The impact of facial attractiveness and alleged personality traits on fairness decisions in the ultimatum game: Evidence from ERPs.

In the mind of the beholder the personality and facial attractiveness of others are interrelated. However, how these specific properties are processed in the neurocognitive system and interact with each other while economic decisions are made is not well understood. Here, we combined the ultimatum game with EEG technology, to investigate how alleged personality traits and the perceived facial attractiveness of proposers of fair and unfair offers influence their acceptance by the responders. As expected, acceptance rate was higher for fair than unfair allocations. Overall, responders were more likely to accept proposals from individuals with higher facial attractiveness and with more positive personality traits. In ERPs, words denoting negative personality traits elicited larger P2 components than positive trait words, and more attractive faces elicited larger LPC amplitudes. Replicating previous findings, FRN amplitudes were larger to unfair than to fair allocations. This effect was diminished if the proposer's faces were attractive or associated with positive personality traits. Hence, facial attractiveness and the valence of personality traits seem to be evaluated independently and at different time points. Subsequent decision making about unfair offers is similarly influenced by high attractiveness and positive personality of the proposer, diminishing the negative response normally elicited by "unfair" proposals, possibly due a "reward" effect. In the ERPs to the proposals the effect of positive personality and attractiveness were seen in the FRN and P300 components but for positive personality traits the effect even preceded the FRN effect. Altogether, the present results indicate that both high facial attractiveness and alleged positive personality mitigate the effects of unfair proposals, with temporally overlapping but independent neurocognitive correlates.

Construction of Monolayer Ti3C2Tx MXene on Nickel Foam under High Electrostatic Fields for High-Performance Supercapacitors.

Ti3C2Tx MXene, as a common two-dimensional material, has a wide range of applications in electrochemical energy storage. However, the surface forces of few-layer or monolayer Ti3C2Tx MXene lead to easy agglomeration, which hinders the demonstration of its performance due to the characteristics of layered materials. Herein, we report a facile method for preparing monolayer Ti3C2Tx MXene on nickel foam to achieve a self-supporting structure for supercapacitor electrodes under high electrostatic fields. Moreover, the specific capacitance varies with the deposition of different-concentration monolayer Ti3C2Tx MXene on nickel foam. As a result, Ti3C2Tx/NF has a high specific capacitance of 319 mF cm-2 at 2 mA cm-2 and an excellent long-term cycling stability of 94.4% after 7000 cycles. It was observed that the areal specific capacitance increases, whereas the mass specific capacitance decreases with the increasing loading mass. Attributable to the effect of the high electrostatic field, the self-supporting structure of the Ti3C2Tx/NF becomes denser as the concentration of the monolayer Ti3C2Tx MXene ink increases, ultimately affecting its electrochemical performance. This work provides a simple way to overcome the agglomeration problem of few-layer or monolayer MXene, then form a self-supporting electrode exhibiting excellent electrochemical performance.

Pregnancy outcomes in infertile patients with endometrial hyperplasia with or without atypia undergoing in vitro fertilization: the early-follicular long protocol is superior to midluteal long protocol.

Background: Although in vitro fertilization (IVF) in infertile patients with endometrial hyperplasia is common after drug treatment, the pregnancy outcomes are often unsatisfactory. Till date, no studies have reported the outcome of patients with endometrial hyperplasia treated using early-follicular long (EL) protocol and midluteal long (ML) protocol. Objective: To evaluate the pregnancy outcomes and disease prognosis of patients with endometrial hyperplasia with or without atypia undergoing IVF treatment with EL protocol or ML protocol. Methods: This was a retrospective study in university-affiliated reproductive medical center. A total of 138 patients with endometrial hyperplasia undergoing IVF treatment were included to compare the pregnancy outcomes and disease prognosis between EL and ML protocols. We further matched 276 patients with normal endometrium to compare the pregnancy outcomes between patients with endometrial hyperplasia and patients with normal endometrium under different controlled ovarian stimulation (COS) protocol. Results: In patients with endometrial hyperplasia, the clinical pregnancy rate (CPR) and live birth rate (LBR) were significantly higher in EL protocol than in ML protocol (61.8% vs. 43.5%, P=0.032; 50.0% vs. 30.6%, P= 0.022). In the ML protocol, patients with endometrial hyperplasia had significantly lower CPR and LBR than those with normal endometrium (43.5% vs. 59.7%, P=0.037; 30.6% vs. 49.2%, P=0.016). While in the EL protocol, they achieved similar CPR and LBR as patients with normal endometrium (61.8% vs. 69.7%, P=0.232; 50.0% vs. 59.9%, P=0.156). In patients with endometrial hyperplasia, COS protocol was an independent factor affecting clinical pregnancy (adjusted odds ratio [OR] 2.479; 95% confidence interval [CI] 1.154-5.327) and live birth (adjusted OR 2.730; 95% CI 1.249-5.966). After 1-10 years of follow-up, no significant difference was found in the recurrence rate of endometrial lesions between both treatment groups. Conclusions: For patients with endometrial hyperplasia undergoing IVF treatment, the EL protocol is superior to ML protocol, and in the EL protocol, they can achieve similar pregnancy outcomes as patients with normal endometrium.

