Mixed company: a framework for understanding the composition and organization of mixed‐species animal groups

Mixed‐species animal groups (MSGs) are widely acknowledged to increase predator avoidance and foraging efficiency, among other benefits, and thereby increase participants' fitness. Diversity in MSG composition ranges from two to 70 species of very similar or completely different phenotypes. Yet consistency in organization is also observable in that one or a few species usually have disproportionate importance for MSG formation and/or maintenance. We propose a two‐dimensional framework for understanding this diversity and consistency, concentrating on the types of interactions possible between two individuals, usually of different species. One axis represents the similarity of benefit types traded between the individuals, while the second axis expresses asymmetry in the relative amount of benefits/costs accrued. Considering benefit types, one extreme represents the case of single‐species groups wherein all individuals obtain the same supplementary, group‐size‐related benefits, and the other extreme comprises associations of very different, but complementary species (e.g. one partner creates access to food while the other provides vigilance). The relevance of social information and the matching of activities (e.g. speed of movement) are highest for relationships on the supplementary side of this axis, but so is competition; relationships between species will occur at points along this gradient where the benefits outweigh the costs. Considering benefit amounts given or received, extreme asymmetry occurs when one species is exclusively a benefit provider and the other a benefit user. Within this parameter space, some MSG systems are constrained to one kind of interaction, such as shoals of fish of similar species or leader–follower interactions in fish and other taxa. Other MSGs, such as terrestrial bird flocks, can simultaneously include a variety of supplementary and complementary interactions. We review the benefits that species obtain across the diversity of MSG types, and argue that the degree and nature of asymmetry between benefit providers and users should be measured and not just assumed. We then discuss evolutionary shifts in MSG types, focusing on drivers towards similarity in group composition, and selection on benefit providers to enhance the benefits they can receive from other species. Finally, we conclude by considering how individual and collective behaviour in MSGs may influence both the structure and processes of communities.     

Spatial modeling of techno‐economic potential of biojet fuel production in Brazil

It is expected that Brazil could play an important role in biojet fuel (BJF) production in the future due to the long experience in biofuel production and the good agro‐ecological conditions. However, it is difficult to quantify the techno‐economic potential of BJF because of the high spatiotemporal variability of available land, biomass yield, and infrastructure as well as the technological developments in BJF production pathways. The objective of this research is to assess the recent and future techno‐economic potential of BJF production in Brazil and to identify location‐specific optimal combinations of biomass crops and technological conversion pathways. In total, 13 production routes (supply chains) are assessed through the combination of various biomass crops and BJF technologies. We consider temporal land use data to identify potential land availability for biomass production. With the spatial distribution of the land availability and potential yield of biomass crops, biomass production potential and costs are calculated. The BJF production cost is calculated by taking into account the development in the technological pathways and in plant scales. We estimate the techno‐economic potential by determining the minimum BJF total costs and comparing this with the range of fossil jet fuel prices. The techno‐economic potential of BJF production ranges from 0 to 6.4 EJ in 2015 and between 1.2 and 7.8 EJ in 2030, depending on the reference fossil jet fuel price, which varies from 19 to 65 US$/GJ across the airports. The techno‐economic potential consists of a diverse set of production routes. The Northeast and Southeast region of Brazil present the highest potentials with several viable production routes, whereas the remaining regions only have a few promising production routes. The maximum techno‐economic potential of BJF in Brazil could meet almost half of the projected global jet fuel demand toward 2030.     

基于植保大数据的病虫害移动智能采集新设备

为提高农作物重大病虫害发生信息自动化、智能化采集能力,全面提升监测预警水平,笔者基于大数据、人工智能和深度学习技术,研发了一款农作物病虫害移动智能采集设备——智宝,主要实现了3个方面的功能:一是病虫害发生信息自动采集上报.通过该产品进行人工拍照,可实现对田间农作物重大病虫害发生图像、发生位置、发生数量、微环境因子等数据的实时采集和上报.二是自动识别计数.基于植保大数据与人工智能技术,通过构建病虫害自动识别系统,可实现重大病虫害精准识别与分析,只要拍摄照片,即可快速、精确地识别病虫害种类,并自动计数、上报到指定的测报系统.三是自动分析判别分级.针对拍摄采集上报的重大病虫害发生信息,系统可在自动识别和计数的基础上,进一步对病虫害发生严重程度进行智能判别分级,甚至根据相关预测模型,对病虫害的发生趋势进行辅助分析预测,提出预测建议.通过2016—2019年组织多地植保机构进行试验改进,该技术产品日趋成熟,有望在未来的农作物病虫害发生信息采集和预测预报工作中推广使用.     

