Synergy of the mirror neuron system and the mentalizing system in a single brain and between brains during joint actions.

Cooperative action involves the simulation of actions and their co-representation by two or more people. This requires the involvement of two complex brain systems: the mirror neuron system (MNS) and the mentalizing system (MENT), both of critical importance for successful social interaction. However, their internal organization and the potential synergy of both systems during joint actions (JA) are yet to be determined. The aim of this study was to examine the role and interaction of these two fundamental systems-MENT and MNS-during continuous interaction. To this hand, we conducted a multiple-brain connectivity analysis in the source domain during a motor cooperation task using high-density EEG dual-recordings providing relevant insights into the roles of MNS and MENT at the intra- and interbrain levels. In particular, the intra-brain analysis demonstrated the essential function of both systems during JA, as well as the crucial role played by single brain regions of both neural mechanisms during cooperative activities. Specifically, our intra-brain analysis revealed that both neural mechanisms are essential during Joint Action (JA), showing a solid connection between MNS and MENT and a central role of the single brain regions of both mechanisms during cooperative actions. Additionally, our inter-brain study revealed increased inter-subject connections involving the motor system, MENT and MNS. Thus, our findings show a mutual influence between two interacting agents, based on synchronization of MNS and MENT systems. Our results actually encourage more research into the still-largely unknown realm of inter-brain dynamics and contribute to expand the body of knowledge in social neuroscience.

Intracortical brain-heart interplay: An EEG model source study of sympathovagal changes.

The interplay between cerebral and cardiovascular activity, known as the functional brain-heart interplay (BHI), and its temporal dynamics, have been linked to a plethora of physiological and pathological processes. Various computational models of the brain-heart axis have been proposed to estimate BHI non-invasively by taking advantage of the time resolution offered by electroencephalograph (EEG) signals. However, investigations into the specific intracortical sources responsible for this interplay have been limited, which significantly hampers existing BHI studies. This study proposes an analytical modeling framework for estimating the BHI at the source-brain level. This analysis relies on the low-resolution electromagnetic tomography sources localization from scalp electrophysiological recordings. BHI is then quantified as the functional correlation between the intracortical sources and cardiovascular dynamics. Using this approach, we aimed to evaluate the reliability of BHI estimates derived from source-localized EEG signals as compared with prior findings from neuroimaging methods. The proposed approach is validated using an experimental dataset gathered from 32 healthy individuals who underwent standard sympathovagal elicitation using a cold pressor test. Additional resting state data from 34 healthy individuals has been analysed to assess robustness and reproducibility of the methodology. Experimental results not only confirmed previous findings on activation of brain structures affecting cardiac dynamics (e.g., insula, amygdala, hippocampus, and anterior and mid-cingulate cortices) but also provided insights into the anatomical bases of brain-heart axis. In particular, we show that the bidirectional activity of electrophysiological pathways of functional brain-heart communication increases during cold pressure with respect to resting state, mainly targeting neural oscillations in the δ $$ \delta $$ , ß $$ \beta $$ , and γ $$ \gamma $$ bands. The proposed approach offers new perspectives for the investigation of functional BHI that could also shed light on various pathophysiological conditions.

Electrophysiological correlation of auditory selective spatial attention in the "cocktail party" situation.

The auditory system can selectively attend to the target source in complex environments, the phenomenon known as the "cocktail party" effect. However, the spatiotemporal dynamics of electrophysiological activity associated with auditory selective spatial attention (ASSA) remain largely unexplored. In this study, single-source and multiple-source paradigms were designed to simulate different auditory environments, and microstate analysis was introduced to reveal the electrophysiological correlates of ASSA. Furthermore, cortical source analysis was employed to reveal the neural activity regions of these microstates. The results showed that five microstates could explain the spatiotemporal dynamics of ASSA, ranging from MS1 to MS5. Notably, MS2 and MS3 showed significantly lower partial properties in multiple-source situations than in single-source situations, whereas MS4 had shorter durations and MS5 longer durations in multiple-source situations than in single-source situations. MS1 had insignificant differences between the two situations. Cortical source analysis showed that the activation regions of these microstates initially transferred from the right temporal cortex to the temporal-parietal cortex, and subsequently to the dorsofrontal cortex. Moreover, the neural activity of the single-source situations was greater than that of the multiple-source situations in MS2 and MS3, correlating with the N1 and P2 components, with the greatest differences observed in the superior temporal gyrus and inferior parietal lobule. These findings suggest that these specific microstates and their associated activation regions may serve as promising substrates for decoding ASSA in complex environments.

