基于Matlab的量子激光雷达稳频通信模拟系统设计

传统通信模拟系统设计较为复杂,导致模拟过程消耗能量较大,不能准确模拟稳频通信质量。因此,提出基于Matlab的量子激光雷达稳频通信模拟系统。由于振荡器是雷达形成初始信号源的基础,通过分析振荡电路与相位噪声,获得相位噪声函数与通信频率存在的关系;为确保通信过程的稳定,将准确性与稳定性作为信号质量的评价指标,并采用锁频环稳频技术计算频率偏移程度,根据PID控制算法控制频率,量子激光雷达稳频通信;利用Matlab确定激光器、探测器等硬件组成结构,通过时序与数字阵列的设置完成模拟系统设计。仿真结果表明所提系统结构简便、性能稳定,能够真实模拟出稳频通信的信号质量。     

An Injectable Hydrogel for Simultaneous Photothermal Therapy and Photodynamic Therapy with Ultrahigh Efficiency Based on Carbon Dots and Modified Cellulose Nanocrystals

The convenience of injectable hydrogels that can provide high loading of diverse phototherapy agents and further long-time retention at the tumor site has attracted tremendous interest in simultaneous photothermal and photodynamic cancer therapies. However, to incorporate the phototherapy agents into hydrogels, complex modifications are generally unavoidable. Moreover, these phototherapy agents usually suffer from low efficiency and work at different irradiation wavelengths outside the near infrared windows. Hence, a method for the fabrication of an injectable hydrogel for simultaneous photothermal therapy and photodynamic therapy, through the Schiff-base reaction between amido modified carbon dots (NCDs) and aldehyde modified cellulose nanocrystals is proposed. The NCDs act as both phototherapy agents and crosslinkers to form hydrogels. Significantly, the NCDs demonstrate an extremely high photothermal conversion efficiency of 77.6% which is among the highest levels for photothermal agents and a high singlet quantum yield of 0.37 under a single 660 nm light-emitting diode irradiation. The hydrogels are examined through in vitro and in vivo animal experiments which show nontoxic and effectively tumor inhibition. Thus, the strategy of direct reaction of phototherapy agents and the matrix not only provides new strategies for injectable hydrogel fabrication but paves a new road for advanced tumor treatment.     

Predicting the mechanical properties of Cu–Al2O3 nanocomposites using machine learning and finite element simulation of indentation experiments

Micromechanics model, finite element (FE) simulation of microindentation and machine learning were deployed to predict the mechanical properties of Cu–Al₂O₃ nanocomposites. The micromechanical model was developed based on the rule of mixture and grain and grain boundary sizes evolution to predict the elastic modulus of the produced nanocomposites. Then, a FE model was developed to simulate the microindentation test. The input for the FE model was the elastic modulus that was computed using the micromechanics model and wide range of yield and tangent stresses values. Finally, the output load-displacement response from the FE model, the elastic modulus, the yield and tangent strengths used for the FE simulations, and the residual indentation depth were used to train the machine learning model (Random vector functional link network) for the prediction of the yield and tangent stresses of the produced nanocomposites. Cu–Al₂O₃ nanocomposites with different Al₂O₃ concentration were manufactured using insitu chemical method to validate the proposed model. After training the model, the microindentation experimental load-displacement curve for Cu–Al₂O₃ nanocomposites was fed to the machine learning model and the mechanical properties were obtained. The obtained mechanical properties were in very good agreement with the experimental ones achieving 0.99 coefficient of determination R2 for the yield strength.     

Effect of the thicknesses of the Al2SiO5 ion conductor on the opto-electrical properties for all-solid electrochromic devices

In this study, an all-solid-state electrochromic device (ECD) with the structure of ITO/WO₃/Al₂SiO₅/NiO_x/ITO was prepared, and the effect of the Al₂SiO₅ solid electrolyte thicknesses on the opto-electrical performance was investigated. The microstructure and surface morphology were characterized using XRD, SEM and AFM, and the surface morphology and degree of surface looseness demonstrate a significant influence on the opto-electrical properties of ECDs. The charge transfer dynamics at the solid-solid interface were characterized using EIS to obtain an ionic conductivity of 4.637 × 10^-8 S/cm. CV, CA and UV–Visible spectra were employed to record the in situ electrochemical and optical properties. The results revealed that the highest optical modulation was 44.58%, the coloring and bleaching times were 14.8 s and 3.7 s, and the highest coloring efficiency was 98.17 cm²/C, which indicates that excellent opto-electrical properties were obtained. When the thickness increases, the degree of surface dense morphology transforms, and the loose morphology is more favorable for ion conductivity, which improves the opto-electrical properties. The results in this study provide insights into the understanding of Al³⁺-based all-solid-state ECDs, which promote the exploration of new types of Al³⁺ ionic conductors for all-solid-state ECDs.     

Piperine Targets Different Drug Resistance Mechanisms in Human Ovarian Cancer Cell Lines Leading to Increased Sensitivity to Cytotoxic Drugs

Our goal was to examine the anticancer effects of piperine against the resistant human ovarian cancer cells and to explore the molecular mechanisms responsible for its anticancer effects. Our study used drug-sensitive ovarian cancer cell line W1 and its sublines resistant to paclitaxel (PAC) and topotecan (TOP). We analyzed the cytotoxic effect of piperine and cytostatic drugs using an MTT assay. The impact of piperine on protein expression was determined by immunofluorescence and Western blot. We also examined its effect on cell proliferation and migration. We noticed a different level of piperine resistance between cell lines. Piperine increases the cytotoxic effect of PAC and TOP in drug-resistant cells. We observed an increase in PTPRK expression correlated with decreased pTYR level after piperine treatment and downregulation of P-gp and BCRP expression. We also noted a decrease in COL3A1 and TGFBI expression in investigated cell lines and increased COL3A1 expression in media from W1PR2 cells. The expression of Ki67 protein and cell proliferation rate decreased after piperine treatment. Piperine markedly inhibited W1TR cell migration. Piperine can be considered a potential anticancer agent that can increase chemotherapy effectiveness in cancer patients.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

Optimal Design of Novel Electromagnetic-Ring Active Balancing Actuator with Radial Excitation

Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the effii-ciency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the opera-tional process,different types of active balancing actuators have been designed and widely applied in actual produc-tion.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance param-eters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving effi-ciency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5％.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electro-magnetic efficiency and a more stable and compact structure.     

Molecular Characteristics of Amyloid Precursor Protein (APP) and Its Effects in Cancer

Amyloid precursor protein (APP) is a type 1 transmembrane glycoprotein, and its homologs amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are highly conserved in mammals. APP and APLP are known to be intimately involved in the pathogenesis and progression of Alzheimer’s disease and to play important roles in neuronal homeostasis and development and neural transmission. APP and APLP are also expressed in non-neuronal tissues and are overexpressed in cancer cells. Furthermore, research indicates they are involved in several cancers. In this review, we examine the biological characteristics of APP-related family members and their roles in cancer.