•The long term spatiotemporal characteristics of ecosystem service value are revealed.•Socio economic factors in ecological restoration are considered in evaluation model.•The spatial differentiation ...mechanisms of ecosystem service value are identified.
The Grain to Green Program (GTGP) has directly led to large-scale transformational land use/cover changes and has impacted ecosystem services. Therefore, it is of great importance to determine the relationship between the land use change and ecosystem services in retired farmland areas. Based on multi-temporal land use data (1980, 1990, 1995, 2000, 2005, 2010, 2015, and 2018), the benefit transfer method was used to calculate the ecosystem service value (ESV), and the willingness to pay and ability to pay were then integrated into the evaluation model. In addition, we used the exploratory spatial data analysis method to systematically analyze the change characteristics of the land use and ESV. Finally, the spatial differentiation mechanisms of the ESV were identified using geographical detectors. The results showed that the transformation of the land use mainly occurred in the farmland, forestland, and grassland; the farmland showed a decreasing trend from 1980 to 2018, whereas the areas of the forestland and grassland showed an increasing trend. The ESV demonstrated an increasing trend during 1980–2018 and formed a spatial pattern with the distribution of high and low values. There was a significant positive spatial correlation in the ESV, and this spatial aggregation became increasingly intense with time. The order of different ecosystem services in the study area was as follows: regulating service > supporting service > provisioning service > cultural service, and the ecosystem service values showed an upward trend, except for the provisioning service that showed a downward trend. The spatial differentiation of the ESV is the result of a combined effect of natural factors and socioeconomic factors. With the restoration of vegetation in the retired farmland area, natural factors such as slope and elevation play a crucial role in the differentiation of the ESV.
Speed of Processing (SoP) represents a fundamental limiting step in cognitive performance which may underlie General Intelligence. The measure of SoP is particularly sensitive to aging, neurological ...or cognitive diseases, and has become a benchmark for diagnosis, cognitive remediation, and enhancement. Neural efficiency of the Dorsolateral Prefrontal Cortex (DLPFC) is proposed to account for individual differences in SoP. However, the mechanisms by which DLPFC efficiency is shaped by training and whether it can be enhanced remain elusive. To address this, we monitored the brain activity of sixteen healthy participants using functional Near Infrared Spectroscopy (fNIRS) while practicing a common SoP task (Symbol Digit Substitution Task) across 4 sessions. Furthermore, in each session, participants received counterbalanced excitatory repetitive transcranial magnetic stimulation (rTMS) during mid-session breaks. Results indicate a significant involvement of the left-DLPFC in SoP, whose neural efficiency is consistently increased through task practice. Active neurostimulation, but not Sham, significantly enhanced the neural efficiency. These findings suggest a common mechanism by which neurostimulation may aid to accelerate learning.
•Left-DLPFC activity is associated with Symbol-Digit Performance.•Practice of SDST increases neural efficiency.•Excitatory rTMS to left-DLPFC further increases neural efficiency.•Neuroimaging may help evaluate the effects of neurostimulation paradigms.
3D convolutional neural networks have achieved promising results for video tasks in computer vision, including video saliency prediction that is explored in this paper. However, 3D convolution ...encodes visual representation merely on fixed local spacetime according to its kernel size, while human attention is always attracted by relational visual features at different time. To overcome this limitation, we propose a novel Spatio-Temporal Self-Attention 3D Network (STSANet) for video saliency prediction, in which multiple Spatio-Temporal Self-Attention (STSA) modules are employed at different levels of 3D convolutional backbone to directly capture long-range relations between spatio-temporal features of different time steps. Besides, we propose an Attentional Multi-Scale Fusion (AMSF) module to integrate multi-level features with the perception of context in semantic and spatio-temporal subspaces. Extensive experiments demonstrate the contributions of key components of our method, and the results on DHF1K, Hollywood-2, UCF, and DIEM benchmark datasets clearly prove the superiority of the proposed model compared with all state-of-the-art models.
•Multi-period land-use data used to analyze change in northern Shaanxi.•ESV of Loess Plateau rose by 5.12 billion USD over 30 years.•Secondary services in order: regulation, support, provision, and ...cultural.•Cross-sensitivity coefficient showed sensitivity of land-use transition.•Provides data for ecological compensation and ecosystem management.
The Grain-for-Green Program (GGP) has been contributing to changes in the nationwide use of land and vegetation, further changing ecosystem services (ESs). However, the influence of GGP on ESs, in terms of land use evolution remains elusive. This study is conducted based on a dataset collected every five years for the past 30 years. This dataset includes land use statistics and is obtained from Landsat images and the random forest algorithm. Land use evolution in the Loess Plateau in northern Shaanxi from 1990 to 2020 is systematically analyzed. The interest transfer method is adopted to compute the ecosystem service value (ESV), and the willingness and economic affordability are included in the evaluation model. Finally, a cross-sensitivity coefficient is specified to reveal the effects of land use evolution on the ESV in the studied area. The results are as follows: (1) Land use changes mainly occurred on farmland, forest, and orchards. In the past 30 years, the area of cultivated land showed a decreasing trend, whereas the land areas used for other purposes increased. (2) In the same period, the ESV of the investigated plateau continued to rise, increasing by 5.12 billion USD in total. Additionally, the ESV provided by secondary services increases in the following order: regulating services > supporting services > provisioning services > cultural services. (3) The cross-sensitivity coefficient showed that the net transition among forest, grassland, orchard, and unused land in the studied region is relatively sensitive, and a larger transition span of land utilization leads to a stronger effect on the ESV. This study offers crucial data for the compensation of interregional ecology and provides model cases for other regions for ecosystem management.
