Diffusion MRI enabled in vivo microstructural imaging of the fiber tracts in the brain resulting in its application in a wide range of settings, including in neurological and neurosurgical disorders. ...Conventional approaches such as diffusion tensor imaging (DTI) have been shown to have limited applications due to the crossing fiber problem and the susceptibility of their quantitative indices to partial volume effects. To overcome these limitations, the recent focus has shifted to the advanced acquisition methods and their related analytical approaches. Advanced white matter imaging techniques provide superior qualitative data in terms of demonstration of multiple crossing fibers in their spatial orientation in a three dimensional manner in the brain. In this review paper, we discuss the advancements in diffusion MRI and introduce their roles. Using examples, we demonstrate the role of advanced diffusion MRI-based fiber tracking in neuroanatomical studies. Results from its preliminary application in the evaluation of intracranial space occupying lesions, including with respect to future directions for prognostication, are also presented. Building upon the previous DTI studies assessing white matter disease in Huntington's disease and Amyotrophic lateral sclerosis; we also discuss approaches which have led to encouraging preliminary results towards developing an imaging biomarker for these conditions.
•Discussion of the state-of-the-art methods in diffusion MRI and their roles•Discussion of diffusion tensor imaging and its limitations•Discussion of advanced white matter imaging techniques and its applications•Imaging biomarker development in Huntington's disease•Imaging biomarker development in Amyotrophic lateral sclerosis
•We examined the correlation among 12 SPAD and 4 nitrogen (N) indicators in rice.•Normalized SPAD index of the fourth fully expanded leaf from top (NSI4) was selected to develop the single-stage and ...duration models from stem elongation to booting stages.•Two stable & general duration diagnostic models were developed between plant N accumulation (NA), N nutrition index (NNI) and NSI4.•The calibration showed the models can be used as suitable N diagnostic tools.
Various indices established on a portable SPAD-502 meter can serve as indicators of the nitrogen status of a plant. We compared di-positional SPAD readings and indices with several reliable nitrogen indicators during vegetative growth stage of rice (Oryza sativa L.) and developed a prediction model for diagnosing nitrogen status. Three field experiments were conducted in Jiangsu province of east China during 2013 and 2014. Different nitrogen application rates were used to generate contrasting conditions of nitrogen availability in three Japonica, Wuyunjing 19, Yongyou 8, and Wuyunjing 24, and one Indica rice hybrid, Yliangyou 1. The SPAD values of the uppermost four fully expanded leaves were measured from tillering to heading stages, and these values were further used to calculate the normalized SPAD index (NSI), relative SPAD index (RSI), difference SPAD index (DSI), relative difference SPAD index (RDSI), and normalized difference SPAD index (NDSI). Five hills from each plot were simultaneously sampled, and four nitrogen indicators, including leaf nitrogen concentration (LNC), plant nitrogen concentration (PNC), plant nitrogen accumulation (NA), and nitrogen nutrition index (NNI), were measured. The results of linear correlations among the SPAD and nitrogen indicators indicated that NSI of the fourth fully expanded leaf from top (NSI4) was the most reliable and generally applicable SPAD indicator. In total, 24 potential single-stage and duration models were established, taking into consideration the fact that duration models covering the period from stem elongation to booting stages are more robust, two duration diagnostic models (Model 1: NA=0.0279e8.6957NSI4, R2=0.730**, n=45; Model 2: NNI=0.0163e4.13NSI4, R2=0.767**, n=45, NSI4=0.80–1.00) were developed and calibrated. Both models can provide accurate and appropriate N diagnosis from the stem elongation to booting growth stages for rice production.
Monitoring the propagation of dunes is essential for natural hazard management. Accurate dunes mapping is critical in this situation. Landscape elements such as vegetation, water, dunes, and built-up ...are commonly separated using spectral indices. The discovery of dune features using a spectral index is one of the most significant achievements in earth observation. In this research, it was suggested Drifting Sand Index (DSI) is a newly created index that can be used to extract the land of dunes. The DSI is calculated using the normalized difference between six Landsat-8 bands (B, R, G, NIR, SWIR-1, SWIR-2). The linear SVM algorithm was implemented using library (LibLINEAR) in the R software to calculate a new linear equation. Two versions of the index have been proposed, the first is the complete version (DSI-C), and the second is the reduced version (DSI-R). The suggested indices results were compared to four previously proposed spectral indices (NDSI-1, NDSI-2, CI, and NDSLI). The acquired results demonstrated that the DSI-C and DSI-R had a high ability to distinguish between sand and different land covers, such as vegetation, water bodies, and various soil types. The average overall accuracy for all levels of the DSI-R, DSI-C, NDSI-1, NDSI-2, CI, and NDSLI was 88.59%, 83.43%, 78.030%, 68.52%, 65.98%, and 56.490%, respectively. The average Kappa Coefficient for DSI-R, DSI-C NDSI-1, NDSI-2, CI, and NDSLI was 77.20%, 66.87%, 56.076%, 37.073%, 31.978%, and 13.011%, respectively.
