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High-strength advanced steel and welded structure are key for service safety and life. Static and dynamic compressive mechanical behavior of high-strength 22SiMn2TiB armor steel and welded structure is investigated, which are carried out by using universal testing machine and split Hopkinson pressure bar. The studied materials are obtained from high-strength steel matrix, welded seam and mix of them with interface, respectively. The strain rate in experiments covers the range of 0.001/s to 6000/s. The mechanical data involve stress-strain relations and strain rate dependencies of mechanical properties. The cracking behavior as well as the corresponding microstructures are characterized at different length scales from millimeter to micron scale by optical microscope and scanning electron microscope. The results show that static (0.001/s) and dynamic (5000/s) yield strengths are 1600 MPa and 2400 MPa for high-strength steel matrix, 400 MPa and 1200 MPa for welded seam, 950 MPa and 1600 MPa for mix of them with interface, respectively. Under dynamic loading, shearing occurs and results in the fracture. Along the interface of steel matrix and welded seam, cracks are firstly initiated and propagated. The relations of mechanical properties and fracture features are analyzed, where strain rate effect is mentioned. This work will guide the design and application for engineering structure.

Biodiversity loss will lead to a serious decline for ecosystem services, which will ultimately affect human well-being and survival. Monitoring the spatial and temporal dynamics of grassland biodiversity is essential for its conservation and sustainable development. This study integrated ground monitoring data, Landsat remote sensing, and environmental variables in the Three Rivers Headwater Region (TRHR) from 2000 to 2021. We established a reliable model for estimating grassland species diversity, analyzed the spatial and temporal patterns, trends of change, and the driving factors of changes in grassland species diversity over the past 22 years. Among models based on diverse variable selection and machine learning methods, the random forest (RF) combined stepwise regression (STEP) model was found to be the optimal model for estimating grassland species diversity in this study, which had an R2 of 0.44 and an RMSE of 2.56 n/m2 on the test set. The spatial distribution of species diversity showed a pattern of abundance in the southeast and scarcity in the northwest. Trend analysis revealed that species diversity was increasing in 80.46% of the area, whereas 16.59% of the area exhibited a decreasing trend. The analysis of driving factors indicated that the changes in species diversity were driven by both climate change and human activities over the past 22 years in the study area, of which temperature was the most significant driving factor. This study effectively monitors grassland species diversity on a large scale, thereby supporting biodiversity monitoring and grassland resource management.

Achieving ecological conservation and governance based on ecosystem services (ESs) can balance regional ecological protection and development, which is of great significance for sustainable development. Existing research has mainly focused on the extraction of priority ecological conservation areas, thereby neglecting to consider the classification and management of ecological engineering areas. To improve regional ecological governance, we combine ESs and dust movement trajectory, using the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) as the research object to generate watersheds’ ecological governance zones. Six ESs were assessed to determine ecological zones. Trajectory simulation of dust movement, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function, was used to determined zones affected by dust. By combining these two aspects, five main ecological governance clusters were identified. We found that: (1) the area with low ESs in the northwest of the BTSSCP suffered from severe dust impacts; (2) slight dust-affected zones were mainly distributed in the eastern of the BTSSCP, and in the area, ESs gradually decreased from south to north; (3) ESs in the region was primarily influenced by natural factors and the influencing factors of ESs vary among different zones. These findings will not only contribute to the overall planning and governance of the BTSSCP, but can offer general guidance for the formulation of targeted ecological protection and restoration measures in other areas.

