A Dense Packing of Regular Tetrahedra

We construct a dense packing of regular tetrahedra, with packing density $D > >.7786157$.Comment: full color versio

Phonon Universal Transmission Fluctuations and Localization in Semiconductor Superlattices with a Controlled Degree of Order

We study both analytically and numerically phonon transmission fluctuations and localization in partially ordered superlattices with correlations among neighboring layers. In order to generate a sequence of layers with a varying degree of order we employ a model proposed by Hendricks and Teller as well as partially ordered versions of deterministic aperiodic superlattices. By changing a parameter measuring the correlation among adjacent layers, the Hendricks- Teller superlattice exhibits a transition from periodic ordering, with alterna- ting layers, to the phase separated opposite limit; including many intermediate arrangements and the completely random case. In the partially ordered versions of deterministic superlattices, there is short-range order (among any $N$ conse- cutive layers) and long range disorder, as in the N-state Markov chains. The average and fluctuations in the transmission, the backscattering rate, and the localization length in these multilayered systems are calculated based on the superlattice structure factors we derive analytically. The standard deviation of the transmission versus the average transmission lies on a {\it universal\/} curve irrespective of the specific type of disorder of the SL. We illustrate these general results by applying them to several GaAs-AlAs superlattices for the proposed experimental observation of phonon universal transmission fluctuations.Comment: 16-pages, Revte

Characterising current agroecological and regenerative farming research capability and infrastructure, and examining the case for a Living Lab network [Final report]

