Pattern Correlation Analysis Research Articles

Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.

Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, resulting in lower BCI performance. Therefore, this study innovatively used MI and high-frequency steady-state visual evoked potential (SSVEP) to construct a friendly and natural hybrid BCI paradigm. Specifically, the stimulation interface sequentially presented decomposed action pictures of the left and right hands gripping a ball, with the pictures flashing at specific stimulation frequencies (left: 34 Hz, right: 35 Hz). Integrating soft robotic glove as feedback, we established a comprehensive "peripheral - central - peripheral" hand rehabilitation system to facilitate the hand rehabilitation of patients. Filter bank common spatial pattern (FBCSP) and filter bank canonical correlation analysis (FBCCA) algorithms were used to identify MI and SSVEP signals, respectively. Additionally, we proposed a novel fusion algorithm to decide the final output of the system. The feasibility of the proposed system was validated through online experiments involving 12 healthy subjects and 9 stroke patients, achieving accuracy rates of 95.83 ± 6.83% and 63.33 ± 10.38, respectively. The accuracy of MI and SSVEP in 12 healthy subjects reached 81.67 ± 15.63% and 95.14 ± 7.47%, both lower than the accuracy after fusion, these results confirmed the effectiveness of the proposed algorithm. The accuracy rate was more than 50% in both healthy subjects and patients, confirming the effectiveness of the proposed system.

True and false memories for spatial location evoke more similar patterns of brain activity in males than females

ABSTRACT True and false memories recruit a number of shared brain regions; however, they are not completely overlapping. Extensive sex differences have been identified in the brain during true memories and, recently, we identified sex differences in the brain during false memories. In the current fMRI study, we sought to determine whether sex differences existed in the location and extent of overlap between true and false memories. True and false memories activated a number of shared brain regions. Compared to females, males produced a greater number of overlapping brain regions (8 versus 2 activations for males and females, respectively) including the prefrontal cortex, parietal cortex, and early/late visual processing cortices (including V1) in males and prefrontal and parietal cortices in females. Males had significantly higher similarity between true and false memory activation maps, revealed by our novel multi-voxel pattern correlation analysis. Moreover, higher similarity between true and false memory activation maps was associated with higher false memory rates. The current results suggest that true and false memories are more similar in males than females. The significant brain–behavior relationship also suggests that males may be more susceptible to false memory errors due to their highly similar true memory–false memory cortical representations.

Chronic exposure to pesticides disrupts the bacterial and fungal co-existence and the cross-kingdom network characteristics of honey bee gut microbiome

Gut microbiome communities have a significant impact on bee health and disease and have been shown to be shaped by a variety of factors, including exposure to pesticides and inhive chemicals. However, it is unknown whether pesticide exposure affects the coexistence and cross-kingdom network parameters of bee gut microbiome communities because microbes may compete in the gut environment under different stressors. Therefore, we conducted additional analysis of the microbiome data from our previous study in which we discovered that exposure to two novel insecticides flupyradifurone (FPF) and sulfoxaflor (Sulf) or/and a fungicide, azoxystrobin (Azoxy) caused dysbiosis of bee gut microbiota that was associated with an increase in the relative abundance of opportunistic pathogens such as Serratia marcescens. We investigated for the first time the potential cross-kingdom fungal-bacterial interactions using co-occurrence pattern correlation and network analysis. We discovered that exposure to FPF or Sulf alone or in combination with Azoxy fungicide influenced the co-existence patterns of fungal and bacterial communities. Significant differences in degree centrality, closeness centrality, and eigenvector centrality distribution indices were also found in single and double-treatment groups compared to controls. The effects of FPF and Sulf alone on cross-kingdom parameters (bacterial to fungal node ratio, degree of centrality, closeness centrality, and eigenvector centrality) were distinct, but this was reversed when they were combined with Azoxy fungicide. The fungal and bacterial hub taxa identified differed, with only a few shared hubs across treatments, suggesting microbial cross-kingdom networks may be disrupted differently under different stressors. Our findings add to our understanding of pesticide effects on the bee gut microbiome and bee health in general, while also emphasizing the importance of cross-kingdom network analysis in future microbiome research.