The accurate estimation of the aboveground biomass (AGB) is crucial for the sustainable utilization and management of grassland resources. Spatio-temporal inconsistencies between field samples and satellite images are major source of error in the estimation of grassland AGB. To solve this problem, this study selected the Three Rivers Headwater Region as the study area and proposed a selection strategy for base-period images of spatio-temporal fusion that was suitable for use at a large spatial scale in which cloud-free images are difficult to obtain. The spatial and temporal adaptive reflectance fusion model (STARFM) based on the selection strategy was used to generate a synthetic Normalized Difference Vegetation Index (NDVI) dataset with high spatial-temporal resolution by using the maximum value composite of GF-1 NDVI and MODIS NDVI to enhance the spatial-temporal quality of the images for field-scale application. Three estimation models for grassland AGB were then constructed by the random forest algorithm using synthetic NDVI, MODIS NDVI, GF-1 NDVI respectively, together with ancillary data. Following this, the estimation model with the highest accuracy was used to generate a 16-m eight-day time-series AGB in the growing season. The results showed: (1) The synthetic NDVI was correlated closely with the observed GF-1 NDVI, with an average R of 0.825 and a RMSE of 0.087. The temporal trend of the synthetic NDVI for each grassland type was highly consistent with that of the MODIS NDVI in the growing season with a correlation higher than 0.9. (2) The synthetic NDVI reduced the spatial difference between field samples and images to 16-fold, and the temporal difference was controlled to within four days under ideal conditions. (3) The synthetic NDVI improved the estimation accuracy of grassland AGB by about 15.9% and 19.7% (R2), and 13.7% and 17.5% (RMSE) relative to MODIS NDVI and GF-1 NDVI, respectively. (4) The time-series AGB revealed accurately the spatial distribution of and seasonal temporal variations in the grassland biomass. The results of this study may serve as scientific guidance for timely monitoring of grassland conditions and precise management of grassland resources in China.

Objective: Osteoporosis is the most common skeletal disease in humans. Early onset of osteoporosis is usually asymptomatic, so early diagnosis is critical. The purpose of this study was to analyze the value of MRI-based VBQ scores for evaluating osteoporosis. Methods: We searched PubMed, Embase, the Cochrane Library databases, Web of Science, and some Chinese electronic databases for published articles and the ClinicalTrials.gov site for completed but unpublished studies on evaluating the value of MRI-based VBQ scores for evaluating osteoporosis. We calculated the summarized sensitivity, specificity, the ROC curve (AUC) values and their 95% confidence intervals (CIs) using MetaDiSc 1.4 software and STATA. Results: Our study included 8 studies involving 999 patients of which 660 patients were diagnosed with osteopenia/osteoporosis, and 339 patients were identified as having normal BMD. The pooled sensitivity was 0.809 (95% CI, 0.777–0.838, I2 = 78.8%), the pooled specificity was 0.640 (95% CI, 0.587–0.691, I2 = 85.9%), and the pooled AUC was 0.8375. Conclusion: MRI-based VBQ scores provided high sensitivity and moderate specificity in detecting osteoporosis. Opportunistic use of VBQ scores could be considered, e.g. before lumbar spine surgery. Prospero registration number: CRD42022377024.

Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopment disease characterized by impaired social and cognitive abilities. Despite its prevalence, reliable biomarkers for identifying individuals with ASD are lacking. Recent studies have suggested that alterations in the functional connectivity of the brain in ASD patients could serve as potential indicators. However, previous research focused on static functional-connectivity analysis, neglecting temporal dynamics and spatial interactions. To address this gap, our study integrated dynamic functional connectivity, local graph-theory indicators, and a feature-selection and ranking approach to identify biomarkers for ASD diagnosis. Methods: The demographic information, as well as resting and sleeping electroencephalography (EEG) data, were collected from 20 ASD patients and 25 controls. EEG data were pre-processed and segmented into five sub-bands (Delta, Theta, Alpha-1, Alpha-2, and Beta). Functional-connection matrices were created by calculating coherence, and static-node-strength indicators were determined for each channel. A sliding-window approach, with varying widths and moving steps, was used to scan the EEG series; dynamic local graph-theory indicators were computed, including mean, standard deviation, median, inter-quartile range, kurtosis, and skewness of the node strength. This resulted in 95 features (5 sub-bands × 19 channels) for each indicator. A support-vector-machine recurrence-feature-elimination method was used to identify the most discriminative feature subset. Results: The dynamic graph-theory indicators with a 3-s window width and 50% moving step achieved the highest classification performance, with an average accuracy of 95.2%. Notably, mean, median, and inter-quartile-range indicators in this condition reached 100% accuracy, with the least number of selected features. The distribution of selected features showed a preference for the frontal region and the Beta sub-band. Conclusions: A window width of 3 s and a 50% moving step emerged as optimal parameters for dynamic graph-theory analysis. Anomalies in dynamic local graph-theory indicators in the frontal lobe and Beta sub-band may serve as valuable biomarkers for diagnosing autism spectrum disorders.

