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Family education relationship is a general term for all the relationships that occur around family education activities. The establishment of family education relationship plays an important role in the activity process and effect of family education and will have a profound impact on children's physical and mental development. The study of family education relationship is an important issue that cannot be ignored in the study of family education theory. In order to enhance the effectiveness of family education, it is an objective requirement of theory and practice to rationally analyze and optimize the contemporary family education relationship from the perspective of communication theory. The introduction of communication theory into the field of family education will help to change the actual situation of lack of communication and barrier in contemporary family education relationship and also provide a new idea and perspective for the research and solution of other related problems in family education. Starting from the research and discussion of the basic theory of the relationship between communication and family education, this paper analyzes the concept and characteristics of family education relationship in detail, analyzes and examines the family education relationship in history, and establishes a basic understanding of family education relationship. On the basis of the research of the relevant basic theories, the paper explores and analyzes the current situation and reasons of the lack of communication and the blocking of the contemporary family education relationship. From the perspective of communication, it investigates the contemporary family-educational relationship, clarifies that the basic structure of the family-educational relationship is the unity of the internal interpersonal organizational relationship structure, the psychological relationship structure, and the activity process structure, and examines the current situation of the basic structure one by one. This paper proposes that, with the development of the times and society, the contemporary family education relationship has a huge development compared with the historical family education relationship, reflecting the characteristics of the times such as democracy, but there is still a lack of communication and barriers. Then it analyzes the various concrete manifestations of the lack of communication and the blocking situation in the contemporary family education relationship and its adverse consequences to family education. This paper verifies the influence of computational thinking on the optimization mechanism of family education and demonstrates the feasibility and effectiveness of computational thinking in family education. This optimizes the family education mechanism from the perspective of computational thinking and provides a research case with reference value for follow-up research.

Coastal saltmarshes are key ecosystems with important ecological functions. Yet, they have experienced a widespread decline. Due to their importance, the conservation and restoration of saltmarshes are globally shared objectives, including China. Despite multiple local studies, nationwide information about saltmarshes in China is scarce. Thus, we used remote sensing to delineate the spatial distribution and areal extent of saltmarshes along coastal China and resolve their species composition. By interpreting 10 m spatial resolution Sentinel-2 images on Google Earth Engine, assisted with field survey and literature search, a total of 118 010 ha of saltmarshes were delineated in coastal China in 2019. Seven typical saltmarsh species were identified, with Phragmites australis, Spartina alterniflora, and Scirpus mariquater as dominant species, accounting for 95.5% of total saltmarsh extent, while Suaeda salsa, Tamarix chinensis, Cyperus malaccensis, and Sesuvium portulacastrum were present in limited abundance. The P. australis and exotic species S. alterniflora grow along almost all coastal provinces, but P. australis dominates in the north while S. alterniflora dominates in the middle part of coastal China. Suaeda salsa occurs mainly in the north and has suffered large losses. Tamarix chinensis is abundant in Shandong province, S. mariquater in the Yangtze River delta, C. malaccensis in Guangdong and Guangxi provinces, and S. portulacastrum in Taiwan. The exotic species S. alterniflora expanded extensively along the coast and its expansion rate continues to increase. The results provided conform a much-needed baseline for future monitoring efforts and the assessment of progress in the conservation and restoration projects toward recovering saltmarshes in China.

The remaining capacity of a battery is a crucial indicator, which has significant impact on State of Charge (SoC) estimation and the safe operations of electric vehicles. In this paper, an electrochemical model considering the electrolyte dynamics is proposed to estimate the real capacity of a lithium-ion battery. The electrochemical model with electrolyte dynamics governed by several partial differential equations has the potential to accurately describe varieties of phenomenons inside the battery. Furthermore, a Pade’ one-order approximation is adopted to obtain the transfer function between the boundary lithium-ion concentration and input current, then a boundary state estimator is proposed to estimate the the boundary lithium-ion concentration. After that, the least square method is used to obtain the adaptive update law for maximum concentration estimation in anode. Finally, the correctness of the aforementioned estimation methods is verified through simulation.

