Search Results (3,119)

Portugal exhibits a large deficit in cereals with an import/export ratio of about 18%. Alentejo is a southern vast plain region, which is the largest cereal producer in the country, with about 80% of the total cereal area. The region also shows a huge local energy deficit with a ratio of about 17% between spent and produced energy. In this context, this work used GIS modeling based on available digital geographical information on soil and topographic conditions in Alentejo for estimating optimal production areas of four main classes of cereal and legume classes, which were wheat, barley, oat/lupin, and triticale/broad bean. The estimated areas were validated by 199 sample points in the field and allowed to quantify a potential of bioenergy production from straw biomasses based on yields of biomass net calorific values of 18 MJkg⁻¹ and yields of 6, 9, 6, and 9 tons/ha for the four classes in the order indicated. The estimated areas allocated to the cereal and legume classes covered approximately four municipalities in the region. The total modeled area in Alentejo for the four cultivation classes was 44,980 ha. The results showed that even if 50% of the estimated total straw biomass produced was used for animal feed, the estimated bioenergy production of the remaining half biomass would be of about 2940 TJy⁻¹, or about 12.5% of the actual regional energy production, which is an energy amount able to supply 35 organic Rankine cycle (ORC) 2.5 MW cogeneration units and 347 boilers with 125 kW thermal power, delivering renewable electricity to the grid, and heating facilities as diverse as buildings, nursing homes, or horticultural greenhouses. More than 160 kton of CO₂ fossil emissions would also be avoided, delivering a contribution to mitigating effects of climate change. By contributing to the reduction of the large cereal dependence and the carbon emissions of the country, the proposed strategy would contribute to increasing the decentralized bioenergy production for applications in buildings and local facilities, significantly boosting the socio-economic dynamics of rural areas involved. Full article

Current trends in the development of technology are linked inextricably to the increasing level of automation in technological processes and production systems. In this regard, the development of systems for supplying working fluids with adjustable pumps that have high performance characteristics, an increased service life and low operating costs is an important scientific and technical task. A primary challenge in the development of such systems lies in achieving low fluid flow rates while maintaining stable operating characteristics. This challenge stems from the fact that currently available controlled hydraulic pumps exhibit either a high cost or suboptimal life and efficiency parameters. This work focuses on the development of a plunger hydraulic pump with a small working volume. A mathematical model has been developed to investigate the characteristics, optimize the design of this pump and further expand the size range of such pumps. The solution was implemented on a computer using the dynamic modelling environment MATLAB/Simulink. In order to verify the mathematical model’s adequacy, a plunger pump prototype was built and integrated with a test bench featuring a measurement system. The test results showed higher pump efficiency and a significant reduction in hydraulic losses. An analysis of the obtained data shows that the pump is characterized by increased efficiency due to optimal flow distribution and reduced internal leakage, which makes it promising for use in hydraulic systems requiring improved operating characteristics. The developed pump has more rational characteristics compared to existing alternatives for use in water supply systems for induction superheaters. The experimental external characteristics of the developed pump are 10% higher than the external characteristics of the ULKA EX5 pump selected as an analogue, and the pressure characteristics are 65% higher. It offers production costs that are several times lower compared to existing cam-type plunger or diaphragm pumps with oil sumps and precision valve mechanisms. Additionally, it has significantly better operating characteristics and a longer service life compared to vibrating plunger pumps. Full article

The development of a city needs the accumulation of culture, and historical buildings are the most direct witness of the rise and fall of a city. Like the human body, historical buildings have a certain life cycle, but the acceleration of urbanization and unreasonable use cause an irreversible reduction in the remaining life of historical buildings. There is a notable lack of quantitative analysis regarding the residual life of historical buildings. Therefore, identifying the factors that influence their residual life is crucial for both preserving these buildings and sustaining urban culture. In order to obtain a more accurate correlation degree of influencing factors, a systematic-analysis model of influencing factors on the residual life of historical buildings based on the entropy weight method (EWM) and the grey relation analysis method (GRA) was established, so as to excavate the mechanism of the influencing factors on the residual life of historical buildings, accurately identify the main influencing factors on the residual life of historical buildings, and propose preventive measures. The results show that the structural system has the greatest influence on the residual life of historical buildings, followed by the enclosure system, and the equipment system. The research findings offer valuable insights for extending the residual life of historical buildings in the future. Full article