In 1971, scientists from Mahidol University in Thailand and the Smithsonian Institution in the USA formed a research team to study a new species of Schistosoma in the Mekong River in Thailand and Laos. The studies, completed during 1971-1973, prior to the construction of any dams or restrictions to the natural flow regime of the Mekong River, provide a unique description of the natural ecological state of the river that can serve as a baseline for current research. The natural transmission of Schistosoma japonicum, Mekong Strain, was first reported on Khong Island, Laos in 1973 using sentinel mice. The first detailed description of the habitat ecology of the snail vector Neotricula aperta was done on-site in 1971 simultaneously with that research and is unique in providing the only description of the river shoreline habitat before any dams were built and any alteration of the natural flow regime was in place. Aggregating current information in a Place-Based Conceptual Model (PBCM) as an organizing template, along with current habitat models that combine ecological data with e-flows, can be developed and used as a tool to predict suitable habitats for snails. The natural flow regime of the Mekong River prior to any impoundments is described with current updates on the potential impacts of climate change and dams with flow-related snail habitat characteristics, including sediment drift and water quality. The application of the PBCM to describe and compare descriptive information on current and potential future N. aperta/S. mekongi habitat is discussed.

Background: The purpose of motivating students is to enhance their learning achievement. The expectancy-value theory (EVT) has demonstrated its efficacy in motivating students in classrooms and in gymnasia. Understanding student motivation in physical education is needed. This meta-analysis review aimed to reveal the determinants and functions of EVT by evaluating the evidence in physical education research. Methods: We followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines to identify and meta-analyze the current research literature published from January 2010 to December 2020 by generating and analyzing the effect sizes from the studies. Results: A total of 31 studies were included. The results show that social support, motivation of teachers and peers, and positive class climate can predict student EVT motivation. EVT motivation predicts student learning behaviors, situational interests, fitness performance, health behavior function, out-of-school physical activity, and physical skill development. Conclusion: EVT motivation could facilitate learning behaviors and situational interest development in the gymnasium. It might lead to fitness enhancement, health behavior change, out-of-school physical activity participation, and physical skill development. Fostering a learning environment with a mastery-centered and/or student autonomy approach where students perceived success and the task values can enhance and maximize student EVT motivation and learning achievement.

Alpine grasslands are important ecosystems on the Qinghai–Tibet Plateau and are extremely sensitive to climate change. However, the spatial responses of plant species diversity and biomass in alpine grasslands to environmental factors under the background of global climate change have not been thoroughly characterized. In this study, a random forest model was constructed using grassland ground monitoring data with satellite remote sensing data and environmental variables to characterize the plant species diversity and aboveground biomass of grasslands in the Three-River Headwaters Region within the Qinghai–Tibet Plateau and analyze spatial variation in the relationship between the plant species diversity and aboveground biomass and their driving factors. The results show that (1) the selection of characteristic variables can effectively improve the accuracy of random forest models. The stepwise regression variable selection method was the most effective approach, with an R2 of 0.60 for the plant species diversity prediction model and 0.55 for the aboveground biomass prediction model, (2) The spatial distribution patterns of the plant species diversity and aboveground biomass in the study area were similar, they were both high in the southeast and low in the northwest and gradually decreased from east to west. The relationship between the plant species diversity and aboveground biomass varied spatially, they were mostly positively correlated (67.63%), but they were negatively correlated in areas with low and high values of plant species diversity and aboveground biomass, and (3) Analysis with geodetector revealed that longitude, average annual precipitation, and elevation were the main factors driving variation in the plant species diversity and aboveground biomass relationship. We characterized plant species diversity and aboveground biomass, as well as their spatial relationships, over a large spatial scale. Our data will aid biodiversity monitoring and grassland conservation management, as well as future studies aimed at clarifying the relationship between biodiversity and ecosystem functions.

