318 research outputs found
The EU Clinical Trials Regulation: Key Priorities, Purposes and Aims and the Implications for Public Health
Regulating New Technologies: EU Internal Market Law, Risk and Sociotechnical Order
The chapter argues that, more than playing catch up with and being determined by technoscientific innovation, law also plays a leading role in the regulation of new technologies by shaping and directing the conditions of possibility for their development and market availability. The chapter charts some of the main ways in which EU internal market law retains its regulatory capacity and efficacy through techniques of negative and positive integration. These techniques centralize the harms or hazards relating to product safety as ātheā risks posed by new technologies. Designing regulation and limiting āriskā (through it) marginalizes and obscures other kinds of harms or hazards to which it might pertain. The current regulatory design also depoliticizes, naturalizes, and quells contestation around the approach taken and obscures other potential framings of regulation, such as by human rights and bioethics.</p
Documenting differences between early stone age flake production systems: An experimental model and archaeological verification
A kin-selection model of fairness in heterogeneous populations
Humans and other primates exhibit pro-social preferences for fairness. These preferences are thought to be reinforced by strong reciprocity, a policy that rewards fair actors and punishes unfair ones. Theories of fairness based on strong reciprocity have been criticized for overlooking the importance of individual differences in socially heterogeneous populations. Here, we explore the evolution of fairness in a heterogeneous population. We analyse the Ultimatum Game in cases where playersā roles in the game are determined by their status. Importantly, our model allows for non-random pairing of players, and so we also explore the role played by kin selection in shaping fairness. Our kin-selection model shows that, when individuals condition their behaviour on their role in the game, fairness can be understood as either altruistic or spiteful. Altruistic fairness directs resources from less valuable members of a genetic lineage to more valuable members of the same lineage, whereas spiteful fairness keeps resources away from the competitors of the actorās high-value relatives. When individuals express fairness unconditionally it can be understood as altruistic or selfish. When it is altruistic, unconditional fairness again serves to direct resources to high-value members of genetic lineages. When it is selfish, unconditional fairness simply improves an individualās own standing. Overall, we expand kin-selection based explanations for fairness to include motivations other than spite. We show, therefore, that one need not invoke strong reciprocity to explain the advantage of fairness in heterogeneous populations
Documenting differences between early stone age flake production systems: An experimental model and archaeological verification
This study investigates morphological differences between flakes produced via ācore and flakeā technologies and those resulting from bifacial shaping strategies. We investigate systematic variation between two technological groups of flakes using experimentally produced assemblages, and then apply the experimental model to the Cutting 10 Mid -Pleistocene archaeological collection from Elandsfontein, South Africa. We argue that a specific set of independent variables--and their interactions--including external platform angle, platform depth, measures of thickness variance and flake curvature should distinguish between these two technological groups. The role of these variables in technological group separation was further investigated using the Generalized Linear Model as well as Linear Discriminant Analysis. The Discriminant model was used to classify archaeological flakes from the Cutting 10 locality in terms of their probability of association, within either experimentally developed technological group. The results indicate that the selected independent variables play a central role in separating core and flake from bifacial technologies. Thickness evenness and curvature had the greatest effect sizes in both the Generalized Linear and Discriminant models. Interestingly the interaction between thickness evenness and platform depth was significant and played an important role in influencing technological group membership. The identified interaction emphasizes the complexity in attempting to distinguish flake production strategies based on flake morphological attributes. The results of the discriminant function analysis demonstrate that the majority of flakes at the Cutting 10 locality were not associated with the production of the numerous Large Cutting Tools found at the site, which corresponds with previous suggestions regarding technological behaviors reflected in this assemblage
LiXEdrom: High Energy Resolution RIXS Station dedicated to Liquid Investigation at BESSY II
LiXEdrom is an experimental station dedicated to high resolution RIXS measurements on liquid samples. It is equipped with two VLS gratings and advanced photon detector (MCP/phosphorous screen/CCD), covering soft X-ray range of 200 ā 1200 eV. The efficient differential pumping and cooling systems ensure successful executions of X-ray spectroscopy on liquid samples in vacuum. Liquid samples are introduced into the vacuum chamber by micro-jet or flow-cell techniques
More Competences than You Knew? The Web of Health Competences for Union Action in Response to the COVID-19 Outbreak
Effects of Gene-Environment Interactions on the Evolution of Social Behaviours
Inclusive fitness models in sociobiology emphasize the importance of relatedness, R, and synergy, S when exploring the evolution of social behaviours. Very few models explicitly consider āroleā, or environmental stimuli, influencing the expression of behaviours, and none consider genetic-environment interactions where genotype predisposes individuals to certain roles. I propose a third key variable for inclusive fitness models, Q, which describes the overlooked potential bias in the genetic composition of individuals exposed to an environmental stimulus ā here referred to as āroleā. I describe a model built from Priceās formula which can be presented in a āHamiltonās Ruleā format. I consider classic social behaviour models using this format, and find that the inclusion of gene-environment interactions dramatically changes the results. This, in conjunction with the increasing evidence supporting gene-environment interactions in eusocial caste determination, suggests that current inclusive fitness models may be missing key details about the evolution of social behaviours
- ā¦