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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]

Diffusion magnetic resonance imaging (dMRI) is an important tool in characterizing tissue microstructure based on biophysical models, which are typically multi-compartmental models with mathematically complex and highly non-linear forms. Resolving microstructures from these models with conventional optimization techniques is prone to estimation errors and requires dense sampling in the q-space with a long scan time. Deep learning based approaches have been proposed to overcome these limitations. Motivated by the superior performance of the Transformer in feature extraction than the convolutional structure, in this work, we present a learning-based framework based on Transformer, namely, a Microstructure Estimation Transformer with Sparse Coding (METSC) for dMRI-based microstructural parameter estimation. To take advantage of the Transformer while addressing its limitation in large training data requirement, we explicitly introduce an inductive bias—model bias into the Transformer using a sparse coding technique to facilitate the training process. Thus, the METSC is composed with three stages, an embedding stage, a sparse representation stage, and a mapping stage. The embedding stage is a Transformer-based structure that encodes the signal in a high-level space to ensure the core voxel of a patch is represented effectively. In the sparse representation stage, a dictionary is constructed by solving a sparse reconstruction problem that unfolds the Iterative Hard Thresholding (IHT) process. The mapping stage is essentially a decoder that computes the microstructural parameters from the output of the second stage, based on the weighted sum of normalized dictionary coefficients where the weights are also learned. We tested our framework on two dMRI models with downsampled q-space data, including the intravoxel incoherent motion (IVIM) model and the neurite orientation dispersion and density imaging (NODDI) model. The proposed method achieved up to 11.25 folds of acceleration while retaining high fitting accuracy for NODDI fitting, reducing the mean squared error (MSE) up to 70% compared with the previous q-space learning approach. METSC outperformed the other state-of-the-art learning-based methods, including the model-free and model-based methods. The network also showed robustness against noise and generalizability across different datasets. The superior performance of METSC indicates its potential to improve dMRI acquisition and model fitting in clinical applications. • We proposed a generic Transformer, METSC, for microstructure estimation in diffusion MRI. • We propose to introduce model-bias to reduce the data demand of the Transformer structure. • METSC was evaluated on two diffusion MRI models with downsampled q-space data. • METSC outperformed other state-of-the-art methods in estimation accuracy, robustness, and generalizability. [ABSTRACT FROM AUTHOR]

This study used Autoregressive Integrated Moving Average with Intervention analysis technique to examine weekly stock indices of the hotel segment and the casino hotel segment in comparison with the S&P 500 index. The results indicate that casino hotel firms were affected at the beginning of the recession and hotel firms and S&P 500 firms were not affected until nine months later. In addition, this study performed multiple t-tests to compare the average financial ratios between the two hotel segments to reveal changes in financial structures through the recession. The findings of this study may help industry practitioners and investors cope with future economic downturns and fill a gap in the existing literature by demonstrating the process of identifying lag time of an impact using ARIMA with Intervention Analysis technique. [ABSTRACT FROM AUTHOR]

Using the single-period inventory model, optimal monthly room capacity was identified for Shanghai's high-end hotels and compared to existing hotel capacity to determine the magnitude of overcapacity in 2011. To cope with overcapacity, this study suggests (a) Shanghai should refrain from developing new high-end hotels to let the demand catch up with the supply; (b) the hotel industry may convert a part of its high-end hotels to condo hotels or time share properties; and (c) Shanghai should take full advantage of the recent World Expo to position and promote itself as a top destination of meetings, incentives, conferences, and exhibitions in the world. [ABSTRACT FROM PUBLISHER]

Using content analysis, this study examined online comments of six luxury resort properties located in a popular travel destination in the southwestern United States. By categorizing and analyzing the online comments, the study not only revealed customers' online complaint behaviors, but also identified reasons customers post comments online. Suggestions for practitioners are provided for responding to online customer comments. [ABSTRACT FROM AUTHOR]

Training is one human resource development practice found in most organizations, however, studies showed that little attention is given to the importance of training evaluation in real life practices. This study is an exploration of the practices and perceptions of hotel managers in training evaluation using Kirkpatrick's and Phillips's models. In-depth interviews were conducted with six hotel managers and paper-based questionnaires were sent out to managers of hotels with more than 30 rooms in a Midwestern state. The findings indicated that hotel managers viewed training evaluation activities as important and observation was rated the most important and the most frequently employed method for managers in evaluating training. The study's findings contribute to the literature by providing researchers with more insights into how hotel managers evaluate their training and what they believed a practical process should possess. It also gives researchers a brief understanding of the perceptions of managers from different hotel sizes. [ABSTRACT FROM AUTHOR]

Oregon wineries have become increasingly reliant on tasting-room employees to increase wine distribution. Properly training tasting-room employees is essential to increasing sales of wine at wineries. In this study, the researchers explore the methods, techniques, and practices employed to train Oregon tasting-room employees. The results indicate managers perceive product knowledge as the most common form of training needed for tasting-room employees to succeed. Sales incentives were not consistent in the findings of the training programs. Three out of every four managers responded that job shadowing was the most popular form of training in their tasting rooms. [ABSTRACT FROM PUBLISHER]

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 GPAs were obtained from the registrar's office. Data were analyzed using t-test, principal component analysis, and stepwise regression. The results were consistent with delayed sleep phrase syndrome, a common sleep problem in college students. Also, sleep latency and sleep medicine were negatively correlated with academic performance, and sleep quality was significantly associated with job performance. The knowledge of the impact of sleep is effective for educators and employers in helping students with sleep problems. Educators and employers need to be cognizant of the importance of sleep for students' success in their academic performance and job performance. [ABSTRACT FROM AUTHOR]

Objective: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases.The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.QuestionHow do specific site MRI acquisition factors affect fetal brain imaging?FindingLower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution.Clinical relevanceThis study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.Materials and methods: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases.The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.QuestionHow do specific site MRI acquisition factors affect fetal brain imaging?FindingLower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution.Clinical relevanceThis study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.Results: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases.The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.QuestionHow do specific site MRI acquisition factors affect fetal brain imaging?FindingLower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution.Clinical relevanceThis study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.Conclusion: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases.The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.QuestionHow do specific site MRI acquisition factors affect fetal brain imaging?FindingLower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution.Clinical relevanceThis study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.Key Points: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases.The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.QuestionHow do specific site MRI acquisition factors affect fetal brain imaging?FindingLower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution.Clinical relevanceThis study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies. [ABSTRACT FROM AUTHOR]