Conservation often requires that people change their behaviour or accept interventions that seek to improve the conservation and welfare of wildlife and the safety and well-being of people. In this study, we show that a short educational video can improve community support for an intervention (electric fencing) that is advocated by experts as a sustainable and cost-effective intervention to keep baboons out of urban residential areas. By varying the timing of the video within a survey exploring support for an electric fence, we demonstrate the value of education, which increased the average marginal probability of support by 15 percentage points. Women were more likely to change their attitude to fences once apprised of the relevant facts than men. This study contributes to the emerging literature on the importance of education in managing conservation conflicts and the need for evidence-based interventions.Papio ursinus) in a residential suburb of the City of Cape Town, South Africa. An educational video on the welfare, conservation and lifestyle benefits of a baboon-proof electric fence was included in a short online survey. The positioning of the video within the survey was randomised either to fall before or after questions probing the level of support for an electric fence. The results showed that watching the video before most survey questions increased the average marginal probability of supporting an electric fence by 15 percentage points. The study also explored whether the educational video could change people’s minds. Those who saw the video towards the end of the survey were questioned again about the electric fence. Many changed their minds after watching the video, with support for the fence increasing from 36% to 50%. Of these respondents, the results show that being female raised the average marginal probability of someone changing their mind in favour of supporting the fence by 19%. Qualitative analysis revealed that support for or against the fence was multi-layered and that costs and concern for baboons were not the only relevant factors influencing people’s choices. Conservation often needs to change people’s behaviours. We need to know what interventions are effective. We show in the real world that an educational video can be effective and can moderately change people’s opinions and that women are more likely to change their position in light of the facts than men. This study contributes to the emerging literature on the importance of education in managing conservation conflicts and the need for evidence-based interventions.Few studies test whether education can help increase support for wildlife management interventions. This mixed methods study sought to test the importance of educating a community on the use of a baboon-proof electric fence to mitigate negative interactions between humans and Chacma baboons ( As human population size increases, competition for space and resources between people and wildlife is increasing, ultimately leading to conflicts amongst people on how best to manage wildlife populations ,2,3. NegPapio is dextrous, agile, intelligent, social, has high dietary flexibility and wide habitat tolerance and is equally adept at running as it is climbing [2 of crops [Papio hamadryas anubis) and found they were responsible for 70% of all crop damage events [Baboons are considered one of the most difficult animals for humans to coexist with  and haveclimbing . These aof crops . A diffee events . The mosPapio are not listed as threatened or endangered [Although wild primates are threatened due to habitat loss and fragmentation, access to high-quality anthropogenic food and the elimination of natural predators can have a positive effect on primate numbers ,15. Babodangered , but thiMany management measures have been used to try and reduce baboon presence in urban and rural landscapes of Cape Town, including herding , light pElectric fencing is a particularly effective but expensive method for minimising human–wildlife conflict . It is a®  mesh fencing, which acts as a physical barrier , which falls mainly within the Table Mountain National Park. The dominant vegetation type in the Park is fynbos. Baboons are able to obtain all their nutritional requirements from natural vegetation [The survey was conducted in the coastal suburb of Kommetjie, Cape Town, located at 34°08′ S, 18°19′ E on the Cape Peninsula, Western Cape Province, South Africa . There agetation ,31. For getation . Only ifn = 1192). This represented about a third of all Kommetjie residents (population size: 3341) . The survey was open between 26 November and 20 December 2020. Both versions of the survey should have taken respondents no more than ten minutes to complete, which included watching the video and answering the questions.The survey was emailed to all Kommetjie residents on the Kommetjie Residents’ and Ratepayers’ Association emailing list .Respondents had to answer questions in the order they were presented, and it was not possible to go back and change an answer. Two versions of the survey were created. Both versions of the survey opened with two attitudinal questions relating to the extent of problems experienced with baboons and level of happiness with the presence of baboons in Kommetjie. In version 1 (henceforth known as ‘video_end’), these questions were followed by most of the other questions, with the video placed towards the end of the survey. In version 2 (henceforth known as ‘video_start’), the video was presented immediately after the first two questions, and then the rest of the questions were asked after the video. Respondents were randomly allocated a version of the questionnaire. Those assigned video_start became the experimental group, and those that were assigned video_end became the control group.The advantage of this approach is that by randomising whether respondents received the ‘treatment’ (video towards the start) or the ‘control’ (video towards the end), we were then able to estimate the effect of having seen the video on how key questions were answered. See  for a diBoth survey versions (video_end and video_start) had 14 identical questions, but respondents who were randomly assigned to video_end had an additional repeat question asking them again about their attitude towards the baboon-proof electric fence. This allowed us to see if watching the video might have contributed to people changing their minds about the electric fence. Analyses were performed in Stata (SE 15.1) and Excel, and graphs were produced in R . A 5% siFollowing published principles for comparing different response scales , we creaA probit regression model was used to test the main hypothesis that respondents who watched the educational video would have a higher average marginal probability of supporting the electric fence and a lower average marginal probability of not supporting it. The key independent variable—whether respondents had watched the video before answering the survey questions—was coded 1 for those that had watched it towards the beginning of the survey (video_start) and 0 for those that watched it towards the end (video_end).We hypothesised that attitudes and perceptions towards baboons and baboon-proof electric fences would likely influence the probability of respondents supporting the fence or not. A further regression model was included to control for this. Respondents were asked, “How do you feel about the presence of the baboon troop in the village?”, and responses were captured on a 5-point Likert scale where 1 = very happy, 2 = happy, 3 = neutral, 4 = unhappy, and 5 = very unhappy. The prediction was that the happier people were about having baboons in the village , the less support there would be for the fence, as a fence essentially inserts a barrier between humans and baboons.Age and gender were investigated to see if these could predict the level of support for a fence. We did not expect there to be any continuous relationship between age and support for the fence, but we hypothesized that people over 60  would spend more time at home and therefore be more exposed to baboons regularly and hence that they would likely be more supportive of a baboon-proof electric fence. A dummy variable was created in which those over 60 years old and of retirement age were coded as 1 and those under 60 years old as 0.Although gender has generally been a poor predictor of attitudes , a studyWe also tested two further propositions: that respondents who watched the educational video at the start would have a higher average marginal probability of agreeing that the electric fence would improve the welfare and conservation status of baboons, and that such respondents would have a higher average marginal probability of supporting a monthly levy towards the construction of a fence.Those who were randomly assigned the video_end version of the questionnaire were allocated additional questions that allowed them to consider, once again, whether they support (or not) the electric fence. Fisher’s exact test was used to test for significant differences between the pre- and post-video support for the electric fence for these respondents. This method follows that of a recent study , where aWe had no prior expectation as to whether gender would influence whether respondents changed their minds. One study found that gender failed to predict support for baboon deterrent techniques in Cape Town , whilst Our study also included a qualitative dimension. Thematic analysis was used to analyse the open-ended responses to the survey question “Please comment on why you do not support a baboon-proof electric fence in Kommetjie if it is built and maintained by conservation authorities and there are no additional costs to you”. The aim was to explore the reasons why people may be against the fence if money is not a limiting factor. A systematic approach was used to find patterned responses or themes within the dataset based (with adaptations) on a protocol provided by Braun and Clarke . This inn = 89, video_start: n = 92). The breakdown of respondents for each gender and age range for video_end and video_start is shown in The survey had a response rate of 15.1%. A total of 181 respondents over the age of 18 agreed to participate, out of which there were 166 complete responses and 15 partial responses. The distribution of respondents per survey version was approximately equal (video_end: n = 77), nearly half of all respondents (49%) strongly support or support the fence. Watching the video before answering the question about support for the fence significantly (p = 0.043) raised the average marginal probability of supporting the fence by 15% (p = 0.021) reduced the average marginal probability of not supporting the fence by 17%.There was a higher percentage of support for the fence amongst respondents that watched the video at the start (video_start) than those that watched the video at the end (video_end) . For vide by 15% . Watchinp = 0.003) and less likely to not support it (p = 0.014). Even when controlling for how people feel about the presence of baboons in the suburb, the impact of the educational video remained strong, with the average marginal probability of supporting the fence increasing by 16% (p = 0.024) and reducing the marginal probability of not supporting the fence by 18% (p = 0.013) (Respondents who expressed a preference for not having baboons in the suburb were significantly more likely to support the fence (= 0.013) . NeitherVideo_end respondents showed a statistically significant increase in support (from 36% to 50%) for the fence  when given an opportunity to watch the video and answer the same questions . All thon = 6) were split in their opinions after watching the video, with 50% (n = 3) increasing their support and 50% (n = 3) reducing their level of support.p = 0.02) raised the average marginal probability of someone changing their mind in favour of supporting the fence by 19%. Of those who converted to supporting the fence, 88.8% (8/9) identified as female and only one identified as male.The probit multiple regression showed that being female significantly  of respondents who had watched the video at the end and had said they were happy with baboons in the Kommetjie suburb (31/90) supported the fence. For those that said they were unhappy with baboons in the suburb (45/90), 46.7% (21/45) supported the fence. Our results also show that across all levels of being happy  with baboon presence in the suburb, the baseline level of support for the fence was higher for respondents who watched the video at the start than it was for those who watched the video at the end. For the respondents that were neutral about baboon presence in the suburb, support for the fence varied from 28.6% for those who watched the video at the end compared to 57.14% if they watched the video at the start.n = 181), 70 respondents (38.7%) entered a response to the question: 34 (48.6%) identified as female, 30 (42.9%) identified as male, and 6 (8.6%) people identified as non-binary.In total, 41% (74/181) of all respondents said that they did not support a baboon-proof fence even if it was paid for by authorities; 59.5% (44/74) of these respondents had watched the video at the end, and the remaining 40.5% (30/74) had watched the video at the start. Respondents were then given the opportunity to answer an open-ended question stating a reason for their objection(s). Of the total sample (n = 88), 34% strongly agree or agree that a baboon-proof electric fence improves the welfare and conservation status of baboons, 34% strongly disagree or disagree that a fence improves the welfare and conservation status and 32% are neutral. For those with the video_start version of the survey and who had confirmed they had watched the video (n = 76), 58% strongly agree or agree that a fence improves the welfare and conservation status of baboons, 25% strongly disagree or disagree that it improves the welfare and conservation status, and 17% are neutral.p = 0.001) the average marginal probability of agreeing that the fence improves the welfare and conservation status by 23%. Watching the video first reduced the average marginal probability of not agreeing that the fence improves the welfare and conservation status by 9%, but this was not statistically significant (p = 0.198) (Watching the video significantly increased (= 0.198) .n = 88), 21% strongly support or support paying a monthly levy to construct and maintain a fence, 67% strongly do not support or do not support paying the levy and 13% are neutral. For video_start respondents who confirmed that they had watched the video (n = 75), 23% strongly support or support paying a monthly levy, 53% strongly do not support or do not support paying a levy and 24% are neutral.There was a very small increase in support (2%) for paying a monthly levy to construct and maintain a baboon-proof fence amongst