Thermal degradation behaviours, VOCs emission characteristics, and environmental impacts during pyrolysis recycling of waste enamelled wires.

Waste enamelled wires represent a significant secondary copper resource, often processed through pyrolysis for material recovery. However, the release of VOCs during pyrolysis poses environmental challenges. This study investigated the thermal degradation behaviour and VOCs emission characteristics of waste enamelled wires during pyrolysis.

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well as many other processes. Surprisingly, lncRNA has an inseparable relationship with human diseases such as cancer. Therefore, only by knowing more about the function of lncRNA can we better solve the problems of human diseases.

A path-based computational model for long non-coding RNA-protein interaction prediction.

Recently, lncRNAs have attracted accumulating attentions because more and more experimental researches have shown lncRNA can play critical roles in many biological processes. Predicting potential interactions between lncRNAs and proteins are key to understand the lncRNAs biological functions. But traditional biological experiments are expensive and time-consuming, network similarity methods provide a powerful solution to computationally predict lncRNA-protein interactions.

Predicting human disease-associated circRNAs based on locality-constrained linear coding.

Circular RNAs (circRNAs) are a new kind of endogenous non-coding RNAs, which have been discovered continuously. More and more studies have shown that circRNAs are related to the occurrence and development of human diseases. Identification of circRNAs associated with diseases can contribute to understand the pathogenesis, diagnosis and treatment of diseases.

Integrating Bipartite Network Projection and KATZ Measure to Identify Novel CircRNA-Disease Associations.

Accumulating biological experiments have shown that circRNAs are closely related to the occurrence and development of many complex human diseases. During recent years, the associations of circRNA with disease have caused more and more researchers to pay attention and to analyze their correlation mechanisms. However, experimental methods for determining the associations of circRNA with a particular disease are still expensive, difficult, and time consuming.