Browsing by Author "Chen Y"

Now showing 1 - 9 of 9
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    A multi-label classification model for full slice brain computerised tomography image
    (BioMed Central Ltd, 2020-11-18) Li J; Fu G; Chen Y; Li P; Liu B; Pei Y; Feng H
    BACKGROUND: Screening of the brain computerised tomography (CT) images is a primary method currently used for initial detection of patients with brain trauma or other conditions. In recent years, deep learning technique has shown remarkable advantages in the clinical practice. Researchers have attempted to use deep learning methods to detect brain diseases from CT images. Methods often used to detect diseases choose images with visible lesions from full-slice brain CT scans, which need to be labelled by doctors. This is an inaccurate method because doctors detect brain disease from a full sequence scan of CT images and one patient may have multiple concurrent conditions in practice. The method cannot take into account the dependencies between the slices and the causal relationships among various brain diseases. Moreover, labelling images slice by slice spends much time and expense. Detecting multiple diseases from full slice brain CT images is, therefore, an important research subject with practical implications. RESULTS: In this paper, we propose a model called the slice dependencies learning model (SDLM). It learns image features from a series of variable length brain CT images and slice dependencies between different slices in a set of images to predict abnormalities. The model is necessary to only label the disease reflected in the full-slice brain scan. We use the CQ500 dataset to evaluate our proposed model, which contains 1194 full sets of CT scans from a total of 491 subjects. Each set of data from one subject contains scans with one to eight different slice thicknesses and various diseases that are captured in a range of 30 to 396 slices in a set. The evaluation results present that the precision is 67.57%, the recall is 61.04%, the F1 score is 0.6412, and the areas under the receiver operating characteristic curves (AUCs) is 0.8934. CONCLUSION: The proposed model is a new architecture that uses a full-slice brain CT scan for multi-label classification, unlike the traditional methods which only classify the brain images at the slice level. It has great potential for application to multi-label detection problems, especially with regard to the brain CT images.
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    Baby Food Pouches, Baby-Led Weaning, and Iron Status in New Zealand Infants: An Observational Study.
    (MDPI (Basel, Switzerland), 2024-05-15) McLean NH; Haszard JJ; Daniels L; Taylor RW; Wheeler BJ; Conlon CA; Beck KL; von Hurst PR; Te Morenga LA; McArthur J; Paul R; Katiforis I; Brown KJ; Gash MC; Rowan MM; Casale M; Cox AM; Jones EA; Jupiterwala RM; Bruckner B; Fleming L; Heath A-LM; Chen Y; Tran PV; Felt BT
    Iron deficiency in infants can impact development, and there are concerns that the use of baby food pouches and baby-led weaning may impair iron status. First Foods New Zealand (FFNZ) was an observational study of 625 New Zealand infants aged 6.9 to 10.1 months. Feeding methods were defined based on parental reports of infant feeding at "around 6 months of age": "frequent" baby food pouch use (five+ times per week) and "full baby-led weaning" (the infant primarily self-feeds). Iron status was assessed using a venepuncture blood sample. The estimated prevalence of suboptimal iron status was 23%, but neither feeding method significantly predicted body iron concentrations nor the odds of iron sufficiency after controlling for potential confounding factors including infant formula intake. Adjusted ORs for iron sufficiency were 1.50 (95% CI: 0.67-3.39) for frequent pouch users compared to non-pouch users and 0.91 (95% CI: 0.45-1.87) for baby-led weaning compared to traditional spoon-feeding. Contrary to concerns, there was no evidence that baby food pouch use or baby-led weaning, as currently practiced in New Zealand, were associated with poorer iron status in this age group. However, notable levels of suboptimal iron status, regardless of the feeding method, emphasise the ongoing need for paying attention to infant iron nutrition.
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    Does information asymmetry lead to higher debt financing? Evidence from China during the NTS Reform period
    (Emerald Publishing Limited, 2018-07-16) Qu W; Wongchoti U; Wu F; Chen Y
    Purpose: The purpose of this paper is to test an implication of the pecking order theory to explain capital structure decisions among Chinese listed companies during the 2005-2007 NTS Reform transition period. Design/methodology/approach: The authors utilize direct proxies for information asymmetry based on microstructure models including Probability of the arrival of informed trades (PIN), Adverse selection component of the bid-ask spread (λ), Illiquidity ratio (ILLIQ) and liquidity ratio, and Information asymmetry index (InfoAsy) to examine their relation with firms’ debt financing. Findings: Consistent with the prediction of Pecking Order Theory, the authors find that companies for which stock investors are challenged with more severe informational disadvantages are associated with higher degree of leverage use. Originality/value: The study provides a more direct test on the positive relation between information asymmetry and financial leverage of Chinese firms. In contrast to previous findings by Chen (2004), the results suggest that capital structure choices among Chinese firms progressively conform to conventional finance theories (e.g. Pecking Order Theory) with the decline of non-tradable shares.
