Natural Photographs Research Articles

Empathy strengthens the effect of emotion on beauty.

Past research shows that emotion affects beauty judgments of images and music. Because it is widely supposed that our faculty of empathy facilitates aesthetic experience, we wondered whether individual levels of empathy modulate the effect of emotion on beauty. 164 participants rated the perceived beauty, happiness, and sadness of 12 art images, 12 nature photographs, and 24 songs. The stimuli were presented in two blocks, and participants took the PANAS mood questionnaire before and after each block. Between blocks, they viewed one of three mood induction videos, intended to increase their happiness, increase their sadness, or leave their mood unchanged. We also measured (trait) empathy with the Questionnaire for Cognitive and Affective Empathy. We used structural equation modeling to analyze the effect of empathy on emotion, beauty, and the relationship between them. We assessed four emotion variables: participants' felt happiness and sadness (mood questionnaire ratings) and perceived happiness and sadness (stimulus ratings). We find that higher empathy is associated with stronger positive relationships between beauty and both felt and perceived emotions, for both images and music (β ~ 0.06 per empathy point on a 10-pt. scale, p < 0.001). We also find that perceived happiness and sadness boost beauty directly for both images and music. However, sadness affects music more than images (β = 0.51 vs. 0.12, all p < 0.001), and empathy amplifies this relationship for music but not images. Thus, felt and perceived emotions produce more beauty, more so in more empathic people, and more so with music than images.

Detecting Artificial Intelligence-Generated images via deep trace representations and interactive feature fusion

The detection of Artificial Intelligence-Generated (AIG) images plays an important role in verifying the authenticity and originality of digital images. However, recent advancements in state-of-the-art image generation methods have significantly challenged the ability to differentiate AIG images from natural photographs (NP). To address this issue, a novel approach based on deep trace representations and dual-branch interactive feature fusion is presented. Firstly, a global feature extraction module that leverages attention-based MobileViT (AT-MobileViT) is designed to learn the deep representations of the global trace information. Besides, we apply multiple enhanced residual blocks to extract discriminative multi-scale features. After that, a low-level feature extraction module incorporating a channel-spatial attention (CSA) block is also carefully employed to enhance the learning of trace representations. To facilitate the capture of complementary information between features, a dual-branch interactive feature fusion module is introduced by reshaping feature vectors into interactive matrices. By conducting experiments on both seen and unseen images, results demonstrate the better performance and robustness of the proposed method.

Impact of Dental Midline Shift on the Perception of Facial Attractiveness in Young Adults.

Background/Objectives: The aim of this study was to quantify the threshold of a dental midline shift that would compromise facial attractiveness and indicate a need for treatment from the points of view of laypeople and dental professionals. Methods: Whole-face natural photographs of a male and a female model were digitally manipulated to create various degrees of upper and lower dental midline shifts through bodily movement of the upper or lower midlines as well as alteration of the axial inclination of the upper teeth. The samples were then assessed by two groups of observers (laypeople (LP) and dental professionals (DP)). Results: The lower midline shift did not negatively affect the DP and LP's perceptions of smile attractiveness. The first significant loss of attractiveness was registered by the DP with an upper midline shift of 1 mm in the female model. However, the LP registered this at 2 mm. The DP registered the necessity of treatment at a threshold of 2 mm in the female model and 3 mm in the male model. LP identified the need for treatment at 3 mm for both males and females. The female model was judged more critically than her male counterpart by both female and male observers. Conclusions: DP assess the midline deviation more critically than LP. Both DP and LP were more sensitive to midline deviations in the female model regardless of their own gender. Both groups registered the need for treatment at a higher threshold than the reduction in smile attractiveness.

