Biophilic architecture: a review of the rationale and outcomes

Contemporary cities have high stress levels, mental health issues, high crime levels and ill health, while the built environment shows increasing problems with urban heat island effects and air and water pollution. Emerging from these concerns is a new set of design principles and practices where nature needs to play a bigger part called “biophilic architecture”. This design approach asserts that humans have an innate connection with nature that can assist to make buildings and cities more effective human abodes. This paper examines the evidence for this innate human psychological and physiological link to nature and then assesses the emerging research supporting the multiple social, environmental and economic benefits of biophilic architecture

Identification of Surface Deformation in InSAR Using Machine Learning

Abstract The availability and frequency of synthetic aperture radar (SAR) imagery are rapidly increasing. This surge of data presents new opportunities to constrain surface deformation that spans various spatial and temporal scales. This expansion also introduces common challenges associated with large volumes of data, including best practices for analyzing these data. In recent years, machine learning techniques have been at the forefront of big data challenges, as an efficient methodology for automatically classifying large volumes of data. Convolutional Neural Networks (CNNs), in particular, have achieved strong levels of performance on image classification problems. Here we present SarNet, a CNN developed to detect, locate, and classify the presence of co‐seismic‐like surface deformation within an interferogram. We trained SarNet using 4 × 106 synthetic interferograms, including both wrapped and unwrapped forward modeled co‐seismic‐like surface deformation with synthetic noise representative of the atmospheric and topographic noise found in interferograms. The results show that SarNet obtains an overall accuracy of 99.74% on a validation data set. We use class activation maps (CAMs) to show that SarNet returns the location of surface deformation within the interferogram. We employ a transfer learning method to translate the accuracy of SarNet trained on synthetic data to real interferograms with manually classified co‐seismic surface displacement. We train SarNet on 32 interferograms containing labeled co‐seismic surface deformation as well as noise. The results show that, through transfer learning, SarNet obtains an overall accuracy of 85.22% on a real InSAR data set, and that SarNet returns the location of the surface deformation within the interferogram

Congenital end-plate acetylcholinesterase deficiency caused by a nonsense mutation and an A-->G splice-donor-site mutation at position +3 of the collagenlike-tail-subunit gene (COLQ): how does G at position +3 result in aberrant splicing?

Congenital end-plate acetylcholinesterase (AChE) deficiency (CEAD), the cause of a disabling myasthenic syndrome, arises from defects in the COLQ gene, which encodes the AChE triple-helical collagenlike-tail subunit that anchors catalytic subunits of AChE to the synaptic basal lamina. Here we describe a patient with CEAD with a nonsense mutation (R315X) and a splice-donor-site mutation at position +3 of intron 16 (IVS16+3A-->G) of COLQ. Because both A and G are consensus nucleotides at the +3 position of splice-donor sites, we constructed a minigene that spans exons 15-17 and harbors IVS16+3A-->G for expression in COS cells. We found that the mutation causes skipping of exon 16. The mutant splice-donor site of intron 16 harbors five discordant nucleotides (at -3, -2, +3, +4, and +6) that do not base-pair with U1 small-nuclear RNA (snRNA), the molecule responsible for splice-donor-site recognition. Versions of the minigene harboring, at either +4 or +6, nucleotides complementary to U1 snRNA restore normal splicing. Analysis of 1,801 native splice-donor sites reveals that presence of a G nucleotide at +3 is associated with preferential usage, at positions +4 to +6, of nucleotides concordant to U1 snRNA. Analysis of 11 disease-associated IVS+3A-->G mutations indicates that, on average, two of three nucleotides at positions +4 to +6 fail to base-pair, and that the nucleotide at +4 never base-pairs, with U1 snRNA. We conclude that, with G at +3, normal splicing generally depends on the concordance that residues at +4 to +6 have with U1 snRNA, but other cis-acting elements may also be important in assuring the fidelity of splicing

Ambient but not incremental oxidant generation effects intercellular adhesion molecule 1 induction by tumour necrosis factor α in endothelium

Proinflammatory cytokines upregulate endothelial adhesion molecule expression, thereby initiating the microvascular inflammatory response. We re-evaluated the reported role of reactive oxygen metabolites (ROMs) in signalling upregulation of intercellular adhesion molecule 1 (ICAM-1) on endothelial cells by tumour necrosis factor alpha (TNF-alpha) in vitro. TNF-alpha upregulation of endothelial-cell ICAM-1 expression was inhibited by the cell-permeable antioxidants, or by the adenovirus-mediated intracellular overexpression of Cu,Zn-superoxide dismutase, but not by the exogenous (extracellular) administration of the cell-impermeable antioxidants, superoxide dismutase and/or catalase. This ICAM-1 upregulation was also inhibited by inhibitors of NADH dehydrogenase, cytochrome bc1 complex and NADPH oxidase. However, a measurable increase in net cellular ROM generation in response to TNF-alpha was not seen using four disparate sensitive ROM assays. Moreover, the stimulation of exogenous or endogenous ROM generation did not upregulate ICAM-1, nor enhance ICAM-1 upregulation by TNF-alpha. These findings suggest that an ambient background flux of ROMs, generated intracellularly, but not their net incremental generation, is necessary for TNF-alpha to induce ICAM-1 expression in endothelium in vitro