Models In Different Countries Research Articles

Comparing Media Systems: A New Critical Academic Reading

<p>The year 2024 marks the 20th anniversary of the publication of <em>Comparing Media Systems</em> (2004), by Daniel C. Hallin and Paolo Mancini, a book that established three major media models in the Western world. Subsequently, the same authors published <em>Comparing Media Systems Beyond the Western Wo</em>rld (2011), which extended the work to other countries such as Russia, Poland and China. In both cases, the interest was in the comparative analysis using a series of variables that made it possible to classify the media structures of the countries into differential groups. For their analysis, the authors included different study categories that need to be reinterpreted considering technological evolution, changes in consumption habits or the irruption of social networks. This monograph is a proposal for a review of media models in different countries and aims to be a starting point for future lines of research on this subject. A total of ten articles are presented to address an academic debate on the scientific relevance of Hallin and Mancini's work, its contribution to comparative media studies and its necessary re-reading in a historical-temporal framework different from the moment in which it was published.</p>

Exploration of Legal Professional Education and the Cultivation Model of Legal Talents

The importance of legal professional education and the cultivation of legal talents, as well as the practical models in different countries, are analyzed in this paper. The unique aspects of legal education in the United States, the United Kingdom, and Germany, such as case-based teaching in the United States, legal ethics cultivation in the United Kingdom, and the integration of theory and practice in Germany, provide insights for the international perspective of legal education. Meanwhile, the future trends of legal professional education and the cultivation model of legal talents are discussed, emphasizing the criticality of practical teaching, interdisciplinary integration, international development, and the cultivation of the spirit of the rule of law. These aspects are considered important factors in shaping the future of legal education. In addition, a thorough analysis of the current problems in legal professional education is conducted, and countermeasures to strengthen legal professional education and the cultivation of legal talents are proposed, aiming to optimize curriculum design, enhance the construction of teaching staff, and improve the practical teaching system, thereby enhancing the level of legal professional education and the quality of legal talent cultivation. Future research directions for legal professional education and the cultivation model of legal talents are also explored, indicating the need for further research into the underlying reasons and mechanisms, as well as active exploration of cooperation models with other countries and regions, to adapt to the needs of social development and the construction of the rule of law.

The Competitiveness of Tourist Destinations: A Review of the Scientific Literature

The competitiveness of tourist destinations worldwide is of vital importance for any destination that wishes to develop and improve its positioning in the global, national and/or regional market, because the actors of tourist destinations are aware that the greater the number of tourists and tourist spending in the destination, the greater the economic development that directly and indirectly affects the different actors, the ultimate objective being to improve the quality of life of the people in the community. Therefore, this study focuses on carrying out a review of the scientific literature on the competitiveness of tourist destinations, with the objective of identifying the dimensions, factors and indicators used in the different models of destination competitiveness, which can be applied to a tourist destination at the present time and have greater clarity when evaluating it. In this sense, a bibliographic review of 40 scientific articles from Scopus and Science Direct published between 2000 and 2021 was carried out, of which 29 articles were selected based on the criteria of the proposed models of competitiveness of tourist destinations, factors and indicators used. The results of the study contemplate a theoretical framework of competitiveness in itself, the competitiveness of tourist destinations and the models of competitiveness of tourist destinations, making an analysis of the differences and similarities between them; likewise, indicators used to analyze the destination are presented, and finally, studies that have used these theories and models in different countries are presented. Finally, it is concluded that the theories of the competitiveness of tourist destinations that have most influenced these models have been those proposed by Ritchie and Crouch, and Dwyer and Kim, since they have between 7 and 9 factors in common and 57 indicators.

Economic and political causes for transformations of social policy in the 20th century

The paper analyses dynamics of social policy in the 20th century in Germany, Britain, France, Spain, Russia, the USA and China as the largest states, where the largest changes in the field of social security took place. The existing approaches to the typology of social states are considered. The article studies reasons for the formation, changes and organisation of the social security systems, the mutual influence of the different states in the field of social policy. The article presents an assessment of the problems faced by social states, evaluation of the advantages and disadvantages of different models of social policy, and overview of changes in models in different countries. Economic and political factors influencing decision-making in the field of social policy, as well as the consequences of social reforms, are analyzed. Analysis of the causes of transformations in social policy is carried out through the study of institutions, regulations, and statistical data. The organization, regulation and modernization of pension and health insurance systems, benefits, allowances and subsidies for certain categories of consumers in the 20th century was caused by large-scale economic and political transformations. Mass industrial production made goods more accessible, and redistribution systems became a tool for balancing the market and ensuring the sustainability of the economy. Democratization and expansion of suffrage, the spread of radical ideologies or changes in political regimes created a demand for means of ensuring social stability, which was supplied by the social programs. The increase in spending on social policy began to create problems for the sustainability of budgets at the end of the 20th century, which led to attempts to limit social programs, but a reduction in spending did not occur due to the political and economic importance that the welfare state has acquired in the 20th century.

