Search Results (1,296)

A brick kiln was experimentally studied to measure the transient temperature of hot gases and the compressive strength of the bricks, using pine wood as fuel, in order to evaluate the thermal performance of the actual system. In addition, a transient combustion model based on computational fluid dynamics (CFD) was used to simulate the combustion of natural gas in the brick kiln as a hypothetical case, with the aim of investigating the potential benefits of fuel switching. The theoretical stoichiometric combustion of both pine wood and natural gas was employed to compare the mole fractions and the adiabatic flame temperature. Also, the transient hot gas temperature obtained from the experimental wood-fired kiln were compared with those from the simulated natural gas-fired kiln. Furthermore, numerical simulations were carried out to obtain the transient hot gas temperature and NOx emissions under stoichiometric, fuel-rich, and excess air conditions. The results of CO₂ mole fractions from stoichiometric combustion demonstrate that natural gas may represent a cleaner alternative for use in brick kilns, due to a 44.08% reduction in emissions. Contour plots of transient hot gases temperature, velocity, and CO₂ emission inside the kiln are presented. Moreover, the time-dependent emissions of CO₂, H₂O, and CO at the kiln outlet are shown. It can be concluded that the presence of CO mole fractions at the kiln outlet suggests that the transient combustion process could be further improved. The low firing efficiency of bricks and the thermal efficiency obtained are attributed to uneven temperatures distributions inside the kiln. Moreover, hot gas temperature and NOx emissions were found to be higher under stoichiometric conditions than under fuel-rich or excess of air conditions. Therefore, this work could be useful for improving the thermal–hydraulic and emissions performance of brick kilns, as well as for future kiln design improvements. Full article

Tricuspid regurgitation (TR) is a well-recognized factor contributing to adverse outcomes and mortality. Recent developments in transcatheter valve repair techniques, with the emergence of tricuspid transcatheter edge-to-edge repair (TEER) devices, have altered the treatment algorithm of TR and now offer a safe and feasible alternative for the effective management of the disease and an improvement in patient symptoms. Evidence from large studies and registries showcases the benefit of tricuspid interventions in terms of heart failure hospitalization and quality of life; however, most studies do not report a significant benefit in terms of hard outcomes. Even though longer-term follow-up may be needed to identify such differences, it is important to also identify distinct patient phenotypes that would benefit the most from such interventions, moving from pure anatomical criteria to an overall assessment of the patient’s clinical status. Therefore, the aim of this review is to provide updates on potential moderators of the effect of tricuspid TEER, focusing on novel anatomical criteria, right cardiac function, and renal physiology, in order to guide patient selection and provide an insightful discussion on the optimal patient phenotype for future trial design. Full article

Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available methodologies are mostly built on experts’ opinions and in just few cases, methodologies and tools have been developed to support the decision makers with a rational approach. In any case, all the available approaches are meant to draw “ideal” maturation plans. Therefore, it is deemed essential to develop an integrate new algorithms able to decision guidelines on “non-nominal” scenarios. In this context, Politecnico di Torino, in collaboration with the European Space Agency (ESA) and Thales Alenia Space–Italia, developed the Technology Roadmapping Strategy (TRIS), a multi-step process designed to create robust and data-driven roadmaps. However, one of the main concerns with its initial implementation was that TRIS did not account for time and budget estimates specific to the space exploration environment, nor was it capable of generating alternative development paths under constrained conditions. This paper discloses two main significant updates to TRIS methodology: (1) improved time and budget estimation to better reflect the specific challenges of space exploration scenarios and (2) the capability of generating alternative roadmaps, i.e., alternative technological maturation paths in resource-constrained scenarios, balancing financial and temporal limitations. The application of the developed routines to available case studies confirms the tool’s ability to provide consistent planning outputs across multiple scenarios without exceeding 20% deviation from expert-based judgements available as reference. The results demonstrate the potential of the enhanced methodology in supporting strategic decision making in early-phase mission planning, ensuring adaptability to changing conditions, optimized use of time and financial resources, as well as guaranteeing an improved flexibility of the tool. By integrating data-driven prioritization, uncertainty modeling, and resource-constrained planning, TRIS equips mission planners with reliable tools to navigate the complexities of space exploration projects. This methodology ensures that roadmaps remain adaptable to changing conditions and optimized for real-world challenges, supporting the sustainable advancement of space exploration initiatives. Full article

