Scaling Analysis of the Tensile Strength of Bamboo Fibers Using Weibull Statistics

This study demonstrates the effect of weak-link scaling on the tensile strength of bamboo fibers. The proposed model considers the random nature of fiber strength, which is reflected by using a two-parameter Weibull distribution function. Tension tests were performed on samples that could be scaled in length. The size effects in fiber length on the strength were analyzed based on Weibull statistics. The results verify the use of Weibull parameters from specimen testing for predicting the strength distributions of fibers of longer gauge lengths

Insights on the gas permeability change in porous shale

Due to abundant nanoscale pores developed in shale, gas flow in shale presents a complex dynamic process. This paper summarized the effects from effective stress increase, shale matrix shrinkage, gas slippage and Knudsen diffusion on the gas permeability change in shale during shale gas recovery. With the reduce in gas pressure, effective stress increase leads to the decline of the permeability in an exponential form; the permeability increases due to the shale matrix shrinkage induced by gas desorption; appearances of gas slippage and Knudsen diffusion cause an additional increase in the gas permeability particularly in small pores at low pressures. In addition, some reported models evaluating the shale permeability were reviewed preliminarily. Models considering these four effects may be potentially effective to evaluate the gas permeability change in shale.Cited as: Li, J., Yu, T., Liang, X., et al. Insights on the gas permeability change in porous shale. Advances in Geo-Energy Research, 2017, 1(2): 69-73, doi: 10.26804/ager.2017.02.0

Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach

Permeability is one of the most important petrophysical properties of shale reservoirs, controlling the fluid flow from the shale matrix to artificial fracture networks, the production and ultimate recovery of shale oil/gas. Various methods have been used to measure this parameter in shales, but no method effectively estimates the permeability of all well intervals due to the complex and heterogeneous pore throat structure of shale. A hydraulic flow unit (HFU) is a correlatable and mappable zone within a reservoir, which is used to subdivide a reservoir into distinct layers based on hydraulic flow properties. From these units, correlations between permeability and porosity can be established. In this study, HFUs were identified and combined with a back propagation neural network to predict the permeability of shale reservoirs in the Dongying Depression, Bohai Bay Basin, China. Well data from three locations were used and subdivided into modeling and validation datasets. The modeling dataset was applied to identify HFUs in the study reservoirs and to train the back propagation neural network models to predict values of porosity and flow zone indicator. Next, a permeability prediction method was established, and its generalization capability was evaluated using the validation dataset. The results identified five HFUs in the shale reservoirs within the Dongying Depression. The correlation between porosity and permeability in each HFU is generally greater than the correlation between the two same variables in the overall core data. The permeability estimation method established in this study effectively and accurately predicts the permeability of shale reservoirs in both cored and un-cored wells. Predicted permeability curves effectively reveal favorable shale oil/gas seepage layers and thus are useful for the exploration and the development of hydrocarbon resources in the Dongying Depression.Cited as: Zhang, P., Lu, S., Li, J., Zhang, J., Xue, H., Chen, C. Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach. Advances in Geo-Energy Research, 2018, 2(1): 1-13, doi: 10.26804/ager.2018.01.0

Global Methylomic and Transcriptomic Analyses Reveal the Broad Participation of DNA Methylation in Daily Gene Expression Regulation of Populus trichocarpa

Changes in DNA methylation patterns in different tissues, at various developmental stages, and under environmental stimuli have been investigated in plants. However, the involvement of DNA methylation in daily gene expression regulation and the plant circadian clock have not been reported. Here, we investigated DNA methylomes and mRNA transcriptomes from leaves of P. trichocarpa over 24 h by high-throughput sequencing. We found that approximately 15.63–19.50% of the genomic cytosine positions were methylated in mature poplar leaves, with approximately half being in the form of asymmetric CHH sites. Repetitive sequences and transposable elements (TEs) were heavily methylated, and the hAT and CMC-EnSpm transposons were more heavily methylated than other TEs. High methylation levels were observed upstream and downstream of the transcribed region, medium in exon and intron, low in untranslated region (5′-UTR and 3′-UTR) of genic regions. In total, about 53,689 differentially methylated regions (DMRs) were identified and CHH context was the most abundant type among daily DNA methylation changes. The DMRs overlapped with over one third of the total poplar genes, including plant defense genes. In addition, a positive correlation between expression levels and DNA methylation levels in the gene body region were observed in DMR overlapping genes. About 1,895 circadian regulated genes overlapped with DMRs, with 871 hypermethylated genes with down-regulated expression levels and 881 hypomethylated genes with up-regulated expression levels, indicating the possible regulation of DNA methylation on the daily rhythmic expression of these genes. But rhythmic DNA methylation changes were not detected in any oscillator component genes controlling the plant circadian clock. Our results suggest that DNA methylation participates widely in daily gene expression regulation, but is not the main mechanism modulating the plant circadian clock

