Although food insecurity affects a significant proportion of young children in New Zealand (NZ)(1), evidence of its association with dietary intake and sociodemographic characteristics in this population is lacking. This study aims to assess the household food security status of young NZ children and its association with energy and nutrient intake and sociodemographic factors. This study included 289 caregiver and child (1-3 years old) dyads from the same household in either Auckland, Wellington, or Dunedin, NZ. Household food security status was determined using a validated and NZ-specific eight-item questionnaire(2). Usual dietary intake was determined from two 24-hour food recalls, using the multiple source method(3). The prevalence of inadequate nutrient intake was assessed using the Estimated Average Requirement (EAR) cut-point method and full probability approach. Sociodemographic factors (i.e., socioeconomic status, ethnicity, caregiver education, employment status, household size and structure) were collected from questionnaires. Linear regression models were used to estimate associations with statistical significance set at p <0.05. Over 30% of participants had experienced food insecurity in the past 12 months. Of all eight indicator statements, “the variety of foods we are able to eat is limited by a lack of money,” had the highest proportion of participants responding “often” or “sometimes” (35.8%). Moderately food insecure children exhibited higher fat and saturated fat intakes, consuming 3.0 (0.2, 5.8) g/day more fat, and 2.0 (0.6, 3.5) g/day more saturated fat compared to food secure children (p<0.05). Severely food insecure children had lower g/kg/day protein intake compared to food secure children (p<0.05). In comparison to food secure children, moderately and severely food insecure children had lower fibre intake, consuming 1.6 (2.8, 0.3) g/day and 2.6 (4.0, 1.2) g/day less fibre, respectively. Severely food insecure children had the highest prevalence of inadequate calcium (7.0%) and vitamin C (9.3%) intakes, compared with food secure children [prevalence of inadequate intakes: calcium (2.3%) and vitamin C (2.8%)]. Household food insecurity was more common in those of Māori or Pacific ethnicity; living in areas of high deprivation; having a caregiver who was younger, not in paid employment, or had low educational attainment; living with ≥2 other children in the household; and living in a sole-parent household. Food insecure young NZ children consume a diet that exhibits lower nutritional quality in certain measures compared to their food-secure counterparts. Food insecurity was associated with various sociodemographic factors that are closely linked with poverty or low income. As such, there is an urgent need for poverty mitigation initiatives to safeguard vulnerable young children from the adverse consequences of food insecurity.

Cathodes with recessed sample surfaces have several benefits in cesium sputter ion sources, including higher output, more efficient use of sample material, and improved focusing of the extracted ion beam. However, the Ionplus MICADAS uses cathodes with a graphite surface that is essentially flush with the sample holder. To evaluate the performance of recessed graphite with the MICADAS and determine the optimal surface depth, we tested four different depths, including the standard (flush) pressing method, 0.5 mm, 1.0 mm, and 1.5 mm. We found that recessed depths of 1.0 and 1.5 mm resulted in 20% higher ion beam current compared to the standard method under the same source conditions. The results are consistent with the beam produced from the recessed targets being more narrowly focused with a lower emittance, resulting in better transmission through the accelerator. Small graphite samples (200 µg C) with recessed surfaces produced higher currents for longer, leading to a 2–3× increase in sample ionization efficiency. Additionally, there was some evidence that isotopic ratio measurements of recessed samples were more stable over time. Overall, samples recessed to 1 mm depth offered numerous advantages over the standard pressing method and we have subsequently started pressing all MICADAS graphite using this approach.

OBJECTIVES/GOALS: Developing pharmacokinetic (PK) models to guide selective serotonin reuptake inhibitor (SSRI) dosing in youth is costly, time-intensive, and requires large numbers of participants. We evaluated the use of remnant blood samples from SSRI-treated youth and developed precision PK dosing strategies. METHODS/STUDY POPULATION: Following IRB approval, we used a clinical surveillance platform to identify patients with routine phlebotomy within 24 hours of escitalopram or sertraline dosing. Remnant blood samples were obtained from youth aged 5–18 years, escitalopram and sertraline concentrations were determined, and clinical characteristics (e.g., age, sex, weight, concomitant medications that inhibit sertraline or escitalopram metabolism) and phenotypes for CYP2C19, the predominant enzyme that metabolizes these SSRIs, were extracted from the electronic medical record (EMR). A population PK analysis of escitalopram and sertraline was performed using NONMEM. The influence of clinical variables, CYP2C19, and dosing was evaluated from simulated concentration-time curves. RESULTS/ANTICIPATED RESULTS: Over 21 months, we collected315 samples from escitalopram-treated patients (N=288) and 265 samples from sertraline-treated patients (N=255). In youth, escitalopram and sertraline exposure (concentrations over time) and specific pharmacokinetic parameters (e.g., clearance) were influenced by CYP2C19 phenotype, concomitant CYP2C19 inhibitors, and patient-specific characteristics. Escitalopram and sertraline concentrations from remnant blood samples were 3.98-fold higher and 3.23-fold higher, respectively, in poor metabolizers compared to normal metabolizers (escitalopram, p<0.001) and compared to normal, rapid, and ultrarapid metabolizers combined (sertraline, p<0.001). DISCUSSION/SIGNIFICANCE: Combining remnant blood sampling with pharmacogenetic-integrated EMR data can facilitate large-scale population PK analyses of escitalopram and sertraline in youth. This real-world approach can be used to rapidly develop precision SSRI dosing strategies, including slower titration and reduced target doses in CYP2C19 poor metabolizers.

