Higher Ed Do Not Resuscitate Orders

Congress has effectively precluded all institutions of higher education from reorganizing in the bankruptcy courts because it was concerned about exploitative profiteers opening fly-by-night colleges, defrauding students, and then finding refuge in bankruptcy. This choice harms students, employees, creditors, and communities. As such, this Article advocates that Congress should reverse its decision and allow IHEs to reorganize in bankruptcy without losing access to federal student loan and grant programs. To support this argument, this Article contrasts the bankruptcy treatment of healthcare enterprises to that of higher education enterprises. In doing so, this Article builds on my own prior work and contributes to the literature on higher education bankruptcies

The Magic of Fintech? Insights for a Regulatory Agenda from Analyzing Student Loan Complaints Filed with the CFPB

This Article looks at consumer complaints about student loan lenders and servicers from the Consumer Financial Protection Bureau’s (CFPB’s) consumer complaint database. Using a novel dataset drawn from 30,678 complaints filed against 212 student loan companies, we analyze consumers’ subjective views about whether traditional or fintech student loan lenders and servicers provide a better customer experience. Overall, we find that consumers initiate far fewer complaints against fintech lenders than traditional lenders. But we find that fintech lenders are 28 times more likely than traditional lenders to receive complaints for making confusing or misleading advertisements. Our data also show that complaints against fintech lenders or servicers have not risen in parallel with greater loan volume by those firms. By comparison, traditional lenders and servicers have received rising numbers of complaints. We consider various reasons for this difference, including whether this means fintech student loan companies are providing a better consumer experience

Equations of state implementation for 1-D modelling of performance in ram accelerator thermally choked propulsion mode

© 2015 Inderscience Enterprises Ltd. This paper presents advancement on one-dimensional (1-D) unsteady modelling of a ram accelerator (RAMAC) in the sub-detonative velocity regime by including real-gas equations of state (EoS) in order to account for the compressibility effects of the combustion products. Several equations of state based on generalised empirical and theoretical considerations are incorporated into a 1-D computer code TARAM. The objective of this work is to provide the best available formulations in order to improve the unsteady 1-D model and make the TARAM code a useful tool to predict the performance of the RAMAC in the sub-detonative velocity regime, without having to resort to more complicated 2-D or 3-D computational schemes. The calculations are validated against experimental data from 38-mm and 90-mm-bore facilities and good agreements have been achieved. Yet, the results demonstrate the need for further CFD studies involving the scale effect

A Preliminary Foil Gas Bearing Performance Map

Recent breakthrough improvements in foil gas bearing load capacity, high temperature tribological coatings and computer based modeling have enabled the development of increasingly larger and more advanced Oil-Free Turbomachinery systems. Successful integration of foil gas bearings into turbomachinery requires a step wise approach that includes conceptual design and feasibility studies, bearing testing, and rotor testing prior to full scale system level demonstrations. Unfortunately, the current level of understanding of foil gas bearings and especially their tribological behavior is often insufficient to avoid developmental problems thereby hampering commercialization of new applications. In this paper, a new approach loosely based upon accepted hydrodynamic theory, is developed which results in a "Foil Gas Bearing Performance Map" to guide the integration process. This performance map, which resembles a Stribeck curve for bearing friction, is useful in describing bearing operating regimes, performance safety margins, the effects of load on performance and limiting factors for foil gas bearings

Project Minerva: A low-cost manned Mars mission based on indigenous propellant production

Project Minerva is a low-cost manned Mars mission designed to deliver a crew of four to the Martian surface, using only two sets of two launches. Key concepts which make this mission realizable are the use of near-term technologies and in-situ propellant production, following the senario originally proposed by R. Zubrin of Martin Marietta. The first set of launches delivers two unmanned payloads into low earth orbit (LEO): one consists of an Earth Return Vehicle (ERV), a propellant production plant, and a set of robotic vehicles, and the second consists of the upper stage/trans-Mars injection (TMI) booster. In LEO, the two payloads are joined and inserted into a Mars transfer orbit. The landing on Mars is performed with the aid of multiple aerobraking maneuvers. On the Martian surface, the propellant production plant uses a Sabatier/electrolysis-type process to combine six tons of hydrogen brought from earth with carbon dioxide from the Martian atmosphere to produce 100 tons of liquid oxygen and methane, which are later used as the propellants for the rover expeditions and the manned return journey of the ERV. Once the in-situ propellant production is completed, approximately two years after the first set of launches, the manned portion of the mission leaves earth. This set of two launches is similar to that of the unmanned vehicles; the two payloads are the Manned Transfer Vehicle (MTV) and the upper stage/TMI booster. The MTV contains the manned rover and the habitat which houses the astronauts enroute to Mars and on the Martian surface. During the 180-day trip to Mars, artificial gravity is created by tethering the MTV to the TMI booster and inducing rotation. Upon arrival the MTV performs aerobraking maneuvers to land near the fully-fueled ERV, which will be used by the crew a year and a half later to return to earth. The mission entails moderate travel times with relatively low-energy conjunction-class trajectories and allows ample time for scientific exploration. This set of missions can be repeated every two years in order to continue exploration at a variety of sites and gradually establish the infrastructure for a permanent base on Mars

UW Dawgstar: One Third of ION-F - An element of the Ionospheric Observation Nanosatellite Formation (ION-F)

The preliminary design for the UW Dawgstar nanosatellite is presented. The Dawgstar is a 13 kg satellite designed as a part of the University Nanosatellite Program funded by AFOSR, DARPA, AFRL, and NASA. The goal of this two-year program is to design, build, and fly nanosatellites. The mission overview is detailed, including the coupling with the University partners Utah State and Virginia Tech in the Ionospheric Observation Nanosatellite Formation (ION-F). The mission includes several formations and formation keeping experiments, and distributed ionospheric measurements. Each of the subsystems is also detailed, including the design and integration of eight miniature pulsed plasma thrusters for attitude control and formation flying

The Promise and Perils of Algorithmic Lenders’ Use of Big Data

Tens of millions of Americans lack access to traditional forms of credit and must rely on payday and pawn loans instead. “Algorithmic lending 2.0” promises to enable fintech companies to lend to those excluded from traditional forms of credit. Version 2.0 algorithmic lenders claim to use Big Data and machine learning to increase credit access by making better predictions about prospective borrowers’ creditworthiness and decreasing the cost of credit. Supporters also claim that algorithmic lending 2.0 removes human bias from the financial services sector. Detractors have cast doubt on both claims, arguing that there is scant evidence that algorithmic lending 2.0 expands credit access in non-predatory ways or that substituting algorithms for loan officers reduces discrimination. This Article evaluates the existing regulatory framework to determine if regulation can support the promise of algorithmic lending 2.0 without imperiling the vulnerable