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We show that a linear model is sufficient to accurately estimate the quantity of yarn that goes into a knitted item produced on an automated knitting machine. Knitted fabrics are complex structures, yet their diverse properties arise from the arrangement of a small number of discrete, additive operations. One can estimate the masses of each of these basic yarn additions using linear regression and, in turn, use these masses to estimate the overall quantity (and local distribution) of yarn within any knitted fabric. Our proposed linear model achieves low error on a range of fabrics and generalizes to different yarns and stitch sizes. This paves the way for applications where having a known yarn distribution is important for accuracy (e.g., simulation) or cost estimation (e.g., design). 

Abstract Decades of research underscore the profound impact of adversity on brain and behavioral development. Recent theoretical models have highlighted the importance of considering specific features of adversity that may have dissociable effects at distinct developmental timepoints. However, existing measures do not query these dimensions in sufficient detail to support the proliferation of this approach. The Dimensional Inventory of Stress and Trauma Across the Lifespan (DISTAL) was developed with the aim to thoroughly and retrospectively assess the timing, severity (of exposure and reaction), type, persons involved, controllability, predictability, threat, deprivation, proximity, betrayal, and discrimination inherent in an individual's exposure to adversity. Here, we introduce this instrument, present descriptive statistics drawn from a sample ofN = 187 adults who completed the DISTAL, and provide initial information about its psychometric properties. This novel measure facilitates the expansion of research focused on assessing the relative impact of exposure to key dimensions of adversity on the brain and behavior across development.