This study was developed to identify the optimal (most cost-effective) strategies to reduce sediment and phosphorus loadings in the Upper Soldier Creek, Kansas, USA, watershed using the Watershed Management Optimization Support Tool (WMOST) suite of programs. Under average precipitation, loading targets for upland total phosphorus (TP) could be met with use of grassed swales for treating urban area runoff and of contouring for agricultural runoff. For a wet year, the same target could be met, but with use of a sand filter with underdrain for the urban runoff. Both annual and daily TP loading targets from Total Maximum Daily Loads (TMDLs) were exceeded in simulations of best management practice (BMP) solutions for 14 alternative future climate scenarios. We expanded the set of BMPs to include stream bank stabilization (physical plus riparian restoration) and two-stage channel designs, but upland loading targets could not be met for either TP or total suspended solids (TSS) under any precipitation conditions. An optimization scenario that simulated the routing of flows in excess of those treated by the upland BMPs to an off-channel treatment wetland allowed TMDLs to be met for an average precipitation year. WMOST can optimize cost-effectiveness of BMPs across multiple scales and climate scenarios. Full article

This study evaluates machine learning-based methods for retrieving thin Arctic sea ice thickness (SIT) from L-band radiometry, using data from the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite. In addition to the operational ESA product, three alternative approaches are assessed: a Random Forest (RF) algorithm, a Convolutional Neural Network (CNN) that incorporates spatial coherence, and a Long Short-Term Memory (LSTM) neural network designed to capture temporal coherence. Validation against in situ data from the Beaufort Gyre Exploration Project (BGEP) moorings and the ESA SMOSice campaign demonstrates that the RF algorithm achieves robust performance comparable to the ESA product, despite its simplicity and lack of explicit spatial or temporal modeling. The CNN exhibits a tendency to overestimate SIT and shows higher dispersion, suggesting limited added value when spatial coherence is already present in the input data. The LSTM approach does not improve retrieval accuracy, likely due to the mismatch between satellite resolution and the temporal variability of sea ice conditions. These results highlight the importance of L-band sea ice emission modeling over increasing algorithm complexity and suggest that simpler, adaptable methods such as RF offer a promising foundation for future SIT retrieval efforts. The findings are relevant for refining current methods used with SMOS and for developing upcoming satellite missions, such as ESA’s Copernicus Imaging Microwave Radiometer (CIMR). Full article

This study evaluated the effects of teaching multiple alternative responses on the resurgence of a target response and the persistence of an alternative response in an applied setting. Using a between-participants design, we examined how teaching multiple alternative responses impacted resurgence and persistence upon exposure to extinction. Additionally, we investigated the role of preference in response allocation and shifts in participant preference following extinction. Results indicated resurgence across both conditions, with no consistent difference in severity between single and multiple alternative response conditions. However, within-session analyses revealed greater persistence of the alternative response for participants taught multiple alternative responses, suggesting potential benefits for sustained engagement. Future researchers should continue to investigate the role of preference, as teaching order may have impacted findings. Despite mixed findings, this study provides valuable insights into clinical strategies for promoting alternative responding. While teaching multiple alternative responses may not prevent resurgence, it may enhance communication flexibility, particularly when certain responses become unavailable. Full article

