Eye-tracking has been extensively used to quantify audience preferences in the context of marketing and advertising research, primarily in methodologies involving static images or stimuli . However, these methodologies do not generalize to narrative-based video stimuli where a specific storyline is meant to be communicated to the audience. In this paper, a novel metric based on eye-gaze dispersion (both within and across viewings) that quantifies the impact of narrative-based video stimuli to the preferences of large audiences is presented. The metric is validated in predicting the performance of video advertisements aired during the 2014 Super Bowl final. In particular, the metric is shown to explain 70% of the variance in likeability scores of the 2014 Super Bowl ads as measured by the USA TODAY Ad-Meter. In addition, by comparing the proposed metric with Heart Rate Variability (HRV) indices, we have associated the metric with biological processes relating to attention allocation. The underlying idea behind the proposed metric suggests a shift in perspective when it comes to evaluating narrative-based video stimuli. In particular, it suggests that audience preferences on video are modulated by the level of viewers lack of attention allocation. The proposed metric can be calculated on any narrative-based video stimuli , and thus has the potential to facilitate the use of such stimuli in several contexts: prediction of audience preferences of movies, quantitative assessment of entertainment pieces, prediction of the impact of movie trailers, identification of group, and individual differences in the study of attention-deficit disorders, and the study of desensitization to media violence. The evaluation of video advertising aims to characterize the profile of a video advertisement and predict its potential impact on the consumer in order to select the best advertisement or advertisement storyline before it is aired. Recently, there has been a growing interest in using methods from neuroscience and experimental psychology in order to identify metrics that could explain and predict the effectiveness of video advertising  through a storyline or script which aims to take the viewer on a narrative journey in the hope that the viewer will be able to associate the message with the brand. In storyline-based video advertising, no single frame or element can be explicitly identified as being of interest, rather the entire sequence of frames work together to drive the communication. This property of the narrative- or storyline-based video renders the application of AOI-based methodologies in this context problematic.More recently, alternative methods for the analysis of eye-movements recorded during video viewing Smith,  have beeAn alternative approach to characterizing video content performance has been the use of neural activity, typically measured through electroencephalography (EEG) or functional magnetic resonance imaging (fMRI)-derived blood-oxygenation-level-dependent (BOLD) signals. Indeed, a number of methods have been proposed for deriving useful components from EEG signals which can serve as metrics for evaluating static or dynamic content. These methods typically rely on identifying spatial, temporal, or spectral projections of the raw neural signal , which can be robustly measured by any off-the-shelf eye-tracking system; hence, the metric calculation does not require any specialized eye-tracking measures such as saccades, micro-saccades, or pupil dilation, which are only available on high-end (and expensive) eye-tracking systems. These features make the proposed metric easy to calculate, affordable, and scalable. Moreover, we explore the relation between the proposed metric and the heart-rate variability indices. Finally, to evaluate the predictive power of the resulting metric, we report results on the post-air performance of video advertisements telecasted during the 2014 Super Bowl.A total of 16 participants  were recruited with self-reported normal or corrected-to-normal vision and participated in the study. All participants were fluent in the English language. The minimum, median, and maximum ages of the participants were 19, 22, and 24, respectively. Participants were compensated for their participation.Each participant was seated in a comfortable chair and briefed on the objective of the study. In particular, participants were informed that they would be shown a set of video advertisement and movie trailers and that they would have to report their opinion of each video using an on-screen questionnaire. Following a short preparation and calibration session (see Section 2.3), each participant was presented with 13 video advertisements . Following each advertisement viewing, a questionnaire would pop up on the screen asking the participant to report the degree to which they liked the advertisement, and whether they would consider sharing a link of the video on their Facebook account. Following the display of all 13 video advertisement, the participants were showen 5 movie trailers of current movies. Subsequently, the participants were shown all 13 video advertisements for a second time. For stimulus presentation, we used the open source software OpenSesame  which employed a BioSemi Active-two system  at a sampling rate of 512 Hz. Subjects were fitted with a standard 32-electrode cap following the international 10/20 system. The preparation procedure took about 10 min during which all electrodes were placed and the impedance of all sensors was kept below 20 eye-gaze Divergence Index (iGDI) metric as described in Section 2.4. The analysis was performed using a custom Matlab code (Mathworks Inc.)  signal sensors attached to the left ear lobe. Relevant research has shown that the peaks of the PPG signal correspond to the R-peaks (heartbeats) obtained using electrocardiographic (ECG) equipment, suggesting that the PPG is a valid measure of cardiac activity including HRV measures in both healthy people and people suffering from cardiovascular diseases  ∈ ℝ2 and w(n) ∈ ℝ2 as the nth columns of matrices V and W, respectively, each representing a gaze position, and let vi(n), wi(n), i ∈ {1, 2} correspond to the ith elements of vectors v(n) and w(n), respectively. The first element corresponds to the x-coordinate of the gaze point, while the second element is the y-coordinate of the gaze point.Denote V and W. Formally,We define the dispersion score between the two renditions as the average pairwise Euclidean distance between V(1), V(2), …, Vs)( where Vs), W(2), …, Ws)( where Ws) using Equation (1). We refer to this score as the between-viewings dispersion score. Note that the number of columns in V and W are now S × N. Also note that N is selected to correspond to a small time window of a video segment (for our study we use windows of 250 ms). We compute the dispersion scores for the entire video in a time-resolved fashion by employing a sliding window with 250 ms duration and a shift of the window occurring every 50 ms (80% overlap between successive windows).We calculate the dispersion between these two renditions on the matrices ij = 1 iff i ≠ j. We note that the within-viewings dispersion score depends on gaze paths of a single video viewing. For the purposes of this study, we calculate the within-viewings dispersion scores for the first, and second viewings of the video .Similarly, we define the within-viewings dispersion scores as follows:The use of short video segments in the calculation of the dispersion scores is motivated by the observation that during a segment participants are exposed to exactly the same frame sequence that aims to guide their attention to a particular storyline, and thus a similar gaze path. The degree to which the video sequence achieves this objective is reflected by the dispersion score. Scenes for which the viewers focus their attention in nearby locations in the video sequence should have a smaller dispersion score, while scenes that do not manage to guide viewers attention are expected to have a larger dispersion score. We hypothesize that the scenes with extreme dispersion scores carry information about the inability of the video to keep users engaged, which in turn reflects in the post-air performance of the video. In the following paragraph we present to the method for categorizing such extreme scores.V and W across different (random) time windows of the same video and second by calculating its dispersion score using Equation (1). The mean value of the fitted distribution Dnull serves as a threshold for classifying the windows. Formally, a window is labeled as divergent based on the following decision rule:F) = 1 denotes a window which is to be labeled as divergent and F) = 0 denotes a window which is to be labeled as non-divergent. Note that the decision rule (Equation 5) is applicable for both with-viewing and between-viewings dispersion scores .Here we provide the details of classifying dispersion scores for each window as being either divergent  or non-divergent. The underlying principle here is to model the probability distribution of the dispersion scores under a null hypothesis that the video frames do not guide viewers attention according to the storyline or in any systematic pattern. To estimate the probability under null hypothesis, we use Monte-Carlo sampling to generate a histogram of the distribution and use it to fit a normal distribution. Each sample is drawn by first randomizing the matrices iGDI metric for a particular video is then defined as the fraction of divergent windows. Formally, let d = ⊤ be a vector with the dispersion scores (either within-viewings or between-viewing) at different consecutive windows spanning the length of the video and denote f = ⊤ as the binary vector categorizing the windows as divergent and non-divergent, then the iGDI is defined asThe iGDI metric for both between- and within-viewings. In reporting the results, we reserve the symbol iGDI without any subscript to refer to the between-viewings iGDI score, and use the notation iGDIv1 and iGDIv2 to refer to the within-viewings iGDI score, for the first and second video viewings, respectively.For our analysis, we calculate the iGDI score. Such information is useful in identifying individual scenes in the advertisement that do not perform at par and taking corrective action  to improve the videos overall iGDI score. In addition, the visual inspection of attention maps during those scenes can provide further information on which specific elements of the scene most likely contribute to the large dispersion scores and thus provide insights into taking corrective measures before airing the advertisement. Moreover, we consider the level of agreement between the two within-viewings models in identifying similar frames as being distracting. In particular, we compare the number of windows during each video for which the two models agree in identifying a scene as being divergent.The model provides information about which scenes contribute either positively or negatively to the iGDI metric to predict post-air audience preferences of each video advertisement, we fitted a univariate regression model, where the iGDI metric serves as the independent variable and the Ad-Meter score as the dependent variable. Formally, the model is defined as:yadmenter denotes the predicted Ad-Meter score, iGDI is the proposed metric, and b0, b1 denote the intercept and slope parameters of the regression model. To train the model, we first calculated the dispersion score for each video at multiple time windows using the Equations (1) or (4). The time interval of each window was 250 ms, and subsequent windows overlapped by 200 ms . The sequence of all the time windows spans the entire duration of the video advertisements. Second, each window was classified as being either divergent or non-divergent using the decision rule of Equation (5). Finally, the iGDI metric for each video presented was calculated using Equation (6). The regression model was fitted using least-squares criterion. A separate prediction model was fitted for the iGDI calculated on the between-viewings dispersion scores and for the iGDI metrics calculated on the within-viewings dispersion scores. Moreover, in the case of within-viewings dispersion scores calculated using Equations  the model was trained on two separate datasets: one dataset using the gaze data recorded during the first viewing