respondents that watched the video at the start compared to those that watched the video at the end . For thop = 0.732). Watching the video first reduced the average marginal probability of not supporting the payment of a levy by 14%, but this was also not statistically significant (p = 0.066)  .After conducting a thematic analysis of the open-ended responses, four main themes/dimensions were identified within the final sample relating to objections toward the fence even if it is paid for by conservation authorities: “Pro-wildlife”, “Pro-human”, “Effectiveness of fence” and “General concerns”. Within the main themes, 14 sub-themes were identified and are discussed below .It would be a hideous blight on the landscape”, and another that, “It will be a terrible eyesore”. Considering the 17 respondents that mentioned this objection, 41.2% (n = 7) had watched the video before answering the question and had seen an example of what the fence in Kommetjie would possibly look like. A further objection is that residents are concerned that they would feel fenced in and that the atmosphere of the suburb would be ruined. One respondent said, “… the idea of fencing in the village is outrageous. Then you should go and live in a gated community”, and another that, “The village atmosphere is being ruined by endless interventions by “authorities” who have no regard for the residents”.Many respondents reported that an electric fence would be aesthetically displeasing, i.e., they believed it would be unsightly and take away from the natural beauty of the area. One respondent referring to the fence said, “Authorities could use that money to improve many other things e.g., maintaining roads in Kommetjie”, and another that it will “cost massive amounts of money that the country simply does not have at the moment”.Slangkop Mountain is a popular hiking spot for Kommetjie residents; therefore, another concern was that a fence would restrict access to the mountain for leisure purposes. The educational video mentioned that there would be gates allowing access to the mountain, and 80% (4/5) of those that expressed concern were respondents who had only watched the video at the end. A number of respondents were concerned about costs associated with the fence, expressing views that the authorities would do better spending the money elsewhere. One respondent said, “We have to keep in mind that the baboons where (sic) here in Kommetjie LONG before humans arrived. So I think it’s highly unfair towards them. And another, that “Baboons came first, humans should discipline themselves and adapt to give baboons space they need. Arrogance to impose restrictions on nature”.The second most frequently occurring theme (12.9%) was that wildlife should be able to roam freely and that baboons had ranged in Kommetjie and the surrounding areas long before humans settled there. One respondent said, “Related to this theme is the view that Kommetjie residents should take responsibility for baboon-proofing their homes and gardens so that baboons are discouraged from entering the suburb, thereby putting the onus on residents rather than using a fence to keep the baboons out of the whole area. Below is a typical comment relating to this theme.“It is unnecessary—one cannot manage a wild animal. Instead, one should strive to manage the behaviour of the humans in the system . Baboons are manageable when the residents ensure that houses and waste is baboon proof. This strategy has worked for the past 35 years that I have lived here and will continue to work if residents are educated and comply to some very basic ‘rules’”.This kind of intervention leads to increased fragmentation of habitat, which is not only a problem for the large furry species like baboons! The ethos of Kommetjie is to act as a corridor for the remaining wildlife; to fence in these animals would do irreparable damage”. Many respondents voiced concerns about how the fence would impact other species in the area, such as caracals, porcupines and mongooses. Many of these concerns were from respondents (11/15—73.3%) who watched the video at the end and had not been given a chance to learn that porcupine tunnels could be built into the fence design.Many respondents said they were concerned about how the fence might affect other wildlife and were worried that it would fragment the landscape, potentially blocking important ecological corridors. One respondent said that “Some respondents regard the fence as being cruel and inhumane, expressing concerns about baboons and other wildlife facing possible electrocution and other injuries. All these comments were from respondents who watched the video at the end and did not learn that no other animals have ever been injured along the Zwaanswyk fence. The preference for authorities to seek alternative solutions before building a fence in Kommetjie was raised by six respondents, suggesting alternative measures such as planting food and providing water points on Slangkop Mountain or relocating the baboons to other areas.These animals are so intelligent that they will still find a way around the fence, so a BIG NO to fencing us all in and out”, and another that, “The fence as proposed is open on each end and I don’t believe it will keep baboons out of Kommetjie”. The educational video showed the positioning of the fence, indicating that it would have open edges—which is different from the Zwaanswyk fence that has a single-entry point where the main road enters the suburb. This sub-theme was slightly more popular with respondents who watched the video at the beginning .Respondents (13.7%) stated that baboons are intelligent animals and will be able to breach or circumnavigate the fence, thus rendering it ineffective as a management strategy. One respondent said, “I’m concerned that due to the difficult rocky terrain building and especially maintaining an effective fence will be almost impossible. There is a strong likelihood that it will be an expensive disaster”.Other concerns are that the fence will be ineffective due to power outages (such as ‘load-shedding’) or because the topography of Slangkop Mountain is not conducive to success. One respondent said, “You are a monkey if you think any fence in the country can be maintained, it’s a joke, there are fences everywhere, not one has been maintained, look at the reserve, look at Imhoff, look at the navy, look at Soetwater. Show me one fence that has done its job for more than six months…”.The final sub-theme within this dimension relates to concerns regarding the maintenance of the fence and the possibility that it will be vandalised. A few respondents worried that parts of the fence might be stolen, and others that maintenance of the fence would be an onerous task. One respondent, who had watched the video at the start, went so far as to say: “This study provides evidence that an educational video about the potential for an electric fence to reduce negative interactions between humans and baboons can increase support for an electric fence. The study has implications for the management of baboons in the area, but the study is of more general interest, too, in that it provides rare empirical evidence of the efficacy of an educational intervention. It is widely acknowledged in conservation that engaging with local stakeholders is essential for many biodiversity conservation projects, yet relatively little attention has been paid to how stakeholder engagement impacts conservation outcomes, in part because this can be difficult to evaluate . To the Watching the video first increased the average marginal probability of supporting an electric fence by 15% and reduced the average marginal probability of not supporting the fence by 17%. Neutral responses were similar between the control and treatment groups , suggesting that the video intervention was influential enough to change attitudes from not supporting to supporting the fence rather than simply pushing respondents towards a neutral stance.Within the broader context of conservation conflicts, the results are significant, as managing a species is considerably more effective if there is collaboration, agreement and support for management measures between key stakeholders such as local community members, policy and decision-makers, scientists and management practitioners . ConversThe pre- and post-test analysis of respondents who received the video_end version of the questionnaire showed that support for the fence increased significantly because of seeing the video. The pre- and post-test conversion results thus provide greater confidence in the robustness of the results gained from the randomised controlled trial method. Watching the video first increased the average marginal probability of agreeing that a fence improves the welfare and conservation status of baboons by 23% and the average marginal probability of support for the fence by 15%. This indicates that there are potentially other factors underlying the reasons behind stakeholders not supporting the fence despite acknowledging that the fence will improve baboon welfare and conservation status.One of those factors, and a major concern that is often raised regarding the use of fences to mitigate human–baboon conflict, is cost. Fences, although extremely effective at keeping baboons out of urban areas, can be expensive to build and maintain ,28. The In a study looking at the human–elephant conflict in Nepal, residents’ willingness to pay towards conflict mitigation programs was found to be positively related to income and education . AlthougAlthough the lack of support for a levy payment might be related to missing information pertaining to socioeconomic status, it was concerning, from a management point of view, that 41% of respondents reported that they would not support an electric fence even if it were built and maintained by conservation authorities and there would be no additional costs to them. This challenged the assumption that residents paying for an electric fence was a major barrier. The qualitative analysis of the responses revealed that objections to the fence were not unidimensional but covered a broad spectrum ranging from pro-welfare to pro-human oriented concerns whilst also revealing many practical issues residents had regarding the effectiveness of the fence.This suggests that promoting support for a baboon-proof electric fence will require a nuanced and tactical approach when engaging with stakeholders. This is emphasised by the fact that the top four recurring sub-themes from the thematic analysis were that baboons might be able to circumnavigate the fence, that wildlife should be able to roam freely, the fence will be aesthetically displeasing and the concern for other wildlife. It is evident that addressing a single dimension will not be adequate from a managerial perspective. The results do show, however, that a higher percentage of those who do not support the fence, even if there is no cost to them, are respondents who had not watched the video before answering the question (60% compared to 40% that had watched the video). This provides some insight into the potential shortcomings and limitations of the video as an educational tool to promote support for a fence whilst also highlighting some of the more successful aspects.The sub-theme with the highest frequency of occurrence is the acknowledgement by respondents that baboons are intelligent animals that may potentially breach the fence, either by finding novel ways to pass over it or by transgressing the fence at its edges. A potential limitation of the video was that the virtual placement of the fence showed that it would be open at either end. What the video failed to convey explicitly was that field monitors would remain employed and that they could ensure that baboons cannot breach the fence, either via access points to the mountain or at the fence edges. The fact that this concern comes almost equally from those that had watched the video and those that had not indicates that the video probably failed to educate on this issue and hence allay residents’ concerns in this regard.® mesh, etc.), as detailed by O’Riain and Hoffman [Pro-human-related concerns, where respondents feel that the fence will impede their enjoyment of life, are more difficult to address regardless of the educational video. There is not much scope to make an electric fence less of an eyesore. The technical specifications required for the fence to be effective against baboon incursions .By utilising two different experimental methods, a randomised controlled trial and a pre- and post-test design, we were able to show that the education of residents on an intervention that is advocated by experts improves their probability of stakeholder support. Watching an educational video, which intentionally addresses common misconceptions about baboon-proof fences, increased the probability of supporting the fence by 15% and reduced the probability of not supporting the fence by 17%. In the broader context of negative human–wildlife interactions, the findings of this study support the popular refrain in conservation and wildlife management literature that education is a powerful tool for improving the acceptance of proposed conservation actions that are known to benefit both wildlife and communities .The successes and failures of the video in this study were revealed in open-ended responses to questions about support for the fence, even if it is paid for by conservation authorities. These lessons can be used to improve future educational videos and further motivate research that seeks to understand the values and ideologies of stakeholders, which underpin support or lack thereof for management interventions. In practical terms, such research would provide conservation practitioners with actionable information that would allow for more effective communication and satisfaction among community members.Through the production of a short video, a wide audience can be educated on the benefits and costs of the intervention allowing them to make a more informed decision on whether they would support its use. It is, however, unclear from this brief study as to the durability of the results and how well the intention to support the fence will translate into future real-world support for the fence. Current research on education in conservation stresses the need for ongoing education on key issues and not simply once-off interventions such as that attempted in this study. Further studies investigating the persistence of attitude change because of an educational intervention are necessary. We have, however, shown that at least in the short-term, Kommetjie residents were more aligned with supporting a baboon-proof electric fence to minimise negative human–baboon interactions following the viewing of an educational video, and thus being nudged towards a positive conservation solution.


