Sliding Mode Observer-Based Stuck Fault and Partial Loss-of-Effectiveness (PLOE) Fault Detection of Hypersonic Flight Vehicle

In order to improve the safety and reliability of the hypersonic flight vehicle, a sliding mode observer-based fault detection scheme is applied in this paper to handle the actuator fault detection issue, including stuck fault detection and PLOE fault detection. A dynamic linear model with uncertainty is first derived from the original nonlinear hypersonic flight vehicle model by using Taylor’s linearization approach at the equilibrium point. Secondly, the actuator fault model, reflecting stuck faults and PLOE faults, is constructed. Then, a sliding mode-based fault detection observer, considering system decomposition, is developed based on the linearized hypersonic flight vehicle model. At last, the designed sliding mode observer is applied to the original nonlinear hypersonic flight vehicle for single-input, single-style actuator fault detection. The simulation results show that stuck faults and big proportion PLOE faults can be timely and accurately detected at the fault time, and the stuck actuator fault from input 3 can cause a deadly impact to the hypersonic flight vehicle, which deserves much more attention than the actuator faults from the other three inputs. Meanwhile, the detection of a small proportion of PLOE faults encounters some difficulties and needs special attention and further investigation

Hibernoma in the clavicular fossa: A case report and literature review

A hibernoma is a benign soft tissue tumor consisting of brown adipose tissue. The tumors are mostly located in the thigh, back, and shoulder region. They are rarely found in the supraclavicular fossa. We report a 39-year-old woman who presented with a painless, slow-growing mass on the left supraclavicular fossa for nearly 15 years. Magnetic resonance imaging (MRI) showed an inhomogeneous round mass with a slightly hyperintense signal on fat-suppression T2-weighted imaging that compressed the adjacent tissues and subclavian vessels. Computed tomography angiography indicated a rich blood flow signal. Postoperative histology confirmed the diagnosis of a hibernating tumor. Although comprehensive imaging is important in the determination of tumor for the size, location, and nature, computed tomography angiography provides clear indication of the vascularity of the tumor, which provides vital clinicopathologic data for surgeons

Sliding Mode Observer-Based Stuck Fault and Partial Loss-of-Effectiveness (PLOE) Fault Detection of Hypersonic Flight Vehicle

In order to improve the safety and reliability of the hypersonic flight vehicle, a sliding mode observer-based fault detection scheme is applied in this paper to handle the actuator fault detection issue, including stuck fault detection and PLOE fault detection. A dynamic linear model with uncertainty is first derived from the original nonlinear hypersonic flight vehicle model by using Taylor’s linearization approach at the equilibrium point. Secondly, the actuator fault model, reflecting stuck faults and PLOE faults, is constructed. Then, a sliding mode-based fault detection observer, considering system decomposition, is developed based on the linearized hypersonic flight vehicle model. At last, the designed sliding mode observer is applied to the original nonlinear hypersonic flight vehicle for single-input, single-style actuator fault detection. The simulation results show that stuck faults and big proportion PLOE faults can be timely and accurately detected at the fault time, and the stuck actuator fault from input 3 can cause a deadly impact to the hypersonic flight vehicle, which deserves much more attention than the actuator faults from the other three inputs. Meanwhile, the detection of a small proportion of PLOE faults encounters some difficulties and needs special attention and further investigation

Data governance and Gensini score automatic calculation for coronary angiography with deep-learning-based natural language extraction

With the widespread adoption of electronic health records, the amount of stored medical data has been increasing. Clinical data, often in the form of semi-structured or unstructured electronic medical records (EMRs), contains rich patient information. However, due to the use of natural language by physicians when composing these records, the effectiveness of traditional methods such as dictionaries, rule matching, and machine learning in the extraction of information from these unstructured texts falls short of clinical standards. In this paper, a novel deep-learning-based natural language extraction method is proposed to overcome current shortcomings in data governance and Gensini score automatic calculation in coronary angiography. A pre-trained model called bidirectional encoder representation from transformers (BERT) with strong text feature representation capabilities is employed as the feature representation layer. It is combined with bidirectional long short-term memory (BiLSTM) and conditional random field (CRF) models to extract both global and local features from the text. The study included an evaluation of the model on a dataset from a hospital in China and it was compared with another model to validate its practical advantages. Hence, the BiLSTM-CRF model was employed to automatically extract relevant coronary angiogram information from EMR texts. The achieved F1 score was 91.19, which is approximately 0.87 higher than the BERT-BiLSTM-CRF model

Stability analysis and control technology of gob-side entry retaining with double roadways by filling with high-water material in gently inclined coal seam

To ameliorate the defects of insufficient support resistance of traditional roadside filling bodies for gob-side entry retaining (GER), overcome the inability to adapt to the deformation of surrounding rock, and isolate the goaf effectively, a new type of high-water material as a roadside filling body for GER technology with double roadways was proposed. The instability analysis and control technology of GER with double roadways by filling high-water material into a gently inclined coal seam were studied. The basic mechanical properties of the new high-water material were investigated through laboratory experiments, and their main advantages were identified. The reasonable width of the roadside filling wall of a high-water material was obtained by combining ground pressure observation and theoretical calculations. The distribution characteristics of the stress and plastic zone of surrounding rock of GER after being stabilized by the disturbance of the working face were studied using numerical simulations, and the failure range of GER by filling with high-water material was revealed. Based on this, a coupling control technology of anchor cables and bolts + single props + metal mesh + anchor bolts is proposed. Through the coupling methods of arranging borehole peeping and observing the convergences of surrounding rock, the results demonstrate that GER with double roadways by filling with a 1.8-m-wide high-water material has a good control effect. The above research will play an active role in promoting the application of high-water materials in GER roadside filling.Applied Science, Faculty ofNon UBCCivil Engineering, Department ofReviewedFacultyResearche

