Search Results (1,036)

This paper presents the design, construction, and calibration of a modular low-cost 3D printer based on open-source technologies, developed as part of an academic research project. The printer utilises fused filament fabrication (FFF) and is built using locally available materials and components, including a T-slot aluminium frame, NEMA 23 stepper motors, and an Arduino Mega 2560 with RAMPS 1.4 control board. The system integrates Marlin firmware and CURA slicing software, enabling autonomous operation via an LCD panel and encoder interface. A detailed methodology is provided for mechanical assembly, electronic integration, firmware configuration, and calibration procedures. Special attention is given to the challenges encountered during the initial testing phase, including filament feeding issues, thermal inconsistencies, and mechanical misalignments. Solutions such as replacing inadequate components (e.g., fibreglass bushings with PTFE), adjusting spring tension, and refining firmware parameters are discussed. The results demonstrate successful printing of complex geometries after iterative calibration, validating the printer’s performance and replicability. This work contributes to the democratisation of additive manufacturing by offering a replicable, open-source solution for educational and prototyping purposes. The findings are relevant to machine design, automation, and robotics communities seeking practical insights into low-cost fabrication systems. Full article

Agile and flexible resource modelling is essential for informed decision-making in early-stage mineral project assessment, and in more advanced stages, particularly when compared with conventional deterministic geological modelling and single-estimate resource evaluations. This study presents a case of rapid scenario generation to view, interpret and test the impact of alternative geological and modelling assumptions, including the definition of geological domains, geological interpretation, grade estimation within domains, and the associated uncertainty. The workflows are implemented in Annapurna™ Resource, a cloud-native geostatistical platform designed to support agile, advanced, and multivariate modelling workflows. Focusing on the multi-commodity San Antonio–Potrerillos district, we demonstrate how rapid model construction enables the systematic evaluation of geological and statistical assumptions, contrasting deterministic estimates with probabilistic outcomes and testing their impact on estimated grades and tonnage under multiple scenarios for five elements: copper (Cu), molybdenum (Mo), gold (Au), silver (Ag), and arsenic (As). The approach provides quantitative measures of model reliability, identifies areas of high uncertainty, and supports the prioritization of new drilling to improve geological knowledge, exploration targeting, and resource classification. This case study highlights the value of fast-turnaround, probabilistic modelling not as a replacement for traditional resource reporting, but as a decision-support framework that enhances understanding of the geology, tests the sensitivity of assumptions, and accelerates learning throughout exploration and into operations. The main results suggest that additional drilling can be strategically placed to reduce the geological uncertainty derived from comparing the current interpretation with the probabilistic model built with indicator kriging. Furthermore, this has relevance in reducing the risk in the assessment of the metal content in each area of the deposit. Sensitivity analysis performed over key parameters of the estimation suggests that outliers’ treatment is the most impactful step during estimation. With current technological tools, it is possible to maintain a live resource model, which can be continuously updated to assess the impact of new data and decisions in near real time. Full article

The rapid development of the lithium battery industry resulted in a large accumulation of spodumene mining residue (SMR). This paper explored the feasibility of using SMR as mineral admixtures in cement mortar. The properties of cement mortar, including flexural strength, compressive strength, fluidity, hydration characteristics, and durability, were studied. The interaction mechanism between SMR and cement mortar had been explored using the Dinger–Funk model, isothermal calorimetry, X-Ray Diffraction (XRD), fourier Transform Infrared Spectroscopy (FTIR), and thermogravimetry (TG) methods. Additionally, the environmental impact of cement mortar was quantitatively evaluated by the life cycle assessment method. The results showed that, while the dosage of SMR was no more than 20 wt.% replaced cement, the flexural strength, compressive strength, and anti-carbonation and sulfate corrosion resistance properties of S2 and S3 cement mortar were similar to that of the blank group. After curing for 28 d, the compressive strength of S1, S2, and S3 were 44.2 MPa, 43.15 MPa, and 40.32 MPa, respectively. SMR powder could improve the workability and reduce the cumulative hydration heat of cement mortar, which confirmed its application potential in large-volume concrete projects. The appropriate content of SMR incorporation into cement mortar could improve the structure and properties of cement-based materials through particle filling, the induced nucleation effect, and the pozzolanic effect. In addition, the utilization of SMR reduced the environmental emissions and resource consumption of cement-based materials. Using 1 m³ cement mortar as an example, for every 10 wt.% increase in SMR powder replacing cement, the energy consumption, the emissions of CO₂, CO, C_xH_y, NO_x, SO₂, dust, and resource consumption of cement mortar were decreased by approximately 342 MJ, 40 kg, 8.1 g, 5.55 g, 88.3 g, 5.24 g, 1.80 kg, and 74.3 kg, respectively. The research findings of this paper are expected to promote the resource utilization of SMR and reduce the carbon emissions of the building materials industry. Full article

