The Growth Mindset and Student Social and Emotional Skill Development: An Empirical Analysis Based on the OECD’s SSES

The mindset is a crucial factor influencing the behavior of individuals. This study aims to evaluate the growth mindset of 10- and 15-year-old adolescents and the relationship between their mindsets and social and emotional skills from the viewpoints of students, parents, and teachers, using OECD’s SSES 2019 data from Suzhou City. The research results show that the growth mindset of students is affected by their socioeconomic status; and that the growth mindset of students, parents, and teachers can significantly and positively predict student social and emotional skills

Variability of sea ice area in the Bohai Sea from 1958 to 2015

With the backdrop of continuous global change, it is beneficial to create consistent long-term records of sea ice area on regional scales for ice disaster prevention and risk mitigation. In this study, a piecewise multiple nonlinear regression model was developed to reconstruct long-term daily sea ice area dataset in the Bohai Sea from 1958 to 2015 by linking the related meteorological data and the satellite-derived ice area. The validation analysis show that related meteorological status corresponding to physical process had stable skill of predictive ability, which was able to account for 81% of the observational variance under consideration of sea ice state, freezing and melting phases. The reconstructed daily sea ice area dataset was further used to study the interannual and seasonal variability of sea ice area. The annual maximum ice area (AMIA) and the annual average ice area (AAIA) in the Bohai Sea exhibited a decreasing trend with fluctuation of -0.33 +/- 0.18% yr(-1) and -0.51 +/- 0.16% yr(-1) over the period of 1958-2015, respectively. The most obvious change of the Bohai Sea ice area occurred in time scale of similar to 30 years. The whole study period could be divided into slight increasing stage (1958-1980), significant decreasing stage (1980-1995), and moderate increasing stage (1995-2015). In most years, the annual changes of sea ice area showed an unimodal variation and the freezing period (similar to 65 days) was longer than the melting phase (similar to 40 days) due to the relatively higher freezing rate. In addition, high correlations between AAIA and Arctic Oscillation (AO) index (r=-0.60, pPeer reviewe

Barley C-Hordein as the Calibrant for Wheat Gluten Quantification

The lack of certified reference materials has been one major challenge for gluten quantification in gluten-free products. In this study, the feasibility of using barley C-hordein as the calibrant for wheat gluten in R5 sandwich enzyme-linked immunosorbent assay (ELISA) was investigated. The gluten composition and total gluten R5 reactivity ranged largely depending on the genotypes and the growing environment. The conversion factor of gliadin to gluten averaged 1.31 for common wheat, which is smaller than the theoretical factor of 2. Each gluten group had varying reactivity against the R5 antibody, where ω1.2-, γ- and α-gliadins were the main reactive groups from wheat gluten. A mixture of wheat cultivars or one single cultivar as the reference material can be difficult to keep current. Based on the average R5 reactivity of total gluten from the 27 common wheat cultivars, here we proposed 10% C-hordein mixed with an inert protein as the calibrant for wheat gluten quantification. In spiking tests of gluten-free oat flour and biscuits, calibration using 10% C-hordein achieved the same recovery as the gliadin standard with its cultivar-specific conversion factor. For its good solubility and good affinity to the R5 antibody, the application of C-hordein increases the probability of developing a series of reference materials for various food matrices

