The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy

Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions (an effect we call stalemate filtering). In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemate filtering for improving the decision-making abilities of group-living animals.     

Deep Learning model for markerless tracking in spinal SBRT

Stereotactic Body Radiation Therapy (SBRT), alternatively termed Stereotactic ABlative Radiotherapy (SABR) or Stereotactic RadioSurgery (SRS), delivers high dose with a sub-millimeter accuracy. It requires meticulous precautions on positioning, as sharp dose gradients near critical neighboring structures (e.g. the spinal cord for spinal tumor treatment) are an important clinical objective to avoid complications such as radiation myelopathy, compression fractures, or radiculopathy. To allow for dose escalation within the target without compromising the dose to critical structures, proper immobilization needs to be combined with (internal) motion monitoring. Metallic fiducials, as applied in prostate, liver or pancreas treatments, are not suitable in clinical practice for spine SBRT. However, the latest advances in Deep Learning (DL) allow for fast localization of the vertebrae as landmarks. Acquiring projection images during treatment delivery allows for instant 2D position verification as well as sequential (delayed) 3D position verification when incorporated in a Digital TomoSynthesis (DTS) or Cone Beam Computed Tomography (CBCT). Upgrading to an instant 3D position verification system could be envisioned with a stereoscopic kilovoltage (kV) imaging setup. This paper describes a fast DL landmark detection model for vertebra (trained in-house) and evaluates its accuracy to detect 2D motion of the vertebrae with the help of projection images acquired during treatment. The introduced motion consists of both translational and rotational variations, which are detected by the DL model with a sub-millimeter accuracy.     

Can a Welfarist Approach be Used to Justify a Moral Duty to Cognitively Enhance Children?

The desire to self‐improve is probably as old as humanity: most of us want to be smarter, more athletic, more beautiful, or more talented. However, in the light of an ever increasing array of possibilities to enhance our capacities, clarity about the purpose and goal of such efforts becomes crucial. This is especially true when decisions are made for children, who are exposed to their parents’ plans and desires for them under a notion of increasing wellbeing. In recent years, cognitive enhancement has become a popular candidate for the promotion of wellbeing; welfarists even impose a moral duty on parents to cognitively enhance their children for the sake of their wellbeing. In this article, I aim to show that welfarists are mistaken in inferring such a moral obligation from the potential benefit of cognitive enhancement. In support of this, I offer three arguments: (a) the vagueness of wellbeing as a theoretical concept means it becomes impossible to apply in practice; (b) the link between cognition and wellbeing is far from unequivocal; and (c) quantification issues with regard to cognition make a duty impossible to discharge. In conclusion, I reject the welfarist approach as a justification for a parental moral obligation to cognitively enhance children.     

人工智能应用于青光眼临床筛查及卫生效益分析

目的:探讨应用人工智能系统对青光眼患者的检出率、筛查的时间成本和经济成本,总结分析其应用于青光眼筛查的优越性与可行性。方法:回顾性研究。收集2019-2020年使用腾讯觅影眼底照片辅助诊断系统进行青光眼筛查的53700例受检者,2012-2018年使用北京同仁医院眼科研究所远程眼科会诊中心的493221例患者,邯郸眼病研究中接受基础眼病筛查的6716名受检者资料。评价人工智能筛查系统对青光眼的检出率,并采用Pearson x~2检验,比较人工智能筛查系统与远程阅片平台、基础眼病筛查对于青光眼检出率的差异,并对三种筛查方式的时间成本和经济成本进行比较分析。结果:临床应用表明,其成本效益的可靠数据及主要指标:检出率、x~2值、时间成本、经济成本等效益显著。人工智能筛查系统对青光眼的检出率为6.56%,远程眼科会诊平台的检出率为2.78%,邯郸眼病研究的检出率为1.70%,人工智能筛查系统与另外两种模式对青光眼诊断检出率的差异有统计学意义(P0.05)。而且使用人工智能筛查系统的患者其医疗时间成本和经济成本花费较低。结论:可行性分析表明,相较于远程眼科会诊平台和基础眼病筛查,人工智能筛查系统对青光眼的检出率较高,同时患者的时间成本和经济成本都得到了大幅度降低,这为青光眼筛查提供了一种有效而快捷的方式,值得临床推广。     

Transgenerational memory effect of ageing in Drosophila

Children born to older parents tend to have lower intelligence and are at higher risk for disorders such as schizophrenia and autism. Such observations of ageing damage being passed on from parents to offspring are not often considered within the evolutionary theory of ageing. Here, we show the 25% memory impairment in Drosophila melanogaster offspring solely dependent on the age of the parents and also passed on to the F2 generation. Furthermore, this parental age effect was not attributed to a generalized reduction in condition of the offspring but was specific to short‐term memory. We also provide evidence implicating oxidative stress as a causal factor by showing that lines selected for resistance to oxidative stress did not display a memory impairment in offspring of old parents. The identification of the parental age‐related memory impairment in a model system should stimulate integration between mechanistic studies of age‐related mortality risk and functional studies of parental age effects on the fitness of future generations.     

