Search results for: Vinogradov%20Dmitriy%20Valerievich

Authors: Ram Prasad Baral, Vinogradov Dmitriy Valerievich, Rameshwar Adhikari

Abstract:

Diabetes has posed a great threat to the human health worldwide, both in developed and developing countries. The disease has basically rooted from the dramatically changed way of living of the present day human civilization as our living has deviated from what the nature has adapted us for. In this context, due to availability of wide range of climatic condition and hence the wide spectrum of biodiversity, Nepal is blessed with a valuable reservoir of medicinal herbs. These assets have been utilized and developed practices in traditional medicines and Ayurvedic way of treatment over several thousand years in the region. It has been established since ancient times that each and every plant has a specific medicinal value. There are many plants’ products which have been utilized in Ayurvedic medicine for the effective treatment of diabetes. The medicaments are less expensive and pose practically no side effects. In this work, we report a general survey of anti-diabetic properties of some medicinal herbs with pronounced effects and their applications. The plants covered in this study originate from far western region of Nepal and include Ficus racemosa, Momordica charantia, Azadirachta indica, Helieteres isora, Saraca asoca, Ichnocarpus frutescens, Tinospora sinensis, Commiphora mukul, Coccinia grandis, and Hippophae salicifolia.

Keywords: Ficus racemosa, Momordica charantia, Azadirachta indica, Helieteres isora, Saraca asoca, Ichnocarpus frutescens, Tinospora sinensis, Commiphora mukul, Coccinia grandis, Hippophae salicifolia

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Authors: Olga Shapovalova, Vladimir Vinogradov

Abstract:

Among many different sol – gel matrices only alumina can be successfully parenteral injected in the human body. And this is not surprising, because boehmite (aluminium oxyhydroxide) is the metal oxide approved by FDA and EMA for intravenous and intramuscular administrations, and also has been using for a longtime as adjuvant for producing of many modern vaccines. In our earlier study, it has been shown, that denaturation temperature of enzymes entrapped in sol-gel boehmite matrix increases for 30 – 60 °С with preserving of initial activity. It makes such matrices more attractive for long-term storage of non-stable drugs. In current work we present ultrasound-assisted sol-gel synthesis of nano-boehmite. This method provides bio-friendly, very stable, highly homogeneous alumina sol with using only water and aluminium isopropoxide as a precursor. Many parameters of the synthesis were studied in details: time of ultrasound treatment, US frequency, surface area, pore and nanoparticle size, zeta potential and others. Here we investigated the dependence of stability of colloidal sols and textural properties of the final composites as a function of the time of ultrasonic treatment. Chosen ultrasonic treatment time was between 30 and 180 minutes. Surface area, average pore diameter and total pore volume of the final composites were measured by surface and pore size analyzer Nova 1200 Quntachrome. It was shown that the matrices with ultrasonic treatment time equal to 90 minutes have the biggest surface area 431 ± 24 m2/g. On the other had such matrices have a smaller stability in comparison with the samples with ultrasonic treatment time equal to 120 minutes that have the surface area 390 ± 21 m2/g. It was shown that the stable sols could be formed only after 120 minutes of ultrasonic treatment, otherwise the white precipitate of boehmite is formed. We conclude that the optimal ultrasonic treatment time is 120 minutes.

Keywords: boehmite matrix, stabilisation, ultrasound-assisted sol-gel synthesis

Procedia PDF Downloads 240

Authors: Sergey V. Vinogradov

Abstract:

Coastal communities are presently facing increased vulnerabilities due to rising sea levels and shifts in global climate patterns, a trend expected to escalate in the long run. To address the needs of government entities, the public sector, and private enterprises, there is an urgent need to thoroughly investigate, assess, and manage the present and projected risks associated with coastal flooding, including storm surges, sea level rise, and nuisance flooding. In response to these challenges, a practical approach to evaluating storm surge inundation risks has been developed. This methodology offers an integrated assessment of potential flood risk in targeted coastal areas. The physical modeling framework involves simulating synthetic storms and utilizing hydrodynamic models that align with projected future climate and ocean conditions. Both publicly available and site-specific data form the basis for a risk assessment methodology designed to translate inundation model outputs into statistically significant projections of expected financial and operational consequences. This integrated approach produces measurable indicators of impacts stemming from floods, encompassing economic and other dimensions. By establishing connections between the frequency of modeled flood events and their consequences across a spectrum of potential future climate conditions, our methodology generates probabilistic risk assessments. These assessments not only account for future uncertainty but also yield comparable metrics, such as expected annual losses for each inundation event. These metrics furnish stakeholders with a dependable dataset to guide strategic planning and inform investments in mitigation. Importantly, the model's adaptability ensures its relevance across diverse coastal environments, even in instances where site-specific data for analysis may be limited.

Keywords: climate, coastal, surge, risk

Procedia PDF Downloads 29

Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

Abstract:

Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

Procedia PDF Downloads 73