Search Results (156)

Microalage are broadly recognized as promising agents for sustainable wastewater treatment and biomass generation. However, industrial effluents such as petroleum refinery wastewater (WW) present challenges due to toxic growth inhibiting substances. Three marine microalgae species: Pseudochloris wilhelmii, Nannochloropsis gaditana and Synechococcus sp. MK568070 were examined for cultivation potential in oil refinery WW. Their performance was evaluated in terms of growth dynamics, lipid productivity, and toxicity reduction, with a focus on their suitability for largescale industrial use. N. gaditana demonstrated the highest growth rate and lipid content (37% d.w.) as well as lipid productivity (29.45 mg/(Lday)) with the N-uptake rate of 0.698 mmol/(gday). The highest specific DIN uptake rate was observed inn P. wilhelmii (0.895 mmol/(gday) along with the highest volumetric productivity (93.9 mg/L/day) and WW toxicity removal (76.5%), while Synechococcus sp. MK568070 demonstrated lower performance metrics. A simple numerical model was applied to calculate continuous operation based on empirical results of batch experiments. Sustainability of the microalgae-based WW remediation under the conditions of optimized lipid biomass production was estimated, regarding 2019–2022–2025 cost dynamics. Parameters for optimum open raceway pond cultivation were calculated, and the biomass production accumulation was estimated, with the highest biomass production noted in P. wilhelmii (171.38 t/year). Comparison of treatment costs, production costs and revenue showed that the best candidate for WW remediation is N. gaditana. Full article

The temperature variations of interconnected coaxial connectors in RF circuits are strongly influenced by the contact surface characteristics and the ferromagnetic properties of the electroplated materials. In this study, specially structured N-DIN connectors with either magnetic or non-magnetic plating were designed. A dedicated high-frequency, high-power RF experimental platform was set up to monitor and measure the temperature and power of the connectors. Finite element analysis (FEA) was employed to simulate the current density and temperature distribution across the samples. Furthermore, an equivalent circuit model of the central conductor was established by integrating electrical contact theory with the magnetic hysteresis effect. Based on the voltage–temperature (V–T) relation and the derived magnetic field–magnetoresistance (H–M) relation, a predictive model for the temperature rise of the central conductor was formulated. Experimental results demonstrated good agreement with simulation predictions, validating the proposed model and highlighting the critical role of plating material properties in high-power RF connectors’ thermal effect. Full article

The severity of physical disability at leprosy diagnosis reflects the timeliness of case detection and the effectiveness of disease surveillance. This study evaluates machine learning models to predict factors associated with late leprosy diagnosis—defined as grade 2 physical disability (G2D)—in Brazil from 2018 to 2022. Using an observational cross-sectional design, we analyzed data from the Notifiable Diseases Information System and trained four machine learning models: Random Forest, LightGBM, CatBoost, XGBoost, and an Ensemble model. Model performance was assessed through accuracy, area under the receiver operating characteristic curve (AUC-ROC), recall, precision, F1 score, specificity, and Matthew’s correlation coefficient (MCC). An increasing trend in G2D prevalence was observed, averaging 11.6% over the study period and rising to 13.1% in 2022. The Ensemble model and LightGBM demonstrated the highest predictive performance, particularly in the north and northeast regions (accuracy: 0.85, AUC-ROC: 0.93, recall: 0.90, F1 score: 0.83, MCC: 0.70), with similar results in other regions. Key predictors of G2D included the number of nerves affected, clinical form, education level, and case detection mode. These findings underscore the potential of machine learning to enhance early detection strategies and reduce the burden of disability in leprosy, particularly in regions with persistent health disparities. Full article

Our time is one of permacrisis, affecting the economy, the environment, and everything in between. In this context, UK higher education faces an existential crisis, where the university sector has been transformed into a marketplace, turning students into consumers and limiting the critical potential of education. In moving beyond these limits, this article explores Democracy in Action (DinA), a final-year undergraduate module offered in a UK university that creates spaces for critical and transformative education through democratic theory and practice. Grounded in traditions of transformative learning, community-based pedagogies, academic activism, and prefiguration, DinA positions students as democratic agents working in solidarity with staff and the wider community. Drawing on in-depth interviews with students, we analyse the interplay between theory and practice to understand how learning can be understood as a form of democratic participation. The article makes an original contribution to the fields of democratic education and critical university studies by offering a novel framework for integrating academic activism, community-based learning, and prefiguration in higher education. We show how students’ experiences of building community, campaign planning, and prefiguring change generate not only deep transformative learning but also new forms of civic agency and collective action. We argue that, through community organising, students embark on a process of learning that involves three key transformative moments: effecting a perspectival shift from the individual to the common, foregrounding the activist dimensions of democratic politics, and envisioning the world we want through prefiguration. This pedagogical model demonstrates that higher education can become a space of lived democratic possibility, where hope, critique, and collective transformation are not only imagined but enacted. Full article

