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New species and records of Cytospora (Cytosporaceae, Diaporthales) from tree branches in Hebei Province, China
No full textSpecies of Cytospora have been commonly reported as plant pathogens with wide host ranges and geographic distributions. In this study, ten strains of this genus were isolated from branches collected in Hebei Province, China. They were identified based on a multi-locus phylogeny of ITS, act, rpb2, tef1-α, and tub2 genes, along with morphological characters. As a result, they were identified as six species, including five known species (C. ampla, C. pseudochrysosperma, C. sophoricola, C. sorbariae, and C. yinchuanensis) and one new species (C. hebeiensis). Among the known species, C. ampla, C. sorbariae, and C. yinchuanensis were newly discovered on Malus spectabilis; C. pseudochrysosperma was newly discovered on Salix matsudana; and C. sophoricola was newly discovered on Caragana microphylla. The results enrich the diversity of Cytospora species associated with tree canker and dieback diseases in Hebei Province, China
A synoptic account of flora in the National Wetland Park of the Alpine Permafrost Zone, Jimunai, Xinjiang
No full textThe alpine periglacial wetland, situated near the alpine snow belt, represents one of the most extreme wetland ecosystems. The National Wetland Park in the Jimunai alpine periglacial zone, Xinjiang, China, is located within the the Mus Island glacier region and harbours rich plant diversity shaped by its unique geography and environment. In this study, we present an updated checklist of vascular plant of the Park based on a comprehensive literature review, including specimen analysis, database retrieval and field surveys. The revised checklist includes 372 species, 179 genera and 46 families, reflecting a significant increase of 158 species, 45 genera and two families compared to previous records. Notably, the updated list identifies 20 rare and endangered species, four endemic plants of Xinjiang and 23 species newly recorded for the local area. These findings enhance the floristic knowledge of the Jimunai alpine periglacial zone and highlight previously overlooked plant diversity in this extreme habitat. This updated inventory will serve as an essential foundation for further biodiversity research and will be instrumental in guiding effective conservation efforts for this distinct alpine periglacial wetland.The revised checklist includes 372 species, 179 genera and 46 families, reflecting a significant increase of 158 species, 45 genera and two families compared to previous records. Notably, the updated list identifies 20 rare and endangered species, five endemic plants of Xinjiang and 23 species newly recorded for the local area. These findings enhance the floristic knowledge of the Jimunai alpine periglacial zone and highlight previously overlooked plant diversity in this extreme habitat
The genus Psilocybe in Italy
No full textIn the absence of specific studies on the Psilocybe genus in Italy, we provide information on the taxonomy, habitat, ecology, and distribution of the nine taxa currently recorded for Italy. A nomenclatural update of Psilocybe taxa reported in the Checklist of Italian Fungi (Basidiomycetes), published in 2005, is provided and seven scientific binomials are confirmed. In addition, P. medullosa and P. serbica, recently found in Trentino-Alto Adige/ Südtirol and Calabria respectively, are added to the list of taxa of the genus Psilocybe in Italy. Data on distribution and ecological categories of each taxon are also reported together with a molecular analysis. Considering how easily Psilocybe species can be found in Italy and their psilocybin and psilocin content, the authors hope that Italy will also legalize the use of psychedelic mushrooms in clinical therapies, as already permitted in many other countries
Global population genomics redefines domestication and clinical diversity in the Aspergillus flavus–oryzae complex
No full textAspergillus flavus is a globally important human pathogen and agricultural contaminant, while its domesticated relative A. oryzae is widely used in food fermentation and biotechnology. Despite their importance, the evolutionary relationship, population structure and domestication history of these fungi remain unresolved. Here, we present the first global population genomic analysis of 639 A. flavus and A. oryzae isolates from clinical, environmental and food-fermentation sources across multiple continents. Our analyses reveal a complex evolutionary landscape comprising well-separated clades interspersed with highly admixed mosaic groups and potential evidence for multiple independent domestication events giving rise to A. oryzae. Clinical A. flavus isolates are distributed across several clades and mosaic groups, some overlapping with fermentation strains, highlighting an apparent role of domestication and admixture in shaping pathogen diversity. These results challenge current species boundaries and provide a framework for understanding evolutionary history, taxonomy and pangenomic architecture in these fungi, with broad implications for pathogenicity, food safety, biocontrol and metagenomic surveillance
Virtual reality and biofeedback in surgical training: a review and proposal for comparative study between novice and experienced surgeons
