Abstract
Background and aims: currently, most endoscopy software only provides limited statistics of past procedures, while none allows patterns to be extrapolated. To overcome this need, the authors applied business analytic models to pre-dict future demand and the need for endoscopists in a ter-tiary hospital Endoscopy Unit. Methods: a query to the endoscopy database was per-formed to retrieve demand from 2015 to 2021. The graphi-cal inspection allowed inferring of trends and seasonality, perceiving the impact of the COVID-19 pandemic, and se-lecting the best forecasting models. Considering COVID-19's impact in the second quarter of 2020, data for esoph-agogastroduodenoscopy (EGD) and colonoscopy was estimated using linear regression of historical data. The actual demand in the first two quarters of 2022 was used to validate the models. Results: during the study period, 53,886 procedures were requested. The best forecasting models were: a) simple sea-sonal exponential smoothing for EGD, colonoscopy and percutaneous endoscopic gastrostomy (PEG); b) double ex-ponential smoothing for capsule endoscopy and deep en-teroscopy; and c) simple exponential smoothing for endo-scopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS). The mean average percent-age error ranged from 6.1 % (EGD) to 33.5 % (deep en - teroscopy). Overall, 8,788 procedures were predicted for 2022. The actual demand in the first two quarters of 2022 was within the predicted range. Considering the usual time allocation for each technique, 3.2 full-time equivalent en-doscopists (40 hours-dedication to endoscopy) will be re-quired to perform all procedures in 2022. Conclusions: the incorporation of business analytics into the endoscopy software and clinical practice may enhance resource allocation, improving patient-focused deci-sion-making and healthcare quality.

Abstract
Original Equipment Manufacturers (OEMs) have sought new supply chain paradigms that allowed them to focus on core activities, i.e. overall product design and commercialisation. This pursuit led to partnerships with a new generation of tier-1 strategic suppliers acting as integrators. Integrators are not only responsible for system supply, but also for system design. However, critical integrators were not able to live up to their new roles, which led to costly delays in development and production. These failures highlight the ineptitude of current risk management practices employed by OEMs. To support OEMs in implementing a more differentiated and suitable approach to the use of integrators, this paper proposes a mathematical programming model for Supply Chain Design (SCD). Instead of looking at the introduction of integrators as a dichotomous decision, the model suggests the optimal number of integrators, i.e. systems, and individual part suppliers. We propose new measures for integration risk, which build upon current risk assessment practices. Robust optimisation is used to study the effect of uncertainty over baseline risk values. All approaches were tested using both randomly generated instances and real data from a large European OEM in the aerospace industry.

Abstract
Due to an increase in population, urban centers are currently seeing an increase in traffic, resulting in negative consequences such as pollution and congestion. Efforts have been made to promote a modal shift towards the use of more sustainable means of transport, such as walking and cycling, but several deterrents influence the citizens' perceptions of safety, security and comfort, discouraging their choice of active modes of transport. This study focuses on the importance of providing meaningful information to vulnerable road users (VRUs) to support their perceptions and objectives while moving within urban spaces through a novel concept of route planning. A broad survey of the needs and concerns of VRUs through interviews, focus groups and questionnaires, applied to the Portuguese population of the Metropolitan Area of Porto, led to the development of a new concept of route planners that show personalized routes according to the individual perceptions of each user. This concept is materialized in a route planner prototype that has been extensively tested by potential users. Subjective evaluation and feedback showed the usefulness of the concept and added value to a familiar product, leading to a satisfying experience for participants. This study shows that there is an opportunity to improve these tools to provide a higher degree of power and customization to users on route planning, which includes addressing mobility restrictions and personal perceptions of safety, security and comfort. The ultimate goal of this new approach is to persuade citizens to switch to more sustainable means of transport.

Abstract
Promoting active modes of transport, such as walking and cycling, has a positive impact on environmental sustainability and the health and well-being of citizens. This study explores the elderly population’s perception of comfort, safety and security when using active modes of transport. It begins with a systematic review of the literature considering research works that relate to active travel, the elderly population, and random forest. Then a questionnaire was applied to 653 participants and the results were analyzed. This analysis consisted of using statistics to evaluate the socio-demographic profile, the preferences regarding the use of active modes of this population, and the importance given to each dimension: comfort, safety, distance, and time, comparing these indicators through the Wilcoxon Rank Sum test and the Random Forest algorithm. The results showed that people over 56 years old walk as much as younger people. Furthermore, the importance given by this group of people to indicators referring to active modes is related to safety and security, distance, time, and comfort. The statistical results of the Wilcoxon Rank Sum test indicate the most important indicators: Adequate Travel Distance & Time and Existence of Commercial Areas by age group [0–55], and Absence of Allergenics and Existence of Green Areas by age group [56+]. Finally, the Random Forest algorithm provides the relative importance for both age groups, [0–55] and [56+], where the indicators that stand out in the [56+] age group, which is the focus of our study, are air quality, adequate travel distance & time, adequate crowd density, adequate thermal sensation, absence of allergenic, good street illumination level, adequate traffic volume, and adequate noise level. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
This article presents a framework to assist in the design of technology-based interactive services for active mobility, which allows the data collected from the sensors to be made available to citizens. The proposed framework was developed based on data collected in focus group sessions held with potential stakeholders and on related models and frameworks. It consists of 8 steps, namely: strategy, scope, structure, skeleton, aesthetics and execution. It will enable the presentation of relevant information that will help users of active modes of transport in decision making in choosing a safe and comfortable route, assist professionals involved in the elaboration of interactive projects and promote more collaborative urban planning. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract