Improving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference

One of the major challenges in coreference resolution is how to make use of entity-level features defined over clusters of mentions rather than mention pairs. However, coreferent mentions usually spread far apart in an entire text, which makes it extremely difficult to incorporate entity-level features. We propose a graph neural network-based coreference resolution method that can capture the entity-centric information by encouraging the sharing of features across all mentions that probably refer to the same real-world entity. Mentions are linked to each other via the edges modeling how likely two linked mentions point to the same entity. Modeling by such graphs, the features between mentions can be shared by message passing operations in an entity-centric manner. A global inference algorithm up to second-order features is also presented to optimally cluster mentions into consistent groups. Experimental results show our graph neural network-based method combing with the second-order decoding algorithm (named GNNCR) achieved close to state-of-the-art performance on the English CoNLL-2012 Shared Task dataset

A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources

Federated learning is an appealing framework for analyzing sensitive data from distributed health data networks due to its protection of data privacy. Under this framework, data partners at local sites collaboratively build an analytical model under the orchestration of a coordinating site, while keeping the data decentralized. However, existing federated learning methods mainly assume data across sites are homogeneous samples of the global population, hence failing to properly account for the extra variability across sites in estimation and inference. Drawing on a multi-hospital electronic health records network, we develop an efficient and interpretable tree-based ensemble of personalized treatment effect estimators to join results across hospital sites, while actively modeling for the heterogeneity in data sources through site partitioning. The efficiency of our method is demonstrated by a study of causal effects of oxygen saturation on hospital mortality and backed up by comprehensive numerical results

A Novel Distributed Secondary Coordination Control Approach for Islanded Microgrids

This paper develops a new distributed secondary cooperative control scheme to coordinate distributed generators (DGs) in islanded microgrids (MGs). A finite time frequency regulation strategy containing a consensus-based distributed active power regulator is presented, which can not only guarantee the active power sharing but also enable all DGs' frequencies to converge to the reference value within a finite time. This enables the frequency and voltage control designs to be separated. Then an observer-based distributed voltage regulator involving certain reactive power sharing constraints is proposed, which allows different set points for different DGs and, thus, accounts for the line impedance effects. The steady-state performance analysis shows that the voltage regulator can accurately address the issue of global voltage regulation and accurate reactive power sharing. Moreover, all the distributed controllers are equipped with bounded control inputs to suppress the transient overshoot, and they are implemented through sparse communication networks. The effectiveness of the control in case of load variation, plug-and-play capability, communication topology change, link failure, time delays, and data drop-out are verified by the simulation of an islanded MG in MATLAB/SimPowerSystems

Ubiquitous conservative interaction patterns between post-spliced introns and their mRNAs revealed by genome-wide interspecies comparison

Introns, as important vectors of biological functions, can influence many stages of mRNA metabolism. However, in recent research, post-spliced introns are rarely considered. In this study, the optimal matched regions between introns and their mRNAs in nine model organism genomes were investigated with improved Smith–Waterman local alignment software. Our results showed that the distributions of mRNA optimal matched frequencies were highly consistent or universal. There are optimal matched frequency peaks in the UTR regions, which are obvious, especially in the 3′-UTR. The matched frequencies are relatively low in the CDS regions of the mRNA. The distributions of the optimal matched frequencies around the functional sites are also remarkably changed. The centers of the GC content distributions for different sequences are different. The matched rate distributions are highly consistent and are located mainly between 60% and 80%. The most probable value of the optimal matched segments is about 20 bp for lower eukaryotes and 30 bp for higher eukaryotes. These results show that there are abundant functional units in the introns, and these functional units are correlated structurally with all kinds of sequences of mRNA. The interaction between the post-spliced introns and their corresponding mRNAs may play a key role in gene expression

Teachers’ and Students’ Views of Using an AI-Aided Educational Platform for Supporting Teaching and Learning at Chinese Schools

