Reconstructing the evolution history of networked complex systems.

The evolution processes of complex systems carry key information in the systems' functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be extracted, including protein-protein interaction, ecology, and social network systems. The recovered evolution process has demonstrations of immense scientific values, such as interpreting the evolution of protein-protein interaction network, facilitating structure prediction, and particularly revealing the key co-evolution features of network structures such as preferential attachment, community structure, local clustering, degree-degree correlation that could not be explained collectively by previous theories. Intriguingly, we discover that for large networks, if the performance of the machine learning model is slightly better than a random guess on the pairwise order of links, reliable restoration of the overall network formation process can be achieved. This suggests that evolution history restoration is generally highly feasible on empirical networks.

A portable magnetic electrochemical sensor for highly efficient Pb(II) detection based on bimetal composites from Fe-on-Co-MOF.

The practical, sensitive, and real-time detection of heavy metal ions is an essential and difficult problem. This study presents the design of a unique magnetic electrochemical detection system that can achieve real-time field detection. To enhance the electrochemical performance of the sensor, Fe2O3@C-800, Co/CoO@/C-600, and CoFe2O4@C-600 magnetic composites were synthesized using three MOFs precursors by the solvothermal method. And the morphology structure and electrochemical properties of as-prepared magnetic composites were researched by X-ray diffraction (XRD), Scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS), vibrating sample magnetometer (VSM), specific surface area and porosity analyzer (BET) and differential pulse voltammetry (DPV). The results shown that these composites improve conductivity and stability while preserving the MOFs basic frame structure. Compared with the monometallic MOFs-derived composites, the synergistic effect of the bimetallic composite CoFe2O4@C-600 can significantly enhance the electrochemical performance of the sensor. The linear range for the detection of lead ions was 0.001-60 µM, and the detection limit was 0.0043 µM with a sensitivity of 22.22 µA µM·cm-2 by differential pulse voltammetry. The sensor has good selectivity, stability, reproducibility and can be used for actual sample testing.

Long-term disability in common mental disorders in Chinese community: evidence from a five-year follow-up study.

BACKGROUND: Common mental disorders are general term for mental disorders with high disability rates and significant social burden. The purpose of this study was to determine the degree of long-term disability associated with common mental disorders and to interpret the relationship between common mental disorders and long-term disability. METHODS: Participants in the 2013 China Mental Health Survey were followed up by telephone between April and June 2018. This study evaluated long-term disability over a five-year period using the World Health Organization's Disability Assessment Schedule 2.0. Poisson regression was used to analyze the relationship between common mental disorders and long-term disability. RESULTS: A total of 6269 patients were followed up by telephone. In patients with common mental disorders, the prevalence of disability ranged from 7.62% to 43.94%. The long-term disabilities were significantly associated with dysthymic disorder (DD, RR:2.40; 95% CI:1.87-3.03), major depressive disorder (MDD, RR:1.63; 95% CI:1.34-1.98), generalized anxiety disorder (GAD, RR:1.95; 95% CI:1.15-3.09), obsessive-compulsive disorder (OCD, RR:1.68; 95% CI:1.24-2.22) and alcohol use disorder (AUD, RR: 1.42; 95% CI:0.99-1.96). CONCLUSIONS: In China, common mental disorders raise the risk of long-term disability, and there is a critical need for monitoring patients with DD, MDD, GAD, OCD, and AUD. For improved quality of life and reduced disability levels, more resources need to be dedicated to mental health in the future.

Help-Seeking Behaviors and Related Factors in Chinese Patients With Major Depressive Disorder: A Community-Based Cross-Sectional Study.

Background: Although evidence-based and effective treatments are available for people with major depressive disorder (MDD), a substantial number do not seek or receive help. Therefore, this study aimed to (1) investigate the total help-seeking rate and first-time help-seeking choices; (2) explore the perceived helpfulness of 23 potential sources; and (3) evaluate the factors related to help-seeking behaviors among patients with MDD. Materials and Methods: Data came from the Tianjin Mental Health Survey (TJMHS), which included a representative sample of adult community residents (n = 11,748) in the Chinese municipality of Tianjin. Of these, 439 individuals were diagnosed with lifetime MDD according to the Diagnostic and Statistical Manual-fourth edition (DSM-IV) and administered a help-seeking questionnaire. Results: In a survey, 28.2% of patients with MDD living community reported that they had ever sought any help during their entire lifetime before the interview, with 8.2% seeking help in mental healthcare settings, 8.0% only in other healthcare settings, and 12.0% only in non-healthcare sources (e.g., family, friends, and spiritual advisor). Among help-seekers, the first help mainly was sought in non-healthcare sources (61.3%), followed by healthcare settings (25.8%) and mental healthcare settings (12.9%). The majority of MDD individuals thought the non-healthcare sources were not helpful and mental healthcare settings were helpful or possibly helpful to solve mental problems. Female, having 10-12 or higher education years, comorbid anxiety disorders were associated with increased help-seeking. Conclusion: A small percentage of individuals with MDD living in community of Tianjin sought help. They preferred non-healthcare sources to healthcare settings. Demographic and clinical features were associated with help-seeking behaviors.

Analysis of Relevant Factors Affecting the Pregnancy Rate of Frozen-Thawed Embryo Transfer Cycle.

