Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories single agents, yet it remains open question to jointly predict scene compliant over multiple agents. The challenge due exponentially increasing prediction space as a function the number In this work, we exploit underlying relations between interacting agents and decouple joint problem into problems. Our proposed approach M2I...

Aberrant expression or function of epidermal growth factor receptor (EGFR) the closely related human 2 (HER2) can promote cell proliferation and survival, thereby contributing to tumorigenesis. Specific antibodies low-molecular-weight tyrosine kinase inhibitors both proteins are currently in clinical trials for cancer treatment. Benzimidazole derivatives possess diverse biological activities, including antitumor activity. However, anticancer mechanism 5a (a 2-aryl benzimidazole compound;...

Interactive traffic simulation is crucial to autonomous driving systems by enabling testing for planners in a more scalable and safe way compared real-world road testing. Existing approaches learn an agent model from large-scale data simulate realistic scenarios, yet it remains open question produce consistent diverse multi-agent interactive behaviors crowded scenes. In this work, we present InterSim, simulator planners. Given test plan trajectory the ego agent, InterSim reasons about...

In autonomous driving, goal-based multi-trajectory prediction methods are proved to be effective recently, where they first score goal candidates, then select a final set of goals, and finally complete trajectories based on the selected goals. However, these usually involve predictions sparse predefined anchors. this work, we propose an anchor-free model, named DenseTNT, which performs dense probability estimation for trajectory prediction. Our model achieves state-of-the-art performance,...

Reprogramming Tumor-Associated Macrophages In article number 2108971, Zhen Li and co-workers find that ultra-small Cu2−xSe nanoparticles can effectively polarize tumor-associated macrophages (TAMs) from the tumor-supportive M2 phenotype into anti-tumor M1 to significantly boost immunity through a novel mechanism. The generate reactive oxygen species trigger polarization ROS-TRAF6-IRF5-IL-23 signaling pathway, rather than classic ROS-NF-?B-iNOS pathway.

With the widespread application of asphalt pavement in highway construction China, especially hot and humid areas like Guangdong Guangxi, this type faces challenges such as softening, rutting, accelerated aging under high temperatures moist conditions. Traditional evaluation models have limitations these specific environments. This study proposes a new performance model using Self-Organizing Map (SOM) Random Forest (RF) algorithms, re-evaluating optimizing weight indicators based on actual...

The contradiction between ecological resource protection and urban sprawl in agglomeration areas is becoming more prominent, facing a serious imbalance the supply demand of ecosystem services. To analyze impact expansion on regional services, based multi-source data, an assessment model services for water conservation, carbon sequestration, soil conservation crop production was constructed. With help value transformation spatial analysis method, this paper explores risk service faced by...

Predicting future behaviors of road agents is a key task in autonomous driving. While existing models have demonstrated great success predicting marginal agent behaviors, it remains challenge to efficiently predict consistent joint multiple agents. Recently, the occupancy flow fields representation was proposed represent states through combination grid and flow, which supports efficient predictions. In this work, we propose novel predictor produce accurate predictions, by combining power an...

Health monitoring and degradation detection systems help to address problems at an earlier stage reduce maintenance costs. A vehicle problem is characterized by high bandwidth vibration signals oil data that allow one diagnose a wide variety of failures from relatively few measurements. Reliable health require the integration research in diverse fields instrumentation, acquisition/storage, signal processing, approximate reasoning, feature extraction techniques multi-sensor fusion. Data...

Pavement quality evaluation is important for pavement maintenance and the basis investment decisions. With use of asphalt pavements on highways, road problems are becoming increasingly serious. This paper introduces prediction analyzes methods in terms damage degree, smoothness, gauge, strength. Based this, a based machine learning, SVM, other techniques established, comprehensive model set performance teaching materials, training label determination method proposed to highlight importance...

Motion prediction is crucial in enabling safe motion planning for autonomous vehicles interactive scenarios. It allows the planner to identify potential conflicts with other traffic agents and generate plans. Existing predictors often focus on reducing errors, yet it remains an open question how well they help planner, which are critical safety of vehicles. In this paper, we evaluate state-of-the-art through novel conflict-related metrics, such as success rate identifying conflicts....

Because of using relational database, there exists difficulty in real-time data processing and analysis traditional transformer substation hotspot monitoring system. And even some important functions are not implemented, such as alarm statistics. In this regard, paper introduces database to transform the The use achieves fast storage temperature data, well intelligent analysis. external display also achieved, which strengthens safety management substation.

Abstract It is significant to evaluate the air quality scientifically for management of pollution. As an comprehensive evaluation problem, its uncertainty can be effectively addressed by Dempster–Shafer (D–S) evidence theory. However, there not enough research on assessment using D–S Aiming at counterintuitive fusion results combination rule in field decision, improved theory with weight and decision credibility (here namely DCre-Weight method) proposed, it used comprehensively quality....

An oblate solid cylinder damping material specimen is used to construct three systems with different additional masses. The excited by an electromagnetic shaker in the vertical direction, and excites mass vibrating. properties of change as exciting magnitude change. Not only traditional properties, such ratio, vibration transfer rate from excitation mass, resonant frequency, but also nonlinear system masses are measured evaluate specimen. magnitude-frequency characteristics under constant...

Modern warfare is mainly based on the joint operation of multiple armies, but there exists phenomenon information chimney in different armed services and it can hardly realize sharing existed command control system. In this paper, a new method battlefield target ontology proposed. Firstly, detection databases navy, army air are converted to resource description framework (RDF); Secondly, mapping used for RDF alignment information; Finally, using SPARQL query shared verify effectiveness...

This paper proposes a distributed data clustering technique based on deep neural network.First, each record in the database is taken as an input vector, and its characteristics are extracted to layer of depth network.The weight connection trained by BP algorithm, training network output realized adjusting weight.Finally, results judged according similarity current vector corresponding data.Experimental small-scale systems show that this method has better test set accuracy than traditional...

Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories single agents, yet it remains open question to jointly predict scene compliant over multiple agents. The challenge due exponentially increasing prediction space as a function the number In this work, we exploit underlying relations between interacting agents and decouple joint problem into problems. Our proposed approach M2I...

Facing the network security problem of power monitoring system, this paper studies knowledge graph-based extraction and management method. In entity recognition module, an algorithm based on idea multi task learning is adopted, which decomposes process into boundary perception classification to reduce impact error accumulation. Meanwhile, introduction comprehensive description information categories tasks can not only be widely used in general fields, but also targeted specific scenes field...