In an empirical study on the classification of the psychoses, 302 patients were rated using the Longitudinal Psychopathology Schedule. The data were condensed by factor analysis, which yielded 10 factors - mania and schizomania, depression and suicidal activity, and 6 factors concerned with psychotic symptoms (verbal hallucinosis/passivity, delusion formation, defect symptoms, social decline, cycloid symptomatology and a factor loading depressive auditory hallucinations and visual hallucinations). Provisional diagnostic groups were obtained using DSM III. Discriminant function analyses showed that the only clearly distinct diagnostic group was bipolar disorder, and this was true for various definitions. Canonical variate analyses were performed using 3- and 4-criterion groups. These showed that a group corresponding approximately to cycloid psychosis also met criteria for being a distinct group. The most detailed examination pf the data, using 4-criterion groups and serial reclassification, suggested that the psychoses might fall into 5 groups - bipolar disorder, cycloid psychosis, depression, defect states and schizoaffective depression.

Los camélidos sudamericanos han sido uno de los recursos de mayor importancia desde la llegada de los primeros humanos al continente, registrándose su domesticación para los Andes centro-sur alrededor de 4400-3000 aP. Las investigaciones realizadas en la región Chaco-Santiagueña para la etapa Agroalfarera (350 dC hasta la conquista española en el siglo dieciséis) en su mayoría han interpretado la presencia o ausencia de la especie doméstica de camélidos Lama glama a partir de fuentes etnohistóricas o por consideraciones eto-ecológicas. Sin embargo, con el avance de los estudios zooarqueológicos en la región, asignamos por técnicas osteométricas y análisis estadísticos multivariados especímenes al taxón L. glama para un sitio Agroalfarero tardío (ca. 1200-1500 dC). En este trabajo se incorporan sitios de toda la secuencia Agroalfarera y de distintas zonas geográficas de la región Chaco-Santiagueña con el fin de diferenciar especies de camélidos. A partir de los resultados se interpreta el posible uso de camélidos silvestres y domesticados en la región desde los primeros grupos sedentarios. El uso de llamas podría haber sido una herramienta importante para el establecimiento de redes de interacción social a grandes distancias.

This article presents a corpus-based investigation of the motivations behind the use of the s-passive and the bli-passive in contemporary written Swedish. Following a probabilistic approach to language variation and building on observations in the literature, we examine the simultaneous effects of semantic and syntactic factors by means of a multivariate statistical analysis. Our corpus sample includes 1,197 passive sentences of three Swedish verbs, which alternate in their use of the passive (acceptera ‘accept’, behandla ‘treat’ and välja ‘choose’). The results suggest that the choice of passive form is significantly associated with five predictor variables: Subject Animacy, Subject Number, Modal Verb, Av-phrase (‘by’-phrase) and Aktionsart. Among these, Subject Animacy and Modal Verb appear to yield the strongest impact effect on the choice of passive form. The study adds to earlier research in that it allows for a more accurate analysis of the simultaneous effect and relative strength of each factor on the speaker's choice of one of the passive forms.

Helium accumulation negatively impacts structural materials used in neutron-irradiated environments, such as fission and fusion reactors. Next-generation fission and fusion reactors will require structural materials, such as steels, that are resistant to large neutron doses yet see service temperatures in the range most affected by helium embrittlement. Previous work has indicated the difficulty of experimentally differentiating nanometer-sized cavities such as helium bubbles from the Ti–Y–O rich nanoclusters (NCs) in radiation-tolerant nanostructured ferritic alloys (NFAs). Because the NCs are expected to sequester helium away from grain boundaries and reduce embrittlement, experimental methods to study simultaneously the NC and bubble populations are needed. In this study, aberration-corrected scanning transmission electron microscopy (STEM) results combining high-collection-efficiency X-ray spectrum images (SIs), multivariate statistical analysis (MVSA), and Fresnel-contrast bright-field STEM imaging, have been used for such a purpose. Fresnel-contrast imaging, with careful attention to TEM-STEM reciprocity, differentiates bubbles from NCs. MVSA of X-ray SIs unambiguously identifies NCs. Therefore, combined Fresnel-contrast STEM and X-ray SI is an effective STEM-based method to characterize helium-bearing NFAs.

A hybrid nanobeam diffraction/imaging method, which combines well-developed diffraction imaging with nanobeam diffraction (NBD) pattern analysis, is described for structural mapping of disordered materials. Spatially resolved crystallographic information is obtained by NBD imaging by collecting NBD patterns at predefined intervals within a field of interest. The resulting dataset of NBD patterns is preprocessed to produce a spectral-imaging-like dataset and is further analyzed via multivariate statistical analysis methods in order to extract the relevant structural components and their distribution within the area of the sample under study without prior knowledge. Additional radial distribution function analysis of either the principal components or averaged data provides real-space maps of short-range order within the field of interest. This technique is demonstrated for two systems, one with multiple amorphous phases and one with multiple phases (amorphous and nanocrystalline) with similar chemistry.

