Abundance of harbor porpoise (Phocoena phocoena) in three Alaskan regions, corrected for observer errors due to perception bias and species misidentification, and corrected for animals submerged from view

Estimating the abundance of cetaceans from aerial survey data requires careful attention to survey design and analysis. Once an aerial observer perceives a marine mammal or group of marine mammals, he or she has only a few seconds to identify and enumerate the individuals sighted, as well as to determine the distance to the sighting and record this information. In line-transect survey analyses, it is assumed that the observer has correctly identified and enumerated the group or individual. We describe methods used to test this assumption and how survey data should be adjusted to account for observer errors. Harbor porpoises (Phocoena phocoena) were censused during aerial surveys in the summer of 1997 in Southeast Alaska (9844 km survey effort), in the summer of 1998 in the Gulf of Alaska (10,127 km), and in the summer of 1999 in the Bering Sea (7849 km). Sightings of harbor porpoise during a beluga whale (Phocoena phocoena) survey in 1998 (1355 km) provided data on harbor porpoise abundance in Cook Inlet for the Gulf of Alaska stock. Sightings by primary observers at side windows were compared to an independent observer at a belly window to estimate the probability of misidentification, underestimation of group size, and the probability that porpoise on the surface at the trackline were missed (perception bias, g(0)). There were 129, 96, and 201 sightings of harbor porpoises in the three stock areas, respectively. Both g(0) and effective strip width (the realized width of the survey track) depended on survey year, and g(0) also depended on the visibility reported by observers. Harbor porpoise abundance in 1997–99 was estimated at 11,146 animals for the Southeast Alaska stock, 31,046 animals for the Gulf of Alaska stock, and 48,515 animals for the Bering Sea stock.

Low rates of Pseudomonas aeruginosa misidentification in isolates from cystic fibrosis patients

Pseudomonas aeruginosa is an important cause of pulmonary infection in cystic fibrosis (CF). Its correct identification ensures effective patient management and infection control strategies. However, little is known about how often CF sputum isolates are falsely identified as P. aeruginosa. We used P. aeruginosa-specific duplex real-time PCR assays to determine if 2,267 P. aeruginosa sputum isolates from 561 CF patients were correctly identified by 17 Australian clinical microbiology laboratories. Misidentified isolates underwent further phenotypic tests, amplified rRNA gene restriction analysis, and partial 16S rRNA gene sequence analysis. Participating laboratories were surveyed on how they identified P. aeruginosa from CF sputum. Overall, 2,214 (97.7%) isolates from 531 (94.7%) CF patients were correctly identified as P. aeruginosa. Further testing with the API 20NE kit correctly identified only 34 (59%) of the misidentified isolates. Twelve (40%) patients had previously grown the misidentified species in their sputum. Achromobacter xylosoxidans (n = 21), Stenotrophomonas maltophilia (n = 15), and Inquilinus limosus (n = 4) were the species most commonly misidentified as P. aeruginosa. Overall, there were very low rates of P. aeruginosa misidentification among isolates from a broad cross section of Australian CF patients. Additional improvements are possible by undertaking a culture history review, noting colonial morphology, and performing stringent oxidase, DNase, and colistin susceptibility testing for all presumptive P. aeruginosa isolates. Isolates exhibiting atypical phenotypic features should be evaluated further by additional phenotypic or genotypic identification techniques.

Hidden interlocutor misidentification in practical Turing Tests

Based on insufficient evidence, and inadequate research, Floridi and his students report inaccuracies and draw false conclusions in their Minds and Machines evaluation, which this paper aims to clarify. Acting as invited judges, Floridi et al. participated in nine, of the ninety-six, Turing tests staged in the finals of the 18th Loebner Prize for Artificial Intelligence in October 2008. From the transcripts it appears that they used power over solidarity as an interrogation technique. As a result, they were fooled on several occasions into believing that a machine was a human and that a human was a machine. Worse still, they did not realise their mistake. This resulted in a combined correct identification rate of less than 56%. In their paper they assumed that they had made correct identifications when they in fact had been incorrect.

I and I: immunity to error through misidentification of the subject

Abstract I argue for the following claims: [1] all uses of I (the word ‘I’ or thought-element I) are absolutely immune to error through misidentification relative to I. [2] no genuine use of I can fail to refer. Nevertheless [3] I isn’t univocal: it doesn’t always refer to the same thing, or kind of thing, even in the thought or speech of a single person. This is so even though [4] I always refers to its user, the subject of experience who speaks or thinks, and although [5] if I’m thinking about something specifically as myself, I can’t fail to be thinking of myself, and although [6] a genuine understanding use of I always involves the subject thinking of itself as itself, whatever else it does or doesn’t involve, and although [7] if I take myself to be thinking about myself, then I am thinking about myself.

