285 research outputs found
Eliciting citizens’ priorities for active travel infrastructure investments: A qualitative analysis of best-worst scaling experiments
Introduction:
The built environment plays an important role in individuals’ propensity to walk and cycle and local authorities increasingly invest financial resources towards its development. Organisations responsible for the built environment have developed auditing tools as guidelines to inspect routes and identify improvements to support active travel.
Methods:
Using these auditing tools as a starting point, this study developed 21 walking and 25 cycling investment-relevant factors that were embedded into two choice-based survey instruments, respectively. The study used cognitive interview pre-testing to internally validate a preference-based elicitation approach known as Best-Worst Scaling (BWS), which aimed to capture pedestrian and cyclist preferences. We report findings from cognitive interviews (data analysed thematically) with 20 participants (10 pedestrians and 10 cyclists).
Results:
In both sets of interviews, four themes emerged regarding how the participants approached the BWS task and five themes related to the understanding of the factors. The BWS choice tasks required refinement regarding the ‘frame of reference’, ‘travel context’, the ‘decision-making strategy’, and the ‘concrete thinking’ (finding some factors easier to interpret). Additionally, issues with understanding the factors, the wording, ‘overlapping’, negatively phrased factors, and technical jargon all pointed towards the need to refine auditing tools if these were to be introduced in a preference elicitation context.
Conclusions:
This study helps to empirically uncover how citizens interpret infrastructure related aspects of walking and cycling by pointing to nuanced aspects that auditing tools may miss. The findings also helped develop an internally consistent preference elicitation survey-instrument that any local authority can implement to determine which walking and cycling infrastructure investments are a priority in their area
Café Mesoamericano: desarrollo de una estrategia de adaptación al cambio climático
La producción de café en Mesoamérica es parte importante de la economía y la sociedad, al ser eje del bienestar de miles de familias y contribuir significativamente al PIB agrícola de diversos países. Pero las proyecciones indican que es en México y América Central donde el cambio climático tendrá los impactos más severos. Los modelos climáticos y los indicadores de aptitud climática del nicho en relación con el cultivo muestran cambios considerables, tanto en la calidad del café como en las zonas altitudinales apropiadas para la producción. Si hoy no se hacen esfuerzos para fortalecer la capacidad adaptativa, probablemente habrá grandes pérdidas económicas en toda la cadena de abastecimiento de café, así como la desaparición de importantes servicios ambientales
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Intergenerational perceptions of household wellbeing in India’s Western and Eastern Ghats
India is home to the largest number of people living in poverty in the world. To inform poverty alleviation strategies, we sought local insights on wellbeing trajectories from three generations of respondents in three communities in the Western and Eastern Ghats. An integrated thematic analysis was carried out using qualitative information from focus group discussions (FGDs) and a survey instrument. Overall, we found most households had a positive perspective regarding their wellbeing over time; when divided into research locations, the Odisha site (Jeypore) was the most optimistic, the Kerala site (Wayanad) had no consensus position, and the Tamil Nadu site (Kolli Hills) was most pessimistic. Scheduled tribe (ST) and non-ST households were similar in their wellbeing perceptions despite the ongoing social and economic marginalization of ST households. Common negative events experienced were health (death or alcoholism) and climate disasters (drought or flooding), and common positive events were asset inheritance or government schemes. An important insight was changing importance of events between generations: elder generations valued labour migration, interim generations valued asset inheritance, and the current generation valued government schemes. We conclude that significant events play a major role in wellbeing perceptions among these communities, and understanding the evolving forms of significant events between generations can provide insights towards designing effective poverty alleviation strategies for the future
Arabica-like flavour in a heat tolerant wild coffee species
There are numerous factors to consider when developing climate resilient coffee crops, including the ability to tolerate altered climatic conditions, meet agronomic and value chain criteria, and satisfy consumer preferences for flavour (aroma and taste). We evaluated the sensory characteristics and key environmental requirements for the enigmatic narrow-leaved coffee (Coffea stenophylla), a wild species from Upper West Africa1. We confirm historical reports of a superior flavour1-3, and uniquely and remarkably, reveal a sensory profile analogous to high quality Arabica coffee. We demonstrate that this species grows and crops under the same range of key climatic conditions as (sensorially inferior) robusta and Liberica coffee4-9, and has a mean annual temperature 6.2–6.8⁰C higher than Arabica coffee, even under equivalent rainfall conditions. This species substantially broadens the climate envelope for high quality coffee, and could provide an important resource for the development of climate resilient coffee crop plants