Attention modulates early visual processing: An association between subjective contrast perception and early C1 ERP component.

The question of whether spatial attention can modulate initial afferent activity in area V1, as measured by the earliest visual event-related potential (ERP) component "C1", is still the subject of debate. Because attention always enhances behavioral performance, previous research has focused on finding evidence of attention-related enhancements in visual neural responses. However, recent psychophysical studies revealed a complex picture of attention's influence on visual perception: attention amplifies the perceived contrast of low-contrast stimuli while dampening the perceived contrast of high-contrast stimuli. This evidence suggests that attention may not invariably augment visual neural responses but could instead exert inhibitory effects under certain circumstances. Whether this bi-directional modulation of attention also manifests in C1 and whether the modulation of C1 underpins the attentional influence on contrast perception remain unknown. To address these questions, we conducted two experiments (N = 67 in total) by employing a combination of behavioral and ERP methodologies. Our results did not unveil a uniform attentional enhancement or attenuation effect of C1 across all subjects. However, an intriguing correlation between the attentional effects of C1 and contrast appearance for high-contrast stimuli did emerge, revealing an association between attentional modulation of C1 and the attentional modulation of contrast appearance. This finding offers new insights into the relationship between attention, perceptual experience, and early visual neural processing, suggesting that the attentional effect on subjective visual perception could be mediated by the attentional modulation of the earliest visual cortical response.

Altered EEG Microstates Dynamics in Individuals with Subthreshold Depression When Generating Negative Future Events.

Negative bias in prospection may play a crucial role in driving and maintaining depression. Recent research suggests abnormal activation and functional connectivity in regions of the default mode network (DMN) during future event generation in depressed individuals. However, the neural dynamics during prospection in these individuals remain unknown. To capture network dynamics at high temporal resolution, we employed electroencephalogram (EEG) microstate analysis. We examined microstate properties during both positive and negative prospection in 35 individuals with subthreshold depression (SD) and 35 controls. We identified similar sets of four canonical microstates (A-D) across groups and conditions. Source analysis indicated that each microstate map partially overlapped with a subsystem of the DMN (A: verbal; B: visual-spatial; C: self-referential; and D: modulation). Notably, alterations in EEG microstates were primarily observed in negative prospection of individuals with SD. Specifically, when generating negative future events, the coverage, occurrence, and duration of microstate A increased, while the coverage and duration of microstates B and D decreased in the SD group compared to controls. Furthermore, we observed altered transitions, particularly involving microstate C, during negative prospection in the SD group. These altered dynamics suggest dysconnectivity between subsystems of the DMN during negative prospection in individuals with SD. In conclusion, we provide novel insights into the neural mechanisms of negative bias in depression. These alterations could serve as specific markers for depression and potential targets for future interventions.

From pollution to solutions: Insights into the sources, transport and management of plastic debris in pristine and urban rivers.

River systems are important recipients of environmental plastic pollution and have become key pathways for the transfer of mismanaged waste from the land to the ocean. Understanding the sources and fate of plastic debris, including plastic litter (>5 mm) and microplastics (MPs) (<5 mm), entering different riverine systems is essential to mitigate the ongoing environmental plastic pollution crisis. We comprehensively investigated the plastic pollution in the catchments of two rivers in the Yangtze River basin: an urban river, the Suzhou section of the Beijing-Hangzhou Grand Canal (SZ); and a pristine rural river, the Jingmen section of the Hanjiang River (JM). The abundance of plastic pollutants in SZ was significantly higher than in JM: 0.430 ± 0.450 items/m3 and 0.003 ± 0.003 items/m3 of plastic litter in the water; 23.47 ± 25.53 n/m3 and 2.78 ± 1.55 n/m3 MPs in the water; and 218.82 ± 77.40 items/kg and 5.30 ± 1.99 items/kg of MPs in the sediment, respectively. Plastic litter and MPs were closely correlated in abundance and polymer composition. Overall, the polymer type, shape and color of MPs were dominant by polypropylene (42.5%), fragment (60.4%) and transparent (40.0%), respectively. Source tracing analysis revealed that packaging, shipping, and wastewater were the primary sources of plastic pollutants. The mantel analysis indicated that socio-economic and geospatial factors play crucial roles in driving the hotspot formation of plastic pollution in river networks. The composition of the MP communities differed significantly between the sediments and the overlying water. The urban riverbed sediments had a more pronounced pollutant 'sink' effect compared with the pristine rivers. These findings suggested that the modification of natural streams during urbanization may influence the transport and fate of plastic pollutants in them. Our results offer pivotal insights into effective preventive measures.

