Low-Complexity Tracking Control of Unknown Strict-Feedback Systems With Quantitative Performance Guarantees.

This article is concerned with the prescribed performance tracking control problem for the strict-feedback systems with unknown nonlinearities and unmatched disturbances. The challenge lies in the realization of a complete performance specification for trajectory tracking in the sense of quantitatively regulating the peak value, overshoot, settling time, and accuracy while ensuring that the initial condition holds naturally. To this end, an error transformation, equipped with a shifting function, is introduced and incorporated with a new-type barrier function. Then, a class of performance functions is exploited to quantify the settling times and steady-state bounds of the intermediate errors. Moreover, to improve the flexibility of formulating performance specifications for the tracking error, a pair of asymmetric performance boundaries are further designed. With their combination, a novel robust prescribed performance control (PPC) approach is proposed in this article. It not only achieves the quantitative performance guarantees but also preserves the unique simplicity of PPC, evading the needs for function approximation, parameter identification, disturbance estimation, derivative calculation, or command filtering. The above theoretical findings are confirmed via three simulation studies.

Fault-tolerant prescribed performance control of nonlinear systems with process faults and actuator failures.

This paper investigates the fault-tolerant prescribed performance control problem for a class of multiple-input single-output unknown nonlinear systems subject to process faults and actuator failures. In contrast to the related works, we consider a general class of nonlinear systems with both multiplicative nonlinearities and additive nonlinearities corrupted by the process faults; only the boundedness of the process faults and the continuity of the nonlinear functions are required, without the explicit or fixed structures of the fault functions. To conquer this problem, a less-demanding and low-complexity fault-tolerant prescribed performance control approach is proposed. The controller is independent of the specific information of faults or the system model and does not invoke fault diagnosis or neural/fuzzy approximation to acquire such knowledge. It achieves the reference tracking with the predefined rate and accuracy. A comparative simulation on a single-link robot is conducted to illustrate the effectiveness and superiority of the proposed approach.

Anterior Gradient 2 is a Significant Prognostic Biomarker in Bone Metastasis of Breast Cancer.

Background: The study aimed to detect DEGs associated with BRCA bone metastasis, filter prognosis biomarkers, and explore possible pathways. Methods: GSE175692 dataset was used to detect DEGs between BRCA bone metastatic cases and non-bone metastatic cases, followed by the construction of a PPI network among DEGs. The main module among the PPI network was then determined and pathway analysis on genes within the module was performed. Through performing Cox regression, Kaplan-Meier, nomogram, and ROC curve analyses using GSE175692 and GSE124647 datasets at the same time, the most significant prognostic biomarker was gradually filtered. Finally, important pathways associated with prognostic biomarkers were explored by GSEA analysis. Results: The 74 DEGs were detected between bone metastasis and non-bone metastasis groups. A total of 15 nodes were included in the main module among the whole PPI network and they mainly correlated with the IL-17 signaling pathway. We then performed Cox analysis on 15 genes using two datasets and only enrolled the genes with p < 0.05 in Cox analysis into the further analyses. Kaplan-Meier analyses using two datasets showed that the common biomarker AGR2 expression was related to the survival time of BRCA metastatic cases. Further, the nomogram determined the greatest contribution of AGR2 on the survival probability and the ROC curve revealed its optimal prognostic performance. More importantly, high expression of AGR2 prolonged the survival time of BRCA bone metastatic patients. These results all suggested the importance of AGR2 in metastatic BRCA. Finally, we performed the GSEA analysis and found that AGR2 was negatively related to IL-17 and NF-kß signaling pathways. Conclusion: AGR2 was finally determined as the most important prognostic biomarker in BRCA bone metastasis, and it may play a vital role in cancer progression by regulating IL-17 and NF-kB signaling pathways.

Multi-focus image fusion based on fractional order differentiation and closed image matting.

This paper presents a novel approach to addressing the fusion of multi-focus images in either registered or mis-registered cases. The conventional approaches often produce blurred edges of objects in the fused images due to inaccurate decision maps. On the other hand, these decision maps are sensitive to mis-registration that causes artifact in the fused images. Therefore, we propose a robust multi-focus image fusion approach with clear object edges for the registered or mis-registered source images. In this approach, a fractional order differential mask is creatively adopted to pre-process the source images, ensuring the initial decision maps both with the boundaries and fine structures of the objects and with the internal holes closed. Then, the closed matting technique, in lieu of the robust matting, is adopted to refine the initial decision maps. This significantly reduces the interaction information from the users, but still preserves the complete boundaries of the objects. Finally, the global threshold processing is skillfully adopted to form the decision maps. This not only yields the final decision maps with smooth boundaries, but also guarantees the rich gradient information from the mis-registered source images. The experimental results show that the designed algorithm provides better visual perception and higher objective evaluation than some existing representative algorithms.