We introduce a geometric analysis of turbulent mixing in density-stratified flows based on the alignment of the density gradient in two orthogonal bases that are locally constructed from the velocity gradient tensor. The first basis connects diapycnal mixing to rotation and shearing motions, building on the recent ‘rortex–shear decomposition’ in stratified shear layers (Jiang et al., J. Fluid Mech., vol. 947, 2022, A30), while the second basis connects mixing to the principal axes of the viscous dissipation tensor. Applying this framework to datasets taken in the stratified inclined duct laboratory experiment reveals that density gradients in locations of high shear tend to align preferentially (i) along the direction of minimum dissipation and (ii) normal to the plane spanned by the rortex and shear vectors. The analysis of the local alignment across increasingly turbulent flows offers new insights into the intricate relationship between the density gradient and dissipation, and thus diapycnal mixing.

The stratified inclined duct (SID) sustains an exchange flow in a long, gently sloping duct as a model for continuously forced density-stratified flows such as those found in estuaries. Experiments have shown that the emergence of interfacial waves and their transition to turbulence as the tilt angle is increased appears to be linked to a threshold in the exchange flow rate given by inviscid two-layer hydraulics. We uncover these hydraulic mechanisms by (i) using recent direct numerical simulations (DNS) providing full flow data in the key flow regimes (Zhu et al., J. Fluid Mech., vol. 969, 2023, A20), (ii) averaging these DNS into two layers, and (iii) using an inviscid two-layer shallow-water and instability theory to diagnose interfacial wave behaviour and provide physical insight. The laminar flow is subcritical and stable throughout the duct and hydraulically controlled at the ends of the duct. As the tilt is increased, the flow becomes supercritical everywhere and unstable to long waves. An internal jump featuring stationary waves first appears near the centre of the duct, then leads to larger-amplitude travelling waves, and to stronger jumps, wave breaking and intermittent turbulence at the largest tilt angle. Long waves described by the (nonlinear) shallow-water equation are interpreted locally as linear waves on a two-layer parallel base flow described by the Taylor–Goldstein equation. This link helps us to interpret long-wave instability and contrast it with short-wave (e.g. Kelvin–Helmholtz) instability. Our results suggest a transition to turbulence in SID through long-wave instability relying on vertical confinement by the top and bottom walls.

Microbial processing of soil organic matter is a significant driver of C cycling, yet we lack an understanding of what shapes the turnover of this large terrestrial pool. In part, this is due to limited options for accurately identifying the source of C assimilated by microbial communities. Laboratory incubations are the most common method for this; however, they can introduce artifacts due to sample disruption and processing and can take months to produce sufficient CO2 for analysis. We present a biomass extraction method which allows for the direct 14C analysis of microbial biomolecules and compare the results to laboratory incubations. In the upper 50 cm soil depths, the Δ14C from incubations was indistinguishable from that of extracted microbial biomass. Below 50 cm, the Δ14C of the biomass was more depleted than that of the incubations, either due to the stimulation of labile C decomposition in the incubations, the inclusion of biomolecules from non-living cells in the biomass extractions, or differences in C used for assimilation versus respiration. Our results suggest that measurement of Δ14C of microbial biomass extracts can be a useful alternative to soil incubations.