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    Enhanced removal of arsenic and cadmium from contaminated soils using a soluble humic substance coupled with chemical reductant.
    (1/03/2023) Wei J; Tu C; Xia F; Yang L; Chen Q; Chen Y; Deng S; Yuan G; Wang H; Jeyakumar P; Bhatnagar A
    Soil washing is an efficient, economical, and green remediation technology for removing several heavy metal (loid)s from contaminated industrial sites. The extraction of green and efficient washing agents from low-cost feedback is crucially important. In this study, a soluble humic substance (HS) extracted from leonardite was first tested to wash soils (red soil, fluvo-aquic soil, and black soil) heavily contaminated with arsenic (As) and cadmium (Cd). A D-optimal mixture design was investigated to optimize the washing parameters. The optimum removal efficiencies of As and Cd by single HS washing were found to be 52.58%-60.20% and 58.52%-86.69%, respectively. Furthermore, a two-step sequential washing with chemical reductant NH2OH•HCl coupled with HS (NH2OH•HCl + HS) was performed to improve the removal efficiency of As and Cd. The two-step sequential washing significantly enhanced the removal of As and Cd to 75.25%-81.53% and 64.53%-97.64%, which makes the residual As and Cd in soil below the risk control standards for construction land. The two-step sequential washing also effectively controlled the mobility and bioavailability of residual As and Cd. However, the activities of soil catalase and urease significantly decreased after the NH2OH•HCl + HS washing. Follow-up measures such as soil neutralization could be applied to relieve and restore the soil enzyme activity. In general, the two-step sequential soil washing with NH2OH•HCl + HS is a fast and efficient method for simultaneously removing high content of As and Cd from contaminated soils.
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    Forecasting the publication and citation outcomes of COVID-19 preprints
    (The Royal Society, 2022-09) Gordon M; Bishop M; Chen Y; Dreber A; Goldfedder B; Holzmeister F; Johannesson M; Liu Y; Tran L; Twardy C; Wang J; Pfeiffer T
    Many publications on COVID-19 were released on preprint servers such as medRxiv and bioRxiv. It is unknown how reliable these preprints are, and which ones will eventually be published in scientific journals. In this study, we use crowdsourced human forecasts to predict publication outcomes and future citation counts for a sample of 400 preprints with high Altmetric score. Most of these preprints were published within 1 year of upload on a preprint server (70%), with a considerable fraction (45%) appearing in a high-impact journal with a journal impact factor of at least 10. On average, the preprints received 162 citations within the first year. We found that forecasters can predict if preprints will be published after 1 year and if the publishing journal has high impact. Forecasts are also informative with respect to Google Scholar citations within 1 year of upload on a preprint server. For both types of assessment, we found statistically significant positive correlations between forecasts and observed outcomes. While the forecasts can help to provide a preliminary assessment of preprints at a faster pace than traditional peer-review, it remains to be investigated if such an assessment is suited to identify methodological problems in preprints.
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    High Protein Yangyu jiaotuan (洋芋搅团): In Vitro Oral-Gastro-Small Intestinal Starch Digestion and Some Physico-Chemical, Textural, Microstructural, and Rheological Properties
    (MDPI (Basel, Switzerland), 2023-06-23) Zeng F; Abhilasha A; Chen Y; Zhao Y; Liu G; Kaur L; Singh J; Rodríguez‑García ME
    Biomimetic foods are expected to have potential health benefits for the management and prevention of chronic diseases, such as diabetes and cardiovascular disease. In the current research, two commercially available and affordable plant proteins (soy protein isolate-SPI and pea protein isolate-PPI) at two levels (5%, 10%) were added to the Yangyu jiaotuan with the objective of developing a product with reduced glycaemic properties and high protein content while maintaining its original taste and texture. The results showed that several important textural properties such as hardness and chewiness did not change significantly during the refrigerated storage. The storage modulus G' increased with refrigerated storage time for different samples, but there were significant differences among the five samples (with and without protein addition) with respect to frequency dependence during rheological measurements. The in vitro starch digestion experiments showed that the starch hydrolysis of Yangyu jiaotuan decreased considerably (by up to 42.08%) with the increase in PPI content and during refrigerated storage due to starch retrogradation. Protein has protected the microstructure and there was less damage when compared to samples without protein. The bimodal peaks of the particle size distribution curves showed that the newly developed Yangyu jiaotuan contains two different sizes of particles; the smaller particles (~30 μm) corresponded to PPI and starch granules, while the larger particles corresponded to the fragments of the gel network of the starch matrix. Based on the above results, Yangyu jiaotuan mixed with pea protein is a convenient potato staple food product, which complies with the biomimetic potato food very well.
