Development and validation of a lateral flow device for the detection of nicarbazin contamination in poultry feeds

Concentrations of the coccidiostat nicarbazin as low as 2 mg/kg in feed can result in violative drug residues arising in poultry liver. A lateral flow device (LFD) was developed for the detection of contaminating concentrations of nicarbazin following solvent extraction of poultry feeds. Test results, as determined by both visual and instrumental measurement, are available within minutes. For 22 feed samples, nicarbazin-free and fortified at 2 mg/kg, the % relative inhibition ranged from 0 to 45% and from 53 to 85%, respectively. Nicarbazin contamination at the critical concentration (2 mg/kg) can be determined in all cases providing the sampling is representative. A wide range of feed samples taken at a mill that incorporated nicarbazin into poultry feed were analyzed. Data generated for these samples by both the LFDs and a mass spectrometric method were compared, and a significant correlation was achieved.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion-extension, forearm pronation-supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60A degrees visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.

Visual function and dysfunction in early and late age-related maculopathy

Late age-related maculopathy (ARM) is responsible for the majority of blind registrations in the Western world among persons over 50 years of age. It has devastating effects on quality of life and independence and is becoming a major public health concern. Current treatment options are limited and most aim to slow progression rather than restore vision; therefore, early detection to identify those patients most suitable for these interventions is essential. In this work, we review the literature encompassing the investigation of visual function in ARM in order to highlight those visual function parameters which are affected very early in the disease process. We pay particular attention to measures of acuity, contrast sensitivity (CS), cone function, electrophysiology, visual adaptation, central visual field sensitivity and metamorphopsia. We also consider the impact of bilateral late ARM on visual function as well as the relationship between measures of vision function and self-reported visual functioning. Much interest has centred on the identification of functional changes which may predict progression to neovascular disease; therefore, we outline the longitudinal studies, which to date have reported dark-adaptation time, short-wavelength cone sensitivity, colour-match area effect, dark-adapted foveal sensitivity, foveal flicker sensitivity, slow recovery from glare and slower foveal electroretinogram implicit time as functional risk factors for the development of neovascular disease. Despite progress in this area, we emphasise the need for longitudinal studies designed in light of developments in disease classification and retinal imaging, which would ensure the correct classification of cases and controls, and provide increased understanding of the natural course and progression of the disease and further elucidate the structure-function relationships in this devastating disorder.

Logic feels so good-I like it! Evidence for intuitive detection of logicality in syllogistic reasoning

When people evaluate syllogisms, their judgments of validity are often biased by the believability of the conclusions of the problems. Thus, it has been suggested that syllogistic reasoning performance is based on an interplay between a conscious and effortful evaluation of logicality and an intuitive appreciation of the believability of the conclusions (e.g., Evans, Newstead, Allen, & Pollard, 1994). However, logic effects in syllogistic reasoning emerge even when participants are unlikely to carry out a full logical analysis of the problems (e.g., Shynkaruk & Thompson, 2006). There is also evidence that people can implicitly detect the conflict between their beliefs and the validity of the problems, even if they are unable to consciously produce a logical response (e.g., De Neys, Moyens, & Vansteenwegen, 2010). In 4 experiments we demonstrate that people intuitively detect the logicality of syllogisms, and this effect emerges independently of participants' conscious mindset and their cognitive capacity. This logic effect is also unrelated to the superficial structure of the problems. Additionally, we provide evidence that the logicality of the syllogisms is detected through slight changes in participants' affective states. In fact, subliminal affective priming had an effect on participants' subjective evaluations of the problems. Finally, when participants misattributed their emotional reactions to background music, this significantly reduced the logic effect.

Optical coherence tomography (OCT) for detection of macular oedema in patients with diabetic retinopathy

Background

Diabetic macular oedema (DMO) is a thickening of the central retina, or the macula, and is associated with long-term visual loss in people with diabetic retinopathy (DR). Clinically significant macular oedema (CSMO) is the most severe form of DMO. Almost 30 years ago, the Early Treatment Diabetic Retinopathy Study (ETDRS) found that CSMO, diagnosed by means of stereoscopic fundus photography, leads to moderate visual loss in one of four people within three years. It also showed that grid or focal laser photocoagulation to the macula halves this risk. Recently, intravitreal injection of antiangiogenic drugs has also been used to try to improve vision in people with macular oedema due to DR.Optical coherence tomography (OCT) is based on optical reflectivity and is able to image retinal thickness and structure producing cross-sectional and three-dimensional images of the central retina. It is widely used because it provides objective and quantitative assessment of macular oedema, unlike the subjectivity of fundus biomicroscopic assessment which is routinely used by ophthalmologists instead of photography. Optical coherence tomography is also used for quantitative follow-up of the effects of treatment of CSMO.

