Development of event-driven optimal control for central air-conditioning systems

Event-driven optimal control was recently developed for central air-conditioning systems to speed up the response of optimal control to irregular changes in the system optioning conditions. In a time-driven paradigm usually, the optimization is carried out with a constant frequency, however the event-driven optimal control triggers optimization actions by events, which will be essentially defined to catch up with the irregular changes. Considering that the occurrence of events should imply the necessity to execute optimization, this paper investigates the necessity of optimization actions, based on which a new method to develop event-driven optimal control law is proposed. This can naturally lead to the establishment of an event-action map. This map indicates that not all the decision variables should be optimized when an eventoccurs, different from other methods that require optimizing all decision variables. The merits of the new method were also demonstrated using several case studies.<br

Circular RNA profile of infantile hemangioma by microarray analysis

<div><p>Background</p><p>Circular RNAs (circRNAs) are a recently identified class of noncoding RNAs that participate in several physiological processes. However, the expression of circRNAs in infantile hemangioma (IH) remains unknown.</p><p>Methods</p><p>The profile of circRNAs was assessed by microarray in four pairs of IH and adjacent skin tissues. The expression of circRNAs was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, circRNA-microRNAs (miRNA)-mRNA networks were constructed using bioinformatics tools.</p><p>Results</p><p>234 up- and 374 down- regulated circRNAs were identified in IH by microarray. Among them, the expression of two up-regulated circRNAs (hsa_circRNA_100933 and hsa_circRNA_100709) and one down-regulated circRNA (hsa_circRNA_104310) was confirmed by qRT-PCR. In addition, 3,019 miRNA response elements (MREs) of circRNAs were predicted, and two circRNA-miRNA-mRNA networks were constructed, including 100 and 94 target genes of hsa_circRNA_100933 and hsa_circRNA_104310, respectively. GO and pathway analysis showed that both networks participated in angiogenesis and vascular development-related biological processes.</p><p>Conclusions</p><p>This is the first study to reveal the profiling of circRNAs in IH and pave the way for further characterization of the role of circRNAs in the pathogenesis of IH.</p></div

Quantitative real-time PCR validation of selected circRNAs.

<p>The relative expression of selected circRNAs (circRNA_100709, circRNA_100933, circRNA_104310, circRNA_102116, circRNA_051239 and circRNA_102039) in IH as compared to paired skin samples.</p

Differential expression of circRNAs between IH and adjacent skin tissues by microarray.

<p>(A) Box plot showed that all the 8 samples were normalized. (B) Scatter-Plot was used for assessing the variation of circRNA expression between IH and adjacent skin tissues. The circRNAs above the top and below the bottom green lines indicated > 2.0-fold change in circRNAs between the two groups. (C) Volcano Plots were displayed for visualizing the differential expression of circRNAs. The red points in the plot represent the differentially expressed circRNAs with statistical significance. (D) Hierarchical cluster analysis of all the deregulated circRNAs.</p

Clinicopathological characteristics of IH patients.

<p>Clinicopathological characteristics of IH patients.</p

Top 25 up-regulated circRNAs in IH.

<p>Top 25 up-regulated circRNAs in IH.</p

Circular RNA profile of infantile hemangioma by microarray analysis - Fig 7

<p>GO (A) and pathway analysis (B) of hsa_circRNA_104310 targeted genes.</p

A snippet of detailed annotation for circRNA/miRNA interaction.

<p>(A) has_circRNA_100933. (B) has_circRNA_104310.</p

Top 25 down-regulated circRNAs in IH.

<p>Top 25 down-regulated circRNAs in IH.</p

Networks of circRNA-miRNA-mRNA in IH.

<p>(A) Hsa_circRNA_100933 with 5 MREs and 94 target genes. (B) Hsa_circRNA_104310 with 5 MREs and 100 target genes. Red represents up-regulation in IH, yellow represents down-regulation in IH, blue represents miRNAs, green represents mRNAs.</p