50 research outputs found

    Modeling dynamic volatility under uncertain environment with fuzziness and randomness

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    The problem related to predicting dynamic volatility in financial market plays a crucial role in many contexts. We build a new generalized Barndorff-Nielsen and Shephard (BN-S) model suitable for uncertain environment with fuzziness and randomness. This new model considers the delay phenomenon between price fluctuation and volatility changes, solves the problem of the lack of long-range dependence of classic models. Through the experiment of Dow Jones futures price, we find that compared with the classical model, this method effectively combines the uncertain environmental characteristics, which makes the prediction of dynamic volatility has more ideal performance

    Stochastic volatility modeling of high-frequency CSI 300 index and dynamic jump prediction driven by machine learning

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    This paper models stochastic process of price time series of CSI 300 index in Chinese financial market, analyzes volatility characteristics of intraday high-frequency price data. In the new generalized Barndorff-Nielsen and Shephard model, the lag caused by asynchrony of market information is considered, and the problem of lack of long-term dependence is solved. To speed up the valuation process, several machine learning and deep learning algorithms are used to estimate parameter and evaluate forecast results. Tracking historical jumps of different magnitudes offers promising avenues for simulating dynamic price processes and predicting future jumps. Numerical results show that the deterministic component of stochastic volatility processes would always be captured over short and longer-term windows. Research finding could be suitable for influence investors and regulators interested in predicting market dynamics based on realized volatility

    2,4-Diiodo-3-nitro­anisole

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    In the title compound (systematic name: 1,3-diiodo-4-meth­oxy-2-nitro­benzene), C7H5I2NO3, the dihedral angle between the benzene ring and the nitro group is 88.0 (3)°, and the methyl group lies almost in the same plane as the ring [deviation = 0.034 (6) Å]. In the crystal, aromatic π–π stacking occurs between inversion-related rings [centroid–centroid separation = 3.865 (3) Å and slippage = 0.642 Å]. A possible weak C—I⋯π inter­action occurs [I⋯π = 3.701 (2) Å and C—I⋯π = 130.18 (13)°], but there are no significant inter­molecular I⋯I contacts

    3,15-Dimeth­oxy-10-methyl­tricyclo­[9.4.0.02,7]penta­deca-1(11),2(7),3,5,9,12,14-heptaen-8-one

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    The title mol­ecule, C18H16O3, contains three fused rings, of which the seven-membered cyclo­hept-2-enone ring has a screw-boat conformation. The two meth­oxy­phenyl rings make a dihedral angle of 50.4 (2)°. In the crystal, mol­ecules are linked by inter­molecular C—H⋯O hydrogen bonds, leading to a three-dimensional supra­molecular architecture

    Research on Three-phase Optimal Power Flow for Distribution Networks Based on Constant Hessian Matrix

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    Influential factors on urine EV DNA methylation detection and its diagnostic potential in prostate cancer

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    The value of Extracellular vesicles (EVs) diagnostic markers is widely recognized. However, current research on EV DNA remains limited. This study investigates the biological properties, preprocessing factors, and diagnostic potential of EV DNA. We found that DNA positive vesicles account for 23.3% ± 6.7% of the urine total EV, with a large amount of DNA attached to the outside. EV DNA fragments are large, there is no significant effect on uEV DNA when store urine less than 6 h at 4°C. In addition, the influence of different EV extraction methods on methylation detection is also minor. More importantly, RASSF1A methylation in urine total EV DNA can distinguish between PCa and BPH, with an AUC of 0.874. Our results suggest the potential of urine EV DNA as a novel marker for PCa diagnosis. This provides a new idea for the study of urinary tumor markers

    Testing and comparing two self-care-related instruments among older Chinese adults

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    Objectives The study aimed to test and compare the reliability and validity, including sensitivity and specificity of the two self-care-related instruments, the Self-care Ability Scale for the Elderly (SASE), and the Appraisal of Self-care Agency Scale-Revised (ASAS-R), among older adults in the Chinese context. Methods A cross-sectional design was used to conduct this study. The sample consisted of 1152 older adults. Data were collected by a questionnaire including the Chinese version of SASE (SASE-CHI), the Chinese version of ASAS-R (ASAS-R-CHI) and the Exercise of Self-Care Agency scale (ESCA). Homogeneity and stability, content, construct and concurrent validity, and sensitivity and specificity were assessed. Results The Cronbach's alpha (α) of SASE-CHI was 0.89, the item-to-total correlations ranged from r = 0.15 to r = 0.81, and the test-retest correlation coefficient (intra-class correlation coefficient, ICC) was 0.99 (95% CI, 0.99±1.00; P<0.001). The Cronbach's α of ASAS-R-CHI was 0.78, the item-to-total correlations ranged from r = 0.20 to r = 0.65, and the test-retest ICC was 0.95 (95% CI, 0.92±0.96; P<0.001). The content validity index (CVI) of SASE-CHI and ASAS-R-CHI was 0.96 and 0.97, respectively. The findings of exploratory and confirmatory factor analyses (EFA and CFA) confirmed a good construct validity of SASE-CHI and ASAS-R-CHI. The Pearson's rank correlation coefficients, as a measure of concurrent validity, between total score of SASE-CHI and ESCA and ASAS-R-CHI and ESCA were assessed to 0.65 (P<0.001) and 0.62 (P<0.001), respectively. Regarding ESCA as the criterion, the area under the receiver operator characteristic (ROC) curve for the cut-point of SASE-CHI and ASAS-R-CHI were 0.93 (95% CI, 0.91±0.94) and 0.83 (95% CI, 0.80±0.86), respectively. Conclusion There is no significant difference between the two instruments. Each has its own characteristics, but SASE-CHI is more suitable for older adults. The key point is that the users can choose the most appropriate scale according to the specific situation.publishedVersionNivå

    Most Lithium-rich Low-mass Evolved Stars Revealed as Red Clump stars by Asteroseismology and Spectroscopy

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    Lithium has confused scientists for decades at almost each scale of the universe. Lithium-rich giants are peculiar stars with lithium abundances over model prediction. A large fraction of lithium-rich low-mass evolved stars are traditionally supposed to be red giant branch (RGB) stars. Recent studies, however, report that red clump (RC) stars are more frequent than RGB. Here, we present a uniquely large systematic study combining the direct asteroseismic analysis with the spectroscopy on the lithium-rich stars. The majority of lithium-rich stars are confirmed to be RCs, whereas RGBs are minor. We reveal that the distribution of lithium-rich RGBs steeply decline with the increasing lithium abundance, showing an upper limit around 2.6 dex, whereas the Li abundances of RCs extend to much higher values. We also find that the distributions of mass and nitrogen abundance are notably different between RC and RGB stars. These findings indicate that there is still unknown process that significantly affects surface chemical composition in low-mass stellar evolution.Comment: 27 pages, 10 figures, 3 table
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