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'Human-nature relations like a boomerang': a case study on children's visions of nature
No full textThis study examines the views and values of children regarding nature and the human-nature relationship using Visions of Nature framework components, namely images of nature, values towards nature, and images of human-nature relationship (typologies). Employing a case study, semi-structured interviews along with guided-imagery and photo-elicitation techniques were used. The findings revealed that nature was viewed as away from city life and technology, where natural settings were depicted as forests and wetlands with various animal species. Mostly nature was seen as indispensable by rationalizing its importance with instrumental value, focusing on nature's necessity for humans' survival and health. For typologies showing the appropriate relationship between humans and nature, the children preferred Steward, Partner, and Participant. This study comprehensively approaches the interplays between visions of nature components and introduces a new visual-qualitative tool to examine children's views on the human-nature relationship. It suggests for school curricula to incorporate diverse perspectives for visions of nature to prepare future generations to achieve sustainable development goals (SDGs). [GRAPHICS]
Microbial and environmental interactions of the 2021 mucilage event in the Sea of Marmara
No full textIn 2021, the Sea of Marmara (SoM) experienced an extensive mucilage event that severely impacted marine ecosystems. While nutrient enrichment, temperature anomalies, and anthropogenic stressors are known contributors to such events, the microbial and environmental mechanisms remain unclear. Here we combined environmental DNA (eDNA) metabarcoding of 16S, 18S, and ITS regions with in situ physicochemical measurements and historical data to characterize microbial communities and environmental conditions across 39 samples from 24 stations during and after the mucilage event. Our results revealed that mucilage formation was associated with a distinct microbial community shift, including the dominance of Dinophyceae, diatoms, Chytridiomycota, and exopolymer-degrading bacteria such as Polaribacter and Lentimonas . Parasitic fungal genera like Cladosporium , Candida, and chytrids (phylum Chytridiomycota) likely contributed to bloom collapse and organic matter accumulation. In contrast, post-mucilage samples exhibited increased abundance of Synechococcus , Halteria , Actinobacteria, and Ilumatobacteraceae , indicating microbial recovery. Anomalous patterns at the Ergene discharge station, including the dominance of Cutaneotrichosporon debeurmannianum , underscored the influence of localized pollution on community structure and potential health risks. These findings highlight that microbial community imbalance—often linked to nutrient fluctuations—plays a key role alongside physicochemical factors in shaping mucilage dynamics, indicating the importance of integrated microbial and environmental monitoring in eutrophication-prone marine systems. Understanding microbial and environmental shifts during the 2021 outbreak will help prevent future outbreaks
Psyllium and its role in improving rheology and structural properties of aquafaba cakes
No full textBACKGROUND The demand for vegan and gluten-free baked goods is increasing due to allergen concerns and plant-based diets. This study evaluates the formulation of a vegan, gluten-free cake using aquafaba powder as an egg replacer, psyllium powder as a binding agent, and rice flour as the primary structural ingredient. The performance of these ingredients was compared to egg-based controls.RESULTS Aquafaba (0.5 and 1.0 g) and psyllium (0.1-0.5 g) levels were analyzed for their effects on batter properties and cake quality. Characterization included cake volume, baking loss, moisture content, water activity, rheology, and texture analysis. Intermediate psyllium levels resulted in the highest cake height and a uniform crumb structure, comparable to egg-based cakes. Increasing psyllium improved viscosity and stability, enhancing air retention during baking. Cakes with higher psyllium levels exhibited reduced baking loss and improved moisture retention. The combination of aquafaba and psyllium produced cakes with structural and textural properties similar to egg-based formulations, making them effective alternatives. However, excessive psyllium (0.4 and 0.5 g) led to a denser texture.CONCLUSION Psyllium powder, combined with aquafaba, serves as a viable egg alternative in vegan and gluten-free cakes, providing comparable structure, moisture retention, and texture. Optimizing psyllium levels is essential to achieving desirable cake properties. (c) 2025 Society of Chemical Industry
Assessment of Potential Side Effects Related To RAB27A Gene Therapy in Stem Cells
