Polarization vision and its role in biological signaling

Visual pigments, the molecules in photoreceptors that initiate the process of vision, are inherently dichroic, differentially absorbing light according to its axis of polarization. Many animals have taken advantage of this property to build receptor systems capable of analyzing the polarization of incoming light, as polarized light is abundant in natural scenes (commonly being produced by scattering or reflection). Such polarization sensitivity has long been associated with behavioral tasks like orientation or navigation. However, only recently have we become aware that it can be incorporated into a high-level visual perception akin to color vision, permitting segmentation of a viewed scene into regions that differ in their polarization. By analogy to color vision, we call this capacity polarization vision. It is apparently used for tasks like those that color vision specializes in: contrast enhancement, camouflage breaking, object recognition, and signal detection and discrimination. While color is very useful in terrestrial or shallow-water environments, it is an unreliable cue deeper in water due to the spectral modification of light as it travels through water of various depths or of varying optical quality. Here, polarization vision has special utility and consequently has evolved in numerous marine species, as well as at least one terrestrial animal. In this review, we consider recent findings concerning polarization vision and its significance in biological signaling.

Presentation and detection of invasive melanoma in a high-risk population

Background: Early detection of melanoma has been encouraged in Queensland for many years, yet little is known about the patterns of detection and the way in which they relate to tumor thickness. Objective: Our purpose was to describe current patterns of melanoma detection in Queensland. Methods: This was a population-based study, comprising 3772 Queensland residents diagnosed with a histologically confirmed melanoma between 2000 and 2003. Results: Almost half (44.0%) of the melanomas were detected by the patients themselves, with physicians detecting one fourth (25.3%) and partners one fifth (18.6%). Melanomas detected by doctors were more likely to be thin (\0.75 mm) than those detected by the patient or other layperson. Melanomas detected during a deliberate skin examination were thinner than those detected incidentally. Limitations: Although a participation rate of 78% was achieved, as in any survey, nonresponse bias cannot be completely excluded, and the ability of the results to be generalized to other geographical areas is unknown. Conclusion: There are clear differences in the depth distribution of melanoma in terms of method of detection and who detects the lesions that are consistent with, but do not automatically lead to, the conclusion that promoting active methods of detection may be beneficial. ( J Am Acad Dermatol 2006;54:783-92.)

Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.

Presentation and mechanisms of concussion in professional Rugby League football

The present study prospectively recorded the circumstances, incidence, mechanisms, injury detection and presentation of concussion in Rugby League. Forty-three consecutive concussions were recorded over three competitive seasons in 175 professional Rugby League players. Data showed (i) the incidence of concussion ranged from 5.9 to 9.8 injuries/1000 player hours across grades - except when age-group players were mismatched (18.4); (ii) 'head-high tackles' accounted for a significant number of concussions; (iii) concussion rarely involved a loss of consciousness with the most common indicators of concussion being amnesia, headache and unsteadiness, with the mechanism of injury often missed; and (iv) concussion often occurs concurrently with other injuries. Concussion (including repeated episodes) is a common injury in Rugby League. Systematic mental status questioning is warranted whenever concussion is suspected. Coaches, trainers and players need more education in the recognition and management of concussion. Stricter penalties for illegal 'head-high' tackling are strongly recommended.

Rumors and stable-cause attribution in prediction and behavior

Two stock-market simulation experiments investigated the notion that rumors that invoke stable-cause attributions spawn illusory associations and less regressive predictions and behavior. In Study 1, illusory perceptions of association and stable causation (rumors caused price changes on the day after they appeared) existed despite rigorous conditions of nonassociation (price changes were unrelated to rumors). Predictions (recent price trends will continue) and trading behavior (departures from a strong buy-low-sell-high strategy) were both anti-regressive. In Study 2, stability of attribution was manipulated via a computerized tutorial. Participants taught to view price-changes as caused by stable forces predicted less regressively and departed more from buy-low-sell-high trading patterns than those taught to perceive changes as caused by unstable forces. Results inform a social cognitive and decision theoretic understanding of rumor by integrating it with causal attribution, covariation detection, and prediction theory. (C) 2002 Elsevier Science (USA). All rights reserved.

