostructures as an efficient metal-free electrocatalyst for the oxygen reduction reaction

Exploiting metal-free catalysts for the oxygen reduction reaction (ORR) and understanding their catalytic mechanisms are vital for the development of fuel cells (FCs). Our study has demonstrated that in-plane heterostructures of graphene and boron nitride (G/BN) can serve as an efficient metal-free catalyst for the ORR, in which the C-N interfaces of G/BN heterostructures act as reactive sites. The formation of water at the heterointerface is both energetically and kinetically favorable via a four-electron pathway. Moreover, the water formed can be easily released from the heterointerface, and the catalytically active sites can be regenerated for the next cycle. Since G/BN heterostructures with controlled domain sizes have been successfully synthesized in recent reports (e.g. Nat. Nanotechnol., 2013, 8, 119), our results highlight the great potential of such heterostructures as a promising metal-free catalyst for the ORR in FCs

Scaffolding Biomaterials for Cartilage Regeneration

Completely repairing of damaged cartilage is a difficult procedure. In recent years, the use of tissue engineering approach in which scaffolds play a vital role to regenerate cartilage has become a new research field. Investigating the advances in biological cartilage scaffolds has been regarded as the main research direction and has great significance for the construction of artificial cartilage. Native biological materials and synthetic polymeric materials have their advantages and disadvantages. The disadvantages can be overcome through either physical modification or biochemical modification. Additionally, developing composite materials, biomimetic materials, and nanomaterials can make scaffolds acquire better biocompatibility and mechanical adaptability

International economic policy of Iran, Pakistan and Kazakhstan within China ”Belt and Road” initiative

China’s “Belt and Road” Initiative is the most ambitious megaproject of the current international political economy. With this plan, China pursues economic growth goals, especially energy security, expanding its influence in various regions, accessing global markets, and creating more cost-effective communication and transportation systems. The idea of the project is to facilitate the supply of energy, goods and bring multiple parts of the globe closer to China. This article deals with the opportunities and challenges of cooperation between Iran, Pakistan, Kazakhstan, and China by relying on qualitative research methods such as document observation and analysis. In this regard, the main research question is what opportunities and challenges do the “Belt and Road” Initiative as China’s foreign policy strategy bring to Iran, Pakistan, and Kazakhstan? In response, the hypothesis raised to this research question is that this initiative, in addition to influencing the future of these three countries, could have positive geoeconomic consequences for them. This research notes that it can contribute to developing and deepening these countries’ relations with China by capacity building for regional dominance, simultaneously facilitating interaction with both East and West, diversifying the onshore and offshore routes and energy import bases, while also ensuring, facilitating, and enhancing energy transmission security for suppliers and consumers. Concerning the consequences for the region, it may assert China’s dominance over the geoeconomic structure of Iran, Pakistan, and Kazakhstan and intensify competition between Russia, India, and the U.S. in the region

Interactive Navigation in Environments with Traversable Obstacles Using Large Language and Vision-Language Models

This paper proposes an interactive navigation framework by using large language and vision-language models, allowing robots to navigate in environments with traversable obstacles. We utilize the large language model (GPT-3.5) and the open-set Vision-language Model (Grounding DINO) to create an action-aware costmap to perform effective path planning without fine-tuning. With the large models, we can achieve an end-to-end system from textual instructions like "Can you pass through the curtains to deliver medicines to me?", to bounding boxes (e.g., curtains) with action-aware attributes. They can be used to segment LiDAR point clouds into two parts: traversable and untraversable parts, and then an action-aware costmap is constructed for generating a feasible path. The pre-trained large models have great generalization ability and do not require additional annotated data for training, allowing fast deployment in the interactive navigation tasks. We choose to use multiple traversable objects such as curtains and grasses for verification by instructing the robot to traverse them. Besides, traversing curtains in a medical scenario was tested. All experimental results demonstrated the proposed framework's effectiveness and adaptability to diverse environments.Comment: Accepted by 2024 IEEE International Conference on Robotics and Automation (ICRA), 7 pages, 8 figure

Imprint of the stochastic nature of photon emission by electrons on the proton energy spectra in the laser-plasma interaction

The impact of stochasticity effects (SEs) in photon emissions on the proton energy spectra during laser-plasma interaction is theoretically investigated in the quantum radiation-dominated regime, which may facilitate SEs experimental observation. We calculate the photon emissions quantum mechanically and the plasma dynamics semiclassically via two-dimensional particle-in-cell simulations. An ultrarelativistic plasma generated and driven by an ultraintense laser pulse head-on collides with another strong laser pulse, which decelerates the electrons due to radiation-reaction effect and results in a significant compression of the proton energy spectra because of the charge separation force. In the considered regime the SEs are demonstrated in the shift of the mean energy of the protons up to hundreds of MeV. This effect is robust with respect to the laser and target parameters and measurable in soon available strong laser facilities