Passive Acoustic Emissions in a V-blender

The pharmaceutical manufacturing process consists of a number of batch steps; each step must be monitored and controlled to ensure quality standards are met. The development of process analytical technologies (PAT) can improve product monitoring with the aim of increasing efficiency, product quality and consistency and creating a better understanding of the manufacturing process. This work investigates the feasibility of using passive acoustic emissions (PAE) to monitor particulates in a V-blender. An accelerometer was attached to the lid of a V-blender to measure vibrations from the tumbling solids. A wavelet filter removed the oscillations in the signals from the motion of the shell, focusing on the emissions from the particle interactions. The particle size, fill level and scale affected the acoustic emissions through changes in the particle momentum. Changes in particle cohesiveness and flowability were also reflected in the measured emissions. Powder properties and behavior are critical to efficient and successful manufacturing of pharmaceutical tablets. As the powders must be transferred between the different manufacturing stages, the flowability of powders is critical. Trials were conducted to investigate the effect of moisture content of a powder on its flowability. Through avalanche behavior, it was found that the flowability and the dynamic density of a powder change with moisture content. PAEs were used to detect changes in solids moisture content as solids tumbled within the V-blender. It was found that particle mass, coefficient of restitution (COR) and flowability impacted the amplitude of the acoustic emissions. To further investigate the effects of particle flowability, PAEs were used to monitor lubricant addition. The amplitudes of the acoustic emissions were sensitive to the lubricant addition due to changes in the flowability. A trend in the emission amplitude allowed for the progression of the lubricant mixing to be followed. Overall, the research supports the feasibility of PAEs as a PAT for mixing in a tumbling blender to increase process knowledge and improve product quality

Measurement of Energy Expenditure During Laboratory and Field Activities

This dissertation was designed to examine the validity of heart rate (HR) and motion sensors for estimating energy expenditure (EE) during activities ranging from sedentary behaviors to vigorous exercise. A secondary purpose was to devise new ways to improve on current methods of estimating EE. Specific aims of the dissertation were: (1) to examine the use of pedometers to measure steps taken, distance traveled, and EE during treadmill walking at various speeds; (2) Examine the use of a Polar HR monitor to estimate EE during treadmill running, stationary cycling, and rowing; (3) compare the current Actigraph regression equations (relating counts·min-1 to EE) against three newer devices (Actiheart, Actical, and AMP-331) during sedentary, light, moderate, and vigorous intensity activities; and (4) development of a new 2-regression model to estimate EE using the Actigraph accelerometer. For the first aim, 10 participants performed treadmill walking for five minutes at five speeds while wearing two pedometers of different brands (10 pedometer brands were tested) on the right and left hip. Simultaneously oxygen consumption (VO2) was measured and actual steps were counted using a hand tally counter. Six of the 10 pedometers were within ± 3% of actual steps at 80 m·min-1 and faster. Most pedometers were within ± 10% of actual distance at 80 m·min-1, but they overestimate distance at slower speeds, and underestimate distance at faster speeds. Most pedometers gave estimates of gross EE within ± 30% of measured EE across all speeds. In general, pedometers are most accurate for assessing steps, less accurate for assessing distance, and even less accurate for assessing kcals. In the second aim, 10 males and 10 females performed a maximal treadmill test. On a separate day they performed treadmill, cycle, and rowing exercise for 10 minutes at three different intensities. During each trial EE was estimated using two Polar S410 HR monitors (one with predicted VO2max and HRmax (PHRM) and one with actual VO2max and HRmax (AHRM), input into the watch). Simultaneously, EE was measured by indirect calorimetry (IC). For males there were no differences among the mean values of EE for the AHRM, PHRM and IC for any exercise mode (P ≥ 0.05). In females, the AHRM significantly improved the estimate of EE compared to the PHRM (P \u3c 0.05), but it still overestimated mean EE on the treadmill and cycle (P \u3c 0.05). The Polar S410 HR monitor provides the best estimate of EE when the actual VO2max and HRmax are used. For the third aim, 48 participants performed various activities ranging from sedentary pursuits to vigorous exercise. The activities were split into three routines of six activities and each participant performed one routine. During each routine an Actigraph (right hip), Actical (left hip), Actiheart (chest), and AMP-331 (right ankle) were worn. Simultaneously, EE was measured by IC. The Actiheart HR algorithm was not significantly different from measured EE for any of the 18 activities (P ≥ 0.05). The Actiheart combined HR and activity algorithm was only significantly different from measured EE for vacuuming and ascending/descending stairs (P \u3c 0.05). All remaining prediction equations, for the devices examined, over- or underestimated EE for at least seven activities. The Actiheart HR algorithm provided the best estimate of EE over a wide range of activities. The Actical and Actigraph tended to overestimate walking and sedentary activities and underestimate most other activities. For the fourth aim, 48 participants performed various activities (sedentary, light, moderate, and vigorous intensities) that were split into three routines of six activities. Each participant performed one routine. During each test the participants wore an Actigraph accelerometer and EE was measured by IC. Forty-five tests were randomly selected for the development of the new equation, and 15 tests were used to cross-validate the new equation and compare against existing equations. For each activity the coefficient of variation (CV) of the counts per 10 seconds was calculated to determine if the activity was walking/running, or some other activity. If the CV ≤ 10 then a walking/running regression equation (relating counts·min-1 to METs) was used, while if the CV \u3e 10 a lifestyle/leisure time physical activity (LTPA) regression was used. The new 2-regression model explained 73% of the variance in EE for walking/running, and 83.8% of the variance in EE for lifestyle/LTPA and it was within ± 0.84 METs of measured METs for each of the 17 activities performed (P ≥ 0.05). The new 2-regression model is a more accurate prediction of EE then the currently published regression equations using the Actigraph accelerometer

