Multidimensional scaling (MDS) models for the analysis of dominance data have been developed in the psychometric and classification literature to simultaneously capture subjects’ preference heterogeneity and the underlying dimensional structure for a set of designated stimuli in a parsimonious manner. There are two major types of latent utility models for such MDS models that have been traditionally used to represent subjects’ underlying utility functions: the scalar product or vector model and the ideal point or unfolding model. Although both models have been widely applied in various social science applications, implicit in the assumption of such MDS methods is that all subjects are homogeneous with respect to their underlying utility function; i.e., they all follow a vector model or an ideal point model. We extend these traditional approaches by presenting a Bayesian MDS model that combines both the vector model and the ideal point model in a generalized framework for modeling metric dominance data. This new Bayesian MDS methodology explicitly allows for mixtures of the vector and the ideal point models thereby accounting for both preference heterogeneity and structural heterogeneity. We use a marketing application regarding physicians’ prescription behavior of antidepressant drugs to estimate and compare a variety of spatial models.

A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the rather unique joint spaces derived. We then conduct a modest Monte Carlo simulation to demonstrate the parameter recovery of the proposed methodology, as well as investigate the performance of various information heuristics for dimension selection. A consumer psychology application is provided where the spatial results of the proposed model are compared to solutions derived from various traditional multidimensional unfolding procedures. This application deals with consumers intending to buy new luxury sport-utility vehicles (SUVs). Finally, directions for future research are discussed.

A variety of joint space multidimensional scaling (MDS) methods have been utilized for the spatial analysis of two- or three-way dominance data involving subjects’ preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the underlying relevant dimensions, attributes, stimuli, and/or subjects’ utility structures in the same joint space representation. We demonstrate that care must be taken with respect to a key assumption in existent joint space MDS models such that all estimated dimensions are utilized by each and every subject in the sample, as this assumption can lead to serious distortions with respect to the derived joint spaces. We develop a new Bayesian dimension selection methodology for the multidimensional unfolding model which accommodates heterogeneity with respect to such dimensional utilization at the individual subject level for the analysis of two or three-way dominance data. A consumer psychology application regarding the preference for Over-the-Counter (OTC) analgesics is provided. We conclude by discussing the practical implications of the results, as well as directions for future research.

This study examines the impact of COVID-19-induced policy environments on civil servants’ public service motivation (PSM), a topic not yet adequately researched. Using a vignette survey experiment, we investigate how four types of COVID-19 policy environment information – 1) total deduction of annual leave compensation, 2) a significant increase in working hours, 3) positive assessments of government responses from domestic audiences, and 4) positive assessments of government responses from other advanced democracies – shape civil servants’ PSM during the pandemic. We analyze original data from over 4,000 South Korean civil servants in central and local governments, gathered as part of a representative survey. Results show that reducing compensation to prepare the disaster relief fund has a negative impact, whereas recognition by advanced democracies has a positive impact on PSM. Our analysis suggests the importance of policy environments in both motivating and demotivating civil servants during a pandemic crisis.

We investigate the concentration fluctuations of passive scalar plumes emitted from small, localised (point-like) steady sources in a neutrally stratified turbulent boundary layer over a rough wall. The study utilises high-resolution large-eddy simulations for sources of varying sizes and heights. The numerical results, which show good agreement with wind-tunnel studies, are used to estimate statistical indicators of the concentration field, including spectra and moments up to the fourth order. These allow us to elucidate the mechanisms responsible for the production, transport and dissipation of concentration fluctuations, with a focus on the very near field, where the skewness is found to have negative values – an aspect not previously highlighted. The gamma probability density function is confirmed to be a robust model for the one-point concentration at sufficiently large distances from the source. However, for ground-level releases in a well-defined area around the plume centreline, the Gaussian distribution is found to be a better statistical model. As recently demonstrated by laboratory results, for elevated releases, the peak and shape of the pre-multiplied scalar spectra are confirmed to be independent of the crosswind location for a given downwind distance. Using a stochastic model and theoretical arguments, we demonstrate that this is due to the concentration spectra being directly shaped by the transverse and vertical velocity components governing the meandering of the plume. Finally, we investigate the intermittency factor, i.e. the probability of non-zero concentration, and analyse its variability depending on the thresholds adopted for its definition.

Shark vertebrae and their centra (vertebral bodies) are high-performance structures able to survive millions of cycles of high amplitude strain despite lacking a repair mechanism for accumulating damage. Shark centra consist of mineralized cartilage, a biocomposite of bioapatite (bAp), and collagen, and the nanocrystalline bAp's contribution to functionality remains largely uninvestigated. Using the multiple detector energy-dispersive diffraction (EDD) system at 6-BM-B, the Advanced Photon Source, and 3D tomographic sampling, the 3D functionality of entire centra were probed. Immersion in ethanol vs phosphate-buffered saline produces only small changes in bAp d-spacing within a great hammerhead centrum. EDD mapping under in situ loading was performed an entire blue shark centrum, and 3D maps of bAp strain showed the two structural zones of the centrum, the corpus calcareum and intermedialia, contained opposite-signed strains approaching 0.5%, and application of ~8% nominal strain did not alter these strain magnitudes and their spatial distribution.

