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Abstract Premature ovarian failure (POF) is one of the common disorders found in women leading to 1% female infertility. Clinical features of POF are hypoestrogenism or estrogen deficiency, increased gonadotropin level, and, most importantly, amenorrhea. With the development of regenerative medicine, human mesenchymal stem cell (hMSC) therapy brings new prospects for POF. This study aimed to describe the types of MSCs currently available for POF therapy, their biological characteristics, and their mechanism of action. It reviewed the latest findings on POF to provide the theoretical basis for further investigation and clinical therapy.

On basis of analysis of detection methods of voltage sag such as voltage peak detection method,Fourier transform method,wavelet transform method,d-q transformation method and pqr instantaneous power method,the paper proposed a detection algorithm of dynamic voltage restorer(DVR) based on instantaneous reactive power theory.For the problem of poor real-time of a traditional ButterWorth low pass filter,it designed a new type of filter which is consisted of a band-stop filter in series with a low pass filter.The simulation results in Matlab/Simulink showed that the new type of filter can reduce the detection time to one third of fundamental cycle without reducing precise,and improve the real time of voltage sag detection.

Background Photodynamic therapy (PDT) has been strongly recommended as an excellent alternative treatment for Bowen disease (BD). However, reported data on 5-aminolaevulinic acid-mediated PDT (ALA-PDT) with red-light irradiation are limited and the long-term effectiveness remains to be determined, especially in dark-skinned populations. Objectives We aimed to review routine clinical practice in the field of BD treatment with ALA-PDT over an extended study period (2011–2021), calculate the overall clearance rate, and explore and evaluate factors that might affect the effectiveness of therapy in a real-world setting. Methods The medical records of patients with BD who received ALA-PDT with red-light irradiation between February 2011 and June 2021 were reviewed and summarized. Univariate and multivariate analyses of clinically relevant variables that may affect treatment outcomes were conducted to identify risk predictors. Results The overall clearance rate of 122 BD lesions was 89.3% with a median follow-up time of 36 months. The correlation between the effectiveness and fluorescence intensity of pre-PDT or PDT sessions was statistically significant after eliminating the interference of confounding factors. All recurrences occurred in the first 2 years following ALA-PDT. Conclusions ALA-PDT is an effective treatment for BD in patients with darker-coloured skin. Well-executed operations and effective pretreatment are the determinants of effectiveness. Fluorescence intensity of pre-PDT appeared to be a significant predictor of final effectiveness. In addition, 2 years of follow-up is necessary following ALA-PDT. [ABSTRACT FROM AUTHOR]

A highly graphitized carbon on a silicon monoxide (SiO) surface coating at low temperature, based on polymer precursor π⁻π stacking, was developed. A novel conductive and electrochemically stable carbon coating was rationally designed to modify the SiO anode materials by controlling the sintering of a conductive polymer, a pyrene-based homopolymer poly (1-pyrenemethyl methacrylate; PPy), which achieved high graphitization of the carbon layers at a low temperature and avoided silicon carbide formation and possible SiO material transformation. When evaluated as the anode of a lithium-ion battery (LIB), the carbon-coated SiO composite delivered a high discharge capacity of 2058.6 mAh/g at 0.05 C of the first formation cycle with an initial Coulombic efficiency (ICE) of 62.2%. After 50 cycles at 0.1 C, this electrode capacity was 1090.2 mAh/g (~82% capacity retention, relative to the capacity of the second cycle at 0.1 °C rate), and a specific capacity of 514.7 mAh/g was attained at 0.3 C after 500 cycles. Furthermore, the coin-type full cell composed of the carbon coated SiO composite anode and the Li[Ni0.5Co0.2Mn0.3O₂] cathode attained excellent cycling performance. The results show the potential applications for using a π⁻π stacking polymer precursor to generate a highly graphitize coating for next-generation high-energy-density LIBs.

A highly graphitized carbon on a silicon monoxide (SiO) surface coating at low temperature, based on polymer precursor π⁻π stacking, was developed. A novel conductive and electrochemically stable carbon coating was rationally designed to modify the SiO anode materials by controlling the sintering of a conductive polymer, a pyrene-based homopolymer poly (1-pyrenemethyl methacrylate; PPy), which achieved high graphitization of the carbon layers at a low temperature and avoided silicon carbide formation and possible SiO material transformation. When evaluated as the anode of a lithium-ion battery (LIB), the carbon-coated SiO composite delivered a high discharge capacity of 2058.6 mAh/g at 0.05 C of the first formation cycle with an initial Coulombic efficiency (ICE) of 62.2%. After 50 cycles at 0.1 C, this electrode capacity was 1090.2 mAh/g (~82% capacity retention, relative to the capacity of the second cycle at 0.1 °C rate), and a specific capacity of 514.7 mAh/g was attained at 0.3 C after 500 cycles. Furthermore, the coin-type full cell composed of the carbon coated SiO composite anode and the Li[Ni0.5Co0.2Mn0.3O₂] cathode attained excellent cycling performance. The results show the potential applications for using a π⁻π stacking polymer precursor to generate a highly graphitize coating for next-generation high-energy-density LIBs.