Agriculture is a major cause of greenhouse gas (GHG) emissions, biodiversity loss, and pollution. Agroecological and regenerative farming have been advocated as alternative approaches that may have fewer negative (or even net positive) environmental impacts than conventional agriculture at farm- and landscape-scales, leading to considerable interest in these approaches (Newton et al. 2020; Bohan et al. 2022; Prost et al. 2023). This report forms the third part of a Defra-funded project Evaluating the productivity, environmental sustainability and wider impacts of agroecological and regenerative farming systems compared to conventional systems. The first part of this project was a rapid evidence review of agroecological and regenerative farming systems and their impacts (Burgess et al. 2023), and the second reported interview findings to examine farmer and stakeholder perspectives on barriers and enablers in agroecological and regenerative farming (Hurley et al. 2023). This third part of the project characterised the current research capability in agroecology and regenerative farming, and explored the potential role of a new ‘living lab’ trial network. Three objectives are addressed in this report: 1) Characterise the existing agroecological and regenerative farming research capability and infrastructure in the UK. 2) Explore lessons from recent research initiatives and identify key research gaps, to inform a potential UK living labs trials network in agroecology/regenerative farming. 3) Develop recommendations for a new living lab trial or research network in agroecology/regenerative farming. Objective 1 was addressed through an online survey to gather quantitative and qualitative data on current research initiatives and networks in regenerative farming and agroecology. There were 22 respondents from 20 organisations (Section 2.2). Key findings from the survey: • The size and the timescales of research initiatives varied substantially from single sites to networks of 50-100 sites and with agroecological/regenerative practices applied from one to over 20 years. • All the survey respondents applied multiple agroecological/regenerative processes and had multiple target outcomes. • Just under 40% of respondents are not currently collecting data from their network. • Three-quarters of the survey participants not currently collecting data stated they would like to collect data, given more funding, knowledge or support. • Biodiversity was one of the most frequent target outcomes, and data collection most frequently focussed on biodiversity. • Face-to-face and email communication was most frequently used between farms in a network. Around two-thirds of respondents also held farm demonstration days as a means of knowledge exchange. • Most of the research initiatives and networks were funded by charities, NGOs or funded themselves, with a smaller number funded by UK or EU government funding. • Growing to incorporate more farms and researchers and developing knowledge exchange further were prioritised as future aspirations by survey respondents. Incorporating more researchers and applying for funding were also a focus for many research initiatives. • Targeted funding was seen as very important in achieving future aspirations by most respondents, along with improved connections with farmers and landowners and improved skills and information for knowledge exchange. Improved infrastructure and monitoring tools were emphasised less, but still considered important. The online survey results illustrate the wide range of current research initiatives in agroecology and regenerative farming, which vary from small-scale trials on a few farms to robust, repeatable data collection across a large network. To illustrate the range of approaches in more details, five case studies were described (Section 2.3) which included an ongoing living lab network, three research project and a long-term demonstration farm. Key characteristics of eight European living labs were also summarised through a network of EU agroecology living labs (the ALL-Ready project; Section 2.4). Objective 2 was addressed through an online workshop, at which participants responded to questions about research gaps and priorities, infrastructure needs, and the barriers and enablers to data sharing and access (Section 3). Participants views were gathered through online discussion boards and facilitated verbal discussion (Figure 1). Key themes and conclusions from the workshop: • Many of the impacts of agroecology and regenerative practices remain poorly understood, with biodiversity and greenhouse gas emissions highlighted. • Impacts on multiple potential benefits and trade-offs (e.g. yield vs. biodiversity vs. greenhouse gas emissions) need to be understood. The variation in responses (e.g. between soil types or regions) was seen as a priority area for research to improve the understanding of scaling-up. • Research needs to be conducted at adequate temporal and spatial scales given the timescales needed for impacts of these practices to become apparent. • There may be a bias in farmer participation in agroecological and regenerative agriculture research (those who can afford the time and money). • Understanding transitions to agroecology and regenerative farming across different types of farm business was raised as a research gap along with investigating the role of knowledge in these types of practice. This was reflected in the discussion of infrastructure and skills, with support (better guidance, input from advisors) and upskilling/improvements in education seen as priorities to support transitions. • The role of economic drivers, including subsidies and supply chain structures, is a research priority to understand why and how farmers may transition to these farming practices. • Standardised assessments and monitoring tools (including farmer apps) were highlighted to support future research, in particular standardised soil carbon assessments. Hubs to loan monitoring equipment to farmers were also suggested. • The time commitment needed was seen as an impediment to data collection by farmers, with comments that research initiatives worked better with someone external collecting data. • Data quality and formats were raised as barriers to data sharing in agroecology/regenerative farming. Formats that can be easily read across a range of software were suggested as a solution, along with more standardised approaches in data collection. • Integration and sharing of data across platforms were another solution, in particular for regulatory data (e.g. pesticide usage). • A potential tension was raised between standardising monitoring approaches and data collection, and constraining innovation by farmers. • Our understanding of how widespread agroecological and regenerative farming practices are, and which are being used / in what combinations, is constrained by lack of uptake data. Practices are being implemented with or without subsidies, and in varying combinations with more conventional approaches. Without these uptake data, larger scale research and modelling may be constrained. The online survey findings, case studies and lessons learnt from the workshop participants informed the development of recommendations for a future living labs network in the UK (Objective 3, Section 4). Four options were proposed: i) Develop a standardised methodology or protocol for each of the 12 attributes listed for assessment within the Global Farm Metric, to support consistency of farm measurements. ii) New research projects funded to collect standardised data on impacts and trade-offs across existing networks of farms applying agroecological / regenerative practices. This would maximise research synergies with existing networks. iii) New research network set up to apply agroecological / regenerative practices on commercial farms, co-designed between farmers and researchers. Standardised data collection on impacts and trade-offs. iv) Long-term living lab UK network set up, within which facilitation roles and research projects funded. These options could be applied in combination (e.g. a standardised methodology (i) developed within (iv) a long-term living lab network ). Which options are taken forward will depend on funding and factors such as the structure of available funding and timescales. Indicative costs were provided for field surveys of greenhouse gases and biodiversity, two of the impacts identified as research priorities in the workshop

The impact of COVID-19 on farmers’ mental health: a case study of the UK

In this paper, we use a UK case study to explore how the COVID-19 pandemic affected the mental health (emotional, psychological, social wellbeing) of farmers. We outline the drivers of poor farming mental health, the manifold impacts of the pandemic at a time of policy and environmental change, and identify lessons that can be learned to develop resilience in farming communities against future shocks

Landscapes of support for farming mental health: adaptability in the face of crisis