of the video and another one using gaze data recorded during the second viewing of the video.To evaluate the ability of the proposed N times, where the iGDI scores of (N–1) videos were used to fit the model, and the one excluded from the training procedure was used as a test case to calculate the predicted score. The predicted values for the N videos were then compared to the true Ad-Meter scores. Performance of the model was reported in terms of the variance explained and Mean squared Error (MSE) on both the fitted model and the predictive model.To obtain an estimate of the generalizability of the regression model on new videos, we employed a leave-one-out cross validation procedure. In particular, the model was fitted/trained iGDI metric measuring the divergence of eye-gaze patterns across subjects and HRV indices that are sensitive to attention allocation levels. The selection of HRV was motivated by its application as a marker of cardiac function which is modulated by activity changes in the Parasympathetic (PNS) and sympathetic (SNS) divisions of the Autonomous Nervous System (ANS). In particular, activity in the PNS division of the ANS  decreases the heart rate, while activity in the SNS division contributes to the increase in the heart rate. In essence, HRV refers to the degree to which the time interval between successive heart beats fluctuates as a result of the influences of the SNS and PNS. This is of particular importance as previous relevant research has reported cardiac deceleration, and hence increase in HRV indices relating to PNS, with increased attention allocation both in adults and infants  = 0.38, p > 0.05, we combined these data in the following analysis. In addition, a set of Shapiro−Wilktests(W) were conducted to test whether dependent variables deviated from normality. The examination of the normality of the distribution of cardiac RMSSD data  and of the iGDI metric  suggested that the obtained data was normally distributed. Therefore, a Pearson product-moment correlation coefficient was computed to assess the relationship between the % change in RMSSD and the eye-tracking metric measuring the divergence of eye-gaze patterns across subjects.To investigate the relation between the proposed metric and the level of attention allocation of participants during video viewing, we used the RMSSD metric calculated from the HRV of the group of participants viewing each video advertisement. As there was no significant difference in the RMSSD between the first and second viewing, iGDI explained 70% of the variance  = 23.4, p < 0.0006). Figure iGDI and the Ad-Meter scores; as the Ad-Meter score decreases, the iGDI increases, and vice versa. This negative correlation is as was expected because the Ad-Meter measures a positive attribute of the video  whereas the iGDI was designed to capture a negative attribute of the video .Results of the between-viewings regression indicate that the RMSE = 0.77) and Mean Absolute Percentage Error (MAPE = 10%). In addition, the cross validation coefficients across models show little variance across the different trained models (std(β1) = 1.1, std(β0) = 0.20) suggesting the stability of the regression-line parameters (slope and intercept). Moreover, the cross-validation coefficient is R2cv = 0.53 and the cross-validation shrinkage is Shrinkage = 0.17.Results on the generalizability of the between-viewings regression model show a small Root Mean Square Error  = 11.6708, p < 0.0066), while iGDIv2 explained 48% of the variance  = 9.3339, p < 0.0121). Figure iGDI and the Ad-Meter scores. We further evaluated the predictive power of these two models on novel data using the leave-one-out cross-validation procedure outlined above. Both models show a small prediction error with iGDIv1: RMSE = 0.82, MAPE = 13%, iGDIv2: RMSE = 0.94, MAPE = 14%. The modulation of the iGDI metric of each video across the two viewings are shown in Figure bottom row).Results of the within-viewings regression model indicate that the iGDI score of the video. It is interesting to note that the videos with the lowest Ad-Meter score  show extended consecutive time points of distracting frames, which correspond to the frames that the video creator should visually inspect for improvement. Moreover, results on comparing the agreement between the two within-viewings models show that the classification decision of the two models agree in 88% of the time-windows considered .Figure iGDI metric, r(22) = −0.33, p < 0.05.The Pearson product-moment correlation coefficient was computed to assess the relationship between the RMSSD % change and the eye-tracking metric measuring the divergence of eye-gaze patterns across subjects. Results show a moderate negative relationship between RMSSD % change and the In this paper we have presented a novel metric to quantify the degree of divergence of viewers' attention, measured by the divergence of eye-gaze patterns across subjects, when presented with a narrative- or storyline-based video, and have shown that the metric carries predictive information about the post-air audience preferences about the video. The proposed metric, which is calculated from eye-tracking data of a small sample of individuals, is shown to greatly predict the preferences of the larger audience viewing the video during a telecast. To evaluate the predictive power of the proposed metric, we used advertisements aired during the 2014 Super Bowl final. For post-air performance score, we used the audience preferences measured by the USA TODAY Ad-Meter Score. Two distinct versions of the metric have been proposed and evaluated: one using gaze data between two viewings of a video (between-viewings metric) and one using gaze data within a single viewing (within-viewings metric), as described in the Materials and Methods Section. The results show that both instantiations greatly predict the post-air performance of video advertisements; however, the metric calculated with the data between the two viewings explains more of the variance in the dependent variable and with smaller generalization error. This suggests that the ability of the video to not lose viewers attention after multiple repetitions encodes additional information for predicting a videos post-air performance. Indeed, by investigating the within-viewings metric for the first and second view, we have shown the modulations of the metric calculated within the first and second viewings separately. Moreover, we have shown that the proposed metric provides frame-by-frame details of those time windows of the video that contribute positively (or negatively) to the predicted performance. One can pinpoint those scenes of the video which need to be edited to improve its post-air performance and thus our metric is a powerful tool for optimizing video performance before airing them. Finally, we investigated the relation between the proposed metric and the level of attention allocation of participants during viewing. The results show a moderate negative relationship between Heart Rate Variability index (RMSSD) and the proposed metric. These results suggest that increases in RMSSD (which likely indicate cardiac deceleration) are related to decreases in the divergence of eye-gaze patterns across subjects as measured by the proposed metric.Our approach differs from traditional eye-tracking methodologies which require specific AOI to be explicitly defined for the key frames of the video. A key advantage of the proposed metric is that it is calculated using only the gaze-coordinate data obtained from off-the-shelf eye-tracking systems and does not require the defining any AOI. This is of particular importance in the study of narrative-based videos because for this video-genre no single frame or element can be explicitly identified as being of interest, but rather the entire sequence of frames work together to drive the communication. Moreover, to the best of our knowledge, this is the first time that an eye-tracking based metric has been shown to carry predictive information that can directly link the metric to the post-air preferences of a large population.Our findings show the highly predictive power of our proposed metric which is comparable to the state-of-the-art methods which use high-end and expensive neuroimaging modalities such as fMRI and EEG. In particular, our metric achieves prediction accuracy equivalent to a recently published method that uses EEG and fMRI based ISC . Current approaches, whether relying on neuroimaging or self-report measures, focus on positive attributes of the video stimuli such as scenes that cause maximal levels of engagement, reduce workload, or have maximal memory recall. Our findings suggest that negative attributes of the video  are at least equally important in defining the impact of the narrative videos. One may interpret these results as suggesting that the impact of the viewers preferences interplay between engaging scenes and scenes of the video stimuli associated with divergence of attention. On the one hand, engaging scenes offer the opportunity to remember specific elements of the stimuli. These elements can serve as iconic-scenes to trigger messages or brand associations. Moreover, the more engaging a scene is, the more likely the viewer will follow the videos narrative. On the other hand, scenes with extreme attention divergence captured via the proposed metric act as interest-landmines. The more the scenes in a video that allow the viewer attention to diverge from a common attention path, the more opportunities for the viewer to disconnect from the narrative and the message, and lose interest.Given the evidence showing that both engagement (captured by ISC of neuroimaging data) and attention divergence (captured by our proposed metric via eye-tracking data) carry predictive information about the videos post-air performance, and the realization that the two metrics could carry complementary information, we hypothesize that combining the two metrics would result in even more accurate predictive power. Moreover, we hypothesize that combined metrics will carry predictive information of different video types. In future work, we plan to investigate and characterize the predictive power of combining ISC based metrics from EEG and the proposed metric on various video types including movies and other narrative-based videos.Finally, the proposed metric can be calculated on any narrative-based video stimuli , and thus has the potential to facilitate the use of such stimuli in several contexts. In particular, we envision that the proposed metric can be useful in the field of cognitive film theory Smith,  by inforThe corresponding author serves as Chief Technology Officer at R.K.I Leaders Ltd. A non-provisional patent applications was submitted under the US patent office which in part relates to the current work. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Reductions in underage drinking will only come about from changes in the social and cultural environment. Despite decades of messages discouraging parental supply, parents perceive social norms supportive of allowing children to consume alcohol in ‘safe’ environments.n = 27; 70 % female) and eight with adolescents . Participants were recruited using local media. Groups explored knowledge and attitudes and around alcohol consumption by, and parental supply of alcohol to, underage teenagers; and discussed materials from previous campaigns targeting adolescents and parents.Twelve focus groups conducted in a regional community in NSW, Australia; four with parents of teenagers  as bad parents, and those who ‘teach responsible drinking’ (themselves) as good people. Both groups expressed a preference for high-fear, victim-blaming messages that targeted ‘those people’ whose behaviours are problematic.In developing and testing interventions to address underage drinking, it is essential to ensure the target audience perceive themselves to be the target audience. If we do not have a shared understanding of underage ‘drinking’ and parental ‘provision’, such messages will continue to be perceived by parents who are trying to do the ‘right’ thing as targeting a different behaviour and tacitly supporting their decision to provide their children with alcohol. In Australia the national guidelines state that for those aged less than 18 years of age, not drinking is the safest option , suicideThe influences on adolescent drinking behaviour are complex. There is strong evidence for the role of alcohol advertising and marketing , 9, persmain source of alcohol  didn’t but other kids did” (P1). There was also a recognition that the child’s peer group was an important influence on their drinking behaviour,I think there are lots that aren’t doing it – that aren’t drinking…It depends on your peer group I think (P1).There was a general consensus among the parent participants that local teenagers  are drinking, They’re maybe big drinkers themselves. I just think it’s that thing, if it’s in your environment, where it’s the norm, where every night at dinner there’s lots of alcohol being consumed and every BBQ adults are getting tiddly it’s an environment where children are used to it being normal, whereas we – they see us just have one glass of wine, it’s very different to seeing a parent getting drunk (P1)They’re allowing parties to go on at their place at 16 and knowing there are kids out there drinking in their garden and things like that…Some parents just think it’s normal because it’s probably what they did (P4)Parent groups also expressed the view that, whilst peer pressure and other environmental factors influence adolescent drinking behaviour, parents themselves are also a significant influence either by role modelling their own behaviour or by the degree of parental rules and boundaries. In this context there was a clear distinction made between parents who drink ‘responsibly’ and those who drink to excess.anniversary or romantic so I don’t think that they would let their kids drink because they look like nice people (A1)[do not provide] …. If you look at the ‘don’t’ pile, a lot of them look angry or less happy (A2)[do not provide] I think they look like the kind of relaxed person that doesn’t care what their kids do (A1)[do provide] These people look like parents who just leave their children at home and go out to find drugs (A2)[do provide] At a theoretical level the teenagers, and particularly the younger respondents, expressed the view that ‘good’ parents don’t let their children drink. For example, the 12–14-year-olds allocated the photos of the ‘nice’ and ‘happy’ parents to the ‘do not provide alcohol’ pile and the ‘angry’ and ‘unhappy’ parents to the ‘do provide’ alcohol pile.Offensive - A few friends at school and stuff are allowed to drink and then if you tell the parent that you want to drink and they say ‘oh no, you’re too young’ you feel insulted your parents are saying you’re too young (A4)[do not provide] If we put awesome over there then why is exciting and amazing on this…[do not provide] I: Parents can still be cool if they don’t let you go outP: They just might be against it (A4)P: Neglectful….If the person doesn’t care about their kid they’re neglecting their kid. I think they don’t care if the kids drinking (A4)[do provide] They know their kid is going to go out and drink whether they say they can or not so they may as well know what they’re doing, know what they’re drinking rather than ‘behind my back they’re going to do this, I’d like to know at least’ (A5)[do provide] Perceptions among the older teenagers were more varied and more nuanced. Some thought the supply of alcohol to adolescent children was ‘bad’ parenting (as was the case with the younger group), whereas others saw it as harm minimisation. These respondents also expressed mixed views of parents who do not provide alcohol. Some viewed this as lack of trust or respect for their children whereas others viewed parental prohibition more positively.do supply alcohol to their teenage children. While some perceived this as driven by misperceptions about harm minimisation, the majority attributed it to poor parenting.But I think most parents, if they are letting their kids [drink], maybe there is that thinking that it is a better way to approach it. I don’t think most parents would choose to give their children alcohol knowing it has a negative effect.Unless they have a problem themselves (P1)Do you know what? It’s because they just don’t want to keep hounding the children. They’ve just given up (P2)There are a lot of different socio economic areas in Kxxx and that’s where sometimes you tend to find – different families…the kids are often left to their own devices a bit more (P3)Among parents, there was a clear perception that supplying alcohol to teenagers was inappropriate. Related to this was the clear perception that ‘other parents’ The responses from teenagers suggested their understanding of the notion of ‘supply’ differed from the strict legal definition My mum thinks a glass of wine at a family dinner for me, mixed with something else is ok but only at a family dinner which we don’t have often (A2)But it was only a tiny bit. They wouldn’t let me have a full on drink, like a full on beer but my sister, she’s 16, she likes Cruisers already (A1)At a personal level, the teenagers in the 12–14 year old groups reported that their parents don’t let them drink. A minority described absolute prohibition, generally related to their parents’ professional or personal experience of people with alcohol problems. However, the majority of them described their parents allowing them or their siblings to ‘taste’ or ‘sip’ alcohol. Some described being allowed tastes or sips of alcohol under direct parental supervision as being ‘taught how to drink’, even expressing the view that these experiences do not count as ‘drinking’. None expressed the view that this practice constituted ‘supplying alcohol’ to them.…one beer, my dad would accept, not too much more (A6)I know a friend whose mum is against it but won’t stop it from happening. She’s ‘don’t do it, don’t do it but once it happens she’s like huh’ [i.e. dismissive] (A4)A similarly nuanced view of what constitutes ‘drinking’ (and thus ‘supply’) was evident in the older (15–17yo) groups, although in this case distinction was made between ‘responsible’ or light drinking and ‘risky’ drinking. The majority believed that their parents would (or do) allow them to drink (responsibly) but would not allow them to drink where the goal or result of the drinking was intoxication. Some expressed the view that being allowed to drink (responsibly) is a developmental or trust issue and others that it is a concession to the inevitability of underage drinking.It depends who you’re with, where you’re going and how you’re getting homeHow you’re getting homeI reckon where you’re going for startersYeah…going to a party with just – locally – with a groupHow many people too, that’s a factorIt’s a party that your friend at school is holding and you know everyone there – but if you go to a party at Axxx and don’t know anyone, it’s just an open house, then they’re obviously going to get –Even if you can just catch a train home, they’ll be like ‘yeah – no’(A4)It depends, on what….if it’s at a party that one of your mates is having, that all the people you know then it might be all right. But if it’s…stupid people… places, like Wxxx and stuff…. (A5)There was also a clear perception that parental provision of alcohol, within their own families, was situation-dependent. Respondents described parents making decisions based on a considered risk assessment rather than applying a single rule to every situation.No I don’t know anyoneI don’t, but I don’t think that means it doesn’t happenI just think I probably have similar philosophies as people who are close to meLike minded(P1)I don’t know any that let under 18s drinkNoNot a single one(P3)The majority of parents were adamant that they did not, and would not, supply alcohol to their underage teenagers. For many this was associated with being part of social networks that held similar attitudes. This was particularly the case when discussing younger teenagers .…but I’ve let X try my wine probably since he was about 11 – a sip. Because I’d rather him know what a good wine tastes like and I say to him what can you taste and smell, think about it like proper wine tasting. Because I’d rather him have an appreciation for a good wine …. (P2)…but I would let my child at 17 have half a glass on a special occasion. I wouldn’t think I’ve done the wrong thing (P4)That’s the only thing but when he had that even 2 years ago, when he was 12, ‘can I have a sip’ I wouldn’t have let him…just this age [, he’s taller than me, he said ‘can I’ and I went if you want a taste that’s fine but you won’t like it. (P1)this age , he’s taIt became clear as the discussion progressed that the nuanced perception of what constitutes ‘drinking’ and ‘supplying alcohol’ expressed in the adolescent groups was shared by the parents. That is, while the majority were adamant that they would not supply alcohol to their underage teenagers (and that those who did were either unwise or neglectful), many referred to giving their children ‘tastes’ of alcohol or ‘teaching’ them to drink responsibly by introducing them to alcohol in a ‘safe’ environment.The perception that this behaviour was appropriate – and even desirable – clearly differentiated them from the ‘bad’ parents who encourage or allow  underage drinking in their children, and parents who ‘supply’ their children with alcohol.The perception that ‘underage drinking’ did not include the drinking these parents facilitated among their own children enabled them to understand ‘underage drinking’ and parental ‘supply’ of alcohol as problems only for ‘other’ children in ‘other’ families outside their own social circle. This idea was articulated very clearly in the parents’ responses to the sample underage drinking campaigns.I think it relates back to what we were saying before about those ads on TV where there’s the girl with her pants down and spewing in the gutter and you go ‘oh, I don’t want that to be my child’ and these ones…. I like those (P1)With the one with the boy – I’d probably have a bit more vomit downSomething running out of his earBlood somewhereA little bit of blood wouldn’t go astrayIs he in prison there?YeahThere are no barsPut a couple of bars or something (P2)The one that scared the living daylights out of you and put the blame on the mother (P2)While we provided a wide range of examples of different messages and approaches , many of the parents were attracted to the high-fear graphic advertising. It was these campaigns they described as being the most impactful and effective for the ‘target audience’. However, this group of parents clearly differentiated themselves and their families from ‘the target audience’, providing a number of suggestions as to how these images could be made more graphic and thus, in their opinion, more effective amongst parents who, unlike themselves, supply alcohol to their children.This guy looks like he’s about to kill himselfYeahI think this one’s the best (A1)I reckon its good having a colourful thing like that or something really serious, like someone throwing up, something really bad – so people see it and go ‘oh crap’ I don’t want that to happen. (A2)And I would put a picture like that, hurt, or beingReally vividYeah, like what x said, with death. (A4)The same response was evident in the adolescent groups, with the participants offering suggestions for ways that the messages could be made ‘more effective’ for ‘those kids’ who, unlike themselves or their friends, engage in  underage drinking. Their suggestions also consisted of making the images more graphic.Last year, at Carols by Candlelight a guy in your year (pointing to other participant) he got drunk that much he peed himself heaps (A2)When teenagers drink they become aggressive and…you know the town hall in Gxxxx?....The other week there was a stabbing at the town hall, it was in the middle of the night. I think a cleaner went past and there was a group of drunk teenagers and they stabbed an adult, like an older person…Yeah. They had no reason to do it; they just came out of a party and stabbed him (A1)You wouldn’t be worried then but there were these people and they were drinking on New Year’s Eve and the fireworks went off and they were drinking and the fireworks finish at 9 so they decided to go to Sxxx Beach and they went to Sxxx Beach and stayed there and then they went home. And they woke up the next morning and realised one of them wasn’t there and then they went looking everywhere and they found him passed out, and they’d left him there and they didn’t even realise (A4)There was a party in Bxxxx and a girl got stabbed in the neck