The interaction between raft foundations and soils is generally modeled with the help of linear elastic springs. The design of structural elements can only be computed when the modulus of subgrade reaction is accurately determined, which is a time-consuming process for raft foundations with relatively large sizes due to the input of many structural loads. In the present work, an approximate procedure is studied based on the relative stiffnesses of soil–foundation systems suggested by DIN—Technical Report 130. To estimate the behavior of soil–foundation systems (rigid or flexible), the limit values of relative stiffness are first determined for raft foundations on elastic soils with the stiffness moduli obtained from one-dimensional consolidation tests by using finite element analyses. Subsequently, the values of subgrade reaction moduli obtained from the FE analyses are compared and discussed with the subgrade reaction moduli determined by using the analytical method considering the relative stiffnesses of soil–foundation systems. It is shown that for a soil–foundation system with a relative stiffness ≥ 0.174, the subgrade reaction modulus obtained from the analytical method assuming a rigid system is about 1.5 to 2 times higher than that in the FE analyses. For a soil–foundation system with a relative stiffness ≤ 0.0004, the analytical method assuming a flexible system and the FE method yield a similar value of subgrade reaction modulus in the central area of the raft foundation. Full article

The marine ecological carrying capacity (MECC) of marine ranching serves as a crucial indicator for assessing the conservation effect of fishery resources and forms a significant basis for scientific management of coastal fisheries. The environmental impacts on the MECC of marine ranching in the northern South China Sea were analyzed quantitatively by employing Generalized Additive Models (GAMs), which have been successfully applied to the study of the relationship between fishery resources and environmental factors, and factor analysis, using satellite and survey observations. Results showed that 95.40% of the total variation in MECC was explained by these factors. Based on the GAMs, the most important factor was Year (calendar years), with a contribution of 66.20%, followed by Chlorophyll a concentration (Chl-a), Sea Surface Temperature (SST), Dissolved Inorganic Nitrogen (DIN) and Water Current, with contributions of 20.60%, 4.40%, 3.60%, and 0.60%, respectively. The findings of this study inspire us to establish a long-term marine ranching resource and environment monitoring platform, and an early warning and forecasting expert decision-making system, providing scientific references for planning and management of coastal marine ranching. Full article

The protective coatings industry is expanding, offering significant improvements in abrasion and wear resistance, which are crucial for economic sustainability. Despite the advancements, there remains a research gap in understanding the tribological properties and surface morphologies of electroless Ni-P and Ni-B coatings. This study aims to fill this gap by characterizing the surface structures, friction coefficients, and wear properties of two types of Ni-P and one type of Ni-B coatings. Using a ceramic ball counterpart in an SRV5 tribometer, we compared the wear rates according to Archard’s and Liu’s models, adhering to the DIN 51834-1 standard. Scanning electron microscopy was employed to analyze the impact of surface structures on friction coefficients and wear factors. The results reveal significant differences in wear resistance and friction behaviour among the coatings, providing valuable insights for their application in various industries. Full article

On 7 January 2025, at Beijing time, an M_w7.1 earthquake occurred in Dingri County, Shigatse, Tibet. To accurately determine the fault that caused this earthquake and understand the source mechanism, this study utilized Differential Interferometric Synthetic Aperture Radar (DInSAR) technology to process Sentinel-A data, obtaining the line-of-sight (LOS) co-seismic deformation field for this earthquake. This deformation field was used as constraint data to invert the geometric parameters and slip distribution of the fault. The co-seismic deformation field indicates that the main characteristics of the earthquake-affected area are vertical deformation and east-west extension, with maximum deformation amounts of 1.6 m and 1.0 m for the ascending and descending tracks, respectively. A Bayesian method based on sequential Monte Carlo sampling was employed to invert the position and geometric parameters of the fault, and on this basis, the slip distribution was inverted using the steepest descent method. The inversion results show that the fault has a strike of 189.2°, a dip angle of 40.6°, and is classified as a westward-dipping normal fault, with a rupture length of 20 km, a maximum slip of approximately 4.6 m, and an average slip angle of about −82.81°. This indicates that the earthquake predominantly involved normal faulting with a small amount of left–lateral strike–slip, corresponding to a moment magnitude of M_w7.1, suggesting that the fault responsible for the earthquake was the northern segment of the DMCF (Deng Me Cuo Fault). The slip distribution results obtained from the finite fault model inversion show that this earthquake led to a significant increase in Coulomb stress at both ends of the fault and in the northeastern–southwestern region, with stress loading far exceeding the earthquake triggering threshold of 0.03 MPa. Through analysis, we believe that this Dingri earthquake occurred at the intersection of a “Y”-shaped structural feature where stress concentration is likely, which may be a primary reason for the frequent occurrence of moderate to strong earthquakes in this area. Full article

