Search Results (3,008)

Addressing the growing need for sustainable innovation in PVC materials, this study presents an illustrative framework that develops and demonstrates an ontological system that integrates lifecycle simulation using Granta EduPack, systematic literature analysis (including bibliometric, thematic, and content analytics) of peer-reviewed publications, and Protégé-based semantic reasoning, and their combination, in a holistic manner. Material and use-phase data for PVC, HDPE, PP, PET, and FRP cooling-tower components were sourced from ANSYS Granta EduPack Level-3 Polymer Sustainability 2023 R2 Version; 23.2.1, and a systematic analysis of the literature was then encoded as ontology classes, properties, and individuals following the Seven-Step ontology development method. Eco-audit simulations, standardised to a functional unit of 1 kg cooling tower fill material, reveal that the use phase dominates environmental impact (67 MJ primary energy, ~80% of total lifecycle), while material production and end-of-life recycling contribute ~15% and credits of ~900 MJ and 28 kg CO₂ via recycling offsets. Ontology reasoning with corrected SWRL rules and SPARQL queries classifies VirginPVCRef and PVC10ES as strong structural materials (tensile strength ≥ 40 MPa), identifies PVCRH40 as high-moisture-risk (water absorption > 0.10 g/g), and ranks hydro-thermal dechlorination (recyclability 0.90) over mechanical recycling (0.55). A systematic analysis of 40 Scopus-indexed publications (2015–2025) highlighted key themes in recycling technologies, LCA emissions, additive toxicity, ontology frameworks, machine learning integration, circular economy policy, and cooling-tower applications. Demonstrated via a simulation-based cooling-tower case study, hybrid PVC-FRP designs yield the highest justified Material Sustainability Performance Index (MSPI), outperforming PVC-only and FRP-only alternatives. This framework provides a conceptual decision-support tool for exploring PVC material optimisation, illustrating pathways to enhancing circularity and environmental responsibility in industrial applications. The proposed framework is, therefore, not intended as a validated decision-support tool, nor does it claim analytical optimisation or predictive performance but rather serves as a method of illustration that shows how domain knowledge can be formally structured using ontology principles linked to simulation representations, and that was examined for internal logical consistency. Full article

Water with a high fluoride content poses a serious threat to both public health and the natural environment. To enhance fluoride ion removal efficiency, a modified activated carbon adsorbent (HPAC-La) was synthesized by impregnating soybean protein in a lanthanum nitrate solution, followed by freezing–drying and carbonization. The results confirmed that lanthanum nitrate modification significantly improved the adsorption performance. Under optimised experimental conditions (pH = 2.0, [F⁻] = 300 mg·L⁻¹, 12 h, 298 K), HPAC-La exhibited a maximum adsorption capacity for fluoride ions of 126.7 mg·L⁻¹, significantly higher than that of unmodified HPAC (86.1 mg·L⁻¹). The adsorption process followed the pseudo-second-order kinetic model and the Langmuir isotherm model, indicating monolayer chemisorption. The mechanism involves ion exchange via surface hydroxyl groups and fluoride coordination with La sites. This study proposes a method for developing highly efficient adsorbents for the treatment of fluoride-contaminated wastewater. Full article

COMCUBE-S (Compton Telescope CubeSat Swarm) is a proposed mission aimed at understanding the radiation mechanisms of ultra-relativistic jets from Gamma-Ray Bursts (GRBs). It consists of a swarm of 16U CubeSats carrying a state-of-the-art Compton polarimeter and a bismuth germanium oxide (BGO) spectrometer to perform timing, spectroscopic and polarimetric measurements of the prompt emission from GRBs. The mission is currently in a feasibility study phase (Phase A) with the European Space Agency to prepare an in-orbit demonstration. Here, we present the simulation work used to optimise the design and operational concept of the microsatellite constellation, as well as estimate the mission performance in terms of GRB detection rate and polarimetry. We used the MEGAlib software to simulate the response function of the gamma-ray instruments, together with a detailed model for the background particle and radiation fluxes in low-Earth orbit. We also developed a synthetic GRB population model to best estimate the detection rate. These simulations show that COMCUBE-S will detect about 2 GRBs per day, which is significantly higher than that of all past and current GRB missions. Furthermore, simulated performance for linear polarisation measurements shows that COMCUBE-S will be able to uniquely distinguish between competing models of the GRB prompt emission, thereby shedding new light on some of the most fundamental aspects of GRB physics. Full article