Analysis and prediction of COVID-19 epidemic in South Africa.

The coronavirus disease-2019 (COVID-19) has been spreading rapidly in South Africa (SA) since its first case on 5 March 2020. In total, 674,339 confirmed cases and 16,734 mortality cases were reported by 30 September 2020, and this pandemic has made severe impacts on economy and life. In this paper, analysis and long-term prediction of the epidemic dynamics of SA are made, which could assist the government and public in assessing the past Infection Prevention and Control Measures and designing the future ones to contain the epidemic more effectively. A Susceptible-Infectious-Recovered model is adopted to analyse epidemic dynamics. The model parameters are estimated over different phases with the SA data. They indicate variations in the transmissibility of COVID-19 under different phases and thus reveal weakness of the past Infection Prevention and Control Measures in SA. The model also shows that transient behaviours of the daily growth rate and the cumulative removal rate exhibit periodic oscillations. Such dynamics indicates that the underlying signals are not stationary and conventional linear and nonlinear models would fail for long-term prediction. Therefore, a large class of mappings with rich functions and operations is chosen as the model class and the evolutionary algorithm is utilized to obtain the optimal model for long term prediction. The resulting models on the daily growth rate, the cumulative removal rate and the cumulative mortality rate predict that the peak and inflection point will occur on November 4, 2020 and October 15, 2020, respectively; the virus shall cease spreading on April 28, 2021; and the ultimate numbers of the COVID-19 cases and mortality cases will be 785,529 and 17,072, respectively. The approach is also benchmarked against other methods and shows better accuracy of long-term prediction.

Neural Network Control of Underactuated Surface Vehicles With Prescribed Trajectory Tracking Performance.

This article is concerned with the fast and accurate trajectory tracking control problem for a sort of underactuated surface vehicle under model uncertainties and environmental disturbances. A novel neural networks (NNs)-based prescribed performance control strategy is proposed to solve the problem. In the control design, a new type of performance function is constructed which provides a way to predefine the settling time and accuracy, straightforward. Then, a pair of barrier functions are employed to combat not only the position error but also the virtual control input. This evades the possible singularity or discontinuity of the control solution. Next, an initialization technique is exploited, removing the requirement for the initial condition of the control system. Finally, two NNs are employed to deal with the unknown ship nonlinearities. The performance analysis not only demonstrates the effectiveness of the proposed approach but also reveals its robustness against disturbances and unknown reference trajectory derivatives. There is, thus, no need to acquire such knowledge or employ specialized tools to handle disturbances. The theoretical findings are illustrated by a simulation study.

Distributed Fuzzy Adaptive Output-Feedback Control of Unknown Nonlinear Multiagent Systems in Strict-Feedback Form.

This article is concerned with the cooperative tracking control problem for heterogeneous multiagent systems in a leader-following form under a directed graph. The dynamics of each following agent is unknown, obeying a strict-feedback form. With the help of fuzzy-logic systems, input filters, and constraint-handling schemes, a fully distributed output-feedback control algorithm is proposed to achieve output synchronization with prescribed performance and guarantee boundedness of signals in the closed-loop systems. In addition, the algorithm exhibits a simplicity control attribute in the sense that: 1) the control design utilizes only relative output measurements, and no extra information needs to be transmitted via the network and 2) the issue of explosion of complexity is addressed, without employing command filters or dynamic surface control techniques. Finally, the simulation results clarify and verify the established theoretical findings.

[Assessment of ecological vulnerability in multi-scale and its spatial correlation: A case study of Bailongjiang Watershed in Gansu Province, China.] / å¤šå°ºåº¦æµåŸŸç”Ÿæ€è„†å¼±æ€§è¯„ä»·åŠå ¶ç©ºé—´å ³è”æ€§­­ä»¥ç”˜è‚ƒç™½é¾™æ±ŸæµåŸŸä¸ºä¾‹.

