Quantitative Characterization of Agglomerate Abrasion in a Tumbling Blender by Using the Stokes Number Approach

<p>Removal of microcrystalline cellulose agglomerates in a dry-mixing system (lactose, 100 M) predominantly occurs via abrasion. The agglomerate abrasion rate potential is estimated by the Stokes abrasion (St(Abr)) number of the system. The St(Abr) number equals the ratio between the kinetic energy density of the moving powder bed and the work of fracture of the agglomerate. Basically, the St(Abr) number concept describes the blending condition of the dry-mixing system. The concept has been applied to investigate the relevance of process parameters on agglomerate abrasion in tumbling blenders. Here, process parameters such as blender rotational speed and relative fill volumes were investigated. In this study, the St(Abr) approach revealed a transition point between abrasion rate behaviors. Below this transition point, a blending condition exists where agglomerate abrasion is dominated by the kinetic energy density of the powder blend. Above this transition point, a blending condition exists where agglomerates show (undesirable) slow abrasion rates. In this situation, the blending condition is mainly determined by the high fill volume of the filler.</p>

Validity of a multi-context sitting questionnaire across demographically diverse population groups: AusDiab3

© 2015 Clark et al. Background: Sitting time questionnaires have largely been validated in small convenience samples. The validity of this multi-context sitting questionnaire against an accurate measure of sitting time is reported in a large demographically diverse sample allowing assessment of validity in varied demographic subgroups. Methods: A subgroup of participants of the third wave of the Australian Diabetes, Obesity, and Lifestyle (AusDiab3) study wore activPAL3™ monitors (7 days, 24 hours/day protocol) and reported their sitting time for work, travel, television viewing, leisure computer use and "other" purposes, on weekdays and weekend days (n = 700, age 36-89 years, 45 % men). Correlations (Pearson's r; Spearman's ?) of the self-report measures (the composite total, contextual measures and items) with monitor-assessed sitting time were assessed in the whole sample and separately in socio-demographic subgroups. Agreement was assessed using Bland-Altman plots. Results: The composite total had a correlation with monitor-assessed sitting time of r = 0.46 (95 % confidence interval [CI]: 0.40, 0.52); this correlation did not vary significantly between demographic subgroups (all &gt;0.4). The contextual measure most strongly correlated with monitor-assessed sitting time was work (? = 0.25, 95 % CI: 0.17, 0.31), followed by television viewing (? = 0.16, 95 % CI: 0.09, 0.24). Agreement of the composite total with monitored sitting time was poor, with a positive bias (B = 0.53, SE 0.04, p &lt; 0.001) and wide limits of agreement (±4.32 h). Conclusions: This multi-context questionnaire provides a total sitting time measure that ranks participants well for the purposes of assessing health associations but has limited accuracy relative to activPAL-assessed sitting time. Findings did not differ in demographic subgroups