Knowing and experiencing the benefits: Factors influencing restoration evoked by nature photographs

Nature experiences improve various measures of human wellbeing. Even viewing nature photographs can lead to subjective restoration, as well as improvement in mood and cognitive function. To investigate how merely viewing images can promote such benefits, we investigated in three online studies whether knowledge about beneficial effects related to nature experiences predicts restoration after viewing nature photographs. Following a Pilot Study (N = 224) with limited conclusiveness, we used a between-subjects design in Study 1 (N = 490) and manipulated knowledge about physical and mental health effects related to nature experiences before participants viewed nature photographs and rated them for preference. In Study 1, we found small differences in preference compared to two of the control conditions and for restoration outcome compared to one of the control conditions. In Study 2 (N = 360), we varied between-subjects the assessment of outcome expectancy. Although the assessment itself did not predict restoration, for the respective sub-sample actual restoration was positively related to expected restoration. Moreover, measured knowledge about beneficial effects of nature and - even stronger - reported restorative effects of the participants’ last stay in nature positively predicted restoration evoked by the nature photographs. Overall, our results show that knowledge about beneficial effects of nature exposure can be predictive for restoration evoked by visual representations of nature. However, related factors, such as previous experiences and outcome expectancy, may play more important roles than factual knowledge.

Color Patterns And Enhanced Texture Learning For Detecting Computer-Generated Images

Abstract Detection of computer-generated (CG) images can reveal the authenticity and originality of digital images. However, recent cutting-edge image generation methods make it very difficult to distinguish CG images from natural photographs. In this paper, a novel method based on color patterns and enhanced texture learning is proposed to tackle this problem. We designed and implemented the backbone network with a separation-fusion learning strategy by constructing a multi-branch neural network. The luminance and chrominance patterns in dual-color spaces (RGB and YCbCr) are leveraged to achieve a robust representation of image differences. A channel-spatial attention module and a global texture enhancement module are also integrated into a backbone network to enhance the learning of inherent traces. Experiments on several commonly used benchmark datasets and a newly constructed dataset with more realistic and diverse images demonstrate that the proposed algorithm outperforms state-of-the-art competitors by a large margin.

Contact with nature through virtual reality and video: An effective solution for improving self-esteem in adults

Abstract It is widely acknowledged that exposure to natural environments offers emotional, cognitive, and behavioural benefits. However, some individuals may face difficulties in accessing these areas frequently and conveniently due to urbanisation, disability, or a lack of time. As a result, research has explored the advantages of nature substitutes, such as photographs, videos, or virtual reality (VR), and has demonstrated their ability to provide psychological benefits. Therefore, our study aims to examine the impact of these substitutes on enhancing individuals’ self-esteem. The study involved 236 participants, who were divided into six experimental groups based on the type of exposure (photographs, video, or virtual reality) and the environment (natural or urban). A control group was also exposed to geometric shapes. The participants completed the French version of the Rosenberg Self-Esteem Scale three times: upon arrival at the experimental room (baseline), after the rumination induction task (post-induction), and after exposure (post-exposure). The analysis focused on changes in self-esteem scores during the experimental study, considering the type of exposure and its content. The results suggest that exposure to nature, in any form, enhances self-esteem more than exposure to urban environments or geometric shapes. Additionally, it was found that virtual reality or video exposure to nature produced greater benefits than natural photographs. In the future, alternative tools may serve as valuable support for individuals who are unable to experience direct contact with nature. However, it is important to recognise that they should be considered as supplementary options rather than exclusive substitutes.

Record of Anoplocnemis phasianus (Fabricius, 1781) (Hemiptera, Heteroptera, Coreidae) from Goa, India

In the survey on diversity of Coreidae, Anoplocnemis phasianus (Fabricius, 1781) is recorded for the first time in the state of Goa. External morphology of A. phasianus is described with its present geographical distribution, taxonomic photo plate, host plants, and natural photographs of the nymphs and adults are provided.