Three-dimensional video services delivered through wireless communication channels have to deal with numerous challenges due to the limitations of both the transmission channel’s bandwidth and receiving devices. Adverse channel conditions, delays, or jitters can result in bit errors and packet losses, which can alter the appearance of stereoscopic 3D (S3D) video. Due to the perception of dissimilar patterns by the two human eyes, they can not be fused into a stable composite pattern in the brain and hence try to dominate by suppressing each other. Thus, a psychovisual sensation that is called binocular rivalry occurs. As a result, undetectable changes causing irritating flickering effects are seen, leading to visual discomforts such as eye strain, headache, nausea, and weariness. This study addresses the observer’s quality of experience (QoE) by analyzing the binocular rivalry impact on the macroblock (MB) losses in a frame and its error propagation due to predictive frame encoding in stereoscopic video transmission systems. To simulate the processing of experimental videos, the Joint Test Model (JM) reference software has been used as it is recommended by the International Telecommunication Union (ITU). Existing error concealing techniques were then applied to the contiguous lost MBs for a variety of transmission impairments. In order to validate the authenticity of the simulated packet loss environment, several objective evaluations were carried out. Standard numbers of subjects were then engaged in the subjective testing of common 3D video sequences. The results were then statistically examined using a standard Student’s t-test, allowing the impact of binocular rivalry to be compared to that of a non-rivalry error condition. The major goal is to assure error-free video communication by minimizing the negative impacts of binocular rivalry and boosting the ability to efficiently integrate 3D video material to improve viewers’ overall QoE. Due to its immense demand in commercial applications, 3D video transmission has drawn a growing amount of research interest in recent years. A greater emphasis has been made on evaluating and minimizing the consequences of methodologies for 3D image or video capture, processing, rendering, and display in an effort to enhance quality of experience (QoE) ,2. NonetFor a given set of stereoscopic pictures, the weighted average of a 2D and a depth prominent map was calculated to produce a 3D prominent map. These reinforcements from the left and right pictures were selected and fed into a 3D convolutional neural network to assess the discerning quality when the value of 3D prominent map reinforcements is higher than the threshold previously established. The quality scores of the distorted stereoscopic picture were then calculated using a weighted average of the conspicuous image reinforcements. Hu et al.  suggesteThe evaluation of quality of service (QoS) and quality of experience (QoE) has been the topic of a significant amount of research, with a particular emphasis placed on video compression standards and communication channel noise. Taha et al.  analyzesIn this study, the goal was to engrave the viewers’ quality of experience (QoE) by performing objective evaluations to validate an appropriate simulation packet loss environment and a comprehensive subjective study to elongate the impact of psychovisual binocular rivalry. This was accomplished by analyzing the macroblock (MB) losses in a frame and its error propagation caused by predictive frame encoding while stereoscopic videos were being transmitted.The impression of depth in stereoscopic 3D video is dependent on how the human brain and eyes function. Two pictures representing two views of the same object appear independently to the eyes, with human vision interpreting the difference (disparity) between them to generate a depth feeling in the brain, which experiences a single image known as the cyclopean view . As a coAs illustrated in B, as shown in b representing the inter-pupillary distance and f representing the average object distance. With At a fixation point of providesΔf=−f2b1+ESPN 3D, Foxtel 3D, N3D, and 3NET .The Mean Squared Error (MSE)  is a meaw—video width, and h—video height.The Peaksignal-to-Noise Ratio (PSNR)  metric dThe Multiscale Structural Similarity Index Measure (MS-SSIM)  is a metThe Naturalness Image Quality Evaluator (NIQE)  is a no-A total of 22 viewers who were not familiar with the ITU-R BT.2021 standard were asked to subjectively evaluate the overall video quality and the sensation of visual comfort associated with several pairs of video materials. The criteria for visual discomfort included feelings of nausea, eye strain, double vision, and headaches. The viewers were asked to rate the videos on a scale that ranged from one to five points. To construct exact MB losses in both views, we used the same parameters, the CRF, fixed length slice, motion vector search method, etc., to encode both the left and right views of a stereoscopic video and then applied the same loss rate to both video streams. Since the videos were encoded in the NAL packet format, the exact numbers of NAL unit sequences and equal quantity of NAL units were discarded from both video streams using the H.264/AVC video stream analyzer ,46, an aIn each trial, error concealment in one and two views were represented as A and B, respectively. The two videos were repeated and then, during a 10 s period, the viewers rated each one. Therefore, the total duration for each trial was 60 s, with the timing of each experiment shown in The scores given by observers are averaged to produce the mean opinion score (MOS) and confidence intervals (CI) as indicated below:i for the degradation j in video sequence k and repetition r, and N is the number of observers. To better assess the accuracy of the results, as it is desirable to combine a CI with each MOS, we used a 95% one inHere, In the final subjective assessment session, viewers were asked to record their observations of video quality and visual comfort in each trial. After considering all the scores between 0 and 5, the MOSs were calculated by Equation , with thx-axis indicates the 1% and 3% packet losses (PLs) and error concealments (ECs) for the 7 different stereoscopic videos and the y-axis the viewer’s MOSs from 1 to 5 . Different loss rates for the same video are connected by a solid line, with the green and red ones indicating the connections between the PL and EC values for both views and a single one, respectively. The significant differences between the green and red lines show that there was a clear division between the viewer’s scores obtained from the approaches for single and both views. Moreover, the successive red lines demonstrate that binocular rivalry in one view generated much greater visual degradation for viewers than that in both views (green lines).A comparison of the scores is shown in the graph in In order to analyze the accuracy and confidence of the given scores, 95% CIs were calculated using Equation . In geneVideo quality can be significantly impacted by network packet loss, which can lead to visual discomfort, artifacts, and other issues. We used an MSE-, PSNR-, MS-SSIM-, and NIQE-based technique to estimate the objective testing for network packet loss in videos. The method allows us to determine if the simulation environment produced the necessary losses in the left and right views of a stereoscopic video.Both the short GOP videos and the long GOP videos underwent a comparison analysis, as seen in During 3 percent packet loss, the MSE experiences a greater loss than when 1 percent of packets are lost. Meanwhile, the PSNR declines when packet losses occur and significantly worsens for extended GOP when there is no I-frame present during encoding. The same outcomes in terms of structural difference brought on by mistake are likewise shown by the MS-SSIM. The score that confirms the video has acceptable losses for greater inspection during the subjective assessment is obviously reduced by the higher proportion of packet losses. The no-reference video quality metric NIQE was then used to measure a video’s naturalness. The red line in this example displays the original encoded video without any degradation. In contrast, the green line indicates the score for 1% pkt loss and the blue line indicates the score for 3% pkt loss.If there is any ambiguity or mismatch in the bit rate or an unwelcome drop or rise in the video, the video is rejected and re-run through the simulation environment in order to pass the objective assessment part. To determine if loss rates are correctly caused, the identical approach is applied to all experimental video datasets. With the help of all of these assessments, we would be able to verify that the simulation-based methodology is maintained throughout the whole study.t-test to compare the means of two variables for a single group by computing the differences between the values of these variables for each case and testing whether the average differed from zero. This sample was then used to compare the mean of a single sample of scores with a known or hypothetical population mean N was the equal number of samples in each distribution and t test value used to express the CIs for a set of data and compare the results obtained from different experiments. The aim was to state the possible range of true mean, t-test value p-value. The obtained p-value to determine how confident we are that the difference between the two distributions was significant. In statistics, the least degree of significance that may be observed while still rejecting the null hypothesis is referred to as the p-value. To put it another way, the less significant it was, the stronger the evidence was that supported the alternative theory. The value of the integral has to be found by the following integral in order to satisfy the area under the t-probability distribution in the interval In our approach, we used the paired-sample  (Hmean) . Based ointegral  was usedt-test scores that were derived from Equation  gave strong evidence against the null hypothesis, as this hypothesis could be rejected, there would be a statistically significant difference between the two populations, which would aid in the comprehension and demonstration of this difference. p-values.The findings that supported the alternative hypothesis revealed that the proposed strategy was superior to other ways that are already in use. We were only interested in one side of the distribution; thus, in order to compute the result of the t-test, and the p-values specified in Equation  Equation  were comt-test and p-value scores and distinct significant criteria assigned depending on the threshold levels established in Moreover, more ExSS in the 3% than 1% packet losses explained that binocular rivalry artifacts affected them more due to more artifacts being induced for packet losses and error concealment afterwards. Even in the matter of comparing t-test analysis. As a result of this, a severe binocular rivalry artifact can be seen in the stereoscopic video’s MB-loss error concealment in a single view. This is the leading cause of viewers’ lack of visual comfort when watching transmitted or broadcasted stereoscopic videos, which were subjected to real-life simulated transmitting conditions and observed in a standardized assessing