Hyperspectral cathodoluminescence imaging provides spectrally and spatially resolved information on luminescent materials within a single dataset. Pushing the technique toward its ultimate nanoscale spatial limit, while at the same time spectrally dispersing the collected light before detection, increases the challenge of generating low-noise images. This article describes aspects of the instrumentation, and in particular data treatment methods, which address this problem. The methods are demonstrated by applying them to the analysis of nanoscale defect features and fabricated nanostructures in III-nitride-based materials.

A new aberration-corrected scanning transmission electron microscope equipped with an array of Si-drift energy-dispersive X-ray spectrometers has been utilized to acquire spectral image data at atomic resolution. The resulting noisy data were subjected to multivariate statistical analysis to noise filter, remove an unwanted and partially overlapping non-sample-specific X-ray signal, and extract the relevant correlated X-ray signals (e.g., channels with L and K lines). As an example, the Y2Ti2O7 pyrochlore-structured oxide (assumed here to be ideal) was interrogated at the [011] projection. In addition to pure columns of Y and Ti, at this projection, there are also mixed 50-50 at. % Y-Ti columns. An attempt at atomic-resolution quantification is presented. The method proposed here is to subtract the non-column-specific signal from the elemental components and then quantify the data based upon an internally derived k-factor. However, a theoretical basis to predict this non-column-specific signal is needed to make this generally applicable.

Multivariate statistical analysis methods have been applied to scanning transmission electron microscopy (STEM) energy-dispersive X-ray spectral images. The particular application of the multivariate curve resolution (MCR) technique provides a high spectral contrast view of the raw spectral image. The power of this approach is demonstrated with a microelectronics failure analysis. Specifically, an unexpected component describing a chemical contaminant was found, as well as a component consistent with a foil thickness change associated with the focused ion beam specimen preparation process. The MCR solution is compared with a conventional analysis of the same spectral image data set.

A comprehensive three-dimensional (3D) microanalysis procedure using a combined scanning electron microscope (SEM)/focused ion beam (FIB) system equipped with an energy-dispersive X-ray spectrometer (EDS) has been developed. The FIB system was used first to prepare a site-specific region for X-ray microanalysis followed by the acquisition of an electron-beam generated X-ray spectral image. A small section of material was then removed by the FIB, followed by the acquisition of another X-ray spectral image. This serial sectioning procedure was repeated 10–12 times to sample a volume of material. The series of two-spatial-dimension spectral images were then concatenated into a single data set consisting of a series of volume elements or voxels each with an entire X-ray spectrum. This four-dimensional (three real space and one spectral dimension) spectral image was then comprehensively analyzed with Sandia's automated X-ray spectral image analysis software. This technique was applied to a simple Cu-Ag eutectic and a more complicated localized corrosion study where the powerful site-specific comprehensive analysis capability of tomographic spectral imaging (TSI) combined with multivariate statistical analysis is demonstrated.

This review traces the development of X-ray mapping from its beginning 50 years ago through current analysis procedures that can reveal otherwise obscure elemental distributions and associations. X-ray mapping or compositional imaging of elemental distributions is one of the major capabilities of electron beam microanalysis because it frees the operator from the necessity of making decisions about which image features contain elements of interest. Elements in unexpected locations, or in unexpected association with other elements, may be found easily without operator bias as to where to locate the electron probe for data collection. X-ray mapping in the SEM or EPMA may be applied to bulk specimens at a spatial resolution of about 1 μm. X-ray mapping of thin specimens in the TEM or STEM may be accomplished at a spatial resolution ranging from 2 to 100 nm, depending on specimen thickness and the microscope. Although mapping has traditionally been considered a qualitative technique, recent developments demonstrate the quantitative capabilities of X-ray mapping techniques. Moreover, the long-desired ability to collect and store an entire spectrum at every pixel is now a reality, and methods for mining these data are rapidly being developed.

Spectral imaging in the scanning electron microscope (SEM) equipped with an energy-dispersive X-ray (EDX) analyzer has the potential to be a powerful tool for chemical phase identification, but the large data sets have, in the past, proved too large to efficiently analyze. In the present work, we describe the application of a new automated, unbiased, multivariate statistical analysis technique to very large X-ray spectral image data sets. The method, based in part on principal components analysis, returns physically accurate (all positive) component spectra and images in a few minutes on a standard personal computer. The efficacy of the technique for microanalysis is illustrated by the analysis of complex multi-phase materials, particulates, a diffusion couple, and a single-pixel-detection problem.