Dynamic cardiac imaging in MRI is a very challenging task. To obtain high spatial resolution, temporal resolution, and signal-to-noise ratio (SNR), single-shot imaging is not sufficient. Use of multishot techniques resolves this problem but can cause motion artifacts because of data inconsistencies between views. Motion artifacts can be reduced by signal averaging at some cost in increased scan time. However, for the same increase in scan time, other techniques can be more effective than simple averaging in reducing the artifacts. If most of the energy of the inconsistencies is limited to a certain region of kappa-space, increased sampling density (oversampling) in this region can be especially effective in reducing motion artifacts. In this work, several variable-density spiral trajectories are designed and tested. Their efficiencies for artifact reduction are evaluated in computer simulations and in scans of normal volunteers. The SNR compromise of these trajectories is also investigated. The authors conclude that variable-density spiral trajectories can effectively reduce motion artifacts with a small loss in SNR as compared with a uniform density counterpart.

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Findings with cine phase-contrast MR imaging employing rapid spiral acquisition are in good agreement with measurements made with PAH-clearance hematocrit and give the promise of clinical measurements of RBF.

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The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

In many scheduling studies, researchers consider the processing times of jobs as constant numbers. This assumption sometimes is at odds with practical manufacturing process due to several sources of uncertainties arising from real-life situations. Examples are the changing working environments, machine breakdowns, tool quality variations and unavailability, and so on. In light of the phenomenon of scenario-dependent processing times existing in many applications, this paper proposes to incorporate scenario-dependent processing times into a two-machine flow-shop environment with the objective of minimizing the total completion time. The problem under consideration is never explored. To solve it, we first derive a lower bound and two optimality properties to enhance the searching efficiency of a branch-and-bound method. Then, we propose 12 simple heuristics and their corresponding counterparts improved by a pairwise interchange method. Furthermore, we set proposed 12 simple heuristics as the 12 initial seeds to design 12 variants of a cloud theory-based simulated annealing (CSA) algorithm. Finally, we conduct simulations and report the performances of the proposed branch-and-bound method, the 12 heuristics, and the 12 variants of CSA algorithm.

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