The Determinants of Customer Satisfaction in Fast Food Industry

This primary objective of this study is to identify the determinants of customer satisfaction for KFC in Vietnam. Fast food industry developed rapidly in an emerging economy like Viet Nam. Current competition in Vietnamese fast food has required companies to pay more attention to customer satisfaction. Data is collected from KFC's customers in Ho Chi Minh City, Viet Nam. The research model is adopted from the SERVQUAL model (Parasuraman et al., 1988). The findings show that the main determinants of customer satisfaction of KFC Vietnam are Food Quality, Ambience, Price, Service Quality. Among these determinants, ambiance causes the most impact on customer satisfaction, following up by food quality and price. Managerial implications for KFC and other fast-food companies are discussed to improve customer satisfaction

Conditional Support Alignment for Domain Adaptation with Label Shift

Unsupervised domain adaptation (UDA) refers to a domain adaptation framework in which a learning model is trained based on the labeled samples on the source domain and unlabelled ones in the target domain. The dominant existing methods in the field that rely on the classical covariate shift assumption to learn domain-invariant feature representation have yielded suboptimal performance under the label distribution shift between source and target domains. In this paper, we propose a novel conditional adversarial support alignment (CASA) whose aim is to minimize the conditional symmetric support divergence between the source's and target domain's feature representation distributions, aiming at a more helpful representation for the classification task. We also introduce a novel theoretical target risk bound, which justifies the merits of aligning the supports of conditional feature distributions compared to the existing marginal support alignment approach in the UDA settings. We then provide a complete training process for learning in which the objective optimization functions are precisely based on the proposed target risk bound. Our empirical results demonstrate that CASA outperforms other state-of-the-art methods on different UDA benchmark tasks under label shift conditions

Delving into Ipsilateral Mammogram Assessment under Multi-View Network

In many recent years, multi-view mammogram analysis has been focused widely on AI-based cancer assessment. In this work, we aim to explore diverse fusion strategies (average and concatenate) and examine the model's learning behavior with varying individuals and fusion pathways, involving Coarse Layer and Fine Layer. The Ipsilateral Multi-View Network, comprising five fusion types (Pre, Early, Middle, Last, and Post Fusion) in ResNet-18, is employed. Notably, the Middle Fusion emerges as the most balanced and effective approach, enhancing deep-learning models' generalization performance by +2.06% (concatenate) and +5.29% (average) in VinDr-Mammo dataset and +2.03% (concatenate) and +3% (average) in CMMD dataset on macro F1-Score. The paper emphasizes the crucial role of layer assignment in multi-view network extraction with various strategies

Архієпископ Інокентій (Борисов) – організатор відновлення православних святинь Криму

Розглянуто внесок архієпископа Херсонського і Таврійського Інокентія (Борисова) у справу відновлення в Криму православних монастирів на місці раніше існуючих обителей. Цей проект ієрарха отримав назву «Російський Афон».Рассмотрен вклад архиепископа Херсонского и Таврического Иннокентия (Борисова) в дело восстановления в Крыму православных монастырей на месте ранее существовавших обителей. Данный проект иерарха получил название «Русский Афон».The article is devoted to the contribution of the Archbishop of Kherson and Taurida Innocent (Borisov) to the restoration of Orthodox monasteries in the Crimea on the place of pre-existing monasteries. This project by hierarch was called «Russian Athos»

MirrorNet: Bio-Inspired Camouflaged Object Segmentation

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the MirrorNet, that leverages both instance segmentation and mirror stream for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the mirror stream corresponding with the original image and its flipped image, respectively. The output from the mirror stream is then fused into the main stream's result for the final camouflage map to boost up the segmentation accuracy. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, outperforming the state-of-the-arts. Project Page: https://sites.google.com/view/ltnghia/research/camoComment: Under Revie

Synthesis of cuprous oxide nanocubes combined with chitosan nanoparticles and its application to p-nitrophenol degradation