Modeling the relationships between adult attachment patterns and borderline personality disorder: The role of impulsivity and aggressiveness

To obtain a better understanding of the associations among Borderline Personality Disorder (BPD), adult attachment patterns, impulsivity, and aggressiveness, we tested four competing models of these relationships: a) BPD is associated with the personality traits of impulsivity and aggressiveness, but adult attachment patterns predict neither BPD nor impulsive/aggressive features; b) adult attachment patterns are significant predictors of BPD but not of impulsive/aggressive traits, although these traits correlate with BPD; c) adult attachment patterns are significant predictors of impulsive and aggressive traits, which in turn predict BPD; and d) adult attachment patterns significantly predict both BPD and impulsive/aggressive traits. We assessed 466 consecutively admitted outpatients using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (V. 2.0), the Attachment Style Questionnaire, the Barratt Impulsiveness Scale-11, and the Aggression Questionnaire. Maximum likelihood structural equation modeling of the covariance matrix showed that model (c) was the best fitting model (chi(2) (21) = 31.67, p >.05, RMSEA = .023, test of close fit p >.85). This result indicates that adult attachment patterns act indirectly as risk factors for BPD because of their relationships with aggressive/impulsive personality traits.

Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models—"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall

Development and evaluation of a youth mental health community awareness campaign - The Compass Strategy

Background: Early detection and treatment of mental disorders in adolescents and young adults can lead to better health outcomes. Mental health literacy is a key to early recognition and help seeking. Whilst a number of population health initiatives have attempted to improve mental health literacy, none to date have specifically targeted young people nor have they applied the rigorous standards of population health models now accepted as best practice in other health areas. This paper describes the outcomes from the application of a health promotion model to the development, implementation and evaluation of a community awareness campaign designed to improve mental health literacy and early help seeking amongst young people. Method: The Compass Strategy was implemented in the western metropolitan Melbourne and Barwon regions of Victoria, Australia. The Precede-Proceed Model guided the population assessment, campaign strategy development and evaluation. The campaign included the use of multimedia, a website, and an information telephone service. Multiple levels of evaluation were conducted. This included a cross-sectional telephone survey of mental health literacy undertaken before and after 14 months of the campaign using a quasi-experimental design. Randomly selected independent samples of 600 young people aged 12 - 25 years from the experimental region and another 600 from a comparison region were interviewed at each time point. A series of binary logistic regression analyses were used to measure the association between a range of campaign outcome variables and the predictor variables of region and time. Results: The program was judged to have an impact on the following variables, as indicated by significant region-by-time interaction effects ( p < 0.05): awareness of mental health campaigns, self-identified depression, help for depression sought in the previous year, correct estimate of prevalence of mental health problems, increased awareness of suicide risk, and a reduction in perceived barriers to help seeking. These effects may be underestimated because media distribution error resulted in a small amount of print material leaking into the comparison region. Conclusion: We believe this is the first study to apply the rigorous standards of a health promotion model including the use of a control region to a mental health population intervention. The program achieved many of its aims despite the relatively short duration and moderate intensity of the campaign.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

Effects of temporal association on recognition memory

The influence of temporal association on the representation and recognition of objects was investigated. Observers were shown sequences of novel faces in which the identity of the face changed as the head rotated. As a result, observers showed a tendency to treat the views as if they were of the same person. Additional experiments revealed that this was only true if the training sequences depicted head rotations rather than jumbled views; in other words, the sequence had to be spatially as well as temporally smooth. Results suggest that we are continuously associating views of objects to support later recognition, and that we do so not only on the basis of the physical similarity, but also the correlated appearance in time of the objects.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

The effects of prepulse-blink reflex trial repetition and prepulse change on blink reflex modification at short and long lead intervals

Prepulse inhibition and facilitation of the blink reflex are said to reflect different responses elicited by the lead stimulus, transient detection and orienting response respectively. Two experiments investigated the effects of trial repetition and lead stimulus change on blink modification. It was hypothesized that these manipulations will affect orienting and thus blink facilitation to a greater extent than they will affect transient detection and thus blink inhibition. In Experiment 1 (N = 64), subjects were trained with a sequence of 12 lead stimulus and 12 blink stimulus alone presentations, and 24 lead stimulus-blink stimulus pairings. Lead interval was 120 ms for 12 of the trials and 2000 ms for the other 12. For half the subjects this sequence was followed by a change in pitch of the lead stimulus. In Experiment 2 (N = 64), subjects were trained with a sequence of 36 blink alone stimuli and 36 lead stimulus-blink stimulus pairings. The lead interval was 120 ms for half the subjects and 2000 ms for the other half. The pitch of the lead stimulus on prestimulus trials 31-33 was changed for half the subjects in each group. In both experiments, the amount of blink inhibition decreased during training whereas the amount of blink facilitation remained unchanged. Lead stimulus change had no effect on blink modification in either experiment although it resulted in enhanced skin conductance responses and greater heart rate deceleration in Experiment 2. The present results are not consistent with the notion that blink facilitation is linked to orienting whereas blink inhibition reflects a transient detection mechanism. (C) 1998 Elsevier Science B.V.

Preeruptive intracoronal radiolucencies: Review and report of case

Intracoronal radiolucencies in unerupted teeth are an uncommon radiographic finding; but their early detection and classification allow the most appropriate management protocol to be developed. Early separation of lesions into those that are developmental and remain static and those that are reactive and aggressive is necessary for a controlled outcome. The current paper reviews possible formative mechanisms and describes a case of severe intracoronal resorption resulting in loss of the tooth.

Magnetic resonance imaging (MRI) and diseases of the liver and biliary tract. Part 1. Basic principles, MRI in the assessment of diffuse and focal hepatic disease

Magnetic resonance imaging (MRI) relies on the physical properties of unpaired protons in tissues to generate images. Unpaired protons behave like tiny bar magnets and will align themselves in a magnetic field. Radiofrequency pulses will excite these aligned protons to higher energy states. As they return to their original state, they will release this energy as radio waves. The frequency of the radio waves depends on the local magnetic field and by varying this over a subject, it is possible to build the images we are familiar with. In general, MRI has not been sufficiently sensitive or specific in the assessment of diffuse liver disease for clinical use. However, because of the specific characteristics of fat and iron, it may be useful in the assessment of hepatic steatosis and iron overload. Magnetic resonance imaging is useful in the assessment of focal liver disease, particularly in conjunction with contrast agents. Haemangiomas have a characteristic bright appearance on T-2 weighted images because of the slow flowing blood in dilated sinusoids. Focal nodular hyperplasia (FNH) has a homogenous appearance, and enhances early in the arterial phase after gadolinium injection, while the central scar typically enhances late. Hepatic adenomas have a more heterogenous appearance and also enhance in the arterial phase, but less briskly than FNH. Hepatocellular carcinoma is similar to an adenoma, but typically occurs in a cirrhotic liver and has earlier washout of contrast. The appearance of metastases depends on the underlying primary malignancy. Overall, MRI appears more sensitive and specific than computed tomography with contrast for the detection and evaluation of malignant lesions. (C) 2000 Blackwell Science Asia Pty Ltd.

Late Quaternary Milankovitch-scale climatic change and variability and its impact on monsoonal Australasia

Four pollen and charcoal records derived from marine cores around the northern perimeter of Australia are examined to provide a regional picture of patterns, causes and impacts of climate change over the last 100-300 ka. The availability of radiocarbon dates and oxygen isotope records for the cores provides primary chronological control. Spectral analysis of components of these records demonstrates an overall importance of Milankovitch frequencies with clear glacial-interglacial cyclicity dominated by variation in precipitation. In addition, a number of pollen taxa, as well as charcoal particles, exhibit a 30 ka frequency that is considered, from its relationship with biomass burning and with results of past modelling, to reflect changes in the intensity of El Nino-Southern Oscillation (ENSO) variability. Pollen components of all records show a decline, frequently stepwise, in more fire-sensitive vegetation and its replacement with more fire-tolerant vegetation. There is some evidence that this trend is linked to an onset or general increase in ENSO activity and perhaps also to variation in monsoon activity dating from about 300 ka BP that was caused by changes to oceanic circulation within the Indonesian region. The trend may have accelerated within the last 45 ka due to burning by indigenous people. (C) 2003 Elsevier B.V. All rights reserved.