Search Results (193)

This study examines the transformative impact of cyberpolitics on political systems in six Latin American countries—Argentina, Brazil, Chile, Colombia, Mexico, and Peru—between 2000 and 2024. Over this period, 34 elections and the emergence of 103 new political parties revealed a dynamic interplay between technological innovation and political fragmentation. Digital platforms have revolutionized political communication, enabling hyper-segmentation and direct voter engagement while contributing to the disintegration of traditional party structures. The rise of digital-native parties and outsider leaders highlights the shift toward personalized, campaign-driven politics. The research identifies a strong correlation between electoral cycles and the founding of new parties, with three times as many emerging in election years. While cyberpolitics has democratized participation, it has also intensified volatility, fostering a fragile political landscape. This study underscores the dual-edged role of digital technologies in reshaping democracy, emphasizing the need for further exploration of their long-term implications. Full article

This study addresses the need for efficient and non-destructive monitoring of the nutrient status of hardy kiwi (Actinidia arguta), a plantation crop native to East Asia. Traditional nutrient monitoring methods are labor-intensive and often destructive, limiting their practicality in precision agriculture. To overcome these challenges, we deployed a rotary-wing unmanned aerial vehicle (UAV) equipped with a multispectral camera to capture monthly images of 10 hardy kiwi orchards in South Korea from June to October 2019. We extracted spectral bands (i.e., red, red-edge, green, and near-infrared) to generate normalized difference vegetation index and canopy chlorophyll content index maps, which were correlated with in situ chlorophyll measurements using a chlorophyll meter. Strong positive correlations were observed between vegetation indexes and actual chlorophyll content, with canopy chlorophyll content index achieving the highest predictive accuracy (average correlation coefficient > 0.84). Regression models based on multispectral data enabled reliable estimation of leaf chlorophyll across months and regions, with an average RMSE of 3.1. Our results confirmed that UAV-based multispectral imaging is an effective, scalable approach for real-time monitoring of nutrient status, supporting timely, site-specific fertilizer management. This method has the potential to enhance fertilizer efficiency, reduce environmental impact, and improve the quality of hardy kiwi cultivations. Full article

In order to determine the impact of urbanization on raptors in the semi-desert conditions of southwestern Kazakhstan, an analysis of the spatio-temporal distribution of raptors is presented for the first time based on the results of surveys of the avifauna of Kyzylorda. Eight species of raptors were recorded: field Hen Harrier (Circus cyaneus), Marsh Harrier (C. aeroginosus), Eurasian Sparrowhawk (Accipiter nisus), Long-Legged Buzzard (Buteo rufinus), Eurasian Buzzard (B. buteo), Steppe Eagle (Aquila nipalensis), Eurasian Hobby (Falco subbuteo), and Common Kestrel (F. tinnunculus). The probability of raptors being present was negatively associated with dense urban low-rise buildings with limited greenery in the bay and the new part of the city. At the same time, the dense urban development with little or no greenery in the old central part of the city provides adequate habitat (including a foraging base and nesting sites) for the Common Kestrel. Raptor presence was positively associated with the Syrdarya River floodplain and wasteland with small groups of trees and/or shrubs. The landfill site located on the north-eastern edge of the city serves as a feeding ground for the Long-Legged and Eurasian Buzzards, while the airport area is inhabited by the Eurasian Buzzard, Steppe Eagle, and Common Kestrel. Based on this study, we would recommend that enterprises (e.g., grain storage facilities, airports) and local executive bodies who are interested in the conservation of raptors and regulating the population of the pigeons around their territories should retain or plant more native vegetation and shrubs and preserve areas with green spaces. Full article

This paper presents a real-time speech-to-text (STT) system designed for edge computing environments requiring ultra-low latency and local processing. Differently from cloud-based STT services, the proposed solution runs entirely on a local infrastructure which allows the enforcement of user privacy and provides high performance in bandwidth-limited or offline scenarios. The designed system is based on a browser-native audio capture through WebRTC, real-time streaming with WebSocket, and offline automatic speech recognition (ASR) utilizing the Vosk engine. A natural language processing (NLP) component, implemented as a microservice, improves transcription results for spelling accuracy and clarity. Our prototype reaches sub-second end-to-end latency and strong transcription capabilities under realistic conditions. Furthermore, the modular architecture allows extensibility, integration of advanced AI models, and domain-specific adaptations. Full article