Xylanase is an essential industrial enzyme for degrading plant biomass, pulp and paper, textiles, bio-scouring, food, animal feed, biorefinery, chemicals, and pharmaceutical industries. Despite its significant industrial importance, the extensive application of xylanase is hampered by high production costs and concerns regarding the safety of xylanase-producing microorganisms. The utilisation of renewable polymers for enzyme production is becoming a cost-effective alternative. Among the prospective candidates, non-pathogenic lactic acid bacteria (LAB) are promising for safe and eco-friendly applications. Our investigation revealed that Pediococcus pentosaceus G4, isolated from plant sources, is a notable producer of extracellular xylanase. Improving the production of extracellular xylanase is crucial for viable industrial applications. Therefore, the current study investigated the impact of various medium components and optimised the selected medium composition for extracellular xylanase production of P. pentosaceus G4 using Plackett–Burman Design (PBD) and Central Composite Design (CCD) statistical approaches. According to BPD analysis, 8 out of the 19 investigated factors (glucose, almond shell, peanut shell, walnut shell, malt extract, xylan, urea, and magnesium sulphate) demonstrated significant positive effects on extracellular xylanase production of P. pentosaceus G4. Among them, glucose, almond shells, peanut shells, urea, and magnesium sulphate were identified as the main medium components that significantly (p < 0.05) influenced the production of extracellular xylanase of P. pentosaceus G4. The optimal concentrations of glucose, almond shells, peanut shells, urea, and magnesium sulphate, as determined via CCD, were 26.87 g/L, 16 g/L, 30 g/L, 2.85 g/L, and 0.10 g/L, respectively. The optimised concentrations resulted in extracellular xylanase activity of 2.765 U/mg, which was similar to the predicted extracellular xylanase activity of 2.737 U/mg. The CCD-optimised medium yielded a 3.13-fold enhancement in specific extracellular xylanase activity and a 7.99-fold decrease in production costs compared to the commercial de Man, Rogosa and Sharpe medium, implying that the CCD-optimised medium is a cost-effective medium for extracellular xylanase production of P. pentosaceus G4. Moreover, this study demonstrated a positive correlation between extracellular xylanase production, growth, lactic acid production and the amount of sugar utilised, implying the multifaceted interactions of the physiological variables affecting extracellular xylanase production in P. pentosaceus G4. In conclusion, statistical methods are effective in rapidly assessing and optimising the medium composition to enhance extracellular xylanase production of P. pentosaceus G4. Furthermore, the findings of this study highlighted the potential of using LAB as a cost-effective producer of extracellular xylanase enzymes using optimised renewable polymers, offering insights into the future use of LAB in producing hemicellulolytic enzymes. Full article

This research assesses the design efficiency of the future centralized wastewater treatment plant (WWTP) in Prishtina, which also takes into consideration rapidly expanding suburban areas, such as Fushë Kosova, Obiliq, and Graçanica. Using a combination of both ATV-DVWK-A 131E deterministic calculations and dynamic simulation with IWASP, this study focuses on the planned configurations for the future Prishtina wastewater treatment plant (WWTP) to evaluate design efficiency alongside operational feasibility. The primary goal was to determine if meeting projected loads for the year 2040 would be possible with compliance requirements for a single-stage CAS system. Simulation data suggest that reliable nitrogen removal would not be possible with a sole CAS stage (aerobic), particularly considering seasonal and peak load dynamics. Alternatively, an optimized three-reactor CAS model, including one anoxic pre-denitrification zone coupled with two alternating aerobic zones, achieved an average total nitrogen (TN) removal efficiency of about 85%, maintaining effluent TN below 10 mg/L. Additional advantages saw COD being removed at rates between 90 and 92%, along with MLSS levels stabilizing around 3500 mg/L. The flexibly scalable design also provides adaptive operation features, including expanded tertiary nutrient removal in phase II. In scenario two’s site comparative analysis, Lismir’s centralized WWTP emerges as the most economically and technically rational option due to the enhanced reactor layout optimization. These findings confirm that enhanced configurations, validated through both static and dynamic analyses, are essential for long-term treatment efficiency and regulatory compliance. Full article

Background: The emergency department (ED) often represents the entry point to care for patients that require urgent medical attention or have no alternative for medical treatment. This has implications on scope of practice and how quality of care is measured. A diverse array of methodologies has been developed to evaluate the quality of clinical care and broadly includes quality improvement (QI), quality assurance (QA), observational research (OR) and clinical quality registries (CQRs). Considering the overlap between QI, QA, OR and CQRs, we conceptualized a modular framework for TECOR to effectively and efficiently streamline clinical quality evaluations. Streamlining is both appropriate and justified as it reduces redundancy, enhances clarity and optimizes resource utilization, thereby allowing clinicians to focus on delivering high-quality patient care without being overwhelmed by excessive data and procedural complexities. The objective of this study is to describe the process for designing a modular framework for ED CQRs using TECOR as a case study. Methods: We performed a scoping audit of all quality projects performed in our ED over a 1-year period (1 January 2021 to 31 December 2021) as well as data mapping and categorical formulation of key themes from the TECOR dataset with clinical data sources. Both these processes then informed the design of TECOR. Results: For the audit of quality projects, we identified 29 projects. The quality evaluation methodologies for these projects included 12 QI projects, 5 CQRs and 12 OR projects. Data mapping identified that clinical information was fragmented across 11 distinct data sources. Through thematic analysis during data mapping, we identified three extraction techniques: self-extractable, manual entry and on request. Conclusions: The modular framework for TECOR aims to enable an efficient streamlined approach that caters to all aspects of clinical quality evaluation to enable higher throughput of clinician-led quality evaluations and improvements. TECOR is also an essential component in the development of a learning health system to drive evidence-based practice and the subject of future research. Full article

Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance. Full article

This study applies stochastic discrete event modeling to demonstrate that reducing wait times for specialized outpatient clinics in the Costa Rican public healthcare system is possible. The classification process identified four medical specialties with the longest wait times. It includes the creation of a separate queuing theory model for each specialty. The birth and death model allowed for estimating the number of arrivals and consultations in the simulation. Validation was performed by comparing the model’s input and output data with real-world statistical reports. An analysis of medical specialists revealed that approximately 22% of patients referred to secondary care did not require specialized medical consultation. Through simulation and the use of stochastic input data, patient waiting times decreased. In an optimistic scenario, waiting times decreased steadily across all specialties over 24 months. Ophthalmology and orthopedics reduced their waiting times to less than 300 days. Otorhinolaryngology decreased from 370 to 250 days, and urology showed the most significant improvement, decreasing from 350 to 100 days in the first year and remaining stable. This evidence transforms the traditional paradigm of increasing capacity as the only solution to the waiting list problem and positions improving the referral process as an alternative. To achieve these results, the study highlights the importance of implementing improved triage protocols in primary care, integrating decision-support tools for general practitioners using machine learning, for example, to reduce unnecessary referrals. Training programs and feedback mechanisms could also align referral practices with specialty criteria. While these strategies were not implemented in this study, the simulation results provide a solid basis for their design and future evaluation. Full article

Tumor immunotherapy has revolutionized cancer treatment by harnessing the immune system to recognize and eliminate malignant cells, with immune checkpoint inhibitors targeting programmed death receptor 1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) demonstrating remarkable clinical success. However, challenges such as treatment resistance, immune-related adverse effects, and high costs highlight the need for novel therapeutic approaches. Aptamers, short, single-stranded oligonucleotides with high specificity and affinity for target molecules, have emerged as promising alternatives to conventional antibody-based therapies. This review provides a comprehensive analysis of aptamer-based strategies targeting immune checkpoints, with a particular focus on PD-1/PD-L1 and CTLA-4. We summarize recent advances in aptamer design, including bispecific and multifunctional aptamers, and explore their potential in overcoming immune resistance and improving therapeutic efficacy. Additionally, we discuss strategies to enhance aptamer stability, bioavailability, and tumor penetration through chemical modifications and nanoparticle conjugation. Preclinical and early clinical studies have demonstrated that aptamers can effectively block immune checkpoint pathways, restore T-cell activity, and synergize with other immunotherapeutic agents to achieve superior anti-tumor responses. By systematically reviewing the current research landscape and identifying key challenges, this review aims to provide valuable insights into the future directions of aptamer-based cancer immunotherapy, paving the way for more effective and personalized treatment strategies. Full article