Studies on functional connectivity (FC) between remote brain regions or in local brain region have revealed ample statistical associations between the brain activities of corresponding brain units ...and deepened our understanding of brain. However, the dynamics of local FC were largely unexplored. In this study, we employed the dynamic regional phase synchrony (DRePS) method to investigate local dynamic FC based on multiple sessions resting state functional magnetic resonance imaging (rs-fMRI) data. We observed consistent spatial distribution of voxels with high or low temporal averaged DRePS in some specific brain regions across subjects. To quantify the dynamic change of local FC patterns, we calculated the average regional similarity of local FC patterns across all volume pairs under different volume interval and observed that the average regional similarity decreased quickly as volume interval increased, and would reach different steady ranges with only small fluctuations. Four metrics, i.e., the local minimal similarity, the turning interval, the mean of steady similarity, and the variance of steady similarity, were proposed to characterize the change of average regional similarity. We found that both the local minimal similarity and the mean of steady similarity had high test-retest reliability, and had negative correlation with the regional temporal variability of global FC in some functional subnetworks, which indicates the existence of local-to-global FC correlation. Finally, we demonstrated that the feature vectors constructed with the local minimal similarity may serve as brain "fingerprint" and gained good performance in individual identification. Together, our findings offer a new perspective for exploring the local spatial-temporal functional organization of brain.
Image coding technology has become an indispensable technology in the field of modern information. With the vigorous development of the big data era, information security has received more attention. ...Image steganography is an important method of image encoding and hiding, and how to protect information security with this technology is worth studying. Using a basis of mathematical modeling, this paper makes innovations not only in improving the theoretical system of kernel function but also in constructing a random matrix to establish an information-hiding scheme. By using the random matrix as the reference matrix for secret-information steganography, due to the characteristics of the random matrix, the secret information set to be retrieved is very small, reducing the modification range of the steganography image and improving the steganography image quality and efficiency. This scheme can maintain the steganography image quality with a PSNR of 49.95 dB and steganography of 1.5 bits per pixel and can ensure that the steganography efficiency is improved by reducing the steganography set. In order to adapt to different steganography requirements and improve the steganography ability of the steganography schemes, this paper also proposes an adaptive large-capacity information-hiding scheme based on the random matrix. In this scheme, a method of expanding the random matrix is proposed, which can generate a corresponding random matrix according to different steganography capacity requirements to achieve the corresponding secret-information steganography. Two schemes are demonstrated through simulation experiments as well as an analysis of the steganography efficiency, steganography image quality, and steganography capacity and security. The experimental results show that the latter two schemes are better than the first two in terms of steganography capacity and steganography image quality.
•Three-stage evaluation method was established based on Logistic Regression Model.•The weight of the model avoids the subjective factor of human being.•Modularly assesses the various elements of ...ecotechnology.•The evaluation process is dynamic because of the weight updating.•The model provides reference for the design of ecological engineering construction scheme.
In order to cope with degradation and unsustainability of ecosystems, many countries had developed a large number of ecotechnologies. Before learning ecotechnology from other regions, we should evaluate the technology to judge whether it is suitable for our own situation. Based on the lack of scientific and reasonable index system as well as evaluation model in ecotechnology evaluation, we constructed a comprehensive evaluation index system consist of the eco-technology attributes, the implementation conditions, the implementation effects and the popularization potential; and established three-stage evaluation method with Logistic Regression Model according to the analysis of advantages and disadvantages of commonly used assessment models. According to our understanding degree of ecotechnology, the model could not only realize the comprehensive evaluation of ecotechnology as a whole, but also modularly assess the various elements of technology, and the evaluation process is dynamic and objective. We realized the evaluation model of ecotechnology based on the investigation on soil and water conservation technology in the Loess Plateau, and verified its effectiveness using the data of Nangou Village. The results show that the three-stage evaluation method based on Logistic Regression Model is suitable for ecotechnology assessment. The model can not only provide scientific and effective support for the introduction and popularization of ecotechnology, but also provide reference for the design of ecological engineering construction scheme.
There is great potential for carbon emission reduction in energy-enriched areas. It is important to master the spatiotemporal characteristics and driving factors of carbon emissions to achieve the ...goal of carbon emission reduction. Previous studies on carbon emissions mainly focused on the numerical changes in regional carbon emissions. There have been few studies on spatiotemporal characteristics, making it difficult to formulate carbon emission reduction strategies according to local conditions. This study is based on the carbon emission calculation method proposed by the Intergovernmental Panel on Climate Change (IPCC), taking the method of exploratory spatial data analysis (ESDA), standard deviation ellipse (SDE) analysis and the geographically weighted regression model (GWR) to analyse the spatiotemporal evolution characteristics and determinants and dividing regional types of carbon emissions. The results show that aggregate carbon emissions and other carbon emission indicators presented an upward trend from 2000 to 2016, and the growth momentum of carbon emissions was difficult to curb in the short term. The carbon emissions of the study area are relatively concentrated in spatial; the direction of carbon emissions presented a trend of “northeast–southwest”, and the main axis and centre of carbon emissions tend to move northward over time. There are six regional types of carbon emissions in the study area. The low total amount–low intensity–low pressure type (L-L-L) became the dominant regional type of carbon emissions. The results of the GWR model showed that the degree of influence of explanatory variables on carbon emissions in descending order is urbanization rate > industrial structure > population > population density > per capita GDP.
Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of ...first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis.
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