Royal Society Open Science最新文献

{"title":"Assessing bias in susceptible-infected-recovered estimation from aggregated epidemic data.","authors":"Naijian Shen, Lydia Bourouiba","doi":"10.1098/rsos.240526","DOIUrl":"10.1098/rsos.240526","url":null,"abstract":"<p><p>The canonical susceptible-infected-recovered (SIR) epidemic model is ubiquitous in assessing severity to guide interventions. It is typically applied to hierarchically aggregated data from distinct sub-regions. The introduced heterogeneity can lead to significant errors in estimated epidemic severity. We develop three analytical methods to extract SIR parameters from data, focusing on the reproduction number <math> <mstyle> <mrow><msub><mi>R</mi> <mrow><mn>0</mn></mrow> </msub> </mrow> </mstyle> </math> that quantifies epidemic wave severity/strength. The estimation methods are applied to synthetically aggregated incidence data formulated by summing two independent SIR solutions of distinct <math> <mstyle> <mrow><msub><mi>R</mi> <mrow><mn>0</mn></mrow> </msub> </mrow> </mstyle> </math> and separated by an onset delay, i.e. temporal offset. When applying the SIR model, we find that <math> <mstyle> <mrow><msub><mi>R</mi> <mrow><mn>0</mn></mrow> </msub> </mrow> </mstyle> </math> estimates from the aggregated data can underestimate or overestimate the constituent epidemic waves' <math><msub><mi>R</mi> <mn>0</mn></msub> </math> even when the prediction appears to agree well with the incidence data, resulting in an erroneous unimodal epidemic dynamics. We find that for two epidemic waves, the stronger the trailing wave, the longer the temporal offset that maintains apparent erroneous unimodal aggregated data. In the special case of two equivalent epidemic strengths, however, the weaker the waves, the longer the offset that maintains apparent unimodal aggregated data. We provide sensitivity analyses with respect to noise perturbation of the data and illustrate our approach using historical influenza data.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"240526"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detect+Track: robust and flexible software tools for improved tracking and behavioural analysis of fish.","authors":"Abhishek Dutta, Natalia Pérez-Campanero, Graham K Taylor, Andrew Zisserman, Cait Newport","doi":"10.1098/rsos.242086","DOIUrl":"10.1098/rsos.242086","url":null,"abstract":"<p><p>We introduce a novel video processing method called Detect+Track that combines a deep learning-based object detector with a template-based object agnostic tracker to significantly enhance the accuracy and robustness of animal tracking. Applied to a behavioural experiment involving Picasso triggerfish (<i>Rhinecanthus aculeatus</i>) navigating a randomized array of cylindrical obstacles, the method accurately localizes fish centroids across challenging conditions including occlusion, variable lighting, body deformation and surface ripples. Virtual gates between adjacent obstacles and between obstacles and tank boundaries are computed using Voronoi tessellation and planar homology, enabling detailed analysis of gap selection behaviour. Fish speed, movement direction and a more precise estimate of body centroid-key metrics for behavioural analyses-are estimated using optical flow method. The modular workflow is adaptable to new experimental designs, supports manual correction and retraining for new object classes and allows efficient large-scale batch processing. By addressing key limitations of existing tracking tools, Detect+Track provides a flexible and generalizable solution for researchers studying movement and decision-making in complex environments. A detailed tutorial is provided, together with all the data and code required to reproduce our results and enable future innovations in behavioural tracking and analysis.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"242086"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning reveals distinct gene expression signatures across tissue states in stony coral tissue loss disease.","authors":"Kelsey M Beavers, Daniela Gutierrez-Andrade, Emily W Van Buren, Madison A Emery, Marilyn E Brandt, Amy Apprill, Laura D Mydlarz","doi":"10.1098/rsos.241993","DOIUrl":"10.1098/rsos.241993","url":null,"abstract":"<p><p>Stony coral tissue loss disease (SCTLD) has rapidly degraded Caribbean reefs, compounding climate-related stressors and threatening ecosystem stability. Effective intervention requires understanding the mechanisms driving disease progression and resistance. Here, we apply a supervised machine learning approach-support vector machine recursive feature elimination-combined with differential gene expression analysis to describe