In this paper, we present a rapid boundary stabilization of a Timoshenko beam with anti-damping and anti-stiffness at the uncontrolled boundary, by using PDE backstepping. We introduce a transformation to map the Timoshenko beam states into a (2+2) x (2+2) hyperbolic PIDE-ODE system. Then backstepping is applied to obtain a control law guaranteeing closed-loop stability of the origin in the H^1 sense. Arbitrarily rapid stabilization can be achieved by adjusting control parameters. Finally, a numerical simulation shows that the proposed controller can rapidly stabilize the Timoshenko beam. This result extends a previous work which considered a slender Timoshenko beam with Kelvin-Voigt damping, allowing destabilizing boundary conditions at the uncontrolled boundary and attaining an arbitrarily rapid convergence rate., Comment: paper submitted to IEEE Transactions on Automatic Control

The past decade has witnessed tremendous achievements of ultrafast fiber laser technologies due to rapid developments of saturable absorbers (SAs) based on, in particular, nanomaterials such as 0D quantum dot, 1D carbon nanotubes, 2D layered materials, and 3D nanostructures. However, most of those nanomaterials-based SAs are inevitably absence of the high damage threshold and all-fiber integration, therefore challenging their applications on highly integrated and high-energy pulse generations. Recently, the real all-fiber SAs based on the nonlinear multimodal interference (NLMMI) technique using multimode fibers are demonstrated to overcome the above limitations. In this review, a detailed summary of the recent advances in NLMMI-based all-fiber SAs is provided, including the fundamental theory, implementation scenarios, and ultrafast fiber lasers of the all-fiber SAs, covering wide wavelength range of 1, 1.55, and 2 μm. In addition to the state-of-the-art overview, optical rogue waves in the all-fiber SA-based ultrafast fiber laser are extensively analyzed, which reveals the laser physics behind the dynamics from low-energy to high-energy pulses and directs the design of high-energy ultrafast fiber lasers. The conclusions and perspectives of the all-fiber SAs are also discussed at the end.

In order to investigate the relationship between production parameters and evaluation indexes for wood fiber production, a bi-directional prediction model was established to predict the fiber quality, energy consumption, and production parameters based on the improved particle swarm optimization and support vector machine (IPSO-SVM). SVM was applied to build the bi-directional prediction model, and IPSO was used to optimize the SVM parameters that affect the performance of prediction greatly. In the case of the forward prediction, the model can predict the fiber quality and energy consumption using the production parameters as input information; in the case of the backward prediction, the model can estimate production parameters using the fiber quality and energy consumption as evaluation indexes for input information. The results showed that the IPSO-SVM model had high accuracy and good generalization ability in the prediction for the wood fiber production. Additionally, based on the effectiveness of the proposed model and preset evaluation indexes, the corresponding production parameters were determined, which was able to save the wooden resources as well as reduce energy consumption in the fiberboard production.

Based on the cloud platform of Google Earth Engine (GEE), this study selected Landsat 5/8 and Sentinel-2 remote sensing images and used Support Vector Machine (SVM) classification method to classify the 35 years of intertidal salt marshes in China, and verified the classification results in combination with field survey. Finally, combining with various driving factors, the reasons and laws affecting the changes of salt marshes species and area were discussed and analyzed. The main results of the study are as follows:The main types of salt marshes plants in China include Phragmites australis, Spartina alterniflora, Suaeda salsa, Scirpus mariquete, Tamarix chinensis, Cyperus malaccensis and Sesuvium portulacastrum. The results salt marshes classification indicated that 166999.32 ha in 1985, 172893.87 ha in 1990, 174952.29 ha in 1995, 125567.51 ha in 2000, 93257.97 ha in 2005, 102539.04 ha in 2010, 96302.92 ha in 2015, and 115722.75 ha in 2019. The main driving factors of salt marsh change from 1985 to 2015 are reclamation, mudflat aquaculture, climate change, coastal zone erosion, invasion of alien species, and natural competition and succession among salt marshes species. The results can be used to quantitatively analyze the salt marshes carbon storage in space and time, and provide data support for the protection of salt marsh wetlands, the restoration of ecological functions and the implementation of "carbon neutral".