Occurrence, removal, and risk assessment of polycyclic aromatic hydrocarbons and their derivatives in typical wastewater treatment plants.

Wastewater treatment plants (WWTPs) have a certain removal capacity for polycyclic aromatic hydrocarbons (PAHs) and their derivatives, but some of them are discharged with effluent into the environment, which can affect the environment. Therefore, to understand the presence, sources, and potential risks of PAHs and their derivatives in WWTPs. Sixteen PAHs, three chlorinated polycyclic aromatic hydrocarbons (ClPAHs), three oxidized polycyclic aromatic hydrocarbons (OPAHs), and three methylated polycyclic aromatic hydrocarbons (MPAHs) were detected in the influent and effluent water of three WWTPs in China. The average concentrations of their influent ∑PAHs, ∑ClPAHs, ∑OPAHs, and ∑MPAHs ranged from 2682.50 to 2774.53 ng/L, 553.26-906.28 ng/L, 415.40-731.56 ng/L, and 534.04-969.83 ng/L, respectively, and the effluent concentrations ranged from 823.28 to 993.37 ng/L, 269.43-489.94 ng/L, 285.93-463.55 ng/L, and 376.25-512.34 ng/L, respectively. The growth of heat transport and industrial energy consumption in the region has a significant impact on the level of PAHs in WWTPs. According to the calculated removal efficiencies of PAHs and their derivatives in the three WWTPs (A, B, and C), the removal rates of PAHs and their derivatives were 69-72%, 62-71%, and 68-73%, respectively, and for the substituted polycyclic aromatic hydrocarbons (SPAHs), the removal rates were 41-49%, 31-40%, and 33-39%, respectively; moreover, the removal rates of PAHs were greater than those of SPAHs in the WWTPs. The results obtained via the ratio method indicated that the main sources of PAHs in the influent of WWTPs were the combustion of coal and biomass, and petroleum contamination was the secondary source. In risk evaluation, there were 5 compounds for which the risk quotient was considered high ecological risk. During chronic disease evaluation, there were 11 compounds with a risk quotient considered to indicate high risk. PAHs and SPAHs with high relative molecular masses in the effluent of WWTPs pose more serious environmental hazards than their PAHs counterparts.

The microbial communities of the rust layer were influenced by seawater microbial communities.

To reveal the responsible microorganisms of microbiologically-influenced-corrosion (MIC), using 16S rRNA and ITS sequencing techniques, we investigated the bacterial and fungal communities in rust layer and seawater. Results show that the corrosion-related genera of Erythrobacter, norank_f__Rhodothermaceae, and Acinetobacter bacteria, as well as Aspergillus fungi, were overrepresented in the rust layer, along with the Pseudoalteromonas and Marinobacterium bacteria in seawater, and Ramlibacter, Aquimarina, and Williamsia bacteria were first detected in the rust layer. SourceTracker analysis revealed that approximately 23.08% of bacteria and 21.48% of fungi originated from seawater. Stochastic processes governed the rust layer and seawater microbial communities, and network analysis showed coexistence and interaction among bacterial and fungal communities. These results indicate that the composition of microbial communities in the rust layer was influenced by the marine environmental microbial communities, which can provide basic data support for the control of MIC in marine-related projects.

Exploring the accumulation capacity of dominant plants based on soil heavy metals forms and assessing heavy metals contamination characteristics near gold tailings ponds.

