246 research outputs found

    The Characters of Soil Microbial Biomass and Metabolic Quotient Associated with Shrub Development in the Arid Region

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    Soil microbial biomass (MBC), as the most active of soil organic constituents, controls many important ecological processes in the ecosystem including nutrient cycling and litter decomposition (Jia et al. 2010), and is considered to be the most sensitive biological indicator of soil quality (Sinha et al. 2009). Moreover, soil microbial metabolic quotient (qCO2) reflects the quantity and quality of soil organic matter, soil nutrient availability, microbial substrate utilization efficiency and ecosystem stability (Mao et al. 2010). Shrub is the dominant vegetation of desert ecosystems, contributing to soil nutrient conservation and carbon sequestration. Considerable research related to shrubs in desert ecosystems has been reported, however changes of soil microbial properties throughout the process of shrub development remains poorly documented. The main objective of this study was to explore how soil microbial biomass and qCO2 change with shrub development

    Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

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    The fast development in the fields of integrated circuits, photovoltaics, the automobile industry, advanced manufacturing, and astronomy have led to the importance and necessity of quickly and accurately obtaining three-dimensional (3D) shape data of specular surfaces for quality control and function evaluation. Owing to the advantages of a large dynamic range, non-contact operation, full-field and fast acquisition, high accuracy, and automatic data processing, phase-measuring deflectometry (PMD, also called fringe reflection profilometry) has been widely studied and applied in many fields. Phase information coded in the reflected fringe patterns relates to the local slope and height of the measured specular objects. The 3D shape is obtained by integrating the local gradient data or directly calculating the depth data from the phase information. We present a review of the relevant techniques regarding classical PMD. The improved PMD technique is then used to measure specular objects having discontinuous and/or isolated surfaces. Some influential factors on the measured results are presented. The challenges and future research directions are discussed to further advance PMD techniques. Finally, the application fields of PMD are briefly introduce

    Use of Ultrasmall Superparamagnetic Iron Oxide Enhanced Susceptibility Weighted Imaging and Mean Vessel Density Imaging to Monitor Antiangiogenic Effects of Sorafenib on Experimental Hepatocellular Carcinoma

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    We investigated effectiveness of ultrasmall superparamagnetic iron oxide enhanced susceptibility weighted imaging (USPIO-enhanced SWI) and mean vessel density imaging (Q) in monitoring antiangiogenic effects of Sorafenib on orthotopic hepatocellular carcinoma (HCC). Thirty-five HCC xenografts were established. USPIO-enhanced SWI and Q were performed on a 1.5 T MR scanner at baseline, 7, 14, and 21 days after Sorafenib treatment. Intratumoral susceptibility signal intensity (ITSS) and Q were serially measured and compared between the treated (n = 15) and control groups (n = 15). Both ITSS and Q were significantly lower in the treated group at each time point (P < 0.05). Measurements in the treated group showed that ITSS persisted at 7 days (P = 0.669) and increased at 14 and 21 days (P < 0.05), while Q significantly declined at 7 days (P = 0.028) and gradually increased at 14 and 21 days. In the treated group, significant correlation was found between Q and histologic microvessel density (MVD) (r = 0.753, P < 0.001), and ITSS correlated well with MVD (r = 0.742, P = 0.002) after excluding the data from baseline. This study demonstrated that USPIO-enhanced SWI and Q could provide novel biomarkers for evaluating antiangiogenic effects of Sorafenib on HCC

    Process Optimization and Physicochemical Characteristics Analysis of Soluble Dietary Fiber from Corn Bran Modified by Composite Enzymes

