The Adjoint Method for the Inverse Problem of Option Pricing

The estimation of implied volatility is a typical PDE inverse problem. In this paper, we propose the TV-L1 model for identifying the implied volatility. The optimal volatility function is found by minimizing the cost functional measuring the discrepancy. The gradient is computed via the adjoint method which provides us with an exact value of the gradient needed for the minimization procedure. We use the limited memory quasi-Newton algorithm (L-BFGS) to find the optimal and numerical examples shows the effectiveness of the presented method

Calibration of the Volatility in Option Pricing Using the Total Variation Regularization

In market transactions, volatility, which is a very important risk measurement in financial economics, has significantly intimate connection with the future risk of the underlying assets. Identifying the implied volatility is a typical PDE inverse problem. In this paper, based on the total variation regularization strategy, a bivariate total variation regularization model is proposed to estimate the implied volatility. We not only prove the existence of the solution, but also provide the necessary condition of the optimal control problem—Euler-Lagrange equation. The stability and convergence analyses for the proposed approach are also given. Finally, numerical experiments have been carried out to show the effectiveness of the method

Assessing Callous-Unemotional Traits in Chinese Detained Boys: Factor Structure and Construct Validity of the Inventory of Callous-Unemotional Traits

The Inventory of Callous-Unemotional Traits (ICU) was designed to evaluate multiple facets of Callous-Unemotional (CU) traits in youths. However, no study has examined the factor structure and psychometrical properties of the ICU in Chinese detained juveniles. The current study assesses the factor structure, internal consistency and convergent validity of the ICU in 613 Chinese detained boys. Confirmatory factor analysis results indicated that the original three-factor model with 24 items showed an unacceptable fit to the data, however, the 11-item shortened version of the ICU (ICU-11) with callousness and uncaring dimensions showed the best fit. Moreover, the ICU-11 total score and factor scores had good and acceptable internal consistencies. The convergent and criterion validity of the ICU-11 was demonstrated by comparable and significant associations in the expected direction with relevant external criteria (e.g., psychopathy, aggression, and empathy). In conclusion, present findings indicated that the ICU-11 is a reliable and efficient instrument to replace the original ICU when assessing CU traits in the Chinese male detained juvenile sample.This work was supported by the National Natural Science Foundation of China (Grant Nos. 31800945 and 31400904) and Guangzhou University’s 2017 training program for young topnotch personnels (BJ201715)

Light anti-nuclei production in pp collisions at s\sqrt{s}=7 and 14 TeV

A dynamically constrained coalescence model based on the phase space quantization and classical limit method was proposed to investigate the production of light nuclei (anti-nuclei) in non-single diffractive (NSD) pp collisions at $\sqrt{s}$=7 and 14 TeV. This calculation was based on the final hadronic state in the PYTHIA and PACIAE model simulations, the event sample consisted of 1.2$\times 10^8$ events in both simulations. The PACIAE model calculated $\bar D$ yield of 6.247$\times 10^{-5}$ in NSD pp collisions at $\sqrt{s}$=7 TeV is well comparing with the ALICE rough datum of 5.456$\times 10^{-5}$. It indicated the reliability of proposed method in some extent. The yield, transverse momentum distribution, and rapidity distribution of the $\bar D$, $^3{\bar{He}}$, and $_{\bar\Lambda} ^3{\bar H}$ in NSD pp collisions at $\sqrt{s}$=7 and 14 TeV were predicted by PACIAE and PYTHIA model simulations. The yield resulted from PACIAE model simulations is larger than the one from PYTHIA model. This might reflect the role played by the parton and hadron rescatterings.Comment: 5 pages, 2 figure

AutoML-GPT: Large Language Model for AutoML

With the emerging trend of GPT models, we have established a framework called AutoML-GPT that integrates a comprehensive set of tools and libraries. This framework grants users access to a wide range of data preprocessing techniques, feature engineering methods, and model selection algorithms. Through a conversational interface, users can specify their requirements, constraints, and evaluation metrics. Throughout the process, AutoML-GPT employs advanced techniques for hyperparameter optimization and model selection, ensuring that the resulting model achieves optimal performance. The system effectively manages the complexity of the machine learning pipeline, guiding users towards the best choices without requiring deep domain knowledge. Through our experimental results on diverse datasets, we have demonstrated that AutoML-GPT significantly reduces the time and effort required for machine learning tasks. Its ability to leverage the vast knowledge encoded in large language models enables it to provide valuable insights, identify potential pitfalls, and suggest effective solutions to common challenges faced during model training

