Phthalates and pharmaceuticals in soil, groundwater, and surface water downgradient of a wastewater soil infiltration system

This study investigates the occurrence, attenuation, and ecological risks of phthalates and pharmaceuticals in a long-operating wastewater soil infiltration system in northern Sweden. Concentrations of 15 phthalates, 67 pharmaceuticals, caffeine, and acesulfame K were measured in influent wastewater, groundwater, soil, and a downgradient pond across multiple seasons. Results showed that most micropollutant removal occurred in the unsaturated soil zone prior to groundwater recharge, possibly due to processes such as biodegradation and sorption. Substantial reductions were observed for caffeine (&gt;99 %), carbamazepine (&gt;96 %), losartan (&gt;99 %), and phthalates (51 ± 72 % and 92 ± 5 %), with the higher attenuation for phthalates comparable to conventional activated sludge treatment. In contrast, compounds such as metoprolol exhibited moderate reductions (&gt;71 %), while others showed low or even negative attenuation, including diclofenac (46 % and −180 %) and ibuprofen (33 % and −11 %). After groundwater recharge, only ibuprofen showed attenuation beyond dilution, although the mechanisms for this remains unknown. Several pharmaceuticals, including metoprolol, irbesartan, and metformin, were detected in soil samples, though it is unclear whether they were sorbed to the soil matrix or present in porewater. In downgradient surface water, diclofenac and ibuprofen exceeded risk quotient thresholds, while oxazepam surpassed the lowest predicted no-effect concentration (PNEC) in one sample, indicating ecological risks. Overall, the findings highlight both the strengths and limitations of soil infiltration systems in mitigating micropollutant contamination, emphasizing the importance of vadose zone processes while underscoring uncertainties in sorption and degradation mechanismsFull text: CC BY license;</p

Digital Twins for Asset Management of Civil Structures : Perceived Potential and Practical Applications

The Engineering and Construction (E&amp;C) industry has vast potential to leverage technology for solving current asset management issues, with significant environmental and financial benefits. This study investigates the use of Digital Twins (DTs) for asset management of civil structures, identifying a gap between the perceived potential of DTs and practical applications due to misconceptions, industry fragmentation, and lack of standardizations. To address this, a literature review and experimental programs were conducted, leading to the development and validation of a proof-of-concept DT platform applied to two case studies. The study concludes with a purpose-driven DT roadmap to address the gap between potential and practical applications in the E&amp;C industry. Background: the integration of Building Information Modeling (BIM) and DTs for asset management in construction offers a promising solution to improve current processes, which are often time-consuming or inefficient. With technology rapidly advancing and the advent of Industry 4.0, there is a growing belief in the transformative potential of DTs to address longstanding challenges within the industry. By leveraging these innovative tools, stakeholders aim to enhance operational efficiency, optimize maintenance practices, and ultimately revolutionize infrastructure asset management. Aims and objectives: this study aims to investigate the use of DTs to improve asset management processes within the E&amp;C industry. The objectives include a thorough investigation of DTs, establishing their purpose within the industry, proposing a replicable DT methodology, demonstrating the methodology through case studies, and addressing the gap between potential and practical applications to promote DT dissemination. Methodological approach: i. Identify problem: thorough literature review and DT investigation (Paper I). ii. Define solution: understand the purpose of DT applications in E&amp;C (Paper II). iii. Methodology and Demonstration: propose and demonstrate a replicable DT methodology through experimental work, digital modelling, and case studies (Papers III, IV, and V). iv. Evaluation: propose a purpose-driven DT roadmap to evaluate the impact of applications, address the gap between potential and applications, and promote widespread DT adoption (Paper VI). Results: the main results include a deep DT investigation, experimental work with a reinforced concrete beam, snow galleries and a trough bridge, digital models using BIM and finite elements, a scalable DT platform methodology demonstrated in two case studies, and a roadmap from conclusions and lessons learned to promote DT adoption in the industry. Conclusions: given the particularities of the E&amp;C industry and its assets, DTs can primarily benefit asset management and maintenance processes by enabling real-time monitoring, predictive maintenance, and data integration for improved safety and efficiency. To address the gap between potential and practical applications, two paradigm shifts are proposed: shifting the perception of DTs from a digital model to integrated technology tools, and adopting a generalizable, purpose-focused approach instead of context-specific frameworks

Technology advancements in future waste biorefineries: Focus on low carbon fuels and renewable chemicals

