Fast Automatic Registration of UAV Images via Bidirectional Matching.

Image registration plays a vital role in the mosaic process of multiple UAV (Unmanned Aerial Vehicle) images acquired from different spatial positions of the same scene. Aimed at the problem that many fast registration methods cannot provide both high speed and accuracy simultaneously for UAV visible light images, this work proposes a novel registration framework based on a popular baseline registration algorithm, ORB-the Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elemental Features) algorithm. First, the ORB algorithm is utilized to extract image feature points fast. On this basis, two bidirectional matching strategies are presented to match obtained feature points. Then, the PROSRC (Progressive Sample Consensus) algorithm is applied to remove false matches. Finally, the experiments are carried out on UAV image pairs about different scenes including urban, road, building, farmland, and forest. Compared with the original version and other state-of-the-art registration methods, the bi-matching ORB algorithm exhibits higher accuracy and faster speed without any training or prior knowledge. Meanwhile, its complexity is quite low for on-board realization.

Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints.

Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the manipulator and the target when the manipulator grabs the target. In this method, the mathematical model of seven-segment manipulator trajectory planning is constructed first. The mathematical model of synchronous tracking of dynamic targets based on a time-minimum manipulator is constructed by taking the robot's acceleration, speed, and synchronization as constraints. The model transforms the multi-constraint-solving problem into a single-objective-solving problem. Finally, the particle swarm optimization algorithm is used to solve the model. The calculation results are put into the trajectory planning model of the manipulator to obtain the synchronous tracking trajectory of the manipulator. Simulation and experiments show that each joint of the robot's arm can synchronously track dynamic targets within the constraint range. This method can ensure the synchronization of the position, speed, and acceleration of the moving target and the target after tracking. The average position error is 2.1 mm, and the average speed error is 7.4 mm/s. The robot has a high tracking accuracy, which further improves the robot's grasping stability and success rate.

The Impact of Labor Force Participation on Elderly Health in China.

In the context of the deepening of population aging and the trial implementation of a progressive retirement delay policy in China, understanding the relationship between the labor force participation and health status of the elderly will not only enrich relevant research but also help the elderly better achieve their goals of active aging and aging. Using the 2018 China Health and Retirement Longitudinal Study, this paper first established multiple linear regression models to analyze the impact of labor force participation on the health status of elderly people in China and then established simultaneous equation models using households living on minimum living allowances and the community average of labor participation as instrumental variables to deal with the endogeneity caused by two-way causality. The findings confirmed significant positive correlations between labor force participation and physical and mental health, while caring for grandchildren and participating in social activities were found to be negatively moderated the relationship between labor force participation and the physical and mental health of older adults. The impact of labor force participation on the physical health status of older men and the mental health status of older women may be greater. In addition, labor force participation may have a greater impact on the physical health of the rural elderly, and its impact on mental health was not found to be statistically significant between urban and rural areas.

Multi-Arm Global Cooperative Coal Gangue Sorting Method Based on Improved Hungarian Algorithm.

The existing multi-manipulator sorting method for gangue that utilizes a multi-task allocation strategy is not satisfactory. The single manipulator working space is fixed, lowering the cooperation degree between the manipulators and leading to a low sorting rate. Therefore, this paper proposes a multi-manipulator cooperative sorting method that can work globally. First, a benefit function based on the sorting time and quality of the gangue is constructed by combining the gangue flow information and the manipulator state. The time parameter is obtained via the manipulator's dynamic target tracking trajectory planning algorithm based on PID control. Secondly, the benefits matrix is standardized and updated many times to improve the Hungarian algorithm to achieve task allocation, and the initial solution with priority is obtained. Finally, the solutions are analyzed and processed cooperatively in order of priority. The conflicts between multiple robotic arms are eliminated through task cooperation and trajectory cooperation until the sorting task that the robot arm can execute is obtained from the allocation results. Experiments involving different sorting methods were completed on a multi-arm coal and gangue sorting experimental robot platform. The experimental results show that the sorting efficiency of the proposed method is about 10% and 20% higher than that of the fixed space dynamic and designated space fixed points methods, respectively, under different belt speeds. This method can guarantee system benefits, effectively implements cooperative control of multi-manipulator operations in the whole area, and improves the efficiency of coal gangue sorting.

Multidimensional energy poverty and depression among China's older adults.

Older adults often face more pronounced energy inequality in their daily lives, which is one of the reasons for their accumulation of stress or anxiety and may further aggravate their depression. Analyzing the relationship between energy poverty and the depression level of China's older adults will provide policy enlightenment for solving the problems of older adults' relative poverty, energy poverty, and mental poverty and thus promote happy and healthy aging. In this paper, using the data of China Health and Retirement Longitudinal Study in 2018, we used the entropy weighting method to objectively assign weights to 10 indicators reflecting the status of energy poverty and construct a multidimensional energy poverty index for older adults. First, we analyzed the relationship between multidimensional energy poverty and the depression levels of older adults using multiple linear regression model and quantile regression models. Next, we used instrumental variable linear regression model and instrumental variable quantile regression models for endogeneity tests. Then, we performed a robustness check by replacing the core explanatory variable. After that, we conducted heterogeneity analyses by residential area, type of residence, and solitary status. Finally, we analyzed the mediating role of life satisfaction using structural equation modeling. Multidimensional energy poverty has aggravated depression among older adults, and the effect is greater for older adults with higher depression levels. The effect of multidimensional energy poverty on depression is greater for older adults in western China, urban areas, and those who live alone. Multidimensional energy poverty has aggravated depression among older adults by reducing their life satisfaction.

The Impact of Family Socioeconomic Status on Elderly Health in China: Based on the Frailty Index.

China is about to enter a moderate aging society. In the process of social and economic development, the family socioeconomic status and health status of the elderly have also changed significantly. Learning the impact of family socioeconomic status on elderly health can help them improve family socioeconomic status and better achieve healthy and active aging. Using the data of the Chinese Longitudinal Healthy Longevity Survey in 2018, this study firstly analyzed the impact of family socioeconomic status on elderly health using the multivariate linear regression model and quantile regression model, the heterogeneity of different elderly groups using subsample regression, and the mediation effects of three conditions associated with the family socioeconomic status of the elderly. The results show that family socioeconomic status has a negative effect on the frailty index, that is, it has a positive impact on elderly health. Family socioeconomic status has a higher positive impact on the health status of the middle and lower age elderly and rural elderly. Overall living status and leisure and recreation status both have mediation effects, while health-care status has no mediation effect.

MetaMHC: a meta approach to predict peptides binding to MHC molecules.

As antigenic peptides binding to major histocompatibility complex (MHC) molecules is the prerequisite of cellular immune responses, an accurate computational predictor will be of great benefit to biologists and immunologists for understanding the underlying mechanism of immune recognition as well as facilitating the process of epitope mapping and vaccine design. Although various computational approaches have been developed, recent experimental results on benchmark data sets show that the development of improved predictors is needed, especially for MHC Class II peptide binding. To make the most of current methods and achieve a higher predictive performance, we developed a new web server, MetaMHC, to integrate the outputs of leading predictors by several popular ensemble strategies. MetaMHC consists of two components: MetaMHCI and MetaMHCII for MHC Class I peptide and MHC Class II peptide binding predictions, respectively. Experimental results by both cross-validation and using an independent data set show that the ensemble approaches outperform individual predictors, being statistically significant. MetaMHC is freely available at http://www.biokdd.fudan.edu.cn/Service/MetaMHC.html.