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Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction.

Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes.

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

The quality of voluntary sector-led community health programmes is an important concern for service users, providers and commissioners. Research on the fidelity of programme implementation offers a basis for assessing and further enhancing practice. The purpose of this paper is to report on the fidelity assessment of Living Well Taking Control (LWTC) – a voluntary sector-led, community-based education programme in England focussing on the prevention and management of type 2 diabetes.

This fidelity of implementation (FoI) study was conducted with the Devon-based LWTC programme. A fidelity checklist was developed to analyse audio records of group-based lifestyle education sessions – implementation was rated in terms of adherence to protocol and competence in delivery; the influence of wider contextual factors was also assessed. Kappa statistics (κ) were used to test for inter-rater agreement. Course satisfaction data were used as a supplementary indicator of facilitator competence.

Analysis of 28 sessions, from five diabetes prevention and two diabetes management groups (total participants, n=49), yielded an overall implementation fidelity score of 77.3 per cent for adherence (moderate inter-rater agreement, κ=0.60) and 95.1 per cent for competence (good inter-rater agreement, κ=0.71). The diabetes prevention groups consistently achieved higher adherence scores than the diabetes management groups. Facilitator competence was supported by high participant satisfaction ratings.

An appropriate level of implementation fidelity was delivered for the LWTC group-based education programme, which provides some confidence that outcomes from the programme reflected intervention effectiveness. This study demonstrates the viability of assessing the FoI in a voluntary sector-led public health initiative and the potential of this method for assuring quality and informing service development.

The reduction of costs has a more and more relevant role in the healthcare context, therefore, a large effort is done by health providers to this aim, for example, by reducing the length of hospital stay (LOS) of patients undergoing surgery. Fast track surgery fits perfectly this issue and was applied to patients undergoing knee replacement surgery due to Osteoarthritis, one of the most common diseases of aged population. The paper aims to discuss these issues.

Lean six sigma was applied to analyze the implementation of fast track surgery through the define, measure, analyze, improve, control roadmap, used as a typical problem-solving approach. It is characterized by five operational phases, which make possible the achievement of fixed goals through a rigorous process of defining, measuring, analyzing, improving and controlling business problems.

The corrective action, consisting in the application of fast track surgery, improved both effectiveness and efficiency of the process of care. The average length of hospital stay (LOS) was reduced from 8.34 to 6.68 days (–19.9 percent) and its standard deviation from 2.41 to 1.99 days (–17.1 percent). The statistical significance of this decrease was verified by means of proper tests. Moreover, some variables influencing the LOS were identified.

The follow up and the satisfaction of patients were not analyzed and could be a future development of this study.

Patients will experience a faster recovery while the hospital will benefit from a rise of available beds. The effect is a general improvement of hospital management.

The introduction of fast track surgery for patients undergoing knee replacement surgery made significantly reduce LOS and, consequently, costs’ with a money saving of more than 50,000 euro per year.

The purpose of this paper is to evaluate the economic benefits of managing an outpatient appointments system with technological innovations.

This study uses a quantitative methodological procedures aiming to evaluate the cost-benefit relation and also the payback of the management and operation of an outpatient appointments system with technological innovations.

This study found a great benefit-cost relation of 30.6 showing the great economic value and social impact of managing an outpatient appointments regulation system with technological innovations.

This study presents contribution to the literature discussion about the economic evaluation of the benefits of managing and operating more effective outpatient appointments systems because of important technological innovations.

This paper presents and discusses the most important and commonly used strategies and technological innovations to deal with and to manage an outpatient appointment regulation system aiming to reduce the patient no-show rates.

The findings of this study show a great benefit-cost relation of about 30.6 which is being reverted to the society.

There not exist many similar studies in the pertinent literature, mostly with the Brazilian contexts.

The paper examines how accounting and accounting experts provided important contributions to the Italian government's strategy to address the COVID-19 emergency in 2020, especially in terms of implementing new rules of conduct and providing justification for penetrating interventions in the life of individuals.

The paper adopts an interdisciplinary approach by drawing upon Agamben's concepts of the state of exception, bare life and biosecurity to understand the purposes of the decrees issued by the Italian government and data provided to the citizens in the “daily bulletin” on the crisis by the Civil Protection Department.

Accounting data provided essential contributions to the government's strategy that sought to spread disquiet and uncertainty in the population to ensure compliance with the strict rules in place, thereby sustaining the management of the country under a state of exception.

The study draws attention to the way in which accounting provides justification for measures that are promoted as provisional but which have enduring effects, most importantly the ability of governments in the future to suspend the rights of individuals. It shows how accounting can influence people's behaviour and contribute to the development of a permanent state of exception that significantly increases government prerogatives.

The work contributes to the literature on accounting and emergencies by studying the use of accounting information as a subtle means to ensure support for extreme government actions and ultimately as a political tool that promotes biosecurity as a new government paradigm.

The purpose of this paper is to propose a framework to improve the effectiveness of university–industry collaboration (UIC). This work enhances the existing body of literature and knowledge regarding collaboration and offers concrete steps to be taken for effective collaboration between universities and industries.