The COVID-19 has become a pandemic. The timing and nature of the COVID-19 pandemic response and control varied among the regions and from one country to the other, and their role in affecting the spread of the disease has been debated. The focus of this work is on the early phase of the disease when control measures can be most effective. We proposed a modified susceptible-exposed-infected-removed model (SEIR) model based on temporal moving windows to quantify COVID-19 transmission patterns and compare the temporal progress of disease spread in six representative regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). It was found that in the early phase of COVID-19 spread the disease follows a certain empirical law that is common in all regions considered. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries. Measure-dependent transmission rates followed a modified normal distribution (empirical law) in the three Chinese regions. These rates responded quickly to the launch of the 1st-level Response to Major Public Health Emergency in each region, peaking after 1–2 days, reaching their inflection points after 10–19 days, and dropping to zero after 11–18 days since the 1st-level response was launched. By March 29th, the mortality rates were 0.08% (Zhejiang), 0.54% (Guangdong) and 3.95% (Xinjiang). Subsequent modeling simulations were based on the working assumption that similar infection transmission control measures were taken in South Korea as in Zhejiang on February 25th, in Italy as in Guangdong on February 25th, and in Iran as in Xinjiang on March 8th. The results showed that by June 15th the accumulated infection cases could have been reduced by 32.49% (South Korea), 98.16% (Italy) and 85.73% (Iran). The surface air temperature showed stronger association with transmission rate of COVID-19 than surface relative humidity. On the basis of these findings, disease control measures were shown to be particularly effective in flattening and shrinking the COVID-10 case curve, which could effectively reduce the severity of the disease and mitigate medical burden. The proposed empirical law and the SEIR-temporal moving window model can also be used to study infectious disease outbreaks worldwide., Graphical abstract Unlabelled Image, Highlights • SEIR model can simulate the transmission spread of COVID-19. • Transmission rate followed a modified normal distribution in three regions of China. • Following strict measures, transmission rate reduced to 0 after 11-18 days. • Effective measures can flatten and shrink the curve of COVID-19 cases. • Temperature showed stronger association with COVID-19 than humidity.

BackgroundThe outbreak of Coronavirus 2019 (COVID-19) began in January 2020 in the city of Wuhan (Hubei province, China). It took about 2 months for China to get this infectious disease under control in its epicenter at Wuhan. Since February 2020, COVID-19 has been spreading around the world, becoming widespread in a number of countries. The timing and nature of government actions in response to the pandemic has varied from country to country, and their role in affecting the spread of the disease has been debated.MethodThe present study proposed a modified susceptible-exposed-infected-removed model (SEIR) model to perform a comparative analysis of the temporal progress of disease spread in six regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). For each region we developed detailed timelines of reported infections and outcomes, along with government- implemented measures to enforce social distancing. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries.ResultsThe main results of this study are as follows: (a) an empirical COVID-19 growth law provides an excellent fit to the disease data in all study regions and potentially could be of more general validity; (b) significant differences exist in the spread characteristics of the disease among the three regions of China and between the three regions of China and the three countries; (c) under the control measures implemented in the Chinese regions (including the immediate quarantine of infected patients and their close contacts, and considerable restrictions on social contacts), the transmission rate of COVID-19 followed a modified normal distribution function, and it reached its peak after 1 to 2 days and then was reduced to zero 11, 11 and 18 days after a 1st-Level Response to Major Public Health Emergency was declared in Zhejiang, Guangdong and Xinjiang, respectively; moreover, the epidemic control times in Zhejiang, Guangdong and Xinjiang showed that the epidemic reached an “inflection point” after 9, 12 and 17 days, respectively, after a 1st-Level Response was issued; (d) an empirical COVID-19 law provided an excellent fit to the disease data in the six study regions, and the law can be potentially of more general validity; and (e) the curves of infected cases in South Korea, Italy and Iran would had been significantly flattened and shrunken at a relatively earlier stage of the epidemic if similar preventive measures as in the Chinese regions had been also taken in the above three countries on February 25th, February 25th and March 8th, respectively: the simulated maximum number of infected individuals in South Korea, Italy and Iran would had been 4480 cases (March 9th, 2020), 2335 cases (March 10th) and 6969 cases (March 20th), instead of the actual (reported) numbers of 7212 cases (March 9th), 8514 cases (March 10th, 2020) and 11466 cases (March 20th), respectively; moreover, up to March 29th, the simulated reduction in the accumulated number of infected cases would be 1585 for South Korea, 93490 for Italy and 23213 for Iran, respectively, accounting for 16.41% (South Korea), 95.70% (Italy) and 60.59% (Iran) of the accumulated number of actual reported infected cases.ConclusionsThe implemented measures in China were very effective for controlling the spread of COVID-19. These measures should be taken as early as possible, including the early identification of all infection sources and eliminating transmission pathways. Subsequently, the number of infected cases can be controlled at a low level, and existing medical resources could be sufficient for maintaining higher cure rates and lower mortality rate compared to the current situations in these countries. The proposed model can account for these prevention and control measures by properly adjusting its parameters, it computes the corresponding variations in disease transmission rate during the outbreak period, and it can provide valuable information for public health decision- making purposes.