Barley C-Hordein as the Calibrant for Wheat Gluten Quantification

The lack of certified reference materials has been one major challenge for gluten quantification in gluten-free products. In this study, the feasibility of using barley C-hordein as the calibrant for wheat gluten in R5 sandwich enzyme-linked immunosorbent assay (ELISA) was investigated. The gluten composition and total gluten R5 reactivity ranged largely depending on the genotypes and the growing environment. The conversion factor of gliadin to gluten averaged 1.31 for common wheat, which is smaller than the theoretical factor of 2. Each gluten group had varying reactivity against the R5 antibody, where ω1.2-, γ- and α-gliadins were the main reactive groups from wheat gluten. A mixture of wheat cultivars or one single cultivar as the reference material can be difficult to keep current. Based on the average R5 reactivity of total gluten from the 27 common wheat cultivars, here we proposed 10% C-hordein mixed with an inert protein as the calibrant for wheat gluten quantification. In spiking tests of gluten-free oat flour and biscuits, calibration using 10% C-hordein achieved the same recovery as the gliadin standard with its cultivar-specific conversion factor. For its good solubility and good affinity to the R5 antibody, the application of C-hordein increases the probability of developing a series of reference materials for various food matrices

Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data

Satellite remote sensing data, such as moderate resolution imaging spectroradiometers (MODIS) and advanced very high-resolution radiometers (AVHRR), are being widely used to monitor sea ice conditions and their variability in the Bohai Sea, the southernmost frozen sea in the Northern Hemisphere. Monitoring the characteristics of the Bohai Sea ice can provide crucial information for ice disaster prevention for marine transportation, oil field operation, and regional climate change studies. Although these satellite data cover the study area with fairly high spatial resolution, their typically limited cloudless images pose serious restrictions for continuous observation of short-term dynamics, such as sub-seasonal changes. In this study, high spatiotemporal resolution (500 m and eight images per day) geostationary ocean color imager (GOCI) data with a high proportion of cloud-free images were used to monitor the characteristics of the Bohai Sea ice, including area and thickness. An object-based feature extraction method and an albedo-based thickness inversion model were used for estimating sea ice area and thickness, respectively. To demonstrate the efficacy of the new dataset, a total of 68 GOCI images were selected to analyze the evolution of sea ice area and thickness during the winter of 2012–2013 with severe sea ice conditions. The extracted sea ice area was validated using Landsat Thematic Mapper (TM) data with higher spatial resolution, and the estimated sea ice thickness was found to be consistent with in situ observation results. The entire sea ice freezing–melting processes, including the key events such as the day with the maximum ice area and the first and last days of the frozen season, were better resolved by the high temporal-resolution GOCI data compared with MODIS or AVHRR data. Both characteristics were found to be closely correlated with cumulative freezing/melting degree days. Our study demonstrates the applicability of the GOCI data as an improved dataset for studying the Bohai Sea ice, particularly for purposes that require high temporal resolution data, such as sea ice disaster monitoring

T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation

Despite the stunning ability to generate high-quality images by recent text-to-image models, current approaches often struggle to effectively compose objects with different attributes and relationships into a complex and coherent scene. We propose T2I-CompBench, a comprehensive benchmark for open-world compositional text-to-image generation, consisting of 6,000 compositional text prompts from 3 categories (attribute binding, object relationships, and complex compositions) and 6 sub-categories (color binding, shape binding, texture binding, spatial relationships, non-spatial relationships, and complex compositions). We further propose several evaluation metrics specifically designed to evaluate compositional text-to-image generation. We introduce a new approach, Generative mOdel fine-tuning with Reward-driven Sample selection (GORS), to boost the compositional text-to-image generation abilities of pretrained text-to-image models. Extensive experiments and evaluations are conducted to benchmark previous methods on T2I-CompBench, and to validate the effectiveness of our proposed evaluation metrics and GORS approach. Project page is available at https://karine-h.github.io/T2I-CompBench/.Comment: Project page: https://karine-h.github.io/T2I-CompBench

Quantitative Implementation of Artificial Intelligence Based on Task Completion Analysis

With the further development of the new generation of artificial intelligence science and technology, the new generation of artificial intelligence science and technology has been applied in many fields. AlphaGo program uses high technology of quantitative analysis to realize qualitative research and development of artificial intelligence, which has important reference significance for the research and development of a new generation of artificial intelligence in the future. From the perspective of task accessibility, this paper analyzes the defects of the disturbance, so as to achieve the quantitative implementation of the new generation of artificial intelligence task accessibility analysis method

