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Stability of financial inclusion determinants in emerging market economies: A dynamic coefficients approach
No full textThis paper addresses a significant gap in the existing literature on financial inclusion — namely, the dynamic instability of the impacts generated by its determinants in four major emerging market economies: Brazil, Russia, India, and China. A time-varying coefficients framework is applied to examine whether the factors shaping financial inclusion at the aggregate level produce nonlinear effects over time. The analysis covers the period from 2000–2001 to 2022–2023. A composite financial inclusion index is constructed to capture inclusion across three key dimensions — availability, access, and usage — using the distance function approach. Three classes of determinants are modeled: socio-demographic, infrastructural, and macroeconomic variables. Evidence indicates structural instability in the financial inclusion process for the BRIC economies, with several determinants exerting nonlinear impacts over time. The findings challenge the conventional assumption of time-invariant relationships between financial inclusion and its dominant determinants. The results reveal considerable temporal volatility in the effects of macroeconomic factors, including growth and inflation, on financial inclusion across emerging markets. Policymakers should adjust strategies, moving beyond assumptions of linear processes and managing dynamic, nonlinear factors more effectively to achieve universal financial inclusion
Identifying potential novel biomarkers for varicocele: A bioinformatics approach to genomics analysis
No full textAbstract Introduction: Varicocele, characterized by the enlargement of scrotal veins, is a common contributor to male infertility, but its genetic underpinnings remain largely unknown. Aim: The goal of this study is to identify potential biomarkers associated with varicocele in order to better understand its molecular mechanisms. Materials and methods: Using the three primary databases, NCBI, DisGeNET, and OpenTarget, we analyzed gene variants and found 79 pertinent genes associated with varicocele. Protein-protein interaction analysis was performed using STRING and visualized with Cytoscape. Molecular Complex Detection (MCODE) and CytoHubba tools helped identify significant protein clusters. Results: The gene ontology analysis shows that there are 79 proteins involved in the inflammatory process, the regulation of gene expression, and cellular components that play a role in oxidative stress and angiogenesis. Our results revealed three key biomarkers: Interleukin-1 beta (IL1B), B-cell lymphoma 2 (BCL2), and matrix metalloproteinase-9 (MMP-9). These proteins are involved in critical processes, such as inflammation, oxidative stress, angiogenesis, and vascular damage, that are central to the pathophysiology of varicocele. Conclusion: The identification of IL1B, BCL2, and MMP-9 offers new insights into varicocele’s molecular mechanisms and suggests potential targets for diagnostic and therapeutic strategies, advancing personalized treatment approaches for fertility restoration
Children as frontline detectors: School-based programs can enhance early monitoring of Vespa velutina
No full textThe yellow-legged hornet (Vespa velutina) is an invasive predator that poses a significant threat to native biodiversity and apiculture in Europe. Early detection and rapid response are crucial to prevent its establishment and further spread. In this study, we tested the potential of using elementary school pupils as active contributors to V. velutina surveillance through a targeted educational program. A total of 358 pupils (aged 10–11 years) participated in a program that included information on V. velutina biology, its ecological and economic impacts, and key identification features, supported by practical demonstrations using real specimens. Knowledge of fundamentals of V. velutina biology and identification skills were assessed using pre-tests, post-tests one week after the program, and follow-up tests after 2–3 months. The results showed a significant improvement in both knowledge scores and identification accuracy, with knowledge retention confirmed several months later. In a practical verification experiment six months after the program, dead V. velutina individuals were placed in classrooms on the windowsill; and their presence was successfully reported in 64.3% of the cases. Control of the verification experiment, by placing dead V. crabro individuals into the classrooms, resulted in no false reports of invasive species. These findings demonstrate that educational programs can be a simple, cost-effective tool for increasing public engagement in invasive species monitoring, significantly improving early detection capacity. Implementing such programs, particularly in regions at risk of invasion, could greatly enhance management strategies and reduce socio-economic and ecological impacts
KIEBIDS: A Modular Framework for Scalable Information Extraction from Written Records in Natural History Collections
