Sight Research Articles

Effectiveness of a new thermal insulation blanket in the control of inadvertent perioperative hypothermia and comfort: a randomized controlled trial

BackgroundDisturbances in the thermoregulatory system can precipitate inadvertent hypothermia in patients undergoing surgeries lasting over 60 min, causing serious complications in the recovery process. Cutaneous thermal protection is relevant for the control of temperature of patients in the perioperative setting. The standard thermal protection widely utilized is an electric forced warm air blanket. This study compared a new layered textile blanket with the standard protection. The hypothesis posited that the textile blanket could provide cutaneous thermal protection comparable to that of the standard protection (forced-air warming blanket), in terms of temperature variation and safety.MethodsThis randomized controlled trial was conducted at a Portuguese orthopedic hospital from October 2018 to January 2019, comprising 124 adult patients undergoing elective total knee arthroplasty. Participants were randomly allocated to either the intervention group, receiving the textile blanket, or to the control group, receiving standard measures. Tympanic temperature, shivering, and thermal comfort perception were evaluated at six time points. Comfort dimensions and ergonomic aspects were also assessed. Parametric statistics were performed, and independent samples t-tests and repeated measures were used to compare temperature variations and thermal comfort.ResultsNo statistically significant differences were found between groups in mean temperature variation, visual perception of thermal comfort, and thermal and perioperative comfort scales. The intervention group (n = 65) scored significantly higher in ergonomic evaluations compared to the control group (n = 59) for: fit to body and general comfort (p = 0.004), touch (p = 0.005), and feeling of comfort with the inner layer texture and shape (p < 0.001).ConclusionThe tested blanket had a comparable performance to the standard protection, suggesting it as a potential sustainable alternative to the recommended measures for thermal protection. However, further investigations across diverse contexts and populations are needed to validate these findings.

Triboelectric Mat Multimodal Sensing System (TMMSS) Enhanced by Infrared Image Perception for Sleep and Emotion-Relevant Activity Monitoring.

To implement digital-twin smart home applications, the mat sensing system based on triboelectric sensors is commonly used for gait information collection from daily activities. Yet traditional mat sensing systems often miss upper body motions and fail to adequately project these into the virtual realm, limiting their specific application scenarios. Herein, triboelectric mat multimodal sensing system is designed, enhanced with a commercial infrared imaging sensor, to capture diverse sensory information for sleep and emotion-relevant activity monitoring without compromising privacy. This system generates pixel-based area ratio mappings across the entire mat array, solely based on the integral operation of triboelectric outputs. Additionally, it utilizes multimodal sensory intelligence and deep-learning analytics to detect different sleeping postures and monitor comprehensive sleep behaviors and emotional states associated with daily activities. These behaviors are projected into the metaverse, enhancing virtual interactions. This multimodal sensing system, cost-effective and non-intrusive, serves as a functional interface for diverse digital-twin smart home applications such as healthcare, sports monitoring, and security.

Perceiving Etruscan Art: AI and Visual Perception

This research project is aimed at exploring the cognitive and emotional processes involved in perceiving Etruscan artifacts. The case study is the Sarcophagus of the Spouses at the National Etruscan Museum in Rome, one of the most important masterpieces in pre-Roman art. The study utilized AI and eye-tracking technology to analyze how viewers engaged with the Etruscan Sarcophagus of the Spouses, revealing key patterns of visual attention and engagement. OpenAI, ChatGPT-4 (accessed on 12 October 2024) was used in conjunction with Colab–Python in order to elaborate all the spreadsheets and data arising from the eye-tracking recording. The results showed that viewers primarily focused on the central figures, especially on their faces and hands, indicating a high level of interest in the human elements of the artifact. The longer fixation duration on these features suggest that viewers find them particularly engaging, which is likely due to their detailed craftsmanship and symbolic significance. The eye-tracking data also highlighted specific gaze patterns, such as diagonal scanning across the sarcophagus, which reflects the composition’s ability to guide viewer attention strategically. The results indicate that viewer focus centers on human elements, especially on faces and hands, suggesting that these features hold both esthetic and symbolic significance.

The use of ChatGPT in the dermatological field: a narrative review.

