How buildings visualise client and architect: The problem that today’s user is typically not the client

An article presented at the last ICAT- conference stated at the end that buildings at all times tend to picture the people who had them erected. This paper aims to show the correctness of that statement. To this end, it will examine a number of typical residential buildings dating from the beginning of the seventeenth century up to today, investigate who had the buildings erected, and relate that to the performance of the buildings. This relation analysis will mainly use the scale but also the degree of diversity in function and appearance as factors. Furthermore, using economic data and data on the buildings to identify patterns, it will investigate how size of the property and relative size of the capital interest behind the building has developed. Since the authors live in Copenhagen and Copenhagen is very typical in its historical development, buildings and environments in and around the centre of Copenhagen are used as examples.

Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity.

Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias.

Memory bias for emotional facial expressions in major depression

Sixteen clinically depressed patients and sixteen healthy controls were presented with a set of emotional facial expressions and were asked to identify the emotion portrayed by each face. They, were subsequently given a recognition memory test for these faces. There was no difference between the groups in terms of their ability to identify emotion between from faces. All participants identified emotional expressions more accurately than neutral expressions, with happy expressions being identified most accurately. During the recognition memory phase the depressed patients demonstrated superior memory for sad expressions, and inferior memory for happy expressions, relative to neutral expressions. Conversely, the controls demonstrated superior memory for happy expressions, and inferior memory for sad expressions, relative to neutral expressions. These results are discussed in terms of the cognitive model of depression proposed by Williams, Watts, MacLeod, and Mathews (1997).

Genetic modulation of the response bias towards facial displays of anger and happiness

Background: Investigating genetic modulation of emotion processing may contribute to the understanding of heritable mechanisms of emotional disorders. The aim of the present study was to test the effects of catechol- O-methyltransferase (COMT) val158met and serotonin-transporter-linked promoter region (5-HTTLPR) polymorphisms on facial emotion processing in healthy individuals. Methods: Two hundred and seventy five (167 female) participants were asked to complete a computerized facial affect recognition task, which involved four experimental conditions, each containing one type of emotional face (fearful, angry, sad or happy) intermixed with neutral faces. Participants were asked to indicate whether the face displayed an emotion or was neutral. The COMT-val158met and 5-HTTLPR polymorphisms were genotyped. Results: Met homozygotes (COMT) showed a stronger bias to perceive neutral faces as expressions of anger, compared with val homozygotes. However, the S-homozygotes (5-HTTLPR) showed a reduced bias to perceive neutral faces as expressions of happiness, compared to L-homozygotes. No interaction between 5-HTTLPR and COMT was found. Conclusions: These results add to the knowledge of individual differences in social cognition that are modulated via serotonergic and dopaminergic systems. This potentially could contribute to the understanding of the mechanisms of susceptibility to emotional disorders. © 2013 Elsevier Masson SAS.

Recognition accuracy and response bias to happy and sad facial expressions in patients with major depression

Impaired facial expression recognition has been associated with features of major depression, which could underlie some of the difficulties in social interactions in these patients. Patients with major depressive disorder and age- and gender-matched healthy volunteers judged the emotion of 100 facial stimuli displaying different intensities of sadness and happiness and neutral expressions presented for short (100 ms) and long (2,000 ms) durations. Compared with healthy volunteers, depressed patients demonstrated subtle impairments in discrimination accuracy and a predominant bias away from the identification as happy of mildly happy expressions. The authors suggest that, in depressed patients, the inability to accurately identify subtle changes in facial expression displayed by others in social situations may underlie the impaired interpersonal functioning.

Designing for User-facing Uncertainty in Everyday Sensing and Prediction

Thesis (Ph.D.)--University of Washington, 2016-07

Empirical evidence of bias in the design of experimental stroke studies: a metaepidemiologic approach

Background and Purpose: At least part of the failure in the transition from experimental to clinical studies in stroke has been attributed to the imprecision introduced by problems in the design of experimental stroke studies. Using a metaepidemiologic approach, we addressed the effect of randomization, blinding, and use of comorbid animals on the estimate of how effectively therapeutic interventions reduce infarct size. Methods: Electronic and manual searches were performed to identify meta-analyses that described interventions in experimental stroke. For each meta-analysis thus identified, a reanalysis was conducted to estimate the impact of various quality items on the estimate of efficacy, and these estimates were combined in a meta meta-analysis to obtain a summary measure of the impact of the various design characteristics. Results: Thirteen meta-analyses that described outcomes in 15 635 animals were included. Studies that included unblinded induction of ischemia reported effect sizes 13.1% (95% CI, 26.4% to 0.2%) greater than studies that included blinding, and studies that included healthy animals instead of animals with comorbidities overstated the effect size by 11.5% (95% CI, 21.2% to 1.8%). No significant effect was found for randomization, blinded outcome assessment, or high aggregate CAMARADES quality score. Conclusions: We provide empirical evidence of bias in the design of studies, with studies that included unblinded induction of ischemia or healthy animals overestimating the effectiveness of the intervention. This bias could account for the failure in the transition from bench to bedside of stroke therapies.

The microbiological signature of human cutaneous leishmaniasis lesions exhibits restricted bacterial diversity compared to healthy skin

Localised cutaneous leishmaniasis (LCL) is the most common form of cutaneous leishmaniasis characterised by single or multiple painless chronic ulcers, which commonly presents with secondary bacterial infection. Previous culture- based studies have found staphylococci, streptococci, and opportunistic pathogenic bacteria in LCL lesions, but there have been no comparisons to normal skin. In addition, this approach has strong bias for determining bacterial composition. The present study tested the hypothesis that bacterial communities in LCL lesions differ from those found on healthy skin (HS). Using a high throughput amplicon sequencing approach, which allows for better populational evaluation due to greater depth coverage and the Quantitative Insights Into Microbial Ecology pipeline, we compared the microbiological signature of LCL lesions with that of contralateral HS from the same individuals. Streptococcus , Staphylococcus , Fusobacterium and other strict or facultative anaerobic bacteria composed the LCL microbiome. Aerobic and facultative anaerobic bacteria found in HS, including environmental bacteria, were significantly decreased in LCL lesions (p < 0.01). This paper presents the first comprehensive microbiome identification from LCL lesions with next generation sequence methodology and shows a marked reduction of bacterial diversity in the lesions.

Clinical Accuracy of the MedGem Indirect Calorimeter for Measuring Resting Energy Expenditure in Cancer Patients

OBJECTIVE: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem) and predicted REE. DESIGN: Cross-sectional clinical validation study. SETTING: Private radiation oncology centre, Brisbane, Australia. SUBJECTS: Cancer patients (n = 18) and healthy subjects (n = 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m(2). INTERVENTIONS: Oxygen consumption (VO(2)) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. RESULTS: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias -5% with limits of -45 to 35% for healthy subjects. Less than half of the cancer patients (n = 7, 46.7%) and only a third (n = 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of -5% for cancer patients and 4% for healthy subjects, with limits of agreement of -30 to 20% and -27 to 34%, respectively. CONCLUSIONS: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).