The nuclear receptors HR3 and FTZ-F1 are highly conserved and function to regulate molting and reproduction in both hemimetabolous and holometabolous insects. However, their roles in Nilaparvata lugens are largely unknown. In the present study, we discover that NlHR3 and NlFTZ-F1 are activated in the nymph stages by ecdysone signaling. Transcription disruption of NlHR3 and NlFTZ-F1 expression prevents nymph ecdysis and metamorphosis, which leads to abnormal appearance, malformed ovaries, and lethal phenotypes. In addition, we demonstrate that NlHR3 and NlFTZ-F1 regulate molting and reproduction by interacting with the intrinsic 20E and JH signaling pathways. Our work offers a deep insight into the action mechanisms of HR3 and FTZ-F1 in insects. Moreover, NlHR3 and NlFTZ-F1 could properly be exploited as potential target genes for developing RNAi-based pesticides to control N. lugens.

Purpose: This study aimed to describe the national prevalence of Chinese children and adolescents who met the World Health Organization muscle-strengthening exercise (MSE) recommendations and identify correlates of meeting the MSE recommendations. Methods: Cross-sectional data from the 2019 Physical Activity and Fitness in China—The Youth Study, a nationally representative sample of Chinese children and adolescents (n = 80,413; mean age = 13.7 years; 53.9% girls) and their parents, were analyzed. Children and adolescents who reported engaging ≥3 days (up to 7 days) of MSE per week were classified as meeting the MSE recommendations. MSE, demographics, lifestyle behaviors (sport participation, moderate-to-vigorous physical activity, screen time, and sleep duration), exercise intention, peer and parental support, and parental MSE participation were assessed through self-reports. Logistic regression models were used to determine the correlates of meeting the MSE recommendations. The analyses were completed in 2020. Results: Overall, 39.3% of children and adolescents met the MSE recommendations. Girls, 10th–12th graders, minorities, those from lower income households and those from families with lower parental education were less likely to meet the MSE recommendations. Children and adolescents who were proficient in ≥2 sports were more likely to meet the MSE recommendations (adjusted odds ratio (aOR) = 1.44, 95% confidence interval (95%CI): 1.26–1.65), as were those with more moderate-to-vigorous physical activity (aOR = 1.57, 95%CI: 1.53–1.61). Additionally, children and adolescents with high exercise intention (aOR = 1.60, 95%CI: 1.51–1.69), those whose parents met the adult MSE recommendations (aOR = 1.46, 95%CI: 1.40–1.52), and those who received high peer (aOR = 1.27, 95%CI: 1.20–1.34) and parental support (aOR = 1.07, 95%CI: 1.04–1.12) were more likely to meet the MSE recommendations. Conclusion: Less than two-fifths of Chinese children and adolescents met the World Health Organization MSE recommendations. The correlates identified in our study can help inform the development of school and community based strategies and policies to enhance participation in MSE and improve muscular fitness of all Chinese children and adolescents.

Abstract The dissipation and residue levels of thiacloprid, spirotetramat and its four metabolites residues in cowpeas were investigated under field conditions. The QuEChERS technique with high-performance liquid chromatography tandem mass spectrometry (HPLC–MS/MS) was used to detect thiacloprid, spirotetramat and its four metabolites residues content in cowpeas. The recoveries were 81.3–95.1% at a spike level of 0.005–0.5 mg/kg, the relative standard deviations (RSDs) were 2.1–9.5%. The dissipation kinetics data showed that thiacloprid and spirotetramat in cowpeas were degraded with the half-lives of 1.14–1.54 days and 1.25–2.79 days. The terminal residues of thiacloprid and spirotetramat were 0.0255–0.4570 mg kg−1 and 0.0314–0.3070 mg kg−1 after application 2 times with a pre-harvest interval (PHI) of 3 days under the designed dosages. The chronic and acute dietary exposure assessment risk quotient (RQ) values of thiacloprid in cowpeas for different consumers were 2.44–4.41% and 8.72–15.78%, respectively, and those of spirotetramat were 1.03–1.87% and 0.18–0.32%, respectively, all of the RQ values were lower than 100%. The dietary risk of thiacloprid through cowpeas to consumers was higher than spirotetramat. The results from this study are important reference for Chinese governments to develop criteria for the safe and rational use of thiacloprid and spirotetramat, setting maximum residue levels (MRLs), monitoring the quality safety of agricultural products and protecting consumer health.

