Search

Relevance. In order to alleviate the problems of labour reduction and heavy financial burden caused by population aging, some developed countries have implemented policy reforms to develop the resources of the elderly, and provided educational measures to improve digital literacy for the elderly in combination with the fact of digital transformation. These positive measures have not only achieved certain results, but also provided a reference for China to deal with aging. Aim. To summarise the measures and experiences in developing geriatric resources in typical developed countries, and to gain insights from them, and then to make suggestions for China’s response to population ageing. Methods. Based on the collection and collation of objective facts and statistical data, this paper summarises the current situation of aging in Japan, Germany and Singapore and the reform measures for the development of human resources for the elderly, and uses induction to analyse the internal logic of the successful experience of these countries in developing human resources for the elderly. Results. The author has summarized and analyzed the measures and experience of Japan, Germany and Singapore in developing geriatric resources in the dual context of ageing and digitalisation as well as logic of the positive results of developing geriatric resources. Combined with the current situation of the development of human resources for the elderly in China, some suggestions are put forward for the development of human resources for the elderly in China. Conclusions. The establishment of a sustainable pension system, the formulation of policies to promote the employment of the elderly, and the provision of a service system for the elderly, such as old-age security, education and training, are the necessary prerequisites for the development of the elderly's human resources. The construction of a digitally inclusive social environment of positive aging, and the enhancement of the elderly's digital literacy through a variety of ways have better benefits for the elderly's confidence in the labour supply and the increase in the rate of labour force participation. Constructing a synergistic mechanism based on stakeholders such as the government, enterprises, families as well as the elderly stimulates the elderly labour supply and other social activities.

In current coal mine data acquisition, fusion, and sharing, there are problems of lack of standardization and semantic inconsistency in device attributes, inability to cross operating systems in data acquisition protocols, poor real-time data access, and low data sharing efficiency. In order to solve the above problems, a coal mine data acquisition, fusion, and sharing system based on object model is designed. On the basis of the coding standard for coal mine data based on tag numbers, a device object model is designed to overcome the problems of lack of standardization of device attributes and semantic inconsistency in device attributes. By using industrial protocol acquisition, Restful API Q&A acquisition, and file data acquisition methods for data access, it can support domestic operating systems and provide convenient message monitoring tools to accurately determine the cause of communication abnormalities. The model implements data fusion through device object model mapping, introduces data governance mechanisms to ensure data accuracy and consistency, and stores data in the form of object models to save storage space and improve storage efficiency. The model stores all device object data in one table. The object-oriented data sharing interface can be simplified into real-time data sharing interface and historical data sharing interface, reducing redundant interfaces and thus reducing data access times. The application results show that the system reduces the difficulty of semantic parsing during data usage after standardizing device data. The system improves the performance of data computation, storage, and access, providing guarantees for big data analysis.

With the gradual improvement of people’s living standards, the requirements for a living environment are getting higher and higher. A good landscape space can facilitate people’s life, promote people’s interaction, provide places for leisure and entertainment, etc. Therefore, it is important to study the landscape space of residential communities. In this paper, we use Cite space software to analyze the research on landscape space literature in recent years, use keyword search to analyze people’s preference and demand for landscape space in the community, and use the data mining technology of plain Bayesian model to analyze the existing facilities and functions of the old residential community, to explore people’s preference, demand for landscape space, people’s activities in landscape space and The design strategies for the renewal of landscape spaces in old neighborhoods are proposed. For different types of landscape spaces, walking activity is one of the main activities, and environmental facilities are the main influencing factor to determine the type of activity. The highest proportion of sitting facilities is 24.6%, showing that people need them first to stay in the space. The proportion of green facilities is 19.8%, indicating that a good green environment is also an important factor that people are willing to stay. The proportion of landscape and green facilities is close to each other, and the attractiveness to people is similar. Waterscape is also the form of landscape that people love. Therefore, green landscape is an important factor to be considered in the design of landscape space, followed by rest facilities. Comfortable and pleasant community landscape design can enhance the happiness of people’s lives, and the contents discussed in this paper are of great significance to the design of landscape space.

