Palm Print Edge Extraction Using Fractional Differential Algorithm

Algorithm based on fractional difference was used for the edge extraction of thenar palm print image. Based on fractional order difference function which was deduced from classical fractional differential G-L definition, three filter templates were constructed to extract thenar palm print edge. The experiment results showed that this algorithm can reduce noise and detect rich edge details and has higher SNR than traditional methods

Pade Method for Construction of Numerical Algorithms for Fractional Initial Value Problem

In this paper, we propose an efficient method for constructing numerical algorithms for solving the fractional initial value problem by using the Pade approximation of fractional derivative operators. We regard the Grunwald–Letnikov fractional derivative as a kind of Taylor series and get the approximation equation of the Taylor series by Pade approximation. Based on the approximation equation, we construct the corresponding numerical algorithms for the fractional initial value problem. Finally, we use some examples to illustrate the applicability and efficiency of the proposed technique

Solution of Boundary Value Obstacle Problems Using MQ-RBF and IMQ-RBF

A kind of numerical method which is based on multiquadric RBF, inverse multiquadric RBF, and Wu-Schaback operators is presented for solving second-order and third-order boundary value problems associated with obstacle, unilateral, and contact problems. The algorithms are proved to be highly accurate and easy to implement. Some numerical tests are also presented to show the efficiency of the algorithms

Improvement on Conformable Fractional Derivative and Its Applications in Fractional Differential Equations

In this paper, we made improvement on the conformable fractional derivative. Compared to the original one, the improved conformable fractional derivative can be a better replacement of the classical Riemann-Liouville and Caputo fractional derivative in terms of physical meaning. We also gave the definition of the corresponding fractional integral and illustrated the applications of the improved conformable derivative to fractional differential equations by some examples

Solving Fractional Differential Equations by Using Triangle Neural Network

In this paper, numerical methods for solving fractional differential equations by using a triangle neural network are proposed. The fractional derivative is considered Caputo type. The fractional derivative of the triangle neural network is analyzed first. Then, based on the technique of minimizing the loss function of the neural network, the proposed numerical methods reduce the fractional differential equation into a gradient descent problem or the quadratic optimization problem. By using the gradient descent process or the quadratic optimization process, the numerical solution to the FDEs can be obtained. The efficiency and accuracy of the presented methods are shown by some numerical examples. Numerical tests show that this approach is easy to implement and accurate when applied to many types of FDEs

Staphylococcal Enterotoxin A Induces Intestinal Barrier Dysfunction and Activates NLRP3 Inflammasome via NF-κB/MAPK Signaling Pathways in Mice

Staphylococcal enterotoxin A (SEA), the toxin protein secreted by Staphylococcus aureus, can cause staphylococcal food poisoning outbreaks and seriously threaten global public health. However, little is known about the pathogenesis of SEA in staphylococcal foodborne diseases. In this study, the effect of SEA on intestinal barrier injury and NLRP3 inflammasome activation was investigated by exposing BALB/c mice to SEA with increasing doses and a potential toxic mechanism was elucidated. Our findings suggested that SEA exposure provoked villi injury and suppressed the expression of ZO-1 and occludin proteins, thereby inducing intestinal barrier dysfunction and small intestinal injury in mice. Concurrently, SEA significantly up-regulated the expression of NLRP3 inflammasome-associated proteins and triggered the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) signaling pathways in jejunum tissues. Notably, selective inhibitors of MAPKs and NF-κB p65 ameliorated the activation of NLRP3 inflammasome stimulated by SEA, which further indicated that SEA could activate NLRP3 inflammasome through NF-κB/MAPK pathways. In summary, SEA was first confirmed to induce intestinal barrier dysfunction and activate NLRP3 inflammasome via NF-κB/MAPK signaling pathways. These findings will contribute to a more comprehensive understanding of the pathogenesis of SEA and related drug-screening for the treatment and prevention of bacteriotoxin-caused foodborne diseases via targeting specific pathways

Identification of Hub Genes and Potential Molecular Pathogenesis in Substantia Nigra in Parkinson’s Disease via Bioinformatics Analysis

