Modeling production efficiency and greenhouse gas objectives as a function of forage production of dairy farms using copula models

Dairy farms are systems with multiple dependent variables whose practices influence their economic and environmental performances. Decisions made and actions taken to improve environmental performances of dairy farms carry the risk of decreasing farm profitability. Correlations among multiple variables must therefore be considered to reliably assess risks of improving environmental performances of farms. We applied copula models to a dataset of conventional dairy farms surveyed in France to decscribe relationships among their characteristics, such as forage dry matter (DM) production, milk production, and greenhouse gas (GHG) emissions. By modeling relationships among farm characteristics, copula models can identify the characteristics' joint distributions, unlike other statistical methods. For dairy farms, copula models are useful for estimating probabilities of reaching a milk production goal or not exceeding a regulatory emission limit as a function of forage production. For instance, when a farm produced at least 4,500 kg DM/livestock unit/year of maize silage, the probability of producing at least 7,000 l milk/cow/year was 75%, while the probability of emitting less than 7,000 kg CO2 eq./farm/year (a value close to the mean of 6669 kg CO2 eq./farm/year for all of the farms) was 48%. When the same amount of grass from pasture was produced, these probabilities changed to 48% and 78%, respectively (i.e., decreased probability of reaching a production goal, but increased probability of not exceeding an emission threshold). Farmers must make trade-offs, since increased milk production goals are likely to increase GHG emissions per farm and/or reduce GHG emission intensities per l of milk, but are less likely to be reached for a given amount of forage DM. By providing information about relationships among farm characteristics that other statistical approaches cannot, copula models are useful for investigating these trade-offs.Industrial Ecolog

NMR and NQR Fluctuation Effects in Layered Superconductors

We study the effect of thermal fluctuations of the s-wave order parameter of a quasi two dimensional superconductor on the nuclear spin relaxation rate near the transition temperature Tc. We consider both the effects of the amplitude fluctuations and the Berezinskii-Kosterlitz-Thouless (BKT) phase fluctuations in weakly coupled layered superconductors. In the treatment of the amplitude fluctuations we employ the Gaussian approximation and evaluate the longitudinal relaxation rate 1/T1 for a clean s-wave superconductor, with and without pair breaking effects, using the static pair fluctuation propagator D. The increase in 1/T1 due to pair breaking in D is overcompensated by the decrease arising from the single particle Green's functions. The result is a strong effect on 1/T1 for even a small amount of pair breaking. The phase fluctuations are described in terms of dynamical BKT excitations in the form of pancake vortex-antivortex (VA) pairs. We calculate the effect of the magnetic field fluctuations caused by the translational motion of VA excitations on 1/T1 and on the transverse relaxation rate 1/T2 on both sides of the BKT transitation temperature T(BKT)<Tc. The results for the NQR relaxation rates depend strongly on the diffusion constant that governs the motion of free and bound vortices as well as the annihilation of VA pairs. We discuss the relaxation rates for real multilayer systems where the diffusion constant can be small and thus increase the lifetime of a VA pair, leading to an enhancement of the rates. We also discuss in some detail the experimental feasibility of observing the effects of amplitude fluctuations in layered s-wave superconductors such as the dichalcogenides and the effects of phase fluctuations in s- or d-wave superconductors such as the layered cuprates.Comment: 38 pages, 12 figure

Global Retinoblastoma Presentation and Analysis by National Income Level

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4) were female. Most patients (n = 3685 84.7%) were from low-and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 62.8%), followed by strabismus (n = 429 10.2%) and proptosis (n = 309 7.4%). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 95% CI, 12.94-24.80, and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 95% CI, 4.30-7.68). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs. © 2020 American Medical Association. All rights reserved

Adaptive Clustering Using Mobile Agents in Wireless Ad-Hoc Networks

A Mobile ad-hoc network is a multihop wireless network, where nodes communicate with each other without any pre-deployed infrastructure. The most important problem on such dynamic networks is to find routing algorithms well performing in most cases. Cluster based algorithms are among the most effective and scaleable approaches. Up till now creation and maintenance clusters were mostly based on basic heuristic methods. Deploying mobile agents has several advantages in the ad-hoc environment due to their flexible, robust and autonomous nature, and their use seems promising for the clustering problem as well. In our proposed architecture every cluster has a clustering agent that is capable of making membership modification decisions, transferring nodes and splitting or merging clusters. Communication is used only between neighbouring agents to reduce the signalling overhead. Clustering decisions can be based on several network parameters modified by an adaptation mechanism to provide adequate performance even under dynamic conditions

