Sensation Seeking and Perceived Need for Structure Moderate Soldiers’ Well-Being Before and After Operational Deployment

This study examined associations between sensation seeking and perceived need for structure, and changes in reported well-being among deployed soldiers. Participants (n = 167) were assessed before and after a six-month deployment to south Afghanistan. Results indicated that although well-being declined in the soldier sample as a whole following deployment, the degree of decrease was significantly different among soldiers with different personality profiles. Differences were moderated by soldiers’ level of sensation seeking and perceived need for structure. Results are discussed in terms of a person-environment fit theory in the context of preparation and rehabilitation of deployed military personnel

High-order propagation of jet noise on a tetrahedral mesh using large eddy simulation sources

Jet noise is an important area of research in commercial aviation due to its high contribution to the overall noise generated by an aircraft. Conventionally, CFD combined with surface integral methods is used to study jet noise because of its low cost. However, it is not always trivial to define integration surfaces around complex geometries. This study employs a different two-step approach that can handle complex geometries. It combines a large-eddy simulation (LES) to obtain the acoustic sources from the flow field, and an acoustic perturbation equations (APE) solver to propagate the sound to the far field. The LES is performed with an industrial 2nd-order finite volume solver. The APE code is a high-order discontinuous Galerkin (DG) spectral/hp solver of the Nektar+ + framework. The APE solver is validated on a canonical test case. A study on different polynomial expansion orders and meshes is further performed to estimate the mesh size for noise propagation in the high-order spectral/hp DG context. Finally, a three-dimensional jet noise case (Re = 10, 000 and Mach = 0.9) is simulated using unstructured tetrahedral mesh for the APE solver and improved noise results for high frequencies are obtained. The results demonstrate that the present approach is capable of predicting noise in complex geometry scenarios, such as installed jets under the aircraft wings

The Use of Sodium Pyrophosphate to Improve a Translucent Clay Simulate

In the ever expanding quest to understand the nature and behavior of soil, translucent and even transparent media have been developed to serve as soil simulates. These artificial soils can be used in experimental models to make visual measurement of phenomena such as geosystem kinematics, soil mass movement, soil particle motion, and pore fluid flow that would be nearly impossible to obtain in natural opaque soils without expensive equipment or boundary effects. One successful type of translucent clay simulate is lithium sodium magnesium silicate (LNM silicate); however, it’s low density/high void ratio results in higher than typical permeability, low undrained shear strength, and extremely long consolidation times. Until now, translucent soil simulates of only 4.5% by mass LNM silicate to total mass have been possible. This paper provides a method for creating mixtures of translucent LNM silicate gel/glass as high as 15% by mass with the additions of an emulsifier, sodium pyrophosphate decahydrate (SPP), which impedes gelation so additional silicate powder can be added. Further, digital image processing techniques are used to present a relationship between LNM silicate, SPP, and translucency and an analysis of the modified simulate’s permeability and consolidation properties, with comparisons to natural clays, is also included.The lead author would like to acknowledge the excellent work of the undergraduate researchers on this project: Elliese Shaughnessy for the laboratory work and MATLAB programming necessary to create the Laponite-SPP curve, Kristen Ewert for conducting and interpreting the consolidation experiments, Nicholas Boardman for mixing the testing specimens and conducting the permeability experiments, and Tom Anderson for assisting with the permeability experiments. We would also like to thank Dr. Cassandra Rutherford for her assistance on the project. This research was funded through the National Science Foundation, Award Number: 1041604.This is the author accepted manuscript. The final version is available from American Society of Civil Engineers via http://dx.doi.org/10.1061/9780784480151.00

Threats for Global Food Supply of Increasing Surface Ozone - Spatial Assessment of Impacts and Adaptation Options

Surface ozone (O3) is a potent phytotoxic air pollutant and significantly reduces the productivity of important agricultural crops. Growing use of fossil fuel and changes in climate are increasing the global background surface ozone concentrations to levels that threaten regional and global food supply. We performed an integrated modeling study, considering biophysical and crop management factors, to identify the spatial pattern of ozone damage in lands suitable for crop cultivation and to assess the potential for adaptation for four key crops (wheat, maize, rice and soybean) under current and future air quality legislation. Results indicate that China, India and the United States are by far the most affected countries, bearing more than half of all global losses and threatened areas. Short-erm adaptive measures at farm level, such as shifting crop calendars (by changing sowing dates or using crop cultivars with different cycle lengths) can reduce ozone damage regionally but have only limited impact at the global level. Considering these limited benefits of adaptation, mitigation of O3 precursors remains the main option to secure regional and global food production

Microstructural characterization and simulation of damage for geared sheet components

The evolution of damage in geared components manufactured from steel sheets was investigated, to analyse the influence of damage caused by the sheet-bulk-metal forming. Due to the inhomogeneous and multi-axial deformation in the investigated parts, different aspects such as the location-dependent shape and size of voids are analysed by means of various microscopic methods. In particular, a method to characterize the state of damage evolution, i. e. void nucleation, growth and coalescence using scanning electron microscopy (SEM) is applied. The investigations reveal a strong dependence of the void area fraction, shape of voids and thus damage evolution on the loading mode. The microstructural analysis is complemented with FEM simulations using material models which consider the characteristics of the void evolution. © Published under licence by IOP Publishing Ltd