Remote monitoring and control of the status of transformers in distribution electrical networks

RELEVANCE. One of the most important expected effects of digitalization of objects of the power grid complex of the Russian Federation is to increase the level of reliability of its functioning. In this regard, research and development in this direction is undoubtedly relevant. THE PURPOSE. To propose a mathematical model for monitoring dangerous developing defects in power oil-filled transformers, this would meet the properties of predictability and adaptability. Based on the model, to develop a decision-making algorithm for long-term reliable operation oftransformers. METHODS: Methods of statistical pattern recognition theory, correlation analysis and Bayesian classification will be used to solve the problems to ensure high reliability of diagnostic assessments, validity and effectiveness of operational solutions. RESULTS. A predictive model was obtained and verified in the form of a correlation function of a sign of a faulty state of a transformer from the values of its electrical load. An event tree has been formed that restores the causal relationship between the result of monitoring the transformer, the defect sign and the operational decision being made. Based on the event tree and diagnostic evaluation criteria, a control algorithm is implemented, with the help of which calculations are performed confirming the effectiveness of the proposed approach. CONCLUSION. The possibility of effective application of the developed defect recognition model and operational control algorithm as tools of industrial technology of the Internet of Things is illustrated, in particular, when organizing remote diagnostic monitoring of oil-filled transformer equipment at substations of the distribution grid area.

Factors Determining Concurrent Reclamation and Abandonment of Cultivated Land on the Qinghai-Tibet Plateau

The Tibetan Plateau has important functions, such as water and soil conservation, wind and sand control, carbon fixation, and biodiversity protection. Agricultural development on the Tibetan Plateau not only maintains local food security but is also related to the important ecological functions in China and Asia. This study analyzed the spatial distribution of reclaimed and abandoned cultivated land in the Yarlung Zangbo–Lhasa–Nyangqu River (YLN) region on the Qinghai-Tibet Plateau from 2000 to 2020 using high-resolution remote sensing data. Additionally, this study explored the factors influencing spatial distribution patterns using a landscape pattern index and correlation analysis. The results showed that: (1) From 2000 to 2020, cultivated land reclamation and abandonment coexisted in the YLN region. The total areas of reclaimed and abandoned cultivated land were 558.57 and 196.85 km2, and their growth and abandonment rates were 25.47 and 8.29%, respectively. (2) Apparent regional differences existed in the distribution of reclaimed and abandoned lands. The reclaimed land was concentrated in the northeast and southwest of YLN, whereas abandoned land was scattered, with relatively higher fragmentation than in the former. (3) Climate and location affected the spatial distribution of both land types, with precipitation, aspect, and SOM having less influence and temperature, elevation, slope, traffic conditions, and farming radius having relatively prominent influence. (4) Socioeconomic factors were the main factors driving changes in cultivated land area in the region, wherein grain output and the number of livestock positively impacted reclamation and abandonment, relatively more significantly for reclamation. This study helps to understand the land use changes and their impacts in the YLN region on the Qinghai-Tibet Plateau. It is of great significance for formulating appropriate sustainable development strategies and land management policies, and ensuring the sustainable development of local ecological environment and cultivated land resources utilization.

Identification of Reference Genes for Reverse Transcription-Quantitative PCR Analysis of Ginger Under Abiotic Stress and for Postharvest Biology Studies.