Parkinson’s disease (PD) is the second most common neurodegenerative disease, with significant socioeconomic burdens. One of the crucial pathological features of PD is the loss of dopaminergic neurons in the substantia nigra (SN). However, the exact pathogenesis remains unknown. Moreover, therapies to prevent neurodegenerative progress are still being explored. We performed bioinformatics analysis to identify candidate genes and molecular pathogenesis in the SN of patients with PD. We analyzed the expression profiles, GSE49036 and GSE7621, which included 31 SN tissues in PD samples and 17 SN tissues in healthy control samples, and identified 86 common differentially expressed genes (DEGs). Then, GO and KEGG pathway analyses of the identified DEGs were performed to understand the biological processes and significant pathways of PD. Subsequently, a protein-protein interaction network was established, with 15 hub genes and four key modules which were screened in this network. The expression profiles, GSE8397 and GSE42966, were used to verify these hub genes. We demonstrated a decrease in the expression levels of 14 hub genes in the SN tissues of PD samples. Our results indicated that, among the 14 hub genes, DRD2, SLC18A2, and SLC6A3 may participate in the pathogenesis of PD by influencing the function of the dopaminergic synapse. CACNA1E, KCNJ6, and KCNB1 may affect the function of the dopaminergic synapse by regulating ion transmembrane transport. Moreover, we identified eight microRNAs (miRNAs) that can regulate the hub genes and 339 transcription factors (TFs) targeting these hub genes and miRNAs. Subsequently, we established an mTF-miRNA-gene-gTF regulatory network. Together, the identification of DEGs, hub genes, miRNAs, and TFs could provide better insights into the pathogenesis of PD and contribute to the diagnosis and therapies

Using Bidimensional Multiscale Entropy Analysis of Ultrasound Images to Assess the Effect of Various Walking Intensities on Plantar Soft Tissues

Walking performance is usually assessed by linear analysis of walking outcome measures. However, human movements consist of both linear and nonlinear complexity components. The purpose of this study was to use bidimensional multiscale entropy analysis of ultrasound images to evaluate the effects of various walking intensities on plantar soft tissues. Twelve participants were recruited to perform six walking protocols, consisting of three speeds (slow at 1.8 mph, moderate at 3.6 mph, and fast at 5.4 mph) for two durations (10 and 20 min). A B-mode ultrasound was used to assess plantar soft tissues before and after six walking protocols. Bidimensional multiscale entropy (MSE2D) and the Complexity Index (CI) were used to quantify the changes in irregularity of the ultrasound images of the plantar soft tissues. The results showed that the CI of ultrasound images after 20 min walking increased when compared to before walking (CI4: 0.39 vs. 0.35; CI5: 0.48 vs. 0.43, p < 0.05). When comparing 20 and 10 min walking protocols at 3.6 mph, the CI was higher after 20 min walking than after 10 min walking (CI4: 0.39 vs. 0.36, p < 0.05; and CI5: 0.48 vs. 0.44, p < 0.05). This is the first study to use bidimensional multiscale entropy analysis of ultrasound images to assess plantar soft tissues after various walking intensities

Effectiveness of Myocardial Contrast Echocardiography Quantitative Analysis during Adenosine Stress versus Visual Analysis before Percutaneous Therapy in Acute Coronary Pain: A Coronary Artery TIMI Grading Comparing Study

The study aim was to compare two different stress echocardiography interpretation techniques based on the correlation with thrombosis in myocardial infarction (TIMI ) flow grading from acute coronary syndrome (ACS) patients. Forty-one patients with suspected ACS were studied before diagnostic coronary angiography with myocardial contrast echocardiography (MCE) at rest and at stress. The correlation of visual interpretation of MCE and TIMI flow grade was significant. The quantitative analysis (myocardial perfusion parameters: A, β, and A×β) and TIMI flow grade were significant. MCE visual interpretation and TIMI flow grade had a high degree of agreement, on diagnosing myocardial perfusion abnormality. If one considers TIMI flow grade <3 as abnormal, MCE visual interpretation at rest had 73.1% accuracy with 58.2% sensitivity and 84.2% specificity and at stress had 80.4% accuracy with 76.6% sensitivity and 83.3% specificity. The MCE quantitative analysis has better accuracy with 100% of agreement with different level of TIMI flow grading. MCE quantitative analysis at stress has showed a direct correlation with TIMI flow grade, more significant than the visual interpretation technique. Further studies could measure the clinical relevance of this more objective approach to managing acute coronary syndrome patient before percutaneous coronary intervention (PCI)

The Design of Integrated Route in Micro-EDM

Fundamental Research Funds for the Central Universities of China [2011121045]Micro-electrical discharge machining (micro-EDM) is a flexible process, consisting of many techniques. The effective combination of these techniques is of great importance to improve machining performance of micro-EDM. In this regard, a new method is proposed in this paper discussing how to design process routes for integrated micro-EDM. The structure of microparts should be divided into fundamental structural components, each of which to be fabricated by means of proper EDM processing techniques according to the features of those micro-EDM methods. In this article, the machining sequence of the integrated route is studied, followed by design principles of integrated machining established to meet specific machining requirements. Then we analyze machining errors during the integrated machining process. Lastly, we demonstrate how a microgear reducer was fabricated with the integrated process. The integrated route of its microparts was designed by following the proposed method. The reducer was successfully produced on a self-developed multifunctional machining platform