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Efficiently and accurately identifying the spatial distribution of tea plantations in the subtropical plateau regions of southwest China is of great significance for ecological and environmental protection. However, the lands of those regions are fragmented with complex vegetation types. Moreover, there is much cloudy and rainy weather over those areas, making it very difficult to identify tea plantations using only optical remote sensing data. In order to solve these problems, this paper uses Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data and Sentinel-2 (S2) optical data to design seven classification feature combinations to explore the influence of red edge features, radar features and texture features on the identification accuracy of tea plantations. The feasibility of Jeffreys-Matusita distance (JM) feature selection and Recursive Feature Elimination (RFE) feature selection algorithm to find the optimal feature combination is verified, and the distribution of tea plantations in the study area is acquired by using the object-oriented random forest algorithm. The study shows that (1) the combination of SAR data and optical data can effectively improve the identification accuracy of tea plantations. (2) S2 red edge features and S1 radar features can significantly improve the accuracy of the identification results of tea plantations. (3) After applying the JM distance and RFE feature selection algorithms, the producer's accuracy of tea plantations is improved by 1.39% and 2.38%, and the user's accuracy is improved by 1.02% and 1.3%, respectively, compared with the identification of all features. The overall accuracy of the random forest algorithm combined with RFE is 93.43%. This study proposes the application of feature selection algorithms in identification of tea plantations, which improves accuracy and increases efficiency while minimizing redundant features and provides an effective approach to identify tea plantations in cloudy and rainy areas in the subtropical plateau of southern China. [ABSTRACT FROM AUTHOR]

Due to the unique climatic characteristics and vegetation features of tropical regions, the correlation R2 of gross primary productivity (GPP) estimation in tropical regions using remote sensing models was generally lower than 0.3. Therefore, for the cloudy and rainy tropical regions, the influence brought by clouds on remote sensing images needed to be considered in GPP estimation. This paper developed a corrected vegetation photosynthesis model (VPM) for estimating GPP under cloudy conditions. It mainly corrected the two parameters, Wscalar and Enhanced Vegetation Index (EVI), which were obtained from remote sensing images and were therefore greatly influenced by clouds in the model. First, the water stress factor Wscalar was replaced by Evaporation Fraction (EF). Secondly, using the good correlation between near surface temperature and EVI, the conversion coefficient between near surface temperature and EVI was fitted to achieve the effective reconstruction of EVI contaminated by clouds. The correction of the two factors improved the estimation accuracy of the VPM model, and the comparison with the observed values of the GPP site in 4 years showed that the correction of EVI had a better improvement, with an increase of 0.22 in R2 compared with the pre-correction, and the correction of Wscalar was increased by 0.11 in R2. To verify the proposed method, the in-situ observation data of Xishuangbanna flux site from 2007 to 2010 were used. The results showed that the proposed method effectively improved the accuracy of GPP estimation by VPM model, especially in 2007 it was strongly influenced by clouds, and the improvement was significant, with R2 increasing from 0.2 to 0.82. In general, the accuracy of GPP estimation by the proposed method had been significantly improved, with RMSE (gC·m−2·8 day−1) decreasing from 15,14.4, 18.1, 14.2 to 8.07, 6.56, 10.33, 11.44, respectively. Therefore, the proposed method can be used to estimate the GPP for tropical seasonal rain forests in Xishuangbanna. [ABSTRACT FROM AUTHOR]

Existential state of solutes substantially affects the efficiency and direction of various chemical and biological processes, about which current consensus is still limited at macro and micro levels. At the trace level, solutes assume a pivotal role across a spectrum of critical fields. However, their existential states, especially at interfaces, remain largely elusive. Herein, an exceptional evolution of solute molecules is unveiled from micro to trace, solution to interface, with the aid of surface‐enhanced Raman spectroscopy, extinction, DLS and theoretical simulations. Given predominant existence of monomers within the solution, these aggregates dominate the interfacial behavior of solute molecules. Moreover, a universal, aggregate‐controlled mechanism is demonstrated that aggregates triggered by cosolvent, which can dramatically promote efficiency of catalytic reactions. The results provide novel insights into the interaction mechanisms between reactants and catalysts, potentially offering fresh perspectives for the manipulation of multiphase catalysis and related biological processes. [ABSTRACT FROM AUTHOR]