A new resource for monitoring reef ecosystems: The background of recreational diver photographs contains valuable habitat data

Abstract Vast numbers of nature photographs are shared online on various social media and citizen science platforms, providing an important and growing source of ecological data. In addition to the focal subject, which provides species occurrence data, photographs often contain secondary information such as habitat captured incidentally in the background. Here, we test whether the background of underwater photographs taken by recreational divers can be used to monitor reef habitat composition by comparing them to photoquadrats from standardised scientific surveys at three locations in Sydney, Australia. Furthermore, we assessed the effect of different photographic styles (wide‐angle vs. close‐up) and photographic subjects (fish vs. gastropods) on the habitat captured. Over 90% of underwater photographs displayed habitat in the background demonstrating the considerable amount of data available within this unutilised resource. Overall, the habitat composition captured in the background of photographs was broadly similar to that recorded by standardised survey quadrats. Although significant differences between photographs and photoquadrats were detected for most habitats, the differences were small. Furthermore, we found the difference between the two methods could be reduced by using subsets of photographs; for example, fish photographs detected kelp habitat at a similar rate to photoquadrats. Synthesis and applications: The background of underwater photographs from recreational divers contains valuable data that can be used to monitor habitat taxa that are typically under‐represented. To reduce the potential for bias we recommend restricting photographs to a single photographic subject (e.g. fish), using wide‐angle photographs only and obtaining at least 50 photographs per site from different divers when using recreational photographs to assess changes in habitat‐forming species.

Color Polymorphism of Unfeathered Parts of the Great White Egret Ardea alba alba in Europe: An Analysis of the Internet Images

Polymorphism has been described in many avian taxa including Ardeidae. This study investigated the spatio-temporal distribution of color polymorphic forms (with regard to the color of the unfeathered parts (legs/lores)) of the Great White Egret Ardea alba alba in internet images from Europe. In total, 140 images of presumed polymorphs from 16 countries (from 2006 to 2021) have been collected and examined. Eight coloration schemes of visible unfeathered parts were distinguished. Since some polymorphs may represent the subspecies Eastern Great Egret Ardea alba modesta, the ratio of beak length to total head length was compared among individuals representing the nominal and Eastern Great Egret subspecies. The ratio distributions were similar in all compared groups; thus, polymorph egrets may represent both of these subspecies. Most polymorph images originate from the Netherlands and the southwestern Norwegian coast. This may have resulted from specific local diets and contact with hormone-disrupting compounds. Nevertheless, some observation biases, such as the presence of local breeding population or high numbers of nature photographers, could have affected our observation pattern. Some analyzed features also followed temporal patterns. Most polymorphs were observed during the breeding season, suggesting disruptions of sex hormones as a possible cause. Studies of spatio-temporal patterns of polymorph occurrence may allow us to obtain insights into the causes of large variation in coloration schemes in polymorphic species.

Nature Photographs as Complementary Care in Chemotherapy: A Randomized Clinical Trial.

This study aims to investigate the outcome of nature images on clinical symptom management related to chemotherapy. A randomized clinical trial was conducted in an outpatient cancer unit of a private hospital in Brazil, with 173 participants over the age of 18 who were undergoing chemotherapy and had signed an informed consent form. The intervention consisted of the presentation of a 12-min video featuring nature images categorized under the themes of Tranquility, Beauty, Emotions Up, or Miscellany. Images were sourced from the e-Nature Positive Emotions Photography Database (e-NatPOEM), a publicly available collection of affectively rated images. Sociodemographic and clinical data, as well as the participants' connection to nature, were investigated. The Positive Affect/Negative Affect Scale (PANAS) and the Edmonton Symptom Assessment System (ESAS) were applied pre- and post-intervention. Data showed very strong evidence of a reduction in negative affect for the intervention group (p < 0.001) and moderate evidence for the control group (p = 0.034). There was also a significant reduction in the intervention group for pain (p < 0.001), tiredness (p = 0.002), sadness (p < 0.001), anxiety (p < 0.001), and appetite (p = 0.001). The Beauty video had the best performance, while the Tranquility video showed no significant improvement in any of the symptoms evaluated. These findings suggest that images of nature may be a valuable tool to help control clinical and psychological symptoms in cancer patients undergoing chemotherapy.

