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Sphere inversion of knots: the trefoil and figure-eight knots
Full text linkLa geometría inversiva es una herramienta fundamental en la geometría moderna por su capacidad para transformar conformemente rectas, circunferencias, planos y esferas, re- velando relaciones profundas entre distintas configuraciones geométricas. Este trabajo presenta los principios básicos de la inversión en el plano y en el espacio, junto con una breve contextualización histórica desde el siglo XIX. Asimismo, se examina la inversión esférica como extensión tridimensional y se ilustran aplicaciones en teoría de nudos mediante los casos del nudo trébol y del nudo ocho, mostrando cómo la inversión ofrece nuevas representaciones y perspectivas topológicas.
Inversive geometry is a fundamental tool in modern ge- ometry due to its ability to conformally transform lines, cir- cles, planes and spheres, revealing deep relationships be- tween different geometric configurations. This work presents the basic principles of inversion in the plane and in space, together with a brief historical contextualization since the nineteenth century. It also examines spherical inversion as a three-dimensional extension and illustrates applications in knot theory through the cases of the trefoil knot and the figure-eight knot, showing how inversion provides new repre- sentations and topological perspectives.Full Tex
Wastewater analysis as a global toxicovigilance tool for the monitoring of new psychoactive substances
Full text linkNew psychoactive substances are a group of synthetic or naturally occurring drugs that mimic the effects of controlled illicit drugs. With limited information around potency, effects and health risks, there is international concern around their use and thus surveillance efforts are needed for public health. This study presents a global assessment of new psychoactive substances in influent wastewater from 52 sites across 20 countries during the 2022/2023 New Year period. Using solid-phase extraction followed by liquid chromatography-tandem mass spectrometry, 21 new psychoactive substances were detected with mitragynine, 3-methylmethcathinone, and eutylone being the most prevalent. Notably, 3,4-methylenedioxy-PV8 was identified for the first time in sites in Australia and the United States. A retrospective analysis of population normalised mass loads for 3-methylmethcathinone at European sites revealed downward trends in 2022/2023 sampling period compared to the previous years, suggesting a possible impact of regional scheduling measures. Additionally, this work demonstrates the stability of new psychoactive substances in loaded cartridges for up to four months when stored at -20 °C. These findings highlight the value of wastewater-based epidemiology for global monitoring of emerging new psychoactive substances threats and policy evaluation.Full Tex
Neuroinflammation in the nerve roots and dorsal root ganglion decreases following 6 weeks of neural tissue management: PET/CT imaging findings in a patient with painful cervical radiculopathy
Full text linkBACKGROUND: There is increasing interest in uncovering working mechanisms of physiotherapy interventions. Advanced medical imaging enables in-vivo visualisation and quantification of neuroinflammation. This case report reveals for the first time how neuroinflammation in the nervous system may change following neural tissue management. CASE DESCRIPTION: A 56-year-old man presented with a 9-month history of left C7 painful radiculopathy. He reported arm and neck pain, and numbness in the C7 dermatome. Elbow extension strength was reduced. The neurodynamic test (median nerve) was positive. MRI confirmed nerve root compression due to disc herniation C6/C7. Dynamic [11C]DPA713 PET/CT imaging revealed neuroinflammation at the neuroforamen and spinal cord. While being on the surgical waitlist, he received six weeks of neural tissue management, which included 12 sessions of nerve and joint mobilisation, and a home program of neurodynamic exercises. OUTCOME: At 6-weeks follow-up, arm and neck pain intensity had markedly reduced, which was maintained at 6 months. These improvements coincided with a substantial decrease in neuroinflammation at the affected neuroforamen (PET/CT: VT: from 12.96 to 6.21). No meaningful decrease was observed in the spinal cord (VT: from 6.43 to 5.38). DISCUSSION: Following six weeks of neural tissue management, in vivo measures of neuroinflammation reduced substantially at the affected nerve roots and dorsal root ganglion, which coincided with decreased neck and arm pain. CONCLUSION: Changes in neuroinflammation exceeding the smallest detectable difference can be measured following neural tissue management in a patient with painful cervical radiculopathy. A randomised trial to validate these findings is warranted.Full Tex
Hybrid SVM–XGBoost framework for wildfire susceptibility mapping in palm oasis ecosystems to enhance risk assessment in arid and semi-arid regions
No full textOasis fires have become increasingly frequent due to climate change, threatening fragile ecosystems and agricultural livelihoods, particularly in the semi-arid region. This study develops a data-driven fire susceptibility mapping framework for Errachidia province, Morocco, integrating Sentinel-2 satellite imagery and machine learning (ML) models, including support vector machines (SVM), random forest (RF), and eXtreme gradient boosting (XGBoost). Unlike previous studies focusing on Mediterranean and arid landscapes, this research explicitly addresses wildfire susceptibility mapping in Moroccan oasis ecosystems, where limited scientific assessments exist. The study introduces an innovative ML-based fire susceptibility mapping framework for palm oasis ecosystems, which compiles multi-source geospatial datasets, including topographic, meteorological, and anthropogenic variables, to identify fire-prone areas from 2019 to 2024. Advanced feature selection and data preprocessing techniques were employed to enhance model efficiency. The dataset was split into 70% training and 30% testing, with model performance assessed using multiple metrics, including ROC-AUC, precision, recall, and F1-score. This work’s innovative hybrid SVM–XGBoost model demonstrated superior predictive accuracy, achieving an impressive 0.996 AUC, outperforming stand-alone models. The susceptibility maps identified high-risk hotspots near Oued Ziz, Ouled Chaker, and Aoufous Oases, where vegetated loss exceeded 30 hectares based on NDVI analysis. This study contributes to wildfire risk management by providing a robust, validated, and transferable methodology for fire prediction in arid and semi-arid ecosystems. The findings offer critical insights for targeted mitigation strategies, including optimized firebreak placement and community-driven fire awareness programs. Integrating remote sensing with ML, the proposed framework enhances early warning systems and adaptive wildfire resilience strategies, making it applicable to global fire-prone ecosystems facing similar climatic challenges.No Full Tex
Fight Fire With Fire: How Does AI-Powered Technology Empower the Elderly Anti-AI Fraud Through a Socio-Technical Systems Theory Lens?
No full textAs digital fraud increasingly exploits artificial intelligence (AI), the elderly, due to their limited digital literacy and declining cognitive abilities, have become vulnerable targets. This paper examines how AI technology enables the elderly to protect themselves from online fraud stemming from complex technologies through the lens of socio-technical system (STS) theory. Using the “Silver Guardian” project, developed under the Cyber-Shield Security Ecosystem of a Chinese company, as an example, this study explores the effectiveness of jointly optimizing the technical and social subsystems within the STS to tailor anti-fraud products for elderly consumers. Throughout the stages of product formation, iteration, and upgrading to cloud-based prevention, the AI-based anti-fraud technology subsystem is aligned with the social subsystem of the elderly, characterized by low digital literacy, high emotional vulnerability, and specific cognitive limitations, achieving a progressive development of the consumer-brand relationship from ability and benevolence to integrity trust, via a “controlled, cooperative, and evaluative” iterative algorithm governance model. This significantly enhances the product's technical performance and reduces the AI fraud risk for the elderly at each stage. Theoretically, this study synthesizes prior work on consumer fraud, elderly vulnerability, AI as a double-edged sword, and STST, advancing understanding of consumer well-being and theoretical disclosures on vulnerable consumers, proposes an integrative socio-technical framework that moves beyond fragmented perspectives to optimize technical and social subsystems, and forms a novel theoretical lens extending in consumer behavior, algorithmic governance, and brand trust, offering a holistic explanation of AI's dual role in exploiting and protecting vulnerable populations. Practically, by understanding the dual role of AI in both promoting and combating fraud, this study develops a generalized roadmap, and suggests technical and policy intervention directions to protect vulnerable groups from AI fraud.No Full Tex
Neuron Abandoning Attention Flow: Visual Explanation of Dynamics Inside CNN Models
Full text linkIn this paper, we present a Neuron Abandoning Attention Flow (NAFlow) method to address the unsolved problem of visually explaining the attention evolution dynamics inside CNNs when making their classification decisions. A novel cascading neuron abandoning back- propagation algorithm is designed to precisely exclude the abandoned neurons on all intermediate layers inside a CNN model for the first time. Firstly, a Neuron Abandoning Back-Propagation module is proposed to generate Back-Propagation Feature Maps (BPFM) by using inverse function of the intermediate layers of CNN models, on which the neurons not used for decision-making are removed. Meanwhile, the cascading NA-BP modules calculate the tensors of importance coefficients which are linearly combined with the tensors of BPFMs to form the NAFlow. Secondly, to be able to visualize attention flow for similarity metric-based CNN models, a new channel contribution weights module is proposed to calculate the importance coefficients via Jacobian Matrix. Extensive evaluations demonstrate the effectiveness of the proposed NAFlow across eleven widely-used CNN models for various tasks of general image classification, contrastive learning classification, few-shot image classification, and image retrieval.Full Tex
Benchmarking soil potassium extraction methods and establishing critical thresholds for wheat production in Inceptisols
Full text linkAccurate assessment of plant-available potassium (K) in soils is crucial for optimizing crop nutrition and enhancing the efficiency of fertilizer use. This study systematically benchmarked ten widely used soil K extractants, Calcium Chloride (CaCl2), Ammonium Acetate (NH4OAc), Ammonium Bicarbonate-Diethylenetriaminepentaacetic Acid (AB-DTPA), Morgan's extractant (Morgan), Calcium acetate lactate extractant (Ca-AL), Kelowna extractant (Kelowna), Olsen extractant (Olsen), Modified Kelowna extractant (Kelowna-2), Nitric Acid (HNO₃), and Sodium Tetraphenylborate (NaTPB) to identify the most effective method for quantifying available K and defining critical thresholds for wheat production in Inceptisols. Pot trials were conducted on soils from twenty Inceptisol series in the Gangetic alluvial plains of Eastern India using five K fertilizer rates that simulates the wide K variability in real field situations. Among the tested methods, NaTPB emerged as the most reliable extractant, showing the strongest correlation (R2 = 0.83, P < 0.05) with Bray’s percent yield (BPY) and a critical K threshold of 1110.3 kg ha−1. CaCl2 also demonstrated high accuracy (R² = 0.82). Multivariate analysis revealed that NaTPB-extractable K was significantly influenced by soil clay content and electrical conductivity, which together explained 76.9 % of its variability. Furthermore, NaTPB effectively captured K from multiple pools, including water-soluble, exchangeable, and non-exchangeable pools, providing a more comprehensive index of plant-available K. A critical K concentration of 0.35 % in wheat grain was identified as the threshold for optimal yield, offering a practical benchmark for site-specific K management. By integrating chemical extraction, crop response modeling, and soil property analysis, this research presents a novel and scientifically robust framework for assessing K fertility. With the successful implementation in Eastern India, the findings have benchmarked broader applicability to Inceptisols in other agroecological regions, providing a scalable diagnostic approach for sustainable nutrient management. This study makes a significant contribution to precision agriculture and global efforts to optimize fertilizer recommendations through the development of improved soil testing methodologies.Full Tex