Parabolic leaf springs are components typically found in suspensions of freight railway rolling stock. These components are produced in high-strength alloyed steel, DIN 51CrV4, to resist severe loading and environmental conditions. Despite the material’s good mechanical characteristics, the geometric notches and high surface roughness that features its leaves might raise local stress levels to values above the elastic limit, with cyclic elasto-plastic behaviour models being more appropriate. In this investigation, the parameters of the Chaboche model combining the kinematic and isotropic hardening models are determined using experimental data previously obtained in strain-controlled cyclic tests. Once the parameters of the cyclic hardening model are determined, they are validated using a finite element approach considering the Chaboche cyclic plasticity model. As a result, the material properties specified in this investigation can be used in the fatigue mechanical design of parabolic leaf springs made with 51CrV4 (local approaches to notches and at surface roughness level) or even in other components produced with the same steel. Full article

This study explores the tensile performance of blind rivet joints in galvanized steel sheets, focusing on their behavior under shear and normal load conditions. Blind rivets are frequently used in structural applications due to their ease of installation and ability to be applied from one side, making them highly effective in industries like aerospace and automotive. Two types of DIN 7337—4.8 × 8 blind rivets—galvanized steel St/St and stainless steel A2/A2—paired with galvanized steel sheets DX51D + Z275, were experimentally tested to assess how their material properties affect their joint strength, deformation patterns, and failure modes. Single-lap shear, double-lap shear, and pure normal load tests were conducted in multiple configurations to evaluate joint performance under varying loading conditions, simulating real-world stresses. Using custom-built equipment, controlled forces were applied perpendicular to the rivet joints to replicate practical loading conditions. The results revealed distinct differences in the load-bearing capacities of the two materials, offering valuable insights for applications where corrosion resistance and structural integrity are critical. Finite element analysis (FEA) was then used to simulate the behavior of the joints, with the results validated against experimental data. To enhance the reliability of numerical simulations in optimizing the design of rivet joints, a methodology was proposed to calibrate non-linear FEA models to experimental results, and a substantial agreement of 92.53% was achieved via optimization in ANSYS OptiSLang. This research contributes to our broader understanding of riveted connections, providing practical recommendations for assessing the performance of such joints in various engineering fields. Full article

Assessing and improving the quality of education in universities can play a prominent role in developing countries. This study aims to demonstrate an extensive methodology with a related algorithm for assessing the quality of education in Water Resource Engineering (WRE) based on Klein’s learning model and using the hybrid fuzzy-AHP-TOPSIS (FAT) method. Four out of the top ten universities in Iran, including Iran University of Science and Technology (IUST), Amirkabir University of Technology (AUT), Shiraz University (SU), and Khajeh Nasir al-Din Toosi University of Technology (KUT), are considered as case studies. First, participants answered questions based on Klein’s model so that the weight coefficients according to the fuzzy-AHP technique were extracted. Second, these coefficients were transferred to the TOPSIS environment, where the previously prioritized criteria were utilized to select the ideal solution. Finally, the relative closeness of universities (CC) as a performance evaluation criterion in the form of CC(IUST) = 0.54, CC(AUT) = 0.49, CC(SU) = 0.45, and CC(KUT) = 0.39 was obtained. The sensitivity analysis was performed based on the number and type of Klein’s qualitative criteria on the model, and Fourier series expansion curves were used to better compare the results of the proposed algorithm. The presented algorithm in this research can be a good basis for education assessment models in universities. Full article

Rivers play a crucial role in nutrient cycling, yet are increasingly affected by eutrophication due to anthropogenic activities. This study focuses on the Barato River in Hokkaido, Japan, employing an integrated approach of field measurements and Sentinel-2 satellite remote sensing to monitor eutrophication as the river experiencing huge sewage effluents. Key parameters such as chlorophyll-a (Chla), dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and Secchi Disk Depth (SDD) were analyzed. The developed empirical models showed a strong predictive capability for water quality, particularly for Chla (R² = 0.87), DIP (R² = 0.61), and SDD (R² = 0.82). Seasonal analysis indicated peak Chla concentrations in October, reaching up to 92.4 μg/L, alongside significant decreases in DIN and DIP, suggesting high phytoplankton activity. Advanced machine learning models, specifically back propagation neural networks, improved the prediction accuracy with R² values up to 0.90 for Chla and 0.83 for DIN. Temporal analyses from 2018 to 2022 consistently revealed the Barato River’s eutrophic state, with severe eutrophication occurring for 33% of the year and moderate for over 50%, emphasizing the ongoing nutrient imbalance. The strong correlation between DIP and Chla highlights phosphorus as the main driver of eutrophication. These findings demonstrate the efficacy of integrating remote sensing and machine learning for dynamic monitoring of river eutrophication, providing critical insights for nutrient management and water quality improvement. Full article

Legged robots, especially quadruped robots, are widely used in various environments due to their advantage in overcoming rough terrains. However, falling is inevitable. Therefore, the ability to overcome a falling state is an essential ability for legged robots. In this paper, we propose a method to fully recover a quadruped robot from a fall using a single-neural network model. The neural network model is trained in two steps in simulations using reinforcement learning, and then directly applied to AiDIN-VIII, a quadruped robot with 12 degrees of freedom. Experimental results using the proposed method show that the robot can successfully recover from a fall within 5 s in various postures, even when the robot is completely turned over. In addition, we can see that the robot successfully recovers from a fall caused by a disturbance. Full article

The winter planting of green manure (GM) is widely used in South China to reduce chemical nitrogen (N) fertilizer use, improve soil fertility, and maintain rice yields, but its effect on N runoff loss in paddy fields remains unclear. This study combines multi-site field experiments with a process model (WHCNS-Rice) to assess how GM with reduced N fertilizer impacts N runoff loss and its forms in the Yangtze River’s middle and lower reaches, considering different rainfall years. The network field experiments included four treatments: conventional fertilization (FR), conventional fertilization plus straw return (FRS), GM with a 40% N reduction (MR), and GM-straw combined return with a 40% N reduction (MRS). Monitoring the results showed that compared to the winter fallow treatment, the GM treatments reduced the peak and average total N (TN) concentrations by 11.1–57.9% (average 26.9%) and 17.1–27.3% (average 22.3%), respectively. The TN runoff loss under the GM treatment decreased by 3.50–10.61 kg N ha⁻¹ (22.5–42.1%). GM primarily reduced the runoff loss of dissolved inorganic N (DIN), with reductions at different sites ranging from 0.22 to 9.66 kg N ha⁻¹ (8.4–43.4%), indicating GM effectively decreases N runoff by reducing DIN. Model simulations of ponding water depth, runoff, TN concentration in surface water, and TN loss in paddy fields produced the consistency indices and simulation efficiencies of 0.738–0.985, 0.737–0.986, 0.912–0.986, and 0.674–0.972, respectively, indicating that the model can be used to evaluate water consumption and N runoff loss in the GM-paddy system. The simulations showed that GM with a 40% N fertilizer significantly reduced N runoff loss under all rainfall conditions, with the greatest reductions in wet years. Under wet, normal, and dry conditions, the GM treatments significantly reduced average TN loss by 0.37–5.53 kg N ha⁻¹ (12.77–29.17%), 0.21–5.32 kg N ha⁻¹ (9.95–24.51%), and 0.02–3.2 kg N ha⁻¹ (1.78–23.19%), respectively, compared to the winter fallow treatment. These results indicate that the combination of GM and a 40% reduction in N fertilizer can significantly reduce N runoff loss from paddy fields, demonstrating good effectiveness under various rainfall conditions, making it a green production model worth promoting. Full article

The connection between a prefabricated reinforced concrete column and a pocket foundation is a case treated from a general perspective in the European Standard named EN 1992-1-1 (EC2), and when the structural engineer deals with the dimensioning or verification of the connection, he must tackle several unknowns. The present work aims to fill in the missing information by presenting detailed calculation models based on the strut-and-tie method for four widely used pocket foundations: a pedestal pocket foundation with smooth, rough or keyed internal walls and a pad foundation with a pocket possessing keyed internal walls. In establishing the strut-and-tie models and writing the equation for the internal forces, we consider several standards (EC2, NBR 9062 and DIN 1045-1), good practices (from Austria, England, Germany and Romania) and numerous experimental and numerical investigations. Additionally, detailed design prescriptions applicable to seismic areas are given. This manuscript covers a wide range of design and technology aspects necessary for designing and building columns connected with pocket foundations, information for which is shown only in fragmented form or partially in other publications. Afterward, as a case study, a pocket foundation is designed in all four variations, with the structural design particularities, similitudes and differences being pointed out. Finally, to conclude, we mention the advantages and disadvantages of pocket foundations with respect to the type of internal wall surface used. Quantifiable data based on the case study undertaken are available. Full article