Research on the destroy characteristics of PTFE/Cu composite liner to explosive reactive armor.

The jet generated through PTFE based inert material liner has the characteristics of low energy, low density, and large aspect ratio, which can effectively achieve the "penetration without explosion" of explosive reactive armor. PTFE/Cu composite material liner with various densities is prepared, to research the roles of preparation procedure and density in the destroy effect of jet on reactive armor. Through numerical simulation research, it was found that there was no reaction at all in the explosive layer penetrated by the jet generated by the sinter liner molded, while the explosive layer penetrated by the jet generated through the hot-pressing sintering and extrusion molding liner experienced local reactions on the jet impact channel, and the overall explosive layer did not undergo any reaction. Through experimental verification, it has been proven that all three types of jets have achieved "penetration without explosion" on explosive reactive armor.

A novel dilated contextual attention module for breast cancer mitosis cell detection.

Background and object: Mitotic count (MC) is a critical histological parameter for accurately assessing the degree of invasiveness in breast cancer, holding significant clinical value for cancer treatment and prognosis. However, accurately identifying mitotic cells poses a challenge due to their morphological and size diversity. Objective: We propose a novel end-to-end deep-learning method for identifying mitotic cells in breast cancer pathological images, with the aim of enhancing the performance of recognizing mitotic cells. Methods: We introduced the Dilated Cascading Network (DilCasNet) composed of detection and classification stages. To enhance the model's ability to capture distant feature dependencies in mitotic cells, we devised a novel Dilated Contextual Attention Module (DiCoA) that utilizes sparse global attention during the detection. For reclassifying mitotic cell areas localized in the detection stage, we integrate the EfficientNet-B7 and VGG16 pre-trained models (InPreMo) in the classification step. Results: Based on the canine mammary carcinoma (CMC) mitosis dataset, DilCasNet demonstrates superior overall performance compared to the benchmark model. The specific metrics of the model's performance are as follows: F1 score of 82.9%, Precision of 82.6%, and Recall of 83.2%. With the incorporation of the DiCoA attention module, the model exhibited an improvement of over 3.5% in the F1 during the detection stage. Conclusion: The DilCasNet achieved a favorable detection performance of mitotic cells in breast cancer and provides a solution for detecting mitotic cells in pathological images of other cancers.

Inter-patient ECG heartbeat classification for arrhythmia classification: a new approach of multi-layer perceptron with weight capsule and sequence-to-sequence combination.

Objective: The objective of this research is to construct a method to alleviate the problem of sample imbalance in classification, especially for arrhythmia classification. This approach can improve the performance of the model without using data enhancement. Methods: In this study, we have developed a new Multi-layer Perceptron (MLP) block and have used a Weight Capsule (WCapsule) network with MLP combined with sequence-to-sequence (Seq2Seq) network to classify arrhythmias. Our work is based on the MIT-BIH arrhythmia database, the original electrocardiogram (ECG) data is classified according to the criteria recommended by the American Association for Medical Instrumentation (AAMI). Also, our method's performance is further evaluated. Results: The proposed model is evaluated using the inter-patient paradigm. Our proposed method shows an accuracy (ACC) of 99.88% under sample imbalance. For Class N, sensitivity (SEN) is 99.79%, positive predictive value (PPV) is 99.90%, and specificity (SPEC) is 99.19%. For Class S, SEN is 97.66%, PPV is 96.14%, and SPEC is 99.85%. For Class V, SEN is 99.97%, PPV is 99.07%, and SPEC is 99.94%. For Class F, SEN is 97.94%, PPV is 98.70%, and SPEC is 99.99%. When using only half of the training sample, our method shows that the SEN of Class N and V is 0.97% and 5.27% higher than the traditional machine learning algorithm. Conclusion: The proposed method combines MLP, weight capsule network with Seq2seq network, effectively addresses the problem of sample imbalance in arrhythmia classification, and produces good performance. Our method also shows promising potential in less samples.

Study on the forming characteristics of polytetrafluoroethylene/copper jet with different preparation processes.

In this paper, PTFE/Cu composite material for liner is taken as the research object, and the preparation process and jet forming characteristics of PTFE/Cu composite liner are studied. The liners were prepared by extrusion molding, molded sintering and hot-pressing sintering. Due to different preparation processes, different microstructures of the liner can occur, including defects such as pores and microcracks, resulting in different strength and density of the liner, leading to differences in the forming characteristics of the jet. Therefore, the forming process of the jet was simulated by the finite element numerical simulation software. It was found that there was obvious radial expansion effect in the head of the jet, but with the increase of density, the radial expansion effect was weakened, and the jet velocity decreased gradually. The strength and densification of the shaped charge liner prepared by different processes were different. The densification of the molded sintering liner was generally better than that of the other two kinds of shaped charge liners. As a result, the velocity of the jet formed by the molded sintering liner is always the highest, with a numerical simulation velocity of 6642 m/s and an experimental velocity of 6534.7 m/s. The second is the jet of the hot-pressing sintering liner and the lowest velocity is the jet of the extrusion molding cover, with a numerical simulation velocity of 6482 m/s, while the experimental velocity is only 6397.9 m/s. The jet velocity measured by the pulse X-ray experiment was compared with the velocity of the numerical simulation, and the error was within 2.96%, which verifies the accuracy of the numerical simulation.