Lost and found: Coffea stenophylla and C. affinis, the forgotten coffee crop species of west Africa
Two species, Coffea arabica and C. canephora, are used to produce the world’s coffee, and serve the coffee sector admirably. However, various challenges at the production (farm) level, including the increasing prevalence and severity of disease and pests and climate change, indicate that the coffee crop portfolio needs to be diversified in order to ensure resilience and sustainability. In this study we use a multidisciplinary approach (herbarium and literature review, fieldwork and DNA sequencing) to elucidate the taxonomic identities, agronomic attributes and whereabouts of two poorly known coffee crop species, C. affinis and C. stenophylla. We show that despite widespread, albeit small-scale, use as a coffee crop species across Upper West Africa, (and further afield) more than 100 years ago , these species are now rare in the wild and in cultivation. Fieldwork enabled us to rediscover C. stenophylla in Sierra Leone, which previously had not been recorded in the wild there since 1954. We confirm that C. stenophylla is an indigenous species in Guinea, Sierra Leone, and Ivory Coast, and show that C. affinis is indigenous in Guinea and Ivory Coast. Both species are likely to be threatened with extinction in the wild, particularly in Guinea. DNA sequencing using plastid and ITS markers was used to: confirm the identity of museum and field collected samples of C. stenophylla; demonstrate the use of plastid and nuclear markers to identify F1 and early-generation interspecific hybrids; identify the hybrid C. liberica x C. stenophylla; and reveal that C. liberica is non-monophyletic and likely to represent more than one species. Contrary to contemporary opinion, we could find no evidence of hybrid status for C. affinis, although the taxonomic identity of this species remains unclear. Sequencing analyses also show that hybridization is possible across all the major short-styled Africa Coffea species, i.e. Coffee Crop Wild Relative Priority Groups I and II. Coffea affinis and C. stenophylla may possess traits useful for coffee crop plant development, including taste differentiation, disease resistance, and climate resilience; these attributes would be best accessed via breeding programmes although these two species may have potential as crops with minimal domestication
Direct epitaxial approach to achieve a monolithic on-chip integration of a HEMT and a single micro-LED with a high-modulation bandwidth
Visible light communications (VLC) require III-nitride visible micro-light-emitting diodes (μLEDs) with a high-modulation bandwidth. Such μLEDs need to be driven at a high injection current density on a kA/cm2 scale, which is about 2 orders of magnitude higher than those for normal visible LED operation. μLEDs are traditionally fabricated by dry-etching techniques where dry-etching-induced damages are unavoidable, leading to both a substantial reduction in performance and a great challenge to viability at a high injection current density. Furthermore, conventional biasing (which is simply applied across a p–n junction) is good enough for normal LED operation but generates a great challenge for a single μLED, which needs to be modulated at a high injection current density and at a high frequency. In this work, we have proposed a concept for an epitaxial integration and then demonstrated a completely different method that allows us to achieve an epitaxial integration of a single μLED with a diameter of 20 μm and an AlGaN/GaN high-electron-mobility transistor (HEMT), where the emission from a single μLED is modulated by tuning the gate voltage of its HEMT. Furthermore, such a direct epitaxial approach has entirely eliminated any dry-etching-induced damages. As a result, we have demonstrated an epitaxial integration of monolithic on-chip μLED-HEMT with a record modulation bandwidth of 1.2 GHz on industry-compatible c-plane substrates
Greenhouse gas emissions in coffee grown with differing input levels under conventional and organic management
Coffee plays a key role in sustaining millions of livelihoods around the world. Understanding GHG emissions from coffee supply chains is important in evaluating options for climate change mitigation within the sector. We use data from two long-term coffee agroforestry experiments in Costa Rica and Nicaragua to calculate carbon footprints (CF) for coffee and identify emission hotspots within different management systems, levels of inputs and shade types. Management system and input level were the main cause of variation in CFs. Carbon footprints for 1 kg of fresh coffee cherries were between 0.26 and 0.67 kgCO2e for conventional and 0.12 and 0.52 kgCO2e for organic management
systems. The main contributor to GHG emissions for all management systems was the inputs of organic and inorganic nitrogen. Nitrous oxide emissions from pruning inputs contributed between 7% and 42 % of CFs. However, these estimates were strongly influenced by the choice of emission factors
Sink or source—The potential of coffee agroforestry systems to sequester atmospheric CO2 into soil organic carbon