SCTLD in the reef-building coral <i>Montastraea cavernosa</i> and its dominant algal endosymbiont, <i>Cladocopium goreaui</i>. We analyse three tissue types: apparently healthy tissue on apparently healthy colonies, apparently healthy tissue on SCTLD-affected colonies and lesion tissue on SCTLD-affected colonies. This approach identifies genes with high classification accuracy and reveals processes associated with SCTLD resistance, such as immune regulation and lipid biosynthesis, as well as processes involved in disease progression, such as inflammation, cytoskeletal disruption and symbiosis breakdown. Our findings support evidence that SCTLD induces dysbiosis between the coral host and Symbiodiniaceae and describe the metabolic and immune shifts that occur as the holobiont transitions from healthy to diseased. This supervised machine learning methodology offers a novel approach to accurately assess the health states of endangered coral species, with potential applications in guiding targeted restoration efforts and informing early disease intervention strategies.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"241993"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A data-driven supervised machine learning approach to estimating global ambient air pollution concentrations with associated prediction intervals.","authors":"Liam Jordan Berrisford, Hugo Barbosa, Ronaldo Menezes","doi":"10.1098/rsos.241288","DOIUrl":"10.1098/rsos.241288","url":null,"abstract":"<p><p>Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps due to issues such as power outages. In response, we have developed a scalable, data-driven, supervised machine learning framework. The models produced by the framework are designed to impute missing temporal and spatial measurements, thereby generating a comprehensive dataset for air pollutants including NO₂, O₃, PM₁₀, PM₂.₅ and SO₂. In this work, we produce models providing concentration estimations at 261 377 locations across the globe. The dataset, with a fine granularity of 0.25° spatial resolution at hourly time intervals and accompanied by prediction intervals for each estimate, caters to a wide range of stakeholders relying on outdoor air pollution data for downstream assessments. This enables more detailed studies. Additionally, the model's performance across various geographical locations is examined, providing insights and recommendations for strategic placement of future monitoring stations to further enhance the model's accuracy.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"241288"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289206/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prominent fin-contributed swimming in squid (<i>Loligo forbesii</i>) supports efficient movement in seamount habitats.","authors":"Seth Cones, Nathan Formel, Jorge Fontes, Pedro Afonso, K Alex Shorter, Gonçalo Graça, C Robert Priester, Diya Das, T Aran Mooney","doi":"10.1098/rsos.250321","DOIUrl":"10.1098/rsos.250321","url":null,"abstract":"<p><p>Animal movements and the associated energy costs dictate an individual's scope for activity and habitat use. Yet <i>in situ</i> measurements of movement often fail to quantify whole-body movement and their physiological costs. These challenges lead to data gaps connecting how movement behaviours and energy output interact to constrain species' biogeography. Here we combined swim tunnel respirometry and multi-positional field biologging data to estimate the energy output of squid (<i>Loligo forbesii</i>), an ecologically key marine invertebrate. Laboratory respirometry experiments revealed a strong correlation between body mass and metabolic rate during fin-contributed swimming, enabling energy cost estimates in the wild. Free-ranging squid enacted dynamic and diverse fin and jet swimming that varied on short time scales. Animals largely selected (66%) low-amplitude fin-contributed movements where fin waves propagated metachronally. Higher amplitude fin and jet movements were rare, accounting for 4% of time budgets. Application of the bioenergetic model on naturally exhibited behaviours estimated that animals consumed 3117 ± 532 mg O₂ per day to fuel the predominant metachronal fin movements, an expenditure energetically comparable to that of similar-niche fishes. These unique data reveal substantial behavioural flexibility and indicate squid prefer low-cost movement behaviours that may enable squids' high growth rates and successful competition with fishes.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"250321"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289209/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of summer weather and heatwaves on wild boar activity.","authors":"Justine Güldenpfennig, Niccolò Fattorini, Miloš Ježek, Kevin Morelle, Tomasz Podgórski","doi":"10.1098/rsos.242208","DOIUrl":"10.1098/rsos.242208","url":null,"abstract":"<p><p>Climate change threatens wildlife species, negatively affecting their fitness through environmental change, such as through increased severity of droughts and summer heatwaves. Wild boar (<i>Sus scrofa</i>), a species with limited physiological thermoregulation abilities, is potentially vulnerable to high temperatures during summer. Yet little is known about the behavioural reactions of this species to heat stress. Detailed understanding of wild boar behavioural adaptations to their environment might help understand their future population growth and change in the geographical range. We used multisensory collars on 24 individual wild boars in the Czech Republic, calculating the dynamic body acceleration as a proxy for energy expenditure to detect activity changes in response to high temperatures on two temporal scales (daily and seasonal) and during heatwaves. Our results revealed that overall, under higher temperatures, wild boars reduce their activity, unless it rained. Heatwave duration did not affect wild boar activity. We show that wild boars adapt their activity to weather conditions and highlight the importance of sufficient precipitation for thermoregulation in this species. This suggests that studies about climate change impacts on wildlife behaviour should consider not only rising temperatures but also shifts in rainfall patterns. Additionally, this research shows the potential of remote-sensing technologies to monitor wildlife behaviour, particularly in challenging observational scenarios, offering valuable insights into the behavioural responses of wildlife in the face of a changing climate.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"242208"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of vection on the use of optic flow cues.","authors":"Meaghan McManus, Katja Fiehler","doi":"10.1098/rsos.250364","DOIUrl":"10.1098/rsos.250364","url":null,"abstract":"<p><p>When we move objects move past us in a relative pattern of motion referred to as optic flow. Modulations in optic flow can impact both our perception of self-motion (e.g. perceived distance travelled) and our feeling of self-motion, referred to as vection (e.g. speed of self-motion). The perception and feeling of self-motion have so far been studied independently, leaving open whether and how the two relate to each other. In the current study, stationary participants performed a self-motion task in virtual reality where they moved to previously indicated distances using constant velocity optic flow. The perception of self-motion was measured as the ratio between the distance to travel and the distance travelled, where stopping sooner indicates that the optic flow cues were more effective in creating the perception of self-motion. Vection experience was measured via a questionnaire. When participants felt vection, there was a correlation between stopping distance (reflecting the perception of self-motion) and the felt speed of vection (reflecting the feeling of self-motion), i.e. the faster participants felt they were moving the sooner they stopped. These results show that the perception and feeling of self-motion are linked and that treating the two concepts independently can lead to misinterpretations.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"250364"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural, optical and biological characterization of a new cobalt-based mixed halide hybrid compound: insights from DFT and vibrational analysis.","authors":"Iteb Ben Mahmoud, Naoufel Ben Hamadi, Sandra Walha, Nourhene Zammel, Ali Ben Ahmed, Ahlem Guesmi, Wesam Abd El-Fattah, Ferdinando Costantino, Houcine Naïli","doi":"10.1098/rsos.250485","DOIUrl":"10.1098/rsos.250485","url":null,"abstract":"<p><p>A novel cobalt-based hybrid compound, bis(4-dimethylaminopyridinium)bromo-chlorocobaltate(II) (C₇H₁₁N₂)₂[CoBr_2.28Cl_1.72] (1), was successfully synthesized via a slow evaporation method at room temperature. The crystalline material was thoroughly characterized using single-crystal X-ray diffraction, Hirshfeld surface analysis, Fourier transform infrared (FT-IR) and Raman spectroscopy, UV-Vis optical absorption, thermal analysis and theoretical density functional theory (DFT) calculations. Crystallographic analysis revealed that compound (1) crystallizes in the centrosymmetric monoclinic space group <i>C</i>2/<i>c</i>, featuring discrete [CoBr_2.28Cl_1.72]^2- anions and protonated amine cations (C₇H₁₁N₂)⁺. These units are interconnected via an