Correlation Clustering Research Articles

PARÂMETROS SOCIAIS E AMBIENTAIS PARA O MANEJO DO USO PÚBLICO EM ECOSSISTEMAS MONTANHOSOS

ABSTRACT Pico do Marumbi State Park, in the mountains of Paraná, is the cradle of Brazilian mountaineering, sheltering several altitudinal ecosystems and endangered species. The elaboration and discussion of indicators to assist in public use management is urgent due to the vulnerability and pressure that these environments are subject to. It is also important to characterize the visitation profile and the correlation of accidents and incidents to adopt tools to protect visitors and nature. The data analyzed were extracted from official sources, registers, and records of incidents and accidents. Statistical treatment was adopted, in the analysis of variance and mean comparison tests, according to an entirely randomized design. Furthermore, Pearson’s correlation coefficient (r) and cluster analysis determined the ideal season for visitation. Statistical differences were verified in different periods, with July with the highest average visitation, 924.6 visitors, and February with the lowest average, with 539.4 visitors. The cluster analysis identified the ideal period for visitation, between June and September. The trails to Abrolhos, Olimpo, and Rochedinho had the highest average, with 965.8, 1,080.4, and 1,088.2 visitors. Of the occurrences attended, 75% were from October to May and 25% from June to September. Olimpo is the trail with the highest number of occurrences, about 45%. For 2018 and 2019, the park received 56% of visitors going on their first time. According to the results, adopting preventive and educational information, consorting with technical and climatic criteria, can better triage and safeguard the environment, users, and rescuers more effectively.

Multivariate studies and heavy metal pollution in soil from gold mining area

Mining generates large volumes of waste, which if not regulated can release toxic metals, causing widespread environmental contamination. This study focused on heavy metal contamination in topsoil within a mining area at Nangodi in the Northern Region of Ghana. A total of 24 soil samples were collected from the study area and control samples were analyzed for Hg, Pb, Cd, As, Cr, and Fe using atomic absorption spectroscopy. Results of Pollution Index estimations and Geo-accumulation index (Igeo) classified the soil samples as moderately contaminated to heavily contaminated. Soil samples were severely enriched with As and moderately enriched with b, and Hg. Multivariate analyses such as factor analysis and cluster analysis were employed to examine the relationship between the metals and also differentiate the influence of the natural background content of metals from that due to human activities. Factor analysis identified three polluted soil factor associations. Cadmium, Fe, As, and Pb associated with factor 1, were due to anthropogenic activities. The high intercorrelation revealed by As and Pb shows similarity in their sources. Factor two dominated by Hg is considered an anthropogenic component. Factor 3 correlated with Cr and can be considered a natural component. Correlation analysis and cluster analysis supported each other. Results from the bi-plots showed that sites S1, S8, S11, and S18, have similar metal composition as the control site. Heavy metal contents in soils sampled from Zones A and B have been influenced by the mining activities as seen from the associations of these sites in the bi-plots. The results are useful for metal source identification, and can contribute to monitoring and regulatory programs.

Value orientations and attitudes towards money among Russian and Chinese students as characteristics of the economic behavior of young people