Artificial Intelligence (AI) encompasses the development of computer systems capable of tasks typically requiring human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Over time, numerous applications have emerged, with AI's integration into medicine marking a significant leap forward in healthcare delivery, diagnosis, and treatment. Among medical specialties, dermatology stands at the forefront of AI advancements, leveraging machine learning and deep learning to enhance dermatologists' abilities and improve patient care. ChatGPT is an advanced language model by OpenAI, originally designed for conversations, which has expanded its utility into diverse fields, including healthcare and dermatology. In this context, the aim of this review article was exploring the synergistic relationship between ChatGPT and dermatology, examining how this innovative AI model is reshaping skin health management, its potential applications, preliminary data on its efficiency and accuracy, as well as ethical and legal concerns related to the use of its tool.

Enhancing Ultrasound Image Quality Across Disease Domains: Application of Cycle-Consistent Generative Adversarial Network and Perceptual Loss.

Numerous studies have explored image processing techniques aimed at enhancing ultrasound images to narrow the performance gap between low-quality portable devices and high-end ultrasound equipment. These investigations often use registered image pairs created by modifying the same image through methods like down sampling or adding noise, rather than using separate images from different machines. Additionally, they rely on organ-specific features, limiting the models' generalizability across various imaging conditions and devices. The challenge remains to develop a universal framework capable of improving image quality across different devices and conditions, independent of registration or specific organ characteristics. This study aims to develop a robust framework that enhances the quality of ultrasound images, particularly those captured with compact, portable devices, which are often constrained by low quality due to hardware limitations. The framework is designed to effectively process nonregistered ultrasound image pairs, a common challenge in medical imaging, across various clinical settings and device types. By addressing these challenges, the research seeks to provide a more generalized and adaptable solution that can be widely applied across diverse medical scenarios, improving the accessibility and quality of diagnostic imaging. A retrospective analysis was conducted by using a cycle-consistent generative adversarial network (CycleGAN) framework enhanced with perceptual loss to improve the quality of ultrasound images, focusing on nonregistered image pairs from various organ systems. The perceptual loss was integrated to preserve anatomical integrity by comparing deep features extracted from pretrained neural networks. The model's performance was evaluated against corresponding high-resolution images, ensuring that the enhanced outputs closely mimic those from high-end ultrasound devices. The model was trained and validated using a publicly available, diverse dataset to ensure robustness and generalizability across different imaging scenarios. The advanced CycleGAN framework, enhanced with perceptual loss, significantly outperformed the previous state-of-the-art, stable CycleGAN, in multiple evaluation metrics. Specifically, our method achieved a structural similarity index of 0.2889 versus 0.2502 (P<.001), a peak signal-to-noise ratio of 15.8935 versus 14.9430 (P<.001), and a learned perceptual image patch similarity score of 0.4490 versus 0.5005 (P<.001). These results demonstrate the model's superior ability to enhance image quality while preserving critical anatomical details, thereby improving diagnostic usefulness. This study presents a significant advancement in ultrasound imaging by leveraging a CycleGAN model enhanced with perceptual loss to bridge the quality gap between images from different devices. By processing nonregistered image pairs, the model not only enhances visual quality but also ensures the preservation of essential anatomical structures, crucial for accurate diagnosis. This approach holds the potential to democratize high-quality ultrasound imaging, making it accessible through low-cost portable devices, thereby improving health care outcomes, particularly in resource-limited settings. Future research will focus on further validation and optimization for clinical use.

The healthy eating movement on social media and its psychological effects on body image

IntroductionThe present study aims to investigate the relationship between social-media pressure, the tendency to internalize standards of beauty and attractiveness associated with thin bodies, which subsequently leads to distortion of body shape perceptions, and restrictive and emotional eating behavior disorders.MethodsA survey-based research design was employed, utilizing an online questionnaire to collect data. The study sample consisted of 614 students, selected from the most prestigious universities in Bucharest. The questionnaire incorporated validated scales measuring Socio-Media Pressure for a Thin Body Image (SMPTB), Body Appreciation (BA), Body Shape Perception (BSP), Restrained Eating Behavior (REB), and Emotional Eating Behavior (EEB).ResultsThe results confirmed the hypotheses of the research, meaning food restrictions are a way to diminish the level of dissatisfaction with body shape, to reduce the difference between the ideal body shape and the real one. Food restrictions are perceived as natural behaviors, appropriate to support the standards of beauty and attractiveness specific to this historical stage. Emotional eating disorders emerge as a way to compensate for the discomfort generated by low body esteem.DiscussionThe results underscore the pervasive influence of social media in shaping eating behaviors and body image perceptions. Food restrictions, framed as natural responses to societal pressures, highlight the need for interventions addressing the normalization of harmful beauty standards. Emotional eating behaviors reveal the psychological toll of body dissatisfaction, emphasizing the importance of strategies to foster positive body image and mental well-being. These findings provide a foundation for developing educational campaigns and therapeutic approaches targeting the psychological impact of social media on eating behaviors.

