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【Objective】With the development of the space-ground integrated information network, the Low Earth Orbit (LEO) satellite communication system is ushering in a development boom. The Paired Carrier Multiple Access (PCMA) technology is gradually developing to the low-orbit satellite communication due to its advantages of saving bandwidth resources. However, traditional PCMA technology is mostly used in high-orbit satellites, and cannot adapt to the highly dynamic fading channel character-istics of low-orbit satellite channels, which greatly degrades the bit error performance of the PCMA receiver. The bottleneck lies in the channel estimation and equalization technologies for overlapping signals.【Methods】Aiming at the channel characteristics of LEO satellites, this paper proposes a channel estimation scheme that combines training sequence estimation and Autoregressive (AR) model prediction. Based on the idea of superimposed training sequence channel estimation, an iterative method suitable for PCMA mixed signal channel estimation is introduced to improve the accuracy of training sequence channel estimation through iteration. The AR model is used to predict the Channel State Information (CSI) of the data sequence in real time. The use of AR model can also reduce the frequency of channel estimation in training sequences, so as to adapt to the dynamics of LEO satellite channels.【Results】The simulation results show that the idea of superimposed training sequence channel estimation can be applied to the PCMA signals, and accurate channel estimation can be obtained after iterations. The method proposed in this paper can effectively improve the accuracy of channel estimation. After signal separation and demodulation, the bit error rate can reach the order of 10-3when the signal-to-noise ratio is greater than 9 dB.【Conclusion】A channel estimation method for PCMA signal is proposed in this paper. The simulation results show that the bit error rate loss is within an acceptable range, which can support the application of PCMA technology in low-orbit satellite communication. The proposed algorithm has the advantages of simple structure, low complexity, and high practical value.

To optimize the performance of the soft actuator, numerical simulation and regression analysis of the multi-structure parameter are presented based on the numerical calculation method. Firstly, numerical simulation and regression analysis were performed on the parameters of different driving channel shapes, including equilateral triangle, square, regular pentagon, regular hexagon, and circle, to determine the driving performance under different channel cross-sections. Secondly, numerical simulation and regression analysis were conducted on the parameters of fiber winding diameter and winding angle of the soft actuator, and qualitative analysis was performed on the failure states of the numerical calculations. Lastly, numerical simulation and regression analysis were carried out on the parameters of wall thickness and driving channel length of the soft actuator to determine the influence of these parameters on the driving performance. Through the numerical simulation and regression analysis, this study provides a necessary theoretical foundation for the optimization design of soft actuator, effectively improving the development efficiency and dynamic performance of soft actuators.

Supercapacitors with high power density, ultralong lifespan and wide range operating temperature have drawn significant attention in recent years. However, monitoring the state of charge in supercapacitors in a cost-effective and flexible way is still challenging. Techniques such as transmission electron microscopy and X-ray diffraction can analyze the characteristics of supercapacitor well. But with large size and high price, they are not suitable for daily monitoring of the supercapacitors’ operation. In this paper, a low cost and easily fabricated fiber-optic localized surface plasmon resonance (LSPR) probe is proposed to monitor the state of charge of the electrode in a supercapacitor. The Au nanoparticles were loading on the fiber core as LSPR sensing region. In order to implant the fiber in the supercapacitor, a reflective type of fiber sensor was used. The results show that this tiny fiber-optic LSPR sensor can provide online monitoring of the state of charge during the charging and discharging process in situ. The intensity shift in LSPR sensor has a good linear relationship with the state of charge calculated by standard galvanostatic charging and discharging test. In addition, this LSPR sensor is insensitive to the temperature change, presenting a great potential in practical applications.

Based on the time-temperature equivalence principle, the relationship between the melt relaxation time (MRT) and melt heating temperature (MHT) in an improved gas-assisted extrusion (GAE) of a polypropylene (PP) sheet was investigated by numerical simulations. In the simulations, the MRT was varied and the inherent properties of the MHT were controlled using experimental methods. With an increase in MRT, the velocity in all directions, pressure drop, and shear rate of the melt increased; however, increasing the MRT does not always yield a positive effect on the GAE process of the melt. For instance, the melt velocity increased vertically at the die exit with MRT, resulting in an outward extrudate swell. In addition, the extruded product was intact when the melt was heated to 220[degrees] C, which verified the principle of time-temperature equivalence. KEYWORDS gas-assisted extrusion, heating temperature, plastic sheets, relaxation time, timetemperature equivalence principle, 1 | INTRODUCTION In conventional plastic sheet extrusion, the high viscoelasticity of polymers makes them susceptible to undesirable extrudate swell [1-3] and tensile deformation, [4-9] and the internal stress in [...]