Different responses of incidence-weighted and abundance-weighted multiple facets of macroinvertebrate beta diversity to urbanization in a subtropical river system

Urbanization is one of the major drivers of biotic homogenization (i.e., decrease in beta diversity) in freshwater systems. However, only a few studies have simultaneously examined how urbanization affects multiple facets (i. e., taxonomic, functional and phylogenetic) of beta diversity and its underlying ecological drivers in urban river macroinvertebrates. Here, we distinguished the patterns and ecological mechanisms of multiple facets of macroinvertebrate beta diversity weighted by incidence and abundance data in a subtropical river system with a distinct urbanization gradient. We also investigated how total beta diversity patterns stem from replacement versus richness difference among sites. Our results showed that taxonomic and phylogenetic beta diversities weighted by incidence data were primarily driven by replacement of taxa, whereas the richness difference contributed more to multiple facets of beta diversity based on abundance data. Furthermore, multiple facets of beta diversity decreased with urbanization for both incidence-weighted and abundance-weighted data, but the former showed more substantial decreases. Both replacement and richness difference components contributed roughly equally to the decline of incidence-weighted beta diversity. In contrast, the losses of abundanceweighted beta diversity were mainly associated with replacement of taxa. Variation partitioning results revealed that all beta diversity measures based on incidence data were governed primarily by local and land-use variables, whereas spatial variables were more relevant in driving beta diversity weighted by abundance data. Overall, by comparing different facets and components of beta diversity weighted by incidence versus abundance data, we suggest that incidence-weighted data may be more sensitive in portraying the impacts of urbanization on macroinvertebrate diversity. This likely resulted from the fact that incidence-weighted data shows the importance of rare taxa in shaping homogenization induced by urbanization.Peer reviewe

Different responses of incidence-weighted and abundance-weighted multiple facets of macroinvertebrate beta diversity to urbanization in a subtropical river system

Urbanization is one of the major drivers of biotic homogenization (i.e., decrease in beta diversity) in freshwater systems. However, only a few studies have simultaneously examined how urbanization affects multiple facets (i. e., taxonomic, functional and phylogenetic) of beta diversity and its underlying ecological drivers in urban river macroinvertebrates. Here, we distinguished the patterns and ecological mechanisms of multiple facets of macroinvertebrate beta diversity weighted by incidence and abundance data in a subtropical river system with a distinct urbanization gradient. We also investigated how total beta diversity patterns stem from replacement versus richness difference among sites. Our results showed that taxonomic and phylogenetic beta diversities weighted by incidence data were primarily driven by replacement of taxa, whereas the richness difference contributed more to multiple facets of beta diversity based on abundance data. Furthermore, multiple facets of beta diversity decreased with urbanization for both incidence-weighted and abundance-weighted data, but the former showed more substantial decreases. Both replacement and richness difference components contributed roughly equally to the decline of incidence-weighted beta diversity. In contrast, the losses of abundanceweighted beta diversity were mainly associated with replacement of taxa. Variation partitioning results revealed that all beta diversity measures based on incidence data were governed primarily by local and land-use variables, whereas spatial variables were more relevant in driving beta diversity weighted by abundance data. Overall, by comparing different facets and components of beta diversity weighted by incidence versus abundance data, we suggest that incidence-weighted data may be more sensitive in portraying the impacts of urbanization on macroinvertebrate diversity. This likely resulted from the fact that incidence-weighted data shows the importance of rare taxa in shaping homogenization induced by urbanization.Peer reviewe

Comprehensive review on gene mutations contributing to dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is one of the most common primary myocardial diseases. However, to this day, it remains an enigmatic cardiovascular disease (CVD) characterized by ventricular dilatation, which leads to myocardial contractile dysfunction. It is the most common cause of chronic congestive heart failure and the most frequent indication for heart transplantation in young individuals. Genetics and various other factors play significant roles in the progression of dilated cardiomyopathy, and variants in more than 50 genes have been associated with the disease. However, the etiology of a large number of cases remains elusive. Numerous studies have been conducted on the genetic causes of dilated cardiomyopathy. These genetic studies suggest that mutations in genes for fibronectin, cytoskeletal proteins, and myosin in cardiomyocytes play a key role in the development of DCM. In this review, we provide a comprehensive description of the genetic basis, mechanisms, and research advances in genes that have been strongly associated with DCM based on evidence-based medicine. We also emphasize the important role of gene sequencing in therapy for potential early diagnosis and improved clinical management of DCM

Advances in diffusion MRI acquisition and processing in the Human Connectome Project

The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease