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The modelling and prediction of traffic flow is one of the future challenges for science. We present a simulation tool for an urban road network based on real-time traffic data and a cellular automaton model for traffic flow. This tool has been applied to the inner city of Duisburg. The quality of the reproduced traffic states is investigated with regard to vehicle densities and typical features of urban traffic.

This paper analyses how social workers in the German child protection system rhetorically frame their cases, and how their rhetoric defines its categorical labels corresponding to positions of gender and generation: to what degree are mothers considered as perpetrators and children as victims? Seventy case narrations of social workers on the frontline are analysed regarding the rhetorical idioms they applied. The results show that violence is an irrelevant interpretive framework for the social problems at work in child protection. Instead, irresponsible mothers and their limited agencies are staged front and centre. Categories of limited agency serve as rhetorical devices for the social workers to justify diverse decisions ranging from implementing interventions to terminating the professional-client relationship due to the labelling of the mother as mentally ill. As the rhetorical idiom of unreason does not operate with categories of perpetration and victimization, equivalences for the labels of the practical objectives of victimization are analysed. Consequently, the responsibility of the mother is deflected as her limited agency is seen as a product of troubling conditions. In turn, children are either ignored as victims or even treated as a troubling condition for the mothers’ limited agency. This may lead to the blacking out of the adverse consequences of child abuse and neglect as well as of possible resources for the children to avoid or prevent violent situations. In this way, child protection helps the reproduction of the generational order, which is the basis for child abuse and neglect.

Social media have become the main channel of direct communication between members of parliament and constituents. The study analyzes the content in all Israeli MPs' Facebook channels throughout an entire term of parliament and asks if the results are consistent with the equalization or the normalization hypotheses.

The study uses automatic analysis to produce a birds-eye-view of the content uploaded to the Facebook pages of all Israeli MPs during a full term of parliament. All 106 MP pages were automatically scraped. Some complementary information was added to each post in the dataset, such as post length (number of words) and whether the page belongs to a member of the opposition or coalition. The total of 441,974 posts was analyzed to compare engagement and publication rates between pages, coalition vs opposition MPs, MPs vs users etc.

The findings demonstrate that the MP-Facebook sphere is non-egalitarian, in that it follows skewed distributions by MPs in terms of post publication and engagement rates; non-inclusive, in that pages of coalition members receive significantly much more engagement vis-a-vis pages of members of the oppositions; and “top-down”, in that MP-authored posts receive dramatically more engagement then user-authored posts, suggesting MPs have a near-monopoly on setting the agendas manifest in their pages, while users have extremely limited agenda-setting capabilities in these pages.

Previous studies have looked at the character of the interactions between MPs and constituents on the Internet and particularly on online social media. Yet, to the best of the authors’ knowledge, no study provides a birds-eye-view of the content in all MPs' Facebook channels throughout a full term of parliament. Such an analysis provides a more comprehensive understanding of the character and dynamics of conversations that take place in such arenas.

The performance of the classical car-following system is easily affected by external disturbances. To enhance the performance of the classical car-following model under sudden external disturbances, a novel car-following model is established to smooth traffic flow.

This paper proposed a Proportion Integration Differentiation (PID) control strategy based on classical control theory and developed a novel car-following model. The linear system theory and Laplace transform are used to derive a closed-loop transfer function. Then, the stability condition is obtained by using the Routh stability criterion and the small gain theorem. Finally, the validity and feasibility of the PID control strategy is proved by numerical simulations.

The analytic results and the numerical simulation results show that both the integration part and the differential part have the positive effect to suppress traffic oscillation efficiently; the collaboration of these two parts has more power to improve the stability of traffic flow. It means that the proposed model integrated with the PID control strategy has the ability of anti-interference and smooth traffic compared with the classical car-following model.

This paper introduces the PID control strategy into the classical car-following system, which enhances the stability of the system and also provides an efficient method for optimizing the traffic flow system.

The purpose of this paper is to compare qualitatively two methods for coordinating traffic lights: a static optimization “green wave” method and an adaptive self‐organizing method.

Statistical results were obtained from implementing a recently proposed model of city traffic based on elementary cellular automata in a computer simulation.

The self‐organizing method delivers considerable improvements over the green‐wave method. Seven dynamical regimes and six phase transitions are identified and analyzed for the self‐organizing method.

The paper shows that traffic light coordination can be improved in cities by using self‐organizing methods.

This improvement can have a noticeable effect on the quality of life of citizens.

Understanding how self‐organization obtains adaptive solutions for complex problems can contribute to building more efficient systems.

The aim is identifying and analyzing some well‐defined types of emergence where the paper uses ideas from machine learning and artificial intelligence to provide the model of cellular automata based on rough set theory and response in simulated cars.

This paper proposes, as practical part, a road traffic system based on two‐dimensional cellular automata combined with rough set theory to model the flow and jamming that is suitable to an urban environment.

The automaton mimics realistic traffic rules that apply in everyday experience.

The modeled development process in this paper involves simulated processes of evolution, learning and self‐organization.

Recently, the examination and modeling of vehicular traffic has become an important subject of research.

The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of the state machine behavior, which can give an emergent to the model.

The purpose of this paper is to propose a method that can calculate the transportation infrastructure network service capacity enhancement given by planned transportation infrastructure projects construction. Managers can sequence projects more rationally to maximize the construction effectiveness of infrastructure investments.

This paper designed a computational network simulation software to generate topological networks based on established rules. Based on the topological networks, the software simulated the movement path of users and calculated the average travel time. This software allows the adjustment of parameters to suit different research objectives. The average travel time is used as an evaluation index to determine the most appropriate construction sequence.

In this paper, the transportation infrastructure network of Sichuan Province in China was used to demonstrate this software. The average travel time of the existing transportation network in Sichuan Province was calculated as 211 min using this software. The high-speed railways from Leshan to Xichang and from Xichang to Yibin had the greatest influence on shortening the average travel time. This paper also measured the changes in the average travel time under two strategies: shortening the maximum and minimum priorities. All the transportation network optimisation plans for Sichuan Province will be somewhere between these two strategies.

The contribution of this research are three aspects: First, a complex network analysis method that can take into account the differences of node elements is proposed. Second, it provides an effective tool for decision makers to plan transportation infrastructure construction. Third, the construction sequence of transportation infrastructure development plan can effect the infrastructure investment effectiveness.

This paper aims to determine the impact of mentorship on the development of self-directedness among beginner teachers in their initial years of teaching.

The researcher adopted a positivist paradigm to explore the situation of concern. Quantitative research was conducted, involving the collection and analysis of numerical data. Two closed-ended structured questionnaires were utilised, derived from the 40-item self-directed learning readiness scale (SDLRS) developed by Fisher and King, and a pre-determined questionnaire by Glazerman focused on the first-year teaching experience, induction and mentoring of beginner teachers.

Beginner teachers merely relying on the knowledge obtained from their studies is insufficient to achieve a satisfactory level of self-directedness when starting a teaching career. Most beginner teachers faced significant challenges in their early years of teaching due to the absence of mentoring support. In addition, most indicated that they resume their teaching duties and rely on their district for general support, guidance and orientation. Finally, the results have shown that mentoring positively impacts beginner teachers’ self-directedness.

The first limitation was that this study was narrowed to one South Africa University part-time B.Ed honours students working as beginner teachers in different provinces at primary and secondary schools. As a result, the findings of this research might be interpreted by some critics as one-sided and not representative of the views of most beginner teachers in South Africa who are working. The second limitation of this study is the sample size. In this study, 222 responses were received. As a result, the findings of this research might be considered not representative of the target sample size.

The presence and effective implementation of mentoring programmes in schools can positively impact beginner teachers' professional development and retention during their first years of teaching.

We contend that our research holds significance for international readership as it aims to garner attention towards potential research endeavours in diverse settings concerning mentorship programs for beginner teachers, specifically promoting self-directed learning. Our research offers opportunities to compare our findings with studies conducted in more comprehensive, comparative contexts and foster research possibilities in broader, contrasting contexts.

Based on the findings of this research, the availability and effective use of mentoring programmes would significantly affect beginner teachers' self-directedness, improve their retention rate and alleviate their teaching challenges. This study was the first research on the perceptions of the influence of mentoring on the self-directedness of beginner teachers.

Since the outbreak of COVID-19 in early 2020, the travel sector has faced an intense challenge, making tourism one of the most affected sectors at the time of writing. Based on the results of a survey administered to a sample of 700 Italian tourists, this paper aims to acquire an empirical understanding of key challenges for the travel and tourism sector in the coming months and the possible responses of tourist cities.

To study tourism after the pandemic, OUT (University of Naples Tourism Research Center) has created an online survey to answer the following questions: What will tourism be like after the pandemic? What will the main changes in travel behaviors be? What role will new information technologies play in future tourism? Are there territorial differences based on the spread of the virus?

The pandemic has inevitably affected everyone’s tourist choices, regardless of how much their specific area of residence has been impacted by the virus. Consequently, it will significantly influence travelers’ experiences. The Italian tourists who were survey respondents are aware that physical distancing rules will probably remain in effect for an extended time and, therefore, they cannot imagine future tourism not conditioned by these measures. This does not mean that Italians will give up tourism in the short-medium term, however. Indeed, the research data highlight the resilient character of tourism in that it is transformed but does not cease to exist.

By studying the future through a sociological approach, it is possible to identify how the COVID-19 emergency will impact tourism and how both the form and social meaning of mobility will be conditioned. On the basis of the data, the analysis will be directed from the present to the post-pandemic horizon, hypothesizing possible scenarios for the future of tourism and providing some possible policy indications.