Aiming at numerous defects at SnO2/perovskite interface and lattice mismatch in perovskite solar cells (PSCs), we design a kind of three‐dimensional (3D) molecular glue (KBF4‐TFMSA), which is derived from strong intramolecular hydrogen bonding interaction between potassium tetrafluoroborate (KBF4) and trifluoromethane‐sulfonamide (TFMSA). A remarkable efficiency of 25.8 % with negligible hysteresis and a stabilized power output of 25.0 % have been achieved, in addition, 24.57 % certified efficiency of 1 cm2 device is also obtained. Further investigation reveals that this KBF4‐TFMSA can interact with oxygen vacancies and under‐coordinated Sn(IV) from the SnO2, in the meantime, FA+ (NH2−C=NH2+) and K+ cations can be well fixed by hydrogen bonding interaction between FA+ and BF4−, and electrostatic attraction between sulfonyl oxygen and K+ ions, respectively. Thereby, FAPbI3 crystal grain sizes are increased, interfacial defects are significantly reduced while carrier extraction/ transportation is facilitated, leading to better cell performance and excellent stabilities. Non‐encapsulated devices can maintain 91 % of their initial efficiency under maximum‐power‐point (MPP) tracking while continuous illumination (~100 mW cm−2) for 1000 h, and retain 91 % of the initial efficiency after 1000 h “double 60” damp‐heat stability testing (60 °C and 60 %RH (RH, relatively humidity)). [ABSTRACT FROM AUTHOR]

In water‐assisted injection molding processes, it is crucial to understand the mechanisms governing the formation of hollow structures and identify the key factors influencing their morphology and dimensional accuracy. This work combined experimental analysis and numerical simulation to investigate the influence of different mold cavities and main processing parameters on hollow structures in overflow water‐assisted injection molded parts of short‐glass‐fiber‐reinforced polypropylene, that is, hollow shape and hollow ratio. The results show that the hollow shape and hollow ratio depended not only on the cross‐sectional location but also on the cross‐sectional shape of the mold cavity. For the circular parts, the hollow shape resembled the cross‐sectional shape of the mold cavity, with a relatively small and uniform hollow ratio across cross‐sectional locations. For the noncircular parts, the hollow shape varied considerably with increasing distance from the water inlet. Moreover, the results also show that except for the influence of water‐injection delay time on the uniformity of the hollow ratio, higher melt temperature (250°C), shorter water‐injection delay time (0 s), and higher water pressure (10 MPa) contributed to the hollow shape being closer to the cross‐sectional shape of mold cavities and made hollow ratios relatively larger and more uniform. [ABSTRACT FROM AUTHOR]

Gas-assisted sheet extrusion is a promising and environment-friendly method used in polymer processing. Insufficient gas intake due to the adherence of the polymer melt to the inlet gap is a disadvantage of the method. Therefore, in this study an improved die assembly with parallel gas intake was designed. As the melt is prone to falling at the die exit during the horizontal extrusion process, different thickness settings are used for the up and down gas layers (0.25 and 0.75 mm, respectively) to avoid this. For the improved die assembly, the gas inlet pressure may be varied systematically to study the mechanism of stable sheet extrusion. When the gas inlet pressure is 0.1 MPa, the melt can be extruded smoothly, and the extruded sheet surface is transparent and flat. However, when the optimum pressure is exceeded, the extruded sheet becomes twisted or even broken. KEYWORDS down gas layer, gas inlet pressure, gas-assisted extrusion (GAE), improved die assembly, numerical simulation, 1 | INTRODUCTION Plastic sheets are used extensively in the production of thermoforming products, packaging products, circuit board partitions, handicrafts, and other industries. [1-5] However, owing to the viscoelasticity [6-8] [...]

In this study, 1-methyl-3-benzyl-imidazolium halides (BzMIMX, X = I, Br, Cl) were introduced to passivate the FAPbI3/spiro-OMeTAD interface for efficient and stable PSCs. BzMIMBr exhibits the best passivation effect, in which Br− ions can well passivate the iodide vacancy from the perovskite surface. In the meantime, the weak coordination interaction between N atoms from imidazole and Pb2+ cations also passivate under-coordinated Pb2+ and reduce interfacial defects to some degree. Interestingly, a very small amount of the BzMIMBr could penetrate the bulk perovskite to further passivate the grain boundaries of the bulk perovskite film. The champion PCE of our small-size PSC devices can reach 25.3% with negligible hysteresis. Besides, π–π self-assembly from the BzMIM+ can strengthen the interfacial modification effect, which enhances the anti-humidity ability of perovskite films and the devices. When stored under ambient conditions (20 °C and 20% RH) for over 5000 h, this modification helps the cell to maintain 90% of its initial efficiency, indicating its good long-term stability. BzMIMBr-modified devices exhibit much better operational stability by maintaining 91% of the initial efficiency after 1000 h of continuous illumination with a bias voltage near the maximum power point. Our osmotic modification strategy provides a feasible way to achieve high-performance and stable PSCs. [ABSTRACT FROM AUTHOR]

