A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees

International Conference Image Analysis and Recognition (ICIAR 2018, Póvoa de Varzim, Portugal

Analysis of nucleation events in the European boundary layer using the regional aerosol-climate model REMO-HAM with a solar radiation-driven OH-proxy

This work describes improvements in the regional aerosol–climate model REMO-HAM in order to simulate more realistically the process of atmospheric new particle formation (NPF). A new scheme was implemented to simulate OH radical concentrations using a proxy approach based on observations and also accounting for the effects of clouds upon OH concentrations. Second, the nucleation rate calculation was modified to directly simulate the formation rates of 3 nm particles, which removes some unnecessary steps in the formation rate calculations used earlier in the model. Using the updated model version, NPF over Europe was simulated for the periods 2003–2004 and 2008–2009. The statistics of the simulated particle formation events were subsequently compared to observations from 13 ground-based measurement sites. The new model shows improved agreement with the observed NPF rates compared to former versions and can simulate the event statistics realistically for most parts of Europe

Implementation of the CORINE land use classification in the regional climate model REMO

Regional climate models provide an effective way to study the effects of land use changes on regional climate conditions. A precise land cover map is a precondition for land use change studies. We introduce a more realistic high-resolution land cover map, CORINE Land Cover (CLC), to replace the Global Land Cover Characteristics Database (GLCCD), which is used as a standard land cover map in the regional climate model REMO. In this study, present-day climate simulations over northern Europe are performed by using REMO at 18-km resolution with both CLC and GLCCD. Simulated maximum and minimum 2-m air temperatures, diurnal temperature range and precipitation are assessed with the observation-based E-OBS data. The updated CLC enhances the realism of the description of present-day land surface. However, biases from simulated climate conditions to observations are only marginally reduced while more improvements are expected to be achieved by further developments in model physics. © 2015, Finnish Environment Institute. All rights reserved

UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters

This work was partially funded by FCT Strategic Program UID/EEA/00066/203 of the Center of Technologies and System (CTS) of UNINOVA - Institute for the Development of new Technologies.Knowing how to identify terrain types is especially important in the autonomous navigation, mapping, decision making and detect landings areas. A recent area is in cooperation and improvement of autonomous behavior between robots. For example, an unmanned aerial vehicle (UAV) is used to identify a possible landing area or used in cooperation with other robots to navigate in unknown terrains. This paper presents a computer vision algorithm capable of identifying the terrain type where the UAV is flying, using its rotors’ downwash effect. The algorithm is a fusion between the frequency Wiener-Khinchin adapted and spatial Empirical Mode Decomposition (EMD) domains. In order to increase certainty in terrain identification, machine learning is also used. The system is validated using videos acquired onboard of a UAV with an RGB camera.authorsversionpublishe

Driving factors of aerosol properties over the foothills of central Himalayas based on 8.5 years continuous measurements

This study presents analysis of in situ measurements conducted over the period 2005–2014 in the Indian Himalayas to give a thorough overview of the factors and causes that drive aerosol properties. Aerosol extensive properties (namely, particle number concentration, scattering coefficient, equivalent black carbon, PM2.5, and PM10) have 1.5–2 times higher values in the early to late afternoon than during the night, and a strong seasonality. The interannual variability is ±20% for both PM2.5 and total particle number concentration. Analysis of the data shows statistically significant decreasing trends of −2.3 μg m−3 year−1 and −2.7 μg m−3 year−1 for PM2.5 and PM10, respectively, over the study period. The mountainous terrain site (Mukteshwar, MUK) is primarily under the influence of air from the plains. This is due to convective transport processes that are enhanced by local and mesoscale topography, leading to pronounced valley/mountain winds and consequently to atmospheric boundary layer air lifting from the plains below. The transport from plains is evident in seasonal‐diurnal patterns observed at MUK. The timing of the patterns corresponds with changes in turbulence and water vapor (q). According to our analysis, using these as proxies is a viable method for examining boundary layer influence in the absence of direct atmospheric boundary layer height measurements. Comparing the measurements with climate models shows that even regional climate models have problems capturing the orographic influence accurately at MUK, highlighting the importance of long‐term direct measurements at multiple points to understand aerosol behavior in mountainous areas

Adopting sustainability competence-based education in academic disciplines: Insights from 13 higher education institutions

Higher Education Institutions (HEIs) have been incorporating sustainability into education and curricula, where recent research has focussed on sustainability competences, pedagogical approaches, and how to connect them, generally on a single HEI. The process of integrating sustainability into education based on curricula assessment has been explained using adoption of innovations; and has the potential to explain the process of developing competences through pedagogical approaches. The aim of this paper is to investigate this process at academic discipline level. An online survey was developed to investigate teaching sustainability competences in 13 HEIs, from which 678 responses from educators were obtained. The competences and pedagogical approaches from the responses were ranked, and then the connections between the competences and pedagogical approaches per discipline were analysed using a correlations-based framework, from which three disciplines groups were created. The groups were categorised using diffusion of innovations theory, which indicated that some disciplines are more innovative than others in adopting sustainability competence-based teaching. The results are used to propose two frameworks to better understand the adoption of sustainability competence-based teaching: (a) the D-RAPID framework; and (b) the Disciplinary Multi-dimensional Sustainability Influence Change for Academia (D-MuSICA) memework. The adoption of sustainability competence-base education must expand from a single HEI perspective to a disciplinary collaborative one spanning many HEIs, where academic disciplines should learn from each other''s insights and mistakes and provide students with more transdisciplinary skillsets to make societies more sustainable. © 2021 The Authors. Sustainable Development published by ERP Environment and John Wiley & Sons Ltd