Human misidentification in Turing tests

This paper presents some important issues on misidentification of human interlocutors in text-based communication during practical Turing tests. The study here presents transcripts in which human judges succumbed to theconfederate effect, misidentifying hidden human foils for machines. An attempt is made to assess the reasons for this. The practical Turing tests in question were held on 23 June 2012 at Bletchley Park, England. A selection of actual full transcripts from the tests is shown and an analysis is given in each case. As a result of these tests, conclusions are drawn with regard to the sort of strategies which can perhaps lead to erroneous conclusions when one is involved as an interrogator. Such results also serve to indicate conversational directions to avoid for those machine designers who wish to create a conversational entity that performs well on the Turing test.

Misidentification of two Brazilian triatomes, Triatoma arthurneivai and Triatoma wygodzinskyi, revealed by geometric morphometrics

Triatoma arthurneivai Lent & Martins and Triatoma wygodzinskyi Lent (Hemiptera: Reduviidae) are two Brazilian species found in the sylvatic environment. Several authors may have misidentified T. arthurneivai and consequently published erroneous information. This work reports the use of geometric morphometric analysis on wings in order to differentiate T. arthurneivai and T. wygodzinskyi, and thus to detect possible misidentifications. Triatomines collected from the field in the states of Minas Gerais and Sao Paulo, and from laboratory colonies, were used. Analyses show a clear differentiation between specimens of T. arthurneivai and T. wygodzinskyi. This indicates that T. arthurneivai populations from Sao Paulo state were misidentified and should be considered as T. wygodzinskyi. This study also suggests that T. arthurneivai is an endemic species from Serra do Cipo, Minas Gerais state.

Evaluation of nine microsatellite loci and misidentification paternity frequency in a population of Gyr breed bovines

Erros de identificação de paternidade são prejudiciais por reduzir o ganho genético anual e comprometer um programa eficiente de melhoramento genético. O objetivo principal deste trabalho foi avaliar o potencial de uso de nove microssatélites em testes de paternidade e investigar a freqüência de erro de identificação de famílias de um rebanho de animais da raça Gir. No experimento foram utilizadas amostras de sangue de quarenta famílias (touro/ vaca/ bezerro) de animais da raça Gir, Puros de Origem e registrados na Associação Brasileira dos Criadores de Zebu (ABCZ). A maior parte dos microssatélites avaliados neste trabalho são recomendados, para Testes de Paternidade em bovinos, pela Sociedade Internacional de Genética Animal (ISAG). As regiões microssatélites TGLA122, TGLA126, BM1824, BMS2533, SPS115, ETH3, ETH10, ETH225 e POTCHA foram amplificadas por meio da técnica de PCR. Os produtos da amplificação foram separados por eletroforese em gel de poliacrilamida desnaturante. A partir dos dados obtidos foram calculadas as freqüências alélicas, diversidade gênica, conteúdo de polimorfismo informativo e probabilidade de exclusão para cada microssatélite. Também foram calculadas as freqüências genotípicas, heterozigosidade, probabilidade de exclusão combinada e probabilidade de Paternidade nas famílias consideradas. A probabilidade de exclusão combinada para todos os microssatélites estudados foi de 0,9789. Os resultados dos testes de paternidade acusaram erro de identificação em onze das 40 famílias estudadas, ou seja, 27,5% da amostra. A probabilidade de paternidade variou entre 0,8691 e 0,9999, com valor médio de 0,9512.

Potential misidentification of in situ archaeological tool-residues: starch and conidia

Microscopic identification of organic residues in situ on the surface of archaeological artefacts is an established procedure. Where soil components morphologically similar to use-residue types exist within the soil, however, there remains the possibility that these components may be misidentified as authentic residues. The present study investigates common soil components known as conidia, fungal spores which may be mistaken for starch grains. Conidia may exhibit the rotating extinction cross under cross-polarised light commonly diagnostic of starch, and may be morphologically indistinguishable from small starch grains, particularly at the limits of microscope resolution. Conidia were observed on stone and ceramic archaeological artefacts from Honduras, Palau and New Caledonia, as well as experimental artefacts from Papua New Guinea. The findings act as a caution that in situ analysis of residues, and especially of those less than 5 mu m in size, may be subject to misidentification. (c) 2005 Elsevier Ltd. All rights reserved.