Current carbon accounting methodologies often assume interactions between above-ground and below-ground carbon, without considering effects of land management. We used data from two long-term coffee agroforestry experiments in Costa Rica and Nicaragua to assess the effect on total soil organic carbon (SOC) stocks of (i) organic versus conventional management, (ii) higher versus moderate agronomic inputs, (iii) tree shade types. During the first nine years of coffee establishment total 0–40 cm depth SOC stocks decreased by 12.4% in Costa Rica and 0.13% in Nicaragua. Change in SOC differed consistently amongst soil layers: at 0–10 cm SOC stocks increased by 2.14 and 1.26 Mg C ha−1 in Costa Rica and Nicaragua respectively; however much greater reduction occurred at 20–40 cm (9.65 and 2.85 Mg C ha−1 respectively). Organic management caused a greater increase in 0–10 cm SOC but did not influence its reduction at depth. Effects of shade type were smaller, though heavily pruned legume shade trees produced a greater increase in 0–10 cm SOC than unpruned timber trees. No significant differences in SOC stocks were found between shaded and unshaded systems at any depth and SOC was poorly correlated with above-ground biomass stocks highlighting poor validity of “expansion factors” currently used to estimate SOC. SOC stock changes were significantly negatively correlated with initial SOC stock per plot, providing evidence that during establishment of these woody-plant-dominated agricultural systems SOC stocks tend to converge towards a new equilibrium as a function of the change in the quantity and distribution of organic inputs. Therefore it cannot be assumed that tree-based agricultural systems necessarily lead to increases in soil C stocks. While high inputs of organic fertiliser/tree pruning mulch increased surface-layer SOC stocks, this did not affect stocks in deeper soil, where decreases generally exceeded any gains in surface soil. Therefore site- and system-specific sampling is essential to draw meaningful conclusions for climate change mitigation strategies
PraNet: Parallel Reverse Attention Network for Polyp Segmentation
Colonoscopy is an effective technique for detecting colorectal polyps, which
are highly related to colorectal cancer. In clinical practice, segmenting
polyps from colonoscopy images is of great importance since it provides
valuable information for diagnosis and surgery. However, accurate polyp
segmentation is a challenging task, for two major reasons: (i) the same type of
polyps has a diversity of size, color and texture; and (ii) the boundary
between a polyp and its surrounding mucosa is not sharp. To address these
challenges, we propose a parallel reverse attention network (PraNet) for
accurate polyp segmentation in colonoscopy images. Specifically, we first
aggregate the features in high-level layers using a parallel partial decoder
(PPD). Based on the combined feature, we then generate a global map as the
initial guidance area for the following components. In addition, we mine the
boundary cues using a reverse attention (RA) module, which is able to establish
the relationship between areas and boundary cues. Thanks to the recurrent
cooperation mechanism between areas and boundaries, our PraNet is capable of
calibrating any misaligned predictions, improving the segmentation accuracy.
Quantitative and qualitative evaluations on five challenging datasets across
six metrics show that our PraNet improves the segmentation accuracy
significantly, and presents a number of advantages in terms of
generalizability, and real-time segmentation efficiency.Comment: Accepted to MICCAI 202
Intensification of coffee systems can increase the effectiveness of REDD mechanisms
In agricultural production systems with shade trees, such as coffee, the increase in greenhouse gas (GHG) emissions from production intensification can be compensated for, or even outweighed, by the increase in carbon sequestration into above-ground and below-ground tree biomass. We use data from a long-term coffee agroforestry experiment in Costa Rica to evaluate the trade-offs between intensification, profitability and net greenhouse gas emissions through two scenarios. First, by assessing the GHG emissions associated with conversion from shaded to more profitable full-sun (un-shaded) systems, we calculate the break-even carbon price which would need to be paid to offset the opportunity cost of not converting. The price per tCO2e of emissions reduction required to compensate for the coffee production revenue foregone varies widely from 9.3 to 196.3 US$ amongst different shaded systems. Second, as an alternative to intensification, production area can be extended onto currently forested land. We estimate this land-use change required to compensate for the shortfall in profitability from retaining lower intensity coffee production systems. For four of the five shade types tested, this land-use change causes additional GHG emissions >5 tCO2e ha−1 yr−1 resulting in net emissions >8 tCO2e ha−1 yr−1 for the whole system. We conclude that instead, by intensifying production, mechanisms similar to REDD that are based on reducing emissions through avoided land-use change (REAL) could play a major role in increasing the climate change mitigation success of agroforestry systems at the same time as aiding REDD through reducing pressure for further forest conversion to agriculture
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