Cultural Impact on Customer Satisfaction and Service Quality Evaluation in Hotels

Purpose: The purpose of this paper is to identify how the cultural differences impact customer satisfaction and service quality evaluation in U.S. hotels. Statement of Objective: The objective of this paper is threefold. The first objective is to define customer satisfaction and what customer satisfaction means to people from different cultural backgrounds. The second objective is to evaluate past research on satisfaction and to develop a taxonomy based on the existing literature to introduce how to measure customers’ satisfaction effectively in accordance with each culture. The third objective is to recommend what should be done by the hotel professionals in order to increase international guests’ satisfaction. Justification: This research has implications for hotel operators due to increases in international traveling. Therefore, it is very imperative to understand different cultures and identify service areas that can be improved upon in order to satisfy guests from around the world. This paper may aid hoteliers in identifying what is the best way to measure cultural attributes, which then will help prepare better services to the international travelers by understanding their culture more deeply. It also has implications for future researchers in the field to investigate how culture impacts customers’ satisfaction, using cultures that are not investigated in this study. There are ramifications of not investigating this field, which are: 1. The hoteliers in the U.S. will not be able to meet the international travelers’ expectations of service without understanding their needs first. 2. The potential customer loyalty to the hotel may diminish due to the hotels’ inefficient accommodations based on the cultural aspects of satisfaction

Improved Flood Insights: Diffusion-Based SAR to EO Image Translation

Driven by rapid climate change, the frequency and intensity of flood events are increasing. Electro-Optical (EO) satellite imagery is commonly utilized for rapid response. However, its utilities in flood situations are hampered by issues such as cloud cover and limitations during nighttime, making accurate assessment of damage challenging. Several alternative flood detection techniques utilizing Synthetic Aperture Radar (SAR) data have been proposed. Despite the advantages of SAR over EO in the aforementioned situations, SAR presents a distinct drawback: human analysts often struggle with data interpretation. To tackle this issue, this paper introduces a novel framework, Diffusion-Based SAR to EO Image Translation (DSE). The DSE framework converts SAR images into EO images, thereby enhancing the interpretability of flood insights for humans. Experimental results on the Sen1Floods11 and SEN12-FLOOD datasets confirm that the DSE framework not only delivers enhanced visual information but also improves performance across all tested flood segmentation baselines.Comment: 10 pages, 6 figure

Simple Baseline for Weather Forecasting Using Spatiotemporal Context Aggregation Network

Traditional weather forecasting relies on domain expertise and computationally intensive numerical simulation systems. Recently, with the development of a data-driven approach, weather forecasting based on deep learning has been receiving attention. Deep learning-based weather forecasting has made stunning progress, from various backbone studies using CNN, RNN, and Transformer to training strategies using weather observations datasets with auxiliary inputs. All of this progress has contributed to the field of weather forecasting; however, many elements and complex structures of deep learning models prevent us from reaching physical interpretations. This paper proposes a SImple baseline with a spatiotemporal context Aggregation Network (SIANet) that achieved state-of-the-art in 4 parts of 5 benchmarks of W4C22. This simple but efficient structure uses only satellite images and CNNs in an end-to-end fashion without using a multi-model ensemble or fine-tuning. This simplicity of SIANet can be used as a solid baseline that can be easily applied in weather forecasting using deep learning.Comment: 1st place solution for stage1 and Core Transfer in the Weather4Cast competition on NeurIPS 2

Domain Generalization Strategy to Train Classifiers Robust to Spatial-Temporal Shift

Deep learning-based weather prediction models have advanced significantly in recent years. However, data-driven models based on deep learning are difficult to apply to real-world applications because they are vulnerable to spatial-temporal shifts. A weather prediction task is especially susceptible to spatial-temporal shifts when the model is overfitted to locality and seasonality. In this paper, we propose a training strategy to make the weather prediction model robust to spatial-temporal shifts. We first analyze the effect of hyperparameters and augmentations of the existing training strategy on the spatial-temporal shift robustness of the model. Next, we propose an optimal combination of hyperparameters and augmentation based on the analysis results and a test-time augmentation. We performed all experiments on the W4C22 Transfer dataset and achieved the 1st performance.Comment: Core Transfer Track 1st place solution in Weather4Cast competition at NeuIPS2

Traditional Herbal Formula Banhasasim-tang

Banhasasim-tang (BHSST) is a Korean traditional herbal formula comprising eight medicinal herbs. The aim of the present study was to investigate the anti-inflammatory effect of BHSST using macrophage and keratinocyte cell lines. First, we evaluated the effects of BHSST on inflammatory mediator and cytokine production in lipopolysaccharide- (LPS-) stimulated RAW 264.7 macrophages. BHSST markedly inhibited the production of nitric oxide (NO), prostaglandin E2 (PGE2), and interleukin- (IL-) 6. BHSST significantly suppressed the protein expression of toll-like receptor 4 (TLR4) and phosphorylated nuclear factor-kappa B (NF-κB) p65 in RAW 264.7 cells. Second, we examined whether BHSST influences the production of chemokines and STAT1 phosphorylation in tumor necrosis factor-α/interferon-γ TI-stimulated HaCaT keratinocytes. BHSST significantly suppressed the production of RANTES/CCL5, TARC/CCL17, MDC/CCL22, and IL-8 in TI-stimulated HaCaT cells. BHSST also suppressed TI-induced phosphorylation of STAT1 in HaCaT cells. These results suggest that BHSST may be useful as an anti-inflammatory agent, especially for inflammatory skin diseases

