Patient knowledge about disease self-management of cirrhosis

This study aimed to define the level of understanding of self-management for patients with liver cirrhosis. A descriptive cross-sectional study was conducted. Thirty cirrhotic patients (14 females and 16 males) in the Gastroenterology Department of University Medical Center, Ho Chi Minh City in Vietnam participated in answering the questionnaire to evaluate their knowledge about liver disease self-management. The majority of cirrhotic patients had an unsatisfactory level of knowledge regarding self management of their disease, particularly in terms of recognizing and preventing complications from hepatic encephalopathy, monitoring for liver cancer, and awareness of medications they should not use. Implications of the study for nursing practice would be to enhance the quality of patient knowledge about self-management disease in the setting and in Vietnam by providing a specialized guideline handbook for each patient with important terms about cirrhosis, self-care information, and ways to prevent and minimize the complications of cirrhosis. Further research with larger samples regarding self-management knowledge and effective ways to better prepare cirrhosis patients for self-care is needed to improve the education for these patients

Evolution of Protein-protein Interaction Networks in Duplication-Divergence Model

Protein interacts with one another resulting in complex functions in living organisms. Like many other real-world networks, the networks of protein-protein interactions possess a certain degree of ordering, such as the scale-free property. The latter means that the probability $P$ to find a protein that interacts with $k$ other proteins follows a power law, $P(k) \sim k^{-\gamma}$. Protein interaction networks (PINs) have been studied by using a stochastic model, the duplication-divergence model, which is based on mechanisms of gene duplication and divergence during evolution. In this work, we show that this model can be used to fit experimental data on the PIN of yeast Saccharomyces cerevisae at two different time instances simultaneously. Our study shows that the evolution of PIN given by model is consistent with growing experimental data over time, and that the scale-free property of protein interaction network is robust against random deletion of interactions

Effects of ribosomal exit tunnel on protein's cotranslational folding

In vivo, folding of many proteins occurs during their synthesis in the ribosomeand continues after they have escaped from the ribosomal exit tunnel. Inthis research, we investigate the confinement effects of the ribosome on thecotranslational folding of three proteins, of PDB codes 1PGA, 1CRN and 2RJX,by using a coarse-grained model and molecular dynamics simulation. The exittunnel is modeled as a hollow cylinder attached to a flat wall, whereas aGo-like model is adopted for the proteins. Our results show that theexit tunnel has a strong effect on the folding mechanism by setting an order bywhich the secondary and tertiary structures are formed. For protein 1PGA, thefolding follows two different folding routes. The presence of the tunnel alsoimproves the foldability of protein

Assessing forest cover changes in Dak Lak province (Central Highlands of Vietnam) from multi-temporal Landsat data and machine learning techniques

Dak Lak is a province in the Central Highlands region of Vietnam, with a large area of forests and forestry land. However, the forest cover has changed dramatically in recent times due to the influence of human activities and climate change. This article presents the results of assessing forest cover changes in Dak Lak province from Landsat satellite image data for the period 2000 – 2020. Three Landsat satellite image scenes, including Landsat 5 TM images taken in March 2000 and February 2010 and Landsat 8 OLI image taken in February 2020 are used to classify forest cover. Three common machine learning techniques, including Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Tree (CART) and the traditional maximum likelihood classification algorithm are used to classify forest cover in the study area, thereby choosing the method with the highest accuracy. The results show that the RF algorithm has the highest accuracy in classifying forest cover from multi-temporal Landsat images by comparing the overall accuracy value and the Kappa coefficient. The obtained results are used to build forest cover change maps in the period 2000 - 2010, 2010 - 2020 and 2000 - 2020. The results received in the study provide information to help managers in monitoring and protecting forest resources

Robust adaptive controller for wheel mobile robot with disturbances and wheel slips

In this paper an observer based adaptive control algorithm is built for wheel mobile robot (WMR) with considering the system uncertainties, input disturbances, and wheel slips. Firstly, the model of the kinematic and dynamic loops is shown with presence of the disturbances and system uncertainties. Next, the adaptive controller for nonlinear mismatched disturbance systems based on the disturbances observer is presented in detail. The controller includes two parts, the first one is for the stability purpose and the later is for the disturbances compensation. After that this control scheme is applied for both two loops of the system. In this paper, the stability of the closed system which consists of two control loops and the convergence of the observers is mathematically analysed based on the Lyapunov theory. Moreover, the proposed model does not require the complex calculation so it is easy for the implementation. Finally, the simulation model is built for presented method and the existed one to verify the correctness and the effectiveness of the proposed scheme. The simulation results show that the introduced controller gives the good performances even that the desired trajectory is complicated and the working condition is hard

Layered double hydroxides as containers of inhibitors in organic coatings for corrosion protection of carbon steel

The present work focuses on the use of layered double hydroxides (LDH) as containers for corrosion inhibitors in an epoxy coating. 2-Benzothiazolylthio-succinic acid (BTSA), used as corrosion inhibitor, was intercalated by co-precipitation in magnesium-aluminum layered double hydroxides. The obtained LDH-BTSA was characterized by infrared spectroscopy, X-ray diffraction and scanning electron microscopy. BTSA release from LDH-BTSA in NaCl solutions was investigated by UV-vis spectroscopy. The inhibitive action of LDH-BTSA on carbon steel corrosion was characterized by electrochemical methods and the protective properties of an epoxy coating containing LDH-BTSA were evaluated by electrochemical impedance spectroscopy. It was shown that the BTSA was intercalated in the layered double hydroxide and its loading was about 33%. The BTSA release was dependent on the NaCl concentration in the electrolyte. The polarization curves obtained on the carbon steel sample showed that the LDH-BTSA is an anodic inhibitor. Its efficiency was about 90% at a concentration of 3 g/l. The impedance results showed that the incorporation of LDH-BTSA (3%) in the epoxy matrix improved the corrosion protection of the carbon steel