Objective: The aim of this study is to explore the relevant factors affecting the pregnancy rate of frozen-thawed embryo transfer cycle. Methods: The clinical data of 931 patients who underwent artificial cycle preparation for endometrial FET from April 2017 to November 2020 in the reproductive center of our hospital were retrospectively analyzed. Results: According to the pregnancy situation, the patients were divided into 450 cases of pregnancy and 481 cases of biochemical pregnancy. The univariate analysis of FET biochemical pregnancy showed that there were statistically significant differences between pregnancy and biochemical pregnancy in terms of years of infertility, age, endometrial thickness, P level, E2/P, and the number of high-quality embryos (P < 0.05). Multivariate analysis of pregnancy showed that age <30 years was a protective factor for biochemical pregnancy and endometrial thickness <8 mm and E2/P < 0.3 were risk factors (P < 0.05). Conclusion: The regulation of endometrial thickness and E2/P serves as the key of treatment for patients undergoing FET using artificial cycle preparation for endometrial transfer, and it contributes to improve the pregnancy rate; also, the patient's age is an important indicator influencing the pregnancy rate.

A digital bandwidth interleaved structure correction method based on itemized correction.

To satisfy the input bandwidth and sampling rate requirements of data acquisition systems, digital bandwidth-interleaved analog-to-digital converters (DBI-ADCs) offer a practical parallel structure. However, the existing DBI-ADC correction methods are broadly inadequate in terms of design, testing, and implementation. Moreover, the evaluation and correction of the most significant feature of the DBI-ADC structure-wideband acquisition performance-is also imperfect. This paper proposes an itemized correction method for DBI-ADC structures. The proposed method simplifies the complex correction filter bank design algorithm into multiple simple correction filters and then separates and corrects the various errors of the DBI-ADC system. This dramatically simplifies the design, testing, and implementation process of the system, resulting in a highly convenient method for practical engineering. In addition, this method achieves a good correction effect, with an appropriate balance between the correction effect and the project implementation. Simulation results and experimental results verify the effectiveness of the proposed method.

Systematic comparison of graph embedding methods in practical tasks.

Network embedding techniques aim to represent structural properties of graphs in geometric space. Those representations are considered useful in downstream tasks such as link prediction and clustering. However, the number of graph embedding methods available on the market is large, and practitioners face the nontrivial choice of selecting the proper approach for a given application. The present work attempts to close this gap of knowledge through a systematic comparison of 11 different methods for graph embedding. We consider methods for embedding networks in the hyperbolic and Euclidean metric spaces, as well as nonmetric community-based embedding methods. We apply these methods to embed more than 100 real-world and synthetic networks. Three common downstream tasks - mapping accuracy, greedy routing, and link prediction - are considered to evaluate the quality of the various embedding methods. Our results show that some Euclidean embedding methods excel in greedy routing. As for link prediction, community-based and hyperbolic embedding methods yield an overall performance that is superior to that of Euclidean-space-based approaches. We compare the running time for different methods and further analyze the impact of different network characteristics such as degree distribution, modularity, and clustering coefficients on the quality of the embedding results. We release our evaluation framework to provide a standardized benchmark for arbitrary embedding methods.

Model-free hidden geometry of complex networks.

The fundamental idea of embedding a network in a metric space is rooted in the principle of proximity preservation. Nodes are mapped into points of the space with pairwise distance that reflects their proximity in the network. Popular methods employed in network embedding either rely on implicit approximations of the principle of proximity preservation or implement it by enforcing the geometry of the embedding space, thus hindering geometric properties that networks may spontaneously exhibit. Here we take advantage of a model-free embedding method explicitly devised for preserving pairwise proximity and characterize the geometry emerging from the mapping of several networks, both real and synthetic. We show that the learned embedding has simple and intuitive interpretations: the distance of a node from the geometric center is representative for its closeness centrality, and the relative positions of nodes reflect the community structure of the network. Proximity can be preserved in relatively low-dimensional embedding spaces, and the hidden geometry displays optimal performance in guiding greedy navigation regardless of the specific network topology. We finally show that the mapping provides a natural description of contagion processes on networks, with complex spatiotemporal patterns represented by waves propagating from the geometric center to the periphery. The findings deepen our understanding of the model-free hidden geometry of complex networks.

A novel algorithm for implementing time-frequency transform with low computation.

In this paper, a novel algorithm called two-dimensional sliding fast Fourier transform (2D SFFT) algorithm is proposed. This algorithm organizes one-dimensional data in two dimensions and calculates the spectrum of current data by using the existing spectrum and new collected data. The algorithm formula and accurate simulation results show the following: first, the computation required by the proposed 2D SFFT algorithm is lower than that required by the traditional sliding discrete Fourier transform algorithm when the sliding rate is larger than or equal to 4/M, where M is the sequence length. Moreover, the computation required by the proposed 2D SFFT algorithm is lower than that required by the fast Fourier transform (FFT) algorithm when the sliding rate is less than or equal to 6.25%. Finally, the error between the spectrum calculated by the 2D SFFT and FFT algorithms is less than 10-10. The 2D SFFT algorithm is used to increase the power of the ultra-short pulse, which is initially invisible in the frequency-domain window of the mixed-domain oscilloscope. Therefore, the 100% probability of intercept of the mixed-domain oscilloscope is lower.

Advantage of Being Multicomponent and Spatial: Multipartite Viruses Colonize Structured Populations with Lower Thresholds.

Multipartite viruses have a genome divided into different disconnected viral particles. A majority of multipartite viruses infect plants; very few target animals. To understand why, we use a simple, network-based susceptible-latent-infectious-recovered model. We show both analytically and numerically that, provided that the average degree of the contact network exceeds a critical value, even in the absence of an explicit microscopic advantage, multipartite viruses have a lower threshold to colonizing network-structured populations compared to a well-mixed population. We further corroborate this finding on two-dimensional lattice networks, which better represent the typical contact structures of plants.