Methods for Calculating the Effective Solar-Optical Properties of a Venetian Blind Layer

© 2005. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Vol. 111, Part 1. For personal use only. Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAE’s prior written permission.Window solar gain can strongly influence building energy consumption, peak loads, and comfort. Shading devices are routinely used to control solar gain. The use of venetian blinds is particularly common. There is a strong need for models that can accurately simulate this type of device. As a first step, previous research focused on the mechanisms of longwave radiant exchange. Methods were presented by which spatially averaged optical properties (referred to as “effective” optical properties) can be calculated. An enclosure model was formulated to model the interaction of radiation with the slat surfaces. This optical model allows the venetian blind to be treated as a planar, homogeneous “black-box” layer in a series of glazing layers and, coupled with the appropriate convection model, can be incorporated within a standard one-dimensional center-glass heat transfer analysis. In conjunction with the longwave analysis, the current study deals with the mechanisms of solar radiant exchange. Methods, based on geometric considerations and fundamental radiation analysis, are presented for determining the shading layer’s effective optical properties with respect to the beam component of incident solar radiation—at any angle of incidence. Both specular and diffuse reflection at the slat surfaces is included. The performance of these effective properties is demonstrated and discussed in terms of expected results and compared with other models and experimental results found in the literature.Natural Sciences and Engineering Research Council (Canada

Heat Transfer Analysis of a Between-Panes Venetian Blind Using Effective Longwave Radiative Properties

© 2004. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Vol. 110, Part 1. For personal use only. Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAE’s prior written permission.Center-glass thermal analysis programs based on one-dimensional models have proved to be exceptionally useful. Recently efforts have been made to extend the analysis to include venetian blinds. It is convenient to model the venetian blind as a planar, homogeneous layer that is characterized by spatially averaged, or “effective,” optical properties. The blind is then included in a series of planar glazing layers. Thermal resistance values were calculated for a window with two layers of uncoated glass and a venetian blind in an air-filled glazing cavity. Three pane spacings and a wide range of slat angles were examined. The longwave effective properties for the blind were obtained using the analysis presented by Yahoda and Wright in a companion paper. The simulation model was completed with one of two simple models dealing with convective heat transfer in the glazing cavity. Calculated results were compared with earlier guarded heater plate measurements, and the agreement was encouraging in spite of the crude convection models used.Natural Sciences and Engineering Research Counci

Methods for Calculating the Effective Longwave Radiative Properties of a Venetian Blind Layer

© 2004. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Vol. 110, Part 1. For personal use only. Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAE’s prior written permission.Window solar gain can strongly influence building energy consumption, peak loads, and comfort. Shading devices are routinely used to control solar gain. The use of venetian blinds is particularly common. There is a strong need for models that can accurately simulate this type of device. As a first step, this study deals with the mechanisms of longwave radiant exchange. Methods are presented by which spatially averaged optical properties (referred to as “effective” optical proper-ties) can be calculated. An enclosure model was formulated to model the interaction of radiation with the slat surfaces. Six enclosure areas, rather than four, were used to account for the possible overlap of blind slats. This optical model allows the venetian blind to be treated as a planar, homogeneous ''black-box'' layer in a series of glazing layers and, coupled with the appropriate convection model, can be incorporated within a standard one-dimensional center-glass heat transfer analysis. Sample calculations were performed and the resulting effec-tive optical properties discussed. The model compares favor-ably with expected trends and limits. The effect of slat curvature was also examined.Natural Sciences and Engineering Research Counci

Evaluating the impact of patient and public involvement (PPI) in the Life After Prostate Cancer Diagnosis (LAPCD) study

Background. Insights from patient and public involvement (PPI) can help researchers understand what it is like to live with cancer, and thus make cancer research more relevant to the needs of service users (patients and carers). Evaluation and reporting of PPI in health studies is important to build a strong evidence base concerning what works for whom and in what circumstances. We evaluated the impact of PPI in a large national study in the UK exploring Life After Prostate Cancer Diagnosis (LAPCD). Methods. An online survey was mailed to all researchers and service users (N=38) in 2018 at the end of this three year study, followed by semi-structured interviews (n=30). Analysis of survey and interview data was informed by realist evaluation principles. Results were reported using the GRIPP2 guidelines. Results. Strong contextual factors and robust processes for PPI facilitated positive impacts on the LAPCD study. Contextual factors included strong leadership of the service user group, commitment and expertise of the service users, clear roles, a positive attitude to involvement from researchers, and sufficient funding for PPI. Processes included a strong collaboration between the service users and the other research team members developed by embedding the PPI into a work-stream that ran alongside all the other 5 work-streams in the study. PPI impacts are reported on the design of the study, sense checking of patient information, at team meetings, analysis of qualitative data, paper writing, developing lay summaries, and dissemination of results. The study size and geographical distance sometimes created challenges for both service users and researchers. More formal feedback channels were suggested for future PPI. Conclusion. Well-resourced, carefully planned PPI ensured effective involvement and positive impacts on the LAPCD study

Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging

Uterine leiomyosarcoma (LMS) is a rare but aggressive malignancy. On imaging, it is difficult to differentiate LMS from, for example, degenerated leiomyoma (LM), a prevalent but benign condition. We curated a data set of 115 axial T2-weighted MRI images from 110 patients (mean [range] age=45 [17-81] years) with UTs that included five different tumor types. These data were randomly split stratifying on tumor volume into training (n=85) and test sets (n=30). An independent second reader (reader 2) provided manual segmentations for all test set images. To automate segmentation, we applied nnU-Net and explored the effect of training set size on performance by randomly generating subsets with 25, 45, 65 and 85 training set images. We evaluated the ability of radiomic features to distinguish between types of UT individually and when combined through feature selection and machine learning. Using the entire training set the mean [95% CI] fibroid DSC was measured as 0.87 [0.59-1.00] and the agreement between the two readers was 0.89 [0.77-1.0] on the test set. When classifying degenerated LM from LMS we achieve a test set F1-score of 0.80. Classifying UTs based on radiomic features we identify classifiers achieving F1-scores of 0.53 [0.45, 0.61] and 0.80 [0.80, 0.80] on the test set for the benign versus malignant, and degenerated LM versus LMS tasks. We show that it is possible to develop an automated method for 3D segmentation of the uterus and UT that is close to human-level performance with fewer than 150 annotated images. For distinguishing UT types, while we train models that merit further investigation with additional data, reliable automatic differentiation of UTs remains a challenge

What motivates senior clinicians to teach medical students?

BACKGROUND: This study was designed to assess the motivations of senior medical clinicians to teach medical students. This understanding could improve the recruitment and retention of important clinical teachers. METHODS: The study group was 101 senior medical clinicians registered on a teaching list for a medical school teaching hospital (The Canberra Hospital, ACT, Australia). Their motivations to teach medical students were assessed applying Q methodology. RESULTS: Of the 75 participants, 18 (24%) were female and 57 (76%) were male. The age distribution was as follows: 30–40 years = 16 participants (21.3%), 41–55 years = 46 participants (61.3%) and >55 years = 13 participants (17.3%). Most participants (n = 48, 64%) were staff specialists and 27 (36%) were visiting medical officers. Half of the participants were internists (n = 39, 52%), 12 (16%) were surgeons, and 24 (32%) were other sub-specialists. Of the 26 senior clinicians that did not participate, two were women; 15 were visiting medical officers and 11 were staff specialists; 16 were internists, 9 were surgeons and there was one other sub-specialist. The majority of these non-participating clinicians fell in the 41–55 year age group. The participating clinicians were moderately homogenous in their responses. Factor analysis produced 4 factors: one summarising positive motivations for teaching and three capturing impediments for teaching. The main factors influencing motivation to teach medical students were intrinsic issues such as altruism, intellectual satisfaction, personal skills and truth seeking. The reasons for not teaching included no strong involvement in course design, a heavy clinical load or feeling it was a waste of time. CONCLUSION: This study provides some insights into factors that may be utilised in the design of teaching programs that meet teacher motivations and ultimately enhance the effectiveness of the medical teaching workforce

Age-related human small intestine methylation: evidence for stem cell niches

BACKGROUND: The small intestine is constructed of many crypts and villi, and mouse studies suggest that each crypt contains multiple stem cells. Very little is known about human small intestines because mouse fate mapping strategies are impractical in humans. However, it is theoretically possible that stem cell histories are inherently written within their genomes. Genomes appear to record histories (as exemplified by use of molecular clocks), and therefore it may be possible to reconstruct somatic cell dynamics from somatic cell errors. Recent human colon studies suggest that random somatic epigenetic errors record stem cell histories (ancestry and total numbers of divisions). Potentially age-related methylation also occurs in human small intestines, which would allow characterization of their stem cells and comparisons with the colon. METHODS: Methylation patterns in individual crypts from 13 small intestines (17 to 78 years old) were measured by bisulfite sequencing. The methylation patterns were analyzed by a quantitative model to distinguish between immortal or niche stem cell lineages. RESULTS: Age-related methylation was observed in the human small intestines. Crypt methylation patterns were more consistent with stem cell niches than immortal stem cell lineages. Human large and small intestine crypt niches appeared to have similar stem cell dynamics, but relatively less methylation accumulated with age in the small intestines. There were no apparent stem cell differences between the duodenum and ileum, and stem cell survival did not appear to decline with aging. CONCLUSION: Crypt niches containing multiple stem cells appear to maintain human small intestines. Crypt niches appear similar in the colon and small intestine, and the small intestinal stem cell mitotic rate is the same as or perhaps slower than that of the colon. Although further studies are needed, age-related methylation appears to record somatic cell histories, and a somatic epigenetic molecular clock strategy may potentially be applied to other human tissues to reconstruct otherwise occult stem cell histories

Galaxy Zoo:Probabilistic Morphology through Bayesian CNNs and Active Learning

We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN can learn from galaxy images with uncertain labels and then, for previously unlabelled galaxies, predict the probability of each possible label. Our posteriors are well-calibrated (e.g. for predicting bars, we achieve coverage errors of 10.6% within 5 responses and 2.9% within 10 responses) and hence are reliable for practical use. Further, using our posteriors, we apply the active learning strategy BALD to request volunteer responses for the subset of galaxies which, if labelled, would be most informative for training our network. We show that training our Bayesian CNNs using active learning requires up to 35-60% fewer labelled galaxies, depending on the morphological feature being classified. By combining human and machine intelligence, Galaxy Zoo will be able to classify surveys of any conceivable scale on a timescale of weeks, providing massive and detailed morphology catalogues to support research into galaxy evolution...