Multi-Objective Optimal Design of a Building Envelope and Structural System Using Cyber-Physical Modeling in a Wind Tunnel

This paper explores the use of a cyber-physical systems (CPS) “loop-in-the-model” approach to optimally design the envelope and structural system of low-rise buildings subject to wind loads. Both the components and cladding (C&C) and the main wind force resisting system (MWFRS) are considered through multi-objective optimization. The CPS approach combines the physical accuracy of wind tunnel testing and efficiency of numerical optimization algorithms to obtain an optimal design. The approach is autonomous: experiments are executed in a boundary layer wind tunnel (BLWT), sensor feedback is monitored and analyzed by a computer, and optimization algorithms dictate physical changes to the structural model in the BLWT through actuators. To explore a CPS approach to multi-objective optimization, a low-rise building with a parapet wall of variable height is considered. In the BLWT, servo-motors are used to adjust the parapet to a particular height. Parapet walls alter the location of the roof corner vortices, reducing suction loads on the windward facing roof corners and edges, a C&C design load. At the same time, parapet walls increase the surface area of the building, leading to an increase in demand on the MWFRS. A combination of non-stochastic and stochastic optimization algorithms were implemented to minimize the magnitude of suction and positive pressures on the roof of a low-rise building model, followed by stochastic multi-objective optimization to simultaneously minimize the magnitude of suction pressures and base shear. Experiments were conducted at the University of Florida Experimental Facility (UFEF) of the National Science Foundation’s (NSF) Natural Hazard Engineering Research Infrastructure (NHERI) program

Hyper-phosphorylation of Rb S249 together with CDK5R2/p39 overexpression are associated with impaired cell adhesion and epithelial-to-mesenchymal transition: Implications as a potential lung cancer grading and staging biomarker.

Prediction of lung cancer metastasis relies on post-resection assessment of tumor histology, which is a severe limitation since only a minority of lung cancer patients are diagnosed with resectable disease. Therefore, characterization of metastasis-predicting biomarkers in pre-resection small biopsy specimens is urgently needed. Here we report a biomarker consisting of the phosphorylation of the retinoblastoma protein (Rb) on serine 249 combined with elevated p39 expression. This biomarker correlates with epithelial-to-mesenchymal transition traits in non-small cell lung carcinoma (NSCLC) cells. Immunohistochemistry staining of NSCLC tumor microarrays showed that strong phospho-Rb S249 staining positively correlated with tumor grade specifically in the squamous cell carcinoma (SCC) subtype. Strong immunoreactivity for p39 positively correlated with tumor stage, lymph node invasion, and distant metastases, also in SCC. Linear regression analyses showed that the combined scoring for phospho-Rb S249, p39 and E-cadherin in SCC is even more accurate at predicting tumor staging, relative to each score individually. We propose that combined immunohistochemistry staining of NSCLC samples for Rb phosphorylation on S249, p39, and E-cadherin protein expression could aid in the assessment of tumor staging and metastatic potential when tested in small primary tumor biopsies. The intense staining for phospho-Rb S249 that we observed in high grade SCC could also aid in the precise sub-classification of poorly differentiated SCCs