Design with uncertainty: the role of future options for infrastructure integration

Decision making for effective infrastructure integration is challenging because the performance of long-lasting facilities is often difficult to foresee or well beyond the designer's control. We propose a new approach for integrating the construction/retrofitting of two or more types of facilities. Infrastructure integration has many perceived benefits, but practitioners also express serious doubts, particularly when it comes to civil engineering works. To substantiate this approach, we test all of the major options for integrating a ground source heat pump system with the construction/retrofitting of an archetypal office building. We use actual data from the United Kingdom, which represent a middle-of-the-road setting among major developed countries. The model highlights the sensitivity of the range of cost-effective solutions to the embedding of future options. The findings point to a clear need for appropriate standards for managing infrastructure integration. We expect this kind of model to find increasing applications among infrastructure complexes, particularly as cities become denser and more multifunctional.All authors wish to acknowledge the funding support of the EPSRC Centre for Smart Infrastructure and Construction at Cambridge University (EPSRC reference EP/K000314/1). Ying Jin would also like to acknowledge the funding support received from the Tsinghua–Cambridge–MIT Low-carbon University Alliance and the China Ministry of Education Key Lab of Eco-Planning & Green Building at Tsinghua University

Lasing in Two-Dimensional Tin Perovskites

Two-dimensional (2D) perovskites have been proposed as materials capable of improving the stability and surpassing the radiative recombination efficiency of three-dimensional perovskites. However, their luminescent properties have often fallen short of what has been expected. In fact, despite attracting considerable attention for photonic applications during the last two decades, lasing in 2D perovskites remains unclear and under debate. Here, we were able to improve the optical gain properties of 2D perovskite and achieve optically pumped lasing. We show that the choice of the spacer cation affects the defectivity and photostability of the perovskite, which in turn influences its optical gain. Based on our synthetic strategy, we obtain PEA2SnI4 films with high crystallinity and favorable optical properties, resulting in amplified spontaneous emission (ASE) with a low threshold (30 μJ/cm2), a high optical gain above 4000 cm-1 at 77 K, and ASE operation up to room temperature

Pedestrian monitoring techniques for crowd-flow prediction

The high concentration and flow rate of people in train stations during rush hours can pose a prominent risk to passenger safety and comfort. In situ counting systems are a critical element for predicting pedestrian flows in real time, and their capabilities must be rigorously tested in live environments. The focus of this paper is on evaluating the reliability of two alternative counting systems, the first using an array of infrared depth sensors and the second a visible light (RGB) camera. Both proposed systems were installed at a busy walkway in London Bridge station. The data were collected over a period of 2 months, after which, portions of the data set were labelled for quantitative evaluation against ground truth. In this paper, the implementation of the two different counting technologies is described, and the accuracy and limitations of both approaches under different conditions are discussed. The results show that the developed RGB-based system performs reliably across a wide range of conditions, while the depth-based approach proves to be a useful complement in conditions without significant ambient sunlight, such as underground passageways.EPSR

Pedestrian monitoring techniques for crowd-flow prediction

The high concentration and flow rate of people in train stations during rush hours can pose a prominent risk to passenger safety and comfort. In situ counting systems are a critical element for predicting pedestrian flows in real time, and their capabilities must be rigorously tested in live environments. The focus of this paper is on evaluating the reliability of two alternative counting systems, the first using an array of infrared depth sensors and the second a visible light (RGB) camera. Both proposed systems were installed at a busy walkway in London Bridge station. The data were collected over a period of 2 months, after which, portions of the data set were labelled for quantitative evaluation against ground truth. In this paper, the implementation of the two different counting technologies is described, and the accuracy and limitations of both approaches under different conditions are discussed. The results show that the developed RGB-based system performs reliably across a wide range of conditions, while the depth-based approach proves to be a useful complement in conditions without significant ambient sunlight, such as underground passageways.EPSR

Erythrocytosis in a patient with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) can be accompanied by compensatory secondary erythrocytosis. However, the exact prevalence of secondary erythrocytosis in COPD is unknown. Although diagnostic criteria for polycythemia vera versus secondary erythrocytosis are mutually exclusive, we describe here the coexistence of polycythemia vera and COPD in the same patient

UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using a VIs time series, and predicted yield using a peak descriptor derived from a VIs time series with 2.3 Mg DM ha−1 of the root mean square error (RMSE). The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production

Participatory Disease Surveillance Systems: Ethical Framework.

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance

UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using a VIs time series, and predicted yield using a peak descriptor derived from a VIs time series with 2.3 Mg DM ha−1 of the root mean square error (RMSE). The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production

Spring emergence and canopy development strategies in miscanthus hybrids in Mediterranean, continental and maritime European climates

Due to its versatility and storability, biomass is an important resource for renewable materials and energy. Miscanthus hybrids combine high yield potential, low input demand, tolerance of certain marginal land types and several ecosystem benefits. To date, miscanthus breeding has focussed on increasing yield potential by maximising radiation interception through: 1) selection for early emergence, 2) increasing the growth rate to reach canopy closure as fast as possible, and 3) delayed flowering and senescence. The objective of this study is to compare early season re-growth in miscanthus hybrids cultivated across Europe. Determination of differences in early canopy development on end-of-year yield traits is required to provide information for breeding decisions to improve future crop performance. For this purpose, a trial was planted with four miscanthus hybrids (two novel seed-based hybrids M. sinensis×sinensis (M sin×sin) and M. sacchariflorus×sinensis (M sac×sin), a novel rhizome-based M sac×sin and a standard Miscanthus×giganteus (M×g) clone) in the UK, Germany, Croatia and Italy, and was monitored in the third and fourth growing season. We determined differences between the hybrids in base temperature, frost sensitivity and emergence strategy. M×g and M sac×sin mainly emerged from belowground plant organs, producing fewer but thicker shoots at the beginning of the growing season, but these shoots were susceptible to air frosts (determined by recording 0°C 2 m above ground surface). By contrast, M sin×sin emerged 10 days earlier, avoiding damage by late spring frosts and producing a high number of thinner shoots from aboveground shoots. Therefore, we recommend cultivating M sac×sin at locations with low risk and M sin×sin at locations with higher risk of late spring frosts. Selecting miscanthus hybrids that produce shoots throughout the vegetation period is an effective strategy to limit the risk of late frost damage and avoid reduction in yield from a shortened growing season