Data from a national survey of 348 U.S. sports field managers were used to examine the effects of participation in Cooperative Extension events on the adoption of turfgrass weed management practices. Of the respondents, 94% had attended at least one event in the previous 3 yr. Of this 94%, 97% reported adopting at least one practice as a result of knowledge gained at an Extension turfgrass event. Half of the respondents had adopted four or more practices; a third adopted five or more practices. Nonchemical, cultural practices were the most-adopted practices (65% of respondents). Multiple regression analysis was used to examine factors explaining practice adoption and Extension event attendance. Compared to attending one event, attending three events increased total adoption by an average of one practice. Attending four or more events increased total adoption by two practices. Attending four or more events (compared to one event) increased the odds of adopting six individual practices by 3- to 6-fold, depending on the practice. This suggests that practice adoption could be enhanced by encouraging repeat attendance among past Extension event attendees. Manager experience was a statistically significant predictor of the number of Extension events attended but a poor direct predictor of practice adoption. Experience does not appear to increase adoption directly, but indirectly, via its impact on Extension event attendance. In addition to questions about weed management generally, the survey asked questions specifically about annual bluegrass management. Respondents were asked to rank seven sources of information for their helpfulness in managing annual bluegrass. There was no single dominant information source, but Extension was ranked more than any other source as the most helpful (by 22% of the respondents) and was ranked among the top three by 53%, closely behind field representative/local distributor sources at 54%.

The stratified inclined duct (SID) experiment consists of a zero-net-volume exchange flow in a long tilted rectangular duct, which allows the study of realistic stratified shear flows with sustained internal forcing. We present the first three-dimensional direct numerical simulations (DNS) of SID to explore the transitions between increasingly turbulent flow regimes first described by Meyer & Linden (J. Fluid Mech., vol. 753, 2014, pp. 242–253). We develop a numerical set-up that faithfully reproduces the experiments and sustains the flow for arbitrarily long times at minimal computational cost. We recover the four qualitative flow regimes found experimentally in the same regions of parameter space: laminar flow, waves, intermittent turbulence and fully developed turbulence. We find good qualitative and quantitative agreement between DNS and experiments and highlight the added value of DNS to complement experimental diagnostics and increase our understanding of the transition to turbulence, both temporally (laminar/turbulent cycles) and parametrically (as the tilt angle of the duct and the Reynolds number are increased). These results demonstrate that numerical studies of SID – and deeper integration between simulations and experiments – have the potential to lead to a better understanding of stratified turbulence.

In recent years, there has been significant momentum in applying deep learning (DL) to machine health monitoring (MHM). It has been widely claimed that DL methodologies are superior to more traditional techniques in this area. This paper aims to investigate this claim by analysing a real-world dataset of helicopter sensor faults provided by Airbus. Specifically, we will address the problem of machine sensor health unsupervised classification. In a 2019 worldwide competition hosted by Airbus, Fujitsu Systems Europe (FSE) won first prize by achieving an F1-score of 93% using a DL model based on generative adversarial networks (GAN). In another comprehensive study, various modified and existing image encoding methods were compared for the convolutional auto-encoder (CAE) model. The best classification result was achieved using the scalogram as the image encoding method, with an F1-score of 91%. In this paper, we use these two studies as benchmarks to compare with basic statistical analysis methods and the one-class supporting vector machine (SVM). Our comparative study demonstrates that while DL-based techniques have great potential, they are not always superior to traditional methods. We therefore recommend that all future published studies of applying DL methods to MHM include appropriately selected traditional reference methods, wherever possible.

OBJECTIVES/GOALS: As hospitals across the nation respond to the need to address community violence, there is a dearth of Hospital-based Violence Intervention Programs (HVIPs) in the South despite having disproportionate rates. This research aims to identify key factors and strategies for implementation of an HVIP among rural patient populations in a southern state. METHODS/STUDY POPULATION: Semi-structured interviews will be conducted with medical providers, social service organizations, and patients transferred from four high-risk rural areas in Arkansas. Data will be analyzed using Framework Analysis, a rapid analysis approach involving framework development, code application, impactful statement identification, and content analysis. Evidence- Based Quality Improvement (EBQI), a group consensus making process, will be conducted to identify key implementation strategies and factors to adapt based interview findings. Priority areas for adaptation will be identified via systematic rating. The EBQI team, including researchers and key rural stakeholders will engage in a series of discussion, vote on final strategies, and develop a guide for future HVIP implementation and pilot testing. RESULTS/ANTICIPATED RESULTS: Findings from this study will result in a prioritized list of barriers and facilitators across sample groups. Factors will be rated by level of importance. Cluster maps will display the relationships among factors. Go and no-go zones will be identified based on importance and feasibility. Implementation strategies will be mapped to barriers and facilitators. DISCUSSION/SIGNIFICANCE: The findings will result in a culturally and geographically relevant HVIP model and package of implementation strategies to test in future hybrid trials (feasibility pilot & multi-site RCT); and shape the future of violence prevention efforts in healthcare settings across the rural South.