Biological control of Verticillium wilt caused by Verticillium dahliae is a green and sustainable strategy. However, the antifungal activities of different amounts of biocontrol bacterial are still not understand. This study investigates the antifungal activity of different amount of Bacillus amyloliquefaciens FH1-RS1 and Bacillus cereus R19 against Verticillium dahliae V991 by dual culture plate. The results showed that both the fungal inhibition rate (FIR) and far fungal inhibition rate (FFIR) of B. amyloliquefaciens FH1-RS1 elevated with the increasing volume. The highest FIR (77.78%) and FFIR (58.33%) of B. amyloliquefaciens FH1-RS1 were both in 22 μL volume (7.2 × 108 CFU/mL). The highest FIR of B. cereus R19 was 48.15% in 12, 18 and 20 μL volume (1.2 × 108 CFU/mL). The highest FFIR of B. cereus R19 was 38.89% in 6 μL volume. This suggests that not all biocontrol bacteria have higher antifungal activity in higher amounts.

In this study, we prepared Mg-9Gd-2Nd-0.5Zr, referred to as alloy I, and Mg-9Gd-2Nd-1.5Zn-0.5Zr, referred to as alloy II. The effects of a long-period stacking ordered (LPSO) phase induced by Zn addition on the high-temperature mechanical properties and fracture morphology of alloy I and alloy II at different temperatures (25 °C, 200 °C, 225 °C, and 250 °C) were studied using optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). The results indicate that Mg5RE at the crystal boundary of the as-cast alloy I transformed into (MgZn)3RE (as-cast alloy II) by the addition of Zn. After solid solution treatment, the secondary phase in alloy I completely disappeared, and there were still residual secondary phases in block-like and needle-like structures in alloy II, while layered LPSO phases precipitated in the matrix. During the high-temperature tensile test, the yield and tensile strength of alloy I decreased significantly with the increase in temperature, while the elongation increased. Compared to alloy I, the yield strength of alloy II with an LPSO phase showed an increasing trend at 25 °C~200 °C and then decreased when the temperature reached around 250 °C. The thermal stability was significantly enhanced, and the elongation was also higher than that of alloy I. As the temperature increased, the fracture surface of alloy I showed increased folding, bending of scratches, and crack enlargement. However, the fracture surface of alloy II remained largely unchanged, with only minor wrinkles and cracks appearing at temperatures reaching 250 °C. [ABSTRACT FROM AUTHOR]

Background: The widespread application and iterative updating of computers and Internet communication technologies have not only increased productivity and enhanced intra- and inter-enterprise collaboration, but have also led to significant changes in the labor market and residents' labor income. In the digital era, accepting digital technology and possessing a certain degree of digital literacy have become the necessary abilities for people to survive and develop. However, the differences in digital literacy caused by individual differences will inevitably bring about a series of chain reactions. Therefore, it is necessary to study the subtle impact of Internet usage preference on residents' labor income in the context of digital transformation to promote digital equity. Objective: This study aims to empirically analyze micro-level survey data to reveal the impact of individual differences in internet usage preferences on their labor income. The findings provide theoretical references for government policy formulation and individual development. Methods: A function model was established to analyze the impact of individual internet usage preferences on labor income. Relevant data from the authoritative Chinese General Social Survey (CGSS2017) were selected, and empirical analyses for significance, heterogeneity, and robustness were conducted using the ZINB and CMP models in the Stata statistical software. Conclusion: (1) Higher Internet Usage Frequency (IUF) increases the likelihood of higher income. (2) Engaging in Online Social Networking (OSN) helps in accumulating social capital, leading to higher labor income. Meanwhile, participating in Online Entertainment (OE) relieves work and life stresses, thereby increasing labor income. Proficiency in Accessing Online Information (AOI) is associated with higher labor income, while frequent involvement in Online Business (OB) is correlated with higher personal income. Additionally, the Marginal utility of these internet usage preferences indicate that OB > AOI > OSN > OE. (3) Individual variations in physical, psychological, and social characteristics significantly influence the labor income effects of internet usage preferences. (4) There are substantial differences in the labor income effects of internet usage preferences between urban and rural areas and across different regions. (5) Education attainment has a positive mediating effect on the labour income effect of individual Internet use preferences, and enhancing residents' digital literacy has a positive effect on increasing their labour income and alleviating inequality in digital gains. (6) The popularity of Internet technology is the background that triggers an individual's Internet use, and the acceptance of a particular Internet technology is catalyzed by an individual's perception of the value and difficulty of mastering that technology; an individual's biased learning or proficiency in a particular Internet technology in order to gain higher competitiveness and value in the labour market is an important internal driving force. [ABSTRACT FROM AUTHOR]

