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Background The prognostic role of the cardiothoracic ratio (CTR) in chronic kidney disease (CKD) remains undetermined. Methods We conducted a retrospective cohort study of 3117 patients with CKD aged 18–89 years who participated in an Advanced CKD Care Program in Taiwan between 2003 and 2017 with a median follow up of 1.3(0.7–2.5) and 3.3(1.8–5.3) (IQR) years for outcome of end-stage renal disease (ESRD) and overall death, respectively. We developed a machine learning (ML)–based algorithm to calculate the baseline and serial CTRs, which were then used to classify patients into trajectory groups based on latent class mixed modelling. Association and discrimination were evaluated using multivariable Cox proportional hazards regression analyses and C-statistics, respectively. Results The median (interquartile range) age of 3117 patients is 69.5 (59.2–77.4) years. We create 3 CTR trajectory groups (low [30.1%], medium [48.1%], and high [21.8%]) for the 2474 patients with at least 2 CTR measurements. The adjusted hazard ratios for ESRD, cardiovascular mortality, and all-cause mortality in patients with baseline CTRs ≥0.57 (vs CTRs P = 0.04) for cardiovascular mortality and 0.697 (vs 0.693, P Conclusions Our findings support the real-world prognostic value of the CTR, as calculated by a ML annotation tool, in CKD. Our research presents a methodological foundation for using machine learning to improve cardioprotection among patients with CKD.

Background: The prognostic role of the cardiothoracic ratio (CTR) in chronic kidney disease (CKD) remains undetermined. Methods: We conducted a retrospective cohort study of 3117 patients with CKD aged 18 to 89 years who participated in an Advanced CKD Care Program in Taiwan between 2003 and 2017 with a median follow up of 1.3(0.7-2.5) and 3.3(1.8-5.3) (IQR) years for outcome of end-stage renal disease (ESRD) and overall death, respectively. We developed a machine learning (ML)–based algorithm to calculate the baseline and serial CTRs, which were then used to classify patients into trajectory groups based on latent class mixed modelling. Association and discrimination were evaluated using multivariable Cox proportional hazards regression analyses and C-statistics, respectively. Results: Here we show the median (interquartile range) age of 3117 patients is 69.5 (59.2-77.4) years. We create 3 CTR trajectory groups (low [30.1%], medium [48.1%], and high [21.8%]) for the 2474 patients with at least 2 CTR measurements. The adjusted hazard ratios for ESRD, cardiovascular mortality, and all-cause mortality in patients with baseline CTRs ≥0.57 (vs CTRs P = .04) for cardiovascular mortality and 0.697 (vs 0.693, P  Conclusions: Our findings support the real-world prognostic value of the CTR, as calculated by a ML annotation tool, in CKD. Our research presents a methodological foundation for using machine learning to improve cardioprotection among patients with CKD.

Manipulation of the valley degree of freedom provides a new path for quantum information technology, but the real intrinsic large valley-polarization materials are rarely reported up to date. Here, we perform first-principles calculations to predict a class of 2H-phase single layer (SL) materials LuX 2 (X = Cl, Br, I) to be ideal candidates. SL-LuX 2 are ferrovalley materials with a giant valley-polarization of 55 meV–148 meV as a result of its large spin–orbital coupling (SOC) and intrinsic ferromagnetism (FM). The magnetic transition temperatures of SL-LuI2 and SL-LuCl2 are estimated to be 89 K–124 K, with a sizable magnetic anisotropy at out-of-plane direction. Remarkably, the anomalous valley Hall effect (AVHE) can be controlled in SL-LuX 2 when an external electric field is applied. Moreover, the intrinsic valley-polarization of SL-LuI2 is highly robust for biaxial strain. These findings provide a promising ferrovalley material system for the experimentation of valleytronics and subsequent applications.

The quantum anomalous Hall effect (QAHE) has special quantum properties that are ideal for possible future spintronic devices. However, the experimental realization is rather challenging due to its low Curie temperature and small non-trivial bandgap in two-dimensional (2D) materials. In this paper, we demonstrate through first-principles calculations that monolayer Co2Te material is a promising 2D candidate to realize QAHE in practice. Excitingly, through Monte Carlo simulations, it is found that the Curie temperature of single-layer Co2Te can reach 573 K. The band crossing at the Fermi level in monolayer Co2Te is opened when spin–orbit coupling is considered, which leads to QAHE with a sizable bandgap of E g = 96 meV, characterized by the non-zero Chern number (C = 1) and a chiral edge state. Therefore, our findings not only enrich the study of quantum anomalous Hall effect, but also broaden the horizons of the spintronics and topological nanoelectronics applications.

