2,499 research outputs found

    VIX to S&P 500 Correlation Over the Weekend: Are Market Makers Using S&P 500 Weekend Returns to Price VIX on Monday Morning?

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    This paper studied the correlation between the S&P 500 ETF (SPY) weekend returns and the VIX changes. Two distinct patterns are found: (1) VIX is dropping intraday and rising overnight; (2) a negative SPY weekend return correlates with VIX weekend change. We found the negative correlation is statistically significant (P=0.000). This proves that option market makers are using SPY Friday overnight returns to adjust the implied volatility the next morning. This may lead to a profitable options model that sells high IV options closing on Friday and buys them back next Monday, especially before the earnings announcement

    Associations of road traffic noise and its frequency spectrum with prevalent depression in Taichung, Taiwan

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    IntroductionExposure to road traffic noise has been reported to be associated with depression in many epidemiological studies, but the association between noise frequency spectrum and depression remains unclear. This community-based study investigated the associations between road traffic noise exposure and its frequency components with prevalent depression.MethodsA total of 3,191 residents living in Taichung who participated in the Taiwan Biobank between 2010 and 2017, were included as study participants. The land-use regression models were used to evaluate individual annual average values of A-weighted equivalent sound level over 24 h (Leq,24h) and particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) using the geographic information system. Multiple logistic regression was applied to estimate the odds ratios (ORs) for depression after adjusting for potential risk factors and PM2.5.ResultsAn interquartile range increase in Leq,24h at full frequency (4.7 dBA), 1,000 Hz (5.2 dB), and 2,000 Hz (4.8 dB) was significantly associated with an elevated risk for depression with ORs of 1.62 (95% confidence interval [CI]: 1.03, 2.55), 1.58 (95% CI: 1.05, 2.37), and 1.58 (95% CI:1.03, 2.43), respectively, by controlling for PM2.5. The high-exposure group (≥3rd quartile median of noise levels) at full frequency, 1,000 Hz, and 2,000 Hz had an increased risk for depression with ORs of 2.65 (95% CI: 1.16–6.05), 2.47 (95% CI: 1.07–5.70), and 2.60 (95% CI: 1.10–6.12), respectively, compared with the reference group (<1st quartile of noise levels) after adjustment for PM2.5. Significant exposure-response trends were observed between the prevalent depression and noise exposure by quartiles at full frequency, 1,000 Hz, and 2,000 Hz (all p < 0.05).ConclusionExposure to road traffic noise may be associated with an increased prevalence of depression, particularly at 1,000 and 2,000 Hz

    A Model and Algorithm of Dynamic Map Expression and Its Application

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    On the basis of summarizing the research results of visual variables, we define six dynamic visual variables of the map symbol in this paper. We analyze the related attributes of dynamic symbols, and then construct a dynamic map expression model based on symbols. A key technology to realize dynamic expression——the key frame transform algorithm is present in the paper. The cartography process of the urban population proportion dynamic change map of the cities in Shandong province are taken as an example to demonstrate the methods and process of dynamic mapping based on the above map dynamic expression theories and models, which includes base map digitization, sorting and processing of attribute data, adding the map elements, the creation of special dynamic effect such as color transform, continuous flashing and object moving, and realization of interactive function. Finally, the paper shows the dynamic map of sea level rising influence on Qingdao, the Typhoon Soulik traveling map, the Western European natural gas trade flow variation map, the Bangkok flood risk level dynamic map, and other dynamic map effect at the end of the article

    Effects of Early Intervention With Maternal Fecal Bacteria and Antibiotics on Liver Metabolome and Transcription in Neonatal Pigs