Large residual stress induced by significant difference in the coefficient of thermal expansion compromises the mechanical performance of a brazed joint between the WC–Co cemented carbide (YG20) and 3Cr13 stainless steel in a cutting tool of shield machine. In this study, a melamine formaldehyde foam precursor was utilized to produce a 3D hollow carbon foam (HCF) used as interlayer through a high‐temperature carbonization process to aid in the brazing process of YG20 and 3Cr13. First, the morphology and microstructure of the HCF interlayer were revealed as a defect‐rich carbon shell with a hollow structure. Afterward, the effects of introducing the as‐prepared HCF interlayer on the joint microstructure and shear performance were investigated. Results indicate that the HCF interlayer contributed to phase homogenization and, moreover, the residual stress relieving through in situ forming a core (metallic matrix)–sheath (ceramic shell) structure. This method outperformed the direct brazing approach without using an interlayer, with a 41% increase in the joint shear strength due to the synergistic strengthening mechanism of the HCF through residual stress reliving and joint seam toughening. Based on the results, in spite of the residual stress, the fast load transfer and the compensation from the matrix core to the ceramic sheath are responsible for the improved mechanical performance of the joint. [ABSTRACT FROM AUTHOR]

Aqueous rechargeable zinc-ion batteries (ZIBs) have been given more and more attention because of their high specific capacity, high safety, and low cost. The reasonable design of Mn-based cathode materials is an effective way to improve the performance of ZIBs. Herein, a square block MnCO3 electrode material is synthesized on the surface of carbon cloth by a one-step hydrothermal method. The phase transition of MnCO3 was accompanied by the continuous increase of specific capacity, and finally maintained good cycle stability in the charge–discharge process. The maximum specific capacity of MnCO3 electrode material can reach 83.62 mAh g−1 at 1 A g−1. The retention rate of the capacity can reach 85.24% after 1,500 cycles compared with the stable capacity (the capacity is 61.44 mAh g−1 under the 270th cycle). Ex situ characterization indicates that the initial MnCO3 gradually transformed into MnO2 accompanied by the embedding and stripping of H+ and Zn2+ in charge and discharge. When MnCO3 is no longer transformed into MnO2, the cycle tends to be stable. The phase transformation of MnCO3 could provide a new research idea for improving the performance of electrode materials for energy devices.

AimsMyocardial salvage index (MSI) is attracting increasing attention for predicting prognosis in acute myocardial infarction (AMI); however, the evaluation of MSI is mainly based on contrast agent-dependent cardiac magnetic resonance (CMR) scanning sequences. This study aims to investigate the prognostic value of MSI in reperfused ST-segment elevation myocardial infarction (STEMI) through the contrast agent-free CMR technique.Methods and resultsNighty-two patients with acute STEMI, who underwent CMR after primary percutaneous coronary intervention (PPCI), were finally enrolled. Patients were subcategorized into two groups according to median MSI. T1 and T2 mapping were conducted for measuring infarct size (IS) and area at risk (AAR). IS was significantly larger in < median MSI group than ≥ median MSI group (P < 0.001). AAR between the two groups showed no obvious differences (P = 0.108). Left ventricular ejection fraction (LVEF) was lower in < median MSI group than ≥ median MSI group (P = 0.014). There was an obvious inverse correlation between MSI and reperfusion time (R = –0.440, P < 0.001) and a strong inverse correlation between MSI and IS (R = –0.716, P = 0.011). As for the relationship LVEF, MSI showed positive but weak correlation (R = 0.2265, P < 0.001). Over a median follow-up period of 263 (227–238) days, prevalence of MACEs was significantly higher in the < median MSI group [HR: 0.15 (0.04–0.62); Log-rank P = 0.008]. The univariate Cox regression analysis revealed that LVEF, IS, and MSI were significant predictors for major adverse cardiovascular events (MACEs) (all P < 0.05). In the stepwise multivariate Cox regression analysis, LVEF and MSI were identified as independent parameters for predicting MACEs (both P < 0.05). In the receiver-operating characteristic analysis, LVEF, IS, and MSI showed prognostic value in predicting MACEs with AUCs of 0.809, 0.779, and 0.896, respectively, all (P < 0.05). A combination of MSI with LVEF showed the strongest prognostic value of MACEs (AUC: 0.901, sensitivity: 77.78%, specificity: 98.80%, P < 0.001). Delong’s test showed that the combination of LVEF with MSI had an incremental value than LVEF itself in predicting MACEs (P = 0.026).ConclusionContrast agent-free CMR technique provides a reliable evaluation of MSI, which contributes to assessing the efficacy of reperfusion therapy and predicting the occurrence of MACEs.