Ultrasonic guided waves (UGWs) in water-filled pipes are subject to more severe dispersion and attenuation than vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called orthogonal matching pursuit based on dispersion and multi-mode (DMOMP) was proposed, which utilizes the second-order asymptotic solution of dispersion curves and the conversion characteristics of asymmetric UGWs in the defect contact stage to reconstruct the dispersive signals and converts the time-domain dispersive signals to distance-domain non-dispersive signals by dispersion compensated time-distance mapping. The synthesized simulation results indicate that DMOMP not only exhibits higher reconstruction accuracy compared to OMP, but also reveals more accurate and stable mode recognition and localization compared to DOMP, which only considers the dispersion under perturbation and noise. In addition, the UGW testing experimental results of water-filled pipes verify the effectiveness of DMOMP, the localization accuracies of three feature signals (defct 1, defct 2 and end echo) with DMOMP are 99.10%, 98.72% and 98.36%, respectively, and the average localization accuracy of DMOMP is as high as 98.73%.

The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems’ functionality. The Inner Mongolian grasslands stand out as one of the world’s most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future.

An innovative morphing scheme, i.e., dynamical chordwise retracting and stretching, has been proposed for flapping wings. Its aerodynamic effects have been investigated based on a plunging two-dimensional flat wing. The conclusive results suggest that the novel morphing scheme can help to enhance the power utilization efficiency of flapping wings in forward motions. Plunging wings equipped with the novel morphing scheme can generate more thrust for a given power consumption or consume less power for a given thrust generation compared with their non-morphing counterparts. Moreover, the morphing scheme tends to function more positively as the defined morphing amplitude increases. In the currently covered parameter spaces, the largest peak propulsive efficiency improvements induced by the morphing scheme are 12.3% at Re = 15 × 104 and 10.8% at Re = 5 × 104, respectively. Examination of the flow structures around the plunging wings reveals that dynamical chordwise retracting and stretching of the wing can ameliorate the vortex distribution, which could account for the propulsive property changes caused by the morphing scheme. The current study may have yielded an inspiring and prospective scheme for enhancing the propulsive capacity of micro-flapping-wing aerial and underwater robots.

Aquaponics is considered a new industrialized food production approach to meet the increasing needs of expanding urbanization. In this system, nutrient recovery from aquaculture sludge can achieve zero solid waste discharge and supplement nutrients to hydroponics system, which yield environmental and economic benefits. Anaerobic and aerobic mineralization are common approaches for the nutrient conversion of aquaculture sludge, but they are challenged by low-value products, nutrient loss, and large amounts of biomass by-products produced during the process. In this review paper, phototrophic bioconversion of aquaculture sludge by anoxygenic phototrophic bacteria (APB) is proposed to minimize carbon and nutrient dissipation, through which the resulting mineral nutrients can be taken up by plants and the assimilated protein-rich biomass can be utilized by aquaculture animals as food. Pre-treatment to solubilize aquaculture sludge is essential to obtain bioavailable substrates, because aquaculture sludge cannot be utilized by APB in the organic solid form. The characteristics of anaerobic and aerobic solubilization processes are discussed, and the performance of phototrophic bioconversion by APB under anaerobic and aerobic conditions is compared. A multi-loop aquaponic system with four ecological coupling models was developed for the recovery of APB-based nutrients. The symbiotic mechanism between the solubilization and phototrophic bioconversion process should be focused in the future.

This paper concerns the dynamic performance analysis of the vehicle ISD (inerter-spring-damper) suspension employing an eccentric inerter. Firstly, the quarter car model of the two basic vehicle suspension layouts involving an eccentric inerter, namely, the series-connected layout and the parallel-connected layout, is established. Then, by considering the overall performance such as the vehicle body acceleration, the suspension working space, and the dynamic tire load, the key parameters of the two suspensions are optimized by using the genetic algorithm. Simulation analysis results indicate that the series-connected vehicle ISD suspension is superior to the parallel-connected one, and all of the RMS values of the body acceleration, the suspension working space, and the dynamic tire load are decreased significantly by comparing to the conventional suspension, while the improvement of the parallel-connected vehicle ISD suspension is relatively poor. At last, the impact of the flywheel eccentricity and the screw pitch on the dynamic performance indices of the two suspensions is discussed, and the trade-offs among the three performances are analyzed, which will provide a guide method for the suspension design when considering the eccentric factor.

Grassland aboveground biomass (AGB) is an important indicator for studying the change in grassland ecological quality and carbon cycle. The rapid development of high-resolution remote sensing and unmanned aerial vehicles (UAV) provides a new opportunity for accurate estimation of grassland AGB on the plot scale. In this study, the mountain grassland was taken as the research object. Using UAV Light Detection and Ranging (LiDAR) data and multispectral satellite images, the influence of topographic correction methods on AGB estimation was compared and a series of LiDAR metrics and vegetation indices were extracted. On this basis, a comprehensive indicator, the vegetation index-height-intensity model (VHI), was proposed to estimate AGB quickly. The results show that: (1) Among the four topographic correction methods, the Teillet regression has the best effect, and can effectively improve the accuracy of AGB estimation in mountain grassland. The correlation between corrected ratio vegetation index and AGB was the highest (correlation coefficient: 0.682). (2) Among the height and intensity metrics, median height and max intensity yielded the higher accuracy in estimating AGB, with Root Mean Square Error (RMSE) of 322 g/m2 and 333 g/m2, respectively. (3) The VHI integrated spectrum and LiDAR information, and its accuracy for AGB estimation for mountain grassland, was obviously better than other indicators, with an RMSE of 272 g/m2. We also found that the accuracy of VHI in univariate models was comparable to that of complex multivariate models such as stepwise regression, support vector machine, and random forest. This study provides a new approach for estimating grassland AGB with multi-source data. As a simple and effective indicator, VHI has shown strong application potential for grassland AGB estimating in mountainous areas, and can be further applied to grassland carbon cycle research and fine management.

Pipeline systems are prone to defects due to the harsh service conditions, which may induce catastrophic failure if found not in time. Ultrasonic guided wave (UGW) testing provides a convenient option for pipeline detection, showing high-efficiency, non-contact, long-distance and large-scale capabilities. To address the problem that UGW signals suffer from poor signal resolution that is mainly related to the coherent noise caused by the dispersion, multi-mode and mode conversion, an advanced signal processing method called VWISSP, based on variational mode decomposition (VMD), wavelet transform (WT), and improved split spectrum processing (ISSP) was proposed, of which SSP was improved by replacing the Gaussian filter bank with cosine filters of constant frequency-to-bandwidth and frequency-to-filter spacing ratios. Compared with ISSP, VWISSP shows better higher accuracy and resolution processing effects to noisy multi-defect UGW signals, which is manifested through the improvement of both the signal-to-noise ratio gain and the defect-to-noise gain. Only feature signals (defects and pipe end) are retained, whereas noise signals are eliminated completely.

The northern sand-prevention belt (NSPB) is the key area for sand control in China, and the various ecological projects conducted there are important to the Chinese strategy for ecological security. In this paper, a new remote sensing-based desertification index (RSDI) based on principal component analysis was constructed from four aspects of vegetation greenness, surface moisture, soil grain size, and surface radiation. The overall evaluation accuracy of the index was 89.2%, and the kappa coefficient was 0.80, indicating high sensitivity to different degrees of aeolian desertification and suitability for multiscale research. The coefficient of variation, Mann–Kendall test, Theil–Sen median trend analysis, and residual analysis were used to analyze the spatiotemporal changes and driving forces of the RSDI in the NSPB from 2000 to 2020. The RSDI was used to compare aeolian desertification in different subregions, land use types, and ecological project areas. The important results are as follows: (1) the trend of the average RSDI was downward, but it increased significantly in 2008–2009 and 2013–2014; (2) the RSDI was characterized by relatively high volatility in 28.9% and moderate volatility in 27.1% of the area; (3) the areas with significant restoration (34.1%) greatly exceeded those with significant deterioration (6%), whereas 59.9% of the total area was stable; and (4) within the area with significant restoration, 57.4% was primarily affected by human activities, and 42.4% was primarily affected by climate change; however, most of the area with significant deterioration (71.1%) was affected by human activities. In general, the degree of aeolian desertification in the NSPB has decreased in the past 20 years and its ecological quality has continued to recover. However, unreasonable human activities still need to be reduced, and the ecological management of areas under serious threat of desertification needs to be strengthened.

