Lossless image compression by LMS adaptive filter banks

A lossless image compression algorithm based on adaptive subband decomposition is proposed. The subband decomposition is achieved by a two-channel LMS adaptive filter bank. The resulting coefficients are lossy coded first, and then the residual error between the lossy and error-free coefficients is compressed. The locations and the magnitudes of the nonzero coefficients are encoded separately by an hierarchical enumerative coding method. The locations of the nonzero coefficients in children bands are predicted from those in the parent band. The proposed compression algorithm, on the average, provides higher compression ratios than the state-of-the-art methods

The role of the family in attributing meaning to living with HIV and its stigma in Turkey

Stigma attached to HIV/AIDS remains a global problem, with severe negative consequences for people living with HIV (PLHIV). Family support is fundamental for PLHIV’s psychological and physical well-being. HIV-related stigma is high in Turkey, where HIV/AIDS prevalence is low and the epidemic is not considered a priority. Based on qualitative data generated with HIV-positive women and men, this article explores the process of stigmatization, as experienced and perceived by PLHIV in Turkey, focusing on the institution of the family. Results indicated that enacted stigma from family members is lower than anticipated. While most participants’ narratives showed patterns of support rather than rejection from families, the strong expectations around the cultural value attributed to “the family” are found to be the main facilitators of internalized stigma. The article critically discusses the meaning and implications of family support, addressing the role of patriarchal values attributed to womanhood, manhood, and sexuality in Turkey

Understanding atmospheric organic aerosols via factor analysis of aerosol mass spectrometry: a review

Organic species are an important but poorly characterized constituent of airborne particulate matter. A quantitative understanding of the organic fraction of particles (organic aerosol, OA) is necessary to reduce some of the largest uncertainties that confound the assessment of the radiative forcing of climate and air quality management policies. In recent years, aerosol mass spectrometry has been increasingly relied upon for highly time-resolved characterization of OA chemistry and for elucidation of aerosol sources and lifecycle processes. Aerodyne aerosol mass spectrometers (AMS) are particularly widely used, because of their ability to quantitatively characterize the size-resolved composition of submicron particles (PM1). AMS report the bulk composition and temporal variations of OA in the form of ensemble mass spectra (MS) acquired over short time intervals. Because each MS represents the linear superposition of the spectra of individual components weighed by their concentrations, multivariate factor analysis of the MS matrix has proved effective at retrieving OA factors that offer a quantitative and simplified description of the thousands of individual organic species. The sum of the factors accounts for nearly 100% of the OA mass and each individual factor typically corresponds to a large group of OA constituents with similar chemical composition and temporal behavior that are characteristic of different sources and/or atmospheric processes. The application of this technique in aerosol mass spectrometry has grown rapidly in the last six years. Here we review multivariate factor analysis techniques applied to AMS and other aerosol mass spectrometers, and summarize key findings from field observations. Results that provide valuable information about aerosol sources and, in particular, secondary OA evolution on regional and global scales are highlighted. Advanced methods, for example a-priori constraints on factor mass spectra and the application of factor analysis to combined aerosol and gas phase data are discussed. Integrated analysis of worldwide OA factors is used to present a holistic regional and global description of OA. Finally, different ways in which OA factors can constrain global and regional models are discussed

Observing clouds in 4d with multiview stereophotogrammetry

Six cameras along a 12-km-diameter circle generate a 4D view of clouds at the Southern Great Plains atmospheric observatory in Oklahoma

Observing clouds in 4d with multiview stereophotogrammetry

Six cameras along a 12-km-diameter circle generate a 4D view of clouds at the Southern Great Plains atmospheric observatory in Oklahoma