Eight RGS and RGS-like Proteins Orchestrate Growth, Differentiation, and Pathogenicity of Magnaporthe oryzae

A previous study identified MoRgs1 as an RGS protein that negative regulates G-protein signaling to control developmental processes such as conidiation and appressorium formation in Magnaporthe oryzae. Here, we characterized additional seven RGS and RGS-like proteins (MoRgs2 through MoRgs8). We found that MoRgs1 and MoRgs4 positively regulate surface hydrophobicity, conidiation, and mating. Indifference to MoRgs1, MoRgs4 has a role in regulating laccase and peroxidase activities. MoRgs1, MoRgs2, MoRgs3, MoRgs4, MoRgs6, and MoRgs7 are important for germ tube growth and appressorium formation. Interestingly, MoRgs7 and MoRgs8 exhibit a unique domain structure in which the RGS domain is linked to a seven-transmembrane motif, a hallmark of G-protein coupled receptors (GPCRs). We have also shown that MoRgs1 regulates mating through negative regulation of Gα MoMagB and is involved in the maintenance of cell wall integrity. While all proteins appear to be involved in the control of intracellular cAMP levels, only MoRgs1, MoRgs3, MoRgs4, and MoRgs7 are required for full virulence. Taking together, in addition to MoRgs1 functions as a prominent RGS protein in M. oryzae, MoRgs4 and other RGS and RGS-like proteins are also involved in a complex process governing asexual/sexual development, appressorium formation, and pathogenicity

Transcriptionally active HERV-H retrotransposons demarcate topologically associating domains in human pluripotent stem cells.

Chromatin architecture has been implicated in cell type-specific gene regulatory programs, yet how chromatin remodels during development remains to be fully elucidated. Here, by interrogating chromatin reorganization during human pluripotent stem cell (hPSC) differentiation, we discover a role for the primate-specific endogenous retrotransposon human endogenous retrovirus subfamily H (HERV-H) in creating topologically associating domains (TADs) in hPSCs. Deleting these HERV-H elements eliminates their corresponding TAD boundaries and reduces the transcription of upstream genes, while de novo insertion of HERV-H elements can introduce new TAD boundaries. The ability of HERV-H to create TAD boundaries depends on high transcription, as transcriptional repression of HERV-H elements prevents the formation of boundaries. This ability is not limited to hPSCs, as these actively transcribed HERV-H elements and their corresponding TAD boundaries also appear in pluripotent stem cells from other hominids but not in more distantly related species lacking HERV-H elements. Overall, our results provide direct evidence for retrotransposons in actively shaping cell type- and species-specific chromatin architecture

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

We propose a deep hashing framework for sketch retrieval that, for the first time, works on a multi-million scale human sketch dataset. Leveraging on this large dataset, we explore a few sketch-specific traits that were otherwise under-studied in prior literature. Instead of following the conventional sketch recognition task, we introduce the novel problem of sketch hashing retrieval which is not only more challenging, but also offers a better testbed for large-scale sketch analysis, since: (i) more fine-grained sketch feature learning is required to accommodate the large variations in style and abstraction, and (ii) a compact binary code needs to be learned at the same time to enable efficient retrieval. Key to our network design is the embedding of unique characteristics of human sketch, where (i) a two-branch CNN-RNN architecture is adapted to explore the temporal ordering of strokes, and (ii) a novel hashing loss is specifically designed to accommodate both the temporal and abstract traits of sketches. By working with a 3.8M sketch dataset, we show that state-of-the-art hashing models specifically engineered for static images fail to perform well on temporal sketch data. Our network on the other hand not only offers the best retrieval performance on various code sizes, but also yields the best generalization performance under a zero-shot setting and when re-purposed for sketch recognition. Such superior performances effectively demonstrate the benefit of our sketch-specific design.Comment: Accepted by CVPR201