Search Results (6,887)

This article presents a case study from a Social and Health Care School in Denmark, where a rooftop garden was designed to promote student health and support nature-based teaching across subject areas. A novel aspect of the project is the formal integration of the garden into teaching, implying that its long-term impact may extend beyond the students to the end-users they will later encounter in nursing homes and hospitals nationwide. This study applies the Evidence-Based Health Design in Landscape Architecture (EBHDL) process model, encompassing evidence collection, programming, and concept design, with the University of Copenhagen acting in a consultancy role. A co-design process with students and teachers was included as a novel source of case-specific evidence. Methodologically, this is a participatory practice-based case study focusing on the full design and construction processes, combining continuous documentation with reflective analysis of ‘process insights,’ generating lessons learned from the application of the EBHDL process model. This study identifies two categories of lessons learned. First, general insights emerged concerning governance, stakeholder roles, and the critical importance of site selection, procurement, and continuity of design responsibility. Second, specific insights were gained regarding the application of the EBHDL model, including its alignment with Danish and international standardised construction phases. These insights are particularly relevant for project managers in nature-based initiatives. The results also show how the EBHDL model aligns with Danish and international standardised construction phases, offering a bridge between health design methods and established building practice. The case focuses on the EBHDL process rather than verified outcomes and demonstrates how evidence-based and participatory approaches can help structure complex design processes, facilitate stakeholder engagement, and support decision-making in institutional projects. Full article

Tunnel boring machine (TBM) hydraulic cylinders operate under pronounced start–stop shocks and load uncertainties, making it difficult to simultaneously achieve smooth start-up and high-precision tracking. This paper proposes a two-phase switching adaptive sliding mode control (ASMC) strategy for TBM hydraulic actuation. Phase I targets a soft start by introducing smooth gating and a ramped start-up mechanism into the sliding surface and equivalent control, thereby suppressing pressure spikes and displacement overshoot induced by oil compressibility and load transients. Phase II targets precise tracking, combining adaptive laws with a forgetting factor design to maintain robustness while reducing chattering and steady-state error. We construct a state-space model that incorporates oil compressibility, internal/external leakage, and pump/valve dynamics, and provide a Lyapunov-based stability analysis proving bounded stability and error convergence under external disturbances. Comparative simulations under representative TBM conditions show that, relative to conventional PID Controller and single ASMC Controller, the proposed method markedly reduces start-up pressure/velocity peaks, overshoot, and settling time, while preserving tracking accuracy and robustness over wide load variations. The results indicate that the strategy can achieve the unity of smooth start and high-precision trajectory of TBM hydraulic cylinder without additional sensing configuration, offering a practical path for high-performance control of TBM hydraulic actuators in complex operating environments. Full article

Pile foundations are critical load-bearing components in bridge structures, particularly in soft, high-moisture soils susceptible to external disturbances. This study investigated the impact of large-scale soil excavation on the stability of adjacent pile foundations through comprehensive field monitoring of a newly constructed bridge during both the bridge construction and channel excavation phases. The close proximity of the excavation site to the pile caps facilitated a detailed assessment of soil–structure interaction. The results indicate that the pile axial force peaked at the pile head and decreased progressively with depth, consistent with the load transfer mechanism of friction piles. Notably, a distinct variation in axial force was observed at the bedrock interface, attributed to reduced relative displacement between the pile and the surrounding soil. Furthermore, channel water filling raised the local groundwater table, which increased the buoyancy and reduced negative skin friction, thereby decreasing the pile axial force. The study also highlighted the sensitivity of pile deformation in soft soil to unbalanced earth pressure. Asymmetric excavation and surface surcharge loading were identified as critical factors compromising pile stability and overall structural safety. These findings provide valuable insights for construction practices and offer effective strategies to mitigate adverse excavation effects, ensuring long-term structural stability. Full article