when I was there and it was meant to be just a normal party and she got stabbed in the neck. Yeah, someone as a joke was ‘oh yeah, go to a party in Bxxxx, bring a knife’ as a joke and it fell out of his pocket and these girls had a fight. I saw them have a fight and then they walked away – some chick just picked it up and before you knew it X was just on the ground. And then it was just crazy. And then they were all punching the police cars. Everyone was violent and drunk (A4)However, it is important to note that many adolescents recounted stories of events that they had witnessed, or that they had heard about from their peers, that were more shocking than any posters we could have shown them. These recalled outcomes of underage drinking ranged from loss of bladder control to public stabbings. They also reported that these experiences had not deterred them from drinking alcohol.The Theory of Planned Behaviour (TPB) posits that the predictors of behavioural intention are attitudes, subjective norms, and perceived behavioural control , 42. In do provide alcohol to their underage children. Consistent with previous research [However, it is clear from the results of this study and from existing national data , that maresearch , 53, 54,Our participants wholeheartedly agreed with the messages (they thought) we and ‘the government’ were communicating – that supplying alcohol to teenagers is inappropriate. They interpreted ‘supply’ to refer to the provision of quantities of alcohol for unsupervised drinking, such as for consumption at parties, and clearly distanced themselves from people who would engage in this behaviour. The homogeneity of the responses was noteworthy, with all of the parents communicating that they would not ‘supply’ alcohol and almost all providing small amounts or tastes of alcohol in specific contexts. It is possible – given that this behaviour is associated with moral censure and ‘bad’ parenting – that our recruitment strategy did not attract parents who provide larger amounts of alcohol to their children and/or that some of the participants do indeed do so but were unwilling to state this in the group context.The provision of alcohol to children and adolescents can broadly be described as three behaviours: allowing children to sip or taste alcohol; allowing them to have a drink of alcohol at home; and supplying them with alcohol to take to a party. While each of the behaviours may be potentially harmful, the degree of harm and the consistency of research evidence for harm (or benefit) vary, as do parental and community attitudes. The findings of the present study are consistent with previous evidence that parents see a clear distinction between ‘sipping’ and ‘drinking’; for example, an earlier Australian study which found that parents reported having strict rules prohibiting their children from drinking but allowed them to ‘sip’ or ‘taste’ alcohol . ParentsIn turn, many of the (older) adolescents in our focus groups perceive that their parents condone or even encourage them to consume alcohol prior to reaching 18 years of age and, like their parents, do not perceive that underage drinking campaigns are targeted at people like them. It appears these children had learned from their parents that supplying alcohol does not include allowing children to taste or sip alcoholic drinks at home and that underage drinking does not include drinking that takes place in the presence, or with the permission, of parents.The findings of this study have important implications for the development of communication materials and social marketing campaigns targeting underage drinking, and particularly parental supply. It is essential to ensure that the target audience perceive themselves to be the target audience, and are not in fact commenting on the effectiveness of the message for ‘other’ people. The frame of reference for, and interpretation of terms by, target audiences can be fundamentally different to that of message developers. High-fear graphic images may test well with adolescents and parents because they genuinely believe these are the most effective strategy for ‘those’ children and ‘those’ parents. Following their recommendations is, then, likely to result in campaigns that the intended target audience will not perceive as relevant to them, or as addressing their own behaviour. These messages will not impact on their attitudes or behaviours because they believe they are already doing the ‘right’ thing.Thus, the first goal of such campaigns should be to ensure that the target audience perceives themselves to be the target audience; which can be achieved by utilising images and words that ‘nice’ parents with ‘good’ children identify with. For example, in our subsequent development of messages for this community, rather than utilising stock images that are reminiscent of previous high fear advertising campaigns we are taking photographs of clean-cut children in recognisable local environments. We are also using the words of our focus group participants in messages and taglines; for example, as one parent stated when she realised that her own children were also at risk of harm: “Bad things happen to good kids too”.The findings also have implications for addressing the entrenched behaviour of parental supply of alcohol to teenagers by their parents . Strategies to reduce parental supply, and thus underage drinking, need to increase parents’ awareness of the negative short- and long-term effects of any actions that condone underage drinking in any context, including providing small amounts of alcohol to children and teenagers in private homes.This study was conducted in one regional town in eastern Australia, and thus the results may not be generalizable to larger cities or other regions; future research in other locations could explore similarities and differences in perspectives. The use of written materials (in English) for recruitment limited our ability to attract participants who were not fluent in English, had lower levels of literacy, or were otherwise hard-to-reach groups. While the use of Facebook as an additional recruitment strategy broadened our reach, we note that all of our participants were fluent English speakers, with 93 % speaking English at home, and all were sufficiently literate to read the participant information sheet and provided informed consent. We utilised mixed-gender focus groups to explore these behaviours as young people typically drink in mixed-gender social groups and parents make decisions about supply with their spouses. However, the use of mixed-gender focus groups meant that we did not explore gender differences in the participants’ responses. Future research could usefully explore differences between male and female adolescents (and between mothers and fathers) in both perceptions of the risks associated with underage drinking and the most salient social marketing messages.Communication materials and social marketing campaigns targeting underage drinking and parental supply need to be carefully developed and tested with the target audiences to ensure that the message developers and the audience have the same understanding of the behaviour that is being targeted. It is also important to ensure that the target audiences recognise themselves as such, and do not interpret the messages as important and effective for ‘other’ people.LGA, local government area; NSW, New South Wales; SEIFA, socio economic index for area; TPB, theory of planned behaviour


An occipital emissary foramen has been traditionally described as a foramen present in the squamous part of the occipital bone at the occipital protuberance transmitting a vein that connects the confluence of sinuses with the occipital vein. The present study was done on 221 South Indian adult modern human skulls of unknown sex in the Department of Anatomy, St John's Medical College, Bangalore, India. The foramen was observed in 21/221 (9.50%) skulls, 6/21 (28.57%) to the right of, 10/21 (47.61%) to the left of, and 2/21 (9.52%) on the External Occipital Crest. It was seen more often near the posterior margin of foramen magnum rather than at the External Occipital Protuberance as has been traditionally described. A new finding is that bilateral foramina were observed in 3 skulls (14.28%). The incidence was higher than seen in other Indian population. Since it is present near the foramen magnum in most cases, knowledge of the number and position of the foramen is important for suboccipital craniotomies. The extensive connections of the veins with cranial venous sinuses may lead to intracranial infections and vice versa. Emissary veins traverse emissary foramina of the skull and connect venous sinuses to extracranial veins. Although they are valveless and blood may flow in both directions, flow is usually away from the brain. In ordinary usage, emissary foramina are restricted to mastoid, parietal, condyloid, and the foramen of Vesalius. An occipital emissary foramen has been traditionally described as a solitary foramen occasionally present in the squamous part of the occipital bone at the occipital protuberance . It tranThe study was done on 221 South Indian adult modern human skulls of unknown sex in the Department of Anatomy, St John's Medical College, Bangalore. The squamous part of occipital bone was studied for the presence of occipital emissary foramina.External Occipital Crest (EOC);External Occipital Protuberance (EOP); posterior border of Foramen Magnum (FM).The anatomical landmarks used in the study wereThe position and number of foramina were noted. The majority of the foramina were not seen on the EOP . Hence they were classified as present to the right, to the left, or on the EOC. A horizontal line was drawn midway between the EOP and the posterior margin of FM. The foramina were then classified as near the FM or near the EOP depending upon their distance from the midline .A foramen was said to be present only if it transmitted a copper wire of 0.5 mm diameter and went through the bone into the skull.Out of the 221 skulls studied, the foramen was observed in 21/221 (9.50%) skulls, 6/21 (28.57%) to the right of, 10/21 (47.61%) to the left of, and 2/21 (9.52%) on the EOC. Of these two cases, one single large foramen was observed on the left side of EOC near the EOP and the second foramen on the EOC near the FM. In 3 skulls (14.28%) foramina were observed on both sides of EOC and classified as bilateral. All were near the posterior margin of FM except the one case where a single large foramen was observed on the left side of EOC near the EOP.Emissary foramina are a byproduct of selection of bipedalism by extant humans . As an uIn our study the incidence of the foramen is 9.50%. This is higher if we compare it to other studies done in Indian population . In studIn our study, all but one foramen are seen near the FM. In only a single case, the foramen has been observed near the EOP , Figure.confluence of sinuses with the occipital vein if seen on the EOC near the EOP (1 case in the present study);marginal sinuses to the occipital vein if seen on either side of FM  ;occipital sinus to occipital vein if seen on the EOC near the FM (1 case in the present study), ;it may also receive the occipital diploic vein.Based on the location, the occipital emissary foramen connects:Previous studies have reported only solitary foramina. But in our study, we have found bilateral foramina in 3 cases, all near the foramen magnum . There iThe position of the foramen is more important than its incidence especially in suboccipital exposure as this procedure is one of the commonest neurological practices for the management of pathologies involving the posterior cranial fossa. These procedures always include the posterior edge of foramen magnum which is either removed en bloc or piecemeal and then replaced . In adults, the dura is tightly adherent to the skull and since it cannot be stripped easily at this location, operators have to pay particular attention to avoid tearing walls of occipital sinus. Due to the adherence of dura, during the procedure, intermittent massive bleeding from the bone or underlying dura or the sinus is expected and taken care of. But since the majority of the foramina lie near the foramen magnum , knowledge of their presence and position is essential to rule out unexpected bleeding that may occur when such findings are missed during initial investigations.


