This study investigated people’s ethical concerns of surveillance technology. By adopting the spectrum of technological utopian and dystopian narratives, how people perceive a society constructed through the compulsory use of surveillance technology was explored. This study empirically examined the anonymous online expression of attitudes toward the society-wide, compulsory adoption of a contact tracing app that affected almost every aspect of all people’s everyday lives at a societal level. By applying the structural topic modeling approach to analyze comments on four Hong (...) Kong anonymous discussion forums, topics concerning the technological utopian, dystopian, and pragmatic views on the surveillance app were discovered. The findings showed that people with a technological utopian view on this app believed that the implementation of compulsory app use can facilitate social good and maintain social order. In contrast, individuals who had a technological dystopian view expressed privacy concerns and distrust of this surveillance technology. Techno-pragmatists took a balanced approach and evaluated its implementation practically. (shrink)

BackgroundThe Chinese version of the Mini-Mental State Examination and the Beijing version of the Montreal Cognitive Assessment are the most commonly used scales to screen for Alzheimer’s disease among Chinese patients; however, their consistency varies according to populations and languages. Equivalent conversion of MMSE-C and MoCA-BJ scores is important for meta-analysis.Materials and methodsMMSE-C and MoCA-BJ scoring were performed on the enrolled patients with AD. Consistency analysis of MMSE-C and MoCA-BJ scores of patients in the conversion groups was performed. The circle-arc (...) method was used to convert the MMSE-C scores of the conversion groups into MoCA-BJ scores, and the conversion formula was generated. The MMSE-C data of the verification group was converted to MoCA-BJ according to the formula, and the consistency analysis of the original MoCA-BJ of the verification group and the converted MoCA-BJ was performed to verify the conversion model.ResultsThe results of the consistency analysis of MMSE-C and MoCA-BJ in group A showed that the correlation coefficients of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.905, 0.874, 0.949, and 0.874, respectively, with high consistency and statistical significance. After applying the circle-arc method for equivalent conversion, the consistency analysis results of the original and the converted MoCA-BJ of the patients in group B of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.891, 0.894, 0.781, 0.909, respectively, with high consistency and statistical significance.ConclusionWe established and validated a model of MMSE-C and MoCA-BJ score conversion for Chinese patients with AD using the circle-arc method. This model could be useful for multi-centers clinical trials and meta-analysis. (shrink)

PurposeOlder adults aged 60 years and above are classified as being of high-risk for infection during the COVID-19 pandemic. This study aimed to investigate the associations of psychological factors of preventive behaviors with three preventive behaviors among Chinese older adults during the COVID-19 pandemic.MethodsA cross-sectional questionnaire survey was administered via SOJUMP, a widely used online survey platform in China. A total of 928 older adults were recruited using a snowball sampling approach from Hubei Province and outside Hubei Province in China (...) during May 18, 2020 to June 7, 2020. Multiple hierarchical regressions were conducted with four models to examine the association between demographic, past behavior, psychological factors and each preventive behavior.Principal FindingsAll three preventive behaviors in older adults increased dramatically during the pandemic of COVID-19. Gender, living status, educational level, past behavior, health knowledge, intention and planning significantly predicted hand washing behavior, R2 = 0.395, F = 54.372, p < 0.001. Gender, education level, important others infection, past behavior, health knowledge, planning and action control significantly predicted mask wearing behavior, R2 = 0.202, F = 23.197, p < 0.001. Living place, past behavior and health knowledge significantly predicted social distancing behavior, R2 = 0.204, F = 26.201, p < 0.001.Major ConclusionsPast behavior and health knowledge predicted all three preventive behaviors. Planning was an important psychological factor for both hand washing and mask wearing behaviors. All those critical demographic and psychological factors are critical for future interventions to facilitate older adults to comply with three preventive behaviors in daily life and to stay healthy during the COVID-19 pandemic. (shrink)

The extent to which visual processing can proceed in the visual hierarchy without awareness determines the magnitude of perceptual delay. Increasing data demonstrate that primary visual cortex (V1) is involved in consciousness, constraining the magnitude of visual delay. This makes it possible that visual delay is actually within the optimal lengths to allow sufficient computation; thus it might be unnecessary to compensate for visual delay.

A test procedure optimization method was proposed in this paper to improve the test efficiency of the industrial robot servo system to be tested on the IRSS integrated testing platform. First, an ordered sequence was used to define the IRSS test project when tested on the IITP. The ordered sequence consisted of execution subelements, which were a combination of control variable parameters of the IITP. Second, the optimization relationships among the IRSS test projects were dug out according to the IRSS (...) test project sequences. Finally, by using the traveling salesmen problem, an optimization model was established based on the optimization relationships of the IRSS test projects, and the optimal test order of the IRSS test projects to be tested on the IITP was obtained by solving the model. A case analysis showed that the proposed method optimized the test procedure on the IITP effectively, and the test time when implementing the test on the IITP according to the optimized order was nearly 50% shorter than before optimization. The optimization effect was thus found to be significant. (shrink)

This study introduces a dual-channel supply chain including a supplier and a retailer with capital constraints, in which the retailer can apply for the trade credit financing from the supplier. This work investigates the effects of two typical behaviors, free riding behavior and consumer switching behavior, on inventory, ordering, and sales effort decisions in decentralized and centralized decision situations with stochastic demand. In order to achieve the optimal performance in the centralized system, this research designs a partial buyback contract to (...) coordinate the supply chain. Furthermore, numerical analysis is provided to test the feasibility of the model. The results indicate that in the dual-channel supply chain with the above two behaviors, the optimal sales effort level, optimal order quantity, the optimal offline, and online profits under the centralized decision-making are more than those under decentralized scenario, except for the optimal inventory level; the increase of the offline consumer switching rate will lead to the reduction of the offline order quantity and the offline expected profit and raise the online inventory level and the online expected profit; the increase of the online consumer switching rate will raise the offline order quantity and the offline expected profit but has no significant impact on the online inventory level and the online expected profit; the increase of the free riding coefficient of the supplier, no matter whether in decentralized or centralized systems, will reduce the offline sales effort level, the offline expected profit, and the online expected profit and raise the inventory level. Finally, this work provides some managerial implication. (shrink)

Accurate short-term traffic flow modeling is an essential prerequisite to analyze and control traffic flow. Canonical data-driven methods are a large account of parameters that may be underfitted with limited training samples, yet they cannot adaptively boost their understanding of the spatiotemporal dependencies of the traffic flow. The noisy and unstable traffic flow data also prevent the models from effectively learning the underlying patterns for forecasting future traffic flow. To address these issues, we propose an easy-to-implement yet effective boosting model (...) based on extreme gradient boosting and enhance it by wavelet denoising for short-term traffic flow forecasting. The discrete wavelet denoising is employed to preprocess the noisy traffic flow data. Then, the denoised training datasets are reconstructed to train the extreme gradient boosting model. These two components are integrated seamlessly in a unified framework, and the whole framework can retain the features in the data as much as possible. Our model can precisely capture the hidden spatial dependency in the data. Extensive experiments are conducted on four benchmark datasets compared with frequently used models. The results demonstrate that the proposed model can precisely capture the hidden spatial dependency of the traffic flow data and achieve superior performance. (shrink)