U-model based predictive control for nonlinear processes with input delay

In this paper, a general control scheme is proposed for nonlinear dynamic processes with input delay described by different models, including polynomial models, state-space models, nonlinear autoregressive moving average with eXogenous inputs (NARMAX) models, Hammerstein or Wiener type models. To tackle the input delay and nonlinear dynamics involved with the control system design, it integrates the classical Smith predictor and a U-model based controller into a U-model based predictive control scheme, which gives a general solution of two-degree-of-freedom (2DOF) control for the set-point tracking and disturbance rejection, respectively. Both controllers are analytically designed by proposing thedesired transfer functions for the above objectives in terms of a linear system expression with the U-model, and therefore are independent of the process model for implementation. Meanwhile, the control system robust stability is analyzed in the presence of process uncertainties. To demonstrate the control performance and advantage, three examples from the literature are conducted with a user-friendly step by step procedure for the ease of understanding by readers

Research on monitoring method of shaft tilt deformation based on SLAM

In view of the problems existing in traditional shaft safety monitoring methods such as low efficiency(need monitoring after production stop), less data and large error, a method of monitoring shaft tilt deformation with laser SLAM (Simultaneous Localization and Mapping) technology was proposed. The main shaft of Niuerzhuang Mine of Fengfeng Group was taken as the research object, the monitoring plan was designed and the laser SLAM technology was used to perceive the internal information of shaft. The K′-means algorithm was adopted to extract the point cloud of shaft boundary, the Markov mathematical model was established to get the center of point cloud slice, and then to the shaft center datum line was set up, the shaft tilt deformation was analyzed based on integral and subsection methods. The results showed that the overall vertical inclination of the shaft was 1.99‰, the vertical inclination of upper shaft(0-100 m away from the shaft head) was 3.06‰, and the vertical inclination of lower shaft(150-205 m away from the shaft head) was 1.85‰. Compared with the traditional monitoring method, the working time of laser SLAM can be shortened from one day or even longer to one hour. The monitoring work can be completed within the maintenance time of the shaft cage, and the work efficiency is significantly improved without stopping production

Efficient Dynamic Integrity Verification for Big Data Supporting Users Revocability

With the advent of the big data era, cloud data storage and retrieval have become popular for efficient data management in large companies and organizations, thus they can enjoy the on-demand high-quality cloud storage service. Meanwhile, for security reasons, those companies and organizations would like to verify the integrity of their data once storing it in the cloud. To address this issue, they need a proper cloud storage auditing scheme which matches their actual demands. Current research often focuses on the situation where the data manager owns the data; however, the data belongs to the company, rather than the data managers in the real situation which has been overlooked. For example, the current data manager is no longer suitable to manage the data stored in the cloud after a period and will be replaced by another one. The successor needs to verify the integrity of the former managed data; this problem is obviously inevitable in reality. In this paper, we fill this gap by giving a practical efficient revocable privacy-preserving public auditing scheme for cloud storage meeting the auditing requirement of large companies and organization’s data transfer. The scheme is conceptually simple and is proven to be secure even when the cloud service provider conspires with revoked users

Using formalin fixed paraffin embedded tissue to characterize the microbiota in p16-positive and p16-negative tongue squamous cell carcinoma: a pilot study

Abstract Background Tongue squamous cell carcinoma (TSCC) is the most common oral cavity cancer, and p16 immunohistochemistry is an exact and available tool in the prognostic and predictive characterization of squamous cell cancers in the head and neck. Microorganisms have a close relationship with the development of TSCC. However, the association between oral bacteria and p16 status has not been well defined in the case of TSCC. Compared with traditional clinical microbial collection methods, formalin-fixed paraffin-embedded (FFPE) tissue samples have several advantages. Methods To compare the microbiota compositions between p16-positive and p16-negative patients with TSCC, we performed a small pilot study of microbiological studies of TSCC by paraffin tissue. DNA from FFPE tissue blocks were extracted and microbiomes were profiled by sequencing the 16 S-rRNA-encoding gene (V1–V2/V3-V4/V4 regions). Alterations in the functional potential of the microbiome were predicted using PICRUSt, Tax4Fun, and BugBase. Results A total of 60 patients with TSCC were enrolled in the study, however, some challenges associated with DNA damage in FFPE tissues existed, and only 27 (15 p16-positive and 12 p16-negative) passed DNA quality control. Nevertheless, we have tentatively found some meaningful results. The p16 status is associated with microbiota diversity, which is significantly increased in p16-positive patients compared with p16-negative patients. Desulfobacteria, Limnochordia, Phycisphaerae, Anaerolineae, Saccharimonadia and Kapabacteria had higher abundances among participants with p16-positive. Moreover, functional prediction revealed that the increase of these bacteria may enhance viral carcinogenesis in p16-positive TSCC. Conclusions Bacterial profiles showed a significant difference between p16-positive TSCC and p16-negative TSCC. These findings may provide insights into the relationship between p16 status and the microbial taxa in TSCC, and these bacteria may provide new clues for developing therapeutic targets for TSCC

Sulfated Hetero-Polysaccharides Protect SH-SY5Y Cells from H2O2-Induced Apoptosis by Affecting the PI3K/Akt Signaling Pathway

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. Recent studies suggest that sulfated hetero-polysaccharides (UF) protect against developing PD. However, the detailed mechanisms of how UF suppress neuronal death have not been fully elucidated. We investigated the cytoprotective mechanisms of UF using human dopaminergic neuroblastoma SH-SY5Y cells as a PD model. UF prevented H2O2-induced apoptotic cell death in SH-SY5Y cells in a dose-dependent manner. An examination of the PI3K/Akt upstream pathway revealed that UF-pretreated cells showed a decreased relative density of Akt, PI3K, and TrkA, and increased the phosphorylation of Akt, PI3K, and NGF; the PI3K inhibitor, LY294002, partially prevented this effect. An examination of the PI3K/Akt downstream pathway revealed the increased expression of the apoptosis-associated markers Bax, p53, CytC, and GSK3β, and the decreased expression of Bcl-2 in UF-treated cells. UF-treated cells also exhibited decreased caspase-3, caspase-8, and caspase-9 activities, which induced cell apoptosis. Our results demonstrate that UF affect the PI3K/Akt pathway, as well as downstream signaling. Therefore, the UF-mediated activation of PI3K/Akt could provide a new potential therapeutic strategy for neurodegenerative diseases associated with oxidative injury. These findings contribute to a better understanding of the critical roles of UF in the treatment of PD

Hishikaku joho o katsuyoshita atarashii intafesu no shisaku to hyoka

Abstract Background Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients. Methods This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images. Firstly, the fundus structures, including blood vessels, optic disc and macula, are extracted and located, respectively. In particular, a new optic disc localization method using parabolic fitting is proposed based on the physiological structure characteristics of optic disc and blood vessels. Then, early lesions, such as microaneurysms, hemorrhages and hard exudates, are detected based on their respective characteristics. An equivalent optical model simulating human eyes is designed based on the anatomical structure of retina. Main structures and early lesions are reconstructed in the 3D space for better visualization. Finally, the severity of each image is evaluated based on the international criteria of diabetic retinopathy. Results The system has been tested on public databases and images from hospitals. Experimental results demonstrate that the proposed system achieves high accuracy for main structures and early lesions detection. The results of severity classification for non-proliferative diabetic retinopathy are also accurate and suitable. Conclusions Our system can assist ophthalmologists for clinical diagnosis, automatic screening and course progression of patients