Husimi functions for coupled optical resonators.

Phase-space analysis has been widely used in the past for the study of optical resonant systems. While it is usually employed to analyze the far-field behavior of resonant systems, we focus here on its applicability to coupling problems. By looking at the phase-space description of both the resonant mode and the exciting source, it is possible to understand the coupling mechanisms as well as to gain insights and approximate the coupling behavior with reduced computational effort. In this work, we develop the framework for this idea and apply it to a system of an asymmetric dielectric resonator coupled to a waveguide.

Fabrication and characterization of deformed microdisk cavities in silicon dioxide with high Q-factor.

We demonstrate the excitation and characterization of whispering gallery modes in a deformed optical microcavity. To fabricate deformed microdisk microresonators we established a fabrication process relying on dry plasma etching tools for many degrees of freedom and a shape-accurate morphology. This approach allowed us to fabricate resonators of different sizes with a controlled sidewall angle and underetching in large quantities with reproducible properties such as a surface roughness RQ≤2nm. The excitation and characterization of these modes were achieved by using a state-of-the-art tapered fiber coupling setup with a narrow linewidth tunable laser source. The conducted measurements in shortegg resonators showed at least two modes within a spectral range of about 237 pm. The highest Q-factors measured were in the range of 105. Wave optical eigenmode and frequency domain simulations were conducted that could partially reproduce the observed behavior and therefore allow us to compare the experimental results.

Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d'Ivoire.

Unlike water and sanitation infrastructures or socio-economic indicators, landscape features are seldomly considered as predictors of diarrhoea. In contexts of rapid urbanisation and changes in the physical environment, urban planners and public health managers could benefit from a deeper understanding of the relationship between landscape patterns and health outcomes. We conducted an ecological analysis based on a large ensemble of open-access data to identify specific landscape features associated with diarrhoea. Designed as a proof-of-concept study, our research focused on Côte d'Ivoire. This analysis aimed to (i) build a framework strictly based on open-access data and open-source software to investigate diarrhoea risk factors originating from the physical environment and (ii) understand whether different types and forms of urban settlements are associated with different prevalence rates of diarrhoea. We advanced landscape patterns as variables of exposure and tested their association with the prevalence of diarrhoea among children under the age of five years through multiple regression models. A specific urban landscape pattern was significantly associated with diarrhoea. We conclude that, while the improvement of water, sanitation, and hygiene infrastructures is crucial to prevent diarrhoeal diseases, the health benefits of such improvements may be hampered if the overall physical environment remains precarious.

Evaluating urban greening scenarios for urban heat mitigation: a spatially explicit approach.

Urban green infrastructure, especially trees, are widely regarded as one of the most effective ways to reduce urban temperatures in heatwaves and alleviate the adverse impacts of extreme heat events on human health and well-being. Nevertheless, urban planners and decision-makers are still lacking methods and tools to spatially evaluate the cooling effects of urban green spaces and exploit them to assess greening strategies at the urban agglomeration scale. This article introduces a novel spatially explicit approach to simulate urban greening scenarios by increasing the tree canopy cover in the existing urban fabric and evaluating their heat mitigation potential. The latter is achieved by applying the InVEST urban cooling model to the synthetic land use/land cover maps generated for the greening scenarios. A case study in the urban agglomeration of Lausanne, Switzerland, illustrates the development of tree canopy scenarios following distinct spatial distribution strategies. The spatial pattern of the tree canopy strongly influences the human exposure to the highest temperatures, and small increases in the abundance of tree canopy cover with the appropriate spatial configuration can have major impacts on human health and well-being. The proposed approach supports urban planning and the design of nature-based solutions to enhance climate resilience.

PyLandStats: An open-source Pythonic library to compute landscape metrics.

Quantifying the spatial pattern of landscapes has become a common task of many studies in landscape ecology. Most of the existing software to compute landscape metrics is not well suited to be used in interactive environments such as Jupyter notebooks nor to be included as part of automated computational workflows. This article presents PyLandStats, an open-source Pythonic library to compute landscape metrics within the scientific Python stack. The PyLandStats package provides a set of methods to quantify landscape patterns, such as the analysis of the spatiotemporal patterns of land use/land cover change or zonal analysis. The implementation is based on the prevailing Python libraries for geospatial data analysis in a way that they can be forthwith integrated into complex computational workflows. Notably, the provided methods offer a large variety of options so that users can employ PyLandStats in the way that best supports their needs. The source code is publicly available, and is organized in a modular object-oriented structure that enhances its maintainability and extensibility.