Instruction of the Deaf

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Mexican-Origin Parents’ Work Conditions and Adolescents’ Adjustment

Mexican-origin parents’ work experiences are a distal extra-familial context for adolescents’ adjustment. This two-wave multi-informant study examined the prospective mechanisms linking parents’ work conditions (i.e., self-direction, work pressure, workplace discrimination) to adolescents’ adjustment (i.e., educational expectations, depressive symptoms, risky behavior) across the transition to high school drawing on work socialization and spillover models. We examined the indirect effects of parental work conditions on adolescent adjustment through parents’ psychological functioning (i.e., depressive symptoms, role overload) and aspects of the parent-adolescent relationship (i.e., parental solicitation, parent-adolescent conflict), as well as moderation by adolescent gender. Participants were 246 predominantly immigrant, Mexican-origin, two-parent families who participated in home interviews when adolescents were approximately 13 and 15 years of age. Results supported the positive impact of fathers’ occupational self-direction on all three aspects of adolescents’ adjustment through decreased father-adolescent conflict, after controlling for family socioeconomic status and earner status, and underemployment. Parental work pressure and discrimination were indirectly linked to adolescents’ adjustment, with different mechanisms emerging for mothers and fathers. Adolescents’ gender moderated the associations between fathers’ self-direction and girls’ depressive symptoms, and fathers’ experiences of discrimination and boys’ risk behavior. Results suggest that Mexican-origin mothers’ and fathers’ perceptions of work conditions have important implications for multiple domains of adolescents’ adjustment across the transition to high school

Effect of ActiGraph\u27s Low Frequency Extension for Estimating Steps and Physical Activity Intensity