Objectives

To determine the diagnostic accuracy of OCT for detecting DMO and CSMO, defined according to ETDRS in 1985, in patients referred to ophthalmologists after DR is detected. In the update of this review we also aimed to assess whether OCT might be considered the new reference standard for detecting DMO.

Search methods

We searched the Cochrane Database of Systematic Reviews (CDSR), the Database of Abstracts of Reviews of Effects (DARE), the Health Technology Assessment Database (HTA) and the NHS Economic Evaluation Database (NHSEED) (The Cochrane Library 2013, Issue 5), Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid MEDLINE Daily, Ovid OLDMEDLINE (January 1946 to June 2013), EMBASE (January 1950 to June 2013), Web of Science Conference Proceedings Citation Index - Science (CPCI-S) (January 1990 to June 2013), BIOSIS Previews (January 1969 to June 2013), MEDION and the Aggressive Research Intelligence Facility database (ARIF). We did not use any date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 25 June 2013. We checked bibliographies of relevant studies for additional references.

Selection Criteria

We selected studies that assessed the diagnostic accuracy of any OCT model for detecting DMO or CSMO in patients with DR who were referred to eye clinics. Diabetic macular oedema and CSMO were diagnosed by means of fundus biomicroscopy by ophthalmologists or stereophotography by ophthalmologists or other trained personnel.

Data collection and analysis

Three authors independently extracted data on study characteristics and measures of accuracy. We assessed data using random-effects hierarchical sROC meta-analysis models.

Main results

We included 10 studies (830 participants, 1387 eyes), published between 1998 and 2012. Prevalence of CSMO was 19% to 65% (median 50%) in nine studies with CSMO as the target condition. Study quality was often unclear or at high risk of bias for QUADAS 2 items, specifically regarding study population selection and the exclusion of participants with poor quality images. Applicablity was unclear in all studies since professionals referring patients and results of prior testing were not reported. There was a specific 'unit of analysis' issue because both eyes of the majority of participants were included in the analyses as if they were independent.In nine studies providing data on CSMO (759 participants, 1303 eyes), pooled sensitivity was 0.78 (95% confidence interval (CI) 0.72 to 0.83) and specificity was 0.86 (95% CI 0.76 to 0.93). The median central retinal thickness cut-off we selected for data extraction was 250 µm (range 230 µm to 300 µm). Central CSMO was the target condition in all but two studies and thus our results cannot be applied to non-central CSMO.Data from three studies reporting accuracy for detection of DMO (180 participants, 343 eyes) were not pooled. Sensitivities and specificities were about 0.80 in two studies and were both 1.00 in the third study.Since this review was conceived, the role of OCT has changed and has become a key ingredient of decision-making at all levels of ophthalmic care in this field. Moreover, disagreements between OCT and fundus examination are informative, especially false positives which are referred to as subclinical DMO and are at higher risk of developing clinical CSMO.

Authors' conclusions

Using retinal thickness thresholds lower than 300 µm and ophthalmologist's fundus assessment as reference standard, central retinal thickness measured with OCT was not sufficiently accurate to diagnose the central type of CSMO in patients with DR referred to retina clinics. However, at least OCT false positives are generally cases of subclinical DMO that cannot be detected clinically but still suffer from increased risk of disease progression. Therefore, the increasing availability of OCT devices, together with their precision and the ability to inform on retinal layer structure, now make OCT widely recognised as the new reference standard for assessment of DMO, even in some screening settings. Thus, this review will not be updated further.

Data Cleaning and Outlier Removal: Application in Human Skin Detection

An outlier removal based data cleaning technique is proposed to
clean manually pre-segmented human skin data in colour images.
The 3-dimensional colour data is projected onto three 2-dimensional
planes, from which outliers are removed. The cleaned 2 dimensional
data projections are merged to yield a 3D clean RGB data. This data
is finally used to build a look up table and a single Gaussian classifier
for the purpose of human skin detection in colour images.