The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of vegetation to a mulch layer) in 2020 and targeted herbicide treatment of woody vegetation, with the aim of reducing vegetation height by encouraging a native herbaceous groundcover beneath the transmission lines. We measured vegetation structure (cover and height) and composition (species presence in 15 × 2 m plots), at 12 transects, 90 m in length on the transmission line corridor, to determine if management goals were being achieved and to determine how the vegetation and fire hazard (based on the overall fuel hazard assessment method) varied among the treated corridor, the forest edge environment, and the natural forest. The results showed that vegetation structure and composition in the treated zones had been modified to a state where herbaceous plant species were dominant; there was a significantly (p < 0.05) higher native grass cover and cover of herbs, sedges, and ferns in the treated zones, and a lower cover of trees and tall woody plants (>1 m in height) in these areas. For example, mean native grass cover and the cover of herbs and sedges in the treated areas was 10.2 and 2.8 times higher, respectively, than in the natural forest. The changes in the vegetation structure (particularly removal of tall woody vegetation) resulted in a lower overall fuel hazard in the treated zones, relative to the edge zones and natural forest. The overall fuel hazard was classified as ‘high’ in 83% of the transects in the treated areas, but it was classified as ‘extreme’ in 75% of the transects in the adjacent forest zone. Importantly, there were few introduced species recorded. The results suggest that fuel management has been successful in reducing wildfire risk in the transmission corridor. Temporal monitoring is recommended to determine the frequency of ongoing fuel management. Full article

Soil degradation has been accelerating globally due to climate change, which threatens food production, biodiversity, and ecosystem balance. Traditional soil restoration strategies are often expensive, slow, or unsustainable in the long term. In this context, cyanobacteria have emerged as promising biotechnological alternatives, being the only prokaryotes capable of performing oxygenic photosynthesis. Moreover, they can capture atmospheric carbon and nitrogen, release exopolysaccharides (EPSs) that stabilize the soil, and facilitate the development of biological soil crusts (biocrusts). In recent years, the convergence of multi-omics tools, such as metagenomics, metatranscriptomics, and metabolomics, has advanced our understanding of cyanobacterial dynamics, their metabolic potential, and symbiotic interactions with microbial consortia, as exemplified by the cyanosphere of Microcoleus vaginatus. In addition, recent advances in bioinformatics have enabled high-resolution taxonomic and functional profiling of environmental samples, facilitating the identification and prediction of resilient microorganisms suited to challenging degraded soils. These tools also allow for the prediction of biosynthetic gene clusters and the detection of prophages or cyanophages within microbiomes, offering a novel approach to enhance carbon sequestration in dry and nutrient-poor soils. This review synthesizes the latest findings and proposes a roadmap for the translation of molecular-level knowledge into scalable biotechnological strategies for soil restoration. We discuss approaches ranging from the use of native biocrust strains to the exploration of cyanophages with the potential to enhance cyanobacterial photosynthetic activity. By bridging ecological functions with cutting-edge omics technologies, this study highlights the critical role of cyanobacteria as a nature-based solution for climate-smart soil management in degraded and arid ecosystems. Full article

In Montenegro, coniferous forests play a key ecological role in maintaining ecosystem stability. Root-associated mycorrhizal fungi and saprotrophic fungi inhabiting forest soils are well known for their roles in nutrient cycling, organic matter decomposition, and supporting host tree health. In contrast, the fungal communities residing within conifer needles, despite potentially important ecological functions, remain largely underexplored, particularly in natural and marginal forest ecosystems such as those in the Balkans. This study aimed to investigate the diversity and community composition of needle-associated fungi in three native conifers: Picea abies and Abies alba (at the edge of their native range), and the endemic Pinus heldreichii, from different mountainous regions in Montenegro. High-throughput sequencing was conducted to assess fungal diversity and community composition. Dothideomycetes dominated fungal communities in all three tree species, followed by Leotiomycetes and Tremellomycetes. Multivariate analysis revealed distinct fungal communities in P. heldreichii, whereas fungal communities in A. alba and P. abies were partially overlapping. Functional classification showed a dominance of saprotrophic, pathogenic, and endophytic fungi, with P. heldreichii exhibiting the highest proportion of saprotrophs, while A. alba and P. abies showed a considerable proportion of pathogens. The findings highlight strong host specificity, biogeographical influences, and the ecological importance of fungal communities in coniferous forests. This study provides new insights into the diversity and functional roles of needle-associated fungi, emphasizing the need for conservation efforts to maintain microbial biodiversity in native forests of Montenegro. Full article

