Temperature-Change-Based Thermal Tomography

Thermal properties of biological tissues play a critical role in the study of tumor angiogenesis and the design and monitoring of thermal therapies. To map thermal parameters noninvasively, we propose temperature-change-based thermal tomography (TTT) that relies on relative temperature mapping using magnetic resonance imaging (MRI). Our approach is unique in two aspects: (1) the steady-state body temperature in thermal equilibrium is not restricted to be spatially invariant, and (2) absolute temperature mapping is not required. These two features are physiologically realistic and technically convenient. Our numerical simulation indicates that a (9 mm)3 tumor inside a breast phantom can be reliably depicted, assuming moderate temperature mapping accuracy of 0.5°C

A CNN based system for predicting the implied volatility and option prices.

The evaluations of option prices and implied volatility are critical for option risk management and trading. Common strategies in existing studies relied on the parametric models. However, these models are based on several idealistic assumptions. In addition, previous research of option pricing mainly depends on the historical transaction records without considering the performance of other concurrent options. To address these challenges, we proposed a convolutional neural network (CNN) based system for predicting the implied volatility and the option prices. Specifically, the customized non-parametric learning approach is first used to estimate the implied volatility. Second, several traditional parametric models are also implemented to estimate these prices as well. The convolutional neural network is utilized to obtain the predictions based on the estimation of the implied volatility. Our experiments based on Chinese SSE 50ETF options demonstrate that the proposed framework outperforms the traditional methods with at least 40.12% performance enhancement in terms of RMSE

Effect of electronic stimulation at Neiguan (PC 6) acupoint on gene expression of adenosine triphosphate-sensitive potassium channel and protein kinases in rats with myocardial ischemia

AbstractObjectiveTo investigate the effects of electronic stimulation at acupoints Neiguan (PC 6) and Lieque (LU 7) on the gene expression of the adenosine triphosphate (ATP)-Sensitive potassium channel (KATP: Kir6.1, Kir6.2, SUR2A, and SUR2B) and protein kinases (PKA, PKG, and PKCβ2) in myocardial cells of rats with myocardial ischemia (MI) induced by isoproterenol (ISO).MethodsRats were randomly divided into a control, model, Neiguan (PC 6), Lieque (LU 7), and non-acupoint groups. The MI model was established by injecting rats with ISO. Electro-acupuncture treatment was given to the acupuncture groups, once a day for 7 days. Gene expression was analyzed with real-time PCR.ResultsThe gene expression of KATP and protein kinases in the model group was higher than those in the control group (P < 0.05). After acupuncture treatment, the KATP and protein kinase expression levels were significantly lower in the Neiguan (PC 6) and Lieque (LU 7) groups compared with the model group (P < 0.05). The Neiguan (PC 6) group lowered these levels significantly more than that of the Lieque (LU 7) group (P < 0.05). No significant differences were observed between the model and non-acupoint groups (P > 0.05).ConclusionOur findings suggest that electronic needling of Neiguan (PC 6) can both reduce the gene expression of KATP and protein kinases in rats with ISO-induced MI