Beyond agroecology: Agricultural rewilding, a prospect for livestock systems

International audienceCONTEXT: Agricultural intensification is a major cause of biodiversity loss. Biodiversity conservation and restoration generally involve human intervention. In comparison, rewilding, a radically different approach to address the erosion of biodiversity, aims to increase the ability of ecological processes to act with little or no human intervention, and thus to enhance biodiversity and the supply of ecosystem services. Rewilding, including that of agricultural systems, has been examined from ecological and social perspectives but rarely from an agricultural perspective. OBJECTIVE: In this review of the literature and case studies, we (i) analyse whether and how rewilding of agricultural systems, particularly livestock systems, can help conserve and restore biodiversity and offer new prospects, and (ii) identify research questions about rewilding of agricultural systems. METHODS: We researched literature in the Web of Science Core Collection that focussed on rewilding, agriculture, and interactions between them. We also identified agricultural rewilding projects established for at least five years in the United Kingdom (UK) to analyse their approaches and characteristics. RESULTS AND CONCLUSIONS: Agricultural rewilding is an emerging form of land use that we conceptually position on a gradient between agroecology and rewilding. It combines restoration of ecological processes with some degree of agricultural production, most often of herbivores. A selection of 11 agricultural rewilding projects in the UK had areas of 121–4402 ha. The projects targeted 48 key species/breeds, 24 of which were ecosystem engineers: 19 grazers, four pig breeds and Eurasian beavers. The main actions to enhance rewilding were extensive grazing and habitat restoration. The main economic activities were meat or animal sales, tourism and education programmes. Agricultural rewilding may provide a multifunctional model to which livestock systems with herbivores may transition to respond better to environmental concerns. However, because it may lack economic viability and conflict with local culture and traditions, government policies may be needed to encourage more farmers to adopt it. SIGNIFICANCE: Agricultural rewilding offers new prospects for livestock systems with herbivores. We identified key research questions about its relation to agroecology and rewilding, conditions necessary to implement it, its potential for plant production and its value for farmers. In addition, the forms it can take remain to be explored, and the potential influence of these forms on biodiversity, ecosystem services and environmental impacts needs to be characterised. Exploring the forms that agricultural rewilding may take requires close collaboration among ecologists, animal scientists, agronomists, and social scientists

An improved indicator framework to assess and optimise ecosystem services provided by permanent grasslands

Livestock farming systems are criticised for their environmental impacts, but they can also provide various ecosystem services to society, especially permanent grasslands. This study aimed to develop a method to assess impacts of permanent grasslands and their management on the supply of regulation and maintenance ecosystem services applicable at the field and/or farm level. To this end, an existing framework, the Ecological Focus Areas Calculator, was adapted to (i) consider attributes and location parameters of permanent grasslands and (ii) integrate impacts of permanent grassland management on the provision of ecosystem services, which yielded a score for each ecosystem service. The method developed was tested with two farms. Analysis of mapping results, which calculated a score for each ecosystem service for each permanent grassland field on each farm, highlighted the direct relation between the novel approach and the underlying ecological theory of impacts on ecosystem services. On each farm, management practices influenced ecological processes differently, which led to different changes in ecosystem service scores. Applying this novel approach directly with farmers can help them identify win–win situations and trade-offs and target their management, by identifying the fields where it may be more optimal to focus certain management practices to decrease the farm’s overall impacts based on trade-offs at the individual-field scale. The novel approach combined representation of the complexity of interactions between management practices and ecological processes with the ability to provide results that are easy to use and interpret. Future development could help increase the accuracy of estimated impacts of management practices on ecosystem services, such as by adding additional practices or considering their long-term effects on ecological processes. The novel approach could also be updated to assess impacts of other types of land use, such as arable land, or management practices. The final goal of such a tool is to support decision-making to optimise the ecosystem services supplied by farming systems, which has advantages for society and for farmers

Determination of Critical Transmission Range in Ad-Hoc Networks

Ad-hoc networks are wireless mobile networks that do not rely on preexisting infrastructure. In such networks, multi-hop routing is used to achieve large degree of network connectivity and each node in the network acts as a router for its neighbors. The range of the radio transceivers is chosen as a trade-off between full network connectivity, the reuse of the available spectrum, and power consumption. This paper presents an algorithm to calculate the minimum transmission range of the transceivers that is required to achieve, with some probability, full network connectivity. Furthermore, we also study the effect of mobility on this value. 1