Laterality and coherence analysis of Laser Doppler Flowmetry signals in bilateral Nèi guān(内关 PC 6):a potential non-invasive method to assess microcirculatory changes of people in different ages

Objective To investigate lateralization and Coherence analysis of blood perfusion in bilateral Neiguan （内关 PC 6） in different ages. Methods Healthy volunteers （n=30） were placed in a temperature-controlled room as a resting state for 40 min. Then the blood perfusion of bilateral PC 6 were carried out using PeriFlux System 5000 for 25 minutes. Mean blood flux of every 5 minutes was calculated. Then the participants were divided into groups of young （n=18） and the old （n=12） as the boundary of 40 years, the asymmetry index and coherence value of bilateral PC 6 were analyzed in different group. Results The mean blood flow of the right PC 6 was significantly higher than the left PC 6 in three different epochs, the mean blood flow of right PC 6 vs left PC 6 is 9.74±3.36 vs 6.73±2.22 （t=5.9, P〈0.001）, 9.83±3.63 vs 6.99±2.37 （t=5.11, P〈0.001） and 9.69±3.40 vs 6.77±2.32 （t=5.99, P〈0.001）, respectively. Although the asymmetry index is higher in old group than in young group, there is no statistically significant age-related differences. Coherence analysis suggest that there is significant difference in frequency value corresponding to peak crest between young and old group. Conclusion The blood perfusion in right PC 6 is higher than left PC 6. Coherence analysis of laser Doppler flowmetry signals in bilateral PC 6 might provide a potential non-invasive method to assess microcirculatory changes in different ages.

The GNSS PWV retrieval using non-observation meteorological parameters based on ERA5 and its relation with precipitation

The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.

Analysis on China＇s Lottery Economy

From such aspects as fiscal and tax revenue, employment and consumption demand, this paper firstly analyzes the impacts that lottery produces to China＇s economy. On the basis of this analysis, it then probes into discussing the contributions that lottery makes to the development of the sports and welfare. Finally, by utilizing gray system model, a coherence analysis between lottery industry and China＇s macro-economy was made.

Time-Frequency Characteristics of the Relationships Between Tropical Indo-Pacific SSTs

In this study, several advanced analysis methods are applied to understand the relationships between the Nino-3.4 sea surface temperatures （SST） and the SSTs related to the tropical Indian Ocean Dipole （IOD）. By analyzing a long data record, the authors focus on the time-frequency characteristics of these relationships, and of the structure of IOD. They also focus on the seasonal dependence of those characteristics in both time and frequency domains. Among the Nino-3.4 SST, IOD, and SSTs over the tropical western Indian Ocean （WIO） and eastern Indian Ocean （EIO）, the WIO SST has the strongest annual and semiannual oscillations. While the Nino-3.4 SST has large inter-annual variability that is only second to its annual variability, the IOD is characterized by the largest semiannual oscillation, which is even stronger than its annual oscillation. The IOD is strongly and stably related to the EIO SST in a wide range of frequency bands and in all seasons. However, it is less significantly related to the WIO SST in the boreal winter and spring. There exists a generally weak and unstable relationship between the WIO and EIO SSTs, especially in the biennial and higher frequency bands. The relationship is especially weak in summer and fall, when IOD is apparent, but appears highly positive in winter and spring, when the IOD is unimportantly weak and even disappears. This feature reflects a caution in the definition and application of IOD. The Nino-3.4 SST has a strong positive relationship with the WIO SST in all seasons, mainly in the biennial and longer frequency bands. However, it shows no significant relationship with the EIO SST in summer and fall, and with IOD in winter and spring.

Seismic attributes and integrated prediction of fractured and caved carbonate reservoirs in the Tarim Basin,China

The carbonate reservoirs in the Tarim Basin are characterized by anisotropy and strong heterogeneity.Combined with an integrated analysis of data from seismic,geology,and drilling results,a series of attributes which are suitable for fractured and caved carbonate reservoir prediction is discussed,including amplitude,coherence analysis,spectra decomposition,seismic absorption attenuation analysis and impedance inversion.Moreover,3-D optimization of these attributes is achieved by integration of multivariate discriminant analysis and principle component analysis,where the logging data are taken as training samples.Using the optimized results,the spatial distribution and configuration features of the caved reservoirs can be characterized in detail.This technique not only improves the understanding of the spatial distribution of current reservoirs but also provides a significant basis for the discovery and production of carbonate reservoirs in the Tarim Basin.