With the growing use of head-mounted displays (HMDs) such as smart glasses, text input remains a challenge, especially in mobile environments. Conventional methods like physical keyboards, voice recognition, and virtual keyboards each have limitations—physical keyboards lack portability, voice input has privacy concerns, and virtual keyboards struggle with accuracy due to a lack of tactile feedback. FlickPose is a novel text input system designed for smart glasses and mobile HMD users, integrating flick-based input and hand pose recognition. It features two key selection methods: the touch-panel method, where users tap a floating UI panel to select characters, and the raycast method, where users point a virtual ray from their wrist and confirm input via a pinch motion. FlickPose uses five left-hand poses to select characters. A machine learning model trained for hand pose recognition outperforms Random Forest and LightGBM models in accuracy and consistency. FlickPose was tested against the standard virtual keyboard of Meta Quest 3 in three tasks (hiragana, alphanumeric, and kanji input). Results showed that raycast had the lowest error rate, reducing unintended key presses; touch-panel had more deletions, likely due to misjudgments in key selection; and frequent HMD users preferred raycast, as it maintained input accuracy while allowing users to monitor their text. A key feature of FlickPose is adaptive tracking, which ensures the keyboard follows user movement. While further refinements in hand pose recognition are needed, the system provides an efficient, mobile-friendly alternative for HMD text input. Future research will explore real-world application compatibility and improve usability in dynamic environments. Full article

Aerated accumulation bioreactors represent a promising alternative for the aerobic bioremediation of solid contaminated substrates. However, achieving homogeneous mixing and effective air distribution remains a key design challenge in solid-phase systems. This study presents the design and construction of a novel pilot-scale aerated bioreactor equipped with an angled-paddle agitation system, specifically developed to improve solid mixing and aeration. To evaluate the geometric configuration, a series of simulations were performed using the Discrete Element Method (DEM), with particle dynamics analyzed through the Lacey Mixing Index ($LMI$). Four paddle angles (0°, 15°, 45°, and 55°) were compared, with the 45° configuration achieving optimal performance, reaching $LMI$ values above 0.95 in less than 15 s and maintaining high homogeneity at a filling volume of 70%. These results confirm that the paddle angle significantly influences mixing efficiency in granular media. While this work focuses on engineering design and DEM-based validation, future studies will include experimental trials to evaluate biodegradation kinetics. The proposed design offers a scalable and adaptable solution for ex situ bioremediation applications. This work reinforces the value of integrating DEM simulations early in the bioreactor development process and opens pathways for further optimization and implementation in real-world environmental remediation scenarios. Full article

This study presents a methodology for developing and validating digital models of tooth-inlay systems, aiming to trace the complete workflow from clinical procedures to simulation by involving dental professionals—dentists for manual cavity preparation and dental technicians for restoration modelling—while integrating micro-computed tomography (micro-CT) imaging with finite element analysis (FEA). The proposed workflow includes (1) the acquisition of high-resolution 3D micro-CT scans of a non-restored tooth, (2) image segmentation and reconstruction to create anatomically accurate digital twins and mesh generation, (3) the selection of proper resin and the 3D printing of four typodonts, (4) the manual preparation of cavities on the typodonts, (5) the acquisition of high-resolution 3D micro-CT scans of the typodonts, (6) mesh generation, digital inlay and onlay modelling and material property assignment, and (7) nonlinear FEA simulations under representative masticatory loading. The approach enables the visualisation of stress and deformation patterns, with preliminary results indicating stress concentrations at the tooth-restoration interface integrating different cavity alternatives and restorations on the same tooth. Quantitative outputs include von Mises stress, strain energy density, and displacement distribution. This study demonstrates the feasibility of using image-based, tooth-specific digital twins for biomechanical modelling in dentistry. The developed framework lays the groundwork for future investigations into the optimisation of restoration design and material selection in clinical applications. Full article