Measuring Civilian Moral Injury: A Comparison of the Psychometric Properties of Three Measures of Moral Injury among the General Population

Moral injury research has been expanded to populations beyond the military in recent years. A key barrier to further research into moral injury in civilian populations is the lack of valid, reliable measures of the construct appropriate for general civilian use. This paper addresses this barrier by exploring the psychometrics of three measures of moral injury in a general civilian sample: the Moral Injury Scale for Youth, and adapted versions of the Moral Injury Events Scale and Expressions of Moral Injury Scale-Military. A sample of civilian women (n = 192) and men (n = 88) completed a battery of questionnaires comprising the above measures, and additional scales designed to capture theoretically-supported correlates of moral pain, psychopathology, and wellbeing. Confirmatory factor analysis found that the factor structure of the three moral injury measures was replicated within our civilian sample. No scale showed significant association with age or gender, indicating discriminant validity. All measures correlated as predicted with measures of psychopathology and wellbeing at the total score level. Correlations of individual subscales with each of these measures were more varied, suggesting conceptual differences in how moral injury is experienced in civilian populations. Despite psychometric support, all three scales required error covariances for certain items to obtain satisfactory model fit and displayed problems in item wording which may inflate internal consistency and warrant further scale construction efforts for this population. Findings indicate that civilian populations also experience moral injury, but that existing measures may have certain problems capturing this effectively.

Binge-Watching, Self-Determination, and Well-Being: A Partially Successful Direct Replication and Extension of Granow et al. (2018)

Binge-watching is a highly relevant new media phenomenon. An increasing number of people watch multiple episodes of their favorite series online, a process often spanning several hours. Granow et al. (2018) showed that binge-watching is accompanied by both positive as well as negative psychological experiences. Because it is one of the most important studies on the topic, we conducted a direct replication of Granow et al. (2018). We also extended the original study by including additional variables derived from self-determination theory. We conducted an online questionnaire with 668 respondents. Results showed that we could not reproduce the exact model that was reported. We also needed to adapt several of the originally tested measures to achieve satisfactory model fit. After introducing these changes, results showed that we replicated 67 percent of all effects in terms of significance (i.e., originally significant effects were also significant in the replication, and vice versa). When looking at effect size (i.e., originally reported effects fell into the replication’s 95% confidence interval), we replicated 42 percent. Together, our study represents a partial replication of Granow et al. (2018). In our extension, we found two further positive links between binge-watching and well-being: Binge-watching was associated not only with greater autonomy, but also with increased feelings of competence and relatedness. Competence and relatedness were related to increased well-being, which included vitality, recovery experience, and media enjoyment. In line with Granow et al. (2018), we find that binge-watching is related to self-determined media use and improved psychological well-being.

Collapse and Measures of Consciousness

There has been an upsurge of interest lately in developing Wigner’s hypothesis that conscious observation causes collapse by exploring dynamical collapse models in which some purportedly quantifiable aspect(s) of consciousness resist superposition. Kremnizer–Ranchin, Chalmers–McQueen and Okon–Sebastián have explored the idea that collapse may be associated with a numerical measure of consciousness. More recently, Chalmers–McQueen have argued that any single measure is inadequate because it will allow superpositions of distinct states of equal consciousness measure to persist. They suggest a satisfactory model needs to associate collapse with a set of measures quantifying aspects of consciousness, such as the “Q-shapes” defined by Tononi et al. in their “integrated information theory” (IIT) of consciousness. I argue here that Chalmers–McQueen’s argument against associating a single measure with collapse requires a precise symmetry between brain states associated with different experiences and thus does not apply to the only case where we have strong intuitions, namely human (or other terrestrial biological) observers. In defence of Chalmers–McQueen’s stance, it might be argued that idealized artificial information processing networks could display such symmetries. However, I argue that the most natural form of any theory (such as IIT) that postulates a map from network states to mind states is one that assigns identical mind states to isomorphic network states (as IIT does). This suggests that, if such a map exists, no familiar components of mind states, such as viewing different colours, or experiencing pleasure or pain, are likely to be related by symmetries.

Modelling Trip Distribution Using the Gravity Model and Fratar's Method

Trip Distribution is a difficult and significant model in the urban transportation planning process. This paper creates and assesses a satisfactory model of the trip distribution stage for the Nasiriyah city by using two models, Gravity and Fratar methods. A large sample was used for developing the model. The research methodology depends on discussing the theoretical fundamentals of the various methods for estimating the trips distribution and examining the suitability of these fundamentals for the conditions of the selected study area. Two different models had been used, namely; Frater and Gravity model. These models were calibrated using real data. The study tests the accuracy of the models, including overall statistical assessments of the predicted movements. Finally, the study recommended to use Fratar Method. These results had been confirmed to the literature that, if the area is a homogenous growth, the best model is the growth factor (Fratar's method) and if the area is experiencing rapid changes. The gravity model will produce satisfactory results because it takes into account the competition in different land uses.