Background: The Balance Error Scoring System (BESS) is the most practiced static postural balance assessment tool, which relies on visual observation, and has been adopted as the gold standard in the clinic and field. However, the BESS can lead to missed and inaccurate diagnoses—because of its low inter-rater reliability and limited sensitivity—by missing subtle balance deficits, particularly in the athletic population. Smartphone technology using motion sensors may act as an alternative option for providing quantitative feedback to healthcare clinicians when performing balance assessments. The primary aim of this study was to explore the discriminative validity of an alternative novel smartphone-based cloud system to measure balance remotely in soccer athletes with and without hip pain. Methods: This is an exploratory cross-sectional study. A total of 64 Australian soccer athletes (128 hips, 28% females) between 18 and 40 years completed single and tandem stance balance tests that were scored using the modified BESS test and quantified using the smartphone device attached to their lower back. An Exploratory Factor Analysis (EFA) and a Clustered Receiver Operating Characteristic (ROC) using an Area Under the Curve (AUC) were used to explore the discriminative validity between the smartphone sensor system and the modified BESS test. A Linear Mixed-Effects Analysis of Covariance (ANCOVA) was used to determine any statistical differences in static balance measures between individuals with and without hip-related pain. Results: EFA revealed that the first factor primarily captured variance related to smartphone measurements, while the second factor was associated with modified BESS test scores. The ROC and the AUC showed that the smartphone sway measurements in the anterior–posterior and mediolateral directions during single-leg stance had an acceptable to excellent level of accuracy in distinguishing between individuals with and without hip-related pain (AUC = 0.72–0.80). Linear Mixed-Effects ANCOVA analysis found that individuals with hip-related pain had significantly less single-leg balance variability and magnitude in the anteroposterior and mediolateral directions compared to individuals without hip-related pain (p < 0.05). Conclusion: Due to the ability of smartphone technology to discriminate between individuals with and without hip-related pain during single-leg static balance tasks, it is recommended to use the technology in addition to the modified BESS test to optimise a clinician-led assessment and to further guide clinical balance decision-making. While the study supports smartphone technology as a method to assess static balance, its use in measuring balance during dynamic movements needs further research. Full article

This paper presents a study on the development and optimisation of thin films of nickel-vanadium oxide (NiV_xO_y) deposited by DC reactive magnetron sputtering (RMS) controlled by P.E.M. (plasma emission monitoring). The hysteresis behaviour of the Ni emission signal as a function of oxygen incorporation was analysed using optical emission spectroscopy (OES), enabling the identification of critical working points along the hysteresis loop and their correlation with film growth mechanisms. Compared to the non-monotonic nature of the target discharge voltage signal, OES provided a simplified response for real-time process control. A set of coatings was deposited under various working pressures (0.6 and 2.0 Pa) and plasma emission monitoring (P.E.M.) conditions and was thoroughly characterised in terms of microstructure, composition, optical modulation, and electrochemical performance. Films deposited at high pressure and under 30% P.E.M. conditions showed an optimal balance between optical modulation (21%) and charge density (4 mC/cm²), which was attributed to the increased Ni³⁺ content and the surface cracks at low density. Full article

Phosphorus is a fundamental macronutrient, yet its low bioavailability in most soils makes phosphorus deficiency one of the most persistent constraints limiting global crop productivity. Although mineral fertilisation has long been the primary strategy for maintaining adequate P supply, inefficient fertiliser use and strong soil phosphorus fixation result in substantial losses. As a result, current research is shifting toward integrated phosphorus management approaches that combine optimised fertilisation techniques, unconventional phosphorus sources, and biological tools that mobilise soil-bound phosphorus. At the same time, silicon has emerged as a promising modulator of plant stress resilience, which can also influence phosphorus homeostasis. Silicon enhances plant physiological robustness by strengthening tissues, improving photosynthetic performance, and activating antioxidant pathways. Silicon may also modify phosphorus mobility in soils, promoting more efficient uptake and utilisation in plant tissues. This review synthesises current knowledge on physiological and molecular plant responses to phosphorus deficiency. It compares modern fertilisation strategies, ranging from precision fertilisation to unconventional phosphorus fertilisers. Particular attention is devoted to the emerging role of silicon in improving phosphorus availability and in enhancing crop plant phosphorus-use efficiency. The review concludes with future research directions that may help integrate silicon-based interventions into sustainable nutrient-management systems. Full article