Fenlong-Ridging Promotes Microbial Activity in Sugarcane: A Soil and Root Metabarcoding Survey

Fenlong-ridging (FL) is a recently proposed conservation tillage technology which has dramatic differences to traditional ones. Previous studies have demonstrated in many crops that FL has yield-increasing effects without additional inputs. However, little is known about the role that microbes play in mediating the growth-promoting effects of FL, which restricts its further application and improvement. Here, we characterized variation in the soil and root microbial diversity of sugarcane (GT44) under FL and traditional turn-over plough tillage (CK) by conducting 16S rRNA and ITS metabarcoding surveys. We also measured several phenotypic traits to determine sugarcane yields and analyzed the chemical properties of soil. We found that: (i) plant height (PH) and total biomass weight (TW) of sugarcane plants were 9.1% and 21.7% greater under FL than those under CK, indicating\increased biomass yield of the sugarcane in FL operation; (ii) contents of organic matter, total nitrogen, available phosphorus, and available potassium were lower in soil under FL than those under CK, which indicates the utilization of soil nutrients was greater in FL soil; (iii) FL promoted the activity of endophytic microbes in the roots, and these diverse microbial taxa might have an effect on sugarcane yield and soil chemical properties; and (iv) Sphingomonas, Rhizobium, and Paraburkholderia and Talaromyces, Didymella, and Fusarium were the top three most abundant genera of bacteria and fungi, respectively, in soil and root samples. In addition, strains from Rhizobium and Talaromyces were isolated to verify the results of the metabarcoding survey. Overall, our study provides new insights into the role of microbes in mediating the growth-promoting effects of FL. These findings could be used to further improve applications of this novel conservation tillage technology

Segmentation of human aorta using 3D nnU-net-oriented deep learning

Computed tomography angiography (CTA) has become the main imaging technique for cardiovascular diseases. Before performing the transcatheter aortic valve intervention operation, segmenting images of the aortic sinus and nearby cardiovascular tissue from enhanced images of the human heart is essential for auxiliary diagnosis and guiding doctors to make treatment plans. This paper proposes a nnU-Net (no-new-Net) framework based on deep learning (DL) methods to segment the aorta and the heart tissue near the aortic valve in cardiac CTA images, and verifies its accuracy and effectiveness. A total of 130 sets of cardiac CTA image data (88 training sets, 22 validation sets, and 20 test sets) of different subjects have been used for the study. The advantage of the nnU-Net model is that it can automatically perform preprocessing and data augmentation according to the input image data, can dynamically adjust the network structure and parameter configuration, and has a high model generalization ability. Experimental results show that the DL method based on nnU-Net can accurately and effectively complete the segmentation task of cardiac aorta and cardiac tissue near the root on the cardiac CTA dataset, and achieves an average Dice similarity coefficient of 0.9698 ± 0.0081. The actual inference segmentation effect basically meets the preoperative needs of the clinic. Using the DL method based on the nnU-Net model solves the problems of low accuracy in threshold segmentation, bad segmentation of organs with fuzzy edges, and poor adaptability to different patients' cardiac CTA images. nnU-Net will become an excellent DL technology in cardiac CTA image segmentation tasks.National Research Foundation (NRF)Submitted/Accepted versionThe paper was supported by the project of Shenzhen science and technology innovation committee (Grant Nos. JCYJ20190809145407809 and KJ2021C019). This research study is also supported by the National Research Foundation, Singapore under its Strategic Capability Research Centers Funding Initiative

High-Throughput Phenotyping of Cross-Sectional Morphology to Assess Stalk Mechanical Properties in Sorghum

Lodging is one of the major constraints in attaining high yield in crop production. Major factors associated with stalk lodging involve morphological traits and anatomical features along with the chemical composition of the stem. However, little relevant research has been carried out in sorghum, particularly on the anatomical aspects. In this study, with a high-throughput procedure newly developed by our research group, the nine parameters related to stem regions and vascular bundles were generated in 58 sorghum germplasm accessions grown in two successive seasons. Correlation analysis and principal component analysis were conducted to investigate the relationship between anatomical aspects and stalk mechanical traits (breaking force, stalk strength and lodging index). It was found that most vascular parameters were positively associated with breaking force and lodging index with the correlation coefficient r varying from −0.46 to 0.64, whereas stalk strength was only associated with rind area with the r = 0.38. The germplasm resources can be divided into two contrasting categories (classes I with 23 accessions and II with 30 accessions). Compared to class II, the class I was characterized by a larger number (+40.7%) and bigger vascular bundle (+30%), thicker stem (+19.6%) and thicker rind (+36.0%) but shorter internode (plant) (−91.0%). This study provides the methodology and information for the studies of the stem anatomical parameters in crops and facilitates the selective breeding of sorghum