A novel type of coumarin thiazoles as unique multi-targeting antimicrobial agents were developed through four steps including cyclization, nucleophilic substitution and condensation starting from commercial resorcine. Most of the prepared coumarin thiazoles displayed favorable inhibitory potency against the tested strains. Noticeably, methyl oxime V-a exerted potent inhibitory efficacy against methicillin-resistant Staphylococcus aureus (MRSA) at low concentration (1 μg/mL) and showed broad antimicrobial spectrum. Medicinal bioevaluations revealed that the active molecule V-a exhibited low toxicity toward mammalian cells, rapidly killing effect, good capability of eradicating MRSA biofilms and unobvious probability to engender drug resistance. Chemical biological methods were employed to investigate preliminary mechanism, which indicated that compound V-a was able to damage the integrity of membrane to trigger leakage of protein, insert into MRSA DNA to block its replication and induce the generation of reactive oxygen species (ROS) to inhibit bacterial growth. Computational study manifested that low HOMO-LUMO energy gap of molecule V-a was favorable to exert high antimicrobial activity.

Long-term fertilization is known to impact the biodiversity and community structures of soil organisms, which are responsible for multiple soil ecosystem functions (multifunctionality). However the relationship between the alterations of soil organisms and ecosystem multifunctionality remains unclear, especially in the case of long-term fertilization. To explore the contribution of soil organismal biodiversity and community structures to ecosystem multifunctionality, we took soil samples from a nearly 25-year field fertilization experiment. Organic matter significantly improved the soil ecosystem multifunctionality. Ecosystem multifunctionality was found to be closely linked to the biodiversity and communities of soil organisms within the major ecological clustering of soil organisms (Module 1) according to the trophic co-occurrence network, rather than the entire community of soil organisms. This indicated that ecological clusters of soil organisms within the network were critical in maintaining soil ecosystem multifunctionality. The application of organic fertilization could enrich specialized soil organisms and increase interactions of soil organisms in the ecological cluster. As a result, our findings emphasize the role of ecological clusters in the soil organismal co-occurrence network in controlling soil multifunctionality after long-term fertilization, presenting a novel perspective on the link between soil biodiversity and ecosystem multifunctionality.

A new methodology for the synthesis of novel benzo[b][1,4]diazepine derivatives via a one-pot, multi-component reaction of benzaldehyde, o-phenylenediamine, and ethyl propiolate has been developed. Readily available starting materials, operationally simple, metal-free reaction conditions, simplicity of product isolation and good yields are key advantages of this methodology. The structure of the benzo[b][1,4]diazepines were confirmed by NMR, HRMS and XRD.

We investigated 15 N abundance (δ 15 N) of winter wheat ( Triticum aestivum cv. Jinmai 1) plants and soil at different growth stages in a field with a 13-year fertilization history of urea and compost, to determine whether or not the δ 15 N of plant parts can be used as an indicator of organic amendment with compost. Plant parts (roots, leaves, stems and grains) and soil were sampled at re-greening, jointing, grain filling and mature growth stages of winter wheat. There were significant differences between the urea and compost treatments in δ 15 N of whole plants, plant parts and soil over the whole growing season. Determination of the δ 15 N of plant parts was more convenient than that of whole plant to distinguish between the application of organic amendment and synthetic N fertilizer.

In order to provide technical supports and visualization tools to the multi-GNSS related researches, 3D multi-GNSS visualization system (3DMVS) is designed and implemented. In this paper, the system requirements are analyzed at first and four modules (user interface module; display module; date calculating module; 3D models library module) are designed to realize the 3D visualization of the earth, satellites and orbits in different navigation system. Then the system general architecture is presented. Next, the system main process, data generation process and data visualization process is introduced. Dataflow between modules are illustrated in details by four steps. The visual C# programming tools and the 3D modeling software ZAM3D are used in the course of system implementation. The system has successfully applied in the related researches of multi-GNSS.