Jaw defects are common in oral and maxillofacial diseases and require surgical repair in extreme cases. Given the limitations in availability and efficacy of autologous bone grafts or allografts, great effort has been made in finding suitable, biocompatible, and effective artificial bone materials. Considering the key role of inflammation in bone resorption, we sought to identify a polypeptide with anti-inflammatory and bone-promoting effects. Rat bone marrow-derived mesenchymal cells (BMSCs) were treated with lipopolysaccharide (LPS) to induce an inflammatory environment, and 1,538 differentially abundant polypeptides were identified using mass spectrometry. Based on mass spectrometry signal intensity, multiple of difference, and structural stability, PAP was screened out as the polypeptide with the lowest abundance in the inflammatory condition. PAP showed no cytotoxicity to BMSCs with increasing concentrations. PAP (10 μM) also increased alkaline phosphatase activity and mRNA expression of Ocn, Bmp2, and Runx2 in a concentration-dependent manner, which confirmed that it can promote osteogenic induction of rat BMSCs. Moreover, PAP reduced LPS-induced expression of inflammatory cytokines (TNF-α, IL-1β, IL-6) and reactive oxygen species and inhibited polarization of RAW 264.7 macrophages to the inflammatory type. Finally, a skull defect mouse model was established, and mice were injected with LPS and/or PAP. Micro-CT, histological analysis, and immunohistochemical staining showed that PAP significantly reduced the number of LPS-induced bone resorption pits and maintained bone integrity. Overall, the polypeptide PAP screened using LPS stimulation of BMSCs is not cytotoxic and can inhibit the inflammatory reaction process to promote osteogenesis. This study thus provides a basis for development of PAP as a new osteogenic material in the repair of jaw defects.

BackgroundThe differentiation between hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) is challenging due to similar myocardial hypertrophic phenotype. The purpose of this study is to evaluate the feasibility of cardiovascular magnetic resonance feature tracking (CMR-FT) and late gadolinium enhancement (LGE) to distinguish between HCM and HHD and the potential relationship between myocardial strain and cardiac functional parameters.MethodsOne hundred and seventy subjects (57 HCM, 45 HHD, and 68 controls) underwent 3.0 T CMR, including steady-state free precession cines and LGE images. Global and segmental (basal, mid, and apical) analyses of myocardial radial, circumferential, longitudinal strain, and left ventricular (LV) torsion, as well as global and 16 segments of LGE were assessed. The multivariate analysis was used to predict the diagnostic ability by combining comprehensive myocardial strain parameters and LGE.ResultsGlobal radial strain (GRS), global circumferential strain (GCS), and LV torsion were significantly higher in the HCM group than in the HHD group (GRS, 21.18 ± 7.52 vs. 14.56 ± 7.46%; GCS, −13.34 ± 3.52 vs. −10.11 ± 4.13%; torsion, 1.79 ± 0.69 vs. 1.23 ± 0.65 deg/cm, all P < 0.001). A similar trend was also seen in the corresponding strain rate. As for segmental strain analysis, basal radial strain (BRS), basal circumferential strain (BCS), basal longitudinal strain (BLS), mid-radial strain (MRS), and mid-circumferential strain (MCS) were higher in the HCM group than in the HHD group (all P < 0.001). The receiver operating characteristic (ROC) results showed that the area under the curve (AUC) of LGE in the mid-interventricular septum (mIVS) was the highest among global and segmental LGE analyses. On the multivariate regression analysis, a combined model of LGE (mIVS) with GRS obtained the highest AUC value, which was 0.835 with 88.89% sensitivity and 70.18% specificity, respectively. In addition, for patients with HCM, GRS, GCS, and global longitudinal strain had correlations with LV ejection fraction (LVEF), maximum interventricular septum thickness (IVST max), and left ventricular mass index (LVMi). Torsion was mildly associated with LVEF.ConclusionCMR-FT-derived myocardial strain and torsion provided valuable methods for evaluation of HCM and HHD. In addition, the combination of GRS and LGE (mIVS) achieved the highest diagnostic value.

