Microplastic coupled with soil dissolved organic matter mediated changes in the soil chemical and microbial characteristics.

The abundance of microplastics (MPs) in soil environments has attracted significant attentions, due to their impact on soil physico-chemical properties. However, limited information is available on the influences of MPs on soil carbon composition and microbial utilization characteristics. Therefore, a two-month incubation experiment was conducted to add polyethylene microplastics (PE-MPs) with different levels (1%, 10%) and sizes (150-300 µm and 75-150 µm) into different soils. After that, soil chemical properties including the dissolved organic carbon (DOC), spectral characteristics of dissolved organic matter (DOM) and soil microbial characteristics were analyzed. Results revealed that PE-MPs addition caused significant differences in soil chemical properties between farmland and woodland soils, particularly in soil pH, DOM composition, and soil phosphatase activity. Woodland soil always exhibited higher levels of DOC content, microbial diversity, and soil carbon source utilization compared to farmland soil, leading to increased humification in the DOM of woodland soil. PE-MPs with a larger particle size significantly increased both the soil DOC content and enzyme activity. Addition of PE-MPs altered the soil DOM composition, and the fluorescence parameters like the biological index (BIX) and humification degree. Moreover, the carbon source utilization intensity of microorganisms on PE MPs-contaminated soils is higher in woodland soils. Various analyses confirmed that compared to other soil properties, characteristics of soil DOM had a more significant impact on soil microbial community composition. Thus, PE-MPs in conjunction with soil DOM spectral characteristics regulated soil microbial diversity, which is crucial for understanding soil carbon sequestration.

Health education in the management of chronic diseases among the elderly in the community with the assistance of a Mask R-CNN model.

OBJECTIVE: To analyze the role of health education in the management of chronic diseases in older people in the community and the countermeasures. METHODS: After establishing a community health management model for chronic diseases of the elderly based on references, a prospective study was conducted on 120 elderly patients with chronic diseases registered in Xinyang Zhongxing Community Health Service Center, Xixiangtang District, Nanning City from January 2019 to June 2020. The lottery method was used to divide all patients into observation and control groups. Patients in the control group received conventional chronic disease health management, while the observation group received an additional community-based chronic disease health education model for the elderly on the basis of care given to the control group. The change in chronic disease prevention knowledge mastering, medical compliance behavior score, anxiety and depression score, and quality of life score before and after the intervention were compared. RESULTS: After intervention, the awareness rates of patients in the observation group on the clinical manifestations, diagnostic criteria, high-risk behaviors, susceptible population and preventive measures of chronic diseases were significantly higher than that in the control group (all P<0.05), the scores of diet, exercise and lifestyle were significantly higher than those in the control group (all P<0.05), and the scores of depression and anxiety were significantly lower than those in the control group (all P<0.05). The scores of mental function, physical function and social function were significantly higher than those of control group (all P<0.05). CONCLUSION: Health education intervention play an important role in community management of chronic diseases in elderly patients. It effectively improves patients' understanding of the disease and enhances their compliance to medical advice, while reducing patients' anxiety, depression mood and improving their quality of life.

A very low frequency (VLF) antenna based on clamped bending-mode structure magnetoelectric laminates.

As the development of wireless communication devices tends to be highly integrated, the miniaturization of very low frequency (VLF) antenna units has always been an unresolved issue. Here, a novel VLF mechanical communication antenna using magnetoelectric (ME) laminates with bending-mode structure is realized. ME laminates combines magnetostrictive Metglas amorphous ribbons and piezoelectric 0.7Pb(Mg1/3Nb2/3)O3-0.3PbTiO3single crystal plates. From the simulation, we confirmed that the ME laminates can reduce the resonance peak from 18 kHz to 7.5 kHz by bending-mode structure. Experiment results show the resonance frequency can be farther reduced to 6.3 kHz by clamping one end of the ME antenna. The ME laminate exhibits a giant converse ME coefficient of 6 Oe cm V-1at 6.3 kHz. The magnetic flux density generated by the ME antenna has been tested along with distance ranging from 0 to 60 cm and it is estimated that a 1 fT flux could be detected around 100 m with an excitation power of 10 mW.

Semi-Supervised Structured Subspace Learning for Multi-View Clustering.

Multi-view clustering aims at simultaneously obtaining a consensus underlying subspace across multiple views and conducting clustering on the learned consensus subspace, which has gained a variety of interest in image processing. In this paper, we propose the Semi-supervised Structured Subspace Learning algorithm for clustering data points from Multiple sources (SSSL-M). We explicitly extend the traditional multi-view clustering with a semi-supervised manner and then build an anti-block-diagonal indicator matrix with small amount of supervisory information to pursue the block-diagonal structure of the shared affinity matrix. SSSL-M regularizes multiple view-specific affinity matrices into a shared affinity matrix based on reconstruction through a unified framework consisting of backward encoding networks and the self-expressive mapping. The shared affinity matrix is comprehensive and can flexibly encode complementary information from multiple view-specific affinity matrices. An enhanced structural consistency of affinity matrices from different views can be achieved and the intrinsic relationships among affinity matrices from multiple views can be effectively reflected in this manner. Technically, we formulate the proposed model as an optimization problem, which can be solved by an alternating optimization scheme. Experimental results over seven different benchmark datasets demonstrate that better clustering results can be obtained by our method compared with the state-of-the-art approaches.

Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization.

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

Digenean parasites of Chinese marine fishes: a list of species, hosts and geographical distribution.

In the literature, 630 species of Digenea (Trematoda) have been reported from Chinese marine fishes. These belong to 209 genera and 35 families. The names of these species, along with their hosts, geographical distribution and records, are listed in this paper.