European achievements in soil remediation and brownfield redevelopment

With the aim of sharing best practices of soil restoration and management of contaminated sites among European countries and to raise awareness of the enormous efforts made to succeed in such difficult commitment, the experts of the EIONET Soil working group on contaminated sites and brownfields agreed to gather their country's interesting cases and successful stories of recovery of contaminated areas. This second edition of the monograph presents seventeen new cases from eight European countries and its Regions of how polluted sites and brownfields have been remediated like new methodologies of sustainable restoration of the subsoil, development of innovative technologies, and funding mechanisms etc. These stories have been compiled to present what national, regional or local governments are doing to improve the quality of the environment and the living conditions of their population. A second aim is the promotion of best practices among industry, consultancies and business operators.JRC.D.3-Land Resource

Analysis of Quality of Backyard Compost and Its Potential Utilization as a Circular Bio-Waste Source

The use and quality analysis of household compost have become very important issues in recent years due to the increasing interest in local food production and safe, self-produced food. The phenomenon was further exacerbated by the COVID-19 pandemic quarantine period, which gave new impetus to the growth of small home gardens. However, the knowledge associated with making high-quality compost is often lacking in home gardeners. Therefore, the objective of this research was to find answers to the following questions: can the quality of backyard compost be considered safe in terms of toxicity and nutrient content? Can weed seed dispersion affect the usability of backyard compost? In general, can the circulation of organic matter be increased with the spread of home composting? In this study, 16 different house composts were analysed for stability, weed seed contamination, toxic elements, and nutrient content using analysis of variance. The results of the research showed that the quality properties of the composts (including their weed seed dispersion effect) were greatly influenced by the different techniques and raw materials used. The toxicity levels, as well as the content of macro and microelements, were within the parameters of safe-quality compost. The specific macronutrient (Ca, Mg) and micronutrient (Fe, Mn) contents of the tested composts have a similar and, in some cases, more favorable nutrient supply capacity in crop production than the frequently-used cow manure-based composts. With a plan of basic education on composting, there is potential to encourage farmyard composting

Autistic Traits in Neurotypical Adults: Correlates of Graph Theoretical Functional Network Topology and White Matter Anisotropy Patterns

<div><p>Attempts to explicate the neural abnormalities behind autism spectrum disorders frequently revealed impaired brain connectivity, yet our knowledge is limited about the alterations linked with autistic traits in the non-clinical population. In our study, we aimed at exploring the neural correlates of dimensional autistic traits using a dual approach of diffusion tensor imaging (DTI) and graph theoretical analysis of resting state functional MRI data. Subjects were sampled from a public neuroimaging dataset of healthy volunteers. Inclusion criteria were adult age (age: 18–65), availability of DTI and resting state functional acquisitions and psychological evaluation including the Social Responsiveness Scale (SRS) and Autistic Spectrum Screening Questionnaire (ASSQ). The final subject cohort consisted of 127 neurotypicals. Global brain network structure was described by graph theoretical parameters: global and average local efficiency. Regional topology was characterized by degree and efficiency. We provided measurements for diffusion anisotropy. The association between autistic traits and the neuroimaging findings was studied using a general linear model analysis, controlling for the effects of age, gender and IQ profile. Significant negative correlation was found between the degree and efficiency of the right posterior cingulate cortex and autistic traits, measured by the combination of ASSQ and SRS scores. Autistic phenotype was associated with the decrease of whole-brain local efficiency. Reduction of diffusion anisotropy was found bilaterally in the temporal fusiform and parahippocampal gyri. Numerous models describe the autistic brain connectome to be dominated by reduced long-range connections and excessive short-range fibers. Our finding of decreased efficiency supports this hypothesis although the only prominent effect was seen in the posterior limbic lobe, which is known to act as a connector hub. The neural correlates of the autistic trait in neurotypicals showed only limited similarities to the reported findings in clinical populations with low functioning autism.</p> </div

Demonstrating the functional connections of the right posterior cingulate cortex with a circular connectivity profile.

<p>Connectivity data were calculated for sub-populations with the lowest and highest ASSQ scores. Key for the abbreviations is given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060982#pone.0060982.s001" target="_blank">Table S1</a>.</p

Demographic data of the study population.

<p>Distribution of subject age, full scale IQ, verbal IQ, ASSQ and SRS scores. Data are depicted as histograms (left panels) and Q-Q (quantile-quantile) probability plots (right panels) in which reference lines of the normal distribution are given (n = 127).</p

Regional neural correlates of self-reported autistic traits, GLM design 1.

<p>We demonstrate the joint effects of Social Responsiveness Scale (SRS Total Score) and Autism Spectrum Screening Questionnaire (ASSQ), controlling for age and gender. GLM: General Linear Model.</p>*<p>: 0.01≤p<0.05.</p>**<p>: 0.001≤p<0.01.</p>***<p>: p<0.001.</p>†<p>: Significant interaction after false discovery rate correction with the Benjamini-Hochberg procedure.</p

Processing pipeline of resting state functional MRI data.

<p>Panel A, far left: two atlas regions, Inferior Frontal Gyrus, triangular part (red, R23) and Middle Temporal Gyrus temporooccipital part (blue, R58) were overlaid on an atlas-space aligned fMRI image. The corresponding regional BOLD curves and their wavelet coefficients are shown on next images. Accordingly, the TR = 2500 ms repetition time and the four level wavelet decomposition the evaluated wavelet coefficients of four frequency bands (0.1–0.2 Hz, 0.05–0.1 Hz, 0.025–0.05 Hz, 0.0125–0.025 Hz) were generated (middle bottom image). In the 4th column the evaluated wavelet correlation matrix (top) and the distribution of correlation coefficients (bottom) are shown. We used these wavelet correlation values between each pair of brain regions to construct the matrix in which yellow color represents high correlation coefficients while red means low values. Panel B: In the bottom row, three adjacency matrices are shown with wired costs 0.1, 0.4 and 0.9. These matrices were generated from the weighted connectivity matrix (4^th panel, right bottom image) by different weight thresholds. Vertical gray arrows represent the calculation procedure of nodal and global network parameters at different cost levels. The horizontal gray arrows demonstrate the final step of Monte-Carlo based cost-integration procedure in which the summed parameters are divided by the integration steps (MC).</p

Connections of the right posterior cingulate gyrus in subjects with low and high degree of autistic traits.

<p>Connection strengths are given as the wavelet correlation coefficients of the BOLD time curves. Cut-off threshold for lowest and highest ASSQ scorers were the 5^th and 95^th percentile values. Regions were listed in descending order of the connection strengths. Key for the abbreviations is given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060982#pone.0060982.s001" target="_blank">Table S1</a>.</p

Distribution of global functional network properties.

<p>Global efficiency (E_g) and average local efficiency (E_l). Data are depicted as histograms (left panels) and Q-Q (quantile-quantile) probability plots (right panels) in which reference lines of the normal distribution are given (n = 127).</p