Understanding, Interpreting and Answering the Question of What Is Being Properly

We have to master six propositions and judges, which are connected each other tightly, in the process of understanding, interpreting and answering the question of what is being properly. They are :1) Being is the representative of all converted forms of the verb of be, and further the representative of all English words; 2) words are the representative of languages; 3) languages are one of the main ways in materializing the human thinking and its results, that is, languages are one of the main ways of expressing the processes of human thinking and its results; 4) the processes of human thinking is the process of subjective disposition on objects, the results of human thinking are the results of human subjective dispositions on objects; 5) subjective dispositions are the processes of humans dispositions on objects，which include the results of human subjective dispositions previously, from multi-aspects, multi-strata, multi-disciplines, in human minds, and the subjective dispositions are the contents of the activities of human minds; 6) the true function and aim of raising the question of what is being continually from ancient Greece to now by Occidental scholars is that they want to know what is subjective dispositions and the relationship between subjective dispositions and their linguistic expressions

Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-like Penalty

With the rapid development of modern technology, massive amounts of data with complex pattern are generated. Gaussian process models that can easily fit the non-linearity in data become more and more popular nowadays. It is often the case that in some data only a few features are important or active. However, unlike classical linear models, it is challenging to identify active variables in Gaussian process models. One of the most commonly used methods for variable selection in Gaussian process models is automatic relevance determination, which is known to be open-ended. There is no rule of thumb to determine the threshold for dropping features, which makes the variable selection in Gaussian process models ambiguous. In this work, we propose two variable selection algorithms for Gaussian process models, which use the artificial nuisance columns as baseline for identifying the active features. Moreover, the proposed methods work for both regression and classification problems. The algorithms are demonstrated using comprehensive simulation experiments and an application to multi-subject electroencephalography data that studies alcoholic levels of experimental subjects

Innovations in Cadres Selection and Promotion in China: the Case of Mudanjiang City

China’s new cadre selection and promotion system has been arguably considered as China’s most significant move in securing its implementation of reform strategies. Almost at the same time when he was advocating for China’s economic reform in 1978, the late Deng Xiaoping, China’s reform champion also issued a set of important speeches on reforming China’s cadre selection and promotion protocols in order that there would be enough leadership to help meeting the challenges of the reform needs. His view on what talents are is a de facto mandate leading the way for China’s cadre selection and promotion reform. This paper uses the case of Mudanjiang, a well-known city in China’s northeast, to illustrate how Deng’s Xiaoping’s cadre selection and promotion ideas are implemented. Through literature and documents review, onside observation, person to person interviews, and surveys, the authors examined how cadres are publicly nominated, competitively elected, and scientifically selected in Mudanjian city. They study shows, the cadre open selection mechanisms have worked well, it has opened the door for many talented people who otherwise would not have had the chance to be even noticed by the upper management. The study also reveals some existing problems in the current system and made suggestions for further reform

Linking stroke mortality with air pollution, income, and greenness in northwest Florida: an ecological geographical study

<p>Abstract</p> <p>Background</p> <p>Relatively few studies have examined the association between air pollution and stroke mortality. Inconsistent and inclusive results from existing studies on air pollution and stroke justify the need to continue to investigate the linkage between stroke and air pollution. No studies have been done to investigate the association between stroke and greenness. The objective of this study was to examine if there is association of stroke with air pollution, income and greenness in northwest Florida.</p> <p>Results</p> <p>Our study used an ecological geographical approach and dasymetric mapping technique. We adopted a Bayesian hierarchical model with a convolution prior considering five census tract specific covariates. A 95% credible set which defines an interval having a 0.95 posterior probability of containing the parameter for each covariate was calculated from Markov Chain Monte Carlo simulations. The 95% credible sets are (-0.286, -0.097) for household income, (0.034, 0.144) for traffic air pollution effect, (0.419, 1.495) for emission density of monitored point source polluters, (0.413, 1.522) for simple point density of point source polluters without emission data, and (-0.289,-0.031) for greenness. Household income and greenness show negative effects (the posterior densities primarily cover negative values). Air pollution covariates have positive effects (the 95% credible sets cover positive values).</p> <p>Conclusion</p> <p>High risk of stroke mortality was found in areas with low income level, high air pollution level, and low level of exposure to green space.</p

Exploring the seasonal relationship between spatial and temporal features of land surface temperature and its potential drivers: the case of Chengdu metropolitan area, China

Global climate change and the process of urbanization have had a significant impact on land surface temperature (LST). This study selects the Chengdu metropolitan area in China as a typical research subject. Based on the seasonal heterogeneity and spatial distribution characteristics of LST, different types of potential influencing factors are selected for Principal Component Analysis (PCA) to determine the categories of these factors. Subsequently, a multiple linear regression analysis is conducted to explore the relationship between LST and the identified potential influencing factors during different seasons. The findings of this study suggest that the regions with high temperatures and secondary high temperatures in the Chengdu metropolitan area are primarily concentrated in Chengdu and its adjacent localities, exhibiting noticeable seasonal variations. In the summer, high-temperature zone and second high-temperature zone of the LST show a central aggregation pattern. In the transition season, the high-temperature zone of the LST presents a “large dispersion, small aggregation” pattern. In the winter, it presents a dispersed pattern. In terms of influencing factors, elevation, slope, wind speed, humidity, and surface vegetation cover related to natural geographical conditions have a significant impact on LST, reaching a peak during the transition season. Factors associated with social and economic conditions, such as population size, nighttime light index, and road density, have a pronounced effect on LST during the summer season. During winter, LST is mainly influenced by landscape pattern-related factors such as Shannon Diversity Index, Edge Density, Largest Patch Index, and Patch Density. This study not only assesses the seasonal and spatial characteristics of LST in the Chengdu metropolitan area but also provides valuable insights for formulating phased measures to mitigate the Urban Heat Island (UHI) in other regions

Continuous Intermediate Token Learning with Implicit Motion Manifold for Keyframe Based Motion Interpolation

Deriving sophisticated 3D motions from sparse keyframes is a particularly challenging problem, due to continuity and exceptionally skeletal precision. The action features are often derivable accurately from the full series of keyframes, and thus, leveraging the global context with transformers has been a promising data-driven embedding approach. However, existing methods are often with inputs of interpolated intermediate frame for continuity using basic interpolation methods with keyframes, which result in a trivial local minimum during training. In this paper, we propose a novel framework to formulate latent motion manifolds with keyframe-based constraints, from which the continuous nature of intermediate token representations is considered. Particularly, our proposed framework consists of two stages for identifying a latent motion subspace, i.e., a keyframe encoding stage and an intermediate token generation stage, and a subsequent motion synthesis stage to extrapolate and compose motion data from manifolds. Through our extensive experiments conducted on both the LaFAN1 and CMU Mocap datasets, our proposed method demonstrates both superior interpolation accuracy and high visual similarity to ground truth motions.Comment: Accepted by CVPR 202

Biochemical and Ultrastructural Changes in the Hepatopancreas of Bellamya aeruginosa (Gastropoda) Fed with Toxic Cyanobacteria

This study was conducted to investigate ultrastructural alterations and biochemical responses in the hepatopancreas of the freshwater snail Bellamya aeruginosa after exposure to two treatments: toxic cyanobacterium (Microcystis aeruginosa) and toxic cyanobacterial cells mixed with a non-toxic green alga (Scendesmus quadricauda) for a period of 15 days of intoxication, followed by a 15-day detoxification period. The toxic algal suspension induced a very pronounced increase of the activities of acid phosphatases, alkaline phosphatases and glutathione S-transferases (ACP, ALP and GST) in the liver at the later stage of intoxication. During the depuration, enzymatic activity tended to return to the levels close to those in the control. The activity of GST displayed the most pronounced response among different algal suspensions. Severe cytoplasmic vacuolization, condensation and deformation of nucleus, dilation and myeloid-like in mitochondria, disruption of rough endoplasmic reticulum, proliferation of lysosome, telolysosomes and apoptotic body were observed in the tissues. All cellular organelles began recovery after the snails were transferred to the S. quadricauda. The occurrence of a large amount of activated lysosomes and heterolysosomes and augment in activity of detoxification enzyme GST might be an adaptive mechanism to eliminate or lessen cell damage caused by hepatotoxicity to B. aeruginosa