Quantitative photoacoustic estimates of intervascular blood oxygenation differences using linear unmixing

The linear unmixing technique is an appealing method for estimating blood oxygen saturation (sO2) from multiwavelength photoacoustic tomography images, as estimates can be acquired with a straightforward matrix inversion. However, the technique can only rarely provide accurate estimates in vivo, as it requires that the light fluence at the voxels of interest is constant with wavelength. One way to extend the set of cases where accurate information related to sO2 can be acquired with the technique is by taking the difference in sO2 estimates between vessels. Assuming images are perfectly reconstructed, the intervascular difference in sO2 estimates is accurate if the error in the estimates due to the wavelength dependence of the fluence is identical for both. An in silico study was performed to uncover what kinds of conditions may give rise to accurate sO2 differences for a vessel pair. Basic criteria were formulated in simple tissue models consisting of a pair of vessels immersed in two-layer skin models. To assess whether these criteria might still be valid in more realistic imaging scenarios, the sO2 difference was estimated for vessels in more complex tissue models

Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions

Significance: Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO2 from 2-D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as they are limited by the 2-D nature of the training data when the problem is inherently three-dimensional (3-D), and they have not been tested with realistic images. Aim: To demonstrate the capability of deep neural networks to process whole 3-D images and output 3-D maps of vascular sO2 from realistic tissue models/images. Approach: Two separate fully convolutional neural networks were trained to produce 3-D maps of vascular blood oxygen saturation and vessel positions from multiwavelength simulated images of tissue models. Results: The mean of the absolute difference between the true mean vessel sO2 and the network output for 40 examples was 4.4% and the standard deviation was 4.5%. Conclusions: 3-D fully convolutional networks were shown capable of producing accurate sO2 maps using the full extent of spatial information contained within 3-D images generated under conditions mimicking real imaging scenarios. We demonstrate that networks can cope with some of the confounding effects present in real images such as limited-view artifacts and have the potential to produce accurate estimates in vivo

Perceptual adaptation by normally hearing listeners to a simulated "hole" in hearing

Simulations of cochlear implants have demonstrated that the deleterious effects of a frequency misalignment between analysis bands and characteristic frequencies at basally shifted simulated electrode locations are significantly reduced with training. However, a distortion of frequency-to-place mapping may also arise due to a region of dysfunctional neurons that creates a "hole" in the tonotopic representation. This study simulated a 10 mm hole in the mid-frequency region. Noise-band processors were created with six output bands (three apical and three basal to the hole). The spectral information that would have been represented in the hole was either dropped or reassigned to bands on either side. Such reassignment preserves information but warps the place code, which may in itself impair performance. Normally hearing subjects received three hours of training in two reassignment conditions. Speech recognition improved considerably with training. Scores were much lower in a baseline (untrained) condition where information from the hole region was dropped. A second group of subjects trained in this dropped condition did show some improvement; however, scores after training were significantly lower than in the reassignment conditions. These results are consistent with the view that speech processors should present the most informative frequency range irrespective of frequency misalignment. 0 2006 Acoustical Society of America

Abstract Argumentation / Persuasion / Dynamics

The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier. We extend Dung's frameworks with acts of persuasion among agents, and consider interactions among attack, persuasion and defence that have been largely unheeded so far. We characterise basic notions of admissibilities in this framework, and show a way of enriching them through, effectively, CTL (computation tree logic) encoding, which also permits importation of the theoretical results known to the logic into our argumentation frameworks. Our aim is to complement the growing interest in coordination of static and dynamic argumentation.Comment: Arisaka R., Satoh K. (2018) Abstract Argumentation / Persuasion / Dynamics. In: Miller T., Oren N., Sakurai Y., Noda I., Savarimuthu B., Cao Son T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science, vol 11224. Springer, Cha

When and why people misestimate future feelings: Identifying strengths and weaknesses in affective forecasting.

