2,594 research outputs found

    Adaptive false memory: Imagining future scenarios increases false memories in the DRM paradigm

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    Previous research has shown that rating words for their relevance to a future scenario enhances memory for those words. The current study investigated the effect of future thinking on false memory using the Deese/Roediger–McDermott (DRM) procedure. In Experiment 1, participants rated words from 6 DRM lists for relevance to a past or future event (with or without planning) or in terms of pleasantness. In a surprise recall test, levels of correct recall did not vary between the rating tasks, but the future rating conditions led to significantly higher levels of false recall than the past and pleasantness conditions did. Experiment 2 found that future rating led to higher levels of false recognition than did past and pleasantness ratings but did not affect correct recognition. The effect in false recognition was, however, eliminated when DRM items were presented in random order. Participants in Experiment 3 were presented with both DRM lists and lists of unrelated words. Future rating increased levels of false recognition for DRM lures but did not affect correct recognition for DRM or unrelated lists. The findings are discussed in terms of the view that false memories can be associated with adaptive memory functions

    Cognitive and Emotional Processes Involved in the Experience of Objects as Holy or Transcendent

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    In recent years, attitudes about religion/spirituality have become more pluralistic (Pew Research Center, 2015a). At the same time, the number of individuals who identify themselves as nonreligious, atheist or agnostic are growing (Pew Research Center, 2015b), yet we are lacking words and research to describe their attributions of transcendence in language not bound to religious concepts. This study aims at examining both concepts – holiness and transcendence – in their similarities and differences through assessing cognitive and emotional processes involved in experiences of objects. The study consisted of two parts with a total of 206 Christian and 52 nonreligious/atheistic/agnostic participants. In study one, 146 students (113 Christians, 33 Nonreligious/Atheists/Agnostics, or NAA) categorized 30 objects as holy or not, as well as transcendent or not. They did so either intuitively or after writing about their understanding of holiness/transcendence beforehand (systematic thinking condition). In study two, different participants (N=114, 93 Christians, 21 NAA) evaluated the same 30 objects on the ability to elicit emotions like awe, elevation and joy, the perceived purity of the objects, as well as their importance in culture and religion. Results showed that there was no difference in perceptions of holiness and transcendence in the intuitive or systematic thinking condition. While Christians categorized about the same number of items as transcendent and holy as NAA participants, objects were generally more easily categorized as transcendent than as holy in both groups. A factor analysis and regression showed that perceived holiness of objects among Christians was predicted mostly by the factors religion (b=.906), and awe (b .261), Adj. R2=.881. Transcendence similarly was most correlated with the factor of religion (b=.720) and awe (b=.510), but the factor of happiness/connectedness also contributed (b=.207), R2=.821. Among Nonreligious/Atheist/Agnostics, perceived holiness was predicted by the relation to religion (b=.909), and additionally negatively predicted by experienced connectedness/happiness (b = -.250), Adj. R2 =.880. Transcendence, even among Nonreligious/Atheist/Agnostics, was predicted by objects’ relation to religion (b=.698) and their relation to awe (b=.344), with the factor joy/connectivity (b=.226, p=.059) approaching significance, overall Adj. R2 = .618. Results show that while there is similarity between the concepts of holiness and transcendence, transcendence is distinct in including a sense of happiness/connectedness not present in religion

    Oedometer and Triaxial Tests on Fill/Gyttja with Shell Fragments

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    Sudden Gains in Treatment

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    Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

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    Objective: The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system. Methods: The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Z(eff)) and relative electron densities (rho(e)) for phantom inserts with known elemental compositions and relative electron densities. Results: The optimal energy combination was determined to be 50 and 90kVp. For this combination, Z(eff) and r rho(e) can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60cGy. Conclusion: Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Z(eff) and rho(e). When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Z(eff) and rho(e) errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system

    SEREEGA: Simulating Event-Related EEG Activity

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    Abstract Electroencephalography (EEG) is a popular method to monitor brain activity, but it can be difficult to evaluate EEG-based analysis methods because no ground-truth brain activity is available for comparison. Therefore, in order to test and evaluate such methods, researchers often use simulated EEG data instead of actual EEG recordings, ensuring that it is known beforehand which e ects are present in the data. As such, simulated data can be used, among other things, to assess or compare signal processing and machine learn-ing algorithms, to model EEG variabilities, and to design source reconstruction methods. In this paper, we present SEREEGA, short for Simulating Event-Related EEG Activity . SEREEGA is a MATLAB-based open-source toolbox dedicated to the generation of sim-ulated epochs of EEG data. It is modular and extensible, at initial release supporting ve different publicly available head models and capable of simulating multiple different types of signals mimicking brain activity. This paper presents the architecture and general work ow of this toolbox, as well as a simulated data set demonstrating some of its functions. Highlights Simulated EEG data has a known ground truth, which can be used to validate methods. We present a general-purpose open-source toolbox to simulate EEG data. It provides a single framework to simulate many different types of EEG recordings. It is modular, extensible, and already includes a number of head models and signals. It supports noise, oscillations, event-related potentials, connectivity, and more

    A PCT algorithm for discontinuation of antibiotic therapy is a cost-effective way to reduce antibiotic exposure in adult intensive care patients with sepsis

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    Objective: Procalcitonin (PCT) is a specific marker for differentiating bacterial from non-infective causes of inflammation. It can be used to guide initiation and duration of antibiotic therapy in intensive care unit (ICU) patients with suspected sepsis, and might reduce the duration of hospital stay. Limiting antibiotic treatment duration is highly important because antibiotic over-use may cause patient harm, prolonged hospital stay, and resistance development. Several systematic reviews show that a PCT algorithm for antibiotic discontinuation is safe, but upfront investment required for PCT remains an important barrier against implementation. The current study investigates to what extent this PCT algorithm is a cost-effective use of scarce healthcare resources in ICU patients with sepsis compared to current practice. Methods: A decision tree was developed to estimate the health economic consequences of the PCT algorithm for antibiotic discontinuation from a Dutch hospital perspective. Input data were obtained from a systematic literature review. When necessary, additional information was gathered from open interviews with clinical chemists and intensivists. The primary effectiveness measure is defined as the number of antibiotic days, and cost-effectiveness is expressed as incremental costs per antibiotic day avoided. Results: The PCT algorithm for antibiotic discontinuation is expected to reduce hospital spending by circa €3503 per patient, indicating savings of 9.2%. Savings are mainly due to reductions in length of hospital stay, number of blood cultures performed, and, importantly, days on antibiotic therapy. Probabilistic and one-way sensitivity analyses showed the model outcome to be robust against changes in model inputs. Conclusion: Proven safe, a PCT algorithm for antibiotic discontinuation is a cost-effective means of reducing antibiotic exposure in adult ICU patients with sepsis, compared to current practice. Additional resources required for PCT are more than offset by downstream cost savings. This finding is highly important given the aim of preventing widespread antibiotic resistanc
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