The study of ecological vulnerability is of great significance to regional ecological environment protection and sustainable development. Bailongjiang Watershed (BLJW) of Gansu Pro-vince is a vital area for water conservation and environmental fragile in the upper Yangtze River. Therefore, it is necessary to understand the ecological vulnerability of BLJW for local sustainable development. Based on the sensitivity-recovery-pressure (SRP) model, landscape pattern index and the typical ecosystem type, we constructed the assessment system of ecological vulnerability by taking township as the spatial unit to analyze the spatiotemporal pattern of ecological vulnerability from the township, county, watershed scales in BLJW of Gansu Province in 2002 and 2014 via the auxi-liary regression, entropy weight, synthetic index, and spatial autocorrelation methods. The results showed that from the view of the township scale, the townships of severe or extreme vulnerability were concentrated in the northwestern Tanchang and most of Wudu in 2002 and 2014. The ecological vulnerability in the watershed had changed from moderate vulnerability to light vulnerability at township scale. At the county scale, the change of ecological vulnerability in Zhouqu was relatively stable, while that of Wudu, Wenxian, Tanchang and Diebu were relatively violent from 2002 to 2014. The ecological vulnerability of Wudu, Wenxian and Diebu improved to a certain extent, while that of Tanchang was deteriorating gradually. On watershed scale, the average value of ecological vulnerability index in the watershed were 0.2976 and 0.2904 in 2002 and 2014, respectively, showing a small downward trend, indicating that the ecological vulnerability in the watershed decreased in the past 12 years. The coefficients of variation were 0.3905 and 0.4358, respectively, with an increasing trend, suggesting that the spatial pattern of ecological vulnerability in the watershed developed in an unbalanced way. In 2002, the Moran I of ecological vulnerability index in the watershed was 0.5460, implying that the ecological vulnerability in the watershed was spatially agglomerated. Specifically, the areas of high-high were mainly distributed in the northern and central Wudu, and northwestern Tanchang. In 2014, the Moran I of ecological vulnerability index in the watershed increased to 0.5635, which indicated that the spatial agglomeration was more significant, and the areas of high-high were concentrated in central Wudu and northwestern Tanchang.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

Identification of interferon-γ-inducible-lysosomal thiol reductase (GILT) gene in goldfish (Carassius auratus) and its immune response to LPS challenge.

The interferon-γ-inducible lysosomal thiol reductase (GILT) has been demonstrated to play an important role in the processing and presentation of MHC class II restricted antigen (Ag) by catalyzing disulfide bond reduction. In this study, we cloned a GILT gene homolog from goldfish (designated gGILT), a kind of precious freshwater fish with high market value. The open reading frame of gGILT consists of 756 bases encoding a protein of 251 amino acids with an estimated molecular mass of 27.8 kDa and a theoretical isoelectric point of 5.24. The deduced protein possesses the typical structural features of known GILT proteins, including an active-site motif, a GILT signature sequence, and 10 conserved cysteines. RT-PCR results showed that gGILT and gIFN-γ (goldfish IFN-γ) mRNA were expressed in a tissue-specific manner and obviously up-regulated in splenocytes and the cells from head kidney after induction with LPS. Recombinant gGILT fused with His6 tag was efficiently expressed in Escherichia coli BL21 (DE3) and purified by Ni-NTA affinity chromatography. Further study revealed that gGILT was capable of catalyzing the reduction of the interchain disulfide bonds from intact IgG. This study shows that gGILT may be involved in the immune response to bacteria challenge and maintain first line of innate immune defense at basal level in goldfish. It also provides the basis for investigating on the role of GILT using goldfish as an animal model.

Evaluation of severe transplant renal artery stenosis with Doppler sonography.

PURPOSE: To evaluate and determine Doppler criteria for predicting a severe transplant renal artery stenosis (80%-99% diameter reduction) and to compare the Doppler findings in patients with end-to-end and end-to-side anastomosis. METHODS: We performed Doppler sonography on 16 consecutive patients with transplant renal artery stenosis (TRAS) confirmed by digital subtraction arteriography (DSA). Fourteen patients had end-to-end anastomosis, and 2 had end-to-side anastomosis. Eleven patients were re-evaluated with color Doppler sonography within 4 days after intervention. Seven Doppler parameters, including the peak systolic velocity (PSV) in the renal, iliac and interlobar artery, Pre-PSV ratio (the ratio of the PSV in the renal artery to that in the iliac artery), Post-PSV ratio (the ratio of the PSV in the renal artery to that in the interlobar arteries, acceleration time and resistance index, were measured. In the patients with severe TRAS the measurements of these parameters were compared before and after successful intervention. RESULTS: In the 16 patients with a single transplanted kidney, arteriography demonstrated 14 main renal arteries with severe stenosis, and 3 renal arteries with moderate stenosis. When using the cutoff values of Post-PSV ratio >13, renal artery PSV >4 m/sec, acceleration time >0.06 second, and resistance index <0.5 for the detection of all 14 severe stenoses, the sensitivities were 100%, 71%, 93%, and 50%, respectively. For assessing all 14 severe stenoses and 12 severe stenoses of end-to-end anastomosis, the cutoff value of Pre-PSV ratio >5 had sensitivities of 86% and 100%, respectively. Pre-PSV ratios in severe stenoses of end-to-end anastomosis (range, 5.1-11.5) were significantly greater than those recorded in severe stenoses of end-to-side anastomosis (range, 2.8-3.1). Statistically significant differences before and after successful intervention were found for all 7 Doppler parameters in the 7 patients with severe stenosis. CONCLUSIONS: An 80%-99% diameter reduction of the renal artery can be diagnosed based on a Post-PSV ratio >13 for patients with either end-to-end or end-to-side anastomosis. A Pre-PSV ratio >5 for patients with end-to-end anastomosis and acceleration time >0.06 second are helpful in the diagnosis of severe TRAS.