Prevented planting payments reimburse crop producers for losses from not being able to plant. These payments provide critical protection to producers; however, these payments, which are determined using a nationwide, crop-specific coverage factor, have been questioned to induce moral hazard. Depending on the region and crop insurance coverage, payments from this provision exceed producers’ losses. This paper estimates the prevented planting coverage factor by coverage level and region that would equitably reimburse corn and soybean producers for their losses. We find the prevented planting coverage factor has significant variation across coverage levels and location within our study region. The prevented planting coverage factor was found to decline as the policy coverage level increases. The further north in the study region the higher the coverage factor, likely due to increased land rent expenses. The results provide a unique perspective of how these coverage factors would vary to equitably compensate producers for losses, which addresses the moral hazard concerns with prevented planting.

Shape deformation during fossilization can prevent accurate reconstruction of an organism's form during life, hampering areas of paleontology ranging from functional morphology to systematics. Retrodeformation attempts to restore the original shape of deformed fossil specimens and requires an adequate knowledge of the deformation process. Although tectonic processes and retrodeformation are relatively well understood, research on quantifying the effect of compressive deformation on fossil morphology is scant. Here we investigate the factors that can cause changes in the shape of fossil specimens during compressive deformation. Three-dimensional (3D) models of trilobite cranidia/cephala are subjected to simulated deposition and compaction using rigid body simulation and scaling features of the open-source 3D software Blender. The variation in pitch and roll angle is lowest on flat surfaces, intermediate on tilted surfaces, and highest on irregular surfaces. These trends are reflected in the morphological differences captured by principal component scores in geometric morphometric analyses using landmarks. In addition, the different shapes of trilobite cranidia/cephala according to their systematic affinity influence the degree of angular variation, which in turn affects their posture—normal or inverted. Inverted cranidia/cephala show greater morphological variability than those with normal postures.

Background: After a transient ischemic attack (TIA) or minor stroke, the long-term risk of subsequent stroke is uncertain. Methods: Electronic databases were searched for observational studies reporting subsequent stroke during a minimum follow-up of 1 year in patients with TIA or minor stroke. Unpublished data on number of stroke events and exact person-time at risk contributed by all patients during discrete time intervals of follow-up were requested from the authors of included studies. This information was used to calculate the incidence of stroke in individual studies, and results across studies were pooled using random-effects meta-analysis. Results: Fifteen independent cohorts involving 129794 patients were included in the analysis. The pooled incidence rate of subsequent stroke per 100 person-years was 6.4 events in the first year and 2.0 events in the second through tenth years, with cumulative incidences of 14% at 5 years and 21% at 10 years. Based on 10 studies with information available on fatal stroke, the pooled case fatality rate of subsequent stroke was 9.5% (95% CI, 5.9 – 13.8). Conclusions: One in five patients is expected to experience a subsequent stroke within 10 years after a TIA or minor stroke, with every tenth patient expected to die from their subsequent stroke.

The purpose of this study was to compare single- and multi-frequency bioimpedance (BIA) devices against dual-energy X-ray absorptiometry (DXA) for appendicular lean mass (ALM) and muscle quality index (MQI) metrics in Hispanic adults. One hundred thirty-one Hispanic adults (18–55 years) participated in this study. ALM was measured with single-frequency bioimpedance analysis (SFBIA), multi-frequency bioimpedance analysis (MFBIA) and DXA. ALMTOTAL (left arm + right arm + left leg + right leg) and ALMARMS (left arm + right arm) were computed for all three devices. Handgrip strength (HGS) was measured using a dynamometer. The average HGS was used for all MQI models (highest left hand + highest right hand)/2. MQIARMS was defined as the ratio between HGS and ALMARMS. MQITOTAL was established as the ratio between HGS and ALMTOTAL. SFBIA and MFBIA had strong correlations with DXA for all ALM and MQI metrics (Lin’s concordance correlation coefficient values ranged from 0·86 (MQIMFBIA-ARMS) to 0·97 (Arms LMSFBIA); all P < 0·001). Equivalence testing varied between methods (e.g. SFBIA v. DXA) when examining the different metrics (i.e. ALMTOTAL, ALMARMS, MQITOTAL and MQIARMS). MQIARMS was the only metric that did not differ from the line of identity and had no proportional bias when comparing all the devices against each other. The current study findings demonstrate good overall agreement between SFBIA, MFBIA and DXA for ALMTOTAL and ALMARMS in a Hispanic population. However, SFBIA and MFBIA have better agreement with DXA when used to compute MQIARMS than MQITOTAL.

