Revisiting the saproxylic beetle ‘Propomacrus cypriacus Alexis & Makris, 2002’ (Coleoptera: Euchiridae) using molecular,morphological and ecological data

Propomacrus cypriacus a saproxylic beetle endemic to Cyprus, was described as a species distinct from P. bimucronatus on the basis of a few morphological characters and has been evaluated as Critically Endangered by IUCN, as it depends on veteran trees and has a restricted distribution. Herein we explored the distribution, ecology, morphology and genetic variation of the populations from Cyprus, and we attempted a phylogenetic analysis including related species based on two mitochondrial and one nuclear DNA markers. We also used published mtDNA divergence rates to date cladogenetic events. Despite extensive sampling, we found only a small number of individuals, adding a few additional localities to the known distribution of the species, and we identified two more host species to those previously reported. Morphological examination showed that only the form of male protibiae differs consistently in Cyprus populations compared to those of P. bimucronatus from Turkey and the Lebanon. Nevertheless, genetic analyses do not support a distinct species status for populations from Cyprus, which should instead be considered as a subspecies of P. bimucronatus. Morphological and ecological data further support this conclusion. Cyprus populations have diverged from nearby continental ones in mid to late Pleistocene.     

Modelling and Trading the English and German Stock Markets with Novelty Optimization Techniques

The motivation for this paper was the introduction of novel short‐term models to trade the FTSE 100 and DAX 30 exchange‐traded funds (ETF) indices. There are major contributions in this paper which include the introduction of an input selection criterion when utilizing an expansive universe of inputs, a hybrid combination of partial swarm optimizer (PSO) with radial basis function (RBF) neural networks, the application of a PSO algorithm to a traditional autoregressive moving model (ARMA), the application of a PSO algorithm to a higher‐order neural network and, finally, the introduction of a multi‐objective algorithm to optimize statistical and trading performance when trading an index. All the machine learning‐based methodologies and the conventional models are adapted and optimized to model the index. A PSO algorithm is used to optimize the weights in a traditional RBF neural network, in a higher‐order neural network (HONN) and the AR and MA terms of an ARMA model. In terms of checking the statistical and empirical accuracy of the novel models, we benchmark them with a traditional HONN, with an ARMA, with a moving average convergence/divergence model (MACD) and with a naïve strategy. More specifically, the trading and statistical performance of all models is investigated in a forecast simulation of the FTSE 100 and DAX 30 ETF time series over the period January 2004 to December 2015 using the last 3 years for out‐of‐sample testing. Finally, the empirical and statistical results indicate that the PSO‐RBF model outperforms all other examined models in terms of trading accuracy and profitability, even with mixed inputs and with only autoregressive inputs. Copyright © 2016 John Wiley & Sons, Ltd.     

A choice-semantical approach to theoretical truth

A central topic in the logic of science concerns the proper semantic analysis of theoretical sentences, that is sentences containing theoretical terms. In this paper, we present a novel choice-semantical account of theoretical truth based on the epsilon-term definition of theoretical terms. Specifically, we develop two ways of specifying the truth conditions of theoretical statements in a choice functional semantics, each giving rise to a corresponding logic of such statements. In order to investigate the inferential strength of these logical systems, we provide a translation of each truth definition into a modal definition of theoretical truth. Based on this, we show that the stronger notion of choice-semantical truth captures more adequately our informal semantic understanding of scientific statements.     

交互随机系统

本书的内容报道了欧洲随机研究协会资助的“DFG．Schwerpunkt随机系统”课题中在概率论方向的网络科研人员所作的原创性工作，题为“极复杂交互随机系统”科研项目，研究目标是探索和开发无限维随机分析、统计物理、基于数学生物学的全球人口模型、金融市场的复杂模型与其它学科相关的随机模型之问的联系。     

Electrons surfing on a sound wave as a platform for quantum optics with flying electrons

