Detection techniques for tenuous planetary atmospheres Semiannual report, 1 Jul. - 31 Dec. 1968

Absorption and desorption of oxygen by zinc oxide film irradiated by ultraviolet ligh

Detection techniques for tenuous planetary atmospheres

The application of detectors developed for analysis of planetary atmospheres under partial vacuum conditions, and data obtained during dust charging studies to various industrial problems is summarized. A specialized apparatus for dust measurements on a planetary lander was designed with the capability of measuring ambient dust density as a function of particle size, as well as for observing the charge of the collected dust. the optical system operates on an intermittent basis and requires only low power. No radioactive source or delicate detection equipment is required. Advances in monitoring catalyst operation by means of exoelection emission are also reported

Detection techniques for tenuous planetary atmospheres Semiannual report, 1 Jan. - 30 Jun. 1970

Developing techniques and detectors for analysis of planetary atmosphere

A multipoint field ionization source Final report, 11 Nov. 1966 - 12 Apr. 1968

Experimental study on use of field ionization and electron emission as ion sources for mass spectrometer

Detection techniques for tenuous planetary atmospheres Fifth six-month report, 1 Jul. - 30 Dec. 1965

Physical methods description for detection and analysis of tenuous planetary atmospheric component gases, especially water vapo

Detection techniques for tenuous planetary atmospheres

Electrostatic charging of dust and its effect on planetary atmospheres is discussed, along with its applications to Martian atmosphere. Laboratory and field experiments in dust storms indicate that the major atmospheric parameters on Mars include: (1) pressure, temperature, and relative humidity; (2) wind velocity and direction; (3) particulate size and composition; and (4) electrostatic charge and field gradient. Various instrumentation techniques adapted for a Mars Lander are briefly reviewed. The effect of exoelectron emission on surface catalysis is studied

Detection techniques for tenuous planetary atmospheres Semiannual report, 1 Jul. - 31 Dec. 1970

Development and characteristics of detectors for analysis of planetary atmosphere

Differential interferometry of QSO broad-line regions - I. Improving the reverberation mapping model fits and black hole mass estimates

Reverberation mapping (RM) estimates the size and kinematics of broad-line regions (BLR) in quasars and type I AGNs. It yields size–luminosity relation to make QSOs standard cosmological candles, and mass–luminosity relation to study the evolution of black holes and galaxies. The accuracy of these relations is limited by the unknown geometry of the BLR clouds distribution and velocities. We analyse the independent BLR structure constraints given by super-resolving differential interferometry. We developed a three-dimensional BLR model to compute all differential interferometry and RM signals. We extrapolate realistic noises from our successful observations of the QSO 3C 273 with AMBER on the VLTI. These signals and noises quantify the differential interferometry capacity to discriminate and measure BLR parameters including angular size, thickness, spatial distribution of clouds, local-to-global and radial-to-rotation velocity ratios, and finally central black hole mass and BLR distance. A Markov Chain Monte Carlo model-fit, of data simulated for various VLTI instruments, gives mass accuracies between 0.06 and 0.13?dex, to be compared to 0.44?dex for RM mass–luminosity fits. We evaluate the number of QSOs accessible to observe with current (AMBER), upcoming (GRAVITY) and possible (OASIS with new generation fringe trackers) VLTI instruments. With available technology, the VLTI could resolve more than 60 BLRs, with a luminosity range larger than four decades, sufficient for a good calibration of RM mass–luminosity laws, from an analysis of the variation of BLR parameters with luminosity

Methods for Identifying Species Complexes Using a Novel Suite of Multivariate Approaches and Multiple Data Sources: A Case Study With Gulf of Alaska Rockfish

International and national laws governing the management of living marine resources generally require specification of harvest limits. To assist with the management of data-limited species, stocks are often grouped into complexes and assessed and managed as a single unit. The species that comprise a complex should have similar life history, susceptibility to the fishing gear, and spatial distribution, such that common management measures will likely lead to sustainable harvest of all species in the complex. However, forming complexes to meet these standards is difficult due to the lack of basic biological or fisheries data to inform estimates of biological vulnerability and fishery susceptibility. A variety of cluster and ordination techniques are applied to bycatch rockfish species in the Gulf of Alaska (GOA) as a case study to demonstrate how groupings may differ based on the multivariate techniques used and the availability and reliability of life history, fishery independent survey, and fishery catch data. For GOA rockfish, our results demonstrate that fishing gear primarily defined differences in species composition, and we suggest that these species be grouped by susceptibility to the main fishing gears while monitoring those species with high vulnerabilities to overfishing. Current GOA rockfish complex delineations (i.e., Other Rockfish and Demersal Shelf Rockfish) are consistent with the results of this study, but should be expanded across the entire GOA. Differences observed across species groupings for the variety of data types and multivariate approaches utilized demonstrate the importance of exploring a diversity of methods. As best practice in identifying species complexes, we suggest using a productivity-susceptibility analysis or expert judgement to begin groupings. Then a variety of multivariate techniques and data sources should be used to identify complexes, while balancing an appropriate number of manageable groups. Thus, optimal species complex groupings should be determined by commonality and consistency among a variety of multivariate methods and datasets