Trade-offs among cost, integration, and segregation in the human connectome

AbstractThe human brain structural network is thought to be shaped by the optimal trade-off between cost and efficiency. However, most studies on this problem have focused on only the trade-off between cost and global efficiency (i.e., integration) and have overlooked the efficiency of segregated processing (i.e., segregation), which is essential for specialized information processing. Direct evidence on how trade-offs among cost, integration, and segregation shape the human brain network remains lacking. Here, adopting local efficiency and modularity as segregation factors, we used a multiobjective evolutionary algorithm to investigate this problem. We defined three trade-off models, which represented trade-offs between cost and integration (Dual-factor model), and trade-offs among cost, integration, and segregation (local efficiency or modularity; Tri-factor model), respectively. Among these, synthetic networks with optimal trade-off among cost, integration, and modularity (Tri-factor model [Q]) showed the best performance. They had a high recovery rate of structural connections and optimal performance in most network features, especially in segregated processing capacity and network robustness. Morphospace of this trade-off model could further capture the variation of individual behavioral/demographic characteristics in a domain-specific manner. Overall, our results highlight the importance of modularity in the formation of the human brain structural network and provide new insights into the original cost-efficiency trade-off hypothesis

An initial assessment of SMAP soil moisture retrievals using high-resolution model simulations and in situ observations

At the end of its first year of operation, we compare soil moisture retrievals from the Soil Moisture Active Passive (SMAP) mission to simulations from a land surface model with meteorological forcing downscaled from observations/reanalysis and in situ observations from sparse monitoring networks within continental United States (CONUS). The radar failure limits the duration of comparisons for the active and combined products (~3 months). Nevertheless, the passive product compares very well against in situ observations over CONUS. On average, SMAP compares to the in situ data even better than the land surface model and provides significant added value on top of the model and thus good potential for data assimilation. At large scale, SMAP is in good agreement with the model in most of CONUS with less-than-expected degradation over mountainous areas. Lower correlation between SMAP and the model is seen in the forested east CONUS and significantly lower over the Canadian boreal forests.United States. National Aeronautics and Space Administration (NNX14AH92G)United States. National Aeronautics and Space Administration (NNX13AI44G

Characterization of a novel qepA3 variant in Enterobacter aerogenes

Five isolates harboring qepA were studied by polymerase chain reaction (PCR) amplification and relevant methods. One was determined to be a novel qepA3 from Enterobacter aerogenes, and four involved three qepA1 and one qepA2 determinants from Escherichia coli; the qepA3 changed five amino acids. These results characterized genetic structures A, B, C, D, and E

Knowledge Graph-Based Assembly Resource Knowledge Reuse towards Complex Product Assembly Process

Assembly process designers typically confront the challenge of seeking information out of large volumes of non-structured files with a view to supporting the decision-making to be made. It is a leading concern that embedding data in text documents can hardly be retrieved semantically in order to facilitate decision-making with timely support. For tackling this gap, we propose in this paper a knowledge graph-based approach used to merge and retrieve information decided to be relevant within an engineering context. The proposed approach is to establish a multidimensional integrated assembly resource knowledge graph (ARKG) based on the structure of function-structure-assembly procedure-assembly resource, and this multidimensional integrated structure can well accomplish the retrieval of related knowledge. The upper semantic framework of ARKG is established by the assembly resource ontology model, which is a semantic-type framework involving multiple domains of knowledge to create instantiated data reflecting the full profile of the assembly resource for obtaining structured data of ARKG while avoiding the data redundancy problem. The ARKG method is validated through assembly scenario of the aircraft, and the results show the effectiveness and accuracy of the ARKG used by the assembly process designer in the assembly process design phase for retrieving the target knowledge of the assembly resources

Knowledge Graph-Based Assembly Resource Knowledge Reuse towards Complex Product Assembly Process

Assembly process designers typically confront the challenge of seeking information out of large volumes of non-structured files with a view to supporting the decision-making to be made. It is a leading concern that embedding data in text documents can hardly be retrieved semantically in order to facilitate decision-making with timely support. For tackling this gap, we propose in this paper a knowledge graph-based approach used to merge and retrieve information decided to be relevant within an engineering context. The proposed approach is to establish a multidimensional integrated assembly resource knowledge graph (ARKG) based on the structure of function-structure-assembly procedure-assembly resource, and this multidimensional integrated structure can well accomplish the retrieval of related knowledge. The upper semantic framework of ARKG is established by the assembly resource ontology model, which is a semantic-type framework involving multiple domains of knowledge to create instantiated data reflecting the full profile of the assembly resource for obtaining structured data of ARKG while avoiding the data redundancy problem. The ARKG method is validated through assembly scenario of the aircraft, and the results show the effectiveness and accuracy of the ARKG used by the assembly process designer in the assembly process design phase for retrieving the target knowledge of the assembly resources