Chromium-based technique has been used over the decades and, up to now, is the most extended technology to produce leather around the world. However, the environmental problems related to its production, with special regard to the extremely high amounts of residual chromium in the soil and in the water, are reducing the use of leather, and it is becoming replaced with the use of synthetic materials. Consequently, the current leather production is becoming unsustainable due to the higher cost of treating the effluents derived from it. To eliminate the high consumption of this mineral, a Caesalpinia spinosa (Tara) tanning technique was developed and optimized on a semi-industrial scale. The reported results indicated that, being highly superior to the traditional methods, this was possible after an extensive Tara characterization, which reported, for example, (a) IRR reported strong vibration peaks in different positions, which suggested the presence of polyphenols as a principal component of the Tara powder. This assumption was confirmed by the tannic acid content, which reported values equal to 52.25 ± 1.74 mg/g of Tara powder. These results suggested that the Tara serves as a good tannin agent. This was proven by the mechanical characteristics of the leather produced by using Tara. For example, when 10% of Tara powder was applied to the formulation, the best results were obtained in all the mechanical characteristics of the leather. Thus, for the tensile strength, the average value was equal to 340.77 ± 4.78 N/mm². Moreover, the sustainability of the process was demonstrated by the good wastewater quality, which showed a null concentration of chromium hexavalent and total chromium. As expected, the biochemical oxygen demand (BOD) and the chemical oxygen demand (COD) increased considerably, reaching values of 1461.00 mgO₂/L and 3150.30 mgO₂/L, respectively. Finally, the economic feasibility of the project was obtained through the cost/benefit and Internal Return Rate (IRR) analysis. The results reported a cost/benefit ratio equal to USD 1.03 and an IRR equal to 31%, thus the investment can be recovered after 5 years of execution of the project. This novel zero-chrome tanning process solves the long-standing environmental problems that have been linked to making leather and meets all the needs of today’s sustainable leather industry. Full article

Introduction: The global disease burden of aortic valve disease is already substantial and is projected to rise significantly in the coming decades. Aortic valve replacement (AVR) with a biological prosthesis has become highly popular and commonly used. This study aims to assess long-term outcomes after biological AVR with regard to structural and non-structural deterioration. Methods: In this single-centre retrospective study, 918 patients undergoing surgical AVR with a biological prosthesis at the University Hospital Frankfurt from January 2006 to July 2009 were included. The primary endpoints were freedom from reoperation and from structural and non-structural deterioration, and the secondary was long-term survival. Follow-up was completed in 95.6% with a median of 7.6 years, accounting 6610 patient-years. The mean age was 74.9 years and a median EuroSCORE II (range) was 3.34 (0.77–62.4). Twenty-two percent of surgeries were either emergent or urgent. Many patients had concomitant surgery, while coronary artery bypass grafting in 45.3% of patients was the most common. Three prosthetic valve models were used in our patient population: Carpentier Edwards Perimount (CEP) Model 2900, Model 3000 and Medtronic Mosaic (MM). Results: Reoperation occurred in 36 patients (3.9%) due to endocarditis (2.0%), aortic root aneurysm (0.1%), isolated or combined aortic stenosis or aortic regurgitation (1.9%). Freedom from reoperation at 5, 10 and 15 years was 97 ± 0.6%, 95.6 ± 0.8% and 90.3 ± 2.3%, respectively. Freedom from major stroke at 5, 10 and 15 years was 97.9 ± 0.0%, 96.4 ± 0.8%, and 96.1 ± 0.08%, and freedom from major bleeding event at 5, 10 and 15 years was 98.5 ± 0.4%, 95.7 ± 0.9% and 92.7 ± 2.2%, respectively. A subgroup analysis of the Carpentier Edwards (CEP) valves and the Medtronic Mosaic (MM) valves showed no significant differences regarding the primary endpoints. The overall survival at 5, 10 and 15 years was 67 ± 1.7%, 39.8 ± 1.8%, and 15.1 ± 2.2% respectively. The Kaplan–Meier survival estimator was 96 ± 2.2 months. Conclusion: This study showed a good long-term survival of surgical AVR with biological prostheses in relatively high-risk and elderly patient population. All biological prosthetic valves showed good long-term durability with low levels of complications and reoperations. The different models did not show any significant differences. Surgical AVR remains a valuable therapeutic option even though transcatheter aortic valve implantation has been greatly expanded since its introduction. Full article