Ultrasonic guided wave (UGW) nondestructive testing suffers from poor signal interpretation accuracy caused by the coherent noise that is related to dispersion, multi-mode and mode conversion. In order to split the L(0,2) UGW from the coherent noise, split-spectrum processing with raised cosine filters of constant frequency-to-bandwidth ratio (FBR-RC-SSP) is proposed. With the advantages of time domain resolution and frequency domain split, FBR-RC-SSP is studied based on time-frequency analysis using the chirplet transform, and the effects of filter parameters on signal-to-noise ratio gain (SNRG) and defect-to-coherent noise gain (DCRG) are explained. The excellent effects of eliminating the coherent noise and improving the signal resolution in FBR-RC-SSP are reported by the validation of synthesized, simulated and experimental UGW signals, of which the average SNRG and DCRG are 22.92% and 23.71% higher than those of traditional SSP using Gaussian filters, and it has the potential to locate and characterize defects in further UGW testing research.

Mass concentration is a commonly used but insufficient metric to evaluate the particulate matter (PM) exposure hazard. Recent studies have declared that small particles have more serious impacts on human health than big particles given the same mass concentration. However, state-of-the-art PM sensors cannot provide explicit information of the particle size for further analysis. In this work, we adopt Sauter mean diameter (SMD) as a key metric to reflect the particle size besides the mass concentration. To measure SMD, an effective optical sensing method and a proof-of-concept prototype sensor are proposed by using dual wavelengths technology. In the proposed method, a non-linear conversion model is developed to improve the SMD measurement accuracy for aerosol samples of different particle size distributions and reflective indices based on multiple scattering channels. In the experiment of Di-Ethyl-Hexyl-Sebacate (DEHS) aerosols, the outputs of our prototype sensor demonstrated a good agreement with existing laboratory reference instruments with maximum SMD measurement error down to 7.04%. Furthermore, the simplicity, feasibility and low-cost features of this new method present great potential for distributed PM monitoring, to support sophisticated human exposure hazard assessment.

The pore and throat structure of tight oil reservoir cores is complex, and the resistance of oil drop to discharge from the core is very high during dynamic imbibition. Surfactant has good ability in interfacial tension reduction and wettability reversal. It can reduce oil drop discharge resistance and enhance oil recovery effectively during dynamic imbibition in tight reservoirs. Here, we first analyzed the pore throat structure and mineral composition of tight core, and then the oil drop visualization instrument was used to study the discharge behavior of oil drop during dynamic imbibition. The oil drop discharge form was analyzed, and the influence of various factors on the oil drop discharge behavior was explored, and then the dynamic imbibition performance of surfactant in tight cores was obtained. The core throat diameter was mainly distributed in 0.07–1.1 μm, and the hydrophilic mineral content in core reached 50.8%. In the case of fluid flow in fracture, the oil drop discharge from near fracture matrix was faster, and its growth rate in height and width was faster than that without external fluid flow. Within a certain range, with the increase of IFT, the rate of core imbibition increased gradually. When the IFT increased from 0.32 mN/m to 0.59 mN/m, the oil drop rapture time decreased by 66.3%. The growth rate of oil drop discharged from the top and side of the core was faster than that from the bottom surface. Furthermore, it was easier to discharge. With the core thickness reduced by half, the rapture time of oil drop was reduced by 74.7%. For tight reservoirs, hydraulic fracturing can create more fracture surfaces and reduce the size of matrix blocks, which contributes to reduce the oil drop discharge resistance during imbibition and improve the oil recovery. This study provides a basis for surfactant to improve dynamic imbibition and oil production performance of tight sandstone oil reservoir.