In Chinese schools in less advanced places, there is an urgent need to improve the quality of education and educational equity. This study aims to investigate how an AI-aided educational platform can be used to provide additional teaching and learning resources to serve this need. The AI-aided educational platform used in this study is called Smart-Learning Partner (SLP), which is based on AI technology to provide new opportunities for personalized learning and more educational resources. A qualitative research method was applied in this study. We interviewed and surveyed 98 students and 32 teachers at 9 Chinese schools located in less developed areas. We used content analysis to interpret the findings based on students’ and teachers’ experiences of using the SLP platform. The data demonstrated that this kind of AI-aided educational platform was viewed by students and teachers as a useful tool in students’ learning and teachers’ work. It provided additional possibilities to students and teachers with its rich assessment tools, personalized and overall student learning analysis reports, plentiful high-quality mini-lecture videos, and recommendations from the platform based on the students’ needs for further enhancement study. However, challenges still exist. Adequate electronic devices for students are needed, especially in schools in less developed areas. Students and teachers called for user-friendly interfaces and features, social interaction aspects, and gamification mechanisms with recent online learning platforms. We conclude that based on the teachers’ and students’ views, AI-aided education platforms are useful tools for supporting teaching and learning in Chinese school

Multi-temporal Monitoring for Road Slope Collapse by Means of LUTAN-1 SAR Data and High Resolution Optical Data

Collapse is one of the most destructive natural disaster, being sudden, frequent, and highly concealed, causing large-scale damage. On August 10, 2023, the slope of 108 national highway in Weinan, Shaanxi Province collapsed. The lower edge of the collapse slope body is the Luohe river, and the collapse body rushes into the river to form a barrier lake. Remote sensing technique can provide multiple dimensional information for disaster emergency and management. Lutan-1 SAR satellites are the first group L-band SAR constellation for multiple applications in China. Owing to the precise orbit control ability and high revisit characteristics for Lutan-1 SAR satellites, surface deformation monitoring with centimeter even millimeter accuracy may be achieved. Based on the multi-temporal pre-disaster and post-disaster Lutan-1 SAR data and high resolution optical data, the collapse information including the pre-disaster and post-disaster were extracted and analysed. From July 11 to 27, 2023, the pre-collapse deformation was obtained with the maximum value of 6 cm, and obvious deformation occurred before the collapse. Lutan-1 monitored results pre-collapse can provide certain information for disaster early identification. From July 27 to August 24, 2023, due to the serious incoherence caused by large deformation and ground changes, effective deformation information cannot be obtained based on the InSAR technique. In addition, the collapse information was clearly extracted by the high resolution optical data acquired pre-collapse and post collapse. After the collapse, significant deformation was extracted from August 24 to September 21 with the maximum value of 6 cm, indicating that obvious deformation still occurred over the collapse area. Through the analysis for the series results obtained by SAR and optical data, it is favourable for disaster emergency and management

Experimental Study on Thermal Performance of Externally Insulated Walls of Intermittent Air-Conditioned Rooms in Summer in Hot Summer and Cold Winter Region, China

Now requirements for the thermal performance of building walls are based on the assumption that heat flux transfers in one direction through the wall. However, in Hot Summer and Cold Winter Region of China, the direction of heat flow in the wall not only changes with the seasons, but also changes in the same period of using. In this paper, dynamic thermal process of externally insulated walls in different air-conditioner’s running state in summer in Chongqing, China, was tested. The distribution characteristics of the outdoor and indoor air temperature and the surface and inner temperatures of the wall were analyzed and demonstrated. Based on the unsteady-state heat transfer theory, the study calculated and analyzed the distribution characteristics of the direction of the heat flux in the thermal process. Also the characteristics of insulation and heat preservation for walls under different air-conditioner’s running state were analyzed. It is shown that, in any air-conditioner’s running state, the direction of the heat flux through the wall is obviously dynamically changing. There is obvious difference in the thermal performance needs of the wall; that is, it has strong demand for thermal insulation in daytime and strong demand for heat dissipation during night time in summer