Short‐finned pilot whales (Globicephala macrorhynchus) of the Mariana Archipelago: Individual affiliations,movements, and spatial use

Little is known about short‐finned pilot whales (Globicephala macrorhynchus) in the western North Pacific outside of Japanese coastal waters. To expand understanding of short‐finned pilot whale ecology in the region, we conducted small‐boat surveys in 2010?2016 within the Mariana Archipelago to investigate individual associations, movements, spatial use, and dive behavior of short‐finned pilot whales. We collected genetic, photo‐identification, and satellite‐tag data and identified 191 distinctive individuals. A preliminary social network diagram of photo‐cataloged individuals revealed a main cluster that comprised 82% of individuals, representing all five mitochondrial DNA haplotypes identified within the population. Kernel density estimates for tagged short‐finned pilot whales (n = 11) during summer were used to identify areas with the highest probability of use (10% probability density contour), core area (50%) and home range (95%). The area with highest probability of use by short‐finned pilot whales was off the northwest side of Guam. Satellite tag data also suggest that some individuals are island‐associated year‐round. Data from five location‐dive tags demonstrated that the short‐finned pilot whales dove more often to intermediate depths at twilight and night, suggesting they may target prey that forage on the deep scattering layer as it migrates to and from the surface.     

植物种质资源引进风险分析方法概述

种质资源作为生物资源的重要组成部分,是培育作物优质、高产、抗病（虫）、抗逆新品种的物质基础。近年来,为满足我国种业飞速发展的需要,我国不断从国外引入大量的种质资源,种质资源相比其他植物产品携带有害生物的风险更高。种质资源引进过程中不可避免地携带有害生物,可能会带来严重危害。目前,美国、澳大利亚等国家已制定了关于种质资源的风险分析方法,但我国缺少针对种质资源有害生物统一的风险分析方法。本文分析了国际植物检疫措施标准、主要的贸易国家及我国有害生物风险分析标准方法的主要内容,针对引进种质资源过程中亟需解决的有害生物风险分析问题开展讨论,并对种质资源有害生物风险分析系统其未来展开工作提出以下建议：设置符合种质资源风险分析特性的指标;采用半定量风险评估方法对种质资源进行风险分析;根据不断的学习和实际工作的需要,对风险评估指标体系进行验证和适当修改。     

A Clustering Method for the States of a Markov Chain with an Application to Primate Communication

In some applications clustering problems in stochastic processes arise when the experimenter wants to improve the insight into the structure of the observed system by lumping its states into clusters. As measure of goodness of a cluster solution we choose the rate of predictability of the forthcoming events which can be quantified by means of the entropy of the lumped process. The entropy in turn can be estimated by making use of a Shannon-McMillan-type theorem. We will establish some asymptotic results for the estimate of entropy in the case where the underlying stochastic process is a Markov chain. Our main tool will be a representation of functions of Markov chains which is due to Blackwell (1957). The method proposed here is applied to data on communication processes in monkeys. The object of our analysis will be to find a subgroup structure in the animal group.     

Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories

With the human Plasma Proteome Project (PPP) pilot phase completed, the largest and most ambitious proteomics experiment to date has reached its first milestone. The correspondingly impressive amount of data that came from this pilot project emphasized the need for a centralized dissemination mechanism and led to the development of a detailed, PPP specific data gathering infrastructure at the University of Michigan, Ann Arbor as well as the protein identifications database project at the European Bioinformatics Institute as a general proteomics data repository. One issue that crept up while discussing which data to store for the PPP concerns whether the raw, binary data coming from the mass spectrometers should be stored, or rather the more compact and already significantly processed peak lists. As this debate is not restricted to the PPP but relates to the proteomics community in general, we will attempt to detail the relative merits and caveats associated with centralized storage and dissemination of raw data and/or peak lists, building on the extensive experience gained during the PPP pilot phase. Finally, some suggestions are made for both immediate and future storage of MS data in public repositories.     

Three-dimensional multiple-wavelength fluorescence microscopy for the structural analysis of biological phenomena.

Cellular events are accomplished by the coordinated interactions of cellular components within the three-dimensional context of a cell. Simultaneous observation of multiple components in three dimensions can be essential for understanding such interactions. Toward this end, we have developed a computerized microscope workstation capable of recording three-dimensional images of multiple cellular components in fixed and living cells. All aspects of microscope control, data collection, image processing and analysis can be performed on the one workstation. In this report, we describe the components and capabilities of this integrated system. In addition, we discuss some general problems of multiple-wavelength, three-dimensional imaging and our application of this technology to the analysis of chromosome organization in Drosophila melanogaster. Three-dimensional imaging of fixed embryos stained by indirect immunofluorescence has revealed the structural organization of chromosomes, microtubules, and the nuclear lamins. Imaging of living embryos injected with fluorescently labelled proteins has confirmed and extended these results by allowing the study of these structures throughout the cell cycle. The combination of the molecular specificity of fluorescence microscopy and the three-dimensional structural information obtained by our workstation has provided novel insights into the dynamic aspects of chromosome behavior during the cell cycle. We believe this system has many important applications in the study of the molecular basis of cellular events.     

A hybrid SOM-SVM approach for the zebrafish gene expression analysis

Microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. In this paper, we present our results from integrating the self-organizing map （SOM） and the support vector machine （SVM） for the analysis of the various functions of zebrafish genes based on their expression. The most distinctive characteristic of our zebrafish gene expression is that the number of samples of different classes is imbalanced. We discuss how SOM can be used as a data-filtering tool to improve the classification performance of the SVM on this data set.     

Home-range analysis using radio-tracking data–a review of problems and techniques particularly as applied to the study of mammals

Ninety-three papers on home-range analysis using radio-tracking data were reviewed; these papers were found in a literature search of 18 of the major journals likely to include such papers, published in the 5-year period to the end of 1988. The review showed that even 25 years after the first radio-tracking studies, in the majority of papers there was still insufficient attention given to accurate and sufficient data collection, and to using appropriate and sophisticated analytical techniques to assess home-range size and configuration. This paper is designed to help people undertaking a radio-tracking study to avoid some of the most common pitfalls. It is based on some of the problems we have experienced studying several species of larger mammals. We use our collective experience to produce a guide on how to plan a radio-tracking study, to highlight some of the potential problems in designing the study and collecting the data, and to identify some of the difficulties that may be encountered during the analytical stages. The advantages and disadvantages of the most frequently used methods of home-range analysis are discussed and methods for determining the minimum number of radio-fixes and techniques for adjusting inadequate sample sizes are described, as are the problems that may be caused by autocorrelated data.     

ISS-An Electronic Syndromic Surveillance System for Infectious Disease in Rural China

Background

syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings.

Objective

this study describes the design and pilot implementation of an electronic surveillance system (ISS) for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system.

Methods

ISS was developed based on an existing platform ‘Crisis Information Sharing Platform’ (CRISP), combining with modern communication and GIS technology. ISS has four interconnected functions: 1) work group and communication group; 2) data source and collection; 3) data visualization; and 4) outbreak detection and alerting.

Results

As of Jan. 31^st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74256, 79701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level.

Conclusions

The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China.     

An assessment of seed quality and its influence on productivity estimation in an industrial antibiotic fermentation

This study investigates the benefits of including seed quality information into data-based models for final productivity estimation in an industrial antibiotic fermentation process. Multiway principal component analysis is applied to assess the seed quality using routinely gathered plant data. Multiway partial least-squares regression is then used to estimate the final productivity using data from the main fermentation only. The issue of selecting appropriate process variables as inputs is investigated. Subsequently, seed characteristics are included into the estimation models to assess the benefits of including information from this stage for productivity estimation. It is shown that it is possible to extract seed fermentation features related to the final productivity both at pilot and production scales. It is postulated that significant influential variations are mirrored in monitored variables during the main fermentation, and therefore seed quality is implicitly accounted for.     

RFID analytics for hospital ward management

In this paper, we present an RFID-enabled platform for hospital ward management. Active RFID tags are attached to individuals and assets in the wards. Active RFID readers communicate with the tags continuously and automatically to keep track of the real-time information about the locations of the tagged objects. The data regarding the locations and other transmitted information are stored in the ward management system. This platform enables capabilities of real-time monitoring and tracking of individuals and assets, reporting of ward statistics, and providing intelligence and analytics for hospital ward management. All of these capabilities benefit hospital ward management by enhanced patient safety, increased operational efficiency and throughput, and mitigation of risk of infectious disease widespread. A prototype developed based on our proposed architecture of the platform was tested in a pilot study, which was conducted in two medical wards of the intensive care unit of one of the largest public general hospitals in Hong Kong. This pilot study demonstrates the feasibility of the implementation of this RFID-enabled platform for practical use in hospital wards. Furthermore, the data collected from the pilot study are used to provide data analytics for hospital ward management.     

Model Building and Analysis for Block Designs with Nested Rows and Columns

The paper deals with two main problems: it gives a unified approach to model building for observations obtained in a block design with nested rows and columns and it provides the analysis of variance for such data. Also, some statistical properties of the design are examined.     

A pilot study of the use of placental cord blood samples in monitoring for mutational events

A pilot study exploring the examination of placental cord blood samples for mutant proteins with one-dimensional electrophoretic techniques is described. Although technical advances are such that the techniques employed in this study are now partially superceded, the practical problems encountered in this study would be typical of any monitoring program of this type. No mutations altering electrophoretic mobility among a battery of 51 different locus products were encountered in a total of 277,747 locus tests. When these data are combined with similar data from other studies, the mutation rate for electromorphs becomes 0.34 X 10(-5)/locus/generation.     