Human embryonic kidney (HEK293) cells are a widespread choice for recombinant protein expression. To optimise yields, the hydrolysate Tryptone N1 (TN1) is commonly added post-transfection. TN1 is obtained by controlled enzymatic digestion of casein. As an animal by-product, TN1 faces stricter regulations during cross-country shipments than plant-based products. This raises the question of whether plant-derived peptides are a suitable alternative to TN1. Using polyethyleneimine (PEI) as a cationic polymer, we transfected HEK293-6E cells grown in suspension in serum-free medium and divided the transfectants into four groups (each in triplicate). Two plant-based hydrolysates each derived from pea and broad bean were compared with TN1 and a no-hydrolysate control group. We monitored the cultures for total cell numbers and viability at days 1, 4, and 5 post-transfection. Both plant-based hydrolysates and TN1 showed similar live cell percentages, in contrast to the no-hydrolysate control, which showed lower viability. Five days post-transfection, the expressed His-tagged protein, a tegumental antigen from the eukaryotic parasite Echinococcus granulosus, was retrieved from the serum-free culture supernatant, and the expressed recombinant protein was quantified. The linear ranges for the protein load on the stain-free blot and for the use of the fluorescent anti-His-Tag Alexa₄₈₈ antibody were determined. Using these parameters, stain-free Western blotting and total protein normalization were performed. The plant-derived pea and broad bean hydrolysates reproducibly resulted in similar expression levels as animal-derived TN1; all three hydrolysates were better than no hydrolysate. We conclude that plant-derived hydrolysates are a suitable, more sustainable replacement for TN1. Full article

This study advances the performance of a tandem-blade centrifugal compressor through a parametric Computational Fluid Dynamics (CFD) methodology integrated with Response Surface Methodology (RSM). Numerical simulations were executed by solving steady-state Reynolds-Averaged Navier–Stokes (RANS) equations utilising the Shear Stress Transport (SST) k-ω turbulence model on a validated structured hexahedral mesh. Local sensitivity analysis identified the hub outlet angle and hub inlet angle as the primary geometric parameters affecting pressure ratio and isentropic efficiency, respectively. Flow-field visualisations confirmed that the tandem configuration effectively re-energises the boundary layer, thereby reducing separation and enhancing pressure recovery. Using a Multi-Objective Genetic Algorithm (MOGA), an optimal blade design comprising 22 blades was determined, achieving a maximum isentropic efficiency of 95.23% and a total pressure ratio of 1.416. These findings provide valuable quantitative insights for the optimal design of tandem impellers and highlight the effectiveness of integrating CFD-based sensitivity analysis with multi-objective optimisation techniques. Full article

(1) Background: Exoskeleton systems are being used increasingly in medical rehabilitation and industrial assistance. Accurate evaluation of their performance is crucial for optimising design and improving performance. In this paper, we propose a performance evaluation index system for exoskeletons and a quantitative evaluation method based on multi-source signal fusion. (2) Methods: The system utilises a variety of sensors for signal collection, encompassing sEMG and MMG, which are indicative of muscular fatigue, along with IMU signals, which demonstrate the movement of both the exoskeleton and the human body. This is then combined with the subjective evaluation scale to constitute the exoskeleton effectiveness assessment index system. (3) Results: This study evaluates two types of material handling exoskeletons. The findings indicate that the ultimate scores for the single-hip and hip-knee exoskeletons are 0.625 and 0.845, respectively. (4) Conclusions: A comparison of the indexes of the two exoskeletons and the subjective evaluations of the testers reveals that this method effectively quantifies the exoskeleton’s human metabolism, human–machine synergy and performance in working conditions, as well as the perceived effectiveness of assistance in different working conditions. Full article