Introduction. In the global economy, young people from the perspective of public administration are considered as intellectual capital. The purpose of this article is to conduct a comparative analysis of value orientations and attitudes towards money as indicators of economic behavior among Russian and Chinese students. Methods. The study used the following methods on a sample of 88 Russian and Chinese students: 1) Questionnaire by B. Klontz and T. Klontz “Monetary Attitudes” adapted by Bayazitova, T.A. Lapshova; 2) Portrait Value Questionnaire by S. Schwartz (PVQ-RR) adapted by T.P. Butenko, D.S. Sedova, A.S. Lipatova); 3) Questionnaire “Moral assessment of money” E.I. Gorbacheva and A.B. Kupreichenko. Statistical analysis of the data used the Mann-Whitney U test, Spearman's rank correlation coefficient and cluster analysis. Research results. In the process of conducting empirical analysis, significant differences were identified between Russian and Chinese students in the manifestations of value orientations such as: 1) reputation (0.036; p ≤ 0.05); 2) personal safety (0.04; p ≤ 0.05); 3) conformity - rules (0.026; p ≤ 0.05); 4) modesty (0.004; p ≤ 0.01). Russian students value their reputation and personal safety more; on the money avoidance scale, Chinese students have a significantly higher indicator compared to Russian students (0.026, p ≤ 0.05). As a result of the correlation analysis, significant relationships between the scales were found among Russian students: (p ≤ 0.05): 1) avoidance of money - hedonism (r = -0.300), modesty (r = 0.298), benevolence (r = -0.353); 2) money as status – modesty (r = -0.333); 3) worship of money - independence of thought (r = 0.375), independence of action (r = 0.331), hedonism (r = 0.341), power - dominance (r = 0.351), security - personal (r = 0.336), benevolence - duty ( r = 0.330). Among Chinese students, significant relationships were found for the following indicators: In the group of Chinese students, the following relationships were identified (p ≤ 0.05): 1) money as status - power - resources (r = 0.312), traditionalism (r = 0.302); 2) worship of money - independence of thought (r = 0.310), conformity - rules (r = 0.320), conformity - interpersonal (r = 0.372), modesty (r = 0.318); 3) vigilance regarding money - achievement (r = 0.315), power - resources (r = 0.309), conformity - rules (r = 0.304). The use of cluster analysis made it possible to identify positive and moral-conflict types of attitudes towards money among Russian students, and among Chinese students - morally uncertain and compromising-positive types of attitude towards money. Conclusion. As a result of the study, recommendations were proposed for the development and correction of indicators of economic behavior among young people: 1) introduction into educational practice in higher education of methods for developing students' knowledge in the field of financial literacy; 2) development of civic identity and patriotic feelings, which act as psychological support for students on the path to professional development and financial success; 3) developing students’ attitude towards money as a result of personal and professional self-realization; 4) providing information and education to foreign students in the field of economic behavior in Russia in order to successfully adapt to a foreign cultural environment.

Groundwater quality evaluation and pollution source apportionment using multivariate statistical analyses in Chuadanga municipality, Bangladesh

This is the first study to report the groundwater (GW) quality indices for drinking and irrigation purposes in Chuadanga Municipality, Bangladesh. GW samples were collected from 32 locations across the municipality's nine administrative wards. The physical parameters, such as total dissolved solids (TDS): 383 ppm, pH: 7.4, and electrical conductivity (EC): 583 μs/cm were reported, respectively. Among the detected chemical components, arsenic (As): 0.16 mg/L, iron (Fe): 0.77 mg/L, and manganese (Mn): 0.75 mg/L were found beyond the standard values. Geospatial analysis and multivariate analyses, such as correlation coefficient analysis (CCA), cluster analysis (CA), and principal component analysis (PCA), were performed to determine the potential sources of contaminants in the GW of the selected study areas. The water quality index (WQI) and heavy metal pollution index (HPI) suggest that most samples are unsuitable for drinking and irrigation. Following the water quality indices, CCA indicates the significant impact of As and Mn on water quality. The CA and PCA suggest geogenic, anthropogenic, and natural processes are mainly responsible for releasing those contaminants in GW.

Prediction-based spatial correlation clustering algorithm for efficient data reduction in wireless sensor network

Prediction-based spatial correlation clustering algorithm for efficient data reduction in wireless sensor network

Prediction-based spatial correlation clustering algorithm for efficient data reduction in wireless sensor network

Prediction-based spatial correlation clustering algorithm for efficient data reduction in wireless sensor network

Approximation algorithms for the lower bounded correlation clustering problem

Approximation algorithms for the lower bounded correlation clustering problem

Potential Phytoremediation of Aquatic Macrophyte Species for Heavy Metals in Urban Environments in the Southern Area of Brazil