No full textNatural history collections preserve invaluable records of biodiversity across time and space. Each specimen is typically accompanied by one or more labels documenting provenance, locality, and contextual data. Mobilizing this information is crucial for research on biodiversity change, biogeography, and taxonomy. To date, much of this data remains inaccessible for computational knowledge engineering approaches because manually processing and converting the sources into structured, interoperable data formats is a labor-intensive challenge due to the volume, heterogeneity, and complexity of the documents—and curatorial resources for fulfilling these tasks are generally insufficient. Artificial Intelligence (AI)-based methodologies can significantly accelerate this process and make it economically scalable.We present KIEBIDS*1, an open-source framework for specifying and executing AI-based workflows for information extraction from specimen label images. Following a linear data-pipeline architecture, workflows comprise five sequential functional steps for information extraction:image pre-processing (to prepare input images for subsequent analysis),layout analysis (to identify image regions that are relevant for information extraction),optical character recognition (to identify text on the syntactical level),semantic parsing (to identify text that references categories of interest),entity linking (to identify entities of interest mentioned in the text with authority records).Modularity and adaptability are central design principles for the framework's architecture. Each function can be realized by one or more modules that operate independently through file-based input and output, enabling substitution or extension as new technologies emerge. This ensures flexible adaptation to various information extraction goals or new data domains.In the current release, image pre-processing is implemented using the OpenCV framework with steps for resizing, grayscale conversion, noise reduction, and binarization. Layout analysis, based on the Segment Anything Model, identifies image regions that depict labels. Character recognition is implemented using two alternative modules. Besides EasyOCR, Moondream is used to leverage locally-deployable vision-language model (VLM) technology. Semantic parsing is implemented using spaCy and regular expressions, as rule-based parsing has proven efficient for syntactically well-defined entities, such as dates or coordinates, given the sparse context of label texts. Entity linking, in the current release, is realized for geographical place names using the GeoNames application programming interface (API).The input for a given workflow run consists of document images and configuration parameters. The configuration parameters encompasssettings for the pipeline as a whole, such as location of input and output files and execution mode,the configurable settings for each functional step of the pipeline, e.g., models to be used, model parameters or the tag selection for the semantic tagging.The workflow's output are PAGE-XML files containing image annotations, including the extracted and annotated text. Optionally, intermediate data and evaluation metrics can be assessed. Integrating seamlessly with Python codebases, Prefect is used for scheduling, monitoring, and graphical user interaction.By combining existing open frameworks rather than developing new components, the project leverages recent advances in computer vision and natural language processing to mobilize biodiversity data. Future developments will focus on improving user experience, integrating better models for handwritten text, and expanding semantic analysis capabilities. KIEBIDS' source code*2 is openly available and locally deployable with moderate hardware requirements
First records of Opius and Apodesmia (Hymenoptera, Braconidae, Opiinae) from South Korea, with descriptions of newly-recorded species
No full textThe subfamily Opiinae comprises more than 2,000 valid species worldwide. Members of this subfamily are koinobiont endoparasitoids, with parasitism generally culminating in the eventual death of the host. Several species of Opiinae have been utilised for biological control of agricultural pests. The genus Opius is the largest genus within Opiinae, with more than 1,000 valid species worldwide. It is divided into several subgenera, classification of which remains under active discussion. The genus Apodesmia was formerly regarded as a subgenus of Opius, but was elevated to genus level, based on differences in the form of the occipital carina.Opius youi Li & van Achterberg, 2013 is recorded for the first time from South Korea, representing the first record of the species outside China. Apodesmia incisula Fischer, 1963 is also newly recorded from South Korea, constituting the first record of the species outside Europe, where it was previously known from Germany and the Netherlands. For each species, detailed morphological descriptions are provided, accompanied by diagnostic characters illustrated with photographs of the relevant body structures. The barcode region of mitochondrial cytochrome c oxidase I (COI) was also analysed for the species
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.
