University of Stirling

About: University of Stirling is a education organization based out in Stirling, Stirling, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 7722 authors who have published 20549 publications receiving 732940 citations. The organization is also known as: Stirling University.

Cultures in chimpanzees

Abstract: As an increasing number of field studies of chimpanzees (Pan troglodytes) have achieved long-term status across Africa, differences in the behavioural repertoires described have become apparent that suggest there is significant cultural variation1,2,3,4,5,6,7. Here we present a systematic synthesis of this information from the seven most long-term studies, which together have accumulated 151 years of chimpanzee observation. This comprehensive analysis reveals patterns of variation that are far more extensive than have previously been documented for any animal species except humans8,9,10,11. We find that 39 different behaviour patterns, including tool usage, grooming and courtship behaviours, are customary or habitual in some communities but are absent in others where ecological explanations have been discounted. Among mammalian and avian species, cultural variation has previously been identified only for single behaviour patterns, such as the local dialects of song-birds12,13. The extensive, multiple variations now documented for chimpanzees are thus without parallel. Moreover, the combined repertoire of these behaviour patterns in each chimpanzee community is itself highly distinctive, a phenomenon characteristic of human cultures14 but previously unrecognised in non-human species.

Bacterial Fish Pathogens: Disease of Farmed and Wild Fish

Abstract: The structure of fish the meaning of disease in relation to fish anaerobic pathogens gram-positive bacteria - the ...lactic acid bacteria... aerobic gram-positive rods and cocci excluding the lactobacilli aeromonadaceae representatives ...aeromonas salmonicida... aeromonadaceae representatives excluding ...aeromonas salmonicida... enterobacteriaceae representatives cytophagaceae representatives including related gram-negative yellow/orange pigmented rods pseudomonadaceae representatives vibrionaceae representatives moraxellaceae representatives small, morphologically simple bacteria miscellaneous pathogens diagnosis of bacterial fish pathogens control of bacterial fish diseases outlook.

Structured interviews for the Glasgow Outcome Scale and the extended Glasgow Outcome Scale: Guidelines for their use

Abstract: The Glasgow Outcome Scale (GOS) is the most widely used outcome measure after traumatic brain injury, but it is increasingly recognized to have important limitations. It is proposed that shortcomings of the GOS can be addressed by adopting a standard format for the interview used to assign outcome. A set of guidelines are outlined that are directed at the main problems encountered in applying the GOS. The guidelines cover the general principles underlying the use of the GOS and common practical problems of applying the scale. Structured interview schedules are described for both the five-point GOS and an extended eight-point GOS (GOSE). An interrater reliability study of the structured interviews for the GOS and GOSE yielded weighted kappa values of 0.89 and 0.85, respectively. It is concluded that assessment of the GOS using a standard format with a written protocol is practical and reliable.

MEG and EEG data analysis with MNE-Python

Abstract: Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.