Fuzzy Superpixels based Semi-supervised Similarity-constrained CNN for PolSAR Image Classification

Recently, deep learning has been highly successful in image classification. Labeling the PolSAR data, however, is time-consuming and laborious and in response semi-supervised deep learning has been increasingly investigated in PolSAR image classification. Semi-supervised deep learning methods for PolSAR image classification can be broadly divided into two categories, namely pixels-based methods and superpixels-based methods. Pixels-based semi-supervised methods are liable to be affected by speckle noises and have a relatively high computational complexity. Superpixels-based methods focus on the superpixels and ignore tiny detail-preserving represented by pixels. In this paper, a Fuzzy superpixels based Semi-supervised Similarity-constrained CNN (FS-SCNN) is proposed. To reduce the effect of speckle noises and preserve the details, FS-SCNN uses a fuzzy superpixels algorithm to segment an image into two parts, superpixels and undetermined pixels. Moreover, the fuzzy superpixels algorithm can also reduce the number of mixed superpixels and improve classification performance. To exploit unlabeled data effectively, we also propose a Similarity-constrained Convolutional Neural Network (SCNN) model to assign pseudo labels to unlabeled data. The final training set consists of the initial labeled data and these pseudo labeled data. Three PolSAR images are used to demonstrate the excellent classification performance of the FS-SCNN method with data of limited labels

Shell Analysis and Optimisation of a Pure Electric Vehicle Power Train Based on Multiple Software

Motor end cover mounting fracture is a problem recently encountered by novel pure electric vehicles. Regarding the study of the traditional vehicle engine mount bracket and on the basis of the methods of design and optimisation available, we have analysed and optimised the pure electric vehicle end cover mount system. Multi-body dynamic software and finite element software have been combined. First, we highlight the motor end cover mount bracket fracture engineering problems, analyse the factors that may produce fracture, and propose solutions. By using CATIA software to establish a 3D model of the power train mount system, we imported it into ADAMS multi-body dynamic software, conducted 26 condition analysis, obtained five ultimate load conditions, and laid the foundations for subsequent analysis. Next, a mount and shell system was established by the ANSYS finite element method, and modal, strength, and fatigue analyses were performed on the end cover mount. We found that the reason for fracture lies in the intensity of the end cover mount joint, which leads to the safety factor too small and the fatigue life not being up to standard. The main goal was to increase the strength of the cover mount junction, stiffness, safety coefficient, and fatigue life. With this aim, a topology optimisation was conducted to improve the motor end cover. A 3D prototype was designed accordingly. Finally, stiffness, strength, modal, and fatigue were simulated. Our simulation results were as follows. The motor end cover suspension stiffness increases by 20%, the modal frequency increases by 2.3%, the quality increases by 3%, the biggest deformation decreases by 52%, the maximum stress decreases by 28%, the minimum safety factor increases by 40%, and life expectancy increases 50-fold. The results from sample and vehicle tests highlight that the component fracture problem has been successfully solved and the fatigue life dramatically improved. Document type: Articl

Nonlinear sub-cyclotron resonance as a formation mechanism for gaps in banded chorus

An interesting characteristic of magnetospheric chorus is the presence of a frequency gap at $\omega \simeq 0.5\Omega_e$, where $\Omega_e$ is the electron cyclotron angular frequency. Recent chorus observations sometimes show additional gaps near $0.3\Omega_e$ and $0.6\Omega_e$. Here we present a novel nonlinear mechanism for the formation of these gaps using Hamiltonian theory and test-particle simulations in a homogeneous, magnetized, collisionless plasma. We find that an oblique whistler wave with frequency at a fraction of the electron cyclotron frequency can resonate with electrons, leading to effective energy exchange between the wave and particles

Application of Machine Learning in Microbiology

Microorganisms are ubiquitous and closely related to people’s daily lives. Since they were first discovered in the 19th century, researchers have shown great interest in microorganisms. People studied microorganisms through cultivation, but this method is expensive and time consuming. However, the cultivation method cannot keep a pace with the development of high-throughput sequencing technology. To deal with this problem, machine learning (ML) methods have been widely applied to the field of microbiology. Literature reviews have shown that ML can be used in many aspects of microbiology research, especially classification problems, and for exploring the interaction between microorganisms and the surrounding environment. In this study, we summarize the application of ML in microbiology

Arcuate Nucleus Orexin-A Signaling Alleviates Cisplatin-Induced Nausea and Vomiting Through the Paraventricular Nucleus of the Hypothalamus in Rats

The most common side effects of cisplatin chemotherapy are nausea and vomiting, and the overwhelming majority of research studies on the mechanism of cisplatin-induced nausea have been focused on the “vomiting center.” As a modulatory center of gastric motility, the roles of the hypothalamus in nausea and vomiting remain unclear. In the present study, we investigated the effects of exogenous orexin-A injected into the arcuate nucleus (ARC) on cisplatin-induced nausea and vomiting, and the possible underlying mechanism. Kaolin intake was calculated daily in cisplatin-treated and saline-treated rats. Gastric motility recording, injections into the ARC, and lesions of the paraventricular nucleus (PVN) were used to study the effects of orexin-A and the hypothalamic nucleus on disorders of gastrointestinal function in cisplatin-treated rats. The pathway from the ARC to the PVN was observed through Fluoro-Gold retrograde tracing. Furthermore, an NPY Y1 receptor antagonist was administered to explore the possible mechanisms involved in the effects of orexin-A in the ARC. We illustrated that exogenous orexin-A injected into the ARC reduced kaolin intake and promoted gastric motility in cisplatin-treated rats, and these effects could have been blocked by an ipsilateral PVN lesion or co-injected antagonist of orexin-A-SB334867. Additional results showed that orexin-A-activated neurons in the ARC communicated directly with other neurons in the PVN that express neuropeptide Y (NPY). Furthermore, activation of the downstream NPY pathway was required for the observed effects of orexin in the ARC on cisplatin-induced nausea and vomiting. These findings reveal a novel neurobiological circuit from the ARC to the PVN that might provide a potential target for the prevention and treatment of cisplatin-induced nausea and vomiting