environment. Stereoscopic videos were tested using real-life simulated transmitting conditions and were evaluated in a prescribed scientific environment.It was found that MB-loss error concealment in both views rejected the null hypothesis more often and supported the alternative hypothesis that error concealment in both views is superior to that in one. The null hypothesis stated that error concealment in one view is superior to that in the other two views. However, it was found that this was not the case. Instead, it supported the alternative hypothesis that error concealment in both views is superior to that in one. The This study identified the binocular sensitivity and rivalry effects of error concealment and showed that 2D EC methods are not acceptable for 3D videos without adjustments. The binocular rivalry artifact’s effect on stereoscopic video transmission was tested using independently encoded streams. For a single view, the MOS score for packet loss and error concealment falls between 2.25 and 2.75, while on both views the range is 2.65–3.37 for a 1% point loss in the short GOP sequences. The same holds for a 3% packet loss, such as 2.39 to 3.09 for both and 2.07 to 2.53 for single-view artifacts. Due to the adverse effect of binocular rivalry, a single view may score lower than both views. Additional analyses of the visual comfort of long GOP or MOS suggest similar concerns. To make it profound, we expanded the method to statistical t-test analysis and discovered that the negative effect is so pervasive that, in the vast majority of cases, the comparisons between single and both perspectives are statistically significant (SS) to extremely significant (ExSS): 13 out of 14 (93%) video quality metrics for short GOP are VSS and ExSS; 10 out of 14 (71%) visual comfort measurements are VSS and ExSS. In addition, the score for lengthy GOP increases to 100% for video quality and 86% for visual comfort. However, utilizing this basic approach, binocular rivalry disrupts the HVS and produces eye strain, headaches, nausea, weariness, etc. This work analyzed binocular rivalry to create a robust error-resilient 3D video communication system without perceptual ambiguity or rivalry. This investigation will enable researchers to develop real-time error concealment algorithms for 3D videos that do not degrade visual perceptual comfort.


Glycerol is a usable component of heat-transfer fluids, and is thus suitable for the use in microchannel-based heat exchangers in biosensors and microelectronic devices. The flow of a fluid can lead to the generation of electromagnetic fields, which can affect enzymes. Herein, by means of atomic force microscopy (AFM) and spectrophotometry, a long-term effect of stopped flow of glycerol through a coiled heat exchanger on horseradish peroxidase (HRP) has been revealed. Samples of buffered HRP solution were incubated near either the inlet or the outlet sections of the heat exchanger after stopping the flow. It has been found that both the enzyme aggregation state and the number of mica-adsorbed HRP particles increase after such an incubation for 40 min. Moreover, the enzymatic activity of the enzyme incubated near the inlet section has been found to increase in comparison with that of the control sample, while the activity of the enzyme incubated near the outlet section remained unaffected. Our results can find application in the development of biosensors and bioreactors, in which flow-based heat exchangers are employed. Glycerol is a trihydric alcohol, which is widely used in industry ,2. PauliThe above-mentioned biosensors ,6 and heElectric ,29,30,31Similar to the case with PEFs, the effect of electromagnetic fields (EMFs) on the activity of various enzymes was also reported to be either positive (enhancing) or negative (suppressing) ,45,46 deThe data listed above clearly indicate that the effect of electric and electromagnetic fields enzymes can vary, and further investigation is required in order to better understand the phenomenon of the interaction of external fields with enzymes. Here, we must emphasize that in the majority of studies listed above, macroscopic methods in solution (such as spectrophotometry) were employed for the determination of changes in the properties of enzymes. In the macroscopic methods, the signal from a large ensemble of the molecules under study is acquired. This leads to the fact that subtle effects of external fields on enzyme macromolecules can well remain unrevealed by macroscopic methods ,36,48. IHerein, we demonstrate how our well-established approach, which consists in a combined use of AFM-based adsorption studies and spectrophotometry-based estimation of enzymatic activity, has allowed us to reveal a long-term effect of glycerol flow in a heat exchanger on the properties of HRP, which has been used as a model enzyme, as was proposed in a number of published papers ,44,47,48HRP enzyme  and its substrate 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) were purchased from Sigma. Disodium hydrogen orthophosphate, citric acid, and hydrogen peroxide were purchased from Reakhim . 2 mM Dulbecco’s modified phosphate buffered saline (PBSD buffer) was prepared from a salt mixture purchased from Pierce . All solutions were prepared using deionized ultrapure water (with 18.2 MΩ  · cm resistivity) obtained with a Simplicity UV system . Glycerol was purchased from Glaconchemie GmbH .In brief, the heat exchanger was modeled by a polymeric coiled pipe, through which glycerol was pumped. The latter was warmed up to 65 °C in order to provide its fluidity, making it possible to pump at 9 L/s flowrate. The coiled section of the heat exchanger was ground-shielded in order to avoid any interference from the electromagnetic field generated in it. Moreover, the entire pipe (both the coiled and the linear sections) were heat-insulated in order to avoid heating of the enzyme samples, which can affect the enzyme properties . The temPrior to the experiment, the glycerol flow had been pumped through the heat exchanger for 40 min, and then the flow was completely stopped. After stopping the flow, 1-mL samples of the enzyme solution under study  were placed 20 cm away from the ground-shielded coil near either the inlet or the outlet section of the heat exchanger, so that the distance between the pipe and the test tube with the sample was 1 cm. The samples were incubated near the experimental setup for 40 min (as in our previously reported experiments ). The coHRP samples for AFM measurements were prepared by direct surface adsorption  accordinThe total number of objects, visualized on each AFM substrate with adsorbed HRP, was ≥200. Blank experiments were performed with pure PBSD instead of HRP enzyme solution, and no objects with heights exceeding 0.5 nm were revealed in these blank experiments. AFM operation and data treatment was performed with NOVAPx software  supplied with the atomic force microscope. The number of the visualized particles in the obtained AFM images was calculated automatically using specialized AFM data processing software developed at the Institute of Biomedical Chemistry.2) were calculated as described by Pleshakova et al. [The distribution of the AFM-visualized objects with heights (density functions), and the number of particles visualized by AFM  at 405 nm was monitored for 5 min, and the resulting dependencies were plotted in the form of absorbance vs. time (A405(t)) curves. The enzymatic activity was estimated based on the first 120 s of observation, and the calculations were performed as described previously [In parallel with the AFM measurements, the enzymatic activity of HRP in the samples incubated as described in eviously .As was noted in the Introduction, we have previously revealed an increased HRP aggregation under the influence of a continuous glycerol flow . In the In the control experiments, 1–1.2-nm-high compact objects were visualized a. These ρ(h) plot obtained for the control HRP sample  is 0.5 nm. We have previously justified that in the case of HRP (whose molecular weight makes up 40 kDa [The density function p 40 kDa ) adsorbep 40 kDa . ρ(h) plots shift towards greater heights (maxh ≈ 1.4 nm). It is interesting to emphasize that, while for the sample incubated near the inlet, the WHH is the same as for the control sample (WHH = 0.5 nm), the ρ(h) plot for the sample incubated near the outlet becomes considerably broader (WHH = 0.8 nm), showing an increased contribution of objects with increased heights to the plot’s right wing. The objects with increased heights can be well attributed to the aggregated HRP. Importantly, for the sample incubated near the outlet, the formation of higher-order HRP aggregates with heights of 2.4 nm is considerable  or near the outlet (N400 = 10 900) section of the heat exchanger, the N400 value was considerably higher than that obtained for the control HRP sample . These data indicate an increase in the number of HRP particles adsorbed on mica.For both working HRP samples, which were incubated either near the inlet (A405(t)) curves recorded for working and control enzyme samples.A405(t) curve recorded for the enzyme sample incubated near the inlet section of the heat exchanger is markedly different from those recorded for both the control enzyme sample and the sample incubated near the outlet, indicating higher enzymatic activity of HRP in the sample incubated near the inlet. Based on the first 120 s of observation, the analysis of the slope of the A405(t) curves gives the following values of HRP enzymatic activity: 237.8 U/(mL enzyme) in the sample incubated near the inlet, 200.9 U/(mL enzyme) in the sample incubated near the outlet, and 201.4 U/(mL enzyme) in the control sample. That is, after the incubation near the inlet section, the enzymatic activity of HRP has increased by 19% in comparison with both the sample incubated near the outlet and the control sample. It should be noted that in the case of continuous flow of glycerol, the change in the activity of HRP incubated near the inlet was comparable with the error, and in the case of incubation near the outlet, a 18% decrease in the enzymatic activity was observed [The curves shown in observed .We have investigated the influence of stopped glycerol flow in a coiled heat exchanger on the HRP enzyme, whose solution was incubated near either the inlet or the outlet linear section of the heat exchanger. In our experiments, an increased aggregation of the enzyme on mica has been revealed by AFM. Namely, an increased contribution of AFM images of objects with greater heights has been observed upon analysis of density function plots obtained for HRP samples incubated near the heat exchanger with stopped glycerol flow—in contrast to the control HRP samples. This situation is similar to the one observed for flowing glycerol, which was described in our previous paper . It is iFurthermore, it should be emphasized that our enzymatic activity measurements performed by spectrophotometry revealed a 19% increase in the HRP activity in the sample incubated near the inlet—in contrast to both the sample incubated near the outlet and the control sample. This is a very interesting result. Of note, external electric, magnetic and electromagnetic fields were previously shown to be able to enhance the enzymatic activity of HRP under certain experimental conditions. Ohshima et al. reported an increase in the activity of peroxidase after its 30 s exposure to a 12 kV/cm pulsed electric field . Wasak eEnzyme aggregation often leads to a deactivation of enzymes . NeverthIt was shown that shape of objects and moving media can influence the properties of biological molecules. This effect was called Ivanov-Tatur memory effect . Namely,It is to be emphasized that in this study we have observed the long-term effect on the HRP enzyme, whose incubation near the experimental setup started just after the fluid flow itself had been already stopped—in contrast to the case reported previously . This ef