The performance of a polymer electrolyte membrane fuel cell (PEMFC) closely depends on internal reactant diffusion and liquid water removal. As one of the key components of PEMFCs, bipolar plates (BPs) provide paths for reactant diffusion and product transport. Therefore, to achieve high fuel cell performance, one key issue is designing BPs with a reasonable flow field. This paper provides a comprehensive review of various modifications of the conventional parallel flow field, interdigitated flow field, and serpentine flow field to improve fuel cells’ overall performance. The main focuses for modifications of conventional flow fields are flow field shape, length, aspect ratio, baffle, trap, auxiliary inlet, and channels, as well as channel numbers. These modifications can partly enhance reactant diffusion and product transport while maintaining an acceptable flow pressure drop. This review also covers the detailed structural description of the newly developed flow fields, including the 3D flow field, metal flow field, and bionic flow field. Moreover, the effects of these flow field designs on the internal physical quantity transport and distribution, as well as the fuel cells’ overall performance, are investigated. This review describes state-of-the-art flow field design, identifies the key research gaps, and provides references and guidance for the design of high-performance flow fields for PEMFCs in the future.

Satellite remote sensing of grassland ecosystem restoration requires considering both the above-ground biomass and soil information, and the latter is even more crucial due to the value and restoration difficulty of soil productivity. In this study, we proposed an approach to support the restoration pattern for mountainous grasslands at regional scale. The approach integrates different aspects and key processes, including degradation status, restoration potential and recovery capability, compared to a reference state. Specifically, we illustrated the method with the case of grasslands in southwestern China from a conservation perspective. Soil erosion conditions, net primary productivity and regrowth rate of grasslands were selected as indicators to reveal restoration possibilities. The results showed that the method proposed for remote sensing identification of grassland distribution has an overall accuracy of 88.21% at the regional scale. 59.54% of grasslands in Zhaotong are being eroded with an unsustainable erosion rate greater than the tolerant soil loss, and the average annual soil erosion rate is 952.17 t/(km2·a). Meanwhile, there is obvious spatial heterogeneity in soil erosion factors, vegetation restoration potential and regrowth rate, and the dry–hot valley of Jinsha River in the southwest is much more sensitive to climate change and vulnerable than other regions. The grassland vegetation cover revealed a fluctuating trend and protection of grassland vegetation on soil from erosion has an obvious lag, restoration efforts should be focused on the months before the arrival of the rainy season. In light of various grassland types, the overlay zoning results suggest various restoration patterns of natural repair and manual intervention should be employed for different grasslands. Urgent action is needed to face the challenge and process of grassland degradation and restore its sustainability with shared understanding by taking the stakeholders, collaborations and mutual relationships among different roles into account (e.g., scientist, government and herdsman).

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the patient’s interactive force situation, resulting in the inability to accurately assess the patient’s true motor intention and difficulty stimulating the patient’s initiative, thus negatively affecting the patient’s rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects’ task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject’s task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject’s motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject’s initiative. Through experiments, this control strategy has been shown to not only improve the subject’s initiative during the training process and ensure their safety during training but also enhance the subject’s motor learning ability.