Faecal examinations for helminth eggs were performed on 1869 people from two riverside localities, Vientiane Municipality and Saravane Province, along the Mekong River, Laos. To obtain adult flukes, 42 people positive for small trematode eggs (Opisthorchis viverrini, heterophyid, or lecithodendriid eggs) were treated with a 20–30 mg kg−1 single dose of praziquantel and purged. Diarrhoeic stools were then collected from 36 people (18 in each area) and searched for helminth parasites using stereomicroscopes. Faecal examinations revealed positive rates for small trematode eggs of 53.3% and 70.8% (average 65.2%) in Vientiane and Saravane Province, respectively. Infections with O. viverrini and six species of intestinal flukes were found, namely, Haplorchis taichui, H. pumilio, H. yokogawai, Centrocestus caninus, Prosthodendrium molenkampi, and Phaneropsolus bonnei. The total number of flukes collected and the proportion of fluke species recovered were markedly different in the two localities; in Vientiane, 1041 O. viverrini (57.8 per person) and 615 others (34.2 per person), whereas in Saravane, 395 O. viverrini (21.9 per person) and 155207 others (8622.6 per person). Five people from Saravane harboured no O. viverrini but numerous heterophyid and/or lecithodendriid flukes. The results indicate that O. viverrini and several species of heterophyid and lecithodendriid flukes are endemic in these two riverside localities, and suggest that the intensity of infection and the relative proportion of fluke species vary by locality along the Mekong River basin.

OBJECTIVES/GOALS: Metastasis to regional areas decreases invasive breast cancer (IBC) survival rate by 13%. Despite the clinical importance of lymph node involvement, the role of extracellular matrix (ECM) remodeling in metastases is unknown. We hypothesize that the spatial dysregulation of the collagen proteome facilitates pro-tumorigenic immune infiltration. METHODS/STUDY POPULATION: Lymph node metastases were compared to patient-matched primary tumor and normal lymph nodes using tissue microarrays (TMA) from 31 generational South Carolina women with IBC (black women, BW n=10, white women, WW n=21) and lumpectomies from 5 triple-negative breast cancer (TNBC) patients (BW n=3; WW n=2) by ECM-targeted mass spectrometry imaging. RESULTS/ANTICIPATED RESULTS: Between metastatic and normal lymph nodes, 10% of peptides, primarily from fibrillar collagens, were significantly different by area under the receiver operating curve (AUROC>70%; p-value< 0.01) within the TMAs. In a subsequent preliminary study of the TNBC metastatic niche, a segmentation analysis of 152 putatively identified peptides and 117,909 pixels revealed 10 uniquely localized proteomic groups. 12 peptides were found to have significantly decreased relative peak intensities in lymph node metastases compared to the primary tumor and normal lymph nodes by a one-way ANOVA test (p< 0.05). 7 peptides could discriminate between metastatic and normal lymph nodes, while 22 peptides could discriminate between metastatic lymph nodes and the primary tumor (AUROC>0.70; p-value < 0.05). DISCUSSION/SIGNIFICANCE: Our preliminary interrogation highlights emerging differences between lymph node metastases, the primary tumor, and normal lymph nodes. Future work is needed to connect these discrete ECM proteomes to immune infiltration alterations, which could contribute to disparate patient outcomes.

OBJECTIVES/GOALS: The correction of spinopelvic parameters is associated with better outcomes in patients with adult spinal deformity (ASD). This study presents a novel artificial intelligence (AI) tool that automatically predicts spinopelvic parameters from spine x-rays with high accuracy and without need for any manual entry. METHODS/STUDY POPULATION: The AI model was trained/validated on 761 sagittal whole-spine x-rays to predict the following parameters: Sagittal Vertical Axis (SVA), Pelvic Tilt (PT), Pelvic Incidence (PI), Sacral Slope (SS), Lumbar Lordosis (LL), T1-Pelvic Angle (T1PA), and L1-Pelvic Angle (L1PA). A separate test set of 40 x-rays was labeled by 4 reviewers including fellowship-trained spine surgeons and a neuroradiologist. Median errors relative to the most senior reviewer were calculated to determine model accuracy on test and cropped-test (i.e. lumbosacral) images. Intraclass correlation coefficients (ICC) were used to assess inter-rater reliability RESULTS/ANTICIPATED RESULTS: The AI model exhibited the following median (IQR) parameter errors: SVA[2.1mm (8.5mm), p=0.97], PT [1.5° (1.4°), p=0.52], PI[2.3° (2.4°), p=0.27], SS[1.7° (2.2°), p=0.64], LL [2.6° (4.0°), p=0.89], T1PA [1.3° (1.1°), p=0.41], and L1PA [1.3° (1.2°), p=0.51]. The parameter errors on cropped lumbosacral images were: LL[2.9° (2.6°), p=0.80] and SS[1.9° (2.2°), p=0.78]. The AI model exhibited excellent reliability at all parameters in both whole-spine (ICC: 0.92-1.0) and lumbosacral x-rays: (ICC: 0.92-0.93). DISCUSSION/SIGNIFICANCE: Our AI model accurately predicts spinopelvic parameters with excellent reliability comparable to fellowship-trained spine surgeons and neuroradiologists. Utilization of predictive AI tools in spine-imaging can substantially aid in patient selection and surgical planning.