A new method for continuous measurements of oceanic and atmospheric N2O, CO and CO2: performance of off-axis integrated cavity output spectroscopy (OA-ICOS) coupled to non-dispersive infrared detection (NDIR)

A new system for continuous, highly-resolved oceanic and atmospheric measurements of N2O, CO and CO2 is described. The system is based upon off-axis integrated cavity output spectroscopy (OA-ICOS) and a non-dispersive infrared analyzer (NDIR) both coupled to a Weiss-type equilibrator. Performance of the combined setup was evaluated by testing its precision, accuracy, long-term stability, linearity and response time. Furthermore, the setup was tested during two oceanographic campaigns in the equatorial Atlantic Ocean in order to explore its potential for autonomous deployment onboard voluntary observing ships (VOS). Improved equilibrator response times for N2O (2.5 min) and CO (45 min) were achieved in comparison to response times from similar chamber designs used by previous studies. High stability of the OA-ICOS analyzer was demonstrated by low optimal integration times of 2 and 4 min for N2O and CO respectively, as well as detection limits of < 40 ppt and precision better than 0.3 ppb Hz−1/2. Results from a direct comparison of the method presented here and well-established discrete methods for oceanic N2O and CO2 measurements showed very good consistency. The favorable agreement between underway atmospheric N2O, CO and CO2 measurements and monthly means at Ascension Island (7.96°S 14.4°W) further suggests a reliable operation of the underway setup in the field. The potential of the system as an improved platform for measurements of trace gases was explored by using continuous N2O and CO2 data to characterize the development of the seasonal equatorial upwelling in the Atlantic Ocean during two RV/ Maria S. Merian cruises. A similar record of high-resolution CO measurements was simultaneously obtained offering for the first time the possibility of a comprehensive view on the distribution and emissions of these climate relevant gases on the area. The relatively simple underway N2O/CO/CO2 setup is suitable for long-term deployment on board of research and commercial vessels although potential sources of drift such as cavity temperature and further technical improvements towards automation still need to be addressed

Automatic music transcription: challenges and future directions

Automatic music transcription is considered by many to be a key enabling technology in music signal processing. However, the performance of transcription systems is still significantly below that of a human expert, and accuracies reported in recent years seem to have reached a limit, although the field is still very active. In this paper we analyse limitations of current methods and identify promising directions for future research. Current transcription methods use general purpose models which are unable to capture the rich diversity found in music signals. One way to overcome the limited performance of transcription systems is to tailor algorithms to specific use-cases. Semi-automatic approaches are another way of achieving a more reliable transcription. Also, the wealth of musical scores and corresponding audio data now available are a rich potential source of training data, via forced alignment of audio to scores, but large scale utilisation of such data has yet to be attempted. Other promising approaches include the integration of information from multiple algorithms and different musical aspects

Overpressured layer chromatography: from the pressurized ultramicro chamber to BioArena system

The pressurized ultramicro (UM) chamber as a closed adsorbent layer chamber enables the use of a special chromatoplate and a pump to increase and optimize the mobile phase flow velocity through an optional development distance in an adsorbent layer. This chamber is the basic instrument of overpressured-layer chromatography (OPLC), which is a separation technique that combines the advantages of conventional TLC/HPTLC with those of HPLC. The versions of OPLC instrument, the character and achievement of off-line and on-line OPLC systems in analytical and preparative use are described. The development of BioArena as a complex bioautographic system means an exploitation of the unique advantages of planar-layer system for detection, isolation and identification of new antimicrobials, antineoplastics, biopesticides and other biologically active substances as well as for studying fundamental biochemical reactions and mechanisms

Pluto's global surface composition through pixel-by-pixel Hapke modeling of New Horizons Ralph/LEISA data

On July 14th 2015, NASA's New Horizons mission gave us an unprecedented detailed view of the Pluto system. The complex compositional diversity of Pluto's encounter hemisphere was revealed by the Ralph/LEISA infrared spectrometer on board of New Horizons. We present compositional maps of Pluto defining the spatial distribution of the abundance and textural properties of the volatiles methane and nitrogen ices and non-volatiles water ice and tholin. These results are obtained by applying a pixel-by-pixel Hapke radiative transfer model to the LEISA scans. Our analysis focuses mainly on the large scale latitudinal variations of methane and nitrogen ices and aims at setting observational constraints to volatile transport models. Specifically, we find three latitudinal bands: the first, enriched in methane, extends from the pole to 55deg N, the second dominated by nitrogen, continues south to 35deg N, and the third, composed again mainly of methane, reaches 20deg N. We demonstrate that the distribution of volatiles across these surface units can be explained by differences in insolation over the past few decades. The latitudinal pattern is broken by Sputnik Planitia, a large reservoir of volatiles, with nitrogen playing the most important role. The physical properties of methane and nitrogen in this region are suggestive of the presence of a cold trap or possible volatile stratification. Furthermore our modeling results point to a possible sublimation transport of nitrogen from the northwest edge of Sputnik Planitia toward the south.Comment: 43 pages, 7 figures; accepted for publication in Icaru

Computational Modeling and Analysis of Multi-timbral Musical Instrument Mixtures

In the audio domain, the disciplines of signal processing, machine learning, psychoacoustics, information theory and library science have merged into the field of Music Information Retrieval (Music-IR). Music-IR researchers attempt to extract high level information from music like pitch, meter, genre, rhythm and timbre directly from audio signals as well as semantic meta-data over a wide variety of sources. This information is then used to organize and process data for large scale retrieval and novel interfaces. For creating musical content, access to hardware and software tools for producing music has become commonplace in the digital landscape. While the means to produce music have become widely available, significant time must be invested to attain professional results. Mixing multi-channel audio requires techniques and training far beyond the knowledge of the average music software user. As a result, there is significant growth and development in intelligent signal processing for audio, an emergent field combining audio signal processing and machine learning for producing music. This work focuses on methods for modeling and analyzing multi-timbral musical instrument mixtures and performing automated processing techniques to improve audio quality based on quantitative and qualitative measures. The main contributions of the work involve training models to predict mixing parameters for multi-channel audio sources and developing new methods to model the component interactions of individual timbres to an overall mixture. Linear dynamical systems (LDS) are shown to be capable of learning the relative contributions of individual instruments to re-create a commercial recording based on acoustic features extracted directly from audio. Variations in the model topology are explored to make it applicable to a more diverse range of input sources and improve performance. An exploration of relevant features for modeling timbre and identifying instruments is performed. Using various basis decomposition techniques, audio examples are reconstructed and analyzed in a perceptual listening test to evaluate their ability to capture salient aspects of timbre. These tests show that a 2-D decomposition is able to capture much more perceptually relevant information with regard to the temporal evolution of the frequency spectrum of a set of audio examples. The results indicate that joint modeling of frequencies and their evolution is essential for capturing higher level concepts in audio that we desire to leverage in automated systems.Ph.D., Electrical Engineering -- Drexel University, 201