High efficiency video coding (HEVC) has dramatically enhanced coding efficiency compared to the previous video coding standard, H.264/AVC. However, the existing rate control updates its parameters according to a fixed initialization, which can cause errors in the prediction of bit allocation to each coding tree unit (CTU) in frames. This paper proposes a learning-based mapping method between rate control parameters and video contents to achieve an accurate target bit rate and good video quality. The proposed framework contains two main structural codings, including spatial and temporal coding. We initiate an effective learning-based particle swarm optimization for spatial and temporal coding to determine the optimal parameters at the CTU level. For temporal coding at the picture level, we introduce semantic residual information into the parameter updating process to regulate the bit correctly on the actual picture. Experimental results indicate that the proposed algorithm is effective for HEVC and outperforms the state-of-the-art rate control in the HEVC reference software (HM-16.10) by 0.19 dB on average and up to 0.41 dB for low-delay P coding structure. Multimedia technology has been upgraded from one generation to another to fulfill daily needs such as television, telephones, computers, robots, etc. Numerous multimedia applications have been utilized, including digital versatile disc (DVD), digital television (TV) broadcasting, video telephony, video teleconferencing, video games, and other forms of video-on-demand. According to , the resIn general, video properties have four redundancy criteria: spatial redundancy, temporal redundancy, perceptual redundancy, and statistical redundancy, which can be eliminated by the video coding standard . High efR–D) score [Q-domain rate control is a direct estimation that attempts to model a correlation function between bit rate and quantization; the bit allocation can be computed from the Q-domain and R–Moreover, HEVC needs to have a functional encoder control, known as rate control, to determine the optimum codec parameters to accomplish minimal rate–distortion (D) score . Many cogorithms ,12 are ueveloped  by introvariable , named RR–Although the aim of software , includiR–R–R–R–R–D optimization, which cannot directly derive the gradient information from the penalty function, the evolutionary algorithm (EA) is chosen to optimize the parameters of our model. There are several EAs such as evolution strategies (ES) [(i)We propose a learning-based neural network to define the mapping between video contents and rate control parameters to assign CTU budgets correctly;(ii)We introduce a particle swarm optimization algorithm to finalize the optimal parameters at the basic unit level to maintain the bit budget and obtain good visual video quality;(iii)We enhance the rate control parameter updating by considering the semantic residue information of the actual inter-picture into rate control.Based on these considerations, we propose a learning-based mapping method between N) model  is used N) model . By incod method ,18 and td method ,22,23,24ies (ES) , simulaties (ES) , geneticies (ES) , and paries (ES) ,26,27,28R–The rest of the paper is organized as follows. In the next section, we briefly summarize related work. Then, the learning-based parameters of R–Q model, R–In this section, we briefly review the existing rate control models: R–Q model [R–Q model (URQ); the quadratic R–Q model is defined as in (1),R presents as the target bit rate, Q is the quantization parameter, and a and b are the parameters related to the video characteristic. The bit allocation of the URQ model is proposed similarly to the rate control model in H.264/AVC, where the target bit is computed based on the mean absolute difference (MAD) corresponding to the quantization step. As a result, compared with the earlier HEVC video coding standard (HM6.0) [Q-domain rate control [The –Q model  has exte (HM6.0) , the vis control ,31, suchR–Q model known as i, respectively. Additionally, the mapping between non-zero transform coefficients and Q-domain rate control. Although this indirect relationship between R and Q technique is advantageous, it is still difficult to adapt its estimation to the variable block size transform in HEVC.The enhanced posed in  by preseR–Q model mentioned above, a new type of encoder control with the hierarchical bit allocation for every picture in a GOP is proposed in [R–R–D relationship, as in (3):C and K are parameters related to video content. Then, to minimize (3), R. As a result, R–R–To overcome the limitations of the posed in , called n method  is used D and R–R–R–R–R–R–A distortion-based Lagrange multiplier is proposed in  to enhantructure . This abition in . A videoposed in . The autposed in .An inter-block dependency-based CTU-level rate control for HEVC is established in , known aA deep reinforcement learning-based rate control for the dynamic video sequences is designed in  to captuUnder a random access configuration, a deep convolution features-driven rate control for the HEVC encoders is proposed . The metR–Hence, we propose effective R–R–This section introduces a learning-based rate control algorithm, which creates a regression map for the G representing the input image characteristic. G is fed into our LB-PSO model to generate the R–The convolutional feature map  is introduced at the first stage to obtain the meaningful spatial representation of CTU pictures for the input of our LB-PSO model. In general, the early layers of convolutions in the deep convolutional networks demonstrate the input image’s local or low-level feature information. In contrast, the deeper layers of convolutions indicate the high-level feature information that provides more global information about the image . AdditioResNets)  model witth frame contains a total K CTUs, then G is a parameter representing the high-dimensional features required as input to the proposed LB-PSO model. To obtain G for re-feedback coding of each coding structure in HEVC, i.e., intra- or inter-pictures, we define G as in (7):c  of visual quality and smooth J can be defined as in (11):N is the total number of pixels in a picture and Our LB-PSO is proposed to define the optimal mapping According to the cost function design, the model parameters are updated after all CTUs are fully encoded. This cost function is aimed at the model learning to achieve the trade-off between distortion and bit allocation. The next section introduces the complete process of the parameters update.M in Equation  and 10). Additionally, the model parameters . AdditioP be the total size of the population, i-th particle, i-th particle, and n according to the following two equations:a is the inertia weight of velocity V, which is used to control the trade-off between the swarm’s global and local exploration capabilities. J. The lower cost function indicates a better J at the CTU coding level, the CTU is encoded.Let t can be computed asFor the picture level of inter coding, the rate control parameters are adjusted by considering the residue score of the semantic residue information. The probability of residue score For the quantization parameter (QP), it can be determined as in (21).J. After that, the velocity V and position M are calculated following Equations (13) and (14). Finally, the best particle for the LB-PSO model is determined to generate the best rate control coefficients for the current input CTU context.To evaluate the performance of the proposed learning-based particle swarm optimization, the experiments are conducted on various videos, including static and dynamic scenes.R–n represents bit depth.In the experiment, the proposed algorithm is implemented on HEVC reference software  and is cRC-HEVC) . AccordiRC-HEVC) , the larRC-HEVC)  by enably—WQVGA) , three vy—WQVGA) , five viy—WQVGA) , three vy—WQVGA) , and twoy—WQVGA) . Table 1(1) R–D performance and Bit Rate Accuracy: The first experiment was conducted on the low video resolution (WQVGA), which contains two video sequences with different frame rates, including BlowingBubbles and BQSquare. These two videos have various dynamic characteristics, such as a moving camera, moving objects, and illumination changes. R–D performance curve of the BQSquare test sequence. The learning-based approach obtains a better R–D performance than the baselines method. In addition, the average Specifically, our method’s average R–D curve, our proposed method is significantly higher than the competitive methods, as shown in R–Next, the WVGA sequences were tested, such as BasketballDrillText, PartyScene, and BQMall. The scene properties are similar to the above experiments, but these WVGA sequences are more challenging than WQVGA because they involve multi-object movement, camera movement, and higher resolution. The outcomes of R–D curve of FourPeople from the low bit rate to the high bit rate. Although the scene is used with a static camera, the proposed method’s R–D performance is noticeably greater than the competitive methods. Additionally, the After testing the WVGA sequences, the HD videos containing video conferencing and online teaching test sequences were simulated. The HD videos are FourPeople, KristenAndSara, Vidyo1, Vidyo3, and Vidyo4. These videos have the characteristics of a static camera with multiple objects moving. R–R–R–D for good visual quality and to maintain the target bit rate. R–D curve on different video resolutions. Consequently, our method has achieved the highest outcomes of all competitive methods. From The last experiment was applied on full HD and 4k video test sequences. The first three videos, ParkScene, Cactus, and BQTerrace, were used for the full HD experiment. The last two sequences, HoneyBee and Jocky, were used for 4k videos. This last test contained all types of scenarios. The ParkScene and Jocky videos have a moving camera and multiple object motions, while the BQTerrace video stacks the camera motion with a static camera. Furthermore, the Cactus video consists of a static camera and the rotation of the objects. The HoneyBee video has multiple object motions and a static camera. According to The PSNR performance of our proposed model is extensively compared with other state-of-the-art rate control methods for both the dynamic scene and interview scene as shown in Additionally, (2) Bit Heatmaps and Visual Quality: To indicate the performance of bit allocation at the CTU level, the heatmap visualization and the subjective results of the reconstructed frame are illustrated in R–For inter coding, the PS-GOP is added in comparison. Similarly, the color representation is defined the same as the intra coding. Regarding bitmaps, R–Regarding residual semantic information, our proposed method can correctly regulate the bit budget responding to the motion information in the scene, as illustrated in (3) Computational Complexity: We compare the computational time of the proposed method with RC-HEVC and PS-GOP. Regarding computational time in an average of seconds per frame, as indicated in R–R–D relationship. Experimental results clearly show that our proposed learning-based approach obtains an accurate target bit rate with 0.19 dB on average to 0.41 dB and 0.10 dB on average to 0.33 dB maximum R–In this paper, we proposed novel learning-based


Patients with untreated cerebral arteriovenous malformations (AVMs) are at risk of intracerebral hemorrhage. However, treatment to prevent AVM hemorrhage carries risks.This study aimed to analyze the AVM nidus-related hemodynamic features and identify the risk factors for subsequent hemorrhage.We retrospectively identified patients with untreated AVMs who were assessed at our institution between March 2010 and March 2021. Patients with ≥6 months of treatment-free and hemorrhage-free follow-up after diagnosed by digital subtraction angiography were included in subsequent examinations. The hemodynamic features were extracted from five contrast flow-related parameter maps. The Kaplan-Meier analyses and Cox proportional hazards regression models were used to find the potential risk factors for subsequent hemorrhage.Overall, 104 patients with a mean follow-up duration of 3.37 years  were included in study, and the annual risk of rupture was 3.7%. Previous rupture , deep AVM location , higher cerebral blood volume  in the nidus, and higher stasis index  in the nidus were associated with subsequent hemorrhage in untreated AVMs.Higher cerebral blood volume and stasis index in the nidus suggest increased blood inflow and stagnant blood drainage. The combination of these factors may cause subsequent hemorrhage of AVMs. Intracerebral hemorrhage (ICH) is one of the most typical presentations of cerebral arteriovenous malformations (AVMs). Hemorrhagic stroke caused by ICH is linked to mortality and long-term neurological impairment . The oveOver the past several decades, numerous angioarchitecture characteristics, including previous hemorrhagic status, AVM location, venous drainage pattern, associated aneurysms, and nidus size, have been reported as potential risk factors for subsequent hemorrhage . BesidesThis study retrospectively identified consecutive patients of all ages with untreated AVM admitted to our institution between March 2010 and March 2021. The inclusion criteria were: (1) patients with an untreated AVM diagnosed by digital subtraction angiography (DSA) at our institution, and (2) patients with ≥6 months of treatment-free and hemorrhage-free follow-up after diagnosed DSA. The exclusion criteria were: (1) pial arteriovenous fistula, spinal AVM, or any other type of cerebral vascular malformations, (2) the quality of DSA data was to poor for further analysis, and (3) patients missing the baseline information. This study was approved by the ethical committee of Beijing Tiantan Hospital and the written informed consent was provided by all patients.n = 1) or multiple (n ≥ 2), and exclusively deep or others, respectively. If the lesion involved the cerebellum, basal ganglia, brain stem, or thalamus, the location of AVM was considered deep; otherwise, it was considered superficial.If an AVM showed signs of hemorrhage on computed tomography (CT) and was consistent with a history of rupture, it was assumed to have ruptured before admission. Demographic information, including age and sex, was collected from medical records. The pediatric patient population was defined as individuals aged <18 years. AVM-related characteristics data, including the number of feeding arteries, nidus size, AVM location, the presence of AVM-related aneurysms, and the patterns of venous drainage, were obtained. AVM size, feeding artery, and venous drainage were divided into two categories: small (<3 cm) or large (≥3 cm), single  the first subsequent hemorrhage, (2) any treatment for AVM, (3) death, or (4) the end of March 2021. The primary endpoint of our study was AVM-related ICH after initial DSA diagnosis at our institution. During the follow-up period, the definition of subsequent hemorrhage of AVMs was a symptomatic clinical occurrence with fresh cerebral blood signs on CT or magnetic resonance imaging, with no other cause that could be readily identified as more probable than AVMs. By dividing the number of subsequent rupture events by the total person-years of follow-up, the annual risk of AVMs subsequent hemorrhage was calculated.Conservative treatment methods were selected for the following reasons: (1) the AVM was considered to have a low risk of rupture and the patient was asymptomatic; (2) using present techniques, the risks of treatment for AVMs were disproportionate to the benefits, or (3) the patient or family refused to accept the risks associated with any treatment option.DSA images were acquired on the 722038-153 Station  and AW6302 Station . The DSA acquisition procedure consisted of four frames per second. For each DSA operation, the contrast agent was injected at either the cervical section of the internal carotid artery at 4 mL/s for 6 mL or the vertebral artery at 3 mL/s for 5 mL. The DSA images that best depicted the nidus were chosen for further analysis.To quantitatively analyze the AVM nidus, two interventional neuroradiologists who were blinded to the patient information delineated the ROI for the quantitative assessment of the AVM, including the nidus and reference ROIs, on the two-dimensional map .TDC was fitted using a simplified gamma-variate function . As descFor each selected DSA series, five contrast flow-related parameter maps were created by calculating the TDC at each pixel of the selected ROI. Time to peak (TTP) was defined as the time taken by the TDC to reach its highest value; mean transit time (MTT) was determined by calculating the average residence duration of the contrast medium; cerebral blood volume (CBV) is a relative blood flow volume index that was obtained by integrating the TDC over 6 s; cerebral blood flow (CBF) was determined by dividing CBV by MTT. The inflow gradient and outflow gradient were defined as the steepest and shallowest slopes in all linear functions that were fitted in the gamma variant function, and the stasis index was defined as dividing the inflow gradient by the absolute value of the outflow gradient. The ultimate parameters were determined by calculating the average gray level intensity within the five TDC-based parameter maps, and the following characteristics were used for the hemodynamic analysis of the nidus: CBF, CBV, TTP, MTT, and stasis index.t-test or Wilcoxon’s rank-sum test, as appropriate, after assessing normality using the Shapiro–Wilk test. Categorical variables were compared using the chi-square test. Cox proportional hazards analysis was performed to examine the relevance of selected variables in predicting the relative risk of time from diagnosis to first subsequent hemorrhage, any treatment for AVM, death, or end of follow-up (March 2021). Variables that yielded a p value of less than 0.05 in the univariate Cox regression were subsequently incorporated into the multivariate Cox regression analysis. The Kaplan–Meier model was used to illustrate the rate of hemorrhage-free survival for untreated patients with and without specific features.The statistical analyses were conducted using the R software (version 4.0.1). Continuous variables are presented as mean and standard deviation for descriptive statistics, whereas categorical variables are provided as frequency and percentage. For continuous variables, the difference between groups was calculated using Student’s One hundred and four consecutive patients with untreated AVMs and with ≥6 months of hemorrhage-free and treatment-free follow-up were included. Among them, 30 (28.8%) patients were aged <18 years, with the average age being 12.7 years. The whole cohort had a mean age of 29.0 ± 14.3 years at initial diagnosis. There were 51 and 53 patients with small (<3 cm) and large (≥3 cm) nidus sizes, respectively. The temporal lobe was the most frequent AVM location (23.1%). Overall, 19.2% (20/104) of AVMs had exclusively deep venous drainage, whereas 28.8% (30/104) had a single feeding artery. Eight patients presented with intranidal aneurysms. Finally, 85 patients had Spetzler–Martin grade I, II, or III AVM and 19 patients had grade IV or V AVM.p = 0.015). The proportion of AVMs with a small size (p = 0.001), single feeding artery (p = 0.015), or exclusively deep venous drainage pattern (p = 0.001) was significantly higher among patients with hemorrhage at presentation. In this study, we found no statistically significant differences in the five hemodynamic parameters between AVMs that had hemorrhage at presentation and those that had not previously ruptured. In this cohort, the incidence of hemorrhagic presentation was 38.5% (40/104). Children (<18 years) had a significantly higher proportion of hemorrhage at presentations in this series . During the entire 350.4 person-years between initial diagnostic DSA and the follow-up endpoint, a total of 13 patients experienced subsequent hemorrhage of AVMs, resulting in an annual rupture rate of 3.7% for this whole cohort. Among the 40 patients with AVMs that have hemorrhage at presentation, the mean follow-up period was 3.10 years . During this follow-up period, 9 out of these 40 patients experienced subsequent hemorrhagic events, corresponding to an annual rupture risk of 7.3%. Conversely, for the remaining 64 patients who initially presented with unruptured AVMs, the mean follow-up duration was 3.54 years . During this period, 4 patients experienced subsequent hemorrhagic events, reflecting an annual rupture risk of 1.8%. Six patients died throughout the follow-up period. Most of their deaths, except the one from congenital heart disease, were thought to be mostly attributable to AVM.As shown in p = 0.021), nidus size (p = 0.026), AVM location (p = 0.003), venous drainage pattern (p = 0.004), CBV of the nidus (p = 0.016), stasis index (p = 0.001), and subsequent hemorrhage. The effects of sex, age, number of feeding arteries, intranidal aneurysm, CBF, MTT, and TTP were not significant. In the multivariate Cox proportional hazards model, previous rupture , deep location , higher CBV , and higher stasis index  were independent risk factors for subsequent rupture (Univariate risk analysis showed associations between ruptured AVM ( rupture . Figure This study quantitatively evaluated the hemodynamic characteristics of the AVM nidus and revealed that quantitative hemodynamic features could be used as a potential indicator to predict subsequent hemorrhage. Our results demonstrated that AVM with hemorrhagic presentation, deep location, higher CBV, and stasis index in the nidus were associated with a higher risk of subsequent hemorrhage.Several publications on the risk assessment of treatment benefits for AVM have been reported. The ARUBA study indicated that the risk of death or symptomatic stroke in patients with unruptured AVM due to inappropriate treatment was higher than that due to medical management alone , 18. HowBy iteratively calculating the TDC acquired from quantitative DSA, Lin et al.  first prBesides hemodynamic features, hemorrhagic presentation and deep location turned out to be significant independent predictors of subsequent hemorrhage, with approximately five-fold and four-fold risks compared with those without subsequent hemorrhage, respectively. Concerning the effect of hemorrhagic presentation, many studies have demonstrated that previous ruptured AVMs were more prone to undergo a subsequent hemorrhage , 23–25. Liew et al.  reportedOur study has several limitations, including its small sample size and relatively short follow-up period after DSA diagnosis. In addition, because of the overlap of the cerebrovascular system, our study only examined hemodynamic features in two dimensions, and measurements may have been vulnerable to inaccuracy. True visualization of three-dimensional DSA and larger studies with a longer follow-up period may be a future direction for exploring the precise hemodynamics of AVMs. Additionally, when comparing older ruptured AVMs with recently ruptured ones, potential bias may arise due to the potential differences in their subsequent hemorrhage risks. Ruptures could potentially alter the vascular structure within the nidus, leading to potential differences in hemodynamic features when comparing previously ruptured AVMs to unruptured ones. In forthcoming investigations with larger cohorts, including solely patients with unruptured AVM for the analysis of subsequent ruptures can help to eliminate this bias.A higher CBV and stasis index in the nidus, hemorrhagic presentation, and deep AVM location appear to be linked to a higher risk of subsequent hemorrhage in patients with untreated AVM. Hemodynamic features may help identify which patients will benefit from interventional therapy, assisting clinical decision-making for the management of AVMs.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Beijing Tiantan Hospital. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.Material preparation, data collection, and analysis were performed by HZ and LL. Formal analysis and investigation were performed by YC, YS, and SL. CM, LZ, FL, and YZ performed manuscript review and editing. CJ performed funding acquisition and supervision. HZ wrote the first draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Beijing Natural Science Foundation project [grant number 7212007].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.The reviewers LM and YC declared a shared affiliation with the authors HZ, LL, YS, YC, LZ, CJ, and YZ to the handling editor at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Editorial on the Research TopicNear-infrared fluorescence guided surgery: State of the evidence from a health technology assessment perspectiveIndocyanine green is a fluorescent dye used in various medical applications, including thoracic surgery. Indocyanine green-based near-infrared fluorescence imaging can provide real-time visualization of the vascular and lymphatic structures, aiding in the identification of critical anatomical structures during thoracic surgeries –4.1.Pulmonary segmentectomy.Near-infrared fluorescence imaging using Indocyanine green can aid in the identification of segmental bronchi and vessels, which can help in the precise identification and preservation of pulmonary segments during segmentectomy. Due to the development of imaging technologies, there has been an increase in the discovery of small, nonpalpable lung nodules previously undetected. Long-awaited randomized controlled experiment JCOG0802 demonstrated that segmentectomy is superior to lobectomy for lung tumors 2 cm in size. Consequently, it is reasonable to predict that segmentectomies will replace lobectomies for stage IA illness . Before Consequently, the tumor’s location is essential for thoracic surgeons undergoing segmentectomies. When nodules are discovered in peripheral segments or intersegmental planes, it is essential to examine the tumor’s location and segmental region to give radical surgical margins. Precise knowledge of the nodule and intersegmental plane is necessary to accomplish a complex segmentectomy .2.Mediastinal lymph node dissection.Indocyanine green-based near-infrared fluorescence imaging can identify the lymphatic drainage of tumors in the mediastinum, allowing for more accurate identification and dissection of lymph nodes during surgery. After peritumoral injection, it can help identify sentinel lymph nodes and observe the lymphatic drainage path during lung resections, allowing for correct lymphadenectomy and N staging, or it can aid in the treatment of problems such as chylorrhea by locating the thoracic duct. Near-infrared fluorescence fluorescence-guided sentinel lymph node mapping can correctly identify the sentinel lymph node, allowing the discovery of micrometastases, providing accurate staging, and possibly improved survival. Using the so-called improved permeability and retention, a passive targeting effect 24 h after the injection of a hefty dose of near-infrared fluorescence can visualize even small pulmonary nodules, filling the vacuum following the loss of tactile input during VATS. Other fluorescent dyes are more specific for adenocarcinomas, although their usage is uncommon .3.Identification of pulmonary nodules.Near-infrared fluorescence imaging using Indocyanine green can aid in the identification of small pulmonary nodules, which can be difficult to visualize with conventional imaging techniques. The indications and complications associated with fluorescence-navigated thoracoscopy have been summarized in a recent consensus study. Specifically, it may be a suitable method for identifying pulmonary nodules, intersegmental planes during thoracoscopic segmentectomy, and the surgical margin after excision. In contrast, given the low-quality evidence for the detection of sentinel lymph nodes, additional research is required to evaluate its role in this context. In addition, the panel of experts felt that fluorescence-guided thoracoscopic surgery could become a standard procedure for treating pulmonary lesions .4.Assessment of pulmonary perfusion.Near-infrared fluorescence imaging using Indocyanine green can provide real-time visualization of pulmonary perfusion, which can help evaluate lung function and identify areas of impaired perfusion –4.5.Thoracoscopic sympathectomy.Indocyanine green-based near-infrared fluorescence imaging can aid in the identification of the sympathetic chain during thoracoscopic sympathectomy, which can help reduce the risk of nerve injury –4.Overall, Indocyanine green-based near-infrared fluorescence imaging has the potential to enhance the precision and safety of thoracic surgery by providing real-time visualization of anatomical structures and improving the accuracy of surgical interventions. Evidence for the safety and effectiveness of fluorescent imaging in thoracic surgery appears convincing, representing an excellent approach with minimal complications and contraindications. However, given the fundamental importance of a multidimensional assessment of health innovation to guide its diffusion and uptake across healthcare systems, additional research to clarify the managerial, economic, and cost-effectiveness impact of these options is still needed.Some potential applications of indocyanine green-based near-infrared fluorescence imaging in thoracic surgery include:Frontiers in Surgery Journal (In this Research Topic for the  Journal , we pres


Regarding the interpretable techniques in the field of image recognition, Grad-CAM is widely used for feature localization in images to reflect the logical decision-making information behind the neural network due to its high applicability. However, extensive experimentation on a customized dataset revealed that the deep convolutional neural network (CNN) model based on Gradient-weighted Class Activation Mapping (Grad-CAM) technology cannot effectively resist the interference of large-scale noise. In this article, an optimization of the deep CNN model was proposed by incorporating the Dropkey and Dropout (as a comparison) algorithm. Compared with Grad-CAM, the improved Grad-CAM based on Dropkey applies an attention mechanism to the feature map before calculating the gradient, which can introduce randomness and eliminate some areas by applying a mask to the attention score. Experimental results show that the optimized Grad-CAM deep CNN model based on the Dropkey algorithm can effectively resist large-scale noise interference and achieve accurate localization of image features. For instance, under the interference of a noise variance of 0.6, the Dropkey-enhanced ResNet50 model achieves a confidence level of 0.878 in predicting results, while the other two models exhibit confidence levels of 0.766 and 0.481, respectively. Moreover, it exhibits excellent performance in visualizing tasks related to image features such as distortion, low contrast, and small object characteristics. Furthermore, it has promising prospects in practical computer vision applications. For instance, in the field of autonomous driving, it can assist in verifying whether deep learning models accurately understand and process crucial objects, road signs, pedestrians, or other elements in the environment. Convolutional neural network (CNN) models have been widely applied in the field of computer vision, such as object detection ,2 and imCAM techniques have limitations in practical usage as they are specific to certain architectures and require architectural modifications. To address this, Selvaraju et al. proposed Grad-CAM, which allows visualization and interpretation of CNN models without architectural changes . FurtherDue to the nature of Grad-CAM, which expresses the decision information of the model in the form of a heatmap, we can indirectly improve the robustness of Grad-CAM by enhancing the model’s robustness. There are six methods to improve model robustness: Data Augmentation, Regularization, Ensemble Learning, Adversarial Training, Weight Pruning, and Reinforcement Learning. In the field of Data Augmentation, Ekin D. Cubuk et al. proposed a method called AutoAugment , which eIn practical applications, images are often subjected to various disturbances, such as rotation, translation, noise, and changes in lighting conditions. Therefore, the system needs to tolerate such disturbances while maintaining its original output. However, Grad-CAM primarily relies on gradient information, which makes it ineffective in resisting large-scale noise interference . In thisGrad-CAM can be comprehensively explained through mathematical derivation. By differentiating the output tion (1) . For theIn the equation, By tracking the weighted combination of forward-activated maps using the ReLU activation function, a heatmap that aligns with the size of the convolutional feature maps can be obtained, as shown in Equation (2) .Grad-CAM computes the feature maps of the output layer and computes gradients of the respective categories by leveraging input information. Subsequently, the gradients associated with each category are weighted and averaged across channels, and the positive weights for each channel are aggregated. Consequently, a heat map is generated using these calculations. Each pixel within the heat map conveys its weight representation pertaining to the designated category . The heaWhen training a CNN model, it is crucial to address the issue of overfitting, especially when the model has a large number of parameters and