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Contribution of improved varieties to maize productivity under climate change in Uganda
No full textOne of the most promising pathways to enhance food security for smallholder farmers is the use of improved crop varieties to increase productivity and minimize climate risks. However, assessing the performance of improved crop varieties under climate change is difficult because of limited long-term empirical data from on-station- and farmer field trials and because future climate could be different from what has been experienced. In this study, the climate change adaptation potential of hybrid maize as an improved variety using the Decision Support System for Agrotechnology Transfer (DSSAT) model applied on grid-scale across Uganda was analysed. The DSSAT model was calibrated with observed weather data and analysed the impact of climate change on maize yield under low (SSP1-RCP2.6) and high (SSP3-RCP7.0) emission scenarios. At the national level, it is projected that a yield reduction of 9.6% (low emission scenario) and 11.8% (high emission scenario) by 2030 will occur under climate change. A yield reduction of 11.2% (low emission scenario) and 19.6% (high emission scenario) is projected by 2050, and 13.3% (low emission scenario) and 29.4% (high emission scenario) by 2090. Comparing the effect of climate change between both varieties shows that it is always better to use the hybrid variety, especially under high emission climatic conditions (8.2% and 24.6% yield buffering by 2090 under low emission and high emission scenarios, respectively) at national level. This positive yield effect is realized across all grids, but substantially varies between sites. However, in order to increase adoption of hybrid maize varieties by smallholder farmers in Uganda, adoption barriers, like access to input markets and financial services, have to be overcome. We identify some of these barriers and discuss opportunities to attenuate them and implications on the modelling results. It is concluded that hybrid maize varieties can potentially be a suitable adaptation measure against climate change-related declines in maize production in Uganda
Autonomous UAV 3D Reconstruction using Prediction-Based Next Best View
No full textHigh-quality 3D reconstruction of infrastructure using UAVs is essential for inspection, monitoring, and digital twin applications. Traditional flight planning methods rely on predefined paths and often struggle with complex geometries, leading to incomplete models and inefficiencies. This paper evaluates a state-of-the-art autonomous Next Best View (NBV) of MACARONS model (Mapping And Coverage Anticipation with RGB Online Self-Supervision), which enables online, self-supervised 3D reconstruction of large-scale scenes using only a monocular RGB sensor. The MACARONS NBV model autonomously adjusts UAV trajectories in real time based on predictions of unseen scene structure to improve reconstruction accuracy and surface detail recovery. Despite its advantages, a key limitation is its lack of consideration for camera coverage percentage from a photogrammetric perspective, which makes it challenging to consistently obtain an informative point cloud. The simulation results demonstrate that the autonomous NBV strategy significantly enhances both reconstruction quality and operational efficiency. To evaluate its effectiveness, we applied the MACARONS NBV model to two open-access 3D bridge models. The generated camera trajectories were imported into Blender, where we rendered high-resolution images using realistic camera intrinsics to overcome the limitations of the low-resolution depth predictions. From these images, we reconstructed point clouds and compared them to those produced by a traditional flight planning approach, as well as to the ground truth models. The comparison highlights the added value of autonomous view planning for accurate and efficient UAV-based 3D reconstruction. The two experiments showed a high coverage percentage of 88 % compared to the ground truth and 90% compared to traditional flight planning based on a 37.5% efficiency raise. This work highlights the potential and current limitations of prediction-based NBV in UAV photogrammetry and motivates further research into integrating coverage-aware planning
Mysterious case of an evaporating binary drop
No full textThis paper is associated with a video winner of a 2024 American Physical Society's Division of Fluid Dynamics (DFD) Milton van Dyke Award for work presented at the DFD Gallery of Fluid Motion. The original video is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2024.GFM.V2685343</p
Amerikaanse heffingen schaden netto export Europa uiteindelijk minder dan vaak gedacht
No full textToen Trump vorige week met zijn invoerheffingen kwam, bedroeg de werkloosheid in de VS 4,2%. Daarmee is min of meer sprake van ‘volledige werkgelegenheid’. Een paar procent werkloosheid is nu eenmaal onvermijdelijk, bijvoorbeeld omdat het soms tijd kost om de juiste nieuwe baan te vinden. Ook bij volledige werkgelegenheid kan het aantal werkenden vaak nog wel íets omhoog, maar niet veel (en alleen bij hogere lonen). De productie en de werkgelegenheid in de VS kunnen nu dus niet veel hoger worden dan ze al zijn. Dit is opmerkelijk, want normaliter is het doel van invoertarieven om de nationale productie en de werkgelegenheid te verhogen
The development of a typology and guideline for selecting innovation-encouraging procurement strategies in civil engineering
Get PDFStimulating innovation through public procurement can lead to improved performance, contribute to organizational and policy goals, but can also play a key role in addressing societal challenges that cannot be adequately addressed by conventional solutions. A significant amount of research has been carried out on stimulating innovation through the public procurement of goods and services. However, there is still a lack of knowledge on which procurement strategies and tendering methods can be effectively used to encourage specific types of innovation within larger public initiatives such as civil engineering projects and programmes. The aim of this study is therefore to provide a coherent overview of innovation-encouraging procurement strategies and tendering methods, and to relate their potential effective use to the technology readiness of the targeted innovations, the required level of cooperation between public client and contractor and the willingness of public clients to bear innovation risks, and to provide incentives, budget and solution space for these innovations. Based on a literature review and a multiple case study, an innovation-encouraging procurement typology is developed. In addition, a guideline is provided that can be used by public clients to select an appropriate procurement strategy for their innovation projects and programmes.</p
The cumulative vehicle routing problem with time windows:models and algorithm
Get PDFThe cumulative vehicle routing problem with time windows (CumVRP-TW) is a vehicle routing variant that aims at minimizing a cumulative cost function while respecting customers’ time windows constraints. Mathematical formulations are proposed for soft and hard time windows constraints, where for the soft case, violations are permitted subject to penalization. By means of the cumulative objective and the time windows consideration, routing decisions incorporate the environmental impact related to CO2 emissions and permit obtaining a trade-off between emissions and time windows fulfillment. To solve this problem, we propose a matheuristic approach that combines the features of the Greedy Randomized Adaptive Search Procedure (GRASP) with the exact solution of the optimization model. The solution approaches are tested on instances proposed in the literature as well as on a new benchmark suite proposed for assessing the soft time windows variant. The computational results show that the mathematical formulations provide optimal solutions for scenarios of 10, 20, and several of 50 customers within suitable computational times. Nevertheless, the same performance is not observed for several medium as well as for all large scenarios. In those cases, the proposed matheuristic algorithm is able to report feasible and improved routes for those instances where the exact solver does not report good results. Finally, we verify that the fuel consumption and carbon emissions are reduced when the violation of the time windows is allowed in the case of soft time windows.</p
Cities near volcanoes:Which cities are most exposed to volcanic hazards?
Get PDFCities near volcanoes expose dense concentrations of people, buildings, and infrastructure to volcanic hazards. Identifying cities globally that are exposed to volcanic hazards helps guide local risk assessment for better land-use planning and hazard mitigation. Previous city exposure approaches have used the city centroid to represent an entire city, and to assess population exposure and proximity to volcanoes. But cities can cover large areas and populations may not be equally distributed within their bounds, meaning that a centroid may not accurately capture the true exposure. In this study, we suggest a new framework to rank global city exposure to volcanic hazards. We assessed global city exposure to volcanoes in the Global Volcanism Program database that are active in the Holocene by analysing populations located within 10, 30, and 100 km of volcanoes. These distances are commonly used in volcanic hazard exposure assessment. City margins and populations were obtained from the Global Human Settlement (GHS) Model datasets. We ranked 1,106 cities based on the number of people exposed at different distances from volcanoes, the distance of the city margin from the nearest volcano, and by the number of nearby volcanoes. Notably, 50 % of people living within 100 km of a volcano are in cities. We highlight Jakarta, Bandung, and San Salvador, as scoring highly across these rankings. Bandung, Indonesia ranks highest overall with over 8 million people exposed within 30 km of up to 12 volcanoes. South-east Asia has the highest number of exposed city populations (~162 million). Jakarta (~38 million), Tokyo (~30 million), and Manila (~24 million) having the largest number of people within 100 km. Central America has the highest proportion of its city population exposed, with Quezaltepeque and San Salvador exposed to the most volcanoes (n=23). Additionally, we ranked the 1,283 Holocene volcanoes by the city populations exposed within 10, 30, and 100 km, the number of nearby cities, and distance to nearest city. Tangkuban Parahu, San Pablo Volcanic Field, and Tampomas score highly across these rankings. Notably, Gede-Pangrango (~48 million), Languna Caldera (~8 million), and Nejapa-Miraflores (~0.8 million) volcanoes have the largest city populations within 100, 30, and 10 km, respectively. We developed a web app to visualise all the cities with over 100,000 people exposed. This study provides a global perspective on city exposure to volcanic hazards, identifying critical areas for future research and mitigation efforts
Fusing aerial photographs and airborne LiDAR data to improve the accuracy of detecting individual trees in urban and peri-urban areas
Get PDFUrban trees provide essential social, economic, and environmental benefits. The sustainable management of urban trees often requires basic information at the individual tree level. Aerial photographs and airborne LiDAR are two primary remote sensing data sources widely used in developed countries for large-scale mapping of individual trees in urban areas. However, limited by the imaging principles of different data modes, achieving high mapping accuracy for individual trees using either of these two datasets alone is challenging. In this study, we aimed to leverage the respective advantages of aerial photographs and airborne LiDAR to improve the detection accuracy of individual trees. Utilizing a RetinaNet-based deep learning model, we first identified key metrics from aerial photographs and airborne LiDAR data for individual tree detection. Then, we rectified the misalignment of individual trees between the aerial photographs and airborne LiDAR data using a newly described object-oriented approach. Finally, we detected individual trees at the pixel level and the decision level, respectively. For pixel-level fusion, we combined the selected metrics (i.e., the red, green, and infrared bands as well as the canopy maximum model) from two datasets to detect individual trees. At the decision level, we fused the crowns of individual trees detected from the two rectified datasets. Our findings reveal that rectifying the misalignment between individual trees in both datasets significantly enhances detection accuracy, resulting in a notable increase in F1-score from 0.724 to 0.828. Furthermore, our results indicate that the decision-level data fusion approach yields the highest detection accuracy, with an F1-score of 0.814. This performance surpasses that of aerial photographs (F1-score: 0.592) and airborne LiDAR (F1-score: 0.776) individually. Our study underscores that integrating aerial photographs and airborne LiDAR data is an effective approach to improve the detection accuracy of individual trees in heterogeneous urban and peri-urban landscapes
The Politics of Platform Technologies:A Critical Conceptualization of the Platform and Sharing Economy
Get PDFThis paper offers a political analysis of the platform and sharing economy—an economic model in which digital platforms facilitate social and economic interactions. Its two central models, mainstream and cooperative platforms, offer similar applications and services (e.g., home-sharing, food delivery), but fundamentally differ in their ownership and governance structures, economic models, and technical designs. Building on literature from the politics of technology (PoT), the paper develops an approach for the political analysis of platform technologies, combining central components from the works of Winner, Feenberg, and Pfaffenberger. This approach is then applied to analyze the platform and sharing economy, highlighting the political significance of platform technologies. The analysis reveals three key insights. First, when incorporated into particular social arrangements, digital platforms become means for shaping social realities rather than mere tools for specific uses. Second, mainstream platforms perpetuate capitalist conditions in the digital sphere and therefore necessitate platform capitalism to function, whereas cooperative platforms resist and undermine it. Third, the dynamics between the platform models embody a struggle over the question of the good life in the digital economy. Additionally, the paper uncovers a philosophical weakness in Winner’s definition of “inherently political technologies” that warrants further attention in PoT literature