Customers Adaptation of E-banking services; extending TAM through Anthpmorphism in Saudi Arabia

This study aims to investigate influence of perceived anthropomorphism, perceived ease of use, perceived usefulness, privacy concerns, as well as attitude on intention to adopt AI banking services. The research follows a positivistic and deductive reasoning approach, utilizing experimental techniques in a cross-sectional design. Data of 210 responses collected through a questionnaire distributed via Google Docs were analyzed using Smart PLS3. The results indicate that intention to adopt AI banking services is influenced by perceived anthropomorphism, perceived ease of use, perceived usefulness, and privacy concerns through attitude. Strong correlations among all variables were observed, highlighting the significant and positive impact of artificial intelligence on encouraging acceptance of advanced technology in banking sector in Kingdom of Saudi Arabia. Future research is recommended to test various other variables using the same research model in different countries. Practical implications include the need for senior managers and policymakers in financial institutions to formulate relevant policies and marketing strategies aligned with customer needs. This research study's primary objective is to prospect and examine factors impelling consumer adoption intentions of artificial intelligence in banking sector in Kingdom of Saudi Arabia.

Designing an innovative primary health care model for the Iranian health system: A mixed methods study protocol

IntroductionToday, the main strategy of countries to improve the health status of people is primary health care (PHC). The present study has two main objectives: 1) scoping review and mapping of the characteristics of innovative PHC models in different countries, 2) developing and validating a model for innovative PHC considering the PHC conditions and challenges of the Islamic Republic of Iran. MethodsThe study will be performed in five phases. In this regard, first, a scoping review will be conducted to investigate the characteristics of innovative PHC. Second, a qualitative study will be performed on the PHC challenges in Iran. Third, another qualitative study will be conducted to identify the appropriate components for Iran's innovative PHC system, using the opinions of experts in this field. In the fourth phase, using the panel of experts, a suitable model will be designed for the Iranian PHC system. Eventually, in the fifth phase, the goals and components of the model developed by experts will be evaluated through a Delphi study, and the validity of the model will be measured using appropriate criteria. ResultsThe findings of this research provide considerable insight into how Iran's PHC system will be able to consider innovative models and changes in response to a new context and newly emerged problems. ConclusionGiven the importance of PHC in the present era and the need to pay more attention to and strengthen it for all communities, it seems necessary to conduct studies and provide appropriate conditions for the development of PHC.

Exploring Primary Aluminum Consumption: New Perspectives from Hybrid CEEMDAN-S-Curve Model

Aluminum is globally the most used nonferrous metal. Clarifying the consumption of primary aluminum is vital to economic development and emission reduction. Based on the signal decomposition tool and S-curve model, a new hybrid complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-S-curve model is proposed to analyze primary aluminum consumption of different countries for the last 100 years. The results show that: (1) Per capita primary aluminum consumption can be decomposed into low-frequency, medium-frequency, and high-frequency components, contributing over 70%, 2–17%, and less than 9% to variability of consumption series, respectively. This can be interpreted as economic development represented by GDP per capita, shocks from significant events, and short-term fluctuations, respectively. (2) The CEEMDAN-S-curve shows good applicability and generalizability by using this model in different countries. (3) A new strategy is provided to analyze and predict the consumption pattern of primary aluminum. Furthermore, some important topics related to primary aluminum consumption are discussed, such as CO2 emission and recovery. Based on the results, to meet economic development and achieve sustainable development goals, some measures should be implemented, such as making policies, encouraging resource recovery, and developing new technologies.

Physician-Suggested Innovative Methods for Health System Resilience amidst Workforce Emigration and Sociopolitical Unrest in Nigeria: A Survey-Based Study.