人体动脉血气波浪式变化特点的实验证据—同时间动、静脉血波浪式变化幅度的不同*

目的: 人动脉血来源是右心系统并在肺脏进行气体交换的静脉血,右心系统的静脉血是否存在波浪式信号目前尚没有证据支持,本研究旨在对比同时间动、静脉血中信号的连续变化特点。方法: 选择心功能正常,需要连续监测动脉血流动力学变化的患者6 例,4男2女,年龄（59.00±16.64） 岁,体质量（71.67±10.37）kg,左心射血分数（LVEF）（61.33±2.16)%。患者签署知情同意书后,选择心功能正常需要监测动、静脉血流动力学变化的患者6 例,连续同时桡动脉、颈内静脉逐搏取血,测定PaO₂。选取2个典型呼吸周期,用于分析同时段动、静脉血气的波浪式变化。分别比较患者血氧分压最高和最低值,以验证同时段动、静脉血气是否都存在周期性波浪式信号变化。此外,将患者动脉、静脉血气周期性波浪式信号的变化幅度进行统计学t 检验分析,比较有无差异。结果: 共6例患者,抽取动、静脉血液充满肝素化细长塑化管需要15~16次心跳,即取血需要15~16次心跳,全部覆盖超过2个呼吸周期。所有患者动脉血气中PaO₂均呈现明显的波浪式变化（P<0.05）,幅度是（9.96±5.18）mmHg,是均值的（8.09±2.43）%。患者静脉血气中PaO₂波动幅度并不明显,为（1.63±0.41）mmHg,是均值的（3.91±1.22）%,与动脉血气组相比有明显统计学差异（P<0.05）。结论: 采用同时连续逐搏动、静脉取血血气分析法证实,患者自主呼吸时动脉血气有明显的周期性波浪式变化信号,而静脉血气几乎没有周期性波浪式变化信号（很弱）,说明动脉血气波浪式信号主要是由于肺通气过程中吸气和呼气期产生肺泡中氧分压规律性上升和下降,通过离开肺毛细血管与肺泡氧气压力平衡的动脉化血液,经过左心室搏血进入动脉血管系统所致。     

基于深度学习与多层次信息融合的药物靶标亲和力预测*

药物研发是非常重要但也十分耗费人力物力的过程。利用计算机辅助预测药物与蛋白质亲和力的方法可以极大地加快药物研发过程。药物靶标亲和力预测的关键在于对药物和蛋白质进行准确详细地信息表征。提出一种基于深度学习与多层次信息融合的药物靶标亲和力的预测模型,试图通过综合药物与蛋白质的多层次信息,来获得更好的预测表现。首先将药物表述成分子图和扩展连接指纹两种形式,分别利用图卷积神经网络模块和全连接层进行学习;其次将蛋白质序列和蛋白质K-mer特征分别输入卷积神经网络模块和全连接层来学习蛋白质潜在特征;随后将4个通道学习到的特征进行融合,再利用全连接层进行预测。在两个基准药物靶标亲和力数据集上验证了所提方法的有效性,并与其他已有模型作对比研究。结果说明提出的模型相比基准模型能得到更好的预测性能,表明提出的综合药物与蛋白质多层次信息的药物靶标亲和力预测策略是有效的。     