On the Effect of Lubricant on Pool Boiling Heat Transfer Performance

   For typical vapor compression processes, lubricant oil is very essential for lubricating and sealing the sliding parts and the lubricant also takes part in cushioning cylinder valves. However lubricants may migrate to the evaporator to alter the heat transfer characteristics. This is can be made clear from the viscosity and surface tension of lubricant since the viscosity of lubricant oil is about two to three orders higher than that of refrigerant whereas the corresponding surface tension of lubricant is approximately one order higher. Typically, the presence of lubricant may deteriorate heat transfer performance, yet this phenomenon becomes more severe when the lubricant mass fraction is higher. However, some previous literatures had clearly showed that the presence of lubricant oil may favor the heat transfer performance at a low lubricant fraction and the heat transfer performance may peak at a specific oil concentration. In this study, the authors aim at clarifying this phenomenon subject to pool boiling condition. Various parameters affecting the heat transfer coefficient, such as viscosity, surface tension, critical solution temperature and other thermodynamic and transport properties will be examined.    During pool boiling process, the lubricant accumulates on the surface since the refrigerant is preferential to evaporate. Hence, excess lubricant enrichment on the surface results in a thin lubricant excess layer and a thermal boundary layer, which influence the heat transfer performance, either enhancement or degradation. The excess layer may bring about a liquid-solid surface energy reduction which increases site density and reduces the bubble departure diameter, causing enhancement and degradation in heat transfer performance, respectively. However, the effect of the bubble departure diameter normally surpasses the influence of site density. This may be the crucial reason that gives rise to an occurrence of the plateau of heat transfer coefficient and followed by an apparent decline of heat transfer coefficient with a further increase of lubricant concentration.    Moreover, with the preferential evaporation of the refrigerant, a surface tension gradient is formed, which induces the Marangoni effect through which refrigerant/lubricant mixtures is supplied toward the contact line. From the phase equilibrium diagram, the maximum of the Marangoni number may occur at the low lubricant concentration with a maximum temperature difference. Hence, the presence of Marangoni effect may also be the favor the heat transfer accordingly. Also, a small fraction of lubricant will increase a larger viscosity that provide a thicker thermal boundary layer which may activate more site density, and enhances the heat transfer performance. Furthermore, miscibility may also play a crucial factor that affects the pool boiling heat transfer performance. The fluid with a smaller difference between the bulk fluid temperature and critical solution temperature may yield a better heat transfer performance by drawing superheated liquid onto the bubble sides.

The p53-dependent apoptotic pathway of breast cancer cells (BC-M1) induced by the bis-type bioreductive compound aziridinylnaphthoquinone

INTRODUCTION: Several aziridinylbenzoquinone drugs have undergone clinical trials as potential antitumor drugs. These bioreductive compounds are designed to kill cells preferentially within the hypoxia tumor microenvironment. The bioreductive compound of bis-type naphthoquinone synthesized in our laboratory, 2-aziridin-1-yl-3-[(2-{2-[(3-aziridin-1-yl-1,4-dioxo-1,4-dihydronaphthalen-2-yl)thio]ethoxy}ethyl)thio]naphthoquinone (AZ-1), had the most potent death effect on the breast cancer cells BC-M1 in our previous screening. In the present study, we determined that the mechanism of the death effect of BC-M1 cells induced by AZ-1 was mediated by the apoptosis pathway. METHODS: We evaluated the cytotoxicity of AZ-1 and the anti-breast cancer drugs tamoxifen and paclitaxel to BC-M1 cells and MCF-7 cells by the MTT assay and measured the apoptosis phenomena by Hoechst 33258 staining for apoptotic bodies. We also quantified the sub-G(1 )peak area and the ratio of the CH(2)/CH(3 )peak area of the cell membrane in BC-M1 cells by flow cytometry and (1)H-NMR spectra, respectively. The apoptosis-related protein expressions, including p53, p21, the RNA-relating protein T-cell restricted intracellular antigen-related protein, cyclin-dependent kinase 2 (cell cycle regulating kinase) and pro-caspase 3, were detected by western blot, and the caspase-3 enzyme activity was also quantified by an assay kit. RESULTS: AZ-1 induced two of the breast cancer cell lines, with IC(50 )= 0.51 μM in BC-M1 cells and with IC(50)= 0.57 μM in MCF-7 cells, and showed less cytotoxicity to normal fibroblast cells (skin fibroblasts) with IC(50)= 5.6 μM. There was a 10-fold difference between two breast cancer cell lines and normal fibroblasts. Of the two anti-breast cancer drugs, tamoxifen showed IC(50)= 0.12 μM to BC-M1 cells and paclitaxel had much less sensitivity than AZ-1. The expression of p53 protein increased from 0.5 to 1.0 μM AZ-1 and decreased at 2.0 μM AZ-1. The p21 protein increased from 0.5 μM AZ-1, with the highest at 2 μM AZ-1. Regarding the AZ-1 compound-induced BC-M1 cells mediating the apoptosis pathway, the apoptotic body formation, the sub-G(1 )peak area, the ratio of CH(2)/CH(3 )of phospholipids in the cell membrane and the enzyme activity of caspase-3 were all in direct proportion with the dose-dependent increase of the concentration of AZ-1. The death effect-related proteins, including T-cell restricted intracellular antigen-related protein, cyclin-dependent kinase 2, and pro-caspase-3, all dose-dependently decreased with AZ-1 concentration. CONCLUSIONS: The AZ-1-induced cell death of BC-M1 cells mediating the apoptosis pathway might be associated with p53 protein expression, and AZ-1 could have the chance to be a candidate drug for anti-breast cancer following more experimental evidence, such as animal models