Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations

Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems. Most recent works primarily focus on using advanced natural language processing techniques to extract semantic information from rich textual data, employing content-based methods derived from local historical news. However, this approach lacks a global perspective, failing to account for users' hidden motivations and behaviors beyond semantic information. To address this challenge, we propose a novel model called GLORY (Global-LOcal news Recommendation sYstem), which combines global representations learned from other users with local representations to enhance personalized recommendation systems. We accomplish this by constructing a Global-aware Historical News Encoder, which includes a global news graph and employs gated graph neural networks to enrich news representations, thereby fusing historical news representations by a historical news aggregator. Similarly, we extend this approach to a Global Candidate News Encoder, utilizing a global entity graph and a candidate news aggregator to enhance candidate news representation. Evaluation results on two public news datasets demonstrate that our method outperforms existing approaches. Furthermore, our model offers more diverse recommendations.Comment: 10 pages, Recsys 202

Postmortem and ex vivo carbon monoxide ventilation reduces injury in rat lungs transplanted from non–heart-beating donors

OBJECTIVE: We sought to determine whether ventilation of lungs after death in non-heart-beating donors with carbon monoxide during warm ischemia and ex vivo lung perfusion and after transplant would reduce ischemia-reperfusion injury and improve lung function. METHODS: One hour after death, Sprague-Dawley rats were ventilated for another hour with 60% oxygen (control group) or 500 ppm carbon monoxide in 60% oxygen (CO-vent group; n=6/group). Then, lungs were flushed with 20 mL cold Perfadex, stored cold for 1 hour, then warmed to 37 °C in an ex vivo lung perfusion circuit perfused with Steen solution. At 37 °C, lungs were ventilated for 15 minutes with alveolar gas with or without 500 ppm carbon monoxide, then perfusion-cooled to 20 °C, flushed with cold Perfadex and stored cold for 2 hours. The left lung was transplanted using a modified cuff technique. Recipients were ventilated with 60% oxygen with or without carbon monoxide. One hour after transplant, we measured blood gases from the left pulmonary vein and aorta, and wet-to-dry ratio of both lungs. The RNA and protein extracted from graft lungs underwent real-time polymerase chain reaction and Western blotting, and measurement of cyclic guanosine monophosphate by enzyme-linked immunosorbent assay. RESULTS: Carbon monoxide ventilation begun 1 hour after death reduced wet/dry ratio after ex vivo lung perfusion. After transplantation, the carbon monoxide-ventilation group had better oxygenation; higher levels of tissue cyclic guanosine monophosphate, heme oxidase-1 expression, and p38 phosphorylation; reduced c-Jun N-terminal kinase phosphorylation; and reduced expression of interleukin-6 and interleukin-1β messenger RNA. CONCLUSIONS: Administration of carbon monoxide to the deceased donor and non-heart-beating donor lungs reduces ischemia-reperfusion injury in rat lungs transplanted from non-heart-beating donors. Therapy to the deceased donor via the airway may improve post-transplant lung function

Research on dynamic stress and excess pore water pressure of asphalt pavement under hydraulic-mechanical coupling

The impact of the initial static stress field on dynamic calculation results was considered, a three-dimensional refined coupling system model was constructed using finite element software, and the time domain and space domain distribution laws of dynamic stress and excess pore water pressure of saturated asphalt pavement under moving load were investigated.The findings show that the influence of the initial static stress field on the pavement dynamic calculation results will increase as the pavement depth increases. On the bottom surface of the upper layer, when the initial static stress field is not considered, the errors in vertical dynamic stress and excess pore water pressure are 29.6% and 30.8% respectively. As compared to dry pavement, the tensile stress on saturated asphalt pavement increases, and the stress attenuation rate slows when the load passes, putting the pavement structure in an undesirable situation. The negative peak value of the hydrodynamic pressure in the higher layer drops linearly as the permeability coefficient of the upper layer increases. In contrast, the negative peaking of the vertical dynamic stress grows linearly. Under the situation of potholes, the dynamic stress components in six directions of the saturated asphalt pavement all rise dramatically. Among the three shear stress components, τyz increases the most under the condition of pavement pothole, which is 345% higher than that without pothole. Among the three normal stress components, the vertical dynamic stress has the largest increase, which is 156% higher than that without potholes, and the increase in shear failure of the pavement is greater than that of tensile failure. The research findings will be helpful in determining the degradation process of saturated asphalt pavement and in designing asphalt pavement structures in rainy areas

