Study of the technique of stellar occultation

The results are reported of a study of the stellar occultation technique for measuring the composition of the atmosphere. The intensity of starlight was monitored during the occultation using the Wisconsin stellar ultraviolet photometers aboard the Orbiting Astronomical Observatory (OAO-A2). A schematic diagram of an occultation is shown where the change in intensity at a given wavelength is illustrated. The vertical projection of the attenuation region is typically 60 km deep for molecular oxygen and 30 km deep for ozone. Intensity profiles obtained during various occultations were analyzed by first determining the tangential columm density of the absorbing gases, and then Abel inverting the column densities to obtain the number density profile. Errors are associated with each step in the inversion scheme and have been considered as an integral part of this study

The solid state photomultiplier: Status of photon counting beyond the near-infrared

Rockwell International's Solid State Photomultiplier (SSPM) is an impurity-band avalanche device which can count individual photons with wavelengths between 0.4 and 28 micrometers. Its response to a photon is a pulse of between 10(exp 4) and 10(exp 5) conduction electrons, making it an important device for use in phenomenology. The characteristics of the SSPM make it a potentially important device for use in astronomical applications. Contract NAS2-12400 was initiated in June 1986 to conduct modeling and characterization studies of the SSPM to provide a basis for assessing its use in astronomical systems. Some SSPM models and results of measurements which characterize the group of SSPMs recently fabricated on this contract are discussed

Direct microwave measurement of Andreev-bound-state dynamics in a proximitized semiconducting nanowire

The modern understanding of the Josephson effect in mesosopic devices derives from the physics of Andreev bound states, fermionic modes that are localized in a superconducting weak link. Recently, Josephson junctions constructed using semiconducting nanowires have led to the realization of superconducting qubits with gate-tunable Josephson energies. We have used a microwave circuit QED architecture to detect Andreev bound states in such a gate-tunable junction based on an aluminum-proximitized InAs nanowire. We demonstrate coherent manipulation of these bound states, and track the bound-state fermion parity in real time. Individual parity-switching events due to non-equilibrium quasiparticles are observed with a characteristic timescale $T_\mathrm{parity} = 160\pm 10~\mathrm{\mu s}$. The $T_\mathrm{parity}$ of a topological nanowire junction sets a lower bound on the bandwidth required for control of Majorana bound states

Unsupervised Color Image Segmentation: with Application to Skin Tumor Borders

The images used in this research were digitized from 35mm color photographic slides obtained from a private dermatology practice and from New York University. The authors compared 6 color segmentation methods and their effectiveness as part of an overall border-finding algorithm. The PCT/median cut and adaptive thresholding algorithms provided the lowest average error and show the most promise for further individual algorithm development. Combining the different methods resulted in further improvement in the number of correctly identified tumor borders, and by incorporating additional heuristics in merging the segmented object information, one could potentially further increase the success rate. The algorithm is broad-based and suggests several areas for further research. One possible area of exploration is to incorporate an intelligent decision making process as to the number of colors that should be used for segmentation in the PCT/median cut and adaptive thresholding algorithms. For comparison purposes, the number of colors was kept constant at three in the authors\u27\u27 application. Other areas that can be explored are noise removal and object classification to determine the correct tumor objec

PlaNet - Photo Geolocation with Convolutional Neural Networks

Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to construct situations where no location can be inferred. Yet images often contain informative cues such as landmarks, weather patterns, vegetation, road markings, and architectural details, which in combination may allow one to determine an approximate location and occasionally an exact location. Websites such as GeoGuessr and View from your Window suggest that humans are relatively good at integrating these cues to geolocate images, especially en-masse. In computer vision, the photo geolocation problem is usually approached using image retrieval methods. In contrast, we pose the problem as one of classification by subdividing the surface of the earth into thousands of multi-scale geographic cells, and train a deep network using millions of geotagged images. While previous approaches only recognize landmarks or perform approximate matching using global image descriptors, our model is able to use and integrate multiple visible cues. We show that the resulting model, called PlaNet, outperforms previous approaches and even attains superhuman levels of accuracy in some cases. Moreover, we extend our model to photo albums by combining it with a long short-term memory (LSTM) architecture. By learning to exploit temporal coherence to geolocate uncertain photos, we demonstrate that this model achieves a 50% performance improvement over the single-image model

Effect of Self-Efficacy on Weight Loss: A Psychosocial Analysis of a Community-Based Adaptation of the Diabetes Prevention Program Lifestyle Intervention

Objective. Weight loss is the most effective approach to reducing diabetes risk. It is a research priority to identify factors that may enhance weight loss success, particularly among those at risk for diabetes. This analysis explored the relationships between self-efficacy, weight loss, and dietary fat intake among adults at risk for developing type 2 diabetes. Methods. This pilot, site-randomized trial was designed to compare group-based Diabetes Prevention Program lifestyle intervention delivery by YMCA staff to brief counseling alone (control) in 92 adults at risk for diabetes (BMI ≥ 24 kg/m2, ≥ 2 diabetes risk factors, and a random capillary blood glucose of 110–199 mg/dl). Self-efficacy was measured using the Weight Efficacy Lifestyle questionnaire. Data were collected at baseline, 6 months, and 12 months. A paired t test was used to determine within-group changes in self-efficacy and weight at 6 and 12 months. Using a fitted model, we estimated how much of an increase in self-efficacy was related to a 5% weight reduction at 6 and 12 months. Results. Self-efficacy was associated with a 5% reduction in baseline weight at 6 and 12 months but was not related to fat intake. Conclusion. These findings suggest that it is important to assess the level of self-efficacy when counseling adults at high risk for diabetes about weight loss. Certain aspects of self-efficacy seem to play a greater role, depending on the stage of weight loss

Program on Earth Observation Data Management Systems (EODMS)

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products