Galton's Quincunx: Probabilistic causation in developmental behavior genetics

In what sense are associations between particular markers and complex behaviors made by genome-wide association studies (GWAS) and related techniques discoveries of, or entries into the study of, the causes of those behaviors? In this paper, we argue that when applied to individuals, the kinds of probabilistic ‘causes’ of complex traits that GWAS-style studies can point towards do not provide the kind of causal information that is useful for generating explanations; they do not, in other words, point towards useful explanations of why particular individuals have the traits that they do. We develop an analogy centered around Galton's “Quincunx” machine; while each pin might be associated with outcomes of a certain sort, in any particular trial, that pin might be entirely bypassed even if the ball eventually comes to rest in the box most strongly associated with that pin. Indeed, in any particular trial, the actual outcome of a ball hitting a pin might be the opposite of what is usually expected. While we might find particular pins associated with outcomes in the aggregate, these associations will not provide causally relevant information for understanding individual outcomes. In a similar way, the complexities of development likely render impossible any moves from population-level statistical associations between genetic markers and complex behaviors to an understanding of the causal processes by which individuals come to have the traits that they in fact have.     

硬件在环测试台模拟车辆电池的电压分布

驾驶辅助系统不仅是为了辅助驾驶员进行一般的驾驶活动,而且要能在关键情况下接管驾驶。使用原型车进行试驾是测试该系统最现实的方式,试驾可使驾驶辅助系统暴露在各种实际环境下,从而检查其可靠性。由于带有原型的测试驱动器成本很高,而且难以完全相同方式复制驾驶活动,因此在系统开发和测试过程中经常使用硬件在环（HiL）测试台。HiL测试台不仅提供相关硬件,还可以为这些被测系统（SUT）提供模拟环境。在实际车辆的试驾过程中,由于不同的环境影响,电气系统的电压会发生变化,这些变化是基于不断变化的电气负载影响。目前,车辆电气系统的电压变化无法在硬件在环测试台上模拟。为了确定电压变化的原因和潜在现象,需要对实际试驾记录数据进行检查,以了解潜在现象。然后将这些结果用于推导唯象激励,该唯象激励可用于模拟测试台上的真实电压曲线。本文分析了车辆测量结果,目的是找出车载电压长期和短期热变化的可能原因,提出一种在HiL测试台上进行虚拟测试驱动的情况下真实模拟电压变化的方法。