Heavy metal contamination of soil commonly accompanies problems around gold mine tailings ponds. Fully investigating the distribution characteristics of heavy metals and the survival strategies of dominant plants in contaminated soils is crucial for effective pollution management and remediation. This study aims to investigate the contamination characteristics, sources of heavy metals (As, Cd, Pb, Hg, Cu, Zn, Cr, and Ni) in soils around gold mine tailings ponds areas (JHH and WZ) and to clarify the form distribution of heavy metals (As, Cd, Pb, Hg) in contaminated plots as well as their accumulation and translocation in native dominant plants. The results of the study showed that the concentrations of As, Pb, Cd, Cu, and Zn in soil exceeded the national limits at parts of the sampling sites in both study areas. The Nemerow pollution index showed that both study areas reached extreme high pollution levels. Spatial analysis showed that the main areas of contamination were concentrated around metallurgical plants and tailings ponds, with Cd exhibiting the most extensive area of contamination. In the JHH, As (74%), Cd (66%), Pb (77%), Zn (47%) were mainly from tailings releases, and Cu (52%) and Hg (51%) were mainly from gold ore smelting. In the WZ, As (42%), Cd (41%), Pb (73%), Cu (47%), and Zn (41%) were mainly from tailings releases. As, Cd, Pb, and Hg were mostly present in the residue state, and the proportion of water-soluble, ion-exchangeable, and carbonate-bound forms of Cd (19.93%) was significantly higher than that of other heavy metals. Artemisia L. and Amaranthus L. are the primary dominating plants, which exhibited superior accumulation of Cd compared to As, Pb, and Hg, and Artemisia L. demonstrated a robust translocation capacity for As, Pb, and Hg. Compared to the concentrations of other forms of soil heavy metals, the heavy metal content in Artemisia L correlates significantly better with the total soil heavy metal concentration. These results offer additional systematic data support and a deeper theoretical foundation to bolster pollution-control and ecological remediation efforts in mining areas.

Distribution, sources, and risk assessment of polycyclic aromatic hydrocarbons in surface soils and plants from industrial and agricultural areas, Junggar Basin, Xinjiang.

The contamination characteristics of Polycyclic Aromatic Hydrocarbons (PAHs) in different environmental functional areas are different. In this study, the contamination of PAHs in soils and common plants in typical mining and farmland areas in Xinjiang, China, was analyzed. The results showed that the contamination levels of PAHs in mining soils were significantly higher than those in farmland soils, and the mining soils were dominated by 4-5-ring PAHs and farmland soils by 3-4-ring PAHs. Analysis of their sources using a positive definite factor matrix model showed that PAHs in mining soils mainly originated from coal and natural gas combustion, and transportation processes; while farmland soils mainly came from biomass and coal combustion, and fossil fuel volatile spills. The cancer risk of PAHs in soils was evaluated using a combination of the Monte Carlo and the lifetime carcinogenic risk models, and the results showed that the overall level of cancer risk for mining soils was higher than that for farmland soils, and can put some people in high risk of cancer. For plant samples, except for individual crop samples, the contamination levels of mining plants and crops were similar, with 4-5-ring PAHs dominating in desert plants in mining areas and the highest proportion of 3-ring PAHs in crops in agricultural fields, and PAHs in both plants were mainly from biomass and coal combustion. The results of correlation analysis showed that 2-ring PAHs in crop roots were significantly positively correlated with it in corresponding soils, and some high-ring PAHs in crop leaves were significantly negatively correlated with it in corresponding soils. Therefore, there were significant differences in the pollution characteristics of PAHs in soils and common plants in mining and agricultural areas. Human health risks and ecological risks are mainly concentrated in mining areas, and appropriate intervention measures should be taken for pollution remediation.

Source apportionment of Cd in karst soil based on the delayed geochemical hazard model.

