Analysis and development prospects of electronic and mobile payments in Russia

The article analyses electronic systems development, its impact on the development of the economy and a number of sectors of life. It enumerates and analyses basic forms of ecash circulation. The article demonstrates the need for development of this sphere of economy as well as financial systems

The validation of organisational culture assessment instrument in healthcare setting: results from a cross-sectional study in Vietnam

BACKGROUND: Organisational culture (OC) has increasingly become a crucial factor in defining healthcare practice and management. However, there has been little research validating and adapting OCAI (organisational culture assessment instrument) to assess OC in healthcare settings in developing countries, including Vietnam. The purpose of this study is to validate the OCAI in a hospital setting using key psychometric tests and confirmatory factor analysis (CFA). METHODS: This is a cross-sectional study. Self-administered structured questionnaire was completed by 566 health professionals from a Vietnamese national general hospital, the General Hospital of Quang Nam province. The psychometric tests and CFA were utilized to detect internal reliability and construct validity of the instrument. RESULTS: The Cronbach\u27s alpha coefficients (alpha-reliability statistic) ranged from 0.6 to 0.8. In current culture, the coefficient was 0.80 for clan and 0.60 for adhocracy, hierarchy and market dimension, while in expected culture, the coefficient for clan, adhocracy, hierarchy, and market dimension was 0.70, 0.70, 0.70 and 0.60, respectively. The CFA indicated that most factor loading coefficients were of moderate values ranging from 0.30 to 0.60 in both current and expected culture model. These models are of marginal good fit. CONCLUSIONS: The study findings suggest that the OCAI be of fairly good reliability and construct validity in measuring four types of organisational culture in healthcare setting in resource-constrained countries such as Vietnam. This result is a first step towards developing a valid Vietnamese version of the OCAI which can also provide a strong case for future research in the field of measuring and managing organisational culture

chemical constituents from methanolic extract of Garcinia mackeaniana leaves and their antioxidant activity

A phytochemical investigation of the methanolic extract of Garcinia mackeaniana leaves led to the isolation, and determination of five secondary metabolites, including one benzophenone 4,3',4'-trihydroxy-2,6-dimethoxybenzophenone (1), two flavone C-glucosides vitexin (2) and its 2''-O-acetyl derivative (3), one biflavone amentoflavone (4), and one mono-phenol methyl protocatechuate (5). The chemical structures of these compounds were characterized by the NMR-spectroscopic method. These isolated compounds were isolated from G. mackeaniana species for the first time. Benzophenone derivative 1 has shown to be associated with a significant IC50 value of 14.97±0.8 µg/mL in the DPPH-antioxidant assay

Cytotoxic naphthoquinones from Diospyros fleuryana leaves

In the search for anti-cancer plants in Vietnam, the leaves of Diospyros fleuryana were selected for chemical investigation. Phytochemical analysis of the ethyl acetate (EtOAc) extract led to the isolation of two naphthoquinones isodiospyrin (1), and 8'-hydroxyisodiospyrin (2), and one isoflavone 7-O-methylbiochanin A (3). The chemical structures of isolated compounds were determined by 1D-NMR (1H, and 13C-NMR), 2D-NMR spectra (HSQC, and HMBC), and MS spectroscopy. Compound 3 was isolated from genus Diospyros for the first time. Regarding the strong IC50 values of 2.27, and 8.0 µM against KB, and Hep cell lines respectively, cytotoxic examination suggested that compound 2 is a promising agent in anti-cancer treatment.Â

Gene Family Abundance Visualization based on Feature Selection Combined Deep Learning to Improve Disease Diagnosis

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level

Efficient methane dry reforming process with low nickel loading for greenhouse gas mitigation

In this study, a series of nickels supported on gamma alumina with a metal dosage ranging from 0.5 to 3 wt.% were prepared and employed as the catalysts. The effect of nickel dosage on material properties, reaction performance, and catalyst deactivation was investigated. At a low dosage, the nickel-free having low metal-support interaction contributed significantly to the total active site. The basicity of the material was enhanced along with the increase in nickel loading. The presence of active metal showed a great impact at the beginning leading to big improvements in feedstock conversion. However, beyond a nickel dosage of 2 wt.%, further additions did not noticeably influence the reaction performance. Regarding catalyst deactivation, different carbon species were observed on catalyst surface, depending on the nickel dosage. Catalysts with less than 2 wt.% nickel exhibited amorphous carbon as the dominant morphology on the spent catalyst. In contrast, catalysts with 2Ni/Al2O3 and 3Ni/Al2O3 compositions showed graphitic carbon as the main side product. These findings provide insights into the relationship between nickel dosage, catalyst properties, and catalytic performance in methane dry reforming. By understanding the effects of nickel loading on material properties and reaction behavior, researchers can optimize catalyst design and develop more efficient and stable catalysts for sustainable syngas production

A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas

A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas

A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry

Logistics services aid import and export businesses located near ports in terms of ease and efficiency in the globalization era. Furthermore, economic growth and global import–export volumes immediately impact the port industry. This research aims to develop a two-stage Data Envelopment Analysis (DEA) model for measuring the performance efficiency of Vietnam’s top 18 seaports. The DEA resampling technique is used to forecast future performance, and the DEA Malmquist model analyzes efficiency improvement. First, the forecast data for the next three years, from 2021 to 2023, were obtained by resampling Lucas weight prediction with the highest accuracy. The results indicate that 12 out of all ports achieved an average progressive production efficiency over the entire study period of 2018–2023. Further, most ports have advanced slightly in technological efficiency, indicating that the determinants of increased productivity are the technical efficiency change indexes. This work contributes to the body of knowledge by being the first to apply the resampling technique in conjunction with the Malmquist model to forecast performance efficiency in the domain of the seaport sector. Furthermore, the managerial implications serve as a beneficial reference for operation managers, policymakers, and researchers when comparing the operational efficacy of seaports to diverse logistical scenarios