First comprehensive catalogue of hibernating Darwin wasps in the Western Palaearctic (Hymenoptera, Ichneumonidae)
No full textIn the Western Palaearctic, many species of Darwin wasps exhibit a form of diapause known as free-living adult diapause, similar to hibernation in certain beetle, bumblebee and butterfly species. This study provides a first comprehensive overview of all known hibernating species and aims to improve the current ecological knowledge.We reviewed 439 species, confirming free-living adult diapause in 340; 81 remain unverified and 18 are excluded, which have been incorrectly reported as hibernators in the past. The validated dataset includes 7443 records from 27567 specimens, spanning over 235 years of both published and unpublished observations. We report 29 species as hibernators for the first time. Amongst the records, 388 provide the first evidence of hibernation for a species in a given country, with 67 also representing the species' first national record. We highlight the value of field-based data and caution against relying solely on collection dates to study diapause. The observed variability in diapause strategies and hibernacula underscores the importance of nature management for biodiversity conservation, especially preservation of microhabitats
Negative impact of the invasive topmouth gudgeon (Pseudorasbora parva) on population growth of a native fish species, the sunbleak (Leucaspius delineatus)
No full textBiotic interactions of invasive and native species are one of the main drivers of declining freshwater biodiversity. The recent population declines of sunbleak (Leucaspius delineatus) in its native range have been attributed to the spread of the rosette agent (Sphaerothecum destruens) carried by the invasive topmouth gudgeon (Pseudorasbora parva). However, both fish species highly overlap in their habitat preferences and omnivorous feeding strategy, and their interspecific interactions may have contributed to the decline of sunbleak populations. To test this hypothesis, we carried out two experiments in small (0.8 m3 water volume) and large (8 m3 water volume) outdoor mesocosms and followed their population and individual responses over one growing season in single-species and syntopy treatments. In each experiment, both species reached similar final abundance, final biomass and biomass-based population growth rate in the single-species treatment. However, the final biomass and biomass-based population growth rate of sunbleak were much lower than those of topmouth gudgeon in the syntopy treatment in both experiments. That is, the biomass-based population growth rate of topmouth gudgeon was not affected by interspecific competition, while that of sunbleak significantly declined. These disparate population-level responses of both species to syntopy were not reflected in the individual-level responses. At the end of each experiment, topmouth gudgeon individuals were heavier than sunbleak individuals of the same size and individuals in the large mesocosms were heavier than conspecific individuals of the same size in the small mesocosms, but we found no difference between the single-species and syntopy treatments. Taken together, these results suggest that presence of topmouth gudgeon in the small water bodies can significantly impact sunbleak populations. More broadly, it underscores the need to mitigate invasive species’ effects on native fish through proactive conservation and management strategies
Competitive exclusion of native species by invasive species within Carassius genus
No full textSuccessful invasive non-native fish species can cause enormous damage to native biodiversity. In the continental Europe, the introduction of the gibel carp (Carassius gibelio) has led to a decline in populations of the formerly widespread native crucian carp (Carassius carassius). Due to the decline of crucian carp populations the status of the specices changed from least concern to critically endangered in Czechia. Its populations have also declined in other countries where the gibel carp has become established. This contribution summarises the findings on the competitive displacement of native species by invasive species from both experimental approaches and historical trends. The recent findings demonstrated that the gibel carp utilises food sources much more efficiently than its native counterpart. The gibel carp are not only more aggressive and utilise shared resources faster, but also use plant material that is not available to the crucian carp as an effective food source. Finally, this contribution provides circumstantial evidence that the gibel carp is behind the transition from the relative abundance of large deep-bodied form of crucian carp to its near extirpation in Czechia, while large and deep-bodied gibel carp have taken over the reports of record angling catches in the genus Carassius. Taken together, the current findings strongly suggest that the crucian carp is being locally extirpated by the gibel carp. Due to the uneven competition between Carassius species, programmes to repopulate selected waters with crucian carp are necessary (Suppl. material 1)
A Case Study of the European Mudminnow Conservation Pilot Programme (2008-): Creation of surrogate habitats and self-sustaining populations, risks of climate change
No full textThe European Mudminnow Conservation Pilot Programme, initiated in 2008, is a long-term, complex, adaptive project designed to respond to changing ecological conditions. The programme's primary aim is to conserve and enhance populations of the European mudminnow (Umbra krameri). The number of mudminnow habitats and the size of their populations have decreased significantly in Hungary over the past few decades. The small, isolated, and shallow waters, as well as the small fish populations, are susceptible to environmental change and human impact. Mudminnows face their most significant threats from habitat loss (e.g., drying caused by climate change), disturbance (e.g., dredging), and the spread of the invasive Amur sleeper (Perccottus glenii). Between 2008 and 2017, we created 10 surrogate habitats (ponds) in the Szada Pilot Area, where we introduced aquatic vegetation and mudminnows rescued from 7 endangered habitats/populations in Hungary. Depending on ecological conditions, clear, turbid, shaded, and oxygen-poor alternative stable states developed in the ponds. Five habitats became excellent for the European mudminnow. Two of our artificially created ponds have established self-sustaining populations of mudminnows. Our monitoring results highlighted that extreme weather events driven by climate change (e.g., droughts, severe spring coolings) could rapidly degrade both natural and artificial shallow aquatic ecosystems, potentially driving them into an oxygen-poor state and significantly reducing the survival and reproductive success of the European mudminnow (Suppl. material 1). To mitigate the harmful effects of climate change, the main priorities are regular monitoring, habitat management (enhancement), rehabilitation, and ensuring the ecological water demands of habitats are met. We have recently developed the comprehensive Umbra Habitat Qualification System (UHQS), which is currently under validation. This system aims to reduce stocking risks by pre-assessing newly created surrogate habitats. UHQS will also be suitable for identifying and evaluating potential and current mudminnow habitats