Rational design and fabrication of efficient catalysts for overall water splitting in an integrated electrolyzer are essential for energy storage and conversion. Herein, an ultra‐small substitutional Zn‐doped Ru/RuO2 heterostructure (5.6 nm) is synthesized through a facile pyrolyzing strategy as an efficient bi‐functional electrocatalyst for water splitting in both acidic and alkaline media. Experiments demonstrate that introducing appropriate alien atoms into RuO2 with an amorphous state can effectively optimize the electron structure and expose abundant defects, and thus increasing the number of active sites and improving the intrinsic activity of RuO2 for the oxygen evolution reaction (OER). In addition, the high hydrogen adsorption capability of metallic Ru makes Ru‐RuO2 heterointerface suitable for water splitting. Notably, the Ru/ZnRuO2 displays low overpotentials at 10 mA cm−2 with only 184 mV for OER in 0.5 m H2SO4 and 35 mV for HER in 1.0 m KOH. Besides, the as‐synthesized Ru/ZnRuO2 displays cell voltages of 1.540 and 1.567 V (at 10 mA cm−2) for water splitting with remarkable durability for more than 220 and 100 h, respectively, in acidic and alkaline media. This work provides a facile strategy for designing pH‐universal electrocatalysts toward overall water splitting. [ABSTRACT FROM AUTHOR]