Study on the Effect of PTFE/Cu Composite Material Preparation Process on Penetration Performance.

The jet formed by the traditional metal liner has a slender shape. The diameter of the jet head is consistent with that of the tail, and the ductility is good. When it is used to penetrate the target, it has a good damage effect. The low-density jet formed by the PTFE/Cu liner, according to the different preparation processes and densities, has different degrees of radial expansion. This phenomenon may lead to the expansion of the jet head during the penetration process, resulting in a damage effect, which is different from the previous jet on the target. In this paper, the numerical simulation of PTFE/Cu liners with different preparation processes penetrating steel targets is carried out, and the effects of different preparation processes and liner density on the penetration characteristics of jets penetrating steel targets are compared and analyzed. The PTFE/Cu shaped charge liner was processed according to different preparation processes, and the jet penetration steel target experiment was carried out, so as to verify and analyze the numerical simulation results.

Automated inter-patient arrhythmia classification with dual attention neural network.

BACKGROUND AND OBJECTIVES: Arrhythmia classification based on electrocardiograms (ECG) can enhance clinical diagnostic efficiency. However, due to the significant differences in the number of different categories of heartbeats, the performance of classes with fewer samples in arrhythmia classification have not met expectations under the inter-patient paradigm. This paper aims to mitigate the adverse effects of category imbalance and improve arrhythmia classification performance. METHODS: We constructed a novel dual attention hybrid network (DA-Net) for arrhythmia classification under sample imbalance, based on modified convolutional networks with channel attention (MCC-Net) and sequence-to-sequence network with global attention (Seq2Seq). The refined local features of the input heartbeat are first extracted by MCC-Net and then sent to Seq2Seq for further feature fusion. By applying local and global attention in the feature extraction and fusion parts, respectively, the method fully fuses low-level feature details and high-level context information and enhances the ability to extract discriminative features. RESULTS: Based on the MIT-BIH arrhythmia database, under the inter-patient paradigm without any data augmentation methods, the proposed method achieved 99.98% accuracy (ACC) for five categories. The various performance indicators are as follows: Class N: sensitivity (SEN) = 99.96%, specificity (SPEC) = 99.93%, positive predictive value (PPV) = 99.99%; Class S: SEN = 99.67%, SPEC = 99.98%, PPV = 99.56%; Class V: SEN = 100%, SPEC = 99.99%, PPV = 99.91%; Class F: SEN = 100%, PPV = 99.98%, SPEC = 97.17%. In further experiments simulating extreme cases, the model still achieved ACC of 99.54% and 98.91% in the three-category and five-category categories when the training sample size was much smaller than the test sample. CONCLUSIONS: Without any data augmentation methods, the proposed model not only alleviates the negative impact of class imbalance and achieves excellent performance in all categories but also provides a new approach for dealing with class imbalance in arrhythmia classification. Additionally, our method demonstrates potential in conditions with fewer samples.

The therapeutic perspective of cold atmospheric plasma in periodontal disease.

OBJECTIVES: Periodontal disease (PD) is one of the most common infectious diseases with complex inflammatory conditions, having irreversibly destructive impacts on the periodontal supporting tissues. The application of cold atmospheric plasma (CAP) is a promising adjuvant therapy modality for PD. However, the mechanism of CAP in PD treatment is still poorly understood. The review motivates to outline the latest researches concerning the applications of CAP in PD treatment. METHODS: We searched CAP-related literature through utilizing the well-established databases of Pubmed, Scopus and Web of Science according to the following keywords related to periodontal disease (periodontal, gingival, gingivitis, gingiva, periodontium, periodontitis). RESULTS: A total of 18 concerning original studies were found. These studies could be classified according to three pathophysiological perspectives of PD. The therapeutic mechanisms of CAP may be attributed to the oxidative stress-related cell death of periodontal bacteria, the suppression of periodontal inflammation and pro-inflammatory cytokine secretion, as well as the acceleration of periodontal soft tissue wound healing and hard tissue reconstruction. CONCLUSIONS: Cold atmospheric plasma has potential therapeutic effects on PD through three mechanisms: antimicrobial effect, inflammation attenuation, and tissue remodeling. This review hopefully provides a comprehensive perspective into the potential of CAP in PD therapy.

Effects of Atmospheric Pressure Plasma in the Treatment of Experimental Periodontitis in Beagle Dogs.

