1,389 research outputs found
Debt and financial expectations: an individual and household level analysis
In this paper we show that optimistic financial expectations impact positively on both the uantity of debt and the growth in debt, at the individual and household levels. Our heoretical model shows that this association is predicted under a variety of plausible cenarios. In the empirical analysis we explore the determinants of debt and of growth in ebt using British data. We find convincing support for our theoretical priors and show that t is optimistic financial expectations per se that are important in influencing debt, rather han the accuracy of individuals’ predictions regarding their future financial situation.Debt; Financial Expectations; Inter-temporal Consumption; Random Effects; Tobit Estimator
A tutorial on group effective connectivity analysis, part 2: second level analysis with PEB
This tutorial provides a worked example of using Dynamic Causal Modelling
(DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject
variability in neural circuitry (effective connectivity). This involves
specifying a hierarchical model with two or more levels. At the first level,
state space models (DCMs) are used to infer the effective connectivity that
best explains a subject's neuroimaging timeseries (e.g. fMRI, MEG, EEG).
Subject-specific connectivity parameters are then taken to the group level,
where they are modelled using a General Linear Model (GLM) that partitions
between-subject variability into designed effects and additive random effects.
The ensuing (Bayesian) hierarchical model conveys both the estimated connection
strengths and their uncertainty (i.e., posterior covariance) from the subject
to the group level; enabling hypotheses to be tested about the commonalities
and differences across subjects. This approach can also finesse parameter
estimation at the subject level, by using the group-level parameters as
empirical priors. We walk through this approach in detail, using data from a
published fMRI experiment that characterised individual differences in
hemispheric lateralization in a semantic processing task. The preliminary
subject specific DCM analysis is covered in detail in a companion paper. This
tutorial is accompanied by the example dataset and step-by-step instructions to
reproduce the analyses
Air Traffic Management Technology Demonstration - 3 (ATD-3) Multi-Flight Common Route (MFCR) Concept of Operations Version 1.0
NASA's Multi Flight Common Route (MFCR) automation represents one element of those technologies focusing primarily on delay recovery in the en route phase of flight. Delay recovery is an attenuation of flight-time delay, accomplished by periodically revising weather-avoidance routing as the convective weather system evolves. MFCR is intended for use by Traffic Management Coordinators (TMCs) in Air Route Traffic Control Centers (ARTCCs, or Centers) and traffic management specialists (TMSs) in the Air Traffic Control System Command Center (ATCSCC). MFCR leverages existing weather, airspace, and traffic data, as well as improvements in navigation, surveillance, communication, and digital information technologies, to build on existing ATM automation and address some of the shortcomings associated with strategic traffic flow management initiatives and weather forecasting uncertainties. These capabilities provide significant potential benefits in the form of time, fuel, and cost savings. The concept of operations described in this document describes MFCR functionality as delivered by NASA to the FAA in December 2017, including a list of potential enhancements that may be realized when the system is fielded
Where Bottom-up Meets Top-down: Neuronal Interactions during Perception and Imagery
Functional magnetic resonance imaging (fMRI) studies have identified category-selective regions in ventral occipito-temporal cortex that respond preferentially to faces and other objects. The extent to which these patterns of activation are modulated by bottom-up or top-down mechanisms is currently unknown. We combined fMRI and dynamic causal modelling to investigate neuronal interactions between occipito-temporal, parietal and frontal regions, during visual perception and visual imagery of faces, houses and chairs. Our results indicate that, during visual perception, category-selective patterns of activation in extrastriate cortex are mediated by content-sensitive forward connections from early visual areas. In contrast, during visual imagery, category-selective activation is mediated by content-sensitive backward connections from prefrontal cortex. Additionally, we report content-unrelated connectivity between parietal cortex and the category-selective regions, during both perception and imagery. Thus, our investigation revealed that neuronal interactions between occipito-temporal, parietal and frontal regions are task- and stimulus-dependent. Sensory representations of faces and objects are mediated by bottom-up mechanisms arising in early visual areas and top-down mechanisms arising in prefrontal cortex, during perception and imagery respectively. Additionally non-selective, top-down processes, originating in superior parietal areas, contribute to the generation of mental images, regardless of their content, and their maintenance in the ‘mind's eye
Implementing Pharmacy Informatics in College Curricula: The AACP Technology in Pharmacy Education and Learning Special Interest Group
Many professional organizations have initiatives to increase the awareness and use of informatics in the practice of pharmacy. Within education we must respond to these initiatives and make technology integral to all aspects of the curriculum, inculcating in students the importance of technology in practice. This document proposes 5 central domains for organizing planning related to informatics and technology within pharmacy education. The document is intended to encourage discussion of informatics within pharmacy education and the implications of informatics in future pharmacy practice, and to guide colleges of pharmacy in identifying and analyzing informatics topics to be taught and methods of instruction to be used within the doctor of pharmacy curriculum
Modules and brain mapping
This review highlights the key role of modularity and the additive factors method in functional neuroimaging. Our focus is on structure–function mappings in the human brain and how these are disclosed by brain mapping. We describe how modularity of processing (and possibly processes) was a key point of reference for establishing functional segregation as a principle of brain organization. Furthermore, modularity plays a crucial role when trying to characterize distributed brain responses in terms of functional integration or coupling among brain areas. We consider additive factors logic and how it helped to shape the design and interpretation of studies at the inception of brain mapping, with a special focus on factorial designs. We look at factorial designs in activation experiments and in the context of lesion–deficit mapping. In both cases, the presence or absence of interactions among various experimental factors has proven essential in understanding the context-sensitive nature of distributed but modular processing and discerning the nature of (potentially degenerate) structure–function relationships in cognitive neuroscience
The impact of COVID-19 on postgraduate business students
Globally, the COVID-19 pandemic has resulted
in significant changes to the way organisations
operate – not least the business schools that
educate tomorrow’s leaders – and it seems
unlikely that this disruption will be reversed
in the short to medium term. This white paper
presents the findings of a study concerning
the study and work experiences of the Gordon
Institute of Business Science (GIBS) Master of
Business Administration 2020 cohort, based
on quantitative and qualitative data gathered
from students who used the opportunity
to express their concerns, needs, and
expectations for the future. Based on the data,
the authors suggest ways in which work and
study conditions can be improved
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