Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation

Unsupervised domain adaptation for semantic segmentation has been intensively studied due to the low cost of the pixel-level annotation for synthetic data. The most common approaches try to generate images or features mimicking the distribution in the target domain while preserving the semantic contents in the source domain so that a model can be trained with annotations from the latter. However, such methods highly rely on an image translator or feature extractor trained in an elaborated mechanism including adversarial training, which brings in extra complexity and instability in the adaptation process. Furthermore, these methods mainly focus on taking advantage of the labeled source dataset, leaving the unlabeled target dataset not fully utilized. In this paper, we propose a bidirectional style-induced domain adaptation method, called BiSIDA, that employs consistency regularization to efficiently exploit information from the unlabeled target domain dataset, requiring only a simple neural style transfer model. BiSIDA aligns domains by not only transferring source images into the style of target images but also transferring target images into the style of source images to perform high-dimensional perturbation on the unlabeled target images, which is crucial to the success in applying consistency regularization in segmentation tasks. Extensive experiments show that our BiSIDA achieves new state-of-the-art on two commonly-used synthetic-to-real domain adaptation benchmarks: GTA5-to-CityScapes and SYNTHIA-to-CityScapes

Scraping social media photos posted in Kenya and elsewhere to detect and analyze food types

Monitoring population-level changes in diet could be useful for education and for implementing interventions to improve health. Research has shown that data from social media sources can be used for monitoring dietary behavior. We propose a scrape-by-location methodology to create food image datasets from Instagram posts. We used it to collect 3.56 million images over a period of 20 days in March 2019. We also propose a scrape-by-keywords methodology and used it to scrape ∼30,000 images and their captions of 38 Kenyan food types. We publish two datasets of 104,000 and 8,174 image/caption pairs, respectively. With the first dataset, Kenya104K, we train a Kenyan Food Classifier, called KenyanFC, to distinguish Kenyan food from non-food images posted in Kenya. We used the second dataset, KenyanFood13, to train a classifier KenyanFTR, short for Kenyan Food Type Recognizer, to recognize 13 popular food types in Kenya. The KenyanFTR is a multimodal deep neural network that can identify 13 types of Kenyan foods using both images and their corresponding captions. Experiments show that the average top-1 accuracy of KenyanFC is 99% over 10,400 tested Instagram images and of KenyanFTR is 81% over 8,174 tested data points. Ablation studies show that three of the 13 food types are particularly difficult to categorize based on image content only and that adding analysis of captions to the image analysis yields a classifier that is 9 percent points more accurate than a classifier that relies only on images. Our food trend analysis revealed that cakes and roasted meats were the most popular foods in photographs on Instagram in Kenya in March 2019.Accepted manuscrip

Infinity Period Dynamic Control of a Kind of Channel’s Price and Brand Investment: A Differential Game Method

The infinity period dynamic control problem of distribution channel was studied with differential game approach. Four differential dynamic control models of coordinated channel game, uncoordinated static game, Stackelberg game with manufacture controlled, and Stackelberg game with n retailers controlled were constructed. Some results applied dynamic optimization theory made with Hamilton function. The conclusions are as follows. (1) Optimization brand investment controlled by manufacture has nothing to do with time. (2) Retail price was the most minimum when channel was integrated. (3) Manufacture’s profits of uncoordinated static game and Stackelberg game with manufacture controlled were more than Stackelberg game with n retailers controlled. (4) Retailer’s profits of Stackelberg game with n retailers controlled were less than Stackelberg game with manufacture controlled. (5) Channel’s total profits of Stackelberg game with n retailers controlled were the most minimum

Channels coordination game model based on result fairness preference and reciprocal fairness preference: a behavior game forecasting and analysis method,”

In a distribution channel, channel members are not always self-interested, but altruistic in some conditions. Based on this assumption, this paper adopts a behavior game method to analyze and forecast channel members' decision behavior based on result fairness preference and reciprocal fairness preference by embedding a fair preference theory in channel research of coordination. The behavior game forecasts that a channel can achieve coordination if channel members consider behavior elements. Using the behavior game theory model we established, we can prove that if retailers only consider the result fairness preference and they are not jealous of manufacturers' benefit, manufacturers will be more friendly to retailers. In such case, the total utility of the channel is higher compared with that of self-interest channel, and the utility of channel members is Pareto improved. If both manufactures and retailers consider reciprocal fairness preference, the manufacturers will give a lower wholesale price to the retailers. In return, the retailers will also reduce retail prices. Therefore, the total utility of the channels will not be less than the total utility of the channel coordination, as long as the reciprocity wholesale prices meet certain conditions