Soil Cd contamination has become increasingly prominent in karst regions. Studies have generally elucidated the natural sources of Cd in high-background areas and analyzed their migration and enrichment mechanisms. This study comprehensively analyzed the total content and speciation of Cd in high-background areas using the delayed geochemical hazard (DGH) model to identify the sources of Cd in the region. The results indicated that Cd in the research area followed a pattern of gradual geochemical disasters. In Quaternary soil, brick-red soil, and submergenic paddy soil with hydromorphic characteristics, 32%, 7.69%, and 30% of soil Cd samples exceeded the critical threshold of the releasable total amount, respectively. Based on the DGH model, it was concluded that Cd in this region was mainly influenced by human activities. Field investigations corroborated this conclusion and aligned with the findings. Compared with the traditional source apportionment receptor models (mainly PCA and PMF), the DGH model not only saved considerable time and cost, but also avoided uncertainty associated with the results and complex and varied data processing and computational analysis processes. Moreover, the DGH model was able to identify the factors having the greatest impact on the ecological risk of Cd in the research area, thus facilitating targeted prevention and management planning based on the characteristics or chemical properties of their elements.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city.

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Spatial-temporal distribution and source analysis of atmospheric particulate-bound cadmium from 1998 to 2021 in China.

Cadmium (Cd) is one of the most serious atmospheric heavy metal pollutants in China. PM2.5, PM10, and total suspended particle (TSP) are all important media for population Cd exposure. However, no studies so far have systematically explored the spatial and temporal distribution of atmospheric Cd bound to all these media in China, and the specific industrial sectors that contribute to the airborne Cd level are still unclear at present. In this study, we constructed the spatial and temporal distribution of PM (PM2.5, PM10, and TSP) binding Cd concentrations in China. Quantitative source apportionment of atmospheric Cd was carried out by analyzing the association of 23 industrial or energy-consuming sectors with Cd concentrations. Our results showed PM2.5, PM10, and TSP binding Cd concentrations decreased by 5.8%, 5.9%, and 6.1% per year at the national level, respectively. High PM-Cd concentrations were concentrated and distributed mainly in central and northwestern China. In addition, the medians of atmospheric PM2.5, PM10, and TSP binding Cd concentrations at the national level were 0.0026 µg/m3, 0.0036 µg/m3, and 0.0042 µg/m3, respectively. The main sources of PM-Cd include nonferrous metal smelting (Zn, Pb, Al) (47%), glass production (13%), pesticide production (12%), cement production (10%), and coal consumption (9%). This study analyzes comprehensively the atmospheric PM-bound Cd pollution, identifies the major industrial sectors that affect atmospheric Cd concentrations at the macroscale for the first time, and provides a basis for further reduction in the atmospheric Cd pollution.

Identification of sources and analysis of spatial distribution of soil heavy metals in northern China coal mining areas.

The mining and utilization of coal resources has not only promoted rapid economic development but also poses a potential threat to the ecological environment. The purpose of this study is to clarify the effects both of mining and land use types on the spatial distribution and particular sources of heavy metals in soil, using inverse distance weighted (IDW) and the Positive Matrix Factorization (PMF) model. A total of 99 topsoil and profile soil samples across different land use types and mining conditions were collected. The contamination of soil with Cd, Pb, and Hg in the research area was most severe, with the coefficient of variation (CV) of Hg being the largest, while also being heavily influenced by human activities. Severely polluted regions were mainly distributed in the center of the coal mining area, as well as near the highway. The contents of heavy metals for various land use patterns were ranked as follows: forestland > farmland > bare land > grassland > building land. Hg, Cd, Pb, Cr, and Zn had showed migration in the 0-60 cm depth range, and the enrichment factors (EFs) of Cd, Pb, Hg, and As in the soil profile were the most significant. The PMF demonstrated that the contributions of industrial activities and atmospheric deposition, transportation and mining activities, agricultural activities, and natural sources accounted for 31.25%, 28.13%, 22.24%, and 18.38%, respectively. The migration and deposition of atmospheric particulate matter from coal mining, transportation, and coal combustion under winds triggered heavy metal contamination in semi-arid areas of northern China. This phenomenon has important implications for the prevention and reduction of heavy metal pollution through various effective measures in coal-mining cities in northern China.

Distribution characteristics, source analysis and risk assessment of polycyclic aromatic hydrocarbons in sediments of Kuye River: a river in a typical energy and chemical industry zone.

