Search Results (346)

Artificial intelligence (AI) has become the mainstream of analysis tools in remote sensing. Various semantic segmentation models have been introduced to segment land cover from aerial or satellite images, and remarkable results have been achieved. However, they often lack universal performance on unseen images, making them challenging to provide as a service. One of the primary reasons for the lack of robustness is overfitting, resulting from errors and inconsistencies in the ground truth (GT). In this study, we propose a method to mitigate these inconsistencies by utilizing redundant models and verify the improvement using a public dataset based on Google Earth images. Redundant models share the same network architecture and hyperparameters but are trained with different combinations of training and validation data on the same dataset. Because of the variations in sample exposure during training, these models yield slightly different inference results. This variability allows for the estimation of pixel-level confidence levels for the GT. The confidence level is incorporated into the GT to influence the loss calculation during the training of the enhanced model. Furthermore, we implemented a consensus model that employs modified masks, where classes with low confidence are substituted by the dominant classes identified through a majority vote from the redundant models. To further improve robustness, we extended the same approach to fuse the dataset with different class compositions based on imagery from the Korea Multipurpose Satellite 3A (KOMPSAT-3A). Performance evaluations were conducted on three network architectures: a simple network, U-Net, and DeepLabV3. In the single-dataset case, the performance of the enhanced and consensus models improved by an average of 2.49% and 2.59% across the network architectures. In the multi-dataset scenario, the enhanced models and consensus models showed an average performance improvement of 3.37% and 3.02% across the network architectures, respectively, compared to an average increase of 1.55% without the proposed method. Full article

Urban areas are at the forefront in addressing global challenges such as climate change and biodiversity loss. Among the key responses are nature-based solutions, which are increasingly being integrated into policy frameworks but which require strong community engagement for their effective implementation. This paper presents the findings of surveys conducted within the Place Lab in Katowice, Poland, an initiative developed as part of an international project and used as a participatory tool for co-creating and implementing green infrastructure. The project applies both place-based and people-centred approaches to support European cities in their transition towards regenerative urbanism. Place Lab activities encourage collaboration between local authorities and residents, enhancing awareness and fostering participation in environmental initiatives. The survey data collected during the project allowed for the evaluation of changes in public attitudes and levels of engagement and for the identification of broader societal phenomena that may influence the implementation of nature-based solutions. The findings revealed, for instance, that more women were interested in supporting the project, that residents tended to be sceptical of governmental actions on climate change, and that views were divided on the trade-off between urban infrastructure such as parking and roads and the presence of green areas. Furthermore, questions of responsibility, awareness, and long-term commitment were frequently raised. Building on the survey results and the existing literature, the study proposes a set of indicators to assess the contribution of citizen participation to the adoption of nature-based solutions. While the effectiveness of nature-based solutions in mitigating climate change impacts can be assessed relatively directly, evaluating civic engagement is more complex. Nevertheless, when conducted transparently and interpreted by experts, indicator-based assessment can offer valuable insights. This study introduces a novel perspective by considering not only drivers of engagement but also the obstacles. The proposed indicators provide a foundation for evaluating community readiness and commitment to nature-based approaches and may be adapted for application in other urban settings and in future research on climate resilience strategies. Full article

The increasing demand for sustainable pet-food solutions has driven interest in alternative protein sources, as researchers seek to avoid allergenic foods while maintaining optimal pet nutrition. This review explores recent scientific publications, patent trends, and market trends relating to various alternative protein sources, including plant-based, aquatic, insect-derived, and cell-based sources. Their nutritional composition, functional properties, and potential benefits for pet health were assessed. Plant-based proteins, such as soy, pea, and lentils, provide essential amino acids and functional properties suitable for meat analogues. Microalgae and seaweed offer rich sources of omega-3 fatty acids, antioxidants, and bioactive compounds. Insect-based proteins such as black-soldier-fly larvae and mealworms are highly digestible and rich in essential nutrients, with additional benefits for gut health. Emerging cell-based proteins present a novel, lab-grown alternative with promising sustainability and nutritional advantages. While these protein sources offer significant benefits, challenges related to digestibility, palatability, regulatory approval, and consumer acceptance must be addressed. The emphasis of the present research is on current developments for industry uses and future potential. The analysis sheds light on the contributions of alternative protein sources to the promotion of sustainable and nutrient meals for pets. Full article

