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Optical Frequency Comb Generation in Gain Switched Semiconductor Nanolasers With Optical Injection
Get PDFClosing the Gap: How Psychological Distance Influences Willingness to Engage in Risky COVID Behavior
Get PDFPandemics, and other risk-related contexts, require dynamic changes in behavior as situations develop. Human behavior is influenced by both explicit (cognitive) and implicit (intuitive) factors. In this study, we used psychological distance as a lens to understand what influences our decision-making with regard to risk in the context of COVID-19. This study was based on the rationale that our relational needs are more concrete to us than the risk of the virus. First, we explored the impact of social–psychological distance on participants’ risk perceptions and behavioral willingness. As hypothesized, we found that close social relationships of agents promoted willingness to engage in risky behavior. In the second phase, we tested an intervention designed to increase the concreteness of information about virus transmission as a mechanism to mitigate the bias of social influence. We found that the concreteness intervention resulted in significantly reduced willingness to engage in risky behavior. As such, communications aimed at changing the behavior of citizens during times of increased risk or danger should consider conceptually concrete messaging when communicating complex risk, and hence may provide a valuable tool in promoting health-related behavior
“I’m Not Sure I Can See Myself in This World”: Experience of Mindfulness Teacher Training among Trainees from Diverse Backgrounds
Get PDFObjectivesThere is a growing recognition of the importance of Equality, Diversity and Inclusion (EDI) in mindfulness-based Teacher Training Programs (TTPs), given current imbalances in representation of teachers and trainers, and a recognised need to build awareness of personal and organisational biases. Little is known about how EDI issues may impact the experience of trainees on a TTP. This study aimed to explore underrepresented trainees’ experiences on a TTP, including what hindered or helped them access training or feel included, and their views on how best to foster EDI in TTPs.MethodSemi-structured qualitative interviews were conducted with seven current and graduate mindfulness teacher trainees from underrepresented groups. Their experiences of EDI throughout training were explored. Data was analyzed using inductive thematic analysis.ResultsKey findings were that feelings of inclusion were influenced by how represented and acknowledged trainees felt by their trainers and peers; feelings of safety influenced their choices around disclosure; a main access barrier was cost; and more explicit teaching about EDI in TTP curricula is needed. There was a need for wider access to entry trainings such as 8-week mindfulness-based programmes.ConclusionsThis study provides valuable insight into how underrepresented teacher trainees experience TTPs and highlights opportunities to better support mindfulness teacher trainees. TTPs need to integrate EDI awareness and understanding into their ethos and curriculum. Further research is needed to inform and develop approaches to further embed EDI in mindfulness-based program teaching and training
Recruitment of European sea bass (<i>Dicentrarchus labrax</i>) in northerly UK estuaries indicates a mismatch between spawning and fisheries closure periods
Get PDFEuropean sea bass (Dicentrarchus labrax) is a species of high commercial and recreational value, but it exhibits highly variable recruitment rates and has been subject to recent declines. Emergency management measures put in place to protect spawning stocks include the annual closure of commercial and recreational fisheries over a 2-month, February–March, window. Whether this protection measure is having the desired outcome for this data-poor species remains unclear. Otolith microstructural analyses (counts and widths of daily growth rings and check marks indicative of settlement) were used to estimate (1) spawn timing, (2) pelagic larval duration and settlement timing, (3) growth rate and condition, and (4) the otolith-fish size relationship for juvenile European sea bass caught from two estuaries in Wales (Dwyryd, Y Foryd), located at the northern edge of the species range. We observed a significant mismatch between the timing of fisheries closures and the spawning, with 99.2% of recruits having been spawned after the fishery had reopened (back-calculated median spawn date = May 5 ± 17 days SD), suggesting that the closure may be too early toadequately protect this population. Further, we present the first empirically derived estimates of pelagic larval duration for sea bass recruits settling in UK habitats, which showed a strong negative relationship with spawn date. Finally, we found significant differences in fish condition between the two estuaries, suggesting local variation in habitat quality. The results suggest that the timing of current fisheries closures may not be adequately protecting the spawners supplying these northernmost estuaries, which are likely to become increasingly important as sea bass distributions shift northward in our climate future
Voluntary thermal maximum of grassland vipers (Vipera spp.): environmental drivers and local adaptation
Get PDFThe thermal tolerance of ectotherms is a critical factor that influences their distribution, physiology, behaviour, and, ultimately, survival. Understanding the factors that shape thermal tolerance in these organisms is, therefore, of great importance for predicting their responses to forecasted climate warming. Here, we investigated the voluntary thermal maximum (VTmax) of nine grassland viper taxa and explored the factors that influence this trait. The small size of these vipers and the open landscape they inhabit render them particularly vulnerable to overheating and dehydration. We found that the VTmax of grassland vipers is influenced by environmental temperature, precipitation, short-wave flux, and individual body size, rather than by phylogenetic relatedness. Vipers living in colder environments exhibited a higher VTmax, contradicting the hypothesis that environmental temperature is positively related to VTmax. Our findings emphasize the importance of considering local to regional adaptations and environmental conditions when studying thermal physiology and the evolution of thermal tolerance in ectotherms
Co-benefits for net carbon emissions and rice yields through improved management of organic nitrogen and water
Get PDFReturning organic nutrient sources (for example, straw and manure) torice fields is inevitable for coupling crop–livestock production. However,an accurate estimate of net carbon (C) emissions and strategies tomitigate the abundant methane (CH4) emission from rice fields suppliedwith organic sources remain unclear. Here, using machine learning and aglobal dataset, we scaled the field findings up to worldwide rice fields toreconcile rice yields and net C emissions. An optimal organic nitrogen (N)management was developed considering total N input, type of organicN source and organic N proportion. A combination of optimal organic Nmanagement with intermittent flooding achieved a 21% reduction in netglobal warming potential and a 9% rise in global rice production comparedwith the business-as-usual scenario. Our study provides a solution forrecycling organic N sources towards a more productive, carbon-neutral andsustainable rice–livestock production system on a global scale
Building semi-supervised decision trees with semi-cart algorithm
Get PDFDecision trees are a fundamental statistical learning tool for addressing classification and regression problems through a recursive partitioning approach that effectively accommodates numerical and categorical data [1, 2]. The Classification and regression tree (CART) algorithm underlies modern Boosting methodologies such as Gradient boosting machine (GBM), Extreme gradient boosting (XGBoost), and Light gradient boosting machine (LightGBM). However, the standard CART algorithm may require improvement due to its inability to learn from unlabeled data. This study proposes several modifications to incorporate test data into the training phase. Specifically, we introduce a method based on Graph-based semi-supervised learning called “Distance-based Weighting,” which calculates and removes irrelevant records from the training set to accelerate the training process and improve performance. We present Semi-supervised classification and regression tree (Semi-Cart), a new implementation of CART that constructs a decision tree using weighted training data. We evaluated its performance on thirteen datasets from various domains. Our results demonstrate that Semi-Cart outperforms standard CART methods and contributes to statistical learning