•An apparent permeability model is proposed based on a unified diffusion coefficient.•Multiple mechanisms of gas transport are considered through linear superposition.•Darcy’s law is applicable in ...pores with diameters larger than 300 nm.
Gas transport mechanism in a shale nanopore is investigated by considering convective flow, gas diffusion, and surface diffusion. A common practice in modeling shale gas permeability is to use Knudsen diffusion coefficient when calculating diffusive flux, but the use of Knudsen diffusion coefficient would be incorrect if the shale gas flow regime is lying either in the transition diffusion or Fick’s diffusion, in which case the diffusion coefficient must correspond to that regime. This study proposes an apparent permeability model of shale based on a unified diffusion coefficient that transforms its value per the flow regime, including the effect of molecular diffusion, viscous flow, and surface diffusion of adsorbed gas through linear superposition. The proposed model is verified by comparing against other models for shale gas permeability. Results of sensitivity analysis indicate that permeability of gas due to diffusive transport is independent of pressure and pore size when pressure is larger than 6.895 MPa, but is dominant at lower pressures and increases with pore size. For pore diameters larger than 100 nm, the permeability due to surface diffusion is independent of pressure or pore size, indicating negligible gas transport due to surface diffusion in relatively larger pores (>100 nm) at any pressure, but it is dominant in small pore sizes when pressure is below 10 MPa. Permeability of gas (with or without surface diffusion) increases with the decrease of pressure when the pore diameters are smaller than 100 nm, whereas for pore diameters larger than 300 nm it is not affected by pressure, but increases with the increase of pore size, indicating that Darcy’s law is applicable in pores with the diameters larger than 300 nm.
Diffusion‐weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion ...detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non‐Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions.
Level of Evidence: 5
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2020;52:70–90.
The incidence of neurodegenerative diseases has shown an increasing trend. These conditions typically cause progressive functional disability. Identification of robust biomarkers of neurodegenerative ...diseases is a key imperative to facilitate early identification of the pathological features and to foster a better understanding of the pathogenetic mechanisms of individual diseases. Diffusion tensor imaging (DTI) is the most widely used diffusion MRI technique for assessment of neurodegenerative diseases. The DTI parameters are promising biomarkers for evaluation of microstructural changes; however, some limitations of DTI restrict its wider clinical use. New diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), bi‐tensor DTI, and neurite orientation density and dispersion imaging (NODDI) have been demonstrated to provide value addition to DTI for evaluation of neurodegenerative diseases. In this review article, we summarize the key technical aspects and provide an overview of the current state of knowledge regarding the role of DKI, bi‐tensor DTI, and NODDI as biomarkers of microstructural changes in representative neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease.
Level of Evidence
5
Technical Efficacy Stage
2 J. MAGN. RESON. IMAGING 2020;52:1620–1636.
Significance Diffusion-weighted MRI (DWI) tractography is widely used to map structural connections of the human brain in vivo and has been adopted by large-scale initiatives such as the human ...connectome project. Our results indicate that, even with high-quality data, DWI tractography alone is unlikely to provide an anatomically accurate map of the brain connectome. It is crucial to complement tractography results with a combination of histological or neurophysiological methods to map structural connectivity accurately. Our findings, however, do not diminish the importance of diffusion MRI as a noninvasive tool that offers important quantitative measures related to brain tissue microstructure and white matter architecture.
Tractography based on diffusion-weighted MRI (DWI) is widely used for mapping the structural connections of the human brain. Its accuracy is known to be limited by technical factors affecting in vivo data acquisition, such as noise, artifacts, and data undersampling resulting from scan time constraints. It generally is assumed that improvements in data quality and implementation of sophisticated tractography methods will lead to increasingly accurate maps of human anatomical connections. However, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of independent knowledge of the true anatomical connections in humans. Here we investigate the future prospects of DWI-based connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the macaque brain. The results of different tractography methods were compared with maps of known axonal projections from previous tracer studies in the macaque. Despite the exceptional quality of the DWI data, none of the methods demonstrated high anatomical accuracy. The methods that showed the highest sensitivity showed the lowest specificity, and vice versa. Additionally, anatomical accuracy was highly dependent upon parameters of the tractography algorithm, with different optimal values for mapping different pathways. These results suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is unlikely to be overcome by improvements in data acquisition and analysis alone.
Purpose
Microscopic fractional anisotropy (µFA) can disentangle microstructural information from orientation dispersion. While double diffusion encoding (DDE) MRI methods are widely used to extract ...accurate µFA, it has only recently been proposed that powder‐averaged single diffusion encoding (SDE) signals, when coupled with the diffusion standard model (SM) and a set of constraints, could be used for µFA estimation. This study aims to evaluate µFA as derived from the spherical mean technique (SMT) set of constraints, as well as more generally for powder‐averaged SM signals.
Methods
SDE experiments were performed at 16.4 T on an ex vivo mouse brain (Δ/δ = 12/1.5 ms). The µFA maps obtained from powder‐averaged SDE signals were then compared to maps obtained from DDE‐MRI experiments (Δ/τ/δ = 12/12/1.5 ms), which allow a model‐free estimation of µFA. Theory and simulations that consider different types of heterogeneity are presented for corroborating the experimental findings.
Results
µFA, as well as other estimates derived from powder‐averaged SDE signals produced large deviations from the ground truth in both gray and white matter. Simulations revealed that these misestimations are likely a consequence of factors not considered by the underlying microstructural models (such as intercomponent and intracompartmental kurtosis).
Conclusion
Powder‐averaged SMT and (2‐component) SM are unable to accurately report µFA and other microstructural parameters in ex vivo tissues. Improper model assumptions and constraints can significantly compromise parameter specificity. Further developments and validations are required prior to implementation of these models in clinical or preclinical research.
Hydrogen peroxide (H
O
) synthesis by electrochemical oxygen reduction reaction has attracted great attention as a green substitute for anthraquinone process. However, low oxygen utilization ...efficiency (<1%) and high energy consumption remain obstacles. Herein we propose a superhydrophobic natural air diffusion electrode (NADE) to greatly improve the oxygen diffusion coefficient at the cathode about 5.7 times as compared to the normal gas diffusion electrode (GDE) system. NADE allows the oxygen to be naturally diffused to the reaction interface, eliminating the need to pump oxygen/air to overcome the resistance of the gas diffusion layer, resulting in fast H
O
production (101.67 mg h
cm
) with a high oxygen utilization efficiency (44.5%-64.9%). Long-term operation stability of NADE and its high current efficiency under high current density indicate great potential to replace normal GDE for H
O
electrosynthesis and environmental remediation on an industrial scale.
PurposeThis paper aims to explore the characteristics of knowledge diffusion of library and information science to reveal its development trend and influence on other ...disciplines.Design/methodology/approachBased on the ESI discipline classification, this paper measures the knowledge diffusion from the library and information science to other disciplines over the last 24 years using indicators in four dimensions: breadth, intensity, speed and theme of knowledge diffusion.FindingsThe results show that the knowledge diffusion breadth of library and information science is wide, spreading to 21 ESI disciplines; the knowledge spread mainly concentrates in four soft or applied disciplines, and yet partially inter-disciplinary, and the knowledge diffusion intensity to each ESI discipline is parabolic whose highest point is mostly in 2004–2005; the speed of spreading to the 21 ESI disciplines is faster and faster, and the articles at the highest speed of knowledge diffusion are basically published after 2005; the knowledge diffusion themes are becoming increasingly diverse, deepening and specialization over time.Originality/valueThis paper modifies the relevant indicators of knowledge diffusion and constructs a measurement framework of knowledge diffusion from four aspects: breadth, intensity, speed and theme. The research method can also be used to explore the characteristics of knowledge absorption of a discipline from other ones.
Social learning Hoppitt, William; Laland, Kevin N
2013., 20130721, 2013, 2013-07-21
eBook
Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of ...behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience.Social Learningprovides a comprehensive, practical guide to the research methods of this important emerging field. William Hoppitt and Kevin Laland define the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. They present techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. They also describe the latest theory and empirical findings on social learning strategies, and introduce readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students.
Provides a comprehensive, practical guide to social learning researchCombines theoretical and empirical approachesDescribes techniques for the laboratory and the fieldCovers social learning mechanisms and strategies, statistical modeling techniques for field data, mathematical modeling of cultural evolution, and more
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