The high energy consumption and cost of operation which result from substantial pressure losses during the transportation of crude oil over long-distance pipelines due to frictional drag created by turbulence are fundamental issues. In order to cope with such challenges, the current research intends to develop a simulation-based study that employs MATLAB R2016b and Minitab 21 to assess the effectiveness of drag-reducing agents (DRAs). An effective mathematical representation of the use of basic fluid mechanics with a semi-empirical correlation on the DRA performance is therefore created and its performance compared to actual pipeline data, showing good compatibility with experimental results. The findings show that DRA addition can produce a significant reduction in the pressure drop by 30–35% with an increase in the overall flow efficiency by 40–60%. Using 25 ppm DRA concentration at a Reynolds number of 323,159 enables an optimised prediction of 33.43% in drag reduction with an efficiency of 45.13%. Moreover, it is also found that there are considerable energy savings, flatter radial velocity profiles, and enhanced particle transport, which highlights the radical effect of DRAs on the hydrodynamics of flows. More importantly, it is determined that DRAs are one of the most effective and cost-efficient solutions to improve throughput and decrease the pumping power in the oil pipeline. However, further research is required to generalise the model to multiphase flows and use the newest optimisation algorithms to control the dosage dynamically. Full article

Wearable sensing technologies are increasingly used to assess neuromuscular function during daily-life activities. This study presents and evaluates a multisensor wearable system integrating a textile-based surface Electromyography (sEMG) sleeve and a pressure-sensing insole for monitoring Tibialis Anterior (TA) and Gastrocnemius Lateralis (GL) activation during gait. Eleven healthy adults performed overground walking trials while synchronised sEMG and plantar pressure signals were collected and processed using a dedicated algorithm for detecting activation intervals across gait cycles. All participants completed the walking protocol without discomfort, and the system provided stable recordings suitable for further analysis. The detected activation patterns showed one to four bursts per gait cycle, with consistent TA activity in terminal swing and GL activity in mid- to terminal stance. Additional short bursts were observed in early stance, pre-swing, and mid-stance depending on the pattern. The area under the sEMG envelope and the temporal features of each burst exhibited both inter- and intra-subject variability, consistent with known physiological modulation of gait-related muscle activity. The results demonstrate the feasibility of the proposed multisensor system for characterising muscle activation during walking. Its comfort, signal quality, and ease of integration encourage further applications in clinical gait assessment and remote monitoring. Future work will focus on system optimisation, simplified donning procedures, and validation in larger cohorts and populations with gait impairments. Full article

Renewable Energy Communities are expected to play a key role in the decarbonization of power systems, but their design and operation involve multiple, often conflicting objectives and evolving regulatory frameworks. However, prospective REC promoters and members must make early-stage design choices under policy constraints while balancing economic, environmental, and reliability goals, which motivates the need for transparent and reproducible decision-support tools. This paper presents Adapters, a two-level decision-making tool that couples long-term planning with short-term operational adaptation for hybrid renewable energy systems. The core optimisation model is explicitly multi-objective, with three weighted terms (w₁, w₂, and w₃) that represent total cost, CO₂ emissions, and unserved energy, respectively, allowing users to explore trade-offs between economic performance, environmental impact, and reliability. The tool integrates detailed component models (such as photovoltaic, wind, and battery storage) with a flexible optimisation layer and architecture compatible with digital-twin approaches. Its capabilities are illustrated through prototype single-household case studies, showing how different stakeholder preferences and regulatory conditions can be reflected in the choice of objective weights and system configurations. The overall aim is to provide a transparent and reproducible environment to support the emergence and operation of RECs in line with EU energy and climate goals. Full article

The ubiquity and environmental persistence of per- and polyfluoroalkyl substances (PFASs) have raised significant concerns about their detrimental effects on human health. Collective scientific efforts are increasingly focused on elucidating PFAS toxicity mechanisms and identifying potential low-impact PFAS structures that retain the exceptional properties of this chemical class. To advance the use of in silico methods in PFAS toxicity assessment, we developed a robust modelling framework for predicting PFAS acute oral toxicity class (high or low) in rats, leveraging the enhanced capabilities of the in-house Isalos Analytics Platform. The automated machine learning (autoML) functionality was employed to optimise four ML models—k-nearest neighbours (kNN), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and fully connected neural network (NN)—using Mold2 molecular descriptors, and to identify the top-performing model through five-fold cross-validation. The selected kNN model (k = 3) was used for predictions on the held-out testing set, achieving an accuracy of 81.5%, while a Shapley values analysis provided valuable insights into the factors influencing toxicity predictions. Furthermore, the nearest-neighbour-based methodology enabled a read-across structural analysis of PFAS similarity groups consisting of each testing set instance and its three closest neighbours in the training set. This analysis revealed a consistent association between polyaromatic and heterocyclic structural features and high acute oral toxicity. The developed, thoroughly validated read-across model is freely accessible through the INSIGHT RatTox web application as well as the INSIGHT Cheminformatics Platform in Enalos Cloud, supporting high-throughput screening of PFAS compounds and investigation of structural similarities with their nearest neighbours for enriched structural interpretation. Full article

