ABSTRACT
Ecotourism is a potential lever for sustainable development, but common standards and approaches lack to manage and monitor the impact of defined packages on natural resources and local communities. A customized version of Ecological Footprint Accounting is evaluated here to assess its usefulness as analytical tool to quantitatively analyse the environmental pressures associated with ecotourism packages developed in and around Protected Areas in the Mediterranean Region. Within the framework of the EU-funded DestiMED project, a bottom-up, participatory approach was developed for managing and monitoring 13 ecotourism packages by involving local tourism stakeholders and service providers. The application of Ecological Footprint Accounting relied on data sourced from local service providers to complement existing statistics and datasets, and was used in an empirical iterative process to provide local tourism stakeholders with recommendations to guide them in the management of a low-impact tourism offer. International travel to and from the 13 destinations was found to place a Footprint on the environment - mainly because of carbon emissions - higher than that of the entire stay at destination. Footprint results of the packages revealed some overlooked tourism's impacts on ecosystems due to unexpected drivers, such as the Food & Drink services offered to tourists at destination. Results indicate that managing tourism product development at destination, and investing in providing knowledge on the principles of sustainability, could lower ecotourism's impacts whilst contributing to building resilience and aiding the post-COVID recovery of destinations. Management implications: This article tested the applicability and usefulness of Ecological Footprint Accounting (EFA) to assess ecotourism packages developed in and around Protected Areas (PAs) across the Mediterranean Region. A customized version of Ecological Footprint Accounting is suitable for managers and can be used to quantitatively assess the multiple pressures of the activities included in ecotourism packages through a bottom up approach. This innovative monitoring process typically fosters the engagement with the local service providers, which is key for a sustainability monitoring of the touristic offer. Applied to ecotourism packages, EFA allows identifying the main ecosystems under pressure as well as the main drivers causing such pressures. This information is useful to understand the actual impacts caused by the packages offered in their territory, and - when combined with tangible recommendations for improvements - to help adjust the services offered in the packages to possibly reduce environmental impacts.
ABSTRACT
In recent times, COVID-19 pandemic has more influence on universal health and affects the daily lives of people all over the globe. Many of the initial screening tests are based on the detection of the genetic material of the coronaviruses, and it resulted to a minimum detection rate with high computation time. Several studies reported that the radiological images like CXR images find useful in the diagnosis process of COVID-19. In this view, this paper presents an intelligent COVID-19 diagnosis technique using multimodal fusion-based deep learning (MMFBDL) technique. The proposed MMFBDL model involves Wiener filtering (WF)-based preprocessing to remove the noise exist in the test CXR image. Then, three DL models are Residual Network (ResNet152), Inception v4 and Densely Connected Network (DenseNet). In addition, a multimodal fusion process is carried out where all the three models are fused together to increase the classification performance. Finally, multilayer perceptron (MLP) is applied to detect and classify the input images into distinct class labels. In order to examine the effective classifier outcome of the MMFBDL model, a comprehensive set of simulations takes place and the experimental values ensured that the MMFBDL model has resulted to a maximum accuracy of 98.12%. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
PURPOSE: In 2020, the COVID-19 pandemic forced global lockdowns. Herein, we examine the effect of a lockdown exercise programme in a case-study of youth Australian A-league academy football players. METHODS: Fifty-five u13-u15 age-grade players were provided with a 110 minute exercise programme including technical, tactical, cardiovascular and muscle strengthening exercises to perform 4 per week at home during the 10-week COVID-19 lockdown. RESULTS: Pre/Post lockdown, maximum aerobic speed was determined via the 30-15 intermittent fitness test (IFT). Exercise compliance was high (78.5% CI72.2-83.8) with an average of 3.15 sessions completed each week. All time-loss (TL) and medical attention (MA) injuries were recorded. Pre/Post lockdown, no difference in the mean incidence or burden of total time-loss (TL), match TL, training TL or medical attention (MA) injuries or injury rate ratio (1.21 CI:0.85-2.74) was observed. Similarly, no difference was observed in any injury incidence or burden data or the injury rate ratio (1.53 CI:0.85-2.74) when comparing the 9-week period prior to lockdown with the first 9 weeks post lockdown (9v9 only). A 9.6% (p = <0.01) increase was also observed in Pre/Post 30-15 IFT composite scores (18.7 CI: 18.3-19.1 to 20.5 CI:20-21). CONCLUSION: In this case study, compliance to the home-based exercise programme was high and no increase in injury was apparent. These findings must however be considered alongside the limitations associated within this case-study.