Despite its importance and potential impact in clinical trials, central reading continues to be an under-represented topic in the literature about inflammatory bowel disease (IBD) clinical trials. Although several IBD studies have incorporated central reading to date, none have fully detailed the specific methodology with which the reads were conducted. Here we outline key principles for designing an efficient central reading paradigm for an ulcerative colitis (UC) study that addresses regulatory, operational and clinical expectations. As a step towards standardization of read methodology for the growing number of multicenter phase 3 clinical trials in IBD, we have applied these principles to the design of an optimal read methodology that we call the ‘2 + 1 paradigm.’ The 2 + 1 paradigm involves the use of both site and central readers, validated scoring criteria and multiple measures for blinding readers, all of which contribute to reducing bias and generating a reliable endoscopic subscore that reflects endoscopic disease severity. The paradigm can be utilized while maintaining a practical workflow compatible with an operationally feasible clinical trial. The 2 + 1 paradigm represents a logical approach to endoscopic assessment in IBD clinical trials, one that should be considered attractive to prospective sponsors, contract research organizations, key opinion leaders and regulatory authorities and be ready for implementation and further evaluation. Central reading . Surprisof noise . The reaClinical Trial Imaging Endpoint Process Standards [‘As compared to site-based image interpretations in multicenter clinical trials, we anticipate that a centralized image interpretation process may provide more verifiable and uniform reader training as well as ongoing management of reader performance, helping to ensure quality control of the images and their interpretation and to decrease variability in image interpretations, leading to a more precise estimate of treatment effect.’While the manner in which central reads are conducted is quite variable among IBD trials and trials in other therapeutic areas, the call for utilizing central reading in clinical trials is clearly stated in the FDA’s March 2015 revised draft guidance tandards : ‘As com‘Nevertheless, the overarching trial design features and the other previously described features may justify the use of site-based imaging interpretations, even in large phase 3 multicenter clinical trials, so long as blinding of image interpretation to treatment can be assured or bias is otherwise controlled.’However, in the same guidance, the FDA also stresses the value of a site reader by stating: et al. recently reported on a variety of distinct read approaches for IBD clinical trials, each of which varied in the stepwise determination of a final endoscopic score [Although a handful of IBD studies have incorporated central reading to date, none have fully detailed the specific methodology with which the reads were conducted ,8,10,11.ic score . These cAs a step toward standardizing read methodology for the growing number of multicenter phase 3 clinical trials in IBD, we present a reading approach for ulcerative colitis (UC) studies involving both central and site readers that we call the ‘2 + 1 paradigm.’ This paradigm is based on the theoretical foundations of read paradigms rooted in voting algorithms  and pracUse of a clinical scoring scheme that has strong construct validity (e.g. the Mayo Clinic Score (MCS) endoscopic subscore criteria, Implementation of a quality-control process to assure suitable video capture that accurately reflects disease in the affected bowel. The quality of the source video captured at a site is critical to all downstream disease evaluations. Engagement with site endoscopists is a prerequisite for obtaining optimal video recordings. The site endoscopist must be fully involved in the read paradigm, adequately trained in the protocol expectations and preferred acquisition technique and fully understand the selected scoring system as it applies to the central and site readers as discussed in Gottlieb and Hussain [ Hussain . Once beReducing/eliminating sources of bias in the interpretation of the video endoscopy. Bias can be introduced by unblinded readers when evaluating patient eligibility and drug efficacy and may reduce the observable differences between drug and placebo [ placebo ,8. To elImplementation of video endoscopy review process that generates a quantifiable reflection of disease activity with reasonable accuracy and reproducibility. Variability in scoring between site endoscopists and central readers can be significant and may alter the outcomes of a study [ a study ,8. ThereOperational feasibility that facilitates proper and uninterrupted clinical trial conduct. While screening periods are typically two to three weeks in length, completion and reading of video endoscopy are usually completed as the last study examination. This leaves only several days for video acquisition and score reporting. This time constraint necessitates a paradigm of reduced complexity that accommodates multiple central readers and circumvents operational roadblocks.There are five principles to consider when choosing an efficient central read paradigm for a UC study. These principles, summarized below, address regulatory, operational and clinical expectations.The following central reading approach, which we call the ‘2 + 1 paradigm’  for the overall MCS endoscopic subscore, a final MCS endoscopic subscore is reported. If there is discordance between the site reader and the central reader for the overall MCS endoscopy subscore, the video endoscopy will be assigned to a second blinded reader  chosen from a pool of remaining central readers who are blinded to the scores of the site reader and the first central reader. The second central reader is also blinded to the number of times that the video endoscopy has been evaluated and will score it according to the same criteria applied by the site and previous central reader. From a total of the three overall endoscopic MCS subscores, the score with which two readers agree will be reported as the final overall MCS endoscopic subscore.In the unlikely event that no two readers agree on a final overall MCS endoscopic subscore, the median score of all three completed reads  will be chosen as the final reported overall MCS endoscopic subscore. Scenarios of final score determinations in such a setting are summarized in In the event that a submitted video endoscopy is determined to be ‘not readable’ by the second central reader, the reported overall MCS endoscopic subscore will default to that of the site reader. Given the burden of an endoscopy procedure coupled with the operational urgency for determining clinical trial eligibility, this method is the most favorable at the current time.The 2 + 1 paradigm utilizes the five key principles outlined in this paper to deliver a sound, centrally based imaging and reading methodology for UC trials. As many previous studies have done, one might suggest exclusion of the site endoscopist entirely from disease evaluation. However, there is a fundamental difference between endoscopist-generated video endoscopy and technologist-acquired imaging such as radiographs, magnetic resonance imaging (MRI) or computed tomography (CT). For example, non-IBD clinical trials utilizing MRI or CT imaging are usually dependent upon the technologist’s skill to generate quality images and may even rely on an automated assessment of computer-generated images to arrive at a quantifiable score of disease activity. In contrast, IBD trials utilizing video endoscopy to assess disease activity depend on the motivation, attention and skill of the site endoscopist to drive the imaging instrument, decide on the area and extent of focus and generate the quality and quantity of video content necessary for accurate disease evaluation by a central reader.Furthermore, site endoscopists who are expected to submit their endoscopic score of disease severity may experience a personal motivation to generate videos of sufficient quality to assure that a central reader will corroborate their own interpretation (Hawthorne effect) . It is iAnother benefit of the 2 + 1 paradigm is the elimination of common biases—of which regulatory agencies are keenly aware—particularly central reader bias associated with knowledge of the protocol-defined timing of the endoscopic video, patient and site-specific identifiers as well as knowledge of another reader’s interpretation. Both the site and central reader independently assess a single video endoscopy using the MCS endoscopic subscore, with the central reader being blinded to treatment assignment, patient identifiers and chronological nature of the endoscopy.Utilization of a blinded second central reader  eliminates bias associated with the need for an adjudicator who is often required to choose a score between that provided by the site and central readers. By blinding all central readers to patient and video sequence identifiers, the second central reader will also not be biased toward a certain score, especially when relying on a scale of only four scores . The unlikely introduction of a distinct third score is efficiently and conservatively resolved by deferring to the median score, which minimizes study delays associated with reconciliation of discrepant endoscopic scores from multiple readers yet allows an unbiased second central reader assessment.Finally, with evidence from multiple studies that reproducibility for the Mayo endoscopic subscore is suboptimal ,17, a siThe 2 + 1 paradigm for phase 3 UC trials described here adheres to the five key principles of an effective clinical trial read paradigm in IBD and is consistent with regulatory guidance calling for central reading with a reasonable rationale for utilizing site reading . While u