Speed-resolved blood perfusion and oxygen saturation in human skin response to thermal stimulation

The functional status of vessels can be determined by assessing blood perfusion.By integrating diffuse reflectance spectroscopy(DRS)and Laser Doppler Flowmetry(LDF),the speed-resolved blood perfusion and blood oxygen saturation can be measured simultaneously by Enhanced Perfusion and Oxygen Saturation(EPOS).The dataset presented in this descriptor contains EPOS data recorded from a forearm point exposed to different levels of thermal stimulation,the classical LDF at control points,the R-R time series and data regarding the subjects’characteristics.All data were recorded from 60 recruited healthy subjects.Half of the subjects received different levels of thermal stimulation,and half of them were blank controls.We believe that this dataset will lead to the development of local blood perfusion methods that can be used to index vessel function assessments.This publicly available dataset will be beneficial to the microcirculation evaluation.

Identification, characterization and evolution of non-local quasi-Lagrangian structures in turbulence

The recent progress on non-local Lagrangian and quasi-Lagrangian structures in turbulence is reviewed.The quasi-Lagrangian structures, e.g., vortex surfaces in viscous flow, gas-liquid interfaces in multi-phase flow, and flame fronts in premixed combustion, can show essential Lagrangian following properties, but they are able to have topological changes in the temporal evolution. In addition,they can represent or influence the turbulent flow field. The challenges for the investigation of the non-local structures include their identification, characterization, and evolution.The improving understanding of the quasi-Lagrangian structures is expected to be helpful to elucidate crucial dynamics and develop structure-based predictive models in turbulence.

Spatio-temporal patterns of temperature extremes and their response to atmospheric circulation factors in China from 1961 to 2020

Changes in surface temperature extremes have become a global concern.Based on the daily lowest temperature(TN)and daily highest temperature(TX)data from 2138weather stations in China from 1961 to 2020,we calculated 14 extreme temperature indices to analyze the characteristics of extreme temperature events.The widespread changes observed in all extreme temperature indices suggest that China experienced significant warming during this period.Specifically,the cold extreme indices,such as cold nights,cold days,frost days,icing days,and the cold spell duration index,decreased significantly by-6.64,-2.67,-2.96,-0.97,and-1.01 days/decade,respectively.In contrast,we observed significant increases in warm extreme indices.The number of warm nights,warm days,summer days,tropical nights,and warm spell duration index increased by 8.44,5.18,2.81,2.50,and 1.66d/decade,respectively.In addition,the lowest TN,highest TN,lowest TX,and highest TX over the entire period rose by 0.47,0.22,0.26,and 0.16℃/decade,respectively.Furthermore,using Pearson's correlation and wavelet coherence analyses,this study identified a strong association between extreme temperature indices and atmospheric circulation factors,with varying correlation strengths and resonance periods across different time-frequency domains.

Understanding Human and Machine Interaction from Decision Perspective: An Empirical Study Based on the Game of Go

The authors aim to interpret human and AI interactions from the decision perspective.The authors decompose the interaction analysis into the following main components in the context of interactions:Individual behavior patterns,interaction relationships,and comprehensive analysis.The authors interpret intertemporal decisions from a physical perspective and employ cross-discipline concepts and methodologies to extract the behavior characteristics of players in the empirical case study.About the individual behavior patterns,the authors find that human players prefer short-term periods to AI in decision-making.The interaction relationship analysis reveals a dynamic relationship between possible short-term co-movement and nearly counter-movement in the long run.The authors apply principal component analysis to descriptive indicators and discover a regular decision hierarchy.The main behavior pattern of players in the game of Go is switching between careful and daring behaviors.The differences in the decision hierarchies imply a discrepancy of patience between humans and AI.