This research investigated four different species of aquatic macrophytes with natural occurrence in an urban environment highly anthropized in Southern Brazil. The aim of the research was to compare the phytoremediation potential among the species E. anagallis, H. grumosa, H. ranunculoides, and S. montevidensis through Pearson´s correlation analysis and cluster analysis, using the heavy metal content identified through HNO3 - HClO4 and phytoremediation indexes. The results highlighted the bioconcentration factor (BCF) of H. ranunculoides, with outstanding results for Cu BCF = 667.09, Zn BCF = 149.93, Cd BCF = 26.85, Cr BCF = 31.77, Ni BCF = 35.47, and Pb BCF= 126.29. Additionally, H. grumosa and S. montevidensis were also highlighted, considering the potential phytoremoval (g ha−1). Therefore, this study demonstrates the tolerance and potential for removal of heavy metals Cu, Cr, Cd, Pb, Ni, and Zn by the evaluated aquatic macrophyte species and elucidates the outstanding potential of application in phytoremediation purposes.

Assessment of genotype by year interaction for yield components and physiological traits in cotton under drought stress using multivariate analysis and genetic parameters

The objective of this study was to identify genotype high yielding and drought-tolerant, by understanding the interaction GY pattern for yield, yield components and physiological traits in 24 cotton genotypes over five years under drought stress conditions using AMMI analysis, genetic parameters and multivariate analysis. All assessed traits were significantly impacted by genotypes and GY interaction using the AMMI model, with the exception of chlorophyll b by GY interaction. Meanwhile, seed cotton yield/plant, number of open bolls/plant, lint percentage, lint cotton yield/plant, and number of fruiting branches/plant were significantly affected by the year's factor. High BSH coupled with high GAM% was observed for all studied traits, indicating the heritability due to additive type of gene action and, the importance of these genotypes and the possibility of effective selection for drought-tolerant genotype development. A statistically significant correlation was discovered between cotton yield and most investigated traits under drought stress conditions. Direct selection can be done through these traits based on genetic parameters and Pearson's correlations analyses, which will be effective for drought tolerance and enhancing cotton yield. The results of our study's Pearson's correlation analysis, PCA and cluster analysis could be relevant and appropriate for studying drought tolerance mechanisms and cotton yield improvement. According to PCA and cluster analysis, the genotypes G20 and G19 followed by G5, G4 and G21 genotypes showed the best performance in response to drought stress regarding the yield, yield components and physiological-related traits. The previous genotypes could be used in future cotton breeding efforts in Egypt to promote drought tolerance, improve cotton productivity, and sustainable production during drought stress conditions.

Software Defect Prediction using Deep Learning by Correlation Clustering of Testing Metrics

The software industry has made significant efforts in recent years to enhance software quality in businesses. The use of proactively defect prediction in the software will assist programmers and white box testing in detecting issues early, saving time and money. Conventional software defect prediction methods focus on traditional source code metrics such as code complexities, lines of code, and so on. These capabilities, unfortunately, are unable to retrieve the semantics of source code. In this paper, we have presented a novel Correlation Clustering fine-tuned CNN (CCFT-CNN) model based on testing Metrics. CCFT-CNN can predict the regions of source code that contain faults, errors, and bugs. Abstract Syntax Tree (AST) tokens are extracted as testing Metrics vectors from the source code. The correlation among AST testing Metrics is performed and clustered as a more relevant feature vector and fed into Convolutional Neural Network (CNN). Then, to enhance the accuracy of defect prediction, fine-tuning of the CNN model is performed by applying hyperparameters. The result analysis is performed on the PROMISE dataset that contains samples of open-source Java applications such as Camel Dataset, Jedit dataset, Poi dataset, Synapse dataset, Xerces dataset, and Xalan dataset. The result findings show that the CCFT- CNN model increases the average F-measure by 2% when compared to the baseline model.

