Chitosan and its derivatives such as low molecular weight chitosans (LMWCs) have been found to possess many important biological properties, such as antioxidant and antitumor effects. In our previous study, LMWCs were found to elicit a strong immunomodulatory response in macrophages dependent on molecular weight. Herein we further investigated the molecular weight-dependent immunostimulative activity of LMWCs and elucidated its mechanism of action on RAW264.7 macrophages. LMWCs (3 kDa and 50 kDa of molecular weight) could significantly enhance the mRNA expression levels of COX-2, IL-10 and MCP-1 in a molecular weight and concentration-dependent manner. The results suggested that LMWCs elicited a significant immunomodulatory response, which was dependent on the dose and the molecular weight. Regarding the possible molecular mechanism of action, LMWCs promoted the expression of the genes of key molecules in NF-κB and AP-1 pathways, including IKKβ, TRAF6 and JNK1, and induced the phosphorylation of protein IKBα in RAW264.7 macrophage. Moreover, LMWCs increased nuclear translocation of p65 and activation of activator protein-1 (AP-1, C-Jun and C-Fos) in a molecular weight-dependent manner. Taken together, our findings suggested that LMWCs exert immunostimulative activity via activation of NF-κB and AP-1 pathways in RAW264.7 macrophages in a molecular weight-dependent manner and that 3 kDa LMWC shows great potential as a novel agent for the treatment of immune suppression diseases and in future vaccines. Full article

Batteries are one of the most important components in many mechatronics systems, as they supply power to the systems and their failures may lead to reduced performance or even catastrophic results. Therefore, the prediction analysis of remaining useful life (RUL) of batteries is very important. This paper develops a quantitative approach for battery RUL prediction using an adaptive bathtub-shaped function (ABF). ABF has been utilised to model the normalised battery cycle capacity prognostic curves, which attempt to predict the remaining battery capacity with given historical test data. An artificial fish swarm algorithm method with a variable population size (AFSAVP) is employed as the optimiser for the parameter determination of the ABF curves, in which the fitness function is defined in the form of a coefficient of determination (R2). A 4 x 2 cross-validation (CV) has been devised, and the results show that the method can work valuably for battery health management and battery life prediction. Full article

A spatial approach that incorporates three economic components and one environmental factor has been developed to evaluate the dynamic behaviours of the rural areas at a provincial level. An artificial fish swarm algorithm with variable population size (AFSAVP) is proposed for the spatial problem. A functional region affecting index θ is employed as a fitness function for the AFSAVP driven optimisation, in which a gross domestic product (GDP) based method is utilised to estimate the CO₂ emission of all provinces. A simulation for the administrative provinces of China has been implemented, and the results have shown that the modelling method based on GDP data can assess the spatial dynamic behaviours and can be taken as an operational tool for the policy planners. Full article

As the rapid advance of digital imaging technologies, the content-based image retrieval (CBIR) has became one of the most vivid research areas in computer vision. In the last several years, developing computer-aided detection and/or diagnosis (CAD) schemes that use CBIR to search for the clinically relevant and visually similar medical images (or regions) depicting suspicious lesions has also been attracting research interest. CBIR-based CAD schemes have potential to provide radiologists with “visual aid” and increase their confidence in accepting CAD-cued results in the decision making. The CAD performance and reliability depends on a number of factors including the optimization of lesion segmentation, feature selection, reference database size, computational efficiency, and relationship between the clinical relevance and visual similarity of the CAD results. By presenting and comparing a number of approaches commonly used in previous studies, this article identifies and discusses the optimal approaches in developing CBIR-based CAD schemes and assessing their performance. Although preliminary studies have suggested that using CBIR-based CAD schemes might improve radiologists’ performance and/or increase their confidence in the decision making, this technology is still in the early development stage. Much research work is needed before the CBIR-based CAD schemes can be accepted in the clinical practice. Full article