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    To investigate the optimal extraction process and functional characteristics of soluble dietary fiber (SDF) from corn bran. This study used corn bran, a by-product of corn processing, as raw material to extract soluble dietary fiber from corn bran through composite enzyme modification. The optimal process parameters were determined through single factor experiments and response surface methodology optimization, and their physicochemical properties were studied. The results showed that the extraction yield of SDF reached the highest value of 16.64%±0.21% when the content of cellulase was 1.5%, the content of xylanase was 1%, the enzymolysis temperature was 55 ℃ and enzymolysis time was 150 min. Its solubility was 87.63%±0.43%, the holding water capacity was 2.87±0.16 g/g, the oil holding capacity was 2.30±0.12 g/g, the glucose adsorption capacity was 5.32±0.12 mmol/g. Under simulated stomach (pH2.0) and intestinal environment (pH7.0), cholesterol adsorption capacity was 11.74±0.15 and 42.93±0.08 mg/g and sodium cholacte adsorption capacity was 15.43±0.17 and 50.67±0.10 mg/g, respectively. The research results can provide theoretical reference for the development and utilization of soluble dietary fiber from corn bran

    Unveiling the spatial-temporal variation of urban land use efficiency of Yangtze River Economic Belt in China under carbon emission constraints

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    Under the constraint of carbon emission, measuring and analyzing the spatial-temporal evolution characteristics of urban land use efficiency in the Yangtze River Economic Belt is the inherent requirement of its ecological protection and sustainable development. In this paper, we calculated the urban land use efficiency of 107 cities in the Yangtze River Economic Belt from 2006 to 2020 by using the SBM-Undesirable model with unexpected output, and analyzed its temporal evolution trend and spatial correlation relationship by using kernel density and spatial autocorrelation method. The results showed that: except in 2020, the urban land use efficiency was generally low due to the COVID-19 epidemic, and the urban land use efficiency in other years was mostly concentrated in the middle levels, and showed a trend of slow fluctuation and rise year by year. The difference of urban land use efficiency level between regions increased, and the dispersion degree in upstream, midstream and downstream increased with each passing year. Urban land use efficiency spatial imbalance was significant, and the urban land use efficiency level of large and medium-sized cities was generally lower than that of cities with low economic development level. The spatial correlation was weak, and the global spatial autocorrelation was basically insignificant, while the local spatial agglomeration areas were mainly distributed in the upstream and downstream regions, with a small distribution range and weak spatial interaction. The distribution areas of the standard deviation ellipse were gradually flattened, and the center of gravity as a whole shift significantly to the southwest. The research results are helpful to understand the development history and future trend of urban land use efficiency in various regions, and propose that cities should consider the impact of public crisis events in advance, reasonably control the scale of land expansion, and lead coordinated development and other reasonable suggestions when formulating land use policies

    Supervised Learning in SNN via Reward-Modulated Spike-Timing-Dependent Plasticity for a Target Reaching Vehicle

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    Spiking neural networks (SNNs) offer many advantages over traditional artificial neural networks (ANNs) such as biological plausibility, fast information processing, and energy efficiency. Although SNNs have been used to solve a variety of control tasks using the Spike-Timing-Dependent Plasticity (STDP) learning rule, existing solutions usually involve hard-coded network architectures solving specific tasks rather than solving different kinds of tasks generally. This results in neglecting one of the biggest advantages of ANNs, i.e., being general-purpose and easy-to-use due to their simple network architecture, which usually consists of an input layer, one or multiple hidden layers and an output layer. This paper addresses the problem by introducing an end-to-end learning approach of spiking neural networks constructed with one hidden layer and reward-modulated Spike-Timing-Dependent Plasticity (R-STDP) synapses in an all-to-all fashion. We use the supervised reward-modulated Spike-Timing-Dependent-Plasticity learning rule to train two different SNN-based sub-controllers to replicate a desired obstacle avoiding and goal approaching behavior, provided by pre-generated datasets. Together they make up a target-reaching controller, which is used to control a simulated mobile robot to reach a target area while avoiding obstacles in its path. We demonstrate the performance and effectiveness of our trained SNNs to achieve target reaching tasks in different unknown scenarios

    Relationship between university students’ physical activity and mobile phone dependence: Mediating effect of subjective well-being and moderating effect of psychological capital

