Deep Learning for Automatic Detection and Facial Recognition in Japanese Macaques: Illuminating Social Networks

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research offered new methodological perspectives through automatization of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identifications done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques' face detector (Faster-RCNN model), reaching a 82.2% accuracy and (ii) the creation of an individual recognizer for K{\=o}jima island macaques population (YOLOv8n model), reaching a 83% accuracy. We also created a K{\=o}jima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this innovative approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques

Linking parasitism to network centrality and the impact of sampling bias in its interpretation

Group living is beneficial for individuals, but also comes with costs. One such cost is the increased possibility of pathogen transmission because increased numbers or frequencies of social contacts are often associated with increased parasite abundance or diversity. The social structure of a group or population is paramount to patterns of infection and transmission. Yet, for various reasons, studies investigating the links between sociality and parasitism in animals, especially in primates, have only accounted for parts of the group (e.g., only adults), which is likely to impact the interpretation of results. Here, we investigated the relationship between social network centrality and an estimate of gastrointestinal helminth infection intensity in a whole group of Japanese macaques (Macaca fuscata). We then tested the impact of omitting parts of the group on this relationship. We aimed to test: (1) whether social network centrality –in terms of the number of partners (degree), frequency of interactions (strength), and level of social integration (eigenvector) –was linked to parasite infection intensity (estimated by eggs per gram of faeces, EPG); and, (2) to what extent excluding portions of individuals within the group might influence the observed relationship. We conducted social network analysis on data collected from one group of Japanese macaques over three months on Koshima Island, Japan. We then ran a series of knock-out simulations. General linear mixed models showed that, at the whole-group level, network centrality was positively associated with geohelminth infection intensity. However, in partial networks with only adult females, only juveniles, or random subsets of the group, the strength of this relationship - albeit still generally positive - lost statistical significance. Furthermore, knock-out simulations where individuals were removed but network metrics were retained from the original whole-group network showed that these changes are partly a power issue and partly an effect of sampling the incomplete network. Our study indicates that sampling bias can thus hamper our ability to detect real network effects involving social interaction and parasitism. In addition to supporting earlier results linking geohelminth infection to Japanese macaque social networks, this work introduces important methodological considerations for research into the dynamics of social transmission, with implications for infectious disease epidemiology, population management, and health interventions

Genes, social transmission, but not maternal effects influence responses of wild Japanese macaques (Macaca fuscata) to novel-object and novel-food tests

Using long-term maternal pedigree data, microsatellite analysis, and behavioral tests, we examined whether personality differences in wild Japanese macaques (Macaca fuscata) are associated with additive genetic effects, maternal influences, or belonging to a particular social group. Behaviors elicited by novel-object tests were defined by a component related to caution around novel-objects (Ob-PC1) and behaviors elicited by novel food-tests were defined by correlated components related to consummatory responses (Fo-PC1) and caution around novel foods (Fo-PC2). The repeatability of Ob-PC1 was modest and not significant; the repeatabilities of Fo-PC1 and Fo-PC2 were moderate and significant. Linear mixed effects models found that sex, age, sex × age, provisioning, trial number, date, time of day, season, and distance to the closest monkey were not related to personality. Linear mixed effects models of females older than 2 years found that high rank was associated with greater caution around novel objects. Linear models were used to determine whether sex, age, group membership, maternal kinship, or relatedness had independent effects on the personality similarity of dyads. These analyses found that pairs of macaques that lived in the same group were less similar in their caution around novel objects, more closely related pairs of macaques were more similar in their tendency to eat novel food, and that pairs of macaques in the same group were more similar in how cautious they were around novel foods. Together, these findings suggest that personality in this population of wild monkeys was driven by rank, genetic effects, and group effects, the latter possibly including the need to exploit different niches in the environment

Deep Learning for Automatic Detection and Facial Recognition in Japanese Macaques: Illuminating Social Networks

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research offered new methodological perspectives through automatization of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identifications done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques’ face detector (Faster-RCNN model), reaching a 82.2% accuracy and (ii) the creation of an individual recognizer for Kōjima island macaques population (YOLOv8n model), reaching a 83% accuracy. We also created a Kōjima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this innovative approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques

Treatment with silver nitrate versus topical steroid treatment for umbilical granuloma: A non-inferiority randomized control trial

<div><p>Objective</p><p>The aim of this prospective multicenter randomized controlled trial was to compare the efficacy of silver nitrate cauterization against that of topical steroid ointment in the treatment of neonatal umbilical granuloma.</p><p>Methods</p><p>An open-label, non-inferiority randomized controlled trial was conducted from January 2013 to January 2016. The primary endpoint for the silver nitrate cauterization and topical steroid ointment groups was the healing rate after 2 weeks of treatment, applying a non-inferiority margin of 10%. The healing rate was evaluated until completion of 3 weeks of treatment.</p><p>Results</p><p>Participants comprised 207 neonates with newly diagnosed umbilical granuloma, randomized to receive silver nitrate cauterization (n = 104) or topical steroid ointment (n = 103). Healing rates after 2 weeks of treatment were 87.5% (91/104) in the silver nitrate cauterization and 82% (82/100) in the topical steroid ointment group group. The difference between groups was -5.5% (95% confidence interval, -19.1%, 8.4%), indicating that the non-inferiority criterion was not met. After 3 weeks of treatment, the healing rate with topical steroid ointment treatment was almost identical to that of silver nitrate cauterization (94/104 [90.4%] vs. 91/100 [91.0%]; 0.6% [-13.2 to 14.3]). No major complications occurred in either group.</p><p>Conclusions</p><p>This study did not establish non-inferiority of topical steroid ointment treatment relative to silver nitrate cauterization, presumably due to lower healing rates than expected leading to an underpowered trial. However, considering that silver nitrate cauterization carries a distinct risk of chemical burns and that the overall efficacy of topical steroid ointment treatment is similar to that of silver nitrate cauterization, topical steroid ointment might be considered as a good alternative in the treatment of neonatal umbilical granuloma due to its safety and simplicity. To clarify non-inferiority, a larger study is needed.</p></div

Baseline characteristics of patients.

<p>Baseline characteristics of patients.</p

CONSORT flow diagram.

<p>Progression of patients through the trial up to 3 weeks of treatment in all participating centers. No patients dropped out due to adverse events in either group.</p