Automating chest radiograph imaging quality control

PurposeTo automate diagnostic chest radiograph imaging quality control (lung inclusion at all four edges, patient rotation, and correct inspiration) using convolutional neural network models.MethodsThe data comprised of 2589 postero-anterior chest radiographs imaged in a standing position, which were divided into train, validation, and test sets. We increased the number of images for the inclusion by cropping appropriate images, and for the inclusion and the rotation by flipping the images horizontally. The image histograms were equalized, and the images were resized to a 512 × 512 resolution. We trained six convolutional neural networks models to detect the image quality features using manual image annotations as training targets. Additionally, we studied the inter-observer variability of the image annotation.ResultsThe convolutional neural networks’ areas under the receiver operating characteristic curve were >0.88 for the inclusions, and >0.70 and >0.79 for the rotation and the inspiration, respectively. The inter-observer agreement between two human annotators for the assessed image-quality features were: 92%, 90%, 82%, and 88% for the inclusion at patient’s left, patient’s right, cranial, and caudal edges, and 78% and 89% for the rotation and inspiration, respectively. Higher inter-observer agreement was related to a smaller variance in the network confidence.ConclusionsThe developed models provide automated tools for the quality control in a radiological department. Additionally, the convolutional neural networks could be used to obtain immediate feedback of the chest radiograph image quality, which could serve as an educational instrument.     

Abnormalities of Fuel Utilization as Predisposing to the Development of Obesity in Humans

A number of recent investigations in man have demonstrated that a low ratio of fat to carbohydrate oxidation (i.e., a high respiratory quotient or RQ) was associated with actual and/or subsequent body weight gain in obese non-diabetic Pima Indians, in American men of various ages and in post-obese European women investigated shortly after the cessation of a hypocaloric diet. It is well known that numerous exogenous and endogenous factors influence the RQ at rest such as: the level of feeding (positive vs. negative energy balance), the composition of food eaten (high vs. low carbohydrate), the size of the glycogen stores, the amount of adipose tissue as well as genetic factors. It should be stressed that some nutritional situations can coexist during which a low ratio of fat to carbohydrate is observed (i.e., a high RQ) despite weight loss. Furthermore, in most studies mentioned above, the low fat to carbohydrate oxidation ratio explains less then 10% of the variance in weight gain, suggesting that numerous additional factors also play a substantial role in the onset of weight gain. It is concluded that: 1) A low fat to carbohydrate oxidation ratio or an abnormal fat oxidation is difficult to define quantitatively since it is largely influenced by the energy level and the composition of the diet. 2) Following a dynamic adaptation phase to positive energy balance, a low fat oxidation is progressively compensated: increased body fat is the price to pay for normalizing fat oxidation since, at least in resting conditions, there is an increase in fat oxidation of approximately 20 g/day for each 10 kg additional fat gain. The subject with a low fat to carbohydrate oxidation ratio will equilibrate at a body fat level allowing to reach a new fat balance.     

On-line estimation of O<Subscript>2</Subscript> production,CO<Subscript>2</Subscript> uptake,and growth kinetics of microalgal cultures in a gas-tight photobioreactor

Growth of the green algae Chlamydomonas reinhardtii and Chlorella sp. in batch cultures was investigated in a novel gas-tight photobioreactor, in which CO₂, H₂, and N₂ were titrated into the gas phase to control medium pH, dissolved oxygen partial pressure, and headspace pressure, respectively. The exit gas from the reactor was circulated through a loop of tubing and re-introduced into the culture. CO₂ uptake was estimated from the addition of CO₂ as acidic titrant and O₂ evolution was estimated from titration by H₂, which was used to reduce O₂ over a Pd catalyst. The photosynthetic quotient, PQ, was estimated as the ratio between O₂ evolution and CO₂ up-take rates. NH₄ ⁺, NO₂ ⁻, or NO₃ ⁻ was the final cell density limiting nutrient. Cultures of both algae were, in general, characterised by a nitrogen sufficient growth phase followed by a nitrogen depleted phase in which starch was the major product. The estimated PQ values were dependent on the level of oxidation of the nitrogen source. The PQ was 1 with NH₄ ⁺ as the nitrogen source and 1.3 when NO₃ ⁻ was the nitrogen source. In cultures grown on all nitrogen sources, the PQ value approached 1 when the nitrogen source was depleted and starch synthesis became dominant, to further increase towards 1.3 over a period of 3–4 days. This latter increase in PQ, which was indicative of production of reduced compounds like lipids, correlated with a simultaneous increase in the degree of reduction of the biomass. When using the titrations of CO₂ and H₂ into the reactor headspace to estimate the up-take of CO₂, the production of O₂, and the PQ, the rate of biomass production could be followed, the stoichiometrical composition of the produced algal biomass could be estimated, and different growth phases could be identified.     

Social pressures have selected for an extended juvenile period in primates

Primates are highly social animals. As such, they utilize a large repertoire of social skills to manage their complex and dynamic social environments. In order to acquire complex social skills, primates require an extended learning period. Here I perform a comparative analysis using independent contrasts to show that social pressures have favored an extension in the proportion of time primates spend as juveniles.     

Too early? on the apparent conflict of astrobiology and cosmology

An interesting consequence of the modern cosmological paradigm is the spatial infinity of the universe. When coupled with naturalistic understanding of the origin of life and intelligence, which follows the basic tenets of astrobiology, and with some fairly incontroversial assumptions in the theory of observation selection effects, this infinity leads, as Ken Olum has recently shown, to a paradoxical conclusion. Olum's paradox is related, to the famous Fermi's paradox in astrobiology and “SETI” studies. We, hereby, present an evolutionary argument countering the apparent inconsistency, and show how, in the framework of a simplified model, deeper picture of the coupling between histories of intelligent/technological civilizations and astrophysical evolution of the Galaxy, can be achieved. This strategy has consequences of importance for both astrobiological studies and philosophy.