The relationship between childhood trauma and Internet gaming disorder among college students: A structural equation model

open access journalBackground The aim of this study was to investigate the mechanisms of Internet gaming disorder (IGD) and the associated interaction effects of childhood trauma, depression and anxiety in college students. Methods Participants were enrolled full-time as freshmen at a University in the Hunan province, China. All participants reported their socio-demographic characteristics and undertook a standardized assessment on childhood trauma, anxiety, depression and IGD. The effect of childhood trauma on university students' internet gaming behaviour mediated by anxiety and depression was analysed using structural equation modelling (SEM) using R 3.6.1. Results In total, 922 freshmen participated in the study, with an approximately even male-to-female ratio. A mediation model with anxiety and depression as the mediators between childhood trauma and internet gaming behaviour allowing anxiety and depression to be correlated was tested using SEM. The SEM analysis revealed that a standardised total effect of childhood trauma on Internet gaming was 0.18, (Z = 5.60, 95% CI [0.02, 0.05], P < 0.001), with the direct effects of childhood trauma on Internet gaming being 0.11 (Z = 3.41, 95% CI [0.01, 0.03], P = 0.001), and the indirect effects being 0.02 (Z = 2.32, 95% CI [0.00, 0.01], P = 0.020) in the pathway of childhood trauma-depression-internet gaming; and 0.05 (Z = 3.67, 95% CI [0.00, 0.02], P < 0.001) in the pathway of childhood trauma-anxiety-Internet gaming. In addition, the two mediators anxiety and depression were significantly correlated (r = 0.50, Z = 13.54, 95% CI [3.50, 5.05], P < 0.001). Conclusions The study revealed that childhood trauma had a significant impact on adolescents' Internet gaming behaviours among college students. Anxiety and depression both significantly mediated the relationship between childhood trauma and internet gaming and augmented its negative influence. Discussion of the need to understand the subtypes of childhood traumatic experience in relationship to addictive behaviours is included

A Comparative Study of Marketing Channel Multiagent Stackelberg Model Based on Perfect Rationality and Fairness Preference

This paper studies channel consisting of a manufacturer and two retailers. As a basis for comparison, the first, multiagent Stackelberg model has been structured based on perfect rationality. Further, fairness preference theory will be embedded in marketing channel multiagent Stackelberg model, and the results show that if the retailers have a jealous fairness preference, the manufacturer will reduce the wholesale price, retailers will increase the effort level, product sales will be increased, and the total channel utility and manufacturers’ utility will be pareto improvement, but the pareto improvement of retailers’ utility is associated with the interval of jealousy fairness preference coefficient. If the retailers have a sympathetic fairness preference, the manufacturer increases wholesale price, retailers reduce the effort level, and the total channel utility, manufacturer’s utility, and retailers’ utility are less than that of the no fairness preference utility

The Assessment on Synergistic Activity of Ebselen and Silver Ion Against Yersinia pseudotuberculosis

Yersinia pseudotuberculosis is a foodborne zoonotic bacterium that is pathogenic to guinea pigs, rabbits, and mice. It also causes pseudotuberculosis in humans. However, it still lacked the scientific basis for control. Here, we found out that Ebselen (EbSe) exhibited synergistic antibacterial activity with silver nitrate (Ag+) against Y. pseudotuberculosis YpIII strain with high efficacy in vitro using UV-visible light absorption spectrum, 5,5’-dithiobis-(2-nitrobenzoic acid), laser scanning confocal microscope, flow cytometry, transmission electron microscopy and Western blotting assays. The depletion of total glutathione (GSH) amount and inhibition of thioredoxin reductase (TrxR) activity in thiol-dependent redox system revealed the destructiveness of EbSe-Ag+-caused intracellular oxidative stress. Furthermore, a YpIII-caused mice gastroenteritis model was constructed. EbSe-Ag+ significantly reduced bacterial loads with low toxicity. It also down-regulated the expression levels of interferon (IL)-1β and tumor necrosis factor-α, up-regulated the expression level of IL-10 on-site. All the in vivo results demonstrated the antibacterial activity and immune-modulatory property of EbSe-Ag+. Collectively, these results provided academic fundament for further analysis and development of EbSe-Ag+ as the antibacterial agents for pseudotuberculosis control