Visual Content Privacy Protection: A Survey

Vision is the most important sense for people, and it is also one of the main ways of cognition. As a result, people tend to utilize visual content to capture and share their life experiences, which greatly facilitates the transfer of information. Meanwhile, it also increases the risk of privacy violations, e.g., an image or video can reveal different kinds of privacy-sensitive information. Scholars have persistently pursued the advancement of tailored privacy protection measures. Various surveys attempt to consolidate these efforts from specific viewpoints. Nevertheless, these surveys tend to focus on particular issues, scenarios, or technologies, hindering a comprehensive overview of existing solutions on a broader scale. In this survey, a framework that encompasses various concerns and solutions for visual privacy is proposed, which allows for a macro understanding of privacy concerns from a comprehensive level. It is based on the fact that privacy concerns have corresponding adversaries, and divides privacy protection into three categories, based on computer vision (CV) adversary, based on human vision (HV) adversary, and based on CV &amp; HV adversary. For each category, we analyze the characteristics of the main approaches to privacy protection, and then systematically review representative solutions. Open challenges and future directions for visual privacy protection are also discussed.

Enhancing the Recognition of Collinear Building Patterns by Shape Cognition Based on Graph Neural Networks

ABSTRACT Building patterns are important components of urban structures and functions, and their accurate recognition is the foundation of urban spatial analysis, cartographic generalization, and other tasks. Current building pattern recognition methods are often based on a shape index that can only characterize shape features from one aspect, resulting in significant errors. In this study, a building pattern recognition method based on a graph neural network is proposed to enhance shape cognition and focus on recognizing collinear patterns. First, a building shape classification model that integrates global shape and graph node structure features was constructed to quantitatively study shape cognition. Subsequently, a collinear pattern recognition (CPR) model was established based on a dual building graph. The shape cognition results were integrated into the model to enhance its recognition ability. The results show that the shape classification model can be used to effectively distinguish different shape categories and support building pattern recognition tasks. Based on the CPR model, false recognitions can be avoided, and recognition results similar to those of visual cognition can be obtained. Compared with the comparative methods, both models have significant advantages in terms of statistical results and implementation.

Visual discrimination learning in the Australian stingless bee Tetragonula carbonaria (Hymenoptera: Apidae)

AbstractKarl von Frisch's ground‐breaking research first demonstrated visual learning in the European honey bee (Apis mellifera). The study of Australian native bees and their cognitive abilities, however, is still a relatively new and emerging field. Here we examined visual cognition in the Australian stingless bee, Tetragonula carbonaria. First we tested for any colour preferences in T. carbonaria. Then we set stingless bees with three simple visual discrimination learning tasks using distinct colours (blue or yellow), oriented gratings (horizontal or vertical) and patterns (radial or concentric). In the colour preference task, we found evidence of a weak colour preference, with bees preferring colours blue and purple. In the visual discrimination task, T. carbonaria learned all three tasks in just 10 training trials. Bees learned equally well across the colour, orientation and pattern conditions, suggesting rapid visual learning. Future research should focus on closing knowledge gaps in Australian native bee cognition research, building upon the results of this study and exploring more complex non‐elemental learning.

Human visual clustering of point arrays.

