Parkin uses the UPS to ship off dysfunctional mitochondria

Parkin is a ubiquitin E3 ligase that is implicated in familial Parkinson disease (PD). Previous studies have established its role in mitophagy, a pathway whereby dysfunctional mitochondria are targeted for autophagic degradation. We recently reported that a major function of Parkin in dysfunctional mitochondria is to activate the ubiquitin-proteasome system (UPS) for proteolysis of multiple outer membrane proteins, and that such activation of the UPS is a critical step in Parkin-mediated mitophagy. Here, we discuss the possible roles of the UPS in mitophagy and the pathogenesis of PD

Optimal design of gas adsorption refrigerators for cryogenic cooling

The design of gas adsorption refrigerators used for cryogenic cooling in the temperature range of 4K to 120K was examined. The functional relationships among the power requirement for the refrigerator, the system mass, the cycle time and the operating conditions were derived. It was found that the precool temperature, the temperature dependent heat capacities and thermal conductivities, and pressure and temperature variations in the compressors have important impacts on the cooling performance. Optimal designs based on a minimum power criterion were performed for four different gas adsorption refrigerators and a multistage system. It is concluded that the estimates of the power required and the system mass are within manageable limits in various spacecraft environments

BANDIT in NASTRAN

BANDIT has been implemented into the NASTRAN April '83 release. It is now a permanent feature in NASTRAN and will be included in all future releases for all four computing machines (IBM, CDC, UNIVAC, and VAX). Originally BANDIT operated as a preprocessor of NASTRAN. It read the NASTRAN input cards and produced a set of resequencing (SEOGP) cards that would greatly reduce the computational time required by the matrix decomposition module of NASTRAN for a large structure. In the past, many computer centers had installed BANDIT in their systems together with the NASTRAN program. The user would run the BANDIT program and NASTRAN as if they were one program (or two separated programs depending on how the two programs were actually tied together in the computer systems). In some cases, the user was required to pass the input cards and the output SEQGP cards between the two programs, and n others, the data was manipulated through the use of cataloged disc files. Although there is nothing wrong with this BANDIT-NASTRAN arrangement, there are, however, several shortcomings which are mentioned in this paper. The BANDIT in the NASTRAN April '83 release has removed all the deficiencies, and it comes in one version applicable to the four computing machines

COSMIC/NASTRAN Free-field Input

A user's guide to the COSMIC/NASTRAN free field input for the Bulk Data section of the NASTRAN program is proposed. The free field input is designed to be user friendly and the user is not forced out of the computer system due to input errors. It is easy to use, with only a few simple rules to follow. A stand alone version of the COSMIC/NASTRAN free field input is also available. The use of free field input is illustrated by a number of examples

A Convex Model for Edge-Histogram Specification with Applications to Edge-preserving Smoothing

The goal of edge-histogram specification is to find an image whose edge image has a histogram that matches a given edge-histogram as much as possible. Mignotte has proposed a non-convex model for the problem [M. Mignotte. An energy-based model for the image edge-histogram specification problem. IEEE Transactions on Image Processing, 21(1):379--386, 2012]. In his work, edge magnitudes of an input image are first modified by histogram specification to match the given edge-histogram. Then, a non-convex model is minimized to find an output image whose edge-histogram matches the modified edge-histogram. The non-convexity of the model hinders the computations and the inclusion of useful constraints such as the dynamic range constraint. In this paper, instead of considering edge magnitudes, we directly consider the image gradients and propose a convex model based on them. Furthermore, we include additional constraints in our model based on different applications. The convexity of our model allows us to compute the output image efficiently using either Alternating Direction Method of Multipliers or Fast Iterative Shrinkage-Thresholding Algorithm. We consider several applications in edge-preserving smoothing including image abstraction, edge extraction, details exaggeration, and documents scan-through removal. Numerical results are given to illustrate that our method successfully produces decent results efficiently