Visual strategies of sustainability communication on corporate webpages. A critical multimodal discourse analysis in the hospitality sector

Anchored in the methodology of digital corporate communication, multimodal discourse analysis, legitimation and relevance theories, the research focuses on the contribution of images – photographs and logos– to sustainability meanings conveyed by the websites to the different stakeholders. The corpus analysis includes 330 images coming from the five hotel chains most sustainable according to the Sustainability Yearbook 2022. These images were downloaded manually from the English corporate websites and particularly from the sites with the header and sub-header related to sustainability. The research procedure was organized in three phases from a quantitative and qualitative perspective by answering the questions: “what do you see?”, “what should the images represent regarding sustainability issues?” and “how visual elements are utilized to convey the different dimensions of sustainability on web pages?”. The results obtained show that, on the one hand, the hotel chains preferred photographs of people in order to elicit people's dimension and humanize their image and, on the other hand, the photographs of nature that depict planet dimension and would be the expected, are in the third position. With sustainability communication as a complex area of investigation, the aim of this paper is twofold. On the one hand, it aims at contributing to the studies of sustainability communication from a multimodal perspective. On the other hand, it aims at strengthening and furthering a methodological tool to critically analyse the sustainability discourse as a multimodal digital discursive practice.

도시환경에서 자연의 시각적 자극 유형별 바이오필릭 효과

This study attempted to investigate the biophilic effect of nature’s visual stimulation when urban sounds exist in the background. For this purpose, human psychological changes by visual stimulus were investigated through experiments and user surveys. In addition, it was investigated whether nature’s visual stimulation has a biophilic effect that offsets urban auditory stimulation. Therefore, the experimental stimulation of this study can be divided into two types. Experimental stimulation A is a combination of actual photographs of nature and urban auditory Stimulation. Experimental stimulation B is a combination of natural patterns designed with natural motifs and urban auditory stimulation. The investigation tools for investigating the biophilic effect are Profile of Mood State (POMS) and Semantic Differential Meed (SD). As a result of the psychological response of natural visual stimuli, it can be judged that natural photographs, which are natural visual stimuli (a), have a positive (+) biophilic effect even when urban auditory stimuli are present together. Natural visual stimuli ((b), a pattern of nature, also improves the overall mood state even though urban stimulation exists together. Also, it is an element with a biophilic effect that makes you feel positive emotions, sincerity, comfort, and natural feelings. The two experimental stimuli, natural photographs, which are natural visual stimuli (a), and natural patterns, which are natural visual stimuli (b), differ by stimulus. However, both stimuli lower the mood of negative emotions and increase the mood of positive emotions to stabilize the whole. It also gives a sense of psychological stability by making you feel calm, comfortable, and natural. Therefore, it can be seen that both stimuli can have a biophilic effect that helps stress recovery. It also has the power to offset the city’s stimulus even though it is given the city’s auditory stimulus. It is expected to play an important role in providing psychological stability in urban interior design. In particular, in the case of natural visual stimulation (b), that is, designed natural visual stimulation, the effect has never been verified in previous studies. However, in this study, physiological and psychological experimental studies on natural patterns were conducted. Therefore, natural patterns are similar to natural photographs. It is meaningful because it has been verified that natural pattern design can also be helpful in stress recovery and stability.

When will AI misclassify? Intuiting failures on natural images.

Machine recognition systems now rival humans in their ability to classify natural images. However, their success is accompanied by a striking failure: a tendency to commit bizarre misclassifications on inputs specifically selected to fool them. What do ordinary people know about the nature and prevalence of such classification errors? Here, five experiments exploit the recent discovery of "natural adversarial examples" to ask whether naive observers can predict when and how machines will misclassify natural images. Whereas classical adversarial examples are inputs that have been minimally perturbed to induce misclassifications, natural adversarial examples are simply unmodified natural photographs that consistently fool a wide variety of machine recognition systems. For example, a bird casting a shadow might be misclassified as a sundial, or a beach umbrella made of straw might be misclassified as a broom. In Experiment 1, subjects accurately predicted which natural images machines would misclassify and which they would not. Experiments2 through 4 extended this ability to how the images would be misclassified, showing that anticipating machine misclassifications goes beyond merely identifying an image as nonprototypical. Finally, Experiment 5 replicated these findings under more ecologically valid conditions, demonstrating that subjects can anticipate misclassifications not only under two-alternative forced-choice conditions (as in Experiments 1-4), but also when the images appear one at a time in a continuous stream-a skill that may be of value to human-machine teams. We suggest that ordinary people can intuit how easy or hard a natural image is to classify, and we discuss the implications of these results for practical and theoretical issues at the interface of biological and artificial vision.

