Search Results (28,773)

This research aims to study the spray flow of a droplet on an aluminum surface. Fluid spraying is a significant topic in various strategic industries worldwide. In this study, the commercial software FLUENT 22.3.0 is used to simulate the spray of a droplet with turbulent flow on a surface. We use Gambit for mesh generation to ensure accurate and efficient discretization of the computational domain. Initially, we validate our finite volume method (FVM) by comparing the simulation results with existing experimental data to ensure accuracy. After verifying the numerical methods and boundary conditions, we extend the analysis to explore new scenarios involving different environmental pressures, nozzle-to-surface distances, and heated surface temperatures. The effects of pressure variation on the efficiency of droplet heat transfer are examined within sub-atmospheric and super-atmospheric pressure ranges at different Weber numbers, all below the critical Weber number of the droplet. Additionally, by modifying the model geometry and boundary conditions, the influence of the spray-to-surface distance was examined. The findings show that both pressure changes and the spacing between the spray origin and the surface have a substantial effect on the droplet’s heat transfer performance. Full article

Intercropping, the cultivation of two or more crops in the same field, is known to have numerous environmental and economic benefits. The success of such systems depends on geographical location, climatic conditions, and the choice of crop varieties, especially in organic systems. This study aimed to assess the effect of the sowing method, wheat variety, legume species on wheat grain yield and quality, and macro-elements of soil and plants. A three-year field experiment in intercropping spring wheat and legume species was performed at an organic-certified field of Czech Agrifood Research Center, Prague. Three spring wheat varieties (Alicia, Hystrix, and Toccata), two legume species (pea and faba bean), and two sowing methods (mixed and row-by-row) were used. Although the intercropping of wheat variety and legume species did not improve wheat yield, wheat grain quality and soil and plant nutrition content were enhanced in wheat and legume mixtures compared to monoculture wheat. Notably, the mixed cropping method resulted in significantly higher yields than the row-by-row method. Furthermore, the baking quality of wheat grains from intercropping systems was superior to that of monoculture wheat. The results highlight the potential of tailored intercropping systems to optimize agricultural efficiency and sustainability, especially in the face of changes in climate change. Full article

The increasing global demand for seafood underscores the necessity for sustainable aquaculture practices. However, several challenges, including rising operational costs, variable environmental conditions, and the threat of disease outbreaks, impede progress in this field. This review explores the transformative role of the Artificial Intelligence of Things (AIoT) in mitigating these challenges. We analyse current research on AIoT applications in aquaculture, with a strong emphasis on the use of IoT sensors for real-time data collection and AI algorithms for effective data analysis. Our focus areas include monitoring water quality, implementing smart feeding strategies, detecting diseases, analysing fish behaviour, and employing automated counting techniques. Nevertheless, several research gaps remain, particularly regarding the integration of AI in broodstock management, the development of multimodal AI systems, and challenges regarding model generalization. Future advancements in AIoT should prioritise real-time adaptability, cost-effectiveness, and sustainability while emphasizing the importance of multimodal systems, advanced biosensing capabilities, and digital twin technologies. In conclusion, while AIoT presents substantial opportunities for enhancing aquaculture practices, successful implementation will depend on overcoming challenges related to scalability, cost, and technical expertise, improving models’ adaptability, and ensuring environmental sustainability. Full article

This study investigates the critical role of indoor environmental quality (IEQ) adaptations in influencing human physiological responses within commercial building settings. By integrating environmental engineering and human physiology, this research offers empirical insights into the relationship between IEQ modifications and occupant well-being, particularly in the context of energy performance and efficiency. This study examines correlations between human physiological responses and key IEQ components, including indoor air quality (IAQ), thermal comfort, lighting, and acoustics, using data collected from two office areas with 14 participants. Sensors tracked environmental parameters, while wearable devices monitored physiological responses. Cross-correlation analysis revealed significant relationships between physiological indicators and environmental factors, with indoor temperature, PM_2.5, and relative humidity showing the strongest impacts on electrodermal activity, skin temperature, and stress levels, respectively (p < 0.05). Furthermore, supervised machine learning techniques were employed to develop predictive models that evaluate IAQ and thermal comfort at both personal and general levels. Individual models achieved 84.76% accuracy for IAQ evaluation and 70.5% for thermal comfort prediction, outperforming the general model (69.7% and 64.3%, respectively). Males showed greater overall sensitivity to IEQ indicators, while females demonstrated higher sensitivity specifically to air quality and thermal comfort conditions. The findings underscore the potential of physiological signals to predict environmental satisfaction, providing a foundation for designing energy-efficient buildings that prioritize occupant health and comfort. This research bridges a critical gap in the literature by offering data-driven approaches to align sustainable building practices with human-centric needs. Future studies should expand participant diversity and explore broader demographics to enhance the robustness and applicability of predictive models. Full article

