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Spent mushroom compost is one of the main potentials for biogas production. In recent years, several studies employed adding nanoparticles and alkaline pretreatment for improving biogas production. The present study is one of the pioneer studies that employ hybrid alkaline pretreatment (0, 5, and 15 mg of NaOH) and zero-valent iron nanoparticles (0, 10, 20, 30, and 40 mg) for improving the co-digestion of spent mushroom compost and rice straw. According to the results, retention time (RT) and nanoparticle (NP) concentrations have the most significant impact on biomethane production (significant at 1% probability level), while the NaOH concentration has the lowest impact on biomethane production (significant at 5% probability level) in comparison with RT and NP concentration. Also, the maximum biomethane production is related to NP40Na15 (about 200% higher than the control). The minimum cumulative biomethane production is related to NP0Na15 (about 30% lower than the control). The lowest relative environmental midpoint impact is related to NP40Na15, which was on average about 60% lower than the control. Adding NPs at high concentrations of NaOH reduces the midpoint impacts. The results of the study could lead to new, ecologically friendly biomethane production methods that make better use of agricultural and organic wastes.

This research investigated the performance of a model traction combine harvester (TCH) for harvesting several varieties of peanuts. The effect of independent factors including tested varieties at three levels (local Moghan, Goli Astana, and Turkish), tractor forward speed (FS) at three levels (4, 5, and 6 km·h−1), and rotational speed (RS) of the thresher at three levels (500, 600, 700 rpm) on losses and wastes were studied and investigated. To analyse the obtained data, a factorial experimental design was used in the form of randomised complete blocks, and Duncan‘s multi-range test was used to compare the mean values. According to the findings, the effects of tractor FS and rotary speed of the thresher on the percentage of threshing losses were significant at the probability level of 1%. Also, the interaction effects of variety type and tractor FS, tractor FS, and rotary speed of the thresher on the percentage of threshing losses were significant at the 1% probability level. Also, the effects of variety type, tractor FS, rotary speed of the thresher, and all mutual effects on the percentage of threshing waste were significant at the 1% probability level. The results of comparing the average effects of the main factors showed that the FS of 6 km·h−1 had the highest average threshing loss (82.89%). Threshing losses were obtained in the Turkish variety with the lowest average value (2.51%) and in the local variety with the highest average value (3.53%).

Biogas production from sewage sludge can be valued in different scenarios of energy usage such as the electricity, heating, and transportation system. Improving the energy production value is the main reason for using different ways such as alkaline pretreatment and nanoparticles (NPs). This investigation uses life cycle assessment (LCA) for evaluating the biomethane production from co-digestion of sewage sludge and wheat straw in the presence of polypyrrole Fe3O4 nanoparticles (0, 20, 40, 60, and 80 mg) and NaOH alkaline pretreatment (0 and 5 mg) at mesophilic anaerobic digestion along with optimization for sustainable biomethane production. Results indicated that retention time (RT) and NaOH concentration had a significant effect on biomethane production. But, the effect of NP concentration on biomethane production was not significant. Also, the maximum biomethane production was obtained by NP40Na0 (about 50% higher than the control). On average, adding the NaOH and NPs improved the biomethane yield by about 25–40% vs in comparison with the control. The maximum biogas production yield was related to NP40Na0 with an enhancement of about 35% in comparison with the control. On average, adding nanoparticles and NaOH alkaline pretreatment improved the biogas production by about 10–20% in comparison with the control. Sustainable biomethane production can be obtained at an NP concentration of 50.24 mg and NaOH concentration of 24.04 mg, which increased the biomethane production by about 198%, and reduced human health, ecosystem quality, climate change, resources, and economic cost by about 87, 86, 92, 95, and 87%, respectively, in comparison with the control.

In the present study, an attempt was made to simulate the hybrid self-power generation process from a diesel engine and propose sustainable power-share management for this self-power hybrid electrical-diesel platform from the viewpoints of environmental and economic aspects (life cycle perspective). This concept means that when the engine works at part-load condition, we need to bring the engine operating conditions to optimal load, and along with doing the necessary work, in parallel, the rest of the power be used to generate electricity to be stored in the battery for more consumption in addition to reducing pollution and reducing fuel consumption by moving towards sustainable energy production. This case study examines the differences between using a diesel engine at idle and maximum load conditions when less engine power is required and if using a diesel engine in a diesel-electricity hybrid cycle. According to the obtained results, it can be concluded that to achieve the most negligible environmental impact, a lower share of generating power can be allocated to electricity generation in higher cycles than the share of generating electrical power in lower cycles. In other words, by increasing the engine speed, the amount of power consumption used to generate electricity relative to the power required from the diesel engine should be reduced so that the system suffers the most negligible environmental impact.

