A Literature Review on China's Population Aging, Human Capital and R&D Capital Stock

This paper mainly studies the impact of population aging on human capital, and combs the relevant literature. This paper compares the different status quo of population aging in China and abroad, and the different effects of population aging in different countries. We also want to know whether the aging of population affects the stock of R&D capital and whether this impact is brought about by the change of human capital. Through the existing literature, we find that population aging will directly lead to the reduction of R&D human capital stock, which is generally accepted by all countries. At the same time, the change of human capital brought by population aging brings about the change of education capital and health capital. But scholars have not yet reached a clear conclusion. Through the study of this conduction effect, we can further explore the mechanism of population aging

X-ray Astronomical Point Sources Recognition Using Granular Binary-tree SVM

The study on point sources in astronomical images is of special importance, since most energetic celestial objects in the Universe exhibit a point-like appearance. An approach to recognize the point sources (PS) in the X-ray astronomical images using our newly designed granular binary-tree support vector machine (GBT-SVM) classifier is proposed. First, all potential point sources are located by peak detection on the image. The image and spectral features of these potential point sources are then extracted. Finally, a classifier to recognize the true point sources is build through the extracted features. Experiments and applications of our approach on real X-ray astronomical images are demonstrated. comparisons between our approach and other SVM-based classifiers are also carried out by evaluating the precision and recall rates, which prove that our approach is better and achieves a higher accuracy of around 89%.Comment: Accepted by ICSP201

FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning

Federated learning (FL), a popular decentralized and privacy-preserving machine learning (FL) framework, has received extensive research attention in recent years. The majority of existing works focus on supervised learning (SL) problems where it is assumed that clients carry labeled datasets while the server has no data. However, in realistic scenarios, clients are often unable to label their data due to the lack of expertise and motivation while the server may host a small amount of labeled data. How to reasonably utilize the server labeled data and the clients' unlabeled data is thus of paramount practical importance. In this paper, we propose a new FL algorithm, called FedSEAL, to solve this Semi-Supervised Federated Learning (SSFL) problem. Our algorithm utilizes self-ensemble learning and complementary negative learning to enhance both the accuracy and the efficiency of clients' unsupervised learning on unlabeled data, and orchestrates the model training on both the server side and the clients' side. Our experimental results on Fashion-MNIST and CIFAR10 datasets in the SSFL setting validate the effectiveness of our method, which outperforms the state-of-the-art SSFL methods by a large margin.Comment: 15 pages, 7 figure

On Two problems of defective choosability

Given positive integers $p \ge k$, and a non-negative integer $d$, we say a graph $G$ is $(k,d,p)$-choosable if for every list assignment $L$ with $|L(v)|\geq k$ for each $v \in V(G)$ and $|\bigcup_{v\in V(G)}L(v)| \leq p$, there exists an $L$-coloring of $G$ such that each monochromatic subgraph has maximum degree at most $d$. In particular, $(k,0,k)$-choosable means $k$-colorable, $(k,0,+\infty)$-choosable means $k$-choosable and $(k,d,+\infty)$-choosable means $d$-defective $k$-choosable. This paper proves that there are 1-defective 3-choosable graphs that are not 4-choosable, and for any positive integers $\ell \geq k \geq 3$, and non-negative integer $d$, there are $(k,d, \ell)$-choosable graphs that are not $(k,d , \ell+1)$-choosable. These results answer questions asked by Wang and Xu [SIAM J. Discrete Math. 27, 4(2013), 2020-2037], and Kang [J. Graph Theory 73, 3(2013), 342-353], respectively. Our construction of $(k,d, \ell)$-choosable but not $(k,d , \ell+1)$-choosable graphs generalizes the construction of Kr\'{a}l' and Sgall in [J. Graph Theory 49, 3(2005), 177-186] for the case $d=0$.Comment: 12 pages, 4 figure

The νR\nu_{R}-philic scalar dark matter

Right-handed neutrinos ($\nu_{R}$) offer an intriguing portal to new physics in hidden sectors where dark matter (DM) may reside. In this work, we delve into the simplest hidden sector involving only a real scalar exclusively coupled to $\nu_{R}$, referred to as the $\nu_{R}$-philic scalar. We investigate the viability of the $\nu_{R}$-philic scalar to serve as a DM candidate, under the constraint that the coupling of $\nu_{R}$ to the standard model is determined by the seesaw relation and is responsible for the observed DM abundance. By analyzing the DM decay channels and solving Boltzmann equations, we identify the viable parameter space. In particular, our study reveals a lower bound ($\sim10^{4}$ GeV) on the mass of $\nu_{R}$ for the $\nu_{R}$-philic scalar to be DM. The DM mass may vary from sub-keV to sub-GeV. Within the viable parameter space, monochromatic neutrino lines from DM decay can be an important signal for DM indirect detection.Comment: 21 pages, 5 figure

Theoretical analysis of a membrane-based cross-flow liquid desiccant system

Liquid desiccant air dehumidification has become one of the most widely used dehumidification technologies with advantages of high efficiency, no liquid condensate droplets and capability of energy storage. In this paper a cross-flow mathematical model is developed for a single layer membrane unit. The governing equations are solved iteratively by finite difference method. The performance analysis is carried out for a small-scale membrane-based dehumidification module consisting of 8 air channels and 8 solution channels. The influences of main design parameters on system effectiveness are evaluated. These include air flow rate (NTU), solution to air mass flow rate ration (m*) and solution inlet temperature and concentration. It is revealed that higher sensible and latent effectiveness can be achieved with larger NTU and m*. Increasing solution concentration can also improve the dehumidification effect

Theoretical analysis of a membrane-based cross-flow liquid desiccant system

Liquid desiccant air dehumidification has become one of the most widely used dehumidification technologies with advantages of high efficiency, no liquid condensate droplets and capability of energy storage. In this paper a cross-flow mathematical model is developed for a single layer membrane unit. The governing equations are solved iteratively by finite difference method. The performance analysis is carried out for a small-scale membrane-based dehumidification module consisting of 8 air channels and 8 solution channels. The influences of main design parameters on system effectiveness are evaluated. These include air flow rate (NTU), solution to air mass flow rate ration (m*) and solution inlet temperature and concentration. It is revealed that higher sensible and latent effectiveness can be achieved with larger NTU and m*. Increasing solution concentration can also improve the dehumidification effect