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This paper aims to highlight the ethical implications of the adoption of Fourth Industrial Revolution (4IR) technologies, particularly artificial intelligence (AI), for humanity. It proposes a virtues approach to resolving ethical dilemmas.

The research is based on a review of the relevant literature and empirical evidence for how AI is impacting individuals and society. It uses a taxonomy of human attributes against which potential harms are evaluated.

The technologies of the 4IR are being adopted at a fast pace, posing numerous ethical dilemmas. This study finds that the adoption of these technologies, driven by an Enlightenment view of progress, is diminishing key aspects of humanity – moral agency, human relationships, cognitive acuity, freedom and privacy and the dignity of work. The impact of AI algorithms is also shown, in particular, is shown to be distorting the view of reality and threatening democracy, in part due to the asymmetry of power between Big Tech and users. To enable humanity to be masters of technology, rather than controlled by it, a virtues-based approach should be used to resolve ethical dilemmas, rather than utilitarian ethics.

Further investigation is required to provide more empirical evidence of the harms to humanity of some 4IR technologies cited, such as virtual and augmented reality, manipulative algorithms and toy robots on children and adults and the reality of re-skilling where jobs are lost through automation.

This paper provides a framework for evaluating the impact of some 4IR technologies of humanity and an approach to resolving ethical dilemmas.

Most of the concerns surrounding 4IR technologies, and in particular AI, tend to focus on human rights issues. This paper shows that there are other significant harms to what it means to be a human being from 4IR technologies that will have a profound impact on society if not adequately addressed.

The author is not aware of any other work that uses taxonomy of AI applications and their different impacts on humanity. The proposal to use virtues as a means to resolve ethical dilemmas is also novel in regard to AI.

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

This paper investigates the factors responsible for the emergence of different arrangements of state–society relations. Being concerned with the relations related to the industrial sector, this study focuses more on state–business–labor relations (SBLRs), especially on power dynamics between the main actors in these relations, namely, the state, tycoons, entrepreneurs and labor.

Based on power dynamics, four SBLR modes are identified and differentiated according to state power vis-à-vis non-state actors and tycoon power vis-à-vis the other non-state actors. The balanced mode is characterized by balanced power relations among the four considered actors. In the capture mode, tycoons are more powerful than other actors, including the state, although other nonsocial actors have organizational rights. The crony mode has powerful state, subservient tycoons who enjoy high levels of favoritism and low organizational power for the other social actors. Finally, the state-dominance mode has powerful state, low levels of favoritism to tycoons and low organizational power for all social actors. The paper then explores the factors responsible for the emergence of each of these modes by investigating the factors’ effects on state power and favoritism to tycoons. The investigated factors include historical political–economic, geographical, legal and cultural factors. The hypothesized effects of these factors are then tested using a random-effects probit regression model, investigating how the different factors affect the probability of the existence of the studied SBLR modes.

The results support much of the hypothesized relations and place more emphasis on some of the investigated factors. Earlier development is clearly responsible for the emergence of either the balanced or the state-capture SBLR mode. Geographical conditions favorable for development, such as latitude and metal richness, also lead to the emergence of either mode. The communist heritage, and more accurately the post-communist economic and incomplete political liberalism of the transition stage, contributed to the emergence of the state-capture SBLR mode. The British legal system, with the power it provides to non-state actors through the independence of judges and other measures, contributes to the emergence of the balanced SBLR mode. Cultural factors are largely responsible for the emergence of the crony SBLR mode, especially hierarchical and collectivist cultures, as well as ethnic fractionalization. On the other hand, the culture of Confucians has the strongest influence on the emergence of state dominance, while other cultures play a marginal role in its rise, and ethnic fractionalization marginally defuses the ability of the state to dominate without resorting to favoritism. Finally, access to rich natural resources, by enriching the state independently from social actors’ financial resources (e.g. taxation), marginally increases the probability of the emergence of the state-dominance mode.

There is room for path dependency to explain the emergence of different SBLR modes in many countries. Unfortunately, the introduced regression model and any quantitative empirical work would not be able to effectively investigate such a process. Instead, an approach depending on case studies and a deeper investigation of country-specific historical political development is needed to complement the research done here. Conducting such an additional quest would help in reaching a more comprehensive understanding of why different countries have different SBLR modes. This should ultimately help in answering an equally important question: How to reverse engineer the emergence of favorable SBLR modes?

Although this paper did not investigate the economic merits or mischiefs of each of the studied modes, it is plausible to think of the balanced SBLR as the best mode. This is supported not only by the fact that most of the countries of this mode are developed countries but also by the attractiveness of the power dynamics governing this mode—a more balanced power among different SBLR actors. While some factors are almost impossible to replicate, for example, geographical factors, reform could target the factors that could be changed or mitigated. This is true for legal reform, especially for fostering the independence of judges. Culture is often regarded as a sticky institution. However, this is not always true, even though the change happens in the long run. A sort of dynamism should always be considered when referring to culture through time and space. Institutional reform could be instrumental in the long run in this regard. Conducting such reform with the help of such “exogenous” institutions should always consider the match between these institutions and “endogenous” institutions, such as culture. That is to say, the connection between democratization, fostering accountability and curbing favoritism and cultural values leaning toward these principles should be firmly established. Finally, a point of optimism is that—based on the results of this paper—reaching a high state of development could increase the chances of realizing a more balanced SBLR mode in the long run.

