14 research outputs found
Motorcycling edgework: A practice theory perspective
In an effort to elucidate a deep understanding of the experience of dangerous motorcycling behaviour, we employ a practice theory perspective, drawing out connections between the practice, the consumption of objects, and the meanings surrounding both. Using the Biographical Narrative Interpretive Method (BNIM), we offer possible explanations as to why, in the face of troubling accident statistics, some motorcyclists continue to drive at excessive speeds. Narrative accounts portray dangerous motorcycling practice as autotelic, impulsive edgework, incorporating a strong connection between rider and machine, and embedded with symbolic, emotional values that cannot be accounted for by traditional rational choice models. Our findings allow for the potential of policymakers to address such motorcycling practice in ways more meaningful to those engaged in it
Les dénombrements de foyers dans le comté de Hainaut (XIVe-XVIe siècle). /
Commission royale d'histoire. Publications in quarto
Recueil d'études suivi d'une table générale et d'un index de la collection des Albums : actes du colloque organisé à Chimay et à Fourmies les 7 et 8 mai 1992 /
Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy
Could predicting fatty acid profile by mid-infrared reflectance spectroscopy be used as a method to increase the value added by milk production chains?
ABSTRACT The aims of this work were (1) to develop prediction equations from mid-infrared spectroscopy (MIRS) to establish a detailed fatty acid (FA) composition of milk; (2) to propose a milk FA index, utilizing MIRS-developed equations, in which the precision of the FA-prediction equations is taken into account to increase the value of milk; and (3) to show application examples. A total of 651 bulk cow milk samples were collected from 245 commercial farms in northwest Italy. The results of the 651 gas chromatography analyses were used to establish (421 samples) and to validate (230 samples) the outcomes of the FA composition prediction that had been obtained by MIRS. A class-based approach, in which the obtained MIRS equations were used, was proposed to define a milk classification. The method provides a numerical index [milk FA index (MFAI)] that allows a premium price to be quantified to increase the value of a favorable FA profile of milk. Ten FA were selected to calculate MFAI, according to their relevance for human health and potential cheese sensory properties, and animal welfare and environmental sustainability were also considered. These factors were selected as dimensions of MFAI. A statistical analysis and expert judgment aggregation were performed on the selected FA by weighting the FA and normalizing the dimensions to reduce redundancy. A class approach was applied, using the precision of the MIRS equations to establish the classes. The median FA concentration of the data set was set as a reference value of class 0. The width, number, and limits of classes above and below the median were calculated using the 95% confidence level of the standard error of prediction, corrected with the bias of each FA. A progressive number and a positive or negative sign were assigned to each FA class above or below the median according to their role in the above mentioned dimensions. The sum of the numbers of each class, associated with its sign for each FA, was used to generate MFAI. The MFAI was applied to dairy farms characterized by different feeding strategies, all of which deliver milk to a commercial dairy plant. The MFAI values ranged from 0.7 to 4.2, and large variations, which depended on the cows' diet and forage quality, were observed for each feeding system. The proposed method has been found to be flexible and adaptable to several contexts on both intensive and extensive dairy farms
Prognostic and predictive role of CD8 and PD-L1 determination in lung tumor tissue of patients under anti-PD-1 therapy
International audienceBackgroundNo study has evaluated the predictive and prognostic role of CD8 and PD-L1 coexpression in non–small-cell lung cancer (NSCLC).MethodsWe analyzed RNA sequencing and/or immunohistochemistry staining in NSCLC patients from The Cancer Genome Atlas (n = 1016), and 34 metastatic NSCLC samples not treated by immunotherapy as prognostic cohorts. As predictive aspect of CD8 and PD-L1, we used 85 NSCLC patients treated with anti-PD-1. Two validation cohorts were used including 44 NSCLC patients treated with anti-PD-1 and an external cohort with different tumor types.ResultsIn prognostic cohorts, high CD8A expression was associated with longer OS (p = 0.02), while high CD274 mRNA was associated with poor prognosis (p = 0.05). In predictive cohort, high CD8 expression and CD8A mRNA were associated with longer progression-free survival (PFS) (p = 0.0002). There was no significant association between PD-L1 expression and PFS while high CD274 mRNA was associated with longer PFS (p = 0.009). A combination of CD8A and CD274 was highly predictive of outcome. These results were confirmed in the validation cohorts. This two-genes signature demonstrated similar results compared to gold standard signatures.ConclusionCD8 represents both a prognostic and predictive factor of outcomes, while PD-L1 share different prognostic and predictive roles