Search

BackgroundMotion sickness is characterized by nausea and vomiting among a constellation of symptoms. Symptom severity is dynamic and distressing. Most validated motion sickness scales are time-intensive and effortful, with alternative scales having uncertain performance or non-specific measures. A validated instrument allowing for facile, rapid assessment of core motion sickness symptom severity would therefore be valuable. We assessed the performance of the Motion Sickness Severity Scale (MSSS), a six-item questionnaire designed to measure real-time motion sickness symptoms.MethodsMSSS construct validity was assessed as a secondary analysis of data from 63 healthy participants without antiemetic treatment in a clinical trial (Unique Identifier = NCT03772340) conducted to evaluate the safety and efficacy of Tradipitant-a novel neurokinin-1 receptor antagonist-in the treatment of motion sickness. Clinical outcome assessments included the MSSS, the Patient Global Impression of Severity (PGI-S), and the Motion Sickness Assessment Questionnaire (MSAQ). The performance of the MSSS through Pearson correlation coefficients, within-group analysis of variance, empirical cumulative distribution functions, and Kolmogorov-Smirnov tests.ResultsThe MSSS correlated very highly with the PGI-S (r = 0.93, p-valueDiscussionThe MSSS is a valid instrument for the assessment of the core motion sickness symptoms and is reflective of global disease severity. Implementation of the MSSS and comparable simplified, short questionnaires in motion sickness research will provide rapid and accurate measures of disease severity. These measures will enable further elucidation of motion sickness as an illness and inform the development and evaluation of motion sickness therapies.

Increasing evidence demonstrates that hepatitis E virus (HEV) can be transmitted across species. According to previous reports, swine HEV has two genotypes, genotype 3 and 4, and both can infect humans by the fecal-oral route. Thus, it is crucial for the control of HEV zoonotic transmission to evaluate the dynamics of viral shedding and distribution in different tissues during cross-species infection by HEV. In this study, rabbits were infected with genotype 4 swine HEV by the intraperitoneal route. The results showed that HEV RNA not only shed in the feces but also in the saliva of some rabbits during infection with swine HEV. Viremia appeared late after infection, and anti-HEV IgG was not obvious until the appearance of high viremia levels. After the rabbits were euthanized, a histopathological examination showed that the livers developed overt hepatitis accompanied by an elevation of alanine aminotransferase (ALT) and aspartate transaminase (AST). Furthermore, HEV RNA was detected in various tissues, especially in the salivary glands and tonsils. Subsequently, negative-stranded HEV RNA was practiced in tissues with positive HEV RNA, which demonstrated that HEV replicated in the tissues. Next, we harvested additional tissues from the liver, salivary gland, tonsil, spleen, thymus gland, lymph node and intestine, which are known as replication sites of swine HEV. Additionally, we also observed the HEV antigen distributed in the organs above through immunohistochemical staining. These results demonstrate that rabbits could be used as an animal model for researching cross-species infection of genotype 4 HEV. It is also noteworthy that HEV can shed in the saliva and presents the risk of droplet transmission. These new data provide valuable information for understanding cross-species infection by HEV.

Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion.

The fern Dicranopteris dichotoma is an important pioneer species of the understory in Masson pine (Pinus massoniana) forests growing on acidic soils in the subtropical and tropical China. To improve our understanding of the role of D. dichotoma in nitrogen (N) uptake of these forests, a short-term (15)N experiment was conducted at mountain ridge (MR, with low N level) and mountain foot (MF, with high N level). We injected (15)N tracers as (15)NH4, (15)NO3 or (15)N-glycine into the soil surrounding each plant at both MR and MF sites. Three hours after tracer injection, the fern D. dichotoma took up 15NH4+ significantly faster at MF than at MR, but it showed significantly slower uptake of (15)NO3- at MF than at MR. Consequently, (15)NO3- made greater contribution to the total N uptake (50% to the total N uptake) at MR than at MF, but (15)N-glycine only contributed around 11% at both sites. Twenty-four hours after tracer injection, D. dichotoma preferred (15)NH4+ (63%) at MR, whereas it preferred (15)NO3- (47%) at MF. We concluded that the D. dichotoma responds distinctly in its uptake pattern for three available N species over temporal and spatial scales, but mainly relies on inorganic N species in the subtropical forest. This suggests that the fern employs different strategies to acquire available N which depends on N levels and time.

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.