Poor mental health is an important and increasingly prevalent issue facing the farming industry. The adaptability of what we, in this article, describe as ‘landscapes of support’ for farming mental health is important to allow support systems to adapt successfully in times of crisis. The term ‘landscapes of support’ refers to the range of support sources available to farmers, including government, third sector bodies and farming/community groups. This article seeks to understand the factors influencing the adaptability of these landscapes of support, especially at a time of crisis. Using a case study of the UK, we undertook a literature review, interviews with 22 mental health support providers and an online survey of people within landscapes of support (93) and farmers themselves (207). We also held an end-of-project workshop. Using an adapted three-point framework to assess adaptability, we found that support-giving organisations adapted during the pandemic using a range of interventions (e.g., enhanced digital offering, use of media), but implementation was affected by organisational challenges (e.g., limited digital training, funding shortfalls, staff trauma) and operational constraints (e.g., lack of capacity, rural digital divide, tension between providers, stigma). We discuss how landscapes of support for farming mental health can be made more sustainable to deal with future shocks

WD + MS systems as the progenitor of SNe Ia

We show the initial and final parameter space for SNe Ia in a ($\log P^{\rm i}, M_{\rm 2}^{\rm i}$) plane and find that the positions of some famous recurrent novae, as well as a supersoft X-ray source (SSS), RX J0513.9-6951, are well explained by our model. The model can also explain the space velocity and mass of Tycho G, which is now suggested to be the companion star of Tycho's supernova. Our study indicates that the SSS, V Sge, might be the potential progenitor of supernovae like SN 2002ic if the delayed dynamical-instability model due to Han & Podsiadlowski (2006) is appropriate. Following the work of Meng, Chen & Han (2009), we found that the SD model (WD + MS) with an optically thick wind can explain the birth rate of supernovae like SN 2006X and reproduce the distribution of the color excess of SNe Ia. The model also predicts that at least 75% of all SNe Ia may show a polarization signal in their spectra.Comment: 6 pages, 2 figures, accepted for publication in Astrophysics & Space Science (Proceeding of the 4th Meeting on Hot Subdwarf Stars and Related Objects, edited by Zhanwen Han, Simon Jeffery & Philipp Podsiadlowski

Evaluating the productivity, environmental sustainability and wider impacts of agroecological compared to conventional farming systems [Evidence project final report]

