Process data refer to data recorded in log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents’ response problem-solving behaviors. Process data analysis aims at enhancing educational assessment accuracy and serving other assessment purposes by utilizing the rich information contained in response processes. The R package ProcData presented in this article is designed to provide tools for inspecting, processing, and analyzing process data. We define an S3 class ‘proc’ for organizing process data and extend generic methods summary and print for ‘proc’. Feature extraction methods for process data are implemented in the package for compressing information in the irregular response processes into regular numeric vectors. ProcData also provides functions for making predictions from neural-network-based sequence models. In addition, a real dataset of response processes from the climate control item in the 2012 Programme for International Student Assessment is included in the package.

Recently released Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) collection 6.1 (C6.1) products are useful for understanding ice–atmosphere interactions over East Antarctica, but their accuracy should be known prior to application. This study assessed Level 2 and Level 3 MODIS C6.1 LST products (MxD11_L2 and MxD11C1) in comparison with the radiance-derived in situ LSTs from 12 weather stations. Significant cloud-related issues were identified in both LST products. By utilizing a stricter filter based on automatic weather station cloud data, despite losing 29.4% of the data, accuracy of MODIS LST was greatly improved. The cloud-screened MODIS LST exhibited cold biases (−5.18 to −0.07°C, and root mean square errors from 2.37 to 6.28°C) than in situ LSTs at most stations, with smaller cold biases at inland stations, but larger ones at coastal regions and the edge of plateau. The accuracy was notably higher during warm periods (October–March) than during cold periods (April–September). The cloud-screened MODIS C6.1 LST did not show significant improvements over C5 (Collection 5) version across East Antarctica. Ice-crystal precipitation occurring during temperature inversions at the surface (Tair-Tsurface) played a crucial role in MODIS LST accuracy on inland plateau. In coastal regions, larger MODIS LST biases were observed when the original measurements were lower.

Zinc (Zn) is widely known as an essential trace element for fish and new ways to supply it to them are needed. Palygorskite (Pal) is a natural silicate clay mineral and the palygorskite structure contains nano-channels, which are filled with water and exchangeable ions. Zn-bearing palygorskites (Zn-Pal) prepared using ion exchange have attracted attention due to the durable antibacterial properties that limit pathogens and as a potential new Zn source for livestock. The present study was conducted to evaluate the effects of Zn-Pal supplementation on the growth performance, nutrient retention, meat quality, Zn accumulation, and intestinal Zn transporter protein gene expression in blunt snout bream Megalobrama amblycephala. The fish were fed a basal diet without an exogenous Zn source and the basal diet was supplemented with 125 mg/kg Zn as Zn sulfate (ZnSO4) or 35, 80, or 125 mg/kg Zn as Zn-Pal. Each diet was tested using three replicates for 7 weeks. The results showed that dietary Zn-Pal supplementation quadratically (P<0.05) increased growth performance, nutrient retention, total and Cu/Zn superoxide dismutase activity, Zn content in scales, and intestinal Zn transporter protein gene expression. The muscular cooking loss in blunt snout bream decreased with the optimum Zn-Pal Zn level of 35 mg/kg. Compared to the fish treated with ZnSO4, the fish supplemented with 35 mg/kg as Zn-Pal exhibited similar growth performance and nutrient retention (P>0.05), increased mRNA expression of the metal-response element-binding transcription factor-1 in the intestine (P<0.05), and decreased cooking loss of muscle (P<0.05).The results suggested that 35 mg/kg Zn supplementation as Zn-Pal could improve the growth performance and body composition, increase nutrient retention and tissue Zn concentrations, enhance the muscle water-holding capacity, and enhance antioxidant status in blunt snout bream. The Zn-Pal was more efficient and could be used as an alternative Zn source to ZnSO4 in the diet of blunt snout bream.

Anaemia is a global public health problem affecting women worldwide, and reproductive-age women are at increased risk. We conducted a population-based cross-sectional study analysing the prevalence of overall anaemia and anaemia according to severity in Chinese pre-pregnant women to update current knowledge on anaemia epidemiology. Based on the National Free Preconception Check-up Projects supported by the Chinese government, 5 679 782 women participating in this project in 2017 were included in the present study. The cyanmethemoglobin method was applied to assess Hb concentrations. Univariate and multivariate logistic regressions were applied for associated factors. The prevalence of anaemia among Chinese pre-pregnant women was 21·64 % (mild: 14·10 %, moderate: 7·17 % and severe : 0·37 %). The prevalence of overall and severe anaemia was the highest in Tibet and the lowest in Beijing among thirty-one provinces. Women’s age, region, ethnic origin, educational level, occupation and pregnancy history were all correlated with anaemia. Women with B blood type (adjusted OR (aOR) = 0·89), higher BMI (overweight: aOR = 0·84; obesity: aOR = 0·70) and alcohol consumption (aOR = 0·69) were less likely to have anaemia, while those with rhesus negative blood type (aOR = 1·10), history of anaemia (aOR = 2·60), older age at menarche (aOR = 1·19), heavy menstrual blood loss (aOR = 1·39), longer menstrual period (aOR = 1·09) and shorter menstrual cycle (aOR = 1·08) were more likely to suffer from anaemia. Meat or egg eaters were not significantly associated with severe anaemia. Anaemia is of moderate public health significance among Chinese pre-pregnant women. Interventions should be considered to prevent anaemia to the greatest extent possible to avoid potential harm in this population.

ABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value < 10-5. For each SNP, we identified the region that was in linkage disequilibrium (r2 > 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases.

Several studies analysed the associations between dietary carbohydrate intake, glycaemic index (GI) and glycaemic load (GL) and digestive system cancers; however, the results remain controversial. This study was to perform a meta-analysis evaluating the quantitative and dose–response associations between carbohydrate intake, GI and GL, and risk of digestive system cancers. We searched medical and biological databases up to June 2018 and identified twenty-six cohort studies and eighteen case–control studies. Meta-analytic fixed or random effects models were applied to process data. We also performed dose–response analysis, meta-regression and subgroup analyses. We found that high levels of GI were significantly associated with the risk of digestive system cancers at the highest compared with the lowest categories from cohort studies (summary relative risk (RR)=1·10, 95 % CI 1·05, 1·15). Similar effects were observed from case–control studies of the comparison between the extreme categories, but the difference did not reach statistical significance (summary OR=1·28, 95 % CI 0·97, 1·69). We also observed significant dose–response association between GI and digestive system cancers, with every 10-unit increase in GI (summary RR=1·003; 95 % CI 1·000, 1·012 for cohort studies; summary OR=1·09; 95 % CI 1·06, 1·11 for case–control studies). In addition, both cohort studies and case–control studies indicated that neither dietary carbohydrate intake nor GL bore any statistical relationship to digestive system cancers from the results of the highest compared with the lowest categories analyses and dose–response analyses. The results suggest a moderate association between high-GI diets and the risk of digestive system cancers.

The local RBFs based collocation methods (LRBFCM) is presented to solve two-dimensional incompressible Navier-Stokes equations. In avoiding the ill-conditioned problem, the weight coefficients of linear combination with respect to the function values and its derivatives can be obtained by solving low-order linear systems within local supporting domain. Then, we reformulate local matrix in the global and sparse matrix. The obtained large sparse linear systems can be directly solved instead of using more complicated iterative method. The numerical experiments have shown that the developed LRBFCM is suitable for solving the incompressible Navier-Stokes equations with high accuracy and efficiency.

In this paper, we study a class of contact smoothed particle hydrodynamics (SPH) by introducing Riemann solvers and using high-order limiters. In particular, a promising concept of WENO interpolation as limiter is presented in the reconstruction process. The physical values relating interactional particles used as the initial values of the Riemann problem can be reconstructed by the Taylor series expansion. The contact solvers of the Riemann problem at contact points are incorporated in SPH approximations. In order to keep the fluid density at the wall rows to be consistent with that of the inner fluid wall boundaries, several lines of dummy particles are placed outside of the solid walls, which are assigned according to the initial configuration. At last, the method is applied to compressible flows with sharp discontinuities such as the collision of two strong shocks and the interaction of two blast waves and so on. The numerical results indicate that the method is capable of handling sharp discontinuity and efficiently reducing unphysical oscillations.

The present study was designed to analyse the usefulness of a modified Calgary score system during differential diagnosis between cardiac syncope and postural orthostatic tachycardia syndrome-associated syncope through a large sample sized clinical investigation. The study included 213 children, including 101 boys and 112 girls, with cardiac syncope or postural orthostatic tachycardia syndrome-associated syncope in the age group of 2–19 years (mean 11.8 ± 2.9 years). A modified Calgary score was created, which was analysed to predict differential diagnoses between cardiac syncope and postural orthostatic tachycardia syndrome-associated syncope using a receiver operating characteristic curve. The median of modified Calgary scores for cardiac syncope was −5.0, which significantly differed from that of postural orthostatic tachycardia syndrome (0.0; p < 0.01). The sensitivity and specificity of a differentiation score of less than −2.5 was 96.3% and 72.7%, respectively. Owing to the fact that the modified Calgary score was an integer, when less than −3.0 the diagnosis could be considered as cardiac syncope. The modified Calgary score could be used to make an initial differential diagnosis between cardiac syncope and postural orthostatic tachycardia syndrome-associated syncope in the clinic.