Geometric distortion, signal-loss, and image-blurring artifacts in echo planar imaging (EPI) are caused by frequency shifts and T * 2 relaxation distortion of the MR signal along the k-space trajectory due to magnetic field inhomogeneities. The EPI geometric-distortion artifact associated with frequency shift can be reduced with parallel imaging techniques such as SENSE, while the signal-loss and blurring artifacts remain. The gradient-echo slice excitation profile imaging (GESEPI) method has been shown to be successful in restoring tissue T * 2 relaxation characteristics and is therefore effective in reducing signal-loss and image-blurring artifacts at a cost of increased acquisition time. Challenges to performing rapid echo planar imaging (EPI) at high field are increased considerably by amplified magnetic field inhomogeneity artifacts (1,2). Echo planar images are typically acquired with a long acquisition trajectory during which the MR signal is modulated by T * 2 relaxation. This makes EPI inherently vulnerable to magnetic field inhomogeneity, which is most noticeable in images of the inferior and frontal brain areas. Given the important role of EPI in dynamic imaging, significant efforts have been made in developing techniques to reduce or eliminate these artifacts (3-31).The magnetic field inhomogeneity artifacts include signal loss, image blurring, and geometric distortion. Among these artifacts, image blurring and signal loss are caused by distortion of T * 2 relaxation predominantly due to the through-plane local gradient, while geometric distortion is caused by a frequency shift of the MR signal due to the in-plane local gradient. Since the gradient-echo slice excitation profile imaging (GESEPI) method has been shown to be capable of removing distortions in T * 2 relaxation characteristics caused by the through-plane local gradient at high field strengths (13,31), it can be highly effective in correcting EPI signal-loss and image-blurring artifacts. While GESEPI provides excellent reduction of these two kinds of artifacts, its utility for rapid EPI is limited by increased image acquisition time. This limitation can be overcome with SENSE encoding, which reduces k-space sampling time (32). In addition, the geometric distortion artifact associated with the in-plane local gradient is significantly mitigated with SENSE as a result of reduced data acquisition time (33-35). The signal-loss and image-blurring artifacts associated with the through-plane local gradient, however, still remain in SENSE EPI. Thus, incorporation of SENSE with GESEPI will provide a more effective method for correcting all three types of artifacts while reducing image acquisition time. In this paper, a SENSE-GESEPI approach is introduced for acquiring artifact-free, heavily T * 2 -weighted echo planar images of the brain at a field strength of 3.0 T. A theoretical analysis of artifact reduction with GESEPI and SENSE in EPI acquisition is provided. To validate the theoretical analysis, experimental results of artifact reductions with...

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Endoplasmic reticulum (ER) stress is highly associated with liver steatosis. B-cell receptor-associated protein 31 (BAP31) has been reported to be involved in ER homeostasis, and plays key roles in hepatic lipid metabolism in high-fat diet-induced obese mice. However, whether BAP31 modulates hepatic lipid metabolism via regulating ER stress is still uncertain. In this study, wild-type and liver-specific BAP31-depleted mice were administrated with ER stress activator of Tunicamycin, the markers of ER stress, liver steatosis, and the underlying molecular mechanisms were determined. BAP31 deficiency increased Tunicamycin-induced hepatic lipid accumulation, aggravated liver dysfunction, and increased the mRNA levels of ER stress markers, including glucose-regulated protein 78 (GRP78), X-box binding protein 1 (XBP1), inositol-requiring protein-1α (IRE1α) and C/EBP homologous protein (CHOP), thus promoting ER stress in vivo and in vitro. Hepatic lipid export via very low-density lipoprotein (VLDL) secretion was impaired in BAP31-depleted mice, accompanied by reduced Apolipoprotein B (APOB) and microsomal triglyceride transfer protein (MTTP) expression. Exogenous lipid clearance was also inhibited, along with impaired gene expression related to fatty acid transportation and fatty acid β-oxidation. Finally, BAP31 deficiency increased Tunicamycin-induced hepatic inflammatory response. These results demonstrate that BAP31 deficiency increased Tunicamycin-induced ER stress, impaired VLDL secretion and exogenous lipid clearance, and reduced fatty acid β-oxidation, which eventually resulted in liver steatosis.

Accurate truck travel time prediction (TTP) is one of the critical factors in the dynamic optimal dispatch of open-pit mines. This study divides the roads of open-pit mines into two types: fixed and temporary link roads. The experiment uses data obtained from Fushun West Open-pit Mine (FWOM) to train three types of machine learning (ML) prediction models based on -nearest neighbors (kNN), support vector machine (SVM), and random forest (RF) algorithms for each link road. The results show that the TTP models based on SVM and RF are better than that based on kNN. The prediction accuracy calculated in this study is approximately 15.79% higher than that calculated by traditional methods. Meteorological features added to the TTP model improved the prediction accuracy by 5.13%. Moreover, this study uses the link rather than the route as the minimum TTP unit, and the former shows an increase in prediction accuracy of 11.82%.

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