Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

AbstractLameness causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods. Eighty variables retrieved from AMS were summarized week-wise and used to predict 2 defined classes: nonlame and clinically lame cows. Variables were represented with 2 transformations of the week summarized variables, using 2-wk data blocks before gait scoring, totaling 320 variables (2×2×80). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3 or 4/4) or not lame (score 1/4). Both models achieved sensitivity and specificity values around 80%, both in calibration and cross-validation. At the optimum values in the receiver operating characteristic curve, the false-positive rate was 28% in the parity 1 model, whereas in the parity 2 model it was about half (16%), which makes it more suitable for practical application; the model error rates were, 23 and 19%, respectively. Based on data registered automatically from one AMS farm, we were able to discriminate nonlame and lame cows, where partial least squares discriminant analysis achieved similar performance to the reference method

Experienced and inexperienced observers achieved relatively high within-observer agreement on video mobility scoring of dairy cows

AbstractAssessment of lameness prevalence and severity requires visual evaluation of thelocomotion of a cow. Welfare schemes including locomotion assessments are increasingly being adopted, and more farmers and their veterinarians might implement a locomotion-scoring routine together. However, high within-observer agreement is a prerequisite for obtaining valid mobility scorings, and within-observer agreement cannot be estimated in a barn, because the gait of cows is dynamic and may change between 2 occasions. The objective of this study was to estimate the within-observer agreement according to the observers’ educational background and experience with cattle, based on video recordings with very diverse types of gait. Groups of farmers, bovine veterinarians, first- and fourth-year veterinary students, researchers, and cattle-inexperienced sensory assessors evaluated mobility using a 5-point mobility score system developed specifically for walking cows (n=102 observers). The evaluation sessions were similar for all groups, lasted 75 min, and were organized as follows: introduction, test A, short training session, break, and test B. In total, video recordings of 22 cows were displayed twice in a random order (11 cows in each test × 2 replicates). Data were analyzed applying kappa coefficient, logistic regression, and testing for random effects of observers. The crude estimates of 95% confidence interval for weighted kappa in test A and B ranged, respectively, from 0.76 to 0.80 and 0.70 to 0.75. When adjusting for the fixed effects of video sample and gait scoring preferences, the probability of assigning the same mobility score twice to the same cow varied from 55% (sensory assessors) to 72% (fourth-year veterinary students). The random effect of the individual observers was negligible. That is, in general observers could categorize the mobility characteristics of cows quite well. Observers who preferred to assess the attributes back arch or the overall mobility score (based on uneven gait) had the highest agreement, respectively, 69 or 68%. The training session seemed insufficient to improve agreement. Nonetheless, even novice observers were able to achieve perfect agreement up to 60% of the 22 scorings with merely the experience obtained during the study (introduction and training session). The relatively small differences between groups, together with a high agreement, demonstrate that the new system is easy to follow compared with previously described scoring systems. The mobility score achieves sufficiently high within-observer repeatability to allow between-observer agreement estimates, which are reliable compared with other more-complex scoring systems. Consequently, the new scoring scale seems feasible for on-farm applications as a tool to monitor mobility within and between cows, for communication between farmers and veterinarians with diverse educational background, and for lamenessbenchmarking of herds

Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines

[EN] The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. 'Big Top' (yellow flesh) and 'Magique' (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630-900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the 'Big Top' cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the 'Big Top' and 'Magique' cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R-2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines.This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds.Munera, S.; Blasco Ivars, J.; Amigo, J.; Cubero-García, S.; Talens Oliag, P.; Aleixos Borrás, MN. (2019). Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines. Biosystems Engineering. 182:54-64. https://doi.org/10.1016/j.biosystemseng.2019.04.001S546418

Quantum dynamics of crystals of molecular nanomagnets inside a resonant cavity

It is shown that crystals of molecular nanomagnets exhibit enhanced magnetic relaxation when placed inside a resonant cavity. Strong dependence of the magnetization curve on the geometry of the cavity has been observed, providing evidence of the coherent microwave radiation by the crystals. A similar dependence has been found for a crystal placed between Fabry-Perot superconducting mirrors. These observations open the possibility of building a nanomagnetic microwave laser pumped by the magnetic field

A Global Network of Science and Technology Advice in Foreign Ministries

This paper is a product of the International Dialogue on Science and Technology Advice in Foreign Ministries (Vienna Dialogue) in October 2016, involving more than twenty nations and several international organisations. The event was a key step to further develop the Foreign Minister Science and Technology Advisor Network (FMSTAN), growing from an initial group of five nations. The Vienna Dialogue was convened by the Fletcher School of Law and Diplomacy, Tufts University, and the International Institute for Applied Systems Analysis (IIASA) at the Vienna headquarters of IIASA, bringing together diplomats from foreign ministries to consider the value of evidence for informed decision-making by nations with regard to issues, impacts and resources within, across and beyond national boundaries. The evidence comes from the natural and social sciences with engineering and medicine as well as other areas of technology. By building common interests among nations, science is a tool of diplomacy, promoting cooperation and preventing conflict in our world. Science diplomacy was discussed as an international, interdisciplinary and inclusive process to help balance national interests and common interests in view of urgencies today and across generations in our globally-interconnected civilization

MCR-ALS on metabolic networks: Obtaining more meaningful pathways

[EN] With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraints can be included in the model, and the same source of variability can be present in different pathways, which is reasonable from a biological standpoint. This work follows a methodology developed for Pichia pastoris cultures grown on different carbon sources, lately presented in González-Martínez et al. (2014). In this paper a different grey modelling approach, which aims to incorporate a priori knowledge through constraints on the modelling algorithms, is applied to the same case of study. The results of both models are compared to show their strengths and weaknesses.Research in this study was partially supported by the Spanish Ministry of Science and Innovation and FEDER funds from the European Union through grants DPI2011-28112-C04-01 and DPI2011-28112-C04-02. The authors are also grateful to Biopolis SL for supporting this research.Folch-Fortuny, A.; Tortajada Serra, M.; Prats-Montalbán, JM.; Llaneras Estrada, F.; Picó Marco, JA.; Ferrer Riquelme, AJ. (2015). MCR-ALS on metabolic networks: Obtaining more meaningful pathways. Chemometrics and Intelligent Laboratory Systems. 142:293-303. https://doi.org/10.1016/j.chemolab.2014.10.004S29330314

Diet quality index as a predictor of treatment efficacy in overweight and obese adolescents: The EVASYON study

Background & aim: A diet quality index (DQI) is a tool that provides an overall score of an individual''s dietary intake when assessing compliance with food-based dietary guidelines. A number of DQIs have emerged, albeit their associations with health-related outcomes are debated. The aim of the present study was to assess whether adherence to dietary intervention, and the overall quality of the diet, can predict body composition changes. Methods: To this purpose, overweight/obese adolescents (n = 117, aged: 13–16 years; 51 males, 66 females) were recruited into a multi-component (diet, physical activity and psychological support) family-based group treatment programme. We measured the adolescents’ compliance and body composition at baseline and after 2 months (intensive phase) and 13 months (extensive phase) of follow-up. Also, at baseline, after 6 months, and at the end of follow-up we calculated the DQI. Results: Global compliance with the dietary intervention was 37.4% during the intensive phase, and 14.3% during the extensive phase. Physical activity compliance was 94.1% at 2-months and 34.7% at 13months and psychological support compliance were growing over the intervention period (10.3% intensive phase and 45.3% during extensive phase). Adolescents complying with the meal frequency criteria at the end of the extensive phase had greater reductions in FMI z-scores than those did not complying (Cohen''s d = 0.53). A statistically significant association was observed with the diet quality index. DQI-A variation explained 98.1% of BMI z-score changes and 95.1% of FMI changes. Conclusions: We conclude that assessment of changes in diet quality could be a useful tool in predicting body composition changes in obese adolescents involved in a diet and physical activity intervention programme backed-up by psychological and family support

Four-month incidence of suicidal thoughts and behaviors among healthcare workers after the first wave of the Spain COVID-19 pandemic

[EN] Healthcare workers (HCW) are at high risk for suicide, yet little is known about the onset of suicidal thoughts and behaviors (STB) in this important segment of the population in conjunction with the COVID-19 pandemic. We conducted a multicenter, prospective cohort study of Spanish HCW active during the COVID-9 pandemic. A total of n = 4809 HCW participated at baseline (May–September 2020; i.e., just after the first wave of the pandemic) and at a four-month follow-up assessment (October–December 2020) using web-based surveys. Logistic regression assessed the individual- and population-level associations of separate proximal (pandemic) risk factors with four-month STB incidence (i.e., 30-day STB among HCW negative for 30-day STB at baseline), each time adjusting for distal (pre-pandemic) factors. STB incidence was estimated at 4.2% (SE = 0.5; n = 1 suicide attempt). Adjusted for distal factors, proximal risk factors most strongly associated with STB incidence were various sources of interpersonal stress (scaled 0–4; odds ratio [OR] range = 1.23–1.57) followed by personal health-related stress and stress related to the health of loved ones (scaled 0–4; OR range 1.30–1.32), and the perceived lack of healthcare center preparedness (scaled 0–4; OR = 1.34). Population-attributable risk proportions for these proximal risk factors were in the range 45.3–57.6%. Other significant risk factors were financial stressors (OR range 1.26–1.81), isolation/quarantine due to COVID-19 (OR = 1.53) and having changed to a specific COVID-19 related work location (OR = 1.72). Among other interventions, our findings call for healthcare systems to implement adequate conflict communication and resolution strategies and to improve family-work balance embedded in organizational justice strategies.S

Laboratory and free-living gait performance in adults with COPD and healthy controls

Background Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised). Methods This case–control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately. Results Slower walking speed (−11 cm·s−1, 95% CI: −20 to −3) and lower cadence (−6.6 steps·min−1, 95% CI: −12.3 to −0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups. Conclusion Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD