Standard Model With Higgs As Gauge Field On Fourth Homotopy Group

Based upon a first principle, the generalized gauge principle, we construct a general model with $G_L\times G'_R \times Z_2$ gauge symmetry, where $Z_2=\pi_4(G_L)$ is the fourth homotopy group of the gauge group $G_L$, by means of the non-commutative differential geometry and reformulate the Weinberg-Salam model and the standard model with the Higgs field being a gauge field on the fourth homotopy group of their gauge groups. We show that in this approach not only the Higgs field is automatically introduced on the equal footing with ordinary Yang-Mills gauge potentials and there are no extra constraints among the parameters at the tree level but also it most importantly is stable against quantum correlation.Comment: 19 pages, Latex, ASITP-94-2

Interaction between Nobiliside-a and lipid bilayers

Nobiliside A (Nob) is a new triterpenoid saponin first discovered and isolated from the Holothuria nobilis with chemical molecular structure of C54H87O26 SNa. Extracorporeal antitumor test showed that Nob may be a new category of effective anticancer medicine which had excellent cytotoxicity as well as inhibited vascular endothelial cell (VEC) proliferation and migration in vitro and chicken chorioallantoic membrane (CAM) angiogenesis in vivo at a lower dose. Unfortunately, the clinical application of Nob was severely limited by the low bioavailability of Nob after oral administration, and highly toxic especially heart toxicity and the ability causing hemolysis of blood cells after intravenous injection. To reduce the hemolysis and toxicity of Nob after intravenous injection, liposomes were used as its carriers and good effect was acquired in our previous study. During the preparation and study of Nob liposomes, we found that Nob liposomes had high encapsulation efficiency (EE), which nearly 100 % and good stability. It was proposed that there would be strong interaction between Nob and lipid bilayers, which would affect the EE, the stability, pharmacokinetics, pharmacodynamics and even the toxicity of the drug. Thus, fourier transformer infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), fluoroscense spectroscopy were used to study the interaction between Nob and lipid bilayers. The results showed that there was a strong interaction between Nob and both phospholipids (PL) and cholesterol (CH) in lipid bilayers, and the interaction between Nob and CH was stronger than that between Nob and PL. There was also interaction between PL and CH, which would be decreased when Nob existed. Thus, the reason of Nob liposomes having high EE and good stability could be infered from the study. In fluoroscense spectroscopy study it was found that Nob could destroy calcein liposomes and lead release of the content, while Nob encapsuled in liposomes could not cause the destruction of calcein liposomes. These phenomena were different with Nob liposomes leading to the content release from red blood cells, so the mechanism of Nob liposomes decreasing the toxicity to mice and hemolysis in vitro should be further studied.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Interaction between Nobiliside-a and lipid bilayers

Nobiliside A (Nob) is a new triterpenoid saponin first discovered and isolated from the Holothuria nobilis with chemical molecular structure of C54H87O26 SNa. Extracorporeal antitumor test showed that Nob may be a new category of effective anticancer medicine which had excellent cytotoxicity as well as inhibited vascular endothelial cell (VEC) proliferation and migration in vitro and chicken chorioallantoic membrane (CAM) angiogenesis in vivo at a lower dose. Unfortunately, the clinical application of Nob was severely limited by the low bioavailability of Nob after oral administration, and highly toxic especially heart toxicity and the ability causing hemolysis of blood cells after intravenous injection. To reduce the hemolysis and toxicity of Nob after intravenous injection, liposomes were used as its carriers and good effect was acquired in our previous study. During the preparation and study of Nob liposomes, we found that Nob liposomes had high encapsulation efficiency (EE), which nearly 100 % and good stability. It was proposed that there would be strong interaction between Nob and lipid bilayers, which would affect the EE, the stability, pharmacokinetics, pharmacodynamics and even the toxicity of the drug. Thus, fourier transformer infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), fluoroscense spectroscopy were used to study the interaction between Nob and lipid bilayers. The results showed that there was a strong interaction between Nob and both phospholipids (PL) and cholesterol (CH) in lipid bilayers, and the interaction between Nob and CH was stronger than that between Nob and PL. There was also interaction between PL and CH, which would be decreased when Nob existed. Thus, the reason of Nob liposomes having high EE and good stability could be infered from the study. In fluoroscense spectroscopy study it was found that Nob could destroy calcein liposomes and lead release of the content, while Nob encapsuled in liposomes could not cause the destruction of calcein liposomes. These phenomena were different with Nob liposomes leading to the content release from red blood cells, so the mechanism of Nob liposomes decreasing the toxicity to mice and hemolysis in vitro should be further studied.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Three Dimensional (3D) Reconstruction of Subterranean Clover

Three dimensional (3D) plant reconstructions, extended to four dimensions with the use of time series and accompanied by visual modelling, is being used for a number of purposes including the estimation of biovolume and as the basis for functional structural plant modelling (FSPM). This has been successfully applied to crop species such as cotton (Paproki et al. 2012). Measuring the growth pattern and arrangement of a pasture sward is a difficult task but can be used as an indirect measure of other variables of interest, such as growth rate, light interception, nutritional quality, herbivore intake, etc. (Laca and Lemaire 2000). Digital representation of individual plants in three dimensions is one way to determine sward structure. The High Resolution Plant Phenomics Centre (HRPPC) has developed PlantScan™ which combines robotics, image analysis and computing advances, to accelerate and automate the measurement of plant growth characteristics and allow discrimination of differences between individual plants within species. Image silhouettes and LiDAR (Light Detection And Ranging) are used and combined to digitise plant architecture in three dimensions with a high level of detail. Colour information, extracted from multispectral sensors, and thermal imaging from infra-red (IR) cameras are then overlaid on these 3D plant representations, thus providing a tool to link plant structure to plant function. Successful reconstructions using data collected by PlantScan™ in controlled conditions, have been conducted for a range of grasses such as wheat (Triticum aestivum), rice (Oryza sativa), corn (Zea mays) and broadleaf species such as canola (Brassica napus), cotton (Gossypium hirsutum) and tobacco (Nicotiana tabacum). This suggests that modelling the sward structure of grass and legume pasture species should be equally achievable. This study explores the use of PlantScanTM to reconstruct 3D images of the important and common pasture legume, subterranean clover (Trifolium subterraneum) with a view to analysing their 3D structure in-silico

Disentangled Variational Auto-encoder Enhanced by Counterfactual Data for Debiasing Recommendation

Recommender system always suffers from various recommendation biases, seriously hindering its development. In this light, a series of debias methods have been proposed in the recommender system, especially for two most common biases, i.e., popularity bias and amplified subjective bias. However, exsisting debias methods usually concentrate on correcting a single bias. Such single-functionality debiases neglect the bias-coupling issue in which the recommended items are collectively attributed to multiple biases. Besides, previous work cannot tackle the lacking supervised signals brought by sparse data, yet which has become a commonplace in the recommender system. In this work, we introduce a disentangled debias variational auto-encoder framework(DB-VAE) to address the single-functionality issue as well as a counterfactual data enhancement method to mitigate the adverse effect due to the data sparsity. In specific, DB-VAE first extracts two types of extreme items only affected by a single bias based on the collier theory, which are respectively employed to learn the latent representation of corresponding biases, thereby realizing the bias decoupling. In this way, the exact unbiased user representation can be learned by these decoupled bias representations. Furthermore, the data generation module employs Pearl's framework to produce massive counterfactual data, making up the lacking supervised signals due to the sparse data. Extensive experiments on three real-world datasets demonstrate the effectiveness of our proposed model. Besides, the counterfactual data can further improve DB-VAE, especially on the dataset with low sparsity