Optimization of Controller Parameters for Energy Saving

Among various technologies to tackle the twin challenges of sustainable energy supply and climate change, energy saving through advanced control plays a crucial role in decarbonizing the whole energy system. Modern control technologies, such as optimal control and model predictive control do provide a framework to simultaneously regulate the system performance and limit control energy. However, few have been done so far to exploit the full potential of controller design in reducing the energy consumption while maintaining desirable system performance. This paper investigates the correlations between control energy consumption and system performance using two popular control approaches widely used in the industry, namely the PI control and subspace model predictive control. Our investigation shows that the controller design is a delicate synthesis procedure in achieving better trade-o between system performance and energy saving, and proper choice of values for the control parameters may potentially save a significant amount of energy

Immune-derived PD-L1 gene expression defines a subgroup of stage II/III colorectal cancer patients with favorable prognosis that may be harmed by adjuvant chemotherapy

A recent phase 2 study of metastatic colorectal carcinoma (CRC) patients showed that mismatch repair gene status was predictive of clinical response to PD-1-targeting immune checkpoint blockade. Further examination revealed strong correlation between PD-L1 protein expression and microsatellite instability (MSI) in stage IV CRC, suggesting that the amount of PD-L1 protein expression could identify late stage patients who may benefit from immunotherapy. To assess whether the clinical associations between PD-L1 gene expression and MSI identified in metastatic CRC are also present in stage II/III CRC, we used in silico analysis to elucidate the cell types expressing the PD-L1 gene. We found a significant association of PD-L1 gene expression with MSI in early stage CRC (P < 0.001) and show that unlike in non-CRC tumors, PD-L1 is derived predominantly from the immune infiltrate. We demonstrate that PD-L1 gene expression has positive prognostic value in the adjuvant disease setting (PD-L1low v PD-L1high HR = 9.09; CI, 2.11-39.10). PD-L1 gene expression had predictive value, as patients with high PD-L1 expression appear to be harmed by standard-of-care treatment (HR = 4.95; CI,1.10-22.35). Building on the promising results from the metastatic CRC PD-1-targeting trial, we provide compelling evidence that PD-L1high/MSI/immunehigh stage II/III CRC patients should not receive standard chemotherapy. This conclusion supports the rationale to clinically evaluate this patient subgroup for PD-1 blockade treatment.