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Advancing the use of metabarcoding derived nematode-based indices as soil health bioindicators in agricultural and natural environments
No full textEffective frameworks for assessing soil health are a priority, yet the value and adoption of soil biological indicators remain debated. Biological indicators provide essential information on ecosystem functions such as nutrient cycling, population regulation, and organic matter decomposition. Nematode-based indices (NBIs) have long been used by soil ecologists to study biodiversity, the soil food web and ecosystem functions. DNA metabarcoding of soil nematode communities is being increasingly used as a more cost-efficient and high-throughput approach than traditional morphology-based identification. Molecular-based NBIs have great potential as soil health bioindicators if method uncertainties can be addressed. We critically review recent nematode metabarcoding methods for soils and highlight the advantages and limitations associated with different workflow steps including the nematode elutriation method, DNA extraction method, barcode and primer choices, and database selection. Based on an analysis of 95 studies, we propose an updated standardised metabarcoding workflow that includes (a) nematode elutriation from large soil quantities, (b) bulk nematode DNA extraction, (c) the use of the 18S rRNA primers NF1/18Sr2b and (d) curated reference databases for sequence identification. While challenges in concordance between molecular and morphological NBIs remain, improved standardisation of DNA metabarcoding protocols may enable more detailed investigations of nematode distribution across diverse environments and testing of molecular-based NBIs in relation to soil disturbances, management practices, temporal scales, soil functional processes, and soil physicochemical properties. These efforts could strengthen the inclusion of NBIs in models and frameworks supporting soil health management strategies
Majorana quasiparticles in atomic spin chains on superconductors
No full textFor the past decade, Majorana quasiparticles have become one of the hot topics in condensed matter research. Besides the fundamental interest in the realization of particles being their own antiparticles, going back to basic concepts of elementary particle physics, Majorana quasiparticles in condensed matter systems offer exciting potential applications in topological quantum computation due to their non-Abelian quantum exchange statistics. Motivated by theoretical predictions about possible realizations of Majorana quasiparticles as zero-energy modes at boundaries of topological superconductors, experimental efforts have focussed in particular on quasi-one-dimensional semiconductor–superconductor and magnet–superconductor hybrid systems. However, an unambiguous proof of the existence of Majorana quasiparticles is still challenging and requires considerable improvements in materials science, atomic-scale characterization and control of interface quality, as well as complementary approaches of detecting various facets of Majorana quasiparticles. Bottom-up atom-by-atom fabrication of disorder-free atomic spin chains on atomically clean superconducting substrates has recently allowed deep insight into the emergence of topological sub-gap Shiba bands and associated Majorana states from the level of individual atoms up to extended chains, thereby offering the possibility for critical tests of Majorana physics in disorder-free model-type 1D hybrid systems
Correction to: “Pink power”—the importance of coralline algal beds in the oceanic carbon cycle (Nature Communications, (2024), 15, 1, (8282), 10.1038/s41467-024-52697-5)
No full textFinding the Optimal Convolutional Kernel Size for Semantic Segmentation of Pole-like Objects in Lidar Point Clouds
No full textAbstract. Pole-like objects (PLOs) are important street assets in urban environments, yet current deep learning methods often underperform in their segmentation compared to other objects. The main challenge is determining the right kernel size to effectively understand the unique structure of PLOs with an appropriate receptive field. In this study, we improve the segmentation performance of PLOs by optimizing the kernel size in a KPConv-based network. Our experiments show that kernel size of 9 yields an Intersection over Union (IoU) of 95.02% on the Parkville-3D dataset. We also develop a post-processing approach that transforms semantic segmentation outputs into panoptic segmentation results, enabling accurate detection of individual PLO instances. Furthermore, qualitative tests on an independent, unlabelled point cloud dataset from a different urban area demonstrate that our method consistently achieves accurate segmentation
Selective In Situ Phase Segregation Enabling Efficient and Stable Protonic Ceramic Fuel Cell Cathode Performance
No full textEfficient and reliable protonic ceramic fuel cells (PCFCs) necessitate the development of active and durable cathode materials to accelerate the sluggish oxygen reduction reaction (ORR). The most promising PCFC cathode candidates are perovskite-type structured oxides with mixed oxygen ion, proton, and hole conductivity. However, mixed conductivity often requires materials with alkaline earth elements and the inclusion of these elements in the cathode structure leads to severe degradation in the presence of even small trace amounts of CO2 in air. Herein, a new approach is presented to address this challenge by inducing selective in situ phase segregation to engineer the cathode surface and bulk separately. This selective phase segregation is achieved via targeted control of the size mismatch of cations in the perovskite-type structure, enhancing charge transfer in the bulk while improving CO2 resistance at the surface. By co-incorporating smaller Li+ and larger K+ into the model BaCo0.4Fe0.4Zr0.1Y0.1O3−δ cathode material, it is shown that Li+ segregates to the surface, protecting it from CO2 poisoning, while K+ remains in the bulk and accelerates proton transport. Consequently, this in situ restructured cathode can boost the PCFC power output by 30% and improve its CO2 tolerance fivefold in the presence of CO2 at 600 °C
Enhancing Vaccine Safety Surveillance: Extracting Vaccine Mentions from Emergency Department Triage Notes Using Fine-Tuned Large Language Models
