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This paper investigates the volatility spillovers across precious and industrial metal markets over the period 1993–2019 based on the DY and ​BK methods. Results are summarized as follows: (1) while volatility spillovers across industrial metals are higher than across precious metals, the opposite occurs during crisis periods where precious metals cause net volatility spillovers to industrial metals; (2) volatility spillovers of the two metal groups show different dynamics in the short‐, medium‐ and long‐term components, especially in the short‐ and medium‐term components.

We develop a heterogeneous autoregressive model of downside volatility (HAR‐DV) model with structural changes (HAR‐DV‐SC) model to investigate the effects of structural changes on predicting downside volatility. Then we employ HAR‐DV and HAR‐DV‐SC models to forecast downside volatilities in S&P 500 index, crude oil, gold, copper, and soybean futures markets. The in‐sample analysis shows that structural changes contain in‐sample information for predicting downside volatility. The out‐of‐sample analysis indicates that the HAR‐DV‐SC model outperforms the HAR‐DV model, suggesting that structural changes contain incremental out‐of‐sample information on future downside volatility. These results are robust and have important implications for risk management of stakeholders.

In this article, we analyze the dynamic linkage between crude oil price and the US dollar at multi‐scale frequencies using time‐dependent intrinsic correlation analysis based on the complete ensemble empirical mode decomposition with adaptive noise. After applying a refined method to extract the trend, we reveal that the overall correlation and the long‐term trend correlation exhibit very similar patterns. The correlation coefficients between crude oil and the US dollar are negative at most of the time; however, the coefficients become positive in certain periods, such as 2013–2014 and 2017–2018. Furthermore, the negative correlations in high frequency intrinsic mode functions (IMFs), with a shorter time horizon, are weaker and display time‐varying characteristics, whereas the correlation in low frequency IMFs, with a longer time horizon, are stronger and more static. The findings of this article may have important implications for investors to construct optimal portfolio diversification.

Currently, experimental evidence suggests that the surgical delay can increase flap survival area, but its effect may decrease if the optimal delay period is missed. The aim of this study is to establish a sensitive and objective modality based on the visualized and individualized infrared thermography for identifying the maximal surgical delay effect. A rectangular three-angiosome flap was designed on the unilateral dorsum of the rat. Ninety-six rats were randomly divided into six groups according to the various delay time. Both the relative temperature and the relative temperature ratio were measured by the infrared thermography. Arterial density, number of vessels >0.1 mm in diameter, microvessel density, VEGF concentration, and flap viability were measured. Receiving operating characteristic curve with the highest Youden-Index was used to detect and identify an optimal cutoff point of the relative temperature ratio in the maximal surgical delay effect. The criteria for identifying the flap maximum delay effect based on the infrared thermography included the surface of the postdelayed flaps presented white color (higher temperature) instead of the red and white pattern of the normal skin and the optimal cutoff point of the relative temperature ratio was ≥1.17 with a sensitivity of 84.6% and a specificity of 77.3%. Instead, the sensitivity and specificity of the conventional method based on the delay time were 38.5 and 90.9%, respectively. Infrared thermal imaging can accurately identify the maximum delay effect when combined with the relative temperature ratio.

This paper examines whether structural breaks contain incremental information for forecasting the volatility of copper futures. Considering structural breaks in volatility, we develop four heterogeneous autoregressive (HAR) models based on classical or latest HAR-type models. Subsequently, we apply these models to forecast volatility in the copper futures market. The empirical results reveal that our models exhibit better in-sample and out-of-sample performances than classical or latest HAR-type models. This suggests that structural breaks contain incremental prediction information for the volatility of copper futures. More importantly, we argue that considering structural breaks can improve the performances of most of existing HAR-type models. Highlights There are many structural break points in return volatility of the copper futures. We propose 12 new heterogeneous autoregressive models. Our models outperform the existing heterogeneous autoregressive models. Structural breaks contain additional ex ante information for volatility forecasting. The ex ante information is obvious in forecasting mid- and long-term volatilities.

BACKGROUND Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. METHODS For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. RESULTS Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. CONCLUSION Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction.

Methyl xestospongoate (MXS), a brominated polyunsaturalted lipid recently isolated from the Chinese marine sponge Xestospongia testudinaria, showed strong in vitro pancreatic lipase (PL) inhibitory activity. Inspired by its promising activity and potential clinical application, a series of shorter or longer-chain and chlorinated analogs of MXS was prepared and evaluated for PL inhibitory activity. The result of a bioassay indicated that the terminal brominated ones are better than the chlorinated ones on their bioactivity, and 16–20 C-atoms in the structures of MXS analogs might be optimal for their PL inhibitory activity. The results obtained in the present work are useful for the design of novel pancreatic lipase inhibitors.

Rare cancer types are not only understudied, but are typically represented by formalin-fixed paraffin-embedded (FFPE) (rather than freshly-frozen) specimens that are suboptimal for genomic analysis. Ameloblastoma is one such rare tumor type, thought to arise from ameloblasts, the cells that deposit enamel during tooth development. Though typically benign, ameloblastomas are locally destructive to the jaw and face, and new non-surgical interventions are needed. To discover novel driver mutations and therapeutic targets, we optimized methods and performed whole-transcriptome sequencing and/or targeted exon sequencing (TruSeq Cancer Panel) of 8 FFPE cases. Identified mutations were verified, and then evaluated on a larger, independent set of 22 FFPE cases by PCR and Sanger sequencing. From the analysis, we identified recurrent somatic mutations in three key developmental or signaling pathways, including Hedgehog, fibroblast growth factor, and MAP kinase pathways. Functional interrogation of a novel Hedgehog ...