Beekeepers’ perceptions toward a new omics tool for monitoring bee health in Europe

Pressures on honey bee health have substantially increased both colony mortality and beekeepers’ costs for hive management across Europe. Although technological advances could offer cost-effective solutions to these challenges, there is little research into the incentives and barriers to technological adoption by beekeepers in Europe. Our study is the first to investigate beekeepers’ willingness to adopt the Bee Health Card, a molecular diagnostic tool developed within the PoshBee EU project which can rapidly assess bee health by monitoring molecular changes in bees. The Bee Health Card, based on MALDI BeeTyping®, is currently on level six of the Technology Readiness Level scale, meaning that the technology has been demonstrated in relevant environments. Using an on-line survey from seven European countries, we show that beekeepers recognise the potential for the tool to improve colony health, and that targeted economic incentives, such as subsidises, may help reduce cost being a barrier to the adoption and frequent use of the tool. Based on the description of the tool, 43% of beekeepers appear to be moderately confident in the effectiveness of the Bee Health Card. This confidence could increase if the tool was easy to use and not time consuming, and a higher confidence could also contribute to raising the probability of accepting extra costs linked to it. We estimate that, in the worst-case scenario, the cost per single use of the Bee Health Card should be between €47–90 across a range of European countries, depending on the labour and postage costs. However, the monetary benefits in terms of honey production could exceed this. In order to successfully tackle colony health issues, it is recommended using the BHC five times per year, from the end to the beginning of winter. Finally, we discuss the knowledge needs for assessing beekeeper health tools in future research

“Takeaway Night”: understanding UK families’ consumption of takeaway food for family mealtimes

Takeaway food is typically of poor nutritional quality and its increasing availability and consumption is considered a contributor to the obesity crisis. Shared family mealtimes are associated with a wealth of positive outcomes for children and adolescents, and are valued by family members. Parents describe prioritising health when planning family meals and consuming takeaway food seems incongruent with this goal. This study aimed to investigate UK families’ consumption of takeaway food for family mealtimes and explore the interplay between the nutritional harms of occasional takeaway food for family mealtimes and the broader benefits arising from sharing meals with family. An online survey was completed by 189 parents diverse in key socio-demographic characteristics. Results showed that consumption of takeaway food for family mealtimes is common (96% did so at least occasionally) but for most families relatively infrequent (74% did so less than weekly). Content analysis of responses to open-ended questions revealed that parents considered takeaway food for family mealtimes a convenient, enjoyable treat associated with togetherness and connectedness. Logistic regression analysis indicated a non-linear association between frequent consumption of takeaway food for family mealtimes, household income and neighbourhood deprivation, with low household income and high neighbourhood deprivation significantly associated with frequent consumption. This study is the first to examine the consumption of takeaway food for family mealtimes. The positivity with which parents described “takeaway night” suggests it is an important part of family culture and may not be readily given up. Given this, policies and interventions would most effectively focus on improving the nutritional quality of takeaway food

Social Life Cycle Assessment (S-LCA) of formal and informal waste collectors in decentralized waste to compost facility

The global generation of municipal solid waste (MSW) is expected to increase by 70 % by 2050, reaching 3.4 billion metric tons. Despite the need for proper waste management, less than 20 % of waste is recycled, and waste continues to end up in landfills. Waste management is a significant problem in Bangladesh and other rapidly urbanizing nations, exacerbated by densely populated housing coupled with inadequate infrastructure. The utilization of informal waste collectors arises from the government’s frequent inability to offer sufficient waste collection and disposal services. A large number of Dhaka’s informal sector workers depend on collecting waste for a living. In this study, the social life cycle assessment (S-LCA) is applied to analyze the social implications of formal and informal waste collectors on the waste management process in Uttara, Dhaka. Working conditions, human rights, health and safety, and socio-economic repercussions are the four primary areas of focus for the SLCA. For the assessment, an indicator score ranging from 2 (best performance) to − 2 (poor performance) was used. The data revealed that informal workers scored 0 for fair salaries, but formal workers received 1, showing that formal workers adhere to higher standards. Both groups obtained an average score of − 2 in the social security subcategory, which is much lower than anticipated. Formal workers scored − 2 on health and safety, while informal workers scored − 1, indicating serious inadequacies in both categories. These findings highlight the need for stronger legislation and support systems to enhance waste collectors’ working conditions in Dhaka and other similar cities throughout the world, as well as the considerable socioeconomic challenges they confront

