中国特有植物雪落樱桃潜在分布及其生态特征

为明确中国特有植物雪落樱桃(Cerasus xueluoensis)的潜在分布与居群生态特征,利用DIVA-GIS软件及其耦合的BIOCLIM模型,首次绘制了雪落樱桃适生区分布模拟图,并对影响其分布的主导气候因子进行了定性定量分析。结果表明,雪落樱桃当前潜在适生区主要分布在亚热带长江流域1 200 m以上高海拔山区,其中渝-鄂-湘三省交界的大巴山-巫山山脉可视为现代核心分布区,湘黔交界及湘南的南岭山脉可视为雪落樱桃潜在分布的南界,陕-豫-鄂交界山区的秦岭南麓可能是其潜在分布的北界。主成分分析(PCA)筛选的主导气候因子及其贡献率依次为:年降水量(bio12)最冷季降水量(bio19)最暖季降水量(bio18)最湿季降水量(bio16),累计频率曲线进一步确定其适宜范围分别为:993.00～1 870.22、500.00～680.00、430.00～669.16和500.00～680.00mm,表明降水是影响雪落樱桃当下分布格局的主导气候限制因子。Pearson相关性分析表明,雪落樱桃分布格局在区域尺度上受海拔、经、纬度影响;最小树分析和聚类分析表明,雪落樱桃7个野生居群可划分为中西部与东部两大分支;受试者工作特征曲线(ROC) AUC值达到0.751,满足模型预测精度的基本要求。这些有助于为雪落樱桃制定科学合理的资源保护与科学引种规划。     

BacStalk: A comprehensive and interactive image analysis software tool for bacterial cell biology

Prokaryotic cells display a striking subcellular organization. Studies of the underlying mechanisms in different species have greatly enhanced our understanding of the morphological and physiological adaptation of bacteria to different environmental niches. The image analysis software tool BacStalk is designed to extract comprehensive quantitative information from the images of morphologically complex bacteria with stalks, flagella, or other appendages. The resulting data can be visualized in interactive demographs, kymographs, cell lineage plots, and scatter plots to enable fast and thorough data analysis and representation. Notably, BacStalk can generate demographs and kymographs that display fluorescence signals within the two-dimensional cellular outlines, to accurately represent their subcellular location. Beyond organisms with visible appendages, BacStalk is also suitable for established, non-stalked model organisms with common or uncommon cell shapes. BacStalk, therefore, contributes to the advancement of prokaryotic cell biology and physiology, as it widens the spectrum of easily accessible model organisms and enables highly intuitive and interactive data analysis and visualization.     

Investigations of the kinetic energy parameters of irradiated (La)‐doped phosphate glass

The current study characterizes and analyzes glow curves obtained from phosphate glass doped with different concentrations of lanthanum. Kinetic parameters of the glow curves obtained from beta‐irradiated phosphate glass samples doped with lanthanum were determined using a newly designed deconvoluted software. The obtained results from the analyses indicated that the glow curves of the phosphate glass samples were composed of five overlapping peaks. The activation energies of the five electron traps were located between 0.622 and 1.133 eV. The obtained kinetic parameters were evaluated using the designed software and another two methods and all revealed good agreement. The first three traps displayed non‐first‐order behaviour, while the two deep traps obeyed nearly first‐order kinetics.     

What Users Want and May Need

An increasing number of software tools support designers and other decision makers in making design, production, and purchasing decisions. Some of these tools provide quantitative information on environmental impacts such as climate change, human toxicity, or resource use during the life cycle of these products. Very little is known, however, about how these tools are actually used, what kind of modeling and presentation approaches users really want, or whether the information provided is likely to be used the way the developers intended. A survey of users of one such software tool revealed that although users want more transparency, about half also want an easy-to-use tool and would accept built-in assumptions; that most users prefer modeling of environmental impacts beyond the stressor level, and the largest group of respondents wants results simultaneously on the stressor, impact potential, and damage level; and that although many users look for aggregated information on impacts and costs, a majority do not trust that such an aggregation is valid or believe that there are tradeoffs among impacts. Further, our results show that the temporal and spatial scales of single impact categories explain only about 6% of the variation in the weights between impact categories set by respondents if the weights are set first. If the weights are set after respondents specify temporal and spatial scales, however, these scales explain about 24% of the variation. These results not only help method and tool developers to reconsider some previous assumptions, but also suggest a number of research questions that may need to be addressed in a more focused investigation.     