Visuospatial selective attention can focus attention on a certain spatial area and rationally allocate attentional resources during visual target perception. Previous studies investigated the behavioral advantages of subjects when the target appeared in the upper and lower visual fields. However, the neurophysiological characteristics of the brain are not clear, and there is a lack of comprehensive analysis of the external behavior and the internal neurophysiological characteristics. We designed two task paradigms containing a spatial location orientation task and a visual search task. We used event-related potentials (ERP) components (P1 and P2) and electroencephalogram (EEG) rhythms (theta and alpha) to analyze the attention level and allocation of attention resources of the brain. The results showed that when the target appeared in the lower visual field in the spatial location orientation task, subjects consumed fewer attention resources and demonstrated better behavioral performance. In the visual search task, when the target appeared in the upper left visual field, subjects could better mobilize attention resources and behaved more advantageously. The study provides a basis for the design of the target in the upper and lower visual fields in the rehabilitation task, especially for stroke patients with low attention levels due to attention disorders such as spatial attention deficit.

In motor imagery (MI) brain–computer interface (BCI) research, some researchers have designed MI paradigms of force under a unilateral upper-limb static state. It is difficult to apply these paradigms to the dynamic force interaction process between the robot and the patient in a brain-controlled rehabilitation robot system, which needs to induce thinking states of the patient’s demand for assistance. Therefore, in our research, according to the movement of wiping the table in human daily life, we designed a three-level-force MI paradigm under a unilateral upper-limb dynamic state. Based on the event-related de-synchronization (ERD) feature analysis of the electroencephalography (EEG) signals generated by the brain’s force change motor imagination, we proposed a multi-scale temporal convolutional network with attention mechanism (MSTCN-AM) algorithm to recognize ERD features of MI-EEG signals. Aiming at the slight feature differences of single-trial MI-EEG signals among different levels of force, the MSTCN module was designed to extract fine-grained features of different dimensions in the time–frequency domain. The spatial convolution module was then used to learn the area differences of space domain features. Finally, the attention mechanism dynamically weighted the time–frequency–space domain features to improve the algorithm’s sensitivity. The results showed that the accuracy of the algorithm was 86.4 ± 14.0% for the three-level-force MI-EEG data collected experimentally. Compared with the baseline algorithms (OVR-CSP+SVM (77.6 ± 14.5%), Deep ConvNet (75.3 ± 12.3%), Shallow ConvNet (77.6 ± 11.8%), EEGNet (82.3 ± 13.8%), and SCNN-BiLSTM (69.1 ± 16.8%)), our algorithm had higher classification accuracy with significant differences and better fitting performance.

Aims: This study aims to develop a prediction tool for the overall survival of cervical cancer patients. Methods: We obtained 4116 female patients diagnosed with cervical cancer aged 25–69 during 2008–2019 from the Surveillance, Epidemiology, and End Results Program. The overall survival between groups was illustrated by the Kaplan–Meier method and compared by a log-rank test adjusted by the Bonferroni–Holm method. We first performed the multivariate Cox regression analysis to evaluate the predictive values of the variables. A prediction model was created using cox regression based on the training set, and the model was presented as a nomogram. The proposed nomogram was designed to predict the 1-year, 3-year, and 5-year overall survival of patients with cervical cancer. Besides the c-index, time-dependent receiver operating curves, and calibration curves were created to evaluate the accuracy of the nomogram at the timepoint of one year, three years, and five years. Results: With a median follow-up of 54 (28, 92) months, 1045 (25.39%) patients were deceased. Compared with alive individuals, the deceased were significantly older and the primary site was more likely to be the cervix uteri site, large tumor size, higher grade, and higher combined summary stage (all p values < 0.001). In the multivariate Cox regression, age at diagnosis, race, tumor size, grade, combined summary stage, pathology, and surgery treatment were significantly associated with the all-cause mortality for patients with cervical cancer. The proposed nomogram showed good performance with a C-index of 0.82 in the training set. The 1-year, 3-year, and 5-year areas under the curves (with 95% confidence interval) of the receiver operating curves were 0.88 (0.84, 0.91), 0.84 (0.81, 0.87), and 0.83 (0.80, 0.86), respectively. Conclusions: This study develops a prediction nomogram model for the overall survival of cervical cancer patients with a good performance. Further studies are required to validate the prediction model further.