Measuring dairy cow welfare with real-time sensor-based data and farm records: a concept study

Welfare assessment of dairy cows by in-person farm visits provides only a snapshot of welfare and is time-consuming and costly. Possible solutions to reduce the need for in-person assessments would be to exploit sensor data and other routinely collected on-farm records. The aim of this study was to develop an algorithm to classify dairy cow welfare based on sensors (accelerometer and/or milk meter) and farm records (e.g. days in milk, lactation number). In total, 318 cows from six commercial farms located in Finland, Italy and Spain (two farms each) were enrolled for a pilot study lasting 135 days. During this time, cows were routinely scored using 14 animal-based measures of good feeding, health and housing based on the Welfare Quality® (WQ®) protocol. WQ® measures were evaluated daily or approximately every 45 days, using disease treatments from farm records and on-farm visits, respectively. WQ® measures were supplemented with daily temperature-humidity index to account for heat stress. The severity and duration of each welfare measure were evaluated, and the final welfare index was obtained by summing up the values for each cow on each pilot study day, and stratifying the result into three classes: good, moderate and poor welfare. For model building, a machine-learning (ML) algorithm based on gradient-boosted trees (XGBoost) was applied. Two model versions were tested: (1) a global model tested on unseen herd, and (2) a herd-specific model tested on unseen part of the data from the same herd. The version (1) served as an example on the model performance on a herd not previsited by the evaluator, while version (2) resembled a custom-made solution requiring in-person welfare evaluation for model training. Our results indicated that the global model had a low performance with average sensitivity and specificity of 0.44 and 0.68, respectively. For the herd-specific version, the model performance was higher reaching an average of 0.64 sensitivity and 0.80 specificity. The highest classification performance was obtained for cows in poor welfare, followed by cows in good and moderate welfare (balanced accuracy of 0.77, 0.71 and 0.68, respectively). Since the global model had low classification accuracy, the use of the developed model as a stand-alone system based solely on sensor data is infeasible, and a combination of in-person and sensor-based welfare evaluation would be preferable for a reliable welfare assessment. ML-based solutions, even with fair discriminative abilities, have the potential to enhance dairy welfare monitoring

Universality and the magnetic catalysis of chiral symmetry breaking

The hypothesis that the magnetic catalysis of chiral symmetry breaking is due to interactions of massless fermions in their lowest Landau level is examined in the context of chirally symmetric models with short ranged interactions. It is argued that, when the magnetic field is sufficiently large, even an infinitesimal attractive interaction in the appropriate channel will break chiral symmetry.Comment: 24 pages, 6 figures, REVTeX. The final version with minor corrections. To appear in Phys Rev D60 (1999

Mott Transition in An Anyon Gas

We introduce and analyze a lattice model of anyons in a periodic potential and an external magnetic field which exhibits a transition from a Mott insulator to a quantum Hall fluid. The transition is characterized by the anyon statistics, $\alpha$, which can vary between Fermions, $\alpha=0$, and Bosons, $\alpha=1$. For bosons the transition is in the universality class of the classical three-dimensional XY model. Near the Fermion limit, the transition is described by a massless $2+1$ Dirac theory coupled to a Chern-Simons gauge field. Analytic calculations perturbative in $\alpha$, and also a large N-expansion, show that due to gauge fluctuations, the critical properties of the transition are dependent on the anyon statistics. Comparison with previous calcualations at and near the Boson limit, strongly suggest that our lattice model exhibits a fixed line of critical points, with universal critical properties which vary continuosly and monotonically as one passes from Fermions to Bosons. Possible relevance to experiments on the transitions between plateaus in the fractional quantum Hall effect and the magnetic field-tuned superconductor-insulator transition are briefly discussed.Comment: text and figures in Latex, 41 pages, UBCTP-92-28, CTP\#215

Thermodynamics of an Anyon System

We examine the thermal behavior of a relativistic anyon system, dynamically realized by coupling a charged massive spin-1 field to a Chern-Simons gauge field. We calculate the free energy (to the next leading order), from which all thermodynamic quantities can be determined. As examples, the dependence of particle density on the anyon statistics and the anyon anti-anyon interference in the ideal gas are exhibited. We also calculate two and three-point correlation functions, and uncover certain physical features of the system in thermal equilibrium.Comment: 18 pages; in latex; to be published in Phys. Rev.

Analytic structure of rho meson propagator at finite temperature

We analyse the structure of one-loop self-energy graphs for the rho meson in real time formulation of finite temperature field theory. We find the discontinuities of these graphs across the unitary and the Landau cuts. These contributions are identified with different sources of medium modification discussed in the literature. We also calculate numerically the imaginary and the real parts of the self-energies and construct the spectral function of the rho meson, which are compared with an earlier determination. A significant contribution arises from the unitary cut of the pi-omega loop, that was ignored so far in the literature

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Land use response to agricultural policy and market movement on Finnish dairy-farms

MTT Agrifood Research Finland, Economic Research, PO Box 3, FIN-00411 Helsinki, Finland, e-mail: [email protected] This study estimates an econometric model for land allocation on Finnish dairy-farms in 1989-1997. Land allocation equations are estimated jointly with the demand of purchased feeds and the supply for milk. The model is used to test how agricultural policy reforms have changed land allocation, animal feeding, and the supply for milk on Finnish dairy-farms. The results suggest that land allocations respond inelastically to the changes in income subsidies paid through the land areas. The use of feed concentrates in milk cows' diet has increased mainly because feed concentrate prices have decreased, rather than through the effects of acreage-based income subsidies on land allocations. At the same time, feed grain production has decreased. Farm size has an important effect on dairy-farm land use. Farmers, who have expanded milk production, have specialised in roughage production. The diet of cows has been intensified by purchasing more feed concentrates. The results also suggest that tradable milk quotas have allowed for a significant re-allocation of milk output between farms. The milk output turned out to be endogenous over the period of tradable milk quotas (1994-1997).

The economic impact of a new animal disease:same effects in developed and developing countries?

Animal disease outbreaks generate a range of economic and non-economic impacts. While a significant number of research studies have estimated the effects of various diseases in a variety of contexts, examining the differential impacts and implications associated with the introduction of a novel disease into a developing country, as opposed to a developed one, is a rich area for further research. In this paper, the authors highlight some of the key dimensions and implications associated with the impacts of new diseases, how they differ in different contexts, and their implications for public polic

Trade-offs between catastrophic assistance and subsidized insurance in European agriculture

Risk management in agriculture is a major policy issue in current EU agriculture policy reforms. Public support systems may play two different roles, one as a device to deliver disaster assistance and another to enhance insurance for marketable risks. This paper contributes to the literature by analysing the trade-offs between providing catastrophic assistance and subsidizing insurance premiums. The goal of the study is to highlight policy options that are coherent in stabilizing income volatility while limiting distortions of public intervention. In this study, farmer incomes were first modelled using Monte Carlo simulation, and options were then ranked by applying the stochastic efficiency with respect to a function. The results suggest that, if catastrophic assistance is available, even higher insurance support is needed to make it a preferred option. The results highlight the fact that well defined and credible ex ante rules for the use of disaster assistance are essential to enable insurance markets to develop. One possibility would be to make a farmer's eligibility for disaster aid conditional on his or her participation in the insurance programmes