the training dataset is limited in size . In 2012Dropkey is an innovative Dropout method inspired by DropAttention. It adapts attention weights in neural networks to promote smoother attention vectors ,25. DropDuring neural network training, Dropkey randomly discards a percentage of the input key units, generating an independent mask key mapping for each query. This masking of the attention scoring matrix positions Dropkey as a technique that modifies the placement of Dropout, lagging it to mitigate model overfitting. The mathematical formulation of Dropkey can be analyzed using Equations (3) and (4).In the equations, The optimized Dropkey-based Grad-CAM framework is illustrated in Overview of optimized Dropkey-based Grad-CAM: The Dropkey algorithm introduces a Bernoulli noise layer on the attention score matrix, which randomly masks a certain proportion of attention weights and suppresses unnecessary signals. This prevents the neural network model from overly relying on a piece of specific local information. Then, Dropkey applies the softmax operation along the last dimension of the attention score matrix to obtain weight coefficients. These coefficients are used to weigh the value vectors and compute their average. Finally, the weighted average is returned as the encoded representation of the query vector, q. The content within the dashed box describes the functioning mechanism of the Q, K, and V parameters in Dropkey.Introducing the Dropkey attention mechanism into Grad-CAM can reduce the reliance on specific neurons during the calculation process by incorporating random binary masks. Specifically, when computing attention weights, a binary random mask tensor of the same shape as the original attention weights are multiplied element-wise with the attention weights. Additionally, a small negative value is multiplied to set the attention weights to negative infinity at the masked positions. This ensures that the attention weights at the masked positions, after the softmax operation, are effectively zero, thus reducing their contribution to the final visual interpretability results. Furthermore, the Dropkey mechanism introduces randomness and enhances the generalization capability of the visual interpretability results by randomly discarding a portion of neurons. Through this mechanism, Grad-CAM becomes more adaptable to different input samples, thereby improving the generalization of the results. Consequently, the generated heatmaps better reflect the model’s attention to the target feature regions in a more comprehensive manner. Compared to Grad-CAM, improved with Dropout, the Dropkey mechanism alters the distribution of attention weights by introducing random masks and neuron Dropout. This enhances the randomness of the attention weights, leading to heat maps that are more interpretable and stable. Overall, the Dropkey-enhanced Grad-CAM exhibits superior robustness and generalization capability. This allows for a more accurate understanding of the model’s focus on input image features and the decision-making process. It contributes to improving the accuracy, reliability, and interpretability of explaining model predictions.The robustness of the optimized Dropkey-based Grad-CAM technique is evaluated in this section. Grad-CAM, relying on gradient information, may face challenges in accurately localizing image features when the input images are subjected to various disturbances such as blurriness or image noise. To assess the performance of the proposed method under different noise conditions, input images were augmented with noise of varying variances, specifically 0.1, 0.5, 1.0, 1.5, and 2.0. It is important to note that the pixel values of the augmented images were normalized to ensure they remained within the valid range of 0 to 255. The visualizations obtained from both Grad-CAM and the optimized Dropkey-based Grad-CAM techniques under the different noise conditions are presented in As shown in On the other hand, Grad-CAM improved with the Dropkey algorithm consistently demonstrates superior localization performance when the noise variance is 1.0 or below h–j. It iDue to its inherent nature as an improvement to the ResNet50 model, we can indirectly observe the resilience of Dropkey Grad-CAM to noise by examining the changes in the model’s confidence in prediction results under the influence of Gaussian noise of varying variances. The experimental results are illustrated in From the data in the graph, it can be observed that when the Gaussian noise variance is below 0.3, all three methods, namely Grad-CAM, Dropout Grad-CAM, and Dropkey Grad-CAM, demonstrate good resistance and maintain a high level of confidence. However, when the Gaussian noise variance reaches 0.5, Grad-CAM’s resistance to noise diminishes. Furthermore, during the transition from a variance of 0.5 to 0.9, all three methods experienced a decrease in confidence levels. Nevertheless, from the data in the graph, it is evident that Dropkey Grad-CAM exhibits better confidence levels compared to the other two methods under the influence of noise of the same magnitude.Under the interference of the same noise, the ResNet50 model improved with the Dropkey mechanism and demonstrated superior confidence in prediction results. For instance, when the noise variance is 0.5, the confidence levels for the prediction results of the Dropkey-enhanced ResNet50 model and the Dropout-enhanced ResNet50 model are 0.998 and 0.983, respectively, while the confidence level for the original ResNet50 model drops to 0.807. Furthermore, under the interference of a noise variance of 0.6, the Dropkey-enhanced ResNet50 model maintains a confidence level of 0.878, while the Dropout-enhanced ResNet50 model and the original ResNet50 model experience significant drops in confidence levels to 0.766 and 0.481, respectively. It is evident from the model analysis that the Dropkey-enhanced ResNet50 model possesses better noise resistance capabilities. Additionally, improvements in the model contribute to the enhancement of Grad-CAM performance. Therefore, we can indirectly conclude that the introduction of the Dropkey mechanism enables effective mitigation of noise interference, thereby improving the accuracy of Grad-CAM.Furthermore, changes in the structure and shape of an image, such as rotation or stretching deformation, can also impact the localization of image features. Image rotation alters the position and orientation of image features, potentially affecting the accuracy of feature localization. Similarly, stretching deformation modifies the aspect ratio of target features, leading to errors in feature localization and weight calculation, thereby influencing the accuracy of the obtained results. As illustrated in To further validate the resistance performance of Dropkey-enhanced Grad-CAM against large-scale noise, we selected four mainstream methods in the field of visual explanation for comparative verification .The experimental results indicate that under noise interference with a variance of 1.5, both Grad-CAM and its four variant methods fail to accurately locate the entire feature object. They only make judgments based on certain parts of the feature target. On the other hand, Grad-CAM optimized with Dropout and Dropkey can relatively accurately locate the target feature, and Dropkey Grad-CAM exhibits more complete feature localization. This further demonstrates the excellent performance of Dropkey Grad-CAM in resisting noise interference.The localization of low-contrast image features is often challenging due to the absence of significant brightness variations and distinct edges, resulting in blurred or ambiguous details within the image. Additionally, noise in low-contrast images tends to be more prominent, causing the target features to be submerged or mixed, thereby greatly impacting extraction and localization. Consequently, the recognition and extraction of low-contrast image features present a formidable task in assessing computer visualization and interpretability.Based on experimental results, it is evident that the original Grad-CAM technique exhibits significant distortions when extracting low-contrast image features, rendering it incapable of effectively locating the target feature objects in the images, as illustrated in The recognition and extraction of extremely small feature objects pose a significant challenge in computer visualization. Due to resolution limitations, pictures containing small feature objects often suffer from detail loss, which hampers accurate extraction and identification. Moreover, noise can substantially affect the recognition, extraction, and matching of smaller features.Based on the experimental results, it is evident that the original Grad-CAM technique fails to effectively locate small target feature objects in the presence of noise interference b. AlthouAdditionally, it is important to note that in practical usage, we should pay attention to the selection of the mask ratio parameter and choose an appropriate value based on different input scenarios. For example, in the following experiment, the visualization heatmaps may vary depending on the chosen mask ratio value .This phenomenon arises because a smaller mask ratio implies fewer lines are “removed” from the model as the proportion of discarded keywords in the Dropkey algorithm decreases. Conversely, a larger mask ratio corresponds to more lines being “removed” from the model as the proportion of discarded keywords in the Dropkey mechanism increases. Consequently, the mask ratio and the number of rows removed or retained in Dropkey exhibit a proportional relationship.In simpler terms, when the mask ratio approaches 0, the Dropkey mechanism has minimal impact, meaning that only a few rows are discarded. On the other hand, when the mask ratio approaches 1, the Dropkey mechanism becomes highly influential, leading to the removal of more rows. To put it simply, when the influence of Dropkey is low, there is a higher risk of overfitting the model. On the other hand, when the influence of Dropkey is high, it can negatively impact the predictive performance of the model. Hence, selecting an appropriate mask ratio becomes crucial, considering the specific circumstances and striking a proper balance between model prediction performance and overfitting.In this paper, the robustness of Grad-CAM is tested and improved. Since Grad-CAM heavily relies on gradient calculations, it is susceptible to interference information. To ensure its stability and effectiveness, Dropout and Dropkey algorithms are employed to improve its robustness. Experimental results demonstrate that both Dropout and Dropkey algorithms improve the generalization capability of the CNN model, thereby improving the robustness of the Grad-CAM technique. During the experiments, it was observed that the selection of the mask ratio parameter in the Dropkey algorithm significantly influences the final Grad-CAM localization effect. Therefore, it is crucial to carefully choose the appropriate parameter under specific experimental conditions and image characteristics. Furthermore, the experimental findings indicate that the improved Grad-CAM based on the Dropkey algorithm exhibits greater robustness compared to the enhanced Grad-CAM based on Dropout. This can help people better validate whether neural network models can correctly process information in images.