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    BackgroundWith the ongoing development of the information society, the Internet and smartphones have become an essential way of life, but also fostered the problem of mobile phone dependence. Physical activity and subjective well-being have both been shown to correlate with mobile phone dependence, but the impact of subjective well-being on the relationship between physical activity and mobile phone dependence is not fully understood. This study investigates subjective well-being as a potential mediating variable in the relationship. It also investigates whether psychological capital moderates the association between subjective well-being and mobile phone dependence.MethodsA total of 9,569 students from 38 universities in Jiangsu Province were selected. Participants were surveyed via the online questionnaire distribution platform Questionnaire Star. Common method bias test and Pearson correlation tests were used to analyze the study indicators, and the theoretical model for this study was validated using Process plug-in developed by Hayes and set at p &lt; 0.05 (two- tail) as statistically significant.ResultsThe levels of physical activity, subjective well-being, and psychological capital were all significantly higher for male students than female students. However, female students had a significantly higher level of mobile phone dependence. As predicted, there was a direct negative correlation between physical activity and mobile phone dependence, and subjective well-being mediated that relationship. Psychological capital moderated the relationship between subjective well-being and mobile phone dependence. It also positively moderated the indirect effect between physical activity and mobile phone dependence via subjective well-being

    Study of Aerosol Influence on Nighttime Land Surface Temperature Retrieval Based on Two Methods

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    The aim of this study is to evaluate the aerosol influence on LST retrieval with two algorithms (split-window (SW) method and a four-channel based method) using simulated data under typical conditions. The results show that the root mean square error (RMSE) decreases to approximately 2.3 K for SW method and 1.5 K for four channel based method when VZA = 60° and visibility = 3 km; an RMSE would be increased by approximately 1.0 K when visibility varies from 3 km to 23 km. Moreover, a detailed sensitivity analysis under a visibility of 3 km and 23 km is performed in terms of uncertainties of land surface emissivity (LSE), water vapor content (WVC), and instrument noise, respectively. It is noted that the four-channel based method is more sensitive to LSE than SW method, especially for dry atmosphere; LST error caused by a WVC uncertainty of 20% is within 1.5 K for SW method and within 0.8 K for four-channel based method; the instrument noise would introduce LST error with a maximum standard deviation of 0.5 K and 0.04 K for the four-channel based method and SW method, respectively

    Insertion of a TRIM-like sequence in MdFLS2-1 promoter is associated with its allele-specific expression in response to Alternaria alternata in apple

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    Alternaria blotch disease, caused by Alternaria alternata apple pathotype (AAAP), is one of the major fungal diseases in apple. Early field observations revealed, the anther-derived homozygote Hanfu line (HFTH1) was highly susceptible to AAAP, whereas Hanfu (HF) exhibited resistance to AAAP. To understand the molecular mechanisms underlying the difference in sensitivity of HF and HFTH1 to AAAP, we performed allele-specific expression (ASE) analysis and comparative transcriptomic analysis before and after AAAP inoculation. We reported an important immune gene, namely, MdFLS2, which displayed strong ASE in HF with much lower expression levels of HFTH1-derived alleles. Transient overexpression of the dominant allele of MdFLS2-1 from HF in GL-3 apple leaves could enhance resistance to AAAP and induce expression of genes related to salicylic acid pathway. In addition, MdFLS2-1 was identified with an insertion of an 85-bp terminal-repeat retrotransposon in miniature (TRIM) element-like sequence in the upstream region of the nonreference allele. In contrast, only one terminal direct repeat (TDR) from TRIM-like sequence was present in the upstream region of the HFTH1-derived allele MdFLS2-2. Furthermore, the results of luciferase and β-glucuronidase reporter assays demonstrated that the intact TRIM-like sequence has enhancer activity. This suggested that insertion of the TRIM-like sequence regulates the expression level of the allele of MdFLS2, in turn, affecting the sensitivity of HF and HFTH1 to AAAP
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