DUSP2 affects bladder cancer prognosis by down-regulating MEK/ERK and P38 MAPK signaling pathways through PTPN7.

BACKGROUND: As one of the leading causes of cancer death worldwide, bladder cancer (BCa) ranks 12th in incidence rate. Dual Specific Phosphatase 2 (DUSP2) is a member of the bispecific protein phosphatase subfamily. DUSP2 is closely related to the prognosis of cancer, but the role of DUSP2 in bladder cancer is still unclear. This study aims to explore how DUSP2 affects the prognosis of bladder cancer and clarify the important mechanism in bladder cancer. METHODS: Bioinformatics and experiments have detected the anti-tumor effect of DUSP2. Construct a DUSP2 overexpression cell model, and then use protein blotting experiments to verify the efficiency of transfection. The effects of DUSP2 on proliferation, metastasis, apoptosis, epithelial mesenchymal transition (EMT) and immune invasion of bladder cancer cells were detected in vitro or in vivo. In addition, the mechanism of DUSP2 regulating MEK/ERK through PTPN7 pathway and P38 MAPK inhibiting the progression of bladder cancer was also discussed. RESULTS: The expression of DUSP2 was down regulated in bladder cancer samples and cell lines. The overexpression of DUSP2 inhibits the proliferation, metastasis and immune microenvironment of bladder cancer cells. In addition, we confirmed that DUSP2 regulates MEK/ERK and P38 MAPK through PTPN7 pathway to inhibit the progression of bladder cancer. CONCLUSION: DUSP2 inhibits the progression of bladder cancer by regulating PTPN7. These results suggest that DUSP2/PTPN7/MEK/ERK pathway may become a new therapeutic target for bladder cancer.

Prediction and Global Sensitivity Analysis of Long-Term Deflections in Reinforced Concrete Flexural Structures Using Surrogate Models.

Reinforced concrete (RC) is the result of a combination of steel reinforcing rods (which have high tensile) and concrete (which has high compressive strength). Additionally, the prediction of long-term deformations of RC flexural structures and the magnitude of the influence of the relevant material and geometric parameters are important for evaluating their serviceability and safety throughout their life cycles. Empirical methods for predicting the long-term deformation of RC structures are limited due to the difficulty of considering all the influencing factors. In this study, four popular surrogate models, i.e., polynomial chaos expansion (PCE), support vector regression (SVR), Kriging, and radial basis function (RBF), are used to predict the long-term deformation of RC structures. The surrogate models were developed and evaluated using RC simply supported beam examples, and experimental datasets were collected for comparison with common machine learning models (back propagation neural network (BP), multilayer perceptron (MLP), decision tree (DT) and linear regression (LR)). The models were tested using the statistical metrics R2, RAAE, RMAE, RMSE, VAF, PI, A10-index and U95. The results show that all four proposed models can effectively predict the deformation of RC structures, with PCE and SVR having the best accuracy, followed by the Kriging model and RBF. Moreover, the prediction accuracy of the surrogate model is much lower than that of the empirical method and the machine learning model in terms of the RMSE. Furthermore, a global sensitivity analysis of the material and geometric parameters affecting structural deflection using PCE is proposed. It was found that the geometric parameters are more influential than the material parameters. Additionally, there is a coupling effect between material and geometric parameters that works together to influence the long-term deflection of RC structures.

Secrecy Capacity Enhancement in Active IRS-Assisted UAV Communication System.

As a new technology for reconstructing communication environments, intelligent reflecting surfaces (IRSs) can be applied to UAV communication systems. However, some challenges exist in IRS-assisted UAV communication system design, such as physical layer security issues, IRS design, and power consumption issues owing to the limitation of the hardware. Therefore, a secrecy capacity optimization scheme for an active IRS-assisted unmanned aerial vehicle (UAV) communication system is proposed to solve multi-user security issues. In particular, controllable power amplifiers are integrated into reflecting units to solve the problem of blocked links, and the UAV can dynamically select the served user according to the channel quality. In order to maximize the system average achievable secrecy capacity and ensure the power constraints of the UAV and active IRS, user scheduling, UAV trajectory, beamforming vector, and reflection matrix are jointly optimized, and the block coordinate descent (BCD) algorithm is applied to solve this non-convex problem. Simulation results show that the active IRS-assisted UAV communication scheme can significantly weaken the "multiplicative fading" effect and enhance the system secrecy capacity by 55.4% and 11.9% compared with the schemes with passive IRS and without optimal trajectory, respectively.