Rapid, objective detection of cataract-induced blur using a bull's eye photodetector.

PURPOSE: To determine whether optical aberrations caused by cataract can be detected and quantified objectively using a newly described focus detection system (FDS). SETTING: The Wilmer Opthalmological Institute, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. METHODS: The FDS uses a bull's eye photodetector to measure the double-pass blur produced from a point source of light. To determine the range and level of focus, signals are measured with a series of trial lenses in the light path selected to span the point of best focus to generate focus curves. The best corrected visual acuity (BCVA), refractive error, lens photograph grades, and FDS signals were obtained in 18 patients scheduled to have cataract surgery. The tests were repeated 6 weeks after surgery. RESULTS: The mean FDS outcome measures improved after cataract surgery, with increased peak height (P=.001) and decreased peak width (P=.001). Improvement in signal strength (integral of signal within +/-1.5 diopters of the point of best focus) strongly correlated with improvement in peak height (R(2)=.88, P<.0001) and photographic cataract grade (R(2)=.72, P<.0001). The mean BCVA improved from 20/50 to 20/26 (P<.0001). The improvement in BCVA correlated more closely with FDS signal strength (R(2)=.44, P=.001) than with cataract grade (R(2)=.25, P=.06). CONCLUSIONS: Improvement in FDS outcome measures correlated with cataract severity and improvement in visual acuity. This objective approach may be useful in long-term studies of cataract progression.

Reducing the visual burden of glaucoma in Asia: what we know and what we need to know.

Despite great progress in elucidating risk factors and effective treatments for eye disease in the last decades, blindness prevalence in the developing and developed world is either static or rising. A research agenda is needed to develop and test specific strategies to reduce the burden of blindness from glaucoma and other common eye diseases. Current knowledge about open and closed-angle glaucoma is reviewed and a strategy to reduce glaucoma blindness in Asia is suggested. A critical component of this strategy is enhanced training in the detection of narrow angles and optic nerve damage by direct examination. Specific research topics that could inform such a strategy are outlined.

Multi-scale keypoints in V1 and face detection

End-stopped cells in cortical area V1, which combine out- puts of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representa- tion, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Al- though a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.

Multi-scale cortical keypoint representation for attention and object detection

Keypoints (junctions) provide important information for focus-of-attention (FoA) and object categorization/recognition. In this paper we analyze the multi-scale keypoint representation, obtained by applying a linear and quasi-continuous scaling to an optimized model of cortical end-stopped cells, in order to study its importance and possibilities for developing a visual, cortical architecture.We show that keypoints, especially those which are stable over larger scale intervals, can provide a hierarchically structured saliency map for FoA and object recognition. In addition, the application of non-classical receptive field inhibition to keypoint detection allows to distinguish contour keypoints from texture (surface) keypoints.

Multi-scale keypoint hierarchy for Focus-of-Attention and object detection

Hypercolumns in area V1 contain frequency- and orientation-selective simple and complex cells for line (bar) and edge coding, plus end-stopped cells for key- point (vertex) detection. A single-scale (single-frequency) mathematical model of single and double end-stopped cells on the basis of Gabor filter responses was developed by Heitger et al. (1992 Vision Research 32 963-981). We developed an improved model by stabilising keypoint detection over neighbouring micro- scales.

Artistic rendering of the visual cortex

In this paper we explain the processing in the first layers of the visual cortex by simple, complex and endstopped cells, plus grouping cells for line, edge, keypoint and saliency detection. Three visualisations are presented: (a) an integrated scheme that shows activities of simple, complex and end-stopped cells, (b) artistic combinations of selected activity maps that give an impression of global image structure and/or local detail, and (c) NPR on the basis of a 2D brightness model. The cortical image representations offer many possibilities for non-photorealistic rendering.

Visual cortex frontend: integrating lines, edges, keypoints and disparaty

We present a 3D representation that is based on the pro- cessing in the visual cortex by simple, complex and end-stopped cells. We improved multiscale methods for line/edge and keypoint detection, including a method for obtaining vertex structure (i.e. T, L, K etc). We also describe a new disparity model. The latter allows to attribute depth to detected lines, edges and keypoints, i.e., the integration results in a 3D \wire-frame" representation suitable for object recognition.