Level of attention mediates the association between connectedness to nature and aesthetic evaluations of photographs of nature.

Aesthetic experiences of nature are associated with beneficial psychological and behavioural outcomes. We investigated in a laboratory study whether an individual's level of connectedness to nature is associated with their aesthetic sensitivity to images of natural scenes, and whether the amount of attention allocated to the images mediated this association. Participants (N = 82) viewed 14 photographs depicting natural scenes and evaluated them on three aesthetic dimensions and completed the Connectedness to Nature (CN) and Openness to Experience (OtE) scales. CN positively predicted pleasure, beauty and aesthetic emotion, independently of OtE. The amount of attention participants paid to the images mediated the relationship between connectedness to nature and aesthetic pleasure, and connectedness to nature and beauty ratings. These findings extend our understanding by showing that attention is an important mechanism through which nature connectedness influences aesthetic responses of pleasantness and beauty in response to natural scenes. The findings have real-world implications as appreciation of the aesthetic qualities of nature is associated with a number of beneficial psychological outcomes.

CHARACTERIZATION AND NUTRITIONAL ANALYSIS OF CULTIVABLE WILD EDIBLE MUSHROOMS COLLECTED FROM DISTRICT AYODHYA (U.P.), INDIA

Holy city Ayodhya is situated at the bank of river Saryu and has a vast diversity of macrofungi, especially mushroom mycoflora. Some of which are excellently edible and cultivable. Characterization and nutritional composition of four selected cultivable naturally growing mushrooms viz. Agaricus bisporus, Pleurotus ostriatus, Volvariella volvacea and Calocybe indica from different sites of study area (Ayodhya) were evaluated. Macroscopic and microscopic characteristics expressed with natural photographs. The proximate analysis of nutritional values was done by encountering complete mushroom samples that were shade dried, powdered and processed. The macronutrients profiles revealed that the cultivable wild edible mushroom contains protein, carbohydrate, lipid, fiber and ash content ranged from 30.21-34.21%, 22.56-38.39%, 2.35-4.15%, 11.79-23.94% and 7.75-12.97% respectively on dry weight basis. Current study confirms that the selected cultivable wild edible mushrooms are a healthy and good source of food and major alternative source of protein. It also exposed the use of varieties of mushroom in their cultivation practice as well as diet to decrease malnutrition and increase socioeconomic values.

Automatic Computation of Meaning in Authored Images Such as Artworks: A Grand Challenge for AI

We discuss preliminary successes and major outstanding challenges in extracting messages, stories, morals, and especially meaning in crafted or “authored” images, such as artworks. Traditional semantic image understanding seeks to summarize an image (such as through a caption), or to answer basic questions expressed in free-text natural language, but can neither infer plausible reasons the creator made the artwork nor compute a high-level message or meaning it conveys. Such meaning is often abstract, dependent upon genre, period, and art movement, and exploits visual conventions such as special objects and signs (“signifiers”), composition, and possibly non-realistic style. Several of these properties have no counterpart in the natural photographs that are studied in most semantic image analysis, nor in the application-specific image analysis applied to robotics, autonomous driving, medical diagnosis, or remote sensing. For such reasons, the extraction of meaning from works in a variety of styles and subjects will be both a tool for art scholars and a grand challenge to artificial intelligence research.