Electrons in a metal are indistinguishable particles that interact strongly with other electrons and their environment. Isolating and detecting a single flying electron after propagation, in a similar manner to quantum optics experiments with single photons, is therefore a challenging task. So far only a few experiments have been performed in a high-mobility two-dimensional electron gas in which the electron propagates almost ballistically. In these previous works, flying electrons were detected by means of the current generated by an ensemble of electrons, and electron correlations were encrypted in the current noise. Here we demonstrate the experimental realization of high-efficiency single-electron source and detector for a single electron propagating isolated from the other electrons through a one-dimensional channel. The moving potential is excited by a surface acoustic wave, which carries the single electron along the one-dimensional channel at a speed of 3 μm ns(-1). When this quantum channel is placed between two quantum dots several micrometres apart, a single electron can be transported from one quantum dot to the other with quantum efficiencies of emission and detection of 96% and 92%, respectively. Furthermore, the transfer of the electron can be triggered on a timescale shorter than the coherence time T(2)* of GaAs spin qubits. Our work opens new avenues with which to study the teleportation of a single electron spin and the distant interaction between spatially separated qubits in a condensed-matter system.     

City living and urban upbringing affect neural social stress processing in humans

More than half of the world's population now lives in cities, making the creation of a healthy urban environment a major policy priority. Cities have both health risks and benefits, but mental health is negatively affected: mood and anxiety disorders are more prevalent in city dwellers and the incidence of schizophrenia is strongly increased in people born and raised in cities. Although these findings have been widely attributed to the urban social environment, the neural processes that could mediate such associations are unknown. Here we show, using functional magnetic resonance imaging in three independent experiments, that urban upbringing and city living have dissociable impacts on social evaluative stress processing in humans. Current city living was associated with increased amygdala activity, whereas urban upbringing affected the perigenual anterior cingulate cortex, a key region for regulation of amygdala activity, negative affect and stress. These findings were regionally and behaviourally specific, as no other brain structures were affected and no urbanicity effect was seen during control experiments invoking cognitive processing without stress. Our results identify distinct neural mechanisms for an established environmental risk factor, link the urban environment for the first time to social stress processing, suggest that brain regions differ in vulnerability to this risk factor across the lifespan, and indicate that experimental interrogation of epidemiological associations is a promising strategy in social neuroscience.     

An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor

Activation of the aryl hydrocarbon receptor (AHR) by environmental xenobiotic toxic chemicals, for instance 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin), has been implicated in a variety of cellular processes such as embryogenesis, transformation, tumorigenesis and inflammation. But the identity of an endogenous ligand activating the AHR under physiological conditions in the absence of environmental toxic chemicals is still unknown. Here we identify the tryptophan (Trp) catabolite kynurenine (Kyn) as an endogenous ligand of the human AHR that is constitutively generated by human tumour cells via tryptophan-2,3-dioxygenase (TDO), a liver- and neuron-derived Trp-degrading enzyme not yet implicated in cancer biology. TDO-derived Kyn suppresses antitumour immune responses and promotes tumour-cell survival and motility through the AHR in an autocrine/paracrine fashion. The TDO-AHR pathway is active in human brain tumours and is associated with malignant progression and poor survival. Because Kyn is produced during cancer progression and inflammation in the local microenvironment in amounts sufficient for activating the human AHR, these results provide evidence for a previously unidentified pathophysiological function of the AHR with profound implications for cancer and immune biology.     

Comparative and demographic analysis of orang-utan genomes

'Orang-utan' is derived from a Malay term meaning 'man of the forest' and aptly describes the southeast Asian great apes native to Sumatra and Borneo. The orang-utan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orang-utan draft genome assembly and short read sequence data from five Sumatran and five Bornean orang-utan genomes. Our analyses reveal that, compared to other primates, the orang-utan genome has many unique features. Structural evolution of the orang-utan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe a primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orang-utan genome structure. Orang-utans have extremely low energy usage for a eutherian mammal, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400,000?years ago, is more recent than most previous studies and underscores the complexity of the orang-utan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (N(e)) expanded exponentially relative to the ancestral N(e) after the split, while Bornean N(e) declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts.