Effects of composite scale on high temperature oxidation resistance of Fe-Cr-Ni heat resistant alloy

Fe-Cr-Ni heat resistant alloys with aluminum and silicon addition, alone and in combination, were melted using an intermediate frequency induction furnace with a non-oxidation method. By the oxidation weight gain method, the oxidation resistances of the test alloys were determined at 1,200 ìC for 500 hours. According to the oxidation weight gains, the oxidation kinetic curves were plotted and the functions were regressed by the least squares method. The results show that the oxidation kinetic curves follow the power function of y = axb (a>0, 0<b<1). The effects of scale compositions on oxidation resistance were studied further by analyses using X-ray diffraction (XRD) and scanning electron microscope (SEM). It is found that the composite scale compounds of Cr2O3, メ-Al2O3, SiO2 and FeCr2O4, with compact structure and tiny grains, shows complete oxidation resistance at 1,200 ìC. When the composite scale lacks メ-Al2O3 or SiO2, it becomes weak in oxidation resistance with a loose structure. By the criterion of standard Gibbs formation free energy, the model of the nucleation and growth of the composite scale is established. The forming of the composite scale is the result of the competition of being oxidized and reduced between aluminum, silicon and the matrix metal elements of iron, chromium and nickel. The protection of the composite scale is analyzed essentially by electrical conductivity and strength properties

Dissociation of Motor Task-Induced Cortical Excitability and Pain Perception Changes in Healthy Volunteers

Background: There is evidence that interventions aiming at modulation of the motor cortex activity lead to pain reduction. In order to understand further the role of the motor cortex on pain modulation, we aimed to compare the behavioral (pressure pain threshold) and neurophysiological effects (transcranial magnetic stimulation (TMS) induced cortical excitability) across three different motor tasks. Methodology/Principal Findings Fifteen healthy male subjects were enrolled in this randomized, controlled, blinded, cross-over designed study. Three different tasks were tested including motor learning with and without visual feedback, and simple hand movements. Cortical excitability was assessed using single and paired-pulse TMS measures such as resting motor threshold (RMT), motor-evoked potential (MEP), intracortical facilitation (ICF), short intracortical inhibition (SICI), and cortical silent period (CSP). All tasks showed significant reduction in pain perception represented by an increase in pressure pain threshold compared to the control condition (untrained hand). ANOVA indicated a difference among the three tasks regarding motor cortex excitability change. There was a significant increase in motor cortex excitability (as indexed by MEP increase and CSP shortening) for the simple hand movements. Conclusions/Significance: Although different motor tasks involving motor learning with and without visual feedback and simple hand movements appear to change pain perception similarly, it is likely that the neural mechanisms might not be the same as evidenced by differential effects in motor cortex excitability induced by these tasks. In addition, TMS-indexed motor excitability measures are not likely good markers to index the effects of motor-based tasks on pain perception in healthy subjects as other neural networks besides primary motor cortex might be involved with pain modulation during motor training

Fault diagnosis method for mine hoisting motor based on VMD and CNN-BiLSTM

The traditional motor fault diagnosis method based on the audio signal is insufficient to obtain the feature information of the motor audio signal and the fault diagnosis precision is not high. In order to solve the above problems, a mine motor fault diagnosis method based on optimized variational mode decomposition (VMD) and convolutional neural network CNN bidirectional long short-term memory (BiLSTM) is proposed. The whale algorithm (WOA) optimized VMD is used to decompose the motor audio signal to address the issues of modal aliasing and endpoint effects. The motor audio signal is decomposed into K intrinsic mode functions (IMF). After Pearson correlation coefficient screening, the 13-dimensional static MFCC feature parameters of the main IMF component are extracted. In order to obtain the dynamic features of the signal, the first and second-order difference coefficients of the 13-dimensional static MFCC are extracted to form a 39-dimensional feature vector. By combining dynamic and static features, the performance of fault diagnosis can be improved. In order to improve the precision of fault diagnosis, a BiLSTM layer is introduced into the CNN. The CNN extracts local features of the audio signal in the spatial dimension. The BiLSTM preserves bidirectional time series information of the audio signal in the temporal dimension. It captures long-distance dependencies of the audio signal, thereby maximizing the preservation of global and local features. The experimental results show the following points. ① Each IMF component of VMD decomposition has an independent center frequency and uniform distribution, and exhibits sparsity in the frequency domain. It can effectively avoid modal aliasing problems. In IMF solving, VMD decomposition avoids endpoint effects in empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) through mirror extension. ② The fault diagnosis accuracy based on 13-dimensional static MFCC features is 97.5%. The fault diagnosis accuracy based on 39-dimensional dynamic and static MFCC features is 1.11% higher than that based on 13-dimensional static MFCC features. ③ The accuracy of the diagnostic model based on CNN-BiLSTM reaches 98.61%, which is 5.83%, 4.17%, and 3.89% higher than the current universal diagnostic models CNN, BiLSTM, and CNN-LSTM, respectively