No full textThis study evaluates fine-tuned Llama 3.2 models for extracting vaccine-related information from emergency department triage notes to support near real-time vaccine safety surveillance. Prompt engineering was used to initially create a labeled dataset, which was then confirmed by human annotators. The performance of prompt-engineered models, fine-tuned models, and a rule-based approach was compared. The fine-tuned Llama 3 billion parameter model outperformed other models in its accuracy of extracting vaccine names. Model quantization enabled efficient deployment in resource-constrained environments. Findings demonstrate the potential of large language models in automating data extraction from emergency department notes, supporting efficient vaccine safety surveillance and early detection of emerging adverse events following immunization issues
Innovations in reproductive medicine, Gartner Hype Cycle and Dunning–Kruger effect
No full textIn the dynamic field of reproductive medicine, the introduction of new technologies often follows a modified Gartner Hype Cycle, characterized by initial enthusiasm, unmet inflated expectations and eventual disillusionment. This paper explores how the Dunning-Kruger effect, where individuals overestimate their knowledge and competence, contributes to the Gartner Hype Cycle in reproductive medicine. By examining the history of the endometrial scratch, the paper illustrates the negative impact of prematurely adopted innovations. The authors stress the urgent need for a more rigorous approach to designating interventions as 'innovative' and call for robust data collection and analysis evaluating their safety and effectiveness. There is a balance between the need for innovation and the imperative to protect patients from harm, while ensuring the cost-effectiveness of reproductive technologies. The paper emphasizes the importance of evidence-based practice encompassing interventions undergoing thoroughly vetted scientific research before being widely adopted. It underscores the role of regulatory bodies in overseeing the introduction of new technologies to prevent the premature implementation of unproven methods. We propose the creation of comprehensive national and international databases accessible to researchers and clinicians. These would facilitate the rapid and reliable assessment of new treatments, allowing for continuous monitoring of their safety and efficacy. This paper advocates for a cautious and measured approach to innovation, ensuring that advancements are scientifically validated and clinically beneficial
POS1016-PARE EMBEDDING A CONSUMER-DRIVEN APPROACH INTO AUSTRALIAN ARTHRITIS RESEARCH: GUIDANCE FROM A NATIONAL MULTI-STAGE CONSULTATION
No full textCatalytic Membrane Vacuum Regeneration: Enhancing Energy Efficiency and Renewable Compatibility in Direct Air Capture
No full textLiquid-based CO2 direct air capture (DAC) is a pivotal technology for mitigating climate change. Energy-intensive CO2 desorption, high regeneration temperatures, and solvent degradation are key challenges. Here, low-temperature catalytic membrane vacuum regeneration (C-MVR) as a promising approach for sustainable and energy-efficient DAC is developed and evaluated. Noncatalytic experiments are conducted using three commercial membrane modules and four green amino acid salts under varying conditions (e.g., temperatures and flowrates). Based on CO2 transfer rates, ultra-thin dense composite membranes and aqueous potassium taurinate (TauK) are the most promising for MVR in DAC applications. For C-MVR trials, commercial ion-exchange resin improves CO2 desorption fluxes by up to 64.4% and reduces thermal energy requirements by up to 39.1%. TauK demonstrates the highest CO2 flux and lowest thermal energy consumption. Parametric analysis of catalyst performance for varying temperatures, catalyst amount, and solvent concentrations is also performed. To minimize any potential precipitation in TauK, potassium carbonate (K2CO3) is added, showing minimal impact on CO2 desorption kinetics and catalyst improvement. The findings of this study highlight the practical applicability of C-MVR using green amino acid salts as a sustainable approach to boost CO2 desorption rate and reduce thermal energy input
Understanding the Association Between Home Broadband Connection and Well-Being Among Middle-Aged and Older Adults in China: Nationally Representative Panel Data Study
No full textBACKGROUND: Access to digital technology is among the major social determinants of health, and digital divide impacts health inequality. Yet, the impact of digital connectivity on the well-being and psychosocial outcomes in adults has not been fully studied. OBJECTIVE: The aim of this study was to investigate the association of home broadband connection with health and well-being of middle-aged adults and adults older than 45 years in China. METHODS: A panel data study design of the national sample of China Health and Retirement Longitudinal Study (CHARLS) was conducted in 2015, 2018, and 2020. This study included 16,185 participants older than 45 years. The associations between digital connectivity (home broadband connection), loneliness, social participation, and life satisfaction were assessed using mixed effects logistic regression models, adjusting for socioeconomic factors, behavioral factors, and locality. Broadband internet connectivity, feelings of loneliness, social participation, and satisfaction with life were measured using the self-reported CHARLS questionnaire. RESULTS: We observed a substantial increase in digital connectivity from 29.5% in 2015 to 59.8% in 2020. Broadband internet connection at home was positively correlated with social participation (adjusted odds ratio [AOR] 1.34, 95% CI 1.28-1.41) and life satisfaction (AOR 1.30, 95% CI 1.20-1.40), after adjusting for confounding factors, while the absence of broadband internet connection was associated with increased loneliness (AOR 0.81, 95% CI 0.77-0.86). These associations were consistent across age, gender, socioeconomic groups, and geographic areas. CONCLUSIONS: This study highlights the potential additional health benefits of digital connectivity beyond the known advantages. Our results suggest the importance of expanding broadband access to enhance social inclusion and life satisfaction. Further research is needed to understand the broader implications and digital determinants of health associated with digital connectivity