DAT-MT Accelerated Graph Fusion Dependency Parsing Model for Small Samples in Professional Fields.

The rapid development of information technology has made the amount of information in massive texts far exceed human intuitive cognition, and dependency parsing can effectively deal with information overload. In the background of domain specialization, the migration and application of syntactic treebanks and the speed improvement in syntactic analysis models become the key to the efficiency of syntactic analysis. To realize domain migration of syntactic tree library and improve the speed of text parsing, this paper proposes a novel approach-the Double-Array Trie and Multi-threading (DAT-MT) accelerated graph fusion dependency parsing model. It effectively combines the specialized syntactic features from small-scale professional field corpus with the generalized syntactic features from large-scale news corpus, which improves the accuracy of syntactic relation recognition. Aiming at the problem of high space and time complexity brought by the graph fusion model, the DAT-MT method is proposed. It realizes the rapid mapping of massive Chinese character features to the model's prior parameters and the parallel processing of calculation, thereby improving the parsing speed. The experimental results show that the unlabeled attachment score (UAS) and the labeled attachment score (LAS) of the model are improved by 13.34% and 14.82% compared with the model with only the professional field corpus and improved by 3.14% and 3.40% compared with the model only with news corpus; both indicators are better than DDParser and LTP 4 methods based on deep learning. Additionally, the method in this paper achieves a speedup of about 3.7 times compared to the method with a red-black tree index and a single thread. Efficient and accurate syntactic analysis methods will benefit the real-time processing of massive texts in professional fields, such as multi-dimensional semantic correlation, professional feature extraction, and domain knowledge graph construction.

Physicochemical characteristics and in vitro digestibility of starches from colored quinoa (Chenopodium quinoa) varieties.

The quinoa flour processing is mostly subject to the properties of starch. Starches from four colored quinoa varieties, including white quinoa (QS-W), yellow quinoa (QS-Y), red (QS-R), and black (QS-B), were compared with respect to their physicochemical properties and in vitro digestibility. Results indicated that QS-B exhibited the highest content of amylose (8.14%) (p < 0.05). All starch samples exhibited as irregular sphere with a particle size less than 3 µm. Results of the FT-IR and X-ray showed that the short-range order of the four quinoa starches exhibited no significant difference; all starches showed a typical A-type diffractrometric pattern and was not affected by seed color, and QS-Y had the highest relative crystallinity (34.3%) (p < 0.05). In addition, QS-W reflected the highest solubility (6.32%) and QS-Y showed the highest swelling power (19.45 g/g) (p < 0.05). QS-Y also presented a higher ΔH value (11.46 J/g) (p < 0.05), while QS-R peak temperature and peak G' were the lowest. Besides, QS-B had the highest slow-digestible starch (SDS) and resistant starch (RS) content, while the lowest estimated glycemic index (eGI) value (p < 0.05). Also, there was a negative correlation between hydrolysis rates and amylose content of quinoa starch. PRACTICAL APPLICATION: Due to the low gelatinization temperature of quinoa starch, it can be used to both produce and improve instant and fast food products. Quinoa starch particles are small, and Pickering emulsions and additives have potential application values. Red quinoa contains easily digestible starch, which can be a good food choice for infants and the elderly, while white quinoa starch has less swelling power and can be used in noodle products. The results of this study can help to underpin the study of quinoa nonstarch components versus starch component.

Oenothein B boosts antioxidant capacity and supports metabolic pathways that regulate antioxidant defense in Caenorhabditis elegans.

Oenothein B (OEB) has various biological functions, although few studies have focused on its effect on in vivo metabolic phenotypes. In the present study, the systematic antioxidant activity of OEB was evaluated both in vitro and in vivo, and the effect of OEB on metabolic pathways related to antioxidant capacity of Caenorhabditis elegans (C. elegans) was explored. Our findings indicate that OEB exhibits great antioxidant capacity and ability to scavenge free radicals and that OEB treatment can protect RAW 264.7 macrophages from oxidative damage by increasing superoxide dismutase (SOD) activity, catalase (CAT) activity and glutathione (GSH) content and the corresponding gene expression (sod2, cat, gpx1), while decreasing malonic dialdehyde (MDA) content. Moreover, OEB treatment significantly reduced ROS accumulation under oxidative stress conditions and increased glutathione peroxidase (GPx) activity and decreased MDA content in C. elegans. Metabolomics analysis revealed that sixteen out of forty-two significantly altered metabolites were selected as potential biomarkers related to alterations in the antioxidant status of worms, including metabolic pathways involved in amino acid metabolism, taurine and hypotaurine metabolism, lipid metabolism, and purine metabolism. Overall, our results provide new insights into the effects of OEB treatment on antioxidant capacity and metabolism that suggest that OEB could be a potentially good source of natural antioxidants.

An Improved Healthcare Accessibility Measure Considering the Temporal Dimension and Population Demand of Different Ages.

Healthcare accessibility has become an issue of social equity. An accurate estimation of existing healthcare accessibility is vital to plan and allocate health resources. Healthcare capacity, population demand, and geographic impedance are three essential factors to measure spatial accessibility. Additionally, geographic impedance is usually represented with a function of travel time. In this paper, the three-step floating catchment area (3SFCA) method is improved from the perspectives of the temporal dimension and population demand. Specifically, the travel time from the population location to the service site is precisely calculated by introducing real-time traffic conditions instead of utilizing empirical speed in previous studies. Additionally, with the utilization of real-time traffic, a dynamic result of healthcare accessibility is derived during different time periods. In addition, since the medical needs of the elderly are higher than that of the young, a demand weight index of demand is introduced to adjust the population demand. A case study of healthcare accessibility in Wuhan shows that the proposed method is effective to measure healthcare accessibility during different time periods. The spatial accessibility disparities of communities and crowdedness of hospitals are identified as an important reference for the balance between the supply and demand of medical resources.