Estudio de la autoasociacion del benceno y del tolueno en solución en ciclohexano

Se determinan los coeficientes de reparto del benceno y del tolueno entre el ciciohexano y el agua a 25°C y los calores de mezcla para los sistemas benceno-ciciohexano y tolueno-ciclohexano. La dependencia marcada de los coeficientes de reparto con la concentración es interpretada en términos de autoasociación del hidrocarburo aromático en la fase orgánica. El fenómeno de la autoasociación es analizado empleando tres modelos distintos: a) dimerización simple; b) autoasociación en cadena de acuerdo a Mecke-Kempter y c) autoasociación en cadena con dos constantes, k^ para la dimerización y k„ para la polimerización. Se halla que este último modelo describe adecuadamente el fenómeno hasta concentraciones de 2mol/I. Los valores hallados para la constante de dimerización, kj = 0,096 I/mol (benceno) y 0,031 I/mol (tolueno) y para la constante de polimerización, kp = 0,087 I/mol (benceno) y 0,043 I/mol (tolueno)muestran la baja estabilidad de los asociados implicados e indican que la polimerización no se halla particularmente favorecida. La combinación de los datos de autoasociación provenientes de los estudios de reparto con los resultados calorimétricos permiten establecer la entalpia promedia de autoasociación, A H = -5,52 KJ/mol y - 5,61 KJ/mol para el benceno y el tolueno respectivamente Se evalúan además las energías libre y entropías de autoasociación. Finalmente se discute la importancia relativa de las interacciones soluto-soluto en la fase orgánica frente a las Interacciones soluto-soluto en el agua

Winter wheat yield prediction using convolutional neural networks from environmental and phenological data

Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction using an extensive dataset of weather, soil, and crop phenology variables in 271 counties across Germany from 1999 to 2019. We proposed a Convolutional Neural Network (CNN) model, which uses a 1-dimensional convolution operation to capture the time dependencies of environmental variables. We used eight supervised machine learning models as baselines and evaluated their predictive performance using RMSE, MAE, and correlation coefficient metrics to benchmark the yield prediction results. Our findings suggested that nonlinear models such as the proposed CNN, Deep Neural Network (DNN), and XGBoost were more effective in understanding the relationship between the crop yield and input data compared to the linear models. Our proposed CNN model outperformed all other baseline models used for winter wheat yield prediction (7 to 14% lower RMSE, 3 to 15% lower MAE, and 4 to 50% higher correlation coefficient than the best performing baseline across test data). We aggregated soil moisture and meteorological features at the weekly resolution to address the seasonality of the data. We also moved beyond prediction and interpreted the outputs of our proposed CNN model using SHAP and force plots which provided key insights in explaining the yield prediction results (importance of variables by time). We found DUL, wind speed at week ten, and radiation amount at week seven as the most critical features in winter wheat yield prediction

The cell receptor level is reduced during persistent infection with influenza C virus

 Persistent influenza C virus infection of MDCK cells perpetuates the viral genome in a cell-associated form. Typically, virus production remains at a low level over extended periods, in the absence of lytic effects of replication. In this study, we demonstrate that persistently infected cells are very restricted in permissiveness for superinfection. By reconstitution experiments, using bovine brain gangliosides as artificial receptors, the degree of super-infection was markedly increased. Analysis of cellular receptor expression revealed reduced concentrations of sialoglycoproteins in general and a limited presentation of the major receptor gp40. Cocultures of persistently infected and uninfected cells (the latter carrying normal receptor levels) initiated a transient rise in virus titers. This kind of induction of virus synthesis appeared to be mainly receptor-linked, since a receptor-deprived subline, MDCK II, did not give rise to a similar effect. Susceptibility of MDCK II cocultures could be partly restored by ganglioside treatment. In accordance to related virus systems, these findings on influenza C virus suggest a role of cell receptor concentrations in the regulation of long-term persistence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42459/1/705-142-6-1155_71421155.pd

Diseño, construcción y calibración de un calorímetro de solución de precisión media

Se descrit)en los criterios de diseño, la construcción y la calibración de un calorímetro isoperit and gt; ólico de solución de precisión media y de bajo costo. Se miden los cambios térmicos mediante un termistor de 15.000 otimios a 293 K, cuya calibración permite encontrar la expresión AT = -52,495 log,o (Rf/Ri) para el cambio de temperatura en función de la resistencia, en el rango de trabajo, 297 a 299 K, La sensibilidad termométríca es 0,00158 K/otimio. El error relativo máximo en las medidas calorimétricas con el sistema de calibración benceno-cíclotiexano es de 3%. el de la capacidad calorífica es de 2,74% y el correspondiente a la diferencia de temperatura es de 1,66%, Se encuentran problemas por la gran pendiente de pérdidas de calor, 0,048 K/mln. (valor máximo observado). El coeficiente de transferencia de calor de las paredes del vaso calorimétrico resultó elevado aunque cumple las especificaciones exigidas