Gene expression analysis largely improves our understanding of the molecular basis underpinning various plant biological processes. Stable reference genes play a foundational role during the normalization of gene expression levels. However, until now, there have been few reference genes suitable for ginger reverse transcription-quantitative PCR (RT-qPCR) research. In this study, 29 candidate reference genes with stable expression patterns across multiple ginger tissues and 13 commonly used reference genes were selected to design RT-qPCR primers. After amplification specificity validation, 32 candidates were selected and further evaluated by RT-qPCR using samples from various organs subjected to NaCl, drought, heat, waterlogging, and chilling stress. Four strategies, including delta-CT, BestKeeper, geNorm, and NormFinder, were used to rank the stability of reference genes, and the ranks produced by these four strategies were comprehensively evaluated by RefFinder to determine the final rank. Overall, the top three stability reference genes indicated by RefFinder were RBP > ATPase > 40S_S3. Their expression pattern correlation analysis showed that the coefficients among each pair of RBP, ATPase, and 40S_S3 were larger than 0.96, revealing consistent and stable expression patterns under various treatments. Then, the expression of three pathogenesis-related (PR) genes and seven MYB genes in rhizomes during postharvest storage and subjected to pathogen infection was normalized by RBP, ATPase, 40S_S3, RBP and ATPase, ATPase and 40S-S3, and RBP and 40S-S3. The results showed that PR and MYB genes were induced by postharvest deterioration and pathogen infection. The correlation coefficients of RBP/ATPase, RBP/40S_S3, ATPase/40S_S3, RBP and ATPase/ATPase and 40S-S3, RBP and ATPase/RBP and 40S-S3, and ATPase and 40S-S3/RBP and 40S-S3 were 0.99, 0.96, 0.99, 0.99, 1.00, and 1.00, respectively, which confirmed the stability of these three reference genes in postharvest biology studies of ginger. In summary, this study identified appropriate reference genes for RT-qPCR in ginger and facilitated gene expression studies under biotic and abiotic stress conditions.

Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1

Abstract. The performance of the Weather Research and Forecasting (WRF) model version 3.8.1 at convection-permitting scale is evaluated by means of several sensitivity simulations over southern Peru down to a grid resolution of 1 km, whereby the main focus is on the domain with 5 km horizontal resolution. Different configurations of microphysics, cumulus, longwave radiation, and planetary boundary layer schemes are tested. For the year 2008, the simulated precipitation amounts and patterns are compared to gridded observational data sets and weather station data gathered from Peru, Bolivia, and Brazil. The temporal correlation of simulated monthly accumulated precipitation against in situ and gridded observational data show that the most challenging regions for WRF are the slopes along both sides of the Andes, i.e. elevations between 1000 and 3000 m above sea level. The pattern correlation analysis between simulated precipitation and station data suggests that all tested WRF setups perform rather poorly along the northeastern slopes of the Andes during the entire year. In the southwestern region of the domain the performance of all setups is better except for the driest period (May–September). The results of the pattern correlation to the gridded observational data sets show that all setups perform reasonably well except along both slopes during the dry season. The precipitation patterns reveal that the typical setup used over Europe is too dry throughout the entire year, and that the experiment with the combination of the single-moment 6-class microphysics scheme and the Grell–Freitas cumulus parameterization in the domains with resolutions larger than 5 km, suitable for East Africa, does not perfectly apply to other equatorial regions such as the Amazon basin in southeastern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell-Freitas cumulus parameterization tends to overestimate precipitation over the northeastern slopes of the Andes, but enforces a positive feedback between the soil moisture, air temperature, relative humidity, mid-level cloud cover and, finally, precipitation. Hence, this setup provides the most accurate results over the Peruvian Amazon, and particularly over the department of Madre de Dios, which is a region of interest because it is considered a biodiversity hotspot of Peru. The robustness of this particular configuration of the model is backed up by similar results obtained during wet climate conditions observed in 2012.