The Correlations of Barley Vitality and Storage Reserve Mobilization during Early Germination

The elucidation of the genetic relationship about storage reserve mobilization and enzymatic activity during barley germination is of particular importance for breeding and malt production. In addition to plant hormones such as gibberellic acid (GA) and abscisic acid (ABA), recent research has highlighted the importance of reactive oxygen species (ROS) signaling with hydrolase induction and plant growth. In this study, the correlation of barley vitality and mobilization of storage reserves during early seed germination was investigated. The activity of important hydrolases, as well as ROS-producing NADPH (nicotinamide adenine dinucleotide phosphate) oxidases, was monitored between six different cultivars. Associated gene expression from imbibition to germination was also analyzed by correlation analysis and cluster analysis. During early germination, the activities of α-amylase, limit dextrinase, and β-glucanase had significant positive correlations with each other and affected seed germination. Gene expression analysis showed that RbohB1 and RbohF1 (NADPH oxidases) had strong correlations with AMY1 (α-amylase) and LD (limit dextrinase). The GA synthesis gene GA3ox2 was found to have a significant correlation with protease genes Cys (cysteine protease) and Ser (serine protease), while the ABA synthesis gene NCED1 (nine-cis-epoxycarotenoid dioxygenase) had significant negative correlations with Cys and GA3ox2. Gene expression and enzyme assays indicated that NADPH oxidase, α-amylase, and limit dextrinase correlated well with barley vitality during early germination. The expression of the GA synthesis genes correlated well with glucanase and protease. These results provide information about barley gene regulation by analyzing correlations between genes.

Chemometric Approach to Pesticide Residue Analysis in Surface Water

Dimethachlor is an herbicide used for oilseed rape protection. Previous studies have demonstrated its high mobility in the soil, which could lead to water contamination. This research aimed to determine the occurrence of dimethachlor and its metabolites (dimethachlor ethanesulfonic acid ESA and dimethachlor oxalamic acid OA) in surface water using a recently developed analytical method. This article is one of the first to document dimethachlor and its metabolites’ presence in surface water samples. The samples were collected from the Danube river and Tisza river. The quantitative determination of dimethachlor and its metabolites in the obtained extracts was done by high-performance liquid chromatography. Descriptive statistical methods, including correlation analysis, cluster analysis, and principal component analyses, were utilized to analyze method validation experimental results. In addition, the artificial neural network (ANN) model was applied as an optimization tool. The developed ANN model adequately predicted observed variables, suggesting the optimum results were obtained at a pH value 7, spike value 1, and injection volume equal to 0.5 μL. The average concentrations in Danube River samples were 1.51 µg/L for OA 0.01 µg/L for ESA, and 0.63 µg/L for DMC, while the average concentrations of chloroacetanilide herbicides detected in Tisza River samples were 1.43 µg/L for OA, 0.08 µg/L for ESA and 1.82 µg/L for DMC.

Source analysis and risk evaluation of heavy metal in the river sediment of polymetallic mining area: Taking the Tonglüshan skarn type Cu-Fe-Au deposit as an example, Hubei section of the Yangtze River Basin, China

In this paper, 25 sampling points of overlying deposits in Tonglushan mining area, Daye City, Hubei Province, China were tested for heavy metal content to explore pollution characteristics, pollution sources and ecological risks of heavy metals in sediments. A geo-accumulation index method was used to evaluate the degree of heavy metal pollution in the sediment. The mean sediment quality guideline quotient was used for evaluating the ecological risk level of heavy metal in the sediment. And a method of correlation analysis, clustering analysis, and principal component analysis was used for preliminary analysis on the source of heavy metal in the sediment. It was indicated that there was extremely heavy metal pollution in the sediment, among which Cd was extremely polluted, Cu strongly contaminated, Zn, As, and Hg moderately contaminated, and Pb, Cr, and Ni were slightly contaminated. It was also indicated by the mean sediment quality guideline-quotient result that there was a high ecological risk of heavy metals in the sediment, and 64% of the sample sites had extremely high hidden biotoxic effects. For distribution, the contamination of branches was worse than that of the main channel of Daye Dagang, and the deposition of each heavy metal was mainly influenced by the distance from this sample site to the sewage draining exit of a tailings pond. The source analysis showed that the heavy metals in the sediment come from pollution discharging of mining and beneficiation companies, tailings ponds, smelting companies, and transport vehicles. In the study area, due to the influence of heavy metal discharging from these sources, the ecotoxicity of heavy metals in the sediment was extremely high, and Cd was the most toxic pollutant. The research figured out the key restoration area and elements for ecological restoration in the sediment of the Tonglüshan mining area, which could be referenced by monitoring and governance of heavy metal pollution in the sediment of the polymetallic mining area.©2022 China Geology Editorial Office.