This study systematically analyzed the distribution characteristics, sources, and ecological risk of polycyclic aromatic hydrocarbons (PAHs) in Kuye River sediments, located in an energy and chemical industry base in northern Shaanxi, China. The results that revealed the concentrations of 16 PAHs in the sediment ranged from 1090.04 to 32,175.68 ng∙g-1 dw, with the four-ring PAHs accounting for the highest proportion. Positive matrix factorization analysis (PMF) revealed the main sources of PAHs as incomplete fossil fuel combustion, biomass combustion, and traffic emissions. The total toxic equivalent concentration of BaP, risk quotient, and lifetime carcinogenic risk of PAHs suggested moderate to high contamination of PAHs in the area. The higher incremental lifetime carcinogenic risk (ILCR) indicated that PAH ingestion was the primary route of impact on public health, with children potentially being more susceptible to PAH exposure. This study can provide valuable theoretical support for implementing pollution prevention measures and ecological restoration strategies for rivers in energy and chemical industry areas.

Assessment of soil environmental capacity for heavy metals in Shantou City, Guangdong Province, China: source analysis and enrichment evaluation.

Most studies assessing soil environmental capacity (EC) often overlook the impact of heavy metal sources. Analyzing the sources of heavy metals (HMs) provides a better understanding of regional environmental capacity characteristics and their dynamic changes. The current study focuses on the surface soil of Shantou, using 511 soil samples to assess the soil environmental capacity. Results indicate that the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in Shantou's surface soil are notable, with lead moderately enriched and other metals lightly enriched. The principal component analysis (PCA) identifies five primary sources of heavy metals: mixed natural and agricultural sources, mixed agricultural and industrial sources, industrial sources, mining sources, and quarrying sources. The primary source contributing significantly to soil HM concentrations in Shantou City is a complex interplay between natural geological processes and extensive agricultural practices. In terms of static environmental capacity, Zn, Cr, Ni, Pb, Cu, As, Hg, and Cd are ranked in descending order. The overall environmental capacity for heavy metals in the soil is at a medium level, influenced by geological backgrounds. However, regions such as Yanhong Town, Guiyu Town, and Chendian Town face lower environmental capacities due to comprehensive human activities, posing certain risks. This study provides a scientific reference for forecasting, controlling soil heavy metal pollution, and improving soil quality and environmental capacity in Shantou City.

Evolution of hydrochemical characteristics and the influence of environmental background in the Hailar River basin, China.

Understanding the evolution of hydrochemical characteristics in river systems is essential for environmental assessment and water resource management. This study explores the spatiotemporal distribution and the determinants of hydrochemical characteristics in the Hailar River basin, China, over an extensive period. Our results revealed that CODMn and CODCr were the primary concerns for long-term river management, with exceedance rates of 42.92% and 50.62%, respectively. These exceedances were predominantly driven by interactions between riparian soils and surface water, rather than anthropogenic pollution, as suggested by the strong correlations between dissolved organic carbon and soil water-extractable organic carbon, and the limited human footprint in this region. Piper trilinear and Gibbs diagram analysis further revealed that long-term rack weathering shaped the basin's hydrochemical characteristics, resulting in distinct HCO3--Ca2+ and HCO3--Ca2+-Na+ signatures. In addition, APCS-MLR analysis identified that elevated of CODMn and CODCr levels were mainly attributed to the interactions with adjacent soils, which are extensively covered by forests and grasslands. In contrast, leaching and migration processes contributed significantly on total dissolved solids and total phosphorus. The study also found that environmental self-purification processes played a key role in regulating Fe concentrations. This investigation provides a nuanced understanding of the environmental background's influence on hydrochemistry and dissolved organic matter (DOM) in the Hailar River basin, which offers valuable insights and methodologies for the rational assessment of water quality and aquatic ecosystem health in similar riverine systems.

Water quality assessment and its pollution source analysis from spatial and temporal perspectives in small watershed of Sichuan Province, China.