Effects of Urbanization on Landscape Patterns in the Middle Reaches of the Yangtze River Region

The middle reaches of the Yangtze River region (MRYRR) are China’s first trans-regional urban agglomeration, located in the center of the Yangtze River Economic Belt. The MRYRR is an important ecological reserve, and its land cover changes are affected by both socio-economic development and geographical environment. In this paper, Landsat ETM/TM/OLI remote sensing images were used to monitor land use and landscape patterns from 1990 to 2015. Through supervised classification, land use transfer matrix, landscape pattern metrics and correlation analysis, the spatial-temporal patterns of land use change and its relationship with socio-economic in the study area were revealed. The results showed that: (1) the main land use types in the study area were cropland (CL) and forestland (FL), accounting for more than three-quarters of the study area. During the study period, built-up land (BL) increased, CL decreased, FL increased first and then decreased; (2) the BL expanded mainly by occupying CL and FL, and regional landscape pattern was gradually fragmented, with complex patch shape and increasing diversity and heterogeneity. Among them, the BL is gradually gathered, and the FL and CL are gradually fragmented; (3) in the past 25 years, the urbanization process in this region has been obvious, and the Gross Domestic Product (GDP) has increased by 36 times. The socioeconomic variables were positively correlated with BL, orchard (OL) and Shannon diversity index (SHID), and negatively correlated with CL, Wasteland (WL), mean patch size (MPS) and contagion size (CONTAG). The results showed that the urbanization development has a great impact on the region, and the ecological protection task is still challenging. It is necessary to protect high-quality cropland and draw a red line for ecological protection. We should strengthen the construction of ecological corridors and ecological nodes to adapt to regional sustainable development.

Adaptive Upgradation of Personalized E-Learning Portal using Data Mining

Implementation of data mining techniques in e-learning is a trending research area, due to the increasing popularity of e-learning systems. E-learning systems provide increased portability, convenience and better learning experience. In this research, we proposed two novel schemes for upgrading the e-learning portals based on the learner’s data for improving the quality of e-learning. The first scheme is Learner History-based E-learning Portal Up-gradation (LHEPU). In this scheme, the web log history data of the learner is acquired. Using this data, various useful attributes are extracted. Using these attributes, the data mining techniques like pattern analysis, machine learning, frequency distribution, correlation analysis, sequential mining and machine learning techniques are applied. The results of these data mining techniques are used for the improvement of e-learning portal like topic recommendations, learner grade prediction, etc. The second scheme is Learner Assessment-based E-Learning Portal Up-gradation (LAEPU). This scheme is implemented in two phases, namely, the development phase and the deployment phase. In the development phase, the learner is made to attend a short pre training program. Followed by the program, the learner must attend an assessment test. Based on the learner’s performance in this test, the learners are clustered into different groups using clustering algorithm such as K-Means clustering or DBSCAN algorithms. The portal is designed to support each group of learners. In the deployment phase, a new learner is mapped to a particular group based on his her performance in the pre training program.

Spatial distribution pattern and interspecific correlation analysis of main species of Rosaceae in a deciduous broad-leaved forest in Yaoluoping

Spatial distribution pattern and interspecific correlation analysis of main species of Rosaceae in a deciduous broad-leaved forest in Yaoluoping

A New Metric to Diagnose Precipitation Distribution in Transitioning Tropical Cyclones

A new coupled dynamic and thermodynamic metric is developed based on the Eady Moist Baroclinic Growth Rate (EMBGR), to discriminate between left-of-track (LOT) and right-of-track (ROT) precipitation distributions in transitioning tropical cyclones (TCs). LOT events pose a major flood risk even when a TC tracks along a coastline or just offshore, as flash flooding can occur hundreds of kilometers inland from the cyclone center. The EMBGR can improve human-produced quantitative precipitation forecasts (QPF) because it is dependent on relatively well-forecast large-scale mass fields. The ability of the EMBGR to identify precipitation distribution is first explored in a case study of TC Matthew (2016), using reanalysis and numerical model forecasts. Subsequently, a composite analysis of 36 years (1979–2014) of United States landfalling TCs using reanalysis data shows that the EMBGR is an effective discriminator between LOT and ROT distributions. The utility of the EMBGR is quantified using a pattern correlation analysis for both TC Matthew and the composites. Finally, a conceptual schematic is developed for LOT cases so that forecasters can most effectively utilize the EMBGR to improve human QPF skill during transitioning TCs.