People try to make decisions that will improve their lives and make them happy, and to do so, they rely on affective forecasts-predictions about how future outcomes will make them feel. Decades of research suggest that people are poor at predicting how they will feel and that they commonly overestimate the impact that future events will have on their emotions. Recent work reveals considerable variability in forecasting accuracy. This investigation tested a model of affective forecasting that captures this variability in bias by differentiating emotional intensity, emotional frequency, and mood. Two field studies examined affective forecasting in college students receiving grades on a midterm exam (Study 1, N = 643), and U.S. citizens after the outcome of the 2016 presidential election (Study 2, N = 706). Consistent with the proposed model, participants were more accurate in forecasting the intensity of their emotion and less accurate in forecasting emotion frequency and mood. Overestimation of the effect of the event on mood increased over time since the event. Three experimental studies examined mechanisms that contribute to differential forecasting accuracy. Biases in forecasting intensity were caused by changes in perceived event importance; biases in forecasting frequency of emotion were caused by changes in the frequency of thinking about the event. This is the first direct evidence mapping out strengths and weaknesses for different types of affective forecasts and the factors that contribute to this pattern. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Deletions of the derivative chromosome 9 occur at the time of the Philadelphia translocation and provide a powerful and independent prognostic indicator in chronic myeloid leukemia

Chronic myeloid leukemia (CML) is characterized by formation of the BCR-ABL fusion gene, usually as a consequence of the Philadelphia (Ph) translocation between chromosomes 9 and 22. Large deletions on the derivative chromosome 9 have recently been reported, but it was unclear whether deletions arose during disease progression or at the time of the Ph translocation. Fluorescence in situ hybridization (FISH) analysis was used to assess the deletion status of 253 patients with CML. The strength of deletion status as a prognostic indicator was then compared to the Sokal and Hasford scoring systems. The frequency of deletions was similar at diagnosis and after disease progression but was significantly increased in patients with variant Ph translocations. In patients with a deletion, all Ph+ metaphases carried the deletion. The median survival of patients with and without deletions was 38 months and 88 months, respectively (P = .0001). By contrast the survival difference between Sokal or Hasford high-risk and non-high-risk patients was of only borderline significance (P = .057 and P = .034). The results indicate that deletions occur at the time of the Ph translocation. An apparently simple reciprocal translocation may therefore result in considerable genetic heterogeneity ab initio, a concept that is likely to apply to other malignancies associated with translocations. Deletion status is also a powerful and independent prognostic factor for patients with CML. The prognostic significance of deletion status should now be studied prospectively and, if confirmed, should be incorporated into management decisions and the analysis of clinical trials. (C) 2001 by The American Society of Hematology

Analysis of Dialogical Argumentation via Finite State Machines

Dialogical argumentation is an important cognitive activity by which agents exchange arguments and counterarguments as part of some process such as discussion, debate, persuasion and negotiation. Whilst numerous formal systems have been proposed, there is a lack of frameworks for implementing and evaluating these proposals. First-order executable logic has been proposed as a general framework for specifying and analysing dialogical argumentation. In this paper, we investigate how we can implement systems for dialogical argumentation using propositional executable logic. Our approach is to present and evaluate an algorithm that generates a finite state machine that reflects a propositional executable logic specification for a dialogical argumentation together with an initial state. We also consider how the finite state machines can be analysed, with the minimax strategy being used as an illustration of the kinds of empirical analysis that can be undertaken.Comment: 10 page

‘Doing the best we can’: Registered Nurses' experiences and perceptions of patient safety in intensive care during COVID-19

Aims: To explore registered nurses' experiences of patient safety in intensive care during COVID-19.Design: A qualitative interview study informed by constructivism. Method: Semi-structured interviews were conducted and audio- recorded with 19 registered nurses who worked in intensive care during COVID-19 between May and July 2021. Interviews were transcribed verbatim and thematically analysed utilizing framework. Results: Two key themes were identified. ‘On a war footing’—an unprecedented situation which describes the situation nurses faced, and the actions are taken to prepare for the safe delivery of care. ‘Doing the best we can’—Safe Delivery of Care which describes the ramifications of the actions taken on short- and long-term patient safety including organization of care, missed and suboptimal care and communication. Both themes were embedded in the landscape of Staff Well-being and Peer Support. Conclusion: Nurses reported an increase in patient safety risks which they attributed to the dilution of skill mix and fragmentation of care. Nurses demonstrated an under-standing of the holistic and long-term impacts on patient safety and recovery from critical illness. Impact: This study explored the perceived impact of COVID-19 on patient safety in intensive care from a nursing perspective. Dilution of skill mix, where specialist critical care registered nurses were diluted with registered nurses with no critical care experience, and the fragmentation of care was perceived to lead to reduced quality of care and increased adverse events and risk of harm which were not consistently formally reported. Furthermore, nurses demonstrated a holistic and long-term appreciation of patient safety. These findings should be considered as part of future nursing work-force modelling and patient safety strategies by intensive care leaders and managers. No public or patient contribution to this study. The study aims and objectives were developed in collaboration with health care professional