State of Charge (SoC) is essential in a smart Battery Management System (BMS). Traditional SoC estimation methods consider the lithium battery cell as an isothermal body simplistically, which is not accurate. Due to the heat conduction and convection, the temperature distribution along the radius is nonuniform, which means the battery model parameters subject to temperature are not identical radially. This paper proposed a modified electrochemical-distributed thermal coupled model (MEDTM) for improving the accuracy of SoC estimation. The distributed thermal model is employed to design a robust H-infinity temperature observer for the estimation of the radial temperature distribution of battery cell, where a radial discretized method is used for the realization of the observer design. Based on the observed temperature, a SoC observer is developed with the backstepping method. Finally, experiments and simulation are implemented. The two constant discharging experiments indicate that MEDTM is more accurate than the single particle model with surface temperature (SPMST), and it can generate reliable temperature prediction. A comparative simulation and a constant discharging experiment verify the H-infinity temperature observer can obtain a more accurate estimation of the battery cell’s temperature than the luenberger observer, and the H-infinity temperature observer has an estimation error of 0.3 K below. Then, through a constant discharging experiment and a simulation with UDDS current, the proposed SoC observer is verified to accurately estimate the SoC by comparing with the true SoC, where the estimated error of SoC under the two cases is below 1.5% and below 0.4%, respectively. Therefore, the proposed SoC observer also has good performance.

Fiber quality greatly influences the performance of medium-density fiberboard (MDF). To evaluate the fiber quality more accurately during refining, a novel quantitative parameter-property relationship model was developed based on the support vector machine (SVM) algorithm. Based on the mill production conditions, a total data set of 1173 experimental fiber quality data points under a wide range of five refining parameters was employed to train and verify the model. By comparing the effectiveness between the model using nonlinear SVM and the model based on multiple linear regression (MLR), the values of mean absolute error (MAE), mean relative error (MRE), root mean square error (RMSE), and Theil’s inequality coefficient (TIC) were reduced 92.19%, 92.36%, 87.29%, and 87.21%, respectively. The results showed that the performance of the predictive model developed using SVM was superior to the MLR model. Furthermore, the variations of the percentage of qualified fibers with each production parameter were predicted using the established model. The prediction model that resulted can be applied to predict the fiber quality during the refining process in an MDF production mill.

Refining is a critical step in the manufacturing of medium-density fiberboard (MDF). To ensure fiber quality and control of the energy consumption during refining, proper production parameters, such as feeding screw revolution speed (SR), accumulated chip height (CH), opening ratio of the discharge valve (OV), and content of Chinese poplar (CP), are vital. These parameters were monitored and recorded in an MDF mill to investigate the relationships between the parameters and the fiber quality and energy consumption. In this study, fuzzy models of the fiber quality and the energy consumption during refining were established based on subtractive clustering and an adaptive neuro-fuzzy inference system (ANFIS). The fiber quality and energy consumption models demonstrated high prediction accuracy because their predictive mean relative errors were as low as 4.14% and 6.72%, respectively. The errors of fiber quality were optimized using the simulated annealing method, and the input parameters were obtained. Based on the energy consumption model, the minimum energy consumption was 41.51 kWh/t, on the premise of the minimum requirement of fiber quality. This study can be a guideline for MDF production management to improve fiberboard quality and reduce energy consumption.

BACKGROUND Isokinetic muscle strength training is presently the most advanced method of muscle strength training. However, the existing control schemes of the training equipment are usually limited to the structure of the brake. OBJECTIVE In order to solve this problem, this paper presents a solution to an isokinetic system based on the force control of a DC servomotor. METHODS A new fuzzy impedance nonlinear controller is designed by analyzing the relevant requirements of isokinetic motion. A series of force tracking comparison experiments between a fuzzy PI controller and a classical PI controller are studied. In addition, some strength training experiments employing different driving forces and target speeds are also conducted. RESULTS The results demonstrate the effectiveness of this fuzzy impedance force tracking control strategy. CONCLUSION Using the aforementioned methods, a comprehensive motion algorithm was designed.

We demonstrate a passively mode-locked all-fiber laser incorporating a piece of graded-index multimode fiber as a mode-locking modulator based on a nonlinear multimodal interference technique, which generates two types of coexisting high-energy ultrashort pulses [i.e., the conventional soliton (CS) and the stretched pulse (SP)]. The CS with pulse energy as high as 0.38 nJ is obtained at the pump level of 130 mW. When the pump increases to 175 mW, the high-energy SP occurs at a suitable nonlinear phase bias and its pulse energy can reach 4 nJ at a 610 mW pump. The pulse durations of the generated CS and SP are 2.3 ps and 387 fs, respectively. The theory of nonlinear fiber optics, single-shot spectral measurement by the dispersive Fourier-transform technique, and simulation methods based on the Ginzburg–Landau equation are provided to characterize the laser physics and reveal the underlying principles of the generated CS and SP. A rogue wave, observed between the CS and SP regions, mirrors the laser physics behind the dynamics of generating a high-energy SP from a CS. The proposed all-fiber laser is versatile, cost-effective and easy to integrate, which provides a promising solution for high-energy pulse generation.