The unique challenges posed by the high altitude and extreme-irradiance variability in the Peruvian Altiplano necessitate innovative and cost-effective monitoring solutions for photovoltaic (PV) systems. This study presents a low-cost wireless monitoring system for PV systems, designed for performance analysis and with potential application in DC nanogrids. The system, based on an Arduino Nano and Raspberry Pi architecture, captures real-time data on key electrical parameters such as voltage, current, and power, as well as environmental conditions like temperature and irradiance, which are critical factors influencing PV system performance. Deployed on a 3 kW grid-connected PV system in the Peruvian Altiplano, the system reveals significant irradiance variability, with fluctuations exceeding 20% within a single day and extreme events surpassing 1500 W/m². This variability resulted in an average daily energy generation fluctuation of 15%, underscoring the importance of continuous monitoring for optimizing PV system operation. This variability impacts energy generation and underscores the importance of continuous monitoring for optimizing PV system operation. The study analyzes the system’s performance under different irradiance conditions and discusses its adaptability for use in DC nanogrids, which offer enhanced efficiency and accessibility in remote areas like the Altiplano. This research contributes a practical and versatile tool for advancing sustainable energy solutions, with implications for improving the efficiency and reliability of both grid-connected PV systems and the emerging field of DC nanogrids in remote areas. Full article

Pastoral systems in New Zealand are under societal pressure due to their increasing negative environmental impact in terms of greenhouse gas emissions. This study was conducted to investigate the effects of supplementing a mixture containing hydrolysable and condensed tannins on the in vitro fermentation characteristics and gas production of three different forages, Lolium perenne, Medicago sativa, and Plantago lanceolata. Three fermentation runs of 48 h were conducted using the ANKOM gas production technique, with each pertaining to a particular forage with or without (control) tannin. Tannins were added to the fermentable substrate (i.e., forage) at a level of 0.3%. For each run, rumen fluid was collected from two fistulated Holstein Friesian × Jersey cows. The ANKOM RF gas production modules were used to monitor gas pressure and temperature every 5 min. At the end of each run, the pH of the fluid was measured, gas vials were taken for methane (CH₄) measurements and liquor samples were taken to measure volatile fatty acids (VFA) and NH₃ concentrations. The addition of tannins reduced the fractional rate of gas production for alfalfa (p ≤ 0.04) but increased it for ryegrass and plantain. There was a tendency for reduced gas production for ryegrass when tannins were added (p = 0.10). There was also a tendency for CH₄ production to reduce (p < 0.10) and N₂O to increase (p = 0.10) when tannins were added. Iso-butyrate tended to be lower for ryegrass control than to ryegrass with tannins (p = 0.08). Valerate concentration was lower for plantain control than to plantain with tannins. No effects were detected for gas composition (p > 0.05) or VFA concentrations (p > 0.05) when fermenting alfalfa. Under the condition of this study, these results may suggest that low-level tannin addition to the diet may affect rumen-fermentation pattern with a potential reduction of CH₄ production in Lolium perenne-based diets. Further research is required on the effect of low levels of tannin supplementation under ex vitro and in vivo conditions as tannin supplementation effects might be substrate-dependent. Full article

