Real-time HSPA emulator for end-to-edge QoS evaluation in all-IP beyond 3G heterogeneous wireless networks

This paper is aimed at presenting the real-time High Speed Packet Access (HSPA) emulator that has been developed in the framework of the AROMA project. Real-time emula- tors allow reproducing realistic scenarios to test algorithms, strategies, protocols and applications under realistic condi- tions. Therefore, real-time emulators constitute a powerful tool to evaluate the end-user's Quality of Experience (QoE), which could not be achieved by means of o -line simulations. The presented emulator is integrated in the AROMA real- time testbed, which has been developed to provide a frame- work for demonstrating the bene ts of the common radio re- source management algorithms as well as the proposed end- to-edge Quality of Service (QoS) management techniques developed for all-IP beyond 3G heterogeneous wireless net- works in the context of the AROMA project. This paper presents a qualitative description of the developed tool, em- phasizing some interesting implementation details that may result helpful in the development of similar emulation plat- forms. Some illustrative results, showing the capabilities of the developed tool, are also presented and analyzed.Postprint (published version

Assessing the reliability of species distribution projections in climate change research

Aim: Forecasting changes in species distribution under future scenarios is one of the most prolific areas of application for species distribution models (SDMs). However, no consensus yet exists on the reliability of such models for drawing conclusions on species’ distribution response to changing climate. In this study, we provide an overview of common modelling practices in the field and assess the reliability of model predictions using a virtual species approach. Location: Global. Methods: We first review papers published between 2015 and 2019. Then, we use a virtual species approach and three commonly applied SDM algorithms (GLM, MaxEnt and random forest) to assess the estimated and actual predictive performance of models parameterized with different modelling settings and violations of modelling assumptions. Results: Most SDM papers relied on single models (65%) and small samples (N < 50, 62%), used presence-only data (85%), binarized models' output (74%) and used a split-sample validation (94%). Our simulation reveals that the split-sample validation tends to be over-optimistic compared to the real performance, whereas spatial block validation provides a more honest estimate, except when datasets are environmentally biased. The binarization of predicted probabilities of presence reduces models’ predictive ability considerably. Sample size is one of the main predictors of the real model accuracy, but has little influence on estimated accuracy. Finally, the inclusion of ecologically irrelevant predictors and the violation of modelling assumptions increases estimated accuracy but decreases real accuracy of model projections, leading to biased estimates of range contraction and expansion. Main conclusions: Our ability to predict future species distribution is low on average, particularly when models’ predictions are binarized. A robust validation by spatially independent samples is required, but does not rule out inflation of model accuracy by assumption violation. Our findings call for caution in the application and interpretation of SDM projections under different climates

Intact but empty forests? Patterns of hunting-induced mammal defaunation in the tropics

Tropical forests are increasingly degraded by industrial logging, urbanization, agriculture, and infrastructure, with only 20% of the remaining area considered intact. However, this figure does not include other, more cryptic but pervasive forms of degradation, such as overhunting. Here, we quantified and mapped the spatial patterns of mammal defaunation in the tropics using a database of 3,281 mammal abundance declines from local hunting studies. We simultaneously accounted for population abundance declines and the probability of local extirpation of a population as a function of several predictors related to human accessibility to remote areas and species’ vulnerability to hunting. We estimated an average abundance decline of 13% across all tropical mammal species, with medium-sized species being reduced by >27% and large mammals by >40%. Mammal populations are predicted to be partially defaunated (i.e., declines of 10%–100%) in ca. 50% of the pantropical forest area (14 million km2), with large declines (>70%) in West Africa. According to our projections, 52% of the intact forests (IFs) and 62% of the wilderness areas (WAs) are partially devoid of large mammals, and hunting may affect mammal populations in 20% of protected areas (PAs) in the tropics, particularly in West and Central Africa and Southeast Asia. The pervasive effects of overhunting on tropical mammal populations may have profound ramifications for ecosystem functioning and the livelihoods of wild-meat-dependent communities, and underscore that forest coverage alone is not necessarily indicative of ecosystem intactness. We call for a systematic consideration of hunting effects in (large-scale) biodiversity assessments for more representative estimates of human-induced biodiversity loss

Wearable Internet of Things - from Human Activity Tracking to Clinical Integration

Wearable devices for human activity tracking have been rapidly emerging. Most of them are capable of sending health statistics to smartphones, smartwatches or smart bands. However, they only provide the data for individual analysis and their data is not integrated into clinical practice. Leveraging on the Internet of Things (IoT), edge and cloud computing technologies, we propose an architecture which is capable of providing cloud based clinical services using human activity data. Such services could supplement the shortage of staff in primary healthcare centers thereby reducing the burden on healthcare service providers. The enormous amount of data created from such services could also be utilized for planning future therapies by studying recovery cycles of existing patients. We provide a prototype based on our architecture and discuss its salient features. We also provide use cases of our system in personalized and home based healthcare services. We propose an International Telecommunication Union based standardization (ITU-T) for our design and discuss future directions in wearable IoT