Infectious diseases poses a growing public health challenge. The COVID-19 pandemic has further emphasized the urgent need for rapid, accessible diagnostics. This study presents the development of an integrated, flexible point-of-care (POC) diagnostic system for the rapid detection of Corynebacterium diphtheriae, the pathogen responsible for diphtheria. The system comprises a microfluidic polymerase chain reaction (micro-PCR) device and an electrochemical DNA biosensor, both fabricated on flexible substrates. The micro-PCR platform offers rapid DNA amplification overcoming the time limitations of conventional thermocyclers. The biosensor utilizes specific molecular recognition and an electrochemical transducer to detect the amplified DNA fragment, providing a clear and direct indication of the pathogen’s presence. The combined system demonstrates the effective amplification and detection of a gene fragment from a toxic strain of C. diphtheriae, chosen due to its increasing incidence. The design leverages lab-on-a-chip (LOC) and microfluidic technologies to minimize reagent use, reduce cost, and support portability. Key challenges in microsystem design—such as flow control, material selection, and reagent compatibility—were addressed through optimized fabrication techniques and system integration. This work highlights the feasibility of using flexible, integrated microfluidic and biosensor platforms for the rapid, on-site detection of infectious agents. The modular and scalable nature of the system suggests potential for adaptation to a wide range of pathogens, supporting broader applications in global health diagnostics. The approach provides a promising foundation for next-generation POC diagnostic tools. Full article

Amid the accelerating pace of global urbanization, the volume of municipal solid garbage has surged dramatically, thereby demanding more efficient and precise garbage management technologies. In this paper, we introduce a novel garbage classification approach that leverages a dynamic graph neural network based on multimodal feature fusion. Specifically, the proposed method employs an enhanced Residual Network Attention Module (RNAM) network to capture deep semantic features and utilizes CIELAB color (LAB) histograms to extract color distribution characteristics, achieving a complementary integration of multimodal information. An adaptive K-nearest neighbor algorithm is utilized to construct the dynamic graph structure, while the incorporation of a multi-head attention layer within the graph neural network facilitates the efficient aggregation of both local and global features. This design significantly enhances the model’s ability to discriminate among various garbage categories. Experimental evaluations reveal that on our self-curated KRHO dataset, all performance metrics approach 1.00, and the overall classification accuracy reaches an impressive 99.33%, surpassing existing mainstream models. Moreover, on the public TrashNet dataset, the proposed method demonstrates equally outstanding classification performance and robustness, achieving an overall accuracy of 99.49%. Additionally, hyperparameter studies indicate that the model attains optimal performance with a learning rate of 2 × 10⁻⁴, a dropout rate of 0.3, an initial neighbor count of 20, and 8 attention heads. Full article

This article presents a comparative analysis of digital manufacturing laboratories (DMLs) in Mexico and Spain. It is argued that DMLs, also known as makerspaces or FabLabs, play a key role in innovation and experimentation, but that their success depends on the relationships they establish with social actors, such as local governments, universities, and firms. Key concepts of the transformative innovation approach such as “protective space” and “embeddedness” are introduced, which allow us to understand how DMLs operate within a complex system. The comparative analysis of a DML in Mexico City (Mexico) and a DML in Valencia (Spain) allows us to identify similarities and differences in their operational contexts. While the Mexican DML faces a lack of government support and dependence on the private sector, the Spanish one benefits from strong institutional support and public policies that facilitate its development. This results in greater stability and capacity for action for the Valencian FabLab VLC compared to the Mexican FabLab Finally, we reflect on how the embeddedness received from different social actors affects the autonomy and transformative capacity of DMLs, suggesting that while both labs have the potential to innovate, their contexts and relationships determine their effectiveness and sustainability in the digital sociotechnical system. Full article

Antibiotic overuse has contributed to the emergence of multidrug-resistant (MDR) bacteria, posing a serious public health threat. Pets may act as reservoirs of MDR bacteria, with the potential to transmit these pathogens to humans. This study aimed to identify probiotic alternatives to antibiotics by isolating and evaluating lactic acid bacteria (LAB) from feline milk. In addition to conventional in vitro assessments such as growth kinetics, adhesion ability, safety, and antipathogenic activity, this study also evaluated the antioxidant capacity and production of beneficial metabolites. Three LAB strains were isolated from feline milk, including two strains of Lactobacillus plantarum (M2 and M3) and one strain of Weissella confusa (M1). Resistance assays revealed that strains M2 and M3 exhibited high survival rates under stress conditions, including exposure to bile salts, acidic environments, artificial intestinal and gastric juice. Notably, strain M3 demonstrated strong auto-aggregation ability (73.39%) and high hydrophobicity toward trichloromethane (62.16%). It was also nonhemolytic and susceptible to various β-lactam antibiotics. Furthermore, strain M3 exhibited potent antimicrobial activity in both co-aggregation and Oxford cup assays. Overall, L. plantarum M3 displayed superior probiotic properties, suggesting its potential as an adjunct or alternative to antibiotics in managing MDR bacterial infections in cats. Full article

Accessibility in web systems is essential to ensure everyone can obtain information equally. Based on the Web Content Accessibility Guidelines (WCAGs), the Electronic Government Accessibility Model (eMAG) was established in Brazil to guide the accessibility of federal government web systems. Based on these guidelines, this research sought to understand the reasons behind the persistent gaps in web accessibility in Brazil, even after 20 years of eMAG. To this end, the accessibility of the Integrated Academic Activities Management System (SIGAA), used by 39 higher education institutions in Brazil, was evaluated. The living lab methodology was used to carry out accessibility and usability tests based on students’ experiences with visual impairments during interaction with the system. Furthermore, IT professionals’ knowledge of eMAG/WCAG guidelines, the use of accessibility tools, and their beliefs about accessible systems were investigated through an online questionnaire. Additionally, the syllabuses of training courses for IT professionals at 20 universities were analyzed through document analysis. The research confirmed non-compliance with the guidelines in the software researched, gaps in the knowledge of IT professionals regarding software accessibility practices, and inadequacy of accessibility content within training courses. It is concluded, therefore, that universities should incorporate mandatory courses related to software accessibility into the training programs for IT professionals and that organizations should provide continuous training for IT professionals in software accessibility practices. Furthermore, the current accessibility legislation should be updated, and its compliance should be required within all organizations, whether public or private. Full article

Heavy metal contamination, particularly lead (Pb) poisoning, is a significant public health issue worldwide. In Bangladesh, Pb contamination of water, soil, air, and food is detected alarmingly. Chronic exposure to Pb leads to severe health complications in the human body, including neurotoxicity, cardiovascular disease, developmental delays, and kidney damage. Research has established that there is “no safe level” of Pb exposure, as even minimal exposure can cause detrimental effects. Although existing physical and chemical methods are widely used, they come with limitations, such as high costs and the generation of toxic byproducts. As a green, sustainable alternative, the potential of probiotics as an effective biosorption agent has been explored to reduce Pb contamination in food, especially meat, while preserving its nutritional and sensory properties. This paper aims to integrate current knowledge from these two fields and highlight their capacity to decontaminate Pb-laden meat, the primary protein source in Bangladesh. The study also investigates optimal biosorption parameters, including temperature, pH, and exposure time, to enhance effectiveness. The proposed application of lactic acid bacteria (LAB) in meat processing and packaging is expected to significantly lower Pb levels in meat, ensuring safer consumption. Full article

