Failure Behaviours of Steel Projectiles with Localised Melting Against Armour Plates

The surface remelting technology of high energy beam can locally weaken the case for controlled fragmentation, which may affect the survivability of the impacting projectiles. Failure behaviours of steel projectiles with melted layers grid normally perforating armour plates was investigated. The results reveal that shear fracture mainly occurs in the nose region of projectiles due to high loading, and the melting zone of projectiles can keep integrity with no damage, which means the survivability of projectile can be assured. Furthermore, an analytical model was proposed to the structural analysis of projectile, which is in accordance with the test results

Multi-label learning by Image-to-Class distance for scene classification and image annotation

In multi-label learning, an image containing multiple objects can be assigned to multiple labels, which makes it more chal-lenging than traditional multi-class classification task where an image is assigned to only one label. In this paper, we propose a multi-label learning framework based on Image-to-Class (I2C) distance, which is recently shown useful for image classification. We adjust this I2C distance to cater for the multi-label problem by learning a weight attached to each local feature patch and formulating it into a large margin optimization problem. For each image, we constrain its weighted I2C distance to the relevant class to be much less than its distance to other irrelevant class, by the use of a margin in the optimization problem. Label ranks are generated under this learned I2C distance framework for a query image. Thereafter, we employ the label correlation in-formation to split the label rank for predicting the label(s) of this query image. The proposed method is evaluated in the applications of scene classification and automatic image annotation using both the natural scene dataset and Mi-crosoft Research Cambridge (MSRC) dataset. Experiment results show better performance of our method compared to previous multi-label learning algorithms

Fracture Properties of Concrete in Dry Environments with Different Curing Temperatures

This paper investigated the fracture properties of concrete in dry environments with different curing temperatures (5, 20, 40, and 60 °C). For each curing condition, the key fracture parameters of concrete were tested using wedge splitting specimens at five different ages (3, 7, 14, 28, and 60 d). The results show that in dry environments, the effective fracture toughness and fracture energy of concrete exposed to elevated temperatures increased at a relatively high growth rate at an early age. Nevertheless, the growth speed of effective fracture toughness and fracture energy decreased more quickly at elevated temperatures in the later stages. As a result, the concrete cured at higher temperature exhibited lower ultimate values of fracture parameters, and vice-versa. Namely, a temperature crossover effect was found in the effective fracture toughness and fracture energy of concrete under dry environments. Considering the early growth rate and ultimate values of fracture parameters, the optimum temperature suitable for concrete fracture properties development under dry condition was around 40 °C

High-Frequency Signal Injection-Based Sensorless Control for Dual-Armature Flux-Switching Permanent Magnet Machine

The new topology of the dual-armature flux-switching permanent magnet machine (DA-FSPM) leads to new characteristics and issues in the control of the machine, of which the mutual inductance of the two sets of armature windings is the most important one. This paper proposes a novel position–sensorless control method based on high-frequency injection (HFI) for DA-FSPM. The high-frequency model of the machine is derived, and the theory of the position estimation method is proposed. Different from the conventional HFI-based position estimation method, the proposed method utilizes the mutual inductance of the DA-FSPM rather than the machine saliency. Meanwhile, because the extracted position information based on the mutual inductance is more obvious, the proposed method also has better steady and dynamic performance. Then, the position observer based on the phase lock loop and the initial position detection method for the DA-FSPM is proposed. The experiments are executed on a DA-FSPM prototype with three-phase stator windings and five-phase rotor windings to prove the effectiveness and superiority of the proposed method

Fault Diagnosis of a Switch Machine to Prevent High-Speed Railway Accidents Combining Bi-Directional Long Short-Term Memory with the Multiple Learning Classification Based on Associations Model

The fault diagnosis of a switch machine is vital for high-speed railway operations because switch machines play an important role in the safe operation of high-speed railways, which often have faults because of their complicated working conditions. To improve the accuracy of turnout fault diagnosis for high-speed railways and prevent accidents from occurring, a combination of bi-directional long short-term memory (BiLSTM) with the multiple learning classification based on associations (MLCBA) model using the operation and maintenance text data of switch machines is proposed in this research. Due to the small probability of faults for a switch machine, it is difficult to form a diagnosis with the small amount of sample data, and more fault text features can be extracted with feedforward in a BiLSTM model. Then, the high-quality rules of the text data can be acquired by replacing the SoftMax classification with MLCBA in the output of the BiLSTM model. In this way, the identification of switch machine faults in a high-speed railway can be realized, and the experimental results show that the Accuracy and Recall of the fault diagnosis can reach 95.66% and 96.29%, respectively, as shown in the analysis of the ZYJ7 turnout fault text data of a Chinese railway bureau from five recent years. Therefore, the combined BiLSTM and MLCBA model can not only realize the accurate diagnosis of small-probability turnout faults but can also prevent high-speed railway accidents from occurring and ensure the safe operation of high-speed railways

The expression and clinical prognostic value of protein phosphatase 1 catalytic subunit beta in pancreatic cancer

Pancreatic cancer (PAAD) is a common malignancy with a poor survival rate. The identification of novel biomarkers could improve clinical outcomes for patients with PAAD. Here we evaluated the expression and clinical significance of PPP1CB in PAAD. PPP1CB expression was higher in PAAD tissue than in matched paracancerous tissue (P < 0.05). We predicted a network of regulatory targets and protein interaction partners of PPP1CB, and identified a PPI network consisting of 39 node genes. The expression of 33 node genes was higher in PAAD tissue than in matching paracancerous tissue. High expression of the node genes ACTN4, ANLN, CLTB, IQGAP1, SPTAN1, and TMOD3 was associated with improved overall survival (P < 0.05). SiRNA knockdown of PPP1CB significantly reduced the migration and invasion of PAAD cells. A PPP1CB immunohistochemical staining was performed using a tissue microarray (TMA), consisting of tumor samples collected from 91 patients with PAAD (88 of which contained matched paracancerous tissues). The expression of PPP1CB in PAAD was significantly higher than in the matched paracancerous tissue, (P = 0.016). High PPP1CB expression was associated with patient sex (P = 0.048), alcohol use (P = 0.039), CEA (P= 0.038), N stage (P = 0.001), and invasion of nerve (P = 0.036). Furthermore, high PPP1CB expression was associated with significantly poorer overall survival (P = 0.022). Our data demonstrate that PPP1CB is associated with the migration and invasion of PAAD cells, and may be useful as an independent prognostic indicator for clinical outcome in patients with PAAD

Efficacy of high-frequency repetitive transcranial magnetic stimulation in a family with spinocerebellar ataxia type 3: A case report

Introduction: Spinocerebellar ataxia type 3 (SCA3) is a common autosomal dominant hereditary ataxia, which is caused by a cytosine-adenine-guanine (CAG) repeat expansion on the causative gene ATXN3, usually with lower extremity ataxia as the first symptom, and effective treatment is scarce. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique that regulates the cerebellum and the neural network connected to it. Methods: Herein, we report familial cases of SCA3 in two nephews and their aunt, each of whom was treated with high-frequency (5 Hz) rTMS. The rTMS treatment lasted 2 weeks, once daily for 5 consecutive days a week, about 20 minutes each session. The Scale for the Assessment and Rating of Ataxia (SARA), the International Cooperative Ataxia Rating Scale (ICARS), and proton magnetic resonance spectroscopy (1H-MRS) examination were evaluated before and after rTMS treatment. Results: We found that the ICARS scores improved significantly (p = 0.04), and the NAA/Cr values were elevated in vermis and both cerebellar hemispheres after rTMS treatment. Conclusion: Our study suggested that high-frequency rTMS therapy can contribute to the improvement of cerebellar NAA/Cr value of SCA3 patients, and improve posture and gait as well as limb kinetic function in SCA3 patients

Morphology and molecular study of three new Cordycipitoid fungi and its related species collected from Jilin Province, northeast China

Cordyceps species are notable medicinal fungi in China, which are pathogenic on insects and exhibit high biodiversity in tropical and subtropical regions. Recently, three new Cordyceps species, Cordyceps changchunensis and Cordyceps jingyuetanensis growing on pupae of Lepidoptera and Cordyceps changbaiensis growing on larvae of Lepidoptera, were found in Jilin Province, China and are described, based on morphological and ecological characteristics. These three new species are similar to the Cordyceps militaris group, but are distinctly distinguishable from the known species. Cordyceps changchunensis, characterised by its small and light yellow to orange stromata which is occasionally forked, covered with white mycelium at the base of stipe, globose to ovoid perithecia, is macroscopically similar to Cordyceps militaris. Cordyceps changbaiensis is clearly discriminated from other Cordyceps species by its white to orange and branched stromata, clavate to cylindrical fertile apical portion, immersed and globose to ovoid perithecia. Moreover, unbranched, clavate and orange to light red stromata, almond-shaped to ovoid and immersed perithecia separate Cordyceps jingyuetanensis from other Cordyceps species. nrITS, nrLSU and EF-1α sequences were undertaken and phylogenetic trees, based on Maximum Likelihood and Bayesian Inference analysis showed that the three new species clustered with Cordyceps militaris, but formed individual clades, as well as confirmed the results of our morphological study