The rapid development of unmanned aerial vehicle (UAV) technology necessitates reliable recognition methods. Radio frequency (RF)-based recognition is promising, but conventional real-valued CNNs (RV-CNNs) typically discard phase information from RF spectrograms, leading to degraded performance under low-signal-to-noise ratio (SNR) conditions. To address this, this paper proposes a complex-valued CNN (CV-CNN) that operates on a constructed complex representation, where the real part is the logarithmic power spectral density (PSD) and the imaginary part is derived from Sobel edge detection. This enables genuine complex convolutions that fuse magnitude and structural cues, enhancing noise resilience. As complex-valued networks are known to be sensitive to architectural choices, we conduct comprehensive ablation experiments to investigate the impact of key hyperparameters on model performance, revealing critical stability constraints (e.g., performance collapse beyond 4–5 network depth). Evaluated on the 25-class DroneRFa dataset, the proposed model achieves 100.00% accuracy under noise-free conditions. Crucially, it demonstrates significantly superior robustness in low-SNR regimes: at −20 dB SNR, it attains 15.58% accuracy, over seven times higher than a dual-channel RV-CNN (2.20%) with identical inputs; at −15 dB, it reaches 45.86% versus 14.03%. These results demonstrate that the CV-CNN exhibits potentially superior robustness and interference resistance in comparison to its real-valued counterpart, maintaining high recognition accuracy even under low-SNR conditions. Full article

This study aimed to develop a credit risk index to classify coffee producers according to socioeconomic, agronomic, and financial performance variables, with the purpose of strengthening financial inclusion. We combined qualitative and quantitative methods to understand credit risk factors among smallholder coffee producers. The study followed a descriptive-analytical approach structured in consecutive methodological phases. The systematic review, conducted following the Kitchenham protocol, identified theoretical factors associated with credit risk, while fieldwork with 300 producers provided the socioeconomic and productive contexts of coffee-growing households. Producer income, cost of living, and farm management expenses were modeled using regression, statistical, and machine learning methods. Subsequently, these variables were integrated to construct a financial risk index, which was normalized using expert scoring. The index was validated using data from 100 additional producers, for whom annual repayment capacity and maximum loan amounts were estimated according to their risk level. The results indicated that incorporating municipal-level economic variables, such as estimated average prices, income, and expenses, enhanced predictive accuracy and improved the rational allocation of loan amounts. The study concludes that credit risk analysis based on variables related to human, productive, and economic capital constitutes an effective strategy for improving access to finance in rural areas. Full article

Wastewater treatment facilities of a diameter of approximately 15 m or more provide the opportunity to process large volumes of stormwater. The current report investigates the operation of a stormwater radial precipitator, without an impeller, working with particles of various sizes. A distinguishing feature is that the two-phase flow is solely gravity-driven, which leads to reduced energy requirements. This entails the necessity of a facility in which the linear and the local losses are minimized as much as possible. Linear losses can be reduced by decreasing the precipitator’s size. The initially proposed 15 m diameter proved to be ineffective since the sand only reached a certain zone and could not flow further to the outlet due to the insufficient energy. Therefore, it was necessary to reduce the size of the radial precipitator, which resulted in a shorter path for the sand particles and the water, which, in turn, reduced the linear resistance. As for the local losses, it turned out that many areas of the precipitator construction could be geometrically modified to significantly reduce the energy loss of the sand–water mixture. The boundary layer cannot be removed. However, it is possible the size and the number of vortex structures inside the settler to be reduced in order to create an optimal working environment. Full article