Although the importance of unsupervised learning has been recognized since William James's "blooming, buzzing confusion," it has received less attention in the literature than supervised learning. An important form of unsupervised learning is clustering, which involves determining the groups of distinct objects that belong together. Visual clustering is foundational for ensemble perception, numerosity judgments, spatial problem-solving, understanding information visualizations, and other forms of visual cognition, and yet surprisingly few researchers have directly investigated this human ability. In this study, participants freely clustered arrays that varied in the number of points (10-40) and cluster structure of the stimuli, which was defined based on the statistical distribution of points. We found that clustering is a reliable ability: Participants' clusterings of the same stimulus on two occasions were highly similar. With respect to the objective properties of the clusterings that people produce, points of individual clusters tend to follow a Gaussian distribution. With respect to processing, we identified five visual attributes that characterize the clusters that participants draw-cluster numerosity, area, density, and linearity and also percentage of points on the convex hull. We also discovered evidence for sequential strategies, with some attributes dominating when drawing the initial clusters of a stimulus and others guiding the final clusters. Collectively, these findings offer a comprehensive picture of human visual clustering and serve as a foundation for the development of new models of this important ability. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Training vision in athletes to improve sports performance: a systematic review of the literature

ABSTRACT Sports vision training (SVT) refers to a training regimen designed to enhance visual skills that are essential for sports performance under the theory that such enhancement will lead to improved athletic performance. SVT regimens involve a variety of drills aimed at improving visual sensitivity, depth perception, tracking, reaction time, hand-eye coordination, and cognition important for success in sports. A growing body of empirical research has sought to develop and test SVT programs in athletes including training activities implemented in controlled, simulated, and naturalistic settings. This pre-registered, systematic review seeks to identify, describe, and evaluate the empirical literature addressing SVT. 126 articles were identified that tested SVT in athlete populations from many different sports and at all levels of achievement. While most studies reported improvements in generic and sports-specific visual abilities, and many also reported benefits in sports performance, the strongest evidence of performance improvements came from studies utilizing naturalistic training approaches where training activities were conducted with sports-specific stimuli or tasks. Despite this, relatively few studies used rigorous methods such as randomization, placebo-control, and blinding and therefore, while there is promising preliminary evidence in support of SVT, future studies will require improved methods and larger samples to move the field forward.

The Role of Body Image Perception, Social Media Influence, and Physical Activity on Eating Behavior among Malaysian Youth

The Role of Body Image Perception, Social Media Influence, and Physical Activity on Eating Behavior among Malaysian Youth

Expert and novice soccer goalkeepers’ visual perception: a practical-coaching approach eye-tracking

ABSTRACT One of the most important determinants of effectiveness in sports is a high level of visual perception as a leading decision-making factor. Two groups of soccer goalkeepers of 30 people each (A – seniors, 22.5 ± 2.25 years; B – novices, 15.40 ± 1.22 years) were studied. Eye-tracking glasses (Tobii Glasses 2) were used for the study. Three attempts were made to take a shot on goal in a fragment of a two-on-one play, after a pass and after a centring. Experienced (A) focused their gaze – after the pass – mainly on the ball, and in the next phase mainly on the striking foot. Novices (B) mostly directed their gaze first to the ball and foot, and in the last phase also to knee, shin and ground. Experienced (A) showed a longer fixation of their gaze on the attacker (taking a shot on goal) - (197.62 ms), compared to novices (B) (183.20 ms). The results of the study indicate that experienced goalkeepers show greater focus, composure on the object and better decision-making. Goalkeepers’ decision-making time is a factor that is important and constantly in need of researchers’ attention in order to achieve better sports performance. Therefore, similar studies should continue.

Dynamic Hybrid Visual-Thermal Multimodal Perception Neuromorphic Devices Based on Defect Modulation of Electrospun Nanofibers

Abstract Neuromorphic devices, inspired by the intricate architecture of the human brain, have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities. Vision, the primary mode of external information acquisition in living organisms, has garnered substantial scholarly interest. Notwithstanding numerous studies simulating the retina through optical synapses, their applications remain circumscribed to single-mode perception. Moreover, the pivotal role of temperature, a fundamental regulator of biological activities, has regrettably been relegated to the periphery. To address these limitations, we proffer a neuromorphic device endowed with multimodal perception, grounded in the principles of light-modulated semiconductors. This device seamlessly accomplishes dynamic hybrid visual and thermal multimodal perception, featuring temperature-dependent PPF properties and adaptive storage. Crucially, our meticulous examination of transfer curves, capacitance-voltage (C-V) tests, and noise measurements provides insights into interface and bulk defects, elucidating the physical mechanisms underlying adaptive storage and other functionalities. Additionally, the device demonstrates a variety of synaptic functionalities, including filtering properties, Ebbinghaus curves, and memory applications in image recognition. Surprisingly, the digital recognition rate achieves a remarkable value of 98.8%. These discernments furnish crucial insights for the prospective evolution of intricate neuromorphic systems.