No full textRAB27A plays an essential role in the regulation of exocytosis and intracellular vesicle trafficking. Loss-of-function mutations in the RAB27A gene cause dysfunctional immune cells and Griscelli Syndrome Type 2 (GS-2), whereas upregulation of RAB27A in cancer cells is associated with a worse prognosis and increased metastasis. Here, we wanted to assess the potential side effects of overexpression of RAB27A in different types of healthy stem cells as preparation for the development of gene therapy for GS-2. Bone marrow mesenchymal stem cells (BM-MSCs) were obtained from GS-2 patients and healthy donors. Healthy murine bone marrow-derived and human cord blood-derived hematopoietic stem/progenitor cells (HSPCs) were transduced with different lentiviral vectors carrying a codon-optimized RAB27A (RAB27Aco) transgene. Cells were used for in vitro functional assays and assessed using flow cytometry, Western Blot and RT-PCR. In vivo transplantation assays in mice were used to assess the effect of RAB27A on stem cell function. Engraftment was assessed using flow cytometry, sections of BM-MSC injection sites were analyzed using histological staining. Overexpression of RAB27A resulted in phenotypic changes in BM-MSCs and decreased colony-forming capacity of HSPCs. Transplantation of RAB27A + stem cells was not associated with any tumorigenesis. Despite high expression of RAB27A in HSPCs before transplantation, RAB27A levels in peripheral blood, bone marrow, and spleen cells remained low, indicating overexpression of RAB27A may have affected the long-term reconstitution potential. Development of gene therapy for GS-2 may require fine-tuning of RAB27A expression but is not likely to be complicated by RAB27A-induced tumorigenesis
An integrated qualitative farm-to-fork approach to rank foodborne pathogens associated with mastitis-affected raw milk from Irish dairy farms to the consumer
No full textA qualitative microbial risk assessment (MRA) framework was applied to evaluate the potential introduction of foodborne pathogens from bovine mastitis raw milk into the dairy chain. In a survey between January and December 2024, 588 raw milk samples were obtained from mastitis affected cows across 66 Irish dairy farms. Following guidelines from the International Dairy Federation and National Mastitis Council, samples were analysed for mastitis pathogens, where 337 positive samples (55.3 %) were further tested for seven foodborne microbial pathogens using a hierarchical testing strategy with ten culture-based methods. A qualitative MRA guided by the FAO/WHO and EFSA framework was developed in this study. Incorporating stages of the risk assessment paradigm that include hazard identification, hazard characterisation, exposure assessment, and risk characterisation through a structured decision-tree approach. For the survey, Streptococcus spp. was most frequently isolated (n = 123), followed by Escherichia coli (n = 76), Staphylococcus aureus (n = 67), and coagulase-negative staphylococci (CNS) (n = 39). Less frequently detected pathogens included Enterococcus spp. (n = 15), Salmonella spp. (n = 4), and Bacillus cereus (n = 1). Exposure assessment and risk characterisation identified S. aureus, E. coli, and Salmonella spp., as high risk, necessitating targeted interventions within dairy chain systems, including processing failures. This study provides novel insights into the risks posed by mastitisassociated foodborne pathogens, facilitating evidence based recommendations for improving dairy safety management in the dairy chain
The flawed logic of theory-free natural kind reasoning
No full textThis paper critiques the theory-neutral Natural Kind Reasoning (NKR) in consciousness science. It demonstrates a methodological incompatibility arising from McKilliam's (2024) proposal: deploying Inference to the Best Explanation (IBE) within NKR directly contradicts the aspiration for theory-neutrality. I argue that IBE's inherent reliance on pre-existing theoretical frameworks undermines the possibility of a genuinely theory-neutral methodology for the science of consciousness
Multilingual Implicit Discourse Relation Recognition via Abstract Object-Enhanced Chain-of-Thought Prompting
No full textLarge language models (LLMs) have demonstrated remarkable performance across a wide range of NLP tasks. However, their effectiveness in discourse parsing remains underexplored where the existing LLM-based attempts fall significantly short of the performance achieved by the encoder-based models. In this study, we propose a Chain-of-Thought (CoT) prompting approach for the task of implicit discourse relation recognition (IDRR), leveraging the concept of abstract objects. We show that guiding the model to identify abstract objects within the arguments of the discourse relation systematically enhances the classification performance across both Level-1 and Level-2 senses, in both monolingual and multilingual settings. Through experiments on three monolingual and one multilingual corpora, covering seven languages and annotated according to PDTB 3.0, we demonstrate that our CoT-style prompting approach achieves significant improvements over previous LLM-based methods
Experimental Evaluation of Electric Powertrain System for Unmanned Aerial Vehicles
No full textWith the growing use of unmanned aerial vehicles (UAVs) in both civil and military applications, optimizing electric powertrain systems is essential to enhance endurance, efficiency ((Formula presented.)), and mission adaptability. This study explores the impact of commercially available propeller variations on UAV powertrain performance, keeping the battery, ESC, and brushless DC motor fixed. The hypothesis is that propeller geometry plays a critical role in thrust production and flight endurance. To validate this, several off-the-shelf propellers are experimentally tested using a dynamometer setup that measured thrust, RPM, voltage, and current at various throttle levels. Results show that propeller P3_30 delivered the highest Thrust to Mechanical Power Ratio (TMPR) (8.48%), while P1_26 offered the longest endurance (16.17 min). Notably, efficiency ((Formula presented.)) peaked at 93.1% for the P1_26 propeller configuration, further supporting its suitability for long-duration missions. These insights provide a practical performance guide for UAV designers and emphasize the value of experimental benchmarking in selecting propulsion components for mission-specific UAV configurations
Light pollution trends for International Dark Sky Places using VIIRS nighttime light composite data
No full text Abstract International Dark-Sky Places (IDSPs) is a global project led by the International Dark-Sky Association (IDA) to protect dark-sky areas for astronomical observation and astro-tourism. Currently, there are 216 IDSPs in the world. This study analyses light pollution trends in International Dark-Sky Places (IDSPs) using VIIRS night light composite data. IDSPs are mostly located near urbanised areas in Europe and away from urbanisation in North America. Dark and large areas away from urbanisation in South America, Africa, Central Asia and Australia offer great potential. Linear regression analysis shows that in 94% out of 216 places there is no change in artificial light at nigh (ALAN). There is a decrease in the level of artificial light in 3% and an increase in the level of artificial light in 3%. Unlike the linear regression analysis, Mann–Kendall and Sen slope analyses revealed significant statistical changes at the 105 sites (78 increasing and 27 decreasing). Machine learning models including decision tree regression (DTR), random forest regression (RFR) and gradient boosting regression (GBR) provided good predictive accuracy (R 2 > 0.6). Seasonal patterns were assessed using the Lomb–Scargle periodogram, but detected periodicities were considered false positives. These results emphasise the need for strategic planning to reduce light pollution in IDSPs, especially in underused areas. </jats:sec
An edge-intelligent three-tier framework for real-time forest fire detection, integrating WSNs, WMSNs, and UAVs
No full textForest fires are becoming prevalent, threatening ecosystems, economies, and public safety while creating an urgent demand for rapid and reliable detection systems. Conventional approaches such as watchtowers, manual patrols, and satellite imaging suffer from limited coverage, delays, and inadequate precision. To address these challenges, we propose a three-tier, edge-centric framework that integrates wireless sensor networks (WSNs), wireless multimedia sensor networks (WMSNs), unmanned aerial vehicles (UAVs), and lightweight machine learning (ML) and deep learning (DL) models for efficient detection. In the first tier, scalar sensors provide early hazard identification; in the second, smart sensors execute a lightweight ML model for intermediate verification, achieving a 94% F1-score with a minimal feature set; and in the third, UAVs equipped with sensors, cameras, and a compact convolutional neural network (CNN) deliver final confirmation. The CNN achieves state-of-the-art results with a 100% F1 score on the FireMan-UAV-RGBT dataset and 99.5% on UAV-FFDB while remaining compact (1.6 MB) and efficient (157 ms inference on Raspberry Pi 5), enabling real-time edge deployment. Simulations show reduced end-to-end delay (813.59 ms) compared to WSN-only (865.84 ms) and WMSN (1066.18 ms) baselines, improved throughput (7.05 kbps vs 3.80 kbps and 3.06 kbps), and a 100% delivery ratio. Real-world WSN testbed experiments further validate the framework, achieving a 97% delivery ratio, 144.39 ms latency (vs. 258.37 ms in simulations), and energy consumption of 0.0559 J/s (closely matching 0.0442 J/s in simulations). These results collectively demonstrate the practicality and effectiveness of the framework for real-time forest fire monitoring and rapid emergency response