Transitioning from fossil fuels to renewable energy sources is essential for combating climate change and minimizing greenhouse gas emissions. Innovative biorefineries are at the forefront of this shift, designed for enhanced productivity and carbon neutrality. These facilities can extract low-carbon fuels and biobased materials from renewable feedstocks, presenting opportunities for diverse product development and low-carbon outputs. Recent advancements in acidogenic and methanogenic biorefineries showcase their potential to produce valuable compounds, including carboxylates, alcohols, and biopolymers while generating fuels like hydrogen and methane. This article explores biorefineries extracting low-carbon fuels and biobased materials from renewable feedstocks, emphasizing advancements in renewable fuel and chemical production. It focuses on acidogenic and methanogenic biorefineries, highlighting synergies in extracting and utilizing compounds such as carboxylates, alcohols, and biopolymers. Additionally, it addresses the production of hydrogen, methane, bioelectricity, and bio-ammonium, emphasising their role in carbon farming and the associated challenges in optimizing these processes for sustainable energy solutions. Validerad;2025;Nivå 2;2025-08-07 (u8);Funder: JSPS KAKENHI (24K11471); Iwatani Foundation for the Promotion of Science and Engineering, Japan;Full text license: CC BY-NC-ND</p

Psychosocial Interventions Preventing Gang-Related Crime Among Young People: A Systematic Review

The objective was to assess the effectiveness of psychosocial interventions in preventing gang membership and gang-related crime among children and young adults under the age of 30. We performed a systematic review and synthesized interventions targeting universal, selective, and indicated populations published between January 2000 and April 2023. We included 42 (seven randomized, 12 nonrandomized, 23 controlled interrupted time series) studies evaluating 33 unique psychosocial interventions. Synthesis without meta-analysis found a preventive effect of psychosocial interventions in middle schools on gang membership. Furthermore, meta-analysis found that focused deterrence strategies prevented gang-involved violence, and that psychosocial support during probation decreased crime recidivism. This systematic review found significant effects of four psychosocial interventions compared to control in reducing future criminality, especially gun violence, among children and young adults. The findings are discussed regarding policy implications and ethical considerations

Hardwood-derived cellulose nanofibrils and micro-fibrillated cellulose via Fenton pretreatment : Issues of fiber fragmentation and coating performance

A novel cellulose nano material was prepared through a controlled Fenton oxidation process utilizing hydrogen peroxide and ferrous ions. The reaction parameters enabled ferrous-catalyzed oxidation, which combined with mechanical treatment resulted in an effective fibrillation of cellulose fibers. Optical microscopy images provided a visual comparison of fiber morphology between untreated hardwood pulp and Fenton-treated samples, clearly illustrating the fibrillation effect. The samples were evaluated for fiber drainage behavior, and conclusions about accessibility and the extent of fibrillation were made. Measurements of the surface charge of the samples revealed an increase in negative charges originating from added carboxyl groups, which is essential for the dispersing and stabilization of cellulose nano fibrils and micro-fibrillated cellulose (CNF/MFC). Fourier-transform infrared spectroscopy (FTIR) confirmed the introduction of the carboxyl groups due to the Fenton treatment. The CNF/MFC material was used as paper coatings, without adding additional materials. The coated samples underwent analyses of permeability and roughness, revealing possibilities for enhancements in barrier properties and hydrophobicity. The results emphasize the ability of Fenton oxidation in generating high-quality small scale cellulosic materials with customized functionalities, underscoring their potential application in advanced coating technologies and sustainable material innovation

Advancing the science of consciousness: From ethics to clinical care

Significant advances in the scientific investigation of the neurobiology of consciousness have been slow to be translated into clinical settings, limited by a lack of generally agreed working definition (e.g., what is consciousness?) and methodology (e.g., how to identify reliable biomarkers/indicators of consciousness? How to improve sensitivity and specificity of the technological identification of consciousness?). In the present paper we aim at proposing potential strategies for reducing the gap between research, clinical practice, and patients’ and their caregivers’ needs regarding disorders of consciousness. By implementing a multidisciplinary (i.e., involving different disciplines) and multiperspective (i.e., involving different stakeholders) approach, the paper focuses on disorders of consciousness: it starts from the review of some of the most promising measures of consciousness from brain activity (i.e., electrophysiology and spectral measures, measures of functional connectivity, complexity-based measures). Next the paper introduces brain responses to illusions as a possible new indicator of consciousness (i.e., a feature that facilitates the attribution of consciousness), and illustrates a possible clinical operationalization of the indicators of consciousness through the case of virtual reality. Finally, the paper analyses a set of urgent ethical issues and describes a model for assessing and dealing with those issues, concluding by elaborating key recommendations for improving the clinical treatment of patients with disorders of consciousness through a better translation of research into clinics

Self-compassion, depressive symptoms, and well-being : A cross-sectional exploration across athlete status and gender

Self-compassion is associated with positive mental health outcomes and may buffer against negative selfevaluations and emotional difficulties. Nevertheless, studies among athletes often explore self-compassion in specific groups in isolation (e.g., women athletes) (Ro&lt;spacing diaeresis&gt;thlin et al., 2019). The aims of this study were to 1) explore whether the relationship between gender and composite scores and specific dimensions of self-compassion (e.g., self-judgement) was moderated by athlete status; and 2) to explore the relationship between different dimensions of self-compassion and self-reported depressive symptoms and well-being among team sport athletes (n = 84, Mage = 22.9 +/- 5.0; 57.1 %men) and non-athletes (n = 189, Mage = 35.5 +/- 5.9; 32.8 %men). For our first aim, the relationship between gender and self-compassion (including specific dimensions) was not moderated by athlete status. However, regardless of gender, athletes reported significantly higher total self-compassion scores and significantly lower scores on specific dimensions of self-compassion, isolation, and over-identification, than nonathletes. For our second aim, self-judgement was positively associated with depressive symptoms in both athletes and non-athletes. Self-judgment was, however, negatively associated with well-being only among athletes, and isolation was negatively correlated with well-being only among non-athletes. Our results suggest that reducing self-judgement may be particularly important for promoting athletes' mental healt

Nickel : Geochemistry, biochemistry and its role in chemical and biological evolutions

Nickel is a versatile element that plays critical roles in Earth's geological and biological evolution, from the depths of the magmatic mantle to the complexity of prebiotic chemistry. While it is not considered the sole catalyst for the origin of life, recent research suggests that Ni may have had a more profound role than traditionally recognized. This review synthesizes Ni isotope geochemistry, biology, and prebiotic chemistry, exploring how Ni isotope variations offer new insights into magmatic processes, hydrothermal systems, and the cycling of Ni through Earth's lithosphere and hydrosphere. We summarize the pathways of Ni in oceanic environments, highlighting its influence on biogeochemical cycles and microbial metabolisms that shape global ecosystems. Furthermore, we examine the essential roles of Ni in biological systems, focusing on its function as a catalytic metal in enzymes crucial for nitrogen and carbon cycling. Extending to the prebiotic world, we evaluate Ni's potential in catalyzing life's earliest chemical reactions, including the polymerization of amino acids and the fixation of CO2, possibly driven by unique metal-ligand interactions. Our comprehensive review positions Ni as a pivotal element across geological timescales and environments, underscoring its relevance to both planetary and biochemical processes

Sonolytic and ultrasound-assisted hydrogen production: insights, trends, and future perspectives

This study employs the bibliometric review method to assess the evolution of research in sonolytic and ultrasound-assisted hydrogen production between 2000 and 2025 using data from the Scopus database. The study found research done so far as a dynamic, cross-disciplinary field driven by global decarbonization and technological innovation. Keyword and thematic mapping identified a central focus towards maximizing the hydrogen evolution reaction (HER) with the assistance of ultrasound catalysis, with advanced materials like g-C3N4, TiO2, and quantum dots. Emerging themes of piezocatalysis, biohydrogen, and ultrasonication-enhanced pretreatment indicate a trend towards multifunctional, sustainable, and bio-integrated processes. The clustering analysis identified distinct strategic research directions, including visible-light-driven heterojunctions, anticorrosion electrodes, ultrasonic fermentation, and hybrid catalytic systems integrating sonochemistry with photocatalysis, electrocatalysis, and thermochemical reforming. Non-noble metal catalysts and nanostructures enabled by sonication are especially gaining prominence owing to their efficiency and scalability. The country-level analysis revealed a commanding position for China, with growing contributions from India, South Korea, and strategic international collaborations. Together, the field is transitioning from fundamental research to application-oriented innovation, and the future opportunity rests in scalable, hybrid systems that integrate ultrasonic, optical, and biochemical processes. These findings suggest that ultrasound-assisted hydrogen generation may contribute to advances in sustainable energy technologies and potential industrial implementation

Enabling dependable flexibility in industrial automation with formal methods integrated to development toolchains

Enabling dependable flexibility in industrial automation requires architectures that can adapt to evolving system requirements without compromising safety, reliability, or performance. One of the major challenges in this context is balancing dependability with flexibility. As systems evolve, rapid revalidation becomes essential. Automatic testing plays a crucial role in addressing this by enabling quick verification after changes. However, in safety-critical systems, automatic testing alone is insufficient. To ensure correctness and reliability, formal verification techniques are required. Closed-loop verification helps mitigate state-space explosion by integrating plant models with the control logic, allowing for more rigorous analysis. Another key challenge lies in obtaining appropriate models of the physical plant for verification. One practical solution is to leverage existing simulation models, discretize them, and inject non-determinism to represent execution uncertainties. Process mining techniques facilitate the construction of plant models by analyzing event logs from digital twins, providing an accurate representation of system behavior. This approach ensures robust validation, verifying system performance under diverse conditions and operational uncertainties.  Within this context, IEC 61499 provides a modular and event-driven framework for designing control systems, enabling distributed control through function blocks (FBs). This architecture enhances reusability, interoperability, and scalability, making it well-suited for cyber-physical automation systems and reconfigurable manufacturing. Blockchain based traceability enhances security and ensures verification in flexible production system. AI-driven automation further optimizes industrial control by enabling intelligent decision-making, real-time adjustments, and process adaptation. AI agents, leveraging large language models (LLMs) and knowledge graphs (KGs), enhance human-machine collaboration by analyzing tasks and executing actions via OPC UA. These agents can interpret operator instructions, generate and validate execution sequences, and ensure conformance with specified requirements to support reliable and adaptive industrial automation.