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To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

The purpose of this paper is to present the use of a free code computational tool, Patent2net, in the search of patents for the implementation of distance learning aimed at Continuing Medical Education.

This technical report is based on the extraction, organization and availability, in the format of graphs and dynamic tables, and also based on information in other patents on the subject, made available in the Espacenet database.

As a result, it was possible to identify a Chinese patent, free for reproduction in Brazil, which describes an e-learning system that simulates 3D scenarios for training nursing teams.

The paper has used one unique patent database, but containing more than 100m documents.

The selected patent can contribute to the improvement of care and behavioral techniques of the health professionals.

The training of health professionals can improve the public and supplementary health systems.

This is the first paper in that de technometric analisys of patents was used to solve a problem regarding the training of health professionals.

Jambolan has be used as a diabetes-treatment aid, and it has become quite popular; studies have been carried out over the years on this fruit because it presents high activity against superoxide anion and hydroxyl radicals due to the bioactive compounds that may play an important role against oxidative stress. No studies have been reported on the effects of pasteurization on the bioactive compounds of jambolan tropical juice. The paper aims to discuss these issues.

For evaluation of the effects of pasteurization on jambolan juice bioactive compounds, a complete compound and rotational experimental design was carried out by varying temperature (80–90°C) and time (45–75 s). The bioactive compounds (total phenolic, total anthocyanin and antioxidant activity) and the enzymatic activity of enzymes (enzymatic browning) were assessed.

The study of bioactive compounds in the pasteurized juice of jambolan, showed that the total phenolics (TP) and ABTS antioxidant activity presented statistical significance (p<0.05). The action of enzymes causing enzymatic browning was only observed in the standard sample. The optimization of the pasteurization process with the maximum bioactive compound retention was 91.65°C for 69.45 s. The optimal point found is in agreement with studies on thermal treatment that recommend using short times at high temperatures for better retention of food constituents.

The incidence of chronic diseases in humans has increased significantly over the years, some bioactive phytochemicals present in fruits may help against these diseases, so the production of tropical jambolana juices can help to nourish and regulate the consumer health. Therefore, studying the maintenance of bioactive compounds present in this product could be an alternative for the production of healthier foods.

Currently, several studies have been published using sensorized insoles for estimating ground reaction force using plantar pressure. However, information on design parameters, manufacturing techniques and guidelines for developing insoles is scarce, often leaving gaps that do not allow reproducing the insole. This study aims to empirically investigate the main parameters of constructing a sensorized insole for application in human gait.

Two devices were built to evaluate the force sensors. The first focuses on the construction of the sensors with different settings: the density of the sensor’s conductive trails (thickness and distance of the trails) and the inertia of the sensors (use of spacers to prevent unwanted readings). The second device focuses on the data capture and processing system: resolution of the analog–digital converter, acquisition rate and sensor activation level.

The resolution increase of the analog–digital converter and acquisition rate do not contribute to noise increase. Reducing the sensors’ coverage area can increase sensorized insole capacity. The inertia of the sensors can be adjusted using spacers without changing the electrical circuit and acquisition system.

Most sensorized insoles use commercial sensors. For this reason, it is not possible a full customization. This paper maps the main variables to manufacture custom sensors and data acquisition systems. This work also presents a case study where it is possible to see the influence of the parameters in the correlation between the sensorized insole and an instrumented treadmill with a force platform.

The aim of this article is to investigate individuals' attitudes about organizational change, considering implementation of business process management (BPM) and resistance to change.

The study examines the attitudes of subjects that experienced organizational change in the context of BPM in Brazil. In order to measure resistance to organizational change, 22 interviews were conducted using a script adapted from Pereira et al. (2019). The study considered two main agents: BPM implementers and end-users. Data were analyzed qualitatively via content analysis.

The results provided interesting insights. In relation to the individuals' attitudes, satisfaction, fear, stress and anxiety were the most frequently reported. However, opinions contradict the negative feelings expressed, given that organizational benefits, facility and pleasure at work and personal benefits were the most frequently reported. In regard to behavior, individuals approved change and in general accepted it. Finally, in terms of confidence in management, the subjects reported leadership and trusting their bosses as positive points.

Study limitations include the difficulty in finding end-users on LinkedIn, the fact that convenience sampling was used and the possible false memory of respondents.

The approach used in this study provided a relevant contribution to the area under study, primarily via the new findings, that is, elements of resistance to change that emerged from the data.

The adverse effect of plastic pollution on the tourism industry is one of the emerging research areas in the field of sustainable tourism over the past years. However, there is a lack of discussion on this issue in the academic platforms. Considering this, in this chapter, a scientometric analysis of 110 academic publications from the Web of Science (WoS) between 1999 and 2021 related to plastic pollution and tourism is presented. A bibliometric analysis using CiteSpace was utilised to analyse the data to present the keyword timezone, collaboration network and co-citation network. The analysis shows that the publications in this field have increased rapidly, and it has become an emerging and interdisciplinary research topic. Scholars from Australia, Spain, Brazil and China have published most on the topic. The Chinese Academy of Science with four articles is the largest contributor in this field among other institutions. Moreover, citizen science is found to be a new keyword coming up in recent years, and human health is one of the major concerns. The findings from this study provide valuable insights for the academicians and policy makers in understanding the issue.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.