23 research outputs found

    Les progrès dans la réalisation de la classification quantitative de la psychopathologie

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    Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level'' dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity'' by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach. (C) 2020 Published by Elsevier Masson SAS

    Laser wafering for silicon solar.

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    Current technology cuts solar Si wafers by a wire saw process, resulting in 50% 'kerf' loss when machining silicon from a boule or brick into a wafer. We want to develop a kerf-free laser wafering technology that promises to eliminate such wasteful wire saw processes and achieve up to a ten-fold decrease in the g/W{sub p} (grams/peak watt) polysilicon usage from the starting polysilicon material. Compared to today's technology, this will also reduce costs ({approx}20%), embodied energy, and green-house gas GHG emissions ({approx}50%). We will use short pulse laser illumination sharply focused by a solid immersion lens to produce subsurface damage in silicon such that wafers can be mechanically cleaved from a boule or brick. For this concept to succeed, we will need to develop optics, lasers, cleaving, and high throughput processing technologies capable of producing wafers with thicknesses < 50 {micro}m with high throughput (< 10 sec./wafer). Wafer thickness scaling is the 'Moore's Law' of silicon solar. Our concept will allow solar manufacturers to skip entire generations of scaling and achieve grid parity with commercial electricity rates. Yet, this idea is largely untested and a simple demonstration is needed to provide credibility for a larger scale research and development program. The purpose of this project is to lay the groundwork to demonstrate the feasibility of laser wafering. First, to design and procure on optic train suitable for producing subsurface damage in silicon with the required damage and stress profile to promote lateral cleavage of silicon. Second, to use an existing laser to produce subsurface damage in silicon, and third, to characterize the damage using scanning electron microscopy and confocal Raman spectroscopy mapping
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