Hydrilla, an invasive submerged macrophyte that is classified as a noxious weed in the U.S., can quickly spread into extensive monospecific infestations, excluding other native macrophytes and disrupting entire lake ecosystems. In Florida, infestation has increased tenfold in just three years, consuming over 60% of total management costs and requiring millions of dollars in annual control efforts. Traditional monitoring methods, such as field sampling, provide accurate localized assessments but are expensive and time-consuming. This study leverages Sentinel-2 satellite imagery, introducing the Submerged Aquatic Vegetation Index for Hydrilla (SVI_H), a novel three-band index utilizing the green (G, 560 nm), red-edge 1 (RE1, 705 nm), and shortwave infrared 1 (SWIR1, 1610 nm) bands to distinguish hydrilla from water and emergent aquatic vegetation (EAV) in two Florida lakes. The index, coupled with other vegetation indices, was validated using in situ measurements of hydrilla abundance levels, confirming its strong ability to accurately distinguish hydrilla. At the highest abundance level, SVI_H produced the highest Mathew correlation coefficients (MCCs), i.e., >0.86 for Lake Yale (2021), and >0.60 (2020) and >0.68 (2021) for Lake Apopka, using three thresholding methods. For Apopka (2022), other tested indices such as MFI and FAI yielded high MCC values along with high recall using incremental search threshold. However, these indices could not distinguish EAV from SAV in the eastern regions of Lakes Apopka and Yale, where EAV was dominant. These findings encourage the use of SVI_H for routine hydrilla detection and mapping, facilitating improved management, conservation efforts, and targeted herbicide applications. Full article

The skin microbiome is a focus for innovative skincare. This study investigated topical semi-solid balm formulations of Micrococcus luteus Q24, a live skin-native probiotic, to enhance skin quality parameters such as hydration, pores, pigmentation, wrinkles and dryness. Firstly, the compatibility and growth-promoting effects of prebiotics and functional actives on M. luteus Q24 were evaluated, identifying oil-based actives, including vitamin E and pomegranate seed oil, that significantly boosted bacterial growth compared to oatmeal, the sole effective prebiotic tested. Subsequently, a pilot cosmetic trial assessed two M. luteus Q24-enriched balms on healthy adults utilising a cutting-edge AI (Artificial Intelligence) driven skin analyser device. Balm B significantly reduced keratin levels, wrinkles, and pore size, and increased hydration, while Balm A effectively reduced spots and keratin. After 4 days of application, Balm A showed mean percentage reductions of 80% in pores, 20% in spots, 60% in wrinkles, and 100% in keratin scores, while Balm B exhibited mean percentage reductions of 100% in pores, 50% in spots, 67% in wrinkles, and 80% in keratin, with a 100% increase in hydration score. Both balms demonstrated compatibility and efficacy, highlighting the potential of M. luteus Q24 in improving skin parameters. These findings suggest that balms optimise the benefits of skin-specific probiotics for microbiome-friendly skincare. Future research with larger, placebo-controlled trials is needed to substantiate these preliminary findings. Full article

Microservice deployment methods in edge-native computing environments hold great potential for minimizing user application response time. However, most existing studies overlook the communication overhead between microservices and controllers, as well as the impact of microservice pull time on user response time. To address these issues, this paper proposes a multi-controller service mesh architecture to reduce data transfer overhead between microservices and controllers. Furthermore, we formulate the microservice deployment problem as an optimization problem aimed at minimizing both system communication overhead and microservice deployment cost. To achieve this, we introduce a novel RIME optimization algorithm and enhanced Adaptive Crested Porcupine Optimizer (RIME-ACPO) algorithm that optimizes microservice placement decisions. Notably, this algorithm incorporates a real-time resource monitoring-based load balancing algorithm, dynamically adjusting microservice deployment according to edge server resource utilization to enhance the execution performance of user applications. Finally, extensive simulation experiments were conducted to validate the effectiveness of the proposed algorithm. The experimental results demonstrate that, compared with other algorithms, our algorithm significantly improves user response time, optimizes resource utilization, and reduces the total cost. Full article

Skin is composed of three layers: the epidermis, dermis, and hypodermis. It is enriched with skin appendages, including hair follicles, sweat glands, and sebaceous glands, which play essential roles in regulating fluid exchange, controlling body temperature, and providing protection against pathogens. Currently, skin regeneration treatments rely on transplantations. However, this approach has several disadvantages, including hemostasis at the recipient site, limitations in donor area closure, increased graft contraction, and hypertrophic scarring. Recent advancements in three-dimensional (3D) bioprinting technologies have enabled the fabrication of structures that closely mimic native tissues, with the aim of enhancing tissue regeneration. Bioprinting offers several advantages, such as high reproducibility, precision, and the ability to create complex geometries. The most promising bioinks combine excellent biocompatibility and biodegradability, with mechanical and rheological stability. This review highlights the most recent and innovative studies on 3D-printed bioinks in the field of skin tissue engineering. In particular, considering the growing interest in the regenerative potential of exosomes, we discuss cutting-edge research involving exosome-loaded bioinks and their potential to support skin regeneration and repair. Full article

Container technology is currently one of the mainstream technologies in the field of cloud computing, yet its adoption in resource-constrained, latency-sensitive edge environments introduces unique security challenges. While existing system call-based anomaly-detection methods partially address these issues, they suffer from high false positive rates and excessive computational overhead. To achieve security and observability in edge-native containerized environments and lower the cost of computing resources, we propose an unsupervised anomaly-detection method based on system calls. This method filters out unnecessary system call data through automatic rule generation and an unsupervised classification model. To increase the accuracy of anomaly detection and reduce the false positive rates, this method embeds system calls into sequences using the proposed Syscall2vec and processes the remain sequences in favor of the anomaly detection model’s analysis. We conduct experiments using our method with a background based on modern containerized cloud microservices. The results show that the detection part of our method improves the F1 score by 23.88% and 41.31%, respectively, as compared to HIDS and LSTM-VAE. Moreover, our method can effectively reduce the original processing data to 13%, which means that it significantly lowers the cost of computing resources. Full article

The rapid integration of large-scale AI models into distributed systems, such as the Artificial Intelligence of Things (AIoT), has introduced critical security and privacy challenges. While configurable models enhance resource efficiency, their deployment in heterogeneous edge environments remains vulnerable to poisoning attacks, data leakage, and adversarial interference, threatening the integrity of collaborative learning and responsible AI deployment. To address these issues, this paper proposes a Hierarchical Federated Cross-domain Retrieval (FHCR) framework tailored for secure and privacy-preserving AIoT systems. By decoupling models into a shared retrieval layer (globally optimized via federated learning) and device-specific layers (locally personalized), FHCR minimizes communication overhead while enabling dynamic module selection. Crucially, we integrate a retrieval-layer mean inspection (RLMI) mechanism to detect and filter malicious gradient updates, effectively mitigating poisoning attacks and reducing attack success rates by 20% compared to conventional methods. Extensive evaluation on General-QA and IoT-Native datasets demonstrates the robustness of FHCR against adversarial threats, with FHCR maintaining global accuracy not lower than baseline levels while reducing communication costs by 14%. Full article

A key feature in sheep biology is reproduction seasonality which concerns the cyclical occurrence of natural breeding, which therefore does not take place throughout the year. Since sheep are short-day breeders, the amount of daylight has an impact on their reproductive activity. The melatonin receptor subtype 1A (MTNR1A) gene is the primary gene that has been linked with seasonality. Nonetheless, information regarding the potential genetic association between other loci and the seasonality of sheep reproduction is scarce. Genome-wide association study (GWAS) is considered a cutting-edge methodology for comprehending the genetic architecture of complex traits since it enables the discovery of many markers linked to different features. In the present study, three indigenous Greek sheep breeds were investigated using GWAS—two of which presented strict patterns of reproduction seasonality, i.e., the Florina and Karagkouniko breeds, while the third one, i.e., the Chios breed had the ability to exhibit estrus throughout the year—in an attempt to detect the genetic loci linked with reproduction seasonality. All three breeds of investigated animals were purebred with Chios and Florina breeds originating from the Greek national stationary stock, whereas Karagkouniko originated from a commercial farm. Interestingly, a significant genetic differentiation of the national stationary stock groups was suggested by principal component analysis, phylogenetic analysis, and admixture and spatial point patterns, with these two breeds being less heterogeneous. This finding highlights the value of stationary stocks towards the maintenance of genetic integrity in indigenous sheep, demonstrating the Greek station’s critical role in the conservation of native sheep breeds. On the other hand, according to the GWAS data analysis, no genetic loci were correlated with reproduction seasonality, emphasizing the MTNR1A gene as the main determinant of the seasonality in native non genetically improved breeds. Full article

Recently, in the field of Virtual Reality (VR), cloud VR has been proposed as a method to address issues related to the performance and portability of Head-Mounted Displays (HMD). Cloud VR offers advantages such as lightweight HMD, telepresence, and mobility. However, issues such as Motion-To-Photon (MTP) latency and the handling of large-scale traffic due to continuous video streaming persist. Utilizing edge computing is considered a potential solution for some of these issues. Nevertheless, providing this in a cloud–edge continuum environment for simultaneous users presents additional issues, such as server rendering load and multi-user MTP latency threshold. This study proposes an adaptive MicroServices Architecture (MSA) and a service orchestration based on it to effectively provide multi-user cloud VR in a cloud–edge continuum environment. The proposed method aims to ensure the MTP latency threshold for each user while addressing network congestion, even when the application is provided to multiple users simultaneously in a resource-constrained edge network environment. Furthermore, it aims to maintain high edge applicability for microservices through efficient edge resource management. Simulation results confirm that the proposed method demonstrates better performance in terms of networking and MTP latency compared to other edge resource-management methods. Full article