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, classified as climate hotspots like other Mediterranean contexts. This paper presents a replicable applied trans-scalar methodology for detailed GI design scenarios, developed through the EU-funded LIFE+ A_GreeNet project to bridge the theory–practice gap and enable pilot implementations in multiple Italian mid-Adriatic coastal municipalities. The research details a comprehensive, multi-disciplinary, five-phase process applied to the Sant’Antonio district of San Benedetto del Tronto—a dense, trafficked urban area projected to face “extremely strong heat stress” by 2050. Design interventions included spatial optimization, strategic species replacement, the creation of vegetated bioretention basins, and systematic pavement de-sealing. The application of the model demonstrated significant improvements: a substantial increase in permeable surface area (+194%), a measurable reduction in the UTCI index (average ENVI-MET simulated reduction of 1.17 °C by 2030), and a series of benefits resulting from increased green space and enhanced meteorological water management. This research offers local authorities a tangible model to accelerate climate-adaptive solutions, showing how precise GI design creates resilient, comfortable, and human-centered urban spaces. Full article

The growing demand for healthier food options has accelerated the development of innovative fat-replacement strategies in spreadable products. Oleogels are semi-solid systems formed by structuring edible oils. Recently, these systems have emerged as a promising solution for reducing saturated fat content without compromising product quality, texture, or sensory attributes. A systematic review was conducted following the PRISMA 2020 protocol, supplemented by a bibliometric analysis. Research was identified through searches in Web of Science, Scopus, Wiley, Springer, MDPI, and Google Scholar for studies published between 2020 and 2024. Inclusion criteria focused on original research articles in English involving food-sector applications of oleogels and aerogels in sweet spreads. Study quality and risk of bias were assessed by two independent reviewers based on methodological relevance and data integrity. Results were synthesized through a narrative approach and bibliometric mapping. After screening 490 records, 34 original research articles were included. Bibliometric data highlighted a clear trend shifting from foundational lipid structuring research in 2020 toward complex, product-specific functional applications by 2024. Overall, the results suggest that these structured systems are viable replacements for traditional saturated fats, providing comparable spreadability and stability. Funding: This work was supported by the Croatian Science Foundation under the project IP-2022-10-1960. This systematic review was not registered in a public database. Full article

Cholera outbreaks are prevalent in coastal regions, where hydroclimatic factors play a critical role. However, evidence on their associations with different genotypes remains limited, and global projection remains lacking. We compiled cholera data from EnteroBase and WHO weekly reports covering 110 coastal countries from 1980 to 2022. A generalized additive model was used to examine the associations between hydroclimatic factors and different cholera serotypes and genotypes. We further projected future cholera occurrences for each coastal country under three climate change scenarios from 2025 to 2100. During the study period, Wave 3 of O1 replaced Wave 1 as the predominant genotype of cholera, while cholera O139 remained at low levels and only occurred in Asia. At the country–year level, each 1 °C increase in sea surface temperature (SST) was significantly associated with cholera occurrence (OR: 1.032, 95% CI: 1.023 to 1.040) and Wave 3 of O1 (OR: 1.149, 95% CI: 1.097 to 1.203). Drainage density (m/km²) and coastline ratio (%) were positively related to cholera, with ORs of 1.067 (95% CI: 1.046 to 1.087) and 1.022 (95% CI: 1.019 to 1.027). For future projections, five trend patterns were identified under different emission scenarios, with most countries showing increased cholera risk due to global hydroclimatic changes, peaking under the SSP585 scenario. Our findings reveal associations between hydroclimatic factors and different cholera genotypes and project future cholera risk across coastal countries, thereby providing evidence to inform genotype-specific surveillance and targeted prevention strategies at the global scale. Full article

Quantitative evaluations in 3D images acquired via Cone-Beam Computed Tomography (CBCT) are limited by the scatter abundance and cone-beam artifacts. This work investigates benefits in using an innovative scanning geometry in CBCT (eCT), which replaces each projection of the conventional scanning protocol with a series of collimated projections (Np) acquired over an oscillating trajectory, realized either with an oscillating source or a multi-spot array. In silico tests employed a cylindrical water phantom embodying inserts of four biological materials. 1 mm-thick bone slabs were sandwiched between 9 mm water slabs to evaluate the image conspicuity. eCT improved the Hounsfield Unit (HU) accuracy, with a direct relation with Np. eCT with Np = 10 reduced the bias of the estimated HU more than two times when compared to CBCT. Increasing the Np presented a large impact on the image conspicuity for portions of the field of view (FOV) distant from the central axial plane, with the signal-to-noise ratio between water and bone slabs increasing by a factor of 18 for Np = 10 compared to CBCT. The proposed eCT configuration is expected to be adopted in applications without strict demand for scanning time and projection number, such as dentomaxillofacial and intrasurgical imaging, imaging of the extremities, and image-guided radiotherapy. Full article

