Modelling the thermal dynamics of buildings: a latent force model based approach

Minimizing the energy consumed on heating, ventilation and air conditioning (HVAC) systems of residential buildings, without impacting occupants’ comfort has been highlighted as an important artificial intelligence (AI) challenge. Typically, approaches that seek to address this challenge use a model that captures the thermal dynamics within a building, also referred to as a thermal model. In this paper, we introduce a novel thermal model, which we refer to as a latent force thermal model of the thermal dynamics of a building or LFM-TM. Our model is derived from an existing grey-box thermal model, which is augmented with an extra term referred to as the learned residual. This term is capable of modelling the effect of any a priori unknown additional dynamic, which if not captured, appears as structure in a thermal models residual (the error induced by the model). More importantly, the learned residual can also capture the effects of physical elements such as a building’s envelope or the lags in a heating system, leading to a significant reduction in complexity compared to existing models. We evaluate the performance of LFM-TM on two independent data sources: the FlexHouse data, which was previously used for evaluating the efficacy of existing grey-box models [Bacher and Madsen 2011], and heating data logged within homes located on University of Southampton campus. On both datasets, we show that our approach outperforms existing models in its ability to accurately fit the observed data, generate accurate day-ahead internal temperature predictions and explain a large amount of the variability in the future observations

The emerging role of MCPH1/BRIT1 in carcinogenesis

The MCPH1 gene, also known as BRCT-repeat inhibitor of hTERT expression (BRIT1), has three BRCA1 carboxyl-terminal domains which is an important regulator of DNA repair, cell cycle checkpoints and chromosome condensation. MCPH1/BRIT1 is also known as a tumour suppressor in different types of human cancer. The expression level of the MCPH1/BRIT1 gene is decreased at the DNA, RNA or protein level in a number of types of cancers including breast cancer, lung cancer, cervical cancer, prostate cancer and ovarian cancer compared to normal tissue. This review also showed that deregulation of MCPH1/BRIT1 is significantly associated with reduced overall survival in 57% (12/21) and relapsed free survival in 33% (7/21) of cancer types especially in oesophageal squamous cell carcinoma and renal clear cell carcinoma. A common finding of this study is that the loss of MCPH1/BRIT1 gene expression plays a key role in promoting genome instability and mutations supporting its function as a tumour suppressor gene