Aha! Measuring pre-service teachers' learning of content-based instruction

Page 127-153This research study investigated the effect of Content-Based Instruction (CBI) and its influence on pre-service teachers' (PSTs) perceptions of their existing knowledge and capabilities for teaching English language learners (ELs). Our goal was to examine the PSTs’ development in content-based instruction during a 16-week CBI course and their insights and changes resulting from the experience. The researchers hoped to determine what aspects of CBI methodology were new, noteworthy and important for PSTs in order to identify what they were not receiving in their general education teacher preparation courses. Over the course of three semesters, 49 participants took pre- and post-course surveys comprised of open-ended questions and five Likert scale close-ended questions to measure their insights and changes. Findings revealed substantial changes to pedagogical philosophy, instructional practices, curricular and materials development, awareness of ELs’ needs, and stance toward advocacy

NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

We introduce a novel visual question answering (VQA) task in the context of autonomous driving, aiming to answer natural language questions based on street-view clues. Compared to traditional VQA tasks, VQA in autonomous driving scenario presents more challenges. Firstly, the raw visual data are multi-modal, including images and point clouds captured by camera and LiDAR, respectively. Secondly, the data are multi-frame due to the continuous, real-time acquisition. Thirdly, the outdoor scenes exhibit both moving foreground and static background. Existing VQA benchmarks fail to adequately address these complexities. To bridge this gap, we propose NuScenes-QA, the first benchmark for VQA in the autonomous driving scenario, encompassing 34K visual scenes and 460K question-answer pairs. Specifically, we leverage existing 3D detection annotations to generate scene graphs and design question templates manually. Subsequently, the question-answer pairs are generated programmatically based on these templates. Comprehensive statistics prove that our NuScenes-QA is a balanced large-scale benchmark with diverse question formats. Built upon it, we develop a series of baselines that employ advanced 3D detection and VQA techniques. Our extensive experiments highlight the challenges posed by this new task. Codes and dataset are available at https://github.com/qiantianwen/NuScenes-QA

A Finite Element Mesh Aggregating Approach to Multiple-Source Reconstruction in Bioluminescence Tomography

A finite element mesh aggregating approach is presented to reconstruct images of multiple internal bioluminescence sources. Rather than assuming independence between mesh nodes, the proposed reconstruction strategy exploits spatial structure of nodes and aggregation feature of density distribution on the finite element mesh to adaptively determine the number of sources and to improve the quality of reconstructed images. With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power

MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection

Fusing LiDAR and camera information is essential for achieving accurate and reliable 3D object detection in autonomous driving systems. However, this is challenging due to the difficulty of combining multi-granularity geometric and semantic features from two drastically different modalities. Recent approaches aim at exploring the semantic densities of camera features through lifting points in 2D camera images (referred to as seeds) into 3D space for fusion, and they can be roughly divided into 1) early fusion of raw points that aims at augmenting the 3D point cloud at the early input stage, and 2) late fusion of BEV (bird-eye view) maps that merges LiDAR and camera BEV features before the detection head. While both have their merits in enhancing the representation power of the combined features, this single-level fusion strategy is a suboptimal solution to the aforementioned challenge. Their major drawbacks are the inability to interact the multi-granularity semantic features from two distinct modalities sufficiently. To this end, we propose a novel framework that focuses on the multi-scale progressive interaction of the multi-granularity LiDAR and camera features. Our proposed method, abbreviated as MDMSFusion, achieves state-of-the-art results in 3D object detection, with 69.1 mAP and 71.8 NDS on nuScenes validation set, and 70.8 mAP and 73.2 NDS on nuScenes test set, which rank 1st and 2nd respectively among single-model non-ensemble approaches by the time of submission

Influence of dietary zinc on growth, zinc bioaccumulation and expression of genes involved in antioxidant and innate immune in juvenile mud crabs (Scylla paramamosain)

The aim of present study was to investigate the effects of dietary Zn level on growth performance, Zn bioaccumulation, antioxidant capacity and innate immunity in juvenile mud crab (Scylla paramamosain). Six semi-purified diets were formulated to contain dietary Zn levels of 44.5, 56.9, 68.5, 97.3, 155.6 or 254.7 mg·kg-1, respectively. Dietary Zn level significantly influenced percent weight gain (PWG), with highest observed in crab fed the diet containing 97.3 mg·kg-1 Zn. Tissue Zn concentrations significantly increased as dietary Zn levels increased from 44.5 to 254.7 mg·kg-1. Retention of Zn in hepatopancreas increased with dietary Zn levels up to 68.5 mg·kg-1 and then significantly decreased. Moreover, inadequate dietary Zn (44.5 and 56.9 mg·kg-1) reduced anti-oxidation markers including total superoxide dismutase and copper/zinc superoxide dismutase activities and total anti-oxidant level. Crabs fed the diet with 44.5 mg·kg-1 Zn also showed significantly lower expression of genes involved in antioxidant status, such as Cu/Zn sod, glutathione peroxidase, catalase and thioredoxin than those fed diets containing 68.5 and 97.3 mg·kg-1 Zn. Highest activities of phenoloxidase and alkaline phosphatase were recorded in crab fed the diets containing 68.5 and 97.3 mg·kg-1 Zn. Expression levels of prophenoloxidase and toll-like receptor 2 were higher in crab fed the 97.3 mg·kg-1 Zn diet compared to crab fed the other diets. Based on PWG alone, the optimal dietary Zn level was estimated to be 82.9 mg·kg-1, with 68.5 to 97.3 mg·kg-1 recommended for maintaining optimal Zn bioaccumulation, oxidation resistance and innate immune response of juvenile mud crab