Different patterns of cortical activity in females and males during spatial long-term memory

It is generally assumed that identical neural regions mediate the same cognitive functions in females and males. However, anatomic and molecular sex differences exist in the brain, including in regions associated with long-term memory, which suggests there may be functional differences. The present functional magnetic resonance imaging (fMRI) investigation aimed to identify the differences and similarities in brain activity between females and males during spatial long-term memory. During encoding, abstract shapes were presented to the left or right of fixation. During retrieval, shapes were presented at fixation and participants made “old-left” or “old-right” judgments. For both females and males, spatial memory hits versus misses produced activity in regions commonly associated with visual long-term memory; however, the activations were almost completely distinct between the sexes. An interaction analysis revealed sex-specific activity for males in visual processing regions, the left putamen, the right caudate nucleus, and bilateral cerebellum, and sex-specific activity for females in the parietal cortex. A targeted anatomic region-of-interest (ROI) analysis identified sex-specific activity for males and females in the left hippocampus and language processing cortex, respectively. A multi-voxel pattern correlation analysis within functional ROIs between all pairs of participants showed greater within-sex than between-sex correlations, indicating the differential activations were due to sex differences rather than other individual differences between groups. These results indicate that spatial long-term memory is mediated by largely different brain regions in females and males. These findings have major implications for the field of cognitive neuroscience, where it is common practice to collapse across sex.

KIBRA polymorphism modulates gray matter volume to influence cognitive ability in the elderly

Genetic variation in the kidney and brain expressed protein (KIBRA) rs17070145 gene has been linked to episodic memory and cognitive aging; yet, the neural mechanism underlying this association remains to be fully understood. Using the magnetic resonance imaging (MRI) technique, this study investigated the effect of KIBRA polymorphism on gray matter volume in 37 healthy, Chinese adults from the older population. Voxel-based morphometry (VBM) analysis revealed that KIBRA gene selectivity influences the prefrontal cortex and the parahippocampal cortex. The gray matter volume (GMV) in these structures is significantly lower in KIBRA C-allele carriers than in TT carriers. Moreover, multi-voxel pattern correlation analysis revealed that decreased prefrontal GMV could in turn affect individual cognitive function in C-allele carriers; whereas, TT individuals utilized more integrated gray matter volume in whole-brain voxels to achieve relatively better cognitive function. Overall, the findings suggest that the KIBRA rs17070145 polymorphism modulates gray matter volume, which in turn further influences cognitive function in the elderly.

