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Slice‐to‐volume registration and super‐resolution reconstruction are commonly used to generate 3D volumes of the fetal brain from 2D stacks of slices acquired in multiple orientations. A critical initial step in this pipeline is to select one stack with the minimum motion among all input stacks as a reference for registration. An accurate and unbiased motion assessment (MA) is thus crucial for successful selection. Here, we presented an MA method that determines the minimum motion stack based on 3D low‐rank approximation using CANDECOMP/PARAFAC (CP) decomposition. Compared to the current 2D singular value decomposition (SVD) based method that requires flattening stacks into matrices to obtain ranks, in which the spatial information is lost, the CP‐based method can factorize 3D stack into low‐rank and sparse components in a computationally efficient manner. The difference between the original stack and its low‐rank approximation was proposed as the motion indicator. Experiments on linearly and randomly simulated motion illustrated that CP demonstrated higher sensitivity in detecting small motion with a lower baseline bias, and achieved a higher assessment accuracy of 95.45% in identifying the minimum motion stack, compared to the SVD‐based method with 58.18%. CP also showed superior motion assessment capabilities in real‐data evaluations. Additionally, combining CP with the existing SRR‐SVR pipeline significantly improved 3D volume reconstruction. The results indicated that our proposed CP showed superior performance compared to SVD‐based methods with higher sensitivity to motion, assessment accuracy, and lower baseline bias, and can be used as a prior step to improve fetal brain reconstruction. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the effects of sleep on academic performance and job performance. A total of 172 undergraduate students completed an on-line questionnaire and their [...]

Background: Oscillating gradient diffusion MRI (dMRI) enables measurements at a short diffusion‐time (td), but it is challenging for clinical systems. Particularly, the low b‐value and low resolution may give rise to cerebrospinal fluid (CSF) contamination. Purpose: To assess the effect of CSF partial volume on td–dMRI measurements and efficacy of inversion‐recovery (IR) prepared oscillating and pulsed gradient dMRI sequence to improve td–dMRI measurements in the human brain. Study Type: Prospective. Subjects: Ten normal volunteers and six glioma patients. Field Strength/Sequence: A 3 T; three‐dimensional (3D) IR‐prepared oscillating gradient‐prepared gradient spin‐echo (GRASE) and two‐dimensional (2D) IR‐prepared oscillating gradient echo‐planar imaging (EPI) sequences. Assessment: We assessed the td‐dependent patterns of apparent diffusion coefficient (ADC) in several gray and white matter structures, including the hippocampal subfields (head, body, and tail), cortical gray matter, thalamus, and posterior white matter in normal volunteers. Pulsed gradient (0 Hz) and oscillating gradients at frequencies of 20 Hz, 40 Hz, and 60 Hz dMRI were acquired with GRASE and EPI sequences with or without the IR module. We also tested the td‐dependency patterns in glioma patients using the EPI sequence with or without the IR module. Statistical Tests: The differences in ADC across the different tds were compared by one‐way ANOVA followed by post hoc pairwise t‐tests with Bonferroni correction. Results: In the healthy subjects, brain regions that were possibly contaminated by CSF signals, such as the hippocampus (head, body, and tail) and cortical gray matter, td‐dependent ADC changes were only significant with the IR‐prepared 2D and 3D sequences but not with the non‐IR sequences. In brain glioblastomas patients, significantly higher td‐dependence was observed in the tumor region with the IR module than that without IR (slope = 0.0196 μm2/msec2 vs. 0.0034 μm2/msec2). Conclusion: The IR‐prepared sequence effectively suppressed the CSF partial volume effect and significantly improved the td‐dependent measurements in the human brain. Evidence Level: 1 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

The extreme sensitivity of the amide-water hydrogen exchange rates of the individual backbone amide protons to the local environment of the protons makes the rates useful for probing fluctuations in the local conformations of proteins. The amide-water hydrogen exchange in peptides and proteins can best be explained by looking at hydrogen exchange between N-methylcetamide and water.

This paper investigated the current levels of environmental sustainability in restaurants across the U.S. to determine whether a restaurant's proclivity for environmental sustainability depended on its characteristics such as chain affiliation or restaurant type. A web-based survey was administered to 2,500 top-level restaurant managers, from which a total of 218 responses were judged as usable. The data were analyzed using independent sample t-tests and ANOVA. This study presents an in-depth account of the environmental sustainability in restaurants across the U.S. based on an evaluation of top-level managers. This study also highlights the differences in restaurant environmental sustainability across different restaurant segments. [ABSTRACT FROM AUTHOR]

The hotel industry has experienced changes brought on by growth, customer expectations, and the proliferation in the use of e-commerce and online distribution channels. Future hotel success depends on how effectively hotel revenue managers are able to manage different booking channels to maximize hotel revenue. A Data Envelopment Analysis–Balanced Scorecard (DEA-BSC) model to measure efficiency of distribution channel mix using BSC results is presented. DEA-BSC was used because DEA-BSC incorporates multiple metrics simultaneously while traditional business models typically focus on one performance measure such as profit. Inputs for the model include the five distribution channels of C-Res/Voice, GDS, Brand.com, OTAs, and property/relationship sales. Output is the consolidated BSC average. The model was tested and results presented, demonstrating support for the usefulness of the model. [ABSTRACT FROM AUTHOR]

This study investigated the occurrence of merger and acquisition (M&A) waves in restaurant and lodging industries. By comparing actual frequency of M&A deals with simulated randomly generated deal frequency distributions, this study proved the presence of restaurant and lodging M&A waves. Macroeconomic determinants of the waves were then identified using factor analysis to extract underlying latent factors from 16 macroeconomic variables and employing a distributed lag model to investigate the effect of the extracted macroeconomic factors on the waves. Results showed that all factors (overall activity, market value, cost of debt, and inflation) significantly affected deal frequency in the hospitality industries studied. Theoretical and practical implications of the findings are presented. [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify tangible and intangible gains resulting from advertising in restaurant businesses from both the marketing and finance/accounting perspectives. Specifically, this study examined both behavioral and intermediate effects of advertising on consumer behavior and firm performance. Annual sales, profit, Tobin’s Q, and advertising expenditure of 119 restaurant firms from 1991 to 2012 were used for data analysis. The findings revealed that advertising led to an immediate increase in consumer demand, but failed to improve profit. The effect of advertising on sales and profit through brand equity was found to be insignificant. This study suggests a new angle on the use of advertising and brand strategies in the restaurant industry and discusses potential directions for future research. [ABSTRACT FROM AUTHOR]