To comprehensively evaluate the current and future aging states of lithium-ion batteries, namely their State of Health (SOH) and Remaining Useful Life (RUL), this paper proposes a joint prediction method based on Gaussian Process Regression (GPR) and Long Short-Term Memory (LSTM) networks. First, health features (HFs) are extracted from partial charging data. Subsequently, these features are fed into the GPR model for SOH estimation, generating SOH predictions. Finally, the estimated SOH values from the initial cycle to the prediction start point (SP) are input into the LSTM network in order to predict the future SOH trajectory, identify the End of Life (EOL), and infer the RUL. Validation on the Oxford Battery Degradation Dataset demonstrates that this method achieves high accuracy in both SOH estimation and RUL prediction. Furthermore, the proposed approach can directly utilize one or more health features without requiring dimensionality reduction or feature fusion. It also enables RUL prediction at the early stages of a battery’s lifecycle, providing an efficient and reliable solution for battery health management. However, this study is based on data from small-capacity batteries and does not yet encompass applications in large-capacity or high-temperature scenarios. Future work will focus on expanding the data scope and validating the model’s performance in real-world systems, driving its application in practical engineering scenarios. Full article

In order to explore the water and fertilizer requirements of eggplants in the western oasis of the river, the experiment was conducted in Minle County of Gansu Province in 2022 and 2023 under three water stress gradients and three nitrogen application levels: (1) moderate water stress (W₁, 50–60% in field water capacity [FC]), mild water stress (W₂, 60–70% in FC), and full irrigation (W₃, 70–80% in FC); (2) low nitrogen (N₁, 215 kg·ha⁻¹), medium nitrogen (N₂, 270 kg·ha⁻¹), and high nitrogen (N₃, 325 kg·ha⁻¹). Moderate and mild water stress were applied during eggplant flowering and fruiting while full irrigation was provided during the other growth stages; a control class (CK) was established with full irrigation throughout the whole plant growth without nitrogen application. This study investigated the effects of water-saving and nitrogen reduction on the yield, quality, and water-nitrogen use efficiency of eggplants in a cold and arid environment in the Hexi Oasis irrigation area of China. Using the EWM-TOPSIS model, we evaluated different water-nitrogen treatments and determined the optimal irrigation-nitrogen application model for eggplants in this region. The results showed that the W₂N₂ treatment had the highest yield, which was not significantly (p > 0.05) different from the W₃N₂ treatment while significantly (p < 0.05) 35.06% higher than CK in 2022 and 36.91% higher in 2023. In the W₂N₂ treatment, the transverse diameter of eggplants, as well as the contents of soluble protein, soluble sugar, soluble solids, and vitamin C, were all the highest. The W₂N₂ treatment had the maximum water use efficiency and irrigation water use efficiency, which were significantly higher than other water and nitrogen application treatments and CK by 14.79–42.51% in 2022 and 8.79–44.88% in 2023, and 15.86–45.55% in 2022 and 4.68–40.22% in 2023, respectively. By employing the EWM-TOPSIS model for comprehensive evaluation, the results indicated that mild water deficit (60–70% in FC) and moderate nitrogen application (270 kg·ha⁻¹) at flowering and fruiting of eggplants was the optimal water and nitrogen application mode under mulched drip irrigation in the Hexi region of northwest China. The results will provide some theoretical basis for water-saving, productive, high-quality, and high-efficiency cultivation of eggplant in cold and arid environments. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social skills and the presence of repetitive and restricted behaviors and interests. The social behavior of the zebrafish (Danio rerio) makes this organism a valuable tool for modeling ASD in order to explore the social impairment typical of this disorder. In addition to transgenic models, exposure of zebrafish embryos to valproic acid (VPA) has been found to produce ASD-like symptoms. This review first sets out to examine the existing literature on adult social behavior in the zebrafish VPA-induced model of autism, and the authors also aim to identify the ideal VPA dosage able to induce a persistent and long-lasting ASD-like phenotype while minimizing the suffering and distress of research animals in compliance with the principles of replacement, refinement, and reduction (3Rs). Full article

Pneumonia, a leading cause of mortality in children under five, is usually diagnosed through chest X-ray (CXR) images due to its efficiency and cost-effectiveness. However, the shortage of radiologists in the Least Developed Countries (LDCs) emphasizes the need for automated pneumonia diagnostic systems. This article presents a Deep Learning model, Zero-Order Optimized Convolutional Neural Network (ZooCNN), a Zero-Order Optimization (Zoo)-based CNN model for classifying CXR images into three classes, Normal Lungs (NL), Bacterial Pneumonia (BP), and Viral Pneumonia (VP); this model utilizes the Adaptive Synthetic Sampling (ADASYN) approach to ensure class balance in the Kaggle CXR Images (Pneumonia) dataset. Conventional CNN models, though promising, face challenges such as overfitting and have high computational costs. The use of ZooPlatform (ZooPT), a hyperparameter finetuning strategy, on a baseline CNN model finetunes the hyperparameters and provides a modified architecture, ZooCNN, with a 72% reduction in weights. The model was trained, tested, and validated on the Kaggle CXR Images (Pneumonia) dataset. The ZooCNN achieved an accuracy of 97.27%, a sensitivity of 97.00%, a specificity of 98.60%, and an F1 score of 97.03%. The results were compared with contemporary models to highlight the efficacy of the ZooCNN in pneumonia classification (PC), offering a potential tool to aid physicians in clinical settings. Full article