Immobilization of Pb and Zn in Contaminated Soil Using Alumina–Silica Nano-Amendments Synthesized from Coal Fly Ash

To apply coal fly ash to the remediation of heavy-metal-contaminated soil, an alumina-silica nano-amendment (ASNA) was synthesized from coal fly ash and was used for the immobilization of lead and zinc in contaminated soil. The investigation on the synthesis of the ASNA shows that the ASNA can be obtained under a roasting temperature of 700 °C, a ratio of alkali to coal fly ash of 1.2:1, and a molar ratio of silicon to aluminum of 1:1. The ASNA could increase the soil pH and cation exchange capacity (CEC) and decrease the bioavailability of Pb and Zn. When the ASNA addition increased from 0 to 2%, the bioavailability (extracted by CaCl2) of Pb and Zn decreased by 47% and 72%, respectively. Moreover, the addition of the ASNA facilitated the transformation of Pb from a reducible fraction to oxidizable and residual fractions and Zn from an exchangeable fraction to a residual fraction. The correlation analysis and cluster analysis verify that the ASNA modulates the chemical speciation of heavy metals by increasing the soil's CEC and pH, thereby immobilizing heavy metals. It is expected that this study can provide a new method for the remediation of Pb- and Zn-contaminated soil.

Bioinformatics analysis of the correlation between m6A RNA methylation regulators and the immune infiltration and prognosis of bladder cancer.

To analyze the effect of N6-methyladenosine (m6A) RNA methylation regulators on the immune infiltration and prognosis of bladder cancer (BC). We explored the related signaling pathways and prognosis-related genes to provide candidate targets for the treatment and prognostic evaluation of BC. After downloading BC data from The Cancer Genome Atlas (TCGA) database, the expressions of m6A-related genes were obtained. We then performed correlation and sample cluster analysis of the m6A methylation regulator genes as well as difference comparison and survival analysis for the clustered patients using R software. Gene set enrichment analysis (GSEA) was carried out on cluster-grouped samples. Finally, the prognosis-related genes of BC among the m6A methylation regulators were screened. Genomic alterations in the m6A regulators were linked to a poor BC prognosis. HNRNPA2B1, HNRNPC, IGF2BP2, RBM15, YTHDF1, and YTHDF2 were found to be associated with advanced clinical stages of BC. Furthermore, the current study revealed that the levels of the m6A regulators were related to the expression levels and immune infiltration levels of immune regulators [immunosuppressive factors, immunostimulators, and major histocompatibility complex (MHC) molecules] in BC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggested that in addition to the relevant immune responses, m6A regulators were involved in the poor prognosis of BC via their participation in blood vessels through regulatory RNA binding, telomeric DNA binding, microRNA (miRNA) binding, negative regulation of messenger RNA (mRNA) processing, negative regulation of DNA biosynthesis, branches of morphogenesis, positive regulation of the Notch receptor target gene transcription, etc. The expression of m6A RNA methylation regulators is closely linked to immune infiltration and prognosis in BC. Thus, it can be utilized as a potential molecular target for the treatment and prognostic assessment of BC.