近25年长江中游地区土地利用时空变化格局与驱动因素

PDF HTML阅读 XML下载 导出引用 引用提醒 近25年长江中游地区土地利用时空变化格局与驱动因素 DOI: 10.5846/stxb201809302138 作者: 作者单位: 上海交通大学,上海交通大学,上海交通大学,北京林业大学,北京林业大学,上海交通大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2017YFC0505500，2017YFC0505501） Temporal and spatial variations of land use and the driving factors in the middle reaches of the Yangtze River in the past 25 years Author: Affiliation: ShangHai Jiao Tong University,ShangHai Jiao Tong University,ShangHai Jiao Tong University,Shanghai Academy of forestry,Shanghai Academy of forestry,ShangHai Jiao Tong University Fund Project: National key R & D plan (2017YFC0505500, 2017YFC0505501) * Communication author Corresponding author. E-mail: chjliu@sjtu.edu.cn 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:长江中游地区（湖北省、湖南省和江西省）位于长江经济带中心，是我国"中三角城市群"所在地，也是国家"两屏三带"生态安全战略的重点区域，其土地利用变化受地理环境制约和社会经济发展的影响，也与未来区域可持续发展密切相关。根据1990、2000、2010和2015年Landsat TM遥感影像数据，采用景观格局分析、梯度分析及相关性分析方法，揭示近25年土地利用时空变化格局及其与社会经济因素的关系。研究表明：（1）研究区耕地与林地为主体景观，分别占30%、50%，建设用地占比 < 3%，具有重要生态功能的土地利用类型（林地、灌木、水体、草地、果园）占比达67%。（2）沿中心城区-边缘区梯度，各土地利用类型表现出明显的空间特征，建设用地和耕地面积占比显著减小，破碎化程度增加，而林地呈整体化趋势。（3）近25年来，该区耕地、林地分别减少1.06%、0.49%，建设用地增加1.08%，整体景观破碎化程度加重、景观多样性升高；除林地外，其它地类变化均与社会经济因素（人口、农业人口、非农业人口、GDP、人均GDP、城市化水平、三大产业产值）显著相关。这些结果表明，与沿海地区相比，近25年长江中游地区土地利用变化较小，还有着较好的基于提供生态系统服务的土地利用基础；但生态保护任务仍然艰巨，需划定生态保护红线，保护优质耕地，控制城市扩展规模，加强生态廊道、节点的建设，增强区域景观生态功能，以便满足未来长江经济带可持续发展的需要。 Abstract:The middle reaches of the Yangtze River (including Hubei, Hunan, and Jiangxi Provinces) and the "Central Triangle City Group" are located in the center of the Yangtze River Economic Belt and are one of the key national ecological security areas. The land use pattern of this region is not only affected by the local geographical environment and social and economic development but also will be closely associated with the sustainable development of the future social environment. Based on the Landsat TM remote sensing images of 1990, 2000, 2010, and 2015, this study reveals the temporal and spatial patterns of land use change and their relationships with socio-economic factors in the past 25 years by means of landscape pattern analysis, gradient analysis, and correlation analysis. The results showed (1) the cropland and forest land areas were the dominant land types (30% and 50%, respectively), and the proportion of construction land was < 3%. The land use types (forest land, shrub, water body, grassland, and orchard) with important ecological functions accounted for 67%. (2) Along the central city-edge area gradient, each land use type showed obvious spatial characteristics. In particular, the proportions of construction land and cropland areas significantly decreased, the degree of fragmentation increased, while the forest land tended to be integrated. (3) In the past 25 years, cropland and forest land decreased by 1.06% and 0.49%, respectively, and the construction land increased by 1.08%. The degree of regional landscape fragmentation and the landscape diversity increased. Except for forest land, all land use types were significantly related to socio-economic factors (population, urbanization levels, output values of three industry sectors, etc.). These results suggest that, on the one hand, compared with the coastal city group, land use changes in the middle reaches of the Yangtze River have been relatively small, and there is a good basis of land use types for the provision of ecosystem services. On the other hand, there is a great challenge for ecological protection in this region. The main measures are to delineate the red line of ecological protection, protect high-quality cropland, control the scale of urban expansion, strengthen the construction of ecological corridors and ecological nodes, and enhance the ecological functions of regional landscapes in order to meet the needs of sustainable development of the Yangtze River Economic Belt in the future. 参考文献 相似文献 引证文献

Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system

Abstract. Accelerated retreat of Arctic Ocean summertime sea ice has focused attention on the potential use of the Northern Sea Route (NSR), for which sea ice thickness (SIT) information is crucial for safe maritime navigation. This study evaluated the medium-range (lead time below 10 days) forecast of SIT distribution in the East Siberian Sea (ESS) in early summer (June–July) based on the TOPAZ4 ice–ocean data assimilation system. A comparison of the operational model SIT data with reliable SIT estimates (hindcast, satellite and in situ data) showed that the TOPAZ4 reanalysis qualitatively reproduces the tongue-like distribution of SIT in ESS in early summer and the seasonal variations. Pattern correlation analysis of the SIT forecast data over 3 years (2014–2016) reveals that the early summer SIT distribution is accurately predicted for a lead time of up to 3 days, but that the prediction accuracy drops abruptly after the fourth day, which is related to a dynamical process controlled by synoptic-scale atmospheric fluctuations. For longer lead times ( &gt; 4 days), the thermodynamic melting process takes over, which contributes to most of the remaining prediction accuracy. In July 2014, during which an ice-blocking incident occurred, relatively thick SIT ( ∼ 150 cm) was simulated over the ESS, which is consistent with the reduction in vessel speed. These results suggest that TOPAZ4 sea ice information has great potential for practical applications in summertime maritime navigation via the NSR.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Measuring the cortical correlation structure of spontaneous oscillatory activity with EEG and MEG