How to improve the phase signal-to-noise ratio (SNR) of distributed scatterers (DSs) is a key topic in DS interferometry (DSI). Although some state-of-the-art phase linking (PL) estimators have been ...proposed, their performance is still limited by the accuracy of the estimated sample coherence matrix (SCM). The key challenges arise from the biased estimation of the near-zero coherence matrix (the magnitude matrix of SCM) under conditions of small sample sizes and heterogeneous samples. To overcome this limitation, we present a sparse regularization-based PL estimator that considers the potential sparsity structure of the inverse covariance matrix. In this new estimator, we first introduced the graphical lasso (GLasso) algorithm into the small samples estimation problem of SCM, which suppresses the biased estimation of the sparse inverse covariance matrix by introducing <inline-formula> <tex-math notation="LaTeX">{L}_{{1}} </tex-math></inline-formula>-norm regularization, significantly reducing the impact of weakly coherent interferograms in fast decorrelation scenarios. Furthermore, we also attempt to generalize this scheme to long-term coherence cases through the utilization of <inline-formula> <tex-math notation="LaTeX">{L}_{{2}} </tex-math></inline-formula>-norm regularization. Both synthetic data tests and real Sentinel-1 data covering Changi Airport, Singapore, demonstrate the validity of the proposed approach.
2.4 times) and higher accuracy compared to the traditional method based on the Kolmogorov–Smirnov (KS) test and sample covariance matrix (SCM). Particularly, it exhibits exceptional performance in ...monitoring fine structures, while the traditional method usually fails with very few MPs. These results underscore the significant potential of this approach in the realm of ground surface deformation monitoring.
Fair and equitable benefit sharing of genetic resources is an expectation of the Nagoya Protocol. Although the Nagoya Protocol does not yet formally apply to Digital Sequence Information (“DSI”), ...discussions are currently underway regarding to include such data through ongoing Convention on Biological Diversity (“CBD”) negotiations. While Indigenous Peoples and Local Communities (“IPLC”) expect the value generated from genomic data to be subject to benefit sharing arrangements, a range of views are currently being expressed by Nation States, IPLC and other stakeholders. The use of DSI gives rise to unique considerations, creating a gray area as to how it should be considered under the Nagoya Protocol’s Access and Benefit Sharing (“ABS”) principles. One way for benefit sharing to be enhanced is through the connection of data to proper provenance information. A significant development is the use of digital labeling systems to ensure that the origin of samples is appropriately disclosed. The Traditional Knowledge and Biocultural Labels initiative offers a practical option for data provided to genomic databases. In particular, the BioCultural Labels (“BC Labels”) are a mechanism for Indigenous communities to identify and maintain provenance, origin and authority over biocultural material and data generated from Indigenous land and waters held in research, cultural institutions and data repositories. This form of cultural metadata adds value to the research endeavor and the creation of Indigenous fields within databases adds transparency and accountability to the research environment.
A physics-based dipole moment source reconstruction is proposed to estimate the near-field coupling between a liquid crystal display panel to a cellphone's cellular antenna. Based on the ...understanding of the current distribution on the source, a magnetic dipole moment source is reconstructed to replace the real radiation source that is located at the edge of the flexible printed circuit board. To characterize the coupling from the equivalent dipole moment source to the victim antenna, the noise transfer coefficient is proposed. The noise transfer coefficient can be calculated from the near-field scanning and the direct coupling measurements using a wideband source. The proposed physics-based dipole moment source reconstruction and noise transfer coefficient are successfully validated through the measured near-field coupling in a practical cellphone.
Drought is frequently recorded as a result of climate warming and elevated concentration of greenhouse gases, which affect the carbon and water cycles in terrestrial ecosystems, particularly in arid ...and semi-arid regions. To identify the drought in grassland ecosystems and to determine how such drought affects grassland ecosystems in terms of carbon and water cycles across the globe, this study evaluated the drought conditions of global grassland ecosystems from 2000 to 2011 on the basis of the remotely sensed Drought Severity Index (DSI) data. The temporal dynamics of grassland carbon use efficiency (CUE) and water use efficiency (WUE), as well as their correlations with DSI, were also investigated at the global scale. Results showed that 57.04% of grassland ecosystems experienced a dry trend over this period. In general, most grassland ecosystems in the northern hemisphere (N.H.) were in near normal condition, whereas those in the southern hemisphere (S.H.) experienced a clear drying and wetting trend, with the year 2005 regarded as the turning point. Grassland CUE increased continually despite the varied drought conditions over this period. By contrast, WUE increased in the closed shrublands and woody savannas but decreased in all the other grassland types. The drought conditions affected the carbon and water use mainly by influencing the primary production and evapotranspiration of grass through photosynthesis and transpiration process. The CUE and WUE of savannas was most sensitive to droughts among all the grassland types. The areas of grassland DSI that showed significant correlations with CUE and WUE were 52.92% and 22.11% of the total grassland areas, respectively. Overall, droughts sufficiently explained the dynamics of grassland CUE, especially in the S.H. In comparison with grassland CUE, the grassland WUE was less sensitive to drought conditions at the global scale.
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