Colocalization of cortical diffusivity changes and microglial activation in dementia

AbstractBackgroundThere is growing evidence that microglial activation plays a crucial role in the early pathological changes reported in Alzheimer’s disease (AD). Multimodal neuroimaging can be used to detect micro‐ and macrostructural alterations together with molecular imaging to quantify metabolism and proteins expression. Diffusivity map, reflecting neuronal integrity, can be derived from diffusion‐weighted imaging, and is thought to be increased in AD following pathological alterations. We hypothesised that changes in diffusivity could be colocalized with microglial activation at different stages of the disease.Method56 patients (mean age=70.4, SD=8.5) cognitively normal (CN, n=15), with mild cognitive impairment (MCI, n=28) and with AD (n=12) were included in this study. All participants underwent diffusion tensor imaging (DTI), amyloid PET ([18F]flutemetamol) and TSPO PET ([11C]PBR28). DTI data were processed with FSL v.6.0 to compute mean diffusivity (MD) maps. Standard uptake ratio (SUVR) values were calculated in SPM12 to identify the amyloid deposition and microglial activation within cortical regions. Amyloid status (Aβ‐positive/Aβ‐negative) was determined from processed data using a cerebellar gray matter ratio with a binding value greater than the CN mean+2SD. Z score maps of MD and [11C]PBR28 SUVR were computed using CN amyloid negative participants as reference. Z score maps were then correlated using SPM8 and the BPM toolbox. Significance was set at a threshold of p<0.05 with an extended threshold of 50 voxels.ResultWe found a significant positive correlation clusters between MD and PBR28‐SUVR Z score maps (higher diffusivity correlated with higher microglial activation) in MCI amyloid negative subjects in the temporal lobe (coordinates: 28 ‐3 ‐32, corrected p<0.001, k=7363). In MCI amyloid positive subjects, we found positive correlation in the parietal lobe (coordinates: ‐47 ‐41 39, corrected p=0.008, k=5712).ConclusionWe found colocalized diffusivity and microglial changes in the early stage of the disease, in the temporal lobe of MCI amyloid negative participants and in later stages of the disease, in the parietal lobe of MCI amyloid positive participants. These results suggest the potential of DTI diffusivity and microglial activation imaging in detecting early neuronal damage occurring in dementia.

Linking neuroanatomical abnormalities in autism spectrum disorder with gene expression of candidate ASD genes: A meta-analytic and network-oriented approach.

Autism spectrum disorder (ASD) is a set of developmental conditions with widespread neuroanatomical abnormalities and a strong genetic basis. Although neuroimaging studies have indicated anatomical changes in grey matter (GM) morphometry, their associations with gene expression remain elusive. Here, we aim to understand how gene expression correlates with neuroanatomical atypicalities in ASD. To do so, we performed a coordinate-based meta-analysis to determine the common GM variation pattern in the autistic brain. From the Allen Human Brain Atlas, we selected eight genes from the SHANK, NRXN, NLGN family and MECP2, which have been implicated with ASD, particularly in regards to altered synaptic transmission and plasticity. The gene expression maps for each gene were built. We then assessed the correlation between the gene expression maps and the GM alteration maps. Lastly, we projected the obtained clusters of GM alteration-gene correlations on top of the canonical resting state networks, in order to provide a functional characterization of the structural evidence. We found that gene expression of most genes correlated with GM alteration (both increase and decrease) in regions located in the default mode network. Decreased GM was also correlated with gene expression of some ASD genes in areas associated with the dorsal attention and cerebellar network. Lastly, single genes were found to be significantly correlated with increased GM in areas located in the somatomotor, limbic and ganglia/thalamus networks. This approach allowed us to combine the well beaten path of genetic and brain imaging in a novel way, to specifically investigate the relation between gene expression and brain with structural damage, and individuate genes of potential interest for further investigation in the functional domain.