Optical Frequency Comb Generation Based on Optoelectronic Oscillator and Fabry-Perot Phase Modulator

We propose and demonstrate an optical pulse generator using optoelectronic oscillator (OEO) and Fabry-Perot phase modulator (FP-PM). A complete theoretical analysis is developed, and the advantages of the proposed system are also discussed. The optical frequency comb (OFC) is generated with an OEO loop to create broadband comb mode with low noise. It is theoretically proved that OFC pulses with a spectrum of 33 flat comb lines can be generated using an FP-PM. 25 GHz optical pulses with full-width-at-half-maximum (FWHM) less than 4 ps, signal-to-noise ratio (SNR) better than 40 dB. By changing the length of the fiber in OEO, the timing jitter is 100 fs in this system. The phase noise of the 25 GHz signal is &#x2212;107.8 dBc&#x002F;Hz at 10 kHz offset, which is measured when the fiber length is 230 m. The system is promising to attain high-quality electrical-optical (EO) comb with low timing jitter

Tunable terahertz all-dielectric linear-to-circular polarization conversion metasurface

Terahertz (THz) linear-to-circular (LTC) polarization conversion plays a crucial role in imaging and 6G wireless communication. This paper will give an account of a thermally tunable THz LTC polarization converter by using the active all-dielectric metasurface. It consists of zirconium oxide (ZrO2) microsphere resonators, active strontium titanate (STO) cladding, and flexible polyimide substrate. Through numerical simulation, the amplitude of the ellipticity of the proposed polarization converter at 0.265 THz is –1, indicating that perfect right-hand circular polarization (RHCP) wave is achieved. Meanwhile, the amplitude of the ellipticity is less than –0.8 between 0.247 and 0.278 THz (relative bandwidth is 12%). In addition, with the temperature changes of 180 K (from 200 to 380 K), the operating frequency of the converter can be tuned from 0.220 to 0.291 THz, a sensitivity about 39 GHz/100 K is achieved. Besides, the modulation depth of the ellipticity amplitude can achieve 92% at 0.220 THz, which demonstrates that the converter can output terahertz wave with different polarization states, and the device can be fabricated on a large scale. These perfect conversion performances show that the converter has potential applications in high-speed communication and imaging

A Perspective on the Impact of Grassland Degradation on Ecosystem Services for the Purpose of Sustainable Management

Grassland degradation seriously threatens the ability of grassland to provide ecosystem services. Grassland ecological restoration and sustainable management decision making depends on an accurate understanding of the impacts of grassland degradation on ecosystem services. Based on the assessment of grassland degradation and four key ecosystem services, including the net primary production (NPP), ecosystem carbon pool (EC), soil conservation (SC), and soil loss by wind (SL), the impacts of grassland degradation on ecosystem services and their relationships were analyzed. The impacts of climate change and grazing pressure on the relationship between grassland degradation and ecosystem services were revealed. Based on the &ldquo;climate change and grazing pressure-grassland degradation-ecosystem services&rdquo; network, the study puts forward specific suggestions on grassland ecological restoration and sustainable management under the premise of fully balancing ecological restoration and stakeholder relationships. The results showed that grassland degradation had a significant impact on ecosystem services and their relationships, but it varied with the types of ecosystem services. Although the degraded grassland in the study area has been in a state of recovery and ecosystem services have been improving in the past 20 years, the degradation of grassland in some areas has intensified, and there are still ecological risks, so it is necessary to continue to carry out ecological restoration work. On this basis, taking the local conditions into consideration, grassland ecological restoration and sustainable management policy suggestions were proposed. The study can provide a scientific reference for ecological protection and sustainable development in arid and semi-arid areas, and help to improve human well-being