For the first time, cuprous oxide nanocubes (Cu2O NCBs) were successfully combined with chitosan nanoparticles (CS NPs) to generate Cu2O NCBs/CS NPs composites material with highly optical property and photocatalytic activity using a simple and eco-friendly synthetic approach at room temperature for 30 min. The synthesized Cu2O NCBs NPs/CS NPs were determined characterizations by Ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), X – ray Diffraction (XRD),  Transmission Electron Microscope (TEM) and Energy-dispersive X-ray spectroscopy (EDX). Results show that the Cu2O NCBs/CS NPs composites have an average particle size of ~3-5 nm; in which, Cu2O has the form of nanocubes (Cu2O NCBs) with size ~3-4 nm and chitosan nanoparticles with spherical shape (CS NPs) with size ~4-5 nm. In addition, the percent (%) composition of elements present in Cu2O NCBs/CS NPs composites material have been obtained respective: Cu (23.99%), O (38.18%), and C (33.61%). Moreover, Cu2O NCBs/CS NPs composites material was also investigated for photocatalytic activity applied in p-nitrophenol degradation. The obtained results showed that the catalytic capability of Cu2O NCBs/CS NPs for p-nitrophenol reduction reached the highest efficiency >55% in the treatment time of 25 min, and this efficiency was higher than that result of using ZnO@chitosan nanoparticles (ZnO@CS NPs) catalyst under the same conditions for comparison

Use of and attitudes towards herbal medicine during the COVID-19 pandemic: a cross-sectional study in Vietnam

IntroductionHerbal medicine has a long and rich history of practice in Vietnam. However, research on this topic is limited, especially in relation to the COVID-19 pandemic. This study aimed to explore (1) the prevalence and indication for herbal medicine use, (2) factors associated with herbal medicine use, and (3) people's attitude toward the herbal medicine within the Vietnamese population.MethodsA cross-sectional online survey was conducted in Vietnamese adults aged 18 years and older, distributed equally across the Northern, Central, and Southern regions of Vietnam, between September and October 2020. Descriptive statistics, chi-square tests, and univariate and multivariate logistic regression analyses were performed to achieve the study objectives.ResultsNearly half of the respondents reported using herbal medicine for common illnesses during the COVID-19 pandemic. The prevalence was strongly associated with marital status, urbanicity, monthly income, and health status perception. Ginger (Zingiber officinale Rosc.), honey (Mel), garlic (Allium sativum L.), and perilla (Perilla frutescens (L.) Britt.) were the most commonly used herbal medicines, mainly for the treatment of sore throat, cough, nasal congestion, and fever. Nearly 70% of the participants believed herbal medicines to be safe, to have less side effects than conventional medicines, and to be effective for minor health conditions.ConclusionThe use of herbal medicine during the COVID-19 pandemic was a common practice among Vietnamese people. These findings may have implications for future medical research in Vietnam, and for policy-makers and those in the pharmaceutical industry with regard to future regulations and product development

Pathogenic Escherichia coli Possess Elevated Growth Rates under Exposure to Sub-Inhibitory Concentrations of Azithromycin.

Antimicrobial resistance (AMR) has been identified by the World Health Organization (WHO) as one of the ten major threats to global health. Advances in technology, including whole-genome sequencing, have provided new insights into the origin and mechanisms of AMR. However, our understanding of the short-term impact of antimicrobial pressure and resistance on the physiology of bacterial populations is limited. We aimed to investigate morphological and physiological responses of clinical isolates of E. coli under short-term exposure to key antimicrobials. We performed whole-genome sequencing on twenty-seven E. coli isolates isolated from children with sepsis to evaluate their AMR gene content. We assessed their antimicrobial susceptibility profile and measured their growth dynamics and morphological characteristics under exposure to varying concentrations of ciprofloxacin, ceftriaxone, tetracycline, gentamicin, and azithromycin. AMR was common, with all organisms resistant to at least one antimicrobial; a total of 81.5% were multi-drug-resistant (MDR). We observed an association between resistance profile and morphological characteristics of the E. coli over a three-hour exposure to antimicrobials. Growth dynamics experiments demonstrated that resistance to tetracycline promoted the growth of E. coli under antimicrobial-free conditions, while resistance to the other antimicrobials incurred a fitness cost. Notably, antimicrobial exposure heterogeneously suppressed bacterial growth, but sub-MIC concentrations of azithromycin increased the maximum growth rate of the clinical isolates. Our results outline complex interactions between organism and antimicrobials and raise clinical concerns regarding exposure of sub-MIC concentrations of specific antimicrobials