Global Navigation Satellite System (GNSS) signal simulator is one of the most important instruments for testing the function and performance of GNSS terminal products. It consists of a Mathematical Simulation System (MSS) and a Radio Frequency Signal Generator (RFSG). The MSS is responsible for generating the navigation message and observation data and then sending them to the RFSG in real time. The simulation accuracy of each part in the MSS determines that of the signal generated by the RFSG. In this paper, the function requirements of each module in MSS are analyzed firstly. Then the general framework of MSS is presented. At last, MSS developed in this paper is demonstrated and tested partly, the test results are compared with that of SimGEN software and STK. Taken as a whole, the MSS has complete functions and good performance. The MSS will hopefully apply to GNSS signal simulator.

To solve the problems which refer to share of design resources, and realize reasonable matching of design ability in the collaborative design process of complex product, a new Missile Design Service Platform based on Virtual Design Unit (MDSP-VDU) is proposed. Firstly, main function modules and characteristics of MDS-VDU are described. Secondly, key technologies including design resource virtualization, Virtual Design Unit construction, service description rules design services separation and combination,design process customization, VDUs scheduling are introduced. Thirdly, prototype system of MDS-VDU is built and displayed. Some theories about MDS-VDU have been applied in the implementation of missile design service platform and virtual resource management system in the Group-oriented enterprise CMfg Platform. Finally, application results show that MDSP-VDU is feasible.

The helicopter Maintenance, Repair and Overhaul/Operations (MRO) system enables the best sharing of the maintenance resources and maintenance ability in a wide area, so as to promote the specialization of the helicopter maintenance organizations. Information acquisition is an important and difficult part of the helicopter MRO system. This paper systematically analyzes the condition monitoring methods which are used to monitor the rotational speed, temperature, pressure, vibration and flight parameter in different parts of a helicopter, and then it puts forward some improved ways for information acquisition. Considering the helicopter’s features, the process of information acquisition is illustrated. In addition, this paper presents the basic requirements of data sampling, and it also shows a detailed discussion on data format and data transmission in the helicopter MRO system. At the end of the paper, a system mode and architecture of helicopter MRO system are proposed.

Based on the concept of Cloud Computing, Cloud Manufacturing which refers to a new networked manufacturing mode is proposed by LI Bo-hu. In this new mode, virtual resources are organized to meet the requirements of various manufacturing services for users over network and Cloud Manufacturing platform. This paper focuses on the virtualization of resources and analyses the factors which affect the classification of virtual resources in Cloud Manufacturing first, and a conceptual classification is given. Then some factors affect the result of task assignment are introduced, and a simple example shows the effect of these factors to task assignment. Based on these factors which include quantitative, human activity, logistics and granularity, a modeling process and a rough model of virtual resource are built.

Three-dimensional imaging lidar can offer the range information and CCD camera can offer the color information of the target. These two information can strongly supplement each other, the fusion of them is becoming a research hot point. The major problem of fusing lidar data and camera data is the coordinate calibration between them. In consideration of the traits of lidar and camera, a new planar object calibration method was proposed, which solves extrinsic matrix using the normal of planar objects. The rotation matrix and transfer vector are solved separately, which can simplify the calibration process and highly improve the calibration precision. The improved extrinsic calibration method was applied on texture mapping and reverse mapping, which show that our algorithm can gives good results.

For complex product design, many software and tools are used, and large scale intermediate data with heterogeneous formats and complex relationships are produced in preliminary design. Efficient organization and management of data are very difficult. The integrated design environments(IDE) are useful to solve this problem. This paper gives an overview on IDE and some correlative key technologies. According to characteristics of preliminary design stage, a framework of IDE is put forward in this paper and the system function components are analyzed. The framework includes some innovative methodologies, such as task-drove design by workflow management, design tools and software seamless integration, and design knowledge templates. The realization of IDE is presented to illustrate the applicability of the new framework.

Based on the analysis of the characteristics of infrared dim small target under complex cloud background, A detection algorithm is proposed for infrared dim small target. Firstly, median filtering algorithm is employed to remove the noise effectively. Secondly, according to the characteristics of the cloud background and targets, a frequency-domain processing method based on Fourier transform and second-order Butterworth high pass filtering is proposed. The cutoff frequency of the filter is adaptively decided by establishing the relationship between the background complexity and the cutoff frequency. Lastly, target detection is achieved by threshold segmentation. Experiments showed that the algorithm can effectively detect infrared dim small target under complex cloud background.