Background: There is limited understanding of differences in the composition and structure of ligaments between healthy males and females, and individuals of different ages. Females present higher risk for ligament injuries than males and there are conflicting reports on its cause. This study looks into T1ρ parameters for an explanation as it relates to proteoglycan, collagen, and water content in these tissues. Purpose: To investigate gender‐related and age‐related differences in T1ρ parameters in knee joint ligaments in healthy volunteers using a T1ρ‐prepared zero echo‐time (ZTE)‐based pointwise‐encoding time‐reduction with radial acquisition (T1ρ‐PETRA) sequence. Study Type: Prospective. Population: The study group consisted of 22 healthy subjects (11 females, ages: 41 ± 18 years, and 11 males, ages: 41 ± 14 years) with no known inflammation, trauma, or pain in the knee joint. Field Strength/Sequence: A T1ρ‐prepared 3D‐PETRA sequence was used to acquire fat‐suppressed images with varying spin‐lock lengths (TSLs) of the knee joint at 3T. Assessment: Monoexponential, biexponential, and stretched‐exponential 3D‐PETRA‐T1ρ parameters were measured in the anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), and patellar tendon (PT) by manually drawing ROIs over the entirety of the tissues. Statistical Tests: Mann–Whitney U‐tests were used to compare 3D‐PETRA‐T1ρ parameters in the ACL, PCL, and PT between males and females. Spearman correlation coefficients were used to determine the association between age and T1ρ parameters. Statistical significance was defined as P < 0.05. Results: Significant correlations with age were found the three ligaments with most of the measured T1ρ parameters (rs = 0.28–0.74) with the exception of the short fraction in the PCL (P = 0.18), and the short relaxation time in the ACL (P = 0.58) and in the PCL (P = 0.14). Data Conclusion: 3D‐PETRA‐T1ρ can detect age‐related differences in monoexponential, biexponential, and stretched‐exponential T1ρ parameters in three ligaments of healthy volunteers, which are thought to be related to changes in tissue composition and structure during the aging process. Level of Evidence: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Background: Three‐dimensional MR fingerprinting (3D‐MRF) techniques have been recently described for simultaneous multiparametric mapping of knee cartilage. However, investigation of repeatability remains limited. Purpose: To assess the intra‐day and inter‐day repeatabilities of knee cartilage T1, T2, and T1ρ maps using a 3D‐MRF sequence for simultaneous measurement. Study Type: Prospective. Subjects: Fourteen healthy subjects (35.4 ± 9.3 years, eight males), scanned on Day 1 and Day 7. Field Strength/Sequence: 3 T/3D‐MRF, T1, T2, and T1ρ maps. Assessment: The acquisition of 3D‐MRF cartilage (simultaneous acquisition of T1, T2, and T1ρ maps) were acquired using a dictionary pattern‐matching approach. Conventional cartilage T1, T2, and T1ρ maps were acquired using variable flip angles and a modified 3D‐Turbo‐Flash sequence with different echo and spin‐lock times, respectively, and were fitted using mono‐exponential models. Each sequence was acquired on Day 1 and Day 7 with two scans on each day. Statistical Tests: The mean and SD for cartilage T1, T2, and T1ρ were calculated in five manually segmented regions of interest (ROIs), including lateral femur, lateral tibia, medial femur, medial tibia, and patella cartilages. Intra‐subject and inter‐subject repeatabilities were assessed using coefficient of variation (CV) and intra‐class correlation coefficient (ICC), respectively, on the same day and among different days. Regression and Bland–Altman analysis were performed to compare maps between the conventional and 3D‐MRF sequences. Results: The CV in all ROIs was lower than 7.4%, 8.4%, and 7.5% and the ICC was higher than 0.56, 0.51, and 0.52 for cartilage T1, T2, and T1ρ, respectively. The MRF results had a good agreement with the conventional methods with a linear regression slope >0.61 and R2 > 0.59. Conclusion: The 3D‐MRF sequence had high intra‐subject and inter‐subject repeatabilities for simultaneously measuring knee cartilage T1, T2, and T1ρ with good agreement with conventional sequences. Evidence Level: 1 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

At present, many diseases are diagnosed by computer tomography (CT) image technology, which affects the health of the lives of millions of people. In the process of disease confrontation, it is very important for patients to detect diseases in the early stage by deep learning of 3D CT images. The paper offers a hybrid multi-instance learning model (HLFSRNN-MIL), which hybridizes high-low frequency feature fusion (HLFFF) with sequential recurrent neural network (SRNN) for CT image classification tasks. Firstly, the hybrid model uses Resnet-50 as the deep feature. The main feature of the HLFSRNN-MIL lies in its ability to make full use of the advantages of the HLFFF and SRNN methods to make up for their own weakness; i.e., the HLFFF can extract more targeted feature information to avoid the problem of excessive gradient fluctuation during training, and the SRNN is used to process the time-related sequences before classification. The experimental study of the HLFSRNN-MIL model is on two public CT datasets, namely, the Cancer Imaging Archive (TCIA) dataset on lung cancer and the China Consortium of Chest CT Image Investigation (CC-CCII) dataset on pneumonia. The experimental results show that the model exhibits better performance and accuracy. On the TCIA dataset, HLFSRNN-MIL with Residual Network (ResNet) as the feature extractor achieves an accuracy (ACC) of 0.992 and an area under curve (AUC) of 0.997. On the CC-CCII dataset, HLFSRNN-MIL achieves an ACC of 0.994 and an AUC of 0.997. Finally, compared with the existing methods, HLFSRNN-MIL has obvious advantages in all aspects. These experimental results demonstrate that HLFSRNN-MIL can effectively solve the disease problem in the field of 3D CT images. [ABSTRACT FROM AUTHOR]