Physician emigration (the brain drain) and sociopolitical unrest significantly contribute to the instability of many low- and middle-income countries' healthcare systems. However, limited literature captures the locally driven and context specific suggestions to promote and sustain these health systems' resilience. Thus, the purpose of this study is to 1) understand the effects of physician emigration and sociopolitical unrest on Nigeria's healthcare system, and to 2) synthesize solutions suggested by Nigeria-trained physicians in the form of a resilience framework. An anonymous online survey was conducted among Nigeria-trained physicians. Respondents were recruited using convenience and snowball sampling methods via a WhatsApp group for Nigeria-trained doctors. Quantitative data were analyzed using Stata 17 and qualitative themes were coded by two independent researchers. The final sample included 49 Nigeria-trained physicians-35 physicians practicing in Nigeria and 14 emigrated physicians. All of the physicians currently practicing in Nigeria have considered emigrating, with 79% of them having concrete plans to emigrate in the next five years. Among emigrated physicians, factors such as remuneration (92%) and socioeconomic state of the country (92%) contributed to their decision to emigrate. Suggestions to enhance health system resilience fell into six broad themes: 1) policy and politics, 2) funding and resources, 3) organization and structure, 4) training and education, 5) research and primary health, and 6) health for peace initiatives. The healthcare system is currently unstable and vulnerable due to physician emigration and sociopolitical unrest. To develop and implement solutions to mitigate these issues, capturing the locally trained physicians' perspectives are critical. While each country's healthcare system is unique, countries with similar strains can adapt this model for resilience building. Future studies should focus on adapting the model in different countries with policy-level action points.

ТЕНДЕНЦІЇ РОЗВИТКУ ЦИРКУЛЯРНОЇ ЕКОНОМІКИ У СВІТІ

Circular economy is an important concept aimed at reducing the level of use of resources and waste, has a significant potential for ensuring the efficiency of the economy. The article examines current trends in the development of the circular economy in the world. It emphasizes the growing awareness of the problems of the traditional economy and the use of resources and the impact on the environment, which leads to changes in the consumption and production of goods. Legislative support for the circular economy is growing, including the introduction of CO2 taxes and standards for manufacturers. It describes innovations and technological advances that contribute to the efficient use of resources, such as smart sorting systems and advanced recycling methods. Also noted is the expansion of business models, where companies pay attention to high usability, ease of repair and reuse of products. The article emphasizes the expansion of the global market of secondary raw materials, the involvement of consumers and international cooperation. In particular, common standards, regulatory frameworks and financial support for the development of circular models in different countries are discussed. The prospects for the development of the circular economy in megacities and its application in the food and textile industries are substantiated. In the context of local development, the circular economy becomes an important component, contributing to sustainable economic growth, creating jobs and improving the quality of life of residents. It has been determined that the circular economy is gaining more and more importance in the world, there is a growing awareness of the need to change the way of production and consumption in order to reduce the negative impact on the environment and ensure the sustainable use of resources. Trends in the development of the circular economy include legislative support, innovation and technological progress, the expansion of the global market for secondary raw materials, consumer involvement and international cooperation. The main trends in the development of the circular economy are systematized, which can be useful for researchers, businesses, government bodies and the public, who are interested in promoting sustainable development and saving resources.

Upravljanje poreskim rizikom u multinacionalnim bankama - pogled iz Srbije

Considering the significant cross-national differences between tax systems, multinational banks are facing a challenge to secure compliance with the tax regulation of each country. In this regard, multinational banks tend to minimize tax risk exposure and the probability that national tax authorities will consider certain tax treatment as illegal. The paper studies the main sources of tax risk for subsidiaries of multinational banks in Serbia. It is pointed out that banks are facing important challenges to secure compliance with the tax regulation, particularly value-added tax and corporate income tax regulation. The paper also shows that subsidiaries of multinational banks in Serbia and neighboring countries disclose the information on the tax risk in notes to the financial statements only to a moderate extent. In addition, multinational banks disclose information on tax risk using different models in different countries, implying that they adapt the disclosure to the assessed level of the tax risk in each country.

Application of photobiomodulation therapy in the recovery of a fracture model in different countries: a concise review

Application of photobiomodulation therapy in the recovery of a fracture model in different countries: a concise review

FOREIGN EXPERIENCE OF BUSINESS PROCESS DIGITALIZATION IN LOCAL GOVERNMENT INSTITUTIONS

The article is devoted to the analysis of the foreign experience of business process digitalization in local government institutions. The authors indicate the following main internal problems regarding the introduction of digital models of public administration in Ukraine: the absence of an officially defined category-concept apparatus; the non-compliance with legal, informational-analytical, scientific-methodical, financial, organizational-technical, personnel support, etc. The authors underline that digital technologies and their use in all spheres of society's life-activity allow to create new business practices that are reflected in the emergence of gig economy, freelancing, crowdfunding, crowdsourcing, crowdcasting, etc. and other new types of services. A comparative analysis of public administration models in different countries indicates that the institutions and mechanics of public power of the countries of Europe, the USA, Japan, China and others are caught by various historical, economic, political and cultural experience. In each of the models, the function of public administration bodies supports the necessary level of regulation of social and economic processes and ensures stable public development. Keywords: local government institutions, business process digitalization, public administration model, foreign experience.