OBJECTIVE: The specific objective of this study was to evaluate the effects of atmospheric pressure plasma (APP) in the treatment of experimental periodontitis in Beagle dogs. METHODS: The APP jet was diagnosed using optical emission spectroscopy and laser-induced fluorescence spectroscopy. Six Beagles received stainless steel ligatures to establish experimental periodontitis model. The teeth in the control group were subjected to conventional root surface debridement (RSD) and chlorhexidine irrigation. The APP group also started with RSD and was then subjected to plasma irradiation. Clinical analyses including plaque index, modified sulcus bleeding index, pocket depth and attachment loss (AL), as well as cone-beam computed tomography (CBCT) analysis, were performed at baseline, 4th week, 8th week and 12th week after treatment. RESULTS: The results showed that typical reactive oxygen and nitrogen species were found in the full spectrum and the gas temperature of APP was close to room temperature. The highest concentrations of hydroxide and oxygen were obtained at 5 mm away from the nozzle. In both groups, all values in clinical examinations were significantly lower (P<0.05) at 12th week after treatment than those at baseline. At the 12th week, the AL in clinical examinations and the bone loss in CBCT images in the APP group were significantly lower than those in the control group (P<0.05). The hematoxylin-eosin staining showed more renascent alveolar bone in the APP group than in the control group. CONCLUSION: These findings suggested that APP has profound potential for use as an adjunct approach for periodontitis treatment.

Mechanical Properties and a Constitutive Model of 3D-Printed Copper Powder-Filled PLA Material.

Three-dimensional printing is becoming increasingly popular because of its extensive applicability. However, printing materials remain limited. To determine the mechanical properties of polylactic acid (PLA) and copper powder-filled polylactic acid (PLA-Cu) materials subjected to static and dynamic loading, stress-strain curves were obtained under the conditions of different strain rates using a universal material testing machine and a separated Hopkinson pressure bar experimental device. Scanning electron microscopy (SEM) was used to analyze the micro-morphology of the quasi-static compression fracture and dynamic impact sections. The results revealed that the yield stress and elastic modulus of the two materials increased with increasing strain rate. When the strain rate reached a critical point of 0.033 s-1, the rate of crack propagation in the PLA samples increased, resulting in the material undergoing a change from ductile to brittle. The strength of the material subjected to dynamic loading was significantly higher than that subjected to quasi-static loading. The SEM image of the PLA-Cu material revealed that copper powder was evenly distributed throughout the 3D-printed sample and that stress initially began to concentrate at the defect site corresponding to the interface between the copper powder and PLA matrix; this resulted in comparatively lower toughness. This finding was consistent with the photographs captured via high-speed photography, which confirmed that the destruction of the specimen was accompanied by an explosive crushing process. Additionally, a Zhu-Wang-Tang constitutive model was used to fit the experimental results and establish a viscoelastic constitutive model of the material. By comparing the dynamic stress-strain curve to the theoretically predicted curve, we found that the established constitutive model could predict the mechanical properties of the PLA-Cu material with reasonable accuracy when the strain was below 7%.

Desmoplastic melanoma involving head and fingers: diagnostic challenges and clinical characteristics.

Desmoplastic melanoma (DM) is considered a variant of melanoma, characterized by a paucicellular proliferation of malignant spindled melanocytes with an abundant collagenous or "desmoplastic" stroma and an intense inflammatory response. As DMs lack pigmentation, their appearances vary and can mimic many benign and malignant conditions, thus presenting a diagnostic challenge. Here, we are presenting one case involving the head and two cases involving fingers. One of our cases distinctively invade nerves and bones. We reviewed the literature for many similar cases. Most cases presented positive staining of S-100 and negative or focal positive staining of Melan-A and Melanoma. So far, the mechanisms of the rare entity have not been clearly recognized. Early accurate diagnosis and complete excision of this tumor is necessary. Some researchers considered BRAF-targeted therapy may be limited to a small number of patients with DM. Advanced DM may respond well to anti-PD-1 monotherapy.

Double hydrophilic block copolymers PEO-b-PGA: synthesis, application as potential drug carrier and drug release via pH-sensitive linkage.

A new type of double hydrophilic block copolymer, poly(ethylene oxide) (PEO)-block-poly(glycerol monoacrylate) (PGA) have been synthesized via atom transfer radical polymerization of solketal acrylate (SA) using PEO-Br as macro-initiator, and subsequent hydrolysis of the acetal-protecting group in 1N HCl solution in THF. The polymerization is of a "living" nature and the copolymers with controlled molecular weight and narrow polydispersity (M(w)/M(n) = 1.01-1.03) were obtained. The complete hydrolysis of the acetal-protecting group was verified by IR and NMR spectroscopies. A hydrophobic fluorescent compound, 1-pyrenecarboxaldehyde, was used as a model drug, which was covalently bound to the PEO-b-PGA block copolymer via a pH-sensitive acetal linkage. The kinetics of the pyrene release was studied in THF/aqueous buffers at pH 5.0 (close to pH in endosomes) and 7.4 (pH of blood plasma) by fluorescent spectroscopy. The pyrene was released much faster at pH 5.0 than that at pH 7.4. The micelle behavior in solutions at pH 5.0 and 7.4 was studied by dynamic light scattering. All results show that this double hydrophilic PEO-b-PGA is a promising candidate for potential application as drug carrier for those carbonyl-containing hydrophobic drugs.