This study examined the effects of the ActiGraph’s (AG) low-frequency extension (LFE) filter on steps and physical activity classification in the free-living environment. Thirty-four African-American women (age, 24.5±5.2 years; BMI, 24.9±4.5 kg/m2) had daily activity measured simultaneously with an AG-GT3X+ accelerometer and a New Lifestyles NL-800 pedometer for seven days. Steps per day (steps/day) and time (minutes/day) spent in sedentary, light, and moderate-to-vigorous physical activity (MVPA) were examined with and without the LFE filter (AG-LFE and AG-N, respectively). The AG-LFE recorded more total steps (13,723±4,983 steps/day) compared to AG-N and NL-800 (6,172±2,838 and 5,817±3,037 steps/day, respectively; p\u3c0.001). Compared to the AG-N, the AG-LFE estimated less time in sedentary behaviors (518.7±92.1 vs. 504.2±105.4 min/day, respectively; p\u3c0.001), and more time in light (247.7±70.4 vs. 279.1±74.7 min/day, respectively; p\u3c0.001) and MVPA (18.9±16.9 vs. 21.5±18.2 min/day, respectively; p\u3c0.001), respectively. These data suggest that steps and physical activity classifications will be affected when using the ActiGraph with and without the LFE filter. Future research should investigate the accuracy of these measures using the LFE filter

Comparisons of prediction equations for estimating energy expenditure in youth

Objectives The purpose of this study was to compare the validity of Actigraph 2-regression models (2RM) and 1-regression models (1RM) for estimation of EE in children. Design The study used a cross-sectional design with criterion estimates from a metabolic cart. Methods A total of 59 children (7–13 yrs) performed 12 activities (randomly selected from a set of 24 activities) for 5 min each, while being concurrently measured with an Actigraph GT3X and indirect calorimetry. METRMR (MET considering one\u27s resting metabolic rate) for the GT3X was estimated applying 2RM with vector magnitude (VM2RM) and vertical axis (VA2RM), and four standard 1RMs. The validity of the 2RMs and 1RMs was evaluated using 95% equivalence testing and mean absolute percent error (MAPE). Results For the group-level comparison, equivalence testing revealed that the 90% confidence intervals for all 2RMs and 1RMs were outside of the equivalence zone (range: 3.63, 4.43) for indirect calorimetry. When comparing the individual activities, VM2RM produced smaller MAPEs (range: 14.5–45.3%) than VA2RM (range, 15.5–58.1%) and 1RMs (range, 14.5–75.1%) for most of the light and moderate activities. Conclusions None of the 2RMs and 1RMs were equivalent to indirect calorimetry. The 2RMs showed smaller individual-level errors than the 1RMs

Effects of Knee Alignments and Toe Clip on Frontal Plane Knee Biomechanics in Cycling

Effects of knee alignment on the internal knee abduction moment (KAM) in walking have been widely studied. The KAM is closely associated with the development of medial knee osteoarthritis. Despite the importance of knee alignment, no studies have ex- plored its effects on knee frontal plane biomechanics during sta- tionary cycling. The purpose of this study was to examine the ef- fects of knee alignment and use of a toe clip on the knee frontal plane biomechanics during stationary cycling. A total of 32 par- ticipants (11 varus, 11 neutral, and 10 valgus alignment) per- formed five trials in each of six cycling conditions: pedaling at 80 rpm and 0.5 kg (40 Watts), 1.0 kg (78 Watts), and 1.5 kg (117 Watts) with and without a toe clip. A motion analysis system and a customized instrumented pedal were used to collect 3D kine- matic and kinetic data. A 3 × 2 × 3 (group × toe clip × workload) mixed design ANOVA was used for statistical analysis (p \u3c 0.05). There were two different knee frontal plane loading patterns, in- ternal abduction and adduction moment, which were affected by knee alignment type. The knee adduction angle was 12.2° greater in the varus group compared to the valgus group (p = 0.001), yet no difference was found for KAM among groups. Wearing a toe clip increased the knee adduction angle by 0.95o (p = 0.005). The findings of this study indicate that stationary cycling may be a safe exercise prescription for people with knee malalignments. In addition, using a toe clip may not have any negative effects on knee joints during stationary cycling