This study utilized capric acid (CA), lauric acid (LA), myristic acid (MA), palmitic acid (PA), and stearic acid (SA) as alternative feedstocks to conduct theoretical analyses on ten fatty acid-based ternary eutectic systems. By leveraging the Schrader equation, phase diagrams for each system were constructed, and their theoretical eutectic points were calculated. The CA-LA-MA (capric acid–lauric acid–myristic acid) ternary system was selected as a representative for experimental fabrication: differential scanning calorimetry (DSC) was employed to characterize its thermal properties, while Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric analysis (TGA) were used to assess its functional group composition and thermal stability, respectively. Theoretical calculations indicate that the ten ternary eutectic systems exhibit melting temperatures ranging from 17.11 °C to 37.61 °C, with phase change latent heats spanning 167.8 J·g⁻¹ to 189.6 J·g⁻¹. For the CA-LA-MA system, experimental DSC results confirm that its eutectic melting temperature is 16.0 °C (accompanied by a phase change latent heat of 177.0 J·g⁻¹, with minor deviations from theoretical predictions attributed to reagent impurities and operational errors). TGA characterization further reveals that the CA-LA-MA mixture has an initial weight loss temperature (corresponding to ~1% mass loss) of 115.6 °C and an extrapolated onset weight loss temperature of 164.8 °C, confirming reliable thermal stability below 100 °C—consistent with its low-temperature application design. These results validate the consistency between theoretical predictions and experimental data, and demonstrate that fatty acid-based ternary eutectic mixtures are promising candidates for low-temperature thermal energy storage applications. Full article

As the retrieval of unconventional oil and gas resources extends to the deep and ultra-deep domains, the issue of cement sheath failure in shale oil wellbores seriously endangers wellbore safety, making it imperative to uncover the relevant damage mechanism and develop effective assessment approaches. In response to the limitations of conventional finite element methods in representing mesoscopic damage, in this study, we determined the mesoscopic parameters of cement paste via laboratory calibrations; constructed a 3D casing–cement sheath–formation composite model using the discrete element method; addressed the restriction of the continuum assumption; and numerically simulated the microcrack initiation, propagation, and interface debonding behaviors of cement paste from a mesomechanical viewpoint. The model’s reliability was validated using a full-scale cement sheath sealing integrity assessment apparatus, while the influences of fracturing location, stage count, and internal casing pressure on cement sheath damage were analyzed systematically. Our findings indicate that the DEM model can precisely capture the dynamic evolution features of microcracks under cyclic loading, and the results agree well with the results of the cement sheath sealing integrity evaluation. During the first internal casing pressure loading phase, the microcracks generated account for 84% of the total microcracks formed during the entire loading process. The primary interface (casing–cement sheath interface) is fully debonded after the second internal pressure loading, demonstrating that the initial stage of cyclic internal casing pressure exerts a decisive impact on cement sheath integrity. The cement sheath in the horizontal well section is subjected to high internal casing pressure and high formation stress, resulting in more frequent microcrack coalescence and a rapid rise in the interface debonding rate, whereas the damage progression in the vertical well section is relatively slow. Full article

The design of aircraft components is a complex process that must simultaneously account for environmental impact, manufacturability, cost and structural performance to meet modern regulatory requirements and sustainability objectives. When these factors are integrated from the early design stages, the approach transcends traditional eco-design and becomes a genuinely sustainability-oriented design methodology. This study proposes a sustainability-driven design framework for aircraft components and demonstrates its application to a fuselage panel consisting of a curved skin, four frames, seven stringers, and twenty-four clips. The design variables investigated include the material selection, joining methods, and subcomponent thicknesses. The design space is constructed through a combinatorial generation process coupled with compatibility and feasibility constraints. Sustainability criteria are evaluated using a combination of parametric Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) regression models, parametric Finite Element Analysis (FEA), and Random Forest surrogate modeling trained on a stratified set of simulation results. Two methodological pathways are introduced: 1. Cluster-based optimization, involving customized clustering followed by multi-criteria decision-making (MCDM) within each cluster. 2. Global optimization, performed across the full decision matrix using Pareto front analysis and MCDM techniques. A stability analysis of five objective-weighting methods and four normalization techniques is conducted to identify the most robust methodological configuration. The results—based on a full cradle-to-grave assessment that includes the use phase over a 30-year A319 aircraft operational lifetime—show that the thermoplastic CFRP panel joined by welding emerges as the most sustainable design alternative. Full article

The fundamental goal of a construction project is to complete the construction phase within budget, but in practice, planned cost estimates are often exceeded. The causes of overruns can be due to insufficient preparation and planning of the project, changes during construction, activation of risky events, etc. Also, construction costs are often calculated based on experience rather than scientifically based approaches. Due to the challenges, this paper investigates the potential of several different machine learning methods (linear regression, decision tree forest, support vector machine and general regression neural network) for estimating construction costs. The methods were implemented on a database of recent high-rise construction projects in the Republic of Croatia. Results confirmed the potential of the selected assessment methods; in particular, the support vector machine stands out in terms of accuracy metrics. Established machine learning models contribute to a deeper understanding of real construction costs, their optimization, and more effective cost management during the construction phase. Full article

Mtx1 is a mosquitocidal protein that exhibits high toxicity toward Culex species. It is produced during the vegetative phase of Lysinibacillus sphaericus but at very low levels and is rapidly degraded. The low expression appears to result from a weak promoter and a potential regulatory stem-loop structure in the 5′ untranslated region. To investigate this regulation, promoter variants of mtx1 were constructed to disrupt stem-loop formation, and promoter activity was assessed using green fluorescent protein (GFP) as a reporter. Disruption of the inverted repeat resulted in approximately twofold higher fluorescence compared with the wild-type promoter in L. sphaericus 2297, indicating partial derepression of translation. To improve protein stability, Bacillus subtilis WB800N, a protease-deficient host, was employed for heterologous expression. Truncated Mtx1 (tMtx1) was secreted into the culture medium, and no obvious degradation products were detected by Western blot analysis under the conditions tested. Although the overall yield was low and not quantitatively determined, the secreted protein retained biological activity. Larvicidal assays showed elevated mortality in tMtx1-containing culture supernatants, with an estimated LC₅₀ at approximately a 1:83 dilution and detectable activity up to a 1:512 dilution relative to control cultures. These results demonstrate that the upstream inverted repeat contributes to partial repression of mtx1 expression in L. sphaericus and that protease-deficient B. subtilis can be used as a host for producing biologically active tMtx1, although further optimization will be required to improve yield. Full article

The para-positronium system $\left({}^{1}S_{0}Ps\right)$ is described by means of specially constructed coherent states (CSs) in the Klauder–Perelomov sense. It is analyzed from the physical point of view and from the geometry underlying the relevant symmetry group establishing the dynamics of the processes. In this new theoretical context, the possibility of a gamma-ray laser emission is investigated within a QFT context, showing explicitly that, in addition to the oscillator solution based only on a Bogoliubov approximation for the condensate, there is a second phase or “squeezed” stage by which physical features beyond the classical ones appear. Explicitly, while the generated photons are in the active medium (e.g., Ps-BEC), the evolution is described by a Heisenberg–Weyl coherent state with displacement operators dependent on the interaction time, which is related to the condensate shape. After the interaction time has elapsed, we explicitly demonstrate that the displacement operator of the ${}^{1}S_{0}Ps$ is transformed into a squeezed operator of the photonic fields modulated by the matrix element of the Positronium decay ${\mathcal{M}}_{{}^{1}S_{0}Ps}\to 2\gamma$. We also show that this squeezed operator (belonging to the Metaplectic group) generates a non-classical radiation state spanning only even (s = 1/4) levels in the number of photons. The implications in astrophysical systems of interest, considering gamma-ray coherent emission and the possibility of an ${}^{1}S_{0}Ps-BEC$ in the context of pulsars, blazars, and quasars, are briefly discussed. Full article

This study focuses on the key challenges in detecting and estimating motion parameters of ground maneuvering targets for airborne radar sensors. The complex unknown motion states of the ground maneuvering target, including velocity, acceleration, and jerk, result in range migrations (RMs) and Doppler frequency migrations (DFMs). These effects severely degrade the long-time coherent accumulation performance of the airborne radar, thereby limiting the reliable detection and precise parameter estimation of maneuvering targets. To address this issue, a new detection and motion parameter estimation method based on the range frequency reversal transform (RFRT) and searching Lv’s distribution (SLVD), i.e., RFRT-SLVD, is proposed. Specifically, the third-order RM (TRM) and quadratic DFM (QDFM) are considered. The proposed method operates as follows: First, RMs are eliminated simultaneously via the RFRT operation, which multiplies the echo by its reversed data in the range frequency and slow-time domains, leveraging the symmetric equal-interval sampling property of the range frequency. Subsequently, a phase compensation function (PCF) related to the jerk is constructed to compensate the QDFM. Finally, the LVD is performed to remove residual DFMs and achieve effective signal energy accumulation. Additionally, the case of a fast-moving target with Doppler ambiguity is analyzed, and a method for estimating three motion parameters is provided. A key advantage of the proposed technique is its ability to directly compensate the RMs without requiring prior knowledge of the maneuvering target, while also avoiding the blind speed sidelobe (BSSL) effect. In comparison with existing algorithms, RFRT-SLVD achieves a balanced trade-off between parameter estimation performance and computational efficiency. Numerical analyses and experiments are conducted to validate the method, assessing its detection capability for ground maneuvering targets, Doppler ambiguity resolution in parameter estimation, computational complexity, and method applicability in multi-target scenarios. Full article

This paper presents an energy-focused analysis of structural materials used in passenger cars, with a particular emphasis on the impact of construction materials on total energy consumption throughout the vehicle’s life cycle. Three production periods (2000, 2010, and 2020) were analysed for B- and C-segment vehicles using inventory data from Life Cycle Assessment databases, the scientific literature, and certified dismantling stations. The embodied energy of key material groups—steel, aluminium, plastics, and other materials—was calculated based on representative mass shares and material-specific energy intensity indicators. The computational model was supplemented with statistical analyses (Kolmogorov–Smirnov test, Levene’s test, ANOVA, and Tukey’s post hoc tests) to verify whether observed temporal trends were statistically significant. The results indicate that total material-related energy inputs increased from approximately 57 GJ to 64 GJ per vehicle, while the specific energy intensity per kilogram decreased from 47.6 MJ/kg to 42.6 MJ/kg. Aluminium exhibited a pronounced reduction in unit energy intensity due to the rising share of secondary materials, whereas plastics and other materials showed substantial increases. Steel remained the largest contributor in absolute terms because of its dominant mass share. This study highlights the growing importance of the production phase in the environmental balance of modern vehicles, particularly in the context of the rising share of lightweight materials and recycling-based components. The results emphasise the importance of energy-efficient material use and underscore the significance of material selection and recycling strategies in reducing energy demand within the automotive sector. Full article

This study examined cast AZ31 magnesium alloy and its variant containing micro-alloying elements of Y and Ca (AZXW alloy), evaluating their potential as anode materials in magnesium–air batteries. The AZXW alloy was fabricated via two manufacturing techniques: casting and extrusion. The synergistic influence of Y and Ca, in conjunction with the production procedure, on the microstructure, electrochemical characteristics, and anodic discharge behavior of the examined alloys was investigated. The addition of Y and Ca results in the formation of secondary phases that affect grain size, particle size, and distribution, as well as the electrochemical performance and discharge properties of the Mg–air battery constructed for this study, over 24 h or until fully discharged. This work demonstrates the potential to enhance discharge performance and electrochemical behavior by adjusting the aqueous electrolyte solution in the battery through the incorporation of Citric Acid (C.A) at varying concentrations. The incorporation of citric acid into the aqueous electrolyte improves battery stability and specific energy as long as citric acid is present in the solution. Magnesium hydroxide (Mg(OH)₂) begins to form on the anode surface as its concentration progressively decreases due to complexation with dissolved magnesium ions. This diminishes the effective anode area over time, ultimately resulting in the distinctive “knee-type” collapse characteristic of electrolytes containing citric acid. Full article