Mitigating the Goldilocks effect: the effects of different substrate models on track formation potential

In ichnology, the Goldilocks effect describes a scenario in which a substrate must be ‘just right’ in order for tracks to form—too soft, the animal will be unable to traverse the area, and too firm, the substrate will not deform. Any given substrate can therefore only preserve a range of tracks from those animals which exert an underfoot pressure at approximately the yield strength of the sediment. However, rarely are substrates vertically homogeneous for any great depth, varying either due to heterogeneity across sediment layers, or from mechanical behaviour such as strain hardening. Here, we explore the specificity of the Goldilocks effect in a number of virtual substrates simulated using finite- element analysis. We find that the inclusion of strain hardening into the model increases the potential range of trackmaker sizes somewhat, compared with a simple elastic–perfectly plastic model. The simulation of a vertically heterogeneous, strain hardening substrate showed a much larger range of potential trackmakers than strain hardening alone. We therefore show that the Goldilocks effect is lessened to varying degrees by the inclusion of more realistic soil parameters, though there still remains an upper and lower limit to the size of trackmaker able to traverse the area while leaving footprints

Learning with Biased Complementary Labels

In this paper, we study the classification problem in which we have access to easily obtainable surrogate for true labels, namely complementary labels, which specify classes that observations do \textbf{not} belong to. Let $Y$ and $\bar{Y}$ be the true and complementary labels, respectively. We first model the annotation of complementary labels via transition probabilities $P(\bar{Y}=i|Y=j), i\neq j\in\{1,\cdots,c\}$, where $c$ is the number of classes. Previous methods implicitly assume that $P(\bar{Y}=i|Y=j), \forall i\neq j$, are identical, which is not true in practice because humans are biased toward their own experience. For example, as shown in Figure 1, if an annotator is more familiar with monkeys than prairie dogs when providing complementary labels for meerkats, she is more likely to employ "monkey" as a complementary label. We therefore reason that the transition probabilities will be different. In this paper, we propose a framework that contributes three main innovations to learning with \textbf{biased} complementary labels: (1) It estimates transition probabilities with no bias. (2) It provides a general method to modify traditional loss functions and extends standard deep neural network classifiers to learn with biased complementary labels. (3) It theoretically ensures that the classifier learned with complementary labels converges to the optimal one learned with true labels. Comprehensive experiments on several benchmark datasets validate the superiority of our method to current state-of-the-art methods.Comment: ECCV 2018 Ora

Circular Networks from Distorted Metrics

Trees have long been used as a graphical representation of species relationships. However complex evolutionary events, such as genetic reassortments or hybrid speciations which occur commonly in viruses, bacteria and plants, do not fit into this elementary framework. Alternatively, various network representations have been developed. Circular networks are a natural generalization of leaf-labeled trees interpreted as split systems, that is, collections of bipartitions over leaf labels corresponding to current species. Although such networks do not explicitly model specific evolutionary events of interest, their straightforward visualization and fast reconstruction have made them a popular exploratory tool to detect network-like evolution in genetic datasets. Standard reconstruction methods for circular networks, such as Neighbor-Net, rely on an associated metric on the species set. Such a metric is first estimated from DNA sequences, which leads to a key difficulty: distantly related sequences produce statistically unreliable estimates. This is problematic for Neighbor-Net as it is based on the popular tree reconstruction method Neighbor-Joining, whose sensitivity to distance estimation errors is well established theoretically. In the tree case, more robust reconstruction methods have been developed using the notion of a distorted metric, which captures the dependence of the error in the distance through a radius of accuracy. Here we design the first circular network reconstruction method based on distorted metrics. Our method is computationally efficient. Moreover, the analysis of its radius of accuracy highlights the important role played by the maximum incompatibility, a measure of the extent to which the network differs from a tree.Comment: Submitte

Generalization Error in Deep Learning

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

Adultery and the Rumor Mill: les bourgeois de Molinchart and El gran galeoto

This article seeks to challenge interpretations of the adultery plot as a subversive current in nineteenth-century literature by examining two texts that are often dismissed by contemporary critics: Les bourgeois de Molinchart (1854), a novel by the French writer Champfleury (the pseudonym of Jules Husson), and El gran Galeoto (1881), a play by the Spanish playwright Jos, Echegaray. In each of these works, the rumor of the adultery precedes and to a large extent precipitates the infidelity at the end of the work. In committing adultery, therefore, the protagonists are not rising up against social norms so much as capitulating to the expectations of society, enacting a plot that has been projected upon them. The essay compares and contrasts the treatment of the rumor mill in the two works and examines the literary strategies that the writers use to undercut a transgressive reading of the infidelity plot

Extrafine beclomethasone/formoterol in severe COPD patients with history of exacerbations

The FORWARD study is a randomised, double-blind trial that compares the efficacy and safety of 48 weeks treatment with extrafine beclomethasone dipropionate/formoterol fumarate (BDP/FOR), 100/6 μg pMDI, 2 inhalations BID, vs. FOR 12 μg pMDI, 1 inhalation BID, in severe COPD patients with a history of exacerbations. Co-primary endpoints were exacerbation rate over 48 weeks and pre-dose morning FEV1 at 12 weeks. The ITT population included 1186 patients (69% males, mean age 64 years) with severe airflow limitation (mean post-bronchodilator FEV1 42% predicted). Salbutamol as rescue therapy, theophylline and tiotropium (if stable regimen prior to screening) were allowed. Compared to FOR, BDP/FOR: (1) reduced the exacerbation rate (rate ratio: 0.72 [95% confidence interval 0.62–0.84], p < 0.001); (2) improved pre-dose morning FEV1 (mean difference: 0.069 L [0.043–0.095] p < 0.001); (3) prolonged the time to first exacerbation; (4) improved the SGRQ total score. The percentage of patients with adverse events was similar (52.1% with BDP/FOR and 49.2% with FOR). Pneumonia incidence was low, slightly higher with BDP/FOR (3.8%) than with FOR (1.8%). No difference for laboratory values, ECG or vital signs. Extrafine BDP/FOR significantly reduces the exacerbation rate and improves lung function of patients with severe COPD and history of exacerbations as compared to FOR alone