Mangroves and economic development in Tobago: incorporating payment horizons, choice certainty and ex-post interviews in discrete choice experiments

Governments have long faced potential trade-offs between economic development and protecting nature. This is particularly true for tropical and sub-tropical islands where most mangroves are found. Motivated by Trinidad and Tobago’s central government’s prior hotel development plans, we employ a discrete choice experiment (DCE) to investigate residents’ preferences for mangrove ecosystem services (ES) in the Bon Accord Lagoon and Buccoo Bay, Tobago. Preferences were investigated in the context of a trade-off between conserving mangroves and promoting economic development through a hypothetical hotel project in the study area. We use a Hierarchical Bayesian Logit Model, exploring two distinct payment horizons, 5 and 25-years, undertaken independently and also merged in models that allow for choice certainty and individual characteristics. We find that respondents have consistent willingness-to-pay (WTP) for mangrove ES and exhibit general insensitivity to the payment horizons due to perceived disbenefits associated with mangrove loss from hotel development. The DCE and ex-post (follow-up) interviews suggest that there is strong public support for policies aimed at long-term protection of mangroves

Eveningness and procrastination: an exploration of relationships with mind wandering, sleep quality, self-control, and depression

While morningness (a preference for rising earlier in the day) is associated with positive affect and life satisfaction, eveningness is correlated with negative emotionality, poor sleep, less self-control, and more procrastination. The current study investigated inter-relationships between morningness–eveningness; bedtime, academic, and exercise procrastination; mind wandering; sleep quality; self-control; and depressive symptoms. An online survey including questionnaire measures of these variables was completed by 306 university students (aged 18–51 years; mean = 20.36, SD = 4.001; 34 male). Morningness correlated with more self-control and better sleep quality—eveningness correlated with more bedtime, academic, and exercise procrastination; depressive symptoms; and mind wandering. All forms of procrastination negatively correlated with self-control and sleep quality, and positively correlated with depressive symptoms and mind wandering, although more strongly with spontaneous than deliberate mind wandering. Mediation effects were found—bedtime procrastination (BP) between eveningness and spontaneous mind wandering (MW); spontaneous MW between BP and sleep quality; sleep quality between BP and depressive symptoms; self-control between depressive symptoms and academic procrastination. A path model of these inter-relationships was developed. This study adds to a growing body of research indicating that interventions to reduce bedtime procrastination may bring about improvements in wellbeing and academic achievement

Empowering stroke recovery with upper limb rehabilitation monitoring using TinyML based heterogeneous classifiers

Stroke is one of the leading causes of disability worldwide, with approximately 70% of survivors experiencing motor impairments in the upper limbs, significantly affecting their quality of life. Home-based rehabilitation offers a cost-effective approach to improving motor function, but it faces challenges, including inaccurate movement reporting, lack of real-time feedback, and the high cost of rehabilitation equipment. Therefore, there is a need for affordable, lightweight home-based rehabilitation monitoring systems. This paper presents an intelligent wearable sensor system that utilizes TinyML AI technology to classify eight upper limb rehabilitation movements with minimal sensors. The system is designed for patients with upper limb impairments who retain antigravity voluntary movement, enabling them to monitor rehabilitation progress at home. The study recruited 10 healthy volunteers to perform rehabilitation movements, creating a standardized dataset for model training. Data normalization, preprocessing, model training, and deployment were carried out using the Edge Impulse platform. A hybrid classifier, combining multilayer perceptron and k-means clustering, achieved 96.1% training accuracy, 95.09% testing accuracy, and 88.01% deployment accuracy. The proposed TinyML-based system shows promising potential for home-based rehabilitation of stroke patients