Analysis of Volatile Components in the Molecular Distillation Fractions of Osmanthus fragrans Absolute by GC-MS Combined with Chemometrics Methods

This study aimed to investigate the differences in volatile composition and aroma of different fractions of Osmanthus fragrans absolute purified by molecular distillation. Gas chromatography-mass spectrometry (GC-MS) combined with orthogonal partial least-squares discrimination analysis (OPLS-DA), P-value, variable importance in the projection (VIP), and relative odor activity value (ROAV) were used for analysis. The light, heavy, and residue fractions of Osmanthus fragrans absolute were analyzed. A total of 73 volatile components belonging to 8 major categories were detected in the three fractions, including 22 alcohols, 5 aldehydes, 10 acids, 3 phenols, 5 ketones, 17 esters, 5 alkanes, and 6 olefins. Alcohols were the main contributors to the volatile components in each fraction, and the types and relative contents of volatile components significantly differed among the fractions (P1) of the three fractions, the key aroma contributing components (ROAV>1) of the 14 light fractions, 9 recombinant fractions, and 11 residue fractions were analyzed by the aroma profile analysis. Light fractions exhibited more intense floral, sweet, and pine woody aromas compared to recombinant and residue fractions. The light fractions had the highest types and relative contents of volatile components and showcased the most intense Osmanthus fragrans floral flavor. This study provided a theoretical basis for the comprehensive utilization of different fractions of Osmanthus fragrans absolute through molecular distillation using GC-MS combined with chemometrics methods

Towards Al3+-Induced Manganese-Containing Superoxide Dismutase Inactivation and Conformational Changes: An Integrating Study with Docking Simulations

Superoxide dismutase (SOD, EC 1.15.1.1) plays an important antioxidant defense role in skins exposed to oxygen. We studied the inhibitory effects of Al3+ on the activity and conformation of manganese-containing SOD (Mn-SOD). Mn-SOD was significantly inactivated by Al3+ in a dose-dependent manner. The kinetic studies showed that Al3+ inactivated Mn-SOD follows the first-order reaction. Al3+ increased the degree of secondary structure of Mn-SOD and also disrupted the tertiary structure of Mn-SOD, which directly resulted in enzyme inactivation. We further simulated the docking between Mn-SOD and Al3+ (binding energy for Dock 6.3: −14.07 kcal/mol) and suggested that ASP152 and GLU157 residues were predicted to interact with Al3+, which are not located in the Mn-contained active site. Our results provide insight into the inactivation of Mn-SOD during unfolding in the presence of Al3+ and allow us to describe a ligand binding via inhibition kinetics combined with the computational prediction

Factors associated with patients’ healthcare-seeking behavior and related clinical outcomes under China’s hierarchical healthcare delivery system

IntroductionThe hierarchical healthcare delivery system is an important measure to improve the allocation of medical resources and promote equitable distribution of basic medical and health services. It is one of the key factors in the success or failure of China’s medical reform. This study aims to analyze the factors influencing patients’ healthcare-seeking behaviors, including socioeconomic and clinical outcomes, under China’s hierarchical healthcare delivery system, and to provide potential solutions.MethodsPatients receiving outpatient treatment in the past 14 days and inpatient care in the past 1 year were investigated. The multivariate logistic regression was used to analyze the influencing factors of patient’s medical treatment behavior selection, and to compare whether the clinical outcomes of primary medical institutions and grade A hospitals are the same.ResultsNine thousand and ninety-eight person-times were included in the study. Of these, 4,538 patients were outpatients, 68.27% of patients were treated in primary medical institutions; 4,560 patients were hospitalized, 58.53% chose to be hospitalized in grade A hospitals. Provinces and cities, urban and rural areas, occupation, education level, medical insurance type, income, whether there are comorbid diseases, and doctors’ medical behavior are the factors affecting the choice of medical treatment behavior. Patients who choose primary medical institutions and grade A hospitals have different control levels and control rate for the blood pressure, blood lipids, blood glucose.ConclusionUnder the hierarchical diagnosis and treatment system, the patients’ choice of hospital is mainly affected by their level of education, medical insurance types, and the inpatients are also affected by whether there are comorbid conditions. Clinical outcomes of choosing different levels of hospitals were different

Five New Amicoumacins Isolated from a Marine-Derived Bacterium Bacillus subtilis

Four novel amicoumacins, namely lipoamicoumacins A–D (1–4), and one new bacilosarcin analog (5) were isolated from culture broth of a marine-derived bacterium Bacillus subtilis, together with six known amicoumacins. Their structures were elucidated on the basis of extensive spectroscopic (2D NNR, IR, CD and MS) analysis and in comparison with data in literature