Power correlations of orthogonalized signals have recently been introduced for MEG as a powerful tool to non-invasively investigate functional connectivity in the human brain. Little is known about the applicability of this approach to EEG, and how compatible the results are between EEG and MEG. To address this, we systematically compared power correlations of simultaneously recorded and source co-registered 64-channel EEG and 275-channel MEG in resting human subjects. For both modalities, connectivity peaked at around 16Hz. For this frequency range, seed-based correlation maps showed comparable patterns across modalities, with generally more distinct patterns for MEG. A brain-wide pattern correlation analysis also revealed maximum similarity around 16Hz. Correcting for different signal-to-noise ratio (SNR) across frequencies and modalities revealed pattern correlation between modalities close to one across a broad frequency range from 1 to 32Hz and only slightly smaller for higher frequencies. The decrease above 32Hz likely reflected higher susceptibility to muscle artifacts for EEG than for MEG. Our results show that power correlation of orthogonalized signals is feasible for studying functional connectivity with 64-channel EEG. Furthermore, besides differences in SNR, for frequencies from about 8 to 32Hz, EEG and MEG measure the same correlation patterns across the entire brain.

Variability in the Levels of BTEX at a Pollution Hotspot in New Delhi, India

It is a matter of concern that despite taking measures to control aromatic content in gasoline in India, the levels of volatile organic compounds are rising again in many of the Indian cities. The transport sector has been one of the major sectors which are re-sponsible for worsening the air quality of Delhi city. While thousands of toxic com-pounds are emitted from automobiles, industries, gasoline stations as well as service stations, however, volatile organic compounds are important due to their significant contribution to ozone formation, cancer, and non-cancer health risks. In this study, roadside levels of benzene, toluene, ethylbenzene and xylenes (BTEX) were investi-gated at the one of the major arterial road of Delhi city. Air samples were collected by activated coconut shell charcoal adsorbent tubes. The BTEX concentrations were de-termined by gas chromatography-flame ionization detector (GC-FID) technique. The mean concentrations of benzene, toluene, ethylbenzene and xylenes were, respectively, 60.22, 162.68, 49.42 and 25.25 μg/m3. The relative concentration distribution pattern and mutual correlation analysis indicated that in BTEX had sources other than vehicle emission at the study site. The samples collected, showed that BTEX had significantly higher concentrations in winter than those in spring and summer.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns.

Syneresis and delayed detachment in agar plates.

Biogels made of crosslinked polymers such as proteins or polysaccharides behave as porous soft solids and store large amounts of solvent. These gels undergo spontaneous aging, called syneresis, which consists of the shrinkage of the gel matrix and the progressive expulsion of solvent. As a result, a biogel originally casted in a container often loses contact with the container sidewalls, and the detachment time is difficult to anticipate a priori, since it may occur over variable time spans (from hours to days). Here we report on syneresis phenomena in agar plates, which consist of Petri dishes filled with a gel mainly composed of agar. Direct observations and speckle pattern correlation analysis allow us to rationalize the delayed detachment of the gel from the sidewall of the Petri dish. The detachment time t* is surprisingly not controlled by the mass loss as one would intuitively expect. Instead, t* is strongly correlated to the gel minimum thickness emin measured along the sidewall of the plate, and increases as a robust function of emin, independently of the prior mass-loss history. Time-resolved correlation spectroscopy atypically applied to such weakly diffusive media gives access to the local thinning rate of the gel. This technique also allows us to detect the gel micro-displacements that are triggered by water evaporation prior to the detachment, and even to anticipate the latter from a few hours. Our work provides observables to predict the detachment time of agar gels in dishes, and highlights the relevance of speckle pattern correlation analysis for the quantitative investigation of the syneresis dynamics in biopolymer gels.