Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes. © 2021, The Author(s).Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

“Rapunzel, Rapunzel, Lanza Tu Pelo”: Storytelling in a Transcultural, Translanguaging Dialogic Exchange

In this study, we examined story circles to understand how the small‐group activity supports and shapes the storytelling of young students in multicultural, multilingual preschool classrooms. Through a representative example, we show how language development unfolds in the context of a transcultural and translanguaging dialogic exchange of stories. We describe features of increasing linguistic complexity present in students’ storytelling as they established affinity‐affirming connections over ideas, shared ways of languaging, and shared ways of storytelling. By examining changes in one student’s storytelling in the context of a mixed‐language story circle group, we offer insights into both language development and features of the language ecology in which such changes are supported

Possibilities of Efficiency Improvement at Creative Industries Companies of Latvia

Radošās industrijas ir viens no visstraujāk augošajiem ekonomikas sektoriem mūsdienās, tādēļ, lai veicinātu Latvijas radošo nozaru konkurētspēju, uzņēmumiem nepieciešams pastāvīgi pilnveidot savas darbības efektivitāti. Maģistra darba mērķis ir izstrādāt radošo industriju uzņēmumu efektivitātes pilnveidošanas metodes un paņēmienus to praktiskai izmantošanai. Darbā apkopotas teorētiskās atziņas par radošo industriju nozīmi, to efektivitātes pilnveidošanas metodēm, vispārīgi raksturotas Latvijas radošās industrijas, kā arī tika veikts pētījums par radošo industriju uzņēmumu radošuma un efektivitātes vadību, un, pamatojoties uz rezultātiem, autore izstrādāja modeli, veica secinājumus un priekšlikumus radošo industriju veiktspējas uzlabošanai. Darba apjoms: 98 lpp., attēlu skaits - 24, tabulu skaits - 4, pielikumu skaits - 8.Creative industries are now one of the most developing sectors of global economy, therefore, to further competitiveness of creative industries of Latvia, companies have to constantly improve their operational efficiency. The objective of the Master’s Thesis is to develop efficiency improvement techniques for practical use of creative industries companies. In the Thesis the theory aspects of creative industries essence, their efficiency improvement methods are described, the creative industries of Latvia are characterized. A study of creative industries business creativity and efficiency management was performed, and on this basis, the author developed a model, made conclusions and proposals for creative industries performance enhancement. The Thesis is written on 98 pages, number of images is 24, number of tables - 4, number of annexes - 8