Life cycle inventories for the production of sodium silicates

Soluble alkali silicate glasses, liquids and powders are an important class of primary synthetic chemicals and are produced in large quantities both in Europe and world-wide. They are utilised in a broad range of application fields, both industrial and domestic, including detergents, chemical feedstocks, paper manufacture, civil engineering and adhesives. In order to establish viable figures for the consumption of raw materials, water and energy and the emissions to air and water and solid waste generation, the production routes for five typical commercial sodium silicate products were traced back to the extraction of the relevant raw materials from the earth. Life Cycle Inventories for these products were compiled by EMPA St. Gallen / Switzerland on behalf of CEES, a Sector Group of CEFIC, using the data input based on the production of 1995 from 12 West European silicate producers covering about 93% of the total alkaline silicate production in Western Europe.     

Computer software for performing likelihood tests of pedigree relationship using genetic markers

Molecular techniques are making ever more genetic markers available for use in parentage assignment, and measures of relatedness. We present a program, Kinship, designed to use likelihood techniques to test for any non-inbred pedigree relationship between pairs of individuals, using single-locus codominant genetic markers. Kinship calculates the likelihood that each pair of individuals in a data set are related by a given pedigree hypothesis, and likelihood ratios for any pair of hypotheses. The program also uses a simulation routine to attach statistical significance to its results.     

Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives

Microalgae are well known for their ability to accumulate lipids intracellularly, which can be used for biofuels and mitigate CO₂ emissions. However, due to economic challenges, microalgae bioprocesses have maneuvered towards the simultaneous production of food, feed, fuel, and various high-value chemicals in a biorefinery concept. On-line and in-line monitoring of macromolecules such as lipids, proteins, carbohydrates, and high-value pigments will be more critical to maintain product quality and consistency for downstream processing in a biorefinery to maintain and valorize these markets. The main contribution of this review is to present current and prospective advances of on-line and in-line process analytical technology (PAT), with high-selectivity – the capability of monitoring several analytes simultaneously – in the interest of improving product quality, productivity, and process automation of a microalgal biorefinery. The high-selectivity PAT under consideration are mid-infrared (MIR), near-infrared (NIR), and Raman vibrational spectroscopies. The current review contains a critical assessment of these technologies in the context of recent advances in software and hardware in order to move microalgae production towards process automation through multivariate process control (MVPC) and software sensors trained on “big data”. The paper will also include a comprehensive overview of off-line implementations of vibrational spectroscopy in microalgal research as it pertains to spectral interpretation and process automation to aid and motivate development.     

MicroWeaR: A new R package for dental microwear analysis

Mastication of dietary items with different mechanical properties leaves distinctive microscopic marks on the surface of tooth enamel. The inspection of such marks (dental microwear analysis) is informative about the dietary habitus in fossil as well as in modern species. Dental microwear analysis relies on the morphology, abundance, direction, and distribution of these microscopic marks. We present a new freely available software implementation, MicroWeaR, that, compared to traditional dental microwear tools, allows more rapid, observer error free, and inexpensive quantification and classification of all the microscopic marks (also including for the first time different subtypes of scars). Classification parameters and graphical rendering of the output are fully settable by the user. MicroWeaR includes functions to (a) sample the marks, (b) classify features into categories as pits or scratches and then into their respective subcategories (large pits, coarse scratches, etc.), (c) generate an output table with summary information, and (d) obtain a visual surface‐map where marks are highlighted. We provide a tutorial to reproduce the steps required to perform microwear analysis and to test tool functionalities. Then, we present two case studies to illustrate how MicroWeaR works. The first regards a Miocene great ape obtained from through environmental scanning electron microscope, and other a Pleistocene cervid acquired by a stereomicroscope.     

incR: a new R package to analyse incubation behaviour

Incubation represents a life stage of crucial importance for the optimal development of avian embryos. For most birds, incubation poses a trade‐off between investing in self‐maintenance and offspring care. Furthermore, incubation is affected by environmental temperatures and, therefore, will be likely impacted by climate change. Despite its relevance and readily available temperature logging methods, avian incubation research is hindered by recognised limitations in available software. In this paper, a new quantitative approach to analyse incubation behaviour is presented. This new approach is embedded in a free R package, incR. The flexibility of the R environment eases the analysis, validation and visualisation of incubation temperature data. The core algorithm in incR is validated here and it is shown that the method extracts accurate metrics of incubation behaviour (e.g. number and duration of incubation bouts). This paper also presents a suggested workflow along with detailed R code to aid the practical implementation of incR.