"I Don't Do Religion": Using Nature Photographs to Engage Patients in Spiritual Reflection.

When caring for healthcare patients, professional chaplains may find an increasing proportion of individuals in the U.S. who do not identify as religious and who may benefit from creative approaches to discussing their spiritual and existential concerns. One approach to engaging patients is using a "third voice," as shared in a personal narrative in which a chaplain uses landscape photographs to engage a patient for discussion of spiritual and existential concerns. The content of the conversation may inform decisions about treatment, quality of life, and person-centered care.

Classifying and Mapping Cultural Ecosystem Services Using Artificial Intelligence and Social Media Data.

Quantifying and mapping cultural ecosystem services are complex because of their intangibility. Data from social media, such as geo-tagged photographs, has been proposed for mapping cultural use or appreciation of ecosystems. However, manual content analysis and classification of large numbers of photographs is time-consuming. The potential of deep learning for automating the analysis of crowdsourced social media content is still being explored in CES research. Here, we use a new deep learning model for automating the classification of natural and human elements relevant to CES from Flickr images. This approach applies a convolutional neural network architecture to analyze over 29,000 photographs from the Lithuanian coast and uses hierarchical clustering to group these photographs. The accuracy of the classification was assessed by comparison with manual classification. Over 37% of the photographs were taken for the landscape appreciation class, and 28% of the photographs were taken of nature, of animals or plants, which represent the nature appreciation class. The main clusters were identified in urban areas, more precisely in the main coastal cities of Lithuania. The distribution of the nature photographs was concentrated around particular natural attractions, and they were more likely to occur in parks and natural reserves with high levels of vegetation and animal cover. This approach that was developed for clustering the photographs was accurate and saved approximately 100 km of manual work. The method demonstrates how analyzing large numbers of digital photographs expands the analytical toolbox available to researchers and allows the quantification and mapping of CES at large geographical scales. Automated assessment and mapping of cultural ecosystem services could be used to inform urban planning and improve nature reserve management.

Worldwide Distribution of Antagonistic-Mutualistic Relationships Between Parrots and Palms

Palms, like all plants, show coevolutionary relationships with animals that have been traditionally categorized as mutualistic (seed dispersers and pollinators) or antagonistic (seed predators). This dual perspective, however, has prevented a full understanding of their true interactions with some animal groups, mainly those that do not ingest entire fruits. One clear example is parrots, which have been described to use palm species as feeding resources, while their role as seed dispersers has been largely neglected. Here, we combined fieldwork data with information from the literature and citizen science (i.e., naturalists and nature photographers) on parrot foraging ecology worldwide to evaluate the spatial and taxonomic extent of parrot-palm interactions and to identify the eco-evolutionary factors involved. We identified 1,189 interactions between 135 parrots and 107 palm species in more than 50 countries across the six realms where palms are present as natives or introduced. Combining this information, we identified 427 unique parrot-palm interacting pairs (i.e., a parrot species interacting with a palm species). Pure antagonistic interactions (i.e., parrots just preying on seeds or eating or destroying their non-reproductive parts) were less common (5%) than mutualistic ones (i.e., parrots benefiting by partially preying on the seed or fruit or consuming the pulp of the fruit or the flower but also contributing to seed dispersal and, potentially, pollination; 89%). After controlling for phylogeny, the size of consumed seeds and parrot body mass were positively related. Seed dispersal distances varied among palm species (range of estimated median dispersal distances: 9–250 m), with larger parrots dispersing seeds at greater distances, especially large fruits commonly categorized as megafauna anachronisms (&amp;gt;4 cm length). Although parrot-palm interactions are widespread, several factors (e.g., social behavior, predation fear, food availability, or seasonality) may affect the actual position of parrots on the antagonism-mutualism continuum for different palm species and regions, deserving further research. Meanwhile, the pervasiveness of parrot-palm mutualistic interactions, mainly involving seed dispersal and pollination, should not be overlooked in studies of palm ecology and evolution.

NFTs and Digital Art

NFTs and Digital Art