New Plum Detection in Complex Environments Based on Improved YOLOv8n

To address the challenge of accurately detecting new plums amidst trunk and leaf occlusion and fruit overlap, this study presents a novel target detection model, YOLOv8n-CRS. A specialized dataset, specifically designed for new plums, was created under real orchard conditions, with the advanced YOLOv8n model serving as the base network. Initially, the CA attention mechanism was introduced to the backbone network to improve the model’s ability to extract crucial features of new plums. Subsequently, the RFB module was incorporated into the neck layer to leverage multiscale information, mitigating inaccuracies caused by fruit overlap and thereby enhancing detection performance. Finally, the original CIOU loss function was replaced with the SIOU loss function to further enhance the model’s detection accuracy. Test results show that the YOLOv8n-CRS model achieved a recall rate of 88.9%, with average precision scores of mAP@0.5 and mAP@0.5:0.95 recorded at 96.1% and 87.1%, respectively. The model’s F1 score reached 90.0%, and it delivered a real-time detection speed of 88.5 frames per second. Compared to the YOLOv8n model, the YOLOv8n-CRS exhibited a 2.2-percentage-point improvement in recall rate, alongside increases of 0.7 percentage points and 1.2 percentage points in mAP@0.5 and mAP@0.5:0.95, respectively. In comparison to the Faster R-CNN, YOLOv4, YOLOv5s, and YOLOv7 models, the YOLOv8n-CRS model features the smallest size of 6.9 MB. This streamlined design meets the demands for real-time identification of new plums in intricate orchard settings, providing strong technical backing for the visual perception systems of advanced plum-picking robots.

Design of Traditional Inkblot Pattern Plane System Based on Graphics and Visual Perception

In order to improve the graphic design effect of traditional pattern with ink and wash elements, this paper puts forward a graphic and visual perception-based graphic system design scheme of traditional pattern with ink and wash elements. Taking plane space media parameters, creative display patterns, characters and other elements as constraint parameters, this paper constructs a plane design model under traditional pattern fusion ink elements, extracts the graphic and visual perception element feature space structure of plane design graphics under traditional pattern fusion ink elements, and combines the three-dimensional internal structure characteristics of plane design graphics under traditional pattern fusion ink elements to carry out information reorganization. The method of color space color feature decomposition is used to decompose the visual elements of graphic design under traditional pattern fusion ink elements, and the virtual reconstruction model of graphic design under traditional pattern fusion ink elements and RGB-D image of visual perception element is established by the method of image aesthetic and emotional factors fusion. The feature recombination method of converting graphic design into materialized image is used to design the three-dimensional reconstruction model of graphic design under traditional pattern fusion ink elements. The 3D multi-viewpoint tracking and recognition method is adopted to reconstruct the graphic design and visual perception elements under the traditional pattern fusion ink elements, so as to improve the graphic design ability under the traditional pattern fusion ink elements. The simulation results show that this method has good visual expression ability, good graphic design effect, and good visual communication ability of graphic design with traditional pattern and ink elements.

A novel method for quantitative analysis of subjective experience reports: application to psychedelic visual experiences

IntroductionPsychedelic compounds such as LSD, psilocybin, mescaline, and DMT can dramatically alter visual perception. However, the extent to which visual effects of psychedelics consistently vary for different substances is an open question. The visual effects of a given psychedelic compound can range widely both across and within individuals, so datasets with large numbers of participants and descriptions of qualitative effects are required to adequately address this question with the necessary sensitivity.MethodsHere we present an observational study with narrative self-report texts, leveraging the massive scale of the Erowid experience report dataset. We analyzed reports associated with 103 different psychoactive substances, with a median of 217 reports per substance. Thirty of these substances are standardly characterized as psychedelics, while 73 substances served as comparison substances. To quantitatively analyze these semantic data, we associated each sentence in the self-report dataset with a vector representation using an embedding model from OpenAI, and then we trained a classifier to identify which sentences described visual effects, based on the sentences’ embedding vectors.ResultsWe observed that the proportion of sentences describing visual effects varies significantly and consistently across substances, even within the group of psychedelics. We then analyzed the distributions of psychedelics’ visual effect sentences across different categories of effects (for example, movement, color, or pattern), again finding significant and consistent variation.DiscussionOverall, our findings indicate reliable variation across psychedelic substances’ propensities to affect vision and in their qualitative effects on visual perception.