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    Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer
    (Elsevier Inc, 2023-09-15) Wang H; Liu B; Long J; Yu J; Ji X; Li J; Zhu N; Zhuang X; Li L; Chen Y; Liu Z; Wang S; Zhao S
    Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.
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    Investigation on in-situ deoxygenation performance of bio-oil model compound guaiacol over Ce-Fe/Al2O3 catalyst
    (Elsevier B V on behalf of Shandong University, 2023-06-15) Yang M; Chen Y; Wang Y; Yang L; Cui W; Liu Y; Wang C; Chen Q
    The investigation of the low-cost deoxygenation of guaiacol (GUA, a model bio-oil compound) is of importance for upgrading bio-oil. At present, common sulfide catalysts for GUA deoxygenation reactions cause contamination of the liquid product, and noble metal catalysts are economically disadvantageous. In this study, four reduced Fe-based oxides with different Ce doping ratios were prepared and their effects on the in-situ deoxygenation performance of GUA in aqueous/methanol hydrogen donor solvents were explored. The results based on the deoxygenation degree, conversion degree, and higher heating value (HHV) of the products showed that the oxide catalyst with a Fe/Ce molar ratio of 2:1 in the methanol solvent performed very well. After selecting an excellent catalyst and a better hydrogen donor solvent, four factors (reaction temperature, reaction time, volume ratio of GUA dosage and methanol dosage, and the ratio of catalyst dosage at the bottom of the reactor to that at the top) in the deoxygenation degree of GUA were investigated using an orthogonal experimental method to further explore the performance of the catalyst. The results showed that the reaction temperature and time greatly influenced GUA deoxygenation. Under optimal experimental conditions, the deoxygenation degree and conversion degree of GUA could reach 34.36% and 92.56%, respectively, based on the relative peak area of gas chromatography–mass spectrometry, and the HHV of the liquid product was 32.27 MJ/kg. Although Fe/Ce catalysts mainly promote demethoxylation, demethylation, and methylation, the stability and quality of the liquid products were improved compared with GUA owing to the reduction in phenolic hydroxyl and ether content. The reduced catalyst in the process of GUA in-situ deoxygenation reactions in methanol maintained a steady performance, as revealed by X-ray diffraction and X-ray fluorescence.
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    Using prediction markets to predict the outcomes in the Defense Advanced Research Projects Agency's next-generation social science programme
    (The Royal Society, 2021-07) Viganola D; Buckles G; Chen Y; Diego-Rosell P; Johannesson M; Nosek BA; Pfeiffer T; Siegel A; Dreber A
    There is evidence that prediction markets are useful tools to aggregate information on researchers' beliefs about scientific results including the outcome of replications. In this study, we use prediction markets to forecast the results of novel experimental designs that test established theories. We set up prediction markets for hypotheses tested in the Defense Advanced Research Projects Agency's (DARPA) Next Generation Social Science (NGS2) programme. Researchers were invited to bet on whether 22 hypotheses would be supported or not. We define support as a test result in the same direction as hypothesized, with a Bayes factor of at least 10 (i.e. a likelihood of the observed data being consistent with the tested hypothesis that is at least 10 times greater compared with the null hypothesis). In addition to betting on this binary outcome, we asked participants to bet on the expected effect size (in Cohen's d) for each hypothesis. Our goal was to recruit at least 50 participants that signed up to participate in these markets. While this was the case, only 39 participants ended up actually trading. Participants also completed a survey on both the binary result and the effect size. We find that neither prediction markets nor surveys performed well in predicting outcomes for NGS2.