Enhanced Motor Imagery-Based Eeg Classification Using A Discriminative Graph Fourier Subspace

Dealing with irregular domains, graph signal processing (GSP) has attracted much attention especially in brain imaging analysis. Motor imagery tasks are extensively utilized in brain-computer interface (BCI) systems that perform classification using features extracted from Electroencephalogram signals. In this paper, a GSP-based approach is presented for two-class motor imagery tasks classification. The proposed method exploits simultaneous diagonalization of two matrices that quantify the covariance structure of graph spectral representation of data from each class, providing a discriminative subspace where distinctive features are extracted from the data. The performance of the proposed method was evaluated on Dataset IVa from BCI Competition III. Experimental results show that the proposed method outperforms two state-of-the-art alternative methods

In Vitro Propagation Of ‘Gisela 5’ Rootstock As Affected By Mineral Composition Of Media And Plant Growth Regulators

The purpose of the presented study was to determine the best mineral composition of media and plant growth regulators in the micropropagation of the ‘Gisela 5’ (Prunus cerasus × P. canescens) dwarf sweet cherry rootstock. Nodal explants from young healthy shoots were excised and cultured on Murashige and Skoog medium without growth regulators. In vitro raised shoot tips were transferred to three culture media including Murashige and Skoog (MS), Driver and Kuniyuki (DKW) and Lloyd and McCown (WPM) containing benzyl adenine (BA) (0.5, 1 or 2 mg·l−1) in combination with kinetin (Kin) at 0 or 0.5 mg·l−1. WPM and DKW media were proving to be the most effective, resulting in a higher percentage of shoot multiplication and shoot number as compared to MS. BA in concentration 2 mg·l−1 resulted in the highest number of microshoots per explant (3.1). For rooting, 0, 0.5, 1 or 2 mg·l−1 indole-3-butyric acid (IBA) on MS, DKW and WPM media were tested. WPM medium containing 2 mg·l−1 IBA was most effective for rooting (93.7%) in comparison to MS (53.1%) and DKW (14.0%). Rooted plantlets were successfully hardened and established in pots

A Comprehensive Study of Retinal Vessel Classification Methods in Fundus Images

Nowadays, it is obvious that there is a relationship between changes in the retinal vessel structure and diseases such as diabetic, hypertension, stroke, and the other cardiovascular diseases in adults as well as retinopathy of prematurity in infants. Retinal fundus images provide non-invasive visualization of the retinal vessel structure. Applying image processing techniques in the study of digital color fundus photographs and analyzing their vasculature is a reliable approach for early diagnosis of the aforementioned diseases. Reduction in the arteriolar–venular ratio of retina is one of the primary signs of hypertension, diabetic, and cardiovascular diseases which can be calculated by analyzing the fundus images. To achieve a precise measuring of this parameter and meaningful diagnostic results, accurate classification of arteries and veins is necessary. Classification of vessels in fundus images faces with some challenges that make it difficult. In this paper, a comprehensive study of the proposed methods for classification of arteries and veins in fundus images is presented. Considering that these methods are evaluated on different datasets and use different evaluation criteria, it is not possible to conduct a fair comparison of their performance. Therefore, we evaluate the classification methods from modeling perspective. This analysis reveals that most of the proposed approaches have focused on statistics, and geometric models in spatial domain and transform domain models have received less attention. This could suggest the possibility of using transform models, especially data adaptive ones, for modeling of the fundus images in future classification approaches

Integrated care competencies and their association with cross-cultural competence among registered nurses: A cross-sectional questionnaire survey

Aim: To examine the association between the integrated care competencies and cross-cultural competence of registered nurses prior to the integration of social and healthcare services in Finland. Design: A descriptive correlational cross-sectional questionnaire survey was conducted. Methods: A simple random sample of 10,000 registered nurses was drawn from the Finnish Central Register of Valvira (National Supervisory Authority for Welfare and Health); 7000 of them were sent the online questionnaire, and a total of 1232 registered nurses participated in the study. We collected data using background questions, revised versions of the Competent Workforce for the Future tool in the four domains of client orientation, responsibility for personal or relative's welfare, fluency and clarity of services and access to the services and of the Cross-Cultural Competence of Healthcare Professional tool in the four domains of motivation/curiosity, attitude, skill and emotion/empathy. Results: Participants demonstrated a high level of integrated care competencies (mean = 4.00,SD ± 0.49).Anassociation was observed between integrated care competencies and their domains of skills, motivation/curiosity, emotions/empathy, and cross-cultural competence (p< 0.001). Female sex, older age, more working experience, employment in the private sector, and higher self-rated competence for working in a multicultural environment were positively associated with higher integrated care competencies. Conclusion: It is recommended that nurse managers and nurse educators emphasize the development of registered nurses' cross-cultural competence alongside integrated care competencies to meet the needs of different individuals and communities when providing integrated care. Patient or Public Contribution: Finnish registered nurses including all types of nurses, midwives and paramedics working the public and private healthcare, were involved in this study by responding to the online survey.</p