Deploying the dynamic wireless power transfer (DWPT) equipment at intersections can improve the transportation efficiency and decrease the energy consumption. It can easily turn the disadvantages of waiting time for red phase into the advantages of charging benefits for electric vehicles (EVs). This study develops a multiobjective speed planning model with differentiated charging strategy to optimize the EV's trajectory at signalized intersections with DWPT. To mitigate the negative impact of DWPT, the proposed model is divided into charging priority driving (C-eco-driving) mode and time priority driving (T-eco-driving) mode for connected and automated electric vehicles (CAEVs) to apply different scenarios. Meanwhile, a widely applied car-following model, i.e., the Intelligent Driver Model (IDM), has been calibrated with the ground-truth dataset to meet the intersection characteristic for EVs in mixed traffic. The efficiency and robustness of two eco-driving modes were validated in single-vehicle and mixed traffic based on MATLAB simulation. For single vehicle, the electricity benefits of the C-eco-driving mode and T-eco-driving mode increase about 0.0867kWh and 0.0532kWh, respectively. T-eco-driving mode reduces 2.5s of travel time. For mixed traffic, the C-eco-driving mode provides more charging benefits about 51~73% than no-control strategy. In contrast, the T-eco-driving mode provides significant time benefits of 2.6s and slight electricity benefits of 12~30% than no-control strategy. The increment of market penetration rate and wireless charging length can significantly improve the charging benefits. When charging length has the same value, the closer the DWPT facilities to the intersection, the more obvious the charging benefits., Author(s): Lan Yang [1]; Mengjie Han (corresponding author) [1]; Shan Fang [1]; Guoyuan Wu [2]; He Sheng [1]; Heng Wei [3]; Xiangmo Zhao [1] 1. Introduction EVs have been recognized [...]

Many studies have simulated traffic behavior at signalized intersections using various Car-Following (CF) models. However, the performance of which CF Model is superior at signalized intersections has not been thoroughly analyzed and evaluated. In this study, two novel Artificial Neural Network (ANN) CF models, the Convolutional Neural Network--Long Short-term Memory (CNN-LSTM) and the Convolution-LSTM (Conv-LSTM)--are first applied to predict CF behaviors at signalized intersections. Both models can extract spatial and temporal information to address the long-term dependency problem more effectively. Based on the filtered NGSIM dataset, we conduct a comparative empirical study of three conventional CF models and five ANN CF models. The dataset is divided into two categories based on the characteristics of CF behavior at signalized intersections: continuous and discontinuous. The experiments demonstrated that ANN CF models outperformed conventional CF models when the output was the velocity in two categories of traffic flow but only failed to do so when the output was acceleration in discontinuous traffic flow. The proposed models were capable of accurately predicting acceleration, but the traffic fluctuations also existed as time passed. Additionally, it was discovered that while the ANN CF model is preferable for traffic flow simulation, the conventional CF model still cannot be ignored for discontinuous traffic flow simulation, particularly when acceleration is required., Author(s): Lan Yang [1]; Shan Fang (corresponding author) [1]; Guoyuan Wu [2]; He Sheng [1]; Zhigang Xu [1]; Mengxiao Zhang [1]; Xiangmo Zhao [1] 1. Introduction With the development of [...]

In order to track the research progress of AEB-related technologies, this paper makes a systematic analysis and research on the impact factors, key technologies, and effect evaluation of AEB. First, the paper deeply analyzes the three levels of factors affecting the performance of AEB, which are vehicle factors, driver factors, and environmental factors. Second, the paper deeply studies the technical status of the three subsystems of environment perception, decision-making, and control execution. Particularly, the performance of Mazda, Honda, NHTSA, Berkeley, and Seungwuk Moon are compared and analyzed based on MATLAB. Third, the paper summarizes the current AEB virtual test methods, closed field test methods, and its test sites. Three classic evaluation methods in the world, including the AEB test evaluation standards of ENCAP, IIHS, and i-Vista are analyzed. Finally, the paper prospects the specific research directions, including the protection of vulnerable road users, target detection method, collision avoidance strategy, complex scenarios application, and application of emerging technologies., Author(s): Lan Yang [1]; Yipeng Yang (corresponding author) [1]; Guoyuan Wu (corresponding author) [2]; Xiangmo Zhao [1]; Shan Fang [1]; Xishun Liao [2]; Runmin Wang [1]; Mengxiao Zhang [1] 1. [...]

Fe2O3 with high theoretical capacity (1007 mA h g−1) and low cost is a potential anode material for lithium‐ion batteries (LIBs), but its practical application is restricted by its low electrical conductivity and large volume changes during lithiation/delithiation. To solve these problems, Fe2O3@Ti3C2Tx composites were synthesized by a mussel‐like modification method, which relies on the self‐polymerization of dopamine under mild conditions. During polymerization, the electronegative group (−OH) on dopamine can easily coordinate with Fe3+ ions as well as form hydrogen bonds with the −OH terminal group on the surface of Ti3C2Tx, which induces a uniform distribution of Fe2O3 on the Ti3C2Tx surface and mitigates self‐accumulation of MXene nanosheets. In addition, the polydopamine‐derived carbon layer protects Ti3C2Tx from oxidation during the hydrothermal process, which can further improve the electrical conductivity of the composites and buffer the volume expansion and particle agglomeration of Fe2O3. As a result, Fe2O3@Ti3C2Tx anodes exhibit ~100 % capacity retention with almost no capacity loss at 0.5 A g−1 after 250 cycles, and a stable capacity of 430 mA h g−1 at 2 A g−1 after 500 cycles. The unique structural design of this work provides new ideas for the development of MXene‐based composites in energy storage applications. [ABSTRACT FROM AUTHOR]