Field manual 3-24 and the heritage of counterinsurgency theory

The Counterinsurgency Manual FM 3-24 has been accused of being over-dependent on the counterinsurgency 'classics' Galula and Thompson. But comparison reveals that it is different in spirit. Galula and Thompson seek practical control; the Manual seeks to build 'legitimacy'. Its concept of legitimacy is superficially Weberian, but owes more to the writings of the American Max Manwaring. The Manual presupposes that a rights-based legal order can (other things being equal) be made to be cross-culturally attractive; 'effective governance' by itself can build legitimacy. The fusion of its methods with an ideology creates unrealistic criteria for success. Its weaknesses suggest a level of incapacity to think politically that will, in time, result in further failures.

Comparative genomic indexing reveals the phylogenomics of Escherichia coli pathogens

The Escherichia coli O26 serogroup includes important food-borne pathogens associated with human and animal diarrheal disease. Current typing methods have revealed great genetic heterogeneity within the O26 group; the data are often inconsistent and focus only on verotoxin (VT)-positive O26 isolates. To improve current understanding of diversity within this serogroup, the genomic relatedness of VT-positive and -negative O26 strains was assessed by comparative genomic indexing. Our results clearly demonstrate that irrespective of virulence characteristics and pathotype designation, the O26 strains show greater genomic similarity to each other than to any other strain included in this study. Our data suggest that enteropathogenic and VT-expressing E. coli O26 strains represent the same clonal lineage and that W-expressing E. coli O26 strains have gained additional virulence characteristics. Using this approach, we established the core genes which are central to the E. coli species and identified regions of variation from the E. coli K-12 chromosomal backbone.

Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response

Abstract Background: The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR. Methods: A total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis. Results: In most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners. Conclusions: Our results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.

Neuromantic : from semi-manual to semi-automatic reconstruction of neuron morphology

The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

User's manual

'Typeform dialogues', as originally planned for publication, was an interactive CD-based screen interface presenting a comparative survey of typeform history and description. The CD was to be held inside a printed book that included two essays and a User’s Manual. Although 'Typeform dialogues' (CD+book) was not completed as planned, a PDF file was published containing the User’s Manual, together with background information about the interface and the project it was part of. The User's Manual presents all interface sections and features (using screen grabs) and explains their editorial rationale, design, and function.

Overcoming your child’s fears and worries: guided self-help manual for therapists working with groups

This manual for therapists accompanies ‘Overcoming your child’s fears and worries’ (Creswell & Willetts, 2007), a guide for parents to help their children overcome difficulties with anxiety

Overcoming your child’s fears and worries: guided parent delivered CBT treatment manual for therapists

This manual for therapists accompanies ‘Overcoming your child’s fears and worries’ (Creswell & Willetts, 2007), a guide for parents to help their children overcome difficulties with anxiety

Slicing the metric space to provide quick indexing of complex data in the main memory

Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Complex networks analysis of manual and machine translations

Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

Kraftutveckling för manuella trädfällningsredskap : Force development for manual tree felling tools

The objective with this study has been to build general models of the mechanics in tree felling with chain-saw and to compare felling torque for different tools. The theoretical models are completed and validated with a comparative study. The study includes a great number of felling tools of which some are used with different methods. Felling torque was measured using a naturally like measuring arrangement where a tree is cut at about 3.7 m height and then anchored with a dynamometer to a tree opposite to the felling direction. Notch and felling cut was made as ordinary with exception that the hinge was made extra thin to reduce bending resistance. The tree was consequently not felled during the trials and several combinations of felling tools and individuals could be used on the same tree.The results show big differences between tools, methods and persons. The differences were, however, not general, but could vary depending on conditions (first of all tree diameters). Tools and methods that push or pull on the stem are little affected by the size of the tree, while tools that press on the stump are very much dependent of a large stump-diameter. Hand force asserted on a simple pole is consequently a powerful tool on small trees. For trees of medium size there are several alternative methods with different sizes and brands of felling levers and wedges. Larger and more ungainly tools and methods like tree pusher, winch, etc. develop very high felling torque on all tree sizes. On large trees also the felling wedge and especially the use of several wedges together develop very high felling torque.