Cost code verification in state-funded construction projects remains a labor-intensive and error-prone task, particularly given the structural heterogeneity of project estimates and the prevalence of malformed codes, inconsistent units of measurement (UoMs), and locally modified price components. This study evaluates a deterministic GPT-based assistant designed to automate Vietnam’s regulatory verification. The assistant was developed and iteratively refined across four Action Research cycles. Also, the system enforces strict rule sequencing and dataset grounding via Python-governed computations. Rather than relying on probabilistic or semantic reasoning, the system performs strictly deterministic checks on code validity, UoM alignment, and unit price conformity in material (MTR), labor (LBR), and machinery (MCR), given the provincial unit price books (UPBs). Deterministic equality is evaluated either on raw numerical values or on values transformed through explicitly declared, rule-governed operations, preserving auditability without introducing tolerance-based or inferential reasoning. A dedicated exact-match mechanism, which is activated only when a code is invalid, enables the recovery of typographical errors only when a project item’s full price vector well matches a normative entry. Using twenty real construction estimates (16,100 rows) and twelve controlled error-injection cases, the study demonstrates that the assistant executes verification steps with high reliability across diverse spreadsheet structures, avoiding ambiguity and maintaining full auditability. Deterministic extraction and normalization routines facilitate robust handling of displaced headers, merged cells, and non-standard labeling, while structured reporting provides line-by-line traceability aligned with professional verification workflows. Practitioner feedback confirms that the system reduces manual tracing effort, improves evaluation consistency, and supports documentation compliance with human judgment. This research contributes a framework for large language model (LLM)-orchestrated verification, demonstrating how Action Research can align AI tools with domain expectations. Furthermore, it establishes a methodology for deploying LLMs in safety-critical and regulation-driven environments. Limitations—including narrow diagnostic scope, unlisted quotation exclusion, single-province UPB compliance, and sensitivity to extreme spreadsheet irregularities—define directions for future deterministic extensions. Overall, the findings illustrate how tightly constrained LLM configurations can augment, rather than replace, professional cost verification practices in public-sector construction. Full article

Background: Climate change is a serious threat to global health. The healthcare sector contributes substantially to greenhouse gas (GHG) emissions, with anaesthetic gases being a major source of Scope 1 emissions. We aimed to evaluate the 2024 impact of the Sustainable Anesthesia Project, designed to reduce the environmental footprint of anaesthetic gases by eliminating and/or replacing the most polluting agents (nitrous oxide and desflurane) with more sustainable alternatives (sevoflurane, total intravenous anaesthesia, and regional/local anaesthesia). Methods: We conducted a descriptive analysis of anaesthetic gas consumption in 2023 and 2024, as well as a comparison of emissions in tons of CO₂, the impact on the carbon footprint, and the potential future emissions savings that full implementation of the project would entail. Results: In the first year, nitrous oxide consumption decreased by 64% and desflurane by 63%. Overall anaesthetic-gas emissions fell by 8386 tCO₂e versus 2023, a 54% relative reduction. Furthermore, the contribution of these gases to the total Scope 1 emissions markedly declined from 35.18% in 2023 to 21.22% in 2024. An additional reduction potential of around 4800 tCO₂e was identified for consolidation by 2025 with full implementation. Conclusions: The results observed in this study demonstrate the success of the Sustainable Anesthesia Project, whose strategy represents an extensible and applicable option to other centers and companies in the health sector to reduce their environmental impact. Full article

This paper examines the role of generative AI in contemporary craft ecologies, with a focus on Italy’s artisanal and design ecosystems. Rather than framing AI as a threat to heritage or merely a tool for efficiency, we propose that AI can be a collaborator within hybrid intelligences that extend craftsmanship, rather than replace it. Drawing on posthumanist and more-than-human design perspectives, we conceptualize hybrid intelligence as a relational infrastructure for co-design among humans, materials, and computational systems. Through a literature review and ten expert interviews with designers, artisans, curators, engineers, and scholars, we identify tensions around authorship, authenticity, standardization, ethics, craft heritage, and data cultures. Speculative scenarios project hesitant futures, balancing risks of homogenization with opportunities for resilience. The contribution of this paper is threefold. First, it proposes a conceptual map of hybrid intelligence for craft and heritage contexts. Second, it offers situated insights into Italian craft imaginaries based on expert perspectives. Third, it demonstrates a methodological approach that combines thematic analysis with speculative futuring. Full article

The Netherlands is widely recognised as the global leader in water management, with its flood risk management (FRM) infrastructure lauded as being of the best in the world. This status notwithstanding, Dutch FRM primarily maintains established infrastructural practices and experimental applications of NBSs remain less frequent than established structural projects. This paper details and examines the challenges associated with the prevailing ‘business-as-usual’ approach to FRM in The Netherlands, in which traditional ‘grey’ infrastructural techniques are prioritised over innovative ‘green’ nature-based solutions (NBSs). In line with emerging international trends, such as the EU Water Resilience Strategy, NBSs are increasingly advocated as a strategic, complementary layer to enhance the resilience of existing safety frameworks rather than a self-evident replacement for them. Contrary to grey infrastructure, NBSs provide a number of environmental and social co-benefits extending beyond their flood and drought protection utility. The literature on NBSs details the design, effectiveness, and positive socio-economic impact of the operationalisation of such projects for FRM. This notwithstanding, the uptake and practical implementation of NBSs have been slow in The Netherlands. From a legal and policy perspective, this has been attributed to a lack of political will and the corresponding failure to include NBSs in long term FRM planning. Given the long planning horizons associated with FRM (50–100 years), the failure to incorporate NBSs can lead to policy lock-in that blocks future adaptations. Against this backdrop, this paper employs a semi-systematic literature review to clarify the obstacles to implementing NBSs in Dutch FRM and sets a research agenda that charts a course to mainstreaming NBSs in Dutch FRM. Seven core focus areas for future research are identified. The paper concludes by drawing on these identified focus areas to construct a research agenda aimed at systematically addressing each barrier to the practical operationalisation of NBSs in Dutch FRM, emphasising a hybrid green–grey approach which may serve to inspire similar research in other jurisdictions. Full article

Rapid urbanization and climate change have intensified flood risk and ecological degradation along urban riverfronts. Recent literature suggests that combining green and grey infrastructure can enhance resilience while delivering ecological and social co-benefits. This study analyzes and compares five riverfront projects in China and Spain, assessing how their tactic mixes operationalize three urban flood-resilience strategies—Resist, Delay, and Store/reuse—and how these mixes translate into ecological, social, and urban impacts. A six-phase framework was applied: (1) literature review; (2) case selection; (3) categorization of resilience strategies; (4) systematization and typification of tactics into green vs. grey infrastructure; (5) percentage analysis and qualitative matrices; and (6) comparative synthesis supported by an alluvial diagram. Across cases, Delay emerges as the structural backbone—via wetlands, terraces, vegetated buffers, and floodable spaces—while Resist is used selectively where exposure and erodibility require it. Store/reuse appears in targeted settings where operational capacity and water-quality standards enable circular use. The comparison highlights hybrid, safe-to-fail configurations that integrate public space, ecological restoration, and hydraulic performance. Effective urban riverfront resilience does not replace grey infrastructure but hybridizes it with nature-based solutions. Planning should prioritize Delay with green systems, add Resist where necessary, and enable Store/reuse when governance, operation and maintenance, and water quality permit, using iterative monitoring to adapt the green–grey mix over time. Full article

Risk management in large-scale construction projects is a critical yet complex process influenced by financial, safety, environmental, scheduling, and regulatory uncertainties. Effective risk management contributes directly to project optimization by minimizing disruptions, controlling costs, and enhancing decision-making efficiency. Early identification and mitigation of risks allow resources to be allocated where they have the greatest effect, thereby optimizing overall project outcomes. However, conventional methods such as expert judgment and probabilistic modeling often struggle to process extensive datasets and complex interdependencies among risk factors. This study explores the potential of an AI-based framework for risk identification, utilizing artificial intelligence to analyze project documentation and generate a preliminary set of identified risks. The proposed methodology is implemented on the ‘Trg pravde’ judicial infrastructure project in Zagreb, Croatia, applying AI models (GPT-5, Gemini 2.5, Sonnet 4.5) to identify phase-specific risks throughout the project lifecycle. The approach aims to improve the efficiency of risk identification, reduce human bias, and align with established project management methodologies such as PM². Initial findings suggest that the use of AI may broaden the range of identified risks and support more structured risk analysis, indicating its potential value as a complementary tool in risk management processes. However, human expertise remains crucial for prioritization, contextual interpretation, and mitigation. The study demonstrates that AI augments, rather than replaces, traditional risk management practices, enabling more proactive and data-driven decision-making in construction projects. Full article