One of the most important issues in the coming years will be the decarbonisation of the European Union member states’ energy systems. The majority of the abstract requires modification. I propose that the first sentence of the abstract in the manuscript should better emphasize the formulation of the problem. The remaining part and any corrections were made by the author. Scenarios of the importance of CCS in the process of transformation of energy systems in Poland. One of the most important issues in the coming years will be the transformation of the energy systems of the European Union’s member states, which will require the development of appropriate technological solutions. The research presented here analyses the importance of CCS in energy transformation. This article proposes adapting the energy transformation method to the structure of the energy mix and conditions prevailing in a specific country. Poland was adopted as an example for analysis due to its exceptionally complicated situation, taking into account the structure of energy production. For this purpose, an expert opinion survey was conducted. Both measurable variables, such as the volume of CO₂ emissions and EU ETS prices, and a qualitative variable, i.e., the impact of the political environment on the development of CCS, were introduced to the constructed model. The model allowed us to construct three scenarios describing alternative visions for the future development of CCS: optimistic, pessimistic, and neutral, taking into account different conditions in which CCS can develop. The use of fuzzy sets allowed us to eliminate the most serious drawback of planning scenarios based on expert knowledge, which is the subjectivity of their judgments. This research showed that stable conditions of the political environment and predictable legal regulations will be crucial for the application of CCS in the Polish energy sector. The prepared scenarios will enable a quick response and accurate decisions under various conditions of the turbulent environment. This will facilitate the preparation of energy strategies. The scenarios indicate what combinations of variables, under given environmental conditions, of CCS will be of great importance in the energy transformation, and when it may give way to other technologies. In addition, the scenarios, and especially their visualisation, are extremely valuable for stakeholders, because they will allow them to observe the potential development of the situation under known conditions of the political environment, prices, and CO₂ emissions. They enable understanding the dependence of the importance of CCS in the changing environment. They also enable the detection of critical points for the development of CCS, which, as a result of recent geopolitical events, may be of key importance in the near future for ensuring the energy and military security of Poland and the EU. Full article

A prototype of an industrial installation for the deposition of self-restoring nitride coatings on the surface of reed switch contacts using electro-spark erosion alloying was developed, manufactured, and tested under the laboratory conditions at LLC Nitron. It was shown that the coatings are formed inside a bulb of reed switches at the final stage of their production following the impact from the spark breakdown between the contacts, stimulated via alternating magnetic and electric fields. The nitrogen concentration in the surface layers of the nitride coatings, estimated by means of X-ray microanalysis, was ca. 19 at. % and their thickness, measured by time-of-flight secondary ion mass spectrometry via sputter depth profiling, ranged between 250 and 350 nm. The novelty of the presented work consists of the development of an innovative piece of equipment, the operating principle and design of which are protected by intellectual property rights (four Russian patents). The technological approach implemented in this installation differs from the industrial galvanic technology due to its high level of environmental safety and economic efficiency, since it does not require the use of gold, ruthenium, or other high-priced metals. Full article

Spider mites are globally distributed pests that cause significant damage to a wide range of crops. The use of predators for the control of pest mites is an effective and environmentally sustainable strategy. Stethorus punctillum Weise (Coleoptera: Coccinellidae), a well-known predator of spider mites, has been widely recognized as the primary natural enemy of pest mites in China. However, its pest control efficacy, particularly under field conditions, is not well known. In this study, we evaluated the biocontrol impact of S. punctillum on a key spider mite pest, Tetranychus urticae Koch (Acarina: Tetranychidae), through a combination of laboratory and field experiments. Laboratory assays showed that the predation rates in relation to the prey numbers were consistent with the Holling-II functional response model. The actually maximum predatory numbers of third-instars of S. punctillum, 3-day-old female adults, and male adults on the pest were 116.67, 181.67, and 166.67 mites per day, respectively, corresponding to the theoretically maximum values of 391.26, 498.07, and 413.95 mites per day individually. Field exclusion experiments demonstrated that both larval and adult stages of S. punctillum significantly suppressed spider mite populations’ growth across three different initial prey densities (80, 110, and 140 individuals for larvae; 100, 150, and 200 individuals for adults) on three economically important crops: maize, cotton, and apples. Within 96 h of their introduction, the pest population growth rate was reduced by 13.2–43.2% by larvae and 25.3–51.5% by adults of S. punctillum compared to predator-free control groups. These findings demonstrate that S. punctillum has a significant control efficacy on spider mite populations under both laboratory and field conditions, highlighting its potential as a promising biocontrol agent for integrated spider mite management in Northwest China. Full article

Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) is a valuable timber species native to western North America that was introduced to Europe in the 19th century. The objective of this study was to select the most valuable and stable Douglas fir provenances in Romania by combining growth and quality traits, using two indices recently used in forest tree species: the multi-trait genotype–ideotype distance index (MGIDI) and the multi-trait stability index (MTSI). The study was conducted across three common garden experiments in Romania, established in 1977, evaluating 61 provenances from the United States, Canada, Germany, France, and Romania. The analyzed traits were diameter at breast height (DBH), total height (TH), and pruned height (PH). Significant genotype–environment interactions were observed, with the Douglas fir showing superior growth performance in one of the testing sites in western Romania (Aleșd). The MGIDI and MTSI identified high-performing provenances from diverse geographic origins, including the Pacific Northwest, Europe, and Canada. Selection differentials ranged from 2.8% to 10.9% for individual traits, highlighting the potential for genetic improvement. The selected provenances represent valuable genetic resources of Douglas fir that are adapted to environmental conditions in the Carpathian region, contributing to the development of climate-adaptive breeding strategies and sustainable forest management. Full article

Aggressive behaviour in pigs poses significant challenges to animal welfare, production efficiency, and economic performance in the pork industry. This review explores the multifaceted causes of pig aggression, focusing on genetic, environmental, and physiological factors. Aggression in pigs is categorized into social, maternal, fear-induced, play, and redirected aggression, with early-life hierarchies and environmental stressors playing critical roles. Physiological markers, such as elevated cortisol and reduced serotonin levels, are closely linked to aggressive behaviour, while dietary interventions, including tryptophan supplementation, have shown promise in mitigating aggression. Environmental factors, such as overcrowding, noise, and heat stress, exacerbate aggressive tendencies, whereas enrichment strategies, like music and improved housing conditions, can reduce stress and aggression. Genome-wide analyses have pinpointed specific polymorphisms in neurotransmitter genes (DRD2, SLC6A4, MAOA) and stress-response loci (RYR1) as significant predictors of porcine aggression. Advances in genomic technologies, including genome-wide association studies (GWASs) and transcriptomic analyses, have further elucidated the genetic and epigenetic underpinnings of aggressive behaviour. Practical application in breeding programmes remains challenging due to aggression polygenic nature and industry hesitancy toward genomic approaches. Future research should focus on integrating genetic markers into breeding programmes, developing multitrait selection indices, and exploring epigenetic modifications to improve animal welfare and production efficiency. By addressing these challenges, the pork industry can enhance both the well-being of pigs and the sustainability of production systems. Full article

Plants face various abiotic stresses in their natural environments that trigger the production of reactive oxygen species (ROS), leading to oxidative stress and potential cellular damage. This comprehensive review examines the interplay between plant antioxidant defense systems and ROS under abiotic stress conditions. We discuss the major enzymatic antioxidants, including superoxide dismutase, catalase, reductases, and peroxidases, as well as non-enzymatic antioxidants, such as ascorbic acid, glutathione, polyphenols, and flavonoids, which play crucial roles in ROS detoxification. This review elaborates on different types of ROS, their production sites within plant cells, and their dual role as both damaging oxidants and key signaling molecules. We discuss how various abiotic stresses—including heat, cold, drought, flooding, salinity, and heavy metal toxicity—induce oxidative stress and trigger specific antioxidant responses in plants. Additionally, the mechanisms of ROS generation under these abiotic stress conditions and the corresponding activation of enzymatic and non-enzymatic scavenging systems are discussed in detail. This review also discusses recent advances in understanding ROS signaling networks and their integration with other stress-response pathways. This knowledge provides valuable insights into plant stress-tolerance mechanisms and suggests potential strategies for developing stress-resistant crops by enhancing antioxidant defense systems. Moreover, the strategic ROS modulation through priming, exogenous antioxidants, nanoparticles, or genetic tools can enhance plant resilience. Integrating these methods with agronomic practices (e.g., irrigation management) offers a sustainable path to climate-smart agriculture. Our review reveals that ROS accumulation can be detrimental; however, the coordinated action of various antioxidant systems helps plants maintain redox homeostasis and adapt to environmental stress. Full article