Antecedents of psychological ownership among family hotel employees

PurposeThis paper examines the mediating process of enhancing employees' psychological ownership among family hotel employees.Design/methodology/approachA total of 1,005 employees from 197 budget-to-three-star family hotels took part in the study by completing an either self-reported or interviewer questionnaire. The respondents were selected using a convenient sampling technique. A partial least square structural equation was used to analyse the data.FindingsWork engagement and organisational performance were shown to significantly predict psychological ownership, except for counterproductive work behaviour. Both counterproductive work behaviour and organisational performance were found to predict psychological ownership. Finally, the relationship between (1) counterproductive work behaviour and psychological ownership and (2) organisational performance and psychological ownership is mediated by work engagement.Practical implicationsReplication of this model in different countries and other work settings is highly recommended for cross validating the reported findings in this study. The study emphasises the need for family hotel owners to create a conducive work environment devoid of conditions that promote counterproductive work behaviour among employees and encourage them to engage in higher productivity.Originality/valueThis study appears to be one of the first to have investigated a model linking counterproductive work behaviour, performance to psychological ownership through work engagement in the family hotel context.

Quantitative Investment Trading Model Based on Model Recognition Strategy with Deep Learning Method

With the acceleration of economic globalization, the frequent price fluctuations of gold and bitcoin and other currencies have attracted wide attention from the quantitative investment industry. For market traders, rational use of deep learning means to improve traditional investment trading strategies has become one of the main contents of current work. In this paper, the deep learning method is used to make a horizontal comparison of the benefit increase of the model recognition strategy with deep learning as the main means compared with the other two strategies, and a longitudinal comparison is made between the deep learning method and the traditional time series of fitting accuracy advantages. We grouped gold and bitcoin prices in the LSTM/GRU framework, trained the recursive dynamic neural network model on the daily data of each group, and used the dropout algorithm to reduce the overfitting effect of the model and retained 20% of the data for cross-checking. The results obtained by this method show that the benefit of the whole neural network model is more obvious when making decisions on the data of the day, and the fitting accuracy of the model is more than 73%, and the average absolute error is 14.040908, indicating a good fitting degree. Compared with model recognition strategies represented by LSTM/GRU, follow-the-winner and follow-the-loser have obvious disadvantages in terms of investment trading principle, and their returns are far lower than the $22,059.583248 obtained under the model recognition strategy. We compare the price trends of gold and bitcoin under ARIMA(2,1,1) and ARIMA(4,1,5) by comparing the LSTM/GRU method under the framework of model recognition with the time series method in model recognition and find that the mean square error is much greater than the fitting results of neural network. Therefore, it is concluded that the model recognition strategy integrating the deep learning model is the best fit and the best profit among the three conditions. Finally, we change the transaction cost of gold and bitcoin to 7% to simulate whether the transaction model in different countries is stable. The conclusion shows that when the transaction cost changes within 7%, the model still has high feasibility and stability and is relatively robust.

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies.

Introduction: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the burden of chest diseases or evaluate the efficacy of interventions such as vaccines. This study explores machine learning models that could standardize interpretation of CXR across studies and the utility of incorporating individual reader annotations when training models using CXR data sets annotated by multiple readers. Methods: Convolutional neural networks were used to classify CXRs from seven low to middle-income countries into five categories according to the World Health Organization's standardized methodology for interpreting paediatric CXRs. We compared models trained to predict the final/aggregate classification with models trained to predict how each reader would classify an image and then aggregate predictions for all readers using unweighted mean. Results: Incorporating individual reader's annotations during model training improved classification accuracy by 3.4% (multi-class accuracy 61% vs 59%). Model accuracy was higher for children above 12 months of age (68% vs 58%). The accuracy of the models in different countries ranged between 45% and 71%. Conclusions: Machine learning models can annotate CXRs in epidemiological studies reducing inter-reader and intra-reader variability. In addition, incorporating individual reader annotations can improve the performance of machine learning models trained using CXRs annotated by multiple readers.