No full textVirtual reality (VR) is increasingly adopted in surgical education as a safe and controlled environment for developing technical and non-technical skills. Parallel to this, physiological biofeedback has emerged as a promising method for assessing stress, workload, and cognitive performance during complex tasks. This review explores the current evidence on VR and biofeedback in surgical training, highlighting their synergistic potential. We discuss how VR simulations replicate operative scenarios with high fidelity and how biofeedback parameters such as heart rate variability and galvanic skin response can provide objective insights into surgeon performance and stress regulation. We then outline a pilot study design in which novice and experienced surgeons are placed in a VR operating room scenario, with biofeedback metrics recorded. We hypothesise that experienced surgeons will demonstrate more stable physiological responses and superior task performance, reflecting greater resilience and expertise. Such findings could inform adaptive, personalised training models that adjust difficulty levels or provide targeted feedback in real time. Integrating VR and biofeedback into surgical education has the potential to enhance skill acquisition, improve stress management, and bridge the gap between simulation and the operating room
Wetland classification and revitalisation monitoring by using drone data
No full textWetlands are essential ecosystems increasingly threatened by human activities and climate change. This study presents a method for classifying and monitoring wetland habitats in the Čiližská Radvaň protected area (Slovak Republic) using RGB drone imagery and the Natural Numerical Network (NatNet), a mathematically based supervised deep learning approach. The primary aim was to evaluate the effectiveness of NatNet in identifying target habitat types and to assess the impact of ongoing revitalisation efforts. Habitat types were classified using RGB drone imagery and ground-truth training polygons that represented the dominant vegetation communities in Čiližská Radvaň wetland. The NatNet achieved the training classification success rate exceeding 97%, allowing the creation of relevancy maps successfully identifying spatial habitat distribution. Relevancy maps verified in the field reached classification accuracy of 0.88 and F1 score of 0.90 across all habitats together. Results showed observable shifts in habitat extent and structure after one year of restoration, confirming the suitability of the method for detecting ecological changes in wetland environments
Using NatureCounts to Support the Kunming-Montreal Global Biodiversity Framework in Canada
No full textTargets 20 and 21 of the Kunming-Montreal Global Biodiversity Framework establish that access to good data and innovative data products are crucial to halting and reversing biodiversity loss, and that biodiversity data access has implications for all targets of the framework. Birds Canada’s NatureCounts platform*1 seeks to meet these needs by supporting easy and accurate data collection, interpreting data to produce meaningful knowledge and data products, and sharing data according to the FAIR principles (Findable, Accessible, Interperable, Reusable) to support conservation action and policy.NatureCounts supports the collection of robust biodiversity data by professional and volunteer-based monitoring programs. The NatureCounts mobile app and web interface are customizable data collection solutions that integrate standardized data from the field directly into a sharing-ready repository using a standardized schema. The flexible architecture accommodates nearly any monitoring protocol, while a user-friendly interface, unique tools, and instantaneous data upload incentivize adoption, encouraging FAIR data participation by projects of all types and sizes.Data collected using these tools are uploaded to the NatureCounts database. Hosting over 250 million records, this massive repository holds endless potential for conservation applications. Tools including an online data explorer and R package facilitate easy data access by researchers and conservationists. Flexible data access permissions support the security of sensitive records and Indigenous data sovereignty. Various data products support research and conservation, and directly address the targets of the Global Biodiversity Framework. For example, a dedicated workflow underpins the process of identifying Canada’s Key Biodiversity Areas—spaces designated as vital to the conservation of biodiversity in Canada—in accordance with Target 3. Another uses the data to set and evaluate federal population goals for Canada’s birds for the federal government, integrating biodiversity into decision making as per Target 14. A third feeds data directly into the Canadian process for identifying endangered species, addressing extinction risk as specified in Target 4 and seamlessly connecting data collection to policy. NatureCounts also processes over 9000 requests for raw data yearly by the conservation community. Users query and filter the data, then access them either through a browser-based download portal or the dedicated naturecounts R package.*2 To help NatureCounts data users interpret raw data, the Birds Canada GitHub page*3 contains publicly available repositories and documents that detail workflows for processing and analyzing data accessed through NatureCounts. These well-documented, tested, and easily shared repositories ensure reproducible research practices. To date, data from NatureCounts have supported over 4200 scientific publications and an immeasurable amount of unpublished work. Data from NatureCounts are used for species assessments, land use planning, impact assessment, academic research, climate change mitigation, and much more, allowing data from NatureCounts to be used in pursuit of nearly every target in the framework. Through the ongoing development of NatureCounts, Birds Canada aims to fulfill the goals of the Kunming-Montreal Global Biodiversity Framework, and make measurable progress for biodiversity in Canada
Unpacking Data Quality in Citizen Science: An Analysis of City Nature Challenge India