Tuning Dielectric Loss of SiO2@CNTs for Electromagnetic Wave Absorption

We developed a simple method to fabricate SiO2-sphere-supported N-doped CNTs (NCNTs) for electromagnetic wave (EMW) absorption. EMW absorption was tuned by adsorption of the organic agent on the precursor of the catalysts. The experimental results show that the conductivity loss and polarization loss of the sample are improved. Meanwhile, the impedance matching characteristics can also be adjusted. When the matching thickness was only 1.5 mm, the optimal 3D structure shows excellent EMW absorption performance, which is better than most magnetic carbon matrix composites. Our current approach opens up an effective way to develop low-cost, high-performance EMW absorbers

Coupling Hollow Fe₃O₄–Fe Nanoparticles with Graphene Sheets for High-Performance Electromagnetic Wave Absorbing Material

We developed a strategy for coupling hollow Fe₃O₄–Fe nanoparticles with graphene sheets for high-performance electromagnetic wave absorbing material. The hollow Fe₃O₄–Fe nanoparticles with average diameter and shell thickness of 20 and 8 nm, respectively, were uniformly anchored on the graphene sheets without obvious aggregation. The minimal reflection loss <i>R</i>_L values of the composite could reach −30 dB at the absorber thickness ranging from 2.0 to 5.0 mm, greatly superior to the solid Fe₃O₄–Fe/G composite and most magnetic EM wave absorbing materials recently reported. Moreover, the addition amount of the composite into paraffin matrix was only 18 wt %

Electrostatic Trapping of Double-Stranded DNA Based on Cd(OH)₂ Three-Side Nanobelt Architectures

In this paper, Cd­(OH)₂ 1D three-side nanobelt architectures have been fabricated through a facile two-phase reaction system. Considering their electropositive character proven by zeta potential measurement, the as-obtained Cd­(OH)₂ nanomaterials have been applied to capture negatively charged DNA. On the basis of the above results, the Cd­(OH)₂ nanomaterials have been employed for trapping negatively charged double-stranded DNA molecules (salmon sperm DNA). Assisted by the detailed observation of their DNA interaction results as well as through UV–vis spectroscopy, infrared imaging automatic target recognition (IRATR) and inductive coupled plasma atomic emission spectrometer (ICP-AES) measurements, it has been clearly shown that this 1D nanoarchitecture can effectively trap and release DNA molecules without use of any other organic reagents. In addition, a miniaturized electrochemical DNA-releasing device based on the Cd­(OH)₂ 1D three-side nanobelt architectures has been fabricated. Using this device, it is possible to recycle the Cd­(OH)₂ nanostructures. In addition, the Cd­(OH)₂ nanomaterials maintain their nanostructures, and no Cd²⁺ ions were released in repeated DNA separation and transfer processes, which demonstrate their practicality for DNA trapping

Terahertz Spectroscopy for Accurate Identification of Panax quinquefolium Basing on Nonconjugated 24(R)-Pseudoginsenoside F11

Panax quinquefolium is a perennial herbaceous plant that contains many beneficial ginsenosides with diverse pharmacological effects. 24(R)-pseudoginsenoside F11 is specific to P. quinquefolium, a useful biomarker for distinguishing this species from other related plants. However, because of its nonconjugated property and the complexity of existing detection methods, this biomarker cannot be used as the identification standard. We herein present a stable 24(R)-pseudoginsenoside F11 fingerprint spectrum in the terahertz band, thereby proving that F11 can be detected and quantitatively analyzed via terahertz spectroscopy. We also analyzed the sample by high-performance liquid chromatography-triple quadrupole mass spectrometry. The difference between the normalized data for the two analytical methods was less than 5%. Furthermore, P. quinquefolium from different areas and other substances can be clearly distinguished based on these terahertz spectra with a standard principal component analysis. Our method is a fast, simple, and cost-effective approach for identifying and quantitatively analyzing P. quinquefolium