•Context, aim and objectives: Existing agriculture systems in the UK are effective at producing safe and relatively cheap food, but they are a cause of greenhouse gas emissions, biodiversity loss, and soil degradation. It has been proposed that greater use of agroecological and regenerative farming would lead to more positive effects. The aim of this project was to evaluate the productivity, environmental sustainability and wider impacts of agroecological compared to conventional farming, by addressing three objectives: 1. to undertake an evidence review of regenerative/agroecological farming systems, 2. to assess the risks, barriers and opportunities, and identifying gaps in the knowledge, and 3. to characterise agroecological farming research capability in the UK, explore gaps and priorities, and explore the potential role of a new “living lab” trial network. •The research has been presented in three separate reports (Burgess et al. 2023, Hurley et al. 2023, and Staley et al. 2023), which are attached as appendices. The main results are summarised here. •Method: Objective 1 was addressed using a desk-based rapid evidence review, and the level of confidence in the analysis was determined using the IPBES four-box model (IPBES 2017, 2018). Objective 2 was addressed by in-depth semi-structured interviews with 23 respondents including farmers in late 2022. The interviews were used to explore definitions of agroecological and regenerative farming, barriers to the adoption, and views towards the concept of ‘living labs’. Objective 3 was addressed through an online survey with 22 respondents from 20 organisations in January and February 2023, an online workshop with 34 participants in January 2023, and informed by the findings of work to address Objectives 1 and 2. •Results and discussion: 1.1 Defining and characterising agroecological farming systems. A review of definitions highlighted, in brief, that organic farming places strong restrictions on inputs, agroecological analyses often focus on principles, and regenerative farming typically emphasises the enhancement of soil health and biodiversity at a farm scale. The stakeholder interviews demonstrated that the terms regenerative agriculture and agroecology are employed interchangeably by some, sequentially by others (with regenerative practices seen as steps towards a bigger whole-farm agroecological system), and viewed by some as discrete (who recognise the social justice, economic and political aspects of agroecology). Within these different interpretations, regenerative practices are often assumed to be those that minimise tillage and bare soil, foster plant diversity, and reduce the use of pesticides and synthetic fertilizers. We noted that the impact of organic, agroecological or regenerative systems on greenhouse gas emissions was implicit rather than explicit. We identified 16 agroecological practices that could be used in the UK: crop rotations, conservation agriculture, cover crops, organic crop production, integrated pest management, the integration of livestock to crop systems, the integration of crops to livestock systems, field margin practices, pasture-fed livestock, multi-paddock grazing, organic livestock systems, tree crops, tree-intercropping, multistrata agroforestry and permaculture, silvopasture, and rewilding. 1.2. Impact of agroecological practices at farm-scale Our detailed review (see Burgess et al. 2023) highlighted that the 16 agroecological practices tended to increase soil and biomass carbon and biodiversity at a field- or farm scale relative to a stated baseline. The soil carbon benefits were due to increased crop cover, the introduction of grass into arable systems, reduced cultivation, and/or the addition of soil amendments. The biodiversity benefits were derived from an increased diversity of crops and habitats, introducing plants that attract pollinators, reduced grazing pressure, and/or reduced use of pesticides and herbicides. Gaps in knowledge were highlighted particularly in terms of greenhouse gas emissions and biodiversity. The analysed effect on yields, product values, and input costs varied according to the practice and the baseline comparison. Hence in most cases, a farmer will need to balance trade-offs, perhaps guided by tools such as financial, economic, or life cycle analyses. In some cases, such as organic farming, a reduction in profitability due to a reduction in yield and certification costs may be compensated by an increase in product price. 1.3 Modelling agroecological systems in a UK context Our review highlighted existing modelling frameworks such as ASSET, ERAMMP IMP, EVAST and NEVO that could be repurposed to model agroecological systems across the UK. However we identified three barriers to their successful use. Firstly, modellers need to quantify the links between agroecological scenarios, spatial contexts and selected parameters within the underlying models. Secondly, the lack of readily available experimental data on the effect of agroecological practices and their change over time means that parameterising models remains challenging, and the alternative use of expert-based scoring or benefits transfer approaches can result in very large levels of uncertainty. Thirdly, a validated assessment of the aggregated impact of agroecological practices at a national scale will require effective national monitoring approaches that can assess the level of implementation of agroecological practices. 2. Opportunities from and barriers to a transition to agroecological systems: The uptake of agroecological practices by farm businesses depends on the balance between the opportunities offered and the barriers to implementation. As indicated in 1.2, the opportunities include increased biomass carbon, increased soil carbon in surface layers, and increased on-farm biodiversity. Supermarkets could support environmentally-positive practices, but there is also a strong drive for low food prices. The barriers to some agroecological practices will be geographical or incompatibility with management objectives at the farm-level. However, where these are not constraints, the major barriers are often related to uncertainty in the effect of the practices on yields and costs, and the need to finance the initial investment and certification costs. Enablers to overcome those barriers include knowledge exchange (particularly as the promotion of agroecological practices is not driven by organisations wanting to sell a product) and financial incentives (with a focus on market mechanisms that differentiate between desired and undesired societal outcomes). Evidence from other countries, particularly France, show that agroecological transitions can succeed where the right combination of policy instruments (e.g. grants, support for advice and collaboration, cultural support) are sustained by long-term political will. 3.1 Existing agroecological farming research capability and infrastructure in the UK: The online survey results indicate that most agroecological farming research initiatives and networks were funded by charities, NGOs, or funded by themselves, with some receiving UK or EU government funding. The initiatives ranged from single sites to networks of 50-100 sites, and with agroecological practices applied from one to over 20 years. Farmer participation in such research may be biased to those who can afford the time and money. Five case studies are examined in the main report (Staley et al. 2023) including an ongoing living lab network, three research projects, and a long-term demonstration farm. Only about 60% of respondents were collecting data from their network, often focused on biodiversity. About three-quarters of those not collecting data, would collect data given more funding, knowledge, or support. Face-to-face and email communication was most frequently used between farms in a network. Around two-thirds of respondents held farm demonstration days as a means of knowledge exchange, and further knowledge exchange was a common future aspiration. 3.2 Research gaps and priorities: The survey and workshop supported the observation from 1.2 that many of the impacts of agroecology practices, especially in relation to greenhouse gas emissions and biodiversity, remain poorly understood. Although 1.2 focused on farm-level effects, the consequential effects of, for example, reduced yields with agroecological practices remains a pertinent area for research. The variation in responses between soil types or regions would also be useful to improve the understanding of scaling-up opportunities. The need to support research over a sustained time period was also highlighted as several years are often needed for effects to become apparent. The transition to agroecological farming across different types of business requires the need for farmer support and changes in agricultural education. The role of economic drivers and supply chain structures in supporting agroecological practices also requires more research. Standardisation of data quality and formats, in particular for regulatory data, could help reduce some barriers, but it could also constrain innovation. National assessments of agroecological practices are also constrained by a lack of uptake data. 3.3 Informing a potential UK living labs trial network Living labs have been defined as “user-centred, open innovation ecosystems based on a systematic user co-creation approach, integrating research and innovation processes in real life communities and settings” (Malmberg et al. 2017). Important roles for a living labs network include providing robust locally-relevant evidence of the productivity and financial viability of agroecological farming, improving data standardisation, and encouraging collaboration between farmers, organisations, and researchers for data collection, sharing, and use. The role of Defra in a living labs network should be negotiated carefully with existing stakeholders involved in agroecological/regenerative transitions. Such a network should be sufficiently resourced in order to fund research and knowledge exchange and in order to build capacity among farmers and organisational stakeholders. Building on the response of the survey, case studies, and workshops, the benefits and disadvantages of four options were examined: 1) Develop a standardised methodology or protocol to support consistency of farm measurements. Soil carbon and farm carbon accounting were particularly highlighted. 2) To maximise synergies within existing agroecological farm networks with standardised data collection. 3) A new research network set up to apply agroecological practices on commercial farms, co-designed between farmers and researchers, with standardised data collection on impacts and trade-offs. 4) A long-term living lab UK network set up, with funded facilitation roles and research projects. Some of the above options could be applied in combination. The optimal option will depend on the ambition of Defra and the available funding and timescales