Density inversion of selected microgravity anomalies using L2-smoothing and minimum support focusing stabilizers

Interpretation and inversion of microgravity anomalies belong to important tasks of near-surface geophysics, mostly in cavities detection in engineering, environmental and archaeological applications. One of the mostly used concepts of inversion in applied gravimetry is based on the approximation of the model space by means of 2D or 3D elementary sources with the aim to estimate their densities by means of the solution of a corresponding linear equation system. There were published several approaches trying to obtain correct and realistic results, which describe real parameters of the sources. In the proposed contribution we analyse the properties of two additional functionals, which describe additional properties of the searched solution – namely so-called L2-smoothing and minimum support focusing stabilizers. For the inversion itself, we have used the regularized conjugate gradient method. We have studied properties of these two stabilizers in the case of one synthetic model and one real-world dataset (microgravity data from St. Nicholas church in Trnava). Results have shown that proposed algorithm with the minimum support stabilizer can generate satisfactory model results, from which we can describe real geometry, dimensions and physical properties of interpreted cavities.

A Simple Cardiovascular Model for the Study of Hemorrhagic Shock

Hemorrhagic shock is the number one cause of death on the battlefield and in civilian trauma as well. Mathematical modeling has been applied in this context for decades; however, the formulation of a satisfactory model that is both practical and effective has yet to be achieved. This paper introduces an upgraded version of the 2007 Zenker model for hemorrhagic shock termed the ZenCur model that allows for a better description of the time course of relevant observations. Our study provides a simple but realistic mathematical description of cardiovascular dynamics that may be useful in the assessment and prognosis of hemorrhagic shock. This model is capable of replicating the changes in mean arterial pressure, heart rate, and cardiac output after the onset of bleeding (as observed in four experimental laboratory animals) and achieves a reasonable compromise between an overly detailed depiction of relevant mechanisms, on the one hand, and model simplicity, on the other. The former would require considerable simulations and entail burdensome interpretations. From a clinical standpoint, the goals of the new model are to predict survival and optimize the timing of therapy, in both civilian and military scenarios.

Performance Evaluation of an Operational Rapid Response Fire Spread Forecasting System in the Southeast Mediterranean (Greece)

The current work presents the operational implementation and evaluation of a rapid response fire spread forecasting system, named IRIS, that was developed to provide support to the tactical wildfire suppression activities of the Hellenic Fire Corps. The system was operationally employed during the 2019 fire season in Greece, providing on-demand wildfire spread predictions for 17 incidents. Satellite remote sensing data were employed for quantitatively assessing IRIS’s predictions for eight selected events. Our results suggest an overall satisfactory model performance. More importantly, this study demonstrates that, as coupled fire-atmosphere modeling becomes an increasingly popular approach, the respective models have great potential to support operational agencies and wildfire managers during the incident phase.

Modeled based analysis of fish farm emissions impact on the fjord biogeochemistry

<p>To investigate the impacts of fish farm emissions, we coupled the biogeochemical C-N-P-Si-O-S-Mn-Fe transformation model BROM with a 2-Dimensional Benthic-Pelagic transport model (2DBP), considering vertical and horizontal transport in the water and upper 5 cm  sediments along a 10000 m transect centered on a fish farm. The 2DBP model had 25 m horizontal resolution and was forced by hydrophysical model data for the Hardangerfjord in western Norway. The model predicted significant impacts on seafloor biogeochemistry up to 500 meters from the fish farm (e.g., increased organic matter in sediments, oxygen depletion in water and sediments, denitrification, metal and sulfur reduction) as well as detectable decreases in oxygen and increases in ammonia, phosphate and organic matter in the water near to the fish farm cages. The model results are compared with field data from the Hardangerfjord in August 2016 and indicated satisfactory model performance.</p>

From undergraduate to postgraduate uses of the dead human body: consequential ethical shift

The dependence of surgical training programmes on the supply of bodies by for-profit organisations places them at serious ethical risk. These risks, with their commodification of the bodies used in the programme, are outlined. It is concluded that this is not a satisfactory model for the trainees’ subsequent interaction with living patients and that a code of practice is required.

The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings

Several studies have indicated that Model Predictive Control (MPC) of space heating systems can utilize the thermal mass of residential buildings as short-term thermal storage for various demand response purposes. Realization of this potential relies heavily on the accuracy of the model used to represent the thermodynamics of the building. Such models, whether they are grey box or black box, are calibrated using relevant data obtained from initial measurements, and the performance of the calibrated model is validated using data from a subsequent period. However, many studies use validation periods with weather conditions similar to those of the calibration period. Only a few studies investigate whether the calibrated model performs satisfactory when subjected to significantly different conditions. This paper presents data from a simulation-based study on the effect of seasonal weather changes on the performance of a black-box model. The study was conducted using 11 years of Danish weather data (2008-2018). The results indicate that the performance of the black-box model deteriorate as the weather data conditions become increasingly different from those used in the initial model calibration. Further, the results show that calibration in heating season leads to satisfactory model performance through the heating season, but lower performance in transitional seasons (especially spring). Results also show that calibration in February led to highest model performance through heating season, while calibration in March led to satisfactory model performance in the whole heating and fall season.