extensive network of N-H···Br/Cl and C-H···Br/Cl hydrogen bonds, stabilizing the crystal lattice. Thermal analysis indicated a significant phase transition at approximately 203°C, underscoring the thermal responsiveness of the structure. Spectroscopic techniques highlighted the vibrational characteristics of key functional groups, and DFT calculations offered further insights into electronic and structural properties. Biological evaluation demonstrated that compound (1) possesses notable antimicrobial activity, particularly against <i>Escherichia coli</i>, <i>Staphylococcus aureus</i> and <i>Bacillus subtilis</i>, with inhibition zones ranging from moderate to strong depending on the microorganism tested. Additionally, the compound exhibited promising antioxidant capacity in 1,1-diphenyl-2-picrylhydrazyl (DPPH) assays, moderate α-amylase inhibition indicative of anti-diabetic potential and measurable anti-inflammatory effects. These findings suggest that compound (1) is a multifunctional material with potential applications in biomedical and pharmaceutical fields.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"250485"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic effects of micro- and macro-sized palm kernel shell fillers on the tensile properties of HDPE composites.","authors":"Abdul-Manan Kayaba, Obed Issakah, Stefania Akromah, E E Nettey-Oppong, Eric Kwame Anokye Asare","doi":"10.1098/rsos.241911","DOIUrl":"10.1098/rsos.241911","url":null,"abstract":"<p><p>In this study, high-density polyethylene (HDPE) composites reinforced with palm kernel shell (PKS) fillers with mixed particle sizes were prepared using melt-extrusion compounding. A 5-ton hydraulic hot-press machine was employed to fabricate samples for tensile testing, with a focus on understanding the influence of varying filler sizes on the mechanical properties of the HDPE/PKS composite. The 30 wt% PKS composites demonstrated an elastic modulus (E) of 1.08GPa, ultimate tensile strength (UTS) at 14.13MPa, yield strength at 8.6MPa, stress at failure 12.87MPa, and elongation at failure 5.16%. However, the incorporation of larger PKS particles (PKSL) had a detrimental effect on the tensile properties, with increasing PKSL content leading to significant reductions in tensile properties. For example, for 7.5 wt% PKSL, E decreased by approximately 18%, yield strength by 37%, UTS by 24%, stress at failure by 29%, and total elongation by 62%. Similar trends were observed for the composites containing 15 wt% and 22.5 wt% PKSL. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were employed to assess the melting temperature ranges and thermal stability of the composites, respectively. Scanning electron microscopy (SEM) provided insights into the failure mechanisms, revealing weak filler-matrix interfacial bonding with larger particles, resulting in debonding and ultimately compromising the tensile properties of the composite.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"241911"},"PeriodicalIF":2.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144708615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning for predicting the occurrence of tipping points.","authors":"Chengzuo Zhuge, Jiawei Li, Wei Chen","doi":"10.1098/rsos.242240","DOIUrl":"10.1098/rsos.242240","url":null,"abstract":"<p><p>Tipping points occur in many real-world systems, at which the system shifts suddenly from one state to another. The ability to predict the occurrence of tipping points from time series data remains an outstanding challenge and a major interest in a broad range of research fields. Particularly, the widely used methods based on bifurcation theory are neither reliable in prediction accuracy nor applicable for irregularly sampled time series which are commonly observed from real-world systems. Here, we address this challenge by developing a deep learning algorithm for predicting the occurrence of tipping points in untrained systems, by exploiting information about normal forms. Our algorithm not only outperforms traditional methods for regularly sampled model time series but also achieves accurate predictions for irregularly sampled model time series and empirical time series. Our ability to predict tipping points for complex systems paves the way for mitigation risks, prevention of catastrophic failures and restoration of degraded systems, with broad applications in social science, engineering and biology.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"12 7","pages":"242240"},"PeriodicalIF":2.9,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12303098/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144733044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}