Post-processing large-scale river discharge forecasts at ungauged locations

Reliable river discharge forecasts are crucial for effective water resource management and flood risk mitigation. However, uncertainty in the forecasts is inevitable due to limitations in hydrological process understanding, errors in the meteorological forcings, observation uncertainty, and computational constraints. For flood forecasting, this forecast uncertainty can lead to ineffective or delayed preparatory actions. The primary aim of this thesis is to improve the actionable information from ensemble river discharge forecasts at gauged and ungauged locations using post-processing – a technique used to statistically correct the forecasts and reduce the uncertainty. Post-processing is already part of the forecasting system of the Copernicus Emergency Management Service’s European Flood Awareness System (EFAS). The skill of the EFAS operational at-gauge post-processing method is evaluated, finding that post-processing improves the skill of the forecasts particularly for large rivers for which hydrological errors dominate. Barriers to the use of the operational post-processed forecasts are identified via a co-production workshop, including lack of local relevance, and difficulty accessing the forecasts and associated documentation. A key limitation of the operational post-processing method is that it is only applicable at gauged locations. To overcome this limitation, a data-assimilation-inspired technique is developed to propagate observation information along the river network. Combined with the at-gauge post-processing method, this new information propagation technique allows the correction of river discharge forecasts at ungauged locations. This new post-processing method was evaluated and found to improve forecasts up to a 5-day lead-time. The new method is computationally efficient, adapts to the flow situation, and is applicable to any ensemble river discharge forecast. By improving the skill of the forecast at ungauged locations, this work aims to support more informed decision-making in flood risk management and water resource planning, ultimately helping to protect people, infrastructure, and economies from hydrological extremes

An investigation into the cognitive ecology and electrophysiology of fungi and plants

The cognitive ecology of non-neural organisms like plants and fungi is a new and controversial research field that has gained momentum since the turn of the century. Many studies have suggested that plants and fungi perceive and respond plastically to their environment, implement behaviours that maximise their chances of survival, and that they have the ability to store memories, learn and communicate. However, little is known about how these phenomena occur and what underpins it. This is not only a scientific question, but also philosophical, with deep implications for what we understand by cognition. This thesis sought to contribute to this debate by focusing on the symbiotic relationship between mycorrhizal fungi and plants. After a general introduction situating the thesis in the epistemological debate and describing the challenge of establishing methods to study the cognitive ecology of plants and fungi in Chapter 1, Chapter 2 departs from the post-cognitivist tradition to build the hypothesis that the cognitive process of plants can be extended to that of mycorrhizal fungi when they are in symbiosis. Chapter 3 describes a failed attempt to test this hypothesis with the use of Perspex microcosms. Chapter 4 focused on the putative cognition of ectomycorrhizal fungi and how memory could be involved in its foraging behaviour, a hypothesis not supported by the evidence gathered during this study. Chapter 5 describes the successful attempt of using electrophysiological equipment to record the spontaneous and evoked electrical signalling of different fungal species, suggesting that this signalling could have the key to understand, in part, the complex and plastic behaviours these organisms present. The thesis concludes with Chapter 6, a rumination on the philosophical and practical challenges of both traditional and alternative views of cognition in non-neural organisms

Constraining extreme storm surges along the European coasts from a large ensemble of climate models

The storm surge contribution to extreme sea levels along the European coastlines is investigated using hydrodynamic numerical simulations forced by atmospheric pressure and surface winds from a large ensemble of initialized climate models from the Decadal Climate Prediction Project experiment. The outputs, representative of the climate since 1960, amount for a total of $>$8,000 years of data, thus increasing significantly the sampling size of extreme simulated events compared to typical decadal-long hydrodynamic hindcasts. The extended DCPP-forced storm surge data set, once bias-corrected, provides information on the probability of storm surges that are plausible in Europe in the current climate but for which there is no observational evidence. Our results show that these unprecedented extreme events are on average 20% larger than the observed maxima, with values reaching up to 1 m. The new data set also enables the uncertainties in the probabilities to be constrained significantly (e.g., up to two orders of magnitude for 500-year return periods). This permits a more robust quantification of coastal hazards and risks, particularly for the most extreme events with return periods that are substantially longer that the observational records