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Digital systems for independent aging, support and care are not being adopted as hoped. The purpose of this paper is to examine the results of three studies to derive key factors during the development and engineering process of care and support systems for older people that can impact acceptance and uptake to provide support to future projects.

The paper analyzed the results of three qualitative studies, including two detailed case studies and a further study with 35 participants, to derive key factors. Methods for deriving factors are based on thematic analysis to identify common factors across cases and participants.

The findings point to a broad set of interconnected factors that give developers of these types of systems specific recommendations. These highlight what makes these projects complex and identify implications for the development process. Furthermore, they show way the needed user-centered and iterative methods may be in conflict with funding processes.

While others have reported on single projects or looked at acceptance, these studies were the first to explore aspects of the development process that may contribute to the lack of success to date of these types of systems. The results here support more successful outcomes in the future, both by helping people involved in the development of these systems to avoid some of the issues others face and providing input to improve the performance of the engineering process.

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.

The purpose of this study is to evaluate the vulnerability of the important rangeland shrub, Atriplex leucoclada (Boiss) to both climate change and livestock grazing, within the Syrian rangelands as a representative landscape type of West Asia.

Ecologically based quantitative niche models were developed for both shrub species using maximum entropy and 13 spatially explicit GIS-based layers to predict current and future species distribution scenarios. Climatic variables varied over time in line with the predictions created from the HADCM3 global circulation model.

Results indicate that with grazing and climate change, the distribution of A. leucoclada will be reduced by 54 per cent in 2050, with the mean annual and minimum temperatures of the coldest month having the highest contribution in the model (28.7 and 21.2 per cent, respectively). The contribution of the grazing pressure, expressed by the overgrazing index, was estimated at 8.2 per cent.

These results suggest that the interaction of climate and increased grazing has the potential to favor the establishment of unpalatable species, while reducing the distribution of preferred plant species on western Asia rangelands.

The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.

Bahrain has set a national target of achieving carbon neutrality by 2060, with an interim goal of a 30% reduction in CO₂e emissions by 2035. The aim of this policy brief is to provide insights on how carbon neutrality in Bahrain can be achieved.

A review of literature related to climate change mitigation in general, and that related to Bahrain in particular, was carried out.

Given that the carbon intensity of Bahrain's economy is relatively high, achieving carbon neutrality requires not only technologies for reducing CO₂e emissions at the source and enhanced carbon sinks, but it also requires the introduction of a circular economy culture and efforts to foster pro-environmental behavior within the population. The involvement of different stakeholders in the journey toward carbon neutrality is critical, along with the formulation of requisite policies regulating the roles of technology, behavior and research.

Pathways to achieve carbon neutrality in Bahrain were explored, and areas for policy focus were recommended.

The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift.

A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population.

Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies.

Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management.

The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.

The purpose of this study is to review literature on the relationship between leadership and workplace learning, to critically analyze and discuss findings and to suggest future research paths based on the synthesis.

This study applied a refined literature review process leading to a selection of 40 articles, which originated from 14 internationally acclaimed journals.

When explaining leadership influence regarding individual and team learning, the concepts of role modeling behavior, relational support and negotiation of meaning is significant. If leaders provide support, show exemplary behavior and negotiate individual arrangements with employees, workplace learning development is positively affected.

Future studies should focus on empirical cases further illustrating how the leader–employee relationship is formed in practice, to further understand differences in leadership influence on employee workplace learning.

The gathered knowledge implicates that carefully designed leadership training programs and personalized work arrangements between leader and employees are beneficial for leader’s ability to influence employee workplace learning.

The reviewed studies were solely published in top management journals, which resulted in an original literature selection. This study also discusses implicit or articulated assumptions about the view of learning in the selected studies, offering additional understanding about the underlying learning views in leadership–workplace learning research.