This paper represents a novel contribution to a topic that has hardly been addressed in the literature. The methodology that is used identifies different state–society relation modes and focuses on power relations in SBLRs is another important contribution to the present literature in many fields, such as institutional economics, socioeconomics and political economy.

The quality of maternal healthcare training is the most optimal degree of health in the delivery of effective, efficient and quality healthcare in midwifery discipline. Student accoucheurs studying at the Free State School of Nursing are faced with resistance, discrimination, rejection and unacceptability by pregnant women during their clinical placement at the Free State maternal healthcare institutions. This results in poor quality of training of student accoucheurs in maternal healthcare. Considerable studies have been conducted on males in midwifery nursing, but no guidelines have been developed to facilitate student accoucheurs' acceptance and improvement of the quality of training in maternal healthcare, hence the purpose of this study.

A descriptive, explorative qualitative design was used in this study. Qualitative focused group discussions (n = 32) were conducted through purposeful sampling method. Data was analysed thematically.

Three main categories emerged: student accoucheurs' related factors with social interactions and relations as a theme; maternal healthcare users’ related factors with transcultural diversity and socio-economic status as themes; nurse training institutions and maternal healthcare institutions service providers-related factors with gender inequality in the work place as a theme. Ultimately, the guidelines to facilitate acceptance and improvement of quality training of student accoucheurs in maternal healthcare institutions were developed and recommended for implementation.

The paper developed guidelines to facilitate acceptance and improvement of quality training of student accoucheurs in Free State maternal healthcare institutions.

The South African wool industry is integral to the country's agricultural sector, particularly sheep farming and wool production. Small-scale farmers play a vital role in this industry and contribute to employment and food security in rural communities. However, these farmers face numerous challenges, including a lack of funding, poor farming practices and difficulty selling their wool at fair prices. This study aims to address these challenges, the University of Free State launched a wool value chain project for small-scale farmers.

In this project, one of the studies conducted assessed the effectiveness of different detergents suitable for traditional wool scouring methods for small-scale farmers who lack access to sophisticated machinery. The investigation was conducted by scouring 160 wool samples using three different detergents and filtered water as a control. The wool samples were then evaluated for their cleanliness, brightness and fibre properties through a combination of scanning electron microscopy, spectrophotometry and statistical analysis at different scouring times (3, 10, 15 and 20 min, respectively).

The results showed that the combination of scouring time and the type of scouring solution used could significantly impact wool quality. It was found that using a combination of standard detergent or Woolwash as a scouring solution with a scouring time of 10–15 min resulted in the best outcome in terms of fibre property, wool colour and scouring loss.

This study demonstrated that traditional wool scouring methods could be an option for small-scale farmers and anyone who want to learn how to scour wool without expensive machinery to make wool products.

After being forced to flee their respective home countries, Sri Lankan Tamils and Rohingya refugees resettled in the Indian state of Tamil Nadu. This study attempts to explore the extent to which the state has provided means for integration in the absence of refugee protection laws and citizenship.

A qualitative research approach was used, including in-depth interviews (IDIs) and focus group discussions (FGDs) with participants from both refugee groups between 2019 and early 2020. A representative sample of male and female Sri Lankan Tamils, living in or outside government camps, in urban and rural areas, was included (total number = 75). Similarly, a representative sample of the Rohingya refugee community was included for this study (n = 44).

Despite constraints imposed by inadequate infrastructure, the study finds that Sri Lankan Tamils and Rohingyas both show to be progressively integrated in local society and have been capable of fulfilling some important basic livelihood needs, especially with regards to education. Some areas for improvement are identified as well, most urgently in terms of health and accommodation.

Other states in India, as well as in similar low-income countries (LICs), could learn from the current case study with regards to administering workable policies for small groups of refugees.

With minimal state facilitation and within the context of limited legal backing, refugee groups have somewhat managed to re-built their lives. This study identifies the threshold of requirements that make this achievement possible and suggests what more could be done to further advance the current state.

Since the financial crisis, East Asian countries have worked on bilateral/regional Free Trade Agreements (FTAs). Currently, East Asian countries are working on over 30 FTAs. So far, the United States (U.S.) has exerted its considerable political and economic power in East Asia, but its political and diplomatic position is increasingly shaky for many reasons-emergence of China’s economic and military strength, growing regionalism in East Asia, weakening influence of the Asia Pacific Economic Conference (APEC) forum, and growing anti-American sentiment after the anti-terrorism war. The U.S. will be even more concerned about the development of FTAs in East Asia, since the country will suffer economic and non-economic losses when the East Asian regionalism is developed. This article evaluates a U.S.-Korea FTA in terms of U.S. involvement in East Asian regionalism, and tries to provide an economic assessment of the FTA. This article points out that the U.S. should take advantage of the U.S.-Korea FTA to secure its interests in East Asia and to avoid exclusion from East Asian regional economic integration.