A literature review to study the best practices, impediments to collaboration and the various models proposed in the past for successful UIC was conducted. A workshop and focus-group meetings of practitioners and academic researchers was designed and organised to explore the current state of the university–industry engagement within the Australian Capital Territory (ACT) region and gather inputs regarding possible approaches to improve collaboration. The findings from the literature review and the results from this qualitative research regarding the approaches to improve the effectiveness of the collaboration were analysed.

The study discovers that various measures have been proposed in the form of best practices or models to improve the effectiveness of UIC. However, these measures often address a specific concern such as technology transfer, intellectual property (IP), etc. There is a scope for a comprehensive holistic framework to address many aspects of UIC in order to improve effectiveness and achieve success. A framework for improving the effectiveness of collaboration considering a comprehensive list of factors operating in a broad context within the collaboration system was proposed.

The framework builds on previous literature dealing with measures for successful UIC. However, it is the first of its kind, in the researcher's knowledge, in terms of comprehensiveness of the factors contributing to establishing and sustaining successful collaboration. The value of the individual experience of the participants in this qualitative research, which is on average more than 10 years in the software engineering field, validates the importance and quality of the data collected. The addition of these results to the framework increases its validity.The framework can be utilised by universities and industry practitioners to foster successful and effective collaboration. The results have significant relevance, particularly within the Australian context as the government has intensified the adoption of measures to encourage and improve collaboration between universities and the industry.

Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model policies for different driving situations.

In this research, a probabilistic decision-making method based on the Markov decision process (MDP) is proposed to deduce the optimal maneuver automatically in a two-lane highway scenario without using any human data. The decision-making issues in a traffic environment are formulated as the MDP by defining basic elements including states, actions and basic models. Transition and reward models are defined by using a complete prediction model of the surrounding cars. An optimal policy was deduced using a dynamic programing method and evaluated under a two-dimensional simulation environment.

Results show that, at the given scenario, the self-driving car maintained safety and efficiency with the proposed policy.

This paper presents a framework used to derive a driving policy for self-driving cars without relying on any human driving data or rules modeled by hand.

One of the biggest challenges in the health sector is that of costs compared to economic resources and the quality of services. Hospitals register a progressive increase in expenditure due to the aging of the population. In fact, hip and knee arthroplasty surgery are mainly due to primary osteoarthritis that affects the elderly population. This study was carried out with the aim of analysing the introduction of the fast track surgery protocol, through the lean Six Sigma, on patients undergoing knee and hip prosthetic replacement surgery. The goal was to improve the arthroplasty surgery process by reducing the average length of stay (LOA) and hospital costs

Lean Six Sigma was applied to evaluate the arthroplasty surgery process through the DMAIC cycle (define, measure, analyse, improve and control) and the lean tools (value stream map), adopted to analyse the new protocol and improve process performance. The dataset consisted of two samples of patients: 54 patients before the introduction of the protocol and 111 patients after the improvement. Clinical and demographic variables were collected for each patient (gender, age, allergies, diabetes, cardiovascular diseases and American Society of Anaesthesiologists (ASA) score).

The results showed a 12.70% statistically significant decrease in LOS from an overall average of 8.72 to 7.61 days. Women patients without allergies, with a low ASA score not suffering from diabetes and cardiovascular disease showed a significant a reduction in hospital days with the implementation of the FTS protocol. Only the age variable was not statistically significant.

The introduction of the FTS in the orthopaedic field, analysed through the LSS, demonstrated to reduce LOS and, consequently, costs. For each individual patient, there was an economic saving of € 445.85. Since our study takes into consideration a dataset of 111 patients post-FTS, the overall economic saving brought by this study amounts to €49,489.35.

The goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).

The methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.

The authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.

The methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.

The Italian government addressed the first wave of its COVID-19 outbreak with a series of social restrictions and calculative practices, all branded with the slogan #istayathome. The hashtag quickly went viral, becoming both a mandate and a mantra and, as the crisis played out, we witnessed the rise of the Italian social movement #istayathome. This study examines how the government's calculative practices led to #istayathome and the constituents that shaped this social movement.

The authors embrace social movement theory and the collective identity perspective to examine #istayathome as a collective action and social movement. Using passive netnography, text mining and interpretative text analysis enhanced by machine learning, the authors analysed just over 350,000 tweets made during the period March to May 2020, each brandishing the hashtag #istayathome.

The #istayathome movement gained traction as a response to the Italian government's call for collective action. Thus, people became an active part of mobilising collective responsibility, enhancing the government's plans. A collective identity on the part of the Italian people sustained the mass mobilisation, driven by cohesion, solidarity and a deep cultural trauma from COVID-19's dramatic effects. Popular culture and Italy's long traditions also helped to form the collective identity of #istayathome. This study found that calculative practices acted as a persuasive technology in forming this collective identity and mobilising people's collective action. Numbers stimulated the cognitive, moral and emotional connections of the social ties shaping collective identity and responsibility. Thus, through collective identity, calculative practices indirectly influenced mass social behaviors and the social movement.

This study offers a novel theoretical perspective and empirical knowledge to explain how government power affects people's culture and everyday life. It unveils the sociological drivers that mobilise collective behaviors and enriches the accounting literature on the effects of calculative practices in managing emergencies. The study contributes to theory by providing an understanding of how calculative practices can influence collective behaviors and can be used to construct informal networks that go beyond the government's traditional formalities.