Inerter dampers are effectively employed to mitigate and dampen structural vibrations in slender or high-rise buildings. The simple viscous inerter damper, with a viscous dashpot placed in series with an inerter, is designed to create resonant vibration damping, although the damper itself is without an internal resonance. The apparent resonant behavior is instead obtained by increasing the damper inertance until the two lowest modes of the considered building model interact, whereafter the viscous coefficient is adjusted until the desired response mitigation is achieved. The present modal interaction tuning requires that the reduced-order single-mode dynamic model of the building includes both inertia and flexibility from the (other) modes otherwise discarded by the model reduction. While the inertia correction adjusts the modal mass of the inerter damper, the corresponding flexibility introduces the apparent damper stiffness that creates the desired damper resonance. Thus, the accurate representation of other modes is essential for the design and resonant tuning of the simple viscous inerter damper. The resonant damper performance by the non-resonant viscous inerter damper is illustrated by a numerical example with a 20-story building model, for which the desired resonant modal interaction requires an inertance of almost ten times the entire translational building mass. Full article

For allowable defect analyses, the fracture toughness of materials needs to be accurately predicted. In this regard, a lower fluctuation of fracture toughness can lead to reduction in safety and economic risks. Crack tip opening displacement (CTOD), which is the representative parameter for fracture toughness, can be measured by various methods, such as the δ5, the J-conversion method, the single clip gauge method, and the double clip gauge method. When calculating CTOD from test results, the principle of similar triangles, which adopts the plastic hinge model, is influenced by the rotation factor, rp. Therefore, in order to reduce the fluctuation of CTOD, the exact value of rp must be defined. This study investigates various methods to predict fracture toughness in metallic materials, and assess the pros and cons of each method. Moreover, the equation of rp is modified by using a double clip gauge in compact tension (CT) to reduce the fluctuation of CTOD. The rp value is derived from 0.55 to 0.68, using the double clip gauge method. Finite element analysis is used to derive the rp values, which range from 0.50 to 0.66, in order to verify the validity of the derived rp values. This ensures the validity of the rp value derived from the experiment. In addition, the fluctuation of CTOD, based on the modified equation of rp, is lower than that using the single clip gauge method, according to BS 7448. Full article

The rheological properties of concrete paste significantly influence its tensile creep behavior. In this study, the tensile creep behavior of high-volume fly ash concrete (HVFAC) employing the same cementitious pastes was experimentally investigated, and the rheological properties of the paste containing a high volume of fly ash using the nanoindentation (NI) technique was investigated in order to explore the influence of the paste’s rheological properties (such as micro-mechanical properties and microscopic creep) on the early-age tensile creep of HVFAC. The results demonstrated that the micro-strain of paste containing a high volume of fly ash (HVFA) showed a larger value than that without fly ash. As the test age extends, a decreasing trend in microscopic creep was observed which could be attributed to the growth of the content of HD C–S–H (high density C–S–H) gel. Moreover, within the same age period, the experimental data revealed that the incorporation of fly ash resulted in the reduction of the values of the creep modulus C and characteristic time τ. The effects of fly ash dosages and loading age on the creep properties of concrete was consistent with the micro-creep properties of the cementitious paste. The tensile specific creep values derived from the ZC (“ZC” are initials for the word ‘‘self-developed” in Chinese) model based on nanoindentation data closely match those obtained from experiments. Full article

A major challenge in accidental or unregulated releases is the ability to identify the pollutant source, especially if the location is in a large industrial area. Usually in such cases, only a few sensors provide non-zero signal. A crucial issue is therefore the ability to use a small number of sensors in order to identify the source location and rate of emission. The general problem of characterizing source parameters based on real-time sensors is known to be a difficult task. As with many inverse problems, one of the main obstacles for an accurate estimation is the non-uniqueness of the solution, induced by the lack of sufficient information. In this study, an efficient method is proposed that aims to provide a quantitative estimation of the source of hazardous gases or breathable aerosols. The proposed solution is composed of two parts. First, the physics of the atmospheric dispersion is utilized by a well-established Lagrangian stochastic model propagated backward in time. Then, a new algorithm is formulated for the prediction of the spacial expected uncertainty reduction gained by the optimal placement of an additional sensor. These two parts together are used to construct an adaptive decision support system for the dynamical deployment of detectors, allowing for an efficient characterization of the emitting source. This method has been tested for several scenarios and is shown to significantly reduce the uncertainty that stems from the insufficient information. Full article

In this study, numerical modeling and experimental tests of the sheet metal cutting process were carried out in order to determine the shape of the cutting knives for a roller shear, ensuring the minimization of burr on the cut edge. A rolling mill was used for the tests, enabling the replication of the cutting process in a roller shear (demonstrating the possibility of using cutting rollers). The cutting edges of the sheets were examined using light microscopy and then compared with the results of numerical simulations to determine the cutting quality. The tests were performed for multiphase Complex Phase (CP) grade steel. The initial thicknesses of sheets were equal to 1 and 2 mm. Based on the results of theoretical research, four shapes of cutting rollers were designed, of which two shapes were selected for experimental tests. The analysis of the test results shows that the lowest burr values were obtained for straight and beveled rollers. Analyzing the size of burr obtained in experimental tests, it can be concluded that for each of the two variants of the roller shape, a reduction in burr was achieved. Greater reductions in burr were achieved for shaped (cut) rolls. Full article

Navelina oranges (Citrus sinensis) are rich in phytonutrients and bioactive compounds, especially flavonoids like hesperidin. This study investigates the anti-inflammatory and anti-fibrotic properties of hesperidin (HE) and a polyphenol mixture from Navelina oranges (OE) in human hepatocytes (Hepa-RG) and hepatic stellate cells (LX-2), in order to elucidate the underlying molecular mechanisms. In Hepa-RG cells, HE treatment increased expression of cannabinoid receptor 2 (CB2R), which was associated with down-regulation of p38 mitogen-activated protein kinases (p38 MAPK) but had minimal impact on cyclooxygenase-2 (COX-2) and transforming growth factor-β (TGF-β) levels. Conversely, OE treatment not only enhanced CB2R levels and reduced p38 MAPK, but also promoted a significant reduction in both COX-2 and TGF-β levels, suggesting that OE might be more effective in mitigating inflammatory and fibrotic processes than HE. In LX-2 cells, HE treatment caused a notable decrease in both COX-2 and TGF-β levels, reflecting its efficacy in targeting fibrosis-associated inflammation. OE treatment, on the other hand, reduced Nuclear Factor-Kappa B p65 (NF-κB) expression, a critical transcription factor involved in inflammatory responses, though it did not significantly affect COX-2. LX-2 cells induced to fibrosis with TGF-β and treated with HE and OE showed a reduction in the expression levels of several fibrosis markers. In addition, HE and OE showed antioxidant effects by increasing protein levels of Cu, Zn superoxide dismutase (SOD1), Mn superoxide dismutase (SOD2) and catalase (CAT) and influencing the state of lipid peroxidation. Further research is needed to explore the effects of the treatments in activated hepatic stellate cells and in vivo liver disease models. Full article

In this work, the NSGA-II multi objective genetic algorithm, numerical methods, and parametric design techniques found in the Autodesk Inventor professional 2023 CAD software were combined to perform the geometrical optimization of the Pelton bucket geometry. The validation of the proposed method was carried out with numerical simulations using the OpenFOAM CFD program and taking into account the case study turbine’s operating conditions, as well as the k-SST turbulence model. The CFD simulation results and operational data from the case study turbine from the “Illuchi N°2” hydrocenter have been compared in order to validate the proposed methodology. The implementation of the NSGA-II in the design process resulted in optimized bucket geometrical parameters: bucket length, width, inlet angle, and outlet angle. These parameters not only resulted in a 2.56% increase in hydraulic efficiency, but also led to a 0.1 [kPa] reduction in the maximum pressure at the bottom of the bucket. Further research will involve testing these parameters using 3D printing methods to validate their effectiveness. Full article

The increasing demand for dynamic analysis of large-scale structural systems has highlighted the need for efficient model reduction methods. Reduced order modeling allows large finite element models to be represented with significantly fewer degrees of freedom while retaining essential dynamic characteristics. This paper investigates the Enhanced Craig–Bampton (ECB) method and further explores its application in dynamic analysis. The effectiveness of the ECB method is evaluated by comparing it with the conventional Craig–Bampton (CB) method and the full finite element model using benchmark examples. The numerical results demonstrate that the ECB method provides superior accuracy and computational efficiency, making it a valuable tool for dynamic analysis in complex engineering problems. Full article