No full textThe City Nature Challenge (CNC) has rapidly expanded across India from 2023 to 2025, leading to a surge in biodiversity observations on iNaturalist. While the volume of data is impressive, its long-term research and conservation value depends heavily on data quality (Vattakaven et al. 2022)—particularly the proportion of observations reaching "Research Grade" (RG). This study investigates patterns and barriers related to RG achievement in CNC India observations over three consecutive years using iNaturalist data (iNaturalist Community 2023, iNaturalist Community 2024, iNaturalist Community 2025).We analyze RG percentages at regional, state, and city scales, comparing the total number of observations year by year (Fig. 1). By tracking these metrics from 2023 to 2025, we quantify the "identification lag" (Fig. 2)—the gap between data quantity (uploads) and data quality (verified records). Our analysis identifies whether growth is driven solely by participation or if it is supported by a parallel increase in expert identification (Fig. 3). In addition to temporal (year-wise) comparisons, we also investigate spatial (geographical) variations in data quality across India.We also identify taxa and locations with disproportionately high numbers of "Needs ID" observations (which are not yet considered as RG; Fig. 4). This analysis is conducted both horizontally—i.e., comparing taxonomic groups (such as, Plantae, Fungi, Animalia, Insecta), and vertically—i.e., comparing taxonomic rank (such as, family, genus, species). This approach helps us to evaluate whether these bottlenecks stem from inherent identification challenges, observer behavior, or a lack of specialized taxonomic expertise within the local identifier community.Our results indicate a widening gap between upload volume and RG attainment (Fig. 2), particularly in high-performing regions. This disparity is most acute for taxa requiring specialized expertise and for observations at the species level. These findings offer practical insights for enhancing community engagement, directing expert identification efforts, and designing support mechanisms for new observers.By providing a nuanced perspective on the evolution of data quality within a massive, volunteer-driven dataset, this presentation contributes to broader discussions on sustaining and improving the living data ecosystems that support contemporary biodiversity science
Development of Reliable Access Control Mechanisms Using Artificial Intelligence for Corporate Data Protection
No full textThe study aims to analyse the vulnerabilities of traditional access control methods and define optimization objectives, constraints, and decision-making processes based on data for the effective implementation of artificial intelligence to enhance corporate data protection. The research methodology addressed various approaches, including machine learning, user behaviour analysis and neural networks, and data protection methods such as anonymisation, encryption and federated learning. Traditional access control methods, such as passwords, biometrics and multi-factor authentication, were discussed, as well as their shortcomings, including vulnerability to data breaches, phishing attacks and infrastructure threats. The use of artificial intelligence to strengthen access control mechanisms, such as machine learning, user behaviour analysis and neural networks, was emphasised. Artificial intelligence significantly improves security by enabling the analysis and processing of large amounts of data, detecting anomalies and predicting threats based on the analysis of user behaviour and biometric data. The study also examined methods of protecting data used to train artificial intelligence, including anonymisation, differential privacy, encryption and federated learning. Privacy issues the risks of data leakage when using artificial intelligence and the need to comply with ethical norms and standards were addressed. The successful integration of AI-oriented solutions into corporate security systems in various industries, including the financial sector, healthcare, and retail, is presented. Evaluating the effectiveness of artificial intelligence in access control systems is based on indicators such as the speed of the system’s response to changes in user behaviour, the number of false positives and successfully prevented incidents. The study also developed recommendations for improving access control mechanisms using artificial intelligence, including the introduction of machine learning-based systems to detect anomalies in user behaviour, and the integration of AI with multi-factor authentication to create flexible and reliable data protection mechanisms.
Taxonomic revision of genus Verbascum (Scrophulariaceae) in the Arabian Peninsula
No full textThe species of the genus Verbascum L. in the Arabian Peninsula are revised. Seventeen species are recognized, a key to the species is provided, and all names are typified. Detailed morphological descriptions, distribution maps, habitat information, and field images are presented for each species. Verbascum sarawaticum A. Alzahrani is newly described, and Verbascum eremobium Murb. is newly confirmed for the flora of the Arabian Peninsula. Seven new synonyms are established in this study. Accordingly, Verbascum sheilae Hemaid is treated as a variety under V. deserticola (Murb.) Huber-Morath (as var. sheilae); Verbascum tabukum Hemaid is placed in synonymy with V. eremobium Murb.; Verbascum luntii Baker is placed in synonymy with V. longibracteatum Defl.; Verbascum hema-figranum Hemaid is placed in synonymy with V. medinecum Hemaid; Verbascum abyadicum Hemaid is placed in synonymy with V. shiqricum Hemaid; and both Verbascum chaudharyanum Hemaid and Verbascum asiricum Hemaid are treated as varieties under V. yemense Defl. (as var. yemense and var. asiricum, respectively). Furthermore, the previously segregated genus Rhabdotosperma Hartl is here reduced to synonymy under Verbascum L., and the species formerly known as Rhabdotosperma saudiarabicum A. Alzahrani is formally recombined as Verbascum saudiarabicum (A. Alzahrani) A. Alzahrani