Osteoarthritis (OA) is characterized by progressive loss of cartilage in joints, and is a major cause of pain and disability, and imposes significant health care expense. New therapies are being developed to treat the symptomatic effect of OA, one of which is intra-articular injection of viscosupplementations of different forms of hyaluronic acid (HA). The current study evaluates the chemical exchange saturation transfer (CEST) effect from two popular viscosupplementations [Hylan gf-20 (Synvisc) and hyaluronan (Orthovisc)] by targeting the exchangeable hydroxyl protons present on these molecules (ViscoCEST).1rms of 3.6 μT and 1 s saturation duration by varying the frequency from −4 to +4 ppm in step size of 0.1 ppm. Field inhomogeneity (B0) and radiofrequency (B1) maps were also acquired to correct ViscoCEST contrast map for any inhomogeneity.ViscoCEST imaging from two viscosupplementations (Synvisc and Orthovisc) was performed on a 7T Siemens whole body MRI scanner. ViscoCEST images were collected with different combination of saturation pulse power and saturation duration. Z spectra were acquired at B1rms and saturation pulse duration.Both viscosupplementations showed broad CEST effect (ViscoCEST), which peaked ~0.8 ppm from down field of water resonance. Orthovisc showed 20 % higher ViscoCEST contrast than Synvisc suggestive of more HA component in Orthovisc. Increased ViscoCEST contrast was observed from both viscosupplementations with increase in BViscoCEST has a potential to image the spatial distribution of viscosupplements in vivo in patients’ intra-articular space as well as temporal variation in their spatial distribution. Osteoarthritis (OA), a major cause of pain and disability, is characterized by the progressive loss of cartilage tissue, increased synovial fluid, inflammation and decreased viscoelasticity of the synovial fluid within the affected joint. Hyaluronic acid (HA) is the major source of non-sulfated glycosaminoglycan (GAG) in the cartilage extracellular matrix and help in maintaining the intra-articular lubrication and optimizing the viscoelasticity of synovial fluid. In OA, the concentration and molecular weight of HA decreases in affected joints and makes it more susceptible to the mechanical stress , 2.New therapies are being developed to treat the symptomatic effect of OA, one of which is intra-articular injection of viscosupplementations of different forms of HA , 4. In rImaging methods that have been used to assess the OA disease progression include plain X-ray and conventional magnetic resonance imaging (MRI) scans. Plain X-ray provides an indirect measure of loss or thinning of cartilage by measuring the joint space narrowing (JSN) . On the 2 relaxation time has been shown after intra-articular injection of hyaluronic acid in a rat model of OA  by exploiting the exchangeable –OH protons present on these molecules. We also assessed the saturation pulse amplitude and saturation pulse duration effect on ViscoCEST contrast of these viscosupplemantations. Finally, we compared the optimal parameters for GagCEST from endogenous GAG from cartilage and ViscoCEST from exogenous HA.∆ω > k) must be fulfilled.The CEST technique is based on chemical exchange between a solvent pool  and a solute pool, a small metabolite or proteins. The solute pool has exchangeable protons with a distinct chemical shift from the bulk water protons. Application of the frequency selective radiofrequency irradiation on exchangeable protons of the solute pool leads to the saturation of solute spins, with zero net magnetization, and exchange of these with bulk water protons results in the decrease of bulk water signal. This saturation transfer magnetization can be imaged to detect the CEST effect from a solute, which provides an indirect measure of solute concentration. In order for the CEST effect to be efficiently observed, the slow to intermediate exchange condition  effects from the bound water protons and the direct water saturation interfere with the CEST analysis. To account for these effects, two CEST images are acquired: one with by applying saturation pulse at the resonance frequency of the exchangeable spins and other at the equal frequency on the other side of the bulk water peak. Signal difference in these two images can alleviate the MT effect. Normalizing this difference signal with the signal obtained without saturation provides the CEST effect from the exchangeable protons of solute as given in the following equation.Msat (±∆ω) are the magnetizations obtained with saturation at ‘+’ or ‘–’ ∆ω offset of the water protons resonance and M0 is the magnetization obtained without saturation. In biological tissues due to short transfer relaxation times of water, the application of saturation pulse can lead to substantial direct water saturation which can attenuates the CEST effect. This can be minimized to some extent by using Msat (–∆ω) [M0 to normalize the signal differences. The other factors which can substantially affect the CEST contrast are B0 and B1 field variations. As the CEST contrast is obtained by subtracting the two images (−∆ω and ∆ω), any asymmetry generated due to the local B0 field inhomogeneity will contaminate the actual CEST contrast. On the other hand the B1 inhomogeneity affects both the CEST contrast as well as the direct water saturation. The accurate quantification and correction of B0 and B1 inhomogeneities are important to obtain reliable CEST contrast [at (–∆ω)  instead contrast .For this study, we used two brands of viscosupplementations i.e. Hylan gf-20  and Hyaluronan  that are being widely used for treating OA patients. Both clinical grade samples were obtained in closed plastic tubes from the manufacturer. Orthovisc has a lower molecular weight than Synvisc but contains a higher concentration of hyaluronic acid per injection than Synvisc. Both products have been already shown their treatment efficacy in alleviating pain associated with OA , 24 and o, GRE readout TR = 5.6 ms, TE = 2.7 ms, field of view = 100 × 100 mm2, matrix size = 192 × 192, and one saturation pulse and 64 segments acquired every 10 s. ViscoCEST images were collected with different combination of saturation pulse power  and saturation duration. Z spectra were collected at B1rms 3.6 μT and 1 s saturation duration by varying the frequency from −4 to +4 ppm in step size of 0.1 ppm. The field inhomogeneity (B0) and radiofrequency (B1) maps were also gathered using the method described in details elsewhere [The ViscoCEST imaging was performed on a 7T Siemens whole body MRI scanner . The experiments were performed at 37 °C using a custom designed Styrofoam chamber to maintain the temperature at 37 ± 1 °C during the course of experiment. A frequency selective saturation pulse followed by a segmented RF spoiled gradient echo (GRE) readout sequence was used. A saturation pulse train consisting of 5–30 Hanning windowed rectangular pulses of 100 ms duration each with a 200 μs delay between them was employed. The saturation pulse excitation bandwidth was 5 Hz for a 1 s pulse with 1 % bandwidth of 20 Hz. The total repetition time of the sequence was adjusted to stay within specific absorption rate (SAR) limits. The sequence parameters were: slice thickness = 10 mm, GRE flip angle = 101rms of 2.2 μT and 0.5 s saturation duration [2, matrix size = 192 × 192 with delay of 8 s.For reproducibility of GagCEST result at 7T as shown previously , we alsoduration . The oth0 and then used to compute the CEST contrast map using equation [1 inhomogeneity and overlaid on anatomical proton weighted image as described in detail by Singh et al. [The acquired CEST weighted images were first corrected for Bequation . The CESh et al. .1rms of 3.6 μT and 1 s saturation duration  both the viscosupplementations provide a ViscoCEST contrast of only ~30 % of the maximum value. On the other hand, with the optimal parameters for viscosupplmentation, the endogenous GagCEST from cartilage is negligibly small. Therefore, using GagCEST, it may be possible to monitor the GAG content changes in cartilage following viscosupplemntation injection, and at the same time ViscoCEST potentially enables probing of temporal and spatial distribution of viscosupplementations in the intraarticular space.Singh et al. have showed that the optimal parameter to observe the GagCEST contrast at 7T is 2.2 μT Bduration . We reprOur initial results demonstrate that both Orthovisc than Synvisc viscosupplements exhibit –OH group exchange mediated CEST effect and they can be measured using ViscoCEST. In addition, ViscoCEST has potential to assess the spatial and temporal variation of these viscosupplementats in vivo. Further studies in these lines are currently in progress in our laboratory.