Assessing Python’s suitability for airborne safety-critical systems under DO-178C guidelines
Full text linkPython is a widely adopted programming language celebrated for its ease of use, dynamic typing, and strong community support. Despite these advantages, Python presents challenges when considered for safety-critical applications, notably those in airborne systems. Concerns arise from performance limitations, limited compile-time checking, and dynamic features that may impact reliability in environments where failures can have severe consequences. Airborne systems, with their stringent safety requirements, provide a context in which these challenges can be critically examined.
This study evaluates Python’s alignment with the objectives defined in DO-178C (Software Considerations in Airborne Systems and Equipment Certification). By analyzing Python’s core characteristics against these rigorous standards, we highlight potential compliance gaps and practical challenges that may hinder its use in safety-critical contexts.
In addition, we perform a comparative analysis between Python and Rust—a modern systems programming language noted for its safety guarantees and performance. Rust was selected not as a replacement for established baselines such as Ada, C, and C++, but as a complementary point of comparison illustrating how a newer, safety-oriented compiled language contrasts with Python’s interpreted model. Our findings indicate that Python lacks compile-time error checking, exhibits delayed signal handling, and has limited optimization capabilities, which together may affect its performance and reliability. Potential enhancements such as Just-In-Time (JIT) compilation, advanced static analysis, and robust type-checking tools are recommended to mitigate these issues. Overall, our study emphasizes both the strengths and limitations of Python and suggests pathways to improve its viability for safety-critical use.Full Tex
Compassionate communities, Māori ageing and end-of-life: A systematic review
Full text linkBackground:
Māori people in Aotearoa New Zealand and Australia experience significant healthcare inequity as they age and towards the end of their lives. Compassionate community approaches to ageing and end-of-life care are increasing in popularity throughout the world. However, this approach has arisen from Eurocentric knowledge systems and not from First Nations people and their communities.
Objectives:
This research aimed to gain insight into what the Compassionate Communities approach means for First Nations people and identify implications for Māori in Aotearoa New Zealand and Australia. A systematic literature review explored the intersection of Compassionate Communities and First Nations peoples’ perspectives and needs. Addressing the overarching question of: What does the Compassionate Communities approach mean for older First Nations people?
Design:
A Kaupapa Māori approach was used to answer the research question and to explore the literature retrieved.
Methods:The main literature search was conducted during 2020–2022, with subsequent searches in 2023 and a final search in 2025. The review was conducted in Covidence systematic review software following the PRISMA process. Screening was completed by two reviewers and assessed against the inclusion and exclusion criteria. Kaupapa Māori theoretical questions were applied to each full-text article, with a rating of positive, neutral or negative allocated to establish conceptual alignment. NVivo thematic analysis software was utilised to code and explore themes.
Results:
Fifty papers were imported into Covidence, with 22 studies included in the final review.
Conclusion:
The review found minimal discussion about how Compassionate Communities approaches are implemented in a way that includes First Nations knowledges of ageing and end of life. There is a greater need to understand the contribution First Nations peoples’ wellness philosophies make to the Compassionate Communities approach. Evaluations of Compassionate Community initiatives need to be more inclusive of First Nation peoples and their knowledges. In Aotearoa New Zealand and Australia, more research is needed to understand pathways to well-being for older Māori people based upon existing community strengths to ensure flourishing futures. Addressing these knowledge deficits will support efforts to address the inequities experienced by First Nations people as they age and at the end of life.Full Tex
When students run the clinic, who's watching? A call for a framework to evaluate student-run clinics
No full textStudent-run clinics (SRCs), in which medical and health professions students take responsibility for operational and logistics management of charitable clinics,2 are a powerful expression of service-based learning: students hone clinical and administrative skills while communities receive essential medical services that might otherwise be unavailable. Yet over the past 20 years, these clinics have begun globalising2–5 and increasing in complexity.5 This is happening within a landscape of limited evidence,5 6 growing concerns about ethics and substandard care,7–13 and a lack of clear standards and accountability.7 Together, these features raise an inescapable question: when students run the clinic, who’s watching?No Full Tex