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    The establishment of a stable bacterial flora in early life is associated with host metabolism. Studies of fecal microbiota transplantation (FMT) and antibiotics on neonatal pig mainly focused on intestinal development and mucosal immunity, but the information on metabolism is lacking. The objective of this study was to investigate the responses of metabolome and transcriptome in the livers of neonatal piglets that were orally inoculated with maternal fecal bacteria suspension and amoxicillin (AM) solution. Five litters of Duroc × Landrace × Yorkshire neonatal piglets were used as five replicates and nine piglets in each litter were randomly assigned to the control (CO), AM or FMT groups. Neonatal piglets in three groups were fed with 3 mL saline (0.9%), AM solution (6.94 mg/mL) or fecal bacteria suspension (>109/mL), respectively, on days 1–6. At the age of 7 and 21 days, one piglet from each group in each litter was sacrificed, and the serum and liver were collected for analysis. The RNA sequencing analysis showed that the mRNA expressions of arachidonate 12-lipoxygenase (ALOX12), acetyl-CoA acyltransferase 2 (ACAA2), cytochrome P450 family 1 subfamily A member 2 (CYP1A2), glutamic–pyruvic transaminase 2 (GPT2) and argininosuccinate synthase 1 (ASS1) were downregulated (P < 0.05) by AM on day 7, and that the mRNA expressions of arachidonate 15-lipoxygenase (ALOX15), CYP1A2 and GPT2 were downregulated (P < 0.05) by FMT on day 7. GC-MS analysis showed that AM and FMT treatments mainly affected fatty acid metabolism and amino acid metabolism on days 7 and 21. AM and FMT both reduced (P < 0.05) the blood levels of triglycerides and low density lipoprotein cholesterol (LDL-C) on day 7. AM reduced (P < 0.05) the blood level of cholesterol on day 21, and FMT reduced the blood levels of cholesterol, triglycerides and LDL-C on day 21. These results indicate that early intervention with FMT or AM can reduce fatty acid oxidative catabolism and amino acid biosynthesis of neonatal piglets, which provides a reference for regulation host metabolism through early intervention in animal production and even human health

    Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells

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    We propose a polarization-based probabilistic discriminative model for deriving a set of new sigmoid-transformed polarimetry feature parameters, which not only enables accurate and quantitative characterization of cancer cells at pixel level, but also accomplish the task with a simple and stable model. By taking advantages of polarization imaging techniques, these parameters enable a low-magnification and wide-field imaging system to separate the types of cells into more specific categories that previously were distinctive under high magnification. Instead of blindly choosing the model, the L0 regularization method is used to obtain the simplified and stable polarimetry feature parameter. We demonstrate the model viability by using the pathological tissues of breast cancer and liver cancer, in each of which there are two derived parameters that can characterize the cells and cancer cells respectively with satisfactory accuracy and sensitivity. The stability of the final model opens the possibility for physical interpretation and analysis. This technique may bypass the typically labor-intensive and subjective tumor evaluating system, and could be used as a blueprint for an objective and automated procedure for cancer cell screening

    The potential of mobile health applications to improve couples’ fertility: a systematic review and meta-analysis of randomized controlled trials

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    The purpose of this systematic review was to examine the safety and effectiveness of mobile health applications in couples with infertility. Nineteen databases were searched from their inception to August 2022. Only randomized controlled trials (RCTs) in which mobile health was used as an intervention in infertile couples were included. A quantitative analysis of RCTs was employed using RevMan software. Study selection, data extraction and validation were performed by two independent reviewers according to the guidelines. The Cochrane criteria for risk-of-bias were used to evaluate the methodological quality of the trials. Eight RCTs met the inclusion criteria. Among the eight RCTs, two RCTs were from the Netherlands and the remaining six RCTs were from China. Meta-analysis showed that mobile health interventions in infertile couples in China were found to be superior to usual care in terms of clinical pregnancy rate (p = 0.001), psychological status (SAS (Self-Rating Anxiety Scale): p < 0.001; SDS (Self-Rating Depression Scale) p < 0.001;), infertility knowledge levels (p < 0.001), quality of life (p < 0.001), and serum levels of 5-hydroxytryptamine (p < 0.001). The effects on intervention groups using mobile health interventions in the Netherlands were not superior to the control groups that used usual care in terms of improving dietary factors (p > 0.05). In general, the positive effect of mobile health on improving clinical pregnancy rate, psychological status, infertility knowledge levels, quality of life and satisfaction with information was better than that of usual care. Mobile health interventions could be a viable supplement to the usual care for infertile couples. However, more high-quality RCTs need to be included in the future to provide additional evidence of the positive effects of mobile health in infertile couples

    Online Sequential Projection Vector Machine with Adaptive Data Mean Update

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    We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM

    Suppressing Decoherence in Quantum Plasmonic Systems by Spectral Hole Burning Effect

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    Quantum plasmonic systems suffer from significant decoherence due to the intrinsically large dissipative and radiative dampings. Based on our quantum simulations via a quantum tensor network algorithm, we numerically demonstrate the mitigation of this restrictive drawback by hybridizing a plasmonic nanocavity with an emitter ensemble with inhomogeneously-broadened transition frequencies. By burning two narrow spectral holes in the spectral density of the emitter ensemble, the coherent time of Rabi oscillation for the hybrid system is increased tenfold. With the suppressed decoherence, we move one step further in bringing plasmonic systems into practical quantum applications
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