Rapid socio-economic development has led to many water environmental issues in small watersheds such as non-compliance with water quality standards, complex pollution sources, and difficulties in water environment management. To achieve a quantitative evaluation of water quality, identify pollution sources, and implement refined management in small watersheds, this study collected monthly seven water quality indexes of four monitoring points from 2010 to 2023, and ten water quality indexes of 23 sampling points in the Shiting River and Mianyuan River which are tributaries of the Tuojiang River Basin. Then, water quality evaluation and pollution source analysis were conducted from both temporal and spatial perspectives using the Water Quality Index (WQI) method, the Absolute Principal Component Scores/Multiple Linear Regression (APCS-MLR) method, and the Positive Matrix Factorization (PMF) receptor modeling technique. The results indicated that except for total nitrogen (TN), the concentrations of other water quality indexes exhibited a decreasing trend, and all were divided into two obvious stages before and after 2016. Furthermore, the proportion of water quality grade of Good and above increased from 73.96 to 84.94% from 2010-2015 to 2016-2023, and the water quality grade of Good and above from upstream to downstream dropped from 100 to 23.33%. From the temporal scale, four and five pollution sources were identified in the first and second stages, respectively. The distinct TN pollutant is mainly affected by agricultural non-point sources (NPS), whose impact is enhanced from 17.76 to 78.31%. Total phosphorus (TP) was affected by the phosphorus chemical industry, whose contribution gradually weakened from 50.8 to 24.9%. From a spatial perspective, four and five pollution sources were identified in the upstream and downstream, respectively. Therefore, even though there are some limitations due to the data availability of water monitory and hydrology data, the proposed research framework of this study can be applied to the water environmental management of other similar watersheds.

A high-density EEG and structural MRI source analysis of the frequency following response to missing fundamental stimuli reveals subcortical and cortical activation to low and high frequency stimuli.

Pitch is a perceptual rather than physical phenomenon, important for spoken language use, musical communication, and other aspects of everyday life. Auditory stimuli can be designed to probe the relationship between perception and physiological responses to pitch-evoking stimuli. One technique for measuring physiological responses to pitch-evoking stimuli is the frequency following response (FFR). The FFR is an electroencephalographic (EEG) response to periodic auditory stimuli. The FFR contains nonlinearities not present in the stimuli, including correlates of the amplitude envelope of the stimulus; however, these nonlinearities remain undercharacterized. The FFR is a composite response reflecting multiple neural and peripheral generators, and their contributions to the scalp-recorded FFR vary in ill-understood ways depending on the electrode montage, stimulus, and imaging technique. The FFR is typically assumed to be generated in the auditory brainstem; there is also evidence both for and against a cortical contribution to the FFR. Here a methodology is used to examine the FFR correlates of pitch and the generators of the FFR to stimuli with different pitches. Stimuli were designed to tease apart biological correlates of pitch and amplitude envelope. FFRs were recorded with 256-electrode EEG nets, in contrast to a typical FFR setup which only contains a single active electrode. Structural MRI scans were obtained for each participant to co-register with the electrode locations and constrain a source localization algorithm. The results of this localization shed light on the generating mechanisms of the FFR, including providing evidence for both cortical and subcortical auditory sources.

Using Data-Driven Methods and Aging Information to Quantitatively Identify Microplastic Environmental Sources and Establish a Comprehensive Discrimination Index.

The global distribution of microplastics (MPs) across various environmental compartments has garnered significant attention. However, the differences in the characteristics of MPs in different environments remain unclear, and there is still a lack of quantitative analysis of their environmental sources. In addition, the inclusion of aging in source apportionment is a novel approach that has not been widely explored. In this study, we conducted a meta-analysis of the literature from the past 10 years and extracted conventional and aging characteristic data of MPs from 321 sampling points across 7 environmental compartments worldwide. We established a data-driven analysis framework using these data sets to identify different MP communities across environmental compartments, screen key MP features, and develop an environmental source analysis model for MPs. Our results indicate significant differences in the characteristics of MP communities across environments. The key features of differentiation were identified using the LEfSe method and include the carbonyl index, hydroxyl index, fouling index, proportions of polypropylene, white, black/gray, and film/sheet. These features were screened for each environmental compartment. An environmental source identification model was established based on these features with an accuracy of 75.1%. In order to accurately represent the single/multisource case in a more probabilistic manner, we proposed the MP environmental source index (MESI) to provide a probability estimation of the sample having multiple sources. Our findings contribute to a better understanding of MP migration trends and fluxes in the plastic cycle and inform effective prevention and control strategies for MP pollution.