Geochemical Characteristics of Soils to the Impact of Diamond Mining in Siberia (Russia)

This article presents the results of long-term research and monitoring of the soil cover exposed to the impact of the mining and processing plant developing diamond deposits in the northeast of Siberia. The soil collection includes 436 samples of different types of Cryosols. Soil pH; soil organic carbon (SOC); granulometric composition; and mobile forms of Pb, Ni, Mn, Cd, Co, Cr, Zn, Cu, and As were identified in the samples. Multivariate statistics of the correlation matrix, clustering analysis (CA), and principal component analysis (PCA) were used to determine the sources of heavy metals. The intensity of the accumulation of chemical elements in the soil was assessed using calculated concentration coefficients (Kc) and the index of total contamination of the soil cover (Zc). In the study area, Cryosols are characterized by biogenic accumulation of Ni, Mn, and Cd in the upper soil layer and Cr, Ni, Co, Mn, and Cu in the suprapermafrost horizon. Correlation matrix, CA, and PCA revealed three distinct sources that could be considered for the investigated potentially toxic elements (PTEs): anthropogenic, lithogenic, and the source which comes from a mixed contribution of anthropogenic and lithogenic factors. The most anthropogenic contribution in the heavy metals in the study area appears in Zn, Cd, As, and Pb. The assessment interpreted that origin of Mn in the area is most likely to be a natural source. The content of Co, Cr, and Ni are controlled by both lithogenic control and anthropogenic sources. Active accumulation of mobile forms of Mn, Zn, and Ni with anomalously high concentration coefficients can be traced in the soils in the impact zone of mining operations. Anthropogenic soil contamination is spread over an area of 260 km2.

The relationship between cognition and functioning in Bipolar Disorder: An investigation using functional imaging during working memory performance

The psychosocial functioning of individuals suffering from bipolar disorder (BD) has a significant impact on prognosis and quality of life. The aim of this study was to assess brain functional correlates of psychosocial functioning in BD individuals during the performance of a working memory task. Sixty-two subjects (31 euthymic BD individuals and 31 matched healthy controls) underwent structural and functional magnetic resonance imaging scanning while performing the 1- and 2-back versions of the n-back task (1-back and 2-back). The Functional Assessment Short Test (FAST) and its subdomains were used to assess functioning. Whole brain analysis revealed only overall activation differences between BD patients and healthy controls, but the patients showed failure of de-activation in the medial frontal cortex. Six clusters of significant inverse correlation with the FAST scores were found in the dorsolateral prefrontal cortex, the superior parietal cortex, and temporo-occipital regions bilaterally, and in the left inferior frontal cortex. Cognitive and occupational functioning were the subdomains most significantly associated with brain activation in these clusters. The results suggest that poor psychosocial functioning in BD individuals is associated with hypoactivation in a range of cortical regions, including the fronto-parietal working memory network and inferior temporo-occipital regions.

Organic carbon and silt determining subcritical water repellency and field capacity of soils in arid and semi-arid region

Soil water repellency (SWR) is frequently observed in different types of land use and climates. Since SWR potentially enhances the difficulty of water infiltration in soil, the phenomenon can severely impact the water use of plants in arid regions. Therefore, understanding the origin of SWR is crucial in arid and semi-arid regions. This study investigated the fundamental and hydrological properties of soils in three arid ecosystems (desert, farmland, and forest). Analysis was done to determine any potential links between these properties, vegetation cover, and the severity of SWR. It was found that SWR was positively correlated with soil organic carbon (SOC), silt content, and field capacity of soil, where the SWR was in subcritical SWR range. The linear correlation and hierarchical clustering analysis confirmed that the SOC and silt content was the critical factor affecting the occurrence and persistence of SWR. The major source of organic carbon and nutrients to the soil was vegetation, which also had an impact on the distribution of soil carbon. The most striking observation was that the silt content was strongly correlated with both field capacity (r = 0.817, p = 0.001) and SWR (r = 0.710, p = 0.010), which can be attributed to the SOC on silt. In arid and semi-arid regions, the specific surface area of silt was relatively larger than that of sand. Meanwhile, compared to the clay in soil, the proportion of silt was much higher. The results imply that silt could significantly affect the soil hydrological properties and that silt content could serve as a new proxy for predicting water repellency in arid and semi-arid regions.