Efficient insulator-defect detection in transmission lines is crucial for ensuring the reliability and safety of power systems. This study introduces YOLOv8-IDX (You Only Look Once v8—Insulator Defect eXtensions), an enhanced DL (Deep Learning) based model designed specifically for detecting defects in transmission line insulators. The model builds upon the YOLOv8 framework, incorporating advanced modules, such as C3k2 in the backbone for enhanced feature extraction and C2fCIB in the neck for improved contextual understanding. These modifications aim to address the challenges of detecting small and complex defects under diverse environmental conditions. The results demonstrate that YOLOv8-IDX significantly outperforms the baseline YOLOv8 in terms of mean Average Precision (mAP) by 4.7% and 3.6% on the IDID and CPLID datasets, respectively, with F1 scores of 93.2 and 97.2 on the IDID and CPLID datasets, respectively. These findings underscore the model’s potential in automating power line inspections, reducing manual effort, and minimizing maintenance-related downtime. In conclusion, YOLOv8-IDX represents a step forward in leveraging DL and AI for smart grid applications, with implications for enhancing the reliability and efficiency of power transmission systems. Future work will focus on extending the model to multi-class defect detection and real-time deployment using UAV platforms. Full article

Rice combine harvester conveyor troughs and their bolted connections are susceptible to vibration-induced failure due to operational and environmental excitations. Addressing the challenge of predicting the state of the combine harvester’s conveyor trough bolted structure prior to vibration-induced failure, this study addresses this by investigating signal analysis, system design, and condition identification for these critical components. Firstly, multi-point vibration signals from the conveyor trough were acquired and analyzed in the time-frequency domain. The analysis pinpointed the X-direction at the trough-frame connection (Point 5) as the most responsive location, with RMS peaking at 6.650 during header start-up (vs. 0.849 idle). Significant responses were also noted at Point 3 (Y-dir, 4.628) and Point 6 (X-dir, 3.896) under certain conditions (where Z-direction responses were minimal), identifying critical points that form the basis for condition assessment. Secondly, a vibration acquisition system was developed using a high-performance AD7606 ADC and A39C wireless technology. It features 16-bit resolution (0.00076 mm/s theoretical sensitivity), 8-channel synchronous sampling up to 200 kSPS, and rapid (0.8 s) wireless data transmission. This system meets the demands for high-frequency, high-precision monitoring of the bolted structure. Finally, after comparing machine learning algorithms, Support Vector Machine was chosen for its superior performance. Using a one-vs.-one strategy and data from critical points, an operational condition identification model was developed. Validation with field data confirmed high accuracy (96.9–99.7%) for principal states and low misclassification rates (<5%). This allows for precise identification of the bolted structure’s working status. The research presented in this study offers effective methodologies and technical underpinning for the condition monitoring of critical structural components in rice combine harvesters. Full article

Energy transition is a challenge for remote northern communities mainly relying on diesel for electricity generation and space heating. Solar-assisted ground-coupled heat pump (SAGCHP) systems represent an alternative that was investigated in this study for the Kuujjuaq Forum, a multi-activity facility in Nunavik, Canada. The energy requirements of community buildings facing a subarctic climate are poorly known. Based on energy bills, technical documents, and site visits, this study provided an opportunity to better document the energy consumption of such building, especially considering the recent solar photovoltaic (PV) system installed on part of the roof. A comprehensive model was developed to analyze the building’s heating demand and simulate the performance of a ground-source heat pump (GSHP) coupled with PV panels. The air preheating load, accounting for 268,200 kWh and 47% of the total heating demand, was identified as an interesting and realistic load that could be met by SAGCHP. The GSHP system would require a total length of at least 8000 m, with boreholes at depths between 170 and 200 m to meet this demand. Additional PV panels covering the entire roof could supply 30% of the heat pump’s annual energy demand on average, with seasonal variations from 22% in winter to 53% in spring. Economic and environmental analysis suggest potential annual savings of CAD 164,960 and 176.7 tCO₂eq emissions reduction, including benefits from exporting solar energy surplus to the local grid. This study provides valuable insights on non-residential building energy consumption in subarctic conditions and demonstrates the technical viability of SAGCHP systems for large-scale applications in remote communities. Full article