Modeling dynamic volatility under uncertain environment with fuzziness and randomness

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

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

Genetic Evolution and Molecular Selection of the HE Gene of Influenza C Virus

Influenza C virus (ICV) was first identified in humans and swine, but recently also in cattle, indicating a wider host range and potential threat to both the livestock industry and public health than was originally anticipated. The ICV hemagglutinin-esterase (HE) glycoprotein has multiple functions in the viral replication cycle and is the major determinant of antigenicity. Here, we developed a comparative approach integrating genetics, molecular selection analysis, and structural biology to identify the codon usage and adaptive evolution of ICV. We show that ICV can be classified into six lineages, consistent with previous studies. The HE gene has a low codon usage bias, which may facilitate ICV replication by reducing competition during evolution. Natural selection, dinucleotide composition, and mutation pressure shape the codon usage patterns of the ICV HE gene, with natural selection being the most important factor. Codon adaptation index (CAI) and relative codon deoptimization index (RCDI) analysis revealed that the greatest adaption of ICV was to humans, followed by cattle and swine. Additionally, similarity index (SiD) analysis revealed that swine exerted a stronger evolutionary pressure on ICV than humans, which is considered the primary reservoir. Furthermore, a similar tendency was also observed in the M gene. Of note, we found HE residues 176, 194, and 198 to be under positive selection, which may be the result of escape from antibody responses. Our study provides useful information on the genetic evolution of ICV from a new perspective that can help devise prevention and control strategies

Work and lifestyle influencing factors for thyroid cancer among young and middle-aged patients with thyroid nodules

BackgroundThe number of persons with thyroid nodules has increased rapidly in recent years, and thyroid cancer caused by malignant nodules has become a key problem endangering the health of young and middle-aged groups in China. ObjectiveTo explore work and lifestyle influencing factors for developing thyroid cancer among young and middle-aged patients with thyroid nodules. MethodsThe subjects with thyroid nodules were reported by routine physical examines ordered at the Huadong Sanatorium. We conducted a 1∶4 matched case-control study in which 232 patients diagnosed with thyroid cancer from 2012 to 2022 were matched to 928 controls by gender and age (±5 years). A validated questionnaire was used to collect data on work and lifestyle behaviors. Univariate and multivariate logistic regression models were applied to explore potential relationships between selected factors (including environment, working hours, stress, diet, exercise, and mental health) and thyroid cancer. Spearman rank correlation was used to analyze the correlations between variables. ResultsThe results of univariate logistic regression showed a history of thyroid cancer reported among first-degree relatives (OR=6.059, 95%CI: 1.007, 36.473), obesity (OR=1.973, 95%CI: 1.296, 3.004), noise and vibration exposure (OR=1.988, 95%CI: 1.143, 3.456), frequent stress (OR=2.093, 95%CI: 1.231, 3.559), frequent depression (OR=2.034, 95%CI: 1.048, 3.947), frequent anger (OR=1.791, 95%CI: 1.066, 3.012), frequent fried food diet (OR=1.535, 95%CI: 1.026, 2.297), and frequent fast food diet (OR=1.836, 95%CI: 1.048, 3.215) were risk factors for reporting thyroid cancer developing from thyroid nodules, while regular meals (OR=0.245, 95%CI: 0.061, 0.989) and frequent exercise (OR=0.571, 95%CI: 0.342, 0.952) were protective factors for reporting no thyroid cancer. The results of Spearman correlation analysis showed that body mass index was positively correlated with frequent fried food, fast food, and sugary beverage diets (r=0.123, 0.083, 0.077, P 30 min per episode) (OR=0.516, 95%CI: 0.300, 0.890) was associated with a lowered risk of reporting thyroid cancer. ConclusionsMultiple risk factors associated with reporting thyroid cancer among young and middle-aged groups with thyroid nodules are identified, such as obesity, noise and vibration exposure, frequent stress, and lack of exercise

RO Concentrate Softening through Induced Crystallization in a Fluidized Bed Reactor

Induced crystallization technique was adopted in a fluidized bed reactor to remove scale-forming ions from RO concentrate in this paper, the result of which is as follows: the effluent of the fluidized bed reactor reached stability in two minutes after the operation started; the optimized consumption ratio of softener was 1, under the circumstances of which the removal rate of Ca2+ was 89.22% the removal of Ca2+ was mainly completed at the position 20 centimeters above the bottom of the bed; the reflux rate had no influence on the removal of Ca2+, but it had influence on the turbidity of effluent

RO Concentrate Softening through Induced Crystallization in a Fluidized Bed Reactor

Induced crystallization technique was adopted in a fluidized bed reactor to remove scale-forming ions from RO concentrate in this paper, the result of which is as follows: the effluent of the fluidized bed reactor reached stability in two minutes after the operation started; the optimized consumption ratio of softener was 1, under the circumstances of which the removal rate of Ca2+ was 89.22% the removal of Ca2+ was mainly completed at the position 20 centimeters above the bottom of the bed; the reflux rate had no influence on the removal of Ca2+, but it had influence on the turbidity of effluent

Effect of ultrasonic pre-treatment on Ara h 1 in peanut sprouts

Ara h 1 is the most abundant sensitizing protein in peanuts; it has high thermal stability and is difficult to degrade. The peanut sprout is a high-quality, natural food that has various beneficial effects and lower allergenicity than peanut seeds. In this study, ultrasonication (US) of peanut sprouts was used to alter their Ara h 1 content. We determined that the optimal parameters for the US process were 35 °C temperature, 30 min duration, 240 W power, and 100 kHz frequency. After 5 days of germination, the protease activity of the control (blank) group increased to 262.39 ± 0.10 U, whereas that of the US group increased to 290.1 ± 0.25 U. We also investigated the effects of US on Ara h 1 protein composition, structure, and related gene expression during germination. ELISA results showed that after 5 days of germination, Ara h 1 content in the blank group decreased from 20.63 ± 0.31 ppm to 3.35 ± 0.42 ppm, whereas in the US group, they decreased to below the detection limit. SDS-PAGE bands between 50 and 70 kDa from peanut sprout extracts gradually became lighter in both groups. The band almost disappeared at day 5 of germination in the US group, indicating that US reduced the Ara h 1 content of peanut sprouts, consistent with the ELISA results. The expression of the Ara h 1 gene in peanut seeds was 173.92 ± 26.37. In the BK control group, it decreased to 0.49 ± 0.17 on the fourth day and increased slightly to 0.75 ± 0.09 on the fifth day. In the US group, it decreased to 1.37 ± 0.28 on the first day, dropped sharply to 0.00 on the third day, and increased slightly to 0.04 ± 0.01 on the fourth and fifth days. Protein structure results showed that the α-helix structure of Ara h 1 decreased after US, whereas the content of β-fold structures increased. The surface hydrophobicity decreased, and the secondary and tertiary structures of Ara h 1 were loose