Leveraging SOLOv2 model to detect heat stress of poultry in complex environments

Heat stress is one of the most important environmental stressors facing poultry production. The presence of heat stress will reduce the antioxidant capacity and immunity of poultry, thereby seriously affecting the health and performance of poultry. The paper proposes an improved FPN-DenseNet-SOLO model for poultry heat stress state detection. The model uses Efficient Channel Attention (ECA) and DropBlock regularization to optimize the DenseNet-169 network to enhance the extraction of poultry heat stress features and suppress the extraction of invalid background features. The model takes the SOLOv2 model as the main frame, and uses the optimized DenseNet-169 as the backbone network to integrate the Feature Pyramid Network to detect and segment instances on the semantic branch and mask branch. In the validation phase, the performance of FPN-DenseNet-SOLO was tested with a test set consisting of 12,740 images of poultry heat stress and normal state, and it was compared with commonly used object detection models (Mask R CNN, Faster RCNN and SOLOv2 model). The results showed that when the DenseNet-169 network lacked the ECA module and the DropBlock regularization module, the original model recognition accuracy was 0.884; when the ECA module was introduced, the model's recognition accuracy improved to 0.919. Not only that, the recall, AP0.5, AP0.75 and mean average precision of the FPN-DenseNet-SOLO model on the test set were all higher than other networks. The recall is 0.954, which is 15, 8.8, and 4.2% higher than the recall of Mask R CNN, Faster R CNN and SOLOv2, respectively. Therefore, the study can achieve accurate segmentation of poultry under normal and heat stress conditions, and provide technical support for the precise breeding of poultry

Prevalence of Aflatoxin-Associated TP53R249S Mutation in Hepatocellular Carcinoma in Hispanics in South Texas

We aimed to determine whether aflatoxin dietary exposure plays a role in the high incidence of hepatocellular carcinoma (HCC) observed among Hispanics in South Texas. We measured TP53R249S somatic mutation, hallmark of aflatoxin etiology in HCC, using droplet digital PCR and RFLP. TP53R249S mutation was detected in 3 of 41 HCC tumors from Hispanics in South Texas (7.3%). We also measured TP53R249S mutation in plasma cell-free DNA (cfDNA) from 218 HCC patients and 96 Hispanic subjects with advanced fibrosis or cirrhosis, from South Texas. The mutation was detected only in Hispanic and Asian HCC patients, and patients harboring TP53R249S mutation were significantly younger and had a shorter overall survival. The mutation was not detected in any Hispanic subject with advanced fibrosis or cirrhosis. Genes involved in cell-cycle control of chromosomal replication and in BRCA1-dependent DNA damage response were enriched in HCCs with TP53R249S mutation. The E2F1 family members, E2F1 and E2F4, were identified as upstream regulators. TP53R249S mutation was detected in 5.7% to 7.3% of Hispanics with HCC in South Texas. This mutation was associated with a younger age and worse prognosis. TP53R249S was however not detected in Hispanics in South Texas with cirrhosis or advanced fibrosis. Aflatoxin exposure may contribute to a small number of HCCs in Hispanics in South Texas, but the detection of TP53R249S mutation in plasma cfDNA is not a promising biomarker of risk assessment for HCC in subjects with cirrhosis or advanced fibrosis in this population. Cancer Prev Res; 11(2); 103-12. ©2017 AACR

Circulating Fatty Acids Associated with Advanced Liver Fibrosis and Hepatocellular Carcinoma in South Texas Hispanics

Background: Hispanics in South Texas have high rates of hepatocellular carcinoma (HCC) and nonalcoholic fatty liver disease (NAFLD). Liver fibrosis severity is the strongest predictive factor of NAFLD progression to HCC. We examined the association between free fatty acids (FA) and advanced liver fibrosis or HCC in this population. Methods: We quantified 45 FAs in plasma of 116 subjects of the Cameron County Hispanic Cohort, 15 Hispanics with HCC, and 56 first/second-degree relatives of Hispanics with HCC. Liver fibrosis was assessed by FibroScan. Results: Advanced liver fibrosis was significantly associated with low expression of very long chain (VLC) saturated FAs (SFA), odd chain SFAs, and VLC n-3 polyunsaturated FAs [PUFA; AOR; 95% confidence interval (CI), 10.4 (3.7-29.6); P \u3c 0.001; 5.7 (2.2-15.2); P \u3c 0.001; and 3.7 (1.5-9.3); P = 0.005]. VLC n3-PUFAs significantly improved the performance of the noninvasive markers for advanced fibrosis - APRI, FIB-4, and NFS. Plasma concentrations of VLC SFAs and VLC n-3 PUFAs were further reduced in patients with HCC. Low concentrations of these FAs were also observed in relatives of patients with HCC and in subjects with the PNPLA3 rs738409 homozygous genotype. Conclusions: Low plasma concentrations of VLC n-3 PUFAs and VLC SFAs were strongly associated with advanced liver fibrosis and HCC in this population. Genetic factors were associated with low concentrations of these FAs as well. Impact: These results have implications in identifying those at risk for liver fibrosis progression to HCC and in screening this population for advanced fibrosis. They also prompt the evaluation of VLC n-3 PUFA or VLC SFA supplementation to prevent cirrhosis and HCC