We experimentally demonstrate that indium selenide (In2Se3), a III−VI group layered chalcogenide compound, can be used as a saturable absorber (SA) for a wavelength-switchable vector-soliton fiber laser. The modulation depth of the In2Se3-based SA (In2Se3-SA), fabricated by incorporating In2Se3 nanosheets with polyvinyl alcohol, is up to 14%. By inserting the In2Se3-SA into fiber laser, solitons switched at wavelengths of ~1558 and ~1530 nm, with the duration of ~1.88 and ~1.76 ps respectively, can be obtained by adjusting the polarization controller and the pump power. Further investigations demonstrate that the achieved solitons are polarization-locked vector conventional solitons, which reveals that the In2Se3 can serves as a polarization-independent SA. The results indicate that the III−VI group chalcogenide compounds, including In2Se3, could be developed as an alternative for ultrafast pulse generations, particularly, vector-soliton pulse.

This paper presents a novel simple method to identify and remove systematic interference in battery powered physiological monitoring devices. This interference is very typically introduced via fluctuations in the power supply voltage, caused by the nonideal output resistance of small batteries, when a transceiver chip changes operating modes. The proposed method is designed to have low computational complexity in order to potentially allow for low cost, real-time implementations on low-power-based platforms, either in the system front or back end. Additionally, the paper provides guidelines on how to choose some of the operating conditions of the transceiver in order to minimize the effect of the interference through the application of the proposed method. Overall, successful performance is illustrated with experimental results obtained from an acoustic monitoring system, since this is considered to have specifications which are representative of most physiological monitoring devices.

Taking advantage of the dispersive Fourier transformation technique, the decaying evolution processes of double-pulse mode-locking in a single-walled carbon-nanotube-based Er-doped fiber laser are observed in detail for the first time to our knowledge. The decaying dynamics of the double-pulse mode-locking state is analyzed in the spectral and temporal domains. We reveal that the two pulses in one cluster disappear either simultaneously or one by one during the decaying processes of double-pulse mode-locking states. In addition, the spectral evolution patterns of the special double-pulse states (i.e., bound states) are extremely distinct at different decline rates of the pump power.

Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds – S1 and S2 – that can be used to determine the heart rate. The conventional method of acoustic signal acquisition involves placing the sound sensor at the chest where this sound is most audible. Presented is a novel algorithm for the detection of S1 and S2 heart sounds and the use of them to extract the heart rate from signals acquired by a small sensor placed at the neck. This algorithm achieves an accuracy of 90.73 and 90.69%, with respect to heart rate value provided by two commercial devices, evaluated on more than 38 h of data acquired from ten different subjects during sleep in a pilot clinical study. This is the largest dataset for acoustic heart sound classification and heart rate extraction in the literature to date. The algorithm in this study used signals from a sensor designed to monitor breathing. This shows that the same sensor and signal can be used to monitor both breathing and heart rate, making it highly useful for long-term wearable vital signs monitoring.

The paper reviews the modification and shaping of electron beam irradiation on carbon nanotubes (CNTs), as well as how this could be potentially useful for electron beam modification of nanotubes. The influence of irradiation on the mechanical property, electrical property and field effect of CNTs is discussed. Several examples are given with particular emphasis on the cutting, shaping and welding of CNTs by the electron beam in an electron microscope. It is shown that the change of incident electron energy and ambient temperature will lead to the different irradiation results. It is expected that electron irradiation studies will continue to play an important role in the research on CNTs.

Nanofibers of Fe3+, La3+ co-doped titanium dioxide (TiO2)/Polyvinyl acetate (PVAc) composite have been prepared by electrospinning process. The ceramic nanofibers co-doped with metal ions were obtained by high temperature calcination of the organic/inorganic composite fibers. The structure, crystalline state and surface morphologies were characterized by scanning electron microscopy (SEM), X-ray Diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and atomic force microscope (AFM), respectively. The observation by SEM revealed that there was a significant difference in the fibrous structure of the nanofibers before and after co-doping and calcinating. XRD patterns indicated the lattice of TiO2 nanocrystalline were distorted by co-doped ions. FTIR spectrum further confirmed the presence of Fe and La oxidate in the co-doped nanofibers. AFM images showed that comparing to TiO2 nanofibers, the roughness was increased on the surface of co-doped nanofibers. Before and after doping, the photocatalysis activity of the nanofibers were analyzed using ultraviolet-visible spectrophotometer (UV-Vis). The photocatalysis activity were significantly improved by the porous roughness surface structure and cooperative actions of Fe3+, La3+ co-doping.