Orthographic knowledge is a critical component of skilled language use, yet its large-scale behavioral signatures remain understudied in Spanish. To address this gap, we developed OrthoKnow-SP, a megastudy that captures spelling decisions from 27,185 native Spanish-speaking adults who completed an 80-item forced-choice task. Each trial required selecting the correctly spelled word from a pair comprising a real word and a pseudohomophone foil that preserved pronunciation while violating the correct graphemic representation. The stimuli targeted six high-confusability contrasts in Spanish orthography. We recorded response accuracy and reaction times for over 2.17 million trials, alongside demographic and device metadata. Results show robust variability across items and individuals, with item-level metrics closely aligned with independent norms of word prevalence. A composite difficulty index integrating speed and accuracy further allowed fine-grained item ranking. The dataset provides the first population-scale norms of Spanish spelling difficulty, capturing regional and generational diversity absent from traditional lab-based studies. Public release of OrthoKnow-SP enables new research on the cognitive and demographic factors shaping orthographic decisions, and provides educators, clinicians, and developers with a valuable benchmark for assessing spelling competence and modeling written language processing. Full article

The adoption of Electronic Lab Notebooks (ELNs) significantly enhances research operations by enabling the streamlined capture, storage, and dissemination of data. This promotes collaboration and ensures organised and efficient access to critical research information. Microsoft SharePoint^® (SP) is an established, widely used, web-based platform with advanced collaboration capabilities. This study investigates whether SP can meet the needs of engineering research projects, particularly in a collaborative environment. The paper outlines the process of adapting SP into an ELN tool and evaluates its effectiveness compared to established ELN systems. The evaluation considers several categories related to data management, ranging from data collection to publication. Six distinct application scenarios are analysed, representing a spectrum of collaborative research projects, ranging from small-scale initiatives with minimal processes and data to large-scale, complex projects with extensive data requirements. The results indicate that SP is competitive in relation with established ELN tools, ranking second among the six alternatives evaluated. The adapted version of SP proves particularly effective for managing data in engineering research projects involving both academic and industrial partners, accommodating datasets for around 1000 samples. The practical implementation of SP is demonstrated through a collaborative engineering research project, showing its use in everyday research tasks such as data documentation, workflow automation, and data export. The study highlights the benefits and usability of the adapted SP version, including its support for regulatory compliance and reproducibility in research workflows. In addition, limitations and lessons learned are discussed, providing insights into the potential and challenges of using SP as an ELN tool in collaborative research projects. Full article

A quantitative literature review of restoration techniques and supporting management strategies used throughout the Caribbean and Western Atlantic from 1998 through 2024 was compiled using references from the Web of Science to highlight those with potential for reef replenishment. From 93 sources listed, 74 publications were relevant and categorized into subtopics based on the most prevalent restoration techniques. Roughly half the studies focused on three general topics: the benefits of restoring Acropora species, studies utilizing micro-fragmentation and fragment nurseries, and outplanting techniques. Other subtopics, each with at least three references, included optimizing substrates and artificial reefs, enhancing larval recruitment, emphasizing the role of herbivory, improving management practices, and addressing the impacts of tourism and community engagement. The information from the references was compiled to determine the overlap among categories and the ways in which techniques and management strategies might be applied simultaneously to enhance restoration outcomes. Additionally, sources were analyzed according to time and location of publication to better visualize the emergence of this area of research and restoration efforts. An increase in publications was observed from 2014 to 2024, associated with the rise in major events impacting coral reefs. The major locations for published research were the Florida reef tract and Puerto Rico, though restoration studies were also reported from the Bahamas and sites around the Caribbean. Criteria to assess the success of techniques included coral survival, recruitment, coral coverage, habitat structure and complexity, and biomass of marine life, including fish and invertebrates that inhabited a restored reef. Most restoration efforts utilized either fragmentation or assisted sexual breeding, followed by cultivation in nurseries or labs. Outplanting success depended on fragment size, attachment style, and site selection, with less-intrusive techniques and intermediate planting densities promoting survival. Tools like GAO maps can guide site selection based on herbivore presence and algal coverage. Monitoring is critical to ensuring coral survival, especially after the first year of outplanting, while community involvement can foster public engagement in reef conservation. Full article

Smart city research often emphasises technology while neglecting how governance structures and resources influence outcomes. This study compares Tier 1 (Sydney, Melbourne, Brisbane, Adelaide) and Tier 2 (Geelong, Newcastle, Hobart, Sunshine Coast) Australian cities to evaluate how urban scale, economic capacity, governance complexity, and local priorities influence smart-enabled resilience. We analysed 22 official strategy documents using a two-phase qualitative approach: profiling each city and then synthesising patterns across technological integration, community engagement, resilience objectives and funding models. Tier 1 cities leverage extensive revenues and sophisticated infrastructure to implement ambitious initiatives such as digital twins and AI-driven services, but they encounter multi-agency delays and may overlook neighbourhood needs. Tier 2 cities deploy agile, low-cost solutions—sensor-based lighting and free public Wi-Fi—that deliver swift benefits but struggle to scale without sustained support. Across the eight cases, we identified four governance archetypes and six recurring implementation barriers—data silos, funding discontinuity, skills shortages, privacy concerns, evaluation gaps, and policy changes—which collectively influence smart-enabled resilience. The results indicate that aligning smart technologies with governance tiers, fiscal capacity, and demographic contexts is essential for achieving equitable and sustainable outcomes. We recommend tier-specific funding, mandatory co-design, and intergovernmental knowledge exchange to enable smaller cities to function as innovation labs while directing metropolitan centres towards inclusive, system-wide transformation. Full article

Citizen science (CS) is increasingly recognized as a complementary approach for addressing soil health challenges—including erosion, pollution, nutrient imbalances, and biodiversity loss—by harnessing public participation to broaden spatial and temporal data collection. This review synthesizes findings from the following: (i) a systematic analysis of peer-reviewed literature and grey sources, (ii) a database of 96 CS initiatives compiled by the European PREPSOIL project, and (iii) questionnaire surveys and workshops conducted in five Living Labs across Europe. Our analysis indicates that volunteer-driven monitoring can enhance the volume and granularity of soil data, providing critical insights into parameters such as organic carbon content, nutrient levels, and pollutant concentrations. However, persistent challenges remain, including inconsistencies in data validation, volunteer attrition, and concerns regarding digital literacy and data privacy. Despite these challenges, ongoing efforts to standardize protocols, integrate remote sensing and sensor-based validation methods, and employ feedback mechanisms improve data reliability and participant engagement. We conclude that sustained capacity-building, transparent data governance, and stakeholder collaboration, from local communities to governmental bodies, are essential for fully realizing the potential of citizen science in soil conservation. This work is framed within the context of the European Soil Mission, and CS is demonstrated to meaningfully support sustainable land management and evidence-based policymaking by aligning public-generated observations with established scientific frameworks. Full article

Background: The availability of laboratory tests to screen and diagnose migrants and travellers for neglected and tropical parasitic diseases significantly impacts individual and public health. Italian scientific societies for parasitology, tropical diseases, and global health developed a survey to assess number and geographical localisation of laboratories able to carry out adequate diagnostics. Methods: An open-ended and multiple-choice questionnaire was constructed and sent to 752 members working in Italian microbiology laboratories via scientific societies’ mailing lists. Data concerning malaria, cystic echinococcosis, leishmaniasis, schistosomiasis, strongyloidiasis, and Chagas disease were included. Results: Members from 96 laboratories replied. At least one laboratory responded from 18 out of 20 Italian regions. Serological tests for Schistosoma spp., Strongyloides stercoralis, Trypanosoma cruzi, Echinococcus spp., and Leishmania spp. are performed in <50% of responding laboratories. Only 56.6% of labs provide all three recommended tests for malaria diagnosis in the emergency room. Direct identification methods availability varies for Schistosoma eggs (75–95.8%), S. stercoralis larvae (53.1%), trypomastigotes (59.4%), and Leishmania amastigotes (53.1%). Geographical differences (mainly northern versus southern regions) were evident. Conclusions: The survey underlines the need to improve diagnosis for neglected and tropical diseases, to define a network of reference laboratories for testing less prevalent diseases, and to share information, education, and training for both clinicians and microbiologists/parasitologists. Full article