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future.

The line between gender and sex has become increasingly muddled in literature. Tensions surrounding this topic are ever-increasing and definitions of the two are rarely consistent. For improving conceptual clarity, we adopted the Social Role Theory to explore how these two terms differ and relate by laying out a cyclical framework of biological, sociological, and psychological components. Herein, we discuss the origins of the binary sex construct, anatomical brain/cognition differences, and sex/gender role implications for education and physical education. We confront the topic in a content area that continues to be masculine-oriented with the purpose to conceptualize sex/gender in physical education research through clarifying the evolutionary biosocial spectrum. Offering a reconceptualization of gender as a multidimensional construct could inspire further curricular reform for the content to be more inclusive of all participants, learnable by all students regardless of sex and gender, and beneficial both mentally and physically to all learners.

Purpose: Cognitive load theory focuses on providing appropriate cognitive engagement to facilitate knowledge learning. The purpose of this study was to determine the contributions of cognitive load on high school students' in-class physical activity. Method: A stratified random sample of high school students (N = 150) who participated in a large curriculum intervention study provided the data. A path analysis and Hayes' PROCESS analysis were used to test a correlation model and moderation effect from gender and race. Results: The results showed that the reasoning learning tasks directly contributed to their in-class physical activity (path coefficient = 0.54, p < 0.01) and the gender and race factors were not significant moderators (p > 0.05). Conclusion: The findings imply that high cognitive load tasks can facilitate in-class physical activity. The findings suggest the power of the concept-based physical education curriculum in providing productive learning opportunities to all students.

Purpose: Guided by the model of domain learning theory, this study was intended to determine the extent to which integrating a 10-min physical activity (PA) break in elementary school mathematics lessons would enhance the learning of mathematics content. Methods: A sample of 22 intact classes from a random sample of eight schools in Taiwan were randomly assigned to an experimental condition with PA breaks (n = 11) and a control condition (n = 11) for 12 weeks. Students' (N = 420) mathematics knowledge was assessed using the standardized aptitude tests accompanying the curriculum, which encompassed five knowledge domains. Results: Analysis on class means showed that adding the PA breaks did not benefit mathematics learning, which lends support to the model of domain learning theory. Discussion/Conclusion: The findings seem to question the theoretical foundation for adding PA breaks to classroom-taught content, including mathematics. Although interdisciplinary or cross-disciplinary instruction and learning may be necessary to advance students' knowledge, including PA in classroom-taught subjects needs extensive research.

Comprehensive investigation of gut microbiota composition is important for understanding digestive physiology in mammals. The hog deer (Axis porcinus) is a small mammal at high risk of extinction in the wild. In the present study, we sequenced the V4 region of 16S rRNA gene and compared the gut microbiota composition among three ages of captive hog deer, including one infant (Z1, six months old), three young (Z2, ten months old) and 12 adult (Z3, 4-5 years old). A total of 26 phyla (15, 22 and 25 in Z1, Z2 and Z3) and 310 genera (153, 254 and 304 in Z1, Z2 and Z3) were identified. In Z1, Z2 and Z3, Firmicutes (63.65%, 62.07% and 61.96%) was the predominant phylum, followed by Bacteroidetes (29.08%, 29.62% and 30.02%) and Tenericutes (3.08%, 3.24% and 2.78%). The alpha diversity (Shannon Index and observed species) of Z2 was significantly higher than that of Z3 (P < 0.05). The Shannon Index of Z1 was higher than that of Z2. At the genus level, Christensenellaceae_R-7_group and Ruminiclostridium_5 had higher abundance in Z2 compared with Z3, whereas other genera, such as Fibrobacter, Lachnospiraceae_AC2044_group and Oscillibacter were enriched in Z3. In conclusion, our results reveal significant microbiota composition changes that occur with age in captive hog deer. [ABSTRACT FROM AUTHOR]