Light-to-moderate drinking has been associated with reduced risk of heart failure (HF). We have examined the association between alcohol consumption and incident HF in older British men.Prospective study of 3530 men aged 60–79 years with no diagnosed HF or myocardial infarction (MI) at baseline and followed up for a mean period of 11 years, in whom there were 198 incident HF cases. Men were divided into 6 categories of alcohol consumption: none, <1, 1–6, 7–13, 14–34 and ≥35 drinks/week. There was no evidence that light-to-moderate drinking is beneficial for risk of HF. Heavy drinking (≥35 drinks/week) was associated with significantly increased risk of HF. Using the large group of men drinking 1–6 drinks/week as the reference group, the relative HRs  for HF adjusted for age, lifestyle characteristics, blood pressure, atrial fibrillation and renal dysfunction were 0.97 (0.59 to 1.63), 1.39 (0.86 to 2.25), 1.00, 0.94 (0.64 to 1.43), 1.16 (0.78 to 1.71) and 1.91 (1.02 to 3.56) for the 6 alcohol groups, respectively. The increased risk associated with heavy drinking was attenuated after adjustment for N-terminal pro-brain natriuretic peptide (NT-proBNP) (HR=1.43 (0.76 to 1.69)). Stratified analysis showed heavy drinking was associated with increased HF risk only in those with ECG evidence of myocardial ischaemia.There was no evidence that light-to-moderate drinking is beneficial for the prevention of HF in older men without a history of an MI. Heavier drinking (≥5 drinks/day), however, was associated with increased risk of HF in vulnerable men with underlying myocardial ischaemia. Light-to-moderate drinking is associated with reduced risk of heart failure (HF) in middle-aged populations. High levels of alcohol, usually more than 90 g/day (>9 standard UK drinks), and alcohol abuse can result in alcoholic cardiomyopathy leading to HF. Less is known about the influence of alcohol on HF in older adults in whom incident HF is high, and the level of alcohol intake which increases HF risk is uncertain.We have examined the influence of light-to-moderate drinking and heavy drinking on risk of incident HF in an older population in whom HF is often not preceded by a myocardial infarction(MI), and assessed the effects of alcohol on N-terminal pro-brain natriuretic peptide (NT-proBNP) (marker of cardiac dysfunction). The study does not provide evidence that light-to-moderate drinking is protective in older adults, and that drinking 5 or more drinks is associated with significantly increased risk of HF compared with lighter drinkers in those with underlying ischaemia.Heavier drinking (5 or more drinks/day), particularly in those with underlying ischaemia, should be avoided. There is no evidence for a beneficial effect of light-to-moderate drinking to prevent HF in men aged over 60 years who have no history of an MI, although there was also no evidence of harm from light-to-moderate drinking in those without MI.Heart failure (HF) is a major and increasingly important public health problem in older people and is associated with considerable hospitalisation and mortality.The British Regional Heart Study is a prospective study involving 7735 men aged 40–59 years drawn from one general practice in each of 24 British towns, who were screened between 1978 and 1980.1) in this cohort have been described.Anthropometric measurements, including body weight and height, were carried out with participants standing in light clothing without shoes. Details of measurement and classification methods for smoking status, physical activity, social class, blood pressure, blood lipids and forced expiratory volume in 1 s  and were asked to estimate the number of alcoholic drinks during an average week. The men were classified into six groups according to their reported weekly intake: none (n=344), <1 (n=338), 1–6 n=1259), 7–13 (n=712), 14–34 (n=740) and ≥35 drinks/week (n=137). One UK drink=10 g alcohol. Light-to-moderate drinking refers to those drinking up to 34 drinks/week. Heavy drinking is defined as drinking ≥35 drinks/week (5 or more drinks daily). To achieve sufficient numbers and because previous report suggest that risk of atrial fibrillation, a major risk factor for HF, is only elevated at levels of 5 drinks or more a day, we have used ≥35 drinks as the threshold for heavy drinking. We have used the large group of 1–6 drinks/week as the reference group for comparison purposes. The alcohol questionnaire used in this study has been validated using 25 biochemical and haematological measurements on a single blood sample which indicated that the reported levels of alcohol consumption were valid on a group basis.9, 7–13  for CV morbidity and development of diabetes and follow-up has been achieved for 99% of the cohort.2 tests and the analysis of variance were used to assess the difference in baseline characteristics between the six alcohol groups. Cox’s proportional hazards model was used to assess the multivariate-adjusted HR (relative risk) by alcohol categories. The large group of men drinking 1–6 drinks/week was used as the reference group. The proportional hazards assumption was examined using time-varying covariates, calculating interactions of predictor variables and a function of survival time and including these in the models. Examination of time-varying covariates indicated no violation of the proportionality assumption in the sample. In multivariate analyses, smoking , recent ex-smokers (<15 years) and current smokers), social class , physical activity (4 groups), diabetes (yes/no), use of antihypertensive treatment (yes/no), prior stroke (yes/no), diagnosed angina (yes/no), LVH (yes/no), renal dysfunction (yes/no), and atrial fibrillation (yes/no) were fitted as categorical variables. Systolic blood pressure, body mass index, FEV1 and NT-proBNP were fitted continuously. To evaluate whether alcohol predicted HF independent of incident MI , we adjusted for incident non-fatal MI, fitting this as a time-dependent covariate.The χDuring the mean follow-up period of 11 years, there were 198 incident HF cases (rate 5.9/1000 person-years) and 336 major CHD events in the 3530 men with no doctor diagnosis of HF or MI at baseline .1 (model 4) and in particular NT-proBNP (model 5) attenuated the increased relative risk of HF associated with heavy drinking. Further adjustment for incident MI strengthened the association in heavy drinkers, but it remained non-significant. Exclusion of all men who had ever reported heavy drinking (>6 drinks/day since entry to the study at 40–59 years) in model 2 made little difference to the findings. We carried out further analysis separating the 21–34 drinks/week from the 15–34 drinks/week category. The adjusted relative risk  were 1.00 (0.60 to 1.67), 1.43 (0.88 to 2.31), 1.00, 1.02 (0.67 to 1.57), 1.48 (0.94 to 2.34), 0.57 (0.25 to 1.31) and 1.80 (0.96 to 3.36) for the seven groups: none, <1, 1–6, 7–14, 15–20, 21–34 and ≥35 drinks/week, respectively.We also examined the association between alcohol and HF stratified by age (<70 vs ≥70 years) using non-drinkers and men drinking <1 drink/week combined as the reference group. The number of heavy drinkers (≥35 drinks/week) in the oldest age group (n=39) was too few to examine separately. In men <70 years , the relative risk (95% CI) adjusted for factors in model 2 (table 2) using non-drinkers and <1 drink/week combined as the reference group were 1.00, 0.89 (0.46 to 1.75), 0.67 (0.30 to 1.53), 2.37 (1.13 to 4.98) and 2.67 (1.15 to 6.19) for none or <1, 1–6, 7–14, 15–34 and ≥35 drinks/week, respectively. No association was seen in the older age group . The relative risks in those ≥70 years were 1.00, 0.84 (0.51 to 1.37), 0.91 (0.52 to 1.61) and 0.79 (0.42 to 1.48) for none/<1, 1–6, 7–14 and 15–34 drinks/week groups, respectively.Since NT-proBNP is a marker of cardiac damage, we further examined the association between alcohol intake and HF risk separately in men with and without ECG evidence of myocardial ischaemia . To achiIn this study of older British men, there was no evidence that light-to-moderate drinking (up to 4 drinks/day) was associated with a beneficial effect on HF risk overall; non-drinkers showed similar risk to light/moderate drinkers (up to 34 drinks/week). Heavy drinking (≥35 drinks/week or ≥5 drinks/day), however, was associated with a significantly increased risk of HF compared with those drinking 1–6 drinks/week, which was largely seen in those with ECG evidence of myocardial ischaemia. Our findings extends those of previous studies by examining the effects of both light-to-moderate drinking as well as heavy drinking on risk of HF and the role of NT-proBNP, a marker of cardiac damage, and underlying myocardial ischaemia.Previous studies mainly from the USA have suggested that light-to-moderate drinking is associated with a beneficial effect on HF.8The magnitude of the health effects of alcohol is dependent on the base group used; non-drinkers and infrequent drinkers are usually not an appropriate group to estimate the effects of alcohol.incident atrial fibrillation, a major risk factor for HF, is only increased at levels of 5 drinks or more.prevalent atrial fibrillation. However, this may be due to the fact that many men with atrial fibrillation are likely to develop stroke or CVD, and have reduced their intake as a result of developing CVD.It is well established that excessive alcohol intake, usually defined as >90 g/day (more than 9 standard UK drinks), can lead to cardiomyopathy,NT-proBNP, a peptide released from myocardium in response to ventricular wall stress and dysfunction, is a marker of myocardial damage and subclinical cardiac function, and is strongly related to incident atrial fibrillation and HF.There are several limitations in this study. The current findings are based on doctor-diagnosed HF, which is likely to underestimate the true incidence of HF in this study population; however, these diagnoses are usually supported by evidence from hospital admissions and hospital attendances investigation. These men who were survivors of an ongoing cohort study and attended the re-examination may have been healthier than the general older population which might have also affected the absolute incident rates of HF. However, this should not have affected the associations between alcohol and HF risk; our previous reports on HF predictors, such as obesity and NT-proBNP, in this cohort have generally accorded with prior data and therefore, suggest external validity for our findings.In this study of older British men, there is no evidence that light-to-moderate drinking is beneficial for the prevention of HF in men without MI; heavier drinking ≥5 drinks/day is associated with increased risk of HF, particularly in men with underlying myocardial ischaemia.