Accurately measuring leaf chlorophyll content (LCC) is crucial for monitoring maize growth. This study aims to rapidly and non-destructively estimate the maize LCC during four critical growth stages and investigate the ability of phenological parameters (PPs) to estimate the LCC. First, four spectra were obtained by spectral denoising followed by spectral transformation. Next, sensitive bands (Rλ), spectral indices (SIs), and PPs were extracted from all four spectra at each growth stage. Then, univariate models were constructed to determine their potential for independent LCC estimation. The multivariate regression models for the LCC (LCC-MR) were built based on SIs, SIs + Rλ, and SIs + Rλ + PPs after feature variable selection. The results indicate that our machine-learning-based LCC-MR models demonstrated high overall accuracy. Notably, 83.33% and 58.33% of these models showed improved accuracy when the Rλ and PPs were successively introduced to the SIs. Additionally, the model accuracies of the milk-ripe and tasseling stages outperformed those of the flare–opening and jointing stages under identical conditions. The optimal model was created using XGBoost, incorporating the SI, Rλ, and PP variables at the R3 stage. These findings will provide guidance and support for maize growth monitoring and management. [ABSTRACT FROM AUTHOR]

The burden of digestive cancers is increasing worldwide. The Global Cancer Observatory (GLOBOCAN) 2020 and the Global Burden of Disease (GBD) 2019 are two primary cancer databases, which have a significant impact on policy formulation and resource allocation. We aim to compare the incidence and mortality of digestive cancers between them. Digestive cancer (esophageal, stomach, colorectal, liver, gallbladder and pancreatic cancer) incidence was obtained from the Cancer Today and GBD 2019 result tool. The top five countries with the most or minor difference between GLOBOCAN 2020 and GBD 2019 in age‐standardized incidence rates (ASIRs) of digestive cancers were identified. A systematic search on the incidence of specific digestive cancer in selected countries from PubMed and Embase was conducted, and 20 of 281 publications were included. The most significant differences in digestive cancers incidence were commonly found in Asian countries (70%), particularly Indonesia, Vietnam and Myanmar, located in Southeast Asia. The ASIRs for most digestive cancers, except liver cancer, in GLOBOCAN 2020 were higher than those in GBD 2019. Gallbladder cancer had the highest average ratio, followed by liver cancer. The most commonly used standard population was Segi's standard population, followed by the World Health Organization standard population. The data sources nor the processing methods of GLOBOCAN 2020 and GBD 2019 were not similar. Low‐ and middle‐income countries without population‐based cancer registries were more likely to have selection bias in data collection and amplify regional variations of etiological factors. Better judgments on the quality of cancer data can be made. [ABSTRACT FROM AUTHOR]

Chlorophyll is an important indicator for monitoring crop growth and is vital for agricultural management. Therefore, rapid and accurate estimation of chlorophyll content is important for decision support in precision agriculture to accurately monitor the SPAD (Soil and Plant Analyzer Development) values of winter wheat. This study used winter wheat to obtain canopy reflectance based on UAV hyperspectral data and to calculate different vegetation indices and red-edge parameters. The best-performing vegetation indices and red-edge parameters were selected by Pearson correlation analysis and multiple stepwise regression (MSR). SPAD values were estimated using a combination of vegetation indices, vegetation indices and red-edge parameters as model factors, two types of machine learning (ML), a support vector machine (SVM), and a backward propagation neural network (BPNN), and partial least squares regression (PLSR) for four growth stages of winter wheat, and validated using independent samples. The results show that for the same data source, the best vegetation indices or red-edge parameters for estimating SPAD values differed at different growth stages and that combining vegetation indices with red-edge parameters gave better estimates than using only vegetation indices as an input factor for estimating SPAD values. There is no significant difference between PLSR, SVM, and BPNN methods in estimating SPAD values, with better stability of the estimated models using machine learning methods. Different growth stages have a large impact on winter wheat SPAD values estimates, with the accuracy of the four growth stage models increasing in the following order: booting < heading < filling < flowering. This study shows that using a combination of vegetation indices and red-edge parameters can improve SPAD values estimates compared to using vegetation indices alone. In the future, the choice of appropriate factors and methods will need to be considered when constructing models to estimate crop SPAD values. [ABSTRACT FROM AUTHOR]