A Perspective on the Impact of Grassland Degradation on Ecosystem Services for the Purpose of Sustainable Management

Grassland degradation seriously threatens the ability of grassland to provide ecosystem services. Grassland ecological restoration and sustainable management decision making depends on an accurate understanding of the impacts of grassland degradation on ecosystem services. Based on the assessment of grassland degradation and four key ecosystem services, including the net primary production (NPP), ecosystem carbon pool (EC), soil conservation (SC), and soil loss by wind (SL), the impacts of grassland degradation on ecosystem services and their relationships were analyzed. The impacts of climate change and grazing pressure on the relationship between grassland degradation and ecosystem services were revealed. Based on the “climate change and grazing pressure-grassland degradation-ecosystem services” network, the study puts forward specific suggestions on grassland ecological restoration and sustainable management under the premise of fully balancing ecological restoration and stakeholder relationships. The results showed that grassland degradation had a significant impact on ecosystem services and their relationships, but it varied with the types of ecosystem services. Although the degraded grassland in the study area has been in a state of recovery and ecosystem services have been improving in the past 20 years, the degradation of grassland in some areas has intensified, and there are still ecological risks, so it is necessary to continue to carry out ecological restoration work. On this basis, taking the local conditions into consideration, grassland ecological restoration and sustainable management policy suggestions were proposed. The study can provide a scientific reference for ecological protection and sustainable development in arid and semi-arid areas, and help to improve human well-being

Analysis of the Spatiotemporal Variation of Landscape Patterns and Their Driving Factors in Inner Mongolia from 2000 to 2015

Understanding the spatiotemporal changes in landscape patterns and their driving factors in Inner Mongolia can benefit land use and ecological environment management in this region. This study used the county landscape index and multiple regression analysis to reveal the temporal and spatial evolutions of landscape patterns and their driving factors in Inner Mongolia from 2000 to 2015 with multitemporal land use data. The results showed that (1) grassland was the main landscape type in Inner Mongolia. Grassland and unused land decreased, and cropland expanded from 2000 to 2015. Grassland degradation has slowed since 2005. (2) At the class level, the dominance of grassland decreased, and the degree of landscape fragmentation of cropland, forestland, and grassland increased gradually. At the landscape level, the landscape shape was more complex, the landscape connectivity was worse, and the landscape diversity gradually enhanced. (3) This study revealed that climatic factors influenced the evolution of landscape patterns, and human activities were the key driving factors of landscape-level metrics. The results of this study provide scientific bases for land management strategies

Analysis of the Spatiotemporal Variation of Landscape Patterns and Their Driving Factors in Inner Mongolia from 2000 to 2015

Understanding the spatiotemporal changes in landscape patterns and their driving factors in Inner Mongolia can benefit land use and ecological environment management in this region. This study used the county landscape index and multiple regression analysis to reveal the temporal and spatial evolutions of landscape patterns and their driving factors in Inner Mongolia from 2000 to 2015 with multitemporal land use data. The results showed that (1) grassland was the main landscape type in Inner Mongolia. Grassland and unused land decreased, and cropland expanded from 2000 to 2015. Grassland degradation has slowed since 2005. (2) At the class level, the dominance of grassland decreased, and the degree of landscape fragmentation of cropland, forestland, and grassland increased gradually. At the landscape level, the landscape shape was more complex, the landscape connectivity was worse, and the landscape diversity gradually enhanced. (3) This study revealed that climatic factors influenced the evolution of landscape patterns, and human activities were the key driving factors of landscape-level metrics. The results of this study provide scientific bases for land management strategies