Currently, more than half of the road transport fleet uses diesel engines, which are often identified as the primary source of air pollution. This parameter is enough to optimize engine performance and emissions. The engine optimization can be done using several methods, the most notably by modifying the engine structure, changing the type of fuel using additives and biofuels, or achieving the optimal operating range of the engine. Modifying the engine structure and addition of different kinds of materials to optimize fuel is not recommended either due to necessity of vast time input, financial resources, or extensive research. However, the third way to achieve optimal engine performance conditions can be the most accessible option. According to the results, the best operational load for diesel engine is approx. 94–95% of the full load from the multi-objective optimization point of view, indicating that the optimum load can be achieved before the full load condition. At this point, the operator can achieve the brake power of 198.45 kW and brake thermal efficiency of 40.7% in the presence of brake specific fuel consumption of 0.226 kg·kWh−1. At this condition, CO2 emission is 124.85 g·kWh−1, NOx emission 7.34 g·kWh−1, CO emission 0.6 g·kWh−1, unburnt hydrocarbon emission approx. 0.009 g·kWh−1, and soot formation approx. 0.006 g·kWh−1. This point is equal to the exergy efficiency of approx. 35% and the exergy destruction of approx. 45%. In terms of endpoint results, this condition achieved the impact indices of 7.96E-007 in terms of human health, 0.105 PDF·m2·yr. in terms of ecosystem quality, 0.24 kg CO2 eq. in terms of climate change, and 12.96 MJ in terms of resources.

Artificial intelligence (AI) is widely used in social sciences and continues to evolve. Deep learning (DL) has emerged as a powerful AI tool transforming social sciences with valuable insights across many areas. Employing DL for modelling social sciences' big data has led to significant discoveries and transformations. This study aims to systematically review and evaluate DL methods in social sciences. Following PRISMA guideline, this study identifies fundamntal DL methods applied to social science applications. We evaluated DL models using reported metrics and calculated a normalized reliability score for uniform assessment. Employing relief feature selection, we identified influential parameters affecting DL techniques' reliability. Findings suggest evaluation criteria significantly impact DL model effectiveness, while database and application type influence moderately. Identified limitations include inadequate reporting of evaluation criteria and model structure details hindering comprehensive assessment and informed policy development. In conclusion, this review underscores DL methods' transformative role in social sciences, emphasising the importance of explainability and responsibility. [ABSTRACT FROM AUTHOR]

Biogas production from sewage sludge can be valued in different scenarios of energy usage such as the electricity, heating, and transportation system. Improving the energy production value is the main reason for using different ways such as alkaline pretreatment and nanoparticles (NPs). This investigation uses life cycle assessment (LCA) for evaluating the biomethane production from co-digestion of sewage sludge and wheat straw in the presence of polypyrrole Fe3O4 nanoparticles (0, 20, 40, 60, and 80 mg) and NaOH alkaline pretreatment (0 and 5 mg) at mesophilic anaerobic digestion along with optimization for sustainable biomethane production. Results indicated that retention time (RT) and NaOH concentration had a significant effect on biomethane production. But, the effect of NP concentration on biomethane production was not significant. Also, the maximum biomethane production was obtained by NP40Na0 (about 50% higher than the control). On average, adding the NaOH and NPs improved the biomethane yield by about 25–40% vs in comparison with the control. The maximum biogas production yield was related to NP40Na0 with an enhancement of about 35% in comparison with the control. On average, adding nanoparticles and NaOH alkaline pretreatment improved the biogas production by about 10–20% in comparison with the control. Sustainable biomethane production can be obtained at an NP concentration of 50.24 mg and NaOH concentration of 24.04 mg, which increased the biomethane production by about 198%, and reduced human health, ecosystem quality, climate change, resources, and economic cost by about 87, 86, 92, 95, and 87%, respectively, in comparison with the control. [ABSTRACT FROM AUTHOR]