Hypoxic acclimatization training improves the resistance to motion sickness

ObjectiveVestibular provocation is one of the main causes of flight illusions, and its occurrence is closely related to the susceptibility of motion sickness (MS). However, existing training programs have limited effect in improving the resistance to motion sickness. In this study, we investigated the effects of hypoxia acclimatization training (HAT) on the resistance to motion sickness.MethodsHealthy military college students were identified as subjects according to the criteria. MS model was induced by a rotary chair. Experimental groups included control, HAT, 3D roller training (3DRT), and combined training.ResultsThe Graybiel scores were decreased in the HAT group and the 3DRT group and further decreased in the combined training group in MS induced by the rotary chair. Participants had a significant increase in blood pressure after the rotary chair test and a significant increase in the heart rate during the rotary chair test, but these changes disappeared in all three training groups. Additionally, LFn was increased, HFn was decreased, and LF/HF was increased accordingly during the rotary chair test in the control group, but the changes of these three parameters were completely opposite in the three training groups during the rotary chair test. Compared with the control group, the decreasing changes in pupillary contraction velocity (PCV) and pupillary minimum diameter (PMD) of the three training groups were smaller. In particular, the binocular PCV changes were further attenuated in the combined training group.ConclusionOur research provides a possible candidate solution for training military pilots in the resistance to motion sickness

Synthesis and characterization of a series of novel 2-Schiff base-substituted phenylpyrimidine

A new series of pyrimidine derivatives containing Schiff bases structure have been synthesized efficiently by modification of the C-2 position of Biginelli 3,4-dihydropyrimidin-2-(1H)-thiones (DHPMs). Their structures have been characterized by IR, 1H NMR, 13C NMR, MS spectra and elemental analysis

Portfolio Construction for Pharmaceutical Industry

In finance area, portfolio construction is one of the most vital questions since the primary work of modern finance and attract numerous studies. In this paper, we focused on this issue in pharmaceutical industry since the industry is crucial for human beings. We adopted several methods for portfolio construction, like Equal Weighted Model, Monte Carlo simulation, and maximize Sharpe ratio etc. Specifically, five assets are selected. Then based on the Monte Carlo method, we constructed two optimized portfolios in the framework of the efficient frontier, i.e., portfolios with minimum variance and maximum Sharpe ratio. By analyzing the two portfolios, we found that the NVS accounts for the largest proportions in the optimized portfolio. The results in this paper may shed lights for certain investors who invest in pharmaceutical industry

An intelligent weighted clustering algorithm (IWCA) for Ad Hoc

Intelligent management to the large scale Ad Hoc network has already become a kind of trend, and the clustering algorithm is the key. This article examines formula factors and their mutual relations of EWCA algorithm weights. After considering complex external environment of nodes, digging factors of network, it proposes an algorithn that calculates, sets and adjusts these weights by comparing weights, efficent-weights and expecting-weights, so as to fit for all kinds of application environment. The algorithm does not only guarantee the rational and effective weights, but also run in a human friendly manner.E

Quantitative evaluation of unmanned ground vehicle trajectory based on chaos theory

The quantitative evaluation of unmanned ground vehicles is difficult. For this problem, we propose a quantitative evaluation method based on chaos theory. First, the ideal trajectory of an unmanned ground vehicle was designed applying the quintic polynomial method, and the deviation time series were obtained by calculating the deviation of the actual trajectory from the ideal trajectory. Then, the phase space of the deviation time series was reconstructed based on the improved algorithm using correlation integral method. Finally, the Lyapunov exponent of the deviation time series was calculated, which was the quantitative presentation of the unmanned ground vehicle’s trajectory. The quantitative presentation of the unmanned ground vehicle’s trajectory for lane keeping, obstacle avoidance, and overtaking lane changing was achieved. The Lyapunov exponent of lane keeping was the least, so the maximum predicted time was the longest. Lane keeping was done the best of all. Experimental results show that the quantitative evaluation method based on chaos theory for unmanned ground vehicle trajectory is feasible and effective

PSII Activity Was Inhibited at Flowering Stage with Developing Black Bracts of Oat

The color of bracts generally turns yellow or black from green during cereal grain development. However, the impact of these phenotypic changes on photosynthetic physiology during black bract formation remains unclear. Two oat cultivars (Avena sativa L.), ‘Triple Crown’ and ‘Qinghai 444’, with yellow and black bracts, respectively, were found to both have green bracts at the heading stage, but started to turn black at the flowering stage and become blackened at the milk stage for ‘Qinghai 444’. Their photosynthetic characteristics were analyzed and compared, and the key genes, proteins and regulatory pathways affecting photosynthetic physiology were determined in ‘Triple Crown’ and ‘Qinghai 444’ bracts. The results show that the actual PSII photochemical efficiency and PSII electron transfer rate of ‘Qinghai 444’ bracts had no significant changes at the heading and milk stages but decreased significantly (p < 0.05) at the flowering stage compared with ‘Triple Crown’. The chlorophyll content decreased, the LHCII involved in the assembly of supercomplexes in the thylakoid membrane was inhibited, and the expression of Lhcb1 and Lhcb5 was downregulated at the flowering stage. During this critical stage, the expression of Bh4 and C4H was upregulated, and the biosynthetic pathway of p-coumaric acid using tyrosine and phenylalanine as precursors was also enhanced. Moreover, the key upregulated genes (CHS, CHI and F3H) of anthocyanin biosynthesis might complement the impaired PSII activity until recovered at the milk stage. These findings provide a new insight into how photosynthesis alters during the process of oat bract color transition to black

Artificial neural network models for forecasting the combustion and emission characteristics of ethanol/gasoline DFSI engines with combined injection strategy

Ethanol was a viable alternative and renewable fuel for spark ignition engines, and ethanol/gasoline dual-fuel combustion with combined injection strategy can strengthen the benefits of using ethanol in engines. However, delicate calibration and optimization were required for ethanol/gasoline DFSI engines due to their higher control complexity and flexibility. Therefore, Artificial Neural Network (ANN) models were developed to represent the performance of DFSI engines. This study established the architecture for the ANN models of ethanol/gasoline DFSI engines, and the topology of 8-36-24-3, 8-64-70-6, 8-48-48-3, and 8-36-16-2 were suggested for the modeling of performance, combustion characteristics, gaseous and PN emissions, respectively. The non-linear relationship between the core control variables and performance, combustion, and emission characteristics of ethanol/gasoline engines can be accurately mapped by the proposed ANN models. The regression values were within the range of 0.9387–0.9962, and the mean square relative errors were within the range of 0.000184–0.03935 between the ANN predicted and experimentally measured results. Moreover, the ANN models had the advantages of high accuracy, sound model completeness, superior robustness, and satisfied reliability, which were desirable for the calibration and optimization of engines