Credit Rationing in the U.S. Mortgage Market: Evidence from Variation in FHA Market Shares

This paper examines the nature of mortgage credit rationing across geographic markets and time. Particular attention is paid to the response of conventional mortgage supply to higher risk conditions associated with regional recessions. We develop a series of four indirect tests based on the spatial variation of the FHA share of mortgages, both endorsements and applications, as well as FHA and conventional rejection rates. Results of these four tests indicate that conventional mortgage underwriting criteria do not become more flexible and may even become more demanding when local economic conditions deteriorate. This result indicates the use of non-price credit rationing in the mortgage market and suggests a special role for FHA-insured mortgages as a mechanism for maintaining mortgage credit supply in declining housing markets

Local Economic Risk Factors on the Primary and Secondary Mortgage Markets

This paper presents a cross-sectional analysis of the spatial distribution of loans in the primary and secondary mortgage markets. Aggregating loan originations to the MSA level, we examine the proportion of the market served by FHA and conventional lenders. We model the geographic differences in market shares as a function of supply, demand, and economic risk factors. Results indicate that FHA market shares are higher in cities with higher economic risk characteristics. To examine the role of GSE activity, we model the spatial distribution of the disposition of conventional loans. Again, we focus on the impact of local economic risk factors on the proportion of loans purchased by the GSEs, purchased by other financial institutions, or retained by the originating lender. Our results indicate that GSEs purchase rates are fairly insensitive to local economic conditions indicating that they serve the primary market with little spatial variation

Automated Extraction of Fire Line Parameters from Multispectral Infrared Images

Remotely sensed infrared images are often used to assess wildland ¯re conditions. Separately, ¯re propagation models are in use to forecast future conditions. In the Dynamic Data Driven Application System (DDDAS) concept, the ¯re propagation model will react to the image data, which should produce more accurate predictions of ¯re propagation. In this study we describe a series of image processing tools that can be used to extract ¯re propagation parameters from multispectral infrared images so that the parameters can be used to drive a ¯re propagation model built upon the DDDAS concept. The method is capable of automatically determining the ¯re perimeter, active ¯re line, and ¯re propagation direction. A multi-band image gradient calculation, the Normalized Di®erence Vegetation Index, and the Normalized Di®erence Burn Ratio along with several standard image processing techniques are used to identify and constrain the ¯re propagation parameters. These ¯re propagation parameters can potentially be used within the DDDAS modeling framework for model update and adjustment

Identity and agency in school and afterschool settings: Investigating digital media’s supporting role

This study documents opportunities for identity and agency experienced by students in urban school and afterschool contexts, with a focus on digital media’s role in shaping these opportunities. We conducted focus groups and interviews with 43 students and six teachers affiliated with an urban public high school and a network of afterschool programs in the United States, as well as participant observations of nine afterschool sessions and three school classes. Compared to school, afterschool programs afforded students greater opportunities for identity expression, with digital media generally playing a supporting role. We found that the institutional constraints and sociopolitical dynamics that shape students’ experiences in school and afterschool contexts are largely mirrored in the ways technology is used in these contexts. Introducing digital media into a setting will not necessarily change these dynamics, though we did see potential for disruption in some afterschool settings. The findings provide new insight into digital media’s role in supporting identity and agency in school and afterschool settings

A Hybrid (Monte-Carlo/Deterministic) Approach for Multi-Dimensional Radiation Transport

A novel hybrid Monte Carlo transport scheme is demonstrated in a scene with solar illumination, scattering and absorbing 2D atmosphere, a textured reflecting mountain, and a small detector located in the sky (mounted on a satellite or a airplane). It uses a deterministic approximation of an adjoint transport solution to reduce variance, computed quickly by ignoring atmospheric interactions. This allows significant variance and computational cost reductions when the atmospheric scattering and absorption coefficient are small. When combined with an atmospheric photon-redirection scheme, significant variance reduction (equivalently acceleration) is achieved in the presence of atmospheric interactions