Decoding business analytics: discovering the hidden core through a novel taxonomy

PurposeThis study develops a comprehensive taxonomy of the business analytics (BA) discipline, uncovering its intellectual core and revealing its evolution over the past 12 years.Design/methodology/approachUsing stakeholder-driven identity formation theory, this study explores how organizational identity emerges through stakeholder negotiations. It investigates how top scholarly journals shape the BA discipline’s image and influence perceptions. High-quality articles from top journals listed by the Australian Business Deans Council are analyzed using latent Dirichlet allocation (LDA), a natural language processing and topic modeling method.FindingsThe study outlines key research areas identified as analytics methods, marketing, finance, operations and decision support analytics, along with 12 subareas. An analysis of the top 100 topics reveals prevalent research themes, showcasing the breadth of BA. A 12-year time-series review shows initial growth followed by maturation across most areas, except for decision support analytics, which maintained steady growth. These findings provide empirical evidence of BA’s development as a distinct discipline, highlighting its interdisciplinary nature and evolving research focus.Originality/valueThis study presents the first comprehensive, data-driven taxonomy of BA research, distilling the intellectual core into five key areas and 12 subareas, while identifying 100 supporting themes. It extends the stakeholders’ approach to identity development theory in the context of BA, providing empirical support for discussions on the field’s identity and diversity. The findings offer valuable insights for scholars, industries, managers and professionals, guiding curriculum development, research directions and practical applications of BA.

The potential role of retinal slip in National Football League (NFL) officiating and its effect on on-field decision making: mechanisms and countermeasures.

Visual processing involves numerous neuro-ophthalmic pathways that enable humans to perceive and interact with the world. These visual pathways can negatively impact visual perception and decision-making. The Vestibulo-Ocular Reflex (VOR) is a compensatory mechanism that stabilizes gaze on a target during head movement, such as running or turning. However, inadequate VOR stabilization can lead to retinal slip, reducing visual acuity. In the National Football League (NFL), officials require exceptional visual training and performance. NFL officiating utilize rapid visual processing, strategic movements, and precise judgement to make accurate penalty calls in real-time. Retinal slip can adversely affect play calling and penalty assessment by NFL officials. Despite these challenges, NFL officials achieve high precision and accuracy in up to 98.9% of plays. To maintain such high standards, the NFL has implemented a standardized curriculum to mitigate the effects of VOR and retinal slip. This manuscript outlines the basics of VOR function and explores countermeasures to minimize retinal slip in NFL officiating. We believe that these scientific endeavours can improve both penalty assessment accuracy and precision. The use of these general principles might also be potentially applicable to other sports.

Aging of visual word perception is related to decreased segregation within and beyond the word network in the brain

IntroductionWe investigated the neural correlates of cognitive decline in visual word perception from the perspective of intrinsic brain networks.MethodsA total of 19 healthy older adults and 22 young adults were recruited to participate in two functional magnetic resonance imaging (fMRI) sessions (one resting-state session and one for localizer tasks), along with a visual word perceptual processing task. We examined age-related alterations in resting-state functional connectivity (FC) within the word network, as well as between the word network and other networks. We tested their associations with behavioral performance in word and symbol-form processing.ResultsWe found that, compared to young adults, older adults exhibited increased FC between the two word-selective regions in the left and right ventral occipitotemporal cortex (vOT). Additionally, older adults exhibited increased FC between these two word-selective regions and non-word-selective regions. Notably, these FC alterations correlated with individual differences in behavioral performance in visual word perception.DiscussionThese results suggest that cognitive decline in visual word perception is associated with decreased segregation within and beyond the word network in the aging brain. Our findings support the neural dedifferentiation hypothesis for cognitive decline in visual word processing and improve our understanding of interactive neural specialization theory.