LCC15-MB cells are MDA-MB-435 : a review of misidentified breast and prostate cell lines

Current stocks of the LCC15-MB cell line, which we originally isolated from a human breast-bone metastasis, were found to be genetically matched to the MDA-MB-435 cell line from the Lombardi Cancer Center (MDA-MB-435-LCC) using comparative genomic hybridisation, DNA microsatellite analysis and chromosomal number. LCC15-MB stocks used for our previously published studies as well as the earliest available LCC15-MB cells also showed identity to MDA-MB-435-LCC cells. The original karyotype reported for LCC15-MB cells was considerably different to that of MDA-MB-435 cells, indicating that the original LCC15-MB cells were lost to contamination by MDA-MB-435-LCC cells. Chromosome number is the simplest test to distinguish original LCC 15-MB cells (n ∼ 75) from MDA-MB-435 (n ∼ 52). Collectively, our results prove that LCC15-MB cells currently available are MDA-MB-435 cells and we suggest their re-designation as MDA-MB-435-LCC15 cells. We also review the known misclassification of breast and prostate cancer cell lines to date and have initiated a register maintained at http://www.svi.edu.au/cell_lines_registry.doc.

Common psychotic symptoms can be explained by the theory of ecological perception

The symptoms of psychiatric illness are diverse, as are the causes of the illnesses that cause them. Yet, regardless of the heterogeneity of cause and presentation, a great deal of symptoms can be explained by the failure of a single perceptual function – the reprocessing of ecological perception. It is a central tenet of the ecological theory of perception that we perceive opportunities to act. It has also been found that perception automatically causes actions and thoughts to occur unless this primary action pathway is inhibited. Inhibition allows perceptions to be reprocessed into more appropriate alternative actions and thoughts. Reprocessing of this kind takes place over the entire frontal lobe and it renders action optional. Choice about what action to take (if any) is the basis for the feeling of autonomy and ultimately for the sense-of-self. When thoughts and actions occur automatically (without choice) they appear to originate outside of the self, thereby providing prima facie evidence for some of the bizarre delusions that define schizophrenia such as delusional misidentification, delusions of control and Cotard’s delusion. Automatic actions and thoughts are triggered by residual stimulation whenever reprocessing is insufficient to balance automatic excitatory cues (for whatever reason). These may not be noticed if they are neutral and therefore unimportant whereas actions and thoughts with a positive bias are desirable. Responses to negative stimulus, on the other hand, are always unwelcome, because the actions that are triggered will carry the negative bias. Automatic thoughts may include spontaneous positive feelings of love and joy, but automatic negative thoughts and visualisations are experienced as hallucinations. Not only do these feel like they emerge from elsewhere but they carry a negative bias (they are most commonly critical, rude and are irrationally paranoid). Automatic positive actions may include laughter and smiling and these are welcome. Automatic behaviours that carry a negative bias, however, are unwelcome and like hallucinations, occur without a sense of choice. These include crying, stereotypies, perseveration, ataxia, utilization and imitation behaviours and catatonia.

The complexities of knowing what it is you are trapping

The effectiveness of any trapping system is highly dependent on the ability to accurately identify the specimens collected. For many fruit fly species, accurate identification (= diagnostics) using morphological or molecular techniques is relatively straightforward and poses few technical challenges. However, nearly all genera of pest tephritids also contain groups of species where single, stand-alone tools are not sufficient for accurate identification: such groups include the Bactrocera dorsalis complex, the Anastrepha fraterculus complex and the Ceratitis FAR complex. Misidentification of high-impact species from such groups can have dramatic consequences and negate the benefits of an otherwise effective trapping program. To help prevent such problems, this chapter defines what is meant by a species complex and describes in detail how the correct identification of species within a complex requires the use of an integrative taxonomic approach. Integrative taxonomy uses multiple, independent lines of evidence to delimit species boundaries, and the underpinnings of this approach from both the theoretical speciation literature and the systematics/taxonomy literature are described. The strength of the integrative approach lies in the explicit testing of hypotheses and the use of multiple, independent species delimitation tools. A case is made for a core set of species delimitation tools (pre- and post-zygotic compatibility tests, multi-locus phylogenetic analysis, chemoecological studies, and morphometric and geometric morphometric analyses) to be adopted as standards by tephritologists aiming to resolve economically important species complexes. In discussing the integrative approach, emphasis is placed on the subtle but important differences between integrative and iterative taxonomy. The chapter finishes with a case study that illustrates how iterative taxonomy applied to the B. dorsalis species complex led to incorrect taxonomic conclusions, which has had major implications for quarantine, trade, and horticultural pest management. In contrast, an integrative approach to the problem has resolved species limits in this taxonomically difficult group, meaning that robust diagnostics are now available.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.