A facile way to produce epoxy nanocomposites having excellent thermal conductivity with low contents of reduced graphene oxide

A well-dispersed phase of exfoliated graphene oxide (GO) nanosheets was initially prepared in water. This was concentrated by centrifugation and was mixed with a liquid epoxy resin. The remaining water was removed by evaporation, leaving a GO dispersion in epoxy resin. A stoichiometric amount of an anhydride curing agent was added to this epoxy-resin mixture containing the GO nanosheets, which was then cured at 90 C for 1 h followed by 160 C for 2 h. A second thermal treatment step of 200 C for 30 min was then undertaken to reduce further the GO in situ in the epoxy nanocomposite. An examination of the morphology of such nanocomposites containing reduced graphene oxide (rGO) revealed that a very good dispersion of rGO was achieved throughout the epoxy polymer. Various thermal and mechanical properties of the epoxy nanocomposites were measured, and the most noteworthy finding was a remarkable increase in the thermal conductivity when relatively very low contents of rGO were present. For example, a value of 0.25 W/mK was measured at 30 C for the nanocomposite with merely 0.06 weight percentage (wt%) of rGO present, which represents an increase of *40% compared with that of the unmodified epoxy polymer. This value represents one of the largest increases in the thermal conductivity per wt% of added rGO yet reported. These observations have been attributed to the excellent dispersion of rGO achieved in these nanocomposites made via this facile production method. The present results show that it is now possible to tune the properties of an epoxy polymer with a simple and viable method of GO addition. A

Lightning strike damage resistance of carbon‐fiber composites with nanocarbon‐modified epoxy matrices

Carbon‐fiber reinforced polymer (CFRP) composites are replacing metal alloys in aerospace structures, but they can be vulnerable to lightning strike damage if not adequately protected due to the poor electrical conductivity of the polymeric matrix. In the present work, to improve the conductivity of the CFRP, two electrically conductive epoxy formulations were developed via the addition of 0.5 wt% of graphene nanoplatelets (GNPs) and a hybrid of 0.5 wt% of GNPs/carbon nanotubes (CNTs) at an 8:2 mass ratio. Unidirectional CFRP laminates were manufactured using resin‐infusion under flexible tooling (RIFT) and wet lay‐up (WL) processes, and subjected to simulated lightning strike tests. The electrical performance of the RIFT plates was far superior to that of the WL plates, independent of matrix modification, due to their greater carbon‐fiber volume fraction. The GNP‐modified panel made using RIFT demonstrated an electrical conductivity value of 8 S/cm. After the lightning strike test, the CFRP panel remains largely unaffected as no perforation occurs. Damage is limited to matrix degradation within the top ply at the point of impact and localized charring of the surface. The GNP‐modified panel showed a comparable level of resistance against lightning damage with the existing copper mesh technology, offering at the same time a 20% reduction in the structural weight. This indicates a feasible route to improve the lightning strike damage resistance of carbon‐fiber composites without the addition of extra weight, hence reducing fuel consumption but not safety

Modular Robotic Vehicle

A modular robotic vehicle includes a chassis, driver input devices, an energy storage system (ESS), a power electronics module (PEM), modular electronic assemblies (eModules) connected to the ESS via the PEM, one or more master controllers, and various embedded controllers. Each eModule includes a drive wheel containing a propulsion-braking module, and a housing containing propulsion and braking control assemblies with respective embedded propulsion and brake controllers, and a mounting bracket covering a steering control assembly with embedded steering controllers. The master controller, which is in communication with each eModule and with the driver input devices, communicates with and independently controls each eModule, by-wire, via the embedded controllers to establish a desired operating mode. Modes may include a two-wheel, four-wheel, diamond, and omni-directional steering modes as well as a park mode. A bumper may enable docking with another vehicle, with shared control over the eModules of the vehicles