The mass-to-light ratio of rich star clusters

We point out a strong time-evolution of the mass-to-light conversion factor eta commonly used to estimate masses of unresolved star clusters from observed cluster spectro-photometric measures. We present a series of gas-dynamical models coupled with the Cambridge stellar evolution tracks to compute line-of-sight velocity dispersions and half-light radii weighted by the luminosity. We explore a range of initial conditions, varying in turn the cluster mass and/or density, and the stellar population's IMF. We find that eta, and hence the estimated cluster mass, may increase by factors as large as 3 over time-scales of 50 million years. We apply these results to an hypothetic cluster mass distribution function (d.f.) and show that the d.f. shape may be strongly affected at the low-mass end by this effect. Fitting truncated isothermal (Michie-King) models to the projected light profile leads to over-estimates of the concentration parameter c of delta c ~ 0.3 compared to the same functional fit applied to the projected mass density.Comment: 6 pages, 2 figures, to appear in the proceedings of the "Young massive star clusters", Granada, Spain, September 200

Quadriceps volumes are reduced in people with patellofemoral joint osteoarthritis

Objectives: This study aimed to (1) compare the volumes of vastus medialis (VM), vastus lateralis (VL), vastus intermedius and rectus femoris and the ratio of VM/VL volumes between asymptomatic controls and patellofemoral joint osteoarthritis (PFJ OA) participants; and (2) assess the relationships between cross-sectional area (CSA) and volumes of the VM and VL in individuals with and without PFJ OA. Methods: Twenty-two participants with PFJ OA and 11 controls aged ≥40 years were recruited from the community and practitioner referrals. Muscle volumes of individual quadriceps components were measured from thigh magnetic resonance (MR) images. The CSA of the VM and lateralis were measured at 10 equally distributed levels (femoral condyles to lesser femoral trochanter). Results: PFJ OA individuals had smaller normalized VM (mean difference 0.90 cm ·kg , α = 0.011), VL (1.50 cm ·kg , α = 0.012) and rectus femoris (0.71 cm ·kg , α = 0.009) volumes than controls. No differences in the VM/VL ratio were observed. The CSA at the third level (controls) and fourth level (PFJ OA) above the femoral condyles best predicted VM volume, whereas the VL volume was best predicted by the CSA at the seventh level (controls) and sixth level (PFJ OA) above the femoral condyles. Conclusion: Reduced quadriceps muscle volume was a feature of PFJ OA. Muscle volume could be predicted from CSA measurements at specific levels in PFJ OA patients and controls