The Cerebro-placental Ratio as a Prognostic Factor of Foetal Outcome in Patients with Third Trimester Hypertension

Background: Hypertensive disorders of pregnancy can cause complications in both the maternal and fetal circulations resulting in poor fetal outcome. These circulations can be safely and non-invasively assessed using arterial Doppler indices of the umbilical and middle cerebral arteries to obtain the cerebro-placental ratio. The study objective was to determine the role of the cerebro-placental ratio as a prognostic factor of fetal outcome in patients with hypertensive states of pregnancy delivered at least 32 weeks of gestation by dates.Methods: This was a prospective cohort study undertaken at Kenyatta National Hospital, a tertiary referral hospital in Nairobi. A total of 160 gravid patients of median age 28 years and at least 32 weeks gestations were recruited from labor ward over a 9 month study period by consecutive sampling method. Doppler ultrasound analyses of the foetal umbilical and cerebral arteries were done and the cerebro-placental ratio calculated.Results: At sonography, the average ultrasound age was 31 weeks. The median gestation at admission was 34 weeks. Twenty nine percent had an abnormal Cerebro-placental ratio (&lt;1.0).125/160 (78%) delivered via caesarean section and 35/160(22%) delivered vaginally.51/160(32%)  severe pre-eclamptic toxaemia out of which 39% had cerebroplacental ratio&lt;1.0 109/160(68%) had mild pre-eclamptic toxaemia out of which 24% had cerebroplacental ratio &lt;1.0 Still births were 12.5 times more likely in mothers with cerebroplacental ratio &lt;1.0 than those with CPR 1.0 (p value 0.05). A foetal birth score &lt; 7 was 66 times more often in  mothers with cerebro-placental ratio&lt; 1.0 than mothers with CPR 1.0. (P 0.05). Low birth weight was 4.7 times more likely among mothers with cerebroplacental ratio &lt; 1.0.as compared to those with mothers with CPR1.0 (95% CI 2, 11.1; p0.001). A foetal birth score &lt; 7 was 66 times more likely among neonates delivered vaginally as compared to those born via caesarean section(95% CI 1.3, 23; p=0.02). Still births were 14.5 times more often than among neonates born vaginally as compared to those born via caesarean section (95% CI 3, 84; p0.001). The prognostic Odds Ratio for cerebro-placental ratio was 12.5 for live births (95% CI 2, 74; p=0.005), 66 for fetal birth score &lt;7 (95% Confidence interval 13, 340; p&lt; 0.001) and 4.7 for low birth weight (95% CI 2, 11.1; p&lt; 0.001) and 1.1 (95% CI 0.9, 1.4; p=0.327).Conclusion: Cerebro-placental ratio is significantly predictive of adverse perinatal outcome when used to monitor mothers with hypertensive states of pregnancy. Cerebroplacental ratio.Key words: Cerebro-placental Ratio, Prognostic Factor, Foetal Outcome, Third Trimester, Hypertensio

Digit-only sauropod pes trackways from China - evidence of swimming or a preservational phenomenon?

For more than 70 years unusual sauropod trackways have played a pivotal role in debates about the swimming ability of sauropods. Most claims that sauropods could swim have been based on manus-only or manus-dominated trackways. However none of these incomplete trackways has been entirely convincing, and most have proved to be taphonomic artifacts, either undertracks or the result of differential depth of penetration of manus and pes tracks, but otherwise showed the typical pattern of normal walking trackways. Here we report an assemblage of unusual sauropod tracks from the Lower Cretaceous Hekou Group of Gansu Province, northern China, characterized by the preservation of only the pes claw traces, that we interpret as having been left by walking, not buoyant or swimming, individuals. They are interpreted as the result of animals moving on a soft mud-silt substrate, projecting their claws deeply to register their traces on an underlying sand layer where they gained more grip during progression. Other sauropod walking trackways on the same surface with both pes and manus traces preserved, were probably left earlier on relatively firm substrates that predated the deposition of soft mud and silt . Presently, there is no convincing evidence of swimming sauropods from their trackways, which is not to say that sauropods did not swim at all

Attempts to detect retrotransposition and de novo deletion of Alus and other dispersed repeats at specific loci in the human genome

Dispersed repeat elements contribute to genome instability by de novo insertion and unequal recombination between repeats. To study the dynamics of these processes, we have developed single DNA molecule approaches to detect de novo insertions at a single locus and Alu-mediated deletions at two different loci in human genomic DNA. Validation experiments showed these approaches could detect insertions and deletions at frequencies below 10(-6) per cell. However, bulk analysis of germline (sperm) and somatic DNA showed no evidence for genuine mutant molecules, placing an upper limit of insertion and deletion rates of 2 x 10(-7) and 3 x 10(-7), respectively, in the individuals tested. Such re-arrangements at these loci therefore occur at a rate lower than that detectable by the most sensitive methods currently available