Interactive feature space extension for multidimensional data projection

Projecting multi-dimensional data to a lower-dimensional visual display is a commonly used approach for identifying and analyzing patterns in data. Many dimensionality reduction techniques exist for generating visual embeddings, but it is often hard to avoid cluttered projections when the data is large in size and noisy. For many application users who are not machine learning experts, it is difficult to control the process in order to improve the “readability” of the projection and at the same time to understand their quality. In this paper, we propose a simple interactive feature transformation approach that allows the analyst to de-clutter the visualization by gradually transforming the original feature space based on existing class knowledge. By changing a single parameter, the user can easily decide the desired trade-off between structural preservation and the visual quality during the transforming process. The proposed approach integrates semi-interactive feature transformation techniques as well as a variety of quality measures to help analysts generate uncluttered projections and understand their quality

Optimal Breeding Strategy for Livestock with a Dynamic Price

China’s livestock output has been growing, but domestic livestock products such as beef, mutton and pork have been unable to meet domestic consumers’ demands. The imbalance between supply and demand causes unstable livestock prices and affects profits on livestock. Therefore, the purpose of this paper is to provide the optimal breeding strategy for livestock farmers to maximize profits and adjust the balance between supply and demand. Firstly, when the price changes, livestock farmers will respond in two ways: by not adjusting the scale of livestock with the price or adjusting the scale with the price. Therefore, combining the model of price and the behavior of livestock farmers, two livestock breeding models were established. Secondly, we proposed four optimal breeding strategies based on the previously studied models and the main research method is Pontryagin’s Maximum Principle. Optimal breeding strategies are achieved by controlling the growth and output of livestock. Further, their existence was verified. Finally, we simulated two situations and found the most suitable strategy for both situations by comparing profits of four strategies. From that, we obtained several conclusions: The optimal strategy under constant prices is not always reasonable. The effect of price on livestock can promote a faster balance. To get more profits, the livestock farmers should adjust the farm’s productivity reasonably. It is necessary to calculate the optimal strategy results under different behaviors

Circulating Anti-endothelial Cell Antibodies Are Associated with Poor Outcome in Renal Allograft Recipients with Acute Rejection

Background and objectives: Anti-endothelial cell antibody (AECA) can cause hyperacute rejection and immediate graft loss after renal transplantation; however, its prevalence and significance during acute rejection are unknown. Previous studies suggested that AECA may be detected in recipients with acute vascular rejection (AVR)

Evaluation of Fengyun-4A Detection Accuracy: A Case Study of the Land Surface Temperature Product for Hunan Province, Central China

Land surface temperature (LST) is an important parameter in determining surface energy balance and a fundamental variable detected by the advanced geostationary radiation imager (AGRI), the main payload of FY-4A. FY-4A is the first of a new generation of Chinese geostationary satellites, and the detection product of the satellite has not been extensively validated. Therefore, it is important to conduct a comprehensive assessment of this product. In this study, the performance of the FY-4A LST product in the Hunan Province was authenticity tested with in situ measurements, triple collocation analyzed with reanalysis products, and impact analyzed with environmental factors. The results confirm that FY-4A captures LST well (R = 0.893, Rho = 0.915), but there is a general underestimation (Bias = −0.6295 °C) and relatively high random error (RMSE = 8.588 °C, ubRMSE = 5.842 °C). In terms of accuracy, FY-4A LST is more accurate for central-eastern, northern, and south-central Hunan Province and less accurate for western and southern mountainous areas and Dongting Lake. FY-4A LST is not as accurate as Himawari-8 LST; its accuracy also varies seasonally and between day and night. The accuracy of FY-4A LST decreases as elevation, in situ measured LST, surface heterogeneity, topographic relief, slope, or NDVI increase and as soil moisture decreases. FY-4A LST is also more accurate when the land cover is cultivated land or artificial surfaces or when the landform is a platform for other land covers and landforms. The conclusions drawn from the comprehensive analysis of the large quantity of data are generalizable and provide a quantitative baseline for assessing the detection capability of the FY-4A satellite, a reference for determining improvement in the retrieval algorithm, and a foundation for the development and application of future domestic satellite products