Synaptic dendritic activity modulates the single synaptic event

Synaptic transmission is the key system for the information transfer and elaboration among neurons. Nevertheless, a synapse is not a standing alone structure but it is a part of a population of synapses inputting the information from several neurons on a specific area of the dendritic tree of a single neuron. This population consists of excitatory and inhibitory synapses the inputs of which drive the postsynaptic membrane potential in the depolarizing (excitatory synapses) or depolarizing (inhibitory synapses) direction modulating in such a way the postsynaptic membrane potential. The postsynaptic response of a single synapse depends on several biophysical factors the most important of which is the value of the membrane potential at which the response occurs. The concurrence in a specific time window of inputs by several synapses located in a specific area of the dendritic tree can, consequently, modulate the membrane potential such to severely influence the single postsynaptic response. The degree of modulation operated by the synaptic population depends on the number of synapses active, on the relative proportion between excitatory and inbibitory synapses belonging to the population and on their specific mean firing frequencies. In the present paper we show results obtained by the simulation of the activity of a single Glutamatergic excitatory synapse under the influence of two different populations composed of the same proportion of excitatory and inhibitory synapses but having two different sizes (total number of synapses). The most relevant conclusion of the present simulations is that the information transferred by the single synapse is not and independent simple transition between a pre- and a postsynaptic neuron but is the result of the cooperation of all the synapses which concurrently try to transfer the information to the postsynaptic neuron in a given time window. This cooperativeness is mainly operated by a simple mechanism of modulation of the postsynaptic membrane potential which influences the amplitude of the different components forming the postsynaptic excitatory response.     

An Approach Based on Mutually Informed Neural Networks to Optimize the Generalization Capabilities of Decision Support Systems Developed for Heart Failure Prediction

Available clinical methods for heart failure (HF) diagnosis are expensive and require a high-level of experts intervention. Recently, various machine learning models have been developed for the prediction of HF where most of them have an issue of over-fitting. Over-fitting occurs when machine learning based predictive models show better performance on the training data yet demonstrate a poor performance on the testing data and the other way around. Developing a machine learning model which is able to produce generalization capabilities (such that the model exhibits better performance on both the training and the testing data sets) could overall minimize the prediction errors. Hence, such prediction models could potentially be helpful to cardiologists for the effective diagnose of HF. This paper proposes a two-stage decision support system to overcome the over-fitting issue and to optimize the generalization factor. The first stage uses a mutual information based statistical model while the second stage uses a neural network. We applied our approach to the HF subset of publicly available Cleveland heart disease database. Our experimental results show that the proposed decision support system has optimized the generalization capabilities and has reduced the mean percent error (MPE) to 8.8% which is significantly less than the recently published studies. In addition, our model exhibits a 93.33% accuracy rate which is higher than twenty eight recently developed HF risk prediction models that achieved accuracy in the range of 57.85% to 92.31%. We can hope that our decision support system will be helpful to cardiologists if deployed in clinical setup.     

Cell division systems that account for the various arrangements and types of differentiated cells within the secondary phloem of conifers

There are two main types of arrangement of differentiated cells within the radial cell files of secondary phloem in conifer trees. In the C-type arrangement, characteristic of the Cupressaceae, fibre (F), parenchyma (P) and sieve (S) cells are arranged in recurrent groups, such as the “standard” cellular quartet (FSPS). In the P-type arrangement, characteristic of the Pinaceae, there are no fibres and one of the characteristic recurrent arrangements is the cellular sextet (PSSSSS). In addition, in both C-type and P-type arrangements, similar cell types are often organised into tangential bands. A simulation model, based on the theory of L-systems, was devised to account for the determination of these two types of regular and recurrent patterns of differentiated phloem cells. It was based on the supposition that, in the meristematic portion of the phloem domain, there are specific spatio-temporal patterns of periclinal cell division. When new cells are produced, those already present are displaced along the cell file, occupying a predictable number of cellular positions as a result of each round of cell division. Each cellular position is assumed to be associated with a specific value of a morphogen, such as the auxin, indole acetic acid, relevant for vascular differentiation. Using published quantitative data on the distribution auxin across the phloem, and assuming specific threshold values of auxin necessary for the determination of each cell type, it was found that sequences of F, S or P cells developed in accordance with the specific pattern of cell division and the related positional values of auxin experienced by the cells during their displacement through the immediately post-mitotic zone of cell determination. The model accounts not only for the typical C-type and P-type cellular arrangements, but also for certain variant arrangements. It provides a working example of the concepts of positional information and positional value for patterned differentiation within a developing plant tissue. There are similarities between the way groups of phloem cells develop and the differentiation of somites in the embryos of vertebrates.