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration

Motor deficits are observed in Alzheimer’s disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans

Locally Activating TrkB Receptor Generates Actin Waves and Specifies Axonal Fate

Actin waves are filamentous actin (F-actin)-rich structures that initiate in the somato-neuritic area and move toward neurite ends. The upstream cues that initiate actin waves are poorly understood. Here, using an optogenetic approach (Opto-cytTrkB), we found that local activation of the TrkB receptor around the neurite end initiates actin waves and triggers neurite elongation. During actin wave generation, locally activated TrkB signaling in the distal neurite was functionally connected with preferentially localized Rac1 and its signaling pathways in the proximal region. Moreover, TrkB activity changed the location of ankyrinG––the master organizer of the axonal initial segment-and initiated the stimulated neurite to acquire axonal characteristics. Taken together, these findings suggest that local Opto-cytTrkB activation switches the fate from minor to major axonal neurite during neuronal polarization by generating actin waves.C. 2019 Elsevier Ltd.11Nsciescopu

LONP1 and ClpP cooperatively regulate mitochondrial proteostasis for cancer cell survival

Mitochondrial proteases are key components in mitochondrial stress responses that maintain proteostasis and mitochondrial integrity in harsh environmental conditions, which leads to the acquisition of aggressive phenotypes, including chemoresistance and metastasis. However, the molecular mechanisms and exact role of mitochondrial proteases in cancer remain largely unexplored. Here, we identified functional crosstalk between LONP1 and ClpP, which are two mitochondrial matrix proteases that cooperate to attenuate proteotoxic stress and protect mitochondrial functions for cancer cell survival. LONP1 and ClpP genes closely localized on chromosome 19 and were co-expressed at high levels in most human cancers. Depletion of both genes synergistically attenuated cancer cell growth and induced cell death due to impaired mitochondrial functions and increased oxidative stress. Using mitochondrial matrix proteomic analysis with an engineered peroxidase (APEX)-mediated proximity biotinylation method, we identified the specific target substrates of these proteases, which were crucial components of mitochondrial functions, including oxidative phosphorylation, the TCA cycle, and amino acid and lipid metabolism. Furthermore, we found that LONP1 and ClpP shared many substrates, including serine hydroxymethyltransferase 2 (SHMT2). Inhibition of both LONP1 and ClpP additively increased the amount of unfolded SHMT2 protein and enhanced sensitivity to SHMT2 inhibitor, resulting in significantly reduced cell growth and increased cell death under metabolic stress. Additionally, prostate cancer patients with higher LONP1 and ClpP expression exhibited poorer survival. These results suggest that interventions targeting the mitochondrial proteostasis network via LONP1 and ClpP could be potential therapeutic strategies for cancer

Breakfast habits, sedentary behavior, and suicide among Korean adolescents: A cross-sectional national study.

This study aims to identify the relationships between breakfast habits, leisure-time sedentary behavior, and suicidal behaviors among Korean adolescents, including the mediating effect of leisure-time sedentary behavior on the relationship between breakfast habits and suicidal behaviors. We conducted a cross-sectional national study using secondary data from the 2017-2019 (13-15th) Korea Youth Risk Behavior Web-Based Surveys, analyzing data from a final sample of 153,992 Korean adolescents using multivariate logistic regression. No breakfast habits were statistically significantly related to suicidal ideation (crude OR [COR], 95% CI = 1.218, 1.172-1.265), suicidal plans (COR, 95% CI = 1.305, 1.228-1.385), and suicide attempts (COR, 95% CI = 1.533, 1.432-1.642). The effects of breakfast habits (independent variable) on suicidal behaviors (outcome variables) were mediated by leisure-time sedentary behavior (mediating variable). Leisure-time sedentary behavior had a statistically significant indirect effect on breakfast habits and suicidal behaviors (p < 0.05). The mediating effect size of breakfast habits mediated by leisure-time sedentary behavior was 3.46% for suicidal ideation, 2.48% for suicidal plans, and 1.06% for suicide attempts. Adolescents who did not consume breakfast demonstrated a significantly higher possibility of suicidal ideation, suicidal plans, and suicide attempts. Parents and teachers should be aware of and monitor adolescents' leisure-time sedentary behavior and breakfast habits to prevent suicidal behavior among this age group