Study on connection and properties of green assembled building steel structures

In order to meet the research and industrialization application needs of green building integration technology and key technology of green building envelope structure in affordable housing projects, the effects of laser power and welding speed on the forming quality, microstructure and hardness of welded joints of heterogeneous steels with unequal thickness in steel structures were studied. The results showed that, for the front weld width, the influence of laser power on the back weld width is more obvious, and the influence of welding speed on the back weld width is greater than that of the front weld width. With the increase of laser power, coarse lath martensite and ferrite are formed in laser welded joints; with the increase of welding speed, heat input decreases, heat dissipation speed increases, grain growth time shortens, and grain refinement occurs. With the increase of laser power and welding speed, the tensile strength of laser welded joint has little change compared with base metal, but the elongation of welded joint is lower than that of base metal. With the increase of laser power, the fracture position of welded joint will shift from base metal to heat-affected softening zone. With the increase of welding speed, the fracture position of welded joint will shift from heat-affected softening zone to base metal. The suitable laser power for HC550/DP780 heterogeneous steel plate is 1.2 KW and the welding speed is 2400 mm/min. At this time, the welded joint has good welding forming quality, the hardness of weld zone is high and there is no softening point in heat affected zone. Keywords: Green building, Unequal thickness heterostructure steel, Connection technology, Propert

Automatic Detection of Rice Blast Fungus Spores by Deep Learning-Based Object Detection: Models, Benchmarks and Quantitative Analysis

The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen inoculum. Traditional spore detection methods mostly rely on manual feature extraction and shallow machine learning models, and are mostly designed for the indoor counting of a single spore class, which cannot handle the interference of impurity particles in the field. This study achieved automatic detection of rice blast fungus spores in the mixture with other fungal spores and rice pollens commonly encountered under field conditions by using deep learning based object detection techniques. First, 8959 microscopic images of a single spore class and 1450 microscopic images of mixed spore classes, including the rice blast fungus spores and four common impurity particles, were collected and labelled to form the benchmark dataset. Then, Faster R-CNN, Cascade R-CNN and YOLOv3 were used as the main detection frameworks, and multiple convolutional neural networks were used as the backbone networks in training of nine object detection algorithms. The results showed that the detection performance of YOLOv3_DarkNet53 is superior to the other eight algorithms, and achieved 98.0% mean average precision (intersection over union > 0.5) and an average speed of 36.4 frames per second. This study demonstrated the enormous application potential of deep object detection algorithms in automatic detection and quantification of rice blast fungus spores

Application of Machine Learning to Assist a Moisture Durability Tool

The design of moisture-durable building enclosures is complicated by the number of materials, exposure conditions, and performance requirements. Hygrothermal simulations are used to assess moisture durability, but these require in-depth knowledge to be properly implemented. Machine learning (ML) offers the opportunity to simplify the design process by eliminating the need to carry out hygrothermal simulations. ML was used to assess the moisture durability of a building enclosure design and simplify the design process. This work used ML to predict the mold index and maximum moisture content of layers in typical residential wall constructions. Results show that ML, within the constraints of the construction, including exposure conditions, does an excellent job in predicting performance compared to hygrothermal simulations with a coefficient of determination, R2, over 0.90. Furthermore, the results indicate that the material properties of the vapor barrier and continuous insulation layer are strongly correlated to performance