We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter. MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets of interest (TOIs) by movement type and geolocation; and (3) a user interface to support streaming multi-intelligence data processing. We also present an activity pattern learning framework that uses the multi-source associated data as training to index a large archive of full-motion videos (FMV). VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection/false alarm results due to the complexity of the scenario. The novel use of ACOs and chat messages in video tracking paves the way for user interaction, correction and preparation of situation awareness reports. In a la1.1.For data collection and reporting, the aerial video is reviewed by humans , as the imagery is streamed down from an airborne platform. During a real-time FMV exploitation process, humans could call out significant AOIs, where a voice-to-text tool converts audible analyst call-outs (ACO) to text  are not synchronized in time or in space. They are not recorded with corresponding time stamps. Furthermore, the called-out targets and activities are not marked in video frames with bounding boxes or with a start and an end of each activity. It is worth noting that the use of ACOs radically differs from a traditional video annotation paradigm that is typically done manually for training and/or benchmarking of computer vision algorithms. The incorporation of the user's ACO requires advances in automation, human-machine interaction and multimodal fusion. In addition, during the overhead imagery review process, there is no advanced equipment, such as an eye tracker  or touch1.2.The ACO messages present a rich source of information allowing for a fast retrieval of activities and providing a summary of events over FMV. ACOs can provide a reference ground truth of the AOIs that occur in the reviewed FMV data. Hence, correlating these two data sources would produce four novel products: (1) a video summary of AOIs/TOIs allowing nonlinear browsing of video content; (2) annotated text-over-video media where only TOIs are highlighted with bounding boxes and synchronized with chat messages; (3) an activities index where linked events are grouped together; and (4) adaptive data play back allowing for user-selected filtering by geographic location. For instance, the end user may submit a query like this: pull out all video segments of activity types “turn then stop” near this house on the map see .i.e., segmenting FMV tracks into semantic sub-tracks/segments); (3) learn activity patterns in low-level feature spaces using the reviewed FMV data; (4) index non-reviewed FMV data ; as well as (5) assist FMV analysts with tools for fast querying and non-linear browsing of multi-source data.In this paper, we propose a multi-source probabilistic graph-based association framework to automatically: (1) identify TOIs corresponding to chat messages; (2) detect activity boundaries  and querying the unlabeled FMV data. Sections 8 and 9 outline our multi-media indexing and explorer (MINER) interface and evaluate several scenarios to provide performance details of the proposed framework, respectively. We conclude the paper in Section 10.Section 2 details related work. The following sections describe various components of our “video-indexed by voice annotations” (VIVA) system. Section 3 provides a video processing overview with extensions to our methods. Section 4 describes the mapping of a single FMV target track to multiple graphs of attributes. In Section 4.2, we describe our two-step algorithm to decompose a single track into semantic segments. Section 5 focuses on parsing of chat messages (or ACO) and their graphical representation. In Section 6, we present the multi-source graph-based association framework and the activity class assignment process. In Section 7, we briefly provide an overview of our approach for learning activity patterns from the reviewed FMV tracks  extracting spatio-temporal interest point detectors and descriptors ; (2) peret al.  (with t the time stamp from a chat message and T : a predefined time window to search for the tracked objects), the chat message and all video tracks are extracted from the data sets.In a given time interval, [Graph representations of video tracks and chat messages are generated as explained in Sections 4 and 5.j) and track segment (i). There are three main reasons to use a probabilistic distance metric: (i) to associate the graphs even if there are missing attributes; (ii) to reduce the effects of errors coming from the video processor and chat messages ; and (iii) to impute the weights of attributes based on the quality of videos. The associated graphs with the highest likelihoods are assigned as a match.Graph matching uses a probabilistic distance measure see  of ensemaw, sw, tw, clw, dw, lw, cnw and mw are the user-defined weights of attributes for actor, shape, time, color, direction, spatial location, tracking confidence and target mobility, respectively. aP, sP, tP, clP, dP, lP, and mP represent the probabilities of corresponding attributes, and cnP is the track confidence value generated by COURSE.The multi-source multimodal association framework consists of the following stages:N, and N-to-M association cases. Furthermore, this framework not only marks the TOI, but also the rendering of activities. Using labeled track profiles, the boundaries of each activity are determined by using the process described in Section 4.2. For example, after labeling each track segment by associating chat messages, track Segments 1, 3 and 5 are marked as travel, Segments 2 and 7 are u-turn and track Segments 4 and 6 are labeled as turn in An illustrative result of this framework is shown in 7.i.e., chain code). In terms of features, we used simple descriptors for vehicles, including speed, heading relative to segment start and a position eigenvalue ratio. By measuring the change relative to a fixed starting value, rather than the instantaneous change, the heading feature is robust to variations in how quickly the targets turns from its initial course. The position eigenvalue ratio is a measure of the mobility of the target, which is the ratio of eigenvalues calculated from the target's position within a short time duration. As for people tracking, we compute the histogram of motion flow and neighboring intensity variance, which describes the extent to which the target is moving toward or away from potential interaction sites.The chat messages provide the pseudo ground truth of the AOIs occurring in the reviewed FMV video (see Section 6). These correlated data also serve as training data for activity pattern learning in aerial imagery. Here, we employ BAE Systems' Multi-intelligence Activity Pattern Learning and Exploitation (MAPLE) tool, which uses the hyper-elliptical learning and matching (HELM) unsupervised clustering algorithm  to learni.e., without chat) to the indexed pattern of life trajectories over large amounts of non-reviewed FMV data. First, we use HELM to classify each instance of a new track to one of the clusters of the index. Second, we use temporal gradient matching distance to obtain matches between the representation of the new track and the indexed learned patterns. The similarity score between a new track j and an index i is denned as follows:ijt represents the similarity metric, which considers only the common clusters, and ijc is the similarity score of temporal gradient for the cluster sequence.The goal of the learning process is to be able to match an unlabeled track .The VIVA and MINER framework produces three useful products for the end users to visualize in the same interface see : (1) a v9.To validate the proposed framework, we used our own dataset consisting of EO/IRairborne videos (60 min long) and 100 chat messages. The activity list is limited to vehicle travel, stop, turn, u-turn, maintain-distance, accelerate and decelerate and human walking and running. The VIVA video tracker generated about 8000 different tracks. The percentage of false tracking is about 15 percent and could be reduced through fusion of both EO and IR . This isEach object was automatically classified into one of the three categories: “person,” “vehicle” or “others.” These models were trained offline using 34, 681 instances/frames of 514 tracked targets. We obtained 72.16% and 76.99% correct classification in HOF and HOG spaces, respectively. After majority voting, the track-wise classification accuracy increased to 86.58% and 92.61% in HOF and HOG, respectively. The biggest confusion is between humans and “others”, due to the low resolution of human targets. Most of the false targets that should be classified as “others” are due to noisy registration, platform motion and inaccuracy of the tracking bounding boxes, which often included parts of the background.i.e., semantic segments) in the overhead imagery are associated with their corresponding chat messages. A false association is flagged when the chat message is linked to the wrong target or semantic segment (see Section 4.2). This could occur when multiple targets are moving in the same area at the same time and in the same direction. A miss is defined as a chat message without an associated target in the overhead imagery. On this data set, we scored 83.77% correct association, 6.39% misses association and 9.84% wrong association . During these experiments, we set the time window in which to perform the multi-source associations to 15 seconds. Making this window shorter leads to less false alarms, but also a higher miss rate. Furthermore, we only used the target's direction, location and speed as attributes, which do not include other useful content to reduce false alarms.Specific low-level features (see Section 4.1) were computed prior to running the proposed multi-source multimodal association framework. i.e., shorter and semantic track segments). Thus, it is robust to scenario variations.The association framework for activity recognition handles complex scenarios with multiple tracked objects. i.e., middle screen region, northeast direction, etc.) rather than fine ranges, causing ambiguities in the association. Extracting buildings from available imagery [These preliminary results are very promising. Both the direction and the location attributes play an important role in the association of chat messages to tracks. The list of potential matches is reduced drastically using these attributes. Nevertheless, in order to make a one-to-one association, additional attributes, such as shape, color and size, and spatial relationships, such as a target near an identifiable landmark in the scene, would be very helpful to resolve association ambiguities. Due to the chat description, the extracted target's direction and location are cast to gross zones . We tested this framework on 54 new track segments/activities and obtained 79.6% correct activity label assignment see . Figure tion see . Add to 10.In this paper, we developed a novel concept for the graphical fusion of video and text data to enhance activity analysis from aerial imagery. We detailed the various components, including the VIVA association framework, the COURSE tracker, the MAPLE learning tool and the MINER visualization interface. Given the exemplar proof of concept, we highlighted the benefits for a user in reviewing, annotating and reporting on video content. Future work will explore the metrics and associations used to increase robustness and to reduce false alarms. However, it is noted that the end user can check the final results presented in our MINER interface to remove false alarms and effortlessly generate mission reports.