[Assessment of preoperative localization techniques for patients with primary hyperparathyroidism].

OBJECTIVE: To evaluate the sensitivity and usefulness of 99mTc-sestamibi scintigraphy (SS) and neck ultrasonography (US) as preoperative localization procedures in patients with primary hyperparathyroidism (pHPT). METHODS: 160 patients with proved pHPT in Peking Union Medical College Hospital from June 1983 to June 2002 were studied. There were 107 women(66.9%) and 53 men (33.1%), with a mean age of 38.9 years (10-73 years). 100 patients were underwent SS and 148 patients were underwent US prior to surgery, and the results were compared with operative and histological findings. RESULTS: The sensitivity of SS and US in localization of the enlarged parathyroid glands was 94.0% and 85.1% respectively, and the positive predictive value of SS and US was 100% and 89.1% respectively, the overall sensitivity was 98.9% by combination of SS and US. In solitary parathyroid adenomas group (n = 145), the sensitivity of SS and US was 93.3% and 84.7% respectively; There was no significant difference (P = 0.428) in sensitivity of SS between the parathyroid glands correctly identified and undetected in classical neck location as compared with ectopic parathyroid glands, whereas significantly (P = 0.026) influenced by the US sensitivity. CONCLUSIONS: Different sensitivity exit between SS and VS in preoperative localization in patients with pHPT undergoing parathyroidectomy. The combined use of SS and US could increase the sensitivity of localization technique. Ectopic parathyroid had no influence on the sensitivity of 99mTc-MIBI scanning, but decreased the sensitivity of ultrasonography. The size of parathyroid tumors had effects on the sensitivity of ultrasonography. Otherwise, various conditions causing SS false negative were observed. Some interfere factors should be excluded when SS negative results were encountered in clinical practice.

Diagnostic criteria for locating acquired arteriovenous fistulas with color Doppler sonography.

PURPOSE: The purpose of this prospective study was to evaluate and determine criteria for locating acquired arteriovenous fistulas using color Doppler sonography. METHODS: We performed color Doppler sonography on 12 consecutive patients with acquired arteriovenous fistulas. We evaluated the morphologic and hemodynamic changes in the involved vessels to help locate the fistulas (10 in the extremities, 1 in the neck, and 1 in the abdomen). RESULTS: In all cases, turbulent high-velocity flow spectrum and flow signals were present at the fistula sites, and arterialized waveforms from the draining veins were detected. In the 10 cases of acquired arteriovenous fistulas in the extremities, the resistance indices in the arteries proximal to the fistulas were all less than 1.00 (mean, 0.65), whereas the resistance indices in the arteries distal to the fistulas were all 1.00 or greater (mean, 1.17). In 70% of the cases, the diameter of the artery proximal to the fistula was at least 1.2 mm larger than that distal to the fistula. The fistula site was inferred by the point of maximal venous dilatation in 70% of the cases and by the focal perivascular color artifact in 82% of the cases. The fistula site was identified on gray-scale sonography and color flow imaging in 33% and 75% of the cases, respectively. CONCLUSIONS: Fistula sites can be located effectively and quickly by a combination of major and minor diagnostic criteria. The major diagnostic criteria are (1) junction of low- and high-resistance flow in the supplying artery, (2) a high-velocity arterialized waveform in the draining vein, and (3) a turbulent, high-velocity flow spectrum at the junction of the artery and the vein. The minor diagnostic criteria are (1) direct communication between the involved artery and vein, (2) significant change in the diameter of the supplying artery, (3) a focal point of venous dilatation, and (4) a focal perivascular color artifact.