退化森林生态系统评价指标体系研究进展

森林是陆地生态系统的主要组成部分,而森林退化是全球面临的主要环境问题之一,准确评价退化森林生态系统是进行森林生态系统恢复与重建的重要前提,建立合理的评价指标体系目前已成为生态学研究的热点问题。在研究国内外提出的关于退化森林生态系统评价理论的基础上,综述了森林退化的定义、特征和一般过程,梳理了退化森林生态系统评价指标筛选的一般原则和指标体系构建的主要方法,分析比较了不同学者所提出的主要评价指标。并在此基础上,重新筛选、构建了一套退化森林生态系统评价指标体系,即从生态系统的组成结构、功能和生境这3个方面选取了32个能够较全面反映退化生态系统主要特征的评价指标,以期为构建我国区域尺度上的退化森林生态系统评价指标体系提供参考,为退化森林生态系统的恢复和重建提供科学依据。总结分析了退化森林生态系统评价指标体系在构建过程中产生的一些问题和不足,提出了今后开展研究和探索应该深入的方向,以提高评价指标体系的科学性、准确性和合理性。     

From Lab to Field Conditions: A Pilot Study on EEG Methodology in Applied Sports Sciences

Although neurophysiological aspects have become more important in sports and exercise sciences in the last years, it was not possible to measure cortical activity during performance outside a laboratory due to equipment limits or movement artifacts in particular. With this pilot study we want to investigate whether Electroencephalography (EEG) data obtained in a laboratory golf putting performance differ from a suitable putting task under field conditions. Therefore, parameters of the working memory (frontal Theta and parietal Alpha 2 power) were recorded during these two conditions. Statistical calculations demonstrated a significant difference only for Theta power at F4 regarding the two putting conditions “field” and “laboratory”. These findings support the idea that brain activity patterns obtained under laboratory conditions are comparable but not equivalent to those obtained under field conditions. Additionally, we were able to show that the EEG methodology seems to be a reliable tool to observe brain activity under field conditions in a golf putting task. However, considering the still existing problems of movement artifacts during EEG measurements, eligible sports and exercises are limited to those being relatively motionless during execution. Further studies are needed to confirm these pilot results.     

A novel approach for pilot error detection using Dynamic Bayesian Networks

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment’s data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.     

Model-free analysis and permutation tests for allelic associations

In this short report, we address some practical problems in performing likelihood-based allelic association analysis of case-control data. Model-free statistics are proposed and their properties assessed by simulation, and procedures based on permutation tests are described for marker-marker as well as marker-disease associations. A memory-efficient algorithm is developed which enables several highly polymorphic markers to be analysed.     

生态城市建设评价指标体系构建的新方法——组合式动态评价法

如何建立科学严谨的评价指标体系一直是生态城市研究中学者们普遍关注的焦点问题。在以往的生态城市建设评价指标体系研究中,很少考虑各个城市的差异与地域特点,也带来了一系列的问题。针对这些问题,以生态城市建设地域类型划分结果为基础,提出了一种新的生态城市建设评价体系构建方法:组合式动态评价法。并以宜宾等城市为例,对该方法的具体应用进行了分析,探讨了其优缺点。研究结果表明,相对于现行的评价体系,组合式动态评价法具有合理性、动态性、灵活性、拓展性、综合性等优点;但也存在着数据要求较高、精度有待提高、管理难度较大等不足。随着我国生态城市建设数据的积累和管理体系的完善,组合式动态评价法有望为我国生态城市建设评价指标体系的构建提供一种更好的思路和方法。     

Dimensional analysis of nonlinear oscillations in brain, heart, and muscle

We present some numerical studies on the dimensional analysis of temporal oscillations observed in human electroencephalograms (EEG), heart rates, and muscle tremors. We show that it is insufficient to characterize the individual system by a single dimension value alone. We also present some detailed numerical analysis of the scaling structure of the attractors reconstructed from the time signal. Our methods are based on the concept of local gauge functions, which we derive from the raw signals and from transformed signals obtained through singular value decomposition. We are able to confirm and improve earlier results on the change of dimensionality of EEG signals. For heart rates we observe an increase of the dimensional complexity during sleep, and for muscle tremor data we find significant changes in the dimensionality depending on the isometrical contraction of the muscle. We attempt to indicate which factors are important in determining dimension estimates and where specific problems lie in each of the examples.     

A Comparison of Two Recorders for Obtaining In-flight Heart Rate Data

Measurement of mental workload has been widely used for evaluation of aircraft design, mission analysis and assessment of pilot performance during flight operations. Heart rate is the psychophysiological measure that has been most frequently used for this purpose. The risk of interference with flight safety and pilot performance, as well as the generally constrained access to flights, make it difficult for researchers to collect in-flight heart rate data. Thus, this study was carried out to investigate whether small, non-intrusive sports recorders can be used for in-flight data collection for research purposes. Data was collected from real and simulated flights with student pilots using the Polar Team System sports recorder and the Vitaport II, a clinical and research recording device. Comparison of the data shows that in-flight heart rate data from the smaller and less intrusive sports recorder have a correlation of.981 with that from the clinical recorder, thus indicating that the sports recorder is reliable and cost-effective for obtaining heart rate data for many research situations.