The field of developing effective catalysts for heterogeneous catalysis has recently focused on controlling the structures of catalysts themselves to optimise the density and energy of crystal lattice defects. This can significantly influence catalytic activity in terms of both reaction rates and reaction mechanisms, and thus the selective production of desired substances as well. In many cases, these crystal lattice defects manifest themselves as so-called electron traps (ETs) and thus significantly influence charge transfer between the catalyst and reactants. ETs provide the missing electronic link between atomic-scale defects and macroscopic performance in heterogeneous catalysis. Therefore, the importance of ETs for catalysis is particularly evident in areas where charge transfer plays a fundamental role in the reaction mechanism, such as photocatalysis and electrocatalysis. In the field of thermally initiated reactions, the importance of ETs in heterogeneous catalysis has not yet been fully appreciated. However, several studies have already addressed the importance of ETs for this type of reaction. This review consolidates and extends the concept of ETs to purely thermal-initiated reactions, with a focus on CO₂ hydrogenation using typical transition metal catalysts. Firstly, in this review, ETs are defined as band gap states associated with internal and external defects, and their depth, density, spatial location, and dynamics are then coupled with key steps in thermocatalytic cycles, including charge storage/release, reactant activation, intermediate stabilisation, and redox turnover. Secondly, electron trap detection is reviewed based on advanced spectroscopic techniques, including reversed double-beam photoacoustic spectroscopy (RDB-PAS), thermally stimulated current (TSC), deep-level transient spectroscopy (DLTS), thermoluminescence (TL), electron paramagnetic resonance (EPR), and photoluminescence (PL), highlighting how each method describes trap energetics and populations under realistic operating conditions. Finally, case studies on the application of metal oxides and supported metals are discussed, as these are typical catalysts for the reaction mentioned above. This review highlights how oxygen vacancies (OVs), polarons, and metal–support interfacial sites act as robust electron reservoirs, lowering the barriers for CO₂ activation and hydrogenation. By reframing thermocatalysts through the lens of ET chemistry, this review identifies ETs as actionable targets for the rational design of next-generation materials for CO₂ hydrogenation and related high-temperature transformations. Full article

The decarbonisation of the construction sector represents a central pillar of sustainable development strategies, contributing simultaneously to climate change mitigation, energy efficiency, energy security, and long-term socio-economic resilience. In this context, the European regulatory framework increasingly recognises the role of digitalisation and smart technologies in improving building performance beyond static energy efficiency indicators. The Smart Readiness Indicator (SRI), introduced in Energy Performance of Buildings Directive IV (EPBD), is designed to evaluate a building’s ability to optimise energy usage, adapt to the needs of its occupants, and interact intelligently with energy networks through automation and control systems. However, the scientific literature has only partially explored its potential contribution to sustainability-oriented decision-making and decarbonisation governance. This study adopts a conceptual and methodological research approach to investigate the role of the SRI as a sustainability-oriented assessment and governance tool for building decarbonisation. The paper develops a multi-scale analytical framework based on a structured synthesis of the scientific literature, European policy documents and evidence emerging from national SRI test phases. The framework systematically links smart readiness functionalities with digital modelling tools, automation systems, and decarbonisation objectives across building, system, and policy levels. The results highlight that the SRI can be interpreted not only as a descriptive rating scheme, but also as a strategic instrument for assessing sustainability, capable of supporting environmentally, economically, and operationally sustainable decision-making in the built environment. This study contributes to the advancement of sustainability assessment tools that enable the monitoring, governance and long-term decarbonisation of the building stock in line with European climate and sustainability goals by reframing the SRI within a digital and decarbonisation-oriented methodological perspective. Full article