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies

Introduction: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the burden of chest diseases or evaluate the efficacy of interventions such as vaccines. This study explores machine learning models that could standardize interpretation of CXR across studies and the utility of incorporating individual reader annotations when training models using CXR data sets annotated by multiple readers. Methods: Convolutional neural networks were used to classify CXRs from seven low to middle-income countries into five categories according to the World Health Organization's standardized methodology for interpreting paediatric CXRs. We compared models trained to predict the final/aggregate classification with models trained to predict how each reader would classify an image and then aggregate predictions for all readers using unweighted mean. Results: Incorporating individual reader's annotations during model training improved classification accuracy by 3.4% (multi-class accuracy 61% vs 59%). Model accuracy was higher for children above 12 months of age (68% vs 58%). The accuracy of the models in different countries ranged between 45% and 71%. Conclusions: Machine learning models can annotate CXRs in epidemiological studies reducing inter-reader and intra-reader variability. In addition, incorporating individual reader annotations can improve the performance of machine learning models trained using CXRs annotated by multiple readers.

How do companies launch circular service business models in different countries?

Companies experiment with new circular service business models (CSBMs) to respond to environmental and competitive pressures. CSBMs help companies to conserve and reuse products and materials over time while providing unique customer service. Companies typically launch a business model in one country and then roll it out to others. This comes with many challenges and strategic choices. Little is known about the external factors that influence the launch of CSBMs in different countries. This study draws on interviews within eight internationally operating companies that launched CSBMs in different countries, to develop a conceptual framework of seven external factors: environmental, knowledge & information, technology & infrastructure, socio-cultural, supply & partner network, market, and regulatory. We also discover six adaptation strategies to anticipate these factors: 1) promote learning for sustainability and circular economy, 2) reframe the sustainable value proposition based on cultural context, 3) collaborate to create new circular service rules and infrastructure, 4) develop location-specific technology capabilities, 5) build momentum and trust in service models, and 6) customise product and service offerings. This research contributes knowledge to CSBM design in different countries. It supports practitioners in better managing the launch of new CSBMs in different countries, and allows policymakers to create a better enabling environment.

Use and Applicability of the Gail Model to Calculate Breast Cancer Risk: A Scoping Review.

Objective:To perform a scoping review of the applicability of the Gail model in different countries for different ethnicities. Methods:The review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist and search strategies based on the PICOS approach. The reviewed articles were included if they were published between 2013 and 2018 in English, Portuguese, or Spanish; were original articles available in full online; and described the use of the Gail model. The PubMed, Embase, and Web of Science data bases were searched. Results:A total of 38 articles eligible for analysis were identified, of which 16 used the Gail model to assess breast cancer risk in women, eight analyzed the applicability of this tool in their population, seven compared the tool and/or modified it according to the specific risk factors of their population, and seven cited the model in determining eligibility for chemoprevention. Conclusion:The Gail model has different applicabilities Greater effectiveness and breast cancer risk are found in developed countries.

The Characteristics of the University Admission System and Their Infl uence on the Accessibility of Higher Education

The study provides a review of the admission to universities models in different countries and also a comparative analysis of the educational systems characteristics from an international perspective. The aim of the research is to assess the possible impact of the educational system characteristics on the accessibility of higher education. There is also proposed an analytical model which explains how the level of autonomy and selectivity of the educational system, along with the characteristics of the student financial support influence the level of accessibility of higher education. The framework of the model is supported by the cases of selected groups of countries: post-Soviet countries, the USA and the UK, Scandinavian countries and Western European countries. Based on the classification of higher education systems, countries with the highest level of access to higher education tend to have low levels of autonomy and selectivity, or they also can be characterized by highly developed system of financial support. As a result, it was found that high selectivity and autonomy level can negatively influence the accessibility of higher education, while high level of the financial support system may neutralize this effect and positively influence on the access to higher education. Results of the study can be useful while reforming the selection system in Russia, since comparative analysis shows which tools make it possible to increase the accessibility of higher education and, as a result, to reduce educational inequality among different social groups.

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies

Introduction: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the burden of chest diseases or evaluate the efficacy of interventions such as vaccines. This study explores machine learning models that could standardize interpretation of CXR across studies and the utility of incorporating individual reader annotations when training models using CXR data sets annotated by multiple readers. Methods: Convolutional neural networks were used to classify CXRs from seven low to middle-income countries into five categories according to the World Health Organization's standardized methodology for interpreting paediatric CXRs. We compared models trained to predict the final/aggregate classification with models trained to predict how each reader would classify an image and then aggregate predictions for all readers using unweighted mean. Results: Incorporating individual reader's annotations during model training improved classification accuracy by 3.4% (multi-class accuracy 61% vs 59%). Model accuracy was higher for children above 12 months of age (68% vs 58%). The accuracy of the models in different countries ranged between 45% and 71%. Conclusions: Machine learning models can annotate CXRs in epidemiological studies reducing inter-reader and intra-reader variability. In addition, incorporating individual reader annotations can improve the performance of machine learning models trained using CXRs annotated by multiple readers.